diff --git a/Prediction Models/wine_type/README.md b/Prediction Models/wine_type/README.md
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+++ b/Prediction Models/wine_type/README.md	
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+# Wine Quality Prediction
+
+This project implements various machine learning models to predict wine quality based on physicochemical properties. The models classify wines into binary categories (high quality vs. low quality) using features like acidity, pH, alcohol content, and more.
+
+## Project Overview
+
+The project uses a dataset containing various chemical properties of wines and their quality ratings. The quality ratings are binarized into two categories:
+
+- 0: Lower quality (rating ≤ 5)
+- 1: Higher quality (rating > 5)
+
+## Features
+
+The following features are used for prediction:
+
+- Fixed acidity
+- Volatile acidity
+- Citric acid
+- Residual sugar
+- Chlorides
+- Free sulfur dioxide
+- Total sulfur dioxide
+- Density
+- pH
+- Sulphates
+- Alcohol
+- Wine type (red/white)
+
+## Models Implemented
+
+The project implements and compares six different machine learning models:
+
+1. Logistic Regression
+2. Decision Tree Classifier
+3. Random Forest Classifier
+4. K-Nearest Neighbors (KNN) Classifier
+5. Support Vector Classifier (SVC)
+6. Gradient Boosting Classifier
+
+## Technical Implementation
+
+### Data Preprocessing
+
+- Handling missing values
+- Feature scaling using MinMaxScaler
+- Dimensionality reduction using PCA
+- One-hot encoding for categorical variables
+
+### Model Pipeline
+
+Each model uses a consistent pipeline that includes:
+
+1. Feature scaling
+2. PCA transformation
+3. Model training and prediction
+
+## Project Structure
+
+```
+project/
+│
+├── winequalityN.csv          # Input dataset
+├── trained_models/           # Directory containing saved models
+│   ├── logistic_regression_model.pkl
+│   ├── decision_tree_model.pkl
+│   ├── random_forest_model.pkl
+│   ├── knn_model.pkl
+│   ├── svc_model.pkl
+│   └── gradient_boosting_model.pkl
+└── wine_quality_prediction.py # Main script
+```
+
+## Usage
+
+### Loading a Saved Model
+
+```python
+def load_model(model_name):
+    """
+    Load a saved model from the trained_models directory
+
+    Parameters:
+    model_name (str): Name of the model to load (without '_model.pkl')
+
+    Returns:
+    object: The loaded model pipeline
+    """
+    filename = f'trained_models/{model_name}_model.pkl'
+    with open(filename, 'rb') as file:
+        model = pickle.load(file)
+    return model
+```
+
+### Making Predictions
+
+```python
+# Example usage
+model = load_model('random_forest')
+predictions = model.predict(X_test)
+```
+
+## Dependencies
+
+- pandas
+- numpy
+- scikit-learn
+- matplotlib
+- seaborn
+
+## Model Performance
+
+The project includes various evaluation metrics for each model:
+
+- Accuracy scores
+- Classification reports (precision, recall, F1-score)
+- Visual comparisons of model performance
+
+## Visualization
+
+The project includes several visualization components:
+
+- Feature distribution plots
+- Correlation heatmaps
+- Bivariate analysis plots
+- Model performance comparison plots
+
+## Future Improvements
+
+Potential areas for enhancement:
+
+1. Hyperparameter tuning for each model
+2. Feature selection optimization
+3. Ensemble method exploration
+4. Cross-validation implementation
+5. Addition of more advanced models
+6. API development for model deployment
diff --git a/Prediction Models/wine_type/test.py b/Prediction Models/wine_type/test.py
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+import os
+import pickle
+import pandas as pd
+import numpy as np
+from sklearn.metrics import classification_report, accuracy_score, confusion_matrix
+import seaborn as sns
+import matplotlib.pyplot as plt
+
+def load_model(model_name):
+    """
+    Load a saved model from the trained_models directory
+    """
+    filename = f'trained_models/{model_name}_model.pkl'
+    try:
+        with open(filename, 'rb') as file:
+            model = pickle.load(file)
+        print(f"Successfully loaded {model_name} model")
+        return model
+    except FileNotFoundError:
+        print(f"Error: Model file {filename} not found")
+        return None
+    except Exception as e:
+        print(f"Error loading model: {str(e)}")
+        return None
+
+def prepare_data(data_path):
+    """
+    Prepare the wine quality data for testing, ensuring feature names match training data
+    """
+    try:
+        # Read the data
+        df = pd.read_csv(data_path)
+        
+        # Convert type to dummy variables and keep all columns except 'quality'
+        df = pd.concat([df, pd.get_dummies(df['type'])], axis=1)
+        df = df.drop('type', axis=1)
+        
+        # Remove null values
+        df = df.dropna()
+        
+        # Create binary quality target
+        df['quality_binary'] = df['quality'].apply(lambda x: 1 if x > 5 else 0)
+        
+        # Select features in the same order as during training
+        feature_columns = [
+            "fixed acidity", "volatile acidity", "citric acid", "residual sugar",
+            "chlorides", "free sulfur dioxide", "total sulfur dioxide", "density",
+            "pH", "sulphates", "alcohol", "red", "white"
+        ]
+        
+        # Prepare features and target
+        X = df[feature_columns]  # Only select the features used in training
+        y = df['quality_binary']
+        
+        print("Data preparation successful")
+        print(f"Features included: {', '.join(X.columns)}")
+        return X, y
+    
+    except Exception as e:
+        print(f"Error preparing data: {str(e)}")
+        return None, None
+
+def evaluate_model(model, X, y, model_name):
+    """
+    Evaluate a model's performance
+    """
+    try:
+        # Make predictions
+        y_pred = model.predict(X)
+        
+        # Calculate accuracy
+        accuracy = accuracy_score(y, y_pred)
+        
+        # Print results
+        print(f"\nResults for {model_name}:")
+        print(f"Accuracy: {accuracy:.4f}")
+        print("\nClassification Report:")
+        print(classification_report(y, y_pred))
+        
+        # Create confusion matrix plot
+        plt.figure(figsize=(8, 6))
+        cm = confusion_matrix(y, y_pred)
+        sns.heatmap(cm, annot=True, fmt='d', cmap='Blues')
+        plt.title(f'Confusion Matrix - {model_name}')
+        plt.ylabel('True Label')
+        plt.xlabel('Predicted Label')
+        plt.show()
+        
+        return accuracy, y_pred
+    
+    except Exception as e:
+        print(f"Error evaluating model: {str(e)}")
+        return None, None
+
+def test_all_models(data_path):
+    """
+    Test all saved models and compare their performance
+    """
+    # List of model names
+    model_names = [
+        'logistic_regression',
+        'decision_tree',
+        'random_forest',
+        'knn',
+        'svc',
+        'gradient_boosting'
+    ]
+    
+    # Prepare data
+    X, y = prepare_data(data_path)
+    if X is None or y is None:
+        return
+    
+    # Store results
+    results = []
+    
+    # Test each model
+    for model_name in model_names:
+        model = load_model(model_name)
+        if model is not None:
+            accuracy, _ = evaluate_model(model, X, y, model_name)
+            if accuracy is not None:
+                results.append({'Model': model_name, 'Accuracy': accuracy * 100})
+    
+    # Create comparison plot
+    if results:
+        results_df = pd.DataFrame(results)
+        plt.figure(figsize=(10, 6))
+        sns.barplot(x='Model', y='Accuracy', data=results_df)
+        plt.xticks(rotation=45)
+        plt.title('Model Comparison on Test Data')
+        plt.tight_layout()
+        plt.show()
+
+def main():
+    """
+    Main function to run the test script
+    """
+    print("Starting model testing...")
+    
+    # Specify the path to your test data
+    data_path = 'winequalityN.csv'  # Update this path as needed
+    
+    # Test all models
+    test_all_models(data_path)
+    
+    print("\nTesting completed!")
+
+if __name__ == "__main__":
+    main()
\ No newline at end of file
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diff --git a/Prediction Models/wine_type/training.py.ipynb b/Prediction Models/wine_type/training.py.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e3e9108d",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "\n",
+    "# WINE QUALITY PREDICTION"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "8d8135c1",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Import necessary packages\n",
+    "\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from sklearn.impute import SimpleImputer\n",
+    "from sklearn.preprocessing import StandardScaler, MinMaxScaler\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.tree import DecisionTreeClassifier\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from sklearn.neighbors import KNeighborsClassifier\n",
+    "from sklearn.svm import SVC\n",
+    "from sklearn.ensemble import GradientBoostingClassifier\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "from sklearn.pipeline import make_pipeline\n",
+    "from sklearn.preprocessing import OrdinalEncoder, OneHotEncoder\n",
+    "from sklearn.compose import ColumnTransformer\n",
+    "from sklearn.metrics import classification_report"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cc675b81",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "# Read csv File"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "94e180bb",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Read the csv file\n",
+    "data = pd.read_csv('winequalityN.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "b8252c4b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Good practices to make a copy of the original dataframe to avoid loss of data \n",
+    "df = data.copy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "5fc3e9ea",
+   "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>fixed acidity</th>\n",
+       "      <th>volatile acidity</th>\n",
+       "      <th>citric acid</th>\n",
+       "      <th>residual sugar</th>\n",
+       "      <th>chlorides</th>\n",
+       "      <th>free sulfur dioxide</th>\n",
+       "      <th>total sulfur dioxide</th>\n",
+       "      <th>density</th>\n",
+       "      <th>pH</th>\n",
+       "      <th>sulphates</th>\n",
+       "      <th>alcohol</th>\n",
+       "      <th>quality</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>white</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>0.27</td>\n",
+       "      <td>0.36</td>\n",
+       "      <td>20.7</td>\n",
+       "      <td>0.045</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>170.0</td>\n",
+       "      <td>1.0010</td>\n",
+       "      <td>3.00</td>\n",
+       "      <td>0.45</td>\n",
+       "      <td>8.8</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>white</td>\n",
+       "      <td>6.3</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>0.049</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>132.0</td>\n",
+       "      <td>0.9940</td>\n",
+       "      <td>3.30</td>\n",
+       "      <td>0.49</td>\n",
+       "      <td>9.5</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>white</td>\n",
+       "      <td>8.1</td>\n",
+       "      <td>0.28</td>\n",
+       "      <td>0.40</td>\n",
+       "      <td>6.9</td>\n",
+       "      <td>0.050</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>97.0</td>\n",
+       "      <td>0.9951</td>\n",
+       "      <td>3.26</td>\n",
+       "      <td>0.44</td>\n",
+       "      <td>10.1</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>white</td>\n",
+       "      <td>7.2</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>8.5</td>\n",
+       "      <td>0.058</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>186.0</td>\n",
+       "      <td>0.9956</td>\n",
+       "      <td>3.19</td>\n",
+       "      <td>0.40</td>\n",
+       "      <td>9.9</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>white</td>\n",
+       "      <td>7.2</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>8.5</td>\n",
+       "      <td>0.058</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>186.0</td>\n",
+       "      <td>0.9956</td>\n",
+       "      <td>3.19</td>\n",
+       "      <td>0.40</td>\n",
+       "      <td>9.9</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    type  fixed acidity  volatile acidity  citric acid  residual sugar  \\\n",
+       "0  white            7.0              0.27         0.36            20.7   \n",
+       "1  white            6.3              0.30         0.34             1.6   \n",
+       "2  white            8.1              0.28         0.40             6.9   \n",
+       "3  white            7.2              0.23         0.32             8.5   \n",
+       "4  white            7.2              0.23         0.32             8.5   \n",
+       "\n",
+       "   chlorides  free sulfur dioxide  total sulfur dioxide  density    pH  \\\n",
+       "0      0.045                 45.0                 170.0   1.0010  3.00   \n",
+       "1      0.049                 14.0                 132.0   0.9940  3.30   \n",
+       "2      0.050                 30.0                  97.0   0.9951  3.26   \n",
+       "3      0.058                 47.0                 186.0   0.9956  3.19   \n",
+       "4      0.058                 47.0                 186.0   0.9956  3.19   \n",
+       "\n",
+       "   sulphates  alcohol  quality  \n",
+       "0       0.45      8.8        6  \n",
+       "1       0.49      9.5        6  \n",
+       "2       0.44     10.1        6  \n",
+       "3       0.40      9.9        6  \n",
+       "4       0.40      9.9        6  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#View the data\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "4ff043f8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(6497, 13)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "0ef12f4a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 6497 entries, 0 to 6496\n",
+      "Data columns (total 13 columns):\n",
+      " #   Column                Non-Null Count  Dtype  \n",
+      "---  ------                --------------  -----  \n",
+      " 0   type                  6497 non-null   object \n",
+      " 1   fixed acidity         6487 non-null   float64\n",
+      " 2   volatile acidity      6489 non-null   float64\n",
+      " 3   citric acid           6494 non-null   float64\n",
+      " 4   residual sugar        6495 non-null   float64\n",
+      " 5   chlorides             6495 non-null   float64\n",
+      " 6   free sulfur dioxide   6497 non-null   float64\n",
+      " 7   total sulfur dioxide  6497 non-null   float64\n",
+      " 8   density               6497 non-null   float64\n",
+      " 9   pH                    6488 non-null   float64\n",
+      " 10  sulphates             6493 non-null   float64\n",
+      " 11  alcohol               6497 non-null   float64\n",
+      " 12  quality               6497 non-null   int64  \n",
+      "dtypes: float64(11), int64(1), object(1)\n",
+      "memory usage: 660.0+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91169ef9",
+   "metadata": {},
+   "source": [
+    "# Data exploration & cleaning"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "c1868345",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Convert the type column to numeric values using dummy variables\n",
+    "df = pd.concat([df, pd.get_dummies(df['type'])], axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "7eec7e3d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#drop 'type'column\n",
+    "df = df.drop('type', axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "331b82c4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "num of rows 6497\n",
+      "num of columns 14\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"num of rows\", df.shape[0])\n",
+    "print(\"num of columns\", df.shape[1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "3d671a71",
+   "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>fixed acidity</th>\n",
+       "      <th>volatile acidity</th>\n",
+       "      <th>citric acid</th>\n",
+       "      <th>residual sugar</th>\n",
+       "      <th>chlorides</th>\n",
+       "      <th>free sulfur dioxide</th>\n",
+       "      <th>total sulfur dioxide</th>\n",
+       "      <th>density</th>\n",
+       "      <th>pH</th>\n",
+       "      <th>sulphates</th>\n",
+       "      <th>alcohol</th>\n",
+       "      <th>quality</th>\n",
+       "      <th>red</th>\n",
+       "      <th>white</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>7.0</td>\n",
+       "      <td>0.27</td>\n",
+       "      <td>0.36</td>\n",
+       "      <td>20.7</td>\n",
+       "      <td>0.045</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>170.0</td>\n",
+       "      <td>1.0010</td>\n",
+       "      <td>3.00</td>\n",
+       "      <td>0.45</td>\n",
+       "      <td>8.8</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6.3</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>0.049</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>132.0</td>\n",
+       "      <td>0.9940</td>\n",
+       "      <td>3.30</td>\n",
+       "      <td>0.49</td>\n",
+       "      <td>9.5</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>8.1</td>\n",
+       "      <td>0.28</td>\n",
+       "      <td>0.40</td>\n",
+       "      <td>6.9</td>\n",
+       "      <td>0.050</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>97.0</td>\n",
+       "      <td>0.9951</td>\n",
+       "      <td>3.26</td>\n",
+       "      <td>0.44</td>\n",
+       "      <td>10.1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>7.2</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>8.5</td>\n",
+       "      <td>0.058</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>186.0</td>\n",
+       "      <td>0.9956</td>\n",
+       "      <td>3.19</td>\n",
+       "      <td>0.40</td>\n",
+       "      <td>9.9</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>7.2</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>8.5</td>\n",
+       "      <td>0.058</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>186.0</td>\n",
+       "      <td>0.9956</td>\n",
+       "      <td>3.19</td>\n",
+       "      <td>0.40</td>\n",
+       "      <td>9.9</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
+       "0            7.0              0.27         0.36            20.7      0.045   \n",
+       "1            6.3              0.30         0.34             1.6      0.049   \n",
+       "2            8.1              0.28         0.40             6.9      0.050   \n",
+       "3            7.2              0.23         0.32             8.5      0.058   \n",
+       "4            7.2              0.23         0.32             8.5      0.058   \n",
+       "\n",
+       "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
+       "0                 45.0                 170.0   1.0010  3.00       0.45   \n",
+       "1                 14.0                 132.0   0.9940  3.30       0.49   \n",
+       "2                 30.0                  97.0   0.9951  3.26       0.44   \n",
+       "3                 47.0                 186.0   0.9956  3.19       0.40   \n",
+       "4                 47.0                 186.0   0.9956  3.19       0.40   \n",
+       "\n",
+       "   alcohol  quality    red  white  \n",
+       "0      8.8        6  False   True  \n",
+       "1      9.5        6  False   True  \n",
+       "2     10.1        6  False   True  \n",
+       "3      9.9        6  False   True  \n",
+       "4      9.9        6  False   True  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "87edf53d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 6497 entries, 0 to 6496\n",
+      "Data columns (total 14 columns):\n",
+      " #   Column                Non-Null Count  Dtype  \n",
+      "---  ------                --------------  -----  \n",
+      " 0   fixed acidity         6487 non-null   float64\n",
+      " 1   volatile acidity      6489 non-null   float64\n",
+      " 2   citric acid           6494 non-null   float64\n",
+      " 3   residual sugar        6495 non-null   float64\n",
+      " 4   chlorides             6495 non-null   float64\n",
+      " 5   free sulfur dioxide   6497 non-null   float64\n",
+      " 6   total sulfur dioxide  6497 non-null   float64\n",
+      " 7   density               6497 non-null   float64\n",
+      " 8   pH                    6488 non-null   float64\n",
+      " 9   sulphates             6493 non-null   float64\n",
+      " 10  alcohol               6497 non-null   float64\n",
+      " 11  quality               6497 non-null   int64  \n",
+      " 12  red                   6497 non-null   bool   \n",
+      " 13  white                 6497 non-null   bool   \n",
+      "dtypes: bool(2), float64(11), int64(1)\n",
+      "memory usage: 621.9 KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "6244e419",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "fixed acidity           10\n",
+       "volatile acidity         8\n",
+       "citric acid              3\n",
+       "residual sugar           2\n",
+       "chlorides                2\n",
+       "free sulfur dioxide      0\n",
+       "total sulfur dioxide     0\n",
+       "density                  0\n",
+       "pH                       9\n",
+       "sulphates                4\n",
+       "alcohol                  0\n",
+       "quality                  0\n",
+       "red                      0\n",
+       "white                    0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "fbbaa99e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of rows before removing null values: 6497\n",
+      "Number of rows after removing null values: 6463\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Remove rows with null values from the dataframe\n",
+    "df_no_null = df.dropna()\n",
+    "\n",
+    "# Check the number of rows before and after removing null values\n",
+    "print(\"Number of rows before removing null values:\", len(df))\n",
+    "print(\"Number of rows after removing null values:\", len(df_no_null))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "82170c53",
+   "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>fixed acidity</th>\n",
+       "      <th>volatile acidity</th>\n",
+       "      <th>citric acid</th>\n",
+       "      <th>residual sugar</th>\n",
+       "      <th>chlorides</th>\n",
+       "      <th>free sulfur dioxide</th>\n",
+       "      <th>total sulfur dioxide</th>\n",
+       "      <th>density</th>\n",
+       "      <th>pH</th>\n",
+       "      <th>sulphates</th>\n",
+       "      <th>alcohol</th>\n",
+       "      <th>quality</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>6463.000000</td>\n",
+       "      <td>6463.000000</td>\n",
+       "      <td>6463.000000</td>\n",
+       "      <td>6463.000000</td>\n",
+       "      <td>6463.000000</td>\n",
+       "      <td>6463.000000</td>\n",
+       "      <td>6463.000000</td>\n",
+       "      <td>6463.000000</td>\n",
+       "      <td>6463.000000</td>\n",
+       "      <td>6463.000000</td>\n",
+       "      <td>6463.000000</td>\n",
+       "      <td>6463.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>7.217755</td>\n",
+       "      <td>0.339589</td>\n",
+       "      <td>0.318758</td>\n",
+       "      <td>5.443958</td>\n",
+       "      <td>0.056056</td>\n",
+       "      <td>30.516865</td>\n",
+       "      <td>115.694492</td>\n",
+       "      <td>0.994698</td>\n",
+       "      <td>3.218332</td>\n",
+       "      <td>0.531150</td>\n",
+       "      <td>10.492825</td>\n",
+       "      <td>5.818505</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>1.297913</td>\n",
+       "      <td>0.164639</td>\n",
+       "      <td>0.145252</td>\n",
+       "      <td>4.756852</td>\n",
+       "      <td>0.035076</td>\n",
+       "      <td>17.758815</td>\n",
+       "      <td>56.526736</td>\n",
+       "      <td>0.003001</td>\n",
+       "      <td>0.160650</td>\n",
+       "      <td>0.148913</td>\n",
+       "      <td>1.193128</td>\n",
+       "      <td>0.873286</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>3.800000</td>\n",
+       "      <td>0.080000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.600000</td>\n",
+       "      <td>0.009000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>6.000000</td>\n",
+       "      <td>0.987110</td>\n",
+       "      <td>2.720000</td>\n",
+       "      <td>0.220000</td>\n",
+       "      <td>8.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>6.400000</td>\n",
+       "      <td>0.230000</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>1.800000</td>\n",
+       "      <td>0.038000</td>\n",
+       "      <td>17.000000</td>\n",
+       "      <td>77.000000</td>\n",
+       "      <td>0.992330</td>\n",
+       "      <td>3.110000</td>\n",
+       "      <td>0.430000</td>\n",
+       "      <td>9.500000</td>\n",
+       "      <td>5.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>7.000000</td>\n",
+       "      <td>0.290000</td>\n",
+       "      <td>0.310000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>0.047000</td>\n",
+       "      <td>29.000000</td>\n",
+       "      <td>118.000000</td>\n",
+       "      <td>0.994890</td>\n",
+       "      <td>3.210000</td>\n",
+       "      <td>0.510000</td>\n",
+       "      <td>10.300000</td>\n",
+       "      <td>6.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>7.700000</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>0.390000</td>\n",
+       "      <td>8.100000</td>\n",
+       "      <td>0.065000</td>\n",
+       "      <td>41.000000</td>\n",
+       "      <td>156.000000</td>\n",
+       "      <td>0.997000</td>\n",
+       "      <td>3.320000</td>\n",
+       "      <td>0.600000</td>\n",
+       "      <td>11.300000</td>\n",
+       "      <td>6.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>15.900000</td>\n",
+       "      <td>1.580000</td>\n",
+       "      <td>1.660000</td>\n",
+       "      <td>65.800000</td>\n",
+       "      <td>0.611000</td>\n",
+       "      <td>289.000000</td>\n",
+       "      <td>440.000000</td>\n",
+       "      <td>1.038980</td>\n",
+       "      <td>4.010000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>14.900000</td>\n",
+       "      <td>9.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       fixed acidity  volatile acidity  citric acid  residual sugar  \\\n",
+       "count    6463.000000       6463.000000  6463.000000     6463.000000   \n",
+       "mean        7.217755          0.339589     0.318758        5.443958   \n",
+       "std         1.297913          0.164639     0.145252        4.756852   \n",
+       "min         3.800000          0.080000     0.000000        0.600000   \n",
+       "25%         6.400000          0.230000     0.250000        1.800000   \n",
+       "50%         7.000000          0.290000     0.310000        3.000000   \n",
+       "75%         7.700000          0.400000     0.390000        8.100000   \n",
+       "max        15.900000          1.580000     1.660000       65.800000   \n",
+       "\n",
+       "         chlorides  free sulfur dioxide  total sulfur dioxide      density  \\\n",
+       "count  6463.000000          6463.000000           6463.000000  6463.000000   \n",
+       "mean      0.056056            30.516865            115.694492     0.994698   \n",
+       "std       0.035076            17.758815             56.526736     0.003001   \n",
+       "min       0.009000             1.000000              6.000000     0.987110   \n",
+       "25%       0.038000            17.000000             77.000000     0.992330   \n",
+       "50%       0.047000            29.000000            118.000000     0.994890   \n",
+       "75%       0.065000            41.000000            156.000000     0.997000   \n",
+       "max       0.611000           289.000000            440.000000     1.038980   \n",
+       "\n",
+       "                pH    sulphates      alcohol      quality  \n",
+       "count  6463.000000  6463.000000  6463.000000  6463.000000  \n",
+       "mean      3.218332     0.531150    10.492825     5.818505  \n",
+       "std       0.160650     0.148913     1.193128     0.873286  \n",
+       "min       2.720000     0.220000     8.000000     3.000000  \n",
+       "25%       3.110000     0.430000     9.500000     5.000000  \n",
+       "50%       3.210000     0.510000    10.300000     6.000000  \n",
+       "75%       3.320000     0.600000    11.300000     6.000000  \n",
+       "max       4.010000     2.000000    14.900000     9.000000  "
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Data Statistics\n",
+    "\n",
+    "df_no_null.describe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "495ef2bb",
+   "metadata": {},
+   "source": [
+    "\n",
+    "# Visualise distribution of the dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "61867c46",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['fixed acidity', 'volatile acidity', 'citric acid', 'residual sugar',\n",
+       "       'chlorides', 'free sulfur dioxide', 'total sulfur dioxide', 'density',\n",
+       "       'pH', 'sulphates', 'alcohol', 'quality', 'red', 'white'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Get column names\n",
+    "df_no_null.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "d6ec2e90",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 500x1000 with 14 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Get the number of columns and rows in the dataset\n",
+    "ncols = df_no_null.shape[1]\n",
+    "nrows = int(ncols / 2)\n",
+    "# Create a figure and a grid of subplots\n",
+    "fig, axes = plt.subplots(nrows=nrows, ncols=2, figsize=(5, 10))\n",
+    "\n",
+    "# Loop through each column and plot its histogram and density\n",
+    "i = 0 # Initialize a counter variable\n",
+    "for col in df_no_null.columns:\n",
+    "    # Get the row and column index of the subplot\n",
+    "    row = i // 2\n",
+    "    j = i % 2 # Use a different variable name for the column index\n",
+    "    \n",
+    "    # Plot the histogram and density of the column values\n",
+    "    sns.histplot(df_no_null[col], ax=axes[row, j])\n",
+    "    \n",
+    "    # Set the title and labels of the subplot using the column name\n",
+    "    axes[row, j].set_title(col)\n",
+    "    axes[row, j].set_xlabel(\"\")\n",
+    "    axes[row, j].set_ylabel(\"\")\n",
+    "\n",
+    "    # Increment the counter variable\n",
+    "    i += 1\n",
+    "\n",
+    "# Adjust the spacing between subplots\n",
+    "plt.tight_layout()\n",
+    "\n",
+    "# Show the figure\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6d1e19ea",
+   "metadata": {},
+   "source": [
+    "# Correlation of features"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "8ef383ed",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Calculate the correlation matrix\n",
+    "corr = df_no_null.corr()\n",
+    "\n",
+    "# Plot the correlation matrix as a heatmap\n",
+    "plt.figure(figsize=(12,10))\n",
+    "sns.heatmap(corr, annot=True, cmap=\"RdBu_r\")\n",
+    "plt.title(\"Correlation matrix of wine quality dataset\")\n",
+    "plt.show()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5f4962cc",
+   "metadata": {},
+   "source": [
+    "\n",
+    "# Bivariate analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "0923de9c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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JycmKi4uTr6+vu8NxqnO91gvNNZ22En3lypX276dOnaqgoCDNnTtXtWrVkiSdOnVKw4YN09VXX+2sEAAAAACI3BwAAADVS3Z2tiZMmKAvv/xSaWlpatu2rd544w1dccUVTpnPaSvRz1a3bl398MMPatWqlUP7tm3bdMMNNyg1NdXZIZQLq10AAADgLO7ONcnNAQAAUJEr0TMzspV+8pSys3IUFByosPBaCgkNqqBISzdo0CBt27ZNSUlJiomJ0bx58/T666/rjz/+UN26dR3GVuqV6H8N5vjx4yXajx8/ruzsbFeEAAAAAEDk5gAAAKg4R1PTNOmJV7R29Xp7W+euV2jSy48rKqaOU+bMz8/X559/rsWLF6tr166SpEmTJmnJkiVKSkrSlClTKnxOjwo/YiluueUWDRs2TF988YUOHTqkQ4cO6fPPP9eIESN06623uiIEAAAAACI3BwAAQMXIzMguUUCXpLWr12vSE68oM8M5CzSKi4tltVpLrCr38/PTTz/95JQ5XbISfcaMGRo3bpzuuusuFRUVnZ7Y01MjRozQq6++6ooQAABOUlhYqMWLFys1NVUxMTHq37+/vL293R0WAKAM5OYAUH0VW4pkLSySl7+vPMwuWTcJoAZLP3mqRAH9jLWr1yv95CmnbOsSFBSkxMREPffcc2rRooUiIyP18ccfa926dWrSpEmFzye5qIju7++v6dOn69VXX9XevXslSY0bN1ZAQIArpgcAOMmMGTO0cOFCWa1Wh7YBAwbogQcecGNkAICykJsDQPWTn5mr3BOZ2v3jbyrIzFXtxjFq0KmFAsND5OFJMR2Ac2Rn5ZyzP+c8/Zfiww8/1PDhw1W3bl2ZzWa1a9dOd955pzZu3OiU+VxSRD8jICBACQkJrpwSAOAkM2bM0IIFC1SrVi2NGDFCiYmJWrdunWbNmqUFCxZIEoV0AKjEyM0BoHooyM7XgV/+1NYv/reFwfFdh7Tnx9/UbcxtqhXrnD2JASAoOPCc/YHn6b8UjRs31qpVq5Sbm6usrCxFR0dr0KBBatSokVPmc1oR/dZbb9WcOXMUHBx83r0Vv/jiC2eFAQBwgsLCQi1cuFC1atXSwoUL5el5+tdJ3759deONN2rAgAFauHChhg8fztYuAFAJkJsDQPVVmJOv379cU6K9KN+iTZ+sVOJ9feQf6rxCFoCaKyy8ljp3vaLULV06d71CYeG1nB5DQECAAgICdOrUKS1dulSvvPKKU+Zx2jU9ISEhMplM9u/P9QUAqFoWL14sq9WqESNG2AvoZ3h6emr48OGyWq1avHixmyIEAJyN3BwAqq8Te1NlGEapfSf3HlFRnsXFEQGoKUJCgzTp5cfVuesVDu2du16hSa887pT90M9YunSpvv/+eyUnJ2vZsmW69tpr1bx5cw0bNswp8zltJfrs2bNL/R4AUPWlpqZKkhITE0vtP9N+ZhwAwL3IzQGg+rKddX+i0pRVYAeAihAVU0cvvzVR6SdPKScrR4HBgQoLr+XUArokZWZmavz48Tp06JDCwsJ022236fnnn5eXl5dT5nPJnuj5+fkyDEP+/v6SpAMHDujLL79Uy5YtdcMNN7giBABABYqJiZEkrVu3Tn379i3Rv27dOodxAIDKg9wcAKqX2k3qltkXUre2vPzYXhGAc4WEBjm9aP5XAwcO1MCBA102n0tu0dy/f3998MEHkqSMjAx17NhRr732mvr376+kpCRXhAAAqED9+/eX2WzWrFmzVFxc7NBXXFys999/X2azWf3793dThACAspCbA0D14hPoqybXXF6i3cPsoXZ3dFNAWLAbogKA6sUlRfRNmzbp6quvliR99tlnioqK0oEDB/TBBx/ozTffdEUIAIAK5O3trQEDBujUqVMaMGCAlixZohMnTmjJkiUO7dxUFAAqH3JzAKhe/EIC1bxnByXe11vhcdEKCA9W/Q5N1ePJOxUaW8fd4QFAteCS7Vzy8vIUFHR6Sf8PP/ygW2+9VR4eHurUqZMOHDjgihAAABXsgQcekCQtXLhQr732mr3dbDbrjjvusPcDACoXcnMAqH78w4LkHxak8MYxshVb5eXnI58AX3eHBQDVhkuK6E2aNNGiRYt0yy23aOnSpRozZowkKS0tTcHBXFYE4NJYrVZt3bpV6enpCgsLU0JCgsxms7vDqhEeeOABDR8+XIsXL1ZqaqpiYmLUv39/VqADQCVGbg6gotiKrTIMm8xOuokbys8/NNDdIQBAteSSIvozzzyju+66S2PGjNF1112nxMRESadXvrRt29YVIQCoplavXq3p06fr6NGj9raoqCiNHDlSXbt2dWNkNceZrV0AAFUDuTmAS1XEYOoIAAEAAElEQVSUV6CC9Ewd3fCHivMtCmveUKGN68knmAIuAKB6MhmGYbhioqNHj+rIkSO6/PLL5eFxeiv2X3/9VcHBwWrevLkrQrhgWVlZCgkJUWZmJqtxgEps9erVmjhxohITEzV48GDFxcUpOTlZH330kdatW6fJkydTSAcAVDqVIdckNwdwsYrzLTr881Yd/WWbQ7t3UIBaDO4l39AgN0UGACiPgoICJScnq2HDhvLz83N3OE6Vn5+v/fv3Ky4uTr6+jltdXWiu6ZIbi0qnV4YGBQVp2bJlys/PlyRdccUVlS5JB1A1WK1WTZ8+XYmJiZoyZYpatWolf39/tWrVSlOmTFFiYqKSkpJktVrdHSoAAJUOuTmAi2XJzi1RQJekwuxcHV6zRdaiYjdEBQAoL6//34orLy/PzZE435nX6HUJ24+5ZDuXkydPauDAgVq5cqVMJpN2796tRo0aacSIEapVq5bDDekA4EJs3bpVR48e1YQJE2QYhjZv3uywJ/rgwYM1atQobd26lUvTAQA4C7k5gEuRvmO/PP18FNmuhfwjw2TYbDKKbUr7badO/rFP9a5uJ7OXS0oNAIBLYDabFRoaqrS0NEmSv7+/TCaTm6OqWIZhKC8vT2lpaQoNDb2k++e55DfbmDFj5OXlpZSUFLVo0cLePmjQII0dO5ZEHUC5paenS5JSU1P13HPPldgTfcSIEQ7jAADAaeTmAC6Fh5dZjftdo8Nrtujwmi2SJE8/H8V0vlwBkeGSa3aMBQBUgKioKEmyF9Krq9DQUPtrvVguKaL/8MMPWrp0qerVq+fQHh8frwMHDrgiBADVTFhYmCTphRde0JVXXqkuXbqosLBQ3t7eOnz4sF544QWHcQAA4DRycwCXIiw+Vn8uWKqinHx7W3G+RSkrflXjfl1l9vN2Y3QAgPIwmUyKjo5WnTp1VFRU5O5wnMLLy+uSVqCf4ZIiem5urvz9/Uu0p6eny8fHxxUhAKhmWrVqJbPZLE9PT/3yyy86+x7JJpNJ3t7eKi4uVqtWrdwYJQAAlQ+5OYBLkXciw6GAfrbDa39TSMMYiTo6AFQpZrO5QgrN1ZlLbix69dVX64MPPrA/NplMstlseuWVV3Tttde6IgQA1cz27dtltVplsVjk6empu+66S/PmzdNdd90lT09PWSwWWa1Wbd++3d2hAgBQqZCbA7gU2YeOldlXcDJTtmKrC6MBAMA1XLIS/ZVXXlH37t21YcMGFRYW6vHHH9f27duVnp6uNWvWuCIEANXM2Te+CA4O1vz58zV//nxJp/f0ysrKst88AgAA/A+5OYBL4RsaXGafp7+vwxWiAABUFy4pordu3Vq7du3S22+/raCgIOXk5OjWW2/VqFGjFB0d7YoQAFQzf/75pyTp5ptv1ogRI7R161alp6crLCxMCQkJ+ve//62PP/5Yf/75p3r27OnmaAEAqDzIzQFcioDo2jKZzTKsJVecR7ZtLpncEBQAAE7m9CJ6UVGRbrzxRs2YMUNPPfWUs6cDUMPs2rVLJpNJbdu2tbfZbDbt3r3bjVHVLDk5OXrxxReVmpqqmJgYjR8/XoGBge4OCwBQCnJzAJcq9+gJNe57tZK/XyOr5X83oQtrESef0EDJxkp0dynMK1BBVp6sRVZ5+ngpICxYHp4u2cUXAKo9pxfRvby8tHXrVmdPA6CGqVu3riRpw4YNeuqpp9SxY0f5+PjIYrHo119/1YYNGxzGwTkeeOAB7dixw/44OTlZffv2VfPmzTVjxgw3RgYAKA25OYBLFRgdoQPLf1Fcry4ybIashUXyCQ5Q1oEjyth7SKHxse4OsUbKOZ6hbUt+1qGNu2Sz2uQb7K9WfTsp+rI4+dcKcnd4AFDlmQwXbFg2ZswY+fj46KWXXnL2VBUiKytLISEhyszMVHBw2fu9AXCfwsJC9erVS56enioqKpLNZrP3eXh4yMvLS8XFxfruu+/k7e3txkirr7ML6B06dFDbtm21efNm+wcYFNIBoHTuzjXJzQFcCkt2rtJ37ldAZLjMvt4yySSbtVh5x04pqF4d+YWHujvEGifnRKZ+nbtUITG1FdkiVobVJpvVpuS121W/XbziOrdmRToAlOFCc02X7IleXFys999/X8uXL1f79u0VEBDg0D916tQLPtaLL76oL774Qjt27JCfn586d+6sl19+Wc2aNbOPKSgo0D/+8Q8tWLBAFotFPXv21PTp0xUZGVlhrwmAe3l7e6tTp06l3gDNZrPJYrGoS5cuFNCdJCcnx15Ar1OnjjZs2GAvntepU0dpaWnasWOHcnJy2NoFACqZisrNycuBmsnTx1uhcfVkKy7WqZ0HVJxvUUjDGAXVj5TZh9zbHQqyctWi5xXa99M2rZv5jQybIe8AXzXt0U7FliLlnsxUUGQtd4cJAFWaSz6K3LZtm9q1a6egoCDt2rVLmzdvtn9t2bKlXMdatWqVRo0apZ9//lnLli1TUVGRbrjhBuXm5trHjBkzRkuWLNHChQu1atUqpaam6tZbb63gVwXAnaxWq9avX3/OMevXr5e1lBse4dK9+OKL9u/T0tIc+s5+fPY4AEDlUFG5OXk5UDMV5hYoc3+qts3+Sod/2qJjG//Urs9XaO9Xq2SzFMlG/u1yhs3Q74vX6vCWvTL+f0/6wtwCbVu8VjarTYbYpx4ALpVLVqKvXLmywo71/fffOzyeM2eO6tSpo40bN6pr167KzMzUrFmzNH/+fF133XWSpNmzZ6tFixb6+eef1alTpwqLBYD7bNiwQYWFhTKZTCptVyqTyaTCwkJt2LBBV155pRsirN4OHz5coeMAAK5TUbk5eTlQM9mKinRg2c8l2nOPntTRTX8oulOCfAL93RBZzWVYbco4eFwmk0nhjaPl7e+rrKPpyknL0K4Vm1S3bWN3hwgAVZ5LiujOlJmZKUkKCwuTJG3cuFFFRUXq0aOHfUzz5s0VGxurdevWkawD1cSnn34qSaUW0M9u//TTTymiO4Gfn1+FjsPFKSws1OLFi5WamqqYmBj179+fLYwAuA15OVAznNp5QMENoxV77RWSIdmsVpl9vJV96JgO/me9Itu1cHeINU7mkXTVbdNYja66TGm7DqogM1fx3S6XX2igtixcLVux7fwHgVPYiouVeTxLVqtNnp5mhUaxrQ5QVVXpIrrNZtPo0aPVpUsXtW7dWpJ09OhReXt7KzQ01GFsZGSkjh49WupxLBaLLBaL/XFWVpbTYgZQMS703yn/np2joKCgQseh/GbMmKGFCxc6bFk0Y8YMDRgwQA888IAbIwNQE1VUXi6RmwOVnXdokGKbxmrftz8p71i6JMns46W6V7VVsztuEDuHuF5wdJg8zB766Z3F9sVEB37ZIb9agbri7utlMpvdHGHNlHk8Q9tX/65fFq1VbkauQuqE6uo7u6lRmyYKrs2NsoGqpkrfnnnUqFHatm2bFixYcEnHefHFFxUSEmL/ql+/fgVFCMBZzH9JBDt27Ki3335bHTt2POc4VIzU1NQKHYfymTFjhhYsWKDg4GANHDhQY8aM0cCBAxUcHKwFCxZoxowZ7g4RQA1TUXm5RG4OVHZBdSO045Mf7AV0SbJaipSy4ldZTmXL08/HjdHVTL5B/tq8YGWJq3TzT+Vo14pNMptNboqs5srNyNF/F6zSf+YsU27G6XuFZKZl6Os3Fmnbj7+pqKDQzRECKK8qW0R/6KGH9PXXX2vlypWqV6+evT0qKkqFhYXKyMhwGH/s2DFFRUWVeqzx48crMzPT/nXw4EFnhg6gAhw7dsz+ffv27TVkyBA1atRIQ4YMUfv27Usdh4pTVFRUoeNw4QoLC7Vw4UIFBATIy8tLn376qV5//XV9+umn8vLyUkBAgBYuXKjCQhJzAK5RkXm5RG4OVHY5h9NUnHf6akOf0CD5RdSSh+fphSuHf9qiYoqDLpdx6Lhs1tK3bDn6xwFZi7nZq6vlZeVpy7JNpfb99OkqZZ3MdnFEAC5VldvOxTAMPfzww/ryyy/1448/Ki4uzqG/ffv28vLy0ooVK3TbbbdJknbu3KmUlBQlJiaWekwfHx/5+PBpOVCVnNl3VTq95+rGjRvPOw4Vx8vLy36p/V9v7nr2Yy8vL7fEV50tXrxYVqtVubm5uvzyyzVx4kTFxcUpOTlZH330kdauXWsfN2DAADdHC6A6c0ZeLpGbA5VdTupxhTSqq8h2LVSQnimrpVD+dcJlycjWwdWbpDLuWQTnKcq3lN1pSIaV98TVMo5llPlvoTC/UPnZeZLCXRoTgEtT5Yroo0aN0vz587V48WIFBQXZ91MMCQmRn5+fQkJCNGLECI0dO1ZhYWEKDg7Www8/rMTERG5eBFQyBQUFSklJuajnenh4yGY7/w1yPDw8tGvXrouaQ5JiY2Pl6+t70c+vrgIDA+1F9L9eNnr248DAQJfGVRMcPnxYktShQwc988wzWrJkiZYvX66YmBg988wzevrpp7Vhwwb7OABwFvJyoGYKbhgja75Fu7/4j4yz8vHgBtFq0v8aiZ1DXC6sYdlX9wRGhMjszRaXrubjf+4Pgz29q1w5Dqjxqty/2qSkJElSt27dHNpnz56toUOHSpJef/11eXh46LbbbpPFYlHPnj01ffp0F0eKmsZqtWrr1q1KT09XWFiYEhIS2I/7PFJSUnT//fc7dY7i4uJLmmPmzJlq2rRpBUZUPUREROjkyZMXNA7OkZubq169ejl8aDF9+nQ1a9bMjVEBqEnIy4GayS88RL/PWlxilW3WgSMKjIlQYN06boqs5vLy81FMQiOlbt3n2GGSWt/UWWYv/l/qav4h/goIDVRuRk6JvshGUfL29XZDVAAuRZUrov91xWNpfH199c477+idd95xQUSAtHr1ak2fPt2+Aks6vQ/oyJEj1bVrVzdGVrnFxsZq5syZF/XcvLw8jR49+rzjpk2bJn9//4uaQzodI0q60MvsuRy/4rVo0UKLFi3Sn3/+WaLPMAzt2LHDPg4AnIm8HK5i2GyyFhSoOL9Ahs0mT38/mX185OFZ5f47Wy1k7D1c5jYVxzbvUERCvBTg5+KoaraTyUdUr128QutHKHnNNhVk5qlWw0g1u769Dm/Zo5B6LGxxOZt025MDtWDyPBXm/+8+AQGhAer3yC2SiUs2gKqGrAO4RKtXr9bEiROVmJioCRMmOOxNPHHiRE2ePJlCehl8fX0vaZV33bp1z7llRd26ddWmTZuLPj7KdqFbhbClSMULCwuzf28ymdSjRw8NHDhQn376qZYvX24vap09DgCAqspmtarg+Amd+HWjbEXFpxtNJtVq3UKBDWJl9mE1p6sVZpVcWXuGtaBQBrVBlyvKt2jzgh9Vu3GMWva+Ul5+Pso6mq4tn65SfkaOmt/Qwd0h1jievp4K9AnW0Ffu08E/U3Ty0HFFNYlRVKNoefvxcwuoiiiiA5fAarVq+vTpSkxM1JQpU+Th4SFJatWqlaZMmaKnn35aSUlJ6tKlC1u7OMFHH32kwYMHl1qorVu3rj766CM3RFV1XMqe9Pn5+Rc87mL3pGc/+tKdOZ8mk0kmk0nLli3TsmXLJElms1k2m02GYWjXrl264oor3BkqAACXrDg3T2lrf3Vc+WwYOvX7H/IODpZfFFuHuFpQvUgd21jyijhJ8o8Ml7iHpctFxNeTJJ3Ym6oTe1Md+oKjw2Rm/22XsxZZ9flLnyht/zE1bh+v8JhwbV66QQe3p6jJFU3V8/7e7g4RQDnxkxS4BFu3btXRo0c1YcIEewH9DA8PDw0ePFijRo3S1q1b1bZtWzdFWb199NFHyszM1NixY7V37141btxYU6dOVUhIiLtDq/RcsSd9bm7uRc/BfvSlW7dunaTT2yh4eno63GDXw8NDVqvVPm7w4MFuiREAgIpgGIZy9qeUuXVIxp875V0rlNXoLubp7yuf0CBZMrJL9MV0uoz7irqB2dtTDa5srgO/7HBoN3mYlHDrVfLyZ2GKqxXkFiht/zFJ0t6Nu7V34257354Nu3XdPUXuCg3ARaKIDlyC9PR0SVJcXFyp/Wfaz4yDc4SEhOiJJ57Q/fffryeeeIIC+gWqqD3pPT09VVxcbO87+/Gl7EnPfvTnV9qHdwAAVBeGzaairJKF2jOKcnNl2KwujAiSVJiTp4Y3JP4fe3ce3kS1/gH8O5nsSfe9lC7sUCggm2VXQAXE5QqioiyieAUXXLjKBYV6Ua8LCiqgeBW8ioKi4k8FUVEpIrIjArKXsnXf0qbZM78/uI3ENqxtJm2+n+fpozlnMvNmUtI375w5B4W/HUDZwTMXObQRoUjs0xmVpwqhj+eUcv5WmVeKyLR4RKTEIWfjXlhNZkSmxKHlgM7I2bgHxphwaI2cp96fzOVm352SBLvF5r9giKhesIhOdBlq5hzOyclBenp6rf6cnByv7YgCSX3NSX92AR2A5zHnpG8YvXv3xp49e6BQKLBq1Srs378fpaWliIyMRLt27TB8+HC43W707t1b7lCJiBott8sJ6X939giiCIXIr01yEBQKaKIiYCkorLNfHRoCge+N3xnjo+Gy2xF3RXvEdm4DyeWGoBCgiQiF0qiF8hIHUNClqywqR+6mP9Dp5j7odscgSG43FCoFSo8VouCP4+gwrJfcIQad0KgQn30KUQGNgXcHEDU2zDiILkNGRgbi4+OxbNkyrznRAcDtdmPZsmVISEhARkaGjFESNQzOSS+P1q1bAzjzGXPbbbfhnnvuQWZmJjZt2oTZs2d7pnep2Y6IiC6cJElw2ayoPn0CzioTAEBlDIMuMQmiRgtB4EQV/iQIAgzNk1Bx4LDnosbZwtPbQ1SrZIgsuAkK4PQvu1F2yHttHVGjRocxQ+GyWqHS8H3xp6i0eIQlROHX/6yGvfrPEc7RrRLR++/Xc050GSg1aiSnp+D43txafR0HZkDJ94So0eF930SXQRRFTJ48GZs2bcLMmTOxd+9eVFdXY+/evZg5cyY2bdqE+++/n4uKUpO1bNkyfPHFF2jZsiUAoGXLlvjiiy9YQG9AJpPJ8/8VFRWYO3cuRo4ciblz56KioqLO7YiI6MK47TaYDv8BZ5UJokYLhUYLR1UFKo/sh9tulzu8oKTU6xDfvzeUBoOnTaFWI6ZnN6hDfY/0pIZjr7LUKqADgMtmx4kNOyBwVnS/0xh02PSXAjoAFB8+jRNbD0LFqVz8zu10YejkEWjVow3wvwuwgkKBjEFd0OvG3nC73OfZAxEFGl76IrpM/fv3R1ZWFt544w1MmTLF0x4XF4esrCz0799fxuiIGh7npPevC50eitNIERFdHMnthrWkCJqIaKhCQuGyVAMARJ0Bjspy2MqKoYtL5Gh0PxMUCmgiIxA/sC8kpxOABEGhhKjT8L2QSenBXGgjQpE8uBeUWjUklxuiWoWCnQdQtPsg3AM5T72/mQrK4Ki2oVmXlmg5oDOUaiWqS03YvWojcrfsR9tru0PHQrpf6cP0OHnoJK6bNBzWO62wVdugC9FBo9Pgj01/oPOgLnKHSEQXiUX0AGG1WnH8eO2r+YEiOTkZWi3n7PJl3759KCkp8WorLi7Gvn37WEQnonp1odNDcRopIqKLI7lcENUauKwWVJ8+AZXxzChnW1kxVKHhEJRKSC4XBCW/Qvmbw1wNl9UKa1ExJJcb2pgoSG4XlAY9C+kyUIcZ0XJEfxz64ifYK6oAAIKoQEKvTmh981XgQHT/MxdX4Oppt8KUV4Jdn6yHteLMwqJXThyG/H25cNmd598J1StjRAhimsVg1dyVOLn/hKe9VY+2uHbSUF7UIGqEmAEGiOPHj2PSpElyh+HT4sWLL2sBwqbszTffxPLlyxEaGoq0tDRIkgRBEJCTk4Ply5cDAP7+97/LHCURNRUnTpw4/0b/2y41NbVhgyEiakoUAgSlCKXeAFGrg8NUDgDQxsRDEBQQFKLnlnzyH0d1NcwnT0MdFgJ9fBwkSYLkdsOUk4vQtBSojIbz74TqVURaEvb+90u4bA5Pm+Ry4/QvvyFtaB+InA/d7+LbJ+OPtduQ++sfnrb8fbko2H8c/abcBLVeI2N0waksrxSrXl6JvMOnvdoPbz0AlVqJIfdch9Bo3sFL1JiwiB4gkpOTsXjx4nrZV25uLp599lnMmDEDKSkp9bLP5OTketlPU2O32/HJJ59AqVTCZDLht99+8+pXKpX45JNPcPfdd0OtVssUJRE1JRMnTrzg7datW9fA0RARNSUCBIUIS1EeXBazp9VRZYJSb4Q2Nl7G2IKXy+6ALi4GpTt3w1ZaBgBQGg2I6pIBh8UKUaeFgusP+VXliXyvAvrZTm3chdDkeIDXNvzK5XB5FdBrSG4Ju1auR5/JN8gQVXCzmi21Cug19m/ah/63XwVE+zkoAgDknyjE0T9ycOLIacQlxaJtRkvENIuGknea0XnwNyRAaLXaeh/pnZKSwtHjDeyLL76Ay3Vmzj+VSoVRo0Zh2LBhWL16NT755BM4HA7PdqNGjZIzVCJqImo+c+prOyIi+h+3Gy6b1auAXsNZXXVmYVG9JENgwcvldEIhKpD/489wO/4s2jqrzCjY+CsSBvaFy2qFwsCKrT+ZC0p89tlNZkhu/jvxt+IjdRdrAcCUVwqnte6LHtRwKksqffZJbgnWaqsfo6Eax4+cwr5t+xGdEIWYhCgYQvTYu/0A0sxWpLVLhkKhkDtECmAsohNdhpppFZRKJb7++mvPaPNJkyZh/PjxGDZsGJxO5wVPv0BERERE8pAA2MvLfPbby0uhDo/wX0AEAUD1qXyvArqHJKH8jwOI7Mo1QPzNEB8N4ECdfeowIwQFpz3yN1F97il0FCILg/4WEhXis09QCNAauOacv5UUlMBUasLPa37FoT1HPe3N0hIwYdodKMkvRUwibw8g31hEJ7oMR4+e+eC94oorak3Xolar0bVrV2zdutWzHRERySvQF/IGuJg3kVwEAYDk9tkvQQJXTPQvt1uCrdj3qGdbWTkk3nnldyHNYiFq1JAkN+K6toeoUaHs8AmYTxch8cpOUKg4J7q/RbWIhyAKiGubjOQebSFqVDAXV+Doz3ugCzdCVLH0428aoxaJrZvh9KFTtfra9e4AtY7z1PubzeLA/723Bnc/MQY6gw5ut/t/I88lzJ22EA8/d5/cIVKA4ycp0WWoKZzv378fTqfTaw4tp9OJAwcOeG1HRETyCvSFvAEu5k0kF0FUQh0RBUveyTr7NRFRUHC+VL8SRAVEne+LikqtFoLAEbb+VplXjPZjhkJyulCyLwfW0gok9EiHLjocVXlFcNntAHRyhxlUrFXVGPzEbcjdcgC7PlkPe7UNYYlRSL/+SoQ3j4Grrrs5qEFZKq246YmRUAgK2C122C02aPRaqHVquF1umCoqEBbDhUX9yWF3YOL0u/DHjgP49D9fovBUMSKiw3H9XdfgH688iIpSk9whUoBjFkh0GZKTk7Fjxw6YTCaMHDkSXbp0gVarhdVqxa5du2AymTzbERGR/AJ9IW+AfzOI5CIIAtRhEbCVFMFtt3n1KTQaqELC5QksiImiiJC0FFQdOw6FSgltTAygEGArKYXLYkVI6xYQ9SzW+pvaqEfFkZM4sX67p614zxHoosLQ6uarzsyNRH6lNeqx+9MNyNtzzNNWcboEm9/9Br3vux7hybHyBRek1EoV4Aa+eftrHN52CJAkKEQFOg7MQL/broJayYF2/hYRE4YfVv2MjxZ86mkrKy7H+69+jPwThbhx/DAZo6PGgEV0ostw3333YdWqVQCA8vJy/PTTTz63IyIi+XEhbyI6F1GtQUiLNrCXlcJWVgwIgCYiGurwSIi8s1AWCq0Gcf17w22zoTqvAJLLjfD2bSHqdVAZDFwETgYqvcargF7DUlKBgm1/ILE356n3N5fd6VVAP9uuldkY+Ogt/g2IIOqU+Gre5zi+N9fT5na5sXvdLgACBt55lWyxBavKCjM+e/erOvu+/2w9rrt1kJ8josaGGQfRZdDpdGjWrNk5t2nWrBl0Oo6QISIiImoMRLUG2th4hLZsh9AW7aCNiYeo5ty1spEkVJ/Mg620HPrEeBiSEuG221F5NEfuyIJW6YFcn33Fe4/A7eQ89f5WeizfZ191iQlOi92P0RAA2M02rwL62fb89Bts1XxP/K2qwgybxVZnn+SWUJTvew0OIoAj0Ykui91uR15e3jm3ycvLg91u57zoRERERI2EIAgQuDhiQHBWW6BPjEPFoSMwHToCAFCHhyGsXRtYi0ug0Gogcq56v3JafRf/3A6nHyOhGmq977UDBEGAIHL8pL+ZSnzPr+12uWE1W/0YDQGAWnPuv+u6c/w7IgI4Ep3osnz++edwu90AziQnSUlJaNeuHZKSkiAIAgDA7Xbj888/lzNMIiIiIqJGx+10QhAEFG3dAWtBkafdXl6Bos3boNRp4bbWPaqQGk5E6+Y++0KS46FgwdbvjLHhUCjFOvviO6ZC4LRHfmcIN3g9FlVnXewTBGh0vMPJ3/QhOiS3SqqzLzwqDGGRoX6OiBobXrInugw7duzw/P+aNWug1f555dJqteK6667zbDd69Gi/x0dERERE1FhJAKzFpXDb6hj5LEmoPHoM4Rnpfo8r2GlCDTAkRMOcV+zVLigUaD6gGySBBVt/c1hs6D5mELa+/z2k/w3yAgBDdBhaX9VFvsCCmC5Eh+bpyWiX2QERCVGwma3QGnXIP3Ia+Tl50BhYRPc3nVGHKVkTMWfKXFSWV3naNToNHnnhfoREGM7xbCIW0Ykuy5EjZ24pbdu2LVQqFXbu3InS0lJERkYiIyMDbdq0wcGDBz3bEREBZy6yHT9+vMGPc/DgwUt6XnJystdFQSIiIjlIbjdsxb7nqLWWlAFuyY8REXCmYNtieF8U7zmCot2H4LLaEJqcgKR+XeFyuwGX+/w7oXqlCzfi0A+70HfyCJQeK4DVVI2I5BiIahVObD+I9tf1kDvEoCOqRAx/4EZ8/uInKMj5c8761Iw0DHvgRtjdnBPd34pPl8JUUYln3pmOQ78fwdE/jqFZWiLSu7eDw+7AicOn0b5rG7nDpADGIjrRZVD+b/7FnJwc3HHHHSgoKPD0xcXFoayszGs7IiIAOH78OCZNmtTgx7nUYyxevBht2jCBJCIieQmCAFHn+6KuqOGaQ3KwV1Thjw+ykdCrI9rcMggKUYS13ITDX2ZDVCvR6uar5Q4x6FTklaBF347Y+OZXCE2IhFqvxendR6HUqNDtjqvh5Fz1flddXo0v53+OwmMFXu3Hdufgu3fW4Ko7B8sUWfByOZ14/oFXAQCPv/wgbppwPU7n5uHRkTMBADPeeFTO8KgRYGWP6DK0aNEC+fn5sNvtKC0txR133IFhw4Zh9erV+OSTT+BwODzbERHVSE5OxuLFiy/puVarFQ899NB5t3vttdcueTR5cnLyJT2PiIioPgmiCGNaCqqO1X33VmjrllBwAVi/qzp9Zn76vM17kLd5T61+wd8BETRGPSS3C73vux6mvBJYTdVIzWwPhVKENkwPSeC74m+S212rgF7j0JaDuOouFtH9TR+iR0iEET0GXIGwSCOK8oqh1qhw/ZhrsG5VNiJjw+UOkQIci+hEl+GJJ57AjTfeCABwOBz48MMP8eGHH9a5HRFRDa1We1kjvdu1a4f9+/efsz8jI+OS909EFOzcLhck15mRm4KohEKse8E+aliCIMBltSK8Q1uU7zvg1advlgiFSgXWBv1PEx7is0+p04AT7PifNkSHb+csg+SWkD7iSoQnxSBvz1Gc2HYICRlp6Dp6oNwhBp3qSovvTkmCw+rwXzAEADCGGjBr0T9QWVGF1R99j5NHTyO2WTSuGXkVBtzQF1qDTu4QKcCxiE5B73LmJj5w4MD5NwKQnZ2Ntm3bXtIxODcxEf3Vm2++ib///e91FtLbtWuHN998U4aoiIgaP0mS4LJZYck7BUdlOQBAFRoOXXwziBotBFZs/crtdKLqaC4UGjVi+/SCvdwEye2CJiIcttJylOzcjfgBfSBquECfP4WlJkJQCJDqmI8+tms7KJS86ORvZccLkT6iF+Lbp+LE9kPI33cMce2S0f7antix/Ee47JzOxd+M4WcWqWzVvQ2uHj/kzEVBpxNfv/5/yD+aD7WO01H5m1KtxMljpzH/n295Pr9OHDmF7dm/YcK0O9BzUDeZI6RAxyI6BT1/zE08d+7cS34u5yYmorq8+eabqKqqwowZM/Dbb7+hc+fOePbZZ2E0GuUOjajBuVwu7N6922sxb5EjhakeuO02VB7ZD8nl8rQ5TOVwmqsQ2qodRA0HNviVIEBp0KPy6DFY8gpgSE6CoFCg5Lc9cJmroQ4P44UNGVTlFyNtaB/kfLPJ699KWItm0MdEwM35t/1OG2qA5Jbw/fMfQZLOFAePbzkAXbgB/R68mQvwyuS+N6agsqwK3729BuUFZYhJicN1fx8OUcWcRQ4VJSYsfemjOi8ALnttJTr17ABEh/s/MAIAFBWWwGqxQqlUIjomEip14E3XxiI6Bb3LmZv4wIEDmDt3Lp588kkkJibi9ddfx6FDh9C6dWs8+OCDOHXqFF544QU89thjlzUSnYioLkajEVOmTMGkSZMwZcoUFtApKGRnZ2PhwoXIz8/3tMXHx2Py5Mno37+/jJFRYye53bCWFHkVBT19LidsZSXQxSWyaOtHolIJQ3ISRJ0WKoMB1XkFkNwuhLdtDQgCBIUCQgB+yW7qqvNLYCkuR+ubBsJeaYbTaoc+JgLVhWU48mU2Ot1zk9whBh1duAEbXv/cU0CvYSk347dPN6D7mEEyRRa8tKF67N+4D9+/842nrSy/DAe3HMAtT45G8/b8nu9vZpMZ5SUVdfbZbXaUFpahWVqCn6MiU0Ultv26Cy/PWYiTx09Db9Dh1jtvxF0TRyEmLlru8LywiE5B73LmJm7ZsiWWLVuG7OxszJkzB9OmTcOkSZMwbdo0tGrVCsuXL0dCQgKGDRvGEXJERESXKTs7G7NmzUJmZiaeeuoppKWlIScnB8uWLcOsWbOQlZXFQjpdMrfTAWeVyWe/o7ICmqgYiCregu8vbqcTgkoFZ6UZ5Xv/nMKs+lQe1BHhiOlxBSS7HVDzPfGn0NQEFGz/A6bcPKiMeogqJWymKkguN4xJseBE9f5Xeiwfbpe7zr6CP3LhtHH+bX9zWh348b/f1+6QJKx98yuMff5uIIIDYPxJoVCcu188dz/VP0mS8Mv6LfjHg8942qrNFix9azkO7DuM5+fPRGRUhIwRemt0vyHZ2dkYMWIEEhPPjAJZtWqVV78kSXj66aeRkJAAnU6HwYMH49ChQ/IES02eKIqYPHkyNm3ahJkzZ+LIkSMAgCNHjmDmzJnYtGkT7r//fhbQiYiILpPL5cLChQuRmZmJOXPmID09HXq9Hunp6ZgzZw4yMzOxaNEiuOoYRUwNp2nl5gKEc+RsgqgEwOKgP7klCa7qalQdP1Grz15WDvPJU8B5iiJU/3TREdDHRQEAHFXVsJaZILncgCAgeWCPc/47oobhqLb57pTOLJZM/lVRVA6VRoWr7hqM0U+Pwd+euBWjn74TfUb1h9VshaXqHAuPUoMwhhkQERNeZ59Gp/HZRw2nsKAYL89ZWGffpg3bUJhf7OeIzq3RZRxmsxmdO3fGggUL6ux/8cUX8dprr+HNN9/E5s2bYTAYcO2118Jqtfo5UgoW/fv3R1ZWFo4ePYoXXngBAPDCCy8gJyeHI+KIiIjqye7du5Gfn48xY8bUGkmkUCgwZswY5OXlYffu3TJFGJyaVG4uAOqIM4VBhVoDTWQMNJExUKjPLFqpiYhiDV0GVcfOFNBFnRbGtBSEtEiFKjT0TF/uiTPFW/Ire2U1kvp1QdwV7SBqzkynE9I8Dm3+djXKjhwH3HxP/C2qZaLPPmNsOJSc9sjvRJUSNz8+Ege37MeKZ5bhsxc+xopnPkD+0TzcPG0UoOAfFH8TFArcN3NcnSPO7/7HGCg5V73fmSurUVjgu1D+x+8H/RjN+TW66VyGDh2KoUOH1tknSRLmzZuHmTNn4sYbbwQA/Pe//0VcXBxWrVqF2267zZ+hUhDp378/+vTpg9WrV2Pu3Ll47LHHOIULERFRPSotLQUApKWl1dlf016zHflHU8rNBYUCgqCAMbU13HYr7KYz86Zqo+OgUGsguZwQhEY3Bqlxk87MVR/ZpRMEhQLVp/POTBmSkgSlXo/yffvPvw+qd2UHclGw4w9EtGqO1CFXQlCKqC4sQ843v8BhtiCmY2u5Qww6Sq0Kzbq2xKmdR7w7BKDzLf0gqhtd6afRC40KxWcvfoz8I3le7Ue2H4JSrcTgu6+TKbLgVV5cjp++3Ihn/vMk1n2ejWMHTyCheSyuGXU1fl23DZEx4YhNjJE7zKCiUqugUCjg9nHxNSLAFnptUp+kOTk5yM/Px+DBgz1tYWFh6NWrFzZt2uQzUbfZbLDZ/rz9yWTyPRcikS+iKHoWD23bti0L6ERERPUoMjISwJl8Lz09vVZ/Tk6O13Ykv8aWmytEJUStDuaTuXBZzJ52Z5UJSr0R+mbJUDC/8yuFqEBY29ao2H8AlvxCT7u1qBiqECOiunWBoGxSX2kbBYVSAUgSyg4dR+WJfCjUathNVQAAQVTwjg0Z2Cot6DDsSsS0SYKltAqCQoDb7UZiehqgEOC0c050f7Nb7Z4CulKrQkhECCqKTHA7nTi4eT+uGjv4PHug+qYQRZhNZqi1avQdmokufTpBZ9DCEKpHZXkVRI5E97vI6HBcfW0/fL9mfa0+nU6LNu1ayhCVb00q48jPzwcAxMXFebXHxcV5+ury/PPPIysrq0FjIyIiIqJLl5GRgfj4eCxbtgxz5szxmtLF7XZj2bJlSEhIQEZGhoxR0tkaY27utJi9Cuie9uoquKwWKHV6GaIKXm6XG26H3auAXsNRWQVLQSEMyc1liCy4RbZLhc1kRmKvTnBYrHDZ7NBGhMJSUoGKoyeh4NQhfmc32yCqlIht2xySyw1BEOB2uaHUqlB04BS0ofzs8rfKEhPiWsRj6N+vh9stoaq0EqGxYXDanfhi7qewVgXgtGZNXFhkKMY8PArPTnkFFaV/XqDXGbR4cv5URMcHzgKWwcJg0OPxmZNx+GAOjh057mlXa9R4Y8m/ERsXLWN0tTWpIvqlmj59Oh599FHPY5PJhObNmYwRERERBYqaxbxnzZqFmTNnYsyYMUhLS0NOTg6WLVuGTZs2ISsri3eCNQFy5eZupxO2kjPzcoo6A1QhZ+bddlRWwGWphq2kCKrQMChEfoXyHwlVOcd99ppzT8DYPMmP8RAAqPQ6xHZugz+WfwOX1e5pj+7UCs368u4AOYQmREBySzix/RAO//QbbJXViEiORccbeyOqVQJUOrXcIQad8PgI3DD1b/jsxY9RcvLPOZ+btU3C7VljISqZr/ib5HZj0ex3vQroAGAxWzHvyTcxa/E/ZIosuCUmxeOdj17F0cPH8duOPUhsFo8u3TsiLj4GSlVg/T0JrGguU3x8PACgoKAACQkJnvaCggJ06dLF5/M0Gg00Gk1Dh0dEREREl6FmMe+FCxdiypQpnvaEhAQu5h2AGl9uLkEQBBhTWsJltcBuKgcAqEMjIMbEw1JaBEgyhBXEFKIISfK9SKXklgCBc4f4m8vpxMHP1iG8RRIi2qRAoVCguqQcRbsOQhcdjqj0lgBYtPW33z7dgLzfczyPy44XYsPrq9D7vuuhTouXMbLgJIoiPn1+BdI6t8ANU2+GqFTCYbNj61eb8f2732DY5BFyhxh0zJXVyD10ss6+suJymMoqkZAcV2c/NayYuGjExEWjV58r5A7lnJpUET0tLQ3x8fFYt26dJzE3mUzYvHkz7r//fnmDIyIiIqLLVrOY9+7du1FaWorIyEhkZGRwBHoAamy5uSAqoUtsDvOJHLhtf95mb7FUQ9TqoE9KhYIjbP1KIYowNE+CJa+gzn59swQoVJw6xN8qc/PQZuQQKDUqSJIEyelCZFQYwlomoWDbPkRy/m2/c1TbvAroZ/vt0w3o/+BN/g2IYKmsxoiHb0LunmP4eM5HMJdXITwuHH1HD4AxIgR2i+38O6F6Zbed+7PJYrb4KRJqrBpdFlhVVYXDhw97Hufk5GDXrl2IjIxEcnIypk6dijlz5qB169ZIS0vDU089hcTERNx0003yBU3UxBQUFKCiokLuMLzk5uZ6/TfQhIWF1ZoTloiILo0oiujatavcYRCaXm7uqq7yKqB72q0WuKzVUOkNMkQVvJwOBxQqJdQR4bCXlXv1iVoN9M0S4HbYIWo46tmfjM1iAAioLq6APjoMUIpwVFvhqLIgMTMDEu8O8Lvio3k++8zFFVxYVAZqrQZbvtyEnWu3e9rKC8rx1Wtf4OpxQxCRGCVjdMEpJMwIjU6D1DbNMXBEH+hD9LBb7diw+lf8vnUfohP4ntC5Nboi+rZt23DVVVd5HtfMlzhu3DgsXboU//jHP2A2mzFp0iSUl5ejb9+++Oabb6DVauUKmahJKSgowJ13jYXDHphXzp999lm5Q6iTSq3BB+//l4V0IiJqUppSbi65nLCVlfjst5cWQx0awdHofiQAgCAgIiMd9vIKVOXkQnK7YWiWCH2zBEguNyROseN3Co0GktOFiqMnkbN6AySXG7qYCCRf1R0umwOaUF5s8je1/hyfqQKg4Pzb/icAu77bUWfXzx9no+2V7f0cEKk0Kkyb+wCO7DuGFYtWobykAsYwAwbfPAAjxl0LFf++03k0ut+QgQMHQjpHpiQIAp555hk888wzfoyKKHhUVFTAYbfB0mIA3NowucNpFBTWCuDoelRUVNRLEZ13Alwc3gVARNRwgis35+havxMEKJRKSE4XrAWFMCQlQlAoYC0th1hWDpXRyIsacnC6cOjzH2At+TMftRSV4cDH36HdbdfC7fI9jz01jMjUOCiUItxOV62++PTUgFucLxiUF5SdWbehDnaLDZbKaj9HRBazFQd/O4KP31rlaauqMGPV0tWoKK/ENbcMlC02ahz4SUpEl8StDYPbEC13GEGHdwJcPN4FQEREF0KhVEETGY3qU8fr7NdERrNg62+SBIVSRF72L5DcbljyCz1dltN5iOt7JdxuFmz9zVJa4VVAP9uJ9dvR8oYBfo6IIAA9x1+Lze+u8Src6iND0PmWfnALvGXD3zT6cy+QrVRzPQd/E0UFVi1dXWffT1/8jOG3D/FzRNTYMAu8TBwRenE4IpTo8vBOgItT33cBEBFR06YODYetpAguq/fiYqJOD2VIqExRBTGFAlXHT0HyUSgv338Q0d2v8HNQVJFzymefOa8Y8DH6lhqO5JYQEheOIf+8A6d+O4rqskrEtk5CWFI0nFY71Eqd3CEGHUO4EYZwI8zlVbX64lrEQ2M4d5Gd6l91VTXsNnudfZIkoayoHM1bNvNzVNSYsIh+GTgi9OJxRChR/eCdABRseNH64vHCNdHFU6jUMKa2hrPKBFtpEQABmshoKENCIaq4eKXfudxwVJh8djsqq3wW2KnhqI16n32iRs2Zj2SgUCpRWVAGp9WOhPQUAALcLicK9x9HVIsEzokuA4VCgVueHI2PZr8Ph/XPwq0h3IAbpv4N4LUmvzt7WqOYxGjEJkShrLgCp3PzAQAaHS9s0LmxiH4ZOCL04nBEKBERXQpetL40vHBNdGlEtRpiZDRUoeEAwClc5KQQoAo1wm4yIaxta6hDQyBJgNtmQ/mBQ1AolRAUrNj6W0SbFJzcsLPOvriu7SCoOE2F/0kIiY+A2+6Cy+WC2+GEUqNCZItEaIw6uO1OuQMMOlWVZoTFhWPi3EkwlZhgM1uhDdHDGGGERq+BxcQ50f1NVCrRY2BX9BuWibLicpzKyUPXvp2RmBKHtSt/hEbHi+V0bswI6wFHhBIRETUcXrS+eLxwTXT5WDyXn+Ryw5iWAn2zRJTu+h328jN3JCn1OkR27gRBq4EksIjubxKAlCFXIvf7zcBZCwsbm8UirGUzCJx/2+8kCYAb2PvVr8j7PQeSJEGl06DDsJ6IbZ8MtUErd4hBxxhiQN6hUzBGhGDXtztQll+KuLR4dL++F04fPIXENpw2xN+0eg1uuWcEnn9oHipKTWe1azH9tanQn+MuGyKARXQiIiJqJHjRmoj8RZIkSK4zIzcVSo6qlYugFAEbUPDzr5Ccf46kdVZbULhpCxKu6suZQ2RQuu8oLCXlaDtyMMwFJXBZ7TAkRsNhtuDgJ9+j44Qb5A4x6AgCsOmdNag4Vexpc1hs+O3TDeh66wA079lOxuiCkyQB1iorVj633NOWd/g0dv+wC7c+NUbGyIKYJGFR1rteBXQAsFZb8eoTizD7P0/IFBg1FiyiExERERER/Y/LbofDVAZbWQkAQBMZDXVoOBScE93vJJcb1afyvAroZyvfdwARXTP8HBW5XW6UHTyOsoPHoYsOh0KlROFvB+CyOQBBgCRxJLq/WcvNMOWVosPwnkjMaAlBABwWO/av3YZ9q7cgvmMqtEYuLupPktuNtW99Xavd7XJj9YL/w51zxvs/qCBXXWVB7qGTdfaVl1TAVFaJhOa8g5N8YxGdiIjoAnFxy4vDhS2JqLFx2e2ozDkIt83qaas+dRy2kiIYU1tDVLOQ7leSG7aSUp/dtvIKgAuL+l14i2bI37IHAGApLq/VJygUMkQV3CpOF2PIjDtQdPgkHFY7VDo1bGYLWg3oDKvZAqfNIXeIQcdUXAGHj/NuKqqAtcri54jIYT/zfuiNOvS97krEJEajrLgcG7/ZjIpSE6zV1vPsgYIdi+hEREQXgItbXjwubElEjYkkSXCYyrwK6DVcVgucVSaIkZxSyp8EhQJKg+85apU6HQSBBVt/czmcCG+ZhPIj3iM6RbUKcd3aQ+KFDb+LaZMEAIhukYiKUyUoO1aFsKQYGKNCobHqoeYodCLojXoMGNEHPQZ2xQ+fZ2PXpt8RmxiD8Y/fjkN7jiAqNkLuECnAsYhOjRZHhF4cjgglujxc3PLicGFLImpsJJfTM4VLXWylRVCFhnPBUT+SABiSmqHy6LE6+0NapJ6ZDJr8ym13IKpDC0S0SUHhzv1wWu0Ia9EM0R1a4PSvu5EyuJfcIQYdUa1EVUE5Nr29Gg7LnwM+ItPi0XPcNV4LwJJ/hESFQqlWwmmvPR1VSGQINFzs1e8UKhGdr0zH3McXeKadKjxVjD1b/8CdU2+FwL8ndB7MAKlR4ojQi8cRoUT1g4tbEhEFK3659ju3G9biEkR26YSy3Xu9RjiHtEiF2+XkqGcZaKPC4TRbkLdtH8JbJkGhUsFcUIKyIyeR0KsT+G/F/9wOFzYt/hoOq92rvTQnH/tWb0anm/rIFFnwspotGHDnIKx7d61Xu6BQ4OrxQ+B01L3WAzUcyenG0pc/qnPdhhWLPkfXPp1kiIoaExbRqVHiiNCLwxGhREREROchKKAOi4TFUl1ntzo8AlCwOOhXggIQAHtlFeKv6gen2QzJ5YYqNATW4hJYCwqhS4iXO8qgI7ndOJG9A3FXtINSp4HkckMXHY7S/cdgKa6AOtQod4hBp/xkca0Ceo2T2w+h/XU9/RwRSRJQlleKkdNvw67vd6C8oAyxyXHIGNQFO9ZuQ2waP7v8rdpsgamsss4+h82B8uIKJKUl+jkqqlFpqkJ1tQVKUURUTKTc4dSJRXRq1DgilIiIiIjqheSGUq+HqNXBZfVe8E3U6aHQaAG3BHAKbj+SoE9qBntZGYq37YQ2JhqCqIDpSA70CXGI6NiBt9/LwF5pRlLfLjj27a+wV5oBAIJCQOwV7QFBAiTeHeBv1sq6L/4BgNvlhtvl8mM0BAC6EB0ObPoD+zbsQYe+6Uhs1QzlBWX49N8rENksCko1y3F+d55pjfj3RB4WixVHDx3D6y/9B7t37kN0bBTumTwGfQb2QlR0YM1TzxSQiIiIiIiCniQBEBTQxiZAl5AEpd4Ipd4IfUIStDHxEBRinbeAU8MRFApITifcdgdCW6bBWVkJe2kZDIkJUBmNcFotkBT8SutvaoMOR77M9hTQAUBySyjYtg9umxPge+J3kc1jPf8fnhSDmDZJ0IUbAACaED2UapVcoQWt6opqDJsyAm6XCzu+2Ybsj37E7h92Qa1T4+qxQ2CvrvvOAWo4xjADouLqHuGsM2gRERPu34AIAPD7zn0Yc+P9+CV7K6oqzTh25DhmPvY83nj5P6goN8kdnhde+iIiIiIiInK7YSsrgf1/C4hqomMBCbBXlMJhKocmOg7aGE6L50+S2w2X1QpLfgEs+YWedmtRCVQhRkR2yQAcLoDr8/lVdVEZXHZHnX352/chvHVzP0dEgiig5YAMJHZKQ1luISwmM1J6toOoVsJpdwAiL2z4myRJ+Pnj9bjpsZEoPV2C8oIyRDePgSHciG/e+hq3PDFa7hCDjqBQYPzjt2P+P9/ympNeEASMe+w2KDhlm98VF5bgX/+cC3cd65t8+tFXuGvirQgLD5UhsrqxiE5ERESNgsJSLncIjUZ9n6uCggJUVFRc9n5sNhvy8/PrIaKGER8fD41Gc9n7CQsL4xokjZEgwGUxw5DcAm67DbbiAgCAKiwC6vAIWEuKZA4wOLkdTq8Ceg1HZRUs+QUwtkz1f1BBzlJc7rPPbjJzSgQ5KBSIT0/BxkVfwu36sxhljAlDn8k3QOJ0Ln5nCDeg9FQJPp7zIaKSomEMN+LwtoMoLyhHREIkVFreHeBvZlMVwiJD8MSrD2HLjztw8uhpxDaLwZWDu0Nv1KK8uALxzZm/+VOlqQq5OSd99u/euQ8tWqf4MaJzYxGdiIiIGgVdTrbcIQSlgoIC3HnXWDjsNrlDaTRUag0+eP+/LKQ3MoIoQhffDJa8k15zojurzRB1eujim0FQiDJGGJyqT5722Wc+dRohLQLny3Ww0Mf6XvBNE2bktEcyUKqV+PXt1V4FdACoKqrA759vRJdR/WWKLHhVlZtxzb1D8dXr/wdTsQkOmwPVFWYoNSoMmnCNz4VgqeGotRosylqKUzl56DagMzp0a4vCU0V45R8LYAgxYMbCR+UOMeiIynPnVXqDzk+RXBgW0YmIiKhRsKT1h1sXLncYjYLCUl5vFx0qKirgsNtgaTEAbm3Y5e3M7YTCVlUvcTUEt8YIKC4vPVZYK4Cj61FRUcEieiMjCAJcNmutRUUBwGWphtth5whbGUjnWqTSLUEC3xN/08dGQNSoIUkS4rt3gKhRofzQCVSeLEBiny4QOCe635UdL4TLUfdo87zfc9Dppj5+joiUShEn9p/A/QsfhN1mh8vhgqgSodKo8O3ba3D1uCFyhxh0nHYnyorKMf7x29GiQ8qZzypJQsce7fHJ4v+DxWyVO8SgEx4Rhh6ZXbF1085afUqliA6d2sgQlW8sohMREVGj4NaFw22IljuMoOXWhtXL+XeH1EMwRA3A7XTAXlbis99eWgJVSBhEhdqPUZExuTkseWem1hH1OgiCAs7qakCSoE9KZMFWBqJGjQ53DYfb4UDx3qOwlVcirlt7pA3tDZfTCYHzb/udw+z7bjFJkiC5znExihqEPkyPXjdm4vgfx2EI00Fj0KGy1ASXy42rxw2BWsPpXPzN6XDin68/Cp1RC7PJjKqKKugMOrTp3Ar/ePVBmE3VcocYdELDQjDz2UcxYdSDKC0p97QLgoB/zZ2O6Jgo+YKrA4vo9YBztF4Yniei+sN/TxeG54mIiC7U2SOaFVodNBHRACTYSovhtlkBSABHPfudqNcipE1L6GNjz0wTIklQKEVYioqhT0zgXM8ycDtdqDh6Cqc27kJYWjMoVCJO/bwTkiShzcjBkJx8T/wtqmWCzz59VChEFmz9ThAVsJmqERYTio2fbEB5filiU+PRZ1R/2K12aI1cEdnfImMjYLPa8Ol/vsTP3/wKyX1m6qmufTrhrkdGIy4pRuYIg1Nay2R8vOYdnD6ZD0u1FSq1CnHxMYiKjoBWd/lrFdUnFtHrAedopWDE4uSFa4hzxc8d+fB3/8LwPBFRYyMoBKjDIqBMTIbkdMBhrgIgQZ+QBEEU4ayu5nQu/iYIUKjVMDRLhEKp9BTMBYUCurg4CKIIKPieyEFUq5A+bgRcdgckpwvKTA0kpxtFvx1CfI8OcocXdNQGLeLTU5C/N7dWX5db+kGtD6xCVDAQBAGnDpzEd2+v8bSVF5Tj4JYDGDl9NCJiI2SMLjg5nS588d4ahEWGYubCx6BUinC7JOzdth//fXUF7v7HGLlDDEqmikrs2rYHrz6/CKdO5EOn0+KWO67H+Em3c070pohztF6Y+pyfleTH91Je/Ny5MA3xucPffSKipkkAoA6LgN1UDlGjhUIUPT3OajNUoeEyRhfcFKII8/GTMJ88Bcnlhi4+FiEtUgEBvLAhA5fdDkN8FA6u/B628koAgKAUkdCzI6IzWsHFkeh+53a60KJPR4TGRyJn0z44qm0ITYxCu2u6w1plgdPhgAaBVYxq6pw2B35Y+l3tDknCmoVfYdwLE/0fVJCzWW3oP7w3HDYHSvJLkX+iENHxUWiT0RJd+2bAZuGc6P4mSRKy123CPx951tNmsVjxwTsrcfCPI3jxjdmIjAqXL8C/YBG9HnCOVgpGLOJeuIYo5PJzRz783b8wvHBKRI2NoBDhslrhttlgyTvp1aeJioXkcEBQcz50vxIEQJJQvHUH7BUmT3PVseOoPp2P+P69Ac/FDvIXlU6Hvf/9Ci6b3dMmOV04/ctv0IQaEd66uYzRBSdTXil+eftrxHdIRddbB0BUKVFdWol9qzejusSE2DZ3yh1i0DEVVcDlcNbZZy6vgqWq9iLW1LBUKhVEhQILnv0vivP/XAMlJNyIh5+7D4bQwJp/Oxjk5xXi1effrLNvyy87kXeqgEV0ovrC6QIuTEOcJxZxKVjxd5+CFf/mXhiep8bL7XTA7bDDVlpUq89WUgiVIQRuhwOimtMi+I3bDXtpmVcB3dNlt8N0JAdhbVvJEFhwqzyR71VAP9vpTb8hNDkeCLBb8Js6S0UVIAH5e48hf++xWv0uB+8O8LfzLbArcCoqv5MkCe+9usKrgA4AleVVePOZpfjnG4/IFFnwMlVUoqjQ96Lue3fvR3pGWz9GdG4solOjxlGO8lFYK+QOodFoiHPF839heO7lw3Mvr4Y4V/ybS02dJEmwlRX77LeVFUOvT/ZjRARJgvlUns9uS14+Qlu38GNABADmAt8FD1tF1ZkFYMmvQuMjffZpQvQQVbxjw99CIkKg1qlht9S+4BQeFw5NgC2YGAys1VYc2ZtTZ19xfgmqKsx+joiUohKiKMLlY5HwsPAQP0d0biyi1wN+qb8wDXGeOK3ChanPaRXCwsKgUmuAo+vrZX/BQqXWICws7LL3w/N/8Xju5cNzL6/6PP9KlRpOR92jDqk2pUpdL+ee/E9yOHz2uZ0OsDToZ4IAQeF7NKcgipwTXQb6WN8FW3Wo4cwCA+RXSo0aEcmxKDteWKuv7ZArzjsqmuqfpcqCwXdfi9ULvwLOurAkKkVcPf4aOH1M9UINx2E/9zm3VnNOdH9Ta9UYMLg3fli7oVafTq9DWssUGaLyjUX0y8Av9Revvr7QezBpvjD1eJ7i4uLwwfv/RUVFYF08ys3NxbPPPosZM2YgJSWwPmiBM58XcXFxl70fnv+Lx3MvH557edXn+V/2wfv1cv5rzlmgqq/3sr7OPfmZIEBpDIHLVveXaJUhsEZDBQUJCElLQbWP0ejGlGRI5yiyU8MITU6AqFbBZa990SkxMwMKtUqGqIKbqFYifUQmcn/9Ayd3HobkdkMTokfbIVdApVV7FXHJf479loPRT43BHxv3oLygHDHJMWjTsx1++fRnXHPvdXKHF3QMoXqoNCo4bLU/uwRBQGRshAxRBTdRocDd99+BY0eP4+ihXE+7RqPGv+Y+GXDTHrGIfhn4pf7i1deXSl7AuHj1eQEjLi4uYIsDKSkpaNOmjdxhNCief/nw3MuH515e9XX+k5OTsXjx4nqIqGEkJydDq9XKHQbJRZKgDouErbQEkNzefQoFVGHhEFiH8i8BgFIJQ1IizCdPe3WpwkKhS4jjeyIHUYG2o6/B4S9+gt10ZvoDQaFAfI90hCTFcZyTDJQqJSrzS6HUqpB5z1BIkgSX3Ynj2w+i/bXdodJzUWR/0+g1OHXgBA5s3o/WPdogNjUO5QVlWP7MMjRr0wyiiuU4f9PqNLh+zDX4/N2va/X1G3ol1Dr+O/E3jVaNstJyPD5zCsrLKnBo/1FEx0SiVZs06AxaaLWBNe1Rk/5Xu2DBArz00kvIz89H586d8frrr6Nnz571egx+qZcHL2BcPI6KIwocVqsVx48fr5d95ebmev23PjTlQmKgn3ugaZ9/rVbbZHMTOjd/5OWXSxAUsJaXwpjSAtbCPDirzxQHlXojtLEJsJWXQhebKHOUwUaAqFJBGxcLQ0pzVB07DsnlhqF5MyjUargdDig0gfUFOxgICgFulxutb74akiRBcjqh1GlhKa2AQimecwoeaiCiArHtmiMkLgIndx6G1VSNyJQ4tB18BXQRIeBcVP6n0WswbMoN+OLVz7D/l32e9vC4CAy8axBUvGPD7xx2BwaO6AOdXosv31+Lyooq6AxaXDPyKlx9Uz+4Xe7z74TqVVR0JEJCjfj2qx/Rb1AmMvv1gADg0IGjqKioxF33jJI7RC9Ntoi+YsUKPProo3jzzTfRq1cvzJs3D9deey0OHDiA2NhYucOrJdC/1AfiF/r6uoBRn+e+IQTiua8vgf57D/D8X6hg+dypL8ePH8ekSZPqdZ/1OUXG4sWLm2yhM9DPPdC0zz8Fp8aSlwuCAHVIKMwnc6GJjIY2Jh4A4LRUw3wyB4akVM6/7XcSoFBAqdehdPdeqENDoVAqYTp0GCEt0qCJiYbk5LzC/iYB0IQaIDldqDxdBKfFipCkOBhiIgFRAcnNiq2/SZIbKr0GolqJtD7pcFgd0IUZoNJrAEGCm1V0vxNVIlQ6Na77+3DYLXZUFJYjMjEKAKAxaKHUsIjub5IkwWyqxhX9OqNz706wWazQ6DRQa9QoLSpHWBSnbZNDh05tYTQa8NZr7+G37XsRHRuFex+4E8NuGoLQ0MB6TwSpiS6d3atXL/To0QNvvPEGAMDtdqN58+Z48MEH8eSTT57zuSaTCWFhYaioqEBoaKg/wsXBgwfr/Ut9fWrKX+h57uUT6Oce4PmXU1M+97x4J59AP/dA0z7/dIYcuaacLicvB/x3vtwuF+zlpXDbbbAW5Xv1aWMToFCpoY6IhEIhNlgM5E2SJNhKSs+MNpfccNudkCQJoloFiArYSsuhjYuBiqPR/cpcXA6lWgkoFIDLBQkCBEGCJAGSqIACAjRGvdxhBpWqknJILkAQBUhONwSFAi6XC4JSgFqjhsvugiGq6f+9CSRV5ZVwuV2wV9lxaOsBVJZWIjI+EmlXtIJar4ZapYbWyHzPn4oLSvHT//2MjCvTcej3oyjOK0ZYZCjSu7fDtuxduPqm/ohrFiN3mEGr2myBucoMpUqFiMh6XEvxAlxortkki+h2ux16vR4rV67ETTfd5GkfN24cysvL8cUXX3htb7PZYLPZPI9NJhOaN2/u1y82gf6lvil/oee5l0+gn3uA519OTfncE1FwC6Yi+sXm5YC8ubnDXAlbaQnUYRFw/2+BUYVGC3t5KbRRMVAajA16fKrNUVUF0+EcCKIChuZJAABrSRmsBYWIzEiHymiQOcLgY62oROnBY4holQJRpYTkliAoBNhMZkCSoI0O44UNPzOXmVBVUAFtqA6aED3cLhcAwFJmhlKngj4iBCoN53v2J7vVDlu1DfZqGzQGzZk7NATAbnVApVYhNLpp//0PRA6HE3m5+fh62bfIO1GI6LhIlJdUQGfUYvTfb0ZMQhR0Bp3cYZIMLjQ3b5LTuRQXF8PlctWa6iMuLg779++vtf3zzz+PrKwsf4VXJ84RKh+ee/nw3MuL55+IiBraxeblgLy5uajRQdRqUXXsEBSqMwUnt8MBfWJzKHhhVxaiVouQVmlwW+2ozMmF5HTBkJQIXacOEETOvS0HQRQQ2ToV+dv2ovJkIUSlElAAzft3gypUzwK6DHRhRkhuCU6LHcd+/QMupxOGyBBEpsRDpVOzgC4DtVYNl8sFhaiA0+mE5Dpzh4BKq4Q+lHdqyEGlUiIiOhxX3dgPgiDAbndArVbB4XAiLDKUBXQ6ryZZRL9Y06dPx6OPPup5XDPahYiIiIiI/EvO3FyhVEITFQN1aDhc1jMj0UWtFoJSBYXIaVzkoFAqodTp4FKICG/fBhAESE4nRLUaChXnFJaDxmiEzWRGQq9OiO8hAZIE/O+ChppFKFkoFAroI0JgEcxI7tkWCoUCLqcLoqiANpR3a8iFRdnAExJuRLsurVFWXA6n3QlRJSIiOpxrntAFaZJF9OjoaIiiiIKCAq/2goICxMfH19peo9FAw6vlRERERET16mLzckD+3FyhEAGNCFHDkeeBQiGKUOjPKkbxu5vsNP8rzNqrLJAECUq1BqKKF5rkpFAoYIgMrEX4iAJVRHS43CFQI9Qk739Tq9Xo1q0b1q1b52lzu91Yt24dMjMzZYyMiIiIiCh4MC8natrURh00Bj0L6ERE1OQ1yZHoAPDoo49i3Lhx6N69O3r27Il58+bBbDZjwoQJcodGRERERBQ0mJcTERERUWPXZIvoo0ePRlFREZ5++mnk5+ejS5cu+Oabb2otakRERERERA2HeTkRERERNXaCJEmS3EEEGpPJhLCwMFRUVCA0NFTucIiIiIioCWGueXF4voiIiIiooVxortkk50QnIiIiIiIiIiIiIqoPLKITEREREREREREREfnAIjoRERERERERERERkQ9NdmHRy1EzTbzJZJI5EiIiIiJqampyTC5NdGGYmxMRERFRQ7nQ3JxF9DpUVlYCAJo3by5zJERERETUVFVWViIsLEzuMAIec3MiIiIiamjny80FiUNganG73Th9+jRCQkIgCILc4Vw0k8mE5s2b48SJE+dcVZbqH8+9fHju5cXzLx+ee/nw3MurMZ9/SZJQWVmJxMREKBScXfF85MrNG/PvWFPF9yTw8D0JPHxPAg/fk8DE9yXwyPWeXGhuzpHodVAoFEhKSpI7jMsWGhrKDwKZ8NzLh+deXjz/8uG5lw/Pvbwa6/nnCPQLJ3du3lh/x5oyvieBh+9J4OF7Enj4ngQmvi+BR4735EJycw59ISIiIiIiIiIiIiLygUV0IiIiIiIiIiIiIiIfWERvgjQaDWbNmgWNRiN3KEGH514+PPfy4vmXD8+9fHju5cXzTw2Nv2OBh+9J4OF7Enj4ngQevieBie9L4An094QLixIRERERERERERER+cCR6EREREREREREREREPrCITkRERERERERERETkA4voREREREREREREREQ+sIhOREREREREREREROQDi+hNyKJFi5CRkYHQ0FCEhoYiMzMTa9askTusoPPvf/8bgiBg6tSpcocSFGbPng1BELx+2rVrJ3dYQePUqVO48847ERUVBZ1Oh06dOmHbtm1yhxUUUlNTa/3uC4KAKVOmyB1ak+dyufDUU08hLS0NOp0OLVu2xL/+9S9wrXb/qKysxNSpU5GSkgKdTofevXtj69atcodFTQhz6sDGXDswMAcPTMzNAwvz9cDDPD4wNZb8Xil3AFR/kpKS8O9//xutW7eGJEl47733cOONN2Lnzp1IT0+XO7ygsHXrVrz11lvIyMiQO5Sgkp6eju+//97zWKnkR5s/lJWVoU+fPrjqqquwZs0axMTE4NChQ4iIiJA7tKCwdetWuFwuz+M9e/ZgyJAhGDVqlIxRBYcXXngBixYtwnvvvYf09HRs27YNEyZMQFhYGB566CG5w2vy7rnnHuzZswfvv/8+EhMT8cEHH2Dw4MHYt28fmjVrJnd41AQwpw5czLUDC3PwwMLcPPAwXw88zOMDU2PJ7wWJl1uatMjISLz00kuYOHGi3KE0eVVVVbjiiiuwcOFCzJkzB126dMG8efPkDqvJmz17NlatWoVdu3bJHUrQefLJJ7Fx40Zs2LBB7lAIwNSpU/HVV1/h0KFDEARB7nCatOuvvx5xcXF45513PG233HILdDodPvjgAxkja/osFgtCQkLwxRdfYPjw4Z72bt26YejQoZgzZ46M0VFTxpxafsy1Awtz8MDD3DzwMV+XH/P4wNOY8ntO59JEuVwuLF++HGazGZmZmXKHExSmTJmC4cOHY/DgwXKHEnQOHTqExMREtGjRAmPGjMHx48flDiko/N///R+6d++OUaNGITY2Fl27dsXbb78td1hByW6344MPPsDdd9/NhNwPevfujXXr1uHgwYMAgN9++w0///wzhg4dKnNkTZ/T6YTL5YJWq/Vq1+l0+Pnnn2WKipoy5tSBg7l24GEOHliYmwc25uuBgXl84GlM+T3vt2pifv/9d2RmZsJqtcJoNOLzzz9Hhw4d5A6ryVu+fDl27NgRkHM2NXW9evXC0qVL0bZtW+Tl5SErKwv9+vXDnj17EBISInd4TdrRo0exaNEiPProo/jnP/+JrVu34qGHHoJarca4cePkDi+orFq1CuXl5Rg/frzcoQSFJ598EiaTCe3atYMoinC5XHj22WcxZswYuUNr8kJCQpCZmYl//etfaN++PeLi4vDRRx9h06ZNaNWqldzhURPCnDqwMNcOPMzBAw9z88DGfD0wMI8PPI0pv+d0Lk2M3W7H8ePHUVFRgZUrV+I///kP1q9fz6S/AZ04cQLdu3fHd99955mfceDAgbzFVCbl5eVISUnBK6+8wluuG5harUb37t3xyy+/eNoeeughbN26FZs2bZIxsuBz7bXXQq1W48svv5Q7lKCwfPlyTJs2DS+99BLS09Oxa9cuTJ06Fa+88gq/pPrBkSNHcPfddyM7OxuiKOKKK65AmzZtsH37dvzxxx9yh0dNBHPqwMFcu3FgDi4/5uaBjfl6YGAeH5gaS37PkehNjFqt9lyp6datG7Zu3Yr58+fjrbfekjmypmv79u0oLCzEFVdc4WlzuVzIzs7GG2+8AZvNBlEUZYwwuISHh6NNmzY4fPiw3KE0eQkJCbWKCe3bt8enn34qU0TBKTc3F99//z0+++wzuUMJGtOmTcOTTz6J2267DQDQqVMn5Obm4vnnn2fy7QctW7bE+vXrYTabYTKZkJCQgNGjR6NFixZyh0ZNCHPqwMFcu3FgDi4/5uaBi/l64GAeH5gaS37POdGbOLfbDZvNJncYTdqgQYPw+++/Y9euXZ6f7t27Y8yYMdi1axeTej+rqqrCkSNHkJCQIHcoTV6fPn1w4MABr7aDBw8iJSVFpoiC05IlSxAbG+u1CAs1rOrqaigU3imUKIpwu90yRRScDAYDEhISUFZWhrVr1+LGG2+UOyRqwphTy4e5duPAHFx+zM0DF/P1wME8PrAFen7PkehNyPTp0zF06FAkJyejsrISH374IX766SesXbtW7tCatJCQEHTs2NGrzWAwICoqqlY71b/HH38cI0aMQEpKCk6fPo1Zs2ZBFEXcfvvtcofW5D3yyCPo3bs3nnvuOdx6663YsmULFi9ejMWLF8sdWtBwu91YsmQJxo0bB6WSf9L9ZcSIEXj22WeRnJyM9PR07Ny5E6+88gruvvtuuUMLCmvXroUkSWjbti0OHz6MadOmoV27dpgwYYLcoVETwZw6sDDXDkzMwQMPc/PAxHw9sDCPD0yNJb/nv+AmpLCwEGPHjkVeXh7CwsKQkZGBtWvXYsiQIXKHRtRgTp48idtvvx0lJSWIiYlB37598euvvyImJkbu0Jq8Hj164PPPP8f06dPxzDPPIC0tDfPmzeOiLH70/fff4/jx40z6/Oz111/HU089hcmTJ6OwsBCJiYm477778PTTT8sdWlCoqKjA9OnTcfLkSURGRuKWW27Bs88+C5VKJXdo1EQwpyY6P+bggYe5eWBivh5YmMcHpsaS33NhUSIiIiIiIiIiIiIiHzgnOhERERERERERERGRDyyiExERERERERERERH5wCI6EREREREREREREZEPLKITEREREREREREREfnAIjoRERERERERERERkQ8sohMRERERERERERER+cAiOhERERERERERERGRDyyiExFRvZs9eza6dOnieTx+/HjcdNNNssVDRERERBSMmJcTEdUPpdwBEBFR0zd//nxIkuR5PHDgQHTp0gXz5s2TLygiIiIioiDDvJyI6NKwiE5ERA0uLCxM7hCIiIiIiIIe83IiokvD6VyIiIKM2WzG2LFjYTQakZCQgLlz52LgwIGYOnUqAEAQBKxatcrrOeHh4Vi6dKnn8RNPPIE2bdpAr9ejRYsWeOqpp+BwOHwe8+zbRsePH4/169dj/vz5EAQBgiAgJycHrVq1wssvv+z1vF27dkEQBBw+fLg+XjoRERERUcBgXk5E1HiwiE5EFGSmTZuG9evX44svvsC3336Ln376CTt27LiofYSEhGDp0qXYt28f5s+fj7fffhuvvvrqBT13/vz5yMzMxL333ou8vDzk5eUhOTkZd999N5YsWeK17ZIlS9C/f3+0atXqouIjIiIiIgp0zMuJiBoPFtGJiIJIVVUV3nnnHbz88ssYNGgQOnXqhPfeew9Op/Oi9jNz5kz07t0bqampGDFiBB5//HF8/PHHF/TcsLAwqNVq6PV6xMfHIz4+HqIoYvz48Thw4AC2bNkCAHA4HPjwww9x9913X/TrJCIiIiIKZMzLiYgaF86JTkQURI4cOQK73Y5evXp52iIjI9G2bduL2s+KFSvw2muv4ciRI6iqqoLT6URoaOhlxZaYmIjhw4fj3XffRc+ePfHll1/CZrNh1KhRl7VfIiIiIqJAw7yciKhx4Uh0IiLyIggCJEnyajt7XsVNmzZhzJgxGDZsGL766ivs3LkTM2bMgN1uv+xj33PPPVi+fDksFguWLFmC0aNHQ6/XX/Z+iYiIiIgaG+blRESBgyPRiYiCSMuWLaFSqbB582YkJycDAMrKynDw4EEMGDAAABATE4O8vDzPcw4dOoTq6mrP419++QUpKSmYMWOGpy03N/ei4lCr1XC5XLXahw0bBoPBgEWLFuGbb75Bdnb2Re2XiIiIiKgxYF5ORNS4sIhORBREjEYjJk6ciGnTpiEqKgqxsbGYMWMGFIo/b0y6+uqr8cYbbyAzMxMulwtPPPEEVCqVp79169Y4fvw4li9fjh49euDrr7/G559/flFxpKamYvPmzTh27BiMRiMiIyOhUCg8czBOnz4drVu3RmZmZr29diIiIiKiQMG8nIioceF0LkREQeall15Cv379MGLECAwePBh9+/ZFt27dPP1z585F8+bN0a9fP9xxxx14/PHHvW7dvOGGG/DII4/ggQceQJcuXfDLL7/gqaeeuqgYHn/8cYiiiA4dOiAmJgbHjx/39E2cOBF2ux0TJky4/BdLRERERBSgmJcTETUegvTXCbaIiCjoDBw4EF26dMG8efPkDgUbNmzAoEGDcOLECcTFxckdDhERERGR3zAvJyIKTJzOhYiIAoLNZkNRURFmz56NUaNGMVEnIiIiIpIB83Iioto4nQsREQWEjz76CCkpKSgvL8eLL74odzhEREREREGJeTkRUW2czoWIiIiIiIiIiIiIyAeORCciIiIiIiIiIiIi8oFFdCIiIiIiIiIiIiIiH1hEJyIiIiIiIiIiIiLygUV0IiIiIiIiIiIiIiIfWEQnIiIiIiIiIiIiIvKBRXQiIiIiIiIiIiIiIh9YRCciIiIiIiIiIiIi8oFFdCIiIiIiIiIiIiIiH1hEJyIiIiIiIiIiIiLygUV0IiIiIiIiIiIiIiIfWEQnIiIiIiIiIiIiIvKBRXQiIiIiIiIiIiIiIh9YRCciIiIiIiIiIiIi8oFFdCIiIiIiIiIiIiIiH1hEJyL6n4EDB2LgwIFyh+GloKAAI0eORFRUFARBwLx58y5rf4Ig4IEHHjjvdkuXLoUgCDh27NhlHe+vLvQc//TTTxAEAT/99FO9Hj9Y1fV+BuLvOxEREdGlCMS8hnn8T/V6/GDFPJ4ocLCITkT1quaP/Nk/sbGxuOqqq7BmzRq5w2sQ1dXVmD17doMkio888gjWrl2L6dOn4/3338d1111X78cgAoDTp09j9uzZ2LVrl9yhEBERUQD55ZdfMHv2bJSXl9fqe+6557Bq1Sq/x1RfmMdTU8A8nsg/lHIHQERN0zPPPIO0tDRIkoSCggIsXboUw4YNw5dffonrr79e7vDqVXV1NbKysgCg3kcE/PDDD7jxxhvx+OOP1+t+5fLtt9/KHQL9z1/fi9OnTyMrKwupqano0qWLPEERERFRwPnll1+QlZWF8ePHIzw83Kvvueeew8iRI3HTTTfJEtvlYh5/4ZjHBw7m8UTyYBGdiBrE0KFD0b17d8/jiRMnIi4uDh999FGTK6I3pMLCwlpfVhqj6upq6PV6qNVquUOh/+F7QURERIHIarVCrVZDoWjcN84zj6eGwveCSB6N+68SETUa4eHh0Ol0UCq9r92ZzWY89thjaN68OTQaDdq2bYuXX34ZkiQBACwWC9q1a4d27drBYrF4nldaWoqEhAT07t0bLpfL53FrppfJzs7Gfffdh6ioKISGhmLs2LEoKys7b9yFhYWeCwBarRadO3fGe++95+k/duwYYmJiAABZWVmeKWxmz559zv0ePXoUo0aNQmRkJPR6Pa688kp8/fXXteKWJAkLFizw7Pdc3G435s+fj06dOkGr1SImJgbXXXcdtm3bVmvbVatWoWPHjtBoNEhPT8c333xz3nMBAAsXLkR6ejo0Gg0SExMxZcqUWrf2Dhw4EB07dsT27dvRv39/6PV6/POf//T0/XWUz8mTJ3HTTTfBYDAgNjYWjzzyCGw2W53H37x5M6677jqEhYVBr9djwIAB2Lhxo9c2lZWVmDp1KlJTU6HRaBAbG4shQ4Zgx44dPl/XypUrIQgC1q9fX6vvrbfegiAI2LNnDwAgPz8fEyZMQFJSEjQaDRISEnDjjTde0LyTNeddq9WiY8eO+PzzzzF+/HikpqZ6tvE1j+SxY8cgCAKWLl3qadu9ezfGjx+PFi1aQKvVIj4+HnfffTdKSkrOG8vZ78VPP/2EHj16AAAmTJjg+X1bunQpZs2aBZVKhaKiolr7mDRpEsLDw2G1Ws97PCIiIqofF5rrbN68GcOGDUNERAQMBgMyMjIwf/58T/+F5BGzZ8/GtGnTAABpaWmeHKEmLzGbzXjvvfc87ePHj/c899SpU7j77rsRFxfnyTnfffddrxhr8p7ly5dj5syZaNasGfR6PUwmE/N45vHM431gHk8kD45EJ6IGUVFRgeLiYkiShMLCQrz++uuoqqrCnXfe6dlGkiTccMMN+PHHHzFx4kR06dIFa9euxbRp03Dq1Cm8+uqr0Ol0eO+999CnTx/MmDEDr7zyCgBgypQpqKiowNKlSyGK4nnjeeCBBxAeHo7Zs2fjwIEDWLRoEXJzcz2JTl0sFgsGDhyIw4cP44EHHkBaWho++eQTjB8/HuXl5Xj44YcRExODRYsW4f7778fNN9+Mv/3tbwCAjIwMn7EUFBSgd+/eqK6uxkMPPYSoqCi89957uOGGG7By5UrcfPPN6N+/P95//33cddddGDJkCMaOHXve1zhx4kQsXboUQ4cOxT333AOn04kNGzbg119/9bor4Oeff8Znn32GyZMnIyQkBK+99hpuueUWHD9+HFFRUT73P3v2bGRlZWHw4MG4//77Pedx69at2LhxI1QqlWfbkpISDB06FLfddhvuvPNOxMXF+TzHgwYNwvHjx/HQQw8hMTER77//Pn744Yda2/7www8YOnQounXrhlmzZkGhUGDJkiW4+uqrsWHDBvTs2RMA8Pe//x0rV67EAw88gA4dOqCkpAQ///wz/vjjD1xxxRV1xjF8+HAYjUZ8/PHHGDBggFffihUrkJ6ejo4dOwIAbrnlFuzduxcPPvggUlNTUVhYiO+++w7Hjx/3SqL/6ttvv8Utt9yCDh064Pnnn0dJSYknib9U3333HY4ePYoJEyYgPj4ee/fuxeLFi7F37178+uuv5/3CVqN9+/Z45pln8PTTT2PSpEno168fAKB3797o27cvnnnmGaxYscJrMSu73Y6VK1filltugVarveTXQERERBfnQnKd7777Dtdffz0SEhLw8MMPIz4+Hn/88Qe++uorPPzww55tzpdH/O1vf8PBgwfx0Ucf4dVXX0V0dDQAICYmBu+//z7uuece9OzZE5MmTQIAtGzZEsCZfPfKK6/0LIYZExODNWvWYOLEiTCZTJg6darXa/rXv/4FtVqNxx9/HDabzWukLfN45vHM431jHk/kRxIRUT1asmSJBKDWj0ajkZYuXeq17apVqyQA0pw5c7zaR44cKQmCIB0+fNjTNn36dEmhUEjZ2dnSJ598IgGQ5s2bd8HxdOvWTbLb7Z72F198UQIgffHFF562AQMGSAMGDPA8njdvngRA+uCDDzxtdrtdyszMlIxGo2QymSRJkqSioiIJgDRr1qwLOkdTp06VAEgbNmzwtFVWVkppaWlSamqq5HK5PO0ApClTppx3nz/88IMEQHrooYdq9bndbq/9qdVqr3P722+/SQCk119/3dNWc95ycnIkSZKkwsJCSa1WS9dcc41XfG+88YYEQHr33Xc9bQMGDJAASG+++WatWHyd448//tjTZjabpVatWkkApB9//NHzGlq3bi1de+21Xq+nurpaSktLk4YMGeJpCwsLu6Bz9le33367FBsbKzmdTk9bXl6epFAopGeeeUaSJEkqKyuTAEgvvfTSRe+/S5cuUkJCglReXu5p+/bbbyUAUkpKiqftxx9/9HrtNXJyciQA0pIlSzxt1dXVtY7z0UcfSQCk7OxsT9tf309Jqv1ebN26tdb+a2RmZkq9evXyavvss8/qjJOIiIga1vlyHafTKaWlpUkpKSlSWVmZV99f86i/qiuPeOmll2rlETUMBoM0bty4Wu0TJ06UEhISpOLiYq/22267TQoLC/McuybvadGiRa14mMczj79QzOOZxxP5A6dzIaIGsWDBAnz33Xf47rvv8MEHH+Cqq67CPffcg88++8yzzerVqyGKIh566CGv5z722GOQJAlr1qzxtM2ePRvp6ekYN24cJk+ejAEDBtR63rlMmjTJa4TF/fffD6VSidWrV/t8zurVqxEfH4/bb7/d06ZSqfDQQw+hqqqqzlsGL8Tq1avRs2dP9O3b19NmNBoxadIkHDt2DPv27bvofX766acQBAGzZs2q1ffXUQyDBw/2jBICzoy2CQ0NxdGjR33u//vvv4fdbsfUqVO95qe89957ERoa6nULKwBoNBpMmDDhvHGvXr0aCQkJGDlypKdNr9d7RjPV2LVrFw4dOoQ77rgDJSUlKC4uRnFxMcxmMwYNGoTs7Gy43W4AZ6YO2rx5M06fPn3e459t9OjRKCws9Lr9cuXKlXC73Rg9ejQAQKfTQa1W46effrqg24hr5OXlYdeuXRg3bhzCwsI87UOGDEGHDh0uKs6z6XQ6z/9brVYUFxfjyiuvBIBz3vZ6scaOHYvNmzfjyJEjnrZly5ahefPmtUb8EBERUcM6X66zc+dO5OTkYOrUqbXm5D47L2yoPEKSJHz66acYMWIEJEny5G3FxcW49tprUVFRUWv/48aN84rnbMzj/8Q8vm7M431jHk9Uf1hEJ6IG0bNnTwwePBiDBw/GmDFj8PXXX6NDhw544IEHYLfbAQC5ublITExESEiI13Pbt2/v6a+hVqvx7rvvIicnB5WVlViyZMkF3+IGAK1bt/Z6bDQakZCQcM7573Jzc9G6detaixrVFd/FyM3NRdu2bWu1X85+jxw5gsTERERGRp532+Tk5FptERER50wma2L6a9xqtRotWrSoFXOzZs0uaMGb3NxctGrVqtZ7+dfjHDp0CMCZL1gxMTFeP//5z39gs9lQUVEBAHjxxRexZ88eNG/eHD179sTs2bPP+cWiRs0cjStWrPC0rVixAl26dEGbNm0AnPlS8cILL2DNmjWIi4tD//798eKLLyI/P/+8rxOo/XtY12u9GKWlpXj44YcRFxcHnU6HmJgYpKWlAYDnfNSH0aNHQ6PRYNmyZZ59f/XVVxgzZsxF/TskIiKiy3e+XKemWFYzhYUvDZVHFBUVoby8HIsXL66Vt9UUZwsLC72eU3PcujCP/xPz+Loxj/eNeTxR/WERnYj8QqFQ4KqrrkJeXp4nkbpYa9euBXDmSv2l7oPgcw556X+LudYHXyOJLlXN6JSXXnrJc4fDX3+MRiMA4NZbb8XRo0fx+uuvIzExES+99BLS09O97myoi0ajwU033YTPP/8cTqcTp06dwsaNGz2jV2pMnToVBw8exPPPPw+tVounnnoK7du3x86dO+vltfpKZutaQPfWW2/F22+/jb///e/47LPP8O2333oWl6o5Z/UhIiIC119/vSf5XrlyJWw2m9caB0REROQfl5rr1LWfhsgjap575513+szb+vTp4/Wc+s4dmyrm8XVjHu8b83ii+sMiOhH5jdPpBABUVVUBAFJSUnD69GlUVlZ6bbd//35Pf43du3fjmWeewYQJE9C1a1fcc889F3WF/q9F96qqKuTl5Z1zAZmUlBQcOnSoVhLz1/gu9gp+SkoKDhw4UKu9rtd9oVq2bInTp0+jtLT0op97IWpi+mvcdrsdOTk5lxRzzX6PHDlSK/H/63FqblsNDQ313OHw15+zb/NNSEjA5MmTsWrVKuTk5CAqKgrPPvvseeMZPXo0iouLsW7dOnzyySeQJKlW8l0Tz2OPPYZvv/0We/bsgd1ux9y5c8/5OoHav4d1vdaIiAgAQHl5uVf7X0cJlZWVYd26dXjyySeRlZWFm2++GUOGDEGLFi3O+zrrcr7f47Fjx+LgwYPYunUrli1bhq5duyI9Pf2SjkVERESX51y5Tk3etGfPHp/Pv5g84lw5Ql19MTExCAkJgcvl8pm3xcbGXvBrZR5/eZjHe2Mezzye6FKxiE5EfuFwOPDtt99CrVZ7bnccNmwYXC4X3njjDa9tX331VQiCgKFDh3qeO378eCQmJmL+/PlYunQpCgoK8Mgjj1zw8RcvXgyHw+F5vGjRIjidTs8x6jJs2DDk5+d73RbodDrx+uuvw2g0euaQ0+v1AGonS+fa75YtW7Bp0yZPm9lsxuLFi5GamnpJc+vdcsstkCQJWVlZtfrqY2TK4MGDoVar8dprr3nt75133kFFRQWGDx9+SfsdNmwYTp8+jZUrV3raqqursXjxYq/tunXrhpYtW+Lll1/2XIQ5W1FREYAzozz+enElNjYWiYmJsNls541n8ODBiIyMxIoVK7BixQr07NnT6/bi6upqWK1Wr+e0bNkSISEh59x/QkICunTpgvfee88rvu+++67W3JkpKSkQRRHZ2dle7QsXLvR6XDMS6a/v77x58877OutiMBgA+P49Hjp0KKKjo/HCCy9g/fr1HL1CREQkgwvJda644gqkpaVh3rx5tf6u1+QNF5NHnCtHMBgMtdpFUcQtt9yCTz/9tM5Cfk3edqGYx18e5vF/xsY8nnk80eVQyh0AETVNa9as8YzIKCwsxIcffohDhw7hySefRGhoKABgxIgRuOqqqzBjxgwcO3YMnTt3xrfffosvvvgCU6dO9YxamDNnDnbt2oV169YhJCQEGRkZePrppzFz5kyMHDkSw4YNO288drsdgwYNwq233ooDBw5g4cKF6Nu3L2644Qafz5k0aRLeeustjB8/Htu3b0dqaipWrlyJjRs3Yt68eZ653HU6HTp06IAVK1agTZs2iIyMRMeOHX3OQ/nkk0/io48+wtChQ/HQQw8hMjIS7733HnJycvDpp5/WmrvxQlx11VW466678Nprr+HQoUO47rrr4Ha7sWHDBlx11VV44IEHLnqfZ4uJicH06dORlZWF6667DjfccIPnPPbo0eOSE7F7770Xb7zxBsaOHYvt27cjISEB77//vucLTQ2FQoH//Oc/GDp0KNLT0zFhwgQ0a9YMp06dwo8//ojQ0FB8+eWXqKysRFJSEkaOHInOnTvDaDTi+++/x9atW885wqSGSqXC3/72Nyxfvhxmsxkvv/yyV//Bgwc9v0cdOnSAUqnE559/joKCAtx2223n3Pfzzz+P4cOHo2/fvrj77rtRWlqK119/Henp6V5fKMLCwjBq1Ci8/vrrEAQBLVu2xFdffVVr7tDQ0FDPXI4OhwPNmjXDt99+i5ycnPO+zrq0bNkS4eHhePPNNxESEgKDwYBevXp5vnyoVCrcdttteOONNyCKotdCXUREROQfF5LrKBQKLFq0CCNGjECXLl0wYcIEJCQkYP/+/di7dy/Wrl17UXlEt27dAAAzZszAbbfdBpVKhREjRsBgMKBbt274/vvv8corryAxMRFpaWno1asX/v3vf+PHH39Er169cO+996JDhw4oLS3Fjh078P3331/UqGvm8czjmcefG/N4Ij+RiIjq0ZIlSyQAXj9arVbq0qWLtGjRIsntdnttX1lZKT3yyCNSYmKipFKppNatW0svvfSSZ7vt27dLSqVSevDBB72e53Q6pR49ekiJiYlSWVnZeeNZv369NGnSJCkiIkIyGo3SmDFjpJKSEq9tBwwYIA0YMMCrraCgQJowYYIUHR0tqdVqqVOnTtKSJUtqHeeXX36RunXrJqnVagmANGvWrHOepyNHjkgjR46UwsPDJa1WK/Xs2VP66quvam0HQJoyZco591XD6XRKL730ktSuXTtJrVZLMTEx0tChQ6Xt27efd38pKSnSuHHjPI9rzltOTo7Xdm+88YbUrl07SaVSSXFxcdL9999f6/wPGDBASk9PrzPGus5xbm6udMMNN0h6vV6Kjo6WHn74Yembb76RAEg//vij17Y7d+6U/va3v0lRUVGSRqORUlJSpFtvvVVat26dJEmSZLPZpGnTpkmdO3eWQkJCJIPBIHXu3FlauHDhuU/eWb777jsJgCQIgnTixAmvvuLiYmnKlClSu3btJIPBIIWFhUm9evWSPv744wva96effiq1b99e0mg0UocOHaTPPvtMGjdunJSSkuK1XVFRkXTLLbdIer1eioiIkO677z5pz549EgCv37+TJ09KN998sxQeHi6FhYVJo0aNkk6fPl3rd7Cu97Ou9+KLL76QOnToICmVylrHkiRJ2rJliwRAuuaaay7o9RIREVH9uphc5+eff5aGDBni2S4jI0N6/fXXPf0XmkdIkiT961//kpo1ayYpFAqvnGL//v1S//79JZ1OJwHwyicLCgqkKVOmSM2bN5dUKpUUHx8vDRo0SFq8eLFnmx9//FECIH3yySe14mcezzyeeTzzeKJAIkhSPa5AQUQUYJYuXYoJEyZg69at6N69u9zhENUyfvx4/PTTTzh27JjcoZzXb7/9hi5duuC///0v7rrrLrnDISIioiaMeTwFOubxRMGFc6ITERHRBXn77bdhNBrxt7/9Te5QiIiIiIjoAjGPJ7p8nBOdiIiIzunLL7/Evn37sHjxYjzwwAOexYuIiIiIiChwMY8nqj8sohMREdE5PfjggygoKMCwYcOQlZUldzhERERERHQBmMcT1R/OiU5ERERERERERERE5APnRCciIiIiIiIiIiIi8oFFdCIiIiIiIiIiIiIiHzgneh3cbjdOnz6NkJAQCIIgdzhERERE1IRIkoTKykokJiZCoeCYlvNhbk5EREREDeVCc3MW0etw+vRpNG/eXO4wiIiIiKgJO3HiBJKSkuQOI+AxNyciIiKihna+3JxF9DqEhIQAOHPyQkNDZY6GiIiIiJoSk8mE5s2be3JOOjfm5kRERETUUC40N2cRvQ41t4mGhoYyUSciIiKiBsGpSS4Mc3MiIiIiamjny805CSMRERERERERERERkQ8sohMRERERERERERER+cAiOhERERERERERERGRD5wTnYiIiIiIiIiIiChIuVwuOBwOucNoECqVCqIoXvZ+WEQnIiIiIiIiIiIiCjKSJCE/Px/l5eVyh9KgwsPDER8ff97FQ8+FRXQiavRcLhd2796N0tJSREZGIiMjo16uMhIRERERERERNVU1BfTY2Fjo9frLKjIHIkmSUF1djcLCQgBAQkLCJe+LRXSiesJCrjyys7OxcOFC5Ofne9ri4+MxefJk9O/fX8bIiIiIiKi+uGx2uO12SJIEhVoFpVYrd0hBzWV3wF5VjfLDJ+AwWxDeMgnayDCojXq5QyMiogvkcrk8BfSoqCi5w2kwOp0OAFBYWIjY2NhLrtWxiE5UD1jIlUd2djZmzZqFzMxMPPXUU0hLS0NOTg6WLVuGWbNmISsri+efiIiIqBGTJAmOykqUbP8NttIyAIDSaEBU187QREZAoeSgFX9z2R0o2Z+DnNUbPW15m/dAHx+NNrdcDU2IQcboiIjoQtXMga7XN/0LoDWv0eFwXHIRXVGfAREFo5pCbosWLbBgwQKsXr0aCxYsQIsWLTBr1ixkZ2fLHWKT5HK5sHDhQmRmZmLOnDlIT0+HXq9Heno65syZg8zMTCxatAgul0vuUImIiIjoEjmrq5H/00ZPAR0AnFVmFGz4BY6qKhkjC172ymqvAnqN6vxiFGzbBzfzbyKiRqWpTeFSl/p4jSyiE10GFnLls3v3buTn52PMmDFQKLw/yhQKBcaMGYO8vDzs3r1bpgiJiIiI6HJVn8qH+38j5f6qfO9+n33UcMoO5vrsK9i5Hw6z1Y/REBER+UejKKIvWLAAqamp0Gq16NWrF7Zs2XLO7cvLyzFlyhQkJCRAo9GgTZs2WL16tZ+ipWDCQq58SktLAQBpaWl19te012xHRERE9YO5OfmL2+WCtbDIZ7+trBxup9OPEREA2KstPvvcdicgSX6MhoiIGrPZs2ejS5cunsfjx4/HTTfdJFs85xLwRfQVK1bg0UcfxaxZs7Bjxw507twZ1157rWdV1b+y2+0YMmQIjh07hpUrV+LAgQN4++230axZMz9HTsGAhVz5REZGAgBycnLq7K9pr9mOiIiILh9zc/InQaGA0uB7nlalVgNBEfBfaZuciBZJPvuMzWKhUHPpNSIiujTz58/H0qVLPY8HDhyIqVOnyhbP2QI+43jllVdw7733YsKECejQoQPefPNN6PV6vPvuu3Vu/+6776K0tBSrVq1Cnz59kJqaigEDBqBz585+jpyCAQu58snIyEB8fDyWLVsGt9vt1ed2u7Fs2TIkJCQgIyNDpgiJiIiaHubm5E+CICCkRarP/rB2bSBqNP4LiAAAuugI6GIiancIAlIG9YRKp/V/UERE1CSEhYUhPDxc7jDqFNBFdLvdju3bt2Pw4MGeNoVCgcGDB2PTpk11Puf//u//kJmZiSlTpiAuLg4dO3bEc889xzmpqUGwkCsfURQxefJkbNq0CTNnzsTevXtRXV2NvXv3YubMmdi0aRPuv//+S151mYiIiLwxNyc5KPU6RHfrCvxlQbCQlmnQRkfJFFVwU4fo0XbUEMR1bw+F6syoc0NCNDrcOazu4joRETVKZrMZY8eOhdFoREJCAubOnes1MlwQBKxatcrrOeHh4V4jyZ944gm0adMGer0eLVq0wFNPPQXHOdYzOXs6l/Hjx2P9+vWYP38+BEGAIAjIyclBq1at8PLLL3s9b9euXRAEAYcPH66Pl16ngL7Pqri4GC6XC3FxcV7tcXFx2L9/f53POXr0KH744QeMGTMGq1evxuHDhzF58mQ4HA7MmjWrzufYbDbYbDbPY5PJVH8vgpq0mkLurFmzMHPmTIwZMwZpaWnIycnBsmXLsGnTJmRlZbGQ20D69++PrKwsLFy4EFOmTPG0JyQkICsrC/3795cxOiIioqaFuTnJQaFSQZ+UiGYxkbCXV0ByuaGJCIdCo4aoVssdXtDShBqQPLAHEnp2AiQ3FGoVR6ATETUx06ZNw/r16/HFF18gNjYW//znP7Fjxw6vOczPJyQkBEuXLkViYiJ+//133HvvvQgJCcE//vGP8z53/vz5OHjwIDp27IhnnnkGABATE4O7774bS5YsweOPP+7ZdsmSJejfvz9atWp10a/zQgV0Ef1SuN1uxMbGYvHixRBFEd26dcOpU6fw0ksv+UzUn3/+eWRlZfk5UmoqWMiVV//+/dGnTx/s3r0bpaWliIyMREZGBi9cEBERBQDm5lQfFEoRCqUBKoNB7lDoLAqlCE0o3xMioqaoqqoK77zzDj744AMMGjQIAPDee+8hKcn3uhh1mTlzpuf/U1NT8fjjj2P58uUXVEQPCwuDWq2GXq9HfHy8p338+PF4+umnsWXLFvTs2RMOhwMffvhhrdHp9S2gi+jR0dEQRREFBQVe7QUFBV4n72wJCQlQqVReBbT27dsjPz8fdrsd6jpGK0yfPh2PPvqo57HJZELz5s3r6VVQMGAhV16iKKJr165yh0FERNSkMTcnIiIiCg5HjhyB3W5Hr169PG2RkZFo27btRe1nxYoVeO2113DkyBFUVVXB6XQiNDT0smJLTEzE8OHD8e6776Jnz5748ssvYbPZMGrUqMva7/kE9JzoarUa3bp1w7p16zxtbrcb69atQ2ZmZp3P6dOnDw4fPuw1P/XBgweRkJBQZ5IOABqNBqGhoV4/RBerppA7aNAgdO3alQV0IiIialKYmxMRERFRDUEQIEmSV9vZ851v2rQJY8aMwbBhw/DVV19h586dmDFjBux2+2Uf+5577sHy5cthsViwZMkSjB49Gnq9/rL3ey4BXUQHgEcffRRvv/023nvvPfzxxx+4//77YTabMWHCBADA2LFjMX36dM/2999/P0pLS/Hwww/j4MGD+Prrr/Hcc895TbNBREREREQXj7k5ERERUdPXsmVLqFQqbN682dNWVlaGgwcPeh7HxMQgLy/P8/jQoUOorq72PP7ll1+QkpKCGTNmoHv37mjdujVyc3MvKg61Wl3ngvTDhg2DwWDAokWL8M033+Duu+++qP1eioCezgUARo8ejaKiIjz99NPIz89Hly5d8M0333gWNDp+/DgUij+vBTRv3hxr167FI488goyMDDRr1gwPP/wwnnjiCbleAhERERFRk8DcnIiIiKjpMxqNmDhxIqZNm4aoqCjExsZixowZXnne1VdfjTfeeAOZmZlwuVx44oknoFKpPP2tW7fG8ePHsXz5cvTo0QNff/01Pv/884uKIzU1FZs3b8axY8dgNBoRGRkJhUIBURQxfvx4TJ8+Ha1bt/Z5V2R9CvgiOgA88MADeOCBB+rs++mnn2q1ZWZm4tdff23gqIiIiIiIgg9zcyIiIqKm76WXXkJVVRVGjBiBkJAQPPbYY6ioqPD0z507FxMmTEC/fv2QmJiI+fPnY/v27Z7+G264AY888ggeeOAB2Gw2DB8+HE899RRmz559wTE8/vjjGDduHDp06ACLxYKcnBykpqYCACZOnIjnnnvOc0dkQxOkv05eQzCZTAgLC0NFRQXnYCQiIiKiesVc8+LwfBERERHVP6vVipycHKSlpUGr1V7QcwYOHIguXbpg3rx5DRvcBdiwYQMGDRqEEydOeO6K9OVcr/VCc81GMRKdiIiIiIiIiIiIiIKbzWZDUVERZs+ejVGjRp23gF5fAn5hUSIiIiIiIiIiIiKijz76CCkpKSgvL8eLL77ot+NyJDoRERERERERERERnVNd69/42/jx4zF+/Hi/H5cj0YmIiIiIiIiIiIiIfGARnYiIiIiIiIiIiIjIBxbRiYiIiIiIiIiIiIh8YBGdiIiIiIiIiIiIiMgHFtGJiIiIiIiIiIiIiHxgEZ2IiIiIiIiIiIiIyAcW0YmIiIiIiIiIiIiIfGARnYiIiIiIiIiIiIgahUWLFiEjIwOhoaEIDQ1FZmYm1qxZ06DHZBGdiIiIiIiIiIiIiC6J2+mEy2qB01wFl9UCt9PZoMdLSkrCv//9b2zfvh3btm3D1VdfjRtvvBF79+5tsGMqG2zPRERERERERERERNRkuex2mE/mwFlV6WlTGkNhSEqFqFY3yDFHjBjh9fjZZ5/FokWL8OuvvyI9Pb1BjsmR6ERERERERERERER0UdxOZ60COgA4q0wwnzzW4CPSAcDlcmH58uUwm83IzMxssONwJDoRERERERERERERXRTJ6ahVQK/hrDJBcjoAZcOUn3///XdkZmbCarXCaDTi888/R4cOHRrkWABHohMRERERERERERHRRZJcrnP3u8/dfznatm2LXbt2YfPmzbj//vsxbtw47Nu3r8GOx5HoRERERERERERERHRRBFE8d7/i3P2XQ61Wo1WrVgCAbt26YevWrZg/fz7eeuutBjkeR6ITERERERERERER0UURlCoojaF19imNoRCUKr/F4na7YbPZGmz/HIlORERERERERERERBdFoVTCkJQK88ljcFaZPO1KYygMSalQNNB86NOnT8fQoUORnJyMyspKfPjhh/jpp5+wdu3aBjkewCI6EREREREREREREV0CUa2GMbkFJKcDktsFQSFCUKoarIAOAIWFhRg7dizy8vIQFhaGjIwMrF27FkOGDGmwY7KITkRERERERERERESXRKFUAg1YNP+rd955x2/HqsE50YmIiIiIiIiIiIiIfGARnYiIiIiIiIiIiIjIBxbRiYiIiIiIiIiIiIh8YBGdiIiIiIiIiIiIiMgHFtGJiIiIiIiIiIiIiHxgEZ2IiIiIiIiIiIiIyAcW0YmIiIiIiIiIiIiIfGARnYiIiIiIiIiIiIjIBxbRiYiIiIiIiIiIiIh8YBGdiIiIiIiIiIiIiMiHRlFEX7BgAVJTU6HVatGrVy9s2bLF57ZLly6FIAheP1qt1o/REhERERE1XczNiYiIiChQ/Pvf/4YgCJg6dWqDHifgi+grVqzAo48+ilmzZmHHjh3o3Lkzrr32WhQWFvp8TmhoKPLy8jw/ubm5foyYiIiIiKhpYm5ORERERH/lstthN1XCVloGR2UVXHa7X467detWvPXWW8jIyGjwYwV8Ef2VV17BvffeiwkTJqBDhw548803odfr8e677/p8jiAIiI+P9/zExcX5MWIiIiIioqaJuTkRERERnc1ZbUHR5u04/d2PyPtxA059+wOKNm+Hs9rSoMetqqrCmDFj8PbbbyMiIqJBjwUEeBHdbrdj+/btGDx4sKdNoVBg8ODB2LRpk8/nVVVVISUlBc2bN8eNN96IvXv3nvM4NpsNJpPJ64eIiIiIiP7E3JyIiIiIzuay21G8fReshUVe7dbCIhRv39WgI9KnTJmC4cOHe+WmDSmgi+jFxcVwuVy1RqvExcUhPz+/zue0bdsW7777Lr744gt88MEHcLvd6N27N06ePOnzOM8//zzCwsI8P82bN6/X10FERERE1NgxNyciIiKis7mstloF9BrWwiK4rLYGOe7y5cuxY8cOPP/88w2y/7oEdBH9UmRmZmLs2LHo0qULBgwYgM8++wwxMTF46623fD5n+vTpqKio8PycOHHCjxETERERETVNzM2JiIiImi7J6bys/ktx4sQJPPzww1i2bJlfF6xX+u1IlyA6OhqiKKKgoMCrvaCgAPHx8Re0D5VKha5du+Lw4cM+t9FoNNBoNJcVKxERERFRU8bcnIiIiIjOJijPXVo+X/+l2L59OwoLC3HFFVd42lwuF7Kzs/HGG2/AZrNBFMV6P25Aj0RXq9Xo1q0b1q1b52lzu91Yt24dMjMzL2gfLpcLv//+OxISEhoqTCIiIiKiJo+5ORERERGdTdRqoI2NqbNPGxsDUVv/AyMGDRqE33//Hbt27fL8dO/eHWPGjMGuXbsapIAOBPhIdAB49NFHMW7cOHTv3h09e/bEvHnzYDabMWHCBADA2LFj0axZM88cOM888wyuvPJKtGrVCuXl5XjppZeQm5uLe+65R86XQURERETU6DE3JyIiIqIaolqN6G5dai0uqo2NQXS3LhDV6no/ZkhICDp27OjVZjAYEBUVVau9PgV8EX306NEoKirC008/jfz8fHTp0gXffPONZ0Gj48ePQ6H4c0B9WVkZ7r33XuTn5yMiIgLdunXDL7/8gg4dOsj1EoiIiIiImgTm5kRERER0NqVeh5he3eCy2iA5nRCUSohaTYMU0OUkSJIkyR1EoDGZTAgLC0NFRQVCQ0PlDoeIiIiImhDmmheH54uIiIio/lmtVuTk5CAtLc2vC3TK4Vyv9UJzzYCeE52IiIiIiIiIiIiISE4sohMRERERERERERER+RDwc6ITEZ2Py+XC7t27UVpaisjISGRkZDTYasxERERERERERBRcWEQnokYtOzsbCxcuRH5+vqctPj4ekydPRv/+/WWMjIiIiIioaZIkCY6qajjMVridLqiMOqgMWogqldyhERERNQgW0Ymo0crOzsasWbNw5ZVXYvTo0dBqtbBardiyZQtmzZqFrKwsFtKJiIiIiOqR5HbDXFCKQ5/9AHulGQAgKATE9+qEhB7pUOmb9uJ0REQUnFhEJ6JGyeVyYeHChWjTpg2OHj2KTZs2efri4uLQpk0bLFq0CH369OHULkRERERE9cReacb+j76By+7wtEluCXmbdkMbHoLYzm1kjI6IiKhhcGFRImqUdu/ejfz8fBw4cAAtW7bEggULsHr1aixYsAAtW7bEgQMHkJeXh927d8sdKhERERFRk1FxLM+rgH62Uxt3wV5V7eeIiIiIGh6L6ETUKBUXFwMAevXqhTlz5iA9PR16vR7p6emYM2cOevXq5bUdERERERFdvuqCUp99dpMZbofTj9EQERH5B4voRNQolZeXAwD69esHhcL7o0yhUKBv375e2xERERER0eXTxYT77NOEGf0XCBERkR+xiE5EjVJ4eDgAYMOGDXC73V59brcbP//8s9d2RERERER0+QxxURA16jr74nukQ6FS+TkiIiKihsciOhE1StHR0QCALVu2YObMmdi7dy+qq6uxd+9ezJw5E1u2bPHajoiIiIiILp+o16DliP7QRoR62hRKEYmZGdCEh0Cpq7vATkREVF9mz54NQRC8ftq1a9egx1Q26N6JiBpIRkYG4uPjERYWhqNHj2LKlCmevoSEBLRp0wYmkwkZGRkyRklERERE1LSo9TpY3KWI694emlAjJJcbUAioPFUEQ1wkFKIod4hERORnDosNzmoLXDYHRI0aSr0WKp2mQY+Znp6O77//3vNYqWzYMjeL6ETUKImiiMmTJ2PWrFm48sorMXr0aGg0GthsNmzZsgW//vorsrKyIDKJJyIiIiKqN6JahbDUZnBUWVCecwqOaivC0xKR0KMD1Ea93OEREZGf2UxVOLp6I0zHTnvawtISkTa0DzShDbdWhlKpRHx8fIPtv9bx/HYkIqJ61r9/f2RlZWHhwoXYtGmTpz0hIQFZWVno37+/jNERERERETVNoloFMVKF+MjQ829MRERNlsNiq1VAB4CKnNPIWbMRLW8Y2GAj0g8dOoTExERotVpkZmbi+eefR3JycoMcC2ARnYgauf79+6NPnz7YvXs3SktLERkZiYyMDI5AJyIiIiIiIiJqQM5qS60Ceo2KnNNwVlsapIjeq1cvLF26FG3btkVeXh6ysrLQr18/7NmzByEhIfV+PIBFdCJqAkRRRNeuXeUOg4iIiIiIiIgoaLhsjsvqv1RDhw71/H9GRgZ69eqFlJQUfPzxx5g4cWKDHFPRIHslIiIiIiIiIiIioiZL1Kguq7++hIeHo02bNjh8+HCDHYNFdCIiIiIiIiIiIiK6KEq9DmFpiXX2haUlQqnX+SWOqqoqHDlyBAkJCQ12DBbRiYiIiIiIiIiIiOiiqHQapA3tU6uQHpaWiLShfRtsUdHHH38c69evx7Fjx/DLL7/g5ptvhiiKuP322xvkeADnRCciIiIiIiIiIiKiS6AJNaLlDQPhrLbAZXNA1Kig1OsarIAOACdPnsTtt9+OkpISxMTEoG/fvvj1118RExPTYMdkEZ2IiIiIiIiIiIiILolKp2nQovlfLV++3G/HqsHpXIiIiIiIiIiIiIiIfOBIdCJq9FwuF3bv3o3S0lJERkYiIyMDoijKHRYRERERUZPlsNjgtFghuVwQNRqoQ/QQBEHusIiIiBoEi+hE1KhlZ2dj4cKFyM/P97TFx8dj8uTJ6N+/v4yRERERERE1TZbSChxd/TOqThYCAJR6LVIG9UB4y+ZQav13Oz8REZG/cDoXImq0srOzMWvWLLRo0QILFizA6tWrsWDBArRo0QKzZs1Cdna23CESERERETUpNlMV/vjwG08BHQCc1VYc+XIDKs9qIyIiako4Ep2IGiWXy4WFCxciMzMTM2bMwNtvv42TJ08iKSkJM2bMwLPPPotFixahT58+nNqlgVksFrz11lue83/fffdBp9PJHRYRERERNQBzXjFEjRotr+8HpVYNt8sNhVJE0Z7DOPHjVhgToqEyMBeUg73aCofFDpfdCaVWDU2IDqKS34WIiOoDi+hE1Cjt3r0b+fn5iI2NxfDhwz3t27Ztw6pVq5CRkYG8vDzs3r0bXbt2lTHSpm3GjBnYuHGj53HN+e/Tpw+effZZGSMjIiIiooZgq6pGqxsHIGfNRpjzigEAolaNpP5XIGxgAtxOl8wRBqeq4gpUnCxGzi97YakwIzI1DmmZHaCPCoU2RC93eEREjR6ncyGiRqm0tBTAmWK6SqXCHXfcgQ8++AB33HEHVCoVdu/e7bUd1b+aAnpd53/jxo2YMWOG3CESERERUT0LT22GAyu+9RTQAcBltSP321/hdrogqDjy2d+qyypx9Oc92Pjmlzi9+yjKcgtwZP1u/PTqp6gsKIPb5ZY7RCKiRo9FdCJqlIxGIwBAFEV8/fXXmDRpEpKSkjBp0iR8/fXXnilcaraj+mWxWDwF9LrOf00h3WKxyB0qEREREdWjqrwiOMx153gnN+yE2+70c0RkN1uxf+3WWu1OmwO/rdyA6rJKGaIiImpaWEQnokapZgqR+Ph4KJXeM1MplUrExcV5bUf166233gIAjBo1Cmq12qtPrVZj5MiRXtsRERERUdNQdcr34qHW0gpIHPXsd8VH8wCp7r7SY/lw2hz+DYiIqAninOhE1CidPn0aAHDq1CnMmDEDPXv2hEajgc1mw5YtWzz9Nf+l+nXy5EkAwLBhw+rsHzZsGD766CPPdkRERETUNOgiw3z2qQw6QPBjMAQAEHjSiYgaXKMYib5gwQKkpqZCq9WiV69e2LJlywU9b/ny5RAEATfddFPDBkhEfpeUlAQAaN++PbZs2YL58+fjxRdfxPz587Flyxa0a9fOazuqXzXndfXq1XX217Tz/BMRNT3MzYmCW2haMwjKuuc9j++RDpWRi1j6W3TLBJ99EcmxUGlUfoyGiMg/Tp06hTvvvBNRUVHQ6XTo1KkTtm3b1mDHC/gi+ooVK/Doo49i1qxZ2LFjBzp37oxrr70WhYW+byEDgGPHjuHxxx9Hv379/BQpEfnTfffdBwD4448/IAjeIy8EQcD+/fu9tqP6VXNeP/nkE9jtdq8+u92OlStXem1HRERNA3NzIlKoVWh7yyCIGu8p/aI7tkJEmxQo1SzY+ptSr0G7a7vXahdVIrreNhC6CK4TRUQNy2a2wpRfipKcPJjyS2EzWxv0eGVlZejTpw9UKhXWrFmDffv2Ye7cuYiIiGiwYwb8dC6vvPIK7r33XkyYMAEA8Oabb+Lrr7/Gu+++iyeffLLO57hcLowZMwZZWVnYsGEDysvL/RgxEfmDWq2GUqmE0+mEy+XCkCFDMGrUKHzyySf4/vvvAZyZG/2v83VT/dDpdOjTpw82btyI4cOHY+TIkRg2bBhWr16NlStXwuFwoE+fPtDpdHKHSkRE9Yi5ORFZCkpQsv8Y2t9+HRzVFrhsDmgjQ2EtrcDhL/+fvTuPj6o6/wf+uffOPpNtsickJGE3EkDWEAkuuC/YVsQ2Vipaq2CtSxepLEah1LZa+q0spdX6q1BRWhfccEEhilEQwUDYIRAgZF8mmWS2e+f3B83ImAQCzMxNMp/36+XL5JyTuQ+TZHLmOec+ZyOGTrsaWpNB7TDDijkmAlmThiNuQAr2f7wdDlsr4gakYED+cBijLRClzu8cICIKhNb6Zmx96UNU7Sn3tSUO64+xP54CkzUiKNd8+umnkZaWhn/+85++tszMzKBcq12PTqK7XC5s27YNc+bM8bWJoogpU6aguLi4y6978sknkZCQgLvvvhuffvppKEIlohDbsWMHPB4PIiIi0NzcjA8//BAffvihr7+9fceOHRg9erSKkfZdixYtwuOPP47Nmzfj5Zdfxssvv+zry8vLw6JFi1SMjoiIAo1zcyICgKayCtSVHkJd6SFojAZIei2cjc2+ftnpYhJdBZa4KGhNeoxJtkLxKNDotdBZjNDoenTah4h6Oafd0SGBDgBVe45i60sfYcI910FvDvzfhHXr1uGaa67BtGnTsGnTJqSmpmLWrFn46U9/GvBrtevRr6a1tbWQZRmJiYl+7YmJib5SDd/12Wef4fnnn8eOHTu6fR2n0wmn0+n73GaznVe8RBQ67b/jTzzxBC666CL87W9/w/Hjx9GvXz/87Gc/w+7du/Hoo48yiR5kixYtQltbW4fnnzvQiYj6Hs7NiQgAtJZv53meNgc8bd/esi8ZeBeomvQmA/RcwCCiEHI2t3ZIoLer2nMUzubWoCTRDx8+jOXLl+ORRx7Bb3/7W2zduhUPPvggdDodZsyYEfDrAT08iX6umpub8eMf/xh///vfERcX1+2vW7x4MQoLC4MYGREFiyAIMBqNeOihh9QOJWzx+Scios5wbk7UN0VlpeL4p9sBr7dDX/yIwRBZE52IKGy425xn6Xedsf98KYqCMWPG4He/+x0AYNSoUdi1axdWrFgRtCR6jz5YNC4uDpIkoaqqyq+9qqoKSUlJHcYfOnQIR44cwU033QSNRgONRoN//etfWLduHTQaDQ4dOtTpdebMmYOmpibff8eOHQvKv4eIAmfkyJEAgH/+859wu93Yvn07NmzYgO3bt8PtduPFF1/0G0dEREQXhnNzIgIAjdGAzOvyIIj+6YTI/smIG5bFUi5ERGFEa9SfpT84dyglJyfjoosu8msbNmwYyss73xUfCD16J7pOp8Po0aOxYcMG3HLLLQBOrTRs2LABDzzwQIfxQ4cOxc6dO/3a5s6di+bmZvzlL39BWlpap9fR6/XQ68/8TSeinmXkyJGIjo7Gzp07ceONN/rd9q3X6+F0OhEdHc0kOhERUYBwbk5EAKCzGGFJjMXgW6egra4RssMJU2IsRI0EjUkPQRDUDpGIiEJEH2FC4rD+qNpztENf4rD+0EeYgnLdvLw87Nu3z69t//796N+/f1CuB/TwJDoAPPLII5gxYwbGjBmDcePGYcmSJbDb7bjrrrsAAHfeeSdSU1OxePFiGAwGXHzxxX5fHx0dDQAd2omod5MkCddeey3WrFkDt9vt19f++bXXXguJJ9ETEREFDOfmRORuacXuf78H2emCPjoColaDk1/uguKRkXXjJMRfPFDtEImIKET0ZgPG/ngKtr70kV8iPXFYf4y9c0pQ6qEDwMMPP4yJEyfid7/7HW677TZs2bIFK1euxMqVK4NyPaAXJNGnT5+OmpoazJ8/H5WVlRg5ciTWr1/vO9CovLwcotijq9IQURDIsoyNGzdiyJAhaGhoQHV1ta8vPj4e0dHR2LRpE376058ykU5ERBQgnJsTke1YFWTnqRq3zsZmv77jn25HVEYKdJbg7DwkIqKex2SNwIR7roOzuRXuNhe0Rh30EaagJdABYOzYsXj99dcxZ84cPPnkk8jMzMSSJUtQUFAQtGsKXm8np4GEOZvNhqioKDQ1NSEyMlLtcIioE9u3b8fDDz+MpUuXYujQoSgpKUF9fT2sVitycnKwd+9ezJ49G3/+858xatQotcMlIiLy4Vzz3PD5IupZjnz4Baq27emyf+T906CPsoQwIiIiOh8OhwNlZWXIzMyEwdC3z7M407+1u3PNHr8TnYioM/X19QCAzMxMSJLUIVGemZnpN46IiIiIiC6cOSm2yz5dpBmCxLtRiIio7+FfNyLqlaxWKwCgrKys0/729vZxRERERER04SLTkyDptZ329Zs0iqVciIioT2ISnYh6pZycHCQlJWH16tVwu93Yvn07NmzYgO3bt8PtdmP16tVITk5GTk6O2qESEREREfUZukgLhv3wOuitkYjKTEXM4P7QWyOReulIRA9IUzs8IiKioAhZORdZlrFz5070798fMTExobosEfVRkiRh1qxZmD9/Pm688UY4nU5fn16vh9PpxJNPPslDRYmIiL6D83IiuhCCIEAfHYFBN1+GmtJD8NjbkD55NExJsdCa+nZNXSIiCl9B24n+0EMP4fnnnwdwaqI+efJkXHLJJUhLS8PGjRuDdVkiCkOnJ9A7+5yIiCiccV5ORIHkcbhQvWMfdr24DlVbS1G3+zAOvP4J9r3yIRyNzWqHR0REFBRBS6L/5z//wYgRIwAAb731FsrKyrB37148/PDDePzxx4N1WSIKE7Is49lnnwUATJgwAb/4xS/w61//Gr/4xS8wYcIEAMCf//xnyLKsZphERESq47yciALJaWvBsY1fdWh31Dfh5Je7oHg4/yYior4naEn02tpaJCUlAQDeffddTJs2DYMHD8bMmTOxc+fOYF2WiMLEjh070NjYiOHDh+Opp55CRkYG9Ho9MjIy8NRTT2H48OFoaGjAjh071A6ViIhIVZyXE1Eg1e890mVf7c4DcDW3hi4YIiKiEAlaTfTExETs3r0bycnJWL9+PZYvXw4AaG1tZY1iIrpg7cnx0aNH48c//jEqKyt9fUlJSbjmmmuwc+dO7NixA6NHj1YpSqLgkmUZJSUlqK+vh9VqRU5ODv/GElEHnJcTUSB5HK4u+xSPDHi9IYyGqOdraWiBIsuQtBqYo8xqh0NE5yloSfS77roLt912G5KTkyEIAqZMmQIA+PLLLzF06NBgXZaIwsyLL76IiRMnYt68ecjMzERZWRlWr16N//f//p/aoREFVVFREZYtW9ZhAWnWrFnIz89XMTIi6mk4LyeiQIoZlIbqr/d02hfZPwmCJmg3vBP1KvYmO8p2HELRy5+gsaoR8enxuGLG1UgdnAqDxah2eER0joL21+2JJ57AP/7xD9x7773YvHkz9Ho9AECSJDz22GPBuiwRhYmcnBwAQEREBJ588klkZ2fDZDIhOzsbTz75JCIiIvzGEfUlRUVFWLBgAbKysrB06VK8++67WLp0KbKysrBgwQIUFRWpHSIR9SCclxNRIOksJlhS4ju0C6KIlNwRkAw6FaIi6lmcbU5sWVeMN/70H9SfqIPikVF1uBIvL/gX9n6xh2d3EfVCQduJDgC33norAMDhcPjaZsyYEcxLElGYEMVTa4DNzc2YN28e7rjjDt9O9FWrVqG5udlvHFFfIcsyli1bhtzcXCxcuND3M56dnY2FCxdi7ty5WL58OfLy8limgYh8OC8nokCp21OG5PEXo6WiBrW7DsHjcCGyfxKSRl+Eis+/QdaNk6DRMZFO4a210Y7P//NZp30f/WM9MkcMQFR8VIijIuo7MjIycPTo0Q7ts2bNwtKlS4NyzaBll2RZxlNPPYXU1FRYLBYcPnwYADBv3jw8//zzwbosEYWJxsZG38dff/01Zs+ejeuvvx6zZ8/G119/3ek4or6gpKQElZWVKCgo6LBIJIoiCgoKcPLkSZSUlKgUIRH1NJyXE1EgeRUFB17/BPbKOqReOgpZ1+XBaI3CwXWb0Hy8Su3wiHqEpupGeBWl0z6H3YE2mz3EEREFV1tzG2qP1+DEvuOoO16Ltua2oF5v69atOHnypO+/Dz/8EAAwbdq0oF0zaEn0RYsW4cUXX8Qf/vAH6E5bhb744ovxj3/8I1iXJaIwYbVaAQA//elPER0d7dcXExODe+65x28cUV9RX18PAMjMzOy0v729fRwREeflRBRIsUNPzTVsR0/iyPuf49DbRaj8ajdkpwsxQzKgMehVjpBIfRq99oz9koZ3jFLf0VTThNf+uBYr7v8r/vnLlVh+///h9T+uRVNNU9CuGR8fj6SkJN9/b7/9NgYMGIDJkycH7ZpBS6L/61//wsqVK1FQUOB3O/mIESOwd+/eYF2WiMJETk4OkpKSUFRUBOU7K/yyLOPTTz9FcnIya6JTn9O+MFRWVtZpf3s7F5CIqB3n5UQUSLooM+JzBgGCAEtKPCL7J0NjMkBj1KPfpFGQdGdOHhKFg4jYSBgjOj88NC4tHqYoc4gjIgqOtuY2vP3XN1G2/aBf++HtB/HOX98M+o50AHC5XFi1ahVmzpwJQRCCdp2gJdFPnDiBgQMHdmhXFAVutztYlyWiMCFJEi677DLs27cPdXV1fn11dXXYt28fJk+ezJrQISDLMrZv344NGzZg+/btPCQnyNoXkFavXt1hAUlRFKxevZoLSETkh/NyIgooxYvYiwcg+84bEJmRAoM1CpnXTsTQH14b1OQFdY/ikeF2uOBVvGqHEtYirBG4dc7tHXac680GfO9X02COtqgUGVFg2ZtaOiTQ2x3efhD2ppagx/DGG2+gsbERP/nJT4J6naAdLHrRRRfh008/Rf/+/f3a//Of/2DUqFHBuiwRhQlZlrF+/XoAgFarhdPp9PW1f75+/Xr89Kc/ZSI9iIqKirBs2TJUVlb62pKSkjBr1izk5+erGFnfJUkSZs2ahQULFmDu3LkoKCjwHaq7evVqFBcXo7CwkD/3ROTDeTkRBZLL3gZ7RS2ObfzK11a9fS9MiVb0v3I8tCYDJD0PFg01V5sTLdWNOPjJDrQ2NCNxaH+kjR0Mc2wkFzdUIEoi+g1Lx8+W/Rz7Pt+NyrJKpGf3x4BLBvJAUepTnHbnBfUHwvPPP4/rrrsOKSkpQb1O0JLo8+fPx4wZM3DixAkoioLXXnsN+/btw7/+9S+8/fbbwbosEYWJHTt2oLGxEcOHD8ezzz6LXbt2ob6+HlarFRdffDEeeeQR7Ny5Ezt27MDo0aPVDrdPKioqwoIFCzBhwgRMnz4der0eTqcTW7ZswYIFC1BYWMhEepDk5+ejsLAQy5Ytw+zZs33tycnJfN6JqAPOy4kokBSX2y+B3q61qh51e8qgj45gEj3E3A4Xjn65Byd3HUH6mMGQtBq01jejeOW7GPeTqxGVEqt2iGFJ0kiwJluR+4NL1Q6FKGj05jOfg3G2/gt19OhRfPTRR3jttdeCeh0giEn0qVOn4q233sKTTz4Js9mM+fPn45JLLsFbb72Fq666KliXJaIwsWPHDgDAXXfdBa1W22En3U9+8hM8+uijTKIHiSzLWLZsGQYPHoyysjIUFxf7+pKSkjB48GAsX74ceXl53BEdJPn5+cjLy0NJSYlvASknJ4fPNxF1wHk5EQVSU1lFl321pQeRPC47hNEQADhsrTBEmBCZGIPtr2yCu82JyGQrhl4zBhXfHIIhygy92aB2mETUB5mjLMgaNRCHOynpkjVqIMxRwS1d9M9//hMJCQm44YYbgnodIIhJdACYNGkSPvzww2BegojCnNfLWn9qKCkpQWVlJaqqqnw70Q0GAxwOB7Zs2YIvvvgCXq8XJSUlLBUQRJIk8fklom7hvJyIAsXjcHXZp7g8AEuHhJyzpQ2HP9uFqj3lvjbbyXpsefEDjLnjSnicbibRiSgojBFG3PDzqXjnr2/6JdKzRg3EjQ9O7fKA3UBQFAX//Oc/MWPGDGg0QU1xAwhyEp2IKFhGjhyJl156CS+++CJGjRoFUfz2nGRFUfDiiy/6xlHg1dbWAgAGDhyIw4cP++1ET0xMxMCBA3HgwAHfOCIiIiLqG6IH9kPVtt2d9llSEyDptSGOiLyK4pdAP93u97YiblC/EEdEROEkKj4K3/vVNNibWuC0O6E362GOsgQ1gQ4AH330EcrLyzFz5sygXqddQJPoMTEx3T6wor6+PpCXJqIwM3LkSERHR2Pnzp14/PHHcccdd/gOV1y1ahV27tyJmJgYJtGDpLGxEQBw4MABTJw4EfPnz/c73PLzzz/3G0dERKHFeTkRBYspPgamBCtaq7/z2iEI6H/lOGiN3PEcak0n6rrsa62zwSvLIYyGiMKRMcIY9KT5d1199dUhrU4Q0CT6kiVLfB/X1dVh4cKFuOaaa5CbmwsAKC4uxvvvv4958+YF8rJEFIYkScIjjzyCBQsW4Ouvv/bbCa3X6yEIAh5++GHWhw6SyMhIAEB0dDSefPJJ361T2dnZePLJJ3HrrbeisbHRN46IiEKL83IiChadxYTBt05B5dZSVO/YB8XtgSU1Af2vHAdjfIza4YUl3RlKtQiCAEHkeyIiogsV0CT6jBkzfB//4Ac/wJNPPokHHnjA1/bggw/iueeew0cffYSHH344kJcmojCUn5+PwsJCLFu2DJWVlb52q9WK+++/H/n5+SpG17fZbDYAp3aaz58/HwUFBX470dt3oLePIyKi0OK8nIiCSR9pRtplo5E0NhvweiHqNNyBriJLQjQkrQTZ3XHHefLwTAgS69QTEV2ooNVEf//99/H00093aL/22mvx2GOPBeuyRBRm8vPzkZeXh5KSEtTX18NqtSInJ4c70IMsOjoaADBo0CAcOnQIs2fP9vUlJSVh0KBBOHDggG8cERGph/NyIgoGUZKgjzSrHQYBcNpaMbrgSnz10kdQZMXXbomPwsDJI1SMjIio7whaEj02NhZvvvkmHn30Ub/2N998E7GxscG6LBGFIUmSMGrUKLXDCCtxcXEAgIMHD2LChAm4/fbbodfr4XQ6sWXLFnzxxRd+44iISD2clxMR9W0RidHY//F2TLzvJjSWV8NhsyM6LQGSVsKhT0sw9s6r1A6RiKjXC1oSvbCwEPfccw82btyI8ePHAwC+/PJLrF+/Hn//+9+DdVkiIgqBnJwcJCUlISoqCmVlZX416ZOTkzF48GDYbDbk5OSoGCUREQGclxMR9XX6SDPSLhmEz5a+ieh+8dCa9DjxzSHIbhlX/PI26EwstUNEdKGClkT/yU9+gmHDhuH//u//8NprrwEAhg0bhs8++8w3eSciot5JkiTMmjULCxYswIQJEzB9+vQOO9ELCwtZVoeIqAfgvJyIqG/T6rVIGz0I1sxEHCraidY6G4ZeMxYpOVkwx0aqHR4RUZ8geL1er9pB9DQ2mw1RUVFoampCZCT/4BARdaWoqKjDwa7Jyck82JWI6Aw41zw3fL6IiLrPq3ihKDIkTdD2TBJRH+FwOFBWVobMzEwYDH37jpUz/Vu7O9cM6KuqzWbzXcxms51xLCfARES9Hw92JSLqmTgvJyIKT4IoQBKZQCciCrSAvrLGxMTg5MmTSEhIQHR0NARB6DDG6/VCEATIshzISxMRkUp4sCsRUc/DeTkRERERUeAENIn+8ccfw2q1AgA++eSTQD40ERERERF1E+flRERERESBE9Ak+uTJkwEAHo8HmzZtwsyZM9GvX79AXoKIqANZlllOhIiI6DSclxNRKCiyAq+iQNKyfAgREYWOLMt44oknsGrVKlRWViIlJQU/+clPMHfu3E7vwAwEMRgPqtFo8Mc//hEejycgj7d06VJkZGTAYDBg/Pjx2LJlS5djX3vtNYwZMwbR0dEwm80YOXIkXnrppYDEQUQ9T1FREQoKCvDwww/jqaeewsMPP4yCggIUFRWpHRoREZHqAj0vBzg3JyLA3eZA8/EqHH67CAf+uwHVO/bB2dSidlhERKSSFpsdJ46cxIFdh1FxpBItNntQr/f0009j+fLleO6557Bnzx48/fTT+MMf/oC//vWvQbtm0JaLr7jiCmzatAkZGRkX9DivvPIKHnnkEaxYsQLjx4/HkiVLcM0112Dfvn1ISEjoMN5qteLxxx/H0KFDodPp8Pbbb+Ouu+5CQkICrrnmmguKhYh6lqKiIixYsAC5ubmYN28eMjMzUVZWhtWrV2PBggUoLCxEfn6+2mESERGpKlDzcoBzcyICPG1OnPxiJ05+ucvX1nSkAroIM4YVXAdDdISK0RERUajVVdVjxVMvouSLUl/biAkX42fzZiA20RqUa37++eeYOnUqbrjhBgBARkYGXn755TNu7rhQgtfr9QbjgVesWIHCwkIUFBRg9OjRMJvNfv0333xztx5n/PjxGDt2LJ577jkAgKIoSEtLw89//nM89thj3XqMSy65BDfccAOeeuqpbo232WyIiopCU1MTIiMju/U1RBRasiyjoKAAWVlZWLhwIUTx2xtrFEXB3LlzUVZWhlWrVrG0CxER9SihnmsGal4OcG5ORIC9uh67Xniz0764nEHIuGoCy7sQEfUCDocDZWVlyMzMhMFgOK/HaLHZ8Zff/s0vgd5uxISL8eDv7oUl0tzJV16Y3/3ud1i5ciU++OADDB48GN988w2uvvpqPPvssygoKOgw/kz/1u7ONYP2l23WrFkAgGeffbZDnyAIkGX5rI/hcrmwbds2zJkzx9cmiiKmTJmC4uLis3691+vFxx9/jH379uHpp58+h+iJqKcrKSlBZWUl5s2b55dAB069ThQUFGD27NkoKSnBqFGjVIqSiIhIfYGYlwOcmxPRKfV7j3TZV1d6CP0uHcUkOhFRmGiqt3WaQAeAb77YhaZ6W1CS6I899hhsNhuGDh0KSZIgyzIWLVrUaQI9UIL2l01RlAt+jNraWsiyjMTERL/2xMRE7N27t8uva2pqQmpqKpxOJyRJwrJly3DVVVd1Od7pdMLpdPo+t9lsFxw7hR8ebhla9fX1AIDMzMxO+9vb28cRERGFq0DMywHOzUldiscDxeWC1wuIWg0knU7tkMKW9wwLb15ZARCUm92JiKgHam1pO2N/21n6z9err76K1atX49///jeys7OxY8cOPPTQQ0hJScGMGTOCcs0+uTwcERGBHTt2oKWlBRs2bMAjjzyCrKwsXHbZZZ2OX7x4MQoLC0MbJPUpRUVFWLZsGSorK31tSUlJmDVrFmtyB4nVeqquVllZGbKzszv0l5WV+Y0jIiIidXBuThfK3WJH4+69sB+vALxeGOJiYR1xMbSRERC+c0ciBV/M4P5+9dBPFz0gDZKeCxxEROHCZDGesd94lv7z9atf/QqPPfYYbr/9dgDA8OHDcfToUSxevDhoSfSgzjg2bdqEm266CQMHDsTAgQNx880349NPP+3218fFxUGSJFRVVfm1V1VVISkpqcuvE0URAwcOxMiRI/Hoo4/i1ltvxeLFi7scP2fOHDQ1Nfn+O3bsWLdjJGo/3DIrKwtLly7Fu+++i6VLlyIrKwsLFixAUVGR2iH2STk5OUhKSsLq1as77LBTFAWrV69GcnIycnJyVIqQiIio57jQeTnAuTmpw9PaisqizbAfOwH87zgvR20dTn7yKdwtdpWjC0+G6AhED0zr0C5qNUi7fAw0TKITEYWNKGskRky4uNO+ERMuRpQ1OOfZtLa2dijtK0lSwO7A7EzQkuirVq3ClClTYDKZ8OCDD+LBBx+E0WjElVdeiX//+9/degydTofRo0djw4YNvjZFUbBhwwbk5uZ2OxZFUfxuCf0uvV6PyMhIv/+IukOWZSxbtgy5ublYuHAhsrOzYTKZkJ2djYULFyI3NxfLly/vdq1R6j5JkjBr1iwUFxdj7ty5KC0tRWtrK0pLSzF37lwUFxfj/vvvZ0kdIiIKe4GYlwOcm5M62qpqILc5OrR7FQVNe/dD8XhUiCq8ac1GZF47EZnX58EYFw1dhAnxIwbj4rtuhjFIyRIiIuqZLJFm/GzejA6J9BETLsbP5s0ISj10ALjpppuwaNEivPPOOzhy5Ahef/11PPvss/je974XlOsBgOD1eoNSsGzYsGG499578fDDD/u1P/vss/j73/+OPXv2dOtxXnnlFcyYMQN/+9vfMG7cOCxZsgSvvvoq9u7di8TERNx5551ITU317WZZvHgxxowZgwEDBsDpdOLdd9/FY489huXLl+Oee+7p1jW7eyor0fbt2/Hwww9j6dKlnZYUKS0txezZs/HnP/+Zh1sGSWeldJKTk3H//fezlA4REfVIoZ5rBmpeDnBuTqGlyDJqvtiKtsrqTvtFvR4pV06GxmgIcWTUzm1vg1dRoDHoIfIwUSKiXsXhcKCsrAyZmZkwGC7sb2mLzY6mehvaWtpgtBgRZY0MWgIdAJqbmzFv3jy8/vrrqK6uRkpKCn74wx9i/vz50HVybsqZ/q3dnWsG7a/c4cOHcdNNN3Vov/nmm/Hb3/62248zffp01NTUYP78+aisrMTIkSOxfv1634FG5eXlftv37XY7Zs2ahePHj8NoNGLo0KFYtWoVpk+ffuH/KKLv4OGW6svPz0deXh4PdSUiIupCoOblAOfmFFqCIEDU67vsl3RaCEIIA6IOtObg1LolIqLexRJpDmrS/LsiIiKwZMkSLFmyJGTXDFoSPS0tDRs2bMDAgQP92j/66COkpXWsn3YmDzzwAB544IFO+zZu3Oj3+cKFC7Fw4cJzenyi88XDLXsGSZK405+IiKgLgZyXA5ybU+gIoojIrAzYj3ZeFz9y0ABIF7hzjoiIiKg7gpZEf/TRR/Hggw9ix44dmDhxIgBg8+bNePHFF/GXv/wlWJclCqnTD7dcuHCh384rHm5JREREPQHn5dSbaSxmRF80BI279/m1G5OTYExOVCkqIiIiCjdBS6Lff//9SEpKwjPPPINXX30VwKl6jK+88gqmTp0arMsShVT74ZYLFizA3LlzUVBQgMzMTJSVlWH16tUoLi5GYWEhS4sEmcvlwptvvomKigqkpKRg6tSpndbAIiIiCkecl1NvJul0iBiQBVNqClpPVsIryzAlJ0FjMkI6Q6kXCj6vosDT5oDXK0DUStDoOf8mIqK+K2gHi/ZmPLyIzhUPt1TPihUrsHbtWsiy7GuTJAnTpk3Dfffdp2JkREREneNc89zw+SLqeZzNdribW9F09CRkhxMR/RJhsEZCHx0BkRuIiIh6hUAeLNrT9eiDRUkdsizzgEUV8HBLdaxYsQJr1qxBTEwM7r77buTm5qK4uBjPP/881qxZAwBMpBMREdE58Xq9UNxueGU3AEDQaCFqtBB4giURgFMJ9MZDx3Hk/WLgf3vyTn65C5bUBAy4YRIMVi52ERFR3xPQJHpMTEy3J5f19fWBvDSh893QSUlJmDVrFndDhwAPtwwtl8uFtWvXIiYmBmvWrMHu3buxY8cOpKamYs2aNbj99tuxdu1azJw5k6VdiIgo7HBefn68sgy3vRn240fg9XgAnEqiW9IyoDFbIIjcIEEktzl9CXRTohWiVoO22ka0nKhG1fa9SM0bAY2BpXaIiKhvCWgSfcmSJYF8ODoHRUVFWLBgAXJzczFv3jy/utwLFixAYWEhE+nUp7z55puQZRmTJk3CjBkzOiweTZo0CevWrcObb76JadOmqRgpERFR6HFefn5klxMtRw76tXk9bjSXHUDk4GxoDEaVIiPqORoOlMM6pD/ihw9Cy8kayA4XEi8ZBtnhwonPv0HiJUOZRCcioj4noEn0GTNmBPLhqJtkWcayZcuQm5uLhQsXQhRFAEB2djYWLlyIuXPnYvny5cjLy2N5EeozKioqAABvvfVWp4tHb731lt84IiKicMJ5+bnzKgocNZVd9jtqq2BOSYfwv7k2UbjSmAywpCZg39oP/drNyXHIuHoCeOoaERH1RUGtia4oCg4ePIjq6mooiuLXx13RgVNSUoLKykrMmzfPl0BvJ4oiCgoKMHv2bJSUlLDcCPUZSUlJAICsrKxOF4/uueceHD582DeOiIgonHFefnZeRYbc1tplv9zWCq+iMIlOYc+SEo9d/1zXod1+sha28pOw9EtQISoiIqLgCloS/YsvvsCPfvQjHD16FN7vLEULggBZloN16bDTXscyMzOz0/72dta7pL4kKysLAHzJgNMXkBRFQU1Njd84Ch4eaExE1LNxXt5NgghRb4DsdHTaLekNTKATAWg6fKLLvtqdB5E8bngIo6HTuR0uOJvbILs90Bp0MESbO2y0IyKi8xO0JPp9992HMWPG4J133kFycjJPsw8iq9UKACgrK0N2dnaH/rKyMr9xRH2BzWYDADQ3N2PatGmYOXMmcnNzUVxcjBdeeAHNzc1+4yg4eKAxEVHPx3l594iSBGNCMty2xk77DfGJTKITAXC1tnXZJzvdYD0XdbTWN2PHfz/Fie0H4FW80JkNuPjmXKSNHgy9hec5EFHf09zcjHnz5uH1119HdXU1Ro0ahb/85S8YO3ZsUK4XtCT6gQMH8J///AcDBw4M1iXof3JycpCUlITVq1f7lbUATu3IXb16NZKTk5GTk6NilESB1b4oNGXKFHzyySd45plnfH2SJGHKlCn46KOPuHgURO0HGk+YMAHTp0+HXq+H0+nEli1beKAxEVEPwnl594l6Pcz9MmA/UQ54/1f2RhRh7pcBUWdQNziiHiI6qx+qtu7utM+SEg9RF9SqsdQJR5Mdny1fB0OkGWN/fBUknQb2Ohv2b9gOQRSRlXcxBJELqEQUPE2Nzaiva0CzrQURkRZYY2MQFR0R1Gvec8892LVrF1566SWkpKRg1apVmDJlCnbv3o3U1NSAXy9of93Gjx+PgwcPcrIeApIkYdasWViwYAHmzp2LgoICvwMWi4uLUVhYyPIK1Ke0Lx61trbinXfewVtvvYWKigqkpKTgpptuwpNPPsnFoyBqP9B48ODBKCsrQ3Fxsa8vKSkJgwcP5oHGREQ9BOfl3SdKGuiirdBYIqC43afatFqIGi13oRP9jykuBsa4aLTVNvp3CALSrxwHrZELTqFmr7dh2LVjUVdWie1rN8Hd6kRkSiwuun48Gsqr0dbUAlNMcJNZRBS+Kiuq8cRv/oDPi7b62ibmj8UTT/8aSSnBOSejra0N//3vf/Hmm2/6Nu898cQTeOutt7B8+XIsXLgw4NcMaBK9pKTE9/HPf/5zPProo6isrMTw4cOh1Wr9xjKxFVj5+fkoLCzEsmXLMHv2bF97cnIyd4NSn3T64tGTTz6JgoIC3HDDDSgrK8OTTz7JxaMgaz/QuKqqCrm5uZg3b16HxTuv18sDjYmIVMJ5+fkTRBGSTg9Jp1c7FKIeSRdhwpDbrkZF8Teo2XkQXo8MU2IsMq4aD1NCjNrhhSXFo+DwZ7tQtafc12arqMOWF9/HmDumQJGVM3w1EdH5a2ps7pBAB4DPi7biid/8AU//dUFQdqR7PB7IsgyDwX/h1mg04rPPPgv49YAAJ9FHjhwJQRD8DiyaOXOm7+P2Ph5gFDzfPSxKUfjHkvouLh6pp7a2FgAwbtw4FBYWYteuXSguLobVakVhYSHmzp2LL7/80jeOiIhCi/Py86fIMrweNzz2FkAANCYLBI0GosQSFUTt9JFm9L9yHFIm5MDr9ULSaaE1cQe6WgRJRPXeY0jJyULamMEQJRFtTXYc/nQndr+3BfGD+6kdIhH1UfV1DR0S6O0+L9qK+rqGoCTRIyIikJubi6eeegrDhg1DYmIiXn75ZRQXFwft7suAzgTbD7Ck0GuvTZybm4v58+f77QhlbWLqy/Lz8zF27Fj87W9/w/Hjx9GvXz/87Gc/g9HIw3OCqbGxEQCQmJiIO+64A1VVVb6+xMREjB8/3m8cERGFFufl50fxuOGorYaj+qRfuzEpBXprAkQNE+lE7USNBhqjHl5FgaTXqR1OWGuqqMXEn90I2SNDo9NAdntgjo3EiFvzUVFyGAoXS4koSJptLWfsbzlL/4V46aWXMHPmTKSmpkKSJFxyySX44Q9/iG3btgXlegGdBfbv39/38eLFi5GYmOi34wUAXnjhBdTU1OA3v/lNIC8d1tprE+fm5vodLJqdnY2FCxdi7ty5rE1MfdaKFSuwdu1a3y66r776Cm+99RamTZuG++67T+Xo+q7o6GgAwLp166DX+9/u3tjYiHXr1vmNIyKi0OK8/PzIjrYOCXQAaKusgMYcAVHDmsJEAOBubYO7pQ2u5lbIbjf0kRZozQboo/g7ogZreiI8Thd2v7cVVXuOAl5Ao9di0BUj0X/sUGgNXOQgouCIiLScsd9ylv4LMWDAAGzatAl2ux02mw3JycmYPn06srKygnK9oJ2O87e//Q1Dhw7t0J6dnY0VK1YE67Jhqb02cUFBgS+B3k4URRQUFODkyZN+tTGJ+oIVK1ZgzZo1sFgsuOyyy3Dttdfisssug8ViwZo1a/haE0RWq9X3sclkwi9/+Uv897//xS9/+UuYTKZOxxERkTo4L+8eRZbRVl3ZZb+jupK7OYkAuFsdaK2uR83OAxB1GugizGitrkf1NwfgaLCpHV5YkrQStv37Y1TtPpVABwCP0409721F9f5jAARV4yOivssaG4OJ+WM77ZuYPxbW2OCflWE2m5GcnIyGhga8//77mDp1alCuE7T7ESsrK5GcnNyhPT4+HidPdtzdQeevvr4eAJCZmdlpf3t7+ziivsDlcmHt2rXQ6/VoaWnBxo0bfX2SJEGv12Pt2rWYOXMmdDruvAi09vMWjEYjtFot/vSnP/n6EhMTYTQa0dbWxnMZiIh6AM7Lu0lR4HW7uu72uIHvnD9EFI48bU5Ieh2iB6ShbvdhyA4XIvsnwzq4P9rqGqGxGKH5zgHGFFytDS2wnez8/f7+DdvR75JBIY6IiMJFVHQEnnj61x0OF52YPxZP/OHXQamH3u7999+H1+vFkCFDcPDgQfzqV7/C0KFDcddddwXlekFLoqelpWHz5s0dErubN29GSkpKsC4bltp3epaVlSE7O7tDf3tNTO4Ipb7kzTffhCzLkGUZMTExuPvuu5Gbm4vi4mI8//zzaGho8I2bNm2aytH2Pe13trS1tWHEiBGYNGkSnE4n9Ho9Tpw4gS+++MI3buzYzleliYgoNDgv7x5BkqAxR0B2Ojrt15gjIIhBu5GXqNdQZBkNB4+hYvM3vra6PWUwWCMx6HtXwGN3QBPNJHoo2Sq/TaCb4yKhMxlgr22Cq9UJl90BxcO7aIgoeJJSEvD0Xxegvq4BLbYWWCItsMbGBDWBDgBNTU2YM2cOjh8/DqvVih/84AdYtGgRtEFayA1aEv2nP/0pHnroIbjdblxxxRUAgA0bNuDXv/41Hn300WBdNizl5OQgKSkJq1ev9quJDpzaLbp69WokJycjJydHxSiJAuv48eMAgKioKKxduxaa/x30deONN+Laa6/FD37wAzQ1NfnGUXBcfvnlKCoq8iXNgVN3AkyePBmbNm1SMTIiImrHeXn3CKIIQ3winA21HXecCyIMsfFMohMB8MqyXwK9naPehsqtpUjJGxn6oMKcJT4acQNSMOTq0bDX2uCw2RGVGgfZ5cGutz6HRs9FDSIKrqjoiKAnzb/rtttuw2233Ray6wUtif6rX/0KdXV1mDVrFlyuU7dFGgwG/OY3v8GcOXOCddmwJEkSZs2ahQULFmDu3LkoKChAZmYmysrKsHr1ahQXF6OwsJCHilKfUltbCwAYP368L4HeTqPRYNy4cfjwww994yiwRo4ciZdeegmffPIJxo0bB4PBgObmZkRERMDhcPgS6CNHjlQ3UCIi4rz8HIg6HSIHDIX9xFHIba0AAMlohrlff4g6/Vm+mig8NOwv77KvbvdhJE8YHsJoCACiUuMw6IpR+OIf70F2e3ztkSmxyLvvJhiignewHxFRuAhaEl0QBDz99NOYN28e9uzZA6PRiEGDBkGv5+QzGPLz81FYWIhly5Zh9uzZvvbk5GQUFhYiPz9fxeiIAi82NhYA8OWXX8Lj8fgl0j0eD7Zs2eI3jgJr+PDhEEURiqL4nuvvEkURw4fzTRQRkdo4L+8+QRChMZkRkTkI3v8dIipIGoiaoL1tIup1ZJe7yz7FI0MQeIhlyCkKtv7rA78EOgDYKuqwf8N2jPnxVSoFRkTUdwR9NmixWFgPN0Ty8/ORl5eHkpIS1NfXw2q1IicnhzvQqU9KS0sDcKoG1rRp0zBz5kxfTfQXXngBTU1NfuMosEpLS896aKiiKCgtLcWoUaNCFBUREZ0J5+XdJ2q0gIblD4g6EzMoHVXb9nTaF5meBEmvC3FE1HC8Bh5n54sbx78+iOFT86CNjwpxVEREfQu3VPQxkiQxYUVhYerUqVixYgU0Gg0aGxvxzDPP+PoEQYBer4fH48HUqVNVjLLvqq6uBgDodDp4PB6/hLokSZAkCS6XyzeOiIiIiPoGgzUKltQEtJzwn+cJkoj0K8ZCazKoFFn4amu0d9nnVRR4znD3ABERdQ+T6ETUK+l0OkybNg1r1qxBdHQ0MjIyoCgKRFHEkSNH0NjYiNtvvx06HXfCBMOePad2H7lcLuTm5mLcuHHQ6/VwOp3YsmULiouLfeOuueYaNUPt02RZ5t1HREREFFL6SDMGTr0MtTsPoGr7XngcLkRmJCNt0iUwxkWrHV5YikmL77LPGG2BqOH8kIi65v3ugep9UCD+jUyiE1Gvdd999+HYsWPYvHkzduzY4deXl5eH++67T53AwkD7H6CoqCj89re/xfPPP4/jx4+jX79++O1vf4s77rgDTU1NYfHHWC1FRUVYtmwZKisrfW1JSUmYNWsWz8EgIiKioBIEQGM2Iv3KcRAlCa7mVgACOPVTh8agQ9yAFNQequjQN/TaMRAlUYWoSJEV2GqbcGz3UdSU1yBlcCqSB6YgKj5a7dCIAABa7anSda2trTAajSpHE1ytracOjG//N58PJtGJqNcqKirC559/jnHjxsHhcMBmsyEyMhIGgwGff/45ioqKmEwMkvYDo5qamnDTTTf52r/66iu88cYbHcZRYBUVFWHBggXIzc3FvHnzkJmZibKyMqxevRoLFizggdJEREQUNK6WVux/7WMobg+sQzMgajWwn6zDsU+24qI7roc5KU7tEMNO7aGTGPXDy1H26U6Ufb4bstsDU2wkcm7Jg6vV2WW9dAoer9eLykMVWDX3RbjaXL52c7QFP158F+L6dX33AFGoSJKE6OhoXxlWk8nU597De71etLa2orq6GtHR0Rd057bg5TbBDmw2G6KiotDU1ITIyEi1wyGiTsiyjIKCAoiiiMrKSr+a3KIoIikpCV6vF6tWrWJ5iyB4//33sXjx4rOOmzNnDsu5BFj7z35WVhYWLlwIUfx2Z5GiKJg7dy7Kysr4s0/Ug3GueW74fBH1LLajJ+FobIbsdKG29BBkhwsR6UmIuygLtbvLTtVFN+rVDjOs1JdXofbgCdQdqkTqqIEQBMBld6B86z6MuDUf+ggTzNYItcMMK7baJjz/8N9gb2zp0Jc0IBk/LLwT5iizCpER+fN6vaisrERjY6PaoQRVdHQ0kpKSOl0k6O5ckzvRiahXKikp8ZWxOD2J2K6iosI3joftBl50dLTvY0EQMGDAABgMBjgcDhw6dMhXxuX0cRQY7T/78+bN6/CzL4oiCgoKMHv2bP7sExERUVDIbg8a9pej8dAxX5tz50E07DuKgd+7HIrLDTCJHlIarQbfrP0UXq8Xx7bt9+vbsbYI42deq1Jk4au5vrnTBDoAVB46iVabnUl06hEEQUBycjISEhLgdvfNu1a0Wm1ANpgxiU5EvVL77UYAMGbMGKSlpcHpdEKv1+PYsWPYsmVLh3EUOJ999pnvY6/Xi4MHD3Y5bvz48aEKKyzU19cDADIzMzvtb29vH0dEREQUSKJWg8ZDx2Adlon4nEEQRRGttY04tmkbqrbtQcbVuWqHGHZqD53s8iyi2oMn4G5zAuBO9FBytTrP2O9xeUIUCVH3SJLEO5nPgkl0IuqVSktLAQAWiwXbtm3zJc2BUy/+ZrMZdrsdpaWlLCcSBPv37z/7oHMYR91ntVoBAGVlZcjOzu7QX1ZW5jeOiIiIKJAayyqQPeMmtJyoRvmGLfA4XIjMSMZFd1yPk1/ugleW1Q4x7MjuMydkvQqr+IZaVEL0qRN4O1nc0Bl1MEaYQh8UEV0QJtH7GFmWUVJSgvr6elitVuTk5HAlifqkuro6AEBLSwtiYmJw1VVXITU1FSdOnMCHH36IhoYGv3EUWGbzt7ce6nQ6uFzfHpaj1+vhdDo7jKPAyMnJQVJSElavXt1pTfTVq1cjOTkZOTk5KkZJRNT7Kf9LBIqcSxP5iRuWgWObvkLT4QpfW92uQ2jYdxQXFVwHr8CEbajFD0rtsi8qJRYagzaE0RAAmKPNuOS6Mfj63a0d+vJ/dAUiYiwqREVEF6JjIeEeaOnSpcjIyIDBYMD48eP9dpx+19///ndMmjQJMTExiImJwZQpU844vi8pKipCQUEBHn74YTz11FN4+OGHUVBQgKKiIrVDIwo4g8Hg+7i5uRmvvvoq/vznP+PVV19Fc3Nzp+MocJKTk30fn55AB+BLoH93HAWGJEmYNWsWiouLMXfuXJSWlqK1tRWlpaWYO3cuiouLcf/993MBlYiCpq/PzWW3C86GOrQcOYiWIwfhbKyH4nad/QuJwoTH4fJLoLdT3B4cK/oaosA5SKhJOi0yL724Q7sgihg5/TKIWu6fDDW9yYD8H16Oq+65FuboUxuLohKiMfXRHyDnipGQ+D0h6nV6/G/tK6+8gkceeQQrVqzA+PHjsWTJElxzzTXYt28fEhISOozfuHEjfvjDH2LixIkwGAx4+umncfXVV6O0tBSpqV2vzvZ2RUVFWLBgAXJzczFv3jxkZmairKwMq1evxoIFC1BYWIj8/Hy1wyQKGJPp29vfPB7/2xdP//z0cRQ43T25u6+f8K2W/Px8FBYWYtmyZZg9e7avPTk5ma/3RBRUfX1uLrtdaDlyEHJbq6/NY2+GZDLD0n8AJK1OxeiIeoaGA+Vd9jUdPuG7i4NCp6WmEUOvGYP4ganYv+FrOGytsGYk4aIbxkEQBMhtLiBa7SjDjyXagnE3TcBFl14M2SND0moQYWVteqLeSvB2dfpEDzF+/HiMHTsWzz33HIBTt6qnpaXh5z//OR577LGzfr0sy4iJicFzzz2HO++8s1vXtNlsiIqKQlNTEyIjIy8o/lCQZRkFBQXIysrq9Nb+uXPnoqysDKtWreLOROoznn32Waxbtw4AoNFokJ+fj6FDh2Lv3r0oKiryJdJvvvlmPPLII2qG2ic99dRT2LBhw1nHXXnllZg3b14IIgpPLOFF1Dv1trnm6fr63NxRX4PW40c77TOnZUIfExvU6xP1BuWfbMXJL3d12idIInLuvgUGa1SIowpvTSfrsOX/fYCxP74KklaCIiuQdBrUHDqJmr3luOj68bDE8XtCRNSZ7s41e/ROdJfLhW3btmHOnDm+NlEUMWXKFBQXF3frMVpbW+F2u894wJrT6fQrP2Cz2c4/aBWUlJSgsrIS8+bN80ugA6eer4KCAsyePRslJSUYNWqUSlESBY/H48HHH3+Mjz/+WO1QwobRaAzoODo/kiTxdZ2IQqavz80VjwfOupou+511NdBGRkGUevRbKKKgsw7N6DKJHjssE6KOvyOh5oUX42dcg69f+QTVe48BADR6LQZdPhLDrh131oNHiYjo7Hp0TfTa2lrIsozExES/9sTERFRWVnbrMX7zm98gJSUFU6ZM6XLM4sWLERUV5fsvLS3tguIOtfr6egBAZmZmp/3t7e3jiPqC9gMrDQYD4uPj/foSEhJ8tdB5sGVwtB/cGqhxRETU8/X9ubkXOONNul6gR9/DSxQaXsWLxDEXdWjXRZqRPH44FDfLuYSaJEr4fOXbvgQ6AHicbuxZvxXHtx+A1sRzooiILlSPTqJfqN///vdYs2YNXn/99TMeLjhnzhw0NTX5/jt27FiXY3ui9p08ZWVlnfa3t59pxw9Rb6PRnNrh4nA44Ha7kZKSAqvVipSUFLhcLjgcDr9xFFjdPbCVB7sSEVG7nj43FyQNdDFxXfbrYuIgcl5BhLrdhxHVPxlDf3gNrEMzEZWRgv5TxmPIrVNw+N3PAEFQO8Sw09bYAtvJzjfN7ftgGzwOZ6d9RETUfT06iR4XFwdJklBVVeXXXlVVhaSkpDN+7Z/+9Cf8/ve/xwcffICcnJwzjtXr9YiMjPT7rzfJyclBUlISVq9eDUVR/PoURcHq1auRnJx81ueBqDcZOXIkgFPlLBobG1FRUYH6+npUVFSgsbHRVxe6fRwF1ullWmJj/evDnv45y7kQEfUdfX1uLggCdFExEHX6Dn2i3gBdBOsJEwFAZEYKtJEmeGUZ1qH9ET9yCDQmAwRJgikxFhLLuYRc08m6LvtcdgfvDiAiCoAenUTX6XQYPXq03+F1iqJgw4YNyM3N7fLr/vCHP+Cpp57C+vXrMWbMmFCEqipJkjBr1iwUFxdj7ty5KC0tRWtrK0pLSzF37lwUFxfj/vvv52Fz1KeMHDkSoihClk9NCNPS0pCfn++75VuWZYiiyCR6kJxepqWuzn/SfvrnLOdCRNR3hMPcXNLpEJE1BMakfpD0BkgGI4zJaYjIHAxRp1M7PKIewRQfg6qtu7Hv1Y9w8I2NOPjGJzi0bhN2v/QOksYMg9bETRShZoqJ6LJP0koQNcwFEBFdqB6/RPzII49gxowZGDNmDMaNG4clS5bAbrfjrrvuAgDceeedSE1NxeLFiwEATz/9NObPn49///vfyMjI8NVntFgssFgsqv07gi0/Px+FhYVYtmwZZs+e7WtPTk5GYWEh8vPzVYyOKPDa2tp8d14IgoBjx475bvcWBAFerxeKoqCtra1P/+6rxWQyBXQcERH1DuEwN5d0OhjiE6G3nrqzSpA0EFiegsjH09qG2l2HOrY7nDjx6XZkXDsRWiNL+oWSMcoMvcUIZ0sbJK0GGr0WrlYHvIoX6eOGQpR69P5JIqJeoccn0adPn46amhrMnz8flZWVGDlyJNavX+870Ki8vByi+O0fhOXLl8PlcuHWW2/1e5wFCxbgiSeeCGXoIZefn4+8vDyUlJSgvr4eVqsVOTk53IFOfVL7m/P4+HjU1NT49Xm9XsTFxaG2thaLFy/GokWL1AixT7viiivw4YcfdmscERH1HeEyNxcEAYJGq3YYRD1S3d4jXfbV7y9Hv8mjmUQPNVFA7r3Xw2FrBSDAZW+DKSYCzpY26CJM8J7x0GQiIuqOHp9EB4AHHngADzzwQKd9Gzdu9Pv8yJEjwQ+oB5MkCaNGjVI7DKKgq6ioAADU1NRAFEW/8wBEUURtba3fOAqs8vLybo870y3+RETU+3BuTkRnxHxtyHkVL7xeYMerm/6XSD8lKbs/hk/Ng1fhN4WI6ELxnh6iAJFlGdu3b8eGDRuwfft2X61uCo7TDzDr7EDdzsZR4HR3cYKLGERERBQostMJ2eGA9ztzPwqt2CEZXfZZB6dD1PaKvXp9ikavRfHKd/wS6ABQWXoUhzfvgsByLkREF4x/3YgCoKioCMuWLfPV+QROJW9nzZrFevRBctFFF6G4uBjAqbqqkZGRcDgcMBgMsNlsaGlp8Y2jwPtuCZ0LHUdERETUFU9bG9pOVsF2+Ai8sgxzv1REZKRDY+bZK2qQPTKswzJRv/cIzEmxELUatNWcOkw+YdRQLnKowF5rg8vu6LTvyOelGHwl71YnIrpQTKITXaCioiIsWLAAubm5mDdvHjIzM1FWVobVq1djwYIFPNg1SPbs2eP7uKWlxZc0P9M4CpyGhoaAjiMiIiLqjKfNgeovvoKr/ts5RdPe/Wg5chRJl02Clon0kKvfdwSx2VlIyc1B06HjcLc5kDIhB7pIEw699SkG3jxZ7RDDTmu9rcs+2S1DdnlCGA0RUd/EJDrRBZBlGcuWLUNubi4WLlzoO0grOzsbCxcuxNy5c7F8+XLk5eXxgNcAa695HqhxdG5OnDgR0HFEREREnXE2NPol0NvJDieaD5UhJnsoBM6zQyp2WCYcdU048J8NvrbKLaUwJcYi85pcQBBUjC48RSbHdtmnMxsg6Zj6ISK6UCyMRXQBSkpKUFlZiYKCAl8CvZ0oiigoKMDJkydRUlKiUoR9V1RUVEDH0blpbm4O6DgiIiKi71IUBS1HjnbZbz92ArLLFcKICAA0Bj3K1n/eob21qg51e8og6ZmwDTWtQYfIZGunfYMuHwlR5MIGEdGFYhKd6ALU19cDADIzMzvtb29vH0eBU1ZW5vd5dHQ0Bg0ahOjo6DOOo8CLiorCyJEjkZOTg5EjR3LhgoiIiAJCACAIZ3jLKgr/G0WhVL+/64WN6m/2QWHpkJCrO3ISI2+djMRh6b5fCY1ei2HXjoVGr4WrjYtNREQXikvERBfAaj212l9WVobs7OwO/e0J3PZxFDh1dXV+nzc2NqKxsfGs4ygwDAYD2traAABNTU3YsWNHl+OIiIiIzocgiojIykBrxclO+yMy0iHpdSGOitz2ti77FJcHXsUbwmgIACKTYrF52TpkTRqOgZeNgOKRAQBHt+xF3aGTSM7pfNMXERF1H3eiE12AnJwcJCUlYfXq1VC+cwq9oihYvXo1kpOTkZOTo1KEfZfX273JeXfH0bm5/vrrAzqOiIiIqDO6qAgYkxM7tGssZlj6p0MQ+ZY21KIyUrrss6QmQGDpkJAzxlhgio3Evg+3YfPyt1D893dR/Pd3UfHNYQy9dix0Jr3aIRIR9XqccRBdAEmSMGvWLBQXF2Pu3LkoLS1Fa2srSktLMXfuXBQXF+P+++/noaJBoNVqAzqOzs2ECRMCOo6IiIioM5LBgNhLRiBh4ngYE+NhiItF7OiRSJo0ERqTUe3wwpIhNgrG+JiOHYKAfpeO5EGvKhAkEbn3XI+0MYOROfEiDJ5yCVJHDcTFN+UiJScLikc5+4MQEdEZsZwL0QXKz89HYWEhli1bhtmzZ/vak5OTUVhYiPz8fBWj67siIyO7VaolMjIyBNGEH1c3D/Hq7jgiIiKirmgMBmiSDTDExwJeQNTybayaREnEwJvyUbltD+p2H4bi9sCcHId+l46ExmKCoGESPdRkpxvHtu1HxoSLcHjzLthONiBuUAriB/dDWXEpBkwarnaIRES9HmcfRAGQn5+PvLw8lJSUoL6+HlarFTk5OdyBHkQOhyOg4+jcvPjii90el5eXF9xgiIiIKCyIGr597QnamlqgMxoQP2IQEkYOhlfxQhBFeBxOCABkhxMw8VycUHK2OOCVFXz63Bu+trqykzi0qQQT7rkespuHvRIRXSiWc+ljZFnG9u3bsWHDBmzfvh2yLKsdEhH1QbW1tQEdR0RERHQmHocTLpsNrqYmeNraeO6NijQaDU5uLYWk1UIQBAACRK0GikdG3Z4ylnNRgUYnYc/6rR3aPU43dr/7JcBfFyKiC8al/D6kqKgIy5YtQ2Vlpa8tKSkJs2bNYkmRIONzH3omkwl2u71b4yjwTl+gE0XR72Dd0z/nQl5wybLMO2CIiALMq8hQPB4o/ytJJup0EDUaCCJfX9Xg9XrhamxC7dav4W5uAQBIBj2so3JgTIjn7nQVeJxuRGekoPSlt6G4vt3hHDOkP+IuyoJXYf3tUGs8Xttlory+rNJvrk5EROeHM44+oqioCAsWLEBubi7mzZuHzMxMlJWVYfXq1ViwYAFrcwdR+3M/fvx45OXlweVyQafT4cSJE3zugygyMhI1NTW+zy0WCywWC1paWtDS0uI3jgIvPj4eNpsNADpMyk//PD4+PqRxhRMu3hERBZ4iy3A11aP1RDnQvtNZEGHu1x/ayCiIEt8+hZrH3orKTZvhPW1hXnY4UVO8FcmXT4Le2skBlxRUkkZE9b6jGHBDPmSnCx6nC4aYSLScqIbikSFAUDtE+g5+T9Th9Xphq2lCVVkl6k7UITErCXH94hEZx/eoRL0RZ4F9gCzLWLZsGXJzc7Fw4UKI4qkqPdnZ2Vi4cCHmzp2L5cuXIy8vjzsUA6z9uU9OTsaWLVs67MZNTk7mcx8kp24d/dZ3k+ddjaPA0Ov1AR1H54YLp0REwaE429B6/Kh/o1eB/VgZIgcOg2ji26dQ8nq9sB8/4ZdAP11D6V7ETxgDSasNcWThzdXcisSRQ1D51W60VFRD0moAUUTqxBFora6HOSVO7RDDTnRa1xtXotPiIWpYyVcN1WVVWDX3n2hrbvO1RcVHoWDhT2BNiVUxMiI6H3wl7QNKSkpQWVmJgoICXwK9nSiKKCgowMmTJ1FSUqJShH1X+3NfUVGBqKgo/PKXv8R///tf/PKXv0RUVBQqKir43AdJd+tgsl5mcHR3hz/vBAi87y6cZmdnw2Qy+RZOc3NzsXz5cpbSISI6R4oso62qEhAE6KKtMPfLgLlfBnTRVkAQ0FZTyTIVIeZVFDhr67vsdzU1wevhgYmhZkq0omz95zBaIzHolsuRdcMk9Msbiaqv98AYG80SOypwNbdh4GUjOrSLGgnZN0yAIvO1K9RsdTa88tQqvwQ6ADTVNOHNZ/+LVlurSpER0fliEr0PqK8/NbHMzMzstL+9vX0cBU51dTUAIDo6GmvXrsWNN96I2NhY3HjjjVi7di2io6P9xlHgdHdnP+8ACA7X/+rEBmocdd/pC6der9fvMGmv18uFUyKi8+VVAK+CiIyBAAB7RTnsFeWAICAiYyC8isIkeogJogiNuevzbTQmE7hfIvRsx6ow+NYrET0wDS0VNWg6fAKiVoP+V46D1mKC4ubCRqhpDDoYIk0YO+NqxA/uh4jEGPQfPxSXzroZ5dv28e5cFbTUN8NWa+u078S+42i1nf18LyLqWbhE3AdYrVYAQFlZGbKzszv0l5WV+Y2jwNmzZw8A4Prrr4fmOzsuNBoNrrvuOrz88svYs2cPrrnmGjVC7LMGDx6M/fv3d2scBV5MTPfqj3Z3HHVf+4JoRUUFnnrqqQ410e+++26/cURE1D2CKMGQmIKWowf9dje7GurgbrbB0n8ABJF7kEJJ8XhgSk1B8+EjnfZHZGWAWfTQi0iJR8uJahz54Au/59/SLwFp+aMh6XUqRheeJJ0GDeXVsFXW45LbLwMgwO1w4fO/v4MR37sUooYbi0LNaXecsd/tdIcoEiIKFCbR+4CcnBwkJSVh9erVfjXRgVMH/K1evRrJycnIyclRMcq+bf/+/VAUpcNzf+DAARWj6ttiY7tXQ6674+jcJCYmBnQcdV/7guiiRYuQm5uL6dOnw2AwwOFwYMuWLVi0aJHfOCIi6iZBgLu58/IgXo8bHnszNCazCoGFL0EU4WpqQuwlI1D/za5va6MLAiIHZp36XnGDbcgJoogj7xd3aG85Xo2mshPQxbCcX6hJWg2Gf+9SNJ+sx9drNsLRZIc1Mwn5s2+Bosgdyr5S8EWc4fBQjV4Lg9kYwmiIKBCYRO8hHA4HysvLz/vrb7nlFvztb3/DQw89hOuuuw6pqak4ceIE3nvvPezcuRM/+9nPcOjQofN+/PT0dBgMhvP++r4qNTUVAPDVV19h7ty5KCgo8Dvg76uvvvIbR4GzadOmbo+76667ghxN+ImKigroOOq+7OxsSJIEg8GAgwcPorj42zex8fHxMJvNcDgcnd6ZREREXfN6PHDbGrvsdzU1QG+Nh8B6zyEjShL0sVY07tqDuLGj4JVPldSR9HrYj1dAG2GB1tR1uRcKjsaDx7rsq/p6L+KGDwxhNAQAgkbEoU++wf4N231tzVUNOPbVflz20A8AiatNoSZKIi669GLs/mxXh76xN4yHKHFhg6i34QywhygvL8e99957wY9TUlLSaR3cFStWXNDjrly5kmUxOjF16lSsWLECBoMBhw8fxuzZs319SUlJvmTW1KlTVYyyb/J08xCp7o6jc2M67Q2rKIpQTqsRe/rnJr6xDbjS0lLIsgy73Y7WVv8DiWpra32H6ZaWlmLUqFFqhEhE1DsJwhnLtQiiBLCucMhpjEYYE+NR88VXECQJgihAcZ8q82JIjFc7vLDkau76QETZyfNw1CA7PX4J9HaKR8bXr3yC3HtvUCGq8NZY1YC82/IRnRiNbe9thbPVCXO0GbnfvxQpQ/qhtcmOqHhuOCLqTZhE7yHS09OxcuXKC34cRVHw2WefYdWqVbjjjjtw6aWXBuTWrfT09At+jL5Ip9Nh2rRpWLNmDbRaLW677TakpKSgoqICH3zwAex2O26//XbodKwLGGiRkd/eHqfRaJCRkeEraXHkyBFf8vz0cRQ477//vu9j5TuHrJ3++fvvv4+bbropZHGFg9raWt/H3u/UgT3989PHERHR2YkaDfRxifCUH+603xCfCJEHloecxmiAuX86jMmJcFTXQvHIMCbGQ9TruAtdJRHpSajavhcxA9NgHZIBUSPBXl2Pmm/2Qxdp5mKTCmoPngBEYPCVlyBt9GCIkgRnSxt2v/slag+cgMz62yEXEROBL9d9gWF52Rh26cXwuDzQ6DRoqmnEwa37MfLqS9QOkYjOEZPoPYTBYAjYTm9RFLFq1Srk5+dz93gI3HfffQCAtWvX4tVXX/W1S5KE22+/3ddPgdW/f3/s3r0bAKDX6zF16lTk5uaiuLgYK1as8CXR+/fvr2aYfZbd3r3T5Ls7jrrv9ANDx40bB4PBgJaWFlgsFl9d9O+Oo8BzuVx48803UVFRgZSUFEydOpULpkR9gNZsgTYiGu7mRv/2qBhojEzYqkVj0AMGPXTcHNEjGOOjMeS2q9CwvxxHPiiG7HLD0i8BmddOhMak5yGWKhAkCVfPKcDx7Qfw6V/fgMvuQHS/eFw8dSJaxwzhwoYKBFHAsLxsrF/xNhIyEmGJiUBjVQNa6ptxxU+uhlfmochqcbQ5UV/dAGebE3qDDtFx0TBZWKOezo5JdKIAuO+++zBz5kwmVELo2LFvazHa7XY888wzZx1HgZOUlISysrJujaPAampqAgBotVp89dVXHUrpaLVauN1u3zgKvBUrVmDt2rWQ2w+4+1/btGnTuHBK1MuJWh3M/fpDdiXCWV8HCIA+Jg6STg9Rq1U7PKIeQXF5cGzjNrRW1fnaWo5XY/+JjzH0tqvhVZgcDLXEwf3w9asb0VLdiIGXjYDOZICtsh5f/ONdjJtxNQwRXAQMNY9bxv4v9+Dqn16PfcW7UXe8BnHpCRh30wQc+mo/Rl07Ru0Qw1LNyTp8sPZjvL/2EzjbnNDqNMi/fiK+N/MGxKfEqR0e9XBMohMFSHtpF+q+CzlQt32nuSRJfomsdu3tHo8H+/fvP+8Yeahu57p7WC4P1Q28mpoaAIDb7YZGo8GIESMQGxuLuro67Ny5E263228cBdaKFSuwZs0axMTE4O677/bdAfP8889jzZo1AMBEOlEvJ2q1ELVaaM0RaodC1CO5bC1oraqDIAqwpCZA1GjQWlMPd0sbjm/ejqwbJqkdYthxtjqQODQdKcMzUba5FA5bK6wZicj96Q0o37oXUf3iYYhkIj2kBAFJWcl4deFq38LSkZIybH9/G2755Q8g8rDXkLM32/HWS+vx/qsf+9rcLg82vFGEpgYb7nnsx4iJj1YvQOrxmEQnChBZllFSUoL6+npYrVbk5ORAYt3MMwrEgbqdJdBPb9+7d+8FXYOH6nbutdde6/a4Bx54IMjRhJfY2Fjfxx6PB9u3dzxE6rvjKDBcLhfWrl2LmJgYrF27FhrNqWnUjTfeiGuvvRbTpk3D2rVrMXPmTN6JREQUYLLTCdnlAhQvRJ0OGiM3OajFVl6FhEuGIn74ICgeD7weGZJBB7e9DYfe+hT4znk5FHwuuwO2ilqUfb7b13ZiRwsqSsqQe891UDydv2ei4BEEAR8+v77DnRmy24MNL3yA6fMLVIosfDXW2rDh9aJO+77atAPT7/8ek+h0RkyiEwVAUVERli1bhsrKSl9bUlISZs2ahfz8fBUj69ku5EBdl8uFBx54AIIgQBCEDiUtvF4vvF4vnnvuuQtKZvFQ3c599zDRCx1H3dfa2ur7WKPRICcnx7cTvaSkxHeXxunjKDDefPNNyLKMu+++25dAb6fRaDBz5kw888wzePPNN3lnEhFRgHi9XribbKjdtgOuxlOlyiSTEbGjRsAQZ4Wo4VvaUIvMTIbObET5x1vQfKwKAKAxGZCaNwJDp18NiKLKEYYfvdnol0Bv51UUlL79BSbed6MKUYW3tuZWuNpcAABjpAnmKDOa65vhtDvQWNUAj8ujcoThp6XZDo+76+e9vroB6QP7hTAi6m044yC6QEVFRViwYAEmTJiA6dOnw2Aw+A73W7BgAQoLC5lI78KFHqibl5eHzZs3Q5IkDBo0CPv27cOQIUNw6NAheDwe5OXl4eKLLw5gxETq83q/3c3i8Xjw9ddfn3UcBUZFRQUAIDc3t9P+9vb2cUREdOE8ra04uWkzvJ5vEx9yaxuqN3+B5CvyoY+JVi+4MGWMicKel9fD3fLtgr2n1YGjH36JgVMvQ0SkWcXowlPDseou+5oq6rgTXQWKrMCaEovJP7ocHo8MW00TYpKtkN0efPz/PoKXm41Czmg68x1MZr520VkwiU50AWRZxrJlyzB48GAcPnwYxcXFvr7ExEQMHjwYy5cvR15eHku7BMGiRYvw+OOPY/Pmzdi3bx8A+P6fl5eHRYsWqRleWBFFESaTCa2trdx9HmT19fUBHUfdl5KSAgAoLi7GjTd23NHV/jegfRwREV0Yr9cL+/EKvwT66RpK9yJ+/GhIPPQ1pFoqa+FuaYXWYkTMoP4QtRq0VtbCVl6JE5t3YNAPrlQ7xLAjStz939NExUfhmnuvx7olr8Pe2OJrj0m24pZHfwC9mSWpQs0SZcawUYOxZ3vHM9OS0hIQFcOzUOjM+EpLdAFKSkpQWVmJffv2YcCAAVi6dCneffddLF26FAMGDMC+fftw8uRJlJSUqB1qn7Vo0SK89957uOyyywAAl112Gd577z0m0ENMURS0tLQwgR4C3a11zprogTd16lRIkoTnn3/eVzanncfjwQsvvABJkjB16lSVIiQi6lu8igJnTV2X/a7Gxi4T7BQ89ooapF0+BmmTR8PZaEPzsUqYk+MxZNpVUGQF4N1wIReVEgtB6PygyriBKRBYYkcV7y57CzqjDpfdcSVu/PlU5N2WD4/TjaKXP4HI70nIWeNj8LN5P0FqZrJfe2yiFY/+cTYSUuNViox6C+5EJ7oAtbW1AIDx48dj4cKFvj+E2dnZWLhwIebMmYMvv/zSN46Cw2g04kc/+hE2btyIH/3oRzAajWqHRBQ03S3TwnIugafT6TBt2jSsWbMG06ZNw8yZM5Gbm4vi4mK88MILaGhowO23385DRYmIAkQQRWjMpi77NUYjk4MqiB6UjrqdB3Gs9JCvzX6yFjU7D2DgzZOBLpK5FDySXosRt+Zjx9pNfu06kx6jbrsMkoZ3RYdaW3MbRl51CczRFmx7bwsaqxoRn56AKXdfi6M7y+ByutQOMSwlpyfisb88hLrKepw4chKJ/eKRkBKHxH4JaodGvUCvmHEsXboUGRkZMBgMGD9+PLZs2dLl2NLSUvzgBz9ARkYGBEHAkiVLQhcohZ3GxkYAwKRJkzqsJIuiiEsvvdRvHBHRhWppaTn7oHMYR+fmvvvuw+233w6bzYZnnnkGt956K5555hnYbDbcfvvtuO+++9QOkSjoODenkPF6Ycno+pD3qCEDwSXj0NPotKgtPQRdpBlJYy5CSm4OojJT4Gl1oPqb/RB42GvICaKImP4JyLv/JvQfPxSJw9Ix7NqxyL33Bsgemb8nKhAAeNwevLt0HaoOV8Jpd+D4nnK8/se1SBqQfNavp+BJSInDsEsGY8r3J2P4uIuYQKdu6/F/3V555RU88sgjWLFiBcaPH48lS5bgmmuuwb59+5CQ0PEHvbW1FVlZWZg2bRoefvhhFSKm3sbhcKC8vPy8vratrQ0AsH79egwcONAvka4oCt5//33fuP37O9bd6o709HQYDKyXRkSnHDp06OyDzmEcnbv77rsPM2fOxJtvvomKigqkpKRg6tSp3IFOYSFc5uZeRfGVCRE0Gu52Voni9QKCAOvI4WgoKfU7iC8iKwMaiwVemaXkQq1+/1GkXzkOkk6LutJD8DhdiExPQtLYbBzdsAVeN0vshJrH4cKnf30DXq8XycMzYYmLQs3BE9izfiv6jR6E4VMnqh1i2NFbDCj+72ed9n3yr49w15/uDXFERHShenwS/dlnn8VPf/pT3HXXXQCAFStW4J133sELL7yAxx57rMP4sWPHYuzYsQDQaT/Rd5WXl+Peey/sD9iuXbvOuPvwhRdewAsvvHBej71y5UoMHjz4fEMjoj6mu+WhWEYquNpLuxCFm3CYm8suJxzVlXA1nTqgWRdthSE+CZJOr3Jk4UfweuGoqgYAJF0+CZ7mFiiyDF10FDwtdjTt2Y+YnGyVoww/lpR41O0pQ/2eMl9ba1U9ancdwoCbJgPc9xxyLdWN8DjdAIDj2w749Z3YfgjZN0xQI6ywZqtpOnVGQCfamtvQ1tIW4oiI6EL16CS6y+XCtm3bMGfOHF+bKIqYMmUKiouLVYyM+pL09HSsXLnyvL5WURQ8/vjjsFgsaGlpQV3dtwcfxcXFwWw2w263+9VLP5/4iIjasSY6EaklHObmsssJ28G98HrcvjZnXQ1ctkZEDhjKRHqIKV4vBFGC7Hbh5IZNEHU6CKIA2eGEKTUJxpRk/r1TgdZk8Eugt/O0OVH9zT6kXzFOhajCm9Pu6LLPqyh+d3FQaIjSmevQ82BRot6nRyfRa2trIcsyEhMT/doTExOxd+/egF3H6XTC6XT6PrfZbAF7bOr5DAbDBe30/sUvfoEFCxZgwoQJyMjIwMsvv4wf/vCHOHLkCL744gsUFhZi6NChAYyYiMKZwWDwlZI62zgiokDq63Nzr9cLZ0OdXwLd1+d2w9XUAENcIgQemhgykiRBGx2J+qLPAUGAxnTqIFHF7UHriUoY4uPPmqiiwGs4cKoUZlRmCqxDMyFqJNir6lBbchAN+8uRdtkYlSMMPzHp35bTikiKgc5kQEtNI5zNbTBEmSHptCpGF54irBbozYZOFzisqbHQm7goS9Tb9OgkeqgsXrwYhYWFaodBvVR+fj4KCwuxbNky3y6sl19+GcnJySgsLER+fr7KERIFnyRJ8Hq9EAQBsiyrHU6fFhERgYaGhm6NIyLqjdSam3s9Hribun59dTU2QB8Tx0MTQ0iRZdiPHoMlsz9MKUlw1tXDqyiIHDwQ7uYWNJcdhTGJB8KFmiBJGPT9K9B8vArHNn4F2elCRHoysm6chMqtpazmogJREjFgUg6SczJhO1kHR5MdAyYNBwDIbhmCyMW/UBM0Em5+6Hv47+9f8SvrojXocOODt0DScgGQqLfp0TPAuLg4SJKEqqoqv/aqqiokJSUF7Dpz5szBI4884vvcZrMhLS0tYI9PfV9+fj7y8vLw7rvv4plnnsGjjz6K66+/HhJ3xlCYYOI8dLp7EPL5HphM3SPLMkpKSlBfXw+r1YqcnBy+5lOf1+fn5oLgd4CoIJ16q+SV/3fAqCgC3IUeUl5FgS4mGnJbG6o3fwlRp4UgiLDtPwRjciKiBg9kmQoVxF2UiUPvfAb7yW/PX7EdqUBzeSWGTL8KgoZ/D0OtpbYJyTmZ+Pxvb0PxfDsvj0iMwfi7roHb4VIxuvAku2VExUdj5rM/Q+mmEtRV1CF5QAqG5A6DIitwO3kAr1paW9rQVG9Da0srjGYjImMiYIk0qx0W9QI9Oomu0+kwevRobNiwAbfccguAUzWoN2zYgAceeCBg19Hr9dDreSsNXRhJkjBkyBAAwJAhQ5hMoR7P4XCEJNG6f//+8/q69PR0liShHqmoqAhLly71SyQmJiZi9uzZvPuI+rS+PjcXNRro4xIh2hqhi7b6am0LggBnQx300VaWDgk1SYI2IgJtJ6uQkDsOXngB76kdnq0nTkJ2unyLHRQ6rpY2vwR6O6+i4MTmbzDgRv4tDLWoJCs++v0avwQ6ADRXNWDP+q0Y8YNJKkUWvgQRqC6vwrZ3tmLirZdi8IShaKpuwrpnX8PkO65AbGqc2iGGpfqaRry9+gNY46MQlxiLxvomVBw5iZvvvA5xSbFqh0c9XI+fcTzyyCOYMWMGxowZg3HjxmHJkiWw2+246667AAB33nknUlNTsXjxYgCnDjzavXu37+MTJ05gx44dsFgsGDhwoGr/DiKinqa8vBz33ntv0K9zvtdYuXLlBZ1XQBQMRUVFmD9/focEX2NjI+bPn48nn3ySiXTq0/r63FxjMgOiCHi9kO0tp9rMFuhj4iAZjCpHF34EAC6bDREDsyAIgLOuAV5ZhiHOClNyIuQ2B8Cd6CHXePBYl33N5ZVQPNxhG2q2qgbI7s6f94qSwxh+S16IIyKvR4GrzYUhucPwwcp30VTThNh+cZhwy0RUH6lCTJJV7RDDTpu9Dbu27EZKeiLeWf0BKo5WIj45FldPuwJ7tx9AzgQdImNYEpO61uOT6NOnT0dNTQ3mz5+PyspKjBw5EuvXr/cdaFReXu53qnFFRQVGjRrl+/xPf/oT/vSnP2Hy5MnYuHFjqMMnIuqx0tPTsXLlyvP62sOHD+P3v//9Wcc99thjyMrKOq9rpKenn9fXEQWLLMt49tlnzzjm2WefRV5eHu9Goj6rr8/NvYoMd2M9FI8bWkskAMBRWw1Rp4NBmwhAp26AYcYryzDEWtFaUYmmvd/e2WbbDxiTEhGdPZTlt1UgGbr+PRBZykUVzuauD533Kl6/mtwUGh6PjOqySny9/itfW93xWrzz3DpcfucU391OFDp2Wysaapvw77/+x9dWc7IOq/9vLa67fQoGZGcwiU5n1OOT6ADwwAMPdHmL6Hcn3xkZGXwxIiLqBoPBcN47vQcPHtytJPq11157Xo9P1BPt2LEDjY2NAE6VsDhd++eNjY3YsWMHRo8eHerwiEKmr87NFVmG7GiDLtoKj70ZzvpT5Sp0UTHQmC2QXU6Iej1EkUnCkBFFeGXZL4Herq2yCsbkRBiTE1UILLzFDO6PE5/tAAQBlpR4iFoN2moa4La3IT5nMEQevhtyMf0TABEYMmU00i4ZBEES4bI7sPvdLbDXNEGj06odYtgRJRHbP9jWad/n//kUg8cPDXFE5HS68PoLbyN9YD9cccskxMRHo6XJjo1vbcb7az/Gld/j3aR0ZvzrRkRE52Xjxo247LLLzthP1Jds377d97HwncMFT/98+/btTKIT9UJeWYYoaWE/cRSKy+lrd9RUQrTpYUrpD6+sAEyih47Xi+ayo112Nx88DENifAgDIgAQNBoM+t7lECQJzceqIDtdiMseAFEjwpQUB4hnfwwKLI1Bh2vm/hjlW/eh6K9vwGV3ICo1DsOnToQhygxB4qHIodZS3wKv0vkisrPVCVcbD3sNtdbmVlz/w6sw4KJMeL0KPG4ZMXFRuPnOa9FY24SG2iakDUhVO0zqwZhEv0BVVVVoampSOww/R48e9ft/TxIVFeW73ZeIer+NGzdi9+7dmDVrlq9t2bJluOiii1SMiig4KisrfR+7XP5vfE7//PRxRNR7eAXA3drsl0BvpzidkNvskIwmFSILY14vFFfXiSbZ5QZYpiLkRAFwtzpw5P1iX1v1jn0wJVox8ObJ8DLNEHKiKOLrVz9B1e5vcwBNJ2rx2bJ1yP3p9TDGWFSMLjzpDGfe/S9p+XsSakaLEcPHX4QvN2zDx28UwelwQaPVYOLV43DFLZNgjODZJ3Rm/K29AFVVVbjjx3fC3clEuydYtGiR2iF0oNXpseqlfzGR3stx8ejc9eUFpIsuuggrV67Evffey8NAu8nhcKC8vDzo19m/v+Pt792Rnp4Og8EQ4Gh6v+6WpOgtpSuIyJ8AwN3U2GW/y9YIvZW7nkNKFGFIiEdbZXWn3Ya4WAgitz2Hmuz2+CXQ27VW1aN6x34kjc1WIarw5rI7/BLopyt57TPkP/g9INIc4qjCmznaAlOkCfHpCRh+xUjoTXq0Ntmx/YNtkD0yDBb92R+EAkqr0+Kz977AR69t8rV53B4UvfM5Wmx23PnwdBWjo96ASfQL0NTUBLfLibasyVAMUWqH0+OJjibg8CY0NTX12WRiOODi0fnhAhKdrry8HPfee2/Qr3O+1+BiSOdkWQ7oOCLqgYSuE7ICBC6ShZggCDDEx0EyGiC3Ofz7RBGRg7IAJtFDrvFA1xsBqr/Zh4RRrPUcanWHT0Kj1yLr0osRP7gfFFmBV/Hi6Jd7cHJnGTwut9ohhh9BwB2LfoJ9X+zFif3HoTfp4bA7MOLKUeifk4lTS7cUSi6HC5+s+6zTvq8//QbT77sltAFRr8MkegAohigo5ji1wyAKCS4enTsuINF3paenY+XKlef1tfPmzUNVVdVZxyUmJuKpp546r2ukp6ef19f1dcePH/d9LAj+ybTTPz99HBH1LrpoK9ra7J33xVgBJtFDy+uFoNUibuwlaD58BK0nTgJeLwzxcYgcPACiXg+vwnIuoeayt3XZp7g8/D1RgTHGjNyf3oADn+zA/o+3A15Aa9Bh0BUjET8oFaKGZzmEmldRULH/BAaPHwqPyw1nqxMGixGSRkLVoUqkDO2ndohhp83ugOzperNLU70thNFQb8QkOhGdFy4eEZ0/g8Fw3ju9ly9fju9///vdGme1Ws/rGtS56upvywlotVq/Ouinf376OCLqTQRIej0kkxlyq38iXWOyQNTqWDokxLwAvC4XFI8bppRkmNNOHfjmlWUIogjF4YBkYg3bUIvqn4zqr/d22mdJTThVNJ1CKrpfPDaveBu2ijpfm9vhwu53t2D4LXnQmVg6JOQEoN+wdLzxzH8gaTSIiI1AQ2U9TFEWXHvv9RD4axJyhrP8HphZ8ojOgrNAIiKiXsRqtZ41Od6dMXRhvlvSgSUeiHo/SasFIMCUnAZzWia0lkhoLZEwp2fBmJQKQRAhargHKaQUBa0VJ9GwoxTweiHpdBC1WogaLRp27UHj3v3cia4CgzUKpsRO5hmCgNS8ERAk7noOtdaGFr8E+un2fbgN7rauD+il4BAEAcWvb8Zld1yJjBGZkLQShuVlY+yN4/HVe1sgclE25CSNhGGXdL6RKTk9EXqDLsQRUW/DWSD1Wjzc8tz05YMticLNa6+9hu9///uor6/v0Ge1WvHaa6+pEFXvcCGHuiYnJ8NmO3Wbp/KdpM3pSfTk5OTzPtQV4MGuRGpRPG6IGg3aqiogOx3QWiIAAG2VxyEZTTDEJUORPRAlvoUKJdnlhnXExWjYtRvu5hYAgGTQI/qioXA2NLJ0iApklxv9rxyPuj2HUVt6CIrLA0u/BKSMHw6dxQzwbJCQazxe02Wfy+6A7PKEMBoCAI/Lg6xRA7B20ct+JUT0ZgNuefTWM5YVoeDwuDyY+esC/N/jK3Hs0Alfe1xSLH7xu5/BxbMD6Cw4A6ReiYdbnjsebEnUt7z22muor6/HAw88gIqKCqSkpOC5557jDvSzCNShrt89PNTj+fbN6b59+y7oGjzYlUg9stMBd/OpTRrO+m/nmYrLBX10LOBlSYRQEiQJlvR+qPq0GN7TXndlhxN1X3+DhInjIIjc9RxyXi88bQ7EDOqPqMxUCIIARZahizCj4VA5YodlqR1h2LHERXfZJ2okSFqmfkLNq3ixfvnbHZLlTrsDG/75Pn7w2HSVIgtfOr0OL/3lVdw//y442pyoOFqJhJQ4RMZE4L//eAs/+vmtaodIPRxfSalX4uGW54YHWxL1TVarFU888QTuvfdePPHEE0ygd8OFHOqqKAoefPBBv1ro36XT6fB///d/F3SLLg92JVKH1ws467o+08BRWw2LOSKEEZFXUdBWXeOXQD+d7eBhxI4ZFeKoSJAkeAHoIi0AvIDXC1ErwV7VgIhUvtdQQ2RSDHRmA1x2R4e+/hOGQWPQqhBVeHPYHWhr7vwQ3tpjNfC4eXdAqLncblwz7XI8+5vlsDU0IzImAi02O7RaDWY/eTccrR1/f4hOxyQ69Wo83JLCEUsZnRuWMqLTXcihrgAwd+5czJ8//4z9Q4cOPe/HJyIVKcoZ62t7FZn1t0PN64WrrqHLbleTDV4PE1GhposwQhBFHHprI1qrTpWWk/RapOaNhCkhBoLEWs8hJwqY9MBUfLbsLTibW33NicPSMfSq0fAqLHsUap6zlNBRZP49CTVRFPHKijdQW3nq/ID2/zsA/GPxKvz62Z+rGB31BkyiExH1IixldO5YyogCKT8/H08++SSWLl2KqqoqX3tSUhJmzZqF/Px8FaMjogsiCNBGREJ2dL5zUBsRBQhCiIMKc6IIjdnUZbfGZALA70moyS4P9r7yPjyn7dqUnW6Uf7wVWrMRUVmpKkYXnlqqGmFJiMbkX3wPDlsrnC1tsMRHQWvUo7WxGcZIi9ohhp2o+CgIotjp4qvBbIDRYlQhqvCmeGQcKi3rtK+2so410emsmEQPALGtUe0QegU+T0QXjqWMzg1LGVEw5OfnIy8vD++++y6eeeYZPProo7j++ushSazLS9SbCYIAXUwcnA11HXY3CxotdNFWCEyih5bXC0tmfzQfPtJpd9TggRAuoHwWnZ+WE9V+CfTTHf9sBywp8dAaeUB2KOksBny29E0MuWo0rFlJMESa4fV6se+jrwGvF0OuHqN2iGHH4/Zgwi25KH5tc4e+y+6cAoUH8Iacy9l1SUYAaGvpfBGdqB2T6AFgLCtSOwSikOOiSPcF47liKSN1sJTOuenLpXQkScKQIUMAAEOGDGECnagP8MILr6LAkj4AzvoauGyNAABdVAz01rhTuwm9LIkQaorsQdy4S1C37Ztva6MLAiIHD4BkNMDLdY2Qa6mo6bLP2WBj6RAViJKIkdPy8dWqj9DWaPe1J2VnYED+cIgif1FCrbXJDlO0BdfNuglfvvk5GqsaEZ8ej4k/uBQn9p9A8sAUtUMMO0aLEVq9Fm5nxx3ngiAgOo6b1OjMmEQPgLbMfCjGaLXD6PHEtsaALzgwkds9wXieuHhE4YaldM4dS+kQUW8jt7ag9eRx6KJiYE5NB7yAu8WG5sP7YUpJh6jVqR1iePECtr0HoLFYkHTZpZDb2uCVFWgsZjjr6lFTvBWJky9VO8qwY4yL7rJPazGx7JEKNHotjn65FxdPzYNGp4HL7oQx2oyG8mq4HS7WqVdBRFwk1hSuQmy/OFxy7VhYYixorGrAJ//aAGerA5dcO1btEMOOJcqEm358LV77x1sd+ibdkAszS+zQWTCJHgCKMZo7QlXCRK56uHjUfcFYQKLQYymdc8NSOkTU63gBZ2P9qcMsG+vhaqz363Y11kMbydf/kBJOldJpPngYzQcPQ9TpIGgkyK2nbrnXWMwAc4MhF5WRAlEjQfF0LEeRPC4boo5phlCrP1KF9HFDUXuoAqIkQGc2omrfMUSlxqLpeA1i0hPUDjHsOOxOjL1xAr5883N8c/9ppAABAABJREFU9Px6v76r7rkOspuHIoeas82N1MxkTPvZVKx/ZQOaG1tgNBtxxS2TMGTEQLjOchgsEf+6Ua/GRG73BCWJyx0m3ReE54p3YXQPS+n0HSylc+76cjkdoqDweoFODoDzdSsKwCoVIWdJS0Xr8RMAAMXlAk4raWtJ76dSVOHN1dKKIbddhQOvfwJP2//u0BMExI8YhOgB/eBlcjDk3G1OtDW0ICrZioNFJXA0tSI2KwlmaxbKv9yL/uOHqR1i+PF6YYoy4br7b8RX72xBY1UD4vsnYtzNE3BsdzkycjLVjjDsOOwO/PXxlcgePQQ/fug26I16eNwebF7/Jd7994d46p+/VTtE6uGYRKdejXcBhF5UVBS0Oj1weJPaofQqWp0eUVGB273Gne0UTlhK5/ywnA7ROZIkaKNiIDs6P1hMFxUDL+sKh5ziccPSPw0tR4/5teutMdBFRQGsvx1yWrMJ1d/sx0UF18Pd2gaP0w1DTATcrQ7U7S5D/MjBaocYduKHpOHghu0oef0zX5u9tgnHvz6IiffeAK1Jr2J04ckUacK297ZCq9ci58pRp8q5VDbg4//3ISJjI6E1aNUOMew4/rfoV7ptH0q37evQ39Jk79BGoVFVWYN9uw9ia/EO9EtLwsTJ45CYHA+drmeV0WMSnXo10dGzdiX2VIF8nhITE7HqpX/1yB2hixYtwuOPP47+/furHU4Hgd4RyrswuoeldPoGltI5dyynQ3TuvB43dJHRcNbXwOv2P3RM1OqgjYiEICt8BxViolYLyWRE/ISxaKusgldWYEyMh1eR4WxshNYarXaIYaelsgaR/RKw84U3IWo0kIw6uJpaEJWZgn75o6GwJELIeT0yDn26s0O74pGxa10xJv7sBhWiCm+iJGDanNvx8hMv4ZP/96GvPToxBjc+OBVe3toUcuZIEyRJgix3LEUFALGJMSGOiADg+LGTeOs/72P8pZcgb/JY6HQ6bC3ejn79UzFydHaPSqRzChgATOR2TyCfJ+6GPneB3AmdmJjYY5My/fv3x+DBYbD7heV0uoeldFQTlOfJyzcb3cbniuicCaKEtpPHYe6XAXdTI1y2BgACdFHR0EZEw1FbBWNSitphhh3JaITzYBlsBw7BEB8HQRDRsGs3BI0G8eNGA10kQyh4NFotanYdwkV33gBHXRPcrQ5YUuLhqLehfMMWZF3Pw15DreZgRZd9jcdr4HG6u+yn4FBkL8p2HcGdv5+J2uO1qD9Rh8TMJEQlRuPgVwcwZMJQtUMMO1qdFpdPvRQfvdYxjzRq4nBotEyRhlpLsx3VJ6tRdbIaM2/7BZT/ldUbNDQLT/7xN6ivbUBSSs/JPfEn5AIwkXvuApXI5W7oc8fauH0DX3fOHUvp9B187ns/h8OB8vJytcPoUnp6OgwGg9phkGq8kB2taCmrhzYyGsbEFMALuFua0HLkACSjiTXRVWA7cAjmfskwpybDfrwCiuJGxIBMaCMiUP/NTsSOHqV2iGHHGBcNZ4MNpS++BX2UBaJOi+ObtkGRFQy57SqAiaiQk7TSGfsFkSfwhpwA9BvSD0X/3gi7zY6kzCQUrdmIxMwkDL8sh/sdVNBUZ8OYySOh0Wqw4fVNcLs8ECURE68ehynfn4yayjqk9E9SO8yw0mpvxaYNxXjtlXf82g/sPYxH71+ApS8+rVJkneNftwvARO65C2Qil7uhKRzxdefcBXoByZF6Cbw6S8Aer68SXC0wnPg6oI/JMkbd11NLGZWXl+Pee+9VO4wurVy5kn+/w5xkskB2OuC2NcJta/Tr05jMTKKHmtcLxeVC3dcl0JhNMCYlQhAFtFZUwtWwF6JeD/DmvJDzAhhw82RUbi1F3Z4yeJtaYEqMRb9LR0JrNp7xgF4KjrisZAiCAG8nmdnYAcmQ9Ez9hJooijCYDRh2aTYkrQYelxv9c7IAADqjni9dKjBHmlB43x8w8epxeOwvD8Hr9UIURXz58TYsnPUMFr80T+0Qw47d3oY1/3qj076K45WorqrFgEEZIY3pTPhKeoGYyCWiUOPrjjp8dwEEODHclwX6LgCWMToHAX6u9u7di2PHjp194Fm43W7MnDkzABEBtbW1WLduHW6++WbExQXmkPGDBw/i6NGjF/w4aWlpGDqUt2n3PgL0MbFwNdZ1LIkkCNBFWwHu5gwtUYQxKRFtldXw2FvRfKjMr9uQEMdElApkpxteWUbiqKFIHDUUXkWBIEnwtDmguD2QtDwwMdRkj4yc71+Kb/77qV+71qDDJdMvh1fmwkbICQJqj9XAYDbAYDZA9iiQNCJaGu1obrAhPr1nvp/ry0RRxOQbJmLD60Uoevtzv75ReTm8Y0MFjjYH2lo7P9AdAMoOliP30jEhjOjMmEQnIiLqBt4FcO4CdRcAyxidn0AtYlRVVWHWrNlQlJ5Zd3jdunVqh9CBKEp4+eV/99gFT+qCIMALwJKehdbKE1CcDgCApDfAmJQKLwQIXMwLLa8X+lgrJKMRcpv/m2xBkhA5IJMLGypwNNigj7TA1dIKUauBV/FCEN3wKl40HjqO+IsHqB1iWBJEAZf/choObSpBa0MLEob0Q7+RA3H8m0NIHzdE7fDCTmujHYmZSbA32rHjo+1wtjphiTYjOz8HWqMObc2tiIoL4GYTOitbQzMGDx8ArU6Dj9/4DC6nC5JGQt414zBm8ijUVdYjLYtnn4SSwWiA0WTsMpGenpEa4ojOjEl0IiKibuJdAOrgAsb5CdQiRlNTExRFZimjbmovZdTU1NRjXy+oc4IoQNJo4WprhSE2HqJWBwBQXC7Ibhe0egPviAkxURCgSBLixo5CS9lR2E+cBBQFhoQ4RA4aCFGrhVdhjZ1QsyTFYe+r7yPuogEwJ8fBqyhQ3DKqd+xD3PCBkIx6tUMMP14vYvon4svn30P84H6ISU9A7aEKVO0txyU/vAICf01CzmDW47NXN2HPZ6UYNG4ILDERqK+ox4u//jsunT4Z2ZflqB1i2DFHmvCP36/C6PwRmF14NwBAFAVs+/Qb/OW3f8PvX5qvcoThxxobjVt/dCNe+sfaDn0p/ZKQ3p9JdCIiIqJzwgUM9clR/aCYA1M2pS8T7bUs+9RLCYIIR2MttFFWCADkNjsAARpLJAAFLlsDjPHJKkcZZkQRsssFSaeDKSUJ5n6ndggqsgLJYIDscEBj4eJeyGklDJp6OQ6+uREVxSUAAEESkTzuYkT1T4Hs8kBrVDnGMKMx6FH67pcYcWs+PC4PnM2tiB+cCnutDdX7jiF93DC1Qww7skfBzk9KAK8Xez4r9ev74vXNuOjSi1WKLHzpjXpc+b1JWP/Kx/jio6/8+sZMHgmdUadSZOFLkiTc/uPvodnWgnX/eR/K/87UGDQ0C7//yzwYTD3rjwmT6D2Ew+FAeXl5QB6rvZZnIGp6tktPT4fBYAjY4xEREVHvIjp61p0APRWfp97LK8tw25rgqK6ExhIJXYwV8AKtJ8vhaWmGZDTBYE2AoOFbqFASALRW1UAbYYZo0ANeQJAV2I+fgDEpHoLAci6h5nW5IRl0GHLb1ZCdLigeGVqzEV4B8LQ5oDHzfWOotTW1oGLHYVTsOAyd2QCtUQdHkx2yW4bObEDKxZlARM9KRvV1TTWNgNcLizUC+T+6HOZoC5qqGlD08idwtDjgaOm6DjQFh+yRce30KdAZ9Phg7SdwtDqg1WmQf8NE3HzntTxjQwXNzS146fm10Ol0+Ms/FsHldEGn0+HokeN4/OFFePJPjyEhMVbtMH04A+whysvLce+99wb0MRctWhSwx1q5cmVY7LIjIiIif6xJf+4CfqguhYYoQJAkAICnxQZPi82/W9KwnEuIiZIEUauFMS4WisuF1uMV8MoKDPGxMCUnQtTpIGqYRA81xSNDcTvham6FpNXAKyvwtDkgGfUQtRqApUNCrulEne9jl90Bl93h97ns9qgRVlgzmA24YfZNiE1LwJZ1xWiorEdCRhIKnvoJ9n25Bxo9D+ANNVOEEYdLy3DpNeORf30unA4X9HodIACHdh/FsEsGqR1i2GlrdeCNV9+Fw+HEq6ve7NBfXVmLodk95/vCJHoPkZ6ejpUrV6odRpfS09PVDoGIiIhUEMia9O115HuqQNW3D1Q9egotUdLAEJ+EFvvBTvsN8YkQ/5dkpxDyelFZtBleRYHeGgNBENBy9Bi8Hg8SJ+VCazGrHWHYUdweuGz2U4eKer2AJEJxe6AB4Gl1QmvkTvRQM1sjuuyTtBJEDV+7Qi0yLgo1x2rwr8ee97VVHa5E6aYSTHv8RzBH8bUr1FxtLqRmpaKhphEb130Gp8MJrVaLvGvHY3BOFmS3rHaIYcfj9sDhcHbZX3myOoTRnB2T6D2EwWDgTm8iCimWkaJw1NN/7oGe+bMfqJr0vWHTQE977im0NCYz9NY4OOtr/dr1sQmQjCaVogpfiizDfuwEvPKpxIazrt6vv2nfAWgjLNAYWaYilFwtbTDGRaN6+z5oTAZIWg2cthZYUhOgj4o4lVinkNJHmqAzG/x2oLdLHzsUgsi7aELN7fLgg7+/16FdkRW8t2wd7lh0lwpRhTd7SyvqKhvQLzMF37v7Rridbmh1GkAAyg+cQFRsJOJTeP5PKEVEWmC2mGBvae20f8CgjNAGdBZMolPY6+kJFb6hp2BhGSn18HVHPT395x7o2z/73DRAPZ2o0cKYlAp9bALctiZAALQRURC1OoishR5yXkWBq7Hru2BcTTZ4ZSWEEREAmOKisXvVu4i7eADMSbGA4oVk0KNySymiMlOQPJ4HJoaas7kV435yDb566UM4bN8moxKHpSN5eCa8Mhc2Qs1W2wiP091Fnw1trIkecpIoYe+OA2isa0JLUwvMkWa02R2QJBEet4y4JKvaIYad+IRY/OTe27H02Rc69KVnpCItI1WFqLrGmSCFvZ6eUOnLyZSenkgE+nYysTfsCO2r+Lqjnp7+cw/07Z99ot5A1GgharTQcOe56kSNBhqLGajqvF9jMkFgmYqQazx8HLLThapte1C1bY9fn7OpBUljLlIpsvAVkRCDz//+DnK+PwmiRoLL3gZTTAQaj9WgfNt+jJo2We0Qw8/Z1i24rhFyRrMRbpcb6/7fe7h86iSYzEY421z4ZN1nSE5PxPgrR6sdYtjRaDW4teBm2O2tWP3P/8LtOrXwNGJ0Nn7357lISOxZdwb0iiT60qVL8cc//hGVlZUYMWIE/vrXv2LcuHFdjl+7di3mzZuHI0eOYNCgQXj66adx/fXXhzBi6k16ekKlLydTenoiEejbyUTuCFUPX3fUw597ogvHuTmFiiAIiMjsj+ZDZZ32Rw0dDE0f3ezQk7maO7/tHgBkpwtehdnBUNNHGJHzvUvx+Yq3AAjQGHRw2dsQkRiDvPtvhpH1t0MuMj4aGr22093oEbGRMEawDFWoRcdFYuJV42A0GbDuX++hpckOg8mAy2++FLlXjUVkTNdnC1DwxMbFYNbDM3HbHVNha2qGwWiANTYa0TFRaofWgeDt4QXLXnnlFdx5551YsWIFxo8fjyVLlmDt2rXYt28fEhISOoz//PPPkZ+fj8WLF+PGG2/Ev//9bzz99NP4+uuvcfHF3butzGazISoqCk1NTYiMjAz0P4mI/ieQO9GDpS/vRCciInX05rkm5+YUaorHg7aqGtR+9TW8nv8d+iYIiBo6GJEDMiDp9eoGGIYaDx3HvrUfdtpnTorFkNuuhtbE+XOoOVodcNlaUXPwBNrqmxGblQJLQjQiEqLVDi0stTW3YvdnpXhv2Vt+7YIo4rbHf4is0QMh8bDqkLM323HyaBXqaxqhKAokSYI5woh+A1IRGc0kerjq7lyzxyfRx48fj7Fjx+K5554DACiKgrS0NPz85z/HY4891mH89OnTYbfb8fbbb/vaJkyYgJEjR2LFihXduiYn6kREREQULL15rsm5OanBK8vwOBzw2FvhVRRoLWZIBgPr1KvE1WzHnpfXw1Fv69A3rOA6RKYlqRAVUc9jq21CY3Ujvnh9MxorG5CQkYjxt0xEVHw0TJEsGaYmW0Mz3C43JI2E6Niet+OZQqu7c80ePetwuVzYtm0b5syZ42sTRRFTpkxBcXFxp19TXFyMRx55xK/tmmuuwRtvvNHldZxOJ5xOp+9zm63jZICIiIiIKJxxbk5qESQJWrMZWjNLUvQEuggzhk6/BseLvkbdnjJ4FQXG2Cj0v2oCzImxaodH1GNExkUhMi4Kcf3i4Gx1wmAxwmhhGZeegKVb6Hz06CR6bW0tZFlGYmKiX3tiYiL27t3b6ddUVlZ2Or6ysrLL6yxevBiFhYUXHjARERERUR/FuTkRtdNHWZBxbS765Y+CV/ZC0muhNTM5SNQZU6QZpkguAhL1dqLaAfQEc+bMQVNTk++/Y8eOqR0SEREREVFY4tycqHeQtFrooyJgsEYygU5ERH1ej96JHhcXB0mSUFVV5ddeVVWFpKTO66wlJSWd03gA0Ov10PNAGiIiIiKiLnFuTkREREThqkfvRNfpdBg9ejQ2bNjga1MUBRs2bEBubm6nX5Obm+s3HgA+/PDDLscTEREREdHZcW5OREREROGqR+9EB4BHHnkEM2bMwJgxYzBu3DgsWbIEdrsdd911FwDgzjvvRGpqKhYvXgwA+MUvfoHJkyfjmWeewQ033IA1a9bgq6++wsqVK9X8ZxARERER9XqcmxMRERFROOrxSfTp06ejpqYG8+fPR2VlJUaOHIn169f7DigqLy+HKH67oX7ixIn497//jblz5+K3v/0tBg0ahDfeeAMXX3yxWv8EIiIiIqI+gXNzIiIiIgpHgtfr9aodRE9js9kQFRWFpqYmREZGqh0OEREREfUhnGueGz5fRERERBQs3Z1r9uia6EREREREREREREREaurx5VzU0L4532azqRwJEREREfU17XNM3hDaPZybExEREVGwdHduziR6J5qbmwEAaWlpKkdCRERERH1Vc3MzoqKi1A6jx+PcnIiIiIiC7Wxzc9ZE74SiKKioqEBERAQEQVA7nHNms9mQlpaGY8eOsW5kiPG5Vw+fe3Xx+VcPn3v18LlXV29+/r1eL5qbm5GSkuJ3CCd1Tq25eW/+Geur+D3pefg96Xn4Pel5+D3pmfh96XnU+p50d27OneidEEUR/fr1UzuMCxYZGckXApXwuVcPn3t18flXD5979fC5V1dvff65A7371J6b99afsb6M35Oeh9+Tnoffk56H35Oeid+XnkeN70l35ubc+kJERERERERERERE1AUm0YmIiIiIiIiIiIiIusAkeh+k1+uxYMEC6PV6tUMJO3zu1cPnXl18/tXD5149fO7Vxeefgo0/Yz0Pvyc9D78nPQ+/Jz0Pvyc9E78vPU9P/57wYFEiIiIiIiIiIiIioi5wJzoRERERERERERERUReYRCciIiIiIiIiIiIi6gKT6EREREREREREREREXWASnYiIiIiIiIiIiIioC0yi9yHLly9HTk4OIiMjERkZidzcXLz33ntqhxV2fv/730MQBDz00ENqhxIWnnjiCQiC4Pff0KFD1Q4rbJw4cQJ33HEHYmNjYTQaMXz4cHz11VdqhxUWMjIyOvzsC4KA2bNnqx1anyfLMubNm4fMzEwYjUYMGDAATz31FHhWe2g0NzfjoYceQv/+/WE0GjFx4kRs3bpV7bCoD+GcumfjXLtn4By8Z+LcvGfhfL3n4Ty+Z+ot83uN2gFQ4PTr9//Zu/PwGK/+f+DvmUkm+0wSshKR2BNiL1OEFlXUVtXSPJXY+pSo0tJSIqKxVFulS2Jr8SVK1aMeW21FWlJbaQi1xBAqG9m3SWbm/v3hl3mMrJKZTJb367rmusw599znc2cxn5w59+c0xfLly9GqVSsIgoDNmzdjxIgRuHjxInx9fU0dXoNw7tw5rF27Fn5+fqYOpUHx9fXF0aNHdc/NzPhfW01IT09Hr1698MILL+DgwYNwcnLCzZs34eDgYOrQGoRz585Bo9Honl+5cgUDBw7EmDFjTBhVw/Dpp58iMjISmzdvhq+vL86fP48JEyZALpdjxowZpg6v3ps8eTKuXLmCLVu2wN3dHVu3bsWAAQNw9epVNGnSxNThUT3AnLr2Yq5duzAHr12Ym9c+zNdrH+bxtVNdye9FAj9uqdccHR3x2WefYdKkSaYOpd7LyclBly5dEBERgfDwcHTq1AmrVq0ydVj13qJFi/Dzzz/j0qVLpg6lwZk7dy5OnTqF3377zdShEICZM2di3759uHnzJkQikanDqddeeeUVuLi44LvvvtO1jR49GlZWVti6dasJI6v/8vPzYWdnhz179mDo0KG69q5du2Lw4MEIDw83YXRUnzGnNj3m2rULc/Dah7l57cd83fSYx9c+dSm/ZzmXekqj0WD79u3Izc2FQqEwdTgNQnBwMIYOHYoBAwaYOpQG5+bNm3B3d4e3tzcCAgKQkJBg6pAahP/+97/o1q0bxowZA2dnZ3Tu3Bnr1683dVgNUmFhIbZu3YqJEycyIa8Bzz//PI4dO4YbN24AAP766y/8/vvvGDx4sIkjq//UajU0Gg0sLS312q2srPD777+bKCqqz5hT1x7MtWsf5uC1C3Pz2o35eu3APL72qUv5Pe+3qmcuX74MhUKBgoIC2NraYvfu3fDx8TF1WPXe9u3b8eeff9bKmk31XY8ePbBp0ya0adMGiYmJCAsLQ58+fXDlyhXY2dmZOrx67fbt24iMjMT777+Pjz/+GOfOncOMGTMglUoRGBho6vAalJ9//hkZGRkICgoydSgNwty5c5GVlYW2bdtCIpFAo9FgyZIlCAgIMHVo9Z6dnR0UCgU++eQTtGvXDi4uLvjhhx8QExODli1bmjo8qkeYU9cuzLVrH+bgtQ9z89qN+XrtwDy+9qlL+T3LudQzhYWFSEhIQGZmJn766Sds2LABJ0+eZNJvRPfu3UO3bt1w5MgRXX3Gfv368RZTE8nIyICnpydWrlzJW66NTCqVolu3bjh9+rSubcaMGTh37hxiYmJMGFnDM2jQIEilUuzdu9fUoTQI27dvx5w5c/DZZ5/B19cXly5dwsyZM7Fy5Ur+kVoD4uPjMXHiRERHR0MikaBLly5o3bo1Lly4gGvXrpk6PKonmFPXHsy16wbm4KbH3Lx2Y75eOzCPr53qSn7Plej1jFQq1X1S07VrV5w7dw6rV6/G2rVrTRxZ/XXhwgWkpKSgS5cuujaNRoPo6Gh88803UKlUkEgkJoywYbG3t0fr1q1x69YtU4dS77m5uZWYTGjXrh127dploogaprt37+Lo0aP4z3/+Y+pQGow5c+Zg7ty5GDt2LACgQ4cOuHv3LpYtW8bkuwa0aNECJ0+eRG5uLrKysuDm5oY33ngD3t7epg6N6hHm1LUHc+26gTm46TE3r72Yr9cezONrp7qS37Mmej2n1WqhUqlMHUa91r9/f1y+fBmXLl3SPbp164aAgABcunSJSX0Ny8nJQXx8PNzc3EwdSr3Xq1cvXL9+Xa/txo0b8PT0NFFEDdPGjRvh7OystwkLGVdeXh7EYv0USiKRQKvVmiiihsnGxgZubm5IT0/HoUOHMGLECFOHRPUYc2rTYa5dNzAHNz3m5rUX8/Xag3l87Vbb83uuRK9H5s2bh8GDB6NZs2bIzs7Gtm3bcOLECRw6dMjUodVrdnZ2aN++vV6bjY0NGjVqVKKdDG/27NkYNmwYPD098eDBA4SGhkIikWDcuHGmDq3emzVrFp5//nksXboUr7/+Os6ePYt169Zh3bp1pg6twdBqtdi4cSMCAwNhZsa39JoybNgwLFmyBM2aNYOvry8uXryIlStXYuLEiaYOrUE4dOgQBEFAmzZtcOvWLcyZMwdt27bFhAkTTB0a1RPMqWsX5tq1E3Pw2oe5ee3EfL12YR5fO9WV/J6/wfVISkoKxo8fj8TERMjlcvj5+eHQoUMYOHCgqUMjMpr79+9j3LhxePToEZycnNC7d2/88ccfcHJyMnVo9V737t2xe/duzJs3D4sXL4aXlxdWrVrFTVlq0NGjR5GQkMCkr4Z9/fXXCAkJwbRp05CSkgJ3d3f8+9//xsKFC00dWoOQmZmJefPm4f79+3B0dMTo0aOxZMkSmJubmzo0qieYUxNVjDl47cPcvHZivl67MI+vnepKfs+NRYmIiIiIiIiIiIiIysCa6EREREREREREREREZeAkOhERERERERERERFRGTiJTkRERERERERERERUBk6iExERERERERERERGVgZPoRERERERERERERERl4CQ6EREREREREREREVEZOIlORERERERERERERFQGTqITEZHBLVq0CJ06ddI9DwoKwsiRI00WDxERERFRQ8S8nIjIMMxMHQAREdV/q1evhiAIuuf9+vVDp06dsGrVKtMFRURERETUwDAvJyKqGk6iExGR0cnlclOHQERERETU4DEvJyKqGpZzISJqYHJzczF+/HjY2trCzc0NX3zxBfr164eZM2cCAEQiEX7++We919jb22PTpk265x999BFat24Na2treHt7IyQkBEVFRWWO+eRto0FBQTh58iRWr14NkUgEkUgEpVKJli1b4vPPP9d73aVLlyASiXDr1i1DXDoRERERUa3BvJyIqO7gJDoRUQMzZ84cnDx5Env27MHhw4dx4sQJ/Pnnn890Djs7O2zatAlXr17F6tWrsX79enz55ZeVeu3q1auhUCgwZcoUJCYmIjExEc2aNcPEiROxceNGvWM3btwIf39/tGzZ8pniIyIiIiKq7ZiXExHVHZxEJyJqQHJycvDdd9/h888/R//+/dGhQwds3rwZarX6mc6zYMECPP/882jevDmGDRuG2bNn48cff6zUa+VyOaRSKaytreHq6gpXV1dIJBIEBQXh+vXrOHv2LACgqKgI27Ztw8SJE5/5OomIiIiIajPm5UREdQtrohMRNSDx8fEoLCxEjx49dG2Ojo5o06bNM51nx44d+OqrrxAfH4+cnByo1WrIZLJqxebu7o6hQ4fi+++/x3PPPYe9e/dCpVJhzJgx1TovEREREVFtw7yciKhu4Up0IiLSIxKJIAiCXtuTdRVjYmIQEBCAIUOGYN++fbh48SLmz5+PwsLCao89efJkbN++Hfn5+di4cSPeeOMNWFtbV/u8RERERER1DfNyIqLagyvRiYgakBYtWsDc3BxnzpxBs2bNAADp6em4ceMG+vbtCwBwcnJCYmKi7jU3b95EXl6e7vnp06fh6emJ+fPn69ru3r37THFIpVJoNJoS7UOGDIGNjQ0iIyPxyy+/IDo6+pnOS0RERERUFzAvJyKqWziJTkTUgNja2mLSpEmYM2cOGjVqBGdnZ8yfPx9i8f9uTHrxxRfxzTffQKFQQKPR4KOPPoK5ubmuv1WrVkhISMD27dvRvXt37N+/H7t3736mOJo3b44zZ87gzp07sLW1haOjI8Risa4G47x589CqVSsoFAqDXTsRERERUW3BvJyIqG5hORciogbms88+Q58+fTBs2DAMGDAAvXv3RteuXXX9X3zxBTw8PNCnTx+8+eabmD17tt6tm8OHD8esWbMwffp0dOrUCadPn0ZISMgzxTB79mxIJBL4+PjAyckJCQkJur5JkyahsLAQEyZMqP7FEhERERHVUszLiYjqDpHwdIEtIiJqcPr164dOnTph1apVpg4Fv/32G/r374979+7BxcXF1OEQEREREdUY5uVERLUTy7kQEVGtoFKpkJqaikWLFmHMmDFM1ImIiIiITIB5ORFRSSznQkREtcIPP/wAT09PZGRkYMWKFaYOh4iIiIioQWJeTkRUEsu5EBERERERERERERGVgSvRiYiIiIiIiIiIiIjKwEl0IiIiIiIiIiIiIqIycBKdiIiIiIiIiIiIiKgMnEQnIiIiIiIiIiIiIioDJ9GJiIiIiIiIiIiIiMrASXQiIiIiIiIiIiIiojJwEp2IiIiIiIiIiIiIqAycRCciIiIiIiIiIiIiKgMn0YmIiIiIiIiIiIiIysBJdCIiIiIiIiIiIiKiMnASnYiIiIiIiIiIiIioDJxEJyIiIiIiIiIiIiIqAyfRiYiIiIiIiIiIiIjKwEl0IiIiIiIiIiIiIqIycBKdiGpcv3790K9fP1OHoSc5ORmvvfYaGjVqBJFIhFWrVpV5bE5ODiZPngxXV1eIRCLMnDmzxuKsKUFBQWjevLleW2257tJiE4lEWLRokdHGbN68OYKCgio8btOmTRCJRLhz547RYqkvTpw4AZFIhBMnTujaSvveEhERUe3BPL72Yx6vj3m84TGPp4bKzNQBEFHVbNq0CRMmTNBrc3Jygq+vLz788EMMHjzYRJEZT15eHlasWGGU5H3WrFk4dOgQQkND4erqim7dupV57NKlS7Fp0yaEhISgRYsWaNeunUFjqa0a6nWT6Rjzd56IiKi2OX36NA4fPoyZM2fC3t5er2/p0qXw8fHByJEjTRJbdTGPN62Get1kOszjqT7iJDpRHbd48WJ4eXlBEAQkJydj06ZNGDJkCPbu3YtXXnnF1OEZVF5eHsLCwgDA4G/Ev/76K0aMGIHZs2dX6tiePXsiNDTUoDHUdrX5uvPz82FmZry3tOvXr0Ms5s1bxrZ+/XpotVrdc2P+zhMREdU2p0+fRlhYGIKCgkqdRH/ttdfq9CQ683jTqc3XzTy+fmAeTw0BJ9GJ6rjBgwfrrbaYNGkSXFxc8MMPP9S7SXRjSklJKfHHSnnH+vj4VHhcQUEBpFJpvUnaKnvdzyIvLw/W1tbVPo+lpaUBoimbhYWFUc9Pj5mbm5s6BCIiogajvuSqzOMrxjyejI15PDUE9eMdgYh07O3tYWVlVeLT/NzcXHzwwQfw8PCAhYUF2rRpg88//xyCIAB4vAKgbdu2aNu2LfLz83WvS0tLg5ubG55//nloNJoyxy2uIRcdHY1///vfaNSoEWQyGcaPH4/09PQK405JSdF9AGBpaYmOHTti8+bNuv47d+7AyckJABAWFgaRSFSp+nm3b9/GmDFj4OjoCGtra/Ts2RP79+8vEbcgCPj222915y1Nce03pVKJ/fv36469c+eOrm/79u1YsGABmjRpAmtra2RlZQEAzpw5g5dffhlyuRzW1tbo27cvTp06VWKMf/75BxMnToSLiwssLCzg6+uL77//vsKvHwAcOXIEvXv3hr29PWxtbdGmTRt8/PHHJa716Tp/pdW0q+x1P8s5+/Xrh/bt2+PChQvw9/eHtbW1Xnyl+fnnn9G+fXtYWlqiffv22L17d6nHlfazcPHiRQwePBgymQy2trbo378//vjjD13/r7/+CrFYjIULF+q9btu2bRCJRIiMjNS1lVZLMS4uDi+++CKsrKzQtGlThIeH662+eNLBgwfRp08f2NjYwM7ODkOHDkVcXFy5137+/HmIRCK934Nihw4dgkgkwr59+wAA2dnZmDlzJpo3bw4LCws4Oztj4MCB+PPPP8sdAwB+//13dO/eHZaWlmjRogXWrl2LRYsW6f0e3LlzByKRCJs2bSrx+qe/9nfv3sW0adPQpk0bWFlZoVGjRhgzZkyl6ks+WUuxvN/5jRs3QiQS4eLFiyXOsXTpUkgkEvzzzz8VjkdERFSeyr6/njlzBkOGDIGDgwNsbGzg5+eH1atX6/pjY2MRFBQEb29vWFpawtXVFRMnTsSjR490xyxatAhz5swBAHh5eenlWyKRCLm5udi8ebOu/cm8pDL5Y3m5KvN45vEVnZN5PPP4ijCPp4aAK9GJ6rjMzEw8fPgQgiAgJSUFX3/9NXJycvCvf/1Ld4wgCBg+fDiOHz+OSZMmoVOnTjh06BDmzJmDf/75B19++SWsrKywefNm9OrVC/Pnz8fKlSsBAMHBwcjMzMSmTZsgkUgqjGf69Omwt7fHokWLcP36dURGRuLu3bu6ZKw0+fn56NevH27duoXp06fDy8sLO3fuRFBQEDIyMvDee+/ByckJkZGRmDp1KkaNGoVXX30VAODn51dmLMnJyXj++eeRl5eHGTNmoFGjRti8eTOGDx+On376CaNGjYK/vz+2bNmCt956CwMHDsT48ePLPF+7du2wZcsWzJo1C02bNsUHH3wA4HEt+uLE4pNPPoFUKsXs2bOhUqkglUrx66+/YvDgwejatStCQ0MhFouxceNGvPjii/jtt9/w3HPP6eLt2bMnRCIRpk+fDicnJxw8eBCTJk1CVlZWuRsAxcXF4ZVXXoGfnx8WL14MCwsL3Lp1q9QE/1mVd93P6tGjRxg8eDDGjh2Lf/3rX3BxcSnz2MOHD2P06NHw8fHBsmXL8OjRI0yYMAFNmzatcJy4uDj06dMHMpkMH374IczNzbF27Vr069cPJ0+eRI8ePfDiiy9i2rRpWLZsGUaOHIkuXbogMTER7777LgYMGIB33nmnzPMnJSXhhRdegFqtxty5c2FjY4N169bBysqqxLFbtmxBYGAgBg0ahE8//RR5eXmIjIxE7969cfHixTI34OnWrRu8vb3x448/IjAwUK9vx44dcHBwwKBBgwAA77zzDn766SdMnz4dPj4+ePToEX7//Xdcu3YNXbp0KfM6Ll++jJdeeglOTk5YtGgR1Go1QkNDy/2+VOTcuXM4ffo0xo4di6ZNm+LOnTuIjIxEv379cPXq1UqvWCrvd97LywvBwcGIiopC586d9V4XFRWFfv36oUmTJlW+BiIiIqBy769HjhzBK6+8Ajc3N7z33ntwdXXFtWvXsG/fPrz33nu6Y27fvo0JEybA1dUVcXFxWLduHeLi4vDHH39AJBLh1VdfxY0bN/DDDz/gyy+/ROPGjQE8fj/csmULJk+ejOeeew5vv/02AKBFixYAnj1/LC1XLcY8nnl8eZjHM49nHk8NnkBEddLGjRsFACUeFhYWwqZNm/SO/fnnnwUAQnh4uF77a6+9JohEIuHWrVu6tnnz5glisViIjo4Wdu7cKQAQVq1aVel4unbtKhQWFuraV6xYIQAQ9uzZo2vr27ev0LdvX93zVatWCQCErVu36toKCwsFhUIh2NraCllZWYIgCEJqaqoAQAgNDa3U12jmzJkCAOG3337TtWVnZwteXl5C8+bNBY1Go2sHIAQHB1fqvJ6ensLQoUP12o4fPy4AELy9vYW8vDxdu1arFVq1aiUMGjRI0Gq1uva8vDzBy8tLGDhwoK5t0qRJgpubm/Dw4UO9c48dO1aQy+V6533al19+KQAQUlNTyzym+HukVCpLjf348eO6tsDAQMHT07PC636Wc/bt21cAIKxZs6bMGJ/UqVMnwc3NTcjIyNC1HT58WABQIranfy5GjhwpSKVSIT4+Xtf24MEDwc7OTvD399e15ebmCi1bthR8fX2FgoICYejQoYJMJhPu3r1b4toDAwN1z4t/ts6cOaNrS0lJEeRyud7XIzs7W7C3txemTJmid76kpCRBLpeXaH/avHnzBHNzcyEtLU3XplKpBHt7e2HixIm6NrlcXumf3yeNHDlSsLS01Lveq1evChKJRHgyRVAqlQIAYePGjSXO8fTXvrSf05iYGAGA8H//93+6tsr83JX3Oz9u3DjB3d1d7/f4zz//LDNOIiKiZ1XR+6tarRa8vLwET09PIT09Xa/v6bzvaT/88IMAQIiOjta1ffbZZ6XmVYIgCDY2Nnq5SLHK5o9l5aqCwDyeeXzF52Qe/z/M45nHU8PFci5Eddy3336LI0eO4MiRI9i6dSteeOEFTJ48Gf/5z390xxw4cAASiQQzZszQe+0HH3wAQRBw8OBBXduiRYvg6+uLwMBATJs2DX379i3xuvK8/fbbevXQpk6dCjMzMxw4cKDM1xw4cACurq4YN26crs3c3BwzZsxATk4OTp48Wenxnz7vc889h969e+vabG1t8fbbb+POnTu4evVqlc5bnsDAQL1VDJcuXcLNmzfx5ptv4tGjR3j48CEePnyI3Nxc9O/fH9HR0dBqtRAEAbt27cKwYcMgCILuuIcPH2LQoEHIzMws95a+4jqQe/bsKfNWxNrAwsICEyZMqPC4xMREXLp0CYGBgZDL5br2gQMHVljPUaPR4PDhwxg5ciS8vb117W5ubnjzzTfx+++/627Ptba2xqZNm3Dt2jX4+/tj//79+PLLL9GsWbNyxzhw4AB69uypW30EPF5xERAQoHfckSNHkJGRgXHjxul9TyUSCXr06IHjx4+XO84bb7yBoqIivd/nw4cPIyMjA2+88Yauzd7eHmfOnMGDBw/KPd+TNBoNDh06hJEjR+pdb7t27XQrY6riyZ//oqIiPHr0CC1btoS9vX2lbkutrPHjx+PBgwd6X8OoqChYWVlh9OjRBhuHiIgaroreXy9evAilUomZM2eWqMn95MrtJ98bCwoK8PDhQ/Ts2RMAqvXeWJX88elc9UnM45nHl4d5PPN4Q2EeT3UVJ9GJ6rjnnnsOAwYMwIABAxAQEID9+/fDx8cH06dPR2FhIYDHtc3c3d1hZ2en99p27drp+otJpVJ8//33UCqVyM7O1tUsq6xWrVrpPbe1tYWbm1u5ddTu3r2LVq1aldi4p7T4nsXdu3fRpk2bEu3VPW95vLy89J7fvHkTwOOk3MnJSe+xYcMGqFQqZGZmIjU1FRkZGVi3bl2J44qT1ZSUlDLHfeONN9CrVy9MnjwZLi4uGDt2LH788cdal4g3adJE77bhshR/b57+eQJQ6vf0SampqcjLyyvze6/VanHv3j1dW69evTB16lScPXsWgwYNwsSJEysVX2ViK/7+v/jiiyW+r4cPHy73ewoAHTt2RNu2bbFjxw5d244dO9C4cWO8+OKLurYVK1bgypUr8PDwwHPPPYdFixbh9u3b5Z47NTUV+fn5Vfoalyc/Px8LFy7U7b/QuHFjODk5ISMjA5mZmVU+79MGDhwINzc3REVFAQC0Wi1++OEHjBgxosT/dURERFVR0ftrfHw8AKB9+/blnictLQ3vvfceXFxcYGVlBScnJ13OWJ33xqrkj0/nqk9iHs88vjzM45nHGwrzeKqrWBOdqJ4Ri8V44YUXsHr1aty8eRO+vr7PfI5Dhw4BeLxS5ubNm+Um26Tv6ZU9xcnvZ599hk6dOpX6GltbW93GUv/6179K1M0rVl7dSCsrK0RHR+P48ePYv38/fvnlF+zYsQMvvvgiDh8+DIlEUuaHIeVtGFuRZz1nWSufTEmlUuk2ToqPj0deXl6l6/1VpPj7v2XLFri6upbof3oD4NK88cYbWLJkCR4+fAg7Ozv897//xbhx4/Re+/rrr6NPnz7YvXs3Dh8+jM8++wyffvop/vOf/2Dw4MHVvo5n+T6/++672LhxI2bOnAmFQgG5XA6RSISxY8ca9I9BiUSCN998E+vXr0dERAROnTqFBw8e6O0HQUREVB2Gen99/fXXcfr0acyZMwedOnWCra0ttFotXn755Wq9Nxa/9lnyx9qYi9UWzOPLP2dt/NlhHl8x5vFEhsNJdKJ6SK1WAwBycnIAAJ6enjh69Ciys7P1Ptn9+++/df3FYmNjsXjxYkyYMAGXLl3C5MmTcfnyZb1b8cpz8+ZNvPDCC7rnOTk5SExMxJAhQ8p8jaenJ2JjY6HVavVWsTwd37OsiC9+3fXr10u0l3bdxlK86ZNMJsOAAQPKPM7JyQl2dnbQaDTlHlcesViM/v37o3///li5ciWWLl2K+fPn4/jx4xgwYAAcHBwAABkZGXqvq85KHmOcE/jf96Z4BciTSvuePsnJyQnW1tZlfu/FYjE8PDx0baGhobh27Ro+//xzfPTRR5g7dy6++uqrCuOrTGzF339nZ+cqf1/feOMNhIWFYdeuXXBxcUFWVhbGjh1b4jg3NzdMmzYN06ZNQ0pKCrp06YIlS5aUmXw7OTnBysqqUtfxLN/nn376CYGBgfjiiy90bQUFBSVeWxkV/c6PHz8eX3zxBfbu3YuDBw/CycmpWrewEhERPa2899fi9/krV66U+T6fnp6OY8eOISwsDAsXLtS1l/b+W977Xml9hsgfn8Q8Xh/z+KphHv8/zOPLxjye6iKWcyGqZ4qKinD48GFIpVLd7Y5DhgyBRqPBN998o3fsl19+CZFIpHtzLioqQlBQENzd3bF69Wps2rQJycnJmDVrVqXHX7duHYqKinTPIyMjoVary/0UfciQIUhKStK71U2tVuPrr7+Gra0t+vbtCwC6VQWVfRMfMmQIzp49i5iYGF1bbm4u1q1bh+bNm1dYk88QunbtihYtWuDzzz/XfajxpNTUVACPP40fPXo0du3ahStXrpR5XFnS0tJKtBWvmFGpVAD+lwhGR0frjtFoNFi3bl3lLqYUxjgn8DiR7NSpEzZv3qx36+CRI0cqrIEpkUjw0ksvYc+ePXq3HycnJ2Pbtm3o3bs3ZDIZAODMmTP4/PPPMXPmTHzwwQeYM2cOvvnmmwrrdw4ZMgR//PEHzp49q2tLTU3V3ZJYbNCgQZDJZFi6dKne78WTr6lIu3bt0KFDB+zYsQM7duyAm5sb/P39df0ajabE7ZXOzs5wd3fXfe9LI5FIMGjQIPz8889ISEjQtV+7dk13N0oxmUyGxo0b632fASAiIqLU8wqCoNf29ddfV2mlVEW/835+fvDz88OGDRuwa9cujB07tlKrgoiIiCpSmffXLl26wMvLC6tWrSrxXlX8XiiRSPSeF1u1alWJMW1sbACU/r5nY2NTor26+ePTmMfrYx5fNczj/4d5PPN4ql/4E0pUxx08eFC3IiMlJQXbtm3DzZs3MXfuXF2CMWzYMLzwwguYP38+7ty5g44dO+Lw4cPYs2cPZs6cqUugwsPDcenSJRw7dgx2dnbw8/PDwoULsWDBArz22mvlrkIpVlhYiP79++P111/H9evXERERgd69e2P48OFlvubtt9/G2rVrERQUhAsXLqB58+b46aefcOrUKaxatUq3et7Kygo+Pj7YsWMHWrduDUdHR7Rv377MOpRz587FDz/8gMGDB2PGjBlwdHTE5s2boVQqsWvXrhK1G41BLBZjw4YNGDx4MHx9fTFhwgQ0adIE//zzD44fPw6ZTIa9e/cCAJYvX47jx4+jR48emDJlCnx8fJCWloY///wTR48eLTXBLrZ48WJER0dj6NCh8PT0REpKCiIiItC0aVPdhky+vr7o2bMn5s2bh7S0NDg6OmL79u26OxeqwhjnLLZs2TIMHToUvXv3xsSJE5GWloavv/4avr6+pf4h86Tw8HAcOXIEvXv3xrRp02BmZoa1a9dCpVJhxYoVAB6vqggMDESrVq2wZMkSAEBYWBj27t2LCRMm4PLly7o/Zp/24YcfYsuWLXj55Zfx3nvvwcbGBuvWrdOtxiomk8kQGRmJt956C126dMHYsWPh5OSEhIQE7N+/H7169Srx4VZp3njjDSxcuBCWlpaYNGmS3s9udnY2mjZtitdeew0dO3aEra0tjh49inPnzumtIilNWFgYfvnlF/Tp0wfTpk3T/dHr6+urdx0AMHnyZCxfvhyTJ09Gt27dEB0djRs3bpQ45yuvvIItW7ZALpfDx8cHMTExOHr0KBo1alThdT6tMr/z48ePx+zZswGAt4ASEZHBVOb9VSwWIzIyEsOGDUOnTp0wYcIEuLm54e+//0ZcXBwOHToEmUwGf39/rFixAkVFRWjSpAkOHz4MpVJZYsyuXbsCAObPn4+xY8fC3Nwcw4YNg42NDbp27YqjR49i5cqVcHd3h5eXF3r06FGt/PFpzOP1MY+vOubx/8M8nnk81SMCEdVJGzduFADoPSwtLYVOnToJkZGRglar1Ts+OztbmDVrluDu7i6Ym5sLrVq1Ej777DPdcRcuXBDMzMyEd999V+91arVa6N69u+Du7i6kp6dXGM/JkyeFt99+W3BwcBBsbW2FgIAA4dGjR3rH9u3bV+jbt69eW3JysjBhwgShcePGglQqFTp06CBs3LixxDinT58WunbtKkilUgGAEBoaWu7XKT4+XnjttdcEe3t7wdLSUnjuueeEffv2lTgOgBAcHFzuuYp5enoKQ4cO1Ws7fvy4AEDYuXNnqa+5ePGi8OqrrwqNGjUSLCwsBE9PT+H1118Xjh07pndccnKyEBwcLHh4eAjm5uaCq6ur0L9/f2HdunXlxnTs2DFhxIgRgru7uyCVSgV3d3dh3Lhxwo0bN/SOi4+PFwYMGCBYWFgILi4uwscffywcOXJEACAcP35cd1xgYKDg6elZ4XU/yzn79u0r+Pr6lnsdT9u1a5fQrl07wcLCQvDx8RH+85//lBpbaT8Lf/75pzBo0CDB1tZWsLa2Fl544QXh9OnTuv5Zs2YJEolEOHPmjN7rzp8/L5iZmQlTp07Vu/bAwEC942JjY4W+ffsKlpaWQpMmTYRPPvlE+O677wQAglKp1Dv2+PHjwqBBgwS5XC5YWloKLVq0EIKCgoTz589X6utw8+ZN3e/577//rtenUqmEOXPmCB07dhTs7OwEGxsboWPHjkJERESlzn3y5End75S3t7ewZs0aITQ0VHg6RcjLyxMmTZokyOVywc7OTnj99deFlJSUEl/79PR03e+yra2tMGjQIOHvv/8u8TUs/p2p6Oeuot/5xMREQSKRCK1bt67U9RIREVXGs7y//v7778LAgQN1x/n5+Qlff/21rv/+/fvCqFGjBHt7e0EulwtjxowRHjx4UOr72ieffCI0adJEEIvFejnF33//Lfj7+wtWVlYCAL331Mrkj+Xlqszjmcczj2ceLwjM44kqIhKEp+7VICKqgk2bNmHChAk4d+4cunXrZupwiKgaFi1ahLCwsBK3c9ZGDx8+hJubGxYuXIiQkBBTh0NERFTnMI8nqj+YxxMZD2uiExERUZ21adMmaDQavPXWW6YOhYiIiIiIKol5PNU1rIlOREREdc6vv/6Kq1evYsmSJRg5ciSaN29u6pCIiIiIiKgCzOOpruIkOhEREdU5ixcvxunTp9GrVy98/fXXpg6HiIiIiIgqgXk81VWsiU5EREREREREREREVAbWRCciIiIiIiIiIiIiKgMn0YmIiIiIiIiIiIiIylCrJtEjIyPh5+cHmUwGmUwGhUKBgwcP6voLCgoQHByMRo0awdbWFqNHj0ZycrLeORISEjB06FBYW1vD2dkZc+bMgVqtrulLISIiIiKq05ibExERERE9Vqs2Fm3atCmWL1+OVq1aQRAEbN68GSNGjMDFixfh6+uLWbNmYf/+/di5cyfkcjmmT5+OV199FadOnQIAaDQaDB06FK6urjh9+jQSExMxfvx4mJubY+nSpZWOQ6vV4sGDB7Czs4NIJDLW5RIRERFRAyQIArKzs+Hu7g6xuFatadHD3JyIiIiI6rtK5+ZCLefg4CBs2LBByMjIEMzNzYWdO3fq+q5duyYAEGJiYgRBEIQDBw4IYrFYSEpK0h0TGRkpyGQyQaVSVXrMe/fuCQD44IMPPvjggw8++ODDaI979+4ZLmmuIczN+eCDDz744IMPPvioj4+KcvNatRL9SRqNBjt37kRubi4UCgUuXLiAoqIiDBgwQHdM27Zt0axZM8TExKBnz56IiYlBhw4d4OLiojtm0KBBmDp1KuLi4tC5c+dKjW1nZwcAuHfvHmQymWEvjIiIiIgatKysLHh4eOhyzrqAuTkRERER1UeVzc1r3ST65cuXoVAoUFBQAFtbW+zevRs+Pj64dOkSpFIp7O3t9Y53cXFBUlISACApKUkvSS/uL+4ri0qlgkql0j3Pzs4GAF39RyIiIiIiQ6sLpUmYmxMRERFRQ1BRbl7rijC2adMGly5dwpkzZzB16lQEBgbi6tWrRh1z2bJlkMvluoeHh4dRxyMiIiIiqguYmxMRERER1cJJdKlUipYtW6Jr165YtmwZOnbsiNWrV8PV1RWFhYXIyMjQOz45ORmurq4AAFdXVyQnJ5foL+4ry7x585CZmal73Lt3z7AXRURERERUBzE3JyIiIiKqhZPoT9NqtVCpVOjatSvMzc1x7NgxXd/169eRkJAAhUIBAFAoFLh8+TJSUlJ0xxw5cgQymQw+Pj5ljmFhYaG7PZS3iRIRERERlY65ORERERE1RLWqJvq8efMwePBgNGvWDNnZ2di2bRtOnDiBQ4cOQS6XY9KkSXj//ffh6OgImUyGd999FwqFAj179gQAvPTSS/Dx8cFbb72FFStWICkpCQsWLEBwcDAsLCxMfHVERERERHUHc3MiIiKi+k8QBKjVamg0GlOHYhQSiQRmZmbV3o+oVk2ip6SkYPz48UhMTIRcLoefnx8OHTqEgQMHAgC+/PJLiMVijB49GiqVCoMGDUJERITu9RKJBPv27cPUqVOhUChgY2ODwMBALF682FSXVOM0Gg1iY2ORlpYGR0dH+Pn5QSKRmDosIiIiIqpjmJsTERER1W+FhYVITExEXl6eqUMxKmtra7i5uUEqlVb5HCJBEAQDxlQvZGVlQS6XIzMzs07dPhodHY2IiAgkJSXp2lxdXTFt2jT4+/ubMDIiIiIiKlZXc01TqemvlyBooS0qgqBWAwBEZuYQm5tXe/USERERUW2i1Wpx8+ZNSCQSODk5QSqV1rt8RxAEFBYWIjU1FRqNBq1atYJYrF/dvLK5Zq1aiU5VFx0djdDQUCgUCoSEhMDLywtKpRJRUVEIDQ1FWFgYJ9KJiIiIiMqh1WhQlJOJvPt3Ifz/W5pFEglsPLxgZmMHMe/wJCIionqisLAQWq0WHh4esLa2NnU4RmNlZQVzc3PcvXsXhYWFsLS0rNJ5av3GolQxjUaDiIgIKBQKhIeHw9fXF9bW1vD19UV4eDgUCgUiIyPrbW0jIiIiIiJD0BYWIPfubd0EOgAIGg1y7tyCtlBlwsiIiIiIjOPpldn1kSGusf5/lRqA2NhYJCUlISAgoMQPhVgsRkBAABITExEbG2uiCImIiIiIajetVoP8lKQy+wtSkyFotTUYERERERHVFpxErwfS0tIAAF5eXqX2F7cXH0dERERERE/RaqEtyC+zW6PK5yQ6ERERkQEtWrQInTp10j0PCgrCyJEjTRZPeTiJXg84OjoCAJRKZan9xe3FxxERERER0VPEYogtrcrsllhYQdQAbncmIiIiMpXVq1dj06ZNuuf9+vXDzJkzTRbPk5gF1gN+fn5wdXVFVFQUtE+tjtFqtYiKioKbmxv8/PxMFCERERERUe0mFktg5exaZr+lkwsn0YmIiIiMSC6Xw97e3tRhlIpZYD0gkUgwbdo0xMTEYMGCBYiLi0NeXh7i4uKwYMECxMTEYOrUqZBIJKYOlYiIiIio1hJLLWHj6Q3RE3mzSCKBrWdLiKUWJoyMiIiIqGbl5uZi/PjxsLW1hZubG7744gu9leEikQg///yz3mvs7e31VpJ/9NFHaN26NaytreHt7Y2QkBAUFRWVOeaT5VyCgoJw8uRJrF69GiKRCCKRCEqlEi1btsTnn3+u97pLly5BJBLh1q1bhrj0UpkZ7cxUo/z9/REWFoaIiAgEBwfr2t3c3BAWFgZ/f38TRkdEREREVPuJJRJIZfYwa2UDQa0GAIjMzCE2N4dIJDJxdEREREQ1Z86cOTh58iT27NkDZ2dnfPzxx/jzzz/1aphXxM7ODps2bYK7uzsuX76MKVOmwM7ODh9++GGFr129ejVu3LiB9u3bY/HixQAAJycnTJw4ERs3bsTs2bN1x27cuBH+/v5o2bLlM19nZXESvR7x9/dHr169EBsbi7S0NDg6OsLPz48r0ImIiIiIKkkkEkMitQC48pyIiIgaqJycHHz33XfYunUr+vfvDwDYvHkzmjZt+kznWbBgge7fzZs3x+zZs7F9+/ZKTaLL5XJIpVJYW1vD1fV/JfeCgoKwcOFCnD17Fs899xyKioqwbdu2EqvTDY2T6PWMRCJB586dTR0GERERERERERER1UHx8fEoLCxEjx49dG2Ojo5o06bNM51nx44d+OqrrxAfH4+cnByo1WrIZLJqxebu7o6hQ4fi+++/x3PPPYe9e/dCpVJhzJgx1TpvRVgTnYiIiIiIiIiIiIgqTSQSQRAEvbYn653HxMQgICAAQ4YMwb59+3Dx4kXMnz8fhYWF1R578uTJ2L59O/Lz87Fx40a88cYbsLa2rvZ5y8OV6EREREREREREREQEAGjRogXMzc1x5swZNGvWDACQnp6OGzduoG/fvgAe1ydPTEzUvebmzZvIy8vTPT99+jQ8PT0xf/58Xdvdu3efKQ6pVAqNRlOifciQIbCxsUFkZCR++eUXREdHP9N5q4KT6EREREREREREREQEALC1tcWkSZMwZ84cNGrUCM7Ozpg/fz7E4v8VNXnxxRfxzTffQKFQQKPR4KOPPoK5ubmuv1WrVkhISMD27dvRvXt37N+/H7t3736mOJo3b44zZ87gzp07sLW1haOjI8RiMSQSCYKCgjBv3jy0atUKCoXCYNdeFpZzISIiIiIiIiIiIiKdzz77DH369MGwYcMwYMAA9O7dG127dtX1f/HFF/Dw8ECfPn3w5ptvYvbs2XolVYYPH45Zs2Zh+vTp6NSpE06fPo2QkJBnimH27NmQSCTw8fGBk5MTEhISdH2TJk1CYWEhJkyYUP2LrQSR8HTxGkJWVhbkcjkyMzOrXeyeiIiIiOhJzDWfDb9eRERERIZXUFAApVIJLy8vWFpaVuo1/fr1Q6dOnbBq1SrjBlcJv/32G/r374979+7BxcWl3GPLu9bK5pos50JEREREREREREREtZ5KpUJqaioWLVqEMWPGVDiBbigs50JEREREREREREREtd4PP/wAT09PZGRkYMWKFTU2LleiExEREREREREREVG5Tpw4YeoQEBQUhKCgoBoflyvRiYiIiIiIiIiIiIjKwEl0IiIiIiIiIiIiIqIycBKdiIiIiIiIiIiIiKgMnEQnIiIiIiIiIiIiIioDJ9GJiIiIiIiIiIiIiMrASXQiIiIiIiIiIiIiojJwEp2IiIiIiIiIiIiIqAycRCciIiIiIiIiIiKiOiEyMhJ+fn6QyWSQyWRQKBQ4ePCgUcfkJDoRERERERERERERVYlWrYamIB/q3BxoCvKhVauNOl7Tpk2xfPlyXLhwAefPn8eLL76IESNGIC4uzmhjmhntzERERERERERERERUb2kKC5F7Xwl1TrauzcxWBpumzSGRSo0y5rBhw/SeL1myBJGRkfjjjz/g6+trlDG5Ep2IiIiIiIiIiIiInolWrS4xgQ4A6pws5N6/Y/QV6QCg0Wiwfft25ObmQqFQGG0crkQnIiIiIiIiIiIiomciqItKTKAXU+dkQVAXAWbGmX6+fPkyFAoFCgoKYGtri927d8PHx8coYwFciU5EREREREREREREz0jQaMrv15bfXx1t2rTBpUuXcObMGUydOhWBgYG4evWq0cbjSnQiIiIiIiIiIiIieiYiiaT8fnH5/dUhlUrRsmVLAEDXrl1x7tw5rF69GmvXrjXKeFyJTkRERERERERERETPRGRmDjNbWal9ZrYyiMzMaywWrVYLlUpltPNzJToRERERERERERERPROxmRlsmjZH7v07UOdk6drNbGWwadocYiPVQ583bx4GDx6MZs2aITs7G9u2bcOJEydw6NAho4wH1LKV6MuWLUP37t1hZ2cHZ2dnjBw5EtevX9c7pl+/fhCJRHqPd955R++YhIQEDB06FNbW1nB2dsacOXOgroHdYImIiIiI6gvm5kRERERUEYlUCttm3pC39oWsZVvIW/vCtpk3JFKp0cZMSUnB+PHj0aZNG/Tv3x/nzp3DoUOHMHDgQKONWatWop88eRLBwcHo3r071Go1Pv74Y7z00ku4evUqbGxsdMdNmTIFixcv1j23trbW/Vuj0WDo0KFwdXXF6dOnkZiYiPHjx8Pc3BxLly6t0eshIiIiIqqrmJsTERERUWWIzcwAI606L813331XY2MVq1WT6L/88ove802bNsHZ2RkXLlyAv7+/rt3a2hqurq6lnuPw4cO4evUqjh49ChcXF3Tq1AmffPIJPvroIyxatAhSI34KQkRERERUXzA3JyIiIiJ6rFaVc3laZmYmAMDR0VGvPSoqCo0bN0b79u0xb9485OXl6fpiYmLQoUMHuLi46NoGDRqErKwsxMXFlTqOSqVCVlaW3oOIiIiIiP6HuTkRERERNVS1aiX6k7RaLWbOnIlevXqhffv2uvY333wTnp6ecHd3R2xsLD766CNcv34d//nPfwAASUlJekk6AN3zpKSkUsdatmwZwsLCjHQlRERERER1G3NzIiIiImrIau0kenBwMK5cuYLff/9dr/3tt9/W/btDhw5wc3ND//79ER8fjxYtWlRprHnz5uH999/XPc/KyoKHh0fVAiciIiIiqmeYmxMRERFRQ1Yry7lMnz4d+/btw/Hjx9G0adNyj+3RowcA4NatWwAAV1dXJCcn6x1T/LysWo0WFhaQyWR6DyIiIiIiYm5ORERERFSrJtEFQcD06dOxe/du/Prrr/Dy8qrwNZcuXQIAuLm5AQAUCgUuX76MlJQU3TFHjhyBTCaDj4+PUeImIiIiIqpvmJsTERERET1Wq8q5BAcHY9u2bdizZw/s7Ox0dRLlcjmsrKwQHx+Pbdu2YciQIWjUqBFiY2Mxa9Ys+Pv7w8/PDwDw0ksvwcfHB2+99RZWrFiBpKQkLFiwAMHBwbCwsDDl5RERERER1RnMzYmIiIiIHhMJgiCYOohiIpGo1PaNGzciKCgI9+7dw7/+9S9cuXIFubm58PDwwKhRo7BgwQK92zzv3r2LqVOn4sSJE7CxsUFgYCCWL18OM7PKfWaQlZUFuVyOzMxM3j5KRERERAZVV3JN5uZERERE9VdBQQGUSiW8vLxgaWlp6nCMqrxrrWyuWatWolc0n+/h4YGTJ09WeB5PT08cOHDAUGERERERETU4zM2JiIiIiB6rVTXRiYiIiIiIiIiIiIhqE06iExEREREREREREVGds3z5cohEIsycOdOo49Sqci5EREREREREREREVHdoCguhKVBBUKshNjeH2EIKiVRq9HHPnTuHtWvX6ja1NyZOohMRERERERERERHRM1Pn5ePhhUsoSEnVtVk6O6Fx104ws7Yy2rg5OTkICAjA+vXrER4ebrRxirGcCxERERERERERERE9E01hYYkJdAAoSEnFwwuXoCksNNrYwcHBGDp0KAYMGGC0MZ7ElehERERERERERERE9Ew0BaoSE+jFClJSoSlQGaWsy/bt2/Hnn3/i3LlzBj93WTiJTkRERERERERERETPRFCrq9VfFffu3cN7772HI0eOwNLS0uDnLwsn0YmIiIiIiIiIiIjomYjMyp9arqi/Ki5cuICUlBR06dJF16bRaBAdHY1vvvkGKpUKEonE4ONyEp2IiIiIiIiIiIiInonE0gKWzk6llnSxdHaCxNLC4GP2798fly9f1mubMGEC2rZti48++sgoE+gAJ9GJiIiIiIiIiIiI6BlJpFI07tqpxOails5OaNy1k1HqodvZ2aF9+/Z6bTY2NmjUqFGJdkPiJDoRERERERERERERPTMzays49egKTYEKgloNkZkZJJYWRplANyVOohMRERERERERERFRlUikUpNOmp84ccLoY4iNPgIRERERERERERERUR3FSXQiIiIiIiIiIiIiojJwEp2IiIiIiIiIiIiIqAycRCciIiIiIiIiIiIiKgMn0YmIiIiIiIiIiIiIysBJdCIiIiIiIiIiIiKiMnASnYiIiIiIiIiIiIioDJxEJyIiIiIiIiIiIiIqAyfRiYiIiIiIiIiIiIjKwEl0IiIiIiIiIiIiIqIycBKdiIiIiIiIiIiIiOqERYsWQSQS6T3atm1r1DHNjHp2IiIiIiIiIiIiIqq3ivJVUOflQ6MqgsRCCjNrS5hbWRh1TF9fXxw9elT33MzMuNPcBj17YWEhlEolWrRoYfTAiYiIiIiodMzLiYiIiKgmqLJycPvAKWTdeaBrk3u5w2twL1jIbI02rpmZGVxdXY12/qcZpJxLXl4eJk2aBGtra/j6+iIhIQEA8O6772L58uWGGIKIiIiIiCrAvJyIiIiIakpRvqrEBDoAZCofQHnwFIryVUYb++bNm3B3d4e3tzcCAgJ0ea+xGGQSfd68efjrr79w4sQJWFpa6toHDBiAHTt2GGIIIiIiIiKqAPNyIiIiIqop6rz8EhPoxTKVD6DOyzfKuD169MCmTZvwyy+/IDIyEkqlEn369EF2drZRxgMMVM7l559/xo4dO9CzZ0+IRCJdu6+vL+Lj4w0xBBERERERVYB5ORERERHVFI2qqFr9VTV48GDdv/38/NCjRw94enrixx9/xKRJk4wypkFWoqempsLZ2blEe25url7yTkRERERExsO8nIiIiIhqisTCvFr9hmJvb4/WrVvj1q1bRhvDIJPo3bp1w/79+3XPixP0DRs2QKFQGGIIIiIiIiKqAPNyIiIiIqopZtZWkHu5l9on93KHmbVVjcSRk5OD+Ph4uLm5GW0Mg5RzWbp0KQYPHoyrV69CrVZj9erVuHr1Kk6fPo2TJ08aYggiIiIiIqoA83IiIiIiqinmVhbwGtwLyoOnkKn8X210uZc7vAb3hrmVhVHGnT17NoYNGwZPT088ePAAoaGhkEgkGDdunFHGAww0id67d29cunQJy5cvR4cOHXD48GF06dIFMTEx6NChgyGGICIiIiKiCjAvJyIiIqKaZCGzRYvh/aDOy4dGVQSJhTnMrK2MNoEOAPfv38e4cePw6NEjODk5oXfv3vjjjz/g5ORktDENMokOAC1atMD69esNdToiIiIiIqoC5uVEREREVJPMrSyMOmn+tO3bt9fYWMWqXBM9Kyur0o/KWrZsGbp37w47Ozs4Oztj5MiRuH79ut4xBQUFCA4ORqNGjWBra4vRo0cjOTlZ75iEhAQMHToU1tbWcHZ2xpw5c6BWq6t6qUREREREtZYx8nKAuTkRERERUbEqr0S3t7fXbVRUEY1GU6njTp48ieDgYHTv3h1qtRoff/wxXnrpJVy9ehU2NjYAgFmzZmH//v3YuXMn5HI5pk+fjldffRWnTp3SjTV06FC4urri9OnTSExMxPjx42Fubo6lS5dW7WKJiIiIiGopY+TlAHNzIiIiIqJiIkEQhKq88MmNie7cuYO5c+ciKCgICoUCABATE4PNmzdj2bJlCAwMrFJwqampcHZ2xsmTJ+Hv74/MzEw4OTlh27ZteO211wAAf//9N9q1a4eYmBj07NkTBw8exCuvvIIHDx7AxcUFALBmzRp89NFHSE1NhVQqrXDcrKwsyOVyZGZmQiaTVSl2IiIiIqLSGDrXrIm8HGBuTkRERFSfFBQUQKlUwsvLC5aWlqYOx6jKu9bK5ppVXonet29f3b8XL16MlStX6u2AOnz4cHTo0AHr1q2rcrKemZkJAHB0dAQAXLhwAUVFRRgwYIDumLZt26JZs2a6RL1406TiJB0ABg0ahKlTpyIuLg6dO3euUixERERERLVRTeTlAHNzIiIiImq4qlwT/UkxMTHo1q1bifZu3brh7NmzVTqnVqvFzJkz0atXL7Rv3x4AkJSUBKlUCnt7e71jXVxckJSUpDvmySS9uL+4rzQqlapa9SKJiIiIiGoDY+TlAHNzIiIiImrYDDKJ7uHhgfXr15do37BhAzw8PKp0zuDgYFy5cqVGdltdtmwZ5HK57lHVmImIiIiITMkYeTnA3JyIiIiIGrYql3N50pdffonRo0fj4MGD6NGjBwDg7NmzuHnzJnbt2vXM55s+fTr27duH6OhoNG3aVNfu6uqKwsJCZGRk6K14SU5Ohqurq+6Yp1fZJCcn6/pKM2/ePLz//vu651lZWUzWiYiIiKjOMXReDjA3JyIiIiIyyEr0IUOG4MaNGxg2bBjS0tKQlpaGYcOG4caNGxgyZEilzyMIAqZPn47du3fj119/hZeXl15/165dYW5ujmPHjunarl+/joSEBN3GSQqFApcvX0ZKSorumCNHjkAmk8HHx6fUcS0sLCCTyfQeRERERER1jaHycoC5ORERERFRMZEgCIKpgyg2bdo0bNu2DXv27EGbNm107XK5HFZWVgCAqVOn4sCBA9i0aRNkMhneffddAMDp06cBABqNBp06dYK7uztWrFiBpKQkvPXWW5g8eTKWLl1aqTgquysrEREREdGzqiu5JnNzIiIiovqroKAASqUSXl5esLS0NHU4RlXetVY216xyOZfY2Fi0b98eYrEYsbGx5R7r5+dXqXNGRkYCAPr166fXvnHjRgQFBQF4fIuqWCzG6NGjoVKpMGjQIEREROiOlUgk2LdvH6ZOnQqFQgEbGxsEBgZi8eLFlb84IiIiIqI6whh5OcDcnIiIiIioWJVXoovFYiQlJcHZ2RlisRgikQilnUokEkGj0VQ70JrE1S5EREREZCyGzjXrc14OMDcnIiIiMoa6vhL9n3/+wUcffYSDBw8iLy8PLVu2xMaNG9GtW7cSx5p0JbpSqYSTk5Pu30REREREVPOYlxMRERGRKalyC6DKzkNRvgrmVhawsLOGhY3xJubT09PRq1cvvPDCCzh48CCcnJxw8+ZNODg4GG3MKk+ie3p6lvrvp9WikutERERERPUO83IiIiIiMpW8tGyc23IEydcSdG0u7TzR/a0BsHa0M8qYn376KTw8PLBx40Zdm5eXl1HGKiY2xEmCgoKQm5tbov3OnTvw9/c3xBBERERERFQB5uVEREREVFNUuQUlJtABIPnaXZzbchSq3AKjjPvf//4X3bp1w5gxY+Ds7IzOnTtj/fr1RhmrmEEm0f/66y/4+fkhJiZG17Z582Z07NgRjRs3NsQQRERERERUAeblRERERFRTVNl5JSbQiyVfuwtVdp5Rxr19+zYiIyPRqlUrHDp0CFOnTsWMGTOwefNmo4wHVKOcy5POnj2Ljz/+GP369cMHH3yAW7du4eDBg1i5ciWmTJliiCGIiIiIiKgCzMuJiIiIqKYU5asq6C80yrharRbdunXD0qVLAQCdO3fGlStXsGbNGgQGBhplTINMopubm+Ozzz6DtbU1PvnkE5iZmeHkyZNQKBSGOD0REREREVUC83IiIiIiqinmVhYV9EuNMq6bmxt8fHz02tq1a4ddu3YZZTzAQOVcioqK8MEHH+DTTz/FvHnzoFAo8Oqrr+LAgQOGOD0REREREVUC83IiIiIiqikWdtZwaVf6xvYu7TxhYWdtlHF79eqF69ev67XduHEDnp6lx2IIBlmJ3q1bN+Tl5eHEiRPo2bMnBEHAihUr8Oqrr2LixImIiIgwxDBERERERFQO5uVEREREVFMsbCzR/a0BOLflKJKv3dW1u7TzRPfxA2BhY2mUcWfNmoXnn38eS5cuxeuvv46zZ89i3bp1WLdunVHGAww4if7VV1/BxsYGACASifDRRx/hpZdewltvvWWIIYiIiIiIqALMy4mIiIioJlk72qHn5MFQZeehKL8Q5lZSWNhZG20CHQC6d++O3bt3Y968eVi8eDG8vLywatUqBAQEGG1MkSAIgtHODkClUsHCovz6OLVNVlYW5HI5MjMzIZPJTB0OEREREdUjpso162JeDjA3JyIiIjKGgoICKJVKeHl5wdLSeBPetUF511rZXNMgNdEB4OTJkxg2bBhatmyJli1bYvjw4fjtt9/qZKJORERERFRXMS8nIiIiIjIsg0yib926FQMGDIC1tTVmzJiBGTNmwMrKCv3798e2bdsMMQQREREREVWAeTkRERERkeEZpJxLu3bt8Pbbb2PWrFl67StXrsT69etx7dq16g5Ro3jLKBEREREZizFzzfqWlwPMzYmIiIiMgeVcHqvRci63b9/GsGHDSrQPHz4cSqXSEEMQEREREVEFmJcTERERERmeQSbRPTw8cOzYsRLtR48ehYeHhyGGICIiIiKiCjAvJyIiIiIyPDNDnOSDDz7AjBkzcOnSJTz//PMAgFOnTmHTpk1YvXq1IYYgIiIiIqIKMC8nIiIiIjI8g0yiT506Fa6urvjiiy/w448/Anhcj3HHjh0YMWKEIYYgIiIiIqIKMC8nIiIiIjI8g0yiA8CoUaMwatQoQ52OiIiIiIiqgHk5EREREZFhGaQmOhERERERERERERFRfVTlleiOjo64ceMGGjduDAcHB4hEojKPTUtLq+owRERERERUDublRERERETGVeVJ9C+//BJ2dnYAgFWrVhkqHiIiIiIiegbMy4mIiIioIWnevDnu3r1bon3atGn49ttvjTJmlSfRAwMDS/03ERERERHVHOblRERERGRK+dn5yM3MgSpXBUsbS1jLbWBlZ2W08c6dOweNRqN7fuXKFQwcOBBjxowx2phVnkTPysqq9LEymayqwxARERERUTmYlxMRERGRqWSmZmLf13ugvHhL1+bduSWGvjsCcie5UcZ0cnLSe758+XK0aNECffv2Ncp4QDUm0e3t7cutt/ikJz8ZICIiIiIiw2FeTkRERESmkJ+dX2ICHQBuX7yF/V/vwag5Y4y6Ih0ACgsLsXXrVrz//vuVzomrosqT6MePH9f9+86dO5g7dy6CgoKgUCgAADExMdi8eTOWLVtW/SiJiIiIiKhUzMuJiIiIyBRyM3NKTKAXu33xFnIzc4w+if7zzz8jIyMDQUFBRh2nypPoTy6PX7x4MVauXIlx48bp2oYPH44OHTpg3bp1rM1IRERERGQkzMuJiIiIyBRUuapq9RvCd999h8GDB8Pd3d2o44gNcZKYmBh069atRHu3bt1w9uxZQwxBREREREQVYF5ORERERDXFwsaiWv3VdffuXRw9ehSTJ0826jiAgSbRPTw8sH79+hLtGzZsgIeHhyGGICIiIiKiCjAvJyIiIqKaYiO3hXfnlqX2eXduCRu5rVHH37hxI5ydnTF06FCjjgNUo5zLk7788kuMHj0aBw8eRI8ePQAAZ8+exc2bN7Fr1y5DDEFERERERBVgXk5ERERENcXKzgpD3x2B/V/vwe0naqN7d26JV2aMMGo9dK1Wi40bNyIwMBBmZgaZ4i6XQUYYMmQIbt68icjISFy7dg0AMGzYMLzzzjtc8UJEREREVEOYlxMRERFRTZI7yTFqzhjkZuZAlauChY0FbOS2Rt9Q9OjRo0hISMDEiRONOk4xg03TN23aFEuWLDHU6YiIiIiIqAqYlxMRERFRTbKyszL6pPnTXnrpJQiCUGPjGaQmOhERERERERERERFRfcRJdCIiIiIiIiIiIiKiMnASnYiIiIiIiIiIiIioDNWeRBcEAQkJCSgoKDBEPIiOjsawYcPg7u4OkUiEn3/+Wa8/KCgIIpFI7/Hyyy/rHZOWloaAgADIZDLY29tj0qRJyMnJMUh8RERERES1EfNyIiIiIiLjMMgkesuWLXHv3j1DxIPc3Fx07NgR3377bZnHvPzyy0hMTNQ9fvjhB73+gIAAxMXF4ciRI9i3bx+io6Px9ttvGyQ+IiIiIqLaiHk5EREREZFxmFX3BGKxGK1atcKjR4/QqlWragc0ePBgDB48uNxjLCws4OrqWmrftWvX8Msvv+DcuXPo1q0bAODrr7/GkCFD8Pnnn8Pd3b3aMdZmGo0GsbGxSEtLg6OjI/z8/CCRSEwdFhEREREZGfNyIiIiIiLjMEhN9OXLl2POnDm4cuWKIU5XoRMnTsDZ2Rlt2rTB1KlT8ejRI11fTEwM7O3tdYk6AAwYMABisRhnzpwp9XwqlQpZWVl6j7ooOjoaAQEBmDVrFj755BPMmjULAQEBiI6ONnVoRERERFQD6npeDpg+N9eqi6DOy0HugwTkPrgHdV4utOqiGo2BiIiIiGqXaq9EB4Dx48cjLy8PHTt2hFQqhZWVlV5/WlqaIYYB8PiW0VdffRVeXl6Ij4/Hxx9/jMGDByMmJgYSiQRJSUlwdnbWe42ZmRkcHR2RlJRU6jmXLVuGsLAwg8VoCtHR0QgNDYVCoUBISAi8vLygVCoRFRWF0NBQhIWFwd/f39RhEhEREZER1fW8HDBtbq4tKkLugwQUZabr2lQPkyG1d4S1mwfE5uYmiYuIiIiITMsgk+irVq0yxGkqZezYsbp/d+jQAX5+fmjRogVOnDiB/v37V+mc8+bNw/vvv697npWVBQ8Pj2rHWlM0Gg0iIiKgUCgQHh4OsfjxDQa+vr4IDw/HggULEBkZiV69erG0CxEREVE9VtfzcsC0ubk6L0dvAr1YYUYapPaOkJrb10gcRERERFS7GGQSPTAw0BCnqRJvb280btwYt27dQv/+/eHq6oqUlBS9Y9RqNdLS0sqs12hhYQELC4uaCNcoYmNjkZSUhJCQEN0EejGxWIyAgAAEBwcjNjYWnTt3NlGURERERGRsdT0vB0yXm2vVahSkJpfZX/AwGWY2dhBzUQoRERFRg2OQSfSEhIRy+5s1a2aIYUp1//59PHr0CG5ubgAAhUKBjIwMXLhwAV27dgUA/Prrr9BqtejRo4fR4jCl4ttyvby8Su0vbjfk7btEREREVPswL68GQYCg1ZTdrdEAglCDARERERFRaTQaDRYtWoStW7ciKSkJ7u7uCAoKwoIFCyASiYwypkEm0Zs3b15ugBpN2cno03JycnDr1i3dc6VSiUuXLsHR0RGOjo4ICwvD6NGj4erqivj4eHz44Ydo2bIlBg0aBABo164dXn75ZUyZMgVr1qxBUVERpk+fjrFjx8Ld3b3qF1mLOTo6Anj8tfL19S3Rr1Qq9Y4jIiIiovqJeXnVicwkMJfZQ1OQX2q/VO4AEVehExEREZWQk5WLzLQs5OXkw8bWGjJHO9jKbIw23qefforIyEhs3rwZvr6+OH/+PCZMmAC5XI4ZM2YYZUyDTKJfvHhR73lRUREuXryIlStXYsmSJc90rvPnz+OFF17QPS+uhxgYGIjIyEjExsZi8+bNyMjIgLu7O1566SV88sknerd8RkVFYfr06ejfvz/EYjFGjx6Nr776qhpXWLv5+fnB1dUVUVFRejXRAUCr1SIqKgpubm7w8/MzYZT1n0ajQWxsLNLS0uDo6Ag/Pz/WoCciIqIaxby86kQiMSwcGkP1KBWCRq3fZ2YGqb2j0VY2EREREdVVj5LTsOaTTYj9I07X1rFne/w7JBCNXIyzoPf06dMYMWIEhg4dCuDxQpIffvgBZ8+eNcp4ACASBOPdk7h//3589tlnOHHihLGGMIqsrCzI5XJkZmZCJpOZOpxKiY6ORmhoKBQKBQICAuDl5QWlUomoqCjExMQgLCwM/v7+pg6z3oqOjkZERASSkpJ0ba6urpg2bRq/7kRERKTHFLlmXc3LgZr9egmCAG2hCnlJD1CU9XiDUam9I6yc3SCxsDTq2FQ2rVoNTYEKBQ8fQdBqYdnIERJLS0gspKYOjYiIqM4qKCiAUqmEl5cXLC2rlufkZOVi9cdr9SbQi3Xs2R4zlr5tlBXpS5cuxbp163D48GG0bt0af/31F1566SWsXLkSAQEBJY4v71orm2saZCV6Wdq0aYNz584Zcwj6//z9/REWFoaIiAgEBwfr2t3c3DiBbmRPfoAREhKi9wFGaGgov/5ERERkcszLK0ckEkFiYQmbpp4QNE0ft5lJIBbz7kJT0RQVITfhH6RditVrt/H0gGP7dpBU8Y9+IiIiqr7MtKxSJ9AB4K8/riAzLcsok+hz585FVlYW2rZtC4lEAo1GgyVLlpQ6gW4oBplEz8rK0nsuCAISExOxaNEitGrVyhBDUCX4+/ujV69eLClSgzQaDSIiIqBQKPRK6fj6+iI8PBwLFixAZGQkevXqxe8DERERGR3zcsMQSyQAc7daQZ2bV2ICHQBy796DlbMTbJs1NUFUREREBAB5OaXvJVMsv4L+qvrxxx8RFRWFbdu2wdfXF5cuXcLMmTPh7u6OwMBAo4xpkEl0e3v7EvUBBUGAh4cHtm/fboghqJIkEgk6d+5s6jAajNjYWCQlJSEkJESvFj0AiMViBAQEIDg4GLGxsfy+EBERkdExL6f6RBAEZN++U2Z/5vVbsHJxguSJOvxERERUc6xtrcrtt6qgv6rmzJmDuXPnYuzYsQCADh064O7du1i2bFntnkQ/fvy43nOxWAwnJye0bNkSZmZGrRhDZFJpaWkAAC8vr1L7i9uLjyMiIiIyJublVJ8IWi00eWWvYNOoVBC0Rtvii4iIiCogd5ShY8/2+OuPKyX6OvZsD7mjcfazycvLK7GYVSKRQKvVGmU8oBqT6F26dMGxY8fg4OCAkydPYvbs2bC2tjZkbES1nqPj412GlUolfH19S/QrlUq944iIiIgMjXk51VdiiQRWrs7IT04ptd+ikSPEZiy7Q0REZCq2Mhv8OyQQaz/ZrDeR3rFne/w7JNAo9dABYNiwYViyZAmaNWsGX19fXLx4EStXrsTEiRONMh4AiARBqNJH91ZWVrh58yaaNm0KiUSCpKQkODk5GTo+k6jsrqxEGo0GAQEB8Pb21quJDgBarRYLFiyAUqnE1q1bWRPdiDQaDfcCICKiOsPQuWZ9zssB5uYNXVFuHhJ/jYa2sFC/QySCe/++kMr5M2FK6nwVBK0WEkvp470EiIiozigoKIBSqYSXlxcsq7lRd05WLjLTspCfkw8rWyvIHWVGm0AHgOzsbISEhGD37t1ISUmBu7s7xo0bh4ULF0IqlZY4vrxrrWyuWeWV6J06dcKECRPQu3dvCIKAzz77DLa2tqUeu3DhwqoOQ1SrSSQSTJs2DaGhoViwYAECAgLg5eUFpVKJqKgoxMTEICwsjBO6RhQdHY2IiAgkJSXp2lxdXTFt2jT4+/ubMDIiIqKawbyc6jNzG2u49uuFtL+uoCA59XGbXIZGnf1gZmu8P86pfEW5+ci+n4LEs1egKVDBvqUHnDu3hYXctsS+DEREVP/ZymyMOmn+NDs7O6xatQqrVq2qsTGrvBL9+vXrCA0NRXx8PP7880/4+PiUWmdRJBLhzz//rHagNYmrXehZlTaR6+bmhqlTp3Ii14iio6MRGhoKhUJR5gcY/PoTEVFtY+hcsz7n5QBzc3pMU1j0eDW6IEAsNedmoiZUlJePu0fP4NFVpV67xEIK3/GvwKqR3ESRERHRszDkSvTazhAr0as8if4ksViMpKQkODs7V/dUtQITdaoKlhSpWU+W0gkLC8OVK1d0X/v27dsjNDSUpXSIiKhWMmauWd/ycoC5OVFtk5OYir93HIZzxzawbeIEQauFtlCN5It/QyqzRYuhvSGRmps6TCIiqgAn0R8zejmXJxlz51OiukIikaBz586mDqPBiI2NRVJSEoYNG4a33nqrRDmXYcOG4fTp04iNjeX3hYiIGgzm5URkbJl3HqDl8H5IPHMZiWcuAwDMba3R5PmOyEtNg7pAxUl0IiKqd6o8if7f//630scOHz68qsMQEZUqLS0NALBhwwYoFAqEhITolXPZsGGD3nFERET1FfNyIqpJdh6uiP/vSRRm5erainLycOdwDLxf6QORmDXRiYio/qnyJPrIkSMrdZxIJIJGo6nqMPSMWFKEGgp7e3sAQPv27REeHg6xWAwA8PX1RXh4ON577z1cvnxZdxwREVF9xbyciGpSUXae3gT6kxL/uAy5p1sNR0RERGR8VZ5E562itU9pm1u6urpi2rRp3FyRiIiIqJ5iXm5YWnURtIUqqDLSIQIgtXeEWCqF2IzlKYgAIPuf5DL78h9mQNBWe9s1IiKiWkds6gDIMKKjoxEaGgpvb298++23OHDgAL799lt4e3sjNDQU0dHRpg6x3tNoNLh48SKOHTuGixcvcqWXkWVkZAAALl++jAULFiAuLg55eXmIi4vDggULcPnyZb3jiIiIiCqiLSpE7j8JyLr1N1QPk1HwMBlZt64h78F9aNVFpg6vQVPn56MwIxOq9Ayo8/Ig8MMjk7F0kJfZZ2ZlwXIuRERULxlkY9HFixeX279w4UJDDENl0Gg0iIiIgEKhKLWsxYIFCxAZGYlevXqxtIuR8C6Amufo6AgAmDJlCvbu3Yvg4GBdn5ubGyZPnowNGzbojiMiImoImJdXjzovF0WZ6SXaCzMeQWrvAKnMvuaDauAErRaqtAyknr0ATX4+AEBsbgbHTh1g5eYKiTnvEKhp9t5NkCAWl/pBhlvPDjC3sTJBVERERMZlkEn03bt36z0vKiqCUqmEmZkZWrRowWTdyGJjY5GUlISQkBDdBHoxsViMgIAABAcHIzY2Fp07dzZRlPVX8V0ApW1uGRoairCwME6kG4Gfnx9cXV0RFxeHLVu24MqVK7q9ANq3b4/Q0FC4ubnBz8/P1KESERHVGOblVadVq1GQWnaZioKHyTCzsYOYi1JqlDovD8m/ndabsNUWqfHw3EW49u0FSeNGJoyuYZLa2aDNmAG48Z9foS1S69od23mhsW9LiMS84Z2IiOofg0yiX7x4sURbVlYWgoKCMGrUKEMMQeVIS0sDAHh5eZW6saiXl5fecWQ4vAvAdCQSCaZNm4bQ0FCEhoYiICAACoUCSqUSoaGhiImJQVhYGL/uRETUoDAvrwZBgKAtuxyfoNEAAms91yRBEJCTcL/M0i3pcX/DWfEcJFKuRq9JYjMJ7Dxc4Td5FPIfZkBdoIK1syPMba1gbmVp6vCIiIiMwiCT6KWRyWQICwvDsGHD8NZbbxlrGML/ylrs3r0be/fuLVFS5JVXXtE7jgyHdwGYlr+/P8LCwhAREVGinAvvACAiInqMeXnliMwkMJfJoSnIL7VfKneAiB/O1yhBq0VhWkaZ/UXZ2RA0agCcRK9pYjMJLOS2sJDbmjoUIiJqoLKzsxESEoLdu3cjJSUFnTt3xurVq9G9e3ejjGe0SXQAyMzMRGZmpjGHIDwua2Fvb4/169eXKCmydetWbNiwAQ4ODixrYQRP3gVQGt4FYHz+/v7o1atXiTswuAKdiIjof5iXV0wkEsPCoTFUj1Ifrzp/sk9i9ngSXcQNE2uSSCyGuVyG/OSUUvvNbWz4wQYREVEtkJmRjbRH6cjOyoGdzBaOjRwgt7cz6piTJ0/GlStXsGXLFri7u2Pr1q0YMGAArl69iiZNmhh8PINMon/11Vd6zwVBQGJiIrZs2YLBgwcbYgiqJoG3nhpF8ep+pVIJX1/fEv1KpVLvODIOiUTClf5ERERgXl5d6rw82DbzRkHaQxRlZQAApDJ7WDg2hlpVAIkFS1XUJJFIBNvmzZB1M77UUjr2Pm0gkUpNEBkREREVS3qQgkUfrcDp6HO6tuf9u2PRpx/C1d3ZKGPm5+dj165d2LNnj64KwaJFi7B3715ERkYiPDzc4GMaZBL9yy+/1HsuFovh5OSEwMBAzJs3zxBDUDliY2ORkZGBKVOmYO/evSXKWkyZMgXr169nSREjKN7cMioqSq8mOgBotVpERUVxc0siIiKqMczLq06rVqPgYTI0BfmwcHCEjcfjOwqLsjORfSceZtbWMLexhVhi1Jt56Slm1lZw6dUDqWcvQFtYBODxCnWHDj6QOtibNjgiIqIGLjMju8QEOgCcjj6HRR+twKdfhxplRbparYZGo4Glpf4CBysrK/z+++8GHw8w0CR68WpbMo3iUiGjRo3C2LFjS5S1UKlUWL9+PUuKGMGTm1suWLAAAQEBulI6UVFR3NySiIiIahTz8uoQAEELCFqo0h5ClfZQv1crALy5s8aJJRJYOjWGe/++0BSoIAgCJJaWkFhaQMwcm4iIyKTSHqWXmEAvdjr6HNIepRtlEt3Ozg4KhQKffPIJ2rVrBxcXF/zwww+IiYlBy5YtDT4eYKSa6FlZWfj111/Rpk0btGvXzhhD0BOeLiny9GpzlhQxLm5uSQ2dRqNhTXoiolqKeXnliSRmkNo3Qn7S/VL7LRwasf62iYjEYphZW8PM2trUoRDVevlZuRA0WphZmENqzRJURGRc2Vk55fbnVNBfHVu2bMHEiRPRpEkTSCQSdOnSBePGjcOFCxeMMp5BJtFff/11+Pv7Y/r06cjPz0e3bt1w584dCIKA7du3Y/To0YYYhsrAkiKmx80tqaGKjo5GREQEkpKSdG2urq6YNm0aP0AiIjIB5uVVJxKJILV3gOpRCrRFhXp9YqkFzGX23FiUiGqtgqxcJF65g78PnUd+Zi4aebmiw8hekLk6wszC3NThEVE9ZSezLbfftoL+6mjRogVOnjyJ3NxcZGVlwc3NDW+88Qa8vb2NMp644kMqFh0djT59+gAAdu/eDUEQkJGRga+++soohdxJX3FJkZiYGCxYsABxcXHIy8tDXFwcFixYgJiYGEydOpUTukZWvLll//790blzZ369a5BGo8HFixdx7NgxXLx4ERqNxtQhNQjR0dEIDQ2Ft7c3vv32Wxw4cADffvstvL29ERoaiujoaFOHSETU4DAvrx6J1AJ2LdrA0tkNYnMpxOZSWLq4w867NTewJHqKuqAQBelZyHuYjsLsXAilbP5KNUOVW4C/dp/Cuf87guzkdKgLCpF8LQHHlm9H2p2kik9ARFRFjo0c8Lx/91L7nvfvDsdGDkaPwcbGBm5ubkhPT8ehQ4cwYsQIo4wjEgzwTmdlZYUbN27Aw8MD48ePh7u7O5YvX46EhAT4+PggJ8d4S/eNISsrC3K5HJmZmZDJZKYOp9JKWxHq5uaGqVOnckUo1VtcCW0aGo0GAQEB8Pb2xsKFC7F37148ePAA7u7uGDZsGBYvXgylUomtW7fyAyUjYikdorrJmLlmfcvLAdPk5oKghaBWAwBEZuZcgU70lIL0LCgPxSDrzgMAgLmtNTwHPAd58yYws+QHTjUt88EjHFq8BQAgloghMTdDkaoQEAA7Fwf0e/81WMltTBwlEdU2BQUFUCqV8PLyKrFB57NIepBSYnPR5/27Y9GKD+Hq5myIUEt16NAhCIKANm3a4NatW5gzZw4sLS3x22+/wdxc/w6c8q61srmmQcq5eHh4ICYmBo6Ojvjll1+wfft2AEB6enq1vgn0bFhShBqa4pXQCoUCISEhepu6hoaGsia9EcXGxiIpKQnt27fH0KFD9Vb/r1mzBv369UNiYiJiY2NL7NNAhsEPkIioNMzLDUMkEkNkzolAotKosnJx7YdfUJiVq2srysnDrZ9PoM3rL8Heu4kJo2uYHikTYeskR7vBz8HcUorCPBWs7G3wMD4R1w+fR1G+ipPoJpKTno2ctBzkZGRD1lgOG3tb2PB7QfWMq7szPv06FGmP0pGTlQNbmS0cGzkYZUPRJ2VmZmLevHm4f/8+HB0dMXr0aCxZsqTEBLqhGGQSfebMmQgICICtrS08PT3Rr18/AI//wO/QoYMhhqBKKi4pQlTfaTQaREREQKFQ6O0F4Ovri/DwcCxYsACRkZHo1asXP0gygrS0NADA0aNH4eDggEmTJkGhUCAmJgbfffcdjh07pnccGRY/QCKisjAvJyJjy016qDeB/qSE4+dg7eIIqY1VDUfVsFnKbdD5jRdwIeoY8tKzde1uHbzQY+LLEEsMUsmXnlFaYhp+/CQKD++l6tqa+jTDqNljIHeSmzAyIsOT29sZfdL8aa+//jpef/31GhvPIP+TTps2DX/88Qe+//57/P7777rJLG9vb9ZeJCKjKF4JHRAQoLeZLgCIxWIEBAToVkKT4RXf4mRnZ4edO3filVdeQaNGjfDKK69g586dsLOz0zuODOfpD5B8fX1hbW2t+wBJoVAgMjKSewMYWWFhIXbu3InVq1dj586dKCwsrPhFRDWAeTkRGVtWQtk1tvNT0yGomYPUNFsne5zdfFhvAh0AEi8rkXL9HsyseGdNTctJz8aP4foT6ABw/2oCflmzDwW5+SaKjIDHf1Pl5eRBU8T/r6jyDLISHQC6du2Krl276rUNHTrUUKcnItJTvMLZy8ur1P7idq6ENo7bt28DAJydnUv9EMPJyQnZ2dm4ffs2uncvfZMRqpriD5BCQkLK/AApODiYpXSMaM2aNdi5c2eJMkZjxozBO++8Y8LIiB5jXk5ExmTpUPZKQzMrC4jE3EOgpuWkZECVnVdq352Ya2jVvwssba1rOKqGLSc9Bw8TUkvtu3nuBnIzcmHJOzZqnEpViNQHDxG97zTuXE+AazMX9B/lDye3RrDm7whVgPf0EFGd5OjoCABQKpWl9he3Fx9HhlVchzs+Ph4LFixAXFwc8vLyEBcXhwULFugm2Z+s102GwQ+QTGvNmjXYvn07ZDIZZs+ejV27dmH27NmQyWTYvn071qxZY+oQiYiIjMreuylE4tKnEtx6dIA5JwZrXE5KRpl9miI1NIXqmguGAAD5WaV/qAEAEAQU5vMuRlOIj1Ni7r8WY8/mg/jrjzgc+vFXzP3XYlw5/zdUKn5PqHycRCeiOsnPzw+urq6IioqCVqvV69NqtYiKioKbmxv8/PxMFGH95u7uDgAYPnw4bt++jeDgYAwZMgTBwcFQKpUYPny43nFkOPwAyXSKS7g4ODiUWsaouJ2lXYiIqD6T2tmg9ZgBEJvr39ju2LY5GrdvUeYEOxmPvEmjMvuk1hYwkxqsCAFVkq1j2XdsiCViWNpws++alvJPKiIWfY8iVZFeu1ajReSi75GWnG6iyKiu4P+kRFQnSSQSTJs2DaGhofj444/RpEkTqFQqWFhY4J9//sGZM2cQFhbGTUWNZMSIEVizZg1+++03bN++HVevXkVaWhocHR3h4+ODsWPHQiKRYMSIEaYOtd558gOkJzfVBfgBkrHt2bMHGo0GkyZNgpmZfgplZmaGiRMn4osvvsCePXswZswYE0VJRERkXGIzCWQervCbPAqawiJo1RpILMxhZm0Bc0tODJqCTWM57FwckF3KJGDrAV1h7ch9imqajdwGXh29ofzrdom+TgO7wsbB1gRRNWzZmblIffCw1L68nHykp2bArZlLDUdFdUmt+4g4Ojoaw4YNg7u7O0QiEX7++We9fkEQsHDhQri5ucHKygoDBgzAzZs39Y5JS0tDQEAAZDIZ7O3tMWnSJOTk5NTgVRBRTfD398fzzz+PP/74A7t27cK+ffuwa9cu/PHHH3j++efh7+9v6hDrLalUijFjxiA9PR1jx47F/fv30bFjR9y/fx9jx45Feno6xowZA6mUmxgZWvEHSDExMaWW0omJicHUqVP5AZIRPHjwAACgUChK7S9uLz6OqK5jXk5EZVFlZuP2gd9x+bufEbd5L65t+wWZ8f+gMIebJZqCbWM5ek8bDqfWTXVtEnMztHu5O5r3bAeJOfPCmmYtt8GwmaPQ9nkf3T4BYjMJug55Dn3G9YPUkn8n1TStpvxNRNVFDbfs0dN399dHhrhGg61E/+2337B27VrEx8fjp59+QpMmTbBlyxZ4eXmhd+/elT5Pbm4uOnbsiIkTJ+LVV18t0b9ixQp89dVX2Lx5M7y8vBASEoJBgwbh6tWrsPz/n3oHBAQgMTERR44cQVFRESZMmIC3334b27ZtM9TlElEtsGbNGpw6dQoODg4YOHAgmjRpgn/++QdHjhzBqVOnsGbNGm7yZ0TFX9sdO3bgiy++0LWLxWKMHTuWX3sj8vf3R1hYGCIiIhAcHKxrd3NzQ1hYGD9AMpLi8kQxMTF45ZVXSvTHxMToHUdkKszLiciYCtKz8PeOwyjMytW1FeXkIX5vNFqP7g9pq2YmjK7hsnNxQM+JL6OooBBajRYScwksZdYwt7QwdWgNlqyxHMPeG4kXgwaiMK8QFjYWsLW3hTkn0E3Czt4WdnJbZGeW/DDfzNwMjd3KLotUX0mlUojFYjx48ABOTk6QSqUQierX5tCCIKCwsBCpqakQi8XVWugnEgRBqG5Au3btwltvvYWAgABs2bIFV69ehbe3N7755hscOHAABw4cqFpwIhF2796NkSNHAnh84e7u7vjggw8we/ZsAEBmZiZcXFywadMmjB07FteuXYOPjw/OnTuHbt26AQB++eUXDBkyBPfv36/UH7ZZWVmQy+XIzMyETMbbnohqo8LCQgwePBgymQw7d+7UK62gVqsxZswYZGVl4eDBg1wNbUTz58/HqVOnSrT36tULS5YsMUFEDYtGo0FsbKyulI6fnx9XoBsR/98hQzFmrlnf8nKAuTlRbfPw6m3E//dkqX1WTg5o/doAWMpZqqKmFamKkJ+ejbz0bBTlFcLKwRaWdlawdbI3dWhEtYK6SI2YI+fwzcINJfrenD4aA17tCxuZjQkiM63CwkIkJiYiL6+czXDrAWtra7i5uZX6d1plc02DrEQPDw/HmjVrMH78eGzfvl3X3qtXL4SHhxtiCACPN0tLSkrCgAEDdG1yuRw9evRATEwMxo4di5iYGNjb2+sSdQAYMGAAxGIxzpw5g1GjRhksHiIyHdYmNr2yJtAB4NSpU5g/fz4n0o1MIpGgc+fOpg6jwSguY7R9+3aMGTMGHTt2hKWlJQoKCvDXX3/pyhtxAp1MiXk5ERlb9r2kMvvyU9MhVFAygQyvSFWE7KRHUOUU4FH8A+Rn5sKhmQusHWwhEotg00hu6hCJTM7M3Ax+Cl+ErvsQu9bvxf3bD+DcpDFGTRgKr7aeDXICHXj8N06zZs2gVquhqaf/f0skEpiZmVV7lb1BJtGvX79e6q3jcrkcGRkZhhgCAJCU9PjN2sVFv9C/i4uLri8pKQnOzs56/WZmZnB0dNQd8zSVSgWVSqV7npWVZbCYicg4WJvYtPLz83UT6FKpFIWFhbq+4uenTp1Cfn4+rKysTBUmkcG98847uHTpEv7++2+cOHFCr69t27YsY0QmV9fzcoC5OVFtZ2FvV2afmZVFvSsFUBcUZOYi4/4jXIg6CkH7uNiA8lQcrBvJ0HPiy5BIzWFpZ23iKIlMz9LaEo5O9nhj2iiIRSJoBS3s5LawsGrYi2BEIhHMzc1hbm5u6lBqNYNsLOrq6opbt26VaP/999/h7e1tiCGMatmyZZDL5bqHh4eHqUMiogo8WZu4NKxNbFxr1qwx6HFEdcWaNWvw999/Qy6Xo1+/fnj55ZfRr18/yOVy/P333/yZJ5Or63k5wNycqLZzaOkBkbj0qQSXrj6QNtDVnKakVhXhzx9+1U2gF8t7lIVrB89CXVBYxiuJGpbbcUrMHhuKkAlLMT9oCUImLMP7Y0Jw5fzfUKn4e0LlM8gk+pQpU/Dee+/hzJkzEIlEePDgAaKiojB79mxMnTrVEEMAePxHAQAkJyfrtScnJ+v6XF1dkZKSotevVquRlpamO+Zp8+bNQ2Zmpu5x7949g8VMRMYxYsQISCQSfPfdd1Cr9XfRVqvV+P777yGRSDBixAgTRVi/Xbt2Tffvrl274ttvv8WBAwfw7bffomvXrqUeR4an0Whw8eJFHDt2DBcvXqy3t9/VFoWFhdi5cyccHBywa9cuLFq0CHPnzsWiRYuwa9cuODg4YOfOnXp3ZhDVtLqelwPMzYlqO6mtNVqNegFiM/19WOxbNYNTh5YQc3+WGpf5Tyq06tLzwKS4u9AUqUvtI+MTtFpkPcxEelI6stN4Z5UppfyTim8XfY8iVZFeu1ajReSi75GWnG6iyKiuMEg5l7lz50Kr1aJ///7Iy8uDv78/LCwsMHv2bLz77ruGGAIA4OXlBVdXVxw7dgydOnUC8Pj2zjNnzuj+KFAoFMjIyMCFCxd0Ezm//vortFotevToUep5LSwsYGHBHauJ6pKnaxNPnDgRCoUCMTEx+P7771mb2MiK96Ru3LgxlixZAvH/X43k6+uLJUuW4LXXXkNaWhoMsHc1lSE6OhoRERF6JRFcXV0xbdq0Uks5UPVxLwaqC+p6Xg4wNyeq7SQWUtg1c0P7iSOQn5oOdb4KNm6NYWZtCQs7rkI3haKCojL7BEEosUKdakZORg6unIjF6Z9+Q15mLuROcvR7qz9adG0NaxnL69S07MxcpD54WGpfXk4+0lMz4NbMpdR+IsBAk+gikQjz58/HnDlzcOvWLeTk5MDHxwe2ts++I3dOTo7eLahKpRKXLl2Co6MjmjVrhpkzZyI8PBytWrWCl5cXQkJC4O7ujpEjRwIA2rVrh5dffhlTpkzBmjVrUFRUhOnTp2Ps2LEs60BUzxTXHt65cye++OILXbtEIsHYsWNZm9iImjZtips3byItLQ1qtVrvwwq1Wq2ru9u0aVMTRVi/RUdHIzQ0FAqFAiEhIfDy8oJSqURUVBRCQ0MRFhbGiXQj4F4MVBcwLyeimmBmYQ4zCzmsHLlhZW3QyKvsu3tsGstgZsmFRTVNlVeA6B+O488D53RtmamZ2LPyPxgw6WV0H/ocJOYGmZKjStJWcNeumndsUAUMUs6lWEJCAu7du4cOHTrA1ta2SisQz58/j86dO6Nz584AgPfffx+dO3fGwoULAQAffvgh3n33Xbz99tvo3r07cnJy8Msvv8DS0lJ3jqioKLRt2xb9+/fHkCFD0Lt3b6xbt84wF0lEtco777yDffv2YeTIkejWrRtGjhyJffv2cQLdyIonP7RaLYYMGYK1a9fi3r17WLt2LYYMGQKtVqt3HBmORqNBREQEFAoFwsPD4evrC2tra/j6+iI8PBwKhQKRkZEs7WIE3IuB6hLm5UREDYegFeDuV/q+Fx1H+4M3h9a83Ixc/HnwfKl90dt+RXZ6Tg1HRHb2trCTl76owMzcDI3dGtVwRFTXiAQD3Gv/6NEjvP766zh+/DhEIhFu3rwJb29vTJw4EQ4ODnorROuCrKwsyOVyZGZmQiaTmTocIioHS1qYxoULF/DBBx9UeNwXX3yhVyOdqu/ixYuYNWsWvv32W/j6+pboj4uLQ3BwML788kvdxBcZRmFhIQYPHgyZTIadO3fqlXRRq9UYM2YMsrKycPDgQZaSonIZM9esb3k5wNycqDbSqDUoyslDbuJDqPNVsG3iBKmdDcytLSt+MRlcVlIaMh88RHZiOm4evwRVTj7sPZzQfpgCaXdT0OqFjrCwtTJ1mA2K8lI8okI2l9k/adU7cGvBhRc1SV2kxukjZ/Htwu9K9I0NHo2XRveFDTdGbpAqm2saZCX6rFmzYG5ujoSEBFhb/6+u0xtvvIFffvnFEEMQEZVQXNLC29tbb2NLb29vhIaGIjo62tQh1ludOnWCvb19ucc4ODjo6uSS4aSlpQF4XI+4NMXtxceR4RTvxZCeno4xY8Zg7969ePjwIfbu3avXzgl0MiXm5URkbJoiNbKU/+DaD7+gMCcPIrEYD2L+Qvy+31CYk2fq8BokK3sbZCdnIOXGffiN6g3FlCHw6NIKsbt/R5OO3pxANwGpdfl7e5hJWcqlppmZm6Gjoj1C132I9t3bQd5IhtZ+LfDhynfR75XnOYFOFTLIb+3hw4dx6NChErVvW7Vqhbt37xpiCCIiPU+XtHhyY8vw8HAsWLAAkZGR6NWrFyQSiYmjrX8kEglefvllbN++vcxjBg0axK+9ETg6OgJ4XJu4tJXoSqVS7zgyLO7FQLUd83IiMrainDwIEOA9pDdS/7oOdUEh7Ft4wM7DBenx9+DcoRVEYoNWjqUKiCVmcGnXDHL3RlCeikN+Zi6cWrqjy7gXYW7DuwNMwc7RDrYOtsgppWyLaws3TtiaiNxBBrmDDE3CXZGfr4LUQgpHJ3tTh0V1hEEm0XNzc/VWuhRLS0uDhUX5n74REVVFbGwskpKSEBISoptALyYWixEQEIDg4GDExsaypIURaDQanDhxAg4ODkhPTy/R7+DggJMnT2LKlCmcSDcwPz8/uLq6IioqCmFhYbhy5QrS0tLg6OiI9u3bIyoqCm5ubvDz8zN1qPXWO++8g4kTJ2LPnj148OAB3N3dMWLECK5Ap1qBeTkRGVtRgQrZCclIOhena8u8/Q+kMhu0GTMQRbn5kNpxgrAm5WfmoDCnAGIzCRq3fFwiRCwRw9zaAomxt9Fc0Q7mlnwPqEl2jWR4PSQA+7/5L9o97wNbB1tkJGfg5rnrGDl7DKzl/B0xJXkjObgtMj0rg0yi9+nTB//3f/+HTz75BAAgEomg1WqxYsUKvPDCC4YYgohID0tamFbxhxjA4//zn9xeQyQS6SbW+SGG4UkkEkybNg0LFy7EK6+8ApVKpeuzsLCASqXC4sWL+eGFkRWXdiGqbZiXE5GxiQC9CfRihVm5eHDmMjz6cj+cmlZUUIiUG/dw/fAFvXaJuQR9Z45GUb6Kk+g1TCQSQe5sjz5v9MVv208gIzkdTs2cMXDyy7B1KH1zSyKq3Qwyib5ixQr0798f58+fR2FhIT788EPExcUhLS0Np06dMsQQRFQPFRQUICEhoUqvzct7XG8xOjoa3t4ld6KPj4/XHXfjxo0qx9isWTNYWvIWyKelpKTo/t2tWzdYWVkhOzsbdnZ2yM/Px7lz50ocR4YlEomeqZ2IGgbm5URkbGl/l10aKu2aEk2e71iD0RDwOP97egIdADRFGlzccQKKKUNMEFXDVlhQiD8PnsPJqF91bff/voet8zdh5OzX4NPbF2IueiGqUwwyid6+fXvcuHED33zzDezs7JCTk4NXX30VwcHBcHNzM8QQRFQPJSQk4O23367WOZYvX15u/5M1i6ti3bp1aN26dbXOUR/FxT1efWRhYaGbMH9S8YrouLg4DBo0qKbDq9ee3A9g/vz5WL9+Pe7fv4+mTZtiypQpWLJkCfcDqAEajQaxsbG6Ujp+fn78elOtwLyciIxNq9Ho/i2WmkFsbgZ1bgEAQNBoTRVWg/bw1oMy+9ITUqBWFdVgNAQAuRk5+G37CQCASCyG1NIcqvxCQBBwaO1+NPPxhMyJBUWI6pJqT6IXFRXh5Zdfxpo1azB//nxDxEREDUSzZs2wbt26Kr/+zz//xNq1a9GhQwd07twZmzdvRmBgIC5evIjLly/j3//+N7p06VLtGKmkR48eAYBeKZEnFbcXH0eGU1xKp3379hg+fDg0//8P2fPnz2Pv3r3o168fEhMTWUrHiKKjoxEREaEraQQArq6umDZtGvz9/U0YGTV0zMuJqCY4tGqGwpw8uPfsAE1BITSFRbCwt0NeSjoexcVDbG6QtXr0DCq8EZF3Kta4zJQMWNlZo/cbfSFrLEN+Vh6s7W2RmpCCUz9GIy8rj5PoJpKVno2MR5lIS82AvaMM9o3lsG/E7wVVrNrvbubm5oiNjTVELETUwFhaWlZrlXfr1q3h7u6OiIgIbN68GQCwefNmuLm5ISwsjJNZRlTZzem4iZ3hFdf5P3r0KBwcHDBp0iQoFArExMTgu+++w7Fjx/SOI8OKjo5GaGgoFAoFQkJC4OXlBaVSiaioKISGhvL/HjIp5uVEVBMs5bZw6dwW1388AksHGSTmZshLTYd9Sw80f6knS8uZQKMW7hCZm6HP1GGwaSSDVitAJALunr2G5KsJMJPyg42aZmZhjhHvv4rDGw7iYUKqrr1pu2YYNWcMxGZiE0bXcD1MSsNX89fi+l+3dG0eLZpgzhfT4dLU2YSRUV1gkN/af/3rX/juu+8McSoiomfi7++PqKgofPDBBwCADz74AFu3buUklpEV16Q31HFUeTKZDABgZ2eH7du3o0mTJrh06RKaNGmC7du3w87OTu84MpwnS+mEh4fD19cX1tbW8PX1RXh4OBQKBSIjI3V3BxCZAvNyIjI2rUaDh3G30GJoH9g1dYZUbguPft1g28QJGbfvQxBzEr2mSczEGBz6FpKv3cXRZT/gUNj/4dSavXBo5oLnJr78eDdYqlFWdtY4suEXvQl0ALh/LQHn95+BuYXURJE1XLnZediwbIveBDoA3Iv/B5/P/hYZj7JMFBnVFQb5OFKtVuP777/H0aNH0bVrV9jY2Oj1r1y50hDDEBGVSiKRoE2bNgCANm3asC5xDXi6TIunpyd69eqFU6dO4e7du2UeR9V3+/ZtAIC1tTUCAwNLlBSxtrZGdnY2bt++je7du5sqzHqpuJROSEgIxGL9dQhisRgBAQEIDg5mKR0yKeblRGRs+WlZsHKQ4/rOI7q21L9uwNrZAR79ukFbUAhYW5kwwgZILMb5rUeR8vc9XVN2UjpOr9mHnpMGw7kdS1TWtIKcfKQmpJTaF//nLRSpCms4IspKz8LFU6XfsZdw6z6y0rJg34gLkahsBplEv3Lliq7u8I0bN/T6eCsXEVH98/RK27t37+pNnpd1HFVf8aR5cnIyHBwcMHv2bL1yLunp6XrHkeEUl8jx8vIqtb+4naV0yJSYlxORsZlbWuDmyQsl2vNS0pF+IwFuPTuYIKqGrTAnX28C/Umxu39HX89XYWnLDzZqUn52OXfkCgKKCrjZa03L//8bIJclKyO7hiKhuqrKk+ixsbFo3749xGIxjh8/bsiYiOokjUaD2NhYpKWlwdHREX5+flwRTfVWQcH/EhAnJyekpv7vNkVnZ2ekpKSUOI4Mw9XVFQDg4uICAPj888/1+lxcXJCcnKw7jgzH0dERAKBUKuHr61uiX6lU6h1HVFOYl1NDoFWroSkshEgAROZmkEhZCsFUMu8+KLPvYVw8XJ8r+R5JxvXodtmLJ/LSsqFWccK2ptk62JXZJ5aIYWHDvaNqmrWdNcQSMbQaban99o25uSiVr8qT6J07d0ZiYiKcnZ3h7e2Nc+fOoVGjRoaMjajOiI6ORkRERImyCtOmTWNtbqq1CgoKkJCQUKXXqlQq3b8fPXqE7t27w9PTE3fv3sWFCxf0jnt6JWRlNWvWDJaWllV6bX3m7e0N4HG9+W3btuG7777D/fv30bRpU0yaNAlvvvmm3nFkOH5+fnB1dUVUVBTCw8P1SrpotVpERUXBzc0Nfn5+JoySGiLm5VTfFeXkIuPqdeTe/wcQBFg2bgTHju1hLrODSMzN+WqauqDsMhTaIjXvejEBCzsrSMzN0LxnO7j4ekLQCtAUqnEnJg6pN/6B2IyLu2qaWCJGs/bNkXDlTom+9n39SpQGJOOzd5Sh7yu9cHzPbyX6OjznA7kDS7lQ+ao8iW5vbw+lUglnZ2fcuXMHWm3pn+QQ1XfR0dEIDQ2FQqFASEgIvLy8oFQqERUVhdDQUISFhXEinWqlhIQEvP3229U+j1arxblz53Du3LkSfY8eParyGOvWrUPr1q2rG169k5X1eMOb7OxsDBs2TNd+/vx5/PzzzyWOI8ORSCSYNm0aQkNDsWDBAgQEBOj9nx8TE4OwsDDehUQ1jnk51WfqvDwkRZ+CJv9/d7cVPHyExOO/wa1/X0hlZa/2JOOQe7oh+fzVUvtsmzpDqOF4CHDwdEGfd0dAbCaBWCKBpkgNM0spfIcrkJuaCYmFualDbHDyc/LRc1QvWFhb4Oa5G4AgQGwmQfu+HeDdqQUKy/kwiozD0toSb0wdCbFEhBN7TkGj0UAkFuG5fl0Q+MFY2NnbmjpEquWqPIk+evRo9O3bF25ubhCJROjWrVuZfzQWb4JGVN9oNBpERERAoVDorUr09fVFeHg4FixYgMjISPTq1YuTKlTrNGvWDOvWravSawsKCjBjxowKj/vqq6+qvJq8WTNugFSaypYKYUkR4/D390dYWBgiIiIQHBysa3dzc+OHpmQyzMupPstPTtWbQC8maLXI/PsmGnXxg9jMIFt9USWJzc1g7eKIvOSn9gARieDeg/XQTUFiLoGV3BaZ/zyESCJGUX4hLOysoFYVwbG5K8Ri3h1Q0+wc7LBjcRQ6DeiC1+ePg0atgVgixs1z13Hk+0OY+Hn1FzPRs3NobI/xs8ZixPghyMvNh6W1BeQOMlhzzwCqhCpnG+vWrcOrr76KW7duYcaMGZgyZQrs7LgKgBqW2NhYJCUlISQkBGq1Gnv27MGDBw/g7u6OESNGICAgAMHBwYiNjUXnzp1NHS6RHktLy2qt9G7bti3+/vvvcvtZ1sLw2rZtq/t3t27dYG1tjZycHNja2iIvLw/nz58vcRwZlr+/P3r16sV9MKjWYF5O9ZVWo0Heg8Qy+/NTUqEtUnMSvYaJzc3QtE9nZMT/g0dx8dAUFsGuqQvcerRHbkoarJz4QX5NE7QC8jNycGlnNPLS/7c5onunFmg3qDvMuBK9xgmCgOde6YmEq3fh3NwFUispstOykRSfCP9xL0Ar8J4NU7G0soBlUydTh0F1ULWyjZdf/n/s3Xd8U/X6B/DPyW6TJt2LTjYUyxQsoyCgXETciojK8nIVHKhwlcusgnvAVUFxAD9FQcWtyFAElSEyZAmUUlpG90rTNvv8/uA2EtuU1eakzef9evHSfr/JOU9O2ubpc77nOf8AAOzatQuPPPIIk3XyO6WlZ1df/Pjjj3jooYfcLp9esmQJbr75ZrfHEbUkb775Ju6///56C+kdO3bEm2++KUFULd9XX33l+v/9+/e79adXq9Vujxs1apRXY/MncrmcJ0fJpzAvp5ZIEATI1J5vvidXKcH2294nk8tgqTAhvGsHtOqbCqcoQnQ4UV1QgtD2iYDIllLe5rDase2dtbBUVruNn9mbBW1IENoNYc7ibWV5pUjq1hpqrRrH92ZBpVHCWmNFrxF9oNIoUVVmQkhUiNRh+h2n04mCU0U4vPcosg6eQKvkGHRN64KI6DAoebKJzqNRTtkvW7asMTZD1OzUtktYs2ZNvTcGWbNmjdvjiFqaN998EyaTCTNnzsQff/yBrl27YsGCBdDp2E+uqezfv/+CH8ciOpH/YV5OLYkgkyEoORFVOSfrnde3aw05b0LudTKlAoakWDidImw1ZogiIBOAwIhQQAYISl6Z5W1VJcY6BfRax385gDYDeXWot+nD9Tj+x3FEJEahvKAM5QXliEiIhC40CJUlFdDo+LtLCrmZpzB/8suorDC5xtQaFWa89ijaXdEaCl7ZRA3gdwfRZTi3XULv3r1xzz33uG4y9/7772P79u11HkfU0uh0OkyZMgWTJk3ClClTWEBvYrU95pOTk7F06VIcOHDA1VKkS5cumDRpErKzsy+5Fz0REZEvkSlVMLRvi4qjx9zGA6IioQ4PlygqPyfIAFGEubgMBbv/hN1shSEpFpHd2gMyBUQ7V6J7W1Wp5xvKO2x2OO0OL0ZDACBXKRCg1WD1Uysh/u+K9axdmfj9u99w87TboFCyHOdtRXnFeH3OO24FdACwmK149ckleOqdGYiOj5QoOmoO+FNLdBnObasg/O1a0nO/ZlsFIjqX2WxGbm7uJT3XYDAAAM6cOYPMzExotVpotVoAQGZmJs6cOeN63NGjRy9pHwkJCS22CH85x95bWvLxJyK6GE6HA7ZKI5wOOyL79oGluASi0wl1eCjsVdWoyj0JoXUSlAG8IZxXCSJO/bIHEIGo7h0hyGSoKalA5heb0PaGQZBpVFJH6HcM0Z6vfFYGqiFXsfTjbXarHevfXusqoLvGLTZsfG8d7ph1l0SR+S9TRRVOZp2ud66ixIiK0goW0alB/E1KdBlq2yqMGTMGP/zwA6ZMmeKai4mJwV133YUPP/yQbRWIyE1ubi4mTZp0WduwWCyYPHmyx/k1a9a4WkpdrKVLl17WTWd9WWMc+6bWko8/EdHFEJ1OVJ08jerTeag8ngN1SDAgCKg8kQPR7oBCGwhdQrzUYfode7UF4Z3boOxoDo5/9wucdge00eGI698dZZk5COvSVuoQ/U5AsA5BUSGoLCirM9fu6m6QcdWz19UYq2GpttQ7V5ZXCpvF5uWIyGZt+JjXVJm9FAk1V/xNSnQZAv636iUsLAzLli3DW2+9hVOnTiEuLg7/+te/8N1337k9jogIOLvSeOnSpZf03CNHjuDll18+7+Mef/xxdOjQ4ZL2kZCQcEnPaw4u59j/XU5ODhYsWICZM2ciMTGxUbYJtOzjT9QciKIIp80G0WEHAAgKBWQKZZ2rDqnpCXL5X6s4RRHW8gpAECA6zramEB0OoJ77ElHTctodOLl5F2qK/irYVuUXI/OLn9Du5qshOtjOxdtKsvLQ/Y5BOLT2NxQfO7vSVq5UoE36FVDrAmCrMgMhvOG0N4lOUeoQ6G+CgoOgD9Xj3kdHIb51LGqqzNAEqlGUV4J3X/gAEbFsEUYNYxGd6DJce+212LBhA5YsWYLXX38dzv8l+b///ju++uoryOVy1+OIiGppNJpLXmncpk0brFy5EgaDAWVlZSgsLHTNRUVFITg4GEajEdddd53rdxD95XKOvSeJiYlcOU7UQogOB2xVlag6dQKivbaIroQ2PglKrQ6CjL9XvUkmk0GXEAenzQZ9m9aAKEJ0OiFTqVB18hRkSiXkGrXUYfode43FrYDuIorI274fbUamez8oP+ew27H93e/QdlBXdLimB5x2BwSZDCd/P4qjP+zBtbPvljpEvxMUpodMIYfT7kCAPhBagxaVpZWwVJkRqA+EOpC/u7wtNDIYGW8/gU/e+hJvzH3HdaKja98umLNkOoIMvLcXNYxFdKLL0KNHDygUCthsdS8LcjqdcDqdUCgU6NGjhwTREVFLJJfLMXnyZMydOxdXXXUVhgwZgo8++gijR4/GiRMnsH37dmRkZLCATkR0CRxWC0wn3G9gKdptMGVnQt8+BQoNry70NlVoKIIcThTv2us6sQFBgKF9G+iSEiDj553XVZ4s8DhnOlMEkQtwvS68bSysNRYc+u63OnOhSVHsiS4Bc7UZg8deg6DQINhtdhiLKhASEwqHzQ5AgN1mlzpEv2MxW/Hp0q+wdb37z8kfWw/g7Zr/w0MLfLvlI0mPv0mJLoPD4YDD0fCdzmsfw4IWETWW9PR0ZGRkYPHixdi2bRsA4KOPPkJMTAwyMjKQns4VYEREF0t0OmEuyvc4by4ugDY2AQLbh3iVaLOheNdeuFVmRREVR45BHRYKpY4rB71NqfN8MkmuUkKQsfWRt8mUCnS+rg8OfbvDbVyhVqL7nVdDoeTfot4mCAJatY/Dp8+uQlW5yTUeEhOKGx+7BSLPNnmdsbQSWzfUPdEEAH/uOYrKchPCIkO8HBU1Jyyi+wiz2Yzc3Fypw/AoISEBGo1G6jB8zueff37eDz9RFPH555/zxqJE1KjS09PRr18/fPfdd3j55Zfx+OOPs4ULEdFlEJ0OOGqqPc47aqohOp0sonuR0+lE5YlceFraXP7nUaiCDVDw/kNeZUiMwSkPc+Gp7Xj/AEkISOzdERHt4nD0h90wV1QhvG0sWg+4AnKVAk7wPfE2jS4AH85e4VZAB87eVPSHZetxw2O3ShSZ/6qqrIboFBEUrMMd99+E8JgwVJRU4JOlX6EkvxRlRWVIas+bVZNnLKL7iNzcXEya5LuXjixdupT9Xuuxb98+1//37t0bGo0GJpMJOp0OZrMZv/32m+txLKITUWOTy+Wum4d26NCBBXQiosshyCBTa+CwmOudlqs1LKB7mdPhgL3S5HHeXl3tuskoeU9VQQkSBl+J3B93uo1ro8NgSIyB0873xNsEiCg4chL7v9yKuB7tYIgNhzGvBD+98ikGPnILlIFcEOdt5spqVBSW1zt38lAubGardwMiBGgDcMf9N6FrWgq+XbkBJ7NOIyouAg9m3If8kwUwhOilDpF8HIvoPiIhIQFLly5tlG3l5ORgwYIFmDlzJhITExtlmwkJCY2ynZampqYGAKDVavH777+7biwKnL0RUmBgIKqrq12PIyIiosvncDiwb98+lJaWIjQ0FKmpqTyJRJdNJpcjIDIGNmN5vfOaiCgW0b1MEASoQoJRU1BY77xKrwf4nnidTCFH5alCpNx7PSpPFsBWXQN9UiwcZitO/rwH7W++WuoQ/Y7NbMXuVZsgOkUc/3m/29yejzej191DJIrMf1UbPV/ZBADWGhbRvS0oWIuEdnGYNf4Z101FT2adxu+b9+KfM+5BUEiQxBH6t5LiMphrzJAr5AiPCINC4Xu5PYvoPkKj0TT6Su/ExESuHm9iISFn+2VVVVUhODgY9913H9LS0rBt2za88847KC8vd3scERERXZ4tW7Zg8eLFyM//q3d1dHQ0Jk+ezPsB0GWTqdXQxiWh6nQuIP5vcYRMBm1cEmQqruT0NgFAQFQEjJlZ9a4417dt7bHVCzUdXXwktDHhyP/9EGqKyiHIBFTllyC2b1ckD0uDXK2UOkS/U5ZT6CoK/l3R0VNw2Hh1gLfpww0e5xQqBdSBai9GQwBQU23GO8+8X+/PyopXVuP5nh0liIoqjSb8sfsgXnz6DWQfy0GQXocxE27D7XfdgIioMKnDc8MiOtFliIyMdPtaFEXXv4YeR0RERBdvy5YtmDt3LtLS0jB79mwkJycjOzsbK1euxNy5c3ljXbpsMrkCquBQKHRBcNpsZ8eUSsgUSq5Cl4JMhqozeYjo3QOl+w/Bbqo6O6xWIaRzR9QUFkFp4OX3XucAjn25GTVFZW7Dxtx8dLrrH7Bb7VAGShSbnxKdTgRFhaD7HYOg0qlht9ihDFCjOOsM9ny8CeC5Jq9TqhXoeX1v9BreG6LTCavZCnWgBk67Ewe37IeSJ5u8rspYjfKSCgBnr3TSBKphrrFAdIqwWqwoKSxFbFK0xFH6F1EUsePXXXjs/jmusUqjCW8uXI6D+45g/ktPIiQsWLoA/4ZFdKLLUFVV5fr/8vJyvPzyy+d9HBEREV08h8OBxYsXIy0tDfPnz4fsfwXNlJQUzJ8/H7NmzcKSJUvQr18/tnahyyLIZJCr1JCruEpQaqLDCVVQEEr3H4K+bWsoAjRnF6w4nKjMyoZSHwTew9L7zGUVdQroAABRxMlNv6PtDQO9H5SfC28Xh/A2sdj5wUaUZp+9UkumkKNNeiqGPjEachU/F73NVGnCVTf2Rd6xM1BpVLDb7LBUW2CptqD78J6oNlYjOIpXrHuTIAgI0Gpw0/gRiG8di8pyE7QGLYrzSvDZu9/wpsgSKCoowfMZr9U79/OP21BUWMIiOlFLITtnRZJSqYTtfyuW/v61jCuXiIiILsu+ffuQn5+P2bNn1/lclclkGDNmDKZMmYJ9+/ahe/fuEkVJRI1JkAlQBAZAkMtRute9z7NMpUJwSiePLSyo6ZQfP332fwQButgIyBRyVBeVwV5thulMkdt9osg7ZDIBPy/+GqaiCteY0+5A5o97oAxQoXX/LhJG55/0IQZUlVdBrpCjqqIKxqIKhMSEQqlSorq8CrpQ9t/2Nl1QIB597gGseedrfPT6Gtd4fJtWeOjpfyI8KlTC6PyTyVSFgrwij/MH/ziM9p3aeDGihrGITnQZWrVq5fr/+v6gr+9xREREdPFKS0sBAMnJyfXO147XPo6Imj+ZXA4IAkI6d4CltBxVp05DdDgQEB0FbVwsrEYj1OEsenibMjAA4V3aIKxzG5hOF8JuNiOyewc4LDac/nkPBHA1p7dVlRrdCujnyvxxLxJ6s9eztzntTlirLfjuja9RVW5yjYfEhGLkIzfDaefJJm8TBQFrV/2AI38ccxs/mXUaHyz6GI88e79EkfkvpVIJmUzm8eRrsA+tQgeaYRF93rx5yMjIcBvr0KEDDh8+DAAwm814/PHHsWrVKlgsFgwbNgyLFy9GVFSUFOFSM2A2m5Gbm3tJz01JSYFMJoNKpYJWq4XFYnHN6XQ6CIIAq9WKlJQUHD169JL2kZCQAI2GN7IiIiL/Fhp6tlCWnZ2NlJSUOvPZ2dluj6Omx7ycmpooipAplTCeyAUgILTbFRAEATXFpSg7eBjhPbtBtNkBtUrqUP1KWKckVJzIw5GP17vGCnYdRmBUKNrdNhQCW4d4XcWZEo9zthoLHBabx3lqGg67A9+89qVbAR0AyvJKsen/NmDEwzdJE5gfs1ms2PPrvnrncjJPwVxt9nJEFBpmwMChfbFp/S915jQaNTp0ai1BVJ41uyI6cLZwuXHjRtfXCsVfL+PRRx/Ft99+i08++QQGgwEPPvggbrnlFvz6669ShErNQG5uLiZNmnRZ2zCbzTCb3X/hlpT8lchMnjz5kre9dOlStG/f/pKfT0RE1BKkpqYiOjoaK1eudOuJDgBOpxMrV65ETEwMUlNTJYzS/zAvp6YkOp0ozzyO0M4dYS4uQcWfRyE6HAiMi0V47x6oyMxCSEfmyd4mOp3I2bC9znh1QSlKDmYhunfdE53UtIIiPffWlqsUkKuaZemnWasx1aCisLzeuZOHcmHniQ2vs9RYGpw3VfBedt6m1Wnx7zkPIvPwcZzKPeMaVygVWPTOAkREhksYXV3N8jepQqFAdHTdO+ZWVFTg3XffxYcffojBgwcDAJYtW4ZOnTph+/btuOqqq7wdKjUDCQkJWLp06WVt49NPP8XGjRvdLkGRyWQYOnQobrvttsuOj4iIyN/J5XJMnjwZc+fOxaxZszBmzBgkJycjOzsbK1euxLZt25CRkcGbinoZ83JqSoJMhpBO7VG8aw8sxX+1arJWGFGZnYPo/mkQ5M3yT9pmrexoLmQKGVoN6Al9YjQECLBV1+DUz3tQ+McRRPVg6xBvC4oMhsaghbmeImDr/l2gCODVGt5mrW64YGu32r0UCdXSBGogk8vgdNTfOkTPPvWSaBUfg2Wf/BeZh49j144/0Co+Blf174nI6HAoVUqpw3PTLDOOzMxMxMbGQqPRIC0tDc8++ywSEhKwa9cu2Gw2DB061PXYjh07IiEhAdu2bWOyTvXSaDSXvdL7P//5D6ZNm4Z33nkHH3/8Me644w7cd999UKmYrBARETWW9PR0ZGRkYPHixZgyZYprPCYmBhkZGUhPT5cwOv/EvJyakiAIsBmNbgX0Wo7qGlRm58DQuYMEkfk3p8OBlHE3IP/3Qzj982447Q5oo8MRf3UvmE4V8GavEhBFEQMevBHbln77V290AYjv0Q5t0lNhr7EBBmlj9Df6cM8HXKFSQKNly1Zv0wRqMGB4GjZ/U/eKuJReHRGgDZAgKgKAqOgIREVHoP+gPlKH0qBmV0Tv06cPli9fjg4dOiAvLw8ZGRkYMGAADhw4gPz8fKhUKgQHB7s9JyoqCvn5+R63abFY3HpZG43GpgqfWjCVSoWhQ4fi448/xtChQ1lAJyIiagLp6eno168f9u3bh9LSUoSGhiI1NZUr0CXQFHk5wNyc/uK02VCVe8rjfNWp09AlJ0IepPNiVBSe0gaZX/yEmqIy11hVfjEOr1qHTqP/ASj4+9jbLJU1OLUnE73HDQMA2Gqs0BgCYSoqR/Hx04hoEydxhP5HrlKgU78U/PnrQcgUMgQGBcJUUQ04neh9QxoUbLHjdQ6HA70GdkPH7u2hD9FBp9eiyliF8hIjwqNCeAKQzqvZ/dQOHz7c9f+pqano06cPEhMT8fHHHyMg4NLOGj377LN1bopERERERL5JLpeje/fuUofh95oiLweYm9PFEKQOwC+Zy4xuBXQXUcTJn35HmxsHeT0mvycAmT/uReaPewEACo0SdvPZntuBoUFIf7iVhMH5J0uVBf3uGID+d6TDZrWjqtyEoDA9ZHIZHA4HLDVWqUP0O5VGExLbJQBwotpUg5LCMgSHGdAqORaqACUKcosQk8Cbn5Nnza6I/nfBwcFo3749jh07hmuuuQZWqxXl5eVuq14KCgrq7dVYa8aMGXjsscdcXxuNRsTHxzdl2ERERERELUpj5OUAc3M6h0wGbXwcqs/Uf/WCNi4WgqLZ/0nb7JQfP+1xznSmCKLd4cVoCAAqTpe4/j8kIRIqrQaV+WWoLqtEdWklnHxPvE4TpIbT5sSa51ajKLfQNR7fORE3TL0ZTtTfl5uaTnBEEBxmJxbPexdH/jjmGk9oG4epz92PmEQW0KlhMqkDuFwmkwlZWVmIiYlBz549oVQq8cMPP7jmjxw5gtzcXKSlpXnchlqthl6vd/tHREREREQXrjHycsB3cnPR6YToZJFDSk6nExAATUR4nTmFNhABUREQ7bw5n7cpAz1faSJXKXmBgARUgWpEd0nCgIduQvuhPRDfqwO63TEQV00cjoBgHQR5sy/9ND9OYM3z7gV0ADh5KAfr3v4Oct4U2ftsApa9tBJH92UhpWcHDLqhP7r17YJT2WewaMabMNc0fDNYomb3Uztt2jSMHDkSiYmJOHPmDObOnQu5XI7Ro0fDYDBg4sSJeOyxxxAaGgq9Xo+HHnoIaWlpvHkREREREVEjaql5udNmhb2mGpbSYgCAOiwCck0g5EqlxJH5HwFATUERtAlx0CUlwGk92/5AkMshV6tRceQYwnp0lTZIPxTaPgGnf9lT71xEajvI2OvZ6wxx4Wiv7Q6n3YHCwydRY6xCWFI0wlrHoO/9IyFTsk+9t5lNNSjKKax37tjvmbCyYOt1NdVm1JjMeHLRI9j/2584lX0Gka0i8O9XHsb6T35ElbFK6hDJxzW7T7dTp05h9OjRKCkpQUREBPr374/t27cjIiICAPDqq69CJpPh1ltvhcViwbBhw7B48WKJoyZqWQoKClBRUSF1GG5ycnLc/utrDAYDoqJ4eRgREbUcLTEvd9qsMOVmw15V6RqzGcuh0Omhi0+CTMkbx3uTIJdDF98K9uoaOK1WVJ08DdHpREB0FOQaNXSJ8RB4U2Hvk8uQdG0aTqzf5jYcGBWGyO4dIdp5BYe3yeRylJ8qwr7PfnGN5R84AZVWg77/uh4yhVbC6PyTqbyBgqwowlLNIrq32e0OXH/3MLw8fTGslr960v/w2RbcP2ccrFabhNFRc9DsiuirVq1qcF6j0eCNN97AG2+84aWIiPxLQUEB7r7nXtisvvmhv2DBAqlDqJdSpcYH7/8fC+lEl4gn7y4eT95RU2uJebm10uhWQK9lNxlhqzJBHRwqQVT+SyaTQabRoPLQEViK/+r5bC2vgDwwAFH906AI0EgYoX8qPXICwcmt0GXCjSg/dhL2GjMMya2gNgTh5JbfET/wSqlD9Dt2ixX7v/i1zri1yoyD32xHr3uGShCVf9OHBXmck8ll0Gj5u8vbNAFqvL9wtVsBHQAcDgeWv/QRnn5vhkSRUXPR7IroRCStiooK2KwW1LQeCKfGIHU4zYLMXAEc34yKiopGKWixmHhxWEhs/njy7tLw5B3RxXHYbbCUFHmct5QUQhmkh4x9bL3KbjK5FdBrOaprYMo5iZDOHSDI2O/Zm3TR4cjd9Dsqc/MRntIG8gA1TmzYAWtlFdrfPJg90SVQcboYolOsd67o6Ck4bbyxqLeptBokdElC7oETdea6DOoKVQCvbPI2S40FhaeL652rqqyGsdyEVl6OiZoXZoBEdEmcGgOc2ro3eaKmxWLixWMhsfnjybuL19gn74j8gtMJiJ7bUIhOEaLDCbB7iNc4nU6YTuT+NSCTQRAEiI6zBcGq3JPQt06EIjBQogj9kyCToTI3HwBQfDDLbS5v50Ek/6OfFGH5Ncd5iuSeCuzUdJyiAyOn3oQTf2RDG6yD3WqDQqlATWUNElOT4XTwPfE2h6Phn5PzzROxiE5E1IywmHhxeBWAtBr7KgCevCOiJiWTQWUIQY25pt5pVXAIwBXP3uU8e1JDHRYKfdvWgChCFEXIlApU5Z6GuaSUxUEJlGeddP2/KkgLmVIOS0UVRIcDxhNnIDpZiPK20ETP+ZY+JhRy3uzV65RKJSxVFhzeeghZuzIBnD0BlTLwCrTqGAeNLkDiCP2PVhcInUELU0XdfvUKpQIh4cHeD4qaFf4mJSJqhlhM9D5eBXDxeBUAETUnMpkcCp0estJiOB12KALO3ojPXl0FmVIBRaAWMhbRvS6oXRvYTVUo3rUXot1+dlAQYGjfFqHxsYCMvUO8TaZQQJ8Yg+henWE3W+GwWKEJ1aMqvwRntu2XOjy/ldinI3J2HEZIQiRUWg2M+aUwV1QhZWQaBP6YeJ3D5sDaxV/j5KG/rqYRnU4c2PQHBAADxwyWLjg/ZbXZcce/bsJ7L6ysM3fDvf+AucosQVTUnLCIfpm4KvHisDcxETVXvArg4rCdCBE1N6LTgZr8U9AltoHTYYfNeDbH10TGQJDLUZN/GrqE1uy/7UWiIECuUKBg9x+AeM6Kc1FExZFMRPbtDTbg9r6Q9onQRoch84ufXK11ACC4TRw6jLoGgpw9j7yt+HgektI6o/2QHsg7kI3qMhMSe3dESFIUjv30B4Iig6UO0e9YqixuBfRzHdi8H2m39vdyROR0OFFaWIZZix/H5+9+i9ysU4hqFYGbJ4xAUX4p7HZeRUMNYxH9MnBV4sXjqkQiau54FQARUQslCFCHRaKmKB+2ijLXsKWkEKrgUKhDwlmv9TLR6URlzkn3Avo5yv88ivA+Pb0cFcmUChz78icEt0tAzJUpEGQyVBWV4cT67dDFRiCsS1upQ/Q7IUlRqCmtxJb/fgHxf22Qjv+8H9pwPfpPvgGCgif/vK2q3ORxTnQ6Ya2xejEaAgC1WoUuvTth2Qsfomd6V1w1tBfKisvx4etrcNdDtyFQz/trUMNYRL8MXJV4cbgqkYiIiIh81v96a59bQK9lLS+F0hACsP22d4ki7JWeC1H26mrX+0beU3H8FLqMvxE1JeU4uXkXHBYrDEmtkDrhRuTvPuTxpAc1HZVGhZ/e+95VQK9VVWzE/s+3ovvoQdIE5scC/leQTbwiCX1vHQC1VoOqchM2r/wRhTmFUAWoJI7Q/wgyYMXLq3D6RB5On8hzm1u6YAXmvvVviSIjADBVVqGqqhpKhQKh4SFSh1MvFtEbAVclEhERNT1ZTbnUITQbPFZEF08UnbAUF3qct5QUufqkk/eoQoJRU1D/+6LS69nrWQKG1q1w+tc/UPpntmusurAMRfsy0WnMcIgOZwPPpqZQllsIp4dWFHkHsnGFha1DvE2ukOPuBeNQXVGNTe9vRHlBOSISIjF0wjDYbHYI/OXldZYaK05mna53rqLEiCpjtZcjIgAw11iQnZWD1196B3/sPoSIyDDcN+VupA3o5XPFdBbRiYiIqFkIyN4idQhE1IKJogjR6bkfquiwc4WttwkCAlvFwJiZ5dZ7u5a+fVuA/be9zmG2uhXQa9nNFpz6eTcShvaRICr/ZquxQBmoQtdb0xESHwmn3QFBJuDEjsM4tmkvRPZ69jp1oAaHt/2JX1b95Bo7eSgHH875P4ycejPUbdTSBeenbDZ7g/Pmat5YVAr79h7CpLseg/N/V9IYKyoxY+p83HrXSDz6xL+gDw6SOMK/sIhOREREzUJNcjqcAcFSh9EsyGrKedKB6CIJMhmUOj0c5pp655VBBkDOvsLeJBNFGE+eQmTfK+GosUCmVEAURUA8e9PRmoICKLTsYettpUdyPM6VZZ5E/KBeXoyGACAkIRKDp4/CoW93YNfKHyE6nVAHBaDziKuQ/vDNkCl5ssnbHDY7tn5Sfy628b11GPfCfV6OiAJ1AdDqteh3bW9069sFNpsdSpUSh/ccxfpPNyE00rdWPfuD4qJSzP/Py64C+rnWfPg17pl4O4voRERERBfLGRDM9mkSKSgoQEVFxWVvx2KxID8/vxEiahrR0dFQqy9/ZZjBYOD9X5ohmUIJVXAoLGXFdVY9C3IFVPpgyOT888mbav+kFu1OlP95BPaqs5fay1RKhKR0Otvgloig0mqw/d21KMv5q/WRpbIGe1ZtQs+7BkMfy/zJ28oLyuH00NqoxliNmsr6T9hS05HJZfjPf6fi24824KXpb8DpcEIQBHTt2wWz3ngcgowtdrytsqISJ46f9Di/b/chtG6b6MWIGsYskIiI6CKw1/SF4XFqOQoKCnD3PffCZrVIHUqzoVSp8cH7/8dCejMjCAKgUECX0AbmkkLYjOUAAKU+GJrwSAgKJXvYSkAbH4f8n35xO7HhtNpQsmcfIvv1YdFDAqEdEpG/82C9cyHtEyEoWGbwNrOx2q2Afq4DX29HZMd4ALyngzcpVA2v/pfxyiavEwCsXf0Dtq77zTUmiiL2/rofVrMV/5xxr3TB+anz/RxofOwGvPx0IyJqhligvDBNcZzYIoP8TUVFBWxWC2paD4RTY7i8jTntkFlMjRNYE3CqdYDs8tJjmbkCOL4ZFRUVLKI3QwqVGg4A6pAwaMKjAIgQHQ7IVGrIVb71h5y/qD6TV28/dAAwHj2GsJ7dvBsQQZDJEJbSGiUHj7uNKwLUiOvXlf23JVB2ssjjnKWyGnaLzYvREADoQoKg1mpgrbEiuVtrBIUEobygDDkHcxAaEwp1IHuie5vVYsPW9b/VO3do1xGYa9gT3dvUahV69knFrh376swpFHK079RWgqg8YxGdmq3GurS8MeXk5Lj915c09qXlLOJeOBZyWxb25b4w7Mnd8giWSsha+E0VG6PAL1h99yQBXRhBEABBgLm4AACgDotg2xAJWUvLAQDKIB0CYqIhCALMxSWwlJTCaqzkvV4lUHm6EJFdOyCkfSIKdx+G3WyFITkW4SltcOqXPYgf2FPqEP2OJsjzvQFkCjlkCvZE9zoBuGP2GNjMVhzbeQTlBeWIbR+HvrenI9Cg5Up0CZirzR5b7ACAsazSi9EQAJjNVtw35R5kHZ2P8jL3+t6jM+5HRZlRosjqxyI6NUu+fmn5ggULpA6hjsa+tJzFMWmxkHthmqKQy77c5G8MBgNkMjk0p3dLHUqzIZPJYTBc5qp9koTTZoXpZDbspr/+kLYZy6HQ6aGLT4JMydXoXiUIUATpEB4XC6fdjqqTpyE6nQiIjoShQ1tUHs8Bm7l4X3ByK+x/7wsERoUhuldnyJRymE4XYf+7XyAuvQfkKqXUIfodfUwolAFq2Grq/n0c16Mt5EqWfrxNFahG6ekSfPLMKoj/u2nisd+P4vdvd+Cup8dCHcU8wdsCdYEQBOHsDarrYQjVezkislqseD7jNTz98pP480AmDu07jPDIMAwc2hfrv/kJarUK3a+8QuowXfiblJqlRr203A80xaXlLOJeOBZyiag5i4qKwuLFb+DkSc83/ZFCXl4e3nvvPUyYMAExMTFSh+MmPj6erVyaKZup0q2AXstuMsJeXQWVgUV0r3I6EZSUgJK9+2EpLnENW8sroAgMQGTfPhDBpeje5hSdSB7eH9nrtiLr679y3OA2cdC1ioCTlwd4nSAAvccNw2/L17kV0kOTo9Hu6m4QG1h9S03DVmPFl6+scRXQXeMWG7569TOMnncPAnWeryCgxqfSKNG1bxfs/XV/nbmkDgkI0GokiMq/BQRqUFxYgocmzEBKake0bpuIwvxiPHb/HNisNtw86jqpQ3TDIjo1a06NgYVEibCIS0TeJjP7VgsvX9bYx6pjx47o2LHjZW/HbDYjNze3ESL6S0xMDBITExtlWwkJCdBo+AeUv3La7TAXF0KmVEEdFgm5+my/WofFDEtJIczFBVDogiCT808or5HJYKuqdiug17JX18B08hSCWidLEJh/KzlwHFV5RWh34yBYTdVwmK0IiAhGVUEpjn76I7qMHyl1iH7HYXNAHRSA3uOuhdVkhrmyGkGRwYAAmCuroQrkZ5u3VRYbYamu/8r5srxSmKvYf9vbTBVVuPbWQbDUWPDn7qOu8aQOCbjrwVtRUVqJ6HgugvAmuUKBO+6+Ee8t+RAH9x3GwX2HXXNJreOh9bETTcwAiYiIyKcZDAYoVWrg+GapQ2lWlCq1z7UUyc3NxaRJkxp1m43ZQm3p0qVo3759o22PmhsRMrUa6sho1BScgcNcAwCQBwQisFUiLOVl4KJnLxNFVOXkQhmkg75ta8jUakAUIYpOVB4/garcU9AlNc5JNLpwTrsdxtx8GHPzodQGQKZUwFpZxdXOEpKrFDj4+a+I7ZIMbVgQNPpAQCZD4eFcBARrYYjl4idvczrP8/PAKza8zm534PU57+KBueNxz9RRqCg1IihYhypjFZYuWIFJs8ZJHaLfsZgtiGkVhTHjb8UnH34Nq8UKAOhxZSr++dA9yMk+hU5dfCc3ZxGdiIiIfFpUVBQ+eP//fPJm0gsWLMDMmTMbbSV0Y2rsG0o3hoSEBCxdulTqMDxKSEiQOgSSkCBXICA8EsasI27FDUdNNUw5x6Fv0wGCnDfn8yoRUOi00CbEo2z/QdirqgEAMpUSwZ07wlZVzUKUBELaJ6Jg158AAFtVjducITkWAm+Y6HXFmafR8dqesNVY4bA5YDNboAkKRHRKIoqPnYHNbJU6RL+jDzdAppDDaXfUmQvUB0LN1iFeF6TX4oE547B94+/Yu+0AwqJCUFZUjjYpyZj45D2IiOHJJm8L0uuwctkadO7SHs//dw4cDgdUKiUO7juCJx56Cu9/9obUIbphEZ2IiIh8XlRUlM8VhGslJiZy9fIF0mg0PFbku0QR5tLi+ouyohOW8hIEagLONh8m75DLoI2PQ/5Pv0B0/FWIclptKN27H5H9+rBgKwG1Xgt9YgyMOXlu4zKFHPEDe/FkkwS0EcGQKxX4bdk6VJUYXeOturdFygj+nEhBhIi+t/bHL6vrXkk5eOw1EPiWeJ1aq8bBXYdxRZ/O6JneFQWnihAWFQK5Qo5fvt+OOyffLHWIfic8IhRznnkc/7zrMXz35Ua3uTvuvhFhEaESRVY/FtGJiIguAvtyXxgeJyJqbkSnA44qk8d5e5UJotMJQcbKh9c4nag+k+dWQD+X8egxhPXq4eWgSHQ4kTC4N4w5Z1C45wjsZgv0SbGIveoKWEzVUOi4wtbbtKFB2PTyJzAbq93GT+85hgCDFh3/caVEkfkvu8UOQRBw/cM3Ydfa31BeUI7IhEj0ur4PsnYfQ2yHOKlD9Dtmkxk9+nfFey+sRP7JQtd4SHgw7p8zDlazTcLo/FeXrp3w0ddv4fWX38P+PQcRHhmG+6bcjT59e0BvCJI6PDcsohMRNUMsUF6YxjxO7Mt98XyxJzcRkSeiCAhKFWCp/2ZvMoXSyxERAFhLyz3PGSshOusvsFPTqcg5g5wNOxB+RVskDUuDIJehpqQCh1ethyCXodNd/5A6RL9TWVhep4BeK/vXg2g7sCsQ7N2Y/F11RRXys/KQmJqMvrcNACBAAKDWalCUUwgbC7Ze53A4sOadr90K6ABQVlyO955ficdemCxRZP5NE6BGx5R2eP6/s1BlqoZCqURoWLDUYdWLRfRGIKsplzqEZoHHiejysZB78RqrkMu+3BfPF3tyExF5IgiAJjwKJpOx3nl1OH+feZ0gQKHXAQWF9U4rtVoAbK/jbTXF5QAAc0kFqgtLIVMqUJVfAqfdDmeNnTfglUBVief81GGzw1FPX25qWvoIPTr164yVs1ZAPOcmo0q1EjdNuw0BQQESRuefnE4RR/44Vu9cweki2G12L0dE59LqtNDqtFKH0SAW0RtBQPYWqUMgIj/BQu7Fa8xCLvtyExG1XKIowmmzQBMeBXNxgducJiIaDosZcg2LHl7ldEIXH4fKY9n19qrXt2sDsL2O12ljItA2MQbWymoU7PoTDosV+uRYdBx1LfJ2HuJ5DQnoIoI9zikD1ZAr2afe22RyOdYt/c6tgA4ANosNG99bh9Hz7pEoMv9lPc8NdqtNNQ3OE7GI3ghqktPhDAiWOgyfJ6spb/QTDlzdfmGa4jixnciFa+xjxUIuERFR4xOdTlhKiqAI1EKX1A4OSw0EADJ1AKwVpXCYjFAFsUWVNwlyOarzCxDesxtK/9gPZ+0qQZkMhg5tYauqgiqY74m3BSVE4cT322A8ccY1VnooG2VHc5Fy9wjIlWx95G2qQDV0kcEwFZbXmWubngpBxjMb3lZZWglLtaXeubK8Uo9z1HQ0Wg2UKgVs1vpXnOtD9V6OiJobFtEbgTMgGE5tuNRh+CVeBeB9bCdyadgbmoiIyLcJMhkUWh0sJUWwlBZDplIBIuC0nV25pgmPBuRc9exNosMJe7UZmogwhPfuCdHugOh0Qq5WAYIMlSdyENgqRuow/Y7NWOVWQK8l2h04uXkXkkb0kyAq/yZTyNFj1NU49N0OFGedfW/kSjlaD7gC2shgttiRgPM8LXT+vkKdvEAEhtycju9X/1hnqvfVPSCKfE+oYSyiU7PGqwAuTGNeBcB2IpeGvaGJiIh8m0yhhDo0AtbyUogOB5zWvy77FuQKqEJCIZPzzyevEgTo2yShbP8hBCUnorYSKDqdqMrNRVByEgSBJza8rfRorse5iuzTED2s8qSmY6uxIuuX/YjsGI8O1/aE0+GEIBNw8vdMGJxifd2QqIkFhekhU8jrLaYH6AOhDtRIEJV/kyvkSGyfgBvHDseGNT+h2lQDlVqFgdf3RedeHaBSq6QOkXwcs0Bq1ngVgDTYToSIiIhaGkEQIALQJbSGuaQQNuPZBQNKfTA0YRGAIEAQ2BLBq2QCbEYTdPGtULJ771/tXAQBhg5tYa+qglzLPvXeJlN47q8tyOVc9SwBs6kGXUam4cS2Q9i5Yj2s1RYYYsPQeUQfqIMCITp5Y1Fvs9RYcNVNfbH105/rzA0cMxh2O082eZvNZofNakPusdOY+OTdUCgUEEUR23/4HaeyziAqNkLqEMnHsYhORERERER+T3Q6YSnKh9VYDk1EDAKiWgEArBVlqMzJgio4FNrYBAi8kaX3OBxQBKiR//M29xuLiiIqDmcivFd3FmwlENwmDnnb99c7F9YpCYKCPyPeFtwqHD+98gkMrSLQ7faBkKsUqCoxYv8XvyKqcyI6DbtS6hD9jtPhhFwhx/UP34Rda39DeUE5IhIi0WtEbxzffQxxHeOlDtHvCCLQ7orWCA4zYO2qjTiVdQaRcRG49varkdQuHk622KHzYBGdiIiIiIj8nuh0wGExIyi5PUS7DTUFZ/sKq0PDEZTcDtV5pyE6nSyie5NMhqrTefDUi6Ly+AmEh4V6OShSBmoQfWVn5O885DauNugQ1aMTBCXLDN5WVVwBc0U1zBU5KDiU4zZXs+0Q2g3uLlFk/ksXrMPu73dCqVbiiqu7QRcahPKCMqx76zvoQnRQa9VSh+h3AoMC8Nm73yDtmt647s6hgCBAFEXo9Fp8v+oH3DxxhNQhko/jpxs1azKzb/Xl9lU8TkREREQNE0VAG5eM6jM5sFeZXOM2YzkUOj20rRIkjM5POZ2wm6o8TtuqqgB22PE6USbA0CYOQXHRKMvMhd1sgT4hGpqwYCgCNYCdqzm9rarY8997Dqv9vDe5pMYnisANj96CT59djZ9X/eQaDzRoMexf1wH8MfE6q8WG7v1S8cKj/4XV8td9T+RyOe6fMw6WGmsDzyZiEZ2aKYPBAKVKDRzfLHUozYZSpYbBYJA6DCIiIiKfJACw1VS5FdBr2U1GOCxmyJS86ZhXCQJUIcGoKSisd1ql1wO8MsDrSg8eR0jHJAhaEcFtWsFpd0AdHASVLhDZG7cjaXBvqUP0O/poz1dkKAPVkCs997GnpmEqM2LzBz/i5um3oyyvBGX5ZYhMjEKgPhBfL/oCtzxxh9Qh+h2H3YH3X12NmMQoDL5pAILDDKgyVmPzN79i+UsfYe7Sf0sdIvk4FtGpWYqKisIH7/8fKip8a4V1Tk4OFixYgJkzZyIxMVHqcNwYDAafvRkoERERkdREUYSltMjjvKWkEAqtzosREQBo42JhzMyC6Ki7ktbQqT3g4HJOb7NVm3HgnS8AlQodbxsMhVqN/F0HUbzv2NkHXM0iurdpDFroIoNhKiyvM9duUDfI5Cyie5vdYseZzNP4+OmVCI+PgC5Eh2M7j6K8oAwAeHWABKwWGwaMSEOQQYdvV65H4elihIQH49rbr0b/f1yF6soaqUMkH8cieiNgq4wL09jHKSoqymeLwomJiWjfvr3UYRARERHRBRJFJ9DATcVEp9jgPDUNe3UNwq/sgbL9h2CvOtvaRaZSIbhzB9hNVZAHBkocof8Jbh2Hwt2HAasVhz/83m1O1yoSgpxXB3hbyfF89Bh1NQ5+tx0lWXkAAJlCjjbpV0CjD4StxiJxhP5HH2GAIBMgOkUUnyxC8cm/TtKqAtTQ6AIkjM4/qdRKQASWvfiha6ysuByrl3yOwTelo+0VrSWMjpqDFl1Ef+ONN/Diiy8iPz8fXbt2xWuvvYbevRvvrDhbilw8thQhIiIi8j9NnZc3CkGAUh8Mh7n+lWgqQzBEgQ24vUtA5fETsJlM0LdvA7laDYgiRKcTlcdPwF5VhaiIMKmD9DuaUD0CI0NQXVjmPiEIiB/UE5Dx58TbRKcT299bi3ZXd0PHa3vBaXdAkMtwalcmMn/ci2tn3y11iH5HkMvQ4x+9sOu7nXXmBtw5CDK2ovI6mVyGrz9YV+/cpq9+xogx13g5ImpuWmwRffXq1Xjsscfw5ptvok+fPli4cCGGDRuGI0eOIDIyslH20ZgtRSwWC/Lz8xshKiAvLw/vvfceJkyYgJiYmEbZZnR0NNTqy797tC+2FDGbzcjNzW2UbeXk5Lj9tzEkJCRAo9E02vaISHr8vSMdXz/2QMs+/uSfvJGXNwaZIINSGwSrshhOm819TqmCPEALmYwtEbxLhCCXwW6qQumefXVmFdrAs3fvI68SRaDtjYOQv+tPFO8/BqfNDl1sBOKv7gW5hvcNkEJY62hYq804+M32OnMhiVFQqJUSROXfKgrKEJkUjcHjrsVvX26FqcyEkOgQ9L1tAIzFRlQbqxES47mXPTW+alMNLB6uyhCdIkoLyxCXHOvlqKg5abFF9FdeeQX//Oc/MX78eADAm2++iW+//RbvvfcennzyyUbbT2O1FDl69CgWLFjQCBH95b333mu0bS1durTFtifJzc3FpEmTGnWbjfletuRjz2IW+Sv+3pGOrx97oGUff/JP3srLL5tMgLmkEIFxSbAZy2GtKAcAqAwhUAYZYCktgiIuSdIQ/Y1MJoM2IQ7Vp/PqndfGxwHs9ex1TpsNDrMVoR2SEJnaHhAAp80BCGffM5G9nr1OkMvReXhvHPruN7dxuVKBHqMGQeDVAV6nClBh7eKvEdcpAQPHDIZaq0FVmQk7v9mBwhMF6JDWSeoQ/Y4moOGFoQFattihhrXIIrrVasWuXbswY8YM15hMJsPQoUOxbdu2Oo+3WCywWP46G2U0Gr0S57kSEhKwdOlSr+/3QiUkJEgdQpPhsZcOi1nS8vWTGC35BAZ/70jH14890LKPP/mfi83LAelyc5lcAXVoOEzZmVDqgxEQGQNAhK3SCNOJTOiS2/HmfF4mUyig1GoRGBeL6lNn3OZUBj0CY6OhYk90r5PJZHDKZXDanagpLgcEAIKAwIgQGHPzEdwhUeoQ/Y4gAK26tUV421Y4+uMemCuqEN4mFq37d4EoAGDrEK/TGnTQBmtx6s9cnPrT/W+uqORoqLWXf6U/XRx9iB4JbeOQe+xUnbngMAPCIkMkiIqakxZZRC8uLobD4aizQjwqKgqHDx+u8/hnn30WGRkZ3gqvXhqNpsUW6nwdj710WMySlq+fxGjJJzD4e0c6PPZE3nWxeTkgbW6uCNBCFRwGa3kJbMZy17g6NBwKDYu1UhDkcugS4xEYG42aM/kQnU4EREVCHqCBTMUWFVIQVHLUnCpD0YEsRF/ZGTK5HKYzRcjbcQDtbr4aKg2Lg94mKGWwG22QyQR0vKYnIAgQRRFmYzV0kcEQnbw6wNuCgvW4dcad+Gju+7CZra7xQIMWNzx6C0Ki2MrF2wyhQXjkmX9h3qTnUVluco2rA9SY/vKDCIkIli44ahZaZBH9Ys2YMQOPPfaY62uj0Yj4+HgJIyLyDyxmScvXT2K05BMYRETkmZS5uUypRGBsPDThUbAaz940UWUIgUyphEzBgq0UlDrt/9qF2IFYAaJThEqnhUytglKrlTo8v6TS6RCUHIeguCiUZebCVmNBcOtWiOjaHjKFHAJXPXufQ4Q2VA+bxYrK/FLYLDYEhuigDddDFqiEAryKxtuUgUpEJkZh4qv/Qs6BEyg+WYTYdq0Q2y4OYa14Q2SpxLWOxXMfzEHmgeM4diAbCW1boVP39giPDoPAm4fTebTIInp4eDjkcjkKCgrcxgsKChAdHV3n8Wq1ulFumklE1JzwJAYRETW1i83LAelzc5lCAZlCAQXbhPiM2mK5OtggcSQEAHKFHBp9IKyV1Yjq0wWCIMBsNkMhyKEMbJmt+HydLjwYFXnFqCqqQFSXJMhkMlhrrCjJPIWQhEiowvj7TAoarQYarQbhcRFSh0LnCI8OQ3h0GNKGXil1KNTMtMhTxCqVCj179sQPP/zgGnM6nfjhhx+QlpYmYWRERERERP6DeTlRyySTy6EJDoJCoYBcLodWq2UBXWKGmHAERYfCeLoUJVlnYDVWISQxGtownnwiImoMLXIlOgA89thjGDt2LHr16oXevXtj4cKFqKqqwvjx46UOjYiIiIjIbzAvJyLyjiDeGJGIqMm02CL6qFGjUFRUhDlz5iA/Px/dunXD999/X+emRkRERERE1HSYlxMRERFRcyeIoihKHYSvMRqNMBgMqKiogF6vlzocIiIiImpBmGteHB4vIiIiImoqF5prtsie6EREREREREREREREjYFFdCIiIiIiIiIiIiIiD1hEJyIiIiIiIiIiIiLygEV0IiIiIiIiIiIiIiIPFFIH4Itq77VqNBoljoSIiIiIWpraHLM256SGMTcnIiIioqZyobk5i+j1qKysBADEx8dLHAkRERERtVSVlZUwGAxSh+HzmJsTERERUVM7X24uiFwCU4fT6cSZM2cQFBQEQRCkDueiGY1GxMfH4+TJk9Dr9VKH41d47KXDYy8tHn/p8NhLh8deWs35+IuiiMrKSsTGxkImY3fF85EqN2/O32MtFd8T38P3xPfwPfE9fE98E98X3yPVe3KhuTlXotdDJpMhLi5O6jAum16v5y8CifDYS4fHXlo8/tLhsZcOj720muvx5wr0Cyd1bt5cv8daMr4nvofvie/he+J7+J74Jr4vvkeK9+RCcnMufSEiIiIiIiIiIiIi8oBFdCIiIiIiIiIiIiIiD1hEb4HUajXmzp0LtVotdSh+h8deOjz20uLxlw6PvXR47KXF409Njd9jvofvie/he+J7+J74Hr4nvonvi+/x9feENxYlIiIiIiIiIiIiIvKAK9GJiIiIiIiIiIiIiDxgEZ2IiIiIiIiIiIiIyAMW0YmIiIiIiIiIiIiIPGARnYiIiIiIiIiIiIjIAxbRW5AlS5YgNTUVer0eer0eaWlpWLt2rdRh+Z3nnnsOgiBg6tSpUofiF+bNmwdBENz+dezYUeqw/Mbp06dx9913IywsDAEBAbjiiivw+++/Sx2WX0hKSqrzvS8IAqZMmSJ1aC2ew+HA7NmzkZycjICAALRp0wZPP/00eK9276isrMTUqVORmJiIgIAA9O3bFzt37pQ6LGpBmFP7NubavoE5uG9ibu5bmK/7Hubxvqm55PcKqQOgxhMXF4fnnnsO7dq1gyiKWLFiBW688Ubs2bMHKSkpUofnF3bu3Im33noLqampUofiV1JSUrBx40bX1woFf7V5Q1lZGfr164err74aa9euRUREBDIzMxESEiJ1aH5h586dcDgcrq8PHDiAa665BrfffruEUfmH559/HkuWLMGKFSuQkpKC33//HePHj4fBYMDDDz8sdXgt3n333YcDBw7g/fffR2xsLD744AMMHToUhw4dQqtWraQOj1oA5tS+i7m2b2EO7luYm/se5uu+h3m8b2ou+b0g8nRLixYaGooXX3wREydOlDqUFs9kMqFHjx5YvHgx5s+fj27dumHhwoVSh9XizZs3D1988QX27t0rdSh+58knn8Svv/6Kn3/+WepQCMDUqVPxzTffIDMzE4IgSB1Oi3b99dcjKioK7777rmvs1ltvRUBAAD744AMJI2v5ampqEBQUhC+//BIjRoxwjffs2RPDhw/H/PnzJYyOWjLm1NJjru1bmIP7Hubmvo/5uvSYx/ue5pTfs51LC+VwOLBq1SpUVVUhLS1N6nD8wpQpUzBixAgMHTpU6lD8TmZmJmJjY9G6dWuMGTMGubm5UofkF7766iv06tULt99+OyIjI9G9e3e8/fbbUofll6xWKz744ANMmDCBCbkX9O3bFz/88AOOHj0KAPjjjz/wyy+/YPjw4RJH1vLZ7XY4HA5oNBq38YCAAPzyyy8SRUUtGXNq38Fc2/cwB/ctzM19G/N138A83vc0p/ye11u1MPv370daWhrMZjN0Oh0+//xzdO7cWeqwWrxVq1Zh9+7dPtmzqaXr06cPli9fjg4dOiAvLw8ZGRkYMGAADhw4gKCgIKnDa9GOHz+OJUuW4LHHHsN//vMf7Ny5Ew8//DBUKhXGjh0rdXh+5YsvvkB5eTnGjRsndSh+4cknn4TRaETHjh0hl8vhcDiwYMECjBkzRurQWrygoCCkpaXh6aefRqdOnRAVFYWPPvoI27ZtQ9u2baUOj1oQ5tS+hbm272EO7nuYm/s25uu+gXm872lO+T3bubQwVqsVubm5qKiowKeffop33nkHmzdvZtLfhE6ePIlevXphw4YNrv6MgwYN4iWmEikvL0diYiJeeeUVXnLdxFQqFXr16oWtW7e6xh5++GHs3LkT27ZtkzAy/zNs2DCoVCp8/fXXUofiF1atWoXp06fjxRdfREpKCvbu3YupU6filVde4R+pXpCVlYUJEyZgy5YtkMvl6NGjB9q3b49du3bhzz//lDo8aiGYU/sO5trNA3Nw6TE3923M130D83jf1Fzye65Eb2FUKpXrTE3Pnj2xc+dOLFq0CG+99ZbEkbVcu3btQmFhIXr06OEaczgc2LJlC15//XVYLBbI5XIJI/QvwcHBaN++PY4dOyZ1KC1eTExMnWJCp06dsGbNGoki8k85OTnYuHEjPvvsM6lD8RvTp0/Hk08+iTvvvBMAcMUVVyAnJwfPPvssk28vaNOmDTZv3oyqqioYjUbExMRg1KhRaN26tdShUQvCnNp3MNduHpiDS4+5ue9ivu47mMf7puaS37MnegvndDphsVikDqNFGzJkCPbv34+9e/e6/vXq1QtjxozB3r17mdR7mclkQlZWFmJiYqQOpcXr168fjhw54jZ29OhRJCYmShSRf1q2bBkiIyPdbsJCTau6uhoymXsKJZfL4XQ6JYrIP2m1WsTExKCsrAzr1q3DjTfeKHVI1IIxp5YOc+3mgTm49Jib+y7m676Debxv8/X8nivRW5AZM2Zg+PDhSEhIQGVlJT788EP89NNPWLdundShtWhBQUHo0qWL25hWq0VYWFidcWp806ZNw8iRI5GYmIgzZ85g7ty5kMvlGD16tNShtXiPPvoo+vbti2eeeQZ33HEHfvvtNyxduhRLly6VOjS/4XQ6sWzZMowdOxYKBT/SvWXkyJFYsGABEhISkJKSgj179uCVV17BhAkTpA7NL6xbtw6iKKJDhw44duwYpk+fjo4dO2L8+PFSh0YtBHNq38Jc2zcxB/c9zM19E/N138I83jc1l/yeP8EtSGFhIe69917k5eXBYDAgNTUV69atwzXXXCN1aERN5tSpUxg9ejRKSkoQERGB/v37Y/v27YiIiJA6tBbvyiuvxOeff44ZM2bgqaeeQnJyMhYuXMibsnjRxo0bkZuby6TPy1577TXMnj0bkydPRmFhIWJjY/Gvf/0Lc+bMkTo0v1BRUYEZM2bg1KlTCA0Nxa233ooFCxZAqVRKHRq1EMypic6PObjvYW7um5iv+xbm8b6pueT3vLEoEREREREREREREZEH7IlOREREREREREREROQBi+hERERERERERERERB6wiE5ERERERERERERE5AGL6EREREREREREREREHrCITkRERERERERERETkAYvoREREREREREREREQesIhOREREREREREREROQBi+hERERERERERERERB6wiE5ERI1u3rx56Natm+vrcePG4aabbpIsHiIiIiIif8S8nIiocSikDoCIiFq+RYsWQRRF19eDBg1Ct27dsHDhQumCIiIiIiLyM8zLiYguDYvoRETU5AwGg9QhEBERERH5PeblRESXhu1ciIj8TFVVFe69917odDrExMTg5ZdfxqBBgzB16lQAgCAI+OKLL9yeExwcjOXLl7u+fuKJJ9C+fXsEBgaidevWmD17Nmw2m8d9nnvZ6Lhx47B582YsWrQIgiBAEARkZ2ejbdu2eOmll9yet3fvXgiCgGPHjjXGSyciIiIi8hnMy4mImg8W0YmI/Mz06dOxefNmfPnll1i/fj1++ukn7N69+6K2ERQUhOXLl+PQoUNYtGgR3n77bbz66qsX9NxFixYhLS0N//znP5GXl4e8vDwkJCRgwoQJWLZsmdtjly1bhvT0dLRt2/ai4iMiIiIi8nXMy4mImg8W0YmI/IjJZMK7776Ll156CUOGDMEVV1yBFStWwG63X9R2Zs2ahb59+yIpKQkjR47EtGnT8PHHH1/Qcw0GA1QqFQIDAxEdHY3o6GjI5XKMGzcOR44cwW+//QYAsNls+PDDDzFhwoSLfp1ERERERL6MeTkRUfPCnuhERH4kKysLVqsVffr0cY2FhoaiQ4cOF7Wd1atX47///S+ysrJgMplgt9uh1+svK7bY2FiMGDEC7733Hnr37o2vv/4aFosFt99++2Vtl4iIiIjI1zAvJyJqXrgSnYiI3AiCAFEU3cbO7au4bds2jBkzBtdddx2++eYb7NmzBzNnzoTVar3sfd93331YtWoVampqsGzZMowaNQqBgYGXvV0iIiIiouaGeTkRke/gSnQiIj/Spk0bKJVK7NixAwkJCQCAsrIyHD16FAMHDgQAREREIC8vz/WczMxMVFdXu77eunUrEhMTMXPmTNdYTk7ORcWhUqngcDjqjF933XXQarVYsmQJvv/+e2zZsuWitktERERE1BwwLycial5YRCci8iM6nQ4TJ07E9OnTERYWhsjISMycORMy2V8XJg0ePBivv/460tLS4HA48MQTT0CpVLrm27Vrh9zcXKxatQpXXnklvv32W3z++ecXFUdSUhJ27NiBEydOQKfTITQ0FDKZzNWDccaMGWjXrh3S0tIa7bUTEREREfkK5uVERM0L27kQEfmZF198EQMGDMDIkSMxdOhQ9O/fHz179nTNv/zyy4iPj8eAAQNw1113Ydq0aW6Xbt5www149NFH8eCDD6Jbt27YunUrZs+efVExTJs2DXK5HJ07d0ZERARyc3NdcxMnToTVasX48eMv/8USEREREfko5uVERM2HIP69wRYREfmdQYMGoVu3bli4cKHUoeDnn3/GkCFDcPLkSURFRUkdDhERERGR1zAvJyLyTWznQkREPsFisaCoqAjz5s3D7bffzkSdiIiIiEgCzMuJiOpiOxciIvIJH330ERITE1FeXo4XXnhB6nCIiIiIiPwS83IiorrYzoWIiIiIiIiIiIiIyAOuRCciIiIiIiIiIiIi8oBFdCIiIiIiIiIiIiIiD1hEJyIiIiIiIiIiIiLygEV0IiIiIiIiIiIiIiIPWEQnIiIiIiIiIiIiIvKARXQiIiIiIiIiIiIiIg9YRCciIiIiIiIiIiIi8oBFdCIiIiIiIiIiIiIiD1hEJyIiIiIiIiIiIiLygEV0IiIiIiIiIiIiIiIPWEQnIiIiIiIiIiIiIvKARXQiIiIiIiIiIiIiIg9YRCciIiIiIiIiIiIi8oBFdCIiIiIiIiIiIiIiD1hEJyKvGTRoEAYNGiR1GG4KCgpw2223ISwsDIIgYOHChVKH1CApjuG4ceOQlJTkNmYymXDfffchOjoagiBg6tSpXo2podgEQcC8efOabJ9JSUkYN27ceR+3fPlyCIKAEydONFksLcVPP/0EQRDw008/ucbqe2+JiIjI+5jDXz7m8OePjTl888McnvwNi+hEzUzth/q5/yIjI3H11Vdj7dq1UofXJKqrqzFv3jy3D+fG8uijj2LdunWYMWMG3n//ffzjH/9oshi2bt2KefPmoby8/JK34SueeeYZLF++HA888ADef/993HPPPVKHRC1cU/4eICIikkpD+eEzzzyDL774wusxNRbm8L6HOTx5G3N4akkUUgdARJfmqaeeQnJyMkRRREFBAZYvX47rrrsOX3/9Na6//nqpw2tU1dXVyMjIAIBGX8Hx448/4sYbb8S0adOaPIatW7ciIyMD48aNQ3Bw8CVtw1f8+OOPuOqqqzB37lypQ6mjpqYGCkXTfbwdOXIEMhnPQTe1t99+G06n0/V1U/4eICIikkpD+eEzzzyD2267DTfddJMksV0u5vC+hzk8c/imxhyeWjIW0YmaqeHDh6NXr16urydOnIioqCh89NFHLa6I3pQKCwubfTIshcLCQnTu3LlRt1ldXY3AwMDL3o5Go2mEaDxTq9VNun06S6lUSh0CERFRi2M2m6FSqZp9MZE5/KVhDk9NjTk8tWTN+5OTiFyCg4MREBBQ5+x9VVUVHn/8ccTHx0OtVqNDhw546aWXIIoigLNn/Dt27IiOHTuipqbG9bzS0lLExMSgb9++cDgcHvdb215my5Yt+Ne//oWwsDDo9Xrce++9KCsrO2/chYWFrhMAGo0GXbt2xYoVK1zzJ06cQEREBAAgIyPD1cLmfP3yjh8/jttvvx2hoaEIDAzEVVddhW+//bZO3KIo4o033nBttz4XEsOPP/6IAQMGQKvVIjg4GDfeeCP+/PNP1/y8efMwffp0AEBycrJrG7W99pYtW4bBgwcjMjISarUanTt3xpIlS857/DzZsGED+vfvj+DgYOh0OnTo0AH/+c9/6rz+v/f6q6+vXX3z2dnZ+Pbbb91ex8Vsc9CgQejSpQt27dqF9PR0BAYGusVXny+++AJdunSBRqNBly5d8Pnnn9f7uPq+P/bs2YPhw4dDr9dDp9NhyJAh2L59u2v+xx9/hEwmw5w5c9ye9+GHH0IQBLf3or5+igcPHsTgwYMREBCAuLg4zJ8/320FxrnWrl3r+l4JCgrCiBEjcPDgwQZf+++//w5BENx+NmqtW7cOgiDgm2++AQBUVlZi6tSpSEpKglqtRmRkJK655hrs3r27wX0AwC+//IIrr7wSGo0Gbdq0wVtvvYV58+a5/WycOHECgiBg+fLldZ7/92Ofk5ODyZMno0OHDggICEBYWBhuv/32C+oxeW4/xYZ+BpctWwZBELBnz54623jmmWcgl8tx+vTp8+6PiIgIuPDP0R07duC6665DSEgItFotUlNTsWjRItf8vn37MG7cOLRu3RoajQbR0dGYMGECSkpKXI9pKD8UBAFVVVVYsWKFa/zc/OP06dOYMGECoqKioFarkZKSgvfee88txtocbNWqVZg1axZatWqFwMBAGI1G5vD/wxyeOTxzeObwRBeKK9GJmqmKigoUFxdDFEUUFhbitddeg8lkwt133+16jCiKuOGGG7Bp0yZMnDgR3bp1w7p16zB9+nScPn0ar776KgICArBixQr069cPM2fOxCuvvAIAmDJlCioqKrB8+XLI5fLzxvPggw8iODgY8+bNw5EjR7BkyRLk5OS4kq/61NTUYNCgQTh27BgefPBBJCcn45NPPsG4ceNQXl6ORx55BBEREViyZAkeeOAB3HzzzbjlllsAAKmpqR5jKSgoQN++fVFdXY2HH34YYWFhWLFiBW644QZ8+umnuPnmm5Genu7qA3jNNdfg3nvv9bi988WwceNGDB8+HK1bt8a8efNQU1OD1157Df369cPu3buRlJSEW265BUePHsVHH32EV199FeHh4a5tA8CSJUuQkpKCG264AQqFAl9//TUmT54Mp9OJKVOmnPf4n+vgwYO4/vrrkZqaiqeeegpqtRrHjh3Dr7/+elHbqU+nTp3w/vvv49FHH0VcXBwef/xxt9dxMUpKSjB8+HDceeeduPvuuxEVFeXxsevXr8ett96Kzp0749lnn0VJSQnGjx+PuLi48+7n4MGDGDBgAPR6Pf79739DqVTirbfewqBBg7B582b06dMHgwcPxuTJk/Hss8/ipptuQo8ePZCXl4eHHnoIQ4cOxf333+9x+/n5+bj66qtht9vx5JNPQqvVYunSpQgICKjz2Pfffx9jx47FsGHD8Pzzz6O6uhpLlixB//79sWfPHo834enVqxdat26Njz/+GGPHjnWbW716NUJCQjBs2DAAwP33349PP/0UDz74IDp37oySkhL88ssv+PPPP9GjRw+Pr2P//v249tprERERgXnz5sFut2Pu3LkNvi/ns3PnTmzduhV33nkn4uLicOLECSxZsgSDBg3CoUOHLnjVUkM/g8nJyZgyZQpWrlyJ7t27uz1v5cqVGDRoEFq1anXJr4GIiPzLhXyObtiwAddffz1iYmLwyCOPIDo6Gn/++Se++eYbPPLII67HHD9+HOPHj0d0dDQOHjyIpUuX4uDBg9i+fTsEQWgwP3z//fdx3333oXfv3pg0aRIAoE2bNgDO5rpXXXUVBEHAgw8+iIiICKxduxYTJ06E0Wisc7PIp59+GiqVCtOmTYPFYoFKpXLNMYdnDn+xmMMzh2cOT35LJKJmZdmyZSKAOv/UarW4fPlyt8d+8cUXIgBx/vz5buO33XabKAiCeOzYMdfYjBkzRJlMJm7ZskX85JNPRADiwoULLzienj17ilar1TX+wgsviADEL7/80jU2cOBAceDAga6vFy5cKAIQP/jgA9eY1WoV09LSRJ1OJxqNRlEURbGoqEgEIM6dO/eCjtHUqVNFAOLPP//sGqusrBSTk5PFpKQk0eFwuMYBiFOmTDnvNhuKoVu3bmJkZKRYUlLiGvvjjz9EmUwm3nvvva6xF198UQQgZmdn19lGdXV1nbFhw4aJrVu3dhv7+zGsz6uvvioCEIuKijw+pvZ9+3ssmzZtEgGImzZtco2NHTtWTExMdHtcYmKiOGLEiEve5sCBA0UA4ptvvtnga6nVrVs3MSYmRiwvL3eNrV+/XgRQJ7a/v0833XSTqFKpxKysLNfYmTNnxKCgIDE9Pd01VlVVJbZt21ZMSUkRzWazOGLECFGv14s5OTl1XvvYsWNdX9d+v+3YscM1VlhYKBoMBrfjUVlZKQYHB4v//Oc/3baXn58vGgyGOuN/N2PGDFGpVIqlpaWuMYvFIgYHB4sTJkxwjRkMhgv6nv67m266SdRoNG6v99ChQ6JcLhfPTReys7NFAOKyZcvqbOPvx76+7+tt27aJAMT/+7//c41dyPddQz+Do0ePFmNjY91+tnfv3u0xTiIiIk/O9zlqt9vF5ORkMTExUSwrK3Obczqdrv+v7zPwo48+EgGIW7ZscY01lB9qtVq3nKPWxIkTxZiYGLG4uNht/M477xQNBoNr37Wfr61bt64TD3N45vCXsk3m8H9hDs8cnvwP27kQNVNvvPEGNmzYgA0bNuCDDz7A1Vdfjfvuuw+fffaZ6zHfffcd5HI5Hn74YbfnPv744xBFEWvXrnWNzZs3DykpKRg7diwmT56MgQMH1nleQyZNmuTW/+yBBx6AQqHAd9995/E53333HaKjozF69GjXmFKpxMMPPwyTyYTNmzdf8P7/vt3evXujf//+rjGdTodJkybhxIkTOHTo0CVttz55eXnYu3cvxo0bh9DQUNd4amoqrrnmmgZf/7nOXfFQe5XBwIEDcfz4cVRUVFxUTLX9Ib/88kuPlyP6ArVajfHjx5/3cbXHeOzYsTAYDK7xa6655rw9HR0OB9avX4+bbroJrVu3do3HxMTgrrvuwi+//AKj0QgACAwMxPLly/Hnn38iPT0d3377LV599VUkJCQ0uI/vvvsOV111FXr37u0ai4iIwJgxY9wet2HDBpSXl2P06NEoLi52/ZPL5ejTpw82bdrU4H5GjRoFm83m9jO+fv16lJeXY9SoUa6x4OBg7NixA2fOnGlwe+dyOBxYt24dbrrpJrfX26lTJ9fqmEtx7ve1zWZDSUkJ2rZti+Dg4Au6NPVC3XvvvThz5ozbMVy5ciUCAgJw6623Ntp+iIio5Tvf5+iePXuQnZ2NqVOn1unJfe7K7XM/A81mM4qLi3HVVVcBwGV9BoqiiDVr1mDkyJEQRdEtpxg2bBgqKirqbH/s2LH1rq4FmMMzh794zOGZwzcW5vDU3LCITtRM9e7dG0OHDsXQoUMxZswYfPvtt+jcuTMefPBBWK1WAGd7mcXGxiIoKMjtuZ06dXLN11KpVHjvvfeQnZ2NyspKV4+yC9WuXTu3r3U6HWJiYhrsm5aTk4N27drVubFRffFdjJycHHTo0KHO+OVu19O+AHjcX3FxMaqqqs67nV9//RVDhw519WOMiIhw9Re82AR81KhR6NevH+677z5ERUXhzjvvxMcff+xzyXirVq3cLif2pPYY//17DKj/uJ+rqKgI1dXVHt8fp9OJkydPusb69euHBx54AL/99huGDRuGCRMmXFB8FxJbZmYmAGDw4MGIiIhw+7d+/XoUFhY2uJ+uXbuiY8eOWL16tWts9erVCA8Px+DBg11jL7zwAg4cOID4+Hj07t0b8+bNw/HjxxvcdlFREWpqai7pGDekpqYGc+bMcd2TITw8HBERESgvL7/o7+uGXHPNNYiJicHKlSsBAE6nEx999BFuvPHGOr//iIiIGnK+z9GsrCwAQJcuXRrcTmlpKR555BFERUUhICAAERERSE5OBnDxud25ioqKUF5ejqVLl9bJJ2oLm3/PKWr3Wx/m8MzhLxZzeObwjYU5PDU37IlO1ELIZDJcffXVWLRoETIzM5GSknLR21i3bh2As6tlMjMzG0y4qfFkZWVhyJAh6NixI1555RXEx8dDpVLhu+++w6uvvnrRiXNAQAC2bNmCTZs24dtvv8X333+P1atXY/DgwVi/fj3kcrnHEyQN3UT2fC52m55WREnJYrG4bp6UlZWF6urqC+75dz617+P777+P6OjoOvN/vylwfUaNGoUFCxaguLgYQUFB+OqrrzB69Gi3595xxx0YMGAAPv/8c6xfvx4vvvginn/+eXz22WcYPnz4Zb+Oi3mfH3roISxbtgxTp05FWloaDAYDBEHAnXfe2ah/EMrlctx11114++23sXjxYvz66684c+aM2z0iiIiILkRjfY7ecccd2Lp1K6ZPn45u3bpBp9PB6XTiH//4x2V9BtY+9+67767TY7nW3/uO+2LO1RIwh/cdzOHPjzk80eVjEZ2oBbHb7QAAk8kEAEhMTMTGjRtRWVnpdib38OHDrvla+/btw1NPPYXx48dj7969uO+++7B//363S+8akpmZiauvvtr1tclkQl5eHq677jqPz0lMTMS+ffvgdDrdVrL8Pb6LWRFf+7wjR47UGa/vdV8oTzHUbsvT/sLDw6HVahvcxtdffw2LxYKvvvrK7TK8810a2BCZTIYhQ4ZgyJAheOWVV/DMM89g5syZ2LRpE4YOHYqQkBAAQHl5udvzLmeFT1NsE/jrGNeuAjlXfcf9XBEREQgMDPT4/shkMsTHx7vG5s6diz///BMvvfQSnnjiCTz55JP473//e974LiS22puBRUZGYujQoQ1u05NRo0YhIyMDa9asQVRUFIxGI+688846j4uJicHkyZMxefJkFBYWokePHliwYIHHBDwiIgIBAQEX9Dou5n3+9NNPMXbsWLz88suuMbPZXOe5F+J8vwfuvfdevPzyy/j666+xdu1aREREXNZlrERE5L8a+hyt/Tw/cOCAx8/zsrIy/PDDD8jIyMCcOXNc4/V9zjb0+VbfXEREBIKCguBwOC45nzgXc3jm8MzhG46NOfxZzOGJ2M6FqMWw2WxYv349VCqV65LH6667Dg6HA6+//rrbY1999VUIguD6MLbZbBg3bhxiY2OxaNEiLF++HAUFBXj00UcveP9Lly6FzWZzfb1kyRLY7fYGz5pfd911yM/Pd7u0zW6347XXXoNOp8PAgQMBwLWK4EI/tK+77jr89ttv2LZtm2usqqoKS5cuRVJS0nl78NXHUwwxMTHo1q0bVqxY4TZ34MABrF+/3u0PkNpE/O/bkMvlAM72uKxVUVGBZcuWXXScwNnLh/+uW7duAM6u0gD+Sga3bNnieozD4cDSpUsvaZ9NtU3A/Rife/nghg0bztsbUy6X49prr8WXX37pdllyQUEBPvzwQ/Tv3x96vR4AsGPHDrz00kuYOnUqHn/8cUyfPh2vv/76eft6Xnfdddi+fTt+++0311hRUZHrssRaw4YNg16vxzPPPOP2s3Luc86nU6dOuOKKK7B69WqsXr0aMTExSE9Pd807HI46l1hGRkYiNjbW9d7XRy6XY9iwYfjiiy+Qm5vrGv/zzz9dV6jU0uv1CA8Pd3ufAWDx4sX1bvfc72sAeO211y5ptdT5fg+kpqYiNTUV77zzDtasWYM777zzglYGERER1bqQz9EePXogOTkZCxcurPOZVPuZV19uBwALFy6ss09P+WHtXH1546233oo1a9bgwIEDdZ5zIfnEuZjDM4dnDs8cvr7tMocnqovfmUTN1Nq1a12rMgoLC/Hhhx8iMzMTTz75pCuhGDlyJK6++mrMnDkTJ06cQNeuXbF+/Xp8+eWXmDp1qithmj9/Pvbu3YsffvgBQUFBSE1NxZw5czBr1izcdtttDa5EqWW1WjFkyBDccccdOHLkCBYvXoz+/fvjhhtu8PicSZMm4a233sK4ceOwa9cuJCUl4dNPP8Wvv/6KhQsXulbPBwQEoHPnzli9ejXat2+P0NBQdOnSxWMvyieffBIfffQRhg8fjocffhihoaFYsWIFsrOzsWbNmjr9Gy9EQzG8+OKLGD58ONLS0jBx4kTU1NTgtddeg8FgwLx581zb6NmzJwBg5syZuPPOO6FUKjFy5Ehce+21UKlUGDlyJP71r3/BZDLh7bffRmRkJPLy8i461qeeegpbtmzBiBEjkJiYiMLCQixevBhxcXGuGzWlpKTgqquuwowZM1BaWorQ0FCsWrXKdTXDpWiKbdZ69tlnMWLECPTv3x8TJkxAaWkpXnvtNaSkpLiuvPBk/vz52LBhA/r374/JkydDoVDgrbfegsViwQsvvADg7MqKsWPHol27dliwYAEAICMjA19//TXGjx+P/fv3u/6A+rt///vfeP/99/GPf/wDjzzyCLRaLZYuXepapVVLr9djyZIluOeee9CjRw/ceeediIiIQG5uLr799lv069evzgmv+owaNQpz5syBRqPBxIkT3b6fKysrERcXh9tuuw1du3aFTqfDxo0bsXPnTreVJPXJyMjA999/jwEDBmDy5MmuP4ZTUlLcXgcA3HfffXjuuedw3333oVevXtiyZQuOHj1aZ5vXX3893n//fRgMBnTu3Bnbtm3Dxo0bERYWdt7X+XcX8nvg3nvvxbRp0wCAl4ESEdFFu5DPUZlMhiVLlmDkyJHo1q0bxo8fj5iYGBw+fBgHDx7EunXroNfrkZ6ejhdeeAE2mw2tWrXC+vXrkZ2dXWefnvJDrVaLnj17YuPGjXjllVcQGxuL5ORk9OnTB8899xw2bdqEPn364J///Cc6d+6M0tJS7N69Gxs3bqy3GOsJc3jm8MzhmcP/HXN4Ig9EImpWli1bJgJw+6fRaMRu3bqJS5YsEZ1Op9vjKysrxUcffVSMjY0VlUql2K5dO/HFF190PW7Xrl2iQqEQH3roIbfn2e128corrxRjY2PFsrKy88azefNmcdKkSWJISIio0+nEMWPGiCUlJW6PHThwoDhw4EC3sYKCAnH8+PFieHi4qFKpxCuuuEJctmxZnf1s3bpV7Nmzp6hSqUQA4ty5cxs8TllZWeJtt90mBgcHixqNRuzdu7f4zTff1HkcAHHKlCkNbutCYti4caPYr18/MSAgQNTr9eLIkSPFQ4cO1dnG008/LbZq1UqUyWQiADE7O1sURVH86quvxNTUVFGj0YhJSUni888/L7733ntujxHF+o/h3/3www/ijTfeKMbGxooqlUqMjY0VR48eLR49erTOMRo6dKioVqvFqKgo8T//+Y+4YcMGEYC4adMm1+PGjh0rJiYmuj03MTFRHDFiRJ19X+g2Bw4cKKakpDT4Ov5uzZo1YqdOnUS1Wi127txZ/Oyzz+qNrb7vj927d4vDhg0TdTqdGBgYKF599dXi1q1bXfOPPvqoKJfLxR07drg97/fffxcVCoX4wAMPuL32sWPHuj1u37594sCBA0WNRiO2atVKfPrpp8V33323zvsniqK4adMmcdiwYaLBYBA1Go3Ypk0bcdy4ceLvv/9+QcchMzPT9bP/yy+/uM1ZLBZx+vTpYteuXcWgoCBRq9WKXbt2FRcvXnxB2968ebPre7x169bim2++Kc6dO1f8e7pQXV0tTpw4UTQYDGJQUJB4xx13iIWFhXWOfVlZmevnW6fTicOGDRMPHz5c5xhu2rTpgr7vzvd7IC8vT5TL5WL79u0v6PUSERGd62I+R3/55RfxmmuucT0uNTVVfO2111zzp06dEm+++WYxODhYNBgM4u233y6eOXOm3s8vT/nh4cOHxfT0dDEgIEAE4PbZWVBQIE6ZMkWMj48XlUqlGB0dLQ4ZMkRcunSp6zG1n6+ffPJJnfiZw5/FHP7itskcnjk8c3jyZ4Io/u0aDSKii7B8+XKMHz8eO3fuRK9evaQOh4ga2bx585CRkVHnkk5fVFxcjJiYGMyZMwezZ8+WOhwiIiKfxRyeqGVjDk/U+NgTnYiIiFqE5cuXw+Fw4J577pE6FCIiIiIiugDM4am5YE90IiIiatZ+/PFHHDp0CAsWLMBNN92EpKQkqUMiIiIiIqIGMIen5oZFdCIiImrWnnrqKWzduhX9+vXDa6+9JnU4RERERER0HszhqblhT3QiIiIiIiIiIiIiIg/YE52IiIiIiIiIiIiIyAMW0YmIiIiIiIiIiIiIPGBP9Ho4nU6cOXMGQUFBEARB6nCIiIiIqAURRRGVlZWIjY2FTMY1LefD3JyIiIiImsqF5uYsotfjzJkziI+PlzoMIiIiImrBTp48ibi4OKnD8HnMzYmIiIioqZ0vN2cRvR5BQUEAzh48vV4vcTRERERE1JIYjUbEx8e7ck5qGHNzIiIiImoqF5qbs4hej9rLRPV6PRN1IiIiImoSbE1yYZibExEREVFTO19uziaMREREREREREREREQesIhOREREREREREREROQBi+hERERERERERERERB6wJzoRERERERERERGRn3I4HLDZbFKH0SSUSiXkcvllb4dFdCIiIiIiIiIiIiI/I4oi8vPzUV5eLnUoTSo4OBjR0dHnvXloQ1hEb2EcDgf27duH0tJShIaGIjU1tVHOthARERER+QunwwHRYQcACHIFZMyniYiIqAWqLaBHRkYiMDDwsorMvkgURVRXV6OwsBAAEBMTc8nbYhG9BdmyZQsWL16M/Px811h0dDQmT56M9PR0CSMjIiIiIvJ9oijCaTGjOv8UbMYKAIBSH4zAmDjIVOoW94clERER+S+Hw+EqoIeFhUkdTpMJCAgAABQWFiIyMvKSFxvzxqItxJYtWzB37ly0bt0ab7zxBr777ju88cYbaN26NebOnYstW7ZIHSIRERERkU9zWi0wZh12FdABwGYsh/HYYThtVgkjIyIiImpctT3QAwMDJY6k6dW+xsvp+84iegvgcDiwePFipKWlYf78+UhJSUFgYCBSUlIwf/58pKWlYcmSJXA4HFKHSkRERETkk0SnE5bSYoj15Myiww5LWQlEUZQgMiIiIvm/Fs0AAQAASURBVKKm4w9X2jXGa2QRvQXYt28f8vPzMWbMGMhk7m+pTCbDmDFjkJeXh3379kkUIRERERGRbxMdDtgqKzzO24zl9RbYiYiIiOjSzJs3D926dXN9PW7cONx0002SxdMQ9kRvAUpLSwEAycnJ9c7Xjtc+joiIiIiI/kYmQGigR6YgVwB+sFKLiIiISCqLFi1yu/Jv0KBB6NatGxYuXChdUP/DlegtQGhoKAAgOzu73vna8drHERERERGRO5lcAU1EtMd5TUQUZJd4IyoiIiIiOj+DwYDg4GCpw6gXi+gtQGpqKqKjo7Fy5Uo4nU63OafTiZUrVyImJgapqakSRUhERERE5PsUAVqogsPqjKtDI6DQtPybbhERERHVqqqqwr333gudToeYmBi8/PLLGDRoEKZOnQrgbJ/xL774wu05wcHBWL58uevrJ554Au3bt0dgYCBat26N2bNnN3hzz3PbuYwbNw6bN2/GokWLIAgCBEFAdnY22rZti5deesnteXv37oUgCDh27FhjvPR6sYjeAsjlckyePBnbtm3DrFmzcPDgQVRXV+PgwYOYNWsWtm3bhgceeAByrpwhIiIiIvJIplQiMDYe+nadoYmMgSYyBvp2nREQHQuZUil1eEREREReM336dGzevBlffvkl1q9fj59++gm7d+++qG0EBQVh+fLlOHToEBYtWoS3334br7766gU9d9GiRUhLS8M///lP5OXlIS8vDwkJCZgwYQKWLVvm9thly5YhPT0dbdu2vaj4LgZ7orcQ6enpyMjIwOLFizFlyhTXeExMDDIyMpCeni5hdEREREREzYNMoYBMoYAigCvPiYiIyD+ZTCa8++67+OCDDzBkyBAAwIoVKxAXF3dR25k1a5br/5OSkjBt2jSsWrUK//73v8/7XIPBAJVKhcDAQERH/9Vyb9y4cZgzZw5+++039O7dGzabDR9++GGd1emNjUX0FiQ9PR39+vXDvn37UFpaitDQUKSmpnIFOhEREREREREREV2QrKwsWK1W9OnTxzUWGhqKDh06XNR2Vq9ejf/+97/IysqCyWSC3W6HXq+/rNhiY2MxYsQIvPfee+jduze+/vprWCwW3H777Ze13fNhO5cWRi6Xo3v37hgyZAi6d+/OAjoRERERERERERE1KkEQIIqi29i5/c63bduGMWPG4LrrrsM333yDPXv2YObMmbBarZe97/vuuw+rVq1CTU0Nli1bhlGjRiEwsGmvIuRKdCIiIiIiIiIiIiICALRp0wZKpRI7duxAQkICAKCsrAxHjx7FwIEDAQARERHIy8tzPSczMxPV1dWur7du3YrExETMnDnTNZaTk3NRcahUKjgcjjrj1113HbRaLZYsWYLvv/8eW7ZsuajtXgoW0YmIiIiIiIiIiIgIAKDT6TBx4kRMnz4dYWFhiIyMxMyZMyGT/dXUZPDgwXj99deRlpYGh8OBJ554AspzbsTerl075ObmYtWqVbjyyivx7bff4vPPP7+oOJKSkrBjxw6cOHECOp0OoaGhkMlkkMvlGDduHGbMmIF27dohLS2t0V67J2znQkREREREREREREQuL774IgYMGICRI0di6NCh6N+/P3r27Omaf/nllxEfH48BAwbgrrvuwrRp09xaqtxwww149NFH8eCDD6Jbt27YunUrZs+efVExTJs2DXK5HJ07d0ZERARyc3NdcxMnToTVasX48eMv/8VeAEH8e/MagtFohMFgQEVFxWU3uyciIiIiOhdzzYvD40VERETU+MxmM7Kzs5GcnAyNRnNBzxk0aBC6deuGhQsXNm1wF+Dnn3/GkCFDcPLkSURFRTX42IZe64XmmmznQkREREREREREREQ+z2KxoKioCPPmzcPtt99+3gJ6Y2E7FyIiIiIiIiIiIiLyeR999BESExNRXl6OF154wWv75Up0IiIiIiIiIiIiImrQTz/9JHUIGDduHMaNG+f1/XIlOhERERERERERERGRByyiExERERERERERERF5wCI6EREREREREREREZEHLKITEREREREREREREXnAIjoRERERERERERERkQc+XUR/7rnnIAgCpk6d6hozm82YMmUKwsLCoNPpcOutt6KgoMDtebm5uRgxYgQCAwMRGRmJ6dOnw263ezl6IiIiIqKWgXk5EREREfkzny2i79y5E2+99RZSU1Pdxh999FF8/fXX+OSTT7B582acOXMGt9xyi2ve4XBgxIgRsFqt2Lp1K1asWIHly5djzpw53n4JRERERETNHvNyIiIiIvJ3PllEN5lMGDNmDN5++22EhIS4xisqKvDuu+/ilVdeweDBg9GzZ08sW7YMW7duxfbt2wEA69evx6FDh/DBBx+gW7duGD58OJ5++mm88cYbsFqtUr0kIiIiIqJmh3k5EREREfmaJUuWIDU1FXq9Hnq9HmlpaVi7dm2T7tMni+hTpkzBiBEjMHToULfxXbt2wWazuY137NgRCQkJ2LZtGwBg27ZtuOKKKxAVFeV6zLBhw2A0GnHw4MF692exWGA0Gt3+ERERERH5O2/n5QBzcyIiIiJqWFxcHJ577jns2rULv//+OwYPHowbb7yxwRzzcimabMuXaNWqVdi9ezd27txZZy4/Px8qlQrBwcFu41FRUcjPz3c95txEvXa+dq4+zz77LDIyMhoheiIiIiKilkGKvBxgbk5ERETU3Djtdoh2G0SHA4JcDkGhhEzRdGXnkSNHun29YMECLFmyBNu3b0dKSkqT7NOnVqKfPHkSjzzyCFauXAmNRuO1/c6YMQMVFRWufydPnvTavomIiIiIfI1UeTnA3JyIiIioOXFYrTDlZqHi6EEYsw6j4uhBmHKPw+Gl9n0OhwOrVq1CVVUV0tLSmmw/PlVE37VrFwoLC9GjRw8oFAooFAps3rwZ//3vf6FQKBAVFQWr1Yry8nK35xUUFCA6OhoAEB0djYKCgjrztXP1UavVrh46tf+IiIiIiPyVVHk5wNyciIiIqLlw2u2oOpUNu6nSbdxuMqLq1Ak47fYm2/f+/fuh0+mgVqtx//334/PPP0fnzp2bbH8+VUQfMmQI9u/fj71797r+9erVC2PGjHH9v1KpxA8//OB6zpEjR5Cbm+s605CWlob9+/ejsLDQ9ZgNGzZAr9c36YEkIiIiImopmJcTERER0fmIdludAnotu8kI0W5rsn136NABe/fuxY4dO/DAAw9g7NixOHToUJPtz6d6ogcFBaFLly5uY1qtFmFhYa7xiRMn4rHHHkNoaCj0ej0eeughpKWl4aqrrgIAXHvttejcuTPuuecevPDCC8jPz8esWbMwZcoUqNVqr78mIiIiIqLmhnk5EREREZ2P6HA0PO9seP5yqFQqtG3bFgDQs2dP7Ny5E4sWLcJbb73VJPvzqSL6hXj11Vchk8lw6623wmKxYNiwYVi8eLFrXi6X45tvvsEDDzyAtLQ0aLVajB07Fk899ZSEURMRERERtSzMy4mIiIj8myCXNzwva3i+MTmdTlgslibbviCKothkW2+mjEYjDAYDKioq2IORiIiIiBoVc82Lw+NFRERE1PjMZjOys7ORnJx8yTeSd9rtMOUeh91krDOn0OmhS2gNmaLx13DPmDEDw4cPR0JCAiorK/Hhhx/i+eefx7p163DNNdfUeXxDr/VCc81mtxKdiIiIiIiIiIiIiKQlUyigjUtC1akTboV0hU4PbVxSkxTQAaCwsBD33nsv8vLyYDAYkJqa6rGA3lhYRCciIiIiIiIiIiKiiyZXqaBLaA3RboPodECQySEolE1WQAeAd999t8m27QmL6ERERERERERERER0SWQKBdCERXNfIJM6ACIiIiIiIiIiIiIiX8UiOhERERERERERERGRByyiExERERERERERERF5wCI6EREREREREREREZEHLKITEREREREREREREXnAIjoREREREdHfiKIIURSlDoOIiIiIfIBC6gCIiIiIiIh8hdNmhcNihqW0GACgDo2AXK2BTKmUODIiIiIikgqL6ERERERERACcNhtMJ0/AbjK6xqzlpVDqgxHYKhFyFtKJiIiI/BLbuRAREREREQGwVRndCuiucWM5HNUmCSIiIiIiIl/Aleg+wmw2Izc3V+owPEpISIBGo5E6DCIiIiKiJuG022EpLvQ4by4uhEKnh0wu92JURERERNSQ5557DjNmzMAjjzyChQsXNtl+WET3Ebm5uZg0aZLUYXi0dOlStG/fXuowiIiIiIiahihCdDo9TzudAG80SkRERFSHw2qFw2yBaLdDplRCplZBrlI1+X537tyJt956C6mpqU2+LxbRfURCQgKWLl3aKNvKycnBggULMHPmTCQmJjbKNhMSEhplO0REREREvkhQKKAyhKDGXFPvvCo4FAJXoRMRERG5sVfXoHjXXpgLi1xjmsgIhPfsBkVgQJPt12QyYcyYMXj77bcxf/78JttPLRbRfYRGo2n0ld6JiYlcPU5EREREdAEEQYAqJAzmkiKIdpvbnEypgsoQDEEQJIqOiIiIyPc4rNY6BXQAMBcWoXjXXkT06dlkK9KnTJmCESNGYOjQoSyiExEREREReYtcpYa+TUeYiwtgLS8FAKhCQqEJj4JcpZY4OiIiIiLf4jBb6hTQa5kLi+AwW5qkiL5q1Srs3r0bO3fubPRte8IiOhERERER0f/I1WoExrRCQEQ0gLNtXgSZTOKoiIiIiHyPaLdf1vylOHnyJB555BFs2LABGo2m0bfvCYvoRERERERE5xBkcggq9j8nIiIiaoigaLi0fL75S7Fr1y4UFhaiR48erjGHw4EtW7bg9ddfh8VigbwJ7mPDIjoRERERERERERERXRS5Rg1NZES9LV00kRGQaxq/Hd6QIUOwf/9+t7Hx48ejY8eOeOKJJ5qkgA6wiE5EREREREREREREF0muUiG8Z7c6NxfVREYgvGe3JumHHhQUhC5duriNabVahIWF1RlvTCyiE1Gz53A4sG/fPpSWliI0NBSpqalNduaRiIiIiIiIiIjOUgQGIKJPTzjMFoh2OwSFAnKNukkK6FJiEZ2ImrUtW7Zg8eLFyM/Pd41FR0dj8uTJSE9PlzAyIiIiIqKWSXQ6YTVVw1JhgsNqgyZED2WgBoomuGyfiIh8n1ylkrRo/tNPPzX5PlhEJ6Jma8uWLZg7dy7S0tIwe/ZsJCcnIzs7GytXrsTcuXORkZHBQjoRERERUSNyOhwwnSnG0TUb4TBbXeOR3Tqg1YDuUGkDJIyOiIioacikDoCI6FI4HA4sXrwYaWlpmD9/PlJSUhAYGIiUlBTMnz8faWlpWLJkCRwOh9ShEhERERG1GNbKahxevc6tgA4AhXuPoPTPbIiiKFFkRERETYdFdCJqlvbt24f8/HyMGTMGMpn7rzKZTIYxY8YgLy8P+/btkyhCIiIiIqKWp+LEGYj2+heqnNm2DzZTjZcjIiIianosohNRs1RaWgoASE5Orne+drz2cUREREREdPlqiss9ztmqaiA6nd4LhoiIyEtYRCeiZik0NBQAkJ2dXe987Xjt44iIiIiI6PIFxUV6nNOE6iHI5V6MhoiIyDtYRCeiZik1NRXR0dFYuXIlnH9b7eJ0OrFy5UrExMQgNTVVogiJiIiIiFoeXUwEFIGaeufir74SKh1vLEpERC0Pi+hE1CzJ5XJMnjwZ27Ztw6xZs3Dw4EFUV1fj4MGDmDVrFrZt24YHHngAcq6EISIiIiJqNGqDDp3HXAdtTLhrTK5RIXl4X+jjoiSMjIiIqOkopA6AiOhSpaenIyMjA4sXL8aUKVNc4zExMcjIyEB6erqE0RERERERtUwBYQZ0uP0a2KvNcDqcUASooNIFQpBxnR4REbVMLKITUbOWnp6Ofv36Yd++fSgtLUVoaChSU1O5Ap2IiIiIqAkpAzVQemjrQkRE1NKwiE5EzZ5cLkf37t2lDoOIiIiIiIiIiFogXmtFRERERERERERERM3CvHnzIAiC27+OHTs26T4brYielZWFWbNmYfTo0SgsLAQArF27FgcPHmysXRARERER0XkwLyciIiIib7LVWFBTUg7TmSLUlFTAVmNp8n2mpKQgLy/P9e+XX35p0v01ShF98+bNuOKKK7Bjxw589tlnMJlMAIA//vgDc+fObYxdEBERERHReTAvJyIiIiJvshhNOPblT9j39uc4+H/fYN/bnyHrq59gMZqadL8KhQLR0dGuf+Hh4U26v0Ypoj/55JOYP38+NmzYAJVK5RofPHgwtm/f3hi7ICIiIiKi82BeTkRERETeYqux4Ph3v8J44ozbeEX2GWSv/bVJV6RnZmYiNjYWrVu3xpgxY5Cbm9tk+wIaqYi+f/9+3HzzzXXGIyMjUVxc3Bi7ICIiIiKi82BeTkRERETeYq+uqVNAr1WRfQb26pom2W+fPn2wfPlyfP/991iyZAmys7MxYMAAVFZWNsn+gEYqogcHByMvL6/O+J49e9CqVavG2AUREREREZ0H83IiIiIi8haHxXZZ85dq+PDhuP3225Gamophw4bhu+++Q3l5OT7++OMm2R/QSEX0O++8E0888QTy8/MhCAKcTid+/fVXTJs2Dffee29j7IKIiIiIiM6DeTkREREReYtcrbys+cYSHByM9u3b49ixY022j0Ypoj/zzDPo2LEj4uPjYTKZ0LlzZ6Snp6Nv376YNWtWY+yCiMgjh8OBPXv24IcffsCePXvgcDikDomIiEgSzMuJyFscVhvM5ZWoKa2A1dQ0l+sTEZFvUwQGwJAcW++cITkWisAAr8RhMpmQlZWFmJiYJtuHojE2olKp8Pbbb2P27Nk4cOAATCYTunfvjnbt2jXG5omIPNqyZQsWL16M/Px811h0dDQmT56M9PR0CSMjIiLyPublROQN5opKnPxpF0oPnwBEEZoQPRKvvQq6VhFQnHNTYyIiatmUAWokD++H7LW/oiL7r97ohuRYJA/vD2WAukn2O23aNIwcORKJiYk4c+YM5s6dC7lcjtGjRzfJ/oBGKqLXSkhIQEJCQmNukojIoy1btmDu3LlIS0vD7NmzkZycjOzsbKxcuRJz585FRkYGC+lEROSXmJcTUVOxVFbh8Kr1sJQZXWPmMiOOrF6PTncNhz4hWsLoiIjI29R6HdrcMAj26ho4LDbI1UooAgOarIAOAKdOncLo0aNRUlKCiIgI9O/fH9u3b0dEREST7fOSi+iPPfbYBT/2lVdeudTdEBHVy+FwYPHixUhLS8P8+fMhk53tTpWSkoL58+dj1qxZWLJkCfr16we5XC5xtERERE2HeXnjE0URot0OABAUCgiCIHFERL6jprDUrYB+rpwffkPHUddCGajxclRERCQlZYC6SYvmf7dq1Sqv7avWJRfR9+zZ4/b17t27Ybfb0aFDBwDA0aNHIZfL0bNnz8uLkIioHvv27UN+fj5mz57tKqDXkslkGDNmDKZMmYJ9+/ahe/fuEkVJRETU9JiXNy6H1QpreQksZSUAAHVoOFSGUMjZooIIAFB+zuX6f1ddUAKnze7FaIiIiLzjkovomzZtcv3/K6+8gqCgIKxYsQIhISEAgLKyMowfPx4DBgy4/CiJiP6mtLQUAJCcnFzvfO147eOIiIhaKubljcdhtaLy+BE4rRbXWE3eKVhKixGU3J6FdCKcvWzfE7laBUHGKzeIiKjlaZSe6C+//DLWr1/vStQBICQkBPPnz8e1116Lxx9/vDF2Q0TkEhoaCgDIzs5GSkpKnfns7Gy3xxEREfkD5uWXThRFWCvK3ArotZwWM2yVFZCHNV2fTaLmIqRtPM7s2I+oHh2hjQyF6HDC6XCg6I+jCEqIhlIbIHWIREREjU52/oecn9FoRFFRUZ3xoqIiVFZWNsYuiIjcpKamIjo6GitXroTT6XSbczqdWLlyJWJiYpCamipRhERERN7HvPzSiQ47rGXFHuctZcVw2tmmgkgZFIiOd1yDiqxTOLrmB2R+sQk5G3cgpH0iIlLbQZA1SpmBiIjIpzTKp9vNN9+M8ePH47PPPsOpU6dw6tQprFmzBhMnTsQtt9xywdtZsmQJUlNTodfrodfrkZaWhrVr17rmzWYzpkyZgrCwMOh0Otx6660oKChw20Zubi5GjBiBwMBAREZGYvr06bAz2SVqceRyOSZPnoxt27Zh1qxZOHjwIKqrq3Hw4EHMmjUL27ZtwwMPPMCbihIRkV9prLwc8MfcXAAauIGoAAFglwoi2GvMOPLxBpjOFJ0zZkHOxh2oLmArRSIiapkapZ3Lm2++iWnTpuGuu+6CzWY7u2GFAhMnTsSLL754wduJi4vDc889h3bt2kEURaxYsQI33ngj9uzZg5SUFDz66KP49ttv8cknn8BgMODBBx/ELbfcgl9//RUA4HA4MGLECERHR2Pr1q3Iy8vDvffeC6VSiWeeeaYxXioR+ZD09HRkZGRg8eLFmDJlims8JiYGGRkZSE9PlzA6IiIi72usvBzwv9xcplBAExaJqlMn6p1Xh0VAJm+UP5+ImjXTmWLYqmrqncvd9Dt0sRFs6UJERC2OIIqi2Fgbq6qqQlZWFgCgTZs20Gq1l73N0NBQvPjii7jtttsQERGBDz/8ELfddhsA4PDhw+jUqRO2bduGq666CmvXrsX111+PM2fOICoqCsDZPySeeOIJFBUVQXWBNwIyGo0wGAyoqKiAXq+/7NfgbUePHsWkSZOwdOlStG/fXupwiDwym83Izc297O04nU5kZmaioqICBoMB7dq1g6yRLiNNSEiARqNplG0REREB3sk1myIvB1p+bu6wWWE6cQyOmmq3cUWgDrrE1pApeWNRohMbd6Dg90Me57s9cDvUBs83HyUiIt9gNpuRnZ2N5OTkFl/3aOi1Xmiu2ahLKbRabaP1H3Y4HPjkk09QVVWFtLQ07Nq1CzabDUOHDnU9pmPHjkhISHAl6tu2bcMVV1zhStIBYNiwYXjggQdw8P/Zu+/wOKqr8ePfmdmqlbTSqsu2ZLl3YwzGwmB67yYBEkJoCXnBSX5AKi8QqtMJCQmQ1yn0kkLvHUyxsXHBuDdZclEvq9X2nZnfH44FiiQD9mpG9p7P8/CA7lnvHO+i1dWZe89dvZpp06b1ea14PE48/ukBQp2dnWn5Owgh9qyuro4rrrjC7jT2SG5GfT5d11m5ciVtbW0EAgGmTJkibXSEEMJm6ZyXQ+bMzTWni+zho0iFu4i3NQMKnoIiHFk+KaAL8R/eAn+/MafPi6JK3yM7xbuiGCkdh8eF0yOfW0IIkS57XUSfM2cO999/P7m5uZ/bX/HJJ5/8ws/7ySefUF1dTSwWIzs7m6eeeooJEyawYsUKXC4XeXl5PR5fUlJCQ0MDAA0NDT0m6bvju2P9+cUvfsEtt9zyhXMUQqRHRUUF8+fPT8tz1dbWMm/ePK6//noqKyvT8pywK0fRvwULFnDPPff0+IwtLS3lqquuknY6QghhkYGal0Nmzs01pwstL4AzZ1ehUJUbw0L04K8agqJpmLreK1Y+czLO7CwbshKxUITmDdtZ+/ISYsEwBSPLmXjaTHJK8tCc0opKCCH21V5/kvr9fpT/HLzj9/d/J/rLGjt2LCtWrCAYDPLvf/+biy++mHfeeSdtz9+X6667jmuvvbb7687OToYNGzag1xRCgMfjSfsq78rKSlk5bpEFCxZw0003UV1dzY033khVVRU1NTU88sgj3HTTTdKXXgghLDJQ83LI7Lm5FM+F6JsrJ4tx55/IhifeQI8nuseLpowmMGFE9+eRsE48EmPN84vY9M7K7rEdyzex8+MtHHPtVygcVW5jdkIIcWDY6yL6fffd1+d/7yuXy8WoUaMAmD59OkuWLOEPf/gD559/PolEgo6Ojh4rXhobGyktLQV2rX5cvHhxj+drbGzsjvXH7XbjdrvT9ncQQogDna7r3HPPPVRXV3P77bd396CfOHEit99+OzfccAP33nsvs2bNktYuA0ha6QghYODm5SBzcyFEb6qmkTO0mMmXnUU8GCIVT+IN+HH6PDg88r1rh3hnpEcBfTfTMPjo0Tc4+upz8eTKDgG7hDvC6KkUDpeTLHkfhEibHTt28JOf/ISXXnqJSCTCqFGjuO+++zjkkEMG5HppOXlv3bp1/cZeeeWVfXpuwzCIx+NMnz4dp9PJG2+80R1bv349dXV1VFdXA1BdXc0nn3xCU1NT92Nee+01cnNzmTBhwj7lIYQQ4lMrV66koaGBCy+8sNchrqqqcuGFF1JfX8/Klb0n8yI9FixYwIUXXsg111zDbbfdxjXXXMOFF17IggUL7E5NCGGjgZyXg8zNhRC7KKqK259NbkUZgdEVeAv8UkC3Ucvm+n5jnTtbSURiFmYjdot0Rlj7wWoevuE+7r3yjzx+y8NsXbmFWFfU7tSESLt4OEZnQxutNfV0NrQRDw/s5057ezuzZs3C6XTy0ksvsWbNGu644w7y8/MH7JppaYx18MEH85vf/Ia5c+d2j8XjcX7wgx/w17/+lVjsi71w1113HaeccgoVFRWEQiEeffRR3n77bV555RX8fj+XX3451157LYFAgNzcXL73ve9RXV3NzJkzATjxxBOZMGECF110Eb/+9a9paGjghhtuYO7cubKaRQgh0qitrQ2AqqqqPuO7x3c/TqSXtNIRQvQnXfNykLm5EELsLzTnnnciKmpa1k+KLyERjfPRCx+y4NG3usd2btjOw9ffz1nXnsvE2ZOkbZg4YETaQix56DUa19Z1j5WMr+TQi44nK5AzINf81a9+xbBhw3rswuyvPpEuafkkvf/++/nZz37GqaeeSmNjIytWrGDatGm8/vrrvPvuu1/4eZqamvjmN7/J2LFjOe6441iyZAmvvPIKJ5xwAgB33nknp59+Oueeey6zZ8+mtLS0x+FImqbx/PPPo2ka1dXVfOMb3+Cb3/wmt956azr+mkIIIf4jEAgAUFNT02d89/jux4n0+e9WOhMnTiQrK6u7lU51dTX33nsveh+HfQkhDnzpmpeDzM2FEGJ/UVBV2m8v+qLRQ3D7PBZnJMLBMO/9o+8zRF79y4uE2roszkiIgREPx3oV0AEa19ay5KHXB2xF+rPPPsshhxzCV7/6VYqLi5k2bRp/+ctfBuRau6VlJfp5553H4YcfzqWXXsrEiRMJh8Nccskl3HHHHWRlffF+T3/729/2GPd4PNx9993cfffd/T6msrKSF1988QtfUwghxJc3ZcoUSktLeeSRR3r0RIddW/0feeQRysrKmDJlio1ZHph2t9K58cYb+22lM3fuXFauXMm0adNsylIIYZd0zctB5uZCiM+XiiUwDQPN7ULVZLWzXTw5WRz89WNZ+sgbPcZdWW4O/vqxuKSIbrlgUweGbvQZi4aiRDsj+IvSexi4EHaIhyK9Cui7Na6tJR6KDMiNvC1btnDvvfdy7bXX8r//+78sWbKE73//+7hcLi6++OK0Xw/SVETfLZFIoOs6uq5TVlaGxyMf1EIIcSDSNI2rrrqKm266iRtuuIELL7ywR0uRhQsXcsstt8ghlwNAWukIIb4ImZcLIQZSMhyla2cz9YtXoccT5I0cRtHUMbj92f2uiBYDx+FxUXHIGALDS9n0zsdE2kKUTqhg6EGjyCrItTu9jORw7rncpjrkppM4MCSj8c+JJwbkuoZhcMghh/Dzn/8cgGnTprFq1Sr+/Oc/D1gRPS3ftY8//jiTJ0/G7/ezYcMGXnjhBebPn8+RRx7Jli1b0nEJIYQQg8zs2bO55ZZb2LJlC3PnzuXUU09l7ty51NTUSE/uAfTZVjq6rrN8+XLeeOMNli9fjq7r0kpHiAwn83IhxEBLRmLUvrmEDU+8QWhbI5GmdnYuXMnq+58j1t5pd3oZy+l1kz+siOlfO4ZZ/3M6Y447GF+hX25q2CSn0I+nn9W3BUMLycr9crvDhBisnN49n3Pj9LoG5LplZWW9DqofP348dXV9r4pPh7SsRL/88sv57W9/y5VXXgnACSecwMqVK/mf//kfDjroIDo75QepEEIciGbPns2sWbNYuXIlbW1tBAIBpkyZIivQB9DuVjp33XUXHR0dNDY2dsdKSkrIy8uTVjpCZDCZlwshBlo82EXr6s29xlOxONsXLGPEqUeguZw2ZCYAVE2TAysHgZxANudedz6P3fwwRurTs4pcXjfn/PArZOcPzGGLQljNnZNFyfhKGtfW9oqVjK/EnTMwN4xmzZrF+vXre4xt2LCBysrKAbkepKmIvmzZMsaOHdtjLBAI8M9//pOHHnooHZcQQggxSGmaJr23LaRpGkcffTSPP/44+fn5/OAHP6C6upqFCxfy97//nfXr13PBBRfIjQwhMpTMy4UQA61t/dY9xGqpOPZQKaKLjKdqGv6iPC742YVsWb6ZjsZ2iiqKqZhUiVdWoYsDiNvn4dCLjmfJQ6/3KKSXjK/k0G8eP2AHG19zzTUcfvjh/PznP+e8885j8eLFzJ8/n/nz5w/I9SBNRfTdE/WlS5eydu1aACZMmMDBBx/MRRddlI5LCCGEEALQdZ23336bsWPHEgwGueOOO7pjZWVljB07lnfeeYdvf/vbUkgXIgPJvFwIIYSwX6itk8duepD2xg4qJ1biy89m87JNvPv421ROqeIrPz0f7wCt0BXCalmBHGZ+6xTioQjJaAKn14U7J2vACugAhx56KE899RTXXXcdt956K1VVVfz+97/nwgsvHLBrpqWI3tTUxAUXXMDbb79NXl4eAB0dHRxzzDE8/vjjFBUVpeMyQgghBiFd16Wdi4VWrlxJQ0MDN954I+PGjev12q9bt465c+eycuVK2SEgRAaSebk4UJmmiR6LAyaqyyXtKmxUMK6K+kWf9BkLjBuOw7Pn/rhiYMVCEYyUgdPrxCnvhW262rtob2gHoHbV1h6x2pU1hINhKaKLA4rb5xnQonlfTj/9dE4//XTLrpeWIvr3vvc9QqEQq1evZvz48QCsWbOGiy++mO9///s89thj6biMEEKIQWbBggXcc889NDQ0dI+VlpZy1VVXycGiA6StrQ2AqqqqPlvpVFVV9XicECKzyLxcHIhS0ShdtdsI1dSCbuAdUoZ/9Egcviw5NNEGrlwfRVPG0LxyQ49xh9fNsNkHSysXm8Q6IzSuq2Pdy0uIBsMUjihj4pnV5JTk45D3xHKxUHSP8WQsaVEmQoh0SUsR/eWXX+b111/vnqjDrm2jd999NyeeeGI6LiGEEGKQWbBgATfddBPV1dXceOONVFVVUVNTwyOPPMJNN93ELbfcIoX0ARAIBACoqalh4sSJveI1NTU9HieEyCwyLxcHmlQ0SuN7i0h2hrrHurZsJbJ9B2XHzMaZ7bMxu8zkzPIw7KiDCYyrpP7DVaRiCfLHVFA4cSSePDks0Q6JcJRVz37AlvdWdY/t/KSG+tVbOeqacykePdTG7DJTTmFuvzHN6cCb47UwGyFEOqjpeBLDMHA6e9/ZdDqdGIaRjksIIYQYRHRd55577qG6uprbb7+diRMnkpWVxcSJE7n99tuprq7m3nvvRdf1z38y8aVMmTKF0tJSHnnkkV4/Yw3D4JFHHqGsrIwpU6bYlKEQwk4yLxcHmnhre48C+m5GIknnpi0YMtewhdPnJW/EUMbMOZZxF5zEkOopUkC3UbQz0qOAvptpmCx79E1inWEbsspsPn82Y2eO7zM244yZ+PKyLc5ICLGv0rIS/dhjj+X//b//x2OPPUZ5eTkAO3bs4JprruG4445LxyWEGDCxWIy6ujq70+hXRUUFHo+1faWE+Dyf7cutqj3vx6qqyoUXXih9uQeIpmlcddVV3HTTTdxwww1ceOGFPXYBLFy4kFtuuUX60guRoWReLg4khq7TVbut33hkx078Y0ehemVFp100twuZcdivdUt9v7HO+jYSkTieXNm1YSVvjpeTrzyN7EAOK15bhp5M4fK6mXnO4Uw/5VCcbmmxI8T+Ji1F9D/96U+ceeaZDB8+nGHDhgGwbds2Jk2axMMPP5yOSwgxYOrq6rjiiivsTqNf8+fPZ8yYMXanIUQPn+3L3Rfpyz2wZs+ezS233MI999zD3Llzu8fLysqkjY4QGU7m5eJAoigKiqP/Eq2iaYD0RBfC4dpzaUdR09KEQHxJOYFcjr/sJKrnzCIZT+LyuMgO5KDt4XNNCDF4paWIPmzYMJYtW8brr7/OunXrABg/fjzHH398Op5eiAFVUVHB/Pnz0/JctbW1zJs3j+uvv57Kysq0PGdFRUVankeIdJK+3PabPXs2s2bNYuXKlbS1tREIBJgyZYqsQBciw8m8XBxIFFUlZ8RwItt39hnPqRqO5nFbnJUQg09geBmKqmAaZq9Y8ZihuLNlZ7NdnG4neSX5dqchhEiDtBTRYdcqgRNOOIETTjghXU8phCU8Hk/aV3pXVlbK6nFxQPtsX+7bb7+9R0sX6cttHU3TpF2OEKIXmZeLA4krNwdfxVDCddt7jvtz8VUMQVFkJbqdUrE4pm6geVyociPfNu7cLKZ/43g+evC1nuPZXg7++rG4sqSILoQQ+2qvi+h33XUXV1xxBR6Ph7vuumuPj/3+97+/t5cRQggxCElfbiGEGDxkXi4OZJrbTWDKRHKqKglt2Yqp6/gqh+HOz8MhvdBtk4xEiQfDpKIxjJSOw+vGlevDnZstNzZs4HQ7GTZtFIHKEra8+wnh1k5KJ1ZSPnkEvoJcu9MTQogDwl4X0e+8804uvPBCPB4Pd955Z7+PUxRFJutCCHEAkr7cQggxOMi8XBzoNLcbze3GHdjVEkH6O9srGY0RbQlS+/oiIk3tAGguJ2WHTSYwoQpvvhRt7eD0uskb4mbaeUdjGIb03RZCiDTb6yL67n63//3fQgghMof05RZCCPvJvFxkCimeDw6pcIyNT71JKhrvHtMTSba/uwxnjhdXthfN6bQxw8ymqAqaKnNxIYRIN5mFCCGE2Ce7+3Ifd9xxTJs2TQroQgghhBAHsK76lh4F9M/aufATkl0xizMSn6WnUiQi8h4IIQ5sw4cPR1GUXv98dpd8uu31SvRrr732Cz/2d7/73d5eRgghhBBCCLEHMi8XQlgp3NDSbyze3gmY1iUjukU6QsQ6wmxfvplUMomvMJfyiVVkFebKIhchxICLhqKEg13Ew3E8Pg9Zfh/enIE7u2TJkiXout799apVqzjhhBP46le/OmDX3Osi+vLly3t8vWzZMlKpFGPHjgVgw4YNaJrG9OnT9y1DIYQQQgghRL9kXi6EsJIn0H/Pc2d2FqYpRXSrxTrDtGyuR3NoeHKziHWG8WRn0bqlHiOl4x9SaHeKQogDWLA5yPN/fIaa5Zu6x0ZMG8Vp3zsLf5F/QK5ZVFTU4+tf/vKXjBw5kqOOOmpArgf7UER/6623uv/7d7/7HTk5OTzwwAPk5+867KW9vZ1LL72UI488ct+zFEIIIYQQQvRJ5uVCCCvlVpShOh0YyVSvWPnMyahyoKXlkrEkmLDory+hf+Z9yS0v4OCvHUOkPURWfo6NGQohDlTRULRXAR1gy/JNvPDHZzjnR18d0BXpAIlEgocffphrr70WRVEG7Dp7XUT/rDvuuINXX321e6IOkJ+fz+23386JJ57ID37wg3RcRgghRBrFYjHq6ursTqNfFRUVeDweu9MQQoj9iszLhRADLdEVYexXT2Dj02+R2t17W1EoOXgc7rwcTN2wN8EMlIzFWfLgqz0K6ACdO1vZ9NYKJp89y6bMhBAHunCwq1cBfbctyzcRDnYNeBH96aefpqOjg0suuWRAr5OWInpnZyfNzc29xpubmwmFQum4hBBCiDSrq6vjiiuusDuNfs2fP58xY8bYnYYQQuxXZF4uDlSGrmPEEwCoTgeq02lzRplLcznp2LKDymNnoDo19EQKZ5aHYF097txsaedig67GDvRE750BADtWbGbi6dUWZySEyBTxcN8HTX/ReDr87W9/45RTTqG8vHxAr5OWIvo555zDpZdeyh133MGMGTMA+PDDD/nRj37EnDlz0nEJIYQQaVZRUcH8+fPT8ly1tbXMmzeP66+/nsrKyrQ8Z0VFRVqeRwghMonMy8WBKBWJENywma7aOkzdwFteSv7EcTizswd027boh6Kw8/0V3f+taipGatfhbonOMBXHHGJfbhkqHo71GzMNU25sCCEGjNvn3qf4vqqtreX111/nySefHNDrQJqK6H/+85/54Q9/yNe//nWSyeSuJ3Y4uPzyy/nNb36TjksIIYRIM4/Hk/aV3pWVlbJ6XAghbCTzcnGgSUWiNCz4gFQ40j0W3VFPrLGJ8mOPwpmTbWN2mal93dZPvzDN7gI6QPv6WoYeOc36pDJc/rCifmPevGzpUy+EGDA+fzYjpo1iSx8tXUZMG4XPP7A/p++77z6Ki4s57bTTBvQ6kKYielZWFvfccw+/+c1v2Lx5MwAjR47E5/Ol4+mFEEIIIYQQX4DMy8WBJtbS2qOAvpuZ0glu2ERgqhxkaTXDMFBUhfwxleSPqURVVSKtHTSv2ECiq/d7JQae6nRQOKqclk07e8UmnXU4yIYNIcQA8eZ4Oe17Z/HCH5/pUUgfMW0Up3//rAHth24YBvfddx8XX3wxDkdaStx7lNYr+Hw+pkyZks6nFEIIIYQQQnxJMi8XBwJD1wlv295vPFrfiDFhnBTRLRYYNxz/8HLaN9RS89L7GMkUvrJCKo8/jEhzq7wfNlAUGHv8dHJLA9R+uA49mcJXkMvYEw8hHoqgSBVdCDGA/EV+zvnRVwkHu4iH47h9bnz+7AE/UPT111+nrq6Oyy67bECvs9vAl+mFEEIIIYQQQogvSVGUPR4gqjgdssLWBs4sL1tfWUi0ub17LFzfwsan32LC10/BVFQbs8tM7XVNbHh9GTMuPpHRx07D0A00h0bHjhaW/eNNyiZV2Z2iEOIA583xDnjR/L+deOKJlp75IEV0IYQQQgghhBCDjqKq5IysIrxtR5/x3FEj0NwDe2CZ6C3a3NajgN7NNKl7+yNGnj7b+qQynMvnofpbp7Lkoddp29oAgOrQGDl7Msf96Hw5WFQIIdJAiuhCCCGEEEIIIQYlZ3Y2OaNGkAwG8ZaVoigKsZY29ESCrPIyFEWWolstWFvfb6xrRxOmYViYjQDwlxWw4I9PE24Jdo8ZKZ2Nb67A6XUz4ohJNmYnhBAHhn3eZ5VMJrnsssuoqalJRz5CCCGEEEKIvSDzcnEgMk2D7MpheIqKCG2qIbh+I5rbRcGUiZimFGvt4MrO6jemuZzSYscG4dbOHgX0z9r45gpS8aTFGQkhxIFnn4voTqeTJ554Ih25CCGEEOJLaGtr45JLLuGMM87gkksuoa2tze6UhBA2knm5OBDpsQQtHy2nY806UpEIeixOaMtWGt5diBGLy6pnG+SPGtZvrGjKaDSvtNixWrC+td9YMhpHT6YszEYIIQ5MaTnx4+yzz+bpp59Ox1MJIYQQ4guYM2cOc+bMYevWrYRCIbZu3do9JoTIXDIvFwcSwzBItLeTDHb2jiUShGpq0RMJGzLLbNFgF1UnH95rPKu0gMD4KvRo3IasMltOcX6/Mc3lQHNIJ187JGNJOhrb2ba2jtpVW9mxfjsdjX2cJyCE2C+k5ZN09OjR3Hrrrbz//vtMnz4dn8/XI/79738/HZcRQgghBLsK6P2tOm9ra2POnDk8+eSTFmclhBgMZF6+70xDx0ilMP5TnFVdLlSHE0VNy/oj8SWYhkGkvqHfeLShEf/Y0RZmJACcbiehmh2M/eoJhHY0occSZA8pwkimSHR24czy2p1ixskpzsPj96EnUww9aBQun5tgfRuNq2sZccQknD7ZHWC1RCJBsKmD2k9q+OiFxXQ0tlNUUcxhZx+OnkpRMKTI7hSFEF9SWorof/vb38jLy2Pp0qUsXbq0R0xRFJmsCyGEEGnS1tbWXUCfMWMGF198MVVVVdTU1PDAAw+wePHi7scEAgGbsxVCWE3m5fvG0HUSwXYiO2rBNHcNKiq+oZU4c/2omqzmtJKqqiiqiub1kDuyCkd2NpgmRjJJaHMNRiqFosnNDaslIzEal62jcfl6fCUFqC4HrWu3kIrGySrOZ/Q5x9qdYsZRNJWjrp5DqKGdrYvWEqxvJVBZwoQffhV3thc9Lu1crBZuC7Pi1WV8+MwH3WP1m3by9G//zUlXnIrD5cJf5LcxQyHEl5WWWaAcXiSEEEJY45prrgEgOzubX/7yl6j/WRk5ceJEfvnLX3LmmWfS1dXFNddcwwMPPGBnqkIIG8i8fN8Y8SiR7Vt7DpoG4W015I4ej+qVIrqVFFUlZ/RIshNJOlavJfGfti5alpf8CeNAVdE8HpuzzDyhbY2gKOSPGkZgbCWKQyPS2EbTxxuINLVjysGilgu3dNKyaQfJaILxJx+K6tCIhyKsfm4hY0+YTlZBrt0pZpxkPMHi5xb1GXvn0beoOmikxRkJIfaV3LYXQggh9iNNTU0AXHbZZd0F9N1UVeXiiy/u8TghhBBfjKHrRJv20DqkqUEOsbSBw+WiefHS7gI6gB6J0vLRcpy+LBRFKrZWc+flMGbOsbhyfWx9bRGbnn6b0PZGRpwyi/yxw8Ew7U4x47iy3JRPHYHD6+K9e57htXmPsPKp9xhzwnQS0Tgg3ydWCzYF+/2ZEeuKEgvHLM5ICLGv0rKU4rLLLttj/O9//3s6LiOEEEJkPJ/PRzQa5dVXX+3zENHXXnut+3FCiMwj8/J9YBoY8f6LGkYijmkY0hvdQqZpEt5Zj5nquxVF+5r1FB02Hc3ptDizzOavGsLm5xYQaWztHgttayS0vYlxF5yE4pD3w2qKprLyqfdpWPXpbqSObc28+8enOfyK09Bcmo3ZZSaX17XHuOaU90SI/U1aZoDt7e09/mlqauLNN9/kySefpKOjIx2XEEIIIQSfHgq4bt06urq6esS6urrYsGFDj8cJITKLzMv3nqJqaN7+b0Bq3iwpoFvMNAziza39xhMdHf0W2MXASXR29SigdzNNdry3HFOX98RqRjLVo4D+WR8/+S56Urc4I5ETyMGT3fchuwVDC8nKzbI4IyEOLLquc+ONN1JVVYXX62XkyJHcdtttmObA7YZKy0r0p556qteYYRhceeWVjBwpfZ6EEEKIdJk1axaqqmIYBqeffjrjx4/n0ksv5b777mPt2rXArrYus2bNsjlTIYQdZF6+9xRVxVNUQqKjFUd2Ls7sXMAkGeokFe7CU1giRXSLKaqKI9sHjX3HHV4viiqrOa3WsXlHv7HQtkaQbi6Wa9lSD4Cv0E/ljLE4szx01rey7aMNhFs60RNJmzPMPHklecz5yVd5/JZHMFKf3sRwed2cde25+Ivy7EtOiAHQ1Rkm2NZJpCuKLzuL3EAO2bkDtzv6V7/6Fffeey8PPPAAEydO5KOPPuLSSy/F7/cP2IKyATsZR1VVrr32Wo4++mh+/OMfD9RlhBBCiIyiaRo333wzP/vZzwBYu3Ztr5+zN998M5omRQUhxC4yL//iNJeb3DETSbS1EG9rBsDlz8c3pALVteet+SL9FEUhp6qS0Oa+V9j6x49Bc8v7YjXN03+7FtXpQKro1nP5PEw990gcbic1H6whFgyTP7yE6m+fxoY3lqHKvNByqqZROXE43/nTXNa+t4rGrY0MG1/B6BljySvOszs9IdKqtbGNP992PysXre4emzpzEt+58WIKSgIDcs0PPviAs846i9NOOw2A4cOH89hjj7F48eIBuR4M8MGimzdvJiXb64QQQoi0mj17NrfeeivFxcU9xktKSrj11luZPXu2TZkJIQYrmZd/MYau07V1I7GWRoxEHCMRJ9bcQGjrph4rCYV1HL4sCmdMR1FVnDnZOP25oKrkjhmFp2BgfjEXe5ZXNaTfWOHEkSia7NiwWkFVKZ0NbSx99E3atjYQaQ+xY/km3r/3WUYfOw2H3GyyhWGamCYEhhYx6aipZBf6wWRA202IL6azrZOG7U10tHZ+/oPFHnV1hnsV0AE+XrSK/7vtAbo6wwNy3cMPP5w33niju53pxx9/zHvvvccpp5wyINeDNK1Ev/baa3t8bZom9fX1vPDCC1x88cXpuIQQQgghPmP27NnMmjWLlStX0tbWRiAQYMqUKbICXYgMJ/PyvWeaJolgO0Yi0StmJOIkQx1oBcV9/EkxkFSHA09xEWXHHUWsqRlTN/AUF6J53Ghut93pZSTV5WTo7IPZvmBZj3FvUT4FE0eCIkV0qxlJnZr3V/ce1w0+efp9Zl11hg1ZZTY9pdO0tQHN4cDUDZq2NVNcVUI8EqNle5LiyhK7U8xI7S0ddLQEee7hV9i2aQclQ4s44xsnESgNUFRaYHd6+6VgW2evAvpuHy9aRbCtc0Dauvz0pz+ls7OTcePGoWkauq4zb948LrzwwrRfa7e0FNGXLVuGoijdX6uqSlFREXfccQeXXXZZOi4hhBBCiP+iaRrTpk2zOw0hxCAi8/K9Z+opEu0t/cbj7a24/AFUx4B1xBR90BNJItu20/bxqh7jvoqh5E+egMPjsSmzzKXHE2geN2O+cjyhugZSsTg5w0pAVTFNAwzZtWG1lpr6fmPBHS2kYtIT3WrRriiY8MgN9xMNRbvH/UV+zr/pG3QFu8j2Z9uYYeZJJpNsXrOVO350N4ZuAFC3aTtL3l7OFTdczKFHHURufq7NWe5/Il3RPcajnxPfW//85z955JFHePTRR5k4cSIrVqzg6quvpry8fMAWjuz1DPDZZ5/llFNOwel08vbbb6cxJSGEEOLAFovFqKurszuNflVUVOCRooQQ+w2Zl6eLAoqK6nLhLihGc+1a5azH48Rbm1BQQPmcpxBplwqHexXQAcJ12/EWF5FdOcyGrDKbqSjkDish3NiKaRqoTgfxzgh5VeU4fV5pfWSDz9487TtuUSKiWzwc44lf/qNHAR0g2BzkhT8+w1k/OBekiG6plvo2/vrzh7oL6J/1wG8fY/y0MVJE3wtZ2d49xr2fE99bP/rRj/jpT3/KBRdcAMDkyZOpra3lF7/4xeArop9zzjk0NDRQVFSEpmnU19f36s0qhBBCiN7q6uq44oor7E6jX/Pnz2fMmDF2pzEgBvsNDJCbGOLLk3l5euxqG1KGgkm0cSd6bFfhQ/N4yRpSgYmCqskqdCuZhkFoy9Z+48ENm/CWFKN5pK2LlVxeD6seeBbN5SIwpgLV6SBUV8+Od5dRecJMCieNtDvFjFNQVYqiKH322i4cWf6fA1+FlSLBMJ0tfffb3rF+O0nZHWC5rmCY9paOPmPxWILWxjbKK0utTeoA4A/kMnXmJD5e1PuG99SZk/AHBubGRCQSQVV7tg/TNA3D6H2TJF32+pO0qKiIRYsWccYZZ2Ca5ufe+RRCCCHELhUVFcyfPz8tz1VbW8u8efO4/vrrqaysTMtzVlRUpOV5BqPBfgMDDuybGGJgyLw8fTS3m86Na+AzhSg9FqWrdgv+0eNtzCwzmYaBHo31G9fjCQw9hYYU0a0U3LoTI5HCSKRoXLauR6x+0Sf4q4bIQZYWS8aSTDxjJqueXdhj3JnlZvwpM0DOsbRctKv/zy6AZKz3+RvCXjJ/2jvZuT6+c+PF/N9tD/QopE+dOYnv3HjxgPRDBzjjjDOYN28eFRUVTJw4keXLl/O73/1uQNsX7nUR/X/+538466yzUBQFRVEoLe3/bo2uy3YuIYQQYjePx5P2ImllZaUUXr+AwX4DAw7smxhiYMi8PD1MwyDe0tSjgP6ZILG2ZrJKh6KocmiiZRQFd1EByVCInFEjcGRlgWlipFKENtfgyPKCvB+Wi7Z29BtLhMJ9fw+JAdWxrYlYMMzh/3M625dtJBYMExheStHooax86j1mXnay3SlmnPzS/H5jDrcTT87AtLgQ/cv2+8gvzOtzNbrb4yJQ3P97JvasoCTA939+BcG2TqJdUbzZXvyB3AEroAP88Y9/5MYbb+Sqq66iqamJ8vJyvvOd7/Czn/1swK6510X0m2++mQsuuIBNmzZx5plnct9995GXl5fG1IQQQggh0ktuYIgDkczL08M0dFLhUL/xVLgL0zCkiG4hRVXxlBThys2lfdUaTNNEVTX0eJy8ieNw5uagKPJ+WC27rJCmfmJufzaosprTatnF+TSsqcXhclA6sQojlcKZ5SYVT2DqBopDszvFjONwO5hw5CTWvNu7xcWMM2bilN0alissC/Dt67/Jb3/4p1590S/54dfw5cqNjX2Rnesb0KL5f8vJyeH3v/89v//97y275j41xho3bhzjxo3jpptu4qtf/SpZWVn7lMwvfvELnnzySdatW4fX6+Xwww/nV7/6FWPHju1+TCwW4wc/+AGPP/448Xick046iXvuuYeSkpLux9TV1XHllVfy1ltvkZ2dzcUXX8wvfvELHA7pAyaEEEIIIQ486Z6XQwbOzRUVxemCeN9b8FWnS4qDFjMNA1XViLa3UzTjYBKdXZi6jivPT6IjCIYhq55t4C3KR/O40PtoR1E6YxLqYPvezgCeHC/lU0bw7h+f6dEXPSs/h+orTkORGrrlIsEIow8dS04glxWvLSUeiZPl9zHjjJk43E7ikRjgtzvNjOJ0Ohk5oZKfP3ADLz72GnWbdlAytIjTLjyRguIA/nx5P8SepeWn20033ZSOp+Gdd95h7ty5HHrooaRSKf73f/+XE088kTVr1uDz7bqbcc011/DCCy/wr3/9C7/fz3e/+13mzJnD+++/D+zaonraaadRWlrKBx98QH19Pd/85jdxOp38/Oc/T0ueQgghhBBCDEbpmpdD5s3NVU3DW1RKqKvvg+A8hSWoqlSirJaKxXFkZbHzzXd3Fc3/I2dkFc6cHKTZs/U6Nm1n1BlHUfvGYmJtQQBUh0bpjEnosThGQg5MtJwJyx57q9fBopH2EGteWMRB5x1lU2KZK9wR5pk7n2TUIaM55crTUR0ayXiSla8vp3bVVi7+9bfsTjEj5RXkkVeQxzevPp9IJIrH68UfyLE7LbGf2Osi+rRp075w0/1ly5Z9oce9/PLLPb6+//77KS4uZunSpcyePZtgMMjf/vY3Hn30UY499lgA7rvvPsaPH8+iRYuYOXMmr776KmvWrOH111+npKSEgw46iNtuu42f/OQn3HzzzbhcsmVGCCGEEEIcOAZiXg6ZNzc3DQPD0PEUlRJrbugR8xSXYegpObjVBppTo2npil7joc01uAP5aFmy/d5qrmwvW9/4kIpjDsWZ5cHUDVSHRtMnGwltrScwfoTdKWaczoY2jFTfZ17Ur97KVGO2xRmJ3MJcME02LdnApiUbesRUTcWTLZ9ddsrJzyEnX4rn4svZ6yL62WefncY0+hYM7rqrHQgEAFi6dCnJZJLjjz+++zHjxo2joqKChQsXMnPmTBYuXMjkyZN7bCE96aSTuPLKK1m9ejXTpk3rdZ14PE48Hu/+urOz79UnQgghhBBCDDZWzMvhwJ+bm7pOrHEnmjeL7OGjMeIxUEB1eUh0tJIMBXH6clCkVYVlTCBUU9dvvHPjZooCchCc1XIqShnuz6blk020rd+KqRt4i/IZUj2FgnFVKJrcaLJaIhrvP2jSb4FdDBx3lpvKKVXUrqzpFZty3DTcXrcNWQkh9sVezwDTuVW0L4ZhcPXVVzNr1iwmTZoEQENDAy6Xq9dBSSUlJTQ0NHQ/5rOT9N3x3bG+/OIXv+CWW25J899ACCGEEEKIgTfQ83LIkLm5qqBoGon2VhLtrbt6oGNiJHe1pnBk54KsQreUmUqhR6L9xlPRKKZp9BsXA6f2tQ+7W7kARJvb2fTsO4w7/0SQG02WC1SW9BvzFfrRnPKeWM1U4PTvnsWO9dvJK8sHwwRFob2xnSFjhpCI7+HGhxBiUBq0R5nPnTuXVatW8fjjjw/4ta677jqCwWD3P9u2bRvwawohhBBCCLG/yIi5uQmu/MLuL41koruADuDOL7AmD/EpTcNVEOg37M7zo2rSp95qkeb2HgX0z9r2zjKQnuiWM1I6ZZOr+oxNPO0wORTZDimDSCiKvySP1e+sZMFjb7Nx8XoCZQEiwQiqOmjLcUKIfqTldqSqqnvsDajrX27r0He/+12ef/55FixYwNChQ7vHS0tLSSQSdHR09Fjx0tjYSGlpafdjFi9e3OP5Ghsbu2N9cbvduN2ylUYIIYQQQuzf0j0vhwyam5smCuDy55MItvcIufICuw7sM+UQS0uZJr4hZXRu2ISZSvUK+8ePxTDkPbFaqG7XLpKcYSUExlWhOR2EG1ppWb2JcENLr8MtxcBr395MxSFjyBtaRM37q4h1RsivLGHsCdOp/2QLecOK7E4x45hAZ3MHT/76n5j/+ZzasnwTHz7zARfcdBGK3NgQYr+TliL6U0891ePrZDLJ8uXLeeCBB77UVkzTNPne977HU089xdtvv01VVc87qdOnT8fpdPLGG29w7rnnArB+/Xrq6uqorq4GoLq6mnnz5tHU1ERxcTEAr732Grm5uUyYMGFf/pp9amxs7O4POVjU1tb2+Pdg4vf7e23pFUIIIYQQ6ZGueTnsn3PzfaE4HOjJBJrHS3ZegGRXCBRw+nJIRSOYuo4iq54tpQDR1jZKjqymbflKEh27fu9yZGWRP3USyc4Q7qLBczhtpnDn+hh11tFEmtqoX/QJqXic3IoyRp15NPUfrZHDd22QP7SIN3/zT4pGD2HSmdU4vW46G9pY+cS7aC4HqkM+uyxnwnN/eLq7gL5bKpHihT8+zddu+aZNiYlQRxfBtk6CbZ3k5GXjD+TiD+TanZbYD6SliH7WWWf1GvvKV77CxIkT+cc//sHll1/+hZ5n7ty5PProozzzzDPk5OR090n0+/14vV78fj+XX3451157LYFAgNzcXL73ve9RXV3NzJkzATjxxBOZMGECF110Eb/+9a9paGjghhtuYO7cuWlf0dLY2Mg3LvomycTg7GU1b948u1Poxely8/BDD0ohXQghhBBiAKRrXg7739x8XymKgju/gM5N6zB1HUeWDzCJt7agOjRyRo6T4qDVTIjt2El481byJo9Hc7kwjV090IMbNhFvbaP06CNtTjLz5I0axpaX3qdre1P3WMembQRrdu7qia5JmwqrOdxOhh48mu3LNpKMJXBleQg1tRPrCHPYZSejyntiuVB7qN8DX9sb2olHBmcd6UDX2tjGm0+/y7CRQwAId4ZZ+NoSjjnzCIqHyI4NsWcDerrEzJkzueKKK77w4++9914Ajj766B7j9913H5dccgkAd955J6qqcu655xKPxznppJO45557uh+raRrPP/88V155JdXV1fh8Pi6++GJuvfXWff77/LdgMEgyESc64igMjz/tz3+gUWNB2PIOwWBQiuhCCCGEEBb6svNy2P/m5umgudzkjhxHrKWBREcboOAuKMRTWILmGlxF/4yggCvPT3D9JpreW9Qr7N5Dv3QxcOLBLrp2NJM3ciiBccNRHQ7Cja00r9zIjg8+ZvhJ1XanmHE0l5ORsycz/pRDaVq/jUhbiJGzJ5NbGiDSHkKVg0Utl0r0bkH1WXrqy7dXE/sm0hWhduM2ujq7uPumv5GIJ9AcGrNOmsHO2gbcXresSBd7NGCfpNFolLvuuoshQ4Z84T/zRXqneTwe7r77bu6+++5+H1NZWcmLL774ha+7rwyPH8NX+PkPFEIIIYQQwmJ7My+H/Xduvq80t5ussmF4Cnf1bFedThQ5AM4Wpgm+YUMJbtwC/1mB/ln+8WNsyEoEt+5kzJxjCTe0Em3rRFEUTNNkxKmzaFy6Vs4OsEG8K4KeSPH6XY9379bY+OYKfIW5zPqfM9CTey7oivTzF+aiOjSMPorlWX4fHp/HhqwyW1cwwkfvrOCNpxZ0j+kpnQUvLKQrGOaia86TIvp+JhQKceONN/LUU0/R1NTEtGnT+MMf/sChhx46INdLSxE9Pz+/x9ZG0zQJhUJkZWXx8MMPp+MSQgghhBBCiM8h8/J9pycSJDs7iLe3AOAOFOHK9aM6pfe29Uxibe0UHTKNtpWr0GO72h8omkbe+LGkQl04s30255h58kYNI9EZxpWTRcvqzaRiCXIrSlE0jdLDJstNJxs43S7e/t0TYJoUjR6CM8tDqKGNUGM7q55bxNSvSNsjq6kOjSPPP4pIZ4SqqSNIJVNoDo0NH65j6IQKNNkdYLl4LM7bz73fZ2zZeys578pzLM7owBLsCNHW2k6os4uc3GwCBfn483IG9Jrf+ta3WLVqFQ899BDl5eU8/PDDHH/88axZs+ZLLx75ItLyXXvnnXf2mKyrqkpRURGHHXYY+fn56biEEEIIIYQQ4nPIvHzf6IkEXTUb0OOx7rHIjlrirV6yh49Gc0kh3UqKohDdUY8ei5E/aQKqywWYmIZJ19Za4u0deEqK7U4z42huJx2btqMoUDJtHKgKsbZOtr25hMoTDgNVzg6wWrC+jbLJVYyYNYmm9XVEg2FGzp5CViCHj/+9ADPVeyeHGFiKqjDhyEm89eDr/Ovnj2EaJqpD46Djp1ExoRLTlPfEatFwDD2lM/u0ao4/92icTieGrvPey4t46fE3CLZ22p3ifqthZxM3/+TXfLBgSffY4bMP5eZf/ZjS8oH5OR2NRnniiSd45plnmD17NgA333wzzz33HPfeey+333572q+ZliL67p6IQgghhBBCCPvIvHzvmaZJsrOjRwF9Nz0WJdXViRaQFo6WUlUc2Vm4C/Jx5eWS6OjE1A1cgTx8FcPQY3EUVbM7y4yjxxIUThpJ24atbH7xPcyUjq+0gCFHHERoWyMFubI7wGqqQ6V0fAXv3f1MdyuuusXr8eZlc+g3T8DUpWBrtVQixat/eZGtH9d0jxkpnWUvf4QJzDxbzg6wmtfn4X//eA3N9a384br/o7Wxjdz8HE77+onMu/96OYB3LwU7Qr0K6AAfLFjCzT/5Nb/6400DsiI9lUqh6zoeT8/WSF6vl/feey/t1wNIy/8hL7/8co8E7777bg466CC+/vWv097eno5LCCGEEEIIIT6HzMv3nqmnulu49CXe1oyRkr7CVlJVlZwRVahuNzvfWEDLR8tpXf4x9W+8Q6y5hcJDD0ZxShHdaoqisu2dpbSs3IT5n37P4YZWNj79NlnFAWmJboOc4jyW/+PtXmdZRDu6WP/6MlSXtA6xmqEbPQron/Xxa8swdPlGsZovx8fmNVv5y88fpLWxDYDO9hCP3f0Ebz7zLtl52TZnuH9qa23vVUDf7YMFS2hrHZj5Z05ODtXV1dx2223s3LkTXdd5+OGHWbhwIfX19QNyzbQU0X/0ox/R2blr28Mnn3zCtddey6mnnkpNTQ3XXnttOi4hhBBCCCGE+BwyLx9I0qLCaqauY+o6bctX9jqssqumlkRHR/chisI6eiJBvL2ToqljGH32MYw++xgqjz8MTyCXnQtXosi3iuU6trVg9LPavHFtLYbe+3BLMbC62rv6jRm6QSIatzAbARCNRHn6vhf6jL35zLvynuylUGf//68DdH1OfF889NBDmKbJkCFDcLvd3HXXXXzta19DHaCzOdJyO7KmpoYJEyYA8MQTT3DGGWfw85//nGXLlnHqqaem4xJCCCGEEEKIzyHz8r2nOpy4A4VEdtT1GXcHClEdsprTSoZpEtqytd9454bNFObng6ffh4gBENrezOg5x9L88QY2Pfs2pmHiCfgZcvhUOrZsxzRkha3VkvEEAOVTRzLqqCk43E4ibZ2sfPp9Iq0haediA2+Ot/+gouD0yBkbVusKhonHEn3GTMOkuaGNoSPSfxjlgS4nd88r+LM/J74vRo4cyTvvvEM4HKazs5OysjLOP/98RowYMSDXS0tp3uVyEYlEAHj99dc58cQTAQgEAt0rYYQQQgghhBADS+bl+8aVm4fm6V340LxZOHJybcgowxkGerR3j/rdUrE4IAVbq+WPHErtax/Str62u2Aeawuy+fkF5I+u6HG4sbBGYHgpx/7oPIZNH42iKpimieJ0MPPyU5l63mw0t9PuFDOOx+ehsKKoz9jIg0fhcMpNWau5Puf7IMu3hxsfol+BgnwOn31on7HDZx9KoGDgD7b3+XyUlZXR3t7OK6+8wllnnTUg10lLEf2II47g2muv5bbbbmPx4sWcdtppAGzYsIGhQ4em4xJCCCGEEEKIzyHz8n2jOl1kDx+Nb+hwHFk+HFk+fEOHkz18FJpTVg1aTdU03IWBfuPufD+KJj3RrZaMxoi177opl1UcIHtIMZp71/fHzkWfIP1crOdwO1AcGr6CXLZ+sIbVzy0kuK0ZV5ab4nEVsovGBolYgq/89AIKhvY8kHrouGGcdMWpJBJ9r4gWAycrJ4vKMcP6jOUX5pGbn/7DLzOBPy+Hm3/1416F9MNnH8rNv/7xgBwqutsrr7zCyy+/TE1NDa+99hrHHHMM48aN49JLLx2Q66Xlk/RPf/oTV111Ff/+97+59957GTJk1/aHl156iZNPPjkdlxBCCCGEEEJ8DpmX7zvN5UILFOLMzQOQ4pONTBOyhpTTuWEzRjLZK543fixI6xDLddbWExg7nKIpo+mqb0aPJyidPp5ULEHdW0vkPbGBoqq0bNjOx0+82z3WtH47G99cwdHXnAtydoDlnG4nr8x/kWMvPgFfXjbhji6yAzm0bmvh3X+8zZEXHG13ihknOzeLuTdfzrzv/Y5g66e787w+D9f86kq82dIbbG+Vlhfzqz/eRFtrO12dXWTnZhMoyB/QAjpAMBjkuuuuY/v27QQCAc4991zmzZuH0zkwu2/SMiOsqKjg+eef7zV+5513puPphRBCCCGEEF+AzMvTR4rn9lMUSCUSlMw+nLblK4m3tQPgyPYRmDoZA1BVWfVstZyhJSTDUdb/67Ue476yQkadeTSmtNixnJHUWfnke7h8HoZOG4Ury0OwvpWG1VtZ/o+3mXHpSXanmHFSiRSHf+VIgo0dvPXQ60Q6wviL8zji/KMYefDofg+CFQMn1NHFM/e/yP/+8Rq2bd5Bzbo6hlSVMWpiFS88+hpnX3IqeQG/3Wnut/x5OQNeNP9v5513Huedd55l15OZoRBCCCGEEEKIQUnTVIyUTsGhB2OmUmCaKA4NPZlCczhk1bMNvIV5bHrm7V7j4foWOrfV4xtS2PsPiQHVsqWesSdMJ6+imLrF62jf1kxgeAlHzj2bVc99QCreeyeHGFiqprLpow18+NQH3WORzgj/mvcYJ195utwAtEFXZ4T3X13M+68uZuzUUVSNrWDRa0uYf/sDABx12uGUV5banKUYzKSILoT40hobGwkGg3an0UNtbW2Pfw82fr+fkpISu9MQQgghxBdg6DqmngJA0Ryo0nfbFoqmoWgOFD1B86IlJIO7tt9rXg+BqZNQsrJweNw2Z5l52jfW9Rtr/ngDJQeNhSw5oM9KXr+PcHMHi/76YvdYe20jtYvWMvPyU6RPvQ0URWHxM4v6jL394OsMn3KFxRmJz67+X//xJtZ/vKlHXE/pVqck9jNSRBdCfCmNjY1846JvkkzE7U6lT/PmzbM7hT45XW4efuhBKaQLIYQQg5hpmhiJOJGG7SSDHYCC059PVmk5mlt6pVrNMAwwTRrfW7RrFfp/6NEYzYs+ovSoWZjJJLjk0FcrJcOxfmN6PImJFGyt5ivI4b17PsKbl82w6aNx+Tx01rexffkm1ry4eFchXVgq2NSB2U8v+lg4RiwUsTgjkZPnIycvm1BHV6+Y0+WgsLT/g6yFACmiCyG+pGAwSDIRJzriKAyP9Av7ItRYELa8QzAYlCK6EEIIMYgZiQSdm9Zi6rtXo5kkg210dnWSO3o8mktWPVvJ1HXC23f2KKB/VsfaDQQOnmJxViK3spTGpWv6jPnKCmXRsw3atjYy6fRqvIEcti5cQywYJjC8hCOuPJM1Ly1GT/b9PSQGjtO954MNNafscLKax+vh0h99nbuun98rdv6V5+B0DcxhlOLAIUV0IcReMTx+DJ/0OxRCCCHEgcE0DeLtzZ8poH8mpqdItLfiKS5DkQqhpRL/OUy0z1gwCP2s9BQDR3M58RbmEW3p6BUrnznZ+oQE3vwc2uuaWPXcwu6xUGM725ZupPrbp6Jo8rlltez8HLw5XqKhaK9YwdBCPNnS8shq0XCUcCjCzX/5CU/f/wLbNu2kZGgRZ150MrFYnHg8YXeKYpDb6yL6nDlzvvBjn3zyyb29jBBCCCGEEGIPZF6eHmZKJ9nZ/5kvic4O3AXFKA5Zh2QZRUHz9V9ocni9KIpqYUICINoaZPiJ1XTW1aNoGqpDIxmOkVtZQuvarXiL8u1OMeN4crLY9PbHvcaNlM7q5xdRfcVpNmSV2UwFzv7hV/jnbY/26LXt9nk465o5gByKbLVQMMzffvkwF//wAr7104tIxlM43A7qNu3g9z/9M9fddTVDq8rtTtMWpnng//+Yjr/jXs8A/X5p4yCEEEIIIYTdZF6eJqqCova/vV7RHHI4nw1yhlfStaXvg+Nzx4zElPfEcnlV5aQSSRweN00r1qPHE+QOL0dzOimZPh7VKTearNa6pb7fWMe2ZvR40sJsBIAC1K6u5bLffYf1i9bSur2FstHljDhoJMteXcphZ1bbnWLGcboc3PXML2lrauf/bn+A7Vt2UlxeyNmXnsZdz/yS9uYOu1O0nNO5q4VNJBLB6z2wd0dEIrvOIdj9d94be/3T7b777tvriwohhBBCCCHSQ+bl6aEoKu6CIlKR3geOAbgDhSiqFGytpCgKiqZReOjBtC5d0eOQvtwxI3H5/aiarES3mmma7PzgY1zZWQw7+hAAEl0Rat9YTOXxh/V7mKIYOJ/72SQ3myzX1d7FB/9cwAf/XED1uUcw8pDRbF9Tx+t/ewWAqcdOsznDzFM6pJhlH6zkjzf8pXusvbmDX139By783leYdfIMG7Ozh6Zp5OXl0dTUBEBWVtYB17bONE0ikQhNTU3k5eWhaXt/HoHcIhZCiP1MY2MjwWD/283tUFtb2+Pfg4nf75cDXYUQQnwuU9fBNHH680kGe/bhduUFMA0DUzdQHFK0tYqqaeimSVfddooOm46eSGIaBo4sL5Ed9eixGJpbDnu1WjISp2zGJOoXr2LDE2+AaeLOy6Hi6EMIbW8iMLbS7hQzTsGIsl1Ln/voVhCoKsXpcVmeU6ZLRhMUVRZz1NePJdzRRUtdM+VjhlI5aThvPPBajxYvwhod7Z3c/5vH+oz98/+eZvpRB1mb0CBRWloK0F1IP1Dl5eV1/133VtqK6P/+97/55z//SV1dHYlEz2b8y5YtS9dlhBAiozU2NvKNi75JMhG3O5U+zZs3z+4UenG63Dz80INSSBdCZAyZl+8lVSHe3oozOwd3XoBkVyeg4MzOQY9FSXa04fJLr2erhbftINbYRLIzhG9IGWgqXVu2kgh2kgx1UXx45q0ctJvq0Nj0zNvEO0LdY/GOEBuffoux552A9Hq2nupyMPmsWXzy9Ps9xh1uJwdfcIzsorFBXlk+J377FJ745T+JdX16uGhukZ+zrpmDN+fAbp0xGHUFuwgF+95tlkykaG1oY8jwMouzsp+iKJSVlVFcXEwyeWC2fnI6nfu0An23tBTR77rrLq6//nouueQSnnnmGS699FI2b97MkiVLmDt3bjouIYQQAggGgyQTcaIjjsLwSA/cz6PGgrDlHYLBoBTRhRAZQeble0/VHHiKSujauglUFYfXB0C8rQVMg5yqMahp+AVMfHGmbpAIBgkcNBlFVYns2ImpG/iGDcE/bgzta9bu2kEgLJXoDGOaJqPnHIs714ehGyiKQuPydWx7ZymjzznG7hQz0pBpowgML2Hj2x8TC4YpHFFO1awJaC6n3NawgappPHvnUz0K6ACdzUHeuP81zvnRV23KLHN93s9wzZnZP+M1TUtLoflAlpYi+j333MP8+fP52te+xv3338+Pf/xjRowYwc9+9jPa2trScQkhepGWFl+OtLQ4sBgeP4av0O40hBBCDDIyL983Dq8Pd0ER8dZmUuFPV9m6C0vQDvADtwYjE5PcUSPo3LSFaMOn28xjLa04c7IpOGgqpi79t60W7Qgy9tzjqH1jMZ21uw60dGZ7GXbUIeRUlGHqUrK1nGmybcl6Nry5nKEHjSKnyE+wvo03f/MvjrjqTHxFsvjGapFgmFBrZ5+xnRu2k4gOzp3FBzJfThZFZQU017f2inl9XvIL86xPSuxX0lJEr6ur4/DDDwfA6/USCu2acF500UXMnDmTP/3pT+m4jBDdpKXFlyctLYQQQogDn8zL943qdOItGYI7UEwy1AGKgjPHj+pwojrkOCmrmYaBaZhEG5pw5mTjLStBUVRiLa3EW9uINbfgGyH9t60WGFnBun+8SiIU7h5LdkXZ8sK7jJ5zLGqGr+a0gx5PsuaFDzFNk5oPVveIrXzqPWZccqJNmWWu/16B/t+S8QOzbcZgllfo58qbLuMX37+TZCLVPa5qKlf+7BKyfB4bsxP7g7TMBEtLS2lra6OyspKKigoWLVrE1KlTqampwTTlLrRIP2lp8eVISwshhBAiM8i8fN+pDgeqw4FDVp7bTlVVuuq2UThjOqaeomvrNkxdJ2tIOXkTxtK2ai3ZFUPtTjPjhJvaehTQP2v7gmWMOfc4izMSrVsa+v2Mb91Sj55M9RkTAyc7PwcUBfp4X5xuJy6vHPZqtYa6RoZUlfLLh2/irefeo3Z9HaUVpZwwZza+XB+NO1vIk9XoYg/SUkQ/9thjefbZZ5k2bRqXXnop11xzDf/+97/56KOPmDNnTjouIUSfpKWFEEJkBmnh9eVJG6/MJPNycSAxgezhFXSu30SsuaV7PNERxJHlpXDG9F1FKmGp0LaGfmPRlg5MQ27YWc2UrueDjsOlMfHISZSNLmfkwaMBME2TT976GEVRcLqcNmeYeTw+DzVr67jrtr/w24dvQTEVVE3hpu/8hnMuPpWxU0fZnaIY5NJSRJ8/fz6GsasX3dy5cykoKOCDDz7gzDPP5Dvf+U46LiGEEEKIDCUtvPaOtPHKTDIvFwcSzeHA1I0eBfTdUpEo0Z0N5I4bbUNmmc2dl9NvzOF1g9zXsFzhyPJ+Y3lDi3B4ZNWz1TSng6O/cRxrP1jDw9ffT7iji7ySPI44/2gqJlZK2yMbKCj83+0PQNzkqb++QPGQQtqbO4gEw/z9Vw/zy0dusjvFjNXW2k5jfTObN26lqLiAyqqhFJcWoaqq3an1kJYi+vbt2xk2bFj31xdccAEXXHABpmmybds2Kioq0nEZIYQQQmQgaeH15Ukbr8wl83JxIDFSKcK1df3Gu7ZtJ7uqEs0pKzqtlDdyGNvfWYZp9D7UtfSQCWhuKdhazelxMvq4aWx8Y3mPcdWhcfAFx+CUXs+WU1SF9/6xgBWvLu0e62js4Pm7nubYi09gynEH2ZdchgqHwoyfPoZZJx3GG08tYOWi1RQPKeTSH32d9R9vor2lg/LKUrvTzDiN9c389P/dytIPV3aP5eX7+fNDv2HcxNGDqpCeliJ6VVUV9fX1FBcX9xhva2ujqqoKXdfTcRkhhBBCZDBp4SXE55N5uTiQ9FWk7fUY6fVvuVhbkNHnHMOmZ9/B+Eyv7fwxleSNGoYeT4BPzhSwUqwzStWsiRSPGcb6Vz8i1hmmYGQ5Y0+YTlttA64cL26P2+40M0oylmTFa8v6jL33z3cYO3P8rr7pwjJOl4vJMybw2x/8qftnR+OOZj5ZvJavzZ2DN0tuNlktGo1x9+/+3qOADtDRHuSKC3/Av176G2VDBs+CoLQU0U3TROmjF11XVxcej/xPKIQQQgghIBaLUVfX/6pSu1VUVOz3c1eZl+87Q09hJpMkw10AOLNzUBxOVE223ltO08gaWk5kZwM5o6rIKi8DIN7eQcfqdWQNKUfRBs8KtUwR3LoTTJOJF51GrD1EKhrDV1pAoivKqgeeZ8q3zrY7xYyjJ5J0bG9m7UuLqThkLC6fh+DOVt790zMccdUZmIbcQLVaR2N7n4eKAiSiCaKhiMUZCc2h8tifnujz5uu///ochx59sA1ZZba2lnaef+rVPmOdwRBbNtUeOEX0a6+9FgBFUbjxxhvJysrqjum6zocffshBBx20TwkKIYQQg4UcbvnlyMGW4r/V1dVxxRVX2J1Gv+bPn8+YMWPsTmOvyLw8PYxUilhzA7HmngcneorL8RQWoTqkbYiVTF3HmZtL+YnHYsTjGIkkpmniCeQz5PijMUzzC61WF+mVP2oYqUiczh1N+IrzceZkEWkP4XS7KJo8CmUQbb3PFO7cLN75w1OYhsG6Vz/qEfv43+9yyEXH25RZ5nJnufH4PFTPOYLiqhKS8SROt4tta2pZ/OxCHHKwqOWiXTE620N9xpLxJG0tHQypKrM4q8wWjyVIfWZH039rrG+2MJvPt09F9OXLd/XbMk2TTz75BJfr095nLpeLqVOn8sMf/nDfMhRCCCEGATnc8suTgy3Ff6uoqGD+/Plpea7a2lrmzZvH9ddfT2VlZVqec3/uFy7z8vTQo5FeBXSAWNNOnNk5qNlS9LCSoqoomkqyo5PWFZ9gxHf9DFY0jbzxY/CWl0EfOy/EwHLn5eD0eUnF4jQsXkMqniBv5FCyiwOUHzYJVHlPrNZW09DvDaWm9dvQE/0XqcTAyM7PYc5Pz+edh9/krYde7x4fdegYzrvh67h90l7HasrnfDZpsrPJclk+L3n5fjra+16oNmbcCIsz2rN9KqK/9dZbAFx66aX84Q9/IDc3Ny1JCSGEEIONHG755cjBlqIvHo8n7Su9Kysr99vV4+kk8/J9Z+g60eb6fuOx5gY0b5a0dbGSomAmUzQvXtqjLYKp67SvWosjJxt3IN/GBDOUadL8ySYaP1rTPdS5dScNi1cz7oKTUGR3gOVS8eQe44Yu74nlFIW3HnyN+o07ewxvWrIBl9vFsZeeYFNimSsr20tBSYDWxjYURcHlcZGIJTBNE6/PQ16B/I5ntaKSAq669lJ+fuPve8UmTB5L6SBq5QJp6ol+3333df/39u3bARg6dGg6nloIIYQYVORwSyHEYCbz8n1gGJjJ/gtRRirZb39bMUBMk6667f2+7p0bNlNw6DSLkxJ6ItmjgL5bIhRmx/srGHbMITZkldkKRvbfgiKnNB+HKy2lH/ElxMOxXgX03dZ+sJojv3a0tQkJsnwerrjhm9Ru2MbQEUMIdXSR7ffRvLOF3PwcnG7ZbWY1TdM46fRjMAyTe373dzqDITRN4/hTj+IH/3slhUUBu1PsIS17FQzD4NZbb8Xv91NZWUllZSV5eXncdtttGHIXWgghhBBCCEvIvHzvKZqGI7v/FfzO7Fzp9Ww10yQV6rt/LUCyqwsMubFhtbZ1W/uPrd+KsYf+tmJgOFxOKmaM7TWuKAoHfWU2qlN20Fgt3NHVb8w0TBLRhIXZCIBwVxS3200iliSZSOLxujF0g1B7F4VlBcSjg7Nt54EuP5DH+Redxb9e+htPvnY/z739MLf86keUlhfbnVovabkdef311/O3v/2NX/7yl8yaNQuA9957j5tvvplYLDYo+7QKIYQQQghxoJF5+d5TVBVPYTHxjjbc/rzugnqqq5N4sB13oFCK6BZTVBVnXh7Rxr4PFnNmZ6NIex3L7ak1iKkbIPc1LGeaJhPPqKZwZDkb31xBLBgmf3gJk86oxunzYMouGsv58rL7jSmqgsvr6jcuBkYqpRMNR+nsCPGnn/2VZDyJpmlUn3AI0a4oHo+8J3Zpbmxl3ZqNLP5gOUOGlTL72GqKNQ2PZ3CdHZCWIvoDDzzAX//6V84888zusSlTpjBkyBCuuuoqmawLIYQQQghhAZmX7xvF6SR35FiiDTsI19WAAs7cPHJHjkN1Da5f5DKBaRhkDxtC58bN0MdOirwJY6XFjg3yR1f02c4FwD9iCIqseracqqp8cO9zFIws47DLT0ZVVRKRGB89/DojjpzMkGkj7U4x4yiKQvmYobTtbGXCkZPICeTQ3tDG2vdWM+rQMXKzyQZOl4Mlby/nzWfe7R7TdZ33Xv6QrlCEi64+z8bsMtf2up1862vXsHP7pwe7/27evfzhL/M47IjpuFyD5+ZGWorobW1tjBs3rtf4uHHjaGtrS8clhBCDjBrtsDuF/Ya8VkIIIawi8/J9YyZThDavw9T1/wxAMthOqitE7ujxaFJIt5SqaURDXZQcPoPW5Z/gzMlGURUSwRC5Y0aSisZw5ubYnWbGcef68I8oJ7ilZ79n1elg2FHTpThog2hnhKEHj8ZXmMvKJ94j1hkmMLyUg75yFBveXE7ZxOF2p5hxkvEkJ33nVMIdXSx76SPqVm2lqKKY8392IYqikJK2R5ZLJZK888IHfcZWvP8JF1x5jsUZia5QmF/efBc7tzcwYnQlI0ZVEuwIsWzxSq79n5/x9BsPMmRY/2c+WC0tRfSpU6fypz/9ibvuuqvH+J/+9CemTp2ajksIIQYZb80Cu1MQQghhkcbGRoLBoN1p9FBbW9vj34OJ3++npKTElmvLvHzvmaZBvL350wL6Z2N6ikRHG56iUhRFsSG7zGSaJq7cbGItbRRMn0pk2w4MXScwdSKmYeLwejClJ7rl9GSK4SdUE6zZSePydeixOLmVZZQdNplUPIE2yLbfZwI9kSQRibH6/kXdY531bWz7aD0zv3WqnIlhg6w8Hxs/XMfrf3+le6xlWzPrFq7hrGvPZcgYv43ZZaZoJI6e6v0zfrfO9v7P4BADo72tgy0ba/nd/93Gjm31rFm5nrETRnHJdy7g6X++xPq1mw68Ivqvf/1rTjvtNF5//XWqq6sBWLhwIdu2bePFF19MxyWEEINMtGo2hjfP7jT2C2q0Q246CCH2W42NjXzjom+STAzOw5YGY3sSp8vNww89aEshXeble89M6SQ7+79ZlAi24w4UoTjS8iuU+AIMwyAZjpIIdtK2fGX3eLhuO+6CAHkTx6FKcdAWrWtrSMUTjDjtCBRFIRGKsOXl9xl52pGYRv9FKjEwPDlZbHxzRa9xPamz5oUPmfmtU6xPKtOZJm8//EbvYcPkjb+/wjd/ebkNSWU2j3fPN/iy/f33sRcDQ9cNrr/9Gm784S9oafp0x+Sj9z3B/956NY5Bdu5JWmaARx11FBs2bODuu+9m3bp1AMyZM4errrqK8vLydFxCCDHIGN48DF+h3WkIIYQYYMFgkGQiTnTEURgeWTX1edRYELa8QzAYtKWILvPyfaAoKGr/v6wpmgayCt1SCoBp0LVla69YvLWNeEsrWsVQq9MSpknzxxsomzGJZCiy6zBRVcGd7aN+8SqGzjrI7gwzTvu2JgBUh0bpxEpcWR4661tp29pIe10TRkpuNlmtsyVIKtF3y5ZQW4hoV5R8i3PKdG6vi4mHjGX1R+t7xcorS/H6PDZkldk8Xjf3/99jPQrosOsm+i9vuYt/v/x3mzLrW1qK6HV1dQwbNqzPlUB1dXVUVFSk4zJCCCGEyGByvsAXNyCvlRze98XY/DrJvHzvqQ4HnqISumq7+ox7ikpRB9mKqAOdqSiEt+1AdTrJHl6BuyAAmKS6woS21NJVt52soUPsTjPjdNY1UHnCTGrfWEy8vRMAxaFRdsgENLcLXXo922J49QSGThvFzpVbiAbDlE2qYsKph/HxE+/a/rMpM8lN18FG1w3OuvhUujoj1G7Y1j1eMqSIS374NRszy1yJeJIP31/G5IPGc+7XTicnNxvThDdffZdXX3ibTetrGDGq0u40u6WliF5VVUV9fT3FxcU9xltbW6mqqkLvo6+gEEKIvSfFxC9GXqcDi7RFspe8/vsHmZfvG0eWD2deAAwDZ07uroNFuzpRNA2HN8vu9DKPbqI6HBTNmE5w42Y6N24GwOXPJX/KRMLbttucYGbKLitk/b9eR48nusfMlM7ORZ9QefxhKJpqY3aZqWB4CclInPfuebZ7rP6TGlw+D4dfcRqqQ24AWi07Pxun20kyngRA1VQMfdeOgNwiPy6vy870MlKovYu7bpjPV79zFoHCPFoa28kv9BONxPi/2+/niusvpryy1O40M4qeSnHZlV+nqLiAe++8n8aGZtxuFyedcSx33HMLoVDY7hR7SEsR3TTNPg/Y6erqwuOR7RBCCJFuUswSmUjOYvjiBuIsBnn9vxi7z8GQefm+UZ0uskrKibU0EW3cCYA7rwB3QRGqw2lzdhlIhZyRVTS+txDjMwXbRLCT5g8/ovTIapDioOWibcEeBfTPaliymryR0mLHaiYKK596D4/fx7hTDsWd5aa9tpkNby1j9QsfcshFx9udYsaJhWOc8K1TiEdiFA4rIhFN4M5ys2PDdoqGFaFLix3LudxOuoJh7vv1ozhdDrJzswmHIiT+83nm9XltzjDz+PNzKSwq4Fe3/LF7LB5P8Oy/X6Zu63Zu++1Pbcyut30qol977bUAKIrCjTfeSFbWp6szdF3nww8/5KCDDtqnBIUQQvQmxawvZiCKWbK6/YsZiNdJzmKwl7z+g5vMy9NDT8Tp3LIeM5nsHou1NJIItpMzciyaa8+Hkon0UhWFcEtrjwJ6N9MkuHkLgckTrU8sw0Ua2/qNxYNd0jnEBh3bmplx8YlkBXLYtOATYh1dFI4s58Trv8Hq5xdhpGQXktU8Pg/FlcW8Mv9F6jft7B4fMW0UlZOr0ByyY8NqniwPw8dWsHV9HclEivaWju5YflEeOXKwqOWSiRR/u/eRPmMrPlpFqPMAWom+fPlyYNeKl08++QSX69PtKC6Xi6lTp/LDH/5w3zIUQgjRixSz7CO7AESmUmPBfX8SI4Ua77vf9GBguLNB3beNmml5nfaCzMv3nWmaxNtbexTQdzOSCRLBdjyFJX2u9BcDw9B1Yg1N/cbjLe2YhlRsreYt6v84RFeuD6Q2aLns4jyaN+7gw/teQdVUNJeT5k072PT2xxx19RwUeU+sp8BLf34e0zA54Vsnk52fQ0djOyteW8aS5xZx3CUn2p1hxnG5nFx506X84nu/p6P10/ma1+flml9dicsjO86sFu6K0Nrc/43ZjWs3M2nqOAsz2rN9+i3hrbfeAuDSSy/lD3/4A7m5uWlJSgghhBisZBfAF2N3SwuRPn6/H6fLDVvesTuV/YbT5cbv91t6TZmX7zszlSIZbO83nuhox51fiOJIS0dM8UWoKpq3/zZEmtslZ/fZIKsoH83lRHO7yB9Tgep0EG5opXPrTkqnT0CRiq3lnF4XW99fzaEXn4jD7SQZieHNy6Z1Sz0rnnyXQ795gt0pZpxENMHko6eiqAofvbCYjsYOiiqKOOK82TRtbSIlB/BaLhqN8cAdj3PdXVezY2s9W9fXUT68jBHjKnny789z9qWnUlhaYHeaGcXldqJpWr9n9hQUD673Iy0zwPvuuy8dTyOEEEIMerILQGSakpISHn7oQYLBfV9hHY/HaWhoSENWA6O0tBS3e9/bdfj9fkpKStKQ0Zcn8/K9Z5omqP0X/xRVxTSlh62VVEXBVzGUrq11fcZzRgxH2cN7JgZGV30LEy46lXBDKy2rNpOKJcitLGXYUQfvaucirUMsF9zRykHnzeajR94g2v7pjq+yyVWMPmoqelwKtnboaOrgo+c/7P66aWsjz/3haY679ESQTTSWi3RFWbN0PT+58BZGTRxO1bjhvPvCB/z51l1zp2PPPtLmDDNPoCCfE087mpeefaNXzJedxagxw61Pag9kGYUQQgghhNijkpKStBWFJ0+enJbnESLdFFXBnRcgEum7/6YrLyArbC1m6DqJ9iB5E8bRsWZdj1jW0HIUTcPU5caG1fJGDGHnBx/Tsmpz91iksZWWTzYx/msno7qkzGA1X2Eu7939DPFQtMd4/Sc1eP0+/EOLbMosc7k8Lpa+uIRhEyo46MTp+Pw+gs1Blr20hPf/uYDRMwZPi4pM4cv2oqgKpmGyafVWNq3e2iOeF7B2F6GALJ+Xq6/7Dls21bJ+zabucW+Wl3sf+A3FpYNr8dqgmwUuWLCAM844g/LychRF4emnn+4RN02Tn/3sZ5SVleH1ejn++OPZuHFjj8e0tbVx4YUXkpubS15eHpdffjldXYO3/6YQQgghhBCDTabNyxXNgeb14fDl9Io5s3PRPF5UaeViLUUlFQ6TDHVRPOsw8ieNJ2/8WIoPn4Ez20do0xbpUW+DVDTeo4D+2fHt738sB4vaIB6K9iqg71b74TrkTbFeqLWTc374FcbNmshbD7zG47c8zKIn32PmnFkccf5RJCIxu1PMOJrTweEnzugzNu6g0Tjd0hPdDmXlJdz7wK954Ik/8ZObv8+d/3cbT712P5MOGodjkM27Blc2QDgcZurUqVx22WXMmTOnV/zXv/41d911Fw888ABVVVXceOONnHTSSaxZswaPZ1e/vAsvvJD6+npee+01kskkl156KVdccQWPPvqo1X8dIYQQQggh9kuZNi9XFAXV6cSVX4A7v4BEKIgCOHP9mCaoTtfnPodIL1WB7OEV1L+5gPC27ThzskFR6Fi/EQyDwhkHY6pSRLda27qtuHJ9lB46Ebc/G9MwUBSF5k820b6hlmGzD7Y7xYwTbu0kuziPg88/Gle2l1Q8idPrpmXzDpY//jaGtNixXG5hLhs+XMdHLyzuHmtvaOeZO57ghG+djCe7//MexMBIxpMccfJMUskUi99a1n0w9eTDJnDGRSdJn3obFRYXUFhcwLRDBveO1UFXRD/llFM45ZRT+oyZpsnvf/97brjhBs466ywAHnzwQUpKSnj66ae54IILWLt2LS+//DJLlizhkEMOAeCPf/wjp556Kr/97W8pLy9Pe85qtCPtz3kgGojXSV77L0ZeJyGEEEJ8WfvjvHxfaS43ZCvo8Sieol0tjExdx+H2ormkiG6HeFs7BQdPpXX5yl3FWlUF0yRnxPBdPYUNaediNYfXTdVJh1P31hKiLR0AqE4HZYdNwldSIIe92iBvaCGzvnM6Hz38Bq019QCoDo2RR03huJ+cj6ppNmeYeUwTlr60pM/YO4+8xahDxlickUglU9zxo7v5yZ3f54Kr5pBKpnA4NMKhCL/4/h/48Z3fsztFMcgNuiL6ntTU1NDQ0MDxxx/fPeb3+znssMNYuHAhF1xwAQsXLiQvL697og5w/PHHo6oqH374Ieecc06v543H48Tj8e6vOzs7v1Re3poFe/G3Eekgr70QQgghhPUGal4O+z433xemaWIaOrGmBlLhEACO7ByyyiswTVNah1jMMAyiDY24CwsoP+4o4m3tmLqOuyBAMhymfcUqSo4+wu40M07+mArWPvISqein36dGMsWO91ZQdfIsHNISwXKenCze/dPTdDV/egi4kdLZ+MZynB4XI4+aamN2mSnY1NG90vm/JaJxov203xEDR0/p/PzBG1n90Vr+dNNfCbZ24sv1cdJ5x3D7/f9La2Ob3SmKQW6/KqI3NDQA9DrYqqSkpDvW0NBAcXFxj7jD4SAQCHQ/5r/94he/4JZbbtnrvKJVszG8eXv95zOFGu1Ie9FbXvsvZiBeeyGEEEJkroGal8O+z833hZGI07lpbY/VzamuEKFN68gdPQHN7bYlr0ylqio5I6tIBjvZ+frbPWK+YUMJTJ8KcmPDcuGG1h4F9M/auWglORUlOH0WJ5Xhwm2ddDUH0ZwOyiYPx5XlIVjfSuvmeja+uYKKQ8fizc2yO82M8nn9tTWH7A6wWkFJPq8+8TZP/vX57rFwZ5gn//o8LQ1tfPWKs2zMTuwP9qsi+kC57rrruPbaa7u/7uzsZNiwYV/4zxvePAzf4DoxNlPIay+EEEIIcWDZ17n53jINg1hrU5/tQUxDJ97ejLekHEVRBzwX8R+KguZ207Rqba9QeNt2vCVFsjvABuGdzf3G4h2hXW12hKWCO1sZccQkyiZXsX35JsJtIYrHDGPCKTP4+Il30aXXs+V8+dn48nyEO8K9YiVVpbiz5Kas1SLhGM8/9GqfsXdfWMiZF51scUZif7NfFdFLS0sBaGxspKysrHu8sbGRgw46qPsxTU1NPf5cKpWira2t+8//N7fbjVtWlQghhBCDmhoLfv6DBCCvlRh4AzUvB/vm5qaukwr13zomGerEU1iK4pAiulVM0yS0ZWu/8eDGzRQX5FuXkADAW9T/a+7Kydp1IqywVEFVKUZS5/17n+sea1xTiyvLzWGXnyItdmzgcDo44/+dw7JXlnLIaTPw+DyEO7pY8sKHHHneUTjd+1U57oDQFQyTiCe6v3a5XSQTyV2t3EyTlsY2ho0cYmOGYrDbr75rq6qqKC0t5Y033uienHd2dvLhhx9y5ZVXAlBdXU1HRwdLly5l+vTpALz55psYhsFhhx1mV+pCCCGE2Et+vx+nyw1b3rE7lf2K0+XG7/fbnYY4QB2Q83JVQXE4IR7rO6w5pHWIDfRo3+8HgB6LY8qqZ8vlVpShOh0YfaxuLquegurar8oMBwSX18OqZz7oNZ6IxFn78hIOu/QkG7LKbLFIlIKhhUyYNZHX/voSHY0dFFUUM/vrx5CVl00sHCenwO4sM4vL7cST5eHsS09l0qHjuw8W3bSmhif+8hxZPq/dKYpBbtD9dOvq6mLTpk3dX9fU1LBixQoCgQAVFRVcffXV3H777YwePZqqqipuvPFGysvLOfvsswEYP348J598Mt/+9rf585//TDKZ5Lvf/S4XXHAB5eXlNv2thBBCCLG3SkpKePihBwkGB9fq6traWubNm8f1119PZWWl3en04vf7e/WrPlDous7KlStpa2sjEAgwZcoUNE16i6Zbps3LVc2Bp7iUrppQn3FPcSmq/H9mKVXT8BQVkgh2kjOqCpffD5jo0Ridm2pw+Lwo8p5YT4GRZ8xm6ysLSYb/cziiolA8dQzegB+zd0ckMcBatzZg9nNHqWXjDlKxpMUZCU1zsPyVpXzw73e7x3Zu2M7jNz/Ead87k8pJVTZml5mycrzccO8PSEQTvPnUArbX7KS4vJDZpx/OdXddQ7acGyA+x6Aron/00Uccc8wx3V/v7od48cUXc//99/PjH/+YcDjMFVdcQUdHB0cccQQvv/wyHo+n+8888sgjfPe73+W4445DVVXOPfdc7rrrLsv/LkIIIYRIj5KSkkFbEK6srGTMmDF2p5ExFixYwD333NPjYMrS0lKuuuoqZs+ebWNmB55MnJc7vFm4C4qIt/bs+ewuLEHzyC/XVjMMA3dRgKKCfCL1jRiJBIqikIpEyZs4DtXt6rOHvRhY7etrceR4GX/hKSTDMYxkalcbFwU2PPkmY796gt0pZpy+dgV8linfJ5ZTFIVFT73fZ+zN+1/jkl9/2+KMhNPlpL2pg99f92f0lA7AhpWbef+VxXz7fy9iyuGTbM4wczXWN7NuzUaWLFzOkGHlHHH0DIpLi3C7XXan1sOgK6IfffTR/d5BhV0fRLfeeiu33nprv48JBAI8+uijA5GeEEIIIYSwyYIFC7jpppuorq7mxhtvpKqqipqaGh555BFuuukmbrnlFimkp1EmzstVhxNvyRDcBcUkQ0FAwZWTi+JwojoG3a9OGUHVnKQSUYx4nNZlH2MaBt6SYjwFARRNRU6xtJ63JIAry0vTsnU0r9qMkUySPaSY8pmTGfuV48CQ98RqecOK+43llhfI55cNOhrbMfS+b15EQ1GiXVGLMxKxSJz7f/todwF9N9M0efDOfzLvoNE2ZZbZttft5Ntfv4Yd2z5dIONwaNz1118wY9Y0XK7BU0iXU3GEEEIIIcSgp+s699xzD9XV1dx+++1MnDiRrKwsJk6cyO233051dTX33nsvuq5//pMJsQeqw4HD48VbVIq3qATN45UClE1Mw8DQU7StWElX7TZMXQfTJNrQSNOiJZDSQZVfaa3m8edQ88oHNHy0Zldfet0gVNfAhn+/TrIrhuqSQyytZqR0hldP6DWuqCoTTzsMRZPzHKzm+JzvA00OqbZcOBShtbG9z1gsEqO9ucPahARdoTC/uuWPPQroAKmUzjXfuYHmxlabMuubzAaFEEKIL0GNDa6+3IOVvE4i3VauXElDQwM33ngj6n8VzVRV5cILL2Tu3LmsXLmSadOm2ZSlECKtFIV4WzupcKRXyNR1Qlu24p84zobEMlu8s4tIYxsF46vIH10BqkKsrZOmFevZ/u4yRpx6hN0pZhx3jpe8YUUcXHkMW95fRawzQmB4CSOPnEzzxh3kV/S/Ul0MjJxADh6fh1i49+HIBUMLcWV5+vhTYiB9/q0kudlktfa2Dha8sbDPWDyeYP3azQwZVmZxVv2TIroQQgjxBfj9fpwuN2x5x+5U9htOlxu/3293GuIA0dbWBkBVVd8Hce0e3/04IcQBwDCINTb1G441teAfL61DrNZZW8/oOcfStn4rm198DzOl4ystoPK4GbSs3sweukCJAaJqKg6Pi/WvfkTFIWNx+Tx07mxl+T/eZua3TpXdATZwuJ2c9YOv8K+fP4bxmfYhLq+bM/7fObg88p5YLdvvwx/IJdjW2SvmcrsoKMm3IavMlkym9tg6MNg2uBZmSRFdCCGE+AJKSkp4+KEHCQYH1w/y2tpa5s2bx/XXX09lZaXd6fTg9/sH7WGgYv8TCAQAqKmpYeLEib3iNTU1PR4nhNj/KZqG6txVaFKdTjzFRSiqQry1jVQkiuJ0gCIrB62WN2IoW19bRLT507YI4YZWNj79NqPPPkYWc9og3NpJ09o6pp47m8a1tQR3tlJQVUrpxOF89PDrVH/rVPD77E4zo6RSKYoqi7n8d99hzXuraN3eQtnockYfOg6310UylrQ7xYyjOR1867qL+N2P7+lVuL3omvPQNM2mzDJXdo6P0vJiGnb2fcN84tTBtdtMiuhCCCHEF1RSUjJoi8KVlZWMGTPG7jSEGDBTpkyhtLSURx55hNtvv71HSxfDMHjkkUcoKytjypQpNmYphEi37KpKXP5cHFlZRHY2YOoG/rGjUTQNQ0/ZnV5G0hPJHgX0bqZJ/YefMPLMo6xPKsN17Ghh56oahh06ljHHHYxpmpi6Se2iNXRsayaVkIKt1fR4iq1rN5Pl93HwyYfsGjShdtVWnF4nxRWD83eKA1lbUzuN25uZ98D1PPvgy9Ru2Ebp0CLOvORU2ps7qK9roGRokd1pZpTikkJ+evP3ufqKG3rFjj7+cIpLCm3Iqn9SRBdCiP2Q9Jv+YuR1EuLAoWkaV111FTfddBM33HADF154IVVVVdTU1PDII4+wcOFCbrnlFllFJMSBRFFQHQ4SwU7aV63tHo7srMeV56fw0INRVFn2bLVgzc5+Y107mzENw8JsBIC/NMAJ132Nda8uZdFfXkBP6mTl5zDxzGqO/dF5aE4p/VjNxOTV+S+hp3ofeO7Ly+Yb8y6xPqkM583yMGpSFes/3kSgKJ/hYyro6gyzdtl6Dj5iKoYhvajsMOPwg/m/h37Lb267m00basj15/DNb5/PnPNPJS8wuFqDyiepEELsR6Qv95cnfbmFOHDMnj2bW265hXvuuYe5c+d2j5eVlXHLLbcwe/ZsG7MTQgwEI5kkvG1Hr/FER5DIzgZ8lcNsyCqzObO9/cY0lxOkDmU5X3Eei+9/hdbN9d1jkfYQSx54lUMuOp7yg0bamF1minSE+yygA4Q7uqSdiw2y/dm8/8qHPH3fi71iO2sbOf/Ks61PSpCd46N69qH89bE7icXjaJpGYVFgUC6MkSK6EELsR6Qv95cnfbmFOLDMnj2bWbNmsXLlStra2ggEAkyZMmVQTrSFEPvGNAxCW7b2G+/aWotvSJl1CQkA8kcNY/s7S/uMFR00BtUtByZaLd4Z6VFA/6zVzy2kcNQQPL7+b36I9FM+77wG2URjuWg4yguPvtZn7P2XP+TsS061OCPxWYHCwX+wqxTRhRBiPyN9uYUQmU7TNKZNm2Z3GkKIgWaCqfffGsTUdVn0bINoSwcVx82g7o3FPcZ9ZYXkVpRhJKRXvdVatzb0G4t2hNGlJ7rlfPnZuLwu/MV5TD1uGtmBHDoa21nx6jLAxJ3ltjvFjNMVDJOM9/29YJomLY1tDBs5xOKsxP5EiuhCiL0ivaa/OHmthBBCiP2HaegYqRRGIg6A6nKjOhwoqux2sJqiKviGDSHa0Nhn3FteiuKQ98VqoR2NBMYMZ8JFpxGs2UEqliB3WCnuvBy2LVhK5XEz7E4x42TlZQOQV1HM1HOPRHM46GruYOmjr2OkTDT5PrGcw+3ga7d8k/pNO/nohQ/paOygqKKI2V8/hoIhhThdUo6zmtvj2mPct4dWVUKAFNGFEF+S9OTeO9KXWwghhBj8DD1FIthOZEcdmP9Z46wo+IZU4vTnoWry65OVFMCV58eZm0OqK4y7IACqQqK9A4DcEVXSf9sGRZNGs+2dpWQPKSK3ohRMSEZj1L7xIeUzp6BIey3L+YcUctxPLyAVTbDh9WXEOiMUjizj+J9+nY7tzWifUzwU6aeqKhuXrOeDf73bPda4pYFn73yS0793FjlFuTZml5m8Pg8jJ1axeXVNr1hhaQE5/hwbshL7E5kFCiG+FOnJvXekL7cQQggx+BmxGJHttT0HTZPw9q3kesajZsmvT1YyDINYaxsF0w/C1HUiO+oxDYOcEVU4s7yE6raTM2LwzfsOdHoqRemhE9nx/goalqxBdWqYhkl59RRirR14i/LsTjHjKE6N+iU1rHnhw+6x9tpGat5fzVHXnAtm/22RxMBIxBIsfOL9PmOv//0VLp0on11WU50a/3PjJfzq6rtoaWjtHs/xZ3Ptr67EKec5iM8hs0AhxJcmPbmFEEIIcaAxdJ1o0x76Cjc3kD2sCkVVLcwq0ykoQLhuG6HNW7tHu2pq8RQVkDOiCgxZim4506Rh6RqGzj4Y1aFh6gaqy0n7+hrcebl77GMvBoYRT7LmxQ/x5mUz7JAxuLLcdNa3sX35JpY//jaHXX6y3SlmnGBjB6bR9/dCLBwj2hkBab9tKRUFwzC57q6radjWSO3G7ZRXljJ0RDmaU8Po5/0SYjcpogshhBBCCCGEaWAkYv2GjUQc0zCkiG4hFRNHlpfWZR/3isWaW/GWleLKz7M+sQyXiiUZNvtgunY00bJqM6l4gtyKUgonjsTQDUxZ9Wy5lk07mXLOEfgK/Wx6+2NiwTCFI8s56uo5fPL0B+hy2KvlPm9Vs+aUcpzV8gvzqFlXQ24gj2Ejh1AxeiimCdGuKBs+2cyRp8y0O0UxyMl3rRBCCCGEECLjKaqG5vVhpFK4A4U4snwApMJdxNtbcHh9UkC3QVft9n5joS1b8ZYNzt2RBzJPIIft7yylfUNd91isNUjrmhrGnX+ifJ/YILs4j4Y1tax88r3usVBjO7WL1zH7e2ejqIqN2WWm7PwcvDleoqFor1jhsCLcPo8NWWU2VVOpGF3JP//8NO+/8iGGbqAoCgcfMYWLf3ABLrecHSD2TIroQgghhBBCiIynqCruolJceQFiLQ3Emne1dnFk5+KrGIHidElx0GKGomAkE/3GzaSsrrVDMhTtUUDfTY8n2PHBxww//jAbsspsnpws1r+6tNe4kdJZ8e8FHP6d023IKrM5spyc88Ov8s5jb3L4uUfiyfbS1RZi4VPvceqVZ+LySP9tq4U6uvjnn5/m3RcXdo+ZpsnSdz8mGonxvdu+TaA438YMxWAns0AhhBBCCCGEAFRVoatuM6muUPdYqquTcO0WVEVWclrONPGUFPcb9hQXgrwvlmvf3LuAvlvH5u0Y0hPdci1b6vuNdWxrJhVPWpiNAEiEYuSXBzjj++fgL85DUaCwoohzfvhV3D43sXD/7cPEwAi2d/L+Kx/2GVuzdD2hji6LMxL7G1mJLoQQQgghhMh4pmEQa22GPg4WMw2deHsr3pIyFEXWIVlGVXEH8nFkZZGKRHqEFE0jZ8RwublhA3UPOzIUBZC3xHrm5x2wKwfwWs3pcaOnUrx497PUra7dNagojD1sHMdfdhKqJj9LrBYORfZ4k6+tuZ3KMcMszEjsb6SILoQQQgghhMh4pq6TCgX7jSdDQTyFJSgOKXxYRVEUFE2jcMbBdNVuI1y3HVPX8ZaV4B87GgBTiuiWyx9TSf2Hq8gZWkJg3HBUp4NwQwutq7fgHzkUxaHZnWLGKRxVvuvmRR+18kBVKQ7p9Ww50zR45ndPsnPDrnMdNIeGntJZv2gtmlPjuMtOtDnDzOP9Tx/6gpJ8jjp9FsVDimhv6WDB8x9QX9eIP5Brc4ZisJMiutivqbH+f9ERn5LXSQghhBDic6gKisOJ0+nCXdizhUispREFRVqHWMw0DBLBIHosDopC8eGHgQLx1jZCNbX4hpajpqSvsNVUp4PxXz+Z4NZ66hevQo8nyK0oY9Q5x+DMzkKRRc+WU1SVSWdUs+rZhT3GHW4n0756lKx6tkGsK0pHQxvHX34ygfICEpEYbp+X+k07WPTU+xx5wdF2p5hxcvNyuPgHF+AP5PLSY6+zvWYnxeWFnP6Nk9B1nZy8bLtTFIOcFNHFfsnv9+N0uWHLO3anst9wutz4/X670xBCCCGEGJRUzYG3tBw9HqOrbsunbV1UFV95BZrbi6rJClsrqYDD4wXDxBPIx9R1TMPEUxDAlZ+HHo3hzM2xO82Mo2oqte+uILStoXusfWMdHVt2MOGiUzGQGxtW05MpCkaWc9TV57Lp7RXEghEKRpYxvHoCyWgcXQ7htVwkGOGsH3yFtx58jYbNn/asHz5lBGf/8KvEI3Ebs8tMOXnZZGVncdf187vHajdu5y8/f5Dz/udscvLk54nYMymii/1SSUkJDz/0IMHg4FphXVtby7x587j++uuprKy0O50e/H4/JSUldqchhBBCCDGIKUS21/YcMgzC27eSO2q8PSllMlXFNE0cWV7aVq4m0d4BgMOXRf7E8ThzcqTVsw1i7aHuArrD40J1u0gEuzB1nW1vfcTwkw+3OcPMoygKzRu2s/GtFQw9aBTZRX6C9W289dt/Uf3tU+X7xAa5xXk8/Zt/0VjT0GN868otOD1OTrj8ZJsyy1ztzR08+LvHKass4dizjqSorJCO1iBvP/c+T/z1OY44ZSaeIUV2pykGMSmii/1WSUnJoC0KV1ZWMmbMGLvTEEIIIYQQX5Ch68Sa6/uNx1oa8Q0djrKHQxVFehm6jsPtomHB+xifWUmbCkdoXryU0tmHY0p10HLBrTspmDCCshmTSEai6PEknkAusbYgm557V9q52MBIGax9cTGmaVLzweoesdXPL+LQb55gU2aZKxVP9iqg77ZxyQaOvVjeE6uFOro4bs5RlFWU8MIjr7Kjpp6i8gJOOu84AFob2iiRIrrYAymiCyGEEEIIITKeqacw4v1vr9fjMYxUEs3ltjCrzKaoKpGdDT0K6J8VXL+JwLTJFmclcoaV4HA5Wfv4y+ixRPd44aRRTPzGqZhydIDlOrY34fC4GDl7MgUjyjBSOigKdYvXsWPFZgzdsDvFjBMJhvsPmiaJaKL/uBgQHp8HX7aX/7vt/u6xph0tPHTnPzj5/GOZetgE+5IT+wUpogshhBBCCCEEoHq86PFYnzHN7ZGDRS1m6jrxtvZ+4/GOIKYhxUGrZRXk8cn9z2Km9B7jLas24S3Mo2DyKJsyy1yq00H1t09l3Ssfse6VjwDQXA7GHDuNoq8OsTm7zOTL7/+QSkVVcWfJDVmrKSg8ff9LfcZe/ffb3SvSheiP7EUUQgghhBBCCFXDU1Dcb9hdUIwiB4taStE0HFnefuMOrwdFlffEasGaHb0K6Ls1LFmNEZcVtlYLVJaw/J9v07R+W/eYnkix9uUl6CkDp9dlY3aZSXNoDB1f0Wds4pGTUDUpx1ktGo4SDUf7jBm6QXtzh7UJif2OfNcKIYQQQgghMp7mcKA4HPiGDUdxfLphV3E48Q2rQnE4UKVga7nsqkoAVKeTrCFl+IYOQfPuKqznjhkFivxKa7VoW7DfWDIclUMsbRDrjBBq6HvXxvpXlkg7FxsEm4Icef5RjDj4050Ziqow6egpjJk5nvCe2r2IAeFw7rkZh9sjuwPEnkk7FyGEEEIIIYQAVIcTPFlkV4zA/E/RSdFU0ByomvzqZDnTJBmOUHLULIxojEh9I6ahkzd+DA5fFjg0TL3vfuli4GSXF9O0fH2fMU8gF0WVtkdWC+5s6TeWiMTR40kLsxEAOQU5dLWHGDdzHIeddThgYhomnS2dKCp4sj12p5hxcvKyGVJVxo6a3oeI5+bnkF/ktyErsT+R2/ZCCCGEEEIIAagOB6rLjeJ0o/xnZbridKO53KgOKaJbTXU4UFSVrppamhcvJbxtO5Ed9bQu+5j2T9ZgJlKon7OyUKRfdnkhTl/fbXaGHjFN2h7ZwOvvv/+25tSkdYgNXF4XK99YgScni1BLkO1rtxENRXE4NWo/2YrLK6uerebJ8nD5T76BLyerx7jT7eQ7N1yCy+O0KTOxv5AZhxBCCCGEEEL8h6mnSLQ1k+za1bLCmePHHSgCKQxaTlEUVIdGsjNE4aEH7yrOmiYoCl1b60h0BPGWFNmdZsYxgbHnnUjNy+8Trt+1AlrzuBh65MG483PksFcb+ApycOd4iYd693uuPGw8ikM+v6yWSqSYfMxUnr3zSSKdke7xvJJ8TrnqDJIxOTvAah0tQe777aPMveVyttfUs33LDoqHFDFqYhVP3/cipcO+SY4/x+40xSAmRXQhhBBCCCGEAPREnNDm9RipJJonCzCJNTeS6GgjZ8RYNJesHLSSaRjEWtvIHTOSto9XdR9YqWga/nFjMA0dPR7H4ZG2CFZSHBpmSmfYUdPR3C7MlI7i1Eh0htHcLpB2LpZTNI0ZF5/ERw+/RrTj017bpROHM+yQMdKn3gaGrvPiPc/1KKADdDS28+5jb3Ha986yKbPMFemKsG3TDn597R+pPvFQJkwbQ82GOn75/54FoKM1yNAR5TZnKQYzKaILIYQQQgghMp5pmiQ62nDlBXD4skmFuwDwlpSTCodIdnagFhSjKFIgtIppGHgLC2h4d+GuFei7x3WdjtVrKZwxvbt3vbBQUmftIy+hJ5IoqoKiaRjJXb3ph584k/yxw+3NLwMpioKeSjH5rFloLgeJSByv30eoqR1FUzFN+T6xWjKWpLO570N4t6/bJoe92sDr8zJh+li+ee351Nc1sXV9LeOmjubk847jib88S26+rEIXeyZFdCGEEEIIIUTGM/UUiuZAj8fo2rrp00AzuAOF4FIxdR1FeqNbxlQUIg2NPQronxXaXIO7IGBxVqJzWwPuvGzKZkxGdWjoyRTOLA/tm+rYuegTcoeXQz8908XAiIeiJGNx3NlZBHc0k4jEUVQFrz9bbjTZJBaJ7TGeSshhr1bzF+RwyQ++xi++/3vaWzq6x7Oyvfz0rqvJL8yzLTexf5DTJYQQQgghhBACBUVVSLS39orE21p29eOWRejW0g2Swc5+w8muLkxdtzAhAZCKJxgyaxq1by5m49NvseWFd1n/79cxdYPymZOldYgNvHk+HC4nDreTRDiOntSJhaLklhfQsaMFh9tld4oZJ7fQ32/M4XbikRtNlouEYtx7y99pb+mgrLKEqTMnUjFqKJGuKL//6Z+JdEU+/0lERpNlFGmgxvreoiN6ktdJCCGEEEIMWgrE23oX0HdLtLXgzOm/KCLSz1TAmZtLtLkV35AyvKUlKKpCvLWdrtptOLOz5caGDfKGD2HNIy92t3ABwDRpXrkRT34uqlMOsbSaCYQa2lny6usMmToCl89D07o61r28mKP+37lys8kGpgnjDp/Aug/W9IodcuoM+eyyQVewi0Q8yQ9/+12adjazfUs94w8eywVz5/DU354n2NZJydBiu9MUg5gU0feB3+/H6XLDlnfsTmW/4XS58fvllw8hhBBCCDHIGCZmqv/t9Yae6retiBggpknWkDK8JUV01e2gdemKXX3SS4opmjEdUzFBkc3VVuuqb+5ZQP+MhqVrCYwbbm1CglQswarnFoIJtR+u6xFb/s+3mXHxiTZllrmioQhHfu1osgM5rHxjOYloAm9uFoeedhhjq8eTiMTtTjHj6IbBRdecz90/+yuhYFf3uNvj4ru3fRs9Ja2PxJ5JEX0flJSU8PBDDxIMDq4V1rW1tcybN4/rr7+eyspKu9Ppwe/3U1JSYncaQgghxD7RdZ3169cDsH79ekaOHImmyco7IfZniqbhyPGjx/vuY+vM8e9q6SIsoyoKiqbSsnglqcin2+yjjU3EWlopPWqWLOa0QbS5vd9YsiuCacjNJqu11zX220anraZBDrG0QXZ+Ng9ddx9Dxw3jtO+ehaqppBJJVr75MesWruHcn15gd4oZx5ft5d6b/96jgA4QjyX46y8f4ub5P7EpM7G/kCL6PiopKRm0ReHKykrGjBljdxpCCCHEoBGLxairq9un51i2bBn/+Mc/aG/fVUS44447+Pvf/87555/PwQcfvM85VlRU4PF49vl5hBBfjqKqeAqKiLc1g9Gz4KRoGu78QhRFSrZWMoFEe0ePAnp3TNfp3LSFvAnjrE8sw2UPKaZx2bo+Y+78XBRVvk+sJp9Ng0+0M0K4o4v1i9ayftHaXvFkXA4WtVoinmTb5h19xoKtnYQ7wxZnJPY3UkQXQgghRMaoq6vjiiuuSPvztre38+c//zktzzV//ny5CS6EXVSVnOGjiDbVk+oKAeDMzsVTXAZSGLScaRhEdjb0G481NmOOk89Lq/nKCnF43aSivdtRDD3iILRsOTDRagUjyvqN5VcU43A7LcxGACRiey6S66m+WyKJgZNK7vlsgLjc2BCfQ4roQgghhMgYFRUVzJ8/f6/+rGEYXH311cRifbd6APB4PPz+979HVfe+R29FRcVe/1khxL5JRcK7VqQXlqKWVQAmRjKBaRjosSia02V3ihlF0TTUPbzmitMBsgL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audga9B5efLEBVDYU0QG4zJEjRzR8+PArOsbTTz99wf59+/Zd0Rhz585Vo0aNSr1/RVYW51+SMjMztXDhwiLta9as0Zo1a0p93Kp87q9EaGioJOmVV17R119/7bBsy5w5c9SlSxeH7QAAAMqSX2QN7Vu4Utb8AnubzWLV8U27FNe9g3zDQ1wYXfVkzbNo/bSP1KzHteo8+u+SySRrfoF+XfeDzhw8oS5j+rk6xGrHP8RfQRHBSk9JK9JXu1msfAP9yj8oAFeEIjoAl4mNjdXcuXNLtW9BQYFGjhwps9msGTNmKCkpSVOmTNH48eMVHR2txx57TFarVTNnziyy3MvlxlhVXcn5/zOLxaJPPvlE69atU9euXXX77bfL3f3K/7xU5XN/JeLj4+Xn56d169YpODhYw4YNU0JCgrZu3aq33npL69atk5+fn+Lj410dKgAAqIKyjqc4FND/7MSWHxVQu+T1ueEcmSmpslls2vPpFu35dEuRfhtL7JQ7k5tJvR/rq6VTlyg77Y/1z0NjwnTTkG5yczO5MDoApUERHYDLeHt7X9FM4w4dOmjz5s0aPXq0brzxRknSjh079NVXX8lqtapDhw5q0aJFWYVb5Vzp+f8zd3d3rVu3TnfeeSezx53MarXab5jbtGlTxcXFycfHR3FxcWratKm2bt2q3NxcWa1Wmc1mF0cLAACqmuyTZ0rsy0/PkgyjHKOBJPmEBJTY5+ZultmdnLC8Zadla+Xrn+rmYX+TzWJVxukMBUeFyJJfqI9f/FD9nxt40SVfAFQs3FgUQKU1ZcoUdejQQYWFhVq9erUkafXq1SosLFSHDh00ZcoUF0cIlL3ly5fLZrPp1ltvVWJiokaMGKEePXpoxIgROnTokG699VbZbDYtX77c1aECAIAqyDe85CXjPAP9JGbYljufID95+noV21e7bSPeExfIOJ2uzDMZSj6YJN8gP4XXjZSXr5dO/HZc2alZysvmxqJAZcNMdACV2pQpU5Sbm6uXXnpJ69evV+fOnfXUU0/Jx4dv9VE1nThxQpI0cOBAPfbYY9q9e7fOnj2r0NBQxcfHKzU1VZ9++ql9OwAAgLIUWCdKZk8PWQsKi/TFXHuVzB6UGcpbxslUtR/UTd8tWKOC7Dx7e40GNVWrTQNZ8ou+V3Auv2B/3f7Undq5cru+XbZFMgy5md3UrGML9Rl9uzx9iv/SA0DFxV83AJWej4+P7r33Xq1fv1733nsvBXRUaTExMZKkrVu3qlevXmrdurVD/9atWx22AwCgKrDk5sqWXyDDMGT28pTZ21smNy6sdgWr1abGd96sA8s3qCAzW5JkcnNTZNtmCoiNYv1tFwiKDtV389eozd1dZLPalJ+VK//wIGWeTNXez7/VdcN7uTrEascnwEfr3v5CR/YetrfZrDbtWb9bJjeT6lxV13XBASgViugAAFQiffr00Zw5c/T222/rb3/7m8NNXC0Wi9555x2ZzWb16dPHhVECQOVlGIZshYUyrOdmbprMHnLz8JDJxHIIrmDYbMo/m6ZT3+2U9X/3BHHz8FBoqxbyiY6S2cPDxRFWPwWZ2fIK9FfD22+UYbXKZrHK3ddb1vwCFWbnyiuIMkN5M3u4KyQ2Qt++vUoePl7y8PZUXmaODJtNHR/pK5OZ31/lzVJgcSig/9neDT+p091dyjkiAFeKv24AAJSzvLw8HTlypNT733TTTVqzZo369u2rPn36KD4+Xrt379by5cuVmZmpW265RYcOHSr18WNjY+Xt7V3q/auDgoICLV++XCdOnFBMTIz69OkjT09PV4cF4ArZbFZZMjOVfeyQDKtFkmQyu8uvdl15+AXIxA2by50lJ0cnv9kiw/bH7GZbYaFOb/9BUTd0kLlGmAujq568g/y1b+FKWfMKzjW4uUn/e3/ielwv77Bg1wVXTVnyC9S81zVqfHMbWQssshRY5OnrJbOnhyyFhbIWWFwdYrWTdTazxD6b1aa8Py27g/KVdiZdGWlZysnIkY+/twKC/RUaHuLqsFAJUEQHAKCcHTlyRMOHD7/i42RmZmrhwoVF2tesWaM1a9aU+rhz585Vo0aNriS0Km3OnDlasmSJrFarQ1u/fv304IMPujAyAFfKlp+vrMMHHNoMq0VZhw4osGFzubNkXLkyDENZR445FND/LHXvL4pIaC+zJ7PRy1PWiVPyjayh2p1ay+RulmGzyc3drIxDyTqxeZcCakW4OsRqx93bS4W5Bdo2b7XSj5+WTJLJZFLcdc3V8MbWcnPnC8Dy5hPo69hgMkmGYf+3Vwk3goVzpZw4rQXTPtCODbvsbU3bNNKDzw5WFL+7cBEU0VHtXemMUGdjRihQ9cTGxmru3LlXfByLxaJPPvlE69atU9euXXX77bc7LO9yJfGheHPmzNGiRYsUHBysW265RTExMTpx4oTWrFmjRYsWSRKFdKCSstmsyk1JKrE/73Sy/GrWYR3ucmTYbCo4m1Zif2Fm5v+uGKCIXp4Mm6E6N7aTzWKVNSdfNptV7j5e8gkLUlzP6yWxdEi5MwztWLhOTbq1U0BkiGQYMiQd+/43Hf7uZ9Xv1NLVEVY7/iEBqtW0thq2b6KIOhEqzC+Uh5enjv1yRGePn5FvkJ+rQ6x20lMztHDGYnsB3Ww2y2q16ufv92vm029q1IsPqUZUqGuDRIXm0iL6xo0bNXXqVO3cuVNJSUlaunSpbrvttgvus379ej3++OPau3evateuraefflqDBg1y2Ob111/X1KlTlZycrJYtW+q1115T+/btnfdCygCFXNcpqxmhzsKMUKDq8fb2LrP/r93d3bVu3Trdeeed/K5wsoKCAi1ZskR+fn7y9vbW4sWL7X1RUVHy8/PTkiVLNGTIEJZ2QaVU7XNzm022vNwSu615uTJsNoro5cjk5iaPwADlnkwptt/Dz48ldlwgMDZK1vwC5Zw8o9N7f5c1v0ABtaMU1jRO7r7ecvNkrl55y8vIUbt/3KyUX49q38ptykvPUWjdSDW5pZ0MGbIWFLo6xGrHsNrU+9G+Wv7qJ/p6wVp7e/22DdXtgR6yWqwX2BvOkHE2Uz9u3aM77r9V9ZvHKS8nT14+XjqeeELLF6xSZnoWRXRckEv/umVnZ6tly5YaMmSIbr/99otun5iYqJ49e+rBBx/Ue++9py+//FLDhg1TdHS0unXrJkn68MMP9fjjj2vOnDm65pprNH36dHXr1k2//vqrIiIq7qUZFHJdp6xmhErS4cOHNWXKFI0fP1516tQpk2MyIxQAKobly5fLarXa85dnnnlGcXFxSkxM1HvvvactW7bYt+vXr5+LowUuX7XPzd3c5ObtLWt+8evUmr28KaC7gF9sLWUc+P2PZRD+JLBxg3NLJKB8GYaSd/wsDz8fRV/TQobNJmt+oY5984Nqd2krswdfbJQ3Tz9v/fzFdlnzC9WsxzVyM7spNz1bPyzeoKv6dmA5FxcoLCjU0n8vUfJBxyucDu78TV/NX6uuQ7pJzEYvV7nZeXpk8nB9sWidPnrzU3t7/WZ19ci/7ldmWsnr2AOSi4vo3bt3V/fu3S95+zlz5iguLk7Tpk2TJDVt2lSbNm3Sq6++ak/UX3nlFd1///0aPHiwfZ8VK1bonXfe0dixY8v+RZQRCrmuU5YzQs+rU6dOlf3SAQCqq+PHj0uS2rVrp8mTJ8vtf8W05s2ba/LkyXryySe1Y8cO+3ZAZVPdc3OTyU3eYZEqTE8733Duv/8r3nqFRVBEL2eG1arc5BTVaNdaZ3/8Sbb/zaY1ubkpqElDFWZmyTMoUGYPlnMpT4U5earRvL6Sv9ujlO9/kZunu9zMZsVc11LZJ07Lo0FtV4dY7disVtVu3UAp+49p5/tfyZJXoIDIEDW5pZ1SD59UYCQ3TSxvedl5RQro5/367c/qdG+Xco4IgSEBWjZ/hX767meH9oP7DmnRrKV6ZPL9LooMlUWlus5q69at6tq1q0Nbt27dNGrUKEnnLrPeuXOnxo0bZ+93c3NT165dtXXr1hKPm5+fr/z8fPvzjIyMsg38ElDIBQCgcmjUqJG9gH6em5ubGjZsqB07drgoKqD8VbXc3LBaJDeT/OrUl8lkkvG/mwebzGYZ/yuk2ywWuZXBvSdw6fLPnFHOiQKFtrpKJjezZLPJZHZT1uFjyjtzVn61YlwdYrV0Zv8h1e7cVpb8QlnzC+QdHKDslLMyMQvdJaz5hTqw4Uel/HrM3pZ5MlXb312rtvfeVNyFHHCyrLMlz2o2bIYKcvJL7IdzWC1Wff/N7mL7En85rIJ8lj3ChVWqqRTJycmKjIx0aIuMjFRGRoZyc3N1+vRpWa3WYrdJTk4u8bgvvPCCgoKC7I/atfnmHAAAOGratKkkaeXKlbJYLA59FotFq1atctgOqOqqWm5uSLIVFMhWUKCswweVfTRR2UcTlXX4dxmFhbJZ+HBd7tzc5BMdpYLUNGX+fkiW7GxZ8/KUdfiYcpKS5R1RgzXRXaRGs3o69dMBWXPzJZuh9MNJykvNkHdYsAwbFdvyZnJzcyig/9nPq77Tud9wKE8BYQEl9pncTPLyrZr3nKvI8vPy7V+Kh4YGqkvfjoqqHW7vz87IdlVoqCSYRiFp3Lhxevzxx+3PMzIyKKQDAAAH59dvTktLU79+/TRkyBAlJCRo69ateuedd5SWluawHYDScVVubtK5JV1yTx6XV0iY3P0DJUmFmRnKSTom/zr1nR4D/sIw5BkUpIjr2iv/bKoyfz8sw2aVT1SkIjtcK5O7mYKtC7j7+aggLVOF2bk68Ol6GTZD3mFBqnldS+VnZMm/ZvjFD4IylXbsdIl9OamZsllt5RgNJMnDy1M1G9fS8WK+3Gh6fQu5cdVGufP191W7zq1136g7lZmepbTT6bqx9/UKDAnQl0s3Kigs0NUhooKrVEX0qKgonTx50qHt5MmTCgwMlI+Pj8xms8xmc7HbREVFlXhcLy8veXl5OSVmAABQNcTHxysqKkpubm5KTk62rwMtnVuiIiYmRoZhKD4+3oVRAuWnquXmhiEVZKQqoE595Z05pewjiZJJ8gwMVkDd+srPSJO7r2+5x1WtGYZslkKl7f1FBel/LOuTlXhYOSeSFHHt1ZKN4mB5s+UV6PDabcpL/eM9yTuTroOfbVSD2zpLFt6T8ublX/KsZpObSW7mSrUIQZVgMpt06+jbtfL1z2QzbAqvHa7jv51QSESwuvzjJr7YcIGg0ADdN+pOJf58WAHB/srNzpOXt6dST6erS5+OCq5BER0XVqmK6AkJCVq5cqVD29q1a5WQkCBJ8vT0VNu2bfXll1/qtttukyTZbDZ9+eWXGjlyZHmHCwAAqhCz2ayHH35YEyZM0DXXXKOaNWsqPz9fXl5eOn78uLZt26ZJkybJzNICqCaqWm5uMkleIWHKOnzQvh66DKkgPVWFWZnyr1NP5+aro7wYJpNsefkOBfTzbPkFyjpyTEFNuQdUectLzXQooP/Zia0/qUGfzuUbEBQQGSKzh1nWQqsimtSWb0iATh88oayUNEVfVY8iuguYZNL+7b+ox4jeykrNUtbZTMXf2Fq+Qb76acOPir+xlatDrHayM3OVm5Wr5QtWKvGXI/b2qNoReuz5B5SV5i5fP74sR8lcWkTPysrSgQMH7M8TExO1a9cuhYaGKjY2VuPGjdPx48f13//+V5L04IMPaubMmXryySc1ZMgQffXVV1q8eLFWrFhhP8bjjz+ugQMHql27dmrfvr2mT5+u7OxsDR48uNxfHwAAqFjy8vJ05MiRi29YgqioKD3wwANasmSJvv32W3t7jRo19MADDygqKkr79++/ohhjY2Pl7c06mSh/1T43N7mpICP9jwL6nxhWiwqzMmX28XNBYNWXSVL28RNy9/dTYIN6Mnt7S4Yhw2ZT5u+HlJuUrKDGDVwdZrWTdfzc1SVBcTGKaNNEbmazspPP6timH5Rz8oy4i2X5S08+q87/vENmd3edOZSsnDOZatXvBnkH+Uk2mwq5YWK5M2SoXusGWvL8Bzp95JS9vXazWPV69DbZuGKj3FmtFr33nyUOBXRJSj6aopnPvKUx0yreF/yoWFxaRN+xY4e6dOlif35+7cOBAwdq/vz5SkpKcvigGxcXpxUrVmj06NGaMWOGatWqpbfeekvdunWzb3PXXXfp1KlTevbZZ5WcnKxWrVrpiy++KHJDIwAAUP0cOXJEw4cPL/Pjnj59WnPmzCmTY82dO1eNGjGzEuWv2ufmNpssWedm17r7BcjDP1CSocKsDFmys1SYmS7vGhUw7qrMMOQREKCAurE6+9M+WbJzZDKZZHJ3V0jzJirM4iZwruAZ7K9m9/VS3tk0ndiyW9b8AgXWjdFVg2/V8a0/yuTGFRvlLaR2uLJPZ2jLnI9kLfzji8DA6FBd92BvuZl4T8qbSSYtfXmJQwFdko7uO6I1b67S3x7q5aLIqq/83AL99N3PxfYdP5Sk3Ozcco4IlY1Li+idO3e23xm3OPPnzy92nx9++OGCxx05cmSFvEQUAAC4VmxsrObOnVsmxzp8+LCmTJmi8ePHq06dOmVyTOlcjIArVPvc3GSSm4enfKJqypKdpfy0M5Ikz6AQedeIVH7qmXNrvqBc+dWuqbM/7VNY65YymUwyZMjk5qbMxMPyr11ThollKspbaINYHfl6h/LOZqhmx1Zyc3dX+qET2vfeKjW9929yc69Uq8ZWDYa05Y3PHQrokpSRdFY/LdusVnd2clFg1VduVq5OHUkptu/g9wdUmJtfzhEhNzvvgv0ZqZnlFAkqK/66AQCAasPb27vMZ3nXqVOHmeNAVWAyySeqprIOH5St4I/iRl5Kkty8vOUfW48iejmzGYYKM7MU3KShDKtNBZmZks0mj6BA+dWMlrWgUO7cWLTcFWTnKfraq2SzWmXNLZAMQ4G1IhXZuolS9h5QVMvGrg6x2kk7ekrWAoskyc3dLLOn+7kirSGd+PGgWtya4OIIq5+ctHNXyoTGhCn+xlbyD/FX2sk0/fjlD8o8k6GC3AIXR1j9+Aacu+m5tZhl2yQppEZw+QaESociOgAAAIBqz2axqDAz3aGAbu/Lz1NhdqY83T0kN2Y+lxubTR5BAcpLTlHqnp8d1tr2i62twAZxMvheo9yZvdxlzS9U2m9HdHrPQVnyChQYG6Xo9i0U0byBbJbiC1RwntyMbPlHBKtp9/Zy9/JQQXaefIL9dTYxWb+s2cF74gIBNQJ1Q/8b5Rfsrx/W7FBeZq78QwPUdUg3Hdl7SF5+3P+mvHn7eKlTzwR9/emmIn0tE1rIm/cEF0ER/QqdPHlS6enprg7DweHDhx3+W5EEBQVVzDUwAQAAUO0VpJ29YJ9nYHD5BQPJzU22/AKl/rRPkmT28ZbJzU2W7BxlHzkqr7AQ+URFuDjI6sfk5qYjX21XdtJpe1vG4SRlHj2pxv26yjs82HXBVVPhDWoqMDJEOxZ+qdy0LHt7dIu6Sri/h8yelH7Km5ePlzx8PFW/bUPVbRknm9Ums7tZNsMmi9UiL18vV4dY7eRm56nXfX+T2cOs3376XbXiopV0JEVRtSN0+9Beys258HIvAL9Jr8DJkyf1j/sGqLCY2SoVwZQpU1wdQhEenl5a+O5/KaQDAIBSs1qt2r17t86ePavQ0FDFx8fLbDa7OixUciaTLrhci0kmlnMpb4ah7CPH5BsTLf+6sbJkZ8uw2eQRGKC8lFPK/P2QvMNruDrKaifvbIZDAf08w2bT8S0/ql6P610QVfXm4e2pb2YuU36m440Rk/Yckl9YkELq8vm7vBky1PiaJkr67bi2fPSN0k6mKjw2Qh3v6azYpnVU+L/ld1B+TCY3fff1TvXqf4tOHE7Wof1H1b5LW8U2rKUfNu/WVe2buTpEVHAU0a9Aenq6CgvylVvvBtm8g1wdToXnlpcu/b5B6enpFNErOa7AuHxchQEAZWPjxo2aNWuWkpOT7W1RUVF6+OGH1akTN05D6bm5e8grNFw5x4vPJbzCasjNzMen8ubh7y+ZTErZ+p3Dci7+dWorIK6u6wKrxtIPJZXYl3n05AVvUAznyDqVZi+gu7mb5e7prsLcAhmGocQte9TwxlbS/7N33+FRlWkbwO8zfVJmUkgnjQ7BUAUCElBApQkWRI0ixUUFV3CFVQQMKKyuKIIFFBfBBRRFFGyIiEIUQhHB0GtIgHSSTNr0Od8ffJl1TEJN5kwy9++6uDTve3LmmTMpT555z/OyZOFWcrkcf2zdj7SPf3aOZR06i6yZK3HXP+5Bi66tJIzOO8kVMnTr2wnzJi1EUd5F57i/3g/PvzUFcgXbtUmlML8IWWfPI+P3I4iICkNilw4ICw+BQulZeZdnRdNIOTR6OHy5AoK8A+/AuD68C4OI6MalpaUhNTUVSUlJmD17NuLj45GZmYk1a9YgNTUVc+fOZSGdrpsgk0Hp5w+51gd2Y5XLnMLHFwofPwjsh+5eggzq4EDkbd9RY6oi6xyCg4MgKPgnrbsptXW3oZApFQB4x4a7VV4su2xPdDt7orud1WzFr5+lwUfng4R+ifAL8kdpXjEOpx3Cj//5Ho++9hj89H5Sh+lVBAF4f95HLgV0ACg3VODN597DC+88I1Fk3i3nQh6eGvs8Tp3IdI5pNGos/e8CdOqWAIUH/Z73nEiIqFHgHRjXjndhEBHdOLvdjiVLliApKQnz5s2D7P+LmQkJCZg3bx5mzZqFpUuXok+fPmztQtfNUlEGTbMwiHYbLGWlAASodAEQZDJYK8ohV3PTMbcSHag8d6HO6fLTmVA3C3ZjQAQAgW1jcWHHgVrnmiW2hkzJn8Hupm/eDJ3v74e8Q2cR0joKKh81TIZKWExm9JowGDI53wB0t9KCUnQb3B3N28fgjy2/49RvJxASG4qR0+7DwZ8OwPiX1jvU8MxGC04fzqx1rijvIirLqmqdo4ZTVVmFhf96z6WADgAmkxmTxj6HL7esRGTzcImiq4lFdCK6LrwDg4iI3CkjIwN5eXmYPXu2s4BeTSaTISUlBZMnT0ZGRga6dOkiUZTUmNksZliKi2A3VkGmVkPppwNEwFSUD4fFDIWPH5Q6PeRKldSheg9RhK2y7qKGzWQCwNYh7iYIQMxtNyP7p70u49pgPcK7tYfDyl7P7qby0cBmtMBqsmD3is1w2OzQBvih3e3d4LDZ+caGBHz8feAX4I8vX1vnHCvJLcaJ3ccx/OkRUGn5u8TdzCbLZeerKlhEd7fii6XYuimt1jljlREnj59hEZ2IiIiI6FoUFxcDAOLj42udrx6vPo7omv2pj7PDaoXdZHL+//8fAIgOCQLzXoJcDk1oMxjzC2qdVwcFQmCferczGyoR0DIaPqFBKDl1DnaTGf4x4fANDYIoipAJXPXsbg6bHUe+3YOLmf/rV28srcD+z7ajy+j+fK9JAiofFdLWbqs5IYr4+b8/4pFXJ7g9Jm/nr/eDUq2E1WxFeHQoQiNDUFJUinOnL0AQBASHBUkdotexmK2w2+tuN1VcWOLGaK6MGQc1Wtzc8tpwY8umg1/714Zf+0RNQ1DQpT9sMjMzkZCQUGM+MzPT5Tiia3epdQt0AZBrtLBWlAMANM1CYTNWQZDLAYGrOd1JdDigCQmBUucPXZtWUPr7AaIIu8UKw9Hj0LVqCZFvbLidJkiHY59shrXSiKD28VBoVMhNPwhTSRna3DsAvtHMu9zNZrK4FND/7Oj3exHWPsbNEVF5URnsddyVUVFSAXOlyc0Rka/OBw88eTdCo0JQlFeMC5k5SLi5HaJbRuHUoTPQ+LBlm7v5+vsgJDQYhQUXa51v17G1myO6PBbRqVHi5pbXjhtbNg382r92/NonahoSExMRHh6ONWvWuPREBwCHw4E1a9YgIiICiYmJEkZJjZkgCFDqAmAsyIUxP8c5br5YAFVAENQhYdwv0d1EoCovDyE9u6MqNx/lJ09DdDigDQtFs26dYSougfwym1xSw6jKvwhtSADi7kiCqdgAu9mC6P7dYS4tx/lf96P13bcBGr4u7lR64SI0el+0u70bfJvp4bDZIVcqkHvoLM78chAObizqdqJ4+eX/V5qn+ldVXoWE7u0wf/JClBsqnONqrRovvP0MqirYp97dQsOa4R8zn8SMKfNqzPXo3QVhESESRFU3FtGpUeLmlteGG1s2Hfzavzb82idqOuRyOSZNmoTU1FTMmjULKSkpiI+PR2ZmJtasWYP09HTMnTuXm4rSdZMpFLBUlsNqqHnrsKW0GEpdABQaHwki82IyAb5REbi47wDMxf97XazlFag8n4OwW3pBYOsQt7NUmhDUJhb5+44iqG0slL5alF/Ih7mkHJFJiRDtvDvA3XyD/dFjzO3IPZwJjc4XgkxAVUk5VH4adB8ziBuLSkAXoofKR40WnVui/S0JkMlksFlsOPjzH7h4oQgaP63UIXodh0PEu6nLXQroAGA2mrHwuSWY9e6zEkXmvQRBQN9be+H1JXOx8F9LkXM+D1qtBvc+NAxjJz6IoOBAqUN0wSI6NWrc3FI6MmOp1CE0Gg1xrfi1T0TeKDk5GXPnzsWSJUswefJk53hERATmzp2L5ORkCaOjxk4UHTBfLKxz3lxcBKW//lJbF3IPhwOW0jKXAno1u8mE8syz0LX1rFu9vYF/VAgsZVXQhgTiXNrvsJss0MWEI6x7B5jLKiAoWLB1N7/QQFQUlMJhtWPvqi2wW2zwbaZHuzu6Q65UQMFNLN3OYXdgzCvjsX/zPnyzeAMcdgeUGhW6D+mBgeNvBwSuRHc3q8WKc6cv1DpnuFgGUxVb7EhBp/fH7UP7o3P3jjAZTVAqlQgOCYJKpZQ6tBpYRK8HLCZeHV6npkWbWfsOykRERA0pOTkZffr0QUZGBoqLixEUFITExESuQKcbJtrtEB11tzwQ7bZL8/xacx9BQOX52gseAFCVkwf/lrVvNkwNx2GzI2dXBipzi5xjhrM5KMvOQ+t7bgP7Hrmf3WLD8R9+Q+HJ/32/VBYZsG/NVnR98DY4bLw7wN0UaiV2fLYdIdGhuOe5+2GuMkPjq0HOiQs4suMwOt/RTeoQvY61jh711UxGz2yZ6i1Cwzx/kSCL6PWAxUTyRsb4ZDi0AVKH0SjIjKX8OUFEVI/kcjm6dOkidRjU1AgyKHz9YTfV3hNV6acD2DrE7S7brkUQILBg63Y2o9mlgF5NdDiQu+cQWgzuI0FU3s1qNLkU0P/s6Pd7ENKmuZsjIrvFhg633IRdX/6K8uJy+AX549yRLJQVlaPLHd1gM1ulDtHr+PhqofHR1LriXJAJCArxrNYh5HlYRK8HLCZeHRYSmxaHNoDtRIiIiKjJkCnkUAeHwFJ6EaLddUW6IFdAFRgMGVehu5cgwC8uBlU5ubVO+8VEAwr+SetuZVm1vx4AUJ6dxw0TJVB64WKdc8aSCojcWNTtbFYb8s/kovPArtj/wz4cTz+CZjGh6HpHdxRm5SMgLEDqEL2OSqvCyHFDUFpkQGLPDrBabFCqlTiRcQpmoxlKtee1DyHPwoyjHrCYSETkHfLz82EwGKQOw0VWVpbLfz2JXq/nhq5E1GgIggyiQ4R/i7Yw5ufAWlYKAFDqAqANi4QoihAErnp2N4WvFtrwUBjzClzH/XzhGx0FsGDrdgqtps45mUIO8PvE7bR63zrnBJkAmYqlH3eTy+Ww2+z48vXPnWOl+aU49dtJDHvqLsiVfE3craq8Ch1vbo/vPt6CBdPegei49PsjsWcCUp6+DxWlFQiLCpE4SvJk/K6lRo191q8OrxPRjcvPz8fDj4yB1eKZvfLmz58vdQg1KFVqrF71XxbSiahRcFitECCi7PQJqAOD4BfTAiIAW0UZys4chy6+DRw2G2Rc+ew+ogjDidPwi42BX2wMys9mQbQ74BsdCaW/Py7uO4BmN7O1k7sFtGyOC7/ur3UuOKEl79iQgD6yGeQqBeyWmj2fo7q0hoybvbqdCBG/flbLnfiiiJ9XbcXD88e6PSZvJ5PJ8O2aH5C+ZS9adohDSGQzlBYZcHDPEXz42hqM/2eK1CGSh2MGSI0a28MQkbsYDAZYLWYYW/SDQ6OXOhyPJzMZgDPbYTAYWEQnokZBFB0wFeUDDjvMFwthvljoMm+6WABtWJRE0XkpUYTDbEbh7t8g99HCJzICglyGijNZsBjKIFOruRBdAlVFJYjq0xkXdhxwGdcE6xHUJhYOtg5xu9ILRejx6O3YvWKzy/XXRQQhvncH2EwWCaPzTpWllbDXsZFlZWkFrHxN3E8A8s7l47lFU3D6SCbOn8lBm06tMHLcUHyzejP3RKYrYhGdGjX2o7867Eff9PDugqvTENfJodGzhRcRURNlN1bVPWcyAmDF1q1kMmjDw2DMK4C9yojyU2dcpjUhzSDIucLW3RxmC6yVRrS5bwAMmTmwmczQRYdDplDg7I+70O7+26UO0etY/3+jxAH/HI2i0zmoKq1AcFw4/EID8McXv6DTPX0ljtD7yGSXr8gKMv7scje71YZRE0fgrZnvw1j5v81Fv/t4CybPnQCz0TPvOCbPwSI6NWrsR0/eim+KEBER1S9BJodMpYbdbKp1XqZUQZCxTYVbiSLUQYGQazSwm1xfF0Emg75NS8DBNzbcTR8fheyffkPhwZPwjw6HXKnAhZ1/wFJWieb9ukHGzfncLqRNc5xJy8C+NVvhFxoAla8Gmb8egt1iQ+8nhkHpo5I6RK/jo/eFSquCxVhzxXlAWAAU7FPvdkq1CqsWf+ZSQAcubQL74b/XYM4Hz0kUGTUW/K4lImqEeBfG1eFdGEREdLVkCgU0IeGwlte+gbQmJJz90CUg2mxo1r0zys9koSo371JhPTgI+ratYCkvh6ZZsNQheh2H1Y5Wd/fH6a/SUHY2xzke2DYW/lEhcFjZzsXdRLsDJ3661Ke+oqDUZe7Qxp3o/cQwCaLybkqVEoMmDMa3737lsgGyXCHHoMcGQ6nhGxvuZjFZkJuVX+tcuaECFWWVbo6IGhtmgUR0XWSm2v/ApJoa4lrxLgzyNvn5+TAYPOvnTlZWlst/PY1er2c/eqJr4LBZYbdaoI2MhjH3/P+KHoIAn8ho2M0myNUaFtLdSkB51jlUnc+Bb0xzhPToBgCwGMpwcd8fkKlV0ASziO5ulopKVJwvRMvhybBVmWAzW6ANDkBVQTEcNgdEO4vo7nbxTG6d3aZKsgtgrWU1NDWsitIKZP5xGqNnP4SjOw6jNL8UITEhaNOjHXau/xW3TxwsdYhex3aF/RqsZqubIqHGihlgPWAx8erwOjUNer0eSpUaOLNd6lAaFaVKDb2em1ESXY/8/Hw8/MgYWC2e2adw/vz5UodQK6VKjdWr/stCOtFVEh0OmAtyoW4WCl3rDnD8/88cmUoNa2U5LBcLoPTzB/+EciPRAYfJDNFuR0VmFioyXd+0FAGIDhZs3U2Qy5G7+yAAQOGjgUypgLW8EqJDRECraMQO7ClxhN5H5A67HsdcacKRXw7h+K5jaNOjLULjwlCaX4K1L62B6HDAamLB1t18/X3g46dFVYWxxpxcLkdQWKAEUVFjwgzwBrCYeO1YSGz8wsLCsHrVfz1yRej8+fMxc+ZMxMbGSh1ODVwRSnT9DAYDrBYzjC36waHh75CrITMZgDPbYTAY+LOH6GoJAjShEbAbq1B2IRuo3vTN4YAmJByaZmGAwI3g3EomgzokGMb8glqnNcGB7FMvAUPm/1q42KpcewuXnj6PmAE93B2S12vWMhIQUOtq9KC4MMjZf9vt/IN1gCDAbrXh6I7DLnMqrQpqH7VEkXkvra8GDz51L5a/urrG3LBH7oCK+znQFfAn6Q1gMfHasZDYNISFhXns6xgbG4s2bdpIHQYRNQCHRs82RkTUYASZHIJCAVPR//dLdTicc6bCPPi3aAOZnAVbtxJFaMNCUXbyDBzmv9yNJAjQtW6JOntYUIMRZELdcwJc+j+T+7Qd1A3Hf9jnMiZXKXDTyD6XCuzkVgqVAom3dULG1gM15nqN7MONRSVgNVvRJrElpr3+FL5Y/jXOnclBWFQIhj9yJ1q0j4WN+znQFfC79gaxmEhERERE1DSYCmvfcKx6zjfGl7UodxIBh9WKkB7dUHbyFIx5l1akqwL0CGjfFhAEiH96s4PcI7BVNHJ3Hax9rm0sBDnv2HC3styLkMlk6DVhMLJ2H4WprApBsWGI6tIKh77aie6PDJI6RK9js1jRtld7BIQGYt+mPagsrYQ+NAA9RyTBP1jHgq0EzCYL5k16Awnd2uGJ2eOgUClgt9nxw7qf8J9X/ov5H82WOkTycCyiU6PGPutXh9eJiIiI6AocDojWujffc9isXGHrbsKlIjpEwC8+Fv4t4gFRhCiKkCkVMBYUwS/Os+689QaWCiOadWyFokOnXMYVPhqE3NQGop1vbLibqbwKR7/fC7WfFs27tII+KgRleRfxyzsbIDpEviYSqCy9tE+AIBdw65hBUGlVMFUYYa4yw1xpgqXKM/f6acpMVSb0H94H/YffghMZp3D2xDlExobjjvsHICImHIZiA4DmUodJHoxFdGqU2I/+2rEfPREREVHdBLkccl8/2M2mWucVPn4QZFxh61aCAIVGi4sHMiAIAnwiwwFBBvPFizCXlCKsT0+IdhsA9hZ2J3NpObTBerQY1hfFRzNhM1mgiwmHX1Qozm37Da3vvlXqEL2OPvJSuztzhRGnf3G9S0Dt7wOZgq2o3E0Xosd/pr6HhFs6IiQ6FA6HAxo/LTIPnMHZg2cwdsFEqUP0On4Bfuh9e0+89MQCGIrLnOMaHw2eW/Q0AoJ0EkZHjQGL6NQosR/9tWM/eiIiIqK6iQ4H1AHBsJRcrLniXJBBpQ+EKIps5+JODgfsViv0rVvCWlmJinMXINrt8AkPg198LEzFpdCGcq8Md9O3iMKhFV9B6aNBYOsYaIL0KD+fj5z0DEQmJQKX6ZlODUPtp0VgTChKsmtuwtv+zpshV7D0424yuRzdBt+M4gtFUPuqofbVwGioQnlxOZIfuBVyBd+UdTcBAt576UOXAjpwaYX64hnvI3XZPyWKjBoL/iSlRov96IlICjJjqdQhNAq8TkTU2IgOO0zFhfCLaQFjfg7sJiMAQK71gTYsEqbiQviENwe4uaj7CAIqz51HZdY5qAL08I2MAGQymIsuouzUGSh1/tCGsIjudqKIFkP64Mx3O1Bw4Lhz2C86DIGtYyQMzHvZrTZ0urcvTqcdxPn9py69Kejvg7aDukIXEQQH2M7F3QwFJUi8rRPyz+Rj8/vfoTS/BCExoUh+6DYoNUpUGaoQEBoodZheparCiKyT52udK71oQFlJOSJjw90cFTUmLKITETVC7HN/dRriOmkz0+r9nERE5AFkMsiVKkAmgzY8ynVOECBXawC2c3E7h+lS32BLqQGWUtff63azBSLYp97dHFY75BoV2o4aBOPFUtiMZvhFNIPdaoPNYoXCVyN1iF6n5FwBtHo/hLSJQnT3NhAdjku90AEUnjwPjc5H6hC9jn+QDn9s3Y/09b86x3JP5eDTl1ZjyOS7ENe5hYTReSerxXrZeZORferp8lhEJyJqRLgfwLWr7/0AjPHJcGgD6u18TZXMWMo3HIioUZErlFAFNUNF5kk4LK5/SMvUavjHtmZLBHeTyaAND4Uxv2aLCgDQNAuGIPCNDXdTaFUoOnIGgS2bQ65SQiYTIEKEtcoItc6X7VwkEBgdip8WfIaYm9si4qZ4AJdWp5/ZcQgmQxXieydIHKF32vXlzlrHf/poC8bd9Dc3R0P+AX5Qa9Uw11IsF2QCmoUHSRAVNSbMAomIGhHuB3Dt6ns/AIc2AA5f3jouBbaIuXq8VkTXThRFWMtKahTQAcBhNsNaUQa5hits3cpuhyY8FPJjatjNf3ldBAH6dq0h/rV/PTW4/D9OIrRzGxQdOoWy7DxABJQ+akTd0gVFh08jvFsHqUP0OjazFREd43A2/QjOph9xmUuaOAQOB79P3K00vwSio/Y2OqYKI4zlRjdHRDKZgKEPDcIXy7+pMdd/eB/ueUJXxCI6EVEjw/0AyFtxZTsRNSSH1QpLSXGd8+bSi1DpAyFTKt0YlXeTKRRwWKxodnMXlJ06A2PepRXpqsAABLRrDYiAIOdKdHdTqBQ4tOIrhHVrh7iBvSDIBJhKynBq4zbYzRaEd2cR3d1EuwPNu7RCQPMQnE7LgKm8CkGxYWh3e3fkHc2CPpILQNxNobr87wpuLOp+huJyyBVyTHxhDMoNFfDT+6GyogpKpRJKlQIFOUWIio+UOkzyYCyiExERUaPAVjpXj+10iK6HCFymNYgAgaue3cwhiqg6n4Oyk6fgGxuNkF7dARGwVlTg4oFDUOn9Edj5JqnD9DqBrWNw4dcDyP/tKPJ/O+oyF969A2RKlhncTa5W4uj3e6Hy1SJheBJUPmqU5RZj/7rtaNWvE7jE1v38Av2g8dPCVFFzxXlw82ZQadUSROXdfP19UFJUiuiWUdj+7U6cz8xFWFQzDH5gIPLOFaD1TexTLzWb1Qa5Qg5B8MwfWvzt5iFMJhOys7Pr5VxZWVku/60PMTEx0PD2VSIikhBb6RBRgxJkUAUEwWisrHVaFRjksX/UNVl2O8wXi+Gw2lB+KhPlpzJdps0OO1BHuwRqODKlEnGDeuHsll0u474RzRDapS0LthJQalTo+uBtOLppD/at2QoAUKiVaNW/E4JbREAml0scofdRqBQY+ey9WDf/E9htdue42keN4VPuhkLFcpy7aXw0iG8bi4X/XOIcO1NWiXdTl+Oex4ZD66uVMDrvduF8HnZu34PDGccQGBSAoSMHIqJ5OHx9PWtTZH7Xeojs7GxMnDixXs85f/78ejvXsmXL2KKBiIiIiJosASLkKhXkWl/Y/1JIV/j4QaZQguvQ3UuQyyH3qbuoodBoIMjYEsHdSk6chW9ECBIeGYrSszmwG83wjwmHOsAP2dt+Q+ytN0sdotexGs3YseQrtEi+Ca36d4LD7gBEEVl7juNs+hHc+uwoqUP0PsKlvTbGL3wcR3cewcXzhYhsFYWW3VqjqqySG1VLwGK24ON31tc699VHm3DLnb3cHBEBwNnT2di983c0CwlGbHw0goIDcPpkFs5l56LXLd2g1XrOgl7Jv2vfffddLFiwAHl5eejUqRPefvtt9OjRo9ZjrVYrXnnlFXz00Ue4cOEC2rZti3//+9+48847nceUl5dj9uzZ+PLLL1FQUIAuXbpg8eLFuPlmz/5FHhMTg2XLlkkdRp1iYmKkDoGIyCPITJ61qaun4nUiapy8OTcX5ApYygzQBIdAdATDWlYKAFDqAyAIMlgqyuHrr5c2SC8j2u3wj49FRWbtd9jq2rTiGxsSsFQYcW7tZkQk3YRm7eIBuQym4jKc2rANpuIyxNxW+88Majgl5wphNVlw/Id9OI59NebtVpsEUXk3S5UF545kIyQmBGofNeISW8BcZUJx7kWc3HscSffcAr9AP6nD9CrGSiMqy2q/28xmtaGksARRceFujsq7GUrLUVhwEd98+QP+2HfYOa4P0OHl159HabEB2igW0QEAn376Kf7xj3/gvffeQ8+ePbFo0SLccccdOH78OEJDQ2scP2vWLKxevRoffPAB2rVrh82bN+Puu+/Gzp070aVLFwDAY489hkOHDmHVqlWIjIzE6tWrMXDgQBw5cgRRUVHufopXTaPRcKU3EZEH0+v1UKrUwJntUofSaChVauj1LDg1Bfn5+TAYbvyNEbPZjLy8vHqIqGGEh4dDrb7xHqV6vd5jN4C+HG/PzQWZDJqQMJSdOAKZSgWlnw6ACFNhHhxWK3StO3DVs5tdut4CAm/qgJJDR4E/9aT3i42GwscHwmX62FPD0MdHQh8XgdJT53F41bdwWG3wiwpFdP/uKMvOY9sjCWgD6i7GyuQyyBRs5+JupQWl2Pn5L9A106Fj/06Qy2WoKK5A+hc7YCyrQpdB3aQO0evIrvA7XMH9HNyusqIS69d+41JABwBDaRlmPfsK/vPJm4iI8pycWtKvkIULF+Jvf/sbxo0bBwB477338O233+LDDz/E888/X+P4VatWYebMmRgyZAgA4Mknn8SPP/6IN954A6tXr4bRaMT69euxceNGJCcnAwDmzJmDr7/+GkuXLsW8efPc9+SIiKhJCQsLw+pV/62XQmJ9ysrKwvz58zFz5kzExsZKHY6L+i4kcnX71avPa5Wfn4+Uhx+BzWqpt3M2dQqlCmtWr2p0hXTm5oBcpYJ/izaoPJ8Jc3EhAECmUsO/RRvIVdwEzu1EEWWnTkO02RGa1AO2ykqIdgeUen+YCopw8fcDCO3NVc/upvL3xZlvfkFVQbFzrOJCAU5++TPaP3gn7w6QgH9YABQaFWymmr+ro7q0gpz9t91O63+pFVVZURl2fv5LjXmlRuXukLyexkeNsKgQ5F8orDHn6+8DHe8McDuTyYQfvt1W61yZoRwXzuWiXUJr9wZ1GZL9JLVYLNi3bx9mzJjhHJPJZBg4cCDS09Nr/Ryz2Vxjc0utVotff/0VAGCz2WC32y97DBER0fUKCwvz2KJYbGxsk72jiXcBXJ/6uhPAYDCwgH6NbFYLDAaDx/68qA1z80sEmRxKP3/4t2wH0WYDBAGCXAG5Uil1aF5JFEU4LBYY8wpgulgM3+hICDIZyjOyYSuvgEythuhgydbdzIZylwK6kyji3PZ9aDmsr/uD8nKG80XoMWYQ9nz0A2xmq3M8IDoEsT3bw1plBoIkDNALaf200IcGwFBQWmMuukMMNxaVhIAJzz+MN6a/C/Of3nCSy+V4bMYj3KdaAnabA7bLtJsqvljqvmCugmTftUVFRbDb7TX+uAgLC8OxY8dq/Zw77rgDCxcuRHJyMlq2bImtW7fiiy++gN1+aadjf39/JCUl4eWXX0b79u0RFhaGTz75BOnp6WjVqlWdsZjNZpjNZufHZWVl9fAMiYiIqD7wLoDrU993Ahjjk+HQBtTb+ZoqmbEU2sw0qcO4ZszNXcmVKkDJVYJSk8nl0IaFQhMSArlahaqcPIgOO3Qt4iBTqWDML4TANhVuV3a27rZcFRcK/tx1h9zEbrXhxNaD6DHuDpjLqmAqq4IuIgjmCiN2f7gJt067X+oQvY7dZsd9LzyAtXNWo7K0wjkeGBGEIZPvcv6uJPexWW1Yt2wjnvn3JBz9/TjOnclBWFQIOiV1xPefbcUDT94tdYheR61RIzBIj5Li2v/Oa9U23s0RXV6jeutr8eLF+Nvf/oZ27dpBEAS0bNkS48aNw4cffug8ZtWqVRg/fjyioqIgl8vRtWtXPPjgg9i3r+bmGtVeeeUVzJ071x1PgYiIiK4D7wLwAOxxe3W86DoxNyd30IaFouTQUVTl5DrHjHkFUOp0CO3VXcLIvJfCp+7WRjKVAmBDF7cLjA1DSfZW7HzvG2gDfKH00aDqYhlsZivC2sewnYsElBolHHYRD859BGWFBhTnFiMkJgQ+el/I5DLusSEBU5UJJw+ewatTFqF9lzYIiWyG85k5+P6zrRAdIoY8OEjqEL2OKIp4ZML9eGvBBzXm2ndsA5mH7Xsi2U/SZs2aQS6XIz8/32U8Pz8f4eG174YbEhKCDRs2wGQy4eLFi4iMjMTzzz+PFi1aOI9p2bIltm/fjsrKSpSVlSEiIgKjR492OeavZsyYgX/84x/Oj8vKyhAdHX2Dz5CIiIio8WM7nWvXGDfVZW5OHkkQYKsyuhTQq1nLylB5IRd+cTESBObdAlvH4MIv+2udC7mpNWRq3sXhbnKVAl1G98Pva3+GsbQSxtJKAIBG74uOw5P+/80NcifRIeKzeWtQfOEimreLRnjLSGT8dAAFmXmI79wSQyYNkzpEr6Px0UAQBIiiiKP7T+Do/hMu87rLbNBLDcNmtcEhOvD36Y/hvx98BkNpGeRyOW69vQ9G3j8EuTn56NQtQeownST7SapSqdCtWzds3boVI0eOBAA4HA5s3boVTz311GU/V6PRICoqClarFevXr8f999e8NcnX1xe+vr4oKSnB5s2b8dprr9V5PrVaDbWaGwURERER/VV9ttOpboHjqeqrNU99t9JxB+bm5IkEQUB55tk65ysys+AbHQmAXy/uFjuwJ7J+3O0y5hMWhPDuHeAwWwFfrUSReafizHyEto1Gv6fvQc7BTJjKKhEUG4aguHDI1QpYyqrgq2eB0J2M5UYIgoB7nrsf5iozDAWl6DWyNwQB+GnlFlhM1iufhOqVSqNC9+TO2Lu95puALdrHQuOjqeWzqCFpfbXYt/sPOBwinpvzd6hUKsjkMqSn7cWMKfOw8vO3pQ7RhaRvR/7jH//Ao48+iu7du6NHjx5YtGgRKisrMW7cOADAmDFjEBUVhVdeeQUAsHv3bly4cAGdO3fGhQsXMGfOHDgcDvzzn/90nnPz5s0QRRFt27bFqVOnMH36dLRr1855TqK/MplMyM7OrpdzZWVlufy3PsTExNTYkIuIiMid6qudTkxMDJYtW1YPETUMb/+dy9ycPI3D4YB4mZ3eRIednUMk4LDZ4B8XiY7jRqDkRBasRhMCWjSHJkgHm8UKBVeiS0BE+rJv0WV0f7ToexPgcAAyGS6eycG+T7bi9pkPSx2g17FZrBg04U5sfPMLGMuqnOMBYQEYNuVu2C+zmSI1DJvNhltH9oXZZEHG7sPO8VYJ8Rj1xAg47NxZ1N2CmwVi8rPj8ewTqXhh6v8W2sjlcsx+5Vno9P4SRleTpEX00aNHo7CwEC+++CLy8vLQuXNnfP/9984/0rKzsyH7U58ok8mEWbNm4cyZM/Dz88OQIUOwatUqBAQEOI8xGAyYMWMGzp8/j6CgINx7772YP38+lEqlu58eNRLZ2dmYOHFivZ6zPlfZLVu2zDt67RIRUZOn0Wj4O82DMTcnTyOTyeATGQFjbn6t89rwMAgKtqlwN5lcjkP/+RIqvR9i+neHn1qJkpPZKPj8OCJ6dkRYt/ZSh+h1AmNCUVFowLY319eYi+zcEgo1f+a6m1+QPz5+8b8uBXQAKM0vxS+f/Iy7nrlHosi8V0VpJRY9/x6GPXw7Bj84EKYqE9RaNc6dvoC3Zn6Ap+f9DVHxEVKH6VXUahWimkdi/psv4OTxTBzJOI5moUHo1bc7IqPCEBYeInWILiTPOJ566qk6bxHdtm2by8f9+vXDkSNHLnu++++/v9ZbSInq0hhWxTVVnn4XAMBViURE5F2Ym5MnEWQyqIMCodLrYDGUuczJVCr4t4yHQsNWLu5WeuYCAMBiqMCpjdtc5goOHEdol7YSROXdBLkMvf42GOnLvoPDZneO+4cF4qYRvSHCeza99hSmChPKCmtvhXf+2DnYLFyJ7m4qtQoWswVfLP8GACDIBIiO/93OpPXl3/1SCA4JhEIpR2TzcHTv2QkqjQq+Pj4IDW8mdWg1SF5EJ5IaV8VJx9PvAgB4JwARERGRlOQaNYK6JMKYm4/K8zkQHXZow8PgF9Mcci0LHlKwVlTVOWc3W12KUuQeRacuwGSowsDnH0DBifMwllQguEUE/Jrp8dt/t6D7mEFSh+h1/roC/a8sRrObIqFqGq0Ksa2bI+vkeQBw+VkVEKyHn477BkhFH6CDPkAndRhXxCI6EUnG0+8CAJr2nQBEREREnk6uUgH+fpCpVFA3C740ptVArlZBwQ1oJaGPj0L+vqO1zvlGNINcxdYh7uaw2nFwww4c/mYX4m/pCK3OF2d+OYi8I5fu0hXZ69nt9GEBdc4p1Epo/Lj5rruJoognXhyPV55+E2Ul5c5xjY8Gz7z6JByX2YODCGARnYgkVF93AdjtdmRkZKC4uBhBQUFITEyEXC6vhwiJiIiISGpylQpylQoqf64S9ATakABomwXAWFRaYy7mtpuh8vNxf1BeLjAmFADgsNlxetsfLnMB0SGQKfi3kbspNSp06NsRR345VGOu54gkqH35JqC7yZUKbFn1Pf755tPIO1eAM0fPonl8JOLaxmDzp1tx94RhUodIHo5FdCJq1NLS0rBkyRLk5eU5x8LDwzFp0iQkJydLGBkRERERUdOj0fuj9T0DkJP+By4eyYRot8MnLAgx/W+GNlgvdXheSRRFtOyXiNPbM1zGZQo5Eob2gowLjNzOZrai/yMDoQ/RY9+mvbAYLdDqfND73r5o06MNzFVm+AdJHaV3CYsKwZCU2/HmP5fCZrMhMi4CGbsOw1hpxLQ3/o7gsECpQyQPxyI6ETVaaWlpSE1NhUqlchkvKSlBamoq5s6dy0I6EREREVE9MpdV4sS6LfCNaIaWw/oCAmAuKUfm9zsQf2dv6OOjpA7R6yg1Kvg10+PmRwYhM/0ITGWVCIoLQ1zPDijOzkdAdIjUIXqdipJyrJ27GiOfvQ+dBnaF3WaHXClH1uGzWPrk2xj/Rv3uDUZXJygkANPeeAr55wuRk5WH0KhmiIwJh3+AH1Rq1ZVPQF6NRXQiapTsdjsWLlwIURTRtWtXPPzww4iPj0dmZiZWr16N9PR0vPnmm+jTpw9bu9TBZDIhOzu7Xs6VlZXl8t/6EBMTA42GG4YREREReZLKvCKYSspgKinDxSNnXOayf96LdqFBUPqy37M7lZwvgn9YIA5+tRPh7WOh8tXAkHMRx7fuQ6vkTrCaLFKH6IUE2K12rH/10zqmBfeGQxBFEacPn8Ub09/FyHFD0bxlJApzirAk9T8Y98+HkTSwO5Tc04Eug0V0ImqUDhw4gNLSUtx0002YP38+ZDIZACAhIQHz58/HlClTcPDgQRw4cADdunWTOFrPlJ2djYkT63cFxPz58+vtXMuWLauXnvlEREREVH/KzubWOVdVUAK7xcoiupvJZAIyvvwV7Qf3AACYK4yI7tYaZbnF2P3h97h9dorEEXof/2AdFGolbGZrjTldMx3UPuyJ7m4lhaVYMudDmIxmrF3yhcvcf/71X7Tv0hohEc0kio4aAxbRiahROnDgAABg7NixzgJ6NZlMhrFjx+LZZ59lEf0yYmJisGzZMqnDqFNMTIzUITQY3gUgHU+/9kDTvv5ERNT4Kf3r3jhUoVUDohuDIQBAYGwYKgoN2P3h91ColVBqVTCXG+GwOxDVuSXUfnxTw92sJjNufWQgtvxnk8u4TC7DbWNvh93mkCgy71VWUo6SWjZEBgCzyYLi/BIW0emyWEQnokZN4G1w102j0XClt0R4F4B0PP3aA037+hMRUeMXEB+JC7/8DtFRs1oe0qkNZGyH4HZavR96Pz4MO5Z+DZvZ6lz97NtMh073JUOp5apndzNVmFBwNg+jZj6Igz//gdL8EoTEhCKhXyL2fr0L/R4OljpE+gu+/0dXwiI6ETVKnTt3xqpVq7BixQp07tzZZTW6w+HAypUrnccReRreBSAdT7/2QNO+/kRE1PjJtWrED+6DzO/TIdrtznF9iygEt4uD0pd3U7mbXClHWLto3DlnDPKOnEVlURlC2zZHQPMQ+AT6Sx2eVwoID8TBbRk4uuMI2vfugJZdW6M0vwTr5n8CtVYFP72f1CF6HV2gPwKbBdS6Gl2tUSE4LND9QVGjIoiiyDdb/qKsrAx6vR4GgwE6nU7qcIioFna7Hffeey9KS0uRlJRU68aiAQEBWL9+PTcWJSIij8Jc89rwehF5FtHhQGVhCawVVbAYKmAzWeATcqn45BcZwn7oRAAsJgt++2Y3fvpoS425e567H+2SOkAml9XymdRQRFHEwd1H8MqURXDYXdvpTJ47AUmDbubGol7qanNNFtFrwUSdqHFIS0vDiy++CLVaDbPZ7Byv/vill15CcnKyhBESERHVxFzz2vB6EXkeURRhKa+CrcoEh80Gpa8WSh8N5GqV1KEReYyq8irknDiPtI+3oTS/BKFxoeifMgAhsWHcWFQiFrMF+ecL8c3qzcg8loWI2HCMeHQwImLCoeVdNF6LRfQbwESdqPFIS0vDu+++i/z8fOdYeHg4Jk2axAI6ERF5JOaa14bXi4iIGrOqsirYrDYo1UpoucmrR7CYLTAZzVBrVFBr+IaGt7vaXJM90YmoUUtOTkafPn2QkZGB4uJiBAUFITExkS1ciIiIiIiISHI+Oh+pQ6C/UKlVUPHOGbpGLKITUaMnl8vRpUsXqcMgIiIiIiIiIqImiLsYEBERERERERERERHVgUV0IiIiIiIiIiIiIqI6sIhORERERERERERERFQHFtGJiIiIiIiIiIiIiOrAIjoRERERERERERERUR0UUgfgiURRBACUlZVJHAkRERERNTXVOWZ1zkmXx9yciIiIiBrK1ebmLKLXory8HAAQHR0tcSRERERE1FSVl5dDr9dLHYbHY25ORERERA3tSrm5IHIJTA0OhwM5OTnw9/eHIAhSh3PNysrKEB0djXPnzkGn00kdjlfhtZcOr720eP2lw2svHV57aTXm6y+KIsrLyxEZGQmZjN0Vr0Sq3Lwxf401VXxNPA9fE8/D18Tz8DXxTHxdPI9Ur8nV5uZciV4LmUyG5s2bSx3GDdPpdPxBIBFee+nw2kuL1186vPbS4bWXVmO9/lyBfvWkzs0b69dYU8bXxPPwNfE8fE08D18Tz8TXxfNI8ZpcTW7OpS9ERERERERERERERHVgEZ2IiIiIiIiIiIiIqA4sojdBarUaqampUKvVUofidXjtpcNrLy1ef+nw2kuH115avP7U0Pg15nn4mngeviaeh6+J5+Fr4pn4ungeT39NuLEoEREREREREREREVEduBKdiIiIiIiIiIiIiKgOLKITEREREREREREREdWBRXQiIiIiIiIiIiIiojqwiE5EREREREREREREVAcW0ZuQpUuXIjExETqdDjqdDklJSdi0aZPUYXmdV199FYIgYOrUqVKH4hXmzJkDQRBc/rVr107qsLzGhQsX8PDDDyM4OBharRY33XQTfvvtN6nD8gpxcXE1vvYFQcDkyZOlDq3Js9vtmD17NuLj46HVatGyZUu8/PLL4F7t7lFeXo6pU6ciNjYWWq0WvXv3xt69e6UOi5oQ5tSejbm2Z2AO7pmYm3sW5uueh3m8Z2os+b1C6gCo/jRv3hyvvvoqWrduDVEU8dFHH2HEiBHYv38/EhISpA7PK+zduxfvv/8+EhMTpQ7FqyQkJODHH390fqxQ8EebO5SUlKBPnz649dZbsWnTJoSEhODkyZMIDAyUOjSvsHfvXtjtdufHhw4dwqBBgzBq1CgJo/IO//73v7F06VJ89NFHSEhIwG+//YZx48ZBr9fj6aefljq8Ju+xxx7DoUOHsGrVKkRGRmL16tUYOHAgjhw5gqioKKnDoyaAObXnYq7tWZiDexbm5p6H+brnYR7vmRpLfi+IfLulSQsKCsKCBQswYcIEqUNp8ioqKtC1a1csWbIE8+bNQ+fOnbFo0SKpw2ry5syZgw0bNuDAgQNSh+J1nn/+eezYsQO//PKL1KEQgKlTp+Kbb77ByZMnIQiC1OE0acOGDUNYWBiWL1/uHLv33nuh1WqxevVqCSNr+oxGI/z9/bFx40YMHTrUOd6tWzcMHjwY8+bNkzA6asqYU0uPubZnYQ7ueZibez7m69JjHu95GlN+z3YuTZTdbsfatWtRWVmJpKQkqcPxCpMnT8bQoUMxcOBAqUPxOidPnkRkZCRatGiBlJQUZGdnSx2SV/jqq6/QvXt3jBo1CqGhoejSpQs++OADqcPyShaLBatXr8b48eOZkLtB7969sXXrVpw4cQIA8Mcff+DXX3/F4MGDJY6s6bPZbLDb7dBoNC7jWq0Wv/76q0RRUVPGnNpzMNf2PMzBPQtzc8/GfN0zMI/3PI0pv+f9Vk3MwYMHkZSUBJPJBD8/P3z55Zfo0KGD1GE1eWvXrsXvv//ukT2bmrqePXti5cqVaNu2LXJzczF37lz07dsXhw4dgr+/v9ThNWlnzpzB0qVL8Y9//AMvvPAC9u7di6effhoqlQqPPvqo1OF5lQ0bNqC0tBRjx46VOhSv8Pzzz6OsrAzt2rWDXC6H3W7H/PnzkZKSInVoTZ6/vz+SkpLw8ssvo3379ggLC8Mnn3yC9PR0tGrVSurwqAlhTu1ZmGt7Hubgnoe5uWdjvu4ZmMd7nsaU37OdSxNjsViQnZ0Ng8GAzz//HP/5z3+wfft2Jv0N6Ny5c+jevTu2bNni7M/Yv39/3mIqkdLSUsTGxmLhwoW85bqBqVQqdO/eHTt37nSOPf3009i7dy/S09MljMz73HHHHVCpVPj666+lDsUrrF27FtOnT8eCBQuQkJCAAwcOYOrUqVi4cCH/SHWD06dPY/z48UhLS4NcLkfXrl3Rpk0b7Nu3D0ePHpU6PGoimFN7DubajQNzcOkxN/dszNc9A/N4z9RY8nuuRG9iVCqV852abt26Ye/evVi8eDHef/99iSNruvbt24eCggJ07drVOWa325GWloZ33nkHZrMZcrlcwgi9S0BAANq0aYNTp05JHUqTFxERUaOY0L59e6xfv16iiLxTVlYWfvzxR3zxxRdSh+I1pk+fjueffx4PPPAAAOCmm25CVlYWXnnlFSbfbtCyZUts374dlZWVKCsrQ0REBEaPHo0WLVpIHRo1IcypPQdz7caBObj0mJt7LubrnoN5vGdqLPk9e6I3cQ6HA2azWeowmrQBAwbg4MGDOHDggPNf9+7dkZKSggMHDjCpd7OKigqcPn0aERERUofS5PXp0wfHjx93GTtx4gRiY2Mlisg7rVixAqGhoS6bsFDDqqqqgkzmmkLJ5XI4HA6JIvJOvr6+iIiIQElJCTZv3owRI0ZIHRI1YcyppcNcu3FgDi495uaei/m652Ae79k8Pb/nSvQmZMaMGRg8eDBiYmJQXl6Ojz/+GNu2bcPmzZulDq1J8/f3R8eOHV3GfH19ERwcXGOc6t+0adMwfPhwxMbGIicnB6mpqZDL5XjwwQelDq3Je+aZZ9C7d2/861//wv333489e/Zg2bJlWLZsmdSheQ2Hw4EVK1bg0UcfhULBX+nuMnz4cMyfPx8xMTFISEjA/v37sXDhQowfP17q0LzC5s2bIYoi2rZti1OnTmH69Olo164dxo0bJ3Vo1EQwp/YszLU9E3Nwz8Pc3DMxX/cszOM9U2PJ7/kd3IQUFBRgzJgxyM3NhV6vR2JiIjZv3oxBgwZJHRpRgzl//jwefPBBXLx4ESEhIbjllluwa9cuhISESB1ak3fzzTfjyy+/xIwZM/DSSy8hPj4eixYt4qYsbvTjjz8iOzubSZ+bvf3225g9ezYmTZqEgoICREZG4vHHH8eLL74odWhewWAwYMaMGTh//jyCgoJw7733Yv78+VAqlVKHRk0Ec2qiK2MO7nmYm3sm5uuehXm8Z2os+T03FiUiIiIiIiIiIiIiqgN7ohMRERERERERERER1YFFdCIiIiIiIiIiIiKiOrCITkRERERERERERERUBxbRiYiIiIiIiIiIiIjqwCI6EREREREREREREVEdWEQnIiIiIiIiIiIiIqoDi+hERERERERERERERHVgEZ2IiOrdnDlz0LlzZ+fHY8eOxciRIyWLh4iIiIjIGzEvJyKqHwqpAyAioqZv8eLFEEXR+XH//v3RuXNnLFq0SLqgiIiIiIi8DPNyIqLrwyI6ERE1OL1eL3UIRERERERej3k5EdH1YTsXIiIvU1lZiTFjxsDPzw8RERF444030L9/f0ydOhUAIAgCNmzY4PI5AQEBWLlypfPj5557Dm3atIGPjw9atGiB2bNnw2q11vmYf75tdOzYsdi+fTsWL14MQRAgCAIyMzPRqlUrvP766y6fd+DAAQiCgFOnTtXHUyciIiIi8hjMy4mIGg8W0YmIvMz06dOxfft2bNy4ET/88AO2bduG33///ZrO4e/vj5UrV+LIkSNYvHgxPvjgA7z55ptX9bmLFy9GUlIS/va3vyE3Nxe5ubmIiYnB+PHjsWLFCpdjV6xYgeTkZLRq1eqa4iMiIiIi8nTMy4mIGg8W0YmIvEhFRQWWL1+O119/HQMGDMBNN92Ejz76CDab7ZrOM2vWLPTu3RtxcXEYPnw4pk2bhs8+++yqPlev10OlUsHHxwfh4eEIDw+HXC7H2LFjcfz4cezZswcAYLVa8fHHH2P8+PHX/DyJiIiIiDwZ83IiosaFPdGJiLzI6dOnYbFY0LNnT+dYUFAQ2rZte03n+fTTT/HWW2/h9OnTqKiogM1mg06nu6HYIiMjMXToUHz44Yfo0aMHvv76a5jNZowaNeqGzktERERE5GmYlxMRNS5ciU5ERC4EQYAoii5jf+6rmJ6ejpSUFAwZMgTffPMN9u/fj5kzZ8JisdzwYz/22GNYu3YtjEYjVqxYgdGjR8PHx+eGz0tERERE1NgwLyci8hxciU5E5EVatmwJpVKJ3bt3IyYmBgBQUlKCEydOoF+/fgCAkJAQ5ObmOj/n5MmTqKqqcn68c+dOxMbGYubMmc6xrKysa4pDpVLBbrfXGB8yZAh8fX2xdOlSfP/990hLS7um8xIRERERNQbMy4mIGhcW0YmIvIifnx8mTJiA6dOnIzg4GKGhoZg5cyZksv/dmHTbbbfhnXfeQVJSEux2O5577jkolUrnfOvWrZGdnY21a9fi5ptvxrfffosvv/zymuKIi4vD7t27cfbsWfj5+SEoKAgymczZg3HGjBlo3bo1kpKS6u25ExERERF5CublRESNC9u5EBF5mQULFqBv374YPnw4Bg4ciFtuuQXdunVzzr/xxhuIjo5G37598dBDD2HatGkut27eddddeOaZZ/DUU0+hc+fO2LlzJ2bPnn1NMUybNg1yuRwdOnRASEgIsrOznXMTJkyAxWLBuHHjbvzJEhERERF5KOblRESNhyD+tcEWERF5nf79+6Nz585YtGiR1KHgl19+wYABA3Du3DmEhYVJHQ4RERERkdswLyci8kxs50JERB7BbDajsLAQc+bMwahRo5ioExERERFJgHk5EVFNbOdCREQe4ZNPPkFsbCxKS0vx2muvSR0OEREREZFXYl5ORFQT27kQEREREREREREREdWBK9GJiIiIiIiIiIiIiOrAIjoRERERERERERERUR1YRCciIiIiIiIiIiIiqgOL6EREREREREREREREdWARnYiIiIiIiIiIiIioDiyiExERERERERERERHVgUV0IiIiIiIiIiIiIqI6sIhORERERERERERERFQHFtGJiIiIiIiIiIiIiOrAIjoRERERERERERERUR1YRCciIiIiIiIiIiIiqgOL6EREREREREREREREdWARnYiIiIiIiIiIiIioDiyiExERERERERERERHVgUV0IiI369+/P/r37y91GC7y8/Nx3333ITg4GIIgYNGiRVKH5BX++rVw9uxZCIKAlStXShYTEREREdWOeTxVYx5P5H1YRCeiRmnlypUQBMHlX2hoKG699VZs2rRJ6vAaRFVVFebMmYNt27bV+7mfeeYZbN68GTNmzMCqVatw55133vA558yZA0EQUFRUVOt8XFwchg0bdsOP09R99913mDNnjtRhEBERETWonTt3Ys6cOSgtLa0x969//QsbNmxwe0z1hXm8d2IeT9S0KKQOgIjoRrz00kuIj4+HKIrIz8/HypUrMWTIEHz99ddNLrGrqqrC3LlzAaDeV8D89NNPGDFiBKZNm1av56VrExsbC6PRCKVS6Rz77rvv8O677zIBJyIioiZt586dmDt3LsaOHYuAgACXuX/961+47777MHLkSEliu1HM45s+5vFETR+L6ETUqA0ePBjdu3d3fjxhwgSEhYXhk08+aXJF9IZUUFBQ448Vcj9BEKDRaKQOg4iIiKjJM5lMUKlUkMka9w36zOM9A/N4oqavcf+2ICL6i4CAAGi1WigUru8RVlZW4tlnn0V0dDTUajXatm2L119/HaIoAgCMRiPatWuHdu3awWg0Oj+vuLgYERER6N27N+x2e52PW91eJi0tDY8//jiCg4Oh0+kwZswYlJSUXDHugoIC5xsAGo0GnTp1wkcffeScP3v2LEJCQgAAc+fOdbawudKqhjNnzmDUqFEICgqCj48PevXqhW+//bZG3KIo4t1333Wety7Vvf5ef/11vPnmm4iNjYVWq0W/fv1w6NChKz7PazVs2DC0aNGi1rmkpCSXN1C2bNmCW265BQEBAfDz80Pbtm3xwgsvXPExzGYznnnmGYSEhMDf3x933XUXzp8/X+P6jh07FnFxcTU+v/p21z9bsWIFbrvtNoSGhkKtVqNDhw5YunTpFWP5ay/FsWPH4t133wUAl9ZFoigiLi4OI0aMqHEOk8kEvV6Pxx9//IqPR0RERFSX8vJyTJ06FXFxcVCr1QgNDcWgQYPw+++/uxy3e/duDBkyBIGBgfD19UViYiIWL17snM/IyMDYsWPRokULaDQahIeHY/z48bh48aLzmDlz5mD69OkAgPj4eGfOU50bVVZW4qOPPnKOjx071vm5Fy5cwPjx4xEWFga1Wo2EhAR8+OGHLjFu27YNgiBg7dq1mDVrFqKiouDj44OysjLm8czjXcaYxxNRXbgSnYgaNYPBgKKiIoiiiIKCArz99tuoqKjAww8/7DxGFEXcdddd+PnnnzFhwgR07twZmzdvxvTp03HhwgW8+eab0Gq1+Oijj9CnTx/MnDkTCxcuBABMnjwZBoMBK1euhFwuv2I8Tz31FAICAjBnzhwcP34cS5cuRVZWljNxr43RaET//v1x6tQpPPXUU4iPj8e6deswduxYlJaWYsqUKQgJCcHSpUvx5JNP4u6778Y999wDAEhMTKwzlvz8fPTu3RtVVVV4+umnERwcjI8++gh33XUXPv/8c9x9991ITk7GqlWr8Mgjj2DQoEEYM2bMVV33//73vygvL8fkyZNhMpmwePFi3HbbbTh48CDCwsJcji0uLq71HA6H44qPM3r0aIwZMwZ79+7FzTff7BzPysrCrl27sGDBAgDA4cOHMWzYMCQmJuKll16CWq3GqVOnsGPHjis+xmOPPYbVq1fjoYceQu/evfHTTz9h6NChV/y8y1m6dCkSEhJw1113QaFQ4Ouvv8akSZPgcDgwefLkqz7P448/jpycHGzZsgWrVq1yjguCgIcffhivvfYaiouLERQU5Jz7+uuvUVZW5vI9QERERHStnnjiCXz++ed46qmn0KFDB1y8eBG//vorjh49iq5duwK4VPwcNmwYIiIiMGXKFISHh+Po0aP45ptvMGXKFOcxZ86cwbhx4xAeHo7Dhw9j2bJlOHz4MHbt2gVBEHDPPffgxIkT+OSTT/Dmm2+iWbNmAICQkBCsWrUKjz32GHr06IGJEycCAFq2bAngUr7bq1cvCIKAp556CiEhIdi0aRMmTJiAsrIyTJ061eU5vfzyy1CpVJg2bRrMZjNUKpVzjnk883iAeTwRXYZIRNQIrVixQgRQ459arRZXrlzpcuyGDRtEAOK8efNcxu+77z5REATx1KlTzrEZM2aIMplMTEtLE9etWycCEBctWnTV8XTr1k20WCzO8ddee00EIG7cuNE51q9fP7Ffv37OjxctWiQCEFevXu0cs1gsYlJSkujn5yeWlZWJoiiKhYWFIgAxNTX1qq7R1KlTRQDiL7/84hwrLy8X4+Pjxbi4ONFutzvHAYiTJ0++4jkzMzNFAKJWqxXPnz/vHN+9e7cIQHzmmWecY6mpqbW+Rn/+N3To0Ms+nsFgENVqtfjss8+6jL/22muiIAhiVlaWKIqi+Oabb4oAxMLCwis+hz87cOCACECcNGmSy/hDDz1U41o/+uijYmxsbI1zVD/PP6uqqqpx3B133CG2aNHCZeyvXwvV13fFihXOscmTJ9c4vyiK4vHjx0UA4tKlS13G77rrLjEuLk50OBw1PoeIiIjoaun1+svmhzabTYyPjxdjY2PFkpISl7k/5yG15UWffPKJCEBMS0tzji1YsEAEIGZmZtY43tfXV3z00UdrjE+YMEGMiIgQi4qKXMYfeOABUa/XOx/7559/FgGILVq0qBEP83jm8X/GPJ6I6sJ2LkTUqL377rvYsmULtmzZgtWrV+PWW2/FY489hi+++MJ5zHfffQe5XI6nn37a5XOfffZZiKKITZs2OcfmzJmDhIQEPProo5g0aRL69etX4/MuZ+LEiS6byTz55JNQKBT47rvv6vyc7777DuHh4XjwwQedY0qlEk8//TQqKiqwffv2q378v563R48euOWWW5xjfn5+mDhxIs6ePYsjR45c13kBYOTIkYiKinJ+3KNHD/Ts2bPW57l+/Xrna/Tnf39d6VIbnU6HwYMH47PPPnO23gGATz/9FL169UJMTAwAOPtAbty48apWxlSrjvevr/FfVy1dK61W6/z/6rsl+vXrhzNnzsBgMNzQuau1adMGPXv2xJo1a5xjxcXF2LRpE1JSUi57Oy8RERHRlQQEBGD37t3IycmpdX7//v3IzMzE1KlTa/Tk/nMe8ue8yGQyoaioCL169QKAGq1hroUoili/fj2GDx8OURRRVFTk/HfHHXfAYDDUOP+jjz7qEs+fMY9nHg8wjyeiurGITkSNWo8ePTBw4EAMHDgQKSkp+Pbbb9GhQwc89dRTsFgsAC7dMhgZGQl/f3+Xz23fvr1zvppKpcKHH36IzMxMlJeXY8WKFdeUxLRu3drlYz8/P0RERODs2bN1fk5WVhZat25dY1Oj2uK7FllZWWjbtm2N8Rs9L1DzeQKXksHanmdycrLzNfrzv6vdeGf06NE4d+4c0tPTAQCnT5/Gvn37MHr0aJdj+vTpg8ceewxhYWF44IEH8Nlnn10xEc/KyoJMJnPeElyttut2LXbs2IGBAwfC19cXAQEBCAkJcfZ1rK/kGwDGjBmDHTt2OF/LdevWwWq14pFHHqm3xyAiIiLv9Nprr+HQoUOIjo5Gjx49MGfOHJw5c8Y5f/r0aQBAx44dL3ue4uJiTJkyBWFhYdBqtQgJCUF8fDyAG8uLCgsLUVpaimXLliEkJMTl37hx4wBc6lf+Z9WPWxvm8WdrjDOPZx5PRP/DIjoRNSkymQy33norcnNzcfLkyes6x+bNmwFcWilzveeg+jN8+HD4+Pjgs88+AwB89tlnkMlkGDVqlPMYrVaLtLQ0/Pjjj3jkkUeQkZGB0aNHY9CgQZfdEPZa1PVmyl/Pf/r0aQwYMABFRUVYuHAhvv32W2zZsgXPPPMMgKvrIXm1HnjgASiVSucqltWrV6N79+43/McDERER0f33348zZ87g7bffRmRkJBYsWICEhASXuziv9jwffPABnnjiCXzxxRf44Ycf8P333wO4sbyo+nMffvjhWldLb9myBX369HH5nLpWoVPDYB5fN+bxRI0Pi+hE1OTYbDYAQEVFBQAgNjYWOTk5KC8vdznu2LFjzvlqGRkZeOmllzBu3Dh06dIFjz322DWtOPhr0b2iogK5ubm17gZfLTY2FidPnqyRlP01vmu9rS82NhbHjx+vMV7b875Wtb25cOLEics+z+vl6+uLYcOGYd26dXA4HPj000/Rt29fREZGuhwnk8kwYMAALFy4EEeOHMH8+fPx008/4eeff67z3LGxsXA4HM6VVNVqu26BgYEoLS2tMf7XlUBff/01zGYzvvrqKzz++OMYMmQIBg4ceN1/tF3udQ8KCsLQoUOxZs0aZGVlYceOHVy9QkRERPUmIiICkyZNwoYNG5CZmYng4GDMnz8fwP829zx06FCdn19SUoKtW7fi+eefx9y5c3H33Xdj0KBBaNGiRY1jL5fz1DYXEhICf39/2O32WldLDxw4EKGhoVf9XJnHx133OevCPJ55PFFTwiI6ETUpVqsVP/zwA1QqlfN2xyFDhsBut+Odd95xOfbNN9+EIAgYPHiw83PHjh2LyMhILF68GCtXrkR+fr5z5cHVWLZsGaxWq/PjpUuXwmazOR+jNkOGDEFeXh4+/fRT55jNZsPbb78NPz8/9OvXDwDg4+MDALUmgHWdd8+ePc7bJwGgsrISy5YtQ1xcHDp06HDVz+uvNmzYgAsXLjg/3rNnD3bv3n3Z53kjRo8ejZycHPznP//BH3/84XILKHDpNuG/6ty5MwDAbDbXed7qeN966y2X8UWLFtU4tmXLljAYDMjIyHCO5ebm4ssvv3Q5Ti6XA4BL70eDwYAVK1bUGcfl+Pr6Aqj7dX/kkUdw5MgRTJ8+HXK5HA888MB1PQ4RERFRNbvdXmMhSWhoKCIjI525VdeuXREfH49FixbVyFOq86Da8iKg9lzrcjmPr69vjXG5XI57770X69evr7WQX1hYWOfzqw3zeObxzOOJ6HIUUgdARHQjNm3a5FyRUVBQgI8//hgnT57E888/D51OB+DSbYS33norZs6cibNnz6JTp0744YcfsHHjRkydOtW5imbevHk4cOAAtm7dCn9/fyQmJuLFF1/ErFmzcN9992HIkCFXjMdisWDAgAG4//77cfz4cSxZsgS33HIL7rrrrjo/Z+LEiXj//fcxduxY7Nu3D3Fxcfj888+xY8cOLFq0yNnLXavVokOHDvj000/Rpk0bBAUFoWPHjnX2oXz++efxySefYPDgwXj66acRFBSEjz76CJmZmVi/fn2N3o3XolWrVrjlllvw5JNPwmw2Y9GiRQgODsY///nP6z7n5QwZMgT+/v6YNm2a8w+mP3vppZeQlpaGoUOHIjY2FgUFBViyZAmaN2/usiHTX3Xu3BkPPvgglixZAoPBgN69e2Pr1q04depUjWMfeOABPPfcc7j77rvx9NNPo6qqCkuXLkWbNm1cNq26/fbboVKpMHz4cDz++OOoqKjABx98gNDQUOTm5l7zc+/WrRuAS5sm3XHHHTUS7KFDhyI4OBjr1q3D4MGDr2nFFREREVFtysvL0bx5c9x3333o1KkT/Pz88OOPP2Lv3r144403AFxaPbx06VIMHz4cnTt3xrhx4xAREYFjx47h8OHD2Lx5M3Q6HZKTk/Haa6/BarUiKioKP/zwAzIzM2s8ZnXOM3PmTGeri+HDh8PX1xfdunXDjz/+iIULFyIyMhLx8fHo2bMnXn31Vfz888/o2bMn/va3v6FDhw4oLi7G77//jh9//LHWAm1dmMczj2ceT0SXJRIRNUIrVqwQAbj802g0YufOncWlS5eKDofD5fjy8nLxmWeeESMjI0WlUim2bt1aXLBggfO4ffv2iQqFQvz73//u8nk2m028+eabxcjISLGkpOSK8Wzfvl2cOHGiGBgYKPr5+YkpKSnixYsXXY7t16+f2K9fP5ex/Px8cdy4cWKzZs1ElUol3nTTTeKKFStqPM7OnTvFbt26iSqVSgQgpqamXvY6nT59WrzvvvvEgIAAUaPRiD169BC/+eabGscBECdPnnzZc4miKGZmZooAxAULFohvvPGGGB0dLarVarFv377iH3/84XJsamqqCEAsLCys9VyxsbHi0KFDr/iY1VJSUkQA4sCBA2vMbd26VRwxYoQYGRkpqlQqMTIyUnzwwQfFEydOXPG8RqNRfPrpp8Xg4GDR19dXHD58uHju3Llar+8PP/wgduzYUVSpVGLbtm3F1atXO5/nn3311VdiYmKiqNFoxLi4OPHf//63+OGHH4oAxMzMTOdxf/1aqL6+f37tbTab+Pe//10MCQkRBUGo8ViiKIqTJk0SAYgff/zxFZ8vERER0ZWYzWZx+vTpYqdOnUR/f3/R19dX7NSpk7hkyZIax/7666/ioEGDnMclJiaKb7/9tnP+/Pnz4t133y0GBASIer1eHDVqlJiTk1NrrvXyyy+LUVFRokwmc8mbjh07JiYnJ4tarVYEID766KPOz8nPzxcnT54sRkdHi0qlUgwPDxcHDBggLlu2zHnMzz//LAIQ161bVyN+5vHM4/+MeTwR1UUQxb/cV0VERNds5cqVGDduHPbu3Yvu3btLHU6DOXv2LOLj47FgwQJMmzZN6nAalCAISE1NxZw5c6QO5YqeeeYZLF++HHl5ec7bhYmIiIjoypjHNz3M44moIbAnOhERUSNmMpmwevVq3HvvvUy8iYiIiIgaCebxRI0Le6ITERE1QgUFBfjxxx/x+eef4+LFi5gyZYrUIRERERER0RUwjydqnFhEJyIiaoSOHDmClJQUhIaG4q233kLnzp2lDomIiIiIiK6AeTxR48Se6EREREREREREREREdWBPdCIiIiIiIiIiIiKiOrCITkRERERERERERERUBxbRiYiIiIiIiIiIiIjqwI1Fa+FwOJCTkwN/f38IgiB1OERERETUhIiiiPLyckRGRkIm45qWK2FuTkREREQN5WpzcxbRa5GTk4Po6GipwyAiIiKiJuzcuXNo3ry51GF4PObmRERERNTQrpSbs4heC39/fwCXLp5Op5M4GiIiIiJqSsrKyhAdHe3MOenymJsTERERUUO52tycRfRaVN8mqtPpmKgTERERUYNga5Krw9yciIiIiBralXJzNmEkIiIiIiIiIiIiIqoDi+hERERERERERERERHVgOxciIiIiIiIiIiIiL2W322G1WqUOo0EolUrI5fIbPg+L6EREREREREREREReRhRF5OXlobS0VOpQGlRAQADCw8NvaE8iFtGJiOiGWCwWbNy4ETk5OYiMjMSIESOgUqmkDouIiIiIiIiILqO6gB4aGgofH58mt/G9KIqoqqpCQUEBACAiIuK6z8UiOhERXbf33nsP69atg91udxkbNWoUnnjiCQkjIyIiIiLyHjarDcbicpSeL0RVSTmCYsPhE+QP32Cd1KERkYey2+3OAnpwcLDU4TQYrVYLACgoKEBoaOh1t3ZhEZ2IiK7Le++9h7Vr1yIwMBATJkxAUlIS0tPTsXz5cqxduxYAWEgnIiIiImpgNqsNxZl5+HXJV7CZLM7xwJhQJE0cCr9megmjIyJPVd0D3cfHR+JIGl71c7RardddRJfVZ0AN7dVXX4UgCJg6deplj1u3bh3atWsHjUaDm266Cd999517AiQi8hIWiwXr1q1DYGAg1q1bh2HDhiE4OBjDhg1zGbdYLFc+GRERNUrMzYmIPIOxuLxGAR0ASrILcGjjTpgrTRJFRkSNQVNr4VKb+niOjaaIvnfvXrz//vtITEy87HE7d+7Egw8+iAkTJmD//v0YOXIkRo4ciUOHDrkpUiKipm/jxo2w2+2YMGECFArXm5oUCgXGjx8Pu92OjRs3ShQhERE1JObmRESeo/RCUY0CerXzv5+EubzKzRERETU9jaKIXlFRgZSUFHzwwQcIDAy87LGLFy/GnXfeienTp6N9+/Z4+eWX0bVrV7zzzjtuipaIqOnLyckBACQlJdU6Xz1efRwRETUdzM2JiDyLsaSizjmH3QGH1V7nPBGRlObMmYPOnTs7Px47dixGjhwpWTyX0yiK6JMnT8bQoUMxcODAKx6bnp5e47g77rgD6enpdX6O2WxGWVmZyz8iIqpbZGQkANT5s7V6vPo4IiJqOpibExF5lsDY0DrnNDofyNVKN0ZDRHT9Fi9ejJUrVzo/7t+//xVbB7qLxxfR165di99//x2vvPLKVR2fl5eHsLAwl7GwsDDk5eXV+TmvvPIK9Hq98190dPQNxUxE1NSNGDECcrkcy5cvh81mc5mz2Wz48MMPIZfLMWLECIkiJCKihsDcnIjI8/gE+iMoLqzWuYThSfAN0rk5IiKi66PX6xEQECB1GLXy6CL6uXPnMGXKFKxZswYajabBHmfGjBkwGAzOf+fOnWuwxyIiagpUKhVGjRqFkpISjBo1Cl9//TWKiorw9ddfu4yrVCqpQyUionrC3JyIyDP5BuvQ67EhiO3ZHjKFHMClFejdUgYg4qZ4yBQeXfohIg9VWVmJMWPGwM/PDxEREXjjjTdcVoYLgoANGza4fE5AQIDLSvLnnnsObdq0gY+PD1q0aIHZs2fDarXW+Zh/bucyduxYbN++HYsXL4YgCBAEAZmZmWjVqhVef/11l887cOAABEHAqVOn6uOp10px5UOks2/fPhQUFKBr167OMbvdjrS0NLzzzjswm82Qy+UunxMeHo78/HyXsfz8fISHh9f5OGq1Gmq1un6DJyJq4p544gkAwLp16/DGG284x+VyOR544AHnPBERNQ3MzYmIPJdfMz26jO6H9oNvhsNmh1ylhG8zHWQyFtCJ6PpMnz4d27dvx8aNGxEaGooXXngBv//+u0sP8yvx9/fHypUrERkZiYMHD+Jvf/sb/P398c9//vOKn7t48WKcOHECHTt2xEsvvQQACAkJwfjx47FixQpMmzbNeeyKFSuQnJyMVq1aXfPzvFoeXUQfMGAADh486DI2btw4tGvXDs8991yNJB24tJnd1q1bXfrlbNmypc7N74iI6Po98cQTGD9+PDZu3IicnBxERkZixIgRXIFORNQEMTcnIvJsKh8NVD4Nd6cQEXmPiooKLF++HKtXr8aAAQMAAB999BGaN29+TeeZNWuW8//j4uIwbdo0rF279qqK6Hq9HiqVCj4+Pi4LMMaOHYsXX3wRe/bsQY8ePWC1WvHxxx/XWJ1e3zy6iO7v74+OHTu6jPn6+iI4ONg5PmbMGERFRTn7Mk6ZMgX9+vXDG2+8gaFDh2Lt2rX47bffsGzZMrfHT0TkDapbuxARUdPG3JyIiIjIO5w+fRoWiwU9e/Z0jgUFBaFt27bXdJ5PP/0Ub731Fk6fPo2KigrYbDbodDe2T0NkZCSGDh2KDz/8ED169MDXX38Ns9nc4HWJRn9fT3Z2NnJzc50f9+7dGx9//DGWLVuGTp064fPPP8eGDRtqJPxERERERFS/mJsTEREReQdBECCKosvYn/udp6enIyUlBUOGDME333yD/fv3Y+bMmbBYLDf82I899hjWrl0Lo9GIFStWYPTo0fDx8bnh816OR69Er822bdsu+zEAjBo1iqsiiYiIiIgaGHNzIiIioqanZcuWUCqV2L17N2JiYgAAJSUlOHHiBPr16wfgUn/yPy+eOHnyJKqqqpwf79y5E7GxsZg5c6ZzLCsr65riUKlUsNvtNcaHDBkCX19fLF26FN9//z3S0tKu6bzXo9EV0YmIiIiIiIiIiIioYfj5+WHChAmYPn06goODERoaipkzZ7psVnzbbbfhnXfeQVJSEux2O5577jkolUrnfOvWrZGdnY21a9fi5ptvxrfffosvv/zymuKIi4vD7t27cfbsWfj5+SEoKAgymQxyuRxjx47FjBkz0Lp1a7fst9Po27kQERERERERERERUf1ZsGAB+vbti+HDh2PgwIG45ZZb0K1bN+f8G2+8gejoaPTt2xcPPfQQpk2b5tJS5a677sIzzzyDp556Cp07d8bOnTsxe/bsa4ph2rRpkMvl6NChA0JCQpCdne2cmzBhAiwWC8aNG3fjT/YqCOJfm9cQysrKoNfrYTAYbrjZPRERERHRnzHXvDa8XkRERET1z2QyITMzE/Hx8dBoNFf1Of3790fnzp2xaNGihg3uKvzyyy8YMGAAzp07h7CwsMsee7nnerW5Jtu5EBEREREREREREZHHM5vNKCwsxJw5czBq1KgrFtDrC9u5EBEREREREREREZHH++STTxAbG4vS0lK89tprbntcrkQnIiIiIiIiIiIiosvatm2b1CFg7NixGDt2rNsflyvRiYiIiIiIiIiIiIjqwCI6EREREREREREREVEd2M6FqJ7Y7XZkZGSguLgYQUFBSExMhFwulzosogbHr30iIiIiIiIiaspYRCeqB2lpaViyZAny8vKcY+Hh4Zg0aRKSk5MljIyoYfFrn4iIiBqa3WyBrbIS5WezIdrt8I1uDpVeB4VWI3VoRB7DZragqqQCWbuPoaKwFBEd4xDSpjl8g3RSh0ZE1CSwiE50g9LS0pCamoqkpCTMnj0b8fHxyMzMxJo1a5Camoq5c+eymEhNEr/2iYiIqKHZzWaUHjmO8jNnnWOV2eehDgpESK+bWUgnAmCzWJGTkYldH24CxEtj5347AY3OB7dOGwX/0EBpAyQiagLYE53oBtjtdixZsgRJSUmYN28eEhIS4OPjg4SEBMybNw9JSUlYunQp7Ha71KES1St+7RMREZE7WMsrXAro1czFJag8fwGiKLo/KCIPYyqrwu4Vm50F9D+P/752GyxVZmkCIyJqQlhEJ7oBGRkZyMvLQ0pKCmQy128nmUyGlJQU5ObmIiMjQ6IIiRoGv/aJiIiooYkOB8pOn61zvvz0WdjNLA4SlZzNg+hw1DqXfzQLlkqjmyMiImp6WEQnugHFxcUAgPj4+Frnq8erjyNqKvi1T0RERA1NFEWINmvd8zZbjZW3RN7IarLUPSkCDnvtBXYiosZq6dKlSExMhE6ng06nQ1JSEjZt2tSgj8kiOtENCAoKAgBkZmbWOl89Xn0cUVPBr30iIiJqaDK5HL4xzeuc10aGQ6ZSujEiIs8UHB9R55xfaABUWrUboyEib+Sw2WA3GWGrrIDdZITDZmvQx2vevDleffVV7Nu3D7/99htuu+02jBgxAocPH26wx2QRnegGJCYmIjw8HGvWrIHjL7fPORwOrFmzBhEREUhMTJQoQqKGwa99IiIicgdNcDAUfr41xgWFAvo2LSGTyyWIisizaPS+iOnRtuaEAHR78DZo9DW/h4iI6ovdYkFF9mkYThxG2eljMJw4jIrsM7BbLnOXzA0aPnw4hgwZgtatW6NNmzaYP38+/Pz8sGvXrgZ7TBbRiW6AXC7HpEmTkJ6ejlmzZuHw4cOoqqrC4cOHMWvWLKSnp+PJJ5+EnMk9NTH82iciIiJ3UPhoEd43Cbq2rSBTqSAoLq1Oj7wtGQpfFgaJAEDtp0Xn+5LR7aHb4NtMB7lSgZA2zTHgnw8gqEW41OERURPmsNlQeT4Ttopyl3FbRRkqz59t8BXpAGC327F27VpUVlYiKSmpwR5HELmdeQ1lZWXQ6/UwGAzQ6XRSh0ONQFpaGpYsWYK8vDznWEREBJ588kkkJydLGBlRw+LXPhHRtWOueW14vQi4tMmo3XRpE1GZSgmZQiFxRESeyWiohOhwQKFSQuWrkTocIvJgJpMJmZmZiI+Ph0ZzfT8v7CYjDCfqbqGib5MAuUZ7vSFe1sGDB5GUlASTyQQ/Pz98/PHHGDJkSK3HXu65Xm2uycyDqB4kJyejT58+yMjIQHFxMYKCgpCYmMhVuNTkJScno1evXti4cSNycnIQGRmJESNGQKVSSR0aERERNSGCTAaFT8P8EU7UlKh9NbDbHVCoWO4hooYn2u2Xn3dcfv5GtG3bFgcOHIDBYMDnn3+ORx99FNu3b0eHDh0a5PH4U5WonsjlcnTp0kXqMIjcqraV6OvXr8ekSZO4Ep2IiIiIyE0sRjMqCw04+fMBVJWUI6x9DKK7tYFvsA6CIEgdHhE1UcIVFo8KsoZbXKpSqdCqVSsAQLdu3bB3714sXrwY77//foM8HnuiExHRdUlLS0NqaipatGiBd999F9999x3effddtGjRAqmpqUhLS5M6RCIiIiKiJs9msiB7zzFs+dfHOJt+BAXHzuHglzuw5V8foyy3WOrwiKgJExRKKPxqb4Gi8NNBUCjdFovD4YDZbG6w87OITkRE18xut2PJkiVISkrCvHnzkJCQAB8fHyQkJGDevHlISkrC0qVLYb/CrV1ERERERHRjjGVV2L92W41xa5UZv3/yE8yVJvcHRUReQaZQwLd5XI1CusJPB9/mcQ22h8mMGTOQlpaGs2fP4uDBg5gxYwa2bduGlJSUBnk8gO1ciIjoOmRkZCAvLw+zZ8+GTOb6fqxMJkNKSgomT56MjIwMtjkiIiIiImpAxZl5EEWx1rnCkxdgqTRBzU1GiaiByFUq+MW0gGizQnTYIcjkEBQNuwl4QUEBxowZg9zcXOj1eiQmJmLz5s0YNGhQgz0mi+hERHTNiosv3RYaHx9f63z1ePVxRERERETUMOy2K23s53BTJETkrWQKBdCARfO/Wr58udseqxrbuRAR0TULCgoCAGRmZtY6Xz1efRw1DLvdjv3792Pr1q3Yv38/2+cQEREReaFmLSPqnNNHBkPFVeiSsllsMFYYYbfapA6FiG4AV6ITEdE1S0xMRHh4ONasWYN58+a5tHRxOBxYs2YNIiIikJiYKGGUTVtaWhqWLFmCvLw851h4eDgmTZqE5ORkCSMjIiIiInfS6HzQ+tbOOPnzAZdxmVyGbikDoPH3kSYwL2cxmlGcV4LdG3ai+EIRIlpHofuQHggIC4RCxXIcUWPD71oiIrpmcrkckyZNQmpqKmbOnIkePXpArVbDbDZjz5492LVrF+bOnQu5XC51qE1SWloaUlNTkZSUhNmzZyM+Ph6ZmZlYs2YNUlNTMXfuXBbSiYiIiLyEykeD9kN6IKRNcxz9fi9MZZUIbhmJhCE94BcSIHV4XsluteHk3hP4csE659iF4+fx+/e/IeWlMYi9qfa2mETkuVhEJyKi65KcnIzRo0dj3bp1SE9Pd47L5XKMHj2aRdwGYrfbsWTJEiQlJbncBZCQkIB58+Zh1qxZWLp0Kfr06cM3MYiIiIi8hEwmgzbID636JwIQIJPLIFMqIMjYxVcK5SUV+OatDTXGHTY7vnrzC4xd8Df4B+vcHxgRXTf+NCUiouuSlpaGTz/9FN27d0dycjK6dOmC5ORkdO/eHZ9++inS0tKkDrFJysjIQF5eHlJSUlza6ACX/nhKSUlBbm4uMjIyJIqQiIiIiNzJajTjVFoG9qzYDEEmg8pHjariMmx99VOU5RRJHZ5XKis0wGq21jpnKDSgqqzKzRER0Y3y6CL60qVLkZiYCJ1OB51Oh6SkJGzatOmyn7No0SK0bdsWWq0W0dHReOaZZ2AymdwUMRGRd6heDR0REYHffvsNaWlp2L9/P9LS0vDbb78hIiICS5cu5UaXDaC4uBgAEB9f+y2g1ePVxxER1Rfm5kREnslUXgV9VDN0vq8fsvccx+Gvd6GqpAL9n7kHFw6egbnCKHWIXkcUxSsd4J5AiKjeeHQ7l+bNm+PVV19F69atIYoiPvroI4wYMQL79+9HQkJCjeM//vhjPP/88/jwww/Ru3dvnDhxAmPHjoUgCFi4cKEEz4CI3MFutyMjIwPFxcUICgpCYmIi21g0sOrV0AAQGBiICRMmICkpCenp6Vi+fDlycnKcx3Xp0kXKUJucoKAgAEBmZmatvwszMzNdjiMiqi/MzYnor2wmM0SHA3K1GjK5R6/Ra9KsRguKz+Ti6Pd7nWOl5wtxNv0I+k25BzazBWo/rYQReh99iB4KlQI2i63GnF+QP7Q6XwmiIqIb4dFF9OHDh7t8PH/+fCxduhS7du2qNVHfuXMn+vTpg4ceeggAEBcXhwcffBC7d+92S7xE5H5paWlYsmSJs6ALAOHh4Zg0aRJ7cjeggoICAEBAQADWrVsHheLSr5Nhw4bhzjvvxH333YfS0lLncVR/EhMTER4ejjVr1rj0RAcAh8OBNWvWICIiAomJiRJGSURNEXNzIqpmqTSiMqcQubsPwWa2ILBVNEI6tYFa7wdBEKQOz+vIFHIc3by3xrjdYsP+z7aj12ODJYjKu/kG+uH2iUPw3TtfuYwLMgHD/j4C/sH+EkVGRNfLo4vof2a327Fu3TpUVlYiKSmp1mN69+6N1atXY8+ePejRowfOnDmD7777Do888shlz202m2E2m50fl5WV1WvsRNQw0tLSkJqaiqSkJMyePRvx8fHIzMzEmjVrkJqairlz57KQ3kCOHj0KABgyZAgEQcD+/ftd7gQYPHgwPvnkExw9ehR33HGHxNE2LXK5HJMmTUJqaipmzpyJHj16QK1Ww2w2Y8+ePdi1axfmzp3LuzGIqEExNyfyXtYqE7J/2ouLh087x4yFJcjffwwJY4ZBG6SXMDrvdPF0DiAC2gBfRHdrA5WPBobcYlw4cAolWfmwW2rvzU0NR6lSosMtHREeH44Lx88DAiAIAmIS4hAYEcg3m4gaIY8voh88eBBJSUkwmUzw8/PDl19+iQ4dOtR67EMPPYSioiLccsstEEURNpsNTzzxBF544YXLPsYrr7yCuXPnNkT4RNRAqntyJyUluazGTUhIwLx58zBr1iwsXboUffr0YTGxAe3evRs//fRTjTsBfH15e2JDSk5OxujRo7Fu3Tqkp6c7x+VyOUaPHs03j4iowTA3JyKzocKlgF7NbrLg3Pbf0XLoLZCrlBJE5t06Dk+CNsgfZ9OPwFRWiaDYcNzy5F04smkPABZsJSGKcNgdOP37SZTklSA8PhzRHWKljoqIrpPHNy1r27YtDhw4gN27d+PJJ5/Eo48+iiNHjtR67LZt2/Cvf/0LS5Yswe+//44vvvgC3377LV5++eXLPsaMGTNgMBic/86dO9cQT4WI6lF1T+6UlBTYbDasW7cOixcvxrp162Cz2ZCSkoLc3FxkZGRIHWqTFBUVBQA4ffo0zGYzpk2bhvXr12PatGkwm804ffq0y3FUv9LS0vDpp5+iR48emDJlCp577jlMmTIFPXr0wKeffoq0tDSpQySiJoq5OREVHz8LANAE6RHZuxOaJ3dFYNtYCDIBJSeyYDOZL38CqnehbaNhKq/C3o9+QOGJ8yjPK0HW7qP4delXaH9nd6j9NFKH6HWsFiuO7DiMlf/8D079dhIXzxfh8C+H8J+pS5F18OyVNx4loqv26quvQhAETJ06tUEfRxAb2XfuwIED0bJlS7z//vs15vr27YtevXphwYIFzrHVq1dj4sSJqKiocOkbezllZWXQ6/UwGAzQ6XT1FjsR1Z+tW7fi5Zdfxr333osNGzbAbrc75+RyOUaOHIn169dj9uzZGDBggISRNk1GoxGDBw+GXC5HUFAQCgsLnXOhoaG4ePEi7HY7Nm3aBK2WmxjVJ7vdjpSUFLRo0aLWnuizZs1CZmYmVq9ezbswiDxUU8o1mZsTeZ/s7fug1vlBtNtRdPg07CYL/GPCEdwuDtk/70Wb+wZCrfOTOkyvYsi9iM1zV9U6FxAdguSn74HGnzm5O5Xml+C9SW/XubHo+Dceh64Zf6eRtEwmEzIzMxEfHw+N5sbebLNbLLCbzBBtNsiUSsjUKshVqnqKtG579+7F/fffD51Oh1tvvRWLFi2q9bjLPderzTU9fiX6XzkcDpceiX9WVVVVIxmvLiA0svcKiOgKgoKCAADr16+HTqdzWQmt0+mwfv16l+Oofh07dgzApYKu1WpF//79ceedd6J///6wWCzONzWqj6P68+e7MERRxP79+7F161bs378foijyLgwicivm5kTep1lCC5SePoesH3ejMrcIppIyFP5xAic3/IzYQUlQaNRSh+h1ijPz6pwrPVcIa5XJjdEQABgKDbUW0AGgorgcxvIqN0dE1HBsVUYU7t6HnC0/I/fnX3Dhh59QuHsfbFXGBn3ciooKpKSk4IMPPkBgYGCDPhbg4T3RZ8yYgcGDByMmJgbl5eX4+OOPsW3bNmzevBkAMGbMGERFReGVV14BAAwfPhwLFy5Ely5d0LNnT5w6dQqzZ8/G8OHDuRqPqIlp164dAECpVOLTTz+F6v/f4Rw2bBhuv/12DB06FFar1Xkc1a/i4mIAQK9evbBr1y5s27bNZb5nz57YvXu38ziqP9XXNCcnBy+//HKNfvQTJkxwOY6IqL4wNyci4FLv89JTNdss2c1W5O05hPjBvdkT3c0E2RV6nnMTS7fjxqHkLewWC4r2HYCpoNBl3FRQiKJ9BxDSs1uDrUifPHkyhg4dioEDB2LevHkN8hh/5tFF9IKCAowZMwa5ubnQ6/VITEzE5s2bMWjQIABAdna2y+qWWbNmQRAEzJo1CxcuXEBISAiGDx+O+fPnS/UUyIvY7XZkZGSguLgYQUFBSExM5B+IDeibb74BAFitVsyZMwcpKSmIj49HZmYm1qxZA6vV6jxu1KhRUobaJFWv8N+1axd69OgBk8kEg8EAvV4PjUaD3bt3uxxH9af6ms6fPx+9e/fG7NmzXb72q3/n8doTUX1jbk5SEkURdrMZEAG5SgmBebZkio+drXOu5NQ5RJssUPqwdYg7BcWFX9o7tJabfILiw6Hy4d0B7uYfrINSrYTVbK0xpwvRw0fH7xFqGuwmc40CejVTQSHsJnODFNHXrl2L33//HXv37q33c9fFo4voy5cvv+z8X1c+KhQKpKamIjU1tQGjIqopLS0NS5YsqbEidNKkSUhOTpYwsqYrJycHADB9+nSsWrUKkydPds5FRERg2rRpeP31153HUf1KSEiAXC6HQqHA3r17XW7LFwQBarUaNpsNCQkJEkbZNFVfe51Oh5deegkKhcI5/tJLL2HUqFEoKyvjtSeiesfcnKRiMxpReT4HFZlZEO0O+ERFwL9lPJS+PlKH5pWEy+xnIAgCV+BKQJAJaH/HzTj6vWsxSaFWouOwXrXV1qmByeQCbht7Oza//63ruEKOgePuuOz3EVFjItpqb1t0tfPX49y5c5gyZQq2bNlyw73crwW/a4luUFpaGlJTU9GiRQu8++67+O677/Duu++iRYsWSE1NRVpamtQhNkmRkZEALq1KWrFiBUaOHInu3btj5MiR+PDDD51F3erjqH4dPnwYdrsdZrMZCoUCt912GyZPnozbbrsNCoUCZrMZdrsdhw8fljrUJqf62peWluLFF1/E4cOHUVVVhcOHD+PFF19EaWkprz0RETUZNqMRBTv3oCTjMKzlFbBVVaHs5Gnk/vwLrJWVUofnlYLaxQEAfMKCEd2vG2IH9kSzjq0gKOQIbBsLuZarnt2t8OQFOOwOJP1tCCI7tURQfDha9e+E3hOH4eDGnbBWsie6u5XmlyLnxHncP+shdOjbEZFtmqPTwC4YPeshHNjyOypLKqQOkaheCIrLr8++0vz12LdvHwoKCtC1a1coFAooFAps374db731FhQKhXOPtvrm0SvRiTyd3W7HkiVLkJSUhHnz5jlvYU5ISMC8efMwa9YsLF26FH369GFrl3o2YsQIvPfee3j77bexcOFCOBwOAMBvv/2Gr776CkqlEnK5HCNGjJA40qapoKAAAKBSqWCz2fDTTz/hp59+AgDIZDKoVCpYLBbncVR/qnudv/DCC1i+fHmNuzBeeOEFzJ8/nz3RiYioSTAXl8JSaqgx7jCbUX46EwEJ7SFjnu1WSn8ftHvwDlTmFKHo0CnYzBboYiLQ9r6BUOv9oOTGom4nyAQc37IPKh81ojq3gn+oHobcYvzyzgaIogiH3SF1iF5HkAk4+PMfOLbzCNomtUdMQixK80vw6byP4bDZMWD87VKHSFQv5Bo1NKEhtbZ00YSGQN4AvxMGDBiAgwcPuoyNGzcO7dq1w3PPPddg9TcW0YluQEZGBvLy8jB79myXHqDApUJiSkoKJk+ejIyMDHTp0kWiKJsmlUqF1q1b49ixYxAEAbfffjvuv/9+fPbZZ9iyZQvMZjPatWvn3HCU6tfRo0cBABaLBUlJSejRowfUajXMZjP27NmD9PR053F33HGHlKE2OdW9ziMjI7FmzZoaezEcO3bM5TgiIqLGyuFwoCIru875ynM50LVuCZmWvYXdyiEid9dBGDL/1zbx4pEzKDmZjQ6PDJUwMO+ljwyGIAiwVJmRudP1bsTglhFX3niU6p2umR4qrQoWowWHtmW4zAWEBcDHn+2oqGmQq1Ro1q1zjc1FNaEhaNatc4P0Q/f390fHjh1dxnx9fREcHFxjvD6xiE50A6pXesbHx9c6Xz3OFaH1z2Kx4OTJk1Cr1bBYLPjhhx/www8/APjfSuiTJ0/CYrGwkN4Aqtvl6PV6vPzyy86+3AAwfPhw3HvvvTAYDC690ql+JCYmIjw8HGvWrMG8efNc3qBzOBxYs2YNIiIikJiYKGGUREREN04AIAiX6b8tkwHsv+12ZkO5SwG9msNqw7ltv6Hl0L5Q+vKNDXcyV5jQYWhPHP5ml8u4UqNC+zt7AMzJ3c4/yB93Tb0Hn7/6qcv1lyvkuOuZe+EfrJMwOqL6pfDRIqRnN9hNZog2GwSFAnKNukEK6FJiEZ3oBlSv9MzMzKx1E7/MzEyX46j+bNy4EXa7Hc888wz69++PV155BTk5OYiMjMSMGTPw888/44033sDGjRsxatQoqcNtcqo3jDIYDJg1axaioqJgNpuhVqtx4cIFGAwGl+Oo/sjlckyaNAmpqamYNWsWUlJSEB8fj8zMTKxZswbp6emYO3cuW0g1MLvdXuMuAF5zIqL6Jchk8G8Zj6qc3Frn/eJjIVezdYi7FZ+4dHdAs05t0CyhBWQyGYwXDTi3fR8MZy7AZrawiO5mPoH+yD2Yid6PD8O5fSdgKqtCUGwYQttFI3vvcSQM7SV1iF5HrpCjRddWmPj2JPz2zW4UnS9CZOsodLmjGwLCAqUOz+tVGCphNlugUinhH+AndThNglylkrRo/tcN7hsCi+hEN+CvK0L/3NKFK0IbVk7OpdUvJ0+exJtvvuncOCIzMxMjRozA0KFDXY6j+tW+fXts2LABCoUCu3btqjGvUChgs9nQvn17CaJr+pKTkzF37lwsWbKkRk/0uXPnIjk5WcLomr60tDQsWbIEeXl5zrHw8HBMmjSJ156IqJ4pdf7wiYpA1QXXQrrS3x9+Mc35hr0EFGolOo4fAcOZ88j89tdLPdFjI9Du/tuR/8dxviYSsFms8A3WYc/KzYjs1AL6yGCUZOfjzM5D6Pf0PXxNJKLSqBAaG4Y7Hh8Km8UGhVrBRRcSq6ow4uyJc1j77hc4f+YCQiObYdQTI9EmsSX89Sym0+WxiE50A7giVDqRkZEALq1IDwwMxIQJE5CUlIT09HQsX74cX331lctxVL9CQ0MBADabDQDQpk0bREVF4cKFCzhx4oRzvPo4qn/Jycno2rVrjbsw/PyY/DWktLQ0pKamIikpCbNnz3b5mZ+amso3MYiI6pvDAW14GHwiwlF5IReiww6fsFDItVqIDm6WKIXghJbI/H4nyrP/92ZyyfEslJ4+jw4pQ6Dw0UgYnXdSalRQ+Wlx67T7UVlkAAQgrH0M/EIDcHb3UbQf1F3qEL1aWZEBDrsIuUqOgJAAqcPxWna7Hft++QPvzP7AOZZ5PBuvPfMWHnrqXtz5wACouTEyXYYgsmFtDWVlZdDr9TAYDNDp2KeKrqy2VYkRERF48sknWUxpIBUVFRg2bBgEQcCmTZug0fwvWTeZTBg8eDBEUcQ333zDomIDMBqNGDx4MARBqLXvefX4pk2boOVmXw1i5syZ2LFjR43xPn36YP78+RJE1PTZ7XakpKSgRYsWtd59NGvWLGRmZmL16tV885Qui7nmteH18m4V53NQtPs3yDVqaMNCAZkM5qKLsJZXwK9FHIISEyDjz1y3MpzNwbG1m2ud08VFouXwZKjYzsWtDLnFsFQacTEzF2d+OeRs59JmQBeo/H2g1fvCN8hf6jC9TmlBCc4fPYedn/+C0vwShMSEIvmhWxESEwpdM73U4Xmdorxi/POhOagsq6wxJ1fIsWj9fIRGhUgQmXRMJhMyMzMRHx/vUlNpii73XK821+RKdPJ6JpMJ2dnZN3SO8PBwzJkzBydPnoTBYIBer0fr1q0hk8lw4sSJGzp3TExMk/9hdj02bdoE4NIGlw8++CDGjx/vXIn+4YcfOgu7mzZtYk/0BvDNN98AuHT9AwICEBcXB4fDAZlMhrNnz6K0tNR5HK9//asuoCuVSiQnJ6Ndu3Y4duwY0tLSsGPHDsycOZOF9AaQkZGBvLw8zJ4926WADlza0DglJQWTJ09GRkaGy4avRER0fRx2OyqzzgEA7CYzKv7//6sZc3LhaNcaMr5h71YlJ+v+26nsbA4cZivAIrpbmQwVOLPjMM7tPe4cKzh+DoUnzqPXY4Oh0jatzf0ag8rSCuz/fh92rEtzjl04fh6fpK7C0L+PwE39E6FQKSWM0PuUl5bXWkAHALvNjqK8Yq8rotO1YRGdvF52djYmTpwodRh1WrZsGdq0aSN1GB6nutf5iBEj8M033+CNN95wzsnlctx111346quv2BO9gVy4cAHApTeQCgoKcODAAeecTCZDWFgY8vPzncdR/TEajdixYwfkcjkCAgKwdetWbN26FQAQEhKC4uJi7NixA0ajkXcB1LPi4mIAQHx8fK3z1ePVxxER0Y0RBAGCou5V5oJcDoC9nt1Npqy78CfI5XxJJKBQK10K6NVEUcShr9LRZ9JdEkTl3YzlRqR/8Wutcz+t/AExCbEIjmrm5qi8m/wyv08AQKliiZQuj18h5PViYmKwbNmyejlXVlYW5s+fj5kzZyI2NrZezhkTE1Mv52lqqnudt27dGl988QVmzpyJ/Px8hIWFYf78+UhLS3M5jhpGXl4eevToAZPJ5LwLQ6PRYM+ePVKH1mS9//77AC61FmndujXmzJnj0pd7586dzuOmTp0qYaRNT1BQEIBLGxgnJCTUmM/MzHQ5joiIbowgk0HXMh5V52tfFOHfIh5y9q91u+B2ccjdlVHrXLMOLdgTXQKl5wvrnCvPL4Fot7sxGgKA0vwSOOy179tgLDfCWG50c0TkH+CHsOahyD9fUGPOV+eLwJBACaKixoRFdPJ6Go2m3ld6x8bGcvV4AxsxYgTee+89LF68GK+//rpzvLCwECNGjIBSqYRcLseIESMkjLLpatu2rfP/L1cw//NxVD/Onz8PAOjSpYtLX+6EhATMmzcPzz77LPbv3+88jupPYmIiwsPDsWbNmlp7oq9ZswYRERFITEyUMEoioqZF6e8H39hoZ1uXaqoAPXyjIyEIXPbsbko/LSKSEpGb7lpIV+v9EJF0ExRqtg5xtyu1BRH+0oaOGt6VXpMrrYqm+hfYLABT/jURcye+BrPJ4hyXy+WY+q/HEcg+9XQFLKITUaOkUqkQHh7ubBcSHR2NuLg4nD17FufOnYPVakVUVBRUKibxDaGiosLlY71eD61WC6PRCIPBUOdxdOPU6ksr7kJCQiCKIvbv34/i4mIEBQUhMTERzZo1czmO6o9cLsekSZOQmpqKWbNmISUlxeUugPT0dMydO5ebihIR1SO5Wo2gjh3gHx+L8tNnIdrt8IuNhipQDwXblknCYbNB1zwMgQ8PQcEfJ2E3mRHQKhq+Ec0g2rjiWQr+4UEQZDKIjporn0PbRkMmZxHd3fyD/aHx1UAfFoBOA7vCL9APpXklOLDldwgyASof5upSiGsTgwVr52LX1t9w/I9TiG0djb5DkhASEcw3NuiKWEQnokbJaDS69Ns+d+4czp1zXaF04cIF9oVuID4+Pi4fGwwGl+J5XcfRjbvllluwY8cO/Pjjj/jjjz+Qn5/vnAsLC0NhYaHzOKp/ycnJmDt3LpYsWYLJkyc7xyMiIjB37lwkJydLGB0RUdMk16gh16ihDgoERJGraiVmKq2Aw25HeWY+tCEBkMnlMJWWQ+mrheFsLiJ6dIBa5yd1mF7FUmlCp/v64sC67YD4v3G1vw/a3t6tzrYi1HAEQcDD/xqHs3+cwd6v0lGSX4qQmBD0vq8vIltHQaFkwVYKcoUcYc1DMeLRIbDZbFAoWBalq8evFiJqlKr7QgOATqeDn58fTCYTNBoNKioqUFZW5jyOfaHrX3Xf7WohISEICgpCcXGxs4hbfdzQoUPdHV6TFh4eDuBS+5CCggIMGjQI999/Pz777DP8+OOPEEXR5Tiqf8nJyejTpw8yMjJc7gLgCnQiooYlCALA9i3SE0XkpGegMrfIZThPJqD13bexYCsBla8GxWfzceu0+2E3WyHIBIiOSzlh1p5jaH9nD4kj9D5ypRwHNx3A7g3pzrHCrAJ889YG3DFxCDr0vUnC6AgAC+h0zfgVQ0SNUvWqc4VCgbKyMmfRvJpCoYDNZquxOp3qR2VlpfP/ZTIZCgsLncVzuVwO+/9vXvTn46h+JCQkQC6XQyaTwWq1YsuWLdiyZYtzXqlUwuFw1LrxJdUfuVyOLl26SB0GERGR24k2e40COgCIDhG5ew6hxRDeDedupgoj2tzWGRcOnMaZHYdhLq9CYEwo2t3eHa36JQKieOWTUL2y2+zY89XuWue2rfkJbXq2c3NERE3LnDlzMHfuXJextm3b4tixYw32mCyiE1GjZDabAQA2mw0ymQxBQUFwOByQyWQoLi6GzWZzOY7qV25urvP/dTod4uLinNf/7NmzKC0trXEc1Y/Dhw/DbrfDbrejZ8+eUKvVKC8vh7+/P8xmM3bv3u08jkVeIiJqKhw2OxwWM0QAMqUScuXlN+2jhlOWVXd+V34uv845ajh+zfT4Y30acjMynWMl2QVI/8936DVhMIJbRkgYnXcyFBhq7VEPAOZKE4zlVdCHBrg3KKIGZDWaYasywm62Qq5WQeGjgVLbsL3/ExIS8OOPPzo/bui7C1hEJ6JGKTo6GocOHQJwqa1FUVHN1TDVx1H9+/OmlaWlpThw4MAVj6P6UVxcDACYOXMmli9fjry8POdcREQEZs6cifnz5zuPIyIiauyslVUwHDuByuzzEB0OaMJCEXRTByj9/dgfXQJyTd35nUypcLaWI/exGc0uBfQ/O7hxJ/r+faR7AyIo1Zd/o0+uZDmOmg5zWQXOfLcDZWdznGP6+EjED+7ToHtkKBQKt7Yx5XctETVKf23TEh4ejokTJ+L/2Lvv8DjKa/Hj35nZXrTqvbhXbHADTO9gOqFDgIQkJCGXFH5phISE5DqQ3NxcuCkmziWEBAgJEFoCmGpTDQZsYxv3ItnqdVfbd2fm94ewsFAxBmlW8p7P8/AgzVntHmm9q9GZ85536dKlfYqKMs5lZOTk5PT5fLCZ6B+9nfj08vPzASgvL+f+++/vN5d77/K1vbcTQgghxrJ0NEbzy6+RjsZ6j8WbW2hsa6f85OOx+2UDS6vlTamm/tXVA8aKZk9GdUiZwWoddS2DxiJtQcy0bmE2AsCX58Od4yEWivaLFVUX4/a7M5CVEMMvFUv0K6ADBHc2sPPp15h47gkj1pG+detWysvLcblcLFy4kNtuu43q6uoReSwAuWwvhBiT1I90HTU1NfHTn/60TwF9oNuJ4XHqqaf2+by1tZXNmzf3KaAPdDvx6c2ePZvS0lLuv/9+FEVhzpw5nHzyycyZMwdFUbj//vspKytj9uzZmU5VCCGE+NRiLa19Cuh7mbpO16atGB+M8BPWMVJpKo7tPzLOXZhL/tQajJQUbK1mdzkGDyqgaPI3kdVMBRZ99ex+Hecur4uTrz1dNuAVB410NNavgL5XcGfDgL/Dh8MRRxzBn//8Z5555hmWLFnCzp07OfbYY+nu7h6RxwPpRBdCjFH7dpjn5uYOOpNbOtFHxs6dfZeL5ubmUlRURGtra+/PfqDbiR7xeJy6urpP/PXnn38+f/jDH/jmN7/JokWLqKiooL6+nqeffpp169bx5S9/me3bt3/i+6+ursblcn3irxdCCCGGg6HrROsH/sMcINbcgpFKo47wDFTRV9uG7Zi6wZSLTiG0q4F0PIm/qgRFU9nyzxeZedVZmU4x6/hL8lBtGsYAHeelM8ehoGQgq+zW2dDB2/9+i4t/cBn1m/fQ1dxJUXUxhVVFvPCnZZz7rc+QUxjIdJpCfGp6IvWp4p/UokWLej+ePXs2RxxxBDU1NfzjH//gC1/4wog8ppxtCCHGJE3Tej8OhUJ9ZnLvG9v3YzF8dL3vCXpXV1ef4vlgtxM96urquO666z71/bz33nu89957/Y7fddddn+p+ly5dypQpUz7VfQghhBCflqIoqPbBO2w1hx1k/rbl7G4n9a+tpW3dNvxVJah2G/WvriHZHekZ5aJIwdZqiXCMuZedyDsPvIBpfPia8OT7mXLiHAx5nVjO7rBRt34Xdet3UT65Am+ej3XL19Ja2zN6R/ZzEAcLbX/z//cTHy65ublMmTKFbdu2jdhjSBFdCDEmlZaW9tlM1OPxoOs6mqYRj8f73E4Mv303rTz88MOJxWKEQiFycnJwu9289dZb/W4nPlRdXc3SpUs/9f0YhsGrr77Kfffdx2c/+1mOOeaYYRlhNJJz5IQQYiww9DTmBxeCFU1D1eTPpkwwTRNvVTmR3XsGjHtrqkAKUZbLmzqO+tfWYhoGodrGPrGiWZOxuWU1m9U8+X62v7KOY64/l7ZtDcRDEfKqS3D43NSu2sTMs47IdIpZx+F24gl4iQYjNGyt7xMrHleCZpdmL3FwsHncBMaXE9zZf+VYYHw5No818//D4TDbt2/nqquuGrHHkLNBIcSYtHjxYs477zygp5AYjfbfsGXv7cTwKywsBHouXtTV1fWZRV9aWorH4yEajfbeTvTlcrmGrdNbVVXuu+8+jjvuOOkeF0KIT8k0TfREnGhDHelwz0xNuy+Au7wSzelCkQ5bSymKgp5K4584nu7tfUfEuYoKsftkU9FMsDnt1JxyBLXPv9nnuKc4n9IFM0ZsAzkxuFQ8ybgjpvPqkifJry7B7nXS8vw7YMKx/3E+hiHzt61m6DpnXn8Oj//6EVL7jLPw5Hg46XOnYcpzIg4SdreT8YuOZufTr/UppAfGlzN+0TEj9jvh29/+Nueccw41NTU0NDTw4x//GE3TuPzyy0fk8UCK6EKIMSoQCKBpWu+4EEVRegu35gfLFTVNIxCQOXMjobKyEoBoNIrD4eCSSy6hvLychoYGnn322d6LGntvJ4QQQowFRjJBaNtG2Ke4kQoHSW8PkzNpBppTioNWUlQVu9dDKhSi5LijiDe3Yuhp3CXF6NEYeiKOzSXPidVM3URzO5l93WdIR+MYuoHmdKBoCsnuGK7cnEynmHWcPjfBPa2ccctVJCIxjLSOzWHH5nTQ3dZF8aSKTKeYdVRNY/Wzb/OZ711Cy85mupo7KawuJrckl3efXsWJV5+S6RSFGDbOHB8Tzz2BdDSGnkihOe3YPO4Rvai6Z88eLr/8ctrb2ykqKuKYY45h5cqVFBUVjdhjShFdCDEmBYPBPvO2TdMkEon0uY2u6wSDQSmkj4DzzjuPu+66C5vNRnd3N//4xz96Y5qm4XQ6SafTvasFhBBCiNHONAzi7a19Cui9MV0n0dmGu6RcutGtZpp4ykoJbtmGkUyhqAqpUJicyRNR7TaMtGwsarV4VxhvST71r62hY9MuTN3AXZRH9YnzSUZiOPweXLn+TKeZVZKRGE6/h83Pv0vtmxvRk2m8hQGmnTafaFc3gdICWSFgMT2lM/eMBfzzlw+RV5qHL89H7fpdxCNxzvvWZ3obv4Q4WNjdTkvfZx588EHLHmsvOdsYJeLxOHV1dZlOY1DV1dW4XDLbToweN998c+/HOTk5pNNpkskkDocDm81GKBTqvd1vf/vbTKU5qn3a952TTz6ZZ599Fq/Xy9SpU3E6nSQSCTZv3kwkEuG0005j165dn/j+5X1HCCGElUxdJx0ODRpPdQdxFZagSMHWMoauY5ombW++jR5P9InF29opOepwjJQU0a3m8LvY9vjL+MoKmHTO8QAkuiPUPv8W4049MsPZZSc9pbPl+dW0bftw9nakLcg7D7zA3MtOxNin+UhYw+V3s/z+F7jgOxfTtruVruZOJh8+DX++n3eeXsXpXz4r0ykKIQ6QnG2MEnV1dVx33XWZTmNQS5culVm7YlRpbOzZxEjTtN6COUA6ne49rut67+1Ef8P1vhOJRHj33Xf7HX/22Wd59tlnP/H9yvuOEEIIS6kKyhAbiKqaDaQL3VKKopDs7OpXQAfAMOjeUUv+YbOsTyzLJUIRqk+YR+u6rWx7YjmmYeIqCFBx9KEEaxsozpXzN6upqtqngL6vjc+sonh6lcUZidySXI677AQe+PFfyCkM4MvzsePdbaQSKa782TUEimS1tBBjzaguoi9ZsoQlS5b0djLOnDmTW265hUWLFg36NV1dXdx8883885//pKOjg5qaGu644w7OPPNMi7L+ZKqrq1m6dOmw3FdtbS2LFy/m5ptvpqamZljus7q6eljuR4jhYvug40jXdWw2G+PHj8fhcJBMJtm5c2dvMd0mnUmDGq73nXQ6zT//+U+ef/55TjnlFD7zmc8My89d3neEEGJ0OdjPzVXNhquohHCke8C4q6gUVdMsziq7maZJvKVt0Hi8vcPCbMRems3GzmdeJ975YSNLvD3I9idfZtJ5J4Bca7Jc155WbG4HR1x7Br7CAEbaQNVU6t7ZwsZ/v4mpy+gQqyVjCZp3NPLF//kqsUiMdCKFw+XA4XFSv3kP+eX52Bz2TKcphDgAo7q6VFlZye23387kyZMxTZN7772X8847j9WrVzNz5sx+t08mk5x66qkUFxfz8MMPU1FRQW1tLbm5udYnf4BcLtewd1zW1NRIF6c4aB122GEsW7YM6Cnibt26ddDbiYEN5/uOzWbj+eef55JLLpH3HSGEOEhlw7m5ze3FmV9EoqO1z3FnQTGa252hrLKXoihoQ2wcqjkcMqM+A1LReJ8C+r4aVq5j0vknWJuQwJPv49SbrmDjM29R99ZmjLSOO8/HzLMXctJ3L5FFNBkQ6Yrg9LpY9e83Wfv8uyRjSTw5HuafdQQuv5twZ4TcktxMpymEOACjuoh+zjnn9Pl88eLFLFmyhJUrVw54ov6nP/2Jjo4OXn/9dez2nit648aNsyJVIYTF6uv7Lle02+3k5ubS1dVFKpUa9HZCCCGE+GSy4dxctdtxl1bgLCgi1R0EwJ6Ti2qzy9ztDFBUFf+EccTbO8g7ZAY2jxtMEyOt07VxM77qyiGL7GJkdO9pHjQWbW4H2TDRcv6SAt66ZxntOz8cZRnrDPP2X59j/mdPoXT2+Axml51S8RSbV21hxsIZzD1jPnoqjWa3sWfjbtrr20jv8zersJau63S2BknEEzicDnILA9jt8jte7N+Y+Vei6zoPPfQQkUiEhQsXDnibJ554goULF/K1r32Nxx9/nKKiIq644gq+973vocnSSyEOKh8dF5JKpWhtbd3v7YQQQgjx6R3M5+aqzYZqs2FzezKdigBMoOiI+XS+t4F4a89oF3uOn/xDD0Gx2zFSKVS7jESwksM3+GtDczoszETsFQ9F+hTQ97X+yTconFwOOV6Ls8puiqZw4pUnsepfb/LEHf8klUjh8rk58vyjOPSUOT1vbsJywY4QK/71Go/d8xSR7ihOt5PTLz6JM684hbzC3EynJ0a5UV9dWrduHQsXLiQej+Pz+Xj00UeZMWPGgLfdsWMHL774IldeeSVPPfUU27Zt4/rrryeVSvHjH/940MdIJBIkEh9uVrPvJoVCiNGpq6urz+cul6t3Jno8Hh/0dkIIIYT45OTcXFjJ0HVUm0bTitcxksne46lQN82vrqTshGMw0roU0S2WO7mKhpXrKJo1CX91KaZhoMeTNK/eRO4EWR2QCR21zWh2jerDp1E2cxymaaIn0+x4bQNt2+rRk+lMp5h17A47K+57kRnHzWLuGfNJJ9PYHDYat9az7sU1zD3r8EynmHWSiSRPP/g8j/7p373HErEET/zlaTpaO7n2u1fi9csFdDG4UV9Enzp1KmvWrCEYDPLwww9zzTXXsGLFigFP1g3DoLi4mKVLl6JpGvPmzaO+vp7/+q//GvJE/bbbbuPWW28dyW9DCDHMcnJyej9WFIV4PN5bPFcUBfODZaT73k4IIYQQn46cmwsrKapKrLG5TwG9l2nStWkL+YfNtj6xLJdOpph+5SJ2L3+HprffB8AR8FF5zBy8JfnoiSR4XBnOMrt483NYeN3Z1L65kTf+72lMw8Dp9zD11LkUT6lEs43e1T8Hq3QyzfGfPYk3H3+DR3+1mnQihdPr4vBzj2TWyXNIx2Wci9W62oL8675lA8ZefXolF33pHCmiiyGN+iK6w+Fg0qRJAMybN49Vq1Zx55138oc//KHfbcvKyrDb7X2Wh06fPp2mpiaSySQOx8BLy2666SZuvPHG3s9DoRBVVVXD/J0IIYZTc/OHsxg1TWPWrFkUFBTQ3t7OunXrSKfT/W4nhBDxeJy6urpMpzGk6upqXC4pPojRSc7NhZWMdJp4a/ug8URHFxiGdQkJAGx2O7tffpfqE+fDifMxdAPNbqOrtoFEKIKnKC/TKWadQEUhK+9+ms7aD//2SXRHee+fr3LYJSdg98p5hdVsDhsv3PMsm1du7D2WiMR55W/LScWTLDjriAxml53CoQipZJr5x8/h6NMPR1VVUGDVS+/y+nOr6Gjpoqy6NNNpilFs1BfRP8owjD7LO/d19NFH88ADD2AYRs+LAdiyZQtlZWWDnqQDOJ1OnE5ZcibEWOJ2u3s/TqfTrF69er+3E0KIuro6rrvuukynMaSlS5cyZcqUTKchxMci5+ZiJCmahuYevPinOZ2gWJiQACCdTFJ9/Dxqn3+T4K4GABx+L1UnzMPh92AYeoYzzD7xUKRPAX1fm555i9IZ1bhlJrql0slUnwL6vt7+91scduo8izMSTpeTL/3gahrrmvnDf95LPBrH7rRz7BlH8vX/vA6PT2oHYmijuoh+0003sWjRIqqrq+nu7uaBBx5g+fLlLFvWs/zi6quvpqKigttuuw2Ar371q/z2t7/lG9/4BjfccANbt27l5z//OV//+tcz+W0IIQbxaTpCA4FAn8+rqqp6Z6Lv3r27z+22bNnyiXOUjlAhDi7V1dUsXbp0WO6rtraWxYsXc/PNN1NTUzMs9wk9OQoxGsm5ubCcaeIfV01418DnizmTxqPYZB661exuF5seXEYyFOk9luyOsP3Jl5ly0cl4SgszmF126hikgA4QD0XRUzIT3WpdLcFBY+lkmng4ZmE2AsAf8FG3bQ+dbUG+8qPPoSgKiqrw9oo1vP7cKq658dJMpygOUH19Pd/73vd4+umniUajTJo0iXvuuYf58+ePyOON6iJ6S0sLV199NY2NjQQCAWbPns2yZcs49dRTgZ5usr1dLdBTRFu2bBnf+ta3mD17NhUVFXzjG9/ge9/7Xqa+BSHEEIazI3Tfwvm+1q5d+6keQzpChTi4uFyuYX9N19TUyPuEyApybi6spqgqejpN3uxD6HxvfZ+Yt7oSeyAHBTND2WWvSHN7nwL6vnaveJfJF5xkcUbCmz/4PlCqpqLaRnXp56Dk9g/d1Wx3Db4iS4yMWCzO+Gk1aFt3s+TWP5GIJ7HZbRx9+hEcffrhJBMyp/7TSETiJLqjpGIJ7G4nTr8H5wiOkurs7OToo4/mxBNP5Omnn6aoqIitW7eSlzdyI8VG9Tvp3XffPWR8+fLl/Y4tXLiQlStXjlBGQojh9Gk7QhcvXkxtbS0AeXl5dHZ29v4fegpbN99886fOUQghhBDZdW6uJxOYes9ICkXVesaGCMspioLN5SQVDFF2yvEk2jsxdR1XYQHpaIx0JIorX+ZvW627rmnQWKy1E0y5sGG1QHkBrhwPVfOnUDy1CkM3MHWDXSs34vS5cMhMdMt5cjzkluTS1dzVL1Y1owa7S1bRWC2dTLFtww6ef2TFh8dSaVb86zW6g2Eu/cr5mUtujIt2dLPqr8/RvPHDlWMl02tYcNUpePL9I/KYv/jFL6iqquKee+7pPTZ+/PgReay9RnURXQhxcPu0HaH33nsvX/nKV9i0aVNv4Xzv/6dNm8Zdd901LHkKIYQQIjsYuo4eixCpr8NIxAFQnS68FTVoLrd0c2aAzeNBtdtpfOFlnIUFqJpK5/qN+MdVE5g+NdPpZSVnYPCCiM0tc+ozIZVIcvw3P8N7j77GtpfWYpomdreTqafMpWz2eFLRBO4cT6bTzDoXfv8y/v7T+wh3hnuP5VcUsOj6szHlYpPlTBOWP/HagLF3X1nLZddfYHFGB4dEJN6vgA7QvLGWVX99niO/uGhEOtKfeOIJTj/9dC6++GJWrFhBRUUF119/PV/60peG/bH2krNAIcSYdtdddxEOh7n55ptZu3Ythx56KIsXL8bn82U6NSGEEEKMMUYyQffOrX06aY1EnO6dW8iZPEOK6Bmg2u14qypwFRaQ6OzC1HXyDpmB5nahDbFBrRg5eZOq2PPyu5iG0S9WMm86moypsJyeSrPq3ucI1rf1HkvFEqx/8g1QFSrnTMpgdtmps6mDt//9Ftf84oukkilS8RQOtwObXeMfP3+As//j/EynmHWikRjpIfYH6GoPUjO5ysKMDg6J7mi/AvpezRtrSXRHR6SIvmPHDpYsWcKNN97ID37wA1atWsXXv/51HA4H11xzzbA/HkgRXQhxEPD5fHzta1/juuuu42tf+5oU0IUQQghxwAw9Tby1eeBRFKZJoq0FtawSVdOsTy6LmaZJKhyh7e3VmKkUqCqmYVAwZzauwgK5sJEBhq4z+YIT2fb4coy03ns8d1IVhTMmoseT4Bl6HrQYXmba6FNA39fWF1ZLET0D3DkeTrrmVJbf/wIbX92AoRvYHDYOO20e537jQjSbuv87EcPK5R56NJvXJ6s1PolULLGfeHJEHtcwDObPn8/Pf/5zAObMmcP69eu56667pIguhBBCCCGEECPFTPeMchlMOhbpmZMuRXRLpSNR2la9i29cNXavB9M0MVJput7fTMGcWThHcAMxMTBFU+luaGXGVWcR7wiSiibwlReSisaJNLfjryzOdIpZJ9TUMWgsEY4NuGpAjCxPjpenf/cEO1Zv7z2WTqZ5+19vYugGx1x6fAazy052h53pc6ew8d0t/WJl1SW4fXLx75Ow7+fihN09MquTysrKmDFjRp9j06dP55FHHhmRxwOQS19CCCGEEEIIoaqo9sH/0FPtDhRV/nyykmmaxNrayJs5nfDOOlreWEXryrfp2rAR//gaok2t6MlUptPMOpGmDhrfeI/19zxB/evv0bFxJxvvf4YtDz3PnldXo6cHH5cgRoY7MPhKXNWmyXtXBiQjiT4F9H2tee5dktG4xRkJXU/zhe99lsoJ5X2OF5Tk843bvoyu64N8pRiK0++hZHrNgLGS6TU4/SPT4X/00UezefPmPse2bNlCTc3AuQwH6UQXQgghhBBCZD3NbsdVVEIqHBow7ioskdEhFjMNA4fPR/OrK3tWAXxAjydof3ctxQsPx9TTgD1zSWahcH1z78ex1s4+sXh7EGS/RMu5Al4cHifJaP+xCtULZAPeTAi2BQeNGWmdWFiK6FZzuV08+Pt/8uUffY5UIkVjXTNF5YV4/R6e+MvTXPoV2Vj0k3B6XSy46hRW/fV5mjfW9h4vmV7DgqtPGZF56ADf+ta3OOqoo/j5z3/OJZdcwltvvcXSpUtZunTpiDweSBFdCCGEEEIIITANA1NRcJWUE29u2Cei4C6rwMTENAzp6LSQYZrEmlv7FND3Fdq+k4J5h1qclXDl5Qwas3lGplgihpZOJDn8c6ez6i/PkQjHeo8XTamk4tCJcmEjA7yBobtvnSM04kIMzjThM184h//53hI627oorymleU8rdqed7/76BjS5UP6JefL9HPnFRSS6o6RiSexuB06/Z8QK6AALFizg0Ucf5aabbuKnP/0p48eP54477uDKK68csceUfyFCCCGEEEKIrGcaOrH6Ohz5heRMnoEe7ylEaS43qe4gscY92MZPkSK6lQyDZGfXoOFkMIipy6xnqwXGV6Bo7w54caN0wUxUu5QZrObO9fHWX57jsEt65mwnwjG8BTmEGjto2lhLbrXMqbeaO8dDfkUBHfXt/WLjD5uIUy44Wa67q5ult/2Fry++jmg42tOJXlZITn4Of/vtI5x5+SkUlRVkOs0xy+l1jWjRfCBnn302Z599tmWPJ7/dhBBCCCGEEEJRUR1OYo17iAGqs+cPQSPRs+TeHsiTArrFFE3D5h28m9Pm8aCoioUZCYBUOMqUC09i2+PL0RMfzqTPnzGB3PEVGCmZiW61dFpnzsXH89qSJ0gn09hdDhLdUQqnVDD/ipNl74AMMHSDC793KQ///G90Nn049qh0YhmnfWkR6ZTM37aay+Ni5/u1fPvSW8jJ9zFh2nh276in/YONeS/9yvmZTVCMelJEF0IIIYQQQmQ9VdNwFZdhpFO4CotRVA0AU9eJt7fgLiqVIrrVDANPRTndO3YNGPZPGLnNw8TgVIed5ve2MP2KRSS7o6TjCTxFeSS6uuncVkfhrEmZTjHr2B02dr6zmRO+dSGxrgjx7ij+0jwURWH36q2MWzgz0ylmnY6GDl79+3LO//ZFpJJpQq1B8krzMU2DB2+9j/O/fREFFdL1bKWcPD9zjplFUVkhhy48pOeCk8PGpjVbWb9qI4GCwUdVCQFSRBdCCCGEEEIIAFSHE3dxGZH6Wsx0TzetYrPjraxBccj8WsupKqnuMAVzZ9OxdsOH40MUhZxJ4zENGfScCclQmLzxFWx84BlUuw3N6SDeGaJg+jgC4ytARuxYLtoZZtPTb7Pp6bdx5/vwFQToqG1FTyaxe5xUzJ6I2z/0jG4xvLy5Xhq21HPPt/+Iy+fCXxAg2NxJMp4ERcHpcWY6xazjy/Fy7Xev5MHfPcqvvv3b3t8hhx11CN+47SvkFgQynKEY7aSILoQQQgghhBCAmU4Rrt3e/9iu7eRMmQE2e4Yyy1KGgT3HR3DTFgoXzMVMpzENA83lIlrf8MHKABnnYjVPcT47nnqV8WcchWkY6Mk0zhwvwV31pCNxVJn1bLlQw4dzt2MdYWId4d7PU9EEuowOsZzT46Swuoi2ulbi4TjxcLw3NnHuJGyyd4DlYtE4Dy99gteWvdnn+JrX17P0P+/lW7d/FX+uL0PZibFAXrVCCCGEEEKIrGcaBvHWpsGixNua8ZZXy0gXK33Qie6trKDt7XcBUBQVI50mZ/LEATe2FCMvFYlTeexctj22HEPXUTWNdDxB0ezJ+GeWokfj4JIuWyt5hxhDodltaHbNwmwE9MxE/8x3LuGRX/yd9j1tvccrp1VxyrWno8uKDcsF20O88vTKAWMb3t5EsCMkRXQxJCmiCyGEEEIIIbKeaejoseigcT0WxTQMKaJbSAEcfh9dGzdTOH8Opm70dKI7nUT21GPP8aFo8nxYrWPzLlLROFMvOw09nkRPJHHm5hBr62TDn5/k0K9clOkUs47T7yFQXkDNkdPJKc1HT+toNo36tdtRVVU24M0Am93Gi/c+y9lfPx9MCHd0k1MUIJlI8trDr3DCZ0/OdIpZJxqOYgxx8aKrPUjlhHILMxJjjRTRhRBCCCGEEEJRUZ0u9ER8wLDqcEoB3WImkOwO462uou3tNWCaoCiYuk5gyiTMtI4p3ZyWc+UHaH5nIx0bd6I67NicdpLdPRegHH4PpiHPidVM0+CIa8/grXufpWt3KwCKqjL+6JlMOG4Wpi77B1gtnUwz94wFPPW7J2iv78CX5yXc2U3l1CoWXngMqUQy0ylmHbfXjaIomObAr4ecPL/FGYmxRoroQgghhBBCiKynahquolJSoa4B4+7CUimiW8zUdZz5eXSsWUfhvMPANDENA9VhJ1JXjzM/FxMpDlrNW1KAardhpNIYyRTJZKo3VjJ3urxOMsDpc/PynY8SaQ/1HjMNgx2vrMPhdTHlpMMyl1yWCrWHeO3hl7nw+5eSTqZJRBO4/W4UVeHBW+/jM9+5JNMpZp1Avp+5xx7KOy+v6RcbN7WaQP7gY5GEACmiCyGEEEIIIQSGoZOORfCUVRFtqgfzg25aVcVTWkkqFkFzu6VAaCFF00h0dOEfX0P7u2sxdL23izAwZRLpWBx7IJDpNLNOKp5g6sWnsu3x5aQisZ6DikLx3Gn4qkqkEz0DIu3dfQro+9q+fC3jjpyOK8drcVbZzV/o5+z/OI9//e/j7H6/tuegojDl8Klc+dNrSKfSmU0wC3l8Hq75f5cRi8R4/53NvcfHTa3mm7d9RYroYr+kiC6EEEIIIYQQhkGyvRXV4cBXPb53ubeiKMTbWzH1NM7cfCmiW0gxIdbQiJFKUTBnds8oF8NAtdsI1+6me+cuPOWlmU4z67jzctj98rtMufBkTMPESKexe1yE6luItXXhnDou0ylmne6mjkFjqXgSIy2b8FrN7rDz798+zqR5kznqomNIJVLYnQ52v1/Lir+9xIlXnZLpFLNONBLj8Xuf5rPfuBhN0+hqD+LP9aPZNP5597+46puXyEgXMSQpogshhBBCCCGEqqK6XKSCXaS6Q/Rsawl8MC7EkVsgBXSLmQrYc3yEtu6g9a13QPngOfngAoezIH/Q2bZi5ETbOymaNZGtj71EMhQBVUUBSuZNw5kfwIglwO3MdJpZxVc0+IoMm9OOatMszEYAJGMJjvrMsbz8t+W89NfnUVQF0zCZOG8yc8+YTyouM9GtFuwMsejSk7n/fx9i9WvrsDtspJJppsyeyHU3X0N3KCxF9DFk3Lhx1NbW9jt+/fXX87vf/W5EHlOK6EIIIYQQQoisp6oa7qIyUsGuD470Lc66ikqkiG413cBTVkq8rYOcSRNQNA1MA0VVCdfuxlNR3ltQF9ZxeD00vPkek88/EdMwMNI6No+L7voWzFQa1S4FW6s5vC7cuT5iXeF+sfFHz0RRlQG+Sowk04A3/vkqUxdO55hLjyMZS+JwO6nfvJv3X1nP0Zccl+kUs46Kwj/ueozVr60DIJXsGamz5b3tLPnpPfzHrV/IZHpjXqw7RiQYJhFJ4PK68AS8uP3uEXu8VatWoesfrrJZv349p556KhdffPGIPaYU0YUQQgghhBACUJ0uvNUTiO6pxTR6/jBTVA1P1ThUp3TWWk5T0ZNJcqdPoe3tNRjJns5NRVXJnTkN1WHnwxUDwirpRJKyw2ex9dGXSHZHAFBUhZJ5M8ifWoMhs54tZ6QNFlx1KqsfWk53UyeqpmIaJlULppA/rhTTkItNVlNUhYUXHsvy+57nxT83oNk09LTOhDmTmHfWAhRF3ruslkykWLV89YCx7Rt2kpDVAZ9YsDXIv37zODtXb+s9NmHOJM664TwCQ6yU+TSKior6fH777bczceJEjj/++BF5PJAiuhBCCCGEEEIAoGoadn+AnMnTMdIpABSbHdVmR1Wlu9Zqigl2n4+GF1b06Tg3DYPOde9TfNQRKJqsDrCa0+/l/b/+Gz2Z6j1mGiZNqzbgzPWTP7Umg9llJ2eOm/cefoUFnz0FFIVUPIkrx0N3cyedu1spmlKZ6RSzkMkbj7zCzONmc+xlJ5KMxnF63TRuq2fDinUce9kJmU4w60TDsSFHgHW1By3M5uAR6471K6AD7Fi9jX//5nEu+M7FI9qRDpBMJrnvvvu48cYbR/QClRTRhRBCCCGEEAIw9DSpUBeR+jowjJ6Dqoq3chx2fwBVk0K6pVSFcN3uQUe2BDdtoejI+RYnJbr3NPcpoO+r8c11BMZXWJyRSEXizDxnIW/88d+EWz8oBCpQNW8K006fT1o6bC2n0NOJ/tJfnqNpe2Pv8XGzJ3D4eQv56MgwMfI8PnfvbPqB5BaMTMf0wS4SDPcroO+1Y/U2IsHwiBfRH3vsMbq6uvjc5z43oo8jl+2FEEIIIYQQAjASCSK7d31YQAcwDCJ1OzCSiYzllbUMk1Swe9BwKhKxMBmxV6y1a9BYMhRBioMZoCi88rvHPyygA5iw++0t7Hx1vUw9ygATePHPz/YpoAPsem8Hq5e9/eFGycIyNruNI06aN2Bs8qyJOJwOizM6OCQiQ58f7S8+HO6++24WLVpEeXn5iD6OFNGFEEIIIYQQWc/QdWItjYPG461NmPsW18XIUxXsgZxBw3a/38JkxF6e4rxBY86Az8JMxF6JcJx4sOeiks3lIreqqHfuwM433pfrGhlg6AbNO5sGjG1dtUXm1GeAYRhc/rULmX/8nD4jP2bMm8rXbv0CpirPySfh9A69Z8z+4p9WbW0tzz//PF/84hdH9HFAxrkIIYQQQgghBJgGRiI+aFhPxDENA0WVPiTLmCa+6gq6t+0Y8AJGYNpk6ebMAHdhLprLgT7AiJDSBTNlTn0GRNpDTDl5DhOOnUUiHCMZieMtyEHRVF7874cw0nqmU8w60eAQK2VMk2RMRuxYzeV2cu+v/84xi47goi+dQzQcw+11EWwP8adf3s8Xv//ZTKc4JnkDPibMmcSOAUa6TJgzCe8IX1y95557KC4u5qyzzhrRxwEpogshhBBCCCEEiqqhutzogxTSNbdHCugWM4FYSxuFC+bS8d56jGQKRe0pmudOn0qyswu7TzqfrZaMxJh0zvHUvvAm8Y4QAKpNo3TBTEzA1GXFhtVKp1eTnlDGy3c+SrTzwxFI5YdO4NTvXY6hSxHdar78wVfKKKo64t25or9oJMZbL77Dmy+8PXA8HLM4o4OD2+/mrBvO49+/ebxPIX3CnEmc/fXzRnQeumEY3HPPPVxzzTXYbCNf4pYiuhBCCCGEECLrKaqKu6iUVLBzwLiroFiK6FYzDOLNraguJ8ULD0ePJzBNA5vHQ6ypmdC2HXgrR3b+qejPU5jHnldWM/Hs4zBNEyOtY3M7iTS0gqpic7synWLWMYGXf/MYie5on+MNa3fgzvUx46wjM5NYFnN6nFROr2bPxrp+sZnHH4LDLUV0q8UjCcxBNqoGCHWFLczm4BIoCnDBdy4mEgyTiCRwep14A76PXUBPp3X0dJpkMoVm07Dbbdjt9v1+3fPPP09dXR3XXnvtp/0WPhYpogshhBBCCCGynqHrJLtDeCvHEW3aA3v/0FZUPGWVJENdaE6XFNKtpKp4qirAMGha8Rrm3m5aRSFn0gTyZk4HRZ4Pq8U7QxQfNoVN/3i2z0iXwtmTKJ49BT2WwC4FQkuFmzv7FdD32vX6+0w+8TDcOR6Ls8pusXCMYy45jreeWNnbnauoCjOOOYQph08jEYlDYSDDWWYXl8eJqqkYg6yWCeTJPhufhtvv/kRd56lUisb6ZrpDH17EsNvtVI+rwLWfi7KnnXbakBdGhtuoL6IvWbKEJUuWsGvXLgBmzpzJLbfcwqJFi/b7tQ8++CCXX3455513Ho899tiI5Nfc3EwwGNz/DS1UW1vb5/+jSSAQoKSkJNNpCCGEEEKIAzTaz8s/NdMg1dWO6Q/gHz8ZI9lTHFTtDhJd7aQjYelGt5ph4Ajk0PjCir7HTZPQ1u0UHTkfVJmJbjWby8HGB5dhfmTOdtt723AG/BQeMjFDmWWv7tauQWN6Ko2eTFuXjAAg3BHm+T89w1lfO5cTrz6FRDSOy+sm3BXm8V8/wiU/vCLTKWYd0zQ56tQFvPrMm/1iM+ZNtbQYK3oYhkFbS0efAjr0FNZrd+5hwqQa7I79d6RbZdQX0SsrK7n99tuZPHkypmly7733ct5557F69Wpmzpw56Nft2rWLb3/72xx77LEjlltzczOfvepqUsnEiD3Gp7F48eJMp9CP3eHkvr/+RQrpQgghRBaKx+PU1fVf1jxaVFdX43LJGILBjObz8uGgqBrOohLMVIrQtk37dKIruEvKcUoB3XqqSnjXh+8ZqsOOoqjoiZ6/v4Kbt1F0xLxMZZe1Ik3t/Qroe7W8u4nC6eMtzkjklhf2fmxz2rG5HCS6Y5iGgd3jRHOM+tLPQSe3OJfTrzuLf/3mcTobO3qPl00q57xvfQa3b+TmRIuBqarC/OPnALDmjXUUlRXS1tjB5FkTOOXCE1BlU2TLpdNpOjsGbkxOp9MkEkkpoh+Ic845p8/nixcvZsmSJaxcuXLQk3Vd17nyyiu59dZbeeWVV+jq6hqR3ILBIKlkgtiE4zFcsgxnf9R4EHasIBgMShFdCCGEyEJ1dXVcd911mU5jUEuXLmXKlCmZTmPUGs3n5cNBUVU0h5PuPR9ZzWmaxJrq8U+cJkV0qxkG6XAEd0kR/gnj0RMJTMPA5vUQbWgi2tDYMwxaWCreGRo0lorEMJHVAVbzFPgpnTmOmiOmAZAMx/AU5BBqaAcF7F65QGw1m9PGs398qk8BHaBxWwNvPfEGZ91wfmYSy2Ka3caOTbs4+6ozOO3ik2je00JhaQG+gJcXH3+FUy48IdMpZh3TMDHNwTejTqVSFmazf6O+iL4vXdd56KGHiEQiLFy4cNDb/fSnP6W4uJgvfOELvPLKK/u930QiQSLxYTd5KDT4ScFADFcAw1u4/xsKIYQQQmSx6upqli5dOiz3VVtby+LFi7n55pupqakZlvusrq4elvvJBiN1Xg6f/tz8kzJ0nXhr86DxeFszmtuNqmqW5CMAVcVbXYGRStP65tuYxod/aPsnjiNv1gykXms9X3kxze9sHDDmys9BrmxYT3PamXnOkbz6u8dJdMd6jxdPq2L+laeQisRx+2UmupVioRjte9oGjO1Yvb1nJnqRNGNaydRNTjrvOP7n+0uo3bK793hxRSHf/fXXsUknuuUUVUXTNHR94NVNTufo2l9jTBTR161bx8KFC4nH4/h8Ph599FFmzJgx4G1fffVV7r77btasWfOx7/+2227j1ltvHaZshRBCCCHEQFwu17B3etfU1Ej3uIVG+rwcMnhubhoYQ4xpNJIJMEyQv7EtY+o6dr+fxhdf7hfr3r6LwsPnSbk2A7ylBdg8LtLReL9YxdGHYZMxFZbT4yle+c1jJCN9n5OWTbvZ+MxbzDr/6Axllr0iwciQ8URsdI4FPpjZHDbu+uk9fQroAC31bfzP95bw3f+5IUOZZS+73UZhcT7Nja39Yk6nc1SNcoExcgo4depU1qxZw5tvvslXv/pVrrnmGt5///1+t+vu7uaqq67ij3/8I4WFH78z/KabbiIYDPb+t3v37v1/kRBCCCGEEFlmpM/LIXPn5oqqoXm8g8Y1t1fGuVhM0bQ+M9E/KrRlG4q0oluuu76FiWcfi7f0w9e25nJQdcJ8Yh0h0uHYEF8tRkKwsb1fAX2v2jc3kQwPHBMjJ6cwZ9CYatNwycUmy8UiMTa8vWnAWP2uRsKhqMUZCUVRyM0NUFxSiKZp2B12NE3D5/NSPb4Su3109X4PezZ5eXkoyv5PZDo6OvZ7m70cDgeTJk0CYN68eaxatYo777yTP/zhD31ut337dnbt2tVnXqPxwZI/m83G5s2bmTix/07hTqdz1C0REEIIIYQQ4tMa7nPzkT4vh8ydmyuqiquwmGRnB/3GUSgKroIiKaJbTAHSkcGLGulYDEWVIrrVos3t7Fmxi5K506k4+lBM3cAwDFrXbiFU20jhzAmZTjHrRNoHH3tlpHX0VNrCbASA0+Nk/GET2LlmR7/YYafMwSVz6i0Xjw7d/d/d1W1RJmJfNruN3PxcfH4v8XgCm92G0+EYdQV0GIEi+h133NH7sWmafPWrX+2dhThcDMPoMydxr2nTprFu3bo+x374wx/S3d3NnXfeSVVV1bDlIIQQQgghxGg30ufmB9N5uaHrJDo78FaPJ9ZU3zvaRXU48ZRWkOjqQHU6ZSa6hQzTxFmQR6y5ZcC4IzfQZ066sIa3rJDmdzay55V3sfvcqDYbye4Ipm7gLgggg+qtl1tZNGjM4XWhOUZfMepgF08kOPNr5/LSX55n42vvYxoGmt3GnNPmcsT5RxMLR/Hn+zOdZlbx+j1oNg09reP2usgtCBDq7CbS3XOxNr84L8MZZqdUMsWe3Y1E97lormkaNeOrcLmdH6sZxCrD/k56zTXX9Pn8hhtu4MILL2TChE92Nfqmm25i0aJFVFdX093dzQMPPMDy5ctZtmwZAFdffTUVFRXcdtttuFwuDjnkkD5fn5ubC9DvuBBCCCGEEAe74Tw3P+jPy02DdHeQVHcQV1EJqq1nDqeRShFtrkdRNSgqHSMDMQ8Suo6nvIzglu2Y6f6dtLlTJ2OaMhXdas6Aj7ypNRQdMolkdxQ9kcRdlEu0uQN7jgdVNueznCfPT6C8gGBDe7/Y9DMW4PDKynurKTr8687HWPS1czj2shNIxpM43A5MYNnv/8VJXzgt0ylmHafbwZmXn0L5uDJcbifNe1opKM1HVRTWr9qI0yWvE6sZhkFLc1ufAjr0bGBfu3M3EyaPwzGK5qKP+suRLS0tXH311TQ2NhIIBJg9ezbLli3j1FNPBaCurg5VllUKIYQQQoyY5uZmgsFgptPoo7a2ts//R5NAIEBJSUmm0xh2B/95uYLm9pLsaida338OtzO/CHP0NENlBcVmI1K/i6LD59K1YRPJYM/ICs3tJm/mNKKNTfgnjM9wltnHNAwKZ05i6+PLMdN67/HcSVWUj5uNoetDfLUYCYnuKAu/dBZrHnmZpg27wAS7y8GUU+ZSNms8yXACl3/wPR/E8NNTaWrX7+Kur/6G8skVlE0qp3ZDLW11PStrTjJPzXCG2SceTXDiucfwX9/+LclEiprJlTQ+2Uw8nuCmO79JMpHMdIpZJ51OE+waeByVruskE0kpoh+Iu+++e8j48uXLh4z/+c9/Hr5khBBCCCGyTHNzM5+96mpSyaHnSGbK4sWLM51CP3aHk/v++peDrpB+8J+XmzjzC0gGO+Cj3c2KgiM3D0Wani1lptMkOzoJ76olZ+J4AtOngmlipFKEtm4nHU/gGz8u02lmHbvHzea/P45p9H1BdG3bjbe0gKLZUzKUWfZSbRor7niEqvlTmHjsLIy0jmmY1L65ke6WTmaefWSmU8w68XCc2SfPYeGFx9DZ0E5HYwdTF04npzDAU7//F6mkzKm3mqIoPP6XZ/iPn36JcDDM7h0NnHz+cRSU5POv+57h7KvOyHSKWcc0zCFXlKVSqUFjuq7zk5/8hPvuu4+mpibKy8v53Oc+xw9/+MMRGwEz6ovoQgghhBAic4LBIKlkgtiE4zFcgUynM+qp8SDsWEEwGDzoiugHO0XVSEej+KonEG2qx0jEAdCcLtylFaRiUWweX4azzC6KzYazqIBYcwud6zdi83lRFJVUOAymibu0RDYWzYDgzvreAroz4EO120h0dWOkdZrf2UjhjIE3DRYjJ9rRTSwYYcsLq9n9zlYcHieRjm7S8SSqpjLjzCMynWLWKagqZME5R3DfD+4h0hXuPZ5Xls+lP7oSzS77a1hNURTOvvI0fvXt39G858O9NgIFOXz/jm+gySiqTyUcihDsCBENx/D6POTk+/HlDL0CRlXV3jn1A3ENMWLnF7/4BUuWLOHee+9l5syZvP3223z+858nEAjw9a9//VN9L4MZ9iL6jTfe2OfzZDLJ4sWLCQT6/tH161//ergfWgghhBBCjBDDFcDwFmY6DXGA5Nz841NUFXtOgHDtdlwFRah2BwBGMkG0qR7/uEkoY3pczdhj6jqe0hJS3RG8lWWkgt2Yho4jN0CivRN3aTGyOMB6iWCYwPgKSuZNJ94ZQk8k8RTnE+8IseeV1bKvaAbEusLkjy9l+ukLiAUjxEMRAuUFJMJx1j36KnpKRuxYTU/pPPzzB/sU0AE6Gzv4928f59xvfSZDmWUvRVP448/+0qeADhBsD/E/31/C9+/8ZmYSOwi0N3dw18/+zHsrN/QeO/TIQ/jyj66hoCR/0K+z2W0UlxTRWN/UL+Z2u7HbBx/l8vrrr3Peeedx1llnATBu3Dj+9re/8dZbb32K72Row15EX716dZ/PjzrqKHbs2NHn2GjaWVWMXTKf9cAcrPNZhRBCCDE4OTc/MJrDibdyHNH6WvR4rOeYy42vajyqw5Hh7LKPomnoySTO3BxaXnsTd2kxaBpdW7bjLS9DsdtQZGNRy+VOriYZDLP1ny/iqyrF7nbQ/M4mPMV5TL7gRLmwkQH5E8pwB7y8ec8zpBMfjj/IrSpi4XVnSddzBkRDUYItXQPGdr9fRzIm87etlown2fLe9gFjLfVtRLqjA8bE0MKhSL8COsDalev5w8/u5es/v27QjnRFUcgJ+MAsoaW5DV3XPzjmp6S0CJt98LL1UUcdxdKlS9myZQtTpkxh7dq1vPrqqyPaGDLsRfSXXnqp37G9823kBF0MF5nPeuAO1vmsQgghhBicnJsfGEVVsXt9+MdPwdTTgIKiaahDdEKJkWOm072b1ZadfDzx1nZMQyd38kTSySTJji5cJUUZzjL7OHweuusamfm5cwjXt5COJSiZNx0Mk+DuZrxlg3cdipHhcDlYce+zfQroAF27W9n5xvvMufi4DGWWvWLdsSHjqbgU0a2W2M+Fi6gU0T+RYEeoXwF9r7Ur1xPsCA051sVms5FXkIsvx4dhGKiKgmaz7Xe8zve//31CoRDTpk1D0zR0XWfx4sVceeWVn+r7GcqIzkS/++67+Z//+R+2bt0KwOTJk/nmN7/JF7/4xZF8WJEFZD7rgZH5rEIMD1kBc2BkBYwQo4ucm398qt0OUjjPOMVmw0inMXWDxhdW9B7vAjyV5QQmTwLDyFh+2SoZjuIuyGXDn5/os7mov7qUcaceiZ5Iw9BjcMUw66pv6y2gewsDOLwuIq1dJKMJ9ryzlZlnHo5rP7OJxfDKLcnt/TinKIAv10ewNUikK4zNYcPld2cuuSzly/Fid9gG3dQ1vyTP4owODtHw0BeMYvuJQ09jh8NxYOdd//jHP7j//vt54IEHmDlzJmvWrOGb3/wm5eXlXHPNNQd0Xx/XiBXRb7nlFn79619zww03sHDhQgDeeOMNvvWtb1FXV8dPf/rTkXpokUVkPqsQwiqyAubAyQoYIUYPOTf/+Ix0GiOdItUdAgUcvhwUmx3VNqL9R2IApq6j2Gx0rn+/Xyy6pwF3URGu0uIMZJbdHB4Xm//+LHxklE53XRNtG7b3dKULS0U7uymcVM600+YTbg0SD0YInDwHPZXmvUdeGXTTPjFy7E47C84+gppZ44l0helq6aKgohCbw0ZnYwcO9+AbJoqR4XA5OO3ik/j3/c/2ix15ynwcTrl4/kl4fENfEHLvJ/5Jfec73+H73/8+l112GQCzZs2itraW2267bewV0ZcsWcIf//hHLr/88t5j5557LrNnz+aGG26QE3UhhBBjiqyAOTDDvQJGVgEcOFkJIPYl5+Yfj5FOEWtuJNHRiubq+aMv1rgHV2ExrqIyKaRbTNU0wjsHf48Nbd+Bq7jAwowEQOe23f0K6Hu1rN5M0ezJFmckiiZX4A74eOOP/+6ziWhOWT5HfulMNIe8d1ktFo4y47hZ/P3W+4hH4r3HcwpzuPjmK4iH4+QU5GQww+wT7Y5y5MnzcXvdPP2354h0R3G6HJx0/rGccO6xdHdFKK3MdJZjTyA/h0OPPIS1K9f3ix165CEE8kfm33k0Gu0d+baXpmkYI7hCbcTeSVOpFPPnz+93fN68eaTTAy+dEEIIIUY7WQFjPVkF8MnISgCxLzk3/3jSsSiKquKrmUg6EgbAXVJOOtyNHo+i+qTgYSXTMNDjg7/364kkILP9rZbsjgwa0xNJZGdR69kcdlb95dk+BXSAUGMHO17bwKEXHpuhzLKXptl46D/7FtABQm0hnl7yL87+xvmZSSyLJZMp/veHS7nxl1/lyJPnkUqmsDvsGKbB72/5E1d+46JMpzgm+XK8fPlH1/CHn93bp5B+6JGH8OUfXTPkPPRP45xzzmHx4sVUV1czc+ZMVq9eza9//WuuvfbaEXk8GMEi+lVXXcWSJUv67Yq6dOnSER3yLoQQBzvpyD0w0o079skqgAMne2GIj5Jz8/0z9DRmOoWRThHete3DQCs48wsxkkkMXUfVtMwlmW0UBVdxIbHmlgHDroI8kA1yLRcYV07L6s0DxjwlBaDKc2K1YEM7+iBznuvf3crMs46wOCORjCfpbg8BMG72eAoqi2jc3kDD5j00bNmDocuIHat5/R6+9IOr+eU3f0NnW1fvcY/PzX/87EsUFMumyJ9UQUk+X//5dQQ7QsTCMdw+N4H8nBEroAP85je/4Uc/+hHXX389LS0tlJeX8+Uvf5lbbrllxB5zxDcWffbZZznyyCMBePPNN6mrq+Pqq6/mxhtv7L3dR0/mhRBCDEw6cg+cdOMePGQVgBCfjpyb74dhggnJzvZ+oURHGzaff9ARFmJkmLqOu7SY4JbtGImPnPsoCoGpUzBlY1HLuQvzcOblkOgM9YtVnzAP1SYXmqwWD0UHjZmGianL68RqiUicGccdwtEXHUfDtnrad7dxxDkLKbi+kGeXPk06IavAMuFvv3m4TwEdejbG/L/b/srNv7tx4C8SH4svxzuiRfOP8vv93HHHHdxxxx2WPeaIFdHXr1/P3LlzAdi+fTsAhYWFFBYWsn79h+39inQOCCHExyYduQdGunGFEKKHnJvvn2maJAYooO+V7GjH5pVxLlZSNA1QKD12IZ3rNhBrbgXAkRsgf/ZMFLsN5SPzUMXIS3SHmXrxKex5+V2SoTCKpmGkDSqOng0KGLKJpeXyqgffYNed60O1y4UNq+VXFrLgrCO493t34y/w48vzs+n1DaSTaS7/yVXYPbKxqNVSyRQ7N9cNGOto6ST2kdE7QnzUiBXRX3rppZG6ayGEyHrSkSuEEOJAyLn5x2CamOnUoGFDT0snusVMXcdIpog1N5M7eyZ5polpgqIqJLqCmKFu3OVlmU4z6yiKgqHrVBxzGF3b9pCKxckdX4Ez10+kI4iUBq3n9LkonFRO27aGfrEZZx2BzenIQFZZTjd45cHlnP/ti2ivb6OrqZPpR8/Am+djxQMvcuoXF2U6w6yTjA/+Ox4gFo5ZlIkYq2SLZiHEAZOZ3AdO5nILIYQQo5tis2Hz5aAnBu5Es/n8KDKmwlKKqpKKhDF1g8bnlveJuUuK8I2rAV1GIljN7vfRXdvArmVv9B5renM93tICJp13QuYSy2KddS1MPWUeOaX51L65CT2VxluQw7TT59Pd1EHhpHLI9WU6zawSjySYd+bhPParh0jGkr3Hvblezv3WhaQSQxd0xfBze104XQ4S8WS/mKIo5BbKSm8xNCmiCyEOiMzk/mRkLrcQQggxuqmahqugiERnG3xkzraiajjzClFVKaJbyTQMNIeT9q1r+sViza24igpx5OVanlfW0/U+BfS9Ik3tNL+zkdKjZmcgqewWD0ZZ+8grVMyZyIKrT+1ZrRGOs/2VdXTtbqXmyOmZTjHraHaVp373ZJ8COkCkK8KL9z7L+TdemKHMspeuG5xx6ck8fu/T/WLHnnkkqUE25xUjL5lIEovFiUZi2B02/H4fNrsNbZRt5i5FdCHEAZGZ3AdO5nILIYQQY4PicJIzcRrRxt2kw90A2Hw5eMoqUR0ypMJqqqYR2VM/aDxcuxtPRbmFGQmAjs2Dr/xsfW8rJXOng8dtYUYif3wppmGw552t7Hlna5+YJ8+PzWHPUGbZKxlLEukKDxhr3tGELpu9Ws5m18jJ83PFDRfx7ivv4fI4iMcSTDtsMqVVJThdMvYoExKJBLU795BKfrg6o6WpjcqaCrxeD5o2evY+kSK6EOITkZncQgghhDjYqKqK6vbgrRoP+gebI2o2NLsUoDLB0HWMZP9l93vpyRSmzKm3XCo6+NxgeU4yw+F1UTytkpZNe/rFZl1wNDanvIdZbX/zt3XZgNdyXr+H0uoSKmpKCeT72bZhF1UTyjnk8Bk01DbidEsR3WrpVJqmhtY+BXTo2ex9T20DE6eMQ9NGz/MiRXQhhBBCCLFfWnAPaqwr02mMekpy4K4zMbZodgdIzSnjVE3DVVxErKllwLirsABFHT0datkid3wFLe9uGjDmKy9CGUVdg9kiFY8z/4pT2LbiPXa8tp50PIm/JI9Z5x+Nw+cilUwhawOs5S/wg6IMuCG1w+3A6ZHVTVZLJpIUFOfxw2t/TjgY6T3udDn4/v9+S1YHZICu64S7IwPGTNMgHovjHEUbI0sRXQghhBBCDCoQCKCqGq76dzOdypihqhqBgIw8E+LTMnQdRyAHze1Cj/Xd8FVRVfwTajANKXpYzVWYi7soj1hrZ9+AolB1wnzMUTbDNhs4PG52vvE+E46bxbijZoBpoqgK6USKRHcMR3lBplPMOqpN49CTDmPtC6v7xRZ+5phRN+s5Gxi6we9+fHefAjpAIp7kju8v4Sd//F6GMstehmkCg69eSo+yFRtSRBdCCCGEEIMqKSnh97//Hbt37850Kn00Njbypz/9iWuvvZaysrJMp9NHVVWV7IEhxDBQNQ09nqBw3mGEd9URqW8E08RVVEjOlInE29rx1dRkOs2sk4zGmPKZk2h8cz1t67dhpHW8ZYVUn7gA1WGDtGzOZzVDN8itKGTZT/7SZ5yOJ8/Pcd+4gEQsicsrvehWinZFqJhWRaAkl3eeeotIV4TcklyOOO8oYt0xErFEplPMOtFwjN3bB95nI9gRItTZTXlNqcVZZTdNVbHb7aRSA48/8oyy/TWkiC6EEEIIIYY0bdo0pk2bluk0+tiyZQt/+tOfOPLII5kyZUqm0xEHESOVQk/GSXR1AODMLUBzOFFlLrrlDMPAkRug5Y23cBXkU7RgLigKyc4u2t99j+Ij52MqMn/bag63ix3LXqXmpCMpXTCzZ1yFqtC8ehN5Eyqx+z2ZTjHrKMCb9yzrN48+2tnNmodfZu7lJ2UmsSyWjCV46ndPUD2zhhOvOgWHx0k0GGHNc+/StL2RCXMnZTrFrJNKDn2BLx6NDxkXw8/hdFBSVsSeuoZ+MZ/fh802ulZsSBFdCCGEEEIIIQA9lSJaX0sq1NV7LNneij2Qh7e8WgrpFlNVleD2nRQcOotw3W5a314NhoGruIiCubPp2ryVvFkzMp1m1unYuJOy+YfQ8u4m2jZsx0il8VUUU3bEITSv3kTVCfPBm+kss0tnbQvGIGMPmjbsQk8MvcmlGH6B4lwUVaFuQy11G2r7xJweJ27f6OqwzQb+XB8uj4t4NM74aTUUVxTS1RZk89ptqJpKYZmMPcoEr9dD9bhKmptaScQTaJpGfkEuufm52B1Dn3d1d3fzox/9iEcffZSWlhbmzJnDnXfeyYIFC0YkVymiCyGEEEIIIQSQjnT3KaDvlQp2ks4rwGHPtTynbGYYBulolJY33sJTWU7R/DmgKCQ6Omlb9S6Kog41SlWMkGQkxp5HXiRvcjXjzzgKVdOItnay69mVpMLRniK6sFQqPsRoEBPZOyADHC47c89YwDtPvdUvduzlJ+L0ycaiVrM7bHz+u1fgD/jYuamW+p2NTJ8zhQuuPYuG2iaZU/8pBbu66WjvpDsUxp/jI78gj0Cuf79fZ7Pb8Nt9OF1OTNNE+eCY+jE2Dv/iF7/I+vXr+etf/0p5eTn33Xcfp5xyCu+//z4VFRXD8F19JNdhv0chhBBCCCGEGGOMdJpEW8ug8XhrMzavH1X+yLaMqml4ysqINbUQbWjCTKd7i+hGMoW3uhJFng/L5U2souXdTXRuqaVzS98OW39VSc/FDWGp3MriQWPewgCqTUo/VosEoxx5/lEUVBYSC0Vw+d1EOsOUjCulbHIFsWAM38coMIrho9lsVE2o4Gdf/S9ikQ9Ht9jut3HT/34Tp1NWm31STQ0t/OR7v+T1l1f1HjvquAX85BffpbR88PenfTn203X+UbFYjEceeYTHH3+c4447DoCf/OQnPPnkkyxZsoT//M//PKD7+zjknXQYqLGuTKcwJsjPSQghhBBCjFqmiWkMPA4B6ImZ0vZsJdMwcBUVkDd7Jja3m2hjMxg6udOngqLgzMsFTQq2VnPm+vGWFhBpau9zXFEVqk6Yj6kqGcosexm6Ttms8TSu29kvNvOsI3qGpgtLaXYba19czYyjD+H9V9axe0Md5VMqKB5fyjtPv8Wc02TFhtWS8QS/+dHSPgV0gHQqzR3fv4uf/emmDGU2tgW7uvsV0AFef3kVP/neL/nFb378sTrSD1Q6nUbXdVwuV5/jbrebV199ddgfD6SIPizcO1/OdApCCCGEEEKIT8E0TWy+HPR4bMC43R/ANGUkgpUURSHZHSYV6qbzvQ29xyN7GnDk52LzzURTVXDKWAQrJbqjTDzvBNrWbiUe6kZBQVFVSuZMJdEdwe517f9OxLCyOe1Uz59CXlURO15dT7w7Sn5NCVNPnUf7jkYKJpZlOsWsowAVUyr5v2/d1TuvftPr7/Pq31/miluvQpGLTZaLRRM01jYPGOsOhgl1hSmrsTipg0BHe2e/Avper7+8io72zhEpovv9fhYuXMjPfvYzpk+fTklJCX/729944403mDRpZDbulSL6MIiNPw7DnZvpNEY9NdYlFxyEEEIIIcSoZJoGjpwAyc52TD3dJ6bY7Nh9fjCkE91Khm6CaRLeVdcvluzoIt7cindcdQYyy252j5PObXUEJlSQen876WicvCk1pBNJnAE/prQ9W87mtLNnzXaS4RiHnLsQu9tJqKmDtY+8wpzLTkS1y9gjq6mayuP//Ui/DV+TsQRP/u9jXPLDKzKUWfbSU+kh48l40qJMDi7dofCQ8fB+4p/GX//6V6699loqKirQNI25c+dy+eWX884774zI40kRfRgY7lwMb2Gm0xBCCCEOajIW7OOTn5UQB07RbKSCXfiqx5PobCcZ7ALAEcjFmVeAHouhuDyZTTLLqDaVyO76QeOR3fX4aqoszEgAGIaJkUix/alXqD7xcDS7Rue23QR31DP5ghOlhJ4JCkw/YwGN63ay4V9vEg9FyK8p5bCLj8dfHGCISVVihIS7wsQ/MjZkr/Y9bSRjQ2wGK0aEy+vC43MTDfdfcaZpGrmFgQxkNfb5c3xDxn37iX8aEydOZMWKFUQiEUKhEGVlZVx66aVMmDBhRB5PiuhCCCGEGBNkNZMQYiQppok9J5funZux+3LwVvas6U51BwnvqSVn/BQpDlrMNExMfYg59XoaE1kdYDVVgcD4cgI15bSs3UI6niBvUhWl82bQuX03+TNHpnghhmBAR20zFXMmkT+utHdUiDvPz6433mfi8bMznGD2SSeG7nrW0zIezGp6SueCa8/m/v99qF/s9EtPIiGd6J9IfkEeRx23YMCRLkcdt4D8grwRz8Hr9eL1euns7GTZsmX88pe/HJHHkSK6GNOk0+7jkZ+TEMNHXk8fz0j8nGR82scnI9SEOHCKzYYe6SZn/BRiLU1E6mtRULDn5uEfP5lUIobTmZvpNLOKooCnooxY08AzbN2lJSiKjKmwnAKdW3bT+Oa63kNd23bjDPiYeslpkEiBN4P5ZaFkLA6mybM/u6/PcafPzXFfvwAjJa3oVsstyUXVVAy9f7Hc7Xfj9rkzkFV2szvthENhvnbrF3jqgefYs7OB4vIiTrvkRBKxJG6P7OfwSQRy/fzkF9/tt7noUcct4Ce//O4BzUM3DANFUVCUj9e2sGzZMkzTZOrUqWzbto3vfOc7TJs2jc9//vMH/H18HKO+iL5kyRKWLFnCrl27AJg5cya33HILixYtGvD2f/zjH/nLX/7C+vXrAZg3bx4///nPOfzww61KWVhICgRCCKvJ+07myPg0ITLrYD8vVxQFm8dLKhLGWViMq6gYTDABPRrB7vN/7D/qxPAwdBNnXi52v49Ud9+ZqqrdRs6kCZgyp8J6htmngL5XIhimYeV7VBw3NwNJZTe728nqvy/vdzwRjrHm4ZeZ/9lTrE8qy9mcNo684Chef/jVfrETrzkVh9uRgayym8Nhp6iskH/84XFOOu9Yzio7jc62IM89vJwFJ8zB5hj1JdJRq7S8mF/85sd0tHcSDoXx5fjIL8j7WAV00zRJpVJ0B8OEw1HsDhv5+bnYHXY0begL5cFgkJtuuok9e/aQn5/PhRdeyOLFi7Hb7cP1rfUx6v+FVFZWcvvttzN58mRM0+Tee+/lvPPOY/Xq1cycObPf7ZcvX87ll1/OUUcdhcvl4he/+AWnnXYaGzZsoKKiIgPfgRhJ0pX48UhH4sFHuqE/HumGzhx53xHi4JMN5+WKopBsbyMd7e5z3ObLwe7PyVBW2cvmtJNMximYeyiR+gYiuxswdR1PaQm+CTWgaagj9IeyGFz7pl2Dx97fSflCGR1itfYdTZiDbHzcumUPRnro0SJi+HU1dTLu0IkUVRfz+sOv0tXcSVFNCcdefgKxUJTujm78BfJ7xUqxaJwpsydy7Xev4OE/Psme7fUUVxRxwefPomZKFZFQBCqKMp3mmBXI9R9Q1/leiUSSXdvr0PcZ39bZ3kV5ZSmBQA6qpg76tZdccgmXXHLJJ8r3kxj1RfRzzjmnz+eLFy9myZIlrFy5csCT9fvvv7/P5//3f//HI488wgsvvMDVV189orkK60lXoshWUpzMHHnfEUJkq2w4L0+Fu/sV0AHS4VBPh3pufgayym7pSIyW11biLi0mb8ZUUFUSbe20vLqSnKmTyZk6KdMpZh0jNXhBdqgZ9mLk6MnUkHFjkAK7GDnpZJoHb72PifMnc+qXFuH0OIkGI7zy4HIaNu/hc//1pUynmHUUReFX3/4tufkBLr7uXPy5fqLhKP++/1nu/sV93Pp/3890ilknndZprG/uU0Dfq7G+Ga/Xg0MbPas2Rn0RfV+6rvPQQw8RiURYuHDhx/qaaDRKKpUiP3/wE95EIkEi8eHOyKFQ6FPnKoQQI0m6oT8e6YYWYnSJx+PU1dUNy33V1tb2+f9wqK6uxuWSeZgfx0idl0Pmzs2NdJp4W8ug8UR7C3Z/Dqo2pv6EGtOMdJrwrp7XeKyphVhT3+cnUrcbX1UFmt+XifSyVt7kaprf2ThgLDCuHGWIrkExMgonlg8ayynLx+aUFRtWyy3JQ7Vp7Fq7E7vDji/PR2dTJ41bG3DneHDneDKdYtZJJpK01LfRUt/G7d+4s188EopmIKvspus60cjAP3fTNInF4jicUkQ/IOvWrWPhwoXE43F8Ph+PPvooM2bM+Fhf+73vfY/y8nJOOWXwGWC33XYbt95663ClK4QQI066oYUQY1FdXR3XXXfdsN7n4sWLh+2+li5dypQpU4bt/g5GI31eDpk8NzfB7L8BXG/U+GBAurCMYZqYxhDPia7LU5IBDr+HnOpSQnVNfY6rNo2qE+bJc5IBmkOj5sjp1K7se3FDURUOu/j4IcchiJFhc9g45xvn4/K62fT6BlrrWimqLuKyW67ENE3scmHDcnp66JUy6SFW2YgRYg79G2OwMVWZMiaK6FOnTmXNmjUEg0EefvhhrrnmGlasWLHfE/bbb7+dBx98kOXLlw/ZVXTTTTdx44039n4eCoWoqqoatvyFOBjJTO6PT35WQgjRo7q6mqVLl2Y6jUFVV1dnOoVRb6TPyyFz5+aKZsORm0+sqX7AuDMvH2U/G1yJ4aUC3opyYo3NA8bdZaXynGRAMhxl3BlH0bm1jpY1W9DjCXJqyqg46lAize34q0sznWLWUTSNaafNp2hSOVteXEM8GCF/fCkzzjwCh9dFz6tJWCkRTaBpGv/85d+ZNH8KxeNK6Gru5OHb/86lt1xJKp7MdIpZx5vjxRfwEg5G+sVsdhv5JXkZyCq7qZqG0+nsswJxX27P6FohOiaK6A6Hg0mTembdzZs3j1WrVnHnnXfyhz/8YdCv+dWvfsXtt9/O888/z+zZQ29s4nQ6cTqdw5qzEAc7GZEhhBDiQLlcLun0HuNG+rwcMndurigKjtx8Eu2tGKm+xQ3V4cCek4eiKJbnlc0MwJ4bwB7IIRXsO9ZHdTjImTRBZnBngM3lZNeyN/BWFjP5ghNRgGQkxtZHX2LiucePus7BbGCkdJ792X2UzZ7AYRcdh81pJ9IRYuXdT+HJ9XPEtadnOsWso9k0tr2zhc989xLef2U9TdsbKaou4qLvX8rqZW9z7GUnZjrFrOPxubn6W5fx+5/c3S924ZfOwe7I3tUB5n46wkeK3W6jrKKE2p27++WQX5CHzTZ8Zevh+B7HRBH9owzDGPQqBcAvf/lLFi9ezLJly5g/f76FmQmRPWQm98cnc7mFEEIcrA6283LN4cQ/cSrJUCdmWgcTFJsNRyAXzTF6ZnJmC5vdjqElyJ89k3hLG5E99Zi6gbu0GG9VJYqmodjH5J+0Y17NKUcQD0VQ7TYwTTSPi0nnnwAKcrEpA9p2NGKaJl17Woi0B7G7nYQaOoh1Roi2d5OKD73xqBh+iViCiqlV/P1nD/SOrNj9fi1rn1/Nef/vQgy5AGi5aDjGhOnV3HLXd3jk7ifZs72B4ooizv/cIsrHl2flOBe7vefCQTQaxe12ZyQHt8fFhEk1tDS3E4vGsNltFBbl4/V50GzDt9osGu2Zvb73e/4kRv0Zx0033cSiRYuorq6mu7ubBx54gOXLl7Ns2TIArr76aioqKrjtttsA+MUvfsEtt9zCAw88wLhx42hq6pnT5vP58PlkwxkhhovM5BZCCCGyS9aclysKqmYnEQwC4CwoBCkKZky6O0zL62/hLCzAP2E8iqoQb2un+dU3CEydRM7kiZlOMeuYuoFmt6GYJrXPvYmeSBIYX0HBjPFEWzvxlhZkOsWsY6R1jvzSmTi9bratWEO8K0rhpDJOvfkKNj6zar9zh8XwszlsvHDPsn4/ez2t8+Kfn+XSWz6bocyyl9vtpLUpgj/Px8nnHYuJApgUlhXQ1dZFUVn21Tc0TSM3N5eWlp6Nuz0eT2YuhCpQUJSLYeSgKAo2m410Ok06/ekvbJimSTQapaWlhdzcXLRPMQZu1BfRW1pauPrqq2lsbCQQCDB79myWLVvGqaeeCvRsUKWqH873WrJkCclkkosuuqjP/fz4xz/mJz/5iZWpCyGEEEIIcdDIhvNyPZkkXLsNPRbtPZaOdKO5vfjGTUSzSze6lYxkkvCu3QAk2tpJtLX3iYfr9uCrrpJVAhbTXE4aVr5H63tbe4+F61toWb2JaZefIeNcMqB0RjV1q7aw8smneo+172xk+8vrOP6bF+IYZXOFs0EsFCMZG3jueVdzF+mErA6wmm4YxCIx/veHf+A/fnYdXp+LZCLFb370f5x/zSIKS/IznWJGlJb27GOxt5B+sMrNze39Xj+pUV9Ev/vu/rOK9rV8+fI+n+/atWvkkhFCCCGEECJLZcN5eao72KeAvpcei5AOd6PlSYetlQzANI0hbmBiyiIBy6Vj8T4F9L1SkRj1r62h+qTRP7rpYGOkDTb8641+x9OJFGv+sYIjv3hGBrLKbqYxxHsXIJearJdMpFAUhW//6gaefvB5dm/bQ3FlEV/50efANEll4TgX6BnBVVZWRnFxManUwXlxx263f6oO9L1GfRFdCCGEEEIIIUaakU6R6GgdNJ5ob8WeE0DV5E8oq6iAp6KMWGPzgHFPeSmKog4YEyOnY9OuQWOdm3dReewc65IRALRtqx+0Ktu+s1FmomdATmEOmt2GPkBh1pvrw+WT1QFWc7rtGIbBD676GfoHM+m3v7+Llc+9zVdu+TzT507OcIaZpWnasBSaD2ZyxiGEEEIIIYQQ+2VK62AGaA4Hjrzc/sddTjwVZZiGbM5nNXOIF4JpIq+TDNjvyHOZiW451aZx8udP6x9QFM746llSrMyAZDzNH/7z3t4C+l6mafKnX96Pnh569YAQ0kYhhBBCCCGEyHqKZsOZW0B0gHEuAI68AlSb/PlkNdMwCUyeSCoSIbK7AdPQ8ZSW4C4pJt7Wjm/c+EynmHXyp9TQvOr9AWO5EytR7VIctFrhxLJBY7lVRWgOu4XZCOi5llRUXcQF37mYNc++Q1dzJ4XVxcw5fT6eHDfIy8RykVCEjpbOAWOJWIKOlk7Kaz7dzGxxcJNOdCGEEEIIIUTWUxQFzetDdTr7xTSnC5vbm4GshD3HR2jbDqL1jXgry/DVVJPqDtP27hq8lRWgSIet1WxuJ3lTavod15wOqo6bi5GW1QFWM3SdySf1H6Oj2jTmXHI8yN4BljPSBn//2QM8+8enKBpXwpzT5+PP9/P4fz/MP3/xD/REds7fzqT9LcgwZcWG2A9ppRgGajyY6RTGBPk5CSGEEEKI0UpPJog17cFTWkk6FiUV6gLAEchDc7mJNdXjqRqHZndkNtEs07VpK/mHzSLR0Ul4Vx2mruMpLyNv9gw6128kb9aMTKeYdfR4ksrj5pI3pZqWdzeRjifIGVdB6dxpdO1uIm9CZaZTzDqqzUbZIeMonlLBlhdWEw9FyR9fypST59K0YSeV86ZkOsWsE2rrIp1IkU6keOvxvpu+JqIJYuF4hjLLXr6Al9yCAF3t/WtTDqeDgpL8DGQlxhIpon8KgUAAu8MJO1ZkOpUxw+5wEggEMp2GEEIIIYQQ/Zi6Trh2OzaPD0cgD4BUd5BYcwM2j3SiZ0Q6TeOLL+OpLCcwYyqKohBrbaPhueVobtmYLxNsHhd7XlmNatOoPuVwFEUl3hViwwPPMOPy0zF16US3mqIoNG+qo2XLHqadNg+700GouZOX//efHP2Vc0CRVnTL7XdOvSVZiH24fU6+eNNV/Pd3f4dp9H0CrrrxEpwuuUguhiZF9E+hpKSE+/76F4LB0dVhXVtby+LFi7n55pupqem/zC6TAoEAJSUlmU5DCCHEGCQrmj4++VkJceA0hxNHbj6xWJR0NEw6Gu4Td+QVSBe61RQFb3Ul0YYmonsaiO5p6BP2Vlag2GSwsOVMk8IZE0hFYtS9uAo9niRnXDmTzz0OVBVFk6mxVlM1haq5kymcVM7WF9YQD0XIn1DG8d/4DKiKTHPJgJyiADannXQi1S/mL8jB5ZOLgFaLhOJUTChj8Z9/yBN/fZrd2+oprSzmnKvPIDc/h0h3VLrRxZCkiP4plZSUjNqicE1NDVOmyLItIYQQY5us/PpkZPWXEAfOkZNLsqMNPdF3mb3mcmP35WQoq+xm83pxFhaQaGvvc1zzuPGNq5au5wxIxxIkw1FUm438KTWgKCiKAqZJy7sbKT38kEynmHX0tMHztz9IoLKI6afPx+Zy0N3cwYu/+ge+olwWXndWplPMOppN49QvnMHTv3+yz3FFVTnz+nOwuWSzV6spCjx57zMcc/oRXPylczFNUFWFztYgyx56iVMvOiHTKYpRToroQgghxAGQDt+PZzh/TrLy65OR1V9CHDjN6cI3bhLJUBfJrg5AwZlXgN2fg+aUrsFMSIW7yZ81g3Qs0XtxQ7FpOAMBoo3NeKvKM5xh9knHEgR31GMaBsVzpqFqKpHmDrb/61UmnHUMpiEXNqzWtq1nlYbNaUe1a6g2DZvDjqpqdO1uRR+gG1qMrFQ8Rdnkcq6+/QusfOw1upo6Ka4p4YgLjiIeiZGMJKAg01lml1QyzdRDJ/Gzr/13v01Er7jhImIRmVMvhiZFdCGEEOJjkG7oAzecndCy8ksIYRXN6cJdVIoj0LOkW3PICJdMUjU7ejJJOtxNuG4PpmHgKSvF5nLhKsjH1I1Mp5h1FJtG+cLZRFs72fPKavREkpxxZUy79FQ6ttXhypdVG1ZTVDj+m58hGYmz+bl3iAcj5I8v5bhvXEDtmxtlJnoGpJIp9mzczYZX1nHm9eegaRrJZJJH/+shjrvsBDw5ss+G1TRN5YHfPtKvgA7w8NInmHP0rAxkJcYSKaILIT4R6cb9+EbiZyU//49HuqEzSzqhhRBjmRTPRwe7z0vrqndJdnb1Hgtt3U5k9x5KjjsKZP625WxuJ/WvrqFr2+7eY61ruul4fyfTr1iEKTsmWq54ajVbX1xN4/pdVC+YisPjJNTUwYo7H+Xor5yN3e3MdIpZx+lx0r6nlaMvOpZX/76CruZOiqqLOe1LZ7Lh5fcom1yR6RSzTjyWINgRGjCWTCQJdXZbnJEYa6SILoQ4INKN+8kMV0eu/PwPnHRDCyGEEGNXsivYp4C+lx5P0L19FzlT5Xef1Yxkuk8BfS89mWLPK+9Sc9rCDGSV3fRkCm9BDtNOm8/O1zd80IlewpFfOIO6tzYx7fT5mU4x6xhpnYqplTz+638y/agZTJw7ma7mTh65/e9c+P1LUVRZHWA1dT8rMlRVLsqKoUkRXQhxQKQb95MZro5c+fkfOOmGFkIIIcYmwzQJ794zaDxa34h/4jhAumyt1LGldtBY1456qtMyE91q8VCU7uZOdry6vvdYtLObhrU7OPKLZ2LIc2I5u8tOflkBV9x6FW/9ayU712yneFwJ19x+Lem0jqZJOc5qnhwPBSV5tDd39ou5PC5yC4en8UocvORVK4Q4YNKNm1ny8xdCCCFENlABRRmiM1BVUJBuTqsN1a2pKArylFjP7nH2KaDvZegGG/61koVfOisDWWU3PWVw3w//jNPn4rjLTmD6UYfQ1dTBX77/J+wuO1ff/oVMp5h17HaNr95yLbd94w70fS4sKYrCdT+8GrtDSqRiaPIvRIxpMhf645GfkxBCCCGEGGsMwDeuimhDI66iAtxlpSiKQrytg2hDI77qSky7/ElrtbypNTS+1b9gC5A3bRyqTZ4Tq3XtaQWgbNZ4Jp1wKDannWh7N+see41gfZt0omdAsKULPa0T7YrwzF3/7hNLxpPEumMZyix76bqBYRh899c38OYL77BnZwPF5YUcddrhpJJp0il5nYihyW83MSbJXOgDN5xzoYUQQgghhBhpKmDzeSk57ijizS10b9+Jqeu4S0soOXYhNo8HUmlwZTrTLKMoFB02hdY1W/octvvcVCycjZFOZyix7KWqKid9+xK6Wzp575+vEg9FyR9XwsLrzqRh3U6GWtAhRoZq04aOy6bIlkundH7zwz8SjcSYd+yhTJ41kc62Lu646Q+YpsEvHvhJplMUo5wU0cWYJHOhD5zMhRZCCCGEEGOJoSiAQsfa9aSCod7j4V11RBuaKD3hGNhPoUoMPwXIn1JD/uQaWtZsJh1PEJhQSd6kKjo211I0e1KmU8w6RZMreP+pt9j1xvu9xxrX7aRpwy6Ou+EC7F650mS1nMIcHG4HyViyXyy3JA+XT54Tq4WDYbqDYY44eR6XXHceiqZimia+gJdn//ES7U0dVIwry3SaYhSTIroYs2QutBBCCCGEEAcv1TSJd3T1KaDvZSSThLZuJ3fG1Axklt1MTDq37Sa0q4HSww9BtdsI1TWx+R/PMvXS02R0SAak4qk+BfS9TMNk9T+Wc8z152Ygq+ym2TTO+o/zeOy/H8Y0zA+P222c9fXzsMkoKsupmsbP//ojIqEIS3/+F/bsbKSkopDzP38WZ1x8El0d/X/XCLEvedUKIYQQQgghxD5Mw8DQe0ZSqJoNZYiNFMXIMRSFSH39oPFYYxM5kyfKOBeL2VxOCqaNJ29yNS1rNqPHk+ROqKRs/nRAQZXN+SzXtm3w10mosYNUPGVhNgKgfU8bwdYuvnjn9XTURVM+LAABAABJREFUt6GqPV3PBZWFvPPUKg45YTY5hTJu1UpFFfm8+/I67vrpPb3HdoQi/Pq7v+fiL5/HCecclcHsxFggv92EEEIIIYQQ4gN6MkG8rZlkZwcAjrwCXIXFaA5nhjPLPqqiDHkBQ9E0FAvzET2SoQibHlyGM9dP2eEzUe12QnWN1L20isC4csadIYUoq2n76WpWVHmlWE2zaegpnfpNu3nnqbfoau6kqLqYBeccgaHrMhM9AyLBGH+94x8Dxh79079ZeMoCizMSY428aoUQQgghhBCCngJ6aNsmEm0tmHoaU0+TaGume/tm9GQi0+llHUM38U8YN2jcN64a02G3LiEBQOfWOgAcOV4wAUw0hx3NaSe4qwHTMDKaXzYqmFg2aKG8aEolNqe8TqwWKM4lEUvw1O+eoHlnE4logj2bdvPofz1MUU0JnoA30ylmnXAwTCQUGTCWTqVpa2q3OCMx1kgRXQghhBBCCJH1TNMk2dmOme4/9sBIJUkGuzBNc4CvFCNF1RQUTcNT0X+jN3sgB1dhAUpaCrZW05wOJp1/Av6KYhpWvseuZ1eS6Opm0rkn4K+RTfkywdR1Drvk+H7HHV4Xh118PBjy3mU1Xdd56/E3Boy9/MCLGLrsHWA1bT8bUdtlFJXYD/kXIoQQQgghhMh6ZjpNMtg5aDzZ1YEzrwDFJn9CWcXQTYKbtuIqKsBTXka0oRHTMHCXFKPa7bS9s4bio47IdJpZp2DGBHY+8xrhPS29x7q27yG4q4Gpl5yGIoUoy6maDV9xLid//zJ2vLKeWDBM0eQKKg6dyJ73tlOzYFqmU8w6wZYuDH3gi3yx7hixUAzkmpOlvH4PJRVFNNe3DhjLLcy1PikxpkgnuhBCCCGEECLrmQpDz9+WzUUtt7cTvXPd+3SsXY+iqmgOB6GtO2hb9S6YpsxEz4BUJNangL6XqRs0vPEeDFI4FCPHNE1C9e28uuRxSmdWM/WUeRiGyUu/eoiC6hJMWbFhOdt+Rk3JTHTrOdxOrr/1Czhdjj7HNU3rOe52DPKVQvSQS8RCCCGEEEKIrKeY4MjNJx0deF6qIzff4oyEoZv4x1cTrW/ASCaJ7K7vE/fVVGNqQy/PF8Ova1vdoLHQrgZMXUaHWK116x6CDe0suPJUGt7bQTwUJb+mhAVXn8q7f3uJhV86M9MpZh2Xz4XT6+LYy09g0rzJKIqCaZisef5dtry5CZus2LBcqKMbwzD4+V9+xBvPvcWOTXWU15Ry/FlHEe6O0NkapKBYfteLwcmrVgghhBBCCCEUBcXuwObzkw539wnZ/Tkomg0U6Xu2kqopqC4n3qpKIrv39Ik5cgN4KspQTOmwtZo2RIetYtP4YLdRYSGby8GuN96nbtVmSqZX4/C6qF+7nfVPvgH7WWUjRoaeTPPFO77CrrU7+PtP76eruZOi6mKOu+JE5p4xn3QinekUs47NpvFfN/6GaDjGNTdexhmXnkRbUwffv+anoMMvHvhxplMUo5wU0YUQQgghhBBZT7XZwDBw5OThzCsgFQqComD3BzD1NCigStezpQzdpGv9RvwTJ+AbV0W4djemruOtrMDmcdP65tsULTw802lmnbzJNdS/tnbAWNEhkz4opAsr5ZTmo6gqRlqncd3OPrHiqVUoMjrEcp5cH2898UafzUVbdjXz8M8f5IyvnMXUo2ZkMLvsFI/GiYZjANz76wf7xbvaglRNrLA6LTGGyDupEEIIIYQQIuuZpolqt5MMdRFt3LP3INGG3aS6Q6iaDdOUDlsrqZqCYrPT8tpK2t5ejd3vx1lQQHDLdhpfegXTMECeE8uZhkH5kbP6HXfl5VAwYwIYsjrAaolwjMMuPo6PbhLgyvEw7dT5YMjrxGqpeJJVT745YOylv75AMpKwOCOxvzn1H52VLsRHjfoi+pIlS5g9ezY5OTnk5OSwcOFCnn766SG/5qGHHmLatGm4XC5mzZrFU089ZVG2QgghhBBCHJwO9vNyM50m2rgHR04AT1lVz+gWRcFTXoXd5yfa2NMFLSykKPgn1ACgx+J0bdhI53vrSXZ2AuCfMA7FPnRRRAy/1vXb0NM6069YRMnc6eRPG8fEc46j+qQFbH3sJUwp2FrOm59D+85Gjrn+PCadcCiVcycz+zPHMO+Kk6l9exOqXVYHWC3Y0tVzoW8AiUicWHfU4oyEZlMpqykZMOYP+HB6nBZnJMaaUV9Er6ys5Pbbb+edd97h7bff5qSTTuK8885jw4YNA97+9ddf5/LLL+cLX/gCq1ev5vzzz+f8889n/fr1FmcuhBBCCCHEweOgPy9XFBRFJdqwm2jDbkzDwDSMns8b96BomsxEt5iiKCgK+Gqq+sWc+Xk4cgMo0oluOUeOl+LDptC5rY5UpGc0QufWOjS3k+I50zKcXXYyMSk7ZDyv3fUk3c2dKIpC7cqNvPO3F5l26nxZsJEBdufQF/g02VjUcqYJ1918DW6vu89xu8PG1376BQy5UC72Y9S/as8555w+ny9evJglS5awcuVKZs6c2e/2d955J2eccQbf+c53APjZz37Gc889x29/+1vuuusuS3IWQgghhBDiYHOwn5erNhuuwmLCdWFMPU0q1NUn7ioskZnoFjN0neDmbThycyk6cj6xphZM3cBdUoRp6LS/vYaSYxdmOs2skz+lhm2PryDa3N7neMfmWmZcsQh1P8VDMfxM3SDS1sUxXz2H5o11xIJRxh01E29BDtGOEP6y/EynmHW8eT7cOR5iof4d54XVRThkdIjlnE47W+uauPGXX6VuWz073t9FxYQyph06iR0baymtLM50imKUG/Wd6PvSdZ0HH3yQSCTCwoUDnyy98cYbnHLKKX2OnX766bzxxhsD3l4IIYQQQghxYA7W83LN68eek9vvuD03H5vba31CWU5RVVS7neCmLbS9vRo9nsDU03Suf5/2d98DVUEabK0X7wz1K6ADYJrUrXgbI5W2PqksZ6R11j+xkld//wRde1oxdJ2dr63n9T/8i3cffAlTlzn1Vkun05z/7YvQ7H17V11eF+d+4wLZYyMD9LRBsKObhl1NvP/OJlKpNNvX72Lz2u043U50eZ2I/Rj1negA69atY+HChcTjcXw+H48++igzZgy8k3FTUxMlJX1nHJWUlNDU1DTo/ScSCRKJDzd1CIVCw5O4EEIIIYQQB5GRPi+HzJ6ba3Y73ooa9KJSEl3tKIAzrwDV7kSV2duWM9JpvFUVRHbXY6Z1Yk3NfeIDjXkRI69r+55BY+E9LaBLcdBqbTsaATANk5bNfZ+fSFuIdCKVibSymt1up3btTq799XVsfWsz7XvaKJ9cQfWscaxe9g6Hn3tkplPMOrpuoKd1tq7bwXlXn4nDZSed1nnl32/Q2tjOpEMmZDpFMcqNiSL61KlTWbNmDcFgkIcffphrrrmGFStWDHrCfqBuu+02br311mG5LyGEEEIIIQ5WI31eDpk/N1ftdlS7HbvXl7EcRA9V0zBSafzja+jeWdsn5iwswO73I8OerWd3D775nmq3gWwdYDnnR2Y870tRFBlFlQkqjJ87kXv+31JmHjeLgspCatfv4uW/vcQVP70GRR1TgyEOCooKU2dPIr8oj9/8aCmtje0ECnI464rTmDF3CjabvE7E0MbEq9bhcDBp0iTmzZvHbbfdxqGHHsqdd9454G1LS0tpbu7bodDc3Expaemg93/TTTcRDAZ7/9u9e/ew5i+EEEIIIcTBYKTPy0HOzcWHDMNAc7tQ7HaKFy7AP3EcvnHVFC6Yi7eynHQshmobE31hB5W8KTWDxgpnTe4ppAtL5dUUow5SACydNQ67W+ZvW01FJdQa5Nr/vo7CqiI6GzsZd+gEPvvzz9PR2I6qytUmq2maxrYNO1i6+F5aG3tGUgXbQzzwm4d56cnX0LQxUSIVGTQm/4UYhtFniee+Fi5cyAsvvNDn2HPPPTforEYAp9NJTk5On/+EEEIIIYQQQxvu83KQc3PxIVVVUVDAMGh98x1S3WH0WJyOteuJ1jfiKizA0PVMp5l10vEk1Scf3u+4pziPkrnTZCZ6BuhpnXmXn4TykcKspyCHKSfNIZ2W58RqejrNk3c+xtIbfk/TjkZyigJsf3crf7zh9/z7N4+TTspzYjXDMHjsz08PGHvxsZdlYZPYr1F/ifimm25i0aJFVFdX093dzQMPPMDy5ctZtmwZAFdffTUVFRXcdtttAHzjG9/g+OOP57//+78566yzePDBB3n77bdZunRpJr8NIYQQQgghxjQ5LxdWU209o0GcRQX4xldjJFOYpolqt2MaBvH2TgITx2U6zayjaiqKqjLzc+fQuaWOdDROYGIlDq+btg3bKT5sSqZTzDpt2xpo2rCLY64/l/YdjcRDUfKqi7G7nbx5zzKOu+H8TKeYdbqau3rHTW1Ysa5PLBlLEuuOZSCr7BYORkjEBr7wbxombU3tVE4otzgrMZaM+iJ6S0sLV199NY2NjQQCAWbPns2yZcs49dRTAairq0PdZ5bUUUcdxQMPPMAPf/hDfvCDHzB58mQee+wxDjnkkEx9C0IIIYQQQox5cl4uMkHzelHtdjrXbyTW2DMeyJmfR96smXjKSvbz1WIkJEIRjHSaDX/5N8WHTsbmdrDn5XdRVIXKY+fKxqIZ4PS6aFy3k8b1O8mvKcHhcdG0sY5oewhFUVBkTIXlnJ7B9w4AsDlGfTnuoONwDr1BuNvrsigTMVaN+lft3XffPWR8+fLl/Y5dfPHFXHzxxSOUkRBCCCGEENlHzstFRqTTNL/6Bnr8w+7BREcnTa+8TtmJx4Jn8A0VxcjwFOXRtX03Uy88me49zaTjCcqPmIWh63TvbsZTVpDpFLOOrzgXza6hp3Q6dvXdi6Js1vg+FziFNby5Pry5PiJd4X6xkgmluP3y3mU1j89NzeRKarfu6RfLLQiQk+fPQFZiLJF3UiGEEEIIIYQQo1KsublPAb2XYRDctJV0PG59UlnO0HX8lSVsfvh5QrWNxDtC1L74Fi2rN1E0axKmzHq2XDIcY96Vp6B+pOPcVxRg0gmHYphGhjLLXoZp8pnvXozjI5u6enO9nPm1c9FTsp+D1QzT5MqvX0wgv+9eKy6Piy/+4KoMZSXGklHfiS6EEEIIIYQQIvukk0liTa2DxuNt7T2bWMoKfEu1rt2CuyiXQ798IUYqhambKHYNTHj/b08z44ozM51i1nHn+9n+ynucevOVYJoYuoFqU0nFEmx/dT0zzzoy0ylmnUQkzo7V2zj//11ER0M7Xc2dFFYX4w14qVu/i4lzJ2c6xawTCUX50y/v56d338SOTbXs2LiLqgnlTJk9ibtuvYeLvnwuZdWlmU5TjGJSRBdCCCGEEEIIMeooqorqGnyusOZwoCiKhRkJAE9RPv6qEupeepuurbWYhokrP4eqExdQcfQckKfEcsl4ktmfOY5Ny1ZR99Ym9JSOO8/HIecsZMaiI9B1WR1gNZvdxmsPvwqmSX5FAf48P1tXbSHY0oXdaWfSfNmA12out5Mf/OZGVr7wNm88+xZun5v1b73Pnh0NXP/TLxAORjKdohjlpIguhBBCCCGEEPsw0mnMD4pOimZDtcmfTZmgKAreynIitbsHjPvGVaPIc2O5nHFlbH7oeRKdod5j8Y4QWx95gamXnobqlqUBVnP53Lx1zzLadzT2Hot1hln1l+eYf9UplB86IYPZZadwRzeYPZvsdtS301Hf3htLJVIk48lMpZa1/Lk+/v3Aszz+56f7HN+5qY6O1i4uv/4zGcpMjBUyE10IIYQQQgghANM0SMeidO/cSnDzeoKb1xPetZV0LIr5QTFEWEdRFPR4gsDU/mMP3GWlaG6XND1nQKy1s08BfV+7l7+DMdAMezGiEqFonwL6vjY8+QapiDwnVnN4Bl9FA2CzaxZlIvYKhyI89bfnB4y99sybxKKyx4YYmly2F0IIIYQQQgjASCYJbdsE+2zCl45GCG3fRGDyDDSndNhaSVFVHIEckl1BSk84hkR7B4au4yosIBkMgWGgDTHuRYyM4K6GQWPR5nYw5IKT1dp3NQ0ai3VFSCdTFmYjADw5HnKKAlRMrWT60TMBMNI665a/R6w7hkPeuywXDkZIJQZ+LZimSVtzB1UTKyzOSowlUkQXQgghhBBCZD3TMIi3tfQpoPcyDBIdbbhLylFUWcxrJc3rwVtdSee69zFTKVBVYvWN5M6chj0QyHR6Wcnh9w0a05wOmYmeAZ7cwZ8TRVXRbNL1bDXTNLnsx1fx9r9W8sQdj5JOpHB6Xcw/63BmHDsLwxjgd40YUU63Y8i41+exKBMxVskZoBBCCCGEECLrmbpOOjzwiAqAVDiEKUUPy5mJJC2vrSTR1k4yGCLZ2UUyGKLljVUYCRlRkQl5k6tgkA1di+dM7SmkC0vllBdgc9oHjFXOmYQio0Msl4wmWHH/C7z7zNukP+h+TkTivPaPl1n7/LvoKT3DGWYft9fNxJnjB4wVlhbgH+JilBAgRXQhhBBCCCGEAFVFsQ9chAJQbfZBC4di5EQamjAGGkVhmnRt3IwuhXTL6ak0E88+FkXt+3rIqS6l8JCJGEnZMNFqiUiCo758Npqj77CBQEUhM846AlMKtpbT7DY2v7FxwNi7T6/q9/oRI6+koojrf3wthaUFfY77c338v/+6nrLqkgxlJsYKGecihBBCCCGEyHqqpuEuKiOSTOIqKEJ19Myr1ZMJEm0tuIpKUTXp5rSSnkqRaG0bNJ7o6MJIpdGcMlvYSm3rtmJzOznkc+cSbmglFY3jryoBw2TDX/7NIdeck+kUs47b72Lriq2cdvOVpOJJ0skUDrcTRVXY9spapp++INMpZp3uju5BY+lkmmRMLjZlQuWEcn74+/9HY10TtZt3UzaulJrJlRSU5mc6NTEGSBFdCCGEEEIIIQDV5cZTUU2sYTd6Ig6A5nLjrRyH6pJNRa2maBqae/Cfu2wqmhnOHB+7V7xDw+vv4a8uxe5x0rTqfdKxODaXU2aiZ4Bhmkw6dhbvPfoqDe/twDRMHF4XU0+dx5ST5pKOy8aiVnP73UPG7a7BVz6JkVVWXUJZdQlzjzk006mIMUaK6EIIIYQQQggBmHqa8K5tYJq9x/R4jO5dWwlMmQk2KXpYydR1vJXlhHfVDRj3j6uWgm0G5E6upnXdVqpOXIDD78FMG5QdMZvmNZtxeN1o+9m8Tww/VVF54+6n6Nrd2nssGYmz7rHXsDlsVMydnMHsspPb5yZQnEuwpatfrGpGNU6PXAQUYqyRmehCCCGEEEKIrGcaBvG25j4F9A+DJvH2FtlY1GKKppGKRsk7ZHq/efTe6kpUux1F5tRbTlFg8gUn0bRqAxv+/CTv3/dvtjz8PP6KYopmTcKQrmfLxUORPgX0fb3/9Fuk4zI6xGqGbrDo+nPwfmSzyryyfI657ARSCXmdCDHWSCe6EEIIIYQQIuuZho4eCQ8aT0fCmIaBokofklVUVcWZm0tw81aKjzqcVHcYUzdwBHKIt/XMSrd5PBnOMvuYhsn2J1aQN6Wa0vkzMA0DM63TsmYLNpcDb0nB/u9EDKuu+vZBY4nuGEZaNha1WkdjB8/f/QynffEM9LROsDVIXlk+6WSaJ379Ty76wWWZTjFrJZMputqCxCNxnG4ngYIcXG5ZGSD2T4roQgghhBBCCAGodkfvLPT+MRnlkgma2427uIiW19/C5naDqpCORPHVVOEslGJtJsQ7Q1SduID619dQ/9paAGweFxVHHUqstQt3YW5mE8xC7lzvoDHVpsmmyBngyfHQ0dDOo796GHeOB0+Oh3BnmESk53eMU8YeZURXe5An/7qMZQ+9SCqRQtM0jj3zSC796gXkF+dlOj0xykkRXQghhBBCCCEAR34hqXBo4FheocXZCAAznUZPpSk/6TiSXUEMw8CZl0sqHMFIJsErnehWs7mdbHt8BalwtPdYOhqn9vk3GX/m0SiKrNawmjvgw+5xkoom+sWq5k0GVcYeWc2T4yGvNI/Opk5ioSix0Ievl5pDxuEYYtNkMTIS8QSP/ulfPPP3F3uP6brO8idfo7srzPU/+QK+wOAXpISQ325CCCGEEEIIoaiAgqukvF/IXVrRMytdClGWMk2TSH0DXevfp+GFFYR27CSyu57GF1+m7a136NywCT0pc4WtlugK9ymg76vpzfWYpuwdYLVUIsnh15yG4yObVRZOLKdq3pSB93oQIyq/vICLbr6cnMKcPscLq4s464ZzyS3JzUxiWayrLcRzj6wYMPbOK2sJdg58EV2IvaQTXQghhBBZIx6PU1dXNyz3VVtb2+f/w6W6uhqXS7qThLCaqmloTgep7i584yZjJHuW3KsOF8muduz+AKoqIxGsZBoGidYPZz0nO4N94smuLkw9DcioHStFmtoGjcXag7JvQAZ4cn2s+utzzL3iZIxUmnh3FF9xLpHWIA3rdjJ90eGZTjErlYwr5cr//BzBli66mrsoqCjAXxggvyw/06llpUh3BH2I/QE6W7uoGFdmYUZirJEiuhBCCCGyRl1dHdddd92w3ufixYuH9f6WLl3KlClThvU+hRD7ZxoG8bYWkp3tJDvbUe12TMBMfdDprGp4y6ukQGghRVWx+bzQPHDc5najyIUNy7nycwaN2TwuTEM60a2WTqc59DPH8tqSJzENA7vbSSwYoWB8KXMvP0lWbGRQQUUhBRUyDmw0cHmGblLxB3wWZSLGKimijxKjvTNOuuKEEEIcDKqrq1m6dGmm0xhSdXV1plMQIiuZho4ejfR+bqT6Fp30WATTMKSIbiFFUfBPGEf39p0DxnOnT0FzyuZ8VguMK0fRNEy9f0dn2eEzsbmdA3yVGEkd2xtper+W475+AbFghHgoQk5ZAXoyxUu/eogT/99FmU5RiIzLyfNzyOHTWf/Wxn6xinFlBPL9GchKjCVSRB8lRntnnHTFCSGEOBi4XC75fSaEGJiiojqc6In4gGHV4ZQCegbYPG6KDp9H29ur+3Q450ydjLNARiJkQryzm4lnHcPOZ17v0+GcP208zoCfdCyBXTZNtJQ710fD2h00rN2BO9eHK9dLqKEdPZlGs2somrx3CeHL8fKVH32eX337t+za/GETa0lFEd/59Q3kFuZmLjkxJkgRfZQY7Z1x0hUnhBBCCCEOZqqm4SouJdUdHDDuLiqVInoGqDYb7vJSyk87iVR3GFPXcQRy0JwOVLvMQs+Eru27iTZ3MOHMY9DTafREElduDqG6JrY9sYLZX7wg0ylmHVeOF6fPTSIcI9b1/9m787goq/0P4J+ZgZlhHRbZRgXBBRXFXUMU97xuqRWacXPNFumWlt0yRcQ02yy9pajldgs10dIyy7RUMtFcQ3FXFBUQlX2bYWae3x/+mOsEKOoMzzB83q8Xr5pzzjzPd55B+PKdc85ThNK8ImOff5eWkIA3RRZLWXEpivOKoS3VQuGkhLObM+QOXEEjFi8/T8z4z1TkZOchO+MmPL094OnrAQ8vN7FDozqARXQrwZlxRERERETikikc4Kj2R0nmVUAQ7jRKJHBU+0Oq4MxasUhlMkidHGHv5Ch2KATAwUOF7GNncX7LbsgU9pDa2aG8pAwQBNg7OUDCem2tK9do0WXc4zj81U6UFZQY231aB8CvbSAECCJGV38V3MzHT8u24fyhc4AgQCKVIrRve/R+rh9cuHWIaNw8VXDzVCGoVYDYoVAdwyI6ERERERER7sx6Vrh7wt5VBX1ZGSABZAolpDI7SGS8gaWYdKVlMGg1EAwCZAoFZEpuryMWVVBDSPbKIOj00GvKodf8b0sX3y4hkCg5y7a2Obm74OCaHQh9sgekdnbQFpfB0d0ZuVezkX3mKjyCfMQOsd4pKSjBlk82I/3kZWObYDDgr11HAQkw8IXBkPPfClGdwiI6ERERERHR/5PIZJDJZJDJeXNEayAYDNDk5uHWn0egKykFAEjt7eHRvi0c/Xy4pYsIBKkEwZEDcP6736Av0xrbG4Q2h0fLJhDKygFHBxEjrH90Oh06PtMHf8T/AG1xKewUcmhLyuDTOgAdR/eBrrQcUIkdZf1SnFdkUkC/W8qvx9EjMgJyP97XgaguYRGdiIiolpWVlSE9Pf3+A2vgypUrJv81B39/fyiV3LaAiIjEpyspxY2k/SY3FTWUl+PWoaPw7RUOZQNPEaOrnyQG4Pq+42jyeBgkAPTacshdnJCXdh2FV7Pg0TpI7BDrHTs7O1xLvYhe056EpqAEmqJSODVwg53cDhf3/YXgxzuLHWK9U5RTWG2fYDCgrLjqm1gTkfViEZ2IiKiWpaen44UXXjDrMefPn2+2Y61YsYL36SAiItEJgoCi9KsmBfS75aWegVdYV8jknI1emwqv3UDh1SwUXs2CxE4GqUwGvebOjHSFmwucG/nAwd1V5CjrFxcfd6jbBOLgyp9RfDsfjh4uyM/KR2BYS7R8vDOUvJ9ArXNUOVXfKZFA4cjVTkR1DYvoRCQaa5+NC3BGLlmGv78/VqxYIXYY1fL39xc7BCIiIggGA7Q5edX2awsLIeh1AFhEr03FWbeM/y/o9NDr9MbHmrxCwMCbWNa20rwi7FuyFcW3CwAA2mINAOBS0gk4qJzQ8h9dION9HWqVk5szvJv4IPvyjUp9LboF37vITkRWiUV0IhKNtc/GBTgjlyxDqVTy+4qIiOg+JFIp7FWuKL2RXWW/vZMTJFIWBmubQwP3avvkLo6ARFKL0RAAFGXnGQvof3du51E0eaw1nDy5OqA2Obs7I3LmGCTOX29SSA8IDcI/XhwCpRMnahHVNVZdRF+wYAG+/fZbnDlzBg4ODujevTs++OADBAcH3/N5ixYtQnx8PNLT09GgQQM8/fTTWLBgAWeTElkZc8zGPXr0KBITE3H79m1jm6enJyIjI9GxY8dHDZEzcomIiP4fc3OqbRKJBM5N/FFw/iIgVJ7d7NY6GDKFXITI6jdVEzWk9nYwlOsq9fl1aws5Z9jWuoKsHDi4OSH48c5w8nSFQaeHzN4OWamXcTHpBPRVvFdkee6+Hoh6dxyK8opQkl8CZ3dnOLk5w9GV2+sQ1UVWXUTfu3cvoqOj0aVLF+h0Orzzzjt4/PHHcerUKTg5Vf2Led26dXj77bexatUqdO/eHefOncP48eMhkUjwySef1PIrIKJ7edTZuElJSVi+fDm6du2KkJAQFBYWwsXFBRqNBsuXL0dcXBwiIiLMGDEREVH9xdycxGDn6ADv8G64dfAIDOXlAO7MUHdv0xpydzdxg6un7F0d0XL04zi/ZTfKi0rvNEok8OnUCm7NGnPbEBG4qhugy3OP4/jmJBRk3JlcJJFI4N+tJbqOfxwye6su/dg0J7c7hXMiqvus+ifpzz//bPJ4zZo18Pb2xpEjR6otjO3fvx/h4eF49tlnAQBNmjTBmDFjcPDgQYvHS0S1R6/XY+nSpXBzc6vy37e7uzvi4+MRHh7ORJ6IiMgMmJuTGKQyGRy8GkDdvxf0ZRoIBgNkDkrIlEpImeOJQl9ShpK8ArR6dhB0pRoYtOWwd3ECpBIUXr0BpZuL2CHWO0pXB+z99CeU5BYa2wRBwJUDp6F0dYRfu6YiRkdEZBusuoj+d/n5+QAADw+Pasd0794dX3/9Nf7880907doVly5dwvbt2/Hcc89V+xyNRgONRmN8XFBQ9V5iRGQ9UlJSkJWVBQCwt7dHZGQkBg8ejO3btyMxMRG5ubnGcR06dBAzVKtl7Td25U1diYisG3Nzqi0SqRR2jo6wc+QWCNZAU1QKRzcVzqzfAW1hMWRyGQw6A3w7t0aD0ObQFpVA7sz3qjYV38w3KaDf7eLeFASFt4Fcya2PiIgeRZ0pohsMBkydOhXh4eFo06ZNteOeffZZ3Lp1Cz169IAgCNDpdHjppZfwzjvvVPucBQsWIC4uzhJhE5GFVBTQ7ezs8OOPP0Iuv5MUvvDCCxg/fjwGDx4MnU5nHEeVWfuNXXlTVyIi68XcnKj+slfKkbp2G/TaO9vr6LV6AEDmn6lQuLnCs3WgmOHVS/mZOdX26TTl0Gm5JzoR0aOqM0X06OhonDx5Evv27bvnuD179uC9997D0qVL0a1bN1y4cAGvvfYa3n33XcTExFT5nBkzZuD11183Pi4oKEDjxo3NGj8RmVfFz4K+ffsaC+gV5HI5+vTpg507d2Lfvn0YNGiQGCFaPXPc2BW4U0g5f/488vPzoVKp0Lx5c0ilUrPER0RE1om5OVH9VXAl01hA/7uMAylwbaKGnVJRy1HVb67q6lcE2SnlsJPXmdIPEZHVqhM/SV955RVs27YNSUlJaNSo0T3HxsTE4LnnnsPzzz8PAGjbti2Ki4vxwgsvYObMmVUWdhQKBRQK/pInqksqlnnfvHkTBoPB5N+2wWDArVu3TMZRZY96Y1fgzs1dly5dajLj39fXF1OmTOFNXYmIbBRzc6L6reRmbrV92oJiQBBqMRoCABcvdzh6uKAkp/KWLs16hULJG1sSET2yR58qaEGCIOCVV17Bd999h99++w2BgfdfFlZSUlIpGa+4qaDAX+ZENqPij/Zjx45h1qxZSE1NRUlJCVJTUzFr1iwcO3bMZByZX1JSEmJjYxEUFIQlS5Zg+/btWLJkCYKCghAbG4ukpCSxQyQiIjNibk5EAODk41ltn0LlDIlUUovREAA4e6nQ85URUDVsYGyTSCUI6tEGTXu2hb3CXsToiIhsg1XPRI+Ojsa6deuwdetWuLi4GGc6qlQqODg4AADGjh2Lhg0bYsGCBQCAYcOG4ZNPPkGHDh2MS0ZjYmIwbNgwY8JORHXfiy++iC1btkAmk+H8+fOIjo429nl7e0Mmk0Gv1+PFF18UMUrbpdfrsXTpUoSFhWHevHnGAklISAjmzZuHWbNmIT4+HuHh4fzZS0RkI5ibExEAuDT2hUwhh16jrdSn7t4OSndXEaKq30pyC3H0m93oMKoXZHI76LU62DsqkXc1Gxf2pqDNE90hs+fPXCKiR2HVRfT4+HgAQO/evU3aV69ejfHjxwO4c2O8u2e3zJo1CxKJBLNmzcL169fh5eWFYcOGmfVmd0QkPgcHB4SHh+OPP/5AXl4e+vbti+DgYJw9exa///479Ho9wsPDjX/Uk3mlpKQgKysLMTExlWYYSqVSREVFITo6GikpKejQoYNIURIRkTkxNyciAJC7OaPlMwNx4fu90OQWAAAkdjKou7WFaxO1yNHVT4U3cnHz7DXsOXutUp9MbodmvdvByZMfbhARPQqrLqLXZInnnj17TB7b2dkhNjYWsbGxFoqKiKzF/PnzMXPmTPzxxx/47bff8Ntvvxn7wsPD+Qe6BeXk5ABAtUv5K9orxhERUd3H3JyIgDtbMjn7NUDLUQOgK9PCoNPD3lEJmaMCcgel2OHVS0U386vt02t10JfrajEaIiLbZNVFdCKi+5k/fz5KS0uxfPlyXLt2DY0aNcKLL77IGegW5uHhAQBIS0tDy5YtkZKSgpycHHh4eCA0NBRpaWkm44iIiIjItnDbFuvh6lt9zm3voIBMzj3RiYgeFYvoRFTnOTg4YOrUqWKHUa+EhobC19cX//nPf5CXl4cbN24Y+3x8fODm5gY/Pz+EhoaKGCURERHZAoNeD32ZBrriYgh6A+xdnCFTyCG1Z2GQCLhzY1FnL1WVM9JbPt4JDipHEaIiIrIt0vsPISIiMiWTydC7d2+cPXsWWq0Wb7zxBjZt2oQ33ngDWq0WZ8+eRa9evXjTOCIiInokBp0OpVk3kLFzN278nozs/Qdx/ZffkH/+YpU3tiSqj5QqJ/SYMhyeQX7GNqmdDM37tod/15aQMicnInpknIlOREQPTK/XY8+ePQgODkZ+fj4WLlxo7PPz80NwcDD27t2LyZMns5BORERED01XUoqbBw6bNgoC8k+fg8LdDY5+vuIERmRFSnOL8Ef8D/DvGoyWAzvDoDdAKpXi6tFzOLvzCNo91RMye5Z/iIgeBX+KUr1XVlaG9PR0sxzrypUrJv81B39/fyiVvEEPWZeUlBRkZWUhJiYGzZs3x9atW5GRkQG1Wo3hw4fj/PnziI6ORkpKCjp06CB2uERERFQHCYKAwrTL1fbnnT4HhYc7ZApF7QVFZIUKsnJQmJ2L1G0HYKeUw14ph6awBAa9ATJ7GYIHdIKTJ/ewJyJ6FCyiU72Xnp6OF154wazHnD9/vtmOtWLFCrRo0cJsxyMyh5ycHABARkYG3n33XWRlZRn7Nm/ejEmTJpmMIyIiInpQgsEAXWFxtf26khIIBkMtRkRknYpvF8BV7YnWg7pCMBigKSqDUwNXFGTm4NSPB6Ev14kdIhFRncciOtV7/v7+WLFihdhhVMvf31/sEIgq8fDwAAC89957CAsLQ0xMDAIDA5GWloaEhAS89957JuOIiIiIHpREKoWigSdKb2RX2S93U0Fixz9pidwDvBE6IhyH/rsTmqJSY7tXi0YImzwYdnLehJeI6FEx46B6T6lUcqY30QMKCQmBTCaDq6sr5s6dC7v//wM2JCQEc+fORWRkJAoKChASEiJypERERFRXSSQSODVWI//sOQg6faV+99YtIbNncZBI7qBA0qJvoS3RmLTfPHcNzl4qeAU3EikyIiLbIRU7ACIiqntSU1Oh1+uRm5uL2bNnIzU1FSUlJUhNTcXs2bORm5sLvV6P1NRUsUMlIiKiOszO0RG+vXrA3tXF2CZTKuHdvatJG1F9VpidV6mAXuHKwTPQ3jU7nYiIHg5nohMR0QOr2Ot85syZWLlyJaKjo419fn5+mDlzJubPn8890YmIiOiRSCQSKNxU8OnZHQatFhAMkMrlkCmVkEgkYodHZBVKcgqr7TPo9NCXV17JQURED4ZFdCIiemAVe52r1WokJCQgJSUFOTk58PDwQGhoKM6cOWMyjoiIiOhR2CkVgFIhdhhEVknVsEG1fQpnB9gpuO0REdGj4nYuRET0wEJDQ+Hr64uEhARIJBJ06NAB/fr1Q4cOHSCRSJCQkAA/Pz+EhoaKHSoRERERkU1z8nSFqlHVhfSQYY9BqXKq5YiIiGwPi+hERPTAZDIZpkyZguTkZMyaNctkT/RZs2YhOTkZL7/8MmQymdihEhERERHZNAeVE3pMeQIN2zU1bnNk76hA+8gINOrYHFIpSz9ERI9KIgiCIHYQ1qagoAAqlQr5+flwdXUVOxwiIquVlJSEpUuXIisry9jm5+eHl19+GRERESJGRkRkvZhrPhheLyKimikv00BTWAp9uR52Sns4qJwg5aQWIqJ7qmmuyT3RiYjooUVERCA8PLzSnuicgU5EREREVLvslQrY894BREQWwSI6ERE9EplMhg4dOogdBhERERERERGRRXBjLCIiIiIiIiIiIiKiarCITkRERERERERERERUDRbRiYiIiIiIiIiIiIiqwSI6EREREREREREREVE1WEQnIiIiIiIiIiIiIqqGndgBWCNBEAAABQUFIkdCRERERLamIsesyDnp3pibExEREZGl1DQ3ZxG9CoWFhQCAxo0bixwJEREREdmqwsJCqFQqscOweszNiYiIiMjS7pebSwROganEYDAgIyMDLi4ukEgkYofzwAoKCtC4cWNcvXoVrq6uYodTr/Dai4fXXly8/uLhtRcPr7246vL1FwQBhYWFUKvVkEq5u+L9iJWb1+XvMVvF98T68D2xPnxPrA/fE+vE98X6iPWe1DQ350z0KkilUjRq1EjsMB6Zq6srfxCIhNdePLz24uL1Fw+vvXh47cVVV68/Z6DXnNi5eV39HrNlfE+sD98T68P3xPrwPbFOfF+sjxjvSU1yc059ISIiIiIiIiIiIiKqBovoRERERERERERERETVYBHdBikUCsTGxkKhUIgdSr3Day8eXntx8fqLh9dePLz24uL1J0vj95j14XtiffieWB++J9aH74l14vtifaz9PeGNRYmIiIiIiIiIiIiIqsGZ6ERERERERERERERE1WARnYiIiIiIiIiIiIioGiyiExERERERERERERFVg0V0IiIiIiIiIiIiIqJqsIhuQ+Lj4xEaGgpXV1e4uroiLCwMP/30k9hh1Tvvv/8+JBIJpk6dKnYo9cKcOXMgkUhMvlq2bCl2WPXG9evX8c9//hOenp5wcHBA27ZtcfjwYbHDqheaNGlS6XtfIpEgOjpa7NBsnl6vR0xMDAIDA+Hg4ICmTZvi3XffBe/VXjsKCwsxdepUBAQEwMHBAd27d8ehQ4fEDotsCHNq68Zc2zowB7dOzM2tC/N168M83jrVlfzeTuwAyHwaNWqE999/H82bN4cgCFi7di2GDx+OY8eOISQkROzw6oVDhw5h+fLlCA0NFTuUeiUkJAS7du0yPraz44+22pCbm4vw8HD06dMHP/30E7y8vHD+/Hm4u7uLHVq9cOjQIej1euPjkydPYsCAAYiMjBQxqvrhgw8+QHx8PNauXYuQkBAcPnwYEyZMgEqlwquvvip2eDbv+eefx8mTJ/HVV19BrVbj66+/Rv/+/XHq1Ck0bNhQ7PDIBjCntl7Mta0Lc3Drwtzc+jBftz7M461TXcnvJQI/brFpHh4e+OijjzBp0iSxQ7F5RUVF6NixI5YuXYp58+ahffv2WLRokdhh2bw5c+Zgy5YtOH78uNih1Dtvv/02/vjjD/z+++9ih0IApk6dim3btuH8+fOQSCRih2PThg4dCh8fH6xcudLY9tRTT8HBwQFff/21iJHZvtLSUri4uGDr1q0YMmSIsb1Tp04YNGgQ5s2bJ2J0ZMuYU4uPubZ1YQ5ufZibWz/m6+JjHm996lJ+z+1cbJRer8eGDRtQXFyMsLAwscOpF6KjozFkyBD0799f7FDqnfPnz0OtViMoKAhRUVFIT08XO6R64fvvv0fnzp0RGRkJb29vdOjQAV988YXYYdVLWq0WX3/9NSZOnMiEvBZ0794dv/76K86dOwcA+Ouvv7Bv3z4MGjRI5Mhsn06ng16vh1KpNGl3cHDAvn37RIqKbBlzauvBXNv6MAe3LszNrRvzdevAPN761KX8nuutbMyJEycQFhaGsrIyODs747vvvkPr1q3FDsvmbdiwAUePHrXKPZtsXbdu3bBmzRoEBwcjMzMTcXFx6NmzJ06ePAkXFxexw7Nply5dQnx8PF5//XW88847OHToEF599VXI5XKMGzdO7PDqlS1btiAvLw/jx48XO5R64e2330ZBQQFatmwJmUwGvV6P+fPnIyoqSuzQbJ6LiwvCwsLw7rvvolWrVvDx8cH69euRnJyMZs2aiR0e2RDm1NaFubb1YQ5ufZibWzfm69aBebz1qUv5PbdzsTFarRbp6enIz8/Hpk2b8OWXX2Lv3r1M+i3o6tWr6Ny5M3bu3Gncn7F3795cYiqSvLw8BAQE4JNPPuGSawuTy+Xo3Lkz9u/fb2x79dVXcejQISQnJ4sYWf0zcOBAyOVy/PDDD2KHUi9s2LABb775Jj766COEhITg+PHjmDp1Kj755BP+kVoLLl68iIkTJyIpKQkymQwdO3ZEixYtcOTIEZw+fVrs8MhGMKe2Hsy16wbm4OJjbm7dmK9bB+bx1qmu5PeciW5j5HK58ZOaTp064dChQ1i8eDGWL18ucmS268iRI8jOzkbHjh2NbXq9HklJSfj888+h0Wggk8lEjLB+cXNzQ4sWLXDhwgWxQ7F5fn5+lYoJrVq1wubNm0WKqH66cuUKdu3ahW+//VbsUOqNN998E2+//TaeeeYZAEDbtm1x5coVLFiwgMl3LWjatCn27t2L4uJiFBQUwM/PD6NHj0ZQUJDYoZENYU5tPZhr1w3MwcXH3Nx6MV+3HszjrVNdye+5J7qNMxgM0Gg0Yodh0/r164cTJ07g+PHjxq/OnTsjKioKx48fZ1Jfy4qKinDx4kX4+fmJHYrNCw8Px9mzZ03azp07h4CAAJEiqp9Wr14Nb29vk5uwkGWVlJRAKjVNoWQyGQwGg0gR1U9OTk7w8/NDbm4uduzYgeHDh4sdEtkw5tTiYa5dNzAHFx9zc+vFfN16MI+3btae33Mmug2ZMWMGBg0aBH9/fxQWFmLdunXYs2cPduzYIXZoNs3FxQVt2rQxaXNycoKnp2eldjK/6dOnY9iwYQgICEBGRgZiY2Mhk8kwZswYsUOzedOmTUP37t3x3nvvYdSoUfjzzz+xYsUKrFixQuzQ6g2DwYDVq1dj3LhxsLPjr/TaMmzYMMyfPx/+/v4ICQnBsWPH8Mknn2DixIlih1Yv7NixA4IgIDg4GBcuXMCbb76Jli1bYsKECWKHRjaCObV1Ya5tnZiDWx/m5taJ+bp1YR5vnepKfs9/wTYkOzsbY8eORWZmJlQqFUJDQ7Fjxw4MGDBA7NCILObatWsYM2YMbt++DS8vL/To0QMHDhyAl5eX2KHZvC5duuC7777DjBkzMHfuXAQGBmLRokW8KUst2rVrF9LT05n01bLPPvsMMTExmDJlCrKzs6FWq/Hiiy9i9uzZYodWL+Tn52PGjBm4du0aPDw88NRTT2H+/Pmwt7cXOzSyEcypie6PObj1YW5unZivWxfm8dapruT3vLEoEREREREREREREVE1uCc6EREREREREREREVE1WEQnIiIiIiIiIiIiIqoGi+hERERERERERERERNVgEZ2IiIiIiIiIiIiIqBosohMRERERERERERERVYNFdCIiIiIiIiIiIiKiarCITkRERERERERERERUDRbRiYjI7ObMmYP27dsbH48fPx4jRowQLR4iIiIiovqIeTkRkXnYiR0AERHZvsWLF0MQBOPj3r17o3379li0aJF4QRERERER1TPMy4mIHg6L6EREZHEqlUrsEIiIiIiI6j3m5URED4fbuRAR1TPFxcUYO3YsnJ2d4efnh4ULF6J3796YOnUqAEAikWDLli0mz3Fzc8OaNWuMj9966y20aNECjo6OCAoKQkxMDMrLy6s9593LRsePH4+9e/di8eLFkEgkkEgkSEtLQ7NmzfDxxx+bPO/48eOQSCS4cOGCOV46EREREZHVYF5ORFR3sIhORFTPvPnmm9i7dy+2bt2KX375BXv27MHRo0cf6BguLi5Ys2YNTp06hcWLF+OLL77Ap59+WqPnLl68GGFhYZg8eTIyMzORmZkJf39/TJw4EatXrzYZu3r1akRERKBZs2YPFB8RERERkbVjXk5EVHewiE5EVI8UFRVh5cqV+Pjjj9GvXz+0bdsWa9euhU6ne6DjzJo1C927d0eTJk0wbNgwTJ8+HRs3bqzRc1UqFeRyORwdHeHr6wtfX1/IZDKMHz8eZ8+exZ9//gkAKC8vx7p16zBx4sQHfp1ERERERNaMeTkRUd3CPdGJiOqRixcvQqvVolu3bsY2Dw8PBAcHP9BxvvnmG/znP//BxYsXUVRUBJ1OB1dX10eKTa1WY8iQIVi1ahW6du2KH374ARqNBpGRkY90XCIiIiIia8O8nIiobuFMdCIiMiGRSCAIgknb3fsqJicnIyoqCoMHD8a2bdtw7NgxzJw5E1qt9pHP/fzzz2PDhg0oLS3F6tWrMXr0aDg6Oj7ycYmIiIiI6hrm5URE1oMz0YmI6pGmTZvC3t4eBw8ehL+/PwAgNzcX586dQ69evQAAXl5eyMzMND7n/PnzKCkpMT7ev38/AgICMHPmTGPblStXHigOuVwOvV5fqX3w4MFwcnJCfHw8fv75ZyQlJT3QcYmIiIiI6gLm5UREdQuL6ERE9YizszMmTZqEN998E56envD29sbMmTMhlf5vYVLfvn3x+eefIywsDHq9Hm+99Rbs7e2N/c2bN0d6ejo2bNiALl264Mcff8R33333QHE0adIEBw8exOXLl+Hs7AwPDw9IpVLjHowzZsxA8+bNERYWZrbXTkRERERkLZiXExHVLdzOhYionvnoo4/Qs2dPDBs2DP3790ePHj3QqVMnY//ChQvRuHFj9OzZE88++yymT59usnTziSeewLRp0/DKK6+gffv22L9/P2JiYh4ohunTp0Mmk6F169bw8vJCenq6sW/SpEnQarWYMGHCo79YIiIiIiIrxbyciKjukAh/32CLiIjqnd69e6N9+/ZYtGiR2KHg999/R79+/XD16lX4+PiIHQ4RERERUa1hXk5EZJ24nQsREVkFjUaDmzdvYs6cOYiMjGSiTkREREQkAublRESVcTsXIiKyCuvXr0dAQADy8vLw4Ycfih0OEREREVG9xLyciKgybudCRERERERERERERFQNzkQnIiIiIiIiIiIiIqoGi+hERERERERERERERNVgEZ2IiIiIiIiIiIiIqBosohMRERERERERERERVYNFdCIiIiIiIiIiIiKiarCITkRERERERERERERUDRbRiYiIiIiIiIiIiIiqwSI6EREREREREREREVE1WEQnIiIiIiIiIiIiIqoGi+hERERERERERERERNVgEZ2IiIiIiIiIiIiIqBosohMRERERERERERERVYNFdCIiIiIiIiIiIiKiarCITkRERERERERERERUDRbRiahe6927N3r37i12GCZu3LiBp59+Gp6enpBIJFi0aFGtnPdRrkXv3r3Rpk0b8wZEZrdnzx5IJBLs2bPH2DZ+/Hg0adJEtJiIiIiIHgbz+P9hHm/7mMcTiY9FdCJ6ZGvWrIFEIjH58vb2Rp8+ffDTTz+JHZ5FlJSUYM6cOSZJjLlMmzYNO3bswIwZM/DVV1/hH//4h9nPYe0seX3p3njtiYiIaP/+/ZgzZw7y8vIq9b333nvYsmVLrcdkLszjLYu5pHh47Yksy07sAIjIdsydOxeBgYEQBAE3btzAmjVrMHjwYPzwww8YOnSo2OGZVUlJCeLi4gDA7DNgfvvtNwwfPhzTp08363HrEkteXzL1xRdfwGAwGB/z2hMREdH+/fsRFxeH8ePHw83NzaTvvffew9NPP40RI0aIEtujYh5vWcwlaw/zeKLaxSI6EZnNoEGD0LlzZ+PjSZMmwcfHB+vXr7e5IrolZWdnV/pjhchS7O3txQ6BiIiI6rmysjLI5XJIpXV7sTzzeKpNzOOJalfd/g1FRFbNzc0NDg4OsLMz/byuuLgYb7zxBho3bgyFQoHg4GB8/PHHEAQBAFBaWoqWLVuiZcuWKC0tNT4vJycHfn5+6N69O/R6fbXnrdheJikpCS+++CI8PT3h6uqKsWPHIjc3975xZ2dnGz8AUCqVaNeuHdauXWvsv3z5Mry8vAAAcXFxxi1s5syZc8/jXrp0CZGRkfDw8ICjoyMee+wx/Pjjj5XiFgQBS5YsMR73XjZs2IBOnTrBxcUFrq6uaNu2LRYvXmzsnzNnTpXHqDjX5cuXqz12xb5733zzDd555x34+vrCyckJTzzxBK5evVrlc06dOoU+ffrA0dERDRs2xIcffmjSr9VqMXv2bHTq1AkqlQpOTk7o2bMndu/ebRxTk+t75swZPP300/Dw8IBSqUTnzp3x/fffm5yrvLwccXFxaN68OZRKJTw9PdGjRw/s3Lmz2td8+PBhSCQSk/e7wo4dOyCRSLBt2zYAQGFhIaZOnYomTZpAoVDA29sbAwYMwNGjR6s9foV9+/ahS5cuUCqVaNq0KZYvX17pvbp8+TIkEgnWrFlT6fl/vx5XrlzBlClTEBwcDAcHB3h6eiIyMvKe72+Fu/dSvNe1X716NSQSCY4dO1bpGO+99x5kMhmuX79+3/MRERHRg6tp3nHw4EEMHjwY7u7ucHJyQmhoqElumJKSgvHjxyMoKAhKpRK+vr6YOHEibt++bRwzZ84cvPnmmwCAwMBAYz5QkZsUFxdj7dq1xvbx48cbn3v9+nVMnDgRPj4+UCgUCAkJwapVq0xirMgxN2zYgFmzZqFhw4ZwdHREQUEB83jm8QCYxzOPJ7JOnIlORGaTn5+PW7duQRAEZGdn47PPPkNRURH++c9/GscIgoAnnngCu3fvxqRJk9C+fXvs2LEDb775Jq5fv45PP/0UDg4OWLt2LcLDwzFz5kx88sknAIDo6Gjk5+djzZo1kMlk943nlVdegZubG+bMmYOzZ88iPj4eV65cMSaVVSktLUXv3r1x4cIFvPLKKwgMDERiYiLGjx+PvLw8vPbaa/Dy8kJ8fDxefvlljBw5Ek8++SQAIDQ0tNpYbty4ge7du6OkpASvvvoqPD09sXbtWjzxxBPYtGkTRo4ciYiICHz11Vd47rnnMGDAAIwdO/aer2/nzp0YM2YM+vXrhw8++AAAcPr0afzxxx947bXX7nt9amr+/PmQSCR46623kJ2djUWLFqF///44fvw4HBwcjONyc3Pxj3/8A08++SRGjRqFTZs24a233kLbtm0xaNAgAEBBQQG+/PJLjBkzBpMnT0ZhYSFWrlyJgQMH4s8//0T79u3ve31TU1MRHh6Ohg0b4u2334aTkxM2btyIESNGYPPmzRg5ciSAO394LFiwAM8//zy6du2KgoICHD58GEePHsWAAQOqfK2dO3dGUFAQNm7ciHHjxpn0ffPNN3B3d8fAgQMBAC+99BI2bdqEV155Ba1bt8bt27exb98+nD59Gh07dqz2ep44cQKPP/44vLy8MGfOHOh0OsTGxsLHx+ch3yHg0KFD2L9/P5555hk0atQIly9fRnx8PHr37o1Tp07B0dGxRse517UPDAxEdHQ0EhIS0KFDB5PnJSQkoHfv3mjYsOFDvwYiIiKqXk3yjp07d2Lo0KHw8/PDa6+9Bl9fX5w+fRrbtm0z5oY7d+7EpUuXMGHCBPj6+iI1NRUrVqxAamoqDhw4AIlEgieffBLnzp3D+vXr8emnn6JBgwYA7uQJX331lTG3euGFFwAATZs2BXAn333ssccgkUjwyiuvwMvLCz/99BMmTZqEgoICTJ061eQ1vfvuu5DL5Zg+fTo0Gg3kcrmxj3m8eTCPv4N5PPN4IrMQiIge0erVqwUAlb4UCoWwZs0ak7FbtmwRAAjz5s0zaX/66acFiUQiXLhwwdg2Y8YMQSqVCklJSUJiYqIAQFi0aFGN4+nUqZOg1WqN7R9++KEAQNi6dauxrVevXkKvXr2MjxctWiQAEL7++mtjm1arFcLCwgRnZ2ehoKBAEARBuHnzpgBAiI2NrdE1mjp1qgBA+P33341thYWFQmBgoNCkSRNBr9cb2wEI0dHR9z3ma6+9Jri6ugo6na7aMbGxsUJVP+orrlFaWpqx7e/XYvfu3QIAoWHDhsbXLQiCsHHjRgGAsHjxYpPnAhD++9//Gts0Go3g6+srPPXUU8Y2nU4naDQak1hyc3MFHx8fYeLEica2e13ffv36CW3bthXKysqMbQaDQejevbvQvHlzY1u7du2EIUOGVHNlqjdjxgzB3t5eyMnJMXktbm5uJjGqVKoavU9/N2LECEGpVApXrlwxtp06dUqQyWQm71VaWpoAQFi9enWlY/z92pSUlFQak5ycXOk9qXhPd+/ebWwbN26cEBAQYHx8r2s/ZswYQa1Wm3y/Hj16tNo4iYiIyDzul3fodDohMDBQCAgIEHJzc036DAaD8f+ryhnWr18vABCSkpKMbR999FGlXLGCk5OTMG7cuErtkyZNEvz8/IRbt26ZtD/zzDOCSqUynrsiHwkKCqoUD/P4/2EezzyeeTyRdeF2LkRkNkuWLMHOnTuxc+dOfP311+jTpw+ef/55fPvtt8Yx27dvh0wmw6uvvmry3DfeeAOCIOCnn34yts2ZMwchISEYN24cpkyZgl69elV63r288MILJvvEvfzyy7Czs8P27durfc727dvh6+uLMWPGGNvs7e3x6quvoqioCHv37q3x+f9+3K5du6JHjx7GNmdnZ7zwwgu4fPkyTp069cDHdHNzQ3Fx8T2XNZrD2LFj4eLiYnz89NNPw8/Pr9J1dHZ2Nll1IJfL0bVrV1y6dMnYJpPJjLOMDAYDcnJyoNPp0Llz5xotn8zJycFvv/2GUaNGobCwELdu3cKtW7dw+/ZtDBw4EOfPnzcuRXRzc0NqairOnz//QK939OjRKC8vN/m+/eWXX5CXl4fRo0cb29zc3HDw4EFkZGTU+Nh6vR47duzAiBEj4O/vb2xv1aqVcWbMw7h7JlF5eTlu376NZs2awc3NrUbXtabGjh2LjIwMk2W7CQkJcHBwwFNPPWW28xAREZGp++Udx44dQ1paGqZOnVppT+67Z27fnTOUlZXh1q1beOyxxwDgkXIGQRCwefNmDBs2DIIgGHO0W7duYeDAgcjPz690/HHjxpnEczfm8ebBPJ55fAXm8USPjkV0IjKbrl27on///ujfvz+ioqLw448/onXr1njllVeg1WoB3NnzTa1WmyRzwJ3ko6K/glwux6pVq5CWlobCwkLjXm411bx5c5PHzs7O8PPzu+f+cleuXEHz5s0r3dSoqvgexJUrVxAcHFyp/VGOO2XKFLRo0QKDBg1Co0aNMHHiRPz8888PFd+9/P06SiQSNGvWrNJ1bNSoUaX3x93dvdL+lWvXrkVoaKhxf0MvLy/8+OOPyM/Pv28sFy5cgCAIiImJgZeXl8lXbGwsgDt7YQLA3LlzkZeXhxYtWqBt27Z48803kZKSct9ztGvXDi1btsQ333xjbPvmm2/QoEED9O3b19j24Ycf4uTJk2jcuDG6du2KOXPmmPyhUZWbN2+itLS00jUFUOX3R02VlpZi9uzZxvsMNGjQAF5eXsjLy6vRda2pAQMGwM/PDwkJCQDu/AG1fv16DB8+vNK/aSIiIjKf++UdFy9eBAC0adPmnsfJycnBa6+9Bh8fHzg4OMDLywuBgYEA8Eg5w82bN5GXl4cVK1ZUytEmTJgA4H85WoWK81aFebx5MI9nHl+BeTzRo2MRnYgsRiqVok+fPsjMzHzgWQQVduzYAeDOTJmHPYat8vb2xvHjx/H9998b95kfNGiQyR6A1X3ocK8bsz6s6vapF/7/hrEA8PXXX2P8+PFo2rQpVq5ciZ9//hk7d+5E3759YTAY7nuOijHTp083rnr4+1ezZs0AABEREbh48SJWrVqFNm3a4Msvv0THjh3x5Zdf3vc8o0ePxu7du3Hr1i1oNBp8//33eOqpp0xukjtq1ChcunQJn332GdRqNT766COEhISYrKZ4FA/y3v3rX//C/PnzMWrUKGzcuBG//PILdu7cCU9Pzxpd15qSyWR49tlnsXnzZpSVlWH37t3IyMgwmblERERE5meuvGPUqFH44osv8NJLL+Hbb7/FL7/8YizePkrOUPHcf/7zn9XmaOHh4SbPqW4Wen3APJ55fAXm8UR1B28sSkQWpdPpAABFRUUAgICAAOzatQuFhYUmn3ifOXPG2F8hJSUFc+fOxYQJE3D8+HE8//zzOHHiBFQqVY3Off78efTp08f4uKioCJmZmRg8eHC1zwkICEBKSgoMBoPJLJa/x/cgM+Irnnf27NlK7VW97gchl8sxbNgwDBs2DAaDAVOmTMHy5csRExODZs2awd3dHQCQl5dnsrT3QWbM/P3DC0EQcOHChXvegKk6mzZtQlBQEL799luTa1gx+6RCddc3KCgIwJ2luf3797/v+Tw8PDBhwgRMmDABRUVFiIiIwJw5c/D888/f83mjR49GXFwcNm/eDB8fHxQUFOCZZ56pNM7Pzw9TpkzBlClTkJ2djY4dO2L+/PnGGzD9nZeXFxwcHKr8QOjv3x93v3d3q+q927RpE8aNG4eFCxca28rKyio9tybu9709duxYLFy4ED/88AN++ukneHl5PdISViIiIqqZe+UdFTf3PHnyZLU5Um5uLn799VfExcVh9uzZxvaq8pJ75QNV9Xl5ecHFxQV6vb5GOdr9MI9nHs88Pq/S2PthHk9kWZyJTkQWU15ejl9++QVyudy43HHw4MHQ6/X4/PPPTcZ++umnkEgkxqSlvLwc48ePh1qtxuLFi7FmzRrcuHED06ZNq/H5V6xYgfLycuPj+Ph46HS6ahOjiviysrJMlgDqdDp89tlncHZ2Rq9evQDAeJf0miY3gwcPxp9//onk5GRjW3FxMVasWIEmTZqgdevWNX5dFW7fvm3yWCqVGhNijUYDAMY/qJKSkkzOu3bt2hqf57///S8KCwuNjzdt2oTMzMx7XsfqVMxyuXtWy8GDB02uC1D99fX29kbv3r2xfPlyZGZmVjr+zZs3jf//9+vj7OyMZs2aGa/NvbRq1Qpt27bFN998g2+++QZ+fn6IiIgw9uv1+krLK729vaFWq+95fJlMhoEDB2LLli1IT083tp8+fdq46qKCq6srGjRoYPLeAcDSpUurPO7d1xQAPvvss4eaqXS/7+3Q0FCEhobiyy+/xObNm/HMM8+YzOwhIiIi86pJ3tGxY0cEBgZi0aJFlX6HV+QIVeVhALBo0aJK53RycgJQdT7g5ORUqV0mk+Gpp57C5s2bcfLkyUrPuTtHqwnm8czj78Y8vmaYxxNZFv+1EJHZ/PTTT8YZGdnZ2Vi3bh3Onz+Pt99+G66urgCAYcOGoU+fPpg5cyYuX76Mdu3a4ZdffsHWrVsxdepUY7I4b948HD9+HL/++itcXFwQGhqK2bNnY9asWXj66afvOQulglarRb9+/TBq1CicPXsWS5cuRY8ePfDEE09U+5wXXngBy5cvx/jx43HkyBE0adIEmzZtwh9//IFFixYZZ887ODigdevW+Oabb9CiRQt4eHigTZs21e5D+fbbb2P9+vUYNGgQXn31VXh4eGDt2rVIS0vD5s2bK+3dWBPPP/88cnJy0LdvXzRq1AhXrlzBZ599hvbt2xs/tHj88cfh7++PSZMm4c0334RMJsOqVavg5eVlkvzdi4eHB3r06IEJEybgxo0bWLRoEZo1a4bJkyc/cMxDhw7Ft99+i5EjR2LIkCFIS0vDsmXL0Lp1a+NqBeDe13fJkiXo0aMH2rZti8mTJyMoKAg3btxAcnIyrl27hr/++gsA0Lp1a/Tu3RudOnWCh4cHDh8+jE2bNuGVV16pUayjR4/G7NmzoVQqMWnSJJP3qLCwEI0aNcLTTz+Ndu3awdnZGbt27cKhQ4dMZpFUJS4uDj///DN69uyJKVOmGP+4CwkJqbTX4/PPP4/3338fzz//PDp37oykpCScO3euyuv61VdfQaVSoXXr1khOTsauXbvg6elZo9d6t5p8b48dOxbTp08HAC4BJSIisrCa5B1SqRTx8fEYNmwY2rdvjwkTJsDPzw9nzpxBamoqduzYAVdXV0RERODDDz9EeXk5GjZsiF9++QVpaWmVztmpUycAwMyZM/HMM8/A3t4ew4YNg5OTEzp16oRdu3bhk08+gVqtRmBgILp164b3338fu3fvRrdu3TB58mS0bt0aOTk5OHr0KHbt2oWcnJwav2bm8czjmcczjyeyOgIR0SNavXq1AMDkS6lUCu3btxfi4+MFg8FgMr6wsFCYNm2aoFarBXt7e6F58+bCRx99ZBx35MgRwc7OTvjXv/5l8jydTid06dJFUKvVQm5u7n3j2bt3r/DCCy8I7u7ugrOzsxAVFSXcvn3bZGyvXr2EXr16mbTduHFDmDBhgtCgQQNBLpcLbdu2FVavXl3pPPv37xc6deokyOVyAYAQGxt7z+t08eJF4emnnxbc3NwEpVIpdO3aVdi2bVulcQCE6Ojoex5LEARh06ZNwuOPPy54e3sLcrlc8Pf3F1588UUhMzPTZNyRI0eEbt26Gcd88sknxmuUlpZW7bXYvXu3AEBYv369MGPGDMHb21twcHAQhgwZIly5csXkHL169RJCQkIqxThu3DghICDA+NhgMAjvvfeeEBAQICgUCqFDhw7Ctm3bKo0ThHtf34sXLwpjx44VfH19BXt7e6Fhw4bC0KFDhU2bNhnHzJs3T+jatavg5uYmODg4CC1bthTmz58vaLXa+15bQRCE8+fPG7+f9+3bZ9Kn0WiEN998U2jXrp3g4uIiODk5Ce3atROWLl1ao2Pv3bvX+NqCgoKEZcuWCbGxscLffy2XlJQIkyZNElQqleDi4iKMGjVKyM7OrnQ9cnNzjd+zzs7OwsCBA4UzZ84IAQEBwrhx44zjKt7T3bt3G9se9NoLgiBkZmYKMplMaNGiRY1eLxERET28B8k79u3bJwwYMMA4LjQ0VPjss8+M/deuXRNGjhwpuLm5CSqVSoiMjBQyMjKq/H3/7rvvCg0bNhSkUqlJ3njmzBkhIiJCcHBwEACY5Bo3btwQoqOjhcaNGwv29vaCr6+v0K9fP2HFihXGMRX5SGJiYqX4mcczjxcE5vHM44msk0QQ/rZuhIiojluzZg0mTJiAQ4cOoXPnzmKHU2ft2bMHffr0QWJiIp5++mmxw7F5c+bMQVxcXKXlnNbo1q1b8PPzw+zZsxETEyN2OERERGQjmMebB/P42sU8nqh+4J7oRERE9EDWrFkDvV6P5557TuxQiIiIiIiohpjHEz087olORERENfLbb7/h1KlTmD9/PkaMGIEmTZqIHRIREREREd0H83iiR8ciOhEREdXI3LlzsX//foSHh+Ozzz4TOxwiIiIiIqoB5vFEj457ohMRERERERERERERVYN7ohMRERERERERERERVYNFdCIiIiIiIiIiIiKiarCITkRERERERERERERUDd5YtAoGgwEZGRlwcXGBRCIROxwiIiIisiGCIKCwsBBqtRpSKee03A9zcyIiIiKylJrm5iyiVyEjIwONGzcWOwwiIiIismFXr15Fo0aNxA7D6jE3JyIiIiJLu19uziJ6FVxcXADcuXiurq4iR0NEREREtqSgoACNGzc25px0b8zNiYiIiMhSapqbs4hehYploq6urkzUiYiIiMgiuDVJzTA3JyIiIiJLu19uzk0YiYiIiIiIiIiIiIiqwSI6EREREREREREREVE1WEQnIiIiIiIiIiIiIqoG90QnIiIiIiIiIiIiqqf0ej3Ky8vFDsMi7O3tIZPJHvk4LKITERERERERERER1TOCICArKwt5eXlih2JRbm5u8PX1ve/NQ+9F1CL6ggUL8O233+LMmTNwcHBA9+7d8cEHHyA4OPiez0tMTERMTAwuX76M5s2b44MPPsDgwYON/YIgIDY2Fl988QXy8vIQHh6O+Ph4NG/e3NIvieoxvV6PlJQU5OTkwMPDA6GhoWb5pIuIiIjI0piXk7XTlWlg0GoBQYBUbg+ZUvlIfwgTERERjAV0b29vODo62tzvVkEQUFJSguzsbACAn5/fQx9L1CL63r17ER0djS5dukCn0+Gdd97B448/jlOnTsHJyanK5+zfvx9jxozBggULMHToUKxbtw4jRozA0aNH0aZNGwDAhx9+iP/85z9Yu3YtAgMDERMTg4EDB+LUqVNQKpW1+RKpnkhKSsLSpUuRlZVlbPP19cWUKVMQEREhYmRERERE98e8nKyVIAjQ5uXj1qGjKC8sAgDIlAp4dAiFg7cXpHZcXE1ERPQw9Hq9sYDu6ekpdjgW4+DgAADIzs6Gt7f3Q094lQiCIJgzsEdx8+ZNeHt7Y+/evdUWHkePHo3i4mJs27bN2PbYY4+hffv2WLZsGQRBgFqtxhtvvIHp06cDAPLz8+Hj44M1a9bgmWeeuW8cBQUFUKlUyM/Ph6urq3leHNmspKQkxMbGIiwsDFFRUQgMDERaWhoSEhKQnJyMuLg4FtItjKsAiIioLqkLuaa15OVA3bheZDnlxcXI2LkHgl5fqc+vT08oPNxFiIqIiKjuKysrQ1paGpo0aWIsNNuq0tJSXL58GYGBgZUmctQ015RaOsgHkZ+fDwDw8PCodkxycjL69+9v0jZw4EAkJycDANLS0pCVlWUyRqVSoVu3bsYxROai1+uxdOlShIWFYd68eQgJCYGjoyNCQkIwb948hIWFIT4+Hvoqkn4yj6SkJERFRWHatGl49913MW3aNERFRSEpKUns0IiIiOos5uVkDQRBQPHV61UW0AEgN/UM9DZ6EzRrJwgCNIXFKM66hYKrN1CWWwi9lu8FEVFdZGtbuFTFHK/RaoroBoMBU6dORXh4uHH5Z1WysrLg4+Nj0ubj42PcRqPiv/ca83cajQYFBQUmX0Q1kZKSgqysLERFRUEqNf3nJJVKERUVhczMTKSkpIgUoW2rWAUQFBSEJUuWYPv27ViyZAmCgoIQGxvLQjoREdFDEDMvB5ib0/8IBgM0t3Kq7dfm50PQ6WoxIgLuvC/FWbeQunYbTq75AacTtiPli824vv8vlBeXih0eERHVIXPmzEH79u2Nj8ePH48RI0aIFs+9WE0RPTo6GidPnsSGDRtq/dwLFiyASqUyfjVu3LjWY6C6KSfnTlIfGBhYZX9Fe8U4Mh+uAiAiIrIMMfNygLk5/Y9EKoW9i3O1/XaOjpBIreZP2npDU1CM0+t/RnlRibFNMAjIPHACuReuihgZERHVdYsXL8aaNWuMj3v37o2pU6eKFs/drCLjeOWVV7Bt2zbs3r0bjRo1uudYX19f3Lhxw6Ttxo0b8PX1NfZXtFU35u9mzJiB/Px849fVq/zFTzVTscQ5LS2tyv6K9nsthaaHw1UARERE5id2Xg4wN6f/kUgkcA4MqLbfrVULyBSKWoyIAKAwPRMGbdUrAK7vOw7tXcV1IiKiB6FSqeDm5iZ2GFUStYguCAJeeeUVfPfdd/jtt9+qnc17t7CwMPz6668mbTt37kRYWBiAOzN/fX19TcYUFBTg4MGDxjF/p1Ao4OrqavJFVBOhoaHw9fVFQkICDAaDSZ/BYEBCQgL8/PwQGhoqUoS2i6sArIdWq0ViYiIWL16MxMREaLVasUMiIqIHZC15OcDcnEzZOTrAK6wLJHffNF4igVurYCg4UUUUxdm51fZpC4sh6A3V9pNl6cv1KLqZh8IbuSjOKRQ7HCKq44qLizF27Fg4OzvDz88PCxcuNJkZLpFIsGXLFpPnuLm5mcwkf+utt9CiRQs4OjoiKCgIMTExKL/H/Uzu3s5l/Pjx2Lt3LxYvXgyJRAKJRIK0tDQ0a9YMH3/8scnzjh8/DolEggsXLpjjpVfJzmJHroHo6GisW7cOW7duhYuLi3FvRJVKZbwr7NixY9GwYUMsWLAAAPDaa6+hV69eWLhwIYYMGYINGzbg8OHDWLFiBYA7b+DUqVMxb948NG/eHIGBgYiJiYFarbbaPXWo7pLJZJgyZQpiY2Mxa9YsREVFITAwEGlpaUhISEBycjLi4uIguzvpJ7O4exVASEhIpX6uAqgdy5YtQ2Jiosm2OcuWLUNkZCReeuklESMjIqIHwbycrJXUzg4OPt5QD+gDXXEJBIMe9s7OkCkUkNqL+udsveXs1wA3qulTqJwhkVnFgvd6p/h2AS7tO4mLe/+CtkQDVcMGCB0ZDnd/byhdncQOj4jqoDfffBN79+7F1q1b4e3tjXfeeQdHjx412cP8flxcXLBmzRqo1WqcOHECkydPhouLC/7973/f97mLFy/GuXPn0KZNG8ydOxcA4OXlhYkTJ2L16tWYPn26cezq1asRERGBZs2aPfDrrClRs474+HgAd/a3udvq1asxfvx4AEB6errJVg3du3fHunXrMGvWLLzzzjto3rw5tmzZYnLTo3//+98oLi7GCy+8gLy8PPTo0QM///wzlEqlxV8T1T8RERGIi4vD0qVLER0dbWz38/NDXFwcIiIiRIzOdt29CmDevHkmPye4CqB2LFu2DBs2bIC7uzsmTZqEsLAwJCcnY+XKlcZ9dFlIJyKqG5iXkzWTymSQOjnC3slR7FAIgEsjH8iUcujLKq8+bNSrE+TOfJ9qW0lOIQ4n/Iobp64Y2/Kv38Lvn29F2AtD0LhjcxGjI6K6qKioCCtXrsTXX3+Nfv36AQDWrl173+3+/m7WrFnG/2/SpAmmT5+ODRs21KiIrlKpIJfL4ejoaLIV4Pjx4zF79mz8+eef6Nq1K8rLy7Fu3bpKs9PNTdQiuiAI9x2zZ8+eSm2RkZGIjIys9jkSiQRz5841fkpBZGkREREIDw9HSkoKcnJy4OHhgdDQUM5AtyCuAhBXxRYu7u7uSExMhJ3dnV8nQ4cOxT/+8Q9ERkYiMTEREydOhFwuFzlaIiK6H+blRFRTclcntH52EM5v2YOynHwAgNTeDg17tIcqUC1ydPVTaUGxSQH9bimbf4e7vzecG6hqOSoiqssuXrwIrVaLbt26Gds8PDwQHBz8QMf55ptv8J///AcXL15EUVERdDrdI2/Vp1arMWTIEKxatQpdu3bFDz/8AI1Gc8+c1By4/o3ITGQyGTp06CB2GPUKVwGIZ+vWrdDr9Zg0aZKxgF7Bzs4OEydOxMKFC7F161aL/yIjIiIiotojkUjg6O2BVlH/gK5EA4NODzsHBeTOjpDacQKLGG5fyqy2r/h2AXSlvGcREZmfRCKpNBHj7v3Ok5OTERUVhbi4OAwcOBAqlQobNmzAwoULH/nczz//PJ577jl8+umnWL16NUaPHg1HR8uuhGIRnYjqNK4CEEdGRgYAVHtjuIr2inFEREREZFvkTo6Qc4sdq6Bwcqi2TyKR8MMNInpgTZs2hb29PQ4ePAh/f38AQG5uLs6dO4devXoBuLM/eWbm/z7EO3/+PEpKSoyP9+/fj4CAAMycOdPYduVK1atmqiOXy03uwVZh8ODBcHJyQnx8PH7++WckJSU90HEfBovoRFTncRVA7VOr7yzVTU5OxtChQyv1Jycnm4wjIiIiIiLLcA/whtROBoOucqHJt00TyJ15HwoiejDOzs6YNGkS3nzzTXh6esLb2xszZ840uT9O37598fnnnyMsLAx6vR5vvfUW7O3tjf3NmzdHeno6NmzYgC5duuDHH3/Ed99990BxNGnSBAcPHsTly5fh7OwMDw8PSKVSyGQyjB8/HjNmzEDz5s2rneBnTrxtNhERPbDhw4dDJpNh5cqV0Ol0Jn06nQ6rVq2CTCbD8OHDRYqQiIiIiKh+cFA547HnB0EiNS3xODVwRfunI6B04YoBInpwH330EXr27Ilhw4ahf//+6NGjBzp16mTsX7hwIRo3boyePXvi2WefxfTp0022VHniiScwbdo0vPLKK2jfvj3279+PmJiYB4ph+vTpkMlkaN26Nby8vJCenm7smzRpErRaLSZMmPDoL7YGJEJN7iJUzxQUFEClUiE/P/+RN7snIrJVy5Ytw4YNG+Du7o6JEyciLCwMycnJWLVqFXJzc/HMM8/gpZdeEjtMIiKrw1zzwfB6ERHdX3mpBqV5xcg4cQklOYXwatEI7o294OzlJnZoRGSlysrKkJaWhsDAQCiVNVux0rt3b7Rv3x6LFi2ybHA18Pvvv6Nfv364evUqfHx87jn2Xq+1prkmt3MhIqKHUlEgT0xMNLkxiEwmYwGdiIiIiKgW2TsoYO+ggKufh9ihEBFZlEajwc2bNzFnzhxERkbet4BuLiyiExHRQ3vppZcwceJEbN26FRkZGVCr1Rg+fDjkcrnYoRERERERERGRjVm/fj0mTZqE9u3b47///W+tnZdFdCIieiRyuRyRkZFih0FEREREREREFrRnzx6xQ8D48eMxfvz4Wj8vbyxKRERERERERERERFQNFtGJiIiIiIiIiIiIiKrBIjoRERERERERERERUTVYRCciIiIiIiIiIiIiqgaL6ERERERERERERERE1WARnYiIiIiIiIiIiIioGiyiExERERERERERERFVg0V0IiIiIiIiIiIiIqoT4uPjERoaCldXV7i6uiIsLAw//fSTRc/JIjoRERERERERERERPRSDTgd9WSl0xUXQl5XCoNNZ9HyNGjXC+++/jyNHjuDw4cPo27cvhg8fjtTUVIud085iRyYiIiIiIiIiIiIim6XXalF8LQ26okJjm52zK5waNYFMLrfIOYcNG2byeP78+YiPj8eBAwcQEhJikXNyJjoRERERERERERERPRCDTlepgA4AuqICFF+7bPEZ6QCg1+uxYcMGFBcXIywszGLn4Ux0IiIiIiIiIiIiInoggq68UgG9gq6oAIKuHLCzTPn5xIkTCAsLQ1lZGZydnfHdd9+hdevWFjkXwJnoRERERERERERERPSABL3+3v2Ge/c/iuDgYBw/fhwHDx7Eyy+/jHHjxuHUqVMWOx9nohMRERERERERERHRA5HIZPful967/1HI5XI0a9YMANCpUyccOnQIixcvxvLlyy1yPs5EJyIiIiIiIiIiIqIHIrGzh52za5V9ds6ukNjZ11osBoMBGo3GYsfnTHQiIiIiIiIiIiIieiBSOzs4NWqC4muXoSsqMLbbObvCqVETSC20H/qMGTMwaNAg+Pv7o7CwEOvWrcOePXuwY8cOi5wPYBGdiIiIiIiIiIiIiB6CTC6Hs38QBF05BIMeEqkMEjt7ixXQASA7Oxtjx45FZmYmVCoVQkNDsWPHDgwYMMBi5xR1O5ekpCQMGzYMarUaEokEW7Zsuef48ePHQyKRVPoKCQkxjpkzZ06l/pYtW1r4lRARERER1W3MzYmIiIjoYUjt7CBTOsDO0RkypYNFC+gAsHLlSly+fBkajQbZ2dnYtWuXRQvogMhF9OLiYrRr1w5Lliyp0fjFixcjMzPT+HX16lV4eHggMjLSZFxISIjJuH379lkifCIiIiIim8HcnIiIiIioaqJu5zJo0CAMGjSoxuNVKhVUKpXx8ZYtW5Cbm4sJEyaYjLOzs4Ovr6/Z4iQiIiIisnXMzYmIiIiIqibqTPRHtXLlSvTv3x8BAQEm7efPn4darUZQUBCioqKQnp4uUoRERERERPUDc3MiIiIislV19saiGRkZ+Omnn7Bu3TqT9m7dumHNmjUIDg5GZmYm4uLi0LNnT5w8eRIuLi5VHkuj0UCj0RgfFxQUVDmOiIiIiIgqY25ORERERLaszhbR165dCzc3N4wYMcKk/e4lqKGhoejWrRsCAgKwceNGTJo0qcpjLViwAHFxcZYMl4iIiIjIZjE3JyIiIiJbVie3cxEEAatWrcJzzz0HuVx+z7Fubm5o0aIFLly4UO2YGTNmID8/3/h19epVc4dMRERERGSTmJsTERERka2rk0X0vXv34sKFC9XOXrlbUVERLl68CD8/v2rHKBQKuLq6mnwREREREdH9MTcnIiIiIlsnahG9qKgIx48fx/HjxwEAaWlpOH78uPFmQzNmzMDYsWMrPW/lypXo1q0b2rRpU6lv+vTp2Lt3Ly5fvoz9+/dj5MiRkMlkGDNmjEVfCxERERFRXcbcnIiIiIioaqLuiX748GH06dPH+Pj1118HAIwbNw5r1qxBZmamMWmvkJ+fj82bN2Px4sVVHvPatWsYM2YMbt++DS8vL/To0QMHDhyAl5eX5V4IEREREVEdx9yciIiIiKhqEkEQBLGDsDYFBQVQqVTIz8/n8lEiIiIiMivmmg+G14uIiIjI/MrKypCWlobAwEAolUqxw7Goe73WmuaadXJPdCIiIiIiIiIiIiKq395//31IJBJMnTrVoucRdTsXIiIiIiIiIiIiIqq79Fot9GUaCDodpPb2kCrkkMnlFj/voUOHsHz5coSGhlr8XCyiExEREREREREREdED05WU4taR4yjLvmlsU3p7oUGn9rBzdLDYeYuKihAVFYUvvvgC8+bNs9h5KnA7FyIiIiIiIiIiIiJ6IHqttlIBHQDKsm/i1pHj0Gu1Fjt3dHQ0hgwZgv79+1vsHHfjTHQiIiIiIiIiIiIieiD6Mk2lAnqFsuyb0JdpLLKty4YNG3D06FEcOnTI7MeuDovoRERERERERERERPRABJ3ukfofxtWrV/Haa69h586dUCqVZj9+dVhEJyIiIiIiIiIiIqIHIrG7d2n5fv0P48iRI8jOzkbHjh2NbXq9HklJSfj888+h0Wggk8nMfl4W0YmoztPr9UhJSUFOTg48PDwQGhpqkR+YRERERERERER0h0ypgNLbq8otXZTeXpApFWY/Z79+/XDixAmTtgkTJqBly5Z46623LFYPYhGdiOq0pKQkLF26FFlZWcY2X19fTJkyBRERESJGRkRERERkm/TacmiLSpF/+Tp0JWVQNVFD4e4KuZOD2KEREVEtksnlaNCpfaWbiyq9vdCgU3uL7Ifu4uKCNm3amLQ5OTnB09OzUrs5sYhORHVWUlISYmNjERYWhpiYGAQGBiItLQ0JCQmIjY1FXFwcC+m1gCsBiIiIiOoPvbYcuefTcXHb74AgAACu7zsO54beaD6iD+QujiJHWH/ptDpoCkugL9fDXmkPpcoJEolE7LCIyMbZOTrAq1sn6Ms0EHQ6SOzsIFMqLFJAFxOL6ERUJ+n1eixduhRhYWGYN28epFIpACAkJATz5s3DrFmzEB8fj/DwcBZ0LYgrAYiIiIjqF21RCS7+kFSpveh6NrKOnEKjnh0gZf5d60pyi3DqxwO4fOA0DDo9HNycEDqyB3zbNIGCKwSIyMJkcrmoRfM9e/ZY/BxSi5+BiMgCUlJSkJWVhaioKGMBvYJUKkVUVBQyMzORkpIiUoS2r2IlQFBQEJYsWYLt27djyZIlCAoKQmxsLJKSKv9xRURERER1W+759Gr7so+dQXlxWS1GQwBQVlCC5C9+xKV9J2HQ6QEApXnFOLh6BzJPXIbw/ysGiIjo4bGITkR1Uk5ODgAgMDAQer0ex44dw6+//opjx45Br9cjMDDQZByZ199XAoSEhMDR0dG4EiAsLAzx8fHQ6/Vih0pEREREZqQtLKm2T68pN27xQrWnJKcQty9lVtmX8u3vKM0rquWIiIhsD7dzIaI6ycPDAwDw3Xff4Ycffqi0ncjQoUNNxpF5VawEiImJqXYlQHR0NFJSUtChQweRoiQiIiIic3Nr2gg3Dp+qss/JrwGkcpYZalvu1exq+8oKSqDTlNdiNEREtokz0YmoTgoNDYWbmxu++OILBAYGmmwnEhgYiC+//BLu7u4IDQ0VO1SbdPdKgKpwJQARERGRbVK6ucDBU1VlX+NenWHvoKzliMjBzanaPolUCqkd96gnInpULKITkc3i3n+WUzHDPy0trcr+inauBCAiIiKyLcXZOfDv2xUN2jSF5P9vIOro7YFmw3sj59xlaIur3+6FLEOlbgA7hX2Vff5dWkDp4ljLERER2R4W0YmoTkpJSUFeXh4mT56MtLQ0REdHY/DgwYiOjsbly5cxefJk5OXl8caiFhIaGgpfX18kJCTAYDCY9BkMBiQkJMDPz48rAYiIiIhsTOHVGzj37a8QBAFNh/ZEsxG94dk6CFf3HEb20TMQdIb7H4TMysHNGRGvjqxUSHf390bb4eHVFtiJiKjmuFkZEdVJFduEeHt7V5pxbjAY4O3tbTKOzEsmk2HKlCmIjY3FrFmzEBUVhcDAQKSlpSEhIQHJycmIi4uDTMalo0RERES2xLGBGwS9AbdTL+F26iWTPntnB0iknKtX26QyKTya+GLg7OeQe/UmSnML4R7gA6cGrnBwrX6rFyIiqjkW0YmoTqrYJmT+/Pno3r07Zs+ebVLEnT9/vsk4Mr+IiAjExcVh6dKliI6ONrb7+fkhLi4OERERIkZHRERERJbg4u8LqZ0MBp2+Up/6sVDYOzuIEBVJZVI4ebrCydNV7FCIiGwSi+hEVCeFhIRAJpPB1dUVc+fOhZ2dnbF97ty5iIyMREFBAUJCQkSO1LZFREQgPDwcKSkpyMnJgYeHB0JDQzkDnYiIiMhGGbTlaDosAmk/74euVHOnUSKBV9tmsHdxhF6jhZ1SIW6QREREZsYiOhHVSampqdDr9cjLy8Ps2bMrbSeSl5cHQRCQmpqKDh06iB2uTZPJZLzGRERERPXErVOXUHA5EwH9u0Eik8Kg1cHeyQF5F6/iwne70f7lSBbRiYjI5rCITkR1UsVe5++88w5WrlxZaTuRd955B/Pnz+ee6EREREREZiST26MkOwcXf0iCRCqFxO5OIR0AJDIZIBE5QCIisnlz5sxBXFycSVtwcDDOnDljsXOyiE5EdVLFXudqtRoJCQmVthOp+MHJPdGJiIiIiMzHI7gJru87DgAQDAYIWoOxr0GbprB3VIoUGRERiaW8VANdSSn0mnLIFHLYOSph72DZVUkhISHYtWuX8XHFNr+WwiI6EdVJoaGh8PX1RUJCAubNm2eynYjBYEBCQgL8/PwQGhoqYpRERERERLZF7uKIhj3aGwvpFRQqZzTsHgqphYsYRERkXTQFRbi0/Q8UXM4wtqkC1QgcFA6Fq7PFzmtnZwdfX1+LHf/vpLV2JiIiM5LJZJgyZQqSk5Mxa9YspKamoqSkBKmpqZg1axaSk5Px8ssv8waXRERERERmZKdUwLdTa4SMGwavds3h1qwxmg6NQKuoQVCoXMQOj4iIalF5qaZSAR0A8tMykPbTHyivuAG1BZw/fx5qtRpBQUGIiopCenq6xc4FiFxET0pKwrBhw6BWqyGRSLBly5Z7jt+zZw8kEkmlr6ysLJNxS5YsQZMmTaBUKtGtWzf8+eefFnwVRCSWiIgIxMXF4dKlS4iOjsbgwYMRHR2NtLQ0xMXFISIiQuwQiYiI6gzm5kRUU3YOCjj7NUDgP8LRfGRfNGjT1KKzDYmIyDrpSkorFdAr5KdlQFdSapHzduvWDWvWrMHPP/+M+Ph4pKWloWfPnigsLLTI+QCRt3MpLi5Gu3btMHHiRDz55JM1ft7Zs2fh6upqfOzt7W38/2+++Qavv/46li1bhm7dumHRokUYOHAgzp49azKOiGxDREQEwsPDK+2JzhnoRERED4a5ORE9KIlEAomMdxIlIqqv9JryR+p/WIMGDTL+f2hoKLp164aAgABs3LgRkyZNssg5RS2iDxo0yORF15S3tzfc3Nyq7Pvkk08wefJkTJgwAQCwbNky/Pjjj1i1ahXefvvtRwmXiKyUTCYz2ROdiIiIHhxzcyIiIiJ6EDKF/SP1m4ubmxtatGiBCxcuWOwcdXJP9Pbt28PPzw8DBgzAH3/8YWzXarU4cuQI+vfvb2yTSqXo378/kpOTxQiViIiIiMimMTcnIiIiqp/sHB2gClRX2acKVMPO0aFW4igqKsLFixfh5+dnsXPUqSK6n58fli1bhs2bN2Pz5s1o3LgxevfujaNHjwIAbt26Bb1eDx8fH5Pn+fj4VNqb8W4ajQYFBQUmX0REREREVD3m5kRERET1m72DAoGDwisV0lWBagQO6gF7B4VFzjt9+nTs3bsXly9fxv79+zFy5EjIZDKMGTPGIucDRN7O5UEFBwcjODjY+Lh79+64ePEiPv30U3z11VcPfdwFCxYgLi7OHCESEREREdULzM2JiIiISOHqjKZP9IaupBR6TTlkCnvYOTpYrIAOANeuXcOYMWNw+/ZteHl5oUePHjhw4AC8vLwsds46VUSvSteuXbFv3z4AQIMGDSCTyXDjxg2TMTdu3ICvr2+1x5gxYwZef/114+OCggI0btzYMgETEREREdko5uZERERE9Y+9g8KiRfO/27BhQ62dq0Kd2s6lKsePHzfudyOXy9GpUyf8+uuvxn6DwYBff/0VYWFh1R5DoVDA1dXV5IuIiIiIiB4Mc3MiIiIiskWizkQvKioyuWtqWloajh8/Dg8PD/j7+2PGjBm4fv06/vvf/wIAFi1ahMDAQISEhKCsrAxffvklfvvtN/zyyy/GY7z++usYN24cOnfujK5du2LRokUoLi7GhAkTav31ERERERHVFczNiYiIiIiqJmoR/fDhw+jTp4/xccWyzXHjxmHNmjXIzMxEenq6sV+r1eKNN97A9evX4ejoiNDQUOzatcvkGKNHj8bNmzcxe/ZsZGVloX379vj5558r3dCIiIiIiIj+h7k5EREREVHVJIIgCGIHYW0KCgqgUqmQn5/P5aNEREREZFbMNR8MrxcRERGR+ZWVlSEtLQ2BgYFQKpVih2NR93qtNc016/ye6ERERERERERERERElsIiOhERERERERERERFRNVhEJyIiIiIiIiIiIiKqBovoRERERERERERERETVYBGdiIiIiIiIiIiIiKgaLKITEREREREREREREVWDRXQiIiIiIiIiIiIiqjOuX7+Of/7zn/D09ISDgwPatm2Lw4cPW+x8dhY7MhERERERERERERHZNE1xGTSFJSgv1cDeQQGFiyMUTkqLnS83Nxfh4eHo06cPfvrpJ3h5eeH8+fNwd3e32DlZRCciIiIiIiIiIiKiB1aSU4hDX+3EjdPpxjafVgHo8lx/OHq4WOScH3zwARo3bozVq1cb2wIDAy1yrgrczoWIiB6JVqtFYmIiFi9ejMTERGi1WrFDqjf0ej2OHTuGX3/9FceOHYNerxc7JCIiIiISSVlRKQqycpCbno3C7DzmhlZApy1H3o1c3EzPRn52HvQ6vidkWzTFZZUK6ABw4/QVHPpqFzTFZRY57/fff4/OnTsjMjIS3t7e6NChA7744guLnKsCZ6ITEdFDW7ZsGRITE00S9GXLliEyMhIvvfSSiJHZvqSkJCxduhRZWVnGNl9fX0yZMgUREREiRkZEREREta3oZj5SvtuH68cvQDAIUDg7oNXgrmjUoTkc3Z3FDq9eKswpxB8b9+LYL0ehL9dB7qBA2JPh6PiPznBy43tCtkFTWFKpgF7hxukr0BSWWGRbl0uXLiE+Ph6vv/463nnnHRw6dAivvvoq5HI5xo0bZ/bzAZyJTkRED2nZsmXYsGEDXF1dMX36dGzevBnTp0+Hq6srNmzYgGXLlokdos1KSkpCbGwsgoKCsGTJEmzfvh1LlixBUFAQYmNjkZSUJHaIRERERFRLim8XYP+Kbbh29DwEgwAA0BSV4vjGvbj+10UYdAaRI6x/SotKsWP5jzj845/Ql+sAANpSDfYm/IaDW5JRrikXOUIi8ygv1dyn3zIr1Q0GAzp27Ij33nsPHTp0wAsvvIDJkydbtA7BIjoR1Xnc0qL2VWzh4u7ujsTERAwdOhSenp4YOnSoSTu3djE/vV6PpUuXIiwsDPPmzUNISAgcHR0REhKCefPmISwsDPHx8fx3QERERBalLSpBSXYOijJvQZNfBAO3qRBNSU4h8q7erLLv1I8HUZyTX8sRUXFeMc7sP1Vl38Hvk1GUW1TLERFZhr2D4j79couc18/PD61btzZpa9WqFdLTq54Vbw7czoWI6jRuaSGOrVu3Qq/XY9KkSZBIJDh27BhycnLg4eGB0NBQTJw4EQsXLsTWrVsRGRkpdrg2JSUlBVlZWYiJiYFUavpZuFQqRVRUFKKjo5GSkoIOHTqIFCURERHZKkEQUHozF+e37EHZ/xdnpfZ2aNijA7xCm8HewfzL9unectOzAQAObk5o3KkF5I5K5Gfm4PrxC9AUlkCn0YkcYf1TeKv6Dy705TqUFZUCcK+9gIgsROHiCJ9WAbhx+kqlPp9WAVC4OFrkvOHh4Th79qxJ27lz5xAQEGCR8wEsohNRHVaxpUVYWBhiYmIQGBiItLQ0JCQkIDY2FnFxcSykW0hGRgYAQCKRICoqqtKHGP/85z9NxpH55OTkAKj+zuMV7RXjiIiIiMxJW1CMU+t+gr7sfysODeU6XN19CHIXRzRoHSRidPWTo4cz2gwLg4OHCy4nn0JZQTE8AnzR4+UncPqXQ5DZy8QOsd5ROjvcs99eaV9LkRBZlsJJiS7P9cehr3aZFNJ9WgWgy9j+FtkPHQCmTZuG7t2747333sOoUaPw559/YsWKFVixYoVFzgewiE5EddTft7SomJFbsaXFrFmzEB8fj/DwcMhkTBrNTa1WAwA++ugjdO/evdKHGB9//LHJODIfDw8PAEBaWhpCQkIq9aelpZmMIyIiIjKnwms3TArod7u29whc/X0hd7bMzEOqmqqRF7LPXsPJH5KNbYVZubh65Bx6THkCSpWTiNHVT84eLnDzcUfejdxKff5tmsCJ7wnZEEcPFzz2/CBoCktQXqqFvYMcChdHixXQAaBLly747rvvMGPGDMydOxeBgYFYtGgRoqKiLHZO7olORHVSxZYWUVFREATBZE90QRAQFRWFzMxMpKSkiB2qTRo6dCgAwN7eHnPmzDHZl3vOnDmwt7c3GUfmExoaCl9fXyQkJMBgML1JlMFgQEJCAvz8/BAaGipShERERGTLijJvVdunyS+CoOdNLGuboDfgwp6/KrUbdHqkfLePNxYVgYuHC0bHRsHFw8Wk3bNRAzwxdSQcLLTFBZFYFE5KuPp6wDPQF66+HhYtoFcYOnQoTpw4gbKyMpw+fRqTJ0+26Pk4E52I6qSKrSoyMjLw7rvvVtpOZNKkSSbjyLzOnDkDACgvL8fo0aMxceJEhIWFITk5GatWrUJ5eblxHPflNi+ZTIYpU6YgNjYWs2bNQlRUlMkqgOTkZMTFxXEFBhEREVmEk3f1+zjLXZwgkXGuXm27fSmz2r68qzdRXlIGpcu9txch8/Nq7I0JC19EbuZt5N3IhWcjL7j5uMHZ3eX+TyYiq/NQRfTS0lIIggBHxzufnF25cgXfffcdWrdujccff9ysARIRVaViq4r58+dXuZ3I/PnzTcaReVV8OPHUU09hy5YtWLhwobFPJpPhqaeewubNm/khhoVEREQgLi4OS5cuRXR0tLHdz8+P9wIgqmeYlxNRbXNu5AOp3A4GbeWbVaq7h3IrFxFIpJL7DLhPP1mMawNXuDZwRUDbqu9nRER1x0MV0YcPH44nn3wSL730EvLy8tCtWzfY29vj1q1b+OSTT/Dyyy+bO04iIhMhISGQyWRwdXXF3LlzYWdnZ2yfO3cuIiMjUVBQUOWe0fToKj6c6Nu3L1588UVs3boVGRkZUKvVGD58OM6fP4/NmzfzQwwLioiIQHh4OFJSUpCTkwMPDw+EhoZyBjpRPcO8nIhqm76sHM2G9ULajmSUF5UAuFPE9W7fEjKFHLoyDeyUCpGjrF88g9SABIBQuc8jyBdyR74fRESP6qGK6EePHsWnn34KANi0aRN8fHxw7NgxbN68GbNnz2ayTkQWl5qaCr1ej7y8PMyaNQsNGzaERqOBQqHA9evXkZeXB0EQkJqayu1ELODufbnnzZuHyMhIYx/35a49MpmM399E9RzzciKqbbdPX0L+pWtoHNERMqUcBp0eMrk9cs9dwcXv96L9y5EsotcypYsDQkf0QMp3+0za7RT26PxsPyicuZULEdGjeqgieklJCVxc7uzh9Msvv+DJJ5+EVCrFY489hitXrpg1QCKiqlRsE9KtWzccOHCgUv9jjz2GAwcOcDsRC+G+3ERE1oF5ORHVNplSjtLb+bi0/f8LthIJINyZAi21k3HrEBHYOygQ1KMNGjRT49yuoyjJK4J3cGMEhYfA0dNV7PCIiGzCQxXRmzVrhi1btmDkyJHYsWMHpk2bBgDIzs6Gqyt/QBOR5VVsE3LgwAG4ubnh8ccfh1qtRkZGBn755RdjYZ3biVgO9+UmIhIf83Iiqm0ezf1x/fdj/2sQ/reHSIO2zWHvqBQhKpI7KdGgqRpujb1g0Olhp7CHlBNaiIjM5qGK6LNnz8azzz6LadOmoW/fvggLCwNwZ/YLl5UTUW1o2bIlAMDe3h7r16/HmTNnkJOTg7CwMEyYMAFPPPEEysvLjePIMrgvNxGRuJiXE1Gtk0qhDgtF9l/n4N7cHzJ7OxRn3UZ5SSkatGkKg8EAKZgLisVObg/I7cUOg4jI5jxUEf3pp59Gjx49kJmZiXbt2hnb+/Xrh5EjR5otOCKi6mzbtg0AUF5ejhEjRkCj0Rj7FAoFysvLjePu3q+bzI/7chMRiYd5ORHVttupF+Gs9oJLI2/cOHoGpWVauDVtBLdmjXF5x34EDY24U8glIiKyIdKHfaKvry9cXFywc+dOlJaWAgC6dOnyQLM+k5KSMGzYMKjVakgkEmzZsuWe47/99lsMGDAAXl5ecHV1RVhYGHbs2GEyZs6cOZBIJCZfnIlKZHsyMjLMOo6IiKiuMkdeDjA3J6KacfD2QM65KzibuAt5F6+h6Ho2riUdxdlvfkHD8A6QCPc/BhERUV3zUEX027dvo1+/fmjRogUGDx6MzMxMAMCkSZPwxhtv1Pg4xcXFaNeuHZYsWVKj8UlJSRgwYAC2b9+OI0eOoE+fPhg2bBiOHTtmMi4kJASZmZnGr3379lVzRCKqq3x9fQEATZs2xbZt2/Dpp58iJiYGn376KbZt24agoCCTcURERLbIXHk5wNyciGpG4eqEWycuVGovLy7FzRPnIZE/1IJ3IiIiq/ZQv92mTZsGe3t7pKeno1WrVsb20aNH4/XXX8fChQtrdJxBgwZh0KBBNT7vokWLTB6/99572Lp1K3744QeTrQTs7OxYOCOycRVF8uzsbEgkEpOfATqdDjdv3jQZR0REZIvMlZcDzM2JqGZyz6dX33f2Cvz7dK7FaIiIqD5q0qQJrly5Uql9ypQpNZ4Q8qAeqoj+yy+/YMeOHWjUqJFJe/Pmzat8AZZiMBhQWFgIDw8Pk/bz589DrVZDqVQiLCwMCxYsgL+/f7XH0Wg0JvspFxQUWCxmIjKPin+nhYWFiIyMxMSJExEWFobk5GSsWrUKhYWFJuOIiIhskbXk5QBzc6J6Q6h+vxZBEABu50JEVO+UFpaiOL8ImmINlE5KOKqc4ODiYLHzHTp0CHq93vj45MmTGDBggEXvifdQRfTi4mI4OjpWas/JyYFCoXjkoGrq448/RlFREUaNGmVs69atG9asWYPg4GBkZmYiLi4OPXv2xMmTJ+Hi4lLlcRYsWIC4uLjaCpuIzKDiD/T+/fvjt99+M5lpJ5VK0b9/f+zatavSH/JERES2xFrycoC5OVF94dGyCTIPnqyyz725P+wcavdnDxERiSv/Zj62fbYVacf+t9VXUIdmGPKv4VB5qSxyTi8vL5PH77//Ppo2bYpevXpZ5HzAQ+6J3rNnT/z3v/81PpZIJDAYDPjwww/Rp08fswV3L+vWrUNcXBw2btwIb29vY/ugQYMQGRmJ0NBQDBw4ENu3b0deXh42btxY7bFmzJiB/Px849fVq1dr4yUQ0SMIDQ2Fr68vrl69igYNGpj0NWjQAFevXoWfnx9CQ0NFipCIiMjyrCEvB5ibE9UnCpULPIKbVGqXKeRoHNERMrl97QdFRESiKC0srVRAB4BLxy7gx8+2orSw1OIxaLVafP3115g4cSIkEonFzvNQM9E//PBD9OvXD4cPH4ZWq8W///1vpKamIicnB3/88Ye5Y6xkw4YNeP7555GYmIj+/fvfc6ybmxtatGiBCxcq3/ikgkKhqPWZOkT0aGQyGXr37o0NGzbA3d0db7zxhsl2LmfPnsUzzzwDmUwmdqhEREQWI3ZeDjA3J6pvBL0B7i0D4OLvi1snL0BfpoVrgB88ggNgMOjvfwAiIrIZxflFlQroFS4du4Di/CKLbusCAFu2bEFeXh7Gjx9v0fM81Ez0Nm3a4Ny5c+jRoweGDx+O4uJiPPnkkzh27BiaNm1q7hhNrF+/HhMmTMD69esxZMiQ+44vKirCxYsX4efnZ9G4iKh26fV67NmzB8HBwVAoFFi4cCGefvppLFy4EAqFAsHBwdi7d6/JHllERES2Rsy8HGBuTlQfld7Ow8Wte3HjyCmomqjRoG0zlJeU4WziTlz+5QDKSzX3PwgREdkETfG9f+bfr98cVq5ciUGDBkGtVlv0PA81Ez09PR2NGzfGzJkzq+y7142C7lZUVGQyCyUtLQ3Hjx+Hh4cH/P39MWPGDFy/ft24RHXdunUYN24cFi9ejG7duiErKwsA4ODgAJXqzh4706dPx7BhwxAQEICMjAzExsZCJpNhzJgxD/NSichKpaSkICsrC8OGDcP3339v0icIAnr27Ikvv/wSKSkp6NChg0hREhERWZa58nKAuTkR1UzuxTtbLJXlFCAjOcWkr+haNgzacoD7ohMR1QsKp3v/vL9f/6O6cuUKdu3ahW+//dai5wEeciZ6YGAgbt68Wan99u3bCAwMrPFxDh8+jA4dOhgLXK+//jo6dOiA2bNnAwAyMzORnp5uHL9ixQrodDpER0fDz8/P+PXaa68Zx1y7dg1jxoxBcHAwRo0aBU9PTxw4cKDShvNEVLfl5OQAAL744gs0bdoUS5Yswfbt27FkyRI0bdoUX375pck4IiIiW2SuvBxgbk5ENWPvoKy2T2pvB1hwP1oiIrIuTipnBHVoVmVfUIdmcFI5W/T8q1evhre3d41WRD6qh5qJLghClRu1FxUVQams/hfq3/Xu3RuCIFTbv2bNGpPHe/bsue8xN2zYUOPzE1Hd5ebmBgBo27Yt4uLicPLkSSQnJ8PDwwNxcXF4/fXXceLECeM4shytVoutW7ciIyMDarUaw4cPh1wuFzssIqJ6wVx5OcDcnIhqxi2oIbKPn4VvlxAoVM4QDAZIJBLcPHEBchcnSGUPNVePzKAktxDa4jLoNOWQOymhVDlBzlUBRGRBDi4OGPKv4fjxs624dNfe6EEdmmHoq8Mtuh+6wWDA6tWrMW7cONjZPVSJ+4E80Blef/11AIBEIkFMTAwcHR2NfXq9HgcPHkT79u3NGiAR0b3k5+djzJgxuHXrlrGtQYMGJj+fyHKWLVuGxMREk73nly1bhsjISLz00ksiRkZEZNuYlxORWErzCtHsid7Iv5wBpbsrAEBTVAJnvwZQBTWCQcd7EomhICsHh9buxO20TACA1E6GZr3aoXnf9nDydBU5OiKyZSovFUa+GYni/CJoijVQOCngpHK2+A1Fd+3ahfT0dEycONGi56nwQEX0Y8eOAbgz4+XEiRMmMw3lcjnatWuH6dOnmzdCIqIq5OXlAYDJsvIKdxfUK8aR+S1btgwbNmyAu7s7BgwYALVajYyMDOzcudM485CFdCIiy2BeTkRiUapcIFPaw8FThcu/JENXpoWqiRre7YOhKSuD3I4z0Wtb0c187FuyFUU3841tBp0e5349CjsHOVoN7ASZvb2IERKRrXNwcbB40fzvHn/88XuuojS3Byqi7969GwAwYcIELF68GK6u/DSTiMRR021auJ2LZWi1WiQmJsLJyQlyuRwbN2409vn4+MDJyQmJiYmYOHEit3YhIrIA5uVEJBaZ0h7Xko4i5/RlY1vpzVzcPHEeraMGAwbxYquvim7lmRTQ73b+12MI6BIMFx/3Wo6KiMi2PNRHxKtXr2aiTkSiKikpMf7/t99+i+joaIwcORLR0dEmd2W+exyZz9atW6HX61FcXFzljV2Li4uh1+uxdetWsUMlIrJpzMuJqLbpistMCugV9GVaXPv9KAysote6gsycavvKSzXQaXW1GA0RkW166F3XDx8+jI0bNyI9PR1ardak7+4CFhGRJSxfvtz4/2PGjIFGozE+/vLLL03G9ezZs1Zjqw+uX78OAOjcuTPmzZsHqfTOZ7IhISGYN28e/v3vf+Pw4cPGcUREZDnMy4moNuWcvVJtX+75q2jcu3MtRkMA7jnLXCa3g53c8jfcIyKydQ81E33Dhg3o3r07Tp8+je+++w7l5eVITU3Fb7/9BpVKZe4YiYgqKSoqMv7/3QX0vz++exyZX4sWLYwF9ApSqRTNmzcXKSIiovqFeTkRWROJROwI6icHlROUro5V9jUJaw0pi+hERI/soYro7733Hj799FP88MMPkMvlWLx4Mc6cOYNRo0bB39/f3DESEVWiVquN/69SqTBq1ChMmzYNo0aNMika3D2OzKdVq1YAgO3bt0OnM10eqtPp8NNPP5mMI8uo2Jt+8eLFSExMrDQDlYhsH/NyIqptHi2bVNvn1jwAUnsWbGtbfmYOuox7HE4NTD88bdSxGbyaNYReUy5SZKQv1yEn4zZupmcjNzMHBgO3OyKqqx7qt9vFixcxZMgQAIBcLkdxcTEkEgmmTZuGvn37Ii4uzqxBEtUFer0eKSkpyMnJgYeHB0JDQyGTycQOy2aNHj0asbGxAIDmzZujV69eCAwMRFpaGi5duoTDhw8bx5H5eXt7AwDy8vIQGRmJiRMnIiwsDMnJyVi1ahXy8vJMxpH5LVu2DImJidDr9SZtkZGReOmll0SMjIhqE/NyIqptdg4KNAhpilupFyu1N+rRHmCRsNY5ujvj4OodaDWwC5QqR+jKtJA7KZF99hqOfrMHA955VuwQ66X87Dz89esxHPrhAEoLS+Hi4YLw0b3QomswXBtwtRhRXfNQRXR3d3cUFhYCABo2bIiTJ0+ibdu2yMvL4038qF5KSkrC0qVLkZWVZWzz9fXFlClTEBERIWJktmvfvn3G/z98+LCxaF7VuF69etVWWPVGaGgofH19IZVKkZWVhYULFxr7ZDIZ1Go1BEFAaGioiFHarmXLlmHDhg1wd3fHpEmTjB9grFy5Ehs2bAAAFtKJ6gnm5VQf6DVa6EpKUHz1Ogw6HZwaN4S9izPslEqxQ6uXbp24AHX3dnAPDsCNo2egL9NAFdQIDUKa4ubJC/Bu20zsEOsd5wYqyOxkOLLuV0ACSGUyGHR3JlqEPtkTDionkSOsf4ryirBn3W848etxY1thTiF+jt+G0oISPDaiO+yVcvECJKIH9lDbuURERGDnzp0AgMjISLz22muYPHkyxowZg379+pk1QCJrl5SUhNjYWAQFBWHJkiXYvn07lixZgqCgIMTGxiIpKUnsEG1SaWkpAMDDw6PK/or2inFkXjKZDFOmTEFmZia6dOmCiIgIdOjQAREREejcuTMyMzPx8ssvczWGBVRs4eLu7o7ExEQMHToUnp6eGDp0qEk7t3Yhqh+Yl5Ot02s0yDtzDpm/JaHg/EUUpV3BjaT9uHnwCHSlZWKHVy+pAhsi5YtvkXP2Mvz7dkHg4J5w9PVEyhfforyoBJA9VJmBHoGDmzN6/msEvFo0AgTAoNNDZm+H1kO6oUlYK0j5ntS60oISnPjtryr79m/eh4LbBbUcERE9qoeaif7555+jrOxOwjJz5kzY29tj//79eOqppzBr1iyzBkhkzfR6PZYuXYqwsDDMmzfPeIPFkJAQzJs3D7NmzUJ8fDzCw8NZTDSztm3bYt++fXB3d8eKFSswffp03L59G56envj444/x73//Gzk5OWjbtq3YodqsiIgIjB49utKWIjKZDKNHj+YqDAvZunUr9Ho9Jk2aBDs701/jdnZ2mDhxIhYuXIitW7ciMjJSpChtH7fwImvBvJxsXXlRMQovXKrUrrl1GyUZmXAJagIJ72ZZu6QS+HVri8yDJ3A79X/vjcLdFQ3aNINEwoKtGCQyCZo81grB/TtCr9NDKpVCgACA/z7EkHcjFxCEKvvKy7QoLeRkLzHp9XpoyrSQy+1hx/s4UA091HfK3TM/pVIp3n77bbMFRFSXpKSkICsrCzExMcYCegWpVIqoqChER0cjJSUFHTp0EClK2zRy5EgsX74cFy9exLPPPmucdVtYWGh8LJVKMXLkSJEjtV1JSUn45ptv8Nhjj6Fr165QKBTQaDT4888/8c0336B169YspFtARkYGACAsLKzK/or2inFkftzCi6wJ83KyZYLBgMKLadX2F1y4BMeGftzWpZbJnR3hEuADt2aNcevkhTvbuTRtDCdfTxjKdVC4cuuQ2laaX4x9n29F/vXblfo6PNMbTSNCK/29SpalcLz3zyU7OQu3YijX6nAz8xZ2fbsXl05dRsNAPwwc1Rc+jbygUCrEDo+s3EP/qzUYDLhw4QKys7Mr3V2Yf0BSfZGTkwMACAwMrLK/or1iHJmPXC5HWFgY/vjjj0rbVlQ8DgsLg1zOfeYsobpVGAAwfPhwrsKwILVaDQBITk7G0KFDK/UnJyebjCPzqtjCKywsDDExMcYbGickJCA2NhZxcXHMg6jWMS8nWyUIAgzl5dX3l+uAqid6kgXJFHLkX7yOm3+dg2sTNaT2dshMToG+vBytnh0kdnj1UvHt/CoL6ACQ+sMBNAxtCkcPl1qOqn5z9nCGs4cLinIKK/X5NVPD0dVRhKjoQuolzJuyELpyHQDg9LFz+HVLEl7/YAo69gjlrPQ6RK/XY86cOfj666+RlZUFtVqN8ePHY9asWRZbofZQ3x0HDhzAs88+iytXrkD42/IUiURisqyfyJZVzP5KS0tDy5YtKy3tT0tLMxlH5qPX65GamnrPMadOnYJer2cR1wLuXoUhCAKOHTtm8r3PVRiWM3z4cCxbtgwrV65E37598eOPPyIjIwNqtRpDhgzBqlWrIJPJMHz4cLFDtTncwousEfNysmVSmQxOjRuhNCsbCg93OPj5QCKVouzWbZRm3oCDnw+k9vZih1nvaAuKcOPIaQBA3oWrJn0Zf/yFJv/oDhkLUbWqugI6AGiLy6DTVv9hFFmGm487np7xDNbH/heaEo2x3dnDBcOmPgnXBioRo6ufcm7m4vOYL40F9AqCQcDSOSvx8Ya5aODnKVJ0dV9RQTHycwpQUlQKJ2dHuHq4wNmCK5M++OADxMfHY+3atQgJCcHhw4cxYcIEqFQqvPrqqxY550P9ZnvppZfQuXNn/Pjjj/Dz8+MedFRvhYaGwtfXF//5z3+Qn59faWm/SqWCn58fQkNDRYzSNh0/fhx5eXlo27Yt5s+fjw8++MBYSHzrrbcwc+ZMnDhxAsePH0enTp3EDtfmVKyuyMjIwLvvvlvpe3/SpEkm48h85HI5IiMjsWHDBgwePNikb8mSJQCAZ555hqswLIBbeJE1Yl5Otk7ZwBPeYV2hzctHcfo1CAYDHHy94dPjMdg5OUFqxw8ta1vOmcvV9t0+nYZGvTpCZu9cewHRPWeZS+1kkPHfSa2TSqVw93HHhI9fQMa5a7h17Rb8mqrhHegDJzf++xBDYV4RbmVV/YFTaXEZbmfnsoj+kG7fyMGyd9cg5cD/Jjq2e6wNXowZB08fy0wq3b9/P4YPH44hQ4YAAJo0aYL169fjzz//tMj5AOChNsU6f/483nvvPbRq1Qpubm5QqVQmX0T1hUwmQ+/evXH27FloNBpMnz4dmzdvxvTp06HRaHD27Fn06tWLMxIt4Pjx4wAAT09PjBw5En/88QfS0tLwxx9/YOTIkfD09DQZR+ZVsbpi/vz5CAoKwpIlS7B9+3YsWbIEQUFBmD9/vsk4IlvALbzIGjEvJ5snAfJOn0Xe6bMoLyyCrrgEhRcv49ahY7xfokgMOl21fYIgQNAbqu0ny3DxcYfcqeo9uJuEteY+9SIoLS5Fyu7jWDblMxzfeQylhSX4Y1MS4l/+DJeOXbjnvyOyDIPh3vt//X1LPKqZooLiSgV0APjrwEksf3ctigqKLXLe7t2749dff8W5c+funO+vv7Bv3z4MGmS5bcUeaiZ6t27dcOHCBTRr1szc8RDVKXq9Hnv27EFwcDDy8vLw8ccfG/t8fX0RHByMvXv3YvLkySykW8iePXvg7u6OAQMGQK1WIyMjAzt37sSePXvEDs2mhYSEQCaTwdXVFf/+97/x0UcfGVcC/Pvf/8aECRNQUFCAkJAQsUO1OVqtFomJiXB3d0dCQkKl7VyioqKQmJiIiRMncja6md29hVdV39vcwovEwLycbJ0mNw/avPxK7XqNBoUXL8MtpCWkzLNrlVszf2QdOlVln3uzxpDwBpa1ThAEdB33OEryi+DVtCEkUgn0Wh2uHjsH72aNoNNoeSPLWlacW4w9X/0KAEhPvYz01MvGvh3Lf4RvUz94cNZzrXJ1c4aruwsKcivvU2+vsEcDC82YtnX5OQWVCugV/jpwEvk5BRbZ1uXtt99GQUEBWrZsCZlMBr1ej/nz5yMqKsrs56pQ45+iKSkpxv//17/+hTfeeANZWVlo27Yt7P+2Dx23rqD64u6l/VXtiX7mzBku7beQNm3aALizTM7Ozg4bN2409nl5eUEqlcJgMBjHkXmlpqZCr9cjNzcXI0aMMLZXrAa4exy/981r69at0Ov1mDRpEhQKBZo1awYPDw94eHhAoVBg4sSJWLhwIbZu3YrIyEixw7UpFVt4JSQkVLqhrsFgQEJCArfwolrBvJzqC4PBgKLL6dX2F1+9DtfmQZA6ONRiVCR3cYRb00bIu3jNpF0mt4c6LBQSFmtr3a1L19EgUI28azexd9FmlBWUwD3AB21HhMOg00FbUgalC29kWZvys3Oh1925L4m7nwec3V2Qn52LglsFKM4rRmlBKeAncpD1jLuXG16YOQ4L31xS6T4y46aNhsrTVaTI6raSotJ79pfep/9hbdy4EQkJCVi3bh1CQkJw/PhxTJ06FWq1GuPGjbPIOWv82619+/aQSCQm32gTJ040/n9FH29gRPXJ3Uv7ZTJZpWIhl/ZbzuXLlwHc+ePq5s2bJn13P758+TK6detWm6HVCzX9nub3vvllZGQAuPN7NyoqqtJ+9P/85z9NxpH5yGQyTJkyBbGxsZg1axaioqIQGBiItLQ0JCQkIDk5GXFxcVx5RBbHvJzqCwkAiaT6Wc0SqQTgfQBqXd6la3BvEQDXJmrcOnkR+jINXAP84NkqEFd2H0LTIT0Ah6q3FiHL8Gzih+OJvyPzxCVjW+6VG0ha/C26vzQU9nw/ap1UJoNvUz/0fKY38rPzkHcjD237hELp7IDf1uyEVMafXbVNKpWibddWeO+/Mdj85fe4cv4afBt74alJT8C/eUPIFVzF+zAcne/9QbbDffof1ptvvom3334bzzzzDACgbdu2uHLlChYsWCB+Eb1iiTIR/Q+X9osnMzPTrOPowTg6/m8my/fff48dO3YYtxQZOHAgnnjiiUrjyDzUajUA4KOPPkJYWBhGjx4NpVKJsrIy/Pnnn8ZtpSrGkXlFREQgLi4OS5cuRXR0tLHdz88PcXFxiIiIEDE6qi+Yl1N9IZFK4dK0CUoyqs7nnAMDIFMoajkq0uQW4saR03DwVMGjZRNI7e1RnHULZxN3QTAYINxn32EyP11ZuUkB/W5/bfodEa+OBFyZl9cmN193RDzbF1s+3gRtqcbY7uzujOFvPAUHvh+iUDoqEdQqAK+8OxllJRoolPL7FoHp3lQermj3WBv8deBkpb52j7WBysMyM/xLSkpMVgYDdyY9WXJv+xoX0QMCAiwWBFFdxaX94qmYWWdnZwd3d3eT2efe3t7IycmBTqfjDDwL+eGHHwAALi4umDx5Mm7cuGHs27RpE1xcXFBYWIgffvgBYWFhYoVpk4YOHYolS5ZAJpPh0qVLSE5ONvb5+PgY94MbOnSoiFHatoiICISHh1fawosz0Km2MC+n+sTe1RWODf1Qct20kG7v4gxn/8aQcCZ6rXNu5I0bR06j9HY+rv/xl0mfQwM37okuglsX76xAlNrJ4N2yMeSOChRk5iDv6k0U38qHTqMVOcL6RyKVYPvnW00K6ABQlFuEX1f/gmfjxooUGQGAg6MSDo5coWEOzq5OeDFmHJa/u9akkN7usTZ4MWacRfZDB4Bhw4Zh/vz58Pf3R0hICI4dO4ZPPvnEZHWmuT30ZmVnz57FZ599htOnTwMAWrVqhX/9618IDg42W3BE1o5L+8VTUlICAJU+eQTu3Finor1iHJlXxQz/wsJCFBeb3m375s2bxk9/uRLA/M6cOQPgzgdJOTk5GDNmDAYPHozt27dj06ZNxg+Ozpw5w/3oLaiqLbyIxMK8nGyZnVLxf+zdd3hUZdoG8Puc6ZNJJr2ShNBrqNJFVBTBgg3FxQKoWNZ1lbWxFkBF147rZ1l2VVBRFLugoqKACCpVegkEAiE9mcnMZPo53x/IyJiEmpwzydy/6+Iic96TmSczyeTJc973eZHYuycsbXPh2FMIWQrCkpsDY3IStGbOHlSDIc4CfawZPkf9PDtjYE/wsoby9GYjcgd2QXb/zijZXAi33YXsvh3R4+LB2PjhCoha/j2qNGe1A84aZ4NjpXtK4LK7YLY2T3GRSGlJaYm484kpsFfXwu10w2QxwZoY12wFdAB46aWX8PDDD+P2229HeXk5MjMzccstt+CRRx5ptsc8pSL6Rx99hPHjx6N///6hGYY///wzevTogQULFuCKK65o0iCJIhmX9qvD6z18Rd/n88Fms+Gcc85Bly5dsGPHDvz444/w+/1h51HTysjICLUT0Gq18Pn+mN2i0+lCz3tGBnfLaWqVlZUADvc/Ly0txXvvvYf33nsvNH7k+JHziKh1Y15O0UBrNEKbboQxOQmADFHLjSvVZNt7EHmjh+HQz5vgKDq8N4suxoTMIflwlVbCkpWqcoTRJ6ldOnwuD1a+/Fno2KHf9sAQa8bgm8dAw17PivO6PDDHmXHBrRchITMRfrcPerMBpXtK8OUri+DzcHUAtS6WuJhmLZr/WWxsLGbPno3Zs2cr9pinlH3cd999mDZtGh599NGw49OnT8d9993HZJ2iDpf2K69Hjx5YuXIlRFGE3+/H999/j++//z40LooiJElCjx49VIyy9brwwguxatUqAId3xf72229DPdHPO+88XHrppaHzqGnZbDYAQJs2bVBWVha2saAgCGjTpg1KS0tD5xFR68a8nKIJZ9NGBktGCvZ8vhypfTojvX83yJIEyR9E+cadkCUJGQPZzkVpUkDCbx+tqHfc66jDti9/Qb9rR6oQVXSLS7LiuicnY8V7P8BgMsCSEAtbeQ20eh1ufH4KRC1/TohamlMqopeUlOD66+v3b7r22mvxzDPPnHZQRC0Rl/Yrq3379gAO9563Wq3o06dPaHPFDRs2wG63h51HTetISxEAoYL5ES+//HLYeUOHDlUqrKgQHx8PAFi7di1EUaxXRF+7dm3YeUTUujEvJyKlGeIt0FlMOLR6U72xLtdcAIi82KG0mv1ljW7oWr7jAGQ/94lSmkavwbaVW9HjrHxs+n4jSvYcQkpOKroM6Ya9G/eg27DuaodIRCfplC59jRgxAj/++GO94ytXrsSZZ555wvezYsUKXHzxxcjMzIQgCPj000+P+znLli1D3759YTAY0KFDB8ydO7feOS+//DLatm0Lo9GIgQMH4tdffz3hmIioZTh6lq3D4cCyZcvw9ddfY9myZXA4HA2eR9QaHF0ct1qtuOeee/DRRx/hnnvugdVqbfA8Imq9miovB5ibE9GJqd6xDx0uHYGUnh0h/L46wJyWhC5Xnw9ncTnk39sqknKCgcAxxxsur1NzkgISdHotFs56DztXb0fZ3lJsWbYJ7z86H7EJFgQDvLBB1NKc0kz0Sy65BPfffz/WrVuHQYMGATjce3HhwoWYOXMmPv/887BzG+NyudCrVy9MnjwZl19++XEft7CwEBdeeCFuvfVWzJ8/H0uXLsVNN92EjIwMjBo1CgDw/vvvY+rUqXjttdcwcOBAzJ49G6NGjcLOnTuRmsrebEStxZHieP/+/bF+/fqwMUEQ0L9/f6xdu5ZF9GaSn58f+thisSAuLg5erxcGgwG1tbVwOp31zqOmUVBQAADQ6/XQ6XR49tlnQ2OpqanQ6/Xw+XwoKCjAGWecoVaYRKSQpsrLAebmRHRiYtKTsPWtRWg7agjSB/YAZAlSIIiiZesgAEjqzpWgSkvKa3wfotj0BGj13EdAacFAED+8vbTecVmSsHTut/jLzPqryIgosp3SO+ntt98OAHjllVfwyiuvNDgGHC5kBYONX10bPXo0Ro8efcKP+9prryEvLw/PPfccAKBr165YuXIlXnjhhVCi/vzzz+Pmm2/GpEmTQp+zePFivPHGG3jggQdO+LGIKLIdmWVrt9uRnJyM8vLy0FhSUlKonQtn4zYPSZJCH3u9Xhw6dCh0W6fTNXgeNY2tW7cCOLyp7tHf9wDCbh85j4hat6bKywHm5kR0YrQmAzqOPRvOkgqUr98OWZJhsMYic1BPiFoNRI2gdohRR9CIyB3UFft/3h5+XBDQ68rhgMj+20qrq61DwNvwqgxHVS38Pq7YIGppTumdVJKkE/p3vET9ZK1evRojR4ZviDFq1CisXr0awOGCwrp168LOEUURI0eODJ3TEK/Xi9ra2rB/RBTZkpOTAQC7d+9GZWVl2FhlZSV2794ddh41re+++y70sf9PS3aPvn30edQ0TCZTk55HRC2bWnk5wNycKFrpzCbY9pUgJj0JSd3aIaFDNpK65aGurBqiRgNdjFntEKNOwONHdr9O6HXFmYhNS4DOZEBa1xwMve1iaLQatthRgXCca0nC8U4goojTotb0lJaWIi0tLexYWloaamtr4Xa7UVNTg2Aw2OA5R2+C92dPPvkkZs6c2SwxE1Hz6N69O0RRhCRJof+P0Gg0oePdu3PDluZQV1fXpOfRiTv77LPx7bffAjjczig3Nxc+nw96vR779+8PbSx69tlnqxkmEUUB5uZE0Sng88OcZoXH5kBcmzQAAvxuD3wOFwJeH4JeP7RGvdphRhcBWPnyZ4hvk4K8od2hNxtRW1KFX+d9A0OsCUNvvVjtCKOOJTEOWoOuwdnosUlxMJgNKkRFRKfjhIvo//73v0/4Tu+8885TCkYt06ZNw9SpU0O3a2trkZ2drWJERHQ8mzdvDhXOA3/aSOfITGhJkrB582b069dP8fhaO4vF0qTn0Ynbv39/6OO1a9eGiuYNnTdkyBClwiIiBbXmvBxgbk4U6WRJhiUtBaVrtuHAsnWQA0HEpCche0R/SIEAJL8fYBFdUbaiwy39bMUVEDdooI8xwlFSDZ/LA5/LAynIFotK87jcGHHtufju9a/DjguiiHNuOI/tXIhaoBMuor/wwgsndJ4gCM2WrKenp6OsrCzsWFlZGeLi4mAymaDRaKDRaBo8Jz09vdH7NRgMMBh4FZCoJdm4cWPo4z/PRD/69saNG1lEbwbr1q1r0vPoxJ1or3P2RCdqvSIhLweYmxNFK41Og4JPl8FdaQsdc5VWYcf736DL+FGQJFm94KKUqNUgM78d2g/vico9h+Cxu5DZMw8GiwkbF66AILJ1iNICvgCqDlTgyn+Ox6bvN8JWWoOU3FT0HNEL675cg+Rsth0lamlOuIheWFjYnHGckMGDB+PLL78MO/btt99i8ODBAAC9Xo9+/fph6dKluPTSSwEcnom6dOlS3HHHHUqHS0TN6Mjsc4vFgg8++ACLFy/GoUOHkJmZiQsvvBBXXXUVnE5nvVnq1DScTmeTnkcnzmg0hj42GAzwer0N3j76PGp6wWAQmzZtQnV1NRITE5Gfnw+NRqN2WBQlIiEvB5ibE0Urb40jrIAeIss4uHwd2l9yluIxRbuEtmmQZRkrX/kc8u8XMQpXbYM5MRaDbhoNQcONRZVmspiw7aet2LZyC7oO647U3DTYymrw4ZMLEJdshVavUzvEqOX3+WGrtMPj9sJg1MOaZIWBq2foBKjaE93pdKKgoCB0u7CwEBs3bkRiYiJycnIwbdo0FBcX46233gIA3Hrrrfi///s/3HfffZg8eTK+//77UPHsiKlTp+KGG25A//79MWDAAMyePRsulwuTJk1S/OsjoubjcrkAADqdDhMnTkR5eXlobOHChdDpdGHnUdM6euZ/U5xHJ65du3YADvf+//TTT7Fjx45QIbdLly646KKLEAwGQ+dR01uxYgVeeeUVlJaWho6lp6fj9ttvx/Dhw1WMjOj0MDcnohNhKyxudMx5qAIy8z/FCRCw/r0foI8xocsF/WGIMaJ6fzkKftiIHUvWos9VvLChNI1OgwtuGYMvXvwUG79ZHzquM+oxcvIoiFpOvlCDrcqOrxYsxVfvfQuvxwetTouzLh6CK28ei8SUeLXDo5PkcDjw8MMP45NPPkF5eTn69OmDF198EWeccUazPN4pFdEnT558zPE33njjhO5n7dq1YRufHel9eMMNN2Du3LkoKSlBUVFRaDwvLw+LFy/G3XffjRdffBFt2rTB//73P4waNSp0ztVXX42Kigo88sgjKC0tRe/evfH111/X29CIiFo2UTw8m6Kmpib08RGVlZWh4u2fx6hpyPKJLdM90fPoxB25MBQMBvGXv/wFkydPxuDBg7F69Wo8+uijCAaDYedR01qxYgWmT58OvT58tkpNTQ2mT5+OmTNnspBOimqqvBxgbk5EJ0YXY2p0TKPXQRDYOkRptoMV6DfhXMSmWLFnxWa47S4kd8jE+Q9fiy2fr0IwEFQ7xKij0WpgSYzFjbNvxebvN6KquAoZHTLRbVgP1FbZoTdwJrrSvB4vPpv3Fb5899vQsYA/gKUfr4CjxolbHpoIizVGxQhbNrvNgeqqGjhqnYiNsyAxKQHW+NhmfcybbroJW7Zswdtvv43MzEy88847GDlyJLZt24asrKwmf7xTKqLX1NSE3fb7/diyZQtsNhvOOeecE76fESNGHLPAMnfu3AY/Z8OGDce83zvuuINLRIlauYyMjNDHf57tfPTto88jag2OvjBUU1OD55577rjnUdMIBoN4/vnnIcsy+vbti2uvvRZ5eXkoLCzEO++8g9WrV+OFF17A0KFD2dqFFNNUeTnA3JyITkxixxwU/9jwz31Kr44QWRxUnDkpDvbiSlQVliK7fycEA0FotBrsXbkZ3cYMZE90Fcgy4K6tw3sz3kZujzxYEiwo3LgHPy38EdfMvI4rdlVgq6rFkg++b3Ds1x/WY/xfL2cR/RSVHirHjPufxqoVa0LHhgw/AzOeug/pmanN8phutxsfffQRPvvss9AkphkzZuCLL77Aq6++iscff7zJH/OUiuiffPJJvWOSJOG2225D+/btTzsoIqLjadu2bZOeRycnLi4OVVVVJ3Qe1efxeMJmc56M5OTDmxClp6fD5/Ohuro6NJaYmAi9Xo/S0lIkJydj165dp/QYOTk57KnegI0bN8Jms6Fnz56YNWtW6EJF9+7dMWvWLPz973/H5s2buaExKYp5OREpThSRd8FQFH79U9jhmIxkpPbtCjnA4qDSjBYzgklWbPpkJWwHKwAAgiii7aCuqKtxIL5NisoRRh8pEMSilz6HFJBQuHFP2NiiFz/F+JnXqRRZ9HLUOBAMBGG2mDBk1ACkZqbAVmnDyq9/QW2NA1Vl1chqy0l4J8tuc9QroAPAqhVrMOP+p/HUS9ObZUZ6IBBAMBis93eryWTCypUrm/zxgCbsiS6KIqZOnYoRI0bgvvvua6q7JSJq0JYtW8Jux8TEICYmBi6XK6yNxZYtWzBw4EClw2v1UlNTT6iInpraPFedW7qioiJMmTLltO7j6H7cRxxdUH/hhRdO+b7nzJmDTp06nfLnt1YbN24EAEycOLHeTH9RFDFx4kT84x//YBGdVMe8nIiaU9DrQ8DvQ49Jl8BeeAiBOg/i8jKh0etQu+8Q4tu3UTvEqON3e7D23aWoq6oNHZMlCYWrtkJnNiA+K1nF6KKTo9oBn9vb4JitrAa+uobHqPnoDDoMGTUAQ0cNxNJPVmDzz9uQmpWMSff+BTt/K4DpGK2qqHHVVTX1CuhHrFqxBtVVNc1SRI+NjcXgwYPx2GOPoWvXrkhLS8N7772H1atXo0OHDk3+eEATbyy6Z88eBAKBprxLIqIG+Xy+sNt/Lp43dh41DfZEPz05OTmYM2fOKX/++vXr8dprr0Gn08Hv94eO6/V6+Hw+3Hrrrejbt+9pxUeNY69XagmYlxNRc6krq8aBpWtwAEBit3bQGfQo/HoVfHYnDFYL4nI5k1NpHoc7rIB+tL0rt6Dd0O4KR0TH22CXfycpzxhjQO8hPfHsP/4v9PyXFVdg86/b8Ze/XQlLrFnlCFsmR63zmOPO44yfjrfffhuTJ09GVlYWNBoN+vbti2uuuQbr1q1rlsc7pSL6kU2GjpBlGSUlJVi8eDFuuOGGJgmMiOhYtm7dGvpYEAR06NABBoMBXq8XBQUFoV+KR59HTaehWdCnc160MRqNpzXTu1OnTsjMzMTLL7+MsrKy0PHExETcfvvt3NiymfTu3Rtvv/023nzzTfTu3TtsNrokSaF+0b1791YnQIpKzMuJSGl1lX/sxVC9bW/YmNfuBFgbVJyr0t7oWMDjQ5AtdhQXl2KFRqtBUptk9BrZF5ZEC2xlNmz8Zh18bi+MMWydqDRZAua/uLDBCxgL53yGAWf3USGqli82znLMcctxxk9H+/btsXz5crhcLtTW1iIjIwNXX3012rVr1yyPd0pF9D9vHiSKIlJSUvDcc89h8uTJTRIYEdGxOByO0Md6vR67d+8O3T5STP/zedR0TvR55fPffIYPH46hQ4fiyy+/xHPPPYd//OMfGDNmDDe0PI7T6UcfExMDi8WCzZs346677sLo0aORlZWF4uJifPXVV9i8eTNiY2MRExNzyv3oAfakp5PDvJyIlBaTltTomD4uBuAmloqLTY1vdExr0EGjZ36oNK/Lg2tmXoeywlKsXfwLbGU2pOSkYNhVw5GQkYign6vFlOZ2eWCvbnjFht/rh63SjoycdIWjavkSkxIwZPgZDbZ0GTL8DCQmJTR7DEfa+9bU1GDJkiV4+umnm+VxTqmIvnjxYsiyjJiYw7vW7tu3D59++ilyc3Oh1TZphxgiogZ5PJ7Qx0e3s/jz7aPPo6YTDAab9Dw6NRqNBp07dwYAdO7cmQX0E9AU/egBYNOmTdi0aVO94w6HA7feeutp3Td70tPJYF5OREqzZKVAo9ch6PPXG8sc0guiju89SotJtsKUYIG7pn7bhPZn5UNn5sV5pRlijNi+aht+/viPDXjL95Xhixc/xejbL0a7Ps0zU5Yad7zLe8Kf9jyiE2ONj8WMp+6rt7nokOFnYMbT9zVLP/QjlixZAlmW0blzZxQUFODee+9Fly5dMGnSpGZ5vFP67XbppZfi8ssvx6233gqbzYZBgwZBp9OhsrISzz//PG677bamjpOIKExGRkaojUVCQkLYJpdH387IYE/G5qDRaE6oQM6iLkWa0+1HDxzuSf/BBx+EbeSalJSEcePGnVYv+iPYk55OBvNyIlKaz+lG+0uGY983P8NXe3hPIkEUkdavC0StBjJn2CpOFoAz77gUP//vS9SWHM5PBEFAzqCuaDesB/wuD0zs96wsWcaaRb/grAnnoEP/TpAkCQKArSs24/t536Jt/ulP6qCTYzAZkJSWiKqy6npjphgj4uKbr+1Ia5eemYqnXpqO6qoaOGudsMRZkJiU0KwFdACw2+2YNm0aDh48iMTERFxxxRWYNWsWdDpdszzeKRXR169fjxdeeAEA8OGHHyItLQ0bNmzARx99hEceeYTJOkWlYDCITZs2obq6GomJicjPz2cBsRkdmXEHIKyA/ufbR59HTUen051QEb25fnkRnarT7UcPHO5JP27cOLbSoYjAvJyijSzL3OBZZbbdRbAXFiNrSC/oYkyQgkGIWi2qtxdi76IfkT/lcrVDjDrlOw7g0MYCDLppDKRAEAGvHwaLCV6XG1/PfAfn/XO82iFGHXuFHZOevhlblm/C2/98Ez63F+Y4MwZfPgxXPfQXuJ1utUOMOl6PD9fddRVeevi/CAb++FtWEARc+/dxcNhdKkbX8lnjY5u9aP5nV111Fa666irFHu+Uiuh1dXWIjT38xHzzzTe4/PLLIYoiBg0ahP379zdpgEQtwYoVK/DKK6+EbaKYnp7ODf6a0bBhw/DTTz+d0HnU9NjOhaIdW+lQpGBeTtEg6PUi4KqDo3A/5EAAMbnZ0Fut0JrYokINWpMRnupaFH69qt6YqNNCZCspxWn1WnQdMwCyJGH/rzvgrnEgtXM20rrkoP1Z+RAEtqlQWnxaIpbP/x7bftwcOlZXW4elc7/B0HHD0XvU6a9epJMjSRKWfrIc9z3/N6xZtgEH9x5CalYyBo08Ayu/+hlt8jLVDpEi3Cn9duvQoQM+/fRTXHbZZViyZAnuvvtuAEB5eTni4uKaNEA6OZwNrbwVK1Zg+vTpGDhwIIYOHQqv1wuDwYDi4mJMnz4dM2fOZCG9Gfx5hnlMTAy0Wi0CgQBcLlej5xEREbUmzMubh+T3QQocbkkhaLXQ6PQqRxS9gl4vHPsPwJiYAEteDiABgiigtnAf4vJyoTWZ1A4x6iR0zEbxyg0NjiX37AjICgdESG6fhYrdB7Hm7W9Dz//B9QUwxplx1l2XQ9BzdajSgoFAWAH9aL98vho9z+mlcERkiYuBrbIWv3y/DiMuPjzZThAF/PzdWuzYuBtX33aZyhFSpDulIvojjzyCv/zlL7j77rtx7rnnYvDgwQAOz37p06dPkwZIJ46zoZUXDAbxyiuvICMjA2vWrMHPP/8cGtNoNMjIyMCrr76KoUOH8mJGE/vf//4Xdvvowvmfz+P3f9Mzm82w2+0ndB4RETUf5uVNS5aCCNS54DqwD5LfBwAQdXrEZOdBa47hpmMq8Hu8MCYmoGr9b/A7Dm+aqDEYkNCrO/zOOmiMRrZ3UZggCMg5+wwU/bAm7LgpyYrU3p0gy5JKkUUvKRjE2neWIibZiq6jB0BvNMBWXIkdS37FhoUr0P/ac9UOMerYymyNjgW8fngcbOeitNTMZEx95nZ8NvdLzLzlaQQDQQiigP7De+PBl/+B5PREtUOkCHdKRfQrr7wSw4YNQ0lJCXr1+uPq2bnnnovLLuOVGzUcmQ09ePBgPPzww8jLy0NhYSHmz5/P2dDNaNOmTaGLFgkJCbjxxhsxePBgrF69Gq+//joOHToUOo9/yDatoy8WWa1WaLVaeDweGI1GBAKBUIH36POo6TgcjrDbGo0GJpMJbrc7rIXLn88jIqKmxby8aQV9Pjj27go7Jvl9cBTuQlzHbtAaOetZSbIkQQRQsvJnyEflF0GvF5W/rkf68CEIer3QGtnWRUlBfwBeZx06XTkS9sJiBL1+xLZJhajVoK6sCrE56WqHGHWq95dh8M1joDXqUPDDb3DbXUhqn4GRD/wFO79bh6CPm70qzRR77N8XWgNXByjN4/Zg0TtLsOyLP9rCypKMNcs2wOfx4W+zpiDWys1FqXGn3KwsPT0d6enhvxwHDBhw2gHRyTsyG3rw4MF4/PHHIf4+Q6Z79+54/PHH8dBDD3E2dDMpLy8HAMTHx2PhwoXQ/t7/76KLLsIFF1yAK6+8EjabLXQeNR29Xg+fzwdBEMJmRB+ZkS4IAmRZhl7P5dfNQZLCZxgFg0E4nc7jnkdERE2PeXnTkCUJnvJGLr7LMryV5dBkZnM2uoIkWYbr4KGwAvrRbDt2Iblfb2WDIrgrbagtLEZMaiLi27WBFAhC1GlRvaMQjoNl6JyVpnaIUceSGo+yrfuwddEvoWM1+8uw76etOOvvl7MnugpMFhPiUqyorai/ejerczZ0RhbRlWavqsUPn69scOy3n7eitrqWRXQ6Jr6TtgJHZkNPmDAhVEA/QhRFTJgwASUlJdi0aZNKEbZe27dvBwCMGTMmVEA/QqvVYvTo0WHnUdM5smGoLMvQarXIysoK/dNqtZBlOew8alonumyay6uJiKilkKUggu6G28MBQMDtgsyLw8qSJPhqbI0O++y1kIJ8TZTmd3uRfVY/HFi+FjsXfovdn3yPnQu/haDRIK1vV4Dpn+J0Bj22Lv6l3vGA148NHyyHoOGLojStQYcrHrgaprjw9pbW1HhceMclEDUsxynN5ag75u+MmsrjtyttraJh8ltTfI3cNrsVqK6uBgDk5eU1OH7k+JHzqOnt2rULkiSFXcSQJAm7d+9WMarWrXv37vj6668BAIFAAMXFxY2eRw3zeDwoKio6pc+1WCxhrVqSk5Ph9/uh0+lQWVkZdt6uXbsauovjysnJgZHLs4mISCmCCFFvQNDraXBY1Bs4C11hgkYDbUzj+6tozWYILEQpzto2A9vnfwXJf1SLEFlG+YYdyB7RH4KeZQalVRWWhDYUjU1PgDkhFjX7y+Gr86B6X2n4a0WKqLM7UVZYigmP3YDqQ1WoKq5CWts0xCbFoXxfGVLzuGJDaXrDH6vU23bJQe8hPbBzYwG2rz/896rZEn37een1eoiiiEOHDiElJQV6vb7VTYSTZRk+nw8VFRUQRfG0uhXwt1srkJh4ePODwsLCBguGhYWFYedR08nKygIArF27Fg899BAmTJgQ1o9+7dq1YedR0zl6E9fjnXfxxRc3czQtU1FREaZMmdIk93V04fxoDofjlB9jzpw56NSp0+mERUREdMJEjQbG1Az4HQ3PRDOlpLOIrjBRFGHJy4Vj774Gx62dO0DHTcwVV1dS1WhRtmzdNiR2bgvEKBtTtJMlGdlndEbX8/vBUWGH2+ZEtzEDAQCr/7sYvy/SJQV5nB7IQQlSIAi9yYDUnBRodIdXTJftK0VCBuszStNoNbhyyiUYdsFAVJXW4MDeYoy9YQymPHgD1ixbD70x+lrBiqKIvLw8lJSUhPb0a63MZjNycnLqdfA4GSyitwL5+flIT0/H/Pnzw3qiA4dnQ8+fPx8ZGRnIz89XMcrWaezYsXjttddgNBpRUFCAv/71r6GxtLQ0xMTEwOPxYOzYsSpG2TrV1dU16XnRKCcnB3PmzDmlz62rq8Ndd9113PNmz54N8yn+cZuTk3NKn0dERHSqNEYjzFk5qDt0AKGqkyDAnJUL0WBQN7gopTUZkTKwHyrXbYQc+L03uiDA2rkDDAkJ6gYXpVwVja9w9jnq2PZIBSkdMhGbloAfnv8Ifrc3dDyxbTpGTL0S7LGjvPj0BMiyjJXvL0fHgV1gjDGi+lAV9m4swICLBsEUx42qleYPBDD0/AF46q5/o6SoLHQ8ITkeD/z77wgt54gyer0eOTk5CAQCCDayB0lLp9FooNVqT3uWPYvorYBGo8Htt9+O6dOnNzgbevXq1Zg5cyY3FW0Ger0e48aNw4IFC6DX63HVVVchIyMDJSUl+Pbbb+FyuTB+/HhubtkMqqqqmvS8aGQ0Gk9rpndWVlaojc6RjVyP/H9kvHfv3k0RKhERkSJEjRaG+CToLFZIPi8gHG7jImq1EETm0mrQGAwwpaUi85yz4K+rA4IStJYYaAwGaAzMsdUQk5bU6JghPpY7r6lBEPDTK5/D7/GFHa7eV4ptX/6KnpcNVSmw6OayuZDRMQubf/gNWp0GwYCELoO7orqkGglZjf8cUfMwGPR4+ZH/hRXQAaCm0obn730F0166W6XI1CcIAnQ6HXQ6bnh7LCyitxLDhw/HzJkz8corr4TNhs7IyMDMmTMxfPhwFaNr3W699VYAwMKFC/HBBx+Ejms0GowfPz40Tk3rRHv8cy+A5jN//nxMmDABxcXFocL50QX0+fPnqxkeERHRKRE0Gmg0Gmg48zxiiDodRJ0OuliL2qEQgNg2adAaDQh4vPXGsob2hsgijOJqD1XVK6AfcXDdLnQbPUDhiCjgC8BebkN6+wyIGhG2shokZ6ciNjkOzmoHgv7WOeM3knlcHuz8raDBsbLiCjjtjW8uTgSwiN6qDB8+HEOHDsWmTZtQXV2NxMRE5Ofncwa6Am699VZMnjwZn332GQ4dOoTMzEyMHTuWM9Cp1Zs/fz7sdjumTp2KPXv2oH379nj++edhtVrVDo2IiIhakaDXB8nngyzLEPU6aLn5uGpkEeg0biQKv1wJd9XhPQREnRYZA3siNjv1j7Y7pBhXjaPRMSkoIciNRRUnakSk5Kbi46c+gN/rDx03x5kx9h9Xgo3qledx17/wdzRHrVOhSKilYhG9ldFoNOjTp4/aYUSlI61dSBla7Ym9fZ3oeXTqrFYr7r//fkyZMgX3338/C+hERETUZGRZht/hQNW63+CtrgEAaC0xSOqTD0NiIkQtJwwpTfYHUfDZMrQ5qx9is9MASYYcCOLA8nUodXuQMYh7cSktMSe10TFDrBkaPf8mUlrQH8SXL38RVkAHgLraOix9cwkuu5e1A6VZ4mKg1WkRaOSiUnIaN3ulY2O3MiJqkex2e9htnU6H7Ozsej28/nweEREREbUcgbo6lC77KVRAB4CA04WyH1fD7+SsQTXU7NyHzuPOg95ixoEf1mLfktWw7z+E7LP7IxgIQvL7j38n1KSMVgsSGimkd7twIHQmtqdSmsflQV0j7UHK95VxdYAKYq0xOH/c2Q2ODTinL0xmrnCiY+PlSCJqkeQ/LX/z+/04cODAcc8jIiIiopajrrik0aKsbesOpAzoyx7cCkvs1g4VG3aidO220DF7YTH0cTHoMn4UwPRbeSIw6MbR2PLFahxcXwBZkmCINaPbmAFI75YDiS12FPfnGeh/FuBrojifP4ALrj4XRrMBX723FG6XG3qDHiMuGYqLrh0FibUDOg4W0SnqeTweFBUVqR1Go3JycmBkz0ciIiIiijJSMAhPeWWj494aGyR/gEV0hUk+f1gB/QhfrQvFq35D9ln9VIgqukm+IL5/7gPkX3YmupzfH1IwCAgC9q3ehgPrdmPADeepHWLUsaZaIYgCZKl+YVZvMsBkMakQVXTz1nnw5N9fxK0PT8SIi4fB7/VDp9fBYavFjJuewj//7261Q6QIxyI6Rb2ioiJMmTJF7TAaNWfOHHTq1EntMJrF6VzAEEURkiSFbqekpEAQBMiyjIqKirDzdu3adcox8iIGERERkXo0psbzMK3RwFWHKqjesb/xse2FyBrSS8FoCACq9pbA7/Ji3TvfQWfWw2Axw1VZC/n3v5ca6wFNzUcQBPQbMwBrF/1Sb+ysCWdzPwcVeD1+tO/aFl6PD2+/8D4OFh5CamYKzrn0TPQf0RvO2obb7xAdERFF9JdffhnPPPMMSktL0atXL7z00ksYMGBAg+eOGDECy5cvr3d8zJgxWLx4MQBg4sSJmDdvXtj4qFGj8PXXXzd98NTi5eTkYM6cOU1yX/v378esWbPw4IMPIjc3t0nuMycnp0nuJxI15QWMowvnR5Mk6bQeozVfxCAiIvoz5uUUUQQBMdlZcO5reNKFpV1bCBpu86U0Kdh4Gwo5KDU6Rs0nGAggrWsOeo4dAr/HB6/DDUuKFV6nG6v/9xXkIC82KS0YCKLHWfmITYjF2sW/wFHtQEJGIgZdOgTpHTIRZDsXxWm0GvQZ2hPP/OOl0AqBkv1l+G31Fky480roDVzVRMemehH9/fffx9SpU/Haa69h4MCBmD17NkaNGoWdO3ciNbX+xhgff/wxfD5f6HZVVRV69eqFcePCdza+4IIL8Oabb4ZuGwzcSIMaZjQam7xImpuby8LrCTidCxi1tbW45557jnves88+i7i4uFN6DKB1X8QgIiI6GvPyP8iSBCkQAARA1GghiCzUqkEURUAQkJDfHTWbtwFHzTq3tM2B1mxiKxcVJHbKQVkD7VwAwJqXxQsbKkjtmoPE3DSsfPULeI7azDK9ey7Ovf9qiHxNFKfRavDGP+cgvV0GzrxmBIwWE5zVDqz98le4HW5c98QktUOMOlqdBu++/FGDLXYW/udz9Duzt/JBUYuiehH9+eefx80334xJkw6/gbz22mtYvHgx3njjDTzwwAP1zk9MTAy7vWDBApjN5nrJusFgQHp6evMFTkSn7XQvYFgsFjidzmOO9+/f/5Tvn4iIKJowLz8s6PPCXV4Cv60GAKCPT4QxJR2aFlD8b410FgvqikuQOvgMBOrckIMSdHEWeCqqoLNYIGrYEkFp+tgYxOVlorbwUNhxUadF9ll9IXA2p+IEWcDKlz+H1+kOO166dT/MiRvR7aKGVxRR87GX2xH0B1C88wCKdx6oN+5xelSIKrp5XB7Yq2obHPN5faiptCErL0PhqKglUfVypM/nw7p16zBy5MjQMVEUMXLkSKxevfqE7uP111/H+PHjERMTE3Z82bJlSE1NRefOnXHbbbehqqqq0fvwer2ora0N+0dEkW/RokWwWCwNjlksFixatEjhiIiIiFqmSMnLAXVz86DPi9qC7fBVV0KWgpClILzVFajdswNBn1exOOgPWpMR1s4d4He44DxQDFdxMTzlFYhtlwudJeb4d0BNzra3GDln9UPuyIEwJcdDZzEhqUd7dLv2QpRt2g2pjj8rSnOUVdcroB+x/+dtCLj9CkdEoigcc1w49jA1g+OtKuOKDToeVb9DKisrEQwGkZaWFnY8LS0NpaWlx/38X3/9FVu2bMFNN90UdvyCCy7AW2+9haVLl+Kpp57C8uXLMXr0aAQb6d325JNPwmq1hv5lZ2ef+hdFRIpatGgRFi5ciKSkJABAUlISFi5cyAI6ERHRSYiUvBxQLzeXZRnemirIgfob8MkBP3z2Gm5iqRKtyQRL2xyk9OuN5H59ENepA3QxLKCrxV1Zgy1zv4DjUAVyzh2ADpeMgCUzBdve+woV63cA/DFRnLPS3uhY0B9EkBuLKi4uxQpdI6syrClWGC0mhSMiU4wBiakJDY4ZzUbEJ556G1iKDqq3czkdr7/+Onr27Flvs6Px48eHPu7Zsyfy8/PRvn17LFu2DOeee269+5k2bRqmTp0aul1bW6t4Id3j8aCoqOENcyJBTk4OjEaj2mEQNSglJQVPPvkkpkyZgieffBIpKSlqh0RERBRVmiovB9TLzeVAAH57TaPjPls1DAnJELQt+k+oFsnvdKJ601a4S8oAAPqEeCT16QldXBzbuajAkpWK8g07UbNzP4JuL0SdFnVlVZA8PhgTrRCOMwOXml58VuN//+hjjNDq2WJHaRqdBhfcdhG+ePHTsP0cRK0GY+4YCy3bHinOU+fFzf+8Hs/e839hG7sKgoCbHrgWjlrXMT6bSOUienJyMjQaDcrKysKOl5WVHbdvosvlwoIFC/Doo48e93HatWuH5ORkFBQUNJisGwwG1Tc4KioqwpQpU1SN4VjmzJnDjTKJiIiIWqlIycsBFXNzQTjmUm9B1HD9vQoCrjqULvsJQe8fLUJ8NTaU/LASmeeeBb2VMweVFpOejIyBPRHbJhW2vcUIen3IGNgTGoMOok4LgRc2FGdOjEVcRiJqS6rrjXU+vx+0Zk6IU5qjshY+txcTn74Jaxb9DFtpDdLy0tF39BnYumITYuJjEJfE9y8l6Qw6VJdV477n/4afl67FwT2HkJqVgqEXDET5wXLkdGijdogU4VQtouv1evTr1w9Lly7FpZdeCgCQJAlLly7FHXfccczPXbhwIbxeL6699trjPs7BgwdRVVWFjIzI3SAgJycHc+bMaZL72r9/P2bNmoUHH3wQubm5TXKfOTk5TXI/RERERBR5mJcDolYLQ3IaAkV7Gxw3pqRx1rMK6krLIGhEJOR3hy7GDFmWIfkDcOwphG37LiT36w1Rx9UBSvLaaqE1GbDro6WhY1Xb9sKYaEXHy0ZAaqAlEjUvKRjAkFsuwob3l6Fs++EV7lqDDp1G9kWb3u3hd3thimX7ECW5nR5898Y3OOOigRhyxZmQJAmCAPy66GdsXroRnQd2VTvEqKMRRbw1+wMMOrc/hl84GLIsQ6MR8ev367H00xV48u1H1A6RIpzq2cbUqVNxww03oH///hgwYABmz54Nl8uFSZMmAQCuv/56ZGVl4cknnwz7vNdffx2XXnppqA/yEU6nEzNnzsQVV1yB9PR07NmzB/fddx86dOiAUaNGKfZ1nSyj0djkM71zc3M5e5yIiIiITgjzckAXY4Eu1gq/I7y/sC4uAVoTe3ArTQoG4at1ILF3T9Rs2Q5/rQMAoDEaEd+9CzxVNQj6/SyiK0xnMWPXh0vrHfdU21G6bgcyB/dUIaroFvQFsWrO5+h95ZnIv2wYgv4ANDotSrYUYv2CZehz9Qi1Q4w68ekJuPy+cdiybBP+d9drkCUJGp0W+ef0wiV3XQYjL2oozuWow03TrsP29bvw5J2zEfAHIGpEDDi7L+6cdQtslXa0aZepdpgUwVTPNq6++mpUVFTgkUceQWlpKXr37o2vv/46tKlRUVERxD8tq9y5cydWrlyJb775pt79aTQabNq0CfPmzYPNZkNmZibOP/98PPbYY6q3bCEiIiIiilTMywFRp0dMm7YIej3w1lQCEGBITIJGb4SoY/9apcmyDEtOG5StXA35qP61QY8HVes2InXIAECSVIwwOtl2H2h0rGpLATIG9lAwGgIA+6Eq1FXVYtV/FtcfFABZ4m6vStPptVi7+FcUbtwDABBEAUF/ABuWrAMEAbk981SOMPqYY03Ytm4HfvhsZeiYFJTw83dr4Xa6ce1dV6kYHbUEqhfRAeCOO+5odJnosmXL6h3r3LkzZLnhXwImkwlLlixpyvCIiIiIiKIC83JA1Okg6nTQWWLVDiXqybIMT3lFWAH9aLUFhUjq20vhqCjg8TY6JgWCYZsokjKC/mO00JHR6Ps0NR+P04PSPYdwzsTzkZKTAp/bB73JgOKdB/DrFz/jjIsGIi7ZqnaYUUWWgBWLVjc49tvPW3Etf0zoOCKiiE5ERERERER0NAGAt6qm0XGf3c6CrQricjNQtm57w2M56RBEbsCrtKS8w/tMpHXNQadz+0Cj18FVZcfmT1dBa9BBw5ZHinM763DpPeOw7J3v8P3cQ6Hj7fp0wNi7L4fP41cxuuhU56xDMNjwRVkAqKm0IacjNxelxvGdlIiIiIiIiCKPKEJriQHKGh7Wms2HK+2kKK3ZBEtWKpzF5WHHBVFE5pB8QBAb+UxqLlqDFiOnXYPakmoUrNgEURQh6LQYetvFAARoDGxHpbTYpDh89txHKN1TEnZ874YC6Aw6nDvpfJUii156g/6Y4+ZYs0KRUEvF325EREREREQUkWLaNL7JW1z7PEDkn7RK05n0aDOsDzIG9oAuxgRBo4G1XRY6XXEuNEYjL2yoQAoEUbWvBNasJLQb2gNpXXPR8ax8BH0BSL7A4TY7pKiAN1CvgH7Erl93IMjXRHGiVkTPAV0bHGvTLhM6PS820bFxJjoRERERERFFHEEGJElC8hl9UbX+N8hHluELAuI6toc+Po4bi6rAa3dh5wffIC43A1nD+kCj08JVWomCz5fD0iYVbUcOVDvEqCNqtYjPTMHyFz6Cr+6PnvVJ7TJwxnUj//jZIcU4axyNjsmSDG+dR8FoCAB0Wi0uuWE0XI467N2+P3Q8IycN108dD4Pp2DPViVhEJyIiIiIioogjC4BGr4eo0SB16EBAkiHLMkSdFoIgwO9yQ58Yr3aYUce29yAAoLaoFEGfH6JOC3dFDYJeH+x7DkI+d4DKEUYfKRjEylc+h98dvulr1d4SbF+yFt0vHqRSZNErNjGu0TFBFGGIMSkYDQFAQlo8Du4rwbDRg3D5TRejpsKG+MQ41NocqKmoQVv2Q6fjYBGdiIiIiIjod1IgAMnnha/WBgDQWxMg6nQQtVzmrQbZH0DQ64XWbEJdeSnkoARTehpkARB1WoAtERSn0WuR1K0dkru3h+NgGYJeH1LzO0EKBFC0fB0Egf1clOYora5XQD/iwNpd6DKqv8IRkd5sQFbnbBTvPFBvrPuZPWAwctaz0oL+IMwxRnTs0Q6L53+LyvJqxMXHYsw1IyFqNAgEubKJjo1FdCIiIiIiIgCS3w9PdQW0Zgv0cfGHjwX88NfaYUhMhqhjIV1RkgRBq4G31IaKX9aGDtfu3gNjWgoSe3YHG3ArL7FrOziKSmDfV4zY7HRAkhHweGEvKkXnK86FoNWoHWLUcVU33jpECgTZE10FUiCIM68ZgZ8//gn7Nu0FAAiigC6Du6HL0G7weX0qRxh9bFW1eOrul9D/rN64dPKFEARAEAR8/9mP+O7j5Xhq/nQACWqHSRGMRXQiIiIiIiIAAZ8XuphY1B0qQtDjBgBoTGaYM3MQ8PugZxFdUTIOrwyo3VVQb8xTVgF3eiXMWY1vPErNQxQAY4IVtftL4KvdC1Gvhc9Rh6SuefDYnNBZ2KZCaYk5qY2OGWJN0HLDRMXVlFbjk2c+xIBLBmHoVcMRDASg0Wqw+9dd+Pjphbj+iUlqhxh1HDYnrv37OJQfqsTMKU/D7XJDb9Bj+IWD8dcZN6KqtBpt8vg7hRrHIjoREdEJKisrg91uVzuMMPv37w/7P5JYrVakpaWpHQYR0QmRggGIoojagu2ALIeOB911cOzdhbgOXSEFgxA1nGWrFFEQ4CwsanTcuXcfTGmNFw+peQS8frjKKpHcrT2qd+9HoM6D+LwsaH9vTyFwdYDiDBYz4rNTYDtQUW+s6+gBEPUs/ShNbzIgt0dbtOmag52rt8FWZkNKTira9e2A4p0HoeFrojiLNQYH9hRjyQffh475vD589/Fy1NY4MO6WsSpGRy0Bf2qJiIhOQFlZGa697nr4fQ33m1TbrFmz1A6hHp3egHfefouFdGpywWAQmzZtQnV1NRITE5Gfnw8NC5t0muSgBE9VeVgB/Y9BCd7qchhTMwB+rylGCgYh+RtveRD0+Rt+vahZyUEJfpcHB5evDx2z7TkIvdWCdmOGQeJrorjqfSUYOOkCbPliNQ79tgeyJEMfY0TX0QMQm5YAv9MDJMSqHWZUiU2ORddh3fH+o/MhS4d7bRes3YW1i3/B5fdfBaPFqHKEUUgGln6yosGhX39YzyK6itxuD6oqqmG3OWAyG5GQGI+ERKvaYdXDIjoREdEJsNvt8Pu8cLc7C5Ix8n6hRxrRYwf2LofdbmcRnZrUihUr8Morr6C0tDR0LD09HbfffjuGDx+uYmTU4skSgi5no8OBOhcgsTioJFGrhTkjDe7S8gbHjSnJENimQnkCULZ2W73DPrsTlVsKkDW0t/IxRbnY9CT88OxC9L9uJHpcPAhBfxAanRb7ft6G3T9sxPA7L1M7xKgjS8CS/ywOFdCP8Hv9+Oa/X+GamderFFn0qnO5EfAHGh23VdmR06GNghERAFRVVGPunPfx7tyP4Pf5AQC9+nXHEy88hOzcyGqvwyI6ERHRSZCMVkgxyWqHQRSVVqxYgenTp2Pw4MF4+OGHkZeXh8LCQsyfPx/Tp0/HzJkzWUinUyeIEHR6wOtpcFjU6gBR4ZiinCzL0MbGQmMyIeh2h40JGg1i83IAfwDghE5F2QuLGx2r2laIzCG9FIyGAEBr1GPo7RfDV+fBhg+Ww1Nbh6S8dHQY0RtZvdtDy9YhinNU2OGta3gFa01JNTxOd4Nj1HwMv7ecaozZYlYoEjoi4A/gw/e+wLw5C8KO/7ZuK267/h688cG/kZoWOX97Mw0kIiIioogXDAbxyiuvYPDgwXj88cfRvXt3mM1mdO/eHY8//jgGDx6MV199FcFgUO1QqYXS6PUwJh9jc77kNGh0BgUjIjkow7nvAJL79UJMmyxAONxr25iSjJRB/WHfvQdcG6A8yd/4+6wcDLLFjgo0WhGHNu3FT698gfIdB1B7qAqFP23F908vACBA5IoNxQUCx85HpKB0zHFqegaTAZ17dWhwLC0rBTGxLKIrraK8CnP/s6DBsaJ9xSguOqRwRMfGIjoRERERRbxNmzahtLQUEyZMgCiGp7CiKGLChAkoKSnBpk2bVIqQWgPRYIQxJb3ecWNqJjR6FtCVJoiAMTkR5avXQNCISDmjL1IG9oc+IR6VazZAazRC1PBPWqUldMgGAMRmpyH3vEFoN2YY0vp2hcaggzUvEwL3DVBc0BfAzm/W1T/uD2LDgh/gr2t4hQ01n/i0eIjahn8WzHFmmOJYsFWaLMsYd8tYpGeHXzBPSI7HjQ9cWy+/pObnrvPA5axrdLxwT+Obi6uBa3qIiFqYsrIy2O12tcMIs3///rD/I4nVamVP7laA3/cnr7V971dXVwMA8vLyGhw/cvzIeUSnQmswAonJ0CckIfB7f3RtjAUQRGgMLKKrQWuJgTYmBs79B+CtrgEEAX6nC6JWC0tOG0jsU684SZLQ+arz4ThQipKfNyPg9SIuJwMdxo6AqNPV6wFNza+ioPHZmjVF5Qh6/QpGQwCg1esw7KrhWPHuD/XGRt54AfTmY7cWoabnqHHipYf/i/G3Xw6DUY+y4gokpyVCFEW8/q93cPOD1yOtTYraYUYVg0kPo9EAj6fh1kdtcrMUjujYWEQnImpBysrKcO1118Pva/iXjNpmzZqldgj16PQGvPP2W62qmBht+H1/alrb935iYiIAoLCwEN27d683XlhYGHYe0akSNVrIAT8EjRYQAAGA0MhsQmpmsgxBFJF8Rm9AkuGuqAQkCYbkJGj0evhdLogmk9pRRqXiVb/BebAsdNtWcAD2wkPofOW5KkYVvX7vdHQaJ1BTc9mcyO6agyv/OR6rFv4IW1kNUnJSceY1I1BbWQu3rQ6x8bFqhxldBMBeVYv/PDYXphgT4pPjUFvjhKvWdXiYPyeKS0lNwlXXjcVb//2g3lhqWjJy2kbWRq8sohMRtSB2ux1+nxfudmdBMlrVDifiiR47sHc57HZ7qykkRiN+35+81vi9n5+fj/T0dMyfPx+PP/542JJbSZIwf/58ZGRkID8/X8UoqaWTAn54ykvhqSwLO25MzYAxOfXw5qKkGBmAoNXCU1aOms3bwsbMbbIQ360TBJFFD6UJghBWQD9CDgZx6OfNyBszTIWooltyhywIGgGZPdshu9/hnwuPow57f9wCjU4LrYGlH6X53D4EA0Fs+GY9zrxmBIwxRrhsLvz04Y8YfNlQ+H1cHaC0WGsMElMTUF1eA7fLDbfrj81dDSYDktI4EUNper0eN0wZj8ryanz52Xeh4zlts/Dv159EekZkrQzgOykRnTS2VTh5Td1WQTJaIcVEzi7VRErg931002g0uP322zF9+nQ89NBDmDBhAvLy8lBYWIj58+dj9erVmDlzJjTsxUunIeCug6eyDIJGA63ZcviYywlPeQl0ljiIFhbRlSVADgbrFdABoO5gMUxpyTCmNb4ZLDUP254DjY7V7i85vLkoKUrUa3HOvVdj36ptWPvOdwh4/bCkWNFl1BlIzEuHhhuLKi42MRbvTn8LtRV27Fm7K2zMV+fDJXdfplJk0Utr0OH6qVfjpQf/W28j+mvvHAcN99hQRUpqEv75+N247a6JqKiogsUSg6SURKSkJqkdWj0solOLxULuyWmqIi7bKpya1tZWgYhIDcOHD8fMmTPxyiuv4K9//WvoeEZGBmbOnInhw4erGB21dFIwCE9FKUwZbSDq9Ag4awEA5ja5kHxeeCpKoTGZIfJCjWIEUYBz775Gx2t374UxOfL+yG7tNIbGezkLWg1bIqjA53Rj0ycrUbHzYOiYs8KOte98h/7XjURqp8hqiRANPC4PaisarlcU7zyAYIAXm5TmtDmx/ItVuPf5v2HVN7/i4N5ipGalYNjoQfj1+/Vo2yUHqVmRNfM5WsTFWRAXZ0Fuu2y1QzkmFtFPEwu5J4eFXPU0VRGXbRVOXmtsq0BEpJbhw4dj6NCh2LRpE6qrq5GYmIj8/HzOQKfTJ0kwJCTDZ6uG3/FHfu+troQuLh76+ARA5iaWSpKDQQQb2WwMAIJeH18SFcS3z0bxyo0NjiX3aA9wNqfigj5/WAH9aFsX/YykOy9XOCLyuDzHHPd72M5FaV63Dxt+2oQta7ah/1l90GNAN9gqbXjpof/C6/Zi6KgBaodIEY5F9NPAQu7JYyFXHc1RxGVbBSIiUotGo0GfPn3UDoNaGUGjAWQ5rIB+hL/WBn18IgSRxUFFiSKMqclwl5U3OGxITADYE11xkhREm+F9cXDF+rDjhoQ4ZAzoAdnPGbZKsxdXNTrmrnFC5qxnxcUlxzU6pjXoYIgxKBgNAYAlLgY6gw5+rx+rv10TNiYIAhJTE1SKjFoKFtFPAwu5J4eFXCIiIiKKVFIwAG91ZaPj3uoKaC2x0LCQrhgBgCk9FfZdBZC8vj8NCojv0omrA1SgMxkhBYLoePk5sO05iKDHh9icdOhMBniq7YjJZJ96pRmtMY2OCaIAUcfVWkrTaEV0HdYd21durTc24JLB0PA1UZxWr8WYa87DZ3O/rDc29IKB0OlZIqVj43dIE2Ahl4iIiIiohZMkyFIQ2phYGJJSQn2dZVmGt7L88GaJEgu2SpIlCVIggLRhg1GzZRs8ZRUAAL01Dom9eiDo80Fn4mxOpblKKnFo1W8QtRrE5WZA1OlQunYbvDW1MCVZ0fGKkYDZqHaYUSUuIwkavRZBX6DeWFbvDhC1vPinNJ/bj84DuyA2MQ4bv10Pn9sLc5wZZ1w8CHqzge1cVKDRiBj2e7F8yfvfw2F3whRjxNljz8RZFw2FIPDnhI6NRXQiIiIiIop6siDAkJwGyBLqDu6HLB1ufyBoNDCltwG4WaLyBAGQgaDHi9i8tkjo3hWQZUiBAPxuD/SWGMiSpHaUUcdxsAwAIAWCsO0J78PtrrJzdYAKBBEYMuVC/PTaIkhHtW6JTU9A94sHQeYFQMW57E589sLH6HhGZ1z414shaEQEvH5s+v437Nu0F5OevVntEKOO3xfAv/7+IjJy0nDd3VfBYDQgEAhg1Te/YuaUpzBr3kNqh0gRjkV0IiIiIiKKeoIgQmMwwrFnR9hxORhEXfF+xHXoyp7oChMEAaJGg9LlPzVYmE0dOgg6I2eiK82YcIxez2bj4T48pCgpIMFVVYuRD4xH1d4S1NU4kdQuA8ZYE9w1TsSms9ez0sxxMZAlGbt+2YFdv+yoN67nag3FuRx1qCqrRlVZNXZuKoA1IQ4OuxNe9+F9DmsqbMjMTVc5SopkEZEFvvzyy2jbti2MRiMGDhyIX3/9tdFz586dC0EQwv4ZjeFvPrIs45FHHkFGRgZMJhNGjhyJ3bt3N/eXQUREUUB02yC6KvnveP/cNrVfKiI6BVGdlwuAp7Ks0eFjjVHzkGUZzgPFjc5stu/YBZmznhUX377N4Y14G5AxoAdEtthRXGXhISTlZaBk6z5U7C6Gx1mH/T9vh9/jg72kCv7fi4SkHGOMEYlZSQ2O5fVuz/7bKpBlGbFWC2584Frc8ehNGH3NSNz68ETcNn0yktOTEAxyZRMdm+o/te+//z6mTp2K1157DQMHDsTs2bMxatQo7Ny5E6mpDW9IEhcXh507d4ZuC39aWvn000/j3//+N+bNm4e8vDw8/PDDGDVqFLZt21YvsSciIjoZpsIVaodARNQsoj4vlyRIHnejw0Gvh61DlCbL8NvtjQ77nU6Ar4niJElCp8vPQcFnyxD0/dHXObFbHuLbt4Hs8QOmCPv5buUS26Th2yfeRd6ZPdB+RC9odVq4bS5s+vhHyBKQ0b2t2iFGpVFTLsRXr3wBW1lN6Fh6+wwMvnwopADfu5QWGxeDO5+Ygreefx8H9hSHjqdkJGHKQzcgNbPhix5ER6heRH/++edx8803Y9KkSQCA1157DYsXL8Ybb7yBBx54oMHPEQQB6ekNL7GQZRmzZ8/GQw89hLFjxwIA3nrrLaSlpeHTTz/F+PHjm+cLISJSEGf5npjmeJ7cecMhmeKb/H5bG9Ft4wUHohYm6vNyQYBoMCLo9TQ4rDGwTYXiRBH6+Hi4yyoAQYA+3gpBFOGz2SEHg9BZLABb7ChO8gVQvOo35I0ZCikQRNDrh8FqgeNAKaq2FyKlVye1Q4w6WqMO7c/siT0/bkbVnhLozQY4y23w1Xkx7LaLoeGsZ8XVlFTDUePAJXdfjrpaFxyVtYhPS4Ap1oQ9GwqgNxmQCBZtlaQ16PDpG1+GFdABoKKkCm8+Mx8PvHiXOoFRi6HqO6nP58O6deswbdq00DFRFDFy5EisXr260c9zOp3Izc2FJEno27cvnnjiCXTv3h0AUFhYiNLSUowcOTJ0vtVqxcCBA7F69eoGk3Wv1wuv94/lTbW1tSf1dbCYdWL4PLUufD1PXHM8VyxOqkcyxUOKSVY7DCKiJhUpeTlw+rn5KZNlGJJS4K+1NThsSEgGq+jKEgDEZGdBCvhhSkuDt6oashREXMd2CDhd0CfEQ+BrojjHgTI4i8tRUFwOjUEHUauFv84DyDK0ZiOSe3ZQO8So4yy3Ial9Jtqd2RNlOw/AXeNEh7N6IS4zCVsX/4KeYwerHWLUMcfHYOfP27HoxU+h1WthjDHC7XAjGAji7OtHwmBm2yOl1dXWYeu6+v3pAaBkfxmcdhfQRuGgCABQVlqBgl2F2PDrZmS2SceAIX2Qmp4MvV6vdmhhVC2iV1ZWIhgMIi0tLex4Wloaduxo+Bu7c+fOeOONN5Cfnw+73Y5nn30WQ4YMwdatW9GmTRuUlpaG7uPP93lk7M+efPJJzJw585S/DhazKBrx+15dnA19YjgbmojoxERKXg6cfm5+ygQRkGSYs3LhLj0IORg8fFijhTmjDSRJgsj+24qSAQQDfoh6PcpX/fLHwO69MKWnwZCSDJk1dMX5HK7Qx0GvH0HvHy1dAnWewy8cKSrgD0IQgKVPvw8pcPi9azcAS2o8+l59NoL+oLoBRiGdXocN36wDAAR8ATh9ztDYqg9/RJch3dQKLWp5PMfeG8DlqFMoEjpa8YES3HLtP1C0748VAjq9Di+/+RT6DciHTq9TMbpwLW5Nz+DBgzF48B9XUYcMGYKuXbviP//5Dx577LFTus9p06Zh6tSpodu1tbXIzs4+4c9nMevEsJjVuvD7/sQ1x/c+Z0MTEZHamiMvB04/Nz9lsgRAhr/OCXNWDgRB/P2wBL/TAX2clRPRlSbLkP0B2LfvqjfkLi2DMSUJ5qxMFQKLbpY2qShbt73BMVNyPAT+nCguLiMBS598L1RAP8JZbkPBik3oPW64SpFFL3u5DbLU8BUlb50XHmfje3BQ8zDHmKDRahAMNHxRKSHJqnBE5HK48MzjL4cV0AHA7/Pjzhun4ZOlbyGrTcNtA9WgahE9OTkZGo0GZWXhO92XlZU12lvxz3Q6Hfr06YOCggIACH1eWVkZMjIywu6zd+/eDd6HwWCAwXDqS2lYzFIPW4qcmOZ4nvh9T0RK43v+iWvq56qsrAz2Y2zud6K8Xu8xZyCrLT09/bRywiOsVmu92deRLlLycuD0c/NTJYgaeCrLYUhIghwMwldbBUCALi4eupgYeKorYLHEKR5XNBMEAa6i4kbHnfuKYMqInD+uo4U5JRH6WDN8DczabHNWP4ga9qlXmqOkutHZ5iWb9yL/sqEKR0Raw7Fnz2q0GoUioSNEjYgRFw/F0k/qT3DrOywfgsgrgEqrqbFj2Tc/NTjm8Xixe8ceFtGP0Ov16NevH5YuXYpLL70UwOGdvpcuXYo77rjjhO4jGAxi8+bNGDNmDAAgLy8P6enpWLp0aSg5r62txS+//ILbbrutOb4MUhFnthMRRQ++56ujrKwM1153Pfy+Yy+BpT/o9Aa88/ZbLaqQzrwcELVaGJJT4dq/B6LeAJ0lFgDgKS+B5PfB0rYDRA2LHkqSJQmS39foeNDnh8Bpz4rz2R1oN2YYDq3ehNqiwxdGdTEmZA7phbryGpiS49UNMAp5jtGGQpZkBP0BBaMhALAkWGCOM6Outv5rk5KbCr3ZqEJU0c1Z60LHnu2h0+vww2c/wuvxQavTYsj5A9D/rN6oqbQju32W2mFGFZ/PD0mSGh2vrqxRMJrjU72dy9SpU3HDDTegf//+GDBgAGbPng2Xy4VJkyYBAK6//npkZWXhySefBAA8+uijGDRoEDp06ACbzYZnnnkG+/fvx0033QTg8GyFu+66C48//jg6duyIvLw8PPzww8jMzAz9QUCtB1uKnBi20iGi1oDv+SeuKd/37XY7/D4v3O3OgmQ8zWWuUgCi13n881QiGSyAeHrpseixA3uXw263t6giOsC8HAB0Zgt01gT47TXwVv9x4UgfnwitKUbFyKKUKMKUkQZ3aXmDw8aUZICznhVn23MQVdsKkdq7E9L6d/v9YkcA5Rt2wnmoAkld2qodYtRJzG18pqY5Ifa4s6Kp6Xlcblx231V4/9F3EPD9cRHDFGvCxX+/DH5v4xcIqXmYzEbMfeZd9BrSA7fPuBEAIIoC1q74Df9+aA6emPeQyhFGH4PBgLT0FJSVVjQ43rlbR4UjOjbVi+hXX301Kioq8Mgjj6C0tBS9e/fG119/Hfqjo6ioCKL4R2JUU1ODm2++GaWlpUhISEC/fv2watUqdOv2x6YM9913H1wuF6ZMmQKbzYZhw4bh66+/htHIK32tDVuKEBFFD77nq6wpNlQUta3/QkgL3niSeTkg6nQwp2dBSkyBz3549pM+PgGiTg9RxyKU0gRBgC42FhqTEUG3BxBFCIIAORiEIIqIzcsBGultS81HHxuDgMeLQz9vrjemMeq5d4AKZFlCapdslO84UG+s20WDwEb1ypMCMrb/tAWTn5uCvev3oPJgBTI6ZqFNl2z88NZ3OPu6c9UOMepodVqM+ct5+Pj1Rfhl6bqwsREXD4VG5EVZpYmigJvvuA6PP/R8vbGBQ/tBPsYsdTWoXkQHgDvuuKPRZaLLli0Lu/3CCy/ghRdeOOb9CYKARx99FI8++mhThUhEREQU1biiKTpEe14e9HrgLi+FPs4KnTUBEAA5GIS7phSm1HRoDJFZ/G+t5KAM5/4DSBlw+A9pyeuDLMvQGA0QNCLsO3YjIb+H2mFGnfgO2TiwYn2DFw3T+nSBqIuIMkNU8bl96HHxYBzISMK+1dvg9/gQm5aALqP6Iy49sdF+6dR89CY99qzdjfVfrUX3s3oiISMRBWt24qtXvkCbrjkQdWwPprSAP4DkjCRcd9dV+PK971BVVo24hFicd8UIZOSkIRhhBdto4HF7sHvXXsx4+j7Mfe097Nt7AJbYGIy98gL0OSMfewuK0KN3V7XDDOFvNyIiIiI6LrbTOTFsodayBT1uaIxGOIv2/lEgFESYM7IQ9HpYRFeaIMPSJhN+pwvVv22BHPi9JYIgwNqpA2Jy2kBgwVZxUlBCh7FnYc8XKyAH/yg6xbXNRFL39pCDLNgqLSbBgm8en4/07m3R95qzIeq0cNc4seObtdAa9Bh802i1Q4w6WoMOV0wbj/cffQdbl/+xaiMhIxFjbr+Ym1iqQKfXIiUjCd988AMum3whYuMt8Lg8WLN8Izrlt4fBpPym5tEuNs6CX1auw46tu3H/jDsRn2BFwO/H4k+/w313zMTH385VO8QwzDiI6JSIHrvaIbQYfK6IqDVgOx1q7YI+LyAIcJccDB+QJdQdOgBL244I+n3Q6PTqBBiFBAAaoxFlq34Nn/Usy7Dv3I3UIQMgs52L4uRAAH6nG91vuBh1ZVXw13kRm5UKKRiAr9YJQ0Kc2iFGnarCUsiSjJLNhSjZXFhvnDPRlScIwIr3fsD5N49BwOeHvcKOxMwkBANBrP54Jc66lu1clGZJiIHH7cO4W8YiEAzAmhALp70OuZ2yodVpoOPqAMUlpybhidkPobK8CvPmvI+tm3YgOTUJl4+/EP/35r+QlJygdohhWEQnopNitVqh0xuAvcvVDqVF0ekNsFpPc0O+o7Awf2Ka43nic39i+DwRUUvkrWp4YysA8NZUwmxso2A0BEGAY19Ro3sN2LbvQvKAvgoHRVqTEboYE2p27UddeQ0EjYC6smok92iPgNcHk55lBqXJ0rH345BltqlQmsfhRsGaXShYswtmawzMVjOcVQ54XB5AEDD4imFqhxh1fG4fRFGATq9DTbEN29buRHp2GrLaZQAAgkH+nKjB5arDXVMegvR7Ox1HrRPPPf4KLrv6QvSMoFYuAIvoRHSS0tLS8M7bb8Fuj6wC2f79+zFr1iw8+OCDyM3NVTuceqxWa2hjttO9H17EODlNdQGDz/3Ja+qLR0REzUuA5PNC0GhgSEiG1hwDAPDXOeGrroLk84I7JipLliQEnK5GxwN1dUDL3cu3xQp4vRA0IhyHKhCflwWNTgtXaRVqCooQl5sBOcBClNISslMOvz018POQkJsGUcMZtkpz2g6/d7XNz0PPs3tBZ9TD43Rj4zfrcWh3Mbx1XpUjjD6CIELUiHjyby+grPiPi+bWxDhM+/ddiMviikulVZZX4fF/PhcqoB/tk/cX44YpV8MaHzmrm1hEJ6KTlpaW1iQF4eaQm5uLTp06qR1Gs+FFjJPXVBcw+NyfvKZ67ikycHXBieHz1HIJoghtrBW62Dh4KsrgqSwDAOhi42DJbQef0wGBhShFCVot9AnxcJeVNziuj4uDIIoKR0XV2wtRu78EGQN6QtRpEPQFkNAxBzUFRSj45AfkT7lc7RCjjyCg07l9seu79WGHNTotul84EIKGFwCVFpcUi4v+Nha2MhuKdx6EJTEW9rIadBveE50GdYExhntsKM3n9eO1R+eGFdABwF5di+fuewUP/t9UWGJjVIouOjlqndhfeLDR8U3rt6Fdh8j5G5dFdCKiFoYXMdTD556iEVdhnDyuwmiZRK0WxsRk1BbsgCz90T/Y76hFoM6F2PZdOJtTYYIgICY7C7W79zS4WaW1aycIrA0qTtTpUFdegz2LVgCCAFEjQvq9N72g1YAvivJ0Jj2M1hgMnHwB9v+yA55aFxJz09CmT0fU1TiRmJehdohRR282QhaArsO6Y++GPag6WIHMTm3QpmsOyovKoDdxfw2luV1u7N68p8GxikOVcNidyEBk/q3XWmm0x86rzObIutjEInoT4IyjE8PniYiIqOXhKoyTx1UYLZMUDMJTXRFWQD9CDgbhq6mCmJYJkTOfFSMHg/DX1SFt6EBUrv8t1NpF1OuRmN8dUsDPbi4qSOyci0Orfjt8Q5ZDBXQASO7e/nAhnRTld/sQn5mM3cs3IiY5Dgk5qXCUVaNk237EZybBX+eBMdakdphRRRCB+JR4vHnPHAR8AQDAxm/Xw2gx4S+PXt/YVg/UjLxu3zHHXY46hSKhI6zxcThjcB+sWb2h3phWq0G3/M4qRNU4FtFPA2dmnTxurqgOPk9ERHQ6uAqDooEcCCDgdDQ67nfWwpCUCug5e1ApsiTBuacQsiQhuX8fCKIAWZIhaDRw7N2HukOlSB8+RO0wo46g0SB9QA+U/rol7LghPhYp+R25c4AKKvccwrbFv6DDiF5IzE1DMBBEQm4qDqzdjTVL1+O8B/+idohRJ+gP4pNnFoYK6Ed4nG588eInuHLaeJUii14Wawx0ei38f3pNjkhKTVA4IrLGx+Ghx+/GxHF/Q031H3UrQRDw6LMPIDklScXo6mMR/TRwZtbJ4+aK6uHSciIiIqJjEMVj9jwXNVq2qVCYIIoQDXoY4uPhdzhRd6gEclCCKT0VptRk+O12viYqqN62F4CMjpefg5rdRQh6fYjLyYAuxoSCz5ejy9Xnqx1i1DHEmuFzebBt8S/1xgRRgMjVAYpz2Vyoq214ZnPF/nL4PMeeFU1NzxxrxqirzsWid5bUGxt83hnsU6+SvA65eO+LOVi57Bf8tPxXtMnJxGVXj0FmVjqMJoPa4YVhEf00cWaWOngB4+RxaTkRERFR4wRRgCExBQGXs8FxfWIyN7FUmCxJsHbsgJqt2+EuKQsd95RXQBcbi+Qz+rB1iAr8Hi/K1+9A+YadsLbNhKjTomzDDniqIutvs2iS0CYFGp0GQX/9dlQZ+e2g0etUiCq6+Y9TJA82Mhuamo+rtg7njzsbQ84/AxqNBi5nHUwxpsO/axLiUOdyqx1i1LImxGH4uYMxYEhf6A06GI0GmGMirwUVi+jUYvECBhFRdGFrqhPH54ro5MnBIGRJgj4+ET5bddiYPiHp8HgwCHBzUeWIIgJuT1gB/Qi/w4G60jLEtM1RIbDoltA+G+Xrd0DyB1CzuyhsLLZN2jFXdFDzcFXXYtDNY7B6zpdhPeotqfHoeckQ+N1eFaOLTtbU+FALqj8zmA3sUa8Ct9MNyWTAx68vwtrlG0PHu/bthJseuA4OW+Mt3aj5VFZU47XZc/HRe4sQ/H0T8c7dOuDZV2YiN6+NytGFYxGdiIiIIhpbeJ0atvEiOnl+ew005hhY2nYIzUjXxlgQcDnhd9ihi+PPlJIEWYazcH+j4659RbC0yVIwIgIAfVwMYtKT4CqtCjsuiAKyR/TjZq8qCPoCELUanPfgX1C+4wDqahxIbp+J2LQE7PhmHbqc10/tEKOORiui3+gBWNtAi53hfzkbWq4OUJw1MRbv/HthWAEdALav34XXHn0Tf330JnUCi2J+nx/vzfsYH7zzWdjxndsKcOt1/8C8D19GanqyStHVxyI6ERERRTS28Do1bONFdPL0iclwFe0FBAFakxkyAE9lGSDLsOS2B6uDypIByLLU+Lgk8yVRQdXOfWh34Zmo2LQbFZt2I+j1ITYnHdnD+6Km4ABS8juqHWLUsWYmYed367H3x83IzM+DKSEWWz5bBUe5DUNvuxhaAwu2SpOCMnqcnY/k7GSs/vgn2MttSM5OwZnXjIAp1hy2YoCU4fX48OsP6xsc271lLzx1HoUjooryKrzz+ocNjhUfKMWB/cUsohMRERGdDLbwah08Hg+KioqOf+IJ2L9/f9j/TSEnJwdGIzeVilaCVgdBFGBMzYCnvASBOldozJSWCQgCNHq9ihFGIVlGTHabBtu5AIA5M5090VUQl5WKzW9+jszBPdFl/CgIogCv3Ym9X/0EY3wcBIF7BygtGAhi74+bAQCHNhWGjW3+5CcMnnKhGmFFNWeNA8GAhOpDVbj0H1dAZ9TD43Rj209b0XlAF7id7L+ttDpnHWRJRkZOGs4eeyZSMpJgq6rFsi9WYv+uA7BxXwfFedweuOsa/1nYX3gA/Qb2UjCiY2MRnYiIiIgUUVRUhClTpjTpfc6aNavJ7mvOnDm8IBLFRFGExmCC3+GApW1HSL7DPYRFvR4+hx16Ay+wKE4QIOp10Mdb4bOFFzc0BgPM2VmQOZtTcYJWA2teJg799BsO/fRb6Lio16LteYMgo/HVA9Q8qgtLQx/HpiVAbzbCWWGD1+mG7WAFpAA3sVSazqjHF099gOF/ORu1lbVwVDtgTbUiNTcNn73wEa59fKLaIUYds8WMS66/ABm56fjy3W9xsPAQUjNTMOqqsyFLMuKT2LJNaUaTESazqdFCeg57ohMRERFRNMrJycGcOXPUDqNROTncoDDaaQxGGJNT4a2pgt9RCwDQxVlhSk6DhkV0xQkABFFEfNfO8NntcB0ohixJMKWnwpyRfnhc7SCjkNZkQFLXPFhzM1C5ZQ8CHi/icjOQ3K0d/G4vjMnxaocYlVI6tUHnkX3hKKuB2+5C+7PyIcsyfvtwBWT2PVKcVqeFOc6ML2Z/Ap1RD5PFiLraOgR8AXQZ0g2ilis2lGa2mGBNjMN/HpsbOlZ2sBxvPf8+xlwzEuZYs3rBRank1CRMmHQ5/vfy/HpjGVlpyM6NrH1PWEQnIiIiIkUYjUbO9KaIJvn98FSWIej1QG+NBwD4HbWQg0GYUtMhatlXWEkygIDLhap1v8GQmICYnDYQRBGeyiqUrfwZMbltYO3eVe0wo48gwJgQh4Nb9yChUw40Oh1c5VWwF5UisVMOWLFVXmK7dGgNOqyaszis13ZsegKG3HIRC7Yq0Og0OPv6kVjx7g84uOMA/B4fAKDDGZ3Q+7y+/DFRgdvlwYf//aLBsa8/+B5njz1T4YhIr9fhL5OuRE21HZ+8/yUk6fBKpg6d8vDCnMeQlp6icoThWEQnIiIiIiICEHC74K2qOPyx0/HHcZcD+lgrxFgW0RUlCKgrLgEAeKtr4K2uCRv2lFbA2rmzGpFFNUEU4TxUgTbD+gAApEAQcW0z4Swph0av54aJKhAEAWve+rbec+8orcHuZRvR6woWB5WmETVwVDvQoX8nDL1qOPxeP3QGPQ5uL4IUlKDT8/eJ0tx1HrhdDbcNkYISbFV25HSIrPYh0SA5JRH/eOivmHTrNbDV1MJsNiIhKQFJyQlqh1YPi+hERERERBT1pGAAnoqGN7AEAE9FKTTmGIgabmSpFAGAqGu80CTotIDA6ZyKk2XE5abD7/SgfMMOBDxexLdvg4SOuQgGAtDHW9SOMOrUllQj6G+47/mhjXvQc+xQhSMip90JAGjfrwPWfrkGNYeqkNYuA31G9cOOVdtgTY1XN8AopNMfuwRqMBkUioT+zGIxw2IxI6et2pEcG9f0EBERERERSTLkgL/x4WCAbSoUJgsCYnKzGx23tM0BRP5Jq7S6ihpseeNzHFy5Hql9uyJreF9IkoxN//0YhV/+BKnOp3aIUcdT62p0TJZkSI0U2Kn5aHUamOPMePvBufC5vUhrlw5baQ3m3f868nq3h6jhjg5K0+p0yGqb0eBYbLwFMRb2RKdjY8ZBRERERERRT9BooI21Njqui7VC0PDPJ0VJEoJuDyx5ufWGDEmJ0FligKCkQmDRrXbfIQCA61Aldr6/BDvmf4XiFesBAHVlVZAlviZKs2YmNTpmSrDwvUsFeqMBnz33EXx1XmxfuRVrvvgFu9fshNflwaJ/fwpRy8YQStPrtbjhH+NhtpjCjusMOkz55/XQ6fia0LHxO4SIiIiIiKKeIIowJqXAW10B/KkIKIgaGBKSIQgsRClJEEV4K6ugMRqROvgMuMsqIAeDMKamQPL7Yd+xGykD+6kdZtTRxzberkVj0B/uw0OK0uh1SOmYhYrdxfXGul5wBkQt21ApzVHjgMflaXCs6mAlfHVehSOiOqcb77y4EHc8ehMO7D2Eg3sPIS0rBe275+HzeV/hmjsuR1p2qtphUgRjEZ2IiIiIiAgARBGxuR3grigJbSyqs8TBmJIOWWRlUHEyYGmbi9LlKyFoNDAkJ0IQRFRv2gLJ60NSv95s56KChI7ZOPjj+gbbG6X26QyNgRsmKk1n1KPTuX0Rl5mE/T9vR8DrhyU1Hl3O7wdZkqFhEV1xAe+xW+gEuQGv4oLBIIoKDuLpqS8hp0MbpGYlY8NPm/Dhfz8HAPh9bHtEx8YiOhEREREREQB/rQ3u0kMwJCbBmHR4NlrA5YSzaA/MGTnQJjbeMoGankanhR9AfLcusG3bAU9ZRWjM3CYTWrMJAlsiKE4WBXS4ZDj2fPFjWOuWuNwMpPbqBInFQcWJOi20Rh18Lg/6TTgXolYDj92F0q1F6HnZ0EY3HaXmY02zQtSIiEu2oufZvWBJjIWtrAablm6EFAzCaDGqHWLUsSZaERNrhstRh6KCgygqOBga02g1SMlMVjE6agmYcUQIj8eDoqKiJrmv/fv3h/3fFHJycmA08k2eiIiIiFonKeCHt7oScjAAT0UZgLKwcW91BXRxVvaxVZAUCKB2dwEEjRapQwfCb6+FHJSgT7DCW12DyrUbkT58CKDXqx1qdAlKgKhBj8lj4SwuR6DOg9jsdIh6LQJuDzRm0/Hvg5qUHAhCkiR0v2gQavaXwVluQ2LbNKR3y4XH4YIlOV7tEKOOKIq4Ytp4uGvrsO6rX2ErsyElJxUX3Hoh9CYDdHqu2FCazqDFX/52Jf77xFv1xsbeMBoaDVds0LFFRAb48ssv45lnnkFpaSl69eqFl156CQMGDGjw3P/+97946623sGXLFgBAv3798MQTT4SdP3HiRMybNy/s80aNGoWvv/66+b6I01RUVIQpU6Y06X3OmjWrye5rzpw56NSpU5PdHxEQ+RePAF5AIiKi6MK8/Fjqt66g5ifLQN2Bg3AdOAhdrAUQBNh27gYkCRoTczQ1VO/ch6TObVGzcz98rjqIei3KNu1Aep9uqNiyB+lndFc7xKgT9AcRk2hF2fb9qLM5YLZacGDdLrQd1A0IypyJrgJRI6J8XxmWv7M0dKxoyz4UbdmHsVOvgNyGs56V5nZ5kJyeiL89fjO+eu87HPi9J/qoq85GUloSvG72qadjU72I/v7772Pq1Kl47bXXMHDgQMyePRujRo3Czp07kZpav6H/smXLcM0112DIkCEwGh4bMcAAAPbaSURBVI146qmncP7552Pr1q3IysoKnXfBBRfgzTffDN02GAyKfD2nKicnB3PmzFE7jEbl5OSoHQK1QpF+8QjgBSQiIooe0Z6XCxotDAlJqHPXNThuSEzhLHSFiVotLLnZcJeUAgD8DmfYeEx2GxbSVRCfl4XNb3yG1L5dkNQ1D4JGhLe6Frs+WgpLVgoE9qlXXM2BMhhjzQj4/Mg9owsEUURC23QcXL8bSXnp0Bq5WkNpQX8QPy5Y1uDYN//7ChOfuknZgAh+nx8vPfxfGIwGnH3JMJx3xQjUVNqxaP43qDhUhSfffljtECnCqZ4FPv/887j55psxadIkAMBrr72GxYsX44033sADDzxQ7/z58+eH3f7f//6Hjz76CEuXLsX1118fOm4wGJCent68wTcho9HIQh1FnUi/eATwAhIREUWPaM/LBUGALi4BYlUFJK8nbExjNEFriVMpsuimi7XAkJQIb1V12HGNyQRLdhZELr9XnGjQI7FrHsrX70D5+h2h4xqjHllDevM1UYHJasH6975H1wsGwFlug8/thTEuBhqdFuve+wHn3DNO7RCjTm2lvdH9Ady1dfDWeRoco+bjqfPCaXfBaXeFNhM9mq2qFjkdVAiMWgxVi+g+nw/r1q3DtGnTQsdEUcTIkSOxevXqE7qPuro6+P1+JCYmhh1ftmwZUlNTkZCQgHPOOQePP/44kpIa3gjI6/XC6/1j2UZtbe0pfDXUUkV6S5HW3E6EF4+ISGmR/p4PtO73fYpckZKXA+rm5hq9HrF5neCvtcFbUwng8Ax0fZwVoo4zOZUmyzJq9xQiNi8X5qwM1B08BDkYhCk9DYakBFRv3oaUAX2hidDVDa2VVq9Der+uSOiYg/INOxDw+GBtm4mU/I7w1bkRk5Z4/DuhJhWTfPgi35q3v4WoEaHR6+D3eAEZ6HbhQOhjmFcoTaM7drmNF5uUp9Ece5WM7jivGZGq3yGVlZUIBoNIS0sLO56WloYdO3Y08lnh7r//fmRmZmLkyJGhYxdccAEuv/xy5OXlYc+ePfjnP/+J0aNHY/Xq1Q1uFPDkk09i5syZp/fFUIsV6S1F2E6EiKjpRPp7PsD3fVJHpOTlgPq5uUavh5iUAn18AgBA1HLzN7XIkoSgqw6Ve/dBFxsLc0YaIIrwVlbBvnM3RIMBssRe9UrTx8Ug6PPDtmcn0vp1g6jVwFlWCfu+Q0ju0V7t8KKSoBUx7K9j8eu8b1BdWArJ7YWo1aD98Hy0HdwNfo8Pxliz2mFGFXOcCQazAd66+n22EzISodGzYKs0o9mItKwUlBVX1BuLiTXDmhirQlTUkrTon9p//etfWLBgAZYtWxY2Y2v8+PGhj3v27In8/Hy0b98ey5Ytw7nnnlvvfqZNm4apU6eGbtfW1iI7O7t5g6eIEektRdhOhIio6UT6ez7A931qmZoqLwciIzcXBAECi+eqEzUaGNNS4C4rh9/hgN3hCBs3JCVA1HI2p9IEQYA5JQG555wBf50HcjCI1JSO0FlMnF2rEskXxKr/LELvK4dDbzEi4A1AZzKgsqAYGz9Yjr7XnK12iFFHa9Dhkrsvx4dPvg9ZkkLHdQYdLvzbWOjZp15xphgjbp0+CU/+bTZ8Xl/ouEajwW0zJkNn4GtCx6ZqET05ORkajQZlZWVhx8vKyo7bN/HZZ5/Fv/71L3z33XfIz88/5rnt2rVDcnIyCgoKGkzWDQZDxG5wRM2PLUUoWkV6Wwu2tKDmwPd8ooZFSl4OMDencObMDNh37ILk84cPCALiu3WGqOPFDrXoYkzQxZjUDoMA2IsrUVtSjRUvfVpvTBAESOOGKx9UlNPqdCjdU4qrH5mAgjU7YSuzISU3FW175qG04BDS22eoHWLUibGYYauy4/G5D+Ln79agcEcRMtqmYfiYISguPASzhX970rGpWkTX6/Xo168fli5diksvvRQAIEkSli5dijvuuKPRz3v66acxa9YsLFmyBP379z/u4xw8eBBVVVXIyOCbFBHREZHe1oItLYiIlMO8nCKV1mxC+lnDULXhN3grD28uqou1IKlPL+gsFpWjI4oMvgZahhwhyzKkoNToODUPb50HPy74AYIoIq93O1gSLCjeeRCrP/4JGq0GXYZ0g9HMoq2S9EY9uvftgqWfrUAwEES/s3qhurwGP339My6ccD5iYmPUDpEinOrtXKZOnYobbrgB/fv3x4ABAzB79my4XC5MmjQJAHD99dcjKysLTz75JADgqaeewiOPPIJ3330Xbdu2RWlpKQDAYrHAYrHA6XRi5syZuOKKK5Ceno49e/bgvvvuQ4cOHTBq1CjVvk4iokgT6W0tWnNLC64CIKJIxLycIpEgCNDHxSJ18ABIPh8gA4JOB62RqxWIjkjKa3zFUExSHHQmtqlQmqPy8KbYsiRh7/qCsLGgPwC3w434tAQ1Qotq1qQ4jL1hNGoqbPC6fdAbdIhPtkKn56omOj7Vi+hXX301Kioq8Mgjj6C0tBS9e/fG119/HdrUqKioCKL4xw66r776Knw+H6688sqw+5k+fTpmzJgBjUaDTZs2Yd68ebDZbMjMzMT555+Pxx57jMtCiYiOwrYW6uEqACKKRMzLKZJp9Hpo9CwEEjXEFG9BZq92OPTb3npjfa4eAZOVqzaUZow9dqsj9kRXj0ajQXJ6ktphUAskyLLM7cz/pLa2FlarFXa7HXFxcWqHQ0RErUxTzkRvDpyJTtS8mGueHD5fRETH57a7ULhqK3Z9tx4+lwfxbVLQ68rhSMxNhc7EC5dKc1TX4q37X0dNaU29sdz8PFz5wHiYjlNoJyJlnGiuqfpMdCIiomjDVQBERERE1JRM1hh0GdUfbQd3gyxJ0Oi0MMaa1Q4rasUmxuHqR67Fu4/MQ+3vrV0AIDknBRffeSkL6EQtEIvoREREREREREQtnCiKMMezdUukSM5OwcRnpsBWVg1bmQ1JWcmIS7EiNjFW7dCI6BSwiE5ERERERERERNTE4pLjEJcch5zuakdCRKdLPP4pRERERERERERERETRiUV0IiIiIiIiIiIiIqJGsIhORERERERERERERNQIFtGJiIiIiIiIiIiIiBrBIjoRERERERERERERUSNYRCciIiIiIiIiIiIiaoRW7QAikSzLAIDa2lqVIyEiIiKi1uZIjnkk56RjY25ORERERM3lRHNzFtEb4HA4AADZ2dkqR0JERERErZXD4YDValU7jIjH3JyIiIiImtvxcnNB5hSYeiRJwqFDhxAbGwtBENQO56TV1tYiOzsbBw4cQFxcnNrhRBU+9+rhc68uPv/q4XOvHj736mrJz78sy3A4HMjMzIQosrvi8aiVm7fk77HWiq9J5OFrEnn4mkQeviaRia9L5FHrNTnR3Jwz0RsgiiLatGmjdhinLS4ujm8EKuFzrx4+9+ri868ePvfq4XOvrpb6/HMG+olTOzdvqd9jrRlfk8jD1yTy8DWJPHxNIhNfl8ijxmtyIrk5p74QERERERERERERETWCRXQiIiIiIiIiIiIiokawiN4KGQwGTJ8+HQaDQe1Qog6fe/XwuVcXn3/18LlXD597dfH5p+bG77HIw9ck8vA1iTx8TSIPX5PIxNcl8kT6a8KNRYmIiIiIiIiIiIiIGsGZ6EREREREREREREREjWARnYiIiIiIiIiIiIioESyiExERERERERERERE1gkV0IiIiIiIiIiIiIqJGsIjeirz66qvIz89HXFwc4uLiMHjwYHz11VdqhxV1/vWvf0EQBNx1111qhxIVZsyYAUEQwv516dJF7bCiRnFxMa699lokJSXBZDKhZ8+eWLt2rdphRYW2bdvW+94XBAF//etf1Q6t1QsGg3j44YeRl5cHk8mE9u3b47HHHgP3aleGw+HAXXfdhdzcXJhMJgwZMgRr1qxROyxqRZhTRzbm2pGBOXhkYm4eWZivRx7m8ZGppeT3WrUDoKbTpk0b/Otf/0LHjh0hyzLmzZuHsWPHYsOGDejevbva4UWFNWvW4D//+Q/y8/PVDiWqdO/eHd99913otlbLtzYl1NTUYOjQoTj77LPx1VdfISUlBbt370ZCQoLaoUWFNWvWIBgMhm5v2bIF5513HsaNG6diVNHhqaeewquvvop58+ahe/fuWLt2LSZNmgSr1Yo777xT7fBavZtuuglbtmzB22+/jczMTLzzzjsYOXIktm3bhqysLLXDo1aAOXXkYq4dWZiDRxbm5pGH+XrkYR4fmVpKfi/IvNzSqiUmJuKZZ57BjTfeqHYorZ7T6UTfvn3xyiuv4PHHH0fv3r0xe/ZstcNq9WbMmIFPP/0UGzduVDuUqPPAAw/gp59+wo8//qh2KATgrrvuwqJFi7B7924IgqB2OK3aRRddhLS0NLz++uuhY1dccQVMJhPeeecdFSNr/dxuN2JjY/HZZ5/hwgsvDB3v168fRo8ejccff1zF6Kg1Y06tPubakYU5eORhbh75mK+rj3l85GlJ+T3bubRSwWAQCxYsgMvlwuDBg9UOJyr89a9/xYUXXoiRI0eqHUrU2b17NzIzM9GuXTtMmDABRUVFaocUFT7//HP0798f48aNQ2pqKvr06YP//ve/aocVlXw+H9555x1MnjyZCbkChgwZgqVLl2LXrl0AgN9++w0rV67E6NGjVY6s9QsEAggGgzAajWHHTSYTVq5cqVJU1Joxp44czLUjD3PwyMLcPLIxX48MzOMjT0vK77neqpXZvHkzBg8eDI/HA4vFgk8++QTdunVTO6xWb8GCBVi/fn1E9mxq7QYOHIi5c+eic+fOKCkpwcyZM3HmmWdiy5YtiI2NVTu8Vm3v3r149dVXMXXqVPzzn//EmjVrcOedd0Kv1+OGG25QO7yo8umnn8Jms2HixIlqhxIVHnjgAdTW1qJLly7QaDQIBoOYNWsWJkyYoHZorV5sbCwGDx6Mxx57DF27dkVaWhree+89rF69Gh06dFA7PGpFmFNHFubakYc5eORhbh7ZmK9HBubxkacl5fds59LK+Hw+FBUVwW6348MPP8T//vc/LF++nEl/Mzpw4AD69++Pb7/9NtSfccSIEVxiqhKbzYbc3Fw8//zzXHLdzPR6Pfr3749Vq1aFjt15551Ys2YNVq9erWJk0WfUqFHQ6/X44osv1A4lKixYsAD33nsvnnnmGXTv3h0bN27EXXfdheeff55/pCpgz549mDx5MlasWAGNRoO+ffuiU6dOWLduHbZv3652eNRKMKeOHMy1Wwbm4Opjbh7ZmK9HBubxkaml5Pecid7K6PX60JWafv36Yc2aNXjxxRfxn//8R+XIWq9169ahvLwcffv2DR0LBoNYsWIF/u///g9erxcajUbFCKNLfHw8OnXqhIKCArVDafUyMjLqFRO6du2Kjz76SKWIotP+/fvx3Xff4eOPP1Y7lKhx77334oEHHsD48eMBAD179sT+/fvx5JNPMvlWQPv27bF8+XK4XC7U1tYiIyMDV199Ndq1a6d2aNSKMKeOHMy1Wwbm4Opjbh65mK9HDubxkaml5Pfsid7KSZIEr9erdhit2rnnnovNmzdj48aNoX/9+/fHhAkTsHHjRib1CnM6ndizZw8yMjLUDqXVGzp0KHbu3Bl2bNeuXcjNzVUpouj05ptvIjU1NWwTFmpedXV1EMXwFEqj0UCSJJUiik4xMTHIyMhATU0NlixZgrFjx6odErVizKnVw1y7ZWAOrj7m5pGL+XrkYB4f2SI9v+dM9FZk2rRpGD16NHJycuBwOPDuu+9i2bJlWLJkidqhtWqxsbHo0aNH2LGYmBgkJSXVO05N75577sHFF1+M3NxcHDp0CNOnT4dGo8E111yjdmit3t13340hQ4bgiSeewFVXXYVff/0Vc+bMwZw5c9QOLWpIkoQ333wTN9xwA7Ra/kpXysUXX4xZs2YhJycH3bt3x4YNG/D8889j8uTJaocWFZYsWQJZltG5c2cUFBTg3nvvRZcuXTBp0iS1Q6NWgjl1ZGGuHZmYg0ce5uaRifl6ZGEeH5laSn7Pn+BWpLy8HNdffz1KSkpgtVqRn5+PJUuW4LzzzlM7NKJmc/DgQVxzzTWoqqpCSkoKhg0bhp9//hkpKSlqh9bqnXHGGfjkk08wbdo0PProo8jLy8Ps2bO5KYuCvvvuOxQVFTHpU9hLL72Ehx9+GLfffjvKy8uRmZmJW265BY888ojaoUUFu92OadOm4eDBg0hMTMQVV1yBWbNmQafTqR0atRLMqYmOjzl45GFuHpmYr0cW5vGRqaXk99xYlIiIiIiIiIiIiIioEeyJTkRERERERERERETUCBbRiYiIiIiIiIiIiIgawSI6EREREREREREREVEjWEQnIiIiIiIiIiIiImoEi+hERERERERERERERI1gEZ2IiIiIiIiIiIiIqBEsohMRERERERERERERNYJFdCIiIiIiIiIiIiKiRrCITkRETW7GjBno3bt36PbEiRNx6aWXqhYPEREREVE0Yl5ORNQ0tGoHQERErd+LL74IWZZDt0eMGIHevXtj9uzZ6gVFRERERBRlmJcTEZ0aFtGJiKjZWa1WtUMgIiIiIop6zMuJiE4N27kQEUUZl8uF66+/HhaLBRkZGXjuuecwYsQI3HXXXQAAQRDw6aefhn1OfHw85s6dG7p9//33o1OnTjCbzWjXrh0efvhh+P3+Rh/z6GWjEydOxPLly/Hiiy9CEAQIgoDCwkJ06NABzz77bNjnbdy4EYIgoKCgoCm+dCIiIiKiiMG8nIio5WARnYgoytx7771Yvnw5PvvsM3zzzTdYtmwZ1q9ff1L3ERsbi7lz52Lbtm148cUX8d///hcvvPDCCX3uiy++iMGDB+Pmm29GSUkJSkpKkJOTg8mTJ+PNN98MO/fNN9/E8OHD0aFDh5OKj4iIiIgo0jEvJyJqOVhEJyKKIk6nE6+//jqeffZZnHvuuejZsyfmzZuHQCBwUvfz0EMPYciQIWjbti0uvvhi3HPPPfjggw9O6HOtViv0ej3MZjPS09ORnp4OjUaDiRMnYufOnfj1118BAH6/H++++y4mT5580l8nEREREVEkY15ORNSysCc6EVEU2bNnD3w+HwYOHBg6lpiYiM6dO5/U/bz//vv497//jT179sDpdCIQCCAuLu60YsvMzMSFF16IN954AwMGDMAXX3wBr9eLcePGndb9EhERERFFGublREQtC2eiExFRGEEQIMty2LGj+yquXr0aEyZMwJgxY7Bo0SJs2LABDz74IHw+32k/9k033YQFCxbA7XbjzTffxNVXXw2z2Xza90tERERE1NIwLyciihyciU5EFEXat28PnU6HX375BTk5OQCAmpoa7Nq1C2eddRYAICUlBSUlJaHP2b17N+rq6kK3V61ahdzcXDz44IOhY/v37z+pOPR6PYLBYL3jY8aMQUxMDF599VV8/fXXWLFixUndLxERERFRS8C8nIioZWERnYgoilgsFtx444249957kZSUhNTUVDz44IMQxT8WJp1zzjn4v//7PwwePBjBYBD3338/dDpdaLxjx44oKirCggULcMYZZ2Dx4sX45JNPTiqOtm3b4pdffsG+fftgsViQmJgIURRDPRinTZuGjh07YvDgwU32tRMRERERRQrm5URELQvbuRARRZlnnnkGZ555Ji6++GKMHDkSw4YNQ79+/ULjzz33HLKzs3HmmWfiL3/5C+65556wpZuXXHIJ7r77btxxxx3o3bs3Vq1ahYcffvikYrjnnnug0WjQrVs3pKSkoKioKDR24403wufzYdKkSaf/xRIRERERRSjm5URELYcg/7nBFhERRZ0RI0agd+/emD17ttqh4Mcff8S5556LAwcOIC0tTe1wiIiIiIgUw7yciCgysZ0LERFFBK/Xi4qKCsyYMQPjxo1jok5EREREpALm5URE9bGdCxERRYT33nsPubm5sNlsePrpp9UOh4iIiIgoKjEvJyKqj+1ciIiIiIiIiIiIiIgawZnoRERERERERERERESNYBGdiIiIiIiIiIiIiKgRLKITERERERERERERETWCRXQiIiIiIiIiIiIiokawiE5ERERERERERERE1AgW0YmIiIiIiIiIiIiIGsEiOhERERERERERERFRI1hEJyIiIiIiIiIiIiJqBIvoRERERERERERERESNYBGdiIiIiIiIiIiIiKgRLKITERERERERERERETWCRXQiIiIiIiIiIiIiokawiE5ERERERERERERE1AgW0YmIiIiIiIiIiIiIGsEiOhHRCRoxYgRGjBihdhhhysrKcOWVVyIpKQmCIGD27NmnfZ9t27bFxIkTT/t+GrJv3z4IgoBnn322ye5z7ty5EAQB+/bta7L7bGlmzJgBQRDCjjXn60hERETUkjCPP33M45sH83iiloNFdCJS1JFE6eh/qampOPvss/HVV1+pHV6zqKurw4wZM7Bs2bImv++7774bS5YswbRp0/D222/jggsuaPLHoNZh27ZtmDFjRlT/kUJERERNb9WqVZgxYwZsNlu9sSeeeAKffvqp4jE1FebxFAmYxxNFBq3aARBRdHr00UeRl5cHWZZRVlaGuXPnYsyYMfjiiy9w0UUXqR1ek6qrq8PMmTMBoMlnwHz//fcYO3Ys7rnnnia9X2r5du7cCVH841r5tm3bMHPmTIwYMQJt27ZVLzAiIiJqVVatWoWZM2di4sSJiI+PDxt74okncOWVV+LSSy9VJbbTxTye1MA8nigysYhORKoYPXo0+vfvH7p94403Ii0tDe+9916rK6I3p/Ly8np/rBABgMFgUDsEIiIioibn8Xig1+vDiowtEfN4agzzeKLI1LJ/6xBRqxEfHw+TyQStNvzansvlwj/+8Q9kZ2fDYDCgc+fOePbZZyHLMgDA7XajS5cu6NKlC9xud+jzqqurkZGRgSFDhiAYDDb6uEfay6xYsQK33HILkpKSEBcXh+uvvx41NTXHjbu8vDx0AcBoNKJXr16YN29eaHzfvn1ISUkBAMycOTPUwmbGjBnHvN+9e/di3LhxSExMhNlsxqBBg7B48eJ6ccuyjJdffjl0v8fy7LPPYsiQIUhKSoLJZEK/fv3w4YcfHvdrBACbzYa7774bbdu2hcFgQJs2bXD99dejsrLyhJ+LP5szZw7at28Pg8GAM844A2vWrKl3zvfff48zzzwTMTExiI+Px9ixY7F9+/YTivnPX7sgCNi/f3+9sWnTpkGv14de7927d+OKK65Aeno6jEYj2rRpg/Hjx8Nutx/3cY58TSaTCQMGDMCPP/5YrwdnY70fly1bBkEQwpYL//jjjxg3bhxycnJgMBiQnZ2Nu+++O+x7vTFH91KcO3cuxo0bBwA4++yzQ98vy5Ytww033IDk5GT4/f5693H++eejc+fOx30sIiIiihwOhwN33XVXKG9LTU3Feeedh/Xr14ed98svv2DMmDFISEhATEwM8vPz8eKLL4bGN23ahIkTJ6Jdu3YwGo1IT0/H5MmTUVVVFTpnxowZuPfeewEAeXl5oRzjSP9sl8uFefPmhY4f3ee5uLgYkydPRlpaGgwGA7p374433ngjLMYj+dGCBQvw0EMPISsrC2azGbW1tczjmcczj2ceT6QozkQnIlXY7XZUVlZClmWUl5fjpZdegtPpxLXXXhs6R5ZlXHLJJfjhhx9w4403onfv3liyZAnuvfdeFBcX44UXXoDJZMK8efMwdOhQPPjgg3j++ecBAH/9619ht9sxd+5caDSa48Zzxx13ID4+HjNmzMDOnTvx6quvYv/+/aGEqCFutxsjRoxAQUEB7rjjDuTl5WHhwoWYOHEibDYb/v73vyMlJQWvvvoqbrvtNlx22WW4/PLLAQD5+fmNxlJWVoYhQ4agrq4Od955J5KSkjBv3jxccskl+PDDD3HZZZdh+PDhePvtt3HdddfhvPPOw/XXX3/cr/HFF1/EJZdcggkTJsDn82HBggUYN24cFi1ahAsvvLDRz3M6nTjzzDOxfft2TJ48GX379kVlZSU+//xzHDx4EMnJySf0XBzt3XffhcPhwC233AJBEPD000/j8ssvx969e6HT6QAA3333HUaPHo127dphxowZcLvdeOmllzB06FCsX7/+pJYyXnXVVbjvvvvwwQcfhP7QO+KDDz7A+eefj4SEBPh8PowaNQperxd/+9vfkJ6ejuLiYixatAg2mw1Wq7XRx3j99ddxyy23YMiQIbjrrruwd+9eXHLJJUhMTER2dvYJx3q0hQsXoq6uDrfddhuSkpLw66+/4qWXXsLBgwexcOHCE76f4cOH484778S///1v/POf/0TXrl0BAF27dsV1112Ht956C0uWLAlbBVJaWorvv/8e06dPP6XYiYiISB233norPvzwQ9xxxx3o1q0bqqqqsHLlSmzfvh19+/YFAHz77be46KKLkJGRgb///e9IT0/H9u3bsWjRolDe9u2332Lv3r2YNGkS0tPTsXXrVsyZMwdbt27Fzz//DEEQcPnll2PXrl1477338MILLyA5ORkAkJKSgrfffhs33XQTBgwYgClTpgAA2rdvD+Bwvjto0CAIgoA77rgDKSkp+Oqrr3DjjTeitrYWd911V9jX9Nhjj0Gv1+Oee+6B1+uFXq8PjTGPZx7PPJ55PJEiZCIiBb355psygHr/DAaDPHfu3LBzP/30UxmA/Pjjj4cdv/LKK2VBEOSCgoLQsWnTpsmiKMorVqyQFy5cKAOQZ8+efcLx9OvXT/b5fKHjTz/9tAxA/uyzz0LHzjrrLPmss84K3Z49e7YMQH7nnXdCx3w+nzx48GDZ8v/s3Xd4VGXaBvD7TO+TTHohIfReRECKCIoFEBW7ohQL66prXddVbLiy7uravlV0cV0ra0EEGxZUJKgonYB00kjv0/uc7w+WkTEFkOSchLl/1+UleZ8zZ57MpLx5znue12QSHQ6HKIqiWFtbKwIQH3744WN6je644w4RgLh27dromNPpFPPy8sTu3buL4XA4Og5AvOWWW47pvB6PJ+bjQCAgDho0SDzzzDNjxnNzc8XZs2dHP37ooYdEAOIHH3zQ7JyRSEQUxWN/LYqKikQAYlJSktjQ0BA99sMPPxQBiB9//HF0bNiwYWJqaqpYX18fHdu2bZuoUCjEWbNmRccOv4dFRUVtfv5jxowRR4wYETO2fv16EYD4xhtviKIoilu2bBEBiEuXLm3zXL8WCATE1NRUcdiwYaLf74+OL168WAQQ83XTWr6rV68WAYirV6+Ojv36PRNFUXz88cdFQRDEkpKS6NjDDz8s/vpX+q/fx8PfF0eeXxRFMRwOi9nZ2eIVV1wRM/7000+LgiCIhYWFR/nsiYiIqDOxWq1tzg9DoZCYl5cn5ubmio2NjTGxw3M7UWx5HvL222+LAMT8/Pzo2JNPPtnqXMxoNMbMRw67/vrrxYyMDLGuri5m/MorrxStVmv0uQ/Pj3r06NEsH87jOY/nPJ7zeCIpsZ0LEcnihRdewKpVq7Bq1Sq89dZbmDRpEm644QZ88MEH0WNWrlwJpVKJ2267Leaxd999N0RRxGeffRYde+SRRzBw4EDMnj0bN998M84444xmj2vLvHnzoisnAOD3v/89VCoVVq5c2epjVq5cifT0dFx11VXRMbVajdtuuw0ulwtr1qw55uf/9XlHjRqF8ePHR8dMJhPmzZuH4uJi7Ny58zedV6/XR//d2NgIu92O008/vdmtvb+2bNkyDB06FDNmzGgWO7y653hfiyuuuAKJiYnRj08//XQAh25/BYDKykps3boVc+bMgc1mix43ZMgQnH322W2+L6254oorsGnTJhw4cCA69u6770Kr1eLCCy8EgOgKlS+++AIej+eYz71x40bU1NTgpptuilkZNWfOnDZXvRzNke+Z2+1GXV0dxo4dC1EUsWXLlt983iMpFArMnDkTH330EZxOZ3R8yZIlGDt2LPLy8trleYiIiEgaCQkJ+Omnn1BRUdFifMuWLSgqKsIdd9zRrCf3kSu3j5yH+Hw+1NXV4bTTTgOAo84f2yKKIpYtW4bp06dDFEXU1dVF/zv33HNht9ubnX/27Nkx+RyJ8/jWcR5/dJzHE9GxYhGdiGQxatQoTJ48GZMnT8bMmTPx6aefYsCAAbj11lsRCAQAACUlJcjMzITZbI557OFb2I7si6fRaPCf//wHRUVFcDqdePXVV4/aW/BIvXv3jvnYZDIhIyOjWb+7I5WUlKB3797NNjVqKb/jUVJS0mL/uhM97yeffILTTjsNOp0ONpsteovq0XoEHjhwAIMGDTpqzsfzWuTk5MR8fHgifrif4eHjW3sd6urq4Ha728zp1y677DIoFAq8++67AA79Abd06VJMmTIFFosFwKFennfddRf+/e9/Izk5Geeeey5eeOGFo75Gh/P99deRWq1Gjx49jivPI5WWlkb/ADGZTEhJScEZZ5wBAMfU2/FYzZo1C16vF8uXLwcA7NmzB5s2bcK1117bbs9BRERE0njiiSewY8cOdOvWDaNGjcIjjzwSLXACiBYijza/a2howO233460tDTo9XqkpKREi3InMg+pra1FU1MTFi9ejJSUlJj/5s6dC+BQj+4jtVUM5Dy+dZzHcx5PRO2HRXQi6hQUCgUmTZqEyspK7Nu37zed44svvgBwaKXMbz3HyWrt2rW44IILoNPpsGjRIqxcuRKrVq3C1VdfHd2kVUqt9anvyFwyMzNx+umn47333gMA/PjjjygtLcUVV1wRc9xTTz2FgoIC3H///fB6vbjtttswcOBAlJWVtUserV3c+fUGuOFwGGeffTY+/fRT3HvvvVixYgVWrVqF1157DQAQiUTaJR8AGDBgAEaMGIG33noLAPDWW29Bo9Hg8ssvb7fnICIiImlcfvnlKCwsxD//+U9kZmbiySefxMCBA2Pu4jzW87z88su46aab8MEHH+DLL7/E559/DuDE5iGHH3vNNddE70z99X/jxo2LeUxrq9DjAefxnMe3hfN4IumwiE5EnUYoFAJwaAMcAMjNzUVFRUXMrWkAsHv37mj8sIKCAjz66KOYO3cuhg8fjhtuuOG4rvD/uujucrlQWVnZ5qY3ubm52LdvX7NJ0K/zO54V8Ycft2fPnmbjLX3ex2rZsmXQ6XT44osvcN1112HKlCmYPHnyMT22Z8+e2LFjx1FzPpbX4lgdPr611yE5ORlGo/G4zgkcuhV027Zt2LNnD959910YDAZMnz692XGDBw/GAw88gPz8fKxduxbl5eV46aWXjprvr7+OgsEgioqKYsYOr9ZpamqKGf/1Kp/t27dj7969eOqpp3DvvffiwgsvxOTJk5GZmXnMn++RjvZ1OGvWLHzzzTeorKzEf//7X0ybNi3mVl0iIiLqOjIyMnDzzTdjxYoVKCoqQlJSEhYuXAjgl80925rfNTY24uuvv8af//xnLFiwADNmzMDZZ5/d4srctuYYLcVSUlJgNpsRDoejd6b++r/U1NRj/lw5j28d5/GcxxNR+2ERnYg6hWAwiC+//BIajSZ66+DUqVMRDofx/PPPxxz7zDPPQBAETJkyJfrYOXPmIDMzE8899xxee+01VFdX48477zzm51+8eDGCwWD04xdffBGhUCj6HC2ZOnUqqqqqorcVAocuBPzzn/+EyWSK3q5nMBgANJ9stXXe9evXY926ddExt9uNxYsXo3v37hgwYMAxf16HKZVKCIIQs0qiuLgYK1asOOpjL7nkEmzbti16i+CRDq84OdbX4lhlZGRg2LBheP3112Netx07duDLL7/E1KlTj+t8R34uSqUSb7/9NpYuXYrzzz8/ZhLvcDiiF3MOGzx4MBQKBfx+f6vnPfXUU5GSkoKXXnop2o4IAF577bVm7/vhP1zz8/OjY+FwGIsXL4457vAqnyNX9YiiiOeee+4YP9tYhz/P1r4Or7rqKgiCgNtvvx2FhYW45pprftPzEBERkXzC4XCzhSSpqanIzMyMzmVOOeUU5OXl4dlnn202Lzg872hpHgIAzz77bLPnbGuOYTQam40rlUpccsklWLZsWYsF3tra2lY/v5ZwHt86zuM5jyei9qOSOwEiik+fffZZdHVDTU0N/vvf/2Lfvn3485//HO1rN336dEyaNAnz589HcXExhg4dii+//BIffvgh7rjjjugk5rHHHsPWrVvx9ddfw2w2Y8iQIXjooYfwwAMP4NJLLz2miVogEMBZZ52Fyy+/HHv27MGiRYswfvx4XHDBBa0+Zt68efjXv/6FOXPmYNOmTejevTvef/99fP/993j22Wejvdz1ej0GDBiAd999F3369IHNZsOgQYNa7U/45z//GW+//TamTJmC2267DTabDa+//jqKioqwbNmyZv0Kj8W0adPw9NNP47zzzsPVV1+NmpoavPDCC+jVqxcKCgrafOw999yD999/H5dddhmuu+46jBgxAg0NDfjoo4/w0ksvYejQocf8WhyPJ598ElOmTMGYMWNw/fXXw+v14p///CesViseeeSR4z4fcOiPyEmTJuHpp5+G0+lsdgvoN998g1tvvRWXXXYZ+vTpg1AohDfffDP6x15r1Go1HnvsMfzud7/DmWeeiSuuuAJFRUV49dVXm63YGjhwIE477TTcd999aGhogM1mwzvvvNNs0t+vXz/07NkTf/zjH1FeXg6LxYJly5ZF+00er2HDhkGpVOLvf/877HY7tFotzjzzzOhKr5SUFJx33nlYunQpEhISMG3atN/0PERERCQfp9OJ7OxsXHrppRg6dChMJhO++uorbNiwAU899RSAQ20UX3zxRUyfPh3Dhg3D3LlzkZGRgd27d+Pnn3/GF198AYvFggkTJuCJJ55AMBhEVlYWvvzyy2YrcwFgxIgRAID58+fjyiuvhFqtxvTp02E0GjFixAh89dVXePrpp5GZmYm8vDyMHj0af/vb37B69WqMHj0aN954IwYMGICGhgZs3rwZX331FRoaGo75c+Y8vnWcx3MeT0TtSCQiktCrr74qAoj5T6fTicOGDRNffPFFMRKJxBzvdDrFO++8U8zMzBTVarXYu3dv8cknn4wet2nTJlGlUol/+MMfYh4XCoXEkSNHipmZmWJjY+NR81mzZo04b948MTExUTSZTOLMmTPF+vr6mGPPOOMM8YwzzogZq66uFufOnSsmJyeLGo1GHDx4sPjqq682e54ffvhBHDFihKjRaEQA4sMPP9zm63TgwAHx0ksvFRMSEkSdTieOGjVK/OSTT5odB0C85ZZb2jzXYa+88orYu3dvUavViv369RNfffVV8eGHHxZ//asgNzdXnD17dsxYfX29eOutt4pZWVmiRqMRs7OzxdmzZ4t1dXXH9VoUFRWJAMQnn3yyxc/l16/LV199JY4bN07U6/WixWIRp0+fLu7cuTPmmMPvYVFR0TG9Di+//LIIQDSbzaLX642JFRYWitddd53Ys2dPUafTiTabTZw0aZL41VdfHdO5Fy1aJObl5YlarVY89dRTxfz8/Ba/bg4cOCBOnjxZ1Gq1Ylpamnj//feLq1atEgGIq1evjh63c+dOcfLkyaLJZBKTk5PFG2+8Udy2bZsIIOa1Pdb38eWXXxZ79OghKpXKZs8liqL43nvviQDEefPmHdPnS0RERJ2L3+8X77nnHnHo0KGi2WwWjUajOHToUHHRokXNjv3uu+/Es88+O3rckCFDxH/+85/ReFlZmThjxgwxISFBtFqt4mWXXSZWVFS0OGf7y1/+ImZlZYkKhSJmXrZ7925xwoQJol6vFwHEzE2qq6vFW265RezWrZuoVqvF9PR08ayzzhIXL14cPWb16tUiAHHp0qXN8uc8nvP4I3Eez3k8UUcTRFGGnSiIiDqJ1157DXPnzsWGDRtw6qmnyp0OnYQmTpwIAPj2229lzeNYfPjhh7jooouQn5+P008/Xe50iIiIiFrFeTx1NM7jiehI7IlOREREAICXX34ZPXr0wPjx4+VOhYiIiIiIjhHn8UQdjz3RiYiI4tw777yDgoICfPrpp3juuecgCILcKRERERER0VFwHk8kHRbRiYiI4txVV10Fk8mE66+/HjfffLPc6RARERER0THgPJ5IOuyJTkRERERERERERETUCvZEJyIiIiIiIiIiIiJqBYvoREREREREREREREStYE/0FkQiEVRUVMBsNnNTBiIiIiJqV6Iowul0IjMzEwoF17QcDefmRERERNRRjnVuziJ6CyoqKtCtWze50yAiIiKik9jBgweRnZ0tdxqdHufmRERERNTRjjY3ZxG9BWazGcChF89iscicDRERERGdTBwOB7p16xadc1LbODcnIiIioo5yrHNzFtFbcPg2UYvFwok6EREREXUItiY5NpybExEREVFHO9rcnE0YiYiIiIiIiIiIiIhawSI6EREREREREREREVErulwRPT8/H9OnT0dmZiYEQcCKFSti4nPmzIEgCDH/nXfeefIkS0RERER0EuPcnIiIiIjiQZcrorvdbgwdOhQvvPBCq8ecd955qKysjP739ttvS5ghEREREVF84NyciIiIiOJBl9tYdMqUKZgyZUqbx2i1WqSnp0uUERERERFRfOLcnIiIiIjiQZdbiX4svv32W6SmpqJv3774/e9/j/r6+jaP9/v9cDgcMf8RUdcRDoexZcsWfP3119iyZQvC4bDcKREREdH/cG5OdHISRREBlwd+pxvhQFDudIiIiDpUl1uJfjTnnXceLr74YuTl5eHAgQO4//77MWXKFKxbtw5KpbLFxzz++ONYsGCBxJkSUXvIz8/HokWLUFVVFR1LT0/HzTffjAkTJsiYGREREXFuTnRyCjg9qN9ZiKpNOxH2BWDpnonsCcOhS7RA0cr3NhERUVcmiKIoyp3EbyUIApYvX46LLrqo1WMKCwvRs2dPfPXVVzjrrLNaPMbv98Pv90c/djgc6NatG+x2OywWS3unTUTtJD8/Hw8//DDGjBmDmTNnIi8vD0VFRViyZAnWrVuHBQsWsJBORESdjsPhgNVqPenmmpybE8WHgNuL/R9+C2dpVcy4oFRi0OzzYUi1yZQZERHR8TvWuflJ2c7lSD169EBycjL279/f6jFarRYWiyXmPyLq3MLhMBYtWoQxY8bgsccew8CBA2EwGDBw4EA89thjGDNmDF588UW2diEiIupEODcn6vp8DY5mBXQAEMNhlHyzASFfQIasiIiIOtZJX0QvKytDfX09MjIy5E6FiNpRQUEBqqqqMHPmTCgUsT/KFAoFZs6cicrKShQUFMiUIREREf0a5+ZEXV/jvpJWY47iCoT9LKITEdHJp8v1RHe5XDErV4qKirB161bYbDbYbDYsWLAAl1xyCdLT03HgwAH86U9/Qq9evXDuuefKmDURtbeGhgYAQF5eXovxw+OHjyMiIqL2x7k5UfxRajWtxgSVEhAECbMhIiKSRpdbib5x40YMHz4cw4cPBwDcddddGD58OB566CEolUoUFBTgggsuQJ8+fXD99ddjxIgRWLt2LbRarcyZE1F7stkO9VosKipqMX54/PBxRERE1P44NyeKP7Y+ua3GUgb3htrA728iIjr5dLmV6BMnTkRbe6F+8cUXEmZDRHIZMmQI0tPTsWTJEjz22GMxLV0ikQiWLFmCjIwMDBkyRMYsiYiITm6cmxPFH43ZiOwJp6Asf3PMuDbRgszTBkOh6nJlBiIioqPibzci6pKUSiVuvvlmPPzww3jggQcwc+ZM5OXloaioCEuWLMG6deuwYMECKJVKuVMlIiIiIjppqHQapJ3SDwk9s1GzbS9Cbi9s/XvAlJkCrcUod3pEREQdQhDbWjoSpxwOB6xWK+x2OywWi9zpEFEb8vPzsWjRIlRVVUXHMjIy8Pvf/x4TJkyQMTMiIqKWca55fPh6EXVuYiQCQdHlOsUSEREBOPa5JleiE1GXNmHCBIwbNw4FBQVoaGiAzWbDkCFDuAKdiIiIiEgCLKATEVE8YBGdiLo8pVIZ3dCMiIiIiIiIiIioPfGSMRERERERERERERFRK1hEJyIiIiIiIiIiIiJqBYvoREREREREREREREStYBGdiIiIiIiIiIiIiKgVLKITEREREREREREREbWCRXQiIiIiIiIiIiIiolawiE5ERERERERERERE1AoW0YmIiIiIiIiIiIiIWsEiOhERERERERERERFRK1hEJyIiIiIiIiIiIiJqBYvoREREREREREREREStYBGdiIiIiIiIiIiIiKgVLKITEREREREREREREbWCRXQiIiIiIiIiIiIiolao5E6AiIiIiIiIiIjoZORqdCESDkOlVsFgNcqdDhH9RiyiExERERERERERtSOP3Y2irQeQ/863aKpqREpuKibNOhtZfbKgM+nlTo+IjhPbuRAREREREREREbUTv9ePnz5ah+X/eB/1ZXUIh8KoOlCJtx9+A7t/3IVwOCx3ikR0nFhEJyIiIiIiIiIiaieeJjd+eP+7FmNf/ftzuBqcEmdERCeK7VyIiIgk5vP5UFpaKncarcrJyYFOp5M7DSIiIiKiLsle0wQxEmkx5nP74HV4YE1JkDYpIjohLKITERFJrLS0FPPmzZM7jVYtXrwYffr0kTsNIiIiIqIuSaVVR/+tVCmhNWjhc/sQCR8qrCtUSrlSI6LfiEV0IiIiieXk5GDx4sXtcq6SkhIsXLgQ8+fPR25ubrucMycnp13OQ0REREQUj8xJFqTkpGDk9NNgsBjhtrthSjShsaoRP68pgNFqlDtFIjpOLKITERFJTKfTtftK79zcXK4eJyIiIiLqBMw2My6653Ise/wdRMJhmBLNsNc0wZxkwUV/vBTGBJPcKRLRcepyG4vm5+dj+vTpyMzMhCAIWLFiRavH3nTTTRAEAc8++6xk+RERERERxQvOzYmIOgef2wdHVQMO5G9HwYrvUbmjCK7aJrnTilsehxvfvvUVzpp7DkZfOBZZ/bphwtWTMHrGWHy/dA28Lq/cKcatytJq/Pj1RrzzwgfIX7kOFSVVCAaDcqdFXUCXW4nudrsxdOhQXHfddbj44otbPW758uX48ccfkZmZKWF2RERERETxg3NzIiL5+d1eNBZV4fuXPkEkFAYA7AZgTk/E+JsvgDk1Ud4E45DX6cXwc07Fh0+9D7/HHx0328w4//YZ8Do90Jv0MmYYn0r3l+Gvtz6Dxrqm6JjBpMf9z9+FHv1zoVSyVz21rsutRJ8yZQoee+wxzJgxo9VjysvL8Yc//AFLliyBWq1u9TgiIiIiIvrtODcnIpKf3+nFD//6NFpAP8xZ1YiCD76Ht8klU2bxKxKOYOULH8UU0AHA2eDEt29+hXAw3MojqaPUVNRh0cOvxBTQAcDj8uLpPy1CTXmdPIlRl9HlVqIfTSQSwbXXXot77rkHAwcOPKbH+P1++P2//GBzOBwdlR4RUafh8/lQWloqdxqtysnJgU6nkzsNOsl09q97gF/7dHLh3JyIqOM1HaxFOBhqMVZRcACDLhwDPXtwSyrg9cPV4GwxVrm/AuEQi+hSczvcKNrT8t8BDTWNcDQ6kZGTJnFW1JWcdEX0v//971CpVLjtttuO+TGPP/44FixY0IFZERF1PqWlpZg3b57cabRq8eLF3CiT2l1n/7oH+LVPJxfOzYmIOp7X4W41JkbEZivUqeP9egX6r4UCLV/0oI4T8Lfd99zjZp96attJVUTftGkTnnvuOWzevBmCIBzz4+677z7cdddd0Y8dDge6devWESkSEXUaOTk5WLx4cbucq6SkBAsXLsT8+fORm5vbLufMyclpl/MQHamzf90D/Nqnkwfn5kRE0kjKy2g1pk80QaVhKy2pWVMTAEEARLFZTK3TQG9mP3SpmaxGaHUa+H2BZjFBEJCSZpMhK+pKTqoi+tq1a1FTUxPzx2c4HMbdd9+NZ599FsXFxS0+TqvVQqvVSpQlEVHnoNPp2n21a25uLlfQUqfGr3si6XBuTkQkDZ3ZgJTeWajdV94sNvjCcdAnmWXIKr6p1CoMmjAYO9YUNIuNvnAMVOqTqhzXJSQkWXH+tedi2csfN4udcf5YGCxGGbKiruSk+q699tprMXny5Jixc889F9deey3mzp0rU1ZERERERPGHc3MiImmYUqwYOfsc7P1mC4q//xkhfxCm1AQMvnAsbLlpUKlOqtJPl9BQ1YC8YT1gSbFiyxcb4XV6YU6yYNQFpyESjsDV6Dq0Wp0kYzQbMOmC8bAmWrD81U/RWNsEs9WE8648CxOmjYUtJUHuFKmT63I/SV0uF/bv3x/9uKioCFu3boXNZkNOTg6SkpJijler1UhPT0ffvn2lTpWIiIiI6KTGuTkRUeeRN3Ygek0YAjEiQlAICAeCEJRKudOKS4IAfPzcCuQN64mzb5gCtVYNn8uLrau2oHzPQVz3VOfeo+dklZKRjMmXnIEhpw1EKBiCSqVEUpoNGp1G7tSoC+hyRfSNGzdi0qRJ0Y8P90ucPXs2XnvtNZmyIiIiIiKKP5ybExHJz13vwI//XomG4upmsREzz0LeuIFQKBQyZBa/rMkJUGvVKNp6AEVbD8TELClW6EzsiS4XpVKJjJw0udOgLqjLFdEnTpwIsYWNGVrTWq9FIiIiIiI6MZybExHJz9PobLGADgA/f7wOqX27wczWIZIyJppw3u/Px8fPLodSrYLOqIPX5QUATLv1Atgyk45yBiLqbLpcEZ2IiIiIiIiIiA5pLKlpNeZzeBD2ByXMhgBAZ9Sh16l98LtFf4C9uhGOegcS0xJhSbbCkMANLIm6IhbRiYiIiIiIiIi6KH2iqdWYQqmAQs2+6HJwN7mxdOF/0VjZEB1L75mBi/90OfRs50LU5bApFhERERERERFRF5WQlQxVKxsjZp/SG1qzQeKMqKGyHsv+9k5MAR0Aqg5U4rMXP4G9pkmexIjoN+NKdCLq8sLhMAoKCtDQ0ACbzYYhQ4ZAyV3oiYiIiIg6lBiJQIyIUKg495aT3mbG+JsvwI+vfIZeE4dCa9KjvrAS9vI6DLpwLLRGndwpxh2Pw4P6sjooNWpM+f00WFKsqCupwZf/+RJFWw/A7/HJnSIRHScW0YmoS8vPz8eiRYtQVVUVHUtPT8fNN9+MCRMmyJgZEREREdHJKej1w9/oQPWW3Qh5fLD1y4MlNwNaC3s9y0GlVsGQbMH4my9A4Xc7UH+gAil9stHv3JEwJVvlTi8ueeweTL/jYqT3SMe2r7dg9/c7kd4zA7/7v99j97pd8HsDcqdIRMeJRXQi6rLy8/Px8MMPY8yYMXjwwQeRl5eHoqIiLFmyBA8//DAWLFjAQjoRERERUTsK+fyo2vAzKn7YFh1rOlAGjdWE/ledB12CWcbs4pO70YnK7UXY8vbq6FjljmLs/mIjJt55CRKyU2TMLj6l5KWiZn8V/n3HSxAjEQDA/o178dOKH3D1o7NgTUuQN0EiOm7siU5EXVI4HMaiRYswZswYPPbYYxg4cCAMBgMGDhyIxx57DGPGjMGLL76IcDgsd6pERERERCeNgNMdU0CPjttdqFhXgEgwJENW8S3sC2Lru982Gw+4fdjy3hq46h3SJxXnIoEwPnr2g2gB/bCgP4iPnl2OkC8oU2ZE9FtxJTpRO2FfbmkVFBSgqqoKDz74IERRxJYtW2Je+5kzZ+KWW25BQUEBhg8fLne6RERERHQCIuEwIoEAIAIKtQoKtVrulOJWw+5iQBBgzctCUr/uUKhVcFfVo7ZgL+p2HEDWuKHQqk1ypxlX6gorIEZEJPfKQu7oftAYtHBUNqDw+x2o3VuGkI+tQ6TmanDC7/G3GGusbGg1RkSdF4voRO2Afbml19BwaJfziooK/OUvf2n22l9//fUxxxERERFR1xTyeGDfewCuklKI4Qj0GelIHNgParMJgiDInV7ciUQi6D1jEpylVSj9ZgNC/gAsOenoMW08qjfukju9uBQOhjBqzrlw1TTi509+hM/hhi03DcMunYDybYUQI6LcKcadUKDtOzIivGOaqMthOxeiE3S4L3ePHj3wwgsvYOXKlXjhhRfQo0cPPPzww8jPz5c7xZOSzWYDAPz1r39t8bX/61//GnMcEREREXU9IY8XVfk/wHmgCGIoDIgivBWVqFydj5DLLXd6cSl5YE9U/FCAqo07EfL5AVGEo6QS+z74BumjBkGp0cidYtxJ65eDg5v2YufK9fDZ3YAINBRXY93LK5ExsDs0Br4nUjMlmaFQtXxnusFigEavlTgjIjpRLKITnQD25ZbPwIEDoVQqkZCQgEcffTTmtX/00UeRkJAApVKJgQMHyp0qEREREf1Gvto6hNyeZuNiKAz73n2IhNh/W2pBlxfuqrpm42JERMW6bYDIVc9SC/mDqNxe1GJsx8frIEZaDFEHUmnUGDNjXIuxCTPPhFrHCxtEXQ3buRCdgCP7cisUsdekFAoF+3J3oJ9//hnhcBiNjY148MEHMWrUKGi1Wvj9fqxfvx6NjY3R4/jaExEREXU9kXAY7rLyVuPeyhpEBoSgUPHPWik1HShrNeY8WI1wIAgVV9lKqqGkutWYu86OMDd7lVzA44ctOwnn33YRNn+2AU3VjUjJScWp549GKBhGwMue6HKpq2qA1+2F2+mBwaiH3qRDSkay3GlRF8DZBtEJONxvOy8vr8X44XH25W5/h1/TSy65BCtWrMC6deuiMaVSiUsuuQTLli3ja09ERETURQmC0OYGooJaBbAluuTaKpAr1CqAfeolpzXqWg8KgFLdclsR6jjhSBg5A3Kx9ctN6D2qLwwWA5z1TtRX1GPg6YPgc/nkTjEuVZfXYsn/LcX6bzZD/N9dM4NH9ccN981CerdUmbOjzo5FdKITcLjfdlFRUYttQ4qKimKOo/Zz+DVdtmwZxowZ02wl+rJly2KOIyIiIqKuRVAoYO6ZB/fBllejW3r1gFLLFc9SS+zVDWX5m1uMJQ/uBbWhjYIudQhrVjIUKiUioeZtRNMHdIdK2/rFKOoYBrMBHz79AaypVvQbMwAAoDPpsWNNAWpLqnHmnHNkzjD+1Nc04J0XPsBPX2+KGd++fhcWPfIKbnn0BqRlpciUHXUFLKITnYAhQ4YgPT0dS5YswWOPPRbT0iUSiWDJkiXIyMjAkCFDZMzy5HS4J7rFYsFf/vIXqI64jXf69Om47LLL4HA42BOdiIiIqAtTm4yw9O4Jx74DMePa5CQYMjMgcNWz5IJeH7JOH47ytVtixvXJCbD1yUXI54fGZJApu/gU8Pgx/IqJ2Pzfb6KrawFAn2hCn8nDEfAGoLMYZcww/vg9fpTtKkXZLuDnNdtjYoJCgfGXnyFTZvHL4/Ri3VcbWozt2bYfHpdX4oyoq2ERnegEKJVK3HzzzXj44YfxwAMPYObMmcjLy0NRURGWLFmCdevWYcGCBVAqeftcezvcE72pqQkPPfRQs9e+qakJoiiyJzoRERFRF6bUamHt2xvGnGy4S8sQCYVg7JYFtdkElY4rnuXQuO8gIsEQ+lw6GY7iCoT8AZiz0yAoFdi3YjUGz71Q7hTjTn1hJQIeHybffxXKtx6Ap8GJ1D7ZsGYlY8ObqzDy2rPlTjHuOOudrcbESAQ+N9u5SM3j8kCMtL7xcWNdE/L65kiYEXU1LKITnaAJEyZgwYIFWLRoEW655ZboeEZGBhYsWIAJEybImN3J63Cv8/vvvx+vvPJKs9f+/vvvx8KFC9kTnYiIiKiLU2o1UGo10CZY5U6FABhTbShc+R3qtu+HOTsVCrUK5d9tRcDphsZihKBUHP0k1K5s3dPgrnPg67+/C1tuGtQGLXau/AkQBJxy5SQotSz9SM1sM7caExQCdG31sacOYTAZIAhCzN0aR0pI4u8Yaht/khK1gwkTJmDcuHEoKChAQ0MDbDYbhgwZwhXoHehwr/PMzEwsWbKk2Wu/e/fumOOIiIiIiOjEmXPSodCoEAmE4CitiolljRvGVi4y0Jr0yH/uA0RCYdQdqIiJHVhTgOFXTZIps/ilNWiR1iMd1YVVzWK9R/WFWsc+9VLTG3UYMWEoNq7Z2izWo38ujGa99ElRl8JLxETtRKlUYvjw4TjrrLMwfPhwFtA72JH96AVBiHntBUFgP3oiIiIiog6gtRjR/6op0Jh/KZYLCgEZpw1GYm+2QpBD08FahIPNNxUFgIqCQgS9fokzIo/DjTNnn4OM3pkx4z2G98KwyafA52I7F6klpydh1p1XYvDoATHjPQfm4bbH5iEtK1WmzKir4Ep0IuqS2I+eiIiIiEh6gkIBY3oSBs46H0G3D5FQCGqTHmqjHko1V9fKwefwtBoTRRGRUMsFduo4XqcXHz3zAcZcPB4TrpqEgC8AjU6L8j0H8cGTS3HNX2bLnWJc0uo1mHf/LHjdPjjtLhjNBuhNeuj1bK9DR8ciOhF1WexHT0REREQkPUEQoDEboTEb5U6FACT1zGg1ZrCZodJqJMyGACAhLRFelw/fvL4KwKGLT2IkAgDQ6DXQm9n2SGrBYBC7t+zFs/f9C6IoQmfSRe8ImH33VZgw9TSYrCaZs6TOjEV0IurS2I+eiIiIiIjimVqvRWrfbqjZc7BZbMDU0VBq+LeR1FRaFYZOHo5tqzYDQLSADgDjLpvAnugyqKtswCt/XxLdWPTIljr/ff59DBszkEV0ahOL6ETU5R3uR09EREREJ6ewP4BIMABRFKFQq6HS8dZ7osNq95Sh5xlDYM1KQvEPOxH0BWBOT0S/c0eiobAStu5pMCSY5U4zrjSU12PElJGwZdrw04p18NjdsKZYMf7KibAkWeCsd8CSbJU7zbjisrvgaHTist9diBGnD0UoGIJKrcLOzXvw3+eXoa66EZndW7+rg4hFdCIiIiIiIuqURFFE0OlC/eZt8Nc3AADUZhNsw4dAa0uEgncfEkGhUuDHl1cifVB3nHLVJChUSnibXNj9+QY4qxvRa9IwuVOMOwqtAnqzHtbUBFzx0EwoFAqEQyHYax1IzLTB5/TKnWLcEQQBj712Pzblb8OC3z0Br9sHtVaNidPH46+vPwC30y13itTJsYhOREREREREnVLI40XVt98hEgxGx4JOF6rXrkPGmROgTeBKTiJb9zQAQOX2IlRuL4qJJfXIgFLD1iFSS0hOxKqXP8fen3Y3i42+cAxOu3i8DFnFt4SUBHzy5hf47J2vomNBfxCr3l8Ne30Trr3jChmzo65AIXcCREQnym6349Zbb8Vll12GW2+9FXa7Xe6UiIiIiKgdeCoqYwroUaKIpp27W44RxZlwIIT+U0c1G1frNBgwbTQi4bAMWcW3oDcQLaBb0xLQe3RfmBIP9dveuHID/G5fWw+nDuD3+LFq2bctxtav3gKf1y9tQtTldLmV6Pn5+XjyySexadMmVFZWYvny5bjoooui8UceeQTvvPMODh48CI1GgxEjRmDhwoUYPXq0fElTp+bz+VBaWip3Gq3KycmBjj0fWzVz5kyUl5dHP66trcWFF16IrKwsLFmyRMbMiIiITn6cm1NHioTD8FXXthr3NzQiEgpBoeYqW6n5vV5EvAF46+0Ie/0wpCVBqVVDx77bsqgrqoJCpcTEuy7BgTUF8NrdSOmdjaxhPbH57W8wYuZZcqcYd5pq7Oh7Wj9MmnU2XA1ONNU0YczF46E36fDhM8vhdbGdi9RcDjdCwVCr8brqBuT0ypYwI+pqulwR3e12Y+jQobjuuutw8cUXN4v36dMHzz//PHr06AGv14tnnnkG55xzDvbv34+UlBQZMqbOrrS0FPPmzZM7jVYtXrwYffr0kTuNTunIAvqoUaMwa9YsvPHGG1i/fj3Ky8sxc+ZMFtKJiIg6EOfm1JEEhQIqo6HVuEqng6DgzdVSC3h88FbWYd+H3yIS+KUgldi3O3ImncpCugys6YkIBULY8MZXSO6ZicScVDQUV6Fufzn6TxkFpbrLlX66vIT0REyYeSbefvgN2Gt/uVM6tXsaLvnzFRDDoozZxSedXttm3Gw1SZQJdVVd7ifplClTMGXKlFbjV199dczHTz/9NF555RUUFBTgrLN49ZWay8nJweLFi9vlXCUlJVi4cCHmz5+P3NzcdjlnTk5Ou5znZGO326MF9JUrV8JgOPQH1hNPPAGPx4OpU6eivLwcdrsdVit7ZRIREXUEzs2pIwmCAHOPXDgLi1uMW/v1hlLbdlGE2l/Y48PeD76BGI7EjDfuKYYx1Yb00wZByQ1fJWWwWfD1399BwOOHuy62taUx2YrBM8bJlFn8UqoUeOeR/8YU0AGgprgany36GNNuu1CmzOKX3qRH36G9sGfb/maxtOxUmCxGGbKirqTLFdGPRyAQwOLFi2G1WjF06NBWj/P7/fD7f+l95HA4pEiPOgmdTtfuK71zc3O5eryDzZ8/H8ChFeiCIODZZ59FWVkZsrOz8bvf/Q4jR47Ehg0bMH/+fDz//PMyZ0tEREScm9NvoTIYkDRiGOo3bwPEX1Zumnt2hzYlWcbM4lfjgbJmBfTDqjbthK1/d+htXMQiJXtlAwIeP/Q2E4ZfPhFqvRaNJdUo+OA7lG7Yg37nngo9C4SS8jq8aKxsgMakxbTfXwBjogkNFfX4YvGnKC4oQsAbkDvFuOP3+nHJDdPx6j/+i8qS6uh4YkoCrvvT1fCzJ7qsRFGEz+eHWq2GStU5L8SelEX0Tz75BFdeeSU8Hg8yMjKwatUqJCe3PsF6/PHHsWDBAgkzJKITVV196Jee1+uNWQG3ceNGrFixAoMGDYo5joiIiOTBuTmdCIVaDV1aCjLPOgP++gZEwmHokpOg0Gig4ip0WfibWr+wFfL4AHapkJy73o4Jd1wMtVaNA/kF8Da5kdwrC+c9Mgt7V29FONB6H2jqGB6HBxfdcymSs1Ow5fONaKhsQHqPdNzw9O+xb+MeFtFl4HF58eXS1bjz8d+jvroBFSVVSM1MRmp2Kla9vxojzhiG7n3ZCUBqoiii/GAlVn22BuvyNyIzOx1XzroI2TmZMJk718W/k7KIPmnSJGzduhV1dXV4+eWXcfnll+Onn35Campqi8ffd999uOuuu6IfOxwOdOvWTap0ieg3SEtLQ21tLbZv3w61Wo3LLrsMU6dOxcqVK7F06VLs2LEjehwRERHJh3NzOhEhnx+NBT/DU1YBpV4PQSGgcftOqM0mpI07DSqDXu4U444lJwM1W/a0GNMnJ0BQCBJnRBkDu6Py52JsW5ofHaveVYq9X2/GxDsvgUavkzG7+JTaPRUVe8vxyp0vQYwcurJUtPUANnzyE656ZBYSUhPkTTAOJSRZMeH8sZg/5zGo1CpYbRY4m1zwuL343QNzkJ7d8ryEOtaBvcWYfemtcDpc0bEP3vkEDz3+R0y9aDIMnej3/Em5C4vRaESvXr1w2mmn4ZVXXoFKpcIrr7zS6vFarRYWiyXmPyLq3B544IHov5cuXYp58+YhOzsb8+bNw9KlS1s8joiIiKTHuTmdiKDDCU9ZBQAg7PUi5PYAooigwwnXwTKIIpc9S82QmgiNueUNXzPHDoVSxzsEpCaKIgreX9tsPOjxY8u73wK8riG5cDCMT/7vw2gB/bBQIIRP/m85gv6gTJnFMVHEm8+8i2AgBK/bh6qDNXA7PRAjIl5/6h1+m8jA3uTAo/f9I6aAftjCB55BfW2DDFm17qRcif5rkUgkpq8iEXV977zzTvTfF110EVJSUpCYmIjGxkbU1tbGHHfHHXfIkCEREf2az+dDaWmp3Gm0KicnBzodV+t1NM7N6ViJkQicB4pajbsKS2DK7QYVv28l1bCnBHlTxqPixwI4S6sAAGqjHpljh8BVUQNjehLUehbSpVR3oBKiQsQpV0xCSu9sCIKAcDCMXV9sQNnGvQj62DpEao46BwKt9NhurGqEz+2TOCNyOtyoraxvMeZ1e9FQ14SM3HSJs4pvTY0ObN20o8VYOBzGzwV70C03S+KsWtfliugulwv79/+yk25RURG2bt0Km82GpKQkLFy4EBdccAEyMjJQV1eHF154AeXl5bjssstkzJqI2ltZWRkAQKPRIBAIoLa2NqZ4fnj88HFERCS/0tJSzJs3T+40WrV48WJuDH6cODenjiQCEMWWN7AEADESjtlslKQR9Phw4KM1SB3eF+mnDoAYiSASDKNm6x64ymuQdkp/uVOMO5GIiCkPz0HJT7uw+h9LEXD7kJCdgsEXjUP30f2brYamjhcOhduMR1rZnJc6TiTc9nsSDrYdp/YXibT9feD3d64LgF2uiL5x40ZMmjQp+vHhfomzZ8/GSy+9hN27d+P1119HXV0dkpKSMHLkSKxduxYDBw6UK2Ui6gDZ2dnYuHEjAoEAlEolEhMTEQ6HoVQq0djYiEAgED2OiIg6h5ycHCxevLhdzlVSUoKFCxdi/vz5yM3NbZdz5uRwM6njxbk5dSSFQgFTbg68lS1vFG/IzoJCo5E4K7L1yUX1xp2oWFfQLGbtmQ2FpsuVGbq8jP7dsPndb1G1ozg61lRWi7XPr8CYedOgTzTJl1ycSkhPhFKlbLGYbrAaYUzgeyI1i80Cs9UEp7156xC1RoWUzCQZsopvFqsJPXrnonBfSYvxIcMHSJxR27rcb7eJEye22ffugw8+kDAbIpLLrFmzsGLFCgDAhx9+CJPpl0mIy+XC+eefHz2OiIg6B51O1+4rvXNzc7l6XEacm1NH09oSoUmwItBkjxlXaDWw9MqDQqmUKbP4pdSqYc3LhL2oImZcoVYhY9QgiGGuepaa3+2LKaAfqWDZWky4fQZ0ps6zOV88UAgCxl56Ota+822z2MRrzsKhe21ISoIg4IqbZ+Dfj7/ZLHbhnKmAwK7oUktKtuGhx/+IG668A6FfXXCaed2lSEpJlCmzlnW5IjoREQC88cYb0X/PmDEDgwYNQlJSEurr67Fjx46Y49gTnYiIiKhrUul1SBk7CmGPF5FAAKIoQqnRQGnQQ21oeXNL6lg1BfuQNKAnLLmZqNuxH2F/AOacdKQM6oWDqzei5/QJcqcYd+oPVLYac9c7EOImlpKrL6+DIAiY/cQNCPmD8Hv90Bl1UOvU2PzZRqTmpiIx3SZ3mnGlqc6Owl0leOzV+Qj4A3A7PdAbddBoNdj24w5UHaxBRrc0udOMOwOH9MPbnyzGv557AwWbf0ZyahKuv/lqnDp6GCwWs9zpxWARnYi6pMO9zlNTU1FTU4MtW7bExA+Psyc6ERERUdcVCYcRcrlRt34Twr5Dm/QJKiVsQwZBkZUBJdu5SE6t06Dw07UwpNqQNKAHFGoVPFX12PP+1xAUAsDFnJLTmFrfXFcQBN6xIQOdUY/Mvtn45rVVOLjzf60qBAG9R/bB0LOGQ8m2R5LTaNUYPm4wPvjPJ9i8dlt0vP/wPrhwzlQYzbwwKwenw4UV766ELSkBc2+6CvYmBz58/3P06d8LiUkJcqcXg9+1RNQlHe6JXlNTA4vFgry8PIiiCEEQUFRUhJqamuhxRERERNQ1hT1eVH/3I3DE5mNiKIz6zdugNhmhTEmWMbv4lNi3O8q/3wZPTQM8NQ0xsZSh/aE2sm2I1Gy5aVColIi00H87fVAu1HpebJKaMdGIL/+9EpX7jmh7JIrYt34PVBoVzpp7jnzJxSmT1disgA4Au7bsRSgYwh/+cqNMmcWvYCCI/762DEteXdYstn9PEd5Y9gJS0zvP73mF3AkQEf0Wc+fOjf57yZIlmDNnDi688ELMmTMHS5YsafE4IiIiIuo6RFGEq/RgTAH9SI0/70b4f5vJk3QioRByJ48CBAGmzBRYcjOgMuhgSE1E2in9EPL65U4x7kQiIkZfdx4EhYDEnFSk9c+BPtEEQ5IFQy+ZgFAoJHeKccfv8ccW0I+w+4edCPr5nkjN7wtgw7dbWozt21EIr9cncUZUW1OPJf9pXkAHgIqyKhwsKZc4o7ZxJToRdUlffvll9N/Tp09v87jLLrtMipSIiE5a1dXVsNvtRz9QQiUlJTH/70ysVivS0thTs6uKhIKIBAIIOBoBABpLIhQaDRQqtcyZxR8xHEGgsanVeNDlghhuvvKWOlbd9v2w9sjGoLkXoHFvCYIeH9JHDoQu0Yy9y1ejz8Vnyp1i3KneWQxb93Sc88A1qNxeBHeDAz3GD0JCtxTs/nITek0YIneKccdZ52g1JkZE+FxeCbMhAHA73BAjrW/o2lDbhO59ciTMiHxeH7ye1r8XSooOYsTooRJm1DYW0YmoS6qoaPmq/m89joiIWlZdXY1rrp2FYKBzrixcuHCh3Ck0o9Zo8dabb7CQ3gVFgkG4Kw8i2PRLiwpfTRW0icnQp2dBoWYhXUqCUgF1QgK81bUtxtUmEwT2epZcQq9u8NY2Yd+yr6NjNZt3w5BmQ+6ZoyAoeMO71FJ6Z8Nd78C3Ty+D+L87Nw6sKYAxyYLxt1wAQcX3RGrmpNY3RBQUAnTG1vvYU8cwWYwQBAGi2HIh3ZaSIG1CBJ1eB71B32ohPSevc7XnZRGdiLqk9PR0AEDPnj3xf//3f3j55ZdRVlaG7Oxs3HjjjfjDH/6AwsLC6HFERPTb2O12BAN+eHucgYjOKnc6nZ7CZwcK18But7OI3gWFPK6YAvph/sY6qBMSoVHze0BKgiDA1C0Ljr37gRaKHta+vbmxqAy0ZiP2Lv2q2binugFNhWXIyT1Vhqzim0qrxk//+TxaQD/MXe9AwfLvMWLmWTJlFr+0Rj0yemWicn/zRV39xgyARq+VIav4ptZqcOrEYdiwunlLl14D86DT88KG1FJSkzBz7sX49wtLmsUystKQk5slQ1atYxG9k/D5fCgtLZU7jVbl5ORAp+MPFOo8evToAQCoqamBIAjIysqCIAjIzMyEIAiora2NOY6Iuja2Ezl+7d1SJKKzImLsPBv7ELW3SDgEX211q3FfbTVUBhMUXPksGTESgbuyCikjT0H9th2I+A/dESMolUjo3weBpiZoEhOg0rEYJaXGA2WtxmoL9iJj1CBoLUYJM6LGkhpEQmGk9s1Gn7NGQKVTwVXrwPYV36NqRzGCXj+QYJI7zbjidXhwwZ0X49PnP0LZrl9qPX1G9cXpV02E1+WGNYUXZqXkdrhxxrRxUKnUSEiyIDUzGY11TagoqcLZl0yEo8mJ9G6pcqcZV9QaNa6eeymaGh344J1PEfnfhcDefXvg6X89itT0FJkzjMUieidRWlqKefPmyZ1GqxYvXow+ffrInQZRlMNxqMec0+nE1KlTY2IvvPBCs+OIqOtiO5Hfhi1FiI5TRIQYab2/thgOtbgamjqOKIoINtmhTUhAyugREEMhiBERSq0GUCjQsHU7TN1z5U4z7gTb6F8bCfD7RA5+lxcT77oU3iYXdq78EV67G7bu6Tj91gtxcONeRELcO0BqHocbHocb586bCp/LC7/HD51JB4PFiJKdxcjoniF3inEn4A9iY/5WnHnR6fh0yZdYv3oTUrNScP7Mc7F76z70HdZb7hTjktliwux5V2DaRZPR1OiETq9Fos0Ki9Uid2rNsIjeSeTk5GDx4sXtcq6SkhIsXLgQ8+fPR25u+0wqc3K4uQJ1LjabrV2PI6LOi+1Ejh9bihAdP0GphNpsRdjXcoFQbUlg/22JKZRKWPv2Qv3mAgSaYu9GUmi1SB0zEgo1/6SVWkKPbFRv2NlizJSVCoWG74nU0gd1x96vNqNw7fboWHnjflRsK8QZt8+AzmKQMbv4lNwtBTu/+xnvPvqrNhWCgBl/vBTW1ARZ8opntpQE9B7UAwtveSo6Vl/diF2b9+Ky312IjBzOmeWwc/seXH/F7Qj96mLftddfht/dMQcWS+e5i4a/3ToJnU7X7iu9c3NzuXqcTlr9+vUDAKjVaixfvhyfffYZKioqkJmZiSlTpmDGjBkIBoPR44io62M7ESLqSIJCAa0tBf6GWojh2D/kBKUK2sQkCIIgU3bxK+T2NiugA0DE74e7rByaBF5clZrGZIAh1QZPza/2DxAEZI0b2uqmfdRxIsFQTAH9MDESwZb31mDcTefLkFV8C4fCyF/yTfOAKOLLl1di1t+ulz6pOBcKhfHOog9ajK149VOMPWekxBlRfV0DHv3zP5oV0AHgzVeW4rKZF7CITkR0oj755BMAQDAYxKOPPgqv1wuHw4H9+/djw4YNCAaD0eMuu+wyOVMlIjopKLxNcqfQJfB16toUGg0svQYg5HVHC+aiKEKlN0KpYd9tqUUiEbhKD0Kp08LcIw8aqxmiKCLsD8B5oAieskpY+/SCQq+XO9W4UrvjALInnIKm/QdR9/MBRIIhmLJSkTF6EKo37ULOWaMAA98TKdXuK281Zi+vQ9AXlDAbAgB7dROUOhUuv+dqWJKtCPqDUGvVqD1Ygw+eXAavs/W2SNQxnE1OOJtcLcaCgRDqKhuQmcs2O1Jy2F04sK+41XjBlp3o3rPzdMZgEZ2IuqSKikO7nKenp2P9+vXN4mlpaaiuro4eR0REJ0ZflC93CkQdTxQRCQXhra5AxO8DACh1ehizcyFG1BAUCpkTjC8CAJXBAHNedzTt2oOmnbsBACqjAQkD+sFXWw/w7gDJCQD2Lvsaib1zkHfeWAhKBby1TSj+ch1CXj/v2JCB8ihtjRRKvidSU2k1uOGpm/D90nzs+LYA4VAYap0GI6aMxE3P34yANyB3inHnaBuDK1Xx3bItHA5HFyNKRRQjSM9qfTNXnVEHn893ws+jVquhbIeWfCyiE1GXlJmZCQCoqqoCAPTp0wdZWVkoLy/H3r17UV1dHXMcERGdGG/eBET0CXKn0ekpvE284NCFhQN+OAv3xGyMGPZ54TiwB9Y+A6HU6mTMLv4ICgXMebmoWvMdIsFQdDzk9qBuw2akTRgLpZZ3CEjN1q87Kn/aDntxOQQBUKhVcFfVI+jyInlQT6j0fE+kltwzE4IgtNhKJ7lXJtR6jQxZxTdLigWfv/QpDmzcGx0L+gL4cfn3CIfCGHvJ6TJmF59MViNSMpJQW1nfLKY36mFLSZA+qU5AFEVUVVWhqalJ8ueORCJ48G+3I+BvXrwXBAEpaUkoKipql+dKSEhAenr6CV3oZRGdiLqks846Cy+88AIAIDU1FXv37sXevXujH9fU1ESPIyKiExfRJ7AnPZ3UxEgEvrrqmAL6L0ERvvoaGNKzuRpdYp6qmpgC+pEcew9Ak2CFUq2WOKv4JobD6Dn9DChUCjTuLUXIF0DKkN7QJVqg1GsR8vqh0rGQLqVQMIiB00/Djo/WxYyrDVr0nzIKkRb6DVPHCnj9MQX0I23+bANGTBkJc5JZ4qzim1Ih4Jo7LsfzD76MYOCX3yuCQsCsu644dJtNHDpcQE9NTYXBYJD0bqJgMIj09AxUV9QgHInExJKSE2E0GqHVndhFQFEU4fF4ojWijIzf3rKHRXQi6pKeeuqXHbUP/zBs6eOnnnoKCxculCwvIqKTlcLXfGO/4xYJQeFvuRdlZxDRmgDFiU2P2+V1IlmIkTDC7ta/PkNuF8RIhEV0CUXCYfhr61qN+xubIIZCAIvokvI1OeGra0LFj79sZNm0/yC0VhPypoyDGOHGolKr3VcOr92NcTdNx8HNe+Gze2DrnoaU3tkoWLYWo+acK3eKccde0/p8IBwKw+tiT3SpNdTa8cV73+CP/7gVW74vQFlhJVIzkzHqzFPwzYffITE5ARk56XKnKalwOBwtoCclJUn+/AIEVFfWoVv3bHhcHni9fqhUSlisZricbkQiEeh0J34XoP5/e6fU1NQgNTX1N7d2YRGdiLqk8vLWN8/5LccREVHLrFYr1BotULhG7lS6DLVGC6vVKncadLwEBRRqDcL+lntvKtQaQBGny9RkIigUUBkNrcZVeh0vashAZ7Og8JO1gCDAlJUCpVoFT00j/HYX6nYWImvcULlTjDtGmwXbluaj5MddyBicB3NaIuoLK7H7i41QqJRQalj6kZrB0vrPLgDQsu2R5PQGHXZu2oNdW/Zi6GkDkZGThsY6O568+3mEQ2FcOOs8uVOU3OEe6AZD21+vHUVQCAj4AygtKoPRaIBGp0E4FEH5wUpEIhFYrN3a7bkOf47BYJBFdCKKL0ajEcChH4RmsznaAx04tKmo0+mEx+OJHkdERL9NWloa3nrzDdjtJ77C2u/3R/ey6IzS09OhbYf+ylarFWlpae2QEUlJoVRCl5qBoMvRYlyfkg6FIr43HZOaIAgw9+gOZ2Fxi3Frvz7siS6DpgNlSB7UC7Z+3eEsrULIH0DSgB4QRREHv92E7HHD5E4x7lgybVAbtAh6/Dj4qxYiOSP7Qm3g94nUDBYDEjNsaKxsaBbLHZwHjYF96qWmN+rQ/5Q+2LV5L7b+sCMmlpGTBpM1fmsHcm0IrVKpYE20oqmhCW63B263JxpTKpXQaNvv+6Q9PkcW0YmoSxo0aBB+/vlneDweDBw4EH379oXL5YLJZILX68WGDRuixxG1l+rq6nYpJLankpKSmP93JiwknjzS0tLa7b0cPHhwu5yHqCModXro07PgrYq9k82Q2Q0KbioqC5XRgOSRp6Bu01bgiH6plt49oUu2yZdYHNNaTVCqVCj8dC0SenWDUq1GzZY9iIRC6DF1PMRf9bWljhcJizj9lgvx3aKPEHD/cjdNcq9MDJg6CkG3H3pL/BYI5RAOhXHp/Vfi3UeXwFH7y98PKbmpmHrLdIT8Le/1QB3H5/XhojlT4WxyoaywIjqenJ6EufdcDZ/HL2N28UmhUCA1LQlBf6BZAT03rxvU6s5Vtu5c2RARHSOV6pcfX4cL5kc7juhEVFdX45prZyEY6JyTq87Y+1+t0eKtN99gIZ2IugyFSgVtUio01kSEvYf61Sr1eggqNRS/8dZfOjEKlQq6lCRknnk6/I12iOEwtLZEKDQarkKXiTHVhqYDZcidPBoNu4vht7tg7ZEFY3oSXBW1MKTx4obUqneVIH1Qd5x5z+Vw1djhtbtgzUqGzqxH8cY9yBqYJ3eKcaexqhHbV2/BVY9cC1eDE03VjUjKTobebMCHTy3D2TdOkTvFuONx+fD8Q//G5TddBEuCGXVV9UhMSUAwEMLLf30D1//5WnTvK3eW8WfhwoVYvnw5fvzxJwT8Adxyy81wOB348MMPZVsh3xpWl4ioS7JYLO16HNHR2O12BAN+eHucgYiOvY6PRuGzA4VrYLfbWUQnoi5FoVQCSiWUXHneKYR8fjRs3QFPReWhorlCQNjrg9psQtr4MVAZ9HKnGHcCTg/8dhfK1m6JjjlLq6A26dFz2ukQQ1yJLrWMgd1RvrUQ25d/B0OiGfpEE+wVdRAg4Iy7LoXWyJ9nUrOmWrHru53Y9d1OJGbYkJqbijVvr4ar3gmlWgW9iT+7pGZOMMHr9uGVv70FjVYDS6IZLocbPs+huzeS03kBUC6CIECv10Gv1+GFRS9AFMVoAX3ixIkYNmwYnn32WXmTBIvoRNRFmUym6L9HjBiBQCAAh8MBi8UCjUaDTZs2NTuOqD1EdFZEjMlyp0FERBQXgg4HPBWVAICw/5e7wYJOF1wlB2Ht24ubi0pMoVGjtmBfs/Ggy4uagn3ImXiqDFnFOVHEjhXfAwA8jU54Gp3R0JZ3V2P03PjbMFFuGp0GfUb1xd71e9BY2RDTG33E1JG8sCEDtVqFMy86HV8uXY2AP4C6qvpo7NQzhkGtVcuYHR1mtXbeBWssohNRl/TDDz9E/719+3YEAoHoxxqNJua4adOmSZobEREREZ04MRKB80AxBKUSxuxM6NNTAQjwNzbBVVwKV3EJTN1zoNKzGCUle1E5BIWAxD65SOyTC4VCAW99E2q27kXjnhJknz5c7hTjTu3+SogQkT6oO3JO7QulRgVPvQOF3+1A/YFKhPxBuVOMO031jTj7xinIHpALg9UArV4Lj8ODSDiCniN6wVnvgNlmljvNuGJvcKB7nxzc+ugNSM1OgUarRigYRmVpFdRqNRqqG5CenSp3mp2K2+3G73//e3zwwQcwm8344x//iI8//ji6MlwQBCxfvhwXXXRR9DEJCQl49tlnMWfOHADAvffei+XLl6OsrAzp6emYOXMmHnroIajVLV+0mDNnDpqamrBixQrMmTMHa9aswZo1a/Dcc88BAAoLC3H22Wfjpptuwh//+Mfo47Zu3Yrhw4dj37596NWrV4e8HiyiE1GX5P/fSiSDwQCPxxMTCwQC0Ov18Hq90eOIiIiIqGsRAQhqFVLHjISzuBS16zcDoghdSjKSTx0OR2Hx/44iKQkKAb0vPguNe0tQ9Nn3iARDMGYkI3fyaNTt2C93enFJjEQw5oapqC+sxJZ3v0XQ64clw4b+U0aibn8FIPL7RGoR/6G2RkqVAqtf/wruJhcS0hIw4eozIUDgBrwyEEURSWmJaKhpxD/nL0ZtZT2sSRacP/Nc9B/eG15uLNrMPffcgzVr1uDDDz9Eamoq7r//fmzevBnDhg075nOYzWa89tpryMzMxPbt23HjjTfCbDbjT3/601Ef+9xzz2Hv3r0YNGgQHn30UQBASkoKrrvuOrz66qsxRfRXX30VEyZM6LACOgDwvjci6pKys7MBAB6PB4IgYMSIEbjxxhsxYsQICIIA7/82Azt8HBERERF1LQqFAtbePVC3aSs8Zb8UAn21daj9cQMS+vWG8og7EEkaSf174OCaTagt2IdIMAQAcFfWYd+K1Ugd1hdKLd8TqaX264YDa7dj79dbEPQeKgQ6Khuw/rUvkdQjAxq2DpFcUnYyvl+6Fqv+/TncTS4AQFN1Ez565gPs+v5nWNMTZc4w/iSlJqJodwn+9djrqK081MrFXu/Akv9bitUff4/0bikyZ9i5uFwuvPLKK/jHP/6Bs846C4MHD8brr7+OUCh0XOd54IEHMHbsWHTv3h3Tp0/HH//4R7z33nvH9Fir1QqNRgODwYD09HSkp6dDqVRizpw52LNnD9avXw8ACAaD+O9//4vrrrvuuD/P48EiOhF1SbNmzYr+22q1YtOmTXj55ZexadMmJCQktHgcEREREXUtvvomhL2+ZuOHWr0UQeQKW8n5HS54axubB0QR5d9vhRgKS59UnAt5/ajZfbDF2M+f/IgI3xPJBX1BbF21ucXYd++tgd/Z/OcadSyfL4Dlr66Mfnx440oA+GZFPgI+tj060oEDBxAIBDB69OjomM1mQ9++fY/rPO+++y7GjRuH9PR0mEwmPPDAAygtLT2h3DIzMzFt2jT85z//AQB8/PHH8Pv9uOyyy07ovEfT5Yro+fn5mD59OjIzMyEIAlasWBGNBYNB3HvvvRg8eDCMRiMyMzMxa9YsVFRUyJcwEXWIN954I/rvpqammFhjY2OLxxEREVH74tycOlIkHIa3shKaBCuSR56ClNNGImX0qUgdMxL6jDR4a+qiK6FJOk0HylqNuSpqWbCVQd2BylZjngYngr5Aq3HqGE3Vja220Ql4A/A6PS3GqOM4m1wQIyIuvv583Pvs7bj9r7/Dn565DVfdcjEMRj1qj9holI6NIAjNLmYHg79cjFi3bh1mzpyJqVOn4pNPPsGWLVswf/78mD3tfqsbbrgB77zzDrxeL1599VVcccUVMBgMJ3zetnS5nuhutxtDhw7Fddddh4svvjgm5vF4sHnzZjz44IMYOnQoGhsbcfvtt+OCCy7Axo0bZcqYiDpCWVnrk/ffchwREREdP87NqSMJggBtchJUej0atu1A5H9/dAtKJaz9ekNrSwSEo5yE2p3G1HqRQqlR8z2RgdasbzUmCAIUKqWE2RAAaA1tt9BRaVreVJE6jlanwW1/nYdVS1fjg1c+iY73HtQDty2cB4O5YwuwXU3Pnj2hVqvx008/IScnB8ChBYt79+7FGWecAeBQf/LKyl8u4u3bty9mz7offvgBubm5mD9/fnSspKTkuPLQaDQIh5tfnJ06dSqMRiNefPFFfP7558jPzz+u8/4WXa6IPmXKFEyZMqXFmNVqxapVq2LGnn/+eYwaNQqlpaXRN52Iur4jrzAmJSWhvr6+xY87+kokERFRPOPcnDqSoFDAkJ6Kiq/zY1Z0iuEwmn7ejdSxo6DSsdez1BJ756Asv+U2FSlDe0PdRpGdOkZiTiqUaiXCweaFpowheVDr2adeasYEI4wJpmg/9COl9UiH1qiVIav4ZjAb8O3iD7Htx59jxvftKMR7L63AbQt/J1NmnZPJZML111+Pe+65B0lJSUhNTcX8+fOhUPzS1OTMM8/E888/jzFjxiAcDuPee++FWv3LBaLevXujtLQU77zzDkaOHIlPP/0Uy5cvP648unfvjp9++gnFxcUwmUyw2WxQKBTR3uj33XcfevfujTFjxrTb596aDi2i/9///d8xH3vbbbd1SA52ux2CIMT0SP41v98Pv/+XXXgdDkeH5EJE7efIq4y5ubnQaDRwuVwwmUzIyMiIFtGluBpJRETUFXBuTl1NJBKBq6Ss1ZYI9j37oUmwQqVvfRUutT+/3YWcM0fi4LcbYcpKhUKthqemAWqjHta8LARdXqhsXGUrpVAgiNHXT8GPr6xE99EDoLMaUbO3DL4mFwZfOA6hAHs9Sy0cDGPqLdOx4qllSMpKgslmRlNVI7xOD86cdTYi4YjcKcadgM+PTfnbWowd2FkMr4d96n/tySefhMvlwvTp02E2m3H33XfDbrdH40899RTmzp2L008/HZmZmXjuueewadOmaPyCCy7AnXfeiVtvvRV+vx/Tpk3Dgw8+iEceeeSYc/jjH/+I2bNnY8CAAfB6vSgqKkL37t0BANdffz3++te/Yu7cue31KbepQ4vozzzzzDEdJwhCh0zUfT4f7r33Xlx11VWwWCytHvf4449jwYIF7f78RCSNzZt/WQnjdDpjbiciIiKiQzg3p65GDIURdDhbjQddLogt3OJNHcteWA6dzYIBs85Hw+5ihLx+pA7rA43JgL3Lv0H/q86TO8W4U7u3HGkDc3H2fVejbMsBeOod6Dl+EGx56Ti4aR8yBnaXO8W401TThH3r92DOEzegaOsB1B2sRe+RfZHdLxtfvfolJlw1CUlZcmcZX9xOT5ubUTfWNSGvL++SO5LJZMKbb76JN998Mzr26aefRv+dmZmJL774IuYxv96z7oknnsATTzwRM3bHHXdE//3II4/EFNVfe+21mGP79OmDdevWtZhfeXk51Go1Zs2adQyfzYnr0CJ6UVFRR56+TcFgEJdffjlEUcSLL77Y5rH33Xcf7rrrrujHDocD3bp16+gUiYiI6DgovE1yp9Bl8LWilnBuTl2NoFJCbbXAW13TYlxtNkFQstez1Ky9suGprMfPr30cHavdthf6lET0mDoeApuiSy5raA80lFTjp1c+jxYJi374GYZEMybcNgPQ8D2RWkJ6AnqO6I1X/7gYocChDZC3rtoMnUmPi+6+BAYL2x5JzWA2QFAIECMtF9ITk60SZ0S/ld/vR21tLR555BFcdtllSEtLk+R5ZemJfviHuiB0zA/yw5P0kpISfPPNN22udAEArVYLrZb9qIi6kmuuuQZvvfUWACAhISHmaueRH19zzTUyZEdEHUFfxPZMRB2Bc3PqrBQKBUy53eDcXwgx0rz1QUK/vmzlIgONUY+9a5v3RPfWNqJp30FkjB0sQ1bxLRKOYP1rXzZbZetpdGLrsnyMuPosmTKLX0qVCp8t+jhaQD/M5/Li69e+xOUPXC1TZvFLb9Bj9Fkj8OOq5pub9xnSEwYjf590FW+//Tauv/56DBs2DG+88YZkzytpEf2NN97Ak08+iX379gE4tCT/nnvuwbXXXttuz3F4kr5v3z6sXr0aSUlJ7XZuIuo8jtyorKmpCQqFAjNmzMDy5ctjCuqrVq3CDTfcIEOGRNTevHkTENEnyJ1Gl6DwNvGiAx0V5+bUFaj0OqSOG426jVsQ9h7qVyuoVLANHgC1xSxzdvGpcd/BVmO12/ch7dT+EmZDANBQXI1IqOXWRlU/FyPkC0icEbkanPA4PC3Gaktq4HOx/7bUHA4Hrrr5Yuj0WpitJqRmpqCxrgmVpdW44vcz4LK7kZYtd5ad37fffit3CpgzZw7mzJkj+fNKVkR/+umn8eCDD+LWW2/FuHHjAADfffcdbrrpJtTV1eHOO+88pvO4XC7s378/+nFRURG2bt0Km82GjIwMXHrppdi8eTM++eQThMNhVFVVAQBsNhs0Gu5ITXSycLvdMR9HIhEsW7bsqMcRUdcV0ScgYkyWOw2ikwLn5tRVKNRqqIxGJI8cATEUhBgRodSooTToodLr5E4vLoV9/lZjkWCI7VxkEGhrQ0QRiHDvAMkFvW1fuAgHQ23Gqf0FvSHs2rMfZ0wbh/df/gj5n65DamYyZlx/PmrKayGi9X7pRICERfR//vOfePHFF2OavV9wwQUYOHAgHnnkkWOeqG/cuBGTJk2Kfny4X+Ls2bPxyCOP4KOPPgIADBs2LOZxq1evxsSJE0/skyCiTsNoNMLlcgEAhg4dim3bftll+8iPjUajLPkRERF1ZpybU1cRdLlR8+MGBO2OmHGFRoOMieOhNptkyix+WXtmo2rjzhZj5m5pgJJFdKkl98xsNWZMtkKl5UVLqSVkJLbaf1tr0MKQwL9TpZackYSqg9VY8LtfNrm0NzjwxJ3/hyt+PwPjp5wmY3bUFUhWRK+srMTYsWObjY8dOxaVlZXHfJ6JEye2uZtuWzEiOnlcffXVeOaZZwCg2c+Qw6vcDh9HREREsTg3p67C39DYrIAOAJFAAPZ9B5A4eACUarUMmcUvjVEPY3oS3FX1MeOCQkDmmKFAB+2vQK1TGzTIGJyHyu3NN5AeesnpUOn4PSI1hUKJ4eeMwObPm/ffHnvZBCgUChmyim8Bnx9vPPNui7Fl//4Yo88aIXFG1NVIVkTv1asX3nvvPdx///0x4++++y569+4tVRpE1In4fD6Ulpb+psceOemoqalBenp6dAX6kUV0hUKBvXv3/uYcc3JyoNPxVmEiIjq5cG7etnAwAPF/7Q8USiUUaq7ilEM4FIK7rLzVuLeyCtY+PVlEl1jtz4XIOn04HCVVqN22F2F/AOacdGSeNgRVG35G7uTRcqcYd6p2HsSgC8bC1j0d+7/dBr/Tg8ScVAy+cBycNY3w2T3QW7jyWUqNlfVI6Z6Gyx+8GoKgQCgQhEqjgkKlRPG2QrgaXUhIS5Q7zbjibHLB7fRg3LmjMfqsERBFEUqlEpu/K0D+pz+gvqoBWd0z5E6TOjHJiugLFizAFVdcgfz8/Gjfxe+//x5ff/013nvvPanSIKJOpLS0FPPmzWuXc1VVVcUUzw976qmnTui8ixcvRp8+fU7oHERERJ0N5+YtEyMRhLxuuA8WIxI41PdZodXCmJ0Hld4AgSsHJSUIQpuvuaBUctWzDFQ6DQRBACAid/JoKFRKeOvt8Nud0CUngC3RpadUKbBq4RL0mjQM42+eDoVKBb/DjR0fr0NDcRXOefAauVOMOyq1CmabGT/nb8eu735GJByBSqPCsLNPQUavTCiU/H0iNaVKid8/NBf7thfinw++jKA/CKVSidMmn4rbF86DSiNZiZS6KMm+Qi655BL89NNPeOaZZ7BixQoAQP/+/bF+/XoMHz5cqjSIqBPJycnB4sWLf/PjN2/ejH/961/o378/ysrK4HA4YLFYkJ2djV27duF3v/sdTjnllBPOkYiI6GTDuXnLwgE/nIV7gSPa0ET8fjgL98DaewCUOr2M2cUfhVIJU/dceMpbbjFkzOkGpZ7vidRsfXKw6+3PEXR5m8V6Tj8DSm74KrnkHpkQFAL2r96K/au3xsRSemdBo+fdNFKzpFjx/ftrUbjll823Q4EQNn66Hqecdypyh+TJmF18siRasHtrPr5ZkR8dC4fD+P6Ln+B2unHdn3ixidom6WWWESNG4K233pLyKYmoE9PpdCe0yrtPnz7IzMzEokWL4HAc6pXpcDjQ2NiIBQsWYMKECe2VKhER0UmHc/NYYiQCX211TAH9l6AIX30tDBnZXI0uoUgkAqVOC0NWJjzlFTExtdUCY3YmIoEAFGy9JylPTUOLBXQAqPhhK4wZyYBeK3FW8S0UCGLwheNQsPw7WLOSoE80o7GkBmIkgv7njUIkFJE7xbgT9AeiBXS9xQCj1QhngxN+tw9bv9qC0Rc135eEOlbAF8CaT75vMbb1hx3we/0SZ0RdjaRF9Egkgv3796OmpgaRSOwPcRa7iOi3mDBhAsaNG4eVK1fiqaeewt13342pU6dCqVTKnRoREVGnxrl5LDEcRtjjajUe8rggRiIsoktIDIfRtGMXrAP6wpyXC2dRMcRwBMacLGisFtSs34S0006VO8244yht3kLxMG+9veULUdShaveXw5BkxnmPzIK9vA6eRhf6nXMq9AkmbHrnGwy9aLzcKcadpho7bJlJOOPqSQiFwnDU2pGYYUMoEMLqN76Cx+FBUpbcWcYXl8ONcCjcaryupgE5vbMlzIhOxIsvvogXX3wRxcXFAICBAwfioYcewpQpUzrsOSUrov/444+4+uqrUVJSAvFXv1QFQUA43PoXMhFRW5RKJfr27QsA6Nu3LwvoRERER8G5eQsUCig0GoT9vpbDGi2gYLNnKQlKJfTZGfDX1sG+vxD6lBQoVCo07dwDrS0RCb17QlBw3ic1nc3aakxl0LEnugxS+mQh5A3iq7+9g5AvEB1PzE3DaddPgRjmSnSpWVIsOGfeVHz87HK4m365QJuYYcMFd14MnYl30EhNb2j7NbckmCXK5OQUCYUghoIQw2EISiUElRoKVceVnbOzs/G3v/0NvXv3hiiKeP3113HhhRdiy5YtGDhwYIc8p2TLKG666Saceuqp2LFjBxoaGtDY2Bj9r6GhQao0iIiIiIjiHufmzSmUSuhSM1qN61PSoGDBVlIKhQJaixWNO3Yh4vPDfbAMrpKDCLnccJeWASKgMrAnutQSemQd2tS1BemnDoDaxPdEaiqNBt8v+iimgA4AjSXV+PmTdVAb2BNdahqtBp8t+jimgA4AjZUN+O7db6FSq2XKLH7pjFoMPLVfi7Gs7hkwWgwSZ3TyCAcCcJUegH3vz3Ac2A373p/hKi1EOBA4+oN/o+nTp2Pq1Kno3bs3+vTpg4ULF8JkMuHHH3/ssOeUbCX6vn378P7776NXr15SPSUREREREbWAc/OWKbV6GDK6wd9QB5Xp0Iq0oNsBnS0VCi1XDUotHA7DWVQMANAm2WDqkQtBUMBbWQX3wXLY9x+ANtkGtckob6JxxlVZh57TxqPo8x8QDgSj47Z+edBaTQi6vFDZWLSVkr2sDkFfy8Wqsk37MGDKaOhbv4GAOoDH7oa9pqnF2MGdpQiw/7bk/L4A5v7pavzzgZdRsvdgdDwtKwW3//V3CPiCbTyaWhMJheAuK0LI5YwZD7kccJcVw5TTo0NXpAOH5gtLly6F2+3GmDFjOux5JCuijx49Gvv37+dEnYiIiIhIZpybt0yhUkFtTQCUSgQa6wEA+pQMqIwmKJSSbidF+F+fen8A6RPHI+TxwlVcAjEcgSErA5Y+vVC/dXuzdkTU8VzlNfBUNyBv6jhEQmGE/UForSY4D1bhwCdrMeSGGXKnGHc8Tc5WY5FwBOFQSMJsCAA8zpY33z2stYse1HE8Li92b9mLO//2e9gbHKgur0Vyug2JyVYU7S6F0WxALnuiHzcxFGxWQD8s5HJADAWBDiqib9++HWPGjIHP54PJZMLy5csxYMCADnkuoIOL6AUFBdF//+EPf8Ddd9+NqqoqDB48GOpf3boyZMiQjkyFiIiIiCiucW5+dOFAAK6SAwh7PdGxkNsJpd4IU/eeUKq5ulZKKo0GiQP7oWH7z/BV10bH/fUNUJmMSB0zqsNXt1Fz1u5ZqNmyB/tXfAul9lDP26DHB4giDKmJEJRsii41W25aqzGdxQCVhq1DpJaQmtBqTKVRQce2R5JLSktEbu9uuPuyB6HWqpGalYy6qgZ4XV7c/Mh1yOzeeks3ap14lH10xEjH7bPTt29fbN26FXa7He+//z5mz56NNWvWdFghvUNnHMOGDYMgCDGrA6677rrovw/H4nbzIiIiIiIiiXBufnRBpz2mgH5Y2OtGyOWEMjFJhqziW8jtiSmgR8ddbrhKD8Lah3dTSE2XZIXWaoLf7kLYH0TY/0sLhKxxwyCwYCs5ncWIxNw0NJZUN4sNmHYaVDpeAJSaWqdGv7H9sfuHXc1ip04bDY1BK0NW8S3oD2HxwtcRDocR9oRRuq8sGnvl70vw+JsPyphd19XaHhnReAfuJ6PRaKJ3VY4YMQIbNmzAc889h3/9618d8nwdWkQvKirqyNMTEREREdEx4ty8bZFQEP6G5sXaw/z1tVBbrGzrIqFIIABXSWmrcffBcphzc6DUsEAopYZdReh+3ljobBaIoQhEMQKFUoFQMISajbugT0kEuOGrpOoKKzBq9jnY9fl6lG3ah0g4Ap3FgAHTToM+wQS/ywu9lXsHSKmxpgGnXzkJJpsFW1dtRsgfhM6ow6gLx6DHsJ5w1TtgSbLInWZccTvcqK9uRO9BPTDxgvEwWY3wefxYu3IddmzYhYaaRmTmpsudZpcjqNRQmSwIuRzNYiqTBYJKugurkUgEfn/H7TfQoTPA3Nzcjjw9EREREREdI87NT5QIsP225NpseS6KEPmmSE6bZIXWakb5d1tRv7MIYjgMQ5oNOZNGIn30IH6fyCASDMFZ04S8sQPR9+wRiITCEBQKhIJBlG3Yix6nD5Y7xbgjhkS8ctdiTLrmTMz++/XR92TPj7vw2p/+jbn/uFHuFOOOKIq46paLoVAqsezfH6OhphHmBBPOvmQixp07CpEIf3j9FgqVCsbs7nCXFccU0lUmC4zZ3Tus7dp9992HKVOmICcnB06nE//973/x7bff4osvvuiQ5wMk3FgUAA4cOIBnn30Wu3Ydup1lwIABuP3229GzZ08p0yAiIiIiinucm8cSlCpoE5PgaaGdCwBoEpPZf1tiCo0GppxseCurWowbsjKg1LAlgtRM6UnY98HX8NY1Rcc81Q3Y/c4X6H/VedCmJcqXXJxK6dMNm5Z8jdq9Zc1ip14zGRr235acNTUBCgXw9WtfNouZbGb2RJeBNckKn9eP5f/5NDrmbHLhg1c+wYRpY3HJiH4yZte1KTUamHJ6QAwFIUbCEBRKCCp1h86bampqMGvWLFRWVsJqtWLIkCH44osvcPbZZ3fYcyo67My/8sUXX2DAgAFYv349hgwZgiFDhuCnn37CwIEDsWrVKqnSICIiIiKKe5ybNycIAtSWRCi0zYuySq0OGrNVhqxIbTFDa2telFXqdTDndYcYjsiQVXzz1tljCuhHFklKv90I0Rds4VHUkYIef4sFdADY+elPCAdDEmdEKrUKZ87+pZintxoAAIJCwHk3TWNPdBmEQ2Gs/G/Lc5y1n61DKMTvkxOhUKmg1OmhMpig1Ok7fOHBK6+8guLiYvj9ftTU1OCrr77q0AI6IOFK9D//+c+488478be//a3Z+L333tvhnygR0cmiuroadrtd7jRilJSUxPy/M7FarUhLS2u38ym8Te12rpMZXyeizo1z85YpNRqY8/oiYG9EoLEOAKC1JR8qrrPvtuRCfj8ad+2Bbdhg+Bsa4SouPdQ6JDMDxm5ZaNj+M2yDBwLQyZ1qXLEXl8PaKxvZ44YjEgohEgxBbTLAXVGLos9/4IUNGdQXVrYa8zQ6EfIFJMyGAKC2tAY5g7rj5sW3w+/2w+Nww5RohkanQW1ZDexVjTAnmuVOM644mpzwt/K9IEZE1FXWIzsvU+KsqCuRrIi+a9cuvPfee83Gr7vuOjz77LNSpUFE1KVVV1fjmmtnIRjouM0yTsTChQvlTqEZtUaLt958o90K6fqi/HY5DxGRnDg3b51So4EuORXaRBuAQ21eBEGQOav4JCgUUCiUqPwmH4asTFgH9IUgCPDW1KHiq2+hNpsgKPjeSM2SkwG1QYe973+FoNt7aFAQkHZKPwy4Zhr47SI9ncXQakxQCFColBJmQwBgTUmAQqXEsr+9i+rCX1pSdR+Sh6m3XohAsHP+PXcy02rbvhhuYIsdOgrJiugpKSnYunUrevfuHTO+detWpKamSpUGEVGXZrfbEQz44e1xBiI63lZ+NAqfHShcA7vd3m5FdG/eBET0Ce1yrpOZwtvECw5EnRjn5m0TBAGCSi13GnFPqVbD3CMX7tKD8JRXwFNeERM39+oBtckkU3bxy5CSgB2vfYzIkS1CRBHVm3ZBl2hB0uD43FdBTgndUqBUq1ps25I5tAfUbB0iOZVWhWWPv4vqotg9HYoLirDqlc9w3rypMmUWv/QmPbr3zUHxntJmscSUBN4ZQEclWRH9xhtvxLx581BYWIixY8cCAL7//nv8/e9/x1133SVVGkREJ4WIzoqIMVnuNOJSRJ/A156IujzOzakriEQiCHm8sPbpBWdxKcw9u0MQFHAdLIfaaIBSq0XI44XKwNWDUrIXV8YW0I9Q+dN2WHtkQd3C3gLUcXxOD069djI2vLEKkVA4Om5OS0TP04ccaufC9TeS8jm90QJ6Vt9uMNlMaKpqRHVRFfat34tJ106WOcP4EwqGcNUtF+PFBa+iqf6X9qh6ox433nctgn7u50Btk6yI/uCDD8JsNuOpp57CfffdBwDIzMzEI488gttuu02qNIiIiIiI4h7n5tQViOEw3CUHkTC4P/SZ6XCVHIQYicA2eABUJiNqf9yA1DEj5U4z7njrGluNBZweQJQwGQIANJbWoLKgEGPnTYOjsgE+hxsJ2SkAgJ/+8zkm3DZD5gzjj6vJjdxB3THmkvEo23UQTdWNGDB+EM645ix8++ZX8HvYzkVqLrsbr/z9Lcz541VwO90oL65CamYyktJsePelFbjylouR0ytb7jSpE5OsiC4IAu68807ceeedcDqdAACzmbdKEBERERFJjXNz6goEpRKJQwbCsb8QrqJfNi93lxyENsmG1DEjISgl+5OW/seYngxgT4sxbYIZUEibDwEJWcnYtjQfNXvKYMmwQW3QomT9HvidHqj1Wig1bE8ltcT0BJwydSSWLnwb4SPuDtAadbjo7kthaKOPPXUMg0mP2sp6PHvfS0hKS0RyehI2rdmK6vJaAIAtOUHeBKnTk+zXW1FREfbt2wfg0AT98CR93759KC4ulioNIiIiIqK4x7k5dQUKhQJhnz+mgH6Yv74BnvIqQM0iutTM2WlQ6Vpu15I1bijUBhYHpWZINMOYfKhfi6OyAfUHKuF3egAAvSYOhVrPIrrUFEolPn/xk5gCOgD43T58/eoX3OxVBnqTDmPPHgUAqK9uxJ5t+6MF9P7D+0BvZGswaptkRfQ5c+bghx9+aDb+008/Yc6cOVKlQUREREQU9zg3p64gEgrBVVQMANClpsA2bDCShg+BsVsWoFDAWVyCiNcnb5JxyFXbiH5Xngt90i9NthVqFbLPGAFDSiKCbo+M2cWnprJajLj6TNi6p0fHFColep0xBIZEEwJutg6RmqvRCa/T22Ks7mAtfK3EqOM4Gpy4/KYLMfacURAUQnR86NhB+N1Dc+BocsiYHXUFkl2237JlC8aNG9ds/LTTTsOtt94qVRpERERERHGPc3PqCiJhESJEpI4ZBV9dPex79kEMR6BPT0Xa2FFo3NlySxHqWJ6KGphSE9HzwokQQ2FEQmGo9Foo1EpUrNuOjNGD5E4x7vjsbgT9QQy+cOyhDXn9QWgMWqi0auz6fANseelHPwm1q6Cv7U0qw61szksdJxQM4c/X/gV/evoPmHHdNHhcXuiNOgT8QSy85WnccN81cqdInZykPdEP91s8kt1uRzgcbuERRERERETUETg3p65ApVXD2rsX6jZtRdDxy9eru7QM3spqpI4bDQV7PUsudWhfFH3+A5ylVTHjgkqJATOnQKFmU3SppfXPxc6VP6F0Q+yFJUEQcNoNU6AxsU2F1BLSEiEoFBAjkWYxnVEHPXuiS86cYAJEYMG8J5rFlEolUjKSZciKuhLJfrtNmDABjz/+eMykPBwO4/HHH8f48eOlSoOIiIiIKO5xbk5dRdDtjimgHxYJBuEqPQhAaP4g6lABp7tZAR0AxFAYB9dshijyPZFaOBRuVkAHAFEUsePjdRDDzQu51LFUWhVGXXBai7GJ154FjV4jcUakUqtx8fXTWoydc9kkqNinvsv629/+BkEQcMcdd3To80i2Ev3vf/87JkyYgL59++L0008HAKxduxYOhwPffPPNMZ8nPz8fTz75JDZt2oTKykosX74cF110UTT+wQcf4KWXXsKmTZvQ0NCALVu2YNiwYe382RARERERdV2cm7ct7PdB/N8FBkGphFKrkzmj+BTyB+EuLYfKYIClVx5URgNEUYQYDMFRWAxvRRUsvXoCWhajpNS4r7TVmKO4AmKId7NIrW5/GSwZSRg562woNSqE/UGo9BrYy+vw478/Q9AbkDvFuFNXWothZ5+C1O5p+P69fDRVNyIlJxUTrz0LWpMe9ho7zDaL3GnGlcbaRnhcXjy3/K8IBUPwun3QGXRQqpTYuXEPqg7WIC07Ve40u6xwIICwzw8xFIJCrYZCq4FS0/G/nzds2IB//etfGDJkSIc/l2RF9AEDBqCgoADPP/88tm3bBr1ej1mzZuHWW2+FzWY75vO43W4MHToU1113HS6++OIW4+PHj8fll1+OG2+8sT0/BSIiIiKikwLn5i0LB4MIez3wlJcgEjxUdFJoNDBkdYdSq5Pkj0H6hUIpQGU2wZyXi8YdOxF0ugAASp0WCQP6IeBwcB26DJRttNARlFzJKQdDkhVjb5qGzf9djZo9BwEcaofU56zhOOfBayAI/E6RmsFkhEqtQk1xNUZMHQlTgglNtXaU7z6IoWef0uqmo9RxlColJl14Oj58bSXWfPIDQsEQBIWA0WeOwNW3XgpHY/O7nujYhDxe1G3aCl9NbXRMl5qC5BHDoDJ0XDspl8uFmTNn4uWXX8Zjjz3WYc9zmGRFdADIzMzEX//61xM6x5QpUzBlypRW49deey0AoLi4+ISeh4iIiIjoZMa5eXNiKAhX8X4AYnQsEgjAVbwPll79AbCILiWFSgVzbjdUrl4bvTMAAMI+P+o3b0Pa6WMg6HmXgNRs/bqjYl1Bi7HkQT2g1Gslzogs6TZ8t+hDOKsao2MhfxA7V66HUqNC3rjBMmYXn/QJenz6z49QXFDYLOayu3HGVROlTyrOJSQnYOm/VmD1h99Fx8SIiB+/2giP04Mb58+SMbuuKxwINCugA4CvphZ1m7YiZfSIDluEcMstt2DatGmYPHly1y+iFxS0/Iu1JVIsuyciIiIiilecm7ctEgrAV1uFwwV0pVYHEUDE7wNEEb76GujTsqBUcyNLqYTDYbjLK6MFdLXZBAjCoRXpogj7nn1IHjEMUEm6Nizuhf1BpI8aiKr1P8eMa60mJA3ogbA3APDihqQ8DY6YAvqR9ny5CdnDe0Nn5uaiUvJ7/NECuinRBGOCCY56B7wODwq+3orRF46FOUnmJOOM1+VF/ifrWowV/LQTXpdP4oxODmGfv1kB/TBfTS3CPn+HFNHfeecdbN68GRs2bGj3c7emQ2cbw4YNgyAIEEWxzeMEQYjZ1Ehqfr8ffr8/+rHD4Tjmx1ZXV8Nut3dEWr9ZSUlJzP87E6vVirS0NLnTICKiLkjh61y/bzszvlbUkniYm58IMRxB2OuBNikVarMVYa8bAKDUGxF0NiHkcQMRbs4nJTEUQqChEcZuWTDmZCNod0AMR6BJtMLf0AhnUQkiMn6txqv6XYVQqNXoPeNMNO4vRdgXgDknHRqzAQc+ykf/q1u/O4U6RlN5XauxgMePkD8oYTYEAI46B5Kyk3HGzDPh9/hhr2mCLTMJggB889oq+Fxs5yI1t9PT5vymvrYRuX26SZjRyUEMhU4o/lscPHgQt99+O1atWgWdTrqLth1aRC8qKurI07ebxx9/HAsWLDjux1VXV+Oaa2chGPAf/WAZLFy4UO4UmlFrtHjrzTdYSCciomNmtVqh1miBwjVyp9KlqDVaWK1WudOgTuRkn5ufMEEBXUo6Ql43XMX7YkLa5FRok1IhKBTS5xXHBJUKhm6ZCHt8qPn+p5iYITsTtqGDIAh8T6Smt1lR8vV61KhVsOZlQqFRoXbrHnjr7VAbudpZDqbk1n/fK9VKKDW8W0NqlmQrzr7+PHz4zAfwOjzR8YS0BJx/+wzoTLxbQ2p6Y9uvuSXBLFEmJxfhKHeDHS3+W2zatAk1NTU45ZRTomPhcBj5+fl4/vnn4ff7oeyAPTo69Cdpbm5us7GdO3eitLQUgcAvu0MLgtDisVK57777cNddd0U/djgc6Nbt6Fef7HY7ggE/vD3OQETHP1KPRuGzA4VrYLfbWUQnIqJjlpaWhrfefKNT3vm1cOFCzJ8/X9Z5TGt49xf92sk+Nz9RSo0GYZUK/vrmtyT762pgzusNBVu5SEqpVEJjNqNy49ZmMU9ZBfRpKVCbjNInFucseVkQVEpEgiE07i2NiaWPHAAli4OSM6fZoDXp4W9hdXPuaQOgMnA/B6lpdCqsXPRxTAEdAJqqm7D27dW48O5LZcosfukMWgwePQDbf9rZLNatZxaMFoMMWXV9Sp0WutSUFlu66FJToNS1/z4ZZ511FrZv3x4zNnfuXPTr1w/33ntvhxTQAQk3Fi0sLMSMGTOwffv2mNtID+8SLecto1qtFlrtb39TIzorIsbkdsyIjgVb6RwfFlOIqCtLS0vrtD/DcnNz0adPH7nTIDouJ/Pc/LeKhMPw1VW3GvfV1UBpMEHRQX+YUXPhcBjOwuJW4459RdAlJ0FtMkmXFCHk9aHvpZOxb8VqhH2/XIBLHtQLiX1yEXb7ABm+h+OZ3+vF6X+4CN+/+BG8Te7oePqg7uh79ggE3X7Awu8TKXmcXjhqW65XlO0+iICvc3Y0OJn5fQFcf+81+OeDL+PAz7/cnZeZm447/nYTQsH2bzsSD5QaDZJHDGu2uaguNQXJI4Z1SD90s9mMQYMGxYwZjUYkJSU1G29PkhXRb7/9duTl5eHrr79GXl4efvrpJzQ0NODuu+/GP/7xj2M+j8vlwv79+6MfFxUVYevWrbDZbMjJyUFDQwNKS0tRUVEBANizZw8AID09Henp6e37SZFs2Ern+LGVDhERER3GuXkLIhGIwdb7BkdCQeAo/eSpfYmhEMJtFJrCfv9Re/xT+6vfWQilTouB10xDwOlGyB+APikBYX8ABa98iCHXXSh3inGnobAKjvJ6TLjtYvhdXvidHphSEgAAX//9bZxxxyXyJhiHPHZPm/GgN9BmnNqfx+nF4r++jtsem4egP4jaynrYUhNgMBvw2pNvY9o156Bbjyy50+ySVAY9UkaPQNjnhxgKQVCpoNRpO6SALifJiujr1q3DN998g+TkZCgUCiiVSowfPx6PP/44brvtNmzZsuWYzrNx40ZMmjQp+vHhWz1nz56N1157DR999BHmzp0bjV955ZUAgIcffhiPPPJI+31CJCu20jk+bKVDRERER+LcvDlBqYTKbEHY72sxrjZZ2BNdYiqtFrrUZHira1qMa22JHdJrldpmzcvCvg++QeW6AqhNeqgMOnhrGgEAhrQkfp/IIKl7OrYtzUfRDz9DY9LDYDPDXl4PMRyGzmqESstWVFJLSEtoNabSqqEzcf8AqZmsRlSX1eJPVz0CjV6DrLwMVJXWwOvyQhAEzL77SrlT7NKUGo2sRfNvv/22w59DshlHOByG2XyoSX9ycjIqKirQt29f5ObmRlekHIuJEye2udpgzpw5mDNnzommS10EW+kQERERHT/OzZsTFAroklLhr68DxEhsUKGA1pbM4qAM9BnpsO/dj4j/V6s2BQEJ/ftAwSK65PRJVmgTzPA3ORF0eRE8og931vihELiJpeS0Jj2S8jJQX1SJgMuLwBHvSf/zRkLB90Ryap0G/ccPwq7vdjSLjb7gNBbRZWBNNGPqlZPx4eufIeANoGjnL214x5wzEkYz3xNqm2Q/SQcNGoRt27YhLy8Po0ePxhNPPAGNRoPFixejR48eUqVBRERERBT3ODdvmUKjhaVXP3jKSxDyHOorrDKYYMjKgULDHs9SiwQC8Dc0IP30sWgo+Dnaa1VjtcA2dBBCPv+hW8a54auk6nYWovu5Y+Cts0NrPrQRX8jnh8qgQ+OeEuiTEgAji1FSqjtQiX7nnYqyLftxcONeREJh6BNM6HfOCHganYd6oieY5U4zrjRW1uPM2ZNhTbFg8+cbEfAGoLcYMGbGOPQbOwD22iaYEtmnXkomqwmTL5kIg8mAT976Ak67C3qjDpMvnohzLpsEW6pN7hSpk5OsiP7AAw/A7T40EX300Udx/vnn4/TTT0dSUhLeffddqdIgIiIiIop7nJu3TZOYDF3KoZ7tkVAI+N+GqyQ9b0UVnEWlSBo+BAJwqC+9UgHH/kJ4K6uRdvpYuVOMPyIAUYSrshYHVxdDjESgT05A1rhhiIQjR304tT8xEsG6xZ8ie0QfjJ57LgAg6PWj8LsdaCiuRu7o/jJnGIdE4F9/eB5XPHANhp09AqFgCCqNCnUH67Dod89h7j/myZ1hnBLRa3Ae7nv+TojhCJQqJVwOl9xJURchWRH93HPPjf67V69e2L17NxoaGpCYmAiBk1IiIiIiIslwbt6ySMAPx4HdQCS2ECgolLD07g+lVidTZvFJodHAmJON2h83ovKrb5vFLb17QqnjHQJSSxqQh30ffANfgyM65q1rwv4Pv0WfS86CUsM7A6SWkJ2MSDiC0vW7Ubp+d0wsMScVCpVSpszilzUlAYgASx54rVnMbDNDx9YhknPa3Vj94Xf44JVPmsUmTBuDK2+5GElcjU5tkLWpn81mi+tJOhERERFRZxHvc3MxEoGvvqZZAf1QLAx/Yx3EX/dKpw6nNpuhTW5e1FAa9DB1zwEirffkp47hb3JFC+hKjQYa6y8tKcq/33bo7g2SVMgfRJ+zhjcbV6pVGDBtdFz/bJeLSqfG5OvPAwAoVAqYbGZAoYCgUGDKLdOhM/OirNScjQ588taXLcbWrvwRHqe3xRjRYdxdgoiIiIiI4p4YDiPkdLQaDzod0CWnQ1Bxc1GphINBNO7cA9uQQQg02eEqLoUYDkOflQFjZgbqt+1A8vAhUGo1cqcaV5oOHETayP5IG9oPQY8PYX8A2gQzgh4fdr/9OcQwL2xITaVTQ6XXYvTcc1H84y747G7Yuqeh26l9UbG9COa0RLlTjDvVhVXIO6Unfv/SbfA6vXA3uWBJtkBr0MHvDaCxrB7G/ka504wrTrsbgV9vUv0/oiiirroB3XpmSZwVdSUsohMRER0Hhc8udwpdAl8nIupyFAIElRrw+1oOq1TsjS4xQaGAQqVE5Tf50KenwdKnFyAI8FbXoOKrb6G2mPmeyMDWtzsEhQI7l6xEyOs/NCgISBnaG0NunAHwLZGcoFDCmGTBtg/WotspfZDUIwOOygasf2MVzrjtIvBNkV5iegLEYATL/vYufC4vjIkmOOocSMpKwvQ7ZiCo5gVZqWm0bbeaMnBDZDoKFtGJiIiOgdVqhVqjBQrXyJ1Kl6HWaGG1WuVOg4jomCiUKuhS0+EqcrYY16WkQ6FkX2EpKZRKmPNy4S45CG9VNbxV1TFxS68eUBsNMmUXvzRmA3a89jEiwSPatogiarfuhd5mRcrQvvIlF6eUGhUaiqtw6jVno3JHEezldbB1T0fu6H4o27wfPSYMkTvFuKNUqbDqP59jwtWT4HV6YK+xw5aVBKVSgbXvrMEZM8+UO8W4YzAb0KN/Lgp3lTSLJaUlwpJoliEr6kpYRCciIjoGaWlpeOvNN2C3d64V1iUlJVi4cCHmz5+P3NxcudOJYbVakZaWJncaRETHTKU3QJuUCn99Tcy4LiUNSh2LtVILh8MIuT2w9usDV1kFbAP7QhQEuApLoFCpIKjVCLrdUBvZEkFK9uIKRIIhCColrLkZUKhVcFfVw9/kROX6n5HQqxtUWl5El5KruhEH1hSg+MfdOOXyM6C1GFCzuxTfr/geSrUK3U7tA72FP8OkFPQHccq5I/HRM8vgPaLXtjXFiqm3XohgK21FqOOkZaXg5keux1//8AxsKQlIzUpBY20TDhZW4O4nbkFGDv9uobaxiE5ERHSM0tLSOm1RODc3F3369JE7DSKiLk2hUkOXnAptYhICzkMXTTVmKwSl8lA7F5KUGArBXVqGxMEDoE9NhqvkIMRwBOae3aE2m1C7YQtSRjbfTJE6lreuCWkj+sPaPRON+w8i7A8gfeRAqPRalHz1E8CW6JJz1jZh6KUTkNI7C6UbdsPzswupfbJxzgPXYMt73yIc4GavUhNFEZ8t+iimgA4A9lo78v/7Dab94UKZMotvaZkpeGDR3dicvw37fy7CwFP74Yb7rkVCskXu1Og4PfLII1iwYEHMWN++fbF79+4Oe07OBImIiIiIiACEA364y0sRcjuh1OoAAL7qSqjNFhiycqDUaGXOML4IKhUShwyEfe9+uEsORsfdZeXQJCYgddQpgMC+wlKz9c2Do7gce5d9HR1r2F0MXaIFvS44g+23ZZDWtxsaSmrw1d/ejl7EKNu8DzqLARNumwGFpu1e0NT+gv4gHHUtb1ZdvqcMYoRXm+RQsv8gHrvlafg8/9v/5GtgxWsrcc9Tt2LAKX2h0XGj6q5k4MCB+Oqrr6Ifqzp4wQNnHERERERERABCbidCLgcgigj7vAj7vABEBJ12hDxuudOLO0qlEmGfL6aAfligsQnuskoIWhY8pKbSa1Dx4/Zm475GBxp2F0Fl4OZ8UlOolNi05OtmdwH4HB5sfT8fShVLP1Lze/xtxkNB3h0gtaqDNXjh4Vd+KaD/TygYwj8ffBn1NQ0yZXZyCHr98NY3wVVRC2+9HUFv298D7UGlUiE9PT36X3Jycsc+X4eenYiIOoTC2yR3Cl0CXyeik1M4HEZBQQEaGhpgs9kwZMgQKLnhI52gcDAAf31tq3F/fS1UJjOUKq7olEokFIKz6NAGcEmnDoc2wQoIAkJeL+o3bYGruBTGrAzAbJI50/jSsKe41VjtjgNIHzUIaq7mlFR9URXESKTFWM2egwj52H9bamZb65tUqrRqrniWgdvpQWVpNZLTkzDpgvFIzUpGQ20T1nz8PSpKqtBYZ0dGTrrcaXZJfocLhSu/h6O4IjpmzctE3pRx0FqO7Xd0OBRGJBIBBAFq9bGVq/ft24fMzEzodDqMGTMGjz/+OHJycn7T53AsWEQnIuqC9EX5cqdARCSL/Px8LFq0CFVVVdGx9PR03HzzzZgwYYKMmVGXFxFbLUL9f3t3Hh5VefYP/HvmzL5nskz2hUACBBAQxAAiKtaiIi4vLqUtittb6OuL/rSVKgUUqnaxbpUWa9ECSn1r0apV6lJBFAWURQRZQkhCdrLMllnPzO8PSjRNBgUycyYz3891cWmeJ5lzZ85kcuc+z7kfAMfnePt9XIWlCBQaDfK+cyFc1TXo+PwLRKQw9Dl22CdXwlVTx/bbMpD8wahzkZAUx0johJMWySPHf5YovqSQhOGTR2Dv5j295sZfNgGRCM9JvEmhEL573UUYXFGCN9e9g6OHG5CVl4npN0yD2+lB8CTvbRRd0OvvVUAHAEd1A6rf/BClV0yFShe9HZ4kheH3+9HS2Aqv1welUomMLBtMJiOUJymmT5gwAc899xzKy8vR2NiIpUuX4rzzzsOePXtgMkW/iHUmWEQnIhqAvCVTENZZ5Q4j4Sm8nbzgQJRENm3ahMWLF6OyshKLFi1CSUkJqqursXbtWixevBhLly5lIZ1Om6BSQWWy/LuFS29qswUCNxeNK6VGBXNpCVq2bEXQ5e4e99TVw9vUjOyp50HxLVerUf9JKytC86f7+pwzF+UASt4ZFG8Zg3OjzpnsaVDpuOo53tRaNYZMKIcp3Yydb38Kf5cfeosB58w4FxqDFiJ/TuLOlpWGrNwMPPXzP3aP1VXV49mH1+Dy71+C7EK7jNENXKEub68C+gmO6gaEurwnLaJ7u7yoqT6KE/2oAoEAGo42wZpmgT0nC8ooPyvTp0/v/v9Ro0ZhwoQJKCoqwksvvYSbb7759L+hk2DGQUQ0AIV1VoQNse33RUSUSCRJwtNPP43KykosW7YMCsXx/q4VFRVYtmwZ7r//fqxYsQKTJk1iaxc6LYIgQJOWDn9HGyKhnqvRFCoV1JY0CAJ3TIw3f1t7jwL6CeFgCM4Dh2AdMUyGqFKbSqeBMS8L7vqWHuOCqEBu5SiZokptolKJ/LGDcfSzQz0nBKBiRiUEBd+74k2lUaHlSDPaGo5h+o8uh0IpIugPYvc7O1Bx/ihojdw7IN6CgRBe/uNrfc69ue4dXHgVF2KcjpPdnfRN88FgCI31zei1oQOAzg4H0jNtUYvo/8lqtaKsrAyHDh365k8+TdxdgoiIiIgS3u7du9HU1ITZs2d3F9BPUCgUmD17NhobG7F7926ZIqSBLhIKoaulEaaSIVDbMiCIIgRRhMaWAWNJGbpamhCR2KoinkL+ILrqG6E0GmAbPRJZleORee44ZIwfC026Dd7mFoS5OV/ctX5+CDnjK5BbOQpqkx4KlRLW0nyUXX0R6j/cCbClS9w1769B9vBijLxyEgwZFohqJTLL8jHp9hk4+tkBBDyx3+CPemqtbcFZ08ai4rwR+PD/PsBrj63Hp29sReU1k5EzJA8djdzEMt6cHS54XF19zkkhCccajsU5ouQgak6+V8zJ5sOShEAgejsq739sAnsybrcbVVVVyMnJ+dZfc6q4Ep2IiIiIEl57+/E/NktKSvqcPzF+4vOITpkgIBLww1n1JXT2XGiKhwAAgh4XnAf2QmkwAlyJHlcKUYDKYoKppBDtn+9FyO05Pq5WI61iKAJuD3hG4k+hFHHwlX/BVJiN3HNHQaFWwtPUhkN/fx9hKfq+AhQ7Kq0GW5/7J9IKszDkgtFQ6zVwNrZj+9p34Hd7UXH5uXKHmHKUGhV+/6MncN4N5+Oae687/vsjEsGW9Zux6+0duPm3t8sdYso5WX9t4PjdA3TqlHodLCW5cFT3buliKcmFUn+Suy6+Ia8Sxehrv++++27MmDEDRUVFaGhowOLFiyGKIm644YZvHfupYhGdiIiIiBKezWYDAFRXV6OioqLXfHV1dY/PIzpVCqUSmowshGqr4W082mtem5EFBVsFxZVCqYSxIB+N//qgx10A4UAAbTt2wz65EoJOK2OEqclWXoyGLbvhqm2Cq7apx1zmqDKIPCdxZyvOhqBQoKO2BR21PdvsZA0rgErPcxJvJpsJWoMWH7y4ER+8uLHHXHp+BrQGtnOJN4NRh5xCOxprm3vNGS0GpKVbZIhq4FPpNCiZPgnVb37Yo5BuKclFyfTJJ+2HrhRFGIwGeP59kfzrBEGAVhv9a48ePYobbrgBbW1tyMzMxOTJk/Hxxx8jMzPzzL6hk2A7FyIiIiJKeKNGjUJ2djbWrl2LcLjnSsdwOIy1a9ciJycHo0axHy+dPpXBBKXJDAgCRK0OolYHQIDKbIWoN8odXsqRJAme+saobXQc+w8i4o9+GzjFRgQR5E0aDQDQpltgyE6HQq2ENs2M7HMqEPaxdUi8Bb1+jJ41Bf95a4bWrMfQ74xD6Bt6FlP/i0Qi+O6/e6EPOacMU753AQpHlECt0+Cimy7pda4o9rIL7Zi/9GZo/+OiklKlxP88eCvMNpNMkQ18GrMRpVdMxahbr0LFDy/HqFuvQukVU6ExG076daJSRE6eHcpeG7cLyCvIOendA+vWrUNDQwP8fj+OHj2KdevWobS0tB++m+i4Ep2ITllzczMcDofcYfRQU1PT47+JxmKxwG7nbt9ERKdLFEXMmzcPixcvxv3334/Zs2ejpKQE1dXVWLt2LbZs2YKlS5dyU1E6IwqVGoa8IkRCIQRcx3MdQ74FglIJUcXbvOMtEgoh0N4RdT7gdCISZv/teGvddQCZo8thG1oMZ00Dgl4/Ci4YD7XZgKo3NqN0+iS5Q0w5xw43IuDxYdq9N6B22350tbtgLy+ArSQb21a/jfE/uFjuEFNOe0M7wpEwbn9qPpqqGtB29BgmzDwXGYVZ2LNxF3QmHdKyefdcvOWX5OKhP9+Pbe/vwOF9NcgtzsbES86BJc0Eg+nkBV86OZVOc9JV59FoNGqUDC6Cx90Ft8sNtUYNq9UMpUrVax8kubGITkSnpLm5Gd//wQ8RDCTmCpPly5fLHUKfVGoN1qz+MwvpRERnYMqUKVi6dCmefvppzJ8/v3s8JycHS5cuxZQpU2SMjpJBOBSEr7UZ/rav2iH4mhugzbRDm5kDRa+VUhRLglIJpckINLf0Oa/U6yEk2B/YqSDjrDJ4Wztw+I3NQCQCAGj4cBdM+XaUXjqZC2xlkFZoh8/hwfuP/hXpg3Kg1mtxaOMuRN7fibP+awpEDd+74i2zKBNdji6s+n8r4fN8tTmiOcOMG5b+EKKGF/3loDPqoDPqMPPGHIRCoT5WQJMc1GoV1DYLrGlmCAm8/wxfLUR0ShwOB4IBP7yDzkdYy55h34bC5wAOb4TD4WARnYjoDE2ZMgWTJk3C7t270d7eDpvNhlGjRnEFOvWLkLerRwH9BF9rM1QmCxRGswxRpS5RFGEsKoCrqrq7WPt1lvLBUBm4cjDeRFHsUUA/wXW0Ga27DiC38iyZIktdWpMOHzy5HlIghOZ9tT3mqj/6AmOunSpPYCksIkXw11+s61FABwDnMSdee/wVXH3PLJkioxNYQE88iVxAB1hEJ6LTFNZaEDZkyB0GERGlIFEUMWbMGLnDoCQTliT4WpqizvtamyDqDNxcNI6kYBDellakjz0L7bv2IBIKHZ8QBFjKShHy+hB0e6AyspAeTx0Havq8qAEALTv3I/OsIVBysU1cOY4egxQIQWvWI3/sEKgNWjgb29Gwqwr1Ow6h4vJzobPw5ySePJ1uuNqc0Bq0GDa5AiabGR1N7dj30V40HDgKX5fvmx+EiBIKi+hEREREREThMCKh6JvvhUOhqIVDio1IOAz/sXaYSgphP68SkteLSDgMpV4PIIK2HZ9DZ8+UO8yUE3B3RZ2T/AGAPyZx1+VwY/ilE2CyW3Hk433wOTywFdsxed5MfPGPjxEOce+AePO6fRj73XEYNGYwdr27A0e/rENmYRb+697r8Nlb27nZK9EAxCJ6P1B4O+UOYUDg80REREREiUoQRSiNZkj+vlcHqoxmCCL7b8eTUqOBpawUHV/sg/9YO6BQQBAERCQJol6HzPFjIfB2/LizlhagZcf+PucM2ekQxMS+HT8ZZZUXoGbLXnyyakP3mKOhDbXb9qPytsuh0qpljC41pednoL3+GP760LrusdaaFuz7cC+uuPMqGNKMMkZHRKeDGUc/0FVvkjsEIiIiIiI6E4IATVo6/B3HgHC455RChNpqgyCwiB5vUiB4vIAOHL9b4MR4lxddTc2wlA+RLbZUpbEaobWZ4Wt39prLmzSaG/DKQKEQcOC9Hb3GpaCEL17bgon/fbkMUaW4SATvr32v93A4jPdW/RM/ePhmGYIiojMx4H67bdq0Cb/61a/w6aeforGxEevXr8eVV17ZPR+JRLB48WI888wz6OzsxKRJk7BixQoMGRK75MpbMgVhnTVmj58sFN5OXnAgIiIiSiKJmJufrogUgre1CcbCUvhaGxHyuAEASoMJ2sxseFsaYcgrYoEwjsKBADw1tVHnPbVHYSwqhKhSxTEqattbjaJpE9D6+SF07K9BJByGLsOK3MpROLb3MLTp7Iceb8cONURto9NR24Jglx+wxTemVOdo6UQkEsaV9/wX7MXZCIfCUCgVqNlzBG+teB1eZxeQw5Mih7AURsexTgR8Aag0KljTLVCq+LudvtmAe5V4PB6cddZZmDt3Lq6++upe87/85S/xxBNP4Pnnn0dJSQkWLVqESy65BHv37oVWq41JTGGdlRssEhEREVHKScTc/EyEA3546qqhsWVAm2EHAIS6PPDUVUPUJF68xLYhcggHQzjwt/eQMXwQSq+YAgAIOD2o37wTfocL+edx4+eEI/BnJd4EQcBtT/4YO97ahn889XcEvAHozXqce9Uk3PbUfPZEl4mj3YnNb36M9X96Ay6HGzqDFt+9bhq+e+2FsGbwAiCd3IArok+fPh3Tp0/vcy4SieCxxx7D/fffj5kzZwIA/vznP8Nut+OVV17B9ddfH89QiYiIiIiSWjLl5gqlChpbBvztx3oUzEWNFgrV8TmuQo8vhVoNY3Ehuhqa+pw3FuZD1GriHBXZhhajadsXaN19EK27D/aYSysvhoIrOuMuY3Du8WtKfaxGtxXbodTwbo14s+bY8N5z/8S+zV90j3U5u/De82/D3+XDuMvPlTG61BTwB7Dh/97Dy8+81j3m9fiw/k+vo625HTfdfQP0Jr2MEVKiS6qmftXV1WhqasK0adO6xywWCyZMmIAtW7bIGBkRERERUWoZiLm5ymSBNsOOrqZ6uGuq4K6pQldTPbRZOVCazHKHl5IUKhW0mb3v+lUa9NBlZyEcCskQVWpT6rXIqCjtPa7TIP+80YiEwn18FcWWgGHfPafXqKhWYvS1UxGJROn1QjET9AV6FNC/7pO/fwy/p+9NrCl2Otuc+Puf3+pz7oN/bIGjo/c+D5TY6uvr8f3vfx/p6enQ6XQYOXIktm/fHrPjJdUl4qam4ysU7HZ7j3G73d491xe/3w+/39/9sdPJH5yBQuHtlDuEAYHPExEREcXbQMzNI5IET111z7FQEJ7aapjLhgNczBlXIb8fjv2HYCjIgz4vB56j9YhIYeiz7VBbzTi2Yzeyzh0nd5gpp2nrHuSdNwZp5UVo/nQfJH8AlpI8ZIwYjM6qWlhLC+UOMeW07K9DxpA8nF9+NQ68uwM+hwcZg/MwaPII7H/3M5RNHS13iCmns7kz6lzIH4TP7Y1fMAQAcDvcCEZpoxOJRNDe0omcwuw4R0Wnq6OjA5MmTcIFF1yAN998E5mZmTh48CDS0tJidsykKqKfroceeghLly6VOww6DdyolIiIiCi5yJWbR8Jh+FqjFfcj8B1rhiG3EIIiqW7mTWiCUglRo0bbZ7ugNBqgz7EDggLe5hZ07tsPldkEgb2e484+8Sz42xzorKpH4UXnABDg63ShYctu5E0ejUiYK9HjzWi3AuEwdv71A2SU5sGSmwFnUxt2/W0zSiYOh0Ityh1iytGZdCedV2nVcYqETtB8Q/svnfHk54xOzu/xwe/qQtDrh0qngcakh8YQu/1kHnnkERQUFGDVqlXdYyUlJTE7HpBkRfTs7ONXjJqbm5GTk9M93tzcjNGjR0f9uoULF+Kuu+7q/tjpdKKgoCBmcVL/8ZZMQVhnlTuMhKfwdvKCAxEREcXVQMvNI2EJkrcr6rzk7UIkHGYRPY5EUYRxUDHcNXUIuT1wHjzcY948ZBBURqNM0aUuIRDE/r++g0hIQuuu/T3mdBlWZI0tlymy1GVMt+C9X78Ev8sLR0N7jzl9mhHpg3Nliix1GSx6mDMtcLY6es3llRdAreN+DvFmTjNhcEUJDn1R3WsuIzsd1nRuLHq6utpd2Lb6bTTvq+0esw8rwvgfTIPeZorJMf/+97/jkksuwaxZs7Bx40bk5eVh3rx5uPXWW2NyPCDJiuglJSXIzs7Gu+++252YO51OfPLJJ/jRj34U9es0Gg00Gr6BDURhnRVhQ+8eiUREREQkr4GWm0cigEKtgeTvu0+tQs2/F+JNkiREQiGkjRyOjs/39pjT5+dBbbEg6PZAZTTIFGFqchyuRyQkQaFSwlKSC4VKCU9TG3xtDjRt+wK2skIobVxlG0/O5g74XX23B6n5eC/KLhoDmPlzEl8K/NfC6/HiktXwOr+6QGu1WzHjf69EOCzJGFtqMlmN+J9lt2LZvN+gtbGtx/hPH7sDtkyrfMENYH6Pr1cBHQCa99Vg2+p3cO4t02OyIv3w4cNYsWIF7rrrLvzsZz/Dtm3bcMcdd0CtVmPOnDn9fjxgABbR3W43Dh061P1xdXU1du7cCZvNhsLCQixYsADLli3DkCFDUFJSgkWLFiE3NxdXXnmlfEETERERESWhZMrNBQHQ2DIRdPVeNQgAmjQu3Ii3SCgE54EqmMsGI2fa+fC1HENECkOXlQEoFGj5eCvsk86VO8yU4213IPucETDlZaHjUC0kXwBZo8uhNulR8/Yn4B6W8edu7Yw6JwUlSAFuwBtvx4624uC2/Zjz8M1orWtFe/0x2IuzYclOwz//+CbOu34q0nmDQNxZ0y342VN3ob66AbWH6pFdYEdxeQEsMVotnQr8rq5eBfQTmvfVwO/qikkRPRwOY9y4cfjFL34BABgzZgz27NmD3//+9yyin7B9+3ZccMEF3R+fuNVzzpw5eO655/CTn/wEHo8Ht912Gzo7OzF58mS89dZb0Gpj14eHiIiIiCgVJVNuLihECEoldDkF8DbVA5HwiQnoc/MhiCJbucSZoFTCNGQQ3NU18Byth8pkBAQBnfv2Q202IWPMaChE9nqON9vQEnRWHcXB9e91j3UcrIXGakLpFVMgKNinPt6sedEv8qkNWoiaAVf6GfDMGWbseGs7dry1HUWjSpBdmoNNL/4LDQfroVCKuPiW6XKHmJJqDtZh+fxHodaoYcuywtHugqvTjf/36/moGFsObQx7eCeroNf/DfOBmBw3JycHw4cP7zE2bNgwvPzyyzE5HjAAi+hTp05F5CSXtgVBwAMPPIAHHnggjlEREREREaWeZMrNBYUCYb8PIbcTxsISRCJhAAIEQYC/rRWCqIRgYP/teBJFEYIgwHO0HgAQdLm75wKdDgQ6O6FKT5MrvJSl1KrRtHVPr3F/pwttew8j/4JxMkSV2vQ2M0zZaXA1dfSaK794LNR6FgbjTa3XoHhUCY7srkbNv/+dMOrC0dDq2fIo3prqmvG7xX+C3xeA3xeAy/HV75TfLX4Wy1b9DLmGbBkjHJhU39DfX6WLzWt90qRJ2L+/574cBw4cQFFRUUyOBwBcSkFERERERClPCgTga29F0O1EwNEJRABEwgg4OhD0uOBva4UUDModZkoJh0JwHT4Sdd5VXYOIt+8e9hQ77ftros4d23MYUtfJVyVS/3M0tmPyj65A6flnYez1F+Dcm6ejYsa5GHX1JOSOGhS1XzrFjqfNjUvnX4GhE4d3350hKkWMnT4elVdPgqvd/Q2PQP3N4+pC89GWvuecHnS29d3OjU5OY9LDPqzvwrV9WBE0Jn1MjnvnnXfi448/xi9+8QscOnQIL7zwAlauXIn58+fH5HjAAFyJTkRERERE1O8iEShEJfTFg+HvaIOn/nihUG1Og6l4MLzHWsFmz/EVliKISOGo8xFJAs9I/En+6LfmRyRuligHb6cDBpsJxkwzvtywHV6HB7ZiO0ZeOQlNe2uRVV4gd4gpx+/1oam6EZNmTcHk685HwBuAWn98xe6nG7Zh+MQRMkeYeqTQyd+fgn5eKD8dGoMW438wDdtWv4PmfV9dZLUPK8L4H06LST90ABg/fjzWr1+PhQsX4oEHHkBJSQkee+wxzJ49OybHA1hEJyIiIiIigqBSQWfPhevIQURCX23CF+hsQ9DthKl4MAQl/3yKJ6VGBUNBHrxNzX3O63KzoVCzJUK8pZUVofnTfX3OmUtyISjZpz7esoeVYPf6zajf8dVGz22HG/H+b/+KSf89A1qzTsboUlN6XgaqPjuIDX94o9fctLmXwGhje7B4M1qMMJgN8Dg9veZEpYiMnHQZokoOepsJ594yHX5XF4LeAFQ6NTQmfcwK6CdcfvnluPzyy2N6jK9jOxciIiIiIiIAAWdnjwL6CZFQEEG3U4aISGUyQmU29RpXqFQwFhZ8tQEsxY1Sp4GpwN5rXFCKyJ0wEuD9AXEX9Pp7FNC7RYBdL3+AkL/3+xrFlhSSsP2NbX3Obf7LRoRDfO+Kt/SsNHz/f2f1OXfV3Mugj1HbkVShMWhhzrYhvSQb5mxbzAvocmARnYiIiIiIUl4kGETQ2Rl1PuDo6LPATrET8gfhOHAQaRXDYB5SClGnhUKthqEwH5kTzkb77i8QDvKcxFvr7oOwjxmKvMmjobEYIWrVSCsrQtnVF+HoBzsQYXEw7tqqGqLOuVs6ETpJCx6Kjc7mDkTCff8s+Dw+dDl6r4am2NLoNBh5znDc99RdKD9rMAwmPUrKC3Hnwz/C1MsnIS3dIneIlOB4PyIREREREZFCgKCI3oZCUIjAvzeHo/hQiAIEQYGWLVuhzcqEpXwIBEGA71gbmj/aCqWeLSrkIKpVOPT3jTDmZcE+bjhElRKepjYcXP8e9w2Qierfvbb7JAAKkS124k2lUZ10XlSxHCcHpVJEU10zbr1vDhSCgAgi+HLHQShErjGmb8afWiIiIiIiSnmiSg1NeiZCXe4+57XpmRCVJy+KUP9SKJUwlhTBU1cPX0srfC2tPeZNg4qh0CXf7eKJzlZejIaPdsFd3wJ3fUuPuawx5VCerKBLMWErzoZCVCDcx0a89mFF3RtaUvwYbSboTDp4Xd5ecxkFmdAmYauLROft8uGFp17Gpjc+6jU3/Oxy3PXIPJis7FVP0bGI3g8UPofcIQwIfJ6IiIiIKFFFwmGIWh1UJguCrp55q8pshUKjQSQchqDgarV4kSQJ4VAIxuJCuI/U9pjTpNugMpkQ8QcAbvgaV0GfD3mTRqP+w53IPqcCSr0ObXsOIRKJwFZejJDXD5WWBcJ4Cnr9GH3tVOxY9y8Y7VaoDVq4WzqhEBUov3gsgoEQeN9GfCmUClx1zyz85cEXIH2t7ZTGoMUVd14NBTfgjTtHmxMfvLmlz7m9n+6Ho93JIjqdFLONM2CxWKBSa4DDG+UOZcBQqTWwWNhnKhkovJ1yhzBgxOK54kWpb4fPExERfVuRsARP7RHo8/KhychCoLMdAKC2pgMAPEdrYCopYxE9jiKhENxVR6BOsyDz3PHwNrcgIknQZWUiIklo27EL9snnyh1myun48ghsw0owcuiV6Dxcj5DXj6JpE6A2G3Bo/XsYfOWFcoeYco4dbkTQ48XF930PrQfr0dXhwtCLx0GfbsK2P7+D8T+YJneIKae1phV6iw63PPbfOPDJl2itbUFeWT4GjSlF05FGSCEJlkzWRuKpy92FSDh6y6nONgfyB+XGMSIaaFhEPwN2ux1rVv8ZDkdiFWlqamqwfPly3HfffSgqKpI7nB4sFgvs9t47udPAo6veJHcIKYkX704dL94REdG3Iiig0KjhOnwACrUaamsGAKCr7gjCoQDUVhsL6HEmKJVQGg1wfHkQgihCm5kOCAp0fL4Xkt8PjS2N50QGmWeVoaulHV++uKG7B3rjx7thzM3EkKsvQoR90eMurSAT3k4P3nl4HcIhCQCwH5/CZE/DmOumQlSz9BNvWSVZcLe58dw9zyCjIAvGNCN2vv0ZPvzrB/jeAz+ESq+WO8SUozPoIAhC1Pcoc5opzhHRQMN30jNkt9sTtihcVFSEsrIyucOgJOUtmYKwzip3GAOCwtvZbxcdePHu1PHiHRERfRsKUYQuKwdBZyfCgQB8LQ095rWZdhZs40wAYCouhOvwEUQkCd6mnv23LeVDIHDDxLhTiCKq//Fhr3F3QyuaP/sS2ZUjZIgqtWnNBnzw5KvdBfQTXM0dqPrgc4y59nyZIktd4YCEvz60Dv4uP+r31/WYe+2x9bj6p9fJFFnqsqSZcPaUs7B9485ecyXlhbDYzPEPigYUFtGJ6LSEdVaEDRlyh5GSePGOiIgoNhQaDQz5xfC3H4PKdPyP6aDbCU16FhRq9niOt3A4jLBCgcxzx6Ft+06Eg0EAgKBQwDKsHEqTEZFQ6Bsehfpb+/6aqHOtuw8ga0w5oI9jQARHQ1uPvttf17CrCiNnToxzROTu9MDd7upzrvFQA/xdvjhHRHqTHnN/Mhs+rx97tu7rHi8pL8Rdv5rPIjp9IxbRiYiIiIiIAChEJZRGE8JSCIGONgCAJi0DSr0BCq54jr9wGI59+2EdMQzZF0yG5PMDkQhErRYQFWj/7HPYzqqQO8qUE+zyRp2T/EGA3Vzizu/sijoXCUd6rVCn2PumInnIH4xTJPR16XYbFvziv+HocMLZ7oLRYoTFZmIBnb4VFtGJiIiIiIgASIEAXNUHEfZ/VfzoaqyD2N4K06AyKFTsYRtPSo0GacPK0bb1M/jbO44PqtVAIABRp4V9ciUUapW8QaYgS0keWj77ss85Q04GBJFtj+ItrTAr6pw+zQRRxdJPvFntaYAgdO8b8HUqrRpaE2/XkIvJaoTJagRK5I6EzkRxcTFqanrfGTVv3jz87ne/i8kx+duNiIiIiIhSXiQSQdDZ0aOAfoLk9yHgSqz9SFJF0On6qoAOAIEAAEDy+uCqPsKe6DLQpVugS+970/aCqeMgqHhO4k1t0iGzLL/PuRFXToTWaohzRKTSqDDqwrP6nJt4zWSoubEoJRmvy4tjR1tRv/8o2o4eg9cV/a6l/rBt2zY0NjZ2/3v77bcBALNmzYrZMXk5kgY0hY9/zHwbfJ6IiIiITi4iheD/dwuXvgTaj0FtToNCyT+h4iUcCMBdexQKtRqmkiKo06xAJIKQ1wvX4SPoqm+EaVAxRBVXo8dT275qDL7qQjR+8jna9lYjIknQZ9lQcME4uBtaoTbqAdZs46r9cCPG/2AaDv5rJ6o//AIhfxDGLCtGzpwIY6YVnlYHrPmZcoeZUtrqj2HcZRNgtadh2+ufwOvsgindjMnXTkFaTjpcrQ6Y2UKEkoSj1YHXn3wV1TsOdY8NGjMYl/3PTFgy+77oeqYyM3u+pz388MMoLS3F+efHbiNlZoA0IFksFqjUGuDwRrlDGTBUag0slti8eRERERElPwEQ5I4h9Yg6DTLHj0Xn/oNw7D8IAFCZTEirGAZPYxMEnpS4k3wBfPHn11Aw5Wxknz0cEUQg+QKo37wD7oZW2MqL5A4x5YT8Qfxz+RpM+tFMlE4ZhUg4AkEh4OjOKmx55h/4zqLvyx1iyhEUAv501x8w4cqJuH7x9yEoBIRDYXz21na8ueJ1zP3NbXKHSNQvvC5vrwI6ABzecQhvPPkqrrpnFnQmXUxjCAQCWLNmDe666y4IQuzyAhbRaUCy2+1Ys/rPcDgSa4V1TU0Nli9fjvvuuw9FRYmVPFosFtjtdrnDICIiIkpICqUKGlsmuup799cEAE16JhQi/3yKJ4VaDfOgEjRt+gjhf7dxAYCgy4XWrZ8ie8pEKDRsiRBvtqHFaNr2BWre+aTPOYWGdwbEW8bgPIhqFdqrm5BWlIWIFIagUMDd3AFbSTZUWv6cxJsl0wqVRoVPXvkIn7zy0X/MWaBjT3RKEh6Hu1cB/YTDOw7B43DHvIj+yiuvoLOzEzfeeGNMj8MskAYsu92esEXhoqIilJWVyR0GEREREZ0ClckCUaeH5O3qMS7qDFAaTTJFldq8zS09CujdIhE4DlTBNnokRNYH40qp1yJz1BC07j4IlVEPUaOGr8MJpVaN/MljEAmG5A4x5QiiAlP+5ypsX/0OPn/lQwCAQlSg9PxROOfGSwCE5Q0wRV1003fw1h/+Aa1BA3OGBZ1NHQiFJFx00yW8s4mSht/jP6P5/vDss89i+vTpyM3NjelxWEQnotPCPuvfHp8rIiKigUFUq2EsHoyQ2wV/eysAAZr0DCgNJogqVmrjLeT3w9dyLOq8v70DEYkF23hr2roHuZNGI2fCCPg6XAj5AtBnpkGhVqFt32GklxfLHWLKCfmD2LLydXiOObvHwlIYB9/bCZVei6IJ5TJGl5ra6tvg6fTgv5/+MdwdbjhbHUjLsUFn0mHzSxthzjAjLdsmd5hEZ0xj0JzR/JmqqanBO++8g7/97W8xPQ7AIjoRnSL2oz897ElPREQ0MIgqNcS0dKjMVgCAQhTlDSiFCUolRJ026ryo1cS09yn1LeOsIfC1deLQq+9D8ge7x23DS1AwZSwi4YiM0aWmgMfXo4D+dQff+QyF41hEjzdzphmWTDPWLVmDzuaO7vHs0hzMvOsagD8mlCQMFiMGjRmMw320dBk0ZjAMFmNMj79q1SpkZWXhsssui+lxABbRiegUsR/96WFPeiIiooGFxXP5iaIIU0kR3Edq+5w3DxkElTG2f5xTb0qlCvtefhMRSeox3r63GvpMG+xnD5UpstTlbGyLOhf0BSCxxU7cqTVqrHugZwEdAJqqGvHPZ97EpT++QqbIiPqXzqTDZf8zE288+WqPQvqgMYNx+R0zY9oPPRwOY9WqVZgzZw6UytiXuFlEJ6JTxn70RERElOzC/y4QspguH0mS4Hc4kTZiGDq++BKIfLV001CYD0FQIOjxQGUwyBhl6uk8fLRXAf2Epm1fwFZeBKWN7Y/iyZBujjqn1KggKhVxjIYAwOvyor2+74sb1TurEPT1sdcD0QBlybTgqntmweNww+/xQ2PQwGAxxnxD0XfeeQe1tbWYO3duTI9zAovoRERERERE/yYFfJC8Xvg7jhc/NGnpELV6iJrY9vSk3iKhELz1jRCUSmRVnoOg242IJEFtscB3rA3tu/cg+/xJcoeZcnwdfbcNAYBQl49tKmRgzLRCZzXA2+npNVc8sQIKFUs/8dbl7H0uvi7gjf1mi0TxpDPpYl40/0/f+c53EInE75cOL0cSEREREREBkPx+eOqOwF1ThaCzE0FnJ9w1VfDUH4HkZ8Ej7kQRmnQbuuob0Ln3SwCAQqmEq+ownAcOQW21QqFgcTDeTPnR70jVpVsA9qmPO6VGhXNvuRTGLOtXgwJQMK4MpeeNhBCHNgfUkzkj+n5YolKE1hjfYiMRnTm+kxIREREREQEIup0Iedy9xkNuF0Jdbq5GjzOlUgl9bjZUJgOCbg/cNXVAOAydPQumwYOgUKkgaNk2JN4MORlQGXUIur295vKnjIVojL4ZLMWGFAihq8ONcd+/CFIghKAvAI1RD6VGhdrt+zFo0gi5Q0w5ap0Gg8aU4vCOql5zoy8eCxXfu4gGnKRcie5yubBgwQIUFRVBp9Nh4sSJ2LZtm9xhERERERGlnIGSm0uBAPztxwBBAY0tA4bCEhgKS6BOSwcEBfztrZCC7GEbT+FQCJLfD+fBw+j84ksEHU4EXW44Dx1G26e7AEFAuKt3IZdiKyIIGHrdJTDmZ3WPKfValHx3InRZaZD6KK5TbB2rasAnz76J9poW6G0mWPMyodap8cVrW7DvH1vZf1sGrlYHpt38XVScPxIK8XjpTalWYvyMczH6O2fD09H7gi0RJbakXIl+yy23YM+ePVi9ejVyc3OxZs0aTJs2DXv37kVeXp7c4RERERERpYyBk5tHoFAqoS8uha/9GDx1RwAAarMVpuJS+Npa2es5zsKRyPH+9O0dveYknw+emjqYywbLEFlqa9tbhcwRQ1B44TkQFAIiIQkKlRIKpRLO6kaYi3PkDjHlSFIIF//se2j4vBobH/sbfM4upBVmYcTMScgZWYJImG9e8RYMBLHu7jX4zm3TUXnVJAT9Qai0atR8fgTP/r+VuPGRm+UOkYhOUdIV0b1eL15++WW8+uqrmDJlCgBgyZIleO2117BixQosW7ZM5giJiIiIiFLDQMrNBaUKOnsuXNUHEZFC3eMBRweCHhdMxUPYVzjOFKIIT31j1PmuhiYW0WWQMawUh9a/B09TW49xQSFg2PcuhUKjkimy1JU9rAg7/+8DNH5+uHuso7YFHzy5HhNvvxxaM/tvx5vFbkUoJOH1J17tNac366Ez62WIiojORNK1cwmFQpAkCVptzz5sOp0OmzdvlikqIiIiIqLUM5Byc0EAAo7OHgX0EyKhEAIuJwRumBhXAgBBOMmfrAoBiHCFbbz5O5y9CugAEAlHULdxOyKhsAxRpbagN9CjgP51u17+AKFA7/c1ii1RpcTk687vc27azd+FUs2LskQDTdIV0U0mEyorK/Hggw+ioaEBkiRhzZo12LJlCxob+17F4Pf74XQ6e/wjIiIiIqIzM5By80hIQtDVGXU+6OxARJLiEgsdJwWD0OfnRp035OciwusacddRVRd1zlXXzJ8TGRyraog65znmQIg90eOurbYV2SXZ+K+fXY+88nwYrAYUjyrB95ffiKAvAFerQ+4QU1Zbczvqquqxb8cB1BysQ2vDMblDogEiKS99rV69GnPnzkVeXh5EUcTYsWNxww034NNPP+3z8x966CEsXbo0zlESERERESW/AZObCwIEhRh9WhSPL1enuFGIIgRRhM6eBW9zS485pdEAXVYmV6LLQKXVRJ1TqJKyxJDw1Hpt9EkBUCijv7dRbKh0aqxe+CfkD83HpGvPh9aghafTjTd//wba6lpx82//W+4QU1JzfSvWPP4Stv1rByL//v1RMW4obrtvDrILsr7hqynVJd1KdAAoLS3Fxo0b4Xa7UVdXh61btyIYDGLQoEF9fv7ChQvhcDi6/9XVRb+yTkRERERE395Ayc0VSiW0mfao89oMOxQiC1HxpFAqoVApocuxI33sWdDaM6HJSEfaiGFIqxiGoNsNhfYkxUOKibShxVHnMkaUQqlTxy8YAgDYiu1RC+XZFcVQanhO4s2YZoTerMfRL4/ipQfX4s/3PouXH/4L2upakVmUBY2B713x1tbSjhee+iu2vvdZdwEdAL7Y/iWeXvIsWupbZYyOBoKkLKKfYDAYkJOTg46ODmzYsAEzZ87s8/M0Gg3MZnOPf0RERERE1H8GQm6u1BuhsqT1GldbbVDqDHGLg46TJAkKtRpBpwudXx6AymCA2mKGp64ezqpq6LKyEAmwTUW8KVRKFF44vte4LjMNOeeMgOQNyhBVahPVKpxz43cgKHreLaNPM2H0NVMgCeyJHm9qswZX/eTaXr3PdSYdrlhwNfRp3Fg03rpcXnzy7vG74O546HasePPXuO93dwEA9u86BI+rS87waABIynutNmzYgEgkgvLychw6dAj33HMPhg4diptuuknu0IiIiIiIUspAys0VKhUMuYUIZ9rh72gHBEBjTYdCrYZCqZI7vJQTCUno/Hwv0kZVwFhUAE9dPcKShLSRwyHq9Wj+ZDuyJpwtd5gpp2nrHuRMGAFzUQ7a9h1ByOuFtbQA+sw0tB+uQ1pxvtwhppyjnx1E3tjB+M59s3F0xyF0tbuQVZ4PW3E2IoIAyRUAel8fpBhq3NeAnLJc3PLYj3Bo+wEcq2tFzpA8FI8sgc6mR2t1CwqGFcodZkrpcnfhp7+9A/b8LBz6ohqv/fkt5JXk4tG/LoPP60NHmwMlcgdJ35okSViyZAnWrFmDpqYm5Obm4sYbb8T9998fs43gk7KI7nA4sHDhQhw9ehQ2mw3XXHMNli9fDpWKiS8RERERUTwNtNxcoVJBoVJBqTfKHUrKE5QiLMOGwF1bB3fVERgHFUFUatC283MoDXpkjRt7vFc9xZX97GFwVDeg5u2PYczLgkKlwpF/fgy1UYfBM6eyTb0MzNlp+MfP/gTYgKsf+DEEQYDf48PrP3kGSo0K0xbeIHeIKceSZUHDl0fxym9exm2/m4+xZgM6m9rx54XP4oo7r4HVbpU7xJSTXWhHZ6sDi295GM4OV/e4Vq/FwicWYPAIltDPhNvpgaPdiS63FwajHmabCUZz7O7ie+SRR7BixQo8//zzqKiowPbt23HTTTfBYrHgjjvuiMkxk7KIfu211+Laa6+VOwwiIiIiopTH3JxOlyiKCEYA5/5DAADngaruuZDbA1/2MZgH991bn2IoAhzZsAUA4Kpr7h4OurvQ/Ok+5E4aLVNgqcuYZYXOaoS33Y2//fipHnOl542EyhB9M1iKDaVaiX/87jUEfQH87ubf9ph77/l/YtbPeGEj3nweH363+I89CugA4Ovy4bc/XYElz/wUZotJpugGtrbmdvz+weew++MvusfOOncEbl80B+l2W0yO+dFHH2HmzJm47LLLAADFxcV48cUXsXXr1pgcD0jSIjoRERFRX3w+H2pra/vlsWpqanr8t78UFhZCy43yiIgQliS4Dkd/j3UdPgJdTjZUBvYWjqf2/dHPSevug7CPHQaVjkXbeAr5Qzjvf67Elxu2IX9sGVQaFdytneisa0Xp1LMQcPugM3Ffh3jq6vTA0+nGtYtmI6s4C6FgCCqNGl9s+hzvrfonfB6f3CGmnC63FzUHj/Y519nmgLPdiZzC6BuMU9/cTk+vAjoA7Pp4D/7w4PO44xe3xWRF+sSJE7Fy5UocOHAAZWVl2LVrFzZv3oxHH3203491AovoRERElDJqa2tx22239etjLl++vF8fb+XKlSgrK+vXxyQiGogi4TDCwegbh0qBINg7JP6CXd6oc1IgiAjPSdy1HjiKjCG5yBs9GPv/uR0+hwe2kmwMu2QcDm/ejYKzy+UOMeX4PD7Me2YBOhvb8frjr6CzuQMZhVmYfO35mPfHBehqd8sdYsoJ+E++6XFXFy9snA5Hu7NXAf2EXR/vgaPdGZMi+r333gun04mhQ4dCFEVIkoTly5dj9uzZ/X6sE1hEJyIiopRRWFiIlStXyh3GSRUWcpMpIiIAEFUq6Ox2eJta+pzXZqZDoU7M3vrJzFqSh5bPvuxzzpibCYWSferjLbuiGAf/tQNVG3d3j3nanKjfWYUpd1wFtYF3uMVbVnE29m3eg3f+tKF7rLO5E4e2H8Q1P70WJaNLZYwuNZksRmh0Gvi9/l5zgkJAZna6DFENfF3u6BdWAcD7DfOn66WXXsLatWvxwgsvoKKiAjt37sSCBQuQm5uLOXPmxOSYLKITERFRytBqtVzlTUQ0gOjsGRB1WkjenisEBYUClvIhgCDIFFnq0qZboctMg7e1o+eEIKBg6jhAzSJ6vIVDUo8C+tfHd/zlfUyeN0OGqFJb0B/Av1a/23siEsFbv38DP3x4LrS8uBFXZpsRV910KdY9vb7X3IVXToGO5+O06I26k87rvmH+dN1zzz249957cf311wMARo4ciZqaGjz00EMxK6IrYvKoRERERERERGdACoXgrK6BfdK5MBTkdxfMtZkZyD5/Elw1dQj7o7d7odjoPFKPsqsvRNbo8u5V54acDAy74bsQRAHhLp6TeGs9VB91zlF/DEEvz0m8OVo6IQVDfc55Ot3wxWh1LkVnNBsx8TsTcPuiG5GZc3zVuSXdjNn/OwtX3nhpzDbATHYWmxlnnTuiz7mzzh0Bi80ck+N2dXVBoehZ1hZFEeFwOCbHA7gSnYiIiIiIiBKQAEBQqRAJh6E0GpB5zlgAAoIeD6RgEEodVw3KIehw44vVf8fQ6y9F9viK433pFQKaP/sSLZ99iZG3XCl3iClHIX7D6n/esRF3CvHka1YFBde0ysGenwl7fiaGjSlDWJKgUIiwZVuh0XAz5NNlNBtw+6I5+MODz2PXx3u6x886dwRuXzQnJv3QAWDGjBlYvnw5CgsLUVFRgR07duDRRx/F3LlzY3I8gEV0IiIiIiIiSkAKpRLG/Fw0/WszwsH/2BBOEJA9dTJEfWxuE6fobEOL0fjJHuz506u95tIrBkHJPvVxl1GaA0EQ+tzUNb00B0oNz0m8mdItUOvUCPRxF4DVboWGrUNklVNolzuEpJJut+GOX9wGR7sTXrcXOqMOFps5ZgV0AHjyySexaNEizJs3Dy0tLcjNzcXtt9+On//85zE7Ji99EREREZ0iSZKwY8cOvPvuu9ixYwckSZI7JCKipNRV39i7gA4AkQgc+/ZD8vl6z1FMRcIRZI4aAgBQajVQmwyAIEBl1CFzVFnUFhYUOwqliBFXTuo1rtKqMea6C6BQcv1kvKn1Klw6/4pedwGIShGX/c9MmDJMMkVGFBtGswF5xTkYPGIQ8opzYlpABwCTyYTHHnsMNTU18Hq9qKqqwrJly6BWq2N2TL6TEhERxZnP50NtbW2/PFZNTU2P//aHwsJCaLVcHRPNpk2b8PTTT6Opqal7LDs7G/PmzcOUKVNkjIyI+kNYkhAJBSF5vYAAiFodBKXqm9slUL8L+f3wH2uPOu/vcCDCi5hxd2zPIVhL85E9bji6WjsQ8gVgyE6HqFZh/8vvYeisaXKHmHIaP69G7lmDkFGai0Pv74TP4UFGaS6Kzh2Gpi9rkVmaB701tgUt6qnpUBPyh+fj5kdvw/Z/bENHYzvsJdkYc8nZ0Bq0aK5qQsGwQrnDTEmdxxw41tyGproWZGSnIys3A7asNLnDogGARXQiIqI4q62txW233davj7l8+fJ+e6yVK1eirKys3x4vmWzatAmLFy9GZWUlFi1ahJKSElRXV2Pt2rVYvHgxli5dykI60QAWDoXgb2+Ft6nnJn363AKorelczRlnglIJ8SR9z5VaDQSBN1fHm3VIERCW8MXqNxD+2qrztLIilF01FQL7b8ddRlkugh4fdv7fRlTMOBcqjQqd9W3YvuZdjP/hxYjEcKM96pverMdTcx/D4AnlmPG/VyLkDUCl1+CZ/7cCrgYHbn1intwhpqSWhmP45Z1PoK7qq9/zGdnpuO93dyK3KEfGyGggYBZIREQUZ4WFhVi5cqXcYURVWMhVMX2RJAlPP/00KisrsWzZsu7d4CsqKrBs2TLcf//9WLFiBSZNmgSRK1aJBiTJ5+1VQAeAroY6KHUGKJRGGaJKXaIowjSoGO4jfd+9ZR5SCpWRq2vjTWs24PNVryIi9SzMdhyogcFuQ/b44TJFlrpUajXe/e06BLr82PxUz171+97cilFX9W71QrGltxhgtafh0Cf78dvvPdJjrnBEMbRG3vUZb26HByuW/qlHAR0AjjW14Zd3PonFK3+CtAyrPMHRgMAiOhERUZxptVqu9B6Adu/ejaamJixatKi7gH6CQqHA7NmzMX/+fOzevRtjxoyRKUoiOl1hSYKvpREAoFCroTKaEYkAIbcT4WAA3tYmGHQlUCh4kSyeFBo10seMQueXB6DLygQUCviPtUGTkQ5Nuk3u8FJSR1VdrwL6CU2f7oNtWAl0ttj1pKXeHA1tCHT5odSokDOiBGq9Bs6mdrQerEfttv0Yesk4aGPcn5h6suXYMOu+G7BuyWq42l3d4xkFmbjsx1fAkmmVL7gU5ehwYu+n+/uca6xthqPNySI6nRSL6ERERETfQnv78b68JSUlfc6fGD/xeUQ0wETCCIdCMOQXIxIJI+h0AAC0WTmAAPjbjwHhCMDuIXGl0usBexbS9Tq4Dh9BJByGpXwINOk2rkKXib/TFXUu1OUDInEMhgAAnnYnSqeMQvbwItR9dhCulk6kD8rF0EvGY/ffPoAU4GavcrCXZOP7D92EzqZOdDS1IyM/E5ZMC9JyeAFQDn6v/6TzbldXnCKhgYpFdCIiIqJvwWY7/gdPdXU1Kioqes1XV1f3+DwiGlgEhQh9Tj68zfUIdXm6x4MuB5QGI/TZeRAUrKDHW8jnR8fne9FV39A95mtuhcpsgn3SuVDqdTJGl5pMBdlo2dH3ak5dhhWCgj3R4y1zSB6kQAgf/v617rGW/XWo+mA3Km+5FEod7wyQS3puBtJzM+QOgwAYzAaIShFSqO8NqW1chU7fgFkgERER0bcwatQoZGdnY+3atQj/xwZd4XAYa9euRU5ODkaNGiVThER0JgSFAlIw0KOAfkLI40Y4GGQRXQZBp6tHAf3r4+7ao4hEuOw53gzZ6VCb+r4LIH/KWCgN7PUcb0qVCl/8fUuv8WCXH3v/8QlUWpUMURElFmu6GZdce2Gfc+dcMBbmNFOcI6KBhivRKeX5fD7U1va9WdGpqqmp6fHf/lBYWAitloko9T++9olOjSiKmDdvHhYvXoz7778fs2fPRklJCaqrq7F27Vps2bIFS5cu5aaiRANUOBSCv6016ry/vRUqswUKkX9CxUskHIarqjrqvLu6BsbiAiiZL8SV43A9ymdNQ827W+GsOb6PgMqgQ8H5Z0MKBBHy+KBUc+VzPHXUtkS9oHTsUAOC3iC0rA9SitNoNZg5ZzrUGjXefPFt+H0BKFVKTJ0xCdfcegWMFrYIo5NjBkgpr7a2Frfddlu/Puby5cv77bFWrlzJDQgpJvjaJzp1U6ZMwdKlS/H0009j/vz53eM5OTlYunQppkyZImN0RHRmIkCk780SARwvUHHRc1xFAEROdk7CYYAr0ePO1+lC47YvUHTROSi8YBzCUhiCIKB5x5c4tqcKo269Su4QU0609hQnRMLRf46IUok13YL/unUGLrpqCvxePzRaNSzpFmi0vPBH34xFdEp5hYWFWLlypdxhRFVYWCh3CJSk+NonOj1TpkzBpEmTsHv3brS3t8Nms2HUqFFcgU40wAmiEuq0dHgbj/Y5r0lLh0LJP5/iSaFQwFhUCG9jc5/zhoJcKLjiOe5sZUVo3r4XB//2Xq85y6B8iBqek3jLKM2JOmfJy4CaLXaIuqnUKmSxTz2dBmaBlPK0Wi1Xu1JK4muf6PSJoogxY8bIHQYR9SNBEKC22OBva0E4EOgxp1BroDJZ5QksxWlsVqitFgQ6HT3GFRoNTKUlUPACZtxpLEZYBuXDcbjnBSeFSomCqWdDbeBmr/GmNesx5ILROPivnT3GFaICZ3/vQmhNenkCIyKKIZfLhUWLFmH9+vVoaWnBmDFj8Pjjj2P8+PExOR6L6ERERERERABEtRqmQeXwt7ch0NkG4PgKdHVaBkSueJaFUqdD1sRz0FXfCNfhI4hIEvR5uTCVlkBlYGFQDhqLEcWXVMJx+CiaP/sSkj8Ac1EOciaMgNbKxttyUOu1GHbpOcgsz8e+N7fB5/QgozQXwy89B8ZMq9zhEVEKcHS60N7WAZfTDZPZCFt6Giwx/p1wyy23YM+ePVi9ejVyc3OxZs0aTJs2DXv37kVeXl6/H49FdCIiIiIion8T1Rro7DnQph+/1VtQqiAIgsxRpTalTgdTaQn0+blABBDVKghcgS4rrcUI7ZihsA7KRyQShlKnhZJtXGSlNemRP3owMgfnISxJUGo1UGlUcodFRCmgqaEFS376S3y0aVv32MQp47HkkZ8gOzcrJsf0er14+eWX8eqrr3bvS7VkyRK89tprWLFiBZYtW9bvx1T0+yMSERERERENYIIgQKFSQ6FSs4CeIARBgFKrhVKnZQE9gWgsRmitZhbQE4jGqIPOYmQBnYjiwtHp6lVAB4CPNm3Dkp/+Eo5OV0yOGwqFIEkStNqeez7odDps3rw5JsdkEZ2IiIiIiIiIiIiITkl7W0evAvoJH23ahva2jpgc12QyobKyEg8++CAaGhogSRLWrFmDLVu2oLGxMSbHZBGdiIiIiIiIiIiIiE6Jy+k+6bz7G+bPxOrVqxGJRJCXlweNRoMnnngCN9xwAxSK2JS7WUQnIiIiIiIiIiIiolNiMhtPOm/8hvkzUVpaio0bN8LtdqOurg5bt25FMBjEoEGDYnI8FtGJiIiIiIiIiIiI6JTY0tMwccr4PucmThkPW3pazGMwGAzIyclBR0cHNmzYgJkzZ8bkOElZRJckCYsWLUJJSQl0Oh1KS0vx4IMPIhKJyB0aEREREVHKGKh5eSQSQTgYRDgYSPhYieQU9HgRcHchHAzJHQoREcnAYjVhySM/6VVInzhlPJb88iewWE0xO/aGDRvw1ltvobq6Gm+//TYuuOACDB06FDfddFNMjqeMyaPK7JFHHsGKFSvw/PPPo6KiAtu3b8dNN90Ei8WCO+64Q+7wiIiIiIhSwkDMy6WAH/72Ywh0tgEANGkZUKdlQFSrZY6MKHEE3F3oPFyPpq17IPkDsAzKR86EEdBaTRBi1IuWiIgSU3ZuFh55cjHa2zrgdrphNBthS0+LaQEdABwOBxYuXIijR4/CZrPhmmuuwfLly6FSqWJyvKQson/00UeYOXMmLrvsMgBAcXExXnzxRWzdulXmyIiIiIiIUsdAy8ulQACuqv0IBwPdY97mBvg72mAaVM5COhGOrz6vfusjdB6q6x5r3XUAbXsPo2LODOgzrPIFR0REsrBYTTEvmv+na6+9Ftdee23cjpeUl4gnTpyId999FwcOHAAA7Nq1C5s3b8b06dNljoyIiIiIKHUMpLw8Eokg4GjvUUA/IRzwI+jsjH9QRAnI1+nqUUA/IRwMoe5f2xHy9/4ZIiIiGuiSciX6vffeC6fTiaFDh0IURUiShOXLl2P27Nl9fr7f74ff7+/+2Ol0xivUbj6fD7W1tf3yWDU1NT3+2x8KCwuh1Wr77fGIgMR/3QN87RMREZ2JU83LAfly84gUQqCjLeq8v6MNaqsNCmVS/glF9K11HIieb3dW1UHyBaDU8K4NIiJKLkmZAb700ktYu3YtXnjhBVRUVGDnzp1YsGABcnNzMWfOnF6f/9BDD2Hp0qUyRPqV2tpa3Hbbbf36mMuXL++3x1q5ciXKysr67fGIgMR/3QN87RMREZ2JU83LATlzcwEQot+oKygEQIhjOEQJShDFk8wpAIE/KERElHyESBJuN19QUIB7770X8+fP7x5btmwZ1qxZgy+//LLX5/e12qWgoAAOhwNmszkuMffnitxY4GpcioVEf90DfO0TEVH/czqdsFgscc015XKqeTkgb27ubz8Gz9Ejfc4ZCgdBY7XF9PhEA4GnpR17/vRqn3MZIwej+DuVEFVJuV6PiCip+Hw+VFdXo6SkJOnrHif7Xr9tbp6Uv9m6urqg+I8dwUVRRDgc7vPzNRoNNBpNPEKLSqvVcrUrpRy+7omIiJLbqeblgLy5udJkhlJvRKjL3XPcaILKYJQlJqJEozHpkTNhBBo/2dNjXG0yIG/SaBbQiYgoKSXlb7cZM2Zg+fLlKCwsREVFBXbs2IFHH30Uc+fOlTs0IiIiIqKUMdDyclGlhrFoEEJdHvjbjwEANOmZUOr0UKjY45kIAJQ6LXImjERaWRGat+9F0OtH+tBiWEryoLHwYhMR0UCThE1KeumP7zEpi+hPPvkkFi1ahHnz5qGlpQW5ubm4/fbb8fOf/1zu0IiIiIiIUsZAzMsVKjXUFjVUJgsAQFBE75NOlKpUei1Uei0M2emIhMMQVSq5QyIiolOk+vd7d1dXF3Q6nczRxFZXVxeAr77n05GUPdHPVCr1qSQiIiKi+GKueWr4fBERERHFRmNjIzo7O5GVlQW9Xg8hyTaHjkQi6OrqQktLC6xWK3Jycnp9Tkr3RCciIiIiIiIiIiKi6LKzswEALS0tMkcSW1artft7PV0sohMRERERERERERGlGEEQkJOTg6ysLASDQbnDiQmVSgVRFM/4cVhEJyIiIiIiIiIiIkpRoij2S6E5mXGXHCIiIiIiIiIiIiKiKFhEJyIiIiIiIiIiIiKKgkV0IiIiIiIiIiIiIqIo2BO9D5FIBADgdDpljoSIiIiIks2JHPNEzkknx9yciIiIiGLl2+bmLKL3weVyAQAKCgpkjoSIiIiIkpXL5YLFYpE7jITH3JyIiIiIYu2bcnMhwiUwvYTDYTQ0NMBkMkEQBLnDOWVOpxMFBQWoq6uD2WyWO5yUwudePnzu5cXnXz587uXD515eA/n5j0QicLlcyM3NhULB7orfRK7cfCC/xpIVz0ni4TlJPDwniYfnJDHxvCQeuc7Jt83NuRK9DwqFAvn5+XKHccbMZjPfCGTC514+fO7lxedfPnzu5cPnXl4D9fnnCvRvT+7cfKC+xpIZz0ni4TlJPDwniYfnJDHxvCQeOc7Jt8nNufSFiIiIiIiIiIiIiCgKFtGJiIiIiIiIiIiIiKJgET0JaTQaLF68GBqNRu5QUg6fe/nwuZcXn3/58LmXD597efH5p1jjayzx8JwkHp6TxMNzknh4ThITz0viSfRzwo1FiYiIiIiIiIiIiIii4Ep0IiIiIiIiIiIiIqIoWEQnIiIiIiIiIiIiIoqCRXQiIiIiIiIiIiIioihYRE8iK1aswKhRo2A2m2E2m1FZWYk333xT7rBSzsMPPwxBELBgwQK5Q0kJS5YsgSAIPf4NHTpU7rBSRn19Pb7//e8jPT0dOp0OI0eOxPbt2+UOKyUUFxf3eu0LgoD58+fLHVrSkyQJixYtQklJCXQ6HUpLS/Hggw+C28zEh8vlwoIFC1BUVASdToeJEydi27ZtcodFSYQ5dWJjrp0YmIMnJubmiYX5euJhHp+YBkp+r5Q7AOo/+fn5ePjhhzFkyBBEIhE8//zzmDlzJnbs2IGKigq5w0sJ27Ztwx/+8AeMGjVK7lBSSkVFBd55553uj5VKvrXFQ0dHByZNmoQLLrgAb775JjIzM3Hw4EGkpaXJHVpK2LZtGyRJ6v54z549uPjiizFr1iwZo0oNjzzyCFasWIHnn38eFRUV2L59O2666SZYLBbccccdcoeX9G655Rbs2bMHq1evRm5uLtasWYNp06Zh7969yMvLkzs8SgLMqRMXc+3Ewhw8sTA3TzzM1xMP8/jENFDyeyHCyy1JzWaz4Ve/+hVuvvlmuUNJem63G2PHjsXTTz+NZcuWYfTo0XjsscfkDivpLVmyBK+88gp27twpdygp595778WHH36IDz74QO5QCMCCBQvw+uuv4+DBgxAEQe5wktrll18Ou92OZ599tnvsmmuugU6nw5o1a2SMLPl5vV6YTCa8+uqruOyyy7rHzz77bEyfPh3Lli2TMTpKZsyp5cdcO7EwB088zM0TH/N1+TGPTzwDKb9nO5ckJUkS1q1bB4/Hg8rKSrnDSQnz58/HZZddhmnTpskdSso5ePAgcnNzMWjQIMyePRu1tbVyh5QS/v73v2PcuHGYNWsWsrKyMGbMGDzzzDNyh5WSAoEA1qxZg7lz5zIhj4OJEyfi3XffxYEDBwAAu3btwubNmzF9+nSZI0t+oVAIkiRBq9X2GNfpdNi8ebNMUVEyY06dOJhrJx7m4ImFuXliY76eGJjHJ56BlN/zfqsk8/nnn6OyshI+nw9GoxHr16/H8OHD5Q4r6a1btw6fffZZQvZsSnYTJkzAc889h/LycjQ2NmLp0qU477zzsGfPHphMJrnDS2qHDx/GihUrcNddd+FnP/sZtm3bhjvuuANqtRpz5syRO7yU8sorr6CzsxM33nij3KGkhHvvvRdOpxNDhw6FKIqQJAnLly/H7Nmz5Q4t6ZlMJlRWVuLBBx/EsGHDYLfb8eKLL2LLli0YPHiw3OFREmFOnViYayce5uCJh7l5YmO+nhiYxyeegZTfs51LkgkEAqitrYXD4cBf//pX/PGPf8TGjRuZ9MdQXV0dxo0bh7fffru7P+PUqVN5i6lMOjs7UVRUhEcffZS3XMeYWq3GuHHj8NFHH3WP3XHHHdi2bRu2bNkiY2Sp55JLLoFarcZrr70mdygpYd26dbjnnnvwq1/9ChUVFdi5cycWLFiARx99lH+kxkFVVRXmzp2LTZs2QRRFjB07FmVlZfj000+xb98+ucOjJMGcOnEw1x4YmIPLj7l5YmO+nhiYxyemgZLfcyV6klGr1d1Xas4++2xs27YNjz/+OP7whz/IHFny+vTTT9HS0oKxY8d2j0mShE2bNuGpp56C3++HKIoyRpharFYrysrKcOjQIblDSXo5OTm9ignDhg3Dyy+/LFNEqammpgbvvPMO/va3v8kdSsq45557cO+99+L6668HAIwcORI1NTV46KGHmHzHQWlpKTZu3AiPxwOn04mcnBxcd911GDRokNyhURJhTp04mGsPDMzB5cfcPHExX08czOMT00DJ79kTPcmFw2H4/X65w0hqF110ET7//HPs3Lmz+9+4ceMwe/Zs7Ny5k0l9nLndblRVVSEnJ0fuUJLepEmTsH///h5jBw4cQFFRkUwRpaZVq1YhKyurxyYsFFtdXV1QKHqmUKIoIhwOyxRRajIYDMjJyUFHRwc2bNiAmTNnyh0SJTHm1PJhrj0wMAeXH3PzxMV8PXEwj09siZ7fcyV6Elm4cCGmT5+OwsJCuFwuvPDCC3j//fexYcMGuUNLaiaTCSNGjOgxZjAYkJ6e3muc+t/dd9+NGTNmoKioCA0NDVi8eDFEUcQNN9wgd2hJ784778TEiRPxi1/8Atdeey22bt2KlStXYuXKlXKHljLC4TBWrVqFOXPmQKnkr/R4mTFjBpYvX47CwkJUVFRgx44dePTRRzF37ly5Q0sJGzZsQCQSQXl5OQ4dOoR77rkHQ4cOxU033SR3aJQkmFMnFubaiYk5eOJhbp6YmK8nFubxiWmg5Pf8CU4iLS0t+OEPf4jGxkZYLBaMGjUKGzZswMUXXyx3aEQxc/ToUdxwww1oa2tDZmYmJk+ejI8//hiZmZlyh5b0xo8fj/Xr12PhwoV44IEHUFJSgscee4ybssTRO++8g9raWiZ9cfbkk09i0aJFmDdvHlpaWpCbm4vbb78dP//5z+UOLSU4HA4sXLgQR48ehc1mwzXXXIPly5dDpVLJHRolCebURN+MOXjiYW6emJivJxbm8YlpoOT33FiUiIiIiIiIiIiIiCgK9kQnIiIiIiIiIiIiIoqCRXQiIiIiIiIiIiIioihYRCciIiIiIiIiIiIiioJFdCIiIiIiIiIiIiKiKFhEJyIiIiIiIiIiIiKKgkV0IiIiIiIiIiIiIqIoWEQnIiIiIiIiIiIiIoqCRXQiIiIiIiIiIiIioihYRCcion63ZMkSjB49uvvjG2+8EVdeeaVs8RARERERpSLm5URE/UMpdwBERJT8Hn/8cUQike6Pp06ditGjR+Oxxx6TLygiIiIiohTDvJyI6PSwiE5ERDFnsVjkDoGIiIiIKOUxLyciOj1s50JElGI8Hg9++MMfwmg0IicnB7/5zW8wdepULFiwAAAgCAJeeeWVHl9jtVrx3HPPdX/805/+FGVlZdDr9Rg0aBAWLVqEYDAY9Zhfv230xhtvxMaNG/H4449DEAQIgoDq6moMHjwYv/71r3t83c6dOyEIAg4dOtQf3zoRERERUcJgXk5ENHCwiE5ElGLuuecebNy4Ea+++ir++c9/4v3338dnn312So9hMpnw3HPPYe/evXj88cfxzDPP4Le//e23+trHH38clZWVuPXWW9HY2IjGxkYUFhZi7ty5WLVqVY/PXbVqFaZMmYLBgwefUnxERERERImOeTkR0cDBIjoRUQpxu9149tln8etf/xoXXXQRRo4cieeffx6hUOiUHuf+++/HxIkTUVxcjBkzZuDuu+/GSy+99K2+1mKxQK1WQ6/XIzs7G9nZ2RBFETfeeCP279+PrVu3AgCCwSBeeOEFzJ0795S/TyIiIiKiRMa8nIhoYGFPdCKiFFJVVYVAIIAJEyZ0j9lsNpSXl5/S4/zlL3/BE088gaqqKrjdboRCIZjN5jOKLTc3F5dddhn+9Kc/4ZxzzsFrr70Gv9+PWbNmndHjEhERERElGublREQDC1eiExFRD4IgIBKJ9Bj7el/FLVu2YPbs2bj00kvx+uuvY8eOHbjvvvsQCATO+Ni33HIL1q1bB6/Xi1WrVuG6666DXq8/48clIiIiIhpomJcTESUOrkQnIkohpaWlUKlU+OSTT1BYWAgA6OjowIEDB3D++ecDADIzM9HY2Nj9NQcPHkRXV1f3xx999BGKiopw3333dY/V1NScUhxqtRqSJPUav/TSS2EwGLBixQq89dZb2LRp0yk9LhERERHRQMC8nIhoYGERnYgohRiNRtx888245557kJ6ejqysLNx3331QKL66MenCCy/EU089hcrKSkiShJ/+9KdQqVTd80OGDEFtbS3WrVuH8ePH44033sD69etPKY7i4mJ88sknOHLkCIxGI2w2GxQKRXcPxoULF2LIkCGorKzst++diIiIiChRMC8nIhpY2M6FiCjF/OpXv8J5552HGTNmYNq0aZg8eTLOPvvs7vnf/OY3KCgowHnnnYfvfe97uPvuu3vcunnFFVfgzjvvxI9//GOMHj0aH330ERYtWnRKMdx9990QRRHDhw9HZmYmamtru+duvvlmBAIB3HTTTWf+zRIRERERJSjm5UREA4cQ+c8GW0RElHKmTp2K0aNH47HHHpM7FHzwwQe46KKLUFdXB7vdLnc4RERERERxw7yciCgxsZ0LERElBL/fj9bWVixZsgSzZs1iok5EREREJAPm5UREvbGdCxERJYQXX3wRRUVF6OzsxC9/+Uu5wyEiIiIiSknMy4mIemM7FyIiIiIiIiIiIiKiKLgSnYiIiIiIiIiIiIgoChbRiYiIiIiIiIiIiIiiYBGdiIiIiIiIiIiIiCgKFtGJiIiIiIiIiIiIiKJgEZ2IiIiIiIiIiIiIKAoW0YmIiIiIiIiIiIiIomARnYiIiIiIiIiIiIgoChbRiYiIiIiIiIiIiIiiYBGdiIiIiIiIiIiIiCiK/w/D7V9llTc01wAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 1500x4000 with 22 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Define the features\n",
+    "features = [\"fixed acidity\", \"volatile acidity\", \"citric acid\", \"residual sugar\",\n",
+    "       \"chlorides\", \"free sulfur dioxide\", \"total sulfur dioxide\", \"density\",\n",
+    "       \"pH\", \"sulphates\", \"alcohol\"]\n",
+    "\n",
+    "# Plot the box plots and violin plots of each feature against quality\n",
+    "fig, axes = plt.subplots(11, 2, figsize=(15, 40))\n",
+    "for i, feature in enumerate(features):\n",
+    "    # box plot\n",
+    "    sns.boxplot(x=\"quality\", y=feature, data=df_no_null, ax=axes[i, 0])\n",
+    "    axes[i, 0].set_title(f\"Box plot of {feature} vs quality\")\n",
+    "    # scatter plot\n",
+    "    sns.scatterplot(x=\"quality\", y=feature, data=df_no_null, hue=\"quality\", ax=axes[i, 1])\n",
+    "    axes[i, 1].set_title(f\"scatterplot of {feature} vs quality\")\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ade621cc",
+   "metadata": {},
+   "source": [
+    "# Explore the Target Variable"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "cd611fec",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "quality\n",
+       "6    2820\n",
+       "5    2128\n",
+       "7    1074\n",
+       "4     214\n",
+       "8     192\n",
+       "3      30\n",
+       "9       5\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_no_null['quality'].value_counts().sort_values(ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "c99759aa",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "countplot() got multiple values for argument 'data'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[1;32mIn[20], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43msns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcountplot\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mquality\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mdf_no_null\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[1;31mTypeError\u001b[0m: countplot() got multiple values for argument 'data'"
+     ]
+    }
+   ],
+   "source": [
+    "sns.countplot('quality', data = df_no_null)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0dffe41a",
+   "metadata": {},
+   "source": [
+    "\n",
+    "# Binarize the Target Variable"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a6425a15",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "b5aa009f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\agraw\\AppData\\Local\\Temp\\ipykernel_15956\\1454888876.py:2: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  df_no_null.loc[:, \"quality_binary\"] = df_no_null[\"quality\"].apply(lambda x: 1 if x > 5 else 0)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "quality_binary\n",
+       "1    4091\n",
+       "0    2372\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Binarize the quality column using a lambda function\n",
+    "df_no_null.loc[:, \"quality_binary\"] = df_no_null[\"quality\"].apply(lambda x: 1 if x > 5 else 0)\n",
+    "\n",
+    "# Check the value counts of the binarized quality column\n",
+    "df_no_null[\"quality_binary\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "9fae113f",
+   "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>fixed acidity</th>\n",
+       "      <th>volatile acidity</th>\n",
+       "      <th>citric acid</th>\n",
+       "      <th>residual sugar</th>\n",
+       "      <th>chlorides</th>\n",
+       "      <th>free sulfur dioxide</th>\n",
+       "      <th>total sulfur dioxide</th>\n",
+       "      <th>density</th>\n",
+       "      <th>pH</th>\n",
+       "      <th>sulphates</th>\n",
+       "      <th>alcohol</th>\n",
+       "      <th>quality</th>\n",
+       "      <th>red</th>\n",
+       "      <th>white</th>\n",
+       "      <th>quality_binary</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>7.0</td>\n",
+       "      <td>0.27</td>\n",
+       "      <td>0.36</td>\n",
+       "      <td>20.7</td>\n",
+       "      <td>0.045</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>170.0</td>\n",
+       "      <td>1.0010</td>\n",
+       "      <td>3.00</td>\n",
+       "      <td>0.45</td>\n",
+       "      <td>8.8</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6.3</td>\n",
+       "      <td>0.30</td>\n",
+       "      <td>0.34</td>\n",
+       "      <td>1.6</td>\n",
+       "      <td>0.049</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>132.0</td>\n",
+       "      <td>0.9940</td>\n",
+       "      <td>3.30</td>\n",
+       "      <td>0.49</td>\n",
+       "      <td>9.5</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>8.1</td>\n",
+       "      <td>0.28</td>\n",
+       "      <td>0.40</td>\n",
+       "      <td>6.9</td>\n",
+       "      <td>0.050</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>97.0</td>\n",
+       "      <td>0.9951</td>\n",
+       "      <td>3.26</td>\n",
+       "      <td>0.44</td>\n",
+       "      <td>10.1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>7.2</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>8.5</td>\n",
+       "      <td>0.058</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>186.0</td>\n",
+       "      <td>0.9956</td>\n",
+       "      <td>3.19</td>\n",
+       "      <td>0.40</td>\n",
+       "      <td>9.9</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>7.2</td>\n",
+       "      <td>0.23</td>\n",
+       "      <td>0.32</td>\n",
+       "      <td>8.5</td>\n",
+       "      <td>0.058</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>186.0</td>\n",
+       "      <td>0.9956</td>\n",
+       "      <td>3.19</td>\n",
+       "      <td>0.40</td>\n",
+       "      <td>9.9</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
+       "0            7.0              0.27         0.36            20.7      0.045   \n",
+       "1            6.3              0.30         0.34             1.6      0.049   \n",
+       "2            8.1              0.28         0.40             6.9      0.050   \n",
+       "3            7.2              0.23         0.32             8.5      0.058   \n",
+       "4            7.2              0.23         0.32             8.5      0.058   \n",
+       "\n",
+       "   free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
+       "0                 45.0                 170.0   1.0010  3.00       0.45   \n",
+       "1                 14.0                 132.0   0.9940  3.30       0.49   \n",
+       "2                 30.0                  97.0   0.9951  3.26       0.44   \n",
+       "3                 47.0                 186.0   0.9956  3.19       0.40   \n",
+       "4                 47.0                 186.0   0.9956  3.19       0.40   \n",
+       "\n",
+       "   alcohol  quality    red  white  quality_binary  \n",
+       "0      8.8        6  False   True               1  \n",
+       "1      9.5        6  False   True               1  \n",
+       "2     10.1        6  False   True               1  \n",
+       "3      9.9        6  False   True               1  \n",
+       "4      9.9        6  False   True               1  "
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_no_null.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "885b8a73",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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1ASa33uMG3IX+9a9/GaNGjTLCwsIMLy8vo1q1akanTp2MxYsXG5cuXTL7Xb582Zg9e7YRHh5uVK5c2ahTp44xbdo0lz6GYRj5+fnG1KlTjRo1ahi+vr5GVFSUceTIkWvedr93716X5xd3S3d6eroRHR1tVKtWzZBk3q5dOMb27duN0aNHG9WrVzf8/PyMwYMHGz/99JPLuMXdjp6RkWEMHz7cqFGjhuHl5WW0bNnS5Rb2Qrt37zYiIyMNLy+vm7oF/+jRo8aAAQOMgIAAw8fHx2jfvr2xcePGIv10k7fdG4Zh/PTTT8aQIUMMu91u+Pv7G0OGDDH++c9/Frnt3jAM46233jLq169veHl5GW3atDESExOLve3+9ddfNxo1amR4e3sbTZs2NVatWmXMnDnTuPo/tTdz231OTo4xaNAgIyAgwJBU7C34ffr0MSQZu3fvvqk5X63w9XrrrbfMutu2betSh2Fc+7b76OjoImNe/Xtx6dIl47nnnjNq165tVKlSxejUqZORkpJSpF/ha/Duu+9et+bmzZsbHh4exg8//FCaKQPXZDMMVloC+EV8fLyGDx+uvXv3ql27du4u57Y7fvy4wsPDtWrVKrd8z1tJPf7449q/f7+OHDni7lJum7Zt2yowMFDJycnuLgV3GdYQAcAd6PTp09q0aZOlFhZ/+eWXSktLu+EnkQOlwRoiALiDHDt2TLt27dLKlStVuXJl/f73vy/SJz09/bpjVKlS5bbfon8rDhw4oNTUVL3yyiuqXbu2nnrqKXeXhLsQgQgA7iDbt2/X8OHDVbduXa1evVohISFF+hT35cK/FhMT4/IFthXde++9pzlz5qhJkyZ6++235ePj4+6ScBdiDREA3GW2bNly3f2hoaGl+rgC4G5GIAIAAJbHomoAAGB5rCG6CQUFBfrxxx9VrVq1W/ruKQAAcPsYhqFz584pNDT0hh/iSiC6CT/++KPq1Knj7jIAAEApnDp1Svfcc891+xCIbkLhVw6cOnVKdrvdzdUAAICb4XQ6VadOHfN9/HoIRDeh8DKZ3W4nEAEAcIe5meUuLKoGAACWRyACAACWRyACAACWRyACAACWRyACAACWRyACAACWRyACAACWRyACAACWRyACAACWRyACAACWRyACAACWRyACAACWRyACAACWRyACAACWRyACAACWV8ndBQCAFUROftPdJQAVUurLQ91dgiTOEAEAABCIAAAAKkwg+utf/yqbzabx48ebbZcuXVJsbKyCgoLk5+en/v37KyMjw+V5J0+eVHR0tHx9fVWrVi1NnjxZV65ccemzbds23XvvvfL29lbDhg0VHx9/G2YEAADuFBUiEO3du1d///vf1apVK5f2CRMm6MMPP9S7776r7du368cff9QTTzxh7s/Pz1d0dLTy8vK0e/durV69WvHx8ZoxY4bZ59ixY4qOjla3bt2Ulpam8ePHa+TIkUpMTLxt8wMAABWb2wNRTk6OBg8erP/+7/9W9erVzfbs7Gy9/vrrmj9/vh566CFFRkZq1apV2r17tz7//HNJ0ieffKJDhw7prbfeUps2bdS7d2+98MILWrp0qfLy8iRJK1asUHh4uF555RU1a9ZMcXFxGjBggBYsWOCW+QIAgIrH7YEoNjZW0dHR6tGjh0t7amqqLl++7NLetGlT1a1bVykpKZKklJQUtWzZUsHBwWafqKgoOZ1OHTx40Oxz9dhRUVHmGAAAAG697X7t2rX66quvtHfv3iL70tPT5eXlpYCAAJf24OBgpaenm31+HYYK9xfuu14fp9OpixcvqkqVKkWOnZubq9zcXHPb6XSWfHIAAOCO4bYzRKdOndIf/vAHJSQkyMfHx11lFGvu3Lny9/c3H3Xq1HF3SQAAoBy5LRClpqYqMzNT9957rypVqqRKlSpp+/btevXVV1WpUiUFBwcrLy9PWVlZLs/LyMhQSEiIJCkkJKTIXWeF2zfqY7fbiz07JEnTpk1Tdna2+Th16lRZTBkAAFRQbgtE3bt31/79+5WWlmY+2rVrp8GDB5s/V65cWcnJyeZzDh8+rJMnT8rhcEiSHA6H9u/fr8zMTLNPUlKS7Ha7IiIizD6/HqOwT+EYxfH29pbdbnd5AACAu5fb1hBVq1ZNLVq0cGmrWrWqgoKCzPYRI0Zo4sSJCgwMlN1u17hx4+RwONSxY0dJUs+ePRUREaEhQ4Zo3rx5Sk9P1/Tp0xUbGytvb29J0pgxY7RkyRJNmTJFzzzzjLZu3ap33nlHmzZtur0TBgAAFVaF/i6zBQsWyMPDQ/3791dubq6ioqK0bNkyc7+np6c2btyosWPHyuFwqGrVqoqJidGcOXPMPuHh4dq0aZMmTJigRYsW6Z577tHKlSsVFRXljikBAIAKyGYYhuHuIio6p9Mpf39/ZWdnc/kMQKnw5a5A8crzy11L8v7t9s8hAgAAcDcCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDwCEQAAsDy3BqLly5erVatWstvtstvtcjgc+vjjj839Xbt2lc1mc3mMGTPGZYyTJ08qOjpavr6+qlWrliZPnqwrV6649Nm2bZvuvfdeeXt7q2HDhoqPj78d0wMAAHeISu48+D333KO//vWvatSokQzD0OrVq9WvXz/985//VPPmzSVJo0aN0pw5c8zn+Pr6mj/n5+crOjpaISEh2r17t06fPq2hQ4eqcuXK+stf/iJJOnbsmKKjozVmzBglJCQoOTlZI0eOVO3atRUVFXV7JwwAACoktwaivn37umz/13/9l5YvX67PP//cDES+vr4KCQkp9vmffPKJDh06pC1btig4OFht2rTRCy+8oKlTp2rWrFny8vLSihUrFB4erldeeUWS1KxZM3322WdasGABgQgAAEiqQGuI8vPztXbtWp0/f14Oh8NsT0hIUI0aNdSiRQtNmzZNFy5cMPelpKSoZcuWCg4ONtuioqLkdDp18OBBs0+PHj1cjhUVFaWUlJRynhEAALhTuPUMkSTt379fDodDly5dkp+fn9avX6+IiAhJ0qBBg1SvXj2FhoZq3759mjp1qg4fPqz3339fkpSenu4ShiSZ2+np6dft43Q6dfHiRVWpUqVITbm5ucrNzTW3nU5n2U0YAABUOG4PRE2aNFFaWpqys7P13nvvKSYmRtu3b1dERIRGjx5t9mvZsqVq166t7t276+jRo2rQoEG51TR37lzNnj273MYHAAAVi9svmXl5ealhw4aKjIzU3Llz1bp1ay1atKjYvh06dJAkHTlyRJIUEhKijIwMlz6F24Xrjq7Vx263F3t2SJKmTZum7Oxs83Hq1KnSTxAAAFR4bg9EVysoKHC5XPVraWlpkqTatWtLkhwOh/bv36/MzEyzT1JSkux2u3nZzeFwKDk52WWcpKQkl3VKV/P29jY/CqDwAQAA7l5uvWQ2bdo09e7dW3Xr1tW5c+e0Zs0abdu2TYmJiTp69KjWrFmjPn36KCgoSPv27dOECRPUpUsXtWrVSpLUs2dPRUREaMiQIZo3b57S09M1ffp0xcbGytvbW5I0ZswYLVmyRFOmTNEzzzyjrVu36p133tGmTZvcOXUAAFCBuDUQZWZmaujQoTp9+rT8/f3VqlUrJSYm6uGHH9apU6e0ZcsWLVy4UOfPn1edOnXUv39/TZ8+3Xy+p6enNm7cqLFjx8rhcKhq1aqKiYlx+dyi8PBwbdq0SRMmTNCiRYt0zz33aOXKldxyDwAATDbDMAx3F1HROZ1O+fv7Kzs7m8tnAEolcvKb7i4BqJBSXx5abmOX5P27wq0hAgAAuN0IRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPLcGoiWL1+uVq1ayW63y263y+Fw6OOPPzb3X7p0SbGxsQoKCpKfn5/69++vjIwMlzFOnjyp6Oho+fr6qlatWpo8ebKuXLni0mfbtm2699575e3trYYNGyo+Pv52TA8AANwh3BqI7rnnHv31r39VamqqvvzySz300EPq16+fDh48KEmaMGGCPvzwQ7377rvavn27fvzxRz3xxBPm8/Pz8xUdHa28vDzt3r1bq1evVnx8vGbMmGH2OXbsmKKjo9WtWzelpaVp/PjxGjlypBITE2/7fAEAQMVkMwzDcHcRvxYYGKiXX35ZAwYMUM2aNbVmzRoNGDBAkvTtt9+qWbNmSklJUceOHfXxxx/rkUce0Y8//qjg4GBJ0ooVKzR16lSdOXNGXl5emjp1qjZt2qQDBw6Yxxg4cKCysrK0efPmm6rJ6XTK399f2dnZstvtZT9pAHe9yMlvursEoEJKfXlouY1dkvfvCrOGKD8/X2vXrtX58+flcDiUmpqqy5cvq0ePHmafpk2bqm7dukpJSZEkpaSkqGXLlmYYkqSoqCg5nU7zLFNKSorLGIV9CscAAACo5O4C9u/fL4fDoUuXLsnPz0/r169XRESE0tLS5OXlpYCAAJf+wcHBSk9PlySlp6e7hKHC/YX7rtfH6XTq4sWLqlKlSpGacnNzlZuba247nc5bnicAAKi43H6GqEmTJkpLS9OePXs0duxYxcTE6NChQ26tae7cufL39zcfderUcWs9AACgfLk9EHl5ealhw4aKjIzU3Llz1bp1ay1atEghISHKy8tTVlaWS/+MjAyFhIRIkkJCQorcdVa4faM+dru92LNDkjRt2jRlZ2ebj1OnTpXFVAEAQAXl9kB0tYKCAuXm5ioyMlKVK1dWcnKyue/w4cM6efKkHA6HJMnhcGj//v3KzMw0+yQlJclutysiIsLs8+sxCvsUjlEcb29v86MACh8AAODu5dY1RNOmTVPv3r1Vt25dnTt3TmvWrNG2bduUmJgof39/jRgxQhMnTlRgYKDsdrvGjRsnh8Ohjh07SpJ69uypiIgIDRkyRPPmzVN6erqmT5+u2NhYeXt7S5LGjBmjJUuWaMqUKXrmmWe0detWvfPOO9q0aZM7pw4AACoQtwaizMxMDR06VKdPn5a/v79atWqlxMREPfzww5KkBQsWyMPDQ/3791dubq6ioqK0bNky8/menp7auHGjxo4dK4fDoapVqyomJkZz5swx+4SHh2vTpk2aMGGCFi1apHvuuUcrV65UVFTUbZ8vAAComCrc5xBVRHwOEYBbxecQAcXjc4gAAAAqCAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPAIRAACwPLcGorlz5+q+++5TtWrVVKtWLT322GM6fPiwS5+uXbvKZrO5PMaMGePS5+TJk4qOjpavr69q1aqlyZMn68qVKy59tm3bpnvvvVfe3t5q2LCh4uPjy3t6AADgDuHWQLR9+3bFxsbq888/V1JSki5fvqyePXvq/PnzLv1GjRql06dPm4958+aZ+/Lz8xUdHa28vDzt3r1bq1evVnx8vGbMmGH2OXbsmKKjo9WtWzelpaVp/PjxGjlypBITE2/bXAEAQMVVyZ0H37x5s8t2fHy8atWqpdTUVHXp0sVs9/X1VUhISLFjfPLJJzp06JC2bNmi4OBgtWnTRi+88IKmTp2qWbNmycvLSytWrFB4eLheeeUVSVKzZs302WefacGCBYqKiiq/CQIAgDtChVpDlJ2dLUkKDAx0aU9ISFCNGjXUokULTZs2TRcuXDD3paSkqGXLlgoODjbboqKi5HQ6dfDgQbNPjx49XMaMiopSSkpKeU0FAADcQdx6hujXCgoKNH78eHXq1EktWrQw2wcNGqR69eopNDRU+/bt09SpU3X48GG9//77kqT09HSXMCTJ3E5PT79uH6fTqYsXL6pKlSou+3Jzc5Wbm2tuO53OspsoAACocCpMIIqNjdWBAwf02WefubSPHj3a/Llly5aqXbu2unfvrqNHj6pBgwblUsvcuXM1e/bschkbAABUPBXikllcXJw2btyoTz/9VPfcc891+3bo0EGSdOTIEUlSSEiIMjIyXPoUbheuO7pWH7vdXuTskCRNmzZN2dnZ5uPUqVOlmxgAALgjuDUQGYahuLg4rV+/Xlu3blV4ePgNn5OWliZJql27tiTJ4XBo//79yszMNPskJSXJbrcrIiLC7JOcnOwyTlJSkhwOR7HH8Pb2lt1ud3kAAIC7l1sDUWxsrN566y2tWbNG1apVU3p6utLT03Xx4kVJ0tGjR/XCCy8oNTVVx48f1wcffKChQ4eqS5cuatWqlSSpZ8+eioiI0JAhQ/T1118rMTFR06dPV2xsrLy9vSVJY8aM0ffff68pU6bo22+/1bJly/TOO+9owoQJbps7AACoONwaiJYvX67s7Gx17dpVtWvXNh/r1q2TJHl5eWnLli3q2bOnmjZtqueee079+/fXhx9+aI7h6empjRs3ytPTUw6HQ7/73e80dOhQzZkzx+wTHh6uTZs2KSkpSa1bt9Yrr7yilStXcss9AACQJNkMwzDcXURF53Q65e/vr+zsbC6fASiVyMlvursEoEJKfXlouY1dkvfvCrGoGgAAwJ0IRAAAwPIIRAAAwPIIRAAAwPIIRAAAwPIqzFd3gLtQgGspz7tQAEAq5Rmi+vXr66effirSnpWVpfr1699yUQAAALdTqQLR8ePHlZ+fX6Q9NzdX//73v2+5KAAAgNupRJfMPvjgA/PnxMRE+fv7m9v5+flKTk5WWFhYmRUHAABwO5QoED322GOSJJvNppiYGJd9lStXVlhYmF555ZUyKw4AAOB2KFEgKigokPTLd4Pt3btXNWrUKJeiAAAAbqdS3WV27Nixsq4DAADAbUp9231ycrKSk5OVmZlpnjkq9MYbb9xyYQAAALdLqQLR7NmzNWfOHLVr1061a9eWzWYr67oAAABum1IFohUrVig+Pl5Dhgwp63oAAABuu1J9DlFeXp7uv//+sq4FAADALUoViEaOHKk1a9aUdS0AAABuUapLZpcuXdJrr72mLVu2qFWrVqpcubLL/vnz55dJcQAAALdDqQLRvn371KZNG0nSgQMHXPaxwBoAANxpShWIPv3007KuAwAAwG1KtYYIAADgblKqM0TdunW77qWxrVu3lrogAACA261Ugahw/VChy5cvKy0tTQcOHCjypa8AAAAVXakC0YIFC4ptnzVrlnJycm6pIAAAgNutTNcQ/e53v+N7zAAAwB2nTANRSkqKfHx8ynJIAACAcleqS2ZPPPGEy7ZhGDp9+rS+/PJL/fnPfy6TwgAAAG6XUgUif39/l20PDw81adJEc+bMUc+ePcukMAAAgNulVIFo1apVZV0HAACA25QqEBVKTU3VN998I0lq3ry52rZtWyZFAQAA3E6lCkSZmZkaOHCgtm3bpoCAAElSVlaWunXrprVr16pmzZplWSMAAEC5KtVdZuPGjdO5c+d08OBBnT17VmfPntWBAwfkdDr17LPPlnWNAAAA5apUgWjz5s1atmyZmjVrZrZFRERo6dKl+vjjj296nLlz5+q+++5TtWrVVKtWLT322GM6fPiwS59Lly4pNjZWQUFB8vPzU//+/ZWRkeHS5+TJk4qOjpavr69q1aqlyZMn68qVKy59tm3bpnvvvVfe3t5q2LCh4uPjSz5xAABwVypVICooKFDlypWLtFeuXFkFBQU3Pc727dsVGxurzz//XElJSbp8+bJ69uyp8+fPm30mTJigDz/8UO+++662b9+uH3/80eW2//z8fEVHRysvL0+7d+/W6tWrFR8frxkzZph9jh07pujoaHXr1k1paWkaP368Ro4cqcTExNJMHwAA3GVshmEYJX1Sv379lJWVpbfffluhoaGSpH//+98aPHiwqlevrvXr15eqmDNnzqhWrVravn27unTpouzsbNWsWVNr1qzRgAEDJEnffvutmjVrppSUFHXs2FEff/yxHnnkEf34448KDg6WJK1YsUJTp07VmTNn5OXlpalTp2rTpk06cOCAeayBAwcqKytLmzdvvmFdTqdT/v7+ys7Olt1uL9Xcbkbk5DfLbWzgTpb68lB3l3DL+PsGileef98lef8u1RmiJUuWyOl0KiwsTA0aNFCDBg0UHh4up9OpxYsXl6poScrOzpYkBQYGSvrlLrbLly+rR48eZp+mTZuqbt26SklJkfTLp2O3bNnSDEOSFBUVJafTqYMHD5p9fj1GYZ/CMQAAgLWV6i6zOnXq6KuvvtKWLVv07bffSpKaNWtWJHSUREFBgcaPH69OnTqpRYsWkqT09HR5eXmZd7IVCg4OVnp6utnn12GocH/hvuv1cTqdunjxoqpUqeKyLzc3V7m5uea20+ks9bwAAEDFV6IzRFu3blVERIScTqdsNpsefvhhjRs3TuPGjdN9992n5s2ba+fOnaUqJDY2VgcOHNDatWtL9fyyNHfuXPn7+5uPOnXquLskAABQjkoUiBYuXKhRo0YVex3O399fv//97zV//vwSFxEXF6eNGzfq008/1T333GO2h4SEKC8vT1lZWS79MzIyFBISYva5+q6zwu0b9bHb7UXODknStGnTlJ2dbT5OnTpV4jkBAIA7R4kC0ddff61evXpdc3/Pnj2Vmpp60+MZhqG4uDitX79eW7duVXh4uMv+yMhIVa5cWcnJyWbb4cOHdfLkSTkcDkmSw+HQ/v37lZmZafZJSkqS3W5XRESE2efXYxT2KRzjat7e3rLb7S4PAABw9yrRGqKMjIxib7c3B6tUSWfOnLnp8WJjY7VmzRr94x//ULVq1cw1P/7+/qpSpYr8/f01YsQITZw4UYGBgbLb7Ro3bpwcDoc6duwo6ZcQFhERoSFDhmjevHlKT0/X9OnTFRsbK29vb0nSmDFjtGTJEk2ZMkXPPPOMtm7dqnfeeUebNm0qyfQBAMBdqkRniH7zm9+43Lp+tX379ql27do3Pd7y5cuVnZ2trl27qnbt2uZj3bp1Zp8FCxbokUceUf/+/dWlSxeFhITo/fffN/d7enpq48aN8vT0lMPh0O9+9zsNHTpUc+bMMfuEh4dr06ZNSkpKUuvWrfXKK69o5cqVioqKKsn0AQDAXapEZ4j69OmjP//5z+rVq5d8fHxc9l28eFEzZ87UI488ctPj3cxHIPn4+Gjp0qVaunTpNfvUq1dPH3300XXH6dq1q/75z3/edG0AAMA6ShSIpk+frvfff1+NGzdWXFycmjRpIumXD0tcunSp8vPz9fzzz5dLoQAAAOWlRIEoODhYu3fv1tixYzVt2jTzDI/NZlNUVJSWLl1a5PN+AAAAKroSfzBj4eWpn3/+WUeOHJFhGGrUqJGqV69eHvUBAACUu1J9UrUkVa9eXffdd19Z1gIAAOAWpfouMwAAgLsJgQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFgegQgAAFieWwPRjh071LdvX4WGhspms2nDhg0u+4cNGyabzeby6NWrl0ufs2fPavDgwbLb7QoICNCIESOUk5Pj0mffvn164IEH5OPjozp16mjevHnlPTUAAHAHcWsgOn/+vFq3bq2lS5des0+vXr10+vRp8/H222+77B88eLAOHjyopKQkbdy4UTt27NDo0aPN/U6nUz179lS9evWUmpqql19+WbNmzdJrr71WbvMCAAB3lkruPHjv3r3Vu3fv6/bx9vZWSEhIsfu++eYbbd68WXv37lW7du0kSYsXL1afPn30t7/9TaGhoUpISFBeXp7eeOMNeXl5qXnz5kpLS9P8+fNdghMAALCuCr+GaNu2bapVq5aaNGmisWPH6qeffjL3paSkKCAgwAxDktSjRw95eHhoz549Zp8uXbrIy8vL7BMVFaXDhw/r559/vn0TAQAAFZZbzxDdSK9evfTEE08oPDxcR48e1Z/+9Cf17t1bKSkp8vT0VHp6umrVquXynEqVKikwMFDp6emSpPT0dIWHh7v0CQ4ONvdVr169yHFzc3OVm5trbjudzrKeGgAAqEAqdCAaOHCg+XPLli3VqlUrNWjQQNu2bVP37t3L7bhz587V7Nmzy218AABQsVT4S2a/Vr9+fdWoUUNHjhyRJIWEhCgzM9Olz5UrV3T27Flz3VFISIgyMjJc+hRuX2tt0rRp05SdnW0+Tp06VdZTAQAAFcgdFYh++OEH/fTTT6pdu7YkyeFwKCsrS6mpqWafrVu3qqCgQB06dDD77NixQ5cvXzb7JCUlqUmTJsVeLpN+Wchtt9tdHgAA4O7l1kCUk5OjtLQ0paWlSZKOHTumtLQ0nTx5Ujk5OZo8ebI+//xzHT9+XMnJyerXr58aNmyoqKgoSVKzZs3Uq1cvjRo1Sl988YV27dqluLg4DRw4UKGhoZKkQYMGycvLSyNGjNDBgwe1bt06LVq0SBMnTnTXtAEAQAXj1kD05Zdfqm3btmrbtq0kaeLEiWrbtq1mzJghT09P7du3T48++qgaN26sESNGKDIyUjt37pS3t7c5RkJCgpo2baru3burT58+6ty5s8tnDPn7++uTTz7RsWPHFBkZqeeee04zZszglnsAAGBy66Lqrl27yjCMa+5PTEy84RiBgYFas2bNdfu0atVKO3fuLHF9AADAGu6oNUQAAADlgUAEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsj0AEAAAsz62BaMeOHerbt69CQ0Nls9m0YcMGl/2GYWjGjBmqXbu2qlSpoh49eui7775z6XP27FkNHjxYdrtdAQEBGjFihHJyclz67Nu3Tw888IB8fHxUp04dzZs3r7ynBgAA7iBuDUTnz59X69attXTp0mL3z5s3T6+++qpWrFihPXv2qGrVqoqKitKlS5fMPoMHD9bBgweVlJSkjRs3aseOHRo9erS53+l0qmfPnqpXr55SU1P18ssva9asWXrttdfKfX4AAODOUMmdB+/du7d69+5d7D7DMLRw4UJNnz5d/fr1kyS9+eabCg4O1oYNGzRw4EB988032rx5s/bu3at27dpJkhYvXqw+ffrob3/7m0JDQ5WQkKC8vDy98cYb8vLyUvPmzZWWlqb58+e7BCcAAGBdFXYN0bFjx5Senq4ePXqYbf7+/urQoYNSUlIkSSkpKQoICDDDkCT16NFDHh4e2rNnj9mnS5cu8vLyMvtERUXp8OHD+vnnn2/TbAAAQEXm1jNE15Oeni5JCg4OdmkPDg4296Wnp6tWrVou+ytVqqTAwECXPuHh4UXGKNxXvXr1IsfOzc1Vbm6uue10Om9xNgAAoCKrsGeI3Gnu3Lny9/c3H3Xq1HF3SQAAoBxV2EAUEhIiScrIyHBpz8jIMPeFhIQoMzPTZf+VK1d09uxZlz7FjfHrY1xt2rRpys7ONh+nTp269QkBAIAKq8IGovDwcIWEhCg5Odlsczqd2rNnjxwOhyTJ4XAoKytLqampZp+tW7eqoKBAHTp0MPvs2LFDly9fNvskJSWpSZMmxV4ukyRvb2/Z7XaXBwAAuHu5NRDl5OQoLS1NaWlpkn5ZSJ2WlqaTJ0/KZrNp/PjxevHFF/XBBx9o//79Gjp0qEJDQ/XYY49Jkpo1a6ZevXpp1KhR+uKLL7Rr1y7FxcVp4MCBCg0NlSQNGjRIXl5eGjFihA4ePKh169Zp0aJFmjhxoptmDQAAKhq3Lqr+8ssv1a1bN3O7MKTExMQoPj5eU6ZM0fnz5zV69GhlZWWpc+fO2rx5s3x8fMznJCQkKC4uTt27d5eHh4f69++vV1991dzv7++vTz75RLGxsYqMjFSNGjU0Y8YMbrkHAAAmm2EYhruLqOicTqf8/f2VnZ1drpfPIie/WW5jA3ey1JeHuruEW8bfN1C88vz7Lsn7d4VdQwQAAHC7EIgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlEYgAAIDlVehANGvWLNlsNpdH06ZNzf2XLl1SbGysgoKC5Ofnp/79+ysjI8NljJMnTyo6Olq+vr6qVauWJk+erCtXrtzuqQAAgAqskrsLuJHmzZtry5Yt5nalSv9/yRMmTNCmTZv07rvvyt/fX3FxcXriiSe0a9cuSVJ+fr6io6MVEhKi3bt36/Tp0xo6dKgqV66sv/zlL7d9LgAAoGKq8IGoUqVKCgkJKdKenZ2t119/XWvWrNFDDz0kSVq1apWaNWumzz//XB07dtQnn3yiQ4cOacuWLQoODlabNm30wgsvaOrUqZo1a5a8vLxu93QAAEAFVKEvmUnSd999p9DQUNWvX1+DBw/WyZMnJUmpqam6fPmyevToYfZt2rSp6tatq5SUFElSSkqKWrZsqeDgYLNPVFSUnE6nDh48eHsnAgAAKqwKfYaoQ4cOio+PV5MmTXT69GnNnj1bDzzwgA4cOKD09HR5eXkpICDA5TnBwcFKT0+XJKWnp7uEocL9hfuuJTc3V7m5uea20+ksoxkBAICKqEIHot69e5s/t2rVSh06dFC9evX0zjvvqEqVKuV23Llz52r27NnlNj4AAKhYKvwls18LCAhQ48aNdeTIEYWEhCgvL09ZWVkufTIyMsw1RyEhIUXuOivcLm5dUqFp06YpOzvbfJw6dapsJwIAACqUOyoQ5eTk6OjRo6pdu7YiIyNVuXJlJScnm/sPHz6skydPyuFwSJIcDof279+vzMxMs09SUpLsdrsiIiKueRxvb2/Z7XaXBwAAuHtV6EtmkyZNUt++fVWvXj39+OOPmjlzpjw9PfX000/L399fI0aM0MSJExUYGCi73a5x48bJ4XCoY8eOkqSePXsqIiJCQ4YM0bx585Senq7p06crNjZW3t7ebp4dAACoKCp0IPrhhx/09NNP66efflLNmjXVuXNnff7556pZs6YkacGCBfLw8FD//v2Vm5urqKgoLVu2zHy+p6enNm7cqLFjx8rhcKhq1aqKiYnRnDlz3DUlAABQAVXoQLR27drr7vfx8dHSpUu1dOnSa/apV6+ePvroo7IuDQAA3EXuqDVEAAAA5YFABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALI9ABAAALM9SgWjp0qUKCwuTj4+POnTooC+++MLdJQEAgArAMoFo3bp1mjhxombOnKmvvvpKrVu3VlRUlDIzM91dGgAAcDPLBKL58+dr1KhRGj58uCIiIrRixQr5+vrqjTfecHdpAADAzSwRiPLy8pSamqoePXqYbR4eHurRo4dSUlLcWBkAAKgIKrm7gNvhP//5j/Lz8xUcHOzSHhwcrG+//bZI/9zcXOXm5prb2dnZkiSn01mudebnXizX8YE7VXn/7d0O/H0DxSvPv+/CsQ3DuGFfSwSikpo7d65mz55dpL1OnTpuqAaA/+Ix7i4BQDm5HX/f586dk7+//3X7WCIQ1ahRQ56ensrIyHBpz8jIUEhISJH+06ZN08SJE83tgoICnT17VkFBQbLZbOVeL9zL6XSqTp06OnXqlOx2u7vLAVCG+Pu2FsMwdO7cOYWGht6wryUCkZeXlyIjI5WcnKzHHntM0i8hJzk5WXFxcUX6e3t7y9vb26UtICDgNlSKisRut/MfTOAuxd+3ddzozFAhSwQiSZo4caJiYmLUrl07tW/fXgsXLtT58+c1fPhwd5cGAADczDKB6KmnntKZM2c0Y8YMpaenq02bNtq8eXORhdYAAMB6LBOIJCkuLq7YS2TAr3l7e2vmzJlFLpsCuPPx941rsRk3cy8aAADAXcwSH8wIAABwPQQiAABgeQQiAABgeQQiAABgeQQi4CpLly5VWFiYfHx81KFDB33xxRfuLglAGdixY4f69u2r0NBQ2Ww2bdiwwd0loQIhEAG/sm7dOk2cOFEzZ87UV199pdatWysqKkqZmZnuLg3ALTp//rxat26tpUuXursUVEDcdg/8SocOHXTfffdpyZIlkn75ipc6depo3Lhx+uMf/+jm6gCUFZvNpvXr15tf5wRwhgj4P3l5eUpNTVWPHj3MNg8PD/Xo0UMpKSlurAwAUN4IRMD/+c9//qP8/PwiX+cSHBys9PR0N1UFALgdCEQAAMDyCETA/6lRo4Y8PT2VkZHh0p6RkaGQkBA3VQUAuB0IRMD/8fLyUmRkpJKTk822goICJScny+FwuLEyAEB5s9S33QM3MnHiRMXExKhdu3Zq3769Fi5cqPPnz2v48OHuLg3ALcrJydGRI0fM7WPHjiktLU2BgYGqW7euGytDRcBt98BVlixZopdfflnp6elq06aNXn31VXXo0MHdZQG4Rdu2bVO3bt2KtMfExCg+Pv72F4QKhUAEAAAsjzVEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEAADA8ghEADRr1iy1adPG3B42bJgee+yxcjlWXl6eGjZsqN27d5fL+DfLZrNpw4YNbq3hdtu2bZtsNpuysrKu2efq34Wb0bVrV40fP/6a+/Py8hQWFqYvv/yyROMCtxOBCKigTp06pWeeeUahoaHy8vJSvXr19Ic//EE//fRTuR970aJFLp/ce6M3vJJYsWKFwsPDdf/995ttZ8+e1eDBg2W32xUQEKARI0YoJyenTI5XUZ0+fVqDBg1S48aN5eHhUWav762aNGmSy/f5lQUvLy9NmjRJU6dOLdNxgbJEIAIqoO+//17t2rXTd999p7fffltHjhzRihUrzC+aPXv2bLke39/fXwEBAWU+rmEYWrJkiUaMGOHSPnjwYB08eFBJSUnauHGjduzYodGjR5f58SuS3Nxc1axZU9OnT1fr1q3dXY7Jz89PQUFBZT7u4MGD9dlnn+ngwYNlPjZQFghEQAUUGxsrLy8vffLJJ3rwwQdVt25d9e7dW1u2bNG///1vPf/882bf4i79BAQEuJzhmTp1qho3bixfX1/Vr19ff/7zn3X58uVrHv/Xl8yGDRum7du3a9GiRbLZbLLZbDp27JgaNmyov/3tby7PS0tLk81mc/kCzV9LTU3V0aNHFR0dbbZ988032rx5s1auXKkOHTqoc+fOWrx4sdauXasff/zxJl+xW7d//3499NBDqlKlioKCgjR69GjzLNWBAwfk4eGhM2fOSPrljJaHh4cGDhxoPv/FF19U586db/p4YWFhWrRokYYOHSp/f/+yncwNpKamql27dvL19dX999+vw4cPm/uuvmR25coVPfvsswoICFBQUJCmTp2qmJiYIpdUCwoKNGXKFAUGBiokJESzZs1y2V+9enV16tRJa9euLceZAaVHIAIqmLNnzyoxMVH/7//9P1WpUsVlX0hIiAYPHqx169apJF9DWK1aNcXHx+vQoUNatGiR/vu//1sLFiy4qecuWrRIDodDo0aN0unTp3X69GnVrVtXzzzzjFatWuXSd9WqVerSpYsaNmxY7Fg7d+5U48aNVa1aNbMtJSVFAQEBateundnWo0cPeXh4aM+ePdesq3fv3vLz87vmo3nz5jc1P0k6f/68oqKiVL16de3du1fvvvuutmzZori4OElS8+bNFRQUpO3bt5vz+PW2JG3fvl1du3a96WOW1vXm7OfnpzFjxtxwjOeff16vvPKKvvzyS1WqVEnPPPPMNfu+9NJLSkhI0KpVq7Rr1y45nc5i116tXr1aVatW1Z49ezRv3jzNmTNHSUlJLn3at2+vnTt3lnjOwO1Qyd0FAHD13XffyTAMNWvWrNj9zZo1088//6wzZ86oVq1aNzXm9OnTzZ/DwsI0adIkrV27VlOmTLnhc/39/eXl5SVfX1+FhISY7cOGDdOMGTP0xRdfqH379rp8+bLWrFlT5KzRr504cUKhoaEubenp6UXmUalSJQUGBio9Pf2aY61cuVIXL1685v7KlSvfaGqmNWvW6NKlS3rzzTdVtWpVSdKSJUvUt29fvfTSSwoODlaXLl20bds2DRgwQNu2bdPw4cO1cuVKffvtt2rQoIF27959U6/nrUpLS7vufrvdfsMx/uu//ksPPvigJOmPf/yjoqOjdenSJfn4+BTpu3jxYk2bNk2PP/64pF9el48++qhIv1atWmnmzJmSpEaNGmnJkiVKTk7Www8/bPYJDQ3ViRMnblgf4A4EIqCCutEZIC8vr5sea926dXr11Vd19OhR5eTk6MqVKzf1xnk9oaGhio6O1htvvKH27dvrww8/VG5urp588slrPufixYvFvumWxm9+85syGUf65bJd69atzTAkSZ06dVJBQYEOHz6s4OBgPfjgg3rttdck/XI26C9/+Yv+9a9/adu2bTp79qwuX76sTp06lVlN13Kts28l0apVK/Pn2rVrS5IyMzNVt25dl37Z2dnKyMhQ+/btzTZPT09FRkaqoKDgmmMWjpuZmenSVqVKFV24cOGW6wfKA5fMgAqmYcOGstls+uabb4rd/80336hmzZrmomebzVYkPP16fVBKSooGDx6sPn36aOPGjfrnP/+p559/Xnl5ebdc68iRI7V27VpdvHhRq1at0lNPPSVfX99r9q9Ro4Z+/vlnl7aQkJAib5xXrlzR2bNnXc5IXa0sL5ndjK5du+rQoUP67rvvdOjQIXXu3Fldu3bVtm3btH37dnNNTnkri0tmvz57ZrPZJKlIwCmpq8/I2Wy2ImOePXtWNWvWvKXjAOWFM0RABRMUFKSHH35Yy5Yt04QJE1zWEaWnpyshIUGxsbFmW82aNXX69Glz+7vvvnP5v/Ddu3erXr16LguxS3rZwsvLS/n5+UXa+/Tpo6pVq2r58uXavHmzduzYcd1x2rZtq+XLl8swDPON2OFwKCsrS6mpqYqMjJQkbd26VQUFBerQocM1xyrLS2bNmjVTfHy8zp8/b54l2rVrlzw8PNSkSRNJUsuWLVW9enW9+OKLatOmjfz8/NS1a1e99NJL+vnnn2/L+iGpbC6Z3Sx/f38FBwdr79696tKliyQpPz9fX331VYk/q0j6ZXF627Zty6w+oCwRiIAKaMmSJbr//vsVFRWlF198UeHh4Tp48KAmT56sxo0ba8aMGWbfhx56SEuWLJHD4VB+fr6mTp3qEgYaNWqkkydPau3atbrvvvu0adMmrV+/vkT1hIWFac+ePTp+/Lj8/PwUGBgoDw8PeXp6atiwYZo2bZoaNWokh8Nx3XG6deumnJwcHTx4UC1atJD0Sxjp1auXRo0apRUrVujy5cuKi4vTwIEDi6w3+rWyvGQ2ePBgzZw5UzExMZo1a5bOnDmjcePGaciQIQoODpb0yxmPLl26KCEhQZMmTZL0y2Wi3NxcJScna+LEiSU+bmG4ycnJ0ZkzZ5SWliYvLy9FRERc8zllccmsJMaNG6e5c+eqYcOGatq0qRYvXqyff/7ZDLQlsXPnTr3wwgvlUCVw67hkBlRAjRo10t69e1W/fn399re/Vb169dS7d281btxYu3btkp+fn9n3lVdeUZ06dfTAAw9o0KBBmjRpksulm0cffVQTJkxQXFyc2rRpo927d+vPf/5zieqZNGmSPD09FRERoZo1a+rkyZPmvhEjRigvL0/Dhw+/4ThBQUF6/PHHlZCQ4NKekJCgpk2bqnv37urTp486d+5srte5HXx9fZWYmKizZ8/qvvvu04ABA9S9e3ctWbLEpd+DDz6o/Px882yQh4eHunTpIpvNVmT9UFhYWJFbz6/Wtm1btW3bVqmpqVqzZo3atm2rPn36lOXUbtnUqVP19NNPa+jQoXI4HPLz81NUVFSJ14KlpKQoOztbAwYMKKdKgVtjM0py7y4At5k5c6bmz5+vpKQkdezY0d3lmHbu3Knu3bvr1KlT5tmU69m3b58efvhhHT161CXY3U0uXLigoKAgffzxx7ftUtrtUlBQoGbNmum3v/1tic72PPXUU2rdurX+9Kc/lWN1QOlxyQy4Q8yePVthYWH6/PPP1b59e3l4uPcEb25urs6cOaNZs2bpySefvKkwJP1ymemll17SsWPH1LJly3Ku0j0+/fRTPfTQQ3dFGDpx4oT5AaG5ublasmSJjh07pkGDBt30GHl5eWrZsqUmTJhQjpUCt4YzRABKJT4+XiNGjFCbNm30wQcflOmaHlQcp06d0sCBA3XgwAEZhqEWLVror3/9q7nIGrhbEIgAAIDlsagaAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABYHoEIAABY3v8HUjIV/O2LoxwAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Make a countplot of the quality_binary column in sns\n",
+    "sns.countplot(x=\"quality_binary\", data=df_no_null)\n",
+    "plt.title(\"Countplot of quality_binary\")\n",
+    "plt.xlabel(\"Quality (0 = low, 1 = high)\")\n",
+    "plt.ylabel(\"Count\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "86438d5a",
+   "metadata": {},
+   "source": [
+    "# Target variable, Train & Test Data "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "4077ada5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# X and y creation\n",
+    "X = df_no_null.copy()\n",
+    "y = X.pop('quality_binary')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "162508ba",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "# data splitting\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b0a6ca7b",
+   "metadata": {},
+   "source": [
+    "#Features Scaling"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "87ff772e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Features Scaling \n",
+    "\n",
+    "# Set the scaler\n",
+    "scaler = MinMaxScaler()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a5f8a0c8",
+   "metadata": {},
+   "source": [
+    "# PCA"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "3d398cd2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#PCA \n",
+    "from sklearn.decomposition import PCA\n",
+    "\n",
+    "# Set pca components\n",
+    "pca =  PCA(n_components=0.9)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c0b77b67",
+   "metadata": {},
+   "source": [
+    "# Logistic Regression"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "fdb5ea02",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-1 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-1 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-1 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-1 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-1 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;minmaxscaler&#x27;, MinMaxScaler()),\n",
+       "                (&#x27;pca&#x27;, PCA(n_components=0.9)),\n",
+       "                (&#x27;logisticregression&#x27;, LogisticRegression())])</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 sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;minmaxscaler&#x27;, MinMaxScaler()),\n",
+       "                (&#x27;pca&#x27;, PCA(n_components=0.9)),\n",
+       "                (&#x27;logisticregression&#x27;, LogisticRegression())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;MinMaxScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.MinMaxScaler.html\">?<span>Documentation for MinMaxScaler</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>MinMaxScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;PCA<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.decomposition.PCA.html\">?<span>Documentation for PCA</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>PCA(n_components=0.9)</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression()</pre></div> </div></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "Pipeline(steps=[('minmaxscaler', MinMaxScaler()),\n",
+       "                ('pca', PCA(n_components=0.9)),\n",
+       "                ('logisticregression', LogisticRegression())])"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Create a full pipeline with pca_pipeline and logistic regression\n",
+    "logreg_full_pipeline = make_pipeline(scaler, pca, LogisticRegression())\n",
+    "\n",
+    "# Fit the full pipeline to the data\n",
+    "logreg_full_pipeline.fit(X_train, y_train)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "63503d4a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.9608753315649867"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Check the score of the full pipeline on the data\n",
+    "logreg_full_pipeline.score(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "1f09138b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# predict the y variable\n",
+    "log_y_pred = logreg_full_pipeline.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "566712e3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate the accuracy of the model on the test data\n",
+    "accuracy = accuracy_score(y_test, log_y_pred)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "c35434a3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.96      0.93      0.95       722\n",
+      "           1       0.96      0.98      0.97      1217\n",
+      "\n",
+      "    accuracy                           0.96      1939\n",
+      "   macro avg       0.96      0.95      0.96      1939\n",
+      "weighted avg       0.96      0.96      0.96      1939\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print the classification report\n",
+    "print(classification_report(y_test, log_y_pred))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2926053e",
+   "metadata": {},
+   "source": [
+    "# Decision Tree Classifier"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "b92eb847",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-2 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-2 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-2 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-2 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;minmaxscaler&#x27;, MinMaxScaler()),\n",
+       "                (&#x27;pca&#x27;, PCA(n_components=0.9)),\n",
+       "                (&#x27;decisiontreeclassifier&#x27;, DecisionTreeClassifier())])</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 sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;minmaxscaler&#x27;, MinMaxScaler()),\n",
+       "                (&#x27;pca&#x27;, PCA(n_components=0.9)),\n",
+       "                (&#x27;decisiontreeclassifier&#x27;, DecisionTreeClassifier())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;MinMaxScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.MinMaxScaler.html\">?<span>Documentation for MinMaxScaler</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>MinMaxScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;PCA<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.decomposition.PCA.html\">?<span>Documentation for PCA</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>PCA(n_components=0.9)</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;DecisionTreeClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier()</pre></div> </div></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "Pipeline(steps=[('minmaxscaler', MinMaxScaler()),\n",
+       "                ('pca', PCA(n_components=0.9)),\n",
+       "                ('decisiontreeclassifier', DecisionTreeClassifier())])"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Create a full pipeline with pca_pipeline and logistic regression\n",
+    "dt_full_pipeline = make_pipeline(scaler, pca, DecisionTreeClassifier())\n",
+    "\n",
+    "# Fit the full pipeline to the data\n",
+    "dt_full_pipeline.fit(X_train, y_train)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "972bb7de",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.0"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Check the score of the full pipeline on the data\n",
+    "dt_full_pipeline.score(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "36ee353e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dt_y_pred = dt_full_pipeline.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "240e1cf6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate the accuracy of the model on the test data\n",
+    "dt_accuracy = accuracy_score(y_test, dt_y_pred)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "ecf97a2e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.9499742135121196"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dt_accuracy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "23b84a73",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.93      0.94      0.93       722\n",
+      "           1       0.96      0.96      0.96      1217\n",
+      "\n",
+      "    accuracy                           0.95      1939\n",
+      "   macro avg       0.95      0.95      0.95      1939\n",
+      "weighted avg       0.95      0.95      0.95      1939\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print the classification report\n",
+    "print(classification_report(y_test, dt_y_pred))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d89d0611",
+   "metadata": {},
+   "source": [
+    "# Random Forest Classifier"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "22cf48a6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.0"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Create a full pipeline with pca_pipeline and logistic regression\n",
+    "rf_full_pipeline = make_pipeline(scaler, pca, RandomForestClassifier())\n",
+    "\n",
+    "# Fit the full pipeline to the data\n",
+    "rf_full_pipeline.fit(X_train, y_train)\n",
+    "\n",
+    "# Check the score of the full pipeline on the data\n",
+    "rf_full_pipeline.score(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "d182fe11",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rf_y_pred = rf_full_pipeline.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "a19331b8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Calculate the accuracy of the model on the test data\n",
+    "rf_accuracy = accuracy_score(y_test, rf_y_pred)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "7c8674b0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.9736977823620423"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rf_accuracy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "59b54e6a",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.97      0.96      0.96       722\n",
+      "           1       0.98      0.98      0.98      1217\n",
+      "\n",
+      "    accuracy                           0.97      1939\n",
+      "   macro avg       0.97      0.97      0.97      1939\n",
+      "weighted avg       0.97      0.97      0.97      1939\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print the classification report\n",
+    "print(classification_report(y_test, rf_y_pred))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "577888c9",
+   "metadata": {},
+   "source": [
+    "# KNN Classifier"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "0de678cf",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-3 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-3 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-3 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-3 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;minmaxscaler&#x27;, MinMaxScaler()),\n",
+       "                (&#x27;pca&#x27;, PCA(n_components=0.9)),\n",
+       "                (&#x27;kneighborsclassifier&#x27;, KNeighborsClassifier())])</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 sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;minmaxscaler&#x27;, MinMaxScaler()),\n",
+       "                (&#x27;pca&#x27;, PCA(n_components=0.9)),\n",
+       "                (&#x27;kneighborsclassifier&#x27;, KNeighborsClassifier())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" ><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;MinMaxScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.MinMaxScaler.html\">?<span>Documentation for MinMaxScaler</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>MinMaxScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-11\" type=\"checkbox\" ><label for=\"sk-estimator-id-11\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;PCA<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.decomposition.PCA.html\">?<span>Documentation for PCA</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>PCA(n_components=0.9)</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-12\" type=\"checkbox\" ><label for=\"sk-estimator-id-12\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;KNeighborsClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.neighbors.KNeighborsClassifier.html\">?<span>Documentation for KNeighborsClassifier</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>KNeighborsClassifier()</pre></div> </div></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "Pipeline(steps=[('minmaxscaler', MinMaxScaler()),\n",
+       "                ('pca', PCA(n_components=0.9)),\n",
+       "                ('kneighborsclassifier', KNeighborsClassifier())])"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Create the KNN Full Pipeline\n",
+    "knn_full_pipeline = make_pipeline(scaler, pca, KNeighborsClassifier())\n",
+    "\n",
+    "# Fit the full pipeline to the data\n",
+    "knn_full_pipeline.fit(X_train, y_train)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "01a14b60",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "knn_y_pred = knn_full_pipeline.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "a8e2a741",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.97      0.95      0.96       722\n",
+      "           1       0.97      0.98      0.98      1217\n",
+      "\n",
+      "    accuracy                           0.97      1939\n",
+      "   macro avg       0.97      0.97      0.97      1939\n",
+      "weighted avg       0.97      0.97      0.97      1939\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print the classification report\n",
+    "print(classification_report(y_test, knn_y_pred))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "46424b6f",
+   "metadata": {},
+   "source": [
+    "# Support Vector Classifier"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "cfc59f62",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-4 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-4 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-4 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-4 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-4 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-4 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-4 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-4 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-4 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-4\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;minmaxscaler&#x27;, MinMaxScaler()),\n",
+       "                (&#x27;pca&#x27;, PCA(n_components=0.9)), (&#x27;svc&#x27;, SVC())])</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 sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-13\" type=\"checkbox\" ><label for=\"sk-estimator-id-13\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;minmaxscaler&#x27;, MinMaxScaler()),\n",
+       "                (&#x27;pca&#x27;, PCA(n_components=0.9)), (&#x27;svc&#x27;, SVC())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-14\" type=\"checkbox\" ><label for=\"sk-estimator-id-14\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;MinMaxScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.preprocessing.MinMaxScaler.html\">?<span>Documentation for MinMaxScaler</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>MinMaxScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-15\" type=\"checkbox\" ><label for=\"sk-estimator-id-15\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;PCA<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.decomposition.PCA.html\">?<span>Documentation for PCA</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>PCA(n_components=0.9)</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-16\" type=\"checkbox\" ><label for=\"sk-estimator-id-16\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;SVC<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.svm.SVC.html\">?<span>Documentation for SVC</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>SVC()</pre></div> </div></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "Pipeline(steps=[('minmaxscaler', MinMaxScaler()),\n",
+       "                ('pca', PCA(n_components=0.9)), ('svc', SVC())])"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Create the SVC Full Pipeline\n",
+    "svc_full_pipeline = make_pipeline(scaler, pca, SVC())\n",
+    "\n",
+    "# Fit the full pipeline to the data\n",
+    "svc_full_pipeline.fit(X_train, y_train)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "7c66317b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "svc_y_pred = svc_full_pipeline.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "004f9dc8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.97      0.95      0.96       722\n",
+      "           1       0.97      0.98      0.98      1217\n",
+      "\n",
+      "    accuracy                           0.97      1939\n",
+      "   macro avg       0.97      0.97      0.97      1939\n",
+      "weighted avg       0.97      0.97      0.97      1939\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print the classification report\n",
+    "print(classification_report(y_test, knn_y_pred))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d50df727",
+   "metadata": {},
+   "source": [
+    "# Gradient Boosting Classifier"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "faddfffd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Create a pipeline using GB Classifier\n",
+    "gb_full_pipeline = make_pipeline(scaler, pca, GradientBoostingClassifier())\n",
+    "\n",
+    "# Fit the full pipeline to the data\n",
+    "gb_full_pipeline.fit(X_train, y_train)\n",
+    "\n",
+    "#Get the prediction\n",
+    "gb_y_pred = gb_full_pipeline.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "9f03b209",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           0       0.97      0.94      0.96       722\n",
+      "           1       0.97      0.98      0.98      1217\n",
+      "\n",
+      "    accuracy                           0.97      1939\n",
+      "   macro avg       0.97      0.96      0.97      1939\n",
+      "weighted avg       0.97      0.97      0.97      1939\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print the classification report\n",
+    "print(classification_report(y_test, gb_y_pred))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f86ff3ff",
+   "metadata": {},
+   "source": [
+    "# Best Models Comparison"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "216b337d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "best_models = pd.DataFrame({\"Classifier\" : [\"logistic_regression\", \"decision_tree\", \"random_forest\", \"knn\", \"svc\", \"gradient_boosting\"],\n",
+    "            \"Accuracy\" : [accuracy_score(y_test, log_y_pred)*100,\n",
+    "                         accuracy_score(y_test, dt_y_pred)*100,\n",
+    "                         accuracy_score(y_test, rf_y_pred)*100,\n",
+    "                         accuracy_score(y_test, knn_y_pred)*100,\n",
+    "                         accuracy_score(y_test, svc_y_pred)*100,\n",
+    "                         accuracy_score(y_test, gb_y_pred)*100]},\n",
+    "                          )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "fd2bcebd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Format the accuracy column to 2 decimal places\n",
+    "best_models['Accuracy'] = best_models['Accuracy'].round(2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "eb720cd0",
+   "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>Classifier</th>\n",
+       "      <th>Accuracy</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>logistic_regression</td>\n",
+       "      <td>95.98</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>decision_tree</td>\n",
+       "      <td>95.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>random_forest</td>\n",
+       "      <td>97.37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>knn</td>\n",
+       "      <td>97.16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>svc</td>\n",
+       "      <td>97.58</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>gradient_boosting</td>\n",
+       "      <td>96.91</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Classifier  Accuracy\n",
+       "0  logistic_regression     95.98\n",
+       "1        decision_tree     95.00\n",
+       "2        random_forest     97.37\n",
+       "3                  knn     97.16\n",
+       "4                  svc     97.58\n",
+       "5    gradient_boosting     96.91"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "best_models"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "d04cc4c0",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "barplot() got multiple values for argument 'data'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[1;32mIn[55], line 2\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;66;03m#Plot the data\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m ax \u001b[38;5;241m=\u001b[39m \u001b[43msns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbarplot\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mClassifier\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mAccuracy\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mbest_models\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m      3\u001b[0m plt\u001b[38;5;241m.\u001b[39mxticks(fontsize\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m8\u001b[39m, rotation\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m30\u001b[39m)\n\u001b[0;32m      4\u001b[0m plt\u001b[38;5;241m.\u001b[39mshow()\n",
+      "\u001b[1;31mTypeError\u001b[0m: barplot() got multiple values for argument 'data'"
+     ]
+    }
+   ],
+   "source": [
+    "#Plot the data\n",
+    "ax = sns.barplot('Classifier', 'Accuracy', data = best_models)\n",
+    "plt.xticks(fontsize=8, rotation=30)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "544c819e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Saved logistic_regression model to trained_models/logistic_regression_model.pkl\n",
+      "Saved decision_tree model to trained_models/decision_tree_model.pkl\n",
+      "Saved random_forest model to trained_models/random_forest_model.pkl\n",
+      "Saved knn model to trained_models/knn_model.pkl\n",
+      "Saved svc model to trained_models/svc_model.pkl\n",
+      "Saved gradient_boosting model to trained_models/gradient_boosting_model.pkl\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pickle\n",
+    "import os\n",
+    "\n",
+    "# Create a directory to store the models if it doesn't exist\n",
+    "if not os.path.exists('trained_models'):\n",
+    "    os.makedirs('trained_models')\n",
+    "\n",
+    "# Dictionary of models to save\n",
+    "models = {\n",
+    "    'logistic_regression': logreg_full_pipeline,\n",
+    "    'decision_tree': dt_full_pipeline,\n",
+    "    'random_forest': rf_full_pipeline,\n",
+    "    'knn': knn_full_pipeline,\n",
+    "    'svc': svc_full_pipeline,\n",
+    "    'gradient_boosting': gb_full_pipeline\n",
+    "}\n",
+    "\n",
+    "# Save each model\n",
+    "for model_name, model in models.items():\n",
+    "    filename = f'trained_models/{model_name}_model.pkl'\n",
+    "    with open(filename, 'wb') as file:\n",
+    "        pickle.dump(model, file)\n",
+    "    print(f'Saved {model_name} model to {filename}')\n",
+    "\n",
+    "# Function to load a saved model\n",
+    "def load_model(model_name):\n",
+    "    \"\"\"\n",
+    "    Load a saved model from the trained_models directory\n",
+    "    \n",
+    "    Parameters:\n",
+    "    model_name (str): Name of the model to load (without '_model.pkl')\n",
+    "    \n",
+    "    Returns:\n",
+    "    object: The loaded model pipeline\n",
+    "    \"\"\"\n",
+    "    filename = f'trained_models/{model_name}_model.pkl'\n",
+    "    with open(filename, 'rb') as file:\n",
+    "        model = pickle.load(file)\n",
+    "    return model\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3417ea8a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Prediction Models/wine_type/winequalityN.csv b/Prediction Models/wine_type/winequalityN.csv
new file mode 100644
index 00000000..e9987e40
--- /dev/null
+++ b/Prediction Models/wine_type/winequalityN.csv	
@@ -0,0 +1,6498 @@
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