Predicting_Parkinson_s_Disease.ipynb

{
  "cells": [
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      "cell_type": "markdown",
      "metadata": {
        "id": "1tZIEYqcdzpH"
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      "source": [
        "# Predicting Parkinson's Disease- A Case study \n",
        "\n",
        "Parkinson’s disease is a progressive neurological disorder. The very first signs of this disease is that the patients faces problems with movements. Tracking Parkinson's disease symptom progression often uses the Unified\n",
        "Parkinson’s Disease Rating Scale (UPDRS), which requires the patient's presence in clinic, and time-consuming physical examinations by trained medical staff. It makes early detection of disease difficult. However, in recent studies remote replication of UPDRS has appeared  as an alternative approach to predict this disease. Wherein, range of biomedical voice measurements were captured using telemonitoring deive installed at patient's home. These biomedical voice measurements meaures the remote symptom progression. \n",
        "\n",
        "Researchers Athanasios Tsanas and Max Little of the University of Oxford, in collaboration with 10 medical centers in the US and Intel Corporation developed the telemonitoring device to record the speech signals and presented it in a form of data set for analysis purpose. The data set is available on UCI repository weblink https://archive.ics.uci.edu/ml/datasets/Parkinsons+Telemonitoring . The data set is composed of a range of biomedical voice measurements from 42 people with early-stage Parkinson's disease recruited to a six-month trial of a telemonitoring device. It has 5875 cases represented in 20 features. The details of features are as below:\n",
        "\n",
        "1. age - Subject age \n",
        "2. sex - Subject gender '0' - male, '1' - female \n",
        "3. test_time - Time since recruitment into the trial. The integer part is the number of days since recruitment. \n",
        "4. motor_UPDRS - Clinician's motor UPDRS score, linearly interpolated \n",
        "5. total_UPDRS - Clinician's total UPDRS score, linearly interpolated \n",
        "5. Jitter(%)\n",
        "6. Jitter(Abs)\n",
        "7. Jitter:RAP\n",
        "8. Jitter:PPQ5\n",
        "9. Jitter:DDP - Several measures of variation in fundamental frequency \n",
        "10. Shimmer\n",
        "11. Shimmer(dB)\n",
        "12. Shimmer:APQ3\n",
        "13. Shimmer:APQ5\n",
        "14. Shimmer:APQ11\n",
        "15. Shimmer:DDA - Several measures of variation in amplitude \n",
        "16. NHR\n",
        "17. HNR - Two measures of ratio of noise to tonal components in the voice \n",
        "18. RPDE - A nonlinear dynamical complexity measure \n",
        "19. DFA - Signal fractal scaling exponent \n",
        "20. PPE - A nonlinear measure of fundamental frequency variation \n",
        "\n",
        "Given this medical data set, the objectives of this case study are as follows:\n",
        "\n",
        "1. Predict total_UPDRS score given voice measurements as features\n",
        "\n",
        "2. Identify important features that influence total_UPDRS score \n",
        "\n",
        "3. Relational strength between total_UPDRS score and other features present in the data set\n",
        "\n",
        "4. Discover if the diease is age specific\n",
        "\n",
        "In order to meet above mentioned objectives using machine learning, we need to undergo  machine learning process which include key steps as defined below.\n",
        "\n",
        "1. Understanding the data\n",
        "\n",
        "            - distribution of features\n",
        "            - features types\n",
        "            \n",
        "2. Data pre-processing\n",
        "\n",
        "            - handling missing values(if present in the data set)\n",
        "            - Scaling (if features are of variant scales)\n",
        "            - handling categorical features( if present in the data set then converting them to suitable numerical \n",
        "              values using Encoder in Sklearn)\n",
        "3. Selecting supervised technique\n",
        "\n",
        "            - Classification( if predictive feature is categorical)\n",
        "            - Regression (if predictive feature is numerical)\n",
        "\n",
        "4. Selecting right supervised technique for a given problem\n",
        "\n",
        "           - preparing suit of supervised techniques selected in step 3 ( suit is prepared for the reason that we \n",
        "             may not know in advance which algorithm will perform better)  \n",
        "             \n",
        "           - selecting the technique with best accuracy score on k- cross validation  \n",
        "           \n",
        "5. Hyperparamter optimization of selected supervised technique in step 4\n",
        "\n",
        "6. Using the selected model for predictive task using appropriate metrices\n",
        "\n",
        "7. Interpret the results\n",
        "\n",
        "8. From the selected supervised technique, mine important features for the target class (to address objective 2)\n",
        "\n",
        "9. Visualization of correlation plot to know relational strength between target feature with other features in the data set\n",
        "\n",
        "10. Understanding relational between gender and total_UPDRS score \n",
        "\n",
        "Below we walk through steps 1-10 mentioned above of the machine learning process using  python to meet the objectives given for this case study. "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EsdDrAL7dzpV",
        "outputId": "04d76f50-00f2-4671-c727-1749fb1159f6"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "CRUxTzpme28p"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "\n",
        "import io\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1Inhg47zdzpS"
      },
      "source": [
        "# Importing Base  Libraries"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0bKyn7fLdzpZ"
      },
      "source": [
        "# Loading the Data set"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "dZH6C_SddzpZ"
      },
      "outputs": [],
      "source": [
        "Dataset_pk = pd.read_csv('drive/MyDrive/Colab Notebooks/datasets/parkinsons_n.csv')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MgmSJOCydzpa"
      },
      "source": [
        "# Analysing Data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "b7Smjspedzpa",
        "outputId": "63320c16-56f0-4205-f0a2-96ddedc00e6d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 5875 entries, 0 to 5874\n",
            "Data columns (total 22 columns):\n",
            " #   Column         Non-Null Count  Dtype  \n",
            "---  ------         --------------  -----  \n",
            " 0   subject#       5875 non-null   int64  \n",
            " 1   age            5875 non-null   int64  \n",
            " 2   sex            5875 non-null   int64  \n",
            " 3   test_time      5875 non-null   float64\n",
            " 4   motor_UPDRS    5875 non-null   float64\n",
            " 5   total_UPDRS    5875 non-null   float64\n",
            " 6   Jitter(%)      5875 non-null   float64\n",
            " 7   Jitter(Abs)    5875 non-null   float64\n",
            " 8   Jitter:RAP     5875 non-null   float64\n",
            " 9   Jitter:PPQ5    5875 non-null   float64\n",
            " 10  Jitter:DDP     5875 non-null   float64\n",
            " 11  Shimmer        5875 non-null   float64\n",
            " 12  Shimmer(dB)    5875 non-null   float64\n",
            " 13  Shimmer:APQ3   5875 non-null   float64\n",
            " 14  Shimmer:APQ5   5875 non-null   float64\n",
            " 15  Shimmer:APQ11  5875 non-null   float64\n",
            " 16  Shimmer:DDA    5875 non-null   float64\n",
            " 17  NHR            5875 non-null   float64\n",
            " 18  HNR            5875 non-null   float64\n",
            " 19  RPDE           5875 non-null   float64\n",
            " 20  DFA            5875 non-null   float64\n",
            " 21  PPE            5875 non-null   float64\n",
            "dtypes: float64(19), int64(3)\n",
            "memory usage: 1009.9 KB\n",
            "None\n"
          ]
        }
      ],
      "source": [
        "print(Dataset_pk.info())"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Dataset_pk_target = Dataset_pk.iloc[:,5]\n",
        "Dataset_pk=Dataset_pk.drop(['age', 'subject#', 'sex'] , axis=1)\n",
        "Dataset_pk= Dataset_pk.drop(['total_UPDRS'], axis=1)\n",
        "# Provide 'Address' as the column name\n",
        "Dataset_pk['total_UPDRS'] = Dataset_pk_target\n",
        "print(Dataset_pk.info)\n"
      ],
      "metadata": {
        "id": "nxj8qD_rk71D",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cea54558-e2b7-4dd2-ee88-df4e95d284e5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<bound method DataFrame.info of       test_time  motor_UPDRS  Jitter(%)  Jitter(Abs)  Jitter:RAP  Jitter:PPQ5  \\\n",
            "0        5.6431       28.199    0.00662     0.000034     0.00401      0.00317   \n",
            "1       12.6660       28.447    0.00300     0.000017     0.00132      0.00150   \n",
            "2       19.6810       28.695    0.00481     0.000025     0.00205      0.00208   \n",
            "3       25.6470       28.905    0.00528     0.000027     0.00191      0.00264   \n",
            "4       33.6420       29.187    0.00335     0.000020     0.00093      0.00130   \n",
            "...         ...          ...        ...          ...         ...          ...   \n",
            "5870   142.7900       22.485    0.00406     0.000031     0.00167      0.00168   \n",
            "5871   149.8400       21.988    0.00297     0.000025     0.00119      0.00147   \n",
            "5872   156.8200       21.495    0.00349     0.000025     0.00152      0.00187   \n",
            "5873   163.7300       21.007    0.00281     0.000020     0.00128      0.00151   \n",
            "5874   170.7300       20.513    0.00282     0.000021     0.00135      0.00166   \n",
            "\n",
            "      Jitter:DDP  Shimmer  Shimmer(dB)  Shimmer:APQ3  Shimmer:APQ5  \\\n",
            "0        0.01204  0.02565        0.230       0.01438       0.01309   \n",
            "1        0.00395  0.02024        0.179       0.00994       0.01072   \n",
            "2        0.00616  0.01675        0.181       0.00734       0.00844   \n",
            "3        0.00573  0.02309        0.327       0.01106       0.01265   \n",
            "4        0.00278  0.01703        0.176       0.00679       0.00929   \n",
            "...          ...      ...          ...           ...           ...   \n",
            "5870     0.00500  0.01896        0.160       0.00973       0.01133   \n",
            "5871     0.00358  0.02315        0.215       0.01052       0.01277   \n",
            "5872     0.00456  0.02499        0.244       0.01371       0.01456   \n",
            "5873     0.00383  0.01484        0.131       0.00693       0.00870   \n",
            "5874     0.00406  0.01907        0.171       0.00946       0.01154   \n",
            "\n",
            "      Shimmer:APQ11  Shimmer:DDA       NHR     HNR     RPDE      DFA      PPE  \\\n",
            "0           0.01662      0.04314  0.014290  21.640  0.41888  0.54842  0.16006   \n",
            "1           0.01689      0.02982  0.011112  27.183  0.43493  0.56477  0.10810   \n",
            "2           0.01458      0.02202  0.020220  23.047  0.46222  0.54405  0.21014   \n",
            "3           0.01963      0.03317  0.027837  24.445  0.48730  0.57794  0.33277   \n",
            "4           0.01819      0.02036  0.011625  26.126  0.47188  0.56122  0.19361   \n",
            "...             ...          ...       ...     ...      ...      ...      ...   \n",
            "5870        0.01549      0.02920  0.025137  22.369  0.64215  0.55314  0.21367   \n",
            "5871        0.01904      0.03157  0.011927  22.886  0.52598  0.56518  0.12621   \n",
            "5872        0.01877      0.04112  0.017701  25.065  0.47792  0.57888  0.14157   \n",
            "5873        0.01307      0.02078  0.007984  24.422  0.56865  0.56327  0.14204   \n",
            "5874        0.01470      0.02839  0.008172  23.259  0.58608  0.57077  0.15336   \n",
            "\n",
            "      total_UPDRS  \n",
            "0          34.398  \n",
            "1          34.894  \n",
            "2          35.389  \n",
            "3          35.810  \n",
            "4          36.375  \n",
            "...           ...  \n",
            "5870       33.485  \n",
            "5871       32.988  \n",
            "5872       32.495  \n",
            "5873       32.007  \n",
            "5874       31.513  \n",
            "\n",
            "[5875 rows x 19 columns]>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mMUzrtmzdzpc"
      },
      "source": [
        "The data set has 5875 rows and 19 features. where, all features are numerical in nature. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vIvSJxJDdzpd"
      },
      "source": [
        "# Inspecting Distribution of Features"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "kw9F7N33dzpd",
        "outputId": "60e50443-1edc-4f2d-c16e-6ab2c5e7b72c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 979
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x1500 with 25 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ],
      "source": [
        "Dataset_pk.hist( figsize=(15, 15))\n",
        "\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8LGStsibdzpe"
      },
      "source": [
        "The result reveals that all features have different scale. Hence scaling them before applying machine learning models is important to get unbiased results. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sD-or8uBdzpf"
      },
      "source": [
        "# Inspecting  Features using Boxplot"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Em5f0QrNdzpf",
        "outputId": "9f77c9f4-9203-42ad-a431-d51151cbc33a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2160x2160 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "Dataset_pk.plot(kind='box',figsize=(30,30) )\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5u9_OTRVdzpf"
      },
      "source": [
        "Boxplot analysis help in identifying the median and outliers present in features. Large difference in median values necessitates scaling down the features. Presence of  very few outliers can be ignored. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "v2PfzeObdzpg"
      },
      "source": [
        "# Visualizing Interactions between features"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "cGlLr7N3dzpg"
      },
      "outputs": [],
      "source": [
        "grr=pd.plotting.scatter_matrix(Dataset_pk, figsize=(15, 15), marker='o',\n",
        "                        hist_kwds={'bins': 20}, alpha=.6, color='red')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9GN-ljNmdzpg"
      },
      "source": [
        "The scatter plot gives a relational structure between pair of variables. For eg. feature Jitter for eg. appears to have positive and strong correlation with Jitter(Abs), Jitter:RAP, Jitter:PPQ5 ,Jitter:DDP. Similarly,   motor_UPDRS and total UPDRS are having strong positive correlation. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dI0GwSRFdzph"
      },
      "source": [
        "# Visualizing correlation strength"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ghk7eZvCdzph",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 850
        },
        "outputId": "86e18d44-1598-4bb6-cee4-aaaebe75643a"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1900x1500 with 2 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ],
      "source": [
        "f = plt.figure(figsize=(19, 15))\n",
        "plt.matshow(Dataset_pk.corr(), fignum=f.number)\n",
        "plt.xticks(range(Dataset_pk.shape[1]), Dataset_pk.columns, fontsize=14, rotation=45)\n",
        "plt.yticks(range(Dataset_pk.shape[1]), Dataset_pk.columns, fontsize=14)\n",
        "cb = plt.colorbar()\n",
        "cb.ax.tick_params(labelsize=14)\n",
        "#plt.title('Correlation Matrix', fontsize=16);"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "28YQOQebdzph"
      },
      "source": [
        "The yellow color shows strong positive correlation whereas, purple color indicates strong negative correlation. For eg. it is revealed that HNR has a strong negative relation from Jitter to NHR."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2cYJlHiCdzpi"
      },
      "source": [
        "# Selecting Supervised Technique\n",
        "\n",
        "The choice is supervised technique is Regression since the total_UPDRS(the predictive feature) is numerical in nature. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0mudHGzxdzpi"
      },
      "source": [
        "# Design Hold-Out enviornment "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "5hfCJ18Jdzpi"
      },
      "outputs": [],
      "source": [
        "# importing method to perform cross validation\n",
        "from sklearn.model_selection import train_test_split \n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ex-rwT5qdzpj",
        "outputId": "82ca89c0-3dab-4ea5-9c39-ae86b67443a9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(5875,)\n"
          ]
        }
      ],
      "source": [
        "# My_data contains all data points from My_data set from from third feature to 19th feature(indicator features)\n",
        "My_data = Dataset_pk.iloc[:,0:18] \n",
        "\n",
        "# My_target contains class information which is 19th feature in the data set of \n",
        "\n",
        "My_data_target=Dataset_pk.iloc[:,18]\n",
        "print(My_data_target.shape)\n",
        "\n",
        "#print(Y_test.head())"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "X_train, X_test, Y_train, Y_test = train_test_split(My_data, My_data_target, test_size=0.8, random_state=10)\n"
      ],
      "metadata": {
        "id": "TYC229wns_V7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RNlx08YJdzpj"
      },
      "source": [
        "# Selecting right Regression technique for a given problem\n",
        "\n",
        "Since we do not have prior knowledge which model will perform best for a given problem so, we make suit of regression model (both linear and non-linear)and choose the model that performs best under cross validation. However, it is important to first standardize the data for the reason that all features are in different scales. \n",
        "\n",
        "We make use of Sklearn Pipeline to streamline the process of standardization and building Regression suit. The process starts with loading appropriate libraries from sklearn. "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "HNe2FeaPdzpj"
      },
      "outputs": [],
      "source": [
        "# importing linear and non linear regression models\n",
        "from sklearn import linear_model  \n",
        "from sklearn.svm import SVR\n",
        "from sklearn.neighbors import KNeighborsRegressor\n",
        "from sklearn.tree import DecisionTreeRegressor\n",
        "from sklearn import metrics\n",
        "from sklearn import tree\n",
        "\n",
        "# importing sklearn Pipeline to automate the ML processes\n",
        "from sklearn.pipeline import Pipeline\n",
        "\n",
        "# importing sklearn preprocessing methods\n",
        "from sklearn.preprocessing import StandardScaler"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TdngxFcXdzpk"
      },
      "source": [
        "# Automating standardization and Regression suit using Sklearn Pipeline"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "eSw1RsIbdzpk"
      },
      "outputs": [],
      "source": [
        "# making pipeline of standardization and various regression models\n",
        "\n",
        "Pipeline_Models = []\n",
        "Pipeline_Models.append(('scaledLR', Pipeline([('Scaler', StandardScaler()),\n",
        "                                             ('LRmodel', linear_model.LinearRegression()\n",
        "                                             )]))) \n",
        "Pipeline_Models.append(('scaledLasso', Pipeline([('Scaler', StandardScaler()),\n",
        "                                             ('Lassomodel', linear_model.Lasso()\n",
        "                                             )]))) \n",
        "\n",
        "Pipeline_Models.append(('scaledRidge', Pipeline([('Scaler', StandardScaler()),\n",
        "                                             ('Ridgemodel', linear_model.Ridge()\n",
        "                                             )]))) \n",
        "\n",
        "\n",
        "Pipeline_Models.append(('scaledSVR', Pipeline([('Scaler', StandardScaler()),\n",
        "                                             ('SVRmodel', SVR()\n",
        "                                             )]))) \n",
        "\n",
        "\n",
        "Pipeline_Models.append(('scaledCART', Pipeline([('Scaler', StandardScaler()),\n",
        "                                             ('CARTmodel', DecisionTreeRegressor()\n",
        "                                             )]))) \n",
        "\n",
        "\n",
        "Pipeline_Models.append(('scaledKNN', Pipeline([('Scaler', StandardScaler()),\n",
        "                                             ('KNNmodel', KNeighborsRegressor()\n",
        "                                             )])))\n",
        "\n",
        "    "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kRD4BUvydzpk"
      },
      "source": [
        "# Evaluating the Best performer"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "bcOsz4Stdzpk"
      },
      "outputs": [],
      "source": [
        "# loading cross validation libraries\n",
        "from sklearn.model_selection import KFold\n",
        "from sklearn.model_selection import cross_val_score"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rdIgyQS_dzpl",
        "outputId": "cd92ef08-348e-4d91-af52-ce609ca6443f",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The 10 cross validation results of each regressor algoritm are: \n",
            "\n",
            "          LR      Lasso      Ridge        SVR       CART        KNN\n",
            "0 -14.056344 -14.805505 -13.887018 -18.292233 -10.413904 -11.825803\n",
            "1 -10.251254 -11.369818 -10.208897 -13.500490  -9.322948 -14.909099\n",
            "2 -12.130726 -13.597621 -12.202333 -16.039134  -8.250228 -13.424328\n",
            "3 -17.715026 -16.790068 -17.437916 -21.866914  -8.886713 -14.412782\n",
            "4 -13.657759 -15.704785 -13.688048 -19.978212  -8.878029 -14.516528\n",
            "5 -10.829915 -11.813173 -10.907676 -16.927711 -11.340475 -12.292517\n",
            "6 -14.478588 -16.704248 -14.482165 -18.526669 -14.316215 -11.380969\n",
            "7  -9.404350  -9.457956  -9.276009 -10.871697 -10.725688 -11.186925\n",
            "8 -13.750885 -13.654935 -13.457756 -18.348744 -12.236458 -16.201272\n",
            "9 -11.241109 -12.559514 -11.279231 -15.305355  -8.166183 -11.844432\n",
            "\n",
            "\n",
            "The mean performance of each regressor algorithm are: \n",
            "\n",
            "LR      -12.751595\n",
            "Lasso   -13.645762\n",
            "Ridge   -12.682705\n",
            "SVR     -16.965716\n",
            "CART    -10.253684\n",
            "KNN     -13.199466\n",
            "dtype: float64\n",
            "The standaard deviattion of each regressor algorithm are: \n",
            "\n",
            "LR       2.471075\n",
            "Lasso    2.405640\n",
            "Ridge    2.403433\n",
            "SVR      3.196656\n",
            "CART     1.968190\n",
            "KNN      1.735060\n",
            "dtype: float64\n"
          ]
        }
      ],
      "source": [
        "# creating empty lists to store results of cross validation and the name of the model\n",
        "Model_Eval_Score =[]\n",
        "Name_of_model =[]\n",
        "# applying cross validation on each algorithm in suit\n",
        "for name, model_detail in Pipeline_Models:\n",
        "    # intiating cross validation with 10 iterations\n",
        "    kfold = KFold(n_splits=10)\n",
        "     # applying cross validation with 10 iterations on the training data\n",
        "    CV_Results = cross_val_score(model_detail, X_train, Y_train, cv=kfold,scoring='neg_mean_squared_error')\n",
        "    # adding result of each iteration in list\n",
        "    Model_Eval_Score.append(CV_Results)\n",
        "    # name of the corresponding algorithm is stored as follows\n",
        "    Name_of_model.append(name)\n",
        "\n",
        "# creating DataFrame with cross validation results where each row indicates the performance \n",
        "# of the model on different cross validation iterations\n",
        "CV_IterationsBy_model = pd.DataFrame(Model_Eval_Score,index=['LR','Lasso', 'Ridge',  \n",
        "                                 'SVR', 'CART', 'KNN'])\n",
        "print(\"The 10 cross validation results of each regressor algoritm are: \\n\")\n",
        "# printing the transpose of the data frame so that each column is a unique model\n",
        "Table_Results_CV= pd.DataFrame(CV_IterationsBy_model.T)\n",
        "print(Table_Results_CV)\n",
        "print(\"\\n\")\n",
        "# printing the mean of R2 square of each model\n",
        "print(\"The mean performance of each regressor algorithm are: \\n\")\n",
        "print(Table_Results_CV.mean())\n",
        "print(\"The standaard deviattion of each regressor algorithm are: \\n\")\n",
        "print(Table_Results_CV.std())\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "m5co7BlBdzpl"
      },
      "source": [
        "Based on the outcome of cross validation, Decision tree is identified as the best Regression model for the given data set"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XamQAiv8dzpm"
      },
      "source": [
        "# Hyperparameter Optimization of Decision tree"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "CvIyH2wXdzpm"
      },
      "outputs": [],
      "source": [
        "# loading GridSearchCV() for hyperparameter tuning\n",
        "from sklearn.model_selection import GridSearchCV\n",
        "from sklearn.preprocessing import StandardScaler"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "GtwFDY4odzpm",
        "outputId": "36dedd62-85d7-415d-90a8-ff2b479cf061",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 116
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "GridSearchCV(cv=5, estimator=DecisionTreeRegressor(),\n",
              "             param_grid={'max_depth': [2, 6, 8], 'max_leaf_nodes': [5, 20, 100],\n",
              "                         'min_samples_leaf': [20, 40, 100],\n",
              "                         'min_samples_split': [10, 20, 40]})"
            ],
            "text/html": [
              "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GridSearchCV(cv=5, estimator=DecisionTreeRegressor(),\n",
              "             param_grid={&#x27;max_depth&#x27;: [2, 6, 8], &#x27;max_leaf_nodes&#x27;: [5, 20, 100],\n",
              "                         &#x27;min_samples_leaf&#x27;: [20, 40, 100],\n",
              "                         &#x27;min_samples_split&#x27;: [10, 20, 40]})</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 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 sk-toggleable__label-arrow\">GridSearchCV</label><div class=\"sk-toggleable__content\"><pre>GridSearchCV(cv=5, estimator=DecisionTreeRegressor(),\n",
              "             param_grid={&#x27;max_depth&#x27;: [2, 6, 8], &#x27;max_leaf_nodes&#x27;: [5, 20, 100],\n",
              "                         &#x27;min_samples_leaf&#x27;: [20, 40, 100],\n",
              "                         &#x27;min_samples_split&#x27;: [10, 20, 40]})</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label 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 sk-toggleable__label-arrow\">estimator: DecisionTreeRegressor</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeRegressor()</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator 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 sk-toggleable__label-arrow\">DecisionTreeRegressor</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeRegressor()</pre></div></div></div></div></div></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ],
      "source": [
        "# It is important to standardize the training data set before applying hyerparameter optimization for the \n",
        "# said model as this model was discovered by cross validation which used standardized training data. \n",
        "\n",
        "# create object of StandardScaler()\n",
        "\n",
        "\n",
        "# My_target contains class information which is 19th feature in the data set of \n",
        "\n",
        "\n",
        "Standardisation = StandardScaler()\n",
        "Standardisation.fit(X_train)\n",
        "Scaleddata_trainX= Standardisation.transform(X_train)\n",
        "#Scaleddata_trainY= Standardisation.transform(Y_test)\n",
        "\n",
        "# setting paramters\n",
        "param_grid_DTR = {\"min_samples_split\": [10, 20, 40],\n",
        "              \"max_depth\": [2, 6, 8],\n",
        "              \"min_samples_leaf\": [20, 40, 100],\n",
        "              \"max_leaf_nodes\": [5, 20, 100],\n",
        "              }\n",
        "# setting paramters\n",
        "\n",
        "# Creating instance of SVR model\n",
        "Model_DTR = DecisionTreeRegressor()\n",
        "# Using GridSearchCV to pass the model,values to parameters for tuning\n",
        "# and cross validation folds\n",
        "Grid_DTR = GridSearchCV(estimator =Model_DTR, param_grid=param_grid_DTR , cv=5)\n",
        "# fitting the model on the training set\n",
        "Grid_DTR.fit(Scaleddata_trainX,Y_train )\n",
        "# printing the best parameters from the given list for the data set in consideration\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Grid_DTR.best_params_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QBYdOVG7BoBr",
        "outputId": "353f2537-61bc-4366-edac-a6dac356dae1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'max_depth': 8,\n",
              " 'max_leaf_nodes': 100,\n",
              " 'min_samples_leaf': 20,\n",
              " 'min_samples_split': 10}"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HY2SmsXidzpn"
      },
      "source": [
        "# Fitting the tuned parameter on the scaled training data set"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "mSGhUHK0dzpn",
        "outputId": "58409fd9-0d4a-478e-efc7-571f78bed9e0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 91
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeRegressor(max_depth=8, max_leaf_nodes=100, min_samples_leaf=20,\n",
              "                      min_samples_split=10)"
            ],
            "text/html": [
              "<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeRegressor(max_depth=8, max_leaf_nodes=100, min_samples_leaf=20,\n",
              "                      min_samples_split=10)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" checked><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">DecisionTreeRegressor</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeRegressor(max_depth=8, max_leaf_nodes=100, min_samples_leaf=20,\n",
              "                      min_samples_split=10)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ],
      "source": [
        "Model_DTR = DecisionTreeRegressor(max_depth= 8,\n",
        " max_leaf_nodes= 100,\n",
        " min_samples_leaf = 20,\n",
        " min_samples_split=  10)\n",
        "\n",
        "Model_DTR.fit(Scaleddata_trainX,Y_train)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b7qkvYwtdzpn"
      },
      "source": [
        "# Evaluating Performance of CART on Test data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PDqjd4Nsdzpo"
      },
      "source": [
        "It is important to perform same standardization on Test data as done on Training data  before using CART for Predictive task. "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Q3UNb0Ppdzpo"
      },
      "outputs": [],
      "source": [
        "Scaleddata_test= Standardisation.transform(X_test)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "j6VoW7zOdzpo"
      },
      "outputs": [],
      "source": [
        "# Getting prediction on train and test sets\n",
        "\n",
        "DTR_pred_test= Model_DTR.predict(Scaleddata_test)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "LwOFWBAYdzpo",
        "outputId": "582732b9-d22d-4bdb-a2ab-dbee5b96b999",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mean absolute Error: 2.206622495979164\n",
            "\n",
            "\n",
            "Mean squared Error: 8.798584987090395\n",
            "\n",
            "\n",
            "R2 score: 92.30000000000001 %\n"
          ]
        }
      ],
      "source": [
        "print(\"Mean absolute Error:\", metrics.mean_absolute_error(Y_test, DTR_pred_test))\n",
        "print(\"\\n\")\n",
        "print(\"Mean squared Error:\", metrics.mean_squared_error(Y_test, DTR_pred_test))\n",
        "print(\"\\n\")\n",
        "print(\"R2 score:\", round(metrics.r2_score(Y_test,DTR_pred_test),3)*100,\"%\")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The performance of CART is excellent as indicated by R2 score with low MAE. It shows the robustness of model on this dataset. "
      ],
      "metadata": {
        "id": "pkB38iZTftCT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# plotting predicted VS actual \n",
        "plt.scatter(Y_test, DTR_pred_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 447
        },
        "id": "7jQkhJeCDKaS",
        "outputId": "cac33ce3-5ecc-4982-93a0-6347563462ae"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x7f4f88ba20e0>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UexOXwcwdzpp"
      },
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IO4b9KFqdzpp"
      },
      "source": [
        "# Inspecting tree of CART "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "HUcZnt-tdzpp",
        "outputId": "e53121d4-2758-4630-efb0-b5b20d5b446a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 233
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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qrrvuMp1TalSoUEEOh0Nz5szRjBkz1LVrVx07dsx0FgAUSIMGDdS9e3dNnjzZdEqp0aBBAzkcDu3fv18jR47UpEmTVKdOHdntdq6lAgAAAADcNhYMBQAAACQtX75crVq10vDhw9W7d2/t3LlTYWFhqlChguk0AABQwqSnpyskJEQPPPCAxowZo1q1aik5OVlZWVkKCwuTu7u76UQAAADAaWzfvl0DBgxQ//79NX78eNM5pVrFihX15Zdfqnz58urZs6fOnTtnOgkAUIxZrVZlZmbKbrcrLCxMvr6+SktLM50FAAAA3BE5OTlyOBxq3LixVqxYodmzZ+vrr79W06ZNTacBAEqh/Px8RUVFqXfv3howYIC++eYb3XfffaazSo1q1aopICBAU6ZMMZ0CANe0dOlSHThwQCNGjDCdUioNGTJEq1ev1tGjR+Xj46PVq1ebTgKAAhkzZoxWrlyp9PR00ymlSs2aNRUREaGDBw/qn//8p+Lj49WwYUPZ7XYdPHjQdB4AAAAAoIRiwVAAAAA4taysLFmtVvn7+8vd3V2bN29WdHS0atSoYToNAACUIGfPnlVMTIxatWolHx8frVq1SuPHj9fhw4cVHx+vrl27ysXFxXQmAAAA4FSOHTum7t27q0WLFpo1axZz8jugWrVqWrx4sQ4fPqyAgADl5uaaTgIAFGNubm6KiIhQRkaG3N3dZbFYZLPZdOLECdNpAAAAQJFZvny5WrZsqVdeeUVjx47Vrl27ZLPZTGcBAEqpX375RU899ZRee+01TZs2TdHR0SpfvrzprFInNDRUW7Zs0Zo1a0ynAMBVRUdHq0uXLvL09DSdUmq1bNlS6enp8vPzU5cuXRQVFaX8/HzTWQBwXf7+/mrWrBmL3xeRKlWqyG63a8+ePZo4caIWLFighg0bymazaceOHabzAAAAAAAlDAuGAgAAwCmdOnVKdrtdzZo109GjR/Xtt98qOTlZDz30kOk0AABQgqSnpyskJES1atWS3W5Xo0aNlJycrB07digsLEzVq1c3nQgAAAA4pfPnz6tPnz66++67tWDBAlWoUMF0ktPw8PDQwoULtXLlSo0cOdJ0DgCgBPD09NTSpUuVmJiolJQUeXl5yeFw6PLly6bTAAAAgEKzZ8+eKw+29vDw0Pbt2xUREaG77rrLdBoAoJTatWuX2rVrp/Xr1+vbb7/ViBEjTCeVWu3atdPDDz+sqVOnmk4BgD85duyYFi9erJCQENMppV6VKlWUkJCgd955R6+++qr69u2rs2fPms4CgOsaNWqUPv30U/3www+mU0qtu++++8rCoTNmzFB6erqaNm0qq9XKQwcAAAAAAAXGgqEAAABwKpcuXZLD4VCDBg00b948ffjhh1q/fr26dOliOg0AAJQQZ86cUUxMjJo3by4fHx+lpqbqH//4h44cOaL4+Hh17drVdCIAAADg1C5fvqxBgwZp3759+vLLL1W1alXTSU7Hx8dHcXFxmjNnjiZMmGA6BwBQQlitVmVmZsputyssLEy+vr5KS0sznQUAAADcll9//VURERFq2rSp9uzZo2XLlikpKUn16tUznQYAKMUWLVqktm3bqmLFilqzZo38/PxMJ5V6ISEhio+P14kTJ0ynAMAfxMTE6N5771WfPn1MpzgFFxcX2e12LV++XOvWrVObNm20detW01kAcE02m02VKlXSjBkzTKeUeq6urrLZbNq6dasSExP1448/qn379rJYLEpKSlJ+fr7pRAAAAABAMcaCoQAAAHAaSUlJ8vb21iuvvKKRI0cqKytLwcHBKlu2rOk0AABQzOXn5ys1NVUhISF64IEH9NJLL8nPz0/p6enavn27wsLC9Je//MV0JgAAAABJY8eO1VdffaUvv/xSDRs2NJ3jtHr06KEpU6botdde06xZs0znAABKCDc3N0VERCgjI0Pu7u6yWCyy2WwstAAAAIASJz8/XwkJCfL29tbkyZMVFRWlrVu36vHHHzedBgAoxfLz8xUVFaVevXrJarVq1apVqlOnjuksp/D000/Lzc1Nc+bMMZ0CAFfk5eVp1qxZGjZsmCpUqGA6x6l06tRJGzduVI0aNdS2bVvOmQMottzc3DRs2DBNmTJFOTk5pnOcQpkyZWS1WrVmzRqtWrVKVatWVe/evdWqVSvFxsYqNzfXdCIAAAAAoBhiwVAAAACUehs3blSnTp3Uu3dvPfzww9qxY4ciIyNVuXJl02kAAKCYO378uKKiotSoUSN17NhR6enpmjRpko4cOaLo6Gi1bt3adCIAAACA33nvvff04Ycf6pNPPpGfn5/pHKc3YsQIhYeHKyQkRMuWLTOdAwAoQTw9PbV06VIlJiYqJSVFXl5ecjgcunz5suk0AAAA4IY2bdqkjh07KjAwUF26dNHOnTtlt9tVrlw502kAgFLs3Llz6tevn8aPH68333xTsbGxqlixouksp+Hm5qbBgwdr2rRpysvLM50DAJKkxYsX6+DBgxo+fLjpFKf0wAMPaMWKFRozZoyCgoIUEhKiS5cumc4CgD957rnn9MMPP+jzzz83neJ0LBaLkpKStHnzZjVv3lzDhg27cm48OzvbdB4AAAAAoBhhwVAAAACUWocPH1ZISIjatm2rnJwcrV69WvHx8apbt67pNAAAUIzl5eVp+fLlCggIUJ06dfTWW2/pscce03fffaeNGzcqODhYlSpVMp0JAAAA4P9YtGiRXnrpJb399tt66qmnTOfgvyZOnKhBgwapf//+2rx5s+kcAEAJY7ValZmZKbvdrrCwMPn6+iotLc10FgAAAHBVp0+flt1uV5s2bZSTk6M1a9YoNjZWNWrUMJ0GACjl9uzZo3bt2mnVqlX66quvFBYWZjrJKYWGhur777/XV199ZToFACRJ0dHReuyxx9SoUSPTKU6rXLlyioyM1Pz58xUXF6cOHTpo//79prMA4A/q1q2rXr16afLkyaZTnFaLFi0UGxurXbt2qWfPngoPD1e9evUUERGhn376yXQeAAAAAKAYYMFQAAAAlDq//vqrIiIi5OnpqaVLl2rWrFlKS0uTn5+f6TQAAFCMHT16VFFRUWrYsKH8/f21b98+ffDBBzp69Kiio6PVokUL04kAAAAAriE9PV0DBgzQ0KFD9cILL5jOwe+4uLho+vTpateunXr06KEDBw6YTgIAlDBubm6KiIhQRkaG3N3dZbFYZLPZdOLECdNpAAAAgCQpNzdXMTEx8vLy0rx58/TRRx9p7dq1atOmjek0AIATWLJkiXx9fVWhQgVt2LBBjzzyiOkkp+Xt7a3OnTtr6tSpplMAQIcPH9aSJUsUEhJiOgWSevfurfXr1+vixYvy9fXVsmXLTCcBwB+MGTNGa9as0fr1602nODUPDw85HA7t379fI0eOlMPhUN26dWW323Xs2DHTeQAAAAAAg1gwFAAAAKVGXl6eYmNj1bBhQzkcDr322mvatWuXbDabXFxcTOcBAIBiKC8vT8uXL1dAQIDq1q2rqKgo+fv7a+vWrdq4caOCg4Pl5uZmOhMAAADAdezfv189e/ZUx44duQGzmHJ1ddW8efNUs2ZNde/eXWfOnDGdBAAogf73sMDExESlpKTIy8tLDodDly9fNp0GAAAAJ/btt9+qdevWGj16tAYNGqSsrCyuVwMA3BH5+fmKiopSz5491aNHD6Wmpqpu3bqms5xeaGioFi1apP3795tOAeDkpk+frurVq6t3796mU/Bfnp6eWrdunaxWq7p166bw8HDl5eWZzgIASVKXLl3UokULffDBB6ZTIKlmzZqKiIjQgQMH9M9//lMJCQmqX7++bDab9uzZYzoPAAAAAGAAC4YCAACgVPjmm2/UunVrBQUFqVevXtq5c6fCwsJUoUIF02kAAKAYOnz4sKKiolS/fn098cQTOnPmjGbOnKkjR44oOjpaTZs2NZ0IAAAAoAB+/vln9erVS9WqVdNnn32mcuXKmU7CNVSpUkWLFi3SuXPn1KdPH2VnZ5tOAgCUUFarVZmZmbLb7QoLC5Ovr6/S0tJMZwEAAMDJHD58WDabTY8++qhq1qypLVu2yOFwqHLlyqbTAABO4Ny5cwoICND48eP15ptv6pNPPlHFihVNZ0FS3759VbNmTc2YMcN0CgAnlpubq5kzZ2rYsGFydXU1nYPfqVixoj766CNNmzZN7733nqxWq06fPm06CwAkSc8//7zi4uJ0/Phx0yn4rypVqshut+v7779XTEyM1qxZIy8vLwUEBGj79u2m8wAAAAAAdxALhgIAAKBE27VrlwICAvTYY4+pRo0a2rx5s6Kjo+Xu7m46DQAAFDOXLl1SQkKCrFar6tWrp0mTJmngwIHatWuXkpOTZbPZuHAeAAAAKEFycnLUr18/nTp1SkuWLNE999xjOgk3UKtWLS1ZskRbt27VM888o7y8PNNJAIASys3NTREREcrIyJC7u7ssFotsNptOnDhhOg0AAACl3IULFxQVFSVvb2+tXbtWCxcuVHJysry9vU2nAQCcxN69e+Xn56cVK1Zo2bJlCgsLM52E33F1ddWwYcM0c+ZMXbp0yXQOACe1aNEiHT16VMOGDTOdgmsIDg7W6tWrtWPHDrVq1Urr1q0znQQAGjx4sO69915NmzbNdAr+jwoVKshms2nHjh2aNWuWduzYoWbNmslqtfJwTQAAAABwEiwYCgAAgBLp9OnTCg8PV7NmzbRt2zYtWrRIycnJatq0qek0AABQzOzatUvh4eGqXbu2AgMDlZ2drblz5+rgwYOKjIxUgwYNTCcCAAAAuAXPP/+81qxZo0WLFql27dqmc1BATZo00fz585WYmMhNzACA2+bp6amlS5cqMTFRKSkp8vLyksPh0OXLl02nAQAAoBRKSkrSQw89pAkTJuiFF17Q1q1b1aNHD9NZAAAnsmzZMvn6+qpcuXLasGGDHn30UdNJuIrg4GCdPHlS8+fPN50CwElFR0fL399fDRs2NJ2C6/Dx8dGGDRvk7e2tzp07y+FwmE4C4OQqVKig4cOHa+rUqcrOzjadg6twdXWVzWbT1q1blZiYqNOnT6tDhw6yWCxKSkpSfn6+6UQAAAAAQBFhwVAAAACUKDk5OYqJiZGXl5dmzpypt99+W1u3blX37t1NpwEAgGLk4sWLSkhIkL+/vxo3bqyPP/5YQ4cO1d69e5WcnKz+/fvL1dXVdCYAAACAWzRx4kTNmDFDn376qVq2bGk6Bzepc+fOmj17tt59911uegIAFAqr1arMzEzZ7XaFhYXJ19dXaWlpprMAAABQSuzcuVNPPvmkevfuLYvFoj179igiIkIVKlQwnQYAcCIOh0M9evTQk08+qdWrV6tevXqmk3ANtWvXVs+ePTV16lTTKQCc0MGDB/XVV18pJCTEdAoKoHr16lqyZIlef/11jRs3TjabTefPnzedBcCJPffcczpz5owSEhJMp+A6XFxcZLVatXr1aq1atUpVq1ZV79691bJlS8XGxio3N9d0IgAAAACgkLFgKAAAAEqMpKQkNWnSRM8//7wGDRqkvXv3ym63q2zZsqbTAABAMZGVlaXw8HA9+OCDGjhwoCQpLi5OBw4cUGRkJBfKAwAAAKVAfHy8Xn31VU2aNEm9evUynYNbFBgYqIkTJ2rcuHH6/PPPTecAAEoBNzc3RUREKCMjQ+7u7rJYLLLZbDpx4oTpNAAAAJRQP/30k8LDw9W8eXOdPHlSqampio2N1X333Wc6DQDgRLKzs/XMM8/ohRde0MSJE/Wf//xHbm5uprNwA6GhoUpJSdG2bdtMpwBwMjExMapRo4asVqvpFBSQi4uLwsLClJSUpEWLFqlDhw7au3ev6SwATqpWrVrq27evJk2aZDoFBWSxWJSUlKTvvvtOLVq0UFBQkDw9PeVwOHThwgXTeQAAAACAQsKCoQAAACj2Nm3apC5duqh3795q1aqVsrKy5HA4VKVKFdNpAACgGMjOzlZCQoL8/f3l7e2tTz/9VEFBQdq3b5+Sk5PVv39/lStXznQmAAAAgEKQmpqqZ555RuPGjdPo0aNN5+A2hYeH67nnntPgwYO1evVq0zkAgFLC09NTS5cuVWJiolJSUuTl5SWHw6HLly+bTgMAAEAJkZeXp9jYWHl5eWnGjBl6++23tX79erVv3950GgDAyRw6dEgWi0WLFi3S0qVLFRYWZjoJBfT444+rUaNGio6ONp0CwInk5uZq1qxZCgoKkqurq+kc3KTu3btr8+bNKl++vFq3bs2DNwEYM2bMGG3atElpaWmmU3ATmjdvrtjYWO3atUtWq1Uvv/yy6tWrp4iICP3000+m8wAAAAAAt4kFQwEAAFBsHTlyRCEhIWrTpo0uXLigVatWKT4+XvXr1zedBgAAioHt27crPDxcDzzwgAYPHqyqVasqOTlZBw8eVGRkpOrUqWM6EQAAAEAh2rdvn5566il17dpVUVFRpnNQSCZNmqTu3burd+/e2rlzp+kcAEApYrValZmZKbvdrrCwMPn6+nJTGwAAAG5ow4YN6tChg4KCghQYGKi9e/fKbrerbNmyptMAAE4mJSVFPj4+ys3N1YYNG9S1a1fTSbgJLi4uGjFihObMmaNffvnFdA4AJ5GUlKTjx49r+PDhplNwi+rUqaOVK1fq2WefVf/+/WW325WTk2M6C4CT6dChg3x9ffX++++bTsEtqF+/vhwOh/bv36/Q0FA5HA7VqVNHdrtdR48eNZ0HAAAAALhFLBgKAACAYuf8+fOKioqSt7e3lixZoo8++khr165Vhw4dTKcBAADDfvnlF8XExMhisahp06aaP3++/v73v+vQoUOKj49X165d5eLiYjoTAAAAQCE7deqUunXrpjp16uizzz5jgYZSpEyZMvrkk0/k5eWlbt266fjx46aTAACliJubmyIiIpSRkSF3d3dZLBbZbDadOHHCdBoAAACKmWPHjslms6lt27Zyc3PT5s2b5XA4dM8995hOAwA4oZiYGPn7++uRRx5RWlqa6tevbzoJt2DYsGHKycnR3LlzTacAcBLR0dF64oknVK9ePdMpuA0VKlSQw+HQnDlzNGPGDHXt2pXz6ADuuNGjR2vevHk6fPiw6RTcInd3d0VEROjgwYOaMGGC5s2bJw8PD9lsNu3evdt0HgAAAADgJrFgKAAAAIqN/Px8JSQkqEmTJpowYYLGjRunXbt2yWazsfAXAABOLj09XSEhIapVq5bGjBmjWrVqKTk5WVlZWQoLC5O7u7vpRAAAAABF5NKlS+rfv78uXbqkRYsW6e677zadhEJWsWJFffnll3J1dVXPnj117tw500kAgFLG09NTS5cuVWJiolJSUuTl5SWHw6HLly+bTgMAAIBhOTk5cjgcaty4sVasWKHZs2fr66+/VtOmTU2nAQCcUHZ2toYOHapRo0ZpwoQJmjt3rtzc3Exn4RZVq1ZNAQEBmjJliukUAE7g+++/V3JyskJCQkynoJAMGTJEq1ev1pEjR+Tj46PVq1ebTgLgRAIDA1W9enVNmzbNdApuU+XKlWW327Vv3z7FxMRo7dq1aty4saxWq9LT003nAQAAAAAKiAVDAQAAUCysXbtW7du3V2BgoDpxmJaYAAAgAElEQVR16qS9e/cqIiJCd911l+k0AABgyNmzZxUTE6NWrVrJx8dHq1at0vjx43X48GHFx8era9euLCoOAAAAlHL5+fkKCgpSenq6vvzyS9WsWdN0EopItWrVtGTJEh0+fFgBAQHKzc01nQQAKIWsVqsyMzNlt9sVFhYmX19fpaWlmc4CAACAIcuXL1fLli31yiuvaOzYsVcebg0AgAmHDx9Wp06d9OWXX2rx4sUKCwvj2qhSIDQ0VFu2bNGaNWtMpwAo5aZPn66aNWuqe/fuplNQiFq2bKlNmzapXbt26tKli6KiopSfn286C4ATKF++vEJCQhQdHa0LFy6YzkEhqFChgmw2m7KysrRgwQIdO3ZMPj4+8vf3Z1FqAAAAACgBWDAUAAAARu3evVsBAQHy8/NTpUqVtHnzZsXGxnLjPwAATiw9PV0hISF64IEHZLfb1ahRIyUnJ2vHjh0KCwtT9erVTScCAAAAuEPGjx+vuLg4ff7552rWrJnpHBQxDw8PLVy4UCtXrtTIkSNN5wAASik3NzdFREQoIyND7u7uslgsstlsOnHihOk0AAAA3CF79uyR1WqVv7+/PDw8tH37dh5uDQAwatWqVfLx8VF2drY2bNigxx9/3HQSCkm7du3UunVrTZ061XQKgFIsNzdXc+bM0YgRI+Tq6mo6B4WsSpUqSkhI0DvvvKNXX31Vffv21dmzZ01nAXACo0aN0i+//KK5c+eaTkEhKlOmjKxWqzZu3Kjk5GRduHBBFotFFotFSUlJLEwNAAAAAMUUC4YCAADAiDNnzig8PFzNmjVTRkaG4uPjlZycrObNm5tOAwAABvz000+KiYlR8+bN5ePjo9TUVL366qs6cuSI4uPj1bVrV9OJAAAAAO6wWbNm6c0339T777/PMYET8fHxUVxcnObMmaMJEyaYzgEAlGKenp5aunSpEhMTlZKSIi8vLzkcDl2+fNl0GgAAAIrIr7/+qoiICDVt2lR79uzRsmXLlJSUpHr16plOAwA4sZiYGD322GNq27atUlNT5eHhYToJhSwkJETx8fE6efKk6RQApdSCBQt0/PhxDRs2zHQKioiLi4vsdruWL1+udevWqU2bNtq2bZvpLAClnLu7u/r166f33nuPRSRLqa5duyo1NVWrVq1S1apV1bt3b7Vo0UKxsbHKzc01nQcAAAAA+B0WDAUAAMAdlZOTo5iYGHl5eWnGjBmKiorStm3b1L9/f9NpAADgDsvPz1dqaqpCQkJUq1YtvfTSS/Lz81N6erq2b9+usLAw/eUvfzGdCQAAAMCAFStWaOTIkRo/frxCQkJM5+AO69Gjh6ZMmaLXXntNs2fPNp0DACjlrFarMjMzZbfbFRYWJl9fX6WlpZnOAgAAQCHKz89XQkKCmjRposmTJysqKkpbt27V448/bjoNAODELl68qKCgII0cOVLjxo3TggULVKVKFdNZKAKDBw+Wm5sb5zwAFJno6Gh169ZNdevWNZ2CItapUydt3LhRNWrUUJs2bTRr1izTSQBKubFjx2rbtm1auXKl6RQUIYvFoqSkJG3ZskUtW7ZUUFCQGjVqJIfDoQsXLpjOAwAAAACIBUMBAABwBy1fvlytWrXS888/r4EDB2rv3r2y2+0qV66c6TQAAHAHHT9+XFFRUWrUqJE6duyo9PR0TZo0SUeOHFF0dLRat25tOhEAAACAQTt27FDfvn3Vp08f/fOf/zSdA0NGjBih8PBwBQcHa9myZaZzAAClnJubmyIiIpSRkSF3d3dZLBbZbDadOHHCdBoAAABu06ZNm9SxY0cFBgaqc+fOysrK4po1AIBxR44cUadOnTRv3jzNnz9fkZGRcnFxMZ2FIuLm5qbBgwdr2rRpysvLM50DoJTZt2+fvvnmGx7E6UQeeOABrVixQmPGjFFQUJBCQkJ06dIl01kASqmHH35Y7dq10/vvv286BXdAs2bNFBsbq927d6tXr156+eWXVbduXUVEROjMmTOm8wAAAADAqbFgKAAAAIrcjh071L17d/n7+6t+/frKzMyUw+HQPffcYzoNAADcIXl5eVq+fLkCAgJUp04dvfXWW3rsscf03XffaePGjQoODlalSpVMZwIAAAAw7Pjx4+revbuaNm2q2NhYbo51chMnTtSgQYPUv39/bd682XQOAMAJeHp6aunSpUpMTFRKSoq8vLzkcDh0+fJl02kAAAC4SadPn5bdblebNm2Uk5OjNWvWKDY2Vu7u7qbTAABOLjU1VT4+Pjp79qzWrVun3r17m07CHRAaGqrvv/9eX331lekUAKVMdHS0atWqpe7du5tOwR1Urlw5RUZG6osvvlBcXJw6dOig/fv3m84CUEqNGTNGCxYs0Pfff286BXdIvXr15HA4tH//fo0aNUqTJ09W3bp1ZbfbdeTIEdN5AAAAAOCUWDAUAAAARebYsWMKCQlR8+bNdfLkSa1cuVJJSUny8PAwnQYAAO6Qo0ePKioqSg0bNpS/v7/27dunDz74QEePHlV0dLRatGhhOhEAAABAMXHhwgX17dtX5cqV0xdffKEKFSqYToJhLi4umj59utq1a6cePXrowIEDppMAAE7CarUqMzNTdrtdYWFh8vX1VVpamuksAAAAFEBubq5iYmLk5eWlefPm6aOPPtLatWvVpk0b02kAACgmJkaPPfaYfHx8tG7dOjVu3Nh0Eu4Qb29vderUSVOnTjWdAqCEOnDggMaNG6esrKwrn7t06ZJmz56t4cOHq2zZsgbrYEqfPn20fv16ZWdny9fXl4WpARSJfv366f7779e0adNMp+AOc3d3V0REhA4cOKAJEyZo3rx58vDwkM1m065du0znAQAAAIBTYcFQAAAAFLoLFy4oKipKjRs31qJFizRlyhStW7dOHTt2NJ0GAADugLy8PC1fvlwBAQGqW7euoqKi5O/vr61bt2rjxo0KDg6Wm5ub6UygyIWGhqpLly5/+KhatareeuutP3yua9euOnr0qOlcAACAO+LXX3/VX//6V509e/YPn8/Ly9PTTz+t3bt3a/HixapRo4ahQhQ3rq6umjdvntzd3dW9e3edOXPmT9tMnTpVy5cvN1AHACjN3NzcFBERoYyMDLm7u8tischms+nEiROm0wAAAHAN3377rVq3bq3Ro0dr0KBBysrKks1mk4uLi+k0AICTu3jxokaMGKGRI0dq7NixSkxM1D333GM6C3dYaGioFi1axAPSANyS06dP67333pO3t7csFov+85//KD4+XqdOndLQoUNN58EgT09PrVmzRl27dtWTTz6p8PBw5eXlmc4CUIq4uroqJCRE06dP16+//mo6BwZUrlxZdrtd33//vaZPn65169bJ29tbVqtVGzduNJ0HAAAAAE6BBUMBAABQaPLz85WQkKAmTZpowoQJCg0NVVZWloKDg1WmDFNPAABKu8OHDysqKkr169fXE088oTNnzmjmzJk6cuSIoqOj1bRpU9OJwB3l7u6ulJSUP3ycOXNG33333R8+t3//ftWqVct0LgAAwB0RFxenL774Qn5+fjp06NCVz7/wwgtatGiREhIS5OnpabAQxVGVKlW0ePFinTt3Tn369FF2drak396TfvnllzVq1Ci9//77hisBAKWVp6enli5dqsTERKWkpMjLy0sOh0OXL182nQYAAID/Onz4sGw2mx599FHVrFlTW7ZskcPhUOXKlU2nAQCgo0ePqkuXLlfOkURGRnJdtZN66qmnVLNmTc2YMcN0CoAS6Ny5c1f+vGbNGg0ePFjDhw+Xh4fHlfOncF6VKlXS3LlzNW3aNL333nuyWq06ffr0NbefPXv2nYsDUCqEhITowoUL+uSTT0ynwKDy5cvLZrMpMzNTCxYs0PHjx+Xr6yuLxaKkpCTTeQAAAABQqnF2EQAAANf1+4sKrmfdunWyWCwKDAxUx44dtXv3bkVGRqpSpUpFXAgAAEy6dOmSkpKSFBAQoHr16mnSpEkaOHCgdu3apeTkZNlsNlWsWNF0JmDEwIEDb7iNq6urnn322aKPAQAAKCamTp2qMmXKaM+ePXr44Ye1adMmxcTEyOFwaObMmXrkkUdMJ6KYqlWrlhYvXqytW7fqmWeeUXZ2tgYPHqy3335bkrRo0SIdOXLEcCUAoDSzWq3KzMyU3W5XWFiYfH19lZaWdsPv27Jlyx2oAwAAKH0OHDhww20uXLigqKgoeXt7a+3atVq4cKGSk5Pl7e19BwoBALixtLQ0+fj46NSpU1q7dq369OljOgkGubq6atiwYZoxY4YuXbpkOgdACfP7e3vy8vKUn5+vixcvav/+/fLy8lLLli0VExOjCxcuGKyEacHBwVq9erV27NihVq1aaf369X/aZubMmRo6dKg+/fRTA4UASqoaNWooMDBQkydPVn5+vukcGFamTBlZrVZt2LBBq1atUtWqVdWrVy/5+PgoISGBfyMAAAAAUARYMBQAAADXtHbtWrVp0+a6Txs9dOiQbDab/Pz8dNdddyk9PV2xsbG6//7772ApAAC403bv3q3w8HDVrl1bffr00ZkzZzR37lwdPHhQkZGRatCggelEwLjGjRurWbNmcnFxueY2OTk5GjBgwB2sAgAAMGfbtm3auHGj8vLylJOTozNnzqh9+/YKDQ3VG2+8ocGDB5tORDH30EMPad68eVqwYIFat26tuLg45eXlSfrtQvSZM2caLgQAlHZubm6KiIhQRkaG3N3dZbFYZLPZdOLEiatu/+OPP+qRRx7RpEmT7nApAABAybZmzRo1b95cu3fvvuY2SUlJeuihhzRhwgS98MIL2rp1q3r06HEHKwEAuL6YmBg98sgjVxbratKkiekkFAPBwcE6efKk5s+fbzoFQAnz66+/XvXzOf+PvfuOiuL6/wb+nl0WEEWxK/aIQcXeEWuiokajRhArauxdjC1GIyZGTTSWYMSeWGJEVOzRny0WrNh7wRIFRQQERCm7O88fPuwXZIFdlt3ZhffrnDknztw781kC9+6tk5IC4MN4/IgRI+Di4oK4uDhThkZmplGjRrh48SKqV6+OVq1aYdmyZZprly9fxujRowEAY8aMQWRkpFRhEpEFmjBhAm7fvo2jR49KHQqZkRYtWmDv3r04ffo0ypYtCy8vL9SpUwcbN26EUqmUOjwiIiIiIqI8gxuGEhEREZFWDx8+ROfOnXHnzh0sWbIkw/W3b9/C19cXn376Kc6fP4+AgAAcPXoU9erVkyBaIiIiMoWkpCQEBgaiffv2cHZ2xqZNmzB48GCEhobi8OHD8PT0hEKhkDpMIrPi7e0NuVyu9ZogCKhfvz6qVatm4qiIiIiIpLFmzZp0bQalUonk5GSIoohChQpJGBlZkurVq6NcuXJ4+PAhVCqV5nxKSgpWrFjBieZERGQSn376KQ4ePIjdu3fjxIkTcHZ2xrJly9LVTQDw7bffIjY2Ft988w0OHjwoUbREREREluXJkyfo0qUL4uLiMG7cuAzX7927h44dO6Jbt25o0aIFHj58CF9fX9jY2EgQLRERUUZKpRITJkzAyJEj4ePjg71798LBwUHqsMhMVKhQAV988QX8/f2lDoWILExCQkKmcxEBQKVSQSaTYfny5ShcuLAJIyNzVKJECRw8eBBz5szBpEmT4O3tjfDwcHTv3l3zUs53795hzJgxEkdKRJakXr16aNmyJfz8/KQOhcyQm5sb9u7di+vXr6N+/foYMmQInJycsGzZMrx7907q8IiIiIiIiCweNwwlIiIiogwiIyPRrl07vH37FgDw448/IiIiAsCHSWyrV6+Gk5MT/Pz84Ovri+vXr8PT01PKkImIiMiI7t69i+nTp6N8+fLo06cPACAgIABPnz7FggULULlyZWkDJDJjffv2zbBRRCq5XI6BAweaOCIiIiIiaSQlJWHDhg1ISUlJd14URYiiiIkTJ2L8+PGZfnciAoBbt26hUaNGeP78eYbfJQB49eoV9u/fL0FkRESUX3Xt2hV37tzBhAkTMG3aNDRu3BhnzpwBAISEhGDdunWahbc9e/bEzZs3pQyXiIiIyOzFx8ejU6dOiI+PBwAcOnRI09Z/8+YNpk+fjjp16iAyMhKnT5/Gxo0bUaZMGSlDJiIiSicyMhLt27fH+vXrsX37dixYsAAyGZfvUXqjRo3CiRMn2FdERHqJj4/PcsNQAPjtt9/QuXNnE0VE5k4QBEybNg27d+/Gvn370LJlS7x8+VLzEs6UlBQEBgZi165dEkdKRJZk/Pjx2LdvH0JDQ6UOhcxUrVq1sHHjRjx48ADdunXDjBkzULlyZfj6+iI6Olrq8IiIiIiIiCwWRxyJiIiIKJ3379+jS5cuCA8P1yy4ViqVmDlzJo4cOYIGDRpg7Nix6NatG+7du4dp06bBxsZG4qiJiIgotyUmJiIwMBDt27dHzZo18ddff2HIkCF49OgRDh8+DE9PT1hZWUkdJpHZc3R0hKurq9bFHyqVCh4eHhJERURERGR6O3bsQFxcXKbXRVHEihUr0L17dyQkJJgwMrIUx44dQ9OmTREZGal1s1AAkMlk+P33300cGRER5Xd2dnaalyyWKlUKLVq0wIABA/D1119rFm+r1WokJyejU6dOiIyMlDhiIiIiIvOkUqnQq1cvhIaGatr+MpkMo0ePxvr16+Hs7Iy1a9fil19+wYULF9C8eXOJIyYiIkrv8uXLmpdenTt3Dl999ZXUIZGZcnd3R7Vq1bB69WqpQyEiC5KQkABBELRek8lkmDFjBsaMGWPiqMgSdOnSBYMHD8aTJ08yjLULgoBhw4YhJiZGouiIyNL06NEDlSpV4vwcylblypWxbNkyPHnyBKNHj4afnx8qVaqECRMmICwsTOrwiIiIiIiILA43DCUiIiIiDbVajT59+uDy5cvpBoFTUlKwfv16fP/996hUqRJu376NVatWoUSJEhJGS0RERMZw+/ZtTJ8+HeXKlUP//v1RtGhR7N69G0+ePMGCBQtQsWJFqUMksjgDBgzIMFFXJpOhdevWKFeunERREREREZmWv7+/1k3U0xIEASdPnsSxY8dMFBVZipiYGAwdOhQJCQlQKpWZplOpVDhy5AgeP35swuiIiIg++PTTT3Hw4EHs3r0bBw4cwM2bN9PVW0qlEhEREejWrRuSk5MljJSIiIjIPI0fPx6HDx9ON29NrVYjLCwM06ZNQ+/evREaGooJEyZoNmYnIiIyF5s3b0aLFi3g4uKCCxcuwMXFReqQyIylbs72559/Ij4+XupwiMhCZPbiTSsrK/Ts2RNz5841cURkKY4dO4alS5dCrVZnuCaKIt68eYMpU6ZIEBkRWSK5XI4RI0Zg7dq1Wb48mihVyZIl4evri6dPn2Lu3LnYsWMHPvnkE3h7e+PevXtSh0dERERERGQxuGEoEREREWlMnDgR+/bt07rgWi6XQy6XY+/evXBycpIgOiIiItLF+/fvcffuXb3yxMfHY/Xq1ZpJ60FBQZg6dSqePXuGbdu2oWvXrlxwRWSAXr16ZdgwVBAEDBgwQKKIiIiIiEwrNDQUwcHBUKlUWq9bWVlBEAT07t0bDx48QNeuXU0cIZm7okWL4ubNm1iwYAHs7OygUCgyTWtlZYU1a9aYMDoiIqL03NzcoFKpIIpihmspKSm4ePEiRowYIUFkREREROZr2bJl8Pf319p/pFKp8PbtW0ybNg1FihSRIDoiIqLMKZVKTJ8+Hd7e3hg/fjz27duHokWLSh0WWYCvv/4aKSkp+Pvvv6UOhYgsxNu3bzP0OysUCjRp0gSbNm3KMEeRCACeP38ODw+PLNMolUqsX78ehw8fNlFURGTphg8fDrVajY0bN0odClmQQoUKYcKECXj06BHWrFmDCxcuoGbNmujatSsuXrwodXhERERERERmjxuGEhEREREAYNGiRVi+fHmmi/ZTUlJw+vRp7N+/38SRERERka4iIyPRunVrTJ06Vaf0ly5dwogRI+Do6Ijx48fD0dERhw8fxt27dzFt2jSUKlXKyBET5Q/FihVDu3btYGVlpTknCAK6d+8uYVREREREprN69ep034VSyWQfhqtdXV1x9epVbNq0ie0QypSdnR2mTZuGp0+fYuTIkZDJZFo3Dk1JSYG/vz+SkpIkiJKIiAiYOnUq3r17l+l1pVKJDRs2wM/Pz4RREREREZmvgwcPYtKkSVo3XE+lUqkwZcoUE0ZFRESUvdevX6NDhw74/fffsW3bNixYsEAz9kGUneLFi8PT0xMrVqzIcO3OnTuIioqSICoiMmdv376FWq3W/FuhUKBSpUrYt28fbGxsJIyMzFVycjI8PDwQExOT7ndHG5lMhqFDh2Y5vkFElKpo0aLo27cvfvvttwzly9OnTxEeHi5RZGQJrK2t4e3tjdu3b2PXrl2IiIhAkyZN0KJFC+zdu1fq8IiIiIiIiMyWIGY1s4aIiIiI8oXAwEB4eXllOekaAORyOSpXrow7d+5oXYhNlJ3r16/j3r176c6tW7cOADBkyJB0552dnVGnTh2TxUZEZOnu3buHDh064Pnz5xAEAf/99x8cHR0zpIuNjUVAQAD8/f1x9epVVK9eHYMGDcKQIUNQokQJCSInyh/++usveHt7Q61Ww8rKCp06dcKePXukDouIiIjI6JRKJcqWLYvXr1+nOy+Xy1GyZEn8/PPP8Pb2lig6smR37tyBj48PDh06BJlMlm4Bgkwmw5YtW+Dl5SVhhERkqQ4cOICEhIR058aNG4evv/4a9evXT3e+Xbt2KFq0qCnDIzMXEhKCJk2aZDvuCnyor/bs2YMvvvjCBJERERERmadbt26hadOmeP/+fbablwiCgBMnTqBly5Ymio4sEeenEZGpXLlyBT169ICVlRV27dqFWrVqSR0SWaCzZ8+iefPmOHv2LBo2bIigoCD4+fkhODgYp0+fRvPmzaUOkYjMSL9+/bB161bNHEQHBweEhISgUqVKUodGZurt27fYvHkz/v77b5w+fRqCIEAUxUzb31ZWVhg7diyWLFli4kiJyBLdunULtWvXxoEDB9CxY0ecOHECS5Yswd69e7Ft2zb07NlT6hDJgpw+fRo///wz9u3bhwYNGmDChAno168f5HK51KERERERERGZDW4YSkRERJTPnTp1Cp9//jmUSqVOC9cAYPny5RgzZoyRI6O8aM+ePejWrZtOaXfv3o0vv/zSyBEREeUNZ8+eRefOnZGQkICUlBQoFAr4+vpixowZmjSXLl3C6tWr8ddff0GlUqFr164YPnw42rVrJ2HkRPlHQkICSpQogcTERAiCgK1bt6JXr15Sh0VERERkdDt27ICnp6em71GhUEAul2PatGmYPn06bG1tJY6QLN2RI0cwbtw43L9/X7OwSS6Xw9XVFadOnZI4OiKyRN7e3ti0aVO26QoXLoyIiAjWZaShVqvRpEkTXLp0CXK5HCqVKsv0MpkMdnZ2uHjxIqpXr26iKImIiIjMx4sXL9CwYUNERkZCqVRmm14QBNSrVw8hISGQyWQmiJAsEeenEVFuuHv3LpycnGBlZaX1+pYtWzB06FC0atUKf//9N18oQwapVasW5HI5wsLCEB0dDZlMBpVKhYMHD8Ld3V3q8IjIjHTt2hX79u2DIAiwtrbGiRMn0LRpU6nDIgsRFRWF/fv3Y8uWLThy5IhmDsfHm4cKgoBTp07Bzc1NijCJyMK0bdsW0dHRUKlUuHXrFhQKBVQqFVauXIlhw4ZJHR5ZoMuXL2Pp0qXYsmULqlSpgilTpmDw4MFQKBRSh0ZERERERCQ5zpQhIiIiysfu3LmDLl26QK1Wa90sVCaTwdraWvPvAgUKoH79+njx4oUpw6Q8pFOnTihcuHC26ezt7dGxY0cTREREZPkCAwPRunVrxMfHIyUlBQCQkpICf39/REdHY/Xq1ahTpw4aNWqE06dPY9asWQgLC8O2bdu4WSiRCRUsWFCz2MzW1hZdunSROCIiIiIi01i1ahUEQYCVlRUEQUDfvn3x+PFj+Pr6coM1yhXt2rXDjRs34OfnBwcHB83ig+DgYNy9e1fq8IjIAvXp0yfbNAqFAj179mRdRumoVCosWbIEv/76Kzw9PVGxYkXNNRsbG8jl8nTp1Wo1EhMT0alTJ0RHR5s6XCIiIiJJvX//Hl988QWioqK0bhZqZWWl+f5kZWUFFxcXDBs2DCNGjEBCQoKpwyULwvlpRGSolJQU9OjRA5MmTcpwTalUYvr06ejXrx+GDRuG/fv3c7NQyhG1Wo0jR47Aw8MDd+7cwd27dxEVFQVRFKFSqSAIAuLi4qQOk4jMTGq5IAgCdu7cyc1CSS/FixeHt7c3Dh48iPDwcKxYsQItW7aETCaDXC7XtMFlMhm+/vprJCcnSxwxEZmzly9fwtfXF5cvX8bNmzdx584dAB/aUwqFgmOflGMNGjTAxo0bcffuXXz22WcYO3YsqlWrhmXLluHdu3dSh0dERERERCQpQdS2MxQRERER5XkvX75Eo0aNEBYWBgCaRdRqtRoymQzly5dHo0aNUK9ePdSuXRt16tRBlSpVIAiCxJGTpRs2bBg2bNig2dTuYwqFAoMGDcLq1atNHBkRkeVZtmwZfHx8AEDr5t/29vaaDXmGDRuGBg0amDpEIkpjz5496NatG/r3749NmzZJHQ4RERGR0T19+hRVqlSBKIpo0qQJVqxYgYYNG0odFuVhsbGx+Omnn7B06VKkpKRg4sSJWLJkidRhEZGFUSqVKFWqFGJiYrJMd/jwYb6Qh7IVExODixcv4uLFi7hw4QLOnTuHV69eAfjwUpmkpCSIoojWrVvj8OHDUCgUEkdMREREZHxqtRoeHh4ICgoCkH7emo2NDWrWrInmzZujQYMGaNCgAVxcXPg9ifTC+WlEZIj58+dj5syZUKvV+PPPPzFw4EAAQFRUFLy8vBAcHIxVq1bB29tb4kjJEiUlJcHPz7OVLIgAACAASURBVA9+fn7477//oFAotNZXVlZWWLlyJYYMGSJBlERkrho0aIArV65g1apVGD58uNThUB4RGRmJnTt3YuvWrTh58iTUajUA4Pvvv8ecOXMkjo6IzM3Zs2exZMkS7Ny5EzKZTOt3WRsbG0yYMAE///yzBBFSXvP06VMsXrwYa9euhZ2dHcaMGYPx48ejWLFiOuV/9uwZKlSoYOQoiYiIiIiITIMbhhIRUb7n6emJ7du3Sx0GUb7Hr6X5x/Hjx/HZZ59lm6ZNmzamCYjMAutjIt2k1pdKpRJjx47F6tWrM61Drays4Obmhv3796NgwYKmDJPMCMtXIt2wPUJEpJ9t27bBy8tL6jCIzF5AQAB69epllHvzxU5E0vPw8EBgYKDUYZCRjBkzBmvXrkVycrLW68WLF0dERATkcrmJIyNTYn1LlD3Wh0TGx34YIuMwZr8NSY/z04gop54+fYrq1asjMTERwIcNhk+fPg1ra2v06NEDKpUKQUFBfDkaGWTUqFFYuXJllmmsra2xYMECzcvEifTBdiSRbozZLuTfIVHu4TiEeRkzZgxWrFiRZRorKysMGjQIa9asMVFUlB+8fv0ay5cvh5+fH5KTk/H1119jypQpKF++fKZ5nj17hlq1amH79u1o3769CaMlIiIiIiIyDiupAyAiIjIHzZo142QKylcePXqEt2/fomLFinBwcJA0lrNnz2Lp0qWSxkCm1bp1a5QqVQqvXr3Ser1kyZJo2bKliaMic8D6mChzaevL+Ph4eHh44OjRo1lucKdUKhEcHIyEhARuGJrPsXw1L3///Td69erFDUXMBNsjRESGCQgIkDoEMnPHjx9H8+bNYWNjI3UoJmeKxT8TJ06Eq6ur0Z9jye7fvw9ra2tUrlxZ6lAoj1myZInUIZCR9enTJ9OFTtbW1ujfvz/b9vmEqerbiIgIhIaGokaNGihatKjRn0eUG1gfEpkW+2Eor4iPj8eNGzdQpUoVlClTRpJN2rlpS97H+WlElFMjR46ESqXS/FutVsPd3R2JiYlo0aIFtm7diuLFi0sYIeUFy5cvx4sXL7B//34olUqtaQRBQHx8vIkjo7yG7ci8Z8uWLejTpw9fdpULTNUutOS/w/j4eERERMDJyUnqUCgf4ziE+fHz88Pr16+xY8eOdG2ntJRKJaKjo00cGeV1JUqUgK+vLyZPnox169Zh0aJFWLlyJby8vDBjxgxUr149Q55ff/0V8fHx+OKLL7Bnzx507NhRgsiJiIiIiIhyDzcMJSIiAlC+fHm+LZ5IQtygJ3+RyWTo378//Pz8kJKSku6aQqGAt7c3F9nmU6yPibK2dOlShIWFwd3dHffv3890gsXHNmzYgClTphg5OjJnLF/NS7du3fLlhlnmjO0RIqKc43cMyk5+/h0xxQIjV1fXfP0zJpJSYGCg1CGQkbm5ucHR0RHh4eEZriUnJ6NPnz4SREVSYH1LlDnWh0SmxfqIKPdww9C8j/PTiCgntm7dioMHD6Y7p1Kp8PbtWzg6OmL37t2ws7OTKDrKS+RyOf7++2+0bdsWly9fzlBXAYAoitwwlAzGdmTe4+HhAZlMJnUYeYKp2oX8OyQyDMchzI9MJsPmzZvx5s0bHD9+XOt3WQCZvsSFyFCFChXChAkTMGrUKGzduhXz58+Hi4sLOnfujJkzZ6Jp06YAgOjoaKxatQqiKEKpVKJr164IDAxE9+7dJf4EREREREREOcfeYSIiIiIiMrk+ffpoHRRMSUnhIlsioizUr18f9+/fz3RixceUSiVWrFgBURSNHBkR6YqbhRIRERERERGZP0EQ0L9/fygUigzXypcvjyZNmkgQFREREREREemK89OISB9xcXEYP3681k3YlEolwsPDMXnyZAkio7yqQIEC2L9/PypWrAgrK6sM19VqNeLi4iSIjIjMGTcLJSIic6BQKBAUFIQGDRpoHU8HgNevX5s4KspvrK2t4e3tjVu3bmHXrl149eoVmjVrhhYtWmDv3r1YtmwZlEolgA8vZFCpVPD09ERQUJDEkRMREREREeUce4iJiIiIiMjkGjVqhCpVqmQ4X6lSJTRs2FCCiIiIzFtISAgAIDIyEqIoQqFQ6DzxLzw8HOfOnTNmeERERERERERERHmOts1lrK2tMXDgQAiCIFFUREREREREpAvOTyMifUydOhUxMTFQq9VaryuVSvj7+2PNmjUmjozysuLFi+PIkSMoWrRohk1DVSoVNwwlIiIiIrNlZ2eHgwcPolq1alo3DY2OjpYgKsqPZDIZunbtivPnz+PQoUOwtrbGl19+icWLF2s2DAX+t2moh4cHtmzZImHEREREREREOZfxFXREREREREQm4O3tjXnz5mkW21pbW2PQoEHSBkVEZIaePn2K27dvAwB++uknKBQKFClSBLa2tihQoADs7e1hbW2NIkWKwMbGBnZ2drC3t4dCoYCDg4PE0RMREREREREREVmmevXqoVq1anjw4IHmXHJyMnr37i1hVERERERERKQrzk8jIl2cPXsWq1evhiiK2aYdM2YMateujWbNmpkgMsoPKleujKNHj6J58+Z49+6dZtNaURQRExMjcXRERERERJlzcHDA4cOH0aRJE7x69SrdyzhjY2MljIzyqw4dOqBDhw6YOnUqFi9enOF6art/wIABUKvV6N+/v6lDJCIiIiIiMgg3DCUiIiIiIkn06dMHc+bM0fw7OTkZXl5eEkZERGSeKlWqBG9vb+zfvx8zZsyQOhwiIiIiIiIiIqJ8w9vbGz/88INmcVONGjVQq1YtiaMiIiIiIiIiXXB+GhFlJyUlBUOGDIFcLodSqdSaRhAEyGQyAMDnn3+ON2/emDJEygdq166NPXv2wN3dXbNhKABuGEpEREREZs/R0RH//vsvmjVrhtjYWE27KikpCYmJibC1tZU4QspvUlJSsHnzZqhUKq3XRVGEKIoYOHAgVCoVBg4caOIIiYiIiIiIck4mdQBERERERJQ/OTs7o3bt2hAEAYIgoE6dOqhRo4bUYVE+0q5dOzg4OEj2fKVSCTc3N9SrVw+JiYl65+/YsSMKFSpkcBwzZsyAvb097t27Z/C9iIgsidT1ABERERERERGZvz59+mgWNSkUCi4WISIiojype/fusLKyyjZdXh1b0XXsfu3atRAEAQcPHtT7GRyXJ5IG56cRUXaWLFmCe/fuad0sNPX7UZ06dfDrr78iPDwc//zzDzp27GjqMCkfaNu2LTZs2ABBEDTnYmNjJYyIiIiIiEg3Tk5OOHbsGGxtbSGXyzXno6OjJYyK8quNGzciIiIi23RqtRqDBw/GH3/8YYKoiIiIiIiIcgc3DCUiIiKtpk+fDkEQcPr06UzT+Pr6QhAE/PvvvwCApUuXaiZWpj1sbGxQtWpVjB49GmFhYZr82tIXLFgQTk5O6Nu3Lw4cOJDhmZk9QyaToWzZsmjevDmWLl2KlJSUdPnevHmDhQsXolmzZihTpgwUCgUKFy6Mxo0b4+eff0ZSUlLu/OBMIDk5Gd7e3hAEAYsWLcr1vGq1Gr/99htcXFxga2sLR0dHjBgxIsMbsS9duoTOnTvDwcEBtra2qFu3LtavX5/jz0X5k7e3N+RyOeRyOQYMGCB1OJQHXb16NUOd8fLlS6nDAvChrr1+/Tq2bdum9a2ZtWrVgiAIGDVqlFHj+OGHH1C3bl14eHjg/fv3Rn1Wbnrw4AE8PT1RsmRJ2NjYwNnZGfPnz4dardYpv771aXx8PD755BMIgoCbN29qzi9cuFDrd5PUQ9tkciIiqRlShuakHZBZGQoAly9fxhdffAEHBwdYW1ujWrVqmDZtGuLj4w36jERERGnlZj9k2qN69eoZ8pmqLZfbDG1jpcqq3gd0b4sZ0gdK+RfHNcxTTssXffpcLl68iK+++grlypWDjY0NnJycMHXq1AztCo5rUE5UrVoV9evX1/zeeXl5SR0SUY7qFinrvI+PBQsWmOTnpAtDvgfrktcY9RkRka7ySpvCFLIbu8+MtrrPxsYGlSpVgru7O/bu3atJm1/H5VNl1Wek6zNYV1JOcX4aEWXmv//+g6+vb7o6x9raGsCHDW++++47PHz4EFevXsWECRNQqlQpqUKlfKJPnz6YN2+eZtPQuLg4iSMiMq7UNtX27dszTTNy5Mh07YjUPBUqVMi0LbB8+XKtefQdqzNXhrTT7t27Bw8PDxQrVgx2dnaoWbMmZs+ejbdv32ZIm5trjyjv4Pyb7Jlq/o2+6YiMrU6dOtizZw/kcrnm+yw3DCVTU6vVmDdvHkRR1Cm9KIoYMmQI1q5da+TIiIiIiIiIcgc3DCUiIjJjz58/hyAIePLkidSh6CUwMBCiKGqOsLAwLFy4ELt370ajRo3w4sWLTNNHRETg77//RqlSpdCtWzd06dIFCQkJ2T4jJSUFZ8+exWeffQYfHx/07t1bkzYuLg7NmjXDDz/8gP79++PGjRtISEjAlStX0KFDB0yfPh1dunQx+s8lN8TExMDd3R2hoaFGyzt27FjMmjULc+fORUxMDAICAhAUFIROnTppOsuDgoLQpEkTFCpUCCEhIYiKisLAgQMxbNgwLuAnvfTt2xcqlQoqlSrd3y1RbqlXr56mrujZs2e6a0eOHEk3IUlbvWusuvjq1atYvHgxvv32W3z66acZrp88eRK3bt1CpUqV8Ndff2mdiJVbrKyssGrVKty6dQu//PKL0Z6Tm16+fAk3NzfExsbi/PnziIuLwy+//IJ58+Zh7Nix2ebPSX3q4+ODx48fZzif+jsUExOT7rtJ6mFlZaX7ByOycMZuvxhyf215P64H8gtDytCctgMyK0NDQkLQrFkz2Nvb48qVK4iKisKSJUuwbt06tG/fXu8JkkRERNnJjX7ItMfdu3fTpTVlWy43GdrGSiuzeh/QvS1mSB8oSY/jGhzXSMuQ8kXXPpeTJ0+iZcuWsLa2RnBwMCIjIzFv3jz8/vvv6NChg6ZdwXENMsSAAQMgiiIaN26MypUrSx0OkYY+dUtmeUxR5318TJ8+3Wg/E30YUk/pmje36zMiIl0Zq02RF8dWshu710Xaui8uLg779u2DlZUVvvzyS2zatAlA/hyXTyuzPiNdn8G6kgzB+WlElJkRI0bg/fv3mrZZ6dKl4ePjg2vXruHBgwfw9fVF1apVJY6S8pvp06drvgdp63chog+eP3+OGTNm6JUnJ/2p5saQdtrt27fRsGFDvHr1CidPnkRERARmz56NhQsXZnhZWm6uPaK8ifNvtDPV/JucpCMyhbZt2yIwMBAy2YftS7hhKJnaxYsXIQiC5mUgqWQyGWxsbDKcBz5sGjp8+HCsXLnSVGESERERERHlnEhERJTPeXh4iB4eHlKHodWmTZtEAOLjx49N/uxp06aJAMRTp05lmmb27NkiAPH48eOiKIrikiVLRABiYGCg1vTbt28XAYjfffedTukPHz4sKhQK8csvv9Scyy6PKH74fwpAvH79uiiKoujv7y8CEBcvXqw1/ahRo0QA4qFDhzK9Z2bevXsnbt68Wfzss8/EW7du6Z1fH9HR0WKNGjXE77//Xjx79qwIQFy4cGGu5k29tmbNmnTn169fL7q4uIh37twRRVEUq1WrJpYvX15MTExMl27IkCGinZ2dGBUVpfPnCggIEI35tRQADx48cukwJlPUxz179hQBiC9evNB6XVu9a6y6uHv37mKRIkXEN2/eaL3eu3dv0d7eXgwKChIBiKtWrcqQxt3dXSxYsGCuxdSjRw+xSJEiYkxMTI7ym7JOHD16tFigQAHx9evX6c4vWLBAFARBU19pk5P6dN++fSIAze/QjRs30sUCQExJSTHsQ2XD2PUl5V2mbO8Yu/1iyP2lbFsZwhhlqyFlaE7aAVmVoe3btxcLFCggJiQkpMszb948EYB44sSJnHxEvbB8JSLKGUsrP43VD/kxXdpyurKUNlZaWdX7urbFDOkDNTcAxICAAIu9f05xXIPjGmkZUr7o2ufi5uYmli9fXkxKSkp3fvLkySIA8cKFC6Io5u64higav72d+jvBgwePrA9jA8yzvs1J3WIudV5OmVs/ma55c7s+MzfmPN+GKC/JST+Mvm2Kbt26iVZWVgbHaomyG7tPa82aNSIA8Z9//hFFMeu6LzY2VpTJZGLDhg3Tnc8v4/JpZTfersszcruuNPb3vNS/Wx48eGR9GLv/lAeP/HoYE/stefDIvcMU30fNnS79iSNGjBCB/7UjUvP07NlTlMlk4rlz5zLk8fPz05pHn/5UfVhKO61r166ijY2NGBkZme78pEmTROB/c/Vye+2RueLfYc5w/k3WTNGXkpN0lswU4xBSfyfgwcMSDv4d8uBhOQcRERER5W0fXoNIREREeuncuTPu37+PnTt3YsKECbh48SIUCgW6dOmCFStW4MCBA5g/fz7u37+PMmXKYOLEiRg/fny6ewQHB2Pu3Lk4d+4cEhISULZsWXTt2hVz5sxB8eLF0bFjRxw6dAgAUKVKFdjY2CAxMVGnvADQsWNHhIaGYvv27RgwYADu37+PhIQEyOVy0/6w0qhVqxYA6Pzmunbt2mHUqFH47bffcPz4cbRt21bn52zfvh3Pnz9H7dq1ERUVBQBo1KiR1vSzZ8/GyJEjUaNGDZ3uDwAhISFYv349tmzZArVajT59+qBcuXI658+JiIgITJw4EcOHD8e5c+eMknf9+vUoWLAgBgwYkO784MGDMXjwYAAf3hb64MED9OrVCzY2NunS9erVC+vWrcP+/fsz3ENKEydOhKurq9RhUCaOHDkC4MPfPJmns2fPYunSpVKHkevatWuHkJAQvHnzRmu926ZNm0zr4qtXr8LX1xenTp3C27dvUa5cOXz11VeYNWsWihQpAiDzuvjly5fYvXs3RowYoUmb1qtXr7Bz5054eXmha9euKFu2LFatWoXhw4dnSCuXy3Ht2jVMnjwZ58+fh1KpRNOmTbF48WLUr18fwIe3cv7444/Ys2cPwsPDYW9vj0aNGsHX1xdNmjTR3Gv06NEICgrC5s2b9XqDrRR1YkBAANq0aaP53pOqR48emD59OrZv346ZM2dqzatvfRoVFYWhQ4fCy8sLbdq0wY4dO9Jdf/PmDQoUKAArK3axUP6WVftFlzIzu7Iqq/vnNLa09QCQO+08XT6rLoxZtua0DM1JOyC7MvTZs2coXbo07Ozs0p2vWrUqAODRo0do1aqVQZ+XiIhIFznth0xLn7ZcViytjZUqu3pf17aYIX2glDWOa+QMxzUMY0j5omufi4eHB0qXLg1ra+t0511cXAAAT548gZOTk8WNawBAs2bN4OPjI3UY9P/NmzcPY8aM0at9T8aTV8ctctPHdYsu6QHj13n6Msd+Mn3y5mZ91rhxY30/IhHlYzlpUygUCoSGhmLy5Mk4fvw4EhMTUbduXSxatAgtW7YEgFwfWzHV2ExOxu6XLl0KPz8/PHv2DGXKlEG/fv1QoUIFnf8fFC5cGMWLF0dMTEy68/llXD5Vdn1Guj7DUuvKgIAAqUOg/4/z08yPl5eX0Z/BeaOUmZSUFGzduhU1a9ZE3bp188y8L1P1l7Df0jRSUlIwd+5cfPfddxm+A5HlM0U9mNd9//33CA4OxrBhw3Dp0iUoFAqD7qdvfypgee209u3b47PPPkOJEiXSnW/YsCGA/83Vy821R5T/cP6N8ftS9E1HumH7Mfft2bMH9vb2RhtDJNNZsmSJSZ4jxd+hKIqIjY1FTEwMYmJiEB0djSZNmqBw4cImjYMoN3AeDREREVH+kDdGNYmIiEzM2toar1+/xujRo/Hrr7/CxcUF/v7+mDp1Kp49ewZbW1sEBQWhaNGiGDduHCZMmICmTZuiadOmAIBjx47B3d0dX331Fc6fPw9HR0eEhISgX79+OHnyJC5cuICDBw9i8uTJ+PXXX/H48WNUrlxZ57y2trawsbFBQkICxo0bh27duqFcuXKQyWQS/tSAa9euAQCcnZ11ztO/f3/89ttv2L59u84DBOfPn4dcLtcsamrdujUA4M8//4Srq2uGiV2lS5dG6dKls71vVFQUNm/ejHXr1uHGjRto1KgRFi5ciD59+qBQoUIAgNevX6NkyZLZ3uvOnTuoXr26Tp8nVfXq1fXOo2/e4OBg1KtXL8OC2bREUQQACIKQ4VqxYsUAfPh/bU4La11dXdGrVy+pw6BMfP755wCQYVCczEteHzDIrN7Vdi4kJAStWrVCu3btcObMGZQrVw7//vsvhgwZglOnTiE4OBhWVlaZ1sWHDx+GKIqZLkJYu3YtkpOTMWjQIMjlcgwYMAC//PILQkJCMizoSklJgbe3N3799Vc0bdoU9+/fh7e3Nz7//HPcv38fJUqUQO/evXH79m0EBgaifv36ePHiBSZPnozPP/8cly5dwqeffgoAaNGiBWxtbXH48OFsFyZJWSc+e/YMUVFRqFmzZoZrTk5OUCgUuHTpUqb59a1PR40aBaVSCT8/P60Tad68eQN7e3ud70eUV2VWjupaZmZXVmV2f0Ni+5ih7TxdP2tmTFG2GlKG5qQdkF0ZWrt2bezduxexsbHpFuI+fPgQALTGSUREZCw56YdMS5+23McsuY2VKrt6X9e2mCF9oJQ1jmvkDMc1/sfU5YuufS4TJ07Uev7atWsQBAEuLi4WOa4BAOXLl+fYhhmpW7euXmUBGV9eH7cw1Md1S3ZMVefpwtz7yfTJm5v1GRGRPnLSppDJZOjbty9mz56NTZs24eHDh/D09ISnpyeePn2qdS6RoW1NU43N6Dt2v2rVKvj4+GDatGmYNGkSlEolVq5cifnz5+v8/yA8PByvX79GmzZt0p3PL+PyqbLqM9LnGZZaV7JNZz44P838mGKjNM4bpaz069dP6hCMwhT9Jey3NJ1OnTrBzs4Otra2UodCuYwbhhquYMGCWLZsGby8vLBw4ULMmDHDoPvp2p9qye20cePGaT0fFhYGAPjkk08A5O7aI8qfOP/GuPNv9E1HumH7Mff16tULYWFhRt+ol4wvMDDQJM/h3yGR4TiPhoiIiCjvk3Z1DRERkQWLjY3Ft99+i6ZNm6JQoULw8fFBoUKFcObMGfzxxx+oUqUKHBwcMG3aNAAfFsSmmjZtGooWLYoNGzbg008/RaFChdCmTRssWLAAN27cwNatWzN9rq55BUFAZGQkunXrhh9//BEjR47UuhDSFKKjo7F7925MmjQJFSpUwOjRo3XOm/p2zrt372aZTq1W48mTJ5g6dSr++ecfTJkyBRUqVADwYaL1okWL8Ndff8HJyQmTJk3Cjh07EB4erlMMSUlJ8PT0hKOjI77//nu0aNECV65cwcWLFzFs2DDNoCEAlChRAqIoZnuY66L3x48fo1y5cti4cSMaNGiAAgUKoFixYujXrx+eP38O4MPiWScnJwQHByM5OTld/tOnTwP48EZHIl0VL16ck7HJokyaNAnFihVDYGAgnJ2dUahQIXTp0gXz58/HhQsXsG3bNgCZ18UnT54EALRq1SrDvdVqNVavXo0qVapoJsikvmV55cqVGdK/f/8eU6ZMQbt27WBvb4+GDRti3rx5iImJwcaNG5GYmIijR4+iU6dOcHV1ha2tLapUqYI//vgDNjY2OHTokOZetra2aNy4MU6dOpXpZzeHOjEiIkJz/4/JZDIUK1ZMk8ZQf/31FwIDA7F8+fJMJwa9efMGCoUCs2fPhouLCwoUKABHR0eMHTsW0dHRuRIHkSXTpczUp6wyNkPaebrWDx8zZdlqSBmqbztAlzJ01qxZsLW1hbe3N54/f47k5GQcOnQIixcvhpeXF5o0aaI1HxERkTHo2g+pjb5tuVR5pY2lS71P5oHjGrrjuIb05UtO+1wiIiKwaNEi+Pn5YdasWahZsybHNShXcLNQsgRZ1S2ZMUWdpytL6SfTJ29u1mdERPrISZsiISEBkydPRufOnVGoUCHUq1cPI0eOREREBEJCQjLNZ0hb09D8xhq7X7hwISpXrox58+ahVKlScHR0xA8//KDT4vbExESEhISgd+/eKFOmDObOnZvuen4al8+uz8jQ+ph1JemD89OIiMgSFStWjJuFEmVCFEX06tULX3zxBX788UfNC6r1oU9/al5pp2m759KlS1GrVi24ubnplVeXtUeUP3H+jfHn33CeDlkKbhZKRERERERElLu4YSgREZEBWrRooflvKysrFCtWDJUrV0bZsmU150uXLg0AePnyJQAgJiYGISEhaNOmTYYJHO3atQMAHD9+XOvz9M2rVColefuop6cnBEHQHGXKlIGPjw+6d++Oixcvah38yoytrS3kcjni4+OzfIZcLkeVKlVw8+ZN7Nq1C/Pnz0+X/ptvvsHTp0/xzTffIDQ0FKNHj0a5cuXg5OSEb7/9FpGRkZnG8P79e2zfvh3NmzfHw4cPsWLFCtSrV0+/H4oFUKlUeP/+PY4dO4Y//vgDf/75JyIjIxEQEIDg4GA0bdoUb968AfBhYvzz588xYMAAhIaGIjY2Fn/++Sf8/f0BACkpKVJ+FCIio4mLi0NwcDDatm2b4Y3IHTt2BPDhLdOptNXF4eHhUCgUWidnHDhwAE+fPsWgQYM0G2JUr14drq6u2Lp1K+Li4jLk6dSpU7p/N2/eHABw4cIFWFtbo1SpUti1axeCgoI05XPhwoXx+vXrDG+LLleuHGJiYpCYmKj185tDnfj+/XsAgLW1tdbr1tbWePfuncHPCQsLw7hx49C9e/csv0+p1WokJSWhYMGCOHr0KF6+fInffvsNgYGBaNy4cYbvMET5ia5lpr5llbHlpJ2nb/2QlinLVkPLUF3bAbqWobVr18bOnTtx9uxZVKhQATY2NujYsSNatWqF1atX5/RjEhER5Yiu/ZBpj0GDBgHIWVsOyBttLF3rfTIfHNfQjuMauc/Q8kXfPpeHDx9q/t/NmTMHzewD5AAAIABJREFUCxYswKxZszTXOa5BRHmRvnWLtjymqPPSHlnd31L6yfTJm9v1GRGRPnLSpmjfvn26f5cpUwZA9hvs56StaWh+Y43dv3r1CqGhoWjevDlksvTT7Dt06KD186et+woUKIDGjRvj0aNHWLZsGapVq5YhfX4Yl9elzygnz2BdSURERESU92TVn7hq1aos865YsQJyuRwjRozQ+zm69KemygvttI9FR0ejW7duiI2NxcaNGyGXy3XOq8/aI8p/OP/GuPNvOE+HiIiIiIiIiCj/4oahREREOSSXy1GkSJF05wRBQLFixTKcAz4MiAIfBmYApJvQnCp1YnNqmo/pm1cQBK1pjS0wMDDdW/WSk5Px6NEjLF++XBOnruLi4qBSqTK83f3jZwQFBQEAXFxc0K1bN633Kl26NMaNG4fdu3cjIiICDx8+xNixY/HHH3+gTp06ePTokdZ8BQoUQM+ePXHmzBlUq1YNY8aMwbVr1/T6HLq6e/duhoHPuXPnGuVZH5PJZJDJZIiNjcXOnTtRp04dFCpUCO3bt8fKlSsRHh6OxYsXAwC6d++OAwcO4P79+6hZsyY++eQT/PPPPwgMDAQA2NvbmyRmIiJTCw8Ph1qtxubNmzOU16lvv3z27Jkmvba6OCoqKtMFsf7+/pDJZJpJL6kGDx6MhIQEbNq0Kd15a2vrDHVk6r0jIyMhk8mwd+9eFCtWDF999RUcHBzQrl07LFq0CNHR0Rmen7oQKrMNJ8yhTrSzswMAJCcna82XlJSkSWOIIUOGAIBm04jMnD17FpGRkZg6dSrKlCmDIkWKwMPDA/7+/nj06BF+/vlng2MhslS6lpn6llXGlNN2nr71Q1qmLFsNLUN1bQfoWoZu2rQJ7u7u+Prrr/HkyRMkJSXh3LlzePToERo3bpzlBkhERES5Tdd+yLTHn3/+CUD/tlyqvNDG0rXeJ/PAcY3McVwj54xVvujb5+Lk5ARRFBEdHY2NGzdi6dKlaNasGWJiYgBwXIOI8qac1C1S1Hlpj9evX2d6P0vpJ9Mnb27XZ0RE+tKnTSGXy+Hg4JAuf+pmIantQ21y2tY0NL+xxu5TNyTV9gLQzNqraes+lUqFly9fYt68eRg5ciTatWuHpKSkdOnzw7i8Ln1GOXkG60oiIiIiorwnq/7E7DYCrVixIn788UfNxpX6PEeX/tRUeaGdllZoaChcXV1x9+5d7Nu3D/Xr19crRn3WHlH+w/k3xp1/w3k6RERERERERET5FzcMJSIikogoipmeS53gbGhemUym11se0ypQoAAAQKlUZpomdTKzMRdRhoSEAAAaNmyYZbru3bujbdu2WLZsGW7fvq3TvatWrYqJEyfizJkzePnyJX766Set6WxsbLB9+3aEhYXB19cXp06dQr169dCkSROsXbsWCQkJ+n2oLFSvXj3DwOfMmTNz7f5ZEQQBJUuWRNWqVVG0aNF011q3bg1BEHDlyhXNuU6dOuHKlStISkpCVFQUAgICIJN9+Hr5ySefmCRmIiKpDB06NNMJKzt37tSky6wu1lbXP378GAcPHoRarUalSpXSTSIZPnw4AGR4U3ZW3xlSrzVq1Ah3797FqVOnMGnSJMTFxWHKlCmoVq1aunId0P4dIy1zqBNTF2FpWzylVCoRHR2tWQCWU+vXr8ehQ4ewcuVKlClTJkf36NixIwRBwPnz5w2KhSgv0KXM1KesMme61g9pmbJszY0yNLt2gK5lqFKpxJgxY9CiRQssWLAAlSpVgrW1NZo2bYo///wT9+/fx8KFCw34tERERPrRtR/yYzlpy6Wy9DZWbrSdyLJwXEM3HNcwbh9Odn0uRYsWRY8ePbB7925cunQJCxYs0FzjuAYR5XU5qVsMkdPv0JmxlH6y3KjjDKnPiIgMoWubwpIYY+w+s/NqtTrbeGQyGUqXLg1vb28sW7YMx44dw4oVK9Klyevj8rr2GRnyDNaVRERERESUavz48WjYsCEmT56MyMjIbMctU+nTn2rp7bS0zpw5g2bNmiE5ORmnT59GmzZt9I5R37VHlL9w/o3x+lI4T4eIiIiIiIiIKH/jhqFEREQmVqFCBQiCgPDw8AzXXrx4oUmT23n1VbVqVQDA06dPM03z4MEDKBQKODk55coztVm/fj0EQYCXl1e2aRcvXgyVSoWxY8dqziUnJ2PRokVYtmxZpvmqVKkCKysrPHjwIMv7lyhRAhMnTsT169dx4cIFzaSCsmXLYuTIkYiNjcXr168zvClQ23H37l3dfwgm1KBBA7x69SrDeaVSCVEUYW1tnWX+M2fOAABatGhhlPjIONauXQtBEHDw4EGpQyHKFfPnz0fZsmXx6NGjdOffv38PAChYsGCO712+fHnIZLIs68fsFC9eXOtEkFWrVkGtVuPq1ataFzP98MMPuHHjBs6ePavJk5SUhNjY2HT3ef36NQCgdOnSmnOCIKBFixb48ccfceHCBZw5cwZxcXGYM2eO1rwlSpTI8jNIWSc6OjqiTJkyuHXrVoZrd+7cgVKpROPGjfW658euX78OAPDy8koX66hRowAAtWvXhiAIePfuHS5fvqz1O0RSUhJEUYStra1BsRBZMn3LTF3LKnOUG/WDKcpWY5WhadsBupahoaGhiI+PR40aNTLcz9nZWRMTERGRqejTD5lWTtpyH7PUNpau9X5WmzeSZeC4hn44rvGBIeVLcnKyTn0u//33H4YMGYKNGzdmSFezZk0AyHaBJ8c1LBvHN4gy0la3GEtOv0Nnx9z7yXTNa8r6jIgordxsU5gzY43dlyxZEgAQFRWVIf2zZ8/0un/dunUBIMMmKXl9XF7XPqNSpUrp9AzWlXkX23RE0uLfIJHx8O+LyLTkcjnWrFmD2NhYTJw4EQqFQue8+vanWmo7LdW5c+fg7u6OKlWq4Pz586hVq5ZeMaRl6Nojyrs4/8Z4fSmXL1/WKR3n6VBu4/dbIunx75CIiIiIiABuGEpERGRyRYoUgaurK/7991/NxmWpDh06BABwd3cHAMhkH6pqURT1zmuoLl26oGjRovDz84NKpcpw/dGjR9i3bx+8vLxQpEiRXHnmx3bt2oUtW7ZgyJAhqF27drbp69Wrh4EDB+L48ePYunUrAMDa2hrbt2/Hd999hydPnmjNt2/fPiiVSri4uOgcW+PGjeHv748XL15gxYoVuH//PsLCwlCiRAmtA5MfH9WrV9f5WabUp08fREdH4/Dhw+nOHz9+HMD/Fsz6+PigWrVqSElJ0aRRq9VYvXo1atSoATc3N9MFTWRCycnJ8Pb2hiAIWLRokdY0Fy9exFdffYVy5crBxsYGTk5OmDp1KuLj47O9f07yxsfH45NPPoEgCLh586bB6fKCMmXK4OXLl9i/f7/mnFqtxu3bt+Hs7Ax7e3ut+T6ud7WdK1SoEFq2bIl///0XL1++TJf/1KlTqFmzpuatuJkpW7YsUlJSNIuAgA+/W+vXr0e9evU0i4Y+NnDgQAiCgJUrV6Y7/3//93/p/n369GkAQPPmzXHixAmUL18e165dS5fG1dUVZcuWzbDIKTw8HA4ODihQoECWnyEtKerEvn374sSJExkWbwUEBMDKygq9e/fW+55pLV26VGus/v7+AIAbN25AFEWoVCq0aNECw4YNy3CPAwcOAAA+++wzg2IhsiQ5LTN1Lau0ldM5jS235Ub9kJYxy1ZDylBd2gG6lqHly5eHjY2N1u8lqecqV66s88+MiIjIEPr2Q6YypC2XGUtqY+la71tZWekdE5kXjmvojuMa6eW0fElKStKpz6VkyZLYunUrli1bBrVanS5d6mKp1I1kOa5B+ZlarcZvv/0GFxcX2NrawtHRESNGjMCbN2+yzXvv3j14eHigWLFisLOzQ82aNTF79my8ffs2R+kuXbqEzp07w8HBAba2tqhbty7Wr1+fq583v9NWtxhDTr9D68tc+8l0yWuM+oyISBfGalOYG2ON3ZctWxbly5fHmTNnMowrpbZjdXXjxg0AwCeffJLufF4fl9enz0iXZ7CupPzOFHPRHjx4AE9PT5QsWRI2NjZwdnbG/Pnztf7NffHFF3BwcIC1tTWqVauGadOm6RQLkSVauHBhlptIZbcRU076ZPLTPE8iXfoUDf07zK4/MjExMdsN41L7dgyNhYyrfv36mDhxIrZs2YJTp07pnM+Q/lRLaqcBwJMnT9CpUyc4Ozvj6NGjKFWqlN7PT0vXtUeUv3D+jXH7UpYvX855OkRmypDvirrm1fcZuqyBJMqLdP3dz+nfiK59pLrOo0mL/UJERERElB1uGEpERCSBX375BfHx8Rg8eDAeP36Mt2/f4siRI5g5cybc3NzQs2dPAEC5cuUAAOfPn0diYiKUSqXOeQ3l4OCAjRs34saNG+jWrRsuXryIhIQEvHjxAhs2bEDr1q3h7OyMpUuX5srzUiUnJ+PmzZuYNGkSPD090aNHDyxfvlzn/D/99BMKFiyIyZMnazrOVq1aBTs7O3z22WfYsmULoqOjkZKSgufPn2PFihXw9vZGxYoVMXPmTL3jLVCgAPr3749jx46hZs2aeuc3hiNHjkAQBEyePFnvvH379kXr1q0xaNAgnDp1Cu/evcPx48cxbtw4ODk5YejQoQCAjh074tGjRxgzZgyioqLw8uVLDB8+HDdv3sSaNWsgCEJufywiycXExMDd3R2hoaGZpjl58iRatmwJa2trBAcHIzIyEvPmzcPvv/+ODh06ZJhEnRt5fXx88Pjx42zj1zVdXtC3b1+4uLjghx9+wMmTJ/HmzRt8//33ePLkCX766adM82mrd7Wd+/nnnyGXy9GlSxfcvXsXiYmJ+Pfff+Ht7Q0bG5ts37bcqlUrAB/+n6favn07IiMjMWjQoEzzVaxYEW3btsW2bdsQExMDlUoFW1tbLFiwACdOnMDbt29x4cIFfPPNNyhTpgz69++Pxo0bw8rKCgMHDtR8hujoaCxevBjPnj3DkCFDNPdPSkrCxYsX0bJly2x/xtqYsk6cMWMGSpQoAS8vLzx8+BCJiYnYunUrFi1ahJkzZ6JixYoADKsTdWFvb485c+bgxIkT8PHxwfPnzxEbG4tt27Zh4sSJqFu3LkaMGGGUZxOZo5yWmbqWVdrub0hsuc3Q+kEbY5SthpShudkOSG23nTx5EjNmzMCzZ8/w7t07nDt3DsOHD4eDgwMmTJiQK5+ZiIhIG0P7IYGcteV0lR/bWGTeOK6ROY5rZC6n5YuufS4FChTAokWLcPnyZQwbNgxPnjzBu3fvcPLkSQwdOhQODg4YP348AI5rUP42duxYzJo1C3PnzkVMTAwCAgIQFBSETp06Zflyldu3b6Nhw4Z49eoVTp48iYiICMyePRsLFy6El5eX3umCgoLQpEkTFCpUCCEhIYiKisLAgQMxbNgwLlDKZdrqltyQG9+hc8rc+sl0yWuM+oyISFfGbFOYE2OM3QPA+PHjERoaiqlTpyIyMhLPnz/H1KlTER0drVNcb968wa5du+Dj44OKFSti9OjRmmscl9f/GawrKT8zxVy0ly9fws3NDbGxsTh//jzi4uLwyy+/YN68eRg7dqzmfiEhIWjWrBns7e1x5coVREVFYcmSJVi3bh3at2+fZSxElip1Y8+YmBitGzNltxFTTvpk8tM8T8rfdO1TNOTvUJf+SFtb20w3itu1axcAaOIxtEwg45szZw4qV66Mv/76S698hvanWko7bezYsUhMTERgYCDs7e0NjkXXtUeU93H+zf9w/g1R/mXId0Vd8+rzDF3WQBLlRbr+7uf0b0TXPlJd27wfY78QEREREWWHG4YSERFJwM3NDSdOnEBMTAzq16+PYsWKYeTIkRg4cCAOHTqk6ZwdMGAAWrZsCW9vb5QvXx7h4eE6580NXbp0wdWrV1GqVCl4enqiaNGi+PTTT/H7779j/PjxOH/+PIoXL27wczw9PTVvsrKzs8Pnn3+Ohw8fIjAwEDt27ICNjY3O9ypbtiymT5+OsLAwzJkzBwBQt25dhISE4Msvv8S8efNQoUIF2NraolatWtiwYQN8fHxw7do1zUJmczV58mTNz8nV1RUAMGXKFM25/v37G5xXLpfjwIEDGDBgAAYMGAAHBwf069cP7u7uCA4O1kwMcHd3x86dO3H9+nVUrlwZzs7OCAsLw+nTp+Hm5mbknwSR6cXExMDNzQ2tWrXCr7/+mmm6GTNmoGTJkti4cSMqV66MwoULo1evXhg9ejTOnTuHS5cu5Wre/fv3Y926ddluqqBrurzCxsYGx48fx1dffYV+/fqhdOnS2LdvH/bs2ZPlz0BbvavtXNOmTREcHIzy5cvDzc0N9vb2GDBgAHr27ImjR4/C1tY2y/g6dOgAQRBw5MgRzTl/f38oFAr07ds3y7yDBw9GYmIiNmzYgKSkJJQsWRLr1q3DDz/8gLJly6JNmzaoWrUqjhw5giJFisDOzg6nTp1Cw4YN4enpiSJFisDZ2RlBQUEICAhIN6nm9OnTeP/+Pdq3b6/bD1pCxYsXR3BwMBwdHeHq6ooiRYrgp59+wtKlSzF79uws8xpSn2ozZcoUBAYGIiQkBPXr10epUqUwa9YsDBs2DKdOnYKdnV2OPyfR/2PvzuOqqvP/gb8usgoooigoLiCOhDq2OS5gWpbATA1lKmXZptTDjMK9cVzGh5kajpottvwSI2tEJqmZxuVR5gYIiZrlJJqY5jIocBFxuSjx/v3hg/v1eu+Fc+7GhfN6Ph48Hnn4nHM+58b7fJb3557T3Nh6z1R6r7J0fHvq5mj2tg+uYs891NHjgNdeew1r167Fzp070adPH7Rt2xajR49Gv3798N133yEqKsrWyyQiIrLIkfOQgG1jOXdkT/9AKaVjMUeP2chxmNcwxbyGMvbcX5TOuUyaNAmff/45jh07hv79+6N9+/aYOHEi7r77bhQWFiIyMhIA8xqkXQUFBVi9ejX+/ve/45FHHoGfnx+GDh2KpUuXorq6GkeOHLG676uvvora2lps3LgRffv2RWBgIJKTkzFp0iRs2rTJ+GAtpeVmzZqFzp0745NPPkFUVBT8/f0xdepUPPvss5g/f77iB3BR4yy1Lbaypc27eR9LP+4y52NPO6V0X0e3Z0RESrWUMUVjnJG7B27MTyxcuBAbNmxA586dMWjQIIgI3njjDQA3HoRxs1vbvh49emDevHl48cUXUVRUhI4dOxrLaiUv7+hzsK0krXLFWrSFCxfi0qVL+Mc//oHIyEj4+PggKSkJc+bMwXvvvYfi4mLj8Tw9PbFmzRpEREQgMDAQDz74IKZNm4bCwkLk5ua65DMhcqX6h7EEBASo3teWORmtrfMkbVM6p2hPHNozH3np0iWkpqYiOTkZ999/v911Idfw9/fHu+++2+CLsixx5Hyqs9k6Trty5Qr+85//wGAwIDIy0uK8bf0DPh393SNqmbj+xjJXzKUQkXuyp6+odF+l5ZR+B5KopVH6t29PjCidI1U65r0Z54WIiIiISBEhIiLSuNGjR8vo0aObuhpEmpWVlSXO7JYCkKysLMXlKyoqJC0tTSIjI8XX11dCQkIkMTFRCgsLTcotX75cIiMjxcvLS8LDw2XGjBnyj3/8QwDIxo0bRUQkNjZWOnXqZHaOt956SwDI9u3bjdu2bdsmI0aMkMDAQPHz85Po6GhZtGiRGAwGY5n4+HiJioqS77//Xvr16yc+Pj5SW1srIiIHDhyQpKQkCQ4OFm9vb4mIiJBp06bJhQsXTM69YsUKY727du0qr776qrzzzjsCQDZv3qz4c6qn5LzW6t3Q9eTm5kpCQoIEBQWJl5eXdOvWTSZPnizl5eWKPg9HO3z4sLz//vsiIrJnzx4BIOnp6WblVqxYIZ999pnZ9oyMDAEgGzZssHoOtfuWl5dLaGioJCcny+rVqwWA/Pjjj2b7Ky3XEGfHqYj22uOkpCQJCgqSqqqqpq6K0aOPPipt27aVysrKpq4KWeCKOKSWSWv3VyK1eH8lIrIN759EjVM7L+luxyeihjl7vG3L8ZnfUEcr+Y2UlBTx9/c3+f+h1KpVq2TFihVm2z/99FMBIBkZGYrL6fV6ASBjx441K7d161YBIJmZmYrr5qr+KNtbooZx/pnINTgP41yuzt0zL+8enN3PsyVuOaZTRytjOlesRWvfvr0kJiaalTty5IgAkIULF4qISHR0tPTo0cOsXP3fe/0YUSl3mz9lDKqjlRgcN26c+Pn52bSv2jmZlrzOk/GljlbiS+nco61xaO985JQpUyQwMFDOnDlj3GbPPeFW7tgfJdIaxiFR8+CKPATHj+zfOoI9fUWl+yotp/Q7kEoxDrcbtzEO3TsOlf7t2xMjSudIlY556zWXeSEiIiIianoedj5vlIiIiIioRXnssceQnZ2NdevWobKyEoWFhfDz88OIESNw9OhRAMC7776LqVOnYtSoUTh58iQKCgrg6emJGTNmAAB8fX1VnTM3Nxfx8fFo3749iouLUVZWhjlz5mDOnDmYNWuWsZyPjw8uX76M1NRUJCUlYeXKlfDw8EBRURGGDBmCuro65Ofno6KiAqtWrcInn3yCkSNHora2FgDw/vvvY8qUKRgzZgxOnz6NgoICeHl5YfHixTZ9VkrPa63e1rZ/++23GD58ONq0aYPCwkLo9Xp8/PHHyMnJwb333guDwdDgcW9VXl5u8S24t/4UFxdbvdbo6Gg8//zzjX4maWlpePzxx822Hzx4EDqdDn369HHYvpMmTUJtbS3eeuutBuuktBy51rx583DhwgW8++67TV0VAMDhw4eRk5ODV155BUFBQU1dHSIiIiIiIiIiIlKJ+Q3ltJTfyMvLw+233w4fHx/Vn1NqairS0tLMtp85cwYAEBkZqbiciAAAdDqdWbng4GAAN/IhRERERK7mytw98/LUEI7plNPSmM7Za9FOnTqFiooKxMTEmJWLioqCl5cX9u3bBwDo168fSktLUVVVZVLu2LFjAGDxGM0JY1A5LcXghQsXEBgYaNPnpHZOpiWv82R8Kael+FI692hrHNozH3ny5Em8/fbbSEtLQ+fOnY3b7bknEBERUcvB/q1yWurf2tNXVLqv0nJKvwPZnDEOldNSHCr927cnRpTOkSod89ZryfNCRERERORgTf3EUiIioqbmijccEZF1zn5zEVS8Yezq1avi4eEhEydONNleVVUl7du3l1WrVomISM+ePaV79+7y22+/mZQbOHCgyZu6lL5hbPr06RIQECAnT540KTd8+HBp27at8d9JSUni6ekpy5YtMyk3dOhQ6dKli9mbyD/66CMBIJ9++qmx3j169Gi03kopPa+1elvbfvfdd0tISIhcvXrVZHtmZqbJG7Ss7e9sat4cVlpaKunp6dKqVSuZN2+eqvM0tO+6desEgKxfv15ExOqbw5SWa4y7vnm+uUtLS5PAwED5+eefm7QetbW1MnToUOnTp49cvny5SetC1vFNf2QrLd5fidTg/ZWIyDa8fxI1Ts28pDsen4ga5uzxttrjM7/B/IY1fn5+MnbsWPn444/ljjvuEF9fX2nXrp2MGzdOTp06pfp4paWl0rlzZ+nbt6/U1taqKhcVFSXh4eFSU1NjUnbFihUCQMaPH6+4Hq7qj7K9JWoY55+JXIPzMM7nitw98/Luxdn9PLVxyzEdx3RKOXot2t69ewWALF682OI+nTp1ksGDB4uIyA8//CBBQUHy5z//WU6dOiU1NTWyZcsWad++vSQnJ6u+FneaP2UMMgatGTJkiHTp0kXmzZsnMTEx4uvrK2FhYTJ58mSpqKhocF81czIteZ0n44vxpYalOUV74tDW+ciJEydKYGCg6PV6k+321OVW7tYfJdIixiFR8+CKPATHj+zfOoI9fUWl+9pyDjXfgbSGcbhdRBiHzSEOb6b0b19tjNgzR2ptvU1zmhciIiIioqZn/vh9IiIiapG2bNmi6A07Op0OgwYNaurqEjUJb29vdOzYEV988QVycnJw/fp1AECbNm1QXl6O1NRUnD9/HiUlJYiLizN7m1VCQoJN501PT0d1dTW6detmsj0iIgJVVVWorKw0bqutrUVycrLx3xcvXkReXh7uvfdeszeR19ensLDQWO8hQ4aY1XvkyJGq66z0vNbqbW17ZWUlioqKMHz4cLM3td1///0AgO3btzd63KZ27Ngx6HQ6hIaGYsGCBViyZAnmzp3rkH3PnDmD1NRUPPzwww1eu9Jy1HTeeOMN9OvXD2PGjDG+Oa8pzJs3D/v370d2djZat27dZPUgIlKD4xsiIiIiopaP/X4i5ZjfUE5L+Y3ffvsNV69exbfffouMjAysXbsWZWVlyMrKQl5eHgYOHIgLFy4oPp5er0dSUhKqqqqQmZmJVq1aqSqXnp6O06dPY/z48SgpKUFVVRXWrl2L1atXA4Dx75aIiIjI1VyRu2denhrCMZ1yWhrT3cxZa9GuXr0K4MbfoCXe3t64cuUKAKBfv37YuHEj9uzZg65du8LHxwcJCQm455578MEHHzjgKpsOY1A5rcVgXV0dampq4O/vj23btqG0tBSrVq1CdnY2BgwYgOrqaov7qZmTaenrPBlfymktvm5lbU7R1jgEbJuP/PXXX/Hxxx8jNTUV7dq1M/mdPXUhIiKiloH9W+W01r+1p6+odF/2R29gHCqntTh0BVvnSK2NeVv6vBAREREROR4fGEpERKQRCQkJEBFFPwUFBU1dXaIm4eHhgX//+98IDg7GqFGjEBQUhPvvvx/Lli2DXq8HAJSWlgIAOnToYLZ/p06dbDqvwWDA8uXLERsbi7CwMPj4+MDT0xMZGRkAbiwerKfT6RAWFmb899mzZ1FXV4d169aZfUm+S5cuAIBTp04Z6x0SEmJ2/puPp5TS81qrt7XtZ86csVqn+s+3vkxDx21qUVFREBHo9XpkZmZi5cqVGDRokEnyx9Z9J0yYAABSx8OZAAAgAElEQVTGBWvWKC1HTcfLywt5eXk4cOCAWYLMlRYtWoRLly7htttua7I6EBGpxfENEREREVHLx34/kXLMbyinpfyGh4cHPDw8UFVVhY0bN+L3v/89AgIC8MADD+C9997D2bNnsXz5ckXHKikpweDBg1FcXIyvvvoKd9xxh+pyDz/8MDZt2oSjR48iJiYGkZGR2Lx5M7KzswEAgYGB9l80ERERkQ1ckbtnXp4awjGdcloa093MWWvR6h9gfO3aNYv71tTUGMt88skniI+Px3PPPYcTJ06gpqYGBQUFOH78OAYMGICysjLHXbCLMQaV01oM7tmzB2VlZZg5cyZCQ0PRtm1bjB49GqtXr8bx48exdOlSi/upmZNp6es8GV/KaS2+btbQnKKtcQjYNh+ZmZmJ2tpapKSkmP3OnroQERFRy8D+rXJa69/a01dUui/7ozcwDpXTWhy6gi1zpA2NeVv6vBAREREROR4fGEpEREREdJO7774bxcXF2L17N6ZOnYqLFy9ixowZ6NWrFw4cOGAsV1tba7bvzRP7aiQnJ2P69OkYOXIkcnNzodfrYTAY8Nxzz5mV9fDwML5B6mYTJ060+mX5jRs3GsvpdDqzfevq6myqt5rzWqu3te0iYnXbzddgbX930a5dOzzyyCP48ssvsW/fPixZssSufdesWYOtW7fivffeQ2hoqNV9lZYjIiIiIiIiIiIiopaB+Q11tJDf0Ol0CAkJQc+ePdGuXTuT3w0bNgw6nc7kb8Oa/Px8DBo0CNeuXUNubi6GDx9uc7nExEQcOHAANTU1qKioQFZWFjw8bixfi4yMVH2NREREREQtBcd06mhhTGeJo9ei1X9R39IX2Wtra6HX69GlSxfU1tZi8uTJiIuLw5IlS9C9e3d4e3tj4MCBWLt2LY4ePYr09HSHXWdTYAyqo9UYrJeQkACdTofCwkKLv1c6J6OVdZ6ML3W0Fl9K5x5v1Vgc1lM7H/nPf/4TAwYMQI8ePRRfg9K6EBERUcvA/q06Wuvf3sqevqLSfbXYH2UcqqP1OHQUW+ZIGxrzamVeiIiIiIgciw8MJSIiIqf4f//v/0Gn02HLli1NXRUi1XQ6HeLi4rBw4UJ89913yM/Px8WLF7FgwQLjG7oqKirM9rv5zVcA0KpVK4tJhHPnzhn/++zZs/jXv/6F5ORkzJ8/Hz179oS/vz88PT1x8uTJRusaHh4ODw+PRss2VO+b3wSmlNLzqtW1a1fodDqcPXvW7Hf/+9//jGXUKC8vN3sLmqWf4uJiu+r+66+/YsKECcjMzDT7XUxMDADgp59+smvfH374AcCNJNPNdZ80aRIAoF+/ftDpdNi/f7+icpYSX+Te2L4SETkH769ERETkDOxjEDUvjFlqCZjfaJzW8ht33nknzp8/b7a9trYWIgJvb+8G61BQUID4+HhERESgsLAQffv2taucJfn5+QCAuLg4xfuQ+2D7SURE7o5tFTUnHNM1TktjOlesRevcuTNCQ0Px3//+16zc4cOHUVtbiwEDBuDkyZOorq7GbbfdZlaud+/exvLNHWOwcVqKwWvXrmH//v34+eefzX5XU1MDEYGvr6/V8yuZk1G6HrQlrPNkfDVOS/FVr7E5RXvj0Bpr85HHjx/HwYMHMWLECLN9nFUXalocLxI1PcYhNVfs3zZOS/1be/qKSvdlf9Qc47BxWopDV1A7R9rYmFdL80JERERE5Dh8YCgRERGRm6iurkZkZCR0Oh0OHTrUYNn09PQGJz5vngTcu3cvRo0ahS5dusDHxwdRUVGYOXMmqqurTY5ZV1eHVatWoU+fPvD19UXnzp3xwgsv4MKFC065Xne0c+dOhIeH4+DBgybbBw8ejLCwMFRUVCAsLAxdu3bF3r17zd6CtXnzZpN/d+rUyfi2sJtt27bN+N81NTUAgA4dOpiUOXz4MHbu3AnA8tu26gUEBGDo0KHYsWMHSktLTX63e/duxMTEoKioCGFhYQgPD0d+fr7Z8bZu3Wr1+PaeV622bdti8ODB2LFjB65evWqxnvHx8aqO2aFDB6tvQbv5Jzo6WnV9bxYSEoL169fjzTffNHtrW/0DPHv27GnXvitXrrRY99WrVwMAfvzxR4gI3n77bUXlPD097bpmInekpo20RGm7uW/fPvzxj39EUFAQfH190b9/f6xZs8bseErLERE1F9euXcNTTz0FnU6HZcuWKd5v//79+NOf/oSgoCB4e3ujV69emDVrltn99WaWxkgGg6HRhSApKSl2XycRERG5hr1jOKVzmkeOHMHo0aMRHByM1q1bIyYmBvPnz8elS5ccVhcirVAST7dS249vbH6G4wJzzG8op7X8xuOPPw69Xo+vv/7aZPv27dsBNPyQzhMnTiAxMRG9e/fGtm3b0LFjR7vKTZkyBb169cL169eN2+rq6vDBBx/gtttuQ2xsrNW6EDV3SnMPlihte5X2jZm3ICKixihdw6Z0bKZmDKfV+RmO6ZTT0pjOFWvRAGDcuHHYuXMnysrKTMplZWXB09MTjz32GEJDQ+Hj42PxnlC/rUePHo18Iu6LMaiclmKwpqYGcXFxFucZN23aBAC47777rJ5fyZyM0vWgzXmdJ+NLOS3FF6BsTtHeOFQ7H5mXlwcAuP322x1eF6LmTsmaQVfkEG1Zg0jUUiiJQ0d9L7ChuSGlOQZ78iLujP1b5bTUv7Wnr6h0X/ZH/w/jUDktxaErqJkjVTLm1cK8EBERERE5Hh8YSkREROQmpkyZgl9++UVR2fpkXWVlpcVJwfpJwF27dmHo0KHw9vZGXl4eysrK8Prrr+Odd97ByJEjTRaDvvTSS5g7dy5ee+01VFZWIisrCzk5OUhMTGxwwrolGTBgADw9PfH000+jsLAQBoMBer0ey5cvx6lTpzBhwgQAwCuvvIKSkhJMnToV58+fR2lpKWbOnGmWRE1MTERdXR0WLFiAqqoqlJaWYtq0aaiqqjKW6d69OyIjI5GTk4NDhw7BYDBg06ZNGDVqFMaMGQPgRqLU0pvK6i1duhStWrXCgw8+iOLiYhgMBuzYsQNPPfUUfHx8jG+fevnll1FSUoKZM2eirKwMp0+fxsyZM6HX6236vJSeV6033ngD1dXVePbZZ/HLL7/g0qVL+OabbzBnzhzExsbi0Ucftem4zubn54dly5Zh//79SElJwYkTJ3DlyhXs2rULEydORFBQEF5++WUAwDfffAOdTofp06er3peIGqa0jbREabuZk5ODP/zhDwgICEBRUREqKirw9NNPIyUlxWQBjtJyRETNRWVlJeLj41FSUqJqv6KiIgwaNAiBgYE4cOAAKioqsGLFCnz00Ud44IEHzL6kVs/SGMnX19fqApAvvvgCwI23rBIREVHzYM8YDlA2p/nTTz/hrrvuwvnz57Fr1y6cO3cO8+fPR3p6ukm/wd66EGmB0ni6lZp+vJL5GY4LzDG/oY6W8hvjxo3DsGHD8Mwzz2D37t24cuUKtm/fjtTUVERFRWHixIkAzPMWwI121mAwIDs7G4GBgVbPobRcQkICjh8/jsmTJ6OiogKlpaV4/vnncejQIXz44YfQ6XSOu3AiN6ImZ38rNW2vkr4x8xZERKSE0jVsSsdmasZwWp2f4ZhOHa2M6Vy1Fm327Nno0KEDkpOTcezYMRgMBqxfvx7Lli3DnDlz0K1bN/j7+2P69OnYtWsXZs+ejVOnTuHKlSsoKCjA888/j6CgILzyyisu/XwciTGojlZiMDAwEAsWLMDOnTsxZcoUnD59GlVVVdiwYQPS0tLQv39/vPDCCwAsz6sonZNp6Rhf6mglvgBlc4r2xqHa+cgjR44AACIjI+2qC1FLo2TNoCtyiLauQSRqCZSu3XXU9wKtzQ0pzTHYkxdxd+zfqqOV/q09/Val+7I/+n8Yh+poJQ6d4dZ4VTNHqnQdDRERERGRakJERKRxo0ePltGjRzd1NVqcDz/8UADI5s2bm7oqzcJXX30lAOTRRx8VAPLjjz82WP7FF18UAHL9+vUGy8XGxkp4eLjU1NSYbJ8+fboAkO+++05ERPbs2SMA5MMPPzQpt2bNGunTp48cPnzYhqtSJisrS5zZLQUgWVlZisv/+uuv8txzz0nXrl3F29tbOnToIHFxcSbHqKurk0WLFkm3bt3Ey8tLwsPDZdasWbJ69WqTv/va2lqZN2+e9OjRQ3x8fCQiIkIWL14sOTk5AkC2bNkiIiLff/+9DBs2TAICAiQoKEgSExPl4MGDUlJSItHR0eLp6Sl//etfJSkpSVq1amWx3vv27ZOkpCQJDg4WT09PCQ8Pl2nTpklFRYVJvRcuXCjdunUTT09P6dKli0yfPl3Wr18vAOTLL79U/fkqOa+1ejd0PXv27JGRI0dK27ZtxcvLS3r27CmzZs2SS5cuKdrf0aZNmyYArP488cQTxrKff/653HPPPdKmTRvx9fWVXr16yZNPPilHjhwxlvn6668FgEybNs3kPEr2taT+b6+xe4fScrdydpyKsD1Wiu1r45S2kZYobTd79eol4eHhYjAYTMpNmDBBWrdubbwHKi2nhCvikFom3l+V4f21cXq9Xm677TaZN2+ecfyQnp6uaN8HHnhA/Pz85PLlyybbX3/9dQEgO3fuNNtH7RipurpaunbtKsnJycovSnh/JSKyFe+fyrCP0Th7xnBK5zQfeugh8fHxkbKyMpNyU6dONemL2FMXS9TOS7rb8bWIMds4pfGklKV+vNL5GaXHcxZnj7dtOT7zG+poJb8hInL58mWZNWuWdO/eXby8vCQsLExSUlLk3LlzxjK35i0uX77cYF4EgEyYMEFxuXpffPGFDBw4UAICAqRNmzaSkJAge/fuVX1NruqPsr1tHNvPxtnTtilte5X2jR2ZtxDh/DORq3Aexj5sq9RRm5+xROnYzFI5R8/PWOPsfp4tccsxnTpaGtO5Yi3ayZMn5YknnpAOHTqIt7e39O3bV1avXm1Wl7Vr18qQIUMkMDDQ+P9y/PjxcvToUdXX5W7zp4xBdbQUg9nZ2RIXF2eMj9/97nfyl7/8RS5evGgsYy0GlczJWNLS1nkyvtTRQnypnVO0Jw7VzEfW90UbWrOtpC5KuGN/VIs4Xmyc0jWDrsgh2rIGsSGMQ/fAOGyc0jh01PcCG5obUppjsCcvcitX5CE4fmT/1lHs6bcq7WcqKafmO5BKMA4Zh80lDpX+7SstZy1eG5sjVTvmvZU7zwsRERERUdNjj4+IiDTPFROWFRUVkpaWJpGRkeLr6yshISGSmJgohYWFJuWWL18ukZGRxgnIGTNmyD/+8Q8BIBs3bhSRG0mTTp06mZ3jrbfeEgCyfft247Zt27bJiBEjJDAwUPz8/CQ6OloWLVpkkpiJj4+XqKgo+f7776Vfv37i4+MjtbW1IiJy4MAB40Sgt7e3REREyLRp0+TChQsm516xYoWx3l27dpVXX31V3nnnHZuTdkrOa63eDV1Pbm6uJCQkSFBQkHh5eUm3bt1k8uTJUl5erujzcJby8nIJDQ2V5ORkxZN548aNEz8/v0aPvWLFCvnss8/MtmdkZAgA2bBhg4iIpKSkiL+/v1nSzhXc7YGh9mCymloqd11IyvZVHa20r0rbSEuUtJt6vV4AyNixY83Kbd26VQBIZmam4nJKMXFHtuL9lfdXRzl8+LC8//77IiKqHxgaHR0tPXr0MNtef2/LyMgw2W7LGGnKlCkSGBgoZ86cUXZBt9SBiIjUseX+yT6GOlrpY9gzhlM6p7lq1SpZsWKF2fZPP/3UpC9iT10scbcvvKvFmFVHKzGrNJ6UstSPV5rXUHo8Z3HHB4bag/kNam7c9YGhbD/V0Ur7aU/bprTtVdI3dnTeQoQPDCVyFUe2e2yr1NFKW1XPlvyMJUrHZpbKOXp+xpqW9mAYjumoOWru86c3YwySu3DXdZ72YHxRS+WO/VGOF9XRynhR6ZpBV+QQ1a5BbAzjcLtxG+OwZcShI74X2NDckJocgz15kVu544MK7cH+LTVHjEOi5oHfiyEiIiLSBg8QERGR0z322GPIzs7GunXrUFlZicLCQvj5+WHEiBE4evQoAODdd9/F1KlTMWrUKJw8eRIFBQXw9PTEjBkzAAC+vr6qzpmbm4v4+Hi0b98excXFKCsrw5w5czBnzhzMmjXLWM7HxweXL19GamoqkpKSsHLlSnh4eKCoqAhDhgxBXV0d8vPzUVFRgVWrVuGTTz7ByJEjUVtbCwB4//33MWXKFIwZMwanT59GQUEBvLy8sHjxYps+K6XntVZva9u//fZbDB8+HG3atEFhYSH0ej0+/vhj5OTk4N5774XBYGjwuLcqLy+HTqdr9Ke4uLjRa540aRJqa2vx1ltvKf6cLly4gMDAwEbLpaWl4fHHHzfbfvDgQeh0OvTp0wcAkJeXh9tvvx0+Pj6K60BE1NTYviqnpfZVaRtpiZJ2U0QAADqdzqxccHCwsbzSckTuiPdX5bR0f42Ojsbzzz9v0+fUr18/lJaWoqqqymT7sWPHAAAxMTEm29WOkU6ePIm3334baWlp6Ny5s011JCIi52MfQzkt9THsGcMpndNMTU1FWlqa2fYzZ84AACIjI+2uS0vEmFVOSzGrNJ6UsNaPV5rXUHo8IiJXYvupnJbaT1vbNkB526ukb8y8BREBbKvU0FJbVc+WNWy3Ujo2s1aO8zNERERERE2D40XltDReVLpm0BU5RLVrEJsjxqFyjENzjvheYENzQ2pyDPbkRYiIiIiIiIiIqAFN+7xSIiKipufsNxxdvXpVPDw8ZOLEiSbbq6qqpH379rJq1SoREenZs6d0795dfvvtN5NyAwcONHljkdK3/E2fPl0CAgLk5MmTJuWGDx8ubdu2Nf47KSlJPD09ZdmyZSblhg4dKl26dDF7s9xHH30kAOTTTz811rtHjx6N1lsppee1Vm9r2++++24JCQmRq1evmmzPzMw0eZuktf2dZd26dQJA1q9fLyJi9gY+a4YMGSJdunSRefPmSUxMjPj6+kpYWJhMnjxZKioqrO5XWloq6enp0qpVK5k3b55xu5+fn4wdO1Y+/vhjueOOO8TX11fatWsn48aNk1OnTjnmYq1w9puLwDeMEdnNHd88z/aV7as1traRllhrN6OioiQ8PFxqampMyq9YsUIAyPjx41WVU4Jv+iNb8f7K+6szNPSWckt++OEHCQoKkj//+c9y6tQpqampkS1btkj79u0lOTnZpKwtY6SJEydKYGCg6PV61dfC+ysRkW3U3j/Zx2Afwxp7xnD2zGmWlpZK586dpW/fvlJbW2t3XSxx9rykM4/PmGXMqmEpnpRQ2o+3Nj9j6/Ecxdn5RWcf/1bMb1Bz46rxvJr2lu0n20+llLZtDe1/a9urtG/syLyFiOvbKyKtclS7x7aKbVVDbF3DdiulYzNr5Rw9P2ONs+dtXJ1/4piOmqPmPH96K8YguQt3XOdpL8YXtVTu1h/leJHjRSXUrhl0dA5RzRpEJRiH20WEcdiS4tDe7wUqmRuyNcdgT17EFf1Pjh+JGsY4JGoe+L0YIiIiIm0wf2UNEREROZS3tzc6duyIL774Ajk5Obh+/ToAoE2bNigvL0dqairOnz+PkpISxMXFmb1RLiEhwabzpqeno7q6Gt26dTPZHhERgaqqKlRWVhq31dbWIjk52fjvixcvIi8vD/fee6/Zm+Xq61NYWGis95AhQ8zqPXLkSNV1Vnpea/W2tr2yshJFRUUYPny42dsS77//fgDA9u3bGz2uo505cwapqal4+OGHVZ+vrq4ONTU18Pf3x7Zt21BaWopVq1YhOzsbAwYMQHV1tUn5Y8eOQafTITQ0FAsWLMCSJUswd+5cAMBvv/2Gq1ev4ttvv0VGRgbWrl2LsrIyZGVlIS8vDwMHDsSFCxccdt3kvrZs2aLo7ZU6nQ6DBg1q6uqSxrF9VU5r7avaNtKShtpN4MbfwenTpzF+/HiUlJSgqqoKa9euxerVqwHA+PeotByRO+H9VTmt3V/t0a9fP2zcuBF79uxB165d4ePjg4SEBNxzzz344IMPjOVsGSP9+uuv+Pjjj5Gamop27do56xKIiMhO7GMop7U+hq1jOHvmNPV6PZKSklBVVYXMzEy0atXKrrq0RIxZ5bQWs7eyFk+NUdKPb2x+Ru3xqGVjfoPcAdtP5bTafqpp26yx1Paq6Rszb0GkbWyrlNNaW2XPGrabKR2bNVSO8zPaxDEdUdNiDBI5D+OLmguOF5XT2njRVs7IISpdg9hcMQ6VYxyas/d7gUrnhtTmGByRFyH3wv4tUdNjHBIRERERaRsfGEpERORkHh4e+Pe//43g4GCMGjUKQUFBuP/++7Fs2TLo9XoAQGlpKQCgQ4cOZvt36tTJpvMaDAYsX74csbGxCAsLg4+PDzw9PZGRkQHgRjKonk6nQ1hYmPHfZ8+eRV1dHdatW2c2SdilSxcAwKlTp4z1DgkJMTv/zcdTSul5rdXb2vYzZ85YrVP951tfpqHjOtqECRMAwJgYU2PPnj0oKyvDzJkzERoairZt22L06NFYvXo1jh8/jqVLl5qUj4qKgohAr9cjMzMTK1euxKBBg1BZWQkPDw94eHigqqoKGzduxO9//3sEBATggQcewHvvvYezZ89i+fLlDrnmlm7ixIkQEZuT7U0tISEBIqLop6CgoKmrSxrH9lU5rbWvattISxpqNwHg4YcfxqZNm3D06FHExMQgMjISmzdvRnZ2NgAgMDBQVTkid8L7q3Jau7/a45NPPkF8fDyee+45nDhxAjU1NSgoKMDx48cxYMAAlJWVAbBtjJSZmYna2lqkpKQ4pe5EROQY7GMop7U+hq1jOFvnNEtKSjB48GAUFxfjq6++wh133GF3XVoixqxyWovZmzUUT41R0o9vbH5G7fGoYcxvENmP7adyWm0/1bRtllhre9X0jZm3INI2tlXKaa2tsmcN282Ujs0aKsf5GdtwTEfUtBiDRM7D+CJyDY4XldPaeNEWzsohKl2D2FwxDpVjHJqz93uBSueG1OYY7M2LtETs3xI1PcYhERERERE1Z3xgKBERkQvcfffdKC4uxu7duzF16lRcvHgRM2bMQK9evXDgwAFjudraWrN9b06uqZGcnIzp06dj5MiRyM3NhV6vh8FgwHPPPWdW1sPDw+IbG+snPy39bNy40VhOp9OZ7VtXV2dTvdWc11q9rW0XEavbbr4Ga/s70po1a7B161a89957CA0NddhxExISoNPpTN6GeLN27drhkUcewZdffol9+/ZhyZIl0Ol0CAkJQc+ePc3ewjls2DDodDqTv1MiInfB9lUdLbSvDWmsjbTEUrtZLzExEQcOHEBNTQ0qKiqQlZVlfOtxZGSk6nJE7oT3V3W0fn9tTG1tLSZPnoy4uDgsWbIE3bt3h7e3NwYOHIi1a9fi6NGjSE9Pt3mM9M9//hMDBgxAjx49nHcRRETkEOxjqKP1PkZjYzhb5jTz8/MxaNAgXLt2Dbm5uRg+fLhD6tJSMWbV0VrM2hpP9dT04xuan7HleEREzsT2Ux2ttZ/1lLRtt2qo7VXbN2begkjb2Fapo4W2ypFr2JSOzWwZw2l1foaIiIiIyFU4XlRHC+NFWzgrh6h0DWJzxzhUh3H4f+z5XqDauSFbcgy25EWIiIiIiIiIiMgcHxhKRETkIjqdDnFxcVi4cCG+++475Ofn4+LFi1iwYIHxLXkVFRVm+9389jkAaNWqlcVE3rlz54z/ffbsWfzrX/9CcnIy5s+fj549e8Lf3x+enp44efJko3UNDw+Hh4dHo2UbqvfNb+NTSul51eratSt0Oh3Onj1r9rv//e9/xjJqlJeXm72J0NJPcXGxxf1/+OEHADeSqzeXnzRpEgCgX79+0Ol0FhO5165dw/79+/Hzzz+b/a6mpgYiAl9fX/z666+YMGECMjMzzcrFxMQAAH766ScAwJ133onz58+blautrYWIwNvbW+EnQ2QuISEBAQEBTV0NaqHYvjZOS+2r0jbSEjXtpjX5+fkAgLi4OIeUI2pKvL82Tkv3V3ucPHkS1dXVuO2228x+17t3bwDA4cOHbRojHT9+HAcPHsSIESMcXm8iInIO9jEap6U+hj1jOEDdnGZBQQHi4+MRERGBwsJC9O3b16F1aakYs43TUszWayyeGtNQP96W+RmOC8hRmMsgR2H72TgttZ+OyD0oaXvtzfczb0GkLWyrGqeltsqeNWw3Uzo2a6gc52fIHhzTEbkO442o6TEOyVk4XmyclsaLajkzh6h0DWJLwDhsHOPQMlvzBI6YG7o5x+CIvAi1fOzPErkfxiURERERUfPAB4YSERE52c6dOxEeHo6DBw+abB88eDDCwsJQUVGBsLAwdO3aFXv37jV7E93mzZtN/t2pUyfjG/tutm3bNuN/19TUAAA6dOhgUubw4cPYuXMnAMtvvKsXEBCAoUOHYseOHSgtLTX53e7duxETE4OioiKEhYUhPDwc+fn5ZsfbunWr1ePbe1612rZti8GDB2PHjh24evWqxXrGx8erOmaHDh2svonw5p/o6GiL+69cudJi+dWrVwMAfvzxR4gIPD09zfatqalBXFwcUlJSzH63adMmAMB9992HkJAQrF+/Hm+++abZWxf3798PAOjZsycA4PHHH4der8fXX39tUm779u0A+MUg0p4jR45g9OjRCA4ORuvWrRETE4P58+fj0qVLJuX27t2LUaNGoUuXLvDx8UFUVBRmzpyJ6urqJqq5drB9VU5L7avSNtISNe3mlClT0KtXL1y/ft1Ypq6uDh988AFuu+02xMbGqipH5E54f1VOS/dXe4SGhsLHxweHDh0y+139th49etg0RsrLywMA3H777Q6vNxERORb7GMppqY9hzxgOUD6neeLECSQmJqJ3797Ytm0bOnbs6PC6tDSMWeW0FLOAsnhqTEP9eDXzM7a1rsQAACAASURBVEqOR9TSKc1lKC1H9mH7qZyW2k9b2rabKW17lfaNmbcg0ja2Vcppqa2yZw3bzZSOzRoqx/kZ0hqlY7Wff/4ZY8aMQUhICHx8fNC7d28sXrzYrH9JRNYpXefJeCNyHqVxWFdXh1WrVqFPnz7w9fVF586d8cILL+DChQtNVHNt4HhROS2NF9Vwdg5R6RrE5oxxqBzj0DJbvxeoZm5ISY7B3rwIkbtS2p/dt28f/vjHPyIoKAi+vr7o378/1qxZ00S1JmrZlMyvpqenN/jQ7sZelkZERERE5G74wFAiIiInGzBgADw9PfH000+jsLAQBoMBer0ey5cvx6lTpzBhwgQAwCuvvIKSkhJMnToV58+fR2lpKWbOnGm2uCExMRF1dXVYsGABqqqqUFpaimnTpqGqqspYpnv37oiMjEROTg4OHToEg8GATZs2YdSoURgzZgyAG5PUlt4WWG/p0qVo1aoVHnzwQRQXF8NgMGDHjh146qmn4OPjY3zb48svv4ySkhLMnDkTZWVlOH36NGbOnAm9Xm/T56X0vGq98cYbqK6uxrPPPotffvkFly5dwjfffIM5c+YgNjYWjz76qE3HdYVvvvkGOp0O06dPBwAEBgZiwYIF2LlzJ6ZMmYLTp0+jqqoKGzZsQFpaGvr3748XXngBfn5+WLZsGfbv34+UlBScOHECV65cwa5duzBx4kQEBQXh5ZdfBgCMGzcOw4YNwzPPPIPdu3fjypUr2L59O1JTUxEVFYWJEyc25UdA5FI//fQT7rrrLpw/fx67du3CuXPnMH/+fKSnpyM5OdlYbteuXRg6dCi8vb2Rl5eHsrIyvP7663jnnXcwcuRILhJ1Mrav6milfVXaRgLm7auadjMhIQHHjx/H5MmTUVFRgdLSUjz//PM4dOgQPvzwQ+h0OlXliNwJ76/qaOX+qsat91d/f39Mnz4du3btwuzZs3Hq1ClcuXIFBQUFeP755xEUFIRXXnnFpnMdOXIEABAZGemw+hMRkXOwj6GOVvoY9ozhAOVzmi+99BIMBgOys7MRGBhod120gDGrjlZiFlAWT4DlmK3XUD9ezfyMkuMRtWRKcxlKy5H92H6qo5X2U03bZqn9VNr2Ku0bM29BpG1sq9TRSlulhq1jPaXlOD9DWqJ0rFZaWorY2FhUVVWhsLAQFy9exBtvvIHXX38dL730UhNeAVHzoXSdJ+ONyHnUrLd+6aWXMHfuXLz22muorKxEVlYWcnJykJiY2OBD68g+HC+qw/GiOWfnEJ25BtFdMA7VYRyaU5onaCgOG6Mkx2BLzp/I3Sntz+bk5OAPf/gDAgICUFRUhIqKCjz99NNISUnBsmXLmvgqiFoWpfOr9X2kyspKiw/IbuxlaUREREREbkeIiIg0bvTo0TJ69GinnuPXX3+V5557Trp27Sre3t7SoUMHiYuLk6ysLGOZuro6WbRokXTr1k28vLwkPDxcZs2aJatXrxYAsnnzZhERqa2tlXnz5kmPHj3Ex8dHIiIiZPHixZKTkyMAZMuWLSIi8v3338uwYcMkICBAgoKCJDExUQ4ePCglJSUSHR0tnp6e8te//lWSkpKkVatWFuu9b98+SUpKkuDgYPH09JTw8HCZNm2aVFRUmNR74cKF0q1bN/H09JQuXbrI9OnTZf369QJAvvzyS9Wfl5LzWqt3Q9ezZ88eGTlypLRt21a8vLykZ8+eMmvWLLl06ZKi/V2h/v/3jz/+aNz29ddfCwCZNm2aSdns7GyJi4uTDh06iLe3t/zud7+Tv/zlL3Lx4kWTcp9//rncc8890qZNG/H19ZVevXrJk08+KUeOHDEpd/nyZZk1a5Z0795dvLy8JCwsTFJSUuTcuXPOu2ARycrKEmd2SwGYxBq5Xnx8vPj7+zd1NRR76KGHxMfHR8rKyky2T506VQDIzp07RUQkNjZWwsPDpaamxqTc9OnTBYB89913Lquzszk7TkVsa4/ZvqqjpfZVSRtprX1V2m5+8cUXMnDgQAkICJA2bdpIQkKC7N2716wuSss1xhVxSC0T76+8vzrKtGnTBIDVnyeeeEJErN9f165dK0OGDJHAwEDjZz9+/Hg5evRog+e1NEaq9+KLLwoAs3u0Gry/EhHZxpb7J/sY6miljyFi3xiusTnNy5cvN9iHASATJkxQVRelnD0v6ezjM2bV0ULMqoknazEroqwfr3R+RunxnMHZ+UVX5C/JVEvNZSgt19y4ajyvtr1l+6mOFtrPekratlvbT7V9WaX5fkflLUTYXhG5iiPbPbZV6miprbqVmjVsIsrHZkrKOXJ+xhpnz6sw/+R6LXVM9+KLL4qfn5+Ul5eblFuyZInodDo5fPiwy+rsaM19/lTLmlu8KV3n2RLizV3XeZLjtdQ43LNnjwCQDz/80KTcmjVrpE+fPs0iDpVyx/4ox4vqaGW8qGTNoCtziLauQbSEccg4bElxWE9JnqChOLyZtbW7SnMManL+DXFF/5PjR9drqf3ZXr16SXh4uBgMBpNyEyZMkNatW5vcn5oTxqE2NLe4VDO/CkCuX7/eFNV0KeYliIiIiLSBPT4iItI8d1+48uGHH5ok7YhaGj4wVJ2KigpJS0uTyMhI8fX1lZCQEElMTJTCwkKTctu2bZMRI0ZIYGCg+Pn5SXR0tCxatMgk6ZSYmCg9e/aUgwcPyvDhw8Xf31+CgoLkySeflIsXL8r69eulf//+4ufnJxEREfLmm2+anGPo0KHStWtX2b9/vwwbNkz8/f2ldevWct9998n3339vLGcpYXDgwAFjct7b21siIiJk2rRpcuHCBdXX6mirVq2SFStWmG3/9NNPBYBkZGSIiMiKFSvks88+MyuXkZEhAGTDhg1OracrtcSFpGxfqblh4o5sxfsrUcN4fyUiso2r75/sY1BzpOUvvDNmSQv4wNCGMZfhPrkMpeWaG3d9YKg92H5Sc9Tc2yui5sJd5rHZVlFL4o4PhnEnHNO5z5iuffv2kpiYaFbuyJEjAkAWLlzo1Ho6k5bnT2/GeHN+vCld59kS4q0lrvN0Bcah+8RhSkqK+Pv7mz1gqSVqaf1RjhepOWIcEjUPfFBh49ifdY/+rF6vFwAyduxYs3Jbt24VAJKZmenUejoL41A9xqX7zK+OGzdO/Pz8nFoXd9Hc8xJEREREpIwHiIiIiIio2XjssceQnZ2NdevWobKyEoWFhfDz88OIESNw9OhRAEBubi7i4+PRvn17FBcXo6ysDHPmzMGcOXMwa9Ys47G8vb1RXl6OF198EUuWLEFpaSlmz56NdevW4aGHHkJGRgZycnJw9uxZxMbG4pVXXkFhYaFxfx8fH5SVleHZZ5/F3/72N5w/fx4FBQU4duwYRowYgfLycovXUFRUhCFDhqCurg75+fmoqKjAqlWr8Mknn2DkyJGora1VfK23Ki8vh06na/SnuLjY6mecmpqKtLQ0s+1nzpwBAERGRgIA0tLS8Pjjj5uVO3jwIHQ6Hfr06WP1HERERERERERERERELRVzGe6Ty1BajoiIiIiIqB7HdO4xpjt16hQqKioQExNjVi4qKgpeXl7Yt2+f1XNQ88B4c368KVnnyXjTNsahe8QhAOTl5eH222+Hj49PI//XiIiIiKge+7Pu0Z8VEQCATqczKxccHGwsT9rAuHSP+VUAuHDhAgIDAxv630VERERE1KzwgaFERERERM2EwWDAtm3bkJiYiMGDB8PX1xcRERHIyMiAj48Ptm7dCgD48ssv4evri/T0dHTu3Bn+/v544oknMGzYMKxdu9bkmFVVVfjLX/6CgQMHIiAgAFOmTEFAQADy8/ORkZGBiIgIBAUFGRMN3377rXHfVq1awWAwYObMmRg+fDhat26Nfv364Y033kBFRQU+/vhji9cxdepUBAcHIzs7G71790ZAQAAefPBBLF68GN999x02bNig+Fpv1aFDB4hIoz/R0dGqPvtz585h5cqV6Nu3L2JjY62WWbZsGd566y3MnTvX4uJRIiIiIiIiIiIiIqKWjLkM985lqClHRERERETawzGd+4zpzp07ZzzfrTw8PBAcHGwsQ80T461p4s3SOk/Gm3YxDt0nDgHgl19+QZcuXZCZmYk777wTfn5+CA4OxhNPPIHTp08rPj4RERGRVrA/6z792eDgYERFRSEvLw/Xrl0zKZ+bmwsAOH/+vOJzUPPFuHSf+VXgxgNDvby8MH/+fPTp0wd+fn7o3LkzXnrpJej1elXHJyIiIiJyB3xgKBERETnVli1bFL3tR6fTYdCgQU1dXSK35u3tjY4dO+KLL75ATk4Orl+/DgBo06YNysvLkZqaCgBIT09HdXU1unXrZrJ/REQEqqqqUFlZabI9Li7O+N+enp4IDg5Gjx49EBYWZtzeqVMnAEBpaalZveLj403+fe+99wIAfvjhB7OyFy9eRF5eHu69916zN0AnJCQAAAoLCxVfqyvo9XokJSWhqqoKmZmZaNWqlcnvjx07Bp1Oh9DQUCxYsABLlizB3LlzXVY/0ia2r0REzsH7KxERETkD+xhEzQtjlsg+zGW4Zy5DbTkitdh+EhGRu2NbRaQMx3TuM6a7evUqgBv/Tyzx9vbGlStXXFZHcjzGm2vjraF1now37WIcuk8c/vbbb7h69Sq+/fZbZGRkYO3atSgrK0NWVhby8vIwcOBAXLhwwel1JG3ieJGo6TEOiWzD/qz79GeBG5/z6dOnMX78eJSUlKCqqgpr167F6tWrAcBYZ2rZGJfuM78KAHV1daipqYG/vz+2bduG0tJSrFq1CtnZ2RgwYACqq6tdVkciIiIiIkfgA0OJiIjc3MSJEyEixom05iYhIUHR235EBAUFBU1dXSK35uHhgX//+98IDg7GqFGjEBQUhPvvvx/Lli0zeaOVwWDA8uXLERsbi7CwMPj4+MDT0xMZGRkAbiyqqteqVSu0bdvW5Dw6nQ7BwcFm227dFwC8vLzQvn17k231+1p6o/rZs2dRV1eHdevWmSXuu3TpAgA4deqU4mt1tpKSEgwePBjFxcX46quvcMcdd5iViYqKgohAr9cjMzMTK1euxKBBg8wSM+Re2L4SETkH769ERETkDOxjEDUvjFkibWMuwz1zGWrKUdNg+0lERO6ObRWRNnBM5z5jutatWwMArl27ZnG/mpoaYxlqnhhvro23htZ5Mt60i3HoPnHo4eEBDw8PVFVVYePGjfj973+PgIAAPPDAA3jvvfdw9uxZLF++3CX1JPU4XiRqeoxDIm1if9Z9+rMA8PDDD2PTpk04evQoYmJiEBkZic2bNyM7OxsAEBgY6JJ6UtNiXLrP/CoA7NmzB2VlZZg5cyZCQ0PRtm1bjB49GqtXr8bx48exdOlSl9WTiIiIiMgR+MBQIiIiIqJm5O6770ZxcTF2796NqVOn4uLFi5gxYwZ69eqFAwcOAACSk5Mxffp0jBw5Erm5udDr9TAYDHjuueccXh8PD/MhhYhY/V29+gUJln42btyo+FqdKT8/H4MGDcK1a9eQm5uL4cOHN1i+Xbt2eOSRR/Dll19i3759WLJkidPrSERERERERERERETkbpjLcL9chtqcBxERERERaRfHdO4xpgsLCwMAlJWVme1XW1sLvV5v/II+NV+MN9fFWz1L6zwZb9rGOHSPONTpdAgJCUHPnj3Rrl07k/LDhg2DTqdzaR2JiIiImgv2Z92jP1svMTERBw4cQE1NDSoqKpCVlWW87sjISJfVkZoW49I95lcbkpCQAJ1Oh8LCQudWkIiIiIjIwfjAUCIiInIrCQkJCAgIaOpqELk1nU6HuLg4LFy4EN999x3y8/Nx8eJFLFiwAGfPnsW//vUvJCcnY/78+ejZsyf8/f3h6emJkydPOrwuNTU1qKqqMtlWUVEBAOjUqZNZ+fDwcHh4eCiuS0PXakl5ebnZm8ss/RQXFzd43oKCAsTHxyMiIgKFhYXo27evye9//fVXTJgwAZmZmWb7xsTEAAB++uknRddI1FTY5hIROQfvr0REROQM7GMQuS/GJ5FlzGU0fS5DbTkid8B2lYiI3BnbKdISjumafkzXuXNnhIaG4r///a/ZvocPH0ZtbS0GDBig6BrJvTHenBdvStd5Mt6Icdj0cQgAd955J86fP29Wrra2FiICb29vRddI5GwcGxI1H4xX0gr2Z92jP2tNfn4+ACAuLk7RNVLLwLhs+vnVa9euYf/+/fj555/N9q2pqYGIwNfXV9E1EhERERG5Cz4wlIiIiMgBrl27hqeeego6nQ7Lli2zWGbv3r0YNWoUunTpAh8fH0RFRWHmzJmorq62etzq6mpERkZCp9Ph0KFDzqo+NRM7d+5EeHg4Dh48aLJ98ODBCAsLQ0VFBWpqagAAHTp0MClz+PBh7Ny5E8D/vQHMUb7++muTf2/fvh3AjTc63yogIABDhw7Fjh07UFpaavK73bt3IyYmBkVFRYqu1ZIOHTpYfXPZzT/R0dFWr+fEiRNITExE7969sW3bNnTs2NGsTEhICNavX48333wTdXV1Jr/bv38/AKBnz55Wz0FE9muojdy3bx/++Mc/IigoCL6+vujfvz/WrFnTRDUlImpeGhuDKBn7EBEREd1K6Twn50OJXKexvn16enqDi7Jra2uNZTkXQzdjLsN9chlqyhGRbdS0l/v378ef/vQnBAUFwdvbG7169cKsWbMaXC9ARERkr7q6OqxatQp9+vSBr68vOnfujBdeeAEXLlywug/nZ7SNYzr3GtONGzcOO3fuRFlZmcn2rKwseHp64rHHHrN6DnJ/jDfnx5uadZ6MN21iHLpXHD7++OPQ6/VWr58PWCKyj5J1f0eOHMHo0aMRHByM1q1bIyYmBvPnz8elS5dMytny3SgiUkZpLoE5BwLYnwXcqz87ZcoU9OrVC9evXzeWqaurwwcffIDbbrsNsbGxFs9BLQvj0n3mV2tqahAXF4eUlBSz323atAkAcN9991k9BxERERGRO+IDQ4mIiIjsVFlZifj4eJSUlFgts2vXLgwdOhTe3t7Iy8tDWVkZXn/9dbzzzjsYOXKkWcKg3pQpU/DLL784q+rUzAwYMACenp54+umnUVhYCIPBAL1ej+XLl+PUqVOYMGECunfvjsjISOTk5ODQoUMwGAzYtGkTRo0ahTFjxgC4sUDjt99+c0id/Pz8sHDhQnz99de4cuUKfvjhB8yaNQuhoaEYO3asxX2WLl2KVq1a4cEHH0RxcTEMBgN27NiBp556Cj4+Pujbt6+ia3WWl156CQaDAdnZ2QgMDLR63cuWLcP+/fuRkpKCEydO4MqVK9i1axcmTpyIoKAgvPzyy06rIxFZbyNzcnLwhz/8AQEBASgqKkJFRQWefvpppKSk8MF2REQKNDQGUTL2ISIiIrJE6Twn50OJXENJ377+4TGVlZUWF2V7enoC4FwMmWMuw31yGWrKEZFtlLaXRUVFGDRoEAIDA3HgwAFUVFRgxYoV+Oijj/DAAw9YXS9ARERkr5deeglz587Fa6+9hsrKSmRlZSEnJweJiYlWv3DM+Rlt45jOvcZ0s2fPRocOHZCcnIxjx47BYDBg/fr1WLZsGebMmYNu3bo5rY7kfIw358ebmnWejDdtYhy6VxyOGzcOw4YNwzPPPIPdu3fjypUr2L59O1JTUxEVFYWJEyc6pY5EWqAkN/jTTz/hrrvuwvnz57Fr1y6cO3cO8+fPR3p6OpKTk43lbP1uFBE1TmkugTkHqsf+rHv1ZxMSEnD8+HFMnjwZFRUVKC0txfPPP49Dhw7hww8/hE6nc0odyb0wLt1nfjUwMBALFizAzp07MWXKFJw+fRpVVVXYsGED0tLS0L9/f7zwwgtOqyMRERERkTPwgaFEREREdqisrERsbCzuuece/P3vf7dabvbs2QgJCUFmZiZ69OiBNm3aYOzYsXjxxRdRUFCAffv2me3zn//8Bx999BEeffRRZ14CNSOtW7fG7t27cdddd2HMmDFo27YtevfujZycHGRlZeGZZ56Bh4cHNm7ciKioKOPbuN5++21kZWXhtddeQ3R0NJKSkjB//nyH1Mnb2xsZGRlYvHgxOnXqhMGDB6N379749ttv0bp1a4v7DBw4EHl5eQgPD0dsbCwCAwMxfvx4PProo9i2bRt8fX0VXaszXLlyBf/5z39gMBgQGRkJnU5n9lO/4GzSpEn4/PPPcezYMfTv3x/t27fHxIkTcffdd6OwsBCRkZFOqSMRNdxGzpo1C507d8Ynn3yCqKgo+Pv7Y+rUqXj22Wcxf/586PX6JqgxEVHz0ND9VenYh4iIiOhWSuc5OR9K5BpK+/b1D0ALCAho8Hici6FbMZfhPrkMNTkPIrKN0vZy9uzZ8PT0xJo1axAREYHAwEA8+OCDmDZtGgoLC5Gbm+uK6hIRkcYUFBRg9erV+Pvf/45HHnkEfn5+GDp0KJYuXYrq6mocOXLEbB/OzxDHdO4zpgOA9u3bIy8vD507d8bgwYPRtm1bLFq0CCtXrnTY50tNh/Hm/HgDlK/zZLxpE+PQveKwVatW2LRpE8aPH4/x48cjKCgITzzxBOLj45GXl8cXIhHZSGlu8NVXX0VtbS02btyIvn37IjAwEMnJyZg0aRI2bdqEXbt2AbDtu1FEpIzSXAJzDlSP/Vn36s/Gx8dj48aN+OGHH9CjRw/07t0bZ86cQW5uLmJjY51WP3IvjEv3ml+dMWMGsrOzUVRUhDvuuAMdO3bE3LlzkZKSgt27d1u9fiIiIiIityVEREQaN3r0aBk9enRTV8MpKioqJC0tTSIjI8XX11dCQkIkMTFRCgsLTcpt27ZNRowYIYGBgeLn5yfR0dGyaNEiMRgMxjKJiYnSs2dPOXjwoAwfPlz8/f0lKChInnzySbl48aKsX79e+vfvL35+fhIRESFvvvmmyTmGDh0qXbt2lf3798uwYcPE399fWrduLffdd598//33xnLx8fHi7+9vsu+BAwckKSlJgoODxdvbWyIiImTatGly4cIF1dfqaIcPH5b3339fRET27NkjACQ9Pd2s3IoVK+Szzz4z256RkSEAZMOGDSbby8vLJTQ0VJKTk2X16tUCQH788UfnXEQTy8rKEmd2SwFIVlaW046vZfHx8RIQENDU1SAXcHacijT/9phtrvPb3HoNtZF6vV4AyNixY83227p1qwCQzMxMl9TT0VwRh9Qy8f7K+6tSjY1BlI59mhveX4mIbNPc75/sY7hPH0NtuebE2fOSLXXek/HpPnmNcePGiZ+fX4PHaslzMY1x9ni7uY/n3QlzGS2Tq/qjzb29Zbvq/HZVSXspIhIdHS09evQw217/t5yRkeGE2jkf2ysi12ju8zDWsJ1yfjuVkpIi/v7+Jp9VQ1ri/Iw1zu7ntdS4bQoc07VcnD91P4y35o/rPJs/xqF2sD/6fzg2dJ/c4KpVq2TFihVm2z/99FOTOUy1341yV4xD9Rivzo9XpbmElppzsMQV/U+OHx2H/dmWiXHYvDEutaMl9j+JiIiIyJyHk55DSkRERG7gscceQ3Z2NtatW4fKykoUFhbCz88PI0aMwNGjRwEAubm5iI+PR/v27VFcXIyysjLMmTMHc+bMwaxZs4zH8vb2Rnl5OV588UUsWbIEpaWlmD17NtatW4eHHnoIGRkZyMnJwdmzZxEbG4tXXnkFhYWFxv19fHxQVlaGZ599Fn/7299w/vx5FBQU4NixYxgxYgTKy8stXkNRURGGDBmCuro65Of/f/buPKzKOv//+OsAsgikoiZuKS4jbi02pqZmyyjYMlaDkjmSk0s/U1PTar5OZk6NaZhrXaZNabQJNmrZWE2ZK265jFmK5ZrLYAiKlIIin98fXpLEAe4DHM72fFwX19Xc53Pu+338ft/3+7Od+2xUZmam5syZo3feeUe9evVSfn6+5c/6W6dOnbL760G//UtLSyvx3zg6OlrDhg0r8/8WY8aMUf/+/Ysd37Vrl2w2m9q2bVvk+PDhw5Wfn6+5c+eWeW7AlYwxrg4BcAvUXOfX3CtKq5FX7kk2m63YaxEREZIu114AnoP7q3vcXyXrYx8AADwBfQz36WM42g7ej/x0n3WNM2fOKDw8vNQ2zMXAU7CWAV9FXXV+XbVSLyWpffv2Sk9PV3Z2dpHj+/fvlyS1adOmzHMAgLehTjm/TqWmpurGG29UUFCQpf+bMD8Dd8WYDqg65BvgeuQhfA1jQ/dZGxw1apTGjBlT7Pjx48clSc2aNZPk+Hej4D3IV+fnq9W1BNYc4M7ozwLuh7wEAAAAvIjLHlUKAICb8NZfuj1//rzx8/MzQ4YMKXI8Ozvb1K5d28yZM8cYY8z48eNNWFiYOXLkSJF2t99+u6lRo0bh/+7Tp4+RZD755JPCYxcvXjRhYWGmWrVq5sSJE4XHd+/ebSSZKVOmFB6LiYkxksx7771X5DqLFy82ksz06dML2139633du3c3DRs2LPJLgsYY8+abbxaez+pndbbSfm3zt9LT001iYqLx9/c3zz33XJHX3n33XSPJLF682BhjzLx584wks3v3bqfE7WrO/uUi8QtjTmPv1zbhnfjl+dJRc6uu5lqpkS1atDCNGjUyeXl5Rd47c+ZMI8kMHDjQqTE6C7/0h/Li/sr91QpHxyCOjH3cHfdXACgfT75/0sdwvz6Gt86HOnte0hvnPclP91rXuPXWW03Dhg3Nc889Z9q0aWOCg4NN/fr1zYgRI0xmZmZhO2+diymLs8fbnjyedzesZXinquqPenK9pa5WTV21Wi+/+eYbU7NmTfPHP/7RHD161OTl5ZnPPvvM1K5d28THxzstPmejXgFVw5PnYUpCnaqaOhUSEmL69etn3n77bXPTTTeZ4OBgU6tWLfPwww+bo0ePFmnrrfMzJXF2P88b89ZVGNN5L+ZP3Q/55vnY5+n5yEPfQX/0MsaG7rU2aE96erpp0KCBadeuncnPJNUrYAAAIABJREFUzy+xTUnfjXJn5KFjyNeqyVerawneuuZgT1X0Pxk/Vh76s96JPPRs5KXv8Lb+JwAAAOzzc+ThogAAwHMEBgbq2muv1fLly7Vs2TJdvHhRknTNNdfo1KlTGjVqlCQpMTFROTk5uu6664q8PyoqStnZ2Tp9+nSR4926dSv874CAAEVERKhp06aqX79+4fF69epJktLT04vFFRMTU+R/33HHHZKkb775pljbs2fPKjU1VXfccYeCgoKKvBYbGytJ2rJli+XP6g72798vm82myMhITZ48WVOnTtXEiRMLXz9+/LhGjRql+++/X/Hx8S6MFABgFTW3amqu1RqZmJioY8eOaeDAgTpw4ICys7O1aNEizZs3T5IKYwbg/ri/utf9FQAAb0Efw736GPRFcDXy073WNQoKCpSXl6fQ0FCtWrVK6enpmjNnjpYsWaKOHTsqJydHEnMxAOCuqKtVU1et1sv27dtr6dKl2rRpkxo3bqygoCDFxsbqtttu04IFC5wWHwC4K+qU8+vUpUuXdP78eX311VdauHChFi1apIyMDCUnJys1NVWdOnXSmTNnJDE/AwAAAMA1GBu619rgb2VlZalPnz7Kzs5WUlKS/P39i7xe1nej4F3I16rJV6trCaw5AAAAAAAA+CYeGAoAgJfy8/PTihUrFBERoQcffFA1a9bUH/7wB02fPl1ZWVmF7XJzczVjxgx17dpV9evXV1BQkAICArRw4UJJlzcPX+Hv768aNWoUuY7NZlNERESxY799ryRVq1ZNtWvXLnLsyntPnjxZ7DOcOHFCBQUFevfdd2Wz2Yr8NWzYUJJ09OhRy5/VHbRo0ULGGGVlZSkpKUmzZs1S586dCxc9Bw8eLEmFX6QF3Nlnn32mn3/+2dVhAC5Hza2ammu1Rt5///1auXKlvv/+e7Vp00bNmjXTp59+qiVLlkiSwsPDnRongMrD/dW97q8AAHgL+hju1cegL4KrkZ/uta6xadMmZWRk6Omnn1ZkZKRq1KihuLg4zZs3TwcPHtS0adMkMRcD98daBnwVdbVq6qrVevnOO+8oJiZGjz76qA4fPqy8vDxt3rxZBw8eVMeOHZWRkeHUOAHA3VCnnF+n/Pz85Ofnp+zsbC1dulTXX3+9wsLC1LNnT73++us6ceKEZsyYIYn5Gbg3xnRA1SHfANcjD+FrGBu619rg1Q4cOKAuXbooLS1Nn3zyiW666aZibcr6bhS8C/laNflqdS2BNQe4K/qzgPshLwEAAADvwgNDAQDwYr///e+Vlpam9evX68knn9TZs2f11FNPqWXLltq5c6ckKT4+XuPHj1evXr20YcMGZWVlKTc3V48++milx+PnV7zrYYwp8bUrhgwZImOM3b+lS5da/qzupFatWnrggQf00Ucfafv27Zo6dareeustff7553r99dcVGRnp6hABAA6g5jq35jpaI3v37q2dO3cqLy9PmZmZSk5OLvzczZo1c0qMAJyD+6t73V8BAPAW9DHco49BXwT2kJ/uu65xRWxsrGw2m7Zs2VJ4jLkYAHBP1FXX1dWr62V+fr5GjBihbt26aerUqWrSpIkCAwPVqVMnLVq0SN9//70SExOrPEYAcDXqlHPrlM1mU926ddW8eXPVqlWryGs9evSQzWbTzp07mZ8BAAAA4FKMDd1vbXDjxo3q3LmzLly4oA0bNuj2228vtb2970bBO5Gvzs1Xq2sJrDkAAAAAAAD4Lh4YCgCAl7PZbOrWrZteeOEFbd26VRs3btTZs2c1efJknThxQh9//LHi4+M1adIkNW/eXKGhoQoICNCRI0cqPZa8vDxlZ2cXOZaZmSlJqlevXrH2jRo1kp+fn+VYSvus9pw6darYrwLa+0tLS3Pwkxb1448/avDgwUpKSir2Wps2bSRJe/bs0TfffCPp8gLp1dcfPny4JKl9+/ay2WzKz8+vUDzwTbGxsQoLC3N1GIBXo+Y6r+ZWRo3cuHGjJKlbt26WPiMA98H91b3vrwAAeCr6GK7vY+zYscNSO/oivof8dP26xoULF7Rjxw798MMPxV7Ly8uTMUbBwcGlnoO5GJQHaxlA5aOuOq+uWq2XR44cUU5Ojlq3bl2sXatWrSRJe/futfQZAcDbUKecO/7r0KGDfvrpp2LH8/PzZYxRYGAga0WoVIzpgKpDvgGuRQ4ClYuxoevXBq/YvHmzYmJiFBUVpS1btqhdu3ZFXrf63Sh4L/LVeflqdS2BNQdUBvqzgHsiNwEAAACUhQeGAgDgpdauXatGjRpp165dRY536dJF9evXV2ZmpvLy8iRJderUKdJm7969Wrt2raRff12vsnzxxRdF/vfq1aslST169CjWNiwsTN27d9eaNWuUnp5e5LX169erTZs22rZtm6XPak+dOnVK/FXAq/+io6Mr8pFVt25dLV68WLNnz1ZBQUGR1658Kb558+aaNWuW3evPmzdPkrR7924ZYxQQEFCheABPsm/fPsXFxSkiIkLVq1dXmzZtNGnSJP38889F2v3www/q27ev6tatq6CgILVq1UovvfRSsZy7Wm5ubpmL8UOHDi1s//XXX+vBBx9Uw4YNFRQUpBYtWujpp59WTk5OsXNfuHBBCQkJstlsmj59euX9g8AtUXOdX3MdqZFjx45Vy5YtdfHixcL3FxQUaMGCBWrdurW6du1axr8cAHfB/dW97q8AAHgL+hju08d49dVX6YugCPLTfdY18vLy1K1btyLzo1esXLlSknTnnXdKEnMxgKyvZezYsUP33HOPatasqcDAQLVs2VLPPPOM3XWG3yooKNCcOXPUtm1bBQcHq0GDBnrsscd05syZcsXiyJoHPBN11fl11Wq9jIyMVFBQkL799tti7a4ca9q0qd1rAIC3ok5Vzfivf//+ysrKKvFzdevWjbUiQO41prN6DasxA+6mKvZgWs2Pym4HeILyzAnm5OSoWbNmstlsduc2fot5TDiCsaH7rA1K0uHDh9W7d2+1atVKq1at0rXXXlusjdXvRsH7kK/Oz1erawmsOcCXWe0bVlYfsrS+sNVrMKaEL7CaD1bHiyWxMldkNecqGgsAAADgKjwwFAAAL9WxY0cFBATokUce0ZYtW5Sbm6usrCzNmDFDR48e1eDBg9WkSRM1a9ZMy5Yt07fffqvc3FytXLlSDz74oPr27Svp8mTdpUuXKiWmkJAQvfDCC/riiy907tw5ffPNN3rmmWcUGRmpfv362X3PtGnT5O/vr3vvvVdpaWnKzc3VmjVrlJCQoKCgILVr187SZ3WlkJAQTZ8+XTt27NDQoUN1+PBhnTt3TuvWrdOQIUNUs2ZNPfHEEy6NEXBHe/bs0c0336yffvpJ69at08mTJzVp0iQlJiYqPj6+sF16erq6du2q7OxsbdmyRWfPntXLL7+sKVOmaOTIkSWePzg4uMRF+OXLl0tS4XXWrVun7t27KzAwUKmpqcrIyNCUKVP02muvqVevXkU2vJw+fVoxMTE6cOCAk/5l4G6oue5Tc6XLv6h48OBBjRgxQpmZmUpPT9ewYcP07bff6o033pDNZnN1iAAs4v7qXvdXAAC8BX0M+hhwX+Sn++RneHi4Jk+erLVr12rs2LE6duyYsrOzlZKSojFjxuiGG27QY489Jom5GMDqWsa2bdvUuXNnhYeHa+fOncrMzNTMmTP15ptvqmfPnqX+AJokjRw5UhMnTtSLL76o06dPKzk5WcuWLVPv3r0Lv1xpNRZH1jzguairzq+rVutlaGioxo8fr3Xr1mnChAk6evSozp07p82bN2vYsGGqWbOmRo8e7ZQYAcBdUaeqZvz38MMPq0ePHho0aJDWr1+vc+fOafXq1Ro1apRatGihIUOGOO3agKdwpzGd1WtYjRlwN1WxB9NqflR2O8ATlHdOcOzYsTp06JDl6zCPCUcwNnSftUHpcv7m5uZqyZIlCg8Pt9uG70b5LvLV+flqdS2BNQf4Kqt9w8rsQ5bUF7Z6DcaU8AWO5JyV8WJJrMwVOZJzFYkFAAAAcCkDAICPi4uLM3Fxca4Owyl+/PFH8+ijj5rGjRubwMBAU6dOHdOtWzeTnJxc2Oa///2v6dGjhwkLCzM1a9Y0vXv3Nrt27TIHDhww0dHRJiAgwPztb38zffr0Mf7+/sWu0aRJE9OpU6cixzIyMowkM2LEiMJjMTExpkaNGmb79u3mjjvuMGFhYaZ69ermD3/4g9mzZ0+RdqGhoUXOt337dtOnTx8TERFhAgICTKNGjcy4ceNMZmamQ5/VGcaNG2cklfg3YMCAwrb/+te/zG233WauueYaExwcbFq2bGn+/Oc/m3379pV6jXnz5hlJZvfu3U79LK6SnJxsnNktleT0/z/wBPZyy93dd999JigoyGRkZBQ5/uSTTxpJZu3atcYYYx5//HETEhJiTp06VaTd1KlTjc1mM3v37nXoujk5OaZx48YmPj6+8FjXrl1No0aNTF5eXpG248ePN5LM1q1bjTHGZGVlmdatW5vnnnvObNq0yUgyiYmJDl3fHTk7T43x/HpMzXV+zbWnpBq5fPly06lTJxMWFmauueYaExsba77++usqj68yVUUewjtxf+X+Wh727q+OjH08CfdXACgfT79/0sdwnz5GRdq5O2fPS3rrvCf56V7rGkuWLDHdunUzderUMYGBgeZ3v/ud+b//+z9z9uzZIuf0xrmYsjh7vO3p4/ny8ua1jJ49e5qQkBDzyy+/FGk3ZcqUIu3subLe8MYbbxQ5/tZbb5m2bdsWroNYjcXqmoc7q6r+qKfXW+pq1fR7rdbLRYsWmVtvvdWEh4ebgIAA07BhQzNw4EDz/fffOz1GZ/HVegVUNU+fhykJdapq6tQvv/xinnnmGdOkSRNTrVo1U79+fTN06FBz8uTJUt/nLfMzJXF2P89b87YsjOnsszqms3oNqzG7O+ZPK8YT860q9mBazY/Kbucu2OdZdbw5B6/2ySefGEnmT3/6k6W+IfOY1tEf/RVjQ/dYG/zll19KbSPJDB48uPCc5f1ulDshDx1HvlbNXI7VtQRvXHOwpyr6n94+frTHm/uzldWHLK0vbPUanjamLAl5WHW8OTetjhftsTpXZDXnKhKLO/PG/icAAACKo8cHAPB5bFypGjExMSYsLMzVYcAN8cBQ+7p3725CQkJMTk5OsdcmTJhgJJk1a9YYY4xZtWqVueuuu0x4eLgJCQkx0dHR5h//+IfJzc0tfM9vFwy6du1q6tWrV+zcc+fONZLM6tWrC4/t3LmzcEE8MDDQREVFmXHjxpkzZ85U4icubs6cOWbmzJnFjr/33ntGklm4cKExxpjatWub3r17F2u3b98+I8m88MILDl137NixJjw83Bw/frzw2MyZM837779frO3ChQuNJJOSkmKMMWbv3r1m/vz5xhjDA0MdRD2uPNRc78TCHcqL+2vl4f7qnbi/AkD5cP+sPPQxvBdfePd85CdKwwNDL2Mtw/paRnR0tGnatGmxdlf6VVfa2TN06FATGhpa5N+qIrFYXfNwZzww1PNQV72Tp9QrwNMxD+N81Cnfw4NhLmNM515jOqvXsBqzu/O1+VPyrWr2YFrNj8pu5y7Y51kyctDxOcFTp06ZyMhIEx8fb/lh8sxjWkd/1D0xNvQt5KFnI199Bw8qvIz+rPW+YWX0IcvqC1u9hqeNKUtCHpaM3LSeD1bHi/ZYnSuymnMVicWd0f8EAADwDX4CAACoIsYYV4cAeIyEhASdP39eK1asKPba4sWLFRUVpdtuu00bNmxQTEyMateurbS0NGVkZOjZZ5/Vs88+q2eeeabCcWzbtk233nqrCgoKtHHjRmVmZmrOnDl655131KtXL+Xn59t936lTp2Sz2cr8S0tLK/Hao0aN0pgxY4odP378uCSpWbNmOnr0qDIzM9WmTZti7Vq0aKFq1app+/btlj/vkSNH9Oqrr2rMmDFq0KBB4fExY8aof//+xdrv2rVLNptNbdu2lSRFR0dr2LBhlq8HOAs1FwCcg/srAABwBvoYgPsiP4HSsZZhbS1Dktq3b6/09HRlZ2cXabd//35JsrvOcUVqaqpuvPFGBQUFlfrvYDUWq2seQGWjrgIA3Bl1Cr6IMZ17jemsXsNqzHAv5FvV7MG0mh+V3Q7ujxx0fE5w+PDhys/P19y5cy1/PuYx4Q0YGwKeg3yFL6E/a71vWBl9yLL6wlavwZjS+5Gb1vPB6njRHqtzRVZzriKxAAAAAK7GA0MBAAAAN9S3b18FBwcrOTm5yPHNmzfr4MGDeuSRR2Sz2fTRRx8pODhYiYmJatCggUJDQzVgwAD16NFDixYtqnAcTz75pCIiIrRkyRK1atVKYWFhuvfee/XSSy9p69atSklJsfu+OnXqyBhT5l90dLRD8Zw8eVKzZs1Su3bt1LVrV508ebLwer/l5+eniIiIwjZWvPjiiwoODtbYsWPLjGP69OmaO3euJk6cWOqmbwAAAAAAAAAAvBFrGfb9di1DkiZOnKjg4GAlJCTo2LFjunDhgj7//HPNmDFD8fHxuuWWW0o836FDh9SwYUMlJSWpQ4cOCgkJUUREhAYMGKBjx445HIu9Nqx5AAAAAL6HMZ19rhrTVeQaVsZ+cC3yrbiqmo+wmh+V3Q7uhRwsrrQcfO+997RkyRK9+uqrqlu3ruVzMo8JAADgHPRni7PaN3S0D1mevrAj12BM6V3IzeJKyoeKjBcrwl7OuSoWAAAAoDLwwFAAAADADdWoUUN//OMf9dlnn+ns2bOFx99//33ZbDYlJCRIkhITE5WTk6PrrruuyPujoqKUnZ2t06dPlzuGs2fPKjU1VXfccUexX8yKjY2VJG3ZsqXc53dUVlaW+vTpo+zsbCUlJcnf31/nz5+XJAUGBtp9T2BgoM6dO2fp/D/++KPefvttjRo1SrVq1bLbZv/+/bLZbIqMjNTkyZM1depUTZw4sXwfCAAAAAAAAAAAD8ZaRnH21jIkqX379lq6dKk2bdqkxo0bKygoSLGxsbrtttu0YMGCEs936dIlnT9/Xl999ZUWLlyoRYsWKSMjQ8nJyUpNTVWnTp105swZh2K5gjUPAAAAwLcxpivOlWO68l6jrLEf3AP59quqnI+wmh+V3Q7uhxz8VVk5ePz4cY0aNUr333+/4uPjLZ+XeUwAAADnoT/7K6t9w/L0IR3tCzt6DcaU3ofc/FVp+VCR8WJF2Ms5V8UCAAAAVBYeGAoAAKrEZ599pp9//tnVYQAeJSEhQXl5eVq+fLmky5PjKSkp6tGjh6KioiRJubm5mjFjhrp27ar69esrKChIAQEBWrhwYeF7yuvEiRMqKCjQu+++K5vNVuSvYcOGkqSjR49W8FNac+DAAXXp0kVpaWn65JNPdNNNN0mSqlevLkm6cOGC3ffl5eUVtilLUlKS8vPzNXTo0BLbtGjRQsYYZWVlKSkpSbNmzVLnzp0rtDADVDZqLgA4B/dXAADgDPQxAPdFfgLWsJbxq5LWMiTpnXfeUUxMjB599FEdPnxYeXl52rx5sw4ePKiOHTsqIyPD7jn9/Pzk5+en7OxsLV26VNdff73CwsLUs2dPvf766zpx4oRmzJjhUCxXsOaBqkRdBQC4M+oUfBljul+5ekxXnmtYGfvBfZBvl1XVfITV/KjsdnBf5OBlZeXg4MGDJUnz5s1z6LzMY8IbMDYEPAf5Cl9Ef/Yyq33D8vQhHe0LO3INxpTei9y8rLR8KO94sSJKyjlXxAIAAABUJh4YCgAAALipmJgYXXvttUpJSZEkffXVVzp58qQGDRpU2CY+Pl7jx49Xr169tGHDBmVlZSk3N1ePPvpopcUxZMgQGWPs/i1durTSrlOSjRs3qnPnzrpw4YI2bNig22+/vfC1+vXrS5LdDdH5+fnKysoqXNwoy4cffqiOHTuqadOmZbatVauWHnjgAX300Ufavn27pk6daukaAAAAAAAAAAB4E9YyLittLSM/P18jRoxQt27dNHXqVDVp0kSBgYHq1KmTFi1apO+//16JiYl2z2uz2VS3bl01b95ctWrVKvJajx49ZLPZtHPnTsux2MOaBwAAAOC7GNNd5uoxXXmu4ejYD65HvhXlzPkIq/lR2e3g3sjBouzl4FtvvaXPP/9cr7/+uiIjIx06H/OYAAAAzkV/tiirfUOr7SrSFy7rGowpvRu5WZS9fCjPeLEiSsu5qo4FAAAAqGw8MBQAAJRbbGyswsLCXB0G4LUCAgLUv39//ec//9GZM2f0wQcfKCwsTHFxcZIu/wLYxx9/rPj4eE2aNEnNmzdXaGioAgICdOTIkVLP7e/vb/fXx06ePFn4340aNZKfn1+Z57Ln1KlTxX6VzN5fWlpaqefZvHmzYmJiFBUVpS1btqhdu3ZFXm/QoIEiIyP13XffFXvv3r17lZ+fr44dO5YZ78GDB7Vr1y7dddddxV778ccfNXjwYCUlJRV7rU2bNpKkPXv2lHkNwB5qKQA4B/dXAADgDPQxAM9CzgJVg7WMstcyjhw5opycHLVu3brYe1u1aiXp8ppGSTp06KCffvqp2PH8/HwZYxQYGGg5FtY8UF7UVQCAu6AmAZWLMZ17jOkcvUZZMcM9+XK+VeV8hNX8qOx2cH/kYNk5+M0330i6/DCbq887fPhwSVL79u1ls9mUn59v9zrMY8LVGC8CnoN8BRxHf7bsvmFF+pBW+8IHDx506BqMKb0fuWktHxwZL1aElZyrqlgAAAAAZ+CBoQAAwCdduHBBCQkJstlsmj59ut02BQUFmjNnjtq2bavg4GA1aNBAjz32mM6cOVPquRMTE0udIL16k8yOHTt0zz33qGbNmgoMDFTLli31zDPPKCcnp1I/LzxXQkKCLl68qBUrVmj58uWKi4tTaGioJCkvL0+SVKdOnSLv2bt3r9auXStJMsbYPW+9evUKf43saqtWrSr877CwMHXv3l1r1qxRenp6kXbr169XmzZttG3bNrvnr1OnTom/Snb1X3R0dImf/fDhw+rdu7datWqlVatW6dprr7Xb7uGHH9batWuVkZFR5HhycrICAgL00EMPlXiNK1JTUyVJN954Y7HX6tatq8WLF2v27NkqKCgo8tqOHTskSc2bNy/zGoC3sVJLt2/frrvvvls1a9ZUcHCwbrjhBr311luWzm+1Rlqt119//bUefPBBNWzYUEFBQWrRooWefvppai4At7Jv3z7FxcUpIiJC1atXV5s2bTRp0iT9/PPPxdpauQ9fLTc3t8zNHEOHDrXcrjwxAwAA17BarysybrJ6DatjPcZw8GVW8smRdYiSVNY6SWXEAs/HWkbpaxmRkZEKCgrSt99+W+y1K8eaNm1a4jX69++vrKwsffHFF0WOr169WpLUrVs3y7Gw5gFfY7WfWt69AZL1Pi57AwDAtzky1+HoGpAj72VfG+xhTOf6MZ0j17C6pw7uyVfzrarmI6zmR2W3g+cgB0vPwVmzZtk977x58yRJu3fvljFGAQEBdq/DPCZQPlbHi+WZw3R0L2Bl790GvFlOTo6aNWsmm81WbCz3ww8/qG/fvqpbt66CgoLUqlUrvfTSS8Vqmj1lff/C0byGd6E/W3rfsCJ9SKt94fr161u+BmNK30Fulp0PVseLFWE156oiFgAAAMBZeGAoAADwOadPn1ZMTIwOHDhQaruRI0dq4sSJevHFF3X69GklJydr2bJl6t27d4mTsJIKF7lPnz5td4L0yiaZbdu2qXPnzgoPD9fOnTuVmZmpmTNn6s0331TPnj0tLQTC+3Xo0EFt27bV5MmTdfr0aQ0aNKjwtSZNmqhZs2ZatmyZvv32W+Xm5mrlypV68MEH1bdvX0mXN5DY+yWx3r17q6CgQJMnT1Z2drbS09M1btw4ZWdnF2k3bdo0+fv7695771VaWppyc3O1Zs0aJSQkKCgoyKm/bDdy5Ejl5uZqyZIlCg8PL7HdhAkTVKdOHcXHx2v//v3Kzc3V4sWLNX36dD377LO67rrrJElffvmlbDabxo8fX+wc+/btkyQ1a9as2GshISGaPn26duzYoaFDh+rw4cM6d+6c1q1bpyFDhqhmzZp64oknKulTA57BSi1dtmyZbrnlFoWFhWnbtm3KzMzUI488oqFDh5b5pSZHaqSVer1u3Tp1795dgYGBSk1NVUZGhqZMmaLXXntNvXr1ouYCcAt79uzRzTffrJ9++knr1q3TyZMnNWnSJCUmJio+Pr5IW6tjmqsFBweXuIlj+fLlki7/KrLVdo7GDAAAXMNqva7IuMnqNayO9RjDwZdZzSer6xAlqcx1korGAu/AWkbpaxmhoaEaP3681q1bpwkTJujo0aM6d+6cNm/erGHDhqlmzZoaPXq0JPtrGQ8//LB69OihQYMGaf369Tp37pxWr16tUaNGqUWLFhoyZIjlWFjzgC9xZO6qvHsDrPZx2RsAAL7NkbmO8qwBOfJe9rXBHsZ0rh/TOXINq3vq4J58Nd+cMR9hL9+s5kdlt4PnIAedm4PMYwKOc2S8WJ45TEf2Alb23m3A240dO1aHDh0qdjw9PV1du3ZVdna2tmzZorNnz+rll1/WlClTNHLkyFLPaeX7F47kNbwP/dnS+4aO9CFL+45hZcQiMab0JeRm2flgdbxY3tyUrOec1VgAAAAAt2QAAPBxcXFxJi4uztVheKSYmBgTGhrq6jAckpWVZVq3bm2ee+45s2nTJiPJJCYmFmt35bU33nijyPG33nrLtG3b1uzdu7fEazz++ONGkrl48WKpsfTs2dOEhISYX375pcjxKVOmGElm7dq1Dnwyz5WcnGyc2S2VZJKTk512/qowdepUI8lERUWZgoKCIq/997//NT169DBhYWGmZs2apnfv3mbXrl3mwIEDJjo62gQEBJi//e1vxfI1Pz/fPPfcc6Zp06YmKCjIREVFmZdeesksW7bMSDKfffZZYdvt27ebPn2UCWyMAAAgAElEQVT6mIiICBMQEGAaNWpkxo0bZzIzM532mX/55RcjqdS/wYMHF7Y/cuSIGTBggKlTp44JDAw07dq1M/PmzStyzi+++MJIMuPGjSt2vSt5u2/fvhJj+te//mVuu+02c80115jg4GDTsmVL8+c//7nIe8aNG1dqzAMGDKiEf52q5+w8NcZ367E319KWLVuaRo0amdzc3CLHBw8ebKpXr17qPcRqjbRar7t27WoaNWpk8vLyirQbP368kWS2bt1q/R/ARaoiD+GduL96jvvuu88EBQWZjIyMIseffPLJIvc+q/dhq3Jyckzjxo1NfHy8w+2sxuzOuL8CQPn46v3Tm/sYFRk3Wb2G1bGeN4zhjHH+vKQ3zHs6mzfnrNV1CHsqe52kIrF4MmePtz1xPM9aRtlrGYsWLTK33nqrCQ8PNwEBAaZhw4Zm4MCB5vvvvy9sU9Jaxi+//GKeeeYZ06RJE1OtWjVTv359M3ToUHPy5MlyxWJlzcOdVVV/lHr7K2+uqxXZG2C1j+utewM8sV4BnshX52FK4ok1yepcR0XWgKy+l31tlzm7n+eJecuYzrVjOqvXcDRmd+bL86e+mG9XVOYezN/mm9X8qOx27oR9ntaQg47PCc6bN89IMrt37y48xjxmxdAfdQ5vHi9WZA7THnt7ASt777a7Iw9dyxPz9WqffPKJkWT+9Kc/FauRjz/+uAkJCTGnTp0q8p6pU6cam81Wao5U5PsXVvcCe5qq6H+68/jRHvqzZfcNrbQr7TuGV7PXF7ZyDU8cU5aEPLSG3Cw7N63MkdrLTStzRY7mnNX5Wk9C/xMAAMA30OMDAPg8b9i4YlX37t1NSEiIycnJKfbahAkTjCSzZs0aY4wxq1atMnfddZcJDw83ISEhJjo62vzjH/8osuj02wnIrl27mnr16hU799y5c40ks3r16sJjO3fuLJyADAwMNFFRUWbcuHHmzJkzlfiJi9u7d6+ZP3++McaUujl66NChJjQ0tNgimxUPP/ywCQkJKbNddHS0adq0abHjVybmFi5c6PC1PREPDAXcHxtJf0UttVZLs7KyjCTTr1+/Yu///PPPjSSTlJRU4jWs1kir9XrmzJnm/fffL3Z84cKFRpJJSUkp9f3ugIU7lBf318s84f46Z84cM3PmzGLH33vvvSL3PqtjGqvGjh1rwsPDzfHjxx1uZzVmd8b9FQDKx1Pun/QxrNfrioybrF7D6ljPG8Zwxvj2F97Li5y1nk9W1yHsqex1korE4sl4YCjgWjwwtGzUVet1tSJ7A6z2cb11bwD1CqganjIPUxJqkvW5joqsAVl9L/vaLuPBMIDrMX8KVD72eQKeg/7oZYwXrY8XKzKHaY+9vYCVvXfb3ZGHjiFff3Xq1CkTGRlp4uPj7T5IsHbt2qZ3797F3rdv3z4jybzwwgt2z1vR719Y3QvsaXhQIeB65CHgGbyt/wkAAAD7/AQAAHxGQkKCzp8/rxUrVhR7bfHixYqKitJtt92mDRs2KCYmRrVr11ZaWpoyMjL07LPP6tlnn9UzzzxT4Ti2bdumW2+9VQUFBdq4caMyMzM1Z84cvfPOO+rVq5fy8/Ptvu/UqVOy2Wxl/qWlpZV47ejoaA0bNqzMGFNTU3XjjTcqKCjI4c935swZhYeHl9muffv2Sk9PV3Z2dpHj+/fvlyS1adPG4WsDAJyLWmqtlhpjJEk2m63YaxEREZKkXbt2lfh+qzXSar0eM2aM+vfvX+z4rl27ZLPZ1LZt21LfD8D5uL9Ko0aN0pgxY4odP378uCSpWbNmkqyPaaw4cuSIXn31VY0ZM0YNGjRwuJ3VmAEAcBX6GNbrdUXGTVavYXWsxxjOd5Gz1vPJ6jqEPZW9TlKRWAAAzkNdtV5XK7I3wGofl70BAHwZNcn6XEdF1oCsvpd9bQAAAADcBeNF6+PFisxh/lZJewEre+82vAv5+qvhw4crPz9fc+fOLfba0aNHlZmZaXfepEWLFqpWrZq2b99u97wV+f6F1b3AAAAAAAAA8Gw8MBQAAB/St29fBQcHKzk5ucjxzZs36+DBg3rkkUdks9n00UcfKTg4WImJiWrQoIFCQ0M1YMAA9ejRQ4sWLapwHE8++aQiIiK0ZMkStWrVSmFhYbr33nv10ksvaevWrUpJSbH7vjp16sgYU+ZfdHR0hWM8dOiQGjZsqKSkJHXo0EEhISGKiIjQgAEDdOzYsVLfe+bMGVWrVk2TJk1S27ZtFRISogYNGmjkyJHKysoqbDdx4kQFBwcrISFBx44d04ULF/T5559rxowZio+P1y233FLhzwEAqFzUUmsiIiLUokULpaam6sKFC0Ve27BhgyTpp59+KvH9Vmtkeev1yZMnNX36dM2dO1cTJ07ky0yAG+D+at/Jkyc1a9YstWvXTl27dq3w5/utF198UcHBwRo7dmyltJOcHzMAAI6gj2GflXpd0XGTvWuUdz6UMZzvIGfts5dPVtchKsLqvEtVxAIAcBx11T57dbUiewOs9nHZGwDAl1GTinPlXAf72gAAAAC4C8aLxZU0XqzIHOZvlbQX0Nl7t+HZyNfL3nvvPS1ZskSvvvqq6tatW+z1kydPFl7vt/z8/BQREVHY5rcq8v0LR/b4AgAAAAAAwHPxwFAAAHxIjRo19Mc//lGfffaZzp49W3j8/fffl81mU0JCgiQpMTFROTk5uu6664q8PyoqStnZ2Tp9+nS5Yzh79qxSU1N1xx13FPtFydjYWEnSli1byn3+ynDp0iWdP39eX331lRYuXKhFixYpIyNDycnJSk1NVadOnXTmzJkS319QUKC8vDyFhoZq1apVSk9P15w5c7RkyRJ17NhROTk5ki7/AufSpUu1adMmNW7cWEFBQYqNjdVtt92mBQsWVNXHBQA4gFpqXWJioo4dO6aBAwfqwIEDys7O1qJFizRv3jxJ0sWLF0t8r5UaWZ56vX//ftlsNkVGRmry5MmaOnWqJk6c6Lx/BACWcX8tLisrS3369FF2draSkpLk7+9fqef/8ccf9fbbb2vUqFGqVatWhdtVRcwAADiKPkZxZdXryhg3lXQNR+dDGcP5HnK2uJLyyeo6RHk5Mu/i7FgAAOVDXS3OXl2t6N4Aq31c9gYA8GXUpF+5w1wH+9oAAAAAuAvGi78qbbxY0TnMq5W2F9BZe7fhHchX6fjx4xo1apTuv/9+xcfH221z/vx5SVJgYKDd1wMDA3Xu3LkSr1Ge7184sscXAAAAAAAAno0HhgIA4GMSEhKUl5en5cuXS7q8YJuSkqIePXooKipKkpSbm6sZM2aoa9euql+/voKCghQQEKCFCxcWvqe8Tpw4oYKCAr377ruy2WxF/ho2bChJOnr0aAU/ZcX4+fnJz89P2dnZWrp0qa6//nqFhYWpZ8+eev3113XixAnNmDGjxPdv2rRJGRkZevrppxUZGakaNWooLi5O8+bN08GDBzVt2jRJ0jvvvKOYmBg9+uijOnz4sPLy8gp/XbFjx47KyMioqo8MAHAAtdSa+++/XytXrtT333+vNm3aqFmzZvr000+1ZMkSSVJ4eHiJ77VSI8tTr1u0aCFjjLKyspSUlKRZs2apc+fOFdp8BKDycH/91YEDB9SlSxelpaXpk08+0U033VTp10hKSlJ+fr6GDh1aKe2qImYAAMqDPsavrNTrio6bSruGo/OhjOF8Ezn7q9Lyyeo6RHk5Mu/i7FgAAOVHXf1VSXW1onsDrPZx2RsAwNdRky5zh7kO9rUBAAAAcCeMFy8rbbxY0TnMq5W2F9BZe7fhPXw9XwcPHixJhQ/vtKd69eqSpAsXLth9PS8vr7CNPeX5/oXVPb4AAAAAAADwfDwwFAAAHxMTE6Nrr71WKSkpkqSvvvpKJ0+e1KBBgwrbxMfHa/z48erVq5c2bNigrKws5ebm6tFHH620OIYMGSJjjN2/pUuXVtp1ysNms6lu3bpq3rx5sV/X69Gjh2w2m3bu3OnweWNjY2Wz2bRlyxbl5+drxIgR6tatm6ZOnaomTZooMDBQnTp10qJFi/T9998rMTGxsj4SAKASUUut6927t3bu3Km8vDxlZmYqOTlZfn6XpyKaNWtm9z1Wa2RF6nWtWrX0wAMP6KOPPtL27ds1derUyv3gAMqF++tlGzduVOfOnXXhwgVt2LBBt99+u1Ou8+GHH6pjx45q2rRphdtVVcwAAJQHfYzLHK3X5Rk3lXaNisyHMobzLeTsZeXtY1+9DlERlbFOUlmxAADKj7p6WWl1tSI1z2ofl70BAEBN+i13nOtgXxsAAAAAV2C8WJS98WJlfr+ppL2AVbF3G57Pl/P1rbfe0ueff67XX39dkZGRJbarX7++JNn9oZX8/HxlZWUVPty0JI5+/8LqXmAAAAAAAAB4Ph4YCgCAjwkICFD//v31n//8R2fOnNEHH3ygsLAwxcXFSbr8i3sff/yx4uPjNWnSJDVv3lyhoaEKCAjQkSNHSj23v7+/3V/7O3nyZOF/N2rUSH5+fmWey55Tp04V+xVAe39paWkOn/u3OnTooJ9++qnY8fz8fBljFBgYaPd9Fy5c0I4dO/TDDz8Uey0vL0/GGAUHB+vIkSPKyclR69ati7Vr1aqVJGnv3r0V/BQAAGegllbMxo0bJUndunWz+7ojNdJKvf7xxx81ePBgJSUlFWvXpk0bSdKePXvK92EAVCrur9LmzZsVExOjqKgobdmyRe3atXM4FisOHjyoXbt26a677qpwu6qKGQCA8qKPUXa9roxxU1nXsDrWYwwHcrbsfLK6DlFRVuZdqioWAED5UFetzV2Vd2+A1T4uewMAwLdrkjvNdbCvDQAAAIC7YbxobbxY3jnMq5W2F7Cy927DO/lyvn7zzTeSLj8Q9er2w4cPlyS1b99eNptN1157rSIjI/Xdd98VO8fevXuVn5+vjh07Ohx/Sd+/sLoXGAAAAAAAAN6BB4YCAOCDEhISdPHiRa1YsULLly9XXFycQkNDJV3e/CtJderUKfKevXv3au3atZIkY4zd89arV6/w1/+utmrVqsL/DgsLU/fu3bVmzRqlp6cXabd+/Xq1adNG27Zts3v+OnXqlPgrgFf/RUdHO/CvYV///v2VlZWlL774osjx1atXSyr5IWd5eXnq1q2bhg4dWuy1lStXSpLuvPNORUZGKigoSN9++22xdleO8et+AOC+qKVlGzt2rFq2bKmLFy8WHisoKNCCBQvUunVrde3a1e77HKmRVup13bp1tXjxYs2ePVsFBQVF2u3YsUOS1Lx58/J9SACVzpfvr4cPH1bv3r3VqlUrrVq1Stdee22JbSsqNTVVknTjjTdWqF1VxgwAQEXQxyi9Xld03GTlGlbHeozhIJGzZeWT1XWIirIy71JVsQAAyo+6WvbcVXn3Bljt47I3AAAu89Wa5E5zHexrAwAAAOCOGC+WPV4s7xzm1UrbC1jZe7fhvXw1X2fNmmW3/bx58yRJu3fvljFGAQEBevjhh7V27VplZGQUOUdycrICAgL00EMP2b2G5Pj3L6zuBQYAAAAAAIB34IGhAAD4oA4dOqht27aaPHmyTp8+rUGDBhW+1qRJEzVr1kzLli3Tt99+q9zcXK1cuVIPPvig+vbtK0n6+uuv7f5yX+/evVVQUKDJkycrOztb6enpGjdunLKzs4u0mzZtmvz9/XXvvfcqLS1Nubm5WrNmjRISEhQUFKR27do59fNb8fDDD6tHjx4aNGiQ1q9fr3Pnzmn16tUaNWqUWrRooSFDhkiSvvzyS9lsNo0fP16SFB4ersmTJ2vt2rUaO3asjh07puzsbKWkpGjMmDG64YYb9Nhjjyk0NFTjx4/XunXrNGHCBB09elTnzp3T5s2bNWzYMNWsWVOjR4925T8BAKAU1NKyxcbG6uDBgxoxYoQyMzOVnp6uYcOG6dtvv9Ubb7whm80mqXgtdaRGWqnXISEhmj59unbs2KGhQ4fq8OHDOnfunNatW6chQ4aoZs2aeuKJJ1z27wSgKF++v44cOVK5ublasmSJwsPDK3y+395fr7Zv3z5JUrNmzUo9R1ntKjtmAACchT5G6fXakXGTvT6GlWtYHesxhoNEzpaVT1bXIaTSxwVlsTLv4kgsAADXoK6WPXdV3r0BVvu47A0AgMt8tSY5Y66jvGM99rUBAAAAcEeMF8seL5Z3DvNqpe0FrOy92/BevpqvjpgwYYLq1Kmj+Ph47d+/X7m5uVq8eLGmT5+uZ599Vtddd50k+/lq9fsXV1jdCwwAAAAAAADvEODqAAAAgGsMHDhQf/3rXxUVFaXbbrut8Lifn5+WLl2q0aNHq0uXLgoICFCXLl2UnJyssLAw7dy5U3369NEzzzxT7JwJCQk6fPiwkpKSNHPmTDVo0EDDhg3TP/7xDz3wwAOFvxbYqVMnpaam6u9//7u6du2qs2fPKjIyUvHx8ZowYYKCg4Od9rnHjx+vV155pcixp556Sk899ZQkacCAAXr33Xfl7++vlStX6u9//7sGDhyoEydOqE6dOrr33nv14osvlvqFoqeeekpRUVGaPXu2brrpJp09e1ZNmzbV0KFD9X//93+qXr26JOnFF19Uy5YttWDBAr366qs6f/686tWrpzvvvFMpKSlq0aKF0/4dfM2mTZtcHQLg0cgh+6ilv7JXS2NiYrR06VK99NJLatq0qfz8/HTrrbdqw4YN+v3vf1/qNazWSKv1evjw4apXr55mz56tG264QRcuXFDjxo3VqVMnTZw4kU0ygJvxxfvruXPn9O9//1tSyRv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15XBfqnpyuRwhISHIzs7GW2+9hbCwMLi5uSEuLk50GhERERERERGRxeHAUCIioipSVlYGjUYDJycn7NixA1999RVOnDiBnj17ik6r8WQyGSoqKkRnEBGRCVy9ehVKpRL9+/dHmzZtcO7cOWg0GjRo0EB0Wo3BgaFEZM6MRiPeeustJCYmYvv27bCxsRGdVKP4+flh7ty5UKlUSEpKEp1DRES1gF6vR0REBLy8vKBQKJCcnIywsDDIZDLRaTWGQqFAmzZtkJeXJzqFiMhkunbtiqNHj2L9+vXYu3cvHB0dodFoeC2JiIhqtV69euHMmTOYM2cOPvnkE/j6+iIzM1N0FhER0RPZ29tj+/bt2Lp1K06dOlX5+a68vFx0GhERERGRxfnll1+gUqng6uqKa9eu4dChQ0hISECHDh1Ep9VYDwaGWltbCy4hosdRKBSVr1WqPk2bNkV4eDhSU1Ph5uaG4OBg+Pv749y5c6LTiIiIiIiIiIgsBgeGEhERVYGEhAQ4Ozvjgw8+wLRp05CZmQmlUgmJRCI6rVaQSqUwGAyiM4iIqBrp9frKwdzHjh3D1q1bsXfvXjg5OYlOq3E4MJSIzNns2bOxceNGbNq0CR4eHqJzaqSFCxeiT58+GDVqFAoLC0XnEBFRDXbixAl4eHhg4cKFWLhwIQ4fPszPeNXEzs4O+fn5ojOIiExKIpFAqVQiJycHM2fORFhYGLp164YjR46ITiMiIhLG2toaarUap06dgl6vR5cuXTB37lyUlZWJTiMiInqiwMBAZGRk4O9//3vl57sff/xRdBYRERERkUXQ6/WIjo6Go6Mj4uLisHr1apw8eRJ9+vQRnVbjlZaWAvhtICERmSdra+vK1ypVPwcHB8TGxuL48eMoLi5G165doVQqcf36ddFpRERERERERERmjwNDiYiI/oTk5GT069cPQUFBePXVV5GRkYHw8HA0aNBAdFqtIpPJUFFRITqDiIiqycGDB+Hp6Yl58+Zh1qxZSEtLw9ChQ0Vn1VgcGEpE5ioyMhKfffYZ1q1bB39/f9E5NZZUKsWGDRtQXl6OiRMnwmg0ik4iIqIa5v79+5g7dy569+6N9u3bIyMjA2FhYZBKedmyutjZ2SEvL090BhGREPXr14darUZqairatm2LPn36IDAwEBcvXhSdRkREJIy7uzuOHTuGTz/9FKtWrUK3bt1w8uRJ0VlERERPVLduXajVaqSlpeGll16Cr68vlEolbty4ITqNiIiIiMhs7du3D56enpgxYwbGjx+PrKwshISEQCaTiU6rFXQ6HYDfBhISkXmytraufK2S6fTo0QM//vgjNm7ciCNHjqBjx45Qq9W4f/++6DQiIiIiIiIiIrPFlXdEREQvoLCwECqVCl5eXigpKcHRo0cRGxsLGxsb0Wm1klQqhcFgEJ1BRERV7MqVK1AqlRgwYADs7OyQnp4OtVrNm6aqGQeGEpE5iomJwYwZM7B8+XJMmDBBdE6N16pVK8TFxWH37t349NNPRecQEVENcvToUXh4eOCLL75AZGQkdu7cye9UTcDW1hb5+fmiM4iIhHJwcMC2bduwd+9e5ObmonPnzlCr1Vz8RUREtZaVlRVUKhVSUlLQunVr9OrVCyqVCr/++qvoNCIioifq2LEjdu7cifj4eBw6dAiOjo7QaDTccJyIiIiI6H9kZWVhyJAh8Pf3h52dHbKysqDRaNCoUSPRabVKaWkpAEChUAguIaLHUSgUla9VMi2JRIIxY8YgIyMDH3/8MT777DM4ODggOjqa60SJiIiIiIiIiB6BA0OJiIieg16vh0ajgb29PTZv3ozIyEicOHECPj4+otNqNZlMxht+iYhqkAfvt05OTjh+/Di2b9+OhIQE2NnZiU6rFTgwlIjMzQ8//IC//vWvmDp1KmbNmiU6p9bo2bMn/vGPf+DDDz/E4cOHRecQEZGFu3fvHlQqFfr27QsHBwekpaUhJCQEEolEdFqtYGtri7y8PNEZRERmwc/PD+fOncOSJUuwYsUKuLq6Ii4uTnQWERGRMB06dMCePXuwbt06bNiwAV26dMG+fftEZxERET1VYGAgMjMzoVKp8P7778PLywvHjx8XnUVEREREJFRhYSFUKhXc3NxQUFCAw4cP8x5sgXQ6HWQyGaysrESnENFjWFtbo7y8nOsSBapbty7CwsKQm5uLUaNG4e2330b37t1x6NAh0WlERERERERERGaFA0OJiIieUUJCApydnfHBBx9g6tSpyMzMREhICKRSvp2KJpVKuXMcEVENsX//fnTp0gUffPAB3nvvPaSlpWHw4MGis2oVDgwlInOSlpaGESNGYPjw4fjXv/4lOqfWmT17NoYNG4bg4GBcu3ZNdA4REVmoXbt2wc3NDd988w3WrFmDbdu2oV27dqKzahU7OzsUFxfj5s2bolOIiMyCXC6HSqVCVlYWfHx8MHbsWPj5+SE9PV10GhERkRASiQRKpRLp6enw9PTEX/7yFyiVShQWFopOIyIieqJ69epBrVYjNTUVLVu2RK9evaBUKvk9GBERERHVOnq9HhqNBvb29ti0aRNWr16NkydPwtfXV3RarVZaWgpra2vRGUT0BAqFAsBvA35JrBYtWkCj0SA1NRVt2rRBv379EBgYiJycHNFpRERERERERERmgRPOiIiIniIzMxMBAQEICgpC165dkZ6ejvDwcDRs2FB0Gv0fmUzGnfyIiCzczz//DKVSCT8/P9jb2yMjIwNqtbryBgwyHQ4MJSJzceXKFQwePBhdunTB119/zc0aBJBIJFi3bh0aNGiA8ePH83MXERE9lzt37iA0NBQBAQHw9vZGdnY2QkJCRGfVSnZ2dgCAvLw8wSVERObl5ZdfhlarxYkTJ1BUVARPT0+oVCrcvXtXdBoREZEQbdq0waZNmxAfH48DBw7A1dUVmzZtEp1FRET0VJ06dcLu3bsRHx+PH374AY6OjtBoNNyEnIiIiIhqhYSEBDg7O2PevHmYOnUqsrKyEBISwvvtzIBOp+PAUCIz9+A1WlpaKriEHnB2dsa2bduwd+9eXLp0CZ07d0ZoaCg3iCEiIiIiIiKiWo/f+hMRET1GYWEhVCoV3NzccPPmTRw+fBixsbGwtbUVnUa/I5VKeXMvEZGFun//PtRqNRwcHJCYmIidO3ciISEBNjY2otNqLQ4MJSJzcPfuXQwePBiNGjXC999/zwHSAjVp0gRbtmxBYmIi5s+fLzqHiIgsREJCAlxdXbF161Zs3rwZsbGxaNmypeisWqt9+/awsrJCfn6+6BQiIrPUvXt3HD9+HGvXrsXGjRthb2/PwTJERFSrBQYGIi0tDcOGDUNwcDACAwNx5coV0VlERERPFRgYiMzMTMycORPvv/8+unfvjsTERNFZRERERETVIjMzEwEBAQgKCkLXrl2RkZGB8PBwNGzYUHQa/Z/S0lLe+0hk5h68RnU6neAS+j0/Pz8kJydj7dq1iI+Ph6OjIyIiIjjclYiIiIiIiIhqLQ4MJSIi+h29Xg+NRgN7e3ts2rQJkZGROHnyJHr37i06jR5DJpOhoqJCdAYRET2nhIQEuLi4YPny5QgLC0NKSgoGDRokOqvW48BQIhJNp9Nh6NChKCwsxM6dO9G0aVPRSbWeu7s7Pv/8cyxZsgTx8fGic4iIyIwVFBQgODgYw4YNg4+PD9LT0zFy5EjRWbWelZUV2rZti7y8PNEpRERmSyqVQqlUIisrC2+88QZmz55dOUiUiIioNmrSpAmioqJw8OBBZGdnw9XVFdHR0TAajaLTiIiInqh+/fpQq9VISUlB06ZN4ePjA6VSiVu3bolOIyIiIiKqEoWFhVCpVHBzc8OtW7dw+PBhxMbGwtbWVnQa/Y5Op4O1tbXoDCJ6ggevUQ4MNU8PruPn5uZi5syZWLBgAdzc3BAXF8frFURERERERERU63BgKBER0f/Yt28fPDw8MG/ePEydOhVZWVkICQmBVMq3THMmlUo5MJSIyILk5ORg6NChGDZsGFxcXJCRkQG1Ws0dlM0EB4YSkUgGgwFvvvkmUlNTsWPHDrRv3150Ev2fkJAQKJVKTJo0icPGiIjokeLi4uDq6opTp05hz549iI2NRbNmzURn0f+xs7NDfn6+6AwiIrPXtGlTaDQapKamonnz5ujVqxeUSiUKCgpEpxEREQnRt29fnD17FqGhoXj77bfRr18/nD9/XnQWERHRUzk6OmLPnj1Yv3499uzZA0dHR2g0GhgMBtFpREREREQvpKysDBqNBvb29ti8eTMiIyORmJiI3r17i06jx9DpdLw/nsjMPXiNlpaWCi6hJ3mwQcz58+fRv39/jBs3Dj4+PtwAlIiIiIiIiIhqFU4/IyIiApCVlYUhQ4bA398fHTp0QHp6OsLDw9GwYUPRafQMZDIZb+QlIrIAJSUlUKvVcHNzQ05ODvbs2YOEhAS88sorotPof3BgKBGJ9O6772L79u1ISEiAu7u76Bz6nTVr1sDGxgZjx47lzZFERFTp2rVrGDFiBMaOHYuRI0ciJSUF/v7+orPod2xtbTn0m4joOTg5OWH37t2Ij4/HkSNHYG9vD7VajbKyMtFpREREJlevXj2Eh4fj1KlTKCoqgoeHByIiIrixKxERmT2JRAKlUomsrCy8+eabeO+999CjRw+cOnVKdBoRERER0XNJSEiAs7MzPvjgA0ydOhVZWVkICQmBVMrlweastLQU1tbWojOI6AkevEZ1Op3gEnoW7dq1Q1RUFBITEyGXy9GrVy8EBwdzE2UiIiIiIiIiqhV4RYCIiGq1X375BSqVCm5ubrh+/ToOHz6MhIQE2NnZiU6j5yCTybgQhYjIzCUkJMDFxQXLly9HWFgYB8iYMQ4MJSJRlixZglWrVmHDhg3w9fUVnUOPULduXcTGxiI7OxuzZ88WnUNERIIZjUZotVq4uLggNTUV+/fvR1RUFDdhMlN2dna8OZ6I6AUEBgYiPT0ds2fPRkREBNzc3LBjxw7RWUREREJ4enoiMTER8+fPx/z58+Hl5YUzZ86IziIiInqqJk2aQKPR4PTp05DL5fDx8YFKpcLdu3dFpxERERERPdGZM2fQr18/BAUF4dVXX0VGRgbCw8PRoEED0Wn0DEpLS6FQKERnENETPHiNlpaWCi6h59GtWzccPnwY8fHxOHPmDDp37oy5c+fi3r17otOIiIiIiIiIiKoNB4YSEVGtpNfrER0dDUdHR8TFxWH16tU4efIkh9JYKKlUCoPBIDqDiIge4aeffsLgwYMRFBQEX19f5OTkQK1Wo06dOqLT6DE4MJSIRPjuu+/w0Ucf4bPPPsOoUaNE59ATODg44Msvv6wc7kpERLVTXl4e/P39MWXKFEyYMAHnzp1D//79RWfRE9ja2uLixYv8HpWI6AXUq1cParUaP/30E7y9vTFkyBAEBgbiwoULotOIiIhMTi6XIywsDElJSVAoFOjRowfmzp3LxdRERGQRPDw8cPToUaxbtw4bN26Ek5MTtFotjEaj6DQiIiIioodcu3YNoaGh6N69O0pKSnD06FHExsbCxsZGdBo9B51OB2tra9EZRPQED16jOp1OcAm9iMDAQGRmZmLp0qWIioqCvb09NBoNKioqRKcREREREREREVU5DgwlIqJaZ9++ffD09MSMGTMwfvx4ZGVlISQkBDKZTHQavSCZTMYLOUREZqakpARqtRpubm64evUqDh8+DK1WizZt2ohOo6fgwFAiMrUDBw5g0qRJmDt3LmbOnCk6h55BcHAwpk+fjmnTpiEjI0N0DhERmZDBYEB0dDTc3d1RUFCAY8eOQaPRoH79+qLT6Cns7Oyg0+lw/fp10SlERBarXbt20Gq12L9/P/Lz8+Hs7AyVSoWioiLRaURERCbn4uKCY8eOYdWqVYiMjISbmxsOHTokOouIiOipJBIJlEolsrKyEBwcjMmTJ6Nfv35IS0sTnUZEREREhLKyMmg0Gjg5OWHHjh346quvkJiYCB8fH9Fp9AJKS0uhUChEZxDREzx4jXJTLMsll8uhUqmQm5uLKVOmICwsDG5ubti+fbvoNCIiIiIiIiKiKsWBoUREVGtkZ2dj6NCh8Pf3h52dHTIzM6HRaNCoUSPRafQnSaVSGAwG0RlERPR/EhIS4OzsDI1Gg4iICCQlJaF3796is+gZcWAoEZlSUlISgoKCMHr0aPzjH/8QnUPPYcWKFXB3d8fIkSM5HIeIqJbIycnBgAEDMH36dLzzzjtISkqCl5eX6Cx6RnZ2dgCAvLw8wSVERJZvwIABSE5OxrJly/D111/D2dkZWq0WRqNRdBoREZFJSSQShISEICUlBR06dED//v0RGhrK7wuJiMgiNG3aFBqNBidPnkRZWRk8PT2hUqlw79490WlEREREVEslJCTAyckJH3zwAd59912cP38eSqUSEolEdBq9IJ1OB2tra9EZRPQED16jOp1OcAn9Wc2aNUN4eDhSUlLg6upauY44JSVFdBoRERERERERUZXgwFAiIqrxbt++jblz58Ld3R1Xr17FoUOHkJCQgA4dOohOoyoik8lgMBi4EJOISLDs7GwMGjQIQUFB6Nu3L7Kzs6FSqSCTyUSn0XPQ6/WQSCSwsrISnUJENVxeXh6GDh2K7t27Y/369byx2cLI5XJs3LgRhYWFCA0NFZ1DRETVqLy8HBEREXB1dcXdu3eRmJiI8PBw1KlTR3QaPYeXX34ZCoUC+fn5olOIiGoEKysrqFQq5ObmYtSoUZg8eTL69++Pc+fOiU4jIiIyOVtbW+zatQsxMTHYsmUL3N3dsXv3btFZREREz6Rr1644duwY1q1bh++++w5OTk7QarWis4iIiIioFklKSkKfPn0QFBSEbt26ITMzE2q1GnXr1hWdRn9SaWkpB4YSmbk6depAIpGgtLRUdApVkU6dOiE2NhYHDhxAYWEhPD09oVQqUVBQIDqNiIiIiIiIiOhP4cBQIiKqscrLyxEdHQ1HR0esXbsWy5Ytw6lTp9CnTx/RaVTFpNLffqUxGAyCS4iIaqfi4mKo1Wq4u7vjxo0bOHr0KLRaLVq1aiU6jV6AXq/nsFAiqna3bt1CQEAA2rZti/j4eA4cs1Dt27eHVqtFTEwMoqOjRecQEVE1SElJQc+ePaFWq7FgwQKcPn0anp6eorPoBUilUrRv3x55eXmiU4iIapTmzZtDo9Hg5MmT0Ov16Nq1K5RKJW7evCk6jYiIyOTGjBmDtLQ0+Pr6YtCgQQgODsatW7dEZxERET2VRCKBUqlEdnY2xowZg0mTJqF///5IT08XnUZERERENdjVq1cRGhoKb29vlJWV4ccff0RsbCxeeeUV0WlURXQ6HRQKhegMInoCiUSCOnXqQKfTiU6hKta/f38kJSVh48aNOHz4MOzt7aFWq3H//n3RaUREREREREREL4QDQ4mIqEbat28fPD09MX36dLz++uvIzc2FSqWCTCYTnUbV4MG/KweGEhGZXkJCApydnbFy5crK4dw+Pj6is+hP0Ov1kMvlojOIqAa7f/8+goKCUFZWhm3btqFBgwaik+hPCAgIwLx58zBz5kwkJSWJziEioiqi1+sREREBLy8vKBQKJCcnIywsjN+vWjg7Ozvk5+eLziAiqpG6du2Ko0ePYv369di7dy8cHR2h0WhQUVEhOo2IiMikWrduDa1Wi23btuHEiRNwcXGBVqsVnUVERPRMmjVrVrkpRElJCTw9PaFSqVBUVCQ6jYiIiIhqkPv37yMiIgJOTk7YuXMnvvrqKxw/fhw9e/YUnUZVrLS0FNbW1qIziOgprK2tUVpaKjqDqoFEIsGYMWOQkZGBjz/+GCtWrECnTp0QHR3NdahEREREREREZHE4MJSIiGqU8+fPIzg4GP7+/rC1tUVmZiY0Gg0aN24sOo2qkVT62680XHRJRGQ6586dQ58+fTB8+HD069cP2dnZHM5dQ3BgKBFVp4qKCowfPx7nz5/Hzp070aZNG9FJVAUWLlyIPn36YNSoUSgsLBSdQ0REf9KJEyfg4eGBhQsXYuHChTh8+DCcnJxEZ1EVsLW1RV5enugMIqIaSyKRQKlUIicnBzNnzkRYWBi6deuGI0eOiE4jIiIyuSFDhiA1NRXjxo3DpEmTMHToUFy+fFl0FhER0TN59dVXcfz4caxduxbffvstnJ2dOQCbiIiIiKpEQkICOnfujEWLFmHWrFk4f/48lEolJBKJ6DSqBjqdDgqFQnQGET2FtbU1dDqd6AyqRvXq1UNYWBiysrIwePBgvP322/D29ua1fCIiIiIiIiKyKBwYSkRENcLt27cxd+5cuLu7Iy0tDTt37kRCQgLs7e1Fp5EJPBhOx53diIiq3507d6BSqdCtWzeUlJTgxx9/hFarRcuWLUWnURXhwFAiqk4zZ87E7t27ER8fD0dHR9E5VEWkUik2bNiA8vJyTJw4EUajUXQSERG9gPv372Pu3Lno3bs32rdvj4yMDISFhVVu1kOWz87ODvn5+aIziIhqvPr160OtViM1NRVt27ZFnz59EBgYiIsXL4pOIyIiMqnGjRtDo9Hg0KFDyM3NhaurKzQaDe/tICIiiyCVSqFUKpGdnY0hQ4Zg4sSJGDhwIDIzM0WnEREREZEFOn36NHx9fTF8+HD4+voiJycHarUa1tbWotOoGul0Ov4bE1kAhUKB0tJS0RlkAi+//DKioqKQkpKCVq1aVV7Lz83NFZ1GRERERERERPRUXOFHREQWzWAwQKvVwsnJCWvXrkVERARSU1MxaNAg0WlkQg+GFlRUVAguISKquYxGY+V77oYNG7B8+XKcPHkSPXr0EJ1GVYwDQ4mousyfPx9RUVH47rvv4OPjIzqHqlirVq0QFxeH3bt3Y/ny5aJziIjoOR09ehQeHh744osvEBkZiZ07d8LGxkZ0FlUxW1tbXLp0CeXl5aJTiIhqBQcHB2zbtg179+5Fbm4uOnfuDLVaDZ1OJzqNiIjIpHr37o0zZ87g3XffxZw5c9C3b19kZWWJziIiInomzZs3R1RUFA4dOoRbt26hS5cuUKlU+PXXX0WnEREREZEFuHLlCkJDQ+Ht7Y3y8nL8+OOP0Gq1aNOmjeg0MoHS0lIoFArRGUT0FNbW1ryGW8t07twZ27dvx969e5Gfnw9nZ2eoVCrcuXNHdBoRERERERER0WNxYCgREVmsAwcOwNPTE2+99RbGjRuH3NxcqFQqyGQy0WlkYg/+zQ0Gg+ASIqKaKTk5Gb6+vpg0aRL+8pe/IDs7GyqVqnJgM9UsZWVlHBhKRFVu7dq1WLhwITQaDYYPHy46h6pJz549sXjxYnzwwQc4fPiw6BwiInoG9+7dg0qlQt++feHg4IC0tDSEhIRAIpGITqNqYGdnh/Lycly5ckV0ChFRreLn54dz585hyZIlWLFiBVxdXREXFyc6i4iIyKTq1q0LtVqNU6dOQafTwdPTE2q1GmVlZaLTiIiInomvry+SkpLw6aef4t///jecnZ2h1WpFZxERERGRmSopKUFERAScnZ2xc+dOrF+/HseOHUOPHj1Ep5EJ6XQ6DgwlsgAKhQKlpaWiM0gAPz8/JCcnY9WqVYiJiYG9vT0iIiL480BEREREREREZonTXYiIyOL89NNPCA4OxsCBA9GqVSucPXsWGo0GjRs3Fp1GgjwYWFdRUSG4hIioZrl9+zZUKhW8vLxQVlaG48ePQ6vVokWLFqLTqBrp9XoODCWiKrV9+3ZMmzYNarUa77zzjugcqmZz5szBsGHDEBwcjGvXronOISKiJ9i1axfc3NzwzTffYM2aNdi2bRvatWsnOouqka2tLQAgPz9faAcRUW0kl8uhUqmQlZUFHx8fjB07Fn5+fkhPTxedRkREZFJdunTB8ePHER4ejuXLl8PLywunT58WnUVERPRMrKysKj/b9e/fHxMnTkRgYCDy8vJEpxERERGRmTAajYiLi0Pnzp2xaNEizJo1C+fPn4dSqeTGnbVQaWkprK2tRWcQ0VNYW1tzQGQtZmVlhZCQEOTk5GDGjBlQq9Vwd3fnJqBEREREREREZHY4MJSIiCzGnTt3MHfuXLi5uSE1NRU7duzA3r170blzZ9FpJJhMJgPAgaFERFXFfxBoywAAIABJREFUaDRCq9XCyckJsbGxiIyMxIkTJ9C9e3fRaWQCHBhKRFXp1KlTGDt2LCZOnIj58+eLziETkEgkWLduHRo0aIDx48fzcxoRkRm6c+cOQkNDERAQAG9vb2RnZyMkJER0FplA69atUa9ePQ4wICIS6OWXX4ZWq8WJEydQVFQET09PqFQq3L17V3QaERGRyTwYtnbu3Dm0aNECPXv2hEqlQnFxseg0IiKiZ/LSSy9Bq9Xi4MGDyM/Ph4uLC9RqNXQ6neg0IiIiIhLo1KlT8PX1xbhx49CnTx/k5uZCrVZzYGQtptPpoFAoRGcQ0VMoFAp+pic0aNAAarUa58+fh7e3N8aOHYsBAwYgOTlZdBoREREREREREQAODCUiIgtgMBgqh5Z9+eWXiIiIQGpqKgICAkSnkWB37tzB7du3UVJSAgC4ffs2bt++jcLCQly4cAEXLlyA0WgUXElEZFnOnDmDXr16YcqUKRg3bhyysrIQEhICqZQfH2sLDgwloqqSm5uLoUOHol+/flizZo3oHDKhJk2aYMuWLUhMTOSgWCIiM5OQkABXV1ds3boVmzdvRmxsLFq2bCk6i0xEIpHAxsYG+fn5olOIapXy8vLK6xcPHg+GYf3++Tt37giuJVPp3r07jh8/jrVr12Ljxo2wt7eHRqOBwWAQnUZERGQy9vb22LdvH1avXo1///vf6NKlCw4cOCA6i4iI6Jn17dsXZ86cwdKlS7FixQq4urpix44dorOIiIiIyMSuXLkCpVIJb29v1KlTB2fOnIFWq0Xr1q1Fp5EJpaenIykpCT/99BMuXLiA69evQ6fTQSKRiE4joqewtrZGaWmp6AwyE+3bt4dWq0ViYiL0ej1effVVBAcH4+LFi6LTiIiIiIiIiKiW48QXIiIyawcPHkTXrl3x1ltvISgoCNnZ2VCpVLCyshKdRoIUFxejQYMGkEgkaNq0KZo1a4ahQ4cCABwdHdGsWTO0aNEC9vb2CAoK4sV1IqJn9Msvv0ClUqF79+6Qy+U4c+YMNBoNGjduLDqNTIwDQ4moKty8eRMBAQGwsbFBTEwMP8PVQu7u7vjss8+wZMkSxMfHi84hIqr1CgoKEBwcjGHDhsHHxwfp6ekYOXKk6CwSwM7ODnl5eaIziGqVX375Ba1atUKzZs0qH5MnTwaAh55r1qwZRo8eLbiWTEkqlUKpVCIrKwtvvPEGZs+eXTlIlIiIqLaQSCQICQlBVlYWunTpAj8/PyiVSvzyyy+i04iIiJ6JXC6HSqVCVlYWfHx8MGTIEAQGBnLTHiIiIqJaoKSkBBEREXBycsLx48cRExODAwcOoEuXLqLTSIDFixejW7du6NSpE+zt7fHSSy/h3r17mDFjBiQSCSQSCRo2bIimTZsiJydHdC4R/Q+FQgGdTic6g8yMl5cXjhw5gvj4eCQlJaFz586YO3cuioqKRKcRERERERERUS3FgaFERGSWcnJyEBwcjAEDBqBly5ZITk5GVFQUWrRoITqNBKtfvz6GDx8OqfTJv8ZIpVKMHTvWRFVERJbLYDBAq9XC0dERcXFx+Oqrr/DDDz/Azc1NdBoJwoGhRPRnFRUVYdCgQTAYDNi2bRvq168vOokECQ0NhVKpxKRJkziYjIhIoLi4OLi6uuLUqVPYs2cPYmNj0axZM9FZJIitrS3fl4lMrFWrVujbt+9Tr2sAwOuvv26CIjI3TZs2hUajQWpqKpo3b45evXpBqVSioKBAdBoREZHJvPTSS9i8eTNiYmKwe/duuLq6YsuWLaKziIiIntnLL78MrVaLAwcO4MKFC3BxcYFarUZpaanoNCIiIiKqYkajEXFxcXB2dsbixYvx3nvvIS0tDWPGjBGdRgINHz78qecUFxejQ4cO6NixowmKiOhZWVtbc2AoPVZgYCAyMzOxZMkSfPHFF3ByckJ0dDQqKipEpxERERERERFRLcOBoUREZDLbt2+HXq9/4jnFxcVQq9Vwc3NDSkoKtm3bhr1798LFxcVElWQJJkyYAIPB8MRzDAYDB4YSET3F6dOn0bNnT7z11lsYP348srKyoFQqIZFIRKeRQBwYSkR/hl6vx5gxY3D58mXs3LkTrVq1Ep1Egq1ZswY2NjYYO3YsF0QSEZnYtWvXMGLECIwdOxYjR45ESkoK/P39RWeRYHZ2dsjPzxedQVTrTJgw4annWFlZYcSIESaoIXPl5OSE3bt3Iz4+HkeOHEHHjh2hVqtRVlb2xL/33//+Fzdu3DBRJRERUfUaM2YMsrKyEBgYiFGjRiEwMBBXr14VnUVERPTM+vfvj7Nnz2LJkiX45z//CTc3N+zatUt0FhERERFVkZMnT6JXr14YN24c+vbti5ycHKjVaigUCtFpJNiQIUOeev+1VCpFaGioiYqI6FkpFAre30pPVKdOHahUKuTm5mLChAmYMWMG3N3dsWPHjqf+3Tt37iA9Pd0ElURERERERERU03FgKBERmcSBAwcwfPhwrFmz5pHHDQYDtFot7O3tsXLlSqjVaqSkpGDIkCEmLiVL4O/vj5YtWz72uEQigZubGxwcHExYRURkOQoLC6FSqeDt7Y169eohOTkZGo0GjRo1Ep1GZoADQ4noRRmNRvztb3/DsWPHsGvXLv4+TgCAunXrIjY2FtnZ2Zg9e7boHCKiWsFoNEKr1cLFxQWpqanYv38/oqKi0LBhQ9FpZAZsbW1x5coVLnQgMrGRI0fCysrqscetrKwQEBCAZs2ambCKzFVgYCDS09Px3nvvISIiAm5ubo9daHT79m1MnjwZgYGB0Ol0Ji4lIiKqHk2bNkVUVBR27tyJ1NRUuLi4IDo6GkajUXQaERHRM5HL5VCpVMjKykKPHj0QEBCAwMBAXLp0SXQaEREREb2gn3/+GUqlEj169EDdunWRnJwMrVaL1q1bi04jM9GgQQMMHDgQMpnssefIZDIEBwebsIqInoW1tTWvtdIzad68OcLDw5GSkgIXFxcMGTIE/v7+SEtLe+zfWbJkCfz8/HDlyhUTlhIRERERERFRTcSBoUREVO3S09MRFBSEiooKfPzxxygsLHzo+A8//IBXX30VU6ZMQVBQELKzsxEWFoY6deoIKiZzJ5VKMWHChMcOM7OyssIbb7xh4ioiIvNXXl6O6OhoODo6YtOmTVi/fj0OHjwIFxcX0WlkRjgwlIhe1Lx58/Ddd98hLi4OXbt2FZ1DZsTBwQFffvklVq1ahQ0bNojOISKq0fLy8uDv748pU6ZgwoQJOHfuHPr37y86i8yInZ0dDAYDLl++LDqFqFZp2LAhhg4d+tihoRUVFXjzzTdNXEXmrF69elCr1Th//jy8vb0xZMgQBAYG4sKFCw+dN3/+fBQVFeHMmTOYOHEiB6kREVGNMmjQIGRkZCA0NBRvv/02Bg8ejIsXL4rOIiIiemZt27aFVqvFvn37kJOTA2dnZ6jVapSVlYlOIyIiIqJnVFxcDLVajU6dOuHEiROIiYnB/v374e7uLjqNzNDo0aMfe61GLpcjODgYTZo0MXEVET2NQqHgxrv0XBwdHREbG4v9+/fj1q1b8PT0RGhoKAoKCh46Ly8vD59//jkKCgrg5+eHu3fvCiomIiIiIiIiopqAA0OJiKhaXb9+Ha+99hpKS0thNBpx//59zJ8/HwBw+fJlKJVKDBgwAC1atEBycjKioqLQsmVLwdVkCd58803o9fpHHtPr9Rg9erSJi4iIzNuRI0fw6quvYvr06XjjjTeQlZUFpVIpOovMEAeGEtGL+OKLL7Bs2TJER0fjtddeE51DZig4OBjTp0/HtGnTkJGRITqHiKjGMRgMiI6Ohru7OwoKCnDs2DFoNBrUr19fdBqZGVtbWwBAfn6+0A6i2uiNN95ARUXFI49ZW1tj6NChJi4iS9C+fXtotVrs378f+fn5cHZ2hkqlQlFRETIyMhAZGYny8nKUl5cjLi4OarVadDIREVGVqlevHsLDw3HkyBFcunQJnTt3RkRExGN/ryIiIjJHAwcOxLlz57BkyRIsX74cbm5u2LNnj+gsIiIiInoCo9EIrVYLBwcHrFy5EvPnz0dqairGjBkjOo3MWFBQECQSySOP6fV6TJkyxcRFRPQsrK2todPpRGeQBRowYACSkpKwbt06JCQkoGPHjlCr1ZU/T3PmzAHw2+8Vubm5GDp0KIfTEhEREREREdEL48BQIiKqNvfv30dgYCBu3LhROdhRr9djzZo1eO+99+Dg4IBTp05h+/bt2Lt3L1xdXQUXkyXx9PSEo6PjH56XSCTw8PCAvb29gCoiIvNz7do1KJVK9O3bFy1atMDZs2eh0WjQsGFD0WlkpvR6PerUqSM6g4gsyNatWzF9+nQsXboUEydOFJ1DZmzFihVwd3dHcHAwiouLRecQEdUYOTk5GDBgAKZPn4533nkHp0+fhpeXl+gsMlPNmzdH48aNkZeXJzqFqNYZPHjwIwc5y+VyjBo1CvXq1RNQRZZiwIABOHPmDJYuXYqvv/4aLi4uUCqVkEr//20/BoMBixYtwoYNGwSWEhERVY+ePXvi7Nmz+OSTT/DJJ5/A19eXGxMREZFFqVOnDlQqFVJSUtCpUye89tprCAwMxOXLl0WnEREREdHvJCYmwsfHB1OmTEFgYCCysrIQFhYGhUIhOo3MXIsWLeDt7f3Q9ZsH2rVrh759+wqoIqKnUSgUHOJIL0wqlUKpVCInJwcfffQRVqxYgU6dOmH+/PnYsmXLQ+uqT5w4AaVSCaPRKLiaiIiIiIiIiCwRB4YSEVG1MBgMGDt2LM6ePVv5pfYDMpkMO3fuREREBFJSUhAQECCokizdxIkTYWVl9dBzVlZWmDBhgqAiIiLzUV5eDo1GAycnJxw8eBD//ve/sX//fnTu3Fl0Gpk5vV4PuVwuOoOILMThw4cxduxY/O1vf0NYWJjoHDJzcrkcGzduREFBAf72t7+JziEisnjl5eWIiIiAq6sr7t69i8TERISHh3OREj2VjY0N8vPzRWcQ1TrW1tYYNWrUHzZq0ev1GD9+vKAqsiRyuRyzZs1CdnY2nJyckJSU9IfrsEajEZMmTcIPP/wgJpKIiKgayeVyhIWFISkpCQaDAR4eHpg7dy4XchMRkUXp0KEDEhISsHXrVqSnp8PZ2RlqtRplZWWi04iIiIhqvcuXL0OpVKJnz55o0KABzpw5g6ioKLRq1Up0GlmQMWPG/GFgqFwux9SpUyGRSARVEdGTKBQK6HQ60Rlk4erVq4ewsDBkZGRgwIABiIiIgEwme+ic8vJybNq0CR9++KGgSiIiIiIiIiKyZBwYSkRE1eLvf/87duzYgfLy8j8c0+v1yMzMhL29PYdR0Z8yYcIEVFRUPPRceXk5Ro0aJaiIiMg8HDp0CJ6ennj//fcxceJEZGZmQqlUis4iC8GBoUT0rDIyMjB8+HD85S9/wapVq0TnkIVo3749vv76a8TExCA6Olp0DhGRxUpJSUHPnj2hVquxYMECnD59Gp6enqKzyELY2dkhLy9PdAZRrTR+/Pg/DABp3Lgx/Pz8BBWRJWrUqBEyMjL+sNj0AaPRiOHDhyMnJ8fEZURERKbh6uqKY8eOYdWqVVi9ejW6deuGxMRE0VlERETPJTAwEOnp6Zg9ezYiIiLg5eWFo0ePis4iIiIiqpWKi4uhVqvRqVMnJCYmIiYmBnv37oWbm5voNLJAI0aMeOQ6J97LT2S+rK2tuTEVVZl27drhtddeQ1lZ2SPXVhsMBixduhT/+te/BNQRERERERERkSXjwFAiIqpyn3/+Of71r3/94QLn/5JKpZg+fTovptCf0rZtW/Tq1atytzWJRIJu3brBxsZGcBkRkRhXr16FUqlE//790aZNG5w7dw4ajQYNGjQQnUYWhANDiehZXL16FYMHD4ajoyP+85///GEHZKInGTx4MObNm4eZM2ciKSnpkeeUlJSYuIqIyDLo9frKxeN16tRBcnIywsLC+F5Mz8XW1hb5+fmVf66oqMDFixeRmpoqLoqolhg4cCCaNWtW+We5XI433niD38XQc4mIiEBBQQEMBsMjj1dUVKC4uBiDBg3C7du3TVxHRERkGlKpFCEhIUhJScFLL70EHx8fhIaG4tdffxWdRkRE9Mzq1q0LtVqN1NRUtGvXDn369IFSqURBQYHoNCIiIqJawWAwQKvVomPHjli5cmXl72ZjxowRnUYWzMbGBq6urpV/lslk8PPzQ/v27QVWEdGTKBQK6HQ60RlUQ+h0OsyZMwcSieSJ5/3973/H999/b6IqIiIiIiIiIqoJJEaj0Sg6goiIao74+HiMGDECz/L2IpPJ8Omnn+Ldd981QRnVVOvWrUNISAgMBgOsrKzwz3/+EzNnzhSdRURkUnq9HpGRkfj444/RqlUrfP755xg6dKjoLLIAq1atwpdffomGDRvCysoKAJCeno6GDRuiW7dukEgkaNKkCQBgzJgx8PPzE5lLRCa2fft2SCQSDB48+KHn7927hz59+kCv1+PIkSMPDbshelYGgwGDBg3C+fPnkZSUhObNm1ce++qrrxAZGYnTp08LLCQiMj8nTpzAlClTkJ+fj08++QRz5syBVMq9AenpjEYjrl27hry8POTl5eE///kPjh49ii5duuDChQu4fv06KioqMHHiRKxfv150LlGNN3PmTERFRaGsrAwAcOTIEfTu3VtwFVmKixcvolOnTpU/P08il8vRu3dv7N69m0NpicjiXL9+/Q/X/e/evYtLly7Bzc3toedtbW2xbNkyU+aRGYqLi8O0adPQqFEjREVFwd/fX3QSEdVwW7ZswcaNGx967tKlSwCAV1555aHnx40bh5EjR5qsjSxXQkICZsyYgbt370KtVmP69OncLIqIiIiomhw8eBCzZs1CWloaJk+ejMWLF6Nly5ais6iGWLx4MRYuXAi9Xg+JRIKYmBgOoiUyExcuXEB0dDTu3r0Lg8GAkpISZGRkICMjA97e3gCAwsJCSCQSeHl5Yd26dYKLydKEh4fjo48+QkVFxRPPk0gkkMvlOHjwIHx8fExUR0RERERERESWjANDiYioypw6dQq+vr4oKyt76sBQuVyOiooKNGzYEDk5OWjRooWJKqmmuXv3Llq1aoWysjJIJBJcvnwZbdu2FZ1FRGQyBw8exIwZM3DhwgW8//77mDt3LqytrUVnkYU4evQofH19n3iOTCaDwWBAdnY2HBwcTFRGROagb9+++PHHHxEdHY3JkycDAMrKyjBkyBBkZGTg2LFjsLGxEVxJluzGjRvo2rUrPD09sXXrVuh0OkybNg1ff/01ACAzMxNOTk6CK4mIxLt//z4WLFiA5cuXY+DAgYiOjuZ7MD2zS5cuwcnJCffv3wcASKXSyu/ny8vLK8+TSCSIjIzE1KlTRaUS1RrHjx+vXOzRpk0bXL16FRKJRHAVWYrXX38dGzduhEwmg1QqhV6vf+L5MpkMkydPRnR0tIkKiYiqTocOHZCXl/fU8z788EMsXrzYBEVk7goKCjBnzhx88803GDNmDNasWfPQRkVERFXp7Nmz8PT0fKZzk5OT4eHhUc1FVFOUlJRg2bJlCA8Ph7OzM1avXs2hEURERERV6NKlS/joo4/wzTffwM/PD5999hlcXV1FZ1ENk56eXvlz1bhxYxQUFEChUAiuIiIAKC0tRevWrVFUVASZTIaKigoYDIZHnqvRaP6wuRnRk9y4cQMdO3ZEcXHxY3+u/pdMJkOjRo1w8uRJdOzY0QSFRERERERERGTJpKIDiIioZsjPz0dAQADKy8v/MCzUysqqcqGjQqGAh4cHJk2ahFWrVmHHjh2oX7++iGSqIRo3boxhw4YBAHr27MlhoURUI+zbtw937tx54jlXrlyBUqnEgAEDYGdnh/T0dKjVag4Lpefi4+Pz1B3RjUYjunXrxmGhRLVMVlYWjhw5goqKCkyZMgWLFi2C0WjElClTcPLkSezYsYODyuhPa9WqFeLi4rB7927MnTsXXl5e+PbbbwH8ttHIpk2bBBcSEVUvg8GAcePG4eeff37sOUePHoWHhwe++OILREZGYteuXXwPpufyyiuvYNiwYZDJZAB++7krLS19aFgo8Ntnv+7du4tIJKp1evTogXbt2gEA/vrXv3JYKD2Xb775Bmlpafjqq68wbdo0eHl5VS4wlUqlf1hsWlFRgbVr12LFihUicomI/hSlUgm5XP7U815//XUT1JAlaN26NbRaLbZu3Yrjx4/DxcUFWq32secbjUZMnjwZt27dMmElEdUUHh4ez3QNvUOHDhwWSs+lXr16UKvVSE1NRevWrdG7d28olUrcuHHjiX/v8OHDuHDhgokqiYiIiMxLWlraU8/59ddfoVar4ejoiJMnT2Lbtm3Yu3cvh4VStXBxcYGdnR0AYOLEiRwWSmRGFAoFlEolZDIZ9Hr9Y4c6SiQSDB8+3MR1ZOkMBgNWrlyJd999F/3790eLFi0qj8nlctSpU+eh8ysqKlBUVAQ/Pz/cvHnT1LlEREREREREZGEkxt9PdSMik4uNjRWdQPSnFBcX48MPP8S1a9cglUorL5Q0bNgQdnZ26NChA2xsbGBjY4OXXnoJUunzz6tu3749evbsWdXplfg6tGxJSUlYtmwZJk+ejNdee010Dv1JwcHBohOIhEpLS0OPHj0wefJkrFy58g/H9Xo9IiMj8dFHH6FNmzbQaDQYPHiwgFKqKWbMmIHo6GiUlZU98rhMJkNkZCRCQkJMXEZEIqlUKqxZswZ6vR7Ab0NHvLy8cPbsWezatQv9+vUTG0g1ysSJE/Hdd98BQOXPHAB07twZ6enporKIiKrdggULoFarMXjwYGzfvv2hY/fu3cPHH3+MVatWISAgAF988UXlcDmi55WZmQkXF5c/bPb1v+rUqYNff/31mQYyUc1x/PhxXL58WXRGrfSf//wH//3vfxEREQFbW1vRObWSj49Ptb23mvq6Y0VFBa5cuYILFy4gLy8Pubm5uHjxIsrKyh4aSDt79mx069bNpG1EolT3/QVkGjk5OU8dxObs7IyMjAwTFZEluXv3Lt5//318+eWXGDJkCNasWfOH9/4vv/wSISEhGDBgAPbu3ftC9zMRUe22aNEiLFq06KFrG/9LLpfjk08+wUcffWTiMqpJEhISMH36dBQVFWH+/PmYPn165eZAD5SVlaFz586QyWQ4deoUGjVqJKiWiIiIyPRWrlyJ+fPnIzc3F82aNfvDcYPBgA0bNuD999+HXq/HJ598gnfeeQdWVlYCal8M1ztZpm+//RZbt27FsmXLuDGsBeF6ptohJSUFXbp0eexxiUSCLl26IDk52YRVZA6q4z6aoqIiXLx4EZcvX8bly5eRl5eHn3/+uXL9jkwmQ0VFBezs7LBgwQIOmaZaozrv2yEiIiIiIqqpODCUyAz87yIdInq00aNHIy4urtr++3wdEpkP/npKtdnNmzfRtWtXXL16FQCQnJwMd3f3yuP79+/HjBkzcPHiRcyZMwfz5s3jxWD603744Qf079//scflcjlu3LiBJk2amLCKiEQqKSlBmzZtUFRU9NDzMpkM3bt3x759+1CvXj1BdVSTlJeX46OPPsKyZcsAPPqzwE8//YSOHTuaOo2IqNrt2bMHgwYNgtFohEQiwYYNGzB+/HgAwK5duxAaGoqioiKEh4dzeD9ViXHjxmHLli2PHWDh7e2NEydOmLiKRBszZgw2bdokOoNIiJiYmGpb8MfrjkTiVff9BWQ67u7uSEtLe+T3RnK5HIsWLUJYWJiAMrIUR44cwVtvvYWCggIsWLAAM2bMgFQqxdWrV+Ho6Ihff/0VUqkUH374IRYuXCg6l4gsTG5uLhwcHJ54r9P58+efOgCb6GmKi4vx6aefYunSpXB1dcXq1avRo0ePyuNLly7Fxx9/DIlEAn9/f2zbto2DsImIiKhWiI+Px8iRI2E0GjF9+nSsXLnyoeMHDhzArFmzkJGRgUmTJuEf//gHWrRoIaj2xfG6A5HpcD1T7eHm5ob09PTHXn9YsGAB5s2bJ6CMROJ9NESmU5337RAREREREdVUvBOEyEzExMTAaDTywYfFPUpKSqDT6ar1/zF69Gi+Dvl46mPz5s3CG/j4c4+YmBiTvNaJzJVer8eIESNQUFAAg8EAqVSKkJAQGI1G/Pzzz1AqlfDz84O9vT0yMjKgVqs5LJSqRJ8+fdC8efNHHrOyssKIESM4LJSolvn2229RXFz8h+crKipw6tQp+Pr64ubNmwLKqCb5+eef0bt3byxfvrzyM8HvyeVybN68WUAdEVH1unz5MsaNG/fQop63334b58+fR2hoKAICAuDt7Y3s7GwOC6UqM3/+fJSXlz/yWJ06ddCrVy8TF5G5GD16tPDvhmvr4/vvvxfeUFsfpmCO1x0NBgMKCwuFd/DBR3U/THV/AZmGUqmETCZ75LHy8nKMHTvWxEVkaXx9fXH27FlMnToV7733Hvr164fs7GxMmzYNpaWlAACDwYDFixfj+++/F1xLRJbG3t4eHh4ejxzMKJFI0LVrVw4LpSpRv359qNVqpKSkoHnz5ujVqxeUSiVu3bqFy5cvY+HChaioqEB5eTl2797NgSZERERUK5w+fRrjxo0D8NuAv8jISKSnpwP4bYPi4OBgDBw4EC1btvx/7N15WFRl/z/w9xlgAEVZ3MAlBTFXXDJcQFML1zJQIcrUNJcnNcstbTHNylzwUbPStFJzeR4R0ywz/WouKCiKkmKKG2qooQiIuLAM3L8//DGP48zAmY1hmPfruu7ryjPnPuczNJ+5z9yfsyApKQkrVqywyZuFlqiIdQe20ltxcTHrgTbUeD2T/RkzZozeh22UXNtD9sma59E8fPjQ4tdqs7FVhEZERERERETG4Q1DiYjIJK6urrxZGVUIAwcOtHYIREQmGTt2LI4cOYLCwkIAjy5yPHr0KCIjI9GkSRMkJiZCDcGJAAAgAElEQVRiz549+PXXX9GwYUMrR0uViUKhQEREBJRKpdZrKpUKI0aMsEJURGRNX331ld7XVCoVTp06hU6dOuHKlSvlFxRVKllZWejUqRMSEhJQVFSkdz2VSoWNGzeWY2RERJZXWFiIiIgI3Lt3D8XFxQAeXbz04MEDvPLKK9i+fTt++eUXbNq0CbVq1bJytFSZNG/eHBEREXByctJ6rbCwEB07drRCVET2LSwszNohkJ2RJAleXl7WDoOIyCCDBw/WOX8kSRI6dOiARo0alX9QZHNcXV0xb948HD58GDk5OXj22Wfxyy+/qOuywKPP1LBhw3Dp0iUrRkpEtmjYsGE6by7h4OCAYcOGWSEiqsyaNm2KXbt24ccff8Tu3bvRokULDBw4UON4qbi4GAsWLMAPP/xgxUiJiIiILOvKlSvo3bs3CgsL1XV3hUKBd999F++//z4CAgKQnJyM3377Dbt370bLli2tHDHZI0mSWA8kqsBef/11vTcMbdSoEZo1a1bOEREBLi4uvFabiIiIiIiIiPTiDUOJiIiIiIisbP78+Vi1apXOCx63b9+Ojz76CCdPnsQLL7xghejIHgwaNAgFBQVay2vVqoWePXtaISIispYjR44gOTlZfSK1LiqVCqmpqXj55ZeRn59fjtFRZeHl5YXdu3cjMDBQ7wmXwKMb6J08eRJXr14tx+iIiCxr8uTJSExM1LgpCfDoho0nT57E/Pnz0b9/fytFR5XdJ598ApVKpbVcCIEOHTpYISIiIiIiotLVrVsXQUFBWnNICoWCN2EjgwUGBuL//u//oFAotD5TxcXFyM/PR//+/fHgwQMrRUhEtujVV1/VWVcrKipCRESEFSKiyk6SJAwZMgQpKSkIDg7WOd8MAG+99RZiY2OtECERERGRZeXk5KBPnz7Izc3VOO+6sLAQf/zxB1auXIn58+cjOTkZ/fr1s2KkRERUkXl5eSEsLEzrwbtKpRKDBw+2UlRERERERERERET68YahREREREREVvT777/jww8/hBBC6zUhBFQqFe7cuaN1IgKROfXo0QMeHh4ay5RKJUaMGAEHBwcrRUVE1vDNN9+UOuY4OjrC0dER77zzDmJjY/kUYzJa8+bNkZCQgOXLl8PV1VXv587R0RE//fRTOUdHRGQZmzZtwtdff63zYRHAoxveTJw4EVlZWeUcGdmL5s2bIyIiQmvc9fT0RKNGjawTFBERERFRGYYOHQpJkrSWDxo0yArRkK2bNm0aHj58qPPmfoWFhbhw4QJGjRplhciIyFZ5e3uja9euGnV1hUKBbt26oW7dulaMjCo7FxcXnDx5Uu85HUIIDBgwAGlpaeUcGREREZHlFBQUIDQ0FKmpqTpvmu7g4AAvLy+MGzcOjo6OVoiQiIhsyahRo7TGk4KCAgwYMMBKEREREREREREREenHG4YSERERERFZyZkzZxAeHl7qOoWFhViyZAmSk5PLKSqyRw4ODhg4cCCUSqV6WUFBAYYMGWLFqIiovGVmZiI6OlrnydSOjo6QJAmhoaE4f/48vvzyS60bDRMZSpIkjBkzBn/99Rc6d+4MhUJ7ulqlUmHjxo1WiI6IyLzOnz+PESNG6LzJTYni4mLcvXsXkyZNKsfIyN588sknUKlU6n8rFAp07tzZihEREREREZUuIiJC47eUQqFAjx49UKdOHStGRbZo7969WLdunc458BIl85ErV64sx8iIyNYNHTpU49+SJGktIzK3+fPn4++//9b7gKqioiLcvXsXffv2xf3798s5OiIiIiLzE0LgzTffRFxcnN7f9kVFRbh8+TJ/1xMRkSwhISFaD3ypXbs22rdvb6WIiIiIiIiIiIiI9OMNQ4mIiIiIiKzg5s2bCAkJQUFBAYqLi0tdV6FQYPz48eUUGdmr8PBwFBQUAHh0AVObNm0QEBBg5aiIqDz98MMPEEJoLCu5gWO7du1w6NAhbN68Gb6+vtYIjyoxX19f7N+/H8uXL0eVKlXg5OSkfk0IgcTERKSlpVkxQiIi09y/fx/9+/dHQUGB1lj7pMLCQqxduxY7d+4sp+jI3jRv3hwRERHq8dbR0ZE3DCUiIiKiCs3LywshISFwdHRUL+NN2MhQ9+/fxxtvvCFrXSEE3n77bRw7dszCURFRZTFo0CCNh6JJkoSwsDArRkSV3eXLlzFnzhy9NwstoVKpcO7cOQwdOrTMuWkiIiKiiu6jjz7Cf//7X42HI+pSXFyMDz/8EJmZmeUUGRER2SqFQoFRo0apz6FxcnJCZGRkqQ+EJiIiIiIiIiIishbeMJSIADx6GpaHh4fV9q9SqRAcHIy2bdsiLy/P4P59+vSBm5ubyXF8+OGHqFatGs6dO2fytogeFxYWpnHxij7WzkUiIiofeXl56N+/P27fvl3miWtKpRLFxcU4ePAgYmJiyilCskchISGoVq0agP+d/EJE9kMIgeXLl2uMSwqFAo0aNcKmTZtw9OhRBAUFWTFCquwkScKYMWNw4cIF9OrVS70MABwcHPDzzz9bMzwiIpOMHj0aly9f1vv7z8HBAQ4ODgAAT09PhIeH4/79++UZItmZTz75RP15LCgoQMeOHa0cEVH5Yz2GiIjItgwZMkT9AD5HR0eEhoZaOSKyNefPn0fHjh3h6ekJ4NFv8ccfXPSk4uJihIWF8eYiRCSLh4cH+vTpA0dHRzg6OqJfv37w8vKydlhUiX3wwQcoKCgoczwDHp2fvW3bNsyePbucoiMiIiIyv++//x5z585Vzw+VRpIk3L17F3PmzCmHyIiIyNaNGDFCfQ5NYWEhBgwYYOWIiIiIiIiIiIiIdOMNQ4nsyJ9//glJkjRaenq6tcMCALz//vs4deoUNm3aBBcXF63XW7VqBUmSMHbsWIvG8emnn6JNmzYIDw/Hw4cPLbovc7pw4QIiIiJQq1YtODs7o2nTprKL4ceOHcPAgQNRr149ODs7w9/fH9OmTUNubq7GeufOnUN4eDi8vLxQpUoVtGjRArNmzcK9e/cs9bYqvDt37iAqKgqdOnWCt7c3nJycUL16dQQGBmL+/PnIz8+3dog2oaz8XrJkidZ3lyRJcHZ2RuPGjTFu3Dhcv35dq19OTg7mzp2LoKAgeHl5QalUwtvbGy+++CI2bNiAoqIinfuTmxPWZkrey+17/Phx9OvXDx4eHnBxcUGbNm2watUqndssKCjAsGHDIEkSFi5caJb3SFRZCSEwcuRIJCUlobCwUOO1kotHgEcXqTVu3BiRkZH497//jYMHD/LiR7IoJycnDBgwQD3Wvvrqq9YOiYjK0a5du3DlyhUAj8YjLy8vfPPNNzh37hwiIiKsGxzZlbp16+LXX3/FDz/8gKpVq8LJyQlFRUXYuHGjtUMjIjLKsmXLsHHjRo3ffw4ODurffp6enggLC8O///1vJCYmIjMzEzExMRg0aJC1QiY70Lx5c0RERKh//z377LPWDomIKgBL1h3y8vJ01noeb6NHj1Zvr7i4GEuXLkXLli3h4uKCunXr4l//+hfu3LljsfdPlvX+++9DkiQcOnRI7zqffPIJJEnC/v37ARheI9S1ftWqVeHv74/Bgwdjx44dWvvUtw+FQgEfHx8EBQVhyZIlWnP5laVObErePy43Nxd+fn6QJAmnT582eh+sN1JpQkNDoVQqAQAvvfQS3N3drRwR2Zp27dph8+bNyMzMxKVLl7Bq1SoMHz4cjRs3BvDoZiIlnzEAKCoqQkZGBgYNGqT3/BIioscNGTIERUVFKCoqwuuvv27tcKiS27BhA06fPo1Vq1Zh7NixCAwMVI9jj597VKK4uBiffvop621ERERkk3bt2oV//etfOl978tindu3a6N27Nz744AM899xz5RUiWQHrDtZnypy+nL6WuO6JSJdGjRqha9euAAB3d3f1fxPR/3DctS5T6vpyx8kTJ07gxRdfhIeHB5RKJZo0aYLp06eXek11aecJEBERERERkWU4lr0KEVUWbdu2hRACABAeHo6ffvpJ/dqePXs01r127RoaNGiAy5cvo1GjRnqXmcOff/6JRYsW4fPPP8fTTz+t9XpsbCz++usvNGzYEBs2bEBUVBTc3NzMtv/HOTo6YsWKFQgICMCCBQswa9Ysi+zHnNLT0xEcHIy2bdsiISEB9erVw86dOzFkyBCkpaVh2bJlevvGxsaiV69eCAsLQ1xcHLy8vLBz506MGDECBw8eRFxcHBQKBc6cOYMOHTrgmWeeQWxsLBo2bIgdO3ZgxIgRSExMxG+//VaO77hiuHv3Ljp16oTr169j7ty5iIyMhLu7O9LS0rBq1Sq8//772LNnD3bv3m3Qdp/MxcrOkPyOiYlBeHi4+t+3b99GbGwsJkyYgK1bt+LEiRPw8fEB8Ggi++WXX4arqys++eQT9OzZE56enrh27RpiYmIwduxYLFu2DNu2bUPNmjU14pGTE9ZmSt7L7bt161aEh4dj0KBBSExMhI+PD1asWIHRo0cjKysLU6dOVW8zOzsbAwcOREFBgcXfu7kdPnwYaWlp1g6D7MyWLVsQHR2tLkIWFxeri5HNmjWDn58fGjdujKeeegoODg7qfjdu3MDPP/9slZhfeeUVi2z32rVriI+Pt8i2yTje3t4QQqBt27bYu3evtcOh/y8oKAj169e3yLY3bdpkke2S7Zk3bx6AR7+LX375ZfXx9JYtW6wcmfU1aNAAnTt3tsi2eTyqn5ubG6KiorBy5UokJSXh8OHD+O6773gzCDvF41GyVampqZgxYwaEEOrff9WrV0dAQABatmyJFi1aqOezAODSpUu4dOmSFSPWjcejlVOnTp0QExODWrVqGTyPTeXLksej5mSpOqI5tq+rr73VY8pi6bqDi4uLuk79pG3btiEsLAyRkZHqZW+//TY2bNiANWvWoE+fPkhMTMSgQYNw6tQpxMfHQ5Iks/8N7IGl89RSDKkRPrn+vXv3cPbsWWzYsAGhoaHo3bs3oqOjUbVq1VL3UVRUhLS0NHz//feYNGkSDh48qD6/wlJ14vJmSt4/adKkSbh8+bJJ+7CleiPnc6ynXbt2OHz4MHx9fflbwkos+fuwvOdpXFxcEBISgpCQEGRmZuLMmTNISUlBcnIybt68CUmSUFRUhAMHDuCVV17ROFYhMkRlyhsqXWFhIZRKJYQQyM/P51hVgVTm+U0XFxcEBwcjODgYhYWFuHLlCi5duoSLFy/i3LlzuHXrFoBHNWCVSoVhw4bh6tWr8PX1tWrcZF9sZX6TiPSz9nhH9u3q1auYMWMGiouL4eDggOLiYggh4ODgAG9vbzRp0gQNGzZUt8evRSkoKCi3z6+9jnesO9hv3cGUOX05fS1x3ZO1cR6nYmvdujViY2PRrl07njdtAzjucty1p3HXlLq+3HEyMTERQUFBGDhwIJKSklCzZk0cOHAAw4cPx4EDBxAfH6/zmmp95wkQERERERGRBQkisjoAIjo6ulz3OWjQIAFA/PPPPzpfX7dunQAgLl++XOoycwgLCxPu7u7izp07Ol9/9dVXRbVq1cTWrVsFALFixQqtdXr37i2qVq1qtpgGDBgg3N3dRXZ2tlH9Hzx4INavXy+ef/558ddff5ktLl3GjRsnXF1dxe3btzWWz5s3T0iSJM6ePau3b3BwsKhfv77Iz8/XWD516lQBQBw9elQIIUT//v2Fs7OzyMjI0Fhv8uTJAoA4cOCAmd6NbuHh4SI8PNyi+zA0D5cvXy4AiEWLFul8fezYsQKA2LVrlxBCiNDQUOHo6GiWWCsTOfm9ePFiAUDExMTo3MbmzZsFAPHRRx8JIYTIyMgQ3t7eolmzZiIrK0tnn2PHjglnZ2fx/PPPayyXmxOGsMT3gSl5L7dvkyZNRP369UVeXp7GeiNHjhRVqlQRmZmZQgghsrKyRPPmzcXMmTPF4cOHBQARFRVl1PuKjo4W5X14Gh4eLgCwsbGV0SylJO/Z2NhKb5b8vWjt98bGZgvNkr9HeTzKxiavWQqPR9nY5DUej7KxWbdZ+njUXNu3VB3RHNu3dGyWYiv1RlP65ubmigYNGojIyEj1spJaw3fffaex7qpVq0TLli1L3Z5cgOXHt/Ku/8thzVyYPn26ACAOHjyod51Zs2YJAGLfvn1CCMNrhGWtv3v3buHk5CRefvll9bKy+gjxv9/up06dEkIYXic2hK3k/eO2b98uAKjPQUlOTjZ4H+asNwph+fMLOJ/DZs/NkuMb52nYKmtj3rCxWb9xfpONzbrN0ud/E5HlWft7hI3NFlpFu96pvLDuYJ91B1Pm9OX2Nfd1T3JY+nomzuOwsZmv2cp5NObGcdc+x11T6vpyx8mePXsKV1dXcf/+fY31vvjiCwHovn9AaecJyAFUzONbIiIiIiKiik77cQ5EZJdCQkLg4eEBAOjTpw+GDh0KAPD19YWLi4vOZSX+/PNPhIWFoUaNGnB2doafnx+mTp2KnJwc9Tp9+vRBkyZNcPLkSbRu3RouLi4oKirC9evXsW3bNrz22mtwd3fXiuvWrVvYsmULwsLC0L9/f/UTbHRxcHDAyZMn0bNnT1SvXh1VqlRBjx49kJSUpF4nKysLkyZNQuPGjeHq6oratWujX79+OHr0qMa2xo0bh5ycHKxfv96gv2NiYiLGjRsHHx8fjB07Fv7+/qhXr55B2zBUdHQ0unfvjho1amgsHzBgAIQQ2Lx5s96+4eHhWLBgAZRKpcbyli1bAgCuXLkCAOjZsyfmzZuHmjVraqzXvn17AEBqaqqpb8PmZGZmAgCeffZZna/PmjULJ0+eRI8ePdTLnJyccOnSJQwYMAAeHh5wcXFBx44dcfDgQfU6j+ciAPTr1w/+/v44deoUevToATc3N3h6emLo0KHIzc1FdHQ02rZtiypVqsDPzw9Lly7ViMPU/oBpOb5nzx5IkqTzqYyG5HdpWrVqBQDqp1EtWrQI6enp+PLLL+Hp6amzz7PPPot33nkHe/fuxe+//65eLjcn5LDk94EpeS+nb3Z2Ni5cuICgoCA4OztrrPfKK6/gwYMH+O233wAAN2/exMSJEzF79myzvDdrCA8PhxCCja1c2okTJ3Dv3j2rxyG3RUdHl0seWvt9smm2iRMnoqCgwOpxsD1q5SE6Otrq75PNum3nzp34888/rR5HRWyPP23YUng8Kq+lp6dj+fLlVo+DrXwbj0fZbLmdO3cOqampVo/D1FYeeDxqvXbmzBksW7bM6nGw6W/lcTxqDqbWEcuq35W2fWNjM3c9Ru57lcPW6o2m9J05cybu3LmDRYsWqZetWrUKVatWVf9/KzFixAicPn0azZo1M+St2QRzfP7i4uLQt29feHp6QqlUomHDhnj77bfVNc3S8qisviX9ddUCrenJGmFZQkJCMHbsWPzyyy/Yt2+fwfu5du0aAOPqxGWxtbwvkZmZiVGjRiEyMhIhISFG78MW642cz7FOy8/Px9SpU60eh7228mLt96mr5eTkID4+3upxsNles+e8sdf222+/YceOHVaPg+1/rTzY2vzm9evXceHCBavHwWYfzVbmN4mobLY23rFVjpaamoqbN29aPY6yWkUc71h3MA7rDvKYMqcvt6+5r3uqSKz9ncWmv02ZMgUPHjywehxspTeOuxx37W3cNbaub8g4mZaWhjp16qBKlSoa6zVu3BiA9v0DyjpPgIiIiIiIiCyHNwwlIi07d+7ElClTADyabMvLy9O5DHg0kRUUFITi4mLEx8cjMzMTS5cuxbp169CrVy+oVCoAgLOzM+7fv48JEyYgNDQUS5YsgUKhwO7duyGE0Dsp9P3336OgoADDhw+Hg4MDhg4dihMnTiAxMVFr3cLCQgwbNgzTp0/H9evXcfDgQdy6dQsvvPACbt++DQB49dVXERMTg/Xr1yM7OxsJCQlwdXXFCy+8gPPnz6u31aVLF7i4uGD37t1l/r0yMzPx5ZdfonXr1ggMDMSxY8cQFRWFGzduYMWKFXB3d8ft27chSVKZLSUlxYD/U48m4jIzM9GiRQut1/z9/eHk5ITjx4/r7T9x4kS89tprWstPnjwJSZLUN0mcMGECJk6cqLXe9evXAQB+fn4GxV0ZdOvWDQCwZs0a9ef8cXXq1EHr1q3h5OSkXqZQKDB48GCMHj0a165dw5EjR5CVlYWIiAjk5+fr3I9SqcTt27cxbtw4zJs3D+np6fjwww+xfv169O/fH6tXr8bWrVtx48YNBAcH491330VCQoLZ+pua46UxJL9Lc/LkSQBA06ZNAQCbN29GjRo10LNnz1L7DR48WL1+Cbk5oU95fB+Ykvdy+wrx6GRpSZK01vPy8lL/TQCgWbNmGDNmTKl/FyL6n3bt2qFq1arWDoOoVHPmzNE4hiGiyq93795o06aNtcMgKlWdOnXw1ltvWTsMIiLZnn76afj6+lo7DKJSNW/eHMOHD7d2GFQJmFpHLKt+p2/7psT2pPKqp+hjq/VGU/pevXoVX3/9NSZOnIi6deuql8fFxaFt27ZaFyxUZqZ+/vbu3Yvu3bujevXqSEhIQFZWFn788Uds3boVPXr0KLXeL6cvYFwt0NKerBHKMWTIEACQdTPMEgkJCXBwcFBfSGRMnVgXW837x40dOxYqlQpfffWVSftgvZHkUiqV+PTTT60dBtmh6tWro3PnztYOg4hsQM+ePXmBNFV4devWhb+/v7XDICIiIiqTr68vateube0wbBLrDsZh3UFe3cGUOX05fS1x3RORHJ9++ilcXV2tHQbZII67xuG4a9nriA0ZJwMCApCenq71QOSLFy8CgNb+SztPgIiIiIiIiCyLNwwlIpNMnjwZXl5eiImJQdOmTeHm5oaXXnoJc+fOxdGjR7Fp0yYAjyaVMjIyEBoais8++wxvvfUWJElCbGwsAOC5557T2nZxcTFWrlwJX19f9dN4RowYAQD49ttvtdZ/+PAh3nvvPYSEhKBatWpo3749vvjiC2RnZ2Pt2rXIy8vDH3/8gb59+6Jz585wcXGBr68vVq9eDWdnZ+zatUu9LRcXFwQGBuLgwYN633t+fj4iIiJQt25dzJw5E126dEFSUhKOHTuG0aNHw83NTb1uzZo1ZT3hqlmzZgb9/W/evKne/pMUCgW8vLzU68jd3sKFC/HVV1/h448/1jmR+Pi6S5YsQatWrRAcHGxQ3JVBly5dsHDhQmzYsAH+/v6YPHkyfvrpJ9y4cUNvn/v372Pq1Kno168f3Nzc0LZtW7z11lu4efNmqTfJzMnJwQcffICOHTvCzc0NkyZNgpubG+Lj47F69Wr4+vrCw8MD06dPB/Boot9c/U3N8ZCQEAghsHDhQo2YDM1vXbKysrBt2zZMnjwZDRo0wLhx41BQUIALFy6gefPmOiezHxcQEABJkkotAMvNifL8PjAl7+X29fLygr+/P+Li4lBQUKCx3qFDhwAAt27d0rkPIiKyfU8+FZKIiIiIiIgqL17sQJYkp8ZgSP3O0sqjnvIkW683mtL3888/h4uLCyZNmqSx/PLly6hXrx7Wrl2LZ555Bq6urvDy8sLrr7+Oa9euGfTebIkpn7/p06fD09MTP/74I55++mm4ubmhe/fumDdvHpKTk7Fx40a9+5XbV18t0Bp01QjlCggIAIAyb7BZXFyMK1euYNq0afj999/x3nvvoUGDBgCMqxM/ztbzvsSGDRsQExODr7/+GrVq1bLIPoh04fErERFVZE5OTnw4JxERERERVQisO8jHuoPpdQdz4nVPZC28hoJMwXFXPo675XMdsSHj5McffwwXFxcMGzYM165dQ0FBAXbt2oVFixYhMjISHTp0UPct6zwBIiIiIiIisizeMJSIjHb37l3ExcWhR48ecHZ21nitT58+AKDxpCOVSoXIyEiN9W7cuAEnJyedE0M7duzA1atXMXz4cPXkY7NmzdC5c2ds3LgRd+/e1erTt29fjX8HBQUBAI4ePQqlUonatWvj559/xtatW1FYWAgAqF69Om7fvo0JEyZo9K1Xrx6ys7PVT1F60sOHD7F582YEBQXh4sWLWLZsGdq2batzXUt5+PAhgEdPodJFqVTiwYMHZW7n4sWLkCQJ3t7emD17NubNm4ePP/5Y7/pZWVkIDQ1FTk4O1q5dCwcHB+PegI2bMmUKrl69iilTpuDSpUsYN24c6tWrB39/f3zwwQfIyMjQ6tOzZ0+Nf3t7ewMouwjZpUsX9X87OjrCy8sLjRo1go+Pj3p5nTp1AADp6elm6W+OHNfHmPyOiIjQeHKWt7c3Jk2ahLCwMBw7dgw1a9ZEbm4uAGhMrOvj4OCAKlWqaD35CjA8J8rz+8CUvDekb1RUFK5du4ahQ4fi0qVLyMnJwZo1a7B8+XIAUH+HEhERERERERERERE9SW6NwdD6naWVRz3lcbZebzS2799//40ff/wREyZMgKenp3p5UVERHj58iL1792L16tVYs2YNMjIyEB0djbi4OHTs2BF37twx6P3ZEmM+f9nZ2UhMTET37t3h4uKisb2QkBAAwL59+3Tuz9C+htQCzUlOjVAuFxcXODg4qGuK+vbh4OAAX19fnD59Gj///DPmzp2rsb4xdeIStp73AHD9+nVMmDABYWFhej8T5jqXgYiIiIiIiIiIiIiMw7qDbqw7VGy87omIbBXHXd047hrP1Jq73HEyICAAW7ZsweHDh9GgQQM4OzujT58+eO6557By5Ur19uScJ0BERERERESWxRuGEpHRbty4geLiYqxfv15jMk2SJNSrVw8AkJaWpl5fkiSNyU0AyMzM1Duht3z5cigUCgwfPlxj+YgRI3D//n2sW7dOY7lSqUSNGjU0lpVsOyMjAwqFAr/++iu8vLwwcOBAeHh4ICQkBAsXLkRWVpbW/ktuYqpvcs/V1RWDBg1CfHw8mjRpgvHjx+PkyZM61zVVSkqK1t/4888/Vz+57Mkn/JTIz8+X9XQzf39/CCGQlZWFtZS6D08AACAASURBVGvXYsmSJejUqROys7O11r106RI6d+6MlJQUbN++He3atTPtzdm4OnXqYMKECdi2bRtu3ryJixcv4u2338bq1avRunVrpKamqtd1cHCAh4eHRv+Sm60WFRXp3YeDgwPc3d01lkmSBC8vL61lurZlbH9z5Lg+huY3AMTExGg8OaugoACpqan4+uuv1cWSatWqQZIkWReLFhYW4sGDB1r/TwDDcgIo3+8DU/LekL5hYWHYsWMHzp8/jxYtWsDPzw+///47YmJiADz6WxMRERERERERERER6SK3xmBo/c6Syque8jhbrzca23ft2rVQqVQYPXq0xnKFQgGFQoGcnBxs2bIFrVu3hpubG3r27Ilvv/0WN27cwKJFi2S/Z1ti7Ofv+vXrAKCzRldSPytZ50mG9jWkFmhOcmqEct29exdFRUVa5xU8uY+tW7cCAFq2bInQ0FCd2zKkTvw4W897ABg5ciQAqC8k0sVc5zIQERERERERERERkeFYd9CPdYeKjdc9EZEt4rirH8dd45lac5c7Tq5btw69e/fGm2++iStXriA/Px9HjhxBamoqAgMD1fdYkHOeABEREREREVkWbxhKRCYbNWqUxmTa423Lli3q9RQKhfrmiI8rmeR83OXLl7Fz504UFxejYcOGGhewjBkzBgCwYsWKMrfz5GvPPvssUlJScPDgQUyePBl3797Fe++9hyZNmiApKUmjjxCi1Pft7OyMzZs34/r16/jkk09w8OBBtG3bFh06dMD333+P+/fvl9rfEM2aNdP6286YMUM9QavrpqYqlQpZWVnqCxHl8PT0xIABA7Bt2zYcP34c8+bN03g9Pj4enTp1QkFBAQ4dOoTu3bub9L4qo8aNG2PixImIj49Heno65syZY+2QTGZqjj/JmPyWS6lU4umnn8bp06fLfBJkcnIyhBClPsGrrJwoUZ7fB6bkvaF9+/bti6SkJOTn5yMzMxPR0dFQKB4dPvr5+Zn8XoiIiIiIiIiIiIiocpNTYzCkfleRya2nPM7W643G9t28eTMCAwPRqFEjjeWSJKFWrVpo3LgxPD09NV7r1q0bJEmyqc9EedJV2y5ZVlod3ZC+cmuBuri6ugJ49LnQJz8/H4BlL95MTEwEALRv377U9cLCwtCjRw98+eWXOHPmjKxty60T23rer1q1Crt27cK3334Lb29vvfs297kMRERERERERERERFR+WHeQx97qDuWB1z0RkT3iuCuPvY275qi5lzVOqlQqjB8/Hl26dMG8efPQsGFDKJVKdOzYEWvWrMH58+cRFRUl+zwBIiIiIiIisizeMJSokps7dy58fHy0nmbz8OFDAEDVqlWN3nb9+vWhUChw9epVo7dRo0YNnZNVK1asQHFxMf7880+dF9V9+umnSE5OxuHDh9V98vPzkZOTo7Gd27dvA4DGk4YkSUKXLl3w2Wef4ejRo4iPj8fdu3cxe/ZsnX1r1qxZ6nuoWbMmJk6ciFOnTuHo0aNo3749pk6dCh8fH7z11lvIycnB7du3NW6KqK+lpKQY9PerW7cuvL298ddff2m9dvbsWahUKgQGBurs+/fff2PkyJFYu3at1mstWrQAAI3J0CNHjqB3797w9fVFQkICWrVqZVCslUlBQQEWLlyIL7/8Uu86vr6+cHR0xIULF8oxMvMyR47rYkx+G2LgwIG4d++e3otvS0RHRwMAXn31VQCG54Qu5fF9YErem9K3RHx8PACgS5cupa5Hlcv3338PSZKwc+dOa4dCZJeYg0TWxRwksj7mIZF1MQeJrIs5SLbK0BqD3PpdRWSOeoqt1huN6ZuamoqTJ0/ihRde0LnNZ555Brdu3dJarlKpIISAUqmU87bsRoMGDSBJEm7cuKH12j///KNex9x9DdW4cWMAKDVPLly4ACcnJ/j7+5tln7qsWrUKkiQhMjKyzHUXLVqEoqIivP322+pl5qwT22renzp1CgAQGRmpEcPYsWMBAAEBAZAkCbVr1za5Lkm2jcexRJbB3CIyHPOGyLqYg0REZA843lFlwrqDYVh3MD9e92TfOKaSveG4axh7G3fNMSbq8vg4efXqVeTm5qJ58+Za6zVt2lS9L7nnCZR2U1kiIiIiIiIyHW8YSlTJeXt7Iz09Hb/99pt6WXFxMc6cOYOmTZvqfVpPyRNiHn+60JPL3Nzc0LVrV+zfvx/p6eka/Q8ePIgWLVqon9ijj4+PDwoLC9U35wQeTbqtWrUKbdu2RZs2bXT2e+ONNyBJEr799luN5f/3f/+n8e9Dhw4BAIKCgnDgwAHUr18fJ0+e1Finc+fO8PHxQWZmpsbyGzduwMPDQ/30IzkCAwOxfPly/PPPP1i2bBnOnz+P69evo2bNmjpvjPhka9asmex9lRg8eDAOHDigdePV6OhoODo6qm+G+KRatWph48aN+PLLL1FcXKzx2okTJwD8byL3ypUr6Nu3L5o2bYo//vgDtWvXNjjOykSpVGLz5s346KOPcOXKFZ3rbN++HSqVCi1btizf4MzIHDn+JFPyW67JkyejTp06eO+993QWPAAgKSkJS5cuRd++fdUXpBqSE3JY8vvA2Lw3pO+kSZPQpEkTFBYWqtcpLi7GypUr0bx5cwQHB8v+WxDZixMnTuDFF1+Eh4cHlEolmjRpgunTpyM3N7fMvsXFxVi6dClatmwJFxcX1K1bF//6179w584drXULCgowbNgwSJKEhQsX6t2m3PWIKhNjP/fHjh3DwIEDUa9ePTg7O8Pf3x/Tpk3Tyl9L5CpRZXHu3DmEh4fDy8sLVapUQYsWLTBr1izcu3evzL6G5FaJ3Nxc+Pn5QZIknD59WuM1uTlNVNlcuHABERERqFWrFpydndG0aVPMnTtX6zeuLsbkTWl5aMp3ApEtioqKKvWEzrJOgjQkf+UcZzIHyd6YmoOAeedbjh8/jn79+sHDwwMuLi5o06YNVq1aZfT7sxXG1hHl1u901S6Njc3czF1PsaV6ozF94+LiAABt27bVub3XXnsNWVlZ2L17t8byffv2AeCFfU9yd3dH586dsX//fvVDQ0vs2rULANC7d28A2rlgSF9TvfTSS/D09MRXX32FoqIirddTU1Oxfft2REZGwt3d3Sz7fNLPP/+M//znPxg5ciQCAgLKXL9t27Z44403sG/fPmzcuBGA5erEtpT3S5Ys0RnD8uXLAQDJyckQQsDR0dGk7xYie2HKXKbceVV7PT4lMrZWZ0rdn8iWGTsmGTIvI3fe0pjaIZGtM+W40JCxS874yHo7ERFZirmO88xx3hh/++nHuoN8rDtYDq97Iiqbpc9fMXcNgvM9unHclc9ex11Tau5yxklvb284OztrHVcDUC9r1KiRQecJEBERERERkeXwhqFEldzgwYPRsmVLfPrpp4iNjcWdO3cwc+ZMXLlyBXPmzNHbr169egCAhIQE5OXlQaVS6Vw2f/58ODg44KWXXkJKSgry8vKwf/9+DBs2DM7OzmjVqlWp8T333HMAgNjYWPWyzZs3IyMjA8OHD9fb76mnnkKPHj2wadMmZGdno6ioCC4uLpg3bx4OHDiAe/fu4ejRo5gyZQq8vb0xZMgQBAYGwtHREW+88Yb6PWRlZWHRokVIS0vDyJEj1dvPz8/HsWPH0LVr1zL/xrq4urpiyJAh2Lt3L1q0aGHUNuT68MMPUbNmTURGRuLixYvIy8vDxo0bsXDhQsyYMQNPPfUUAGDPnj2QJAlTp05Vx7hw4UKcOHECo0ePxpUrV/DgwQPExsZi1KhR8PDwwDvvvAMAePvtt5GXl4eYmBi9N5m1NytWrECVKlXw/PPP4z//+Q+ysrJQWFiIa9euYdmyZRg2bBieeuopzJgxw9qhmsTUHH/yc2dMfhuqZs2a+O2331BQUIAOHTpgzZo1uHnzJgoKCnDlyhX8+9//Rvfu3dGpUyf897//VfczJCcMYYnvA2Pz3pC+ffr0QWpqKsaPH4/MzEykp6djzJgxOH36NL777jtIkmSW90JUWSQmJqJTp06oVq0akpKSkJmZicWLF+OHH35Az549y7xJ09tvv42PP/4Yn3/+ObKzsxEdHY2tW7eib9++GjcyyM7ORu/evXHp0qVStyd3PaLKxNjPfWxsLLp27QqlUom4uDhkZGTgiy++wDfffINevXpp5K+5c5Wosjhz5gzat2+PW7duITY2Fjdv3sSsWbMQFRUl6wm+cnPrcZMmTcLly5e1lhuS00SVSXp6OoKDg5GTk4OEhATcvXsXCxYswBdffKHxdGxdjM0bfXlo6ncCkS0qOXE5Oztb50mRpZ0EaUj+yjnOZA6SPTIlB0v6mWu+ZevWrejQoQPc3NyQmJiIzMxMvPHGGxg9enSlf5iEsXVEufU7Xds3JTZzM7Weoost1BsN6Vvi3LlzAAA/Pz+dsQwePBjdunXD8OHDcfDgQTx48AD79u3DhAkT4O/vj1GjRlnor2C7FixYgNzcXIwYMQKXL1/GvXv3sGfPHsyYMQPBwcEYNGgQAN25ILevqTw8PLB27VokJycjNDQUx44dw/379/HPP//gxx9/RLdu3dC0aVMsWbLELPsrUVBQgNOnT2Py5MmIiIjAgAED8PXXX8vuP2fOHFStWhVTp05V38TIknViW8l7c++DyF6ZOpcpZ17Vno9Pyb4ZW6szte5PZKtMGZPkzssYMm9pTO2QyJaZkoOGjF1yxkfW24mIyJLMdZxn6nlj/O1XNtYd9GPdQb7yqC/wuieyV+Vx/oq5axCc79GP465+HHdNq+vLGSdL/j6xsbH48MMPkZaWhgcPHuDIkSMYM2YMPDw88O6775rlvRAREREREZEZCCKyOgAiOjraYtu/deuWGDNmjKhfv75QKpWiTZs24pdfftFY54UXXhDu7u7qf2dmZoquXbsKJycnUaNGDXH16lWdy4QQ4vjx4yI0NFR4eXkJR0dHUb9+fTFlyhSRmZmp3l5oaKhwcHDQiu3atWtCkiQxduxY9bIuXboIJycncevWrVLf17p16wQAsXjxYtG1a1fRoEEDkZSUJJ5//nnh5uYmXF1dRUhIiDh9+rS6z99//y3efPNN0aBBA6FUKkXNmjVFly5dtP7+e/bsEQDE0qVLZfyFre/q1avi9ddfFzVr1hRKpVK0atVKLF++XGOd3bt3CwBiypQpGst/+ukn8dxzz4nq1asLFxcX0aRJEzFkyBBx7tw5IYQQ9+/fFwBKbSNHjrTo+wsPDxfh4eEW3YcxeXj16lXx7rvvipYtW4oqVaoIhUIh3N3dRYcOHcTs2bNFdna2el19OfDf//5XABAxMTFCCO1c1NevYcOGomPHjhrLMjIyBAAxfvx4s/UXwrQcf/JzZ0x+L168WONvJFd2draYPXu2aNeunahSpYoAIKpVqyb69u0rNmzYIIqKinT2KysnKgpT8l5OXyGE+Pnnn0XHjh2Fm5ubqF69uujTp484duyYxjpTpkwp9fvh9ddfl/2eoqOjRXkfnpbH90tl8N133wkA4vfff7d2KBVWz549haurq7h//77G8i+++EIAEAcOHNDb9/DhwwKA+O677zSWr1q1SrRs2VKcPXtWCCFEVlaWaN68uZg5c6a6T1RUlNb25K4nh6Xz0hp5b4uYg2Uz5XMfHBws6tevL/Lz8zWWT506VQAQR48eFUKYP1flsvTvRUtvvzJgDpatf//+wtnZWWRkZGgsnzx5stnGwcdt375dABCDBg0SAERycrL6Nbk5LZeljxd5PCoP87Bs48aNE66uruL27dsay+fNmyckSdKZSyWMyZvS8tCU74Qn8Xi0YmAOlm3cuHECgCgsLDSqr5z8lXucac4cFILHoxUBc7BspuSguedbmjRpIurXry/y8vI0lo8cOVJUqVJFY15dDls6HjWljiinfqdv+8bGZu56jNz3WpGVR91BiP/lbGl1l/v374vp06eLhg0bCicnJ+Hj4yNGjx4tbt68afobFRVvfDPH5+/w4cOiV69ewt3dXTg5OYnGjRuL6dOni3v37qnX0ZdHcvrqi9FQZ86cESNGjFD/v3VzcxOBgYFiwYIF4uHDhxrrGlojLFn/8ebg4CBq164t+vfvL7Zu3aq3T2n7+OyzzwQAMXXqVPUyQ+rEFZkpef+k5cuXa/0+lLsPc9YbhbCt8bMy43Fs2UyZy5Q7r2rO41NLj5+cp5GHuVU2U2p1ptT9dWHeVAzMm7KZMibJnZeRO29pTO2wNBXt9589Yg6WzZQclDt2yR0fba3eTkTlg+Nd2Tjelc1cx3nmOG/M3L/9KuL1Tqw7sO5gSXLn9HXVFwypB5jzuic5eJ5axcAxtWzlcf6KuWsQ5pzvqYh1QI67HHctzZS6vtxxcs2aNSIoKEhUq1ZNODo6inr16omhQ4eK8+fPlxqbvvMEysLfmURERERERMbhDCNRBWDvExuhoaHCw8ND5OTkWDsUtUGDBgl3d/cKN7FnrypiAZ1sy507d4Szs7MIDAy0dihUClu5YWhmZqaYOHGi8PPzEy4uLqJWrVqib9++IiEhQWO9RYsWCT8/P+Hk5CTq168v3nvvPfVNgrds2SKEeHRiUp06dbT28dVXXwkAYt++feplf/zxh3jhhRdEtWrVhKurq2jWrJmYM2eORmG1d+/ewt/fX/z5558iICBAODs7C5VKJYQQIikpSX2xulKpFL6+vmLKlCnizp07GvtevHixOu4GDRqI999/X3zzzTdGF93l7Fdf3KW9n0OHDok+ffoIDw8P4eTkJJ566ikxfvx4jRuslNbf3Jo1ayYaNWqktbzkc7169Wq9fUePHi2qVq2qVSR/0tmzZ8WKFSuEEKLUwr7c9eSoiCe+MAcNYy85aMrnfvHixeI///mP1vLVq1cLAGLTpk1CCPPnqlwV7QIm5qBh7CUHly5dKhYvXqy1fMOGDWYbB0vcvn1beHt7i8jISJ0nmMjNabkq4ollzEPD2Ese1qhRQ/Tt21dr+blz5wQA8dlnn+nta2jelJWHpnwnPInHo/vUy5iDFTsHBw8eLFxdXY3qKzd/5R5nmjMHheDxaAnmYOXNQXPOt2RlZQkA4pVXXtHqv2vXLgFArF271qD4KuLxKFFlUNHGNyIyr4o4fvI41jD2chxrylymnHlVcx+fVsQbHzK3DGMvuWVKrc6Uur8uzJt96mXMm4qdN6aMSXLnZeTOWxpaOyxLRfv9xxw0DHOw7ByUO3bJHR9trd5OROWD4x3HO3Mwx3Geuc4bM/dvP17vRFQ58Dy1feplHFMr9phaHuevmLsGYc75nopYByQiw/H4loiIiIiIyDgKEBFZ2cyZM3Hnzh0sW7bM2qEAAM6ePYutW7fi3XffhYeHh7XDISIzcHd3x4svvojExEScOXPG2uGQjXv11VcRExOD9evXIzs7GwkJCXB1dcULL7yA8+fPAwCWLVuGyZMnY+DAgbh69SqOHDkCR0dHvPfeewAAFxcXg/Z56NAh9O7dGzVq1EBKSgoyMjIwY8YMzJgxA9OnT1ev5+zsjPv372PChAkIDQ3FkiVLoFAokJiYiKCgIBQXFyM+Ph6ZmZlYunQp1q1bh169ekGlUgEAVqxYgUmTJiEiIgLXrl3DkSNH4OTkhLlz5xr1t5K7X31x61u+d+9edO/eHdWrV0dCQgKysrLw448/YuvWrejRowfy8vJK3e6Tbt++DUmSymwpKSl632tAQADS09ORk5OjsfzixYsAgBYtWujtGxcXh7Zt28LZ2bnUv2ezZs0wZsyYUtcxZD1bxRyUz55y0JTP/cSJE/Haa69pLT958iQkSULLli0BmD9XbRVzUD57ysEJEyZg4sSJWsuvX78OAPDz89PbV25ulRg7dixUKhW++uorna/LzWlbxjyUz17yMC0tDZmZmTqPOf39/eHk5ITjx4/r/TsZmjdl5aEp3wm2gDkon73kIADcuXMH1apVM/hvZEj+yj3OZA4yB0swB+Ux53yLEAIAIEmS1mteXl4AHo2vREREZH94HCufPR3HmjKXKWde1R6OT5lb8tlTbplSqzOl7m8rmDfy2VPemDImyZ2XkTtvaWjt0NYwB+VjDsrLQbljl9zx0R7q7URkeRzv5LOn8c4cx3nmOm/MHn77EVHlwDFVPnsaU8vj/BVz1yAq+3wPEREREREREVG5se79SolICD4JRQghJk6cKKpVqyYuXLhg1ThUKpXo2rWraNmypbh//75VY6H/4RM3yRxSUlKEUqkU7dq1E2fOnBH5+fkiPz/f2mHRYyz9RE5dDP1+efjwoVAoFGLUqFEay3NyckSNGjXE0qVLhRBCNG7cWDRs2FAUFRVprNexY0eNp13KfUrn1KlThZubm7h69arGet27dxfu7u7qf4eGhgpHR0excOFCjfW6du0q6tWrp/U0xh9++EEAEBs2bFDH3ahRozLjlkvufvXFrW/5s88+K2rVqiUePnyosXzt2rUaT3bW198STp06JTw8PMTLL78s0tLSRH5+vti5c6eoUaOGiIyMLLWvq6ureOWVV8SPP/4o2rVrJ1xcXISnp6cYPHiwSEtL09lH35NAjV1Pn4r2pFzmIHNQDlM/9+np6SIqKko4ODiImTNnqpdbMldLY+njVEO2zxxkDhoiPT1d1K1bV7Rq1arUp2Qbklvr168XAMTGjRuFEEIsX75cABDJycmlxqErp+WqaE+iZh4yD3U5duyYACDmzp2r8/U6deqIzp07y95eaXljTB6WbFPOd8KTeDy6TwjBHKzoOSiEEEFBQaJevXpi5syZokWLFsLFxUX4+PiI8ePHi8zMTL39jM1fQ48zjc1BIXg8KgRzsDLn4JPMMd/i7+8v6tevrzX3vHjxYgFADB06VHY8QlS841GiyqIijW9EZH4VbfzkcSyPY+UyZC5T7ryqOY9PLT2+cZ6GuWUJhs6hmFL314V5s08IwbyxtbwRwrAxyZR5GV3zlsbU5UtTkX7/MQeZg3IZkoPGjF2GjI8Vvd5OROWD4x3HO3Mw9TjPnOeNmfu3H693IqoceJ7aPiEEx1RbGFMfZ6nzV8xdgzDnfE9FqwMSkXF4fEtERERERGQc7UfUEBFZwYIFCxAQEICIiAj1k7WsYebMmThx4gRiYmJQpUoVq8VBRObXtGlT7N27F0VFRWjdujVq166N5ORka4dFNkapVKJ27dr4+eefsXXrVhQWFgIAqlevjtu3b2PChAm4desWLl26hC5dumg9EbJPnz5G7TcqKgq5ubl46qmnNJb7+voiJycH2dnZ6mUqlQqRkZHqf9+9exdxcXHo0aOH1tMYS+JJSEhQxx0UFKQVd69evQyOWe5+9cWtb3l2djYSExPRvXt3raedhoSEAAD27dtX5nbNLSAgAFu2bMHhw4fRoEEDODs7o0+fPnjuueewcuVKvf2Kiorw8OFD7N27F6tXr8aaNWuQkZGB6OhoxMXFoWPHjrhz547F47cVzEH57C0HzeHixYuQJAne3t6YPXs25s2bh48//hgAc7UEc1A+e8/BrKwshIaGIicnB2vXroWDg4PO9QzJrevXr2PChAkICwuT9Z5Ky2lbxjyUz57y8OHDhwAefT50USqVePDgQZnbKStvDM3DEnK/E2wBc1A+e8pBACguLkZ+fj6qVq2KP/74A+np6Vi6dCliYmIQGBiI3Nxcnf3Mlb+lYQ7+D3NQe7/64ta3vLLloCVERUXh2rVrGDp0KC5duoScnBysWbMGy5cvBwD155ZMs3PnTkiSJKt16tTJ2uESVUrMQyL5eBwrn70dx5YwdC7TkHnVynx8ytySz15zyxjG1v1tBfNGPnvNG2Pqa8bOy+iat6zsdXnmoHzMQfk5aKmxq7LW24nI8jjeyWdP452px3nmPm+ssv/2s1WsOxBp4pgqnz2NqYYwtj5g7hpEZZ/vsVUcd4mIiIiIiIhsE28YSkQVgpOTE+Li4pCUlKQ1gV6e5syZg3v37qF58+ZWi4GILCc4OBgnT55EYWEh7ty5g/bt21s7JLIxCoUCv/76K7y8vDBw4EB4eHggJCQECxcuRFZWFgAgPT0dAFCzZk2t/nXq1DFqv3l5eVi0aBGCg4Ph4+MDZ2dnODo6YvXq1QAeFWRLSJIEHx8f9b9v3LiB4uJirF+/XqtoV69ePQBAWlqaOu5atWpp7f/x7ckld7/64ta3/Pr163pjKvn7lqxT2nbNbd26dejduzfefPNNXLlyBfn5+Thy5AhSU1MRGBiIjIwMnf0UCgUUCgVycnKwZcsWtG7dGm5ubujZsye+/fZb3LhxA4sWLbJ4/LaCOSifveWgOfj7+0MIgaysLKxduxZLlixBp06dkJ2dzVz9/5iD8tlzDl66dAmdO3dGSkoKtm/fjnbt2uld15DcGjlyJACoTyIrS2k5bcuYh/LZUx6WPPSmoKBA5+v5+fmyHoxTVt4YmoeAYd8JtoA5KJ895SAAHD58GBkZGZg2bRq8vb3h7u6O8PBwLF++HKmpqZg/f77OfubKX32Yg5qYg8zB8hAWFoYdO3bg/PnzaNGiBfz8/PD7778jJiYGAFCtWrVyi6Uy69OnD4QQstqRI0esHS5RpcQ8JJKPx7Hy2dtxbAlD5zINmVetzMenzC357DW3jGFs3d9WMG/ks9e8Maa+Zsy8jL55y8pel2cOyscclJ+Dlhq7Kmu9nYgsj+OdfPY03pl6nGfu88Yq+28/W8W6A5Emjqny2dOYaghj6wPmrkFU9vkeW8Vxl4iIiIiIiMg28YahREREREQGePbZZ5GSkoKDBw9i8uTJuHv3Lt577z00adIESUlJ6vVUKpVW38eL44aIjIzE1KlT0atXLxw6dAhZWVnIy8vDm2++qbWuQqGAg4OD1vJRo0bpLd5t2bJFvZ4kSVp9i4uLjYrbkP3qi1vfciGE3mWPvwd9/c1JpVJh/Pjx6NKlC+bNm4eGDRtCqVSiY8eOWLNmDc6fP4+oCnuTcAAAIABJREFUqCidfSVJQq1atdC4cWN4enpqvNatWzdIkqTxuSLmoKHsIQfNzdPTEwMGDMC2bdtw/PhxzJs3j7n6GOagYewtB+Pj49GpUycUFBTg0KFD6N69e6nry82tVatWYdeuXfj222/h7e1tUEy6ctrWMQ8NYw95WHKSqa4LFlQqFbKystQnvsqhK2+MyUNDvxNsBXPQMPaQg6Xp06cPJElCQkKCztfNnb+PYw4yBw3Zr73moKX07dsXSUlJyM/PR2ZmJqKjo6FQPCrL+/n5lWssREREVDHwONYw9nocK3cu09CaRWU+PmVuGcZec0suU+r+toR5Yxh7zRtz1Nf0zcuUNm9pD3V55qBhmIOl52B5jF2Vsd5ORJbH8c4w9jDemXKcZ+7zxuzltx8RVQ4cUw1jD2OqoYypD5i7BmEP8z1EREREREREROWFNwwlIpvw/fffQ5Ik7Ny509qhEJEBmLtUWUmShC5duuCzzz7D0aNHER8fj7t372L27Nnqp1xmZmZq9Xv86ZEA4ODgoLMQf/PmTfV/37hxA7/88gsiIyMxa9YsNG7cGFWrVoWjoyOuXr1aZqz169eHQqEoc93S4n78aZpyyd2voRo0aABJknDjxg2t1/755x/1Ooa4ffu21pNEdbWUlBSd/a9evYrc3Fw0b95c67WmTZsCAM6ePat3/8888wxu3bqltVylUkEIAaVSadD7sQfMwbLZUw6a4u+//8bIkSOxdu1arddatGgBADhz5gwA5urjmINls8ccPHLkCHr37g1fX18kJCSgVatWsvYvJ7dOnToF4NGJiI/HNHbsWABAQEAAJElCamqq7Jy2dczDstlTHtatWxfe3t7466+/tF47e/YsVCoVAgMDdfaVOxbKzcOSk4+N/U6wFczBstlTDhYUFODEiRO4cOGC1mv5+fkQQsDFxUVnX1PytzTMQeYgc/CRsnKwPMXHxwMAunTpYuVIyBisdRBZH/OQKgMex5bNno5jDalP6GJqzaIyHZ8yt8pmT7llClPr/raEeVM2e8obU8YkQ+dl5Mxb2kNdnjlYNubgI2XloLnHLlOPUYmIHsfxrmz2NN4Bxh/nmfu8MXv67WfvWFegyoJjatnsbUw1lZz6gLlrEPYw30OaOA4TERERERERWQZvGEpEVIkcO3YMAwcORL169eDs7Ax/f39MmzYNubm5ZfY9ceIEXnzxRXh4eECpVKJJkyaYPn26Vt9z584hPDwcXl5eqFKlClq0aIFZs2bh3r17GusdP34c/fr1g4eHB1xcXNCmTRusWrXKrO+XqLIwJXfl5hpz1zwOHDiA+vXr4+TJkxrLO3fuDB8fH2RmZsLHxwcNGjTAsWPHtJ4k+fvvv2v8u06dOuonbj7ujz/+UP93fn4+AKBmzZoa65w9exYHDhwAoPuJlSXc3NzQtWtX7N+/H+np6RqvHTx4EC1atEBiYiJ8fHxQv359xMfHa21v165derdv6n4N5e7ujs6dO2P//v14+PChzjh79+5t0DZr1qyp90mij7dmzZrp7O/t7Q1nZ2ecPn1a67WSZY0aNdK7/9deew1ZWVnYvXu3xvJ9+/YBqBwX6pkLc1A+e8pBU9SqVQsbN27El19+qfVE4hMnTgAAGjduDIC5CjAHDWFvOXjlyhX07dsXTZs2xR9//IHatWvL3r+c3FqyZInOmJYvXw4ASE5OhhACPj4+snPaVjEP5bO3PBw8eDAOHDiAjIwMjeXR0dFwdHTEq6++qrOf3LFQbh46Ojqa9J1Q0TEH5bOnHMzPz0eXLl0wevRordd27NgBAHj++ef17t/Y/NWHOcgcNGS/hqqMOWhukyZNQpMmTVBYWKheVlxcjJUrV6J58+YIDg4ut1iIypvcOoQuFy5cQEREBGrVqgVnZ2c0bdoUc+fO1ThGjYqKKvWiqZKb1xPZM1Py0Ny1RNYc/4fHsfLZ03GsIfUJXeTWLCrz8SlzSz57yi1TmFr3twXMG/nsKW9MGZMMmZeRO29ZmevyzEH5mIOPlJWD5h67TD1GJSICON4Zwp7GO8D44zxznzdmD7/9iAxVUFCAYcOGQZIkLFy4UOc6cmp5+si9XpH1Qk0cU+WztzFVLlPqA+auQVTm+R4iU5hSU5czvho7bubm5sLPzw+SJOk8biYiIiIiIiLr4Q1DiYgqidjYWHTt2hVKpRJxcXHIyMjAF198gW+++Qa9evUqtQiXmJiITp06oVq1akhKSkJmZiYWL16MH374AT179lT3PXPmDNq3b49bt24hNjYWN2/exKxZsxAVFYXIyEj19rZu3YoOHTrAzc0NiYmJyMzMxBtvvIHRo0frLR4S2StTcldurjF3zScwMBCOjo544403kJCQgLy8PGRlZWHRokVIS0vDyJEjAQDvvvsuLl26hMmTJ+PWrVtIT0/HtGnTcOfOHY3t9e3bF8XFxZg9ezZycnKQnp6OKVOmICcnR71Ow4YN4efnh61bt+L06dPIy8vDjh07MHDgQERERAB4dNNZXU/7LDF//nw4ODjgpZdeQkpKCvLy8rB//34MGzYMzs7OaNWqFQDgnXfewaVLlzBt2jRkZGTg2rVrmDZtGrKysoz6e8ndr6EWLFiA3NxcjBgxApcvX8a9e/ewZ88ezJgxA8HBwRg0aJBR2zVW1apVMXXqVMTGxuLDDz9EWloaHjx4gCNHjmDMmDHw8PDAu+++CwDYs2cPJEnC1KlT1f0HDx6Mbt264f+xd+9RUdX7//ifA8NNBiXERMULiEdEO546mRqYmiVwVh07plJado6IrVJL1PRTmX5dllqw1Kw+VK4jRtpH5FPYyWW5OqZ4x2teUjQx7x8UZhDwMijx+v3hjzkOM8AehpnZM/N8rMVauee9Z783+fT9nvdr9t5///vfsX37dty8eRNbtmzB1KlTERMTg4kTJzr1fNSMGbSNt2TQFvUzGBQUhMzMTBw8eBBpaWk4e/Ysbt68iW3btmHixIkIDQ3Fa6+9BoBZBZhBW3lTBqdMmQKj0Yi8vDyEhIQ02M7R46AtmXZXzKFtvCmHb731FsLDw5GSkoLTp0/DaDRi7dq1yMzMxJw5c9ClSxcA9o2FSin9N8EdMYO28ZYMhoSEYP78+SgoKEB6ejouXryIiooKrFu3DtOmTUPfvn3x8ssvA7A+FirNr1LMIDNo63Ft5WkZbGlJSUk4c+YMJk+eDL1ej5KSEkyaNAnHjh3DihUroNFoHHZsIldSWoewpqSkBPHx8aioqEBhYSEqKyvxwQcfYOHChZgyZYqpXd2/4+Xl5VYvmtJqtQ49RyK1syeHLV1LZM3RHOextvGWeawtazL2rKt68vyU2bKNt2TLFvWzZUvd310xN7bxltzYMybZsi6jdN3Sk+vyzKBtmMGmM9jSY5c31NuJyPE43tnGW8Y7QPk8r7n1PKXjmDd89iOyRXl5ORITE1FcXNxgG6W1PGuUXq/IeqEljqm28aYxVSml9QFn1CA8eb2HqLnsqakrHV+bO26mp6fjt99+a9kTJiIiIiIiopYhRORyACQ3N9fV3VC1FStWCAD5/vvvXd0V1YqPj5fIyEiprq422z5z5kwBIHv37m1w3yeffFKCgoLkxo0bZtsXLlwoAKSgoEBERJ5++mkJCAiQ0tJSs3bTp083a9ejRw+JjIwUo9Fo1i41NVVatWoler3epnMbNWqUjBo1yqZ9bMUcOgaz2zR7sqs0a67Krq1yc3PF2dPT5vz7cv78eZkwYYJ07txZ/P39JTw8XBISEsz+DamtrZX33ntPunTpIn5+fhIZGSmzZ8+WrKwss0zU1NTI3LlzpVu3bhIQECBRUVGyaNEiyc/PFwDyww8/iIjIzz//LIMHDxadTiehoaGSnJwshw8fluLiYomNjRWtVitvv/22jBgxQnx9fa32+8CBAzJixAgJCwsTrVYrkZGRMmPGDLP/r7W1tbJgwQLp0qWLaLVa6dSpk8ycOVPWrl0rAOTbb7+19Ves6LgN9bux89m9e7cMHz5c2rRpI35+ftK9e3eZPXu2XL9+XdH+jrBq1Sp59NFHJSQkxPT7e/HFF+XUqVOmNj/++KMAkBkzZpjte+PGDZk9e7Z07dpV/Pz8pEOHDpKWliZXrlwxtZkxY4YAaPBn3LhxNrVTwtG5bM77M4O28ZYMKv1731AGv/76a3nsscekdevWEhgYKD169JAXXnhBTp48adauJbOqlKPnqba+PzNoG2/I4I0bNxr9Ow9AUlNTRcS+cdCaur9TR48eNduuNNNKOPrzKOejzGFLOnfunIwbN07Cw8PF399f+vTpI1lZWWZt7B0L66ufQ1v+TVCC81Fm0J0ymJeXJwkJCaYM/uEPf5A333xTKisrTW0ayqCS/CqZZ7Z0BkU4HxVhBq3xpAw6Yr1l/fr10r9/f9HpdNK6dWtJSkqSffv2Neu81Dgf9UasdTRNaR3CmldffVWCgoKkrKzMbPvixYtFo9HIiRMnTO0AyJ07d+zur9rGN2oac9g0e3LY0rVEV9cc1Th+ch5rG2+axypZk7F3XbWl5qeOHt+4TsNstRR764ZK6v5KMTfMjbvkRsS+MampdRlb1y2bWzu0Rm2f/5hB2zCDyjKoZOyyZX3TnertROQcHO843rUUJfO8hsa7+uz93lhLfvbj9U7qxLpC0wwGg/Tq1Uvmzp0ru3fvFgCSkZFh0U5pLc8apdcruqJeWB+/p8Yx1V3G1Jb+/oqzahAttd6jxjogWeI43DR7auq2jK+2jpsbNmwQAPLss89anW+3FM5viYiIiIiImoc3DCVSAVsXNvR6vUybNk2io6MlMDBQ2rVrJ8nJyVJYWGjWbsmSJRIdHW1a7H/jjTfkf/7nfwSAfPPNNyJy90Z17du3tzjGRx99JABky5Ytpm2bN2+WYcOGSUhIiAQFBUlsbKy89957ZgtSiYmJEhMTIz///LM88MADEhAQIDU1NSIicujQIdOiu7+/v0RFRcmMGTPk2rVrZsdeunSpqd+dO3eW//qv/5JPPvmk2QuESo7bUL8bO58dO3ZIUlKShIaGip+fn3Tp0kUmT55sVpxqbP+WtnTpUvnqq68stmdnZwsAWbduXYP7xsbGSrdu3Sy21xWjsrOzRURk+fLlsnTpUot2a9asMbUzGAwCQMaMGWPRbtOmTQJAcnJybDgzzymgM7u2YXYbz64tWXNVdm3lLjcMtQcLXuRu1PjFF3swg+SO1HYBkz2YQXJHnvbFMuaQ3A3no0Sux/kokWupcT7KWodtvKXWoaQO0ZC2bdtKcnKyxfaTJ08KAFmwYIGIiIwdO1aCgoJapL/uPr4xh7ZhDpvOYUvWEtVQc1Tj+GkPzmNJLdR440N7MFvkDMwNkeu5++e/ezGD5I54oxUiz8Dxjqhx7nC9E+sKtvGWusKJEyfks88+ExFp9IahSmt51ii9XtEV9cKG+uQoXMchahnuWAfkOGwbbxiH7a2pKx1fbR03y8rKJCIiQlJSUhq8QX9L4Q1DiYiIiIiImscHROR2nnvuOeTl5WH16tUoLy9HYWEhgoKCMGzYMJw6dQoA8N///d+YPn06Ro4ciXPnzmHPnj3QarV44403AACBgYE2HXPHjh1ITExE27ZtUVRUhNLSUsyZMwdz5szB7NmzTe0CAgJw48YNTJ06FSNGjMCyZcvg4+OD/fv349FHH0VtbS127doFvV6P5cuX48svv8Tw4cNRU1MDAPjss8+Qnp6O0aNH4+LFi9izZw/8/PywaNGiZv2ulB63oX43tP2nn37CkCFD0Lp1axQWFsJgMOCLL75Afn4+hg4dCqPR2Oj71ldWVgaNRtPkT1FRUYPnOm3aNDz//PMW2w8fPgyNRoPevXs3uO8DDzyAkpISVFRUmG0/ffo0ACAuLg4AMHXqVEybNs1i/0uXLgEAoqOjISIAAI1GY9EuLCzM1CdvxOwqx+w2nV1bssbsEhEREREREREREVFLYK1DOW+qdSipQ1hz4cIF6PV6Uy3yXjExMfDz88OBAwcAANeuXUNISEgTv3XvwBwqxxw2nUOl+yqtJbLmSERERERERERERKQurCso5011hdjYWEyaNKnR34cttTxrlFyvyHohEXk6jsPKecs4bG9NXen9AGwdN1955RXU1NTgo48+UrwPEREREREROZkr71ZKRHfBhieh3Lp1S3x8fGTixIlm2ysqKqRt27ayfPlyERHp3r27dO3aVX7//Xezdv379zd7Mo/SJwrNnDlTdDqdnDt3zqzdkCFDpE2bNqY/jxgxQrRarWRmZpq1GzRokHTq1Mns6UMiIv/85z8FgKxZs8bU727dujXZb6WUHrehfje0/eGHH5Z27drJrVu3zLbn5OSYPYGnof2doaSkRDIyMsTX11fmzp3baNsjR45IaGio/PWvf5ULFy5IdXW1/PDDD9K2bVtJSUlp8jgdO3aUPn36mJ6WFBMTI5GRkVJdXW3WdunSpQJAXnzxRZvOxR2euNkUZpfZVcqW7NqTNWdk11bOfmKmiPOfYM+ndJK74ZNyiVzP0fNUR7//vZhBckfu+CTqxjCH5G44HyVyPc5HiVxLbfNR1jpY67CFtTpEffv27RMAsmjRIquvt2/fXgYOHCgiIo8++qh06tRJ5s6dK3FxcRIYGCgdOnSQyZMni16vt6lv7jy+MYfMoS2U5NCWfZXWEl1dc1Tb+GkvzmNJLRw9fnKdhjwRc0Pkeu78+a8+ZpDckbM/PxGRY3C8I2qc2q93Yl2BdQUldu/eLQAkIyPDbLsttTxrlFyv6Kp6YX38nhqRe3C3OiDHYY7DDbGnpq70fgC2jJurV68WALJ27VoREcnKyhIAcvTo0RY86/9w5udMIiIiIiIiT2L5WAsiUjV/f3/cf//9WL9+PfLz83Hnzh0AQOvWrVFWVoapU6fi6tWrKC4uRkJCgsXTa5KSkpp13IyMDFRVVaFLly5m26OiolBRUYHy8nLTtpqaGqSkpJj+XFlZiZ07d2Lo0KEICAiw2p/CwkJTvx999FGLfg8fPtzmPis9bkP9bmh7eXk59u/fjyFDhlg8memJJ54AAGzZsqXJ93WU06dPQ6PRICIiAvPnz8fixYvxzjvvNLrPAw88gG+++Qa7d+9G586dERAQgKSkJDz22GP4/PPPG9zPYDBgxIgRqKioQE5ODnx9fQHc/fty8eJFvPjiiyguLkZFRQVWrVqFrKwsADD9vfUmzK5yzK7y7DY3a8wuNdcPP/yg6Al4Go0GAwYMcHV3iTwOM0jkWswgkesxh0SuxQwSuRYzSGrAWody3lrrqNNQHaK+W7duAbj7d8saf39/3Lx5EwBQW1uL6upqBAcHY/PmzSgpKcHy5cuRl5eHfv36oaqqyjEnozLMoXLMobIc2rKv0loia450L85jiRyD2SKyHXND5FrMIBEReQOOd6RGrCso5+11BWtsqeVZo+R6RdYLyRqOqeQpOA4r523jsD01daX3A1A6bl66dAlTp07FM888o5o5CBEREREREVnHG4YSuRkfHx989913CAsLw8iRIxEaGoonnngCmZmZMBgMAICSkhIAQHh4uMX+7du3b9ZxjUYjlixZgvj4eHTo0AEBAQHQarXIzs4GAPz++++mthqNBh06dDD9+fLly6itrcXq1astFuQ7deoEALhw4YKp3+3atbM4/r3vp5TS4zbU74a2X7p0qcE+1f1+69o09r6OEhMTAxGBwWBATk4Oli1bhgEDBpgt4tb35ZdfIjExERMmTMDZs2dRXV2NPXv24MyZM+jXrx9KS0st9ikuLsbAgQNRVFSEDRs24MEHHzS99swzz2Djxo04deoU4uLiEB0dje+//x55eXkAgJCQkJY/cZVjdpVjdpVntzlZY3Zda+LEiRCRZhfsXC0pKQkiouhnz549ru4ukQVmkMi1mEEi12MOiVyLGSRyLWaQyH6sdSjnrbUOoPE6RH2tWrUCANy+fdvq69XV1aY2u3fvRmlpKWbNmoWIiAi0adMGo0aNQlZWFs6cOYP333+/5U9GhZhD5ZhDZTm0ZV+ltUTWHFsW57FEjsFsEdmOuSFyLWaQiIi8Acc7opbHuoJy3lxXaIgttTxrlFyvyHqhY3BMJVIHjsPKeds4bE9NXen9AJSOm6mpqQBgulkpERERERERqRdvGErkhh5++GEUFRVh+/btmD59OiorK/HGG2+gR48eOHTokKldTU2Nxb73LuTZIiUlBTNnzsTw4cOxY8cOGAwGGI1GTJgwwaKtj48PfH19LbbXFRqs/XzzzTemdhqNxmLf2traZvXbluM21O+GtotIg9vuPYeG9ne0++67D3/729/w7bff4sCBA1i8eLHVdjU1NZg8eTISEhKwePFidO3aFf7+/ujfvz9WrVqFU6dOISMjw2yfXbt2YcCAAbh9+zZ27NiBIUOGWLxvcnIyDh06hOrqauj1euTm5pqeFBUdHd3i5+sOmF3bMLuNZ7eOLVljdomIiIiIiIiIiIjIHqx12Mbbah1K6hD3qrvIwtrDC2tqamAwGEwXfjQkKSkJGo0GhYWFze63u2EObcMcDmnRfZXWEllzJCIiIiIiIiIiIlIH1hVs4211hcbYU8tTer0i64VE5Ok4DtvGm8bh5tTUm3M/gPruHTdXrlyJTZs24dNPP0VERESLnyMRERERERG1LN4wlMhNaTQaJCQkYMGCBdi7dy927dqFyspKzJ8/3/REHr1eb7HfvU+6AQBfX1+ri4ZXrlwx/ffly5fxr3/9CykpKZg3bx66d++O4OBgaLVanDt3rsm+RkZGwsfHp8m2jfX73if/KKX0uLbq3LkzNBoNLl++bPHa//3f/5na2KKsrMziqUfWfoqKiqzuf/78eaSmpiInJ8fitbi4OADA8ePHre577tw5VFVVoVevXhav9ezZEwBw4sQJ07Y9e/YgMTERUVFRKCwsRJ8+fRSf565duwAACQkJivfxNMxu05jdu5rKbmOsZY3ZJbVISkqCTqdzdTeIvBYzSOR6zCGRazGDRK7FDBK5HnNILYG1jqZ5U62jTnPqEB07dkRERAR++eUXi9dOnDiBmpoa9OvXD7dv38bBgwfx66+/WrSrrq6GiCAwMFD5SXsA5rBpzKFt9UBn1BJZcyQlOF8lsh9zROQ4zBeR6zGHRETkDTjekSOwrtA0b6wrNEVpLc8apdcrsl5IzsQxllyF43DTOA7f1VRNXen4qnTcPHLkCIC7N5m9t++vvPIKAOCBBx6ARqOxekNbIiIiIiIicj7eMJTIzRQUFCAyMhKHDx822z5w4EB06NABer0eHTp0QOfOnbFv3z6Lp958//33Zn9u37696elA99q8ebPpv6urqwEA4eHhZm1OnDiBgoICANafrlNHp9Nh0KBB2Lp1K0pKSsxe2759O+Li4rB//3506NABkZGR2LVrl8X7bdq0qcH3t/e4tmrTpg0GDhyIrVu34tatW1b7mZiYaNN7hoeHN/jUo3t/YmNjre7frl07rF27Fh9++KHF05cOHjwIAOjevbvVfSMiIhAQEIBjx45ZvFa3rVu3bgCAs2fPIjk5GT179sTmzZtx//33W33P9PR09OjRA3fu3DFtq62txeeff45evXohPj6+8V+IB2J2lWN272oqu4DyrDG7RPY5efIkRo0ahbCwMLRq1QpxcXGYN28erl+/btbu119/xejRo9GuXTsEBASgZ8+eWLRokV1PRiQi5Rk8cOAA/vKXvyA0NBSBgYHo27cvVq5c6aJeE3kWpTkEgNu3b2P8+PHQaDTIzMx0QW+JPA/no0SuxQwSuZ4t89E6VVVViI6OhkajsVr/oOZhrUM5b6p1AMrrENaMHTsWBQUFKC0tNduem5sLrVaL5557DtXV1UhISEBaWprF/hs3bgQAPP7444qP6c6YQ+WYQ+U5bOlaImuO5G2Uzldra2uxfPly9O7dG4GBgejYsSNefvllXLt2zUU9J1KPffv2YeTIkejUqRMCAgIQExODWbNmoaqqyqxdcz4fEnk7pflS2o6IbGdLvlhvJyIid8W6unqxrqCct9UVlFJSy7PGlusVWS8kapjSz5SsQagTx2HlvG0cbm5NXen4qnTcXLZsmdW+Z2VlAQCOHj0KEYFWq1X+CyIiIiIiIiKH4Q1DidxMv379oNVq8dJLL6GwsBBGoxEGgwFLlizBhQsXkJqaCgB4/fXXUVxcjOnTp+Pq1asoKSnBrFmzLBZ4k5OTUVtbi/nz56OiogIlJSWYMWMGKioqTG26du2K6Oho5Ofn49ixYzAajdi4cSNGjhyJ0aNHA7i78GztyUR13n//ffj6+uKpp55CUVERjEYjtm7divHjxyMgIAB9+vQBALz22msoLi7GrFmzUFpaiosXL2LWrFkwGAzN+n0pPa6tPvjgA1RVVeEf//gHfvvtN1y/fh3//ve/MWfOHMTHx+PZZ59t1vs2V1BQEDIzM3Hw4EGkpaXh7NmzuHnzJrZt24aJEyciNDQUr732GgDg3//+NzQaDWbOnAkACA4OxsyZM7Ft2za89dZbuHDhAm7evIk9e/Zg0qRJCA0Nxeuvvw4AmDJlCoxGI/Ly8hASEtJgf5KSknDmzBlMnjwZer0eJSUlmDRpEo4dO4YVK1ZAo9E4/peiMsyubZjdprMLKM8as0vUfMePH8ef//xnXL16Fdu2bcOVK1cwb948ZGRkICUlxdSupKQE8fHxqKioQGFhISorK/HBBx9g4cKFmDJligvPgMi9Kc1gfn4+HnnkEeh0Ouzfvx96vR4vvfQS0tLSeAEFkZ2U5hAAysvLkZiYiOLiYhf1lsjzcD5K5FrMIJHr2TIfvVd6ejp+++03J/bUO7DWYRtvqXUAyusQ1modb731FsLDw5GSkoLTp0/DaDRi7dq1yMzMxJw5c9ClSxeEhIRg/vz5KCgoQHp6Oi5evIiKigqsW7cO06ZNQ9++ffHyyy8741R4cpPJAAAgAElEQVRdjjm0DXNoyVoOW7qWyJojeRNb5qtTpkzBO++8g3fffRfl5eXIzc1Ffn4+kpOTG70wk8jTbdu2DYMGDYK/vz927tyJ0tJSLFy4EJ988gmGDx9uumlMcz8fEnkzpflS2o6IbGdLvlhvJyIid8W6urqxrmAbb6orKKWklgfYd70i64VE1tnymZI1CHXiOGwbbxqHldbUmzu+ctwkIiIiIiLyUEJELgdAcnNzFbc/f/68TJgwQTp37iz+/v4SHh4uCQkJZu9RW1sr7733nnTp0kX8/PwkMjJSZs+eLVlZWQJAvv/+exERqampkblz50q3bt0kICBAoqKiZNGiRZKfny8A5IcffhARkZ9//lkGDx4sOp1OQkNDJTk5WQ4fPizFxcUSGxsrWq1W3n77bRkxYoT4+vpa7feBAwdkxIgREhYWJlqtViIjI2XGjBmi1+vN+r1gwQLp0qWLaLVa6dSpk8ycOVPWrl0rAOTbb7+1+fer5LgN9bux89m9e7cMHz5c2rRpI35+ftK9e3eZPXu2XL9+XdH+jvD111/LY489Jq1bt5bAwEDp0aOHvPDCC3Ly5ElTmx9//FEAyIwZM8z2XbVqlTz66KMSEhJi+t2/+OKLcurUKRERuXHjhgBo9Cc1NdX0fuvXr5f+/fuLTqeT1q1bS1JSkuzbt69Z5zVq1CgZNWpUs/ZVytYcNgezaxtmV1l2m8qaK7Nrq9zcXHH29NQZ/76QucTERAkODnZ1NxR7+umnJSAgQEpLS822T58+XQBIQUGBiIi8+uqrEhQUJGVlZWbtFi9eLBqNRk6cOOG0PrckR+fSFbn3dp6awR49ekhkZKQYjUazdqmpqdKqVSuz+YO7cfQ81RnzYDLnqTk0GAzSq1cvmTt3ruzevVsASEZGhiu63KIcPV/kfNT5PDWDnI+q8/3JEjPofjgf9TyemsN7bdiwQQDIs88+KwDk6NGjzupui1PjfJS1Dtt4Q63DljpEQ7WOc+fOybhx4yQ8PFz8/f2lT58+kpWVZXGsvLw8SUhIMLX7wx/+IG+++aZUVlba1Gd3H9+YQ9swh43n0FG1RFfWHNU4fpJynjpfrVszXbFihVm7lStXSu/evd3ic6Ojxzeu07Qcd8tRfHy8REZGSnV1tdn2mTNnCgDZu3eviDTv86GrMTeex1PzpbSdO3L3z39kyVNzyHo7EakZxzvnc7fxztvr6u5wvRPrCrbxhrqCiMiMGTMarQ2MGzfO1FZJLa+51yvacgyRlqsX1sfvqXkHdxtjlX6m9IQahFLuWAfkOGwbbxmHRZTV1O0dX5s7btb93XPU9+74OZOIiIiIiKh5uMJIpALOXNhYsWKF2QIhkTtwhwK6ozG75A14w1Db6fV6mTZtmkRHR0tgYKC0a9dOkpOTpbCw0Kzd5s2bZdiwYRISEiJBQUESGxsr7733ntmN9ZKTk6V79+5y+PBhGTJkiAQHB0toaKi88MILUllZKWvXrpW+fftKUFCQREVFyYcffmh2jEGDBknnzp3l4MGDMnjwYAkODpZWrVrJ448/Lj///LOpnbUC+6FDh0zFPH9/f4mKipIZM2bItWvXbD7XlrZ8+XJZunSpxfY1a9YIAMnOzhYRkbZt20pycrJFu5MnTwoAWbBggUP76Sj84kvjmEF1ZNBgMAgAGTNmjEW7TZs2CQDJyclxaD8diRcwNY45VEcORUROnDghn332mYgIL2BS0fs7GjOongxyPqrO93c0ZpAZdAbORxvHHKonh3XKysokIiJCUlJSHP7FZWfwtPkoax2kFt48vjGH5A08bfy0B+er6pmvpqWlSXBwsMWDz9yJt974kDlyfI6WLl0qX331lcX27OxsASDr1q0TEds/H6qBt+ZGKeZLPflS2s4defPnPyWYQ/XkkPV2IlIzjncc75ri7XV1T7/eiXUF8hb8nprtOMaq5zOlJ9QglPK2OiDHYfJU7v45k4iIiIiIyFU8a4WRyE3xhqFEjfP0AroSzC55A94w1HZPPvmkdOrUSXbt2iW3bt2SM2fOyMiRI0Wn08nJkydFRGT79u2i1WplzJgxcunSJbl+/bqsXr1aNBqNvP7666b3GjFihLRp00bi4+Nlz549UlVVJR988IEAkMGDB0tiYqKcOXNGysvL5YUXXhAAsmfPHtP+TzzxhAQGBkrfvn1ly5YtcuPGDTly5Ih06dJF2rZta3pqdP0C+759+yQoKEiefvppKSoqkqqqKvnuu+/k/vvvl0ceeUTu3Lmj+FzrKy0tbfSpt3U/zXlaZt3vpqCgQM6fP2/1aX0iIr///rv4+fnJM888Y/Mx1IBffGkcM6iODOr1egEgKSkpFu327dvXYD7dBS9gahxzqI4c1scLmNTz/o7GDKojg5yPqvf9HY0ZZAadgfPRxjGH6sjhvUaPHi3h4eFy9epV3jBUBe9fH2sdpBbePL4xh+QNPG38tAfnq+qZr8bFxUl8fLzN76Mm3nrjQ+bIdTmaNm2aaDQa+eWXXxpt11i9wtW8NTdKMV/qz5fSdmrmzZ//lGAO1ZlD1tuJSG043nG8Y129cZ5+vRPrCuQt+D0123GMVc9nSk+oQSjlbXVAjsPkqdz9cyYREREREZGreNYKI5GbcubCBhcIyR15egFdCWaXvAFvGGqbW7duiY+Pj0ycONFse0VFhbRt21aWL18uIiIzZ84UnU4n586dM2s3ZMgQadOmjenPI0aMEACyYcMG07Y7d+6ITqcTPz8/uXz5smn70aNHBYAsXLjQtC0xMVEAyJo1a8yOs3btWgEgmZmZpnb3FtgHDRoknTp1sniS5T//+U/T+yk9V2cpKSmRjh07Sp8+faSmpsZ0Q8JFixZZbd++fXsZOHCgU/vYUvjFl4Yxg+rJoIhITEyMREZGSnV1tVnbpUuXCgB58cUXndrHlsQLmBrGHKorh/fiBUzqeX9HYgbVk0HOR9X7/o7EDDKDzsL5aMOYQ/XksM7q1asFgKxdu1ZEhDcMVcH718daB6mFN49vzCF5A08bP5uL81V1zVeDgoJkzJgx8sUXX8iDDz4ogYGBct9998nYsWPlwoULTu1fc3njjQ+ZI9fkqKSkRDIyMsTX11fmzp3bZNvG6hWu5o25UYr5Une+bMmh2nnz57+mMIfqzSHr7USkNhzvON41hzfV1T39eifWFchb8HtqtuEYq67PlJ5Qg1DK2+qAHIfJU7nz50wiIiIiIiJX8gERkRv54YcfoNFoFP0MGDDA1d0lov8fs0vU8vz9/XH//fdj/fr1yM/Px507dwAArVu3RllZGaZOnQoAyMjIQFVVFbp06WK2f1RUFCoqKlBeXm62PSEhwfTfWq0WYWFh6NatGzp06GDa3r59ewBASUmJRb8SExPN/jx06FAAwJEjRyzaVlZWYufOnRg6dCgCAgLMXktKSgIAFBYWKj5XZzAYDBgxYgQqKiqQk5MDX19f3Lp1C8Dd/yfW+Pv74+bNm07rIzkHM6ieDAJ3f88XL17Eiy++iOLiYlRUVGDVqlXIysoCAFOfybMwh+rKIXkfZlA9GeR81Dsxg8wguR5zqJ4cAsClS5cwdepUPPPMM0hJSXFaf8i7sNZB5HrMIZFynK+qZ776+++/49atW/jpp5+QnZ2NVatWobS0FLm5udi5cyf69++Pa9euOa2PpBxz5NwcnT59GhqNBhEREZg/fz4WL16Md955p8H2rFe4N+ZLnfmyNYfk3phDdeaQiIhaFsc79ayPsK5OrsK6ApFjcIxVz2dK1iBIzTgOExEREREREbUs3jCUyMtMnDgRImJatHY3SUlJEBFFP3v27HF1d4laDLNLRPX5+Pjgu+++Q1hYGEaOHInQ0FA88cQTyMzMhMFgMLUzGo1YsmQJ4uPj0aFDBwQEBECr1SI7OxvA3eJwHV9fX7Rp08bsOBqNBmFhYRbb6u8LAH5+fmjbtq3Ztrp9r1y5YnEOly9fRm1tLVavXm1R6OvUqRMA4MKFC4rP1dGKi4sxcOBAFBUVYcOGDXjwwQcBAK1atQIA3L592+p+1dXVpjbkOZhB9WQQAJ555hls3LgRp06dQlxcHKKjo/H9998jLy8PABASEuK0fpLzMIfqyiF5H2ZQPRnkfNQ7MYPMILkec6ieHAJAamoqAJgeHEHqxFoHkesxh0Teg/NV9cxXfXx84OPjg4qKCnzzzTf44x//CJ1OhyeffBKffvopLl++jCVLljitn6Qcc+TcHMXExEBEYDAYkJOTg2XLlmHAgAEWNw0AWK/wBMyXOvNlSw7J/TGH6swhERG1LI536lkfYV3dfbGuQETWcIxVz2dK1iA8G8dhIiIiIiIiIroXbxhKREREROSmHn74YRQVFWH79u2YPn06Kisr8cYbb6BHjx44dOgQACAlJQUzZ87E8OHDsWPHDhgMBhiNRkyYMKHF++PjY/nxQkQafK1OXQHT2s8333yj+FwdadeuXRgwYABu376NHTt2YMiQIabX6p5WWlpaarFfTU0NDAaD6QsD5FmYQXVksE5ycjIOHTqE6upq6PV65Obmms47Ojra4X0k12AO1ZVD8j7MoDoyyPmo92IGmUFyPeZQHTlcuXIlNm3ahE8//RQREREO7wsRERGRu+B8VR3zVY1Gg3bt2qF79+647777zPYbPHgwNBqNU/pIzcMcOS9Hde677z787W9/w7fffosDBw5g8eLFZq+zXuE5mC/15cvWduT+mEP15pCIiFoOxzt1rI+wrk5E5Hk4xqrjMyVrEERERERERERE3oM3DCUir5SUlASdTufqbhCRDZhbIus0Gg0SEhKwYMEC7N27F7t27UJlZSXmz5+Py5cv41//+hdSUlIwb948dO/eHcHBwdBqtTh37lyL96W6uhoVFRVm2/R6PQCgffv2Fu0jIyPh4+OjuC+Nnas1ZWVlFk/6tPZTVFTU6HH37NmDxMREREVFobCwEH369DF7vWPHjoiIiMAvv/xise+JEydQU1ODfv36KTpHcj/MoOsz2Jhdu3YBABISEhTvQ+6HOVR3DsnzMYOuzyDno96NGWQGyfWYQ9fn8MiRIwDuXmhy7/u+8sorAIAHHngAGo0GNTU1is6TqKWwrkGkXswneRPOV10/XwWAhx56CFevXrXYXlNTAxGBv7+/onMk12COHJej8+fPIzU1FTk5ORavxcXFAQCOHz9u2sZ6hedhvlyfL1tzSJ6HOXR9DomIyPE43rl+fYR1dXJnrCkQNYxjrDo+U7IGQZ6OYzERERERERHRXbxhKBGRyhmNxiYLA2lpaab2v/76K0aPHo127dohICAAPXv2xKJFi1BbW+vCsyDyTrW1tVi+fDl69+6NwMBAdOzYES+//DKuXbvW4D5VVVWIjo6GRqPBsWPHnNhbcjcFBQWIjIzE4cOHzbYPHDgQHTp0gF6vR3V1NQAgPDzcrM2JEydQUFAA4D9PzGwpP/74o9mft2zZAuDukynr0+l0GDRoELZu3YqSkhKz17Zv3464uDjs379f0blaEx4e3uCTPu/9iY2NbfB8zp49i+TkZPTs2RObN2/G/fffb7Xd2LFjUVBQYPHk69zcXGi1Wjz33HMNHoPcEzOorgymp6ejR48euHPnjmlbbW0tPv/8c/Tq1Qvx8fENHoPcF3OorhyS92EG1ZVBzke9DzPIDJLrMYfqyeGyZcusvm9WVhYA4OjRoxARaLXaBo9DRHcprWs0p/5BRPY5cOAA/vKXvyA0NBSBgYHo27cvVq5cadFu3759GDlyJDp16oSAgADExMRg1qxZqKqqckGvyZU4X1XPfBUAnn/+eRgMhgbPnw8+UyfmyPE5ateuHdauXYsPP/zQ4rttBw8eBAB0794dAOsVnob5Uk++bMkheRbmUD05JCIix+F4p671EdbViZzr9u3bGD9+PDQaDTIzM622UXoNImsPVB/HWHV9pmQNgkhdMjIyGr0fwL0PvT558iRGjRqFsLAwtGrVCnFxcZg3bx6uX7/uwjMgIiIiIiIiteINQ4mIVC4wMLDBgsD69esBACkpKQCAkpISxMfHo6KiAoWFhaisrMQHH3yAhQsXYsqUKa48DSKvNGXKFLzzzjt49913UV5ejtzcXOTn5yM5ObnBomZ6ejp+++03J/eU3FG/fv2g1Wrx0ksvobCwEEajEQaDAUuWLMGFCxeQmpqKrl27Ijo6Gvn5+Th27BiMRiM2btyIkSNHYvTo0QDufnnj999/b5E+BQUFYcGCBfjxxx9x8+ZNHDlyBLNnz0ZERATGjBljdZ/3338fvr6+eOqpp1BUVASj0YitW7di/PjxCAgIQJ8+fRSdq6NMmTIFRqMReXl5CAkJabDdW2+9hfDwcKSkpOD06dMwGo1Yu3YtMjMzMWfOHHTp0sVhfSTXYAbVlcGkpCScOXMGkydPhl6vR0lJCSZNmoRjx45hxYoV0Gg0DusjuQ5zqK4ckvdhBtWVQc5HvQ8zyAyS6zGH6sohEbUMpXWN5tQ/iKj58vPz8cgjj0Cn02H//v3Q6/V46aWXkJaWZnaR77Zt2zBo0CD4+/tj586dKC0txcKFC/HJJ59g+PDhfMiol+F8VV3z1bFjx2Lw4MH4+9//ju3bt+PmzZvYsmULpk6dipiYGEycONFhfaTmY44cn6OgoCBkZmbi4MGDSEtLw9mzZ3Hz5k1s27YNEydORGhoKF577TUA/HzoaZgv9eTLlhySZ2EO1ZNDIiJyHI536lofYV2dyHnKy8uRmJiI4uLiBtsovQaRtQeyhmOsuj5TsgZBpC51D9stLy+3el+AuodeHz9+HH/+859x9epVbNu2DVeuXMG8efOQkZFhumcAERERERERkRkhIpcDILm5ua7uhldJTEyU4OBgV3fDLlVVVdK5c2dJSUkxbXv11VclKChIysrKzNouXrxYNBqNnDhxwtndbBGjRo2SUaNGOfQYzKH6uVtud+/eLQBkxYoVZttXrlwpvXv3tprHDRs2CAB59tlnBYAcPXrUWd1VhdzcXHH29NQZ/7440vnz52XChAnSuXNn8ff3l/DwcElISDD79+znn3+WwYMHi06nk9DQUElOTpbDhw9LcXGxxMbGilarlbfffltGjBghvr6+Fsfo2rWr9O/f32xbaWmpAJDJkyebtiUmJkqbNm3kwIEDMnToUNHpdNKqVSt54okn5Pjx42bt6mf5wIEDMmLECAkLCxOtViuRkZEyY8YM0ev1Np1rS7tx44YAaPQnNTXV1P7cuXMybtw4CQ8PF39/f+nTp49kZWU5rH/O4OhcuiL3LYkZVFcG169fL/379xedTietW7eWpKQk2bdvn8P65yyOnqe6+zyYOVRPDmfMmNFou3Hjxjmsn47k6Pki56PMYGM4H+V8tCnMIDPoDJyPNo45VFcO68vKynL7dVbOR92bp9Y1mlP/UBuOb+Ru+ezRo4dERkaK0Wg0256amiqtWrUyjdnx8fESGRkp1dXVZu1mzpwpAGTv3r1O67Mrcfz8D85X1TVfvXHjhsyePVu6du0qfn5+0qFDB0lLS5MrV644rI8tydHjm1rXaZgjx+aoztdffy2PPfaYtG7dWgIDA6VHjx7ywgsvyMmTJ0XE/s+HruKtuVGK+VJHvmxt5274+a9xzKF6csh6OxGpGcc7jneNYV2d1zt5A3erKRgMBunVq5fMnTvXVNfLyMiwaKf0GkRvqT3we2q24xirns+UIu5fg1CKdUDv5G5j8auvvioA5M6dO422e/rppyUgIEBKS0vNtk+fPl0ASEFBgSO76VKc3xIRERERETWPZ60wErkpd1/Y0Ov1Mm3aNImOjpbAwEBp166dJCcnS2FhoVm7zZs3y7BhwyQkJESCgoIkNjZW3nvvPbOLWpKTk6V79+5y+PBhGTJkiAQHB0toaKi88MILUllZKWvXrpW+fftKUFCQREVFyYcffmh2jEGDBknnzp3l4MGDMnjwYAkODpZWrVrJ448/Lj///LOpnbUFwkOHDpkW9/39/SUqKkpmzJgh165ds/lcnSE9PV1CQkLk0qVLpm1t27aV5ORki7YnT54UALJgwQJndrHFsIDe8phbx+c2LS1NgoODLS7ca0hZWZlERERISkqKR1zI3hy8Yah7S0xMFJ1O5+puUAvjF1/cBzPouXgBk/tgDj0Tv1jmPphBz8T5qPtgBj0X56Pugzn0TJyP/gfrGuqpa9ha/1Ajjm8ti/l0bD4NBoMAkDFjxli8tmnTJgEgOTk5IiKydOlS+eqrryzaZWdnCwBZt26dw/qpJhw/1YnzVffHGx+6HnPkfpgb98F8eS5+/nMfzKFn4ucnIs/A8a7lcLzzTLzeyTasKTi+5nfixAn57LPPREQavWGo0msQvaX2wO+puTeOsd6DdUD7cSx2/Fg8duxYCQoKarLd8uXLZenSpRbb16xZIwAkOzvbAb1TB0+a3xIRERERETmTD4iI7PTcc88hLy8Pq1evRnl5OQoLCxEUFIRhw4bh1KlTAIAdO3YgMTERbdu2RVFREUpLSzFnzhzMmTMHs2fPNr2Xv78/ysrK8Oqrr2Lx4sUoKSnBW2+9hdWrV+Ppp59GdnY28vPzcfnyZcTHx+P1119HYWGhaf+AgACUlpbiH//4B/7f//t/uHr1Kvbs2YPTp09j2LBhKCsrs3oO+/fvx6OPPora2lrs2rULer0ey5cvx5dffonhw4ejpqZG8bnWV1ZWBo1G0+RPUVGR4t/5uXPn8PHHH2PatGno2LEjAODChQvQ6/WIi4uzaB8TEwM/Pz8cOHBA8THIszG3js/tzp078ac//QkBAQGK/p+88sorqKmpwUcffaSoPZEaiYiru0Dk1ZhBItdjDolcixkkci1mkMj1mEPyZKxrqKeuYWv9gzwf8+nYfNaN7xqNxuK1sLAwAMDhw4cBANOmTcPzzz9v0e7w4cPQaDTo3bu31WMQOQvnq0T2Y46IHIf5InI95pCIiLwBxzvydqwpOL7mFxsbi0mTJjX6/8GWaxBZeyB3wTGWSBmOxY4fi69du4aQkJAm/19MnToV06ZNs9h+6dIlAEB0dHST70FERERERETehTcMJSK7GI1GbN68GcnJyRg4cCACAwMRFRWF7OxsBAQEYNOmTQCAb7/9FoGBgcjIyEDHjh0RHByMcePGYfDgwVi1apXZe1ZUVODNN99E//79odPpkJ6eDp1Oh127diE7OxtRUVEIDQ01LSz+9NNPpn19fX1hNBoxa9YsDBkyBK1atcIDDzyADz74AHq9Hl988YXV85g+fTrCwsKQl5eHnj17QqfT4amnnsKiRYuwd+9erFu3TvG51hceHg4RafInNjZW8e/93XffRWBgINLT003brly5YjpefT4+PggLCzO1Ie/G3Dont7/99hs6deqEnJwcPPTQQwgKCkJYWBjGjRuHixcvmrVds2YN8vLy8PHHH6Ndu3ZN/j8kIiIiIiIiIiIiIvIWrGuoq65hS/2DPB/z6fh8hoWFISYmBjt37sTt27fNXtuxYwcA4OrVq1b3vXLlCjIzM/HRRx/hnXfesXrhLxERERERERERERGRM7Cm4JprEK2x5xpE1h6IiNwXx2LnjMXXrl2Dn58f5s2bh969eyMoKAgdO3bElClTYDAYGv1/dOXKFSxbtgx9+vRBfHx8o22JiIiIiIjI+/CGoURkF39/f9x///1Yv3498vPzcefOHQBA69atUVZWhqlTpwIAMjIyUFVVhS5dupjtHxUVhYqKCpSXl5ttT0hIMP23VqtFWFgYunXrhg4dOpi2t2/fHgBQUlJi0a/ExESzPw8dOhQAcOTIEYu2lZWV2LlzJ4YOHYqAgACz15KSkgAAhYWFis/V0c6fP48vvvgCU6dOxX333WfafuvWLQB3/59Y4+/vj5s3bzqlj6RuzK3jc/v777/j1q1b+Omnn5CdnY1Vq1ahtLQUubm52LlzJ/r3749r164BuPvEr6lTp+KZZ55BSkqKQ/pDREREREREREREROSuWNdQT13DlvoHeQfm0znfF8jIyMDFixfx4osvori4GBUVFVi1ahWysrIAwNSXOqdPn4ZGo0FERATmz5+PxYsX45133nFY/4iIiIiIiIiIiIiImsKagvOvQWxIc65BZO2BiMj9cSx2zlhcW1uL6upqBAcHY/PmzSgpKcHy5cuRl5eHfv36oaqqyup+BoMBI0aMQEVFBXJycuDr6+uwPhIREREREZF74g1DicguPj4++O677xAWFoaRI0ciNDQUTzzxBDIzM82edGM0GrFkyRLEx8ejQ4cOCAgIgFarRXZ2NoC7F6HV8fX1RZs2bcyOo9FoEBYWZrGt/r4A4Ofnh7Zt25ptq9vX2tPtLl++jNraWqxevRoajcbsp1OnTgCACxcuKD5XR8vJyUFNTQ3S0tLMtrdq1QoAcPv2bav7VVdXm9qQd2NuHZ9bHx8f+Pj4oKKiAt988w3++Mc/QqfT4cknn8Snn36Ky5cvY8mSJQCA1NRUADBd0Efkrn744Qdcv37d1d0g8lrMIJHrMYdErsUMErkWM0jkeswheTLWNdRT17Cl/kHegfl0zvcFnnnmGWzcuBGnTp1CXFwcoqOj8f333yMvLw8AEBISYtY+JiYGIgKDwYCcnBwsW7YMAwYMsLhwi8iZOF8lsh9zROQ4zBeR6zGHRETkDTjekbdjTcH51yA2pDnXILL2QGrGMZZIGY7FzhmLd+/ejdLSUsyaNQsRERFo06YNRo0ahaysLJw5cwbvv/++xT7FxcUYOHAgioqKsGHDBjz44IMO7SMRERERERG5J94wlIjs9vDDD6OoqAjbt2/H9OnTUVlZiTfeeAM9evTAoUOHAAApKSmYOXMmhg8fjh07dsBgMMBoNGLChAkt3h8fH8t/2kSkwdfqTJw4ESJi9eebb75RfK6O9r//+7/o168funXrZra97mlLpaWlFvvU1NTAYDCYFjyJmFvH5niBT+oAACAASURBVFaj0aBdu3bo3r077rvvPrPXBg8eDI1Gg0OHDmHlypXYtGkTPv30U0RERDikL0RERERERERERERE7o51DXXUNZS2I+/CfDrn+wLJyck4dOgQqqurodfrkZubazqf6Ohoq/vcd999+Nvf/oZvv/0WBw4cwOLFix3aRyIiIiIiIiIiIiKixrCm4NxrEBtizzWIrD0QEbk3jsWuG4uTkpKg0WhQWFhotn3Xrl0YMGAAbt++jR07dmDIkCFO7xsRERERERG5B94wlIhahEajQUJCAhYsWIC9e/di165dqKysxPz583H58mX861//QkpKCubNm4fu3bsjODgYWq0W586da/G+VFdXo6KiwmybXq8HALRv396ifWRkJHx8fBT3pbFztaasrMziSUXWfoqKipo89pkzZ3D48GEMGzbM4rWOHTsiIiICv/zyi8VrJ06cQE1NDfr166foHMk7MLeOze1DDz2Eq1evWmyvqamBiMDf3x9HjhwBcLeIcu/7vvLKKwCABx54ABqNBjU1NYrOk0ippKQk6HQ6V3eDyGsxg0SuxQwSuR5zSORazCCRazGDRM3Huobr6xq2tCPvwnw65/sC9e3atQsAkJCQgPPnzyM1NRU5OTkW7eLi4gAAx48ft/kY5H04XyVqGcwSkeMwX0SuxQwSEZE34HhH5FisKbimpnAvpdcgsvZAjsBxlsj1OBY7biy+ffs2Dh48iF9//dXquYoIAgMDTdv27NmDxMREREVFobCwEH369FF0XkREREREROSdeMNQIrJLQUEBIiMjcfjwYbPtAwcORIcOHaDX61FdXQ0ACA8PN2tz4sQJFBQUAPjPE39ayo8//mj25y1btgAABg8ebNFWp9Nh0KBB2Lp1K0pKSsxe2759O+Li4rB//35F52pNeHh4g08quvcnNja2yfPauXMnAOBPf/qT1dfHjh2LgoICiyf85ebmQqvV4rnnnmvyGOT5mFvn5Pb555+HwWBo8LwSEhKwbNkyq++blZUFADh69ChEBFqttsHjEHmTkydPYtSoUQgLC0OrVq0QFxeHefPm4fr16xZtb9++jfHjx0Oj0SAzM9Om4yjdt6l2GRkZjRYHeTNgckdK8nHgwAH85S9/QWhoKAIDA9G3b1+sXLlS0fv/+uuvGD16NNq1a4eAgAD07NkTixYtQm1tbbPaKe0zkTtwxjjYksfgOEieSGlGbMlSffv27cPIkSPRqVMnBAQEICYmBrNmzUJVVZWpjZJ8GY3GJr+slpaW1uK/IyJHak62qqqqEB0dDY1Gg2PHjjV5DKXzTKVzXnvmxkRq44xxsLa2FsuXL0fv3r0RGBiIjh074uWXX8a1a9fM2inNqpJxldwD6xrqqWvY0o68A/PpnHymp6ejR48euHPnjmlbbW0tPv/8c/Tq1Qvx8fFo164d1q5diw8//NBiTDx48CAAoHv37g0eg8jdKZ2HKp1zWtOSNQyun5JaNZUle9cdbfm7b8u6CuuB5A6UrlPYs7YCNJ4HWzPM9U3yJEozaMv3Ueprat/mjKMc44iIyBZKxzt7amhKx8qm1mD4vRbvxJqCc69BbIqSaxBZeyCyrrHvpNmzttPSa6L2rjOR5+FY7PixuLq6GgkJCVbnshs3bgQAPP744wCAs2fPIjk5GT179sTmzZtx//33W31PIiIiIiIiojq8YSgR2aVfv37QarV46aWXUFhYCKPRCIPBgCVLluDChQtITU1F165dER0djfz8fBw7dgxGoxEbN27EyJEjMXr0aAB3C86///57i/QpKCgICxYswI8//oibN2/iyJEjmD17NiIiIjBmzBir+7z//vvw9fXFU089haKiIhiNRmzduhXjx49HQEAA+vTpo+hcHe3kyZMAgOjoaKuvv/XWWwgPD0dKSgpOnz4No9GItWvXIjMzE3PmzEGXLl0c3kdSP+bWObkdO3YsBg8ejL///e/Yvn07bt68iS1btmDq1KmIiYnBxIkTHXZsIk90/Phx/PnPf8bVq1exbds2XLlyBfPmzUNGRgZSUlLM2paXlyMxMRHFxcU2H0fpvkra1X2prby83GpxkDcDJnej5O99fn4+HnnkEeh0Ouzfvx96vR4vvfQS0tLSmrxwoaSkBPHx8aioqEBhYSEqKyvxwQcfYOHChZgyZYrN7ZT2mcgdOGMcbOljcBwkT6M0I7Zkqb5t27Zh0KBB8Pf3x86dO1FaWoqFCxfik08+wfDhw01fulaSr8DAwAa/pLZ+/XoAaLI/RGrS3Gylp6fjt99+U3QMpfNMpXNee+bGRGrjjHEQAKZMmYJ33nkH7777LsrLy5Gbm4v8/HwkJyebvmiuNKtKx1VyD6xrqKuuwfoH3Yv5dE4+k5KScObMGUyePBl6vR4lJSWYNGkSjh07hhUrVkCj0SAoKAiZmZk4ePAg0tLScPbsWdy8eRPbtm3DxIkTERoaitdee81hfSRyJVvmoUrmnNa0dA2D66ekRkqyZO+6o9K/+7asq7AeSO5A6TqFvWsrTeXBlgxzfZM8idIM2vJ9lPqU7GvrOMoxjoiIbKF0vLOnhmbLWNnUGgy/1+KdWFNw7jWITVFyDSJrD0TWNfSdNHvWdlp6TdTedSbyTByLHT8Wh4SEYP78+SgoKEB6ejouXryIiooKrFu3DtOmTUPfvn3x8ssvA7g7ZzYajcjLy0NISIhD+kNEREREREQeRojI5QBIbm6uq7vRbOfPn5cJEyZI586dxd/fX8LDwyUhIcHsnH7++WcZPHiw6HQ6CQ0NleTkZDl8+LAUFxdLbGysaLVaefvtt2XEiBHi6+trcYyuXbtK//79zbaVlpYKAJk8ebJpW2JiorRp00YOHDggQ4cOFZ1OJ61atZInnnhCjh8/btYuODjY7P0OHDggI0aMkLCwMNFqtRIZGSkzZswQvV5v07k60quvvioA5OTJkw22OXfunIwbN07Cw8PF399f+vTpI1lZWU7pn6OMGjVKRo0a5dBjuHsObcXcOie3N27ckNmzZ0vXrl3Fz89POnToIGlpaXLlypVG98vKyhIAcvToUYf3UU1yc3PF2dNTZ/z7okbW8qR2Tz/9tAQEBEhpaanZ9unTpwsAKSgoEBERg8EgvXr1krlz58ru3bsFgGRkZCg6htJ9lbarG7fv3LnTjDNWB0fn0hW5VwN3zKDSv/c9evSQyMhIMRqNZttTU1OlVatWZmN0fa+++qoEBQVJWVmZ2fbFixeLRqOREydO2NTOnn8P1MTR81RvmweLuGcGnTEOtvQxPGEcFHH8fJHzUfehNCNK21kTHx8vkZGRUl1dbbZ95syZAkD27t0rIvblq6qqSjp37iwpKSk27+sKnI86hidn8F4bNmwQAPLss88qWmdROs9UOue1Z26sJpyPtjxPzqA942Dd3HLFihVm21euXCm9e/e2+TOh0nFV7Tgf/Q/WNdRV12hu/UMtOL61LObTOflcv3699O/fX3Q6nbRu3VqSkpJk3759Fu2+/vpreeyxx6R169YSGBgoPXr0kBdeeKHR7xh4Go6f9vHk+arSOac1LV3DcMf1U0ePb562TuPJWbJG6bqj0r/7StdV1F4PZG4cwx3zpXSdwp4c2pMHaxnm+qY63l+NPDmDSudy1tizr7UMqn2MU8rTPz8ReQuOd+5B6XhnTw1N6XhnzxqMu32vRYTXO9mKNQXH1xRmzJghABr8GTdunKmt0msQvaH2wO+pOY87jrP3auw7afas7bT0mqg9fVEz1gHtx7HYOfX9vLw8SUhIMI2xf/jDH+TNN9+UyspKEbn7vZvGxmsAkpqa6vB+uoonzW+JiIiIiIiciSuMRCrAhY2Wk5iYKDqdztXdoBbGArpnY26pDm8Y2rBBgwZJUFCQVFVVWbz21ltvCQDZunWriIhs3rxZhg0bJiEhIRIUFCSxsbHy3nvvmRWN6xfK4uPjpX379hbv/dFHHwkA2bJli2nboUOHTAU1f39/iYqKkhkzZsi1a9da8IwtLV++XJYuXWqxfc2aNQJAsrOzRUTkxIkT8tlnn4mI2PxlaaX7Km03duxYCQoKUnRsteIXX+5iBpX9vTcYDAJAxowZY7H/pk2bBIDk5OQ0eIy2bdtKcnKyxfaTJ08KAFmwYIFN7ez590BNeAETMyjinHGwpY/hCeOgCL9YVoc5VJ4Rpe2sWbp0qXz11VcW27OzswWArFu3TkTsy1d6erqEhITIpUuXmrW/s3E+ehczaHu2ysrKJCIiQlJSUhQ/mEXJPFPpnNfeubGacD7KDIo4ZxxMS0uT4OBgiwsf6lP6mVDpuKp2nI+qE+sa7o/jm+diPknE+8ZPzleVz0OVzjmtaekahjuun3r6jQ+ZJfs+0yldd1Tyd9+WdRW11wM9PTdKMV/K1ynsyaE9eaifYa5vquf9WwIzqDyDSudy1tizr7VxVO1jnFJq+/xERM3D8c6zxjt7amhKxzt71mDc7XstIrzeyZ2xpkD34vfUGsZx9j+a+k5ac9d2HLEmas86k5p5Wx3Q03Es9l6c3xIRERERETWPD4iIPIyIuLoLRGQj5paocePHj8etW7fw3XffWby2du1aREVF4bHHHsOOHTuQmJiItm3boqioCKWlpZgzZw7mzJmD2bNn292P/fv349FHH0VtbS127doFvV6P5cuX48svv8Tw4cNRU1Njdb+ysjJoNJomf4qKiho89tSpUzFt2jSL7ZcuXQIAREdHAwBiY2MxadKkZp2f0n2Vtrt27RpCQkKa1RdSF2ZQ2d/7uvFco9FYvBYWFgYAOHz4sNV9L1y4AL1ej7i4OIvXYmJi4OfnhwMHDihup7TP5B6YQeeMgy19DI6DnoU5VJ4Rpe2smTZtGp5//nmL7YcPH4ZGo0Hv3r0BND9f586dw8cff4xp06ahY8eONu9PrsMM2p6tV155BTU1Nfjoo48UnZvSeabSOa89c2NSH2bQOePgzp078ac//QkBAQENtrHlM6HScZWouVjXIFIv5pO8DeeryuehSuac1jiihsH1U/Vhlpr/mc6WdUclf/dtWVdhPdA9MF/K1ynsWVtpbh6sZZjrm56FGVSWQVvmcvXZs29D4yjHOCIi23C8Uz7nbG4NzZbxrrlrMPxeC7kCawpETeM4+x9NfSetuWs7jlgTtWediciZOBYTERERERERKccbhhIRERERqdzo0aMRGBiI3Nxcs+179uzBmTNn8NJLL0Gj0eDbb79FYGAgMjIy0LFjRwQHB2PcuHEYPHgwVq1aZXc/pk+fjrCwMOTl5aFnz57Q6XR46qmnsGjRIuzduxfr1q2zul94eDhEpMmf2NhYm/pz5coVLFu2DH369EF8fLzd59fSrl27Bj8/P8ybNw+9e/dGUFAQOnbsiClTpsBgMLi6e2QDZlCZsLAwxMTEYOfOnbh9+7bZazt27AAAXL161eq+V65cMfW1Ph8fH4SFheHKlSuK25FnYQatc8Y4aM8xOA56FubQOqUZaW6Wrly5gszMTHz00Ud45513TBddNDdf7777LgIDA5Genq78JEkVmEHrGsrWmjVrkJeXh48//hjt2rVT/F51fa3v3nmm0jmvPXNjUh9m0LqWHgd/++03dOrUCTk5OXjooYcQFBSEsLAwjBs3DhcvXjS9V9051dfUZ8KGxlUiIiIid8f5qnXW5qFK5pwNvVddX+trbg2D66fqwyxZp+QznS3rjkr+7nNdxfMwX5ZsWadwdE3QWoaZQ8/CDFqylkF71x6buy/rd0RELYPjnSWlc05b2tX1tb76411z12A4LhIRqRPH2bua8500QNnajrPWYtR+DRYRERERERERETWONwwlIiIiIlK5Nm3a4K9//St++OEHVFZWmrZ/9dVX0Gg0GD9+PAAgIyMDVVVV6NKli9n+Uf8fe/ceFlW1/3H8M4DOKFBqVGia4eWIilqWF7xk1pNIaZqpWBZZ3k6loWnazcLqmKap2MWyi0ZZiuWN4pTlNVHzxkEtsNSyzONd0aOCwOzfH/40FYQ93PbM8H49D8/TM7Nn7+/YfGetWd+11g4JUUZGho4ePVrkGI4fP67k5GR17Ngxzx2fO3fuLEn68ccfi3x+Vx05ckTdunVTRkaG4uPj5evrW2bXNsvpdCorK0v+/v5aunSp9u3bp2nTpmnevHlq0aKFTpw4YXWIMIkcNG/ixInas2ePHnroIe3cuVMZGRmaNWuWpk+fLknKzs7O93WnT5+WJFWsWDHf5ytWrKhTp06ZPg7ehRzMqyzaweJeg3bQu5CHeZnNkaLk0o4dO2Sz2RQcHKyxY8dq/PjxGjNmzPnni5Jff/zxhz7++GMNHTpUVatWLfobhyXIwbwul1t//fWXhg4dqu7duysqKsr0+VzpZ5rt8xa1bwz3Qw7mVdLtYG5urk6fPq1ly5Zp5syZmjVrlg4ePKi5c+cqOTlZrVq10rFjx4r0m7CwdhUAAMDT0V/NK79+qNk+Z35Ko4bB+Kn7IZfyMvObztVxR7OffcZVvAv59TdXxylKuyZYUA6Th96DHPxbQTlYnPkoRX0t9TsAKDm0d38z2+d0tW9qtr0r6hgM7SIAuC/a2aLPSXNlbKe0x2I8YQ0WAAAAAAAACsaGoQC8yjfffKP//e9/VocBwAXkLWBOdHS0srKytHDhQklnN1JISEhQhw4dFBISIknKzMzU5MmT1bZtW1WvXl12u11+fn6aOXPm+dcU1d69e+V0OvXpp5/KZrNd9HfddddJkv78889ivktzdu7cqfDwcKWnp+urr77STTfdVCbXddXatWt18OBBjRo1SsHBwbryyivVs2dPTZ8+Xbt27dKECROsDhEuIAfN6d69u5KSkvTLL7+oUaNGqlOnjv79739r3rx5kqTAwMB8X1e5cmVJynNH3HOysrJUuXJl08fB+5CDfyuLdrAkrkE76H3Iw7+ZzZGi5lK9evVkGIaOHDmi+Ph4TZ06Va1btz4/YbYo+RUfH6+cnBwNHDiw6G8cliIH/1ZQbvXv31+Szk+UNsuVfqbZPm9R+8ZwT+Tg30qjHfTx8ZGPj48yMjI0f/58NW3aVAEBAbrzzjv17rvvau/evZo8eXKRfhMW1q4CRUFdA3Bf5CfKK/qrf7tcP9RsnzM/pVHDYPzUPZFLfzP7m87VcUezn33GVbwP+XWWK+MUZVETLCiHyUPvQg6eVVAOFmc+SlFfS/0OAEoW7d1ZZvucrtbQzLZ3RR2DoV2EFagpAOaV93a2KHPSXB3bKc2xGE9Zg4Xyh7YYAAAAAADXsGEoAAAA4AEiIiJ0zTXXKCEhQZK0bNky7d+/X/369Tt/TFRUlEaOHKlOnTpp9erVOnLkiDIzM/Xoo4+WWBwDBgyQYRj5/s2fP7/ErnM5a9asUevWrXXmzBmtXr1at912W6lfs6R17txZNputTO4UjpJDDpoXGRmplJQUZWVl6fDhw5o7d658fM4OP9SpUyff11SvXl2SdPDgwTzP5eTk6MiRI7ruuutMHwfvQw6eVRbtYGlfg3bQc5GHZ5nNkZLIpapVq+ree+/VokWLtGnTJo0fP77A4wvKry+++EItWrTQDTfc4HIccA/k4FkF5dZHH32kb7/9Vu+++66Cg4NdOq+r/Uyzfd6i9I3hnsjBs0qrHbTZbLr66qtVt25dVa1a9aLnOnToIJvNppSUlGL9JnS1XQUAAPAk9FfPKqgfarbPmZ+yrGEwfmotcuksV37TldS4Y36ffcZVvAv5dbHCxinKam5MYTlMHnoPcvBi+eVgcfpyRX0t9TsAKFm0dxczWxsze5zZ9q6oYzC0iwDg3spzO1uUOWlFHdspjbEYb1iDBQAAAAAAgLPYMBSAJTp37qyAgACrwwDgInIXsI6fn5/uv/9+LVmyRMeOHdPnn3+ugIAA9ezZU9LZO2YuXrxYUVFReumll1S3bl35+/vLz89Pu3fvLvDcvr6++d6tc//+/ef/u2bNmvLx8Sn0XPk5dOhQnrt45veXnp5e4HnWrVuniIgIhYSE6Mcff1RYWJjLsZSVM2fOaPPmzfr111/zPJeVlSXDMORwOCyIDEVFDhbPmjVrJEnt2rXL9/kaNWooODhYP/30U57n0tLSlJOToxYtWpg+Dt6HHCybdrCkrkE76J3IQ/M5UpRc+uOPP9S/f3/Fx8fnea5Ro0aSpJ9//rlI+bVr1y6lpqbqjjvuKDQOuC9ysPDc2rJli6Szk88vPO9jjz0mSWrSpIlsNptycnLynLsk+pmF9XldPQ7uhRws3XZQkpo3b64DBw7keTwnJ0eGYahixYqmc9VsuwrvR00DcF/kJ1Cy6K+a64ea6XPmp6RrGIyfui9yybXfdK6OO5bEZ59xFc9VnvPL1XGKspobU9TaAXnomcjBwnOwOHWCoryW+h0AlDzau8Lbu+LU0Fxp71wdg6FdRFFRawDKTnluZ12dk1bSYzvFGYvxpDVYcG+0uQAAAAAAuAc2DAUAF505c0bR0dGy2WyaNGlSnucnTpxYYPEgvwXpF9q8ebPuvvtuValSRRUrVlT9+vU1evRonThx4qLjfv31V/Xq1UtXX3217Ha7GjRooNdee01Op/Oi4zZs2KAePXrouuuuk91uV7169TRq1Kg85wO8XUG5m5mZWWjhb+DAgaavdeLECdWpU0c2m03btm276Lnt27erZ8+eqlatmipXrqxGjRrppZde0v/+97+Ljtu0aZPuuusuValSRQ6HQ82aNdNHH31U9H8AeIXo6GhlZ2crMTFRCxcuVM+ePeXv7y/p7AIaSQoKCrroNWlpaVq5cqUkyTCMfM977bXXnr9754WWLl16/r8DAgLUvn17rVixQvv27bvouB9++EGNGjXSxo0b8z1/UFDQZe/ieeFfaGjoZd/777//rsjISDVo0EBLly7VNddcc9lj3UFWVpbatWuX73dHUlKSJOn2228v67BQTOU5B80aPny46tevr+zs7POPOZ1OzZgxQw0bNlTbtm0v+9oHHnhAK1euzHMH+rlz58rPz099+vRx6Th4n/Kcg2XRDpbkNWgHvRd5WHiOFDWXrr76as2ZM0dxcXF5xnY2b94sSapbt26R8is5OVmSdOONN5qKBe6LHCw4t6ZOnZrveadPny5J2rp1qwzDkJ+fX77XMNvPNNvnLU7fGO6JHCy9dlCS7r//fh05ckTffffdRY8vX75c0t8LH8zkqtl2FXBXZusIFyqoLlGca5itVRQlZsATmfmsF3W+gKv1SrPzCi7k6ncFPAv91cL7oWb7nPkpyRoG46fujVwy/5vO1XFHVz77jKt4p/KaX66MU5Tl3JjCcpg89D7kYOE5WJz5KK6+lvodAJQO2ruC27vi1tDMtneujsHQLqK8KWydX3HXN7lSpzC7NrEoNQl4n/LazroyJ604YzslPRbjaWuwgNJgdm19cdbxOp1OTZs2TY0bN5bD4VCNGjU0ePBgHTt27KLjSnOuAQAAAACg/GDDUABwwdGjRxUREaGdO3de9phzA3lHjx7NtxhwuQXpkrRx40a1bt1agYGBSklJ0eHDhzVlyhR9+OGHuvPOO88X3Pbt26e2bdsqIyNDP/74o44fP67XX39d48aN05AhQ86fb9WqVWrfvr0qVqyo5ORkHTx4UOPGjdPbb7+tTp065SngAd6qsNx1OByXLfgtXLhQ0tk7AZo1fPhw/fbbb3ke//nnn3XzzTfrwIEDWrVqlfbv36+XXnpJEydOvOj8CxYsUMuWLRUQEKCNGzfq8OHDevjhhzVw4MB8NypG+dG8eXM1btxYY8eO1dGjR9WvX7/zz9WuXVt16tTRggULtG3bNmVmZiopKUk9evRQr169JJ0tdOV3583IyEg5nU6NHTtWGRkZ2rdvn0aMGKGMjIyLjpswYYJ8fX3VpUsXpaenKzMzUytWrFB0dLTsdnup3m1yyJAhyszM1Lx58xQYGFjs833//fey2WwaOXJkCUSXV2BgoMaOHauVK1dq+PDh2rNnjzIyMpSQkKBhw4apWbNmGjx4cKlcG6WnPOegWZ07d9auXbv0xBNP6PDhw9q3b58GDRqkbdu26f3335fNZpOUfw4+99xzCgoKUlRUlHbs2KHMzEzNmTNHkyZN0gsvvKDrr7/epePgfcpzDpZFO1iS16Ad9F7kYeE5Yva4S/OwUqVKmjRpkjZv3qyBAwfq999/16lTp7Rq1SoNGDBAVapU0ZNPPlmk/Nq+fbskqU6dOiXwLwE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            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ],
      "source": [
        "# Create DOT data. The first argument in tree.export_graphviz is the model name, out_file is used to write \n",
        "# model into out_file, next parameters are information on indicator and predictive parameters \n",
        "\n",
        "from IPython.display import Image  \n",
        "import pydotplus\n",
        "\n",
        "dot_data = tree.export_graphviz(Model_DTR,feature_names=My_data.columns,\n",
        "                                class_names=['total_UPDRS '] )\n",
        "\n",
        "graph = pydotplus.graph_from_dot_data(dot_data)  \n",
        "\n",
        "# Show graph\n",
        "Image(graph.create_png())\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vMmpXP1adzpq"
      },
      "source": [
        "Interesting rules can be mined  by following each  branch of decision tree\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "C1q3ngSPdzpq"
      },
      "source": [
        "# Discovering important features from CART"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yK5raU58dzpq",
        "outputId": "2da84a51-6e5b-43a4-ace8-9638353bbdc4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "     Feature_name  Importance Score\n",
            "0       test_time          0.008664\n",
            "1     motor_UPDRS          0.957385\n",
            "2       Jitter(%)          0.000803\n",
            "3     Jitter(Abs)          0.011356\n",
            "4      Jitter:RAP          0.000000\n",
            "5     Jitter:PPQ5          0.000000\n",
            "6      Jitter:DDP          0.000000\n",
            "7         Shimmer          0.000000\n",
            "8     Shimmer(dB)          0.000566\n",
            "9    Shimmer:APQ3          0.000715\n",
            "10   Shimmer:APQ5          0.000386\n",
            "11  Shimmer:APQ11          0.000000\n",
            "12    Shimmer:DDA          0.000000\n",
            "13            NHR          0.000000\n",
            "14            HNR          0.002632\n",
            "15           RPDE          0.004356\n",
            "16            DFA          0.013138\n",
            "17            PPE          0.000000\n"
          ]
        }
      ],
      "source": [
        "#printing score of importance to features using feature_importances_ function of the model\n",
        "\n",
        "\n",
        "CART_featureImportance= pd.DataFrame({'Feature_name':My_data.columns, 'Importance Score':Model_DTR.feature_importances_ })  \n",
        "\n",
        "print(CART_featureImportance)\n",
        "\n",
        "\n"
      ]
    }
  ],
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