{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# New York City Taxi Trip Duration","metadata":{"id":"yaZ0XXI4ssX6"}},{"cell_type":"markdown","source":"## Problem Statement\n\n### Overview\nThis is a kaggle competition that challenges us to predict the taxi trip duration in New York city. Dataset is provided by the NYC taxi and Limousine commision for building a model.\n\nMoney prize: 30,000$.\n\nBusiness motivation: providing good driving time estimation to\n- Detect bottlenecks that appear in the taxi traffic network.\n- Predict the taxi trip price. \n\nInput: a taxi trip with it's attributes. \\\nOutput: trip duration in seconds. \n \n### Input and Output Data description\n\nThere are three files:\n- train.csv: (1458644,11)\n- test.csv: (625134,9)\n- sample_submission.csv: (625134,2) \n\n| Column name | Description | \n| -------- | -------- | \n| id   | the id for each trip     |\n| vendor_id   | the id provided Associated with the trip record     |\n| pickup_datetime   | date and time when the meter was engaged     |\n| dropoff_datetime   | date and time when the meter was disengaged    |\n| passenger_count   | The number of passengers in the taxi    |\n| pickup_longitude   | the longitude when the meter was engaged     |\n| pickup_latitude   | the latitude when the meter was engaged   |\n| dropoff_longitude   | the longitude when the meter was disengaged     |\n| dropoff_latitude   | the latitude when the meter was disengaged     |\n| store_and_fwd_flag   | This flag indicates whether the trip record was held in vehicle memory before sending to the vendor because the vehicle did not have a connection to the server  |\n| trip_duration  | duration of the trip in seconds     |\n\n\n- A record in train.csv\n\n![](https://i.imgur.com/LtLFbTO.png)\n\n- A record in test.csv\n![](https://i.imgur.com/gEJR1jT.png)\n\n- A record in sample_submission.csv\n![](https://i.imgur.com/zwq0ezw.png)\n\n\n\n\n### Evaluation Metric\n- **Root Mean Squared Logarithmic Error** (RMSLE) is the metric was used to assess the result of this contest.\n\n$$\\epsilon = \\sqrt{\\frac{1}{n}\\sum^{n}_{i=1}(log(p_i + 1) -log(a_i + 1)) ^2}$$\n\n* With respect to:\n    * $\\epsilon$: RMSLE score\n    * n: the number of records (trip duration's observations) in the dataset\n    * $p_i$: the prediction of trip duration\n    * $a_i$: the actual value of trip duration\n    * log(x): natural logarithm (base is e)\n\n* **The smaller the RMSLE value is, the better the model**.","metadata":{"papermill":{"duration":0.012248,"end_time":"2022-06-26T23:23:12.043415","exception":false,"start_time":"2022-06-26T23:23:12.031167","status":"completed"},"tags":[],"id":"0190a467"}},{"cell_type":"code","source":"from google.colab import drive\ndrive.mount('/content/drive')","metadata":{"id":"tkt0MnEFugbn","outputId":"e2f44151-794b-4596-e0c6-0e1a981b164e"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"%matplotlib inline\nfrom tqdm import tqdm\nimport numpy as np \nimport pandas as pd\nfrom datetime import timedelta\nimport datetime as dt\nimport matplotlib.pyplot as plt\nimport random\n\nplt.rcParams['figure.figsize'] = [20, 15]\n\nimport seaborn as sns\nimport xgboost as xgb\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.decomposition import PCA\nfrom sklearn.cluster import MiniBatchKMeans\nimport warnings\nfrom math import radians, cos, sin, asin, sqrt\nwarnings.filterwarnings('ignore')\n\nfrom sklearn.pipeline import Pipeline,make_pipeline\nfrom sklearn.preprocessing import StandardScaler, OneHotEncoder\nfrom sklearn.impute import SimpleImputer\nfrom sklearn.compose import ColumnTransformer\nfrom sklearn.linear_model import LinearRegression\n\nfrom sklearn.metrics import mean_squared_error\n\nfrom sklearn.model_selection import RandomizedSearchCV, GridSearchCV\nfrom sklearn.model_selection import StratifiedKFold\nimport xgboost as xgb\nfrom sklearn.metrics import accuracy_score\n\nimport json","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:23:12.067426Z","iopub.status.busy":"2022-06-26T23:23:12.066475Z","iopub.status.idle":"2022-06-26T23:23:13.858248Z","shell.execute_reply":"2022-06-26T23:23:13.857333Z"},"papermill":{"duration":1.806753,"end_time":"2022-06-26T23:23:13.860952","exception":false,"start_time":"2022-06-26T23:23:12.054199","status":"completed"},"tags":[],"id":"f7fb069c"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"pd.set_option('display.float_format', lambda x: '%.2f' % x)","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:23:13.885872Z","iopub.status.busy":"2022-06-26T23:23:13.885374Z","iopub.status.idle":"2022-06-26T23:23:13.890567Z","shell.execute_reply":"2022-06-26T23:23:13.889550Z"},"papermill":{"duration":0.019542,"end_time":"2022-06-26T23:23:13.892842","exception":false,"start_time":"2022-06-26T23:23:13.873300","status":"completed"},"tags":[],"id":"99f9221b"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# !unzip ../input/nyc-taxi-trip-duration/train.zip -d nyc-taxi-trip-duration\n# !unzip ../input/nyc-taxi-trip-duration/test.zip -d nyc-taxi-trip-duration\n# !unzip ../input/nyc-taxi-trip-duration/sample_submission.zip -d nyc-taxi-trip-duration\n%cd /content/drive/MyDrive/CSC14115 - KHDLUD","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:23:13.916991Z","iopub.status.busy":"2022-06-26T23:23:13.916287Z","iopub.status.idle":"2022-06-26T23:23:19.045532Z","shell.execute_reply":"2022-06-26T23:23:19.044483Z"},"papermill":{"duration":5.144178,"end_time":"2022-06-26T23:23:19.048193","exception":false,"start_time":"2022-06-26T23:23:13.904015","status":"completed"},"tags":[],"id":"becfaff6","outputId":"413ee254-9e30-4877-c4c5-5b78c0a93761"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Explore data and Extract features","metadata":{"id":"yTo2JuOIs3Fe"}},{"cell_type":"code","source":"np.random.seed(1987)\nN = 100000 # number of sample rows in plots\nt0 = dt.datetime.now()\ntrain = pd.read_csv('./nyc-taxi-trip-duration/train.csv')\ntest = pd.read_csv('./nyc-taxi-trip-duration/test.csv')\nsample_submission = pd.read_csv('./nyc-taxi-trip-duration/sample_submission.csv')","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:23:19.072718Z","iopub.status.busy":"2022-06-26T23:23:19.072340Z","iopub.status.idle":"2022-06-26T23:23:25.703014Z","shell.execute_reply":"2022-06-26T23:23:25.701860Z"},"papermill":{"duration":6.645923,"end_time":"2022-06-26T23:23:25.705575","exception":false,"start_time":"2022-06-26T23:23:19.059652","status":"completed"},"tags":[],"id":"af2113c7"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train.head(2)","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:23:25.730994Z","iopub.status.busy":"2022-06-26T23:23:25.730638Z","iopub.status.idle":"2022-06-26T23:23:25.752929Z","shell.execute_reply":"2022-06-26T23:23:25.751737Z"},"papermill":{"duration":0.038057,"end_time":"2022-06-26T23:23:25.755371","exception":false,"start_time":"2022-06-26T23:23:25.717314","status":"completed"},"tags":[],"id":"3048c1ba","outputId":"44407653-f341-4911-8984-10275cac0bb8"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test.head(2)","metadata":{"id":"cbt7dmbLWzGN","outputId":"2dd6e730-e136-4485-c187-e92da49ca803"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Basic information of datasets (train and test)","metadata":{"id":"YR6PgksyV3LQ"}},{"cell_type":"markdown","source":"* Check whether the dataset has :\n    * unique values for the id column.\n    * missing values.\n    * duplicate record.\n    * the trip_duration values are consistent with pickup and dropoff datetime (only for the training dataset).","metadata":{"id":"yIARIYACpUFg"}},{"cell_type":"code","source":"def check_basic(df, df_type=\"train\"):\n    print(\"{} DF has {} rows and {} columns\".format(df_type,df.shape[0], df.shape[1]))\n    if df.id.nunique() == df.shape[0]:\n        print(\"1. Id is unique\")\n    if not df.isnull().any().any(): \n        print(\"2. No missing value\")\n    if train.duplicated(keep='first').sum() == 0:\n        print(\"3. No duplicate record\")\n    if df_type == 'train':\n        trip_duration_diff = (pd.to_datetime(train.dropoff_datetime) - pd.to_datetime(train.pickup_datetime)).map(lambda x :x.total_seconds())\n        if len(df[np.abs(trip_duration_diff.values - df['trip_duration'].values) > 1]) == 0:\n            print(\"4. Trip_duration is consistent with pickup and dropoff times.\")","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:23:25.821061Z","iopub.status.busy":"2022-06-26T23:23:25.820434Z","iopub.status.idle":"2022-06-26T23:23:25.829436Z","shell.execute_reply":"2022-06-26T23:23:25.828435Z"},"papermill":{"duration":0.024596,"end_time":"2022-06-26T23:23:25.831958","exception":false,"start_time":"2022-06-26T23:23:25.807362","status":"completed"},"tags":[],"id":"198ca5cf"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"check_basic(train, df_type=\"train\")","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:23:25.857803Z","iopub.status.busy":"2022-06-26T23:23:25.857059Z","iopub.status.idle":"2022-06-26T23:23:47.289975Z","shell.execute_reply":"2022-06-26T23:23:47.288671Z"},"papermill":{"duration":21.449297,"end_time":"2022-06-26T23:23:47.293076","exception":false,"start_time":"2022-06-26T23:23:25.843779","status":"completed"},"tags":[],"id":"4ae851ab","outputId":"fd758c70-af91-4e13-b6f5-599620f5bc17"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"check_basic(test, df_type=\"test\")","metadata":{"id":"uZ_AE56fW2gP","outputId":"4891d9f7-d877-4d82-9c66-8b28f8caa1b5"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* Show the datatype of each column in dataset.","metadata":{"id":"RQUs2JyhwPZa"}},{"cell_type":"code","source":"print(\"Train:\\n\", train.dtypes, \"\\n\")\nprint(\"Test:\\n\", test.dtypes)","metadata":{"id":"jYh1Y2bBXFd-","outputId":"becf7a83-db83-4791-920d-c5724d542e0a"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* Show the number of unique values in each column.","metadata":{"id":"rNGXWA2swRbW"}},{"cell_type":"code","source":"train.nunique()","metadata":{"id":"LSjMSDIDwSqZ","outputId":"bb002ec0-6b10-47f7-aee4-f4eff31ba5d9"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"#### Convert datatypes","metadata":{"id":"3XMDsERDV3IS"}},{"cell_type":"markdown","source":"* Because datatypes of `pickup_datetime` and `dropoff_datetime` are \"**object**\" which is difficult when we handle it with built-in functions of pandas $\\rightarrow$ we convert it into \"**datetime**\" datatype to be easy to extract data from these columns.","metadata":{"id":"r7fGSZ3uta-w"}},{"cell_type":"code","source":"train['pickup_datetime'] = pd.to_datetime(train['pickup_datetime'])\ntest['pickup_datetime'] = pd.to_datetime(test['pickup_datetime'])\n\ntrain['dropoff_datetime'] = pd.to_datetime(train['dropoff_datetime'])","metadata":{"id":"f5hrZ7CbXmn3"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* We convert the datatype of the vendor_id column from **int64** to **object** (str) because:\n    * vendor_id is the id provided Associated with the trip record.\n    * this column only has 2 unique values, 1 and 2, but it does not mean 2 is bigger than 1.","metadata":{"id":"99Zo52Gka2Nn"}},{"cell_type":"code","source":"train['vendor_id'] = train['vendor_id'].astype(str)\ntest['vendor_id'] = test['vendor_id'].astype(str)","metadata":{"id":"f4w2bDBsa2No"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"#### Statistics information of the train set","metadata":{"id":"zuQ5Naus063M"}},{"cell_type":"code","source":"train.describe(datetime_is_numeric = True)","metadata":{"id":"ttfZnli5f98R","outputId":"841b857b-e4e3-4274-dcc6-c81f6dc08078"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* Get numeric, categorical column names","metadata":{"id":"sB3p7fUc2Dhq"}},{"cell_type":"code","source":"num_cols = list(train.select_dtypes(exclude='object').columns)\ncate_cols = list(train.select_dtypes(include='object').columns)\nprint(\"Num cols: \",num_cols)\nprint(\"Cate cols: \",cate_cols)","metadata":{"id":"b9OTSxjIYDGR","outputId":"2c77f22b-8a14-4819-e8fe-608517a3f0a0"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"##### Numeric columns","metadata":{"id":"naBeJokD88gq"}},{"cell_type":"code","source":"def value_percentages(col):\n    val = col.groupby(by=col).count().sort_values(ascending=False)\n    total = val.sum()\n    return (((val / total)*100).round(1)).to_dict()\n\ndef num_values(col):\n    return col.nunique()\n\ndef missing_percentage(col):\n    per = col.isna().mean()*100\n    return per.round(1)","metadata":{"id":"XgdEuJDJX7Ye"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train[num_cols].agg([value_percentages, num_values])","metadata":{"id":"MY0KWNwKYALg","outputId":"bfca5c81-a8d1-4376-90f9-be65a672d651"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* **Observation**:\n\n$→$ The number of distinct values of `pickup_datetime` and `dropoff_datetime` takes up more than **90%** of the dataset $→$ extract the data of these columns to new columns (month, hour, day,...) to reduce the unique.\n\n$→$ The value of longitude and latitude have **float64** datatypes $→$ it is difficult to compare.","metadata":{"id":"n9LIQBlYXu8z"}},{"cell_type":"markdown","source":"##### Categorical columns","metadata":{"id":"GUY7qI4O9TTK"}},{"cell_type":"code","source":"train[cate_cols].agg([value_percentages, num_values])","metadata":{"id":"bgCkaCGMeLx9","outputId":"6f5ef40c-0b01-498a-fe38-f5b349d7d112"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train.groupby('store_and_fwd_flag')['trip_duration'].agg(['mean', 'min', 'max'])","metadata":{"id":"FErL2aPFfAtn","outputId":"1bbc07e9-c68d-4510-dc50-48cc1462f430"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* **Observation**:\n\n$→$ The `store_and_fwd_flag` column has only 2 values, N và Y. We decide to remove this column because:\n\n1. The proportions of \"N\" and \"Y\" are 99.4% and 0.6%, respectively $→$ \"N\" dominant this column's value.\n2. This column meaning is the flag indicates whether the trip record was held in vehicle memory before sending to the vendor because the vehicle did not have a connection to the server $→$ **does not affect** the `trip_duration`.\n3. The average trip duration of these two groups has not much different.","metadata":{"id":"_CqOn3LLekZZ"}},{"cell_type":"markdown","source":"### Extract new features","metadata":{"id":"XNMHixJBbEYY"}},{"cell_type":"markdown","source":"#### From `pickup_datetime`","metadata":{"id":"Tj_wwYTLEXcD"}},{"cell_type":"code","source":"train.loc[:, 'pick_month'] = train['pickup_datetime'].dt.month\ntrain.loc[:, 'hour'] = train['pickup_datetime'].dt.hour\ntrain.loc[:, 'day_of_month'] = train['pickup_datetime'].dt.day\ntrain.loc[:, 'day_of_week'] = train['pickup_datetime'].dt.dayofweek\n\ntest.loc[:, 'pick_month'] = test['pickup_datetime'].dt.month\ntest.loc[:, 'hour'] = test['pickup_datetime'].dt.hour\ntest.loc[:, 'day_of_month'] = test['pickup_datetime'].dt.day\ntest.loc[:, 'day_of_week'] = test['pickup_datetime'].dt.dayofweek","metadata":{"id":"6YqPBkjRYtrw"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train.head(2)","metadata":{"id":"QyrJ0CO3aEM5","outputId":"f043777d-1279-4af2-c971-fc6c68c6911a"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* **Comment**:\n\n$→$ Because this problem predicts the trip_duration so that the `dropoff_datetime` column is not necessary $→$ we **remove** this column.","metadata":{"id":"tHaIdDqfZTQg"}},{"cell_type":"code","source":"train.drop(['pickup_datetime', 'dropoff_datetime'], axis =1, inplace= True)\ntest.drop(['pickup_datetime'], axis =1, inplace= True)","metadata":{"id":"I5H787xZZibN"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"#### Remove `store_and_fwd_flag`","metadata":{"id":"iajqYK5VEkt6"}},{"cell_type":"code","source":"train.drop('store_and_fwd_flag', axis = 1, inplace=True)\ntest.drop('store_and_fwd_flag', axis = 1, inplace=True)","metadata":{"id":"XdNaQq9Zjtl4"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train.head(1)","metadata":{"id":"oJWbRSlVj8P8","outputId":"b40ec8c3-5a05-4721-e711-42799628f483"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"#### Distance ","metadata":{"id":"pjA66obY2zlX"}},{"cell_type":"markdown","source":"* The solution of Beluga about haversine distance and manhattan distance (in km).\n","metadata":{"id":"GEL4fUA953HH"}},{"cell_type":"code","source":"def haversine_array(lat1, lng1, lat2, lng2):\n    lat1, lng1, lat2, lng2 = map(np.radians, (lat1, lng1, lat2, lng2))\n    AVG_EARTH_RADIUS = 6371  # in km\n    lat = lat2 - lat1\n    lng = lng2 - lng1\n    d = np.sin(lat * 0.5) ** 2 + np.cos(lat1) * np.cos(lat2) * np.sin(lng * 0.5) ** 2\n    h = 2 * AVG_EARTH_RADIUS * np.arcsin(np.sqrt(d))\n    return h","metadata":{"id":"zZg26fSv6CNU"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def dummy_manhattan_distance(lat1, lng1, lat2, lng2):\n    a = haversine_array(lat1, lng1, lat1, lng2)\n    b = haversine_array(lat1, lng1, lat2, lng1)\n    return a + b","metadata":{"id":"WsxKhhgyWXFl"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* `distance_haversine`, `distance_manhattan`: knowing the distance between two positions can help to estimate the duration => used to predict trip duration.\n","metadata":{"id":"DtgXuZx2bz0Z"}},{"cell_type":"code","source":"train.loc[:, 'distance_haversine'] = haversine_array(train['pickup_latitude'].values,\n                                                     train['pickup_longitude'].values,\n                                                     train['dropoff_latitude'].values,\n                                                     train['dropoff_longitude'].values)\n\ntest.loc[:, 'distance_haversine'] = haversine_array(test['pickup_latitude'].values,\n                                                     test['pickup_longitude'].values,\n                                                     test['dropoff_latitude'].values,\n                                                     test['dropoff_longitude'].values)","metadata":{"id":"cDpndxBk6Gym"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train.loc[:, 'distance_manhattan'] = dummy_manhattan_distance(train['pickup_latitude'].values,\n                                                              train['pickup_longitude'].values,\n                                                              train['dropoff_latitude'].values,\n                                                              train['dropoff_longitude'].values)\n\ntest.loc[:, 'distance_manhattan'] = dummy_manhattan_distance(test['pickup_latitude'].values,\n                                                              test['pickup_longitude'].values,\n                                                              test['dropoff_latitude'].values,\n                                                              test['dropoff_longitude'].values)","metadata":{"id":"NWDgsJiuWgTu"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train[[\"id\",\"distance_haversine\",\"distance_manhattan\"]].head(2)","metadata":{"id":"McP5DE3G6TXm","outputId":"781f5f5a-fc8a-4871-ab6d-2e55f84aac1e"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* Determine the direction of pickup and dropoff positions and divide it into 8 bins (N, NE, E, SE, S, SW, W, NW):\n    * Bearing_array function from solution of Beluga.\n    * Assign direction for each degree.\n\n    \n* `direction`:  the direction of the trip has 8 directions => for each location, which direction do the riders need to move mainly => the traffic situation when moving in the directions at the pick-up point and the pick-up time => affect the prediction of travel time.\n    \n\n","metadata":{"id":"g4yploM29eWk"}},{"cell_type":"code","source":"def bearing_array(lat1, lng1, lat2, lng2):\n    AVG_EARTH_RADIUS = 6371  # in km\n    lng_delta_rad = np.radians(lng2 - lng1)\n    lat1, lng1, lat2, lng2 = map(np.radians, (lat1, lng1, lat2, lng2))\n    y = np.sin(lng_delta_rad) * np.cos(lat2)\n    x = np.cos(lat1) * np.sin(lat2) - np.sin(lat1) * np.cos(lat2) * np.cos(lng_delta_rad)\n    return np.degrees(np.arctan2(y, x))","metadata":{"id":"RnhDCxfM7hoj"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train.loc[:, 'direction'] = bearing_array(train['pickup_latitude'].values, \n                                          train['pickup_longitude'].values, \n                                          train['dropoff_latitude'].values, \n                                          train['dropoff_longitude'].values)\n\ntest.loc[:, 'direction'] = bearing_array(test['pickup_latitude'].values, \n                                          test['pickup_longitude'].values, \n                                          test['dropoff_latitude'].values, \n                                          test['dropoff_longitude'].values)","metadata":{"id":"-KQrKU1j28lp"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train[[\"id\",\"direction\"]].describe()","metadata":{"id":"oZYoRZRm8hZD","outputId":"e105ca26-dd2f-45a1-d439-3236041aa89f"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"new_df = train.copy()\ntrain.loc[(67.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < 112.5) ,\"direction\"]=\"N\"\ntrain.loc[(22.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < 67.5) ,\"direction\"]=\"NE\"\ntrain.loc[(-22.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < 22.5) ,\"direction\"]=\"E\"\ntrain.loc[(-67.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < -22.5) ,\"direction\"]=\"SE\"\ntrain.loc[(-112.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < -67.5) ,\"direction\"]=\"S\"\ntrain.loc[(-157.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < -112.5) ,\"direction\"]=\"SW\"\ntrain.loc[(157.5 <= new_df[\"direction\"]) | (new_df[\"direction\"] < -157.5) ,\"direction\"]=\"W\"\ntrain.loc[(112.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < 157.5) ,\"direction\"]=\"NW\"\n\n\nnew_df = test.copy()\ntest.loc[(67.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < 112.5) ,\"direction\"]=\"N\"\ntest.loc[(22.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < 67.5) ,\"direction\"]=\"NE\"\ntest.loc[(-22.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < 22.5) ,\"direction\"]=\"E\"\ntest.loc[(-67.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < -22.5) ,\"direction\"]=\"SE\"\ntest.loc[(-112.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < -67.5) ,\"direction\"]=\"S\"\ntest.loc[(-157.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < -112.5) ,\"direction\"]=\"SW\"\ntest.loc[(157.5 <= new_df[\"direction\"]) | (new_df[\"direction\"] < -157.5) ,\"direction\"]=\"W\"\ntest.loc[(112.5 <= new_df[\"direction\"]) & (new_df[\"direction\"] < 157.5) ,\"direction\"]=\"NW\"","metadata":{"id":"mhdh34X089f_"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train[\"direction\"].unique()","metadata":{"id":"ub02I6zrBm8R","outputId":"8a70178d-a26e-41e3-877c-0da70d1bfbd0"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"#### Speed features (from Beluga's notebook)","metadata":{"id":"qd4LGCnqV3Ig"}},{"cell_type":"code","source":"train.loc[:, \"avg_speed_h\"] = 1000 * train[\"distance_haversine\"] / train[\"trip_duration\"]","metadata":{"id":"yl4ErSJyWADi"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* Based on the tuple of longitude and latitude, we using KMeans in order to cluster pickup and dropoff positions to 100 groups respectively. Learning Kmeans with 500000 examples from both train and test set.\n* From the area clustered, the average speed features can be extracted based on pickup, dropoff groups, and pickup hour. These features can be used in test set.","metadata":{"id":"ZoZ8HuNXswAz"}},{"cell_type":"code","source":"coords = np.vstack((train[['pickup_latitude', 'pickup_longitude']].values,\n                    train[['dropoff_latitude', 'dropoff_longitude']].values,\n                    test[['pickup_latitude', 'pickup_longitude']].values,\n                    test[['dropoff_latitude', 'dropoff_longitude']].values))\n\nsample_ind = np.random.permutation(len(coords))[:500000]\nkmeans = MiniBatchKMeans(n_clusters=100, batch_size=10000).fit(coords[sample_ind])","metadata":{"id":"VSlJavq7WAVL"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* `pickup_cluster`, `dropoff_cluster`: group of nearest/similar pick-up and drop-off latitudes and longitudes ==> We assume that location in that group has the same traffic and has the same impact on trip duration.","metadata":{"id":"h9fPVqMxbpR9"}},{"cell_type":"code","source":"train.loc[:, 'pickup_cluster'] = kmeans.predict(train[['pickup_latitude', 'pickup_longitude']])\ntrain.loc[:, 'dropoff_cluster'] = kmeans.predict(train[['dropoff_latitude', 'dropoff_longitude']])\n\ntest.loc[:, 'pickup_cluster'] = kmeans.predict(test[['pickup_latitude', 'pickup_longitude']])\ntest.loc[:, 'dropoff_cluster'] = kmeans.predict(test[['dropoff_latitude', 'dropoff_longitude']])","metadata":{"id":"n3aXLPo3WAYn"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* New features of speed (use average speed of haversine distance) groups by: `hour` - `pickup_cluster`, `hour` - `dropoff_cluster`, `pickup_cluster` - `dropoff_cluster`.\n* To avoid learning model being overfitted, we only keep the shared values of each group with a count over 100.\n* Average speed of haversine distance is calculated on the train set so that the test set does not leak.\n\n* `avg_speed_h_hour_pickup_cluster`, `avg_speed_h_hour_dropoff_cluster`, `avg_speed_h_pickup_cluster_dropoff_cluster`: because **t = s/v**. Estimate the average speed based on pickup hour, pickup and dropoff clusters. These values are calculated using `avg_speed_h`. Although the `avg_speed_h` is invalid due to using the target column, these values are the average of group by and not directly inferred from them => we can assume these as an estimation for speed => used to predict the trip duration. \n\n* `cnt_hour_pickup_cluster`, `cnt_hour_dropoff_cluster`, `cnt_pickup_cluster_dropoff_cluster`: the number of trips in each attribute pair => affects the travel time because it shows how crowded the traffic is at the hour of pick-up, pick-up and drop-off area => used to predict the trip duration.","metadata":{"id":"tImcclYevC1H"}},{"cell_type":"code","source":"for gby_cols in [['hour', 'pickup_cluster'],  ['hour', 'dropoff_cluster'],\n                 ['pickup_cluster', 'dropoff_cluster']]:\n    coord_speed = train.groupby(gby_cols).mean()[['avg_speed_h']].reset_index()\n    coord_count = train.groupby(gby_cols).count()[['id']].reset_index()\n    coord_stats = pd.merge(coord_speed, coord_count, on=gby_cols)\n    coord_stats = coord_stats[coord_stats['id'] > 100]\n    coord_stats.columns = gby_cols + ['avg_speed_h_%s' % '_'.join(gby_cols), 'cnt_%s' %  '_'.join(gby_cols)]\n    train = pd.merge(train, coord_stats, how='left', on=gby_cols)\n    test = pd.merge(test, coord_stats, how='left', on=gby_cols)","metadata":{"id":"k9RETOOe124j"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"num_cols = list(train.select_dtypes(exclude='object').columns)\ncate_cols = list(train.select_dtypes(include='object').columns)","metadata":{"id":"uJqdc6WgkRZR"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Visualize data","metadata":{"id":"BsIawMQJTjaI"}},{"cell_type":"markdown","source":"#### Histogram all numberic columns","metadata":{"id":"p751lkE3Sg4_"}},{"cell_type":"code","source":"train[num_cols].hist(figsize=(20, 15), bins = 50)\nplt.show()","metadata":{"id":"FShd81bnQ9I4","outputId":"d668e2e6-e0ca-4d27-d05c-e5ab79944c0c"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"\n* Scatter of each numeric column for the number of each value.","metadata":{"id":"AWNmLFBZSoBN"}},{"cell_type":"code","source":"def draw_chart(df, fig_size = (15,15)):\n    temp = list(df.columns)\n    figure, axis = plt.subplots(len(temp)//2 if len(temp) % 2 == 0 else len(temp)//2 + 1, 2, figsize = fig_size)\n    color = ['#582f0e','#936639','#f3722c','#c2c5aa','#414833','#457b9d','#ffb703','#e63946', '#c77dff','#55a630','#f72585','#ffa69e','#4d908e','#7f5539','#b5e48c','#b6ad90','#38b000','#a84c32','#a84c32','#471f13','#8c842d','#408061']\n    for i, col in enumerate(temp):\n        t = df[col].value_counts()\n        axis[i//2, i%2].scatter(list(t.index), t.values, color = color[i])\n        axis[i//2, i%2].set_title(col)\n    if len(temp) %2 !=0:\n        figure.delaxes(axis[len(temp)//2,1])\n    plt.subplots_adjust(top = 0.99, bottom=0.01, hspace=0.5, wspace=0.4)\n    plt.show()","metadata":{"id":"T-tAkhqMRfy2"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"draw_chart(train[num_cols], (16,25));","metadata":{"id":"rOVtC9jZRqvO","outputId":"9defabfa-2224-4fa7-ecf9-a15f3c1afec7"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":" **Comment**:\n\n- pickup_longtitude, pickup_latitude, dropoff_longtitude, dropoff_latitude have some values which dominate because in this problem we focus on New York city.\n- People in New York tends to go alone (passenger = 1)\n- pick_month: in March, the number of people using Taxi is the highest.\n- hour: less people uses Taxi at 5am and more at 16-20pm.\n- day_of_week: on Monday and Sunday, less people uses Taxi\n- day_of_month: at the end of a month, the number of human using Taxi decreases.\n- 2 types of distance and average speed have no much different.\n- Trip duration is calcuated by second so the range is quite big (1e6) and there are some values that occur most of the time.","metadata":{"id":"y-s7n0CIRbB8"}},{"cell_type":"markdown","source":"#### Trip duration column","metadata":{"id":"bbggKn2OOuCe"}},{"cell_type":"code","source":"train_log_trip_duration = np.log(train['trip_duration'].values + 1)\nplt.hist(train_log_trip_duration, bins=100)\nplt.xlabel('log(trip_duration)')\nplt.ylabel('number of train records')\nplt.show()","metadata":{"id":"UP1YPqf-LPu5","outputId":"21be44d6-72ef-4530-f4c0-15d5b17faa2c"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"#### Average speed depends on hour and day of week","metadata":{"id":"JWEDHUf8O92X"}},{"cell_type":"code","source":"fig, ax = plt.subplots(ncols=2, sharey=True,figsize=(10, 7))\nax[0].plot(train.groupby('hour').mean()['avg_speed_h'], 'bo-', lw=2, alpha=0.7)\nax[1].plot(train.groupby('day_of_week').mean()['avg_speed_h'], 'go-', lw=2, alpha=0.7)\nax[0].set_xlabel('hour')\nax[1].set_xlabel('weekday')\nax[0].set_ylabel('average speed')\nfig.suptitle('Rush hour average traffic speed')\nplt.show()","metadata":{"id":"CnfxJqtZMU3X","outputId":"01583b5e-196a-471a-e3cf-3acd389f9b31"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"**Comment**\n- As we can see, because at 5am less people using Taxi so the street won't be crowed $→$ speed will be high. The opposite is true for hours around 16-20pm.\n- On Monday and Sunday, the speed is higher than other days.\n","metadata":{"id":"E8DMClIdNnep"}},{"cell_type":"markdown","source":"### Choose columns affect trip duration\n","metadata":{"id":"w0FHCnrUNj76"}},{"cell_type":"code","source":"print(len(train.columns)) \ntrain.columns","metadata":{"outputId":"310b2001-b28d-4a9c-d7ed-6d64a970cec5","id":"ceYWp6PrN6kA"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* **The effect of each column on predicting trip_duration**:\n    * `id`: id of trip => does not related to trip duration => do not use to predict trip duration.\n        \n    * `passenger_count`: the number of passengers does not indicate the speed of that taxi => do not use to predict trip duration.\n       \n    * Features from pickup_datetime: `pick_month`, `hour`, `day_of_month`, `day_of_week`: this is the basic information of time => Based on those, ***we can know on which time, the number of vehicles will increase***. We do not add minute column because this column is too detail or that can be known by other previous added columns => Feed to model.\n    \n    * `avg_speed_h`: do not use these columns to predict the trip duration because they are calculated based on the target column.\n\n=> Features rejected: `id`, `passenger_count`, `trip_duration`, `avg_speed_h`.\n\n=> Features used: \n* `vendor_id`\n* `pick_month`\n* `hour`\n* `day_of_month`\n* `day_of_week`\n* `distance_haversine`\n* `distance_manhattan`\n* `direction`\n* `pickup_cluster`\n* `dropoff_cluster`\n* `avg_speed_h_hour_pickup_cluster`\n* `avg_speed_h_hour_dropoff_cluster`\n* `avg_speed_h_pickup_cluster_dropoff_cluster`\n* `cnt_hour_pickup_cluster`\n* `cnt_hour_dropoff_cluster`\n* `cnt_pickup_cluster_dropoff_cluster`\n* `pickup_longitude`\n* `pickup_latitude`\n* `dropoff_longitude`\n* `dropoff_latitude`","metadata":{"id":"tIsXE08pN6kB"}},{"cell_type":"code","source":"train = train.drop(columns = ['passenger_count', 'avg_speed_h'])\ntest = test.drop(columns = ['passenger_count'])","metadata":{"id":"Xqr_nOE0clOy"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Write features_train.csv\n# Write features_test.csv\n\ntrain.to_csv('features_train.csv', index=False)\ntest.to_csv('features_test.csv', index=False)","metadata":{"id":"FlL6SKIbPfm-"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Modeling\n","metadata":{"id":"iU6j4oYIdGM7"}},{"cell_type":"code","source":"# Read features.csv\ntrain = pd.read_csv('features_train_AD.csv')\ntest = pd.read_csv('features_test_AD.csv')","metadata":{"id":"Tg16ZnUWYG3b"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"do_not_use_for_training = ['id','trip_duration']\nfeature_names = [f for f in train.columns if f not in do_not_use_for_training]","metadata":{"id":"Fm0efkQkqBZi"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(len(feature_names)) \nfeature_names","metadata":{"id":"aMAlaUOEdxKG","outputId":"4c68c66b-b415-4753-e8a4-ef7ee28920a3"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"y = np.log(train['trip_duration'].values + 1)","metadata":{"id":"8rLsNAPOpdI3"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"dtrain = train[feature_names]\ndtest = test[feature_names]","metadata":{"id":"xY3grK0mI6QW"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Preprocessor","metadata":{"id":"shf04bFtqkRR"}},{"cell_type":"code","source":"# Checking columns that contain null values\ndtrain.isnull().sum()","metadata":{"id":"knce1Iw0e6WZ","outputId":"788ad295-2d30-4aef-cfa6-c91e17c0d2bb"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"num_cols = list(dtrain.select_dtypes(exclude='object').columns)\ncat_cols = list(dtrain.select_dtypes(include='object').columns)","metadata":{"id":"Yooyc42eImqJ"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"!pip install category-encoders","metadata":{"id":"n1U3o2dQKToG","outputId":"87d96096-9569-4bba-e8e3-e7b5fe0ddca9"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\n\n#Preprocessing for missing numerical data\nnum_transformer = Pipeline(steps = [\n         (\"imputer\", SimpleImputer(strategy=\"constant\", fill_value=0)),\n         (\"norm\", StandardScaler())])\n\n# Preprocessing for categorical data\ncat_transformer = OneHotEncoder(handle_unknown=\"ignore\", sparse=False)\n\n# getting together our scaler and encoder with preprocessor\npreprocessor = ColumnTransformer(\n      transformers=[('num', num_transformer, num_cols),\n                    ('cat', cat_transformer, cat_cols)])\nX_train, X_val, y_train, y_val = train_test_split(dtrain, y, test_size=0.2, random_state=1987)","metadata":{"id":"Addy1Kl4Hp1s"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Linear Regression","metadata":{"id":"-fbvuRG8N51d"}},{"cell_type":"code","source":"model_linear = LinearRegression()\n\n# giving all values to pipeline\nlinear_pipe = Pipeline(steps=[('preprocessor', preprocessor),('linear', model_linear)])\nlinear_pipe.fit(X_train, y_train)\n\n# make predictions on training set\ny_pred = linear_pipe.predict(X_val)","metadata":{"id":"jKDO9EKqLS99"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(linear_pipe)","metadata":{"id":"kDnDVc46zjbz","outputId":"4fa20af8-0e5d-4659-8721-7ba44446418e"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# to print the results in good way\nprint(f\"Validation RMSLE: {mean_squared_error(y_pred, y_val, squared=False)}\")","metadata":{"id":"nlvbQ9bMzPai","outputId":"a1bbf0d5-4e46-4f75-da7f-c2179ada902a"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"y_pre_linear = linear_pipe.predict(test)\ny_pre_linear = np.exp(y_pre_linear) - 1\ny_pre_linear","metadata":{"id":"CxYMQi3lVEVm","outputId":"31123df0-add3-4074-f562-961bd2d8e514"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"new_df = test.copy()\nnew_df['trip_duration'] = y_pre_linear\nnew_df = new_df[['id', 'trip_duration']]\nnew_df.head()","metadata":{"id":"5xC2YHpeViwT","outputId":"754274b2-95dc-414c-a385-49791573d3ee"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"new_df.to_csv(\"submission_linear.csv\", index = False)","metadata":{"id":"pJ-fzk28XDjA"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* **Week08**","metadata":{"id":"CKCz0_TQXhty"}},{"cell_type":"markdown","source":"![image.png](data:image/png;base64,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XGB\n**Bagging**\n\nAn emsemble meta-estimator:\n1.   Fit each base classifier on it's corresponding subsets (random). \n2.   Aggregate their individual prediction. Using voting for classification and calculating mean for regression. \n\nRef: [Geeksforgeeks, @pawangfg, xgboost](https://www.geeksforgeeks.org/xgboost/)","metadata":{"id":"Py0tRj2Gpupu"}},{"cell_type":"markdown","source":"![image.png](data:image/png;base64,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)","metadata":{"id":"7Il3UkWZxfCy"}},{"cell_type":"markdown","source":"Bagging classifier\n\nimage source: [Geeksforgeeks, @pawangfg, xgboost](https://www.geeksforgeeks.org/xgboost/)","metadata":{"id":"Aes4vI8ndMse"}},{"cell_type":"markdown","source":"**Boosting**\n\nAn emsemble method, it temps to build a stronger classifier from a week classifier sequentially. The second model is learned from the errors present in the first model.\n\nXGB (Extreme Gradient Boosting)\nIs built from Gradient Boosting technique (The new classifier is trained using the residual erros of previous classifier)\nAssign a weight to each variables, the weight of variables which predicted wrong will be increased in the next classifier.\n","metadata":{"id":"LGEYyLQOxmJF"}},{"cell_type":"markdown","source":"![image.png](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAA+gAAAIxCAYAAADe5ZK3AAAABHNCSVQICAgIfAhkiAAAIABJREFUeF7svQecZGld7/2rnKs6557pnpxnMxtZlt0lxxUFRIKKCoKvr773qtdXEV5f8Yr4uV5Q8QpeQFRWBRYJG2DzsjlMztM5x+rKuer+/qenZ7p7qrurq3p2e3b/z1LMTFWdc57zrfOc8/yefzIV2KBNCSgBJaAElIASUAJKQAkoASWgBJSAEnhFCZhf0aPrwZWAElACSkAJKAEloASUgBJQAkpACSgBg4AKdL0QlIASUAJKQAkoASWgBJSAElACSkAJrAMCKtDXwY+gXVACSkAJKAEloASUgBJQAkpACSgBJaACXa8BJaAElIASUAJKQAkoASWgBJSAElAC64CACvR18CNoF5SAElACSkAJKAEloASUgBJQAkpACahA12tACSgBJaAElIASUAJKQAkoASWgBJTAOiCgAn0d/AjaBSWgBJSAElACSkAJKAEloASUgBJQAirQ9RpQAkpACSgBJaAElIASUAJKQAkoASWwDgioQF8HP4J2QQkoASWgBJSAElACSkAJKAEloASUgAp0vQaUgBJQAkpACSgBJaAElIASUAJKQAmsAwIq0NfBj6BdUAJKQAkoASWgBJSAElACSkAJKAEloAJdrwEloASUgBJQAkpACSgBJaAElIASUALrgIAK9HXwI2gXlIASUAJKQAkoASWgBJSAElACSkAJqEDXa0AJKAEloASUgBJQAkpACSgBJaAElMA6IKACfR38CNoFJaAElIASUAJKQAkoASWgBJSAElACKtD1GlACSkAJKAEloASUgBJQAkpACSgBJbAOCKhAXwc/gnZBCSgBJaAElIASUAJKQAkoASWgBJSACnS9BpSAElACSkAJKAEloASUgBJQAkpACawDAirQ18GPoF1QAkpACSgBJaAElIASUAJKQAkoASWgAl2vASWgBJSAElACSkAJKAEloASUgBJQAuuAgAr0dfAjaBeUgBJQAkpACSgBJaAElIASUAJKQAmoQNdrQAkoASWgBJSAElACSkAJKAEloASUwDogoAJ9HfwI2gUloASUgBJQAkpACSgBJaAElIASUAIq0PUaUAJKQAkoASWgBJSAElACSkAJKAElsA4IqEBfBz+CdkEJKAEloASUgBJQAkpACSgBJaAElIAKdL0GlIASUAJKQAkoASWgBJSAElACSkAJrAMCKtDXwY+gXVACSkAJKAEloASUgBJQAkpACSgBJaACXa8BJaAElIASUAJKQAkoASWgBJSAElAC64CACvR18CNoF5SAElACSkAJKAEloASUgBJQAkpACahA12tACSgBJaAElIASUAJKQAkoASWgBJTAOiCgAn0d/AjaBSWgBJSAElACSkAJKAEloASUgBJQAirQ9RpQAkpACSgBJaAElIASUAJKQAkoASWwDgioQF8HP4J2QQkoASWgBJSAElACSkAJKAEloASUgAp0vQaUgBJQAkpACSgBJaAElIASUAJKQAmsAwIq0NfBj6BdUAJKQAkoASWgBJSAElACSkAJKAEloAJdrwEloASUgBJQAkpACSgBJaAElIASUALrgIAK9HXwI2gXlIASUAJKQAkoASWgBJSAElACSkAJqEDXa0AJKAEloASUgBJQAkpACSgBJaAElMA6IKACfR38CNoFJaAElIASUAJKQAkoASWgBJSAElACKtD1GlACSkAJKAEloASUgBJQAkpACSgBJbAOCKhAXwc/gnZBCSgBJaAElIASUAJKQAkoASWgBJSACnS9BpSAElACSkAJKAEloASUgBJQAkpACawDAirQ18GPoF1QAkpACSgBJaAElIASUAJKQAkoASWgAl2vASWgBJSAElACSkAJKAEloASUgBJQAuuAgAr0dfAjaBeUgBJQAkpACSgBJaAElIASUAJKQAmoQNdrQAkoASWgBJSAElACSkAJKAEloASUwDogoAJ9HfwI2gUloASUgBJQAkpACSgBJaAElIASUAIq0PUaUAJKQAkoASWgBJSAElACSkAJKAElsA4IqEBfBz+CdkEJKAEloASUgBJQAkpACSgBJaAElIAKdL0GlIASUAJKQAkoASWgBJSAElACSkAJrAMCKtDXwY+gXVACSkAJKAEloASUgBJQAkpACSgBJaACXa8BJaAElIASUAJKQAkoASWgBJSAElAC64CACvR18CNoF5SAElACSkAJKAEloASUgBJQAkpACahA12tACSgBJaAElIASUAJKQAkoASWgBJTAOiCgAn0d/AjaBSWgBJSAElACSkAJKAEloASUgBJQAirQ9RpQAkpACSgBJaAElIASUAJKQAkoASWwDgioQF8HP4J2QQkoASWgBJSAElACSkAJKAEloASUgAp0vQaUgBJQAkpACSgBJaAElIASUAJKQAmsAwIq0NfBj6BdUAJKQAkoASWgBJSAElACSkAJKAEloAJdrwEloASUgBJQAkpACSgBJaAElIASUALrgIAK9HXwI2gXlIASUAJKQAkoASWgBJSAElACSkAJWBWBEiiFQL5QQDydRzyTQzqbNzaxWkxwWi3w2M2wWXStpxSO+h0lsBKB2bGWQ4JjLZMrQP6zmDjWbBZ4HVZYzaaVdqGfKwEloASUgBJQAkpACVymBFSgX6Y/3EXdpoDOxmJIB4PIRKMoZLIwUTxbPR7Yq6th9XphMq9eRItAGAwlcXw0ipeGIsafY5E0+DaqXBZsqXXjqjYf9jR5saXeQ7Fuuahr+oYSeDURKOTzyHCspWZmOObiKORzMFmssLndcNRUw8YxV04TYd43HcfJcY61gRmcHItgIpFFLl9AwGnBZmOsVWFXkx+dNW5DrGtTAkpACSgBJaAElIASeHURMBXYXl2n9No6GxELqfFxTB88iJnDRxA5cwapsVHkE0mYnXbY6xvg27wZVXv3ovrqq+FqaqKYKE1EzyQyuO/kFL53eAyP9sUxlbOjYHHSdG4jZFrxCjkgnYQLSeyvMeOufQ24a28DNlFI0OCnTQm86ghEh4YxeeAgpk+cQKi7F6mpKRTSKZgdDjjr6hDYshk1u3ehdu8eeDjWSh0IoSTH2okx3HNkBE/0RRDK22GyOQAKf2Os5bJcCMjAnk/iijo73r27Ce/gS4S6RS3qr7rrTE9ICSgBJaAElIASeO0SUIF+Gf/2+UwaU888h/7vfAczTz8Fy9g4xTLg4ITeTIVcKOSR5vJLjC6ymVqKh2uvRttdd6Hp9tthtonIXrpNxdL44iO9+PaRafSl3ICvHnAHAJuTmmPWEm+s7GRSQCrKg0zDm5rEmzpd+G+3b8I17f6ld66fKIHLjEAuncHATx9E7333YebAIViCM3DTI8XGsSBjTazfGY63OF+52lrUXXctOt/5djRedx2sLi5qLdOGQgn8zc+68S8vDmPKEoDZW8PFNXq8iEA3zy2m0dE9m0YhGUM+PgNfega3d3rx26/fjCtbq9TtfRm++pESUAJKQAkoASWgBC4nAirQL6dfa35fKQhEmJ/9+6/AdLYHDTSyeWltc1A0zHd8zXKbNF1kY/ksxnI5ZNvbsfFDH8KWT/zGki7vEvv6O98/iX89PI2IbwPFeSNgpzBfhlWBFj4kZmCe7MLr2Jn/9b6d2NvsW2YL/UgJXB4EMnRjP/6P/xtd37sH9rEJNDiccFE42znWmIbhfJOwjzTd3aMcZ9P8M9/Wiu0f/bAh1Jdyex+NpPCnPzmJuw+NIV21AWZ/LUNTKMyXaTLWCrEgLKEh3NhsxxfeuRu7GnylGuuX2bN+pASUgBJQAkpACSgBJfBKE7B8lu2V7oQef/UEhn58L45+7nNwDw6hk9bwAF8OWvIWR5nLv21830W39gBFRZIx6kMvvWTEp9dee23RA//FQz34m6eHEKvZClS38ru2ZcW57MSIb7e7UXAGMEQ34JNDQbxzTwNcTGylTQlcrgRy6TSO/v3/wul//jbqIjG0OV3wcDzY6Fa+2LNc/m3jOHBzrHloWU9wrA0ePMywkgZU0fV9cWhJiskWv/xEN7750jCSNZtgqW7gOFres2VurJnsLuStLvSPTmB4KoS37WqEXRM1Xq6XmfZbCSgBJaAElIASUALnCSzWc4rmMiAQOduFA//lv8I9OYHNTiddbS0wr5BJQD53Uqh3OuyojjMR1f/4nxh79NGLzvbFgRC+9LMBJLytzAJHcX7Onf2iLxZ5Q4yJJqcPheY9eLo/QvHRX+Rb+pYSuHwI9P7ox7Scfx+NqTRaKM7Fas7gkWVPQMaBLIi109LuZiK5A1/4K8xwzC5uj52dxD2HhxH3NsMSqOPHq7gdi2u9J4ACF9DuOxPEdw4NL969/lsJKAEloASUgBJQAkrgMiSwihnhZXh267jLs8WTlp/oF+u+JIU7/Nk/QSEcwlYKhpVt2wv3YqG82MSEVo5oDCe+8EVkIpHzX5B0gX9DUR1MU2I0bFnRal6sf/KeyVOFpLcF/0G33d7pxFJf0/eVwLomEO7tRfd//hCuqWk0csyYVxDmi09GrOntLjfM00G89Jd/xSRvs+UJ5XuxdA4PnBrHmRhHpOR3WI04P38gWvH9Dcg5/fjzB08b2d61KQEloASUgBJQAkpACVzeBLROz8v0++WZPCqVjiGZYim0TJKvhFHf2G5zwcGX0+6Bgy7i5vNJoYp3bPLJpxB84UV02h2wr8K6PX9vItI307p3qrcHw3SV3/iB9xsf97DE03MDYWQDbXS1rdA1vXYDxhmv+5NTk/j1G9qLnwzfleRaiRyT2VG85MlD7JNipXTTBX+5mPcld6gfvOYJyLjKM+eC8eK4K0i1AV5NZhOvKSNu3HpunC19hYmYHnnyaUSPn8RGjhVrmWUJJCdEE7fveeJnmGD294arrzJ+HymhdnBwhokjJObcXvZvZmK/LFXN6Bs8hodpkb9zm4j94k3GWpLx8TLWZDFOTslBS7+Tr6VJFN+XvqsElMDlSyCZLWAkWsBoLI+oZJLlzcBtM6HRbUKrjyFxVr0jXL6/rvZcCSiBVwMBFeiX+FeUTOoRZjgfHDuFMwPPo3f4EKZCA8jmmP2czWqxo9bfhvamvdi28Vr+uQt+DyftS4jv4QcegJkl1Ort5U/q5bhemxVO1nIef+IJtN/1Xpi5P3Fvn0lSzNQxKVyljTGyoYKL9ZzDKFx/cbWpBIVCN5NvdUfjOBWOYSiVRDybM1yD25j1eqffi06PGxvdEvNb4WJBpeei2182BDLZBBLpCOLJaaQyEY6zpCFGRbSbOaasjNv22KvhdlZzQczLEmXFY75TjB+fOnrMGCNOWsEraTUcW0OpBM7+x3fOC3TJ3N4TztJ6zprpFS6GmejqbjJb8SAt8sUEejybRR89ZvqiUY61MEZiCaQ4/ty8B7Swdvu2gB8bWLu9w8tFwhJLMFbCQ7dVAkpgBQK8acVZPlW8eJIMZculUrBIKUdWiPB3dMDF8qmLc1qssEfj43CqgOdGcni8P4tTwTzGYgVILgwTE2jYmfGy3sXF+2ozbmy14LYNVvjsKtRL4arfUQJKQAmsNQEV6GtNdN7+8szk3D96HM8d/THF+VO0XIXh9lhR3WCFhcJcHF4LtB4nU8M43NOPY92PYGv7Dbhm99uwpX3W0ja/e7lEAqFjxxCg6K9UskocbRV3HhnoR2JsDB5md+8LJpHI8oHMUmqVNxPSNg9GmKU6zqzwHvuFHh8PR3HvyDjuH5vE4UQaMZvUfOalKInmWOu5MB2Bs3cIV7udeEtjHd7aVI+tFDLlWjErPxfdw3onIAth8VQQodgIxfmMIbxl8ctprzKEuXh/iyU9x+srkhhDNDkOj7OOi2HNsFvdXBBbOBGNc0xEevtYGcHC666ySCC5bv1WK0aeeobjnQtg3OckyxhOSSgJE85V2kziGeBw4ehIeMGucpzkn5wJ4cGREfxkaARH4glkZayxL7NjjZZ0Jplz5jLYT4H+ppYW3N7ahK1+v1rUK/1RdHslUAYBuT8ET51C7/33coHwCBIizrlIaOJcosCFPAsX1Jw1Najdsxcdb3sHanbsLEmoy/2vi4L8q4dSeHQgx2dyATVOE6odFObu2WdzhhOSyQTvGVMZ/LQ3ix+fzeB3rnViR21l978yMOgmSkAJKIHXPAEV6JfwEjjT/zweevYbGA+dgr+GlnKvH3YHJ9OLFqXFwpdJU2BEUzje9yBGp7pw2zUfxv7tb1zQu9TkFLLRCPwVCgbZqSSNk1JRQVrWkucEeiTFMmwWEQxrtGrOfaVyifMCXQTD/SMT+AcuRjxG63muph6mpgCsjKU3SV12Q6BTNGQyyCQTeIoJtg4NjOKpqSA+uXkDbq6rMcrIaVMC8wkUeF2FYqO8lvvFVA6XIwCbxcnL6eLbm7h55ynSs7wuI/EJpLNxerB0Ush7F1z36XAEmelpZmVnAsY1GA5u9mVigsfjfi2BAOKMQc8WTBWL//McuCARTGbO/1Ms5I+MjOLrp7vwHJNCZgJVsNAzxsGkkgvGWjYDWfh7gZb1A6fO4OnxCfzyts24pbGBtdV1rOlIUwIvF4E088F0ff8enPmPu5EZHoKfY7iJi3nyzDPzJiQL+ulICKGhAfQeO4r+n/4EW+56H3Z//NdhlkW3JRpviTg2lccfPEIvnmABHQET9tRbDDd28WSfm4/IPISe77SomzEaL+AhivQDYzH8j9vduKmtUpPAEp3Tt5WAElACSqAogaXv6kW/rm+WSmCAlvMfPf5lupQNoanVBwdXqRdb6eb2JQ9Iu8MMG93CnS4bxkd68eMn/g42qxO7Nt94/pBZitY83cDXypIsUjxPMZyjy7w0KR1loiVyzRr3ZebJSX9lkvD9oTF84VQXjtGyae7cBotY6ha71Eo8rIh1WgrMFBWJUAg/HRnCyPEz+NNdW/H6+to1O/81O0/d0StGQMR5OD6G6UgfrzUbXEyYtpTbunRSrkezXH8UzPK9ZDrEkJNuNFRvN8bbXMun6clBt1L5/lo0I6STfc3QzdxWxUUpKaDO/0n/1+YIBaOcojSJMX9weAR/dewEuqRE4oaNsHtZJ32JsWamC3+BYy1fVYXHaG2fpGt/lvu4vaV5zc5/LRjqPpTAq5WAiPNDf/tlnL37X1DLcbzJyRwzDI2RET3/FuThGA5wTGf4bB3iwvqRv/sypijWb2alCKvLVRTPBOPMP/lAAuPxPK5psqDOTcFf5KYjx2EYOuchdHPnX5rcNjxKV/iP35/At97hMrbVpgSUgBJQAi8PATWRXALOyVQU333oi5iJDaCpzQ8n3dqXEufzDy8PSKfbym18TOY0gQee/hqmQxfKJ5llss3V9LWS0DkeUCbt5nO1yhv8zO5uylK181Vpo/AwMxFewGmB32XF05NBfOlsL07SFdeyheK8uvpiwbDomNI3+V5h4yYchhV/cuwM+hk/q00JzBFIZaK0ng8ZbuweJ63ES8SULyYm37cxHt1pDyDJWHXD+j6vmSRJIV8ioNeizY1ZC8sciugPOG10n+e7RgK7Shsj7JNxdNRSaHNXRxk//6VjJ3GW7uzmtnYuhDFGfbE4X3RIY6xRpJsp5o/lTfj7k2dwJMgkdtqUgBK4pATyzBFx/Ov/iLPf+gZa+XzvoNB2itWc84Fi64PyvljVN3nd6ORi9tAjD+PpP/5DZOkJs7gxvBz/90NJDITzuK7ZigZPcXG+eDs5rpdC/c4OK3N55PGHjyWZVG6tZh6Lj6b/VgJKQAkogcUEVKAvJrIG/37y4Pe5un0KTe0+WsRXv+osbvCtG6swEezBzw5873yPnPV1MNNFNZmrXEBzDm5kdLZwMmCvlRrMwK5GD7xi6kuGKqfAmDlPLortDR6EMll8s38IB+jGj/ZO4xxKbpwpWJi8yryxAwcYy/6l7j4j87s2JSD+7BFazzPZpBFrLrHYq2v07qBIt1l5jUZHWFnhQslBG2OyRbBmJQv8Gti4JSmiET9aV2t0scnnQCszJheYHNHIYldBKzABXSGXxg0dNQjS6v/tsz04xtwW5qYWiHW86Cy/2PE41sw8b1NLK55jCMp/9vVjJp0u9k19TwkogTUiMPTYozjxj/+AJi6oNTNBajHr9lKHqqelvZOLfqNPPI5T3/5nrq0vnBv855kMfkJX9b11ZtQxAdxqm4PzgZs22NAzk8c3jzL0TDX6ahHq95WAElACZRFQgV4WtqU3StB6/uKxe+GvcsDtLT/Tut1phq/Ggq7BFzA+3Wcc0Or1wrdpE4IVZn2WfYnoCNGN1VlXD++GDcb+r2kLoC3ggCk0VKlmAKKTqHUUcMumGjzJOtKPTwRRaG2DmVnZy2lmH93h6xrw9Z4h9DHZlTYlINnaE3RRlyRvpVrOF1OjDwnFPa8tWtSnwrPjTL7jqq+Hp60NcQrrbKUCmvsLceLceM3V58sXbq7zYGc9Ld7xGYrrC7Hji/tXyr9zkQm6phbwrt3N6I7Qe2dwGGZme7bwflFOs/jpDs/z/xH3czq0MPFcOfvTbZTAq5nArJeNLLKtfqEtNRPEi3/5F/DxHtNCcb56CQ2ISK/iQl/fvT/GzOnT51EnGFD+dy+lDGHeWVX+VK+KieQaPSY8Rnf3npm18Ph5NV8Nem5KQAkogbUhUP5de22O/6rbS/fAAcSSQVRz8l1pq6p2IRqfYmm2o+d31XjHHUg77ZiRbNAVtBQtbFGK5bobroeZ5VukOW1m/NI1zfCwRBU46S+3ieCwBHtxJWPvr2jz4rmpGQyIuy1jzku25hU5uLmhCVm7DV/tGSjyqb71WiOQysSY5C1lxI6XEkKyFJ/Z8mtuxrJPGrXTpbka6lGzayeidHNPVeixEmKehzSt05ve/c7zXWivcuGWzlpU58LIJ6N8f/WTe9lZIRVHITKOD17VijqfHfcODCHJ8Wypql7qdEt4n14rTGQ3yD6/yMSU4mmjTQkogQsE8gxNkQVCyX8RjA5iKtJvvILRIVaJmKQ3DsdlCQt7kugt2teDFnqVWVZjOp/3Y4iob6BITw0OYOiJx4w8NdKOTORxmpnbt3Ohv9x9y35kktjuN7M8Yx4vji1vQpfFzBn61Y/Q222IiTBH+WeEc43lt5p3MvpXJaAElIASMAhokrg1vhCGJs4ghwyt57Oit5LdWygOcibWKp/uPb+bpje+Af7tO9D34otwi3t6GRndRYL0Z1JwbtqOlre+ZUEXP3BlM+45whJovWdQsFP4OH2rOoUCs0Jj4izaHFn89i0bEKS4Oc465yaJg62wdruZkxATk13dOzyBP9uzvSxrw6pORr+8bglIWbUsa55LPPfqXdsvPi0HRX6K1niJaXc5GIvNrMhNr7sWAw8+iCnGY7ssTCpXhnkrQy+VUVq3fNu2of2O288fWBYU3rq7CY/3TOO+3gHkbby2HayJvopW4OJEbmoAHYwr/Z3XbzYSuz3JskxmSbC4RMKoUndvYmUFcY9/nt4vP88QFecKMeyl7le/pwQuZwJ53nfEaydKEZ6kQM/kUoYQF480uT3Iy8z4cKki4eZ9xO9uMHJdFGuyXd/998HD57xPyoxW0CQm3c1kr9PHjyM5PQV3QwNeGM0ix3W/lkBldhiJR3fT1V3i2buDOYaY2Ra44cvSYowH6kplMUhRPiOlY1nXTZYJJOjIwxtnLfu3kflo2u1WVo8p40ZaARvdVAkoASVwORKo7KlwOZ7xJe5zKDoBi1UeWZU/hOTBaDLnOBmY4UMxx4eiBTa6em/7rU/jhU//Fob5QG5l/BlTx5V8VqymijFOuIOcEOz5pV+Cp7NzwbZ+pxWff/tWjN19jCVWKNIbNtOcSHFdwhEKGcbTBgdRnRzD776lE6/fUoMXpkN8aDOO1VezYqKqEg5hCPSzFCERnoO/zElNIhXBZHAA4dg0BdmspcNudcDrrkZNoAUBb30pXdHvvIIEZDyItVvGxKyNp7LOmM8ll5N4dte5tbVqWtA3vOlOnOrth4ux3Q3nPE1KPZJYk8Z47afpMn71p34DlkXbb6x249eu70B/8DgOTfbCVLuB+RlKWxCTsZabHkKzOYo/uG0zxGU+xsWwM1wMM7dWldrFJb8nSeNM7G8PyzrO5rwob8Exy9j4bC7JV/q8d4KZITpSo95qcfG1hmUdlzwb/UAJVE4gx/KMQeaqCMdHKXxzsPP6lSSTFt6DZMFNao0zw6pxncs1P03LeiQxhbrARnids7kn5vciHWbJtO4u1DDRWynP1+XOwMLjeymCw+OjiI+OGAK9P1yAxJDTQ73iZqXGt1NoT6ckd40I9gu7PJXI4Nl4GhMMUJd7npMCXCpKiA6X4J0Qc8/0kt3xlBkbmJD2Ohovmu1MTltxr3QHSkAJKIFXLwEV6Gv82+Y4EV2rBWITi5WLSM8z4VqB1jGcs2I13XYbdlCkn/nrv4YplUYTLdMO+eIKjYWjME7BMEArQMcv/yraf+6uoltc2erHF9+1DZ/7aS9+NnwS+UArCj7WLKeVr1griAtsPMgn8Qiz0Ibwu7dvxK+/rs2YdKTY9xhnLitlkS6236Lv2R3GyvwUy2CtVqBHKchP9j2LLoYhTAT7EOPkKc162FIEzmJmzgBaPGoCbdjYvBs7N92I+urZ2Pyi/dA3X1ECYn2aTRY4OxGsvDOz00UR/nPNwnHV+a53IjIwiKF7vm8kdKunV0kp4zvNa34izUk697H5Fz+I1ltuLtrF12+uxR/esR2ff/AUXho5y6oFTTB7uZjFBaOijeMpz7j13MwYOp0p/OYNHXj3vhZa7My06OWMmHnHMjWRi+5ziTdN3E+IxysnBl8WOuKpaSRS4pUQOyfOZ934xdpoE48Ei5tjLgCvq45CfYnzXaJv+rYSeDkJyH1hOkwX9vgIr10XfOJlY1pYneV8ikpey2I1t3IukEgFMTJ9Eg2BTQh4mhd0OTE+gVw6Re+c1Sa3vPjM5Vlrp0DPhsMQ4S8tni4Ydc7Xosn0ghFwrJGF/cP/AAAgAElEQVReYFhRwbCoy2h+LJJiQkkuvvF+XMN7kIsvqdk+X3znOcvM5s3GPOAkrexDNMW/2e/EZhoDVKSvxa+j+1ACSuDVSEAF+hr/qg67m5PRtXkqFrgfCWOzW6Vu84WHuEycOz/2McOtrvsrX0GCD+UmlmDz0VWOa/kXnZGImQgfjqPZNGZode78lV/Dlk98wkg6t1R7A63fXocV//jMIL5zrI91psdRoCUdLsaRsz807fOpS8t4KgYWK4eN7n43tznwyRu24O276hnPPq+/chJr3FbzYBd36O6hw3j28D388yCypjC8fjtcjM1zczJhTCcKaWQyI+ib7GdivudwoudpXLv7bdi37TbD2qdtfRGQpG7ykthtmRyW434+/4xMxrKP1ElfeEt0NzZgz6//Ki93E3ru/ndaqXNo4CKRh2Pw4pE2G0keZkK4CYr5hM+Hzvf/PLb94vuXrFEssaFv3tGAesaPf+3pPnznaD+SkUkjtMTk9FKo89qT4UPreIEu/fkYk+Jl47i5xYWPX78Vt2+rh5/jdLbv4u5fbjT7fBoX/s7cc0XPs/i3eWxxAU7NGLG4Ei5gxPdT0Egiv7k8AUZ4Aq2MqXSUiwozhrtwjX8DxXolcfNL9UjfVwKVEwhGhhBkOUenjWVTjaSSxUb/hePIdS9hM3ZLI8KJCYyHuo1FKI+z5vyXcvTKkWezWL/XohnPRHqW5fmS5qJzSlZ83NegySNcMriLFd127mb7SDiFxynQ/fx3I8X2UssM8r7c5+w8Tw//HOFC4j3TcXyQZSHbz9271qCLugsloASUwKuKgAr0Nf45q/3NTNIiwjp/TkCUfwAjti1npet13UX7EnHd+dGPwM0M7F0U6aePHIGH/mQBWqZkRV5+WHlMJzkRDnHFOkpLmGPrVuz+5CfQ/OY3w8764ss1ie29pt2PjuqteNeeEL57aBQ/PTuC4dEh5EUYGc/9AqhzcX2rG+/b1w4R9R01LFvFVfS5Jn0JiIVAYtPXolH4yLk1MFFeKU1+hxPdT+HBZ7/JRYZuVDVwkuTxw2ITMbNwYiSTEB9X9tNc5R8bP4r7n2TCn/g0btj3XthtqygNV0rH9DsVERDXdnGPFu8ScSuttGXPZVJ32C5O7uhlNvf9/9enUbt7N4787VdwZoQupBxnfr4kNlsWxSR0RJKphXids+gZ3Fu2YN+vfBRtt70BDiZcM5TzEk0mr9e2V0Nc3u/a14z/ODSMR7snONZGZhfCZKzx4nRzwn0Dx+R79m7GG7fUMbbURRFwYaxJX/xcOIivUWm0ApPb1XJBz1Jingu5X8WYYHJiptv4TRw2Hy2JjK0XF+BFMt9GRgWbhwIixW1CGJ0+gdpAJwLuhVbGJZDp20rgZSMgC00T4W6Kc29J4nx+x2QR0e9qwAwt7+OhXrTzmp/zFrGxfKhJrN7iHbcGzdgL87TMhdJsZOx5grfHDC3etgpN6RJ/nqLYr3GajPvQUbq1PxdLIcD9NnExfum724UTk1ugePq18PuSQO67wQR+vd7De+lqltvXAJTuQgkoASVwGRBQgb7GP1J74066bjoQDadZaq0yUZeiULSbPWiVOPAizUYLXevb3oraa6/B6MMPY+Df/wMDBw8in4if/7aJ2dP9FBbb3vdzFOZvgqu5GWbGvJXSRKQ30LL3lh11hvhOMCPrYCiFgaDElOZQz1gyEeQSt+7iQ3duZX3+vmuYdb2dYvpgMgkzV/ZNZcaNz+0zT/e9/QFfyW6BkgH//if/N2PWe9G4wQMH+7qUVpL3Rbi7yKeFK/sT4yE89vzdcNl9uGb3Wxd4MZTCT79z6QjI4oq4kcpvJiK90jlelqEOUqrNbi/uVeKsqcGm974bLbfchJ4f/hh9P74XA6eYoyF5YawVzFbU7d+Lfe96h5EQTmqeS7K5UlsDx9Od2xtw86Y6imy6goaSGAlzrNH7pZazYokzd3H8uOhrOn8RbG7/NoqBnYx3fz4+m1dh8QJUqf2Q7xXoBZDnmN3ChUA3PXNKaSnWkR8LnjbyArhpKVy+9N1scj8bLes+t4NW90lMUtjT3s5/aw6IUnjrdy49AVngHQ2eMTxrJHlkOWNKtvExBj2WnMJMbBS19BaRBSt3YyOsTOgYjUZRX2GER573CFkgtFdVwVEzu/h+TZOVFm+GtEUL2FRVioRemmdcRD4XErdUmxFiErhno2lDlDeKOF/lrsUK3+iwYCCVwyORJN5WRe+apQ+tnygBJaAEXpMESp89vibxrP6kO1r30l2zGZOjp+ELSPmn1e9DtpCEMzOTSdR429DRsn/JnYi7u4juzg99yHhlIxGWbelDhm7vskLvbtsA+7kH9txOxCAnZdb6WU/83tEJHAiGMJKkux3fb+YK/FVVfry1qR4dXreR7EUsfB4mdZFXnceOK1pKS2Qlx2tm+Zi9FA0/Gp3kQZlEjlaIcltehAcnM3dt3VjSLmbolv/Uoe8imOhCCy2PTlfpl7sI9foGD8ZzUTx56DtoqN3I32FvScfVL708BMSiJSI9TZdvWRQTt9JymiR/SmUSqPK2XGTpnb8/Edvupibs/rVfxe6P/wpSM3TPHhpGhuPIzrHi27gRNs/CTOzifi8x3F3hCH7K7x6eDtL9PcW+mtDMTOtX1Nbg9uYmtHncnEwzcRLfnxtrsgB2RSut7yU2K8fprXTJf66nDwUu0pncq8sKP/8w+XiMNdrjuL6zHd4SFvQYaGBYweV2NyvOVzHWGL7jcTbQ1X2Mteh76K3ChbQingwlYtCvKYE1I5Ck9TyenIHHxcU2IyFleU2SUJrNdiMng3iNSJZ3K6sk1O3Zh7EH7kOOD/xKSqGJB0+U+/C3tcPT3GJ0cn+9GdsoqM/M5I0yaRJDXk4T6/lAKI82nxlXNlpwKpnFJBfr6yiyecspq0loWRWF+gvRDG7w5Y34dW1KQAkoASVwgUDpsyilVhIBC61ot1z5C/i3n/wZpicTqKkrr0ZzjPFdyZgZe/fdDp/nQtzaSp2w0qpetWfPkl8L0Yp9cCaM/3m2Bw9OMtkUJ8cFKV9Gd2HDGhmK4bsTQXzmVDfeXF+DT2xqx7XVVUYZmHKexU4+eK+vq8b2kTGcCgZh4aTEVM7DmG6AObr81tGl90MbW5c8v7kPxKraM3yYseSPo6aJ2Xbnp51dcevZL4hIr651YWigB8fOPo7G2g5aUUpfnCjxMPq1MgnYKeIkpnOa9Ydl0mtfopzRcruXsklJlk2y8Jqs9q0iKSAHi4NhIvIq1mSxK0IX8WeZCOrrZ7rwxMQUsnRnBcWumYnjDK91hk/cw3Hxp4eP4c6mBnxy5zbsDFRREJd3W7Zy/3e2tuAbXT2YnpqCnaXSqAqKdW/Z9yTpY46LDzscNlxBzwFJPrVSkwRaaSaG89GdV+6Bq21iZZTfUuLRI7ER2OnuPptjYLV70u8rgbUjINejPBjlXlNJk8VDuT+lszEjaaIIdGmb3vFu9D1wP4IMjamroAxpnM/HFL1d6vbug50lTaVJBvffvMqO3/xJAr3hPLbQ5b0cg8EE659PJgp4z3YLw2pMOBpiRRmK61IS0y7HrIrP8kmq/2N0l79lDcrSLncs/UwJKAElcLkRsHyW7XLr9Hrvrwi5cWYJ7xs4bbhU27nSXKprnMRBJ2MZDPeFsa39erzpxl8x4jjXog3Ek/hKVx9+//hZHOck2tzcCkvnJtha2mChu52lgS53Tc0w1dQxw4wTp0MRPEQBkcnmsFkshGWK9FqWghthSbgjo+PI0qpnWm2NZhHn09OwjQzjtzta8OZGZpRfYaaRSEXx0LPfQDwzjDpawmVCUU4TkZ5n7N34xAS2bbyOiyUXl8spZ7+6zVoQMBkJ/GTCm86EKQwlmWLp4lDEucSXigW+xtdBgVhcbK+2p2I1H6L1+asnT+OLJ07jBMe0hV4ujg0bYW9thbWetZHr62GTMVddYyyQnQ7O4AfdPUbW5Y0+L8daaWEo8/smV7iT7ugJLgwckAzRnPCbOY5XleZNxhoX0pwT4/hIxwa8saWZlv3lBXqOeS7Gpo/zt3AaZadWGJrL4DQb5SSltrSLibg0OeMyqPSjl4WALP7JNenmdV1pk2rpaZZHdNBDRK5vaeKRM3nwAIL9/axKYuP4X/1zKktvuAFWc3FRnO/8yMeY8+JCmcWNfgv6KM6fGcrBZ6erPV+rOcRMsoCXxnLYVWfB717LCiosIXuYglos51LffPW9vUBRzjVC13nJY3eFu7ScMpX+Brq9ElACSuByIaAC/RL8UmL52di0G2OTfRgc7aN1jkKCE+eVRKI8aGMh1hMdjqK1fg/eceunUe1vWpMe9sbi+OLpbnyDrubxhiZYOzbBzHg1cZFf8MTmQ9MkVj7WWzdTPEhplMPj44jSBX6332tMIlbbHLTANbG4dHcojN6ZIPIOehXQ9b2kRsGQD83ANNCPt/rd+L3tm0vqg7i3/+SZr8FDq4FHMtmV2YyFAE4gprlAsKFxHxprOtSyVybLS7GZxDmLkEsaGcEjhvV2cfmjYsctcNKdprDP8OVjma9qX3tFLqxzxxDL+EgigS8dP4m7ubgVq6uDo30DLEwUd9FYE4d6jieL1wdLVTUyFPYvDg5TYKewnd8vZ6yJm3wDF8B66Urfx3FTEJHOBYDSRDrd8blQYBkbwR1VAXxs6xY0uWmFX6HFmRguRKu3ixbw2brmK2ywxMezi24mw8ooLu4O5n7QpgReSQKTkQHeF5iRnaK68kaBnosbyeakvKA0yQcTYELJ3kcfZvWGCLxSfnAVfuMSe97PXBFRXwD7Pvkp1F9x5YLFaymmIuL66EQOhybyXMCjSGdh9FKE9Rgt58+P5MBIPXz+VpexnzFavE/QxZ0636h3XmlLSmJJznuu99GLr8ydieeOeDpItvwoX5HkJBLpsFGLXqrfLJ8Lo8yD6mZKQAkogUtMQAX6JQLsdHjQ0rAV8XgUA8O9SBox3oznpjVqsVDP8QElVvOZqQRCUxlazm/Cm2/6DYr0rWvSu2nWDP9a9wD+ieI81twGawtjbUtIXiW1y00UDymK1DO0yMkUZW+VDyK4V9vqHQ60c7LfMzmN3olJI8bezHJVpmUSUBWYjTo/NgrL0BDe5HPiD7ZvoiWf1vASTAB9I8dw8NS9qK5jbC89GCppIhwiUk7G3YLO1n38DUu30lZyXN22NAI2KWck7qNM9JZkia8cLeNG5nG+FntaiDDPsFyZTOAKhQxrcNcbru1rVYc7xhCSr585i3+h0E41NsFGrxQR4Ss1GWuyKJbhtdZFYW/nxHUPc0c4pALCKppMcqvosdLOcdLPRaXBqWnyKMDM8SfHWKrlOdayY2Mwj47iFlrwP71rB3ZQpC/mV2z7SHyUiyNhI/a8lO8X28eF9wrG7yO5BVwUMaVJieX3qJ8qgXIJzEQGjQXstRDoknBOvHUk6aibCefmmqu2Di560/Q8+STnCQmjQoTkk1ipZfgQ7aOnDp3wsfdTv4VNb39n0QSwVcy8vqfegu4gLekU3AnWR/dTpEuytmItning+FQehynom30mfOXNblzB2HPp0ji96c4kskb1CCmbVmlL0HyeLpjwOq991eXm5D4xzsSSk8xbIdUjElyglVCntNzfUxHmDphGhIJd8ggYdem1XGqlP5durwSUwMtIQAX6JYTtYd3wtsbttNDV0wI7gcnJCcQp9BLxNBIU5DFmQo0wU3OQyeDCwRRXtttx4/5fwM1X/DyaajvXpGfibvvo+BT+mgJ9vJ4uteLCvsxEffFBpQyMyenmQy6Ds6NjuLE6gFa6za52Ii6P8jYK9H3MwC7C+9jwEDLRiPF3UeuyeCGlpAoUOAUmqMrRpTw3MIDq8Aw+2FCN39nWid3ctlQXwDP9z+PM4LOoYgy5tdzsOOdgiNaLzKThcTRgZ+cNFVkJF/PVf68FgdmM7lKjWFzcRSyK67pM1uSVM/5MnnOFj9CFOmlM2Kq9rQh4mundsjYhJHImz01O4r8fPYFITS1d2JtWN9Y44TUzq7NkYx7hgtg2Xu+bmFNitU0WsBo5RndxrKYZWnKWojsxEzJqqcsYM+bVMuYkUzvHWpZ9znA8Omhx/xBj2D+1czt2M+9EKQth0rcQBXqGViwR1JU2KdWW4+8jCyZuu2TNXv1iYKV90O2VwByBcGKcVSIyFOjlJzed25fkRZFx4nZWnXdxl8/kGevf2AF3ezv6XngB0xyr8pyT/C3FnrPyTJ/mc7IrFkOY4+O6z3wO237h/bAsEcMuw73ebcaNreJdBPxsIIejkzkjrjxBF/MkS7GFKdpHonkcn8wzPEZizvP44E4b/uYOFzqrLiSDm+b3zxrVZWbrmld6pUQo0CVB3s0sb1r6SC/QY2cMQ1PHWe0ixMUCJsPlgofL4Td+J+PFahzihZOnB14sNU0PwEmytDAEx6uLfpX+aLq9ElACLwsBNQVeQswyuZS66K/b+05sZfzywNhxdA8ewOhkF6LxIB8YrG3MuNfOtk5sbrsS7U27UBNoZh6pEt2/S+j7OGPT7h0bxwDdys21jN1ehTif272URjNT2A9RLP9z/zCu4sTfucTq+3JdkonCPmaI/8yurcwS34Bv9Q3h4aFBRGQjTlIKc5Z5CgcvJyFvaajBBzZ0MkldALUs11aqYJDd5USMsK3BIr+xH5nY5FgrW5YStK1PApLIqdrKrON0WZdsyQla08Vilc2l+auZDc8Ht63GcMUWN1MRgWspAGXi/E0mhJvgGHPSIlbWWOO21tpa9LMKw0NDo0aStlpav1fbbBxLexjC8t/278Gdbc24u6sXj1OEM6QUPPHZ3YlI5wQ2wIv7Dczr8MFN+7CPwrxmlccTy2BpLvSlnoWJ6wjSUR1rpRLT710aAnbeJ2a9bSp/lsg4kfuNjbkyFjepXd751rfD19qGQ3/zJXQffAnWaAwBft9Na7UkgBRPmDi97UJcwMvwXla9/0rc+gd/aCSGW6nJs7fZa8If3ejA+7ZbcffJDO7ryuDEFOsvnBtm8oxr4NTjw7tt+PAeG3bU0j1cNpzXnFTRkhxOSj8W+Gelz9cU9+PjgZf27Vl4fGEYjA7Sat5vLMZWu2l0oBv74mZ43gg7LoZI6cxEKsg69N0816yxMFtJRv7Fx9J/KwEloAQuBQEV6BVQPTEew2Nnp+n+HUOMZUc8DPjaUu/B6zdXY1cjV2rPPdxEcDeyTFd9dRv2bX0DV4xpJTYmoPLQlzJmjDtjFvVysh+v1H1JDPfYVAj5esadGwmjymtmxoznq2pwz9gQPpvZQoG+etEwd+Q6uuC+uakON9dXYzqVwRHGpp+NxhHlxMNL8bCF7rlXBvwIUJS7aEWwlDELcDlpqSfjwtzso7zTNraSn0r25WQG97UUdBV06TW1qYyUEcZDdrOe70Scid1oxXHSK6LeZcJmlg+qpwvn3ERSJl5iQbHTquL3MH+DXAPnhJ5M2mS8zf6Gi2aea0B0nNbqB+iebm1vg4nhG+U2M2PIs4xJf5ahIH2RaFkCXY4tC1r1HLdvYkjLLXS1D9Nb5RBj03sY6xrjWJNEdJtZAlGs5QH+3SVu9mWMNSvzAEgirbVqMgmX2FEda2tFVPdTLgEvF9BDUXp7MXymnCoRc8eV58es547dKCNYrIklXWLI3/Dlv8XoM8+g/8GfYPrkCcSZ00IqK8iCn40eNk1btmLjHW9C8003GaXa5pokW+PMgmUdZ8u0ygKXjGdJPMkaLcYiszQR3p+9yYLP3OjEKO+r4/HZuUidy4wGt7i+F+vd7HsBPo9FUI9xocDH2eMyX116J+c+Ect5jJ3e41k5BEg2kftCKD6G6eiw4QElVvNSSmtaOb+SChFSrUPEvY2u7lJtQu8vK/5E+gUloAReQQIq0FcBX4Rahhan+45P4vMPduG5wSi35lNPVnClRipd2PgklUcJrmrx4P+9czPesZvZmsVNXL7G79nNKyddWkWXlv2qrLhLrfNuPgStLMFyfsVg2a2W/tDMxFWh0WE8w7rp72puWPqLJXwiEwcf4+DltdGz9kwaGSKQzzPhVCpXVom1+acg+8gyOU4DF1iKrdaXcLr6lVUSkCkj17xwfCaHh4dzGOJEUt6TOaaIcaYONCw/Jl7jG30W3NFmxTaKdRqbjGYIcZk+rr0OX/JMHmUICAM24PJfiC9d8svLfsCesy76mYkxDHP8Xinns+z3l/9QFrikdJu8WrjftW7iuSCTZ1l4rHSRUfYjYsZKK6NOoNf6l9L9rZaAx8EygzaXYUUXj5tSBGGxY+ToJi/u7X53/YpCX0R3221vNF5ZivMEKyrkmMNGrOxOJp20eRYKfBHkIQrmIF/TvGlKPfTMuU5InLiXN8waiuoaGhBEXM+FiYlgb/Ga+SrW4+Lv+TiXaeZ+BjJ53p9Zu32xib34ZkXfDRs3cCaxKzGDe5IJPUOxUeM3cDGr/mp+C1m4tTMEKpefoUhnOM85V/iiHdM3lYASUALrgIAK9BJ/BHHpOjMRw+cf6sF3jgaRtHCiS5d0eFmj3O4yJtDGOjTLqID1jV+aHsIH//Uk3rt7DJ+5cxO2sdRXKYlfSuxOSV9LcTGhh9nbYaNLna18i97cwUxSIo0PxyOso76SQJcSVhmyyGTFvZiufSKX6JYnk51KJ/Fz/RGXYmmzYmwhkipvPeoC7YhHx+Grksl++RInxbIyTIeNtqYdhqeDtktLQOZtY4yBfITC/Mh0zrAAtdCy4yd6GUPyUxqLZXxFGDs5we9+/UQK++useGu7lS7albtelnOGR1meTJIerrqMYJGDmaw2ZDlehpkEKk3r2XLJ4gxPES4MyjgTLsKH9jL+WXp5xyJdWPDW3FgrZmF3OaqNyXKG2dctFZSjEk8HifcVS+JSVsaV+qmfK4G1JCCL6rX+ToxMnzJyWEhozGqfJTI+JYGZmRZwn3t1llsrvWl8LM+4VItQlPdTlA+lcwxfKRiJ21gZdLZGOf8td4VJKvgRzgU8/F4r709tNJF7JL59qZ0u876I+q0um5HJfYaL1o08p3L2k+ZNfprbd7AvG+wrR5+Lh44kgksxAZyH95tyFsrFki4x6NHkFDO+T6LO6tZFwGV+a/1ICSiBV5aACvQS+Is4f3EghD+5vwsPDWSQrd0MBJgJfZHoMx5UEj/Ozwp8pWeG8d1T/RgPn8D//7YtuG5jVVkiXVzBEny4imuvPCBddO91Sv2UFVqWD+gQk8mY5GG8TLb0FXZz4WNauyVOfIJx7Uu1dCaByZkhTAb7MTh2FsEIs1lTqNspOPyeOjTWbUYzrdu1VW2QJHqraeIRIMceoTUhyMz0ESauk+hXNycJVXSHb6DrfAvd+CXLvMPuxp7Nb8BTR/+FSfmycJfoRre4PxkKwGg4g46mq1Dj529e1nRk8V7130sRkCWXQVrL7+vPoo9Ji+roxl7Fmj6LDTUy9KTUTy3d26so3INpE45SzE8l87ir04Y2WobKmTgabpec7ErJQzMHm5sTyDkPmKX6PPf+BK9LqY4gArPiJkKf13WI+Rik/Fqx5bU8LdaSsVjKkqXSTKyYT/I1uxgmme0lUZK4+otr7mrqw0vfxVNokuczSgueuMZH2Q8R/272q4rJqOo5zhqdLqNGumS4lvrnUurOZvWWNXk2eHFRT0rfzSZ4Ku4GXDFX3YESWCUBP5O8JjwzdK8eNxai7IawK+3uIuI8np4xklXWBzr43F590selujtBgXsqmYH8KXkkGjkncHCMLjYESDaWZM6EGPtyhve2IP/cYbeiiu5GpZ3Fwh6IBX2324anoynen3hsI5ndUr28+H25x05xO1lIuCPABfsSNhZ+ccaR2+jFUEk2dtneZnEiEp9AjbeFx744H8DFPdZ3lIASUAIvPwEV6Cswl0lp12Qcf/lIL11t88g2bAM8LCe0wnbyeaGqBVlajJ8Y78J/p+X982/fht1NF2LTV9gFRsIpHBmOoHs6geFQChFmTxULVg0fjhuqndhW78ZOxrr7ncV/RumDCHppEou9Up9X6s9cNhlbkQequKaOTvXgRNfPcJSvidAZJrujHU8mATywcMyPcgJ+nLFrrmbs6LgBe7bcio0tu1Z84Bqija6+T04F8dgEvRPCUfSlswgbualYAod/tNDMusfrxk21VXh9XQ2zxXuxe/NNON79OELBYU76GecvM4JVNKkxGw0nYcq6sW/bbfB5alextX61HAKhVAEPDGbRT5HeTKu5l79Zkcttwa7FzbKOURJOrlmNMjPxjynu39thRSMzF5fS5HfuDcZxfDSCPv45xt88QRdOG/db73VgY42bY82LXU0+Y/wt1WQRYS1yHhj7Z59YfciI8Vx8RJn0p5mlXmr+ijUoxyR4s9by2RhysXZLFvsI4zXNdBX3umqNxHlOu3+prp9/XxbBBpkd+smxCTw9Po5D9JYZ5EIYsRrNTotcGz1ydvu9uIGJ5W5mMrxNLMtWR/ExMnWUxw0bYn017qdzBxcLpdj8pL9rVfZuxRPWLyiBFQiI11gNSzHKglgkGTS8VcRFeqUQjAyTikrcc4oLaA20wgeY0KxUYb9ClwyBe5SeXREupIlgdvNBb9ztFt8s+JbMDrwU0RJIFuXC4xQX+4/w/nIVXcu9cxOElQ4473PxaLqa206w5NoJllyTW0OpYl+MHdL3OI0NtwcchjW/lCaJPlMZ1pBnibpy7i0XjkEPAwr0GMW+LG66lsh8X0qf9DtKQAkogUtJoLiyu5RHvMz2HaYo/veDo7i/l+7agU00X1cXewYWPSt5VhY81Uza0omHBrvwbwdH8Lu3djDz6PJu0lEe8/tHx3HfiUm8NBxHb9SMpKz00grNWQLTicfgt6SxK2DCTZ0BvGdvI67bEODK/kJBYuPEQuqPGwlmshKVVswOV7Trxd/kPkyMs29j4qn5TWJPz/S/gCcPfM4AOYQAACAASURBVAf94wfhZExbfYsbTi4cWGjtF0ukiIosfZIlnjvJDPYHznwfPUOHcMP+92D/ttuZgK24xUxqvT47PYNv9AzgQYqFKZZ8MzEbvXgq2BhTKzOSHM+vP5VCXyyKB3sGcfXIOH5xQwveXb8B1+1+Nx478E8ITsdZE52r9ZyolNKkv7EwLYesHbur8xZs3XCtllcrBVyF33lilOWDuPLSQst5KeJ8/uG8NKkzLRyGmEju6fEc3d25eLPY9L6of8Msc/jjY6P46ZlxHB6JYihpQV7q5dJ6LWPNnJ9CnS2Hnbx2bumswfv2t2ArxXqx1i6xobz2CqwgYKJ7eiVNxixVuJEgTiz4c00WwsTVMxgdYF6EJLvJuFTD5ZNVDiSxGv+Ta1dcQiXuVUrMhaMjtD7NMHtxG7yMgV3KC0Q8bp5kHP23znTjaSZunKF7raWai5Ec7w4jzwb3TUv6wLmx9ujJs7h2aITZ3zvxtnaWrGN25GBkiBNoCWXxrGoiLQsKqUyEMbpN8DrrKkGn2yqBNSdgp0dKHZ//ZvMAwrSki6u1uLtLsrLFglHGXZpiUoS5jNfm6u0QK/xqvViWOokEn4liORf39mY+810limyRwn5+X+4mE9z2RCJNke64yDtpqePOf9/H++qb/S7eZxI4zoWCBEV3HRcKlqqtLiJe+j3J74lIv9VvxxUU+aU8jeV+luF9jLMpegcsP3cqpe9igZd7oHj8SCy7NiWgBJTAeiRQ2SxyPZ7RGvaJzwX00nr9z4cmEHNSFPrrVr0Cboh0dzXiyXrcfXgUb99Vj9dtkPq+xTvax+N9gdb6H1KcD2ToDuffKEVMKc4pGii4jUaRHM6m8EwyjIMvjuGJ7hn8xo1tFA9NC6zpUqt0ExOwuRkHnkozyQyKC4viPbn43TyzP3PGj2topZ5rEmsu4vyBp75G60If6ppYv9gnYmHhCYrlwEYBZWO8mdvLjNFeO8LTA3jouX8ySqJds/utRnz6/CZuto/SYv5nJ7twuGBGtmUDzH5a55bIRl+gpS9L699TTKrTfaKL8but+GjnzQjHJvH8iR+wDHQMtcyyb10h5k0sqjNTCUSms3Rtfx1u2v9zhnu+tktLYITZhJ9hDd4ArxMfX0uNkeV64aHF3U/rzKlQHjurC9jORayl2qHhEP72iW48cDaIKTBDv78DZlp1zLIQJgfndSBJH6cyKTzORaJnB/rwTO8UPnXLZty5nbGki3Z8DRM4FVhmLc9r0MLrtJJW4HgN8AbU7HbNE+hcNKI4nwx3G5Z6l2QxpoV8sUCQsWahSJZcDwVai6x8SW34yRD7xvMREVzMknf/4BC+ePQ4uphc0dzSCgcrKUgs/EU/BPslQj3FBbFHWWO96/BRjCeT+MjmDcaiQCjGRQoex0533pViRUXAzNatjzA+tx5VvrY1EzKV8NdtlcBCAsxuTjHeENhsZA+fivQhwjhm8agxUzRauIgmt4vZCi2zJT5loamhapMh4pdaFCuH8iAt4OMUuo1cbJZa6atprOwKH7dhRBC90HKM/84ZrvHlND9F+l3VLrRw+0e40BnmmJckdCLeHecs+ryVIMFkcuIKL8nr6rhA8LYqF7Zz8b6YJ17xftCvhhZ0+gNSoq/ufIvtz/B8YL/EbV6bElACSmC9ElCBvswvYwjEM1O06PFu3ijivLyHg8SkFuge3TM+icdZlm1/i49x5Bc/FGUx4Pd/eBo/OhVCvHYLUEeXaiZ3WywEjC47mDnZXYUk9/vCdD+GH+hBig/Cj1zTAs85tzGZPLRzgr+D8dkHoxHGxdP6v8oH+nk8fLjmZ4LYzDjvnXRvnWtjU7147LlvI5TsRW2jCy43Y3CLdvgCaPnc7RErmxuTY2E8ceDfODFvwM5NN55nLCvux+jK/tnjZ3CEixOm1g2wSCb6ZeJ7TSwVZWLtZxMtmeNjTvwD66y7LRvwS1f8nGGhf/LQv6O/O4iqWhf8AQqXRUJdLPxxxtUFJ+ktwRnMvi134PbrPoyaqtaigubCGenf1oLA8xPMs8BreKOnPHEufZBrS8T9MMV+Ny3xW5jZvZgR/chIGJ+7/yQeG2QMd4DXlofXjSyCFWkmXjsmlx8ZXx3DXHoxdt8JJOne+a7dzQu+fX19HSegVsxMT1ck0MV6no9GsYOLa23Muj43nNK0mE+EzoohifV9awyr+UrNWBij9U+sd1ILOBgZoNBwUtxXL9hUSrp95qVDGKPV3N7JhQpjEWyJgcx9ylizBqpgYdmnwf5+/CWFvZRFfHf7RsOCHo6NcAKc5LE9dAeWmN2F9zsRMuIBIJbzbD7NeNB2Q5xXEl+6Egv9XAksR8AQ2LImJw+fc03WmeX+MfdMEy8VPxO9+RgyEueiV4whJikmgBN3dhHpLuZ9EKusx1lrCPpiC2HL9WGlz0TkjlKg08HIsJwvMUJX2g2qeUIhvo7TW69cgS4HEZF9s8+BnUwcJzHpJ+MZjBDiPIS8H9DOQIg3+Jy4kt8TAb8u2tyPui46o51QAkpACSwkoAJ9mSsiyTjUh2ldy/FBC8fK8ZvL7IoBsj7kOFF9rGcGv3J920UCPcSsqH/xUDd+cGIGyaY9VBm1Kz58jYc//cnz9VswOG3FnzzQjc4aF+7cVsvJwuxDsIOT/Dvra+kqPwFzNffpKy9JTT4SRj4Uwoc6mo1a5dKSTEx1+PRDPPZhNNClXUT3apoI5Op6J8bZt+eO/YhrIEweF2g1dhFhcrsvnurGYXr0m9s46feIOC/twS7iwdzYwpIzWfxz/xBDAXbgtqvej02tV+DB576Jkz1PY2yYCa24kOHgSzhmOOkR9/scXf8aqjvwpls/jp2dN9CN3rmm1o/V8HktfVcmdIenGH9MzWmXIMcKmsSOO7kfiUcPMcmfZHWf30YYY/6lx7vw4ECCi2CdhjhfUoye21Bc1k1uPwpNW3GMyQ//+tEuNHmdTPx4Qeh6GHLx8xvb8fe85nIU2MaCUhktz8ztptA0bty4kfHdF8brxMwZXp8ZJldsKEmczz+0WNO9FPXinjsdGUQT3XPnBH6IiRf/n2efx4gIjE1bDPFdUhOhznrv9s5NCJ08iT8/eAT7ampYW30jFwACXAzoZ/bqoLEwIMc3UbjLLUtiebN8yUqDi3HxTf4dxvfLXQAtqa/6JSWwBAGGUUNyXwxF8ujjol6QhVjEDVvWb+uYx6KDXjjNTDrp58LfXMi0XKseWtLl9XI2KacWpuGgmgvti5PBraYfsngvceOjzOUSzTEWvQLRLHdXsYy/k5bxN/mdRtK6oLiy83259dbys3oaJMozb3An7KtFwo6MajCSeKayJl47soIgpRy1KQEloATWK4HVKar1ehaXqF/ykD4yyjJljmZ6l1cmGkQEFuwenJgIQ4T//CYr9t87PIbvH5tCsp5J6EoQ5/O3NzFpU6G2AxOMV/+je8/i6jY/k1vNPnykzvidTXX4Ka33B8dGjXjSkifg5w4iruM51j/fTV3+cy1NnLjMPmpDkXG8ePxe+AJWeHzlPewczOwVqHage/BZDI29BdX+ZsNl9xm6FN9D93ZLx2aYy1hUMFEsmRqbcZILCz8YGcM11QF0tO7Fx9/7RUwEB7iw8Cj6ho9hJjrKs8zD66thGbWt2N55Eza3XXGJrijd7VIEZIIcoWt6PbOyV9rk6pTdiDiP0CtivkDPcIL74OkJfPvIBEz1Is4XWpJXOraJJRXNDZ14bugU/vWlAWxhyETNuTq+Mun96NbN+DFdxYdGhmGmcJWs7qtpxljjOL3S4cQdLc10YZ1dDEukQoglpuCiyLYZk9UyGq3YIoSNfdFV3s+kVdK+euYMelmO0bF3/6rvDbK9ZJt3btuG0UMH8JUTp/DF6642LIge9lWsi1H2O8FkWeKmKgsxkvU9IFZGWiHl7yrMy/gtdZOKCYi1fISi/OBEHoeYsyLK+4WsDUoqF3neS6hT10weTw7QNdtjwdWNZuyutxiVJSqcDpTVdxk7Md6/xNJfunv40ofyyEnwnjXGhWzvGpUPFdd2SfxWavK3pXt34RPxE5Ds67KImmUITaUJJCXhnNj4JdGfNiWgBJTAeiWwutnjej2LS9QvKQcykWCyJtbRXpPGeM6JoFiP5juAAT10bf/RsUmMWlhT3b1yhvhifRH33ELtBrw4chzfpdj/xI3t5792bU0VPtbRhj+nRXqcWUvNzSwXVqKVrMASS7mhQTSEQ/j9vdvpfsx4eLY84+C7Bg+wJNUUmpsYq1qBrnJ57LA4kjjR+xS2bLiKIsSPvz3bx9SzXpjrGftfZhM33UJdPZ4cH8ERJr26lZ4E0uqr23H76z5c5l51s0tBQIS0LFQxp2DFTa5FieQQd3k6RSxo0/E0vvJkD8cZE6sxp0Q5zcQSfqaqZvzk9AjetnNmNh793PXfQpfv39+7G3984AgiHDc2GWslZgo2cihQ2DfEIvjA7l3YX3Nh8WAmNswxRo+PCieVErMuglhEuo+Jq6ZSGfywd4AmsHouVhRP1FgKIyO8pKkZz09O4sRMCLurZ70SHLSQy0ubElhPBNK8NxybyuOx/hwmWDHCR1Nvq5eeN1wPs563JtOzit9LZE3GQt/DrA7RzdwWr2+3ojMgFuyX94wkiSON+4bl/OIAudX3RWqmyymEF81Hiu0pzVKpoegEc+mEGbqSNTxi3PQKlNA0u5SWXYM2Z7YohlVCXyRURsR13srknWWGG4rpPCOhNxT8EoKgTQkoASWwXgmoQF/hl5Gk6WvWZj2rFuxORMnRkQieHaGl3ruJ/r0VZFpn+TdQ3P7D04P4NbrRz7m5W/kgfn87Xb6ZFfqrnIyPMAuzuZGJolwUGkYm9IubxMEW6KaLsRG00gr9W1vp9s04fNs504HEkHYPHjTcxCXuvJImieNkH4Njx2hxiyNuduJxllQzb+gwrHNlN563uPR3j4/hdCSGG2tpfXwlTB9ln8BraMNzKzwVrPOUBOulwRlay5j9vJkLWIviokvagXyJk0OzJ4D+0XE83x/EDczu7nPMjgHxLrmjpYVJ01L46ukuTHIya65r4PdpKV7iWpaEa+LWnqXlvImJ136ZVvi7OpgQ8RwTcclMJGeMJIrlT0xnz07EuVigMsxCnWEM+POTQYaC0Cq1cdaaXjKDIl+01tRiamICz1Kkzwr0Il/St5TAK0yA3tc4RKv5g72SB6GAFuapcPMxU2yRWcJlJF0Mqy3Sws5yn3SBv78ni7d0WrG5iveBMm5YSYZTTccyjGHPGYsBdfR28567fyyHRpb1ZXHfxP6Xe+uav3/puohhrj0s2cKxKZzqfY73uhOYDo9SoEeYo5b3NIb8uB1eCvRGbGjeie0brzXE+mqaTK3EFX6GXgExTrTowGC4nks1VDe5iBt/DV9yH5R7lpt5M6ajQ4ZIlzwa5TTJBi8CvYYVLWSRQZsSUAJKYL0S0DvUMr+MPBjqvVb0MQv6mrRCFrUu64LYMUk2dXoijuEU4z4DFxJClXM8eeAWvHU4PDaJfgbSdTIZ2lyTuPFPbt6IGiZy+tf+Ybx49iRyNUx852X2arrIz4kHQ5jTal5IRGFnsquruN1Hd2zCO1sa4Z8n5iV7++RMPxzO2TJq5fR3/jYi9KeCoxQNKRwIsnYsP7T5Kre8SYxslqWqztKFN0IhJOdfapN60mHmBpiIzk6mZALndVjQyKQ4c4n4St2Xfm95ApK+QPguiv5YfqMlPpVFL3FflSoGixP2P3ByAgVJvMikb5U0k50TRCaEenEwhKlY+rxAl31KsrQPbupgSSMr7u7uxdG+XmT8fpjpEXLxWEsZ8erm0AyuZULHD9D6/m7Gsc+5tsv+JIlavpBhybjyLdxz5yoCX2LPM7mEsd8THGsJgpcFhEqbiQkkY7Skn6W3SjlNOMpL7oly7/Uz07PUoS+WULOc/es2SkAIdNNt/XFazqkLeS83X3SPKEZJhKyPylFc4MdZxlGs6VUOGwuslKbQJbTmhd4ZPHh8HMeGwwjGsxyDeWMRXZ4lWxu9uG17HW7aWosAE6kt1cySmaa0Qy61i/Pvix4W43mxlB/iIXes+yk8c+SHGJnsYjx5lGVT6enG1QoLY/HT3DAWy2Fw8giO9z6NI2efYEnTt2LXphtKSvQ4yTHewwWKaQr0NG/YwnfutIx+ccoli+kBCvRN5NPA40rIjITmSDlGuYetVCFiMQDJeyGl1Ry0nHsZXqOhNYsJ6b+VgBJYTwRUoC/za8jq+S4mMeujdVtqcVaSkVW2RyqO7Q0OPiAuOHFF6IPbzZJeUg4J1gqs53PnIcnoCia8NBheINDlYxHp4uq+n+WTfjo+gSenZnAsOIVJLsfnz8WVmyhiG1iLZbfbiZvbGnEHreb7+P3FlufZesxhWJlEZy2a1CfP86ksrnR9MXlU88U43IqbxABzAWKCibCSUlsaS09+5o4lwvzFAWaXZ8b3E2MxjEbSdOVnLXku7/uYfayVpbj2Nntxy6Zq7GjwnPdUqLivr+EdSAImroUhxsxCs4EI5cMQy4y4tjcwVlQm1fPbIWZvN0niv0pjLjlmRKT3zkwiykzIi1sV3drf19mBnVUBPMza4s9yvJ0cHsSUzD6lprj8weuxnkJ0h9eNG7Zswm3NjdgjVQgWmfLyTAxnbLYWZjPux8iHwQU2eU2wPFqWotqy6JiLz6e0f5uYCNOGIMdalhYx6zIVF+b2l+IE/YWBIJ7uncbp8SjGaaZM0MIoIQoBjrU2Jp7a3xLArVvq0M6/a1MClRCQXBcvjeUQSbFMGRO/LV7AW27fMkRcVLM1fCwN0NX9IOPWb6W7+1ziuKW2HQwm8P/94CQeZ0WYYMpEDzEP89FwsU7KIHKcFNIJPNE3ge+9NIwrWYL1U7dtws1bJdfEwmereMKJC36GJu/SnmRL9Wj2fXGZ51QBnkXjNMv7zc8OfBdPHfpPPjOnUVXjZcWTKgpv9od9EA4ynZH/y7P/Kd7/BiYOYfzxPgTDY7h+7zsY1jIbCre4B7Jw2svEdGe4TZLbV1GE13K/cv+ZL9Dl/OJcBBinkJ/iq5MeBtvFYu9pxmSklzktZgyLeqkeRVJeUso55sVI4unkHKx4/xb3V/+tBJSAEnilCKhAX4a8COk3bK7GfX3jnPHT3Zvit+xG120w6/ktndVwz3uip8XFK5Fh0CzF+Vq4XInI58NuiHVJizV5EF5TE8CegA/vaY1jKJ7EOF3eg3xoyoO3ihPselrC2hi/LRngXUu45crjVFawjQf1GjQjDI4veeCmDCHNVsIEf8VDG/2T5DILS78std1wOMUM3314qCuIs9M5zJj5mzOxllGHXk42zKX9gSjqj/ZjT/0Y3rOnHh+4qhkN55LyLbVffX95AmLF2VFtwfOc9DJnEctzLRTWy2+98FN6rTJutIAGZooT4T+/TVAAmixrJPSYUyLI+NW0mOKKNAcnnlexVOIOivR3tLWy9FucgjiFcDZjTEZFxNfTu6OFeR020ro+l3zxol3JwGQr7Qq+aOuib3C50RjvWRHqZcdzXrzrAsdsTibuF3900TunKMi/8VwfHjk7iS4m6xLhYpS0o/uscbZB+tHQ6th4dAw7DwzgA1e24337W5ihv4Kwl4t6oW+8lghIpvaT03l6Z8yK3dWeu4wZiVeP8h717FAW1zRZKNCXvlc9dnoSH/vHFzHJghFg7hNzIyswyPV9bkwbx+d4kXE4EZ/BA10DOND3Iv7oHTvwgdctrPYict0tY5WDy8hjs8xxSzkvEcDyeKyfZzAQy/nTFOaPvnA3rC6WYGuiCC7yHDa6z/+TOYCbC/92ehOEpqN46Llv8d7tMKzp1kVlK+Wp3sWcF8fplSZl4jZwO1n4L0ZPltEdPL8Ajz1BgX6K22TY3z0scZdjorjJMOvQ5yeMZJTWFeZNYjmPp6aNChi1/g3wuevZ9bUxLJTCWb+jBJSAEiiHgAr0ZajZOcF+w5YatD89Qk02iQIFerGHyTK7MD4yNGJkEm3ONG7dXAP34gnmWqncuY7wgCv108lz2+nzGi+ZUMvDT5q4Bc/Fvs7trtifYoXzOutoEZgu9vGq38vxIeziCrmUNauZM2sw1q0Ui/eyB+PEx8QHtLgRrmQlfInuyr/HOvTPDMYRY01mNDAuVyYZxgTgHFF6F4ACa4JWj8dmRnHk4X4cp5X999/YeZHHwrL90g8vInBToxXPjmYRzJjQUOadSYaSZGMWS9cmH+NHi83Dygkcvai3fIMHk3ne7Mgp9oXZ99z04hCRLi8Za2JdlsmtWMRWuiZlDxZJ7Mb/pDxZpU2m5DlOwi0SR8+yZx4uMlj47zVpwoOLaw4u6tmKTOrnjiG/0c96pvCFh8/gaS52paRyQ0MNLXRMNCfeBTL75/8KsvDBe8AEY+VHx4Zw4v4THGth/JfbtjFz/sqeMGtyTrqTVw0BWbQT93Z51LnpWTNfI6/mJOVJ4OflJ1Uaz3J/11KkL27ihfXgiQl8/OsHMJl1wNa+y/DcKdrYERGMJoanFRh6MzrVh//63RN0tDHhA9e2LfC4kxriHgpqEdcSN1/s9lb0GIveFMu5lGzz8l5YfU6gy73hVN/zeOrwD2Bx0oW/lklalxnH83dp5T6qaz2YQQQPv/AvaKzZgE1trApxTgjLPXKYnjEnaTmXY8qiwEr3PuEsaxCNfHbbuG2vUf/dhK18NouL+3i4CzOxIS7Y+fiSvi58aMh9LpOJ0SMnbFS+aKzaDL+HuXdWnB2VQlC/owSUgBK4tATKvb9f2l6tk73LA3xbvRsf2s9szyGW4+IKd1ktEaLldQQ/v7sGu5vo2nZO68m+xEpfLWWaZPK9BhNwZCR6u4DWqiUmA0VOQB6UItjlVYo4l12Iu21Lw1Zk6fqdpbiupMmEKcVs+bWBjUZG2L3VEh/M6UIsVslujW0LNMfmGVMvHgHeZUpeHRqO4NPfPYlHB+nO3nY1s1qzRBZrzEt2fBMnKVJ2x3jJREpimFk7O1+3BZO+zfj6gWl87oGzGKH1XVv5BJoZz3ktlflUkvGNRsag1TfZbJLbd9B9dWvg4omzeDoUMmuVUyJHK7iZgrT026iMNRGwDl5TK01Q585eMhiLVUoSu1XaJNQmx1ASSbokwr+d1nsbeUjuiYob9+1Mp9DGfc67xV202xcHg/gsxfZjQ2lkGrfDUts6azk3FsNEoAtPjjOpPc8wArO7CrbWHRj3tONrzwxQ2J9mbgh6HWlTAqsgII5qgxFeo7zEHKUP2aJHcNMzR7x8Tk8VHzeHGCL1x/cwsRo4vtr2LS3OF+3dJGOdJVOTrgb84fdO4tmuhQvgYlFu4JwhyuejuIiX02SrMJN9JOlvvp15HubGajg6hYOnH6H7/yhLn7pp6V8dJDO/7w146FEUwtOMXY8x4/tci3Ax4Cyt4JI5Xuqil3rvk+1lTbyK1nYvt+2nSJ/iQkuAQntj/VWo9rRw4TKDaHISodgowolxlnWcMP4eS45zMTRFt/gmtNXt4zYsl7vsnakcmrqNElACSuDSEFjdHfjS9GFd77WKCVvEhfkNbbTuTHajwDjy1bRCJgHTVA9ubjLjF69uZvzTQsuPjw9ISeZmokWWanc1uy7+3VSED7S8UQv9UjZx09vR8TpkqIgS4u9XQcskc0jz1dF6BZysFb/X7+MKuxX54BpY51MJ+LhosTPgNWLwi7WxSAp/+pMuPEf36lzrlRQFsoiynMSY3YshIKpakK7djH86HMQ3nxu6qMZ9sePpe8UJCPG3b7CimlEaYwmWSFsuvXCRXUh8Yz+zLEvd8ze0FI8N3d/sM8ZwwfDOqKTRNZz5EjYxIHUug3sle1tpW6+z3sg+LO6dlbQCYzGlHrmdFicbMyFfycoGXk76s9NTlezW2DafiMNPq9Veo8Ra8TYUSuDLT3TjmTGG1DRuhsnN8JFS7IBcELRUNyNR04FvvTCEu18anHXzLX4YfVcJXEQgTYeMUDJveNWUcHu/aPv5b8jEiflCWa3h4q8F46yW8ngPzswUYKnfei5k4+LvLfkOPUksVW2YKbjxJ4xdD8vKwrkmzj9t9MDzc8xOU/RKgrXVNPl2kivism0dLdMbziVNlXwUwxNncXbgRfj8XFRYorrLSseyM1bc43PiVP9zGKcngFjlJdxljMI6xIV8iTkvp4a7PLklYZz0fYT7kvOWMmlN1duwof4KNFRtQZW3mTliauj2Xo1q/r0hsBnt9fv5ne0s0VZ5EsyVzl0/VwJKQAmsJQEV6CXQ3Nfiwx+8sQPXVLMc0cRJFGhJX2mCbyRhouXcOnYSV3gT+D1uf3WbTEYXNidXk3c2etBipzhnnPvqHrcL92UkogtP4KpmxrTWLB9nKxazLGNiM2HWNY1EkGOyKElYU2oTS3Jz/Wa01u9CeIbCYZViau44Ums+EmZdUnMA2zZeZ5SSEqH2kQ3NwEwQOWZfL7eJ9bwQDOJqtwPbvMUf0BLL928HR/FoTxS5uq2cdZWRPIY1sQv+FvzFYwM4ybja10KbYDmtSZbTWuv2f9h7Dzi5yvNq/OzOzE7dMjvbe1WvgEAg0YvANAM2zWBsHOdzi/25xImTX77EccrnL3HwP3HiRnEBG1zAgLFwoSNAQr237b3v7E6v//Pc1aLd2ekzEgjdNxmLnblzyzP3ve9TznOOmdDT25vzyNOQg34G6QJXl8A73pDPnbz/2kjcJPmvG+t1kGp8tHHNknJoSRQkcziTIUF+rseJc6oLUWxm5TfOCNExDbjc8HGe+cnYnupck10XWqoUSLqXREeJQfWxToatLAGet6JhPBNEr2KAvqSQ0PvBgcyq6Hx2yD7qyAZ/QVlp1BOQXv0Xj47gN4cpoVhcQ4RKqpweRPgUlMLO1prHd/djbz+RSeo4Yy3Q1dVFJvDMUVLJGkDWGgK+Mm3dfudwAr92RUH6bGsfxxvtdvgFdCtHGAAAIABJREFUTp2mHJggRzTWamztnsJze4fmXWIhfYYWBtey3I+QwybZSrrA2t2cg9LTbaTnt4wkjLNUHz6qp/QOHSH/yxT0wiIf/fGZlKlNZj3bCLw41PEWz1H668PooeGNDLBNKVbl5x5Qz+DezNcg+XLcArs7MSTRWGgqZ0DepATj8irlf0vFXNU6T+onUzdSLaBa4D1ogTQ7Pd+DV3IKT0nWqqsX2RRY1rdJIPZaz35MGcopaUa+aekrE3ZlScnLiin9nNTaxPQYLK4BbKg14X9f2opr+P1YWftlDNA31Jvxq84RhExW7jNNNndqluoC0/jkhfVRrSEBuJdBlaunB67eXjg7u+BjgC7QNL3NBnNjI0zV1TDX10NL0qpEI99swwUrbsTmN7oYpLtRSCRArqT4kxxiLg8lzJyMOdYtvgqVAis/YaR762vwZN8IGfT7kFvfQIhgij2n3HmI0lUWstRf3VSD1hgBetuoC388Mo4xHX9LQmmTP/uTFynfCTPgmOwZw7df78GP7liepAXO3M0cDDSfeOIJ3H777WhqasrahYgtBZ5+W4MOL/QHMEASNgODbwsDd1FVEKdYsTdfEpj7+T/TLIa7uE21ORfXkVW5ibrGsca6OitWlxux0z6qVG/TY3NnH6vLjnqSKK2vP6mBPveYkgDzUKbQ0ds38+rpZoBOOTXC2w2ca5b6Oliol24heZxOJM5iPRxO7FQg6VYSHI1PdUPrdzGRJYmk1O5WgciLzFARg31j3kyyUPrgP76oBdvf2ArX0ADyKqpSJ2cUJ5wVeOOUHbetXgUbie+ijUlWFh95uwdBQwG0+cXRNkn4nvxeufkl2DXSjjc7xrGsXPpPoyNjEu5M3eBdtcDg4CB+85vf4O6770ZpafSkTjZPUNYWaVOSQDUbQ55BkdNWVAne7pxA9zSPVcI5lmQPd7TzyaUvIGiuh17rxF0kjJsdcvpVrHBLjHqAsPEBBr8StOfHqU77OUen+ay08/wkyF3KIFw0xmdN4fE60ccKel4ekUdpVs9nz09L9JuO+2nv20eXiAkEaGCn71FCBFvsJ3M0C8x/T75r5LkPE54vPfgF4nYl/pq6hWoB1QKqBc5IC6gBepI/mwSeVy22sTJtUCquLx2nBNfYCIZ8eQgpQTqXDy5GucxEl+l8WFKsw6WExt/F12JKccUbdVYjblpeRlbYTnSx1z1sq0sKYj13nwKlx0QvNlQbcPPKsgWH801OYmzbNgz+4Y8Yf2MLAp3dCmu0uLYKcZQEOwZKwC1i9vnSS1Bx5RUoXku4d5y+bSF1kqp37/DV2Nf2e5rAgwIre0aTCNIlOHdSvmximP3htpU4Z+kmmI0nobH1ZJD/i5Y6/FNbN6aGB0kixf6xFByHEBMP2sE+XGHNVzTcpec3csg5HBpyYMcgbWdhHywJs9IdQgAUZsLimf19GLvBx1aG+FXVdI/zXvqeh6iLRx99FB/4wAdw3nnnZe3U5PZpKcxV9MR3jwZxjMzLY5RH8ivwVCExnNHvlcqMPMBsLAedV6LB+WUa9oTHd9lEW/vP19fjq5uPw0HiRk0RiQBTchuZ+GFGSe8YwQfITbGqamEriSS9hrZuQ9/Lr2KEc87fN8CqPeGudCdn5hrnG4NYU2szKi7egOpLL4Vt5QoleI83rOZq+BhgeygxJENLiGdyMkNSOXfD5ZkgEWPhTC/mCfIm2c/llRWKbvtDHV3wU5JQa6NGcJT5Ev3cGJwTpeLr6MBNNVX4IDXcY42jo5xr/S7klDbS5OkvPTlGC/z6fLxKormbVlaq8muxDH4GvD/Be+fBBx9UEn3Nzc2n9IwZwyrkkYFEkJwkz4KxLkqEjnzOGHV4cWzYCR9bSDQRLOZJ7vbkZpyjueZi7O3rxhBVWcoLT/LKyDOwhnByqUi3kXitn2ixKWYLDHxJpXl2dkmHvFSblSo7/7+SlfdGBs9F/N7cZTrAtpcpPtO0DKIliZHR4Nd1PM6YvU8pWkyJlByffXJemQ7l+c+Xg0iAsJxrCrsU3fl+ov06x1xsGwgoyd7SfKLrqEFfqJJOZvrTqN9XLaBaIMsWSN9LyvKJnCm7ay0142tXNuHmFQ5CLKfROe6mdq8fkjnXM5gtZWDZQHj5qup8LOeDX5PEoiTbbFpigxCVfX9HP6YmqI9azIAxSaOIjipGO7HY5CXDcRNKIoJDqZh3/vxx9D/5JPIGBhTtZRM1xpUAXTmIwNBYzeZi6jhwAP1792L4lVfRcNedqL3tVmilwhdjFJB5duOa20gU58XBjpepiepEERMOemPsYMPPZsBpOhzOySAqilfg8vPvRXnJfOdMAurbairQTRj+jwYGWSUNUqKGbM9MIsQdArUdG0MOg/N1vLjPNtejmaRV0YaXC3YbNeiHfAzMlYpkhoOVvYmJbmzrtuO6pae+IpTh2Wbl66KD+9vf/hZjtPnVV1+dNOtvooPLbSk65ldUa7GCpG/9LgbpQh7HSrncq+JsW0STmP3m1WayvjNIn7mX4+9ZlBmuWcxkWNcEfrZ/AAEGirkFory+MIETbU8h3t85TISdXy7cFDUoscy/H93UOz/0k5+i7/k/IJf3bRF5CmSuyf08W68SSSUvkTaOw8fQefgIhli9brn9NjR+8Oa4QbpA020FjRi1dyg6wDqSSup53wqjcawhPeteMhn7/A6eRxGK+X0dA/u5Q5BBf7F8Kew+P37FZ4Xf74euhFJElIGLN6TNJ0BETqCvD9eUl+BLy5dRdz72ubzBirefaCMdmaozGaIfnUOd5b3Ul59gf66qj56JNd/973op8/nYY4/huuuuw7p1607ZCUnPeAlbX7rtMwnpZJ4XsU5GVE98DPRrpYw7Z4zTFxiye3l/svqtyAVmNnKYiPJOcJ0i0mtugC57lSdWCR+EFs7/egbEvezNHuZrkhXmWd9hRuc8hxV3DWqUwDxHIWqL9C0EXeenWkIyyfVkrkjY371E+vBRzWddWEkGZG4NtiecuG7xVSTsP4kBiH1WTiYwnt49gKfoWx1jC5qL9pEkjQT3ebRfIdEEF1Fd567za3BOfVFSPlvso6mfqBZQLaBaIDsWyMYzMztncgbtRQLqlSSbkpdAbB1cAORfgeCa6QVIEJDqkKD6MxtqSWLjx0/2dLJKxsVNKulx4O6y+DHKBUjG0mJ04auX1lK3nXJFc5ICbjrPR7/z3xh59lmUsN/Pxqy+wtYuGfV3BrPbXKwkDJfMejED16FDB3HkgW+zR92Opvvvh9YUO4C1Ud/1ivPvgzW/Cm/tfwoD06zUWbQwMiutpVOgoV3CXKT9dB7cLmqSUos65NdiTeu1WL/qJqWXPVolsIR67J9taWCVQIsf9Q5ikJXJUCl1ZK3FZH2eHzwo/eZO9tKzNzpMWPuNxQX48qImnGNd2Pc/e9mycPcxox7SsDJBNEDGgwR3ArrbP+g4awL0WZu9+eabGCek+7bbbiNMMn5gl4qdJRCvolNdRU0hKXx5+T8C7ZRbXHRy03GyS8nk/tmNjWQr9uPZY928L73ItbJfNE5VV3opQ5RaxEQfVhfl4C8vX8rq+fx7y08I+47/9y0Mv/gSSng/FhuYqKKjGukM59HNNLFaXsCnbxGh8MP79mMP56lnwo5l998Xt3qtI0dDSWGjwlLscA9Rj9mlkL3pCIHPYY+6wHjlXMPss/ez1UYSZyEmBATWXqD0ZEafxwJL//LK5bAa8vBYZw/RBdOspLOtp5BtHxFBd5gBfNDBuTY2Ci3n5N1Vlfj0ssVopGRjvHFkxKGgVHLyEiTZ4u3kxGfyXBywByFzWB1nvgUk0ffcc88pib5rrrkma4m+uZYRabWGQmFeJwElbxv5O93hJG+brPnLbPPXeg8TyW6uc0rb24KZn8bRuC7JUj3hjE0ga+DDsJzqB6WsKIeNTBzIc1IekgxgDXz+yGWKOotcbawrlueGhsfyKd/LfMgzSJQn5HgiOadE6tkcEl3HvJqTBzrAosdnHt2Nff0O+HKZmDSXI9dIuVxpw5HKPpMSPQ6iId8awK939uO+C2vxuSuaUVaQ+TMqm5er7ku1gGqBs88CaoCe4W8uQbk1S/Aoqbx//doW1BX14l+or+1yjbPPnZVYEiOBGuGz/dlhkWNzkiBpehgazzjOLdORxK6JlcESRe97dvjpZHc+9jMMP/UUKik1VkrHWPnB5wXn8w0gMNx8kYFioK5jwNXxox8hr5jQ/jvviBk4yNJfXFiJDefchtaG87DnyJ+wv/1V6rkOzsDluJYqCzUXf6niLandQEj7taguW6TA2mMxpst3qiiP9rnWegbaBfhhRw9e7u6At6+HlXQG1ZK8kIWa7PdhVmHClHhaRFj0Z5Y24QMVZajmd2M5JHLVAlF0CLWvBGZzIL/zLZL8XxJ8hOkQjYn3dhaOI0eO4OGHH8Zdd92FQhKPZXtIMG6aZTXKYOfirC4qteD/XLOEFfAOPLarD1MCdy8oI6SU96NeKsw8mAS6hH5Kv3lochhhzzSubSnC321aghUV+fMSYeKQbv/mv6H/+edRS0e3mFXzRMkD+TyfTrUh14TeiUkc+MEPYSorQeNNN8a8Oplr0n9ezH50IXoTSSGXZ0ypkM93WNluQxk1M1mN801l0OflszIU/3FfTaTJ55YuxRomwB5pa8eOzk642VYicy2H0HeZa2E+R0JeVtpYbV9JXoePr16pQOTLONcSjUlho85a4KJlMMHHIPtvJQBIVh4y0Tmqn7+7FnjrrbfeSfTpY3AZpHuGwt5eT36KIib8pnkrkiMtSdzM/CNK9XWSaJ56tuFUEL0zdwgaZQY1NxMgJxNExr0eJtdk6PmciDfkLGaeN4S3y3MyCeTevPOmvJvFVIzpyT4lwRdrTY53DnM/CzBJYc2vVp4ZkkAQa0QXpEt2jzPbhXhtYhEJn+Ov7WE8w6r5J6hD7yViSFu6hEhA4b2Y/60c+lW5ZurPB+oxxuTrv7/QjaODTvzLbcvQWGJW3At1qBZQLaBa4N2wQHyP7d04o7P8mBXsifryZY24cVkp/vXFDjxzsAuu8U4liAwLZE6C64AEgCFUWTT41KU1+Oi6KlSzP21u5Vy2s+/bhw7291WwV7hMAoYUbEv1b1TSOfeNjKL7l79C4XJW10gAFW+IRFptxVJU2JpYUf8oJqeHMDzeTTSAk7rLOuqcV6OU1fY8wlPzJLueRFAs62MRK3ibKkqxsaQYh1ilfK5vCNsnp9DLJIU4SyWs+q1kr/nV5Y24qMTKPmSdAt9PNGTxlQrtTHo/8xR/mMgDsbto25+tQ4iffvjDHypBejUJB9+rQ5zoJpsZ37huKQkcS0n+2IZX2o8jwABSuS+VucbfU+TYCEdfTjKyL16/DDcsp5QPez8jHbfu3/8Rbb9+EnVEqJQQQZCKX6fjvVpvNMEzNY293/0BStauQX5t7F5usakE2yInJD3l4XATA3QqMgTdTIIFGJgTxcNKuU5DRQT+9ww6JfEZyRbFRKZ8oK4GF1eUYx/7g1/sH8RuVjUHiE6RR48E4isry3Elq+ZriosVngA5/2RGnkQQImqcjcHql7j9ss+FgN1sHEDdx7tlgaNHjyqJPiGPy3air5IB9SqbBq/3BRg4MvdN6FjkXI533VJgniAHrPy7sYbtKxFVeJFNVVQdJmUjSf6msuouPLJwy8i0qUmgyrLwm6m9Y+CaLOt29/AeBekmZHHpjgAz316ik1bUL1eepYU0gQT9UtU3JspaJjiotBUIG78lood+7tek1/xp8gR94Wf74DMWQ1dGqbsEfADyuba0gdwgFjxzuAt46iAeuH0lKosSJx4TnLL6sWoB1QKqBdKyQPpP4bQOp34pGQsYmOpfVV2An92zGqLR/dLxcewmVEv+W8eFqY6LxoWNRbi40RozGAwFAjj2ve/DQJmyCjr/6bgJeVxcKxioHNuxnT3pr6BwyWLkJqhqzFT42N9O0jSpjleXLU7mkhNuI5WJAiYMLiguUl7ZGCb25ZUR7ky8Lj2ILOT3haiPTlkT2ezfK0P6O9va2gh1zi4UWGTWYg1heP8RkRe33HILli1bFmuzd/19cczlHthE6TV5dY678MLRYRxin+Kky0epNy1aWEW5pLkEKyrJPB6jKhWkjff9z/dg5m9fKdXmNK5MKsBNZgv2E+p+7PFf4JyvfEmpPsUfQpjHmc2XBOpGZAe1IMzuVgbqlzBIl1e2Rl2RiZUqpyJRmWl/bjjoZ3Igly1FC5Ml2Trf9/p+ROawv7//vX6aMc8v3rkPDQ0pib4777wTNTUnGcxj7izJD/QsL68p12DQFUb7JFEmnD7sxko81bh/abGxCw8GSTDOq9SiuWg+0ZqcQimh0XUSTHdSMpXJMkmQZTJClIOs5D4bbdFbUzLZ99zv5uUZUV+5HDsP/w4+ttmJDnrCx0+Mg3tcbBkKa7G0cT33IRV0SbLnwsUgXdgnkkvnLdy59NNL77kQ4wkTfayn467uSXzz+WOwawuhLV+cwm9A9IOgFTmePdiO5pfa8fWbl8Z87i88Q/Ud1QKqBVQLZM8CaoCePVtmfU+yQFZwcRYmeHmlMlyUdxp96WXUc6FNQGwdd7fSr25lbDf21puouu5a5Le2xt1+9kMfgxUn+/Hk3yAXVSVw56JqIlTPmICtOqkDZGEjaQdoLjExsBoh+ZiHkPkMA2sPibvoj13UkJ0EQhYuEW+//Tb2kvQv28NHqHO8IURjv/jFL3Drrbdi1ar4yIt4+zmdnzUUm/CJ9Q0pH3Lg9S1w9fehyUhIZMrfPvkFQX0Uszo0tGMnnEQimCuTm/Ne9rG7lLkmcO+Z/nwdAwMz51oe51om55TB5Sz46vn1VuRuo0qFh73obCVIf7D1gDr0S2x6FApO+Swc0rP99NNPs1LJSu0ZOtxuJjTjjNlE38c+9rGsBunlrKJfVqtRWpw6SFTqNbCti5V0fZzIkaTfsFNJwss87nIqRlxUrYElysIq9+MKJtete0ZZRKdiAaHj6Ua6Qv4adk3gg5dUkwwyzsnRhiLrKO0nCuJHVluizhSSxySjbEHZVJU2MUhfjY6ht2EgcZo2BdWU2Z8xQO6N6Sm3sh9pYZN1XyD3NdzXYbcPLp6PVL/TGVKBdzJLUsuknMitRRsi5fiTN3rQRmoeDSvi6SRINAUlJBhw4Yevd+PG1RVY35SeJGS081PfUy2gWkC1QLIWUAP0ZC11hm038Ic/QMPF2kroWiaDyzzMdPL7Dx2Cm0FDogB9goFZm8OF/fZp7JwgDJ3wegeDBwnOK1l9X1WUjzWFBWjJN6OCjOzRl9nEZyxyVUKANU0HxuN18L8lYKQzQKiaicy3ZmrI6hLB2njwRWTlX07I4zb2GYcN1MVOEq4beYai94qpEZxXbWHVNTObR+47k79dZMGXYSLJnyUJbftkjyXO8ySl++INqZ4vZU/z+30Mbn0bOV4fCpXe9fSHzIVi9nr3DI9i/MDBuAG6AMXHPV60k6xt3/gk9rOHvY9oGVLC0XnVkFTPiBXWIiwrKkJrQT4r4unPNbkigc4HQuw/ZxJgpiVEfH+NArXXsNc9mZ7VdbVWVFGrvt85gVwTa2lJtLhEs6YE57kM8i9abj0r5Ayj2SDIgGw2OC9mq4FoT59pQwjhpsmTEm9ccMEFp6RVpo7949c15WDbALBziKoi3hARM6z2MsEqsbDEf1IxJ+E3JDh3kXlNqGY2UFXiHFbgiyPk1WavQeLhDS02rCzrw6tUGYApnx+l8dtIYts+wJaTMO7fWB/dREx8B0niGhwdIwhsikkrCdCFoI5hMe+HHKJ5NJz/GioyKJwtCUZRfhnWLLocg6NtmJq0w2oj700K62GI0PIpu4v8NYW4YMX1RNDNqDVIOF7Btq9eBuaTNGoe21zEH0hlSJJ/khkVxY9gFlwXI/Gwu8eObR2T8FvK2aWU+JqjnwORSeTUcUyP4D9faFcD9OhGUt9VLaBa4BRbII2V4xSf0ftp91xUQiRTCjJIzeHipBH462lypCZ27YYE13qpVkvzaAZDL440nQAvIZWSqc+JUgEXTerd7At/pn8Izw6N4Kj4CWSxpiAqSbdylR40akPhZ5ODKA1047qyYtxaVaH0jEulL5UhPe1d/fvRPXgQ/SPHYZ8eJCsv5a/4f3nUn7UVVKKK2fs6QvYkiy+98bGGaNRf1lyE/TtItuVlpjwNCSjFulPDMASm8dkNzUkFK7HO51S930rkw4YNG7K2+46ODnSSRCzWuPjii3HFFVecVlsEWJELMUEk96dW5lqU+zTW+ab9Pu9rO21hYnUnmSA10XGE9R1MfjiIgIk1PJyDe8cn8GxXD/4wNIw+3oBh6XuXqplwVdC5D08y8BkaRS33dxX5G66vrcEFpSUpk6mJ9JLHNw2P367ItYUILRdWeAkCBF6vJwFTHgnojHkFnGcSjMR2vG3szb19VQX+v7eHEXLbZoL0WBcZ631BCTDArzP4cSlbDwrZ83u2D2E9lyD9TBtbt27FAGU/ow2R6brxxhuxdu3aaB9n/J7cpVWWHFxVr8Wi4jD2jwTRNhHEIIFUMuRz5bnOeV1MCcd1hLQvK8lFTX4uEt1yzUz63npuNQ5sPo4xrncaa+oQ/SAVI8KOYXzmmgYsrliojhByu+Dr7KJqyZBC2igtI0rFXCD1nJ9hN1N1kxMIDPYjx2SBrobcL8IJEueZKMm2RfXrMDLRgy17n8LkuANFxWQ8TyKYluDcPuGE363BxtXXo7lm7TxSSqmaN7PyvZ9EkePclk+ipKHjQgo3we94+Fu0EqFQrPBOLBxCFinw9s5pPotJKksyjoUbJfmO9KTnUkL2lSP96J/woMqabrCf5AHVzVQLqBZQLRBhAdW7OQW3hIf9c+M7d2Lq6DF42asbZOAgAbqOlSwTF8rCFStgXbOavG+nDp4p58AWzQg5tfQuVvq/c+n0++2sMkcJ0N187w8MBv6njRrgZFUO2MqgtRQQxkrIr5BtnVjgRQoNXjfGSPT26NgI3hw9jE821+LO2krYkpTm6hk8jO0HNuN4z1YysA9Bb8plgMBKnlwshzc4hq6xDhzrex0Fh2uwrEkY4zehtLheCeAjR5FRi1tWluM1Zt23UsM8pCMsL0HlPXIfcJNRf7wHNy4uOOvk1SJtoaEDKI71mjVrIj/K+t8SiDr7BzBGmTJ7exvcJDSUhJg4oXqiNIRozUbpsMLmZmgScCeke3JBJgREijBbM1nu0Fy/D34G6dGGm2iU53p78fDxNuznXAtbbdDyWnONJISTuXZiSJ93iM+dPhLPPTIwjG20zcdaW/ChxvqkCBQFEeLyTmDKOcQAnfc3546WcN1cai6Tdo7Bi0i5UVLKx2QClSREW91iKKGUW4WyXbQh/f63rqrEy+3j2DUxoMyznLxUHF8mPD1T5NUYwU1rS7G2tijlhEO081Lfe29ZwMh7+Y477kBDQ8MpPzGBqS+15aCuIIdVcg2mWIQWKLtUzgXybiXju4VEcGZOcAOx2gtXkIWnqGUA+eHzqnBgYAqPvNkDdqIzSK/ihsl8m1VxByviJFe9dUWxUj2P/FaQ5I3eI4cRnBhnEEk1iXKRiGRgzoB0trAsCXENg9owCWWDVGPxHjqAEJ9T+laub3GehUaSpF246maSrwbxxt5fY8A9juKSfAXyHuv8PR4fJkYd9BH0WL/yZkU61WiYn1SQ1bmaMHcP7XqUBHKDJKIr4/MgUSVdKudDrJy7GJw3MsBvpIytcGREG1OEOnRQL96VY1Qk4zIduWR9d9q7sbt3kgF6Raa7U7+vWkC1gGqBlCygBugpmSv+xhLA9v1uMwY2b8b0sWPIGR2B3u1RFhTJxvu5gPoIM9Yyk120YiUa7rkbxeecE3+naX/KxTltOpZYB+XCGFGM9zNI+uPgKP75UBuOkIwODAC0dBqiZa9zpKdNR4eCn4cow9VGyPx/tFOHmovvxxtqUBin500cjsMdb+Cltx/DwPhBFJXoUVFGW9KL0kb0tAXpmPg81EhmZX3rwaco99aBy9fdizoyzEdjjl9bnY/PUYO+f3M7uoaPIZwE66tYSDEFofEYbceF5NL64iX1kID/bB2n07H20Ons+t3z6CXPgoOSYNRmgo7Bq5AE83aCn/8GCwqgr6pC2XnnoPX2D6OwqVGp/GZ/iOMeMTEyPEi0vYmz+jxJ5P79wGH0ECGgq6+Fhq0LUecag3UN55mGz5sQA/iDnGv/tu8AE1hB3NfaHDewDTHwdriGMT7do1TjBJWipc567gmd9dlLkyBdeqHDYT+r6y5u360gWWwFTAJE0VsX0y8lG/5nLqzHN144jp7xXsJvaxmoi2hS4hFyTvKZ2omNtQbccx6TL8KWrY73lQVsNpvC3i7/nq4hTwQJwuXF4vc8wJncs+k8MQoY0H79xiWYZtD46NY2JpYc0JY1MokW+55VkmqEtQdZwb5+WTG+/sGlKC+Yn8AK2ifhPXiAQfw0tBUVSmIu2jNNOWcmKnOosiDw9iAh6/7uLuXi9IuXzFTbYxjYbCzEVRfcg8qSJjz9yn+hv3sMel6P2WKAXs/98SErkqk+TwBOBxE2RMZZ88tx7cZPYGXrpTFby6QXvYVBtgTl+0kk1+FjCx7X7iK+IgN1vyCTuI6PMTiXa1nG48t3YwXncilTrM6POZhh4bMqG+ipHCLvZC3pZNCvDtUCqgVUC5xuC5y90USWLe0k3Pfo/3wXg79/HuYJOxqliseFSIG1nziWLDUBBux26kUPHD7CKvsONH3sPjR85CPIJTw1m8PIxXtScZ4zh95KYBAkzF3HoFoJsueMA1MOPHCsE0cEzl5bT2eA/yYBictlYJHDCucIt/1eZy/qKN90U3V5zAX4aPfb+MObD2PS3YGq+nw6DCKHFd110nDBN7LXVc9g2WD0UzpmOzZvceOWK76EclbSI4fIot1vQ1usAAAgAElEQVS8okyRb/nKM0cx3E2m6bImwGyLeQyl59xOnXdWOtZXaPD1TU04t5aVzBjnFHnM99vfp82x5r043d2D3d/+Twy/8RbMTieqiUTRM8jT0MGeDZSlU9pPNmI7USxdrDYPvvEm1nzpf6Pm8suyanoN560uPx8EmWZlvxKYB9kWkheFL+AInex/2bsf/UyE5clci1MJO3kyRL+QHT6vrh6jPd14kPaoIbLl6uroBHRyXzvdYxib6uK9T0JHSrlJ1Txa7VDe0ygs1aypsw9dR8fY4R5VfoOSwmYlqI8cRlbNblxRAQeraP/+aif6+lwM0usU/flYQwlcJgnV5XzbUGPC/9m0GEvKCL2N9QX1/TPSAg0NDUrlXBJ979aQeypbj/B8BpXfv3eNQhr3zc1H4egeR9BSxnud6wq5YWb7u8N+r1I1zyEyJD/Xizs3VuMrm1pRFSHxJYgYH5FCQUoeasvLZ4LzZAzFwoCGfBScrPD39hDyboK+sZHrdOzWMpFFXb3oUjKxX4Ct+5/DjoO/p2RqD6bIcqHkImkoaXEpKqjGVeddi3UrrlO4XxINSaA2EvFmyzXgoDeAPlbSx8hvoeE+lSBdkquKvyF7ylGq7CsJa7cmIV0qiX6RWJvhtsj86SBBvsDrXT75X3WoFlAtoFrg9FpADdCzYG8Jzg988/9hdPPzqOP+bJQoEpc26uBDX5jMSxk8d7a34/B/PIAAyZ1a/vyTWQ3Si1avxvDTzyiyJMYMPQ6vBPmlNhjYwzqXNGZSmLp7B7CdeMDc2mr2lKZGjqb0zFZUoc/jxo+7erGSBHKtloX94qOTfXh9568x4WxHea3A7WI7FnNtnssF31wgTLZAX/9evLbj57jhks/BQBhf5BBG9zvXVpI0zoRP/eogdveQ+dyQj3ABS+MSPEiwQTuwyQ5gDyymhmAIe3DTMhv+9qpGLGOfYCwZrshjvd/+bqSzd/vtt58Wx9pNLoQtX/0anIS1V/P+sRpMSlLkZAV7Zt5JukvkfczUAi9m33LH8Xa89sWvYP0//SMab/hA9n4CHruwoQETb23Nyj6FiR2F+bDULNSQ//vde9BHJ1SfdHB+8pRkrulq69BNaOxPmbBYY7OiNApxlC/gxqi9Q0GaGPUkmGJfajJDWKB1Oioi0PwOBvhasXsBA2+RgYsYoiN/3/n1qLea8PfPH8a+XlYEOSdzKXGUQ/K4HGn9keQilRVCjglCc0eQQ0LI+8+vxd9cvRjl+VLNj/F8jTyY+vcZYQHpNb/hhhtY9F14v5wRFxDjJGUN+sJVzbh6eRl++HIHXj8+hgn2l3so1RYIi0xbSIHSFzKZvGJZAe67cDkuWVSykLWd8yEwMowAW9c0xeRv0KfSGsKT43yRRJ0wvQd6eqC1WpX9JBoil3rx2tuwYc0tmGYSYWyqHz7OSx0TorbCKj6qOGdj+Tpxdl7AgHs9W1ycfJ4NMEgXAjgPo/Mw/zYwoVDIZEI5g3P5N9mRx231/I7Sgy8+S7JfjLGdIgfJz/KFOVAdqgVUC6gWOM0WSM77Os0ndSYdzkcm6/ZHHsHoM08zM2yAjRXm3Gj41DkXJZ+LxngTF9ke+f5DD0Iq3rW33pK19H3Vpk04/E//RHKVIFmdk1/kIm0voi1O2QfZuA08x7mj1+XBY72DQFklWU/T02DOJZN7uKQML3e1YSdJ5hrNpnlV9CADlv3HX0HnwHaUsXqWbHA+e57ix1sYpHsJx9tx+DmsXnwlWuvWRV6m8reO6f0L6ouw/YsX4rEd/fjelh7sGTpGx0jpuFW2EWdEfICN1KH/3MZmbFpaStbfTF2BqKdzRrx5Dls0rr/++tPiWAv/wZa/+hqmSIDYTGez8B3CxdgTTn4aE53+pdz+CKvtW//hH2EqK0X5+dHvgXSMXr7+ArT95jeQhFVRBkgYuYox9tAbeX7Fy5bOO5XXyQj9KskX9S2tSTEyR7sOCdJziVrZ29GOF/sHcUdTw7zNpHpud/TTuQ0wOLclHZzP7kTmhgTmep2fQfoITIYiVtWs0U6FiIdczp1ybGi24dHtPfj+FpIOkvBRIKWzv6by23G7q5aU4StXtGJNdXrPmKgnoL75nrCAoKCuuuoqXHTRRTHRSu+JE83wJJZV5uNbd67EoN2L/X1T6B5zEUUSUAJKkVJdzip7C/H1EtBHGyHK6QVY/RZIe64ksWNsF+27s+/lsDAgPetKoD88woQYEXFJktZKAk6CcXllc4ieuUDXsRBsk/JhCkmzXyJtL2yzIVkOv5+ZexumOoyYWUj/1KFaQLWAaoHTbYHMnmCn+2zfY8cLBwIYfeMN9D72GKt5zCgnEZzPvQQxfhXJ0bwkcOqmZnTh8mUoWLIkK1dprKlByRVXYfSFF2DjwqwwsacxJDif4CJev/5CEtydZKMVONkrw+MYYV9qXoYMwhLcB8g0K0RzV5XZ5hHGjZC47WjXVqrVCGw9/du10GrE9KQXr+54HC1158XN+mu4Kn90XTXuPrcKvZNu9u86MeL0KVU7caZW09kqJbNviL8/I3+EpNdPZG0ySISk8dO8q18Rx1rYoy+88MLT41izInLoxz/F8Gtb0ESkxsngPDkzyG+3iEH6QcJDd//nd3DJt/8DxpLEFaRk9l550XpY6urQe/Aw8ln9FRhnOkP6wydYBWpZdx7M7J2fO37Wzqo29621UaM3g6Ghgz/KxOB2KjLcUFdDBYWTcyoQFNnCYQYNTJJFgacnc1ilks7+c79nDG7vJJndpe0jdgXKkqfFpy5qVF7HSTR1eMiBcfaS5tGI1YVGrKwsQAFbF4SdP+Ai2aYEGWfZXEvG7mfiNjomjAR5czZIMcrvI88gga1HQteT+e1CJI0MTE1BV0IUWwYoA0mIS096YHQYujrhf0i8pkrCbIISbr1ONyaZQPQRRp7Hta6I/ejVlHO0GWL31SdzbdnaRpA5zVRlsYRH4aLsarLcFrGOH3KOkSRQh1W1amIwlo3U91ULqBY4dRZI/HQ+dcc+4/csTMsdP/4JLFy8BC6aqHIe7YIlcK6g493+9naMbHkD5sbGrDBOixPb/Gf3Y/funRiyTzERoE85nyzQ9iFWsI1rz0H5pZcq/fSzw89q2xZKPeWa2GNvyizDrEDduY/tU2NwkujLdmK9l6r1KAlzBsePoaCEgU8KcLdIW2vp5BcU5eF47w4FqldACZVEQyDrDcUm5SVDGMLdA/1w7z+G3sEBeChxJYGDjhUNIwMqQRiYSACopxP1fh/19fVoaGg4bZfpoq0PPPgwrLxXbOzRTmdI4FxHjoTOY8fRxXaUJSRpzEbDqZYJgxWf/ASr+3+DISZsKtgbnioEW8gWu/hd86IWNH/wpnmXJ7Jqb1EbXctEWMZJIJFjInleN9tqevlaTAK52eEkGztp36ipnVqrSuRvkUtYvFZjIAu8Hfkmb1TCuMjvyN8tJRblJUMk8+Q3d+2lVBWZ+t2KxCP1k0UJg/PMXFHGJEa18nfGNol2Mup7p9wCAmuPxSNyyg9+Jh1AerLJ2C73uWibZzSYJMhhgk72F2ZVHgnW7s5pJ/7YO4w9E5PoYYA+Qe4IPyN2LqcoIgFdjdmI1cWFuKK6DK0FC1vHkj9XQv6DPoVs0h8k2F2pgEvbPFtzqBCh1xFdECfRJ9vy0nAuEXCN1l7sc02yDYB+SZqFibBP2mvGsOncMpSxpUYdqgVUC6gWON0WUAP0DCw+fZwa3FvfQj0DbAoGpb0n0QHP52I58tqrqLzmapgIQ814cLWy0gGqvece9D78MHQeL0qkDzXJ8/QxAB+gLJqzvBSL77oDBRGQW4GitnHBhoXZ5SxUjnNY2esZ8sPFYGR2BCgRM27vRyDkIntsYgKaRDYzmPUkgnOivW8P1hDqnuxQ5Lw6Olm9fQ3DL7+sQKxB+TxxUsTBFP3VIO+BXAastgsvQPnll6PkogtJHnYy+En2WGfKdqfbse7+w5/gp7xQFXvOMzm2hQGqyeHEIDWYG2+4HnohT8rCqL36KrRs34nOx38BLfs8RTZQ5AmTGV7eXwMeD5z5Zqz7+McUWbi5Y5DBqpNojdwoxHHJ7H/uNlJ9kwra2NQkxsVBnzPclFUTYjghiMpkSBVd9uHxOxCkbnoqmUFBpUxxrvW/9joGmLCc3n8AYSYYxZZiTYWwkhwfRs61sgvOR9XGDWxXOG9e8jCTc1e/e/oskMk8Pn1nOedIXPRCDNzCTMqKpKHMo2ysfQmvRe756Wmlcp5MxTvR/oTZXfhUhHROU8SFPMpzSp5JT3b04Ym2HhyadmFaT+kyIpByjPR0uL30eIuE2/YJB14YGMPve4co4ViNm+urKEmXmlspvBd21yARN3YG6dRvFwJWDh5CesrI7aJlW5kR+cYSWIzSehP7+STV7o2txTi2dRh+s5XJiHSSBrQ3eW8KdEF8/sr5z+JEtlU/Vy2gWkC1QLYskNqTNFtHfZ/sZ+TV1+iMB0jwEnvBSOZSJWi2MMgd3LMHXspFZSVA54F1dOjryRDvJfvz4FNPwUeIaBkXT2OcrHKIi6+DVewBOiGOEiur8J9E5bXXLiCwExG3SSFRyQBuN882ZJSVir1bWFhPDD+Joewk1NHqyEKbBItrIlvnkTVMnIvh8c5Em77zeYjB1uibb6Ljp4/C/vpryKcNq+mcGeicKQE6/09hDJcgvrML9rbjGPrTn1D9wZvR+JF7FESEOjK3wMAbW2DibzcXkp3OXqWnsIjokvG+fkyR3LHUmh29dkGsrPrspxVERS/JGX0kPiwhakUvFet3uqrnn7EkuRycQ8OsnDuLCrH6s59C/XWbFlyWnQgdSQLlMOjPyuD8F/JIgdTPHR5Wr7SK85tcYiHeuUigHyb6ZrYSFm/b2c+CnGv9r76OYz9/nEmwPTAzgVBBu+qNZoWXQuIICdB9nGuu9g4MEAkxyEC+9vrrsPSj97Ca/v5NiCVjP3WbU2MBP9FSojseIHoqRNSJEjnKzcj5qKMGuX7RIuQRUZRutTaZs5ZgWEkGRAmmk/n+3G2EADKHaDRJNEQbDibm//tAG37W1s12GBN0NQ0wCGpJEgRzkvESpOsKilj19mEbIfPH9xxFP5P2n1jSCCuTaMkMu2uIpJRdnNc+RQUiT2tRuC9mkzcSrM9U1p1w++xwsHXGll/H1pnoCXshe/34hnq8cWwce0bboKlYriRTUhlBqkWEHUP4yxtbsKwq+nFS2Z+6rWoB1QKqBdKxQGpPrnSO8D7+zuS+fSQIo4anQK8l25vBMNChDY2NKf3oUrGNB9t0eqYwQL3uiSnCrH1urtu5zCwXoczWwICj7mQFjIu5idDrRZ/9DAxlZeh5lEEm9ZCtXLCEHdUgmWkBtXI7kTZxUu7ETkZVuwTeixdj2ef/AhVXXslFeKHjKy68jgu9LNJZGbIfvubqnIpz7w9QwIrnlypkONo5iZ0kQHOT/CWZIZD2oZdfUZj2cw8fRh2/XEj4clQUAvddyH3bghpMkGm890c/gZsQ3cV/8XkULGpN5nDqNjEsICoHjp5emJNkFI+xG+VtuW8NTAYFmLRyDgyidG28rQm1ZkXHJ7BLVnlEH1ycWy21jEXnW3qt51YBDcVWrPrMp2Ai6qTjF78m0f8wColaKSC6Qo6psPxLgMmXi3PMTkdY5pp5xTKce//HUXvl5QsSYXJ2OnGM5cT5XMjOCEMYKeimz9udEkzHqU6ldmzum/8/Uw07UQpLsIPuP/4J+//zv5Hb24caBgQWyslF0z020x6FtKmVCYDx3n4cfegROPmdc7/2VejTJKtMcGrqx2ehBQJE7LhefwVeIuVk3uYw4ZZDOVAJbuXvELXI3cPD8OzfC11lJcyXXA4dW5xOxcjlMWekxzLfu1L9ZnYwmo/hZYL8wSMdeOhoJ1y2MuhtZGmPkYRXnn18vonUZG5VLcbHR/E/RzphYhHgY4saFLWaWEPOYZRSjuPTXQojfIGh7AQp5fxnkuxBnrcCcZdnsNMzSWSOE5XWxSSgFL9k/vZyvCVUVPlHash/7OEdGOujj1a1LLl+dD5fg9PDCI514SPnleMTGyllmYWESCwbqO+rFlAtoFogngXUAD2edRJ8JsG0VFHT6T2P3LWW+9FwcfTbJ2cc8Siw8RH2Y+84+DyOdL5FluRJ+Cl3ghzROZdlipUmaquWMEBft+xarGi9jIvLTMZd+qKbGQDYyFzd88tfY/B3v8XAtIPfmBVImdEdFcZ2Q0MDam69DdU33QgL/zuWPrs491XMknew6pWVQVIXG6tlwrg9OyQY0lGKRXEo+Iq2GKdy7BNtbWSQTqLHlsezHzqEw9/6D2gZnNcq58YAP04+Qj4Txvw8akLnMfDq+t1mtDHIWPrlL8FA3Vp1pGcBH7kegqym6rPkLClOF/fnJ6t79MEgmkG53TnAPupJtkX4FId2xhecuQ+lyiNOY4G5UmEql3tVhqm8DEvv+ygD/7XoeOa36H/xFXJATFIpXIpfPK449vzvEO8TI0maWm+6AXWExxc0NSrkZ9FGhTA3y3dYac98cC6xclbAJF2+QF3nDHleZC3hxsSf7IupNR5hoRMdeR2je/Zi1//9NxjGxhWeAL0kJSI3mneuM+z8eiY+9Kzgdfz2d9AweFr3N38d85kVZ3fqR6oFTlqAgZqXSCjHKy8haLeTmJGw6qKid+b4XFPJPR4i/NzPxLf96V/DfOEGGFauzgoU/Z3j8LkhyQH4J8nDwOR9Blwsyj5FylGKABH97PJke6F/GI8R1u6yliAvTnAeebsI9F62F3TLfx/uwFJrAS6tKIka4Aq3zISjB+N86VgxzzeK0kPs2S5eijw7lT50PneFK2No4giqS1YyUWqMPBXlmFdSXeXH95+L+xikT/axJa2QwXYBCfbkeSSJUjme+BTyn+Jf0JcSWLuO6hN3nVeBbzDAL8oQGbngxNQ3VAuoFlAtkIIFonuEKezgbN40hw/6WPDVdOwyE4MuXKgC7OPce/RFvLjtp8w498Jk0aKglEGggdlrWWyopRrwsQJOzeBOOgrtJELbuu9ZfOjqv4K1YEYaTargJevXw0p9dP9ffQXj27dj6uAheOgQCzOyVNqlZz2/tVWpmGtYKY43pBq4ptCCLaNT7Msjw3km8FtxclglXWo2zMu6S2Y931SCIDVSA3RM2PUX75QSfuZnO0KQgVaZTdTq4w8fHbO2hx5C+OABVvP0SgtCsigJCcaK6bAI3Ln72WfJzr+CcPe7suu0xT/99+WnWYrP49pGpMamnIOs7nQqFXM9HUBjHvXA2VM9m84K0cGVvkm3h1V4OosWI4mEiprpPDLg5UlKa0kFpddK16yG53Ofxtje/Zg4cgQekirKXDOz2laycgUKW1uQl58PjcydOBcncNFGbreH30fVSSWFuBcS40ORqgsxMVFF9uUKvuaOPLK3e32CLsk8GSa2E3vkMoBONILshd3y1b8BKP3UYClggmvhMzDWPoT4r4T2C3rDCvFf2do1aGRyUR2qBdKxgMwP77GjcG55TdEM1xO6nhOHlFICRw3Xy1wSRQZGR+B8600FAWdctYbfy6z1be755xZaEe6nBCITizkR8zbV65Trksp3LhNhc587fYSn/6azH71MMBuokR6rch7reLK9zmrDONt7HjncieVFBSgzLvQjXKyCj1POMU9roMZ4cbLLqnJYgcGbDVbluTtib0dV8dKoiRPZ9goG6S/95cX4u6cOYhvbzybYouDLo7Qc+9JzhGfjRGAOtx2m4DTqi3W4m3KO966vhc2SHEQ/li3U91ULqBZQLZCpBdQAPQMLGqhX7FQqqpk7tAEuFgFWw/MiFkav342te5/G7998CHnGAOpaCqA3RDq9hM/ylzSYtCguNWJqwoNj3dvwg19/AXdd9/eoreAiJv/HIFNrZj8nX9U33Ki80h06OiZXl5Xguz1DCJHhNZeVw3RHWCqZrJJeUl1CmaqT1yYBeom1hlVrA/zeIDXQM7td3SKVFs6hDvq5CU916tBhDFHbuo5OR34aFQupplv5o0zx2gaIWCgleVw+exXVkboF9OzPlv5rYTPPxpB+brAilZcfSSAUxjgD8zFCL3VaMys7pUrFJnJoeE8YBXbJPkiPbxpT7KP08t/q0tUKHFOGMtfotFvkRXnC+g9cG7mbpP+WcPVGSqLt3LOfxE4uaiEngQCJsXdxznWUa1rS3ICKiAqaUV8IcZ4lITh7HTF2E/dtqZAFQyKVpo9L6DS7kyNP/FLhbliZX5hScD77fbFPOROK43YHjv3ySVRdcjH0rHiqQ7VAShaQNZgJbveO7QDniba0LG5wPnffUkHWso0sOE55wV07oSFBqL6FrU1RkHApnZNsLEkAK6vMhI4r818hp0s+iTX3eGG21Qg5nKIIMSepLs/EAxNTeH10EjpC23PjJCXinX+utIAVFuFl9u0fnpymHCnbAuZ8QZ4LdiZAWcJn4tOWUnA+uxsdFSL0unyiCEfhJLGlxRBbLrOFsmsPf/wcvHh4BH84MIyjww5MuqYIlyeCgHY1mjUor8jDuQ31uGF1BZZSQjVZcs94dlA/Uy2gWkC1QKYWyKwkmenRz/DvF65eRWIz9jRnoTXUzQVS+tj07GOdzWorlfMjL+CFbQ/DYg2jqq4wSnA+34iy6BQWG9G02IZpzyCeevFb6B8+KoDTrFpbYGRLC/NxuZUkKuw9C5PIKp0hkL0ge+/rEaAGOllaI2C+tqJqVBS3wsngOjiHQC7VY0kF3k4d9IYaogTM8WXQpALS9fjjMDIgFNh9ukNqrlYmHBw7d2LqCH+DrPUQp3tGZ+b3BM1R2NiIadov07tYvi/93zqbValkzw6pnI9PkRSJLwMDVTPZgqMF53MtKJBwE7cVdmGRBuob3avA4U/FuJ0Q+FI61L7e3pkWmDQOIvdfkOoDi1iRv6SiXHFQ5w6znvOCb/kDroyeF8LcHqJkktgxUaAfJHt9+5O/4TzRMTmX/lyTK6nifeLo7sbAG2+mYR31K2e7BUKs/HoOHVCCbA0D2FRRYTlEi2gYnEoSzLOPzwImwrI1ctnmoi2rQMjlYqvLfPWFpI8hSDV+n5A0Jh84/+dU+EXedNfoBCaYkNSI9FocRE+i42nM+fBx338ks7uSDJ0z3ExkevzTJ8jgIgsNifZ88vMZuLtOIZhL5NsYSRx3/aoKfOv2lXj4vnPwnbtX41t3rMQDfH33njV4+GPn4EuXVJNjhmz1AwNwkqg3lKVkcPJXpG6pWkC1gGqB+RZI3yNSLYmyDRejzfBfJHrysfd4IZQrWROJSy9szvlr1rKP62Q2eGDkOF54+8fQm0MoLSO7qTS8Jzn0Rg2q6wvQ392JV3b8Ajdc/OmktL+T3L2yWRkd/Xtrq7D/UBtGhgfJmFrFRT+FW0ocBvsEjBNjuKOqHIsoMxU5Sopq0FK3Dq+TIdbtJKFWvsi8RG4V/2/pE3RM0KkJ5mHD6tvib8xPBZo+8sorKGGfbt6J3uKEX4qxgYlOm8HtweS+PSi79JKohHsxvqq+PccCVRdvRN+LL8FFGa5MmNyFBXySEPX82hoUsGoyOwQyOTrVobADC6Q9MniN92MIWZzZkINp9i+OTnaQqLGFBa70nc9oxyph8PlFksn98/6D8I8MQ8fqXmrVOZEOmoCeAfo1rU1YwwAkcmilpYRwfScrU3JNiYLryO/L30IKpwT4SvLCmjDJMU6kimt4CPXUZs50CH+FZpLwWUqz1V+7KSoJVqbHUL///rVAkIGZ9J7nWvJnqtRpXKrA4aV67icc3U9ItcDfU5un0Q8qFXod29BCTB6EpuxKu1RKa63MTUqtync1ROlpxM+YU90X5vaDrHjnChFemtXz2TOXxIZU0rcx4JcAfbYiLYG0tNAESUZrlJ76ebX16Ncd611JjhrYky4VdCGSjdaLHvldLfthKosMykuGh9wBHdu24q29e9in3gvP1LSSRNcRoWApLUUFiXIbzl+P0qamyF2pf6sWUC2gWuCUWyCFaOqUn8sZdwBLSzOsGy7C2IsvUropDEOqkSOvOMRgc5oSKk6zCS2XEppZMlPdlYrelt2/gsM7zMo5e8JTCM5nDSlBuq0sD539Owl5fxtrl26aIY5L0dLSt60stITVzWU1zeMCf1mZDfdyYXuQ5DJT/FvDLH9SjgP3F5wYh66/F1ex9/zDNZWwRpBWyWkKzH1580Z0ULt8kBVKkVxLBeouCXy3w4/JcS+WNlyBltrE8HYPs+g+svOashA0SICvp12mj7chQLh7NEb8FH+Os3Lzmssvw8GHHkZf3wCaNUxWpZikmTWazDUPoe2LLroIeScYv6XqPUE2YQ17L0361ILz2f3q2KtuYH+jwzMCi7eEAXts2GW8H9B/AiWiZVtF5CXe2dRAGOokfk3H3y8QeithqklUncOsjgWZCAt3d+GaijLc3dw0wygfcSKSVCgk6Z3HO0Xo/pRii0Qogrm7EAc8wN58QRMUmMqVFoBEY/LoMVYESVrHCnqmQ55Nel6rc2hIIQCU/n51vL8t4PE7+Cxg8Mp+5kxGmIk/X0+PQh6ZWxSftCzRcaQfPTg9BV9HO/RNzex5Tj95/86xeG8LUZ2url5JIoDJNg3PM6m1ljuR3vUgkW5CDJdXT/JXVuTnDmFv73ezv508FNHY3RNdc+TnueRt6Zoan4d4Eu4OeTYIwWY2JOm0hLqLnyTPqmQC9NlzDPG3PvLSS3j7iZ9j4BATnnxeaEnAydS/kvyXJK6X6/ZeWzGK6hqw7JpNWHfHHbCUlEZepvq3agHVAqoFTpkF1AA9A9NKj2nDR+7G/r17MUJJlkpmhVM1qCyMQ3QqLRsuIInbRe+Qs41N9uNA+2soKNbDyN7ydMZMj1Uepkl4drxnF1rrzyfrdHKBw5FhJ3b2MsM87sKEyw+2bFE+JQcVBQYsKTNhHeH2wolOV08AACAASURBVHJayir6/Y218DDz/BgD20lCVjXsxctlFSHWCFFLPDQ2gjy+JDj/4uJGLI5SPZ/9fjnl4zau/TCe3zKK0YEe2MpN7B1L7NBLYsE17cP4sBs1Jatx8Tl3EHa7sEofeZ4uVj/IZ03W8MhPUv9b6qjClu8mwZdU5tWRngWEHX3ZJ+7Hjn/4BkZ9HqI3KHeU4q6kh72P8NNi8gFIwD87nJ4Javm6GFST5TcDxIRU3wMBJ6bZkz6X2T3eaXo4sQ4OTmH/wBS6J92Y8oiWApCv16K60IDlFflYWVkIE2GaJgbjX1i+lJ+G8SzvUY/0kjKhJwFB9GrUDKTVP0rHnJXzWxicf55V+Mo4JFN6nQXW/FqMMWEhDPaSdNAKoVKCISgVH6/dS/iqwP4l0Fcc8QRDiPNypWolMhYZDuHZyKOHHXA4lWSYGqBnaNAz4Osuzt1XDzyCy1f9LxQyKZT2IIIt0N+naJtnGlBL0kwqyFJBF/3yTPc3e02i562rqeU+mUzo6kB4SPrk+cyKkwBQWOaZQA9OjvOc2Lu9aDH72YmeiSgmSALeIwzxhux0PQrTvMDm50boQhwZYg96DhOBisJMhmM2eegPJA/5l6r5locfwtuP/4wJmV5UanNh5rlq6MeQAmhmSJDO//IRjTMyuh0vU8WlZ/cuXP2lL6Ny6bIMz1r9umoB1QKqBZKzQGIPKrn9nJVbyUIszOjVd92Jnh8+CB0DsBL2XiVrVC8XxW4f5Z7YX9vKQN/c0PCOHQ+2vU6H14WCooVQ1FSMrcsTIhQdBkZFN30wYYB+bMSJH23rw+uddnRO+DAa0MEtaulcUDWEphXmjqHSGFaC9A+tqcCNy0pRT4f/Cy0NaOC/P+joxVGB4BEmKC+F0Eak03itksUX7dgwe/OsDLI+XleJj9RVK9D2eHqjEjS1kNhtEz6FP7zxA8L229lnT+3UIiO5vqIv9F5PkGR5brimgqgrPxeXr/soKkqakgrApC9eRuYhw8wvpexHSvnqyMgCjTdej/F9+9HzqycVB0/Yu5P9jTx0wDuk/7K2Gss/+QkY6djO/CxUPyC8XarHgtbIZMg5CTRcgn2pFIlWeqwRYPJoR88kntjVi7f5b9+0H+NBLfzhmaeHLieIIo2fwbQGq6sKcPe5tbikuQS1RNp8acVy1Od34/HObnSxkqZAclktlqAAwprOSlWIbRUhp0N5iTLzRxe34paGOtTw+/GGzDULe+oFqi5SSC7PGIN0i3JdsZIXQWrFe1nJ9PGahbCpOL+O2y+UP4p6XJF8yuLcmGXaz55cXNSzVt98j1hAQ1LG9YvvQAEJHTMZCj8D5RBFVjSV9pZYxxQCtiBZ3YWULdGYmBzB7gNvorP3KKYcJGmjtGhZSTWWtqzG4pY1TJCd9Cikb1zfxBYaJuW8rP76urr432b2vhcwuDYqKhEiCSmJgTCVUYJci6UnXsvqr4FqIvKciAzO5fyEc07PQDUsmfgsDLGnBL7zHtDiA/D/smFfOUXNiSBfqujJDC+Tdq9+/7t4/Yc/QDH5Bhr19NWYqHgnVzFnMRGL60Vxg68prxvHf78ZXj5Lb/i7v1eD9GSMrW6jWkC1QMYWSDaWzPhA79cdCGS58d574SP0tOcXvyA81IsqYYhOEDlMs5rXSViVv7IKiz/3OaU/OXdO/3YbK946Vs10+sx6WWUx1LMaN24n+YmLMk0xhmTQn9k/jG+93IXdQx44TCTQKqTTI6zUJ6SSglxcx+lQj3umcaitD9u6j2JL2zi+ckUj6q1GfLS+BpeU2vDc4DCe7RvG3rFRMtPTELL602mQqnQzHZdrKmy4Tek5t6A4Cqw92ilKFW9R/ToU5Zfj9Z2/wK6jz2Nq3AM9q/gmM4ltmAkXP18k2aRX3eUiSZWuAOcvvwHrll8PW2E14brJ2dLA4E2pCGYhppYWBr/AEwmnzs0CjDeabc6W93RUH1hJ2bIA51j3s89RczeoVNJFUSDWkJ9wkomzPo8LARIwbviH/4NSkjvODqnqCCw7h/D2bKRkBGorlWc/g/RYAbrDG8Av9/Tju1va0TZFOKWplH2hhNWy4qw90RcqDu44E2JjZBw+dHAIr3aM4yPn1OAvL29FNYPs+1ubcTFRBX/s68fz/QM4yiq5wN5n55p0xLQyYbaJ7O/XVFdhCR14qcAnM6QyVWAuV2Cj49M97POkjjthpBpCSjUinUbHWBztEM8vwOBcmJk1PLYtv4GyiGUp9a7nEbYrmvDy/ImXpEvmvOWc/HTWDUwKaiMgvMl8X93mzLNAIe+3jCrns5fM+096tHMNmSXp3rHgiXkshGzRRoAB9PHOA3hq88PYuuslJSGmTF8JkuVcgnxy8f+tRWW48ep7semyD5O40jyTJOM2uuoaaNgn7W9vh4+tK8I+P5PnOrFoKYEnW9K47uStWAltZTWfcbGfk3om0StYRT7sY2DPHWUaRIf8PkpDMqk35+Jln1I9ZwaB72a+uAb57JaRTBtOkGvAvt8+izdZPS8lE34F/Y5k2Nol/V9Ev6yJaICOV17Ga+UVuPavvoaCihn52mi/rfqeagHVAqoFsmGB5Dy2bBzp/boPLjpGskEv/cuvUCLNis5HHsEIIWWVJFopoUM8ty9dAlwHq7ODXLzGCFMzkpl59T//C0rZD5sbEagO27uJthMoWOaGy2HDrl90m71OLr4iLzK/6hxi8PzzXQP4+h8YMLiNCFWzT1t60WIEPmHCxEP5JeiZGsKDO9sw7g7gn65rRaPNiOUFFjQzgPhkQy3sXBQ7qa1q57Ua6FTU0WkWSLyJWWkjHYJUL00gsxW2Rtx8+RewYc2tePvgczjS8RaGCfeVQEscFHHyS4uasG7NRqxefDWEBV7LisRsZS0Za5pJHibVf5ew5SYZ1MTar5+Blp+BZCH1dDVq0BDLTEm/b6ZjdM5fflmpgB977OfU051CGRNiVvY8ztXPFv9W+s2HiFCZ4n1YtGYVLvvXfyYbfMM8fV8JLuXe0Z2QR0v6RGJsmMt+WJljAe432nD7g3hsRy/n2hFM6YpJrFgLbR5RJhFzUr6rzA/OtXBBKbrHevDAy8cxOO3Fv9+0AvmspK1lj+QyStD9+ZJFmKSKQifhm04+Xyw6DWpYVbMx2JB5Js53qnNNEAUmQ5FCmufy2hXYvhAyef1T78wluv/sMxdIfA3l5MqUXuDIZ0s0G8x9T4j65Nk37SM6Zw6rdKLvRfucjzF4OP+LSmzIE3IudZwFFkj1zo5lEq4QXJdORLmxNkr+fbkZJQadDdRPfFNRi2DFfPOLT2Dzy08ojObWMpKSFeQpyfjZNTfARLPXFcD0pB2P/eYBvL7teXz0w1/E8lYSycrzQnbN555+yVIFth4kHDtIdJrIw8kxpddcU8CkMJOa3GnC87YwCF1ZXICXuoZZcWcvegb8K9LKJW1s59ex1W3OsSWQFuJJeZ4oCJfEpxX3vP0k55UhjO7xhhxr+NgxbH30JzARvVdqIJFfEjaZu0+Rf60K63Dw2WdIHHc+zrntw3xuq1rp8eyufqZaQLVAZhZQA/TM7DfzbT7s9WRFXfbVr6L88stx+IFvo2vLFqVCTu44VvhY2+Ei4aMTLrljLaVYWu69B62f+TR0MYiMRKYoyYJvwiuQxUj8hCCz+eIzzF0XZZ188dg4/u8LHTjmKwSqF9NRib/wKN/nYhtm8OshLPgJMkuXmTvxt9c0o8ScpwTj8hLSt4YEkNqEJx+xgTgweTojqsoW4Wa+wpeyd87nJPP0hBIcFFBCLWOoMpMrtg0bYP/jn9iLRnK8DDwJNwMmJ41ft2oVf+tI3e1Ur17dXpxN6Udf++UvomrjBuz77vfRtWcv2h12kvFplPYSIflhHYgEjDkwV1Vijcy12z+k6JIvGDIBOGIloxZsn8Qbyr6iwC7lUC+3jeJrmw/DJ5Xm8gZlHsUdvKdlPmrLm+HNMxIS34FySx6+dhV7SZm9MzD4lpeVzmJj1u8veW5oCXm3KS8ZIqEmSQ1Bo0g1PdWAPPJaS2ReFOQzyTaYcYAuiAofA/PipUuyQnQVea7q3+9jC3Au5VgsbL9ikJuFEeZaK0HyXCkz8QGGRvrwy+cexJs7nufzKIja2kIF/RU5tHxPy6DdmK+Dx+knQeoxfP+n38BdN38W68+9komxOaR4XF9EFk5e6Q6Bcp9bYkVRRz8cLudMu0ya616QSVMjV84rayICdCb9BJUjdhAm92Q4KuJdT4AtgJIQNSYgowwyaXF8y2sY3bkLdXmizJJ6ZkC+UcTn7DR9ut1PPomWjRejuLYu3umpn6kWUC2gWiAjCyTwDjPa91n5Zdu6ddjws8fgaGvHyBtvYPrYUfiZBRfSFANlUorokJaxYq6NEZjPGs1ktJKcbTwrNhSyNDaRK4t6JDe0EFM99HY/9jvYM1rBHu0EwfncE5JFK2yyIWhrwo8YOJxfX4QPra5gNTL1BTDdC5VgyKi3KK9sDWGxrbvtVux9+WWMs/pvY8CeeyKQS+UYkg6ZZCuDkb954RJJfKjTLRX7xds2l7aspIJC+frzMXnkGIZ37IS9rQ1+B1mdWVmyENZtW7USJYSzx6umzrQ95NBhnIFLxjtmcp/JXJOAf2E7xYjTi688fQBesqNry+oTB+cRB9RYKykz58Uv9w6SpLEY1ywuS6Y4ltxpJ7mVhq0m8srWkKRV4/XXY///fBfVDGpMc/ptUzmGPOIELZFPNEHFBRek8lV1W9UCXJ9JwEbpQi+l1oSELaNnNZNzwrciBI6Mvt+x7pRjAptfegJbd/8eZna05BcKY3r8tVIq0CYm5KTdbZxyhL/e/CBMpnycs2ID5+HCZ0y6P6UcZ4m1gC1qRXiWxI2ihS6kcqmOkLTtkRfjypIiLOf+Iq9O2s7ymNQXfh2ppqdLFudnotBLVGChuSIhxN1NktyDzz8PM/MgFumLT3Po+FsV0ub9O7djhGuNlW0G2WC8T/N01K+pFlAt8D63gBoxnKIf2NLcBHmlOypLmjF07IjSwpamz/rOoYPsnzLmWWE0zCeI8RMH/FaXHb87xqoBYeE5STCcR16POBjhgjJMuifx4x2DuLjJipoTOqOR257uv6WSOkWSHieDZCHlEkIYCysFAqWNm0TnhyUXXogiVmiHXn2NCzsDhxThDNJ7Pkk487jJgIbrruW90Hy6L/+sOF4uJ0fxsqXKK52h9FSzShxIgQk43nECRL7k8F6JJvv036+2o4OkhdraWgYE6QS5IrVUiQ4yvj+1v59BehGKTfHRLvHONZufBTjX7KxUufmskX5yLZ8LFs4z0axPBCdtvfPD6Hj2t+geGEQzAwNdBCw40XkKBmKCbUN2QldXXnsNLNS4V4dqgVQskMPAK49tSN5Dh9iL7oaGLU7pjpCQofJlbOCaeqJtI8CFfN+hbXh122+RZwoxOGd1PUFwPvf4EqAXlRgwNtyFP776K1RXNKCqPLsV3EquVR9sqMJ++1F0UPUhr6KSAJ/kXcQwoe0+8s7U54TwkZZaFLGdLXLo2TpnNhTD7uxX+CtSkUeb3Zf064u0mrTUFFNxItFwMWEwsH8vyvkbJ3oWJdqXWdoHyFXQs2snmqXQoui5q0O1gGoB1QLZt0DyT9/sH1vdYxwLLGvagJ2HnoObZGfSn5bukADfzR7x4oI6Bf49d9g9fmw+OEL9clafWbFPd0jVPWwpwavdx3FoyImqQn3GhE/pnot8z8WAfOe4HYcot3ScryEuqCIhY+DiWm7UY5HFrPTKLy/MR34MB0TIq5o++Ukc6OlFb0cHaoUNP0qfcKzzlMTAAIP0oksuQ9W1m6LDq2N9WX3/tFlAINoGXT6DSwehl8Gole9UTsbHqo5UhvIi+iIn3H78ZEcPe0KLSUSVvvOfQzRHiAmxXT1D2MdA/VIyu7+bY4yBiGizH7VPoX3agVGpoDHxZ2SlqortLU1ECi1hn/wKaxE5AqJXr8zk8FhLXoHtX/8G+rmPSrJRx9o28loFLjvBimcXj1t9zQfQdPONkZuof6sWSGwB3pva0nJoK8qpF05VB4URPXX3SMgdQ4Li4X2vk0TciX04Sfb4p9eeYtXXjtIyS0rB+ezJC9mrpTAPB4+9jQNHd6DMVkmKlNQSfZLMEpES+VeQ9XMr3JLA3lhegnuaXPjOoU5MDA1AX16ZlB2k79w3MoQi1zTuW1yPC8psSkI8cihtaJTDc/vsVIgga76RbUkp8H/IfPf4pvmMcaOMRYVEAb7yfOjtZX++g3wa6ftRs9eRJwR9/GPo6FGEREYu811Gmkj9W7WAagHVAooFUl+BVMOdFgs0154Da0E1HBNjhLhJlW/hYpfMiXjJGO11hlFft4L7m888OkUpste6HYChAjmZZoJNRdT61uNVsrpf1sIgJHvou2Qu851tdkzY8UTPAF4bncBRVs29AtMjgZjShC99wZMu6AbHsZy6y5eVFOO22kqsZqAeySAtjpXtvPPQ9OlPo+0730FXdzc1U3UM6EncJ95NjCGcvaN0Vki1A/0F69H8538GS1P6SIoYh1HfzqIFLGRRn3YN0ml0KBre6Y5gyKdUhfIpUyaV+blje8+EQvCmq89MDoo3soJ06RgN4eiwg4gV24J7N93zT+V7oim/dXgUz9H5fXNkDB0MTMKiTS9OsDjmJH0LO0dh7O7DYibFNpaV4lYSwi0mm3y0Ub/parjIRH3kwUcUwish/pPqe7ynno/ze4yw9gG+yq6+Eis/+xnomVhTh2qBdCyQS/4CkSJzvPwS5cmmoGVSKRp5Y8x9MxgMsX9bXsZ166G1nUye9Q50UPlkOwps5JPQRU9Uxdzv7AecDAZKpk7bHdi1f4sCc7dZyxJ+TRJmRyfDODIWZAKMKidcpGQJ03MNLDflYFFxLpbyZaT0g5DF3c3qt2zwwME22Ml4nldWwZY8wtWjBNxKP/n0FLwMzkvDAXx6cQPuaqkjiWVs11KC6tKCZgyMH8SUe1iRZkwUaMtFCsGem5VzhVjPUk1pvcTXLt9zSsKF/wqqJ9Mh+xHuDzer8nLt6lAtoFpAtcCpskDsp+ipOqK636QsYKATvmHNh/D8G/8Fh92LAmsa/WBciKfZY15oqsPihvPZg36SJEvWllGnDz0OBq0l8VlQkzph3UwgvHfAwQx9+LT2ocv5CZz9yb5BfK+tG9vJaB0qIzyPToVGggbFWeDiLEEEAwvpk9tDfdjDgyPYycrfZ5vrcTUrB5FVOy0ZcKuv/4BS/W77/g/Qvm8fioQRnIG6kOrMJs8Fzu7lvqdYmhgnc/g0HZmyD96Mlj/7JAqXL5sJWJIyorrRu2EBg86iaH9POgcVRzGVis7s+Qrs0uVh7yYD83z2RUaOXT125R7MyaB6PrtPgcfTbUaf3QO3n3rDhL+ezjFFKabfdHXjR+TZaJNqHDWWdSTYUoJzycyJI6/MNcqwscK+l8HO3rZO7Bobx/9ij/gVlUwIRjj70sspRH55rDwe/fFP0XHsuDLPpB1F+tIZSyhDXGJBw0wFfGwhCcDN4L/xrnux5J67kF+XXcjv6bSpeqx33wJyD+qbWxAYHoZ71y5WjgmJVtQAkgvsQi5KOfK7eS2tMCxbPjMf5J7l2rTnwFts/fDDaCbXSwZDyOOMJh2OduyFw2lPGKAfHA3i2WOUa/SKzCkDfE5PnWgwMmh3+8Pgco2dQ0EUGXJwZb0W55Szws05d/+SBqwsKcTXtu7D4c42IgooXSis8IIsIFQ8LK0s1Af3M5mWw/aSpYUW/O2albikcuE6Gu1yDXlcW20r0DN2ANMM0uUZbMjjeh2R2JTvinyiJD7dZH+XFiKBtRdTOSLattGOdSr6xDMlx4x2nup7qgVUC6gWmGsBNUB/j94PIgu2svUyHO/ZgfaBN9mHroGZjK6pDDurxV5HHs5fezlqKpYs+OoY2WH9El1GWRQXbJzgDXFhwoS6D5LBVXpQE41JBrujb72F6ePH4Z+gPjuhb/oyatqSgbnskktgqkm+j1SO96veQXzzSBuOMQmhWdwCjYEEPJGEMPxbCdYpPyUyan46HFv6ejF68JgCx7uSQXokLE9Y9is3XYOCRYvQ+/TT6H3icQwPDkHnzVGCBnF6hF5MWMMD7GUuYNV95cfuQ+n69TDweuI3uyeykvr56bCAOFvW/Do43ONwesaUYD1Z50/OTxxwN7XCfX4PqkqWMchfmEwbmHIrZBJCRpXxkCCYQbqdsHkPeQ7iBeghJqTGDxzE8NvbYW/vgI+JKUGHGElgVbx4MSouvAAmQsyTdWKlx/wpBucPHDiMUc4fHWXvckU+MBK+Lr2aAu9lgizXbEGoyIo3uzoxuXe/kkwTbfbIITr3jTdej6JFrej63WZ0/3YzRtgLK+kH0bqXZ4wQLyoS0exvLdmwHqvuuB1l550LvVQ71aFaIEMLiLyYad0FJHnzwHPwoKKNrqNsn1JJj1JB5uTnEfnsJxFscHIceXX1MF+08URgf/Jk2nsOs5+bbOvpVs/nXJf0o4+MDSgBujx7IpNdsqkE35s7AnijP0h1C6AmPwf5bNM6mWo4+V9ObjtMlN2TR/zosGuwqUHLgD0XGwhTf+mGS/FMVz+eaOvFrtFRJqIlXJZgn6SzrCRfyCD+jsYluLG+inKOqSADRI2FLTDl52LY3oFJRz/h/2SPZ1+5VsNnBkk2c6h+I2zvfvKDSPtRntaEyuKlRCjZ+FnyxyrkM4risvAn4Zckun1Eklb4NvKph57sMzPRPtXPVQuoFlAtEM0CWfAWo+1WfS8bFihgX/dVF3wcT704huG+oyirzodR4O4JEvqyaI8NuTA+4sM5Sz6Ai6gZHik9piyzWViw5l0nHZhwgpMbfWsrjjzwHxjfvYd6q37ouQCTy1VZ9Me4s25WzXLofEtQvPgvPk94eGNCU745NonvHO/CcYMZmsZmfj8xcYsE7zmFhQjxeIe72/GvDO4bWN1YHEWqSsP9FSxehMVf+Dya/+wTGN++XXk5u3sRIrxW+tXzGcCXXLge5sYG6BiQpNO/mPBC1Q1OmQV0rJzXlK5E9/BuBuqjJDJiD2USvZEK7FL0wdkXWVbUzOBeIOwLJyjd6Jnyb5auQKZuvPkrSJGhbW9j/w8exNj+Aww0PJxrhHkqko/soeRcPc4gWsN7vu6qq7D6859TtOXjDUmE7Rgdw7cOHsI4A+68GvbYniDBivc9qbhppMLO6uTB9jZ879BRVBGVIn3pkUPmmm3FchS1tmLJR+/FyK7dGN27F66+PoQYmeuLi2DlXCxjIkzI4HTcj+xfHaoFsmUB0Q43X3qFgsDyHNgPX0+3kmTKVe41ukyyxkmgKmgsEsoFKc2WS/SIYdlKmNZfuCA4l4k/aR9jv3huVtpRcqmSIkG53THJuczQM0IxYorVcgnOdw8GUcqlsNTC48YxjpkV9frCHEx4wtjNanqQ82xTkw42I0kpeZxbGqpJHlcNJ7ke+p1uKkmQdJZzrprPDoHEZzIk0C5nL7nVUoUpF5ELvkklIA8QbaCkE3h8C0nlzCL1yGdyqtJsYqei6mrK4BbDxeSkSKVlMtx8BjKfgSo+ozRpcBRkcmz1u6oFVAucXRbI7Ol6dtnqtF+tLFA15YtxyxVfwtMv/ye62/ehuNSI4jIjJVZkyWVArPzv7CCBijOAoT4HPO4Q1q+6GTdc+jnCzRcGrLLvEgb7OZSXkux0VgahbqXE0EUrNARI0nLkv76D9ocehMblRgMdGhsXuMhqo5sOxzCJ3foefwLDL7+C5V/7a9TccguL/NHRAxOEnP+ydwA7AyFomxuSCs7nXmsuiaxClTXY1nYcj3b346+XNMMcbRHnRWkI85NX5aZNyksd7y8L5BFmWVO6Gv0Cu6SzqKe+rp7v5Uo1eN4sm0luBYMeVtwn6asHUGZtRZElNuqjlFJJoH74jEMdz11OwqbCpcBj5hss7CNduC8vSdsO//RRHPrRT6BzulAjQa+e0P2IielmgDE85UTH479Ax3PPYeO/fRM1l10aM+Cd4lx7gNX4Uco16quqkwrO5801gcmywvg2pSef6uwigZwFpihOrlSmtEZua6xUdOwbrr8uCaOom6gWyJ4FBNJtunADmd0blSA9MDKsEI0JtFuGsuYKHwm307c0Q794GfTCNRKJJDlxSvGSaWmfdZQEu4dtbW+yan5gJMTOtRwU6+c+uWIfSXIOxYS5i1txcCyEAj11zFlJN53wEOV6LZyri8jXkv3BajoTpCUF9dx1vSJ5Kc9U4YXJzRHFlYUJz1TOwUAUXMP6Dej93bPwM8EicmnpDPG1pvnM1DAhX7f2/2fvPOAkq6r8f2a6e7pnOk3OOTJ5GGDIOWckShIVBQERXAV1/bvL4rr7WTeaMIGKKJJzkhwGUEDJYWByzjn0dPyf74PbVFdXdVd1rKr+Ha0P0y/e933vhhPuubPTynDfkvvpHBEQga5NQAp6Frz/4YMm23nH/7O98Pc77N2Fc23Zh5t8jdIaK/IMqD08ZI4531W7a61ylysOtT2svGS0nX7YhTZj4hFJOzf6PJZoGl6WZ8sqdziFpr1nzWGq8zmhPuHUpg1hHlnDDrDC5+V98H//aytvv8OGeEjucPdGJPvwyJQ+yhWKQa7AL16/zt771x/42rSbbMyFFxhzwmOFDvNvnq39ifWeBGbw8I9DbZsraIL93b3DzevXz25eusouGjXcxpd8Olc/weHalMMEilwpH+FK+sZtS1z53uhh656R2aeARN50/zYZaNe6ol3zibJd1KPE50OO8iUMG3uDYzHNHPpx8rm6im3WrWfLE9FxzTpfA7iodrcN86Wains0rEm7PCT8XfeaL/zjbTbIQ+EH+1SOZMuW4QUb5V7BQV7fFu/aYS9+/Zs269pv2IQzz4gMUfHy8pq19pIr/z08SqV7ClEq8efzd57fr9YzZT/t1zrKQQV2wAAAIABJREFUw9z39+RxEhHIRAIohgXufeVX40nBqj16pHanK+me+4CoDTzqeX37fpwMrhklsndZX1uxjrAXf9KW6Yf1iIgk4SIlxeUNQr3ZumhLrb25tsZ8mrovc4anPXWyHFvm51S6DeK1VTU2tnd3m9LPjZNpXCP1uyU/Ms/bLf7XVlLkbeCU446zxc8/Y1t86kI/n4rWkkci98Vmz60x/sijrM+IkUnHVm1Vbl1HBESgaxNIpid1bSoZ+PRkYD/ZveF7TT7Ok7a8ZItXvuuhtdusxsPE811xKPG5c/18SZSxI/a0qWMP+njN82aeo6wo3w4cUWK3LdoaDfpbtjbzJzfZtcWKrNIO8XXQY7OlVm3ZYot+f4utuedeG+EDi4Eevp5K11vko4KxnpBmhSehWXzTTVbo8wCHn3JKFEoYJFpObfNWW+Lqfr5byVszksjzObkb3EvymCsOX3UDh6TrEiDcfWDviT6/e7vt9HD3XR6+jkenzj07DOzyff43CY2KfWnCXoV9Uwq73H90H+vjo+at29a7ISn1xFON34Ib4VyZHu3esQkDPGw8ZqRZ4wnZPrr9Tlt06+021L1dZEKPX52g8fVIHJVnE4tLXUnfZe///FeeqK0s8lrHr4H8x0WL3bjgSkmfli/JiIeR0OEFvl4yy7PNdsNYenNXEz2BtolA+xLI8ykd/Fom3Wz0iEn21ry5Vu1JHfN7NI56See6Va5B9y7tb2UlvRsoiTs99vqDjbW2o7LOhpT69JUWaKGUrI+Htm+vrLWXVlR7hvcenv8hndK137Hkv1jhEUEbd+22SleUizyCYZCv3c5yjk2tb57nY4Yx++5rYw47whY//KD19DaI9czTEeadr3fDTIFP65lx8qlW3Jo2MJ0b61gREIEuS0AKeha9euZrDRs0MfrVege1fecG2121y8e8edaryJeI8cyo6SRP6d0z346b1M8emb/Utm7faHXlg1pkWa7zzOW2bZ3NGVJo04d8umRZnc9ZW//XV2zFXXfZAO9U+/cocOU89d6+hx87xJWMSl9+aYmH7JZPmeJJ5CbXK+Kb3Djxpivo5vNbjURVrZBuvdw779d4eu1G+6qHyku6NgHqUU9XwvkRll7tS6hF4ek+mxOPOnUuHelXXGjnzx5uP3tltdWWe2I1X6WhJUKkSp4vX7bn+DKb6tEqscJ87Xke1t7fyz7Aw9DTieREkR/p3/8iT3b14a23WW8P2+3LCgSfCOHwr7gHMc+XXGrtnO/ubkys8pD799x4t6Wy0gZ6OLtEBHKVAJ74mVP2swef/K1V7KyyklYsaVrtU7kqfJ206eOmW2lJw0icjR5Bt3ATSSNJ4NZymijkeNIXujeeaw5yY2BnyortO+2hRcvt1TUbbI1Pj2MufLRSjCvZpR5BNKK0lx06bIgdPnyQh+k3ns5H2cs9qdu+F3zONi5ZYsvfetNGuqOgZ4pJ7Uhqudbvuc2dAPufe56NmTOnkfGyM/no3iIgArlJoBXNeG4CyZanYl5sWckAG9BnpPUrH2Y9C0vTUs55zh7eQR3kHu8jRvlSZNtW+VphO9N+/Ghu3fZ11rd2i12412AbWPqph7vSvd8rH3nECjxT+gD36PlssrSvjyd9kCdy2+1J5dY++6zVeLKrIDvcor7Ul1TrRlb2RPPG07mb80RJf9fn5EpEIJYAynqBZxYmi3CBZ2hPVzkP17r0gDE2zqeU1G5Y7nNZfUpIuuIGgprNa2xYQYWdMm2wDSr9dDBa5+GXb//8l9bD8zcMcgW4Jd4z5qhjEKv48CNb/rSvBR1T15bt2GFb3YPU3T3orRVWUuju91nm3jAG2xIRyHUCw4eMsQmjZ9n2rZWGkt1S2b3TldPK7rbntIOsvLRv/WUIb/fVWG2jJ3pjKbXWhqV7ehpXgs0WbG55WVv6jOE8klL+4YOFdv5jL9j/vDXPHt+yy95wR8SCfkNt8aAR9lHfQfZaXi+7b/Vmu+6vb9rXnnvFXlixxo2p0GgoRAONnrOPHX7V1VY4YaLNd8PgJm/PmpNKL8Piikrb4NF8sz57nu173gXW05PLSkRABESgvQlIQW9vwhl+/ZF9etoX9x1mU3t5775hsc+v8/+mKFE3uH299di81M6YXGbH79HPw84++aS8YyPz8oZnnvbMqQWtCmMlOU2xX2/Vo49Zla+pHKSKKAIf7LRaOf/kgmRe3+AKv0QE2oPA2H697NojxllptS/JtGllNK0kVcEQVrN5lZX4Wu1nzxxih40f0MDctcGXhFrnWdsHuOLbIx3XeVwBmJde5sng8MZv9/obZIMvN8WoP5Ws7c0/kxvqXEnf7so5oaoSEch1AijTxx12tu2u8PBxNOnGOmSzCAht37qpwvYYu5dNmTjbs8J/mjgVnX+TZ29HMS9oiXUu7u6FvoYol1m+tXPqZ4Ub36+d+zf77suv20cesVQ5frIVjJ9kPYYMtfw+Pu/fpxvk9/U114cOt/yJU2zryHH2nC8re9Xzr9o9vqJLJdaFOMn3tnHKUUfbGf/zv9Zvz73so8pqe9+NkBtcUa8kK/8n74Sl1Lb5+Sjmb+Kx9yk5R17zbTvmmmutxKfCSURABESgIwgoxL0jKGfwPejMj5zQz/7h0Cq7/onFtnj1+1Y3cIJnQ286BDfynG9eYQWunJ88vpddfcgoG1IW69GrsS3vvmvdPCy21MNZu7dgQBKw8ZGWueKw5J23rWLtOisaNCjaRehgFGmcwGLeIuT+TLHz51t0DZ0kAkkIEEZ+yrQhtm5Hpf3w2UW23RX0vL7DrVuPpqdnoMjXrPelnrausbP2GmpXHDzOyB8RKyuee96TNNZE89xbI8zlLPGB/xqfb75tyTIrHzcuulxBfThoKypybMG8rnGv1nr6WvOsOlcEOopAnvdf0yfPsSP2P9Weefkeyy/Is+LS1DOU43XfunG39czvb0ce/BnDIx9XnTxnBuuTJ00kn9ajEuuGgr6jmQVeWGquasd2W/3KX23F88/Z5g/neVLXjb7MaIGVDB9mA2buaSOPPsZKffUG8seksnY4UTX//NIbdvvCpb6e2SgrcqW8QUMRAvFoPGhDPPoNhb3Ok/atWb7UvvfqW54kz6fvjRrWqD/Hkz5q9l526Z1326t/utVeuPHXtmgVxlLPL+I5cpiaHuXg83+wXOpeJ59kh19xpfUb3ZB3WjB1sAiIgAi0gIAU9BZAy7VTevXIs/NmD/Gs7gV2zQPzbP6iV6yu7zCfuOUdYzSvPfSIbvj3RFnmia5s01LrWb3dzpkxwK47dpyN6MOc10+Pq/UOb+sHH3r6tm6elOXT7S1l18vDjLu7d3vb/I+st69BSsdc6J1oP9fQP6xpPlQtlfvWedjbsCRz2FI5X8eIQHMEyosK7Ev7jormTv7H0/Nt5dJNrqQPse7kf4hbd73OV0Wo2bLeat1znue5Jv7x6An21YPGekLIxs32hrff9tBWH1SmmfwoUXl7eN0iY/Wu9V7PP5Fh5HhwpbrWPel5rY3wxGvuXvq+PogvSnMuf6LyapsIZAOB3mX97KSjzrdt2zfZG+/PtVr30hb7lLC8BEslhufBm1vjieU2ra+w/LpyO+XYC22/2YlXZ2mDbrYBRvRUd6QnFm8LdvkqK8uefNLe+91vrMLXiqfdKPTEbb38v3Uo90uX2MaXXrT3bvyFDTn4cJt0wYXWf9p0y3dFOpkQUfOH9xfao8tXW7cRo61g4JBkhzba3s095IUjRtn2pXV2/atv25iyEpvaL/HqGgW+SsUBX/ii7XfRRbbs76/bSl9Kb4vnuqnxdqmXJ4AbNGG8jdpnjieD+3QaQaMbaoMIiIAItCOBxiO9dryZLp25BFhP+dRpA22/Ub3t355YYL95dantdu94bbceVucevrpunt7Nw9/zqna6lb7OJvQvsuuOm2ynzxiUOFO0d7S7PVMzjrdo2bVWOt7yXfHAWb7bl5HCe4/RoMyt5OM9g+tLnn26jrnonvilpYIFvc49AXv3aZh4q6XX03kikIxAmSvpX95/tM0Z2dv+89n59uQHS23HmoVWV+BKcMEnUSg+R71bVYXnbai1g8f1t+uPn22zhicebHKfinU+1cSXD2oLidYf9oFqFes+41ly798QH1QP8UHtuu3bzD6JYGnpvWqrKqP57eMG9rMyTxwpEYGuQmDksHF27mlXWHGvcnv1rWdtl9ex4jLPz+JG8u7usg7G8DpXzPGa7/Kkcju2VNtwTwx7zKFn2hEHnuKzQxr3c/SzJZ4cjmCyGlzArdTWuQRR4m53byS0CRvff9/e+fUvbM3TT1q5983DvR8ude90gyVWvdvf7RfZ5G3Jhmefsr/Oe88mXnCRjT3pFCtMkgX93fWb7YGFy2xLaW/r0Tf9JRi7FfTwMPhhtmzhfPvZmx/Yjw/f140MyawMOMp9qcm9945+EhEQARHIJAJtM6LLpCdSWVpFYJBb9H90+mT77tFj7ZH319vflm+xZT7vrdJ77D6eIGrSoIF2qCeWO3hcn8SKedzdw7yuVhWKkz1BVv0ksU8u1scV9H16l9mf1rkhYeeOVinotVs2u/Gh0o4fnP6goNXPpgt0SQIzh/W2W87b2z5Yt82e/Wi9vbF8s63d6TkQfJTdr7jYpnmW9iMnDLQ9BpXEhJgnRoX9qxt1pK3EB7WxkTNc9iRft/zGFSut1pdza+k66Fyn1pPDlfg1pvXp7UY2Keht9cp0newgMHLYeLvwzK/ZJM/E/tqbz9vi5fNs/Ya1rqC74dkVa9TJ6mrPUu4J0Ab2HWf7T5tlB8851o+f6Qpl4rRBhKP3KeoWhXTv9iC3Vs50sV0eLo+yP6a84WoVGMc3uLf5jR/9r+3422ueDb3Q+nod7p7IIODnE+U22I/p7cesXrvWPrzxV8ZykBPPPsd6lDUMxWHe+NyVa2zeLl86duQID5Nv2fC0uyd7ze8/wB5Zvswu37jFpiXxomfH16JSioAIdFUCLWsBuyqtLvTcAz1D9OfnDIt+LRLvmAs9ocp2H26wJEoq6zE3dR/WIa3p5hlqB3pyrE8s4oTz7tm33PbqWWB/2eTz3nwZlJZ06nVu4a/zNdBnFRfZgf0V0tbUe9C+tiXApzx5YGn0a430GjjQNr37fmsuUX8u3rM6H1AXuJEgNgHjmWNH2d2eOG6b15UeQ71dSKIsNFUI6lqt19W9PPx0mnvRWtsuNHUv7ROBTCVA0rijDznDl1/b3xYvm2cr1y6zTZvX2e7Kj5dNLS0utwH9hvhc87E2dtQe1iNE1jTxQL19abQhpd1sw846K/M63NJccRjVt3n+ShZkGVnW0Pu8w1dk+eCW39vON1634YUFVp6iEl3kbcVQV9RXb91iC2671Yq9/Rjlc9O7xxjoVntCtjc3bLKKklLr4dE6rZH8Pv1s1+oVdrcnjJOC3hqSOlcERKCzCEhB7yzyOX7f7mSD3mMPW81cNVfQW5tZdqdfp66olxWP8aRVMSFrE0uL7ZQhA22er5O6xddDz3PLeTqKA+F6tWvXWLmHt186aYyVu1deIgLZRqCf52VY9dQzUTbi1mRx57mrPM9EXr++VtS/XwMME93jdY57tm5avtKqva7l9ybkPnn4aCOGPu2lyue19/O6dsLkSTamtKTRIdogAl2JwMD+Q41frUe/VFTsdM95lXdvbtz2pRIJZY+PYmmKTZ+e3Wxi7+729NZqIxCn1BX2lshO995v84zwBwzPd0/8p9eo8RwtJIJb9/ILNtQd+WUpKuehDCzrOshzvFS4gW/eLTfbwNmzrXjwp3PMWeN80TY3UJT2a5GhPfZZifDp3rPYnvO57LbvzJZg0DkiIAIi0KkEEsdLdWqRdPNcIIDnrXzyZLMB/W2bD/hrm5gH1tzzkgJumyeCK54y2XoO/jiDezinl9/n1KGD7IR+5dZj5XKr2bihUSh8sutHyrnPaS9as9rOGdjXjhnky7a0wCuY7PraLgIdRWD44YdandeFTT5NozVCpMo2rxe9xoz2zMsjG1yqyBNAnT9urB1aVmY1y5Zb9eYtHq+eWlg9obFVPjAvdGPYSUMH27HDh6quteZF6dycItDdlfJePUusrLSPlZZ4X+Ye83SUc2AU+Ghucv88G1bSzdbv8vrGvJc0xfPR2YYKD5d3ZX+vQT4vPkbH3+4h48ufe9aKt++Mpqa0RP0n5H2g54rZ/t47tmruCw366i27fa66L3kWLeXYivFCeGRC3Rdu3ZZwXfQ0sehwERABEehwAlLQOxx5F7mhd7C9fJmV/ocdapvdK7DbB/0tlR2unG/zAf6QE0+wgvLGKaRH9iqyqyeMsRPLfe7ZkkVWvWRxlG26KWF/jWee7blymZ3Zv9wuGzfK+rciyVxT99I+EWhvAr0nTbKB++5j6yt3uwc8NaU5UZkqWH3Bo0j6z5ppJSOGNziEAflo93pfNWWSHVLc02q9nlW5cYuw9aakdtdOq1y8yLp5eOxnPNrlkkkTbWArQ1ibup/2iUBXJTCoVzfbf1i+9fD066u2+7SwNJoCd5zbOg+Pr/Ku+qhR+Taw+OP58IHl1iVLbMubr/t88jwraIUCTVh8kUf6LHrwQU8t82kBabcqfHsqS7Gl8n67eztW5dfb5cu2SURABEQg2whIQc+2N5ZF5e3hc0yHnniiVQ4ZbOtdSW9JN7nbQ//W+LlFHg438JBDLM9D1+IFT8MePqf1B1Mn2tUjBluhr2ta9e7bVr1ooXvUN7qyXmG1lT731f/L39ULF/j+t6zf+jXR8d+dPN7GlvTSfNh4sPo7awiwvu+MK6+wCpIx7a5o0aIJNW4EW+kJnIrG+7KJRx+VsK6REXmmh7//0+wZ9tnBA61o1Srb9f57VunetRqfXxrVNeaZ+8oK1R7NstvrWsW8D6zY//0dV+yvmT7VRpYUZw1XFVQEsokAevOMAXl2pCvY6L6LNrvS65o388qTCft2+zErttXZTu+kjxqdZ1PdEx87h73a6/OWBfMtf8eOVi+NGFZg2fDm36OEcUHyvPBMzyHapi2krromigAg8kciAiIgAtlGQBNus+2NZVF5CXPvv//+Nvycc2zRz35mPXzpqP4eupeXYgfsqdtstc972+prkU658EIrmzgxaegb3r3hvXraNZPG2hnDh9iP5y+2B1etts2rVvie2GC8Oivxv88eMci+NGakTfI57D29nBIRyHYC/WdMtymXfdne/b+fRuHjA30ea6phqAyJl7qne2d5qe153jnWZ+KEpDhIzjjJI1n+ZfZMO2nEMLt5/kJ73BX0isirFnNHN66RwfkU98RfvMcEG+JrqWsKSVKs2iECbUKAarjf0Dwr9UjxxxZW21JXvHt6hvhyz/Lew7XuKGzdKzxrleMt3+rzzXd4PHzfnt3tkBF5Nmuge8jjXDc1bvTbsXKlb+/eKu95eED63LpdFbbVo3D6Tp4SbS7zpHN9fJ46EXdtITU+p3+s58qgzBIREAERyDYCUtCz7Y1lWXnzvYMc8/nPe0bVtbbwzjusyi3mQ3ztY19VPemTMF+92uetL3ZP3CZfX3XCJV+2YSeflFLiGDr+qe5N/+XsafY/Htr25uZtNm/7Dtvu/yapDUnl9u5Trk47KX3tyFYCeT162MTzzrWda9baotvvNOaTD3Ilval1gD2gNAqJX+TLFG7x0NXpF11oY087tdn5r9TeXl6fDvXoGH47vX69umGDLdm23cNUaz3ZYoHt0bvcI1vKrFAGsGz9pFTuLCYw1T3pw8u6219X1dhHG2tsizurCfnGQ41BjhUU8JKXezK56f27295D8mxISWJlFm909c7tfjwKfvK+O1VcXIcl5XZv3lx/yiA34I32SLYF7qWv6+1z0dNMQhd772i1iG3bfDnYhtN0Ui2fjhMBERCBziYgBb2z30AXuH+RL7c29TvftgJXnJffd79tWLfBBrulvNQ7YHzXUTIc97ahLKBUbPbB/iqrtbyRo2yPi79go889N2G4bXPoiv36B/TvE/0kItAVCBR6ZvWZHurew5ccXHDv/bbFE7kNzC+wEq8L3b1+fZx46uOQ1yqvc5t9ILvW/9t90ADb54qv2Pgzz2hWOU/EMVLWB3kCR34SERCBjCCA8n306Hzb15XvFdtrbdMus52fZI8r8tFfH/eaD/G55v08KVyTgkKdl/9x+HkzhzZ5nU921hsJ3KgYZEhJTw/P72PPf7Tc6txj3y2/5as8VPtSjj3cUHj6+IaJLlMpm44RAREQgUwgIAU9E95CFyhDoc9bnfad71i/OXNs6W232cr5C6zWPW6FO3daHpPlXDGv9kF+pSsW+b6m80AP1x19wQXWd6+9ugAdPaIItB0BDGLTr7jM+s2cYYvue8DWzJ9vqzZusnzqWuQ962Y1Pi+zxhO9FQzztZb9uMmfu8B6NxHW3nal05VEQAQ6kgD6NIp6eWHLp3J1d0W6qF9/2+StB0Z0POCtkUqmufk1iocMrb9MkUfaHDh4gP15yUp7b8N6Xwu9pxsF0i9zlP9iw1o7cugAmzWgb2uKqXNFQAREoNMISEHvNPRd78YsnzL0uONs0KGH2obXXrMt775ru3xeW7WHoBPxTob24lGjrM/MmVY+bbp1V3KXrveR6InbhEC+h4uO9ERvg/edYxvefsc2vveB7fCEbiR7IktyDw89Lx01wvpPnx4p5t1Z2kgiAiIgAgkI0J6UjxljS7yj3u2p4VkurTXClLMiV857ujExVma6Qn38yKG29MPFtmtjL8sfMDCt2xDaXrV2lQ2qq7YrZ07SVLa06OlgERCBTCIgBT2T3kYXKUued/YDDz44+uE5r/XOmtDbyFreSst8F0GoxxSBlAigiA858IDoF4WVsuTQJ3Ut3XWWU7qhDhIBEcg5AqwSUTpqtBWMGOnJ4lZ4Arp8bOotkt0eMbfd57QPO/QwN8I3HIL2dKP8BZPH2nxfv/yBpUt8Lfc6K0BJT2FcUOcJZSs9KWzPzRvtH/aeajP7y3veohekk0RABDKCQOvMoBnxCCpEVhPwjhfvXZQQJoVOOKufVYUXgU4kgEJOXWNQLOW8E1+Ebi0CWUigfOxYG7Dv/rbRs6xX1Hj69xbK+t2uSBf28GSUpydc83xAzyL7/n6z7PjhA2z34vlWsWi+1fnyjUnFlfiabVutYsGHVrJ5vX1rz8l2+riRnpxSw9ukzLRDBEQg4wnIg57xr0gFFAEREAEREAEREIHOI1DYu4+NOPJIW/vaK7Zu2VIbWtS9yRUiEpV0S2WVbXDv+bhzz7cy98gnk75FhfaLw/ezWf3n2Y9f9+k57hWvK+9teeV9rFthTzOi7WqqrdZXn6jZtMHytm+zKeUl9s05e9lRI4dYfitD8JOVS9tFQAREoKMISEHvKNK6jwiIgAiIgAiIgAhkKYHB++xr49zz/d5Nv7b8XTttgCePK4gWVm9aan15t+3udV/lU2xK99rbJpzz2WiliaaE5dwun7GHnTh6uP1x3iJ7YeUa27BmuVV6iHztJ4nqWMJxqGd/P3HKdDtl7AjD+y4RAREQgVwgIAU9F96inkEEREAEREAEREAE2pEAU2TGn3m2Vfla5fPvvN0qtvoyjoUFVtQ9L6E3nWTtlb6M49aqalvns9Z7zpptMy7/qpWNHpNyKUf58qz/uM9021E12Rb53PQ1Oyus0hPV9fL56sNKim2M789LwUiQ8g11oAiIgAhkAAEp6BnwElQEERABERABERABEch0Ani+p3zhYs/APsAWPnS/LXz3HSuzKit2b3YP8lyQS8b/X+1e8wr3dm+rrbHdHp4+2JPCTTjjLOs3dXrCuefNPXexJ6ab1q+P/5o7UvtFQAREIPsJSEHP/neoJxABERABERABERCBDiFQUFxsE8462/pOnWqr/vKSrfv7323t/A+tZsMGM1/qDOnmx/TwrO99XSEfvN9+NmifOdZr4KAOKZ9uIgIiIALZTkAKera/QZVfBERABERABERABDqQAMui9p8+w/pM2sN2HH2s7Vq31nZv2Wo1FbuiJVMLikussE8fKx485OP1zrVKSwe+Hd1KBEQg2wlIQc/2N6jyi4AIiIAIiIAIiEAnEMjzRHHMKY/mlfuk8zomnrt0Uyb1TngbuqUIiECuEJCCnitvUs8hAiIgAiIgAiIgAp1FwL3k3eQp7yz6uq8IiEAOEeieQ8+iRxEBERABERABERABERABERABERCBrCUgBT1rX50KLgIiIAIiIAIiIAIiIAIiIAIikEsEpKDn0tvUs4iACIiACIiACIiACIiACIiACGQtASnoWfvq0i/49u3b6xO4pHI2yV62bduWyqFpH7Ns2TL761//2m7XT7tAOkEE2oBAra/7u2PHjrSu9NZbb9nf/va3tM5pi4NfffVVe/vtt9viUrqGCIhAGxKg3w3J1lK57MqVK6P+dPPmzakc3mbHLFq0KLrvzp072+yaupAIiIAIiICZksRlwVdAR/3666/b+++/b6tWrbLCwkIbMmSIHXDAATZ06NCUnmDhwoX23//933bSSSfZ8ccfn9I5zz//vN1xxx32la98xaZPn57SOake9HdfN/Xxxx+3f/iHf7DS0tJGp1VUVNgf//jH+u0FBQU2cOBAGzZsmE2bNk2JaBoR04ZUCDz44IO2du1a+9znPmd8U0H4FjEanXDCCVHdCvLOO+9EA9BDDjnEJkyY0Owt+GY5/l//9V+td+/ezR7PAffdd1+k1O+1114pHd9WB1HWQYMGJa3b1FHanSBlZWVRHZw8eXL0X4kIdEUC9MMvvfSSHXjggbbHHnvUI6CPfeaZZ2zixIl28MEH128PfRl913HHHdcssnnz5tmPf/xj+8xnPmNHHXVUs8dzAIa2Bx54wK644oqU252ULtzMQX/5y19s7ty59t3vftd69erV6OitW7fanXfeWb+9h2d8p+0YMWJE1I4ooVynZJ9yAAAgAElEQVQjZNogAiIgAhEBKegZ/iFUV1fbTTfdZHjZ6Nzo5On0PvzwQ3vhhRfsrLPOsoMOOqjZp+jbt6/NnDnTxo4d2+yx4YBRo0bZjBkzokF8RwvPjYLAM/fxtVQrKyvtlVdeibwKY8aMsQsuuMAGDx6cVrHwUuI1xOAg6ZoEdu/eHX1XsQo3Xu8nnngi8gJh8IpV0F977bXoeAxbqQgDdu5RXFycyuFpHUM5qAMd9f1iDOSeGBowCr733nuGspHnaxwfeeSRdvLJJ1v3NJdS+sUvfmH77LNPhxsj0gKtg0WgCQLUbeoFdSJWQQ9txfLlyxso6CjuHJ+qUat///5Rvzt69OgmStGyXdRfDPUXX3xx2v1nS+5Iv82zFxUVWXl5edQ2otQjGDzpx3nedATjCOOfz3/+8+mcpmNFQAREIKsISEHP8Nf17LPPRsr5lClT7Itf/KL17NkzKjHevp///OeRh3vSpEk2YMCARk+CMrtly5bIQ80g+5JLLml0DBt27dplKMQlJSUNLNoMEC699NKE57CxqqrKUG4YqCQS7o8xgfunO5AP1xs/fnzkFUDo7J966il7+OGH7de//rV95zvfsfz8hp8wAxDKFG/Npywvv/xykyGAcEAC40TPpG3ZTYABNV6ujz76qN4jvmTJkkg5572/++679REmfDMcR92JH1wzXYTvPtYLDxmUT37xEuoi3yVGp2TCcZQlXsFnOwPTpkJYqcN8w/H1ONyLa1DusD9V79V5551nU6dOjYxjq1evjiJbiDjAo3744Yc3eJSm6jyRC3j6iIBJJNRbQntb014kuq62iUBbEhg+fHhUP+fPn9/gshiwaEP4ztevX1+veNKGIPTTsUL/icJKfYyVfv36Je13k/XV4fxQp2lDUIrj+13qH+Hw3DuRNFV/w/GUASNdU+1Y/LVpPxi/IPTRf/7zn6M25De/+Y1985vfbFTOZH0x5XvxxRcbHR/uF9pPysfzS0RABEQgWwlIQc/gN0dn89hjj0VKKJbmWMWREDG8emGwfP7550dP8s///M+RMk+H+Kc//Ska0P/TP/1TpKgTNkd4+4knnhgdi8WfQT8DCAbHsQP2//u//4s89Hfffbd9+ctfjrzveNR+8IMfRGWho8dwwACAe3FdyoTQ+f/+97+PjuHflJsyEd6Xakh+dKE4YUDAfTZt2hR10oTWHXbYYdFRWOUfeeQR27BhQ/QceP/33XffyFNKGW644YbI6o589atfjf777W9/2xhsYQTBgwornocog/3339/222+/6DhJ7hDA4MM7jh1cE7KKzJkzx5jWQbg5A3C+Jb4JvqNQNwj5vuuuu6LtbEPhR4ElQgX57W9/G80nDyHuDEb5Lqkr69ati44J1+L7oi4hDCb5nu+///5IQcc4Rpgsx/D9Yowj9BUJ3++3vvWtqM5Rt2kHeA7qMYrzGWecYXvvvXd0PEKo/h/+8IdIAeZetB3xRqz6g5P8g3ITXYDR7rrrrotCaqknXA/j2S233NKozlNfOQfl5eabb46uTLt022232bhx4+zrX/96xJuycUwwFNJe0E6l611LUnRtFoE2I0D7gff3jTfeiOoenmEUcuo3/RH9CYa+Qw89NLon/SuGPCK/ENoV6iv9EX08EWJnn3125DVHOJf6fsopp9gxxxwTbWPaDAbmBQsWNOirKQv9ehDKQx+NEk659txzz+g6GBOffvrpqH1B/uM//iP67xFHHGGnn356dE0U5ieffDIy8jHmoO2hHQmKONemfeN5aAvo90O7V1+AFP5Be3HqqadGzPCuE9VGG4s899xzUV9MH8896IuZykdZaBfpxxcvXhwdG9rBf/mXfzGMGpQf4ytOAbjQ1tOGzp49O4VS6RAREAERyCwCUtAz6300KA2dFJ0lHQ2dbbyEeeGE1AWhw2cwTmfOwBhvHgMAOlf28UPowH/3u99F8+UYbDNo+NnPfhZ54q+++uqog449Pvb6DKYJtafzRmlHscBiTdgcwmAEBYdOmDLQoTL3d+PGjZG1vLVCZ42CHjpqrsf98MzhpaipqYmUottvvz1SdDAKMA2AhDYcx4AECYMLtjH/l0EXChVl5RnhLgWhtW8rs85ncIjxhrBTlEG+cxRDvlPqEwPEDz74IPoegueLOoKg1N94443RN8W3z4AcAxpeoG984xvRgDK+zjz00EPRoJGpKFyT4xnAEx4eO7+UusF3x3dKGRlM8/1yDtdlvitljv1+GZQysKbeMthFoWU6CoNs6jbfLmXl2r/85S+j66A0cA0GwQxk4713qbwtPNwMzjFEUP9RPBjEo/CHOk9d49lDnScKAWUBox8DbgwblAPhPJ6Zekn54R+mHFx22WWpFEnHiECHEuD7RUGnjcAQRhuC0DdRL/ibuobhiggd+hb6Rdqcn/zkJ1EkC3WFPgjFkoiwf/zHf6yfXhPbjixdujQyeFPnUEbXrFkTKar0wVdeeWWD58bwhXGLezMdhraG+kkZMeZRDgx5tD+0DyEyiPaG9gdlFmWZ8tMWUuYzzzwzugdl4HlRmrkeBn6MCS0VWKGg01YEBZ02gXaCcsIu9MXckzEQBhCOp9xh2lHIYUM7wjUx/MEXAyJGQfpxjJYSERABEcgmAlLQM/htoTQjyazUDK5RMIJnLjwKg2I6/2B9T/SIKLcMAujQGOjzoxOkA24uxJt7XnPNNfXh5ZyDUYAONVjbP/vZz9bflsEMnTlh+dwzeBATlSuVbSGcn3DbIChXsYns8MoxWGFwM3LkyEjRufXWW6Nni0/GFR+WDHcGBpRXCnoqbyS7juF7ZJDHt0EeA+oCAz8GcgxIGZzyjQQve5hnSlgmcuGFF9bP3+QbZCCMwYsBc7ygVOO9IpIDrw73YdDMNxY7PQNFG088kSoIdQllnrKwjfLgeY7/fql3K1asiAbkIQEVBrn//M//jIx0KOj8l+szKA/HMIhFUWipxNbB4Bk899xz6y8XX+cxknEcCjoGktg6SHtw0UUX1Z+LkQ2PIe9HIgKZSCCEqwcFHaWX/piILJKfEWlD5AvtDHUvHM92+utjjz3Wjj766OjRUEqpi0SBkRguXrgGQrQKYwF+1CH6p/goGJR4It4QlNzrr78+UoJRqPk7JJtFiQ8Rb/TJtG2Un3pIu8R1eCYM4RgjMQBiOEMxJrErdZY2DaMChr6WSOhbMTgEoZyxkT+0kyjaOCG4N+0GXnzKGt+Px+fiwXiIsZK2WQp6S96QzhEBEehMAlLQO5N+M/cOc7sZrCcSPMX84r1gKAJ05k1JSIRFx0doL9ehQ6MjwxvelDDoj1UuGJTQyRI+i6JPh88ghMELSg7hwPzwHrSFgh7mp8U+N9tQhrgnzxTm6iabaxf7fCjzhA5SVpQdDBxIMu5NsdG+zCfAYPnRRx+NvhW+E75JBqwo5yjpeIXYxn4GhSEbOwM96gYh7kHCt8L3nkhBp57hQWM/3mG+LwQlOl5QmoNQpxAGxk0JZUL4dn/6059G/6bsSDDcMScWib0+dbg1hrL4OpiozhO1k0qd51wMHTwDP84jkoV2TCICmUgAAxV1mO+VvpPpJ4SoU6doSzDasY8+CQkKOn0sgvIbDFAo8Ei8oT3a6BKSodKv4V2mTtHf0i7F1+HYOk7bRZvWXBtCfSN8nP6UJI5BqIP0gSjgsW1IuCf/xahPJEFLJL4N4RqUI7QD6fbFeM3DmIP2JPBUP96St6NzREAEOpuAFPTOfgNN3D94qeiMEym2WJfZHp9lnZCvREuXxd4qzNEm6RqWcTppOlzmwjUn8feLH0ij/JDIDeWEwQohwnTyoUNu7vrN7Q8Dm2BkYPCAx5CBEl50rP8MSsJgqKnr4YX4n//5n0jx4lwGWWwLA5KmztW+7CSAJ5eBK4oz3z3/xruEBM8R+6hfscslkdCJbz18dxzPvzkHw1QiwUvGXNN///d/jxR4vl3ujyc9VvCixRqc4gfeia7NNgbRCMpCbCI7PNahTGGAGnt9jH/x3rdk94jfTpsT6mDIKcGUEn6xdR62qdR5DB5EFYSll/BAMrgOzxZ/f/0tAp1NgPpJv0akB0ohbQN9HRKWD0M5px1h+gZRXEj4poMnPDwHbUOyVUkwGuItJqKGiBmmvmEgZ9pMvMT2zZQxlXaEsiOUM75tYzv3Cm1I/LgikaExvkzJ/qafRcI9Ucj/67/+q0FfjFEilb4YAztz8XkG+nGijlD0QxRisjJouwiIgAhkKgEp6Jn6ZrxchLOiSNPJ09kEJSIUmYRWSBgYpPMoKBqEmGGFZ34rA4jWetW4P4N3BtuEujOXHaUADwFham0hDCZQ/hl4hBA3ksxgeT/ttNPqwwZRFuKFc4J3MewjrJDBB0n2mBuLxHpI46+hv7OfAANOPD8M/lAiQ2g7T4ayzfsnrwISm3kZBZi6SH1JNpiOp8P3Tz3mfoR9M3hPtD56KgNprh3//QalHGWcUNREEqbIECoba9QicqQlA2w8ZlwLQwPXpkzMV22uzodnjH0GvIGwxkBBwjgMB9RHVqdIlUmiZ9Y2EWhvAkFBJ9EqQt1GqPOh38aQxXHBiB3qK4o0ydtSEYzH1G/6a/oo+mn660T1I9G22HskqoNcm/JhTKMPTRRBF9uGxF4vRAik8hyxx9D2YMjnXkQFIEzFoe4zVSaEq5OkNpHEt4O0IbQlTK0L16OtloiACIhAthJQDGGGv7mQ0IwkT3RgWJPp9O+5555IEaZzDdli03kUOjgSMYV1n+m4Q1h4OteJP5br0JmjlNPZ0umHhFTxx6byN+fzvIQEksiGOXUwYHknBipIGDxwP+7LoCEMmmLvwaCJaATCgrkuxwcFBcWfc/GGEJ4oyW0CKN54V1DSw8CaJyZqhYEwOROQkCCOfwcDDnWPwR91iMiQpr4Xvls8Q3yrKPUYBII3Kl3Csd9vCD/FW4RCQHkpB9dmWgde+xD+HnIz0F7gaaIOJDJgJSsP9Y15+iS/Io/DTTfdFEUdYNSivvOjHsEj1HkSX8XPTaX8CFMIqG/sZ4DOtJpwLgN3yha8esnKpO0i0NkEQtvACg1MSYn1LmM0pw4y7SvWyIfyiJeXvpz6RF3lRxRbMk8x/RKRbvTV/KgrtCMtkVAH33zzzei+hIVjsGSaG3WPto12kXtSHlZiQfDwU8cxzGGM4zyU4lTzRGBA51jqPuOB73//+9EzkBMjGA1T6YtpazBO0G4TJUc/znOEMUDox2l3mXsvEQEREIFsJSAPeoa/Obx7LGvEwJjM4rHCAIGEVQyW0xU6OhLE4YUPGWi5Bp0lyarw+LVUCAsmodX3vve9qPPHa4DXkYQz6QoDgrAkDOfiffz85z/fIJEMgx6Wj2Fgj2LA4IIkeffdd1+D25EMjrmCLEODkAGXbYQO4jXleLiQDTv+3HTLreMzm0AYXON1iY1A4f3zN/UirHccnoRvGGWbfQw0US6ZVoH3lwFuIkH5Z+AeG5VBneAeJHOKnx6S6BphW/z3yzJDXP8LX/hClK2YH0udhTmtrDvMgB4FgZwUKAVM50CYyhHC05u6J/viI0o4F299bAJF6jxJGanzcMFDGF/n2YahgkE/iab4myUgOZf6+53vfCeqfygRPGtQDporn/aLQGcQQCnEoMd0jPgoNv4ORrBYIx+ZyOm/qKes/kD9D/X18ssvbzBNJTwTx9C+UH8xBgSh/rJMY1C6U2HASidMbaHP48d1SQxHcjoM9Bjx+IVycTwGPtosvNMY54hu4YdhjXYlkTE8viwozPyC4Fi45JJL6peWYzt1Hq86RoIQcUdiy3vvvbfB5cj4fuedd0ZLyiLXXnttlAWe1TLgytiDNgjlv60i9xoUQH+IgAiIQAcQ6ObW2I8zCnXAzXSLlhPAMoxywLzqMFcMZZoBbaxgieeVxnoF2Y/FG88yyjKePMLE8UiT6Z25nygaDDQYKHPuV77ylchCjReOAQADC7x2eAXoXGMTYmEZp3MnhDdkccc7hhKDchKWTEHZprOnzDwH9yOpTVhuKfY5UJxiDQccQ9nxFsY/M+eFRD3cl9BbBv+wQImIVSSw2jOPj3JSFliGe8GYczmeYxgABct8y99c556JwYLpEczJQ2GSfEyAQTHvGAnfZGCDB4m6hjEozB2N5UYCIjzK1AfqBQpwmM8d6gJ1iO+K3AjsI+MxdQFPEt4rvGcsIcYAGKMRxxJeH4TvFC89dTzkomBfou+X7XiS8I5Tpwipp07z/Ya6QpvAfjxP1H+UBp6RZ4ifOhPKgKc9ZFhmwE5doG6EOh7LJJSNOhvqPPUJTrF8KQftAPNPMYCEpFYk26O+wpzy0F5RPvhIGhPAa8jSXAiKU7a3U42fMDu28H3T59BOxE5daap94clCYlLaGuorhqswbQavO3WEv+nzUFAxbpP5nX6Xvo56SV89a9asaHlTvN20S/RfsZ780NfFGglCf0dbQl0L9w11k3qH0M9zXmxCWMpLe4VTIIwxGFdwHH1pvBBRQ70OQv/NM9GfJ+rHQ9lol3AS0N4wjqAdjP3GmYfPdtjRvtAmUSd4XvhwLh55jHxh/BJfNv0tAiIgAplMQAp6Jr+ddiobgwfWI8cThjU/CB0bIeR0vv/v//2/drq7LtuRBKSgdyTthvci5ByvNnOriYQJgieJjOskeYpPFtd5pdWds4mAFPRselstLyvvmb4aTzdTSoKw/brrrou82N/61rdafgOdKQIiIAIikJEEFOKeka+lfQuFNwxrP9ZlwtnwNmOBx/uF1zxRdtj2LZGuLgK5RyB4fIhWIekRhi882ISq4uXCQCYRAREQgWQE8F6jhJOYkYgTvM94z/EeE7XGdCyJCIiACIhA7hGQgp577zSlJyKEnSQvZECnw6fzJyyM5GuEqktEQARaRwCvOeGnzBslpwGRK4R0H3nkkVFYpsKSW8dXZ4tArhMgDPyKK66I+mpWHGEKC+H0hLIfddRRDRLQ5ToLPZ8IiIAIdCUCUtC70tuOeVYs8SFDfBdFoMcWgXYnMHv2bOMnEQEREIGWEGCO+JlnntmSU3WOCIiACIhAlhLQMmtZ+uJUbBEQAREQAREQAREQAREQAREQgdwiIAU9t96nnkYEREAEREAEREAEREAEREAERCBLCSjEPUtfXKYUm2yyLNeGkAgr0ZJpmVJWlUMEcoUASzuRbA45+uij01pPPVcY6DlEQATSJ8AShizbhpAPI3YZtfSvpjNEQAREQATag4A86O1BtQtdk8RXrK/MD2VdIgIi0P4EWGM81Lv2v5vuIAIikCsE6KdD20H/LREBERABEcg8AlLQM++dqEQiIAIiIAIiIAIiIAIiIAIiIAJdkIAU9C740vXIIiACIiACIiACIiACIiACIiACmUdACnrmvROVSAREQAREQAREQAREQAREQAREoAsSkILeBV+6HlkEREAEREAEREAEREAEREAERCDzCEhBz7x3ohKJgAiIgAiIgAiIgAiIgAiIgAh0QQJS0LvgS9cji4AIiIAIiIAIiIAIiIAIiIAIZB4BKeiZ905UIhEQAREQAREQAREQAREQAREQgS5IQAp6F3zpemQREAEREAEREAEREAEREAEREIHMIyAFPfPeiUokAiIgAiIgAiIgAiIgAiIgAiLQBQlIQe+CL12PLAIiIAIiIAIiIAIiIAIiIAIikHkEpKBn3jtRiURABERABERABERABERABERABLogASnoXfCl65FFQAREQAREQAREQAREQAREQAQyj4AU9Mx7JyqRCIiACIiACIiACIiACIiACIhAFyQgBb0LvnQ9sgiIgAiIgAiIgAiIgAiIgAiIQOYRkIKeee9EJRIBERABERABERABERABERABEeiCBKSgd8GXrkcWAREQAREQAREQAREQAREQARHIPAJS0DPvnahEIiACIiACIiACIiACIiACIiACXZCAFPQu+NL1yCIgAiIgAiIgAiIgAiIgAiIgAplHID/zitT6EtXU1FhlZWXrL6QrNEtg9+7d9cdUVFTYrl27mj1HB3Qcgerq6uhmVVVVejcdh73d70RdC0Kd695dttZ2h55BN6A+B1G7m0EvJguKEt92MF6SiIAIiIAImBUUFFh+fmaoxplRijb+KlBKtm/f3sZX7bqXo0N/8sknLSh7sSRqa2tt8+bN0ab77rvP8vLyGoFCeTj88MOttLS00T5taF8CYfClOtG+nNvj6tSr5557zurq6hpdnvcZ6t0f//hH69atW6NjevToYUcddZTxX0luEYhti3fu3BkNKiQiEAhs27bNnnnmGaN/jpfYtuP2229P2HbwPR155JFWVFQUf7r+FgEREIGcJVBcXCwFPWffbg4+GJ30lClT7NFHH23y6VavXp1wv5TzhFi0UQSaJNC7d28bPXq0zZ07t8njVq5c2Wg/CvvJJ58s5bwRGW0QgdwngDF87NixkYGvKUnUdnD8CSecIOW8KXDaJwIiIALtTEBxke0MOFcuT2e///77p/04s2bNipR7iQiIQPoEZs6caVOnTk37xEMOOcRGjBiR9nk6QQREIDcITJs2zWg/0pUDDzzQxowZk+5pOl4EREAERKANCUhBb0OYuX6p2bNn2+TJk1N+TLx/BxxwQMrH60AREIHGBFC2hw8f3nhHki0zZswwBucSERCBrk0AZXvUqFEpQ8CYjlFdIgIiIAIi0LkEpKB3Lv+su/uhhx5qQ4cObbbc/fv3t2OOOSbh/LZmT9YBIiAC9QTI4XDccccZIe/NCYNxBuUSERABEWCqy7HHHmv9+vVrFsawYcMMY6BEBERABESg8wlIQe/8d5BVJSAJ3PHHH2/l5eVJy92rVy878cQTlbgoKSHtEIH0CBQWFtpJJ53U5LzQvn37RkYxZXRPj62OFoFcJkDCN/rjnj17Jn1MjH/064mSvCY9STtEQAREQATajYAU9HZDm7sXJmkcHT5KQ7zQwbOvpKQkfpf+FgERaAUBjGIMohMp4Ay+UeCVsb0VgHWqCOQoAZLGkfgtkQJOP56sP89RHHosERABEch4AlLQM/4VZWYB+/TpE4Xdxi/vxLJOAwcOzMxCq1QikOUEmF5y2GGHNXgKBt0MvrWMYZa/XBVfBNqRwODBg6Ol02IFYx9Gv1Smz7Rj0XRpERABERCBOAJS0PVJtJgAiauYkx5k3333tfHjx7f4ejpRBESgeQIkaiRhY5AjjjjCGHxLREAERKApAhMmTLA5c+bUH0L/zdxziQiIgAiIQGYRyM+s4qg02UaAJaA2b95su3btsr333jvbiq/yikBWEthvv/2iekfyp4kTJ2blM6jQIiACHU9gn332sU2bNkXT0LQEasfz1x1FQAREIBUCUtCboPTss8/aggULmjhCu2IJ3HTTTQKSgADzgi+88MIEe7SpOQKrVq2yRx55pLnDuuz+lStX2ttvv91lnz+dByfSQOs7p0Msu4998sknbcmSJdn9EO1c+vfff7+d75D9lyfp7bnnnpv9D6InyCgCVVVVVl1dnbBMTB0l11OuyO9///uoLaYeNRdl++GHH9rtt98e9dUXXHBBriBo0XNIQW8CW2VlpVVUVDRxhHaJQPMEamtrmz9IRyQkADvVwYRotDFNAjU1NWmeocOzmYD672x+e5lT9kRJOTOndCpJthJ4/PHH7bnnnktYfKaPfu1rX0u4Lxs3EmG7bds2S2UsTD/NsRr3mUlBz8avXWUWAREQAREQAREQAREQARHIWgL9+/dvlFiZqWsSEZCCrm9ABERABERABERABERABERABDqQwJ577mlHH310WnfEy5xoycT4i+Cxbi4CpK6uLjotfkWm+GuFv5Ndk+1cI9XrEN6fn98yFTRZGZKVOVu3t4xOtj6tyi0CIiACIiACIiACIiACIiACGU7ghRdesJdfftm++MUv2uLFi+2ll16yFStWWHFxsc2aNStS7nv27Fn/FBxDXhrmcq9fv95GjBhho0ePtpkzZzZYsWHRokX2xBNP2NKlS6NzOe7YY4+Njg3CNe677z47+eSTI4NAOB4P//Tp06Pj165da48++mh9vi5WijjllFOMpZjjBWPBY489Zq+99loUxs49TzzxxJRyw2BI+Otf/xr9yL3D83OvXF4mUgp6/Bekv0VABERABERABERABERABESgEwkwfxtF+9Zbb40U03HjxkWKLYr13LlzjVwbZ555ZlTC1atX2y9+8QtDmUWBHjVqlM2fP99IeM3fQd566y37wx/+EP0ZVnJ477337IYbbrAvfelL9SvDkMiOe6NUc+2ysjIbOnRoZCB45plnon0fffRRNLd85MiR0b3effdd27Fjh1122WWNvOko+yj0JIrjWjwD5b388sujsjYlnIuhgqTLrBi1fPlye/311+2DDz6wb37zm1ZaWtrU6Vm5Twp6Vr42FVoEREAEREAEREAEREAERCBbCaAsb9iwoUHx8XZPnjy5wTYUUpTesBIJyumf/vQne/XVV+0zn/lM5OHGe46yjGf9vPPOqz+fJVl79+4d/b1792574IEHon9fcskl9VnVUaxvvvnmyGN+7bXXNrg3q+mcdNJJdsABB0Rh6U8//XSktOOpnz17tp166qmRF5/7o+Tz361bt1p5eXmD62BMuOaaa2zAgAGREeGee+6JPOKsuHHxxRc3ODb2D54d5ZzM9t/+9reNlRUQngMjBcYCvPa5Jt1z7YH0PCIgAiIgAiIgAiIgAiIgAiKQyQTWrFljf//73xv88EzHCx7n2GVCJ02aFB2CoosyjODFRlC2UXzxgCNBOeffeK05fuDAgZE3PsjEiRMj7zT33r59e/328I+99tqrfs54uDf7UNBDiD33D8pzKFPshfbYY49IOUeYqz5jxozo3/PmzUu65Bz733nnnei4ffbZp/76/B3OJ1w/F0Ue9Fx8q3omERABERABERABERABERCBjCVwyCGH2KGHHtqgfEeWSPwAACAASURBVCjK8RK/fjiKMB5lliMLS4gSfn7YYYdFy7fdfffd9uc//9kOP/zwSLEN66oHb/26devse9/7XoPb4OFGtmzZYiUlJfX7yDTPnO8gGAuCsCRcEOaYM/d8586d9WWq3+n/iA9jHzZsWP1ujAKxhoTY84LBgvn3GB6ChAR3hM3nokhBz8W3qmcSAREQAREQAREQAREQARHIWAKFhYUpzZ9Odem1E044IVLIQwj6gw8+aM8//3w0zxvlmezpCEp38EDHw4lVxsOx8ceEv4PHPNn+2O3xGd4Jy2cbinYwMiS6TjAcYKSINQiEY+Ovm+ga2bhNCno2vjWVWQREQAREQAREQAREQAREIOcJpKOEEkZ+4YUXRgnZ7rjjjvqEcmRjD4o+yeeOOuqolJZrS+feTb0IwusJiQ9C0rvgBY/1ysdfg3B8ksFhDCBzfFcRzUHvKm9azykCIiACIiACIiACIiACIpBzBAh3DwovD4diu//++0fPSaI4hAzwhNATUo7SGy/Bwx6/vS3+Jst77PVZxg1h7npBQUHSW4TwfpLSJZrb3p5lTlqoDtghD3oHQM6UWxDeMnXq1Gh5ArIsdoRgraNChWQV3JN5KmPHjo1CVZgPw/IOTYW3dEQ5dQ8R6CgChJ9RB2LnUrXnvZl7xi900OFeffv2jZZYIXxswYIFjTLJtmeZdG0REIH0CBCSSpIlvFBh7eL0rpD+0dyTdiN2AEzbxYCZ+a7MDaX/JnO0RAREIH0Cf/vb3xrVZ8bNp512WtoXY0zB/HMSvrGeOXPBwzgjJHZjbjlh8GRrJ2s7iedYgo3s7iyfhoJ/0UUXpX3vVE7YuHFjtKwa7Rj/Zj105Mgjj2zydI6fNm1alCzu3/7t36LQfJ6PtdRZ5o2s9QcddFCT18jGnVLQs/GtJSkzYSgMuPlwsZKhFKOM05m///770ZwTQlpItNARCjphNldccUWUUfLOO++MSk0Zr7zyymguDJ06VryQoTHJY2mzCGQVAazWLJGCVZiwLZYooR4ykOV7pyNhqZKOUtDPP//8aDD9wx/+MOqEERLHkJiGzpg6edttt0lBz6qvTIXNNQLUQwzoof+mrgZjOp6mQYMGRf03A/COUNBpM1iG6Y033ogG8whzRq+66qqoXaP/Rnmnf5eIgAi0jACKKr9YSTTPOpWrM+Ym0Rp1lszwGNPI1E4iOhwDQVgujTp8//33GxnQQxZ0DPlHHHFEKrdK+xgyvV999dVRyP3jjz8enY8n//TTT2+0pFyii7NsHG0fS7zxfPwQHA2MuXJRpKDn0FsNySHo2FEKCBnZe++9o48XBb2jhc6bkJTYMBoGHyjnrOFI8goqaGxITkeXUfcTgbYkgFLO3C8UcLKkopDzzWOhDuFcbXm/VK5FHaQsIdEK52CN3rFjR2TNZntshEsq19QxIiACbUcA5Zy1hPEExfbfc+bMieaMdkbbgdKA8Ty2/8ZzzsCetZcfffRR9d9t9wnoSl2MwDHHHBMZ3BJJ7JxvFGaM6RjH4uW73/1utClkfcdBx4+IF+ovynqijPCcwxiAH15ofijQpaWl9UupcQye6+9///uRoh8reOHZnkhYq50xfWzI+he+8IXoUMpy6aWXRmMPvPu0bfHXxvvPtePnvTOmwtOOc2HTpk3RuIU56bRH8ccmKlc2bpOCno1vLUGZg4VsyZIldvvtt0cfP0KGyOayLFJBysvLo4883pIXbsW+EO6WaDBP1kcqZGwYLY3Eww8/3CB8Pay7iAefyhqrNHAPGhT+SwWMVdypnDRQwQOI1YzrJ5qPkgCPNolAuxOgfpx77rmRZ+nWW2+NQq8QvmeMZPEh5vEFooOkHqJMJ5vyQQfK9RJ999RjysC0kdjzsTTHdoJ0aHSMWM2py5Q3NkSVNgMjGteJrevcl31s4/r8m3q4evVqGdniX6b+FoE0CDAIRzlfuHBh5GFiLikSpqc0danQf3MM/WYiCf03+xPN12TATf/K8kpB6JsfeuihBm0JU9OQZP037Qb9Nm2d+u9Eb0LbROBjAk3NuY5lxNiXXyKhD04kHJ+qV5kxBb9EQpuQyDAQxgKJzklkEIjfhr4Qnyk+XCvZPcN+2rtUM9onKl82bUv81rPpCVTWiMBee+0VdaT33HNPvXLOdhTaoNQmQrXvvvtG1rmgxNOBE4r75JNP1oe/nnnmmVGYDIMFBvIoEKyxSIZIQnkZXBBag2AZQyF44oknImWBEHes8HfddZdxHUL4kM985jPRfwl9J0RuwoQJdsopp9Q3FCggeNiDknPwwQdHYTo/+tGP7LOf/awNHjzYmLvDMRIRyAQCeMlRsp999tn675ZyMVBds2ZN0iKi5J599tnRN40wMMbQhocqGMwYvFMHQseExRsvFsun0Emfc8450bQWOn0G4Nzvj3/8Y9QWfO5zn4vyPVx//fWRdf3EE0+M7sPcs29/+9vR/PNbbrkl6jCZ90ZdRCg392C5Fuo9z3bttddGa6vSodN2sP0HP/hBdLxEBEQgfQIMdum/MXzRrwblnCvx79i/469+4IEHRu1CWOOY9oKImWeeeSY6lMEsbQt1nXaCMQL9N/0uBjjaLPp/+mqEiB/6Vc4nxP1LX/pSfYg7xke8W8hZZ50V/Zc2hj6accBJJ51UP+hG0Sd8FoMDwhiBaICf/exnkRET5eHll1+O2hKJCIiACIhAYwJS0BszybotDKzxvDGoj7WAp/IgoUMnuyIDBUJI6PTxrrGNZAwo1cyXJUx+yJAhkSJBchg6f8J0OA+PIVa70R7OS6KJRILijnWMzvyFF16IwvCXLVsWeeFQuik7c9243mGHHRYp9D/96U+j8BuE7V/84hfrE2x1RthfoufSNhGAAANa5K233koLCN4mjF3UMQbNhJ0xmGUwzdxwlO6jjz46Mn794Q9/iAbjsfWM+WR4tp566qmo7qGM0yaEKJrYwqC4M4eLwTRLnMydOzcalCMYzQhhffHFF6OBNXPWKAflI29FELLC4nFjYE6bIxEBEWg5AaLGMJDT31LH0xH6b6aLUV/pW+m/Ubj5m7qJ4k+YKvWX/nLYsGGRMs559Ne0KxgGULTxcjXVf6O40+djwMMISZtFG4KyjcLONVG4aa8oA9t+8pOf1LdD3C+Euv7lL3+xefPmpfOoOlYEREAEuhQBKeg58LrxnCHpKuecwyA7eKn5G0UfDxuKOAMGBg9B4rO/0xGjCGDhx/OOZR7vezLheljyERSJMLeN+zG4IAHEm2++Ge3nuszPweMXm0wL7+INN9zQICQ32f20XQQ6kgBJnEJ4Zzr3xQtN5EsQBr177rlnfVQKA2e819QzBsH8YhMrUmcRFHoMa8FrlagMGNZCiCuKeaivDLJRzhnUE/2CUEevueaayMsWq6ATIv/73/++yfskure2iYAINCYQEkK1pP/GaB6bXwZjN0Zz+m/qcmgbaGMwhhOaHgSFmX6WaDX6b9qGphK+oeCH6BqS1IV2BiUfxR3DX2hPaCNQ0skcjQEhCEbDX/3qV+q/G38G2iICIiACDQhIQc+BDyLME011TkvsI9ORMjAfNWpUlCU2hLqHOS90rgzQCWfFk/7KK68Y1u+QWIowNULsLr/88shCT8htMg96MtQhvA7PfVizMcxZYU5brKCYxM6XTXZNbReBjiaA4kuUB/WwqWkl8eUKkScYrxisUwcxWIU6iFeNUHPq4Fe/+tVoQE49C2Hz1Ek86AzMSQpJncTblU49oe4jhNB/5StfaVDEWCMdOxjMh6yv8c+iv0VABNIj0Jr+m7rJ9DP6b4xs8f037QBGblaOmDlzZtR3015wTwx+/E0EDlPRMJjTrhDZlo6E/huFnGloSOi/MRjECuH36bRL6ZRDx4qACIhALhGQgp4Db5OwWCTdxAkMyi+++OLoXAb9LMuAQhyUZLZjXcdjjXLAduaSzZ4922666aYo9Jy5aljN8XZjLefHEgqxHrfoBk1IUESwyscrNlj9YwUrv0QEMpEAHjAGpNSrdJZBYvkQFGy8Wyi+1GdC0GOF+egMbqlnGMoYdD/wwAORdwqPO6GkGMoISyciBQ/8b3/725SzswfjHuHssWHrzE+PT1gXn8AxE9+FyiQC2UKgpf034eqf//zno/qJco0yTi4YpqUEoa4y75u+e7/99otC2gl7v/HGG6PQc6Jl8JrTrjD1jB+JXTEIpiqh/6bdiE0qyfnx7SBRdhIREAEREIHmCUhBb55Rxh+BYoDiigWdELTYkPWmCs9cVyzdhJaHpDJ04PGCxRuvHKHmJ598cjT451y2ISEhFQOGiy66KBoIpKOgM0AhTJ/rpDMwiC+n/haBziRAyCdecDxSGJZSWT6QCBaUcwbShI1T1zCSUS/jk0MxxeR3v/tdNE+UxG8MukP4KANjQkyZU07COLxqXDfVeZ5h4Eyoaghx70yWurcIdBUC9H8Yxug/qduxYehNMSCyDcMa/Tf1HmGp1XhBgWc//TV5Jui7MfC99tpr0aEY+Gh7WCKS/pt2JZ1+mCk35KXhOmFt4vgy6G8REAEREIH0CDRc3C69c3V0hhBAESBBFELGVsLMCHmjw8VaTqK3RBIs9ygJZHjFek4YXKyQPZqwWZQGBgPBQk6nT6IoktKgCGBFD6Fr8R63RPeO3cZAgWdAsUH5JwkWnki89txDIgLZQIABMMYykjKR9JD6ROI4/ptsvVO8WLt27YrqFvNF8YAde+yxUah8EOoCa39Sp0M9o76EeoZBjHob1jANc8zTqYco/4S2Ul6MdETjMD+VrM08j0QERKB9CNBvBgM50TSEo9N3U9/pe1GoE0l8/01kTfyxRLsxBiAUPr7/pr0hIg6jQGy7kmgZtkT3D9uCMk8ED+0QYwnaDxT9kF2+qfO1TwREoGkCRJYS6RLyNjV9dPvujY+SCXejjDgEiMQlEjBRktr2LVnuXV0e9Bx5p4Sok2gKCzqdbqygACfKLE2FZ94YSjE/BvR4z2K96AwU6OSDoBjgKcRzh/LMYIKOOQjzZdP1wKEcPPLII9F9Tz311OiHMHBRpvbYN6l/ZzIBBrZ4uPFShekeobzkbGDpwnjhHDo0jFNXXXVVtJsIGL77MC+cQS5GN+pqEKaehOuhRIf1idlPPSYcnvD0VIV6TftxxhlnRKs48AuC9y0TBgapPouOE4FsI0ByVPJOYJyLN+Zh+ItNChmejTpO30tIOz/aEtoErhEE5TvWQE+fSvvCuRj+wvKl4XimrSVqp5riyWCc7O2MO8LyqRwf2qGmztU+ERABi5RZpoMQPUMdxThHRE3I/0K9vPnmm6McE9ddd12nIaOdYsWm448/PlppKQgRvL/85S8bJKpmOUX0CknLCXTzgVldy0/PzDOx5DCAba0wlzrVcPHW3qutzsdKTrgZnjgq9erVq+uXKaNy4yEjnDZY3/HUoYTjRUdRZh+NA+cSusZ+9tFYICjnsaG34X4kiiE5HKGy4ZNiX7hWSGiFZR1vPOFw8RY2PHaEunM/FP1YKxyDCX54+dJdiqat2Lb0OoQrf/nLX27p6a06jyRAhFujxMVHR7Tqwh10Mt8US+9lk1Bn+M6ph4SM8+1TL0KECYNmjolNtMY3T1g6dY6Omo4ZD1cId+UbIjMzdYD3GZuLgWtRp6ij1E3OibVyk3gOJR+FnboZktJRj+ITQlFejme6DNeg3BzDeezDEEC9pf5mm6C4kBAzFwRl7N57740eheSAIVt3LjxbWz0DRt9sS2ZIPQ/9N9E4tB1hmVH6R9qAsJIDnKj7TKuhb6f/JlSe9oX/8mM/3wZtAwozPGLzvNBHc03aK86nXQn9N55w+mPGUiyphtDP0zbRLhP5EysY7Dme/4b+OxzTVL/fVu+7va4D27A8XHvdQ9ftmgSoa7TjjNMSCQ43FGHq5Q9/+MNOV9CZ5nr33XdHxrjjjjuuvsi33357lAODtghHAvWeaTSsPpNtQjsbkm12dtnlQe/sN9DG92dQzQA+Prkat2FgzVJnsUIDEb+Wcezf7GegkGwJmKbux774+2EYCMaB+EenU0/mqYsdlMSfp79FIJMIUGfoUJMlNAxKd2yZGQTHLkeEoYxfEDzw1Mv4usp+7tdU/WDgHSsod/H1MuzHiICBID65E/vZl+y8BjfQHyIgAi0iQD1PVv/oH+PrH3U/flnF2PaF/UFZT1Qg+uhk90ORj79fU+0ayzbGLvkWe7+m+v1E5dI2EegKBDAiopxjDMMrjXENwTDHeCDTnCpMO2XKGw6FWAljDKa84gyStA0BKehtw1FXEQEREAEREAEREAEREAEREIEmCeBxJsEjUTNf+9rXoqjXIES6phoejuEuRM8QEUP0G1FwiQRDGQY5Iuq4R3zkVXAu4OALEbexyjiOAK5BpF6YghdrAOTfRB1zTthPOXA2EHVHWYnCIWo3rP7AfpwGRPcQnQMHPPBE/GEkJIdGVxUp6F31zeu5RUAEREAEREAEREAEREAEOpRAiDYhhD1WOU+nEKyWdP/99zdaMYZkkRdccEE0LQ1B+f3Tn/4URdPECkr017/+9eg4FGtC1eOnB6NMX3HFFdF0GfJWPfjgg1HuqVNOOSXy/pO7Jshdd90V/ZPcFqz4RNQdRojHHnusQRmZcnP++edHyjqCQv7rX/86WiYWLz3z2YnuYb8U9Hq8+ocIiIAIiIAIiIAIiIAIiIAIiEB7EAhTUZir3VIhJJ6VHlhykfw05JxCYSepJAndghceJRrlnHwlKO/8m/uz8ktQ4u+4445IOT/xxBOjJLd4y1HsMR6gnCcSlnW+9NJLowR2eNVZRYp8OMHrzrKLjz76aOTVJ/yda7HqA4kvb7vtNrv88svr78/1SY6LEYCEmawCQX6MrizyoHflt69nFwEREAEREAEREAEREAER6BAC5HQKnur4MPN0CkCY+llnnVV/Coow4e7PPvtslMgxKOjktkBQ6ElCyS92+VQ83SGxLInewjHNGQ9I/sgvhKuTJDKEthMuj3KOoPSz3CxCmTEgEGpPKD2JpIPAhXuy3CSh/11dtA56V/8C9PwiIAIiIAIiIAIiIAIiIALtTiB2JQW8xa0VvNckdGTJVpI1IrGrJOFlR2688cYoJJ3VWWIFL3o45he/+EXkhU+WzLnBiU38weoTKNx43ykLHn1+LPGIUo8kSqS73377STn/hKs86E18YNolAiIgAiIgAiIgAiIgAiIgAm1BIKxvzrXwpJO0rSXy/PPP21tvvRV5ovFYJ1sejGXRCDvHo828cX6zZ8+OMscHDz7LphGe/uc//9lefPFFY347c8LZztKJ6UqY7065mNueSOKXWuaYXFkKNdHzprtNCnq6xHS8CIiACIiACIiACIiACIiACKRJgPBtFGaUc5ZOJTQ9XcFb/tBDD0Xh5RdeeGGUGZ1rxidu47p46Um+xlz1V155JUrcxvmEwV999dXRfq5z4IEH2qxZs6JroPxzLNnXr7zyyqTz0JOVO6yBzrVJRJcoZD2RYSI2u3uya3eV7Qpx7ypvWs8pAiIgAiIgAiIgAiIgAiLQqQRQmJGnnnoqWk4sXSGkHSGZGonfQmI2Eq0lEzzsZI3/xje+EXnbWW997dq1DQ4vLi6OErqhVLNsG3PaSRiXruCNJ3S+pqYmCqknaiD+l0hBT/c+uXy8FPRcfrt6NhEQAREQAREQAREQAREQgYwhwFJlKMkovz/5yU9s3rx5kUedJcdQnF977bVGy6LFFp5kawhrjKMEs5b4e++9FyVgi5cXXnghSsrGMUg4nn8XFhZG2+fOnRsp4+wLxxCeHo6J/pGG4Ak//PDDozOefPLJ6PnCtQltx4MvaZqAQtyb5qO9IiACIiACIiACIiACIiACItAmBAgBZ4ky1idnebSbbrqp0XWvuuqqyOucSAhXf+CBByKF/Prrr48OIVs7S6k9/vjjDU5h7XIEjzjXC0nimGPO8mycx7WQEH4fErixpnlL5qBzLbz1zI/Hq8/z8cwhaRz7mQcvSU5ACnpyNlHISP/+/Zs4QrsgENZRZKkGSWMCiebeND5KWxIRoENRHUxERvUuMZXkW/EUSLoOAfXfyd+1+uzkbOL3hLm08dv1twi0lgDrfDO/m0RvKOn8UIZZ5ox56awbjtB3HXDAAQ3mcZPc7dprr43WDV+4cGE0Tpo5c2Y0Fx2FO3Ze+yWXXBJdm/nkhNMz15zl1MKSaIyzvvzlL9uqVauiY/CoH3LIIdGybOEYykG5KEfs0mhsJwM894yvK5T74osvjjK3L1iwIAqnJ6wdo0BYdo3zuT/XlTQk0M1DGD6OYcghMnyAYY3BHHqsjHwUKiVLMiBkeywtLc3IcnbVQpHsAwvmxIkTo8ZbkhsECGsjbAw544wz6o1kufF0eormCDCAuvfee6PD8Ji0Zi3d5u6l/blFgLERmZqR0047LRocS0RABERABMyYg58sG35H89Ec9I4mrvuJgAiIgAiIgAiIgAiIgAiIgAiIQAICUtATQNEmERABERABERABERABERABERABEehoAlLQO5q47icCIiACIiACIiACIiACIiACIiACCQhIQU8ARZtEQAREQAREQAREQAREQAREQAREoKMJSEHvaOK6nwiIgAiIgAiIgAiIgAiIgAiIgAgkICAFPQEUbRIBERABERABERABERABERABERCBjiYgBb2jiet+IiACIiACIiACIiACIiACIiACIpCAgBT0BFC0SQREQAREQAREQAREQAREQAREQAQ6moAU9I4mrvuJgAiIgAiIgAiIgAiIgAiIgAiIQAIC+Qm2Zf2mgoICKysry/rnyIYHqKysrC9mSUmJuGfYS8vP/7iK9+jRQ+8mw95Na4oTW+9o67p3l621NTyz7dzq6mq1u9n20jKkvLW1tfUloe1gvCQRAREQAREwC2PmTGCRkwo6g9XCwsJM4NulyoASKO6Z9crz8vKiAvFfvZvMejetKQ11LQjvVQp6a2hm37mx71vtbva9v84scWzbwb9j/+7McuneIiACIiACnxKQ20VfgwiIgAiIgAiIgAiIgAiIgAiIgAhkAAEp6BnwElQEERABERABERABERABERABERABEZCCrm9ABERABERABERABERABERABERABDKAgBT0DHgJKoIIiIAIiIAIiIAIiIAIiIAIiIAISEHXNyACIiACIiACIiACIiACIiACIiACGUBACnoGvAQVQQREQAREQAREQAREQAREQAREQASkoOsbEAEREAEREAEREAEREAEREAEREIEMICAFPQNegoogAiIgAiIgAiIgAiIgAiIgAiIgAlLQ9Q2IgAiIgAiIgAiIgAiIgAiIgAiIQAYQkIKeAS9BRRABERABERABERABERABERABERABKej6BkRABERABERABERABERABERABEQgAwhIQc+Al6AiiIAIiIAIiIAIiIAIiIAIiIAIiIAUdH0DIiACIiACIiACIiACIiACIiACIpABBKSgZ8BLUBFEQAREQAREQAREQAREQAREQAREQAq6vgEREAEREAEREAEREAEREAEREAERyAACUtAz4CWoCCIgAiIgAiIgAiIgAiIgAiIgAiIgBV3fgAiIgAiIgAiIgAiIgAiIgAiIgAhkAAEp6BnwElQEERABERABERABERABERABERABEZCCrm9ABERABERABERABERABERABERABDKAgBT0DHgJKoIIiIAIiIAIiIAIiIAIiIAIiIAISEHXNyACIiACIiACIiACIiACIiACIiACGUAgPwPKoCJkOIGdO3fa/fffb1VVVY1KWltba5s3b46233333VZQUNDomO7du9vJJ59s5eXljfZpgwiIQGICGzZssEceecTq6uoaHVBZWVlf72655Rbr1q1bo2MKCwvt1FNPtaKiokb7tEEERCB3CdAnP/TQQ0b/HC/046HPvvXWW43+OV7ox2k7evXqFb9Lf4uACIiACHQAASnoHQA5229BJz1z5ky74447mnyUZcuWJdx/0kknSTlPSEYbRSA5gX79+tm4cePs8ccfT36Q71m0aFGj/Sjs559/vpTzRmS0QQRyn0Dv3r1t0qRJ9vDDDzf5sIsXL260n7bjnHPOkXLeiIw2iIAIiEDHEWhsOu24e+tOWURgypQpduSRR6Zd4v3228/23nvvtM/TCSIgAmb777+/zZ49O20Uxx9/vI0fPz7t83SCCIhAbhDYZ599bN999037YY466ijbY4890j5PJ4iACIiACLQdASnobccy56900EEHRZ70VGXixIl2zDHHpHq4jhMBEYgjgDfrxBNPtDFjxqTMZs6cOcZPIgIi0LUJHHvssWkZ6vbcc0874IADujY0Pb0IiIAIZAABKegZ8BKypQgoC8wlHzVqVLNFHjRokJ1xxhkJ57c1e7IOEAERqCeQl5dnZ599thHy3pzgNT/uuOOaO0z7RUAEugAB5pefeeaZNnDgwGafdvTo0cZ0tET5LJo9WQeIgAiIgAi0KQEp6G2KM/cvlp+fH81P69OnT9KHLSkpsXPPPddIUiURARFoPYGePXvaeeedZ/w3mQwYMCAajCdK+pTsHG0XARHIbQIkiaTtKC4uTvqgffv2jYyAGAMlIiACIiACnU9ACnrnv4OsKwFJ4+jwE2WHRoH/7Gc/aySpkYiACLQdATzoDKITKeBN1cm2K4GuJAIikI0E6I/pl+mf4yUo8MrYHk9Gf4uACIhA5xGQgt557LP6znjrzjrrrEbKwmmnnWbDhw/P6mdT4UUgUwkwF50w1FjB68Xgu6molkx9HpVLBESgYwiMGDEiWjotVjD2ERHXv3//jimE7iICIiACIpASASnoKWHSQYkIsATUCSecUL/r8MMPt2nTpiU6VNtEQATaiABZ3Q888MD6qzHoHjlyZBtdXZcRARHIVQLTp0+3Qw89tP7xMPalk4AyV7nouURABEQg0wg025YF6AAAIABJREFUjnfKtBKqPBlNgCXU1q9fbzt27LBDDjkko8uqwolArhBgycMNGzZEyZ9mzJiRK4+l5xABEWhnAocddljUdpSVlbVoCcd2Lp4uLwIiIAIi4ARyWkHfVLnJ1las0YtuZwKj9x9ltTW19uG2ee18p651+UFFg6x3j+TJ+Dqaxu7a3bZkx2Krq6vr6FvrfgkIzDhmuid16m7ztn6QYK82xRMozi+2Yb2GWzf/nyQ3CNC/089L0iMw5YjJ1l1tR3rQ2uHo4b1GGO2SRAREQATiCeSsgr69epv9+7vXW01dTfwz628RyAoC+d3y7Z+mfz9jOvBfz/+5Ldq+MCvYqZAikIjABWMusj377JVol7ZlGYHlO5fZ/37wn1lWahVXBD4lUFZQZt+bdr1176bZpvouREAEGhLIWQUdq3pQzgu7+3Jfcpro288WAu6gxltdXVft3qGNGaOgr9+9LiKY373A8jSgyJavSeV0ApU1lVbn/1tX8fE3LCjZT2DdJ+0RT1KYpyU9s/+Ndp0nIAqtsrbStlZt9f/utqK85Mtndh0qelIREIFYAjmroMc+5L/O/A9ZKPXdZw0BDEvXvv71jC3vhaMvsmm9Ne85Y1+QCtaIwK/m36CpAI2o5MaGPj362v+bdl1uPIyeoksQWONTM3743g+6xLPqIUVABFpGQHE1LeOms0RABERABERABERABERABERABESgTQlIQW9TnLqYCIiACIiACIiACIiACIiACIiACLSMgBT0lnHTWSIgAiIgAiIgAiIgAiIgAiIgAiLQpgSkoLcpTl1MBERABERABERABERABERABERABFpGQAp6y7jpLBEQAREQAREQAREQAREQAREQARFoUwJS0NsUpy4mAiIgAiIgAiIgAiIgAiIgAiIgAi0jIAW9Zdx0lgiIgAiIgAiIgAiIgAiIgAiIgAi0KQEp6G2KUxcTAREQAREQAREQAREQAREQAREQgZYRkILeMm46SwREQAREQAREQAREQAREQAREQATalIAU9DbF2fqLLd2xxOr8fxIREIHWE6AuUackIiACIpBpBNQ2ZdobUXlEQAREIDMISEHPjPcQleLFdS/Yj+b9t/151aNS0jPovago2UkA5fyRlQ9Fderl9S9m50Oo1CIgAjlJ4Jk1T0Zt09Orn8jJ59NDiYAIiIAItJyAFPSWs2vTM1HO71l2Z3TNJ1Y9Zs+seapNr6+LiUBXIhCU8zD4vWvp7fb3ja91JQR6VhEQgQwlgHL+0IoHotI9vPJBm7vu+QwtqYolAiIgAiLQGQSkoHcG9bh7xirn7CrJL7Ep5VMzoGQqgghkH4F45Zwn6FfY38aVjs++h1GJRUAEcooAxvegnPNgZQXlNqlsj5x6Rj2MCIiACIhA6whIQW8dv1afnUg5v2zilTa4aEirr60LiEBXI4By/qiHtceGjaKcXzHxa1Ze0Lur4dDzioAIZBCBj5Xz++tLhHJ+uff3AwoHZlApVRQREAEREIHOJiAFvRPfgJTzToSvW+ccgaCcPxUzp1PKec69Zj2QCGQlgcbKeZmU86x8kyq0CIiACLQ/ASno7c844R0SKucT5DlPCEsbRaAZAsmU88u9Tslz3gw87RYBEWhXAs+uedrD2mM95yjnX5PnvF2p6+IiIAIikL0EpKB3wrtLqpz3VFh7J7wO3TLLCXysnD9s8Z5zlPPePfpk+dOp+CIgAtlMAOX8wRX31T9CWYGU82x+nyq7CIiACHQEASnoHUE55h4vrZtbn62dzSSEuwzPuZTzDn4Tul0uEPhUOX+8/nH6FfYzKee58Hb1DCKQ3QSknGf3+1PpRUAERKCzCEhB70DyKOd3L7uj/o7F+cVSzjuQv26VWwSSK+dfk+c8t161nkYEso5AIuX8sgkKa8+6F6kCi4AIiEAnEJCC3kHQEynnl3tnLc95B70A3SanCEg5z6nXqYcRgZwikEw5H1ikbO059aL1MCIgAiLQTgSkoLcT2NjLvrS+sec8t5TzOtu5e6NV1VS0I03uscGqa3a34z0+vnRtXY1tr1hndXW17X4v3SB9Aijnj61kznl8WHv2e86r68xWVNdYe355VXV1trKd7xHe6pbKOltX4Q8lEYEuQuC5tc80mnOO5zzblPMaf1+0Rfy33aTG27oVK838v+0tO71xXb2T3kMiAiIgAplPID/zi5jdJYyU86W5F9a+u2qbvb/iUVu/7SP/zbddlZutm/+vvHiE9S8dZ0P7zLSxAw+xbt26tfgFcs0PVnKPBdE9Kiq3RPfoXTzS7zHehvWdZWMGHujXb/k9QuG4/oI1z0X32bh9UWQIyM8rtL4lY2xA6QQbO+iQ6J6SziUQlPMn45RzBsDZmhDurxWV9sjOXfZ2ZZW9X1ltla5AF3fvZtN6FNgM/51Z0svGF7SuqX5h1257fFeFvb27yj6oqjaU9NJP7jG9Rw87p6SnjW7lPfgyqt2ycMtHlfbimhp7fX2NLdj6salhWHF327Nfd9tnYL59aVKBFRe0vs527peou4tAYwIo5w8sv7d+R6knhMsm5fw9b4Pu3eFtkbcT7/q/d3o7UeR9+BRvh6b77+TinrZnYUHjB09jS/Vbb9nu+x+06nfetur33re6igrr1rOn5U+dYvnTplnhqaf6f6emccXEh6KI372wyp5eWW2vb6ixeZtrrdY3DuzZzduiPNuzf559aY8e1r9IbVFigtoqAiLQmQRaN+rrzJK3071r3Hu6YPt8m1g6qdV3SKacD+k5tNXX7swLLF3/ir304c8jpTxWUJ4271ga/eavfsY+Wv20HTTpq1ZSNCDt4i5a+6K9/NEvDUNA/D027Vhi/D5a/ZTNX/OsHTjxMuvlicFaIjW1VfbG4tvs7aX3eukb2tZR0tdu+SD6vbfiYZs+8nSbNepsy+veugFKS8qZzedUeGTFql0rbUzJ2FY9RlPKeZ8szNbO4PffN221W7ftbMRlh48kUdz53ez7/6F3qX2xrNjyGh3Z9IZtfp1/9Xvctb3xPdj3sl+f3++37bBr+5TahaXF1tKwqg98AHzZ3F2RYh4vK3bUGr+Hllbbbz6otBsO6mkHDk73aeKvqr9FoHUEqrz9X7JjkY0vndi6C/nZiZRzIuWywXOOwe5nW7bbDf6Lr70Vvu/vuyuj3y3eTlzs7dDXvT0qTNP4Xrd7t+380Y9t102/MattGCNUt2uXVb32t+i365Y/WK9LL7VeX73crKBlfS1tzZUvVkTKebys3VVnf15eHf1u9Lbof/cvspNHtew+8dfW3yIgAiLQVgRaOhZrq/tn1HVQzm9e+Bv71Uc32KsbXmlV2V5e/2JCz3k2K+d13lHP/eAn9tQ7/95IOU8Ea9Wmt+y+V6+yJev+kmh3wm2Elz/73n/7778aKeeJTlj+/9k7D8A4iquPv2vSqXf3bsu9YgMGDAkl9GZC6IQWek2AjxZ6NRCq6STUJBBq6JBQQrEBY9wb7r1JVq93J33vrXSyfNq+K+uk+7989xntTv3t3ez8Z97MFM+mdziP9fyvVauo3Urvz76G5q97u404j01L3N3nr32Tw1+ruL/DzBEQcf7siifp6eXTaVn5EnORVEKJOP9000fUeuY8NylPmZ3qjOJ8Kc9OHblpu6o4j62+zKjfxyL75C3FVBLTsY0N2/rvhZzHEZu3q4rz2HjSCb9jRzmdsbWYyi3kEU3nhWX1dMB7lariPDavtZUNdNQnVXTrT+25JCY2V/wNArsSEHH+wqrn6Blun+aWzHGE52uVmfPOIs43sxv7Cdy2PK4izmOhiKx+rryKjt1cROs4nlmLrF9PpcefQDXPPd9GnLdJg93dq598kkpP+C01bGL3d4v28fowTX63SlWcxyZVxMtvzvyyhi78poYi8H2PxYO/QQAEOpAABHor+K+v/QctKlugiLXX1/7dtkgXcf7mutdbUo7u1t6ZxblUZvHG95VZcSsWitTQ10sfJRHDZkxmsldv+9ZM0JYw9eEq+nrJw8oadbMmgw3fLHmMZ+LXmY2ihJOZ+2+4PhIfpk9AfkfSAV5btYbCjTxzuvI5WyI9Ks7/s+XTlgxFnF8ytHOK8zr+7lxZVErrLXRwpeJzeAbr1uIyfejNd2V2/vLtJSSdbysmM/Yy427F5rL76DXf11K9xYXzjy6sp3fWhKxkhbAg4BqBf6x5hdujpez23EB/X/OSbZEu4vzfMW7tcsxjZ5g5l7fYddymiGu7FVvBy2T+xG2YqdaFBXflNddSZMUKK1lQeOkyqrj+BmNB3yrVDTxzfv7XNVQRsvZ+fn1liKYvqrdUPgQGARAAgfYkAIHeiu7+3X5FKb4U5Ypdkd5VxXlZ9UaavepVW9/FMM+ifrt0uqGo3VG5RnE3t2Mi0r9jt3t5cmZs8cYPaGvZYjNB24TZUrqI18Z/1OY6LuxKQPYLOLD7IeT3NK2ksSPSu5o4F0KPllaSdHDt2IfVtSQfI3ugpMLSDFfr9N6qrKEveM26GavjHvpFDmafrp5ZS+JyCgOB3U3gV90PpGRvspJtVKTPsziTri3Ou+/u6tjK75+8fOa7WnO/9dgMZMDwbzybbmQ1L75EoZ/teSiEZn5Ptf801yeQVuQydmuvtCjOo+W/++dakmU6MBAAARCIBwIQ6K2eQt/UfnRh4aVtRPpPO8y5u39fNKNLzpwLohm/PE2yXtuubSldyOvS9WffZ/zyJHeUTI3JqxZD3N1l7bqRVfFM++xVrxgF070/a+XLys71MH0CwzNH0DmDz1cR6Uv1I/JdRZxv/pi6ysy5VHgZC/PnyisN664X4Bae8ZIZci2bxxs8yZpyJ3ZjcSnJTL+RPbawzlGndkddI/15lvGAg1E5cB8ErBIYkDaQLii8ZBeR/irPpJsV6Z1dnBdFGpQ9MJzYQ6UVtEHHS0dc1KsfethJFlQ17X5q2F5kmIbMgn+lsubcMGJzAPEAumpGjdngCAcCIAAC7UoAAj0Gr5pIf23N38lIpIs4f2PdzpHeruLWLnhkBnwrzxo7tQ07ftZMoi5USdvLl2veN3tj4w7jkXqpi5PBBilLpKHe9gy82bp0lXDqIv1Zxb1Uy1rE+eZPWoI0ubVf3inXnEcr8S3PTDudoynlNeKyy7KWfWtzRqx1etu58y6DCUb2+UbjMEZp/JfTMB4KMEoF90HAOgER6ecPudiySP9621cxbu0Z1OTW3jlmzoXUbJ4B1xvoM0NT9sf4kZfFaFnox1nUWK99Xyte6+vKBnKzjfeYcaMt+n5bxLJ7vJk6IAwIgAAIWCUAga5CLCrSg63c3fVEelcW54JHXM9FMDm1Yj4uTcuKK7XvacVRuy7HpBmZHNvmhrmVjhtlifc0rIh0fXGeG+9V1S2fHKXmhumlM9+tPHQGAaQOcqTavB1Ohxu4feFZ9PW8cRwMBDqCgJwuYUWkN4nzt1uKmhEQcS67tXcecS6F12tDrDwHvXTCCxZaSUozbHjBAs170Rtqp0cYRlIJMI/31ICBAAiAQEcTgEDXeAIi0i9id/dYkT57x6xdYnR1cS6VdUuIykZxMlOuZmaEtVq82GulVeuVGX89c2swQG/AQS//RL0XFek+T9PxWsqadN5ErvVMuojzz8StfZeZ81zeEE5mzju3OJfnLjuru2F6neKFBsLabP5GZV1e1kA1YecDd1IetzrXZuuGcCDQmoCWSJ9fOncXUN8oM+edX5xLpYx+32a/IXptUXiRSwJ9ob4Hn2wKt6LcnUG+ucXupGOWH8KBAAiAgBoBCHQ1Ks3X1ET6P9e8SlGRribOLyq8jDr7bu2xSGpCu553Hnvfyt+1IfVdqGvr1a9bSVvCisCLPTs9No3Y89tj75v9200uZvPs7OFEpJ/La9JbRDrvaxAV6VFx/lkbcS67tXd+cS7Proh3NHbDtNKRruUOG8ekqZVJK49o2O217nVkt/FxRzBrBPx+P8kH5g6BqEhP8iYpCcrGca+sfpGiIl3E+bsx4lyOeexsM+dRWrIG3Q3TaycaisyfrKJXlsZi/TXoclyaW7atxh0ubpUH6YAACCQmAQh0g+euJdJf42PYYtecizjvldLbIMXOdzsvfaArhfb7kikzpadqWrku5ZHM7oZpwXzVPKIX3crLLS66he2CN4dnjlQV6TL41ZXFuTzKkUkBV57oaI10pEEfkeSOaDMq65jcJk8INyo0Ls+9tNwoT7ynEQgE6IILLlA+ubldY/AqHpiLSL9gyCUUK9JfW/uqqjjv3snc2lszHulSOzFKoy2SvPwjR7jyWH0jR+qm0z/dSxkBj24YszfHutiumc0T4UAABEAglgAEeiwRlb/VRPqs4h9aQsqGcF1VnEsl8zOGqFCxfimPOz8ej/pXLj9jsPUEVWI0paP/onatPi5xUalGl7+kJtJbLx/J5RnzpnPOu5b4GKvTmbXy0LUEuqQxxqU8xiTrDybkJHtIOsZOzcs/1zE5ztNxWg7EBwEhoCbSZxXvPMlF1pzLzHlnFudSzzFJTZ4CTp+6XnvjHzPGafJKfP/o0brpSBsy3qVBvgn5GCzUhY2bIAACu4UAekUmMSsbx/HIenRNejRaqj+1S4tzqWd6sIBkZtqp5emI8KzUPuT3BZ1mQXkmRLNbAt2tQQXHle6kCYhIP2fQTnf3aDVEnF88tOu4tbd+PHqdWSuPUS8dvXtu5RFNZw8XOrPDs72U4tcfVLNSboQFAacEYt3do+k1ifPLO704l/q41U6M1hnIMxLWZp+TmXQm5DvvzmYmeWhghvN0zNYL4UAABEBAiwBaIi0yKtf7pfXfRaSLOL+48PIu6da+a/U9NK7/iSpEzF8S8T2yz9GaEWRmfWy/32reN3MjiT0ZRvQ63DBo96yRJB8n1iN7FHXj9dQwZwRG8HNoLdKj4lz+7Yp2SGqQhgScuaAfxWkM0EnjyLQU6ud3Ngv02/QU6u4zTuPKMUm8n4CzJ3XtuGRnCSA2CLQDgUHpg5Xd3aPu7jvFeY92yG33JzmOhfV+QWe/vQmcxj46aQT22pMCe0xwVLnAPpMpMH6cYRoXjEiidIdu7lePTSaZjYeBAAiAQEcTgEC3+AREpF8z4jr6bd+T+N/rE0CcNwEa2ftoFrX2Bemeg8+mDIP1emP6TeUZcPuu7pML/0CpyXmGT9Tj8dD+wy/nGXt7nRMZbJgy7HJ218eb3BC2iQAi0v804v/oxH4n01XDr6WuKs4FRTJ/Zx7MzyZj6asOLs/npdvzstRvNl9N5Twe4DzsfjtFmP85J1M3j+hNcSuVTq1dO35AgKbyBwYC8UhARLq85+V9/6fh1/HMedcQ58Ja2of7uC1Js6lIpS27P8+gLeO2JH3aNPIE7XnHeVJTKf3ee4i8xl3VPmleuncve/kIjz0LfHTZKHfc/uPxu4wygQAIdC4Cxq1e56rPbimt7Ci9b8EUygpk75b84iETmeGeooha6y/AXjnjaHivQw2r4eXjtw4YfgX5vNY77P3y96LB3X9lmEc0QEZKD9pz0Fmmw7cOqAw2pHSuM29tVXQ3RuoR7En75O9Hsp9DVzdxLb04K91WNe/MzaIcE53VSclJdF6mPZbSac80kUe0AtfwDPhoGxsrFQR5sGKy9fbEFjhEAgGbBPKS85X3fWbA3KCVzWw6JFov9rS52eRgXGwBr83OoEE6njzR8L4B/Sn12mtio5v6O+3GG8jX2/zGu2cUBujQPtY9lII8YvrklBTH3kCmKoVAIAACIGCCAAS6CUgI0kRAdmA/duKDVJA51CQSD43uexwdMuZGDm9uPi87rR8dM/EBkg3lzJiH0xXX+F+PlA6AuTyi6Q7vfYQSz+z6+iB30A4cdS0PNhxmpmgIAwKaBK7izu1dLLZlttuM9eCZqBe75dJh7N5u1q7jjvctuZkUNJlHX+6s/6N7Hh2QYm1GPInfIh8enkqnDTE/sHZQLz99dUwa5bNIh4EACHQcgd+lp9JTBTmUy945ZiyLB+8eZg+dsy0MAKaceQZlPPwQebL0vX+i+Xv5ZIKM6Y9R8OSTzBSpJYy0Ji8fmEpXjk4y7aoum8J9dUw6FWaZq7+lAiEwCIAACNgkgBbJJrhEjZaV2puOnHAPTRx0Js90a7uDZab24nB3k8w264VT45jDywiOnng/jR9wsu5senZaXzpqj/u4LGfohlPLI3ptYLf9aOqej1G//L31glH//Ml0/J6P0oCCfXXD4SYImCEgHclTM1Lpo14FvIZT+3ckDbSsB/+4Vz7tb1E4S9yzMtLog575JDPqWibhpCwf9iygvXXKohVfrmfx5koyA/XawanUM1VbdMtRSA/vE6S3Dk2l3uySCgMBEOh4AofywN+n/Ps/kv/V/vUSHZwSVNqiY3mfC71wbWrEg4TJRx9FOR9/SEkHH9TmdusLyYcdRtkffUDyrx2T2fDbJwXpkyPTaKiO6E7mcDdNSKb/cDjZqBIGAiAAAvFEwLovUDyVHmXpEALiij623wnK7Hhp1ToqqlhJxfxJCqTzkWyDlWPZ0pS14JZe4bvURfKYMOAUGtfvRCpR8lhBOypXUTCQpaxTl3xSk2UjMft5RDNMScqmg0dfT/XhaiUPyausehNl8SCD1CWXZ/OTeENAGAi4TUBmrV/lWevShgZaWB+iBXUhWh+O0FA+o1hc4Ufwx+wsu1bZBrIb6us98mhHpDkPzmcj5zG8OY/hnEeKyVl2rTyi1w/v66fD+mbQ2ooGmlMcoTlFEaqLEMkslaxXl1kqp5vKGZUB90EABKwTkBn0x3kmvbKhkRZJW8SfVaEwSfshxzqO4vbCytIXtRJ4Cwoo8+mnqLGigsKLFlN44QKKrF5DvkGDyD9mNJ+bPpI86faW/8TmtxevKf9hajptrpK2qIHmcntUXNtI4/K8Sns0PNvHGwDGxsLfIAACIBAfBCDQ4+M5dMpSiIjOTR+ofKjnIe1SB6/Xz4J8kPJpbxMR3iN7tPKBgcDuJJDNbqNTeDdk+bSXSQdc3NeturBbLY8MmQ3go4rkgw3grNJDeBDoWALpvGmceNLY9aYxU3pPRgYFJu+tfNrTpC3qxZ468jmqH7q77ckaaYMACLhLAOOH7vJEaiAAAiAAAiAAAiAAAiAAAiAAAiBgiwAEui1siAQCIAACIAACIAACIAACIAACIAAC7hKAQHeXJ1IDARAAARAAARAAARAAARAAARAAAVsEINBtYUMkEAABEAABEAABEAABEAABEAABEHCXAAS6uzwTNrVIQ4gaGxvbtf6SB1H75hGtQC3vPA0Dgdbfh93zzSOqa+ffkdSjvfOIcotwZvUN+B6BAAh0RgJN79z2Lfnuaou4g0KN9fXtWxmkDgIgAAIuEcC2li6BTLRkwpE6Wrn1f8qRZPKR49b8vmTebX2IcjRZr5yx/BnnCEsoUrMzj3LOo3o9BXypLUe59c4d79qO6yvKid5cTTS7iOgn/qytJOrPp71MyudPAdGJA4gGZzqqDiJ3IgJFfBzPm6tCLUeFLS9roIIUD03go8LkiJ7D+viVf92wZXyU0X+qa5Uj1uRoo62RCPX38zFryQHlqLVj0oLU3ecsr8Wc7n9r6jiPeiWP7XzkmhyfJOnLR841zudd3p2aiP+P14Xp261h5Yi1eXy8UZiPbRqd28RtTz766LcDAxRwnpXToiI+CIBADIGK2q20ZtuMlvd6Ze02SgsWtLxzB+TvQ5l8/KgTW8Pt3cfS3jUf5baJj3zsw8dNKm0Rt3lHpqaQHD/phoVmfk/1331H4QUL+Ui3hdRYVUX+wsKmI93GjqHk444jT0qKG1khDRAAARBwlQAEuqs4EyOxbWVL6Zulj1F5zeZdKizniG8uma98Fqx7mwZ1P4AmDzmfkvl8dKu2pXQh5/E4SQehtdWHK2lTyTzlM3/dW1TY42Daa8i5ts8pZ+1Ajy8munEWUU3MrLmIdPm8tYbojp+J7tuL6NIRRHwKDawLE/iABeZVM2pIRHpr21bTSJ9uCCufaXPr6LLRSXTThCAFbfYlw5z8k+WVNL20gmIdNtaGwySfD6pq6ImySrolN5OOZxFt9atXz7NGj3H8Z/gTO5G9mjvK8nmvOY878rLoqNSg7Se7ubqRrviuhv6zMdwmjZ9ZrMvnr0uJnlpcT09PSaEROVDpbUDhAgh0AAHxflu26ROateplCkdqdylBVe12ks/a7d/T3DWv08SBZ9DIPkeTx2Pt9yvtz4vlVfQgt3exs+YbWKTLR4T746WVdF1OJp2ekUrWcthZ7Maycqq86y6qe/ffbWiGly4l+dAbb1LNc3+l9Gn3UWDSxDbhcAEEQAAEOpKA3favI8uMvDuMQCPNXvUKfTTnxjbiXK1Iq7Z+Te/MupwF+wK126rXpKPw44q/0cdzb24jztUiLN/yOb076wqSQQOrtrWG6OCPiP74fVtxHpuWiPcrZxId8jHRNo4H63oE6vgZX/B1DZ3xRXUbcR5bW5Hujy+sp1+9V0lLS2Olb2zotn+v587oCVuK6FEVcR4buryhga4pKqWLtpdQlYwombRVLL6P31xET6mI89gkSjmPKzh9+dTYcLF/b22IJr9bqSrOY/OaVxyhX71fSU8sgrtpLBv8DQK7m0BtqJw+nX8bzVz+bBtxHlsWcXn/ceUL/H7+M1XX7Yi9rfm3eOyctqWY7i4pbyPOYyNJ+3PbjjL6/dZi2sHxrFpo1iwqOfIoVXEem1Zk3ToqO+10qpp2P6+eM9+2xqaDv0EABEDAbQIQ6G4T7cLpLd/yBc9av82rwM2/yGrqS+nLxfeT/GvGlvIo/qIN75sJ2hKmqq6Yvlg0jepCFabjSQ3+8A3R/7aYjqIE/IqdBi74dnethLdWNoR2RuBenhX/F7u1W7Fl7Pp+1pfVZGXPApktv7KohBaxi6cV+y/PLt3DHVwzFuLO5uUs6sV93op9yHn8hQcNrNgvzEAGNsrqzbcLsi79ABp8AAAgAElEQVT9plm19LnKbLuVvBEWBEDACYFGmvnL04rXmxXbWraEvl32OEcx/s1LiP8rLqVZvLzGis2sraebWKgb57Az1YYdO6jisiuoYduunne6+XJbWfP8X6n29X/pBsNNEAABENidBCDQdyftTpxXVV0R/cAz23asLlRJM355iqPqv2orarbQT6tespOFMgDw/YrnTcd9aTnRh+tNB98l4HvriF5dYS8uYsUngVnbI/TYwjpbhRORfu+cXd1C9RJ6jme05/F6czv2WmU1fcNryY1sOuex1OIAQDRNcUP9kTvHZkw2gbvk2xpLAxSt072MXeKtCHszZUIYEAABcwRWb/uO1mxn1zAbtnHHXPpl838NY77BbdbXJtostYQ+4wHD93kJjiljoV11y20kIt2OVd17H0U2brQTFXFAAARAwHUCEOiuI+2aCc785RkK8Rpzu7au6EeSzoCefffLk+xiZyw+tNIQl/r1xT9p3W65Li7qV9nrk7SkcQXH325ekxmWCQE6jkBUZFrwHm9T2MfZXXsuu24bmWyQ9AiLZyd2fXEZ1eq4Y8qsubi127XojJeskTeyZ5fU0088uGHXZN36rT/Z/83bzRfxQCDRCcjA+czlzzjCIMvRqutLNNMQ1/a7THr9aCVy245ykiU4Rlb/n/9S3aefGgXTvN9YXU2Vf75F8z5ugAAIgMDuJACBvjtpd9K8ZN3Zxh1zHJd+XTHvxKZhIv6trFXXSIZkIMDIxK293N4EZkvSZTzB+I1F93ijcuF+xxBYUd5Asku7ExNxL5vHGdnXtXUk7udObAvv8i67smvZVzW1bTad0wqrdV3WyP8S0s4jGu9D3lDPqX28no9odJoI4oMACFgisK18CS8Lsz+QJ5mFeEO5LTp7zPzA7Z2VfTPUKlDG4vwnEx49dZ9/rhbd0rXQjBnUWGNyxt5SyggMAiAAAtYIQKBb45WQoXdUrqGGRvuzZFFochyblhVXrtK6Zel6ccVKw/BylJob5lY6bpQFadgnIMeBuWFm0plv07U9tnxyRJGWyXFtbpheHpK+DEqY8RowKstW3h1/C8+kw0AABHYfAb33sZVSFOm8c43aELP5zNdp76JpyFFqjo0HA8KLlzhOBgmAAAiAgFMCEOhOCSZA/OJKY9FrBkN59SZNN3m3OgslVWtJZvz1zC1h7VY6emXFvfYn4IbIlFKaSWehiY6mmRrriXC38jBKZyV7HlSG3BHWZgY3zHBBGBAAAXMEzAxmm0lJr3/glkA3aotk1juy0p1+SniRC0LfDDiEAQEQAAEdAhDoOnBwq4lAVa1LU86cnOy4rmayCZ0bJjP9NTpr4iSP9VVu5ES0zqV03CkNUrFLYGOVM/f2aL5yTrrsTq5nm9k93Q3bpJGOZO9aHuzmrmducZM81rv0DPTKi3sgAAI7CVRqvIutMqrkM9K1bLNBG6IVL/b6JoN0lF3bTaxTj01X7e+GTXxUCwwEQAAEOpgABHoHP4DOkH1Oen9XiunzBigztZdqWjlpA1SvW72Y5E+ltOQC3WhjcnRvm7451qV0TGeIgO1CYFSOz5V0h2Z5KcmgRR0WCLiS13CNdCT7oRr3rGY8PEm/rCNd4iblGpPrzjOwWkeEB4FEJZCb1s+VquemD9BMZ5hBG6IZMeaGUVvk69OHPCkpZpPTDecfNkz3Pm6CAAiAwO4gYNCd3B1FQB7xTiA/Y4grRcxNH0hej3pH3K088jIGk8fj0S3vxHzd26ZvTtQfBzCdDgJ2LIHxeerfSaulMpPOGJc6rGOStcXzWLfyMEinW4qHeqc5f4XIr3VsrvN0rD4vhAeBRCaQ59J7Xd65WuZae2fQFpHPR/5RI7WKYem6f8xoS+ERGARAAATagwB6Re1BtYulmRHsQTIz7dT0XuTZaX1JZtidWn66dmchmvYkl4T1xDynpUX8eCAwPt8lgW4iHT1hbYWFXsfXrTxGG3WKucAT8py/QgrZ8yA9oD+oZoUNwoIACBgTcGtQXO+dq9dOGZdwZwgzbZF/tHNhLbPwvoEDrRQNYUEABECgXQg47121S7GQaDwRkBnpkX2OdlQkr9dPw3sdrpmGzKyP6H2U5n0zN3zeJBra61DDoAf0IBrvUFzvwfH353RgnZ9AD54JPmGgs8Gh/KCHTjSRxm9SgtTb72xAYP+UZBoc8GuCPyI1SN18zpr2QzgNM+W8aGSSZjnM3rjYhTTM5oVwIAACTQQKModSQWahIxw57CbfM2esZhr7BJPIyD1dM3LzDRH5kzgdIwueegp5kozD6aUT/P2ZJLPxMBAAARDoaALOenEdXXrkv9sIjOv3O9Jba2ZUkAkDTiV5mevZHgNPpazU3npBdO/tOfj3lJnSUzeM3JR1wi8cQBSw+e2XeC/+yn58wwIiwG4n8MDeQSpgkW3XHtk3hUSkG1ma10PT8rKNgmneT+f49+ZmkV5OWV4v3eMgj2yOf7dBHtECTunhpwtH2O8UH9jLT2cPsx9fE1Qnu9HAG1yVl5fzPlcGuwy2qldtbS1VV1ebrmk0j4jGBoOmE0LALkFABsWnDL/Ctueax+Ol/YdfqRs/wIP7D+RlkV3JK/EfzM82Fd83aBCl/umPtp+Nr7CQUq+43HZ8RAQBEAABNwnYlChuFgFpdQYCMgMuL2OtNeR6dZBR+tF9j9MLotyTGfD9ucPg0ZUf6sn0yB7FM/RHqt9UuToul+jmCSo3TFy6bQ+i0dggzgSpzhMkj8W1iGw79rtBATq6n/aMdmyaMqt0Zoa9JSN/zsmkniZm4A/kWfYT0+3lcUduJuVbmIG/dWIyDcyw/ioRt/bH9wva+LXHEu28fzc2NtKHH35IF198MV155ZV04YUX0ttvv016InrLli10zz33KHEuvfRSuuWWW2jNmjWaECSPTz/9lC655JKWPN544w0Kh8OacXAjMQhkp/ahPQaeZquy4/qfSHkZgwzjjuQZ8MuyMwzDqQX4U3Y6DdHxFoqNk3L2WRSYyC9oq8az5hn3T3M8A281W4QHARAAAS0C1ntVWinhepcnIDPoR4y/y9QsdRTGoO4H0G/G3GJa2Ivb3eHj76D0YDfTPAt7HEwHj77RcHO42ARvHEf08GSiFJPD+xLu0X2IrtP26IvNAn93IgJHsch+9aBUUzPhUi2Zxb5idBKLTOvC/s85WXQld1pNfvUog2fOZSbJiui+k4X2xVnpZLaRl5nzxwpy6Kg0a/VJ9XvooyPS6JDe5gcpxvKu7f85Mo36uLDJXCf6irUp6s8//0xvvvkm1dfXK/dENL///vs0Y8aMNmHlgsyCP/PMM7R8+fKW++vXr6fp06dTXV2dapyFCxfSa6+91nJfxP9HH31EX3/9tWp4XEwsAjJ4vs/QC8nvC5qquOwVs9fgc2h8/5NNhZdAl3E7dBMPLiYbbOAaTTCFw93GXjx/yEw3nYcSkIV2Jv8+kqcebzqer18/ynr1ZfKPHmU6DgKCAAiAQHsTMNt3a+9yIP1OQqBb1nA6btLDvCZdf714MJBJB426jn414o+UHLD2ku2RPZqO3/MRGtbrMF0qKUnZdMiYm9hN7zJbm9ix5qEr+Z08ZyrRPgbjAft2J5p7AtHlvFGsxIN1TQIyE/798el03AD9NemDMr30CQvMOyYFKWhWZbdCxpqWruBO6zs98/lYNH1hewDPhn/aq4CmsnC28tVL4k7uNTwI8EaPfBpkkIesOZc8juJ/7VjPVA+98ZtUeoy9EPQ2fPPzG+f68cn0+dFpNCIHr5+5c+eq4ta6XlRUpDpbXlxcTBs2bFBNa86cOarXZXAABgIy1Cj7wxw/6RESTzQ9E284ef+P6nssD4ib//1KyHMz0+gDbu/G65xAIXlPSk6iD3vlK15G5nPYWWpPVqYyG5751JPkzdc/siV4xumU/cF7FJg0Sa/auAcCIAACu52Afs9wtxcHGXYGAn5fMu095A80rv9JVFyxkor4I/8mBdJIdoaVT05af921aUb1DPhSaN+hF9GEAafszKNyFYnwz+djXSSPbF7T7sbO70OziL7hPfBWVhDNLmr6LCsjGsbX5Ui2SfwZxB56EOZGT61r3Je15C/+OoU2VSXT3OIG/kRowY6IMts7gY9km8C7tcuZ5yI2ndoodv/8gIXx6lCYFtSHaEFdiNbzLOpQvi6bI8nuxbJZmxVhHlsm6RB/wnms5DwWcvqSzwbOQzZviuYhbvNO8pA8Jf7vhwboxEF+5tVAc5jb3KII1UZ4t3dmNp53fB/H/LKTnOYUW8PO+7fWGvLKykrVSsm6cy3TuldTU6MaRStv1cC42OUJZKR0Zw+5O6miZiu/01co7/Wy6g2UmdqLZKd2eedm8B4vRseY6oGSgUIZMFwXbe+4LZK2Tza9VNoibqv6+f2O2yIpQ9IhB1POAftTZNkvFF64gD+LqKGkhI9jG8Wz5aOVGXNvnsPdYvUqi3sgAAIg4IAABLoDeIkeVcRy79wJyqe9TGbJ++RNVD7taSK+CzObPqcMas+ckHZnICASUs74lo+4vrenyQS8rLOUj8ySt4dJHjJTL58TqH3yiJZbXN737uZTPjB9Av379ye1mex+7HarZt26daNAIEChUKjN7e7d2c1HxSSt77//vs0drTzaBMSFBCLgYRHeQ/kM7DalXeot45oDuB2SzzHt1N5FCy67usu55jjbvF0eJRIFARBoRwIuzAG1Y+mQNAiAAAiAAAh0UQIHHnggZWfvuqt/WloaHXaY+vKeYDBIJ554YhsaEj5fw533gAMOoLyYmcLU1FQ64ogj2qSDCyAAAiAAAiAAAh1PoH2nhjq+figBCIAACIAACMQlgYyMDLrzzjvphx9+oO3btytCeq+99qKsLF5fo2GHHnooyez30qVLld3ehwwZQmPHau9cKYL/jjvuUGbRt23bRrm5ubTnnntSTg6OotBAjMsgAAIgAAIg0KEEINA7FD8yBwEQAAEQSGQC6enpdPDBB1tCMHz4cJKPWZMZ84MOOshscIQDARAAARAAARDoQAJwce9A+MgaBEAABEAABEAABEAABEAABEAABKIEINDxXQABEAABEAABEAABEAABEAABEACBOCAAgR4HDwFFAAEQAAEQAAEQAAEQAAEQAAEQAAEIdHwHQAAEQAAEQAAEQAAEQAAEQAAEQCAOCECgx8FDQBFAAARAAARAAARAAARAAARAAARAAAId3wEQAAEQAAEQAAEQAAEQAAEQAAEQiAMCEOhx8BBQBBAAARAAARAAARAAARAAARAAARCAQMd3AARAAARAAARAAARAAARAAARAAATigAAEehw8BBQBBEAABEAABEAABEAABEAABEAABCDQ8R0AARAAARAAARAAARAAARAAARAAgTggAIEeBw8BRQABEAABEAABEAABEAABEAABEAABCHR8B0AABEAABEAABEAABEAABEAABEAgDghAoMfBQ0ARQAAEQAAEQAAEQAAEQAAEQAAEQAACHd8BEAABEAABEAABEAABEAABEAABEIgDAhDocfAQUAQQAAEQAAEQAAEQAAEQAAEQAAEQ8CcCgtJQKXnJkwhVRR27AIFIYySua1EVrqLS+pK4LiMKBwKtCYQaQgDSRQk0cHuJ9qiLPtwuWq2KUFkXrRmqBQIg4BaBhBDody+8zS1eSAcEEp7Av9b9M+EZAAAIgEB8EChjsXPnwlvjozAoBQiAAAiAAAi4QKDLurgXJHejzECmC4iQBAh0DIGsQBYVBLt1TOYquQ5JH6pyFZdAoHMQ8Hl8NDB9UOcoLEppSKBval9K9iUbhkMAEIhXAn2U73AwXouHcoEACHQgAU8jWwfm365Zi6twVbiyXfNA4iDQXgTS/OkkosKJffbZZ7RixQoaN24c7bfffk6Sokb+X2WoQvkXBgKdjUCSN5mC6Ax3tsemW976hnqqjdTohsFNEIhXAhk8ieTB8st4fTwoFwh0KIEu7eIu4iaTZyFhIAACzglIR0I6FDAQAAEQiAcCSd4kkg8MBEAABEAABLoSgS7r4t6VHhLqAgIgAAIgAAIgAAIgAAIgAAIg0PUJQKB3/WeMGoIACIAACIAACIAACIAACIAACHQCAhDoneAhoYggAAIgAAIgAAIgAAIgAAIgAAJdnwAEetd/xqghCIAACIAACIAACIAACIAACIBAJyAAgd4JHhKKCAIgAAIgAAIgAAIgAAIgAAIg0PUJQKB3/WeMGoIACIAACIAACIAACIAACIAACHQCAhDoneAhoYggAAIgAAIgAAIgAAIgAAIgAAJdnwAEetd/xqghCIAACIAACIAACIAACIAACIBAJyDg7wRlRBFBAARAAARAAASaCTQ0NNC8efOUv4YPH04pKSlgAwIgAAIgAAIg0EUIQKB3kQeJaoAACIAACCQGgUgkQjNnzlQq279/fwj0xHjsqCUIgAAIgECCEICLe4I8aFQTBEAABEAABEAABEAABEAABEAgvglAoMf380HpQAAEQAAEQAAEQAAEQAAEQAAEEoQABHqCPGhUEwRAAARAAARAAARAAARAAARAIL4JQKDH9/NB6UAABEAABEAABEAABEAABEAABBKEAAR6gjxoVBMEQAAEQAAEQAAEQAAEQAAEQCC+CUCgx/fzQelAAARAAARAAARAAARAAARAAAQShAAEeoI8aFQTBEAABEAABEAABEAABEAABEAgvglAoMf380HpQAAEQAAEQAAEQAAEQAAEQAAEEoQABHqCPGhUEwRAAARAAARAAARAAARAAARAIL4JQKDH9/NB6UAABEAABEAABEAABEAABEAABBKEAAR6gjxoVBMEQAAEQAAEQAAEQAAEQAAEQCC+CUCgx/fzQelAAARAAARAAARAAARAAARAAAQShAAEeoI8aFQTBEAABEAABEAABEAABEAABEAgvglAoMf380HpQAAEQAAEQAAEQAAEQAAEQAAEEoQABHqCPGhUEwRAAARAAARAAARAAARAAARAIL4JQKDH9/NB6UAABEAABEAABEAABEAABEAABBKEAAR6gjxoVBMEQAAEQAAEQAAEQAAEQAAEQCC+CUCgx/fzQelAAARAAARAAARAAARAAARAAAQShIC/K9czUltLoZKyrlxF1K0LEwjkZpMvOTluatjY0EB124uIGhrjpkwoCAiYJeBLTaFAVqbZ4AjXCQiEq6opXF7RCUqKIoJAWwLJBXnk8XfpbnjbSuMKCICAKQJdtmWIVNfQwtvvpUhNrSkQCAQC8UZABMXoW28gX0owLoq26vmXqGzhkrgoCwoBApYJeDw0+PyzKWv0CMtRESH+CNRu2UpLpj1CjZFI/BUOJQIBEwSSuxXQqJuuIeK2CQYCIAACrQl0WRf3uqIiiHN81zs1ARlkqisqjps6VK9dHzdlQUFAwDKBxkaq3rDRcjREiE8CNZs2Q5zH56NBqUwSqNu2nSK1dSZDIxgIgEAiEeiyM+itH+K4abcTebvsWEQifV8Toq6N4QjNv+G2uK3rwLNOo0zMQsbt80HB2hJY9dxLVPHLirY3cKXTE0jKyaYRN17d6euBCiQOgbqt22npg48lToVRUxAAAcsEEkKge3kdrwcC3fKXAxE6hkCjP75dNj2BQFytje+Yp4RcOxMBtP+d6WlZLCu7B8fTXh0WS4/gCUjAm5yUgLVGlUEABKwQwLSyFVoICwIgAAIgAAIgAAIgAAIgAAIgAALtRAACvZ3AIlkQAAEQAAEQAAEQAAEQAAEQAAEQsEIAAt0KLYQFARAAARAAARAAARAAARAAARAAgXYiAIHeTmCRLAiAAAiAAAiAAAiAAAiAAAiAAAhYIQCBboUWwoIACIAACIAACIAACIAACIAACIBAOxGAQBewfD7uxvc+orIFi1zDXLlqDa177S1qbGhwLU0kBAKdkUDF8pW0/l/vuPZbiNTU0uoXXqX6HSWdEQfKDAIg0AEEGiMRWvvq61S9boNruZfMnkubP/6P0oeAgQAIgAAIgIBbBBLimDVdWPxi3fDuB7Tty29om89Hg849g7LGjNKNYnRTxPmKJ5+nhvp65dP/jJNxzJsRNNzvkgREnK98+m/UEApRQzhE/U/9HREfi2TXRJyvePI5qlq7XvkMveIiSsrNsZsc4oEACCQAARHnMqhXOn8RlS5YTIWXnk+p/fo4qrmI89Uv/7NJnHM/oucRv3HUtjkqDCKDAAiAAAh0KQIJL9Drioqp6LvvlYcqL/FVf3uVRfqZLNJH2nrQrcW5JFDy8zwqOGA/ShvQz1Z67RVJxvvXVhL9tJ1odhFRA1+YWEA0KZ9oYAb3M9zKmDsukY0bKbxgIX8WKKn6x4zhz2jy9e7tTodG8li/vimPhQs5Az8FOH3/6NHk7dnTnTyaedTzv0vCjTQn3EAL+d8+Pg+N98vHS9muQXMLfgenw89l80efKeJcrPj7n5R/7Yr01uJc0pEZ9O1fz6Dexx+lpNtRFuHfzoryBppTFKG5xRHKCnhoQr5P+XRPcfFLwe1TZNWqpu/5osXkyc5SfkfK9zyff7huGOcRXrGSwgsXUGTxEvLk5irpSz5e/m83LRyppeLK1VRUsYLKqzdRVmofys8YTLnpA8nvS3YzK6SV4AQqV65WhLlYpKaGlj/xHBVexiK9rz2Rvos45zS3ffUt5e2zFyXlZMcF6S01jTSX2yNpk8pCjTQ+r6k9GpLpJX5luWYN27a1vNsbq6p2vtv79yfyOnfQlH7KpipuW4ub2tdabmwnNNdlYIaXvC7WJcJ5rQqFaUFdiBbWhyjb56WxSQEazZ98/m8YCIAACOxOAgkv0JML8mnwhee2zPI1ifRXbIl0RZw/1TRzLg/Rwy+ogWefHnfi/N9riS6fSbShSv2r1j2F6JHJRCcPUr9v9mrdJ59S1R13UsN2HgVQMW+3bpR+682UdOihKndNXGIBWPf+B1R1z73UUFy8S4Sa5r+8vXpR+u23UtKvf20iQe0gtdxTuLs6TM/WREhEuprtF/DSo+l+GuxmD0gto85yjWfKB59/NneGn6Xq9RuVUtsV6U3i/Hll1jxquZMmUK9jj+gwGjKo9eySerp7Th1VcCdYzYZn83di3xTau5tP7ba5ayyaa154kaofn06N1dWqcfzDhlL6PXeTf+xY1fuGFzmP6meeoZqnn6VGFjBq5h81ivO4i/wj7Q1eRtOsrS+jmcufpbXbZ1Ij/y/WPDw8OLDbFJpceD4lB3i0EAYCDglkDB1CA04/idb8/V/KjLci0qfbE+klP7eaOedy+YJBGnLJH+JCnH+/NUJXzqihZWXqS+syePDwpj2S6YLhSY7EbeiHH6ny5pspsnqN6pPxZGZS2tV/ouCpp9geIP9iU5j+OKOWJxLU65Kb7KE7JgXp9MKAowkFEeZ/La+kx0srqVpjqcJwFun35mUpgh0GAiAAAruDAIYFmXJG4WAafNG55A00Nb5RkV7WPOJu5kG0iPO6JvkWFefZ48eYib5bwpTUEf3+f0RT/6stzqUgW7l/fuqXLNC/INpea71ojaWlVHHVH6ni8is0xbmkKqPv5ZdeThV/vJoay8osZdRQVMRxL6OKq69pI85bJ9SwaROVn38hVV5/IzVWVFjKIxr4J54tP6C0nqbriHMJ+12ogaZwuGc4nHqXwlb2nTqSLzWF3Ukv4Jkq9pZoNhHpa//5hul1mzvF+bqWNEScd+TSkTUVDXT0J1V0/Y+1muJcCru0tIEO/6iKbv6plmqlJ2jRImvWUtlpp1PVtPs1xbkkGV72C5X+7mSqfuhhauRlNVYssmIFxz2Jqh9+VFOcK3ksYvfgE05UBgooHLaSRUvYNSzK35l1Ba3ZPkNVnEtAEe2rtn2jhFtX9KOtfBAJBGIJ5O41URHp0SU2UZFevd78mnRFnL/U7NbOGUTFeUd7yEnbctOsWjri4ypNcS48ZCDx+h9q6ZhPqzSFbyy31n/L4F3VnXdR2RlnaopzCd9YXk6Vt95GZWefS/IOtmKVXMarWJif8Fm1bhl31DXSZd/V0Cn/raYt1W0H+szkuZpnzE/eUkTTSio0xbmks5Rn1E/cXEQPlVZQSEPEm8kPYUAABEDALAEI9GZSmiJ9YZNbnB7QziDOWTPSlA+IXl2hV5Nd772xmmjye/JSNx9HXuClJ55EdR9+ZDpS3QcfKAJBa+YuNiF5+YtQqP8PjzSYtNq33qKyU0+zLF5msug+rDREy8WP2YTJTPv1VWG6iT+wJgJORHo8ivMN7HJ5wPtVNINnq8yYfHMeX1hPp35erTJfrJ1CZN06Kj3ueAr9PEc7UOs7vCFl9VNPU8VlV5gf/BBxfvwJipuqKZOZ9sceVwbGrNrSTZ/Ql4vup9pQuamoNfWl9PnCe2n5ls9NhUcgEDAi4ESktxHnycnKzHlHi3Px5DmJReoTi+pNty/fbYnQ/u9V0UZuy0wb//bLz/0D1bz8iukooRkzqOS4qboD9a0T49ctDx5U04u/mB9k/HRDmH71fiWJYLdia3mQ8VgW3XPYpd2MSWv/RFklXba91DRnM+kiDAiAAAioEYBAb0VFVaT/9RUq0xHpnUGcSxVv5uW/S0rVvgL611bzpPP/WZjEqrr/AYqsZR96iyauctUPPmQqVtXd7NK+ebOpsK0DySyjMvtn0mRQ/tLKsK3Z8Kd5RORb6W3AFAIi0ofIxkxtZtLf1BSTijjnJSNVa+Nn5ly6gJd9V0vl9dY6g8LgS3bZ/NtSkx1PFtuV192gO2uu9dWq//JLqn37ba3bO69zh7viuuupsY5dayxa3UcfWxqEq6jZQrNWvmgxl6bgP6z4G1XVqi+TsZUgIiU0ARHp/WNn0nlNenQZjhoc2Utml5lzEefcnnW0OJeyPs9tytebrQ8ISxt2ObdlZluymhdfotBPTfuIqDHSuiYedZV/vkWznW8d76EFdcq6eau2ldfcX/u9eXc/yeHaojLdWc1JCf8AACAASURBVHOtMvyX30vvVKovA9KKg+sgAAIgYJUABHoMMSsivbOI82+3Ej1scoJM7Qv0zFKiz5qWEKvdbrkWmvk91b76d90wejdrXn6ZQj/qjwaYFh8aGdU8+xyF58/XuLvr5dt4Fny1yZlztQRF3FeZ7f2oJdDFrvlTU5tEep/W7u6z2N29rUhvEedr4kecy+N4YVk9fcVC267d/FMdiXu8kckslZ3OcDTdqrvuMRzEqlZ+C00bNxqVR+2+uLA2bOcdJg2skV1Cv1n6OIUj1gcCJOlQuJq+XfYE/xd+TAaocdskgbxYkV4tG8ft3CujdTJN4vwfLQLTF0fifBVvTnnrbHu/K6mjrPN+2cRstWxOKctn7Fr9F19Q3bv/1o2+YEeEHphnvy5vrQ7Rv9eYmw1/sbyKZjcvR9QtlMbNO0rKaAsPcMJAAARAoL0IQKCrkFVE+oXn7LomPWYmXU2cDzjrNIqnNefRqt0z13nX9m5Ow8iqn3zSKIjh/eonntINUz3dYR7NbsC6mfDNEtYCz9lZNNwq4XUs7v9Vh5d4a9aKSJfdk3VEeqS2eeY8zsS51OP+ufY7kBK/mnf+f3KxwSw6C9rq6SJI7VtjZaW+K6psPMfu8E5M9o2o/QcLFwPbUraQtpYZLxXSS2ZTyTzaXr5cLwjugYAlAopIP23nsY8RFZGuKs7jwK09WtEnuC2p4TbFiU2bZ9AeceI1zz1veXlYbJmM2rSHF9QTb/fiyO43URehNZ1d1Z1YBa8reKlcfcNOJ+kiLgiAAAhECUCga3wXZNdXdZG+hKpWr23arb3VhnAiznMm2NxBWaMMblyWl9FPxpNchln9zGnoTiaz8A0vXGSYjlGAsByTprUJCx/XFVnK0/kOzcx627lOewrNZZzjsPPksKpxGV1TpL/2lrK78oon2a09DsW5bEQkxxc5NSMXzsiGDZY3TVQrU/RYQ7V7kZWrTO/5oBY/ek35vRpYUcVKgxDmbstxbDAQcJNA3t6TNEW6iPM10XPOOVNl5lzE+cD+bhbBUVpGbYmZxOUYM3ER1zMzv3O9+HJP9tRoLNPef8KNuiwt5YFHg3fuOl57Xs79Fae2wOJmnE7zQ3wQAIHEIgCBrvO8VUX68y/x8SzPUEMnEOdStXU8UFxkfmmWJg3Z82yZzkbrEV4nLLN2Tk02gJMzzdUsvHy541F8Sbdh61ZD19y5Bi95tfKpXZPz0mFtCaiK9Jk/0qK7HthFnOdMHN+hu7W3LvkcPuPcDRNXTr2vhZkBJDPlUAbMNDqiIT7n3A1Tyqo1oNacQbFLwhoC3Y0nhjRiCaiJ9F8efYrXnP+DGpt/P/Eozuv51bKQ2xI3bK5O29bIHk3h5e4MjoUXqQ/olfJ6+NUmlv4Y1VUmERaU6L9z5ZxzN0zOStcf1nAjF6QBAiCQqAQg0A2efBuRzi/sBj6aQ0yOUhtw1qlxOXMerdacXY8HN6it/m29tMKLnbmwts45vHiJakG0rqsGNrhoVN75egrKIO3Wt5ey0Dd2ILSQYBcKqibSwxU7B3lEnA848xTldxYPNk+nE2ulfLJyYrnGOcWSjtF302xejVVVPGulPtgVWeTO77WhuNhwh+biilVmi6wbzq10dDPBzYQkoIj0U3e6uzfI7GjzwFM8inN5SL/wbLGIdDdMr22L/PILT3+7MxCg1bbJoKVbplcXyWNRvf09RFqXUdzcN4TdK7db9Uc6IAACXYNAfPR845yliPRexx7RppTdDjqAxfm4Ntfj6UJ+0L3S5Cdrp+XNydG+afGOVlpa1y0mrwQ3SivX47GTbJs4GZxMoM1VXIgSEJE+6A+/J29S0i5QkvPzaMAZJ8eNOJfC5QXd+U5IWrk6aRl9N618e7TS8uTmWklGOywPnngyMrTv851gIFP3vtmbwSR30jGbH8IlFoG8yZOoYL/Ju1aa3wN9TjwurtzaowXMC7rXfcvXaY88Lr7btdLKS949dRF2uT738sqOk8HjxPqlorYgkBgE3GupujAvWXO++YNP29Rw25ff8BFs6rO9bQJ30IXx3A/3uqQrJuZrV8I/apT2TYt3/KNGqsbwjxmtet3yRb+ffMOH6Uab4HcH2gQ/CxjdnBL7pmwIJ66kyoxVK6srKqb1/3rH0H16d9KbkOdzJbueqR7qnqL9rXDre+7r1488Weqi1j/and+Sv3AIeVJSdLnkZQzRvW/2Zr5L6ZjND+ESi0DJnHlUNOOHXSvNs+gb3nmfqjeYOMZkN+PqYdCOWCmOXtvm69NHsx2xkoeE9Y8eoxplaJaXgu40r6RXF8l8TJI7Q+YDuB+R4VbnSpUKLoIACCQyAQh0g6evbAjHm1ZFomcF84i6x9f0Jmlkt69Vf32ZyhbFr0hP53fRiGyDSpq4PSCdSG82XoSAr7/zzXN8AweSJ50zUzFvt27kLShQuWPtkn/YMPLEzNjGpiDC2g0bH9AWYm6k35nTaNqt/a/KpotRk/PSo1bEa9LX8cZxRmucdxeD0bk+cuNrMSFfvyfqH8kDVC54cOgJff9odwbUtDrcrZ9JfsZgVx4RBLorGJGICoGSOfNpzUv/bFlz7mHxFf0NKru7T+cj2OJMpMubxagtUalqm0sBftWNzNFpk7gtMvM7b5NwzAVPMEj+IeptgbSr41wYAM1O8lD/DP139yiXBPqYZHeEvhE33AcBEEhMAvotWWIyaal1rDiXtbADebf2IRefx0ew8QucTRHpz8e3SD9057HTtp/ooX2Mowam7GccyCBE0v5TdEMEDO7rRm6+aaacw3gGvacLo+MHSu8H1oaAmjjP2WM8jbzpWkrp3aslvCLSX387LkS6zPDs273pd9+mQhYuHNRLPw0ZoApMGG8hRfWggSnavyVvXh75R4xQj2jhqpnfUo/s0eT16tfZKEufN4m6ZQ43Cob7IGCZQJM437khnDc5iYZefiGvST9xF5G+YvpzcSfSDzRoS8zAmNLDT8k6+lzSSHLh3R7YZx/eCl87IzfqclBvv6HHmsx6T3BBXO8f1FnzZwY8woAACICADgGoBw04auJ8wO95Q7g9xlHTxnHndhqRftseRP3VJ6U1ar/r5R48qXnPJOOgaX/6I8kst13z9uhBqVddqRs97br/I6+D9bPi9pt66SW6echNkROPpzsTFaezopsCgd6GtZY4H/D7UyiQkU6Fl12wq0hnt9N4EekP7RN05Iq5Z4GPzhm263r7NoD4Qvqdd/LmBfZnaAJ77UXBE6aqJd1yLf2eu3U7zLqR+WbSAftT8lFHGgWj9GAB7THgVMNwegEmDfo9pSa7tG5eLyPcSygCauK88JLzlTXneZP33EWkh6urKd5E+nnclkw08MjRe6Ay6PiXycYb1aScfZajAT0P7zWSduvNekWhq8Ykk7i62zWZPb9nT+O6SPp352WTk1Vsk4NJNDVdf2mP3XogHgiAAAgIAfutYRfmFyvOxdUtKs6j1VZE+gXntBXpi52f0+022gzu5/91f/upPssTcbkmBos9mZmUfu89tjPKuPduww2nRJyn3XGbvTz4OaZPu89wzWw08YOTvPR7mwvjevEo/T1pzgS+vUrGdyxZKrLiqV3d2mXQS8R5dLd2f1pqs0jv2VIZWRsaDyJ9SKaXbp1orhMY+yTkq/TklBTymVj14BtaSGlXXhGbhKm/ZU14+n38OzTYwEjc3FMvutBUmrGBZGO49LvvMu2KP6rvcVSQOTQ2GVN/98geRSN6Gw8EmEoMgUCgmYCaOB9y8a7nnGuJ9JqNm+KCo7iGP7l/iuEMuFZhb58UpEHcphkau/ynP3A/j1zbe6el3XA9+Xrru/JJ+/gU18Wu49r9PNAg6/LN2DD2gLwyS39zS610UrkfMY0FvglqWkngOgiAAAgYEkAbE4Ooas26NmvOxa1dRESsZQwrbCvSn3uJyuJQpB/EXsP37skTZubeX0pVJegtE4iO7hdbc+2/ZVZNmQU3EAe7pMBhU/94Fem55LYOn3zYYZRy4QXahVC7w651addfR4FJE9Xual67i0X2fhZnwQu4h/HXDD9lWmCtWYAudEMR57yfQ+s1503i/NQ2u7U3ifQLeSY9/kT6hSOS6NQh1ma3U3i65vH9UqjQwgxRyh/Oo+Sjj7L0DVDEOQ9C+fr2NRVPvEmSfnOIqbDRQOKCn/Hg/SQeL2bN6/HRASOuoszUncsXzMTNTutLU4ZfzmOk+DGZ4YUw5giUzl3Aa853dWsXcZ4+aECbBNRE+vLHn6V4EenDuE15bN8Uy549p3Ebdv5wY2+eKBD/sKHs2XOH4f4tsQCDp5xCwZNPir2s+rd4A9y/d5AsvnLp4pFJ9LtB1trkC7PS6ahUa4OtIs4fyM+mPn5tV33ViuEiCIAACFgkAIHeCpgizp94bpcN4bTEeTRaZxLp140lmnGMuU3jBvPmz/87mkjc462adPqzX/sH+QYYbxonm8Jlv/5PSr3kYkvZpF1zNWX9/RWSHWaNTGYjs996g1LOPccoaJv7ckzae1kBuo+Fus5JNC3xpvJxMTOzAzTZag+jTc5d64IVcR6tebyKdJnheYpnwl89KJU3TjQWjpO7+ei7Y9MsdyBlvWbGww9RxqOPkCfbeKdHcWvP/ugDSj7icPNfHnajz3xiOmXw7JjRcWmSqAyi5XAeSQcdZD6P5pCZKT3puIkP0ag+x/IVfW68FSeN6TeVjp34F8oIdrecFyKAgBYBEeerX/x7y4ZwsuZcS5xH02gR6c0XxN09nkT6yYMD9O1x6bQXL6ExsgJus/7ObZd481idrQ6e+FvKfu9d8o9V3429dd6yoWvmc8+wqL/dtKeNxP8DDxp8dUwajeFNOY2sd5qX3j00le7dK2jQorRNSVJ/tCCHHmXBbea4NHFr/7hXAR1uUdS3zRlXQAAEQMCYgO82NuNgnS9EqKycj0z5USl4z8MPMZyBUZ85lzXnxps1yZnNqf37Uenc+U0vfT6apZR3hU3r14eSC3TOJusArL3TiM7jE8ayeeBcllhXhYnKQ00F6Z1KdCBPWJ5VSPTCAURD1E9oMlVqb8+eFPzdieRlV1iZ1WvknXAbKyuVuDLzFthnMt//reISb0Zkq2UqLnPBk35H3rS0pjw4/UbuOCl59OrFeeyjjNyLK66Py2PXREpMYsF9PO+kw8vc+OOhHfyMBZuMcI3g2dFDk3x0XaqfruWPjLI7Mk57y6efK0nk87m8AY2jsszksXLlStqxYwf1YOb9eP29E9v2xf+U49DkNxHsbn6vARHnK2Pd2iewW/tZbWfOY8vn5R13cyaMpfKlv1C4oun7U71+I4X4v7NG8aZhTlnHZmjhb1kvedqQJHYv9ZDMkJfVN1JNpCkBcRuVzeAu4pmdaXunODpD3V9YSMGpU5tmrngn5MayMqLmUyV8AwfwBk5TePDpbEq/8QbyZmVZqEFzUGboHz6cgsexcObTDTzJyTvz4Hu+QYOU9eap57P77/9da0rIaxVCNovrnTuBeuWMJZ+3acarNlzOG/U3KH/Lju/98vemvQvPo8IeB7OAMO6ka+XV+vqOWT+THN2XUTiYMoYMMhMlrsM0NDTQzz//rJRxNB+Zl2Jw1F1cV8Zm4Wo3b+F37gLycd27/drcGi474jxavNQ+vSkpO4uPVl2sXGoIhZT3fOaIYRTItOcubbPqqtFykz10WmES9UrzUCq3R3UNRCV1jUrYPBbl+/EGlyfyLPPT7EbuZMd0WWYmQl0EuEdO3aito8byciUfuRfYa09KPvYYZdBP2hU71i3FS2dwXWQANI1PQqnhfoq0r2Ld+IhK2dhOBiWe5kGGYdn22wh5Uw/ld8wJ6akU4LYuyJ/yhkaq5Xew2EB2hT8gJZnOy0ynG3MzKcuKZ6BOxcNVVbT9mxlKiB6/ObBlqaROFNwCARBIMAL2FhR1MUgt4pzPZFaMG+mBLB7MiPMoiszhhTTo/HNo1XMv8Is7rOzuvpLd3QeffxZljrT3kmovzLLW62oeAJeP2LYaogi/j3qyQHfTRJincKc+upVKw/YiZeLMm+/eoIVsPpPC62hb8ti2TVkn52QjOS0GQ1iIicu7GPd9aC1D68FTEDpHWmsllTDXo+K8ctWaljrnmBTn0Qh+HoCRjePkqKOajZuVy0Xffa/82+8k3gitA0W6dCBvmtC0QYN06TZWNVAGdyizZCTHRfPyQF8qb8KoGHceI5s2kZf3fDAz6222GDJwJp4pLXls3EhenrnXOvbQbLpq4bpnjSD5iDU0hKmybjtvJsfHKLokyNXyxLXEJuBEnEfJ5e2zl/Kfa//5pvJv00z6M1TIu763Xo7TUaRlCdvZQ5P401SCUha1laFGkplmV1sk9u4Jnnaq8hGTQUMZHFeWvbjUHvMWMCTLiS5sPmyiuLaR6vnFK+vMXa0Ll7/A56VrspsGWZR2PBxRxDjOOe+obzLyBQEQSHgX97rtxU1rzh2I8+jXKCrSWx/BJiK9au36uP6mdWN167Y4V6uwiAw3xblqHnJWuoNd3tXSVLsmP5yBMnPqdk9BLbPOeo2F5Cr+/jsR59GqR0V6Sq9Wa9JZpG/64JO4oSNfhT7cEXZbnLepoMxqs/eIm+JcNQ9ePtIe4jw2L5lVF/d3iPNYMvjbLQIVy1fu6tbOniJGbu1aeYtIV45ga7aoSA+VsmdLnJnsbC5tUnu/pjzsuSNec26JczWM4gXQsx3EeWxeSjvOa8whzmPJ4G8QAIHdSSDhBXpyfu7ODeBk5lw5Ss3YrV3rITWJ9LNbXJbEDTe1j7WNkbTSxnUQ6FQE+PfU7cD9ydN89q24qptxa9eqoyLSL+cj2JpFeoBnkHP3NnH+n1aCuA4CIJAQBNIG9FOORxXziji/RH1DOLMwRKT3ayXSc/ee6Ggpktl8EQ4EQAAEQCAxCMDFnUVEv5NPUHaRTh88kHIm2hfn0a9M5vCh7O5+NhX/8BMNOOPkFoGSGF8p1BIEdhLIGjWCfwtnUcnsudT/9JPa7NZulVVUpK95+TXq89tjKditwGoSCA8CIJBgBLy8GaK0Q2teeU1Zr662W7tVJPnN7u61W7ZRn+P5tAWXXLutlgPhQQAEQAAEuh4BCHR5pvxi7StrWV00EenygYFAohPI4j0Y5OOWiUgfcvF5biWHdEAABBKAgCLSzz3T1ZpGRbqriSIxEAABEACBhCeQ8C7uCf8NAAAQAAEQAAEQAAEQAAEQAAEQAIG4IIAZ9Lh4DG0LUclneM0pJprNn5I6ogl5fNQXb34ux6S5teGLHLEmefzEm6vzySJK+pJPRtPpR20LZfOK7O4aXryYwgsWKin4x4wm/8iRfESLe9vGV3D554cbaE64kaT4E/iYmTF+b7ts4raFYUk+C/nTm4e4JvARbEN5wzj7h73YBItocUNAjjOaWxxRPpm8i/se+T4amePjI9jcLWJDSQmFFy6iyKJFfDZ6FvlHjyH/MPbU4dlBt6y2voyKKvl4vopVFEzKojw++iwnrX87bOLWSOU1W6i4YiWVVW+irNTefMzaEMpIkSP83Grl3KKCdEDAHQL8mqLlZfyu4rZCTn2Q877Hc3vRw8UdR+t5g86lfJrMgroQVfCRfKOTAzSajxMzc963lVo28nGPkWXLlHd7Ix8d5ucj//yjRpHHwdGgsfnLkWdL6kO0gD9yatwYrsco/rTHJm61oXKlPSquXEXJ/nRujwq57etHspElDARAAAR2JwG0OruTtom8FpYQXfwd0YytfHSJSvgevOP6bXsQnS9HQKvcN3NJ0r6ST6kScS7CvLVJmmNziR6a3HQmupn0tMKEZs2iqrvuofCSJcrRULsYr/n3jxhBaX++iQKTJmolYXj9q1AD3cQjDUtYLMfyEvcQEer38YHvk1isOzE53vpJPuT6Cf5sjYXG96RvdQSfC3MvH8PWjY9egyUGgbdXh+iuOXW0qlwO3tvVeNyG9uGzhx+cHCQ5M9228W+n7r33qfqRRymyYUPbZFicB/bai9Jvu5V8A/q3vW/qSiP9svm/NG/tG1RZu71NDDmjvCefXb5P4QXKcWhOLBSppdmrXqWVW7+i+nBVm6SSuGNc2OMg2mPgaeT3NR1h1yYQLoBAJyOwtaaRrvuhlj7dEOZzvWPfVk3Hh10+KpkuGplEclyaHVvBovzWHWX0U109qWRB/fkI0qtzMuio1KCd5FvihJf9QlW330Ghn3/mM1rl7bir+QYOVI5sTDr0N7G3TP+9iAX5rTvKaT7XpW0OREP4jPIbcjLp13xOuTNrpBVbvqK5a16nilruHMWYiPOe2aNpMrd9ctoEDARAAAR2BwEHvcbdUbzEyUPOIZ82n2ex3yX6TkOcC40tfGb5RSzgj/yUaEPbvq0usFp+y/3fj0T7f8Az882z5rERpNswbwfRwR8RXTGTSGbZrVpjTQ1V3X0PlZ1+pjJz3kacS4I8qh/mWcCy006nqnvvo8boMXcmM6vigv6pMkxTy0K0WEWcK1nwZzbfO6w0RHdwRWT03Y6t5IdzJOdzC6ehJs4lTe570dt1DbRPSYje5X9hXZtAEZ/Je/ZXNXTu/2pUxbnUnseO6OvNYTrgvUp6YhF3Mm18/xqKiqj8kkup4ppr1cW5klGIQt99R6XHHEs1L7+s/LasWHVdMf1n/l303bInVcW5pBVpCNGG4tn07qwradmmz/iKjcpwrK1li+nfP11FSzZ+qCrOJa/6cCUt2vAe/Xv2n2hb+TIrVUFYEIhLAjKQN/ndSnp3TUhVnEuht1Q30k2zaumoT6o02xStyomAfa68io7ZXETf16qLc4m7NhymK7aXKJ8Si+2EkjeL8Zqnn6HS46eSDMCriXMl2OrVVH7pZVRx9TV8Rnq5EtWshXhA8pHSCprKdZmjIc4lLRmMOG/bDrq+uIy9BOy1RzX1pfT5wvvom6WPqYpzyaehIUwbd8zlduuP3G59xN0Ze3mZrT/CgQAIgIAQgECPg++BNPdnfEV0A7/v6k32rT/libTx7xCtNynSRSwcxKL7wQXmu9bTWVtPeZ9IhL1pY7EgorvmxZfUhXlsQvyyq/nbC0ocERpmTMTwIaX19ILJggnSh3nme2p5SHUkXi/PBSzwp3BePwpAE7aD63NORYgeqLYCzUTCCBI3BEScT2HRLZ1tMyZfU+l4n/91jSVZ27BtG5UefSzV//dzM9kog1xVd95NFTfcaCq8BJLZ8ndmXUUbdvBMmAmT2e8ZvzxFM3951kToXYOs3vYtfTTnz1RR03aWSi2xcnZ7/+jnG2htEbv7wECgkxK4b26dMpAny2DM2PdbI7Tfe1W0qMTcO0RSvYoF930l5SSu7Wbsw2oeCNhURDsi5t5rSpqctojuqr88RMRC34yJ50/JcceZFulSmvO2ldDjZZWm39VvVFbT8Szmq03WPVpuGZiUAcd1RTxrYcLCkTr6fvlzPJD5hInQCAICIAACzghAoDvj50rs11cRyceq7eC16ed/Y05w3zeP6PttVnNomk2/3VzfXUm8evoTyhpZqyZr2KqffMpUtDurw7TUxnTkTBbZ01mom7V6DngxbwbAesyyTeMyzlXzMbScEiLEEwH5KvxpZq0y22XVZBbtrVXmRL10hitvupkainkdikWre/sdqv/sP4axZCbo22WPKzPWVm3ppk94VmmO6WjVdTtY2D/D4a1xk4UrM5Y9RbI2FAYCnY3Az0URemAev6gtmrjAX/RNrakB+39X1dBHLLit2laeDb+N3eHNWu2bb1H951+YDd4SrmHjJqq86y5T8V6pqKLvaq3zWsMDBvfyAIV5a1Q8huy0K8u3fG5a1JsvD0KCAAiAwK4EINA7+BshLuuXzbBfiM82Ej1v4AU6l/v4d861n8cDPOtuRtyH5y+g6mesz6xFS1b91NOK27uezWCR/bQFkR2b1j3spr7MpLh/gEX2IpsiW4YBLuaZdJOTJrHFxN9xSkBE9ntrTYpslTpc8z2Le3EBMbDad1hkf/WVQSjt25U330INO3itio4tY5G9uYR/3DbtW55JUltD3jY5Ftk8625nIEDSkk70TEXcw0Cg8xAQz5mLv6mxtbRFarlgR4Qemq8vVkVk387rtO2azKTLx8gaNm1Slq3Ztbp3/23oCbSGXdbvL6mwmwX9o6KavjUp7pdv/sK015Bagb77xZ64V0sL10AABEBAjQAEuhqV3XjtUd7YXGbCndjNs/XnpW7niS7ZOdauyfKuWzgPI6t+9FHNNWlGcZX73NmofuQx3aB3seu4sbzRTkJmxWV228hkV/iHHbqpyyz/m3XmZ+yNyoT7HU/g9tnOfqyl9Y00faFBGjyzXf3gXxxVVsR57Uu8Hl3DZPZ89uq/a9w1d1lcRJdu/Ngw8LayZbS++CfDcHoB1myfoeysDAOBzkLgXytDtIx3a3diD7JArwxpv/Fk3Xm5nbXkrQr1oImZZxl4l13anZjiGq9j09mtXXZsd2J/MSXwG+mn1a84yYbkpIslGz50lAYigwAIgIAeAezirkdnN9ybxZu1ObVtPAu/nr1U+6Wrp/Rj202Z1QPqXJVyilDX3KCcX6yhebzLnUMLz+c05CXtabuNrcjquU5GGprLJhvHGdk8zscNaS158ep6B8ZijY+ps2thk2sF7aafSPG281qHdZXOOtzCaza7vepZw5Yt1LDdecOg93ssr9lkcvZbr6RE2yuW6wfgu2bCGCbCAYrKl1Ne+iAzQW2HifAgYR0fHRXvht91vD8h49+5mRrI627BDt58tLv6eY3z+Bg1p7YuHKFSFvl6R7Ap72WHFlm5khorK8mTrt5Rmc+7tju1xbyPjazDT1LpP0TTrqwtUgS2U3OrXXNaDsQHARDomgQg0DvwuYrgld3U3TA5y1xNoG9ibbfZvr5rKVoZTz2vZO+zwkz10kY2buSNYJy/9GTmr2HzZvL26tUmo+U8I23CO7hNvNgL6zgdFX2jMwAAIABJREFU2cwtV+clLuecu2FOBxQauJwvv/iiG0VBGg4JyBnnbti8Yh784a+X1lFKsh+DGxZeKDtCqg92FfFZv26YmXSKK1a4kRVJXsNcSUk7kTVr1tCnn36qHQB3QMAkgTkGA3EmkyFJR02gS2u02AVRK+WQ89L31ziurLGed4VfarCOzkxluC2SU13kSMhYq+LO0Cp2cXdq8tpexunIWelaVuRaeyTtmvQT2k4maOWN6yAAAiBglgBc3M2Saodwq1jwivB1w+RMczX72aUBAElbbzDBaO24Wtm0rmltMiez2m6Z0QZubuUla9idzws4q7WHByJ69OjhLBHEpnkuCfRq/k6sUDk3PYo4vIiPT3DB5Hgj1XPTOe1ilwS6uLnLUUV6Vlzhjmu6Wx1rvbJ2tnupqamUmakxatrZKtOFyisrm5aUujOgpzUwKILWqUt4FPkCHaEfWc5eMi55Ymm922Xm250h8abBBr2vkltLZepCFXwKhosdLL1C4x4IgEDCEcAMegc+8qwk9zLXSitdeyDZcuYZOml5UtMsp6cVwZOunlaazoy3Vlpa1zMMBr3TXcoryPmoOydqlWzX614uxxlnnGEusEaopKQkCgaDGndx2SyBdL/Bl8ZsQhwuQ6fl9aSlWkhJP6iHBZyaBXxufR885Pclq2XRcs3vUl4BX4puPm7c7Nevn+PfmxvlMJtGWloa+XxOWhizOSGcFQIBnvpIYheZkM3zuVvnlR5Qb3dSXXpHSV7pmmvXeH7YzXc7f1/VzM13e5pOXSRv99o+d9NS44JrIAACiUtAp5uYuFB2V80LuI/cn5djrbV+ylGbIk7Mb3NJuTAhT/26nataeUha/tGj7CSpGsc/Sj2t8S4JJHEbGe3Tdx4Z51Je4/xe0s9JFUGrix7MkBkh2k33x+e5I4QKeNSmZ5r2t8Kt35IsE/HmqTcAeRmDXaGWldqLO7z6wjmf83Jj9js/Y4grZdZLJBAIkHxgIOCEgGjEcblemsFnmjs1rXanl9+nrBuX9eNOTc8l3Ne/H3lYWDvdJE7KqNW2FQb8FOABh5DDTeIkD726yP28dHfavvRgN0oOZDhFj/ggAAIgoEpAu5eoGhwX3SYwSUNYW81nD/V+OMnM+tAsq6m1Dd+bJ+J66PTDvTk55O3ddt1425T0r/j69iVPlnqB+3CvJ89gdFw/9aa7w1l8p6hPSrREn8DC2g2b4JLQd6MsSMMZgTHc4Xbh60cT8n26qxb9o0Y7K2hzbP9o7XTcErtm0slzSViL0IeBQGchIL9zN2xCvvq7SF5hY5OdDyZJKYfrrNkmHgTQEtaW6scDX/6hQ1WjiDgfwSLdqcns+QCDdNxqR8y0fU7rg/ggAAKJS0C95U9cHru95gc517QkIl/LxV0qdGBP59X6tYk0kvae7DijwN5tN5CJJiodkv013P2sZDxF/A8NbCQLa71N5Ayit9w2k5fZtBCuYwmk8Xdvogud7ik99DuinqxM8o8Y4biyer+l1ORcyuTZb6fWI1t7ECCado+skTwgYTAiZlAQr8dH3bKcMzHIBrdBwDUC+xv8zs1klMfeNsOztYX+5KDzdXLjkpN4wFr/9xmY7MK7feIe7BOuPaAwOai/VMYMr725LkZvd5n1zkkfYCY53TBm2j7dBHATBEAABHQIGLVlOlFxyw0C5/O2xHsV2E9JdoJ+eop+/DsnEnXTmf3Wj02UzX2Aadq6uSV66jVXa85+G+Uh92UWXtLQszvT/JSu35fQi07deYT9hlR9gSQJSLfngXTjcHqZHZ3kpUP4A+s6BB6cHCQnzhUjcrx04QjjTnX6HbfxD8L+d0eWiaScdqou+P2GXqx73+hmt6zhVNjjIKNgykDAmH5TDcPpBRjX/yRKDzpoKPUSxz0QaAcCh/X10xH8cWJ/4fZGbzz57Iw0GmIwY6yXv0j/O3KNNxlMOe9c8g3or5eU/j0W5um33qIb5tKsdBK3fbsmgww356p738Wmue/QixwNGsoSoWG9Do1NFn+DAAiAgGsE7PcAXStCYicknf0XDiBKtvleumk8kZZ7e5RsPq91f2o/+5wf24eol/peU7sk6i3Ip/TbbrWdUdrtt2mumY0mKm7u97BIt2uPs+jONinwpyZ76Tj+2DGZff8L52UyKztZIE4HEBjH69CvGWtvpkd+609PSTH1W/ePH08pfzjPXg25M5xx/zRe8Kn/O5EZoBG9j7KVh8+bRPsPv4I8HnO/j/EDTqHstH628pKzz8f2/62tuIgEAh1FQNr+R/ZNoZxke2+BEwYG6PgB2jPOUq9kfs88mJ9teyPSK7IzaISee3szPE9KCqVP4zbF5qBh2h+vIt8Q/T0kZKO6aXnmBLbaM70uJ5P6mRT43TKH0ei+x6klY3jN6/XTAdz2iVcPDARAAATai4C53lV75Y50FQIjspsEtNXJ1iP7Et3IAt2MTeXB7z8ae6O2SeqC4USn679Xd4mTfNSRFDzj9DbpGF1I+f2ZlHzE4UbBlPtnBH10On+s2lUpPvqNBcjSrXqQBwNGaB1YrVGAVI74FG/T3c2NBcsaeeByxxG4mgX6Ib31xW9s6eQrdNeeQRKBb9ZSr7yCAvtYdC3lHb3Tb/kz+YYWmspm0qAz2HWcf+QWTDqoMgOVmWJi3Utzuj5vgH414ipKSeLGzoKlJufR/iOuRGfYAjMEjR8C3Xmzk6d4UC7V4l4ko3J89MDe5k5akE3RbmBxarUz9ys+9/yiTN6l1qQF9phAaeLhZuAOH5tc0iEHU8q558ReVv17X3Zzv4Jn0q3a0WkpdHqGiVmEVglPGHgaWXVTF1G+T+EFtgcbrdYL4UEABBKXgNU2PXFJtXPNz+b+9Ozjide4Gmckx509y27t77OHlQW9SX/Zm+gDjtPTxHtMdph/6xCe8eOZd0vj//zyFle2zKefIm++cWVk1j3z2acp7eY/G1e8OYSUZzrPTv+NQZhZJ96LhfJbWQG61cbMez7H/ZJ9/P/I4t7Mj2U/9kecweEPtfJgTNccAeOBgLicvvGbVBL3UzMd72FZXvrPUWl0kQnX9tb18/DxeFkvvsC/jZvIY+KYPBHl2W+9QcFTTjGNSY5AO3L83TRp8Fk8OWY86CCz2cdO/AsN6XGg6TyiAXPTB9LUPR+jQd32NxVX8pi656OUY3Pm3VQmCAQC7UzgcHZzn3FcGu3b3XhwTgbyxEPny2PSSNafm7VzMtPojR75NMiEu7scz3YXu4L/tVsuWRw3oJTz/0BZ//wH+fobu7vLzu/p995DmU8+wWeNGtc9WtcreVb/793zqLeJ2fBMntF/iD0IHuGPmfdza54yaHj4uDtoryHsvs//bWSybv2YiQ/Q0J6/MQqK+yAAAiDgmIDvNjbHqcRhAqGyciqa8aNSsp6HH8KDvuZfdh1VHVknfs5QolwWx/LiLAsRVYWbSiMu8LIZ3NQBRK/8mkg2l7NTo0L2IDuX85DjWfn/qKiWKCz/wSZ5yADBiQOJ/nmQucGCppht/79v0EBK/u0JnDhXgI9OaSwtJYo0HTnjSU4m/5gxlHzkEZT5yMO2N8QawZBODXqJMSl1KebTZqKH2kjfZg9WUieyi/rzmQHLs+CtayTP4lcsuA/mTw1nJPntaGYm4UTE78t5XcYifhoPHOQ4nTlnXls+/VwpQv5+kynAm4bFg2374n/UUF9POXuMp2D3bvFQpA4rg/z29uAN437LbqjVkUaKNHqouJa/580lkrOL9+rmpzMKA/T0/qnUN91q97E5IW63AuPGsXfJEUQ1NfzDbaCGEv4tNR9H5MnIIJnZSjn5ZHZBvY98Pc3PakfhSdvYnWfRB+RPpkhDPScdobpQeQvbJH8a3x9Jw3sfTvsNv4xSk3Jsc5cz0wcU7EO5aQO4DYpQOFJLoUh1S3ppvM68V85YmjToTBrb7wTuOBuv1zdTmB2zfqa6omLKKBxMGUMGmYmCMHFOoHbzFiqdu4B87H7d7dfmBn06qkrZ7OZ+6pAk3gvGo7x7y0KNVNP8bpcyFfIg3sHslfPYfil08uAAWXTaUqrVgwXtSemplMS/Z2mH5Pg1zkYxkcfiyn5wSpAeLsih/Xj23E7/QUmrV08K/u5E8ojo5vSVd3tI3opy06e8z5MOPpgyH36IApN5VsBG36tPc10kqlShhOsSxSXv45Fcl0NTg/RoQTZN5I3h7NZF2j5xdx9QsC+3RXXc9jVQXbiCc2wCl+RPVTyMhvU6jPYfdjmJR48bFq6qou3fzFCS6vGbA8lrYmDFjXyRBgiAQOchYDxl0nnq0iVKKrNzV/Ex4PKRV8TGKhaDdU1u8HqbxVipfA4vob2/edO3MIvaxaKdObPR3O92Kw8pj2z6lnbjDU1FY6EeXr5ceVn7ZS2awfpYs/URN/L7mmfG6znSEh5tSOK3dSH3cNz+ck/iRcSTMpqEVjnzWsLwenM+vbkMdjsIZuuJcPFJYAB/Hx7jdaZitTw6tKgkwicqeGgQX3c6TtO6xr6BA5TZKLFGFuqRZcvIk51Dvn68zsXmutDW6ct/yxrxKcMvVy6LcN5RtZZSAlmUkdKdr7j7De9fMJnkI1ZbX0ZlNZsoK7U3BQPxMRilFAwGAi4SkPbgvOFJyqfp3d5AG6oaaRRvHJnhwukkUtQgv18vZxdx+cjp6GtCYargEYFhSX7lnlsma9JlCY5iPPAeWbuWGiuryDdsKMkAvBsmR6ZdzbPpShb8WcV1qeOByaEsZmUQwk2TtmcKDz6KiVAv4bZPdnvPCPboFJM7brJAWiDw/+2dCXhdVbXHV5J7b+a0GdqkbTrTNm1ToC0doAVaGUVRUEBRUeFzoIqiIiD0+eQJCAVEQZFB4APFB4pQFXwFBGoZWkrpQNOWtHSypSNJmnm69yZvrZMG0uQMe58h43993/ny5Zx91t77d+7ZZ689rAUCvYOA3zZM76hVPymFfIIK09uOoKokjquOzwlKewe9bJD7ETrKrqQy13aC7po9O4U217L44czxczTDJi9c6hsExC2CH2HYnGornWNxIhekyNJ3mVnqDkmJDCI5ICAwUAi0fdsTje97UCJDySpL3j3nz7PmSeOCXZUiKwAmdNMss6zyGZLFywwhIAACINCDBFyuu+zBEiNrEAABEAABEAABEAABEAABEAABEOiHBGCg98OHiiqBAAiAAAiAAAiAAAiAAAiAAAj0PQIw0PveM0OJQQAEQAAEQAAEQAAEQAAEQAAE+iEBGOj98KGiSiAAAiAAAiAAAiAAAiAAAiAAAn2PAJzE9cZnxp5K43v3UqxkE8U2bTLCmISmTuXQZMWUVFTki5dU8Yq6jV23r4+20Hr2fC4eX6ezg7Xp7DVuEv/17YfBHl5j23dwPUqM+ohIPULF09ib+3it+KhWj0oCvGzlOqxnr+pSF3GI216X49jLunoEVqscPj5fw5mtLyd6p4xoI/8dmdEWjk5C4I1ghz/++pZ1Lg9S2BOQUF5V9R9QWc12PnYYifMyx/NxHHsNL2RP695/Hc38vpayh+GSpihtao5SJnsfPp7DAE1LDtModo7o12+itamJ4qWlbe3C5s3sxX0wv0f8Lkm7MJK9ufvg2Vg8GFfU7aZy5lVes4udt2UZrHKZWWaKhNbzqzbsvZ1DuZXzM5FnU1W/nwazJ+Vczkuej3hQhoBA/yPQSnVNFcb7Jb/7uqZyyuH42vKO5WSMozA7Z/Qq8i3fI+0Rt0VyiBf34qPtUZGPHtAlXNzOGv7mlsX5mxinWo7pNj03iaZz+Mkp2UnEUUk9i4Q9kwgP7bziLdGP2qPs9NG+tN/thRTdFbW7jO9Eee0OSg5lGnnJkZnqb9vnGQwUgAAI9HsCvtlh/Z5UN1Uw+tZqqr1xsWGgHyN/fabtX+7wpy26ktK+s8hVqDIJ7/LXpjhdXxujI22hPrvUTDyU38yhyy5jt9Suu+NstDQuXUp1t95GrdUfx1TumFkCx/fOWLyYki/4rCvjQor/GMe2+m8OFl9rUZdcNpbu4Lp8juOhexExzK97m+ih0vYIqV21SQz5R08jmuY+THRXpTjjkkArbT/4b1q9/VFqjtWa6pD43rOPu4ImFCzk6/q/dBnkeqCqln7LhxjpZjKC4/neljuI5qV4CD3EMYbr73/AOIjDFZqJGOgShi0852j8RLNENuekc7p+91O0ee/fjfjkZmKEIpp0lREX2IuIUfLm1vtoX8V6SzUjc2fRKZMWeYq5bqkcF0CgBwhU1O6mN0p/w8bfTovcE6iI422fNP5rrg311xua6MaKKtofO/Yd/svRHCU8mYRg+zYfXoYmX/ogRlevbKAD9ce2e3+gtnjoEtHixukp9N2pEVcx3aW4/yl7i1Zte5AamjkObAfZSi8Z/0mkiZljv0KTR5znKRRaS0uM3v3P07RxzzOWbV9maoHR9hUM5vi3EBAAARDoBgJJN7F0Qz7dnkW0qprKVrJFxTLs3DM9NeDdUXiJbVx/+xKqvel/LA1aoxwtLRR9+21qXv5vCs2YQYl5ucrFO8xD3otqYvTLhjg12tzFYdfpheYWWsuz0adyKLFMzZm5lg8/pJofXkMNv3+YiGf9LIWvNf/rZYpt2cKGxVxKSE+zTNr5wj6uy9erY/QgG+gS/9xKGrj/8A+uy1ZeLSB1SdOsi+hdfoDoky8QvbLfKpe28wfqiR7Zyh0HHgs4mQfcXcfBZmPv4IuvGErz5s2lMA9k9AY5/OoKamlupuwZJ1JKvswo9E6RDt2KLb+ikr1LKd5i/esQo3RP2ds8O7OTCrKLuVPcFs9cpVbbeYbqG4cr6O91HJPc5gaZvVrKacr5vZ3DRnpY8/cXK91K1d/8FjX98/+Md99KZBCs6dml1FpVReHZsyghHLZK2uW8zGK/VHIzs3iL4zObDzTITU3RGh70eNWIkZ7PHVX91QdtgyavbLqVKus6DUB2KlU1z5q9f+AVykjOo+yMUXxVfwClo8qKNeuoqaycMifwSoDjgg0J1QUwTgRCoPHAQarcUEJJHHZw6IJTA8nDD6Uy4LVxz7P02nt3U31zha1KmVXfdfgNnk0fSxnGihU1qeN25udHqukWPqTNsRJpq1Y1NtNrjU00MzlCOUl6A9fVza10zVuN9NN3mnjG3CoXHkfkIizfH6MVB2J0Sn6IcpLV39+maC2t3HYfrdv1v0ZbYyUtrTEe5FtHB6s2G4ZzcoiXs2mKDJr8q+QW2vXhm7Ztnwzybj+43BjsLRjEbV+it7mtWF0dffj6SqO0BWctpMRuCiGniQfJQQAEepCAXuvcgwXt11lzx7v6ykXU8Ic/KldTjNqqz19E8Z1Wo/HHqqrjD+Y5VVF6no1VVXmZ055RGaUq6+99F1WttbVUedElPICwvMs1qxPNr7xKlRdfTK380VKRCjZgP8HlWs7L81Xlb00tdC7Xv1GjLqL7ZTbKz2DbaLf5JGyX7KVIi98humpVl0s40Q0EorF6en7ddbS3fI1ybpL2+XXXk9yrInt4durCA2XG8lFV+VNNPV1xqMLYSqIq8m5XXXQxxd57T/UWow2pvvI7vMxD7YcuHVSpe2XdHqU8xIAv2fs3Wr75Tk6vlke74s17n6PXS+/lTq4aZ+kMr3jvV1S6j0fHICDQRwms2vYAG5t/spyd7VytmsZDtGzDT+lAZUnnS6b/i9F9OQ8WPsltjKq8y9txpA3b22mm3e5+3kFGF7xUT0+8r97urT4cpwXP1dG+OrWWTwZNl234L9px6DW7ohxz7WDlJnpu7bVdZtqdFMggoXwrZFm7mrTSlg+ep1c3387J9do+Nf1IBQIgAAIfE4CB3gt+DY1PPkXRlfoWnexJrbnuJ0S8z9tJfsbLwHfzLLKuHODR+Bt4Obyq1P3iNmrZ7zDVbKKsZd9+quMVBCpyLZdHVgPoynau/8316nWp5n7IN17XzaUtvSyFf/EDd/fiLvcE3t7xGNU2fqitoI7vkXudRLqZ15VVUr2iAdxR35qmZnqsWm0QSt7pmmuvJ3nHdSW6ciVJm+IksrTztdJ7lA2HjvpkUEO2EKhKVf0+WrvrCdXkx6Rbs/Nxqmk45Ope3AQCPUngg/K1tO3Ayy6K0MrL4X9L0XiD472PcpuyltsWXZE27PrySuVBw19vaqJ1vN9cV2p4b/r33mxUMmk37P4zHan7j24WxuqelTwQomo4y6oGGSyUAQFd2Vexgbbub1tmr3sv0oMACICAKgEY6KqkAkone83rltzhWnvs3Xep4ZFHbe9fwdO6j/BScLfyJO9ZlyXvTtK84jVqfPqvTsksrzc+9WeKvvGG5XW58HeeCX+WD7dyPy/vX6U48/7j1exsR3Hm3Kw8YtxX6vebzFThnAIB2dO87cC/FFKaJ5F77fZFy12Pc2dYDG23cldlDe3k5fFO0vDwIxTbuNEpmeV1Gezq4seiU2rZd3mEZ9DdyurtDxtOrpykrTN8j6vOsOgWx3VvbP0NLwrQH5RzKhuug0BQBGQFyJvbfudafW3jYVqz43Hb+2Wrzd3cpriV1bzc/Yka50HDzUfitGSD/mBhe7le5eXuj2+zbzc/rH6fSngrgFvZU7aaZ97VRtQ37VlqOOlzKzKYKysdICAAAiAQFAEY6EGRVdTbyEtSZf+5F6l/8CHbJa331rs3ztvL9Ss2bJ2k4aHfOyVxvG7UxUbuaXA2bmxuN0bx71GoSxlvfXuY95N7kX284vBP7vsAXrIekPeWcKfLq4ijICuR384D1R5GbPj+JjYyH3PqEHOaeo/vkrQpjX+0nrEWo1n26HsRWaq+db/z8vNDlZtJOt9e5KChw+ML6aUAuBcENAnsOLSC6tljuxfZuv9Fnh22bnOkLbFyUKma7/3s5NJJ7tvcTIrj2paq7t5ob6Bv4q0zdj4wLBV3uGDXfrcnk4G+jR7bPtkbX7pvmUqRkAYEQAAEXBGAge4Km383SRg1ryIOoqxmy8SokPBjXqWEddiaxryP3o+6xDZvsXSG1cSV2STeZzzKBgUdazmMmh+yznmC0Y9sBrwO6XSVcWgcryIO46xmag/xsvOyuPd3SUKx2Ul8zx57R5F2N3e41h7W0Cy57L90s7yzs6720HWdz3f838tMVRB67MqKayDgFwGVd0MlLwn5ZSUS2tGrHOY2Tdo2O5Ewal5lT20LVchH3ELEWaVXqeJ2LWrjWE701zQcUPY3Ylcev56vXR64BgIgMHAJwEDvyWcvMcLFIPVBrDrje3jftVU4NZ1sxRv6+zZ72OO7d1NrvbqTGqu8W2tqKL7H3MPze5y/9+4I0SHev37QYQ+7xDn3Q97R3w7tR7YDTodfnS7Z8ykexM3Ej86w6H2vOUZRm+XaVu+yWZnszsU4VrqVfwq/jOa2TrV1p1vK51dH1q8y2zHDNRDwi4Bfv1er90dmzks5BKMfYufwsp4HtLdWeh+YlHJusDD0ZQ+5H0vGZQbeyembX89F2j6rwVw/ngl0gAAIDGwCMNB78PkbM2Uel7e3F1+8uptJiY1RbZbe7txGm5n42BZ1T9N2ecg1y7rY5O+ks/P1jQ6z6O96W5n4UXabOYQrb+GHBEygXNkTr3NBrDp4Wxxmvp01t6WQjvUOm33oOl7b7fKUtsVqsMuqjnb6zK41Rqt5H7r9y+JXXn7pMasHzoGAnwRkdUplnT9eQiss4qbL/nOHz5hylWTQ0Eq2HGlhR5JWV/XOb7Qw0CWahF/i1E44XVcthwzm1jQeVE2OdCAAAiCgRQAGuhYufxMn5qjHMHfKOXHoUNMk+T4+4XybwN6JQ4aY5u/mZOJQc112+evm46SrQD0ktm3WuclEkSTbJLjoA4HUyGAftLSpSI1km+oakuTfg7TT5eu7lJtjWherOpomtjkpsdBTwpk2KYj8ejZ+ldm2sLgIAj4QSOI42cnhdB80yftj3h7l+doeWXcU8lPVY5g7VbggzTwfv9oIyd9JlxVPp7J3vZ5AqeFBXU/jDAiAAAj4QMC8tfRBMVQ4E0gYlEVJo0c7J1RIEZo61TRVcVIi+fWQTwhZawpNmWyav/bJhAQKTZlietuJIX86ChHWPtlB14w80yJon5zJevwptXbWA+qG3MxxXF9/SOdmjDVlV5wcNj2ve3JYKIly+b20klCx+btsld7qfNKY0ZSQlWV6OS9zvOl53ZOD00dSUqK8UdaS61NefpXZuqS4AgJ+EUig3Ax/3jGr3/1QbkPyfTLSp0Ws27bCjETKSfanbT0x13yQc1DaCAolpfgCPy/zOFs9frVHg9KGUziUZpsXLoIACICAWwLWvUS3GnGfFoHQtGKt9KaJExPZqDU3kGXwu8jBGDXV2enkmKQEyrb5RidkZlLS2DEqqmzTJI0bRwlp5h+9oTyDP8xmFt9WcYeLU5mHvUlBdJJPBrpfelTrNlDThZNSSTpMXkU6iladrqJwiHx4lciuMyzlNwaoeKDKq4SKp1mq8KuT6tQZlgKopLEsaIcLuQ4dbxUdSAMC3UWgO373Tm2JSl3D3NZM5LbNSqQlmp5nblhb3WN2PpUbzwmDzLucCQmJPKBhPjBqpsvqXDKv5slIMV+B135PWz7e21ergROrsuE8CIAACOgQMG8tdTQgrScCkdNP93S/3ByedZKlUSvXzw57f8xnKujwoy6R00+z5XF2xIe6KOgo4pVrYzJsi6J08ZxCpWRI5AOBwtyZnrUU5syw1BHhjuwpKbxnwaOcnmqvQwaowrNnecyFt1bYvEsp4SwakjXBcx4jbHi1Ky8YXOw4y+5UkDDPruUPMh+EdLoX10GgJwgU5lq3JarlyUzNp0Gp1gOPCxzaEpV85qVESIx0Ozmr0NqAt7uv47UzhicRj/Nbin/tt00mnLsMwBYMNl+lZ1k4kwsjcrx/b0zU4hQIgAAIGAS8WzsA6YlA8mc/Q+F581zrSEhJoYybb7a9/9q0EI2z+zLa3k00gmetf5oQhnOvAAAOyklEQVTu/IFO+8HVlDjCujPhkA0lFRZS2tXft032My6H0/5xOwUTmMOPUp3rIqv5H7EfK7DLxri2iO2JefmOyZDAJwLTx1zKsyfmvhhUspB7p4+91Dbpz3MGUZpDZ9ZOwRzuDF+SYb5CpON98k4nJNsb8nb5hOfPJ2lb7GTepO+S7CF3K6Py5tCYIXMdb09PzqWTxl3mmM4uwazxlzvuLbW7H9dAoLsJ5A+aQpOGn+0p2/mTvseLaay7aV/ITKNZyU7rwayLIG2ZtGlO8o1JETppiPu2IiuSQHfOtXfsUlz4WcrOGONUFMvrMug4+7grLK93vHDKxEU8aGi9rN9JyYic6TQ+/1SnZLgOAiAAAq4JWLf8rlXiRi0C/IHMvO1WSshwN12b9uNrHJeWp/GA8u8yQq536P4mM0RZ9oPSRpUT0tMp8/bbtarfMXHGkttsVwJIWllmfy/XxY3Ij/3+zDClKNRF9C8cRnSVy4H2sew3a4n3SVA31Ryw98gs66lF33Nd//lFV5EslbeTkbx//IZs833ddvfJNekML8kdrDQqmjR2DMm77UakLcn8xS2Oy+Sz00fT9DFfdJMFO8DKpFMmXsn3qr1Mk0d8imet3O2tH559Ahs6Z7kqJ24CgZ4kMGv81x2XXFuVb0rhpx3fGfmm3ZE3mFJdDhouzsmiEdymOYkMWP9ufiqlOCc1VXXHnBQaJh0RG0lkx3qnFX3f9aDhydweiZGuIrKVaebYr6gk7ZImwjPwMrip2vZ1UYATIAACIKBAAAa6AqSgkyQOG0aZd99l6dDJKv+USy6m1MvUPjJzeIn6EjZsdcbaxQy+iWesFyosb28vY3juHEq/4SdEOs5rQiFKX3wjL+udbVXVY87LMvf/4lUBOn0F8XFzF9d/puYm4tvYyD5vpFKxPko0kp33PrWQKMP9AL1ehkj9EQFZTi2zKDozw5J2Ns/QDhtsvWe7I+JLedbqMj50JINXofySO9Ji4KtK6lcvI3nHdUScwklbIm2KihSPupBngvS22UgneMGUa7RmtBPYgDi16GrK0Zwhk73y841BF/vOvUpdkQYEupuADPgtmPJjklUkOjIy9yRlA3IUtyl3cdsibYyOfDUznb6gsJqnXedE3j9+HxvpaZrf0KumRugL49U+hjm8D/2USd/R3BKTQCeMvphX85ysU32SAZCJw87UuicSyqDTJ/9I+3lqZYLEIAACIMAEYKD3kp9BZOFCyl72T4oscO4sSximrN8/SBm38iwZO4hTlW/y8Pe/syN0vMIHtoiXgr88OEJXp6obFO3lSL3ichq89BkKFU1yLFqoqMhIm/r1rzmm7ZjgmrQkeonLN1Fh6f4Mru8KTnu5i+F/Wdn/HK9SfJhXs/Hku6NcMZFo4+eIZtn7qXHUgwTuCUwtPJ/On3mXkjEoSyrPn3knTR1pvxy8Y2mkG3wTLwt9bGgOFSgMRJ3K+0RfGDaEzk7T9FLM77a84/Kuq4Rek7bDaEO4LVEVGZw4bfIP6BPF1yvNPo3Om0sXzrqXZFZbV8R50/kz7qQTR19iu2xX9Eq5ZLvBp2csQWdYFzTS9yoCQ7Im0gWz7qEJBZ9wLJfsj5YBqTOn3chezdW3uJzLbcsybmPmKfjIkCgSj+fn0M949lzPpCf6/NgwrbogneYXOK9iG8Xe358/N41umZWilY9wumDWr2lolnP/ISt1GH1q+i9oxtgvObLtnEC2DshM+JnTFisNNsqgyYWz7yU/9sp3Lgv+BwEQAIHOBJxb2c534P/ACEgs86yHHqSmZS9QdOVKim3aTLHSUqJ4nBKHD6dQcTGF2et7yqVfpIRBzvvGzAo6+ajh/URjnFZHW2l9rIXej7dSKyeW/dknsDE7m2fMv5qcRF4iq4QmT6bBzz5DjX95mqLr1hl1ie/aZRQpaexYEu/14RkzKOXii9hri4Lla1KZdsP7D1yXt7keG2KttIPrIp0OMdyn87q8ueEE+jIb5l5+6KJPDO8zeXv9o9uI1pYRreHjcAMZS/6m8+SIeGs/nyPmSRpIzxOQmVoxBrcdfJkOV5VSWc12qqrfbxRMvL2LB96hWUU8g3IWj3G5+3WI4b1seB49WVtPG5uitKk5Sh/E4sbKjkkctkg8LJ/Me84/nZ6q1UHtTC+yYIFheDc++RRFSzbxu7SJWvZzXXhwQAa4JCyb+LFIPvccx2XtnXW3/y+Gt+yZ3br/RYNVec0OqmsqNwxlmdWSmexC3nc5Kk9Wueh26z/OVViL4S3713cdfp3z2kFltTsoGqsnWToq+Yj363FDT1MaYLGqD86DQG8iEAmxUcuG99ihp9Le8jXGO1ZRu4viLVHDOJT2SH770h6lJ7sLITL8qOH9XF0DrWpsNtqjrXzEGUQhX5P26HgOFXlpBm9F05xt78hyNBve/zgnjZ7eGaXXD8ZofVkLlVbGiT+9JNfE4/tMPi6fFOZVZO7aCjG8z2PDe/uh5XSocovBq7JuL/dTWkmuCStxcjlp2Nmew7MZhjcPOra1fdwecV51TWVG25edMdpoj2RAsm2G3l19etNvEWUBARDoGwTc9Uz7Rt36Zil5KWjyeZ80DpHWpiZqra+nxOxs3+oj5rDMJl9+dEKvlj+sLXxOZZ+5ViHY8E758peMw6hLba1hQMhedb9E9pN/i2f5v3V0wXs110UMpPQAvqOj2E3ATUcd88qAhhjouTzJYRMe3q9qQo8LAmIMFg0/1zhEonF+YK2tlmHUXGRBWTzL/e2sj/1HVLa0GPtBk13uCbUqgwzIpV75bWrfId9y5Ijhr8GLI7nOecnSdVkq2i6N0WpjT74XZ0qd82j/X+LWt8Wul0fSSo3RKjZUZNAxgBfXqhA4DwLdTGBEzokkh0hLa5yaojW+/u7l7fkMDwjKIdIo7xYfgzVW2qkgEftelq23L13nMXJq4AHybC+j+p0ylhnuCQVnGIdILN7IzGI8kOfOX49dvcSnxvGjebLgqATZ9tmVA9dAAARAoJ0ADPRe/luQDrifnXCz6mZ0U5/YrSM8szJbnfN9kMEiI0GWb+9PzOJOnO4pAk4O4Pwol98dYasy+TlgZ5WHqsMlq/tVz8v+dJlFhIDAQCIgM7RB/+5T+N2SI2iRlWQpCtvNvJQjxE5Au0u6q+3rrvogHxAAgb5HQH0Dc9+rG0oMAiAAAiAAAiAAAiAAAiAAAiAAAn2GAAz0PvOoUFAQAAEQAAEQAAEQAAEQAAEQAIH+TAAGen9+uqgbCIAACIAACIAACIAACIAACIBAnyEAA73PPCoUFARAAARAAARAAARAAARAAARAoD8TgIHen58u6gYCIAACIAACIAACIAACIAACINBnCAwML+4cZqSVwx9BQKAvEOj1v1V+l3p9GfvCg0YZu5GABEaE9EsC+L73y8fanyuF72d/frqoGwj4Q2BAGOjrf3iDP7SgBQRAgHY++kdQAAEQAIFeQaD5SCWt/8FPekVZUAgQAAEQAAEQ8INAv13iHsnNpcRIxA9G0AECPUIgMTlCybk5PZK3WaapI4aZncY5EOgzBFKHF/SZsqKg9gRSCvhZdkOMb/tS4CoIuCcQ4e+7fOchIAACINCZQEIrS+eT/eX/WF09NZeX95fqoB4DjEAkL5dCaWm9ptat8Tg17D9A1H+bjF7DGgXxn0BSenqvGvDyv4YDT2O0qpqiVVUDr+Kocb8gkFKQj4mkfvEkUQkQ8J9AvzbQ/ccFjSAAAiAAAiAAAiAAAiAAAiAAAiAQDIF+u8Q9GFzQCgIgAAIgAAIgAAIgAAIgAAIgAALBEICBHgxXaAUBEAABEAABEAABEAABEAABEAABLQIw0LVwITEIgAAIgAAIgAAIgAAIgAAIgAAIBEMABnowXKEVBEAABEAABEAABEAABEAABEAABLQIwEDXwoXEIAACIAACIAACIAACIAACIAACIBAMARjowXCFVhAAARAAARAAARAAARAAARAAARDQIgADXQsXEoMACIAACIAACIAACIAACIAACIBAMARgoAfDFVpBAARAAARAAARAAARAAARAAARAQIsADHQtXEgMAiAAAiAAAiAAAiAAAiAAAiAAAsEQgIEeDFdoBQEQAAEQAAEQAAEQAAEQAAEQAAEtAjDQtXAhMQiAAAiAAAiAAAiAAAiAAAiAAAgEQwAGejBcoRUEQAAEQAAEQAAEQAAEQAAEQAAEtAjAQNfChcQgAAIgAAIgAAIgAAIgAAIgAAIgEAwBGOjBcIVWEAABEAABEAABEAABEAABEAABENAiAANdCxcSgwAIgAAIgAAIgAAIgAAIgAAIgEAwBGCgB8MVWkEABEAABEAABEAABEAABEAABEBAiwAMdC1cSAwCIAACIAACIAACIAACIAACIAACwRCAgR4MV2gFARAAARAAARAAARAAARAAARAAAS0CMNC1cCExCIAACIAACIAACIAACIAACIAACARDAAZ6MFyhFQRAAARAAARAAARAAARAAARAAAS0CMBA18KFxCAAAiAAAiAAAiAAAiAAAiAAAiAQDAEY6MFwhVYQAAEQAAEQAAEQAAEQAAEQAAEQ0CIAA10LFxKDAAiAAAiAAAiAAAiAAAiAAAiAQDAEYKAHwxVaQQAEQAAEQAAEQAAEQAAEQAAEQECLAAx0LVxIDAIgAAIgAAIgAAIgAAIgAAIgAALBEICBHgxXaAUBEAABEAABEAABEAABEAABEAABLQIw0LVwITEIgAAIgAAIgAAIgAAIgAAIgAAIBEMABnowXKEVBEAABEAABEAABEAABEAABEAABLQIwEDXwoXEIAACIAACIAACIAACIAACIAACIBAMARjowXCFVhAAARAAARAAARAAARAAARAAARDQIgADXQsXEoMACIAACIAACIAACIAACIAACIBAMARgoAfDFVpBAARAAARAAARAAARAAARAAARAQIsADHQtXEgMAiAAAiAAAiAAAiAAAiAAAiAAAsEQgIEeDFdoBQEQAAEQAAEQAAEQAAEQAAEQAAEtAjDQtXAhMQiAAAiAAAiAAAiAAAiAAAiAAAgEQ+D/AQR60U7JSVHsAAAAAElFTkSuQmCC)","metadata":{"id":"kQ0N64BfxnQe"}},{"cell_type":"markdown","source":"Boosting classifier\n\nimage source: [Geeksforgeeks, @pawangfg, xgboost](https://www.geeksforgeeks.org/xgboost/)","metadata":{"id":"6QbMDbjndSwC"}},{"cell_type":"markdown","source":"#### Our training","metadata":{"id":"klh934TNyZJ4"}},{"cell_type":"markdown","source":"Hyperparameters will focus on 3 categories:\n\n\n\n","metadata":{"id":"SbyQ3CLq61Iq"}},{"cell_type":"markdown","source":"**General parameters**: guide the overall functioning of the XGBoost model\n\n  1. booster: `gbtree` and `dart` - use tree-based models, while `gblinear` uses linear models.\n\n  2. nthread: number of cores for parallel processing","metadata":{"id":"MV2Qwbbl_Bp1"}},{"cell_type":"markdown","source":"**Booster parameters**\n3. eta: is learning rate\n\n4. max_depth: the maximum depth of a tree\n\n4. min_child_weight: minimum sum of weights of all variables\n\n5. subsample: subsample ratio of the training instances\n\n6. colsample_bytree: the subsample ratio of columns when constructing each tree\n\n","metadata":{"id":"i0C9H4Mn_JA3"}},{"cell_type":"markdown","source":"**Learning task parameters**\n\nParamaters that using in optimization\n8. objective: the loss function \n2. eval_metric: metric for validation data\n","metadata":{"id":"C93XeGO08XX6"}},{"cell_type":"code","source":"my_pipeline = Pipeline(steps=[('preprocessor',preprocessor)])\n\n# Transform the data\nX_train_xgb = my_pipeline.fit_transform(X_train)\nX_val_xgb = my_pipeline.transform(X_val)\n\ndtrain_ = xgb.DMatrix(X_train_xgb, label=y_train)\ndvalid_ = xgb.DMatrix(X_val_xgb, label=y_val)\nwatchlist = [(dtrain_, 'train'), (dvalid_, 'valid')]","metadata":{"id":"Rtg3X37YBHBS"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"#####**Learning rate**","metadata":{"id":"nvC_JX90Ffmp"}},{"cell_type":"code","source":"best = 100\ndic = {}\nfor ETA in tqdm([0.05, 0.1, 0.15, 0.3]):\n    \n    xgb_pars = {'eta': ETA, 'eval_metric': 'rmse', 'objective': 'reg:linear'}\n    model = xgb.train(xgb_pars, dtrain, 60, watchlist, early_stopping_rounds=50, maximize=False, verbose_eval=10)\n    if (model.best_score < best):\n        best = model.best_score\n        lr = ETA\ndic['eta'] = lr","metadata":{"id":"dpnAalTtEx3N","outputId":"85399199-16a9-4f5c-a27a-255cc078fc77"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(best)","metadata":{"id":"5gf_X-FFEXKa","outputId":"6a609b14-8786-4008-e5b1-94b39095843d"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"##### **min child weight**","metadata":{"id":"3LISWan7BZOO"}},{"cell_type":"code","source":"mcw = 1\nfor MCW in tqdm([50, 100]):\n    xgb_pars = {'eta': lr, 'min_child_weight': MCW, 'eval_metric': 'rmse', 'objective': 'reg:linear'}\n    model = xgb.train(xgb_pars, dtrain, 60, watchlist, early_stopping_rounds=50, maximize=False, verbose_eval=10)\n    if (model.best_score < best):\n        best = model.best_score\n        mcw = MCW\ndic['min_child_weight'] = mcw\n\nprint(best)","metadata":{"id":"kAoZzR7JHHpB","outputId":"3ff85c30-ce60-4303-e27b-093c1189f970"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"##### **colsample_bytree**","metadata":{"id":"v1WkuMWYBdQl"}},{"cell_type":"code","source":"cs = 1\nfor CS in tqdm([0.3, 0.4, 0.5]):\n    xgb_pars = {'eta': lr, 'min_child_weight': mcw, 'colsample_bytree': CS, 'eval_metric': 'rmse', 'objective': 'reg:linear'}\n    model = xgb.train(xgb_pars, dtrain, 60, watchlist, early_stopping_rounds=50, maximize=False, verbose_eval=10)\n    if (model.best_score < best):\n        best = model.best_score\n        cs = CS\ndic['colsample_bytree'] = cs\nprint(best)","metadata":{"id":"AMNbWq7LIsFL","outputId":"d7477049-5b4d-4e50-9610-fcdf6bd4d5c0"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"##### **max_depth**","metadata":{"id":"dh28aYmmBirz"}},{"cell_type":"code","source":"md = 6\nfor MD in tqdm([8, 10]):\n    xgb_pars = {'eta': lr, 'min_child_weight': mcw, 'colsample_bytree': cs,\n                'max_depth': MD, 'eval_metric': 'rmse', 'objective': 'reg:linear'}\n    model = xgb.train(xgb_pars, dtrain, 60, watchlist, early_stopping_rounds=50, maximize=False, verbose_eval=10)\n    if (model.best_score < best):\n        best = model.best_score\n        md = MD\ndic['max_depth'] = md\nprint(best)","metadata":{"id":"uuPDftKgJQag","outputId":"ceae18dc-16fe-4458-94d0-6185de2599b7"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"##### **subsample**","metadata":{"id":"PYrIF39cBpoB"}},{"cell_type":"code","source":"ss = 1\nfor SS in tqdm([0.5, 0.8]):\n    xgb_pars = {'eta': lr, 'min_child_weight': mcw, 'colsample_bytree': cs, 'subsample': SS,\n                'max_depth': md, 'eval_metric': 'rmse', 'objective': 'reg:linear'}\n    model = xgb.train(xgb_pars, dtrain, 60, watchlist, early_stopping_rounds=50, maximize=False, verbose_eval=10)\n    if (model.best_score < best):\n        best = model.best_score\n        ss = SS\ndic['subsample'] = ss\nprint(best)","metadata":{"id":"dS20ws4OJqXu","outputId":"62349dcc-e6eb-4488-dbe9-1d7bab8c39ab"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"##### **lambda**","metadata":{"id":"UmE6j3umBtDY"}},{"cell_type":"code","source":"ld = 1\nfor LAMBDA in tqdm([0.5, 1.5]):\n    xgb_pars = {'eta': lr, 'min_child_weight': mcw, 'colsample_bytree': cs, 'subsample': ss,\n                'lambda': LAMBDA, 'max_depth': md, 'eval_metric': 'rmse', 'objective': 'reg:linear'}\n    model = xgb.train(xgb_pars, dtrain, 60, watchlist, early_stopping_rounds=50, maximize=False, verbose_eval=10)\n    if (model.best_score < best):\n        best = model.best_score\n        ld = LAMBDA\ndic['lambda'] = ld\nprint(best)","metadata":{"id":"84kbmxnIKLks","outputId":"1183e98c-c2b0-419a-83d2-883ae8955fe3"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"##### Result","metadata":{"id":"umM0x_g6B2uL"}},{"cell_type":"code","source":"# with open('tun_AD.txt', 'w') as tun:\n#      tun.write(json.dumps(dic))","metadata":{"id":"JI9PDJo_LHJJ"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"with open('tun_AD.txt') as f:\n    tun = json.load(f)\ntun","metadata":{"id":"-q5_JfHtEldx","outputId":"f454bf02-a2f3-464b-e38d-99205532d288"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model_xgb_tun = xgb.train(tun, dtrain_, 60, watchlist, early_stopping_rounds=50, maximize=False, verbose_eval=10)","metadata":{"id":"yQCItxNtVo6Z","outputId":"2a41e419-4de1-48fd-b6ca-a4e16af184f8"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print('Modeling RMSLE %.5f' % model_xgb_tun.best_score)","metadata":{"id":"RuIJjUj5Mx0T","outputId":"e142f36e-c4f2-4c36-ae13-52330bc9fd2d"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"dtest_ = my_pipeline.transform(dtest)\ndtest_ = xgb.DMatrix(dtest_)\ny_pre_xgb = model_xgb_tun.predict(dtest_)\ny_pre_xgb","metadata":{"id":"DAFdK_hcM8Ny","outputId":"81fc7f44-2e6f-4b20-c918-9209d3d41d0f"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"new_df = test.copy()\nnew_df['trip_duration'] = np.exp(y_pre_xgb) - 1\nnew_df = new_df[['id', 'trip_duration']]\nnew_df.head()","metadata":{"id":"qqHUgeLGM-qV","outputId":"08f862ad-8e70-48ab-f2cf-335388974663"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"new_df.to_csv(\"submission_xgb_tun.csv\", index = False)","metadata":{"id":"YnFsSMExNA4A"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* **Week 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1eX+aM8e9V21O1TBXrU3VTu3UuYvNmzfffZYvXz67pHx591c+++xze+SRbrZ161bXnR60TtQAW2ppWb3x5oiYZeXKfMklVrLkBe5zzYvmSfPmU23Z5wPrSOtONUIvvricW75azuqnz77/4UdvaHM1f5/r1z9OA4PLli9328COHTu8Pselplw+1QweOuyNRBulmzN3rg0Y8FKcMv366yJ7pvezrsE73+LFS6xDx85uuxHlKtY8a95VttGjx1rvZ/vENIapv8+/MMCtb9Hwl15aIdb290zvPikqu5bngBcHuukF0+9lSCobGh06dLh9MGGi1xVN43910GBX8zdwTHL9UvN7Us1t7RdUA1nDX1erprVs2dzOPPNM9/nkyR8Fpj/MjTu9qdzvvDPe+vbtF7N/0XbjbzsqU7du3RPcN+kJkldfHRzv9vryy6+kad8ULjoW6pgIAAAAAEBSCECnwKHDhxN8zDxcFNhQ4KRp02bxBo8So0DL4MGvW9du3d3j3qeiw0cO2zfTv7QVy/+w/v36xjx2r2DgzTfXtSWLF9miXxe6vKy+pUuXxgTmgimYc+edd9iffyyxlSv+tOHDhsQEapWm4bffFrv3oUqVKmkzfvzOHnroAa+P2Qsv9Le/Vi23x7o/6rp/+fVXmzBhknt/1lln2YQP3rP/ff6Jff3VF9ahQzvXX8GlMWPGJhhMUgqAaldd6d7v2bPHfv75F/de1qxZa3/+GZ3+46qrqrmctdo2PgxsGwq2yk11atu333xt06Z9ZJ9/9rFVrVrF9Vcags8C85delDah15NP2JyfZtm0qZPt7LPP8j5JHi2rkSNHu/cqo8qq8Xz5xef2/PP93DrWPGneNI/adhXwVpoGLVsN+8nHU933nnyihxuPgpRfffW1HTp0yG33Clgr1YVoGj/+8J1bX/pbvHhxt3xDpbRcwRTg12vwoFds/ryfbMSbw11qiWAbNmy0Ro1uc9vsqpXLbOyYUTHb3+zZP9mvgenLwYMHbdy4d2LK36plC/vh+2/cPE/5aFJMw3dTpkyLCcD+/ffqwPz97QLU9evXs+++/Tow7If26SfTrHbtG90wKruCtKHiK3umwLxOnDAxJvjcsGED+3nhfFdulePIkaOuf0qtWLnSzbfGo+XQpk1r7xML/H4muhstkprfk+bND+B27tzR3nrrTbedfjR5kl1eubILyv/zzz8x04iPfs9fffk/N0257LJLbeGCue73r/1AQtasXWtj337HvdcNIu1bNJ7gbUfLcszYcTHrNZhSetSrd4vbl/2+9Dd75uleMfu6Xxf9Zv/8+697H0l0LNQxEQAAAACApBCATgEFtjIlkJs2XBQ87PlEL5s5a5Y9/Ei3ZAehXfD5tdftlVcHuQD2sGFvuH6nmrvvutMF3JR7tU6d2la+/MWuv2o13nFHI8uZM4fLh1undm3XPzGVKlW0Fs2budy2yotbq1bNwPeig3MKDs1fsMC9T43vvvs+Jqh5zz13ucCVaFp33HF7TNAwsWCSajSrZrMCWKKApB9IVzDaH3+1K690w+zcucu+/+4H10/drdu0sgIFonP8aPnc26Sxey8KVO7dGzconxoKACrgrwbYlFM7ofzLCQleVg880CamhqrWyQ3XX2dly5Z13YsCy0rBxdy5c7uAvxqMUyDwwgsvdJ+Lcjj79gWG1XqMitodK9CqafhBcv1t+9CDMcG9YCktV6heT/Z0wV/lWw7Oz+0rV66stWzR3G2zWtdXX32V3RnYNkTl9mu4/xvYPvwa5tpu7ru/acwyVi3gRo0auvf6jnIdKxhetuxFNmnSB65xPAWSc+bM6YZRQLpIkcLuvUQlcCMqtOxbt2yx33//w32mfq1btbT8+fO5cqsmdvANn5TQNnnNNdXdeLQc7r23ccxvQzdYdKNF0vp7WrJ4ictTrWWjPMoTJ77vtp9hw4a4+UtvCxcsjKlBfsvNdd2+RfOobUf7pipXXOE+++2332zFyhXufTB/29C+TOv6ttsa2pVXVnWfaZ+/fVvCQfOTRcfCU/GYAgAAAAA48QhARzgFG3v3ftoFzBSUSk4Q2g8+q/azqPZi27YPxgmInQoyJlBmBXYyZkjZ5qvApQI8PgWzKla8zOvSY/JbUhVQUZB4rRc4k3Llyrngk69I4ej0CZJUMEk1m1XDWfRY/pYtW934/dqxCqZVqxYdmFJDhOs3bHDvS5Q4184qHrsmcpmLysQEUVXz88CB/e59WhUtWjTW/KVE6LLq16+/Nbzt9phXs+YtXUNworQFqg3sU7dupvTq9bQbtuqVV9tDbdt7nx4XvFxUk/Xcc85x733qd8YZZ3hd0dJSLp+WS2JKlyrlarn79HssfWFpryuwbaxb78qhxgBXr1nj+qnWbeFCxxu51HIP3mY3bdzoUmjI0aNHXRnfGjkq8Htvb/XqN7AKl1ay8ePfc58nJrTswWVQ2ovixaO3I9+FpY+XOyV0Aymh34YCztu2b0/170m/C/0+RI1OXnX1tVax0hVu3SlliQL7oTXX04uervBddNFFMQ04itb5xd6NM/n333Xeu+M0fLZsx7+j2sWFCtK4HwAAAADg9EAAOgUUMDpyNHWPnqeWAq2qJdm377PJCkLHF3zu8+wzrhbpf51qcIamUAkOcO/Yvj3ewGJK5fJqn/oUO0tuzXnVZNZNB9Fj+ctXrHBBaAWjpeJll9m5557r3gcLDWCJAvTafiLZypWrXA5k/6U0EX4OXQUWlatZQUMFnq+5tpZLJ/PO+HfdsEql4AfY01tyynUi5MyRI846zJwpbu1t1cju2fNJq3PTLfbcc/1dAFZlVm1av1Z8JFCN+WChvw3dPAiV3N+TaocPHvSq++tTSo4ffvjRnu3T12rWusHeemtk2Gvt5sod/QSDT8HzTJki+3eYGjoWnoo3NQEAAAAAJ97pd1UcRlkyZ3Y5Zk+05AahDxw46BrzClfwWTUTFfTTy3883nc0FUGdPfGkMQinf/75N04aCtVm9Z1Z/EzLkSOH15V8Wic5goJk69bFruGobWbrtm1eV9KCa3IumL/ABaEVjJZa19WKlV4hR47o1AzxBUWVOzmlgdJwr5PQZfX+e+Ndbub4Xt99N92lWvjzzz9jGo9U7WWlmFA6BaWbeOXll7wxHRe8XFQ72A8c+9Tt1xr2paZcKbU38PtRLeVge3Yf/x1p+iqHyu+nYVFtWf2ug22LZ1tSXmq/cT81vqd0HL/+ssB+XjjP7r77Ltc/JYLLoJsyoWVI7XYS2tBh6G+jxLnnpvr3pEBvlSpXuNzdC+bPsXFvj3G5oP2AtFKWDBk63OWIT2/B+9i1a4/X3haVN7iBydOF5kvHRAAAAAAAkkIAOgWyZc9q+/fHDmadKAkFof/+62/3+b59++2VV161118f6rrDUfP5f//7wipVruJe3bp1j8mDqxqFS5f+7t6Lgkjx+eOPP2JqH+rvjBkz3PsTZd68ebZq1SqvKzr4rNqRvtQEFUW1qpXD1ff99z+4YL1PAWS/QUGlVFAjeIlRDWfVdBblMv4isNxFwddKFSu691KoUEErVTK6YTSlS5g3/3gOa9UanjFzZsyNAqUFiG9bONHrRMsqOH2Dph+cFkGBYTUwOXPmLFeDVwHbvwLbuN9wW/36t7hcxWpQTrUvN22K26BbwYIFYtalGtebP39+zDT094cff3T9g6WmXCmlPNzLlh1P1RAVFRWT91k0fZVDtbovuOAC1+/3QDmWLF3i3ouCwcqP7FMKD+0Pgn9/yl9duVIl1wiigoTbtib/5odPubWV1kVU5qW/Hx+/yjB9+nSvK2W+DZRd8+1Tg5b+b0Pbt/JNp+b3pG1X+ZW1fmbNmu0+q179auvSuZNN+OBdu+66Wq6fakSnVy70YOUvvtitB9F6Dr6xtW79+pic3grqpzZ9SaTRsVDHRAAAAAAAkkIAOgX0OPzefemTRzc14gtC61F7US3RCRMnuffhSruhhs78mrlfT//G+vV/3gVwBw1+LWba+txvMEyCg7rjxo23Lg93dQ0jtmjZ2uVlPZEUxHzs8R42ddrH9s2339njj/d0wSIJDe7GJ3h5TpwwyaYHlsHy5dENil177TUxgaVPP/vcXnllkKu5qcYj+/R5LiYQfNNNdeLk0w2lGs5XXX2Ve69GKP1le/VV1ezcc4/nM9ZwCsb6ga+XXnrZPv74E9f42vh337O33hrl+ivoVa/ezS6wJyd7nagROi1veeXVwW7+FBDW8nrxpYF2192Nrel9zeyDDya4wGLeoLzJuuGiNA0KDmubHzlqtPfJcZpfTcPX//kBbv4UnNTfQYNe8z6JLaXlSikFP3XT6KOPprjtr9ujj9mXX37lPgvO7a3GHevWrePea7t5tndf+/HHGa4cQ4YOs8mB74vKqgbutP6Dc5ur8UAFiVXGTz/9zL7wppESarjwqmrRuchVc1i/FW0bfjqLCYHtPzU0v0893dvNv9KqPPZYz5jfxuWVKwXmKfrmTGp+T9OmfeLWj17P9O7jnhBRAF6NG+omhmg5B+fhjk9wDfrFi5fYu++9736HwUHwUJdeemlg/UWnztE+pW/ffq62t77/bKAsfs1vNWZZpszxRjRPZToW6pgIAAAAAEBSCECnQO5cOS0qarfXdXKEBqFDhTPnc+nSpWMe51dQSo2bqYGv114b4tIaqDxduz4SKwdrzRo1rGrVKu69vvPJJ5+6FCGLFv1mDz7YxvU/US6vXNkyZcxkXbo8Yq1atXFBMFG59ah+yZLRtU4TooBcvnz53Pv5CxZY6zYP2pdfRQf31NBdhw7t3OeazxFvjbSrq9ewpk2buRzCogDnfU2bJitvqvJA+8FQn2p0BjduJjVrahpN3HvVuuzU+WGrdtU1rqE+BTw1bw+0aW1XVo0ObsrJXidazo883NkF+lRGBTcvv+JKt7xGjRrjhlGQvOl997qgeamSpeySSy5x/XXD5Yoq1eyCkhfaTXXrBX6TuV2t2VA3170pJoC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Refering Beluga's notebook","metadata":{"id":"mQLkpB1ix7sJ"}},{"cell_type":"code","source":"# Data preprocessing pipeline\nmy_pipeline = Pipeline(steps=[('preprocessor',preprocessor)])\n\n# Transform the data\nX_train_xgb = my_pipeline.fit_transform(X_train)\nX_val_xgb = my_pipeline.transform(X_val)","metadata":{"id":"JHuXTjFv_nQx"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"dtrain = xgb.DMatrix(X_train_xgb, label=y_train)\ndvalid = xgb.DMatrix(X_val_xgb, label=y_val)\nwatchlist = [(dtrain, 'train'), (dvalid, 'valid')]\n\n# Try different parameters! My favorite is random search :)\nxgb_pars = {'min_child_weight': 50, 'eta': 0.3, 'colsample_bytree': 0.3, 'max_depth': 10,\n            'subsample': 0.8, 'lambda': 1., 'nthread': 4, 'booster' : 'gbtree', 'silent': 1,\n            'eval_metric': 'rmse', 'objective': 'reg:linear'}","metadata":{"id":"_LljgyCeesgC"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model_xgb = xgb.train(xgb_pars, dtrain, 60, watchlist, early_stopping_rounds=50,\n                  maximize=False, verbose_eval=10)","metadata":{"id":"8r2R8Aj3pNLQ","outputId":"86121807-23e5-4172-e385-bb90c9b20f4e"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print('Modeling RMSLE %.5f' % model_xgb.best_score)","metadata":{"id":"SVMfdy-apQN_","outputId":"62811272-00a8-4373-f2c4-74b93a0b07aa"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"dtest_ = my_pipeline.transform(dtest)\ndtest_ = xgb.DMatrix(dtest_)\ny_pre_xgb = model_xgb.predict(dtest_)\ny_pre_xgb","metadata":{"id":"0XxjBCnzbdJl","outputId":"2213b8f0-c0e5-49e2-dbef-32c5c0ceefa3"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"new_df = test.copy()\nnew_df['trip_duration'] = np.exp(y_pre_xgb) - 1\nnew_df = new_df[['id', 'trip_duration']]\nnew_df.head()","metadata":{"id":"4nkseZk5hea2","outputId":"0e60e2b8-b9a3-4151-d41f-8ff3a66f0493"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"new_df.to_csv(\"submission_xgb.csv\", index = False)","metadata":{"id":"TccAThs_hsIu"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* **Week08**","metadata":{"id":"Zsn3Ky4PX9I1"}},{"cell_type":"markdown","source":"![image.png](data:image/png;base64,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cell_type":"markdown","source":"##### Features importance","metadata":{"id":"vw_r2w6nYRTY"}},{"cell_type":"code","source":"feature_importance_dict = model_xgb.get_score(importance_type=\"total_cover\")\nfs = ['f%i' % i for i in range(len(feature_names))]\nf1 = pd.DataFrame({'f': list(feature_importance_dict.keys()),\n                   'importance': list(feature_importance_dict.values())})\nf2 = pd.DataFrame({'f': fs, 'feature_name': feature_names})\nfeature_importance = pd.merge(f1, f2, how='right', on='f')\nfeature_importance = feature_importance.fillna(0)\nfeature_importance['importance'] = feature_importance['importance']/ feature_importance['importance'].sum()\n\nfeature_importance[['feature_name', 'importance']].sort_values(by='importance', ascending=False)","metadata":{"id":"ESknL_8oM5Dp","outputId":"686f5460-1a7b-4baa-8d2b-3ff213686d50"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Ref: https://stats.stackexchange.com/questions/396986/feature-selection-meaning-of-importance-type-in-get-score-function-of-xgbo\n\n**get_score(fmap=' ', importance_type='total_cover')** \\\nCalculate the feature important\n\n'total_cover' means: when the tree is splitted by a features. the number of rows will be splitted by conditions. total_cover will calculate the sum of rows which each branch/feature of tree is used. ","metadata":{"id":"_0ePNatGkksc"}},{"cell_type":"markdown","source":"* **Observations**\n    * As expected, distance has a significant impact on trip duration. Besides that, the group of location/ area and direction let us know whether the destination will be crowded or not to estimate the time correctly.\n    * As we visualised before, the hour and day of the month let us know more about congestion.\n    * The count of trip records when grouped by pickup cluster and dropoff cluster is seen not good as expected. It just counts the id having the same pickup and dropoff location without caring about the situation (the hour, the day,…).","metadata":{"id":"jzAKdQhZYZHW"}},{"cell_type":"markdown","source":"### Stacking model ","metadata":{"id":"B3clYL8I-w2Y"}},{"cell_type":"code","source":"# from numpy import mean\n# from numpy import std\n# from sklearn.datasets import make_regression\n# from sklearn.model_selection import cross_val_score\n# from sklearn.model_selection import RepeatedKFold\n# from sklearn.tree import DecisionTreeRegressor\n# from sklearn.ensemble import RandomForestRegressor\n# from sklearn.ensemble import ExtraTreesRegressor\n# from sklearn.ensemble import StackingRegressor\n# from matplotlib import pyplot","metadata":{"id":"i4axMTRV-wJO"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# # get a stacking ensemble of models\n# def get_stacking():\n# \t# define the base models\n# \tlevel0 = list()\n# \tlevel0.append(('xgb', xgb.XGBRegressor()))\n# \t# level0.append(('random', RandomForestRegressor()))\n# \t# level0.append(('extra', ExtraTreesRegressor()))\n# \t# level0.append(('cart', DecisionTreeRegressor()))\n# \tlevel0.append(('linear', LinearRegression()))\n# \t# define meta learner model\n# \tlevel1 = xgb.XGBRegressor()\n# \t# define the stacking ensemble\n# \tmodel = StackingRegressor(estimators=level0, final_estimator=level1, cv=5)\n# \treturn model","metadata":{"id":"bObPmWA8_tmb"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# model = get_stacking()    \n# # giving all values to pipeline \n# stack_pipe = Pipeline(steps=[('preprocessor', preprocessor),('stack', model)])\n\n# stack_pipe.fit(X_train, y_train)\n\n# # make predictions on training set\n# y_pred_stack = stack_pipe.predict(X_val)","metadata":{"id":"J7SFDoLDAcfU"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# # to print the results in good way\n# print(f\"Validation RMSLE: {mean_squared_error(y_pred_stack, y_val, squared=False)}\")","metadata":{"id":"Y-QCCtgiBfCm"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# y_pre_stack_test = stack_pipe.predict(test)","metadata":{"id":"20XSzBg2uECV"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# y_pre_stack_test","metadata":{"id":"ugBZxGuIuUTy"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# new_df = test.copy()\n# new_df['trip_duration'] = np.exp(y_pre_stack_test) - 1\n# new_df = new_df[['id', 'trip_duration']]\n# new_df.head()","metadata":{"id":"If0fA6oiuax9"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# new_df.to_csv(\"submission_stack_xgb_linear.csv\", index = False)","metadata":{"id":"M9t03Zq3ueRQ"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"![image.png](data:image/png;base64,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)","metadata":{"id":"Lq1hnaQrukzM"}},{"cell_type":"markdown","source":"## Improve model with auxiliary dataset\nBased on the important features of XGB, we know that distance has the strongest affect on predicting the trip_duration. $\\to$ we decide to use the additional OSRM dataset.\n\nOSRM features - Open Source Routing Machine is a routing engine to extract shortest paths in road networks for each trip (with pickup and dropoff location). ","metadata":{"id":"QhtYkazZEAG4"}},{"cell_type":"code","source":"osrm_train = pd.read_csv('./nyc-taxi-trip-noisy/train_augmented.csv')\nosrm_test = pd.read_csv('./nyc-taxi-trip-noisy/test_augmented.csv')\nprint(\"OSRM Train shape: \", osrm_train.shape)\nprint(\"OSRM Test shape: \", osrm_test.shape)","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:25:45.858833Z","iopub.status.busy":"2022-06-26T23:25:45.858152Z","iopub.status.idle":"2022-06-26T23:25:50.703801Z","shell.execute_reply":"2022-06-26T23:25:50.701991Z"},"papermill":{"duration":4.865745,"end_time":"2022-06-26T23:25:50.706733","exception":false,"start_time":"2022-06-26T23:25:45.840988","status":"completed"},"tags":[],"id":"6a752c90","outputId":"9a251dc1-8365-47cb-ae39-413a8e5beb7e"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* Definition of each column\n\n| Column name | Description | \n| -------- | -------- | \n| id   | Record id     |\n| distance | Route distance (m) |\n| duration | OSRM trip duration (s) |\n| motorway | The proportion spent on different kind of roads (% of total distance) |\n| trunk |  The proportion spent on different kind of roads (% of total distance) |\n| primary | The proportion spent on different kind of roads (% of total distance) |\n| secondary | The proportion spent on different kind of roads (% of total distance) |\n| tertiary | The proportion spent on different kind of roads (% of total distance) |\n| unclassified | The proportion spent on different kind of roads (% of total distance) |\n| residential | The proportion spent on different kind of roads (% of total distance) |\n| nTrafficSignals | The number of traffic signals |\n| nCrossing | The number of pedestrian crossing |\n| nStop | The number of stop signs |\n| nIntersection | The number of intersections, if you are OSRM user, intersection have different meaning than the one used in OSRM |\n| srcCounty | Pickup county |\n| dstCounty | Dropoff county |\n\n* **srcCounty** and **dstCounty** values: There are 6 different values\n    * NA: Not in NYC\n    1. Brooklyn\n    2. Queens\n    3. Staten Island\n    4. Manhattan\n    5. Bronx\n\n$\\Rightarrow$ We will fill in NA values with the number 6.","metadata":{"papermill":{"duration":0.018566,"end_time":"2022-06-26T23:25:50.742196","exception":false,"start_time":"2022-06-26T23:25:50.723630","status":"completed"},"tags":[],"id":"972cc536"}},{"cell_type":"markdown","source":"Based on the column definition, we will keep features that we need for the problem","metadata":{"id":"vyzVM-gLPJMI"}},{"cell_type":"code","source":"osrm_features = [\"id\", \"distance\",\"duration\", \"nStop\",\"nTrafficSignals\",\"nCrossing\", \"srcCounty\", \"dstCounty\"]","metadata":{"id":"gxJj_vSCPTBA"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"osrm_train = osrm_train[osrm_features]\nosrm_test = osrm_test[osrm_features]","metadata":{"id":"MiiGgbqfPnK2"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"osrm_train.srcCounty.fillna(6, inplace = True)\nosrm_train.dstCounty.fillna(6, inplace = True)\nosrm_test.srcCounty.fillna(6, inplace = True)\nosrm_test.dstCounty.fillna(6, inplace = True)","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:25:50.775877Z","iopub.status.busy":"2022-06-26T23:25:50.775484Z","iopub.status.idle":"2022-06-26T23:25:50.789772Z","shell.execute_reply":"2022-06-26T23:25:50.788548Z"},"papermill":{"duration":0.034519,"end_time":"2022-06-26T23:25:50.792525","exception":false,"start_time":"2022-06-26T23:25:50.758006","status":"completed"},"tags":[],"id":"d072e488"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"osrm_train.dtypes","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:25:50.826520Z","iopub.status.busy":"2022-06-26T23:25:50.826144Z","iopub.status.idle":"2022-06-26T23:25:50.834959Z","shell.execute_reply":"2022-06-26T23:25:50.833794Z"},"papermill":{"duration":0.028852,"end_time":"2022-06-26T23:25:50.837330","exception":false,"start_time":"2022-06-26T23:25:50.808478","status":"completed"},"tags":[],"id":"7d12372c","outputId":"f99df6df-8d75-4136-d14e-8310b1bd2b2a"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"osrm_test.dtypes","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:25:50.871526Z","iopub.status.busy":"2022-06-26T23:25:50.871090Z","iopub.status.idle":"2022-06-26T23:25:50.879962Z","shell.execute_reply":"2022-06-26T23:25:50.878784Z"},"papermill":{"duration":0.028363,"end_time":"2022-06-26T23:25:50.882404","exception":false,"start_time":"2022-06-26T23:25:50.854041","status":"completed"},"tags":[],"id":"96902c02","outputId":"b32c84d0-7742-4bee-93be-2ecec75fdf40"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"osrm_train.head(2)","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:25:50.917226Z","iopub.status.busy":"2022-06-26T23:25:50.916804Z","iopub.status.idle":"2022-06-26T23:25:50.932453Z","shell.execute_reply":"2022-06-26T23:25:50.931322Z"},"papermill":{"duration":0.036132,"end_time":"2022-06-26T23:25:50.934823","exception":false,"start_time":"2022-06-26T23:25:50.898691","status":"completed"},"tags":[],"id":"a5a73728","outputId":"c614fb24-b926-449e-a8e1-631d75897419"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(len(np.intersect1d(osrm_train['id'], train['id'])))\nprint(train.shape[0])","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:25:50.969732Z","iopub.status.busy":"2022-06-26T23:25:50.968834Z","iopub.status.idle":"2022-06-26T23:26:20.933833Z","shell.execute_reply":"2022-06-26T23:26:20.932446Z"},"papermill":{"duration":29.9855,"end_time":"2022-06-26T23:26:20.936738","exception":false,"start_time":"2022-06-26T23:25:50.951238","status":"completed"},"tags":[],"id":"af442e17","outputId":"362d883c-5775-41ce-a805-afd9b740b09c"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* The number of ids in osrm_train is less than the origin train set 1 id, every id in osrm_train are in train set.","metadata":{"papermill":{"duration":0.016295,"end_time":"2022-06-26T23:26:20.970621","exception":false,"start_time":"2022-06-26T23:26:20.954326","status":"completed"},"tags":[],"id":"4c9688d6"}},{"cell_type":"code","source":"osrm_num_cols = list(osrm_train.select_dtypes(exclude = 'object').columns)\nosrm_cate_cols = list(osrm_train.select_dtypes(include = 'object').columns)","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:26:21.917084Z","iopub.status.busy":"2022-06-26T23:26:21.916228Z","iopub.status.idle":"2022-06-26T23:26:22.011878Z","shell.execute_reply":"2022-06-26T23:26:22.011032Z"},"papermill":{"duration":0.116179,"end_time":"2022-06-26T23:26:22.014463","exception":false,"start_time":"2022-06-26T23:26:21.898284","status":"completed"},"tags":[],"id":"66b38821"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"osrm_train[osrm_num_cols].agg([missing_percentage, value_percentages, num_values])","metadata":{"execution":{"iopub.execute_input":"2022-06-26T23:26:22.049687Z","iopub.status.busy":"2022-06-26T23:26:22.049292Z","iopub.status.idle":"2022-06-26T23:26:31.948372Z","shell.execute_reply":"2022-06-26T23:26:31.946996Z"},"papermill":{"duration":9.919987,"end_time":"2022-06-26T23:26:31.951202","exception":false,"start_time":"2022-06-26T23:26:22.031215","status":"completed"},"tags":[],"id":"3171087a","outputId":"40b8b8d6-f4f2-462e-9f88-12d49db8adbe"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"osrm_train = osrm_train.merge(train, on = 'id')\nosrm_test = osrm_test.merge(test, on = 'id')","metadata":{"id":"DltlgpDuPABg"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"do_not_use_for_training = ['id','trip_duration']\nfeature_names = [f for f in osrm_train.columns if f not in do_not_use_for_training]","metadata":{"id":"1dXlEYc3njZy"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(len(feature_names)) \nfeature_names","metadata":{"outputId":"7851e64c-4c2c-43de-b6b6-5fdea94f9249","id":"I-O6XV8lnjZz"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"osrm_dtrain = osrm_train[feature_names]\nosrm_dtest = osrm_test[feature_names]","metadata":{"id":"QI2yDfa2njZ1"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"osrm_y = np.log(osrm_train['trip_duration'].values + 1)","metadata":{"id":"1oLdxoC1pIWk"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Preprocessor","metadata":{"id":"iNb_2VocybMZ"}},{"cell_type":"code","source":"num_cols = list(osrm_dtrain.select_dtypes(exclude='object').columns)\ncat_cols = list(osrm_dtest.select_dtypes(include='object').columns)","metadata":{"id":"Pu3Dy5beybMi"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#Preprocessing for missing numerical data\nnum_transformer = Pipeline(steps = [\n         (\"imputer\", SimpleImputer(strategy=\"constant\", fill_value=0)),\n         (\"norm\", StandardScaler())])\n\n# Preprocessing for categorical data\ncat_transformer = OneHotEncoder(handle_unknown=\"ignore\", sparse=False)\n\n# getting together our scaler and encoder with preprocessor\npreprocessor = ColumnTransformer(\n      transformers=[('num', num_transformer, num_cols),\n                    ('cat', cat_transformer, cat_cols)])","metadata":{"id":"NXuBduTUybMp"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Linear Regression","metadata":{"id":"FkryeoJJTnjI"}},{"cell_type":"code","source":"model_linear = LinearRegression()\n\nX_train, X_val, y_train, y_val = train_test_split(osrm_dtrain, osrm_y, test_size=0.2, random_state=1987)\n\n# giving all values to pipeline\nlinear_pipe = Pipeline(steps=[('preprocessor', preprocessor),('linear', model_linear)])\nlinear_pipe.fit(X_train, y_train)\n\n# make predictions on training set\ny_pred = linear_pipe.predict(X_val)","metadata":{"id":"0qQUdqbrTnjM"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"linear_pipe","metadata":{"id":"UmF8QBRdTnjU","outputId":"f517d59f-4e1d-47f9-fda0-d269b87d83e1"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# to print the results in good way\nprint(f\"Validation RMSLE: {mean_squared_error(y_pred, y_val, squared=False)}\")","metadata":{"id":"e0Euf83cTnjX","outputId":"5e9bc06a-25d7-4c68-fe5f-8b83d3175eeb"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"y_pre_linear_new = linear_pipe.predict(osrm_dtest)\ny_pre_linear_new = np.exp(y_pre_linear_new) - 1\ny_pre_linear_new","metadata":{"outputId":"bb96ae04-2f26-406d-d9a8-16546ced76d5","id":"yziXDJQYY8s4"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"new_df = test.copy()\nnew_df['trip_duration'] = y_pre_linear_new\nnew_df = new_df[['id', 'trip_duration']]\nnew_df.head()","metadata":{"outputId":"d40ef5c6-ccd7-4c2a-bd02-bd6d462ab8be","id":"0lXpOYX4Y8s7"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"new_df.to_csv(\"submission_linear_osrm.csv\", index = False)","metadata":{"id":"uvItViIXY8s7"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"*  **Week 10**\n\n![image.png](data:image/png;base64,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)","metadata":{"id":"Ysm--QDilEvH"}},{"cell_type":"markdown","source":"### XGB","metadata":{"id":"qCt8uZBuTxio"}},{"cell_type":"code","source":"my_pipeline = Pipeline(steps=[('preprocessor',preprocessor)])\n\n# Transform the data\nX_train_xgb = my_pipeline.fit_transform(X_train)\nX_val_xgb = my_pipeline.transform(X_val)\n\ndtrain_ = xgb.DMatrix(X_train_xgb, label=y_train)\ndvalid_ = xgb.DMatrix(X_val_xgb, label=y_val)\nwatchlist = [(dtrain_, 'train'), (dvalid_, 'valid')]","metadata":{"id":"4cTH3eutTxit"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"with open('tun_AD.txt') as f:\n    tun = json.load(f)\ntun","metadata":{"outputId":"fbe53a29-78b1-4273-cf5b-ed7595c5f990","id":"4yWIcv0he7Ny"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model_xgb_tun = xgb.train(tun, dtrain_, 60, watchlist, early_stopping_rounds=50, maximize=False, verbose_eval=10)","metadata":{"outputId":"7489a589-c641-4ebc-d725-13ca21328924","id":"tRKc-QZze7Nz"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print('Modeling RMSLE %.5f' % model_xgb_tun.best_score)","metadata":{"outputId":"fc413c09-3e88-4376-dd6c-a2515bc28dd5","id":"0CfLq5xoe7N0"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"dtest_ = my_pipeline.transform(osrm_dtest)\ndtest_ = xgb.DMatrix(dtest_)\ny_pre_xgb = model_xgb_tun.predict(dtest_)\ny_pre_xgb","metadata":{"outputId":"5fda6b32-bd66-49a5-d535-fb74d6b3a3ee","id":"qUG4wcrZe7N1"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"new_df = test.copy()\nnew_df['trip_duration'] = np.exp(y_pre_xgb) - 1\nnew_df = new_df[['id', 'trip_duration']]\nnew_df.head()","metadata":{"outputId":"d1c7d79d-c3aa-4596-e4c5-e13f39d12e13","id":"GtKHlqnhe7N1"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"new_df.to_csv(\"submission_xgb_tun_osrm.csv\", index = False)","metadata":{"id":"99CQe7qUaM_Y"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"*   Week 10\n![image.png](data:image/png;base64,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)\n\n","metadata":{"id":"HxznMg3xmsZX"}},{"cell_type":"markdown","source":"## Reference","metadata":{"id":"c6_rN15GcSfz"}},{"cell_type":"markdown","source":"https://machinelearningmastery.com/stacking-ensemble-machine-learning-with-python/\n\nhttps://scikit-learn.org/stable/modules/model_evaluation.html#mean-squared-log-error\n\nhttps://www.geeksforgeeks.org/xgboost/","metadata":{"id":"gRRapofqfWix"}},{"cell_type":"markdown","source":"https://www.kaggle.com/code/tilii7/hyperparameter-grid-search-with-xgboost/notebook\n\nhttps://www.kaggle.com/code/prashant111/a-guide-on-xgboost-hyperparameters-tuning/notebook","metadata":{"id":"4a5LA8OPfWiy"}},{"cell_type":"markdown","source":"https://www.kaggle.com/code/felipefiorini/xgboost-hyper-parameter-tuning ","metadata":{"id":"ZKo9ScXyfWiy"}},{"cell_type":"markdown","source":"https://machinelearningmastery.com/stacking-ensemble-machine-learning-with-python/\n\nhttps://scikit-learn.org/stable/modules/model_evaluation.html#mean-squared-log-error\n\nhttps://www.geeksforgeeks.org/xgboost/","metadata":{"id":"nSnD14LKBXyu"}},{"cell_type":"markdown","source":"https://www.kaggle.com/code/tilii7/hyperparameter-grid-search-with-xgboost/notebook\n\nhttps://www.kaggle.com/code/prashant111/a-guide-on-xgboost-hyperparameters-tuning/notebook","metadata":{"id":"ukDlP8Qwzr3g"}},{"cell_type":"markdown","source":"https://www.kaggle.com/code/felipefiorini/xgboost-hyper-parameter-tuning \n\nhttps://www.rdocumentation.org/packages/xgboost/versions/1.6.0.1/topics/xgb.train (read for hyper para)","metadata":{"id":"e2vlSQHMnLpx"}},{"cell_type":"code","source":"","metadata":{"id":"f2Ip-PIgeJSz"},"execution_count":null,"outputs":[]}]}