{"metadata":{"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"name":"python","version":"3.7.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# Implementing PyCaret 2.0 on Wine Quality Dataset (Highly Imbalance Classes Problem)","metadata":{}},{"cell_type":"markdown","source":"# **Since PyCaret 2.0 is recently launched, i plan to work with it and see if this is as amazing as it is hyped. To be honest i found it wonderful, they way it has reduced the work for data scientists and provide low code model to automate most of the repetition work is marvelous. Let start and see for yourself how it can save precious time for users.**","metadata":{}},{"cell_type":"markdown","source":"# **I've selected Wine Quality dataset due to its highly imbalance classes which is a key problem in dataset for incuring bias.**","metadata":{}},{"cell_type":"code","source":"#important libraries\nimport numpy as np \nimport pandas as pd","metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0"},"execution_count":1,"outputs":[]},{"cell_type":"markdown","source":"**importing wine quality data from UCI ML repo via wget**","metadata":{}},{"cell_type":"markdown","source":"**wget: helps to retrieves content from web servers**","metadata":{}},{"cell_type":"markdown","source":"# 1. Importing Dataset and PyCaret 2.0","metadata":{}},{"cell_type":"code","source":"!wget --no-check-certificate \\\n https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv","metadata":{},"execution_count":2,"outputs":[{"output_type":"stream","text":"--2020-08-04 05:15:12-- https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv\nResolving archive.ics.uci.edu (archive.ics.uci.edu)... 128.195.10.252\nConnecting to archive.ics.uci.edu (archive.ics.uci.edu)|128.195.10.252|:443... connected.\nHTTP request sent, awaiting response... 200 OK\nLength: 84199 (82K) [application/x-httpd-php]\nSaving to: ‘winequality-red.csv’\n\nwinequality-red.csv 100%[===================>] 82.23K --.-KB/s in 0.05s \n\n2020-08-04 05:15:12 (1.56 MB/s) - ‘winequality-red.csv’ saved [84199/84199]\n\n","name":"stdout"}]},{"cell_type":"code","source":"df1 = pd.read_csv('/kaggle/working/winequality-red.csv', sep=\";\")","metadata":{},"execution_count":3,"outputs":[]},{"cell_type":"code","source":"df1.head()","metadata":{},"execution_count":4,"outputs":[{"output_type":"execute_result","execution_count":4,"data":{"text/plain":" fixed acidity volatile acidity citric acid residual sugar chlorides \\\n0 7.4 0.70 0.00 1.9 0.076 \n1 7.8 0.88 0.00 2.6 0.098 \n2 7.8 0.76 0.04 2.3 0.092 \n3 11.2 0.28 0.56 1.9 0.075 \n4 7.4 0.70 0.00 1.9 0.076 \n\n free sulfur dioxide total sulfur dioxide density pH sulphates \\\n0 11.0 34.0 0.9978 3.51 0.56 \n1 25.0 67.0 0.9968 3.20 0.68 \n2 15.0 54.0 0.9970 3.26 0.65 \n3 17.0 60.0 0.9980 3.16 0.58 \n4 11.0 34.0 0.9978 3.51 0.56 \n\n alcohol quality \n0 9.4 5 \n1 9.8 5 \n2 9.8 5 \n3 9.8 6 \n4 9.4 5 ","text/html":"
"},"metadata":{}}]},{"cell_type":"markdown","source":"**you can see for yourself how imbalance the classes are, target quality for class 4,8,3 are negligible as compared to 5,6,7. This will surely impact the model performace on minority classes and introduce bias**","metadata":{}},{"cell_type":"code","source":"df1.quality.value_counts()","metadata":{},"execution_count":6,"outputs":[{"output_type":"execute_result","execution_count":6,"data":{"text/plain":"5 681\n6 638\n7 199\n4 53\n8 18\n3 10\nName: quality, dtype: int64"},"metadata":{}}]},{"cell_type":"markdown","source":"**installing the latest version of PyCaret**","metadata":{}},{"cell_type":"code","source":"pip install pycaret==2.0","metadata":{},"execution_count":7,"outputs":[{"output_type":"stream","text":"Collecting pycaret==2.0\n Downloading pycaret-2.0-py3-none-any.whl (255 kB)\n\u001b[K |████████████████████████████████| 255 kB 575 kB/s eta 0:00:01\n\u001b[?25hRequirement already satisfied: textblob in /opt/conda/lib/python3.7/site-packages (from pycaret==2.0) (0.15.3)\nRequirement already satisfied: seaborn in /opt/conda/lib/python3.7/site-packages (from pycaret==2.0) (0.10.0)\nRequirement already 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cffi!=1.11.3,>=1.8->cryptography>=2.1.4->azure-storage-blob>=12.0->mlflow->pycaret==2.0) (2.20)\nRequirement already satisfied: oauthlib>=3.0.0 in /opt/conda/lib/python3.7/site-packages (from requests-oauthlib>=0.5.0->msrest>=0.6.10->azure-storage-blob>=12.0->mlflow->pycaret==2.0) (3.0.1)\nRequirement already satisfied: testpath in /opt/conda/lib/python3.7/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets->pycaret==2.0) (0.4.4)\nRequirement already satisfied: bleach in /opt/conda/lib/python3.7/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets->pycaret==2.0) (3.1.4)\nRequirement already satisfied: pandocfilters>=1.4.1 in /opt/conda/lib/python3.7/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets->pycaret==2.0) (1.4.2)\nRequirement already satisfied: defusedxml in /opt/conda/lib/python3.7/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets->pycaret==2.0) (0.6.0)\nRequirement already satisfied: mistune<2,>=0.8.1 in /opt/conda/lib/python3.7/site-packages (from nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets->pycaret==2.0) (0.8.4)\nRequirement already satisfied: webencodings in /opt/conda/lib/python3.7/site-packages (from bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets->pycaret==2.0) (0.5.1)\nBuilding wheels for collected packages: pyod, combo, suod, prometheus-flask-exporter, databricks-cli, sqlalchemy, querystring-parser\n Building wheel for pyod (setup.py) ... \u001b[?25ldone\n\u001b[?25h Created wheel for pyod: filename=pyod-0.8.1-py3-none-any.whl size=105651 sha256=468e9f3ee1062549c477b9f21277cad5c791a13f8c83483e5dfa71ffdf7e1bb9\n Stored in directory: /root/.cache/pip/wheels/d6/f2/24/2c050361bd259bee34bbef8047bbcd3f08085f2a8a5ed1fc85\n Building wheel for combo (setup.py) ... \u001b[?25ldone\n\u001b[?25h Created wheel for combo: filename=combo-0.1.1-py3-none-any.whl size=42113 sha256=5dfd021545feb373b65924cbb8ce1bb21698bf140f6f6d043d3d845363b4dfc0\n Stored in directory: /root/.cache/pip/wheels/3e/e1/f8/08f19ba48f75d3dbbb549cec4b86cc0392c14b2b6bb81f4e1f\n Building wheel for suod (setup.py) ... \u001b[?25ldone\n\u001b[?25h Created wheel for suod: filename=suod-0.0.4-py3-none-any.whl size=2167157 sha256=678eb1a2c80c149fdbff47afb8baeba674428dcea668949d4cc4c4d64bbc4279\n Stored in directory: /root/.cache/pip/wheels/dc/ae/aa/3b8cc857617f3ba6cb9e6b804c79c69d0ed60a08e022e9a4f3\n Building wheel for prometheus-flask-exporter (setup.py) ... \u001b[?25ldone\n\u001b[?25h Created wheel for prometheus-flask-exporter: filename=prometheus_flask_exporter-0.15.4-py3-none-any.whl size=16451 sha256=e5ed543196680fbd7108c543d469249cd160e6255c433b3f9f4f9a9b21d126fc\n Stored in directory: /root/.cache/pip/wheels/69/e3/ab/f10afded2fa6225f1672b34a7438cadf596e359a21f454d22c\n Building wheel for databricks-cli (setup.py) ... \u001b[?25ldone\n\u001b[?25h Created wheel for databricks-cli: filename=databricks_cli-0.11.0-py3-none-any.whl size=90300 sha256=b5a56f384d753c2d54bc7e8f022672cbe13848119d0b92dcc0f671738a782dca\n Stored in directory: /root/.cache/pip/wheels/81/3f/18/5678c9d403583e583a251463196998b17852b98de34aa9ab51\n Building wheel for sqlalchemy (setup.py) ... \u001b[?25ldone\n\u001b[?25h Created wheel for sqlalchemy: filename=SQLAlchemy-1.3.13-cp37-cp37m-linux_x86_64.whl size=1221855 sha256=e009c1d130fcb7a3caa35c14649001533f0ec7da0b857267318d6dd4375985aa\n Stored in directory: /root/.cache/pip/wheels/b9/ba/77/163f10f14bd489351530603e750c195b0ceceed2f3be2b32f1\n Building wheel for querystring-parser (setup.py) ... \u001b[?25ldone\n\u001b[?25h Created wheel for querystring-parser: filename=querystring_parser-1.2.4-py3-none-any.whl size=7076 sha256=5ffc4d11d9964eefab8c52e2f98be00e9b5c1efa9596a3f39c93d30c98919553\n Stored in directory: /root/.cache/pip/wheels/69/38/7a/072b5863ca334d012821a287fd1d066cea33abdcda3ef2f878\nSuccessfully built pyod combo suod prometheus-flask-exporter databricks-cli sqlalchemy querystring-parser\nInstalling collected packages: combo, suod, pyod, prometheus-flask-exporter, databricks-cli, azure-core, isodate, msrest, azure-storage-blob, sqlalchemy, querystring-parser, gorilla, gunicorn, mlflow, zope.interface, DateTime, datefinder, pycaret\n Attempting uninstall: sqlalchemy\n Found existing installation: SQLAlchemy 1.3.16\n Uninstalling SQLAlchemy-1.3.16:\n Successfully uninstalled SQLAlchemy-1.3.16\nSuccessfully installed DateTime-4.3 azure-core-1.7.0 azure-storage-blob-12.3.2 combo-0.1.1 databricks-cli-0.11.0 datefinder-0.7.1 gorilla-0.3.0 gunicorn-20.0.4 isodate-0.6.0 mlflow-1.10.0 msrest-0.6.18 prometheus-flask-exporter-0.15.4 pycaret-2.0 pyod-0.8.1 querystring-parser-1.2.4 sqlalchemy-1.3.13 suod-0.0.4 zope.interface-5.1.0\n\u001b[33mWARNING: You are using pip version 20.1.1; however, version 20.2 is available.\nYou should consider upgrading via the '/opt/conda/bin/python3.7 -m pip install --upgrade pip' command.\u001b[0m\nNote: you may need to restart the kernel to use updated packages.\n","name":"stdout"}]},{"cell_type":"markdown","source":"**Since Problem is classification, you can read about other options here: [Modules](https://pycaret.org/modules/)**","metadata":{}},{"cell_type":"code","source":"from pycaret.classification import *","metadata":{},"execution_count":8,"outputs":[]},{"cell_type":"markdown","source":"**The use case is simple you have to setup a preprocessing pipeline with 'setup' module, select the target and name your experiment.**\n\n**you can specify a session_id, if you didn't by default a random seed is generated and returned in the Information grid. The unique number is then distributed as a seed in all functions used during the experiment. This can be used for later reproducibility of the entire experiment.**","metadata":{}},{"cell_type":"markdown","source":"# 2. Using Default Setup of PyCaret 2.0","metadata":{}},{"cell_type":"code","source":"session_1 = setup(df1, target = 'quality', session_id=123, log_experiment=False, experiment_name='wine_q1')","metadata":{},"execution_count":9,"outputs":[{"output_type":"stream","text":"Setup Succesfully Completed!\n","name":"stdout"},{"output_type":"display_data","data":{"text/plain":"","text/html":"
Description
Value
\n
\n
0
\n
session_id
\n
123
\n
\n
\n
1
\n
Target Type
\n
Multiclass
\n
\n
\n
2
\n
Label Encoded
\n
None
\n
\n
\n
3
\n
Original Data
\n
(1599, 12)
\n
\n
\n
4
\n
Missing Values
\n
False
\n
\n
\n
5
\n
Numeric Features
\n
11
\n
\n
\n
6
\n
Categorical Features
\n
0
\n
\n
\n
7
\n
Ordinal Features
\n
False
\n
\n
\n
8
\n
High Cardinality Features
\n
False
\n
\n
\n
9
\n
High Cardinality Method
\n
None
\n
\n
\n
10
\n
Sampled Data
\n
(1599, 12)
\n
\n
\n
11
\n
Transformed Train Set
\n
(1119, 11)
\n
\n
\n
12
\n
Transformed Test Set
\n
(480, 11)
\n
\n
\n
13
\n
Numeric Imputer
\n
mean
\n
\n
\n
14
\n
Categorical Imputer
\n
constant
\n
\n
\n
15
\n
Normalize
\n
False
\n
\n
\n
16
\n
Normalize Method
\n
None
\n
\n
\n
17
\n
Transformation
\n
False
\n
\n
\n
18
\n
Transformation Method
\n
None
\n
\n
\n
19
\n
PCA
\n
False
\n
\n
\n
20
\n
PCA Method
\n
None
\n
\n
\n
21
\n
PCA Components
\n
None
\n
\n
\n
22
\n
Ignore Low Variance
\n
False
\n
\n
\n
23
\n
Combine Rare Levels
\n
False
\n
\n
\n
24
\n
Rare Level Threshold
\n
None
\n
\n
\n
25
\n
Numeric Binning
\n
False
\n
\n
\n
26
\n
Remove Outliers
\n
False
\n
\n
\n
27
\n
Outliers Threshold
\n
None
\n
\n
\n
28
\n
Remove Multicollinearity
\n
False
\n
\n
\n
29
\n
Multicollinearity Threshold
\n
None
\n
\n
\n
30
\n
Clustering
\n
False
\n
\n
\n
31
\n
Clustering Iteration
\n
None
\n
\n
\n
32
\n
Polynomial Features
\n
False
\n
\n
\n
33
\n
Polynomial Degree
\n
None
\n
\n
\n
34
\n
Trignometry Features
\n
False
\n
\n
\n
35
\n
Polynomial Threshold
\n
None
\n
\n
\n
36
\n
Group Features
\n
False
\n
\n
\n
37
\n
Feature Selection
\n
False
\n
\n
\n
38
\n
Features Selection Threshold
\n
None
\n
\n
\n
39
\n
Feature Interaction
\n
False
\n
\n
\n
40
\n
Feature Ratio
\n
False
\n
\n
\n
41
\n
Interaction Threshold
\n
None
\n
\n
\n
42
\n
Fix Imbalance
\n
False
\n
\n
\n
43
\n
Fix Imbalance Method
\n
SMOTE
\n
\n
"},"metadata":{}}]},{"cell_type":"markdown","source":"**you can complete details about all functions here [1](https://pycaret.org/classification/)**","metadata":{}},{"cell_type":"markdown","source":"**compare_model(): This function train all the models available in the model library and scores them.**\n\n**I blacklisted 'catboost' as it was taking much time in k-folds, you can test if it helps in accuracy and other metrics**","metadata":{}},{"cell_type":"code","source":"best_model = compare_models(blacklist=['catboost'])","metadata":{},"execution_count":10,"outputs":[{"output_type":"display_data","data":{"text/plain":"","text/html":"
Model
Accuracy
AUC
Recall
Prec.
F1
Kappa
MCC
TT (Sec)
\n
\n
0
\n
Extra Trees Classifier
\n
0.6658
\n
0.0000
\n
0.3701
\n
0.6409
\n
0.6453
\n
0.4541
\n
0.4584
\n
1.3902
\n
\n
\n
1
\n
Light Gradient Boosting Machine
\n
0.6524
\n
0.0000
\n
0.3760
\n
0.6256
\n
0.6344
\n
0.4388
\n
0.4432
\n
0.5277
\n
\n
\n
2
\n
Extreme Gradient Boosting
\n
0.6435
\n
0.0000
\n
0.3752
\n
0.6178
\n
0.6274
\n
0.4278
\n
0.4306
\n
0.6911
\n
\n
\n
3
\n
Random Forest Classifier
\n
0.6426
\n
0.0000
\n
0.3728
\n
0.6176
\n
0.6267
\n
0.4265
\n
0.4296
\n
0.3988
\n
\n
\n
4
\n
Gradient Boosting Classifier
\n
0.6283
\n
0.0000
\n
0.3589
\n
0.6082
\n
0.6130
\n
0.4013
\n
0.4043
\n
1.6138
\n
\n
\n
5
\n
Ada Boost Classifier
\n
0.6024
\n
0.0000
\n
0.3498
\n
0.5848
\n
0.5854
\n
0.3544
\n
0.3586
\n
0.9083
\n
\n
\n
6
\n
Linear Discriminant Analysis
\n
0.5969
\n
0.0000
\n
0.2892
\n
0.5741
\n
0.5714
\n
0.3352
\n
0.3410
\n
0.0364
\n
\n
\n
7
\n
Ridge Classifier
\n
0.5880
\n
0.0000
\n
0.2509
\n
0.4973
\n
0.5318
\n
0.2989
\n
0.3103
\n
0.0383
\n
\n
\n
8
\n
Logistic Regression
\n
0.5853
\n
0.0000
\n
0.2602
\n
0.5387
\n
0.5411
\n
0.3005
\n
0.3098
\n
0.2686
\n
\n
\n
9
\n
Naive Bayes
\n
0.5657
\n
0.0000
\n
0.3083
\n
0.5614
\n
0.5588
\n
0.3155
\n
0.3183
\n
0.0245
\n
\n
\n
10
\n
Quadratic Discriminant Analysis
\n
0.5594
\n
0.0000
\n
0.3334
\n
0.5543
\n
0.5482
\n
0.2936
\n
0.2994
\n
0.0293
\n
\n
\n
11
\n
Decision Tree Classifier
\n
0.5121
\n
0.0000
\n
0.3824
\n
0.6239
\n
0.5551
\n
0.3108
\n
0.3236
\n
0.0574
\n
\n
\n
12
\n
K Neighbors Classifier
\n
0.4835
\n
0.0000
\n
0.2604
\n
0.4667
\n
0.4728
\n
0.1828
\n
0.1840
\n
0.0279
\n
\n
\n
13
\n
SVM - Linear Kernel
\n
0.4432
\n
0.0000
\n
0.2087
\n
0.3790
\n
0.3354
\n
0.1040
\n
0.1401
\n
0.0492
\n
\n
"},"metadata":{}}]},{"cell_type":"markdown","source":"**models() provide list of models in library and their id that can be used in functions**","metadata":{}},{"cell_type":"code","source":"models()","metadata":{},"execution_count":11,"outputs":[{"output_type":"execute_result","execution_count":11,"data":{"text/plain":" Name \\\nID \nlr Logistic Regression \nknn K Neighbors Classifier \nnb Naive Bayes \ndt Decision Tree Classifier \nsvm SVM - Linear Kernel \nrbfsvm SVM - Radial Kernel \ngpc Gaussian Process Classifier \nmlp MLP Classifier \nridge Ridge Classifier \nrf Random Forest Classifier \nqda Quadratic Discriminant Analysis \nada Ada Boost Classifier \ngbc Gradient Boosting Classifier \nlda Linear Discriminant Analysis \net Extra Trees Classifier \nxgboost Extreme Gradient Boosting \nlightgbm Light Gradient Boosting Machine \ncatboost CatBoost Classifier \n\n Reference Turbo \nID \nlr sklearn.linear_model.LogisticRegression True \nknn sklearn.neighbors.KNeighborsClassifier True \nnb sklearn.naive_bayes.GaussianNB True \ndt sklearn.tree.DecisionTreeClassifier True \nsvm sklearn.linear_model.SGDClassifier True \nrbfsvm sklearn.svm.SVC False \ngpc sklearn.gaussian_process.GPC False \nmlp sklearn.neural_network.MLPClassifier False \nridge sklearn.linear_model.RidgeClassifier True \nrf sklearn.ensemble.RandomForestClassifier True \nqda sklearn.discriminant_analysis.QDA True \nada sklearn.ensemble.AdaBoostClassifier True \ngbc sklearn.ensemble.GradientBoostingClassifier True \nlda sklearn.discriminant_analysis.LDA True \net sklearn.ensemble.ExtraTreesClassifier True \nxgboost xgboost.readthedocs.io True \nlightgbm github.com/microsoft/LightGBM True \ncatboost catboost.ai True ","text/html":"
\n\n
\n \n
\n
\n
Name
\n
Reference
\n
Turbo
\n
\n
\n
ID
\n
\n
\n
\n
\n \n \n
\n
lr
\n
Logistic Regression
\n
sklearn.linear_model.LogisticRegression
\n
True
\n
\n
\n
knn
\n
K Neighbors Classifier
\n
sklearn.neighbors.KNeighborsClassifier
\n
True
\n
\n
\n
nb
\n
Naive Bayes
\n
sklearn.naive_bayes.GaussianNB
\n
True
\n
\n
\n
dt
\n
Decision Tree Classifier
\n
sklearn.tree.DecisionTreeClassifier
\n
True
\n
\n
\n
svm
\n
SVM - Linear Kernel
\n
sklearn.linear_model.SGDClassifier
\n
True
\n
\n
\n
rbfsvm
\n
SVM - Radial Kernel
\n
sklearn.svm.SVC
\n
False
\n
\n
\n
gpc
\n
Gaussian Process Classifier
\n
sklearn.gaussian_process.GPC
\n
False
\n
\n
\n
mlp
\n
MLP Classifier
\n
sklearn.neural_network.MLPClassifier
\n
False
\n
\n
\n
ridge
\n
Ridge Classifier
\n
sklearn.linear_model.RidgeClassifier
\n
True
\n
\n
\n
rf
\n
Random Forest Classifier
\n
sklearn.ensemble.RandomForestClassifier
\n
True
\n
\n
\n
qda
\n
Quadratic Discriminant Analysis
\n
sklearn.discriminant_analysis.QDA
\n
True
\n
\n
\n
ada
\n
Ada Boost Classifier
\n
sklearn.ensemble.AdaBoostClassifier
\n
True
\n
\n
\n
gbc
\n
Gradient Boosting Classifier
\n
sklearn.ensemble.GradientBoostingClassifier
\n
True
\n
\n
\n
lda
\n
Linear Discriminant Analysis
\n
sklearn.discriminant_analysis.LDA
\n
True
\n
\n
\n
et
\n
Extra Trees Classifier
\n
sklearn.ensemble.ExtraTreesClassifier
\n
True
\n
\n
\n
xgboost
\n
Extreme Gradient Boosting
\n
xgboost.readthedocs.io
\n
True
\n
\n
\n
lightgbm
\n
Light Gradient Boosting Machine
\n
github.com/microsoft/LightGBM
\n
True
\n
\n
\n
catboost
\n
CatBoost Classifier
\n
catboost.ai
\n
True
\n
\n \n
\n
"},"metadata":{}}]},{"cell_type":"markdown","source":"# **creating 4 best model from default setup output and tuning them to see improvements**","metadata":{}},{"cell_type":"code","source":"#creating random forest model\nrf = create_model('rf')","metadata":{},"execution_count":12,"outputs":[{"output_type":"display_data","data":{"text/plain":"","text/html":"
Accuracy
AUC
Recall
Prec.
F1
Kappa
MCC
\n
\n
0
\n
0.7232
\n
0.0000
\n
0.4492
\n
0.7043
\n
0.7069
\n
0.5540
\n
0.5629
\n
\n
\n
1
\n
0.6518
\n
0.0000
\n
0.3929
\n
0.6264
\n
0.6385
\n
0.4395
\n
0.4404
\n
\n
\n
2
\n
0.5893
\n
0.0000
\n
0.3009
\n
0.5809
\n
0.5831
\n
0.3561
\n
0.3574
\n
\n
\n
3
\n
0.6607
\n
0.0000
\n
0.4807
\n
0.6330
\n
0.6460
\n
0.4586
\n
0.4598
\n
\n
\n
4
\n
0.6696
\n
0.0000
\n
0.3212
\n
0.6307
\n
0.6468
\n
0.4625
\n
0.4658
\n
\n
\n
5
\n
0.6250
\n
0.0000
\n
0.3118
\n
0.6057
\n
0.6111
\n
0.4059
\n
0.4102
\n
\n
\n
6
\n
0.5625
\n
0.0000
\n
0.2925
\n
0.5310
\n
0.5442
\n
0.3007
\n
0.3030
\n
\n
\n
7
\n
0.6875
\n
0.0000
\n
0.3355
\n
0.6467
\n
0.6644
\n
0.4926
\n
0.4959
\n
\n
\n
8
\n
0.5982
\n
0.0000
\n
0.4472
\n
0.5853
\n
0.5826
\n
0.3455
\n
0.3490
\n
\n
\n
9
\n
0.6577
\n
0.0000
\n
0.3965
\n
0.6319
\n
0.6437
\n
0.4500
\n
0.4517
\n
\n
\n
Mean
\n
0.6426
\n
0.0000
\n
0.3728
\n
0.6176
\n
0.6267
\n
0.4265
\n
0.4296
\n
\n
\n
SD
\n
0.0463
\n
0.0000
\n
0.0659
\n
0.0437
\n
0.0447
\n
0.0717
\n
0.0729
\n
\n
"},"metadata":{}}]},{"cell_type":"code","source":"#creating Extra Trees Classifier\net = create_model('et')","metadata":{},"execution_count":13,"outputs":[{"output_type":"display_data","data":{"text/plain":"","text/html":"
"},"metadata":{}}]},{"cell_type":"markdown","source":"**You can witness how easy is to create model and CV it**\n\n**Similarly, you can tune your model with best hyper params with just single line of code, isn't it amazing**","metadata":{}},{"cell_type":"code","source":"#Hyper params tuning via tune_model\ntuned_rf = tune_model(rf)","metadata":{},"execution_count":16,"outputs":[{"output_type":"display_data","data":{"text/plain":"","text/html":"
Accuracy
AUC
Recall
Prec.
F1
Kappa
MCC
\n
\n
0
\n
0.6964
\n
0.0000
\n
0.4258
\n
0.6772
\n
0.6818
\n
0.5061
\n
0.5117
\n
\n
\n
1
\n
0.6875
\n
0.0000
\n
0.3904
\n
0.6612
\n
0.6670
\n
0.4837
\n
0.4882
\n
\n
\n
2
\n
0.6339
\n
0.0000
\n
0.3100
\n
0.6103
\n
0.6176
\n
0.4055
\n
0.4109
\n
\n
\n
3
\n
0.7054
\n
0.0000
\n
0.4821
\n
0.6644
\n
0.6765
\n
0.5173
\n
0.5233
\n
\n
\n
4
\n
0.6429
\n
0.0000
\n
0.3187
\n
0.6198
\n
0.6275
\n
0.4226
\n
0.4257
\n
\n
\n
5
\n
0.6786
\n
0.0000
\n
0.3329
\n
0.6402
\n
0.6582
\n
0.4852
\n
0.4872
\n
\n
\n
6
\n
0.6161
\n
0.0000
\n
0.3227
\n
0.5829
\n
0.5955
\n
0.3778
\n
0.3821
\n
\n
\n
7
\n
0.7054
\n
0.0000
\n
0.3259
\n
0.6555
\n
0.6757
\n
0.5190
\n
0.5246
\n
\n
\n
8
\n
0.5893
\n
0.0000
\n
0.4346
\n
0.5618
\n
0.5676
\n
0.3264
\n
0.3302
\n
\n
\n
9
\n
0.7117
\n
0.0000
\n
0.4425
\n
0.6824
\n
0.6961
\n
0.5345
\n
0.5363
\n
\n
\n
Mean
\n
0.6667
\n
0.0000
\n
0.3786
\n
0.6356
\n
0.6464
\n
0.4578
\n
0.4620
\n
\n
\n
SD
\n
0.0408
\n
0.0000
\n
0.0605
\n
0.0387
\n
0.0401
\n
0.0668
\n
0.0668
\n
\n
"},"metadata":{}}]},{"cell_type":"markdown","source":"**And you can see the params of your best model as well**","metadata":{}},{"cell_type":"code","source":"tuned_rf","metadata":{},"execution_count":17,"outputs":[{"output_type":"execute_result","execution_count":17,"data":{"text/plain":"OneVsRestClassifier(estimator=RandomForestClassifier(bootstrap=False,\n ccp_alpha=0.0,\n class_weight=None,\n criterion='entropy',\n max_depth=20,\n max_features='log2',\n max_leaf_nodes=None,\n max_samples=None,\n min_impurity_decrease=0.0,\n min_impurity_split=None,\n min_samples_leaf=4,\n min_samples_split=7,\n min_weight_fraction_leaf=0.0,\n n_estimators=60, n_jobs=-1,\n oob_score=False,\n random_state=123,\n verbose=0,\n warm_start=False),\n n_jobs=None)"},"metadata":{}}]},{"cell_type":"code","source":"tuned_et = tune_model(et)","metadata":{},"execution_count":18,"outputs":[{"output_type":"display_data","data":{"text/plain":"","text/html":"
Accuracy
AUC
Recall
Prec.
F1
Kappa
MCC
\n
\n
0
\n
0.7054
\n
0.0000
\n
0.4297
\n
0.6798
\n
0.6898
\n
0.5199
\n
0.5228
\n
\n
\n
1
\n
0.6607
\n
0.0000
\n
0.3768
\n
0.6339
\n
0.6389
\n
0.4384
\n
0.4438
\n
\n
\n
2
\n
0.6696
\n
0.0000
\n
0.3239
\n
0.6391
\n
0.6500
\n
0.4579
\n
0.4622
\n
\n
\n
3
\n
0.6964
\n
0.0000
\n
0.4782
\n
0.6620
\n
0.6663
\n
0.5003
\n
0.5080
\n
\n
\n
4
\n
0.6429
\n
0.0000
\n
0.3020
\n
0.6162
\n
0.6195
\n
0.4120
\n
0.4176
\n
\n
\n
5
\n
0.7054
\n
0.0000
\n
0.3440
\n
0.6658
\n
0.6849
\n
0.5283
\n
0.5300
\n
\n
\n
6
\n
0.6339
\n
0.0000
\n
0.3300
\n
0.6009
\n
0.6126
\n
0.4064
\n
0.4119
\n
\n
\n
7
\n
0.6964
\n
0.0000
\n
0.3225
\n
0.6521
\n
0.6664
\n
0.5005
\n
0.5071
\n
\n
\n
8
\n
0.5357
\n
0.0000
\n
0.4041
\n
0.5580
\n
0.5117
\n
0.2248
\n
0.2302
\n
\n
\n
9
\n
0.7027
\n
0.0000
\n
0.4087
\n
0.6977
\n
0.6863
\n
0.5084
\n
0.5160
\n
\n
\n
Mean
\n
0.6649
\n
0.0000
\n
0.3720
\n
0.6405
\n
0.6426
\n
0.4497
\n
0.4550
\n
\n
\n
SD
\n
0.0499
\n
0.0000
\n
0.0541
\n
0.0388
\n
0.0507
\n
0.0859
\n
0.0857
\n
\n
"},"metadata":{}}]},{"cell_type":"markdown","source":"# **Plotting ROC for initial/basic model**","metadata":{}},{"cell_type":"code","source":"plot_model(rf)","metadata":{},"execution_count":19,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{}}]},{"cell_type":"markdown","source":"# **Plotting ROC for hyper parameters tuned model**","metadata":{}},{"cell_type":"code","source":"plot_model(tuned_rf)","metadata":{},"execution_count":20,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{}}]},{"cell_type":"markdown","source":"# **This is an interesting way of seeing how our model create boundry and how it fits the space of features, below you can see our model is overfit**","metadata":{}},{"cell_type":"code","source":"plot_model(rf, plot = 'boundary')","metadata":{},"execution_count":21,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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GiDIzsnNq+/9iafnPYJBgyopaFhON/9/jdzcqniKgoKCgoKVYdGbwtefZ/tMd1by1r9AoL0rHZ3LgghuOVL3+e+ZQ+i6z1f027fth0pJTfecDO7duziv+d9kU9OO6ZHnFUzaSt5vDRc/cWnir9v+VTyeGE25eAqtk8RCDg6H3dHHt+9aw+P/PT36CHBtPcHcP+1t2N5deZc/98Mqx9aEJftOWBH2w5u/cVP2L69lWu+ch1/f+rhrKtzJY8Xg0vJ433CZ1+IX41ZAkoeL8ymHFzF9qn7fI7Ox92Rx4fVD+Ww44/E9c/tjAsPRv/nxxz2qSOpHz6sYC4b77ChHH7EYbjdLhobR1MzoIb2Pe09ir1qJm0FBQUFBYVSYfp5zeweEObtKQF2Dwwz/bwZPeac9qlP8MbrbyGEoH3PXvxdfgYPGdwjzqqZtJU8Xhqu/uKzL8SvxiwBJY8XZlMOrmL7LEQez4dMkvb6dRsYdOoEvvnSrxl0ygTWr9vQ4+zxhhENnDZjOtdc+S2uu+Z6vvHtq3PeK1fyeDG4lDzeJ3z2hfh77NMAvJEf98G++N/ZjvFKHjOXz4NmWKDbT5i6IUCTcZtixeXUTsnjpfNZSnkcYMKk8fzPrd/A5XLxP7d+gwmTxheluMrnPn82d933S37/4O84+ZQTctqq7HEFBYU4au8G17jI35oOUkT+7rwcxMayhdVtHPL7FmrGddgf+0ML78+dSWB9zyRIBYVKRdVM2koeLw1Xf/Gp4rdDiuoeMyWPF2ZTDq5i+yxl9nhP7FTt8SxQ8nhpuPqLz74QfzF9anp1j5nKHi/MphxcxfZZanm8u3aq9riCgoKCgoJCRih5PJ+dksf7hE8Vvx1KHi/cp5LHy+tTyeMRVM1KW8njpeHqLz77QvxKHk9AyeOF2ZSDq9g+lTweQdWstPsihJG4KAhbOhJoHXoAjYGPwOOKP6eFLDSHV3MKClkRAhld4MkdQEP08Qo/tDQsMgUpQq74+7Ghwt+PQv/Bosef4blnWiL/aLD6/TW0/OvpHnFWzaTdF+Xxj+6cS3BcpPj9jS0T2dbhQ9fgob99H/HTmfHnJs77I75NuwryV2y7avep4oeuq5L+0fJLjZUyZpHmEfatXVYgzJrLm2nyPpfWWCKm/Ct5vLxcxfZZjfL42Z/7NGd/7tMAvPXG2/yj5YWcXE7mpqqZtF26G0vk/3Cd2BXC5VQeF/6ugm20kIkWPWC9ZghfWGNCaC+alLbnNJmfq7tx9ST+avLZF+IH1JhF4fJ5sLpCPbYpxGc5xqyY77O3uYrtsyB5PM9cq2mabbJd/9Ea3n+7xSZhSyk57MgzGDdhckFc2fDHBx7kppu/lz/2PKiaSbsvYuI1D8X//mv0t15TG/kyJz2noKCgoFA6DKwbiuafz7QjW+OPvfqfkQwcdEFR+Fe9t5qRI0c4akCSD1WTiNYX5fFK4OovPksZ/6NhUXKfqva4HSp7vDCbcnAV22cpa483NIygS5wRf1xKSZc4g+HDGzK9PCdXJix6/BnO+q+Zee1U9ngxuFT2eJ/wWar4W8KCuujvUvosdvZ4tX/mKnu8MJtycBXbZ6mzx0858xpef2cUAK+9PYpTZ11TtOzxN994myOOOjyvnSquoqBQQoSEYKeEWR6dnTLyv4KCQnUittoWIrLKbmgYURTeHTt2Ultbg8fj7OIkH6pm0lbyeGm4+ovPUsT/SBg+E70w/owb/hpOtymWTyWP26Hk8cJsysFVbJ+llMdjOOXMa/jdg2M5ddY1Oe2ccMWwa+duhg4booqr9MROyeP9z2cp4vdpUBftjVun6/i0dJti+VTyuB1KHi/MphxcxfbZG8VVGhpGMHfe/fFVdjHk8UOmTOb2O3+mao8rKJQbAQkdUUm8QwgCqqiHgkLVY+Kkg8sdQk5UzaSt5PHScPUXn6WIf44Hno4eSk+b8AVPuk2xfCp53A4ljxdmUw6uYvvsDXm8O3aq9ngWKHm8NFz9xWcp4jd0neEaLA4LGjQwdD3Nplg+lTxuh5LHC7MpB1exfara4xFUzaStoFBpeDQsaPbodAAzPOqrpKCgUHpUTUU0JY+Xhqu/+Cx2/Ev2dcb3Z8/OMmFXcvzV7lPJ44XZlIOr2D6rsfZ4oXZKHi8Gl5LH+4TPYnKFhGAnMu/+bCWPJ/BoWCh5vBt2Sh5PQMnjEZRl0g4EAsyYMYMFCxaUw72CQo/wSBg+44r8nWl/toIdsapxS/zBcoeioNCr6Oryc8O3b+Jr877JvC99jVdfeb3HnGWZtH/3u98xZMiQgl6j5PHScPUXn05s3gw7s8u3P7sQn07tqjV73FY1LhTOWzVOyeN2KHk8gWrMHn9m0XM0jW3krvt+yS0/v4lf/+9vc3JVpDy+bt06PvzwQ0499dSCXqfk8dJw9Ref+WxMIfhtaAjCMPJyOd2freRx8laN665PJY8XZlMOrmL77A153DRNlv7jJUzTzGnnhAtgyJBB7Nsb6fe+v2M/Q4YMzslVkfL4z3/+c66//vredqugkBEbTcHNXfX8MjCa2RzD7Xvrubmrno1m9hXhHA88bUX+zrQ/WyEBp6qEgkK58cLy1/j5n5/ifd84fv6nRfxz+Ws95mw+83Rat7dxwecu4aovf4OvXvuVHnP26qT9+OOPc9RRR9HY2Fjwa5U8Xhqu/uIzm81Yt85kPcQkxjNRr2eiGMfBeoix7uxfDUPXGY6WdX92qeKvlDErxK7QqnFKHrdDyeMJlFIeD4VCLH1/O6NOPJOBw+oZddIslry/nWAwfx5GLnn8uWeWMnLUCP7v8Qe583f/y69+cVePY+/VSfuFF17g+eef54ILLuDRRx/l7rvv5uWXX3b0WiWPl4arv/jMZTPb2MsW2lkqV7OFds439ublmzloQN792Uoex141zsqvSih53A4ljydQannc7atJ+7+n8vg7b7/HtE99EoDJB09iR9tOTNPKau8k9l7dp/3rX/86/vdvfvMbRo8ezQknnNCbISgopGGFpdHONq737eZn4eGssDSmObiczbY/WyGBSNU4EVElPB4Msp+wFBRikLgQuGyPmbIOR7N2N2EG/Dn/7w7GNB7I+ytXcdqM6Xz88XZqa3243a78L8wBVVwln52Sx/uEz1w20zwa0zztgM4Pfe0g858YKin+SvfZ7NF5NCyYrcm83yclj9vRX+XxzcHmdMOgRkjU5efrRnEVwzA487AD+NdLixkw5ZN0rlrBzENHO+qBnUse/+x5Z/PTn/yCr877BpZp8e0bvpE39nwo26R99dVXF2Tv0t1YIv8B4MSuEC6n8rjwd/XYphxc/cVnX4gfqNoxm+3Ri+rT5fNgdYV6bFOIz3IcZ8V8n73NVQqfGvnXUS7dnddI07S0yXb6CcdywrSjWfbivzntsrNxu90Z7ZxwxVBbW8PNP/thXjtb7HlQNSttBQUFBQWFUsLtdnPG6SeVO4ycUDflFBQUFBQUqgRq0lZQyINHw7mreCkoKCj0Fqpm0laJaKXh6i8+u8sVq5vdkjJxlyP+ahmz3vCpEtEKsykHVyl8Oik+agkTS5oEw9nHuFK6fAXDASyZmI8qbp92T6D2aZeGq7/47A6XrW52SjevmF2uVbgTG6exVes+7VL5VPu0C7MpB1cpfDrZ8OXS3QjCrN32Op1dnZhhK+3HMkXGx7tj112uzq5O1m57HUHYFns+qEQ0BYUseCQM50bPJ7G62Zd6E88nr8Kbs+zZdmKjoKBQfGztXMnHH6zBlWH7l655EDL/Ct+JXXe5LGnaJmynqJpJW8njpeHqLz67w5VeNzuxYg50dbFTwhxD55GQICREWjlTJzaljL+ndpXsU8njhdmUg6sUPp3K4zEIwpknVBnA0cndiV0RuZQ8XgwuJY/3CZ/d4cpVN/sRK3/3Kic2hcRfDWPWWz6VPF6YTTm4SuHTqTxeDJtK5aqaSVtBobdhq5ud0s3LJ0Xe7lVObBQUFBQKQdVM2koeLw1Xf/HZHa5I3WwydvMKiPzdq5zYFBJ/NYxZb/lU8nhhNuXgKoXPQuXxnthUKlfVTNpKHi8NV3/x2V2uZo+esZvXRYNqs67CC7FxGpuSx+1Q8nhhNuXgKoVPJY9X0aStoFAuZOrmlWsVXoiNgoKCQiGomrOIksdLw9VffJYi/myr8EJsnPpU8rgdSh4vzKYcXKXwqeTxKpq0lTxeGq7+4rNU8efqqe3ExqlPJY/boeTxwmzKwVUKn0oer6JJW0FBQUFBob9DFVfJZ6fk8T7hU8Xft3wqebwwm3JwlcKnkseraKWt5PHScPUXn30h/lx2sfrmlRp/sX0qebwwm3JwlcKnkseraNJWUFDIjGydyBQUFPoeqmbSVvJ4abj6i8++EH8mu9ROZIGurqL6LBZXsX0qebwwm3JwlcKnkseraNJW8nhpuPqLz74Qfya7R8Ip9c0tRy6rfsyUPF6YTTm4SuFTyeNVNGkr9B/k6z+tkEBaJzKpxk5BoS9DZY/ns1PyeK/6tPWf1qov/t7minUiq9N1lhsWGw+Gh12JiVsCUz6CYwL26/NqHzMljxdmUw6uUvhU8ngVrbSVPF4arkrymXp/1jSMovms9jHLJo8ndyJ7pwvOuEjjK3fq8Z8pF8DQDPNDtY+ZkscLsykHVyl8Knm8iiZthb6P1Puzf+l0thrpz0iubz5ZarzXoiFlZD0ipeS9pZLx6muuoNBnUDXfZiWPl4arknym3Z8Vzu7PVkr8pebKZpdc3/zEl+BfL0cO2heXS05annltUu1jpuTxwmzKwVUKn0oer6JJW8njpeGqJJ+x+7MQ7T/tsCtWpcRfaq5cdrH65hN9A3hvKQiRe5Vd7WOm5PHCbMrBVQqfSh6voklboe8j+f7s0yZcPMDZia3YqPbs9RNfgv93m8i6ylZQUKheOLpEWLFiBe+++y6apnHkkUdy9NFHlzquNCh5vDRcleQzcn9WxPtPu0Ohovl0GteSfZ2J7PUitNN0gmJzjUfnxBdE2ipbSJ2YdBT0+/DIIAAaFo+ZIq0bWSUfZ0oeL8ymHFyl8KnkcQcr7TvuuIPbbruNtrY2WltbueWWW7j33nsdBVlMKHm8NFyV5jP5/mxvxx8Sgp3IePZ6KMc99UqTx1O5jjXTv9pbQqezLnAu6wLnsVU7i3WB81gXOI/FYU/GMqiVfJwpebwwm3JwlcKnkscdrLRfffVVHnnkEfTo/UXTNJk7dy5f+cpXHISpoFA48vWfLhUeCcO50fPHZ9zw1zBc6nX++kfD6avVSkKTt4WNgZmE5OD4Y6Yw2esKMsej80hIEBICw2EugYKCQu8j77dTCBGfsAHcbjea1vv3ypQ8Xhqu/uLTiU1a9nqOwzyVL1PTjt7KHi+UCxKS5DJ9ub0MapJSWcmfuZLHC7MpB1cpfCp53MGkfdhhh3HllVcyf/585s+fz5VXXsnUqVMdBVlMKHm8NFz9xWeyTbZEs7Ts9RxniGS+1KIwMVm9nPJ4PsQkyWGunVkvVCr5M1fyeGE25eAqhU8ljzuYtL///e9z9tlns2XLFrZs2cI555zDDTfc4ChIBYVKQ642lnM88HS04cbTJnzB2bkkvWmHs4VDSZHtwkTTBBomhtaBhskeq97xhYqCgkL5kXdav+qqqzj55JO5+OKLGTt2bG/ElBFKHi8NV3/xKQKB+Ip4jpH5/q2h6wy3ZDx7Pde93WSf6bK6KEn8Trls9dtT7rE3elsif0g31Jg0CsFCE+YY6RcqlfyZK3m8MJtycJXCp5LHHay0r7zySjo7O/nJT37C2WefzU033URLS4ujIIsJJY+Xhqu/+NR9Pkcr4pmDBsSz1536zCarFxJ/vr3hTuVx0zAySvUxbArM5EP/bNZzIR/6Z7MpeCGD8Wa8UKnkz1zJ44XZlIOrFD6VPO5g0j7qqKOYN28e99xzD9///vdpbW3l2muvdRSkgkIlwWmiWaYM8DdzLAZSi8I4ldVjWOIPZpXsC8XDnYGCpfrT3TWOLlQUFBTKj7zf0t/+9rd8+ctf5vLLL+fFF1/kggsu4OWXX+6N2GxQ8nhpuPqLTxEIOEo0y8RlCsFvQ0MwRebM8OSmHcmrVSdxhYRgZyicd2+40+xxX7RNJ+S+MEmVJJMvVGKr/kr+zAtcUXQAACAASURBVJU8XphNObhK4VPJ4w4m7WXLlmFZFieddBIzZ87klFNOYdCgQY6CLCaUPF4armrw2VLr5XeTD6ClNvOmaadcTlbEyVwbTcHNXfX8MjCa2RzDrwKjubmrno2mSPOZXBSmkLicJrE5lccDuu4osSybJJl8P7ySjzMljxdmUw6uUvhU8riDSfuxxx7jjjvuYNKkSSxevJhLLrmEK664wlGQCgo9xe3HTULcPofpd16MuH0Otx83qdtc2VbE2TDWrTNZDzGJ8UzU65nIeA7WQ4x1Z35ddwqrFLI33AkuGuBzJNW3hN5Ieyzb1jUFBYXKgaOzTGtrK9u3b6etrQ2/38/gwYPzv6jI6IvyuMzw4zetjI8X6q/YduXw+ZwumXrZiYwe3wDA6PENTL30xLQVdyHxZ1oR5+KabexlC+0slavZQjufN/YiASsQyvr5FBKX073hTuVxdyiU98JkhXifJlaxQrxvezytn/m+rrz+YrEVy07J43Yoedxup+TxHFu+PvjgAw466CCmT5/OpEmTOOGEE7jiiis49NBDHQVYbLh0N5bI/+E6sSuEy6k8Lvy5T3CZbNbdexnBscMBuLFlIts6fNR6XDzwl+sRP5sZf27iV/6Ib+OugvwV264cPj9sqkcueZ/RXzkl/tjoCQ28OHoozR9sL4gr2SbXilj3+fjbvv1xmxWWRjvbuN63m58FhvGM/5Mcok/EVWtg+SMNTZq8z+HV93XrPc7xwAIL5ui5V8YxOdXJ+2yWXVlLqoaFQHpWM8uj8bBcjRmeHH8ubdWvO1tpl+M4c/k8WF25G8o4sSnEZzm+J8V8n73NVQqfGvnXUcWeA3qbKx+yWtx8883Mnz+fpUuX4vUWUIBZQaFIkGu3M37lZt4c5OWYL3wKgK0f7eCgrXtK5jM5k7vZozPNozHN0w7o/LC2nU3BYYSEiaEF8WOgIXAkx2SBoesM110sDocdSfZOke3C5HntDS5yhwGds91hHrSWMyH6XGzVXxe9Lx7QVDa5gkKlIe+3slIm7L4oj2fiDphW+nMpdv1BHg8JwTB/iLNcGtpfXsEMmWz9aAfv/nk5zV3Bgn0WK5O7ydvCpJqFjJFP4dX20Ohdilfv6LZPgGZN5t1yVaza44Nd7bbV9FDXzvhzaYl6rvyxO/FZiJ2Sx+1Q8rjdTsnjOVba69at4zvf+U7WF9522215yYuJviiPZ+L2uV3pz6XYZeQynNkJ0s/EwjscPZA4eWtYaaH1tjye3HHrs6Ewv/r8XZzgcXFdyoTt1Gc+m58ELMZpWt4uX7HxE97hjJEvAJFrqkyHSSFjMVvmjx/AtEJxZ1rIQpMyzS6bT4GLvdYgOsSu+Gp6jzUC6Q4jcOHRsfUz99XWlv4zTzlu3eN9mGu6QMbGWkMaboQrcqqSIQ2shKSqGZB8SIuQK07YU3k89btSrO+JwGXjysQTQ3+Vx6WhpX2pXBNq0TRNyePZnhg0aBDHH398XgKFykDt3eByUGV2c2CGrTUjgEtL3J+F7PdoexOp91cP7gzRbHRfrv1bZ5DZWV5+d8DiWJfG8rCkzuuK+4yVI01GbPySx6w3x+uj38zNmuuQD5sDM5guBrDIfJKLDItFpofTxIlsDkZOA03e52j27OvVFqO1d4NrXOJ/TYf9XwKxMTbWg/jo9ouRB3lBB/el29A3JE58vl+78I1LTK5rLm8mtCHzllSJC4Er5yQZg8DF5kAzIZngSv2eNHpbMFI+d1PWoRO5sNSwkBn8bQ7MwNIaynL8VAvMu0Yix9oTPOQOHTm6TAFVELJO2g0NDZx77rm9GUtO9EV5XAuaaDFpKLpiisnjtueEPYhs/qRjGT0TX+7TWG/J40LqaIj0+6s5Pod8PiN7jwUtFmm1uPebFnW6xlkenR1S8HHI4gDDlcenTBuzWNzJXWuzxZU6KRZy/GhBE4RAC1tpx4UTLrfuQgsfwmJtJXp4Cu4MV/ax2Ar9LDONQdxG6oT8HjySjM/HIEW6T8+87YTvHRU5iUffc0xSXXN5c1auVNl1czBi2+htwdASk2TQ78Mj7QrOpmAzYWmf/LPx2RDU4jE2elvYHprGKOM1mz+JZuOSuBDSvqqX0WOrv8rjnnnb0w11Df4wCsYbufkqUNIuJlfWSdvjKbAWY4nRF+Xxidc8FP/bN/sWGDY6Lo8nP+eEq+sKqH0gv91Y35J0vpr8MmhvyeN6dHXrNKs6n898TULuDMPVUQn8XDfcFoSbye4zNn7dHbNMzTycHj+Q+7jIxzXWt4RNwWaOZTL/xM8p+kFIZFIynXOpPZOdnkGZiNtoAl9NGOHPzaXpPsDuUxoa7mtaI8+HIjEm5HELTU+5CA26QGppsquGBUi2BE+12fsGWAQ6M93At9/4yMZn46pJcMX8pPqTuHDVJLi2BE9L45FRab6/yuPZxjac9mgGvv4qj//+97/P++LeghY08bbtwj+8Jq+td+e+nHbScDvcnd67MKwwvnCQcZ170+5T9kcUK6s6+d54pvvU41yaTYY/xCWy7nHuqWyc7wKimL6yoSna5WtyTS3C/xGbgs2M9LyaNZmuEmDeNwoZXV2lyuOH/L6Fmgl2afn9uTMJrE+vJdHobcm8Nc9bixDpFyebgs2ERF10Ak2/es/El40rGRsDM7FoyMmzMTAz7TZWf0K2sV2rX0CQ4WWKqjLgrP5amXHQvD9CaytIB/tGNT2n3Yf3XEb4wKHg4IQoA4Feqz3+pwU/jvyRJ36n/optVw6fzZrkUfJXGsvFla1tZgwbLGmT4TdYEsOtpflMXSF3Z8yyXUAk2z0aFgwF6oDbAxbX+Vx532Mun/nsYpN4MbiKYZdJHpeQdu/HJi9n+Y5mkl0zJQ1mK3wUa2O6KTqBZuOz+8y8qkz1WamSdqXI45BlbB2cjytR0i4mV1VM2lA8eXbSlX9yJG2CMwnUaWyVXMChkn3my6rOx5Xv3vg1HlhowiUGPG5Ck0tntkezrXQzrZB9AwqXx7NdQMTsWsKCGiHZrmnMNXR2SsHioMUsr6ug4irV/JlnkseNyz5Os4tJqqsuOTMrV6rsuil4Zsakr0xxbcqw0s3El+YzpejO9tCnGGX8O81npUralSKPZxvbkMzf96Kvy+OO9LcXXniBhx6K3EvbtGkTsofy7W233caFF17I5z//eZYsSb/HqqBQLORrEjLQ7aJDSJ4NCz4yJQ2a5O6AZWuVGSvv+WhYxFfIj3Q4u7pORq6SpbELg91ofDb6vf2sG95SNcAVFBSSkHfS/sUvfsFjjz3GggULAFi0aBG33HJLtx3++9//5oMPPuBvf/sbDzzwALfeequj11W71FupXH3dp5MmIVf5XLxqSg52a8zy6NTpGqe7iBdY8WnwqhWRrF+1wG1JngwOSBTCcRhXtgsIEQjELwxSV+PjdY2/hotXXKUQu0qRxzOhmLJrbxQ6Sa1Tn2qXrddAf5bHM9mp4ioOJu13332Xu+66iwEDBgDw1a9+lffee89BiJlx7LHHcscddwAwePBg/H4/lpX75AeV3T6vmlpziuheVZn0v+ltiD+e/FyxfHbXrlhczR6dDpcnZ8WxCboWb5bxuehqOraq3m9JdkoYYkkWhEbxHzmOuRzNj4LjuLpzBP8OZD5+U+N6wsJ2AfGElbCLTdapq/GgjEzkTltzVuL4F2IXkcfzo7stHzcFzyQohtqO99TjX2RJPEvli+y/Nm0/NTWB+N+bgzMIywFsDs5gnf/c+E9IDrJxbQqeyYf+2bafmDSvWnPa7bSQhICI/GQRoCqxnWYxufJaxKRwLbq50rIsR5Ns1qBcLmprawF49NFHmT59Oi6Xw3qJCj1CcsGIWGGIzYFmLG2446IRTgtTxOxSq0plen2mKm2RLR+5fTixi+HCAd6c91Mz3W+O/e6KTuh1uovnOk0OYzIT9Xr2ixBrWMU0n5Hx/JFcaKMlbFIXfbwDGIxGHZKWsGBmTUI6n+OBBSbMMSKr8f9ySZ6yetivMwecFhspFWTQhRVd6OpYyB30pJR7XmhY6Vu+dIuAP9MxaF/1GFqQQNKxGslwtmfddyd7XME5kvdvh/90QHxXQX9C3kn7mGOO4YYbbqCtrY0//vGPLF26lGnTpvXYcUtLC4899hh/+MMfHNlXu+xXCVyRClORqcNWGKKAohGN3ha82h4kOrHVSKTyU+T/oN/Hx4GT4wUlUotUxApbJBe0yFTIotHbgubX0opexLC462gO0sfH7QzZBRrIaIEPSeI3aIT8Htwy+8XhOlPS4bYnrHUIwS5rFMNcO6mLdrz6vncHvwm287HYh4ngPKazzp/laxQdM1OY7PREqpA9EhJ8WtN4Srq4yBA8EhLs7TS4wO3icdNijqGzWVg8G12NLxUaX/CU7pjdHJiRMVGqO1zdsVt9+Yx4clGTdwle135nGcLdlF0zbvuSOtQ4yBtwYFdMqd2pXaVyldpntsOkEiXtYnLlnbS/8Y1vsHjxYnw+H9u3b+eyyy5j5syZjoLMhn/961/cc889PPDAA9TV1eV/AdWfFVsJXGN9SzLu/ywkw3NzsDmeFRvjeV1fyIny9Eh5z1oDS4YyT/wkLgiSs2yz2WWzMYXgMf7Jt8XYuJ3w+4l9jRu9LbSGj7PtP44U9kisymN7cAEO8CzhA+njidBu5vokC6P3mx8z3ZwujucfLKdDtFGn6/wppPEe2znHNYGnrY1oCP6LgzPu5Y2N2TJ9OZdEO2t9xg23hwTXGTL+/8OmmxnW5xjseorF4SDHuDRWWJIjXVr8PnwpssdNf5BG3/MR3gwr7t74nqQW+9F96Vn52Qpt+DsNNEMUXFylmPF3l6tSM74rJXvciV22Np19PXs8r8V9993HvHnzmDVrVl4yJ+jo6OC2227jT3/6E0OGDCkKp0L5sEK8zzB3iFfD6zhaO6akvlpFB8/xAV7cXMARLGAlAWFyljmFT3hftK2gcu0/jj2/0RTMDzXgDQ3iAqaw3FrHd7r2UyMl/9B2MlIzOWTAE7zst3ja1JhjwEA3HBdu5Qlh8X39aEZ7X8erv5+zGMZgV6tNej9IF7b/h2htTKpZyCTg0XBkX/okaybLxT+4yFt4lrpTpNahr9Qa2NkKbWzwn8CE372Kb5xdol51+UwCG+yfhYaVsyObgkK1IO+kvXbtWjZu3MjYsQ66UTjAM888w549e7j22mvjj/385z/nwAMPzPm6SpCXK8VnpbT/M4WJ9KxmlkfnYbkeM3wEBJzdHbUCYf4h3uF0/QjHPkfqdTSKQdQzgIl6PZ0ixC66aDBrIU8uS6axGOvWmWyG8IiDmajX0yVC/EduZK5+HK+Lx+MT5kCXxjAN/uK3eEc24MHLbDmFv7OKQMDgi4ZgiVjDqdqxaT5XiNV8rAk6RKTyWocUrKvz0REIUKdFpfgkxTW5qMvnPbXAPlv8QiZuS2RC6m0ADcteD10mbhfIFJ7UGtiZanLn85nqL9VnvtrjmQuduJAprxOBAE3eFsyvwf40jsirkuvDZ7r/nMtnd+2UPN57PpU8ngVr1qzh05/+NEOGDMHj8SClRNM0XnjhBUeBpuLCCy/kwgsvLPh1lSAvV4rP7nLlyootRMKKScHJsu/ZbpMHreXM8p3hSOp6Q1/DWGM1K0JuPqkfmtdnDKcwgedYy3bRgYlgFpNx+TxIy5UxoS0G4R3Ogo6PuSDWDCNq+3ljP3cH9rJddmBqFj8YEsAdWsjEJJsuKTnLLVmMxlQrhM86JDLJywmY+ruskRqNnvWsZwPNnsRXKmAMQ9vfyjVujb9FC7gs8nr5zF/msegL93JROMzTJsyuG4kI7bbFmyxbx+IHbK0hM0H3+SCQOo0lITrz6T4fWsr8knpLI9ctjORkxUJ8Etib0SQmz7uyHdvRwzZW9CYm76dK+gJXYux89laaxWihquTxyvGphSQykJ5j4N6hYzbkzj1wYlMuLo7NaZJ/0r7nnnvyBqNQIQiRM4lnS/C0eCJa8v29WFZsbDJOTiyL2RlaEH+0+XHs5B5J0ErIvENduSeUGExhIuRKZhkaD8vVmOHJGbtNZcIq2mhlP3M5iof4D6to4wiast5Dj8X/H3MVg/g4XoZ0S/A0QqKOlaKNVrZxCUfwIO+wuHMqU8z6+OskLo4TFou0SCLZQ9Z+ttJBq1yLKQVnWKfyH/0pLjIED4dcrOk8J/5eWoL/Yq4nck96qGbxrCkRlx2Pb6CPPbMO59kFb0J4KrvNifHs5efFu8zQp0ZbOsYaeUQynIGMWc7JSM2ETl1hxt63T7cISxfJU1nqPd/UbOlkJGdgJ/vMtKJN9tkglmVc8W4JnsZIz6vUJO0G0DQBUrIleBqN3qX8y9obL3ozsybxmtT3FxRDAK0iW84qFA/ur7VmvApzTahF+yj3hZMTm3JxcV5unrxnyldeeSXj4+eff36+lxYVlSwvV4o83nVVbrsmbwuboj2KbSfXaFZs8nOtoWl2O6mzSTstnukrcbHbGk6H2B7PuN5jjXAkddlX6GEetJZzBqek2WXiOkwfxWGMAuAyPpnRTsOM9zFu9LagsZcVJsxKKkMau+c9CfgcAOuZF5hJSAwBZPw+6qbADDR9EFr4YBZrK+mSsFfbzPU17fykq4m/a09wrVvG38tD1kucwUkADNMS97L/y+PiprDkgjnT2PrRDgJtHexHMmfAeyBXQY2gJSwYC2xgLZOtMxhpvGb/jCB/lnOeDOf4vf6UzxwyTLhFyqq2+dQz28VsREC3PbYpMIORxmto7LWVkg10dWXMW0g+xt3BdgQDkwPN6Lt83/PkiyU7Yl2+nLfNzX9bqre5euIz05ikfp7h+xozbvkKZ01RK8ymfFy5kXfSfuONN+J/h0Ih3nnnHY455phen7QrQV6uFJ894WqKSoeZ7JKfS7XTfT6aZOKxjYGZnGadyCIzsgJdZLo5TZyIqza/1JVxhZ5hu3Uhspnoyp49Pj+Yu9NXDJomqKkJRFsrSts4xJLE5tXoQDt6TS23aJv4v5C0vZdhrlYmGQsBeNm01z0fpGm8ePVDHLR1D017/fH717rPR6Bzv21Smm4stVVvK1Xt8UzHQ3e5imGXahOLL+0ztODSLGev2GuK2Tugu/FnwljfkqL2P6hUrlL7/FC/LGPHr36fPf7Tn/7U9r/f7+eGG27IS6zQt6FpAo9OfAXqMSc5lrgzrdB7itQM4+RVWL5OX8mvSS2Okdw4RJh6WsJbroYkFw3w8VhHV7xQytVuifHB9ow9tfO1EO3vSPsMLUFF9thVUCgxCj7qa2pq2LRpUyliyYlKlarL4bMS4m/ytjCpZiFfGPA+HcA0fQLgLBP0NHEii8zIDLXI9HCaODGjXXezSh8N2yflXI06UpH8PpMn14BpsUgMjdcbj9nlakjiDoXS6p7HGoPM8ujx2uYiEMhwYZEeV388zmJI+wwdqPaVFH+1+Kyq+LO1ZK3AjO9icuWdtC+66CIuvvji+E9zczOjRo1yFGQxUe01lSuVqxg+k7cpOakj7Nbd6Nrh/CxgoYen8CLvZ7TrTn3j5Ik2hjkeeDoqv2fq9JWM2PuMTa6xeuM3Be31xl8VEVUhV0MS3eeL1D2HeN3zWGMQSKyodZ8v74VFf6k9ns0m9eLo4kG1vRqXU7tq91lV8We5/VuJ9cKLyZXXInk/taZpDBw4kClTpuQlVqg+JNfzlkl/aynP64YFYWxXupom0KQZzzKPZT5ny4Z2a0GOdOm8a7VyhNHGipCLY/XMlcWSkZzVHctuN7QOQGbse23oemRi1V0sDoezdvpKRUyuzlxv/H2Or3UjopnJzR7dJqOnIvnxbFJ9as3xXBcW/RGRiyNhuzhSDUsV+iPynr0WLFjAtGnTmDZtGsceeyxTpkzh8ssv743YbKgIOaZCfJayDvU6/3mExCDb3zGb2GPuuwahN9k5YnL5GPkUhraPRm8LG9x/Z6yxlg3uv8cfm1SzkCbv3zHF+5zl0TjA08oeIdA8K2n0RuxiyFY7emLNwrhdo7eF0fIZDL0j4yo2hmZNxle8qfJ5DBKwAiEk4E2aXI/Td7CZdhaLNWymne96d6SN7fke3VHLx0wrahEIpK3YPbqdr1TyeLaWkJm4so1bbx3byapFf/iel8NnVcXfT+XxrCvtJ598kkceeYQPPviAiy++OP643++nvb3dUZDFRKVkX1eCz6w2BrYVcCY7kbKCFrgQ3lgRiuwrXN3nA3+UIxSpnBU7hSevzIV3OPg1gkKLr3pv7xKMi66OJfakq6FIXLqGJSV/CRvMSIohU/b4puCZaf+7ag0OFM/g1XalrWJju5B1n4/Zsssmn5/usS9nNweasWoiHc+69MfoEBZeoEVodPIxx2ltvCpH8JewzsUDG2yFOzYHmqNbtPbE30Fs/JPreh9MZCWdvKKO2Z3u8fBYOMwFHp2NgZm2Rh75ssdTi47EkK2DV8wu1vUN0ru7JY6LRJeyJWFJs8dt4+3N70lyxn1f/56Xw2c1xa+FTLQMF/Y1O/34h9fk5HJiUy6ubhdXOeecczjuuOP41re+xdVXXx1/XNd1Jk2alDdAhd5H7a8h8DMQOfIEY/Wmc7XmzCdRr7ncXsgkeV+3S4s0DHko7OUSb6S5x3tyGF7e4sxosxGf1k5dNClrPxouIIiGR5rx4i+FYnOwmV3805aVvtsaRUj443uPU+Xz9f5TkAy2vedYKZHzXQN42txHSMJNNVCn76JDaPiDOidyHttDFn5/9DaAEbkgiTVTSS3gESsC4mIv95nDmO3exT1+wUFuu1S/OTCDc4zXEewDtEhZ0WhEZnRcYq0+k5E8oZ7uq2Nr4OSME/GjYZPZ0YptprTbxcYwGbHiJMldymIFZMbXvICh77Ptp83W5jPXrQMFhe5i4jUPZXy8mrfJ6TW1cO6vctpoMtYw2yHC4TDXXXcdd955ZyEv6xaCwSArV65EXPg5aG0F6eAulqbnt3NiU2y7CuFKNLZI+th1HUTyYRD7W0tMQprORn9zWlOMtJ7Drv0ErcG0yMfYST1eDI6QU1jOavYDX/W087Lcz7keWBiGYZrErWmYUvIfC76ozYxPJIZrPyFrIPkQszOF4E3Pomh1Mh0hNOb6rPhYzA+Y0fvUkUl9QRi+6I1MJpti46JH2mk2eZ/jX1Y7bRIuMhITzt9CggsNHTSdTf7TGGm8xtB7Oljzo5kENw60N6WIjn+8MUl0LN7mPVYS4keenUw0XAm7HE1H0KNTobB/XU1h8lbShHq09VncGaqYrRDvM9RYyZ7Q4ZGysdH3mRNRm6X8k0u8iYuhB4OjOIPpQKSdpuHqAmmyKaoOJK/WW8ICC9DROMVTj8Hu3OUjfDqOUsNjdpEifXbEKgM65aqQ72ZF+Kz2+Mvhs8hcR+zsYOXKlRx++OF4ven7PvMmoj3xxBP89Kc/Ze/eSM1gXdf51Kc+lT/AIqMS5JhK8dkTeTyGRu/ziZW2b7hNhm70Ph9fOUNCQseffrod433BLqn6hrO1/SgkIxivdVEbbcbRIcazQXuH9dr+aO9ogVsK9msaczyRle8YTdqKfcSuTN8MwzG5Mr6TrmC3hAWLw9AuLPYBLWGN5qhs7Avut8nnhqbzof/zNq5kSb7Zo3OL36BDBNL2YacWm5ny0BJWf7EZtiXFFR1/zZrJRP1N/NYolrMRGMDFHMYCcxUBM8RldZ00WoF4Mh8Q/yyljCoAPg+G1hEt/JLAC/pLzE2qLveQfJlmcXL8+dWijYMYivSsYpZH42G5Cis8iYEDJP5O+4yXWsbUV2MR6HQxzLUjpRjODqb86TlqJnSwam4ztNUS6IqUwU2+fWEKkx1JFxQb5Rkcev+z1EzIXkpU031Ikf974sRO06PHf/QtdV2VWYWq1O95OXxWe/zl8FlsrnzIO2nPnz+fRYsW8c1vfpN7772XRYsWOe6BrdC7qL0bAjeD2Jj+XEutlw/GDKN+/U6O3jfYJoWmrstSZdLNgRlYWgOWTK9OllFSlSFOEyfyhutxttDOVtGBicV1vr38nwlbAjPAs4O18k2uS0ocuy1DQylTCH4bGsa9rt24c2R9xyTYZo/OX4MWncBRLo23LMl0l8BHeiEUJ0VdvuMN5M3q7roqMvZNRgsiQ4hN3hbmCMFdgVEIaXEUo6MNR8Zj6u8y1tARfntBmNoHIp/lhrWRvt+GFqTJ22Ir/ALwZii1zWcr/xBvMUOfiikEC3mPE/UdXBAvtWqyQC7kS96BbPCfEO8pDullTGOFZl4OCjpEQqEISTDMDmQg8p6J2m0MzCQsB8br1qeWq30o9E8OCbmQOfKO5A6gIen/qOSe0W50ZPGS9lwQkBGbrpty3y5SUKg25J206+rqaGhowLIsamtrufDCC7n88sv59Kc/3RvxxVER2YoV4rNQrtuPm8TUy05k+vgGtq7fwWN/WMn5L06I2/W8fV5idRarI+zW3Wy1GmnTtlFPgKDmY4Wl8Rm35C/WG2jmCCa5NNuEc7ArIR1tNAXzd9fglYOZzRR+FVhFgBBfNHYw1m0/Uy/Z12mrMOYX0OjSmOXRaZeCB4OSQVZn2raqmfJIpJa4FZDpfWbaapQ8tjGk1n1PtVlhabSzjRu9u/hdcACtYh9Cs/iasRcRyP41TK7bLTJ87KkXIhssSZO+hvvlbuo1LxfII1guVvHrQGLsfJqIt7bMheQCMqkXLrb3m9QurNHbwvbQpwjJQWnlaodobay5/DyavEuyN+7QArY7NxsDM2wJecl2tfeDPja91WfXVdEL1xSufO+zGHb97dyifPY+V97sEJfLxbJlyzjggAP4zW9+w+OPP87WrVsdBVlMVMRm/grxWQjX0lovUy87kdHjI8uX0eMb+MSXDuf1uoSO66SISS6bJu8SDqp5jINqHmPykGcxfB1Ir8Z5ruOYLEcywRPix7XtTPNEJul92i7GulfzsaXZtj+Fk9Irxrp1U16dhwAAIABJREFUDjYEkxjPRL2eiYznYD2UNmGHhGAn0lZhrE2zb/1q06AOyYsWtm1Vk2qXclDNY3woNuR8n8lbjWLbnrJ9BsnbopJtpnk0fljbzjtSp0Pbyryat2lnG78MZubqusKumGQrrpJcdOSJkGS8S+PiGhd1hOJjdyTjmaAHGetOSPyFHGe5CshkGouxvsjxEJKm7fNtlyNyT9hZuDLZ6z5f2hjl4+oNu2r3We3xl8Nnb3PlnbRvu+02Ro0axfe+9z3a2tp47rnnuPHGGx0FWSwIw0XnmEEIrzvvjxO7Qrhk/qYrRbmCCro8+N0GqwaOQDjqiuMsrg/HDItP2DGMntDA1rH++P89WWlLQwMt8hnFxix0/4GElzQRnOjlROModorh8ZP3LtNilA6zPBoHaIInzMhE/YQJF3vs7/t8fQ9baGepXM0W2jnfSO/F/EgYPhPV92N7s5t0+wp+jK7FJ/XpLugATo/uqw4LwaOsx4zGZwXC/EEsSfMz26Pbtotl+gxSq7FlsolN3oauc4JnN4e7I0pBPmTbp508obaSuFi52tjLRhkZu21aOxqRsYutlAs9ZlMru2Wzg8Se7wuTLigWmR5OFSfYns/nM3UPefJPbD99NjixyRZ/T+zUqrH/+extrrzyeH19Pbqus2XLFm6++WYsy8Llyt3Tt9j48P7/Rmhhh51UPA46qeS3idmN+/J9+DbuymlXjGSFL513Ex8NG02tx8UDf7meCXu2ZbUtJPHhoC272bp+h23iXr7oHUZvTOwXLLRRfWyiBjDvOwBxew3rvv15Qk31trG9ee4JfLzTQIRPwzf/61xBkPtM+Fq0m95nDY27gpJnw4IDMqzg3tQN2tnG9b7d/CwwjBWWxrSUOSO5wthiK/K/X0p7E49olnRsUr/E6+HVzuN5mo/x4uYCRrOAlQSEiS7amW7s4f6QzteSLnpDQvB2GK6r1fmx3+LUgQbuYOILFnILdobs1dh8A7Jv8bBtPwsLQkLmrNSWa592rCJbY9LFyhqps1Hbxm3RsfNKzbZS7s4xm23bVqrdpqQseCneZ7G2Ej08Be/AGjZ1nRltmbo0Y1/tZK4Yj3nfCOTYyKnKM+9jtI1hfAMsAl0uDhEt1GDn2RRsJuCvwzfAosHK3L87V/w9sVNJVf3PZ8Uloj311FPceeedGIbBU089xS233MKhhx7K7Nmz85IrdBMGEMv0j21fcfKaDAv05q4gt/9pOUQl8o1rW3npf9/gBnGqA50lAk0TGFoH/qgT866RyLFRGdnQWf+/X0B60i/kbjphLZ4vb0PbGOaWo2Yw5v2nGZdyH3uCS7CfzBPCNJ+bT8p2BB5urG1HS3qDsf3LXdEJ+lUL6oC3LMk3vRqPmjDXgAWm5FJDi/vzaYLNgWbq9UE0ik7qGcBEvZ5OEaKNDgZ6PuAsj86DUrDP1BjojnxFHgpavCfrWRzcxXFujV/s8/Ndb+Lr83/jJZ9dk7g4eDisMVfWxfdVp+5ftnX1cvW8q9dsj878oIhfrExxSY4WuzF0nR/WtgPppVZFSgpitkIshSB1j/8n9UP5R8jkdD1R+niMdxkevSvrvu5UjL/6YQxfR4Q2JKEGhDEcXezE0NOT1Bq9y7DiNl1pBYUUFKoZeSftv/71rzzxxBPMmzcPgO9+97tccsklvTtpS4kMBsBBgQYZyG/nxCZuV6RElnw2EglSIgIBBtwNddHtup2Xp9+3y8RVeze4xma2u+7VD/nbGxt5NljPgJCPi8SR8ZXlmRzEyMCgNL5kNHlbQOps1CL7tD3ztsefC987igm3P8zWb59FsKkeY0sb/gnD0cIWE772IL623VADf1it85glCackTvklXOrREVJHQ8QzjzWsiCQsdTYFmxllvGYrcbop2ExYDuI4YbJQPo6hW8wxdHYLnaCo441wF/VakG0WBN2Ra5oOIVgTHswxeuT9nsIEFrOW7aIDE8EeVjI3+o34nBt+FXRzerCZ5/gQSRcXMIXl5ioMLcQQ2ljTeU60HanE/d4C6oyILF6n63g1nQ17T0IKLTqGS3jSao9Pmk7bhcbwt32dzDZyK1z56pfbJuxAgC2B0wjKoQDR1a89e7w7st/m4IzoX4kvzun6VCB2i0WyOTgjnhGe36dkk2wmfOcBMNaD+7KP0TeEIRjZQz5FPEcN9nvem4IzCPgHR20S45rtfnqlSqXl8Fnt8ZfDZ8XJ44ZhUFOTkFJ9Ph8eT+92M5h82QPoe/dWZAUbKI6E8tdHb4z79H2qC7LU2HDqL9XuQjMM4U48YlJ8ZbmLLkbqdY7k8eQypsnwfGU7mjccr06k19Syfs9JjDL+jUfvjK9yNgebeU8+x/e8gr+bbi4yBE+bcJI1k6B8g9bQNEYar8V/G/o+rGgZTQ34sV9wU82g+N7ycHQPuVt3s41avuqOnPjP9pj8MriHmQYsCkl+XaPFJ7JFIckGDEwhcOs6K2nlbT7mG5zEI7xNnWbZJtKJrjCNmqTRGsQwRtm2aZ1laDwYXM4ZnEKTdwktwcF0iF1J+7ktJg95Nj7+qT20c/XhTkX8tVIjeYNd6srZ0HWGG84ao6TuM89mU8hxNtaXngsAkQusoBiCy2cw2lqUNxEt5nOsbwmbgs2M1F7Fe2VHnCtEXXwPefLFQWyrlyYFGia+GosGU8nj5eLqLz4rTh4fMmQICxcuJBgM8t577/HMM88wbNiwvMQKlYfZxl7u8u/l4+jKchaTHb1O4IqW0cwuLtrLbUZKcCbXtV4oXuBThuC+kIuRYgKLtQ8YTA0e3RXf6536O1ZGc6F4genGHu70j+Rc/bw03+N0f8pkKzjLo7NDChYHJRL4blc9PgwuYAr/x9vsEJ0MxMcFHMGTRLaThVLuha+3JCdpWnxF/rHYh4xu0/qPpTPUtROsiCQshLDVFN+RNFSZuo/ZVsVW9q5e9nvfYUKuyGQcm8gf8AuuqElMzjNrvPwtHK6osqFjvMsiRXwoTP8XuBjjXWbbpz3GuyzyXAZ5vOsqMDe6OJBlSRK6kscV+hbyfrN//OMf8+6779LZ2ckPfvADgsEgt9xyS2/EZkOlyhnl8NldrhWWRht7OZ0JtLGfVbQBubPHJS42BZpZv/cUW53qWB5vpIypZEvgVNb5z2XD3pMIyTo2B2dE64hLnhNvcoCnlbM8OoN1iynyMDaak5lknR23Se81FblVEBCh+GtHeVoJiFCKHey2htu2FgWjW8fOdcPrwFHifAxZyxFyIhP1eg5nFMOo4dhokZNDaGCI1sFNXng8mu280ITPic8RknWsoo029rOPD9jFNv4dltwVGsKq8MDIew+eSr2nw7YtaozXwy+OOBDI3EP7ieTtZ2hZV8W210bvfccm8mYXvCSG0WUm1f8OBBxN2L15zG4JnEpY1uIOtpHvflMy1x+6RrPOf2680xwkOtGt33uKrQtdsq91/nPjNh/5z4n/JBeSKST+Quz667mlP/usGHl89erVHHLIIQwaNIgf/vCH7N69u6wr7EqVMxzZGeCe4MNcn2STkmAWdHmQmkbriEYO0T5KPOklssBNLhWey1+SfardJz1uRlpTCEk3l/HJ+OO55PH4qrfGk1bqNNYwQoN4+dFHhYvPJ80Zz4fDTASspIn0TmsBNw6rQ/g/SMjn0S5ZsfKpjd7ncdca/GzPTr4ePUrPdcMd1gK+V2PYVvHNvtNYFH6MiwyLhSZc4kkknh3iEryiP8mNdcO4p30P74gt1FPHFziSpXzIdtFBCJNrjD0MdLvYE7B4NizYJ1wcNmARmwIzmVWzkqND0+hkO3dbOi9ZY7iAKSxhDX+Vy7jU2MEGWcdn3B0sNmGWG/58RCNTLzuRlnc34wvZlYA2aTE1uubrAC4cNIAV+7oylmrNdO/7noBkDw380vQyhyncGlyFNxQpnjK+rrBbOrlWocU6/pt8z0dK4fqG4wo4k6pbwoIxng28FTZoxIUw3KCBDGlgZTlmvTCm5gU2+yPHhsvn4UBrqa3MbqzrW3ISXnI3s1yr8Yo8t1QwV3/xWTHy+K233sr8+fPj/1977bW2/xWco/ZucE+w14pPTTBL3vL11yHXMylaxHrA3ZmT0bIhZh9YL3grZCLMhNO20NGYcj+HUhtNoOoeNMNiS+hUkPZEoohkK3gscBDHaEcSFpJdnr/bZOE6XWdcUuWzzYEZ8dKXySVRNwebcbkMJrgetE1a412Cdf5zSZbq3bobLXwIi7WVrAxrBN0ynni2wZJMcAlauiayTX7MFvYRRPIQbwEaczmKe7VlrJE604BrfC6u7rT4un4uIbEUiHTpkuj8UeynARfj5RQm6vWcIMbzqtzAn0MjMScMZtGuEBdpYR42PJx887m4DTcvjh7KgD3+uOy+y7QYGd03/khIcJ47Vqp1SMZSrZnufY9ya4wUYTziECbq9ewX4xH6u2mFZ5wg1vWtyfscePx4hIleWA8hR9gSPA1dr6VB5L/HnHxL4GG5no+sz8KdjchxHtyXboskomXAgLvh/bkzCK3P3rksubtd7KLPpRm817mFQ/QR8eeT280qWV2hkpD1zJ3a/KvAZmBFR6XKGU7tZKYalMnPR38HTCtvwroTf28IuLb5qzDYXlhFX/MG33p5O0dwYPyxQourTP7dMuRte5BJNZ1TT7Qj9J08HNa5OEUWPs8TmUhjmeESjTHeZWwPTeM5az2n60eQXFL0Q+GhQ4ST7jNrnKh1xBPRYnaxrUWXcAh3Bxby3dqI1P3fLrg/bLKDj/DhYy5H8zwfshs/MzkIt+5mMgZTXJE1WIcQHKqPiu8jju0pvsOvcaRH4yL3Pu7wt7NddCCQHMcYhP4e7Gpkx6zDWfz4m4iLjsdtuHnq58/wia17ONkTkdvnGHC/CV+N7lM/AskN/gZGBryRUq3B1QS0IF/07GCsKzIBZ8oIfyQMn3W38+dQJI4gFl839gJ6Qces8LiQUkdKDeF185Xzf8hN/7if8e2RC8b/z96bx1dVnfv/77X2OfuckxCmJAxCEkIQEqaqIKKoTBFnrbUoolav9trBfvtr+7uDHa612vb2etvab9Xa9qq9dapTxWpVhjA44IAUlUECIhASIANkzskZ9l7r+8c+Z58xA4gILc/rlRec5Dlrr7322mv4rOf5fELD8jDrew9QBAgPy8Hbh99o3xoiI/Lx1nej8DhayFk6ugqFeMIWXOlx/nipJ8ofy99l7pixKX6H2mdXqY3Mk1MzJnGAcDDMErbwr6rA/btDxzqDqB7oKt0dq2PLsVrWp31NZRqZHLZA9+iB+Pb03h/74/NZldWX9Thpi7TGSP98tO1YhTP669eXKlG8df0eo89VfX/rxaBCxJCR7kelLErXvY6iLMXtUMhVBDYSC0Xq6WRy3vGlHotnou0MMXQGtLvEgv/PG49GDyKFjcDiXf0RJeYO3rcs/OokKmQh/oBNUUcZz1vVXG/Gz5kvw4qlWcVbLV63eXJqTL87n7+GD9CpYbX08m1fgF9FbCp0cUxxLMxumtnGAT5Q9cznc7xoHWSxafOi5WWumoVmTezk3KDDAsto4XKPcDjExV4G6JHU0EojHXzfI2nqKOSJ+gN8cN5kLlk0gzX3r2Tqii00hSdDoJYC0crSqKIkiQBlomkwxIowjopYZPoYLLHJnbAhjfvc9GJis8ir+FVIEGIfY42DfKzyXeKZQ+mzNS1nE9V5CDQ3feF2ducNZE/HfFRrp9OuEbPHfjHhoSpyxrcQ/GfwNAZRYat3adFYef2JHs9JU2PL/yiTNvlQ+ux69SElZjXrIx5HljRmDaqDP7ORApHHVUxNSYMky+R+pMaWuGresQjJH09Q9c57rydcUpDhd6QJto52WWf0Uc7hY6Qn7Lgx1byfiX99mhwlucyezJvsZqNqdHK05aEpthX5qrC+kQlvpp+95gqbsMZVh3osbLNfQ5sC058Yoop9VUSUwjbauMArecL+iKU0M0I2c6o3h4A3SLPSsXNmzeTcF4FY6k8ssMgUYXarbpbxMT4MFnMqVdZWpAgzXTexVFiMku3U2iPZp9pQaC5jIptp4CBBRsnB7I9OYKnYginHs8HzIoGII1QB8GvVyaTYZOswsrXwRBRuZS6P6fdZbk9mEnl88bWB7ByyglW3PsKQ6nou9EqeUFuJqIDLWpaepz5KtLFXt1Kv27FwItPT40MrvZJnlMHVAV/s7Ftymldh0YwXwXX+VnqL7O+P3fmntdx2/Tl9O8Zs282VVDy6DE0XUZdE5sgs7NOPBJonFPXoqyIGdigpfz2Nd9hSFtpbHZMlrcaKjnePhmqpZaToYKwem5EGmWwaw82gkIQ/MVzuquZ1O4sOV7P+hJ2wfliPk/Z7773HnDlz3M8HDx5kzpw5aK0RQrBmzZqjUL2EHQtwzCfxO9rweLLJoSPpGF3KRZsOUCby6dQRmpMGp76gxlVqI/NCn0v8Ik23G7KfvV4Tg3YLhCJfCj6IaG4PCH4T0Zyhg+4h/zpLc56Eu4L5eDG5ggnca33A0GbNLd4uJvoNfthtM1amTvauacnoXMXeUB5eNYUy4eRTb2UjQz1OfPs7tqCL/XQQZhB5NPE3hpEXS3vTfCFQxwu2Zoj+EEtq3ol+zOXAn85ppHxtfAGSYBubNrGZvLZ2/qnmFMr/p4rdd/oJ1QxkTtCm4cN6Lk9CHZ6LdnCDR7LQK4kolQJ3T5CCKrWX23w9U7UCLDQ0kWDQPfuOLwLSI8UPt89GDIeLPWJIwrGz8eYcD0MjVtbv+4woSE1teA6qXRKxB6AxnHLSZjSvpZDE+lkfFA8qFEo5EnjR8nL2Ny/N8Iv32W03Z+6Ik33S5UEftZ3c+vhk/i+eKL/ubqGhlzRIF1KPEbr0Nsn2t/37A+/3t7zjfWw87LJ6GChtlb3PHqrPsVpWj5P20qVL+1WRo2XHAhzzSfw+E3g8yWrnXMKezfeyj04gyoVMcP/WG9QYhxb/hp9pyhnQsul2p5+9LvKCR3oZpCPUI7jOlLRphQ8YbJp8a9FdyL0fo0aV8fUnb2eitHgt2s3H5PA++1nMqaxmG3+2DHJlEz8KGDwVSWUNi0cAx6HGK81OfhNqpV7H9LvNNp5XgjMlvEwBxcJkkB7NO9TgpZu9WGylkQt8mzFlO5di8LylWGRKfuXfwQPlkpwxDezoFhRbit8B83YrNrZrrtuTiye8kj2ykq6vgx0xGO1bgyk7emU7S5f6PMuUnB2IoLrjdKOZT7/GUjxqFWJispAJKTKl6XYofTaZLOf2xbPYl5/HT6+bwf8+dQelzfuRKocvXf+v7B6aOGJ5uvJHlA3c734u9q2EQU7Eek1oAcWeJBnN2OKuxnZgc8PvJYs0dka9zO5grI00MlqB1+NBA9vX72FibMjqLzw+NJwqDxrPrY9P5uttQYvYS7720IiT3jeJET2W1x8Sov60f3/K6m95x/vYeNhl9TBQGtLTDxi6b5/Pqqy+rEePUaNG9fnlE3aMW1uTuxgVdR+xYVCUHefM4+znl/Q6OMUtBVqMbMZSY3v0TZ6MDGs8eBqpDc2kXqzgix5npL7YA49GNe+cVIoeVEjpo/+XHd/4MW+NnMAX9m/mlkAnP+gupJyCWFR0CWG5MUVSMtnikc9xEpYtqp4W8SHf9Tfxs9BQfhkR/B+/M1hPi0bIUeVMZiTrqGOa6KZDRJjECGrDIyj2LeOPYYPFvoOAoNJWRK7SzJ61H2d0MFjzhuLD/9DsLBiAGRUoSCH/qA1XUuSrIqib06haRUqK0TyvwTNRi4VeDwpc2LUnK/IYlCHxRcYksbJtpsjjRceg2jiPd9wOlVDEtBRm1Oapyh8z4qVGVLMDBz95zo+RafS4dshAmjZCOtBxMjweh5IBcu6B0H8B2w8dTK70Sv4nWMIcWUEUsCzFC99dzfgR8zEPoRwnh7/efRYt9jAAV+t7hoQZ3lb+FJFcaM/tV5kaIymiov+W6AOp30xuM1yPw4fg08uKW1/9rL8+R9ovm8+JiP2e7bg50z4m4JhP4He04fFpEn718j2gFVpLGqOnYuvB8PwGJnJ6SspXT1BdNmixrAdhEoirTWlmyLEQI27JSaMGrbFswu0m0x95gMvsSbz4yAN0Cg+/V17O0VE6aWEfuexT7WhsCmkDjKxc2un1nyRHcKHvA/5iw+05rTwdSex4Zxtt/ErVsIF9LOJzbGIr9TrCVN3KCOmQpAw2Wlz/yRjct9zm3LOc4yCtNe8s12wdPIDLLYWKXbMuNIc3xBpmxepSG67kDGXxonjBDWw7w7qMnbHNdjyNaJppsyv2O//wToLbBrnnscK0QeiUXP4zRTsvUO+efV+mprGze7CbclcXmsNwcx2+UJdbLyffPSklL8fHR6OHcnJdM5XdIQQ21aqRcjmMu/78KmHtpePB0+mKXdQ/vJOarw3I2uYTHq4iMKaDOj0HhktCuwaACXuZgwoZoAXiqxY6arj31V94PG4L5ARq7Q6Wfn8jPuHh6vAUlux9j7CyOL/rZLboeLZBz/1irprFi9YLKUGGyJ4n894s3s9qw5U9QuRZ380Y4lDbPT8RqJf0zmWLaP8kEevxxWyGxeD9Xq0/PkfaL4tPtvY9AY87dnxM2iZ4JqSRk/RgntK+/frj4/ptC/YpGtIrvBOb5DLgcR+uklfYdohV4DDh8SwTqSklswIJ2LJQDOoZTkqC6uKpMZDYjUACWsz5zYAMYZJku3pgLrtaEmpPQZ1I2WqxbHaRT3ign4v35lIm8pndFuWpqcN41RjOxI1LmSxbqdfSkeOMFuBXjqRkQRqXtkpSkzL8XlZ0rmeenMpKK0yegOVRTVALd8dbowVhQpxLSSzoqJRGNjIrd4XbLGGt3MC5DqWw18Brb8LsWfDqW7Bp+0DGTRxJ5Ts7XF76aqOKoWjeie7kVHEqkJo3LqMVeKSHovggHJu0BzxoY4xxritkDlsWn01oV0zOMuL4FPuW4ZXOJPy2GEBryOA27wF+FhpKvXcrM7ySZ6NRrpKS0f41TmS/36lXnOwmbr84YxxTbpzFuaWF7N3VxC//+BbffHMFd3QX8q9qDlMeWsmij/6NX8z8DWP9DWgNVmMBnmEH3F11Nit/eCVC5qBVEBU2EF6brV9aQGjXIMofWsmu22e699VfeDy5bw+XeYwqL2TYaigT+XRZTrBYnXc/JWRGhCeb4fdCUGc8C6DHybw3O1x4PH6cxLb+lxXffSdHmfdkcZ+7QhH+w9/zqvpQJXiPll82n2zoQ0Zb9JDR9A8Ljx9LlvswGDKVnKQnE/3w649P3K/zq30Tm8gSULuy/y2b+hY4RBBxu27ZD9ndflKmU9ySJniy9P+ernGolp4ak203oiJRtIq/VKkwVjJHeXz3MNO+jMfsZzlAPiFMrhUVrA3XUaci7JOdWEJTO/tGRFsD1e+9wrcDBuBISd4xOITqljzYXcz1vhZI0k2uC8+NUaDCushmSsxq1kUMhBFlsVfyREQy3bqYF8VLLDYVe4WHrzGTVeymXju5zefINpZG/FxoOi/SIi88Z8Mi6ZzLf80jeHqF5pwz4fXVBlcGLSrf2eHWwclNd8RPntC7sKJT3ElhupzIamzmyooYbK0T9VZ5WXWgs1l81zQix+SOwUvcs++lciq/GPcRPhnh19jkMhivaGPK3ginpgm7rMjxMSUmzQrg8Ugatit+HBnFVVTwHJv587/7iFzunJFX3zyf0K5BGDlOylfFo8sIjO07urn65vmU3vm2+1lFErvswzEhFGjNOdeewspXX6NedmJFbSoZywf6r1xgZkaEZ7Ns8qDJCyuPmPKJyIY+DUvn3+/NDGHybNdyZpgN/LxrKFfIvnN9j3XLhj6kt0W0B1rav3c7tnpqL9YXvHwofodSVvLk2rN9smsmb+SzwePJdei6GdSeQyDQiBGY9GZ2KJo1NWYumbuRbTd7qHh0GbXh0wl1p8KvdaE5EJHuZAqOAmqHWYIv2kYFFZTpfD5sbGDHgBZqC3LJa/citrwBeYOZ6RFObrR25DnD3X68OsxNfidPVycdJI42V7EnfB7ddg5Kb+YCU/CI3sLFUgEGl3os/qxf4CQBS6OafOEl6H2ZOmsQc4yDvGzlM8sj2anDPBHWLPYZbLYlBWiWRhU1SuMVBoNfVfzkbsXlqzWlKPd52aFIjCzGIj0yOW5z1VRAO/rRIojWTr1BYAobrUFHJKEavyvhmWzO2WkCWu7WTnsA1HdFmH9tF7NnxXcjrbz6hmLQj3RG//lo9FBmlyZIdoYX5TNmxigKn7PcVKfI/oNsb8tHhw23LnE4WEUM7O7UXY/02TFaUaf+vqIwWglUxGBLRzNlDMqI7LZDUbTXQOvsm6QNfsXW0s6k3rqcoJ1Pd9VY6kvDLPrNhTx14Qv8KbKGf88SEZ5s6RkP2WB0dzL3OBkEfVl/Ir6PVPS4k/MAnnAriuxHFHGLdh1w+fmbdAOhaAS/zDz5P1RCmqPll80nfv/J1p+2gGMT0j6SZR0Xk7YOg270Q2E/Iqab+uHXH59P4BcPVAGQcTww5hPnGI+bz46mMEOlw+NxucGkwjMhuAjoEGCSAmNKv589rWcR1b2vSA2/lxXBNVlTY3rajTj36CEZiiv2r3SlOeNnakW+leSV52JXjGfvs+000ImBwRnXlnDJw2upjhTz1TV/wiuDTJOwJ4mgw8hJrKzjsH2xbxn1kZmuz2r5qlvvKzya56KCGzwJTetS60relUu4brCX3a2z+Yn/He7oDvBfgWaHBzyiMKRgadjmGSuf/xka4p62Lj5nSF4KGzxn5/NPKzsowUZj83RUM9O+ADtQgFc8Tl6svZMjk5Pb1Q5Gsu4auC7JLyc7iUny9wy/l71ciN0dwVKKVaxCLNcpZ+4blg1kHpezI21nNnZPFXt3Nbk7bYDSS4upfu49GlSnk+pkz2b6E5voeGJmRv17Squa8FAVNXfNINr2pLCuAAAgAElEQVRY4NZ/yz/N42le5V8pyaBkNfxeaoNOsF6yNnrcBocUE6+Gc2clvrfmjWaarQXM+4qTq33D6Jm8V/tk1ojwuGXLeOjJ5smphwX19hSMlv5uOhBv5plAX9d0MhHaUf6+4fGfhSz+TxI//z32X7mGTDW84wkej99/sil/AVIddBv9Y+N6IuRnlncCHv/sLXgzyDZQWfSc000G+vbrj88n8dsTg0Ahwc0d97nxC99j9+BECs0fnvsR6jwgSYtFxydhHLlBlUQXGr9esgW/7vyb8yDIkaRM8sW+KlfPuLd412zn19iJ3ch5AyZhW4kXS6Bcha9s5nA3O+WdXNfMR5WT2Ftay6LfXMiTX32F4P9u4gavoF3XMNPTu/ZzArY3KE673iCjIaXePpFQ+2qxhyGwudIbAGw3t/tUr3POHVGKWgsOUEhYmyykgp+3VbPbNmlTHpT2cRUVvNW1nee0zTTRSIHX4k27jmlqMDVK06H0IQUzfRKrt9p4RW3Fh4fFnMqbK9/ntQUHnTP3tZpxa2ZCFr2BspZKnn14M9w0hVGlBezd2cTye94moC2u4xQe4/1+ZROkW3wyN3IcdrFlfIQPTwa7WDpZSbZFzCq1kRsD+3mzqo1zkhYi7y3L46wvDU956r0FkWXLePg0oO/egtFS/ELzKVNvA4dGnnIo8PgY46kMHfi+YgeOdesJHg/9aii6JBbNaB478rNH046LSTsOR/bH+uN3JMvK5leUTPwRszhs9ofnfpTxt3R4PPh1aO9K8OoKkcrTnA2CU6aBEoLgt0A1AL4E1+1o35oYg1jSWVdEu2XaoSjNqueBcJ6c6kJYwrRAaop9Vai0xUO8bnG+7obIDEBTGQzzwd92M/f7s/CYHgpy27lF2IB0OclviJ3ZJ85/RQZs/6TejEjyWa+2sl8oOpRIcJPHoN04nF8UcBZNKiTZEIXTvAkimCVRuM4veDkSwasmOMQz9hhGGRvxEBPkEE7qmRYfgCfqsLbprazoruMWU/GSJVhkwhJLMFfNohonGjverslPOCFCIVJ+nx1C1CkpXJ5wK6OBIvLIZ4CT+qXKeWv5m5xzpub1ZQaXqDw84casEOLC14p5971qPigJM7rGx7eCY4hIhxAlWfEt2XqDNoVpIUSckSzKcJlHkRpIPrk9sovZoWjK+X7c3lXbKDGrWWWZzHoDXn9Tc+4swatrYdyaM9BfSr12b0FkPZGp9GZHEuo90uQq/fHbYafy839se5lxmGUdK/B4T37eW+rdz5H/HQmlWY4BjkFI+0iWdVxM2rtDF6EJ9bnihFRI9ZP4HCm/Il8Vfn8LnrF+wrtsrvv87ewa7ASd/cecjzn7+w+lwOV+j0Hug7B061xKp09Ch6HsG4/hqz3o+mSLUN3182uIjMyHexOQeuBAN90Fzsyq0yIxPbfUI2qcl8Xwe5nb2Xs0bRzCGv/AGvzFHXRhuDnCySb9fkbrNQBuRDPAt9/ZxapNtbw2aggnfbiPPG8q+Ug8z7jYv9LlsDb8Xt4IPRPL805M8Nf717AzOA/treabHsFTFlwfY88abY9nafRDZLSC0oADsW2IwikDTO7v9PM7o9klgomToCw027gv1Mpe1YGNzTdNZ1d0X6iVWtWBwma4aONyj3O3l3os7lPN5HsMCqJObnqDEoB0hSc8UrptFpcxBVLUpYp8K2mIzMD2F2TAg0W+lfhki/vclN/hWL4p2MhvQhNpUG1EsLl0rc1dd8PFb2nKAkswAj1Lc46zgI9jz2lQDlZ3OKU+6dYbtDn+gTXkjG9h65cWEG0oxA5GmM1YlrGd+h7YxZzyUhnFIkqx3iKmehamyMxh7YogZ5+p+XCF4lxt0EXqNO+RHqSYzNLo+ykR4dAzYtSbHQ7Uu0pt5MYsPkeaXKU/fl80P8/z1jMuP/8V6pKskfDHEzzeH780xeKE3wl4/IR9EqsNVzL296s4MGIw23J+SeeKbmh3sPS71pTBeT/N+I5lKZ777noeX7Gc8Dclqrbv65R98zFyHgRjDHR9xYl4l0kDeF9iDtnSlLLZtpsrmfBQFXtCMyhU6/DJFnfi3hCF6YHUPNFkKcSz1TrmfdTEI0qkkI90aS+1oUpGmG9lwI3ped5+oagNzedB/Rrf90QxpWQINq/E2LNOlxWsiijmyQpqwxVsVn9lKXmUtXlYSLnLJjZM59Bh7KZDKbbagoPso1geZKPOZ0lI87oeRIQmLmISL7OFqBrEXNVOnnTqUSQVHUpR6ZXcF7TZp0fwZzZzFVN5lPUYysOFVgWFBLKfaZMEgfbwt2LfMhqiM4ioPPzSmXnWdx+kgX2OpChvs6xbopcWYURPJ+KrInAIuGhdeC5RneMG/aSiAL3b9q/NpfwPK1J+t5VGGujkeqbyKBvZSj2TGZZUNhk77WShmYs98HhXiHPfgJ/crbh0rROQSERDyE10B2CGOZkVnaGUiHA4vPzrQ7X4cc0qy+TCfjK9HErbHqr5PX72h4bzimigMToiaxDaCfv7seNm0v6s4Jgj4XfVih+yvzAPpZt79VPN+yn+69P88XEvXwxP5MfXbaW7McL1uol1CpdnukcCh7Qx4VChumypMXHb0lVHuRiGMG22f30OOmJQp+e4Z/aOJvRQfhdsTfleXXiOO2DFJ6lpKsLzYom7MzjduoRI2kCzSn3A/NAUDqoRKYNwt4a31U5mm0HesaFSwiWmwR3dmmtj9Z4np9KgOljKdrrIp4w8Su2hMUi5FMvYxAym85Lt5yVrG4tMwU7dzBc8AkQrz0UFZyqBYZ/MBFlIRJ/MZjYyNLZ76VCKNnsYL9LCYtNmqMfEiJ7EsBhs3alCVLOXQisH0Em57+n7gtQo7Wzmcqxr5+KjcxWnheYT1ga3cjar1Ht8QzbgCywBQIX6d873VHsXC9OOcdIXdu6RSFIkb/xZlj/kkKsIbBeSnywLuND3Pj75F34CQCIPck9oPoQlw31vp+hpZ1C+WopSJLPWKDyh84nogSmQaHLdskWEH07+9aG85ynHNZEwEZXGH9DDO7cnPD8F0TjS49kVcg4PR5Zzk+z5KOBYHBs/SVk9xfsfi5D2kSzruDnJN/x9UCkdgt+RLKtffsKBvfsyOXQk3SVjKa8vpkzkU7q3lMmXRvhoEOQBVVFntyH9mdFG2XK1k/2ETyH9FtlEjJPrHx8Iq1Wj+ztLKZboLVjKuX75w1UExrQ6msOqjbuC+fwyNIqFnMY94VE8ZG+nQTkDswPzthI/oxVYvCHfpCWm3NWqNK/Lt1Lqs07voMSsZrfveb7sq+cly9nFv2TBTKsS27OLC72SA9qBVzuUYhjD3e/Hg6K6iTKLMVzORPbSzlJVTZ1o5XR1BlE9kAXyFAbhc3nATSnx5+RQICBPtLKXNl5R1dTRyr+ZbbwUe59esuArgzvx2iUsjWo+sgcxT4yljjaWqmr2iVbGGDUYvmAiiE5ticHCre6/AguBRSAQIn0IEqaNkM7vFAaWr9B9nqP9azBFRyx4qxGvDKJxUqYen6R4YmLi5/GJig3+VFKCqqgiD+32J+USWaSu+uL9YrRvDWMDLzA28AKmSM0tL/atZMygtYwLLGFcYEnKhJzi53f80v8ejy8A599QbAI83ep9aOrpnXMRo6jud/71obznq+VaLvU4k0f8uCbZsr2bn/Sa/fW5SS44YmUdTb/DLasn3KI/EHN/fI7Vso6bnfbxbKalOKm5kz1+k6hHppxhp1vDvMuo2/RzGmQ7lrD5ztdaefQvgkVeyZMRRUSpbAHCfVQAyh+owiiBD69b4DJU9WSWUixhC19SPlbycUpEsB7WzNeMNicQTUKJlIy3YoFcMp+gGkMLrYyQOcQzhuMR7MO97+CTHawL2Ugp6ASGSUFUNbpzliPTucM544xGwYDBWvPr6GCuNg+yxniPAf4Ij5cLbK35lQaJJE8pqj+qZV9nC/PkVIrUQIYQYB9tvMde2gjxc18dd0fy2ewJsM+qZZ6YyjxPgBfscIpaVqVX8qOuQtrFPs4RB1it89moJbVKpUzwCwM7+XFoEGeYB3jJXMuudsUdvnruj+TzOaF4zforplemBNHFd87JKmXSl8OuYCJNTpg25X9YgbqrA7Uf6iJz8YzMYXS98506PZe3jFpKjGpW2yYTo3MZMeAdhoTbmLhQpaRMvfqGYsgdiWfrEMLAIjPRn/ZHej86qQ1XurC2GxsRz3DoB5Nlb5YuNHNtnh/Ch6Zil249ZTwcCUs/M08Wg8lmQjjK89JUzoL5E5DNnLATBsfRTvtYgGMO1+9Hf1rL9x55jQfvX8ZJBzt79Y3s2ERTcQPfWvEB7WP2ceetgotjTym+sj9UTvSce0D2LEns1r9BdfCI2uCeza6lhk5CjIhFBJdTSPl4Rcmo1G6z0GyjjlZW6GrqaGGeGJmRi1ucRMKyWzv3UhYLLtulEyjEk1HnbwBTtea73QVstEeziNPYMHQS22xY3pXHxKvh1nsN7rrP4Ef3CaYvbqI2WO/uamdTyvvsYzsHyMdPoehmo3bYxLo+b1PidfxAp0zY8Tb7bqCB0z0H+XzAYLQ8SDMwRfrpAOZ7JSoUIqIUJ+e2coEhGWXs58xAA/keg0u8rcz2STxKcanHSnl2vT2nuJU/VIW/xGkr/z2S8hdXU/Svb7h+Y35dhcjZzAVeQasIM8K7nMEPdFBWLNmyArR2ZlKtNZuXS8boxP0lt29vdUruF/FsgHGBJe4z7fo6dF7ipCN+Eo5+R2gGdzHkiSQHGmVGmqfXrSdLznjoyw7FzzkzT0IG0qqXfo/FvipM2cGEB6rwFyfeh2N1PDsBjx/7ZR03k/axAMccrt93rz+Hb3zrIr70rYvYW9A70Yl//Of4xn1eTFPys/9tZVxdusxjJgSnTE9Wiqm4X/DWzFzvbPUfLvMoYiAVFCYmaYYTJMpyvZ062rj49XBGWettQSv7+LL/A1qNejbr5l4Db8oMQQC4PzKYAHCykditJJ9xTjQNhogI4yhlACYt9V14GMBiNZNXl3lSJqf3luUx2NjDBV6B9m5jMw2YooNvywo6RCMX5waZ4RVElILnN3CBVyC8mxG0ZW2z5Mntq6bg1YiPOZ4BfDE2wUu/nyejcFFsHLkoBNvDmhbL5v7IYFosm9pYDjcknl26bYhmPs/qmyt5cvbZBHcPZtvN5/FB5Rf46NYLsXyFKAweuGUIF8VEkS6WzsRbfXMlof15zN7r5/W3nXZ5dS0Ur06NDk8/QzaF0eMuO94v+gqiygYJb8gyDvcEHVd6pbsYSvYp9q/MSsKSXLfe7NN4z+eqWSnHJMkiNs9EVY/3GPw2qLpPp27Halmf9jX/UeHx42bS/ke1yBR6XdkD7Pr5IsKjh2b+Icl02MAO9c0FPZux7KWN5cqZpAsJ0EAn5wXKaaST92SMvjKJ9W2GV3B7TiumdPjCpxoF1IZTJ4tnYuenNZZiXbSAn8fOwH8RGsU70UL3DDyk4bGw7d7vKOHs4t9jL14kZ1BMmcxnwKrJvPZmYnLqeK3d3dVe6onSID/iNn+UssAqfphzkBl+52W4K6z7tdNMn9ymei2XNzybT7OCDlXIz8OjnfsKF9Fgj+TDSOJe0p+dE7w32I0ViNu43y3neWMz9cNPS6GErY+cwc7uyxhktGUsBsofqiL/5Q4mPeRh63ZQSvPB6lxGqSEpZaefIbfZg7M3QJL1tuPNZun3lW0CT7dktONYNo/0oKOTU45JIB4nAMu7s8tQ9oV2nbAT1l87bs60jwU45rD9tEOa0h9L5x6/6afwxwUJEYtrvJkQXNk3H8P3IDAmtaxkv+qbe5DrS6t/PG0nzpRVwmBulNMhorlRTqfiwWUYJd3UhufEUr4SgUVKS95pFwxPy6Csiio+tjVVOClS060IXrs8Fmk9lkF0uSQcw4RGC0FV1Dl7nSAFK+x9lBkHOWgPoZZc6pUjT/n6Ms05Z2o+XKEZpUnLz23CCd9LtEVVVHGWR7hR59nOJONtFp/cklOHknnWVSiU4jNUQp6IMFmXx8hFxhAytvM+XiaiUnZlNZbikUghPhwWtl+0VNOht3MqRWxgH3m3DeaL4fE8s7eadmVyPuUMDw2k0PcGXn8bVaFBdKiDbt1CscwocDjuK2fDT36pOGPbJITPQvi0uzxfpOG5qHOG/LBXkzNRs0asdu9fAyO3lVHeVez2i+K8Kky7I+mRpk7g8TZLv697QlsJ6hA1aH5vNOM5grK5n+V7/oVAHX+x4arYQiM1TiBKJAvDX/DbqWjXsTqenYDHj/2yjo/lLccGHHPYfv2MHodM7nHTlBQMJmVl398I1cOJHp8kR3CjnI5HerhRTmeSHMEqtTHhE3EU0op9KzMigZW2+H3UROmoGyEdUTbv2ZpTDMF7tiaiFFeb7ewVbSxT1dTRxlzKnKKVohXBhV5JvYYhHoOzfJJSo5nLTcFFZhutYh+S99nGPsa8DnfdrThzvZmxg4xoOyXn2zJNDmgyos7Td7/xNpsAKVHr5zMZ0E6E9kTFE5M18hTN76doHp+oeNiruc1sY59ojUWcd3CG7zxEtCJjV1bikYyXDuxfJvMpo5QScpksR1DEQMY1llAm8imLjqWIoQyXeQ73uLiQj0NfYLaaw4uW8zxesuAaiTuCCemnbIykcrZgNEMYzRq80Q42dAJhMEXiDHlYBKZf08x37j3g/ky7uom87ryUfqGTdL0Bin3LU9o23mbJ9zUAk0btIUoOV3Ea94RG8ePufGqs3gO3pN/vojK92Wf5nu8Jn8/lRgKh6E+cQO5vHDXAT6Nux2pZn/Y1T8DjJ+xTMW0KvB7NyLwwpqF6/BE9rBuV9nBevuGe+R2ulT9UxSkrl+Afc2gcyPGUpXWRzYATgJR+pl1jqUTalz6VP+ut3B0y0cZynom2UyQFF3glRVLwaFiz3ha0GfvJ97zPAdp5gncAeNbucge/yz1Qr5w2icPQM7yCH+W00m7A3YFmipTB9NWwtstikZcezxoBnugKZQys2fzAgXd/bw2lJqr5dWQwg7WmNPAqpuxgSAgmXg1fuUfztXsN7vi/BuVXwZAwbNSSg+zjAHtopJPt9i6mywqalZnx7FKD91qZJxw++tmMZY/tLGhqdCuzKc2oX3Ja02B8mH6JjhopcrNnnu5crzZcSdAakAJXV3olHYaXawyD95bnZsQGpEPqrrZz7Gw7/jm9xyoMvhi7r43COc44TZS4C5MJXosST+99eHl32E1vzJaGdjQtOe0x3ZLbxJeeay4SaXTpmtAn7IR9UjsBj3/KftHfj+A/SmvJIN0LK/AKkM6gdOfqsezv8DEsN5QSU7bJvo6T9Iss9CZoTLNyj4clIqScIU5n8Qv3rCGeXv+42Iel7AzxhWxW4klL+9KlWHITJR5Jo2Vza9JkeZ9yzsBniFbQBs/YHvK8H7M+MpAcw84g2gCZAVUbKhHI9jujmf1KsUlLCkQiJWtzDmwdq9whv0lpXpCCip0KOiReoSgQqTBmjaX43cEAuQxiIRWs4iOGIXjTMllmSW71tlNmBnl8hUoRtXjrTU0BghlewXa7lVX2EH4f+BiPUcMeKzcmWJKKSsSD9/7d38zPwvlsUV4miMFspp7doo67/c38W2gom3UeUxmFHYpiinYUATSGm9Z0Y2A/OfdE2f7DOYy5fR1eoxujCDBhX6iLv6od5EYGsZAJLhvcl8wmFnolWsOE1Z/j9QVvce4sYlzfCZWveL9IZ3SLp4AV+VZgyg6Xe782NJ868Tot7OM2fzP/2T2YWp1LPR1Y2Nwq27IqY4HTZSNKccBSbjrazuBctMhOsfppv+fxtMc4JW2yn8CmLjzH9W3mDTpUg9s/m+3h7Ow+2yU8KsfRThemjfA5K0vv8A7Uvizk/WnWH79jtaxP/Zo9rOeORUj7SJZ13EzaxwLX7eH4iYhGhxSeJolVqNCmFxG18PxzPfb3813FmtvO3oUW0BbOZcSAtLLSOmc2fuNtN1cywnw7A7aM+wVvdVTA+lP/eC5uNvGFKTGqVGenkbAvmm3cH2qjXndgafiyR6IwKJbOZPtMVLHQKzFUgiAm1NWJ7YnlZOvNdGudMjnHiTYWeeFZy8NiU/HHbsFGhnJ3t8lCJvGL0Fb2aotlWPw20MoS2yl/TAgmXq0zcpYH3qH5aWQwJXRyZSCHZPWlURKatGB6DLbuVBGaCTKUALvERt6NloI9gaKVLbx+3ip3opvyYiUfWnv490grXp3HVYzlntBWwtKiUgWTaF8SNsMrmOFtZU94ATfn5hDqciQcG+V27vI3YwrJXf5mHgvvQDACfyACmES74oFhMF9OBPZR/eVKIiqP6psr8efasbIgHyiii4JYyl7yYkr6/exuPYtCTwGvL9/C2We2896yPGYn7bL76v/xydyfaxMKGmgMhusLuVZooIoBspU2LblWnMbDahcvWXM431ifVRlrT2gBq8QKvuh17u1iDzxu/435ZKeA/bTe897Uyk7KyccORjJ4/Oeos1NY2Oaos9HSQ8VDy9h1+0yIidjoiIEOO0NutCEfHe67bv3xO1bL+tSv2cOh9gnu8SNsP/3pT/nggw8QQvC9732PqVMzqQj/nixOwWjkmMhghP1PfIOCHzyNrIkik+gZf3zNLHYPG0jA9DBxrsm4WMyYxDpiAKEO9xw9Xq0S6lRxyyq+EFOQqg3PJdSdCPRqkK/QqDu4KXcqD3VtYXl4MpOjwwiJ5/lrxCJPCF4I2WzR+ViqGZNM3umnww5knU60YUpJR3QU/24F8ZLHtYzlTXaznI/Q2mAAPi5iLP/dXUcznZwma1kXmUL38j2cc1aHuyOuWiYhOJKrqGA9dfxXqIUbTGeSfyRSSFRLBuNnN+3sU11EsNnNQQrI4Qf+Np60tjJc7macp4vHqnBFLa73rWa2D27vOolTxCjKhDNB2t6tzDRS2d7SrdhXhfTloJSzuNoQUeSJRJsPNRoYZy5B+nIAXL/0MuKCK4YvB0slIphLVZT7Q5Op107w3jfMNuKnYsW+Ktb99jmKv2/z47uf5tSkXXZfNtq32hVBUWYBUh2gNlTJcHMdpmxnZTTKZA94aKbU+yq3hCqxzYIM8Y4EfCwyeOYHGa1HXWKyP2pl6ZbM299fFrYTdgQsmZM+yURTFAr7IL3ph89nVta03ss5qr1r3bp11NTU8NRTT7Fjxw6++93v8swzz/Tru8crPA5OHnWkuADP7iYnXcr0oEVqTNidf1rLbdedw/7CvJQF5BTPY3RByq42GzyeLS0n3W/b1+cQDmcOPuFgOAMKhJ7EF5wy06U526Pw49w9IOq4xahkuPkupnib4ZbF/0ahlUJC2uSaWFRxKBxhmO4gz+cM2nlSMsBQ5PdAtHGBUcGD9oecwmjKZD4dKsz77EWhmRb7XVCH2Mo+rg0YPBnZzNlrNa+/KTh3luC1tZqu1X6m6FLX15L73TNWB96fwkZdTy2t3MLp/J53gWZs0c16W3Cpx+K5aAc3eCRD1sBPfIrL1yYWQT8M1HF/aHBigpQtKC0RKOe5Z/m/RhLu9uPVYQQ23Ro6tDNxxwPl4tK0ItYLsjGY14bmM8J8GzMUpC40x023a5Cv0BqDq38WGsp6WzBDJvrGsFseZHAkl2DTWRln2b3167rwXLcm3kg3UduB7evCc7GUzUHvEhfm3hU8FyXyqO6qY1RaDGW8rhqDZntEWn/rWd/703zPe1IrS/dbpT5waX+nywpWRaLM95S5TICfRt2Op7I+7Wtm46QHQApM1ccz6I/PZ1QWX+jd5ahO2m+99RaVlQ7cNW7cONrb2+ns7GTAgEz933Q7XuFxgMbf3Ywnx0do+EC06aHxdzcz/Ibf4t3dlOJn2oqx7d19Rgdmg8eL/St79IvvZsb/Zg0f3VlJaHdsQI9BgX6RCQUOl3nZxRciKzPOxuNiIQ8YbcicQuhOiIO8IZ/jRn80RbM6qEuxza2EKwQd1Q4cvta0qZkAtiHYrzQjpeBxqajYoTgtJoLxPV8r/xNpZr9qI4JiovyYj9QQ6sQAGnQbYW1zrmwDDC72wHNhgbHC2RFvqRL80Ozm192tNOrYGWvSrjMuz1lAgEHksIodlIqBFMoarvGHIabk7RcKSymeC+fzz6sPUJr0tF4JTaNBt3Kbr5F7Il42SJPC7jm9UoRCqrTrDGXxcu6fudqCF5WHQdZZ7FAjMXJMin1VGKEG9sSEPYRpUxxY4fCBR5yoZiPHxNaJvnh6rsksoxWQ3B5ohYgA7fSNp9o7OcMTQZDDxPDozHrF+nUKD3ocrTFBSOez7ctHx/q/xmCVfIPrk+IYHrffZ7aaxxK2ME8pfEkd3Mn3d5znJPc3JVigp/ZIK3A477kwbXRUZqBN6X7paY9baWQSI1L84gGaNVRTGQsyPBmQgTr33bS+AaoHAsRjdTw7nqQ5j5VrHumy+rKjOmkfOHCASZMmuZ/z8/Npamrq16R9PNuIf/qdM5gmwePpEzY4u20jx+SkOZ3Q+zh/SOZKZd7kfH43bx97S7oZVROgqK1nKDAb7Nf1dTB/C+jMvNyfd+8hHLYZq5o5SzoLg4DQGZrVFjbfzunGuNXgsVsF10jF+0HJeYtTz6DXpPFmb7BtZ9cYcHaNZ3skJ9PGUuXhNu8BvtU9lHdUHmeqTjcHe0ZM5vGKvwVYZ0dpE/v4rr+ZO7vH8HY0l1k+RyY1HhhWmdvJo12DKKIJi6HstiWXxM7ZP4zYrIsWUmP5WKgreL1jKytigV0lHslFORu5CAf1uN0D0p/Dru5De1Ye6SH//ABLX+hmxD/ZPPa7rUxQwzGAPeFKTlIvEw9yGP/AavxjgoCBvFnA7szy/L8y8I9JnMEGY9H/S4NOFvvHl65g3LsXuAu5bOZcx4HCt93sLPriv9t2cyXRRl+Kf/KxSrOCHVpyIEaNe39kG+GIz22zD+1mxslB7r1LMZmXrfcxAvpOVPEAACAASURBVIPwWgaRT8BtXhX5G3OZknIfNXfN6PVewUl7nISzy7+R6Rl/Tyh9OUhCSAk3oNHSeUic44kBv7GRPzj8+p+wE5bNjuqkHU8tSf4sehHPSLZjAY45XD9hWviKW+nanQ/CWfH3JB6QXpatDXTawd6hcj3HofNq1cTmOZ1Mu2kKnystYO+uA+x68ANCr8UCyJKgwLi5cp2e8cTh0OC3gGhy1Hi5CzlHxSaW0c4MVYxHShdiT9as3qTzWdcZYvhXFoC9l6V6M/mRKWxevjklKvud5RpC8PUYpDrd62WWL7ZrzGkFBM9EFTd4mvmvUAE+AtzIaQ6pB2GG0ESpaTBrjaLEthD2PG7zr8OUkn82yhnhbQWcWTUeGIaQnJV7kKeDJzPQu4MDkUm8aG1jsWmzEcE0I4Lfvd9EYBckFkdx3vVwtx/dj4iE5Ge+Sm1k0tNz+TMbCfzWy1WUOQhIp8X54mRskQjM2nZzZpBWev/J5mMpi+qBz1E4CfbvgI8G/w1xqkRrzcjtZZQHi1LKSpSReH9TypWp10w+Vhkqwa8Nlxo3qMdgyY2UeCSWUjzDLv5FlaC9zpFRQf7p/E9BAV+rH0VEZ57f93Sf6bZefUgxW1mvnEj7ntqiP2Wl+yUHaF7sgYfDhZxHTBIzLCAGgVaoZYdd/0PxO1bL+ke55tEu66jmaQ8fPpwDBw64nxsbGykoKOjXd4+FZP7D8XMUm6qo+MNaOlZfiVVaQMMfvkK0tDCrb255CGRicNxsX083+Sl+h0quUuxfiWE286zYzOe+NIlRpU6bjyotYOiMfHZ6WpjHWBrpZCtObuozgddZfcoa1pz6KnJaC6+e9iqrT1nD+/4wOb8BWexcw8k3bmG5qqZGt7FLDeAqPsdzbOYRtYE5ooMlljMpVnia+bwXTjWamTnQCayaLidSEylnmqxgxlo/r8eoSdeshQVvQp4UtFvZE4WqooqIpfnP0CA6tZdZsajvMXosUR3hqzGy79MtJ1q62J8ghCnyr3QDqdLbbEMUzpBl1ETKOUNOcnOiiU7l8x6DOt3Bcr2dWt3BJbEo+eTlaG24ko9DX2CvuJCo7n1XB4n+E4dcaz17GIqX0xjlcsCXeIYyZoAZ07buefuZSUBhuxKg8Z+3Pc9TaSsmXg0/uk/w/99/gO/c18i0axrJCw1wvxOXDI1/LvYtc7nAk8sNBEIp5c9TZ6bkzP/At9+hxtXbqaOV02Wrm9d/FZ/j9wM/5r8HVvP1qyp44rKT2VO52BHa6IF3PNt9Jluy5rX2VmP1kUZzqO959gDNzLK2Xn++q6in0oJAD+WaveWLH079j1ZZ/yjXPNplHdWd9qxZs7j33ntZtGgRH374IcOGDfu7h8bLH6oiMKYDyGGOWsga+QzT1G3s9ZYS8qcGhU14qIqcsTY6KUL4k0aP11iKR6xCAsO3cs3+z7H+jr/xptdi3l1nMbwon3MvP4Vg1QG8G+FGpgHC0X629zJxsWT2rMTV17yhGXBHaj5lHFa+LdDMv3UXUqyHp0DtZWYTeyxHO7tQwAolXEIT4VMQ1m4wjxGRrF5mcPaZinXLcugKDiZImJ/oFr6cFL17Z8jmNlNwQMPVPsGybsk8SthHG/tjFKezPW2Y0nBTzdKtLjyX4d53eMFuS/l7nDf7e0IlBRk5aMN8OZ7l4UE0sI8bAjP4Y3CdGyVf5KtCCIXQiQnCFGFCOKlQ8aCznpJLbRVFe7dygVfwmNxEachgn5XLftWBAq7wlTjBfypITdKZNlEnUi1Z1CM5KDFOvbohCqfF2n1DRDEZg8fS8s0/WJbDuSqPIt8KfLID6cthd/dZrqQq4N5jka/Kbbvk6He3faOJgMKNWtIqavnekBA/bfHTJBzmtHhe/7kdISy5mYVL7sAI5LDoku9lbaP+WrZUxfOY3eOZ9qFa9gDNnk1FDKpvquwTls9m2fLFT9g/th3VSfu0005j0qRJLFq0CCEEP/zhD/v1PWHaeIYf/OyT+Q/HL7Zr1sqBqueohQCUP/xxVnetUl/MKZ7H6PLFUj2zkaZksxipA8NDlCjJpNMjsNIJAuvaG6HpCoPhRc7ufe+uJk4Nb2Pc4PfZE55P0BqAUJu5zjC4b7ni3LNwB/X3l+dxvVeASFzfhZWR/DLQxH2hEazQ1VjA+YwHdnCBaXBn90BmmK0UDgKzU/JUexc3/LGKbT9I6HsXeTzs2pzPXXc3ctqaWTQTxJKbiEobr+pAY3B/yOZ0Q3Bbt2aQKOSXlo/FVPA8m1FoihjAQVo4UxisiIk4rIgqzhMhp12iTjuONlex0rJc9q2ThZP25Q0GWMh4ntK76da73KC8eXIqo31VjBXtnBKuJBrR3B44iE/ucttitLmK5Ek5qgbh9bexJ1zJCHMd9ZEZRPXAjPQ6OxTlLc9f+KLHBiSRbihDsZN93Oo7yJ3hfPZHt1CcNteMf2A1+u4W1B7c4DQ7FKXYV8Vmu92dpKOxQMHfGs14ZIKsZtYb8Pqb2o2un/NWF6WBJW75KhSiKEn3G3A/xwUyqqKKSpHZHyu9MmXBNMPbChHJ7TkhQDDdcGIc6mNBgZepaUTUenyhLkw7gtC9H2bHYcR+pyrazgJ61+0zM/TkDxXezBqgKXsuqz/HGOnm5osHsweJfpL6f1KfE9f8bMs66ku3f/mXf+HJJ5/kT3/6E+Xl5f36jo4YscR6T58//fE7kmX15RcnVhDSgaptfDHA0Ycd9mCHHPWteER23C/Z0hWC+oTHI0AYaPBDGBYvamOvbKXKU80eWhlziYNt793VxObH11LZJCAMkaBg+ai/uHSfc9ZqXnvT+f9rb8LF13bgG9mBDhkkj6lxeHi9LWg19nOTfzONtLlQO8APAl20KcG8Thkb8DUv3KBQuxPlrM4RXPyfF9K8rIgPrQbqaOV8TyvblEFUDyQowwyUDjf5KV6Rwt89n5OZa4RQooXFZgun5SgOarjAKzmoHe5xgA2x4E1LW+7fD2gYKWEkwxnPGMpkPhMYQRGDUgZIgU1dZC6WznGh42Sri8xjZ+gy96dJns3O0GVYOoe68ByiOs/dOSUrexl+L4EkKswBQjDb55zb53sMZnrbGOW7JOO5b//aXD7afgUfd1/hpngZfi87u8/j/kgBr3adx13BQu7uPpmFnMbd3eXcFSxkltC8ZEMpkleXaZTSbFmh8YQXOGXFlMyk3+8sBlRih7gntIDqritS2i7etumWjnAk1z+O0Nzk30wL+9ik29F4sHyF/OG5Oylt3Z+1zOQ2y9aWAAft/BQe+upo7zvcQ4U3k2lkZbQiJS/7SEGlrkyuSMjkpvfHI3XNZPj9eIeqP4tr/l3D4ycMXpXPMF19h/Xyl+R+eRnenc4LU/HoMgJjs5/hBbPwfR+KvfYVQUt0H3c+0sxtN4/h/a/9jU0n+5m6dyffCbVCwDlf3sJBBu03yIuNtZMxuHe5o6T11jI/C1ZeyhDfcmq+PCMFMo1DzTO8HXhlkMbu+ZwxoIP946t5RnYghaJbDcXWkjd3tnEgEnZzeMco5W5OdxQNZMSBINboXAK73qdW5XN/RBComALV8FtPF/8nNj5f4YEnw2000Uq96iCM4iJ7AVcEVmFKD0+UWly+3ZlUL/bA410hvny/4P5/HsTvjGaeiAqu9Cb+/qco3OTfzP2hKdTrtiSkINXiRCbKLMCIyYnGd/CjfatjZ72OxWFjhcEeS/FwuAQTX8rOaSCKKzmLbi3pUFHypKQzjRkurAUjTIeffYNfsWHCu2jhZcDUJvROGxUUFFSfwoCOkSwLJti83mQXbVowkUGxILAwltxPmWmwC4O/hiOsX5nHT3I6uHytYLTPUfsSfTCaOPAzKW17Qx8jicLA0nkYBBEkEJqa0AIWi0EgoDY8FsMwGaVezMqaFrcG1ZFyn+m7UFtpl6TnxYhmFyJjYu/Lsu3gk80N0JQVh1TuoVhP+eJH0k7A78efHTdP6ViFM/rrF4fHky3ORSx8VgaM3pu58HgcBu/Db0au4PYhrZheyVeKyrkyPInPby5jTlChY37xPeObhaV0xKJfO5Tmb9Vj+dHPBcPf0HiFM0mNNlc5ucE4cpyjzdV4RZCILbivI8AIz0qGhgWnL27ka/dqvvJrybfua2b6NU2sD6YKd6wQf3Pr27mtgYHDBnD9Hy6j8YxSTvc2Ezl1NCV7nd3FmKBOgT0PaGe3NsDYTBNBttJIbXg+H3dfgWeL4TKLNSvYFBnKHV8uY6E+jXtCo9lkF9AcG8fjIg/rbUGL2MuX/R9kIAVum2rJnlAlu9pmE1ZDUNrAf4+BKHKix8NqiItCqFDI9Y9Gr2Q0Q9wo6nIK8WExxdzJO8H3mWld5ip3mQF4OZZF9bIfzh21gN1tZ6NCIQaFBNMWN/Od+xq55RbNV34mqbgK/N0Fzu5MD3SvMYERTJcWXURZrrZTq9u51KOpsRRvdQ/mbXs016mZ1C8bymPBQtZ1zeTj7i+49xXq9maNfk+Hn/39mBBrQ/PZ3XZ2yq49Ydr96U9mxHCZh6lESlsm70KHeZsRtubbXUPZrkazmFN5js3c8V0f+0JdGeWlv7897eDT/eIxD7359GT98dtKIw26MyNI9Ehcs0F18IjawJ9jqXjxwNF9XQd7KeGTXfNolPVZXPPvHh4/XDtW4Yz++mWDveNcxNlg9N7MhRnTJBN788u5B+RwEFq5Ub614flEVB7S76c2XImt/bw3+0s8FavDUzLAh5//Hi9ErsXHKVg6B9BIoVxREykU67pn8MNgCXeHxrGQU/nv0MksjTby7rIBqQpSy/MYoUXKgD/YaAXgXbmVU+wQr935Ant3NXHJf13F8uJ8/AOHMaNjGAKLXXaq/GZQaGZ4mxnll/w0dxefz32dkwPPcnLgWdrsQa7vUAkDRJQKY1hMcWoMuVowNNb748xjM7yCO4ZG3JSwSTKTkUsKR5HN8HupC88lqnMI3Wqj90CJfzl+2ZJoG78fKRRj/Ms4OfAsC+QQJ4pabaeONsYaO7nAKxCeTZQF/swwEWVpVDEyLMgPOoFcBV0w9sAKxg9+Ben3U4Zgywqd0q4frlCUaofG9IKcUewVLazQ1ewVzZTKJhppYz5jaKSTDbajtDXBVJwWO1qYEZ7EBBnhJE/A7RtS2PgDUaRIZdoTQtGSBj+H+rFDK/EvZ/zgVzJ20CX+5ZwceBafbKXYtyyrT7pZSrGLVmppcdsyWQ2t2S5ggRc6EEyNMeCVU0h5heIkf25GefH3t6eJrCGGqBztsWWSHMHNA85Kkck9Utd04fe0hc9Jufm9lPDJrnk0yvosrnkCHv87Nuc8W6Ji//bbfGSIhLm77D4m7rgFv+78exKrIRYzl4Bycyj2VVFnCITnUl6cdiknvfMMf5l5GdLjITxsEsO8zzBOrsta9syct3g3OJCRerILw7boVspWn8nr569whTUq52iefC1VsavNzndScgZUMywkmVxzEPXtJ3itKJ9Lg1HmvLsJApsA+Kaled4SXG/C8xb8q1fyioYr/QWoUCLtRmBzg6+V55N4zL83MMxv21pdxanbfE28kPT3bBKdfVk8Mrsviwdk1XtW/z/23js+jurc/3+f2d3ZIslykbslWbZxt8Hgggs2YGFDuCl0YkwCdm4IhG8u/G4S0i8JcHPT700ChCQmCSUJAQKBhFiy3CjB2DRjG/ciycaS3FS3zM6c8/tjdmZni4odBzD4eb30krT77HPOnDk75zyf8zyfh2PJYu4ItXBHrJizUqv7pT4bnv90MDN4q7PI98wAMpiTolIdFlzN60JyDOHSlgpN4zsFB4AD3EUa+r46EuOniXQg2C16O5q22m3DgbMdyNxJuhsWXM2NUmaMrcMR7/CfC48NrzjEI/l0nHYMVYJfj6bntgepzy7msZJdBPHRgeGyljXKNt6hkB8lhnE5Y9jOYfbLNhRw++IEtXd2fp9OhHf8VJZ3A34/LSdfTplF+/0KZ/RUT8k4a7WnaRcjWet7AoAC5cCCmXrZEvkJRG9On2vLeJzIr+xqWx1LQdbmbzMbanw8KZkh57sQpbPoOHqHjLMAaJx6KffGOzhyziVpW4ZBZ6WBTSnZoDTOodlNUbqYMWhSY121YM5MxcaqAmbWLGQ7q3nWd5hFIfuBX6nOoVp7iU8mEnzR6MdcjtDYkuDmeAMIjdp4pRtkVRpcSUMC/i6O0JgcRKM2l7OB2phCxtMwblmwmkbjXJR1gOViM70J8mbUyODgXmVModi/heXJBP09JTozx6zz3VBPjzG8UdZnWBezSBRTn1DMCvyJeXoacdCE7bl6F2nv395+lSs/L60wmTNTsblasFj5qcOmju2vCRYJhaKGT2vTGeRbT118upsv7hC/vNzu5xjvcEewhbvipfw1NifXk/MQhTifq0tUklS96OV7huXJGP2EwEpE0FTSjZJ38qsd3Ux7krJgtetN24Q0aR1NKcb8agXhEa34l1gYO+yUNoHFIC2cd1G9QLNLxgosBmqFlMli+jIYA4s6mjmDEg6IFtZvMRmsW2jBdFqeNHype2nPn64WshN9tgjdRCUz87TfD8+zvHSt8cEnrV891TsNjx+fjlDZNGXvI0kkEmzevJndH/8lqiXeM37XFF3oP6tzsvTGLKshNLwVs6mElwb9grbgaETSwjn4nGddRSHp9C+zqQR9WCPC42BlL8xaOELoZ1F30TZrfUTuBa08M2hNhkoo/NFhtHJ47jGT+G8VoRsEH7nG3qs5uo7e43dM5u7Z50NxFvFLyyF+tOJBZsn2DC/JoTENoNNLDWAz7xDEpKBccfXnWzh3msbbn0ny1ERF04be9PMXMrF+HOsKt3KwrYP5vY/RNtvP1r/3YYAK0jfSl9rROxBCUi4MwgE/yrI48yLB9IvS+8uv3mrw3Z/raFgofCSbSkje2UjoDh+iHPd1BTz6a5PLXxeIQxGCP0y4769/zcf4ZfCn3Umu9iyOWjji8rUX3mchytLEKVrK7XPa1Ac0dhkkaAZDPNEWdYPuplmVKIoZu6yGB7/QwmUmLuLwC0NRANwSyr8z0lLBgn84GmWmVskeFG9cWsPZf5vPENkXZ9H5Z+fsKvlWOm/eo+PMY4fGdMyyGp6sOcrUly8m2VTS4zZH/ew5IsOPAbDhNSi8bwHl39xAaHgrmm6h+SMZPAXZIqXkfy6YiF/4MLH48t+3IoTGq69B0X1236SUVLEDkcqOv5jRTHh0RaeBnkKz29y2pJJXd8VYb75jL2TqTaYxzN3MHO+zxckLH/dQdU6q2cl8Br1fbX1Y2jzZtj5x+Jds3ryZiRMnEgwGc3ROL9rvkp4vopM0JY2/+xz9vv1nAtsP5s1F9UV0Rj/wbMYDpuOWzEXbXxFB/1IUXzm03exn385KkvEiVEBkBKb5RkSQ2zowLZM3AnZe6e8NH1OSH3PTVJQu8I2MsK5hJweGRmF/kpHHinOczEmRYYi4pCxYlXHm+Fi8CJ81mTO1IWxSB4hpb9EiIlQGzgegXFvOW/5mNrZMog99mKwNZqPczzNs4+eFR7ilvR99gLmMp78/TK//WZFB6LL2RUnsztn0l6VkS5lYQWNiOla4hCHWczQa0zFUL0qDNe7fAGXBKsIFJnuPzSER6M2QYDVfaPHxJc5nRHgFAa3D3Yw4i3ZtfAED9Q05djZbHZRYlW6bQe1Yp7GAD5lwmZY+CngyKfhUUQCSCsOSPG1aXKtrPGRIrvXDYyZcpikK/bkLtxaOEDdNljQX8OvgYRrNS3hTb+NittBgnOsWJfln5uyr8m366Js5ZkxkqjY+ZwESmsph9jqRNkuDNWg0c3OsmK+JaUjRG7AzKCKjzLyLtkoAAXh5g+Iv9/bhG3cGuPs7Saa0jGBEQwU/YC0fYzwTtIFskQ1sYD+fjtgEONMYxpWPbux20ZaJdCqjsznp7jqzq+t565mPXVbD3rtmUnHXutOL9r/AltJF3kBc34gI1p7ON3491XmvbF322r1dLtqn4fF3sc2mZZ/FGtSbpvuXMPDGXxDYdzivnjTs3G1HQj/O1Ek2BGCgDysOe35wHTHVD/9nD2J9vQRVnj6cNetNfHclWF23Ni9DFID5s4E8sWY9UxeO46wUH/lrD2/mypUVmY2mKjcofEhl901gcZXewk/jzTS59ZpbecwfI/mkXTVKfSHAtHqNEjGY36taXpB7CRFgEVO4q30XQ4CYSPKi2scAs5DCKp25swyX0OWNLb2Z+fR0kmisXfY885bMY8cbdYyeUkbtZy9Gq0si4nHq5Xy3q/WJ+WSLjMc5aHXw10H7CGpDubplIH9mE1Y8xEVqMmeH3yKotWbA0Nl2klJwr9GbL1GIP56kXla6sLFXBBZCQEhKivxpCDwoBNu+fzO+ew7jq4tT7Psrf08m6IdC13x8wi/5vwR8PetbuS5u8WhHIRGCLOYM7kzspJ1NzI+NQoV9GRHePZuzTpR2+nOmtFzqz9+rbZjJ0Yi4dHXGLqshNLSVrTcuIF5bjMBMsbCRY6szseJJGmUrD8X6EKSEqyjlj6qWuNrNQs5gnGMrT3xB9DYIfQVmThf0eeAc9v+Xxo23vMQvv3qEN0Qbl6uJ/Im32CDruISx3KBNBUPZvwHY2PloyDhKwbal84nv9S7Uzkm+6vQ67SMmz/1XGoTtow7zVsg8RUkv7t3fp87bzJb8Ot3XNcgn7x+oOtehyb7O5C8HQ0UuR0AyJwAoV3qi897Z6lpOmUX7/VpK7XjaHHTjAz2y1Z3YEeZ2zb/ATQ1Y++zdm3ZTZn1Ze2dqdsoQBfDmF19j6s/GZfCRs3gCG9bvYlrbkPzXmJpXCh/rTcFedYBvBY9wr9GPF5LQkuiFfnF96oFmQ6Gb1VGS4ijTNAPdmsxIrR/t0uAoUfqoMKvYgY6PTSuLeH7hEebNhudfgvMfb6Hi8Z9TkzQZgaL2ifU8aw7gS5xPeXgVergVGSpxS1b+wnqF/wprGR6ywocZ7M/gWCFlB6L0JZJqP4HUDjIz9KJ7nU450/JQNRIf9fFK6i1hB0AlBnE1Q9N5wfIMSOSyXZUGawiKY8RTHrY36G7EFx5B11oRYYtRwH/FFN8Op2uKD/flpk+dG/JRE5eMtcrdcdtEPRO1QQg2IjwPgp7MxdLgSvwRHc0TvPdwIsnlfnA2dk+qP7O4eBAHms9ikP4y5mdbaSe9CJUGV7qLlYNOZIs3EK0+XokVKmGa9TIHDEVATkqVaU1gapuYFarF+CzEQ/3xxRvzPrqiS+3fw/SV+EdE0IdEGRI4xK5EP97kIIs4ixfYQxU7WSjPYEikX4++v0IL0XFjlNKGajdIE6A2voCkKkzTunZynV7JLptbHqrG/CyUkrZdl6i0kZOOToJESMeb9KjNLJ26RKVLkOOVUNjqss2e6pxsvXw6+YI8s69zd3IxiXhutHv4cIxYSddMlj3Rea9sMa1rO6fMov1hkmzaw+x6xr5wEGnG0nBlN9IVV/KB8jhnVmQWbRk6oj8byzcxbXOurfqsRaof8DlMquQzfCvSzBc6BDdzPmi2rgOnT/aVMFaNRFlJlrObJtmOgYUGdGAwir5s5RD/Ic/juapnOW+mxRsrejE3djHbpcku8TRH6EtC6VzNOHvhjPVmIVPZntzNYl8Rj1vrmasf46exgVzmifjdn7iAkN/EUDqzCbGCXTSpVgwsPudvprMIu/2JCzBUEQM1kRMAdUxLMBAPW5rnHh3gfEqpYVFBMnWmnQ66q0/0SdfBTrYRJDOafp+Vfyf+taJW/q+5OcWtLrmWKS40K4RklbWR+dpEdNFG3HM9Xk5ySLFfJSrx+dI1vAFCvscyNnZBoVGXqMRSho2uuDaFa9d5zVuOMmOueIIISY2ywscVejP3xVOV5RQstC5id8xu2yd0hvmfRffZGwJp+NxANJHKmIjcB/4KUBJuGtnO1zb2ZywlnUZ8C93KKMKTV4KpH68YMMy/moAWdaPps6/TG+PRqXjoc8Em6MnH136ypCyLetaRnrTZ036dTL0THYuRX3gkv70T2Oj8M3on2xaX/aRLnVNm0f4gwOM9tSV0E2/F0jEPOkVHYNuS+SA0yr+5jvDwNt5evCCHSzm7zc64krfJJobWhjiw9zBDK0pY+8Ba5t00jwN7DjG0NpzXlgOLelmz/JqP/cm+/NRsoJV+vM42pjMxpz9CN2myltOUHEA/fGymnYWMYjU7mKUd5j/Dgtp4jBmrL+TuyAqmrJkBpBi4ghbPGakiE8J+OBu+bUR91QwFqhOSgQGb4vSwasRKHsWn2bvw0mANuopSJy7kd7yCTwi+HjrKPfG+/MgQfM2fXtYceFylPudweudEFcsxGdc2dlkNoYo0TBr9DMg6jRKRLpwR0DQM5ei2Ef0MfGE3PGXiprH9RydAy6OtCXZwkB8Em/hSYgA+YtwUPISutbFdq6ZcF+xUe7lEWS48C1AXn09C9bHvnIf9iqz5eMQalLOxc+559kYt5zVPlHk+cdjFrNSRwhbZQCP7M6OWU/WrrXiS0K98REaD0ODtxfNJHCigLFxD7/vb8JXbNp3o/U03CsL3HuNgbQHvGK1IFJcwxrXl3Bvn+5NPlIxTcF/qb89laNdD/d70dW6LNjFWZLKklRdVoVut+esCeDYZ8f8BuYue1w+g53rvV1sfljbfbVunzKL9QYDHe2pr9APLOw2aGfvgSjdwpie2VrS/yoXaZJsrWWx2uZKdB/hP40ke+N1RdvYPM/Lp11ljmrQ2aFzZNiJv/0uDK2kwzmWQvs6FR1/smEkjkpAaxrWM40W2sVW+ysWMoczb92UrGX1PnNm1dWjhCI+1tnNV4BBXA26FKiEZKnvTUj2LMn0glmm48P5Vul1k4kAqrazSms1G7VkW6ZJvmfCl1Gz+hB9+Yq3lk1wO2AtMqMD2tCcGWrlWV4DGtyPN/MHwYchCF4pz4M36RCUJ2dvtV3Z6zHb/OOpTQgAAIABJREFUUcaZaWhu6/UL3b8FFqXBFYQLLCpV1M23rk3tc7ZdXwkoSoM1FPrbaEvaVdDapaJQz+/1f7pvAZ8mhoz5+LgxnFGijPoEDAxUc0jFWKRL/mgkMPUI/kT6i/+2bKZQ+alil4f2cxOGTHKRHM1AzfaE823sfBH7nncVhOadG/nEu1EIRkJYUYMJ2iB3kb6BqRn6vlAATbfc7Inxj1TntSu0EEpGmTVDAC08c7/GnT9r4Y5/K2WrYW8Cevqdc2ypRHZqZeZ1PFnwGjNHh9G09BgERRsT90rOjtsdzoDHnaYVOXwK2TB6Z9ITvferrQ9LmyfbVndyyizap+X4Zb2xmXJ9G68afpcreQLDeEi+7j7A/y9xgPiqJAPYysURwUNPvsmFyU90ypXnwK1eeHSLto1CleRMxqTOKYfzmtrlQpQy9RlppKJzdVgRTFAEVCcVFwWE6+kOC66mPl7J+MQwsLOcXHh/qyU4wjv0w08TRfyBNdzhNwGNsb5MprWRvqR7bl8arCEcNNkbnZPB8d0mJYYiL0FKWbDGLYEJNjtVo2yy2amYik/Xscz8C0JZUQ26ZZdjhdzCGWVFNS78iwG39irgzuY2vlWctWDnIc4xpeRxtZsHQhvwaxoPJSSXBQC0HB5wR/drog+lKg3vR1WCZGAXpaYbX2gXwVBjWJ7cgk+MRY9AaHgbHVt121Md0cq2JZVEd/QGJbotc5lNhPJnNhOP2nEAJ5usZNYMwawZzby9eAGfNotPiOcxe8F2xHsdlbGxjL9uQ1Z2g6LPnd0Y7yEB0mk5LT2RU4bG9MMEj4MN03X2Y8UMukvUM6WJVJu5OCBQgW2Y0uRCbXJe+kKp2rghZBu8zG+xWnup037VJ+aTDESoN2yO792xyyj2tTBOa2E/zaxQ29hPM+N9aZ7k/fHzWW7tZcfN5xOvLcL/U8nhaDJVJcpHu1ngsk/vl+djUITQLQIDj4BQKS8wwPSAYIy/jYs4jxu0qUwMtLkL9T5LZVBr7rbSOLPCRywWQiEyOL7/ZsI1fjsaXmXBllJpGVHZr8q37Q2QfDtjPPJJ6H99MMxuUyqf++PYC/2vj8gT9o+j99+/1t3XnB/hyXLb2x7l20fD/Dg+lKuw+dPvivYjZqkcHvBaU3JXtJ+r+5jaRx3NbKPR5SCfkpyFoYrw8n5f96uDxK6CG5dvY9Jfn6HsS2sJlqU3NGMftHO1wS4L6rxnxZNUy+0ZY5CXJlN5q1Qpz0/uPIPj+w7k+z709DunZJzo7SDrc9/zXscMKlhXFc6gkN1cLajwPEbzwZvR23Jtn8rw7Ok231tbp4yn/WGCx71QK5CRG10bX4AV7s+onz1nP0A78XTsSkz507yyz2cn+Jo6jS7P7r/LZuXDja4+apVwWB3E4h33rLjJKmZ66lm2Tu6jXN/FLvYySkvy2x/DxxOAgI/6TR5OFHBR8iMZ7TnlWFFGuhSiB96HzAC7G3322fCndPv3ZfLf3C1pfaLSjqRXBn4N1xbJydRb41w4OyjaMuBxh83LlGZOOlQwEsl7P7fJJlhayTbZwJSiPsQ7fDnBYE6gYVmwisbkdLRwhPoluXre+15RGGFMu8SfqEh5y8MxtU3EhcgIZItrGuV+GG2mzv+1fkSlwQ4O00aCK6jgMfECrZHtTFWZ/Ze3wmUIok/bN18LJ6HZAkOhJDmsXk7cRdIveNmsZ64cSchTpjJ7nl0anoiKm6lrs+eRF81w5hkGqDhsXbqA+L5ixiyrQX3/GKoOV9/hMwgO7UCpTvKqU3PWZj0jg7DIK0ILEflJNK+nnXEdqo1jK4fywsJdLjXvjH+EgPSDNh8EGvnf1Jm2x/b7GZ49laHq96LNdxseP2U87Q+zOOxeXtm+tJKN8y/PeVA5kjfNKyXO+axbPUj2zvBSj1kleW26ooMUPjc6uEj2o0yDcf6j6JrGGF8r13EhAIaUmP69XBwQNAcTmMMk+i7cClx23w6BUHaUr7CvVOgWoeFt7v9TtfHUGmM5x1MK0fHAAVYToCE5kL8nJU3JQYS0zlPnHFtTQ6MRwnRTehx5PWmfrTte4GrtJT7qt722j/qTeZEISJ/fxqXJ02xmSKCaUeGnCGrNCEzXnh1xbP9fFqyhLFjDqPBT6KLVfc+r78jVkVgGmnGF3sK1ARsxgBQPeIH9pb9K9yIfLVzGBG7QpjI8vJZxgUNMD+Xu12XqyMP5MVLc48atUWRdKo85Nd+2L63k1T1R/k++yO/i61jMFB7hdf5PvshmaaceZs+zt81Gt618c9qR9lt8tP6bD1kr3LY6m+fbls7v8nvQ3ecdid4OspG8KdHOdVwUHktMSl6uirg1yMfo8XTkedBmJfT+T9BjuzO97lNzj0/03D501rcT0TnZeidqSwb9eX8SZX07fe94dN4rW93JKeNpf9jgca94U6d6aqurNK/sQCATi2fNv+REl+frl8IuRbnj25UYtb0wpYkvsIPBQrDNUvw9qdDM8a43/IQV48qAfe58aRIePQC+UdC2XVIkUufKEwIEW9oY/q317PvOdBK1vRh9/2qEJth75zQStfYDN7sUotcD70OAWb6zecBYx3+FkzQYbRm81/nKKo6+vwb5vVZUXRpWMKJR7jV680C4mgPGxRiqOO8GKLvMYRU78SO4msk8wuv0o4hvH/XjFwVcH6hhhO5zubizCTm8kNiw4Or04u15mMt4nPWGpJl3WMRUfqN2sy5ZwKxgjH5C2hXBBPgN23t+1bLLln452Mxd8TK20sQB2UIs1ouJ+hGqWzuoDAik0gCBwKI+MZ+3rES6jrQnKnycrMqZYxO1QbwuD3AmQ9z88bd4h4kp2s+cgDOZJpeoT9jENNmlP50I82xxSH0c/RP5zm3YANPy5MB6o8cz2AcTdnfd60iRtRxYfczObli1AP/v1mcFjfYMKvXqZTMeAu45+IlAqpH77LoEXbXZk369e3onZmujuZgY+RyMnpCd9IwQ5b2wdU43GqfMov1hgsfzUSU+mexgUdD2AMPhuEtGsL6okQPlcYbWhjPIUDpL88onwUgY0Z4LP+frV32ikvol6dcdGL5I02iQFs+bEZZ4vOGw8Jy5Cg3dEFxzW4THb2vjGgOeNQPMePOjGJpgx9LzXZat7Usre0RvOFUbz2osLrAmkQSWaAvYn7ByqqjlG9ftSytdaLzBauEhoz9BLcRVjOEn8a20qe0sYCzHyN0AOZHVkFkdKonFNEo5SpQSEcbU3kKTleyJF7nXli1e2MxJpXIIWoRH59wQTI81UxvXuEFNBQm7YjAcmzP80+EmzKBNmjI1AFMDbdTHF3KD1ou4NHmCzSiS3OaDJyxISEnQM0zeSG+/prljJrB4bZNJPh9gEWeynJ1u/vgnObPTe5V9D/KlknX2PcnW7WmZQ8eWaUp++OXePLriKH5/5txwosfBLs7jPFe1pcC+XHtDZR9aqmcxVPbJadNrqyvx6jkbBq849QZOJjzbk76dSP/fb236ND+W7HpT1xOd98pWd3LKLNofZtnpe5a+IklNEio9xAw/mjGKSTfM5syK/hzYe5gnHtzElc/bqVoBTaBrZ7A8ubXThdgrTnT5hZ4FN58ILNCVe77p9UIXB338wUhknIcf83r8SmLoUKh3MHhxgOUPmGjJsVSEV9rVxnQ/de3zSVpdQ5nZUqmfgzRjqYVaUBqsyeDj7kqGBW3yjDJNoyARY7gcmzozHoHp20QpMNmf4G+eUpQLxOQcO4uDe/hlYhivc5AzGUQQwX4S3Kq3oGk22UX2+W1X4kVXHGIPXbS5kfjZcqE2mfoEOaQpm2UDNbxFmACLmcIqdvP/YgX4aOOg6OD2SLrwi6b2piO9pckl5jj6E2ZQYCW3/UTn60Ny2dqq2Mk2DnEr5/Jz1iGAS+l6Dr2b4qAgRV8p5srEGO5evJVEwOCm/z7E8NL04q1SXnVGwZ0uHMDxiWH/2o6fltPSiZwyi/b7Bap+t9s0pUmLL8G1AbtSVEJK9LjBinCYSTfMZmiFXZFraEUJ3DiRDW/Y9KPDgqsp1QQPRSs4v5uF2GkzG37OpzMsuJq+y46x/Zs2qUtXMDzA4kCUZ00/i3TJ3wJwXary30euVPzmD4prY1tc3b0/vBbrbgtRa+Ydi676VtbNQt0Zv7HNLy4YEvg7W/CjqaM00OoydRmaRmNyAUq+zXKxmf5XhNFf8ZGoz4THf5UoRtHGIs5iBTvQiSKVwauWoLUgzI5hfei37zBntxZn8LcDGLEAfuXLgYoVPl4zfPSTlSQTxZQFazgYPy+z3GU315kPwn6FOqb5okjN5tYu92t24Jo12MMq1o6WOMpDqoFgYgBXilL+sH8fMbmHhYxmoFbINnmIS7WxXKqNB6n4InNzxje3b85r+Q9yM/vfGZQoutDL5GF3UJCSpkF2OuKBCrTLN2Uu2DJuL9ZZEHW13M75YnonfbNFGj6smA8taOeWd1Wy1dkYAFj1cbTcGjg5l3RCEccJO5AvW7pts4c6J1vvhG3l379iSTP3xRPQeb/aOmUW7fcLVP1ut2nDz/bfl/phWWIQF0cuYuOQrXykIrOEppd+1ImYPl8cX5sbit7hQHmMobVh2loOp8s0euDxFYuaGKvZi2M2DF8ZugDiaY9M1zT8RgXLxS4GfCKI/kaS6GdAC4e4KgvSG/mFR2xvlOLjHjNl2d/gVfItPp3n25zP1riHq3npy5P464EGCoxirmIMq9lBAVGa0dlKb/dM1kEi5j89gURSwxfOhMdHyX4emtPhGL6tXNdH8oPJZzDphtnMq+jPgb2HeOLBzdz+it09kSohqoVCiHhLBoe4wGJfbC738hJfooBgYYADXIKljn+eZUPYgwmx0N/M01Z6jGzimqM0qBZMYXFraDP+gkJqj/kJyImp/Ps4x4pbGNhWxBm/+Tvfu8nPxMFTUYcG5lQDA7ucZ5rJrxLhi1ByYDUH22fyVjLBuFC/nFxvXyjgUvTaxVgyc+jrEpUk4r3xhexCEeW9qpERQOUiGc5YnK+XU8VOGmnFFBZf+Y8WvGdFNpd/5lysSUpKA/t41Shkqja+07HdcfMFCE2519oVhBu9Pb0x8FeEMPd2AfWmmjkReDx6O3kXs27b7KHOydY7UVvyZ5DB3pSS0/D4aXlPpbMo8KG1YZd+1BEv/agTfR3b4+uUySpbnpi7h3OWTOLMihLW3LuKEU9t48HEMZZo81wdy5/kKWMLd+i90ZKB3HSsoB+LzAf4ub4K/i4Fn/+3RuQbSdDtSFC5nRxnSgiJUCboEBqeoGOr3qO+709cwAa5nXJ9G0/FJjJVS3ujzlh0bNURAekuKmiKYb3ClDYUUSIHpWDxckztLc4Nnk2SImRCue1fqE1m7LIq9n7rXJKNmRum7PSmz/rjrNC1LDSkP9w4kafeCDCtbbBdQjQ5A02L0F+udq+9QbazSrxJSPi5Wk3mKd4iEbW4NFhBX7qG13WRyOAeBxvC3koTvQlyjCgWbdxv+Pi8XgB0AOnAta+EjvI/8b68agnOBWaoqTzrb6RRtJGwLGaEi3mo5XUXbv7D/n0krN1cJEcxSCtk7P01dtR/ShyPb8x9NXAoAv2jvHOjyVP7tvDRn8XY/92ZxPcVpahxJbpoY/j9qzNseGU8NWxbWmnbMhSRH6chbXfuZI1Fy63LaflbiLt+eZRvfbYv6zYIZs1I9S8BqomMeWhIyWEF1+rpFL/s4yWH9917vSoO6hCQVY7ekYi3Wl8XekCXddq7k8j/gpZnMeuuzR7rnGy9E7Tls0xEHvQjeLi128IcPdF5r2x1F4l2ytTTNhvbuuQ3dkXrmge5xzonWy+lk62Vsxxl2VrBWq4PpuHnRxP9+IhvKoavkMdn1XLODZMZWlHCgT2HeO03m90z7XEPVxEcGkXoJluvz+Un96ZXBYfEeKG5mZKfjGVoRQmmYbLlinu5PBbnM4kSvuibRbL8GM/sbaBocILJB8ewpWwrrQ06F8nRDPIXsjK+hQvFmRn9H7esCvn9VmQdRO4F7QyI/juEvgxoGvHvyk4fTKF7NUxRxJ47z3Wjx/OLQmiKgb4qnpVRFumS3xsaU5Ifdx+045ZVofva2f5flVTcvc7lCBfCJuWQUvK9CyfiS/rs8qKhzRTer6GdAU9+ajK1xQcRqVDugomHie0qJrm9BK2s2X29XSVoVnHO3nEmb0Z3c0ngMK9NGMrcny7K6fHa//con9vRlPK07ev0q/YMnccTBQTkJCaJIWxS75DQdlDhSzDd39HFWEBSFBNQLRmv1Xlyznf6nkETMSDCAn/6gef0JaP0oSjmDeMYVWYxMwJHWJHsxyAVpphBlIhIRt+uCR7NaFNgpdAE5y5BnaXxUKIPQXQmq3FsEluJY3B94ChYCxikr0dowu2/0yeBzNu3oH7UfsmJtFa5OgHVgha0iNyPy1vulY5bADRkbQodMuChuM0y53znHk4MsjkOPHPbKcmqBa2ML7FW7rHVhXSr57Co2Zh718aydVKc58fdZg91TrbeidrqLL4jUVZCsC637PHx6rxXtmas2/3BqKf9foCqT0abDb+/lZJv/InDd19NyTf+RGBPU149Ry6Qs/mb+aQbBLUkeIRQwUvsPTaHK9eMZMNrO9lY/hZDa8MZfOFbr1/YZfS1MtLeWLKxHwdGNLnVvh67+VHamvuwMVW/+VH5FvF6g4rpLQx/7Wz3bPBYpIWB7b1RFvaCndX/jlsgqNl5z2d/HiK/ttuLft6Gx7uC/X73WYsrikKo5i6H1S0z+WhLK5en6Dw/6jd51FrDfCrdfsiCEPKYMzYLKP/GBiKjj9Hx7z7W7VIcS6a8zGQJr1qC6Z+3HwqFRoRp321iroe6cs2LR9n37XGMWLQj63VF21d78ZVQkqAmaG9s5cDeQ66nDXBg7yFGRg00YUfrCSShcBIZszJKKk6RkuXs4aBqx0QyXEzgl8ZmGoyzmKAN7HQ8fJHMQDRHtkXqOTh6N0IUc0QJSvzF/Nq0GLJjBGOjQ/PaChVY9LN0rlEmr6tn+FGkmd8bbZyZnM5Kle7bpcFKdqdIUxwP1L436fKK9YlKfOEII5MvErJGusF+x2jGNOei8NnV2ApMNzPCQSIGBl6hwZiZCX1HdEb/+FlCw1tdr3S/cWEGX7wzFuPurUIrzc/lX3CfDY/LWJpcJSTIQrcOISwzo4Tk/sT5AIy9NxNZ4FAI+vegYlU3es41nQg83rmn3YO+naT+vxttbrI+SUx9AEtzdiOnzKL9QRGRSIJU7u/uxK/5KSbI8mSC/gL8WiBFP2k/mKa1DclbQrMzcSouZYsXbp988Ci7KGYso9P1m80GLn1lDlViGw3+NkzT4qNtQzG7Qa5NKbnX6Mv9vhYiqAyihHzwONh85MXAE22DOKeLoCtILQY+nZB4OONBW+xrdqPYFT4MFca7K//LjZO57NE3qEucy5m+DUwPHEOgcWfvODJm69XH5zNAFfNC9RbOm9WKEAKlFG9UFXEhFayueovzZrVlvD7PkwZUaUh+8NuXIAWRH9hziE2/e4n/7x3bK/WWttyYTDAluNr97Pqk5FiymEX+Y/wkOZDXzANcyUSeYDMbZD2XMOa4OLyL4oUMW+TdfMRZ+6Ki+M5DVIT9eUtMasEIe6NzWOVfwZV+C4dd73vJNSj6usVT3jYbGYf98BwWXI3uzUFPVYQbFlyN1Eu4xjzMvfFj9tk5FreEtqJp26iPVzJQX49f1/HJRjc9bpg7JrkTLXobmD7c81+Ht97ImjPR20B/IL+n7ep44Oi4yiyXmlCCEeFnkHoJmsz0lJK3WnhDh7QwyO6fuz3WOxGJ3nLibZ7s/v8r2yzX/5g/EG34IHz7Grq01ROd98rW6dKc/2Jbx9vmoBsfyPjdE1sX+sP8xUpwdUCjNj4fI9E7P9lyN7ay83C9etPkEJ54cBMsmcThScP4/Kt7+K3hqd+sJrOVJo6JBu76zSG+smQ4G404E0T+NhtlG3+IhwgxlKsYxw/jdcg7WvjcDxoZXqqhRBK5FKxUYI67lFhwWPlSMPdmTDnCc56YL0pYIeNxjsjs0pKDXM36xHxEUqGUljEOHzVl6n1PelUe7vERq2bwwoIVLnVln1UT+Y16meTKPjy/sI15nte9fZTxOP/5yi5qNtXz/NA+9Ns3hEt++hHiB/9IqLaJ+sR8DNULK2bxs/AKZo4OZVSQ6idN7t8xED3pZzBhXqKWRZzFGnZTxU5P8Y3MNvM9yYbKPrxQ3Stn8zEvdhF7yPSKM21BRFgZG6IJgTamWhcBcAPnIKTCOfixo/Ezxa4MNx0zUUgDy2lUbSzmHB7hTf4am+MiB859GhZYRYMxnaTK3pSkr9OKJ4n8DkIV0P4ZDblPpI4BijJ0IEU20sWCrWQ8zUym4NoA/DmV4vesGWCG+TF2S39WCVL7d3lRdbr4C0BpHLKJUvJJd3r/BLnKP6N3KvGA7/npYhLDT5OrvG/lgwKPn4itusRCPh6sAlpPyFbeikvSZCH2Q9/Ru/L5EWx4YycdpX24y9CIcZBp4jCvqEFomo+PMJpLghvRfRo3lY7NW8fbsTVQK6L/+WcwcDV2RLUwkDNaaC25kfXJPhQEogxQT9EUP5uB+np0zWYB+6OpuCLFoJbNmV4aXImutWZ4U2XBasIFJmUd7TyRSi3LJpNxdF68Yz6PfSuEsPZzNZO559MHiLObhZzhBqE6UKMmpBvN7Sx4c2a2svVtwU2rNiC/W4Kv+gzerG7mvJmtvFwjuDW8LmMsHFuV0QSVOxuABrj5dftNAfiX80ejP0EtkreC1JoXFbE7xjCCARyhg75udLrBEaKup+2Mi8DCF47kwKlOVLV38/H8S4oLX26lIvxUp/NHC4UoV9WsTWR6njElOCP8RFovT5vZMjxUhRaOMCoWZU6wA6jjHgD2ZraZsjU8ZDOwvZ6Es1M8Kg4yUR+vxAqVEL0FTAtQEk3YbXgjyI+nNGfBfVH7GGWnnfFQIiTLkyqD48Brb8yylYSGt2aUEXVsKRllw+uSjVvI3D8pOHMCTDtb65YopGMpPLZLck2v7sc2B0Lv5Ez7gxY93hlZ1Ono8dNyUkXqfkTSQgV8iKSF6IHH7D0nFMKOsI119s30fEYXbcTxMUgLUyqL6Eeh56HfwUCtMOdz09qGMO1teJUkffTNNBuT+KI2Lud8XOBwc6f7UC23cwmT3P/nr+rPcrGTg9I++7z9Y1HqPnuA0d/4M6ECi22JWSRVxD0fLA3WEBZtFKW8Te95IqTPEe32HVDSHhdd0/CbdmqZ/aDNZR+rHPYsDVOK4MkSexyUwREVZZBm5ww9FoNPeo6chJCgFALJyFVTuTu8iiunh9i+ZA4zGkM8rWqJrh3Ad77fwidelNAJ41lnUu7XGGwMpK/syyQxmBVVm5k7K+Z6whurInxcjuM59gCSDpK8I1uQKD7CSHcMMsYvu9KL5zqGyj6sqxbMmanYUiO4voek117P828mLA7YUPm/WpyjlQd8R/FrGvsTF2BIO9Lch312K7/ffZT1a5tM5ozoWgfs822HiawyoPGraHmnHAfZqV7Z0rcvjBkF581Mj9Paf0j6dk8tDUB1s6QIu4Tt/G5itLRykJ69T2fIwonEtL0beidqy2+aJMldBMOilSjdnB33QOe9stWdnDKL9gcFHm/87U30+/qfOHLP1fT7+p/Q9x7q1pYXuiwL1oDSqBWVXbJrlQZrCKp2CNuzfISU/Dx2ZjolKbiXJrM/hirO22YmQ5rKgV3LgjXsFQtSHq8gLk1epp657aMIpRbMQ/4qmq0gXwnbaURvvtnOWXoN5q3QLjSGqRqy53BCSdpkOnLXUDCqC28QQMbtB+MMbSTLDT+fDh+gwRiaQUIiU7lH19/ewnefbOGgbMPSTT4+dDCDGmpQsplnZQkfbz9CyGfbG6avoi5xEYP09YwQrYRWQ+nzcaSxipeTEY4JP3eIFr5WVcAhK05Fqm62Ezltxe1NjvJENTvvOXJD8G3uS0ygQbVwdNUgXli4h7mzBc+/pLjg5Q4aA3+hxezN+T6DP5phrvMdZqXsw1H/FqYHtJwobWcsvOJcR1L1YvpLIe75fgcff6n7RdeBI9Oep6S/sP/Pp9dTe93pOAxtQXSuYhw/idtR5p/Sqxmh++1riWtuoCPA6yHJ1hEQl68i8dOhEkQIMnB7Bc/8JMi5l7bn0Jc60hkhygJtjFtvHDK/m06N8c5sjRyuUbNWMudc5W7Ctu5QzJvl67JNAMOQHInBNQGNx6JJgk+Drnd1v3o2/l21eTw6J1vvRG1N8j/SiaYG/u52AT3ReY9s8QE5036/QNX/TJtJU9p5RsGA+1sJkeFt98SWTcaRmZPqlHVMe+UqAzZ71RI00cJipvAwb/G6ZVKaymt1omK9NhQaF2qTXW7ucIGVhuBS523loWqe7TiLKhopSNFkPsJrdEiD+VTwkaCf2cFmQONbkWb4he2fO9eQD/bL8Oos+GT3FNMZthw6T68U/Boio2w48h+vCJoCLVxnnMMTQ57nL4fj7DRDRMzhLOYM7ozvpIME1/kOMpgFJFUvl/e6L6Atq6H+rukMbiphkWlQb8DNqXZ2p5zc0mAND8eKmV8wO28kt1e2yAYatQMslmfyiPUmL1cVMGdmlM3VGovxoclKFole+EI6XwKsqMEiAViZ7QU1m6c837juNy7EVBEEJsNlgNlrBCNDBccFu1YGNB5PSq4K5C4eJ6M0oROw5guFKFfRVGlRD6WstolSvz0ZBGlCHQfr6ROH8dfA3Nnp1LM1LyoevyPEVWpKp/SlkMVp7VSRAnuee4CLnnw3vbYq58GL6xTnzRQ8/7LiovNFXr1sefBr8LFU6dqPJOz/P/fDnrXZ0769G7Y+LG2ebFvdySmzaH8QPO2mZZ/FLC+h8YGlEPDR+NvPMfCTP8vwtntiS8bjDNNX4XXZnFxcb5Uh/9WWAAAgAElEQVQox+tSwLSAYFqgDqjj7tRnlLJtJGUxgVBLhg07EMj+OyCixGLFBJS9GkZvs5CGzWR1aWQTG6O9GctIN9J8O1v5eOQVu68qP2SciIVce44ILPzCT19hsTwp6U0Ev0h2G2Tv2MqmAcW9+vQufdYMQd+RZ9BRG+Tb301S+53h/GLrHs5kqKf/b3NuyEdd3NkApe3uuPl8m3ddJD1pVOn3lVJEtxcwNrCXV6KFTO2Gh3uCNogJ2mBAcQOeClKrK9ntiUTval44FbNCoWPpACcnz5cUOkM6j3lqUkNaud5Ndp6zYdn0qk4u8lVBDZnQEEoinMAtowsPOvsEJ0/fHJ361vkMDGxAxAQBleCKQDv3xVvdtLKLrYvYHfMstqlqYE6+dDk+VlQFOM9zvLCqyo8poRCdiv0j0K54K2fBhkwPzlu8w7/EwtyX3hgHy5qJ700dKWn5J6XXluNtz56R6WVn6+UM2yZP6Vqh4d/UtXf2fvB6P8xtvtu2TplF+4PgaQ+68QEOevK0zREDMh74PbWlhULUHpuTFx53vMKyYBXhkImMRalLBed4073KglUuV3d2bq+3opLzt1dn3K9sVjAnEO0KzAyazMuZy+5411MrXz6x06cKVcwf5MssLpzH7p6Mfye5yZAOGBJaxN3ljn1wJRZBNAzGPriSH5oW/31egdv/O4KHAB9loZU51Jhjl610GdFy06hs727dN+DigOD3aitm8oxui7V473lnFaScqladzY36RCVj7qvBH9HxDzhM7BYLlXXWWxU9m1FaRcbc8ErBfQLhOQs1m0Ls/uq5VNz1sgsFv724kgHvrKPPfa34httnwDTl96Aj90FqP2JLKs/WSa+K3AfaKPusUlsM9Xsr3Xu5RTbQyH43rWwrTS6lrHfMvHN19OpjPL9wBZGwZNWLCnksROHZDbzAEZSQfGJuO/niDjrzgMY+uDJLL3LcXlflPLjnx5JFV4ou9bxiTIK2N1Kla5XEnJRXrUe2jlfvVPd634s2T3vaH2Cxc2EVSve7Hkgazu5ZUJBrK4uyMVdUhq5lGTzFFr4se6fSvZRrIx/1peqEbcgbFOfIya70ZErJPuKYUh7nqJDj/a75eYCCSYKzpxtMm5LWW6s9ztnyqxSym988YrAjeJAflTfxnzsG8Iek5vK9dyX50qjWrBCUTLL4vRCYyuIv6ln6qj4M3jGSsdEeVEXgxCtIecuZeuuvgz2mj7OXL8uhdJZ2sv0zF7jkLmCTq8Q7dDDAkkE0zbNhMFIUpV2hIAYuYQnk5tlGb4HwvT57o5BFVZtTi7sHMlT24fmqIi69oYVzzxHM+4LDHmew5kXF/gMwo7t8Go/IhC8js9JsKsI/wEaHsqPGO5ORwzUq50lGDu954N6S/4aHPgHXGPBc0P7/tJwWR06ZRfuDAI8PK3qBw74lLjwOMExfzREx3A2aymcrX1WoYfrqHD2vOPD4viQ8bL1BUOhcrSbzrNhAXCW43mqnTF/NqojOttISxtYf5kKPF+elvvT2a1hwNf5kFCXTD9lLtXHuIv1FbV6PSGPyXWedqXjY2oFOkKuZzOPR14mTTk3ria183u/alxR9+0icTYhMaKigvXADDFgC993wMXxLj3B/4bEecZ3bMJZgxKrpvLCgxs3hTr5gMfkuwdzZzkPaZM2LTbR9NbfOtIN8dFaBrLNr7KJXbr+cOVNvJnkoaQd1Xc04nhUbOBjT+LyUjPCRQQ+aPadMfyHviHNpv8XHpt8+wrSyO1Kt+IjeZn9MGhpmIECAzC2eVBrtN2eOo1PNTGDhAEzbls7PIEP5p79zK0fxaOR1CmIFzJ0VTQeBvS24+bP5j2o6gyS3LZ2fmdbopeh9uKrLQDSvzJzWNSSfLbquMXixZPmvJEOuF+h61/Px/Qr1fljaPA2PdyKnKjwudb/9ZR8xgA3ffAKzfAADb/gFR/7rcsyKAdQblQRUU5e2BJZLewm4tJdd1Wd2INAylWC0lSQgx5IsjKKNbici2viHZvFo7yCFQ4opnzoFWdyH7z+4kSueP6PLa6xPVFK/pPOx2KEdYbTsPq8l75hZFzOMXelqWamUrO6Yv7Lh5Wzv9+0tgvPPS0ObWlAyn49B1lFhB10HSwndAk0x/pFqFyqNLKmkakURc2a28eaKInolImyqPsh5s1RepjSniIopJU/F7cIrRaMUsT2ZC4o3lejtxQvcAiU5cyNlTyZ8jHuomsgoEyWjbupSeUBjtGUQkGNSZ/ZlbGE7FQUWIuGk7tnier0pMZtCjB9Qg6ZbXKhdBcD4R/bQsRRC3wTfcACJ0JK035hZ2rLwfulC305fnHnrlXEPVqONgq2fsvnx885/3eq0GhhJBQG7HZnwMVedwdvVYYqTBRmEOPMmhOgsyroz2FLTJVoojWaFR1jp+9TJmfbJgkovXaTxcIvk6usKTlmo98PS5ml4/AMmTQ8sxazoT6ixFbPUXswaf/u5d639+vh8zrKKqGIHHdEYCxe1pAg8NCDOmn8c5GjvYoYM7w83nunW4z4RMaXkSWMjX2JeBuPa8UhGtSwhuZjRx20jm8HsvFEFxPcV4h+QQNMtVNKHDPjxaUZGOczuZGyenNyxD9YQ2Ce558eKRTe20lE7nap1B3nhH8pO3XpZMWHPeBB2tbDw3cv53f1hdFPn6rrJ/HXgehJxk5t+25gTJOXUXxbKzs03chjCYPT9qwkNb2X70kqk4SO+L4w+IJrhqF+ht/O9WCPPq1rCBLiWKfywZScJGeVT+iE3Knvb0kwKUAdqH7esitDoVjtP1qkJ7cDjpCpbZQ3j7/5d8ulfaTYHdhdDHL3FPtv26mQXLxl9/2pq75pOfF8mPeno+1cjv99K6A47V3n70kri+3q5xwsvrChmzswW3t4imPfvPfOGsu1nwuMl+AfYNKaanpsPf7Ll+pv/9bnwp+XUk1Nm0T5V4XGXrlQTHHzkFswRmcUesous9TR6XCqNLdZRztA6z9V2onq30kQj7SyWZ/Fc1V7mzjJdL/D17f2YNd3uk7ce9/FcY3eMa/mkM3tuXzmLR1RuAFJPbHkZzN6oKmLeqkvYkoI2xz1sB9HtvedrnFf+GYrYlfFZZ2zT6XOZopSdrZcdJeycW6rfrGL3FYJXqhVzZiperVLc9t/r2f713sT3FlM+2M/YKQY8PcYtvKJdvsmmds1a3KK3gblTY4haTVIUU+cJunJk+9LKzL81QWlgBXqKpEFg8ffYFJKiloGREProo9RrUfwqjk908IImKNk2kZEduZsjZ1zbb/GhLwNtOLTfoqFqZao6VkqEYW8uUv/WJG1ikGf+XVIZ0Nz1ODvK3GE7i94CznBa8SSlnuyF7Gv09s19vRPkZ8Tq6dwdWsGUv1USv2h9XjgbuoPH0xsFLaSQcfsqxz1c3WN4/HjaPBG996utD0ubp+HxTuRUhce9OiJhgpQuIxqa1qPocYXPpXAEkMESao9O5gne4EuyPK9Xq/BhBvtDTGQE9Zyz+gJeWJjyQv8Bw8+71P2Mtx738VzjQK2IUtkrDWtn0Wwejz1vX5dGZp3w+I9YNYO7wyuYsubcTnQEq33Puv9dYH0UH7tS8HjCLWDhPandev1C9yzTgbqcYKWdryimT/KxfWklc5rXsy95mHt+rHjjxSIu2jEbs87eXEnDx+L/OML3nmmmUWvDxOL2y0JY8ajrKYJ9ZvpqvIXXxxSjRIAjRCnxrUWassugNl8oQH00c5Ebq8FYRlIfO0rv62qYNzu92Kx5Edq+mr+YccaRyOIuxj+iM0Q+h661kpTJVC1qjT8akrgUrPFPpmnMJjS/hrDsYEypFCu3FvIr2YGmpU/E8/W/q751JWX6wLyR+NnSGWw5/pHqLL3jjx5/N/Ter7Y+LG2ehsc/YOKcacvh/Rlw84M0/uYm+n37z+6ZtiOr5FtcqE3Oa8Ob1tIo26iK7SSo6rr0avcnLiDkNzGUnmHL64WufSHIxCvszYBbj9tT3vN4xIW1lc24diKw9smUzlKneiL7ExdgqCL2Jy5IwbSdy7al83ls93Ym6vtY9uhYpmq9eFVOo3b1LmKhDj4Zn8Dv99USZw8LOQOx9AKab3uOlvJ3+M7Pj/Lljw7nmRtGMjo5x61s5UgiNoNzPvOKJ6iuPVX+MzeoLZ9kw8yt0uCNKn8G0pJdmexEpT5RicDiBe0prgzYCMWlfngw0Z/xyf5MutZi7mwnGFCw5kUFd0zgJ+oAbSrIAgQD/wVo8PjEMDcW4bSclg+CnDKL9qkKjzf+5ibMEQPwJQ2sgA5CZJ5pK8Wr8m3K9W28aviZGp+Qx0r6gTNQK6RUde/VOjSmdeKCnFKFI1dN5Z5wDTOeO5vaNTtS9bhDXNlWcULXCFDFDhvWFlN4RL3RLaz9btwnb+pUto5IJNFisbQj7bMDsjaoKNumVBOXJQTFMRKqD5byZXi3KgFmnYGvFGKGySZauM2n+FNgK2ZyNNPC6zhgKAKJyTajlzQ4TLvNAR9cwagH4pxDnMTlGncF6kC8A36T+rgnktpQiOTLrKjyc94s6S6yK6p8jDETtJFbYlVg4UscQaa4YUuDNTQa012bE7SB9F59Ac8vXOFWJhuVQiJOdPy3yQYmJwqQhCkN1lBgpiuC7YxAx/gGdiKJPa9lXMfLVSEWUsEmdI7R7PLgH889zxeglq//+WIRvPJ+hUrfizZP9f6/F22ehsc7kVMVHp9281XoWhtGxSg2fuV/iJaPzHh/oL4CFdidIuPYhgpMRMQzvYKyYHVGzu0ZwRA/PTbC5RHvzKvVQiHK1Mqc10cBkTWCc/QNzDRBHihBMw9TL3JrEffkGk0peZODfIl5BCMhboh2n1f7bt+nbJ3s0qi7OIdtciglRRrjr1njocM8muPdbr+5koOG5C979mGqnXySs/lJfCtREtSxlisTlUyRFsvFHrdYysWMRqFRn7iIsctWsO+uGcT32RutUIFFPOphy8IHumBYeCGNK7fw/MJ33EX20KpBfELvx/eNF7lD751zNBIYoWPugVJRg04bZaGV1CUq3fzrQWYhT1dpnDdT8mZVEfNkEZA/39+ht/WKN3/flJInC96gYbxOWB1jvbA4IBW/ExaT9gr0uGL+JwXzZh9m9z7Ji+vgvJmCtS8pmlcPZoXahonFx7RBbtmH44seN222tpTIhA8RkIiUV+1Ge3fjZb9fodL3os1Tvf/vRZun4fEPmGz4xROYIwbg1wRmnvzlP9ZF+ZQ/XYryEWMtFzELl34zD4PTq4akmXe4TjubB+VettLARAZkaXX9oJpmatSlqiaFNIt4zJe3ra4kbwBa1PTUeT51xJSSp9nMvX4/v68u4LxZHZ1CyGMfrGGcFqHuBz7kE5NS/NgVmNomLK2DYf7VvGk1c8wq4Q79MHfHSl3koayoBvM/2xhGDfS27fkrIhklB+sSlaApynrV8L1Ci59XhThvpsGaqgBhFeSZkg1cfTAVeZ7Fp+2cu3bckk7BKgvWUJuULGuvoEAzGbbyHL4TWc+htYLKgicpz+ITl4YPFEi9BE0eznivPl5JvSXc+14ZG8v4azZ4MhJgzYuSPnfCK4YgWSOYO0ulKD0tZs9QbFgBFq3cWPwO328toMG/lcHWgk43jF1Fj4eGpzez25dWUv7N9e5r3mhvleXASD2ISlWTizOCUCogUUskEEoh9SAkLbzRgV5yFeWkcmaJ11ZXcjL13q+2Pixtnmxb3ckps2ifqvC4UCaoJFr0KAT7IhIKFKigH4SgxNxPUar6UJGm0Vs0pQpA2A+euvh8shfgqZhMjTQDq/LWJHYkX8Unrzic1CgNwtKT9+205zyUsqt82b/zBqD1IK8a3v371JmOd+NxFVP40bEDHK0J8PyCji4hZCXjXH+7yd1PttAk2zCFxacDzfzBV0KdVUlfn+C6kRp1+ySf8ik740uH0P1+IsNtGxvesGsuC9UB56Y2aQrGnVHF79YN4foftfPkH328uayAuwsMtrxUwIhxhxm1Y1I68vyyTRmpYg68VnBfxnrDBDTO+vFReHoSk+RQnlvRxrmfeIcJt+fOkW1Lzye+rxfB3jES79hQuzJ8rqc7UMO975PJLSm6vlpRYQnin/8UBTMu5YV/XMvc2VBcCHf9SFB64x8Zd9cY1gPX3PgL/HsPYVg+9z4J3bJT5FKy45bz7faz7ueOmy9wPXDHG99x8wXuZ4ND0v0vC9WgizREvuGBR4iW2ahXEXtp0+yjoam3X0lB7R42PPAIRd9agX9fui6A117jbz+HOTwdwGcRxKVI6+ne92TqvV9tfVjaPIm2umGtPXUW7VMVHp++5DKCWita2C5m7yyMDs3kQ5aiTVNuKcpmNQhIe11loVx4+2RUVepKryxY7fKSO/+HC8yM/juSkVeN5NLwRFS8K3pVW94reHzr9QszXs/ZeCiDI7KAN6vbOM9JGcsK1JIJH8nGEl6tbeJwoI0xVj37ZDEPCMGV/acy+h4nwjzClkVzXFYtYYCmTISwCVMaayVj/mdFKtDMXhDvur+cPXuuYcJHPsrdf36G3ss38nVVzLY1DXzcV0by7ThV7OAgOzCl5PaPZW7ovBDc1usXZDB6TZDS/SwxnXGPL+CNJzvf2CUb+6ESuePaKNuopZkOkhyUbRxdOYTnF+5m3mx4/h9wxRLBPwbDLdc8jsaj/HKtYs5MaG7TWHC+ZObwT7rENvI+H9uWpKPm7fvUfdBYtp6zqDu/BRaiSYeEfaYdyjrTvoCr0l+zQxHon/rnx+n3tyUqiSfSG9D/v703j2+qyv//n/cmTdONpYggUFqgQAFRQSqWrYxUcEZBUTYVHJGRkVFnRv19UNRRB51FxuGhDxdAAXUAB7/ggjgiO+ggmwOiAqWAgGWxpUIX2iZpcu/vj9ubfSukTQLn+XjwoE3eeb/PPUl67nmfc94v3R9Afs0YzDUunxuTPqFK6howo+ZNJO1i1delEjPSvkL6CWkhuCAkE2BwE6qvl/tTEhNxyGbGqTY+rIO7TAor7QkMM+WDusr5el2ysKE1uMNBP0ZmV9OQqdcCxLfuuIoBm5rkYaPjca6ab9hnL6EHrRqhtY2Hv4IupzakexwZc6do2i+QDMmk/GDgPiPsJJXrDHupcPRGLU31WEP1rqqlPyebFDJMaWxem8bgAVVIksS5agdKl2lc/8tbAbj+nvv4pvUK1nz4EomJBkooorLOQnFRAlOrB7OYb9jxvYNfZId3nR7vlbSH/WroM/D+aCOnkaBIFFPO/eTylrKTTasTGJxXpxUyGSjRZRpskJfRT3mUgvwi/jJbYczAVuRcWw646nq7H3OLJBmJ60hKtKMoNZp+exBb75roOh3w1HuXE5NR6m+IfHzOtSJn1pJy+hQV7bPgPIsLCQShiJNB21VTOaRlGHaR9BXKLvkNSOoMeglFXe7v63nLqG7bjL3THufyfcf5XNqHXNcDQ4LdOdADHLcOpa1ph0dqzylxCJ4yh+CSQ7SBolp85RHdOG4dSp3SDHObc1iOpLLPcYYcOY1i6zD9ygAotg5DllyFJdzT5z7CDoqEdzrfH9FLj3un/gMUdFHaBjwylrNwHdr6rYJilemtSCxZAFN+txe1bj9SgjaNVBVLva0v+uNpbhu0/rsVTEkpHnamlGQenl1KSrK+XqxSNeNGjLKRe+lH95x1OCzabFir0hV496nHeyX3I9T75N6vismIVGd3Zq3vpA+rKWIDP5BJS3p92YMXZq1h9OAW2OvboCKjkEhmVjJd9/SiYv8gqq/4N+asSgqnFWA5Vj9Ym7Xd/JIaufdcxUBtrVGTbK1figpEVcdOJB89HDJmMLu+f5gEQE1WF/bOeNFnw6k34czMwrWLVV+XSsym9hUXg/aVy1dhkCvC3KEXTgGE0Da63aoNDvYdS6dn5hluGmoNaBfuDkNd7u+blbs4/L8xdP/nMxRu/JAj31Xzj2e+R5J/8PDVC9/0eKR2K+q+JTmZOts5/nZjOuPWnsFo9J0leF/jvomeqVedWF3G0G16LFrjISsKgQu6BFPb0vu2cEoBliPNuRKw/EqrttZp5jaPAizB0DZoqQzsr1L0A9iyqj2et1XXOKvm+dsUJ5scGMyuHdThfjYa2v+l86bQ6s8fklC/xutxoyPvIe2hYTRr9yuO9LuBI/XjqWoystmwHIDkt+uo/KmCDW3ugzrAc/M+be6dR8LR0xF7z4utLpnP0rn3U5d1WUDbtNOnqGp9hc/j3hszzSWVWNpoNxpazXbXH1jFlAiyLFK9l2BMkR6PIWa+2YGe+XkMGNSaE0dO8/z8LfzpN6F3CYaiukbhWNI0+o3Q0qC5Y6byTVobqmumk5p6we4bxNFihXlPpmCqa84Yaw9emLjfZ0eyO4rVwI7ddra13YnSIsH5uKqqXFHUhV4En2E0Jt6ynE3dLsVts5bPc1YDUoKnnKP+WEF+In+ZXcuEkTKf/HMV207/TM9fjWTff1Zi+HQ7u1JkZx317E3Xs77lbsp7H0GSJAxLbUgGFVWBrl1g0oTA7XPvH8kgoTpUZ/+Ekg31PiLneaOTh2P2/+qf+cppc+q9h3C0bwmqSpt752EurQhrQI401/52PIny2YA5M32/iTfe+zf0Wuygpd9NcqVz6Wr7wk+o7uRfbEcgiCRxM2g39QH2zzYl0jM/j/adtB2i2v8D+XxTsc+M+3xiJiYl+/29qQ/zZ2XI5FxjgY97+9TC9uercMowTh9T6OvcQKWhn2V2EL1d/v5kORvWLvdd8u5pft8/93p/yCYHcqK2Zn3wd0O1J+vXrXWbnTshbc5QMp/Z4VHko2ia9liXrGpy9lxD9WfZDANsRYV8/tFWRpe1xCS3YvMaTUVsz6YU8hPSKLO0oP/IOoYMkHEes9qiYC0xebzn7m0DaK4m+e2f6ueu9LDTSexYjuWI512kfhxMMrnkNaUOZXxaVcdNZS0xya4/KQbJwuW/fY2EI6dRbAYcYQhQN8aSSLG1wEdf3B3vmuigSYuqXu+7e0y9SmFG4jpMUqXTVqR6L72YIj0egKY+DF94LJ0BgzxrMrfv1JotX7XkJn5i5y7tuI72910CVQEVru4FuX39pZc9Y1q97uz136NRjOCex+r4m14LW3LwxB8qwKt8p+7L3wYq97StIbnp0uP6MR+DWZsB+ZPl3L06jaHGZiRnW3wKbbjLWqJKzl3yR84Oqt/h77mL3l9/dJuzyUfoQ1eAkmQzdbZzvDQ9nSVr1/osO+hLJZKczNhF36FY96Gq2uuvczNNKVL5y2yVMcNMdPv/PsG2t46PP1Mp+sGBfnPxwxEYfbMNSU51vuc5C9c7N3yBdpRk/r9VBg/A2T+FRSr3f/qF3/71OOdsMiK5nVuWTVrW4J2VmRx2jKH70Nv4ZOOHZBs/5N6R+oaLj2CB9pMuLxrNgjqB8HfKothLTz6QP33w1s+Yi1TvpRfzok6P2+12nnrqKYqLi7Hb7UyfPp1+/UJXz3JYZepKXIUNgsYoDW0Xjk1Oh3JOHDntnGkDnDhymh4dKnBYDLRIUemWrTIkT0abkcls/kqhRYqEw+JaC9P/uLmTkizTyTKHnctL6D50NAc2fkR2wofOzUZNzbbtCpWdTjLzzTM8MzWdbTslBvT3b6vLFaYcs/PlV3ikbZsavehGXWmiM/VbedLAF1/hPGNt3JZFzoJ1Tp1pd3IWrMPU2cr+KTdSdyARfWYtSQo+I3E9is2Aw2Jwfob87X7uvmAdJYZy3nw6jUS0ZYfn7y7ElmDlt3/zXHZYNEfhnge1nzVVqeZOURKdupkj6PJzLfKBlnz3g4HUmasYMayG/AEuP5u2KKT7kTHXfeq0k8/yZTeXbGn7t4ezZ4H/2uN6OlgyOTj17u9J//NHJB49joRC9wXrUC6v8F3mWa0t80TrsywQXOw06aC9YsUKkpKSeO+99zh48CAzZsxg+fLlIV+3/+6bsJdUQThpiHoJxgu1aQssH/I93Neb9p0ucwlqfHELe+ptdhd8zuDrXbO6Xauakbbhl87nAecfYD1tqVhlVEXi7mHHsdhe5l+fLmXGLT9hNsk4ag1Yi80kZgS/oQjHpiF2V7dM5bo5FeBI4C9zqgAjDq8jMLqvwikFWOt3/e4u+Nwlf1m/Oaopi+A4pRnlOtJwpcbnvasyOA/+t0ehm6Ut8GPApYIv6v5N1Zwu9HtgLKZjVSgWmQ6mDfxovTFEzMCfId2mtXqIVmr9+e8fO6OO2O8xYH+6RMH8/+DT5tX86k7PO2zve4acc1fQ9bUPkUzaOe9578KQPNU1Yz6oMnSgweM6VStIqgPJrUxpByWNL+rT7aHKmBqsVSgkkTNnHWcz7+X0vHvJt99BGj+ACWosgZd5/BHtgjqBvvH67nt3NFlWFfelEX8xdTuDzYJiqSWx5CT2jE4hj3zFc3pWxIyuryYdtEeNGsUtt9wCQHp6OuXl5WG/Nhpps/Ff57Bt98F6QY0kHwWszhv68+XwtUFnm66ZmZZq9J6Z9QcOvOHWNrfNLgHbH4ZNpO382XjLX0L0do+3r3Glxgvy4S+zFRynkp1HtryXChSTEYdspvUDC0k72owSa29MplMkmR38WD6AOjV4Vbdw2nZDUg6f1XzvLDzzyETXDZSlSuLkW0buNCos/ZfK++9fS7cybUasS4Aee+E6Mp/Z7oz33S3j6TZvJUmdtWv8YqtK/gCJzV+p3DhU8rlOKRF6LFmvFS855rqe7C25vPCPDdz8PzumpCqfa3WQiIqMo3MmvZ56G1OWDVWSURLNKMYkNK1x7Y9LoGWe8+2zxvr8/GgdEdiufpf5+cTUd5g7TGYUcxLWTtlhTS5iOT0bz6nqaMS8qNPjCQmu3cbvvvuucwCPZXKr2pH7vf/n3GUuA0kc6rOucAbGDcq33Ejo5YJY4ULkL8NlZ9pJTmTW0v5YErlV7YLaum6iZNq0dnDFisEuPxV8MvQAACAASURBVDsU3FdiSudN4VSn6SjvmACZ6yaPJPFoFZBMx8R1Wv3vMM6bB2OfvYQSztEOI6XYnYVQdu5S+OgdI+171/GeJFGnqOxSdmOvNtKztiOg3ex1fWOj5shtR7piM6Aq+lExhcHXu2bZgchZuM65ti2bHFwjQ/rOBPr+0QIJ63yWbzbJyzhHF5rJp7DbV7Jd/jvnJK3M55fyYoYqY0jjsNsyTyndh94W9WUegeBSoNEG7WXLlrFs2TKPxx5++GEGDx7MkiVL2Lt3L3Pnzg3bX6zWHvc32zwfX7o85/aaBPrR44LbFWm7cOQvIx3z/X6FXHtfb67udBknjpSxfOF3jPnCt6C+7sv9Jqr6UHPnzYTdrvCP/zOzZG2NczNY28lz6bFoDVuzF1MlZTvHZ30nsbMuuw+qm13wu+JexpZU20poafqedNuVXH9VAlBLejqMGG8n322g3fRfB8sfP8XXShkj6Ap6Gl5H1q7xwJQC55KLnlG4a4zbETevZQA9za6tbTejx6I1mDtVcv3VCjXTwPwnMGR5hhqqjK3vDK2AzFBlLBtkrUxnfu1YUhMOo0ra/st7bjmGxTKbd1Ys4alRpzDLsibO4aeoT6j3vFApJcfSJqhNuL48bdT6NLZ/jNZyFDx3ybvOaAdPjzs/OKoKqopqsUKCyY+d16siaBervi6VmBH3FYJGG7THjh3L2LFjfR5ftmwZGzZs4I033vCYeYciVot2tFdaUrV5SMjZZnBpSztqQmG9POd+7HVdMcqB35qmrJ0erZg7005wbf1+AkD7f/KV7Nx9yGfG7e7L/SZKFwNJe6I5Y6zdXWfQ//Y5PevXlm9QRrFB/sT5tzlYvXYJBzmL1qL8pQpKkzG/WuMz4BXeV0DmM9tJyqqizm5mR4GNm4ya7KrNnkQS2ix56TsSQ9z0pXevTqOf0tGvNrp+jYBHn3XJkinIV+iS5ZrZei8D1DwI5schs9kajhiGU/M7sBvA2MmM8qPvdS5eDBMn+vcFUP2gJv+dPAcMmdpjScnJPDC+hOrfyZw7CKiQPB8ss7TYlhdB+TG0vOtH7OUJUzukCNeuz0hc3+Bz2goGii2eUrX+YmYkrsckV9L5dytBkrB1ysZ0JHQth0jaxaqvSyVmpH2xZXtQmyZNjxcXF7N06VIWL15MYmJiU4ZuVHrZO+Lg/ItGbJS3MMlYhy7PucixhRvJj1wDYxz96JaUoDhVm05kWri6k2cVq/adW7On03f0L/L8o27OsmrHuYAM0qjc2J8MUxqYIMOaxmWlbYOeQZexIplUSKyvEX8Av5lxraBGVZBCoVD10Bpe/xRatIAfD9TQ5iqVJUhkHXKw+BWFB1/X7Prsy+WLr7aRP1By6mRXUxFQGz0QebnBU9Epb7j+lydC8kytrK4kw7kH8JgNWywOlr1+GWPGlGE2+0+3SybPAds7VvXvQDkIX38H/b1iO0p8X+Mt77qsdhcW1c4IIifvWmwtcBZD8Yer9r7bayyBteW9fQOcWvBQUAleb2J5TTWe2x+NmJH2FeDgjssmZKQIsmzZMsrLy5k6darzsQULFmAyhU4txGp6PBIx0w1lpMkuec6WhjKCZPNirv2B7DYo33KDfJWPjWSyexTu6L5wHcdmXkfmMzs4NlPTTc44YfI9cvfDafrdeJhr5uzy8qilcXWucXvmKkXh77+4khIqA55BH6qMBedmQIuHFrVkc4DDcxexRVF4z9yM+2znSPHy1byZSm4fuV5fWmPzfxVaPidx/JDDGTvL1IIVqxMZnGdj/WoDtym9Wcw3Tt1tb8Lt/2AFdWSTw6Pwiz6gb9nuYP70K0hWE5lIVx4bfpBqycr9s35iYH/P60t+w1dd0D1myhtQ8YDC7H+ms+SXWklc/cSEv2s4Sy0ZeMm7Bsg2uNPQz6w+uPrFGsaJk5AxtdeLndCXXsyLevf4o48+yqOPPnper43nVG8omzOOy6hSfnLKc551XN5k7QrXrqG+9DX6r21G+sk9PWxyFqz3OTetFxrR/78GeH7+GUCrSnfiyGn2fbGFP/2mwidmsCIy23ZKVHY6yfPzLfzpN+agZ9B1XylvaL5UK2RNW8/RgwXYlDRAZcGfMvnxV2PI+eVt/HX9h3Q9oBUTOVqsMG9Ga0x2E6ndyhkyoMaZ+t67VuU2VcLuJZR75cZ8nk9eQ962EU4BkGD9CoR8D4L1hd63up1SWwMJMLC/gU8z7HQ73I0ucivO1dk4lL2PQXmpDSri4+yDOhNjbK6SuMNqc0g/1cyn8I6eEn+MwaznkEtlTQ2dbYi977l2kyZmjZdezIt69/iliF51S0/h6tW33PmFMpCV9k+4y+RgpT2BXygDvSeDcYXnGn0h9rpuGGWjsy/cq5IF45mpx1m1YSlbvmpJr8yz/Ok3oTdpeDOgv8SA/uVIcjJ/f6eccFTbdGoeAaUEOpg3ggoWYx2nJj1Fbr105nXjXMVEsjJkcvrY4OPupJ9I5u3uq1EUiTNnVRLOwpu9Vdr11naO6xXztN33A2lvSHcurwSqn97hWA9yrMHrg4fCu/55zSPamrMhE55/5zR/HVzOKaUSOwp/fvs00LD0tLMPPujusRzR7n8pHksK3inx99nDz9QylitZKx0+b8lQgeBSIG4G7Wines/XLmfBuvrqVloK1586llE2ItXl8Ln0PbKjR9BNaJFqV0PtGuIr0Bq9qy9AVULflaiKhZuGKtzETyHtwvEVDt6pXoB9E7WqYplvrSLxbOBiIpMeqeDvn5RTQhU/f2Pk5tsdDMlzJZM3f+VbtayntQMO2dW3AeunP3U1DiX0e+Defj0trVM4pYCsZ3aQlHUWpdhG8my0Xd7Au4tlihJPMffTUh645XLeXSwz5V4/fWYFNQGQXGqX7jHd+0Bfjii8R3vOYalz3pSkUksCMsXSWZorFpKKWtG+tkVYkqG6r0jYRM5OpMcv1ZgXdXr8QojX9Lh3cZVAKlD95J5ssNm5MfXqgL70P3iyUUZ11K9NBlFpilafpVv9r9HrfSGbHMhGM45aa6BqoYBn7Wt/6CViG7Neu3dmJFgxET0VP/PNMzx6byqbv6pi8PWuqmX7i1TyB/hu8HLv20D1028waUehGpIe12VD3XGvG9DBsJIW8yoxZMKUeyWm3PszYGDxpp8BycOXjBWDWkvNIyrSsfq17UzfmNt2Spw1nGTmW2f48/NaSdwWbtfpe1NSyab/qlQ8nuvTF8GIte+5SI9fujFFevwioyHFVfxt2nInmIpVLBFojV7vix6LVpOcbfepi+1NqD7zrtHdGBROGeasYJdsDl4zXk/Fg8xr79XwwUoD/92mMDhP4outrqplTt9uN2FltTVIreormZUn8tJrCi1bSMiyqlXaMze87bJJQTb7Pz5lzrKS/JTqdxe4P5xnt92q91ksCu+suILJoytIrJ+xD+gvMWCD1gf6csS+V12v8XdTsmG1ka6KLa6XhASCpiJuBu14TY9H0legWZi/SmyRink+vsJZow+nbGRDdkwHm7FrImyRkTOddPMxrNZ/8s6Kf/P0rScxmwOPNHeMlJn3rsLA/v5n2e43YYePKpw8BYPzZKAGMLD5K4WNHyRzjdLSt452gOtVam1I9QNo5QPryM0NcJ02I5LJHrTfdF+S5CtS+s7KTA7bx9B9xG08/x9vdS//6NfgXf43d9MvaC83fe36iNrVF1dx1NaByehaOwhAPKdnRczo+oqbQTt+02aR9RVOvfNIx2yoL2pU1xp9ne8a/f5JI8Krdx5mTEk2s/yubI41P+Wzgav/zZUM+pU1InKmek3wpM6VTLuzMuS6vCSbKcg/51O1TMf9JkwrS+pgkFs6fdMWFaXCzKY+m5EM2usVu0Lhb3v6XQ4BV3bCrij8g838H/kY/YhXhFtvXq91vlH+hH7KozTjENU1ynmpe+nvZ7Dyv7H4nQvH7oq7tQP4hmQTx+dPxd45+AmQWE7PxnOqOhoxRXo8RilUSsmRg38Rm4L2Sku+XNucQXkVQWfZ0WK/7Se6ke5co79BDl6S9UJRrAbqStJIq0sm18/SQbqa1Kjxvduiz1xVkxGL3JnMrEMMy6+h0xUJqIqvTKv7TVizVDxkRaXV3Sj486EGLYf8ZK9glbLfuTP7Q77HokS2WAk0TN3LH+GW/xUIBJ7EzSpSNNNm+nlSu6IEtYtkzGB03ngdL8wKrWHd1H1mVxQ+sO1x9lOwNfpIxSyaNpQjf76K1ic6sHtNM1TVtUFv9+o0OrXXcsWRSo+Dtiu7utCMqng+tn9yAXuG3c6eYbez5tB/+LLoFT6zbadX7xz2T/bV3QbtJmz3mmYoispP3zTnm/qfd69O45bavn6vKVjJ3Nb2ZDJoRg9a00VuRQ6tyaC5z4DdkP53T6HXZ4EbpO7lL2Z7pSWd/YjNxG163MMm9lKq0fB1qcRsal9xM2jrxSUiYReur9PGGv6l7OIDvnfOWv6l7KJEqWq0mOHYdTS18fsHrzFjBrMpUarC6qdIxtTJWbieHm9vwZxVqc1av9Ie9146kOTwdnKFY1c4pYCDD/7SYxB21xkHaDt5Hu2mLaTDL17g8LCrPZ7zputXg5w3YZ039Pe4IQt2Tf4wmBPIpzMnqGCNUsRxKsink187n+tSSn1s9k8ageWI1vaNhpXsuOdBioaPJ+OnBexc/iaVZafZufxNMmvnhFT38o7pLTYTqF3h+Dpfm8aJGUaKM4w0aLh2serrUonZ1L7iZtCOBm2NzcOatUQDf3/wokUbOS0m+sl91rp7dRpV9vBmUI2B9wAYjPakO2/CvGeg7tf0zdpmYcmg7qeUEs5xA50p5Rz7Cd2WUNkkAFm1IJvqQFK5c0AJT//yn1SvGcufbp4TchOaQCCIDHGzph2ttFk+nVlNkVZiEcWvoENTp+picfd7OP2ko9cerznQPOC59XDbBVpKWzY5kBPtZG/pxwuzNtB743W8x7eMtCtOm3B9BUPTs9bqaO/crTLwCkP961zXoQ+A2TWtkU0JGCQrCqaAt8gOSx09FddNmPcNmWv9N5SUgOarl9zWWVEsUGlUvW+9q5N5rIFbPLMD+cpY0uYfYv+k4QCYzTIPjC8h3Hv/S+Z7oq8hBMEe+N7Iyy720rMxEzNAHzsUO6iB9eXDtYmarxDEzaAdrV2le8+dooRzTOSagIIOTb2TNRZ3v+uzu18nX8e7NTsCCl+Aq/b43rsGBT+n3YDd43pd7RbFCiv/L41awzHGOa7iHzMOUJecyAN/qyazQ+iBO9juccnk4OCDQwFI7FbD315KJPm1G5y7s0uN5XxedxizZGCcehUfGb+l1lrHA/8sgbcGEGitM9R16vKvHU1tcNhtrnKweBZ/kUwOkrPtAcvl+ovZRk4jQ/Ev2GEwJ6DYa0FWNSU0VA5M8V2bD7UzXzYpIKkYzJE7MRDL3xN9J3kgTr33EGS3idndy/Gyk7tV3YcY1XIfO4OcELJ6YDg20fIFTwe1iZtBO1qEM2sRuPrJIBvrS1FGh6wMWZOr/LgNXeRW1JRmanKcHWWPjWPnQ86CdZQklGuiGNVmxklX8WmbHZpG919Pc02GTMk/0+Dj3nRRWlGrWJHGfktOXg3krbug2L3sHT3aoReVKbyvAMsxbRmi+4J1JHd2oCo1FN5XQE1Ri6ADt06wLEnOgnUkZVU5i6vkLDxM4X0FYdeP116zjn0Th1NX0jq0sUAgCErcrGlfFGmzGPQVrZjhpKvP19ekRyo4IZezzljICUM5d/+hImLp8cwOmihG5xNZdJFa0elEJ3r2tTk1ut1jHzec5e4/+KqSuUUD1PqYaoB/Gg5Lnd/+yFm4jmvWf8Q16z8iKavK2f6cheswZwWuFufuK9AaeKD+z1moDeTOqwizb8X3REeNjfRyI/tq7JiBXhVOijkcm1j1FTcz7YshbRaLvqIVM5xd2g3x5Z6eda8B/sxUrf71wLzIFVeZ9Eg5f19ZTonsq9HtEfu3lwWUAu25eI1bzGS/Md3FZSIhzemOe98GyiaFu6v6fGJeiE00fEU2phQT6eXG9tXYMQPlkAyyMYw0dGibaPkKRdwM2gJBuLjXAG+oHGc4aAPzKWbOK3PeFOgDs3vsF9+1eGxQEwgEggslbgbt+E2b1RfGUCy4Bo8L2zEdu2m/80lp+7vDloL48rXf8XU1e/aqnt2qwtW9cGpXn096fOcuhS1X7ERp4fqa7FxbRd9clb+/HfqmIDIpeRWQ3Poi+IzE15e7vaud4fiLZEEaz5gXZhMNX5GNKdLjkfAl0uMxTrTTZroik3dt6yuKutCLLgH99Vi0hqTOlc4UqD897aZo/4XaNUZ6vOfiNeybOJxOM7dx5Jnrnf+7p4S9fen96U56eiLdsy31Yhsa3trV51N7PD0drr39Z79+G1MOVEfvH8uR5s5UtV4LPBxf7il478+d3rf++tPly3/aPtz2eyPS4zoiPR4JXyI9LghKUFnM85BNFESO7M5G1m3GQ2wjkHZ1Q9BEPJSI+xUIBILzJW4G7WinzYLJYobjL1ZTiNGKGend4wX58N9takDt6vNN9br7ffs9BZsN5i9WgHP1L/BMw0cipj+8+2LnLoU9e/GzJFBNbt/Q6+iR/MzG6mc7dr8nIj0eCV8iPR7jxELaLJAsZjj+YjWFGK2Y4fRHQ3x1yaph3ebA2tXnm6rWZ9sD+6uUlMGg66SgafhIxPSH907u9HTono2ftiQCWp+5q455n9fW+1axGXBY/GcO7KWXYepQ4qNMplgNSAkuxbJY/WzH6vdEstpJOlaGpU3gevQ65pLKkHbh2ETDV2PHlGwK/oovGE/L2FsHL8oQjk20fJEbwk/ISAInwXSABdGnIJ+A2tWR8tsYafjzIVDqfuggI6pSvw9jyrCg+ycADkwpCPicu562O4VThtFp5raga+uCwLSdPC8sPXMgbN3zWPQVzZhyGDFD2UTLF7cH9yOKqzTQzluFKVx/sZpCjFbMxiiu0iVLpiBfoktWZFPV7n71dDngNw0fqZje+Cuu4q8t0ficxepn+2L4nog+i/2YTe0rbgbtWJHs86cDHI6/cKUhY1tyMHIxwy2u0lBfebnaR3rnzobHC2an++2SJbOvCBRFm9n6u0EIJ6Zi1dLSqqLZ6b/rj+k2elrbYE7QaoHbXHZZbRPYV1jflkLIapuA9cfWzudD1R4PhR5PVcBBIg6r0cevYjVg/bF1WCVim/pzdjF8T0SfxX7MpvYl0uPnQSzJYgp8sdsVXpqezpK1ZzAaI39fGok0vJ667rFoNcnZdo9Udo9Fq0nqXKk95iXO4Z3Obief5YWStfT5z3D2LGgZdgoxXA5MKaDHotVszV5Mym9Wk/CDp8xn4ZRh1JW0DnkUTSAQRIa4GbRjNZ0Rjp2qglJrQzJFJma8p5NAS6mGUC8M6Mv9dZLkSs8eLVY0MQ+7iTHWHrwwcb9TzCMr4/xT1d7xtDS5Spes4IN22GnjWt9B1rtvAvVFe6UlFW6Zn8Z8z1WvRum/hvP5P9+YF2J3MXxPRJ/Ffsym9hU3g3a87irdP2mEZhPuJooYa39j+FJsWkp1zoxETndcjzRfgo4bYD6oGetpUd6JYWf7+PWl9ye4ZqSSbMZRayWjtYGcq+pgZQ5dpFbUnOiMPPpbsjLkC9rJvX/ScOesWJ9NDuifEpHiKvsnjfD72dBj6gSrPe6e+WmM93z/pBHUvtecFLfCQnoddve2BUK/FkOy2D0e6zHjvf3RiBlpX6GIm0FbcPFwYEoBhmQTabaD9H3wKEMGuFLYm7YoHP4qwBmqIOjp5V6KwmqKOMU57IrCI6PCl5AUCASCWCemB209HWe8PBU1KQGpNoxScWHYhWMTabtY9RXNmLm1vdn8fTED81zHlr79Doa27h2WL9XYBoUUJMwYWrfAaEnjoHIaK0mMpicfsY9vfmhNXnYaEmZUQqer/dnpvvV4gezC8eXt0991qsY2Hs/rNkDUPmdmo0RC6xSMta41dr2dquTZNz5+6q9FfE9iP2a8tz8aMSPty2bTZuPey1E6khromRigqqqKoqKiaDdDIBAIBIImpVu3bqSlpfk8HtODtqIoVFdXk5CQ4CHUIRAIBALBxYiqqtTV1ZGSkoIs+55+ielBWyAQCAQCgYu4Ka4iEAgEAsGljhi0BQKBQCCIE8SgLRAIBAJBnCAGbYFAIBAI4gQxaEeQsrIycnNz2b59e7Sb0mTY7XYef/xx7rrrLsaNG8fXX38d7SY1CX/9618ZP348EyZM4Ntvv412c5qUWbNmMX78eO644w7WrFkT7eY0KRaLhWHDhvHhhx9GuylNzieffMKoUaO4/fbb2bx5c7Sb0yRUV1fz0EMPMWnSJCZMmMCXX34Z7SbFdnGVeGPWrFlkZGREuxlNyooVK0hKSuK9997j4MGDzJgxg+XLl0e7WY3Kjh07OHbsGO+//z6HDh1ixowZLFu2LNrNahK2bdvGwYMHef/99zl79iyjR49m+PDh0W5WkzFnzhxatGgR7WY0OWfPnuX111/ngw8+oKamhldffZX8/PxoN6vR+eijj+jUqROPPfYYJSUl/PrXv+bzzz+PapvEoB0htm7dSkpKCt26dYt2U5qUUaNGccsttwCQnp5OeXl5lFvU+GzdupWCAk1tKzs7m8rKSs6dO0dqamqUW9b45ObmctVVVwHQvHlzamtrcTgcGAyGKLes8Tl8+DCHDh1i6NCh0W5Kk7N161by8vJITU0lNTWV559/PtpNahJatmzJgQMHAKisrKRly5YhXtH4iPR4BLDZbLz++us88sgj0W5Kk5OQkEBiYiIA7777rnMAv5gpKyvz+PK2atWK06dPR7FFTYfBYCA5ORmAZcuWMWTIkEtiwAZ48cUXeeKJJ6LdjKhw/PhxVFXlj3/8I3fddRdbt26NdpOahJtvvpmTJ09y4403MnHiRB5//PFoN0nMtBvKsmXLfFKhQ4YMYezYsTRr1izAqy4O/F37ww8/zODBg1myZAl79+5l7ty5UWpd0+ErUalechX71q1bx/Lly1m4cGG0m9IkfPzxx1xzzTWX3PKXOyUlJbz22mucPHmSe+65h40bN170n/sVK1bQrl07FixYQGFhIU899RQffPBBVNskBu0GMnbsWMaOHevx2IQJE1AUhSVLlvDjjz/y7bff8sorr9C1a9cotbJx8HftoA3mGzZs4I033iAhIbS0XLzTpk0bysrKnL+XlpZy2WWXRbFFTcuXX37J3LlzmT9/vt/ayBcjmzZtori4mE2bNvHTTz9hMplo27YtAwYMiHbTmoRWrVrRp08fjEYjHTt2JCUlhTNnztCqVatoN61R2bVrF4MGDQIgJyeHkpIS7HY7RmP0hk4xaEeApUuXOn9+4oknGD169EU3YAeiuLiYpUuXsnjxYmea/GJn4MCBvPrqq0yYMIF9+/Zx+eWXXxLr2aCJ+MyaNYt33nnnktqQ9fLLLzt/fvXVV2nfvv0lM2ADDBo0iCeeeIL777+f8vJyampqYmJ9t7HJzMxkz549jBgxghMnTpCSkhLVARvEoC24QJYtW0Z5eTlTp051PrZgwQJMJlMUW9W49O3bl169ejFhwgQkSeLZZ5+NdpOajM8++4yzZ8/yxz/+0fnYiy++SLt27aLYKkFj06ZNG0aMGMGvf/1ramtrefrpp/2KWVxsjB8/nieffJKJEydit9t57rnnot0kIRgiEAgEAkG8cPHfKgkEAoFAcJEgBm2BQCAQCOIEMWgLBAKBQBAniEFbIBAIBII4QQzaAoFAIBDECeLIl0AQwxw/fpybbrqJPn36eDz+5JNP0qNHjwb7W7FiBbfeemukmueksrKSl156id27d2M2m1FVlcmTJ3PzzTdHPJZAcCkjBm2BIMZJT09n0aJFF+ynpKSEpUuXNsqgPXXqVG666SZmzpwJwMmTJ7n//vtp0aIFAwcOjHg8geBSRQzaAkGcUlFRwbPPPsvZs2ex2WzcddddjBw5krKyMqZPn47dbufcuXPcc8893HbbbTz22GMUFRUxffp07rjjDl5++WX+/e9/A1olv2uvvZa8vDymTZtGt27d6Nq1Kw888ACzZ89m165dSJLElVdeyfTp0z1qTm/btg2Hw8G9997rfKxdu3Y8+uijzJ07l4EDBzJp0iTy8vLYvXs3R48e5eGHH2bUqFEBr0EgEPhHDNoCQZzy8ssvM3jwYO644w5qamq49dZbGThwIKWlpdx9990MGzaM0tJSRo4cyW233cbDDz/Myy+/zKxZs9i+fXtAv4cPH+aVV16hc+fOrFq1ipKSEhYvXgzAgw8+yMaNG7nhhhuc9kVFRU65Tnf69OnDk08+6fy9pqaGt956ix07dvDCCy8watSogNeQnp4ewZ4SCC4exKAtEMQ4Z86cYdKkSR6PvfLKK2zfvp3vvvuOjz/+GACj0cjx48dp164d8+fPZ/78+RgMhgZrnDdv3pzOnTsDsH37dr755htn/KqqKo4fP+5hL8syiqL49WWz2Zw/X3fddYA2C6+oqHD693cNYtAWCPwjBm2BIMYJtKZtMpl49tln6d27t8fjTz/9NJmZmcyePZvq6mr69u3r81pvScW6ujrnz+5KbSaTiXHjxjFlypSA7evevbtfucLvvvvOo23uQgt69eRA1yAQCPwjjnwJBHHKtddey6pVqwCwWCw899xz2O12ysrK6NixIwCffvopsixjs9mQZRmr1QpAamoqJSUlqKpKbW0te/bsCRhj7dq12O12AF577TWOHj3qYZObm0tqaipvvvmm87HS0lJmz57NH/7wh/O6BoFA4B8xaAsEccpDDz3EsWPHuPPOO7n77rvp2bMnRqORiRMnMnfuXCZPnkxKSgp5eXk89thjZGdnU15ezuTJk8nJyaF79+6MHj2axx9/3OdImc7w4cPp06cPEyZMYNy4cfz8889kZGT42M2dO5cTKb7eXQAAAHNJREFUJ04wcuRIxo0bx+9//3vn5rbzuQaBQOAfofIlEAgEAkGcIGbaAoFAIBDECWLQFggEAoEgThCDtkAgEAgEcYIYtAUCgUAgiBPEoC0QCAQCQZwgBm2BQCAQCOIEMWgLBAKBQBAniEFbIBAIBII44f8HPvkyeNdBu2YAAAAASUVORK5CYII=\n"},"metadata":{}}]},{"cell_type":"markdown","source":"# **Do you see the difference in boundries of models (normal and tuned)**","metadata":{}},{"cell_type":"code","source":"plot_model(tuned_rf, plot = 'boundary')","metadata":{},"execution_count":22,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{}}]},{"cell_type":"markdown","source":"# 3. Oversampling to balance the classes","metadata":{}},{"cell_type":"code","source":"from imblearn.over_sampling import *\nadasyn1 = ADASYN(sampling_strategy='minority')","metadata":{},"execution_count":23,"outputs":[]},{"cell_type":"markdown","source":"# **Here i have worked and tweaked some of the functions of the pipeline and try to balance the imbalance classes**","metadata":{}},{"cell_type":"code","source":"Session_2 = setup(df1, target = 'quality', session_id=177, log_experiment=False, \n experiment_name='wine_q2', normalize=True, normalize_method='zscore', \n transformation=True, transformation_method = 'quantile', fix_imbalance=True,\n fix_imbalance_method= adasyn1)","metadata":{},"execution_count":24,"outputs":[{"output_type":"stream","text":"Setup Succesfully Completed!\n","name":"stdout"},{"output_type":"display_data","data":{"text/plain":"","text/html":"
Description
Value
\n
\n
0
\n
session_id
\n
177
\n
\n
\n
1
\n
Target Type
\n
Multiclass
\n
\n
\n
2
\n
Label Encoded
\n
None
\n
\n
\n
3
\n
Original Data
\n
(1599, 12)
\n
\n
\n
4
\n
Missing Values
\n
False
\n
\n
\n
5
\n
Numeric Features
\n
11
\n
\n
\n
6
\n
Categorical Features
\n
0
\n
\n
\n
7
\n
Ordinal Features
\n
False
\n
\n
\n
8
\n
High Cardinality Features
\n
False
\n
\n
\n
9
\n
High Cardinality Method
\n
None
\n
\n
\n
10
\n
Sampled Data
\n
(1599, 12)
\n
\n
\n
11
\n
Transformed Train Set
\n
(1119, 11)
\n
\n
\n
12
\n
Transformed Test Set
\n
(480, 11)
\n
\n
\n
13
\n
Numeric Imputer
\n
mean
\n
\n
\n
14
\n
Categorical Imputer
\n
constant
\n
\n
\n
15
\n
Normalize
\n
True
\n
\n
\n
16
\n
Normalize Method
\n
zscore
\n
\n
\n
17
\n
Transformation
\n
True
\n
\n
\n
18
\n
Transformation Method
\n
quantile
\n
\n
\n
19
\n
PCA
\n
False
\n
\n
\n
20
\n
PCA Method
\n
None
\n
\n
\n
21
\n
PCA Components
\n
None
\n
\n
\n
22
\n
Ignore Low Variance
\n
False
\n
\n
\n
23
\n
Combine Rare Levels
\n
False
\n
\n
\n
24
\n
Rare Level Threshold
\n
None
\n
\n
\n
25
\n
Numeric Binning
\n
False
\n
\n
\n
26
\n
Remove Outliers
\n
False
\n
\n
\n
27
\n
Outliers Threshold
\n
None
\n
\n
\n
28
\n
Remove Multicollinearity
\n
False
\n
\n
\n
29
\n
Multicollinearity Threshold
\n
None
\n
\n
\n
30
\n
Clustering
\n
False
\n
\n
\n
31
\n
Clustering Iteration
\n
None
\n
\n
\n
32
\n
Polynomial Features
\n
False
\n
\n
\n
33
\n
Polynomial Degree
\n
None
\n
\n
\n
34
\n
Trignometry Features
\n
False
\n
\n
\n
35
\n
Polynomial Threshold
\n
None
\n
\n
\n
36
\n
Group Features
\n
False
\n
\n
\n
37
\n
Feature Selection
\n
False
\n
\n
\n
38
\n
Features Selection Threshold
\n
None
\n
\n
\n
39
\n
Feature Interaction
\n
False
\n
\n
\n
40
\n
Feature Ratio
\n
False
\n
\n
\n
41
\n
Interaction Threshold
\n
None
\n
\n
\n
42
\n
Fix Imbalance
\n
True
\n
\n
\n
43
\n
Fix Imbalance Method
\n
ADASYN
\n
\n
"},"metadata":{}}]},{"cell_type":"markdown","source":"**You can several of the func are now shahed green because i will be envolving them in pipeline**","metadata":{}},{"cell_type":"code","source":"best_model1 = compare_models(blacklist=['catboost'])","metadata":{},"execution_count":25,"outputs":[{"output_type":"display_data","data":{"text/plain":"","text/html":"
"},"metadata":{}}]},{"cell_type":"markdown","source":"# **This function creates a Soft Voting(Majority Rule classifier) for the selected estimators in the model**","metadata":{}},{"cell_type":"code","source":"blend_soft = blend_models(estimator_list = [tuned_lgbm1, tuned_xgboost1, tuned_gbc1, tuned_et1], method = 'soft')","metadata":{},"execution_count":34,"outputs":[{"output_type":"display_data","data":{"text/plain":"","text/html":"
Accuracy
AUC
Recall
Prec.
F1
Kappa
MCC
\n
\n
0
\n
0.6339
\n
0.0000
\n
0.3152
\n
0.6126
\n
0.6221
\n
0.4190
\n
0.4206
\n
\n
\n
1
\n
0.7232
\n
0.0000
\n
0.5067
\n
0.7014
\n
0.7043
\n
0.5562
\n
0.5628
\n
\n
\n
2
\n
0.6786
\n
0.0000
\n
0.3183
\n
0.6504
\n
0.6625
\n
0.4807
\n
0.4831
\n
\n
\n
3
\n
0.6250
\n
0.0000
\n
0.3200
\n
0.6184
\n
0.6176
\n
0.4013
\n
0.4042
\n
\n
\n
4
\n
0.5804
\n
0.0000
\n
0.2586
\n
0.5422
\n
0.5552
\n
0.3169
\n
0.3211
\n
\n
\n
5
\n
0.6339
\n
0.0000
\n
0.3131
\n
0.6032
\n
0.6122
\n
0.4051
\n
0.4108
\n
\n
\n
6
\n
0.6250
\n
0.0000
\n
0.2875
\n
0.6130
\n
0.6059
\n
0.3921
\n
0.4020
\n
\n
\n
7
\n
0.7143
\n
0.0000
\n
0.4327
\n
0.6888
\n
0.6983
\n
0.5392
\n
0.5433
\n
\n
\n
8
\n
0.6429
\n
0.0000
\n
0.3153
\n
0.6226
\n
0.6297
\n
0.4232
\n
0.4261
\n
\n
\n
9
\n
0.6667
\n
0.0000
\n
0.3424
\n
0.6361
\n
0.6508
\n
0.4637
\n
0.4648
\n
\n
\n
Mean
\n
0.6524
\n
0.0000
\n
0.3410
\n
0.6289
\n
0.6359
\n
0.4397
\n
0.4439
\n
\n
\n
SD
\n
0.0415
\n
0.0000
\n
0.0697
\n
0.0427
\n
0.0425
\n
0.0682
\n
0.0681
\n
\n
"},"metadata":{}}]},{"cell_type":"markdown","source":"**Check the ROC Curves w.r.t to default setup and check improvements**","metadata":{}},{"cell_type":"code","source":"plot_model(blend_soft)","metadata":{},"execution_count":35,"outputs":[{"output_type":"display_data","data":{"text/plain":"
"},"metadata":{}}]},{"cell_type":"markdown","source":"# **Now Comparing best tuned model with blended model**","metadata":{}},{"cell_type":"code","source":"plot_model(lgbm_1, plot = 'confusion_matrix')","metadata":{},"execution_count":37,"outputs":[{"output_type":"display_data","data":{"text/plain":"