diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md new file mode 100644 index 0000000..b690921 --- /dev/null +++ b/CODE_OF_CONDUCT.md @@ -0,0 +1,76 @@ +# Contributor Covenant Code of Conduct + +## Our Pledge + +In the interest of fostering an open and welcoming environment, we as +contributors and maintainers pledge to making participation in our project and +our community a harassment-free experience for everyone, regardless of age, body +size, disability, ethnicity, sex characteristics, gender identity and expression, +level of experience, education, socio-economic status, nationality, personal +appearance, race, religion, or sexual identity and orientation. + +## Our Standards + +Examples of behavior that contributes to creating a positive environment +include: + +* Using welcoming and inclusive language +* Being respectful of differing viewpoints and experiences +* Gracefully accepting constructive criticism +* Focusing on what is best for the community +* Showing empathy towards other community members + +Examples of unacceptable behavior by participants include: + +* The use of sexualized language or imagery and unwelcome sexual attention or + advances +* Trolling, insulting/derogatory comments, and personal or political attacks +* Public or private harassment +* Publishing others' private information, such as a physical or electronic + address, without explicit permission +* Other conduct which could reasonably be considered inappropriate in a + professional setting + +## Our Responsibilities + +Project maintainers are responsible for clarifying the standards of acceptable +behavior and are expected to take appropriate and fair corrective action in +response to any instances of unacceptable behavior. + +Project maintainers have the right and responsibility to remove, edit, or +reject comments, commits, code, wiki edits, issues, and other contributions +that are not aligned to this Code of Conduct, or to ban temporarily or +permanently any contributor for other behaviors that they deem inappropriate, +threatening, offensive, or harmful. + +## Scope + +This Code of Conduct applies both within project spaces and in public spaces +when an individual is representing the project or its community. Examples of +representing a project or community include using an official project e-mail +address, posting via an official social media account, or acting as an appointed +representative at an online or offline event. Representation of a project may be +further defined and clarified by project maintainers. + +## Enforcement + +Instances of abusive, harassing, or otherwise unacceptable behavior may be +reported by contacting the project team at j.m.hoch@uu.nl. All +complaints will be reviewed and investigated and will result in a response that +is deemed necessary and appropriate to the circumstances. The project team is +obligated to maintain confidentiality with regard to the reporter of an incident. +Further details of specific enforcement policies may be posted separately. + +Project maintainers who do not follow or enforce the Code of Conduct in good +faith may face temporary or permanent repercussions as determined by other +members of the project's leadership. + +## Attribution + +This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4, +available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html + +[homepage]: https://www.contributor-covenant.org + +For answers to common questions about this code of conduct, see +https://www.contributor-covenant.org/faq diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md new file mode 100644 index 0000000..7d221b0 --- /dev/null +++ b/CONTRIBUTING.md @@ -0,0 +1,38 @@ +# How to contribute + +This python-package is a first outcome of an interdisciplinary project aimed at understanding the complex interplay between conflict and climate and environment. +As such, the presented code and functionalities can only be seen as a first step towards a fully-fledged model. +We therefore strongly encourage other users to contribute to this project! + +## General notes + +When contributing to this repository, please first discuss the change you wish to make via issue, email, or any other method with the owners of this repository before making a change. + +Please note we have a code of conduct, please follow it in all your interactions with the project, the project owners, and users of the project. + +## Getting Started + +* Make sure you have a GitHub account. +* Fork the repository on GitHub. + +## Making Changes + +* Create a topic branch from where you want to base your work. + * This is usually the dev branch. + * Only target release branches if you are certain your fix must be on that + branch. + * To quickly create a topic branch based on master, run `git checkout -b + fix/dev/my_contribution master`. Please avoid working directly on the + `dev` (or `master`) branch. +* Make commits of logical and atomic units. Write a [good commit message][commit]! +* Make sure you have added the necessary tests for your changes. + +## Submitting Changes + +* Push your changes to a topic branch in your fork of the repository. +* Submit a pull request to the repository. +* The core team looks at pull requests as soon as possible, but no maximum waiting time can be given here. +* After feedback has been given we expect responses within two weeks. After two + weeks we may close the pull request if it isn't showing any activity. + +[commit]: http://tbaggery.com/2008/04/19/a-note-about-git-commit-messages.html \ No newline at end of file diff --git a/README.rst b/README.rst index 3bd19c0..c50bbf0 100644 --- a/README.rst +++ b/README.rst @@ -2,21 +2,25 @@ Overview =============== -The conflict_model +CoPro ---------------- -(Machine learning) model for mapping environmental drivers of conflict risk. -.. image:: https://travis-ci.com/JannisHoch/conflict_model.svg?token=BnX1oxxHRbyd1dPyXAp2&branch=dev +Welcome to CoPro, a machine-learning tool for conflict risk projections based on climate, environmental, and societal drivers. + +.. image:: https://travis-ci.com/JannisHoch/conflict_model.svg?branch=dev :target: https://travis-ci.com/JannisHoch/conflict_model .. image:: https://img.shields.io/badge/License-MIT-blue.svg - :target: https://github.com/JannisHoch/conflict_model/blob/dev/LICENSE + :target: https://github.com/JannisHoch/copro/blob/dev/LICENSE + +.. image:: https://readthedocs.org/projects/copro/badge/?version=latest + :target: https://copro.readthedocs.io/en/latest/?badge=latest -.. image:: https://readthedocs.org/projects/conflict-model/badge/?version=dev - :target: https://conflict-model.readthedocs.io/en/dev/?badge=dev +.. image:: https://img.shields.io/github/v/release/JannisHoch/copro + :target: https://github.com/JannisHoch/copro/releases/tag/v0.0.5-pre -.. image:: https://img.shields.io/github/v/release/JannisHoch/conflict_model - :target: https://github.com/JannisHoch/conflict_model/releases/tag/v0.0.3 +.. image:: https://zenodo.org/badge/254407279.svg + :target: https://zenodo.org/badge/latestdoi/254407279 .. image:: https://badges.frapsoft.com/os/v2/open-source.svg?v=103 :target: https://github.com/ellerbrock/open-source-badges/ @@ -24,32 +28,37 @@ The conflict_model Installation ---------------- -To install the conflict model, first clone the code from GitHub. It is advised to create an individual python environment first. +To install copro, first clone the code from GitHub. It is advised to create an individual python environment first. You can then install the model package into this environment. .. code-block:: console - $ git clone https://github.com/JannisHoch/conflict_model.git - $ cd path/to/conflict_model + $ git clone https://github.com/JannisHoch/copro.git + $ cd path/to/copro $ conda env create -f environment.yml - $ conda activate conflict_model + $ conda activate copro $ python setup.py develop Execution ---------------- +To be able to run the model, the conda environment has to be activated first. + +.. code-block:: console + + $ conda activate copro + Example notebook ^^^^^^^^^^^^^^^^^^ -To run the example jupyter notebook, follow these instructions +There are jupyter notebooks available to guide you through the model application process. +They can all be run and converted to htmls by executing the provided shell-script. .. code-block:: console - $ cd path/to/conflict_model/example + $ cd path/to/copro/example $ sh run.sh -This automatically executes the notebook and converts it to a html-file, also stored in the example folder. - It is of course also possible to execute the notebook cell by cell using jupyter notebook. Runner script @@ -60,11 +69,21 @@ All data and settings are retrieved from the settings-file which needs to be pro .. code-block:: console - $ cd path/to/conflict_model/scripts - $ python runner.py path/to/conflict_model/data/run_setting.cfg + $ cd path/to/copro/scripts + $ python runner.py ../example/example_settings.cfg By default, output is stored to the output directory specified in the settings-file. +Documentation +--------------- + +Model documentation including model API can be found at http://copro.rtfd.io/ + +Code of conduct and Contributing +--------------------------------- + +Please find the relevant information on our Code of Conduct and how to contribute to this package in the relevant files. + Authors ---------------- @@ -72,4 +91,4 @@ Authors * Sophie de Bruin (Utrecht University, PBL) * Niko Wanders (Utrecht University) -Corrosponding author: Jannis M. Hoch (j.m.hoch@uu.nl) \ No newline at end of file +Corrosponding author: Jannis M. Hoch (j.m.hoch@uu.nl) diff --git a/conflict_model/plots.py b/conflict_model/plots.py index 604dc72..445e88f 100644 --- a/conflict_model/plots.py +++ b/conflict_model/plots.py @@ -1,10 +1,12 @@ import matplotlib.pyplot as plt import geopandas as gpd import seaborn as sbs +import numpy as np import os, sys +from sklearn import metrics from conflict_model import evaluation -def plot_active_polys(conflict_gdf, extent_gdf, polygon_gdf, config, out_dir, **kwargs): +def plot_active_polys(conflict_gdf, polygon_gdf, config, out_dir, **kwargs): """Creates a (1,2)-subplot showing a) selected conflicts and all polygons, and b) selected conflicts and selected polygons. Args: @@ -15,18 +17,16 @@ def plot_active_polys(conflict_gdf, extent_gdf, polygon_gdf, config, out_dir, ** out_dir (str): path to output folder """ - fig, (ax1, ax2) = plt.subplots(1, 2, **kwargs) + fig, ax = plt.subplots(1, 1, **kwargs) fig.suptitle('conflict distribution; # conflicts {}; threshold casualties {}; type of violence {}'.format(len(conflict_gdf), config.get('conflict', 'min_nr_casualties'), config.get('conflict', 'type_of_violence'))) - conflict_gdf.plot(ax=ax1, c='r', column='best', cmap='magma', vmin=int(config.get('conflict', 'min_nr_casualties')), vmax=conflict_gdf.best.mean(), legend=True, legend_kwds={'label': "# casualties",}) - extent_gdf.boundary.plot(ax=ax1) - ax1.set_title('with all polygons') - - conflict_gdf.plot(ax=ax2, c='r', column='best', cmap='magma', vmin=int(config.get('conflict', 'min_nr_casualties')), vmax=conflict_gdf.best.mean(), legend=True, legend_kwds={'label': "# casualties",}) - polygon_gdf.boundary.plot(ax=ax2) - ax2.set_title('with active polygons only') + conflict_gdf.plot(ax=ax, c='r', column='best', cmap='magma', + vmin=int(config.get('conflict', 'min_nr_casualties')), vmax=conflict_gdf.best.mean(), + legend=True, + legend_kwds={'label': "# casualties",}) + polygon_gdf.boundary.plot(ax=ax) - plt.savefig(os.path.join(out_dir, 'conflict_and_casualties_distribution.png'), dpi=300) + plt.savefig(os.path.join(out_dir, 'selected_conflicts_and_polygons.png'), dpi=300) return @@ -38,26 +38,18 @@ def plot_metrics_distribution(out_dict, out_dir, **kwargs): out_dir (str): path to output folder. """ - fig, axes = plt.subplots(3, 3, **kwargs) - sbs.distplot(out_dict['Accuracy'], ax=axes[0,0], color="k") - axes[0,0].set_title('Accuracy') - sbs.distplot(out_dict['Precision'], ax=axes[0,1], color="r") - axes[0,1].set_title('Precision') - sbs.distplot(out_dict['Recall'], ax=axes[0,2], color="b") - axes[0,2].set_title('Recall') - sbs.distplot(out_dict['F1 score'], ax=axes[1,0], color="g") - axes[1,0].set_title('F1 score') - sbs.distplot(out_dict['Cohen-Kappa score'], ax=axes[1,1], color="c") - axes[1,1].set_title('Cohen-Kappa score') - sbs.distplot(out_dict['Brier loss score'], ax=axes[1,2], color="y") - axes[1,2].set_title('Brier loss score') - sbs.distplot(out_dict['ROC AUC score'], ax=axes[2,0], color="k") - axes[2,0].set_title('ROC AUC score') - plt.savefig(os.path.join(out_dir, 'distribution_output_evaluation_criteria.png'), dpi=300) + fig, ax = plt.subplots(1, 1, **kwargs) + + sbs.distplot(out_dict['Accuracy'], ax=ax, color="k", label='Accuracy') + sbs.distplot(out_dict['Precision'], ax=ax, color="r", label='Precision') + sbs.distplot(out_dict['Recall'], ax=ax, color="b", label='Recall') + plt.legend() + + plt.savefig(os.path.join(out_dir, 'metrics_distribution.png'), dpi=300) return -def plot_nr_and_dist_pred(df, gdf, polygon_gdf, out_dir, suffix='', **kwargs): +def plot_nr_and_dist_pred(df, gdf, polygon_gdf, out_dir, **kwargs): """Plots the number of number of predictions made per unique polygon, and the overall value distribution. Args: @@ -69,16 +61,18 @@ def plot_nr_and_dist_pred(df, gdf, polygon_gdf, out_dir, suffix='', **kwargs): """ fig, (ax1, ax2) = plt.subplots(1, 2, **kwargs) + gdf.plot(ax=ax1, column='ID_count', legend=True, cmap='cool') polygon_gdf.boundary.plot(ax=ax1, color='0.5') ax1.set_title('number of predictions made per polygon') sbs.distplot(df.ID_count.values, ax=ax2) ax2.set_title('distribution of predictions') - plt.savefig(os.path.join(out_dir, 'analyis_predictions' + str(suffix) + '.png'), dpi=300) + + plt.savefig(os.path.join(out_dir, 'analyis_predictions.png'), dpi=300) return -def plot_frac_and_nr_conf(gdf, polygon_gdf, out_dir, suffix=''): +def plot_predictiveness(gdf, polygon_gdf, out_dir): """Creates (1,3)-subplot showing per polygon the chance of correct prediction, the number of conflicts, and the chance of correct conflict prediction. Args: @@ -98,41 +92,11 @@ def plot_frac_and_nr_conf(gdf, polygon_gdf, out_dir, suffix=''): gdf.plot(ax=ax3, column='chance_correct_confl_pred', legend=True, cmap='Blues', legend_kwds={'label': "chance correct conflict prediction", 'orientation': "horizontal"}) polygon_gdf.boundary.plot(ax=ax3, color='0.5') - plt.savefig(os.path.join(out_dir, 'output_evaluation_{}.png'.format(suffix)), dpi=300) - - return -def plot_frac_pred(gdf, gdf_confl, out_dir): - """Plots the distrubtion of correct predictions for all polygons and only those polygons where conflict was actually observed. - - Args: - gdf (geo-dataframe): containing model evaluation per unique polygon. - gdf_confl (geo-dataframe): containing model evaluation per unique polygon where conflict was actually observed. - out_dir (str): path to output folder - """ - - fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(20, 10)) - sbs.distplot(gdf.chance_correct_pred, ax=ax1) - sbs.distplot(gdf_confl.chance_correct_pred, ax=ax2) - plt.savefig(os.path.join(out_dir, 'distribution_chance_correct_pred.png'), dpi=300) + plt.savefig(os.path.join(out_dir, 'model_predictivness.png'), dpi=300) return -def plot_scatterdata(df, out_dir): - """Scatterplot of 'ID_count' (number of predictions made per polygon), 'nr_test_confl' (number of conflicts in test-sample), and 'chance_correct_pred' - (fraction of correct predictions made). - - Args: - df (dataframe): dataframe with data per polygon. - out_dir (str): path to output folder - """ - - fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(20, 10)) - sbs.scatterplot(data=df, x='ID_count', y='chance_correct_pred', ax=ax1) - sbs.scatterplot(data=df, x='ID_count', y='nr_test_confl', ax=ax2) - sbs.scatterplot(data=df, x='nr_test_confl', y='chance_correct_pred', ax=ax3) - plt.savefig(os.path.join(out_dir, 'scatterplot_analysis_all_data.png'), dpi=300) - def plot_correlation_matrix(df, out_dir): """Plots the correlation matrix of a dataframe. @@ -170,5 +134,101 @@ def plot_categories(gdf, out_dir, category='sub', mode='median'): fig, ax = plt.subplots(1, 1, figsize=(20, 10)) gdf.plot(column='category', categorical=True, legend=True, ax=ax, cmap='copper') + plt.savefig(os.path.join(out_dir, 'polygon_categorization.png'), dpi=300) + +def plot_ROC_curve_n_times(ax, clf, X_test, y_test, tprs, aucs, mean_fpr, **kwargs): + """Plots the ROC-curve per model simulation to a pre-initiated matplotlib-instance. + + Args: + ax (axis): axis of pre-initaited matplotlib-instance + clf (classifier): sklearn-classifier used in the simulation. + X_test (array): array containing test-sample variable values. + y_test (list): list containing test-sample conflict data. + tprs (list): list with false positive rates. + aucs (list): list with area-under-curve values. + mean_fpr (array): array with mean false positive rate. + + Returns: + list: lists with true positive rates and area-under-curve values per plot. + """ + + print(len(X_test), len(y_test)) + viz = metrics.plot_roc_curve(clf, X_test, y_test, ax=ax, + alpha=0.15, color='b', lw=1, label=None, **kwargs) + + interp_tpr = np.interp(mean_fpr, viz.fpr, viz.tpr) + interp_tpr[0] = 0.0 + tprs.append(interp_tpr) + aucs.append(viz.roc_auc) + + return tprs, aucs + +def plot_ROC_curve_n_mean(ax, tprs, aucs, mean_fpr, **kwargs): + """Plots the mean ROC-curve to a pre-initiated matplotlib-instance. + + Args: + ax (axis): axis of pre-initaited matplotlib-instance + tprs (list): list with false positive rates. + aucs (list): list with area-under-curve values. + mean_fpr (array): array with mean false positive rate. + """ + + mean_tpr = np.mean(tprs, axis=0) + mean_tpr[-1] = 1.0 + mean_auc = metrics.auc(mean_fpr, mean_tpr) + std_auc = np.std(aucs) + ax.plot(mean_fpr, mean_tpr, color='r', + label=r'Mean ROC (AUC = %0.2f $\pm$ %0.2f)' % (mean_auc, std_auc), + lw=2, alpha=.8, **kwargs) + + std_tpr = np.std(tprs, axis=0) + tprs_upper = np.minimum(mean_tpr + std_tpr, 1) + tprs_lower = np.maximum(mean_tpr - std_tpr, 0) + ax.fill_between(mean_fpr, tprs_lower, tprs_upper, color='grey', alpha=.2, label=None, **kwargs) + + ax.set(xlim=[-0.05, 1.05], ylim=[-0.05, 1.05], **kwargs) + + ax.legend(loc="lower right") + + return + +def plot_kFold_polygon_analysis(y_df, global_df, out_dir, **kwargs): + """Determines the mean and standard deviation of correct chance of prediction (CCP) per polygon. + + Args: + y_df (dataframe): output dataframe containing results of all simulations. + global_df (dataframe): global look-up dataframe to associate unique identifier with geometry. + out_dir (str): path to output folder. + """ + + gdf = evaluation.calc_kFold_polygon_analysis(y_df, global_df, out_dir) + + fig, (ax1, ax2) = plt.subplots(1, 2, **kwargs) + gdf.plot(column='mean_CCP', ax=ax1, legend=True) + ax1.set_title('MEAN') + gdf.plot(column='std_CCP', ax=ax2, legend=True) + ax2.set_title('STD') + + plt.savefig(os.path.join(out_dir, 'mean_and_std_CCP.png'), dpi=300) + + return + +def plot_confusion_matrix(clf, out_X_df, out_y_df, out_dir): + """Plots the confusion matrix based on all data points. + + Args: + clf (classifier): classifier used. + out_X_df (dataframe): dataframe with all observations. + out_y_df (dataframe): dataframe with all predictions. + out_dir (str): path to output folder. + """ + + fig, ax = plt.subplots(1, 1, figsize=(20, 10)) + + metrics.plot_confusion_matrix(clf, out_X_df.to_numpy(), out_y_df.y_test.to_list(), ax=ax) + + plt.savefig(os.path.join(out_dir, 'confusion_matrix.png'), dpi=300) + + return diff --git a/conflict_model/__init__.py b/copro/__init__.py similarity index 94% rename from conflict_model/__init__.py rename to copro/__init__.py index ab1c6c3..b7213a7 100644 --- a/conflict_model/__init__.py +++ b/copro/__init__.py @@ -13,4 +13,4 @@ __author__ = """Jannis M. Hoch, Niko Wanders, Sophie de Bruin""" __email__ = 'j.m.hoch@uu.nl' -__version__ = '0.0.4' +__version__ = '0.0.5' diff --git a/conflict_model/conflict.py b/copro/conflict.py similarity index 100% rename from conflict_model/conflict.py rename to copro/conflict.py diff --git a/conflict_model/data.py b/copro/data.py similarity index 98% rename from conflict_model/data.py rename to copro/data.py index 2427524..969ab89 100644 --- a/conflict_model/data.py +++ b/copro/data.py @@ -1,4 +1,4 @@ -from conflict_model import conflict, variables +from copro import conflict, variables import numpy as np import xarray as xr import pandas as pd diff --git a/conflict_model/evaluation.py b/copro/evaluation.py similarity index 75% rename from conflict_model/evaluation.py rename to copro/evaluation.py index 2cc930d..3dc101a 100644 --- a/conflict_model/evaluation.py +++ b/copro/evaluation.py @@ -1,4 +1,5 @@ import os, sys +import warnings from sklearn import metrics import pandas as pd import geopandas as gpd @@ -59,6 +60,9 @@ def evaluate_prediction(y_test, y_pred, y_prob, X_test, clf, config): 'ROC AUC score': metrics.roc_auc_score(y_test, y_prob[:, 1]), } + # out = pd.DataFrame().from_dict(eval_dict) + # out.to_csv(os.path.join(out_dir, 'eval_dict.csv')) + return eval_dict def fill_out_dict(out_dict, eval_dict): @@ -101,7 +105,7 @@ def fill_out_df(out_df, y_df): return out_df -def polygon_model_accuracy(df, global_df): +def polygon_model_accuracy(df, global_df, out_dir): """Determines a range of model accuracy values for each polygon. Reduces dataframe with results from each simulation to values per unique polygon identifier. Determines the total number of predictions made per polygon as well as fraction of correct predictions made for overall and conflict-only data. @@ -109,6 +113,7 @@ def polygon_model_accuracy(df, global_df): Args: df (dataframe): output dataframe containing results of all simulations. global_df (dataframe): global look-up dataframe to associate unique identifier with geometry. + out_dir (str): path to output folder. If None, output is not saved. Returns: (geo-)dataframe: dataframe and geo-dataframe with data per polygon. @@ -147,6 +152,9 @@ def polygon_model_accuracy(df, global_df): #- convert to geodataframe gdf_hit = gpd.GeoDataFrame(df_hit, geometry=df_hit.geometry) + if out_dir != None: + gdf_hit.to_file(os.path.join(out_dir, 'all_stats.shp'), crs='EPSG:4326') + return df_hit, gdf_hit def init_out_ROC_curve(): @@ -162,62 +170,7 @@ def init_out_ROC_curve(): return tprs, aucs, mean_fpr -def plot_ROC_curve_n_times(ax, clf, X_test, y_test, tprs, aucs, mean_fpr, **kwargs): - """Plots the ROC-curve per model simulation to a pre-initiated matplotlib-instance. - - Args: - ax (axis): axis of pre-initaited matplotlib-instance - clf (classifier): sklearn-classifier used in the simulation. - X_test (array): array containing test-sample variable values. - y_test (list): list containing test-sample conflict data. - tprs (list): list with false positive rates. - aucs (list): list with area-under-curve values. - mean_fpr (array): array with mean false positive rate. - - Returns: - list: lists with true positive rates and area-under-curve values per plot. - """ - - viz = metrics.plot_roc_curve(clf, X_test, y_test, ax=ax, - alpha=0.15, color='b', lw=1, label=None, **kwargs) - - interp_tpr = np.interp(mean_fpr, viz.fpr, viz.tpr) - interp_tpr[0] = 0.0 - tprs.append(interp_tpr) - aucs.append(viz.roc_auc) - - return tprs, aucs - -def plot_ROC_curve_n_mean(ax, tprs, aucs, mean_fpr, **kwargs): - """Plots the mean ROC-curve to a pre-initiated matplotlib-instance. - - Args: - ax (axis): axis of pre-initaited matplotlib-instance - tprs (list): list with false positive rates. - aucs (list): list with area-under-curve values. - mean_fpr (array): array with mean false positive rate. - """ - - mean_tpr = np.mean(tprs, axis=0) - mean_tpr[-1] = 1.0 - mean_auc = metrics.auc(mean_fpr, mean_tpr) - std_auc = np.std(aucs) - ax.plot(mean_fpr, mean_tpr, color='r', - label=r'Mean ROC (AUC = %0.2f $\pm$ %0.2f)' % (mean_auc, std_auc), - lw=2, alpha=.8, **kwargs) - - std_tpr = np.std(tprs, axis=0) - tprs_upper = np.minimum(mean_tpr + std_tpr, 1) - tprs_lower = np.maximum(mean_tpr - std_tpr, 0) - ax.fill_between(mean_fpr, tprs_lower, tprs_upper, color='grey', alpha=.2, label=None, **kwargs) - - ax.set(xlim=[-0.05, 1.05], ylim=[-0.05, 1.05], **kwargs) - - ax.legend(loc="lower right") - - return - -def correlation_matrix(df): +def calc_correlation_matrix(df): """Computes the correlation matrix for a dataframe. Args: @@ -284,4 +237,77 @@ def categorize_polys(gdf_hit, category='sub', mode='median'): gdf_hit['category'].loc[(gdf_hit.chance_correct_pred < average_hit_median) & (gdf_hit.nr_test_confl < nr_confl_median)] = 'LL' - return gdf_hit \ No newline at end of file + return gdf_hit + +def calc_kFold_polygon_analysis(y_df, global_df, out_dir, k=10): + """Determines the mean, median, and standard deviation of correct chance of prediction (CCP) for k parts of the overall output dataframe. + Instead of evaluating the overall output dataframe at once, this can give a better feeling of the variation in CCP between model repetitions. + + Args: + y_df (dataframe): output dataframe containing results of all simulations. + global_df (dataframe): global look-up dataframe to associate unique identifier with geometry. + out_dir (str): path to output folder. If None, output is not saved. + k (int, optional): number of chunks in which y_df will be split. Defaults to 10. + + Returns: + geodataframe: geodataframe containing mean, median, and standard deviation per polygon. + """ + + ks = np.array_split(y_df, k) + + df = pd.DataFrame() + + for i in range(len(ks)): + + ks_i = ks[i] + + df_hit, gdf_hit = polygon_model_accuracy(ks_i, global_df, out_dir=None) + + temp_df = pd.DataFrame(data=pd.concat([df_hit.chance_correct_pred], axis=1)) + + df = pd.concat([df, temp_df], axis=1) + + df['mean_CCP'] = round(df.mean(axis=1),2) + df['median_CCP'] = round(df.median(axis=1),2) + df['std_CCP'] = round(df.std(axis=1), 2) + + df = pd.merge(df, global_df, on='ID') + + df = df.drop(columns=['chance_correct_pred']) + + gdf = gpd.GeoDataFrame(df, geometry=df.geometry) + + if out_dir != None: + gdf.to_file(os.path.join(out_dir, 'kFold_CCP_stats.shp'), crs='EPSG:4326') + + return gdf + +def get_feature_importance(clf, config, out_dir): + """Determines relative importance of each feature (i.e. variable) used. Must be used after model/classifier is fit. + Returns dataframe and saves it to csv too. + + Args: + clf (classifier): sklearn-classifier used in the simulation. + config (ConfigParser-object): object containing the parsed configuration-settings of the model. + out_dir (str): path to output folder. If None, output is not saved. + + Returns: + dataframe: dataframe containing feature importance. + """ + + if config.get('machine_learning', 'model') == 'RFClassifier': + arr = clf.feature_importances_ + else: + arr = np.zeros(len(config.items('env_vars'))) + warnings.warn('WARNING: feature importance not supported for this kind of ML model', UserWarning) + + dict_out = dict() + for key, x in zip(config.items('env_vars'), range(len(arr))): + dict_out[key[0]] = arr[x] + + df = pd.DataFrame.from_dict(dict_out, orient='index', columns=['feature_importance']) + + if out_dir != None: + df.to_csv(os.path.join(out_dir, 'feature_importance.csv')) + + return df \ No newline at end of file diff --git a/conflict_model/machine_learning.py b/copro/machine_learning.py similarity index 98% rename from conflict_model/machine_learning.py rename to copro/machine_learning.py index f5af113..653808f 100644 --- a/conflict_model/machine_learning.py +++ b/copro/machine_learning.py @@ -3,7 +3,7 @@ import numpy as np import matplotlib.pyplot as plt from sklearn import svm, neighbors, ensemble, preprocessing, model_selection, metrics -from conflict_model import conflict +from copro import conflict def define_scaling(config): """Defines scaling method based on model configurations. diff --git a/conflict_model/models.py b/copro/models.py similarity index 88% rename from conflict_model/models.py rename to copro/models.py index ca0f186..0f0f8c4 100644 --- a/conflict_model/models.py +++ b/copro/models.py @@ -1,4 +1,4 @@ -from conflict_model import machine_learning, conflict, utils, evaluation +from copro import machine_learning, conflict, utils, evaluation import pandas as pd import numpy as np @@ -45,7 +45,9 @@ def all_data(X, Y, config, scaler, clf, out_dir): return X_df, y_df, eval_dict def leave_one_out(X, Y, config, scaler, clf, out_dir): - """Model workflow when each variable is left out from analysis once. + """Model workflow when each variable is left out from analysis once. Output is limited to the metric scores. + Output is stored to sub-folders of the output directory, with each sub-folder containing output for a n-1 variable combination. + After computing metric scores per prediction (i.e. n-1 variables combinations), model exit is forced. Not tested yet for more than one simulation! Args: @@ -55,11 +57,6 @@ def leave_one_out(X, Y, config, scaler, clf, out_dir): scaler (scaler): the specified scaling method instance. clf (classifier): the specified model instance. out_dir (str): path to output folder. - - Returns: - dataframe: containing the test-data X-array values. - datatrame: containing model output on polygon-basis. - dict: dictionary containing evaluation metrics per simulation. """ if not config.getboolean('general', 'verbose'): @@ -86,18 +83,18 @@ def leave_one_out(X, Y, config, scaler, clf, out_dir): eval_dict = evaluation.evaluate_prediction(y_test, y_pred, y_prob, X_test_loo, clf, config) - y_df = conflict.get_pred_conflict_geometry(X_test_ID, X_test_geom, y_test, y_pred) - - X_df = pd.DataFrame(X_test) + utils.save_to_csv(eval_dict, sub_out_dir, 'evaluation_metrics') if not config.getboolean('general', 'verbose'): sys.stdout = orig_stdout f.close() - return X_df, y_df, eval_dict + sys.exit('With LEAVE-ONE-OUT model, execution stops here.') def single_variables(X, Y, config, scaler, clf, out_dir): - """Model workflow when the model is based on only one single variable. + """Model workflow when the model is based on only one single variable. Output is limited to the metric scores. + Output is stored to sub-folders of the output directory, with each sub-folder containing output for a 1 variable combination. + After computing metric scores per prediction (i.e. per variable), model exit is forced. Not tested yet for more than one simulation! Args: @@ -107,11 +104,6 @@ def single_variables(X, Y, config, scaler, clf, out_dir): scaler (scaler): the specified scaling method instance. clf (classifier): the specified model instance. out_dir (str): path to output folder. - - Returns: - dataframe: containing the test-data X-array values. - datatrame: containing model output on polygon-basis. - dict: dictionary containing evaluation metrics per simulation. """ if not config.getboolean('general', 'verbose'): @@ -138,15 +130,13 @@ def single_variables(X, Y, config, scaler, clf, out_dir): eval_dict = evaluation.evaluate_prediction(y_test, y_pred, y_prob, X_test_svmod, clf, config) - y_df = conflict.get_pred_conflict_geometry(X_test_ID, X_test_geom, y_test, y_pred) - - X_df = pd.DataFrame(X_test) + utils.save_to_csv(eval_dict, sub_out_dir, 'evaluation_metrics') if not config.getboolean('general', 'verbose'): sys.stdout = orig_stdout f.close() - return X_df, y_df, eval_dict + sys.exit('With SINGLE VARIABLE model, execution stops here.') def dubbelsteen(X, Y, config, scaler, clf, out_dir): """Model workflow when the relation between variables and conflict is based on randomness. diff --git a/conflict_model/pipeline.py b/copro/pipeline.py similarity index 84% rename from conflict_model/pipeline.py rename to copro/pipeline.py index 4838bb7..6cdb3c1 100644 --- a/conflict_model/pipeline.py +++ b/copro/pipeline.py @@ -1,4 +1,4 @@ -from conflict_model import models, data, machine_learning, evaluation +from copro import models, data, machine_learning, evaluation import pandas as pd import numpy as np import os, sys @@ -27,13 +27,13 @@ def create_XY(config, conflict_gdf, polygon_gdf): if config.getboolean('general', 'verbose'): print('saving XY data by default to file {}'.format(os.path.abspath(os.path.join(config.get('general', 'input_dir'), 'XY.npy'))) + os.linesep) - np.save(os.path.join(config.get('general', 'input_dir'),'XY'), XY) + np.save(os.path.join(config.get('general', 'input_dir'),'XY'), XY) else: if config.getboolean('general', 'verbose'): print('loading XY data from file {}'.format(os.path.abspath(os.path.join(config.get('general', 'input_dir'), config.get('pre_calc', 'XY')))) + os.linesep) - XY = np.load(os.path.join(config.get('general', 'input_dir'), config.get('pre_calc', 'XY')), allow_pickle=True) + XY = np.load(os.path.join(config.get('general', 'input_dir'), config.get('pre_calc', 'XY')), allow_pickle=True) X, Y = data.split_XY_data(XY, config) @@ -79,11 +79,11 @@ def run(X, Y, config, scaler, clf, out_dir): if config.getint('general', 'model') == 1: X_df, y_df, eval_dict = models.all_data(X, Y, config, scaler, clf, out_dir) elif config.getint('general', 'model') == 2: - y_df, y_gdf, eval_dict = models.leave_one_out(X, Y, config, scaler, clf, out_dir) + X_df, y_df, eval_dict = models.leave_one_out(X, Y, config, scaler, clf, out_dir) elif config.getint('general', 'model') == 3: - y_df, y_gdf, eval_dict = models.single_variables(X, Y, config, scaler, clf, out_dir) + X_df, y_df, eval_dict = models.single_variables(X, Y, config, scaler, clf, out_dir) elif config.getint('general', 'model') == 4: - y_df, y_gdf, eval_dict = models.dubbelsteen(X, Y, config, scaler, clf, out_dir) + X_df, y_df, eval_dict = models.dubbelsteen(X, Y, config, scaler, clf, out_dir) else: raise ValueError('the specified model type in the cfg-file is invalid - specify either 1, 2, 3 or 4.') diff --git a/copro/plots.py b/copro/plots.py new file mode 100644 index 0000000..a2e3c0d --- /dev/null +++ b/copro/plots.py @@ -0,0 +1,188 @@ +import matplotlib.pyplot as plt +import geopandas as gpd +import seaborn as sbs +import numpy as np +import os, sys +from sklearn import metrics +from copro import evaluation + +def selected_polygons(polygon_gdf, **kwargs): + """Creates a plotting instance of the boundaries of all selected polygons. + + Args: + polygon_gdf (geo-dataframe): geo-dataframe containing the selected polygons. + + Kwargs: + Geopandas-supported keyword arguments. + + Returns: + ax: Matplotlib axis object. + """ + + ax = polygon_gdf.boundary.plot(**kwargs) + + return ax + +def selected_conflicts(conflict_gdf, **kwargs): + """Creates a plotting instance of the best casualties estimates of the selected conflicts. + + Args: + conflict_gdf (geo-dataframe): geo-dataframe containing the selected conflicts. + + Kwargs: + Geopandas-supported keyword arguments. + + Returns: + ax: Matplotlib axis object. + """ + + ax = conflict_gdf.plot(column='best', **kwargs) + + return ax + +def metrics_distribution(out_dict, **kwargs): + """Plots the value distribution of a range of evaluation metrics based on all model simulations. + + Args: + out_dict (dict): dictionary containing metrics score for various metrics and all simulation. + + Kwargs: + Matplotlib-supported keyword arguments. + + Returns: + ax: Matplotlib axis object. + """ + + fig, ax = plt.subplots(1, 1, **kwargs) + + sbs.histplot(out_dict['Accuracy'], ax=ax, color="k", label='Accuracy') + sbs.histplot(out_dict['Precision'], ax=ax, color="r", label='Precision') + sbs.histplot(out_dict['Recall'], ax=ax, color="b", label='Recall') + plt.legend() + + return ax + +def correlation_matrix(df, **kwargs): + """Plots the correlation matrix of a dataframe. + + Args: + df (dataframe): dataframe containing columns to be correlated. + + Kwargs: + Seaborn-supported keyword arguments. + + Returns: + ax: Matplotlib axis object. + """ + + df_corr = evaluation.calc_correlation_matrix(df) + + ax = sbs.heatmap(df_corr, **kwargs) + + return ax + +def polygon_categorization(gdf, category='sub', method='median', **kwargs): + """Plots the categorization of polygons based on chance of correct prediction and number of conflicts. + + Main categories are: + * H: chance of correct prediction higher than treshold; + * L: chance of correct prediction lower than treshold. + + Sub-categories are: + * HH: high chance of correct prediction with high number of conflicts; + * HL: high chance of correct prediction with low number of conflicts; + * LH: low chance of correct prediction with high number of conflicts; + * LL: low chance of correct prediction with low number of conflicts. + + Args: + gdf (geo-dataframe): containing model evaluation per unique polygon. + out_dir (str): path to output folder + method (str, optional): Statistical method used to determine categorization threshold. Defaults to 'median'. + + Kwargs: + Matplotlib-supported keyword arguments. + + Returns: + ax: Matplotlib axis object. + """ + + gdf = evaluation.categorize_polys(gdf, category, method) + + ax = gdf.plot(column='category', **kwargs) + + return ax + +def plot_ROC_curve_n_times(ax, clf, X_test, y_test, tprs, aucs, mean_fpr, **kwargs): + """Plots the ROC-curve per model simulation to a pre-initiated matplotlib-instance. + + Args: + ax (axis): axis of pre-initaited matplotlib-instance + clf (classifier): sklearn-classifier used in the simulation. + X_test (array): array containing test-sample variable values. + y_test (list): list containing test-sample conflict data. + tprs (list): list with false positive rates. + aucs (list): list with area-under-curve values. + mean_fpr (array): array with mean false positive rate. + + Returns: + list: lists with true positive rates and area-under-curve values per plot. + """ + + viz = metrics.plot_roc_curve(clf, X_test, y_test, ax=ax, + alpha=0.15, color='b', lw=1, label=None, **kwargs) + + interp_tpr = np.interp(mean_fpr, viz.fpr, viz.tpr) + interp_tpr[0] = 0.0 + tprs.append(interp_tpr) + aucs.append(viz.roc_auc) + + return tprs, aucs + +def plot_ROC_curve_n_mean(ax, tprs, aucs, mean_fpr, **kwargs): + """Plots the mean ROC-curve to a pre-initiated matplotlib-instance. + + Args: + ax (axis): axis of pre-initaited matplotlib-instance + tprs (list): list with false positive rates. + aucs (list): list with area-under-curve values. + mean_fpr (array): array with mean false positive rate. + """ + + mean_tpr = np.mean(tprs, axis=0) + mean_tpr[-1] = 1.0 + mean_auc = metrics.auc(mean_fpr, mean_tpr) + std_auc = np.std(aucs) + ax.plot(mean_fpr, mean_tpr, color='r', + label=r'Mean ROC (AUC = %0.2f $\pm$ %0.2f)' % (mean_auc, std_auc), + lw=2, alpha=.8, **kwargs) + + std_tpr = np.std(tprs, axis=0) + tprs_upper = np.minimum(mean_tpr + std_tpr, 1) + tprs_lower = np.maximum(mean_tpr - std_tpr, 0) + ax.fill_between(mean_fpr, tprs_lower, tprs_upper, color='grey', alpha=.2, label=None, **kwargs) + + ax.set(xlim=[-0.05, 1.05], ylim=[-0.05, 1.05], **kwargs) + + ax.legend(loc="lower right") + +def factor_importance(clf, config, out_dir=None, **kwargs): + """Plots the relative importance of each factor as bar plot. Note, this works only for RFClassifier as ML-model! + + Args: + clf (classifier): sklearn-classifier used in the simulation. + config (ConfigParser-object): object containing the parsed configuration-settings of the model. + out_dir (str): path to output folder. If None, output is not saved. + + Kwargs: + Matplotlib-supported keyword arguments. + + Returns: + ax: Matplotlib axis object. + """ + + df = evaluation.get_feature_importance(clf, config, out_dir) + + ax = df.plot.bar(**kwargs) + + return ax + diff --git a/conflict_model/selection.py b/copro/selection.py similarity index 95% rename from conflict_model/selection.py rename to copro/selection.py index a4c50f0..6645e6d 100644 --- a/conflict_model/selection.py +++ b/copro/selection.py @@ -2,7 +2,7 @@ import geopandas as gpd import numpy as np import os, sys -from conflict_model import utils +from copro import utils def filter_conflict_properties(gdf, config): """Filters conflict database according to certain conflict properties such as number of casualties, type of violence or country. @@ -141,7 +141,7 @@ def climate_zoning(gdf, extent_gdf, config): return gdf, polygon_gdf, global_df -def select(config): +def select(config, out_dir): """Main function performing the selection steps. Args: @@ -164,4 +164,7 @@ def select(config): gdf, polygon_gdf, global_df = climate_zoning(gdf, extent_gdf, config) + gdf.to_file(os.path.join(out_dir, 'selected_conflicts.shp'), crs='EPSG:4326') + polygon_gdf.to_file(os.path.join(out_dir, 'selected_polygons.shp'), crs='EPSG:4326') + return gdf, extent_gdf, polygon_gdf, global_df \ No newline at end of file diff --git a/conflict_model/utils.py b/copro/utils.py similarity index 83% rename from conflict_model/utils.py rename to copro/utils.py index 822718d..0817221 100644 --- a/conflict_model/utils.py +++ b/copro/utils.py @@ -40,7 +40,7 @@ def show_versions(): """Prints the version numbers by the main python-packages used. """ - from conflict_model import __version__ as cm_version + from copro import __version__ as cm_version from geopandas import __version__ as gpd_version from pandas import __version__ as pd_version from numpy import __version__ as np_version @@ -57,7 +57,7 @@ def show_versions(): sys.exit('please upgrade geopandas to version 0.7.0, your current version is {}'.format(gpd_version)) print("Python version: {}".format(os_version)) - print("conflict_model version: {}".format(cm_version)) + print("copro version: {}".format(cm_version)) print("geopandas version: {}".format(gpd_version)) print("xarray version: {}".format(xr_version)) print("rasterio version: {}".format(rio_version)) @@ -152,6 +152,10 @@ def initiate_setup(settings_file): if config['conflict']['conflict_file'] == 'download': download_PRIO(config) + if (config.getint('general', 'model') == 2) or (config.getint('general', 'model') == 3): + config.set('settings', 'n_runs', str(1)) + print('changed nr of runs to {}'.format(config.getint('settings', 'n_runs'))) + return config, out_dir def create_artificial_Y(Y): @@ -215,3 +219,40 @@ def get_conflict_datapoints_only(X_df, y_df): return X1_df, y1_df +def save_to_csv(arg, out_dir, fname): + """Saves an argument (either dictionary or dataframe) to csv-file. + + Args: + arg (dict or dataframe): dictionary or dataframe to be saved. + out_dir (str): path to output folder. + fname (str): name of stored item. + """ + + if isinstance(arg, dict): + try: + arg = pd.DataFrame().from_dict(arg) + except: + arg = pd.DataFrame().from_dict(arg, orient='index') + arg.to_csv(os.path.join(out_dir, fname + '.csv')) + + return + +def save_to_npy(arg, out_dir, fname): + """Saves an argument (either dictionary or dataframe) to parquet-file. + + Args: + arg (dict or dataframe): dictionary or dataframe to be saved. + out_dir (str): path to output folder. + fname (str): name of stored item. + """ + + if isinstance(arg, dict): + arg = pd.DataFrame().from_dict(arg) + arg = arg.to_numpy() + elif isinstance(arg, pd.DataFrame): + arg = arg.to_numpy() + + np.save(os.path.join(out_dir, fname + '.npy'), arg) + + return + diff --git a/conflict_model/variables.py b/copro/variables.py similarity index 100% rename from conflict_model/variables.py rename to copro/variables.py diff --git a/docs/Execution.rst b/docs/Execution.rst index 34da32b..aed5e8b 100644 --- a/docs/Execution.rst +++ b/docs/Execution.rst @@ -5,7 +5,7 @@ To be able to run the model, the conda environment has to be activated first. .. code-block:: console - $ conda activate conflict_model + $ conda activate copro Example notebook ----------------- @@ -15,7 +15,7 @@ They can all be run and converted to htmls by executing the provided shell-scrip .. code-block:: console - $ cd path/to/conflict_model/example + $ cd path/to/copro/example $ sh run.sh It is of course also possible to execute the notebook cell by cell using jupyter notebook. @@ -28,7 +28,7 @@ All data and settings are retrieved from the settings-file which needs to be pro .. code-block:: console - $ cd path/to/conflict_model/scripts - $ python runner.py path/to/conflict_model/data/run_setting.cfg + $ cd path/to/copro/scripts + $ python runner.py ../example/example_settings.cfg By default, output is stored to the output directory specified in the settings-file. \ No newline at end of file diff --git a/docs/Installation.rst b/docs/Installation.rst index 6e86c03..6de1c6b 100644 --- a/docs/Installation.rst +++ b/docs/Installation.rst @@ -9,10 +9,10 @@ You can then install the model package into this environment. .. code-block:: console - $ git clone https://github.com/JannisHoch/conflict_model.git - $ cd path/to/conflict_model + $ git clone https://github.com/JannisHoch/copro.git + $ cd path/to/copro $ conda env create -f environment.yml - $ conda activate conflict_model + $ conda activate copro $ python setup.py develop From PyPI diff --git a/docs/Output.rst b/docs/Output.rst new file mode 100644 index 0000000..eceacf6 --- /dev/null +++ b/docs/Output.rst @@ -0,0 +1,77 @@ +Output +========================= + +The model can produce a range of output files. Output is stored in the output folder. + +.. note:: + + In addition to these output files, the model settings file (cfg-file) is automatically copied to the output folder. + +.. important:: + + Not all model types provide the output mentioned below. If the 'leave-one-out' or 'single variable' model are selected, only the metrics are stored to a csv-file. + +Selected polygons +------------------ +A shp-file named ``selected_polygons.shp`` contains all polygons after performing the selection procedure. + +Selected conflicts +------------------- +The shp-file ``selected_conflicts.shp`` contains all conflict data points after performing the selection procedure. + +Overall output +--------------- + +Per model run, a fraction of the total XY-data is used to make a prediction. +To be able to analyse model output, all predictions made per run are appended to a main output-file. +This file is, actually, the basis of all futher analyes. +Since this can become a rather large file, the dataframe is converted to npy-file (``out_y_df.npy``). This file can be loaded again with ``np.load()``. + +.. note:: + + Note that ``np.load()`` returns an array. This can be further processed with e.g. pandas. + +Model accuracy per run +----------------------- + +Per model run, a range of metrics are computed. They are all appended to a dictionary and saved to the file ``out_dict.csv``. + +Model accuracy per polygon +--------------------------- + +At the end of all model repetitions, the resulting output contains multiple predictions for each polygon. +By aggregating results per polygon, it is possible to assess model output spatially. + +Three main output metrics are calculated per polygon: + +1. The chance of a correct (*CCP*), defined as the ratio of number of correct predictions made to overall number of predictions made; +2. The total number of conflicts in the test (*NOC*); +3. The chance of conflict (*COC*), defined as the ration of number of conflict predictions to overall number of predictions made. + +k-fold analysis +^^^^^^^^^^^^^^^^ + +The model is repeated several times to eliminate the influence of how the data is split into training and test samples. +As such, the accuracy per run and polygon will differ. + +To account for that, the resulting data set containing all predictions at the end of the run is split in k chunks. +Subsequently, the mean, median, and standard deviation of CCP is determined from the k chunks. + +The resulting shp-file is named ``kFold_CCP_stats.shp``. + +all data +^^^^^^^^^ + +All output metrics (CCP, NOC, COC) are determined based on the entire data set at the end of the run, i.e. without splitting it in chunks. + +The data is stored to ``all_stats.shp``. + + +.. note:: + + In addition to these shp-file, various plots can be stored by using the provided plots-functions. The plots aer stored in the output directory too. + Note that the plot settings cannot yet be fully controlled via those functions, i.e. it is more anticipated for debugging. + To create custom-made plots, rather use the shp-files and csv-file. + + + diff --git a/docs/api/XYdata.rst b/docs/api/XYdata.rst index 338de71..48a34f1 100644 --- a/docs/api/XYdata.rst +++ b/docs/api/XYdata.rst @@ -1,7 +1,7 @@ XY-Data ================================= -.. currentmodule:: conflict_model +.. currentmodule:: copro .. autosummary:: :toctree: generated/ diff --git a/docs/api/conflict.rst b/docs/api/conflict.rst index 16ae8a5..2e9ca7f 100644 --- a/docs/api/conflict.rst +++ b/docs/api/conflict.rst @@ -1,7 +1,7 @@ Work with conflict data ================================= -.. currentmodule:: conflict_model +.. currentmodule:: copro .. autosummary:: :toctree: generated/ diff --git a/docs/api/evaluation.rst b/docs/api/evaluation.rst index 1885a01..dfc6b7a 100644 --- a/docs/api/evaluation.rst +++ b/docs/api/evaluation.rst @@ -1,7 +1,7 @@ Model evaluation ================================= -.. currentmodule:: conflict_model +.. currentmodule:: copro .. autosummary:: :toctree: generated/ @@ -14,7 +14,6 @@ Model evaluation evaluation.evaluate_prediction evaluation.polygon_model_accuracy evaluation.init_out_ROC_curve - evaluation.plot_ROC_curve_n_times - evaluation.plot_ROC_curve_n_mean - evaluation.correlation_matrix - evaluation.categorize_polys \ No newline at end of file + evaluation.categorize_polys + evaluation.calc_kFold_polygon_analysis + evaluation.get_feature_importance \ No newline at end of file diff --git a/docs/api/generated/conflict_model.models.all_data.rst b/docs/api/generated/conflict_model.models.all_data.rst index 6e8df82..de53de5 100644 --- a/docs/api/generated/conflict_model.models.all_data.rst +++ b/docs/api/generated/conflict_model.models.all_data.rst @@ -1,6 +1,6 @@ conflict\_model.models.all\_data ================================ -.. currentmodule:: conflict_model.models +.. currentmodule:: copro.models .. autofunction:: all_data \ No newline at end of file diff --git a/docs/api/generated/conflict_model.models.dubbelsteen.rst b/docs/api/generated/conflict_model.models.dubbelsteen.rst index 57aaa01..8e95c9c 100644 --- a/docs/api/generated/conflict_model.models.dubbelsteen.rst +++ b/docs/api/generated/conflict_model.models.dubbelsteen.rst @@ -1,6 +1,6 @@ conflict\_model.models.dubbelsteen ================================== -.. currentmodule:: conflict_model.models +.. currentmodule:: copro.models .. autofunction:: dubbelsteen \ No newline at end of file diff --git a/docs/api/generated/conflict_model.models.leave_one_out.rst b/docs/api/generated/conflict_model.models.leave_one_out.rst index a40f5f1..bb5b7f5 100644 --- a/docs/api/generated/conflict_model.models.leave_one_out.rst +++ b/docs/api/generated/conflict_model.models.leave_one_out.rst @@ -1,6 +1,6 @@ conflict\_model.models.leave\_one\_out ====================================== -.. currentmodule:: conflict_model.models +.. currentmodule:: copro.models .. autofunction:: leave_one_out \ No newline at end of file diff --git a/docs/api/generated/conflict_model.models.single_variables.rst b/docs/api/generated/conflict_model.models.single_variables.rst index ba127ca..6ddfe14 100644 --- a/docs/api/generated/conflict_model.models.single_variables.rst +++ b/docs/api/generated/conflict_model.models.single_variables.rst @@ -1,6 +1,6 @@ conflict\_model.models.single\_variables ======================================== -.. currentmodule:: conflict_model.models +.. currentmodule:: copro.models .. autofunction:: single_variables \ No newline at end of file diff --git a/docs/api/generated/conflict_model.pipeline.create_XY.rst b/docs/api/generated/conflict_model.pipeline.create_XY.rst index 8f93949..b4f6218 100644 --- a/docs/api/generated/conflict_model.pipeline.create_XY.rst +++ b/docs/api/generated/conflict_model.pipeline.create_XY.rst @@ -1,6 +1,6 @@ conflict\_model.pipeline.create\_XY =================================== -.. currentmodule:: conflict_model.pipeline +.. currentmodule:: copro.pipeline .. autofunction:: create_XY \ No newline at end of file diff --git a/docs/api/generated/conflict_model.pipeline.prepare_ML.rst b/docs/api/generated/conflict_model.pipeline.prepare_ML.rst index 9b24a5c..102eba2 100644 --- a/docs/api/generated/conflict_model.pipeline.prepare_ML.rst +++ b/docs/api/generated/conflict_model.pipeline.prepare_ML.rst @@ -1,6 +1,6 @@ conflict\_model.pipeline.prepare\_ML ==================================== -.. currentmodule:: conflict_model.pipeline +.. currentmodule:: copro.pipeline .. autofunction:: prepare_ML \ No newline at end of file diff --git a/docs/api/generated/conflict_model.pipeline.run.rst b/docs/api/generated/conflict_model.pipeline.run.rst index f56746d..1e94201 100644 --- a/docs/api/generated/conflict_model.pipeline.run.rst +++ b/docs/api/generated/conflict_model.pipeline.run.rst @@ -1,6 +1,6 @@ conflict\_model.pipeline.run ============================ -.. currentmodule:: conflict_model.pipeline +.. currentmodule:: copro.pipeline .. autofunction:: run \ No newline at end of file diff --git a/docs/api/generated/conflict_model.selection.climate_zoning.rst b/docs/api/generated/conflict_model.selection.climate_zoning.rst index 5d7d5ed..2439118 100644 --- a/docs/api/generated/conflict_model.selection.climate_zoning.rst +++ b/docs/api/generated/conflict_model.selection.climate_zoning.rst @@ -1,6 +1,6 @@ conflict\_model.selection.climate\_zoning ========================================= -.. currentmodule:: conflict_model.selection +.. currentmodule:: copro.selection .. autofunction:: climate_zoning \ No newline at end of file diff --git a/docs/api/generated/conflict_model.selection.clip_to_extent.rst b/docs/api/generated/conflict_model.selection.clip_to_extent.rst index d3a7c7c..1f79821 100644 --- a/docs/api/generated/conflict_model.selection.clip_to_extent.rst +++ b/docs/api/generated/conflict_model.selection.clip_to_extent.rst @@ -1,6 +1,6 @@ conflict\_model.selection.clip\_to\_extent ========================================== -.. currentmodule:: conflict_model.selection +.. currentmodule:: copro.selection .. autofunction:: clip_to_extent \ No newline at end of file diff --git a/docs/api/generated/conflict_model.selection.filter_conflict_properties.rst b/docs/api/generated/conflict_model.selection.filter_conflict_properties.rst index 28cf8f2..7083029 100644 --- a/docs/api/generated/conflict_model.selection.filter_conflict_properties.rst +++ b/docs/api/generated/conflict_model.selection.filter_conflict_properties.rst @@ -1,6 +1,6 @@ conflict\_model.selection.filter\_conflict\_properties ====================================================== -.. currentmodule:: conflict_model.selection +.. currentmodule:: copro.selection .. autofunction:: filter_conflict_properties \ No newline at end of file diff --git a/docs/api/generated/conflict_model.selection.select.rst b/docs/api/generated/conflict_model.selection.select.rst index 564a3ec..7c1abba 100644 --- a/docs/api/generated/conflict_model.selection.select.rst +++ b/docs/api/generated/conflict_model.selection.select.rst @@ -1,6 +1,6 @@ conflict\_model.selection.select ================================ -.. currentmodule:: conflict_model.selection +.. currentmodule:: copro.selection .. autofunction:: select \ No newline at end of file diff --git a/docs/api/generated/conflict_model.selection.select_period.rst b/docs/api/generated/conflict_model.selection.select_period.rst index fade85e..ac4512e 100644 --- a/docs/api/generated/conflict_model.selection.select_period.rst +++ b/docs/api/generated/conflict_model.selection.select_period.rst @@ -1,6 +1,6 @@ conflict\_model.selection.select\_period ======================================== -.. currentmodule:: conflict_model.selection +.. currentmodule:: copro.selection .. autofunction:: select_period \ No newline at end of file diff --git a/docs/api/index.rst b/docs/api/index.rst index e2fc76f..7655944 100644 --- a/docs/api/index.rst +++ b/docs/api/index.rst @@ -2,7 +2,7 @@ API docs ======== This section contains the Documentation of the Application Programming -Interface (API) of 'conflict_model'. +Interface (API) of 'copro'. .. toctree:: :numbered: diff --git a/docs/api/machine_learning.rst b/docs/api/machine_learning.rst index 1e356b5..3ae055f 100644 --- a/docs/api/machine_learning.rst +++ b/docs/api/machine_learning.rst @@ -1,7 +1,7 @@ Machine learning ================================= -.. currentmodule:: conflict_model +.. currentmodule:: copro .. autosummary:: :toctree: generated/ diff --git a/docs/api/models.rst b/docs/api/models.rst index 403d61a..f45e4ef 100644 --- a/docs/api/models.rst +++ b/docs/api/models.rst @@ -1,7 +1,7 @@ The various models ==================== -.. currentmodule:: conflict_model +.. currentmodule:: copro .. autosummary:: :toctree: generated/ diff --git a/docs/api/pipeline.rst b/docs/api/pipeline.rst index 1c3fdfe..450c537 100644 --- a/docs/api/pipeline.rst +++ b/docs/api/pipeline.rst @@ -1,7 +1,7 @@ The model pipeline ==================== -.. currentmodule:: conflict_model +.. currentmodule:: copro .. autosummary:: :toctree: generated/ diff --git a/docs/api/plotting.rst b/docs/api/plotting.rst index 283b15d..a136ffc 100644 --- a/docs/api/plotting.rst +++ b/docs/api/plotting.rst @@ -1,17 +1,17 @@ Plotting ================================= -.. currentmodule:: conflict_model +.. currentmodule:: copro .. autosummary:: :toctree: generated/ :nosignatures: - plots.plot_active_polys - plots.plot_metrics_distribution - plots.plot_nr_and_dist_pred - plots.plot_frac_and_nr_conf - plots.plot_frac_pred - plots.plot_scatterdata - plots.plot_correlation_matrix - plots.plot_categories \ No newline at end of file + plots.selected_polygons + plots.selected_conflicts + plots.metrics_distribution + plots.correlation_matrix + plots.polygon_categorization + plots.plot_ROC_curve_n_times + plots.plot_ROC_curve_n_mean + plots.factor_importance \ No newline at end of file diff --git a/docs/api/selection.rst b/docs/api/selection.rst index eacb04b..6a425c2 100644 --- a/docs/api/selection.rst +++ b/docs/api/selection.rst @@ -1,7 +1,7 @@ Selecting polygons and conflicts ================================= -.. currentmodule:: conflict_model +.. currentmodule:: copro .. autosummary:: :toctree: generated/ diff --git a/docs/api/utils.rst b/docs/api/utils.rst index a8bad5f..fe127e9 100644 --- a/docs/api/utils.rst +++ b/docs/api/utils.rst @@ -1,7 +1,7 @@ Auxiliary functions ================================= -.. currentmodule:: conflict_model +.. currentmodule:: copro .. autosummary:: :toctree: generated/ @@ -15,4 +15,6 @@ Auxiliary functions utils.initiate_setup utils.create_artificial_Y utils.global_ID_geom_info - utils.get_conflict_datapoints_only \ No newline at end of file + utils.get_conflict_datapoints_only + utils.save_to_csv + utils.save_to_npy \ No newline at end of file diff --git a/docs/api/variables.rst b/docs/api/variables.rst index bc75dfd..a2ad0c9 100644 --- a/docs/api/variables.rst +++ b/docs/api/variables.rst @@ -1,7 +1,7 @@ Variable values ================================= -.. currentmodule:: conflict_model +.. currentmodule:: copro .. autosummary:: :toctree: generated/ diff --git a/docs/conf.py b/docs/conf.py index 5305664..7e341c4 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -37,10 +37,10 @@ def __getattr__(cls, name): # # sys.path.insert(0, os.path.abspath('..')) -sys.path.insert(0, os.path.abspath('../conflict_model')) +sys.path.insert(0, os.path.abspath('../copro')) # sys.path.insert(0, os.path.abspath('.')) -import conflict_model +import copro # -- General configuration --------------------------------------------- @@ -86,7 +86,7 @@ def __getattr__(cls, name): master_doc = 'index' # General information about the project. -project = 'conflict_model' +project = 'copro' copyright = f"2020-{datetime.now().year}" author = "Jannis M. Hoch" @@ -95,9 +95,9 @@ def __getattr__(cls, name): # the built documents. # # The short X.Y version. -version = conflict_model.__version__ +version = copro.__version__ # The full version, including alpha/beta/rc tags. -release = conflict_model.__version__ +release = copro.__version__ # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. @@ -134,7 +134,7 @@ def __getattr__(cls, name): # documentation. html_theme_options = { - "github_url": "https://github.com/JannisHoch/conflict_model", + "github_url": "https://github.com/JannisHoch/copro", "use_edit_page_button": False, "search_bar_position": "sidebar" } @@ -148,7 +148,7 @@ def __getattr__(cls, name): html_show_copyright = True # Output file base name for HTML help builder. -htmlhelp_basename = 'conflict_model_doc' +htmlhelp_basename = 'copro_doc' # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, @@ -166,7 +166,7 @@ def __getattr__(cls, name): # -- Options for HTMLHelp output --------------------------------------- # Output file base name for HTML help builder. -htmlhelp_basename = 'conflict_modeldoc' +htmlhelp_basename = 'coprodoc' # -- Options for LaTeX output ------------------------------------------ @@ -193,8 +193,8 @@ def __getattr__(cls, name): # (source start file, target name, title, author, documentclass # [howto, manual, or own class]). latex_documents = [ - (master_doc, 'conflict_model.tex', - 'conflict_model Documentation', + (master_doc, 'copro.tex', + 'copro Documentation', 'Jannis M. Hoch', 'manual'), ] @@ -204,8 +204,8 @@ def __getattr__(cls, name): # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ - (master_doc, 'conflict_model', - 'conflict_model Documentation', + (master_doc, 'copro', + 'copro Documentation', [author], 1) ] @@ -216,10 +216,10 @@ def __getattr__(cls, name): # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ - (master_doc, 'conflict_model', - 'conflict_model Documentation', + (master_doc, 'copro', + 'copro Documentation', author, - 'conflict_model', + 'copro', 'One line description of project.', 'Miscellaneous'), ] diff --git a/docs/index.rst b/docs/index.rst index 4bf5f27..2c680fb 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -1,19 +1,19 @@ -conflict_model +copro ========================= -This is the documentation website of the 'conflict_model', a (machine learning) model for mapping environmental drivers of conflict risk. +This is the documentation website CoPro, a machine-learning tool for conflict risk projections based on climate, environmental, and societal drivers. .. image:: https://travis-ci.com/JannisHoch/conflict_model.svg?token=BnX1oxxHRbyd1dPyXAp2&branch=dev :target: https://travis-ci.com/JannisHoch/conflict_model .. image:: https://img.shields.io/badge/License-MIT-blue.svg - :target: https://github.com/JannisHoch/conflict_model/blob/dev/LICENSE + :target: https://github.com/JannisHoch/copro/blob/dev/LICENSE -.. image:: https://readthedocs.org/projects/conflict-model/badge/?version=dev - :target: https://conflict-model.readthedocs.io/en/dev/?badge=dev +.. image:: https://readthedocs.org/projects/copro/badge/?version=latest + :target: https://copro.readthedocs.io/en/latest/?badge=latest -.. image:: https://img.shields.io/github/v/release/JannisHoch/conflict_model - :target: https://github.com/JannisHoch/conflict_model/releases/tag/v0.0.3 +.. image:: https://img.shields.io/github/v/release/JannisHoch/copro + :target: https://github.com/JannisHoch/copro/releases/tag/v0.0.3 .. image:: https://badges.frapsoft.com/os/v2/open-source.svg?v=103 :target: https://github.com/ellerbrock/open-source-badges/ @@ -33,6 +33,7 @@ Contents Installation Execution Model settings + Output Workflow API Docs diff --git a/docs/model_settings.rst b/docs/model_settings.rst index 4b06e2e..b8a0abc 100644 --- a/docs/model_settings.rst +++ b/docs/model_settings.rst @@ -21,7 +21,7 @@ Additionally, the cfg-file included in the GitHub-repository already contains th .. note:: - the 'leave_one_out' and 'single_variables' models are only tested in beta-state. + the 'leave-one-out' and 'single variables' models are only tested in beta-state. They produce only limited output (see :ref:`Output`). - *verbose*: if True, model messages will be printed to screen. diff --git a/environment.yml b/environment.yml index 08ad248..1dafc3a 100644 --- a/environment.yml +++ b/environment.yml @@ -1,4 +1,4 @@ -name: conflict_model +name: copro channels: - conda-forge @@ -14,15 +14,15 @@ dependencies: - pytest>=5.4.2 - pytest-runner - descartes - - rioxarray + - rioxarray==0.1.0 - ipython - notebook - nbconvert - - scikit-learn + - scikit-learn==0.23.2 - netcdf4 - ConfigParser - click - - seaborn + - seaborn==0.11.0 - pip - pip: - rasterstats==0.14.0 diff --git a/example/example_settings.cfg b/example/example_settings.cfg index b98c118..fa1e771 100644 --- a/example/example_settings.cfg +++ b/example/example_settings.cfg @@ -46,5 +46,5 @@ irr_water_demand=irrWaterDemand.nc # choose from: MinMaxScaler, StandardScaler, RobustScaler, QuantileTransformer scaler=QuantileTransformer # choose from: NuSVC, KNeighborsClassifier, RFClassifier -model=KNeighborsClassifier +model=RFClassifier train_fraction=0.7 \ No newline at end of file diff --git a/example/nb01_model_init_and_selection.ipynb b/example/nb01_model_init_and_selection.ipynb index 8ad0cc2..b730624 100644 --- a/example/nb01_model_init_and_selection.ipynb +++ b/example/nb01_model_init_and_selection.ipynb @@ -18,11 +18,11 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ - "from conflict_model import utils, selection\n", + "from copro import utils, selection, plots\n", "\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", @@ -40,15 +40,15 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Python version: 3.7.9 (default, Aug 31 2020, 17:10:11) [MSC v.1916 64 bit (AMD64)]\n", - "conflict_model version: 0.0.4b2\n", + "Python version: 3.7.8 | packaged by conda-forge | (default, Jul 31 2020, 01:53:57) [MSC v.1916 64 bit (AMD64)]\n", + "copro version: 0.0.5\n", "geopandas version: 0.8.0\n", "xarray version: 0.15.1\n", "rasterio version: 1.1.0\n", @@ -56,7 +56,7 @@ "numpy version: 1.18.1\n", "scikit-learn version: 0.23.2\n", "matplotlib version: 3.2.1\n", - "seaborn version: 0.10.1\n", + "seaborn version: 0.11.0\n", "rasterstats version: 0.14.0\n" ] } @@ -74,7 +74,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -90,14 +90,17 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "saving output to folder C:\\Users\\Icke\\_code\\conflict_model\\example\\OUT\n" + "saving output to folder C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\OUT\n", + "\n", + "no conflict file was specified, hence downloading data from http://ucdp.uu.se/downloads/ged/ged201-csv.zip to C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\UCDP\\ged201-csv.zip\r\n", + "\n" ] } ], @@ -118,14 +121,14 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "reading csv file to dataframe C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\UCDP/ged201.csv\n", + "reading csv file to dataframe C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\UCDP\\ged201.csv\n", "\n", "translating to geopandas dataframe\n", "\n", @@ -133,7 +136,7 @@ "...filtering key best with lower value 1\n", "...filtering key type_of_violence with value(s) ['1', '2', '3']\n", "focussing on period between 2000 and 2015\n", - "reading extent and spatial aggregation level from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\waterProvinces/waterProvinces_Africa.shp\n", + "reading extent and spatial aggregation level from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\waterProvinces/waterProvinces_Africa.shp\n", "\n", "fixing invalid geometries\n", "\n", @@ -147,28 +150,26 @@ } ], "source": [ - "conflict_gdf, extent_gdf, selected_polygons_gdf, global_df = selection.select(config)" + "conflict_gdf, extent_gdf, selected_polygons_gdf, global_df = selection.select(config, out_dir)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Depending on the settings, we may focus on some climate zones only. As such, not all water provinces are used in the model. For a visual inspection if this selection worked as intended, we plot below the conflicts and as background map only those water provinces that are actually used in the model.\n", - "\n", - "In case climate zones are specified, the number of active polygons should be less than the number of all polygons. If not climate zones are specified, both plots should be identical." + "Depending on the settings, we may focus on some climate zones only. As such, not all water provinces are used in the model. For a visual inspection if this selection worked as intended, we plot below the conflicts and as background map only those water provinces that are actually used in the model." ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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8mRiT5HqabctPRJ7CGK3ZcKbr02iqQrVRdpWxTNJ1GH5ORzCGWItXPZiC8XL8HTiE8RGp6GN1tryD8bJcgvEh+BJjUgwYSuLXYgwZ3ewh7ecYQ7HbMZS3ORWU0xnYICKnMBSSCUqpQ5Uspzy+M+U+aP69AqCUisPwG12GsVzV6lLpvgRam+XN85DvKxgK6A6MSVlbivOuBJEYk+UqoiOwxVQGW3KGZYEuwXbSDKPuTwHrMPwUV1aQ92jgG6VUaeUzAmP4MxvjPjgxFONiJmBYlTIwPtT3lSrnfTMs1vx/n1tYpClbeZypjVSG9zHa+hIRycaYrFasQNbDUDCyMNwbVlGJDpVSKhZDqf8Qwwp2HYYlyu4h+osYw86HMO6bJ2WrON9sjAk/12G4UOzDmMUPxhJMt2Hch885rZCBoaB+jtGBjccY1n7bDHsXw4/5BIaFc7pbusUYfqlxZrp8Sg7pu8uWC7wKrDHvRzcPsl8N3IphfTzO6YmCAHcCh8VwwRiHUX/lkYfRbsGwZue5hZ3p2X4No5OcISVXfPgGY1k9T/f3J4wJftuAnzHaHUqpueY1zDDl3gkM9lRoFdtEeXwHDAR+LK+jrJRajuEfPBuj890Eo8498RSGK9N6U/5lGPMJKsM/MZ73TRjuG29g+IMnYMxz+DdGBygBYxShPJ3gPxj3718Y9ZNnnsNUkE+Z5WBeVwiwSE6v2f2LW17u994Hw20nFeP9MwS4VpVcOUaj+ctI2W+iRvP3QIxdnSYopfZcbFk05SMiX2B82BdfbFk0lwYisg1jwuEZl7Iqle4u4H6lVM9S5xWGa8j+cyimphKIyB0YbhZPVyKuN4ZB53JzdECjuSBoZVej0Wg0f3tExB9j1ZpPlFLflArTyq5GoymXauPGoNFoNJrqiemjmozhxlHepC+NRqPxiLbsajQajUaj0WiqLdqyq9FoNBqNRqOptnhaa/SiERoaqqKjoy+2GBqNRqPRaC5RYmJiUpRSdc4c89Jk0KAuKjU184KUFRMTt1gpdc0FKew88rdSdqOjo9m8+UzLpGo0Go1Go9F4RkQq2uHwkic1NZMNGyddkLJs1n5nsxPj3w7txqDRaDQajUajqbb8rSy7Go1Go9FoNJoKUIDTebGluKTQll2NRqPRaDQaTbVFW3Y1Go1Go9FoLhmUtuxWEW3Z1Wg0Go1Go9FUW7RlV6PRaDQajeZSQlt2q4S27Go0Go1Go9Foqi3asqvRaDQajUZzqaAApS62FJcU2rKr0Wg0Go1Go6m2aMuuRqPRaDQazSWDXo2hqmjLrkaj0Wg0Go2m2qItuxqNRqPRaDSXEtqyWyW0ZVej0Wg0Go1GU23Ryq5Go9FoNBqNptqi3Rg0Go1Go9FoLhUU2o2himjLrkaj0Wg0Go2m2qItuxqNRqPRaDSXDHrpsaqiLbsajUaj0Wg0mmqLtuxqNBqNRqPRXCpon90qo5VdTbUnPT2duXPnk5OdR1RkC+qEhtKpeyu8vHTz12g0Go2muqO/9ppqzaRPv+TtJ36klq0xgpDrWMUpWwq1azdg8vdPc0Xn5hdbxItCbOwOJkwYz8qVm/Hz8+Hee2/h5ZffxdfX72KLptFoNJoKUYjSlt2qoH12NZc07785idpBDakb0oi5MxaWCIuNjePDJ5dSy9YYhZNj9j0cKthEak4CJxJjGX3Dc+TnFVwkyS8eSUlH6NatD0uWrKegoJCMjFN89NE0Roy89mKLptFoNBrNOUdbdjWXLMG+9cguSHUdDx91I7Xvj6BuRDjNmjekVesmDB7TDIACdQrF5cDl2O2F/DhzCfaUfH5bEsPgYT0u0hVcWJRSzJw5kz17dnHHHXeilGL37j1s27ad9PQMli/bQGzsDlq0uPxii6rRaDSaitA+u1VCK7uaS5K7RjxAdkEqjRpFc+zYMS67rA3XXVfWMnksPo9cZwZ2lQtAYIAfDaPCqVkziMSck7zx3FsMHjb3vMvrzLez6bPvSPojhtYRDal7Qz+C+3VERM572e7s3buXvLw8jh8/jre3N3369KJPn158//1Mjh8/yu7d27Syq9FoNJpqhVZ2NZckmQUneeGF/5QbnnMqj1/mbcc/uTHbcxehcAAQHR3BbVHhZixFXFz8eZf18P4DXNO1D/GZqVgRBHhxzSpuveN2wh8bdd7LL43NBvPnL8RuL3TV4ahRNwPQvHmbCy6PRqPRaKqAApzqYktxSaGVXc0lx6RJk+jQqX2Z83Pn/oTdbqdWzbpkZhXgExBCcKCdpvYGrjiNGxu/iy2qgUE+51y+nJwcEhMTAcN14IGx9yN1QoiqEwxAcnIKz2xbTuOAmgy5eQDeEWHnXIaK6Nq1Bz4+k01l9xUuu6w1I0YMB6BVqysuqCwajUaj0ZxvtLKrueRITk72eP7GG4eVk6JBiSOHw4nD4QSEVVvPrQvDzp07+eKLKdSsGeI613/QgBJxTpw4yaRPP+e9uC3sfvZdut18Df0G9XYp4BmpmTw68BWcKUWkkErUgLq07dKakSOvp06d2n9ZxuDgmvz++688+OBDbNiwi/3795OTk0nduhFYLHrOqkaj0fy90TuoVRWt7GouOEopUlJS2LlzJ/Hx8dSpU4fBgwdXWtGaOHEiJ06coEePPkDJB17ED6vVt/gIX1sICicFRVmny3cqTp5MIyygFvUj6p2jq4KNGzfSr99VXHvtYEAxc+ZsbDYbVqCgqBCA/v37Urt2KEG+0WzNKGDz9OlYvvuOqDrh/L5lEb/9spnVLy7HmX+cBSlrCfCJZNe8ZObOWsOz/36TmbMnMWBA778sa/v23Vm3bitFRUVYLBamTJmCt7f3X85Xo9FoNJq/G1rZ1Vxwli5dyrp161zH8fHx9OzZk5CQEBISEpg3bx41a9bEZrPRo0cPGjZsWCK9n58f0dHRxMbupEnDy0nOSALAyxaIVZw4yXGLnYqIFQsWlHKicGDBwtV9r2TBkpnn9Loee2wiubm5gKKoqJCkJEMuEUEpw7/KXiBYLV5YbUEAWJWTXHsKB08mctfV9+KbUhc/lc2C1E3UCmiLRYxH1Mvih1PV4fZbHybh2Ba8vLzOicw2m83V+Wjbtu05yVOj0Wg05xG9g1qV0cqu5oLjrugGBASQk3NaOZ09ezaZmZmkpaUBEBsby2OPPUZwcHCZfIKCgjiZfojMzCySkk7SsGEEDkcRU6Z8zawffyE0NBSFYuOGraC8uX7YAN7/4GV8fM69ny5ATMxWj+eVUvj7+uFw+GEVbwIDfRl5W08zEBQKpypEEOp51yHZDrdZriuzUkNyUg5rV2eybt1mevfuXm5Z8+bNc9VfZcjJyaGgoIDatf+6i4RGo9FoNH83tLKrueD07duXI0eOuI4DAwMJCjIsnR07duTw4cMcPHgQgNDQUAICAirMLyQkmJCQ08rwhAnjmTBh/HmQvGJq1arlsua6ExgYyLRpU3lozPPsi0vCP8C3TByHswgQsEBeQQE+Nj9wU3ZDavrQuFUt1q/yZfOmreUqu4WFhezYsQOAxo0blwlv2rQpzZo1K3Hu+PHjgFHXGo1Go9FUN7Syq7ng9OnTp9ywXr160atXrwsozblj4sTHeO65F0qc8/f3Z/z4h7jhhmE8N/51Dh88yeGDJ0vEUcpJnj2FKN+6ZAVZWXnyF2oGdsUiVlecjr3DiG5eg+RT25n4zxW0adOCQdeUnPhWmoMHD/L8889XGGfPnj389NNP+Pv7Ex4eXmFcjUaj0fxN0NsFVwmt7Go054AjR47QveuV9Gh/HTWCamOzeFPbvykj7uzHyy+/CMDljYM5vj0Vpyq9kYQiwOpNDYuVY365dAzpwJ6CVHxstbGIlfyiNLLtdsQSQp0IP6ABjz46gW+nf13GGutwOEocO51OjxP/HA4Hy5YtY/369URERDBy5Ej8/f3PZZVoNBqNRvO3QCu7Gs1fJD09na+++gqAnlcbLgInkjIQazDe9obYbMZj9sY3k9jS4xZOZBciptVWgFa+NUjLzyHmVDzxO+cz9dOFxH88hZzCFHxstTlxagt2exd8fX0ZO3a0q9yFCxeeUbaVK1fSv3//EueysrKYNWsWCQkJdO7cmauvvtolo0aj0Wj+7uilx6qK/sJpNH+RgoIC1+9Tp/JY+ss20tNyUDiZMWsuL779MDVrBRERHc2GPUsZ0Okq9iSm4nDaKShMZXV2ETZbCD3a9qB+RB2efmUMT78yhp0799KubUec2Fm1ajUHDhyiQ4f2tG17GQDbt+/g7bffKiPPtGnTXL8jIyNLhB04cIBvv/0WgOHDh+sVGDQajUZT7dHKrkZzlqxZvJMZn/xGSvoJWg4wlgILDPSjU5dmzJu13owlLF+0nhF3XAVAUEgwG/dt4IPXJvPvF1/GYgnA2+LLLUOHMXXOhyXyv+yyloQ3iCQx8QBFRYXccssIfH2NyW1ffDEFb2/fMpPQXnzxxRLH3333net3cHAwWVnGesOjRo2iefPm56wuNBqNRnOB0NsFVxm9XZJGcxZ89tYMfvhhBs4axwlrYZzbsDYWgIjI00t4KRSR0WU3rnjk6fs5lZ9AYdFJ8uxHyii6xWzduhY/vwCGDr0WX19flFIsXryMtLQMxo27r0x8q9XqIReDYkUXKLMig0aj0Wg01RWt7Go0VSQnK49du3dSI9yGT4Bg9YKUo3nE7j7Gof3HsViE4bd0p0bNAAJ8Auna8+xdBUJDa3Hw4F7X0mwbN25m27btDBp0FY899miZ+I8++igdOnRg/PjxPPPMM4wePZrHHnusTLyXXnrJ9buoqIi8vLyzllGj0Wg0FxLTZ/dC/FUTtBuDRlNF4v48itUmKGDz3EwK843zXs5Q/li5h7B6NYhoUJs7xvTF19ePNWvW0KVLF5RSJbbkLcgtZPuyOHIy8mh1ZSPqNanNwYMHuP7669mzZx82m5URI65n+vQfGD36TtatW0fPnj146603aNOmjUfZAgMDue6661zH0dHRAAwZMoRFixaViFva5aFFixbceuutf72CNBqNRqP5G6GVXY3GjczMzBITzjwh3oWE1LdisQp9763NpjmZZBwroqalPlnZ8PWkJfQf1ImefduRkpLMsmXLWLZs2en0IghCkd0JDnAWwfIt4B/oyyvvvEJenqE92+1FfPfdHBYuCGXq5Fmu9K1atarydXXu3Nml7LZv357Y2Ngy1tzY2FjS0tKoVatWlfPXaDQazQWkGlldLwRa2dVoTE6ePMmnn35aqbgWq5j/ofPwEPavyyFpt5PP5rxJu26nJ40dPXqUL774AhGhYcOG2O127AV2TiamgQXEClYvIAAKJZ/rrx/KDz/MKlFWVnYmE//xKkNHdKZ2PVi0aBFDhw496+vctm0bdevWJSQkxLV7WjErVqxgxIgRZ523RqPRaP53EJFI4BugHuAEJiul3heRWsAPQDRwGLhZKZXuIf01wPuAFfhCKfX6+ZBTK7uaak384aN8/dVcEhOS6NOvK8NHXI2fX9ntegGXpbN3796EhYVVmO+prHymvv4bOUUpNO7kS4tegbQfEETbLtEl4h06dAiAAQMGcOWVVwKwb+MR3vlgOvmn7CXi1rs7nxYtmmO1WnA4SvbaT2TuZflPtRl5fyv27dtX6et359lnn+Xll1828jtxgokTJxIYGMj+/fvZsGEDDoeDXbt20bZtW5o3b46Y2xVPfWERK7/ahLIrvEK8uePla+g7ssNZyaDRaDSav4gC+ftYdouAiUqpLSISBMSIyFLgbmC5Uup1EfkX8C/gKfeEYiw4/zFwFZAIbBKR+Uqp3edaSK3saqotK1ds4M7b/klRYRGFhUX8uugPPnzvG5b+NpWg4MBy00VFRZVZ0qs0mzZtZWXsHJKTMvFd78ctd/eHYJg9ezYjR450xfPz8wPAbj+t2BYVOkBK76IG27Zso1uPbgwY0J8lS5aVCPMSP+wFRTiKnGRlZfH666/Tpk0bBg8eXOkNISwWC7fffjvTp08HYOnSpdx44400bdqUpk2bkpGRwfvvv8+MGTNc9XBiSxG7ZydicZquFxl2pj4yn52LVtFpRH0KCh1kHMlk2CMPVUoGjUaj0VQflFJJQJL5O1tE9gARwDCgrxnta2AlpWzZQg8AACAASURBVJRdoAuwXyl1EEBEZpjptLKrOTtWrlxJenqZEQTAUIJ69OhBnTp1LrBU54e8vDyWLVvG7B9/pWfvliXCLFYL7733MZe1LbvGbE5OTqXyT05O5ZpBt3DqlBG/ecdwcnPzCA4OYPfu3eTm5rq23i1e4uvAgQP069cPgKYdIz2ukehM8MHhcNCx4xVllN1afsaEtJjfkxl2eztOnjzJli1bSEtLY/To0WXyKo+mTZu6fqekpJQIq1GjBqNGjWLdunUcPnyY+Ph4qA3Ro4W8RMg9DDn7DCU9L9dC58H1cDoVJxKCmfnRZ9w8flyl5dBoNBrN2aJAXbB1dkNFZLPb8WSl1GRPEUUkGrgC2ADUNRVhlFJJIuJpuDQCSHA7TgS6nguhS6OV3f8B7HY7q1atwtfX17UpgTsZGRnUqFGDPn36XATpzh6n0+lSLC2W06voJSQksGXLFsLqBlNU5CiRxsvLitVm59DBvTgcTgqLFAEBQa7wsLAwateuTUV8++2PBPj7MGBgV5o1i8Lb2wulFEopbDavErKcOnUKgICAgNMy+Nq476MbmfTgbBxOhcPuwCfAm4GXDedw6nrCwurSseMVxMRsBaCOf3usVis+Pl70G9CDBx64A6fTyQcffMDhw4fZtGkTnTt3rnL9JSUllTnXvHlzmjdvzjfffMOhQ4dIXa/wDhH8G0FAE6gzADK3QppvJovm7efz/+6iaZcA/IKtLL35Xwwb1Z8GNXwIsFmoHdWYWg0jADiWeIxfp86kQ7dw8nMLWbv6KI+/+WSVZdZoNBrNBSVFKdXpTJFEJBCYDTyqlMoSD6OXnpJ5OHdetHit7P4P0bNnT5ffaDFOp9Plx3kpMW7cP/l66g84nU5EhOE3Xcu3335aQtFcsmgbiQmnrZeNm4SyZOUE/Py8sNmMzRdycwr5aXYcd9z9sCue0+lkxowZHD16lKKiIoqKirBYLFgsFhwOB3a7nbH33oSIUFRUxM6d+1i2dB1Op+KNN58r0aHYvn07AK1bty4hf4drWvLq7w+zZuZ2slNzaDugGW37NSU3dzj/93//x5Ahg0g/5oW/JQrlVFhtVlq2iWL8E4aLhMViYezYsbz33nusWrWq0squ+8YSqgLLQGFhIQCZ24zFuNNWQ9R9RpqQKwRQbPnzKB2vq+FKE97Sl5gd64gBbFYhLHQ9wbYAmrbrQpBK4NYJbfEJsOIoUrQbUI85H33G8L+5NTgrK4slS5YQERFB9+7dK4yrlCImJgar1UpoaCh16tTx2LnUaDSav8zfx2cXEfHCUHSnK6XmmKdPiEh906pbHzjpIWki4L6nfQPg2PmQUSu71ZDc3FwcjtMWzWLF5e9CVTYx8Pb2xsfHBwCHw0Fubi7PP/8mM2fOIzDQH4fTuM5ff13O3aPH8/Enb7jybhgVzrGjaTjNl8KTT19dQtEF8A/w4tphTcnJyXZZeDMyMoiNjXWVb7VaERGUUlitVmx5dg6dTGHr9lh27dzvysvPx5suXU5P3EpMTGTz5s2IiMflwkIjazBsYklremBgIBERERw9epSlq78lfn8aifEnadU2mo5dW+LeWw4ODiYwMLDS7hcA7777rut3zZo1y41X3Gbq9wok6Y9TWBzCoU8VcY4jWOo5uGqE4dO8Y+VJLu8bhlKKw39mkhon3PVYNEF1bCSdzGXf8RT2Hv2ZoEBvWqXVoXnz2kRF1cBqszJkbDPmfDWX4WNurLT854vn7huHI0NQRYr/zv2MkydP8vPPP3PkyBEAdu3adUZlNyMjg59//tl1bLPZuOuuu4iMjKwglUaj0Vy6iPFR+hLYo5R6xy1oPjAaeN38/5OH5JuAZiLSCDgK3Arcdj7k1MpuNSMuLo7vv//eY1hFW8leSKZMmeJxCN0TVquVxx9/HH9/f6ZPn86hQ4cICbExYcKdHuO/887pZ+2lVx9lzJ3PkJ6WiVLQuVt0CUW3GJtN2LVjG1269wJOux60a9eOG264oUTcgp17OfnfD7l28SoO5+S6zvtZLPSIqE+HDpcDsGXLFhYuXIhSimuuuQZvb29OncrBYrHg7+9X4TVfc801fPnllyxbtpT777+/wrg1a9YkOzubjz76iFtuuaVKftePPPJImXMFBXb+WLUJq9WQsXZnhTM1lGO7jhOXv4ckZyodaxv7IyunnV/WT+VkUScGDOhH4/Y1OLBvK47MRlx9k+G+UGB3sGFNCkn5djZuOMrGDUcJDPSmbdswmkTXJvnIPpxOZwmL/IWkoKCAZ0f/kwUrUykqNCzdOwc8QMfe4YCx0UZxx+dMFFvKBwwYQFhYGL/++is//vgj48aNc/lwazQaTTXjSuBO4E8R2Wae+zeGkjtTRO4BjgAjAUQkHGOJsSFKqSIRGQ8sxlh6bIpSatf5EFIru9WMNWvWANCkSRNatjw9OctisZQZSr9YZGdnExkZyeWXX15hvKNHj7Jt2zby8vLw9/cnOzubsLAwTp40RkMyMrJYt9ZwEwirW5umTSMJCTGss3Xr1qVd+8uI2TGP1X/EcOJ4CieT0mjQoKw102q1EBHZ0HVcvIJCWlpambiWwAC8Uczp2Z3P9h/kp6PH8BILo6IieeBWQzFevXo1y5cvx2KxMHLkSES86N3rOmJidiACffteyeTP3yE8vJ7H627QoAEhISEkJSWRmppaoQ/xTTfdxPfff8/x48f55JNPaNGiBcOHDy+xU1t55ObmkpNdwIyvlxK35xAhobBn314aN61LQKAvIoIjM5/L2qXx7sr3cTiddO7YjB/nDOG/H24jPf0Uefl2Vq9eS9u2bahbty5JuXvwq3naVcbH20qLqBB6tgsjLS2P/ftTOXQwnQ0bjrJuXSIFBXZuvG4M/XoM5NFnPHdgzifPjHiQn9Yarh0+flZ6DoqkfsPTPtzFG3BUheDgYJo3b05AQABffPEFb731Fs899xyV9GHTaDSailH8bdwYlFKr8ex7CzDAQ/xjwBC340XAotLxzjVa2a1mFFvIOnbseFY7bV0IcnNzKSwsJCMjg8jISFq0aOEKS09PZ//+/eTn55Obm1smbXZ2tut3SEgQXbq2pUaNoDJW6xYtWhg7lYnQu4/hzzprxlRati7EP8DLFS8/r4iVyw9w7fUDXeeKfS0TExPLlG+LaoClTiiBhcf5Z8vm/LOluaqDjzc1rruaLVu2sHz5cqxWKw8++CA2mxctmncnIyPTZflbsWI1/frewM5df7B/v+EG0bJlSReFQYMGMXPmTObNm8c999xTbl0GBwfzwAMPsG/fPubNm0dsbCxvvPEG/fr1o2fPnmXi9+nTh1WrVgHw1ltvsej7g5zKKqBRq2CuaFCPy6+IRilFRnoOG9fFcWhfAsmZu3Ao48X6xacPsWq9YZVPTUt15RsYGGS4MhyO5+CJOMCoF3u+k12bM+jZIpTQUH9CQ/3p1i2SvLxCtmw5xjdfbeKKzo1YtWE50T804IZb+pV7reeDhHzjFRgY7MUNdxudw81/HKNDj3qICD/88EOl88rPN3a+mzt3LoWFhXTs2JGGDRty5MgRXnrpJVe8a6+9lg4dOlw0a7ZGo9H8r6GV3WrG4cOHAWMzg4KCAtq3b39R5Ni+fXu5rgpKKQoKClizZg02m40ePXqwdu1anE6ny7/WnaVLl1KjRo0yS2WJCLVqhZCTk0diwnHq1gsnPLwm+fn59OrVq0w+I269m+lTP2bIsCbYbBasVgsrlx/gyl4ldww7efIkdrvdoyVORKj1nwmkvfo+zpMpYLWiHA6C7rgJS4sm/Pzaa1gsFu655x5q167NpM++pqCgoMRkMIfDwcmTKTSMbE72KcN6HBoayqxZP9CpkzHptVWrVgQHB5OYmEhKSgqhoaEV1nezZs144okn+O233/jjjz9Yvnw50dHRNGjQoES8vn37EhgY6PItHTKqMdmZBQSF+KCUYuvmg6xfs5eiIuM+FBSm4VTGssBKQdPoeixZZSyB6L52sJeXDafTSdNm0ViUocQV5DrISnbS+447+WPeD/QcHoWj0EmhswinUvz3hQVs3hRP/6svp33HRrz16ucXXNlNzzB8k4sVXYC64QFYrBZOHMqibqNg1/lff/0VMHxxr7zySvz8/Dh8+DCbN28mMDCwROds4cKFLFy4sERZwcHBZGVl8fPPP7Nu3ToaNWpEjRo1CAkJcf0FBQVpJVij0ZwB5XH5Sk35aGW3mlBUVMTixYvx8fGhoKCALVu2sGPHjoum7C5evJiCggK8vLzKhNlsNmrVqsWJEycICwtj7dq1FBUVERwczLFjx9iyZTuZmZmEh9enTZtWxMbG4uPjg9Vqxdvbm4iICPbvO8JXX/1AcnI6IsK4B0fz0EOjmTZtGlFRUeVutHD73Q+Tk5PNrj+30yAyqoRF1112p9PJwIFlwwCsdWoT+u6LFB05ijP7FF5NorH4+bJkyRKcTic9evSgfv36AMTtO0hubtnJeLm5uWRln8LpNMJyco4wYMAgjhw5SEhICABDhgxhxowZfPXVV9SrVw8vLy+8vb3x9fXFz8+PwMBAAgICCAoKIjg4mKCgIPr164e3tzfLli3jwIEDZZRdgE6dOhEZ2ZDPPjO2Rg4KMSYAigjtOzaibfsocnMLiNm4nw0bknj2uX+5FLCMrHyGXR3F9z8doE2bNiQlnWD16rWsWLGSQYOuYtSoW7F4+bFvqwNv33o07NgZm48XA28fw+TXPgdnOmt27WXZ0j0UFBQBcHB/Em3aNgTvAo/1fT6JivAnMfH0BL9vP/iT/tdHA1An4vRycT4+Pmzbtg2lFHa7nfDwcFq3bs306dMpKirCy8tYcs7Pz6/cyZdNmjQhLy+P9u3bs2bNGnbv3u0xrpeXF6NGjaJRo0bn9mI1Go3mfxSt7FYTNm3axObNm+nTpw99+/Zl8eLFbNmy5aLK1LFjR4YMcbnm4HQ6OXXqFDabjaNHj/Ldd99x7JixykjNmjVp3LgJzz33omuzhpgYWLDgZ9Ol4HAZ39XnX3i6xPFnn30GGC4AFREQEESXbmWH+HNzc1m4cCEHDx4EqNCaKiJ4RZVUJGNiYrBYLK7NIwA6dWxHYGCA65rcUaqoxLHD4eDHH2dx772G20KLFi2oX78+SUlJLpmqQlxcXLlrJ+/c+Sf5eUX4+pV8BYgINpuV4GB/+g28nH4DS/pVT/42jntva8ENg6KY80s8jRpFsXnzJrZv28bhw/GMG3cf6bn5/PDHn4wdayi6xdz/9H0kHD7BM5dfh0K5rN1HE1IpKCikcYtQnnjiJd5889kL5t96dNcuwsKjAVizxFjb/NiRbMKjg7B4n3aNGTRoENnZ2TRp0oQvvvjCdb6oyLiHjzzyCIGBJXflKyoq4oMPPnC53mzdaqybvHfv3gplKiws5Mcff+TBBx8kKCiowrgajeZ/kL+Rz+6lglZ2qwFKKdauXQtQZl3P4o9xRWnPFqfTicPh8KiYeMr33Xffda104E50dDQ33ngj//jHox6VQi8vL5YtW84tt9xcrixpaWmcOHGCmjVruqyqlWXPnj38/vvvHD9+HDAUvnbt2rl2P6sMe/fuxW6307x58xJW5eE3XcuLL71NQYHdtZyXzWbFXpiPUiWXhMvLy+P48RMlzt1///04nU7sdjt5eXnk5uaSm5tLdnY2OTk5ruP8/Hzy8/MpKCigoKCAjIwM10S+0mzZsoXVq1fj42vDUeRkxfzDZGcUMHxs5Xy8v/ju9ISt8WO70qGlD998vZXDxxzs2ZlEq8uM+t+6dWuZZbcio+vSvVNX1m5eDxh1XVjo5M9t8XTq2pQvJ/1C1y7tGTHy+krJ8ldZtG8lDw++A4CAQC9sNsHbw/Dg/PnzAaOtgNExcX+2Siu6YIxgPP7447z88sse3XMqIi8vj2nTpjF69Ghyc3M5fPgwycnJKKVwOp14e3vToEEDoqOj8ff3P+edgzW/r6F338FYLMb7xKnyWfLzLAZcczVKKRwOB4WFhRw4cIBatWpRp04dj6M4Z8OumD188d5XANzzyN1c1vnvMbFWo9FcumhltxqQn5/vUiKLJ2pZLBbsdjuvvvpqpfI4Gz/BM21G4Z5nsVUXjNUGLBYLPXv2pEmTJq54xTuhlVYMRE6vkFAeixYZkzkHDCgz+dMjTqeTP/74g/Xr17smFhWXfdVVV5VZU/VwzBEmT5jNwf1p+PvbGHZvN4b9+7QFeePGjQD07t27RDofHx9Wr17Ic8++zpw5P+PlZaN3n27Mm/cDpfshfn5+9OpV1uJssVhcu99VtDauO1OmTCEhIYGsrCyCg0/7nebn57Nw4UJEhDFj7mHCmPfISrMjFmHW53to3CqAiEZe5OcXMmxYW67pEUX+B3Pp+WEi9br50LNXtxLlzJ60gzWH93MkSbCIjU3rY2l1WX28vLy4/nrPCuu8Ze/TOKIfp9yWbjt5IhOAO8cM5OOPp1wwZff48RTmbT7E7ZdF0r5HPf5Yt5lVMYe5vG+EK87111/PqlWryMzMdHVY5syZ4wp33x3PE88++2yJ4xdffNH1+5lnnsFms5GSkoKIUFBQwOeffw5AcnIyb7/9titusSuPiJCbm8v69UaHwWq1YrVaCQkJoW7durRq1YpGjRqd8Zkpj4yMDPr0H4bVGoCI8WyKsrF6wzpWb1jnMY3h3uEkskEDruzZ7YwrrZTHE2P+zXtfn14L+qPpHzLhzkd5++vXzio/jabaoi27VUIru9UAPz8/7rrrLpKSkmjTpg0AnTt3xs/Pr1KWW4vFctYfJ3dExDWELyIuWUrTtm1bunTpUub82LGj+eabaR5WYRCuvvqqCstOTk4GKnY9AMjMzGTFihXs2rXLZZVu2rQpgwYNwm638/nnn5dZheHI9kQeHzSJQvPdkmO389X//U7C3hOM/+YuAOLj4/H19SUiIqJ0kYSG1uKTT9/kk0/fBAzFYNCgeNasWee6Vn9/f7p370bv3mUn1p0NLVu2JCEhgZiYmBJuFRaLBaUUgYGBNGwYwZxlb7J9SxzxB2Np3jqI5q3CgHzAiT3ZSvI3KxDq8csbfZi0bz9KKZcVMTs7h+krVyKFp3dRKypy4uXlVWJTk9JYLBYCg/xLKLtHDp9k/ZpYOnRuQt9+V/D111/Ttm1bwsPDqVGjBj4+PufFteFownF8fLzIyMghINCX6MZhHD542iI+cOBArrjiCtq1a8crr7yC0+nk2muvdfnarlixotIbpBTz/PPPlzlX3G6//PJLj2nGjh2Lv7+/y5XHbrezf/9+9u3bx/HjxwkICODAgQMkJyezc+dOwPD5ruo20vHxibRs1gGLeCMihIfX4W4Pm34kJ6cwcOAAfl8Zw5rft1G7TjD16tfAZjVWowgNDSU8PJyjR4/i7e1dqfWft63bwbtfv4ujlHvP+9Pe445xo2jf/a+/ozQazf8mWtmtJjRq1KjEhJYaNWp4XHrqXOLl5UWnTp2Ii4sjNTWVBx54gLp163qMa7FYCAkJITMzs9zJY507d+b555/l+edfwGbzcik38+fPPeO2q3379mX+/PlMmjSJoUOH0qFDhzJxZs2axa5dxnrVNpuNDh06MGjQINeatMUW3tLKy5TH51JUqhPtULDs51hGp5zCK9BYiaBePc/r5pZGRFi4cD6TJ3/OlClTARg79m7uv/++c6bQdejQgaVLlxIXF1dC2S1WPJKTkzly5AgNGzakfccWtO/YokwefnWhwROn6/FlSlolU1LSKMgOxGI5XTm+ft40atSIuLg4du3aVW6HZ8Qt1/DR+9MoXp6xsNDBpvX7iItN4MYRvUhPT2fBggUl5G7QoAHNmjWjefPm1KpVyxXmtBeRvHQrqb/vxBbsT/0buhHUJqpS9dSkaUPs9kIWzt3IveMGcf2NXcg/ftq9ZPv27Vx55ZVYLBZEBKfT6VoxAwy3hqSkJF599VVsNhve3t6EhYXRqVOnEkvqVZZia2zxRNNipkyZ4vo9btw46tatS+vWrUusna2UIjY2llmzZuFwOFi0aJFrxMNisXDffffh7+9PUFCQx3Y2b94i7h79DxzKeD7//Uz5G5rs3r2HP1Zt4mi80ak5sN9wAfLytnHX2H68/da7xGzZTP/+fV1pevbsSZ8+fVxbb5fm83engFJERITTr18f6tYN4+OPJ1GYX8jkd77kkx/fP0PtaTT/KyhjeRxNpdHKrqYEWVlZbNu2zaOP4bZt2wgLCyM83NhdyuFwYLfbSU9Px2KxlKvolmbBggUEBAR4VAaefPKf3Hnn7SxduoyAgAAGD76mUrtPXXHFFdhsNubNm8eCBQtITk4uMVFtxowZxMbG4ufnx8CBA2nfvn2JD65Sik2bNgPG0mPuFsz9sSl4eq2IQOzqA/g3N3wV3RWwM+Ht7c348Q8zfvzDlU5TFYrdHkov1wbGRglLly5l48aNNGzY0EPq8nn66ad57TVjSLlRo0jq1Y/n5IkMvLxt2Kw2Pp38Eld0bElcXBy//PJLucruxCfuYfaPv3LsWDKCoMx1fE/lpvPIhIeJjAzn2LFjpKWlkZWVRXp6OvHx8SxevJjFixcTGhpK8+bNada4CelvLCT/0Emc+XYQIfW3HUSNG0z4iDN39mrUDGbIVb2Z8M+ObNp2lPgjGTz1Wi/ee99wERgwYAAffvghGRkZOJ3OMkri4MGDmT17tsuH9dSpU2RlZbF//35XW/PU8SqPYt/fPn360L179xKdi2KKJ2LecssthIaG8vHHHwPw1FNP0bJlS/7zn/+QkZHB6tWriYmJAQy3nUmTJrnyaNGiBa1bt6ZFixb4+PiQm5vH2DETyMvLJyysFkOH9nXF3b49llWrNpGddYqHx4+iRo0Q+vTpxbw5q1Aqy1Un3vhRt6gJhzYU0KZ/ML2uLDlKsXr1alavXu0qPygoCD8/P/z8/PD398cWYOXmUTfRokVzV5rLLmvNls3bKhwp0Gg0mjOhlV1NCbZu3crKlSvLDc/MzGTfvn2u42Jr15l27Nq3bx9+fn5kZhq+mevWrSvX8lW/fn3uuqvqu2kVD3tPnjyZ9evXc/DgQcaMGePabCEoKIjx48eXkTUrK4v+/a8iNjaOiRMncPDgIa64ohO//baMmjVrEhLiQ2Zu2Yl+TgV1m4SyfpcxObCqy7ylpqQzYfwzLFu2hMDAYJ548jEeeOjc7SJWt25d4uPjSU9PL+HrW2z19bRDnCeSkpL48ssvPU5GHDd+OLG7jxPRoB533DWMhlFGR6hx48YcPHiQpUuXctVVZV1QgoIDidkxn/fe+ZLp384jLy+XQUN68vTTj7h2louIiCjjFpKWlkZcXBz79u1j/fr1rF27Fq8wRW2LEJpipXaqA6+CQuI/XUTYoI7Ygsr3W/353Y8JOLSbLh2aEFLHm/gjGdSs6etSdMEYIUlLS8PLy4uIiIgy6zdHRkby6KOPlqmvFStWsH//fhYsWEBkZGSlt3EeOHAgW7duZf369XTv3p3nn3/eo8ILlNnw4o033gDg4YcfJjQ0lKFDhzJ06FAAjhw5wsGDB8nNzUUpRVxcHLGxsS4ff3//AJo2bUiDyLq0a2c8l/v2xfPjzMUlypj03mRuHj2SRo2iuWF4Hz5427C+CxYaWFpjwUbiTjvRVzjwC7awZ3U6rXrW5M8/d9G27emOT2pqKgkJCeTl5blcrWpFBxPiCODgrt3M+GkhEydOYOjQIWyL2cGYh++qVP1pNP8T6NUYqoxWdjUlKP7wPPfcc2XC3HeB6ty5M4MHDyYhIYHNmzeXOxnG6XQye/Zsdu/e7Tpns9no37//OZbcoHbt2kycOJGvvvqK48ePuxSA8hRdgIkTn+DPP3fi42P4KWZlZbNnz14mTHiMb76ZysiJ/XjviYU43My7FiCyXiCRbSP4eY2xk5gnf93ySE1JJzqqJTm5mSgcnEiFB8ffx8rfVvP9j5POnEElaN26NfHx8cTExJRYM7h4GTM/Pz+cTicrV2xg7Zot1K0byvCRg6hdu0aJfCZPnuz6bbPZXJO0AB56+D6PbikjR47knXfeYe3atWRkZHDjjTeWieft7cWT/xrHk/8aV+lrqlWrFt26daNbt24UFBSw6vnPOZx+nJRQG8fr2xCnolaag0YnhMztB6nds6xledmCpbTasojBza2oMF+aXtmcn34yVllo3LgmMTHGZih33dWOWV8YqzA0bdqUm28ufzUQd+rXr8/tt9/O1KlTiY+Pr9LkT39/f2rWrEl6errrXGkf39zcXN56661y8/j444955JFHSnRwGjZsWMKKP2TIEBITE9m1axcbNmwgOzuLa4f2pqDATlJSMvXr1yEjw1gyzXgnOBFnLnkU8OuvS3jwwZIuDkFSG8Fw9VBOiPkpE58AC06n0Um0iIVvP9nI088/wNiHTk8+fGLM/Xzz8yosVis+3t7k5OTg6+vF1Vd04PjxE0RFNeSeEffQbUBZH3+NRqOpLFrZ1ZSg+CM7bdo0EhMT6du3L926dcNisdC7d29+//13wFjXd9OmTdx3330A5OTkkJmZ6doQ4ejRo2zdupXt27dTVFSEv78/o0aNIjw8HIvFQmxsLEOHDmPlylUEBwczfvxDPPnkP10KkSoswllYhNW/Yl9dT3h7e/PAAw8wffp013ByeYouwPffz8But9OuXVsAEhMTsdvtzJw5i6+//oq+Y7tzNPYEs7/chNN0lYqODOLFXx8EjC2MbTZblZSaxyc851J0i1HKwQ+zvuathOdpEBle5esuzeWXX84vv/zCgQMHXMpuZmYms2fPBowh+huHPsi2rXvIycnD18+HV178mJlzP6Rrt3YALuuvr68vTz31FADvvfeey0Jfnv+1r68vY8aMYdq0aezevZvY2Fjq1KlD165dz9lGJz4+PkQHhhKwNgGl7GSGWEgJtXIs3MbmUAsJMb/Ru5bQsmVL173JTM8kbM3P1GtnkmC/zwAAIABJREFUQ2wCSli/MYGUlFz69otm5W+HXfnXqOGH1WJcX1WXDoPTq5FUda1cd19dT/j7+3Pbbbfx3Xff0bJlS2655RaXjMUrpHzwwQeu+J4mxIkIkZGRREZG0qtXL9auXcuTT7zC3r0HqV8/lNF334CXlw1Q+NochNWvwYnkAuynoKDA2Dlv9597aWKrRZA1iPQiKxY5vS5xboaT3AwnYc0MF5/atWtSZD/FzGkrXMru8fjDTP/1dzIySi5HmJdnJaBjG5wpViRauPGe66pUfxrN/wR6B7UqoZXdakBycjKffPIJUFL5aNCgAaNHj64wrVKKjz/+mNTU1BLnDx06BBhb9W7atIkJEybQr18/WrduzZQpU1xbxRYvk1RUVMScOXMIDg4mNjbWZf0TEVq3bs1NN93k+vgnJibSteuVZGVloZQiJyeHV199jbi4OL785BOOf/AD2X9sRTkV3g3CqP/Ybfi3rtpuUk6n07V18n333Vehm0VhoWF9atasKYDLCu2+jurtb/w/e+cdHkW59uF7Zks2G9JJo4TQW2IIvVelSpEuRQREUdRjP3o8yFE8IqKiKCCGo4KUUARpUqWHTkInEkggkN7bJrvZ3fn+WHbIkgTSQPzc+7pyZTPlndmSnd887/P8nmGMmjWQmJM38PR3x6t+zWL7F1XYY3TX7h02QteKIIisXvErb7/3UoXGK42783YNBgPfffcdZrOZgQMHsm3zISJOX6KgwFKYV1hgEVlTnnmX81HbEEWRTZs2AVQqEu/n58dbb73F7t27iYyMJCkpiU2bNrFjxw4aN27MiBEjqvwcfYd2JP3AecyFRbhlm3HLNlM/tojUxjWIdzezbt06wOJX7Ofnx/fzvmZGXRFRKfBboppTmWoghRYtvDh44IY87ptvdSLmcjbjZoxg/vz5lRK71oLH+6X4FOfmzZvodLr75n83bty4hIgtXgRanLLSIIqjVCoZ9lRv4M777O9fixkvT+WLLz7CbDazffsOTp06Tb16/nRq2oXFPy1Hr3LgfGEsRZIJBymfmqoGNuM262rJQfb180Upptrk3q748hsKCgzcTVGRiVPnr3A15ixff/01x44do3fv3tXm42vHjp2/H1UWu4IgaICDgMPt8dZLkjRLEAQPYA0QAFwHRkuSlFnWOHYqT37+nUYMVkuv2NhYuTvZvZAkqYTQbdOmDa6urtSvX5+1a9fKxTnWIrT33nuv1AtoXFwcYLlwNmjQgJCQEBo1alTCSeHrr7+xydUDy9TsmjVr+Zdzc8wxCUhFloui4UYSce9+S4Pv3kVdq3x5j2DxQTUajbRr1+6+3rT9+/dj27bf8PT0wGw2k5qajiiKPP54H5scVbVWTbMeto0mzGYzRUVF5fa/teLi7EZSamlrJPxqla/Qrzz4+fkRGxtLaGgoSUlJmM1mQkJCaNeuHe++uUAWusXJy83n8qVrtAxsLAv+Nm3aAJYblbvF1L0QRZF+/frRr18/0tPT5UjzhQsXGDp0aJmR4fLiEhSA/7T+3FiyHVGlBElCrXVgwPvPoannLUc6v//+e5RKJSqViTNGNZFXHUgzWG6+ArV6sjL1mG9HSnx9a1CQZ2btd1f514JBQOUiu0VFRRVy19DpdCxbtgygRG5webHmD+fk5DB//vz7bH2H0prPtGzZjOeft8zcKBQKnnxyEE8+OQiTycR/XvoYl/ECNa64wB4P1IiYMXHdEEldxWMoRAVmycjx327S62nLjapnoywORBwgNLQ106ZNxtvXp8zCMxdnS1Gqo6MjWVlZnDhxgi5dulTotbBj5/8vkj1nt4JUR2RXD/SWJClPEAQVcFgQhO3AcOB3SZI+FQThXeBd4J/VcDw7dxEQEACAi4uLXAy0c+fOEiL2fnh7ezNtmm0Opre3N7m5ueh0OpsuUdao0ty5c+UIFlhyG59++ul7TukfPXpMjgwXp4mrN0XXbiHe5fMlFRnJ+PUAvi+NLNfzSE5O5uLFi2g0Gvr373/f7b/55iuOHTuOg4MGk8mEk5MTjo6OLFr0zX33tTbKKK2D1r149703mTrt2RLRXbXKkXETS/qaVoaUlBQ5up2QkICDgwPNmjWTmz1Yi5PuRpJAobC8f9bnlZOTg5ubm40PbGnT4/fC09OTCRMmyDdKlWlkUhq1R3fDZ0Abcs5dR6F1wOWx+gi3z3/WrFnyzIfRaMQoiuzOckQhSNRxNNHJ08C6W46gy5HHu3Eil0hPJz5e+p78Oa1Mp8GKit0tW7ZgMplo165dlVM9XFxcmDVrFgaDgaSkJHx9fbl58yY+Pj7ye2o0GjGbzfzwww8kJycjCALvvPMOMTExrFu3juTkJFJSUvD29pbHzczMZGnoUpS1ABQ0bulJ7XouHN51k5Rb+WjVNUnWR+Hr0JR8sujY744d34CB3TCaTCQkxMmfgQH9OrNtezhFRXf+D7RaB7q3CgTg2WefZf78+cTFxdnFrh07dipNlcWuZLkKWJOuVLd/JGAo0PP28mXAfuxi94Hh6+tLUlISx48fB5Bb35ZGXl4ely5dQpIk+SLes2dPevToUWJbq+1XZmZmqYLun//8J5s3byYyMhKw2CHdT8QEBgZy/PiJEtEkb9EBUakE411C2GRGf6Ps51Mcs9nMypUrAegT0p1bh6/iHVwHjWvZ9mX+/v5cvRrF/PnzMZlMfPbZp0yYMM6m81hZnDt3Drhzw1FeJj83ln17D7Ni9dLbXaokHFRatm/fWmURmJOTw/Lly+WbHYVCwYABA+TorJUJzwwl6vI1dDrb6K6HpytNm1mmo63veXp6Om5utoVrH374IS+++KKNGLofxSOk1SV2AZTOWjy6lN5WtrTosUkSuFWgsAjdYqTt8eCVr4bRpE1dm3OsTGS3rFbaZWF9v4r7ZVcVtVotF6Y1bNjQZp31dZk+3bZA0NfXF61Wi06nY/HixdSuXZvBgweTlZXF2rVrMZvN3IpOIzYmj3bd6qCtoaLHQH/WfX8ZAQUF5LLpwkd8/MnHeHjYfmYGD+5p83fLoGZcuxbHtdgElEoFer2RQb3b88m3n8vn37p1a44ePUpeXl6Fbyrt2LFjB6opZ1cQBAVwGmgELJQk6bggCD6SJCUCSJKUKAhCqVdEQRCeB54HKuz5aceCJEnyhWvHjh3y8rLsjk6ePCkXmlmxFpbdTUpKSomxoqKiyMjIkDs25ebm3vaNfblc09JvvPEPVqxYaSN2NRoN3sFNEczmEp62gkqJY/OA+44LsG3bNnJzc3HKUnJh1j6LNZrRRMj0HrSaUvbUsJOTE5Ik4enpyUsvlc8dwGg0ym2Cg4KCyrVPcZav+pa5n39A2MqN+NXyYfTTQ6osAPft28ehQ4eQJAk3NzeysrIQBIGQkJAS246bOJjdu8I5sO8ERUVFqNUqlEoly1d9Los0a4pMWW4bixcv5uWXX5Y7e92P4s/PaDRWOY2hPGzduvW+23gX6Jg8czaaWbb5tVURuxVl5MiRLF68mPDwcJo3b/7Aj1cWHh4evP3220RHR7Nt2zbi4+Nlb1+wODk80+cd9AoXbvyRy9iXWqJ2UKBUi7Tq5E2z4MdYEroIL6/7+057eHpyKjKcT6a/So5ejzlDJPGKC7OnhfLypxOoHeBLq1bBHDlyhDNnf6dzp2AEwRdL9pwdO39T7NZjFaZarjSSJJmAVoIguAEbBUEIrMC+3wPfA7Rt29ZeXlhBJEliz549covb3r17yxE8BweHUvcxmUyIosibb74JWC7oZXUos07T//DDDzg4OJRopWtFoVCUO4rVpEkTdu36jRdeeInLl6NQKpVMmDCOr7+eT+aCdeSGn0XS37a3EgUEjRqPod3vO25aWhoRERGIRnDZb8RYrFr1zPcH8WpRi9odG95jhLKn9u8mNjaWsDCLi0ODBg1KRD3Li18tb15/+4VK7VuchIQEwsLCyM3NtYnkrlu3jkuXLrFs2TImT55ss49SqeTn1Z8TceoiR45E4O3tyaDBvXBycrQZVxRFuZHIrFmzSExMtLEj2717N2PHjq3wOX/++edMmTKlQpHhihATE8PPP/9ss6xz58706NEDpVJJVlYWbm5u97zBeJhi19vbG1EUy+1//KBp3Lgx/fv3Z926dfLzt36/uHubSc6w/L/Hx+ZSr7Ero6e1QFTc/zvgvx8v4f1/Wz7z1mh2uydGs2zGDkQElIKSW/uzeafTAt7eMJ6gDgV4emr5fc8ZOnZ0RSAOkSAEoWJ58nbs2Pn7Uq1hFUmSsgRB2A/0B5IFQfC7HdX1A1LuvbedimIVukeOHCEwMJALFy6gVqvL1XFMEIQS223fvp2TJ0+iUqnw9/fHZDLJkb3U1DvVVHXr1sXDw4N69erRuHFjfvvtNy5fvswXX3zBhAkTSkyXlkbnzp05f/4MBQUFqNVqWWQ6vj2B9Hq+ZG4+hLlAj1PrpnhPG4bS/d4pBZmZmbIAc78gIpptc2GNBUVcXH2iTLEriiIqlUoW9/dj/fr1GAwGWrVqxdChQ8u1z4PAaDSyceNG2UGiYcOGjB49WnYAGDFiBNevXycuLo5Lly7ZtJe10rptS1q3Lb3TmSiKNvmqX375Jbm5uTbbDB8+vNznW1w06vV6Fi9ejJeXFwMHDqxwKkjxMfPy8uS0k99//13u1FUcPz8/mwYXFel4V5mc3crg7OxMdnY2ycnJ5e5I+CCIiopix44dNsWI/fv3x2iUcHR0xWAoxFnlj1eNIKIvpFIroAaiIGBt/wyWFJj33/+c996zzJTE30qmdh0fRFGgV6/e7Nu3F7Ckw1z+IQ8NTvINs1JQYpZEfv5+NdM8WpOergMgMjKB1q1rYZYuIdK52tpr27Hzl8NuPVYhqsONwQsoui10HYHHgbnAZmAS8Ont35uqeiw7d5Akid9//50jR47Qtm1bevXqxYULF+T1e/bsITw8vFSPz+I+nlbXhsjISDnKYjAYuHr1qryNRqOxKUK7efMmN2/e5OzZswC8+OKLXL5sMeVfsWIFISEhchHU/bh7elxQKKj5dD9qPt2vjD1KkpKSQmhoKEajkdaNHiNjVxRFpdh66bML7jmOk5NTuZ0GrNHxP1PoXrx4kU2bNlFUVISjoyOjRo0qke8piiLPPvssixYtYvfu3aWK3Xvh5eVFdnY22dnZnD171kbozpw5s9SoqNlsJjk5GVEU8fLystnG6uPs4eHBE088wY4dO0hNTWXZsmX079+f5gYHUpb+yiUpj5jaTjjV9KDH4AE0adKEjIwM9u3bR25uLr1798bf35/z58+zYcMGwFKU9frrr5cQujNnzuSzzz4rtXVyeXkYkV2w5MhnZ2dTUHDvz+qDwmw2s2rVKq5du1ZiXbt27dBq3TEYLN8FuUVxCNm5ZER5cvGPCNSSjgK1wAez3iI/Pw0HBwd+/30De/bsAqDodtrSv95/ge7du8liF8BBry0hXBu8KAIia8LOy8sO7L9O69a1ADOQD9hzeO3YsXN/qiOy6wcsu523KwJrJUnaKgjCUWCtIAhTgThgVDUcyw4Wobt3717Cw8Np06YNAwcOlMWoNQJlnQqtX79+qVPz3t7e8hS3FU9PT8aPH4+rqysXLlxg48aNADZCtzQWL14sP9ZoNERGRpKRkcEzzzxTrUVIpZGens7333+PyWSiT58+dGjdnpULLpXYTqFREvB42XmQMTExJCQkotU6MnjwEF577TX69CnpLZuTk8PKlSvR6/XlKmB7EOh0OlauXClby7Vr147+/fuX+Vp7eXnh4+NDcnJyhYt8rDdGgiCwb98+eXlZTgzx8fH8/PPPNvv5+fnRpk0b/P390Wg0ODg4kJGRwaZNm5g6dSq5ubmsWLGCHTt2sMssIdQDk8Jyk5adl8Xq1atLHOfHH39EJSgoku7c1OTk5JQQtNbzFEWxTJur8vCwIrudOnViw4YN7N+/n2efffahHNOK0WgkNDSUlJQUXFxcyMvLsxH5m37dil6vs9knx5yJu1aiQYP6REbEoTA5E3H6HE2a+qHRaOjSpRPe3jVZtWoVw4YN4syZM0iShMlkYtSoUbIPslsbiZyIO+MGlJE23717vduPJCyXGzt2/o5IINlzditCdbgxnANKVL9IkpQO9Knq+HZsMZvN7Nixg5MnT9K6dWsGDRrEypUr5UiMNSLk6uqKWq3mqadK2lgVr9Z3cHAgMDCQ+vXr07LlnansnTt3lthPpVIRGBgoR22XLVsmW1tZef3111myZAk3btxg0aJFTJ8+/YEVIaWnp7N48WJMJhOPP/64bE3U8Z3+HPtsB0aDEcwSSo2KGrXcaDa8TanjXL16lTZtOtCzZzdatw7hwoVLDBnyFAsXLuDJJweRl5dHbm4uiYmJHDt2TC7+Km/72Ork+PHj7Nq1C7PZjKenJ+PGjSvXdHzTpk1lS7YOHTqU+3jWXO7SPg93YzQa+fHHHzGZTDRo0ACNRkNcXBwJCQmlej4XFhZSUFBA/fr1eeWVV1g0/2uKBFBIEk4FZtpH55LmrOB8/TuzE02bNqVBgwbs/G2HHL2vedWESi+R2FLJip9XyM4kYJki79+/PwUFBRVq53w3D0vsBgUFsWPHDtmz+mGh0+n47rvvyM3Nxc/Pj+eee072KFYqlbz++us89ljrUvd96aUXUKlUuLu7c/TIRR4LbkFhYaacStOoUSPc3Ny4du0a/fr1Y+fOnfzwww9MnTpVHsOjvYLCZBOGeIXNVSn/honpM9vy8/JInJxUtGlrfQ81QOlFk3bs2LFzN/YOan8h8vPzCQ0NlafaExMT+fjjj22iL5mZmZw7d67UKdvCwkJ++eUXOUXB09OT559/vtQOT5MmTZIjtgqFgn//+9+lblMaM2bM4KeffuLmzZuEhobywgsvVEuENy0tjdzcXAoKCsjJyWHfvn0lhC5AsxFt8Gjiw6U1JylIz6Nez6Y0GdIKpWPpnaw++OA/5OXlkZFhmWLv06c3Dg5qYmNjWLhwYYnta9WqJbdJfljk5OSwYsUKUlNTEUWRvn370qlTp3LvHxQUxMGDB4mOjq6Q2B05ciSff/45ly5dokaNGnJOc/HWtGBJS2jbti0mk4m2bdsyaNAgeV1ycjIXLlwgISGBmJgYAOrVq8fAgQPl4jQ3NzeGns4mW2nCXXfn8+yVa6R+WhGb21kEvV6vp0WthiTuMVMoGTE5gOPtzIrE5hLZOdkoVbZfa4cPH0YQhEoV0Vl5WGkMgGz79bBIS0sjNDQUg8FA06ZNS7xODRs25P33ZxIfH4+Dg1puFwwwbNgQubNZ166dadUqGEdHKCy0vGb79u3j4sWLZGVlAZa86ZCQECIjI5k9ezb9+/eXHWRqDS45AzVz/jv8snE5Wq2K519oD1gmEEWhpT1f187fFwl7zm4FsYvdvwA6nY4TJ05w6NAhm4tuYmIiCoUCX19f+vTpw9q1azl//jznz1ty3Ip39YqPj5ejbiqVip49e9K5c2d0Oh1z5syxOd7YsWNtIksVnf4VRZEpU6awZMkSkpKSSnUCKA/R0dFER0cTGxtLZmZmqefRunXrUs3mvYPq4B1Up1zHOXjw0O3OaZYbhLp1ayNJEnl5+bRo0RwPDw+cnZ0xGo2cPn2ahIQEvv32W5599tlq9f2UJIkzR66xb9tpihxSMalyaNy4MT4+Puzfvx9JkvD19WX8+PEVPm7NmjURRbHCeatqtZpx48axbNkym+K94kIXLGkzu3ZZcjNPnTrFgAED5BscHx8fnJ2dWbBgAWCZqu/bt2+JYzn61US8kVhiuVOxvO5hw4aRffoWolKBOt8IxS2ZRYv4Kd5MZdasWXz00Ue4urpW+r0SBKFSkd27i/seReLi4li+fDkmk4nOnTvbFPBZ+eOPP3Bzc+Hdd98CLDn9n3zyGV27diY4OAidroAVK1YxbNgQvLxqynnZN27c4MYNSwtma97/uXPnGDJkCHl5eURHR3P69Gnq1asnb1ec999/H4PBQFxcGt26daRGjRYIqAGP297UduzYsVM+7GL3Eefq1ausX78evV5Ps2bN6Nq1K7Vr1yYqKorY2Fj69OkjR2Zfe+01m8KWGjVqYDAYCAsLIzY2Vl5eVFTE7t272b17d6nHDAsLs/m7skVY06ZNY+HChcTFxbF06VKmTJlSrghvZmYmy5YtsykW02q1+Pr6UqNGDbRaLY6OjtSpU4cGDRpU6tyK4+fnR3x8AtHRV5EkCb1ez7x5X6JUqkhJSbDJze3Vqxc///wzt27d4quvvmL48OEVLvoqDUmS+Oi1/5Glv4GrrwIBAYrg0qVLXLp0CYVCQf/+/Wnbtm2lj6FSqe6bf303ZrMZDw8PGjRoQExMDKIo2txwPfbYY3JjjeLMnj0bQRD44IMPAFi9erX8Ge7duzcHDx60yQEGEOoIaLw9GHzSkm9+vaaaE02coVgE79q1azSo7YtkKhlpFQ0SZvWdbUeOHElycrKcdlIVKhPZdXJyIicnR261/aiQmJjI5cuXuXHjhnxT269fPzp27Giz3axZs0ptC279vunduyeSJPHTT8tJSUnlhx+WERl5kjVr1sjbtmrViieeeAKtVsv69eu5ePEi/fv3p3///kRHR5Oamkq9evWoV68eEyZMsORiq1RyvnJUVBSSJNG4cQtEodYDeT3s2PlLYvfZrRB2sfsIExERwdatW/H29uapp56ysSJq1qwZzZo1s9leq9WWsBM7cOAAsbGxKBSKe0ZoR40aRaNGjUpEeV9//fVKF2KJosiLL77IkiVLiI+P55NPPgEsVfMjRowoNYfy8OHD7N27F0mSqFu3Lh06dKBp06YPtPnAe+/9k4kTn0Wn08lWaCqVmuHDh5V47mq1mqlTpxIeHs7vv//OunXraNasGR06dKBmzZpotdpyCxuDwYBOp+PSpUscOngYyV2HKwoMOjM3zhSSHKMnuL8LQW0aM/bp0WV6IVcEk8lEeHg47dq1Q61Wy9ZlWVlZ1KlTBycnJ5ycnGjcuDEuLi5yOoqVyZMn4+3tbZP6cvPmTTIzM+XXYNu2bYBFwKelpVGzZk25YDIqKor//ve/pZ6bhESBWmRtl5plnn/r1pa8UZcGPmRfScRsvPOZdksTyKhleY+GDh1KixYtOHbsGGARnlWhMhFa6zHvbrX9sDl79iynTp0iIyODgoICm+eiUqkYMWIETZs2LXXf4cOHy24Xd2M2S+h0OvLzdTg6OvL999/RpEkTm23OnDnDmTNnAEva08WLFzl16pRNCk5iYioZaVk8P+XfBLepjaurSl539epVHB0dZZ9nO3bs2KkMdrH7CCJJktwJq2HDhowaNarMBhH3Y//+/YBtKoK7uzsvvfQSV65coUmTJjZCsqwq+8qiVCp58cUX+eyzz9Dr9SgUCjIzM1m6dCn+/v6MGjWKGjVqoNPpWLZsGSkpKSgUCgYPHkxwcHC1nktZDB/+FNevX2fWrA/JycnB19eXp54aSmjoEnmbS5cu8eVHC3njgxm0aNGCLl260KRJE3766SeioqKIioqSt7V69qrVakwmE0ajEZPJJIuM4m2ai5OdbOSPQ/lkxt/pLBf5q47HuzarFqFrdUiwejM3bdqUCxcuUFRkaeBxdxGZn58fiYm2aQU7duzgueeeAyypMWvXriUnJwcHBwf69+8PQNu2beWI4MKFC+95ozVz5kxWrVrFjRs3cHFxKbWhQmnT652/mUTkxxtJPPQHIFGjrifjXx7OsZvnOXnyJOvWrUOj0WAwWPIcbty4wdGjR+nQoUOFo6yVTWOw3hAUFBT8aWI3OTmZX3/9FbDk3ru5ueHt7U3Dhg1p3rz5fc8rKCiIoKAg9uz5nfBwi6XbxYsWtxPpdjV4q1bBbNu2We7CGBwcTEpKSonPzqlTp2jUqBH79+8nMPBO36G01DQcHFQo1DqysjLIz9PdHl/i6tWrNGzY8JGKjNux86djz9mtMHax+4ih1+v59NNPAQgJCWHQoEHl7up1Nx999FGpy729vVEqldUy/V4eRFFk6tSpLFq0CKVSycSJE9m4cSNxcXF8+eWXNG3alCtXrmA2m/H19WXixInlaoxxNwaDgaysLDw9PSv8mr3xxuu8+OJ0Fi1aRF5eHitWLJcvsO08+nDLWEARRWz5LQJ/VQ2WHfqaFi1a8Oabb3L06FHS0tLIy8sjPz8fnU5HYWEhOp0OURRRKBSo1WpEUZT/VigUODo6olQqiYmJQZIkHLQCqSlpCJIWhWARSoIgoFKX/7nkpeew+b01JF9Jpmb9mgz7bBzOXi42ne8UCgU6nY7IyEgEQaB9+/Z069aNa9euUVRURE5ODkePHpXFyuDBg2nVqhWffvop8fHxfPjhhzYCVq1Wl7gxmTlzppzXe68ZhbCwMEaOHElMTAwZGRmcPXtWzitu2bIlI0eOLHU/tYsjHT4bh6mwCFOREbWzJa93YFBdOnXqxKZNm4iPj5fTD/Ly8ti1axdHjhxh7NixFXZmqKrY/bOwCt3x48fTqFGjSo+zd+9eHBwsz2fdug34+vqgVCoxGPScPXvOpt34sGHDgJJFjAaDgQEDBrBo0SJ27dqFp3sd0jNv4eKqJSvT0rzm1s10tm+OYMaMl8jNyyY/P79cTWrs2LFj517Yxe4jgMlkIicnh+vXr7N582bAcqEfPHhwpSuOP/744xIX6MmTJ6PRaB5Ye9Z74eXlJed3nj17ltdee42TJ0+ya9cuoqKiEASBJ554gs6dO1d4bJPJxPvvz+SbbxZiNpvRarV88slsXnjh+QqN4+joiE5nmZK1Ct22Hr24YdQhYRFNJoxcL8phUrd/cDJ9N6IollogVxGMRiPv/+sDHJ3V9Hu+HitWrEGf5Ew9TWfMZolOT5Te3exurp+IZv6o5RQaRQxmEXV0Iid+/5xXlo1m7x93Gi288847pKSkyLZf1sh+ccHas2dPjEYjSqVSfi38538NAAAgAElEQVTeeecd1q9fT1paGgUFBRQWFhISEsKTTz5Z4lxEUbQRvKIo8v7778tjRUVFsW3bNqKjo5k7d26J/Z2dnUsd924UGhUKjcpmmbu7ewmPWp1Ox4oVK0hMTGTp0qV4e3szZMiQcoleQRAqlbP7Z4vd+Ph4kpKScHd3r5LQBUueb0CAxePW0VHDkCEWt42dO3eTl5dHYWFhidkHURRtcrrHjRsHQNeuXS3pVVezOXHsHIOGtcPN3QmNo4rQhbtwdnHixPFzZGTdQqlUlkjXsmPHjmTP2a0gdrH7kDGbzSQlJREXF8fBgwdLvRD6+/uXGdG6Fz/++GOZ/py9evXC39+/wmNWJ0OHDiUqKorIyEg6duxIu3btCAkJITw8nFatWtlEhyrCBx/8h2++WSjbNRUWFvLGG2/j6enJyJEjyj1OcnIyZrPZJj8wyVQkC10rEmbiivLKbL9bUT7//Eu+XbiQ1q1D6NOnJ88+O54FXy0m2XyWVT99h5Nz+VIYlj+3nDyDAvPtlq0Gs0iRWWLFjDCeWjmCzZs3o9VqUavV1Klzb6cKURRLWNIplcoK2XeJolhmWkyzZs1o0qQJ27ZtIzMzE09PT7y8vCgsLCQ8PJzc3Fw2bNggC6SqotVqef7554mLi2PLli2kpKSwdOlSNBoNrq6uaLVanJycKCoqoqioCKPRKP9Y22YvWbIEpVIpp6hYfzs4OMg/Go1G/jHe7hiWmZlJVlYWJpNJ/jGbzaVGi1UqVZWaXxTH2hTGGmmtCg0aNMRstjyff/7zLW7digcgLc3ifBEbe53mzUuK0uLFi9bUluDgYNzd3THWk9i+LY9lob8z4/VBaDRqOnRuwsVzt1AoJKKioujatWu1pPDYsWPn741d7D5ErN23UlJSbJbXqVOHkJAQjh07RmpqaoWiSFu3buX06dOlrmvUqBHNmzdny5Ytj4QFkiiKDB8+nLCwMFatWsVrr72GUqmkR48elR7TaDSyYMG3JXxJdTod//nPRxUSuxcvXgSwKdbRS4ZStzVh5KN3Pids6w+VOGtbvvhiPh4ebjRp0hCz2YxCoaBdh9acPHm63FFdgJvpoix0rUgIxGcqCWwZyIkTJ0hKSiI7O7vSNxbViSiKDB48uMTyjh07MmfOHPLz86v9mP7+/syYMYO4uDi2b99Oeno6ycnJ991PkiS5UUVF2blzZ7maclQn165dIz09HR8fn2q5yR0y5ElCQtoya5bFb/v48ROMGPEUTzzRh7Vrf8Hfv265xzp79izjxo1j1apVtOvQmGPhUWz65ThDR3Sgfacm1K7jRXLqTRwcHCo102PHzt8Ce85uhbCL3YdETEwMv/zyC0ajkT59+lCvXj18fHwoKiqSq7a1Wi1r1qzh1q1b5YoabtmyhYiIiFLXeXl5MX78+DLXV4a4A39wauFe8uKzcGvoRbtXH8evbUCFxmjatKnsq7l371569y7Zkrci5OTkyEVId3Pz5q1Sl5eF1euzefM7bYUdBQ06qWT0XYWKDz57q0Ljl4XJZGLq1Mk2f1ujgZIklTuVpcytbq/w8/MjKSmJa9euya4GjyLr168HqBZbubLw9/fnhRdeACxFd8ePH6dv3740a9YMR0dHOce6NAwGAwUFBXJutjWlQ6/XU1hYiMFgQK/Xo9fryczMxMnJCYVCgSAIct629XFxJEnCbDZz5cqVMj/T5WXr1q0ApXZQrAzp6RmolXdcMkaMeAqTyYS/f13UStcy3S5mzZrFTz/9RGpqKuPHjyc0NBRALpATBIFr0YlkputYtzKc/oPbULuuO1euXKFXr144Otq7pNmxY6fq2MXuQ+DUqVNs27YNLy8vRo8eTc2ady4a1qniX375hQsXLgAWa67i25SF1by9OJMmTSIgIED+2yqUqtoB6tr28xz8z2ZMhZbK/ZSzt9gxYwX9FoyjVoeKiZJx48bx2WefcfjwYdq0aVOlKKObmxtubm4louVgqRKvCFZXguIV6t4KkRtG0SaVQUCkjkpTLSkM0dHRzJjxAoIgsGfPXg4fPiKvCwoKrFDOtr+3RGyyhFm6s4+IRF13EwqlgsuXL1uWPeKV7XFxcSgUCnr16vVQjmed9fDw8LBpxFIWarUatVr9wKLjX375JQaDoVSP24ry3XffVcMZWXj3Xy/Y/G00GtFoHFEp3Pjll82MGDGk1P3uzp8GmDdvHtOnT+fq1avM+ngavt4BuLjWoFVIc44ePUp+fn6FOgTasWPHzr2wi90HTGZmJjt37qRhw4aMHj261Na8y5cvJzY2FkdHRyZOnIifn999x737Qng/y7CqtNaUJInjX+6Sha4VU6GRE/N3MyzshTL2LB21Ws2gQYPYvHkzK1eu5KWXXqr0uYmiyGefzeGll16xSWXQarV8+mnpfq5lkZubW0IInsrYT1uPniSbzBRKhagFNX4KNSfT91b6nK1YI/NKpZJTpyIIDz8KWN4rR0dHFiz4qkLjTV7+HF8MCSXfIGI0CyhFCUeVmWd/fIaLFy/KDSU2bdrEkSNHaNKkCa1bt8bDw6PKz+V+XIg4zuHFS8FBxcRPP8apxr2PqVKpHpoot4rdyrqeVDfWgkEfHx+b/9uy/ofvTlEym80UFhaiVqvL7U9dnhmEc2ej8Pa505xDoVBgMOjJ199k5MiRONdw59LlCOrUKbvoT61WYzAYKCwsxNnZmfbt2xMeHs7jj/eRb/CrWvBpx87/eyRAsheoVQS72H3AHDlyBEmSGDJkSKlC19oJTaFQ8Oqrr5arGMNqTWblXkLXOh36xx9/0L1790oJCJPeSEFaXqnrMmNSKzweWGzVjhw5QmpqKteuXauSvdCkSc/g7u7Of/7zETduxBEc/BiffDK7REeo+2EwGEp9j05l7K/0ud3rWBERESgUCiZPnsyTTyYhigrOnz9PYGBLPvjg3xXullY7yJ9PL89ky7/WkHQ5Ee/GXgye8zQaJw2bNm0CoF69emRmZpKamkpqairh4eGIooiTkxN16tRh4MCB1e4Ju3DMBEbVlRjlDgpBIO6dlzig9mb6VwtK3V4QBAwGg+wG8aCxFoQ9KhFv63OePn36n3YOkiRx6McT7P/+CPmZOmq38OV8fCw9+j6GUqWQz1OhUDBy5FB++20nuXmZtGnTmeTkkq1/rbz33nvyjfrs2bPx9PREqVQSHh5e6U6NduzYsXM/7GL3AZKenk5kZCQtWrQoswtZZGQkYJnaL2/VsbOzs9wgAO5EeUsTvdZoTVJSEnPnzmXIkCG0bFn+oicAhYMSlZMDhtySrWadvJ0rNBZYIk8bN26U/VSrmp8IMGTIYIYMKVnsVBEkSXpogscqFMCSS1u7dm02bSq9U1VFUGvUjPhyYonlV69eBWDQoEF4eXlhMBg4c+YM0dHRpKSkkJeXx+XLl7ly5QrTp08vVxpNeVjyxj+YEACOqjtR0wA3FU66NOKuXsG/UZMS+7Rq1Ypjx46xZcuWass5vRfWyOijInYfBX6bt5fDP52gqMAymxN3Jp52DiGErdjDhMmPy9sJgkBgYEuaNm3Cjz8uJyEhgdjY69SvH1Dm2JMmTWLZsmWA5TuydevWnDlzhh49elS5rbMdO38PJHuBWgWxi90HyLfffgvA448/Xup6s9lMbGwsoihWqBhnxowZ5c7ns4pdT09P0tPTWb9+PYcOHWLs2LHlvrAIgsBjk7tw5vuDGIulMig1KkKm9yz3eQNcv36dNWvWUFhYiKOjI2PHjv3TLdGsiKJYbbZP5TlWUFAQZ86c4fTp07Rr1+6BHi8gIIALFy4QGRlJ3759UavVtG/fnvbt28vb7Nu3j4MHD3LgwAFGjLi/i4UuLZfsG6l4BfuXGYHVxsajbGZbZKQQBZzUAmH/+YQZK34qsY9VaJ87d062rrJ+jgVBkIu7iv82GAyYTCY0Gg2Ojo4oFAq5k51SqcTBwQGtVovBYKBevXo4OjqiUqlwcHAgL88ya2EXuxb0OgOHfzxOUaHRZrloEHi/38v8kX8djZPtja9KpWLatCns2rWH+PjEe4rdgIAAZs2aJX+HRUREIIoi4eHhDBo0qJqfjR07duzYxe4Do3hBWFlR3SNHjlBUVETjxo0rPP4rr7zCr7/+yrPPPisb96enp+Pp6WmznVUkBAcH07JlS1avXk1ycjILFiyQO7SV5yIfPKUrZqOZ88vCMRlMqLRq2rzUi8ZPlq8IzGw2s2HDBtneKygoiGHDhj1SAsOSg1j1KHN56dOnD2fOnOHw4cOEhIQ80Cn7gtvpzEeOHKdz567UqFGyQ12PHj04dOiQTbe10siNz+TXYV+jlYwIgFECfR03Jm4q6U7h5iCgUpSSCyqBoNOXWJyTk8P27dsBS86q9QbEbDbLv62Pre4F1uWA7IpwL6u9S5cu3fP5/d3JSshGVJT8v5QkiL+UzPSfJzB8+FiGDL1zE299/R9/vDeBgc1L7FsaTZs25Y8//pD3P3XqFN27d8fZueKzRXbs/O2wR3YrhF3sPiCuXLkCUGYe2sWLF/n9998RBIF+/fpVeHwPDw+mTJli4xG6fft2JkyYUOr2kiTh4eHBjBkzOHv2LNu2bSMiIoKLFy/y1FNP2XjLloYgCLR+oQetpnbFkKdH7awp9YJYGtHR0fzyyy/o9XocHR15+umnqVu3/L6cD4PExEQKCgoeSo6olRo1alCrVi0SEhL48ssvGTVqFPXr16/WYxQWFtI2eDhJiam88Eo/1GoVbR8bzLdLPuLxJ2wLgay5uzk5Ofcc89chX6EVTIi3NaxKAEV8Ft8Om83Lv8602famQUm+wYyT2vazcl1Vg/wWNdm4cSOurq7ExsaSlJQkN2Lo1q1blW3prJjNZnJyckhPTyc7O5u8vDy5eURRURGXL1+moKAAlUp1/8H+Brj6uGAyll784tOoJvUCatOxQw9MJpOciiOKIrm5eTg712DlypW88MIL9/1fGjt2LHv37uXQoUPysiNHjlTq+9COHTt27oVd7FYzZrOZ8+fPs3PnTtzd3QkKCiqxTVxcHOvXr0cQBCZMmFAiGlsRilsLldZtqrQK6+DgYIKCgti0aRPnzp0jLCyMOnXq8PTTT6PVloz4FUdUKtC43XsbKwaDgTVr1hATEwMgt5Z9lKK5Op2O0NBQsrKyAKpNYJWXqVOnsnHjRi5cuMDPP//MBx98UK3jv/LiRyQlWooIszN11PR2ISdXxzNPv01C2pES2/v5+REdHU1ycjI+Pj4l1t/YF2UjdK0IgMt1PZmZWbi730mPafeP57i5OhR/VyValYgOkVWiH6lKBxAEmw5bGo0GFxcXunTpUq0+wKIoyhZ1pWEwGLhw4cIj9bn8M9E4O9BhTAgn1p2Rc3YBVBolT7zaHYCFiz9m0aKlpKZaOqnp8nU4O9dAoVCQlpbGnDmfkp+jonWbIIYM64NG41DqsXr37i2LXRcXF06fPk23bt3u+z1kx87fGgl7u+AKYhe71YTRaOT69evs2bOH5ORkatWqxYgRI0q1M7K28Rw3bly1GudfvHixhLguazpXFEWeeuopunbtyurVq7l16xZffPEFXbt2rRZ/07Nnz7J161aMRiPOzs6MHz++VPH0sDEajRw8eJCYmBjy8/PJycnBbDZTo0YN+vTpQ6tWrR7q+YiiyIgRI4iOjpZ9fquT7dsOotGo6dy9GZ5eLhgMRgx6S/T08KFTdO1m6/jQvHlzoqOjOX36NBqNhitXrjBu3Dg5FSf+6BVK+0QJAqhFiIw8T+/e3eTl7Xr0YWdiMsdWbSSwlpq9PgGYRAWenh4MGDAQtVpNWloatWrV+tM+H9b/karY8/1/Y+gH/XB01XDox+Po8w14BXgy7D/9qRdyp830Sy89J+fdap20KJVKjEbj7fQSE9diYli9YhufzfmeXXt/wsPz3jUCEyZMYNGiRRw7duyh33TasWPn/zd2sVsNJCUlsWbNGrKysqhRowbDhw8nMLDshgAFBZaOXL6+vpU6XkZGBtu2bZMjplbu5RNa1rl4eXnx6quvcuzYMfbs2cPBgweJiIhg9OjRlUo1KCwsZOXKldy6dQtBEOjSpUuZBXoPm+joaMLCwuT8QkEQ0Gq1BAUF/alTp8nJyej1+gci9lo+VpfO3ZoBYDKaOHLwsryuoKBkzmxQUBCbN2/m5MmT8rLVq1fL3cYaDQkhccOJEvtJEuhMEr4+3vIy/c1kdDm5qLx9kQY9zu7b7XY7depE37595e3+7JQWu9gtiagQ6f9GL/q93hOz0YxCVfp3yz//+U/mzp0LWNqeX7p0Ba3WYt/XMsgfL29Xdm6L4JOPv+Pz+e/e85gODg40b96cEydO0Llz53K709ix87fEnrNbIexit4rs2rWLo0ePotVqGTVqFI0bN75v7l/nzp3Zt28fq1evZtq0aRU6XlkuDG+//fY9p/7uVbAD0LFjR1q3bi2nHfzwww80adKEUaNGlTuP9ezZs2zZsgWTyYSHhwcTJ058YFZC167GcmB/OAOf7Iuvr/f9dwCOHTuG2WymXr16jBs3rlRP3T8Da/e3lJQUMjIyqq3JQ0REhCx0Dx+4SOSpWHmdqBDp83jJDlVKpZIWLVpw7do1WrZsyY0bN0hKSmLz5s0MGTIE78C65ItKnMxGOZVBksAMHFXcZErLpuRcj2fVkv+R7GC2hHxv4+LiQrdu3SrsH/ygsd782NMYSiIIQplCF7ARpNevX2dD2BHGPXvHz9vH142JU3qRkpzCnDlzUCgUPPnkk3L3weKFvPPnz+f555/n8uXLnDhxgu7duz+gZ2XHjp2/G3axWwUyMzM5evQotWvXZsyYMeWuIu7evTv79u0jISGB5cuX4+HhQcOGDe8pvlasWFFimVarlR0NEhMT5eWSJMlRXuvy+4ldsHQ3mjhxInFxcaxdu5YrV64wd+5cBg4cSEhISJn73R3N7dGjBz179rzv8SpDXl4+tXwbkJufIS+rW6shcfFR9923d+/exMbGEhcXR0xMDM2aNXsg51hRgoKCSE5OJjw8nEWLFjFlyhRq1apV5XGLR/qLC12AuZ+/Xaa4GzVqlPw4MzOTBQsWEBkZSatWrfD392fckX+zvPcnOOUbUAhQYIRTqiRm//Y5UZcvsz5sDSaNgINBwkVXRM0cIw2yigj6+kUc6pTvxuTPwC52K0dxGzEvX1d+23yagUPaIAgCJpMZhULEx9dVdjpZt24d48aNo3HjxiVe89WrV9O4cWOOHj1K69atq73BiR07/y+Q7D67FcUudqtARoZFcHXq1KnCdjmOjo4UFBQQGxtLbGwsp0+frvDxdTodq1atKte2Dg6lF4iUhr+/P2+88QZ79uzh2LFjbN68mWPHjjF+/PgSNmrnz59n06ZNDyWaC1C3dhMboQtwM+EarYK6cOZ8+D33td6UhIWFsWXLlkdG7ILFi1mr1bJ7926WLl1K9+7dCQgIwNfXt9LTucHBwZw7d46YmBhefn04e3edo1Ztbz746BVatGhUrjHc3d3p1q0bhw4d4sCBA0ycOJHdu3eT/ZQzkosLTk4uNG1Qn5ZKke3btxEXFwcCNI/TEXTzTvtmFCJZWw/jM314pZ7Lg8TeVKJqFI/OtmvfjLAV+1m9/CCjnu6C2uHOLFd2djaurq4AHD9+XLZcLC6Wc3NzeeaZZ1iyZAlbt25lzJgx9vQSO3bsVBm72K0kJpOJAwcOoNFoaNSofMKhOGPHjuXo0aP07NmT//3vfxQVFcnTu6X1qc/NzSU1NbVEW13rhbp45FYQBPkCpFAocHBwqPDUsSiK9O3bl44dO7Jy5UpSUlL46quv6NatG7169cJgMLB69WquX7/+wKO5VrKyssnKSSl13dkLJ0tdfjdNmzbF2dmZ/Pz86jy1aqFz5844OTmxadMmDhw4wIEDBxAEgX//+9+VFmJPP/00n3/+OXq9nuWr5xAQEFDufQ8ePMjBgwflGYeYmBi+++472e7OalH2xx93fGtrqDV0OZOOa2aB7WAmM0WpWZV6Dg+a4jncdiqO1ecb4N333uDgvktkZmaz/Ie9hLT3QafLJzz8KM88M14Wu3c3b3n77beZN28eAAsXLqRv377s2rWLc+fOERxcPi9vO3b+VtjdGCqEXexWkujoaG7evMmAAQMqFDW14u/vL3cO02q15ObmPpLdg1xcXHjxxRc5deoUO3bskAvY9Ho9RUVFuLq68swzz1Rbnum9uHTxj3usLf+UjvVmYNu2bQwYMOCRiugFBwfTsGFDIiIiOHz4MEVFRRQWFlbaikmpVDJ27FiWLVtGWFgYb731VrlysCMiIti3bx9wp6BSEASSk5PRarW88sorGI1Gzp07R1JSEq6urjRp0gRfByeuTZ5d4t0QNGpqtCtfs4GHzaMW2S1PytGjSIMGDfCr5c3JMxvYu+cYS5eGsnnrBvT6QkaMGEatWn6A5fl5e9ums2i1WsaNGyfPVO3atQtBENi+fTv169cvszGPHTt27JQHu9itJNbOP9XpB/oo07ZtWx577DE5mgvg7OzMyy+//NAaMbTvUPZrLQrlP4e+ffuyfv16Tp06haenJx07dqyO06s2atSoQffu3bl27RpxcXEcP368SnZwAQEBtGvXjpMnT7J8+XKmTJly332s73Hfvn1p0aIFDg4OqNVqMjMzcXd3l4Vh586dS+zrNqgLWTuOIhVacjQFtQqVjycuvR+twjQrj5rY/asSExNDTk4OLi4u9O3flf/9uAi9vpA6dWoRFBQob3fmzDkaN25SYv/GjRszadIkli1bBiB3yNu5c6dNHrkdO3aw5O3aKTf2b/dKkJyczJkzZwgODn6oHbf+bNRqNZMmTWLkyJFoNBpyc3P57LPPOH/+PNkJ2fw2cwuLHl/AsrH/48qe+xeMVRSlUkn7Nl1LXffc1OnlHqdly5aMGTMGQG4m8SgyaNAgVCoVBw8etOTCVoGBAwfi4eHBzZs3OXKkZDOJu+nRowcAp06dwtXVFY1GgyiKeHp63lcU+rw4glpvjscxqCEODWtTc0J/6i94k6S0ND788FPmzfsanU53zzEeJnaxW33Mnz9fdhcJDGyJRqMhJydXXn/tWgx79uylcePSU78CAgJ44okn5L+7dOnCpUuXuHHjxoM9cTt27Py/xv7tXgms/rbVlaP6V5u2bNmyJW+//Tbt27fHaDSyYcMGFnz+NWe2RZB9K4uEM/Fsfnsjx/53f1FVUY6f2seg/sMRBIvTgEJU8fJLb7AkdH6FxrHepNydO/go4e3tLU/3Hj161KYQSKfT8eGHH8o/GzdulKvdy2Lq1KmAxYLtfnh6eiIIgpzCUBEEQcClR2sCvniNBovfpebYvrzy1r+oH9CGT/67gH+/Pxd3t0YsDf2pwmM/SB4VsfuwcoclSUKScjBLCUhSRqW/h2bNmmXTjGXx4sVkZ2fz/PPPoVarycnJpbCwEICGDRvQq1cP2rVrV+Z4xWdaMjIycHFxYdeuXX+570k7dh4YEhY3hofx8/+Ev09YshqxioqKOjD8FcnJybERhJYLpOUfoH379jRr1ow1y8PQuxowDwHxsoTyrEBRQRGHvz1A66fbotZWr5/t1u1rqjzGX0HsAsTHW9qxRkVFMXv2bKZNm0ZoaGiJ7c6dO2fTelelUvHOO+/YzDxotZYuV+ZyFjaoVCoKCwspLCysksH/rl2/szR0NZamwneYMeNfDB8xFA8P90qPXR08apHdhyF2JcmEWToPWIoMJQRAhUgIglDxGoShQ4fSpEkT1q5dC8BXX33FrFmzCA8/wLRp09mxYzfDhg0GoG3b1oSFhTFmzJhSX/Piy86dO4ePjw8JCQn2YjU7duxUGrvYrQTWtq45OTlym+Dt27fj6enJpEmT0Ov1eHp6/slnWXW2bt1aMUs0AcwtwFBfQrkPBJNIekwafoFV94ytbv4qYvdu7ha6U6ZM4YcffiixXVFREf/9738BywyENS0B7hScZWflsuLnTZw4epbGTQOYPHUEtevc6erXo0cPdu/ezerVq5k8eXKlz/mjj+YhSTb9JWTmzPmCefM+rvTY1cGjJnYfBpJ0A4vQLX7jY8IsRaEQKicomzdvTlBQEOfPn5eXBQYGcvToYfR6vewrDnDlyhXOnj1bpn93cTsyq/vHzp078ff3x939z705smPHzl8Pu9itBNYv8wULFtgsT0tL44svvpD/FgQBBwcHWrZsSd++fctsGvGoWh7p9ZZ2snXr1sXJyUm2RCt+vpIkcSviJvlp+aAAyQPQgHEAFNzQo/WsnIvAg8bacKG8Uc5HjUmTJsk2YrNmzbJZt2XLFiIiIuS/9+/fj4uLCyEhIbi5uZGWlsa2bdt56x9fkZebT0GBHvUuFaHfrWHD5kW0aWcpJurcuTN79+7l1q1bVTrXnOzcMj/jmRl/fs70ozY9/lAiuyRhK3StZCFJRoQKFHwWZ/jw4fL345w5c3jvvfcAi893/fr1CQgIkIsf7+di8+abb9p8n0qSxJo1a5gyZcoj0/3Qjp0/h/9fKQYPg79PKKOaiIuLk/1FmzZtSosWLQgODmb69Ok0atQIX19ffHx8qFmzJq6ulq5Bp0+fZt68eTZdzorzqF1srdSsWROAxx57jDFjxjB27FjGjBnD6NGj5Z8xY8YwasRIHE+rUR0UUP8qoNwPFIEpQOK75UvkHOdHCWtL579SZFehUDBgwABmzpx5T7/cwYMHM2vWLBsRvHnzZsAikgVB4OTJ4xQV6dHr9WidHDAaTeTnF/DqjNk2Y/n6+mI2m6t0UzBi5GDKsoabMnVCpcetLh61yO7D+T641zGqdnyrpaLBYCjR3ry4e4c1Racs7u6eNmLECJKTk/nmm2+qdH527Nj5+2GP7FaAP/74g7CwMADGjBlTogPX+PHjS+xjNpvZs2cPR48eJTQ0FH9/f9RqNV5eXnTp0qXS/qkPAx8fHwBSU/qbfV4AACAASURBVFPvuZ1/+wD6zRrAnjm7MBtNmDPMNMqoj6KXmouXL/Lzzz/TsGFDRo8e/chEZKxpDI96ZFer1crOBWazme3bt7Nnzx66du1K165d7yvQik8Hz549m5kzZxISEkJERAQTJve0iSIWFRnZsuEkmRnZuHtYzP9dXV2Jj48nNTVV/jxUlPfff4sl3y0jPT0bEG7PEECHDsF07vzn2749KHH5+8ZN1GlkoGFzy03j9SsZXDljZOC4MX/K+dhSE0iipLB1QhBUpWxffiZPnlxC5FqJPHFKfnzy5En69OlTrpsMtVotN+/Jy8vjxIkTtG/fvkrnacfOX5pH/Nr1qPFohDL+Apw+fVoWuq1bty53q1lrJ7IRI0agUCi4ceMG0dHRHDlyhHnz5rFw4UL0en21XuC2bfuNfv0G0LZtB/773zlyJLqi1KplybW1tkW+F4891Yp/hL/J5PXTePnA64xZPI6Ro0fy/PPP4+zszLVr15g3bx5nz56t1LlUN1axazQa/+QzuTczZsyQH7/xxhu0aNECo9HIvn37+OSTT/jxxx85f/78PUV7YKAlLcFsNpOamsrgwYO5eP4WOp2ewgJLsaXJZEapVPDU6I7s2r1DHs+ae56QkFDp56BUKrl+4ywvzZiEt7c7/vV8mPPpvzh4aHulx6xOHoS4zEhOplM/Jxq2qIkgCgiiQEBTD3oPr8nNq9ce+vncjSjUBxy4cwkQAQWiUD0ttN988035cUJCAga9nmF9hrFw4Vp5ucFgYNO6X8s1nsFgoLCwkOeffx6A7du3y17nduzYsXM/7JHdcnDs2DF2795NgwYNGDdunJzvWRECAwMJDAzEYDBQUFDAhQsXOHXqFGlpaUD15el9+OFs5s37Qm6He/HiJX76aTmRkSdLTAveD2vXoszMzHJtr1Ap8GxQ02aZn58fb7zxBrt37+bo0aP8+uuvnDhxgvHjx1cpqp2VkM22z34nav9VHLRqOk9sS49pnVEoy3f/ZnUXeJTTGMLCwmwu6DVq1GDUqFEUFhayc+dOLl26RFxcHHFxcWzYsAFfX1+mTZtWIlI2YsQILly4AMCiRYv45z//SedOXfjis/9RUFAob9e8ZV16PRFEVFQUn376KaIoyp/1+0X374darWb+/DnMnz+nSuMAXDp8hAWzvyHqejKtmtbllVmv0bBN6YVO5eFBiMvNq0OZ8EoXm/9rQRBQqkQO7VnHuEbvVvsxK4IgqBFph0QKkpSDgBZB8K1yVNdK8e+a0NBQ0m8kcfp8MhrtHVePK5fj+W39IZ4aM7zMcYYNG8avv1oE8dy5cwHo3r07Bw8eJCwsjPfee++RmS2yY+ehYbUeewQQBOEH4EkgRZKkwNvL1gBNb2/iBmRJktSqlH2vA7mACTBKkvTAOg/ZI7v34ciRI+zcuZOAgABGjRpVKaFbHLVajaurK126dOEf//gHr732GlA9YjctLY05c+bKQhegsLCQhIQE/ve/khX79yIxMZEvv/wSgOzs7Cqf2xNPPMGrr76Kp6cnCQkJfPHFF5w4caJSY+Vn6pg/OJQzWy5SkF1IVmIOuxccZPUbG8s9xoOK7N66noSTui5qlR9qVS3UKl/6tB5R4XEKCwtthO6kSZPkxxqNhqFDh/Lee+/x8ssv07JlS5ycnEhKSmL//v2ljlc8f3fu3Llk593g8b6d0WgcqOGsxcnJEaXCkVdf+QeBgYEUFRWh1+vlFIryRPcfBkd+2US/Ia+x4dhVLiTmsvrAJXr3nc65fQcrPeaDELuNWvqVulwQBBq1fDTcSQRBgSj4oRCbIop1q03oWgkKCpIfR0ZepaDQSEADL3nZ3t8vkJCcf8/obnBwMDNnzrRZdvDgQQYMGPB/7J13eFNl+8c/5yRN96C0tMyWMsreQ0CW7C0IDqYDAVFUVMSFvAg/cYAI6stQcWFREF+g7ClQZtkCFtpSaEs3pXukSc7vj5DTpEnapC2Kms91cZGenPOckzbJ+T73c9/fG9AXwRkKaR04cPCX8C0w2HiDJEmPSZLU7q7A3QT8Ws7xfe/ue09bbDrErhWysrJYsGABe/fuJTAwkPHjx1fJa9Qa3t7eeHl5VYvYPXUqEhcX8wrngoICtm3bYdMYOp2OTZs2sWbNGnJzcys+wA58fHx44YUX6N+/P6Bfivziiy9sjhwbOBF2huJ8NZLRzLakSMOlPVe5HW/fWNUd2W3UpD0lkgZBEO86Vyg48vtxnh71ol3jGCYaBqx1HKtZsyZjx47lxRf148fGWl8inzNnjsnPwY3d+O3oj3z62Tv8b9tKDhxZh5+/L4888ghvv/22PCZUz4SnOpgzdxmFGkkOamglyC/R8c6rlY8Y3wuxm3g9w+q5rD1n4H51Z7EXQxEoQFGxjnHje/Bg75bytuBgP0RRILuCiZQoisybN88kdcz48ZIlS6rxqh04+JtwnzSVkCTpMGDxQyzov8weBdZX74u3H4fYtYBGo2H58uXyz0899VSVI7p/Bv7+fhbFmyiK1K1bt8Ljo6Oj+eijj7h06RIuLi5MmjQJHx+faheEPXr0YPbs2dSuXZuMjAxWrFjB7t27bS4WizudgKbYPCKrdFKQ9EeqXddSnZHdT+avREJAEMw/VmE7N9o0hqEjmsHL2cDGjRvL7Xx27tw5AFxdXa3u4+bmZmZT9mPYt/Tt14UOHVuaiCylUkmNGjVo2LAhUPU0hupAXVTEtbR8i8+dibv9J19N+XR+cBQ6rWQipCVJQtJBo6Y9yz32nyB2NRqNif1dsya1CKyt98fVafWf887dmuKiUjBuUvkFe4sXL2bhwoVERZW2IDekNhi4n9ORHDj4m+MnCMJpo3/T7Di2J5AqSVK0leclYI8gCGfsHNduHGLXAgYzftDbbv1dcsI6depE3bp1zXI2XVxcmDVrptXj1Go13333HWFhYRQXF9OuXTvmzJlDSEgInp6eSJJU7cv9Hh4eTJs2jTFjxuDk5MSJEyf45JNPSEhIqPDYgCb+KJzM37parY6a9X1svgZBEKrVjWHDz1uxZNskCAK6cqKHOp2OH3/80WIFu7u7u/x49+7dFvfJyspi165diKLI8OHDK7zO+fPny8WHoO92ZY0xY/T5lPeDmFCqVLgoLQtBL5fKlx/ci8huo5bN+HnlFbIzi+Wug7lZxfywLJK23ay3yv2nYNz8ZP78+XQb+KD887HjF8nLK8DPz4sJE/vi6uZuaQiZsm2wVSoV48ePl3+eO3fu3yIY4cBBtSH9SVFdfWQ3Q5KkTkb/1thxpU9QflS3hyRJHYAhwPOCIPSqwm+lXBwFahUwatSoP+U81XHDFQSBPXt2Mnz4KGJjr6NUKpEkHV988TkdO3a0eMzp06fZtWsXWq0Wb29vnnjiCROLKV9fXxISEkhKSpL9M6uT1q1b07x5c37++WdiYmJYu3YtLVq04JFHHrFqSdRjcmeO/3gabUmpUFU4KagdWos6LQItHmMJQRCqVcQ9+thIzr5v7jYhSRIClkWaJfEaEhLCpEmT5J91Oh0LFy40OebVV1+Vi4CuXLkC6CPmPj62if1nn33WZNwFCxYwcuRIs45WHh4e1KlTR+5+1b17d0JCQu65J21RURFKpdKk3bEoikzs35Yf9l2gSFP6eXFVCjz7SPnR0vK4V+4Hk156AYDLZ/QRzpYdO/D064PLO+QfQ1paGqB//9y5c4f0jAzU6hJ2747g94vRODsr6dy5FW41yu80aSyavb295RoHY4zfIw4cOLg/EPSdacYAlsUHIElS0t3/0wRB+B/QBah8AUY5OL4lLFCvXj0SExMtVrZXJ9HR0fzvf/+T27dWBw0aNODixXNERUWRlZVFu3btLOYa5+TksG7dOtLT0xEEgd69e9OnTx+z/QzWU8nJyfdE7IL+ZjVhwgRu3LjBhg0buHLlCjExMYwZM4bQ0FCz/X3r+TDth4lsmBvO7Zv6VKEW/Zry6Icj7DpvdYvdVxY8x5vvv3e3Na6puB03wLzivGwerouLC3PnzjXbTxRF5s+fz8KFC+VI9NKlS+WUBE9PT8D+lAxRFBk6dCg7dujzubdu3crWrVtxc3Njzpw56HQ6Dh8+TEpKCgBxcXHExcUB+nQJPz8/goODadasmUmkuCrEx8eza9cukpOTEQSBpk2bMnToUNkZ5D/friB9xBR2nr2BSiGg1kqM7dmcF5f9tS2Hy6Nlxw5/9SX8ZUyfPl1erXFyUtKrVycKC4rx8NCn22zevJMXZk23mn5jbHlnWGVw4MABJjUr9yn9gShJkiy24BQEwR0QJUnKvft4IPDevboYh9gtQ3R0NImJidSpU6fabuDGxMXFER4eTlZW1j310yzPB3j//v0cPXoUSZIIDAxkwoQJVm3JAgP1kVJDf/p7SXBwMK+99hrbt2/n7Nmz/PTTT4SEhPDYY4+ZpZIEd6jP63tnUpBdiJOzEicX+yvJqzuNASDq0glatu6BRtICAqDjgeZdWLfjCwAyMjL55pu1FBSY5p6WzaW1xLx581i1apX8t9BoNCiVStm+7tatW5w8eRI3Nzfc3d3x8vLCx8en3MhX586d6dy5s0mEuaCggD/++IPw8HAKCwsRRZEePXpQu3Ztrl27xq1bt8jOziYhIYGEhASOHDmCIAi4u7sTEBBAt27daNSokV2/t/Pnz3Pw4EHZE9rDw4OSkhKuXr3K1atXqVu3LsOGDaN27dp8tX8DyTGx3LwcRaN2rfEPqtok7H5I0finsnTpUmbPnk1JiQYnJyXe3p40btyAyFOXad68EY0a1ycqKob27VuXO46lz0fjxo25ffv+ytV24ODfhiAI64E+6HN7E4H5kiR9DTxOmRQGQRDqAF9JkjQUCAD+dzcwpATCJEnada+u0yF2jSguLiYsLAwwtXqqDtRqNRs2bJCr5ZVKJb6+vjRs2JCTJ09W67mskZyczPr168nNzUWhUDBs2DCzZeuyGLxwK2rtWV2IosiIESN44IEH+OGHH7h+/TofffQRQ4cOpUMH8wiZm7f1gqyKuBdit2FoEAVq/US2qKhIjqpnZ+cwZfILHDgQwauvmb63ylorlUffvn3l5ib/93//x9y5c6lXrx6A7LlrCYNnrlKpRKVS4eLigpubG56ennh7ezNixAiOHj0qW4xt2KA3//f19WX69OnyZKNly9Jq+oKCAq5cuUJsbCzJycnk5uYSGxtLbGwsvr6+TJ48GW9vb6uvxeD8ERMTI+dl1qlTh8GDB1O/fn0Azp49y6FDh7h16xZr1qyhZs2aDBo0iCZNmlC7caO742QDGYAbEGD3aozDuqr6efbZZ+UUBC8vL86djaVT5yaUlGjYt+8Ew4brU/OSkzMICPC3OEbZXN2ylJSUkJubK0/6HDj4V/GndFqsGEmSnrCy/UkL25KAoXcfXwfa3tOLM8LxDWGEIWImCEK1FqVpNBqWLVtGUVERnp6ePP7443LUWKfTyWI342w03o3r4uRVvS2EdTodmzdv5vfffwewGi21xJ49ewCq3YasIvz9/XnllVc4cOAAERERhIeHExkZWW4U2l5EUTSLru/5dDORhy6gUIj0e7Q3nR+tfL68cfrI+Cemc/jwCdRqNXl5BXh4uCFJEv37D7FLnIWGhlK7dm2Sk5MB+OWXX5g4cSIzZswgOTmZ/Px8CgsLKSgooLCwkMLCQoqKiiguLkatVqPRaMjNzbXZSiwzM5PFixdbjKy5ubnRqVMnOnUqtUdMTk7mu+++IzMzk08//ZQpU6YQHBxsclxeXh7ffvutWVSuadOmPPGE6fdmhw4d6NChA9evX2fXrl2kp6cTFhaGh4cHPXv2pGMnHVBkdMQ1dLpOiGL5RU9lcRQ4VY3ly5fTrl07rl69Sr169YiMjDR5fuy4QcTH3yAqKo7OnVvSqJF+MuPv70+dOuZ59r///ju//mrdmvPEiRPcvHkT0E/63nnnHcff0IEDB1ZxiF0jdu3SR9CHDRtWreNu3bqVoqIiWrVqxSOPlDYYuHDhgomFTsxbP6Ar0VB7dDeCnx9eLRZE0dHRbNq0ieLiYlxcXBg7dqzNS8w5OTlypPDPaGFqiYceeohOnTqxbt06UlJSWLZsGf369aN79+5VHlsURZMl7HeHvcvhM1loNBKiKLDzyC88svU4L64zz6O1h4SEW0REnJQjVR4e+smMIAgsXbqSBx/satd406ZNk9MODNHugIAAk8JCWygqKiIjI4NDhw4RExMjX9PYsWNp0KABS5culfe9cOECbdtWPAlfs8a0UPe7775jxIgRdOjQgdTUVLZt20ZiosUULq5du2Z13JCQEGbOnElaWho7duzg5s2b7Ny5k/37FXTtWpeevYLuThokJM4BD1odqyySJP0j7L7+KgzvRUNDE8NEzMCHH35IUZF+QhIaGmziBR4aWo+MjAz8/Ew7LxoLXcPKx9q1a7l16xaurq7k5+ejUCjkz++iRYt49913HX9HB/8O7qMOan8XHGLXCMPyrjXngsoSFxeHIAiMHj1a3la2Cr/55SK0+fov7pQtJ3Cp50fth7tV+pxqtZr169dz48YNANq1a8eIESPsiiKGh4cD+pSLipYU7yVeXl7MnDmTU6dOsXv3bvbu3cu5c+eYOHFiucvkFSEIgiziNy8I4/CZLIqL9T9rtfr/N+29xcADF2n2UJtKnyc1NR2VyomiomLeervUSvCXjbtROVctit+iRYtKH5uQkMDWrVvJy8tDFEUefPBBevfuLb9H5s+fL79PN2/eLE/M3n77bZRKJTqdjqKiIj7++GOr5xAEgfDwcA4fPixHk52dnQkKCiIrK0uu2reVWrVq8eSTT5KXl8e27d9x7WoGR47Ec+xYAm3aBDBgYCNUKtDpChFF21Jc/qqJ3D8dV1dXfHx8ZPHbuXNnOeKrUCjRavUFlQcPHmTcuHEmx7q7u8udIBcuXEjv3r3lQrf8/HycnZ2ZOnUqNWvW5L339DUt7733Ht26daN///733C3EgQMHfy8cYvcuBQUFpKWl2dR8wV78/f3Jy8sjPT2dgIAAszzRbkfzcTcyZNAVlZD08+FKi92K7MRsoaioiNjYWJMblk6n+0tvIl26dKFVq1asW7eO5ORkli9fTp8+fejVq3KpBqIoyn+L0yf+QK02Fz0KhcCeb3ZVSew2a6bPVXzzrWdNtsfFJTHjuSftHq+qxYJZWVls2LBBFiH169dn4sSJNqfuGPtQW8OQ9pCens6XX35JdnY2fn5+DB48WF5Z2LZtm4nYtSda7+HhwbhxLVGrNezbe50LF1I4dy6F8+dTCA31Y9iwULnivyIckd3KY4jYgj5YoFaradSoEaGhoQQGBrJ792769++Pt7c327ZtA2DChAmEhITwzTffkJycbLEQ+LXXXiMvL09eXTh06BAAkydPJigoyOR7aN68ebKF3vHjx0lLS2P06NEmHtUOHDj4d+MQu3fZs2cPxcXFDBo0qNrHbtGiBXFxcVy5coWAgACTIqIBh4qQSsyP0eTYb0dW1k6sV69e9O3bt1LXvG3bNiRJomfPnsTHx5OcnMzt27fx97dcTPJn4ebmxrRp0zh//jzbtm3j4MGDXLhwQe72Zg+GnF2dTocVG1wsNYmwFw8Pd1559SkkSR+512q1LF3yLV5eXrzyygy7xzOeuCxYsMAmJwfQ545v3bpVzt2uWbMmjz76KLVq1bJ6zKuvvmqSzmCNWbNmsX37dlq2bGlSSOjv789rr71GQUGB2d8nNDSUM2fOyD8fO3aMAQMG2PRa9LihUhUwdFhTBg9pzJEj8Zw8kUhUVAZRUWsIDg5m+PDhsn2eg+rnww8/lB9rNBpUKhUTJ06UnysqKjIpbu3cuTONGzcG4Jlnnil3bA8PD95++22TydX3339Pt27dGDhwoLzNYM0nSRKnT59mx44dLF++nJkzZ9r9neDAwd8GRxqDXTjELvo0gwsXLtCzZ897IuYMkYvMzEwOHDjAkSNH5OecfD1Rp2aZHiAIeHewz7rJ2E4sICCA8ePHy96k9qLRaPjjjz9QqVR07dqVvLw8QO95+VeLXQPt2rWjWbNmrFu3jlu3brFixQp69uxpl7j38vIiJyeHpUuXEto1iIiz2XIagwGtFgY/W7Uc7lWrVslCF+Dnn/Yw5cnHefPNlywW59iLLYI3MjKSPXv2oNFocHZ2ZtiwYbRuXb7dE+gFh1KpRKPRmJ2jqKiIiIgIunfvjpubm0kjDGNUKpXFqLEhwuvv7y+3IzakTdgi4AVaIHEa0Aue3r2D6d07mNORxRw+fJEbN27w+eefExgYyPDhw62u2jjSGCpH2VQsnU5Hnz59KCgoYNOmTRQVFREcHIwgCKjValq3bk3XrhXnp+t0Og4dOsTNmzfJzMw0WYEBffQ2OTmZli1bmhRHCoJA586d8fHxISwsjOXLl9O4cWMmTJhQfS/agQMHf0v+9WI3MTGRzZs3U6NGDXr2rHwXpvIwFF9cunTJZPubb75J/rk4ot7+Hp1aA5KEoFQgOjsRNM22Tktl7cSsWXTZw65du9DpdHTt2hVRFGWvXXvzK+81Li4uTJ06lQsXLsh5ob///juTJ0+2KaIzadIkfv31V65evcp1CugzyZejv9yhKE+HKOpDvWMH1adpr5YVjFQ+xmkH8+fPtzkSWx7z589n//79REREANYFb3JyMhs2bCArKwtBEOjSpQuDBg2yKx3l7bfftrjdxcWF/v37V+4FoBeozs7OZGdny13aDNgi4EXRA53uASSuAbmACoFGdO7sQefOjYmKimfv3gukpKTw1Vdf4evry+DBg2nSpInZWI40Bvuw1mI6ISGBvXv3IkkSCoWChx9+2O68+v3793Ps2DFA/x5xc3OjYcOGjBkzRhbYN27c4MaNG6SmppoVFDdp0oQZM2awatUqYmJiOHr0KD169KjEq3Tg4D7F0C7Ygc38q8WuQSz4+Pgwbtw4nJzsb0xgC5aiWg0aNNBHvLqG0nrl89wK+43C+HS82gRT9/HeOAeUL9aqYidW0bjnz59HoVDIHdUMYtfgwXq/0bZtW0JDQwkLCyMhIYEVK1bQo0cP+vXrV+5xKpWKxx9/nNTUVDZs2EAmmTz4pC/KK6DSKRgweQDtRtjnlFAWQytfsC1aaQ/9+vWTxS7oBeJzzz1HrVq1UKvVbNq0SXY4qFevHo899li12bZVFzVq1CAlJYUpU6agUqlMooULFizgnXfeITsrF28fT4vWUqLoApTmU+t0CUhcBCC0mUBos3bExwvs2nmFtLQ0wsLC8PT0ZODAgbRq1Qq4/3J2DXmwxi2ioWrXaS16XdnxrPlT//HHHyb7LF++3OT8giDI5xQEgbZt2zJs2DCTyZchKDB79myz1alnnnmGr7/+Wv759OnTFt1zAgICmDt3LitXrmTfvn04OzubRIEdOHDw7+JfK3ajo6OJiIigZs2aTJ061WJL3eqk7FLcU089JT/2aFKH0PnjbR6rKnZiFXHw4EG0Wi2dOnWSb0CGnEdbvVn/ClxcXHj66adlO7eIiAguXLjAU089RY0aNco9NiAggFmzZskpJm0ndWT48OFVvqajR4+yb9++Ko9jDUmSGDp4NDt2/U/etnLlSgYNGsS+ffvQarW4ubkxZsyYant/VDcG8a1Wq1GpVMyfP5/Vq1fLLYoXLVrE6s924+LqzKtznmHmrAnk5KQhiko8PU1zcXW6YiRizc7RoIHE9OnjyMjQER4eTmJiIps2bZKLp+63NAaDqDeOiBqEbkWCt+xrqUjMljee8Vg6nQ5Jksz8tn18fNBqtfK/4uJivL29TQStIAjyRNl4xSU3N5ezZ88SGxvLlClTEEWRW7dukZOTg5+fn8U0LEMDFVtwcXGhVatWHDt2jO3btzvEroN/Fo7Irl38a8Xu6dP6XL/Jkyffc6ELerFr8IesLNVhJ1YehgYXoiiaFOqJoogoilW69j+Ltm3bcvbsWeLj48nNzeWzzz6jV69e1A8M4pnuLxLi1hAFSm4W3WT07OE893bppKNPnz5EREQQFRVVLWLXWOg+/vjjVR7PmMSEFEaPeI601NuIChF1cQnTXtAX7ezevRtBEOjRowcPPfTQfW3DZBBUhmvU6dKY+mwbFv9fClp5biiRk53H4kUrybxzgTlvDEKS4PSZBAIDu1Kvbou7e1nuHmd4rlatDjzzzDNkZWWxZcsWbty4IdupVWcTmapiWGF68cUX/+Ir0VM2N9eYl156yaYxlixZQnFxsclr0mg0hIWFERcXx4oVK0z2t1WYzp1bvgf2X2mZ6MCBg/uHf63YzcrSF4VVtojLXnQ6nd1iUafTkZ6eTlpaGklJSURGRqLVavHy8mL8+PF224lVxIkTJygpKaFVq1Zm7TdVKpWJzVB1oNFo0Ol01S40UlNT5bbD27Zt49ChQxRlqenephP9X2hE297+5GeXsPPLGA6EH+GhEfpcbUN+cnJyMllZWVWq5DYWCNWdvgAw4fFXuHkjCZ1Oh1IpMniYaZ62QqGoUj7tn4Wx2JWkDCSiAB1h3x3isUm9AZg+azCfLd1GUZGan9ad4a15+mXr1q0bkJYahVodgkrlAmitnAVAIz/y8fFhypQp5OTksHnzZuLi4lCr1SxZsoT+/fvTrl27e/Rq/37s3LnTbJtKpeLNN9+0axy1Wm2WJiaKoslqUZMmTfDx8SEwMNBq3YHx5+rNN9+s8Ltj6NChcmDDgYN/EpIjsmsX/1qxm5OTg7OzM9HR0eXuVzY3rTQCVeo5K0kSGo3G7Mvc+Niy46xdu5bu3buTm5tLRkYGd+7cITc3l4KCAoqKiigpKbG4JFkVO7GKiIiIQBAEizlwLi4u1ZbGEB0dTb9+g2ST+Bo1fNi48acKc2xtYefOnRQXFxMSEiI7Nrw79z+41XBFfAhUgTp8ajrjU9OZCe+0YvfPl4DSwsROnToRHh7OkSNH7MNQpQAAIABJREFUGDFihF3nzsnJYdmyZSbbyt6MCwsL+WVjOBcvXqFFy1AefXQU7u72NZaIjYnnekwCOp2Otu1D6NGrGQqliDpfh8pd/57UaDRyakB1IEkSu3YeZuNPO1EoFTz+xDAe6t+tyrmuhqX677//nmemtgf0y+Xp6bmsXL6D514aCsALrwzj80+2k56eJx+rVCrw9HLl7LlwHug6DoHaSKSYjJ+amse1q7fp1auP2bm9vLyYPHkyd+7cITw8nLi4OLZs2cLevXsZMGBAtYhenU5HXl4eFy9epEuXLvdVBNkWTp06JT+uyqTNkFJjzIkTJ8jMzEShUPDWW29VuAJRNsJsy+/S+P25evVqpk+fbsdVO3Dg4J/Cv1LsSpIkRynDwsL+9PO7urqSkJDAzz//bPacKIqoVCq8vb1xd3fH29sbHx8f/Pz8CA0NNbthVBfnz5+nsLCQxo0bW0zr8PDwICsrC41GYxb1tQeNRkPr1u0pLi6Wt925k8WAAUO4cSOWBg3qV3rsQ4cOcerUKRQKhdyRycXFhZPrLjF+Tj/SSnLZvz+Oy1fSmTixLa7uSoaMb0pm2m18a+nzP9u1a8e2bduIioqyS+xqNBozoduxo2nub1JSCj16DCM7K4f8/ALc3d14d94HRBzdTlCQ7bmIubn5+Pl70XdAN7x93NHpJJJOakg6oaPTS6UCYPHixdUSVZYkiRnPvsvO7YcoyNf7P+/ecYQnJgznw6WvV2nsoUOHEhMTQ3JyMpmZQfj6OiMIAg1D/Lgem4FOp2/dbBAtDUNM28qqnJQUFeYgSRok4kye270rmshIvcPDoUPfMnPmTBPrvIKCAtauXQvo87Znz57N1q1biY2NlUXvwIEDbWqTbImvvvrKxGN2//79wL2J9N8LNJrSaLi9kdyy6HQ6s++VDh06sHfvXry8vOxKtSnrs1sRHTp04OzZs6SkpNx3xYgOHFQKR7tgu/lXil3jIgtXV1cTv1FDNPXWrVsmVki24OLiQuvWrU0KSQyPJUmSW2W+/vrrxMbGcvnyZXx8fPD09CQoKAgfH5+/LL/ScCO2JvB8fHxITEwkNTW1Sl3mli9fYSJ0DUiSxGuvvc6GDesrNW5ycjK//fYboigybdo0kxur6CLStWd9Grb24sd1F0hJzmPZJ8eY+mxHXFROpCYlymJXFEUCAgJISUmxKzJqbHw/atQoi1HBV195l9SUdLRa/XJ7fn4BRUXFzHrhDbaGr7PpPBqNhqirFxk1tjMAObe0xG7Tor2bYRK9tYTGI5ww3M8/+OAD3njjDZvGtkbkqYvs3PYbBQWlaSwFBYWErdvKU1MfoVnzyhe/KZVKBg8ezMaNG9m5I5oJE/UOCQv+bwTPPrWOL5ZtZ9ar+gnDrFeH07WLaQOMEo0Wb+9AdFI0YLryYBC6Bv773//SuHFj7ty5w+3bt02eu337NleuXGHOnDloNBq2bNnC9evX2bx5M/v27WPIkCF2tWbWaDQmQtcY4wjlvHnz7tucauP3dFUi0obAQtmJ+tWrVwF9Bz97aNiwoV37Dx8+nLNnzwKQkpJC7dq17TregQMHf3/+9WK3sLCQwYMHm8329+7dS1JSEoIg4OrqKgvXslXGhp+zsrJwdnZm6NChFs+5ceNG+fGCBQuYN28ejRo1Mlua+yuiPlevXiUvL48GDRpYzWE2RMSSkpKqJHbPnDlr9bmyPsS2Eh0dLUfJR44cadYRLOzkas7u30XzTr5Mn9GZ/ftiOX48kb17YhkzpgXeNXxN9jfclK3ZK5UlNrbUAWDy5MlWb8Y7duyTha4BrVbLvn2HbWrFfO7cOXbs2HE3uu7E4U0xKG8EoBBKLbmy4yT++FlNi8f14sTSxMJe9u89TmGh+TgarY4D+0/IYrey7aRbtGiBs7MzcXG3KSjQ4OamZODgFnz34xTeX7iLyBPRdH5A74178lQaJ0+V+j2PHhNC6zaPAcdsOldMTEy5z//2228MHTqUSZMmcfr0abZv305eXp78+R05ciTt27c3OSY1NZWcnBzZv9e4zS2UfqYtFXpFRERUut31n0VVxbjBiaFs+16D44aho1p5GNcLWPJJLg/j7/b09HSH2HXwz8AR2bWLf6XY9fPzM7ECO3LkiNkNp1+/fkRGRqLRaHjuuefK9SeNjo4mLCyMBg0aWN2nY8eOJp6rBQUFsnF6WRITE2UvSRcXlworjqvK7t27AetRXShtjFE2ImYv3bt3Z/168/QNoFLNMOLi4li/fj2SJNGvXz+LS86169Xm+NGb9B5TH6WTSN+HGnL8eCK5ucXERxfSrGYm0o1UCGyK4GJ/weK6daVR2fKiTtZEg/EyvTV++uknrl69iiAIdO3aVe8TW+8Ia1/fg6Qx3dcgdKF6Jk9e3h6oVEqKi037WjspFXh6urN1yy5en/secddv4ufny9w3XmTWrKl2LReXlOjHLi4Kxs3tNlBIn4da0uehfohCI9577z2Lx/3v1+v879fFpdfkJKJSKXj6GdP30vz583nvvfdM8uCNfzcGIRoZGSmvwFhi69atHD58mBEjRhATE8Px48fLfV3GriaG861YsYI7d+4AVGiL91exZs0a+fG8efOqNJZB7JadSBs+D/v27SMoKKjcYuGy9Q/2CHBjf/DyvqMdOHDwz+VfKXadnZ2ZN28excXFfPDBBxw8eJCDBw8ybtw4ealSFEVat27N2bNnOX/+PA8++KDV8S5cuABQbkFLSEgI8+fPl2+qxpEfY8pGf4qKiuRt96L1ZXx8PHfu3CEwMFAWtJYwRHOr2lhi5swZzJ37JgUFBSbbRVFkyZIP7RorIiJCTr+wFHEzZtGa/xB14SJe3gkUavRRyvT0An7bdYbgRidxUUqg0yG1HmLnKyqlIlEw7tGRrA/7FbW6VDQ6OTkx6mHzlQUDGRkZfPvtt+Tn5+Pp6cnUqVNlUTByck92/fcsKTcy0Wr0YsDZs3ScUaNGVfq1GDN6zAAWL1pltl0CPDxVTJ78PIWFRXevN5P5736IWq3mtdeet/tcN2/eoYavCCgAHZBMYWEa+WlenIi4Sv2gWjz/6liORe6x6G5SUqKjpETHZytOmj337rvvWj2vh4eH3Ba7IrKysvjhhx8q3M9aioJB6AIcPnyYrVu30qVLFwYMGGDT+e81ixYtMlmBqGzE3oDB+aZsJ7V+/fpx48YNkpKS+PTTT3nxxRetOqAYp0AsXLjQrknczZs3AXjyySer5LDiwMF9g6ODmt3cn8lifxLOzs4mkUDjVAPQd78SBKHCiKMhtzc4OLjc/ay12JwzZ44NV1vxEmxl2L59O0CFvrKGG1VOTk6VzieKItHRf9CyZWn+Y926dTh58pjcqa0idDodq1evZv/+/YiiyNixY8sVugBbNvzKspdW8GD7/zK02zoyUvORJIm0YoGPrijZkyiBTgOXdiGVVH3p3xIffTSfpk0b4eHhjrOzCg8Pdxo2bMDy5e9b3D8+Pp5Vq1aRn59PSEgIL7zwgkn0SxRFPtj+LJ0GhKJQiogKgdZPlzqCVJeFVp26Aaz+aiFu7q54errL/34IW8JHH30mC10DBQWFfPjBZyYFThUxcuRIALZt20FiYjJ6GzEdOZmFfL/gAvG77uCS4MG1iCSmj/+AZg0fYN68efIkoWNHy0vTbm4uNgmjV199VW7lbOlfeQQEBDBjxgx5PycnJ+bPn2+TQMzIyECj0XDs2DEWLFjA999/X+Ex95IFCxaYpdqU7eRmL4bvjLJRbFEUeeaZZ+jWrRuSJLFp06Zyx3nhhRcqdX7Dee15Pzpw4OCfxb8ysmvMww8/TL169WTRd+7cOdq3b09kZCRFRUU2OSB4enpy584dCgoKyk13KJsD2rVrVwYPHgzAlClTOHPmDKNHjza7SZ4/f54tW7bIY1RXQUtqaippaWnUrFnTpjxchUJRLY0l6tSpw6VLFzi0aSe/ztsIxU78+NwXhB5Yiqdn+cu6ly9f5pdffgH00bipU6eaRYwM6HQ6kxt1nb71mdK3Ptf/uMOZIykIgkSHLn741ffhRKYzK1ZfJTkph+6jC/BvUIM357zDgkXv4uXtRfTVaMJ+Kt+5Q6PRlFvI4+PjTeTpvRw8GMGVK9do2rQRAwb0tvj3PHPmDNu2bQNgwIABdO/e3fKY/h688+NEStQavv3uG3niVd3dooaN6EtUbDeOHIpEoRB5sFcnXFyciY2Ns7h/cXExWVk5+Pn5Wny+LG3btuXatWtcuXKFb785R1CQN/36hvCfkRfITClGUyLhjDO18Ce3MJdFb3/D0NHdeffdd9HqzgNZDBnaVB7v/PlkdDro1HFclV97eRHfmjVrkpqayqpVq6hbty4vvvhihakJoaGhcnFWWeLi4sxyzqtCQUGB/P2VmJiIn5+f1SY65TWPMGDc9tdWDDUSln4voigycOBAzpw5U2FBsLXfq0ajYceO/VyNiia0WROGDu1n4hjj66t/D2ZmZt63nQQdOLCb+6zz4/1OlcWuIAj1ge+BQPTrjmskSVouCIIv8DMQDNwAHpUk6Y61cf5KOnXqhJeXF+vXr2fr1q20adOGgwcPAqURp/Jo1KgR8fHxXLhwgR49eljd75VXXiE1NdViM4jg4GCrkeF27drJYtdYvDVs2JC4uDj58eTJkyu8VmPCw8MBGDLEtqV7lUpVLQVPAP8ZM4vkk77opPpoJQFFIbzd8iMeWdaL3o+YX8+JEyfkFrgAtWvX5umnny7XBs1aRCqkeQ1CmpvfOLuMayNbXQFE/naa2gENcXb256VXnij39TRv3tyminVRFOnXrxf9+lkvStq5cyenTp1CFEUef/xxmwpySjRqE7FgySu5qri5uTBoSE+TbaGhjTl16pzZvq6urtSoYXkSYo1x48Zx/sLPbN92jZs3swlbd4ns22o0JaVf6iIinnhyKyubzIwc/Gr5IApB6KQc9F8/etq1qwsEIghVn8+XncDOmDHD5DMcGxtLeHg4t27dYsWKFYSEhDB69GirE9+y3fR27Ngh5wn36tWLqKioKl+zLcLVGjVr1jTLzb+VmMKyRRvYueUYWq2O7n3a8N6SadRrULEwN0yQDaLTEs7OzhV2OzOeFEZERPDggw+Snn6b3r1GkpqaTmFhEa6uLtQK8Ofw4a34++sdVjw9PVEqlVVOwXLgwMHfl+qI7GqAVyVJOisIgidwRhCEvcCTwH5Jkj4QBOEN4A3g3lZaVYGmTZvStm1bLly4wKZNmygsLKRJkyblRnVLSko4ePA3OSctJiamXLELVLrr2csvv2yWBmEQumUf20JWVha3bt3Cy8vL5miHm5tbtd0wMiM9UesEQC8sNRIUlDjz65wtJmJ3z549nDlzRr4RBgUFMWLECGrWrGnzuXrW6ci0uWupH+JNj0H1cVIpzPZJSbpDYJ0astAFGDC2LwMwbeCxZcsBLl+KIcg3hCuJB+VWytWBTqdj3bp1xMXF4ezszNSpU8vNozbm448/lh+Xt+z+31kfkrA7EWc8UJNHvUH1mPlZ5T+W7y18g9EPTzFJZXBzc+Wdd2ajUJj/niuidesWHD+WQFpaPsXZUFxg7oghIeEsueDppf9sCkINBKk5EjGAGv17qg6iEFLJV2VOeb/TRo0a8fLLL3PlyhV27NjB9evX+eSTT2jRogUjR44sdxJ06dIlk4K4vn37Vlnsvv++5bQYWzGkCxgL5ulPfMT16CRKSvSpAEcPXuSR/m+w/8wXeHi6ljteYaHem7m8z0lBQQHOzs42X+P+/ft58MEHmT17HvHxifJ15eXlU1xczOzZ81i37r+APgpdo0YNk1xpBw4c/LuostiVJCkZSL77OFcQhD+AusAooM/d3b4DfuM+FrugX9aHUv/H8qK6p06dYujQEfKX7IsvzpQLIe4F3t7ezJkzh1WrVvHQQw/Jkd7KsnXrVgC7imI8PDy4fft2lRtLfPHa++RrVBiErgEtAiXqUtP/nJwcudq9SZMmDBs2zGrKQlmMb9RdHumFbu6XJMbl8vOqKyb7Seg4ce0Znp2yjp3bziAIAiVqLVNnDrC4VBsbEw9Awp2EKv0OylJUVMTq1avlNsXTp0/HxcWF9ORsFAoB31q2uUSUVyT37vBXUF/xQiv5UYKAgAvx2wt5N+4V3tv2SaWuu2/fB/l5w1fMnfse0deuExDgz9vvzObpp8dXarxrVyXS0vLx9nHBCx/OKPLRWegC3KFHU5xdSkWkKPojSX7oc31FBOHPL0do0aIFLVq04PTp0+zbt4/Lly8TFRVFly5d6N+/v4nYO3ToEMeOHTOJZrq6uvLRRx/J4vDDD80LNstLHxAEwazwc8qUKXh7e+Pt7Y0oikRGRrJjxw4A2rdvT15entxFskmTJowfX/p3Mwj8E0cu8evXH8jfdaCfmBUWFhP+yxGeeKr8Bg/FxcUVTny0Wq1NxWPPP/88X3zxBaBfudm6ZafJdQGUlGjYstm0zbGvr68jsuvgH4MESLY5Yzq4S7Xm7AqCEAy0B04CAXeFMJIkJQuCYHG9SxCEacA0+OttYQy+jzqdjsaNG1tdhiwuLmbQoGFyRBcgM/MO/v5+nD9/vtoKg8ri5ubGK6+8AuhTGyy1p7WFgoIC4uLicHNzo1WrVjYfZyiOSkpKqtrfSlPep7T0Zu7l5SXnNxo8j23BODdaEAQUbon4uajJLFKYiCAJHe26+uHt7cqYce05cri0AHDPjnM80CMUBI2JwH559mSSktL54btwm67FFjIyMvjyyy9Rq9U0bNiQiRMnEnM5iXenfkvyzdtIQEjz2iz8+inqh/iXO1Z0dDShoaEWnxOvOaORjF+/gEYScLlme0TNEoMG9WXQoOppYX3okN6Ob+KEEahzC/l1xU0Eo/eEhIQGDYKHeb6a/v3x15chdOrUiQ4dOnDo0CEiIiI4fvw4kZGR9OrVi06dOrFo0fvk5+dRo0apuFOpVHKKjlKpRKfT2eTzbGylZrBvM+bixYsmk/bOnTvTuXNnu15PbPQttFrzayksKOaPyzcqPF6tVlc4MbS1HbnxSodOp2Pa9EdZvWqDWQpE2Vbrvr6+xMbGOjqoOXDwL6Xa7gyCIHgAm4CXJUnKsfULRZKkNcAagE6dOv1lGdcGoWugPNumPXv2mlUsx8cnUKuWP+vW/VhtYlej0bBhwwbi4+Nt2n/hwoU4OTlVuJ/hxtCnTx+7rsdwo0lNTa2S2H3+03eYtelt8jROGItbhSDh5JRhsu/jjz/OunXriI2NZdWqVbzwwgsVFgwat2GWJImPPtxIZPI+ujcbQmpa6Vu+VYca/Lj5sbv7mY5xLSqJjGu5RGcfQRTdcXH25oFubejVqxP16gXgY2OEuSKio6P56aef0Ol0PPDAAwwaNIicrAJmDl9Ofk5pasC1i4nMGLKMzb+/h5PK+sf2p59+srrknl9iuTApz8r2v4KcnBycnJzw82vBHTGXJGUStUpqoUAfGSyiiCSSyDyWUcFIfy2iKNK3b1969uzJrl27OHfuHAcOHGDPnj3s3r2XBx7ojE6nY9GiD/D1rUFU1GW7UnMsYbyaMXHiRNatW2cm+ipD49B6KBTmkXI3d2eatwqu8HiNRlPhZ7ZmzZrcunXLpgJcYwtHT083XpvzpPzcRx+uBSSGDzddsfLz80Oj0ZCRkWHSMtqBg78ljnbBdlMta32CIDihF7o/SpL0693NqYIg1L77fG0gzdrx9wMXL16UHzdq1KhcV4WcnByzm8jly1es7F05EhISWLJkCdHR0Wi1WpOObYZ/ZYvFbI0ESZKEQqGwO8JjyDdOT0+36zhLeLe5g0qUUAoSIKEUdLgp1AxZ0N9s34kTJ9KqVSsKCwv57LPPzJZqy9KypeWCrujko5y99iyb9o3jdOx0Nu2ehFKpQFukZeuG32VBpUCBMyrU6iQ83GqgEN3RaDREHDlLaqq+cCfYP6hqvwD0qTBhYWFIksSIESPkBgR7fzmNtsR0MiXpJIoK1ETsstxlzhbjf4Vg+ctRaWX7X0FxcbEsjFxdVRSLRcRynevEEct14oUENIIWL2/3CkaqHEk3M1i1MJyFM39g98bTlKirZlelVCoZPnw4c+bMoW7duigUCkaMGIK/f2ljm/z8Atas+aqaXoEeWya9ttKlewuCQ2qjMppkiQoRN3dXRo7tWc6RerRarVUHCAOGNAdb7cHefvtti9tfn/s0desGsuzTRSbbDXUJ1lwwHDhw8M+mOtwYBOBr4A9JkowT/7YCU4AP7v5ftSTTPwlBEBg7dmy5+zz0UF80mtIlQzc3N0aN0vvUNmhgX593S5w4cULuata+fXuGDx9uFu2wVm39xhtvlDv2li1bOH/+PD17VnyTKkt1NZYAWLT9v2z5748cWH4A1CpE7yJe/WUe9RpbLip65JFHcHJy4ty5c3z66ac8//zzVvN3W7UOpGWrPuh0Wt7/vyPy9vTsHN5/8Rve+3I6SBK6Ei2SFnIP3mTCnRqkqXzI0WhwUYg06OrP2EkvMXzUcOr7dSFfk4OEFl9f/TnXb//c7tecnZ3N5cuXiYuLIz09nezsbERRZMqUKSaR8qSbtykqNF+SLlFrSEks/d3v2nmQF55/i6TkJNzc3Jn14mPlX4AiHYW2FlrJNJqOouqTl+pArVaj0+nkdBkXV2cGjezG7vATqI26t7m6OfPUc+X7QleG4/uu8NL4JSTkX6ZAk43nD750avYgPx1ahItbxU4b5eHi4oKXlzc3bhylYcNgoHSpvbCwkJMnzZtgVJaBAwfKS/XVEdkVBIF1W//D++98x/Zfj6LRaundrz3zPngad4/yi9MM4tXVtfz9UlNTUSgUNjmagH4SMX/+fNRqNUuWLKFmzQBSUhIBmDBxGGvWrDJZ4fD29qZ27dpcu3at3AZBDhz8bXBEdu2iOtIYegCTgN8FQTh/d9tb6EXuBkEQngHigaobXt5DevXqxfHjx+nSpUuFUYjatWvz7rvzWLTofQoLC+nfvy8+Pj7k5ubx1ltvVfoadDodR48e5cCBAwBMnjy53PazoF/+e/rpp+Vq/OTkZKu93zUaDRcvXkSpVFZK7Bqi3QbfTHuR1PlwKxKyboCLDyMn9WXUTNs7whlyD8+dO8fnn3/OSy+9ZCUCL1K2+M3Ah2H/Y9Nvx5kzeTTu7q50yvUg41gutZQuLG7eBhQg1HGhe1hpe9rbBaXRVMMkoyJf4qysLP744w/i4uJITU0lLy/PLJfYx8eHCRMmmDkutO4agus3RynMN43cK5UKWnQIBmDH9v2MGT0FCf0XXm5uxfmOM7a8yjcP/5cijSciEjoEnJW5PPnLixUe+2eQmKgXK8a/j4VLp5GVmcupY5dRqZwoLi7hkSf6MuHpQdaGqRQajZaXp3zM71n70aGPqhcV57H7wk8smd+Edz5+tsrnCAlpKAtdKBWizs7OtG7dusrjG+jWrZv8u6wuPL3cWbxiJotXzLRp/0u/X2P1yp9ITU2lZZtaFYrYGjVqkJKSQlJSEnXq1LH5ulQqlfydWzYAULaQtmnTphw6dIj8/Hzc3e/NyoADBw7uT6rDjSECa8oC+lV1/D8LFxcXAgMDSUuzLdvizTfn0qvXg3z11Vp8fPSRqFdffaXSy4dqtZo1a9bI/pYPPPCAmdBVq9UsXrzYZFvZrkJr1qyxmrN54MABdDodXbp0qbRdllKprFRjCak4F85+DZpi9OHUJLh9DanpCIRazW0eZ+TIkWi1Wi5evMiKFSuYOXOmWRW3gB8SMajVltM6YpJSmP7BShrXC+LFmoMIdXPB3VAtrgXS1Bza9D96PzLa5DiDRZS3t7fJzTsvL48rV64QFRVFSkoKxcXFZsLW3d0df39/goODadmyZbn5mQ8ObkXd4JrEx6ShLtZHxpxdnGjRMYg2XfXviRdnvSML3bJ89dVXTJ061Wx7cIsQFlxbwqqXlxB1JIpmPZsx41Pb267eawy56caTNXcPV9ZufIeEm6kkJaTTuFl9avpVT760MbFXkriWeVIWunokdGhZ+fXqKovdskIsIyND9p1VqVQ899z0Ko2/efNmi9urI7JrTHJyMjk5OTRu3Niqw8K2rQd47tn5FBerCWroR8s2tdi5/QgDBw7B39+y1+6gQYP47rvv2LlzJ88880ylrs0Q6TV8R65fv55JkybJz4eGhnLo0CGuXbtWYcdFBw7udxxuDPbx15cu30c0aNCAU6dOUVhYWOGyG0CPHj3o0aMHP//8M1FRUXzzzTeIomiWW6tUKhkxYoSZn61Op+P8+fOcO3eOpKQkdDodgYGBTJkyxSy6fPjwYbnRhQHjJhTz5s2TmygsX76cl156yexckZGRd5saVH4O4uzsXLnGEvERUFKEsfE/Og3E7ELyD7XLKmr06NG4uLhw6tQpli9fTqtWrejatSv16tUDQBBUCFIz8vPPysf4+nqRmVna6thN5Y+qqC1rbqWhleCxAF/6301REBQCObdSzc5ruLlnZ2ezevVq1Go12dnZZsWKHh4e1KpVi6CgIJo3b253QYxSqWD1rlf4ftke9vxyGoVCZPiEB3jihYfk5emkZOvdpm7dulXu+DM+fc2u6/mzMFj/BQWZ50PXDwqgflDlPKptQaEUKNBajo5n5pu/F+xh1apVJj/HxyfIkcVOnTry5Zer7IpmWuLChQsmP1e340BqaiqPPvoEJ0+eQqlU4ubmytdff8mIEabpJFqtltkvvi/7Lnt56V9nRno2yz/5jkWLZ1scPzg4GA8PDxITE026vtmL8ST0+vXrJgVvgYGBeHl5cfXqVYfYdeDgX8afb0Z5H2NYSjQuVrOFtm3b4u7ujlKpRBAEJElCq9VSUlJCcXEx2dnZrFu3jvPnz8vHnDp1ikWLFhEeHk5iYiJOTk507dpV9lcti7HQbdy4MePHj2fKlCnyNuNIbVZWFqtXrzY5PiIiAo1GQ5uIbfFNAAAgAElEQVQ2barkD+vq6lq5HvN3rmMidA3oNFCUZb69AoYMGSLf0C9dusTXX3/N+++/z9q1azl48CB5eS4UFzWT98/ISGbl4reYMXE4zQIHEeDWhfTCRJILYslSp/JTcgZxhXoRL2klOgw3Xybv0KEDjz76KEqlkpSUFDIzM3F2diYoKIhevXrJgmXWrFlMmjSJXr16Vbry283DmRnzRvBT5NsoGt9g+luP4eVegwcCO7Fm+GIG1+qAc5nuYMXFpfZLVemg9VdhyAW3tZFGdRLSrA4K0fKqjJenZ5XGNoh40Ecfv/76K5o00UdGIyNPVIt7y9ChQ+XH1VFAaowkSQwaNJRjx45TXFxMfn4+6ekZPP74BC5dMi2YvB6bgNrofejhqf8uu5OZx+4dh8s9j6Ehz65du6p0vca/z4ULF7JgwQKWLVtGYWEhoaGhxMbGWrRpc+Dgb4PBjeHP+PcPwRHZNaJevXq4ubkRHx9P165dbT6uWbNmNGvWzOrzsbGxhIWFsWXLFnJycvDz82Pnzp2IokiHDh3o3r17ua00QR9VNEQQH3jgAYtdz4yju2Wt1I4dO4YgCDa3BraGt7c3GRkZ5OXlletYYYbSDbAQOZN0oKicz6uTkxOCIDBq1CgOHDhAZmYmCQkJJCQkcPjwYZOUEkFQMeONBUQcvMCOba+RW3ILDK4WUh4pxXfYnq5iVpMgUto40z3Ecq508+bNefPNN0lPT8ff399kkpGQkADAyV/3cWPzOfJz1Li6KOk1vh8Nx3av1Gts26YbV69eQro7UYhM/Z0/dsfwn2bTae/agA/j/keJpH9fLF3yLVOmjKZuvb+ntVJBQQEKhaLaOtLZgyiKPPXkeNZ+sw6dVBqpd1I68drrtuWpWsJ4YigIwj2bhHTu3FluFpGYmEitWhW38bWVCxcuEBMTazbJLS4u5rPPvmD16pXyNk8vDzSa0t+fu4de7ObnFVO7TvnWal26dGH//v1cuXKFhx9+uNLvg1GjRpkEFkDvoPPxxx/z6KOPEhkZSVxcHE2bNq3U+A4cOPj74YjslqFevXrcvHnTJhsvW2nUqBHTpk1DqVRy8OBBNm7ciCAITJkyheHDh1codMF0WdKa+booihbz3SIjIykuLiY0NNTmamdr1KhRA9Dn7tlFva5QNnImiOAThKCqfLGIIAg0b96c559/nnnz5jF79my6detGnTp1LEZv8nILySlJRRAUiIK+yYQgKBBFJ/Zm/EHaoNqM+aR8QSKKIgEBAWY3Y0Mu84GrkVxvriG1q8iNtjo2he/m6pd77X5tx49FEnX1d1noAujQUagtJiLjPLVcfejq0xRDynxok1CWLC3N6bY1//x+QaPRVKrFcHXx6WcLmDDxEVROTri5uuHsrOLZaRN59TXrYlery0ari0SrO4ZWdxVtmXZvxqso1Z0/K2Umodu+Et1Xr6Fbv1DevnXr1iq3HDbm1q0ki38XrVbL9eumbcoDA/3o2LkVTk76121w0Rj7RHcGD2tPTk6O2TgGRFGkXbt2aLVafvvttypd8/z58y0Kfjc3N1QqFREREeVeiwMH9z26P+nfPwSH2DUiKyubLZt3kp+fT/PmbWjSuC1nz1ww20+SJGJiYirMjTQmICCAWbNmyTe/4OBgmxszfPzxxyZRlQ4dOljdNzY21myb4cYxbNgwm6/XGobCKuOlWZvwbw71uoCg0EdyRSV41oVm1pt3VERJSQmCILBmzRoWLFggL1c2a9aMpKTSnFb/Qnc+H/I+a59Ywr6w9YiCk1lOoyAo0AoSD895qexpbMYQ6Xa9IeEeI4FGL26UWQKRqyPsnkBt27bLYi5ziaThWt5NFDqB2Q9PYtkni1mz+jMOHNqEl1fpkvvKlSvNjr2fsaWhQGUpKChg27bthIdvs+rT7OTkxFdfLyPu5ln2HfiFm/HnWPbpIqvXpNVFA+eAfECNvmv6EbQ6025eb775psnPkyZNombNmlXKq5UyU5A2fADXL0BhLmQk8qpfaaONiIiISo9dlo4dO1jM03d1dWXAAPP8/6+/W0yLlo1xc3PhbOQNjh2JAkTy8rNYtmwZMTExZscYGDBgAKIocuLEiSoHHJ577jnmz59Pr1695G3169dnyJAhJCcn88UXX3D69Olqn4Q4cODg/sORxmBEs9B2qEvyad7ieXx9vTlx4hRdunbn5o1o6tbT52P+9tshJk16kszMTHQ6Ha1bt2Ljxp8sFtWUxcvLi1deeYUVK1YQFxfHuXPnyi2UsLTkOWLEiHLP0bBhQ5OoyKVLlygoKKBhw4b2pR1YITAwENBXk9uDIAgQ3BupbhfITwdnDwTXiiPa5WEoBiwbZf7mm29Mfk5V55MfJSCKGpyUNRnRshnbrlwzv8YqXU1p3rTXJRA1kN8IBLWE2w0oAkqy8nH2tT3/s03b1uat3QAFIgHOvqRq8vhw67dotun3eev1pUx7YaC839+tLaokSfdE7G7fvoPHHhuPVqtDU6IFJBb+5wPeeMey5Zqfny9+fuW/N/URXGuT3YtAJ/knlUpl1SGlskinwkGjBiNHDrcyIhuqJ5ocGBjIzJkzWLPmS/Lz9RMFlUqFr68v06aZu1T4+/uy//APXLkcQ0pyOm3aNcPPrwYbN27kypUr5VoXqlQqWrRowaVLl1i0aBHe3t50797d7gY4Bs6ePUvDhg05fFifL3z8+HF69OhBUFAQ4eHhbN++nStXrjBq1Cirvt0OHNx3SBLSPyif9s/AIXbvsumXraSlJaFQ6gWCwY1Bq9Xw2mvzWP/T18THxzN8+CgT662zZ8/Ru3c/rl+/ZtON2tXVlalTp/L5559z6dIlM7G7evVqs3xb0Ofsvv766xWmIRgLPWOxfOPGjQqvzRYMRVhZWfYXlQEITq7gU/lWw2UxjtL17t2bQ4cOlT4pge4OiL7gOkiicLeATg3185oiClfRGTVXkCSdvliumtC6AYKAKkNCBEQBlBUY8Jdl3LiRPDvVm9y8OybbFYKCPjU7sjb5FNmaQqvHv/zyy5W48r+OexHZTUtLY9y4xyksNP09vfXu64g6T15/96lKjlyej21euUcWFBTIFoOVJvm6xYnQvWLp0o/p0KE9n366gqysLEaNGskbb7xuZvtnTIuWjWnRsrH8s+Gz2qSJ5Q6HBkaPHo2TkxOxsbFkZWWxY8cOkpOTZZ9tW7EULOjWrRugT8eaNGkSZ8+eZc+ePaxcuZJBgwbRrl27v90k0YEDBxXjELt32bf3NxD05vIlJSUEBRkEmY7Tp08D8NVXa83yQLVaLZmZmRw8+Bv9+j0kb9+7dx8rVnzO7du3GTNmNDNmTCtd5r4rpC3d2C0JXXuiQkFBQdy8edNse3Ut1RnEdlnxYA+SJBGz/SK/f3eMoqwC6nVvTIfn+uARaF9kpexr6tOnj4nYVa4XkJQS2qGgrA0ekyU0saA9LdCqTgDnE5MRBQWSpEWn07By5TusW7fOak50RRiOU0gSJU76G2ZJDUCQaNiuFgqVfR83URQ5e/YEvXoNJCUlHoUg4q304OlGD6N1VlGilMBInz//cmlFfnVHEq1x+/Zttm/fbjVaZ8v7ziAutFpttYvdjRt/MSmYMrowli39ghkvPVrJ1sOVE0Q6nU5uAFMlvHwhz7yTYWvnQn4vLp1UGbyLq4ogCEycOIGJE21vAlOWzMxMRFGscIVJFEVZ2GZnZ7Nq1SrOnTvHnTt3mDRpkk3vkZ9//tlsm4eHh8mxgiDQsWNHQkJC2LJli5zrPHbs2Gptt+zAwT3hH5RP+2fgELt3ad+hrfzYycnJ6CYt0LSJvmo3Lu4GarXlpULj/N3Fiz/k//7vfXnJ7/z5C3z99VpOnz6Ju7u7nH9bXgTBx8enUst3Tz75JBkZGXzxxRdmzxkiHePHj68wulIeoihSVFRU6eNPf7afy2En0dxtiRsdfp6bB6N45NeZuPnZtsx/+fJlk5w+g7jrnFeX81tv6X+3AqAVEHZKaAaC4M3/s3fe8VGU+/d/z2zJpldSqCEQCAGk995CsyCIIChXUAG72BW9iICNa7uAICgdwUaRopRQhEAogUQglJBCIAkhhfTdbJn5/bHsJMtuIAH0+vua83rlxTLzPLOzs7MzZz7Pec5BEw5SsMxwdQ9OLViL2WzEy9OFteu/5uTpk4ok4naqO7ZzpknHYM6kXQEEJFeB8n4aen80ucbbA2gaHkZm1gUupWeQl3+NBu51MJcZOXUlneWT4qz6iOsQVX+dBD8/P58NGzY4Teq6k8rYjZ7Fd4ri4hKnVnkyEogyfxy/QM9+bZz0vBXqASlVrPOqsteGDRtu470cIXQajrx14XUpw3WoNYzo0By5yEuxBGvQ4M7jy+8W1Go1kiRRVFSkRELfCt7e3kybNo2FCxeSlpbGihUrmDjx5tX4yhVdV1dXXn/99Zu29/X15V//+hd79+7l999/JyEhgY4dO960Ty1qUYv/v1BLdq/jyace4+WXX6G0rJCLF9MV4iIIInM/nQ1A//592bBho0OCmNlspkuXzoCVBLz//iwMhooJHXq9nvT0SyxbtpznnntWuaHfbOZ5QUEB7dq1Y/78+YiiSLt27ejUqVO1PHIDAgJ46qmnWLJkCf7+/rRr145du3Yp67/77jvg9qt/Wq32tsmuobCMU6tisRgrCIhskTGVGTm16hCdp0XdpDcYDAbWrFljR7IqT9i7sD8dsD+uollAvRVKPWXUPUHlAyWCiedesyZYy7LMjl07AOuDzquvvnpbrhUrV64kNTWV3vOfomdJOQn7YtkWf4BcHzOH447Svfvt2Y8BNGhYjwYNKyKKT+WkUVSUiyRpUalUPDutYvLh4vk7mPzU04TUvXv2Uzbk5+ezceNGxWbNy8uLIUOG0KJF9VPwqsL777+Pi8vt2dBVhSFDonj3nfcwW+zLIAIqPLRB+AVUj3TdCJWowiI1xJqEbr9lqJo8V3ZJuJOHAqFhJHLf8XDgByvhlYFmnRH6PkLbtHQH/9u/A3r37s3GjRvZvHkz48dXv0Ks1Wp5/vnnWbBgAenp6SxfvpzHH3/cadvt27fb/f9WRNcGQRAU95KtW7fSpk2b2upuLWrxfwi1ZPc6RFEkPv4IA/oPQ6vVotfr8fTwZfnypURGNgdg7NgxfPTRJ1y8mK7MTnZzc+PBBx+geXNrm8OHj+Di4mJHdsGqV/vlly0899yzSqXpRknEjQQyLi5O0fbt2LGDHTt24O/vT0REBIIgUFZWhl6vR6/Xo1KpGDRoEEFB1pSpLVu2ANYJbY0aNVK0ajYf3juBq6vrbWt2r124iqhV2ZFdAMlkIfNY2k37Hj16lN9++82uouvn56dM2pNlGekmon1VkYBLDPR5ryd7jscgyzKenp64u7vj6+tLYGAgPXr0uO3QjcpD9lofdzo9MIA6bZqwevVqdu7ciY+PD5GRkbe1bRuuXMkmNDSS8vIirMRKRi36kJ6WQ2iYldxOfi6KRQvWMnPO7TtL3Ii8vDw2bdr0p5BcG2RZvuvWY23btuX++0awYdN65Ov+uQIqvFzq07RJM1q0Cq3R9i5dSuHChVgE0YKHe33ate8IJAEmIAAIRSU6/wySJN1eIEsVEFt0RW7eGcoKwcUNQWN9UHDmwf13gG1U7Ha+Y1EUefbZZ1mwYAEXL15kxYoVdqE6Npw8eVJ53b//YH7+aTOdu7SnQYN6Dm0lSSIvL481a9Y4SJeOHTumXDNrUYu/JWrnp9UItWS3EpqGh7F950a+//576tdvwIoVy+3Wu7q6cuTIIT755D98//2PuLm58cwzU3nqqScoLdHzy4/72b71IE9PnYrOtaIyuHjxt1y5kk1wcJDdEFtycnKVJvODBg2iWbNm/Pbbb/j5+dG8eXMSExPJy8sjJibGaZ/k5GRCQkLo27cvWVlZ+Pj4KC4RNq3afffdx+bNmwFYt24dY8eOrfFxcnd359q1a5jN5moRw93bD3LuzAWG3NsP/yAvJJOToWoBvOr5Ou1fVFTEvHnzFKLQrUFTDl2y2hdVJlvHjsVzTZWFC45DtwIyXR5qyLBZExBVKroP7Qs4103fTYSGhjJlyhQWLlzIzz//TF5eHr169brt7TUJa42pvIgQF1/yTMUYJTNmqYB1azfx5vSKmfG5+TebQFU9FBUVsXfvXs6fP6+MZnh6ejJkyJA7Ju1V4c/w2f1p/RreeeMTFixYjAB4uzakdWR7Fq99u0bV1djY7bRsBV261sHFRUNJiYG4uI20bzcWtfrWVcDKD5p+fn5cu3btJq2rB0EUwcP57+bvBEmS2LVrF4Ig1HiimQ2iKPL000/z1VdfkZaWxsqVK5kwYYJDGxtGPDABQRAwGk08+eR4Pv3sfeX7zsrKYvny5Q6ytIEDB5KcnMzBgwfp2LFjbXW3FrX4P4JasnsDbMk7w4Y5Txrz9vZmzpxZzJlTcePKyynkwQGvU3CthFFPNuPGYfTJkx2DHm6GN954Q4kMdnd3Jz8/n6ioKKKiojAYDJw6dQqNRoOXlxeenp54eXmRnp7O1q1bycrKYu3atYCVrMyaNQtZltFoNDz11FO0bdtWIbvnzp2r0X7Z4OPjw+XLl7ly5Qr169evsl3qhUt07diP3MIMBEFEmmZhYI/7eaH1MK4mXLIjvWoXDa0mdCMvrwAPD6uhvyGvhOyD50nNu2wNHLDIDEzI50yeEfytDxPHjh2jRZNIPnr0S4TLGiCYIHcJLPYk1jvYwL0fVGj9/sqUrjp16jB8+HC2bdvG7t27iY2NZdy4cdSr51htuhkupl2mm0dj/sCDQosJF42Obl4hHMqJx2DKZd6nW3j+lXsBCAy+fZu5srIyNm7cSFJSElAx3O7r68sLLzi367pT2Kr1dxJlXRUEQWDOJ2/w7syXOHMqDW8fD8LCa3bsDYYyWkTKuLlVRHl7eOiIiKjD4cPb6dHj3ir73vhA+9JLL7Fy5cqafYhqQpIkO1L9d/GQ3bdvH0ajkVatWuHm5nbb21Gr1TzzzDMsWLCA1NRUVq1axWOPPaast02UtFgslJRUyM2WLVtH164deXjMAyxfvtxuEq+rqysDBgygdevWaLVa6tevz/Lly4mLi6Nr1663va+1qMWfBpla67EaopbsVkJhYSHnz5+ne/fuhISEOKw3m81cvXoVPz8/Pv74Y7t1A0bVdWivLzXi6u6o/VSr1XbDmW3atCEhwRpeMWDAAIXo2tpWhk6nczp5omnTprz44oskJSWxefNmSktL0Wq1SqRuUVERX3/9NVOnTr3FUbg1bMESV69evSnZ7ddjGFcL07H+Mq3LdsX8Qsc299C3R1Mu7juLhIwZma3GROYMn0BpqQFRFHip32DCL0sIKhGLZIaBIhaVwPb29pGjbdq0ZVb/z3CV3VCJ1mOVW2bBRW0i2E9GEGX+KDtD64G3r5etLm5WJezQoQPNmjVn/peLKS0tYsmSJUhGV5574SkCg6vnN/z2/S9wpCiL8uspXWYZjhdl0bVOW37POQHA7p1/0H/QPXf0OZYsWUJBQQFubm7069eP9u3bM2vWrDtO37sZbGT3z6yk6VxdaNep+W31TUw8RuMwx5uLu7sOjfZStbej0Wjw9vb+0+yt7oZM6W5DkiRiYmIQRfGWPuHVgVqt5tlnn2X+/PmkpKTw2WefMWzYMLvI9m+W/GTXJyDAm5Ur19KufaRCdDt37kznzp2V65kNjRo1IjQ0lJiYGDp06FBb3a1FLf4PoJbsVoItTccZmaxJpv2ezWlkpBajVot8tvQp+vTrgZubGyUlJXzxxRcK0Q0ODuaRRx7By8uLESNGON1WTb1Hw8PDefnllx2WHzhwgOjoaBYvXsw999zDH3/8AcAPP/zA0KFDWbt2HadPJ9K2bRvGjHn4ptUXWwxnVcESslxOWtofpOec40ZhUZMmjbiUnsKq0jTO5uipE6IjMTmbEstVpW2w1p0GF/RIooqkHir0vs6HtrUmifjDJ/C+xw3LHxWnskpQUWay8PXZvaQY0vDUqPl3mgf6zz7CZcoLCK466/DvLbBz5z7en/kfUlLSaNWqBe/PeoMuXTpU2d42LF1V8tPrz3zFgT3xePtr6DO8EVoXA/O/+pJmzZoxbtwjt/yej188pxBdG8olCyeKsvDUeKJSiXdEdCVJ4vTp0xQUFBAcHMyUKVPs1v+Z/qN3ouf8K6BSqanq41sszisskiQ5nAsmk4lNmzbd7d0D7L2vGzZseNdsx+4EkiSxevVqLBYLnTt3vmsPTGq1mueee445c+ZQXFzM999/bze5ccrUMahUApJk1fHbzl3b5FxPT0+GDnU+egdWz+4VK1bUVndr8fdFrfVYjVBLdq/DZDIRFxdHREQEvr72GrhbEd3D0Tl0GVCHpFN5HN5dEVMrCCK9evfEzc3qe/n9999jsVjw8fGhf//+tG7d+pb7ZW+DdnuQJEmRLLi4uNhNxvDx8aFJk+aUlZVRWlqKu7s77777HkeOHFQCJG6ELUUtP9/R51OSriJzlssZp5X9Dg9vwvjxjzi0bdrH+m8XKkImonckMCCqDWcdWleCLCMARo0IGHFrr8JgljElVrARjaAhQOOPpM5hab9I/FVgOpvI1YkvkZHrT51B7Qh78QFUbs5n/2/YsJVJE1+krMzqJ7x3bwyDo8awZesaevbs4rSP7SHG2VB80tlLHNgTj0FvxHDZyA9fJ9JtUD1Cm/mSnHyBDRs2MGrUqKo/skUiz1S1t/GEh8dRJzxA+X91XQ2MRiM//fQTly5dspsgee+9jsPy/2Sy27JlJ/Kv/eawvLTUgEp0/jupqsoaHx/vUE28G/jyyy+V18OHD/+fxkVLkkR0dDRHjhzBbDbj4eHB4MGD7+p7qNVqRFHE1dWVkJAQUlIqrOBcXdWo1SKiKFBUVK7kb4SFhZGfn8/TTz99022HhobWVndrUYv/Q6glu9eRmJiIXq+nc+fOyrIb9W+Jicnk5RZQXm7k1KkkzGYLjz46mqH39WbxFxsxGComO6jVKrr0bImHp6uyrZycHMCa2V7dCkdwcDD5+fksW7aMLl26EBERUaNKr8FgYNGiRRQWFqLVaikuLlZ0baIoMnfuZ+Tl5SkVqNLSUsrLy5k27VW+//47p9u0pSYVFRXZLZdlEzJnAYm01AyeemoS9eo5JwJVYUCUo22TYJZp/ZsZAZkANwP+LkYkQUDfoh7RXiIGVRnccEgssoSHGEqAtj73+F3/vMj4eum5nGUmZ+dxDJlXaD3PUYMqyzKvvvKeQnRt0Ov1vPXmLPYf2OJ0300mE1qt1un3k/hHKqobfHAP7cwgIMgNbz9dlbP0zaUGUj7fSG50AvV1XhSW5Di0UQsiEV2ak5dvde6YPn16tbSv8fHxbNmyBYvFglqtJiAggODgYNq2bVtjPfGdwlaFvHLlCgUFBTdN5vpfQK3WcDU7CI0mD0EAlcoaVX087iq9ez/q0P5mD8jdu3e/bb18deDu7s7p06cByMnJISYmRvl9C4KAIAhK1LbttUqlws3NDQ8PD8Wh5Hb00xaLhX379nHo0CHMZjOiKNKhQweGDRv2p+nkNRqNYmVmkQ4hywa7B7OffzrNmTO5BAUF2el7b4VevXqxatUqzp49W63CRC1q8VdCrq3s1gi1ZPc6YmNjAaqcOFJcXEqLFmHKRXTgoApbmvyyM4x6qjk/f3MOURQQEAiq68/cr54HrER34cKFlJeX07hx4xoN5UVFRZGcnEx6ejrp6el0796dQYMGVauvwWDgiy++oLy8HG9vbwd7nSlTpjBz5hyHoVaz2czmzc4JHVhJsiiKDn7DFimXObP3XP+fxoHoHv6iDJWgxrM+FFcyC2gzWY3G1f5G2GSbHnfJ8fT00poRXF3QuGgIf20SSft2cT7pPOZK6auSLKGXytiXv45mHr1JL3ankZftZm/9k00SJWeyKElOxKOJvbOAXm8gKyvb6Wf/448zVR4XSZKqJAj1GtZxmu6adr6QNl11TlPvABJfW0rJ2UtYTBbaeNzDhbK9dlIGF1FF78BwhejCrSd5FRUVsW7dOrKyshAEgV69etG/f/+b9vkzkZiYyMaNGwGrbv7LL78kMDCQqKiov5WNVqtWnSktLSYhYT9mcwkNGraib19HX+gbia4zP+u7TXZtHrFgfWD9/fffleWVPbZrispkWK1Wo9FocHFxwcXFBa3W6vFcXl5OWVkZBoNBeZAWBIH27dszdOjQP2XSIVivb5Ik3TDiUO4wAnHmjFVu1aNnBDVBaGgobm5unD9/vpbs1qIW/5+jluxireQ5i+mtDE9P55Gisixfr5DA2KdbEdG4Kw1Cg+nUrQWCIGAwGJg3bx5lZWWoVCpGjhxZo33z9vamTp06SohCTW4chw8fpry8nICAACZOnGgXUzpjxgwnN4oK3Op9XFxcKC4uJjY2VtG0zZm92KFdZmYW3y5ZgwYN/byfBOyJLsCxxXqOmfdSWd/7eL3WdPOuhyjJIAioNGoaD21JSJgnmiB/PHvcg+iipbDISuDzLhvwEV0AmYv6VHbmbUUvFXGyaCvJ1+6nkdf1mGODGlm2fmZBLVCWftaB7Op0Lri7u1FU5BiBGxJye0ENHbpEULd+AGkpWZgruVCkniuiTdcg9Ho9x44ds9OLl17IpDQpA9lkIaNMhcYcxgMBMgmlCVwyFOGr1tHRuxktJ1XoiN3dq46+lSSJLVu2EB8fjyzLBAQE8Oijj+LtXbOY5ruJmJgYxZJq9OjRWCwW9uzZw9WrV1m9ejVubm5069aN7t27/6UOGlXB3d2T7t2H3bohVr/bRx91rPrWBF9+Pp+d2zfi4urNzxt+pmvzASBIjBlzH9NmVmjzbZNaNRoNPXv2RBAEJElCp9M5HDerH7X14U+SJGRZxmKxKJ7dBoMBg8FAeXk5RqMRk8mk/BkMhirjtCtLUKKiou661lWSJDjt6iYAACAASURBVIxGo/JnK0y0bNmSPw4nkhD7BwNGeBLUwN2uD4BaLRIZWTOyK4oi4eHhnDt3rsZzJ2pRiz8VMrWa3RqiluyCIi9wBnd3dwIDA/l93xGiow+QmVnR1s3NlR9+/JZWrZqxePFizGYTp5L288DD04mOjub48ePo9dahcJ1Ox2uvvXZbF8zsbGuVcezYsUp4xa1QVFTEvn37ABgyZIjD+2ZlZRESEsKIEfezadNmu4ALrVbLuHGO/rsFBYWcP59M/fp1GThwIFu3bmX79u0kJyc7JCK9824fjhw5y+QRKwELBtmASS5HJdhr32RkytV6/DR1EVwKMckQGOhPp1dG0rt5SzKjTyFq1TQY2haf5iFkZ+Wzb08Crr8eo8/AdspN/rIukZVJu5AwIVcizTISa86m0bdhM2RJ4PKVCmJnMUrkFZkoO5RC3Tb10bpZCfF7b39MSVExyBICIpIMgmj9vt9++yWnx3v//v2YTKYqtbKCILB600xee3Yesb+fAgEahgbz8fxniT22mytXrrB161YsFgudOnVCFEX0l3KViXQGyXp9U1ua0kHXlA42w45K1eIRI0bQpo3z9K6EhAS2bt2qSC2GDh1K27Ztnbb9q/DLL79w4sQJVCoVEydOVKQTrVu3Jisri+3bt3Px4kWio6PZu3cvERERDBkyBA+P27dV+ytxu36yNjz//Bhmz3mcxx6fhlarZtuvcykWrpB4Lokjsw7y3Q8/cfTMQQAlftfPz4/evXvf8b7fCpIkYTAYMJlMdpKH1NRUVq5cecviQXUQHx/P1q1bbxrEERYWRkl6Gt3GQKPm/mi0Ivs2XKb78LpotKJy3TObJWQpwEHudCs0a9aMhIQE0tPTCQ0NvYNPU4ta1OJ/iVqyC3ZDyA0aNGDSpEkObUaOHMUTT7zEr9t2odFoEEWRjz5+l0GDrLOsZsyYoQxfzpkzR+nn5eVFixYt7qgy5e7uTkFBATExMdUmu2q1GlmWcXV1dToUvHjxYmbMmMHChQs4efIUmZmZmEzWkIjw8KZ88slHSltZlnnnnQ+ZP+8btC5ayg1GBg/uy8JFc1mwYD55eXmYbjBnB4HGQiCzw8czpXAp2YZsTpbtoJ37fYioEAURi2xGrRYIbnsNTaGJ0ylG7mnTnG9XfEjdetYkuDodGitbfOnJz9m6MQZkEEUBjVbD8+8MAMAnQIYLssNkPhmJNEMJ+SWeXL2qw2S0nvKlgooTmS6YXjuLqDqPRqtiyMzhTJn1Jsf+sNrACYKIJMsgyLi46Jjx3ms8NuFhp8c7JiYGQRAYN25cld+Jfx1vlv7wDiXFeoxGE37+VoLSsk1j5Zz57bff2Lt3L2+88QZuYcHI12NuQ3QSN9oqht7gIteyZUuH9ywqKuK7774jOztbGVoePnz4/7RKZTabWbp0KVlZWeh0OqZOnepQXQ4JCeHxxx/HYDCwc+dOTp48yenTpzl9+jR169Zl+PDhVU6g/F+i8iSpgoIChYTWFA+NGsLS5S/i7u6qLOvTpw0f/+df3HffdGRZ5tjZY3SN6EfsWat0SKVSUVZWdmcfoJoQRdGpY0uDBtZAF1vS3u0iLS2NTZs2IQgCwcHBqFQqRUqhUqkQRREfHx9yTqcycEo4Z36/xqa5aeReNhAS7kbWmTLGvt0Ms7mi/HU7coomTZogiiLnz5+vJbu1+NtAplazW1PUkl2wqxxUlbnu4eHO998vIS8vn5ycfMLCGjpobydMmOCg+S0qKqJDhw63fdMDa0V30aJFN61A3wg3Nzfq16/P5cuXSUxMJDIykhkzZhAXF6dECQMEBASQmHiSnTt3cf78eVq1akXfvn3s5A3Llq3lqwVLMRjKlRjkHTv2Mn36HOrW9eZiahoffPih3fvPfHs9Pc7URTJITG4wgNlJ68g2XeBg8Xc0cemEu8qXcrmQdHMW5tiKqvLxuEQeGD6Vw8d/tiNkH767gq0bKpLjJEmm3GBk689xdOgVRN0mIQixN4piRfx0TTC7RvLcRTO9fQW6ygJqFzUnM3VYZAmVKIAsYy43s+3dzRw7G48gVLyvIAjIMuj1JeTl5iuylcqIj4+nvLycpk2bOvVnvhHWSYsVJEatVjNt2jSSkpKUCWMAbo0C8W7flMK4JDwwI2BBllXW93fyy50zZ45CBF5++WV2796t2OkFBgYyfvz4OzoP7wauXbvGkiVL0Ov1BAYG8sQTT9xUw67T6bjvvvsYPnw4cXFx7N+/n8zMTJYsWYK/vz+DBg2q9gPgneDo0aN4enoSERFBVlYWsbGxikTo9OnTREZGMmDAAFatWqX0sVn03Q6mPjPEjugC6HRa+vZrQ5cO7TkcdxyQuVSQrKzXarUOkeN/NWwTHXNzc8nNzeXqlUzmfvw+mZmZuLvpGDt2Eg+Pv7W0w6YzfvTRRwkLC6uy3bVOO4j/LY+Vr5/HqLfe/VPiirl0upT2/cPJx0r+K088rgxnv+fKcHFxITQ0lKSkJKKiHPXZtahFLf7/QC3ZBXbs2KG8vlXFy9/fD39/5yEAjRs3ZurUqaSlpZGXl8fx48exWCz88ssvBAYGsXDh1xQVFTF27MM88cQkXF1dnW7H8T39lRvZkSNHqrxw3wibnVNlgtOhQweF7H733XeMGzcOURQZPDiKwYOdX8w/+3ShgzOBwVBOctIF6tbtgJePfVVux44Yjh75g8VtHsVb0NHOuwHvhI9hXtp2Ckw5xJf9hkrljpsukN592iMKAhfTcsm8nIvFYiHnaj6HDp6gR0+rFtVkMrNqya9O9+3ihQI69AqiSedWNN5Qj9SyDMyy9eGlnmc3XNS+FBXLFJ3L56JrEYldQpj+Ymfkl8443OQuFF4EHG981nYq5s//Fq2LlnfffcVuvW2y0T333L7HrZeXFx06dGDHjh122seI2Y+RvnQH2VuOUC6VU2aR0alUCEZwNiZrsViwWCxK6IlKpWLo0KF06FC1P/BfhYKCAhYuXIjJZKJ169Y10q+LokinTp3o1KkTaWlpbNu2jZycHNatW6cErfTp06fa1Tuj0cjatWspKSmhTZs2dO3a1Wnf9PR0Vq5cqTyA3Ajbd3/w4EEOHjxot27s2Ec4ciSOYcOG8OCDo5n53lzS0i4RGdmMYUO7W7NWLNbglBtRt65zazKTyYy3b8V1o7jSJFFXV9e7EkF8pxg4cCDr1q1j2bJv+XHNKn78ZQZeXu7IkoRao2bSxAdYuuzmXsNhYWFkZGRw8uTJm5Jddy81P85KUYiuDSaDxIppx/AdaV1+Y0T30aMnePGF6Rw//gfu7m48+eSjzJr9ptMHL1ts+4ULF2jatGl1D0MtavHnoVazW2PUkl2wcyooKiq6o+pXUFAQQUHWIfghQ4Ywa9YsLl26xCuvvKG8x4kT8SxfvpKDB/dXy5lBrVbz/PPP8+mnnxIfH39Tsnv8+HECAgJo2LCh8n5VpZwlJSWhLyslYe9OVCoV7QcORaVyPCXy8pzfQHv1sSdQkiTzyUfL0Wm88dLVZ3P9PJo3q4eLoMZFCmPOlSlkHk5jbc4JPBr6MGxYb3Q66+dv36kpBr2RJV/tQAYyMypml+deLawyqEEUrNVclUrF1l8W86/RL3Om6DKi6IWr2heECuJo0Js5cfQKJ4451xO6qXROl4NVW1xWpufLLxYzffo05aEoNTWVpKQkRFF0KiOoKbRaraLzBhC1akKnDiN06jA+7/QqhgsyRkXPcPNzZ+DAgXTp0uVPmw1fE5SUlPDVV19hMpno3bs3/fr1u+1thYaG8swzz5CTk8P27dtJSUnhwIEDHDx4kLFjxxIeHn7T/hkZGaxatYrycusoRXR0NNHR0YiiSIsWLQgJCSEvL4/Tp08rD4w2b+mSkhKCg4Np3rw5Hh4epKen07hxY3bs2EFhYaGd9r1du7a0a9eWK1eyWbN6Db37tGPosG6YTGb05dYKbNKYtwl57VE8u7Sy28ddu07QuHEwWq2jv+vx4xUu1A2DGyivbdHiZrP5f/qdN2/enICAAHJycvhswSvUretvV0T44r9P88yTj/PVN8sd+kqSRHp6OpGRkRw6dIiEhASGDx9e5edJPJJPSb7J6bqCklJcDdaH18r9k5JSGBz1MKWl1qpvSUkpX3+9goyMLFavcfQmvueeezh48CBr1qzhySef/Mtt+WpRi1rcOf7x00vLy8vtZAzz5s3DaDSybdu2KglWdWGz7BEEgWefnYpGY73glpWVcfbsOX780T7S0mAwMH/+fGbOnMn7779PSUmJss7DwwMXF5cqU8sAli9fzubNm1m3bh3nzp2jvLwcPz/HKnRlK6RP5v6HqFHjGD9yDp39hrN5saO3bu/eXZ1WvG2SBrBWnH7fdwwvtzpo1FrGPtabe9qF4uKuATcBs4dATlMVutFNmPDSQ4wcORCdTkthYRn7dp/CbLbgorPe2C1mC+07VBBHP39PB49aG2wSXVmWCe/fn5grR8k58hsT+4y0I7o2lJebySorQTI7+oDV9QxGxInuV5aQrwukysr06PVWorJ+/Xql6mfTcd8pPD09sVgsdudeYWEh33zzDb0mhNGwn4hfC5k6rUWKLzuen5Wrwj169PhbEF1Jkvj2228xmUz06tXrjohuZdSpU4dHH32Ut99+m27duiFJEj/++GOVQ/mSJPHDDz/wzTffUF5eTseOHXnxxReVh0dbgtyuXbs4ceIERqMRtVrNiBEjmDJlClOmTOGVV15h/PjxdOjQgebNgxgwsAFhTUw0bVrfjuju2bNPIdPBwUE0j2iMp6cbpaX6SvsjMzh6L33vf4bV87+zO+/2RqdSVFSG0VixzdJSPW+/uYzc6zZzKpWaBm6NlPU23XNlG7L/FWyxwPt/v+ywzsVFQ/N77IN7DAYDa9euZc6cOaxYsYKvv/4as9mMLMt20pAbcWx/CRqd89+dX6Xsl3nTnuP9CRN4dfQsBnWeaPc9gNVucPPm7WRkZDlsx9XVVZG3ffPNN3cc8lOLWtwNyPJf8/d/Bf/7O+H/GDt27LDzizWbzXx4XX969OjRm85wrw6Cg0PIyLiMVqth+vQ3WbhwMdnZVyktLWXr1m2MH18xoemrr75SfCplWWbhwoVMmzYNtVpNQkKCcvOcO3cusixjNpsJCgrCYDBQWlqqVAT1ej3r1q0DrClnt0qAe/mN15XXcZnniXtvpl00amTLBrSIfMKhX2UZgEajpm+/TvStxGNkWWbVsj2UXDMw9YWhiBoBy/VipE6no0WLSD5491ualJWTm55HcFggLdvUJTs7j3Xf/0D9+nXw8fGhtLSUMZM7cGhvEhdO2ae2PTC6P4KQRW5urtUeSKNB3a4jusbHEeIu2jkzALi4qKkX5oXPvzQcXpKBIFs/hwSERATx7wff4L0PPq50QxOQZTOioKFvv874+niRkpJMaWkpJ0+eRKPRYLFYFK/Rm8UsVwfe3t5kZWXx1VdfoVarFfs6WxRscJsKt4fKN92AgACioqKUONS/E7Zs2UJBQQGhoaF/ip+vWq0mKioKWZaJjY3l888/Z9CgQbRv3155AElLS+P7dd9jKDfg5ubGQw89ROPG1smPQ4cO5dSpUxiNRsW2q6CggICAALp37273XpmXsti7LZq23YJp3koLSMTHZxEbe15ps2vTFt58dRzHkqyhKwMHhXEtXw+Wct6fvQ2tRku/AdYfSn55IUVmd96aMZ+c8nKmvTIRgPUbNzByxIP06RfKgIFtuXw5l8Vf72TXjiNotS6EhjSkvrYR/wrpq+hObQ+2V65cuWuT986fv0Bi4jkGDuxTIxeMoKBACguv4uMTxK/bkhh+b4WuWq1WEVinQvoUExNDdHQ0siyj0+kICwtDlmWKi4u5fPky6enpHD9+nPbt2zu8z5NvPk5W/FekH8rFbKz4PagEGZdKh6DsegXcE4msTcncGGMOVn3uhQup1KvnqLuvPNr3yiuvYjQaGTPmYQd5RC1qUYu/J/7RZDc1NZXjx4/ftM3GjRvviOw2aNCAuXM/Zdy4MQCMHz+Wzz77L2q1WhkaBWu110Z0o6KiOHXK6pDwySefMGXKFMV039bWBpv/blXw9vbG1dXVbiJGZVsgi1HGcM1WHrX+owsAldpeuyoIAkajhYJrhYCAStDiotPg4VUxlF5uMFJWZkSSJDIv57M3+hQAGkFN9sFigrt5YrCUMWbMI7Rr146sf89jfVgAggClZUbWyDL9BrRDkiTM5lLS0iqFVojQtX89uvSrS/SmNIpyTTz32mieemEEixcvJisri8TERFq1sg4HP/vOSH78aZcD2VWpBHr0q8f3Kw9R0EaHzgO0HiIewe6UeBpwM8OcD16m4FohgmjTcAvX+1qJ0/r165XtjRkzRhlO37Vr1x3bTdm+27y8PLvlKpWKl19+mUuXLnHx4kWMRiOdOnVSJDNXr17lzTffplGjBnbbulPyfeM+1BRpaWmcOHECFxcXB3u6u43BgwcTGxuL0Whk69atbN26FVEUlSq5LMsUXpSI3ZRDQ+/TNJ7c2K6/IAj06dOnyu3/Z+a/efLF7tw7LhBRlFj19UGyiywYDBUjQ/6uJaRcKebjBZsYENUPURTo2rWB8v5Rwz7k932pxMRcJjPzIkX6FERRgyw35fO5y5j6zCO4ulrlNOs3blC2e+yJOQzTd2VYE3vv2uKrRRw7fJRt2ys07TarwjtBRkYmkZHtKSqynYcC/foNYvfurdXq7+Ki4/jhowy+934SErIZOixcefAoKdETvSOByMgEoqOjKS4uRqVSMWDAALp162a3nWvXrjF//ny2bNlC48aNHaLcAaZ/9zTzxs3n5O95yDKoRGhW10Kp2vn52q9fJ/bsOeKw3GAoJzzcqg/Ozs5my5YthISEMGzYMIzGcmJiYujRowfe3lbi+9NPP3H8+AlefNExhbEWtajF3wv/OLKbn38NSZLx8HBj8+bN+Pr68vjjj/P5558rbUaNGsXPP/+s/D8hIcGO8ObnW2flVyfffsCA/hQWFvHllwt48cVn8fLyon//Phw6dISnnqqolv76q/Vm1bFjR7p160aXLl1YsWIF6enpzJ8/H7CSjUmTJuHn56f4yxYVFZGQkICXlxfh4eHodDpycnJYu3YthYWFFBYWMmHCBDs5g63SW1xYisroilsdgYxYC1eOStzzpMaO6Pr7+5OXl2eNkPWuz9iRHzhM7Op7XyPqN/bi4IGTnIzPdFgvyRJc0JCbbGJN4Y/s2R3DD49NRnsqAdvIv4ckE5ZfQqqPO/pyE8kXksnMyqF+/Xp88cUcSktLOXLkCBcuXGDgiMbUqVMHTz8DJ06coFmzZmRlZbF7926F7IY0COCt9x7loxmrkZARVeDtq2Xkv+oxfvxsIiO7UCfSegwlLBQZiyCvIh3O08vDWl0qKqHcaEKr1aDTedChg7W6dOXKFUJCQmjSpAmNGzdm586dnD59+o7Jbm5uLqIoMn36dERRJCsri/Xr1xMWFoabmxvNmzd3cB+wxlx3IzMzi+nT31CWDx48jN9/33PT2ebVgY0s1pTs2iaBAYwbN+5Pl1TYIofDwsLw8vLi0qVLlBvKuZpWhKFAJvu4hdIroJLVrHwjhh5RHakfGnyLrVox67W3ePHffXF3r6isu/l7YrhaISvqFeHCyCnL0ZcZObB/NitXn0aq5BcnCAIqlYDRZF02blwvtvyyg8wr2ZQYLuLh2ZpLFzNpFmElXKdPpPLpe2vJzMilRbmK5oIr6kpOIRkjrd9r5nb7yZtHjhxh6NChNTl0DoiIaEtJSWWtvsyePTuYPPkFFi/+b7W28eWCr9m4aT2CoCE9vQAvLx0lxXr27btAWHgn5QE+NDSUUaNGOa0c+/r6cu+99/LLL7+wdOlSpk2b5iAXEkWBqcueYm33d9EJLqhFSByqBkGg7lEjxeZCshoF4FHXery6dW/Lnj1HeOvtpxAEgeLiUrb/doAOHTtQt24wJSUlLFq0CLAWEySpgIGDgtm67U3m/TeW4mKrtMTPz4+CgmtkZmYSEhJyx7+zWtSiJqi1HqsZ/jFkNzk5jcf/9Rzx8acRRZj69Fjc3a1aLC8vL4dITx8fH7799lvAWt2tXFm1YdSoUQq5qgpqtZo9e3YyfPj9pKSkEhbWmN69e9G/fz87AnrqlLUKaqvsiaLII488wty5cxWy8fbbbztc6L28vByG0oKCgnjppZdYsGABubm5rFmzhocfflipAtrg6V2RNFS/u5r69iO2vPbaa3z66acAfLd4BbsPxVNUYkSn8sZP15j6Df3p2Kcu3n4uyLLMhdTTiKKvnc7HHS+CVaGcL9VTLhVi0qtISspi64YNPOgTYPd+gzIKMKTn0Xv3PrKv64FPHD/DunXfKmlGBw4cIDo6mpycHHJycuxiV69du8bMmTPR6XQ0adKEUjGb5r1M6IsktFoNR+P3sO6nugwY0BdPT09CQkIYPXo0np6ed0TERFGkYcOGpKWlUVBQgI+Pz21tp6ioiLKyMkJCQpTvOSQkhGefffam/b7//gdyc/MwmUy8995s3nvvHcB6PA4ePEiPHj1ua39ssO1LTTXs33zzjVKBbtiw4R3tQ3UQFxcHQKdOnYiIsKZlPXvvHNJijIhO7ORmT13Cot/erda2H36inR3RhYoYWrCGqIx6cC76MuuEts1brZZgnp4VIx9Go5nCwnKOHskAYO/edB4e24//frkek6UUd42KLx5YiqUEMqR0zhuuAu5IQKooEqPWcJ9PQ/KMFnwfr1pScONDiSzLYCoGJNB435KUxcXF30B0K7B82fJqkd1Vq1aRkpKCcD1EZvWqkw5tmjVrxvDhw285Ibhdu3acP3+es2fPsmzZMiZOnOhwHXRx1eHR2xfzgWKK/EVklYC6TELI0HPe7EXGERMRI1R4NLIem7enT1b6enq689DowYBj1DNAXFwScXFJNG/uz4MjW7JyRbzdepuOd9KkSYrPcC1qUYu/F/4RE9TKy8vp13cEx44loNGqGDqsN25uOs6dS8PX17mNWP369Rk0aNBNt/vzzz9Xy8S9RYsWJCef56WXXqRly5Z4enpiNptZtWqVMtvbhoyMDOW1TqfjxRdfRBRF2rZtW+MJULYqY35+PosWLSIpKQmgWr6kcmJjfvrpJ+vs6JR0ftsXR1FJOSBjsBQwYGR9Bo4Mw8dfhyAIHIs9S2BxHeqqNHTo2BK1qMIbf9ToSLecJ8l0miLJTAvXARjLRI5k5yi64GWRddncuA4ARkkisFIKmUajtrs59+zZk+nTpzNw4EBlmVarVY6NWq3GZDJx+vRpcnNzad++LT36tqdT99Y888wURoy4Dw8PD86cOcvkyZPx9fWtkuju3x/LwAGjaNigLYOjHubQoaNVHi/b+1fHXaMqHDliHVqtqWzm6NFjiu68SZMKm6bRo0cSH59w2/tzI6qy33KG9PR0cnJyCAwMZNiw6sXr3ilSU1MRBIFmzZopy3IzihGc2ckB+VmlDssr45uFnzJs6BCaNrmHoOCbE7KNb+ykVev2dO/RlslTHubaNeskueJiI7Nn7WP2rH188nEMXy86ZtfPx6cpXl7Wh6Oc/CJ+zNrJCXMKPpZQIlXNkCQzAjKSJGMwqth09Rqa+ytcQ7RqN2bMmKH82RL8FOlGeT6k/ACpP0Lqekhei6x3PoGtqKCQf/WawItD59A7+D76tezk0MZsuTE8xhGxsbFKuEb37t3x8/Ojbt26REREKD7U7du355FHHqm2883o0aPx9/fn8uXLzJs3z+kkxIe+fBvfceEU6a8TdaOZA8U6MjKs33/agXKHPjdDixb218lz5/KoX9+LTp3s9dA27fzSpUtJTEys0XvUoha3BZv12F/xdwsIgrBUEISrgiCcqrTsPUEQMgRBiL/+5/QmIAjCEEEQzgmCcEEQhDdrehhqgn9EZfeXTb9hNpt5860nlWWHY/8g9vBJfvzxFyZNcp561b17d7p37052djaLFi1Cp9Px/PPPo9PpmDVrFmCdLHZjVdgZBEGgXbt2tGnThmPHjrF//35KSkqUyXA23Fgp9vLy4t13q1d9uhENGjRg4sSJbNq0ifz8fA4fPkx4eDhjx45l/fr1ZF+5QuIPGaT+Yb1Y+zUTCWqr4sJGmaUJD5KakURqSirefj4YjPaRnfUbWId/LRaJlPhsLsWKlBOERtJh/MOdVx9/hE+WrkXCSpBMGDDIxQTIDannEom7t56v76mogmR6qpT/qy6l0bddczp1bo0oiixevJgnnniCgwcPkpCQQGFhoUK8unXrppi9GwwGhWwmJSWxbt06ZFlm167dADRq1JDs7GxSUtKYMeO9mx677dv3MObhJxXnhezsHIYOOc6Gjcvp16+nQ/u6deuSkpLC5s2bGTNmTPW/pEqwaS1btGhRo34RERG4ublRVlZGcnIKFotFqe7VqVPntvbFGWoyCz0mxhoAcqMG88+C2WymuLgYf397m6uW3RtwOC3Dge7KQIsuVVtIzf9iNu/M+Ba93kruTiVk0a1Xhcb3UmIWumITBk9r5fKUhxYN0Ldv9TywK+OlaZN5f+YnyIJ1MuTJa3s5avoRABE1LUN6YHbNpUHzhnTuUuHzKllkNv83nWEDUmjT1fqQU69ePVJSUtiwYQMjH3wALm4GqRLJM5fApa3ITR5BqGS1dy03h8HhLyHIXoiCNyajBJeDGNrUn18v/Ka08/Cw99S+EWazmZ07dyIIAk888QT16tWzKxqcO3eOdevWIUkSer2Bz+YuZd13W7CYJUaMGsQbb03G28fTYbuiKPLMM8+wevVqUlNT+eKLLxg3bhwNGzYkNzeXDRs2kJ2dbfWZ7hWICiiR1eTlV1y3ynIFPpyzhMcnjUCtVrFu7a+46Fy4/74oPvzoXYxGo/W6mJ1NcHAwo0cPQZKt17nZs6zR6x/M+R2AFpHenEksdNjPH3+0HHtSAgAAIABJREFUfm9vvPGGIjWrRS3+j2M5MB9YecPyz2VZ/k9VnQRBUAELgEHAZeCoIAi/yLL8pzwx/iPI7sX0DPz97S/SObnXKC0pJS01/Zb9g4KCbkpoZ86cSZMmTUhPT+f1119XKoUGg4H//Oc/1a6IqVQqu4rl3UDDhg2ZMmUKH374IcnJyezevZv+/ftXGPo/Awc2nmTNh9EU55cRaAnjndP34e3vjm9Qe9b/+DNe3p52E30iIhor1dblc7/DrAnGhBEZCUEWuWpM5+LSCwrRtUFGIo9L1BdaEDg4tMp9HjbCfsb+lStX+OCDDxSy5ebmhp+fHwMGDLCL8Kx8c2nevLkSMdq//wD+859POXgwlsDAIFauXE5U1ICbHrdXX5mhEF0b9Ho9r782k6PHdjq079evH8ePH+fs2bNs376dwYMH33T7zmDzRa6pz/Njj41nxoyZ6PV6ZFnmu+/W8dhj1slgZ84kYjQa76jinJmZWaP2RUVFnD9vdSe4k/etCU6cOAFgV9UFeOOzJ3lg3TsIkkY5Z2VZxiKaeXveZIft2PD1NxsVogvw8b838N2W59C5qhFFkV9e2Ern8iC8W6rYXM/5iEvLSH9GjLRa6JWW6ikrMxMYaP1ut209x/HjFRNFn536GI+M60ZpqYmPZm9iT8xuJNmIhJmTWfsUaUpl7JiXh4zM9wv3KGR3/PjxzJkzhwsXLkBxGk5LM7IERcngW2HvNznqBZB9EAXrtcsq+xDJy6lPXT9/MvPzAIH//vezKo+ZJEmK7CoyMtKpH61NdhQREcGo+58lIeEs5QbrcV7+7c/siY7l90NrFZvGyhBFkQkTJvDrr79y5MgRli1bhlarVUbH3NzccHNzIzvTmjSpcb9hki0iHRt1ptxgAp31Qf2RR0bxwQdvK+epn58fsiwzZcoUSsty+c/cfU4/qzOiWxlz587lscceq40YrsWfhr+LZleW5d8FQQi9ja6dgQuyLKcACIKwDngAqCW7t4sOHe7hgw++ACAtLYPAQH/uvbcP5QYjHTu1u61tzpgxg02bNhEfb9VvJSdbNXpz5sy5re29++67d8Wn1Rn0ej1hYWGkpKSwf/9+Tpw4wSuvVKSA9RzRmp4jWtv1kSSJxYsXo7ke+tCiRRinT18AoHXrCkLRsl1Hjp5MwqZJkJGwyBLFgnPNn4yMi5f9r7TtlULig70RZJCrkBO6urrStm1bevXqVa2KSU5ODhaLBR8fH9566znef//W1XcbJEni/Plkp+sSE885XS6KIo8++ijffvstsbGx9OjRo0ZWTQClpaW3pR328fHh4MHfmTjxSY4diyM9/ZLd+g8//LBaow9VwTZZ0+bjejMcPnyY7du3A9Zqd2Rk5G2/b01g07x36mQ/9O7i4sLS+Fd5YehnlGZaTy63uhKLtr6sDPlXRlxcHNHRuxj10L0UFpYQHR3LubOp7DgUx8ND/8vL0+8jolUg9co80GpUePT1Ytp9rdi4/iypaVZ7uCsZ+cQducDCL3P592u+/HfhCNLTr7D79+M8Pqk/er1MXFwBslwhf/EPCqFNh7rM/eQgvQZ25KGHevHenC/59IsnuZBkf13Yvz+G48dO0lx4CAGBqxkVvzVRFPHz87P6cZvLQHLyoC1bwGQv4UhPE1AJjueejEy7kPYUGI7w5Zef8vjjzh01Lly4wIEDBzAajbi6ujJq1Cin7WwewFezizh9KkkhugBGo4nMzKts27KXBx6s+qF/6NChtGzZkn379nHp0iVcXFwYPnw4rVtbr2Gzx6/G0OAC4nXpstoVwh9Qo/NUU6d+P4qLi/Hz82fBgi+dTrrMzc1l3rx55OfnO6xzhqlTpxIUFGSn9/Xx8WHFihX079+/1p6sFv+/I0AQhMr6q8WyLC+uRr/nBEGYABwDXpFl+UZSUA+ofLO6DHThT8I/guz27duDVq0i+OzTFRgM5TRt2pCHxwxh1EOD6NmzE5IkUVJSgpubW43IxgMPPMD58+erpdsFaNq0KcnJyUyYMIEVK1bYrYuOjr6lRvh2EBMTo+TMq1QqLBaLXVhFVfj111+VYXVJkki+cFFZ99NP23nooSjCm4XSdXAELbo0YPOGo1zLv75dAQfLrwrIDHmyQlf68EOt2L/7IuGeWgbf15SL6YVs/uWsXY/u3bvX+Nj4+/uj0WjIy8vj559/rvLm6wxWwuBLfr4jYa9Tp2oHjpCQEAYMGMCOHTs4dOhQjffZaDTelr0XWCtlhw4doLS0FJVKhU6nu6W/8q2Qm5vL6tWrlYpzVQ8Zsixz6uQZzBYLx48ftwZ8hIfXKA74TpGVlYVWq3VqTVW3QRA/nfr4ltswmUxKlLYgCPj4eDJq1CDy8wtZtPB7dh85wenJKZSVlPPfCKtPbnmoO646NU0SJVJ0MoIo8NBZDUNdmrLUXabN8IboKOfh+1oxsGcYWzec4lKZGq1WS/SuvQyK6gZYj+vcTyrihrML9Hy37n1iYjKweQJGRPjTo2cIH38811p19rH+zroNsk/uq1OnDrm5uSSmlxDpJjqWgAQ1uNm7UIiChCzJTievNQlvxJZT26o8bkePHmXbtm3KcXM2gcwG2yjXH/HnMJnMDutLS8o4EXf6pmQXrCNWjz32mNN1T8weyvz581G5QuR4NW4B1n0J9A8kMMQ6KTY8PNzpb619+/bKckmyUFBQiL+/K0ajheJi53rlRYsW4e/vz6RJk1i6dClgnSfh5eXF7t1WCVUt4a3F3cZfGPiQK8tyxxr2WQjMwnrxmgV8Cky6oY2z0taf9qn+EWRXEAS2b/+ejz+ax+rVP1JWZsRkEtBoZObNm+e0T3UrYa+99prd/41Go6LDbd68Of369XNwQbAFBABoNBpMJhMHDx6862Q3Pz9fIbpQcaO51TD51atXOXbsGFqtlrxcA2tWrqNzZENiT6VhMltoHR5CUWYBbUd35NdfdxBS14/7R3ZmxTe7KzYiy0q114bJzw5WUtIAZIvMw1E/YrFIqF1E9h+4SHADx2ro7Rjki6LI1KlTmTdvHqdOnaoR2QV49dWnmT37c8rKKpKW3Nxcef3152/az+bEYCOINYGfnx9Xr16lpKSkxlVhG9zd3R1Ibk2kBMnJyWzbtg1BEBSvX39/f8LCwhgyZIhD+xMnTjI4ajSFhcWAzP3396NV62a46a6RkXyaJi07OPS528jLszpRNGrU6NaNq0DliaIPPPAAKxcs4NQf2XQf2h5fXy+efGwkm3fuYeLj93I5o5hSNyiNMyFllXB+azpl2Zl4+Oko9VZzpKc7vffrGXN/JMPf6oK7u/X413P1RhtYB5esMo4ePUbMwRgGRVWdJrd/v72H9kOjW1FcXMboh/uwakU0JsmAr48PD03ubddu4MCBnDlzht92HyLy4UgoywL5OrEUVODiD+72rgFtO3tw/JAFweGWIPHekpuPVtn8wdu2bcvQoUNver4FBwdz5coVvH1c0Go1dglxAG5uOho1dh5vXl2ENPbHK9AVg0GvEF2Abj270LZt25v2bdq0KU2bVuiiLVIMYN3Hzz87SGmp9fXUqSMoK/PCYrGwc+dOrl69qhBdG4qKimjdujW7d+9GrVb/Zfr1WtTifw1ZlhWzb0EQlgBbnDS7DFS+ENUHaqaZqwH+EWQXrMPg7818nfdmVqSF3azytWXLFu69994avYdsLkdjMfDvf7+LIFQtSahMZN5++21mz56tRMTeTSnDgQMHlNevvfYaarW6WsRnzZo1APTqOYDxI95CJ4Vz9qwRweKBLBfyx/kszqbl0uFEIj+uPcBz0+7Fy9uNrj2ak3k5j/SLuSDItA6vw8kkqz3TPW1D7YguwPplZzEYzHj7uXDv+HAEQaCsxETvvt05dqzC+eCnn36iZUv76lV14Ofnh4uLC+Xl5TU+ttNefpriklL+++USayCHKPDKK8/w9DMTb9qvSZMmgP0DTXVgNBqV2Ors7OzbJrvOzum33nqrWn1jY2MVCQJYifOwYcPspAipJ45QkHIMN62FAr2Oh178lMLCYn5d+TRdekWSnlXKD1tTyM8vJSg0j5SzuwmLuPupaZVhsxy7lQ3gzWDTg0+cOJGCyzks/PZnjHIZR87F8PTTkwlsGMCkSQ8hCAING7qSCWRGyZQfvMrQFqWYLoM52Hp+WUTrQ557V19cXCousXEnc7mcVYaXh4bhfVvw0ccP8fNPacr6d961BlqUlBj54vNDynJXVzWvvGq1j/P0dKNly8YEuTbGPaCAHw5/xrXcDLIzDDRuFoFGq8XPz48GDRpw6dIlLtOS+nUaQOFZ6wOodzj4tnKo4C789Rv61RtFWWnQ9VEZ69+gEV74BlRvkmNoaOgtry+dO3cmPj4efXkBnl7u6PUGLBZr5VkQBLRaDaMeqrne/UbYAmCmTZtGXl4eK1eurNZvqqSkhEuXKkZWZdkTmWTAgtFYIQlZtGgj48aNIywsjKeffpqUlBQ2btyoEH8bkpOTiYyMZMeOHajVageZTS1qcVuQAenv6+ssCEKILMu27O0HgVNOmh0FwgVBaAxkAGMB524BdwH/GLLrDI899phD7rqXlxd+fn507Oi8al9YWOigXZTNRoj7CS6ftBbm1a7I7R9EqN/a6TYqSyVmzpypzKRPT0+/qxMaEhIqbKfmzp2Ll5cX0/4fe+cdH0Wd///nzPb0bApJIEBCILTQixQpIiAggoBYAUXFcp71rHcc+tU7C4jlFFEQEJWiAhak9xZKaAktlDTSQ9ruJtk68/tj2EmWJALeeeVnXo9HHo/szmdmZ2envD7v8no988wvriNJEhaLBbM5jCenfoRODkEQBbSiEb0mkQpHNjZXEW63h8FD+vHh3BW4XB4MBpHeN7RFlhP4x7trSeoax5q1C/ly6ZdK7Vud63LWrFk8/dBcaqoVctd9QJQSSSyqZve6PEaPrJ/+rkvirqe+OSIigtzcXL7++utG055eLF36Jc8//xKVlZV07NiBb79dwUsvPUlxcSnNmoU3WON5JfR6PUajkby8PHJzc2nRojZKZbFY2Lt3L5cuXWLEiBE+EX9vNkAUxQYbe64FVxJdjUbDK6+8ck3rrlu3jkOHDqHRaLjnnnuIiYmpV7aQuukH2kYWENteRKPRYre7Sf7pSULbxmEIUCToEpqFwM8ZWK0eaiptNI8PxlJ+Frs1h43v7qEy24rYUk+bkc3p3vMWIqMSGtmja4e3Xr5Lly6/eht+fn5YrVa++eYbNny5HadcjYSHykoLb701hyFDBtGpU0cGd40jOthDYZ6V83YtCH5sywMG+oMgYLBL9DisZAMSO0ShEaDyQjXllU427M1FFODu0XEsX3CaDh1aYTTm+jiwAQQE6Hn55RupqXESEOj7G1it1Zw7WcyN/mO4KBzDUvATYWYDklHGVpBOdn4zuvUbRMeOHbl48SKnT58hdsQIMF99IrA9bxVffbCANZ9vwT9Iz/8tmkXrdtf++3jrcetClh3IFCPLLkTBTFRUFEFBQeTn5/P1ytn8+cUPSDmkaPB27JTAvM9eIyj41030vHC73VRVVREWFkZQUBAWi+Wa1920aRNpafU1gRvCsmXLmDRpEp06dSI+Pp5nn32WtLQ01q9fr1q3V1dXM2HCBJxOJ+vWrUMURXr2/O2zHU1owr8LgiAsB4ag1PbmArOAIYIgdEOh5VnAI5fHxgALZVkeLcuyWxCEJ4CNgAZYJMvyyd9qP3/XZLehtGdDZPDQoUNs3boVj8ejRt8iIiKYMWOGQlwPLIPCdJAuP7Q8Vji4HNkUiBDWusHP9pYvQG15QUlJyb+U7E6ePJkVK1aor6/lpr9w4UJlXworqaqy+0SAREFDiKElVe4S+vXrxZChA4loFsDizzaT2L4FQ4d3UcYLEnM/mMn8+fNxOBz1KnOS9x5Gkjx06RtJXqaFkDAjsiyzeVUmRpMBSZLVMhKvVFFdvP7669dcZjJt2jTeeecdMjIyWLFiBZMnT26QKD/44AwWLVqsvj569BgJCe1JSdl/3Q+nQYMGsWnTJj7//HMMBgOhoaGIokhhYaGqaDF//nwCAwPp1q2bT2rV65x2rfCS1CtxPQ1pp06d4tChQxgMBh599NEGTTFcTgctg/MwGpVbRlmpBK1aERVtApSo3KlTxRy8bJhQYXFizyjCGOTPqT2HuPBqKjoEmosm7BfdZCdnEr8khRVLV/HkCy/W+7xrwYEDBzh69CjFxcUYDAY1qihJEmc3H+L4qmPIkkzn8Ul0HNUPUdP4cZ0+fTpr1qwhJyeHqA4RSKm+jV07duxiz4796G+bwJw3B+DsGI6ufStOLtnLmjwJBIHE0w5i82qJ66UMK81jYvBLDGT7xnPIMvRpG0FIkB5dtpLlGDAglq1bMwGoqXYhSUoW4YVHNvDszP7o9Rr0BmWsxyPhsMoIO5MwaBwYwiuIjjapUUyABF0JFzMy1AnAleoUV8N9Tz3MfU89fF3reCdn+/bto6ioiPvuuw8AWS5Fkk/ijRJLci5gZsyYMSxfvpzk/Xv4acNnWCpteDweQs1Xb4C8Fnjvq1dabl8L3G43oaGhTJ48ud6yrVu3UlZWxkMPPcTFixdZvny5+jzwIikpiaSkJJ8Gt4yMDG6//XZmz57N2rVrMZlM/7bGzSb8/wmZ/yo1hrsbePvzRsbmA6PrvF4HNN4Q8C/E78JUojFoNBrCw31dvD7//HNmz57N8uXLWbFiBStWrGDdunU4HA7cbjeCIODn50dJSQl/+9vfePvttyjKSsftdpNWoWFnsQ67G/C44PT2Rj+7LqFxOBQdzO7df50yRGNITEz0cd/S6XzLCOx2O4sXL8ZisfDxxx/zwQcfUFCgZB4EjQvJ09DVJBASaObjj5WGn5Rj6+jSLY4TqZnqiCefG8dPa7/H4XAQEBCExeKb2ht440DCYqBL32aMuqstAUF6BEFAkiQkj8QNA2ujUImJiUybNo0JEyYwY0atVJS3IeZq0Gq1PPbYY4BCnF9//XV++OEHHzcwp9PpQ3TrYsyYcdf0OV5s3ryZTZs2qa8dDgeFhYXk5+cjSRJdunRh/PjxxMTEYLVa2b17t0/d+IEDB675s+x2ez2iGxMTc11E1+12q1bVEydObNT9rfD8GXQ6ZdaSfsxBakYQQVGmy25kMgcP5rJ61WlyL9ZOqI7kCtjLJUSrC6OgxSAqRNkoagmR9Gx59Rh3TG1Pacn1k5KCggI2bNhAUVERfn5+jBkzRl229uUvWfvSZjJ2FZG5p5gNM7ez+qlFv+gAFxISwtChSv1sQIB/g2NkJBLiQxFEkUybAKJIYV6tPF1sqW9vRcdubTBEGND5aykuUdQP+o6Io+iIjcBKpQmqbx2tX6NJi16rYcfX6RzaWsB9t65m38az2C8rFgjAe/cdpqbaTmrNLh5/dIQP0QXQakVyLxxStZq9kmz/DC5cuMD06Q/x4osv1zPBAeUanT59OkFBQVy4cIH58+djtVYiyadQpM+8x0UCykhoG0JoaCiFhYUUFxcTFBzwLyO6ALt371b///jjj6/b+c/tdhMVFVXvz5vpMJlMV9Wvvvvu2uf/smXL1MxabGwsq1atUicjTWhCE/49+F1HdgEee+wx1SACFC90QNUJvRKyLKPVai/Xl+mx2x0sOG9AxoB8OYS585KB5iYPutxcxnWubx/rcrlUglsXa9asYcCAAezcuVN1xLoSGo2G0aNH12t6awzh4eFERkZSXFyskl2bzabaAAO899579dYTNQKhEUbKS3y1ZnVaLXv2/EhCOyUqHhDgz8YtSuR19erVpKWlodPp8Hg8dO3alUcf/hNjx99EUJAiFL9ly3Yk2U3yoV306+9bKnL3HzoTFhqFyc+3XKChaPehQ4eu2ZkrNDSUCRMmqOnFY8eOkZ2dzeOPP45Wq2XFipWNrutVpLganE4nn376KWVlZeh0OsaOHUvHjh3RaDRsWbuXD5/+AsGuwTEwgFu/GEvXrl1xOp0cOHCAEydOYLfbsVgsbNq0CVmW6d+//1U/8+23axUGfq202JIlS7DZbLRt25a2bds2OGbHmh0sff4TwgkgICwMW6CZ137sCMi88fqueuM3rTvKzSO7cvRMIV98vJ0pt96Aq2s4+uOlas+iTtRgynBgMun561Nv8eGS2de13+fPKzJ4Q4cOZdCg2gatgpMXSN94Ebe9luC4aiSy9haSe+QMLXs1HlGLilIUCqJiIhDRIlE3aifgpwnhsUeUidj2LRlYNS7mrN/CLZPHY7U6OToiiH5HHDgvOQjuF45/rJ8aTb50qRqtVsQvyACJZsyxZUjl5WSn16b+i4uraNYsgOH3dSAqOISXZm3lLy/so/i59zl7bgGSWyav2MbWylWMmzKEW27uUe876HQiOo1brR0vKirCI6UDJYCAQAzQqsHsQXW1HYNB56NSMGDAIPbtq60ffuedObz33rs8/fSTPuvGxsbyxz/+kYULF1JUVMTcue9jDjMxcWJHmjWrW5YgIcuF3HzzzXz77bfs3buX22+/vdHf5FpRVVXF6tWrcTgcPi6Uly5dYvHihieyDeH06dOAUhIUGRmJyWTitttuU63dy8rKeO211656/w0PD6djx44+jmoWi4XHHnuMJUuWsHLlSqZMmdJkL9yEXwkBuTGdziY0iN91ZBdq9VFBiYr5+ytRncZuZjqdDovFogjTezxKRPIKQ9IoowcByLJIFBYW1ttG3eYl70MJlHTyggULOHv2LC6XC6PR6POn1WrJyclRCfm1wqvy4JVIe//99xsdW7dsISTUz2eZwaBj+Ji+KtG9EhMmTGDWrFm88sorzJw5k9tuuw3/QJGYmGh1TOvWyoM21KyQ37hWbQnQtcKkD0YURcoqikhLS2Pu3Ll8+umn9SJJdUnda6+9ds1amElJSbzwwgtq02F5eTl/+9vfKC0tVS1Mr3Y8fgnnz5+nrKwMURR5+umnSUpKwuFwMTBxEkse/JlgayRmTxQ520u5N/ZFyoor0ev1REZGEh0dzejRo1UnuM2bN/ucN/n5hdw/7Y9EhLfn1lsn8+qrr/HJJ5/4kJLrkRmrrq7m6NGj7N69WyUG586d47XXXvP5e/PNN3n373NJ+XgTPU3t8CeGI+d1XDxRwbr1Z/n733bX23bPyFDST+exfu0RANr0jWP6m//A3rqK05W+txsZZfIoCNduQ+yFVz7vyus0KzkdyV1fvcZll8jY27BGshdGoxGDwYDRz8gtXUegQYcGPSJagjQRrPlUaW71uCX6xLVgyn1zsYkOxoxS6lpLq510+3oInVYNYb/JgizV7kezZv643RLvvZfMF2tPUtDNxbufpvH15trfeeGCw9hsTnQmDd0nNWfd8SlsT53OkiXPkp1dQll2FRWFWsx+3Xl6xh/RahsirC5kbQRfffUVAN26hwAFgBtwIZONzBGfdbZtSaZX1/HENR9M65ghzHz5PVwuN2+++ZYP0fXimWeeU2tS60Kr1fLoo48yZswYQkKCKCutYc3q0w0caYH27dsjCALZ2dkNLL9+lJSUkJGRgSzLtGnTBn9/f1V1JiIigg4dOvzide6Ft1dDEAQMBgPZ2dlqtqvufbeoqIjExERatmzZ6LbuuOMO+vb1lQ19++23ue+++wgMDGTZsmXXPJluQhOa8M/hdx/ZBYVwNhYZy8jIUJvYkpKSmDBhAmVlZaxatcrHWUq6THeNosyMeDuFbgOfNRwcVjFx4kQ6d+6sRkTrIjg4mHvu8W1MtFqtzJ3buINRY/CqK3hR19HNq/84ZMgQRFHkrbfewuFwYDKZmPrQeOa+sQKPR8Lt9jB0ZC/e/ugPXCt2797NfVPuvrzvNgIC/ElIiOevf61tmgoNC2Tq/WMBVJOO1atXq9932bJltGrViri4uAYjvP/4xz+uK6p56dKleu8NH36zj0NcXVz5sGoM3ki9JEl8/PHHjBkzhqVLviWpTRvsR2sj1TrRgChreLjfKyw++qZaj3z8+HEfYr1ixQqefvppyssruHXMXVRarEydNpagoABkWaaoqOiaibgXkiSxYsUKzp07V2+ZYJfROgVEEYzRBpxuAYfdiVN2wo0GqjwyRSke7vOrpHN4DStPmNR1zRvcGKoEQCBHLubxmF6MCZLZW1KDEOnHkKE38OZX33GHOBqPLKIRwCl5cHfQodVqGDX+tuv6HlA7cbuyZtIYZESjE+oRXq1ewC/Ed/LWEPz8/CgvL+fpWY/w92YvsnbZZtq0j+OuJ6YiOyshaw1bN2dTGRTKxZxSyssFNm7OAEAUlZKOOycu5ERqLnc+1B+tSbnFPvhQT75ceozs7EocdjdeYbo2ccGUVTooL1MyKC7X5WtTAK1eIbN9+rbD5fLwlzG7AIFATQBl54sor3DSqaOWlCO5zH5vJxUVdgYNSODRZ5/l0vZkwsOD6N3bV09XgQ1JKkcUQzmScpJp976gugXW1NhZsmgVlRYbXy77sNHj9NRTz/LZZ580uKxXr14IgsDatWsJD7/ymIuIQjSCIBIUFERlZeW/VIVm+PDh/1Tfw5gxY9SSmJKSEubNm8fx48fp1KmTT5DiWu85t9xyC0lJSWovBMC7777LU089xeLFi1m0aBEzZswgLKxx/e4mNKEe5P+emt3/FTSR3avAexMeMWIE0dHRZGVlAbXR0pMnT5KWlobL6USSZUxaAVp0gciecPYbiouL63W1N6TBGhgYyOjRo9m2bRslJSW/SGRKS0vV/bgeTJw4kU8//NjnvYEDB6qNPZcuXVJJ2wsvKFGsyVOGk5dTQmhYICGh9T3rfwm7dikp7rNnz7Ns2Qo0GpE777yDdu2UdPnIkSPp06ePOn7cuHHo9Xqlji8oiNTUVLKzs8nOzmbXrl3o9Xqef/55Zs2apZJyUKKa1/rw8R7XLl26+KRPf/rpe8aM8SVdwcFB7Ny5tdFt5ZwvJud8MfGeXszZAAAgAElEQVQdotSmGI1GQ3V1Nd9++y0mfzD2MZF9RdmkRtCitZp8ZJo6derEuXPnCA4OxuVyUVFRwZIlS8jJuci48UotqSzLZGbmsuq7TWi1Ot57bybZOVnqNo4ePUplpYXIyIh6DTCSJPHee+9hs9mUUo4jqdzs1xP/Eg061WNERqMXSJrejIS7YxjUajF39WxDfjOZsHZ6mvXVcpII6rbLhq9xY5A1IMhENJfQG0CXY+asrYQR56r53mykW7dEkpLaohEFzlpkWu10UKlzMuGtIbz91828MbdR+/QGkZWVxcmTJ9FoND6ZEYD2I3uz9a360UgEgY6j+9R7u6CggP3799O5c2cCjQEU55ehNcJbT23G7ZQYfU8cdzymTNgEfTCulpO4VP4R78w6QGiomQemT6K83I5GI/DHJ2/g+LFcTqblU1Pj5vM3t/LI6yMRtAIancjdd3TGWliDZJQ5sOM03Vv7sWKfhapqNyaTlrvv6UJoaG3DnxdarQZnjYQ5OowLqSXYpGqat4+jRdfhzJj6LN//uFcde/b8JWTTAvz8DYwYkdjoMZQpAEKZO3sRdrtvSVVNjYNV32zAbrc3vPLl49YYnE6neu2HhwegJBBllKrjZoBC7Nq2bUtKSgqpqalX1b9tCNXV1aoCREMZtH8WXgmyc+fO8cMPP/hYE2dlZaHVaomJibkqUW/evDkzZ87kzTffVCdnH3zwAd27dyctLY1ly5Yxffp0NavYhCY04V+PJrJ7FXgJSd2mo19CcExrhH73YbicXt++vfEmNa+UlU6nw2q1snJlbe1oQzd/b61wcnIyyckNPNCvAq/tqxevvvoGr736BmVlxYSEhpKTk6MuW7lyJXfeeSd6vY64hOs3dQBFoP3MmTMY9CYERGRJw/Jl3xHXKpGNW1aTkNCm3jqjRo0CIDMzk9TUVJ9lTqeTZcuWMXXqVF544QWfWutrjQ7FxsaSnJxMamoqpaWl3H///Wi1WkaPHoXbbefll//MqVOnmTZtCnfcManBbdirnbw4ZQHH911Aq9fgcroZ8mAYog4eeeQRNBoN33//PRcvXkRyNbgJPLIHo9FIWFgYpaWlhIaGqnq4paWlzJs3T03xlpVVYrNVsX3bQfLylIe7Tq9HozH5bPOHH34gMzOL1NS0y2nSr1Tps2+++UZN/YuiSO8+PXEWCQT5Ogvjccrk7i6DHjpMQijrj9pwI6HfBf3vDsUYqLlceiAQsz0Hlyea4AiJW+6xozfKIIOogfXr9Cw+cJQiOYS2A3urtbquYJG8Ww0kdovk/b+n8Na86yO61dXVLF26FFmWGTduXL2JpCk4kDvmj2f1H39Qo7uCCOPmjiYgItRnOytXrlTP+dTUVGRZRmcSqCp3U21VSMmGlVl06rWGW+9RuvPXb9hL8vJqDGIggwb3RafTUVFRSVb2MdLSwjh/xqJ+1zcW7WDK04NwFjkRdCJ4ZEI6BKExaripfwwV+eVUVbsRRYH4NmZSjxeQnV2Bx+2hutqNVifSrVsUZrMfGq1IZKyJLoPM3DW6Ny27t6OkpMyH6AIMGdYZP38DbrdIfJtooGFzEwHlvnb2bKaqMVwXer2Orl26c+Bgw/eZ559/rsH3JUli/vz5WCwWAgIC6NVrLILgANwIhCIItfW7nTp1IiUlhezs7F9FdtesWaPWbtfu97UbqFwNdZuXvbbwXngdMCdPnqw2A/4SRFHk5Zdf9rlnHT16lAceeIAvv/ySTz75hB49ejB06NDrztg0oQlNuDqayO5VEB0dzcMPP9xgQ1lD8Hbpms1mZsyY0Wh0RKfTqZI9I0aM8BHE12q1DWqtmkwmHn300Uab1xqD2+0m72IuDzyoSAqNHn0LkZHKfspA9w5dySzMoUePHuTl5XHkyBHOnDmj1oH26tWLUaNGsWvXLk6cOIHL5VKJU+/evTlw4ICq6bp9+3b27t2L0WhU9Yhv6NeLhx96hJ079tGvXy8G33R1J6G4uDjVnW7//v1qh7XXTU0URWbNmqXu47WmQTt06MATTzzB8uXLycvLY+7cucyYMYOQkBCqqqoYOnQwkydPalRnGeD9P6/i2N7zOB1uHHYXiTf6Ieo8aKnt0p4+fTp/fmUmOr0GSfYgCrX1tW7JyZmaFBYvXkJERASlpaU+erxhYWG8/PLL/O1vfwMEliz+od55JCAgamrzWBaLBZPJRHx8HPHxcYAiI9fQg1Oj0SAg4GqhoaC5TOBJCKpTcmM06ygttqFFgwflM5zVsOPz8sufDePi3ej93LgEiVH3OjEFyNT9CUaMMvB6chYn91bywoBeXMy5iNngR2B0BDWiSO++dzHu9uufRHkj6EA9JRUvWvXpxB93t2Prj+vJKykiKDyEk+UXObte6f6vqKigsrISWZYJDg5m8ODBHDqYQkGhUpa09+vadLW92sN3C9IYdVdXRCGWkzvSKbbVoBF0JCYqJQKfzFvJ2NsGc/dd/+Cm3j1V8tg3MQJDhQ2jAUSzCW1MnUbVUDPa/CL0WnC6ZU6eqK9RC5C87yK9ejendcsQIloYefit9tTUuNi1cwMH92cx6c4eeNwSWzafwWqxE9sqAkmS+XbZbl577Qlkjje4XVBqTbv36EhWZl69Eh6X280LLz7H6tWtuHAhg/37D6rL4uPjGTSovv2tw+FgyZIllJeX07p1a6ZNm9bIZyvwNn1di315Q3A4HERFRam17gaD4Zrqcq8VLVu2ZODAgRiNRvR6PeHh4dhsNgwGA3a7nTVr1jSoTtEYRFFkwIAB7N1bO0Fp2bIl06dP57PPPmP37t3s3r2bRx999JobkJvw+0VTGcP1oYnsXgWCIPwqu1rgmm+8BoOBuLi4axobGRn5q/blD1MfIitLiRSmp5/FbK6NcmUV1aYkx44di7+/P2fOnMHpdFJZWUlKSgopKSk+2/NKTnmlsjwej0/UoqamRm1iCQ8Pp9+AnvQbcH16tX5+Sr1fly5d2Lt3L5Ik+ZCdX/uQDAsL44knnlBrpT/88EM1wuolKsePH+fBBx+st64kSaxffhCn47IhxthAIuP1uJ0S+74ppk3CWsrKKxl4Yy8iIsKpqCynWrKhF4xqG2OBM4tTVQf5wx+OM2fOW+rnJSbWpp29xiN6vY4WphjamOIwiAYu1GRwwZXFH564i/Pnaxuu3pv7ETISMTEx9O7dA4PBcFnHtyuyLFNeXo7NZuP48TR27ziBSR/JkyOGQ5KRqoRasqsxiHS6pwWGNnoETiE1YFUuAxcqNNzdycPmfBuvfX+IgxcK6NDCzDNjetAuJhStBh4ZkcTD87fg8Xgwh5lZs+Ybpk5VjumCBQvoF9+FEVOurxM/ODiYO++8kxUrVrBhwwYeeKC+o116ejo//vijWtdLcX0HSj8/PwYPHqyW0ezcUasqIfmWAV+O8hawddE62scYyTIZuWi343GC1gAvv6JI4nXunIgsuyi2OLm7f0vufnkUgiiAKIBbwnmiEH3nKCRJoviCixV/LkMYrmR3REDKd2C5qGPUE62JbO5PYZGV5ORcDh3M49DBPG4cpDSGarUiLlcGjz3RBre7NTKKY9hjDy3DaNLhdrnR63WIYigeqTmKOVEtBBIRRSUC+twLD7J+3S6qq+raYht58JHxpKWl0rZtAm3bJuByuTh16jTTpz/ARx8ptbxut5tFixZx6dIlJElSewEiIyOvauDi/Q282/m1MJlM13zv/DUYNmxYg++Xl5df8zbKy8vR6XQEBAQwcOBAH7Kbnp5OYmIizz//PLNnK4ok8+fPbyK8TWjCvxhNZPd3Ao3W96fWaDTce+9d6uu6TWwRERE8/vjjgGLVe/KkUqVpMBgwm83odDr0en29FKJ3jFc+zePxqNI9/wzCw8OZNm0aixcv5uDBg0RGRtKzZ0/OnDmjjjlx4sR128VOmDCBFi1asGXLFrVxLSYmhvz8fHJzc3G73Srp9P4veWRcl21Du4wKoFkbA3abh21f55JpO8WZPx3E6XThkTzcM20QoaGBHA/aRvVFO/6aIC658ilzKx3YOp2OkpISQKk5vLKREJTSjVtDb8HtcCvCUfoobnvgRp+I7dbvzxMbPJRcyy7y8/P54QeF3IUGhTKg5UhqcmU6tOrAvF1z2HVoOwGGeARBZMm2PdzfdhiSSaQ81k1ADphvCSKiZzClJdUk9vTn9BFbPborAHEhHsodNp7ZvQaH5MbpltiXns+Xu06z/pXbubFDcyKCautPAwMDycu7xLQpHVm58ix2p5tD51LR3HcKi6mKxAfH0fEG32bAc+fO0apVq3qp6cTEREwmEzk5OaxatYqJEycqx2HrVk6dOqUqdMSERCH8XIqEhEeUMUb60+nB/rTv3lHt1Pei0qJEcy0lvsRLZxAZMrY5h7dmMeT+blSVuziw6BJaBA6trqTn+CBMAVqCgw2UldUgCDqe/8MgBo3qgKCvc81pRHRtw6nKKMURbCRlbTquIQYkl0xRQRl6vZ3i8ktcPKDFeh5ufyaBXuOa0yYujJ07ssgvsrB7Vzbt2oXRrJk/AwcloNVqgFrt7A/nTebDDw/i56cl5fhzWEo3U5SuJ77vDQhCMQql9q0xDQwy8tiToygrtfHtij2EBAUxYdLNuKUyREGgT58+HDp0iLFjxzB2rNK41bf3zWg0IkNu6o3BoMfj9mC3O9EbdOh0WtYv36NqW1+J0vxKrKU2wvSgj1B+g4bKKP5/gNPpVJ0RQTGM8TbferFixQpMJlM9VYfvvvuOhx9++F9altGE/3+gKNk0lbtcD5rI7u8ES79bRmSUkirPyMgkLq4Vfn4KGTHo9GoUzGq1cv78eTU1OGnSJPLz8ykvL8fhcFBQUEB0dDRut9sn4u1Vpnj66acxGo3s27cPj8fD0KFDfeyRfy1atmzJuHHj+OGHH1i7di3nz5/njjvu4OeffwaUemSXy0WbNm3qEZlfQp8+fdToniRJLFq0SF129OhRDhw4oDoxxcfHM2XKFBK7xXLmaA7BzXTIssz2BWVkSWeQ8FB1OUL24KPD8fNXonYX8y4gIWHTmwiPMXND4kjM5jBat659wJlMptpIJL6KGR6HR40K60QdglBLDubNXkd5zTkk2UmEXws6dwpn68FD6AUjNxvvY/+SszhrXGh0GtpqbqQsoopCmw23LGH1ONiyM5VhI7tS0Vlm3sEdLB/1ILe1/5A/vXIbc78Zym0d1uF0+UqDiQjcn1TFIzuOUeVy4lXYcksyzYjikwX+fB+gQdREEG2IUiXSXn75Rb748hQPTevJwi8O49aAJb0Ga3MtP/6wgQs5WZTV2LHZbDgcDqxWxYykWbNmdO3ald69e6vn0iOPPML777/PiRMnGD16tBphBAgICOD2obey87Fv8djdiCg0z1NkJePNZHqv821U8yqhiKLI8Z+taLQCHreM0U+DOdJIm2Y19LipE4IgEGDWM+qFeJxvShwuLmPbp2WERxtZeXgEs9/ZB0CkICFLXtXtOtCKFKYXMu7xb5g8/gZEsx+BHg2bVh8lzVqAR3YToA0gvErH+tkyn/zfATKkEjR6geGT4gkMMfD5wiM8/XRfDEbdlVsn7UQxgiDQuXMzNFoR/1CRFl3cXDiwm+hOOkwBMnAOyQ22slAuWQJYvnw5kiQREKjn0SdGce5YPjXOYowmPVkZxbgKt6OP9rXvHT6yH1qtUrtdUFDCF0sUk5aIiFAeengS4W0C6N1yFIdy1qvrlBdZefP+5ZxLyUGQJDQiDEv0wHA/9LKILFv4y4Sn+GpzMhXuGiJ0AdzarQvv715e73t6YbFY/qvJYF0dbOByWVJ91NTUkJ6uZGn69+9PQkICS5cuZceOHep9+H8ZR44cYcGCzyktLeP228cxadLEegZHTWjCb40msvs7QUSzZgy/oT+b9+8jMzOLhQuXAApxsVjL8A9QHmg7duxg586dPutOnTqVzz77TC1LeOCBB+rdrJKTk9UmvtTUVLXGNCDgn/O5r4tu3bpRWlrKnj17OHPmDHPmzGHmzJlq+cSPP/4IKCYSVVVViKJI+/btGTdOcUG7Uos2MTGRu+6qjW6LouhDMq90acvIyGDp0qW8OPdOHr/1Q5XMeHR2ZEdtAVVwsB9+/gYkj4RHknjqqT9gMvk2k9XFLbfcUk/irK7xhy5RxpWufJpdchF4+bJNP5VNSdVxQozxhJraAiKZ5yS6txmEvtSPAF0wzprLltQuDx4XdBOGUaKvwS27OOdJ4/TJXPr0a0dAoJEaTxV/ue17Bnfow6B7W6Mzavhi9zCenbCXgnylTtzPIJAUmcrtG/I5WFSAXjDSLWwQNQSglfUYpGAu2gQuVlUjy3pGht/FwW2H6HNTb/W7LfzisPp/2mgtsqh8tyOnayP1oOje6nQ6ioqK2LRpE5s3b2bMmDH07NlTrQcHeOeddwAlKv/AAw+g1WrZ99Y6pCtIOpKMo7KGwqM5BCaGI0kSQUFBqgvdxIkTmXqXgdWLNlGQU0HvIZGMuqsV54/5aqEOvL85rXoEcWB5PmV5NrSBVbzw/KdERCQBcKHYTmIjwcr8/ApKyquxZJcRHuqPTSMxZcRQ1m4sp3f7GBxlHlw1EsjQMbgZce4w9gnnCQypla8rK6uheYv6JM/fX3nPaKq9NvV+GmK7gs4oq9kAGZmAsHKWfL0FSZIYNGgQ1dXVpBxKoWUHRSmhymLn1ZeGE948gAvZpVRmu/n2nSzkaDvmdhqcdjerVm8kK6u2RKSkpBynw0XLVtGYbjWRmZlJXFwcsiwzc8Iics4UI8sg6gRcLjgepCcKaBUnY7Mk8+IXdzKlYAS3j3ud4FKR9oSxeMgzdHt2PN1vG+zzXQ8fPtygqs1/E37Jua1z586cOHGC0NBQhg8fztq1awkKCmLYsGGIokhISMivLtP6b8Knny7g2Wefw253IEkS69atZ968+WzbtrmJ8P4zkEGWmiK714Mmsvs7wqbknWxeu477pz1IVU0NI4YM5pt1PzQ41it2LssyCxcu9CGBv5R2nD17ts9NXqPRXFU43WQyNRiNzcrKwmQy+dSuDRs2jFatWvH1119TU1NDfn6+WnrgRd16umPHjtXrpPYiPT1dJcABAQE899xzjB07lgULFviMu/HGG7nhhht4//33ycxUute/3vcyCxZ9giR7uHliD5b9cI6qKiUyq9UpkUxRIyJqRHQ6LRaLBZutiurqakpLy8jKyuaGG/rSqlXsVaNTuvbgKVKOecjA2ka3Stsl4lp0IcQYj71axmn3ABps5cE014QjN+DVIMigQ4tG0NJZ25sCTxblZVaCgv0YHz0M0aLDJtVQmlNDZIIfc17aQHKuQk5lZCKdBj49cxZJVpSlO4WNoUxygyxhloOQEfAAXD5HzlbZSbzQgrcOvkNm1td8Ot+3YUoWBQJKJPzKZCriNYy75456smkWi4Xk5GT279/P9u3b6dlTqf1+5plnfNz/Hn74YfX/qiILsqeB81SAQ6mHObr2BKCcn95z2+te12FwB564OR5RLAQkAkON9TYT2yWQ2KR2UFVF2t4TPDH+Z155pRMgcqzATvciG81bh/qsI7slFq5IwShqGDK8Lc6vLZy+WUtxgkifkhbYc10K0b0Mt0PG30+HX5kRySMjagTKi+yEhTWsF+wls94yGwBHjQe9UUQQBJxON3q9ouhSU+Oi0lKF2WxWbZLfeH4hpnAtodooJk7qRGTrQPQGDQankQ8eScFRI8EJyNos4ZZdCI5QwLceetOmvQwf0Z+IyBC+/PJL/vSnP5F/toyCzEvIMnR7RIfW6PuQ7twjGr8A5Rpo06YZf+98O+XnNWBV0rVH/7qVtE/XM/XntygvL8fpdKoZnf9WwnTuXAaHDp2gd2+ltGr58nVkZuRiMhl56aUnOXHiBKIoMnXqVEJCQuopOlRXV6s1zf+rqKys5JlnnlU1nAMDA7FarRw9eowVK1YyZcp9/+E9bMLvCU1k93eG4beOJq+0cY1Mb5p4/vz5jY6p69zlhbcO8MpoxvLljachvRAEgeeffx6TyURJSQm7d+8mNzfXh7S2atWK+++/H6iVbAP4/PPPVY1dt9vdaKrQC7PZ7NM854XNZmvUheymm24C4Nlnn2XOnDlkZWWxecfP6AwanE4PM+fez7frV8FlkYyefRLqbSMoKEgl9AkJbejbtzbS2dADu+4x1oSC/3jvq1qi0KdPT7wyxVVWJ2sWK6lQGZFCuYLW1Ff0UJbXbitG0xp9iR3iICQmEHeVgDtPZt7k4whJlXy37TDuy6xZqxVp3TuaHtq2rN93nCg5EKvkQQb0GFQl1bqQAIcUyMS+t+KySWg1Im6PxOAhrdi5Q2mYDMmTMOfKJOoN9Yiu99iNHDmSlJQU7Ha7Wj8dFBTEAw88wOLFi+uJ8scObEte8gXcNb7ab5JL4njuKQRBIDIyksrKSpXsVlZWIggCBw4c4PDhw/Tr15YbB0Wi5Rcc3srLiYoKweORACugRJy/WXiIp2Yq5423mXPTp7vZdCifWIMRfTRUBoMggawT0CVWcKrqBMZoPc1K2iFZlUyAs1qiT0JL9m3OYeAtLQmJNCAI4KpxIvjpfepvjQbl2j1xooibhyuyfi67QnaPHy/gpx9rJTc0GuWXqkuci4oq0eQFUSV4GLkyDr1BOQeXv5OB0+57XWsFHXGGbmS5TiMLtcvS0s6RlnaOvr26MWxkH/7xj38QoAkipr+Ax6NBc/nStVdIGENEWjQPIiCgdrJ3/KszFAtV+A0RqSkCTgcgyiLuPD3ff/I1x4t9+wR+y+a0fwZpqac4sD9NJbsTJw5nzuzF1NTYqagsxmTS06dPHx8r+bNnL7B79z4sllKcTuf/PNnds2cvOp2epKTOjB59i/r+qlXf8+23q5rI7j+J/09L3X8zNJHdJvigT58+hIeH+5BWp9OJRqNBo9EQHBzcINnt0aMH1dXVHD58mC5duhAaGorT6SQ0NLTe2LrIzMwkJSUFp9OJIAh88sknauTYz89PrWPNzs5mzpw53HnnnT51tXWh1WrrmUvUJbANGU+sX7+egwcP+rzXpUsXmjdvzsaNG32iykajkXvvvZelS5eSmZmpvq/X61n0xZvcd9dzuN2KbqokyWxcl4ylKh+dTkeXLkm8/PKLDe5zfHx8vfdNJhPTp09nz/a9nN2QhatUsaaWRQlTX5EL5ws5cHgHzQJ60qaDmWYtfAXp3bIHt+xGK9Re4rIs45Zln4YzN04CLEqpib49uM8psmauGg/p20sJDtIzonNL+utFbrqvF7oBrRH99MxxT2BG39WkVSipZKF+haoKh+RmY/J+1ndO4cmXpgKQkGDm4J5catweLJEiEZdk8v1+OS0dHx/P2bNn2blzp9olHxISgiiKlJeX+zQUJozpwomv9mPNK8fjcOP2A1dzDR37dian+jgGg4FHH30UUM7Bbdu2MXbsWMxmM+vXr+fYsWPs3n2a3bvOEBsTwr3tzGjrnPeSJJF7vhhzjZUIfx29eyfy47eHGHTTQILNBjZ+l0/Vz+uJDzIR3VpDSHcthw8XEycmUmk8RHJyKZob/NTfZfFPyZSVWi8fyyzuG9wF7ck4tAYBc2sDWesqSexSRUSMP3Pn7lfGiQJJSZG0TwynotJOdZWLoCADFouDQ4fy6N0rBm8Pi3diERxsoLLSgSTJBAcbuGlYDLLsQRA0JLSMpizTX5HJq3OSZJ20NvJglTEKJmrwlUIU0WDLcdO+fXvOnDmDHTvhSbXHrvy8h+oSmeb9RLp0a6Yeg8KsEozmMu5+qQ16nTKRLK+0s+6vZRiqdBRsTYUkP2666SZ0Oh0mk+mfckv7LREf3xq3u3aSpNfreOXPM8jPV4hudHQ0I0eOBJRz6ck/vkiN3UrLloqCz6VLFYSEmP8j+/6vgr+/PwEBAT5EF2DixPGUlV27mkUTmvCvQBPZbYIP9Ho97du3v+71dDodQ4cOVVOi14q6NrsfffQRsiyr6gveet/q6mpmz55NVVWVSnSHDh3KwIEDr7r9qzmrjRo1ilGjRvmQ4q5du6rE6kp95bi4OGbMmMGXX36pRofdbjeDhvQhJfV7Vn+7kfMZJ6ioqCT1ZDKSJDF+/Dg++eTj665fjo2N5e6pdyHdJ5NzLBe71UHrHrEYAw3YaxwkmLtjMxQQEe1fj+y6pBqKpGJaGlvgcDkRZQ2SDFaXr9qALNTgyDHi79AgmkEMlpEqBUyTZHoYW9Ljsh7rWaDNxnO0+ukMIX8bSUZqBuFaEQEBGRkXjgYJrwYocWXjlN246pTC+Ou0eKweMIE9REDTQeKej976xeMxbtw4Zs+ezZ49ezh+/DhTpkyhoqJCnZht27ZNbejRGnWM+/ohTq04RMamk5xILEISJfZUK2UUdc+duLg4H5m5sWPH0jq2A+/NnkdsQhAXC8qZMzuZpM4R5OdZqai043DWTgb9jSJfzH+OocNm4xegQ/bAZGMrkMFeKZB+FGqOSoz6Sz+iBxSSX3I56lpcg+VSESs3ncDjAUGojdJ+tTOV+2NbIAoGjhfn4eevpTi3irh2IXjcEmHh/hQW2kg9XkTq8fplQqdPFdO7RxSrFhym682tsVgctGgRxP0PdMdmc+Lnp70cFdYADsCPJT/OYVzSqwBsWpXD+Gnx6I0aWrT1pzS/vs64Xqfj6Km3CQwy8P2aQ8yctYyqcg8JEQkcyd0AKGYmp0+fRpQFMja6cFRJWHPhlr+YuWS1IdZRFbmQcoq+7SMxXI5QG/RajAYtHe6v4MJHIF1m3K1btyY2NvYXz5XfGt5zrjGd3W7dO9O5c3vmzF7Cn56/X30/JiYSvV6vZqlcLhcfvP8PIiIDgAAuXixk9erNVFfZ2bvnOEeObvuNv8n149uVP3I0ZQtTH+xPQICRTetPsnNrJl+sqLVElmWZyMgIJk1SUlI//riWI0eOodGIzJz5ynUr5zH5CCUAACAASURBVDShPprUGK4PTWS3Cf8VWL16tWqWERERUc+xrlOnTqoEGijWxt9//73PGGtBJd9+9DXmqEjG/eEOBPHa8zxJSUlUVVWRkZHh835paWk9uSBAbcALCQnxaWSLjDZS44xAr9eTnn6SkJAQAgOvz2b5SoiiQOsevg/3i2lFDDWPZ3/lLmRZQqMVGTCidkyNu5RmzUJon9iMYwdOE4Q/To9IiKyh8LCEvfSyu5hkQCOIOI+AsR/43w40oK0LsD42nBC7i3vnJWMVbIT5lSKgRUZGEiSqZAv+KKUaAoq8rFaoYb9V0WIODPJHkmREUeDtuWsIqQ4CUxCSRiZp/ISrGoP4+fnRs2dPMjMzKSsrY968eeqy4OBg2rZt6zNe52eg6/SBdJ0+kLT/+z/1a0VHR9O/f/8GP8MjOQCJN15ezJGDOWi1Irc/kAgmLUcvN6rptALhQVpC/UUuFjuoskssX53OqpWPserHPPSheoqHCQQfBUcxVHhA7CGz7nSmIgtxGUuWHiAkqBq3W27Q/MPW6gKPPj2OL7+r4s6Hb2LEqFbosi+SJ+m5cMnGvfd25tixIoqKbASHmAgK1HP+fBmnT1+irMzOwQM5HLiQzsUaB6IoMPY2Rce5btkAl4tQAGJioxk3JZGfv8pg4Zun6HljJDGt/bnjudak7StFctXuo1t20XmQnpbxSubmvmkDGX5zTx4ZuYuX3r9XHTd58mTeeON1jEYNU59ty0+f5hAXr8XmsiMI0KWrEtkVBIGubcwq0VV/Q52G/v1asHNuGhWSSAj/HZa63uaxTZs2qbbCLVu29DGj+WntV/zh8ReZM3sxf3q+Vg/6qaeeUuv0//73v/tsNzY2iuHD+7N58z4yMrK5cCGLNm1a/8bf5tox/6PPCQ4u46W/jsbfX6llv3tKX7r0aMXMl2cxdPhgkpOTVe3kyMhINmzYxLlzFwgMDFSzgp061S9XakITfks0kd0m/EcRFRVFRESESnT1en2jDW1ms5nKykqMRiN5eb5C+SUlJZw7d4F1Z3bTVkqgzclE7DY34c3M6A3XfppHRUWpzlxxcXGUl5fX+yxQShqUkgWx3nKtVktCQsJvGn1y2t34mwIYKA3HXVRFVaWL8CiT4qwG2CWZ1q2j8OAgOMqI7HbjLxgxhgg4KmUKLpNdjWCiIrCS0H71U6aiJPHwCeW7fdpF+S4VRh2utELu3nmCapeH9voOFHtcuGQ3DqEGEZl2AUHEmGtYlZFJVFuZ2MoowsNDGTFyAKIoYNRr6NixJbt3lxAG6Ksg9d11tBjRBVFbv0SmLm699VYAUlJS2LJlCw6Hg6lTp161dtNbGvPEE0/Uq+8F8EglwEl17DN/7sjLTxaQm21h43cXSOgchtsh0aVLJC+99TAC4SCLcHghc7cUYnXoGXn7HKa3vAXNmGa4QwRKh4LkltFoFDInuUF7RoPUUYlwP/ynISz9+KdG7WFdHifZWed5dc4wDOmn0KzfiijLHHIEMO7uQQiCQESEkUWf7SI7q5Tqaid9bogjMNiM1ergxx/O0ry5ooZw/HgqJtMNV/7CQBRCnVKXe54YQGBpGWGFJtx5eRhbtqRzz0C+Se3JwndSWb/IhRsnGfbD7FyXwnMlvYiICEGn12COMNDv5kgKskvrHHcXkiRhNBq4cUIUA8c1Axk+/uQgDofbZ4IjNnIcBEFgfu4mBrW9lRB8XfT+U4iOjkaj0aDT6cjLy8Nms5GVlYVeF0hsbBSh5mBCQoL5etl8nE4nTqeLd99VrLHrWlxPmjSJ7777DlDOu+Tk4/Tv343ExNYcOJBG1X+JIkN1dTX7du3l+JYz/OXjG/H3N2K3u8nKLKeg0Ma+vTlojaLqdAnQr18/Bg0axAsvvMD27TuorKwkMbEda9asadT9sAnXjiY1hutDE9ltwn8U0dHRqoHFr8WY9jcTO6QtoijQf0BftW7z6+UraSeO45vDf8Uccf3R1QEDBjBgwIB/at9+KyT0ilUjldocf0pzlP9dkpPDNVt57I17efLJPwJw8sQ5Jo3+Iwm27vR6yldZILSdQNyo+kS37JyNZ6stasfZI6kXVcK7yKnF5QrAI1WRZj9Np6BIugfHEmTQcHN7B2dtOby2p4iOveMYMKg2giNJEqn7zqBz6nF69AiCUrPa7KwHyeWhOr+cgJbX9hDs1asXvXr1QpKka7aKBvjoo48ARcnB2zDokZx4iS4o5KpH32hWrJvEzb2WYil3cmS30tSZcdrCrLcvOyMKIHebyoCilWw8nM3wEf3pZGmGtAGKu8p42giIWgG3DaynofIoCJKHVnWCWndMH86Cjzf5lDAAyILAgNHdeWHmET6Pj6Jf+0iEbCWC2HNg7QZKim1s3ngKq1UpMzh9qpCHHh+ByaTH4G/Az+Gh+wUrzlNVPDDtY959735iYkIRRQ3QHFHwnSQkz1lPRLbIyE+iCenQCi5H4rRhoTz65o1k13zO+wt2Xj5OBtas3sOMR5QJiF+Ajk49zbROVBojZdmDJB8BwOWSEAQBQaucUMHBRiorHdjtboxG5XpNzSijd/sI9Lrax5LbI7HzYBZljhoSuyrNf1c2l/4noNfr+ctf/gIo5/Wrs96krLSYcaMfwel0ccedo5jz/ktotVr0ej16vZ7ExETS09OpqKhQrZI7derEjz9s5t1352G1VhEdHUH//t3QaDT079+Nrds206Xrvy/l7/F4EEVRnYBVV1ezefNmVdEmqnsACxcerbeev7+OIUNa0rrFTZgjo+pdkyNGDAcU7XJo3Oq7CU34rdBEdpvwP48D2SfoE30j0dFRtGtXm8o2hwdRkJnJT18lM+2Z/31x9row+Om4f85tfP7M9zgdTkQ0uGQn5VIRnW5uxeOP1zpYderclmPnfuTZWz4CrGj0AroA6Pqgr+RZ+g8WQlpriexiwtw2gA2ZGsZUXkJ7BZd094zmwZ7RFOZYObnzNP6BDpZnHsUjScy73Cwfag5Qia7VWkVxcSm71qXgdLgYNWQgn326lsGDh2E2mylvIRJ80oM++Pq7z6+V6M6aNcunLtsrWdavXz+G3RxVb7xGI2Ly03LLbQl8v1LR/zUa9dw5dbjPOEFnos/oqaw/9H906BCPQ2tASnZQeRD848FTDblf1RkvwrCElmw9r8xOTCYjwX4ildUSgiAqEWgB7rirK1Me6UOC2Y/XZm5jw76HwaBHdjiJiAxWyUjHzjG4Pb5KCWWlVmKam6n+7jh3xihGMpNi4nhs5x6SOv+JEyd2EBsbWy+i/MS4R+hf0owbu+cR0mGwSnQvH2gAXv/rRD5eshe324Ms6/j88y0q2XXYPYhaAz1vbAeATDFgJyBAaZorKLASHa1MOsPD/cjJqeRiTgVt2ynEp+3AruSdTMff34jRoMdW7aTG7uJPc7YQGOiv7m9xcTGdOnVq9Lf+d+PjD7/i/LkcYpqHYrUqGapV324kLDyUma/+QR3njUh7SxhsNhsXLlzAz1/gscfv5Gx6Ni1bRSPLMt9+s4knn5pOYWEeOTk59RzW/pVwuVykp6eTlpbG+fPn0Wq16rH29iwkJSWx/r29jH6gGRetMuUVdsLD/ejWPYquXaMwmXTKOXE+BTGqccdMr8JOXRWKJlw/ZLlJjeF60UR2m/A/D7u7fvMMQOmlUgyeCC6eL/4379G/Bzfc3plWSVHs/Pow6SfOY4yVuWXqZLp261pvrMGg5+3vH2PO3HeI6qEhqodvucDBbacgsw2WLKgu8hA3QkthnIn0k360c9aQZ3dz8VwFsW1rH1JRLQOJmqJonwVssVJwvgxdmypk0cOQYUnquJrqYnb8dIriqksIaDmRl0Ju7iXCzUo5gSzJhPaO/1Vk93owa9Ys7Ha7j7NVcnIyFy+GcP8D9Y+Zf4CeuIQQAoP8cDpdDLypK8/8+W51udvt5quvviIvLw9RFBBFLZdwQj+BgH7KGEuq7za1epHk/Wf5+6dLeeXPMwCY/XA/jjkl1m08TWCggWdfGMmYW5X96X9HEtO+TQFAvmUoJB8mP6+MuPhmCIKAv7+eWa/fymsz11JTrZApa3kVQoswBrZvBRalZEIvitzWPI5+Q5IaJU4am4X2UXroFt1w2bYoog0KICtnHvfc/QG7dp4iLTWP0lILZnMgeoPIbVNbIMlHOHvaip9/ObYqtxp1Li+ruUx2RaKiWwMF5OZa/x975x0eVZX+8c+9d3omk94TIIXQCWAACR0EK4pgo4iKrL1hWdvuz7XXVSxYsCCsa0EFQQURBKRJCyAQOoQUEtL79Lnn98eECSFBxQVFvZ/nyZPMnXPOPedOkvnOe9/zfklrH4EQYAuzcvNra8no2avZaS+9YlSzx6mpqa3O//fijdf+S7eeic2OORxOvlywGMVQE8hfPZpKc9Qs5lh0Oh2du6Q2tpNZuGgOcXHRTJs2jTVr1pwWsVtZWcmqVavYuXMnbreb4OBgevXqFXAuNJvNWCwWOnbsSFJSEovfXsKQKB0/BOvZWO1k6NBkOnRsitDqdApqigWfvQ7FcuI7aZIkndTdGA2NU4EmdjX+8KSGxjNnzlxSU9tx+LC/yL3T6aLwcBH9os6lS2a733eCp5G4tEiueuRc4NyfbWsNMXPNtZM4sCefdf9dj4i1o1olZj77DoWOCvqGTMGGhfKdkDRIQWeSWJMUyf7lDexoqGD1xgJ8i/y30ife0a3Z2F3OCabLOS3f4A7tK2DRV7sRunoUSU+ULpLN2/LQ6yKpq6giLCKM2non5mtbis3TgclkClTomD59OuXl5c1yVo9n7LgsOncbRkr7BNq0aypDV1tb28zQ4kToQpo/lmR48eN5zY4dEUE88vBg/vXMZS0HUCQuvXcgwu5CshgRvXvx/t8/5NGXJwWaXHd9Fukdovn3s0vY/UMJiYft0FVwqJ2V9tuaSsMNHtyf/tP+fsK5VjlUYhMaEPk+/+7CVhAuN+HhNj77/B46tL+DmhovGzfu4bzzjtaNFqhqLWntBcuXV/LDD4VIEpx3bho229F60hJhoVH+c1ZZOPSNlyU7llPr0uOq9f8OrV6VTU1tU76qXqfnwYfuJCIi7HevxHA81dV1rR4fMLgjHo8Hm82GTuc3ljkqfMFfPzouLo4BAwZQVlYWcIB86KH7A9Hfvn37smLFCrKzswNmKr8EIQROp5Pa2trAl8PhoEePHqiqyvbt21mzZg0Oh4OuXbvSq1cv2rZt+5MiNNgq0Nks+NbvB33rYlaoAtFQCycQu0drTmv8r0haNYaTRBO7Gn94HnjkQSbdeRM7d+6iKSQlE2vsSlR0FOdd0funuv+lSE5OJjk5meHnDuLz1z8ip3wfF8UM5K28eeyzf0eqZSiKJFO820xSDwvBoSr3751Bgi4LSWmyPP7gle2kdQmjy1lRzaxsj6dd+yRGD7Bw8HAuq3O2UuwpRpYNWHQy8Qb/P+t8q5PUzr+9OcCoUaOYOXMmNlvMCdtExmQyJK6lw92xQtdqtRIaGorks/LkAx/xyHPDuHxCJ55/di3Bnfxpz3Ub/GsNG1xJ5Qd1zYq0lRtMqAXlyB0TkI4XmYqMaWBHhE9FCEHDoVo6hA7j//7+Cfc8PIqQEAuqKrDXuyldG0lqUCxXW1UWeVSqrU3/3hWTkV43Xn7CzXAAs9d+QuEtN7FlSzEjK6rQhYc2T2Xw+agsqSIixIYkwaVj+jBr1tfExDSvpS3LEp98vIN9+yrR62WuntSD+PjgRoc/AD0ul/+a7ty5mx0+eObp95FQ6NnFX81gz548SkrKAbBYzEz520QuuuiCE8799ySjR8tSjUOGdyUkNIiIiAhuu+22n+xfU1PD7NmzABg9ejj6Y3KWs7KyKCws5KuvvsLpdP7sHoKcnBx2797N/v37AxVjjuX7778PCO527dpx7rnnEhvbMo2nNZ6Y/SCb1n4JXhX0IFqxQ5a8Ajn8xH9PGhq/F5rY1fjDM+42vxPPM48+w77qIiSMJJozuPa6a7jxHxdhDjqxGPurIkkSUV0TYMU+qnpFckn3cbjVSlS1EJs+mrgO/pBkrSpx1cQrKSqswGaIw9f4YSI2wUpoZEsb3daI6x3BntJ9yDIYZQWdLHH9oC688XkOt93djsSkSEzmn7ZMPhUcOHCAPXv2BB7v27cPgPj4eKA7sBU4GnlTgAwU+afnFRoayp133gnAdddNoc5VyKN/X8a0p37gorHt0VkVgjtB8llWrpo4lm9XZDPO5yW84giDD+7l+xR/fqvni2yM98SAsclNT4imkmQOl5eGeje7Dzp4790tWILD8d3TH114KB9Me49VywpJ72EjPlFPyCWDCV+9jKIwhbIQPdFOCLt4IJYuLc1Ljuc/ZdWEO7wMHjqdp56/jL0Fdq67JgOdDDV5RUSktwX8JglhYSaSkyPo0aN5WkFFhZ19+yoJCtJz8y19AhvQhFfQUKknOKIHXbqYKCoqChjKXH7leXw6ZzF13pKjiwcEAweezSP/+jsDBx5fSeLM4R//vJHpbzTVmJUkidh4/weAo8YlJ0IIH5s3L8Lj8WIwKHTtJlDFOmR6IUkm9Ho9V111FfPmzWPp0qXY7Xa6detGTExMsw8uCxcuZNeuXdTX12OxWEhJSSEpKSng3Giz2aiurmbr1q2EhYWRkpJCQkLrDovH4nK5+PjjT5g3bz7R0ZFccm5XqhLDoEIFr4rwqUiKPxrsdbgRBSb0XVqXFUII9u/fj81ma/a7raHxW6CJXY0/BeNumxgQvRq/jNjYWCRJoW16CIgQIAG9QcZs8Qsul8sfiYuKiiIkJASTYsSjNtbnPcFtbgCvx4dO3zwneMiFZzMktCem4BrOzorncMERbu/bN/D8O++8wx133HGKV9icNWvWcOjQIUwmEz6fL2AI0L17dxTZCvy8ScnxdOvmT+eor6/nP7M/wKf6qHMXUOuM5/XpO/HpKrj5tkmUS7Avv5hx48cwbvwYXJ9+xHM5TcJb5Jfjemkh+tG9kdtEsG5rCd99l9vqOdsPMLBrRQNvP/U1D782gYn3TGbiPc3bDGkfzYdfzGV9RiR3TLwOY7u4n1yHqqp89OFcvi6q42y5ntRu6azaVAbAzJmbuebaHoSktQ20d7s95Bcc5uuFT7UQLfPm7gTg3PPSAkK3bGMle94/yI41+eyuewt7RwPvLnqHwYMH8+CDD9O+fVtuvuUqVq3K9g/SOGRW/8wzWugCdOxSwcjzOnPgQCVp7aPo2CmWmNhQdIouUBnmRAiRz9n9olmzZi9utw+324XBoEMVO1Ekf+6yoiiMGTMGk8nE2rVrWbt2LVarFUVRqKlp7jqYnJzM+PHjWz2vzWY7qdxfp9PJwIFD2LVrNw0NDciyzH//a+Lpp/8F1LJ6/kZqC+Jo260dBrvAIiezdc0Rdj70EjqjQs9xPeh28QDkRjG8detWioqKuPTSSzWhewpQtdJjJ8UpEbuSJL0HXASUCiG6Nh4LBz4B2gGHgCuEEJpHoIbGGUKHDh247pq/cX7WVFzOJicoRZHo1DWGWfMew1hbybU3TWbBis0YPDAz82q21viI7ASrd+ooKlM4asomSwIPbm7+vzjOPieN6S+sJir5mFuk/Y04iWZFvRfCmpceqqqq4ptvvuG885pbi55KhBAkJSVx3XXXkZ+fz8yZMwH48ccff3GJOa/Xy5NPPhl43KePf4NeRUUFBp2RcKkj4foUfMJDiXsH1Y4SPnh/JlNuupmlS5fSo0cPTCYTun79UXfuBSDG7b/dLA6VY5+2iAMhNr6zRp9wDoldzexY2sDqxTtO2KZ9RjeSsjdSUFBAnVXP8fc2vF4vCxcuYvv2HaSnt2fRwpXMm7cIu91Ox0mjSE+Kw2F3IYCSMpj28kYuu6wzKanhuN1eystrmTWrpf31/n0VHDnSQLBVT5dQL5SWkvu9gx2vHkB1qcQbbUTpg3Ae8TB5xBRe++w13nvrEy657FySkxO5+OLmDozjR7Vu/nGmsGfzOlIzzISGWggPd7Fm49+pqLDzxusbCQn7+bsVgiMYDDIZPWLZnF3M9yvyGDEyFahDCA9ffrmI3NxcLrnkEjp06EB2djayLJOUlERlZSWhoaFERkaSnZ3NmDFjAh++TgWzZv2HnTt3BSzbVVXFbrfzzTff0bdvbwZf+beA26bX7WHWldOpPFiP1+VPbyjft5K8H3K5+LlrUFWVZcuWkZSUdErnqKHxSzlVkd33gdeA2cccewD4TgjxjCRJDzQ+bvnfUUND43cjqW0MT7x0I/+Y+hY6nYKE/03trocmYwsJh5Bwnn9tFnG33syXO7Zzy945/KP7ALrWtKFjL5XFhYLs3aAKiYwBkdz8aHeqqxtY+t9sPKujEbGgt4D3F+xJWb9+PfX19YwaNeq07NY+0cYYvV7/i40KjnW8kiQpYAEdHhpJR/PF6LCiNG54C9JFEuyOJaNzPQ0V9VjCg5gzZw6TJk3ik5WrA+NMrCkDoxGED8uN5/Dl53sDOb333tc/EB11uTy88tIGXB4vOqOENcTYYt6KogSuXefOnSkoKODHH39k+PDhgTaVlZVkZQ2kqKiIhgY7ZrMZu92JTgnl/AsGk5QUh9PpoCD/IN8t3s+gYRl06dqWDz/cTqdO8Vw6pjtt2yj+VINjInT2Bheff74TBGz5oooXdrqYMD6Sna+Vorqarr1e9v+eWQ+4WfT6Gh69vA/3/fdrhgztS1ZWj6OvFm3CTKSfwRWqvF4vdfVFeDw2VLVpfTk7/NVfklNDAq/Psa9Lc/z9hg1LYcvmYtavLyQ0zETv3okcOLA/UJd21qxZgf5TpkwhLq55pP6o2cqp5LPPPg8IXQCbHIMHJ75G2++H736KOV/ORFEU9izZSFVek9AF8DhU9iwuoPzGfFwmhfr6ekaOHKlFdU8FWumxk+aUiF0hxEpJktodd/gSYEjjz7OAFWhiV0PjjGP0FYMZdm4ma1b8iKIoDBiagSWoKR83MTmZFxd+w2VfrGLlW99S7XBTPKILY+4ZxzkGf8qDz+flSO5mvF4X7c8eRWbf8TjudfHOrLeob6gH0XIzS2vk5OQ0s4U+1bRr1w5oXp930aJFLFq06KTGuaqskDivh5cvu4n31m/FXmUiytgZoTalbyiSnmhDJ+4YF8nO8jg8Bhe5ubnk5uYG8oUBjOMmgV6P0q0LGGuQ5vqLFSuKhNvtRggfXq+PI/kOXI1h9HNu9pdtO95uNjw8nNtv95uJ9OrVi8WLF7N9+3aGDx+OvaGGZdNmc/b4NDZveJkjOXV88c4mHnh/uv8cvjqiosIRQvDG65+wbce/8T4IqhDYPV6+WXaAXbuKKHnDyZS/XY7etw0MOiQEXo/Km29uwu32kb/RzcEdLg7tdrJ5eR3j4lta/OpkhY5BoWz8ahfXXdkdR1Uljy7aQM8eHTFbTHRPDOXzCf0h5JdtnvqtcTqdPPfccwgh+Hq5/1hoqP9vJjfXfwNzw4YiNmzwvz42ayjL38zHUyGjyj56XdSGJ9+7A4gGDmMy6bh6Ug/+M3srS749QGJiNJ99Nh+A0aNH882ihTicLsoOF7Po49mMv+k2TObTa518bC1cmxxNvVqBSlM1iV0Ht9C73XA2F6zg0A8H8Nhb+RuXoCB7Pw3x/ij3zzkdamicLk5nzm6MEKIYQAhRLElSq/flJEm6AbgBOK2FszU0NE6MLSSI8y/56VvGWaMHkjV6YKvPKYqOhLQ+zY4FR1iob6hHbdy1HRoaSnV1Nf3798dsNjdrW1ZWRl5eHlFRUcTFxQVKL51qjr7ZxsfHM3ToUKqqqn6xm5NwuziwdAmHDCYaZIWL521iTdkevMJDe8vIZkL3KGazjl27JG574RaKi4uZMWMGS5YsadZG338Q4I+oP/54U5WHtLQOzJ61ibS0BLZ8W8uyzwvpMMhMbAc9NNgYNqo38jG50wcOHODQoUOBxwaDgcjISMrLy6mvr2fT7DkMv7MzBot/nvE9bQy6sSv3yzezft8+PFIV4eF+V7mbrzifCf3nU9pgR5YkVCE4Oy2WITelkp9fydNPvM5LL05nzAUZDMrqTGl9NG4hqNyrUvoDhElWnD4XVQ0evG5BazHNGq8bk9XAx5/K/GN8J+4emsYL1XrcwBtX9kCJDEGOblnp4EzA4XAE7hQM6J+EwagjLj4Yu93N4cP+UmRhwcGc1bcvmzZuprS4Al+5AZ0kgwo/zi9m8rB/8dbiB9DpKwEXbdqEkJ4eyZ495bz7zloAevbsyZqv5/HM0zNRDAbq6ux8aNLx9szPWLZuOWaL9X9aR211PQvnLMMaEsQFlw9t9iHw1ltvZuFCf2qLQG0mdAFUfGwr3MAVbW/mpjuGI+slVE/zcKOsSFgjbeQc2k1UVFTgTojG/4YArfTYSfK7b1ATQswAZgBkZmZqgXkNjT8RR4Xu8OHDsVqtzJ8/n8zMzN/dQUmWZQYNGnRSfdzfLiSxropDEXHklLtYXbobX6MAcKv1qMKHLB0veCXK3f6d+XFxcciyHCjafzxPP/104OdBgwYxdGhT/uqFF8IVUwpZvXYlRWW5/OO5qS36NzQ0kJuby8cff0z79u0xmUxER0dTXl7O3A8/5PJJqQGhW1Xl4J23s3G5fOgSTfRPbMqj9Hg8rFvioKShAYE/sguwfv8R2nwVTNQAK5U1grvuuYXa2jr2l5oxmQX1xSq53/iQGpMwLJiwSHqOeH0kGBXEMVrJ6fOwtr6c+yf34YOHFvLuingmnVuNu9o/P3tQBPLolms8UzjqLIYQRL61g8hnBhDTLpR339kcSGnoHNGO/v378+m732CNVJCPsYROHWkkopPMs8+8wM233MTrr7/R6nkG9OtL8vjbcLp94PJfQLvTy+5DpXz01nQmT/31N0ufv/9tls3YG3j86i0LeGD2VQy90O+IMmTIYP7xj4d47LEncLrqWx1DIMivcTN/znqSlgJmggAAIABJREFUdCHNxa4EOpNC0tldmPPSYnr16tXqGBoavwWnU+yWSJIU1xjVjQP+nDZWGhoaP0tubi56vf7nG57BqAX54PXnYO4wmRk0ZAAClYKCQg7n7iTa2Al/ybKjCMKjw/nnNH9psgMHDqCqKvX1TcLhqMFFdnZ2M8MBgOXLl7eYg9A5OFHKY3m5vy7tnj17mpVYA8gtKubNtysDfWtq/GItJSWMmPAgdr6dj+QF2Quech9FdfUtTNR8CL5bX0icu4zElA6Eh4cRHu4X8vZyld1zmuavGCG6u0yQUUdBsIoxVMZZ5UMVAgmJXZW1LMj+FCFg+5Yc9uw+wP8tDyYozX9W0XsCsuk4R44zCL3eP8+EagldtYeCu1eyNN7EkdimOxaWBP8dA1e9j7C2OjqN01GTK4jqJqO3+F8IgTih0AWY++knGPSKX+weg8dj5OHHP+f/nvmSPn2688Qzd9O5S9ovnv/Kb9azfMY+dFLTHRSh6njm6jlkFfXCaPJvaXzwwfuZMmUy6Qk9qfa0rNsrISMwsm2/k7u+vJoF932Nx6EiVIEt3szY166kpKwUr9erpTCcYrTI7slxOsXuAuAa4JnG7/NP47k0NDTOQEJCQqipqeHgwYMABAUFtUhh+KMgt22HZWs2JtUHbWMY3NZfPL+0tIzXX3+L/Q1LSbUMRZZ0gERwhJHXFtweuDV8fJmoo+Lfbrfz1VdfNXtu5cqVJ5zH8ZuTjtKlS5dmucAAtVVO9EYFs0VPff3RihtNMvbgwSoOHqwi5rCErvFpu0egNKYuHI/D42XhNz8waBhkZTWVBDOGSLQZqlBboBKcKBOWJmMIOvpmLHMYILopshlDLBUVFURGRiIn12MzH7OBTa8nMe2nS6X9XgghUMUuBPkAJKfYIKecDWlWqmx6JCEQkoQkIC7V7/TmbdycFxQtE3TiIhutcrisikFD+/LVV6sCx4w6G3rFgscr8HhdrPx+I+efcz0r1vyX5JTEnxitibefnId0XHKJJMnIQsesV+Zxw9+vChyPiori1ltv4+lpjzZLZZAlHW1MZyFLCm4VkrO6c/vKrpTty0Nn0BPROJcdK1YgSVIgX15D4/fgVJUe+wj/ZrRISZIKgUfwi9w5kiRdD+QDl5+Kc2loaPxxuOuuu37vKZwy9FkDsSxcwK1HDlFc56Hzx/MZPfYiYmP9orfKm8em2lkExGQNpLV/h6Ij+Sz5bik7d+4MjPW3v/2t0cyiqUrE+eefHyhl9mvIyMggIyODyy6+ntAdEknXJJFUonA4u4rPq0qY9cZoOp0fh96s4HZ7ee7ZNYG+JRdJJMz1zyNMZ0QBjq9PIQEpUTYc+rYsW7aC2tpaDAYDHdM7EBcfS3R3hejuzdM4qj8HX7WPhhG1vPHGcxgMBnJycvjss88C61ZVlY4dO3LllVf+6rX/VjgdOeiNZRx9jd2bizkUY6Sq0Qr5sjUVONunkzHtZhSD/+119PjzmH7TwkCVDgCf8KILddFzXAiyUabhgJs13xUy8oYUtq0r5eJLz6fWeYjKqgq6Z3QiPDyM2bMXICGjV4JaVDRwuVy89vJs/v3yQ79oHfWVDmSp9fzZsqLKFseeeOkB6usaeHfm24FqDAmWztQZ/dHrWIs/XUlWZGI6No/g5ubmEhcXh8n0y0xoNH4ZqhbZPSlOSX0fIcQ4IUScEEIvhEgUQrwrhKgQQgwXQrRv/N7yL0hDQ0PjD4JkCcLy0KMo3XoQF2ri1cHnIiMDEnrJ2Jir2jwa6vA4yeo/qJnQHT9+fEDonmrWrNlA170GRoT5Q4hGWaaPLYQ7E1J5deYqfpxbgNvuQ5Fk7pjSt1nfms6gArIkMTI0Dt0xpsYyEgZZ4ea/9+Dl128En8S6dRtZuXI1M955l7y1JRxe56XqgA9XrYq7wS9+FBWIhHffnXbaNh3+Vni9bnSGMiRJQvX411enk8hO9YtGvVdF0snEpkUEhC7AhVcOZvQDmXhkB6rw4RM+zFFuMvUhyHn+axyUYmBkqF8kutxO7r33cZYsXo/Pp1JX00BiUizXTb4Uq8XE8b9j/rn52Jz9y6uY9B7ZEa9wtzguIZM5tEurfaa98zj/mTadGDUDgIiQJHSShEGGyY+0Xh+7traWgoICUlJ+3r1PQ+N08rtvUNPQ0ND4oyBHRmG+7W4AbgLCPv6E3Xt28/Aj9+H1evF6vXzwwUcUFh4GYMCA/pxzTnOjhE8++aTVsU9F/dFPp39Ev6AwDMfsqtdJMkGKwL3Tw9qSnVR/2YDHo7K3oLZZ3/qOEp5QQeRa6BQUihoDu0obqLG7aBdlY/gFaQyZ0AFJkvjm65e448Y3OXj4EAbJzBfLv2JAm/5Eb0unDkF4RwXDIFBRmfqfKa2u880330SSJHw+HxEREf/z2k838z+bx679e/D5msTmriRL4Ge9V4BPxb59f4u+N9x/OVPuG0vegcMsWDiXqooqBFLAKQ4J5AwJFeg9qA29B/krE3k8Pt5/ZznjrxlMXFwUd9w9kYP7S9i4bi8lR5rSYhRFpmOn1BbnPRF3Pn4tKz/+Oz6nhCI1lg8UXo6IAiZPeZBLF53LK6//s0Vt4NG3j8VhdrH38D6iomRsSQpTnr2KPue37nK3adMmhBDa5rRTjZAQmoPaSaGJXQ0NDY1fycBBA4mI9Au1l19+lczMXoSHh1FYeJikpOSA0PV4vOj1OjxuL/2HtnRrk2WZTp06/c/zCaoTqK1E/oyyQrIpiCvG9Sc6JhhZljkfKDpYwRfXbUZWdFSeLeGKAUesoKG0ioN7g9H7rCRaFFLbhTB2atP8hpzbgW2HXkIIwdZvN7Cn1EFZsR57now7R8Jn9QI+Dlo2Me8VF3e/9Uygb0pKCoMHD262Ie9UrP10c6SkrJnQBYiocaP3CULsPiLq/OvRR4W12l+WZWISIqiurkYqA/novc46UHuBmg51R+wExzYJ6IK8IwB8OOt77rl/LD7VS3JqDMmpMbhdHgryy9m4fj8NdS7umDrpF68lyGpmzq6nubj3DcQ2RNA2WOH8tAYs5gZe3mdm/rwl9OnbnUnXXcr7r3zCM4++idPtomunVPpc1B6AAWN6/WTqidfrJTs7m/T0dMLCWr8mGhq/FZrY1dDQ0PiVxMfHB1ISrrxyApmZvRgzZjSXXnpJIIJZX29n5nvzuP2OCXz77Womjp9Exy7tT8t8+ozoR8P7m2leFQI8qkpYmpXYuOYVDuJTIhg9oxcfXLec0FXBVI4wUnm2RO+wJGyFVrbk5LA5bxV7dtXgfWEAU++5nMjI5mP0GNGb9L0FBKUlgE8FRSH7+30sWlvCtuJ6svctIzH5Na544DYATCYTQ4YMOS3rP5043f4sZpNJR79+iSxffojkCjcpxU1VCiSjgcirRvzsWGqDQDJLKJtA9kr4fAJfFoTHBXH73Wfz4r9/ACAlLYHb70lAVr3cdHMPLFYD2RsP8+kn27HaTKS2jyO1fRwet48Vy5cRGhbU6gbG+pp6Xv7bm9RVO5j4j0voOqg7FVWVjIo5wsT2giD9USlg46VeFm7aVMI7M+bw4bTPWLFrJbIsER5ho8vQhECu9d69e5k9ezYDBgxoNU0hJycHu91O3759Wzyn8b/hr7P7e8/ij4UmdjU0NDROAZdfdGng52OF7s6dB+jRo8kc4f6pDzH/209PyxwuumUsH3y0GUNjTqk9VKI8WcaHxOCprUdP4ztE8Pe1lyGEYO33B1m+qpBNtXaMUSV8uOI97E6/yNv78lxm/2cJW7bOaCZ4D221896zu6mvyKH3WUH0T6yjoKQajEkkpxtx2CU+WLqM+AE90en8ItxsNtO9e/c/lHVsXEIM+/bVktUvCWdjzVtzSgii1IWs1yMpCtE3XkpQr583wpBTZX8N42SJhgMC0y5AgKqAxWJgzNhOzP18V6C9KutYt+EwI0em0rdfEt0zYpk65Rt27S6ja69oohKCKC33m5YYjUbS0tIYOHAgMTExzLj3PVZ9cChQ//j5K+YigmeRdnkUN6fHYNY1lwEmncLViQYezatn4/5t6A06br31KswW/wazbdv2EqwPoUNGUsARUK/X07ZtWwYOHEibNm0QQrB+/XoiIyO1kmMaZwSa2NXQ0NA4Bbz4xos8//zzzY5ZrRb69PEbNgghqK1rINRkaa37KUHR6bhiwcMsuf1t9PY66qNl6hvLXX29ZB/dMmNRlJb7klUfuCqDoTSK2D2FlHQEh8NKeGQU9sIiAFwuD5WVdUyb9jlPPDEZgI2Ly3hq0hZUVSCjZ9/WBmbp68kNWs3Vk65i0KCmlI3vvlvafK5CR9cerW+GOhOJjo5m3759LFueGzj2IzF0e20KISYZfUwEkq6li96xVBwuDvys08l4vSrGVBDRMkhqQPx37hxN587R5OVV85/ZPwKwYX0hI0f683LNFj13PdSP0UM/pqTgEAAJ7Wz0G9YGRfEGbLcNBgMVJU5METLeyqYPFmpdMAXz97EpLpwqexCRFjfd4msINnmRJYkOoRbE7gYUncxNN1+B2WLC4/FyYH8+X325ArNso/rjXRQUFLBq1SoOHTrE/v372b9/PwaDgYiICIqLi7ngggv+UB9o/kho1RhODk3samhoaJwCLBYLDz30EF6vl0mXT+bblT/AMRUNVFXgdrt59sl/ndZ5mKNsXPzxPYyormfyFTexYNVXnJ3Vm0GDBpy4kwTGcDcDr7yQLQt+oE2IibxqifT0dAobxS74Be83izbyxBOT8bhVpt2SA6ocKOujQw9uG95qK08//Ryy3CT+jIqFRe88jS7ZyMJv9hMWdpDFr61m+E2T0enOfMOR4cOH079/k3hXFOWkK0ws/WgBAJIEDzw4kJ05pcyduwuC/ZH4zh2bb9QLDTFx771ZvPCC3z64psZJSIg/wprQJrhZ28O5taxbXMTybTPYvXs369atIy83j+A0GWsqCDfY86E6G6iBNp42bD8s8AmZgiqVbcWhjOleSGSQg11VdlLjEhkxNgOr1UJOzn7mf7Gs6WSNAjYpKYnx48cD/hJjq1evJj8/n+Jiv6jPyMg4qeujoXG6OCWlxzQ0NDQ0/IYIZrOZWXPexWRUcDpdOJ1uHA4XbrebjE4pXDL2gt9kLhW11Xy2dB52ZwMejz8VQZwg0U+WQZJdlJQu5vUNC9mwyn8L/ahD2rHExYcjVMG+zTVIisrtr3Tm/V2D+eDAEO57tztt0kJIMHTG7fbgdDoDX/XOatJHRGEw+WMsXpePYTe2Z97zb5+mK3BqkSQJs9kc+Po1pdS6ZvnzabOy/NUW0jtENjnieWHUhenN2gfbjDidTe5pr76ynice/x5VVTmwp6rF+O07+fPHO3bsyLXXXkvt94KihSquYpB0YG0PCVdCwrUSoh94rP6Tq0LG45NZti8ap09lW1R7/vXGXQQHBwE0E7oSMsmhbVqcOzk5mYkTJ5KZmQlAZmbmH77cnMafBy2yq6GhoXGKsVgs5OZtZ+LY69i07UcMeh2XnD+Kf7/x9G82h5eeeg1xXGWGV19Z3+pt5dBQE5Ou6UFkpJkJkwYwc+Z8runakZAQW7N2FrOBqbePpm5bGQ63hZnbh6A3yoExs0ZF03NoBFf3z4edzc8xcGB3jMJAVVUFAB/N3YEiSaBIrF27lqysrFO4+jMTn8f/elitfhGo08kMPyeV7E1F5G+qxPn2ckxThoKqggSSIrPs0xwyM+PZtKkpwv7Uk6vYs7GiaWABEhI3Tbyk2fnGTh3BWzcu4Yjf8A1zMoRkgCkKRAp4kxs7N3IYI6/TAVmSmPfFXAAWfb260RZYRUImWBfOyj2t55wvXLiQTZs20b59e0aM+PmNehq/Hs0u+OTQxK6GhobGacBisTB3Ues1dX8LImMiAmI3J2cnNlswo0ZlERcX7m/QKFBLS+opLKzF61UxGBTuf2AM99x7CS88/wPx8fFcfvmlLF64EJ9P5dmHr2ToOZnMmLyW698egE7fXExLsoQxSOHSO5OYfyN065LM/VNvRFUV+g9tiynMQFFxPQAuV1PEMjc39y8hdvdvPtLi2NlnJ5LWLoKMfz7B2JpOdN77IYZuSaDI+HIKOafGycyctky84yxUSfDhf7cDsHlNUSBLRi9gWEgSC+/7AlOogc4Du9CQn03vC1zMsDWg1gYhAY5ciYaDKik2GaUt+NIBY9NcJCCkTWjA2rp37970yxjCvTc8icPt5KweXfh4xRutrq2iooJNmzbRqVMnLr/8ci1XV+OMQjrRba3fg8zMTLFp06bfexoaGhoaf3jcbheRtjbUuao4NnoXEx3BtOfv4bIJmUiSxA8/FPDd0oPcc0kKBhnk9Di+XX6IjRsOB/p072hixPndMFstqD6VnZsr6dQzAkXXuqApPlzJkq+389pzfhMGVRWoPsGEKd259pYMZryV3aLPI488csqvwZlGTU0106a9zPBhKWT0iEX4wOcTXD/mI1Zu2UEvWwzvDo3ApBOYdAKnV6LaqTBXDWLOxiouvqYpzUH+UKCTmmciqkIlXy5k2rL70UcXBgTnU1ctZ+cqFwgZxdqAV60jw5IM3qbfC8WgkHxuKntDD+D1ehkyZAiDBw/+xWs7agOdnp7OuHHj/scr9b8hSVK2ECLzd53EaaRrSLSYe/YVv8m5Onw7/U9xLbXIroaGhsafEIPByBOP/4sHHnoYt89fC1YVKrG2VC4aMx7YC4Ao9Tupud9bAQj26k1stMVgMChMvLo77727hYo6PWarv4qErMh06hmO1+tj9+5KfD612XkFUFtaz2cfFVFb09yS9qOZ2+k3MJEbb8pk9qytOByNJbyMRv4K6PX+9IUf15Wzc1UpbpeXdz9bQUFBOQCba0sY+FU1N7brSKJVwZYay7DX+nFvmIlzt5Yw/8vdgbFUIY7d/wiALMnoXXqc7EOPOXD8oY/95iZVVQ2U7LWR0r03C+9fwMFV+5H1CsKrEpYRGRC6gwcPPimhC7B7t39uF1100UlfFw2N040mdjU0NDT+pNxx381cf+vVTP3bg5SXVTL6iguYNGUCALv3ZJOaYMS7di9Yw8HlASFYEpoIQnDNmA7ExNuwWPQUFdWhquox9rEyu/dU8eWCXSc8d59h8RTk1uBoaHJKc9i9zPkgh1dnXsA99/orG7z15kbCQuJP2zU4k9Dr9ej1esrtjVbNMoy8sCfTX/0cr8+OQOCQjTy/345eNlL0/b0UF+fw8J0fsGLFDtolJ3DWWX38fSfI8FHT2DqjTLuBoSSZVQxW5QS52RbKVSd6o56+D2Sx4PBCdq7dCSFwYfIFSF6JAQMHYNp9kMWfr0c2SCSe24NOI0f+5LrKysrYsWMHiYmJBAcH/2RbjVOA0HJ2TxZN7GpoaGj8iQmyWJnx31dbHO/Y4WK2vP48x6Y4rLSF41QUguscrHgzh/Me7kvHjpFs3lxMdnYx9furaZMYSnznSKry/X6311yTQZC1adf94jk/4pUN5JXUoygt35Cdjibx63X58DoEcsRf461Ir9czdepUnE5/pH3lypWsX7cBj68+0MarOvG53PTLGM72bfkMHXIHdrsXkNizp5TQ0DhSU5MAcI8TGD6SiO9h47K3uiJJoJMFskmHEKJVwfvvf62lIO9bsqs+oKqqCovFzG3X3wxAYUEhjv9somCXC69DRVKgcNU6SjbuYsjDd7a6Jp/Px7x58zAYDIwZM+YUXzENjVODVnpMQ0ND4y+Ku8KCavQL1UV9e7AxOBy8UPylmS1fyDzbdyN5n5cihGDFkgP0v7g9ib2jEWaJoBh/WsOy2dtYPH8zH721ih5d7mHt9irCw22tns9s0XHRmHSEEAghUAwyOvNfK0JlNpsJCwsjLCyMqsqa4ypmSETpUuhgGoq+KoIpV/9fQOgeff6Tjxc1G889TjBmeidMwTqMVh2KRY8k+9sfuydHCMHBXbXs2FTO7sKNVFXWYDQaufO22zAaDATtFvRYF8eWdbW47P7Ng8IHPpdK7vwaynNzaY2FCxdSXFzMxRdfTFhYy1J1GqcH9Tf6+rPw1/g4raGhoaHRgjYX9eNATRB8n8f+gjqEA+rnA26/WPKpkPe9ijVR4JIEz734Q4sxLpjUk3nzHAy+sDNX33I/YWGh/Pjjj2zZ9QVGow6nzofXq2IJ0pNxVgwXjklvFnGUJIm6mrzfasm/K6qq8sEHH5Cbm4vZZKamuq7Z8ynGswlWolAkHXUVbnbU50Ir0dknn3iT22+diC3MCsCLr61j0KC2DBrcrqmRAK/Dg2LW4/OqrPjyMI/ftBGAeu8R9AaFO2+/FZ1BwbJPELbLXwYuSpKocHuJNjYZfcg6id1ffEO/OyejukFnNCBJEkVFRWzZsoXu3bvTpcsfxw1P46+HJnY1NDQ0/qJEZ+g4sNZ/g0+RJGo+FaA2F1cCgWGbgahRZhSdjCxLlJc3UF/vN6pAD3Pf+YrLJ4wkLCy0Wd/HHu3Ltt21VFc7GTwimcEj2rZqV2y1nT4L5TMJp9NJbmOE1OF0UFfgYXvBDgAsclhA6DbR9Fr4o+FufKodhOC16bOItMVzwx2XArByZV4zsSvJEiWbi/n7ffnk7ysFwGSAD7/ojTWyD298fgiH04fpoCBsR9N5dLJEuF5HrceLTe+fS9/700i7MBYh1iLpYP/3Nai+dJbt/R6r1cp55513Oi6XxgmRtJzdk0RLY9DQ0ND4y1KDt7H8lNGnILX6BirhyROMGpTCpGt6MPHqDO6amsW556UBoFMUquw+Vn63tUXP3iMnUPDRZoaur6NXjzBk+cRv0EI4TsmK/ijsfa+e2qUmdm7IQ0YmSA5HOq68QpguMZCK4PPV4/XVIIQHgRe3t4qK6sITju+ze6iqUhgx5iwMRh1hYTq+W9+HMJuDt+YewuFS0R0WRPzY8jVRETh8/vP2vS+NtItikWQJSZKQZInkgSHklfxAaWkpQ4YMwWw2txhDQ+NMQovsamhoaPxl0eN0+iO0MQlBVCTUHF/NCgkIaiPz5ivfc9mN/VAMCgAV5XYA1s3bg8cnodMrrZ6hk9GGSdGTM2UNWV9egKoKDh2qxuf1ZwS6XN7GPXJ/pgzB1jk2h9bnERgkieG2i9hQv5IG1YVABZquYxtDJnW+ElyqA7WVDwMetaHZY69HRaeXsdd7KN9WTNcLriL9HMG2ZVt4bnoK3oZa3vi6lAanSuckE1XZDnxC+J3sjkFCwmJS0FlkOlwe32KjmyRJFLnr0HkUevbseQqujMbJIABVi+yeFJrY1dDQ0PiLIpFEROQhAHKLazCf03q7ejxAKJ/Na1lq7KHH1yJkPUNH9mq1b5XPg0+oKHUyDRW1FFd6+OSTnGZtEuOtwF8jlQEgJiaG2j4ypetcGGUTA20j8ahect01qMdsWJNlmV7WURiVbSwrX4d63AcClabKFu2j4tm2voKKEgfffHKIx965E53BQNWPm3nq3Z5IzlLeWFRKrUOlQ7yRy7LCKIgy8/VDFcg0VW7wqoJ6n4/4vj6cXgdyK8YhVVUO8vJqCCoyak5pGn8INLGroaGh8RdFkuLp2TOT+PhgVBW8Xg9Lnt3P4e12vF5BWKyBmrhSZi9cFuijlxXaRkdTXFlJkJSGkPW8/O7dBNuCWj1H8AVn4Vmdj6LI7Jy4DuPjnQAYM6YTISEGvE4Pie0G/yVE09E19uzZk0kTu3N9z4egzgJIIKnEGYzU+tzYVRUJMMoywyKtHHElsaJiA6o4cfR77PWpqKpAqLB98xFsoSEANBzJwdg+khmfFVHdoJISY+DKgX7L6KT2JvrcEcKKV6sIFjICqPS4+ahkFUWfOAHBuNdHYjTpm52rpMQfUY40R5/qS6TxC9Fydk8OTexqaGho/EWRJAmdkkZ8XDvADpiY/LLMmg8+I3NMJLIOXB4Pb3+2kKqaplqwBYdLGDpoCDdc/zeGn59JSKj1hOe47bm7uG/oTZzjNCHVQf4LOdDVQlleLV0uGI4kxSFJptO+1jMNi9XMf/f8m68/XMqm77aTkBrDNfdewWNZ92BzBKOTFGw6GRWBSUnAYDLiPaZGMUCvXk32watWHWLosBQAbv3nWVSWHiE8Opbo/lFMfzsbu91Lmyg9E4dENBuj55AQgr4vZnVQGCUry4kyBHNj4mDW1eaxpGovL7+4jPseHNnsw0hOTikSMOT6oafvAmlonEI0savxp2fJkiVkZ2ejqioej4dOnTpxxRW/ja+4hsYfAUnSAf7auDoDDJ58FfVltVQVlGGLi6SwOIenn36FT+fMJzTUxj/+eQ8jRw752XE//fRT9Ho9aVf1pEBWqCmoQh9sAHs1m3ZWsjt/EUajkd69e9O9e/fTu8gzEFmWGTVxJKMmNjmULaOY+PpS+tna4VAVdttLWVy1B6sphdi4egoKDuP1eBHANVddRpU/dZo1awoYOiyF+mInh1aUU1ZazIDrxzD7o+3Y7V6ioixcfXECouGYPF9Jwhsdi+3SJHQvbCLG4P8dMEl6smzJhOrM/Pu5paiqyt33jkBvVKitdrFrZxlJMUm065X8G14tjWNRxc+30WhCE7saf3rWrl3b7PGuXbvYu3cv6enpJ+ihoaFhjbJhjWoyh/jnP+/mn/+8+xf1TUpKIi0tDZ/Pb05w5MgR/xMKYPerM4fDgcPh33TldDr/kmK3NcorqthXU8v3NQebHTcYTaxbt5Q1K1cy5dpHEOgxKMHcf38Pnn12DQBPPP49bb6SQAafEGzMex53GERFWmjbxowaE4vk9fhfA0UBqxWPy0fuHhc+V/OosUFW6GKJxaaY+PfzS1j8/h5WHvyCxd/6PYovGH3Bb3NBNDROAZrY1fjLER0dTfv27X/vaWho/GkJDw9nwoQJgcevvPIKQUFBZGRkYLfbsdvtOByOQN3ZoKDW833/imT26cbSb9c2q9wAEBYWQmRkGKPHjmbx/I18s2gTcz/P5uomacdcAAAgAElEQVQbejRr53Or+HwePFcYcAswuF1c3r8r+2pqcDo9mM165EanM5fLi6xIlO0oQvj8+cCHfPlst9dT7xV0suq5s113SmtDKXfqeDDrn5jO1dGvXz9iY2N/mwuioXEK0MSuxp8Cu91OUVERqampLTa6jB07li1bttCnTx/S09P/EhthNDTOJCRJwmAwEBMTA/gtcyMjIwF44403ACgoKGi1b3R0NEajESEEJSUleDweKioqCA8PJzo6GpPpzMv3raiowN4YwT4Wp9P5s30feex21q7ejNPpwtcoQM1mE888f1/gf9fL79zFR+9/zMfvb+ejGbu4794BPP/CagAs7dw4OsMRAWHCzfUiH/vsPCIzh5FXlI+xUzBxaf4NahaLAZ9PxZYaTsXuI2xy7ua7EnegHkR+g5t1+hJ6yMH4JAP6QTI+h6Di2VUwcmSLuWv8Nghx5mxQkyTpPeAioFQI0bXx2PPAKMANHACuE0JUt9L3EFAH+ACvECLzdM1TE7safwpeeOEFhBDcc889WK3NN8t07dqVrl27/k4z09DQMBgMHDx4kIMHm27NS3urufqRyRgMBvLy8njvvfda7du1a1fGjh1LYWFhizZxsXHccOMNp3XuJ4vD4WD69OktIrPHYjAYTvhcx06pfLfyP/z7uXfZtHE7ySlJ3H3fZM7u54/gCuFE0e1i4pRuTJzSDYCDu5t0RE5bGYNJT7DwMMVbgE6WCbGArbuC1KEdiuKv45u3pIDK1bmoskyDKY56UddM6B6lxgNE5xGa3hHFDJXrJNbtg7EuFwaj8dddJI0/E+8DrwGzjzm2BHhQCOGVJOlZ4EHg/hP0HyqEKD+9U9TErsafhHbt2pGbm4uq/vkL02to/NG46qqrePLGB4h2JuAOUvGkC0wF4Syc+hWl0cW0HdCbxYuX41N9nHPOYIYNG4CiKCxcuBCXywW0HhXN3V3EqHb3Ep0l8cOyr/G6HNxy31TueuiO33qJATweD0II+vbt22q6lCzLtGnT5ifHSGvfljfefoyHL3+Mw3klNORVQj//c6oootGFg7oKN7Me2MMX8/Yz5E5/tNYQ4S8TJspd6I5xb3Z/vQ6REA2KRO5jK+iYUE1COKiqRDcKeUStbyF0j1IcYiKpF9TvhdqtIKFQX1hBeGr8SV0bjVOH2sL+5fdBCLFSkqR2xx379piH64DLfss5tYYmdjX+FEyYMAEhBDqd9iutoXGmERISQjtHErX7vajxAtLB61RpqPYSERxO3exCBoamsbRsAw8+8BQDBvRlwZcfNEtRqKmpAcDnkKjY6yM6Q8ZdK1Br9BQu8nCovgGHt5ypD9/DM088xhH7aQ8W/SRRUVGkpqb+qr7vPTqLf704E4dwICHx9Q0b6XBXOxZseYuQGH/9W69H5alRmynJr6DaW82BXS5SO8UFxqgND6LGASGNwVdvRS1PXvEcI3oMYnB8DfrAv0q/xDUZWpe6QcF6egxLwl0JFSv9x0yKijUxotX2Gn86IiVJ2nTM4xlCiBkn0X8y8MkJnhPAt5IkCeCtkxz3pNCUgcafgqO35jQ0NM48Hhh3E2EHEhC+pmPeTL+9rccgQ5kbeY9Ef2MmoWdZWbBmPcuXr6akpASfz8ejjz5KQkICAHlLBZUHvZijdFijJbImGBBmA5lV48lzlOBT/RHg8/qP4Js1S36T9R04cIAffvgBj8eFLP+6/0XC68Wz/xCSTuHRF9/HLvwlwgQQERFMTEYQT9z3NLHRoXQbEUP1YTemEAd5oQUk9/WS0rF5GTBZkZitTyRC8eFBoqeuim+3FXF991oM+pbCdvJwPR8fdDWL7koSDL24HQajQuFcEF7QyyqZ8W4theF35ieyZE415b82l1aSpIcBL/DfEzTpL4QokiQpGlgiSdJuIcTKE4wVBDiEEKokSelAR2CREMLzS+aiiV0NDQ0NjdOKu8EV+FmuArUMMPi/vDaBlAzyYXDjo2NiByJ7xrNq1bJmY9TX12M1hOGoqAAg9IiKLkjGFSUDYFUNdA9JpBYPqlEiyPLbVHjwer189tmHuFwqkZEWJEkiIsJCQsIvr1bg2rKD6pdmgKry1l47dmEnLj6MvlkdiIsPQ6dvEtAOPGzYUAiAkiUzFL8jncPhYMuWH8nKOjvQtt5o5KgViEuRWXZhbyrl1lVSdKSJixPdLChsyttt3y2C0AgT9asdqLUmjIqgT5yLiase/eUXSOMviSRJ1+DfuDZcnCCBXQhR1Pi9VJKkeUAfoFWx23h8oCRJYcB3wCbgSmDCCdo3QxO7GhoaGhqnlRcXzGT6BU9Tm+tBqpfQL/Ufl3USnlEqRzPtvWPAi0owzYVqaXEl9069l0M5Zax7fRY2PXQoVNEVCXJ7Q12MTPRBlcjDPhJDa5nZ7rfLZ3z55adJTY0gP7+G6GgfsbHh9DormZqaHUBCs7ZCVDbm3HqRiEaSYlEra6h6/nVqhIGtZVEEh3u47eYkhFlCkiRcLg+HcyvYvbMQe6WX65N7U5qpohhlKreUk+srQFYkli5dHijrds45wwDoW1tOP3c10yJSkVQw6WRKaky0cbswHJe2IMtwwHqEx669iAVfbqBOwFkDY4mLiubqzydSuukA0T1SMIfb0Ph9EUioZ0g1htaQJOk8/BvSBgshWpYlIRCplYUQdY0/jwQe+6lhhRB2SZKuB14VQjwnSdKWXzonTexqaGhoaJx2io2HCLO2QfUIvE4VnVnGGKpQ563DoDfii2894ug5rLJn3gGmB7/Dfc/dQWL7SDhwGNG4QScux0ddtERhDx3hhYIGl5FIs5kaj49Jwx+jW+8Uxl4/hJT2iad8TR6Ph5hYL1u35mK3+7j3Xn8VBltwCF8vfILYGDuSZAFAVXMpK9zJ4o9zqa5003tIDJnD03GuKKVONrJy+/+zd9/xUVVpA8d/Z2p67wkhQOgdAoKAoohYUGwgrq597Q17eV11V7fpWlfd1UXXioqLGhAFWVRAxAICoSSElpDe60wy7bx/TBgSCBhKCuH5vp/74d5z2zPju5lnzpz7nFCK09y4enh7qvfk5rF82dfs3pNHT/8BhJljiDcl0mCGothKkvpGUbStji8yv8LNvl9yV61a7Ut2cywBTKz1VmowNvXXDvIUklsUTnJ8I2aTxu0B7VF8kxnM0vVr+cM/X2D23+9m0aJFrF27ljPOmoZ/SDA9T29Zz1cIAKXUPGAy3rG9ecBjeKsvWPEOTQBYo7W+SSmVAPxba30OEAt80rTfBLyvtf7y0LdS4/H25F7X1NbmHFaSXSGEEO3uyU/+xZzzryExMI4g7Ydd1ZCdVUB0Y190HLhb+dXfVQcFCw30tabxxefLuP/pO/nzwt9xfb+70YQC4GcDSz04gmDjOd5pj5VBEQaExWps7OCd93cwathIlMHG8JFj6ZHc+5i8ptraWnJ2l7NtSxkpvZLxV37YtI2a2iqmnH4vNvslGI0BaN3Imi9X8cj1PwOKk86IpaTEwZKPNjFBKTaWhZOLxthDY7c38Prrc6ms3FdOrKBhFwnWgTgwsLjwF3qUpkBfcIQ2opQRDjJssdjqT/P6NB7A4/Gw8scKEgYlE2VsxOVRLNq1nT99OZeQkBBycnIBWLt2LePHj6d372PzXoljqwtVY7islea5Bzm2ADinaX0nMPwwbnUX3iT6E631ZqVUb+Drtp4sya4QQogO8Vz6m751j8fDdy8vZPWHG9Hh4MaDZzh4vJWzcNsh713veqNbkWpJAWDRF0tYUJbO1JhZmJQVg1L0W+Fi0zlmMCjcTo12eTBZDGitfRMxPPHUU2RnZ9LY6OQ3l57Da3M/OKrqLeVFxTx67T1YsvwYPak/DX6Kh2+eg83q4IV/vUx9vQ2TKQ4jJp5/4g5ufPBMlu25AA3YKupw4MGjzeQW1pIz0ohxtHe63i8WLqGysgqz8sPPEIw2+WExh5Pt2oFBGTFhIq46HIggOjmZ0VmT+blqOaDZOyBkx9Z8+gxMRCuF2+Pt0S22+PFaXAq/3bObD7cG48yuo+dQK28tfZ69FRkaGxvp0SOJhQsX0qNHD6ZMmXLE748Qx5LW+lvg26YhD3uT5TbXGDS0V2BCCCHEwRgMBibdPoM5S+/juueu4p7376V+075yDX9++u8srJhHrasGDfSN60deXgHXX3cXbu3mDzu+oNRRR4PbSaPTAVrjX+tkxT/LWPZKBdvX1LeYLTExMZ6aGhuNjU4+nP8lLz13qOGBh7Y7czsD+k7EsdlDv4A43EEKLApXtMISYuW+++4mNNTb8/zo7ddw8yNnYTAa8GjNU0+u4LlX1vHyK+t59dWf+PTTTGr9XGDWZK7fxqatWxgaMI0zQm9hQOAZ+FuiUcqAVuDGTSONrMraBlozuo/i9B6xDA3tTWrgyfTyH8vloy9n7ruzfbFWDk7mjLIizB4PNoORe78JotZpxOVwEthYys3nTMOgFAEBAVxzzVUsW7YMPz8/Zs6cKVVuujDvLGrtv3QVSqnxSqktwNam7eFKqVfaer707AohhOg0lgA/olOTqaqqJGwUNDZ9wMYnBnPKKb1ZteJTJjTMovfwZD7+eKFv4pi8hiruzPyYZL9wrMrEJVxAvr2exqZ8OXVcy4fcwsLCuOCC8wDIzt7OSy+/yZz7jizhnXne5cz87VkkmiOor1W4gwC3JnQj2HqCM0IxZ87tgLd81/PPr6GuztHiGvn5xTQ2OqiqquWXX7ZSVFiGy11Nf79TSLQMwqhMlOkiPBw4UU6D24UC7CYTd6c1ss2ayjvf3ILF33zAsRFThrNxzTLqrR7MwUa2V5lIG1HJ/Izv2breg0drkuN7cd2MU7D2SsHlcnHNNdcQHBx8RO+NEO3keWAakA6gtd6glDqlrSdLz64QQohONW/uO1j91jLt/IG+tjvvvJnFi7/HbHWTYVzDtHtPx26z43K5W5yb21DJNlsJAI3uBqqceaD2dUk98/QLFBcXExERTkpKTwYPHsTJJ4+nprb+iGKtqqqmsL6e2NgoXBEGGqNAeSBgDwTtgphvwFS2L0HVmgMS3Y8/Xshb//mMD+Z9wZdfrKK4qBylFCZjECl+IzApb9LqpuVr3cugQGmNSyksRhib2Buny9XqsS98konNGIPT5a3uMOWGcJblZ1FZ00CtzUG93UlxhY3djQZsNhsXX3wxMTExR/TeiI6hAY9WHbJ0JVrrPfs1tf4/kFZIsiuEEKJTTT4nFJPRgNW6r2eyrs7NXXfdTmVlPWPPjiA4Opizzp6C1Wo5xJU02bavGDB138/vrgbFq6++zvPP/4Pnn/8Hu3btRimYNnV8m+Ob97dXeXXkb7m519kkxgz2JZbmtQ3ELYG4JRC+rikCDa4lNSxb8h12WwORkf6ccca+CR8uv2IY2dsKD3InI8ZmP7hGqlhUKx/TQX4GjHgfUjIoGEcJTufBP/e39jKx6as6Snc5MPkbuPQ35zJz1jRMJgMmk5GZM6fRIzkBv5pyUlNT2/y+CNGB9iilTga0UsqilLqXpiENbSHJrhBCiE6zbWs2UdFBGIz7Po6MRm+PktZGxo8/meraGgBGjhzKRRdOJ9QvkRj/QUT69cViCMTjsTcdD27tIGVQhO9a6emvERYWTGhoMIGBgVjMZoxGI3/68zNtiu/jF98g+tNtON2KT2t3Yg30wz/AO43xD2VZNHqceLS3J9etPXjQfFC4kuy1WRR+UEOPME1urneq4+HD4+jVK5y4uPBW72VUZsp1LeW6hlptJyrAnwCTBdXsyXujgr+ekkijy021y02Pd77hkY1beeimN7HVN+BweCsz3HnXWN85JouBky4NpSLPReGGTdTX2+nbtyf33HsNt972G1J6JbJ0ySoaSovb9J6IzqdRHbJ0ITcBt+ItXp0HjGjabhMZsyuEEKLTuJ1utEe36Hq55pqRfPXVDnJyqjGZDAQFBXDBaVfy8tt/Y8Wi3QSbEjEoI1pr/E3hlNsym870Dl+oqaklJMQ75jRt/OnMmXMXzSdxiouNoWevfUMmDiX/zWXEBiawY0wINyX/psW+XFsZz+cs4szI4cRYwtDaytbaIvwMJm5PuZYvK3/hD0/v5vyLxhIYaOacc1PRWvPwwxdw113/we3eF5PCQKJlCCiF1VLPo3fFcPKYXtgdyXz8dR5vLMglr8xFf79Q/vVjFqN69cVsMVHvcrN6dzardm3k2w2/cN31Z+Mq92fpvBrMbn8m3BDue1Cv/6QA2BzKi699xOixw5kwcSSBgf58tXQ1mzO28fg19xzufz4hOoTWuow2zpbWGkl2hRBCdBqPw8b3a7YwYcKQFu0ut7e3NGd3DlvtNWRn5eO5NpgGRz11zhLcnkb8TGEEW+KIDBgAgL+/PwBvvv4+d95zIwD19fVorRkzZgzR0dEA9OjRo83xpVjCMCgDEcnec9evz6SosBSX20N2dg4ep4tFxRtI8Usk25ZNAx7mJF+OQSkajW7OPm8UWmsm1+ZhXGVE19q4NshO/YUjeOS/v+DyeMujJZmHEGXyDnd46sFYRg4NxGoxYLUYuP68Xlw+NZm7/5DLd5l15JRUM8ztxt/kx/0PXItSioKCQizfZzP0UxMBRoUtNo4NO92se9Hb0zv6Tu/wD3dSEsP6RGO1eD/+t2/PZXNGFueM7c3U37W5kpMQHUIpdX/TbGkvsffbbDNa6zb9P60ku0IIITpNTHwsM6e8wI8//wPdlODa7I2k9gkhP6+WGTPO46knXyQ4oDfffPctja4q9n7mORx11DmLiQkYDEB4eDinTDiF++56mLWbV7W4T79+/Y5oPGqRs44oSxCNu8pxRPqx+PMVLfY7nGXkOkvItWdhNkXw5yuu4MyLelFb3kjtumGYzSZiqksZmRaAoazMe5LFwJ3nD+Dak/oQdterpPpNIsrijS04LI9RQ0djtezr6v7wtUqWramnxmHm1Igwtlj6sWH9FkaOGoLWbqxWKz16JJFkCCH2+kHEJUVgW5vL9ofyqS+0kHbnvnHOyRkuLkudQuFgP/J27iZ/yxZ+f/lp3PbCvw77vRGdRIOnC5UFa2d7x+X+fDQXkWRXCCFEp3G7IVJHktrrSv79yt0A/LhiBwZno/cAZeDMM87h+++ysDcW0bxzR6Nxayd1jiKqSusIjwnm9KmnMP2SKb5k94svvjiiuDweD6tWraL83D78UuYgLMiPYkc9VoORRs++h8GMhkDcnloUFgq2vkJYL2993Xfe2YA10oJyubmqrwWDueX4R2VUBMWYmZQSj6E6EjdQ665mSFwADqfHl+w+93gR6Rs9NLoNgKKwTuNWceSu2cSalZmYlJWQCAvX3XgBdYNjGJbWB6UUU88NZ8rZw/jTU/uSc7dDkx9tgH4WQsvgzJAJjPj8WfwPMoZYiM6mtV7YtGrTWs9vvk8pNbOt15EH1IQQQnSakj0FlLkrCCGEG257BbvNRuauWrbk7psCN21cX1LCvA+dGZWFAFMkVmNo016N3VWBo25f6a0PP/yQ2NhYAAoKCo4orvLycr7++mucJiiPs9Dop+jVYOXKhH3DLRRGTMYgzIZwvvzXHwjrFYpSinff2UBuTjXh4X7c/8ipGC0HedBHw5DoJHr7x2M2KKpchSzfthmzyfvRXFPt4vMMD41uBU0PC1W5KvildiWlzjKcNGDX1ZSUlxMQaKS6upHt2eXe2JTC5XL7xuvmLHdRst4D/U2k9k3llr8/xPiXrpdE9zh0gpYee6iNba2SZFcIIUSnGTZhDHtyKsguy+HMiaOoysol/z/V2N8342761V8pxZkTxhNpTiYhcCTh1l5E+vUhPmAEJoMfQYYgdq3Yyumnnw5AZmYmM2bMOGYxXnHFFTz8+O+ZPudans6Yz9Ch3ofbNG40bpTRzMRLBqCUoqiolpycagIDzdx40xhMZgPlbj88TQ+j2R0u5i7fxGXPL+aB97/j6801WM8oYb19KQ5PPXm1ZSxYVIGtwc3PK+wHzGKV59iIZ7/yohoPn3zyPwDWrvOWNfN4PDz9t9W+YyL6GYgfa8RRCLNnz8ZiOVQJNyG6BqXU2U3jdROVUi82W/4DtF5cuhUyjEEIIUSnuvK06fzzqw95a8FixoaOZ3xYX98+VwEY48BvoIELK4cxrcqfxSXlZNUaadANaGtPAjyKhdmLcTS4qKioYP369aSnpzNs2DA2btx4RDHV1dUBEBUVRZ8+fQBIGeAdV3vXzLMYcv0EEpJDydxcwgOvLUM1lU6z272fv/36RWIyGdBas7pIc75FU+1uZPyjH5BfUUd9owuTMqBR7JlfhtNloJ5aAK599UPyCi4grX8wrv2SXbun+oBYB4SEM7Tae3+X0zvu+U9PrfTtd9o0wUkG6ne42bS8EuM/ZRrg41uXKwvWngqAtcD5Tf/uVQvMaetFJNkVQgjRqV5Z+hYpt/bkjXkf40cARpqSMQ2mhH3HxZwcT8AqG7NNcfxYZmZTtZFUcypb1GamJN2D262JTgxjxIUGioqKKCoqOuKYAgO90w1PmjSpRfviF55n9tlBKFMwBqMismcg355xHeuX7WbUBX1pGjXQokf2yX/9QEF8EhstO8kpraWxaRY4V1N93np7BWZTpG/IAcDvP/sUA0ZmJ01ne7UBl8e7z6QsOHUDAEalSJ9yKmMSDLg9ipe0pmZzIU/+sapFzOYARU2Og4WLtnFSUp8jfk+E6Gha6w3ABqXUu1rrNvfk7k+SXSGEEJ3u/pf/wP0v/4HnH32NXW/vwazMNP7k7dUFMPbSmMIVjVaFf4NmdKSTrTVmQNHP058tDQUEGEIoyqmgsT4Ca+DRjdLbm3gajft6Qd0uFxOHGzBa913bYFIogwFPdRnO2hRvzWBg48ZiMjKKcbs1F/xuEpVAD9WbB8+cQkNDA+XlFWRlbWPlyu8AD96ZT1t+JA+wplHf6KJ3iJHdNUZMBki09CXPsQWXdvNM2hjS4o0YDRqjwXvfikD/A15LSUE9X6XvxIyF19b8/qjeF9E1nCjVGJRSGTQ9ldr8y+BeWuthbbmOjNkVQgjRZdz++HUUGUtweJy4SxQNGzT1613kfpfX4jizwbsAmJQJRb1v39evV9BQcmDSd7QKd+wiMMp6QLsyKEaNDKfB05cf07O9jVpjdrmoqqynqrQO/3JN7o5cSkvLMBqNJCYmMGXKaYSH731ArOUHeZApiNMGDyE1OJo/LH6Evn2qGRBezcODUrlmWF/8TEYu7BOCydgs62klGVi7opCv5u/C3xPArdedg39AwLF6O4ToCNOB8w6xtIn07AohhOgyjEYj72e/wh9vfZatS7PxOBz08HNwcUJPfgEK401URGjcHghoKsjg0YpB7hAU+xLcqjIbcTH7kj+Hw/Gr9y4uLiYrKwvwTkYBYLfbffv9Q8PRJZr9E1MAR50LgyuEky+6lOy33sJYUcb15jKmfFBKnq2ae3uMYXXOGnbaduHQTm699SaioiKpqqzCoMwota8H2d/fwuzpE9jxhZsBYyPoOTCJzdm7eDxtHKedXcflhlT+7ErBuWVfxYp6Q8txuEV5Bcx7P53fX/UUl0+P5dI55/7q6xfHjxNlzK7WOudYXEeSXSGEEF2K0Wjk8X/eB0DF6q1k/f5dahpdGNya/CSz77h9RbOMRNLzkNfc14N6cCtWrGDLli0t2j7//HNSU1MJCwvjidve5cpTKhgxOQFjs0kf3I0evv48k36Zr2GdehkAiUNGQNYynpwcxTWLa3k5/xdmRYxgEU522vZgNBhQSnH77bdQuGUHVdpO5rYCeqVEMzCmH7lfxOAXaOGKRy8CYEbcCEaPt2Mye3tyA40mdjkUkYZGfgkJY0VoFABhLgcT80tJe/NNAg1R3P3Ktb/6uoXo6pRS44CXgIGABTAC9VrrkLacL8muEEKILivi5IH0fXQ2u1/+nMnLy6lze/il0sLWaiMacGsn/6v6mFi/kwg2RALg52fita/uJaV/LEoplFIYDL8+ak9rTXR0NDfddBPgnZDi559/5j//+Q+33XYbPy3PZuNKN6+FWek9IhKPS2MwKX74ag8ffLGFN283s7eqb3hMNPPWhzMzsYKXz+jBk99V8l7VToLNCfQKN/O/975l8iWTiE6IIvKUMeSt8GCtd8JmyN/sHZ+oAxtpsFRRWlJBrDWQ8KiWD57VpgbymTuOWpOZILeLaeXFJDY0cNPyjRgwkRLQ/1j+pxBdhLfObmdH0eH+AcwG5gNpwJVAm6dElGRXCCFElxZ16lCiTh1KTXUtCTEDMHs0MeYe2D11lLgK6R3UlxS/MOpcmn5xVua8fQepgxOP6F7NE+Nzzz2XzZs3U11dzZ/+9CcsAQYa6w1cdWcRiXE76ZkIWTsUZZV+9ExSB/ywfNs/XqG0oICiJ//A9TPCuPiBR0js06vFMcuXL2flypUkTFQEJBgp+NZEnaOadfXLaCio4+tpHxOmk/ld7AjcbjCZvJUevrEHs0oFgwmSs4tJa6hnd42dG375hTVle0iyDmJz3XdH9B4I0RVprbcrpYxaazfwplJq9a+e1ESSXSGEEMeFkNBg6hrzeeD2x/h03mdEmII4e/yF/HFwX4wejd8p4wiYMgllPrKPNq01Hrebh297ltSBPbn21ou58cYbef7559FaM/naKJa8WIpSivyiAPJ9lc00150eQg7RGJtqju19cjw6IYE7XvlnK/dy8sYbL3DbbY8REhLM1VdfRVhvf5L6h/GvNz6nurICj8eDx+0iOMDJt5U2LtxmJSbVyYt13hIV/srN1QElLHDmMHzBN0yKOR2HK4XLBo/mvU0fHNF7II4PXWx2s45gU0pZgPVKqb8BhUBgW09Wev/pWTpRWlqa/vnnnzs7DCGEECcQ7Xajv/+Ev/33RypdfmS814jSilpdyaz/G095vfcZmXFjx/HY5Z+Bp+WQiIT4bN67dwjF427mb0++QewAK2/707cAACAASURBVFsz8nAUmHjx3d+T1DseAE9NNbqsFBUdxdY9Sxkx7Epcbm/N3YSEBH73u2uora1j7r8XYLc34na78ehqzFjpE3YOw2PCGX5pJI0GIwkGB1cElLI0q4LL3vwcu8vFA/f8H3955rGOffO6IKXUWq11WmfH0V76BcXrl4Zc0yH3OuuHP3eJ91Ip1RMoAcx4J5MIBV7RWm9vy/nSsyuEEOKEpr95jxWfrKCwOgG/MIUREygIJoIFT67ljPvj8Xg8TJ02lSklU7jz8qf5aXkmQQEeLprqx7iJl8AllzFr2G9xWO1cOGA8bjys2rSWU8f+hvXbPsP86fu4fv4RzCZwOlmXX4qn2cDLgoICdu3aTe/evRgytDc//bgVpRxojxsH9fiH1TLgsv40Apu+yGWXo4x5ZSa+3fMFHtycMfF8SXRPIF2nm7JjNKvKYAeeONzzJdkVQghxwtIN9ZD1A298pQgf03KfQRnwI4CygnpCoy1kZGQwfPhwXv7woQOus/j9r8ktLyQ63vtwuAI8aOqddn559ClGUQYup3cBpkWGcNew/jy7YavvGh999F/uu28Op00ez9qfs/C4PYBm4sSTOeMMb+faV/O3UZ7fSKO7npQhRlw59a0W2xeiO1FK7aKVHF9r3bst50uyK4QQ4sRVVwkGEzX1mohWkkZzsCYo3PtRmZmZyfDhw1u9zOpv1qG19k0TvDcBdWk3gxoKwAh//SmTf27Nwu5ycXJMDE+ePKxFstvQ0MDq1WuYNGkCMy44nf9+vJBJkyYyZcpkAF5//Q3y8wsAA/2SB/O/79ZKonsC0vqEHLPbfCiFHzATiGjryZLsCiGEOHGFRIHHTWpSA048NJ9Y1D8SBl0egFKKgQMHcsEFFxz0Mqn9ezI5KYGtzlIA3J4GegdYKWlwYjFopn+2km9LCnzHf1WYzzcLCgk2mKn17JscYvn/VjImbQwDBvTi4gtmMHBoCps2bWbhws9pbPROjGFQJn5Y/7UkuuKEobUu36/peaXUKqBN81/LdMFCCCFOWMriB8NPZ875VnTTr6SB8TDqVjODr7CglCI+Pp7p06eTnr6Qt99+h8LCwgOu8/376Xy2/WfqXN6Z1zzaw8aKHPyNbpbllrdIdPdyag8pAS0nu9C4Wfz5Sm+CPTSFzHUFfPrJEl+iazYE8t6/3yAsPPRYvxVCdFlKqVHNljSl1E1AcFvPl55dIYQQJzR18oXEB4Ux1LmMAswMnGXx7ausrOLZZ1/gllvuwGq1YjAYcDqdPP747wkPi+ONuR8SFhDCzp1ZaDwtrqvxsKu2iBc2NBz03jkNVfu1aOISvIlsxoYcfvwhm3+++m8uvuRMLBYzAYEBx+x1i+OX59cP6W7+3mzdBewGZrX15HZPdpVSZwEv4J3a7d9a67+09z2FEEKItlJKoYafTsGnK1u0v/TSK5SXV/i2bTabb/3hhx8l2K83JmMAsUY35Y5awFurF/BNMKEw0Mi+5Hl/AUYLNS6Hb/u0007l5JPTyNycz/crs7j62ou49vpLZMiCOKFprU87mvPbdRiDUsoIvAycDQwCLlNKDWrPewohhBDHwu2338Idd9za6j4/PwuNrkqUMlCj6wm3tqxvr33/epgwqBfGgySrsc3OO/XUSZx66iS2Z2Vz55xbyMj8nKf+eo8kuuIAWqsOWboKpdSdSqkQ5fVvpdQ6pdSZbT2/vXt2xwLbtdY7AZRSHwAzgC3tfF8hhBDikLTWbN++nYYG7zCDhIQECgpajq2NiAjn8cf/76DXeOnvi2jQDZw/ejSFQTYyMrb59ikMPPTI9QA8euowX/tf//oMdnsDg0KTiQgcxkUx/tjiKhl32jjWr9/A2u+/45333z2WL1WI4921WusXlFLTgBjgGuBNYGlbTm7vZDcR2NNsOw84qfkBSqkbgBsAkpOT2zkcIYQQwqusrIz333//qK5x+z3Teenvi4idlEwsMGLkAACGD+/P8OH9Wz3ngQfu5bW/f06Fx0BxbR59Y+I58/STqMyrJD39c3rGRx1VTKJ705yQY3b3djOfA7yptd6gDuMnj/auxtBaIC2KAmutX9Nap2mt06Kjo9s5HCGEEMLL5XIBcM4553DSSfv6YZRSTTVzW9aw11qze3cOzz33PBvWfu1rv/2e6Ye8T4K5kYuCKjA3S1FuuOdcbrrnbHr0jOKMc0dQUlzF959n4/F4uPf+h4/FyxOiO1mrlFqKN9ldopQK5jBy/vZOdvOAHs22k4AD668IIYQQnSQ4OJizzjqLyMhIAC688EIeffRRbLYGcjPWMGJ4LOBNgnv0SODd9x7igw8eIlFVHHCtpPXGFtthP2h+WvIjg/ydPBBRdMDxF1wyDpPZyMJPfmRnXSk9ImK45SDjhIXYy6M7ZulCrgMeBMZorW2ABe9QhjZp72T3J6CvUqqXUsoCzAbS2/meQgghxGG7/PLLUUqRnp6O1pq//e0vnHvaMM49O5Xrrh8FgNFo5rTTRmH0szJ+fApP//ltfvpxE888/TKPP/4kznA3AP67NYkLNIH5sGFTKTPn/UCpxcIjsSW8+vfFLe770furaLA7MaC48445Hf66hejqtNYeYBfQTyl1CjAYCGvr+e2a7GqtXcBtwBJgK/CR1npze95TCCGEOBLh4eGcdNJJuFwuPvnkEwCq6jR4PMTH76tf/8zT36GdLnbuKKS+MZcvF6cT6AgAFE999SYARrPCYFaYA41srNnOZ99tI/m2jxnx4A8MDE+gvLQGgPnvr6K4sAoDitSAGO557N4Of93ieKPQHbR0FUqp64EVePPJJ5r+fbyt57f7DGpa68Va635a6z5a66fa+35CCCHEkZo6dSp+fn5s2bKF8vJyZt38CC5bA9rj4f4HJviOW7J0B/f9ZR6jgk7h3PC7qXXXARpP02+/q8s28XLhfNb1yyQo0IRHNxIcHMjMOecx+doRhEUEsXD+j5QW1mBWRsJNgWCs7KRXLUSXdycwBshpqrk7Eiht68kyXbAQQogTWmFhIdu3b2f79u3s3LmTkSNHAvDRRx8REBTM8uW1VG3Px2xUGI3e3q6f1hYyKOkUkszjaPQ4sHu8k0rU1Xn/HTCwH9X+TgzKxvWzpjKwfyq/u2Gm755rlqylH+GcHN2byUl9OPeSUXyXv6qDX7k4HmlOyDG7DVrrBgCllFVrnQm0Xu6kFTJdsBBCiBOS1WoFYMWKFa3uLykpYfv27RhqnZx11gvUNzqwq3quufEalFIsXP0JocZ40gIvQKHQgNPpBMBisfDb3/7Gd61LLxva4to79mzg1fkv0mfChe3z4oToXvKUUmHAp8BXSqlKDqPggSS7QgghTkgRERHccsstvkklmispKWHRokX88e6H+Wjp9wAHlCK75NIL+OiDBWxvWEOiZRD5jq2YTGYANm7MYOPGTdxyy01cPMQEjTVk55aSVVDD0Hgzj350J2rstPZ/kaJb6krjaTuC1nrvt8LHlVJfA6HAl209X5JdIYQQJ6yD1Xf38/MDIGNPsa9tbw37LZt3MGhwHwYM6I8HN3scGUwJvQmnbsBOCQB5eQVMn34ud911J7jssG0xPUINnD4kBoLjod+5KHNAO786IboHpdQ4YLPWulZr/W1Tnd2RwA9tOV+SXSGEEMc1m81Geno6jY2NvrbBgweTlpZ2yPMcDgeffPJJqz27DofjoOd98cUKBg3u49vu0zeFgZP8GchMMHpLjz399F845ZRTvAeYA2DwJWiPG7QHZTQfzssT4gBdbDxtR3gVGNVsu76VtoOSB9SEEEIc10pKSsjKysJms+HxeCgsLGTjxo0HHOdyuXjyyWdJShxGaEgfrrj8RjIzM6mrq8Pj8bRYysrKAOiZknDAdRoa9iXCgwcPZMzwMQQlKExGRXhYECkpKQwcOPCA85TBKImuEEdG6WbjiJrq7ra5w1Z6doUQQnQLZ599NikpKbz99tu+qYCbu/66OXz66WLsdm9P7g8/rGPwkBSGDx/JxIkntzj2s88+Y/369VRX1bZyp33datOmnUla2miKioqY8weZEEKIdrJTKXUH3t5cgFuAnW09WZJdIYQQ3Y7D4WDz5s2EhXknWSopKeOXX9bTMyXBl8BGRIYCsPjzrw5Idi0WCwCJgf4HXDvQbMTj8WAwGAgJCWb37t0YDPJDqegYuuuVBesINwEvAv+H99vm/4Ab2nqyJLtCCCGOa3t/3ayrqwPAbDZTXFzMxx9/3OK4iy4+o9XzM7O2H9BWUuJ90Oz3z/2JWf9bzuN//ReNThfXXTSVm/76JM8884zvWIfDIcmuEO1Ia10CzD7S8yXZFUIIcVyz2WwA/Pe//yUrK4t+/fqxbds2AIxGI7NmzaKwsJh33nmPHj3ifedt2pTNpoxspp45pcX1qqur2b17N0FBQfTv35/+/fsz45abffsrK70znSUmJnLKKadQWlra6hhdIdrLiVZ67GjJV1EhhBDHtcDAQN/6pk2bWLRokW/74Ycfpl+/fpx66iTKSm28+85C374tm3dQXFzBHXf8zte2e/du5s6dC8CZZ555yPuOGTOGfv36MWHCBCIiIo7VyxFCHGPSsyuEEKJLWrt2LRkZGQe019bWEhwczNChQxk9erSvPTk5mdzcXN+2wWBg/vz5vvq4l84+m02bUnz7J592EiNGDCU+PsbX9t///pe6ujqio6MZOnTfrGfbt29n3bp1wKHLkgnREU7AMbtHRXp2hRBCdEkZGRkUFRW1aMvJyaGiooKcnBxfIhwZGUlSUhJ2u73FJBFKKcrKynxLZWUliYlxmEwmjEYjqak9KSjI48svv/RVb5gwYQJw4GxpGzZsICsri7KyMmpqaoiPjyc+Ph4hRPtTSv1fs3Xr4Z4vPbtCCCG6rLi4OK6++moAFixY0OoxwcHBXHfddYd97d27d/PWW2+xadMmtm3bxo033si4cePYuHEjhYWFrFq1iokTJ/qODwsL45Zbbjmi1yHEsaIBT2cH0UGUUvcDK4FLgCebmr+njZNJ7CXJrhBCiC5twYIFbNu2zTdD2tChQ6mpqTnq65pM3o9Ag8GAw+HgpZde4qSTTuKSSy7hlVdeYfny5QwdOpTQ0NCjvpcQ4ohkATOB3kqplcBWIFIp1V9rndXWi8gwBiGEEF1WUVERGRkZLaYCrqmpOWB4w5GwWr2/hno8+/rJfvjhB1566SXcbjda6wPKlwnRFWitOmTpAiqBh4HtwGS8tXYBHlRKrW7rRaRnVwghRJfU/AGxvQ+l7RUXF9di/5GIiopi9uzZNDR4Z1RbuHAhbrcbo9GI2+0mMDCQtLS0o7qHEOKonAU8BvQBngU2APVa62sO5yKS7AohhOiSRo8e3aLawrGmlKJ///6+7aysLMrLy7n55psPcZYQnetEGrOrtX4YQCm1AXgXGAlEK6VWAZVa6/Pach1JdoUQQogmNTU1LFy48ID2/Px8XwkzIUSHW6K1/gn4SSl1s9Z6olIqqq0nS7IrhBBCAD169GDPnj2+2df2169fvw6OSIjWdZU6u0qpN4DpQInWekhTWwTwIZAC7AZmaa0rWzn3LOAFwAj8W2v9l4PdR2t9f7PNq5vaytoapyS7QgghBDB+/HjGjx/f2WEIcTz5D/AP4O1mbQ8C/9Na/0Up9WDT9gPNT1JKGYGXgalAHt4e23St9ZZfu6HWesPhBinVGIQQQgghjiO6g5ZfjUPrFUDFfs0zgLea1t8CLmjl1LHAdq31Tq21A/ig6bx2IcmuEEIIIYRoTZRS6udmyw1tOCdWa10I0PRvTCvHJAJ7mm3nNbW1CxnGIIQQQgghWlOmtW6P+nutPe3ZbiORJdkVQgghhDhOaMDTNSZ8OJhipVS81rpQKRUPlLRyTB7Qo9l2ElDQXgFJsiuEEKLLczgcLFq0iPz8fAYMGAB4qyP07NmzkyMTQuwnHbgK+EvTv5+1csxPQF+lVC8gH5gN/Ka9ApIxu0IIIbq8PXv2kJGRQUVFBatXr2b16tWsWLGis8MSolN0lQfUlFLzgO+B/kqpPKXUdXiT3KlKqWy81Rb+0nRsglJqMYDW2gXcBiwBtgIfaa03H/k7cmjSsyuEEKLL0/rAj97W2oQQHUdrfdlBdk1p5dgC4Jxm24uBxe0UWguS7AohhDgu2e32zg5BiI6nu86kEscLSXaFEEJ0SWvXrmX58uXYbDZf27hx41izZg0ARUVFPPHEEwBYLBZuvPFGIiIiOiVWIUTXJcmuEEKILikjI8OX6KamppKTk+NLdAFOPfVUAKqqqtiwYQM1NTWS7IpuTwOezg7iOCPJrhBCiC4vLi6OgoICnE4nEyZMYNiwYcTEeGvV7969mw0bDnsGUSHECUKSXSGEEF3C2rVrycjI8G3n5OT41tevX+/r5f3uu+8444wzWj1/3bp1hIaGYrVafe0Wi4VRo0ZhMslHnuge5NnMwyP/yxdCCNElZGRkUFRURFxcXItEF2D06NEkJSXx3nvvAVBTU0NISAgAwcHBmEwmNm3adNBrR0VF0bt37/YLXgjRZUmdXSGEEF1GXFwcV199dYu2Bx98kMmTJ5OamorZbAbgnXfe8e2PjIzkwQcf5OGHHyY4ONjXfv/993PVVVcB4PHIKEfRXSg8HbR0F5LsCiGE6DJycnJ8FRYAHnvssRZDEu6//34A3G53i/OMRiNms5m7776byMhIAJ555plD9vYKIU4MkuwKIYToEhwOx68es27dOgDflMGtSU1NBby9uWvXrgXA6XQegwiF6Bq07pilu5Axu0IIIbqE+Ph4CgsLAbj66qvp2bPnAcds2bIF8NbbPZiSkhKCgoKIi4vDYDBQU1NDnz592idoIUSXJ8muEEKILmHvcIXY2NhWE13w1tQFaGxsPOS1wsPDufzyy49tgEJ0AVJn9/BJsiuEEKLTFBUVkZ+fD0BxcfGvHh8SEkJ1dTVFRUVER0e3d3hCiG5Akl0hhBCdJj093Td0Ya/4+PhfPS80NLS9QhJCdDPygJoQQohO43a7SU1NZc6cOb629evXt3psXl4ee/bsITg4mOTk5I4KUYgux6M7ZukupGdXCCFEp7Hb7ZSUlLBs2TJfW0BAQItjGhoaWLBgAdnZ2UDben6FEGIvSXaFEEfE7Xbz5JNPAt5xlEajEfDOZnXllVf6toU4FKW8heubTxN82223+dazs7P54IMPWkwKYbFYWlyjpqaGefPm+R5aq62tlYRYdGvdqNO1Q8gwBiHEEWleE7WmpoakpCT8/f3Jzc3FZrN1YmTieDJ27FjA+yXJz88P2FdxobCwkPfffx+Px8OAAQO45557GD16NOedd16La1RUVFBUVER4eDhJSUkMHDjwkKXJhBAnFunZFUIckb2JCXhnuQL4+eefKSgo6KyQxHFowoQJTJgwAYDMzEw+/PBDNm7cyFtvveXrqY2OjubSSy8FYPr06Qe91qRJk0hJSWn3mIXoTJruNZ62I0iyK4Q4Int/fgYoLy/3TdEKsG3bNvz9/QFISUk5YAymEK0pLS0FYM2aNb62Pn36cMUVV3RWSEKIbkCGMQghjtisWbMAmDt3LoAvwV20aBHz589n/vz5fPnll50Wnzi+1NfX+9aVUjz66KNMnDgRl8vViVEJ0cV00FTBMl2wEEIAAwcOBLxP1D/xxBOtHlNeXt6RIYnjWEpKCj/88AMAWmv++Mc/+vZZrVZuueUWQkJCOis8IcRxSnp2hRBHpU+fPofcHxER0UGRiO5CKYXBYMDPzw+Tydsn09jYyHPPPSdfnoTAO11wRyzdhfTsCiGOyowZM3j22WcBePTRR/F4PL4E5bnnnvOtC9FWkZGRLcqL2e12KisrAZg3bx5Wq7XF8XsfZBNCiNbIp5AQ4qgEBwcTFBREXV0dGRkbcNdUYbHYcDb6o7vToC/R7hITExk0aBBOp7NFe2BgIP7+/tjt9lZ/KQgMDCQuLo7Y2NiOClWITiPVGA6fJLtCiKN288038/TTT/Ppp+k89PAkDAZv9YWvf26kod7eydGJ40VwcDAzZ87s7DCEEN2MjNkVQhy1F194kxEjYgDYsb0CpZSvNJmmojNDE0KIbkd30NJdSLIrhDgqkyZczNN/egOT2ftDUXl5s55cpfALkD8zQgghOo8MYxBCHLFNGZls2ZiDUgaqq70PCWmt2bmtnCXp22iQ+qhCCHHMyZjdwyPJrhDiiP3tr6+iFNx859lkb/OWhHrzhV/YvKwRrTycfl0Mi+btIN6ygpPOOaWToxVCCHEikt8XhRBHLCwshNvvOQ+TyehtaPCweVkDBmXEiNnb5jFy829e77wghRBCnNAk2RVCHLG//O0h33p9rYOqGicGte8HI/9gI1E9LZgJ5ptPvu6MEIUQolvxPjymOmTpLiTZFUIcsYCAANwu7+CxwGALRpMBZWx5jL3GjUaTu7OoEyIUQghxopNkVwhxVB5+5EHf+pqlOQSEK4KjjQRHG2ms9+C0a4KjDUy84CSqq6s7MVIhhOgePLpjlu5CHlATQhwVPz8/UlNT2b59O1Nnpx6wPzbVSmxqDO+8+w5KKe69914CAgI6IVIhhBAnoqNKdpVSM4HHgYHAWK31z832PQRcB7iBO7TWS47mXkKIrmvWrFns3LkTrTXbNuzgrVcWYq+HkVNjsPjtG9egtcbhcEiyK4QQR6E79bp2hKPt2d0EXAT8q3mjUmoQMBsYDCQAy5RS/bTW7qO8nxCiCzKbzfTv3x+AAQMGcP6l5wLw3HPPERERQU1NDRUV3pnU3G75MyCEEKLjHFWyq7XeCvimBW1mBvCB1roR2KWU2g6MBb4/mvsJIbqunJwcli5dikGZKC2twGq1YLPb6N27N1dddRXr1q1j4cKFGI3GX7+YEEKIVnW3qXw7QnuN2U0E1jTbzmtqO4BS6gbgBoDk5OR2CkcI0d6Ki4spKCgAoKqyHu93YIVqqrdrMMjzsEIIITrerya7SqllQFwrux7RWn92sNNaaWv1i4jW+jXgNYC0tDT5siLEcWr3zjLfevqCH6iusgGw9PONTD/vrM4KSwghupduVimhI/xqsqu1PuMIrpsH9Gi2nQQUHMF1hBDHiXff/oySkkLOPm80w0aksPKbLQDU1taT/o9FlNWUdHKEQgghTkTt9btiOjBbKWVVSvUC+gI/ttO9hBBdgNvlZtfOYkqKqxgxujexcWEkRUQxu9e5fPnCBjat8H7ffeGqudRX1XZytEIIcfzSHfR/3cVRJbtKqQuVUnnAeOBzpdQSAK31ZuAjYAvwJXCrVGIQonu79DfnYrVY+GT+Gux2B+ecn8aFg0+jPK+RRpsHt8P7h7NwRx3vPvRRJ0crhBDiRHFUya7W+hOtdZLW2qq1jtVaT2u27ymtdR+tdX+t9RdHH6oQoiu77PLzGDN2GGaTmbpaO0HBfuRl2nE7W/YOuB2Q8a1MHSyEEEdCIzOoHS55PFoIcUyYzSbmf/oS/3n3b0RHJQAQNLD1Y/dPgIUQQoj2IsmuEOKYMRgMnDZlHI894Z0SOCTFeEBtFmWAPqPCOidAIYToBnQHLd2FJLtCiGOuoaEBm81G8sAg/IOMmP32/akJDDUx69FphzhbCCGEOHbaa1IJIcQJbM+ePQD0GRzOlM/68M2b+RTV1dKIjTvfHkJSP/9OjlAIIcSJQpJdIcQxl5mZCcC33+7mW3ZDIN4FCI2VRFcIIY5Gd3p4rCNIsiuEOKa01gQENPi2ExKCGTQoGoCAQAshIX4oojorPCGEECcYSXaFEMdYBZo635bN5mTc+L0TKioUfVDKr3NCE0KIbkBLz+5hkWRXCHFMeXQhlRV233ZgkKVpTaEYgMEQ2zmBCSGEOCFJsiuEOCZ2byog/cUVTLkqiJ07KwkJsaKBqKiApiMMKGXuzBCFEOK4pwFPZwdxnJFkVwhx1J67bx5L31xHjbuRH3P86HtyICOGJrA5q3i/I0M7JT4hhBAnLqmzK4Q4Kiv+t56Fc3+k2t1A3EALfU/2ll149o4MPO69A8sMGNRAlDJ2XqBCCNFNyHTBh0d6doUQR6yitIo7r/wrVh1Bj8H+DJkaDMDm/9VRV+GittJBWaEDgzoJpaydHK0QQogTkfTsCiGOyLo1W0nrdyVOu2LKjVG+RDdvUwN7MhrwaI3L4SH/uzLu6v0Ab/z9g06OWAghugHtrcbQEUt3IT27Qogj8uDsJ7g1MRVLWhAV/t7vzesWVFOS6wS836QNgEEZiLGEkfnKWuw3z8A/QCaVEEII0XGkZ1cIcdjqs/O4OqIXIf0CqehlxL/Kw8B0B6cqM8nD/UgZ6UfKKH+MFgV4E94Ao5V7Z/2xkyMXQojj295qDB2x/BqlVH+l1PpmS41S6q79jpmslKpudszvj+oNOALSsyuEOGzbnv8UZVYUDPf+CYnI1ZgNiqBkC4NGtPyzour3rVfmV3ZkmEIIIdqR1joLGAGgvE8g5wOftHLoSq319I6MrTlJdoUQh60sr5xt53gfOAso9xCZ6+0DcNM0yCvdhbnR++dFuZp6dzFw+mWTOj5YIYToZrroeNopwA6tdU5nB7I/GcYghDhsmUP3fU9O/d7tW1fevJa6Bjsuh9uX6Do8TjLtBVx//286NE4hhBBHJUop9XOz5YZDHDsbmHeQfeOVUhuUUl8opQa3Q5yHJD27QojDUlVVRYXZ5d3QmookRf5QI/7VmmCnN7md/veL+MeNr5NsjMChXZQGN/DO5lc7MWohhOg+OnAGtTKtddqvHaSUsgDnAw+1snsd0FNrXaeUOgf4FOh7bMM8NEl2hRCHZfXq1fs2lCKvaYyuLUJha2oeNWEo83Pe7PjghBBCdIazgXVa6/2nzURrXdNsfbFS6hWlVJTWuqyjgpNhDEKIw/LTTz8B0Lt3b8xmMzExMZx//vmdHJUQQohOdBkHGcKglIpTyjvITSk1Fm/uWd6BsUnPrhCijyDxmQAAIABJREFU7ZxOp289LS2N3/72t75tq9XK/PnzAfB4OvBHNiGEOIFoNLoLPaGmlAoApgI3Nmu7CUBr/U/gEuBmpZQLsAOzdQe/AEl2hRBttmHDBgCioqIYOHBgi32DBg1i2rRpLFmyBINBfjQSQogTgdbaBkTu1/bPZuv/AP7R0XE1J8muEKLNdu/eDcDs2bNb3W8yyZ8UIYRob56u07F7XJDuFyFEm1VWeieFcLlcnRyJEEII0TbSDSOEaDObzVtvITo62teWnp7Onj17ALDb7Z0SlxBCnEikY/fwSLIrhGizqqoqgBZjcrOysrBarSQkJAAQFBREUFBQp8QnhBBC7E+SXSFEm5SXeyvF9OrV64B9ffr04dxzz+3okIQQ4oSjkTG7h0uSXSFEm3zwwQcADHbm45j7CKpPf4xjZ7T5fLfbza5du6gqK+f5x/9BVl4uJoORMUMGcetjt7d6Tn19PTabjR49etCzZ89j8jpaU1tbS0FBQYu2iooKli5dCsAdd9xBeHh4u92/q3K5XOzatYv6+nqsVusBVTYCAwNJSkrqpOiEEKJtJNkVQvwqrTVlZd7JbobszgSt0XsKcP3wPaiUNl0jMzOTjz/+GIC+41PpS6pv395E+lBuu+02IiMjf/W4I/HFF1+wdevWg+5/8cUXeeyxx9rl3l1ZRkYG6enphzzmvvvuIyAgoIMiEkKgpWf3cEmyK4T4VRvWr/etq721wF1usNnRlsY2XWPvhBTz3p9PTW31fnsN/PXh/+OMi6e3aH3ttdd86+358JvT6SQ6OpoLL7zQ11ZWVsaCBQva7Z7Hg+aTiABcf/31vt7drVu3snLlSqnMIYTo8iTZFUL8qj3ZWwC4xFXYcofbA273YV2ruKSIqqqWya4BE4s+/h87y71DCQwGwwGzsLV3DV+LxUJ8fLxvOz4+nqFDh/Lhhx/6Sq6dqPr3709WVhYLFy7kpptuAjhg2IcQouNoqcdwWCTZFUL8qso6O5HaQV9ta2WvYuvWrRQVFaG1Jj8/H+CAsZz19fW+4/f3uxuvIT4+1rfdPNENCgqirq6OTz/9FLPZDMCoUaMYOXLk0b2o/ZSUlDB37lwAzGYzM2bMIDQ0FPA+nDd37lzy8vKAjhvDq7VmwYIFvioY+zMYDEydOvWoxs3m5+ezdOnSVqd4rqurA+C8884jKyuL4uLig15n+fLl7Nq1q033DAgI4JJLLvH99xRCiPYkk0oIIQ6purqawtJyIv2NYNgvUTWbGN0vidjYWCwWC6Wlpb5dFoulxRIeHo6fNlNXc2DC3DzRbe6N57/mpH796d+/P4GBgVgsFkpKSsjMzDymr3Ho0KH06NEDi8WC1ppdu3ZRVFQEwJAhQ0hOTsZisfiOf/HFF4/p/Q/G4XCwadMmbDbbAe+n2WwmNze3zQnmweTk5JCbm4vJZKK0tJS8vDzfsjfJfuaZZ3zHH2zYwsaNG6mqqjogzv0Xh8PBtm3bDprACyEObW81ho5Yugvp2RVCHNSOHTt49913ARg38yJY/jaUV3mTXrcHxo7ltGnX+sZxLl++nJUrV3LqqacyefLkFteqq6vjyy+/5IbfXM3XP69kW+Z2NPD7xx9ocdxLf1/UbEsx8/K/sKt0KX5W70NQzcfxHivDhg1j2LBhgPfn+ddff923b/DgwQwePBiAJ554AoCJEyce8xgOJS0tjfHjx7doc7lcPPXUU8fsHvn5+S3G6Pr5+REYGIjdbqehocHX82u32wkODm71GqmpqcyYcegKHZs3b/Y9qCiEEB1Bkl0hxEH9P3v3HR5VmTZ+/HumpEwaJCEFQkxIIISW0JEiYBABFxCxIAgqisKiu4rLu6KreZGXn6uuBUFlUVbRFVlqAOmwgvQaQmghhRASkhDSk0kymZnz+2OcQyaTDqH5fK6LyzNnnjnzTMKy9zznfu573759gCVnM7hTJHSKxJx5Hrn4GpJ/R1Ru3jbjrTmv1lQGK4PBwFdffYVer8cn1IenQsdjNpoxFta3uU3GSCUzxs3g283LlLN6vZ5Lly5RXl6Oo6MjkmSfGlETHx8fnJ2dGzQ2JycHJycnm3Njx45l/fr1Nrm9tTEYDGRmZtY7rjayLNttyjMajVy5cgVZljE1Mle6qoKCAgoLC5FlmbS0NMCyGc3Ly4s+ffrg4+Nj9zPdtGkTOTk5XL58GRcXF44fP97k9wfLlwprR76aGAwGTCYTQUFBdr8HQfi9k++hVddbQQS7giDUysfHh9TUVIYPH66cU/l3hFpiPWsA5OPjQ0ZGBtu2bcPR0ZGkpCTAEgwHBgaSnZ1NamoqDl62gee+PWdquKrM6YSryiMHBwcuXbrEd9991+jP0759eyZOnFjnGGu6wq5du+odU5edO3dy9OjRxk2wnvfbv38/u3fvbvRcqvv6669rDDRzc3PZsmVLna9dtWqVzWNr3q3JZGpQAG6db0xMTIPm2rp1a6ZNm9agsYIgCDURwa4gCLXy9ras3KrV6gaNt9bivXjxIgcPHkT+bflBpVLRvXt3/vCH66XFzpw5w7Fjx3BzcyM+Pt7y+qvFNVxVIjz0+gry+PHjycnJ4cqVK+zatYuWLVvaXLc227dvp6Ki/jJp3t7eTJs2jfLy8hqf12q1DdoQZjAYcHFx4bHHHqt3bE327t1LamoqkiQRGRmpXFOtVisBu0qlatLmtIqKCjp37kxSUpLyM5kwYUKdG8bMZjMlJSW4u7sDcPnyZUJDQ5WVclmWiY+PJz4+HkdHR958880arxMSEsLUqVPtyppVFxMTQ3FxMUVFRY3+fIIgCFWJYFcQhFpZbx8XFxcrlQlq89577ynBrfX2vUqlom3btkyZMsWu+5Y1F9aaBwuQkVa9xJeEBi1LNvxTOePm5oabmxs+Pj7s2rWLFi1a0K5du3o/i7Ozc40VB2rSunXrBo2rj1arbdDcqtuxYwepqakATJ8+3ebLhiRJTbpmdS1atLB5HBwc3KhV4upzuF5twxJML1iwgDFjxqBWqwkICFB+/9a/E1ZGo5FTp05x5MgR+vTpQ48ePQDLxsCqX5gEQbjOLEqPNYoIdgVBqJHRaFSCVmsJqtps2bJFCUp8fHwoKysjJCSk3s1K1oAOLB3SfM0a5n26jQrKAAmdSseP385SNqdVf0+gUd27rl69yvLlywHLKumlS5dQqVSEhIQ0+BrV6fV6MjIyuO+++2yCxaysrAaviFf19ddfKzVshw0bho+Pj83zRqNR+QwqlYohQ4bg5+dX5zUzMzPZs2ePEuybTCbS09MxGAyNnl9tPDw8MJvNFBdbVucLCgr4/vvvlXkGBQXxyCOP4OnpqbxGr9fz8ccfK/PauHEjFRUV3H///QwfPpyDBw/afX5BEITGEsGuIAg1Sk9P5+DBgwBs3bqVjh071jr29OnTgCXQnTFjRoOun5mZybJl1zedeXl5MX3u20yf+zblFZZ8UidHHcnH03l/3Leknc6mpb8bj/5lCH3GdFZKbg0YMKBB79exY0cqKiqUwN0ayFtvzzeV9TqXLl3Cw8NDCb5dXV2btAJrrWUrSZLdZwsODiY1NZWSkhJkWSYrK4s2bdrUG+wmJiaSkJCAl5cXubm5ynwBpRzYjerc2fI7cXV1JScnB6PRSFhYGGq1mpSUFFJSUli4cCE9evQgMDCQiIgIvv32W8xmM66urgQEBHD+/Hm2b9/OL7/8wpAhQ3BxcWnSFwZBuNeJGx6NI4JdQRBq1KZNG+W4sLB6e19b1o1J1vJd9TGbzTYlxFxdXQEwGkzsXRHLwTWn0DpqCR9wHxsX7MNQZsnvzEysYOlr67mUnkpZWRlarbZBlREA+vbtS9++fZXHVdMnXnrppQZdozY//PADKSkp6PV6nn/++XpTPuoyevRoYmJialyxDg0NJTQ0FGha6TFrbVuVSkVoaCgDBgwgPT2dHTt2NHm+Vg899JByHBcXR0xMDA8//LDSfGPZsmWkpqZy4sQJTpw4gaOjI9euXUOSJGbOnImTkxOJiYnExMSg1+uVOd1IRQtBEAQQwa4gCLWoullp+vTpXL16tcZxiYmJODs7U1FRwc6dOwkNDcXXt+YmEVbz5s1Tjt3c3Jg1axaF+UVMHvIm5zIT0Ko0tDEHcm5/AHK1NFtDWSWHfj6Je18ICgpq8ueravv27TYVJxpr8uTJLF++nMTERBYuXMirr77a5IA3MDAQsOTAGo3Getskl5aWKr8bV1dXJUjW6/WUlJRgNBpJSEgALF9KBg0axJAhQ5QcWmtXuOaQm5urbEQbMWIE27dvJyUlBbBUqwBLOTdrbnj79u2ZPXs2iYmJnDt3jtjYWLy8vJptfoJwN5KBhu0+EKxEsCsIQq1CQ0NJT0/np59+qnd112rx4sW8/vrryq796g4cOGDzeNasWZSVlTN0wDNkXc3BYLB06Cp2LsZf9keN/W1slbtlJflGArWJEycqua8HDx4kJmYTPXv2YerUiQ2u21v9ehs3buTEiRN89tlnzJ49u1H5xFYtW7ZEq9VSWVlJQkKC0tACLKXdrJUrrDnShw8f5vDhw4Alf3n27NkALFq0yK5OL8CDDz7Y6Dk1ljVA//HHH2sdk5ubi0ajoWvXrnbPOTs7c+rUKQBRjUEQhBsmgl1BEGpVVFREeXk55eXl+Pr6MmjQILsxhYWFZGVlYTQaSUlJoaKigs8++4xnnnnGLme16u1pgOjoaABWr9xKTu41JdAFKCurpFRXgrtkv0JaHKvCNdxks9mpujNnzrBo0ZdcunSJ4cMfYurU520CcE9PL5Z+s44XXhwHgK+vJ+npSbz33nvKvBpr9OjRJCUlUVRUxMcff8z48ePp1KlTo69jXQ2tvjocHx9PVlYWfn5+SkDu7e3NkCFDOHPmjE0b5ZoCXYDy8vJmb9IQFhbGhAkTamwtfOrUKS5cuADAY489ZlelA2D9+vVKakz1qhGCICCqlDSSCHYFQahV1dQFBwcHm1XGmhw5ckSpzPDDDz/g6elJSEgI6enpdrmXnTt3VtrGxsef5MGHI6g02AZHLhoTLSQZ5OsrrSq1hF9IS4rka2RkZLBmzRrlufLyciRJ4tq1a+zff4C4uHgSEi6wZ89eFixYyPHjR5QA+Z///J7CwiJSUzMICmpj875z586lY8eOPPXUU434aVm8/vrrSkrDqlWrmPj0M8h5GpzdnQgIt+9MVp31y4B101Z1fn5+PPfccwBKY43OnTsrG9uqCwgI4Pnnn1dSRz777LNaa+DeLBqNhrCwsBqfy87OVoLd8PDwGsfk5+fj5OSEp6dnnbV/BUEQGkIEu4IgNMjly5frHWNdpfP09CQvL0/5U5MzZ653S3Nx09LOre6KAtfJFMnXlEfWShDVdeoUTnh4R376aSUXLiRy5UomH330Me+/b9nUtWf3AcrLK1j+4yZl7uMeG0ZYWBAA58+fZ+7cuXh4ePDnP78KlAFaJMmxztldTc9ny8cXqfQoIXywK8t/+jf5sVAer6alvzuP/X0gOUVZZGRkkJOTg8lkQqPRYDKZ0Ol0SumuCRMm1Hj9rKwsJci1rvIqPxlZZt26dUqlBYChQ4eiUql49tlnWbZsWb3NHJqbNWcXYN26dXbPFxcXK93Y8vPzcXFxuZXTE4Q7nwxmsbDbKCLYFQShVh07diQvL4+CggKl2H9d/P398fLywmQy4eHhYZfn6+bmxqRJk+xedzntEutiNuLgoCEzI5+SkjLSLuYgY2LJl3+lhV87KkoqcNA5oNZYAmqTyYRKpbJZKf3mm2+QJIklS/5Fz57d6datC08//STffvs9aWmXWbs2Rgl2Q0LuY+/eQ8rtcrPZzJrV29HpnHnt9cnKNQsLC3nvvf9j2EkjUmElrh29CPzjY7ToYl+b12w2M+X+9ykqKUMG/Ds40sJfS8vuQHcTspzP5l0blfGSJKHRaJTSX9ZAF2Dbtm1MnTrV5vrV81v9/PyUcwEBAXh6eiq5rgBRUVFKKom1KsLtXikdNmwYP/30E46OjqSlpdk9L8syzs7OlJWV4ejoeNM2IQqC8Pslgl1BEGql0+k4f/58gztrtWnThldeeUV5XLW8l06nY9asWTW+ztfXlzNnTpB6KRv/Ni2BloR28KddOy86dOtNbm4+ew/9SmZmJrIs1/gHLAGwo6Mj2dnZrF0bg8lkIjKyG1OnPkt6egZarZaFCxfSqlUrpk59mkOHj5Jw/iIqFRgMRhwdHenWLVzJ2f30048pKrLU4N0ZqYFtV/hxxT7y/r0SH++WvPnuDKY8Nw6j0UhSUhLbN/6XzmMccfZwRuMg2QTiZpOMMV/CWCDx8JNDGPhwP+XnajQaKSgoIDs7W0ntuHz5MkuWLKFz584UFRWh0+kYNGgQPXv2rPFn2KFDB9RqNf/+97/RaDTMnDnTJt/166+/BqBPnz4N+l02l6CgIObMmXNb5yAIdzNLNQaxtNsYItgVBKFW1oL+TW064OrqSklJCZ06deKJJ56oc+yUZ18mJ+cc8fGx7N+fBEhcvJjH++9/oKy+ajQa1Go1kiQpq7rWP9bH3bp1IzIygqNHj7F+/UbS0i4zZswjBARY8nKtqRUJCQmMHTsUxg4FLCuK1uB07ty5REZG8uyEPqyN3k5Gm9/+qXw4kEkPB7JrexxtArw4fuIAqWmnkavUR3NrpcZUKVN8zURpnpGCLCOZ5ytwrNDSxsEdZzcHPKf44eDggNls5uuvv0alUild06rKzMy0yXXevXu3smLu5OREmzZtiIqKwsPDg9jYWKWc16RJk2wCXb1eT2lpKY6OjgwZMoTKykrKy8sBS2tfQRCEe5kIdgVBqFVQUBBHjx4FaFInK5VKRWRkZL1tg8FyS9/HpxNRUZ3Yt8+yItytWzfOnj2Lr68vQ4cOJSwsjIsp6SQkpBASEkj7DkE1XmvNmo489NAI0tLSSE5O4e9//wd//vMrDBv2ED/9GIO7hxPOOgc0GjXIoHNxVlaFDQYDRqORkydPcvIk0Mb+n8mo4RGAJUCuqDAQGBiAVqvl8uXLGA0yxgoZV0817q00+IdB+GBXsk9VUnbA0jijXffWfPPNN2RkZNT7cwkODsbT05Pjx48D1xt8lJeXk5ycTHJyss34bt262d36//nnnwFL2oNKpWLhwoVKg4mqP39BEO4OohhD44hgVxCEWnXs2JEXXniB7OzsWnfXNwdJkpBlmXHjxjFunKU0mMFQybOTZrNrx0EcHDQYDEb69ovg+5/+gYuLs83rW7duzenTcRw7dowrVzLp06c3/v7+zJj2Lps3HsNYeb3qg0ajZvjDA/n+p38o5w4dOsTevXuprKyAUiM9juv5Y/whRozuga9/SxLOpePkpCUgsBWGikquXr2K2WxZ3dU6qlBrZQx6MyV5JrwDLakKvt205FxSEzWxL59+8XGDfxbp6ek888wzPPDAA6xevRoPDw+ioqJwd3dn69atnDhxAoCQkBDuv//+GnNcrXm6165ZNvYVFxcTEhKitID28PC47bm8giAIzUUEu4Ig1EqlUhEQEFBjCazmkpaWhizLODraVj348P0l7Np5kPLyCsrLLbfeDx08yd/mfMKnn79tdx1Jkujdu7fNuZ83/GIT6AIYjSa2bdtnk8bQr18/+vXrhyxX8O28jznSFyb3GWrJlTPLhIVf/3m4ujmjVqtp164dvr6+hAaH8f7U/3A63vI5vNxc6fWCpa5tq9EmThXvr/WzP/nkkzbluNatW8epU6fYtm0bI0eOtNuwNmrUKEaNGlXr9aysJeScna9/KfDz86NXr171vlYQhDuLjCxydhtJBLuCINxRNm/eXOP5Zd+uo7zMNr+0osLAyp8288mCtxp4G75x/wchSY7k6RyQSytR600UGQ2YTDK514pxcFDT9r5WgKUJhMFgYNiwYQD8c89fbK5jNpttWiRX17NnT/7whz/YnR89ejSnT5/myJEj3HfffU1qUAEoTSQiIyNJTU3FZDKxf/9+MjMzcXV1RaVSKfnQ1bm7u9O/f/8mva8gCMKdQAS7giA0m6KiIk6ePMnIkSMbXNHhgQceYNWqVXYbp/SlNXcEMxgqlVq19Rn1hyGsX7cTo9GknFOr1Tw0fECdwbJGo+Gtv7/LpvX/Zd57X3Lp0hXatvXjkUfGcOr0QYAay2g1xDvvvFNjFzHr+z7++OOsXLmSVatWMXbsWCIjI23GZGZmsmTJEuWzTJ06ldatW9uMsQa71g1sVlVr3gI2q+kmkwmDwYBKpWLNmi288cZMWrduaC1kQRCEO4cIdgVBaHbvv/8+QIPa8CYmJtZ4fsCgnvyy65Bdm8zuPTo1KNAFmP/BGxw/dpprOfmUlOhxddXh4eHGR5/W31FMkiT+8GgUf3g0yub8wAe68+WXXwKWKg5//etfleAyJyeHNWvW2HQ3i46ORq/XYzQabdoX1yY8PJxHH32UmJgYDh8+TLdu3Zg/f76SI1yVyWRSSozdd999Sqe1sWPH4urqSnFxMYWFhbi5uWEymUhNTVWuo9PpmD17NgA//LCSP736FuGd2vHwwwP4ftlKlv+4jiNHt9G2bRu79xUE4dYSG9QaRwS7giDcMv/85z95+eWX6xxz8uRJVCqVEqhZzf9gFg8PfZ6KCgMVFQa0DhoctA4NClStvL1bcvDYarZu/pVzZ5Np3+E+Hhk9FAeHpm/OatWqFZMmTeLHH38E4IMPPqh1rDW/VqfT1XlNa6k3ayAaFhaGWq0mKyur1nSIsWPHsn79euXxpUuXmDt3LtHR0Tg5OfHII4/YvWbPnj3s3r2b8PBwnnzySeW9/2f2XCoqDMqKc2VlJXp9Oe+/v4Avv/ywzrkLgiDcaUSwKwhCs3F3d6ddu3acPHkSsLS3bQiz2Uzbtm1tzrVvH8SBY6tYumQlscfP0LlLB6ZNf4qAto27ta7Vahg99kFGj32wQeOrryTXJDQ0lLfffpv58+fXOa76hrmarFy5knPnztU7zsvLy6aBB1hycg8cOMCOHTuUc2azudY0ib59+7J7924SEhKUcYsX/5PpM560GSfLMkajkf/u2lvvvARBaH5ig1rjiGBXEIRb6j//+Q9PPfVUveM+/vhj3njjDZtzfn7evP3uH5trarVqyOY3jUZDdHQ0e/fuRZIkgoKCuHr1aoPaLFeVm5sLoLT5rcqaY/vaa6/h4eFR4+v79+9P//79le515eXlta4kOzk54eDggMFg4Pjx4/Tu3ZvS0hIyMrK5kJCKDBQXlVBWVoEkSfj6tmrUZxEEQbgTiGBXEIRm98orr7Bo0SIAzp8/T3Z2Nr6+vjWO7dq1K/Hx8ZSWlrJlyxYiIiKUZgh3g0GDBinHN1KybfLkyXbn9u7dy3//+19+/vlnJk2a1KDrGAyGOtMmIiIiOHr0KDt27KB3795IkoRG48CBAwepNJb8NkqFi86LN/4ysykfRRCEm0gGzCJpt1FEsCsIQrPKysoiPj6ePn36cOTIEQAWL16sPC9JEq+99pqyWWvAgAEkJCRgMBg4cuSI8hq1Ws3o0aOJiIi49R/iDjFo0CD2799PcnJynekJVS1YsKDOjYGjRo3i6NGjVFZWEhMTA4CzsxqTuQydTkfPnt1RqVSo1WoKCrLZsGEDycnJREZG4u7uTs+ePQHLxsK6OsKFh4fX+gVHaJwLFy6QlpambMyUJInIyMhaV/sF4fdOBLuCIDQbb29vUlJS6szVlWWZTz/9lODgYKZMmYKvry9z5szBYDBw+vRpkpOTyc/PJzMzk5iYGMLCwpRqB79H7du35/Tp08ybN4+BAwcSFRVV47jQ0FCSkpIAS1m0wMDAeq8dFxcHQELCBcxmE506dSQqaqjy/MWLF5XjX3/9FbBsnnN1dWXz5s12LYirys/PV7rhCTfmp59+sjsnyzJDhgy59ZMRbgtZ5Ow2yg0Fu5IkfQSMBgxAMvC8LMsFvz03B3gBMAF/kmV52w3OVRCEu8wzzzyjHJ88eZINGzYwY8YMEhMT6d69O4mJicpqYtVACsDBwYEePXrQo0cPtmzZQmZmJmCpduDg4MCcOXNu3Qe5g4wdO5arV69y9epV9u3bh16vZ+jQoRw+fJjKykpycnJwcnKie/fuSrC7e/dupkyZUuP1rN3VqmrRogWAsnL84YefoNfrCQ8PZ8KEx5FlmZEjR7JlyxalYoQsy0RERDB27Fi76y1atKjGUmlC45lMJpvHvXr14tixY+LnKwh1uNGV3R3AHFmWjZIkfQDMAf4qSVInYALQGWgN7JQkqYMsy6Y6riUIwj2m6sYu67GDgwMDBgwALPminTt3rrWKgXWTVXUGg4G5c+ciSRLvvvvuTZ71nU2j0TBjxgxiYmKIi4vjxIkTnDhxwm7c2bNnlePqXySqWrZsGQBubm4UFxcD0L59aLVRMsOGPcjAgf2V6hQ1dVuTJKmBneyEprp27ZrN4+7du3P8+PHbNBvhdhFfbRrnhoJdWZa3V3l4CHj8t+OxwApZliuAi5IkJQF9gIM38n6CINxdVqxYQXJyMnC9Zmz1YKhqQ4i5c+fi5+dXa9qDj4+PzUpkQ8qC3a3+/e9/M3HixFrzch999FEefPBBvvjiC6UuL1hq+Hbt2pW4uDjKy8uV8z/++CMhISH069dPObd582b0ej0AkyZN4syZM+zdaykv9u67bynvPXv2LJvfW/WycGD5vcbFxXH69GkAXFxcmDFjhk1XNuHG+fj4KMcNadIiCMLNzdmdCvznt+M2WIJfq/TfztmRJOkl4CWgQTllgiDcPTIzM/H09CQ01LJS6OLiUm/XsLrye0eOHEllZSXLly8HoFOnTk2aV0JCAnl5eYSEhKDT6XB1dW3SdZrKbDazbds2Ll++zNChQ2nfvr3y3KBBg9i4cSPJyckkJyfbPFedu7s7c+bMISUlhTVr1qDX69Hr9Zw9e5ZXX32VL774Qglmk5KSSEpKIjk5mVaCfdq/AAAgAElEQVStWlFUVMSZM2cAePjhh/H19cXX15dWrVqRmZnJwYPX1yasga6npyczZ85EpVLZrSYOHz6c9PR0wJIakZSUhF6vF8HuTfbee+/d7ikIt5mMqLPbWPUGu5Ik7QRqqtr+tizL638b8zZgBH60vqyG8TX+ZmRZXgIsAejVq5f47QnCPaZ169Y89NBDdY6Jjo62SVmw7i6Pi4vDbDbj7+/PiBEjCAwMtBn3xBNPNGou+/fv58CBA0oAWJVKpcLR0RFHR0fc3Nxo1aoVZrMZvV5f4y37ptq9ezd79uxRHi9fvpwHHngAZ2dnioqKKC4uVlbBKysrG3TNdu3aMXv2bMrLy/n8888pLi6mpKSEN954w67jmjXotRo0aJDNam/Xrl0JCwvj4MGDuLu707dvX6VJxbRp02pdaQ4PDyc8PBywbHSr+h7CzZGTk6McV28oIghC7eoNdmVZHlbX85IkPQv8AYiSr99TTAeq3ucKAK40dZKCINz5EhMTuXbtmk0wVFFRUe/rDAYDK1euZOjQoZSXl5OQkEB+fj6xsbGAJQh96aWXAPi///s/5XWNuYV74sQJtmzZgtFoBCzNFDp27EhhYSGSJJGbm4vRaKS0tJSysjIKCgq4fPmy8vqbmS5x6dIlZQ6SJFFWVqZUNqhKkiRatWpcEwcnJyclpeH777/H2dm5xnEeHh5otVr8/Px48EH7TnLWcm+dO3emf//+HD16lIKCAj7//HP+53/+x2ZsbGysXXWMK1fEP/c3m8lk4ssvv1Qee3l53cbZCLeXfE+ncDWHG63GMAL4KzBYluWqSyUbgOWSJH2CZYNae+DIjbyXIAh3LlmWWbVqVY0rkXXV/jQajbz//vsASm6vVdu2bTGbzQwbZvm+/fnnn9vtRG+I9evXK+2KW7RowfPPP19nKkVRUREmk4kzZ85QWFjIsWPHbmpDC+sq8auvvopOpyM+Pp6EhAT8/f1p2bKl8qcp5dWqrnqXlpZSWlpqN2b69Ol11rtNTU1l165dgGWnv3Wu8+bNo6ysjD179tAhuAu/bjwLkmWluiZarVb5DHl5eY3+LIKt6j/nhtZZFgThxnN2FwGOwI7fcroOybI8XZblM5IkrQTOYklvmCkqMQjCvUuSJHr37s2BAweYPn06bm5uyvnagrarV6/y1VdfKeOsKxUqlYqnn35ayfMF+6oMDV3V/fXXXzl58iRqtZpp06Y1qKmBNRAeOHAgYKlq0NB0goaw5r9aUxW6du1K165db/i61UtPVU0NmTx5shJE16ewsFA59vT0BCy/k8cee4y1a9eyZ88e/nfiBoyVJmTJjLOLAx6eOhbGvIqHp4vyWq1Wi1arVR5bKz0IjXfq1Cn27dtnc27evHn8+c9/VsrECb8vIme3cW7oa6Esy6GyLLeVZTnytz/Tqzw3X5blEFmWw2RZ3nLjUxUE4U5mDU7PnTuHTqdDp9Ph6OjIkSNH2L59O/n5+cot9rVr1yqBro+PD3/729+YOHEiYAnaNmzYQEJCAtD0QBdQAoRXXnnljuneZV2Nu9l1URcuXKgcV/8ZVVZWNijQBQgKCgIsK/K//PILq1atwmg0KoGrLMuU6w0YK02YDDIl+RVkpxWx4otfld+7TqezCXSBWlMqGuP3eut23bp1yvE777yjHC9YsIC5c+f+bn8ugtBQooOaIAg3RVBQEL6+vuzZs0e59V91Na/q7n6r1q1bM23aNMDSGWzOnDksX76cS5cusWLFCptyV15eXg3elJOWlsby5cuprKzEycnphla/KisrqaysrLXmb311ZWsLRK5cuVJvZYrGsHYvq1pZQqvVUllZSVhYWIOuUVJSwueffw5YVnitucRVa/YCDPujJzu/vJ6aYKw0sWdjHK+/P97umtZmIEVFRXzyySd1vr/JZMJoNGIwGJS7A9VXhOvqGneve/fdd5EkiejoaFasWKF8IRQEoW4i2BUE4aaQJIlnnnmGX3/9VdkIZt1k5uHhgSzLGI1GzGYzHh4ejBkzhtatW9tcw8HBgeeee46MjAyWLVtmkz7QmA05MTExyua44ODgG/pcarWayspKZWVYlq9vDqn6X1mW7QLfmppqVFZWUlBQwNq1a5k1a9ZNb338+uuvK8eOjo5UVlayYcMGxowZU+9rNRoNjo6OlJWVKed8fX3Jzs62Hedgf1PQ2cWhxmsuWbIEgJYtWyqrxrUpKChQGmAEBARw7tw5uzH79u37XQW7VTd5vvfee0ydOpW2bdsyYcIEMjIy+OabbwDLFxXh90GUHms8EewKgnDTuLq6MmrUKOVxcnIy7dq1q7GFbF3atGnDW2+9ZZPXW/22eG3Wr19Pfn4+YAmQH3/88XpeUTeVSoVWq2X69On1D26gnTt3sn//fpYuXcrMmTNv+HpVUxiqGjduHD/88AOxsbGEhYXVu8Lr5OSkVFuYN28eZrOZ7OxsJS3CbDYrpcxGvOYNQOoJPalHjYx/cVCd1w4MDGTUqFE2TUQA9Ho9iYmJ+Pn5sX79euV81UDXxcWFkSNHsnr1amUe9/rmrNruJBw/flxp6tGmTRvefvtt5s+ff8trRQvC3UQEu4IgNIuMjAyKiopu6Bo+Pj5EREQQFxdHampqg14THx+vHD/66KN3ZFA0bNgwUlNTycjIYP369Y3+MgC1B0NVP2+7du145pln+Pe//83KlStt8j3rM3v2bD744APAkhs6c+ZMNBoNzzz9PP/+6VtlXFAPHUE9YMi4LoCllJyDg2WVt+rvIi4ujri4OHx8fOjYsSOXLl2ioKDAZkNcdUFBQTz77LPKY2uwm5eXh7e3d4M/y70gOjqawsJCJb3DqurPWPj9kEXD4EYRwa4gCM3CenvVxcWlnpF1i4uLAyyltP7xj3/wl7/8BbCULSsoKMDd3V0JrgBCQkK4cOECPXr0ICAg4IbeG2wrRdxMzz33HB9//DEnT56kXbt2N6UiQ02b90JCQgDLaugHH3yAWq2mTZs2ODk5MXjwYKXiQnVOTk689NJLLFmyhIKCAubPn4+3tzcTJ07k3Xff5eTBZDbs+FEZ/8UXi2xe//jjj7N27VokSWLs2LEcPnyYrKwsrl69atPyGSyrvkVFRUiSxJgxY2pNd3jjjTdYsGABGzdu5Lnnnqs3X/peYU3hqV7GT5ZlNmzYcDumJAh3FRHsCoLQLLp27Up8fLxyy7UprLm/VqWlpbWuaD755JNs3bpVWU2+ePEiRqMRlUp1R67uajQann/+eRYvXsy6deto3bp1g/OSq3bSeuedd+r9fI8++ihbtmyhsrKS8vJyLly4AFhKWmk0GiIjI3nooYdsvjQA+Pv7M2PGDJYuXYrBYODatWt8/vnndOnShfHjx9O9fzR6vZ6PPvrI7j2tq7BTpkwhKCiIiIgI9Ho9mzZtIjEx0SYfOy0tTTletmxZrbWAXV1dGThwILt37+bq1at3TIWNm+3UqVM2j3Nzc7l69arS+MTf35+ff/5Z2fwH2DRBEe51ssjZbSQR7AqC0Cz69etHfHw8K1as4M0338TR0bHR17CW51KpVPWW6lq5cqXN4/z8fObPnw9Ymkn8+c9/bvT7NzcfHx9Gjx7Nhg0bWLp0KbNmzbLLaa3J4sWLleOGBPIRERFEREQAlp/poUOHyM3NJSEhgdLSUo4dO8a1a9dsUgaqznHOnDmYzWYWLFhAUVERp0+fplu3brRv3x6dTmezorxkyRIlCOvYsaPNKq1Op+OJJ54gISGBFStW1Pn5aisxZ/28ubm592yway011r17dwoLC0lJSVFy12tTfbOnIAjXiWBXEIRm0bp1a8aPH8+aNWtYuXIlkyZNavQKq3Wl0Ww22wU/RqNRCWbBsgrp7OxMSkqK3XUKCgqYO3duraugq1evrrWMk9FobFAA2lTdu3cnNTWVU6dO8d133/Hiiy/W+xq1Wt3kOr0qlYr+/fsDMHr0aHbs2MGBAweUrnGdO3eu9XWvv/46a9as4fTp0yxfvpxXXnnFZjU6LS2NrKwswLLSHh4eXuO1QkJCcHBwwGAwMGDAAIYNG8YPP/xg87uzruBbf++FhYWsXr2a3NxcwNKUpFOnTk36GdzJrJsrAaWCxpdffmmzmm/15ptv4uDgwLx585TOfMK9T1RjaLw7796eIAj3jC5duhAVFUVKSgp79+5t9OurtplNS0vjypUrZGZmsmfPHptA95133uHFF19UgqX777+f6OhouwB53rx5dmW04HrKg5OTk90fV1fXZg+qxo0bh5eXFxkZGWzfvr3e8c8995xyPHfu3BtqUNG7d2/Acht89erV/L//9/+YO3cu7733HgsXLuTo0aM248ePv15Ld9GiRUqqibVcnCzLPPbYY7UGumBJ4ZgyZQoA+/fvZ+zYcUybNoMVK1bbjS0vLwcsqRvp6en4+PigUqlo165dkz/znaymTZ1//OMf+etf/2p33nq3RJZlpc6yIAj2xMquIAjNauDAgUqwGxwcTGBgYINfu2nTJuX422+/rXFMVFQUKpXKps5oZGSkchwdHU15eblSWWDx4sVKrdKqtFotb7zxRoPndrO9+OKLfPLJJxw8eJD77ruvzjJh1W9Zz5s3r1Gd5aravHmzzWNrLq1GoyEvL4/NmzezdetW/P39UavVlJSU4ObmpjR7mD9/PlFRUfzyyy+YzWbGjBnToM12VVMQtm3bQUVFBefPn+d///f/cHV15S9/eQ3Arg5xVFTUDeWB3+lq29Dp5OTEjBkz0Ol0fPzxx8p565eNK1eu3JL5CXcG8x1UjUGSpFSgGDABRlmWe1V7XgIWAKMAPfCcLMsnbuUcxcquIAjNbvz48ZhMJn7++edGva6+3fZTpkxh4MCBgGXzkvVW7ldffWWz2unk5GQTDP7rX//i73//e6Pm0tycnJyUnNmVK1fWWZKruqZUvDAYDKxZs4bExEQAJkyYwMsvv8ycOXOIjo7mrbfeYtq0aTg6OmI2m8nIyCAtLY28vDy7rma7du3CbDbzhz/8ge7duzfo/Y8fP64cV22cALYNEqpvUrzXWatj1LRZ0cfHB1dXV/r378/gwYOB6/Wn78WUDuGuMlSW5cjqge5vRgLtf/vzElB3AnozECu7giA0OxcXFzp16sTZs2cpLi62qxVa3cmTJ9myZQsGgwGAsLAwgoODCQ4OxsfHR8nnXLduHbNmzVJe9+abbyrpDfv27eOBBx6wue6kSZP48UdLuayq1QCao7RYU7Rp04YRI0awdetWvv76a2bNmlVjjvHatWuV49GjR9OjR48GXT8uLo4dO3ZQVlZm82UgMjKyxpXk7Oxsu0C0V69ejBw5EpVKRWFhIYcOHeLQoUN4eXnRs2fPhn5Utm7dWuN5SYJXX73eaONOrKTRnFQqFS1atMDf37/WMQ899JDN499LCTbBSkaW7pyV3QYYC3wvW/6hPSRJUgtJkvxlWc6s74U3y+/rXxFBEG4ba9te60pibYqKili/fj0GgwGVSsWIESOYMGECffv25auvvrIpPVa9RqxGo2Hy5MlAzaWYquZ5ms1mjh07ZjdGr9ff1tXEvn37Eh4eTmlpKd9//73d89nZ2TaNBBoT6MbExFBaWopKpcLJyYnu3bvz2muv1drUwvqFYNKkSbzwwgs4OTkhy7ISgHp4ePDwww/j4OBwQzmj/fr1UY6jo/+Gp2dL5fHvLdgFS/BaNV9dEG4jb0mSjlX581INY2RguyRJx2t5vg1Q9R/k9N/O3TJiZVcQhFvCmlNo3XBUm6pVEZ5++mlCQ0OBmjuGVd2oZdWuXTskSSI1NdWuraxKpWLChAlK2atNmzaxZ88ewLK6W/09goODlY1Ut9Ljjz/OokWLuHTpErt27SIqKgqw3PqvmgoyZMiQBl0vNTWVmJgYAJ566ik6duzYqPm0bt0anU5X647/4OBgEhISSExMpH379g26ZnR0NDExMcTFxTFixHB0Oh3//e9umzGvvvpqo+Z5rwgKCiI2NpYdO3bQp1cvPFq2rHWs2WxGlmW7Rh3CvesWV2O4VktqQlUDZFm+IkmSD7BDkqTzsiz/WuX5mm493NLbaSLYFQSh2ZlMJmJjYwFwdnauc+zhw4cBS1ct60rs+++/rzz/7LPP1tphy0qWZYxGI2vWrOGJJ56weS4sLIzo6GglsK2aH1rdxYsXmTt3LjqdjtmzZ9f5njeTSqXipZde4pNPPmHfvn0EBATg5eVll/M8aNCgeq9lNpuVFeIuXbo0OtBtiMGDB5OQkMD+/fsbHOyCpdmFp6cnv/zyCw88MJDi4uu/C7VazYULFzh//jwAZWVlN33ed6pevXoRGxvLgQMHqNi7meEeKtQjJ6LuZJ8motfrAZHKINw+sixf+e2/VyVJWgf0AaoGu+lA1V2lAcAt3VEpgl1BEG6pqpUSamLd/PTss8+iUqkoLy9XcndVKlW9gS5YAiWTycTZs2drHVM14K3qT3/6E999951NCSi9Xq+M1el0hIeHk5CQgNls5uWXX8bd3b3eOTWWk5MTU6ZMYenSpXYNGBpSecFsNrN7926l5Jubm5tN2bCbyd/fH0dHR9LT0xv92gceeICjR49SUlLCI4+MUM6bTCa2bduGs7Mzvr6+6HQ6wsLCaNWq1c2c+h3J59whLAtfEpdUOtILrnJu1U/cP9aIZ2Rfm7Gurq4Av4ufi3DdnVKNQZIkF0Aly3Lxb8fDgfeqDdsAvCJJ0gqgL1B4K/N1QQS7giDcAmq1muDgYC5evIgsy7WuQmVmZiqBbXx8PBEREaxZs0Z5/p133mnQ+/Xo0UOpD1s9laGq6OhozGYzH374IQaDgaCgIDZu3Ii3tzfe3t4Adk0q9Hq9TSWBTz/91K7mq3XDm1arZdy4cXblsxoqICBA2bBm9fbbbzfotV999RXXrl0DLD//V155pUlzaCh/f39SU1MpKSlRAjCw5GDrdLo6G3O8/vrrzJs3D4C2bdva5FsHBAQwceJEsi5cpTinBHOFDE37cd4VZKMR8/4tzKms4H1tCNckB37QBADQevdWu2AXxKqucFv5Aut++zuoAZbLsrxVkqTpALIsLwY2Yyk7loSl9Njzt3qSItgVBOGWuHjxImDpfOXn51fjmKqBpbW9bVJSUqPfa9iwYcTGxmI0Gjl//nydZZlUKhUmkwlZlpU5NlZNXdusjh8/zoABA5p0XbCvWpCYmFhrwwaz2cx3331nEyx27dqVMWPGNLgLXHFxsVL2rGo3r/qYTCbAsvJd1aeffgpYAtraVsCrfhm5fPmyzap7YmIiHz21iPwrhajMKoy5Mg/OGMDwPw9u8NzuKmUlUEuTEE1xPhUVFUpd6ZYtW5KRkXHHVBMRbhUZ+Q5Z2ZVlOQWIqOH84irHMjCz+phbSQS7giDcUt988w3Ozs64urrSsmVL2rRpQ9++fdFoNMTFxQGWldmqjSAApcpCQzg4OODq6kpBQYGywa0uWq0WSZL4y1/+AlhWZqsGEHWtDlvHVt8IZ80z9vHxafC86yNJEqtXr2bOnDl2wWtJSYlNswGAUaNGKR3SGuqbb76xSeGQJKlBrWitgeyqVat46qmn7J7/9NNP60y/aN++fa2VOvSdcnH87fuKYR3s/ucBWof70WV47Y037lo6V1BrwFjJzMpUvtAGKU+tNbeEWupDW1fxBUGwJ4JdQRBuif79+3PgwAEkSaKsrIySkhKysrI4d+4cO3fuBCy70HNycsjKyrIJdIFGt4ft2LEjhw4d4v3336ddu3Y2q69hYWFMmDDBZrwkSTg4ODTx09lr0aIFBQUFXL58uVGbtqrTarVUVlYiSRJBQUFcvHgRvV5vt0paNdAdOnSoXY3hhqqoqCAsLIxevSwbsF1dXZW2tHV59NFHSUlJ4fz58zZfDv70pz/x+eef1/v6CRMmKKkMVT+L4YgKY6EZtRc49gAcwFBYya9LD96Twa6k1qAaMgbzf9chVZqU84GUk1ZH/kbV1BFBEGyJYFcQhFvCGjC98MIL+Pn5YTabiY+P55dfflFum6empgI3p8lDVFQUZ8+epaioyC7NIDEx0SYAKysra9DqZWMMGTJEKfd1I6y1bmVZVioS1BXYPPnkk7WmOTRUixYtGrQiXpVGoyE8PJwTJ06wa9cupfFByypls9LT0wkICKj3WjYVMi5pMZUaoNrfidJ8faPmdzdRDxyF5KTD8Zf1UAZDdCYGPTYZVcj1dJyqdxTee++9JueFC3cfGTDfXU0lbjsR7AqCcEtYVyKtwZtKpSIiIkLJzTWbzcTGxpKYmMjgwYPZsGEDWVlZyuvnzp3boCoEVhqNhtdff52SkhLy8vIIDAzEbDbz5ZdfkpeXZ9cE4WbnPVpzWJOSkujQoUODgrzqsrOzleOOHTuSmZmJSqWyS6mwfllwdna+4UAX4MKFC8o13d3dGTFihLIJKjk5mf/85z+AJegeNWoUsbGxHDp0SAnGDxw4gIODA4MHD7bp1LZ161ZefPHFGt+zpjSRgQMG8WvGfiSjjKpKxTq1Vk2nqA43/DnvVJIkoe49FJdeQ1DPn48hsr9NoGsdIzamCULDiGBXEIRbqrZVSZVKRc+ePZWWsy+//DIbNmxQ6vPeyPtZ31OlUtVYleDDDz+86V3T2rRpg0qlIjMzk6VLl6JWq/Hz86Nr16707NmzQRvGlixZohw/8cQTfPjhh2i1Wrtx1vq73bt3v+F5d+7cmYyMDPLz89Hr9Zw/f57BgwcrJdcuX76sPFdcXExxcbFNIxCr3bt3s3v3bptzGRkZDWoXbZVyMRltWxXkmpFlMGaDqlyDi5eOIdP63/BnvdNJkoROp1Nq6QqC1Z1SeuxuIYJdQRBuCevKXVlZmc2t7bqMGTPmhoPd28XX15e3336bCxcucOLECS5fvkxGRgYZGRls3boVd3d3QkND6devX601Uq2rojqdDpVKRWVlpd2XhaNHjyoVKxoaRNZl9OjRyvGRI0fYsmWL8viRRx5Rjq3d3Nq3b68Eu25ubjz44IOsX7++1ut/8sknta7Qu7m5KXWWrdqFBDNwzGD2/uswBTmFhL0USv/JvdB51N2c5F7h7Oz8u2qoIQjNQQS7giDcEsHBwahUKnbt2sWoUaMASz5nbVUOwLbsWGNSGO4UKpWKjh07Kl3LioqKOHToEAkJCeTn53PixAlOnDiBVqvF39+fiIgIunXrhkajYfXq1cp1hg8fzt69ezGbzTaB8VdffWXTJrZPnz7N8jny8vKUgKv678zb2xuVSoXZbGby5Mm0atWK/fv3c+3aNXr06MGZM2eoqKiwud7cuXNrXGF3dXVVgt1u3bpx6tQpQkJCCIxow6QFjzXLZ7vT6XQ6uy5/siyTn5+vpN6I0mO/N7JY2W0kEewKgnBLuLm5ERYWxrlz51i0aBEAffv2ZcSIEbW+pqbb43czd3d3hg8fzvDhw5UNeidPnuTKlSukpaWRlpbGxo0bcXd3tyn/FRERoXRRu3TpkjLWGuh27dqVxx67+cGgNdVi6dKlyrkePXowevRo5bnvvvtOee7LL79kzpw5dOjQgWvXrhEUFMTo0aNZunSpXXc169+B2pw6dQq4no/8e9WyZUtiY2PZtWsXUVFRGAwGTpw4wbZt22zGNbSOsiD8Hon/dQiCcMs88sgjtG/fHo1Gw7Zt2+rMRczPz+fYsWO3ZF7V6+reCtU36OXl5XH48GESExNtNs9ptVpWrVqlBP5Go5Fvv/1Web5fv348/PDDHDt2jNjYWJ5++ukml6FKT0+nsLCQzp07A5YgWpIkNmzYoIzJyckBoFOnTmi1WkwmE2VlZUq6w9GjR5WVXGdnS6qBXq8nICCArl27sn//fry9vYmIiKhxg1VFRQV6vZ6rV6/i5uZGv379mvRZ7hUjR44kKyuLffv2ERkZafMlwfoFR5KkRlfPEO5eMtwxTSXuFiLYFQThlnFxcVE2Uf3yyy91jrUGSreCwWDAbDazePFinnvuudtSxsnT05ORI0cycuRIzGYzBw4cICkpicuXL3P27FmbsRqNRtlQd+jQIY4fP65Uudi2bRvjx49v0HsWFhayfft2SktLSUtLUwL+tm3b4u7uTlJSkk2gK0mS0iRDq9XadKb773//i8FgoEuXLuzduxewvb3eokUL+vTp02ypFvcqrVZLaGgomZmZdqvhXbt2vU2zEoS7iwh2BUG4LWRZJjk5mX/961+YzWZlddXV1ZUJEybYBZzZ2dn4+vo2y1ysK4zZ2dn84x//4KWXXrqpnc8aS6VSMXDgQAYOHEh5eTnx8fFs3rwZgIkTJ9K+fXsyMzNZv349BQUFVFRUKKkPp0+fJisri3bt2nHy5Enl8zk6OhIcHMzw4cOpqKjgX//6l10uqNXmzZtxcnJSOtoBREZGEh8fX+ucnZycCA8Px8PDQykzV728m9A0ffv2Vb5AAHZNUoTfGxkzpvqHCQoR7AqCcFtUVFRQVlZWYyrD+fPn6dSpE9HR0cydOxeAxYsXN9smNQcHByorK2nZsiU5OTl89dVXd8yGOCcnJyIiItiyZQtarVbpxubv78/06dNtxh49epRt27Zx7do1m/axkiRRUVFBXFycTQDr6OiIv78/6enpeHl5KXV9ExIScHd3R5IkZFnG3d2dlJQUXFxcaNu2bb1z9vb2BiA3N/eGP79guSMSGRmpfHkRga4gNI4IdgVBuC2cnJwIDQ212ViVmJjI8uXLSUpKUm6RP//88zY5qs1FkiT++Mc/Mm/ePMxmMz/++COTJk1q8vXi4+PZtGkTarUao9GIJEk888wzTWousW3bNmRZpn//umvL9u7dm969e3P8+HFiY2Np0aIFjz/+OIDypaEqBwcHnn32WeWx0Whk/vz5N7zhzVoLuGpDCeHGjB07liFDhnDo0CEOHTrUpL9Hwr1D5Ow2jgh2BUG4bYxGo83KrjVN4cqVK8p56yohWAK22bNn43skHmIAABfaSURBVOzsXGv3qJSUFA4dOoTJZMJkMtGzZ08lt9FsNnPx4kWlDFpNRo8ezfr160lKSiI5OZmQkJBGf660tDTWrl1rd37p0qW4urryxhtvNOp6J06cACyNGgYPHqycNxqNGAwG5bGDgwMajcamOYd1XE3uu+8+u5V1BwcHdDpdo+ZX9X30ej1paWmAJejV6/WiNNZN4uHhwcMPP8yQIUNwcHC43dMRhLuGCHYFQbgt1Go1586d49y5c3bPZWdn89FHH9X4uo8++oiePXsyfPhwli5dSmFhIZ6enuj1ekpLS+0Cu0uXLrFhwwYlOK6srESlUhEcHEynTp1o06YNZWVlympkZGQkGzZsQJZlVq1axZtvvtnoz2Zdifb29mby5Mk4ODiwbNkysrKyKCkpYe7cuXTu3JlWrVoxaNCgOmsNV897zczMxN/fH7PZzGeffUZpaanynIeHB6+99prdNarme1Z1+vRpTp8+bXe+rvnURqVS2V3vwIEDHDhwAIDAwMBGX1OomaOj4+2egnAbyciYJbGy2xgi2BUE4bYYM2YMmZmZdueLioqQJEnpBibLMqdPn8bPz4/8/HwuX77M8ePHOX78uPKazMxMVCoVjo6OBAQEMHToULy9vdm5cycpKSnKKq81EDabzSQnJ5OcnKxcw2S6vuFj8uTJfP/993bNEBqiarA9c+ZM5fjll18mNzdX2VF/5swZwLJa27ZtWx555BF8fX3Zu3cvZ86cwcfHBzc3NyVYtDpw4ADjx4/HbDZTWlpKhw4dCAkJ4cKFC7Xmcv76668A9O/fHw8Pj3o/g7UJRmM8+uijZGVlAZZ87OLiYptVeVEaSxCE20UEu4Ig3BZt27Zt0GYnsOxGt/rwww9tnnvnnXdqXYkcM2aM3bmSkhKOHj1K69atiY+PJy8vTwmWrYKDg5XjHTt28NBDDzVonnB9Vbem1r1eXl688847rF27loSEBCUwvnz5MosXL7YZa90sBpZGDgUFBaSkpNitnrq6utKnTx9KSkpITk5mz5499OjRg59++snuy8SDDz6IWq1u8GdpjMDAQLF6Kwi3iKjG0Dgi2BUE4a7SokUL2rZty/jx49Hr9Y2+5e7q6srQoUMBCAsLAywBdNWVXUDZ/X7q1KlGBbtXrlwBqPU1KpVK2TQGlgoKaWlp5OTkkJubiyzLhIeH4+7uTnZ2NqNGjcLT0xOoeZPZ+fPnGT16tNJxbPfu3ezevbvB8xUEQbjXiWBXEIS7koODQ7Nu0hk7diwnT56stRZtTTZt2qQcN7Tgv7WCQkMMGDCA/fv3o9VqMZvNmEwmZfW6f//+Shez6tRqNa1atWpSLq4gCMLdTgS7giAINbh69SpwvYxWXYqKili0aJHSxay5gkpZltFoNLz11lt2z4nuZILweyGL0mONJIJdQRCEakpKSvjnP/8J1J6OYJWamsqyZctszmk0N++f1qplu+7kEl41zU2WZaUKRm2l4gRBEJqbCHYFQRCq2blzJ2azmfbt29eZYmBtPgEQEBDA5MmT+eCDDzAYDHz33Xc1tj1uDJPJxMKFCyksLFTO3an1VX/88Ueb6hbVDRkyxKZGsCAITSMDZllsUGsMEewKgiBUY92sZm3NW11OTg5Lly5VSpO1bNmSF154AbBsoMvLy+PSpUt88MEHvPHGG7i6ujZpHkajkcLCQkJCQpTKFa1atWrStZrbtWvX8PPzU8qW7d+/n8rKSrp06UJycrJN+2JBEIRbSQS7giAI1Vhzbzdv3syWLVvw9PRErVZTUlKCRqOhrKxMGRMWFmbTWnfmzJmUlJTw6aefAlBcXNzkYNcqJCSE+++//4aucSv4+fkxePBg0tPTlYoQaWlplJWVNalmsSAINRE5u40lgl1BEIRqBgwYQEJCAmDJNc3NzbUbo1areeWVV2jRooXNeZVKhbu7Oy1atLDrfmaVl5enNJWwvqZ79+5NbtN7p4mNjVWOi4qKbuNMBEEQRLArCIJgp23btkyePBmNRkNgYCB6vR6DwUCLFi0wGo2Ulpbi5uZWZ9UFaxvfxMRE/P39bZ47ePAgx44dsznn6OhIr169bv6HuQ2sAe6rr76Kq6srCxcuFC1uBeEmkkVTiUYRRRcFQRBq0K5dO6UjmE6nU1ZwNRoNHh4e9ZYXc3FxAeDs2bOYzba3HEtLS5Ekib/97W+8/vrrAHZj7jYmk4nk5GQOHz5Meno6YMlfbu56yIIgCPURK7uCIAjNYNy4cfzwww9kZ2czb948PDw8eOaZZ9Dr9Zw7dw6wpEI0V/veW62srAyTycTWrVuVc6KJhSA0BxmzyNltFBHsCoJw10lMTOTvf/87YLn9/+KLL+Lm5nabZ2UrMDCQOXPmEBMTQ3x8PIWFhXzxxRd1viY9PZ3WrVvflUGis7OzXbc56++ooqKCNm3a3I5pCYIgiGBXEIS7y5AhQ0hJSQGgoKCAhIQECgsL77hgFywrm4899hgDBw7kq6++UnKAU1JSGDdunM3Yqq1+/f39ee6555QV4PLy8ls676YYMWIEly9frvX5hrZPFgShbjKIagyNJIJdQRDuKh06dKBDhw6AZYXXWjXhTmbdnDVy5Eh69OhR7/jMzEyWLl2qtCwuLi5u1vndDJ07d6Zz5863exqCIAh2RLArCMJdJTMzk5MnT+Ll5XVHNyooKCggKSkJsOSzVlVUVMSFCxcA7G79W1kDXbhzG0kIgnA7yMiig1qjiGBXEIS7yurVq8nLy1Meq1QqpfLBneTXX3+1qTcLKKkW+/bt4+jRo3av0Wg0GI1Gu/N3YoqGIAjC3UIEu4Ig3FX0er1yrNVqmTp1Ki1btryNM6qZ2WzG3d2dadOmAZbKC87OzoClTJdOp2PGjBlkZmaycuVKfH19eeihh/juu+8AmDVrFpIkoVKp7plmE4Ig3ByiGkPj3H1bfgVB+F1r2bKlEjRWVlayc+fOG7peTk6OXZrBzaJSqXB1dcXV1VWZc/Xn2rdvz9tvv82LL77IkSNHlOfd3NxwdXUVga4gCMINEiu7giDcdSorK5Xj5ORkSktLG53K8J///Ifz588rj5uzw5fRaGTZsmVKfq5er6+x0UJhYWGzzUEQBOH3SgS7giDcVfr3709SUhI5OTkUFxdTXFzMihUriIqKIjAwsN4atUVFRfz8888kJiYClhXU0NBQRowY0WxzLi0tJT09nYCAALy8vABqrDubkZEBWNIzBEEQaiaLdsGNJIJdQRDuKl26dKFLly4AHDt2jE2bNpGens6yZcsACAgIICoqCrBUNLhw4QKSJOHt7c2gQYNYsGCB0pp30qRJhIaG3rK5d+/evdbSY1U3pkmSdKumJAiCcM8Twa4gCHctDw8PAFxcXHByciI/P98m8K0qKSmJQ4cOKY9ffPHFZu/qZTAYOHPmjM2mutps2rQJACcnp2adkyAIdzcZkGWxQa0xRLArCMJdq7S0VPnvtGnTcHR0ZNu2bWRlZaFWq/H09KR3795oNBp2795NYmIiKpWKBx54oNkDXWdnZ/R6PatXr7Y5V5Py8nLi4uLQarV06dKF06dPN+vcBEEQfk9EsCsIwl3r+PHjyvFnn30GQHR0dI1jn3766VsyJ6thw4bZpCyo1epaS6TFxMQgyzJDhgwRm9QEQaiHLEqPNZIoPSYIwl1LrVbf7inUSq1W06pVK+WPp+f/b+/+Y6wsswOOfw8IA3GHyCAyKihW0CwsihliRGui1KC1RuwPEhutYv8wNjZ1zRq7Lulu2MbEZBPTpGtTf+zKxtUafyxo2loVa7NbhbW6RUCR7gQca3SkaBQRHGTn9I97ZxzwDsPsMPPe+97vJ7nhfZ/nnbnnngyTM88993nbavbi7t69m23btjF58mTOP//8AiKVpHJzZVdSQ2tpaaG9vZ2uri6gssLbtzftxIkTWb58eV3eYa3Pk08+CcCll15acCSSGkLi7YKHaUQruxHxtxGxKSI2RsRzEXHSgLk7IqIzIrZFhL/FJR11CxYsoL29HfiyH3bGjBm0trYyfvx4urq6eOCBB4oM8bA+/vhj3nnnHVpaWjj77LOLDkeSSmmkK7s/yMy/AYiIvwK+C9wUEfOAq4H5wEnAuog4I/1TRNJR1NHRQUdHR825+++/H6gUlPWqL7aenh5ef/11C15JRyBJe3aHZUTFbmbuHnB6LJUdMQCWAY9mZg+wIyI6gXOB9SN5Pkk6Un176QJs374dqKz6FtXS0N3dXXMLsra2Nj766CPWrl3Ls88+279SLUk6OkbcsxsRdwLXAZ8AF1eHTwY2DLjs3epYra+/EbgR4JRTThlpOJIEwJw5c+ju7gbgoYce6h+75pprxjyWvXv3cu+99w553b59+9ixY0f//sGSdCj32R2+IYvdiFgH1FpqWJmZT2XmSmBlRNwB/CXwPaDW7X+yxhiZeR9wH8CiRYtqXiNJw7VkyRLmz5/P/v37AXjmmWfo7Oxk1apVwOBblI2GL774AoALLriAM844o+Y1PT097Nu3jylTptDW1jZmsUlS2Q1Z7GbmJUf4vR4B/oVKsfsuMGvA3EzgvWFHJ0m/pYg4qCWgb5W3z6pVq1i8eDFLly4ds5ja2tp8B0vSCCWJH4EajhG1MUTE3Mz8dfX0SuCt6vHTwCMRcTeVD6jNBV4ZyXNJ0tG2fv16tmzZwvTp00f1eQ4cODCq31+SNLiR9uzeFRFnAr1AF3ATQGa+ERGPAW8CB4Cb3YlBUpFmz55Nb28vN9xwA5s2bWLNmjUAHHvssf1tBqP9/LNmzRr6Qkkagj27wzPS3Rj++DBzdwJ3juT7S9JoOO644wC49tprOf300wuORpI0mryDmqTS6Onp4cMPP/zKeG9vLx988MGotytIkuqPxa6k0njiiSfo7OwcdH7g3ruS1KhsYxgei11JpfH5558zY8YMLr744oPGN2zYwNtvv820adMKikySVBSLXUmlMmnSJM4888yDxiZPnsyDDz7Ipk2buOqqqwqKTJJGrnKzYFd2h2Nc0QFI0tEyc+ZMurq62LFjx0HjfXvbZiaPP/44L774YhHhSVKpRMSsiHgxIrZGxBsRcUuNay6KiE8iYmP18d2xjtNiV1JpLFmyhGnTprF27Vp6enpqXrNz50727NnDSSed5AfWJDWkzN4xeRyBA8C3MvPrwHnAzRExr8Z1v8jMhdXH949mLo6EbQySSmPChAlceOGFrF27lq1bt7Jw4cL+uYH77EqSRi4z3wferx5/GhFbgZOp3GehbljsSiqVvj10n3rqqYOK3UN99tln7N+/v/+8tbWVY47xV6KkOpfJGN6n6/iIeHXA+X2ZeV+tCyNiNnAO8Msa04sj4nXgPeC2zHzjaAd6OP5ml1Qqp5566pDX7Nq1i3vuueegscmTJ3P77bePVliS1Ih2ZeaioS6KiK8BTwLfzMzdh0z/Cjg1M/dExOXAWmDu0Q91cPbsSiqtzKw5vnfvXgAWL17MsmXLAJg6deqYxSVJI5H0jsnjSETEBCqF7sOZ+bOvxJq5OzP3VI//FZgQEccfzXwMxWJXUumcddZZAHzyySeHvW7cuHGsX78egH379o16XJJUJhERwI+ArZl59yDXtFevIyLOpVJ7fvVWl6PINgZJpdPa2grAunXrmDRpElBpXWhrazvoupdeeqn/ePfuQ995GzuvvfYamzdv7j9fsGABHR0dhcUjqZ5lPd1B7QLgz4DNEbGxOvYd4BSAzPxH4E+Av4iIA8A+4Ooc7G23UWKxK6l05syZw8aNG9m+fTvjxn35BlbffrtTp05lypQp/QVuS0sL55xzTiGxAmzevJnu7m7a29vp7u4GsNiVVPcy8z+BGOKaHwI/HJuIarPYlVQ6s2fP5rbbbht0vrW1lVtvvXUMIxpae3s7K1asYPXq1UWHIqmOJdTTym5DsGdXkiRJpeXKriTVge7ublavXk1XVxctLS0HrfDawytpoCPdKUEVFruSVLAFCxb0H7e0tBw0Zw+vJI2Mxa4kFayjo6O/mO1b0V2xYsVB55Kk347FriTVmb6WBoCuri6mTJnCCy+8AMAJJ5xw0EqwpGZTV1uPNQSLXUmqIwML2b6tKD/99FNefvllent7v3KNJOnwLHYlqY4MbGno6enhrrvuYv78+WzZsgWARYuGvE29pJJzZXd43HpMkupcX6F74oknsnTp0oKjkaTG4squJNWpiRMnMm/ePN58802uu+46TjvttKJDklS4BLceGxaLXUmqUxHB8uXLiw5Dkhqaxa4kSVKjSHt2h8ueXUmSJJWWK7uSJEkNIvF2wcPlyq4kSZJKy5VdSZKkhuEd1IbLlV1JkiSVliu7kiRJDeU3RQfQUFzZlSRJUmm5sitJktQw7NkdLld2JUmSVFoWu5IkSSot2xgkSZIaim0Mw+HKriRJkkrLlV1JkqSGkeAH1IbFlV1JkiSVliu7kiRJDSTJokNoKK7sSpIkqbRc2ZUkSWoo9uwOhyu7kiRJKi1XdiVJkhpJ2rM7HK7sSpIkqbRc2ZUkSWoY6W4Mw+TKriRJkkorso76PiLi/4CuQaaPB3aNYTiNwrzUZl4GZ25qMy+1mZfBmZvais7LqZk5vcDnH1UR8W9UcjwWdmXmZWP0XKOmrordw4mIVzNzUdFx1BvzUpt5GZy5qc281GZeBmduajMvqje2MUiSJKm0LHYlSZJUWo1U7N5XdAB1yrzUZl4GZ25qMy+1mZfBmZvazIvqSsP07EqSJEnD1Ugru5IkSdKwWOxKkiSptOq62I2IH0TEWxGxKSLWRMRxA+buiIjOiNgWEZcWGWcRImJ5RLwREb0RseiQuWbPzWXV194ZEd8uOp6iRMSPI2JnRGwZMNYWEc9HxK+r/04tMsYiRMSsiHgxIrZW/w/dUh03NxGTIuKViHi9mptV1fGmzw1ARIyPiP+OiH+unjd9XiLi7YjYHBEbI+LV6ljT50X1pa6LXeB54BuZeRbwP8AdABExD7gamA9cBvxDRIwvLMpibAH+CPj5wMFmz031td4D/D4wD/jTak6a0WoqPwMDfRt4ITPnAi9Uz5vNAeBbmfl14Dzg5urPiLmBHmBJZp4NLAQui4jzMDd9bgG2Djg3LxUXZ+bCAXvrmhfVlboudjPzucw8UD3dAMysHi8DHs3MnszcAXQC5xYRY1Eyc2tmbqsx1ey5ORfozMztmbkfeJRKTppOZv4c+OiQ4WXAT6rHPwGuGtOg6kBmvp+Zv6oef0qleDkZc0NW7KmeTqg+EnNDRMwE/gB4YMBw0+dlEOZFdaWui91D/DnwTPX4ZOB/B8y9Wx2TuWn21z+UGZn5PlSKPuCEguMpVETMBs4Bfom5Afrfqt8I7ASez0xzU/F3wO1A74Ax81L5Y+i5iHgtIm6sjpkX1ZVjig4gItYB7TWmVmbmU9VrVlJ56/Hhvi+rcX3p9lA7ktzU+rIaY6XLzWE0++vXEYqIrwFPAt/MzN0RtX50mk9m/gZYWP2MxJqI+EbRMRUtIq4AdmbmaxFxUdHx1JkLMvO9iDgBeD4i3io6IOlQhRe7mXnJ4eYj4nrgCuD38stNgd8FZg24bCbw3uhEWJyhcjOIpsjNYTT76x/KBxFxYma+HxEnUlm9azoRMYFKoftwZv6sOmxuBsjMjyPiP6j0fTd7bi4AroyIy4FJwJSI+Cnmhcx8r/rvzohYQ6WVrOnzovpS120MEXEZ8NfAlZm5d8DU08DVEdESEacBc4FXioixDjV7bv4LmBsRp0XERCof1nu64JjqydPA9dXj64HB3iEorags4f4I2JqZdw+YMjcR0/t2vYmIycAlwFs0eW4y847MnJmZs6n8Tvn3zLyWJs9LRBwbEa19x8BSKh+ebuq8qP7U9R3UIqITaAE+rA5tyMybqnMrqfTxHqDyNuQztb9LOUXEHwJ/D0wHPgY2Zual1blmz83lVPrrxgM/zsw7Cw6pEBHxT8BFwPHAB8D3gLXAY8ApwDvA8sw89ENspRYRvwv8AtjMl/2X36HSt9vsuTmLygeKxlNZDHksM78fEdNo8tz0qbYx3JaZVzR7XiLid4A11dNjgEcy885mz4vqT10Xu5IkSdJI1HUbgyRJkjQSFruSJEkqLYtdSZIklZbFriRJkkrLYleSJEmlZbErSZKk0rLYlSRJUmn9P6yWBCOMIgKAAAAAAElFTkSuQmCC\n", "text/plain": [ - "
" + "
" ] }, "metadata": { @@ -178,46 +179,22 @@ } ], "source": [ - "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(20,10))\n", - "fig.suptitle('conflict distribution; # conflicts {}; threshold casualties {}; type of violence {}'.format(len(conflict_gdf), config.get('conflict', 'min_nr_casualties'), config.get('conflict', 'type_of_violence')))\n", - "\n", - "conflict_gdf.plot(ax=ax1, c='r', column='best', cmap='magma', vmin=int(config.get('conflict', 'min_nr_casualties')), vmax=conflict_gdf.best.mean(), legend=True, legend_kwds={'label': \"# casualties\", 'orientation': \"horizontal\"})\n", - "extent_gdf.boundary.plot(ax=ax1)\n", - "ax1.set_title('with all polygons')\n", - "\n", - "conflict_gdf.plot(ax=ax2, c='r', column='best', cmap='magma', vmin=int(config.get('conflict', 'min_nr_casualties')), vmax=conflict_gdf.best.mean(), legend=True, legend_kwds={'label': \"# casualties\", 'orientation': \"horizontal\"})\n", - "selected_polygons_gdf.boundary.plot(ax=ax2)\n", - "ax2.set_title('with selected polygons only');" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Storing the data now, to be used later or in other notebooks." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "conflict_gdf.to_file(os.path.join(out_dir, 'conflict_gdf.shp'))\n", - "extent_gdf.to_file(os.path.join(out_dir, 'extent_gdf.shp'))\n", - "selected_polygons_gdf.to_file(os.path.join(out_dir, 'selected_polygons_gdf.shp'))" + "ax = plots.selected_polygons(selected_polygons_gdf, color='0.5', figsize=(20, 10))\n", + "plots.selected_conflicts(conflict_gdf, ax=ax, cmap='magma', vmin=1, vmax=conflict_gdf.best.mean(), \n", + " legend=True, legend_kwds={'label': \"# casualties\", 'orientation': \"vertical\"})\n", + "ax.set_title('conflict distribution; # conflicts {}; threshold casualties {}; type of violence {}'.format(len(conflict_gdf), config.get('conflict', 'min_nr_casualties'), config.get('conflict', 'type_of_violence')));" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Since the more straighforwad option to store the dataframe as csv does not with geometry information, we need to take a detour via numpy." + "The selected conflict points and polygons are saved as shp-files to be re-used later. For the dataframe with polygon ID and geometry we need to take a detour via numpy because the more straighforwad option to store the dataframe as csv does not with geometry information." ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -229,9 +206,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3.7.9 64-bit ('conflict_model': conda)", + "display_name": "Python 3", "language": "python", - "name": "python37964bitconflictmodelconda0a7cb69c875e4f578f0c3bf47b804900" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -243,7 +220,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.9" + "version": "3.7.8" } }, "nbformat": 4, diff --git a/example/nb02_XY_data.ipynb b/example/nb02_XY_data.ipynb index ecc33f9..a9aca50 100644 --- a/example/nb02_XY_data.ipynb +++ b/example/nb02_XY_data.ipynb @@ -15,7 +15,7 @@ "metadata": {}, "outputs": [], "source": [ - "from conflict_model import utils, pipeline\n", + "from copro import utils, pipeline\n", "\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", @@ -41,8 +41,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "Python version: 3.7.9 (default, Aug 31 2020, 17:10:11) [MSC v.1916 64 bit (AMD64)]\n", - "conflict_model version: 0.0.4b2\n", + "Python version: 3.7.8 | packaged by conda-forge | (default, Jul 31 2020, 01:53:57) [MSC v.1916 64 bit (AMD64)]\n", + "copro version: 0.0.5\n", "geopandas version: 0.8.0\n", "xarray version: 0.15.1\n", "rasterio version: 1.1.0\n", @@ -50,7 +50,7 @@ "numpy version: 1.18.1\n", "scikit-learn version: 0.23.2\n", "matplotlib version: 3.2.1\n", - "seaborn version: 0.10.1\n", + "seaborn version: 0.11.0\n", "rasterstats version: 0.14.0\n" ] } @@ -91,7 +91,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "saving output to folder C:\\Users\\Icke\\_code\\conflict_model\\example\\OUT\n" + "saving output to folder C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\OUT\n", + "\n", + "no conflict file was specified, hence downloading data from http://ucdp.uu.se/downloads/ged/ged201-csv.zip to C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\UCDP\\ged201-csv.zip\r\n", + "\n" ] } ], @@ -112,8 +115,8 @@ "metadata": {}, "outputs": [], "source": [ - "conflict_gdf = gpd.read_file(os.path.join(out_dir, 'conflict_gdf.shp'))\n", - "selected_polygons_gdf = gpd.read_file(os.path.join(out_dir, 'selected_polygons_gdf.shp'))" + "conflict_gdf = gpd.read_file(os.path.join(out_dir, 'selected_conflicts.shp'))\n", + "selected_polygons_gdf = gpd.read_file(os.path.join(out_dir, 'selected_polygons.shp'))" ] }, { @@ -166,7 +169,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -181,131 +184,131 @@ "entering year 2000\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2000\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2000\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2000\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2000\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2000\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2000\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2000\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2000\n", "\n", "entering year 2001\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2001\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2001\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2001\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2001\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2001\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2001\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2001\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2001\n", "\n", "entering year 2002\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2002\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2002\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2002\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2002\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2002\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2002\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2002\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2002\n", "\n", "entering year 2003\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2003\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2003\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2003\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2003\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2003\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2003\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2003\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2003\n", "\n", "entering year 2004\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2004\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2004\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2004\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2004\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2004\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2004\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2004\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2004\n", "\n", "entering year 2005\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2005\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2005\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2005\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2005\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2005\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2005\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2005\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2005\n", "\n", "entering year 2006\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2006\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2006\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2006\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2006\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2006\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2006\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2006\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2006\n", "\n", "entering year 2007\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2007\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2007\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2007\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2007\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2007\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2007\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2007\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2007\n", "\n", "entering year 2008\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2008\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2008\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2008\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2008\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2008\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2008\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2008\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2008\n", "\n", "entering year 2009\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2009\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2009\n" + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2009\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2009\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2009\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2009\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2009\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2009\n", "\n", "entering year 2010\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2010\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2010\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2010\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2010\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2010\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2010\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2010\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2010\n", "\n", "entering year 2011\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2011\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2011\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2011\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2011\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2011\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2011\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2011\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2011\n", "\n", "entering year 2012\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2012\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2012\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2012\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2012\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2012\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2012\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2012\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2012\n", "\n", "entering year 2013\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2013\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2013\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2013\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2013\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2013\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2013\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2013\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2013\n", "\n", "entering year 2014\n", "\n", "listing the geometry of all geographical units\n", - "calculating mean total_evaporation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2014\n", - "calculating mean precipitation per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2014\n", - "calculating mean temperature per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2014\n", - "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\irrWaterDemand.nc for year 2014\n", + "calculating mean total_evaporation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\totalEvaporation_monthTot_output_2000_2015_Africa_yearmean.nc for year 2014\n", + "calculating mean precipitation per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\precipitation_monthTot_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2014\n", + "calculating mean temperature per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\temperature_monthAvg_output_2000-01-31_to_2015-12-31_Africa_yearmean.nc for year 2014\n", + "calculating mean irr_water_demand per aggregation unit from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\irrWaterDemand.nc for year 2014\n", "...reading data DONE\n", "\n", - "saving XY data by default to file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\XY.npy\n", + "saving XY data by default to file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\XY.npy\n", "\n", "number of data points including missing values: 4110\n", "number of data points excluding missing values: 4005\n", @@ -326,7 +329,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -335,7 +338,7 @@ "True" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -347,9 +350,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3.7.9 64-bit ('conflict_model': conda)", + "display_name": "Python 3", "language": "python", - "name": "python37964bitconflictmodelconda0a7cb69c875e4f578f0c3bf47b804900" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -361,7 +364,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.9" + "version": "3.7.8" } }, "nbformat": 4, diff --git a/example/nb03_model_execution_and_evaluation.ipynb b/example/nb03_model_execution_and_evaluation.ipynb index 52da967..b88263e 100644 --- a/example/nb03_model_execution_and_evaluation.ipynb +++ b/example/nb03_model_execution_and_evaluation.ipynb @@ -13,7 +13,7 @@ "metadata": {}, "outputs": [], "source": [ - "from conflict_model import utils, pipeline, evaluation, plots\n", + "from copro import utils, pipeline, evaluation, plots\n", "\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", @@ -42,8 +42,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "Python version: 3.7.9 (default, Aug 31 2020, 17:10:11) [MSC v.1916 64 bit (AMD64)]\n", - "conflict_model version: 0.0.4b2\n", + "Python version: 3.7.8 | packaged by conda-forge | (default, Jul 31 2020, 01:53:57) [MSC v.1916 64 bit (AMD64)]\n", + "copro version: 0.0.5\n", "geopandas version: 0.8.0\n", "xarray version: 0.15.1\n", "rasterio version: 1.1.0\n", @@ -51,7 +51,7 @@ "numpy version: 1.18.1\n", "scikit-learn version: 0.23.2\n", "matplotlib version: 3.2.1\n", - "seaborn version: 0.10.1\n", + "seaborn version: 0.11.0\n", "rasterstats version: 0.14.0\n" ] } @@ -99,7 +99,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "saving output to folder C:\\Users\\Icke\\_code\\conflict_model\\example\\OUT\n" + "saving output to folder C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\OUT\n", + "\n", + "no conflict file was specified, hence downloading data from http://ucdp.uu.se/downloads/ged/ged201-csv.zip to C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\UCDP\\ged201-csv.zip\r\n", + "\n" ] } ], @@ -138,7 +141,7 @@ { "data": { "text/plain": [ - "'C:\\\\Users\\\\Icke\\\\_code\\\\conflict_model\\\\example\\\\example_data\\\\XY.npy'" + "'C:\\\\Users\\\\hoch0001\\\\Documents\\\\_code\\\\copro\\\\example\\\\example_data\\\\XY.npy'" ] }, "execution_count": 6, @@ -163,8 +166,8 @@ "metadata": {}, "outputs": [], "source": [ - "conflict_gdf = gpd.read_file(os.path.join(out_dir, 'conflict_gdf.shp'))\n", - "selected_polygons_gdf = gpd.read_file(os.path.join(out_dir, 'selected_polygons_gdf.shp'))" + "conflict_gdf = gpd.read_file(os.path.join(out_dir, 'selected_conflicts.shp'))\n", + "selected_polygons_gdf = gpd.read_file(os.path.join(out_dir, 'selected_polygons.shp'))" ] }, { @@ -202,7 +205,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "loading XY data from file C:\\Users\\Icke\\_code\\conflict_model\\example\\example_data\\XY.npy\r\n", + "loading XY data from file C:\\Users\\hoch0001\\Documents\\_code\\copro\\example\\example_data\\XY.npy\r\n", "\n", "number of data points including missing values: 4110\n", "number of data points excluding missing values: 4005\n", @@ -231,7 +234,7 @@ "output_type": "stream", "text": [ "chosen scaling method is QuantileTransformer()\n", - "chosen ML model is KNeighborsClassifier(n_neighbors=10, weights='distance')\n" + "chosen ML model is RandomForestClassifier(class_weight={1: 100}, n_estimators=1000)\n" ] } ], @@ -255,9 +258,7 @@ "outputs": [], "source": [ "out_X_df = evaluation.init_out_df()\n", - "out_X1_df = evaluation.init_out_df()\n", - "out_y_df = evaluation.init_out_df()\n", - "out_y1_df = evaluation.init_out_df()" + "out_y_df = evaluation.init_out_df()" ] }, { @@ -298,55 +299,32 @@ "name": "stdout", "output_type": "stream", "text": [ - "run 1 of 50\r\n", + "run 1 of 50\n", "\n", - "### USING ALL DATA ###\r\n", - "\n", - "fitting and transforming X\r\n", + "### USING ALL DATA ###\n", "\n", - "splitting both X and Y in train and test data\r\n", + "fitting and transforming X\n", "\n", - "Accuracy: 0.852" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "No handles with labels found to put in legend.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "splitting both X and Y in train and test data\n", "\n", - "Precision: 0.551\n", - "Recall: 0.312\n", - "F1 score: 0.399\n", - "Brier loss score: 0.113\n", - "Cohen-Kappa score: 0.322\n", - "ROC AUC score 0.781\n", + "Accuracy: 0.846\n", + "Precision: 0.477\n", + "Recall: 0.289\n", + "F1 score: 0.360\n", + "Brier loss score: 0.107\n", + "Cohen-Kappa score: 0.278\n", + "ROC AUC score 0.813\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.88 0.95 0.92 1013\n", - " 1 0.55 0.31 0.40 189\n", + " 0 0.88 0.94 0.91 1022\n", + " 1 0.48 0.29 0.36 180\n", "\n", " accuracy 0.85 1202\n", - " macro avg 0.72 0.63 0.66 1202\n", - "weighted avg 0.83 0.85 0.83 1202\n", - "\n", - "\n", - "run 2 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", - "\n", - "fitting and transforming X\r\n", - "\n", - "splitting both X and Y in train and test data\r\n", + " macro avg 0.68 0.62 0.64 1202\n", + "weighted avg 0.82 0.85 0.83 1202\n", "\n", - "Accuracy: 0.843" + "\n" ] }, { @@ -360,22 +338,30 @@ "name": "stdout", "output_type": "stream", "text": [ + "run 2 of 50\n", "\n", - "Precision: 0.530\n", - "Recall: 0.311\n", - "F1 score: 0.392\n", - "Brier loss score: 0.117\n", - "Cohen-Kappa score: 0.309\n", - "ROC AUC score 0.773\n", + "### USING ALL DATA ###\n", + "\n", + "fitting and transforming X\n", + "\n", + "splitting both X and Y in train and test data\n", + "\n", + "Accuracy: 0.858\n", + "Precision: 0.593\n", + "Recall: 0.273\n", + "F1 score: 0.374\n", + "Brier loss score: 0.107\n", + "Cohen-Kappa score: 0.306\n", + "ROC AUC score 0.820\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.88 0.95 0.91 1006\n", - " 1 0.53 0.31 0.39 196\n", + " 0 0.88 0.97 0.92 1015\n", + " 1 0.59 0.27 0.37 187\n", "\n", - " accuracy 0.84 1202\n", - " macro avg 0.70 0.63 0.65 1202\n", - "weighted avg 0.82 0.84 0.83 1202\n", + " accuracy 0.86 1202\n", + " macro avg 0.74 0.62 0.65 1202\n", + "weighted avg 0.83 0.86 0.83 1202\n", "\n", "\n" ] @@ -391,41 +377,32 @@ "name": "stdout", "output_type": "stream", "text": [ - "run 3 of 50\r\n", + "run 3 of 50\n", "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.860\n", - "Precision: 0.509\n", - "Recall: 0.318\n", - "F1 score: 0.391\n", - "Brier loss score: 0.107\n", - "Cohen-Kappa score: 0.317\n", - "ROC AUC score 0.781\n", + "Accuracy: 0.846\n", + "Precision: 0.514\n", + "Recall: 0.203\n", + "F1 score: 0.291\n", + "Brier loss score: 0.108\n", + "Cohen-Kappa score: 0.223\n", + "ROC AUC score 0.807\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.89 0.95 0.92 1032\n", - " 1 0.51 0.32 0.39 170\n", - "\n", - " accuracy 0.86 1202\n", - " macro avg 0.70 0.63 0.66 1202\n", - "weighted avg 0.84 0.86 0.85 1202\n", - "\n", - "\n", - "run 4 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", - "\n", - "fitting and transforming X\r\n", + " 0 0.87 0.96 0.91 1015\n", + " 1 0.51 0.20 0.29 187\n", "\n", - "splitting both X and Y in train and test data\r\n", + " accuracy 0.85 1202\n", + " macro avg 0.69 0.58 0.60 1202\n", + "weighted avg 0.81 0.85 0.82 1202\n", "\n", - "Accuracy: 0.844" + "\n" ] }, { @@ -439,22 +416,30 @@ "name": "stdout", "output_type": "stream", "text": [ + "run 4 of 50\n", "\n", - "Precision: 0.450\n", - "Recall: 0.277\n", - "F1 score: 0.343\n", + "### USING ALL DATA ###\n", + "\n", + "fitting and transforming X\n", + "\n", + "splitting both X and Y in train and test data\n", + "\n", + "Accuracy: 0.851\n", + "Precision: 0.543\n", + "Recall: 0.273\n", + "F1 score: 0.363\n", "Brier loss score: 0.113\n", - "Cohen-Kappa score: 0.260\n", - "ROC AUC score 0.776\n", + "Cohen-Kappa score: 0.289\n", + "ROC AUC score 0.797\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.88 0.94 0.91 1025\n", - " 1 0.45 0.28 0.34 177\n", + " 0 0.88 0.96 0.92 1015\n", + " 1 0.54 0.27 0.36 187\n", "\n", - " accuracy 0.84 1202\n", - " macro avg 0.67 0.61 0.63 1202\n", - "weighted avg 0.82 0.84 0.83 1202\n", + " accuracy 0.85 1202\n", + " macro avg 0.71 0.62 0.64 1202\n", + "weighted avg 0.83 0.85 0.83 1202\n", "\n", "\n" ] @@ -478,24 +463,37 @@ "\n", "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.856\n", - "Precision: 0.565\n", - "Recall: 0.326\n", - "F1 score: 0.414\n", - "Brier loss score: 0.105\n", - "Cohen-Kappa score: 0.338\n", - "ROC AUC score 0.804\n", + "Accuracy: 0.857\n", + "Precision: 0.546\n", + "Recall: 0.293\n", + "F1 score: 0.381\n", + "Brier loss score: 0.102\n", + "Cohen-Kappa score: 0.309\n", + "ROC AUC score 0.828\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.88 0.95 0.92 1015\n", - " 1 0.56 0.33 0.41 187\n", + " 0 0.88 0.96 0.92 1021\n", + " 1 0.55 0.29 0.38 181\n", "\n", " accuracy 0.86 1202\n", - " macro avg 0.72 0.64 0.67 1202\n", - "weighted avg 0.84 0.86 0.84 1202\n", - "\n", + " macro avg 0.72 0.62 0.65 1202\n", + "weighted avg 0.83 0.86 0.84 1202\n", "\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No handles with labels found to put in legend.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "run 6 of 50\n", "\n", "### USING ALL DATA ###\n", @@ -504,22 +502,22 @@ "\n", "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.849\n", - "Precision: 0.512\n", - "Recall: 0.335\n", - "F1 score: 0.405\n", - "Brier loss score: 0.106\n", - "Cohen-Kappa score: 0.323\n", + "Accuracy: 0.840\n", + "Precision: 0.549\n", + "Recall: 0.277\n", + "F1 score: 0.368\n", + "Brier loss score: 0.117\n", + "Cohen-Kappa score: 0.288\n", "ROC AUC score 0.817\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.89 0.94 0.91 1017\n", - " 1 0.51 0.34 0.41 185\n", + " 0 0.87 0.95 0.91 1000\n", + " 1 0.55 0.28 0.37 202\n", "\n", - " accuracy 0.85 1202\n", - " macro avg 0.70 0.64 0.66 1202\n", - "weighted avg 0.83 0.85 0.84 1202\n", + " accuracy 0.84 1202\n", + " macro avg 0.71 0.62 0.64 1202\n", + "weighted avg 0.81 0.84 0.82 1202\n", "\n", "\n" ] @@ -528,7 +526,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "No handles with labels found to put in legend.\n", "No handles with labels found to put in legend.\n" ] }, @@ -544,24 +541,37 @@ "\n", "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.834\n", - "Precision: 0.571\n", - "Recall: 0.227\n", - "F1 score: 0.325\n", - "Brier loss score: 0.122\n", - "Cohen-Kappa score: 0.250\n", - "ROC AUC score 0.773\n", + "Accuracy: 0.856\n", + "Precision: 0.534\n", + "Recall: 0.263\n", + "F1 score: 0.352\n", + "Brier loss score: 0.106\n", + "Cohen-Kappa score: 0.282\n", + "ROC AUC score 0.803\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.85 0.96 0.91 991\n", - " 1 0.57 0.23 0.33 211\n", - "\n", - " accuracy 0.83 1202\n", - " macro avg 0.71 0.60 0.62 1202\n", - "weighted avg 0.80 0.83 0.80 1202\n", + " 0 0.88 0.96 0.92 1023\n", + " 1 0.53 0.26 0.35 179\n", "\n", + " accuracy 0.86 1202\n", + " macro avg 0.71 0.61 0.64 1202\n", + "weighted avg 0.83 0.86 0.83 1202\n", "\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No handles with labels found to put in legend.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "run 8 of 50\n", "\n", "### USING ALL DATA ###\n", @@ -570,22 +580,22 @@ "\n", "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.843\n", - "Precision: 0.505\n", - "Recall: 0.258\n", - "F1 score: 0.341\n", - "Brier loss score: 0.109\n", - "Cohen-Kappa score: 0.263\n", - "ROC AUC score 0.807\n", + "Accuracy: 0.862\n", + "Precision: 0.548\n", + "Recall: 0.291\n", + "F1 score: 0.381\n", + "Brier loss score: 0.099\n", + "Cohen-Kappa score: 0.311\n", + "ROC AUC score 0.837\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.87 0.95 0.91 1012\n", - " 1 0.51 0.26 0.34 190\n", + " 0 0.89 0.96 0.92 1027\n", + " 1 0.55 0.29 0.38 175\n", "\n", - " accuracy 0.84 1202\n", - " macro avg 0.69 0.61 0.63 1202\n", - "weighted avg 0.81 0.84 0.82 1202\n", + " accuracy 0.86 1202\n", + " macro avg 0.72 0.63 0.65 1202\n", + "weighted avg 0.84 0.86 0.84 1202\n", "\n", "\n" ] @@ -594,7 +604,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "No handles with labels found to put in legend.\n", "No handles with labels found to put in legend.\n" ] }, @@ -602,39 +611,32 @@ "name": "stdout", "output_type": "stream", "text": [ - "run 9 of 50\r\n", + "run 9 of 50\n", "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.854\n", - "Precision: 0.505\n", - "Recall: 0.260\n", - "F1 score: 0.343\n", - "Brier loss score: 0.105\n", - "Cohen-Kappa score: 0.270\n", - "ROC AUC score 0.806\n", + "Accuracy: 0.855\n", + "Precision: 0.608\n", + "Recall: 0.251\n", + "F1 score: 0.356\n", + "Brier loss score: 0.106\n", + "Cohen-Kappa score: 0.289\n", + "ROC AUC score 0.832\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.88 0.96 0.92 1025\n", - " 1 0.51 0.26 0.34 177\n", - "\n", - " accuracy 0.85 1202\n", - " macro avg 0.69 0.61 0.63 1202\n", - "weighted avg 0.83 0.85 0.83 1202\n", - "\n", - "\n", - "run 10 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + " 0 0.87 0.97 0.92 1011\n", + " 1 0.61 0.25 0.36 191\n", "\n", - "fitting and transforming X\r\n", + " accuracy 0.86 1202\n", + " macro avg 0.74 0.61 0.64 1202\n", + "weighted avg 0.83 0.86 0.83 1202\n", "\n", - "splitting both X and Y in train and test data\r\n" + "\n" ] }, { @@ -648,26 +650,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "\n", - "Accuracy: 0.851\n", - "Precision: 0.521\n", - "Recall: 0.332\n", - "F1 score: 0.405\n", - "Brier loss score: 0.106\n", - "Cohen-Kappa score: 0.325\n", - "ROC AUC score 0.818\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.89 0.94 0.91 1018\n", - " 1 0.52 0.33 0.41 184\n", - "\n", - " accuracy 0.85 1202\n", - " macro avg 0.70 0.64 0.66 1202\n", - "weighted avg 0.83 0.85 0.84 1202\n", - "\n", - "\n", - "run 11 of 50\n", + "run 10 of 50\n", "\n", "### USING ALL DATA ###\n", "\n", @@ -675,22 +658,22 @@ "\n", "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.844\n", - "Precision: 0.539\n", - "Recall: 0.282\n", - "F1 score: 0.370\n", - "Brier loss score: 0.115\n", - "Cohen-Kappa score: 0.291\n", - "ROC AUC score 0.775\n", + "Accuracy: 0.859\n", + "Precision: 0.494\n", + "Recall: 0.249\n", + "F1 score: 0.331\n", + "Brier loss score: 0.101\n", + "Cohen-Kappa score: 0.261\n", + "ROC AUC score 0.821\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.87 0.95 0.91 1007\n", - " 1 0.54 0.28 0.37 195\n", + " 0 0.89 0.96 0.92 1033\n", + " 1 0.49 0.25 0.33 169\n", "\n", - " accuracy 0.84 1202\n", - " macro avg 0.71 0.62 0.64 1202\n", - "weighted avg 0.82 0.84 0.82 1202\n", + " accuracy 0.86 1202\n", + " macro avg 0.69 0.60 0.63 1202\n", + "weighted avg 0.83 0.86 0.84 1202\n", "\n", "\n" ] @@ -706,15 +689,32 @@ "name": "stdout", "output_type": "stream", "text": [ - "run 12 of 50\r\n", + "run 11 of 50\n", + "\n", + "### USING ALL DATA ###\n", + "\n", + "fitting and transforming X\n", + "\n", + "splitting both X and Y in train and test data\n", + "\n", + "Accuracy: 0.849\n", + "Precision: 0.510\n", + "Recall: 0.266\n", + "F1 score: 0.350\n", + "Brier loss score: 0.107\n", + "Cohen-Kappa score: 0.274\n", + "ROC AUC score 0.824\n", "\n", - "### USING ALL DATA ###\r\n", + " precision recall f1-score support\n", "\n", - "fitting and transforming X\r\n", + " 0 0.88 0.95 0.91 1018\n", + " 1 0.51 0.27 0.35 184\n", "\n", - "splitting both X and Y in train and test data\r\n", + " accuracy 0.85 1202\n", + " macro avg 0.69 0.61 0.63 1202\n", + "weighted avg 0.82 0.85 0.83 1202\n", "\n", - "Accuracy: 0.864\n" + "\n" ] }, { @@ -728,47 +728,30 @@ "name": "stdout", "output_type": "stream", "text": [ - "Precision: 0.606\n", - "Recall: 0.310\n", - "F1 score: 0.410\n", - "Brier loss score: 0.103\n", - "Cohen-Kappa score: 0.342\n", - "ROC AUC score 0.809\n", + "run 12 of 50\n", "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.89 0.96 0.92 1018\n", - " 1 0.61 0.31 0.41 184\n", - "\n", - " accuracy 0.86 1202\n", - " macro avg 0.75 0.64 0.67 1202\n", - "weighted avg 0.84 0.86 0.84 1202\n", - "\n", - "\n", - "run 13 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.849\n", - "Precision: 0.534\n", - "Recall: 0.251\n", - "F1 score: 0.342\n", - "Brier loss score: 0.115\n", - "Cohen-Kappa score: 0.269\n", - "ROC AUC score 0.775\n", + "Accuracy: 0.851\n", + "Precision: 0.595\n", + "Recall: 0.242\n", + "F1 score: 0.344\n", + "Brier loss score: 0.114\n", + "Cohen-Kappa score: 0.277\n", + "ROC AUC score 0.799\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.87 0.96 0.91 1015\n", - " 1 0.53 0.25 0.34 187\n", + " 0 0.87 0.97 0.92 1008\n", + " 1 0.59 0.24 0.34 194\n", "\n", " accuracy 0.85 1202\n", - " macro avg 0.70 0.61 0.63 1202\n", - "weighted avg 0.82 0.85 0.83 1202\n", + " macro avg 0.73 0.61 0.63 1202\n", + "weighted avg 0.82 0.85 0.82 1202\n", "\n", "\n" ] @@ -784,15 +767,32 @@ "name": "stdout", "output_type": "stream", "text": [ - "run 14 of 50\r\n", + "run 13 of 50\n", + "\n", + "### USING ALL DATA ###\n", + "\n", + "fitting and transforming X\n", + "\n", + "splitting both X and Y in train and test data\n", + "\n", + "Accuracy: 0.844\n", + "Precision: 0.581\n", + "Recall: 0.248\n", + "F1 score: 0.347\n", + "Brier loss score: 0.117\n", + "Cohen-Kappa score: 0.274\n", + "ROC AUC score 0.805\n", "\n", - "### USING ALL DATA ###\r\n", + " precision recall f1-score support\n", "\n", - "fitting and transforming X\r\n", + " 0 0.86 0.96 0.91 1000\n", + " 1 0.58 0.25 0.35 202\n", "\n", - "splitting both X and Y in train and test data\r\n", + " accuracy 0.84 1202\n", + " macro avg 0.72 0.61 0.63 1202\n", + "weighted avg 0.82 0.84 0.82 1202\n", "\n", - "Accuracy: 0.854\n" + "\n" ] }, { @@ -806,47 +806,30 @@ "name": "stdout", "output_type": "stream", "text": [ - "Precision: 0.508\n", - "Recall: 0.343\n", - "F1 score: 0.409\n", - "Brier loss score: 0.110\n", - "Cohen-Kappa score: 0.329\n", - "ROC AUC score 0.785\n", - "\n", - " precision recall f1-score support\n", + "run 14 of 50\n", "\n", - " 0 0.89 0.94 0.92 1024\n", - " 1 0.51 0.34 0.41 178\n", + "### USING ALL DATA ###\n", "\n", - " accuracy 0.85 1202\n", - " macro avg 0.70 0.64 0.66 1202\n", - "weighted avg 0.84 0.85 0.84 1202\n", + "fitting and transforming X\n", "\n", + "splitting both X and Y in train and test data\n", "\n", - "run 15 of 50\r\n", + "Accuracy: 0.860\n", + "Precision: 0.593\n", + "Recall: 0.277\n", + "F1 score: 0.378\n", + "Brier loss score: 0.102\n", + "Cohen-Kappa score: 0.311\n", + "ROC AUC score 0.832\n", "\n", - "### USING ALL DATA ###\r\n", + " precision recall f1-score support\n", "\n", - "fitting and transforming X\r\n", - "\n", - "splitting both X and Y in train and test data\r\n", - "\n", - "Accuracy: 0.856\n", - "Precision: 0.535\n", - "Recall: 0.300\n", - "F1 score: 0.384\n", - "Brier loss score: 0.108\n", - "Cohen-Kappa score: 0.310\n", - "ROC AUC score 0.785\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.89 0.95 0.92 1022\n", - " 1 0.53 0.30 0.38 180\n", + " 0 0.88 0.97 0.92 1018\n", + " 1 0.59 0.28 0.38 184\n", "\n", " accuracy 0.86 1202\n", - " macro avg 0.71 0.63 0.65 1202\n", - "weighted avg 0.83 0.86 0.84 1202\n", + " macro avg 0.74 0.62 0.65 1202\n", + "weighted avg 0.84 0.86 0.84 1202\n", "\n", "\n" ] @@ -862,15 +845,32 @@ "name": "stdout", "output_type": "stream", "text": [ - "run 16 of 50\r\n", + "run 15 of 50\n", + "\n", + "### USING ALL DATA ###\n", + "\n", + "fitting and transforming X\n", + "\n", + "splitting both X and Y in train and test data\n", + "\n", + "Accuracy: 0.852\n", + "Precision: 0.513\n", + "Recall: 0.217\n", + "F1 score: 0.305\n", + "Brier loss score: 0.107\n", + "Cohen-Kappa score: 0.237\n", + "ROC AUC score 0.811\n", "\n", - "### USING ALL DATA ###\r\n", + " precision recall f1-score support\n", "\n", - "fitting and transforming X\r\n", + " 0 0.87 0.96 0.92 1022\n", + " 1 0.51 0.22 0.30 180\n", "\n", - "splitting both X and Y in train and test data\r\n", + " accuracy 0.85 1202\n", + " macro avg 0.69 0.59 0.61 1202\n", + "weighted avg 0.82 0.85 0.83 1202\n", "\n", - "Accuracy: 0.858\n" + "\n" ] }, { @@ -884,47 +884,30 @@ "name": "stdout", "output_type": "stream", "text": [ - "Precision: 0.514\n", - "Recall: 0.322\n", - "F1 score: 0.396\n", - "Brier loss score: 0.108\n", - "Cohen-Kappa score: 0.320\n", - "ROC AUC score 0.770\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.89 0.95 0.92 1028\n", - " 1 0.51 0.32 0.40 174\n", - "\n", - " accuracy 0.86 1202\n", - " macro avg 0.70 0.64 0.66 1202\n", - "weighted avg 0.84 0.86 0.84 1202\n", - "\n", + "run 16 of 50\n", "\n", - "run 17 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.868\n", - "Precision: 0.533\n", - "Recall: 0.337\n", - "F1 score: 0.413\n", - "Brier loss score: 0.099\n", - "Cohen-Kappa score: 0.343\n", - "ROC AUC score 0.812\n", + "Accuracy: 0.859\n", + "Precision: 0.571\n", + "Recall: 0.284\n", + "F1 score: 0.380\n", + "Brier loss score: 0.106\n", + "Cohen-Kappa score: 0.310\n", + "ROC AUC score 0.817\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.90 0.95 0.93 1036\n", - " 1 0.53 0.34 0.41 166\n", + " 0 0.88 0.96 0.92 1019\n", + " 1 0.57 0.28 0.38 183\n", "\n", - " accuracy 0.87 1202\n", - " macro avg 0.72 0.65 0.67 1202\n", - "weighted avg 0.85 0.87 0.85 1202\n", + " accuracy 0.86 1202\n", + " macro avg 0.73 0.62 0.65 1202\n", + "weighted avg 0.83 0.86 0.84 1202\n", "\n", "\n" ] @@ -940,15 +923,32 @@ "name": "stdout", "output_type": "stream", "text": [ - "run 18 of 50\r\n", + "run 17 of 50\n", + "\n", + "### USING ALL DATA ###\n", + "\n", + "fitting and transforming X\n", "\n", - "### USING ALL DATA ###\r\n", + "splitting both X and Y in train and test data\n", + "\n", + "Accuracy: 0.855\n", + "Precision: 0.522\n", + "Recall: 0.264\n", + "F1 score: 0.351\n", + "Brier loss score: 0.102\n", + "Cohen-Kappa score: 0.279\n", + "ROC AUC score 0.835\n", + "\n", + " precision recall f1-score support\n", "\n", - "fitting and transforming X\r\n", + " 0 0.88 0.96 0.92 1024\n", + " 1 0.52 0.26 0.35 178\n", "\n", - "splitting both X and Y in train and test data\r\n", + " accuracy 0.86 1202\n", + " macro avg 0.70 0.61 0.63 1202\n", + "weighted avg 0.83 0.86 0.83 1202\n", "\n", - "Accuracy: 0.850\n" + "\n" ] }, { @@ -962,46 +962,29 @@ "name": "stdout", "output_type": "stream", "text": [ - "Precision: 0.535\n", - "Recall: 0.283\n", - "F1 score: 0.371\n", - "Brier loss score: 0.107\n", - "Cohen-Kappa score: 0.295\n", - "ROC AUC score 0.805\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.88 0.95 0.92 1015\n", - " 1 0.54 0.28 0.37 187\n", - "\n", - " accuracy 0.85 1202\n", - " macro avg 0.71 0.62 0.64 1202\n", - "weighted avg 0.83 0.85 0.83 1202\n", - "\n", + "run 18 of 50\n", "\n", - "run 19 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.856\n", - "Precision: 0.513\n", - "Recall: 0.335\n", - "F1 score: 0.405\n", + "Accuracy: 0.862\n", + "Precision: 0.558\n", + "Recall: 0.273\n", + "F1 score: 0.366\n", "Brier loss score: 0.105\n", - "Cohen-Kappa score: 0.328\n", - "ROC AUC score 0.798\n", + "Cohen-Kappa score: 0.299\n", + "ROC AUC score 0.810\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.89 0.95 0.92 1026\n", - " 1 0.51 0.34 0.41 176\n", + " 0 0.89 0.96 0.92 1026\n", + " 1 0.56 0.27 0.37 176\n", "\n", " accuracy 0.86 1202\n", - " macro avg 0.70 0.64 0.66 1202\n", + " macro avg 0.72 0.62 0.64 1202\n", "weighted avg 0.84 0.86 0.84 1202\n", "\n", "\n" @@ -1018,13 +1001,32 @@ "name": "stdout", "output_type": "stream", "text": [ - "run 20 of 50\r\n", + "run 19 of 50\n", + "\n", + "### USING ALL DATA ###\n", + "\n", + "fitting and transforming X\n", + "\n", + "splitting both X and Y in train and test data\n", + "\n", + "Accuracy: 0.854\n", + "Precision: 0.568\n", + "Recall: 0.266\n", + "F1 score: 0.362\n", + "Brier loss score: 0.109\n", + "Cohen-Kappa score: 0.292\n", + "ROC AUC score 0.817\n", + "\n", + " precision recall f1-score support\n", "\n", - "### USING ALL DATA ###\r\n", + " 0 0.88 0.96 0.92 1014\n", + " 1 0.57 0.27 0.36 188\n", "\n", - "fitting and transforming X\r\n", + " accuracy 0.85 1202\n", + " macro avg 0.72 0.61 0.64 1202\n", + "weighted avg 0.83 0.85 0.83 1202\n", "\n", - "splitting both X and Y in train and test data\r\n" + "\n" ] }, { @@ -1038,41 +1040,38 @@ "name": "stdout", "output_type": "stream", "text": [ + "run 20 of 50\n", "\n", - "Accuracy: 0.841\n", - "Precision: 0.538\n", - "Recall: 0.315\n", - "F1 score: 0.397\n", - "Brier loss score: 0.116\n", - "Cohen-Kappa score: 0.313\n", - "ROC AUC score 0.795\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.87 0.95 0.91 1002\n", - " 1 0.54 0.32 0.40 200\n", + "### USING ALL DATA ###\n", "\n", - " accuracy 0.84 1202\n", - " macro avg 0.71 0.63 0.65 1202\n", - "weighted avg 0.82 0.84 0.82 1202\n", + "fitting and transforming X\n", "\n", + "splitting both X and Y in train and test data\n", "\n", - "run 21 of 50\r\n", + "Accuracy: 0.853\n", + "Precision: 0.608\n", + "Recall: 0.312\n", + "F1 score: 0.412\n", + "Brier loss score: 0.109\n", + "Cohen-Kappa score: 0.338\n", + "ROC AUC score 0.828\n", "\n", - "### USING ALL DATA ###\r\n", + " precision recall f1-score support\n", "\n", - "fitting and transforming X\r\n", + " 0 0.88 0.96 0.92 1003\n", + " 1 0.61 0.31 0.41 199\n", "\n", - "splitting both X and Y in train and test data\r\n", + " accuracy 0.85 1202\n", + " macro avg 0.74 0.64 0.66 1202\n", + "weighted avg 0.83 0.85 0.83 1202\n", "\n", - "Accuracy: 0.837" + "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "No handles with labels found to put in legend.\n", "No handles with labels found to put in legend.\n" ] }, @@ -1080,57 +1079,31 @@ "name": "stdout", "output_type": "stream", "text": [ + "run 21 of 50\n", "\n", - "Precision: 0.500\n", - "Recall: 0.250\n", - "F1 score: 0.333\n", - "Brier loss score: 0.117\n", - "Cohen-Kappa score: 0.252\n", - "ROC AUC score 0.783\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.87 0.95 0.91 1006\n", - " 1 0.50 0.25 0.33 196\n", - "\n", - " accuracy 0.84 1202\n", - " macro avg 0.68 0.60 0.62 1202\n", - "weighted avg 0.81 0.84 0.81 1202\n", - "\n", - "\n", - "run 22 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.832\n", - "Precision: 0.482\n", - "Recall: 0.201\n", - "F1 score: 0.284\n", - "Brier loss score: 0.123\n", - "Cohen-Kappa score: 0.206\n", - "ROC AUC score 0.757\n", + "Accuracy: 0.864\n", + "Precision: 0.624\n", + "Recall: 0.312\n", + "F1 score: 0.416\n", + "Brier loss score: 0.100\n", + "Cohen-Kappa score: 0.349\n", + "ROC AUC score 0.846\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.86 0.96 0.90 1003\n", - " 1 0.48 0.20 0.28 199\n", - "\n", - " accuracy 0.83 1202\n", - " macro avg 0.67 0.58 0.59 1202\n", - "weighted avg 0.80 0.83 0.80 1202\n", - "\n", + " 0 0.88 0.97 0.92 1016\n", + " 1 0.62 0.31 0.42 186\n", "\n", - "run 23 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", - "\n", - "fitting and transforming X\r\n", + " accuracy 0.86 1202\n", + " macro avg 0.75 0.64 0.67 1202\n", + "weighted avg 0.84 0.86 0.84 1202\n", "\n", - "splitting both X and Y in train and test data\r\n", "\n" ] }, @@ -1138,7 +1111,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "No handles with labels found to put in legend.\n", "No handles with labels found to put in legend.\n" ] }, @@ -1146,64 +1118,38 @@ "name": "stdout", "output_type": "stream", "text": [ - "Accuracy: 0.843\n", - "Precision: 0.532\n", - "Recall: 0.296\n", - "F1 score: 0.380\n", - "Brier loss score: 0.116\n", - "Cohen-Kappa score: 0.299\n", - "ROC AUC score 0.787\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.87 0.95 0.91 1006\n", - " 1 0.53 0.30 0.38 196\n", - "\n", - " accuracy 0.84 1202\n", - " macro avg 0.70 0.62 0.65 1202\n", - "weighted avg 0.82 0.84 0.82 1202\n", - "\n", - "\n", - "run 24 of 50\r\n", + "run 22 of 50\n", "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.857\n", - "Precision: 0.495\n", - "Recall: 0.310\n", - "F1 score: 0.381\n", - "Brier loss score: 0.105\n", - "Cohen-Kappa score: 0.305\n", - "ROC AUC score 0.787\n", + "Accuracy: 0.875\n", + "Precision: 0.533\n", + "Recall: 0.314\n", + "F1 score: 0.395\n", + "Brier loss score: 0.093\n", + "Cohen-Kappa score: 0.331\n", + "ROC AUC score 0.825\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.89 0.95 0.92 1031\n", - " 1 0.50 0.31 0.38 171\n", - "\n", - " accuracy 0.86 1202\n", - " macro avg 0.69 0.63 0.65 1202\n", - "weighted avg 0.84 0.86 0.84 1202\n", - "\n", + " 0 0.90 0.96 0.93 1046\n", + " 1 0.53 0.31 0.40 156\n", "\n", - "run 25 of 50\r\n", + " accuracy 0.88 1202\n", + " macro avg 0.72 0.64 0.66 1202\n", + "weighted avg 0.86 0.88 0.86 1202\n", "\n", - "### USING ALL DATA ###\r\n", - "\n", - "fitting and transforming X\r\n", - "\n", - "splitting both X and Y in train and test data\r\n" + "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "No handles with labels found to put in legend.\n", "No handles with labels found to put in legend.\n" ] }, @@ -1211,56 +1157,31 @@ "name": "stdout", "output_type": "stream", "text": [ + "run 23 of 50\n", "\n", - "Accuracy: 0.835\n", - "Precision: 0.423\n", - "Recall: 0.242\n", - "F1 score: 0.308\n", - "Brier loss score: 0.112\n", - "Cohen-Kappa score: 0.222\n", - "ROC AUC score 0.786\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.87 0.94 0.91 1020\n", - " 1 0.42 0.24 0.31 182\n", - "\n", - " accuracy 0.84 1202\n", - " macro avg 0.65 0.59 0.61 1202\n", - "weighted avg 0.81 0.84 0.82 1202\n", - "\n", - "\n", - "run 26 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.856\n", - "Precision: 0.569\n", - "Recall: 0.310\n", - "F1 score: 0.401\n", - "Brier loss score: 0.109\n", - "Cohen-Kappa score: 0.328\n", - "ROC AUC score 0.797\n", + "Accuracy: 0.861\n", + "Precision: 0.671\n", + "Recall: 0.291\n", + "F1 score: 0.406\n", + "Brier loss score: 0.106\n", + "Cohen-Kappa score: 0.341\n", + "ROC AUC score 0.827\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.88 0.96 0.92 1015\n", - " 1 0.57 0.31 0.40 187\n", + " 0 0.88 0.97 0.92 1006\n", + " 1 0.67 0.29 0.41 196\n", "\n", " accuracy 0.86 1202\n", - " macro avg 0.73 0.63 0.66 1202\n", - "weighted avg 0.83 0.86 0.84 1202\n", - "\n", - "\n", - "run 27 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + " macro avg 0.77 0.63 0.66 1202\n", + "weighted avg 0.84 0.86 0.84 1202\n", "\n", - "fitting and transforming X\r\n", "\n" ] }, @@ -1268,7 +1189,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "No handles with labels found to put in legend.\n", "No handles with labels found to put in legend.\n" ] }, @@ -1276,57 +1196,32 @@ "name": "stdout", "output_type": "stream", "text": [ - "splitting both X and Y in train and test data\r\n", - "\n", - "Accuracy: 0.846\n", - "Precision: 0.481\n", - "Recall: 0.282\n", - "F1 score: 0.355\n", - "Brier loss score: 0.112\n", - "Cohen-Kappa score: 0.275\n", - "ROC AUC score 0.771\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.88 0.95 0.91 1021\n", - " 1 0.48 0.28 0.36 181\n", - "\n", - " accuracy 0.85 1202\n", - " macro avg 0.68 0.61 0.63 1202\n", - "weighted avg 0.82 0.85 0.83 1202\n", - "\n", + "run 24 of 50\n", "\n", - "run 28 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.858\n", - "Precision: 0.567\n", - "Recall: 0.279\n", - "F1 score: 0.374\n", - "Brier loss score: 0.108\n", - "Cohen-Kappa score: 0.304\n", - "ROC AUC score 0.776\n", + "Accuracy: 0.859\n", + "Precision: 0.558\n", + "Recall: 0.293\n", + "F1 score: 0.384\n", + "Brier loss score: 0.104\n", + "Cohen-Kappa score: 0.313\n", + "ROC AUC score 0.818\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.88 0.96 0.92 1019\n", - " 1 0.57 0.28 0.37 183\n", + " 0 0.88 0.96 0.92 1021\n", + " 1 0.56 0.29 0.38 181\n", "\n", " accuracy 0.86 1202\n", - " macro avg 0.72 0.62 0.65 1202\n", - "weighted avg 0.83 0.86 0.84 1202\n", - "\n", - "\n", - "run 29 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + " macro avg 0.72 0.63 0.65 1202\n", + "weighted avg 0.84 0.86 0.84 1202\n", "\n", - "fitting and transforming X\r\n" + "\n" ] }, { @@ -1340,51 +1235,30 @@ "name": "stdout", "output_type": "stream", "text": [ + "run 25 of 50\n", "\n", - "splitting both X and Y in train and test data\r\n", - "\n", - "Accuracy: 0.850\n", - "Precision: 0.561\n", - "Recall: 0.311\n", - "F1 score: 0.400\n", - "Brier loss score: 0.111\n", - "Cohen-Kappa score: 0.322\n", - "ROC AUC score 0.802\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.88 0.95 0.91 1009\n", - " 1 0.56 0.31 0.40 193\n", - "\n", - " accuracy 0.85 1202\n", - " macro avg 0.72 0.63 0.66 1202\n", - "weighted avg 0.83 0.85 0.83 1202\n", - "\n", - "\n", - "run 30 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.839\n", - "Precision: 0.505\n", - "Recall: 0.247\n", - "F1 score: 0.332\n", - "Brier loss score: 0.115\n", - "Cohen-Kappa score: 0.253\n", - "ROC AUC score 0.781\n", + "Accuracy: 0.854\n", + "Precision: 0.568\n", + "Recall: 0.287\n", + "F1 score: 0.382\n", + "Brier loss score: 0.108\n", + "Cohen-Kappa score: 0.309\n", + "ROC AUC score 0.820\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.87 0.95 0.91 1008\n", - " 1 0.51 0.25 0.33 194\n", + " 0 0.88 0.96 0.92 1014\n", + " 1 0.57 0.29 0.38 188\n", "\n", - " accuracy 0.84 1202\n", - " macro avg 0.69 0.60 0.62 1202\n", - "weighted avg 0.81 0.84 0.82 1202\n", + " accuracy 0.85 1202\n", + " macro avg 0.72 0.62 0.65 1202\n", + "weighted avg 0.83 0.85 0.83 1202\n", "\n", "\n" ] @@ -1393,8 +1267,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "No handles with labels found to put in legend.\n", - "No handles with labels found to put in legend.\n", "No handles with labels found to put in legend.\n" ] }, @@ -1402,55 +1274,68 @@ "name": "stdout", "output_type": "stream", "text": [ - "run 31 of 50\r\n", + "run 26 of 50\n", "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.849\n", - "Precision: 0.570\n", - "Recall: 0.311\n", - "F1 score: 0.403\n", - "Brier loss score: 0.117\n", - "Cohen-Kappa score: 0.325\n", - "ROC AUC score 0.784\n", + "Accuracy: 0.863\n", + "Precision: 0.552\n", + "Recall: 0.303\n", + "F1 score: 0.391\n", + "Brier loss score: 0.103\n", + "Cohen-Kappa score: 0.321\n", + "ROC AUC score 0.805\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.88 0.95 0.91 1006\n", - " 1 0.57 0.31 0.40 196\n", + " 0 0.89 0.96 0.92 1027\n", + " 1 0.55 0.30 0.39 175\n", "\n", - " accuracy 0.85 1202\n", + " accuracy 0.86 1202\n", " macro avg 0.72 0.63 0.66 1202\n", - "weighted avg 0.83 0.85 0.83 1202\n", - "\n", + "weighted avg 0.84 0.86 0.85 1202\n", "\n", - "run 32 of 50\r\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No handles with labels found to put in legend.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "run 27 of 50\n", "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.855\n", - "Precision: 0.500\n", - "Recall: 0.276\n", - "F1 score: 0.356\n", - "Brier loss score: 0.106\n", - "Cohen-Kappa score: 0.282\n", - "ROC AUC score 0.788\n", + "Accuracy: 0.859\n", + "Precision: 0.517\n", + "Recall: 0.260\n", + "F1 score: 0.346\n", + "Brier loss score: 0.101\n", + "Cohen-Kappa score: 0.276\n", + "ROC AUC score 0.817\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.89 0.95 0.92 1028\n", - " 1 0.50 0.28 0.36 174\n", + " 0 0.89 0.96 0.92 1029\n", + " 1 0.52 0.26 0.35 173\n", "\n", " accuracy 0.86 1202\n", - " macro avg 0.69 0.61 0.64 1202\n", + " macro avg 0.70 0.61 0.63 1202\n", "weighted avg 0.83 0.86 0.84 1202\n", "\n", "\n" @@ -1467,55 +1352,185 @@ "name": "stdout", "output_type": "stream", "text": [ - "run 33 of 50\r\n", + "run 28 of 50\n", "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.856\n", - "Precision: 0.531\n", - "Recall: 0.285\n", - "F1 score: 0.371\n", - "Brier loss score: 0.108\n", - "Cohen-Kappa score: 0.298\n", - "ROC AUC score 0.792\n", + "Accuracy: 0.852\n", + "Precision: 0.540\n", + "Recall: 0.254\n", + "F1 score: 0.346\n", + "Brier loss score: 0.106\n", + "Cohen-Kappa score: 0.274\n", + "ROC AUC score 0.814\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.88 0.96 0.92 1023\n", - " 1 0.53 0.28 0.37 179\n", + " 0 0.88 0.96 0.92 1017\n", + " 1 0.54 0.25 0.35 185\n", + "\n", + " accuracy 0.85 1202\n", + " macro avg 0.71 0.61 0.63 1202\n", + "weighted avg 0.82 0.85 0.83 1202\n", + "\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No handles with labels found to put in legend.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "run 29 of 50\n", + "\n", + "### USING ALL DATA ###\n", + "\n", + "fitting and transforming X\n", + "\n", + "splitting both X and Y in train and test data\n", + "\n", + "Accuracy: 0.838\n", + "Precision: 0.584\n", + "Recall: 0.216\n", + "F1 score: 0.316\n", + "Brier loss score: 0.114\n", + "Cohen-Kappa score: 0.245\n", + "ROC AUC score 0.819\n", + "\n", + " precision recall f1-score support\n", + "\n", + " 0 0.86 0.97 0.91 994\n", + " 1 0.58 0.22 0.32 208\n", + "\n", + " accuracy 0.84 1202\n", + " macro avg 0.72 0.59 0.61 1202\n", + "weighted avg 0.81 0.84 0.81 1202\n", + "\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No handles with labels found to put in legend.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "run 30 of 50\n", + "\n", + "### USING ALL DATA ###\n", + "\n", + "fitting and transforming X\n", + "\n", + "splitting both X and Y in train and test data\n", + "\n", + "Accuracy: 0.852\n", + "Precision: 0.547\n", + "Recall: 0.253\n", + "F1 score: 0.346\n", + "Brier loss score: 0.104\n", + "Cohen-Kappa score: 0.275\n", + "ROC AUC score 0.831\n", + "\n", + " precision recall f1-score support\n", + "\n", + " 0 0.88 0.96 0.92 1016\n", + " 1 0.55 0.25 0.35 186\n", + "\n", + " accuracy 0.85 1202\n", + " macro avg 0.71 0.61 0.63 1202\n", + "weighted avg 0.82 0.85 0.83 1202\n", + "\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No 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"### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.835\n", - "Precision: 0.474\n", - "Recall: 0.281\n", - "F1 score: 0.353\n", - "Brier loss score: 0.117\n", - "Cohen-Kappa score: 0.266\n", - "ROC AUC score 0.778\n", + "Accuracy: 0.842\n", + "Precision: 0.556\n", + "Recall: 0.250\n", + "F1 score: 0.345\n", + "Brier loss score: 0.112\n", + "Cohen-Kappa score: 0.269\n", + "ROC AUC score 0.813\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.87 0.94 0.91 1010\n", - " 1 0.47 0.28 0.35 192\n", + " 0 0.87 0.96 0.91 1002\n", + " 1 0.56 0.25 0.34 200\n", "\n", " accuracy 0.84 1202\n", - " macro avg 0.67 0.61 0.63 1202\n", + " macro avg 0.71 0.61 0.63 1202\n", "weighted avg 0.81 0.84 0.82 1202\n", "\n", "\n" @@ -1525,8 +1540,6 @@ "name": "stderr", "output_type": 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macro avg 0.78 0.64 0.68 1202\n", + "weighted avg 0.85 0.87 0.85 1202\n", + "\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No handles with labels found to put in legend.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "run 34 of 50\n", + "\n", + "### USING ALL DATA ###\n", + "\n", + "fitting and transforming X\n", + "\n", + "splitting both X and Y in train and test data\n", + "\n", + "Accuracy: 0.855\n", + "Precision: 0.530\n", + "Recall: 0.246\n", + "F1 score: 0.336\n", + "Brier loss score: 0.106\n", + "Cohen-Kappa score: 0.267\n", + "ROC AUC score 0.801\n", + "\n", + " precision recall f1-score support\n", + "\n", + " 0 0.88 0.96 0.92 1023\n", + " 1 0.53 0.25 0.34 179\n", + "\n", + " accuracy 0.86 1202\n", + " macro avg 0.70 0.60 0.63 1202\n", + "weighted avg 0.83 0.86 0.83 1202\n", + "\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No handles with labels found to put in 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0.308\n", - "F1 score: 0.400\n", - "Brier loss score: 0.112\n", - "Cohen-Kappa score: 0.320\n", - "ROC AUC score 0.806\n", + "Precision: 0.556\n", + "Recall: 0.255\n", + "F1 score: 0.350\n", + "Brier loss score: 0.111\n", + "Cohen-Kappa score: 0.275\n", + "ROC AUC score 0.815\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.87 0.95 0.91 1001\n", - " 1 0.57 0.31 0.40 201\n", + " 0 0.87 0.96 0.91 1006\n", + " 1 0.56 0.26 0.35 196\n", "\n", " accuracy 0.85 1202\n", - " macro avg 0.72 0.63 0.66 1202\n", - "weighted avg 0.82 0.85 0.83 1202\n", + " macro avg 0.71 0.61 0.63 1202\n", + "weighted avg 0.82 0.85 0.82 1202\n", "\n", "\n" ] @@ -1599,50 +1781,77 @@ "name": "stdout", "output_type": "stream", "text": [ - "run 37 of 50\r\n", + "run 39 of 50\n", "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y 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"stream", + "text": [ + "run 42 of 50\n", "\n", - "run 39 of 50\r\n", + "### USING ALL DATA ###\n", "\n", - "### USING ALL DATA ###\r\n", + "fitting and transforming X\n", "\n", - "fitting and transforming X\r\n", + "splitting both X and Y in train and test data\n", "\n", - "splitting both X and Y in train and test data\r\n", + "Accuracy: 0.856\n", + "Precision: 0.562\n", + "Recall: 0.246\n", + "F1 score: 0.342\n", + "Brier loss score: 0.107\n", + "Cohen-Kappa score: 0.275\n", + "ROC AUC score 0.808\n", "\n", - "Accuracy: 0.839\n", - "Precision: 0.528\n", - "Recall: 0.333\n", - "F1 score: 0.409\n", - "Brier loss score: 0.118\n", - "Cohen-Kappa score: 0.321\n", - "ROC AUC score 0.773\n", + " precision recall f1-score support\n", + "\n", + " 0 0.88 0.97 0.92 1019\n", + " 1 0.56 0.25 0.34 183\n", + "\n", + " accuracy 0.86 1202\n", + " macro avg 0.72 0.61 0.63 1202\n", + "weighted avg 0.83 0.86 0.83 1202\n", + "\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + 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@@ -1714,57 +2015,31 @@ "name": "stdout", "output_type": "stream", "text": [ - "Accuracy: 0.845\n", - "Precision: 0.534\n", - "Recall: 0.285\n", - "F1 score: 0.372\n", - "Brier loss score: 0.116\n", - "Cohen-Kappa score: 0.293\n", - "ROC AUC score 0.778\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.87 0.95 0.91 1009\n", - " 1 0.53 0.28 0.37 193\n", - "\n", - " accuracy 0.85 1202\n", - " macro avg 0.70 0.62 0.64 1202\n", - "weighted avg 0.82 0.85 0.83 1202\n", - "\n", + "run 45 of 50\n", "\n", - "run 41 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.844\n", - "Precision: 0.509\n", - "Recall: 0.291\n", - "F1 score: 0.370\n", - "Brier loss score: 0.110\n", - "Cohen-Kappa score: 0.289\n", - "ROC AUC score 0.807\n", + "Accuracy: 0.836\n", + "Precision: 0.550\n", + "Recall: 0.266\n", + "F1 score: 0.358\n", + "Brier loss score: 0.119\n", + "Cohen-Kappa score: 0.277\n", + "ROC AUC score 0.814\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.88 0.95 0.91 1013\n", - " 1 0.51 0.29 0.37 189\n", + " 0 0.86 0.95 0.91 995\n", + " 1 0.55 0.27 0.36 207\n", "\n", " accuracy 0.84 1202\n", - " macro avg 0.69 0.62 0.64 1202\n", - "weighted avg 0.82 0.84 0.83 1202\n", - "\n", - "\n", - "run 42 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", - "\n", - "fitting and transforming X\r\n", + " macro avg 0.71 0.61 0.63 1202\n", + "weighted avg 0.81 0.84 0.81 1202\n", "\n", - "splitting both X and Y in train and test data\r\n", "\n" ] }, @@ -1772,7 +2047,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "No handles with labels found to put in legend.\n", "No handles with labels found to put in legend.\n" ] }, @@ -1780,57 +2054,31 @@ "name": "stdout", "output_type": "stream", "text": [ - "Accuracy: 0.857\n", - "Precision: 0.515\n", - "Recall: 0.291\n", - "F1 score: 0.372\n", - "Brier loss score: 0.107\n", - "Cohen-Kappa score: 0.298\n", - "ROC AUC score 0.777\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.89 0.95 0.92 1027\n", - " 1 0.52 0.29 0.37 175\n", - "\n", - " accuracy 0.86 1202\n", - " macro avg 0.70 0.62 0.65 1202\n", - "weighted avg 0.83 0.86 0.84 1202\n", - "\n", - "\n", - "run 43 of 50\r\n", + "run 46 of 50\n", "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.838\n", - "Precision: 0.560\n", - "Recall: 0.248\n", - "F1 score: 0.343\n", - "Brier loss score: 0.119\n", - "Cohen-Kappa score: 0.266\n", - "ROC AUC score 0.780\n", + "Accuracy: 0.846\n", + "Precision: 0.573\n", + "Recall: 0.258\n", + "F1 score: 0.355\n", + "Brier loss score: 0.105\n", + "Cohen-Kappa score: 0.282\n", + "ROC AUC score 0.838\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.86 0.96 0.91 996\n", - " 1 0.56 0.25 0.34 206\n", - "\n", - " accuracy 0.84 1202\n", - " macro avg 0.71 0.60 0.63 1202\n", - "weighted avg 0.81 0.84 0.81 1202\n", - "\n", - "\n", - "run 44 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + " 0 0.87 0.96 0.91 1004\n", + " 1 0.57 0.26 0.36 198\n", "\n", - "fitting and transforming X\r\n", + " accuracy 0.85 1202\n", + " macro avg 0.72 0.61 0.63 1202\n", + "weighted avg 0.82 0.85 0.82 1202\n", "\n", - "splitting both X and Y in train and test data\r\n", "\n" ] }, @@ -1838,7 +2086,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "No handles with labels found to put in legend.\n", "No handles with labels found to put in legend.\n" ] }, @@ -1846,66 +2093,38 @@ "name": "stdout", "output_type": "stream", "text": [ - "Accuracy: 0.864\n", - "Precision: 0.474\n", - "Recall: 0.350\n", - "F1 score: 0.403\n", - "Brier loss score: 0.099\n", - "Cohen-Kappa score: 0.328\n", - "ROC AUC score 0.791\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.91 0.94 0.92 1045\n", - " 1 0.47 0.35 0.40 157\n", - "\n", - " accuracy 0.86 1202\n", - " macro avg 0.69 0.65 0.66 1202\n", - "weighted avg 0.85 0.86 0.86 1202\n", - "\n", + "run 47 of 50\n", "\n", - "run 45 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.853\n", - "Precision: 0.583\n", - "Recall: 0.257\n", - "F1 score: 0.356\n", - "Brier loss score: 0.107\n", - "Cohen-Kappa score: 0.287\n", - "ROC AUC score 0.818\n", + "Accuracy: 0.864\n", + "Precision: 0.588\n", + "Recall: 0.331\n", + "F1 score: 0.424\n", + "Brier loss score: 0.104\n", + "Cohen-Kappa score: 0.354\n", + "ROC AUC score 0.803\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.87 0.97 0.92 1011\n", - " 1 0.58 0.26 0.36 191\n", - "\n", - " accuracy 0.85 1202\n", - " macro avg 0.73 0.61 0.64 1202\n", - "weighted avg 0.83 0.85 0.83 1202\n", - "\n", - "\n", - "run 46 of 50\r\n", + " 0 0.89 0.96 0.92 1021\n", + " 1 0.59 0.33 0.42 181\n", "\n", - "### USING ALL DATA ###\r\n", - "\n", - "fitting and transforming X\r\n", - "\n", - "splitting both X and Y in train and test data\r\n", + " accuracy 0.86 1202\n", + " macro avg 0.74 0.65 0.67 1202\n", + "weighted avg 0.84 0.86 0.85 1202\n", "\n", - "Accuracy: 0.848\n" + "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "No handles with labels found to put in legend.\n", "No handles with labels found to put in legend.\n" ] }, @@ -1913,56 +2132,32 @@ "name": "stdout", "output_type": "stream", "text": [ - "Precision: 0.490\n", - "Recall: 0.271\n", - "F1 score: 0.349\n", - "Brier loss score: 0.109\n", - "Cohen-Kappa score: 0.271\n", - "ROC AUC score 0.784\n", + "run 48 of 50\n", "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.88 0.95 0.91 1021\n", - " 1 0.49 0.27 0.35 181\n", - "\n", - " accuracy 0.85 1202\n", - " macro avg 0.69 0.61 0.63 1202\n", - "weighted avg 0.82 0.85 0.83 1202\n", - "\n", - "\n", - "run 47 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.829\n", - "Precision: 0.483\n", - "Recall: 0.284\n", - "F1 score: 0.357\n", - "Brier loss score: 0.124\n", - "Cohen-Kappa score: 0.267\n", - "ROC AUC score 0.762\n", + "Accuracy: 0.864\n", + "Precision: 0.584\n", + "Recall: 0.254\n", + "F1 score: 0.354\n", + "Brier loss score: 0.104\n", + "Cohen-Kappa score: 0.291\n", + "ROC AUC score 0.812\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.87 0.94 0.90 1001\n", - " 1 0.48 0.28 0.36 201\n", - "\n", - " accuracy 0.83 1202\n", - " macro avg 0.68 0.61 0.63 1202\n", - "weighted avg 0.80 0.83 0.81 1202\n", - "\n", + " 0 0.88 0.97 0.92 1025\n", + " 1 0.58 0.25 0.35 177\n", "\n", - "run 48 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", - "\n", - "fitting and transforming X\r\n", + " accuracy 0.86 1202\n", + " macro avg 0.73 0.61 0.64 1202\n", + "weighted avg 0.84 0.86 0.84 1202\n", "\n", - "splitting both X and Y in train and test data\r\n" + "\n" ] }, { @@ -1976,49 +2171,30 @@ "name": "stdout", "output_type": "stream", "text": [ + "run 49 of 50\n", "\n", - "Accuracy: 0.861\n", - "Precision: 0.562\n", - "Recall: 0.348\n", - "F1 score: 0.430\n", - "Brier loss score: 0.109\n", - "Cohen-Kappa score: 0.356\n", - "ROC AUC score 0.787\n", - "\n", - " precision recall f1-score support\n", - "\n", - " 0 0.89 0.95 0.92 1021\n", - " 1 0.56 0.35 0.43 181\n", - "\n", - " accuracy 0.86 1202\n", - " macro avg 0.73 0.65 0.68 1202\n", - "weighted avg 0.84 0.86 0.85 1202\n", - "\n", - "\n", - "run 49 of 50\r\n", - "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.852\n", - "Precision: 0.529\n", - "Recall: 0.203\n", - "F1 score: 0.294\n", + "Accuracy: 0.851\n", + "Precision: 0.466\n", + "Recall: 0.279\n", + "F1 score: 0.349\n", "Brier loss score: 0.109\n", - "Cohen-Kappa score: 0.229\n", - "ROC AUC score 0.779\n", + "Cohen-Kappa score: 0.271\n", + "ROC AUC score 0.803\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.87 0.97 0.92 1020\n", - " 1 0.53 0.20 0.29 182\n", + " 0 0.89 0.95 0.92 1030\n", + " 1 0.47 0.28 0.35 172\n", "\n", " accuracy 0.85 1202\n", - " macro avg 0.70 0.59 0.61 1202\n", - "weighted avg 0.82 0.85 0.82 1202\n", + " macro avg 0.68 0.61 0.63 1202\n", + "weighted avg 0.83 0.85 0.83 1202\n", "\n", "\n" ] @@ -2027,7 +2203,6 @@ "name": "stderr", "output_type": "stream", "text": [ - "No handles with labels found to put in legend.\n", "No handles with labels found to put in legend.\n" ] }, @@ -2035,37 +2210,44 @@ "name": "stdout", "output_type": "stream", "text": [ - "run 50 of 50\r\n", + "run 50 of 50\n", "\n", - "### USING ALL DATA ###\r\n", + "### USING ALL DATA ###\n", "\n", - "fitting and transforming X\r\n", + "fitting and transforming X\n", "\n", - "splitting both X and Y in train and test data\r\n", + "splitting both X and Y in train and test data\n", "\n", - "Accuracy: 0.846\n", - "Precision: 0.517\n", - "Recall: 0.245\n", - "F1 score: 0.332\n", - "Brier loss score: 0.110\n", - "Cohen-Kappa score: 0.258\n", - "ROC AUC score 0.791\n", + "Accuracy: 0.859\n", + "Precision: 0.593\n", + "Recall: 0.261\n", + "F1 score: 0.362\n", + "Brier loss score: 0.105\n", + "Cohen-Kappa score: 0.296\n", + "ROC AUC score 0.830\n", "\n", " precision recall f1-score support\n", "\n", - " 0 0.87 0.96 0.91 1014\n", - " 1 0.52 0.24 0.33 188\n", + " 0 0.88 0.97 0.92 1018\n", + " 1 0.59 0.26 0.36 184\n", "\n", - " accuracy 0.85 1202\n", - " macro avg 0.69 0.60 0.62 1202\n", - "weighted avg 0.82 0.85 0.82 1202\n", + " accuracy 0.86 1202\n", + " macro avg 0.74 0.61 0.64 1202\n", + "weighted avg 0.83 0.86 0.84 1202\n", "\n", "\n" ] }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No handles with labels found to put in legend.\n" + ] + }, { "data": { - "image/png": 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r5lkK8Zp5XjXPZdJNKWQtySC+tNvAYMBl1bR1TCkD5yycc+XoWIHra+oTimMaIUtThyShZFCSKGQZ/6xRFB6M8ZAkGmmqYHODzuElhocLGidL15hla0xzSg0tijXaNqLyad1MDTloT0EHNOd26C6w7VHXUDRcIp6skE5otCwazJEFfWgNFIUq01IKRUGdSFkEZDfUlZTnFkWhYa2C54XwPIUw1BgMNDodjfHYx2SiMRoB8zkJovGYLt0uCSLpIxLeNyKPBEEQBEEQBEH4ZHmXpM/bpn58n1Ib942Gfd8P6XeNhL1JGqgpf05FUBDQcd9VGn06epYkr6aCTtNBpwkhHhNLEiqSThK67rSvqJlI8n0SG8NhnaSi5+XgnIFSFsYYWOuQpgaHg0Ecm1IIWaSpQ54DcUx9QnnukGUkiNKUpJC1PtJUIc+pa8gYAFGMUbLBKNpgFa8xLUfKZsUa8/wCM3MJDUsbynSdHNLKQQeAbgFF0Ma+f4bbLvUNJeMl4vEK8WiJdLpC3J/Bln1C1lpkmdcopDYwe4c0pQSUMXR9lmkopWCtjyDw4fsK3S4VVrfbPsZjXUmh8RiYTunrYFCPmkkfkfBDIW81QRAEQRAEQRB+FJqpn3ctewbePvVz+nvv+/m8rQTi53CXCGLh8iaPxSKoKF69z9P7bt4HpWFqCcRf+b64kJr/ltfb87FxOohHojh9BNDomOeRFKJ+ngK7nUEUGSSJRZYV5UiZLnuEKI2TZRrW0nVFESDPNYxRSFNVdhspGnFLLTrJDYbRBuP4AqP4ErP8HPN8jVl56dvt8TiZojEyrQDdpgRR3JmUcmiFXX+JdLJCMl4hHi+QTVewvQGgLAANpfhcq2orm7slKZRlBlnmQKXaGllm4JwPpTS09uH7Gu02jZq12x6GQ43BgITaYFD3EI3H9dp76SMSPgZEHgmCIAiCIAiC8E5wiuX7yJ+HpE5TntwniD7UaM6bSJ+HRsLuSwPdJayaI2HNLqLm/Z7eV1MuBcFxMsjzjlfNN6VQmtZpq9OOIi5wDkMSGfN5/Xu1rHJQikbHAFt28DhEUYEXL0gKpSnJojStpVCWKeS5Q54rWOuVx+cjy1pl+bUuk0WqLKEuJViWYRBR19AkusQ0o44hHiubFRsELqvLp3VdSO15gA4B5/k4DFa46dXr65PxCslkhWS8RDaZw+sE1d8Cukw/6bKAW8G8dAA0jLFVUTWdE40kcbA2qASR1hphSJvMul2/TBKREBqNSAqxIOIUUatVvz8E4WNE5JEgCIIgCIIgfKa8i+xp/gy8mfy5LxH0Q3xQ/hAjYby17HSd/F2PdSqCmqNyd114PO501TyLoMOhFkIsg/K8Fj/NY+b74ULpfv9YUPBIGSWJLLS2VdF0UVgkiSkvRZUUcs5UfT3cGVQUQFFoFAXgHPcJtZHnDsYoAKoqoi6KUsYYwBqHMNliGG3Q221wlq0xzS4oMZStMcsuMDTXtRhStRzSuiyi7ihk7QF2/RVdurTCPpmskIwWSCYr2NEIYVvB9ylxZK2Cc6g2paWpQ36tYK2DUtSrlKYORWHKn3V5zBpACN/34XkaSlGCaLHw0WqRIOr16tRQr0eJovGYzj0XVksfkfApIvJIEARBEARBED5B3iX1c/rzQ1KHx72aouT0937ID8AfaiSMZU3z9rseqylxmimh03X0fL/N++f0TvN+0rTuDOL18pwO4g1op+eb74fHyIbD41QWyyDnmivqLQDeOmaqrWMsheKY0kNF4VAUqjwuXSaFKFljLaWFrA3LTWRU+uwcKhlEiSGSSsY4OKeAokB3v0Zv9wKzdI1JeoFZTn1Dk2yDWX6Blk1q8aXdUeeQ1yPLFvUpLbTt0tdouEI0otRQOllC91potYBWy0IpVb5+Cq4AdK6QpwrbrUNRaDjnALgyGQUUhSu7l0iGFYUHpTwEgQ+tPTin0Gp5mM08dDoKnkdJIR4163SopJo3mnFhNUsiQfipIPJIEARBEARBEH4EHpI6b/I98LD8+RhSP/fxIUfCTpM8d90vX9L01etelwpqPj6/jtw1xDKIy6OzDIii+meWJPy68PfNcbFery6TbsLF17zly1razMVSKM8d4jhDmhqkKRVNZ5ktn5Mq195TAshaBWO8MhXkw9oQRUHjV3kOOEeShUfI8pzTQiSG6Jwq6HiP7naDSbLBOKHy6QlvKsvWGOVX8JQlIdQYKdMa8AIH3QJMq4v9cImb/hl23SV2/RWi4aocK1si7s3Q6SmEoUOr5aqCaK8AWoWCV1CCKIoUtltVvYbOORhTIMso/cTvBRJdAZQKoLWPIPCQ5xq+rzGfe+j1VLXprdOh1BCXUw8GJIkGA+p5kj4i4XNC5JEgCIIgCIIgvCWnqZ93kT8PFTyfCoYfO/XzuvPwIUfCThNBbyqCqEfn1VTQaeqoeR2PcJFoqRNBPBrG3/Oq+eZzaR6zUvVoUq9Hq9T59Wyeu+ZX2oxm4RzJIGPqr1lWIE0LZBlJIeoUIoGT53SpRsGsRlFQ944xqlwLX5ZL5/U5zHONPEd54dEzOhZrgSKzaO2vMTysMU/WmKS0pYy+XmCardE1+0ZSzVWl1NoDdMdB9xWS/gyH/hK7wRLb7gqH/gr7/grpdIl4tITp9ktp5hAEDmHoECoFXTiEhUK3YImlcTi4KtlECSw6RyyIKHVFCaM0DQB04XkefN9DlmlorTEYeBgMaMSMpWOvR2NlLIQ4RdQsrOb3pSB8rog8EgRBEARBED473ma0667vgTdP/dz3ex8T941pvW5MDHi7kbBT8XV6fzwOlud3C6KHUkGcADl9LGuPxU9TBNGYVS2EWK40X8OmfFKqTgexTGCpdXo+gfp+aP28rVJCAAmhPKfRsSyjouk8d2UqiMRQVdZsdJkG8uBcAEBX5dMsgGi8zCFN6fssc5UUosQQQONaNHJmDil6+0vMsguMkzUm6QbT8vtZtsY42yCAIRGkXLmljJ+Tg+4DLggRjc6wHyyx7y+w651h1yM5lEyWyEZzqNCH7wO9nkW7DQSBw0ADnUJh5ByKwqIoKBEVRR6MschzSj7Ra2FgTI4sc5V0pW1uGnkewJgWPM+H73vlv00f7baHyYRGyLhQvNUiIcSCqN2mn/v9V0fNPgYxKwgfGyKPBEEQBEEQhE+Kpuj4IVI/d/3ex/zh8occCWueh/tSQfeJIGPuTwWxDOLuoFMZxN1DLICiqC6U5guLIn6c5uvafI5akzyYTOrHa9IslQbq+9KaipWtNXDOoihIEGVZDmNICiWJQRzb8hyrxrngxJBXvmY0OqaUBq17J8FTFCST6HuLovDKny2yzCuFChdVOyhFj5GlCq2I1tev0jXGyQaTdINxcoFpusYkW2NobspuIVcJPc1yqOWgO0DaHyMerrAdLrHvLbHtLbHvn2HbXSEeLeFGIyjN6R1LEiZwmGsalTOGzhH1Imlstyx+UB4zv4fo3FHBNr0Gx4LIB6+5t1YD8BCGHvp9Enntdt0DxTKIt5d1OvWGMy6slj4iQXh7RB4JgiAIgiAIPyjvKnxOUz8PyZ9mKqR5Pf/8KfCmI2Gn17/rSNgpdz0WFQzfnwpiQfMmqaCmfDLmWPwcDnVnEAui5vfAq6Kv+Vx8n6QBjybx43CZdLNUms81y4fm6BgnhUhs5Miyoiyapk1kJEhIBlnLW9U08pyKlp0Ly8SQakgvdTT2SOkghzz3SllEm8vy3JaJIdoC5pyub4sK9KMNJska4+Si/LrBJCU5NM3WCJFBaVWlhqoSau2ge4DyfUTDBeLRCtFwQZvKeitseytse48QD+bwey14niuTOxa9nkO3BQw8KsQuClOdxzhW2O0UikIDcMgyVf7bVdCaSruds8gyA2t12dsEAD7S1Ie1PpSiNffWUsrK8zy02ySDKLVUd0+dpoUGg2NxJH1EgvB+EXkkCIIgCIIgvDGvS/28ifx5KNHDX++TPx976ucufqyRsNNjeJtE0Jukgu66vvl4zXQQbxDjn1kM8YXLpE8FUFMQdTr12BFJnlefK3ccsRSqN8o5OGerkmn+Ps8L5HmBoigQxwZRVKAoatFDW8bqjiBjPDjnwVofgFdKHVXJL2sVssw1ZJEr/06jKGw1ksY9Q83jpXPiocgtgnSPSXKBSbTGOLnEOFljnFDX0CRdY1xcUUqoMU6mVCmGQsDrAEWnj3i4xL6UQ4fBCtsuyaGb9hnS/gStjkYYUn9Qp+PQ7VpMOsC8lEN5XpSvpypH+zR2Ozqv9BpTUso5Ba1pHI86mgwAEkT03HwUhV9uMqMUEZ0jH0pp9Pt1Sojf10FArzVfx+Nn3EXULKyWPiJB+PCIPBIEQRAEQfiJwR92X/c7r5M9d90GPJzo4Q999yWCPpai53flTaTPhxgJO+X0MU9F0Gk6qNnj07z4/utTQc3nXhT1VrFmEoi3jXH/Dq+aP32+ze9ZDrAI808+mTQlUPPr8Tl9desYraMvUBQGeV7gcDBIElOulnfgjWGU6CGx45wG4MOYsBwDc2VyiAWQgrX131NiyCHLeIzsWCKxeAIcAFWmtihZ5IxDL7rCKL7AKFpjFG/KnqELjNMNZukF2i6qxuNYDFERtYPXAbSnkQxniIdUOh2NVjgMlrjtnuG2s8Rt5wxFq1smcFz5OlNyaNZ2eNxC43xR0TQdo8LLl1SwrZQ7kl10LAbUm2SR5xZKqcYooQdjfOR5G0r5cM6D1gpK+bBWo9Wqt5R1OvV/D9ptev15zCwI6s1mzcJqvv1T/u+HIHzKiDwSBEEQBEH4ibFeUwfMQ/9PPKc8fuqpn/v4sUfCTo+Fky4sHx5KBL0uFcTy7r5UUPNxOR3Eo2L3lUlTIXMtofhDfPM5ak0f9vk63mTG75nTUunT48jzeuRNa1v1CFFKyJSdP3lVNB1FdOG18s20EKWCFPJcAwjgXAt1aTSvqufNXSR56Da6Pk018lxXY2TcJVSXU7MYopG1otDVxi8/jzGK15gcNhhGNE42Ti4wzTaYphcYZxtaX9+QQ9w95GlQEXWrjXiyQjJalGvrlzgMlrjpnOG6tcRtuIQKvFKouFK6kBw66zh81QaAHEWhkOcOWtdpqv1e4+pKVe+jolCN95WD1hZKWRQFdRCxvCL5pmFMAGMCeF6AotBQijqInNPwfRoba4pBrWs5yLcFQZ0m63aPR9Ckj0gQPk5EHgmCIAiCIPzEcA5Yraj/46fOxzASdkrzsd5EBBnzsAjiD+FvkkridFBznfxpiTQng7iwGKhlUC1vagHU6dSr5zmldNeGMX49+CuLqboHyUGpWgpxYqgoTCmFqGQ6ikw1+nV8PlXZ+8Or6ElYkCDhx6V+IN4wRmkhW6aCajHEvUkkTFS5oQzl43pQypaPratzZy1gDdBJrjE4rDGKLjGKzjFJ15hkG0wTGinrmW3VL9RMDSnt4IWAbgP5cIJ0vMR+tEQ8Jjm076/wsnWG284KezWE9ig1xOc9DKmQ+mnH4p+0HLTOS3FF50opfm1ptCxJVPU+of4hklueZys5l+e22mrmeSgTWQGcC1AUAZQKYAydc9/3oRTdZ79fp9b43wpLH9+v37P8c7f7amE1F6ILgvBpIP9cBUEQBEEQPlH2e+qSOSVNf/hjeR98LCNhdx3XXSLovuJooJZQ75oKYjghlWX0Wj+0ap7XzDeLq+8qkg5D2j7FsogvLIROS6UZPu9peiyaPM8BqGUQf6WEUIE0pVX0cWyOen7qkUjeoKVRbx3jbWR8Hrh7yFUiiZJQDkrpMiWjkGW6kmLOOQAaWcbbyhys9UpxQo/LIo1+VlB5hv7hHIPDGsNog1FMiaFxssY0LdfXu6ySQ1oBKLuHtAZ0B0AQIp0ukE6WiEcLpOMlouES+8EZrsMVrltLJLYFANVYWavlEAQO7TbwVdei1crh+/U5KgrA8+g5GKNwc6OQJPUoHW9co/4hwPcdaMW9K8fLXPW+oPPjQ+sQ1oZwjiWchtY+PSHUBdUsr1gEhSG9fiyOWBJxZ9FpYbX0EQnCTwORR4IgCIIgCJ8ot7f1h7km4zF9iHtfFAWNwX0f7lvj/qFHwk5pjoe96eV1qaBmYulNxFRTRp32B51KIZYnLGua28z4fPA2KhgoVsMAACAASURBVE5G8e3N47lLBrFo4qQSp0+ao2NK1dvGSAwZGFMgywqkqUGa1n1Cdfkz9wJ55XiXhnMhyRmlqo1jLNr4OEjIqbJryIIkBq2lT1MeG9Plhi4SQ3nuyuSRKvt3XCmVdHUOaSxNwRqHINmhv9tgGF1gGK0xSdeYpWuMkgvM0jX6+XVjnMxBK+r+4et0Dyh6Q2TTJZLpEslogWSyQjRcYjc4w5V/hp03QlaQETyVQ502MGvIIU7O0eusyveHQhRR/xAlourrqb+KXkStHZQqYAyNmJXvFGhNySsghFIBgBDOUUF1lnlQyivPKz2nTqd+H7Fs5f+u8MgZp4RYFPH2s6YgYqkkCMJPE5FHgiAIgiAInzD9Po2DfEi2W7q02+9+H9yP831Hwk55nfg5FUXAq4XR75oKYmrxQWmwu8qkm+Njpxvn+AM7f2intej0PZ+T5rE2r+fHbwoiPhYusW4KJx4do04bU0oaA6UM8jwvy6UpKZRlrpQ59f3TOdRl942uVtEDPPZF6Rig/juWIzQ65srnX4+XUb+QKxNI/Ld++fgoJRSdF5KNlCRKUxZNlCgyWYHu/gWGh4syNbTGLKfU0CShMuq2jatxMl2OlEE5KqMOANX1kE0WyKYLZJMF0ukSyfgM+/4C2+4KL8MzRK6DNK3TOWHoyvEyh1EHWLUtOh1bJrKoG6lOXNHXJCF5E8cshFS1cY2Ekqvef9aSIDLGlueGCrDzHPC8EM61SknklxvSPABe9RqwAOIxRE4QsZQF6mQR38bvQy6sbiaJpI9IED5PRB4JgiAIgiD8QDx/TqXE7wvngOn0/d3fQ/T7wHz+YR+jKWG+byqIJdW7JpU4ocQr5jkhdNe4GKU8aiF2Oi7meZTuGAxQJViao2XNv3loZKwojlNC/CGfnheNKTlnobWB51k4V8BagyTJq5RQmpqqD4hHu5RS5VgYF037sDYASaJa/rAAKl8tAKq6jkemSLaRBMpzhSRh4aNLcaRBqRdXlXDTOVHl668bz1GV74sypXQ4YHDYkBiKLjBJN5gkFxjFa0yzDYbZC3iwpRyi1BCaqaE24DodpNMlsvkK+XSJZLxAOj3Dvr/EbXeFK7VAmtOoG1Anh4KA0kPTDvC4XVQSpvn6cEoMUOWII20t4/SQc64qp+aEVp0M4wSRA+DK/qFylE4FUKqNIPBhjAdjNLKMBBGP8wF1OqgpgpopIh41a3YR8W2dzqspIukjEgShifwnQRAEQRAE4QeiKIAnT75fgqcJl/G+L+IYuL5+9fose7fy7TcVQCyLgPtF0F2poLdJKzW7g7g36KFxMf5Azo97Oi7GRdKcGGLZ0xRID/UrnW5Yi6Lj/qbj0TFTpYWUMtCato0dDkWVEkpTU/XelI8AANBaVxuxjAnLlIsuE0quFBx1cTRAMqleZU+ihwUMJYGAPPeQprz2nh9TH72e1LOjKlGSZfXt1K9DMskYhyIzaB9uMDxcYBqtSQyl1Dk0SdYYp2t0in1jnKw83lIOKQ3onkI+niGfLpDPlijmCyTjJeJxLYduimH5+tNxsRziy7IDtFpFNcLVhEbgOD3kEMe0ySzLNJLElefalYksV0pAFmoWzplSoLlS8tF5VkrDuQBKhQiCANYGZRLJL187lmj1eBnL0aZ85ERas4OIJZFS9H7lBFEzSSR9RIIgvAkijwRBEARBEN4jcdxMIBzDvT4f64e1JKEPqKMR/cxFwq0WfWDlxMub9AbxaNaHSAUxzUQMi5/T7WJ84RJlHhM7TQf5PgmyppRqlk+fjo01j/V0rIsFSS1ljlNCPDoWBLZKCxljkOckg3h0LEmKxjhX3XVD0lBXKR5rW+XqeVVJIVpTT8fBUoiTTCSE6rExkhv1Nq4sU+WYlarSLzxSRn9D98dpIe4YynNKGxUF9wSRLMpzB5Xm6O3XGBw2mCRrjOIyNZSsMU0vMExeIEDRSA2h8VwBFQDohcimSxJDywWK2RLxeIl0ssK2d4abYI5d0ipfczo23lLG42XzFo2UtVoOYUjPg0fBOEHFzylJWHSp6j1E54LOLb0H6KQGgYK1JIics9XrpbWrOpe0DuD7PF7GW8w8WOtVz5WTWDza2WrV/1ZYAjVlZlMSsag8XXsvfUSCILwPRB4JgiAIgiC8RzabWhKc0ul8/H0hYUgSJcuA8/O6E2W/r3/nVPo0RVAznfO2H1abY2unIuiudBAnXu5KJrGg6naPxRSLgeMeoFfLpZvHdDoydjgcl0s3pZDvGwSBLYulLYqCUkJxnJfl0gWyzJabv+ryZ1UmaZSirWOUXulUyR4aLXOl+Km7cepzTPKHpAn36NCx0UYzui5NVUNwcVcRpX/4/DtnoZQq+3Z4/MqiKHQpjujxqF/HociBTnqL3vYC06hMDCVrjCISQ+Nkg35+A6Vd1TUEVdZD8yr7DlAMxshmSxTzJcxigWK2QDpZIBqSHLpVY0SxV70HrFW1HPKBMHCY9y3abYtO51U5BKjq/eWcRpq6hvTyyp9V+XrX42WAK7eXscArANiycNpBKYcsA3xfQ+sAntcB4MMYv3yNPTjnvVIQzu/RU0HE/+1gWdQcNeP/fvj+cWE1J4k+9v++CILw6SLySBAEQRAE4T0zn9OHuU8ZTm387Gff7354m1ozBZQkqFaksxRiIdTsAgrD41SS71NvECeBWJyQHHm1Q6iZ1jjtEWqOV2UZJcY4GXZ6H1pbtFoG7Xa9eSzLSAZtt3k1Nkabv+p+G+4T8jxdSiFVjSSRiAF4w1ad5nJl91CdFlIKVRKI0j+qSr2wKMpzV/UF8YYxXkdPY1Ku7M+xpYji86CQ5xZZpiupQb1HNFKVZYA2BTq7SwzjNUYHKqCmcbJNWUS9RuCye8WQ8gDV8pFNFsjnCxTzJdxqgWKxQjxa4DBY4bazwj5vI4r0UbF4EAAt5dAyQKvlMJlQcqjXA4Kgtnx1ObcqE3PUNVQLI05UkTgqCoei0KUEdFWihxJTDp5nYS1JPq3p/Grt4HkefD+A77fL9FBQvi4+8ly/0lOldf0+5nEzvrCA5Pf3aR8Rp/7uShFJH5EgCD808p8dQRAEQRCEN2SzIfHxEFn2wxzL+8Ra4OqK+o54bKfusTmmOZrFAublS+DFi+ORtbr3hv6OE0rNtA8XSd81Lsb3c9dmtPvKpes+HRIocVyXWTc/tHNKKAypQ4j6aGj7WJKQDNrtaGyMCqbr/h8SQq5KCWldr6Kn39HVqBedWy5JdtV1WrtquxaPQNUdQbpKu9RiiOQHCQ+v8VxrwUTdQrZMx/BqdyDLbNU1RGNmtRiy1sEUCjraY3hYYxhdYhTTlrJ6Q9kag+Rl2b1UyyGgFkQ6AEy3j2y2RLag1JBdLlAslkjGS+x6K9z6M0SJ94ocCh3QSh19bVlMp5QcYjnEI3cs07iM2lra0lafJzrPXNDNCS3eFuf7JIgomWPLsUFXijPqJSoK3nCm4XkkiJQKked+mUgiQdQcS+Uxs2b59OmYmXP0uPx7zUJrvv0+SfQm2/4EQRB+CEQeCYIgCIIgvCFRBMxmrx8N+T6pI2tJejQTDB+aOAa+/bZOO8RxXRh9fn6c0rlr5CuKaKX3cHic7uEkC/W/vCqEThM+p+XSp9vXioLk3V33w/cRBA5BYKA1raA3xlZdQlFUlKNjeTmGxQkd6ugBeHRMwfc1nPPgXFDKCF0WaXN5saskDHXaACwy+NjznHuISArR/TtwsbQx1BHkHMryaa9KatUr6LnEmoWVq8aqKOlEY1d0m1edc05BwTq0d7yhbIPBgcTQOLnALKNC6lYRVTLuaNSQE0QdjWI0Rz5fwiyXsMsl3GqJYkEjZbveElvTRxQpxLGuxgutBYID0CpcKUcsZjOLMHQYDFwph47fiyzUmr1FVODNKSlVJat49M6YWg5xKg2w5f1b5LlFmjr4Pr1eWjv4vgfPC9BqtQG0kGUenNMwxqsSSXcl23jLGn/lcck8fzVF1Cys5vs7LauWPiJBED4VRB4JgiAIgvDZ0tyq9SY0EwIfisMBuLz8/mNvLFtYRjz0fZYB2y1tghuPabyG18k30xJ3JXySBNjt6PZu9+6xsdNy6aYM4sfn6+4qpyYpVG8dYynEPULbbd0nRAXTXHzMxc2UuqGkkIbWIeqV8/UGsHpUjKVQ8zq+PxY3tSSiMmR+L6ny3LpSHjnkuS5TSZQcorSKK7d20RvQ8zhZwx1D9HdZRlu8+DWlFe71ynedxujtNhjsSQSN4k1ZQk0jZcNkAw1bbidDlRpilAbcoFN2DS1gl0vY5Rw4W8EsF9j3V9i159jFQSWHqjLwCPAzoLVzZW+PxWRCZdS9nkO7XRd8N19/507l0PH7is4bnQdOD7EgAmh8jYrnbVlITYKIy79pDM0hCDy02wE6nQBatxDHXlky7sMYGmtrvjc5bccJuSA4HjXjY2xuNWsmhPjfjOfdnSLipJEgCMKniMgjQRAEQRA+W549e7t195ws+NB0OsCjR8fXvXhBiaCH4HGx5qazZm+QMcA33xyvledkxGgErFb0O7vdcSF0UwL5Ph3f4QDc3NDjttvAZELjZywAuEOIx+DukkqtlkO7XUsh5wzy3CKOM6QplUxnmUWaFlVKiLt8uLtHa+oU0lpDqRY8T5dbrmrJ0RRAfI7qMSge83KlsGiuu+ckUi09rHVVAskYhzTVjQSSB2trWeWcrUaWjOHHcmXHE5dUe2VXD41kUb8RpZmcsQj21+jsLzHYrzFONhhGF5hma1pfn1ygk++qxE11zKgHvZQP5KMJkiknhhawqyVwtkSxWOLQX+LWDXGIdCWHqFgbMJdAcINyM1ndOdRqOXS7dKFzVD82y7Q8B5JEHUlIFocshPgrJ4kAVMXUlCRyaLUsPI9G7NLUlqN7Cp5HvUS+76PbDeF5IZwLkCReWTbuoyhqQcRyj6UpF06zIOJRM5KD9d/wv5FmkojTXU1J1EwTSR+RIAg/ReQ/bYIgCIIgfLY4Bzx9+m4f9oqCeoLe93hZnt99PHFMZdGniST+MMyjXMDxhjBj6lGvJCGZ8uWXr4ocvjTHzviDPkugNK2ve/mSfm8+rz9EW1tLIcCUPTlUMM2r5w+HAmlaNLaOsYhRJ+XFukwKeVDKRxBQvw0VIKtKCvH6eiqhrkfPeLsWoMrnoMvbeQyMS6P5Bay7h+qCZV0KB1euVa/FEPXmHK9rZwGVZZQYAjxoTeKI/y7LXCUxkGXo7l6gt6USah4pm2Vr2laWbODbjEbKUB0myZjye7QDpFPaUGaXS+BsDrdaAGdL5PMl9r0ltkkLUaQRRUAU6aok3H7LXVQOYejQbgPTqS2/d+j33Yn84c1lKJM7LPLq88rr7rmniTqbalHEcohGu2iLWRBYFIWFMQ5JYqtRNc+jY/G8AJ2Oj8GgBecCpKmHPPcAeDBG4XCgU0PnmgvG6WdO0bVaJD35Pc+Slf+tcdKIx9HqJNlxwkj6iARB+FwReSQIgiAIwmfFy5eoCm/vK4V+E3hD12Tyfo6L6XTogyl9+K43kv3hDzRSFgS10OHjP+0Qal7CkD5AK0X34/t0P3wfXCzNgojHcU7lEn/wpg/bBp0O9Qf1ejnStKgKpkkKGVirq7QQrTpnIcCjYwG0Vmi3dbnJikbB0vRYyLEUIqGgy8LqOgXEo00sNQBUJcssISgt5MqtWDQuRV05dRE2iyHPQ5lc4gungiycU0gSKmWmpFPdoaOULou1y/RK7qD3W3S3LzCJLjCKSAxN0zUmKcmhXvLyaJysykJVzwPIh0MkswXMfAm7XEA9XlbJoXy2wD6YYB9REfXh0JBDN4C5UghDW0oRkkPzuYXvO7RaDv1+PQpG57o5QqaqsTI+FlZYzRLvWg7Vo2a+78oxLlc+NqWVaLyMEkR0LkkWBoFFqxWi0wkwmQQwJkSee0iSWhDt93Xah4+Vt/NxMojfpyyAnKsL7DlVxLdxkohTRM37OU0SyaiZIAiCyCNBEARBED4zbm5InvCmr/tSR3UPzt2kKf1Ou11fl2WURnpbmj1Ap0JosyG5c3tLx9tcY8+jZM3tZ7xtqnl/zXLpbhflh/a6p+h4LX29pYu2jRXYbgtcXmZ49oxGyVgSjEYGk4mF55EUAkgKBQHFo3yfk0q6KlBuDlXRxi8e8QIoEaQbG8pUuWZeVwkjFkMsM5rPnUVSnrPIUVXKh8+VtVyY7OB5DvXomkaS8CYvGofjbiL6vtxOZihdkxwswpsXGMXrsoj6ApN0g2m+xjii7qHQxEdiiFND1UxZoJGNaX29WayARwuoswXwaAG7XCGfznFwPez3CoeDxn4PxDGlobJzwDxTCAJbjZS128BiYcrXluQQl1LXSSxXnTdeX8+3Nzeb8egcp4b43HJCrCmISLLYsuDbIkkckqSWUpQgAlqtAN1uCN8PYYyPLPOQZT6s1cgyVb1HmuXdnGLiVBCnibrdurie03Aslij9VgsiEoL1RfqIBEEQ3h6RR4IgCIIgfDZwimI4fP2o2vl5PfrCpClwcVHfz6l82u9J8oxGb3dcnHjhD71H/TWKRsP6ffp6FzxC09w6dvoVOB5BowSIwXZrkGVUNh3HOZIkhzE5nCuq8SLawOYhCHw8eqThnC7HfoIqgdVM+3CxcN0nxeXQtA6dC61pxX0tkKhEmkejXJksOd60lab0ONyZw6NjdKG/py4c+pkfJ45ZTih4niqP01WJlDy35Va4crRsn6C/W2MU0zjZJFljmm0wSc4xStYYxFfQylZSSKGWEzxjZjod5LMV8jmlhdTZAvrJEm41h12dIRtOEacedrtaDiWJhs2A7P8Din8gOUTdPFRK3e/XcojX2dPry5ve6AB4I1sUqfJ1YDPS3AbX7B9SRwXVSrlGko26h9ptwFoeL6MLv8605c6h0wnR7frw/bAcMdNIEh/WekjTsmjb1BKU+p7oeh4vYznabtO/Me7r4sQgP5WmRG1uQCTpdyyHWCZJH5EgCMK7If/5FARBEAThs+D3v68/oD6UMNhu6wTRdEofYPlDa1HQh9mzM/r59L5aLRJTq9Xrj+dNu5JWK5JRcQx88cXdv9PcXNYcRUtTgzQ15aryopRCOYzJkOf50TpySp9oAB5oG1ULSVJLocOBUyq2TPIcp3aOt5zRfXJnDHUE1T1DJGmaW8NcOUpWiyL+W0638CUIXHmfNFJGpci6TIKp8rFIcpAYqourATrO/daitb/G8HCBwWGDYbTGNN9gmlIJ9Sheo53tj1NDAGxdbQRohWw4Qz5fwcwXcKsl1KM5vCdL2BUliYpOH4eDOkoOpamCuVHIL7kDyJaFzZTg6fdNKUNcOcLoSjFSSzUe0aPnrir5xsktThHx+c0ylkks4Thd5apEVhA4hCH1OBlDxdRpaquRRpIx1I3U6QTo91sIwwDGBMgyD3HswRgPUUSvGb9+3B/EI2Sc1uNEUKdTp4iaQov/xlr6d8W/0xxb47RRc8RM+ogEQRA+DCKPBEEQBEH4LLAW+PnPX588+PbbOumgNW0eu7ig7zll00w5nDIYHCeH7uK77zit82bHvtvRJUnuui+Dw6FAnhtYWyDPM1hrUBR59QEe4I1iCtZqGNOC1m0097bzB3WSMrWkaI6FdToOQcBpIVVtdLtrJIrG5XjrloYx9qgYmxNDtDWLvoYhSwEH5xyyTJcdQ7p8PXh7ly3PMcusujR7vwdsnGFwWKO7v8TwcI5xssE8v8C43FA2iF/AczSTyK9BlRri8xGESKZUOk1F1Et4XyygHlFyyMwWyBEcyaHDgTaMmecKxTfUBURjZQrtNo1uDQZ1KqrbreWQ1u7kOOoUEI0ZNneo1QXW9aiequQdje3xljsHz1NV/xBtt0PVP5QkJIj4uYehRaej0W57GA67pSDykeceoshDUXjY748lTnM0zBggiur+IKXqMTMur26KTjqWWiQNBsf/vlgSNfuImpfX/VsTBEEQ3g8ijwRBEARB+GTZ7d689LopUh7i9hZ48gRYLqkb6eKCPtg+fky393qUSPo+7HbAL3/56ua0JllWf6BPEvqbIHB4+bJAnueI4xhxHOPZMyo/Phx0uUpco9XSGAzCSsocF1ADAIucemU69yLRmBePc9lKrtAoUL3ljBNOtKrewhhK9QC1VKLNaTRGxukZkkIOec4dQ7pKhHmeanQS8XiaK4WfQpI4pIlCK96it9tgeLjAMNpgVlAJ9SRZYxSt0Ulv6kQVSLk05ZACkPXGyOYrFLMF3NkC6mwO/XgJ78kCZrmEHY6RF6qSQ1FUjpUdFMw/Kpi/q5NDLIdaLYfBoO4C4vJm3+fn4Koxrfoc8rYwVY2f8ba45ta4wwHluKBDUXCnk65eK15vT6LGlq+1RRxbZJlDHPPj0vhbu63Q6wUYj9vw/QCAXyaIfKSprgQRH2+dUKLzyCKz06nHLgcDlKN03JtV94YpRT83BVFTQHE3F3cbSR+RIAjCx4XII0EQBEEQPlnWa/ogenFBfUQP0RzPahJFJGaY589JDgUB3e92S4mJp0+/37HGMd1XnlNpd7d7vzyKYzoOz3PI8wxZlkGpGLtdgna7QLfrEIYavV6A3a6NdttiMFCYTm01lpRlrhQeCs6xjKi7ZpoFyb5PY01pimrcKYpI7JBYUlVRNPcLceF0EFgo5eAcjbMZY0shRMIlzzllpKpOouZWM993VUJpu1VQRYF+9AKtUg5Nsw2m2brsGtpgeFjDNxmNk3FqqByDY0dmPR/peIF8toRdLODOllCPF/C/WEI9XqKYzYFWG1kGHA4kZvZ7j5JDlwrmQpWl3Rpa12Nl7XYth6gHqJZDJDiON5fVySsSRSzEjt+DNH6XpiSqOHFkjK6SR5waArgLyJaPVyDLHLLMIk0doqgebaNRL4V+P0C7HSAIAjjnI8t8xLGHONa4va3FDwsi7hEqClTCqdWqxVuvR91bnQ79zBsBWc5ykXyvRxdOH7G84/cDP86pJBIEQRA+TkQeCYIgCILwUXF1dSxzHuLZM+DLL0nKLJfvVoZLvT4kcwDgq6+A2azeouZ59CH6+7LZkIzi0l5KZTgYY44ueZ5ju83x8qVFr5eVaR7A83ycn7cRhqr64J5lwO9+5+HxY1V+AHfVGE+r5fDiBRolxzTWFEWukkLNbWzOqSppwmIoDCnVBHAPUS2Gttt6NOpYDNWpoSCon+vhoJBnCq10i8HhEu3dGuNkg1lOqaFxQuXUneglNFwlh5x7VQ5lnT6yyRLFgtbX42wJ78kc+skK6tECZjyBhYc8B6KIRtkqOfQ7BfMbVW5OIzlEEshVySHeJBaGpny9XJmUOS6qYjlUFKoqDeeEUXOMj9JfJKms1dUoVnOLGZdTK8XJIFtKPlsKKIM0dVVKyTlKNnU6GoOBj/k8QBiGsNZDUfjY7z0kCQmi7ZbunwURj4jR/dKFy6vpvUOpu07nOEXE3V/WAodD3UU0Gh3/22sWYHMJtvQRCYIgfNqIPBIEQRAE4b2TJG8+TvbsWf27RUGChbcsvQ7qcKEPr/M5fTB9W7hLpTmK1rwfz6s/NL8r1lqkaY4wLDCfR1AqRZblMI2TlOcO260HpTSU8jCbaXheCB5nurnRCEONp08N+n2SGFdXCt9+q6si4u++85CmNFqWZcD5uYfxmEbUAAutVVXGTIkZi1aL0kScGEpThd1OV2Nznsebt2j0arfjomVXCgmFNHWIY0o4qSzDYHuO6eEZZvFzLNLvMIu/wzi+QP+wQVCk1UY1KBJDtjFS5rRGNJwjn5IccqsF1KMFvC9opAxnS9hOF8aosoPqWA6l/556lYyp5VC7TWKNk0NB4MoRrGM55PucCjreWJbnJL+MUVXC6DQ9FIaUMIoiANBVcokkka76h3irHI+XUerLIsu44JzKyWlMkH6v19OYTEKEoY9WK4S13EHkI4oUbm7qFfQk8+h93evRv6k0rQVos4R6NAIeParf75wiYikYRXRfvR7JJE4R0Xu6FmCcXpI+IkEQhJ8uIo8EQRAEQXjvPH9+/EGzCX/oZJ49q7eI8ZgY8GYfPJWigmul6O/e9cNqv/+wePrtb4Hz8ze7L2st8pzEUJqmSNMEWZYjzzVGI4N226DX8xHHIYypIxhxrHB9rTAYkEXxfYcXLzS6Xfr5H/7BQxwDt7c+fJ9k0d/8jY+bG4XJxFW9MFpzsbVFu+0wmzkoZaAUpW2yTJUl1ADgQylXybswtAgCh9HIVQXNWaYQx7oUKMB33/noqQOmh29xlj7DLP6uFETPMdo+Qze6ggKgdEMINQI7WdhBMl2hmHFqaAH9eAHvCV3cfAbn+TCFQt6QQ4eDxv6FQvacV8o7WFvLIRJiDsOhKyUNySGWQvyVe4WaG8t4tCzPSdTRJjn6vXotPJ2TKKK/afY+cQKpHgmsu3v6fRJERWGrEbMkcWW6js5xu+3Q63kYj0N0uyF834dzPorCRxR52O8Vrq/r5BBAjxWGlPzhbXtRRMcThnQdy9XJBKVAqwVRmtbdRUlCt/V6tC2wmSJqbkkz5njtvfQRCYIgfD6IPBIEQRAE4YNwdnb8ITRJ6MPvxQWlIFj0KFV3/4Qh8E//KY2iBQGJoYdW2j9/XqeCvvvu3Y/122/vv81a4O//HvijP6pH25rQqFmGOI6QJBnyPEeWqTK1o+F5PjyvDc+jcbxf/5puOz9XVVLEWpIX263CcGiRJAoXFz7imH7W2uH83MfjxwXmcypm5iLjP/3THEHgMJ/Ticoyui9rVSmyFKLIq1bbA/WIFo2iAdutVxYz0wumNdBSGabRd3gUf4Pp4Rmm+2/Rv34O/c0zTOzLSg41Xx+lANXykC7OUKweoXj0CO7xI+CLR1DlSBn6PcACKBSKjMbKogjY7zX2f1DI/vE4OeR5tpQVJFlYDlHvECeHjkfLmhvUuAOKzgM9XxKbrloHT8kZV6bM6HWg7XS0coLbQQAAIABJREFU6p6LrWkbHSoBxemeMDTlFjHuH7KIIofrawWlVDmK5jAc+hiPQ/R6IXw/gHMejCFBtNsp3N7S2CYJLHoOYViXUrPAy/O63Nz36d/PZEKl7txPxGNmnCQ6HOjS7VJP2Gz26tp7GsGrxZT0EQmCIAiMyCNBEARBEABQqmCzeVjWXF292QhXFNXlu8xvf0sfgl+8oA+wLGJ4HAYg4fTll/QzJTruL6rmsZqf/ezNnt9DcEcL328zGQUAl5eU3BiPqeS5KHIkSYIoOmC7TbHZeNBaIwh8pGkHt7caWqMUOJzaUPjd72jDmOcBt7cK7barem547Ge/J1mx3wPWOux2JFPSlEqVv/nGg7V039fXHgYDV96/Ra9HRcp0bm214SrLFFotVYkBax26bYtx8QLjeA27v8AsO0d/e4H2yzU6V+cIrzcAy6Gyb8gYGjPTwwDm0SOYJ4+BL54AXz4CnjyCffwI+XSB3HrVWFkUUddPFGns/1YhTXml/LEc4kLq0+QQv4+a6SGSPlT4zaXStPlNoSjq9JBSPGKmym4jeuw4JhnEaazmunuAu43o+3q8DOV4nys3mFns9w7X17oadWu1HEYjH5NJC0+fsiDyYYxXCaKbm2NBxCklXmPPPUQ0/kavH5dL93rAYkG/6/u87a4urI4iEkS+X6eIWFDye5uFUpbVYqiZJJI+IkEQBOEuRB4JgiAIggCg3q60XB5fz6MtztHts9nD42FxTB9Mb26Or7++po6V4ZBSEv1+fRuPTbXbdUKCP0Sfyire6gTQB9270kBvy1/+JcoiYpI2vIWK2e8t+v0Uvh8hiiIURQGlFIIgQKfTwWymsVhY3N5SegQAlktTSYxaFIT4+c9zdDpUdE19NvTJnteVA5QcurpyuLrS+PJLixcvFBYLezSypLXD06cWg4GrEjW7HX3y930gDCz6dovx9Tkmz89xZp+jd3OBzvUFOtdrtG82UEUG51Q5DkVSRisaOYNWSJePkJ89Qf7oCZLlEzz3v8TgP3yEya+mUJ531DkURRr73yhk2d1jZa2WRafjMBzaMjVEcoj7eWhzW73WnuUQjWSRHIpjVQme05QR3Q/dR54r7PfcG8T9QwpFoZHnrlHwraAUSc1u11br49PUIU1JEN3euko0ARadjsJg4GGxaKPXC+F5fimIfESRxm5HI2aXl7Ug4rQSd3nxv6U4pteckz6+T79zdlaXVTeFT5rWY2bOoXz/UN9X898ky9A0RZW0kj4iQRAE4fsg8kgQBEEQPmOa6+15O1JT6nC65+VL+qDKKYiH0glXVzRCxskhJo7r8TRrUUmWhwhDemzmcADWaxwJg9/+9vX3c8puR5KI+fWvKcE0GNDzG48der0ceZ4himIolWK7taVYCHE4dKo0R5apaj355aVGGFIhM58jkhbA9TWNTXHKYzy2GI+BxcKW50fh6krD94Hh0OFnPzO4uvLwL/5Fil//2ke367DfK8xmtj6PhcXt314gzJ/BfLPGInsOdb5GsLlA++U53CEBQBmaIHBQuuxFUoAKHOxsjGK5QrE6g/flEvbxGZLZEsnsEZLpGXLnI0koObTdajx75mOytzB/Wcshz7Po9Ui+8La3VsuWo3GmlES1FOIEEe9Oc67eWJam1G1Ea+1rocUdRb7PBdOUMtrvqXvIOVeNuhWFhjEsiOg88XYxLsgGSBAliUWeW7x86UopRVKJSth9zOchvvoqRBAE1RazLPNwc0MJOn4v8r8J7jyaTGrpSimn+vc4RcRjZu12PYJG6TKUY3b1e7zXq3uLGO4Oo012dwui+3rHBEEQBOFtEXkkCIIgCJ8paQp8881xUfTphrPf/a6WR48f0+Xp04dTC7x5qdejTU7M+0gJbbeUXjo7e/W2w6EePXsd1lICqtul5xdFDn/yJzmUSvHNNxGcizGZUAzI9334vo9WizqI/vAHhefPFcKwLlVOEoXra0qddLucfKGTlGWcmqFz/vvf++X4ExAEFoeDB2NQShoaZQNQ9uEA/+7fefjDHzTGY4dWfIvB//vv0f7m79D7/d+h/du/x9lhT2NcFgjCOsmiFJD2urCPz5DOH+F2vkI6e4R0doZ0tkI6XcGEHWQZJYfimORW/i1gfq9RFCRslOKV8BarlcGXXxq02zRixukYZrPRaLUc+n0Ha0mANOUQpcl0VS59nB5yCAIF33dVkXUUqXKEUEOpensZl1SzsOHRr16PR90oVRTHFnlOkujFCy66plG2bpcSRNNpC91ugDAkQWSMjyTxsN3S+55HOXmkiwXRdFp3C8UxvY+40Jp/t9ulJB+PmXGKiBNE9N6r758l0V2F1c1RMxrzI9kpfUSCIAjCD4HII0EQBEH4DMgyGqNpkiQ0SvbkSX1dUQB/+7d1R8q335KoGY/pQy1Af3Nzg3Jb1KukKX2wVYo+3L4tSVJvXLvrefj3/K+XqytOuLz+MUhIFMiyFL//fQKlIsRxiv1eQ2sfZ2c+2u2716+RqHD4xS8MgoA2oiWJh17PYjIBRiMqvB6PKVH0/7P3Hj2WZeea3rO2Od5FnLAZmRFpylexDC95ebsvWwLUkBsIGkrQTJOGAGmuH6BJDzQRIAGNhiBpIAGaCBB60ECjNdLta0SyilW8ZJl0EZmR4d3xZ/ulwXfW2edERJoiWewy6wECccw2a++9Epnrzfd7v8NDF9fV7O87eJ4DaNrtDKU0WaY4OnJoNDLCcCLexBOhIYwo7Dzi6P/+itc7n3N78DkL4wNcZyK2KMhSiBptwltbpGvrVF5b5aSwjntrldHCOl3dZGU1m5Q6Sd5QEEhpWXgBUSRlZZKlk1GtaioV/Vxx6Lr7KKVkIsycnDiTAGcRjy53OHNdNck4yjOGhkM1mW+m+1kuNCmlpvlDpkyrVssmJV5y/6JIupiNRprjYz3dT6mMatWh0fC4caNEpeLj+1JilmUe47FDv89EVGJmvHnbeTPnkyQXe6QUjmmJW7Eof0ZMNzMTZD4rEI3HchxTIleriag0K8LOuohm297PikSvMrctFovFYvkmsH8FWSwWi8XyLaPXy7Nv/lgMBrJIni0jS9Or3bK0FhHGLJorFRGOTJmUIQzFJVGtXn8+E4z9+zAaySJ6tnzOYDpPPY/LpT3ApONYTBgmBEFAGIb0ejGel9BoaHzf59Ytl0qlQhQpPE/h+9n0GcSxCEBhKM6aODZt2U3HMykxu3UroVQSkWY0UqytZWSZiCtBoKhWFVtbCUrB0pKm11N0u4rlZbi1FtI42aF48YDF/fu0Du5TeLJNMEwZj6XUzXE0ulmkd+sNBltv0d96i/3Ft3HXl/ALEMfORLBQlP2Mk22XYhF6fWfaXa1U0rRakj30KuKQEUGMmGOu3ZTimUynMFT0+zKnymURocRxpCailWQPSfmZ5A7FsbibXFfcTcblZNrbm45ooAiCbPIDFxd6Evwt21erikbDZ2PDo1oVBxFIidl47DAYiHAqopRcrxF+pHwwF3xMmdlwmLuZjKBUr4vzzriKjNAloeDzgevGBbWyMv9nZza/qNfLXUrFYu46snlEFovFYvk2YsUji8VisVi+ZRwdyYL2j4Fp123KalxXym0Mvn81E0WpfJulJQnIvkwYirjTaFx/Xq1/P/HItK03nc2u4+REruXsLHd0AESRZjBIcJyEKIoIw5AwDEmShF7PpddTuK6D6zr0elWKRUW1qielVZKF0+1Ki/bRKL8pQQCdjrSyPzhwaDSkw9Yvf2nECYdqNWNnx8VxoN93cBxNva5RSjMei7OoXBYB5/CZpvJsG/3ZQ27s3mf1/D5LF49QSUKmJZ8oUxAAJ/XbnL/+FrW/eJ3OzXc4qt3mol8A1LSDW2ucUdKSs7S4KKKQ72taLc1rr6XXPuPZ+z1bUnb5txFCTF4RaAoFRaGQAfm2Z2eSQ1St5u9nRSbfV1OR0nFElGw200mYtJ4INxlBoBmP4fRUStdMm/tazaFe91lZ8acOIqU8ksSdCkRnZ3B4mLevNz++L6WO0mUu//Mg3ezy7Uwu0tKSiDlGVDP3aDS66rYzgdXt9rwryIhuYSj7zWYQGReRzSOyWCwWy3cJKx5ZLBaLxfItZGnpD19YDofwt38rDgcT1uv7V9vQX8Zkyhi++GLesWRI06ud0AyzbqavQ6cjP8vLz99mPBaHRhhq1tYSIGQ4HDIej9A6JU1FCGg0JKuo1yvR77u021Cvy8BWVlLa7YxaTUQK4/SoVKRTWLudX3CnI8KI62r6fbh1K2MwUMSxCCq3biUsLmZTscFx9KSDmqbbdfAvjvE//Zzlwy+4cfY5bz17QMmJSBOF52tcB+IMLuo3OV16g5OlNzhcfIv+jXuchzXa7XTant11RBRaWjKd3K6bJyKAmTbt5jldJxDlQoueiEx6IqRIaLSUhUk4tZQSmswgEa+iSI4xGDh4nriG4ljmWaWiKRbz+5KmGWGYMR5rul3N4aEiyySbSMQ2j0bDZ3XVo1ot4HnunEA0GokgGUXMuJ5yF1GjkT9H06lvPM7nv3ER+b78+apU5J4qlbuIjNgzGuV30+R3tdsiLpn7Pes8Ggzy3CLjJKpUbB6RxWKxWL4/WPHIYrFYLJZvAbu7f/xSNRO0e+9e7h4ybb1fhAkyhlx4mHUrvQpKvVgAmkUcNPI6DGXRXS5fH34dxzHDYQwMOD4OiKKIYlHjeR6Liz6OIzVCJvw5iuD8XE0cJSnNpiYMRewYjxXn5w6jkeL8XDpzhaHC9zX1usNwKCLLxx8XUIpJALNmby+j11MUCg71uow3TeVcKo6oPX7MxvlvqT3+gubTL6iOTshSYBIknmmIVm5wuPAG4d3XOV15i5PF1xg5NarVbCLqKNaaGWuIMCXhy3pa5rS4mItbs+6h2bygNFVsb7tT4cS4h0w3Ma2lJMxkD/X7sq9cqwhHcSxdzOIYXFe6miklv4tF8LwMcFhYECGuVssmpXOaXk8zHGZT4dEIeo2Gz/q6R63m4/su4JGmLqORYjwWB9H+vggzs6KndKHLxRsjco5GMm+0nt+2UpHA9mIx7w5o/kyMRiIqzWZrmVKzjY15V5DZJwwl78txbB6RxWKxWH542L/mLBaLxWL5FhAEsLnJdOH+qq6jMMzdOmk67xAyTopGA9544/cfm+NcX7r2PLrd3LkxW1b2PPb2ZOxKySK9UsmFoySRErTxeMxoNCJNU0Czvq7x/TKu6027ec26oI6ORPwpFjXDoaLREOEkihSdjgRGB4GIJqYtvOPIeX0f+n1Fv+/guuJMevPNhH5fAqGzTMSbxcWMpcWE5rMvWf3ibyj+9jPq+49QaYLOIJ509hoXa+wtvcPZjXcY3n2b8/U3qa7XiCJFrSb5PW6qaBckrHo8VpRKGQsLxr6lJkKKCY7O6HadqWAkXdty95BkGxlxiKn4Y3KJtDbuobyMyxzHcRSSSyTfS2lfNumSpyeOIz3phCZlYv1+husmlEqaQgFKJU2j4XLrVoF6vUix6OM4/sRBpKbd+w4OmJbGmRwhcSxJmZnJ45oVe2bFm9mw6lpt3uFjAq6HQybXnP+5MsevVHLnltZMnFSyX7+f5xEVCnn2l80jslgsFssPFSseWSwWi8Xyb5koyhfQX7dUzbQTD0P5naYiJBmqVSYL/xeTZfDkyfXlaV93TMOhLORng6tfVMZWLjMty8qyDMcJiaIRw+GQLAvxPGi1XFZWCjhO3gGt23U4PRWxwjhLzLlOThyiSLG4mFEqiWsnitTEdaSm7d3HY0Wn40yEBRE/pCOZlKt5nsJ1FfW6ZjAQwWa5FbK+9yk3f/FXrD/4Gwq9CzxvIsJkivPWHZ7U3+Vw5V2yd98iWL1Jql3W1lKadU1T7jiDgYhCS0uaRkNTr2dEkWI41DSbkgNkXESSwSOuKM+DNNUTR5GenFsEMdPC3ohhIHPCOJJMpzBznyTnR9NoZJPnJQJVlumJwKbodDQHB5okydA6w/PUpBtbyuJiga0tn/X1Op7nk2U+UeQxHisGA2lzP9vJzAhExeJVgSgMZe50OvmfB+MkarVEBDVd/AxxLPucnc3PKc+TuX+d88gEVg8GMjabR2SxWCwWy8ux4pHFYrFYLH9iLgspOzu5wPN1s4K0ln0XFvLuTt3uvFPoVTJXskx+traufvcyp4XpYmUwLqIwzD/b2xNHxzVXwPl5TK8XkiRDwslOSik8zyMMS0QRk/KzfCBhCP2+S5bBwkI6zfY5O3MIAocgEMGg2cxv6GCguLhwpqVxcm3iollbS6f5P6bcTVxbGtfVDI5GbHz+S37y1V/z3r/+O/xoNL1v/foqnQ/+AY/W/4JH5XeorVVJU0WzmXLjRgZkVCoplYqeKykzgka9bgKjnYlTSwKpRbzQkxDxPHtoMBDBK02NcKZntlXTbm9aS3mZ54kbSQK7Zx1JIihdXIhDLAg0WabJMgmyLpUk4LtWc1hf9ygWSxQKBdLUJQw9osjj/FxNg6SNg2s2fHplJRdhzD0128+GVRuxcWlJ5vFsCViayvj6fZnbs5RKedv7WVeQcREZ19JsHlGhIMKVySOyIpHFYrFYLC/HikcWi8VisfwJ6XTEjTHLzo6INg8eyPvB4NXzjy4uZKG+uZl/ZlwXr4JpSW4En98nt8V0uNJasmqMu6NazYWr/X0RBnxfkyQxURQxGo0JggCtNaNRRrHoU60WUTOr+dNTEUMk30a6loGIKPV6RqWiWV/PO6WlqaJUSigUoNeT4GvX1ZN75bCyIqJIrabpdhX7+x6djqLblXMWixmHhw5ZqlmNdrnz8BNuP/kbXrv4BJIEBaiy5nz1Dgdv/CVfrP2cwY3XqNVFpEiGDisrKWEICwsy1jRVXFxI4LTr6mmJWb2uqVQyikVxBHW7DmdnDpWKjFVElTynSIQPEZPCUEKmTUC1yanyfc3ZmVyj48h1G3dOt6sJAj3JLTLZR5pKBVZWfGo1j0LBx/M8skwEojCUsGrjIDJB1b4v5yyXRbgsl+V5zbauPz+X1647X5a2ssI0zHuWKJJxnpzMf266s8mzywWf2cDqIMiDsYtFm0dksVgsFssfG/tXqcVisVgsf0IkLycPrTbt7F9/PXdAPHokbopXyVap1ZiUdcn2XyePJUlE1DFCU73+8n06navd2s7P5fymHGljQ5xG7bYs9pMkASJarSFxPJjkFsHqqnRDc5yZmjNEcBGBRMqRpPROyqhWVuT7kxOHSkVEICMMBIG4ccpl6XamtUOzmVEsypjTVNPruZTLGY4Do5ELaFZWROhZCA8p//Yz/p0vP+Pu2Sc0wxMcd1LaVFXsL7/L4Ts/Z/+1v6TfvDG5dkVFaRGOEqjV9NRhlJfuZWidh1mPx5Ak8qB6PWfa7Ww8VpTLmuVl6VBmxJGvvnLp9/PtXFfuTbUq5wKIY+lkFkVwdibCWq0mwpkILx6tloRUF4s+rish1UEg4pBpXT8Y5GKUcQQ1GrC6mgswaSrnN6LUyYn8Nt3PPC9veV8uz89JIyyen89/BiLymED32S5lZi5EkbiP4ng+j6hczp1Es+WLFovFYrFY/nhY8chisVgslj8BxlUxHovAYjg/l8XyrCATx7IYfpWFcJbJonlhQd73+19vXK4LN26IeygIpOvbi9jZmW+JDrm75PQU9vel7CkMY4bDMd3ugCRJ0FqTZYpKpTDtiAYiAo1GudPo/Fy6oI3H4sSJIglsXl3NKJc1x8cuQSBuJK0zQE+ychRPnrgMhw6Li5ogUNO27MfHLp2OIo7FYdRsyvniww53nn7C+t6n3Dn9Nc3BHmmqUIBf0NCsc3DrIw7v/IT0L3/G7w6WaTQkq6g1EW1KJc3SUsp47OA4+TMTkUjOY7p/lct64iTS09Iug9aSsZSmEqINTIOwtYb19YRSyQRfZ/h+QrUa47oK181YWPCoVHxqtQJBUKDVcqlWPaLIJQzd6dzb3RVXkHG/mbEZwadSEUFyNhdpNBKHWx7MLb8LBbh5UwSy/X2ZFyaYOstkXvR6udBj9qlW5/OMzH24XGqWJLkgafOILBaLxWL5t4sVjywWi8Vi+RNgXB3lsizOj45kkXz/vgg3s0JCGHJFXHgRxjlkQrMvlwPNkmXS5coEFc+Ob3395YvyTgfu3JFw6SRJJj8xSoX0+wmeF9NoSKs0x1EMh+WpWDTrNjEcHjo0GppCIS+xWlhIqddFRFlYyKhWNc2mhEmfnjrUapqlJXHdOI7kARWL0G6L2+b27ZRGI+8YJkHRitF+nzeffcYbn/+axcef8Zf7T/FcPSm/0ujlCmdbH+D+7Ec4f/kB2Z3bjA58mkoTx4oNJ+PmzYQ4Vty5k9cVBoGi19O02xkHBw5pqmi1EjY2spfmTaWpceI4dDoO1aqm33fo92XcSiUMhwnNZsjCQornaarVAvV6mW63xWjk47o+QSD7HB+L8FIq5aVdRqAxwk2jIeKkcb9lmWwXBLloY+aG44hTrlYTYcnMj9lObeOxzD3TjWz2x3Qzg7zEzGQfiUBo84gsFovFYvkuYMUji8VisVj+CDx69OKcItNBamFBXBy7u/K62RQxZjbgWqn5TmWvShTJYt+IAtchwcxy3keP5Fy9Xt4V67qyNyMSxXFMFIWcnY0YjSLSNF/ZO45DHBcolws0GvLPC+lq5dJuz98YCYyW16US1Ovp9HrHY8ntkXbv0GxmBIHD48c+ris5RcUiZJlmb08xHKpJaLOaureMABKdDlnd+w0Ljz7jzb1fs9Lbxi9oigVNmimSepHw7XfpvvEhlX/3fS5WXuOs409CroFOHrZcq2U0GnBxoVhaEjHJcHamGA4dfB/6fYdWS1MqQacjN9MIRBKWnbuq4lj29315JuI4S9E65uREUSoxKS8roFSDIPAAn07HIYqkXCxN82wp4yBaWBCXTrmcl5oZMSgIJFsrCMy9zh1BlYrJpZoXFo3oMxjkLezNPr4vwtLWFty6Nd/NrN/PxaIokrlmBCKbR2SxWCwWy3cL+9e1xWKxWCx/BNIU3njj+u96PRFlFhbEnQGyYF5bEzdOuZwHDr8Ik/3yPE5OxMU0GDy/a1uWiVAUxyJi3bwpC/taTdwpWZYSxzFxHBMEAUEQkKbpNMTacRyePPE4PS2jtUKp+ROtrmZz78/PnUmos+bsTMSU01Nnbt9+X00FhPFYXpuyswcPpAX9yYm0qVdK0WiIo+fgQISkTkfR6ym8aMTNo09ZP/81GwefstJ5hKs02WSIqe/T2XyHk60PuN/4M8LX3qC24FGva1qljPMdh8FAzmfudxBIqZgEcjsTESSdaw1/cuJQrWakqeLszCGKMlxXkSQiaJkgcilXk/I9389ot01+UYxSGaORy2CgKJVqaF2iWvVxXRet85LHWQoFeW5GLJwtGQsCmQeXhR4Qh9lbb4noNCvuRJHpunZ9mZk8Dwmu1nreRaQ1PHki720ekcVisVgs3z+seGSxWCyW7x39/tdvef+H8LJzxbGUCvV6ItgoJT9G5KnVXu083a4ESF9cyL6X6XTE0dHtzrs5Lt8P3xeRoNnU1OvS+Ww8HrO9nQtFSikcx8HzfDxvvg7OlCu1WulcfhOIiPboUa4SOA602ylaS/v5paWM/X0JrTaZQLPs7ro8eOCSJFKGNhhAFGkuLhSVClQqGb0ejEaK4UBxM33C21/+grVHv+D2xWcUnGQqolD0uLj5Ng+bH/Fk6UOOV9+huiAKitawUk/x/Ywsg709EY6UyrOKkkSErigSASVJjDCj0FpNHFRGMFL0+yIGKSVd0KrVq9lGkgWUEQQprislcK5bIMtqlEo+7XaBWk2udWND3EBxLM92towry2Q81aoINLNlX7NikckeMj+9nux/eirHfJnIY/Y3JWZHR3Jck0dk9jW5RDaPyGKxWCyW7ydWPLJYLBbL9wqT6dNo/GnPawKrL2NKfozrY2sr7xxlMoCGQ/l5Gd2uHK9Uku5XJuvIMBzmwtCdO/n5t7dlfFprzs8Ter2Ir74K8f0+47E4hcpll3rdw3GuC+nJlad+X01CrJmWZ10mmzEfKSXiTK+nuLhw5sSFSgUaDRGRDg8lOPvJE5dCQbO4qFlby6ZC1empZmFB066OaNz/DO+3v6L9xS+o9Q+JIshShXIVvVtvs7/xEeN3PyB99y10scT2todSms0y1OsZ/b4IRKORy2gkY0lTGAwUy8vptJzMiEWViohCtZomDJ1J9k82cfVoNjdhcTGj23UoFMRhNRsCHgQZOzuaIDAd8RStVoVms0SlUqBYdPntb2XOVir5/Njelu2NG2hpKXcSmRK1KBIxUTq5mfI4+W2uw+xj9ms25zORJHA8Lzcz+0ZRHshu9q/VRNSyeUQWi8VisfywsOKRxWKxWL53OI6UhIFk1pye/mnO+/Sp/B6P84V7pyML88VFEQCyTNwbJtS62ZwXWwyjkYhFMJuZIy4PU5o0u5/pinVZzEmShDCM0HrIYDDg6AiKRU2jUeDGDQ/nSsjRi21U5+eKUklPWsHrqQBhrjeKYH/fnctOimOXkxOXhYUMpfSkm5hCKbke0wktjqU0rdmU731fLmz81QHrn37M2+d/x8rupzhJTJoACkbFJruv/ZSTN/6cszd+wms/rlL1NStVGduzZ3DrVkqlkrG0JKLUyYmD72uq1TykezSSMO7V1ZTBwEFrub/ttkZrEZCqVU0YZmxtzWc4KcUky0hz40ZGFGXU6yGuK9sFgUep1OC11wo0GkU8z6NYVFNXkuvKGH76UxGQ9vfzzmb1urjMhkMpFzOijhF5zO/LHc3M68t5QmYfI1CZ9yaPqFKZzyW6vL8J3rZYLBaLxfLDwopHFovFYvleYzJYFhf/dOfc2RFXkOOI4FOrifNHKVhels/W1vJSn+tCqs/PZfHfaEiOURDkC3fPE+eRKRnTWrYfj6V1PIQ8eTKm1xuwvZ3hOJo01RQKBdK7+Eb8AAAgAElEQVTUo1jMWFhwaLVSXiYWXabf1ywuZnMZTZ2OYjCQi9jeduh2HZaWcmVrMFDs7Tl0u1IeZtBa7sX+vkunI6Vgvq9Z1Mcsb/+a2//PJyw8+AR1fIKjpCOacmD02hscv/4zdm7+jM+ztymUHJaXU5Khg1IJrqsIArHFnJyIG6hUkjI9z9MMhyJcRdIUjl5PTT8LQ0W3q1hclPviOBm7uy7lsmZvT8rTzs7mLTdaa4IgYTjUbG+njEYFNjeb+H4J8Ikin35fxD0j+IUh04BvEBHHceQ5DgbyLE9ORDyKY3nWs13JTA7RdaVis3lE4/F82ZrryrFmA6ttHpHFYrFYLJaXYcUji8VisXynMY4XgylzMp+nqYgtL+te1u3mTp/fl6dPjRgiIpHvy/lrtTzoendXRIJKJS9lS5L5Tm1ZJgKC6zJ1p6yuymJ/ljCUEr3z85RHj2IuLgJqtQFZpul2XeK4xLNnPpWK5pe/lH20lhKrQgGePHHnjvUqOVFaw8pKOh17GMLurjct7zo+dqnX9TR0GphmCNXres618uyZw3CocIIRb59+yhudj7m5/wnNsx3Q4E+2HVSa9N76iORnP2H35p/TdRfRGnZ2HAYDh+VlcUG12ykbG5LDdHjokCSKhQXNrVsJy8viODo7c+j3FY2GJggUjsMkd0ixsJABiixTFApyM6JIOqmlqWY8dmg05Bq01qRpQhwnKAVLSxWq1Rrttg94RJE8a9eV591qiRBoRJrTU3n+jiOi0ngMv/qVfO55Mj+KRQm2nm17f5nxWALQzTyKovk8IiM0LSw8X6i0WCwWi8VieRlWPLJYLBbLdxbTYt6UGIG8PjycF4tMh7MXMR7Lgv1yjtDLOD3NhaEwlHbl7bZkG/l+Xm52edE+m3G0uzsv3HS7EnK9sCAB2f2+XMPsPqYb2oMHY46PI4ZDj5s3UzY2XMZjF6UcarWMYjHljTeSqUvJhHXPkqbi/imVNKORmt7LOM6FnyzLu3nt7eX/fBiPFYOBot2WDKBqVXPjRkq9LhektbiNikU5z3gMThLR3P2Stz75lPXdT1g++gK07J8kEBeKXNx+n7N7H3F69884rN1hdV0yloKOouplVCqap08Vd+/G3LmTsbmZoZQEWI9GcHHhsLKSEoaSo3R+LuKR42hOTxWnpy6ViqZSEaGrUNDTUsDFxWzqnCoW5f3duynNZkajEeJ5EUopqtUqjcYSpVIJ13XZ3pbudXEsz21rK3eYSZD2/H2/eVPmSKcjc6fdFuGx1ZJtu92Xz93hUO5rtZo702wekcVisVgslj82VjyyWCwWy3cWrWXR3O8z1/Xr9ddlYf48TIbQ5c/KZebKsV7GxYWUFjWb4gpZWpI26CbDZn9ftrkuiwhyl8jRUe4MgdwBFYa5MNXpJJyciGA0Ho8JgoQkUXS7BZQq8eabGRsbct7zc0WlItlBlUrK7dvpC68rTWXMt2+nPHrkTjKH4OJCwrFLJc2zZ86cABaG0OvJB8WiplzWE4dURqul549Nyp3hfdp//2sWH/2ahae/RcXxtI09yqFz6x2ONj/iN+U/h/feoNzMu6KFfcXxsQh1R0dSQlYua87OXCCjUkmudG7rdh201hweeqytJcQxHB9LFzdxX6VUKnKcXs+ZZjWB3Iv798116snzEIfR+nqJhYVlisUi/b5LtyvP2YRL9/vyTHs9cZ+ZazAlakYo2tnJO6gNBnKfzs/l+XW7MhdKpavz9DJZxqQk78XbWSwWi8VisfwhWPHIYrFYLN85kkQW6eOxiA+OA7dvv/r+Jyey7+WcFylHevXjHB/LuU3+TLOZl5adnkq5mu/LMZeWru7/7Fnezcp02QLZp1xOqFYjgiBgOByytyclVa6r8H2POK4Aco4kkWs5OnImrheH9fV04njS9PsO4/Hzr+NyYLdx3TiOCDKLixI+feeO1NaNRorHj12q1WzixtHTjCBzQP/pDsXffErhN5/hfPL3uNGINFG4niaKFceNuzxu/5jHix9xuPEBXqvKxYVDpZLxejOdhGqLePLsmUcYypj6fahUMoJABCBxCekrJV1pKl3VRiMRwIwQ12hIyd7iop4GfpdK4i7yfWi3U9JUfvRkMrRaJd57r0WlUsGdmTTb2zK+3V0Rilw3LyGrVkXQNO9BXEKffSbP+vxchEYj6rVa8tpxZH6urclzefbs+c8tf14v38ZisVgsFovlD8GKRxaLxWL51nJ2dr2Y0+uJa6NS+XpOIcNgkHeymuXRo1yQehUePxaHkwk3BhESIM+xybI89PgyxrW0sgKOExNFMa47ZDgc4TgRp6cO/b6P7/ukqUezmU0dTKORptnMcBwRi4pFTZrC6alLsZhRKGh2d12azYzB4PoL0loCpdNU4brw4IE7bd1+eCifN5tSInZw4PLokQgnQQDn5y6VSsagp+mc79M9fEjj4CHNw4c09x/gj3sAZECq4bRxk73bH6F//D6/dn9C2mwSBIrRyKHVylhdTQnDjI2NhLU1PX0Gkl+lePvtBN+Hw0OXzc2UnR2X83MHz5OMIhN+bej3HUYjqFYl3LtSEYGoXtcsL+dlaWkKjpPQaoX4vsPGRkK5XKZWa1IsFikUCjiOg1Iy70w2Va8nz7rdljD2P/uz6zOJZpFsJHj/fbmHq6syrlnCUOb01taLj2WxWCwWi8Xyp8SKRxaLxWL5VmLKeNrtq9+ZwOmVFXn/skX7Zc7O5Liz3a5AhIq1tZeHa4OUFg2H8vvgIM9Mmh3/eCxCQL9/1UESxzGjUUK5PELrYBKQrWm1wHWLuG6FTsfBdcUhMx47+L4iTUVNc11FqSRul1JJzpMk0pFsbU1EpVIJVlefb6XSWq55fT3h7Eyxs+PheZr79z2Ojx3a7Yx+3+X0VMQTHUa85myzdvCQW48fsTm8z9LFY9z4qq1pVF/m5PaHHG1+xIPGh+ylNyiVMioVODhwaCpxCzmOZmUlw3U1cSziUK+XjzlJ4PTUmXRNg1JJusdFEaytJayuimNoNFJzIpkEjSvqdRFqfB9qNT11dQ2H0dRZ1GgUieMlbt8usLkpYpHh5ESeZbcrYmGjIZ/v74swaFrcm7b3nQ7PdXkFgRxvfz/PJbrsfjPHtFgsFovFYvk2YcUji8VisfxJCIL5Ep6XkaYSfD2bZWTQWjKCFhd///EsLMwLU0EgpUPLy68mHoWhnP+dd3LhYGlJXhuR4OREBKXxGHw/BmKCICQIRmRZiudpPM+hWCxQryuaTcngmdwBarWMalXTaGhqNYeFBU2ppOl21cQxJKVqWSbnMNlFvm9EkYxWK3vuNQwGino9o9HI2N0V4WhrS6w1xYLmdnGf+s4X6N99wdrx55SfPaboiuKWJlAsaVQBktUlwtv3CG/fI7j9GuHWPZLlVTylKJ0pFvdcyuMMrTOKRU2jIQHUjqPo9RTvvJPgeeKCKpf1tGQNRKBrt+H119M5UaVe17TbmpUV2TbLFL6v8X3pojYcSgbT2lpGuaxpNFL6/ZBuV7G8DI1Gg2q1SqFQII4dDg+vd/t0OuIO+/JLya/yPBF3gkDmSrEo32stP4OBPPPZrnL5mEX4fPPNF3c9+7piqMVisVgsFss3jf3nicVisVj+JMSxLJhflM8i7dfzUrWlpdxdZL43ZUO+f9U59Dx2dpgra5KyLBEGDHt7TNq2X3WDXMfBgTiK7t8X10+tJsc9PpZjXFxkFIsRzeaA8TikXI4pFjNc18X3fRxnVl3Qk5/5a61UNPV6RrEoodSlkkYpCXhOU0W5nE1CnLMZwSih0ZAStk5HMRxetbFEkXRJe/TIo1bL6PU8DrZjNnpfcnvnd9S2v+CjL7+gFl0Acj2SLaUI124yvnWPk/brlD64S3znLmnjakuwcV8RhoqjI4edHWfS1Ux+Zxk8fuwyHkvG0cGBi+uKe0hrcU1FEZyduezvS5j1cHj1nyz1umQagezreZrBwOHw0OHszKFcTomiEN9PJuHWi7RaJVqtIkopgkBEoCiCBw/keV5mf1/caL0e/PzncO+elKttbcHdu1fniilNe1455aNH8t2rzDGLxWKxWCyWbwtWPLJYLBbLFV5VlPk6GFfMi1w9aSqi0J078t6EYRv29r5eJpHh6VPJJjIL9uVlcQW1WrlDJEnE4WLatb+I42PJNFpdlX3ee8+4RTLOzgKePg3o9wNarYReD1qtAjdvqksuquef5OlTh6Mjh05nvsPZ6mqK1nB66lEqSYA2qIkbRm5Kv+/Q6ci9PD520Tq9cvyTE4dhXxN+/AXvdP9f6l99xj88e0jZTyXgG4gjSBbqDO68w9mNd9htvUP29hukxbw2r9nUqAzoiBD3+LE//a7TYSoI9fsOy8sJpRK0WhlJIkJPq5XSbOppUDiI6DUcKsZjxWgk4djSBS/PQer31eTH5csv5aFqDa2Wpt/XXFwkuK4Ib0nSIIpKRFGRXk9RrcJXX83fjyQREfA6QSdJZM5Vq+IcOj4W4XF9XULR83sqcyJN8w5o1/GyuWWxWCwWi8XybcSKRxaLxWKZYzQSkeabcEaYvBhDmkopkHEamZyjZlNe56KCcHgo313n6uj3ZezXYY5vRLEkEXGjXhexCkRQqlReTTjTWtwo3S6cnmbs7IQMBgOGwyEHBy5KKT780KHd9iaCx6srBmEIe3vuNLvIdDE7OHDo9SQE+skTl7U1SFM1zc0xwsr5ubh75JoyVlez6Zj3d6H56Dcs/u1fc+PLf4N7foZfkGv2Sopo6y6du+8wuPMWu613aX+4DkpxfOxwfOyw1shoVOYdUmkqzqTh0KFcztjcFLFKMookxygIFEtLmnZbMo/29118X1MqSfnZc+4ynieOrjSFzc10Ws51ceEAmmZTT56lJo4jQBOGBZaXq7TbZYrFAqWS3KMsk7lznfDoOHKemzfnP+/3ZZ50u+ImCgL5XHKT8rljjrG+LnPoRWVnlYp1HVksFovFYvnuYcUji8Viscwh5VKwsfHHO2avl5eNzbo1RiNxbBhRKU3zBfvZmXw/u0AfDPLSssscHUn+zHUL91pNRKpHj+bL16pVOebhoRx3NBIn0nU5SwatNb1eSrUak2VjWq0+YRhTKrk4jk+n46O1Q5om15ZBvYwwlGtYX89wXaZdwZIENjZShkMZ9xtvJNPtZ3FdxcpKShhCp+Oyv5PQevApi7/+Kz785G+pxD3SiZbVqa3Q+fHPOX3rZxR+/DpuvYLWcq7uocvFIzl+v++gtdyb9JKR6fxcSseGQykvazQkg+nszCUMRSip1zMGAygUpCtarwe+rybZUM6cG0fei8JTLutpt7fRSHF05E7Cqx2USiiVEsZjKWlrtxcol0tkWYFqVbG6KoKR7+diTbMpQlCzefW+v/8+vP76/Gf378ONG7kTzrCxIZlZ8xlM4kK73D3NYrFYLBaL5fuAFY8sFovFAshCu9vlSsvzPwbn5yJ4uO5V8aFQyIOrpWRJ3msteUetmTgdpWThf13YsAnQft7i/cEDEZAWF3PnUqWSl8rduCHCVqMhYhNAlmXEcUyapgRBQBAERFHE+rqUXBUKzqSVuyhcv/mNx+mpw/JyRpqqqVPFXFun49Dvq6kTapYkyUuetJaxZpkiSUShkPwid9p9rNFwJ9lN7jTvCOT9+HhE44tPWP3837D55G9xI2n/laXQX9/g6N1/xNN7/4j77ltsbolA4xY1aSSunuFQcXLi4nnQaKQsLuppcHerddl5pPB9cQatrKTcupURx+IuevDAZXExo1Awz05UompVU6lIhtP5ucPaWq4ePX7ssLU179RSikm5XkK5HAKKlRVFtVonCCokiQhGUSTCW6Ui+4zHTLqyyXHCUO7xdXPEdUXInOXiQubVbO6W3GPpvHbZxWQdRRaLxWKxWL6vWPHIYrFYLIAstDsdEU6uc2b8oTSb4hj69NP5RXe1KuVAaSq/jfOnVhORZ2Hh658rjsW5NEunIwJNkuRupjgWQSHLII5TKpWYej1E6zFBEBDHMUoptNaUSi7Vqovn+dN8octoLe6ge/eyma5pwngs5VtJAo3GVfXo4MCZlJ9pPE/T6TjEsZq6coJAs7vr0WplNJspjqNJEmlPv9BMaRw+YuXhL/jwN7/ixtnv0GmG1iJo9Nbvcfj2zzn50c9x7m0SRortbY9WPePmzZSFBXH2nJ3JOOMYisWMel2ztJQxHDqEoWIwgCiav/Y4VtRqmps3RRV8+tQhSRQXFw7jseLGjXQqAJ6diXimlObkxMVx9ESsyt1Hg4GaBplnWUaSJKRpSpZBr1dmeXmRtbUSS0s+BweSI7WyIuNeWJCxFwqSOeR58rxbLRGRTk9FmGxdzfee8uxZXrroOJJrdZksE0GqXn/+cSwWi8VisVi+T1jxyGKxWCxTCgXJ/vlD2d1lznUDshA3i/L337+6z/m5CDmVSt4F7UXlYy8iDOWnUMiPNRjk3dqqVUiSZCIOBVSrQ7JsjOcpdncd4tjHdQs4ztXU425XEQQS2ByG80LKaKQmmT8areHoyGEwUNMx7e66ZJliff1qiHW3q1hYyIhjcf0A1GryHpiUeykaDQgCh+P7XVpffcw/+OKXvH7+S/z+xWQ7hV9y6N7+EY/X/wHnH/6ccftGfqKBBE5XKrC1lTEaQa8nAd1nZ5JTFIaKlZWMZlNEMCn1yrugnZw47O66jMdqGoT+93/vTTKsHHxfnncYiqhjnD7drriUKhVNv69wXXnd6ylarQytNVmWsL8vdYmO41IuVyiVSpRKBZaWfJaW5PktLsr8MJ3NnjwRUej0VIQj4y4rlURUCkOZk1tbL547Z2ewuSnjN3lSsxiHmMVisVgsFssPCSseWSwWyw+QKJKMoFlM+dYfg+FQBANzvCyDhw9FwOl2RVC4TBAwKZOaP85weHVbra/mHh0e5kLFeCz5RcWiXFetpvH9hEolQuuANO2TpglKaapVB9/38bwqIKVljYaedMu66hAaDBTNprSbb7czCoX5bZpNEZF+9zuPnR13Up4l4x2NxFElZWnztXedjuQKRZEIMvW6uI9OTkQ80nHKyv7fs/HZx9zY+QX13a9wlHQgKxY1ydIyg/d/wtmbP2XpP36fMTVGjzzefyOmXJ6vRby4UGSZYnExY3/fQSmN60ontI2NjDBUbGykU/GuUoFbt1JcF46PHUCRJCmbmymlEpRKco1JAr/7nUexmGcxbW6m03kQhopGQxxNe3sS/l0qpeztQbUa4TgOaVpG6zqFQmHq8soymR9BICKj50nXs05HxKNiUb5bWJD51W7nwqPWMjeeJ/gMh/PfaS3Hv640EqS0LU3zLn0Wi8VisVgsPwSseGSxWCw/QJJEFsmXXUZ/iHg0HOaCjik/a7VEONrelgV8oSClPkEgQtLson00EpfHi8Oq81Dt8/N5V8jJiQgzZlFfLCbEcchoFFAsjjg5gUolpV530NqlcGn1b+5JHJsubNd3AQsCNQlhVlSrIppIxzE1vQ/DoZReVSoZGxsp5bJc38GBy+pqSrGoybL5/KBCwaXdTskyceQsthKO/nqXpe1PWHz4Cc3t35INA7IMPBci5dO59x5H937K/u2fcly9jUbhOND/v6TkbTSChw+dK0KH1lI6NxyqSXe2bCLcafb2FIWC3FsjoCg1X2pYqWhu3JDto0icWEEAWktGU7udsbysJ+fNM558X5MkCRcXKcOh3L+tLZ9Wq86bbxYoFAocH8s1zOYSRdF8GeJgIM/p5k2ZY2ZsxaK8X129vqvadfN7fz/PuAIRL58nHBlmxSmLxWKxWCyWHwJWPLJYLJYfEGmaCzCOc33L+1flsvtndzcPKi6X5XWjIedqNGTBXS6L8OM4EkZcqeQL9VJJtqtWn39O4y46PZXXs9k1FxcZ+/sxcRwRRRHxZHD1OjSbZZQS0UNrzeHh9cLQyYlk+0RRymDgXHE3xTE8ferh+xn1OkSRxvcVnY7s57qabtfh5ERcNUaI0FqyiQYDhdaKOBaxqtfLx3FyDOrZEatPf83a049Z3P6MG2c9EXEmIllnYYv+mx9w/uZPedT6kIWNEmGopNzM09OcpcEA1tdTSiXNykp2bZDzxYVDpyOd2VZWxEHk+/J5s5lO50kcw/m5w+6uR5ZBkojoMxhIuVurJd3UJrOC1VVxMLXbmkplNrMoQylFsVikWm2wtlam2SzQbjvs7EgZmhm7mTuG83P53GQalUoy/157bT53KE1zx9N1oeRRdDUQvt8XEXVWbOp2r50e02NYLBaLxWKx/NCw4pHFYrH8QBiPJQzYCAmzbovfh4sL+THHOz6G9XURIIrF3JlxeSFeKklnszCUbBnva/xNFIayr9ZSKnXnTkQYhgwGA2q1cJInlNFoeHiTA8v4Xm3F7/uahQURYZ4+hcXFDNfNVYhnzxyOjx0cR9No5OVYUvokHcTSVAKv3347ZWFBRJVez6FU0pTLMm7XgRZHrOw+orr/mOrBY6o796kPDudEjM7CMmfv/Jj4gw/ov/UhF94yN26khIcumw7cuJEwGikaDYdqVbO8LOc7PXXY3EyvddBkGTx44DEYQKul2dxMp88wy0zJnzt1Gw2HsLvrEcfMOIikm1qawtpaRqWiZ46fUC5LB7dCAXy/TLlcolgs4nk+zmRQRlT87DPZzwh1JkNpNjPr4ECcW3JtMmdaLRGTZh1AvV4uPr2IvT2mAd1RJOd6Tgb6FaRM79W2tVgsFovFYvm+YMUji8Vi+YGgtTh/bt6UBXMYiuvi96Xfl0V+uy3vez15PVsadHEBv/mNuEP6fXEVeZ4s1E3J2miUu0UuMytYyDlTDg8DvvwywveHKJWglMJ1Her1Elo7VKvzOURm//FYPfc8+fmks5rWst9wqBiNFKORCB4PHzpcXDi8/XbCrVt6xrmlWVhIWVnRHB46nJ8rVlczdnZcgm5EZe8J9waPWDp/SOHJNq3Tx3jjwaWza+Janf4bH9B76yO6b37E43gLv6C5cUOUjqbSpKkEdUvpmyJNJb8oyyDLRAER189VQaTfV3Q6igcPPNrtlEYjRalcSAEmXc3EXVQua7RWFAqaxcWMxcVsKvaVSppGI+HHPx5SLstzUEpRLpcZj2uEYYFKpTAVi55HEMicNJv5vghYs7lYo5F0N2s0RDC6rgOaoVR68fcggqYJznacP17Wl8VisVgsFsv3lW9UPFJK/UfA/wC4wP+stf6nl75vAv87sDkZy3+vtf5fv8kxWSwWi0XcG0ny9Vw/lzHdy0yeznAoAtHsQjxJJKum2RSxqFiU8qRaTQQlz5PgbqWuLuC3t+H+fQ3ERFHEeBwQRTH9vmI49HjzzSLD4XzwjCmlu06vEMfQi69ZKeh0FMOhM3HeaJJEytmKRc3hoUuzKW6kR4/cqThzfu4wGMDFhebsVNE4ekzhX/0NP/ns71g6vY9DNhXNoggKPmTLdeI7d4m37hDfvkN89x7x1h1wHCpABcj2UqIod3cliXRs831YWdGsrmaTUjgJBV9dzZ53aYCEch8dwd6e3IujI5e9vfz4FxeKblcEsxs3MkolGa8c34RaS1e0W7cUW1sO9+7VqFQq+L6P70vA9f6+PL+XiXXmeaXpfP7V5XJBuccy54pFEX/Oz69uE8dyLdeFrF/GZhZZLBaLxWKxvDrfmHiklHKB/wn494FnwC+VUv9Ca/35zGb/NfC51vo/UUotA18ppf4PrbVNFLBYLJZvkDR9tfKeFxHH4g4xQo3Jk5l1CplQ7loNVlbEPXJd/k6zKa6kkxPodjOiKOLLLwNOTiJu3Agpl6HR8HEcl/Nzl6WllB/9KCHLFEdHMoAsg709l8HgmhMAZ2cO9bq+0h3tMv2+O+m4lXFx4U5asyvW1lLSFJRS7O56JAlUq5OMoYuEle3PWN7+a9763d9RHRyBll5tcdFhtHyb4fod+uv36KzcY3zrDklz6VLQDvCbq+NptURVabczxmMpgWu3U5IE9vdNRpNitjPc/r5Dms7bjrIMPv7YZ2/PmTjGRARqNrOpkPLllx7r65rRSHH3boJSkldUqWS02xnlcplKpU4QFLi4KFAquYThVZHo/FxEweXlF2dYgTz7lzl/PE/mVqXCpOObiJKzuUgG15UubC/iuv0sFovFYrFYLM/nm3Qe/TnwUGv9GEAp9X8C/ykwKx5poK6UUkANOAeSb3BMFovF8oOg3xd3EYjIE4ZSHtTpSCnZ2ZkIP3fvfv1jmxDl4VCyaKJINBDHEWfM+XmeTwMiWkh+kJS2XSaOodNJGI0Cnj4dAwHFYkavV6RWc9jamm0VpllaSlhbyyiX5Xi1mmT9GCeV614fauz7mmZTo5RmPL4acKO17FcsyrbjseQUZZmiXM7Y3BT30HvvJbgu+OM+qw/+Dv7qF/A3v6KYjNDAaKQYVxY5fvMvGP74Lyj9Ox+gi3lITjmD/rEzzSe6PIYwlLF1OooogqMjh91dn0IBkkRzcSHi2fy1SeczE5h9fOzQamVzDp40FVGpUtHcu5fgeYpiUYQ914UkyXDdmKWlkEpFc+dOSrVaoVqtUywWGQwK9PvSae78XESh1VWm7iRDFEl5ZLMp5Wh37lx9FrNjepUA6kZD7s3KirwfDkVI2th4+b4Wi8VisVgslj+cb1I82gB2Z94/A352aZv/EfgXwD5QB/4zrfWLPfcWi8VieSlxLIvreh1+9zsRjxxHFuHFYr4I/33Eo7MzEW3qdREJ3n57vhRsb0+EBZMHdHYm4pHn5aVCWmviOKLfH9PrDTk9TSdCjU+5XCBJFK2WdP1aX0+vjGG25MgEOycJ0/yera30Snlauayp1zWPH7uMRuqKA2k8lq5pWst247HGcaTd/PJyRql/wsZX96n+f5/T2P6cxtMvcJWIVmmiSF+7Te/Dv+Dj2s+p/uQe6xtQd425KL8Gk0+0uXn1usZjxfGxQ6GgGQwcFsGcfVYAACAASURBVBakm1uWJbTb2aRbnOLevWTiiLr+GR0duaytpTx75hLHImglCRweOhQKIhaVShlJogmCgLMzF8+DtbUK779fZXW1SLns0+8rDg/lmJ2O3NvFRZlPJpvo4EDKyMz9NmVwJt/KoDXs78/nK52diRD0KuWT9XrucMqyP6zk0mKxWCwWi8Xy9fgm/+l1Xd+Sy7UC/yHwKfDvAfeAf62U+iut9dz/TSul/gnwTwA2Nze/gaFaLBbLd5frBIQsy8vDHAfu3ZPuVFrL4r5eZ9IJ6+ufz/MkGLvdhseP5RizC3nTbc1kIcWxCA7tdkapFDAcDhkMBmRZynjs4Tg+1WqZRkPcRI4j3cpcN6XfV9d2wTJuFVMqNx7D06cu1aomCMSxk136rwitFcfHkk9Ur2scRwQVgxGhwCHsxyzsfsXa2eesHH7O8uEXFDvHxLFcq9Yw0i6nWx+xs/kPOXrzL2j/aIUwVOzsuNwZJFS61zuLLi4cPE+EnMuMx4p+X9Fqafp9F89LCUMHpRyazYylJSgUMtpt2N52J/f4ahne2ppmYQEeP3ao1TT1uripOh3Nz34WsrgYkiQJx8cFNjdrrK/XuXPHx/flZl9ciFj04IG42FqtXJBUSkKrl5flObuuuIyWl+XczaY4gnx/fn5pLY60mzfnP1tZkeN9XWzItcVisVgsFsufjm9SPHoG3Jp5fxNxGM3yXwL/VGutgYdKqW3gLeAXsxtprf858M8BfvKTn7w4rMJisVi+x8SxZBUZej3JCbouIHpxkamIUi7LjxE/bt26uv3L6PVEUJgVXC4ucoeJCT0+OoKdnbwF+vFxjOOM8bw+5XKC67r4fhnHcTg9dSiXNbWaplaT1u4XFwrHgUpFnECgrr2+bldxduZwempKqZxJ+Zp8Ll3D8h2lBb2iVALPS+l0HBYWMhylKXWOWd/+nDd3Pqf08EvaJw/RSYKjwHEnJXmFMkfrbxO+8Rb7S+9yuPIuWbUGQLOZkabgeZp6PaPVgmIxV73CUMrQ4hh2djxqNc3e3tVsJiP69XrOVBTTWrOykrK1lU5L6kCEl/X1lIsLB63l3h8cONPMqd1dl2fPXLa2Unxfc3KiOTpKePgwpVisUavV6HaLBIHcXxMm3u3Kc6vVRDzy/VwIHI/l+UL+O8vmM4TOzq4XJrNMXEqzrrE4zh1sFovFYrFYLJZvL9+kePRL4HWl1B1gD/jPgf/i0jZPgX8M/JVSahV4E3j8DY7JYrFYvrOEIXzxhQg2ZrHd7+fOnsscHsqCPYpyQeCyG+frnr9UEqFgZ0c+G49FLPA8KUkymUdBoEnTgCgakWVjlpczFhd9CoXSzBE1S0sZxaJ09YpjNS2xEiFDVJA4ZprlM0sUKZrNDHC4dStlPFbcupUyGsHRkeLpU5fjY0Wlkk3ulYRLr7RGZM8esPbwC14PfsfC7ucU+3nrriSFQlExvrVF8NbbDO+9zeju24Trtwgih42NlI2BQ3OgKBYTSqX5cfm+Ymtr/nPJClJUq5pez2F9PX3us5BwaBOCrWg0JKvJ3B9j7NUajo8Vu7surZaUz3U6DmtrKb2eYn/fodvVbG8nOE5GEBQplyusrBRwXY9OR3KxwlAEHZNHNRzKc2w25bN335Wg8xfhurmoORrJ68vikQlPNyWThkIBi8VisVgsFsu3nG9MPNJaJ0qp/wb4V4AL/C9a698ppf6ryff/DPjvgP9NKfX3yL+G/1ut9ek3NSaLxWL5rpJlIhSlqbiG1tfl8+FQFuWrq9fvF8eSN9Rq5Z/Nvr7McCiCkNl3touWaZPuOCJGLS2J+GDKmbpdaDQSisUxjtNDqZjFRZeFBZfx2CMMJfB5lkJB0+u5hKGeuoukVE2jlDiPej1Nq5VNy/NM1k+v51CvZ0BGFGlaLSl3Ozlx+eQTnyhShKFmyemw+uwzatufs3r0OasXD1BpAip3wSS1Gr3bb3Nx8x126u/h/Oh1vGZlmk8EwIm4nR4+9HBdue/VqrimZhmNFAcHkjV0fOxOQ7DTFJpNEY+KRVhcvF49Mnk+CwspSaKmzixz7f2+QmtxW/3yl4Wp0GSEwrOzjNNTTRAkbGxoVlYqFIsVjo8LhKGi2cyf5+amlIxdLi9bWBBB8vQUXnstF3iuKwe8jO/LHL2urMxxuLYM0WKxWCwWi8Xy7eYbjZvUWv9L4F9e+uyfzbzeB/6Db3IMFovF8l2i15PFu9b5a5CF/vFxLubMlvm8qO241rJgN4LBy+h0xEUSBOIkCsP5PCPPg91d+RkOJYz7xg1NtRpyejpmZ2eE4yg8r0CWlQhDTa+nOTtTuG6ewzQawWgkatHpqZSPme+yDKpVaUsfBKCUIghcwlDyj87PpSTNcUSoyTKFUhmdjozrycOUyhef8ZPuL9g6+BVrnQcApEb0cBWD9duM7r3D6LW36d95l2DlJihFrycOqI2NjFot4+jIZWEhmwoehYLC86Sz2XisqNczGo1cPDo4cKhW1bR0rttV065qlYqIQI1GhlKau3evqjDJpX6jJydqOgdARKjBQHKRQHFw4PDmmyHLywFZlhEEcH5eY2GhxNpakdVVH6UcTk/FNba2lmcOmfcm/HwWpWTuLC3lgiHInPC8FwtApZKITdeVGlosFovFYrFYvpvYXiUWi8XyLUGcKrKQDwIpO6tW5bvhUH7fuycL/suL/etIEnjyZD5j5lUw5282JfdmVpza3pbvtNYMBhHFYszS0gVLSxF37ngMh0U8D46ONFqntNsapSCKHGq1bCp6nZ87uG6C1tBsOqyupldCt7WW3J4gkGDrYlFTqWiSBGq1bHpdSkHhaJ/KZ79i4f7HfPDoU0rZGM/V+AVwyj6D19/j7NZ7HK+9Q/fmW5SWqvMXrQGtyTKF62pGIxgOnUmGkLiiggC6XcloMoHdWaYYDnMl5dkzl5WVlNFIkaYSVF2pZIzHLmEo4o/jiAjV7c47loZDxcmJMycWHRw4uK6e3rcwFCExSVJ8P2Y81mitGY0WKBaLBIHPeOxy924uADmOCDrFojxLI9KtrYljbTiEGzdezRGktbiKrDBksVgsFovF8sPCikcWi8XyLcJxZEEvjhspK0oSCcWGvFztVTAixI0bVx0thtNTKYczHB6KwHB+Lt3U6vVcqMqyDK1DyuURWSZuF9d1uXfPpdEQdeOzz9xpaVOxqHFdU9Ym+UZGBCkW9TT/59athMVFcfckCZOsH9mv21WsrWmKRU2hoDk7c6SzV33E8vYnNH77Kxqff4x3eIBGoTOIFESbWzy5+VMq//gjRm+9RzcokyQKx9H42fNLxqpVRZZJCdz/z96bPll6nvd51/O873v2vU/v07NisIOEuIgSRVGhFjJiaNmWrJKpWHH5k5OUv+RPSSUVp8qxE1mJlSqnkpi2KFuk6UjmThMiTJAABsBMz/T0errPvp/zPk8+3P326R7MgJQJggRxX1VdvZ31ebtAzlW/+3fv7AQsL8esrMRniadsNqbfF5k1mcDh4cXS6+NjkUTey0jeykp8Nk5WLl+URXt7Fw3McGg4OZFkUyJ42m0ZzQuCGaORo9WSDWvGZIA0N2+GlMshjYY852AgI4RhKN1YUSQCcjKRtNr162/uHGo05Hc/jDz6UTqzFEVRFEVRlHcvKo8URVHeQZLeoodxvtPn6Ei+9l62Wp2cSNlwp/PDP1cyxnV+3O1Bjo9FHCTF263WQj70+3Bw4JhOpwyHQ4bD0anMceRyadbXwRiLc57p1NPtGvp9ETPZrCeXk68PD+3pYyaFz5KEKRT86fNJ4gdE0IxGhjD0xLEklnI5R7HoyfRO4M+/xfu3v07t1guY+fTsfUyLRZo3P8DBtQ/zcvlDrL1v6fS1wKAtQiqX84Cn0bBYazHmzTJkMjEMBtBue/b3A0C2ohnjT0uvpXh7dTVmMJCuoWx28SBRFDMYiIiZzaTM+vjYUiz6s/f+KJJRvFLJk07H9HpSJL68PKNUSmNMkfk8zfJyxNGRnNfqqtxvNltIoVpNhNFgIOmxSmVxfR8UR4lwKpd/OHlUrWrqSFEURVEU5b2IyiNFUZR3kCTZ86h/qFerIo+ck8TQbCbJkGSV+nj8wz/XbCaPkU7L5/MFxqORCKWTE3k9jYakmlotSRy1WmP29/uMx32yWcjlLI1GhkxG+omyWUerZTk8DBiPPdmsZ2/PMptJt1E67QlDSdGEoayyF1kkwmU0kpX1u7shGxvzs9fWbCabxAzDgSd153UuNb7C8vbXye+8RmVkSKc9EwvN1Se5s/kL7F39eY5XniCI5L6DgSHVdESRZ29P0kbOGVIpD8jzG+Podi2DgblwLaZTc5oscqfbzQxLS44wFNlVrToGA8flyzGDgT29ZrLpbD6H0cjQ7RqqVRFKrZYljuX7MFw8UbdrGI/le0l0OSaTmOnUk83GzGYBQZDj2rU0ly6lSKeDs21opZJ0DxWLi5HCVErGyRbvQ67/eCyCcDqV6/+gREzSaYWCFlkriqIoiqIoj0blkaIoyjvM8vKj0xvOyT/4pRdH/tEfhiJ0HrVRzfuHjxOlUlJMPRotSrgTTk7kc78viad2G7JZTxyPaDZPaDRm5POWq1cjzKlVyGQ8W1vTs5GqRsNSqTg2Nx3DoRQ7ZzKeft/QaESUSu5sxCvZFjYYWNJpx3QqB5DPuwvjXMd7c1Z3/pLM17/O5XtfJ9s/xuCZx4ZOkOH28geZfOQXOHr8IzTtEvO5SKF+xzKdLpJNJyee0cjSbAbUao583hHH8pzzuWE0EnGUTovoarfl9RsDpZKjUvFUqzG7uwGVij8n3gzFIlhryOc9mYyUYO/vW5wzeO9Jp0XGyPs1PPHElJWVCUHgcM4xGECvl6FcdqRSniAICMOQ4TCF92nq9RTjcYRzhlpNrm27LaOExaIkyZIkWrIZL5O5KIZ6vYuF6yAScX//zX8nmczD/64URVEURVEUJUHlkaIoyjtAr/fo3qGE6RS2t+XrJGWSCI234uCAs1GpB5+z05GPk5OLW9OSYu5eD3K5GBjQbDYZDDzdbpr9/RzZrCOf93ifrIi3nJws+njGY8toJAmXZGQtlZJC61TKkU77s6TU0ZE9fa2WKDJ0u5ZW67RI23WpvPQN1l79Gk+88i2C6YjJ2BBG0M8u8draR7m19kucXH+emU1TqTiYyYiZcxAEIqjKZRmXs1bSQM2mpVKZs7UVXzgba2VULps1lEqeMPTk88FZgqjdNmcpoWzWsb6+2AR3nuHQcHgYkEp5Gg1zOm5mmEwcOztz5nORamFoaDazpFIpwjBkOg2JIsvVqwGlUnAm5/p9uYZLS3LepZIk0W7fljMvlyVBBvLz973v4jU9T7cr4nBt7a3/doAfOE6nKIqiKIqiKCqPFEVR3gGOjiSNUqu9deook5GE0d6eJEtAJM+jOotABNPa2iLtktDtSudRGErxdpKeOTyU15HNThmN+kAH72EySbO9naLRkHGt1VWRQsOhjHKFIcTxRYtirdxmOjWnqSlzutrdX3ifcQytlgimft9S6B3w5GtfY+vOV6lvv4iLpTDbO9gt3+TWE79E+Ksfxj9+g8HQspE2fHgzZjSacHxszh7bGI9zsqGsUnGnP5PeoFQKlpcd9foifiPdP+b0XKW0ezaDMJSxuslE0lFLS1JAlUoZlpbih16zKJK+o0xGEkSVypRMxvHSSxmiKEMQ5KnXI/L58LQDST7abbnWUXTxbyEZQwtDSQjNZiL97t+X62et/B2Mx/IYd+4s5NF8Lrc7/7eUz4uQUhRFURRFUZQfFZVHiqIo7xD1eiJbJC30YOJD0j2SGGk2RQyMx3LbXO7NyaVERrRaUoqcP7d9fjqVHqPBQIREvS6ywntPqzVmaanN/v6IctlSKqW4fTsil/N0OpYokm6ftTWRLv2+bAqrVi9uC0vI5TzWeg4OLOOxjKgtLcVnm9UA8J7hd7a5/LWvs/ryV1npvI73SDG2CRg8/Tyjj3yU1nO/wLd2Nlle9ly6GjOfQ9Q2bG3FrK05Dg4sk4llbU3kztGRJZVy1Gr+bDQuIY4dKytStp3QagX0egv51O/LuFo67TFGSr87HchkRDBFkcguEDHWbNrTx46ZzeZY65jNoFBIEYY1UqkM2WyK9XXpfko6ic6TbNFL5OB5nJNrP5tJush7ue2NG3D3rqSSxmMZSbx06eL1BrltQhj+cD1GxmjfkaIoiqIoivLWqDxSFEX5MdDvL/5BD4tOokTqtFoiDy6WNcv9BgO5/XAo33svYmg4vPgcR0ecpmbk8/nf9/siGZaWZMNWEDh6vQG7u2329uasrRmy2SyViiSHZjNDsyllz/W65/r1mGrV0evZ0/JrqNcfvqe92RSpcngY4L2n34dmM5CepVaHtRe+wJUX/w1PHdwhjmUEa5DNsXv5w5w894u8svSLVC7nqVQ8OBEjS0sxuZyMzNVqMaWSo9eTjp8g8AwGcnDjsWEwMGdF2+dxbrGiHuQc33gjoN22LC9fXHlnraHRsBwdWapVz3S6eLzx2OC9o92eMxw6ikVHEAQUi1larTztdsRwGJxtwku2n1l7saQ8IUkcvVWarFCQFJr0SIlAPDyUv5c4lnNIRhtBfhZF0mukKIqiKIqiKG83Ko8URVF+DBwfi7RIunLOj6uJiIErV7jQpTOZyD/+SyURScmK9V5v0XVznlRKJEOxKN8fHsptYZFqMiZmb2/IK6+0ieOYdjvDcJhlf19ExOpqTK9nabcNo5HhypU5jz0258oVSeHM5556XbapPUpMvP56wHBoKBYdpZKjXIx5uvtN+NwXyHzj68zHc+YzQz9T4talj+N++RcZP/c8LkwRhnANToujRYIUi47RyNJqiTwqFDzb2xGHhwYw5POOwcCwtSVl3d57lpY8qZQ/k3TNpqSgzp/vwYGl3zdMp7C09PAU1XjsqVQc87ljPp8TxyKZut2I4TBHLpchmw0Jw+hszX2pJCKwWJR+qVZLrkWxKO8HZMzsvOxZWZH7PgrnpP8qCEQUtdsiEINA/n6Sa54QBCIKFUVRFEVRFOXHgcojRVGUHxPVqggeEImwt7eQCedJRpWSsTTnRBBkMovRtIdtxMpkFh+w6DbK56HZnHN42CWKWoShp1JJ02xmaDYDgsBTqYgQmkwMQeApFj1RZFla8pTLi0RUOo0kgt6C6dSwvOywu3tc+eq/YelrXyDTPWY8NjgsB9c/wmtP/+dMP/Lz2HSKD34wmb9bzO1973shQeBxzjCdWo6PYT53hKGMlE0m0mmUSKLjY4u18rq6XUsQOI6PgzNZdHRkyec9UbR47Ts7AcbA+rpjdfViimp/3zMcSn9RuTwnigy5XI5cLkcqlaLRiKhUDPX6oltqZwe2tqTIOp+Xz42GiJxq9eIZHRyITEzG2H7QmNhgIMJoc1O+7nQujqkpiqIoiqIoyjuJyiNFUd5TxLH8Q9y/tQ95W57nPPO5pIlWV0Xy7OwsfjebyWuq1RaFyuf7cJJxtgdJkiuJiIhj2N6eMhz22NvrMx4HZLMFOp2AODbs7lpyOekASqdF1OzuBuRynn5fEj2yhcwzncprmU4lEdVsGo6PF+3OzsnHuDVi+if/ntXtP2H53neJIo8P4KiyyTcv/xfcf/9vcGyXKZU8W2FMJuPpdN5sTjodw/q6OxNFuZw//dpwcmIZjSzgGA7lfU4mhk5HeoWScm7vYWNDpNBoBNmsP5N3AMvL/rT82tNuS6rIe48xhm43zfp6lmIxTTodEUURs5lhMJBzvntXSqzPS7z79+V6ymNLL1W3K+NjzebF99doiDx6sNQ8uW5JYuz830Qcc7at7sGkkaIoiqIoiqK8k6g8UhTlPcV4LKLm7f7HuHugDqhUkgRK8nPnRBAk8uDB24fhoiA5m5UUy2gkrzUp135wLfvJibyf0cgzHo/p9bo0GkO2thz1ep5OR3qHZjMRKWEItZojnZZNYfN5MibmKZU8UST9Po2GxHd6PXO68Svg4MDgvaFclhc+/+7rbH3786x950uEk6GkhlIZjn/x4xz/4qe4XXqOV14NuXrVYUeOSkXG31Ipz3C4kEfTKZycWPb25LWK2IJqdSGR2m3D8nJMGEopdq0mUqhcdmd9Rs7BdOpZWpLXt7Mj3UWlkmc+n5+OoFnK5ZjhMOL69YhyuUQqlSKKInZ2AjY2uCCbdnZkBC1JEl29KqOECVeuyPhhq7UYSczlRCQ9KImKRfndwwq0BwPpr3rwbzKbvViCriiKoiiKoig/KVQeKYryniOVkn/0v13MZrI2/cF17kmBckK3K2NI1opgCC5uvb/AaAS3bsl9plO5bbLiPWEwmJPJjIjjLqNRTByHTCYFgkCSRJWKYzIxFIuwsuJIpx3PPRcThpymeeR56nV3ll4qFDzNpiGOYTg0GCNbyFIpKNJl6cv/js1vfp7svTewAcw9NK8+ze3nfpP41z5O7ZJEc2ptuHLFce2adBLlcrC+HnN8bBkOF9vOplODMbC1Nefxx2cUCiLJdncDBgNzlkDKZj2tliUMHTs7hn7fEgSe+XxxJpMJHB5avPccHTlgjPeeMAwpFCpUKhny+YhqNWRt7WKZdbcrz3teHu3vy/msrIjMOy8DQa6hcyKUftS+oSh6e/8mFUVRFEVRFOXtROWRoijKj4j3Ih2uXv3Bt61W3yyZHvWY06kkTzY35WfzufQPdbsT+v0+YTggDD25XIS1GcZjQ7Hoz0ar4tjQ7VqiyLG3F1AqLbaUdbuGKJLbZrP+TB5NJtBqWUYjkTrZjGf4le9x9Tuf57HtP8fMpgQhDMIiL139FC9e+wzxlS2Wlz1V4/iP/zEgijz37wdY6xmPLWtrMb2eiJZWy5JKefJ5mRsMAuh0Asplx3gcMJvJe799O2RzM6ZUkj6mbFZKsWs1x96eZXNzTqnkOTiwTKcG52Lu3JFNaMZAEOTZ2sqztpYhiqKzMbxcTmRPFEnaJ9lQ9+qr0heVJJlg0TW1vi7f5/Nv3pB2ciLprUbjra9nt3ux3Pw8yaY0RVEURVEURflpReWRoijKD4n3Mnr2YF/Sw0qwQXpyZotO6LP7eS/SIvk+uU0ci4xIRtwODqQkuVaDdjtmNhvR77eYz2csLVnW11OYU+vzyiuSFgqCpCfHn24Wk3Gzw0NLNuvY3g7PRIoIG3MmisZjGWU7ObGYVpuf2/1T1r/xpwR7u0QReAd7Vz7A8cd+k7vXPsbYpbhZd8SxyKDZzJwVbO/vw6VLjpMTS7Npz0biOh1JE+VykuqZTAz9vqFalWQRJALLUC4bhsOAdFqST9ms9DS12xZjYiaTOQcHIowKhYhstsSVKxnS6QhrLWtrkibyXkbLkvOZTiUp9t3viixKpRbX9XyRdbksZ5+MqrXb8jjn00m9npz3fP7WyaFaTX7/qI11Ko8URVEURVGUn2ZUHimKovyQzGaSVnlY6XG5LJ9HIxFAAPfuyTauJGlkjGxcm0zkc5Jykd4ikU1HRzImdXQEu7sQx1Nu3Rqyvz+kWo1ZXg7J5VLM5/5sOxuAc4bHH5+xvOxPv4dbtwJAuo6Wlx2PPz4nl3Pcvh2QyYiQCUPZPHZ0ZGk0DJWD1/jov/1/Wf/uvyMbzsBDt17n7gc/yd3nP83y8ytc3YgJ71vu3IFSyTGfG5aWPM2mJZPxhKFnddXzzDMxOzuyJc0YkVmZjPQZRRFsb1uck8Lr0Wgh0aZTyGQ8mYy8F+/lzLz33LnjiGPHaDSjWMySy+VZW0vTbEaUy7C2JufqPWd9T8m1azYXyaFkg1m1Kumi978f3ve+HyxxstmLZeZRlLw2SS4piqIoiqIoys8iKo8URXnPEMcyPvSjEIYiKICzzV8JvZ6kU4ZDSauUy5I2eXBMbTIRmZHIhlZLBFIYyv2yWTg4cGxudtnYOGE4DLl2LYX3Kfb27Nlo1sXX5XEO2m3ZitZuS/G1MY5CwVOpOAYDsFbSSMlWMoDmUczkX32Fm3/yL1jefwk8zIxh58ZHee25z7B75edp90JyQ+i8HvPGGwHHxwHFYky/byiXPdY6ZjMp2O73IQxjBgPPfO7p9eQ9WSudSum0Pz0/i3Oezc2YQsGd2xpnCAJ3+p5iZrMY5xxxbLE2z8ZGhlIpTRAEZ/e5f19Ezs6OdBUl42gJSZor6S6KYxlhq9UWG9Tu3Xvra9/titQ7nzAajeT+yWihoiiKoiiKovwsovJIUZT3DJOJSJpkvfqjeHAT2vmfJx8gouJ8Csk5EQzzuXwsL4s0cQ4ODxdjas6J6Gi35fXcvi0/K5c5XSM/wtoWKytT1tcznJxIUqjXk7TRcGgvyBHnJNV0fGzPPmeznijyTKeG+VxW3r/ySkg2K9vOUilP0Ouw/JXPs/YX/xLbOME5CCp5xp/8JCe/9tcYlDYo9S2m5zl6wXD9+ox6fZEGymalc6jf92xvWw4OAkYjKbKuVj23bsmIWTYrKSfnDPm8I5eTxzg5kTE35zzD4cKwzWYx29vQbMYEgSWXK5HJpImiNGA4OrpYRu69CKPHHpNz7XZhY2MhhRKOj6XYOim3DkMRSecTXG9FGMo1unLl4s8LhTc/l6IoiqIoiqL8LKHySFGU9xRRJImTR9Hvy0jZw0qtp1NJnpyXR1euiLgZDkUQWSvr2Ecjuc2dOyKtjo4W0mI6FWm0syPP12pJKXOvN6Pf79BujykWQ7rdIsfHIlqWlhzjMfT7litXZmcjXf2+kY4iA/fvh9RqDucs4ABDPu/Z2nJ4b2i1LPV6TPtbd9n64v9D5etfws6nGKBX3+I7T/42e8//Brl6lvv/IThNDVnC0DMeS2fR3p5hd1fWxFUqjlbLYowjiqBW89RqcwqFmK0tRxDAt78dUiqJvAoCORfZ4iYF1FeuOJ54Yg7MaTbnzOceY9IMBiWefz5FJrPodUquz4PpHxCps74uIqlYlPLy8+XXV+TX+AAAIABJREFUIEKpWr04dvYg3stzPNhrBSKZej3diqYoiqIoiqK891B5pCiKcg7nRP4ko2nnmUxEPCVb1byXtIsxIhWWl0VgJB045+8XhovEyt6ejK1NJjI2tbHhqFR6tNttsllLoZAhCDx7e4bJRPqBGg3pB/JeEjzei8yYTCS9U606ul3pHIqimFzO02jYsw1rva6heuvbrP35H/PE6y8SRTCLYfBzH2bvV/4mtyofYvteSC3jabcN3nsuX3Y0GiKJSiXHtWsxe3sB/T5sbsq8XrHoWFmJyWTkPWWz0rE0mch43GBguXp1frrlzRPHhpWVGGs9S0sxlcqU4dCRSqU4OalTLqfxPkWxKLItCC5eg05nIei8lx4j5+R8p1PZepbPi0wKH/hfuFzu4X1V55nNRAI+6nal0lvfX1EURVEURVF+FlF5pCjKexrnJGmSkCSGHmQ+h+1tERfJbZKia2NEXIAkkPb2Lm7kmkykRDubFTnxne/ImJNzMJ2OqFROWFkZceVKFu8tr73mmE4N6+uOq1djnONUvsB87qhUHHEM9+8HHBwEtNsiidptESqNhmE4NBwcBFy7MmXl+1/j+b/8Z6w0b+EczDJZDn/pU7zw2N+k9OyGJGr2LakUdDqG4VAk0HzuCQKPtR7v4eWXQ+7fD4hjQ7W6OK9ez5wVUbdahuHQcu9eQD4v29wOD+1pN5TBuTnT6Zj53NDv58hkynifZjKJ2N6GJ5+UM97YkM8PJoCMkdtcvy7n98YbF8cQ02mReD9KOuh8r5WiKIqiKIqiKCqPFEV5jzMYSBfO+VG2fP7Nt0tGzaJI5BDIuNnx8WK9e7EonzMZuHRpcd/JRGRSsSiyI46hXJ5zfNwhDHvkciGdTpFOR353dGQpFDzVqox+jceSLkpG1QYDQ6djaTbBWsflyzGXLjmOjy3lsiOXs4x6MT+3/+e87//+Z6T37mEtxNUKLz33u4w+/Wky9RyHL0aMj0REdTqGUkn6kCoVw5NPzsjnPdOpA6SzaDCQ567X5TkBdnYCKpVFSdR8biiXY1ZW4KmnZmSzkM/PaLVmjMcBly+nuHSpjvdZ+v2QOJaz9V7Kwi9fXiSGEiF3nlrtYjm1MRfTQN2uXEvvL/ZM/bA8qu9KURRFURRFUd7LqDxSFOVdz/HxD/eP/mRt+4Nksw9PmvR6C/nw6qtScJ3Py2gayBja1tZCHk2nUtx8flzK+8WGt9EI4nhGudzn5KSLc5aVlQwnJ5Z02pPJgPcicUolj3MyttbtGjIZf/a4nY5hNIJuN8QYj7Vw9668iLSZs/6VP2P9C/+cYn9f3vfyMsef+V26n/gUnUbuLFXUbFri2BBF8nzLyyKg1tbmPPNMzGAABwdShN3pWMLQcXIiG9LiWObJ9vbshcLpwUAeL5ebY8yIOIZeL81sVqVWy1AqhXS7IsnCUBJdly/LeNr2tiSKHhw3e5C9Pc5G+B7cOpeQJMp+UDn6w4iiv/p9FEVRFEVRFOVnGZVHiqK8q3FOEkBvVYKckErJWNMPw/nuG+ekW+fKFfn+fKrIe5FMjYaMrLXb8lpu35bfTyawuwu53JSTkz6HhwPSaUsYZrl61bG05JhOZT29MRDHMiJ2cCAdR/m89AbFsTvrVnrppYhMRjadXb8+wxiYdUY88dLnuPIX/xepQVtG4tYvcedXPov5zf8Mm5L/3AcBpFKebFasWLUqqaXDw4DhUMbfNjc96bTn9u2QZtMymxmq1ZhiUYqvy2VJQ3kPS0uepSV3ehaefH5GsRhTLFo2NysUiwV6vehso1yS2gKRRMnIYBjKmFry8Si8l3O+fFm+Trqfzv8+wZhFGkxRFEVRFEVRlP90VB4pivKuxxgZeXq7EdEigiMMZVNXJiPjWwkHB/C974nAymQkfdTrLX7f7094+eUxqdSQILBUKhm8lzLp+dxzchIwmxnKZcfKiiR7XnstpNUKKJUc3a68jiiSkbC9PUuvZ1ldnTMaeUrzFhv/7l9w/YXPkZvLE/c3bnDrY7/PvRsfB2vZmswJTgVLHEsv0WRiqNUcN2/G3LgRU616rlyRUbT5XNJNx8eWKPJMp5ZaTRJOhYLnySfnzGaGGzdivPdMp1Pm8znGBKRSZQqFAqnUYkuac5LuymZlxOx8Wmh1VUqwnRNh99prb5088h7u3pXHODzkrGvpPGtrct00QaQoiqIoiqIobw8qjxRFeVdzcvLwn0t65wePs/X7IoMevF2SYDk+llG1tTURHd2uSIskwdRui6S4eVOSSbmcSKZGY0yr1abVGjCZZHjqKUuh4Lh719DvG1ZW5ly5EtPpSMJoPLYMBlI+vbMTsLnp2NyMz7aUtVoW76UPCSDf3ueTf/nPWfvmvyZ0U9lw9tQzHHz6s/Se/RBpC1tjz3DoKBREQElKyjOdGioVx6VLMd7DyYmh3bbk856TE0ujIQXYR0eGy5cdzomMkT4kR6HgOToyHBxMcM6Rz+cpl8tMJhlOTgy9nlyXRLLN5yKEokgeJ0kW7e+LbNvZkTRXEDx6DC3BGLh2DW7cEFlXrT68o0pRFEVRFEVRlLcPlUeKorxr8V4SPxsbb/5dHIu8SPqJHnX/ZnPRSfQgYSgjZ5WKlGUHgYij27cXq9wHA7ldvQ7WetrtMa+/3ubOnfnpbQpMJgGTSUwQeMZjw2OPzVha8kwm0GxKf1EiWFotg/eGZ56ZUq8nm8xkY9nSkmO5+TpPvPjHbN36C3zsGHmD/cTPM/3s79LcepZRx579hz2Vkr6kMJQxtX4fJpPgTN5Uqx7n4PAwIJNxTKeeZtPQaBhkM5psTptMpK8pnfYsLc0JghHNZkS1WmJtrUjqdLVcvy9yaHlZUkRbW5I2AhE9h4fSaWStnOdkIkJufR0ef1zE0KPk0XC4SBkZI9Iujt/6PoqiKIqiKIqivD2oPFIU5V2NMQuRc77vxnuRFG+VSpnNJHGUpHKGwzffptUSQZTPw9GRjKQFgSRlkvGqUsmTyw1ptVpMJhOCICCfz7GxEdNoJCNn0O8bxmPo9y3DoUiru3dDrJWRsPv3ZSTNGM9gYM7ez3Ti8N/8j1x/+Y8pvfwC1npMJqD/y7/Ot576LO/7G2LPbr8YAos+I5ANbUEgRdZHR5bDw4B6PWYygTD0Z2dVqXiyWRFO1aqhUolpt0UiLS87arU5xeKYUslRrVZZWytTrYZMJhdHx2o1+ZhM5PP58280Fp1Gu7vy/rNZSQ/9oJLsdlvud34UrVAQKaUoiqIoiqIoyo8XlUeKorxraTQWXzsHb7xx8fengZg34ZwkaWYz+SgURGBsbUG5LLdJypjLZREUuZx8DAYyynbzJuRyjn6/T7PZZDSaMRqliaI84zEMh5bZzHH/fkgq5eh0JB6Tz3syGc9sBp2OZTLxlMuy7ezkxFKvzxmPI15+OUU6cmze+vc89tX/kyd3b5HJeEY2y73nP03jk7/NqLRCs2kp35VCo/19y6VL8WliKuD+/YBu15BKyQhav28wRsRQImEmE0+7HbC05AhDkVaZjKSVrPXk8zH5/JTZDGq1ZVqtHPfvB2fnH8eLMwM5n9FIvu73JWH0KNbWYHPz0dfpQcplHVFTFEVRFEVRlJ8EKo8URXnX0m6LfIBF0ujGjTffrtmUDp4kIdPrSTFzIA6ElZXF2vdkzGpvT5JIt2+LPMpkFgmnMIxpt7scHbWI45h0Ok0mk6fRCMjlHN7Dyopjc9NxcOAol2MmE3uWCBoOpVNoNjPUanD1akwcQ7NpsdawsuJ4cvZdnv3T/5HMnddwDoYrFSa/81vcev9fJ6wVqRooO4dzsqVtMoFy2VOpOOZzQxR5Njdjnn7aUSx69vYCisWYbtfivaFYlJKngwPD7duGy5fnTKdS5L2xETObzSmXJywvW65dq5LP57EPrEG7c0fG9a5de/j1uXVLrkmyDc1aEW/J9XoUx8cXS8lBJJ+OpymKoiiKoijKTwaVR4qivKvJ5yXhcn5d+4OMx5KQSacl5eKciKDnnhOBdO+eiI04XqyO7/Vk7Oqxxxab3JaWZnQ6HdrtNqMRBEEGawNmM3n+0Qi6Xct8LqJjNJLRs/FYrEet5ohjaLftafrJEIYijXZ2AoLAkx21ef+X/jHXvvunRCHMa3Vu/dJn+Wr906SKafqvyWvP5cS+xLFhODTs74vY+df/Os1kIpvZgsBTLFpSKc9sZlhehpMTS7XqqNXg8NCevZZyGSYTRxzPSKfnFIsZ1tZWqFazhKF56FYzaxey7TxJoms0ktvUagvxk1ynUunhY4KQiLA3P3ZSUq4oiqIoiqIoyjuLyiNFUd7VxLFs7SoU5KPfl26iZnORbmm1ZKuXdPqITJpORWQk0md1lbP+njiW28xm8nWnMwXaTKcdjLEMh3mGQ8vBgQgbYziVRPL8lYojDB2tliGdls6hIJDxtMlExFS16rh3L6Bed0QRlAtznnn5X7DxuT8kNe3jo4jdT/0tdn79s9w9KhAMPamUo1iUxFI6Lcmh+RxefTXg+NgSRY6XXgopFByplIzZWevp9SxRBAcHAfv7ljg2ZLOwu2sJAnjiiQk3bvQxxrCyUmJ1tY61KV54QV7ro+j15PkfLBw/PJSfR9Fi9C8JLcXxQiAZI18/mEJyTu6rskhRFEVRFEVRfjpQeaQoyrsea2Vj1/6+jFIdHIikKBbl94WCCInXX5fEi7UybpVKiehIVsgnHB2J1Gi3Z/T7XaKoTa1mSKVyeG8YDCwbGzGDASwtxWeSYzaD/f2Q1VV39ljDoafVMlgL3/teyGgErZaMkL3+esh8Pqd8+7t8+Ev/A7WT21gLnec+zOHf+a+JNy8xakqBNlj6fUkvWespFBLxZcjlPDdvxqTTMeNxwIc+NGVlxbGy4hgODb2eoVz2vPFGwNWrhmefnVMoeF57zVEozLh0ybC8vEw+nyc4neWbTORMHnvsYqfReUolEXPnS6xByq9rNZFX87l0SSXJo91duTaJTDo6evPjGvODC7QVRVEURVEURXnn0P97rijKTz3eixB6MKFyePjmAuV6XRIrhQJsbCx+vrsrSZlPfOLihq44hsuXL/4siuY41+bu3R7WBnif53vfC5lOYTIxNBqW1VXHYGCoVIIz8TSdwmBgGQ7FlDgno2GDgcE5GRkDKcyOooiTV9t86iv/E4+/8QUA2pV1/vJX/1u+X/8o5vsBsxc947GhWvUUiw5rDfW6o1h0vPhiijD0NJuWRsOSyzkmk5BMRl5jv2/IZg2DgcijRsPSaATk8zHHxzP29x1xnKdQWKJWyzCZGFotzl73yYn0PqXTIokeRrcrvVM3by76o5JrsLws18aYN3cVra5q8bWiKIqiKIqivJtQeaQoyk89zkkvUa22+NlkIqmXkxMRQJ//vKSOkk6jahWWluS206lsBhsMJH2UyJ75HHZ2Fo8ZxzH9fp833uiTzzuGwwL1uvQUBYEnl4NCwbO+HrO15TBGRtQScTIaQbMZsLkZA9DpGIIgPB0dkxG29XVHOT8j+r8/x+9/+5+ynBsQ11Lc+8Tv8fov/R537+fxfYM1njCU7Wy1miSZrJXPg4Hh6MjygQ9MsDZgY2POlSsxd+8G5POeRsMyGAR0Opbx2NBsJjJpTKkUU6mUsDZPpxNhrZxNuy3nk04vziuTkfLqTmdxXg8KvGT73Hl5BDLC97Aequn0r3z5FUVRFEVRFEX5CaPySFGUn2oSWTEYwJNPLsadEtFx/bp8PZ/LeNUTT4hQWl+/uDnt9m1JGJ3fxvbaa/DUU3DpkuPoqM/h4clpyXSOQiEkk/HU644gMJTLDmM81ao/25qWvI5XXgnxHrw3GOPxPmA6hbt3LffuBZRKnt1dSzY157FXv8jjX/s/SB/dx1roPv8LvPE3/hvuTDfpnUgH0dZWfDYKViw61tYWY3DFoqfRCKjVHOvrjnTaUKs56nXHyUnA6qrHGMfSkrzWft9zeAjLy47nnsuztVUkDAOGQ5Fo6+uce2xJDY3Hkjba2pIOp6Qrant7cf4JS0vyGD/sJrRy+WLKS1EURVEURVGUn35UHimK8lOH95KEuXVrIY/6fflIvh+N5Db7+yI7ej2RH0nRciq16OKJItmYdl4cATjnqVb73L17zN27kM+n8D7g+DgCHLmcxzmxIsWio99/syEZjw3eGx57bHZahm05Prbs7wd8//uBFHBPZ1x56Yv82p1/Sr65i/fQKm/yrY//A0Yf+Hl8y9Dve0YjSzotciWd9kwmhk7HAoZu15y9d0kWwbe+lSaKPMOh4c6dgJ0dSxB4UilDtTonikaMxyFRtMTHP56lWhVplGyXy+cX55nJiCRaXpbzdE6+nk7lXPN5Oe/Ll7WPSFEURVEURVHea+g/ARRF+aljPIYXXpCxtFJpsfr9298WqdHricgYjUR+dLsiNDY3pdsoDKUPKZEc3l8sxG42od8fsb/fwtoBg0GWZjMNSMKnUHA88cScXO7ijNZ5eTSZyOP2+4aTE8vqakCrZWi1DP2+ZX/fMJ/EfKTxBX7+S/87xc4umYynWd3g4DP/JcFnPsFTaUuxOKXbNbRalsNDRyYD1aonijzTqaFQ8GxuxuzuBlSr8vq2twOaTcN8DsvL0osk/UueUmlOEIxxztNoLNFsFslmA6pVOYNWS1JCKyvyPgaDxfuLYzmb8VjOdzKRkTXv5WvnUBRFURRFURTlPYjKI0VRfurwXtJDzzwjiZhaTdJDrZaMPfV6IjLmc/ncaokMeXDr13nCUG7X6Uz5zne6RFGPdDqi1yuyvy8l10tLiYSK3ySOhkN44YWIVMozGhnabUn5jMeGKIJczvLiiyHdroHY8fgbX+R37vwhq/NdrIXg8TV6v/dZvr/6SS5dMZRKnk4HZjNDOi1b1EYjizGGzc2YTMbT7xsmE3P2PvN5z717lqMjSxxLMbbIIulDcm5CEHgqlRqFQpHDw4Aogp/7OUlenZzIRz6/2EQHIo1aLRFEsDjXyUTG2DKZRY/Ug91GiqIoiqIoiqL87KPySFGUnwhJyuX4WFJF5xkMJPGSSi3GpkCkxnwu901SRc6JNNrcfOvenTiOeemlDtNpizBM8/jjmdPHlJRPrea4dCl+6Jr4btfw4osBt26FbG3NmUwM3ssGtCgyxLFhd9dyuAcf6/4pH7v1RxTae6RTnvHqJi995O8w+pVPcHicYrYH7Z4nn/dY60mlPL2ePXuv6TQcHQWkUp7BwDAaycfRkcVauHUrpN02bGzEzGYG7x2p1IRi0VOtVlldLeKcGJ5SScTPk08uCqxLJbh6VX6enHuS4CqXF+85lRJhtrSkm9EURVEURVEU5b2OyiNFUX4iTKfSYTQeS7IoSbRIOkiE0MHBooMnjqWTp9eTr3O5Re/RgxvAzuOco9frcXJywiuvRNTreapVQz4vG9EOD6VTKIpk7f2b7y/yqNezVKsijEajgEpFCqnj2BMFjvUXv8Snv/FHrEz3SKU8nY1NGn/79/nu5q8zngVUUh5rYWnJ4b05TRVZvBeJU6s5jo8ty8uOTgc2NhylkiGfh0pFUkj5vKNYdBQK8NRTc77//ZiVlTH1epUgqNDvBxweytkEgUi4dlsKw0ejhTxKpeDoSK5BEMj5drtQKCze92gkMu6t0lyKoiiKoiiKorw3UHmkKMpPjDCUtMvmpnztvQijXE7SRkEAjz0m34OInO98RyRS0stz/z5cuyafz+O9p98f02gcM5/PSaezNBop6vUZxni2t0UUbW9bdnYirJVy7Hx+YaKmU9jft7Tbll7PUig4Wq2IXM6zthYTzz3pr36FZ778h1Sb2zgP/Y1LdP7WZ7l17de4fA24GxB6KaiuVh3lssM5Q6djSKc9uZz0JjlnmE4tznnu3Ak5PraEIRgjUmtnJ2RtLT7tWpoxnc6I4zKTyRpHRyGDgQihTke2n0WRSKNsViRQcqaVisgj70XM5fMiijIZ2a6mKIqiKIqiKIryICqPFEX5qcF7aDREaqysSCLJWrhzR1JKvR7cvStb07pdkSLZrMij8+vfJ5MJJycnvPHGlFwuRRim6feTsTd7YUxuOpXUUbXqMMZTLMq4mPdw507IcChCKZebkcsZUilHOuXxX/k2z37jn1Defw3v4Si/ztee/a94/YlPUo0t5g3PK6/JyJkxsL4uPUa9XsBwaJjNDNmsJ593LC87RiORSMvLjuHQcHBgiSJzuknOkko5CoUxmYzH+zz1eg1jIg4PZeNcHItcKxalmygRc2trkjZK6HTkI+k3UhRFURRFURRF+UGoPFIU5aeK8Vjk0dqaJI+Gw4UIKRYlNfPss7JVbX1d0jWVikim6XRKs9mk1+sRhiHVao6rV2OMmXP7dsDTT8fcuDEnmxXZ0m5bOh0RM7Wao1Bw5HKy5SwIPHFsuH59zvKyp9021Gqe2vaLXPrc/0bm1e8RBJ7OyhJ3f/33CX77kzwXpXg6np2N0R0dBVSrMXt7IdmsZzqV5+x2LZWKI5dzBIGn14Pd3YA4lsRQEDjSaUu97pnNoFqdsLw85erVLOVymUIhxdaWnNV3viPPVSyKUCsWpTcJ5Fw2Ni6KNVgUYne7IuXi+J27voqiKIqiKIqivPtQeaQoyjuG9/DGGyIuGg0py87lRIIkJdWyOWxRjj2dwr178jPvZczq8FDERz4vn4+P53S7bTqdDkEQkErlmc8vtmcbw9mqe4BOx3D7dkCnAzs7Afv7lkzGn4kW2ahmWF+P6XQM/qVXuf4f/jHLb7yAczBMlzj41O9x8Mu/RWUtxZVrMd47Dg8tzsko2GQiG9HC0FMoOAYDQ7XqSKUk6TQaWfp9aLelA6lclg1scSwb2HK5KfX6kJWVPNevr5LLpd90pu02XLokws2YxWdYjKk9WHg9GMh5Z7OLn6Xf/NCKoiiKoiiKoiiAyiNFUd5hvIfHHxcxVChIosgYWSHf7crnr39dJAgs1sg/84yIpJUVGdPK5cC5mEajx2TSIggM6XQOY2S1/dGRBTwHB28uwQaRO4eHlmw2Pk07eUqlmDCUUbZeT8qrU3v3uflv/xGbb3wFa2CczXH7l3+X27/w2wSlHJWcbE0bjQzb25bDw+B0PE3EUDotj7ezEzIYGEoljzHgvSGKoFj07O0FZ5Kp3Q4Yjx3V6oiVFcsHP7hB9tTyzOfy2sdjOYvxWETapUsi2OZzOb/zZ10sLu6XkCScKpW3+eIqiqIoiqIoivIzicojRVHeMYbDi9+XSiKBklTR1pb09WQycPOmSI44hm98QxJJR0dyv1bLMR732d1tEwSeS5cigkBkEXi8lw1ppZKn25Ukz2AAo1FAr2cIAvj+9yOOjgw3bzqCQLag5XKeft/K91GPD33zf2Xlz/8VoYlx5TR3f+FvEPy936G2VKBzJ8Raz9ZWjLXw1a9G7OwEFIuepSWHMfKaUylPt2vodkUW1evyPMWiJ5v1spmtY3j6acczz8zp9cbs7UVUq1WgwP6+wbmL57a/L8ItjuVMjo5Ehq2uXtyOZoykux5Gsfg2XVRFURRFURRFUX7mUXmkKMo7gvfwrW8t+neSNIz3MkIVhjJONZtJomZvT4qyg0CSR5ubskFtPO4DLfL5CWtrWayVMbHzgiXpHJpOodMJiCLH7q7InpOTEOc8x8dShC1pIOkemk4NzSPHE9/7l9z80h8SjXrMjeXwY5/m9m/8XZpmiZs2hhYcH1uKRU+nY+l2Dd//fkg26yiV4lOB40mlDIUCDAaeIIh58klHve6IY2g0DK2WJJzGY0sUjRkOx5RKFYKgSqUSEoYif5IzO19yXS6LdHv6aXjqKTm3Wk3SXIqiKIqiKIqiKG8nKo8URXnHaLUkUeScCJ6dHSm9XlsT0dPvJ4XRkkgqlWSz2u3bcHAw4fCwhXMjisU0w2GakxPzyOcKAs9wKL+PYwN4CgVJJoWhZzazbGzEGOPJ5axsVXvxP/Crf/Y/szK4Cx46z7yfoz/4+0wu32C0Z7m0FLO5GdPrGQoFS6HgmM1EhA2Hhhs3HDduOCYTQ6NhcM4wGBiiyHDpUszWljRTt9uGRiM4vW9MsThibS1kNrvMYJBmPheRVirJOV29KnLoxRfl+35fvs9koF6Xcb9sVsrEFUVRFEVRFEVR3m5UHimK8o6wvS1jVqur0mc0GkmqZmtLft9oiBRZWZHb5XJS9JzPe7zv8+qrHQqFgGIxRxRJOqndtqTT/hHPKKNiznm63YB+32CtI532GGOo12PW1x17e5bswT2e+cI/ZPnWtwhCT3h1nbt/8++zf/OjVGuelaLDOdjcjGk0LK2W5fjYcvt2yGwG+bw7Tf7EWCsb0rJZWFmZsb4ukajzpdXTKYSho1AYUa8brl1bIpPJs7dnuHpVxtCS0bSk/Np7SR49+SQsLUnKKOks2t2VJJLKI0VRFEVRFEVRfhyoPFIU5a9EHIus8I9yNg/gnEiPr35V+oy2t+HWLbl/ECzGzRoNuZ2IFRnJcs7RaBxzfDxgPC7w7LMxKyuS3hmNpGA6kTPn6fcl8TOZBGSznvncE0WedNqfblw77RHqdHn/n/0RtS/9K/zcMUnn2P71P2Dy1/8aY5di0DFEKc906uh0DGFoGQwM7bZsOQsCx9ZWzNaWZzCwVCoea+H+fSnpns0sjYZlMlkkpJyD4+OYKIp5/PEqmUyRTsfSbEqCKPnY2ZEzshZefVXO/fgYOp2LUqnTkXMzjw5hKYqiKIqiKIqi/EioPFIU5a/EfC4iY2Pjh7v9yYmkjMJQ+nmKRUkYra3Jz4JAbjeZyNfTqTx2qzXly19uUatN6PfztNshg4Gj2RQx45whlfIPXTHfbhtyOfk6lXLEsUicTEZub2cTtr7xOTb/zR8TDHoM5gEvPfZb3P3NPyBcrrIycpycWA4OLP1+zM5OCmMkBeUcNJsB3a7HexFDvZ4nCDxRlIirgLW1mEIBmk0p4I4ix2y9RZGYAAAgAElEQVQ2YzZzZLNlrlzJUSyGTCYygpbQbIqY6nYlSZS8vyCQ1FahIKmm5P31+zLedrqQTVEURVEURVEU5W1H5ZGiKD+Q+XyRNJrPJeXyMGmzv78owt7elpRNsjp+ZQWuXJHfz+cikbpdGT+bzWSjGogI6fcH3LrV5sUXMzz+eHgmbmo1SQ2NxxKziSJoNOybXsfJiXQY7ewEGAOdjmUwsBSzUza/8XlufOmPCFsnzGZweOUDfPF9/4D42lWuX58zm0lCKYo8y8uerS3H4WFApeIolTy5nGd3V8bGcrmY979/Tiol76FeF+m0uRnz5JMxtZrj8NBg7Zhcbk65XCaXq3JyErG2JhIuIY6lIHw2k4+1Nbh2bSGJQM48kUewuCaZjCSUFEVRFEVRFEVRfhyoPFIU5S2ZzUQEhef+a5Fs/wIRQb2efL23J+mYZITq8mW5fy4nsmV/X34+GMDrr8PduyJDDg5kTOuDH/REUZs4brK0lOd974Nf/dUJBwcST1pZ8eztGbJZkTsnJ5Z+fzGvlfQgARhjyGYdtZrj/j14fu+L/NKf/RNy7QPC0NO78Riv/8bfY/D+D1PZDdjYmJHNwsGB4fg4AAylkieODem0Z3PTcfmy49VXQ+JYOpMKBc/ly7I97d69gFbL0uvJ7WUz3JjRCFZWCmxsVGg0UgwGInr29iRNZK2kh5pNOYPNTUlflctydsPh4qwPDiSVdP78Qc5WURRFURRFURTlx4XKI0VR3hLvJeFz9erFnyfja+229O7kcvKzKBJ5lEqJcFpaklXyifC4f1/G2KyV26ytSUIpk5mzsdHg9u0ZYVik1wsoFh3ey++vXo3PXk82Kwmg11+XwuxMxp+KFsNoJL/v96FUjMl988v8xh/9EbX2NjaA/uolWn/777L/1C/T6VkmJ5ZuV7an3b5tz3qG1tdjJhMp3U6lZFObtZ7dXUs+7/DesLTkMEZeUxjC5qYjmzU0GnMGgwn1ep7NzRrVapogkNttboo0unNncb/BQM6xXJbtaSDpokTKnefSJemOUhRFURRFURRFeadQeaQoygW8FxnkvXy0WpKMabUu3u72bREfvZ4kZJaWRCBFkfw+CEQYLS1JeqbdlhG2l1+W200mMra2vw+t1oQ4PmQ6dVibZ3VVRJG1nKWLej1JGG1vB0QRZDKeu3ctjz0Wc3yc3Mayu2upLznW73+bD3/jf6G89ypxDMPKCi9//O8S/tYnqCxZMmPoDSStFIaQzTqsNVgLcSzPNZ3Ke3EOOh1DrxfQahkqFU8QSLfSt74V4r1Iq35/Trs9w/scly6tMBql2dmRxFAmI2eVjJqNRiLZtrZEugWBjPU9KIbGYzkrEFmXnK+iKIqiKIqiKMo7hcojRVEuMJvJVq9yWeTJ8bGkYZIuo4T5XH4exyJGlpfl53EsgiTp86lURBpVKnDvnjzmlSvyfSoFqVSPavWIajVkOs2cPYa10lUURdL1k2wsm0wMKysxUQSXLzs2N2P29wNKJUcUxVwf3eIDX/5HFF99kXlsGBSrvPCBP+DL9c9Q3wi52p/TH4kgOjoS6eQ97O0F3LsXkk576nVPpxPQ6yVjeQZjJJU0m8lrm0wsS0vyJp2bY+2EdDpia2uV2SxDFIn0GY3kfIJAUlaVipzLcChna4zcLp2W83iQZlPklQizh3dNKYqiKIqiKIqi/DhReaQoypsIApFB06nIkgdH1kCSRMXiYgtYFMHR0UIa1WoLoXRyAvm8CJPnn5eta957vvGNJrdu9SgUChweGhoNi3PQbodn42/1ugMWiZ0kEXV0ZAlDePnlkEYjYC3X5pn/75+w9Bd/QiryzIoFXv/o7/Hy+/46Q58jfxTy9NMz6nV5oE7H0+tBEBjiGKpVx3wes7zsePzxmGLRc+eOPZM7xaLInZUVw40bjm7XcfPmnNFohLWWer1OsVik0TC0WpKuKhREPmUy8v5BZBIsJFoUSfIpnX70xrRKRR5LURRFURRFURTlJ4HKI0VRcE4KnBMxY8wPvk9CFC1GqdptSdeASJK7d+Xr27dhd1e6fZaXIY5jDg8POTycEQS505EzGVErFDzNpiEIZMPa0ZF0Eo1GlunU0G4byuWYft9I19EUnr73Bd73xX9I2G0zMQF3PvY7ND7zezTGZdzc44aGGzdinn12zmBgGA4NzWZIv29JpRyTiTlLNhUKnmzW024b2m3LbJaMpHmKRY+15nSsbcJwOKFarVKtVhmPA/b2Fmmiel1kUDotH7ncxfLrcllG+rpdEUOJXEpoteS8JhO5raIoiqIoiqIoyk8KlUeKohDHkoRZX5fvg+A//bFKJfncbIociSIRU/W6SJRSacrOzh5xHJPNFhmNRKrEsaVa9VSr7rQUG0olRyolRdj1esx0CqWSIZWCycQzv73Hh77437N69wUccHTlWb7yK/8dxfdvMZsawtDjPQSBJ5uF3d2ARsMyHsMLL4SMx+BcQBhCGM4JQxE/x8f2dBQuptezlEqOUslTLnuGQ0ejMcXaPPfurbG/L7NmnY6kjNJpSV21WtBoiEy6ckU2qf3/7N15tGXnWd/577v3med7zp3nmlSDJEue8QAYjA0J8xBIB2fobkIcuglDoKHDZGinAzFNmiE0IZCw6GYwJJjR2GkGY2zjScgIqaQqqYY7j2eez9n7ffPHU6dOlVQqlcFXLknPZ62z7j1773Puu7eWtJZ+63medzC4ue1sf1+Cu1sNwO52JXAqlZ65u5pSSimllFJKPZ80PFJKARKaJJMSZoxmFll7+884J4FJEMjvg4FUyoShhB9BIPOBQL57c7PLBz5wQK8X5erVHHt7HqWSJQikdevBB4dMTlqCwBCNOoJAdjsbhTKeJ2GU6w+598O/wYkP/RpRN4DJLJe+/Js5eM1bOJUzlEoBV6/6+D7s7Eh7G0ib2uGhoV6XCqcHHhgwGHgsLATk8xIa5fOye1siYZiasgwGHqWSI5MJSSQ6eF6M6elZMpkkQTAOfspl+ZnNyr2EoVQOhaEEQLu7Es7NzDzzOY4qt26cFWWttMk9WyubUkoppZRSSj1fNDxSSl0XBNJidmPl0e2qXvb34amnpELm8BCuXpWwo9eToCeTkaqibtcxO9tiba3N6mocayOsr/uUSiH5vCUahVTKcfastKOVy9JGdnDgkUg4SiXLxIRlMDAkHnmYpV/5abzNbTCw8eAXs/sN/5RBKk80CpOTIRsbMvw6kXD0++B5jmbTo9NxtFqGWMySz3vs7UXpdg29nk8QSNiTTMpObsaMP3t4OKDXsywtTZHN5vA873p7X+Taf0UjEbnvrS0Jg3Z35XmmUlJ5Za189+12S9vdlTWMAreI/hdaKaWUUkopdRfQ/zVRSl3nnIQbx47d/rpmc3x9MgkPPCDh0T33SGVNJiOhiYQhlieeqGFtnUIhyeysw9ohw6HjxAkJhcJQdlYLAqjXDb7vCAJIJi2djmF7O8LjH67x4J/+P0w98Ud0nKFeXOGvv+zbeCz2ClYbAe0dw+amz8SEpVaToMj3DcZAPm/pdiWRicXk/cyMtKQdOxYyPx/ieRLaZLOOdNpRqXjUagGNRoAxOZLJHBsbESqVUcAkFUWDgTyLapVrbXCwsCDPcWpqXDk0M/PMuUa3ev6zszocWymllFJKKXV30fBIKUWr9cxj3e54Z7Cnu3RJhjj3+xIQbWzIfJ9SSXZnM0bClO3tgPX1CtvbAadOpen34dIl2VGt15PgJRYbtb4ZLl6MsLdniEblveeBtZbVKx/kvvf8BIlBE1eMcuXNb+Pgi7+O5DBG7qJldTWk2TR4niMalcqiZtMwPR2QSo2qh2TgdT7vKBYtrRbs7PhUKhJalUqWVArAYa2l3e6Sy8U5fnyGSCSJc7Lme+8d7yIn85HkuMxNkvAoEoHpaWlTk++8s+c7CqKUUkoppZRS6m6i4ZFSL3HDoczrKRZvPl6rjefuPJ21Mhh7a0uCkuFQZv9ksxImXbwI5XKfer1KOh1y6lSUBx4I2N/3ePhhgzGGatXn6lVDsyktYNZCvy+7qZVKlkzGkot3yf3Cf+T4w7+PH4H6y17B5j/8Vi73l8gMLb0eTExYCgVLt2vY3Y0QhobpaUs+bygWHYeHHs2mz2BgiMWCa9VNHltbPrmcY3IyZHlZdlxrNmEwGNDpOHq9aWZm0jQaHhMTMovIObn/G3eja7clSBuFS9aOn+Xt5hVVq/Lzxja2TEaHYyullFJKKaXuPhoeKaXwfQk8hsObj+dyEgjdaHNTgqJEQoKP5WUJkObn5Zgx0G63mZw84MQJj0QiinOyg1q9Li1oU1Oyi9rSUng9nPI8ePJJ2Q0tmTRE169w/Lf/D1J7a9h4lK3/4ZuoffFXMhgaGk8a6nWfw0OPYtHx+ONR9vZkQPbUlOXMmeG1tjLLxz4WJ50OWF62zM9LqxpI2LO0FF6rErLs7oakUgNmZzN0OkUODqIUChIaHR7KKx6X++10pFoKpPoqEpFzxkh49GzVRk+Xy2mLmlJKKaWUUurup+GRUgqQ0GN/f9xy1m7fOtjodmF1VYZAV6tQqUjlTSIBsZjMN+p0Wpw7FyWXM2xuGioVj0bDsLHhEYs5CgXL5KTl1a8OqNUMrZaU8mSzHlOTli/t/Ba5X/t5TDCkvrDME//wX8E9x+mUDeUyrK/7JJOOWMyxshLQ7xtSKUu57LG765PJOCIRGeC9t+dx+nTI0pLs4mYMZDKOVMoRjzuGQ8fGRpdGI87c3Bz5fIrBQFrTzpyRAeKRiIRE8biESU8+CY2GBF7GjAdnp9NSfaSUUkoppZRSLyYaHimlAAlFej1YXJRAqFiU8CgIZJ7RaAv5alUqjyoVCVOCQIY8VypDKpUyvd6A1dUopZLDOajVPHzfMTFh2d/3mJy0+D7MzVkANjZ82m1DLOZobjZ5wx/+OMXDDzHoG9Zf8Xe4+OXfQmEuTrdriMdlCPbsbEg67UgkJEDq9WQd0agjkwmZmQmJx2W9mYxlcVEWPxwaYjHI5RyZjGMw6NPrOeLxSZLJLLGYR6832iFOZjltb8sA7HxeAqVcToKy5WV5DjfqdjU8UkoppZRSSr34aHik1EtcGEpVTa83bluzVlrSjJFA5IknxnN8Egk5v7cng7ZlVlGHcrlMqQSlUpxcTmYQXb5sOH8+wspKwMGBoVr1yOdDwFyfG1StSuXR6fan+LJf/bekWwfYYprz3/CdbJ/7fObmLL2eY3vbJ5939Psyy6he90inQw4PfbpdQ69niEQc+TzMzLjrs4OSSUcYetTrMrAom7V0uz06HY+JiRQrKxN0u9HrbWlBIPcE8kxGoZHvj+cRWSsh2mgG0sjT2/5u9axH7W6jv6GUUkoppZRSdzsNj5R6iRq1X33qUxJkbG9LeDKaW3TjIOdoFI4fl5BpfR2eeko+OzPj8P06e3sNJiZ8ikUPsHge7Ox47OxI1VEu5+j1DI2GYW8vQiRi6PdDOh1DoxJy30d+mQcf/lX6fThcOUfze76HzcY89arPxIR8tts1eJ4hlXLk85adHZ+FBUelYqjXDckkzM5aFhYsc3P2erBjrWF31yOdtgwGA9bWwLkJjMnQaESJx8e7vi0tyWficdjZkTlON4ZGI70e1OtShXQj339mNdKN9vcljBu1u934jJVSSimllFLqbqXhkVIvQUEgO6Xt78ucnlOnnjkYu1weX9tqyewf35ffjYF4PCCZrNBuD4A4zhmGQ3vts4bNTZ9GwyMSsXS73rWt6Q3WOmZmQtLpkMHVXV7xH/4ts3vnaScNj7/uG/no/f+EM6Fla8sjk3HX/pa0vc3OWubmQvp9w+XLjkxGQqJs1nHiREA6Dc2m7Ni2vi5/31pHtRpw7NiAXC5LsZgllYoSBFI51GhIoDMYyC5x/b6EadbKHCPfH1cLjYwqsyYnP73n7hxMT+uQbKWUUkoppdQLi4ZHSr3EtNsSGu3sSDCSyUgFTS4n4UYQSPtVrTb+zOamhCszMxKabGx0abVqQECplKBUsoShVAiFIVy6FKFa9chmLfm8xTmDtVI1FIk4fB9mH/8wx3/lJxgctnHTJXa/87tZ81+O2fUIAkun4zE/H+D7UkIUj4PnySDsvT0PY2TgdaMBiYSETNvb3rXZSNDpODKZFtksTEwUuP/+KaLRCJ2OVAf1+3IvExPyTC5elLBoVIHleXLfo/a6G3W7cu2dPu9uV37v9/92/+yUUkoppZRS6rNBwyOlXkKCQNrOtrclyFheluOZjLxGc4zabWnLymSkyqbdllatWs3R6zW5dKnN1JRHsRgjErGkUpbDQ5/JSRlk3WgYVlYCFhYsjYZHs+mIRAz7+4almS73vO/nWf3Y70jQdOyN9L7n2/EmctQfiTA3J983Px/yspcFGAP1umFqyrK6aqnXDfv7PpWKx6OPxqhUfKamQq5cidBsGrJZi7UDPA+OHy+STqcpFHxSqfHucJ2OhD+zs+NnY61UBYG06Hnesz/HTke+507U6/JdsZjMT0om/2b/7JRSSimllFLqs0XDI6VeYmSnMwmGlpelAgng8FDCo2QSUikJU7pdCZwWFiCTGZLLlUml2pw+nWFhQYZSnz/v0+n4GCMBUzrtaLc9YrGQRsPQbsP6us/lyz5ufYsvf/cPU9h9km48yhNv/af8yczf44tmBpTLhmLRUiqFJBKG2VlLsShVR82m7Ma2ve1z5YrHYADptGVyMiSVkusaDUM+HzAz02NiosDCQo6ZGZ9odNyeNqqqajbl3ra35d6DQI4lEuNB4TcaBWijOUqDwaf3zEfhnFJKKaWUUkq9EGl4pNSLnHPSphaGEpasrUk4MqrECUNpR9vbk+qY0cDs0a5jMzNgTJsLF+r0+xbfz+H74FxAuWwYDKSyJh53hKG71tIVsrNj+NSnIsTjsLXlsfT4B/iqx97FRLyNPTHDp77h+2ksniF/2TEYwOGhRyzmaLU8Oh0oFOy18Mlw4UKUQiGk1wNrHYWC4/AwQrMJ0aij33dEoz2yWXjggVmS18p72m15BoOBtKCBVFYVCjLjKRYbP6fVVQnVbhUedbtwcHBz1dDTZ0SNHB5KUDUShlJxpJRSSimllFIvVBoeKfUiF4ZSVVMscm0+kPzu+xKUdDoyPHt9XSqRolEJW/b2wLmQg4MaW1tdstkoU1M++XxAo2F48sko7bahXPZIJh3Hj4dY69FswsZGhEYDKhWP06sdvvCjP8t9T/4+yYSj/ODnsv6PvpOHniiwOgzJZqFc9onHYXLS0m4bEgkoFBzNpuykZoyjVjMcHPgMh2CtvVZBNcT3La3WkGIxzdTUBL7vP6MyqN+XMGxpSe6vWJRA59OpBorHJVx6LoMBlEoyiHzkTucjKaWUUkoppdTdSP+XRqmXgNHuYCBVSNbKTmGNhlQNZTJw9iycPCltXXt7EAR9isU9Op2AyckMp06FdLuGVstweOgThlAsWrpdiEYNiYQjCGBnx6daNbRajszBVT7vj95B7vAqNhHlE2/+5xx+/pdiKjJYO5ezFAoWYyAMZei15xlSKctTT/msr/t0uwbfd3ieo1CwTE875uZCtrchmZQJ1CdPlohGM9cHXT9dpSJVSK3Wza156+t39vxGYdRo8PXthKEEcxoYKaWUUkoppV4s9H9vlHoRsRYuXZJQpN2WqiIYt2oNBtKS9QVfICHHY4+Nt6MPQ/jUp6DVcuzuttjdbXL8eJRGI0W16hEEhmrVEIaG4VA+0+tJZdDx4yFh6NjZ8dnZ8cnlQs5dfj+f+9GfIm57tBcXufIt/4pLg9PksEQjhpWVkGzWUa8bNjdlALbnOaz1mJ8PuXDBJwhk9lGj4ej1PKy1DAYyhLpe7+F5CZLJIo1GlG4XTp26dXjkeRKOzczI+5MnpRrL8yREey47O/J8Dg/v7J/DKKhTSimllFJKqRcDDY+UehGxFjY2JCTKZqV1KpmUeT/xOORyMrtnd1cCpXpdQqDhkGttZkMajRrd7pDJyQiFgmMwkBaxwUACFIBEwpFIWDodn3TasLDg6PcN+bzjzEqTL3roJ4l9+I9wDvZe8WZ2/8dvZWolTvFxx4kTAfG4/N1YDNptj1RK/k4mY4nFQmZnLfW6BF3Hj4esrUWYmRlSLFp8f0C1GpLJTDI3lyEMpc2t05GB3f3++Hm02/K+05G2tVpNfna7cj++L218z2X07HTotVJKKaWUUuqlSMMjpV7AWi0JhqyV98PhOCjyfa4NtpbQJ5WSMGlmBlZWJDgCCVwWFuCJJ1pYW2d11VIoRInHLYOBub7NvIQyhl4PqlWP3d0onie7nu3uegwGhu75db7w/T9MvHGVThjnw2/8NuJf92ZyKSiXYW/PkMn41wdVhyE8+miEgwMP52BuzrK4GDIcmmstbDAYGNJpy8JCgLV9fN9ncXGOTifB1JRUBQWBhDvW3jwEu92WKqBCQe5dBnuPK4g0DFJKKaWUUkqp56bhkVIvYLUa/NVfwdSUvLdW2tDicRkKPTUlAVKjIcOwfV+u29gYh0o7O45ut0a53OTcOZ+5OR+w7O3JIOx4XEKpeNwwMyPBTi5nSKXgnnsCWi2PubmQ4sf+mIXf/ynitktveYkPveUdrEdPsDIIeewxj07H0GwaJifd9bau4VDCnsVFSyrluO++IamUnNvfh+HQ0e0a5uaGpFItisUJCoUS5bLH1asSGiWTcs+lktzfqDUNxsPBR9+plFJKKaWUUurTp+GRUi9g1kow8sADEqRYK9U0xkh1UTIJa2tSNXSrAc5Xrlh2dhpkMjWWlxPk8+76UOhuVwKmgwOPTsejWAyvtauBMY7NTRmanfT7nHj3z5D9oz+k1zVcPP0W/uwN34EfS5KIw9RUSDot8412d33m5sLrf384NMTjjnLZwzlHo2E4PIR+39DpcG1Qdo9SKWRpaZFUKkWlImsbBWGrq1JFlU5LFdXI9rZcd6sZSEoppZRSSiml7pyGR0rdxQ4Pxy1pTz/unOwcBrKb2I0tWKMqnF5PQqN8/uaKHGuhVguo1yvMz/cplZJ0OoZq1QHyuYceitHvGw4ODNYahkNDvS47o5XLMuT6WGSd1/7Wj5A5vETPxXjoi/8Xal/wJUy0fWZnh3S7HtEo1Os+zaajXveYmJC/0WoZej1DLObwfSgUHGBwDqw15PNDGo0hi4spTp+eIBqVtGhvTyqWkklpSUunxy14N7JW2vFuN9Nof//Wn30656T1TSmllFJKKaVeijQ8UuouZS1Uq+OWtBuPd7uyS1inA0tLEoA4J21s/b6EKvG4XBeNSoASjY53X6tWBzz22AHDocfSUpREQlrJSiVJqg4ODLmcY3o6YG/PIxJxLC5aSiVLve5x+bLPqbU/4gv/33fh97sM5+b4xFf+EFuZe/C7lmQS+n2PRsMjlZLqn/l5y8qK5fhxqTx67DGfeFzCo+HQEY0aDg8N2axUG+VyjmJxkoWFFLXa+P4PD2FuTu5lNO9p1IIHMgeq35eA6bkEAczO3tnsI2Oe+xqllFJKKaWUejHS8Eipu9zTK16slUqi+XkJZfJ5CY3yeQk4XvYyCYvCEC5f5nobWqMBjz8OQdBjfb1Mv+9TKvn0+yHdrkcsBrGYJCStlqHTcdRqhp0d79rwbJ+NDY9Obcjye/4DL3/yPdioo/KKN7L3zd9Js5yjGAlJJkPSaUO9blhaCjh2zLK97WGMhDyjUGd316dQsGQyUpHU7Rr29x39fp/5+QTLy0UiEf9am9z4/tNpqawKQwl+cjkZxl2rwcSEBG7RqByPx5/9uQ4GEh4Zo8GQUkoppZRSSt2OhkdK3WWckzlFYTie1zM6Nqqy8TwJTPp92VGs05FQxphxm1YYyvmJifH3DIctJid3iUaTJJPQbFrOn4+STjsSCcf+vlzYbBo2NqI0GiGVis/EBPT7jmB9n8977w8zsXOReMrjib/zdmJv+zLySehtyc5sW1tRCgWpXpqftwSBR73ukclYnDPXh2WHIczMSJXS9rZhOBwQixmOHSuyspK+/jye3laWTkvo43kSEkUico/T03K+1ZIgLZm8/XMul+XnjbuzKaWUUkoppZR6Jg2PlLoLDYdw7NjN4dHoGMjxjY1x9czBgbSx5XLj7+j3pRonGoUwdDSbdcrlOrOzSWIxn1LJ0mz6JBKWs2fHQ6zDEIzxMEbmGy0uhhw7NmTp8kdY+e0fJz5o0Zqf5eG3fT/27GkKaXu9mmhmJiQeNywuOnq9CJGIY3fXo1IxpFIengdhKDcVjcL+vsf6uuHy5YBiMcXqaoZMJoJz43totZ75bC5elHvNZmW20ygA+nSGZDsnoZOGR0oppZRSSil1exoeKXUXGAzGg7FHwclod7R+fxTo3Lxj2s6OfCadlvatc+fkmjCEq1elfSsIwPcttVqVarWN7ye4dEkGVbdahsNDj1rNo9m0pNOOZtPw6KM+V65E2N/36HYt81N9lv/Lz7P6F/9VWuFOvJ4nv/G7qQR5jpmAalW+6+DAYziMEI06fD8gHocTJ0IqFcfKCkxOWrJZe72VbG/PcOmSpdeLMDeX401vSjIxYSgUxtVTlYrccyo1vu/DQwnFRsFRo8G16iXY2oJicVxVdDu93s1hm1JKKaWUUkqpW9PwSKnPMuck7LlxV7B0enxubU1+NpsyIHpkfx+WlyVYSafHc3uslQBpchJ8P6TR2Gd7e4jnJWm3DYOBub7NfadjqNc99vZ88nlHpWKoVHwKBcfKyoDpcJdXv+edTO89QRjxuPCWb2L/LV/L8pLDXnUUi4543LG1FaHXg2jUkU5bGg1DNGoZDmWXttXVkGLRUq16HBwYWi3L1taQfj/LykqWWCzCgw9yfV0jvZ7cV78/PtbpyLynkyef+SzrdQmEnqtlDeS6G0MppZRSSimllFK3dqThkTHmS4CfBHzgF5xzP3qLa94E/N9AFDh0zvI1aPcAACAASURBVH3+Ua5JqbuRMRIEPZ1zcm7UmjUcjiuTRoOj220JU0DODwZSmdPthlQqhwyHAZVKmnzeMRwa0mlHKuUolSyxmGF72zA9HZLJODodj1zOI5u1zD31UV7+2z9GtNdkMDvJR7/i+7mcuZ/JvmVzEyIRRxgawhB6PY98Xr6zVpPh1/G4YzCAVEqqmup1w+XLHsb0qFYjLC5O4nkpOh1pH6vXparo6VIpqT4a3eNoGPatdkhLp+X4nYRHSimllFJKKaXuzJGFR8YYH/j3wFuATeATxpjfdc6dv+GaAvCzwJc459aNMdNHtR6l7kaVilQJ1Wq3Dk5GQVGtJoFJEEibFkh7VqEgVTm5nHzPJz8p1TrVasjGRo10OqTdTrG25rO0ZBkMDJ4nYY4xsLvrcflylEhEWtlqNUMuNeTBD/5H7v3L3yASgf2zr6X+Hd9F2C1w3A85eTKkWvXodqU9LB73sBbicUcqBdlsSD4v4VK7ba7dg6PdtkSjPU6ezDAYFLnnHp+NDam6evnLZd2lkrxGrB0PBh+17EUidzbTSCmllFJKKaXUZ8ZRVh69BnjKOXcZwBjz68BXAudvuOYfAL/lnFsHcM7tH+F6lLqrOCeBUakkYcgoEGk0pCVtJBKR+UUrK1JV1G5LdU21Ch//uFQleZ4ESzs7cPy4BQ7pdIbkcjG2t6VaZ2rK0u0aCgXLxIQlFoMgMBw7FvBFXzSgWvXorx/w4G+8k/iFxwk8j+2v/Z/Yf+vXMrcA5SuOtbUIrZaH73Ot4giaTe/64O7tbY8gMExOyrDtXM4SizkefjhgdzfG7OwknU6CRx+VtfZ6EhB1OnJvo9a90TDwbleGgctub3Juf1+qkW5VeXTjDnVKKaWUUkoppT4zjjI8WgA2bni/Cbz2adfcA0SNMR8AssBPOud++QjXpNRdp1iUCqR2WwKT0db0N1bgZLPSktVsyvvjx2F3F06ckFCl0ZDwJgwtm5sHdLs99vayNBoOz5Pg6NixgFjMkEpZtrc9zp+PsLnpUyxaKhWP2Cc+zn2/8mMkBg2qyWn+8HN/gOKrz5HoOioVSxhCsWh5wxsGeB5cueKzteWRTIZMTMiuatPTIZ4H8/OWZtOjUBjgeT2y2QnOnZtgdtYnmZQA6MwZWfvhoaw9Gh3PehoOYXFRnkcsJvObRjxPwqRs9pnP0hgNj5RSSimllFLqM+0owyNzi2PuFn//lcCbgSTwF8aYjzrnLt70RcZ8M/DNAMu3Ggyj1AvAxoZUxtzIOQmNOh0JUubnZV6PMTB9QxOnMXD5slTqxOMSqgyHcu2FC1KFlEpZ1tbqJBIhiUQG35fgqN02eJ7MO8pk3LV2Mo8wdCwvh5w51WXx936Zuf/2bpyD4LWv4mNv/F6Mm+DcuQFhaAgCGAx8KhXD4aHs0ra97XH5sk8kYpifD/F9qQgqlw3NJgwGHSoVj9nZRYIgSasl7XeVilRLJZPjQd/T03Jv/b68rJVrfF8Cs1RKwiUYDwh/+nBtpZRSSimllFJH4yjDo01g6Yb3i8D2La45dM61gbYx5oPAA8BN4ZFz7ueBnwd41ate9fQASqkXhG4XVldvPtZswt7eaHaQVNNEIuNt6EfCUKp1pqak6qZaleuSSam0OXHCMjGxR683ZHY2Rjo9YHvbp9k0TE/LNcWiJQgMe3se5bJHvw9n5muc/bl3knzkLzFRj4+/8n/mo/d8A1uPxCkWQx56KE4QQK9nqFYNnY7h/PkoOzsee3sem5s+Kyshw6Ehl7P0+4Z+39Fo9MhksoThBK2W3Mgo/Flbk3ut1W6urtrdHYdJ+fzN95/P37rSSCmllFJKKaXU0TvK8OgTwCljzDFgC/j7yIyjG/0O8DPGmAgQQ9ra/t0RrkmpIxcEUjlzK7HYze8jEQlSnJPd1hYWxm1X1o4rlSoVaLWk1SublXlBmYwcHwwc6+sVLl8esr+fBixTUxbPc8RiEsIcHnocHHh0ux7tNvT7jtjaVe775e8jUd+jnyrwiW/8Af68/XKKWTg3MeTkySHDoUci4a4N6jZUqz4nTgREoz7xuGN6OuTzPm/I3JwlEoHBYMDGBpw+PUkmk6VSkfazzU1YX5f7qVRgaUkqjPb3ZX31utzT0rW4eRSqDYcSuplb1TEqpZRSSimllHpeHFl45JwLjDH/K/B+wAf+k3PuMWPM26+d/znn3OPGmPcBjwAW+AXn3KNHtSalng9Xr453BrvRaBg0jGcb9fvSzhaPw9ycnNvclOBob09auYyRwMU5eOopCVackwqkgwPHwUGVRKJNNptkdTVkdjYkl3NsbUlrWSQi65metljrqFQ8En/+QV75B+8iFe3SWDjNY//kB3lkb46NjQjNpqNQcOztxdnZ8YnHQwYDj1rNI5VyrK97WCutbCsrAYmEo9WCXq9HNBolk5mh349Rr8u6r1yRYCgelzAIJERLJsfP4+JFqUwqlaSFr90ezz+anx//rpRSSimllFLq+XeUlUc4594LvPdpx37uae/fBbzrKNeh1PPJOdkZ7XbVMt2uvDIZqcaZmZHj1kqgtLAgFUy5nAQnOzvy+2AglUftNtTrjvX1Gs61cS7B3p5HMgmDgWFrSyqN1tY8fN9QKslOazawnHjfL/Lqj78bz3PsvPatPPwl306tk2Bjw8M5OHt2yOKiZXPTZ2HBcvr0kOHQsL7uc//9Q2IxWefOjs/EhGUwcHQ6XXK5HMViic1Nj91dCYGaTbm/ZFKGXjebMuR7YkJmF434vrSmjXZQy+flGSillFJKKaWU+uy74/DIGJO+NptIKfUs6nUJj+5EPC4tav2+BCuRyLhFK5GQVxBI5U67LeetlfP1uuPwsEy53KPVSuMclEqOqamQXC4kDCOcPj3E82Kk046Xv3xIUGkx+9M/SvHCJxlan09+/tvpf9VX4GMYNqTaaGVlyPHj0nPnnCEWcwwGHtGoIxqVECgalXUUCg4YEo8POHNmmmw2y+XLMtPIWrm2UJDWtIkJ2VWu05F7r9XkBXLPe3syz+ngQI7pfCOllFJKKaWUuns8Z3hkjHk98AtABlg2xjwA/DPn3Lcc9eKUeqHZ35cg6E5m9Dgn1xeLEpaEobSs9fvSxgXyPUEgwUomMwqPHFevVul0mnhelslJy8SEJZt1NJuGK1eiVCoe6bRHu23I5y324hon/v07iO7tUvMK/Norf5it1MuJ/5m7ttObRz5vCUPDlSseqVRIuw3WehhjyGQsgwH0+9Ku5pyjXu+RSkU5d26JbDZGoyFzjQDuuUfa8CYm4KGH4L775B49D44fv/n5NJvyDEbVVzCe+6SUUkoppZRS6rPvTiqP/h3wxcDvAjjn/soY83lHuiqlXsAmJm5/fnMTDg9lnlGrJYOyjZEwyfdl7k88Lq1bly/LfKBiUdrWrl4NeeihMleuDMjnUzhn8Dx3rUXN0GoZdnc9slnLwYEHOAoP/TmnP/hjeIMeu6VT/M4bf4Rebo5TxYDJSctwCJ7nmJtz5HKOTMZRKknbWrttWFiwZLOW7W2fuTlLGIZ0u13m5oocP14kmfS4eFEqjvb3ZZ3z81I5VamM5xw9Fw2MlFJKKaWUUurudEdta865DXNzKUV4NMtR6oVre/vOWtYGA6myCUNoNKQSp1we76y2syNhUjYrx6enpQUsCAKefPKAZjNkZiaOMY58PiSZlPAok3HMzUloMz8f8PGPRnj9I/+JVz7yKwwdXDj+Vt5z7l/iiLNaDJmZkVY3a6UVLZNx7O351OuOq1d9Dg89kkm5oXze0O/DwUFAEARMTc0Ri2WJRKRy6LHHpGKq15MwrF6X4d7WSph043BspZRSSimllFIvLHcSHm1ca11zxpgY8C+Ax492WUq98LTbzz0oG7i2M5mEQqMZQI2GtKZZK+fPnBmHRp0ObG8P2NvbY3/fIwwTLC6GRKOwv++xu+uxt+eTSkEmY6WiqWn43I/+FK+88tu4iM/HX/d21l7/1eT3I+RyltlZizEeuZwlkXB4HqTTjmhUqo42NnxKJak4MsZQLFquXBnS73vMzy8Si8UACcu2t2X9p09LtdTZs3JPmYy8dH6RUkoppZRSSr2w3Ul49HbgJ4EFYBP4b4DOO1LqFq5lKrflnAQqpZK0dTknLVv5vIRKN+46FgRQrfaIx7dJpXzy+QT7+6PZQ461NY9o1JDJhOTzjlTK0et5nPrjX+LYld/BS8T40Ff9CAcnX82x+ZDSZMDEhGVmxgKWhYWQgwNDv28wRiqQYjFpm4tGpYopDC2DQYtMJs8990wSifgAVKvwV38lc456PbmHSgXOn5e1D4cSpN0Ypt3pMHGllFJKKaWUUnePOwmPTjvnvvHGA8aYNwAfPpolKfXiEoZSlTTS74+PX70qv8fj4/O+Pw5cWq0WBwdl7r8/QiQS4eJFsNYwPR2SSDguX/avVw9duhTBWjj+F/+F1Y/9KtZ4fORLf4DHcq9l0loaDQmJ2m3DYGCYmLB0u7C762OtYW9P/rbMTfKJRCCRsPR6Q1ZXp8nl8jSbMjA7GpXd0hoNCY2KRbkHGaYNqZRUTY1a80ZyuTsbJq6UUkoppZRS6u5xJ+HRTwOvuINjSqlbaLdldtFgINU4YSiVRaPfV1flusFAXs5BGDrW12s89FCTyckY7bZjMIAnn4yQTMpsolrN4+DAp9u1DIeGK1cifG7193jjJ38WfHjoK74L702vZXLHcu5cQBhKGOR5jqkpaVHrdmVY9uyspVYz5HIW5yRAgiH5/JCzZ6eYn08DEnZZC4XC+P7yedlZbWpKwqd0+vatauXyze/7fQ2UlFJKKaWUUupu9qzhkTHmdcDrgSljzHfecCoH+Ee9MKVeCJrN8aDr27VkJRLys1SSYMUY+OQnZde17e3xdQcHEIs5nnqqzPnzbdrtNIWC5fHHDeWyoVo1LC8PKRRCIhFHu22oVAxhCKe3PsCb/vL/wvfgj1/+rTw++SXM7FgSCYhEpEKoULD0eoZm09DtegQBNJse/T7s7XlYC4mEo9vtMzNjmJqap9OJcfGifP7SJakekuHZsLUlYVI8Ph6KHY1+es8wHpdKJaWUUkoppZRSd6fbVR7FgMy1a26sI2gAX3eUi1LqhWJ3d9yKVSzeXEEzGIy3qo9c+zctlZJ2r3odNjbgvvtkMPaItZZGY59KpYsxadJpg+8bfN/R7/uk047d3QiNhk+jYRgMoNczzG8+xN996J3E45b1L3kb6ytfTSKUKqPBAJ54IkI0Ct1uSDbriMctqRSk0xZjHPv7PpOTIWBZXGyTz6dJp6cYDHz6/XH4lM3KKwzl2NKS3Pf998tPpZRSSimllFIvPs8aHjnn/gz4M2PMLznn1p7HNSn1gjI9feu2q35fAqRCQapr1telWufwUK5vt2VG0JNPwt4eVCqWjY0KsZjFmDzVqmFlJcD3He22o9k0zMwE+L5HKmUJAh/fh+n987z1T36AuBmw9rqv5vzr/hFsQyxmOHUqJJ+XaqNEwjEzY9ne9rh6NUoq5UgkDIeHHuWyx/x8n+FwQC5XJBIpsL9v2N2VyiJrpaIoEpF7ymZhcVF2gguC5/+ZK6WUUkoppZR6/tzJzKOOMeZdwL1AYnTQOfeFR7YqpV4Adnefe/ewaFQqk0B2JAsCmQsUjcLkJMzPy+5mBwcOY2rk8z0mJ6M0myHxuKFYtPi+w/NkwPXycngtgJJ2tcTWVd78/38v/qDHlfvezNZXvp1WxaPTMSwthUxOWqanLYeHHpGIIxKRndomJ6UCCSAeDxkMBnhewOTkDI1GksFABl1XKnD8uIRdnidr7XQkRPL9cZCklFJKKaWUUurF607Co18B3g18GfB24B8DB0e5KKVeCJpNqb653bDn4RC6XRkSXS6PZ/skkxI81esyD+ngoEmv12J+PkGp5IjFZLh1MunodDx2dnzKZY8giNJqGbpdw6zd5ks//F2kXJMLy6/nd+7/HnIXI9RqhnbbY2EhZG3No1aTmUixGNfPJZMyZDufD4EO0WiO5eVpCoUosRhsbspafV/Cr3hc1jtqz8vlJERqNmX4t1JKKaWUUkqpF687CY9KzrlfNMZ82w2tbH921AtT6oUgkbj9+d1daV978kmp3DFGQpx6Xap6qlXo9TrU6w3uuSdKqSSVRmEI09OWSsUwGDhaLcNwCO22odczeJUKb/3T7yLVLlM/9TLe++AP0e7EyZsQY2BuLuSee0JiMYfnSYh1+XKESESCqVbLsLMDuVyItVM0m1ms9VhchNlZWfvSkqx3dlbCoytXZF7T5KSsv1yWcCmb1QBJKaWUUkoppV7M7iQ8Gl77uWOM+VJgG1g8uiUp9eLhnFTqRCJSydNsShBz4YIEM8PhgErlkOXlCLmcubbTmbSrZTKOSsXg+9Jqls9bcjlHtNvkjX/wXUx0d2gsn2b9295B/C+jzOVDXvaygM1Nn/vuG3DixLinrl43VKuO5eWARsPjiSdColF4xStKNJtSDhWGsLwsa+x0ZD5TqyXvR+1qiQQsLMh3xuPSfjcx8dl4skoppZRSSimlni93Eh690xiTB/4l8NNADvj2I12VUi8w9brM/7lRqyUVP1tbEr7MzUE6LceMgbNnQ4zZZXHRUCwa4nFLv29otaSSp9s17O15bGz4rK35rK5aMpEer//N7ye7d4VKaYnffN2PMngoz5UrEZaXA4ZDCXhmZqRdbmR318PzHNFoSLfbZ34+yYkTJU6dirC7K/OY9vchn4erV2VAdqcjr9FcJ2Nk2Hc0Ov7emZkjf7RKKaWUUkoppT7LnjM8cs79/rVf68AXABhj3nCUi1LqblarSdjS7Uq44nmwvS3BkO+Pr6tWpXrn4EBmBJXL493K7r3XAQdUq5BKxYhEQvb2fMplQxAYnAuvBToevR7E445SPuC173knubXHaGem+cMvfRfVQYH5vOXMmYDp6RDfh1IpxPNgd9cnFnNsb/vs73vEYgHVqqNcnmR5OU2nY3j4YWmr8zwJhup1Geq9tCQhVLMJJ09KlVGnI612i1p3qJRSSimllFIvKc8aHhljfODrgQXgfc65R40xXwb8KyAJvPz5WaJSd5e//EuZ8xOJSJAE8jMelxAGJJC5cEHCmHRazmUyUoF09SqcPFmm2exQqeQYDi1B4LO7K8OtAba3I7TbHjs7HtaCwfGq9/8Ei5c/yiCTZfN7/zUT/iTdbcfKSnh9N7R83uEcHBx4HB56TE9b2m0DDNjfN8zOTjE5mSCblSCoXpfh3aNgKJ+X8Mg5+T7fH1dQ9fuflcetlFJKKaWUUuqz7HaVR78ILAEfB37KGLMGvA74Xufcbz8fi1PqbvXAA1JJ1OvJ+1JJqnVGLV0HB3LuxAkZOH1wwLXZRWBMm0ikgrU5qlVDNivzhpJJKJcNMzMhtZpHJBISjztyOcvq7/0i91x8P8NknA989b8hMMe4/JRPvW7IZv1rAZUllwPnLE88EaFQsEBIr9cnk0mRyxW4994Ivi/BUCQioVGxKMFRuw1nzsj6s1nZcQ2kIimbld/T6ef1MSullFJKKaWUugvcLjx6FfAy55w1xiSAQ+Ckc273+VmaUp89BwdSbWOtvG40et/vy8yfaFTmAUVu+Lep2ZSKnbk5CZGuXIFTp6Db7bG/XyWbzVKr+Tjn6PcllEmlQpzzCAIwxrCwEFAuw/GP/leOf/TXCRMe7//CH+Zi9F6KVUsy6UgmLXNzIZOTjk5Hhmp3uwbnDKurAca0WVmZotnMk80aVldlbe22rHN6WnZP6/dl/YXCzfc6PS3tefPzR/aolVJKKaWUUkrd5W4XHg2ccxbAOdczxlzU4Ei9VDQaMDUFOzsS/hgzPjc3Nw6KIpFxtVGtJu1enc64tS0M5X0mA+fODfnEJw44dconmzUMBo4ggFjMUSqFHB56dLvSchaJyLn0B/+YE+/7OYIQ/vwLv5tPRF9Laig7suVyluHQI5ezFAqOaFTCo37fw/cdxnTwvBLOFeh24ZWvlHXU6xIYdbtS7eT7Mp+p3b45PGq1ZO35/PP33JVSSimllFJK3X1uFx6dMcY8cu13A5y49t4Azjn3siNfnVKfRVINJO1oqdTtrw1DqVYqFCRw8X24/34JnqanwbmQTmeHdNqwsgKtlmM4hErFIwgMmQysr/vXh1zHYhB88JN80R/8OG1j+MPT38JDw79Ldd8wNWXxPEen4wGGvT2fZhMiEcflyxEODz36/T57e3nq9QkODyXU2tuTkKhalXUmkzLIGyQ4isUkXBoxRqqvZmeP7BErpZRSSimllHoBuF14dPZ5W4VSd5HRVvU3VhvdCc+TaqVIRGYglUoS2EQijkajwmAwIBbLAiGdjiEedxSLjpMnh/T7HoOBIRqF06cD8htP8IoPvQMXC3nydX+Pwwe/jmXnOH065MSJkOlpS7lsSKUcJ09KH10k4rhwIUIs1mVmJsbiYomPfcyQy3FtFpK0p6VS8j4Wkyqkel2O5/Pj2UYg999ojIeAK6WUUkoppZR6aXrW8Mg5t/Z8LkSpu8HhIVy6BAsL8nO069izcQ62tqTy6FZh02AA29t12u0Oe3tZLl2KUK0aKhXv2lwkD+ci7Oz4gLSSxbbXeeA/fx9m0OfCPW/lQw/+M3o9Q6lkmZhwRKNQrxvKZZ9EIrw+g6nZNDz1VEgyGePs2UkuX/ao1WBxcXwPoxa7clkqkJwb38dzVVcppZRSSimllHppul3lkVIvKr2ehDy302jI7mMnT0rrGdy+AslaCXwWFsbX36hW6wBVcrkk+/seyaSjULCEIRwe+uRyjlQqxPM88nk4eOyQ17zve/GaTdZXXssjX/GdJKxhcspy9uyQZNKRzToeeSSKMRCPO5pNQ7Vq2N8PuXQpzud8To4rV3w2NyU0On5cQrEzZ8aVRb0e7O5KddTIKFhSSimllFJKKaVupOGResnY3pZWrduFQfW6zDry/Wde59y4UgfGO7EZI/ODmk2p5imXJVCqVgdsb1dZXIwThh71uiGRcHiefK5S8ZiZsZTLUaJRR2e3xTd86LvJBQeszd3LR77iB2l1ooQhnD49ZHraMhwaIhFIpRyLi9LCBlCtOqamhqysTLK6GuXCBYjHZYZRuy1revJJSCRk7YOBBGVB8OzPwrmb29iUUkoppZRSSr003VF4ZIxJAsvOuQtHvB6ljtTs7HintFvxfQlYtrdvDoqck1lINxpV7qRSEko99pjMDqpUIJkM2dysUatFmZyEvT2fWs1jcTGk2zUcHnqEISwthXQ6cLhtecOv/CCl+lUayyu85/X/hgQJwBCNyk5qe3s+nuc4ODDUaoZkEtptw6OPGj7yEZ9Tp6bw/Ri9noRgx49Ly1qxKDvBWTsOjxIJmJmR1+18unOflFJKKaWUUkq9+DxneGSM+XLgx4EYcMwY8yDwI865rzjqxSn1mVKpPHfL2kgQSAh04y5j1koAc+LE+NjamgzIHg4lXPJ9WF6G2VlHGB7y1FNDlpfjLC0FHBz45HKWMJSh1pubHtWq4dFHo2xvwVs+8qMsHP41vYlJHnrbjzLtpVlYCAgCGax9770B1aqH58Hlyz6xGIShoVp17O8HvOY1eb7ma2K8972wvi4Dsc+elcqhbleGYa+uwuTkZ/SxKqWUUkoppZR6CbiTyqN3AK8BPgDgnPuUMWb1yFak1BGo1cY7od0Jz7t5gLS10pomoY0ci0ZlllCnIy1i0qoGw2ET32/T7+dZXg7IZBy9nuHgwKNYBGs9slmHc4bJyZCX/9Wv84ry+7GFOJe+/YeZu7dIvhPQ6Rh6PUMs5q63zMXjjiCAXM4Si1m2tgbE4yVqtSQf/KC0pq2syH1WKtKyFoayPm1BU0oppZRSSin1N3En/ysdOOfqRvtX1AtcJnP7882mBEG53LNfs7U1nnM0HEKrJZ+JRCRw6ve7hGGZVivN7q5PIuHY2PA5OPDwPMf8fEClEmE4dBQKjtUrf84rPvYLEDE8/rb/ncGxE8yULLGYodOROUm7uz7ttke16pHLWba2PObnQ7LZHr1enqmpLJWKVEolEhJqlUrympiQdcdiEiAppZRSSimllFKfrjsJjx41xvwDwDfGnAL+BfCRo12WUp85GxvSivZc+WenI8OyMxkJhW4lCGSnslhMhk7v7MixQgG63SGNRpWJiQRbWxEymZCJiZBWy2N+PqDX8+h0PHo9GXq92n+S1/zej+LHHZ/4nG9i++QbSXZlJzZrIRZzJJNQKDhe+9oBGxs+Cwsh589HyGbblEopLl4skEzKustlmJ6GBx6QqqlI5PZBmFJKKaWUUkopdSfuJDz6VuD7gD7wq8D7gXce5aKU+kwaDmXej+8/97WNhoRD+/s3V+o4J5VJqZR8z9ychDXVqpyfnrY8/HCVXM4SicSwVlrOdnYi1Goe09Mh0ail3zf4PhSGh7zpd7+PuOtRe9NbePz+v89s0lIu++zueqytRUinLcbAyoqj0TBcuRKhXPbY2QmZnk5y8eIU6+uGuTmYn5f1TUzc3G6nlFJKKaWUUkr9bd1JeHTaOfd9SICk1AvGYCDzfpyTlrLbabXg/HkJg1ZXpfroxja30W5rsZi0hq2vS9XR4SHMzDguXKhg7ZBMJsrurkcq5UgkHMeOBVQqHtGo4/HHI+ztRUh5Hb7gT34IGmX2Tt3PJz7/OwgOPOp1RybjaLcNJ06EFAqWdttw6tSQnR2fixd9SiXodi2zsxPUah6Tk7Kj2tycVE6dPCmznQ4OjvLJKqWUUkoppZR6KbmT8OgnjDFzwG8Cv+6ce+yI16TUZ8TWllQJxePPHR41GhIMnTkD58498/xwKK/JSZkp9Mgj8p3HjsHERIP9/TpLSxlSKcfGBqyuhtRq0qaWzTqaTUMYQj474Ks/+X8yX3+CYGaGR//xDzEkhnNQrXosL1tyOUc87lhZsXS7hlLJsb8P4HjwwTrHjis3OgAAIABJREFUjs2QSMSIRmVXuHPnYGFB2vLS6aN4kkoppZRSSimlXsqeMzxyzn2BMWYW+Hrg540xOeDdzjltXVN3vbk5CXuezeXLMl9ob0+qiGZnn3lNpQJPPAG7u7C0BNvb8NBD0iK2tNSj2awQj6doNj1aLccTT0QxJiAed/T7hlLJ0mh4ZDKWV1/4JY5d+iCDZIo//5p/TSeYYDg0PPWUDxg6nZBi0TIzE2ItbG35DAayxm43YH4+z8xMmrU1qYzq96Xy6MbQyDm5XimllFJKKaWU+ky4o43LnXO7wE8ZY/4U+N+AH0TnHqm7UK0mFUIgLWvPJQik1SuRgGQSjh+/+fxwCI8/LvONzp2TcGltDU6cgBMnhnjeDpFIBGPgwgWPTkcqmFZXh9TrHr2ex+XLETzPcfziH3Pyz/4/hlGPT3z9D1AvHePMiQDPk5azY8cCVlak6qjRMBQKMvNoeTnEuYBEIsuxY3nW1uCxx6Ddlha1p884Kpdl/tHMzGfmmSqllFJKKaWUeml7jmYeMMacNca8wxjzKPAzyE5ri0e+MqX+BqpVad+KRKTFLHKbeLTfl5+eN34ZI5U7QSCv4VAql1ZX5fs2NqTFrVQKaTb3SaUgm/VJJBy+75ictCwshHS7HvW6T6kUMhzC6f5f84Y/+XEM8NgX/3NaL3sVkYgjlbLs7HgMhzAYePi+w1qo1TyqVfnXs1YLqVQgn8/geR6NhgRExSI8+OAzd5FzDkolyGaP5BErpZRSSimllHqJuZPKo/8M/BrwVufc9hGvR6m/tXz+9q1qI6PWLxgHSSDDphv/nb07j5Isvcs7/33vvbFvuUXuWVtXd6m7unpVa0MCI4yMWYwRGNnCO4uxgZmxB4yxOGMf2Qz2sfHBA3gMtjGHzQtgi8UyDFhsElpbUu/VVdWVWZV7RkbGvt973/njrVRWtbqrS63KKnXX8zknT8SNiMx4I073H/Wc3/u8zYP7o5ELodbX3bRPLmdJpXbo90NSqRTDIYThQYJjDGxvGxoNFyzZjQr3/vb7ifsjPnXsz/Ps8W9mom0pldx2tuef98lmodVygdH2trv1PCiVIvr9AUePzrG5mWB72xWBWwtvf7sLicAVfrdaB5+lVLoJX6SIiIiIiIgIN9Z59JZbsRCRL9bGhgt6XjyJ83Li2E3vdDouGJqePni8XHbb2DzP9SatrBxMI83M7BGGHaBAFEUsL/t0OoZ227C66tFqeQSBx8mTIRPZDid/4314nTorc4/yiS//Xh67LySODZ5nWV722Nnxue++EcWiZWwsptUy+H7E1FREo9FlNJrE81ypUasF8/Pw1FMwNnbwWTodt9Zs1gViL97KJiIiIiIiIvJqvWx4ZIz5r9babzXGPAXYq58CrLX2gUNfncgXYDBwhdbX26p2tWbTBU77W9UWF6Hfd5M9mYx7rNNx19Wq61OKohbG1Mhd1VDd7xtSKRgbi7l8OcH8fEwQxJTLlsVf+WkKrYt4J+Zof/8/4C2pkMlJy/a260lKJmF6OuINbwhx/2sdqNVG9PtZfL+E57leJoBG49rPEceu3ymX01Y1ERERERERufmu98/s//3K7dffioWIfDHC0IU9NxIctdsucGm33YTR2Ji7zmbdiWq+7+73eu6ktXIZdnagXu+RzdaJ4yz9viGTiQlD2NvzKBRiul0IQ0u5HHHxos/RF/6Q6T/+IN0gwflv/2FS5QKDpsdoFJPJWPp99z7lcszkpL0yCWXZ3oZmM6LTMUxNTXHxooe1bg2bmy48mpo6+DyVigu9rp5EEhEREREREblZXrYw21q7eeXu37HWXrr6B/g7t2Z5Ijdmbc2FPt4rVsC7aaNu1wUu3a6bWLo6eMnnDzqTgsCdsBbHA6Joj2PHPMLQZzQytNse6+s+KyvuenU1QRwb6nWf9oUK93/gXxFG8MSf+m72pk4yGhlqNY/dXY9m000Zra8bGo39cmzL5cs+Z8/67O5G9HpTxHGCfB4WFtypcIuLbhrq2LFrP+vkpLaqiYiIiIiIyOG4gX9q89Uv8difvdkLEfliWOu6gHz/xl4/O+sCl1TKhUfttivQrtddELW8DE8/7V77mc+EfOITLYZDj8EgQaNh8H0+95PPW4IAmk1DPm/Zq8R8w8d/hFzcovfom2l/7TcQhjAcGoxx29R8322X6/cNpVJMKgW7ux5PPhnQ7Q4ZGytQKmWYmoJi0U1WLSzA3Xe7z/nIIzfe7SQiIiIiIiLyxbhe59Hfxk0YnTDGPHnVUwXgI4e9MJHDFIZu+1cYuqLs/QqjKHKTSYOB60SamYn58If3KBRgZsajUnGv2dpyXUidjqFWg91dnyhyW8/u++gvcqzxFPHMBE+9+/+k2zNYLNZaRiPL9rbP9rYhl3MBUK/n/ka1ami3Rxw5YiiXiywtuVPTWi23ZW1y0m2js/b6n01ERERERETkZrpeQ8wvA/8T+FHgH1z1eMtau3eoqxI5ZL2e2/6Vy7mtaanUweONhrv2PEuzuctwGFEuJ4hjS69nmJ+PqFY9PM8FSKWS5dy5gMnJERMrT/HYk79AkICLf+MH6afH8GPwfXe6WiYDYIljy2BgmJiIqdc9Wi2oVi25nOWee8p0u4ZCwXUx1esuZIoit80uk3Hh1r4wvB3foIiIiIiIiNwprhceWWvtijHme178hDFmQgGSvNYlk67raGLCTfj0+/DUUwfPjUZNgqDNiRMFgsBtLSsULKdPRywvw/h4zNaWx+6uYX0dlkot3voHP0rCi2l983sovPNBUituW9vUVIwxLjQKAkuv52MtZLOWatWwu2uAkIcemqRcDlhdPehjarXc1jVrD06G23vR/3374ZeIiIiIiIjIzfZKk0dfDzwOWK49R9wCJw5xXSKvaGvrYALnRqZvej13WtnqqiubfqnOoDCEEycgl2uxt1flnntSPPlkzNmzCYpFSzJpWV/32N52dWHVqsdgAJ6Jeex3fozioMLozCna7/3L1CoeFy/6VKseySTkcpZsFnzfsr7uUypFpFIBmUzMxESPe++d4p57UiSTbh3z8y7QqtddeJTJuMLswcDdioiIiIiIiNwKLxseWWu//srt8Vu3HJEb1++7I+sTCRcE7Z+Q9nLC0E3ozM2508p2d93Wtb0991y/D9UqBEGfKNoll8swGlnqdbdF7dixkDiGiYmYVstQLEacP+8xGllOPftbLJ77MPVEjsEP/iC5ks8gsiQSblvbI48MSSYhkbA0GgZjLEtLEaMRJBIdxsamyO0XL+EKvD/+8YNupmRSp6mJiIiIiIjI7fGKp60ZY77MGJO7cv8vG2P+lTHmyOEvTeTzRRGMRu7HWheqpFLu9kZ4nus4GgxccLRfmr0vk4kZDHZZWvIYH4e1NZ+9PY8ogunpmEzGTQClUtBseqytBXSfXuOdn/5JPB8+9Oa/Rzg9S70Oly/D1pZhMIDRyNBue/R6Hr2eT6lkmZiIGQz6jI2VKBQK16yzXodaDcplV+g9NqbwSERERERERG6P621b2/f/Ag8aYx4E/j7wH4BfAL7iMBcm8lLW1lyAZIz78f1X93eGQxcABYH7G8mkC5La7SbpdEQ+n6DbhUbDMBrB7GxMv28+t9VtNILnnkvAYMjXffj95JIDml/xLj6Tehezl/psb3usrPi024YzZ4ZkMpYogsnJmFTKTTNtbQ2p1XKkUhOsrRlmZtxaEgl4+ml3Ozfn+piKxYMT4URERERERERupRsJj0JrrTXGfCPwr621/8EY89cOe2EiL8Va1/dzo5NGL6dWg+1tF8j4vptI+tSnhgwGLebmErRahs1Nj+XlAGNgcTGk3zdMTcUsL/s8+2zA+rrPV37iJ8hurbBbWOLDD30v7U8aslnL2JhlcTGkVIKHHgrZ2/NoNDyCK//HNZtDhsMUmcw4g4ELjlzXkns+iuDMGXj4YT73O/D5RdkiIiIiIiIih+1GwqOWMeaHgL8CvMMY4wOv0C4jcvN1Oi5UeTUGAxcY7fciDYdQKLhS6kwGZmYsmUyN+++PSaV8lpc9Njc9hkPL+HhMsRizseEThh61mkciYXm48Yfc+8yvQyLgF+//R0SbecBy+bJheTlgcjJmcXFEIsGVbW8RU1OW0WjE5qYhn5+kXPbxfZicdJ/v4kX32uEQZmauDY6sdT1NMzNf9FcpIiIiIiIicsNuJDx6D/Be4G9aa7eu9B39i8Ndlsjnq1Qgn782ULlRw6H7yWSg2XTTRlF0sO2t0WgwGPRJJpPU67C56XHxYkAUQa9nCEPvyoRSzHPPJUnXt/nq3/0xRiPD01/5HVTz9/D2+wcsLcH8vCWfH3H6dEgqBe22YTAwbGz4bGxEhKGl3Z7BmMSVQm33mXI5t6bFRXdbLn/+5zDGvV5ERERERETkVnnFf4ZfCYx+CXjMGPP1wCestT9/+EsT+Xzj426L2RcqjuGFF1x4tLEB3a7rEXLPjahWq6RSeSBma8unVjNXgpqYwcBQLMYYgyvP7g74i4+/jwJNnl16M2tf9k3M7YSMj0dEkaHfd8VI1arbqravUoHp6R7J5DSjUYq5OReGTU+79Q0G7rNls66PCWBz89VPW4mIiIiIiIjcDK8YHhljvhU3afQHgAF+whjzA9baXz3ktYlQqUC/7+6PRq/ub7TbsLPjpntOnXJbxKpVuPdeyGYtzz1XJZfzqNV8Ll6ECxd8ul1DJgNTU5ZEwvLIIyHNpiEcWb7p2X/B9N55oukZPvpVP0TJ9/A8OHs2QbfrkctZCoUY8Emn3alqnQ4YE/Hoo2PUallKJZidhV7P9RglEm4bXTbL50q5AVotWFg4eOzVBGciIiIiIiIiX4wb2QD0PuAxa+0OgDGmDPweoPBIDl2366aNEgkXoHwhRdmdjivFrtXc/f2+o17PTfoUCnDpUodPfzpkYSHP+fM+nQ7s7bkT1vJ5izEW3wdrLZWKR/G3/ht3X/hdel6aP/yz/5RafwzTjOj1DMkkPPzwkFQKOh1DGBoaDUMUuZPVstkcW1slzp1zXUu5nAuQajW4556Dda+tQRgeBEY6ZU1ERERERERupxsJj7z94OiKKqD5B7llUqmDbVxfiP2Jo3rdTfBMTbkpn9VVN8V06VLERz7SYG8vzfx8TBwb2m2X2IxGHqlURKnkOovOnw9o/d5nefsf/TsI4INv+iFa+bswA0un45HJwOJizNJSzAsvBOzteczMxCQSMcePd5iZybC4WGJ7252s9thjLhy6dMmFR1dPFO2HR5cvv7rPLSIiIiIiInIz3Uh49NvGmN8B/tOV6/cAHzy8JYncPMbA2Bjcdx/Mzbn+oFbLhUfJZBVr3fTP0lLMykpEJmOZm4vx/ZjZ2YhEAjodn9TuJm/+0Pvx0hErX/legrd9GQ8eCanVDFtbHuVyzNSU60WKIshkLOVyTBjGRJEll5tkZcVQqbgi7ETCdTD1enDypCvB3thw16ORW9Ndd0E6fbu/QREREREREbnT3Uhh9g8YY94NvB3XefQz1tr/fugrE3kVrHXhy+4uXLjggpwwdIHR6qrrPXL9Q312dprAGKWS25qWy1kGA1eqnclYwhDAUM61efSn/i+8Xotzs2/ld499O4tBTK9n2N42rK35TE/H1Ose6+s+zaZHKmV58smA8fEO6fQMmUyCbtd1GpXLbo2jkZssSqfdGgcDmJmBo0ddL9P+SXAiIiIiIiIit9PLhkfGmLuBfwncBTwFfL+1dv1WLUyk2/3CTxqr110Z9t6e+/2xMRca3XefC2dOnoRaLebixQqDQZpEAkoli7WW0cjQ7Rrm50MSCcv6ukcmbXngl/8lXLzETu4Iv/nmH2Zu0pBOQ6tlqdcDZmYi7rsv5Ny5gMHAcORISBBY9vZC3vKWgOEwSyIB5865rXMnTriAam3NfT7Pcz9jY+7kNU0biYiIiIiIyJeS600e/Szw88AfAd8A/ATw7luxKBFwJ61lMgdF169kNHITRr7vtn1lMu623XbbwdptN5H0+ONtVlZ8BoMMcex+d33dUKsZ0mlLvW44dy5BFBnetfbzTD7xYbrJLP/ra/8pU3MZ7r9/xHDo3qfZjK+crAaDgcEYS7FoWV42NBo+3e4knmcIQzddND3t1gWu66hQOAiPxse/sEJwERERERERkVvheuFRwVr7767cf94Y8+lbsSCRq01MvPLx9FHkpox2dtzEUToN/T7k8y7g2dhwgU2hANXqkHa7yT33BPT7IVNTMTMzMRsbHsmkpdXy2Nz0GA7hzcM/5v4P/0ei2PAnf/Z91IpLTKZj+n3D5qZHreaxtWVIJAy7uz7WWqLIsLlpqVZHzM8XMSaB5x2c+OZ5LsACNwk1N+c+o7aoiYiIiIiIyJeq64VHaWPMw7ieI4DM1dfWWoVJclNVqy702Tca3djvtVpuu1qnA8UiLC66IGm/W8ha95jnWS5c2GNpyZLLwdqaYXzc0usZ2m0PYywXLgTU6x7zwxXe/ic/imcsZ//032DuW99Iph4yPR1TLsdUKsHnJoUqFY9CIWZpKaJS8cnlejz4YJrZ2RxRBHEMw6ELuTY3udKl5G6LxVcOx0RERERERERup+uFR5vAv7rqeuuqawu887AWJXemdtuFKftbt8bGbvyo+mzWTRel026L2sWL0Gi4UKlWc0XZy8ttKpUhyWSaS5c8qlWfVgvW1326XUgkLMvLHvPFFn/zmX9I0e+w+eg7uPCO9xKddcXYxaIFLJcuBWSzMdWqTzYbMzcXA4adHSgUAhYWxikUzOc+hzFuDWNjcOSIu3/xottWZ8x1P5qIiIiIiIjIbfWy4ZG19itv5ULkzmTttdfZ7CsHRsOhC4b29fvX/k616vqDggDW111gU68PuXixwdJSgO9bul2YnY3I52P29gxTU5ZCIaaybfhr597PVGeVwdFjPP3N38/uqk8mYzl2LKJcDtnc9LnnnhGjkSGTgenp6ErpNsTxkPvvL5DLJcjlXJC1seHWm0x+4QXgIiIiIiIiIrfb9SaPRA7V2prrKtpnzI1t4er13E+h4K7zeTdxtLbmSrZrNRcYNZvuuRMnYnZ2qkxOQrHoUa26rWaTkxGbmz57ez5Hj46YnIz52o2f4+jqxzEzebZ/4B8R1rL4vmVy0nUjVSo+o5HHwkJEpeJRLEYcORLRbHoMBgOmpzPMzORpt93UU7ns1rO05EKuctmFWiIiIiIiIiKvFfpnrNw2cey2cL2ao+lTKTddtK/Vcn1Cg4G7bjbdT68Hm5sNarURpVKKy5c91td91tY8pqZiEgk4dSpkfj4i8cQT3PfZnydKGC58+w9zvrFEpeLRaHh0Oh5RFNLtehw/HhIEcPmyx+KiGyXqdGKWlmJKpRKTk4YgcOXdcex6l6LIBWP7gZeIiIiIiIjIa4XCI/mSNRi44usXC0O3ve1q1roQamrKTRttbrrbTqfLcFhnYSFDJmMxJqLdNpw6ZbnrrpBm06PVMoSVBvf/0j9nFFjOv/3bGHvrQ5S2IrLZmGYzQSpleeABt2VtZibm3Dl3ulomE1OteoRhj3J5ksEgQSYDKytw4YILtZpNFx7Nzbnpqu3tgwJt9R2JiIiIiIjIl7pXDI+MMQb4NuCEtfb9xpgjwKy19hOHvjq5ow2H7nZq6vOf8zzXbWStC5mqVdct9IY3HLwmjkcMBnWy2RTJJOzsuGLstTWPY8ci1tZ8MpmYyyse9/yPHyPaqrJRPsOTb/mrvKkfc+GCz8pKwPp6wOJixNaWTxhaPvvZBM89FxAElmLRp1KJWVzM0u3mSKfd2oyByUk4c8ZNIE1PHwRenY67DgLw/cP/HkVERERERES+GDcyefRvgBh3utr7gRbwa8Bjh7guEcCFK5nMwfX6utsG1um4LqFczgVHrZYLkoyB1VXwfUutVqNUiimXA3I5S7NpCQIolSz5fMzFiwmmp2Hqd/87k89/gm6uyG+/44fJWZ9KxVKtevR6HnfdFfHYYwOyWVhf97hwIaBQiDl9OuTEiSGXLlkWF2cJQ4MxsLzsJo8yGTddlEp9/qRUKgWJxC39KkVERERERERelRsJj95srX3EGPMZAGttzRiTPOR1yR2u14OtLSgWr32834f5efd8Lue2gi0vu+f2J3niGNbWmlQqITMzKeI4otHw2NszDAYwHBq2t33Sacux7nMsPfPTpFNw6e/8XeanJikULL5v8DxDuRzz8MMjpqctw6Ehk3HB06lTIUtLMdb2GB+fZ28vwdKS2zq3u+u22913nwu49j/D6qpbP9xYMbiIiIiIiIjIl4IbCY9GxhgfsADGmDJuEknk0ESRC4fSaRe67NvYcM9Vq25yZzBw/UYLC1AquQmkYrHP2bNNpqcThCGsrnqsrQWkUpZcLubSJSgWfSZSLY5+4P/G2JCtr/hGem96G+M1C8Dzzwd0uwbfh0bDY2bG/Se/teURx+ZKmDQglyvQ62UZDmFmxq1xNIITJ+DNb7620ygM4ehRt251HYmIiIiIiMhrxY2ER/8P8N+BaWPMjwDfAvzwoa5K7mjWugAG3KROOu2CJIBG4+DEstlZFx75Ptx1lwtn6vWQVmubZDLF+LjB8yyDgaVYjJiejjDGsLaW5shSxDt/78fxNrfYGT/Js1/5XSS3fNLpmKefDmi1fPL5mGTSMjYWYQzs7RnqdY84toRhSBwblpen6HQMySR8/ONuO1qlAseOuZAriq79XMYoOBIREREREZHXllcMj6y1v2SMeRz4KsAAf95a+9yhr0zuWN2umyyamHAhUjJ50BmUybj71rrtYJ2Omzza2YEoslSrewyHYG1AtxvT73ufO9UsnTZ0Ou53vzb8dR6qfAi/nOJT3/E+ErmA3V1Dt+vz/PNJyuWQQsFe2cLmTkxrNg27ux6LiyGTk13Gxpb42McCFhfdVjmABx6AS5fg9Gk3MRXHB2FREGi7moiIiIiIiLz23Mhpa0eALvCbVz9mrb18mAuTO5e1LiCamHDH2oPbjhaG7rl9cewe39pyJ7KtrDQ5d25Aq5WnVvMIQ9dvlMtZWi2Pp582XL4ccNxe5KHf/SlXqv23vpdadom4ben3DfW6IZuNKJVcaFQqxQwGhn7f0O0aEglLNtul15tmezvNzg4sLbkJqcEA6nUXdhnj1jo356aRRERERERERF6rbmTb2v/A9R0ZIA0cB54HTh/iuuQOFcdu8ujFdnYgn4exsYPpnXbbTR3ValCrDVhebpJMJtnbM6RSlnTakkpBuRzT6cDenke3NuR/O/+P8cMBKw+8i89kv4bz531yOUsiAb5vuPvuiFzO4nmWMISzZxNXAijDcDhidbVILlek3Ybxcbelrt122+implyI1Ghcu2VNRERERERE5LXqRratnbn62hjzCPC3Dm1Fcsfq911fUKUCk5Owt+eCmHTaPT856bZ+tdvuem8PLlyAwSBidXWXKApIJAyjkceJE0OSSRcsPfOMT71uAMOfu/CTzHYuUs0v8YsLfxf/rCvVNgampmKmpmKqVY/NzQBjLMeOjRiNLIVCxGgUc++9EXE8yf33u5PbMhkXGsWxC5IyGbf+IHChUiJx275OERERERERkZviRiaPrmGt/bQx5rHDWIzc2RoNFyAlEi54iWMXFEXRtd1B4EKl1VXXRTQ+3qBQGOD7efp9y+RkRLEIUWSIY0MQwMREzNyzf8wjy79OMJZg5bvfx+l8ktnZAdvb7gS12dmYOIZazefkyRGZDJw5E/L00wbPi7A2Znx8ik7Hx/ddQBQEbg2djps62jcxcRB6iYiIiIiIiLyW3Ujn0d+76tIDHgEqh7YiueOEoSvIrlTclrSJiYMgptl0992WsoPf6Xah14NisUupVGd+PsXuruXyZY9MxrKz4zM/HzM5GVGr+SQqW7ztQz+GH8Dat3wXm4W7ePopn2bTsrUVkE67bWn1uqHTMRSLhqmpmGwWkklLItHjscfKTE4mPzdlFMfu5LcgOAi8trcPTooTEREREREReT24kcmjwlX3Q1wH0q8dznLkTtJouADIWtjddeHL1JTbnna1TMYFNPuiyBVT7+2FdLs1KpU8q6seg4Gh23UTSvm8ZXw8YnMzoNuI+OoP/AjpUZvt+97Gr/Et1D7lc+FCQL/vYQxkMhHGGKw1LC1FHDsWMjtrOX/eZ3d3xPT0GN1unkTCFWLv7kKp5EKj/RLvRsMVfU9NqSRbREREREREXj+uGx4ZY3wgb639gVu0HrmDDIduyiibdSHM4uLBSWUvp9WC5WW4fBk6nRbGWIbDgOnpkEzGEEWGlZWA2dmIjQ2P7W2PU7/97xhbO0t3qsyH3/n36VYNc3MhUWR59NERJ0/GNJuGUimmVvOYm4vpdAw7Ox7nzsUcO+Zx9GiJwQDm510wFARu+giuLfjO57VdTURERERERF5fXjY8MsYE1trwSkG2yE2xteXCljg+mDpqNFzgciPTOta67W2rqwOSyQ6pVJpMxjIzEzMxYXn+eZ/lZUM6bVlb85l85qO88ex/JZH3uPQ9/5BWu0AcGwYDw8SEpdczjEawvu4xHLqtcevrHmFoyOeH9Ps+09OTRJH3smuqVNypby+emBIRERERERF5Pbje5NEncP1GnzXG/AbwK0Bn/0lr7X875LXJ69BwCDMzLjCamXGhUbfrTizr9Vz/0dXi+NrrXg8+9rGIy5c73H13kmrVY2Ehpl73CMOYVsvg+5ZSydJ8fpuv+9Q/w0vA9rf8DbonTxM9bpicjEkmLblcTKvlMRrFBIHbrhZFhkbDTUJlsx18/yjZbIJ83nUZXbzopqN8321bAxcczc7CkSPariYiIiIiIiKvPzfSeTQBVIF3AhYwV24VHsmr4vvuZ3rahTT9vrve2nLBjHfVkE8+f21RdqMBjUaPKLIkkz6+72GtZX3dJwx9Wi33+6NuyJ/+0D9hzGty6f63Uv+6d9OpG5pNjzi2jI0ZxsYszUmMAAAgAElEQVQipqYs994bkk5bZmYs7TaMRobRqEe5PEkqleLIEde7dPas62U6cuRg25q17jn1HImIiIiIiMjr1fXCo+krJ609zUFotM8e6qrkda3bdYHRS3UD7QdKL2atK8p+4okenU6fQiHgTW/qMRx6lEox/b7HuXM+29s+e3sw9Ymfo7R6lt50mT9+5z8geynBxYsJLl/2mJiIOXYsIpGAVMoyGMDKis/Ojk8UwXA4JJPJs7c3wWjkgqJKBdbW3LRUuw1jY7Cx4e4bc23gJSIiIiIiIvJ6cr3wyAfyXBsa7VN4JK9aq3VwtP1w6B6rVq/dstbpuGPv921uwt5exG/+Zp9s1ieZNJ8LbAYD93rft0xORty9+XEeO/dfSGY8nvrr7yOZzpHJxIyNxZw8abn77hELCzHttqFQgF7P/a1yOaRQGBBFkMlMs7ZmeOMb3Vp3d11IdOyYmzRKp917Li66wm8RERERERGR16vrhUeb1tr337KVyB0ll3MTPe22u242oVw+mDoKQxfSlMvuemMDoqhBOh1z8qRHJhOSy7kJpm7Xo902dDoGNnd4x//659gYPv7Yd3KBBwhCy8pKgkrFIwgs1por3UY+iUTM3p4hCOyVsMowPj7L3l5Ave6mpM6fd+HRxITbniYiIiIiIiJyJ7neZpvrHJgu8urU627yyBhXfr2760IicIFSHLuJnsHAbQUbDl3A1OsNgAaZTEAQuNeurfm02wZj3N8zUcSf/tA/JTVo8cLcW3jyzF9gbCym0/G4cCGgVIrJ5y3pNIShIYogkbBEkSEMI4wZ8Oij06TTSXZ2DtZbrbpJo4WF2/a1iYiIiIiIiNw215s8+qpbtgq5Y4xGMDcHxaILj1Ipd8R9s+meb7VcWJNIuHLsF14AY2LOnq3T6+UZDiEILMlkTBi6CaVz53wqFY8zv//TjK09Rys3xW+/9YeYzbtu927XMDYWk8m4oCgI3K5LFyZBPh9SrY64994yyWSawcCtb2zMBVkPP+yuRURERERERO5ELxseWWv3vtg/boz5GuBf4/qT/r219p+9zOseAz4GvMda+6tf7PvKl4adHbft62ou/Ln+76VSbtpov/Nob69BtWoZDAKSSUO9buj3ffJ5y9aWx6VLPvftfpjTn/4VBp7HLzz2j9nujeFXIqz16HZhYSFkasoyNhYDhmrVIwhinngiAEYEwRTDYY7nn4enn3aTT/W6O1Htpcqwe71rO5pEREREREREXq9e4Z/xr54xxgd+CvhqYA34pDHmN6y1z77E6/458DuHtRa5PQYD1xN09alqQfDKR9rHMfg+HD0Ko1GfS5faFItZEokYz4uxFk6ciFhcjFheDjiW3uDPfOxHidOWp9/57fTn7uPUbEgyCfPzMeVyzAMPjNjZ8Vlfd6exJZOGEycsvt/mzJkciUSe+XlYXna9RpmMC42OH4d8/vPXWK1CMvnKn0VERERERETkte7QwiPgTcAFa+1FAGPMfwa+EXj2Ra/7PuDXgMcOcS1yi0WRC4ESCRey7NsvxH4p1sLly24LWxTB7GzMxkaFRCJBOg25XEwmAxsbPrOzMevrHjsbEQ/8/I8wqra5OP8WHr/3PaT7hiBw00XT0zFx7H7HGEunY1haiikWIzqdPslkntFognrdhUUuWIJCwa0/l3v59Y6NuZBLRERERERE5PXsMMOjBWD1qus14M1Xv8AYswB8E/BOFB69rmxuuvDl6i1qnY7b7uUKq11QczVrDzqRogharQZbW4ZEImAwgEzGUCxGbG/75HKWra2AN/yvn6a8dZZmvsxzf/HvMzUBzWbM1FTM3XeHPPhgyNmzAdZCrRZQqXgcPx7S6w0xJs2ZM+NkMoZ63a3J89zEVBy7Mu98/uBEuKsNh4f7/YmIiIiIiIh8qTjM8OilTmuzL7r+ceAHrbWRMS9/uJsx5ruA7wI4cuTITVugHB5rYXb22kmjdtsFR/m8C1+qVdcpVKm4sGhfIgGj0YBms87iYoY4jrl8OaBSgVLJkE5bV2r9wlOc/Niv0DE+n3z3+zj+UI5aDYIgplCwBAEsL/tsbHjk8zHDISwtRSwsdNncTDA3N8nRox6tlguLpqbcqW3ufdx6MxnIZj//8+Vy127HExEREREREXm9OszwaA1Yuup6Edh40WveCPznK8HRFPC1xpjQWvuBq19krf0Z4GcA3vjGN744gJLXkEzmYKtXq+WmjILAFWuvrbnJH2st1WqVRiNJp+MTxx47Oz6ZTEyjYbl40Wf5eY/3/MaPMxwa/uQN30bvntOkUhG9nqFSMeRyEWFoiGMYG7MUi5bz5z0ymQGPP55iaqpMOu0mkvb23JTR2pq7HY1gZsaFXMXiS3ceiYiIiIiIiNwpDjM8+iRwtzHmOLAO/EXgvVe/wFp7fP++MebngN96cXAkr33VqgtorHVTRSsrbtLHGDfhk0y6aZ/5eRfeNBpNms0hKytFPM+9zhiYm3MTRb5vefMz/4nZ/iU2ckt8/L6/whnPI45DWi3D9HRMKmVptXxGI3fCWqkUk0iEHD3aZWJikWQyQRjCpz8NTz4J/b6bMEqnXaA1Pu7WKyIiIiIiInKnO7TwyFobGmO+F3eKmg/8rLX2GWPMd195/t8e1nvLl5YwhHLZBUWDgZs4Wlx0AdLVhkMYDEYMh7t0OgV2djxOnRoRBLC767G359FqGeKLqzz8mV/GAh+4/weIgyR7exHLywnW1z1SqZizZ30mJy1BYIlj957t9ohSaYZEIoXvuzV5nltLsQgLCzA9fVDw3enc8q9KRERERERE5EvOYU4eYa39IPDBFz32kqGRtfavH+Za5NbZ3XUh0dU1VvvTQ/v3k8mD7WvLy+53hkP49KebjEZZtrcDrLXMzMRsb3t0OlAsxuSzEe88+2OkgyGNr3gX3fIZypmY48dj8vmIft+wsBBjrc/4uKVW88jlYjqdAUEwSb2eZ2rKTUK98IKbONrdhdOnXY/R1SfDiYiIiIiIiMghh0dyZ+r13FTPSxVKR5HrFBqNXMBUr8P2tnv8mWc6bG4OyGTcZJDvG1otw+XLPoOBAQzzj/8Oc5tP0h0b5w8f+tt0z3ssLoYsLERUKh7T0zGJBBQKMZOTMdmsZXGxg++n2drK0+u5KaRm063z9Gk3YXTmjJtCgoPtatq2JiIiIiIiIqLwSG4ya93Py03wrK25fiPPcyXZqdR+kBTR6zXIZBJsbHgUi5Z+3/CRj6So1TxmZiIyvTqP/cnPYC38wSPfwyfOTtDreYShR7NpaLcNpZJle9ujULB4HuzsxGQyAel0mX7fMD4OR4648KjTcdvUtrcP1re56U5Z2zcxcbjfl4iIiIiIiMiXOoVHclOtr7swqNuFWs09NhgclGXv348i14V0+bK7bjRaDIdgjMfcXMSb3hTy/PMJNjYMDz00ZGIiZuYnfpJc3OLckTfRe8dXULxoWVwccepUSK/nwqMwhG7Xw5iIwQBeeMFQLE6TSASMj7vT3rJZt2XOhUuuHHt/6iiOXXF3Lnf7vkMRERERERGRLyUKj+SmstaFL82mC2hyORcY7e66sKjTcSHSkSOupHp3F5LJATs7TaIoS7NpmJmJGQ4NjYah3zdMTlpKz3yS+ad+n34mxe++8f+gcynB+rpPJmMJQ8P6uo/nuS1pySQ0mx6+P2BxcZx7702RTLr33p90Go3chNFo5Iq8q1W3/uHw9n5/IiIiIiIiIl9qFB7JTdHruZAoDA8eS6chn3dhUbvtTjULQ1dSHcdu+9rWlmU02qPXS1CvG7pdQ6Hgtp71+5BIWPq1Aff/0k8SR3DuK/4qm2ae1ADGxyMefHDEww+HWAu5XMzGhs/ERMzKSsTJk0l6vSyVCkxOui1zqZSbirL2YNroaqXSS3c1iYiIiIiIiNypFB7JTbG7ezBpdL0Ty9bX3baxSgWefx62tztAyNpagWoVRiOPmZmY3V2fvT1DoRBT/sAvkm1ssVK6m9+f+1ZGuzA+bslkDKVSzGc/m2B11SeRgF7PUCgMKJV8HntskuefNxw/7t5zdxeWltxkFEAQwMqKC5ZeKkgSEREREREREYVHchONjbmQ5nqiyPUO9Xpw+fKI4bDN5GSKTscwNRXj+xFHjkQUi5bxcUPq0guc+tSvYPH4n498P2ubSfJ5t93srrtCUilXeD0xEbG352GtJQxDyuUpWi2fOHaTRKORmzqanDyYLOp0dKKaiIiIiIiIyCtReCQ31XDogqHh8OW3fw2Hbkqp2ewwPR2Rzfrk85bFxYhkEpaWXOdRwo95y6/+GLlMxNNnvpmz3n14Q3jggSFxDIuLMTs7Pjs7PsViTBBAsdjlwQcnGY1S5PMu0CoWXXl3NusCpH2bm+45Y27NdyMiIiIiIiLyWqTwSG6qWs2FQ8mkC4+iyG0XazRgddWdbhZFUK32qFQGpNMZwhDS6ZhUCra2DB/6UJJ63eON53+VzMo59sam+dWp76C/ZTh9esTsbMT6uk+l4mGtmyqKY8PsbIepqSxTU3laLSgU3FRSo+HWdXUf075yWeGRiIiIiIiIyPUoPJKbrlh0xdPgSrQHA1ecXau5TqSpqYhz5+ocP+4zNRWRThvm5y2eZ1ldDTh+PORYeoc3/ad/TzJhOfsXvpfRXpaJiZgTJyJ6PbfFbXIyJp22QEAuN2B21ieOJ6jVXCF3GMK5c64gu9VyvUabmwf9RnGs4EhERERERETklSg8kkPn+66cutl0E0nLy03W133iOEkyGRGGUC7HtNvQbHqkU/DwH/wkQdhn68w7aD38VuzvGWZn3alqUQT1uqHRCBgMYGXF48QJj4WFKVZXPQYDmJhwpdxxDKdOHYRHExMH6/I8hUciIiIiIiIir0ThkRyKKILz593UUSKx33EElcqATqdFPp8lDGNOngzZ2fExBra2fMIQ3rD9YcpnP8peMsen3/k9TPjub3qee83994/Y2vKYmLBEERw50uFbvmWMsbEEUQQnT7rJp40NN/E0GLgepsnJazuPREREREREROSVKTySQxFF8MILMD3tTjS7dMmFOJcutfH9JL5v6HQM7bbHzo7Hzg5UKh4M+oz/x5+h1zP8zt3fxXObszw8G2Kte20cu61v/b5hNLJYO2JuLkcU5dnZcR1Hk5MHXUv33OOmi0olV54tIiIiIiIiIl8YhUdyaFoteOQRF9584hOwtzdgbS0imUyRTEIuZ+l0DJWKodMJGB+3vGPzP5NrbrIxfhefOfENnDoaMTUVk89HdLse4+MRuVxMoWAJgpDZ2RGLi9Ok0y6kGh93IVE264Kr+Xk38aQtaiIiIiIiIiKvjsIjOTR7e653yBh34lki0ebUqYjhMCCTcQXZrZYhmYTp6YhHFzY4/V9+GT8JH33797Ewa3j44SG1mk+xaAlDS7EYMzZmmZ6O6XRGnDw5QTbrUyq58CibdRNH5bI7ba3Vcu89PX27vw0RERERERGR1yaFR/JFqdfdaWbD4cFkz9qau+503O1wCNYO8LwB8/MBTzzhXmitodEwLC8HjI9HfNkHf5awO+LS/V/Js+lHmM+GtFqGZ58N6Pdd6XYUGfp9w+5uxPh4klwuh7Wfv67JSVfOXa26aaRi8RZ+KSIiIiIiIiKvIwqP5IvSbkMm48KZdBpqNdjZcaecJRLw3HOub6jXa9NuB2QyHo2Gx9LSEDAEgcHzIr5+/pPc9cHfZ5RJ8vjbv4vusguK1td9PA9SKUu16uN5IZ4Xk0rFzMyUWV01NJuwugqjkQuu7r3XBVlR5IKrZPJ2f0siIiIiIiIir10Kj+RV2w9n8nkX0IxGbhKpUoGLF930T7EIc3N9Ll7sE8cZTp4csb3tUyhAFFl83xINY+76b/8GgPZf+EukjkyxOIpYWgoZjQwQ8dRTAXFsyedjNjZGTEyUyGRSzMy4k9yWlmBrCx591J22lki4bXODgaaORERERERERL4YCo/kC7a56bqEVlfd5FE+D6mUe67RcL1DhYIryz57Fs6dazIaBfT7hrU1j91dn0TCEgTQ6xne8NQHsOeWaeRnefy+97C14QHu73heTK/nE0UeCwshY2MhuZzh9OkClYorwvZ9dwJboQB3332wTmvdY7ncbfiSRERERERERF4nFB7JFyyKYGHBhTbJpPsJAtcvNDHhAp0XXoCNDahW+8TxCN9PY60LmWZnI2ZmYkqlmGGlzVuf+Fkw8MKf+25eWM2QSLjT1BIJdyJbtQqTkyHz8xGJxIAzZ8pEkU+t5iadqlW3Tc5aV5a9r9dzAZSIiIiIiIiIvHoKj+SGDYdua1oUuU4hYw6CG89zBdljY+42DN1jntcmlzOkUjHZrKFcjmm3Y7JZS69nuPt3/iPJXovmg4/QfvRteOcti4sxUWRIJNxUU69n6HQ8hsMe9XqeCxdybG+7bWqeB1NTrnepVDoo7QYXHOXzt+/7EhEREREREXk9UHgkN6xSccFRELhOIXDTPuWy6xWq1w9OV3Ml1X2GwwG5XIowtHiexfchjg07Oz7pyxeY/9gHsSmf3z79fbQu+ESRIY73T2iztNuwve3R7cY0m5DNlmg0DMOh6zYqFmFmxm1PU7eRiIiIiIiIyM2n8EhumLVuymd/K5i17mdfFLkJoHIZnnwShsMGYRhgLQwGHplMTLdrGAzAM5a3/clP4JuY+ru+ibXEcd5495CLFw07Ox6tlkcqZTEGdnY84njI0lKOQiFJPu+KsOfm3Alvvn97vg8RERERERGRO4HCI3lVdnfdJFIYukmkfca4YGdra8DKSsxwmGZhIeTcuYDh0CedhkrFcP/Ghyicf5pmeoyNr3svxedjjhyJGY0iMhlLFLleJGPguedGNJuWTqdIHLsJo+lpOHXKvefW1u35DkRERERERETuBAqP5FVptdwUkrUvXUpdq/UYG/M4dSqkVIrZ2/NZWoo4cWJEc3vAuz/9k4wS8OSXfzvj2SJzczGplNsOl067rWqjkWF6OqbXC8nlShw75rG46MKjbvfWf2YRERERERGRO5HCI3lVrHW9RoOBu97ZgfV1V6ANA4bDIfl8wPh4yHBorpycFlMsWk7+f79MulllfeoNDP/MV3P//SGZzMHes17PbVWbn4+I4z7GlMhm0ywtuWBJRERERERERG4dhUdywzY3YW/PBUaXL7vTzaanXbn1Cy+4U9aGQ0in64RhwM6OTz4f0+sZ2m04fz7A21jn0T/8FXoR/P7bvo97JlwQFceuMwng4kWfnR2Pe+4Z0u/HhGGO+XnD9LR7bb9/e78HERERERERkTuJwiO5YaORO+Gs33enm01NwdiY20Lmea4o2/cHWNsmm51gbCyi34d63SOZtKTTMV/99L8h5Y145vi7yL7lFAsLI/7oj5KcP++TyViyWcvWlsf4eMzUVIsoKjM2luDBByGfd9vlREREREREROTWUXgkN6TXc9NBxrigaL8kezCAs2fdbTIJq6sNxsZS7O25wGhvL0G7bRgOYXHtcaae/ShRLsP5r/kOxsdhY8OnWvUYH48YH7fU6x5bWwHd7oiPf7wEFOl0oNGAtTX3noWCOo9EREREREREbhWFR3JDnnjChUap1EHPUa3muo5WV90U0vnzfc6fh7m5NMOhAQwTEzFBYEkn4Gv+509ggLNf9m00EpP4fctg4JFKWcCQzVri2PLII0PS6T5/6S+N8wd/4HHsGBw7BsePu/eNY6jXb8vXICIiIiIiInLH8W73AuS1wVq4917IZK59bGwMlpbgDW+AKGozNmYpFCCft1hrabdhczPgTZu/xWRjhe74HKtf9k0kEm56KY5hYiIiDMH33esnJ4ekUgkymQzWwqlTKsoWERERERERuV00eSSvaGsLtrdhfNwVYjcabuIojt1jAJubfS5csMzN+YShpVyOSaWg2zXQ6fHY4z+HMfDEl38n6WKCiaQlk7Ekk5bRyAVHGxse29s+Ydhnfn6CbtcQx7f3s4uIiIiIiIjc6RQeySva2nKTP+Pj7jYM3fa1RAImJ6FSgY99rE0UGcrlmO1tH9+3gAuPvmrtlyhFNWp330f1oS/n9OKIlRWPwcBQKMSMRh7lcky/b0gmu9x9d5JMJkWr5TqWNjfdNrVe72BNxtymL0NERERERETkDqPwSG7I+Lj7SSbB9+GFF1yY40qyB5w7FzIcZtjeDmm3DZubPmDINHZ468X/gpezrHzT38J4hr09n60tw+xsjOe5v7O5GZDPx8QxpFLjLCzA9LR7r37fbY3bn3IC17+0f/LaaHRbvhIRERERERGRO4I6j+RlPfssfOQjsLLipo2unvbZ2oIogmIRms0Ovu8zPx9x8mREPm8JAsv8fMjXXfppknbI5pk/xaXifTSbhnrdkExCoWDpdFzQtLtryOe7DAZ5qtUEnQ489ZSbOspm3Xu32y5I6vfdaWvttvsJAjcJJSIiIiIiIiI3nyaP5GU1m3DkiJsAKhbdNjVr3U8cw/w8FAojdnd7eF6GatXj7NkE7bahWIS7R2e5b+X3iNNJPvXm72R7221Vm501FAqu62gwMHQ6hsXFiOPHLblcnnvugbvucqe5nT3rirpHI1fOncvd7m9FRERERERE5M6i8EheUhS5gCifd1vT0mlYX3cTP52O22rWbsNHP9pmdzeg0fBIJiGfj0kmYbcCx3/9pxkODc+ceTfb/hypBORyMeVyRBBAvW6uvIelVOrR7U5Qq/m0WvDJT8Jg4LatlcuwsXG7vxERERERERGRO5O2rclL2t52AVJwVbwYhjA1BYuLbgppayvk0qUe+XxAFBnm50dEkaXR8Fm88CfMbj5JN1Xk2be8F4CJiZiTJ0OKRUsuFzMcGjwPisURk5NgbY7xcZibc1NG99zjpo5Uji0iIiIiIiJy+2jySF6Ste4ktVQKdnddmLS56a5HI3j+eZie7rC2FpDLGTodj7W1JJlMjB+HfM25f0syCX/8yF/j6OkMiUTE3JwllbJXSrEhlbIMBrC5GVMsTmCMR7HoOo7i2L1/p3O7vwkRERERERGRO5vCI/mcTseVUe/uui1q4IKcy5ehUnGBTybjTjnrdGKq1R7pdALPg2zWTRPde29I9gMfIF3ZYDu9xMcXvpG/emxIreZhjGV318PzoFSy9PuGSiXG8xIEQZbFRbcV7uJF17HU79/e70NEREREREREFB7JVep18DxYXXW38/MwPu6Co7Ext13N991z5XKfu+4a0GgEhKElDEeAR3+nw1s/9QsYz7L5nu9kNmsol2MuX/ap132SSTh6NKRUslSrsLoa/v/s3XmQHeV97/93d599m33TjNbRgjYQILaYLcZgm2CDcX4UzuI4+Gap5FacqqQqt+JK4kq5nKVcWVzx/aXsa8rlhIB/sWPHcQy+BAcMXjFGgJCERtJImtGMZl/OmbP06e7n98eDNhC2MAxnNPN5VZ3SnD59up8emVTpk+/3+9DZ2UQi4dDcDIODdih2PG4HZmtAtoiIiIiIiEhjKTyScxQKNihavRq6umB62oY4iYStOEqlIIoML77o43lp4nGXeh2Gh2M0NYVc+91/JlMvMr35cipXXs3UUx7HjnmMjHikUoaOjohKxaVahZMnI8rlDKtXp4jHbVCUzdrQavVqu57xcVuJFIY2yBIRERERERGRt5YGZstp8/M2rAnDM8cmJuyuZz09dnB1UxOUyxWiKGL9enBdw/w8+D40F4fZuvffcWMOg3f9FjiQSES0tkYYA9msYePGkA0bQpqaIlw3oLs7S3+/DY3m521V09l83+62tn69baETERERERERkbeWKo/ktPl5O9OotdVWGkWRnYOUTkMuZz/PZg3z8/NkMik8D8plF2PsTmo3//CzpLw6w5e/k4NsZvY5hyBwGB/3yOUi+vpC0umIoSGXl14KKZXytLYmiMdtYFWr2aCoUrEtdGB3ePO8c3d9ExEREREREZG3jv5JLoANioyxbWv1uq0ymp+HkRHbtpbJ2GHWJ05UefZZh1LJ5ciRGGNjDum04ZLqc2wYfBI/meLY7R8kEUS0t0NnZ0Qyacjl7DUHBz1KJYdqNSKfz5HN2oAokbCfJ5P2frmcDY0yGfuZiIiIiIiIiDSGwqMVbGzMVvmAbVdbWLCBTb1ujxljj83P2/a1kRH49rerfPe7GbJZl9HRiJkZh7aWkOuf/t+4nuGFK+4hau8gNunguoYwhNFRl1QqolCImJjwMKZKX18z5XKM3l7o74cXX7TzlGo1e++WFlvxJCIiIiIiIiKNpZlHK1itBm1tdkB1RwdccYWdaXRKvW7PaWqCyy6D/v4aqVSF9nZ429tq7N7tk8sZrp3/L9rGXqKcauWJ1fcSBA75fITrOmSzES0thksuCUmlYHLS4DgemzfnaG2FdetsSOR59p5DQ1Ctvnr2kYiIiIiIiIg0hiqPVpgosi+wlUXxuG0LSyTsz6dMT8PevTA8bIdl+z4MDpYZG0vS1BTR3R3adrLQsPOp+wlDh/233IeXz9DSUiMeN4yOOngeLCw4VKsO8/MO09N1Nm9uYXDQpViEqSlb3TQ9baugUikbKCWTjfjtiIiIiIiIiMgrKTxaYUZGbDWR49jXqYqfVxoagslJaG62c5Cmp+sUi2Xy+SzJZPRyVZLDZWOPkZ45yVB+DeNX3YZ73DAy4jE87FKvO3R2RvT1RcRihsOHQ3w/Q1tbhokJ6Oqyg7Adx842iiL7Z0fHW/s7EREREREREZHXpvBohTHGtqm9cp6QMXZwda0GJ07A6KgdWt3XB+UyDAwsUCrFcBzDiRMxOjoMyXjAdQcfwETw3S2/RDrpAOB5hp4ew9q1Ac3NEeAQj0eA4W1vy9HZ6TAwYCudZmfPBEi1Gqxdq1lHIiIiIiIiIkuJwiNhZsZWJKVSto3s+edtG9u6dbbqaGIi4OTJCul0glwuwhjYurVO7sc/oLs0iN/RzsCmd3C5B6mUIWD1NmoAACAASURBVJ+Hej3C8wzT0y6FQsTBg3Xq9XZmZxOMjtqAqrXV3jOVsj8fPmyrkRyn0b8RERERERERETlF4ZFQqdiQqKvLto1NT8PmzfbY88/DzEwVY6BScfF9e/6hAY87Hn0QL2Z47vJ7qIYJTpwIcF3wfYfW1pCpKZdk0hBFdWq1JBs2ZGhrs5VMngdXXmkrjxYW4ORJDcoWERERERERWYoUHq1QxtgQp1y2YZHnnan4iSI7JHtuDubmIubnizhOnIkJF2OgszNiy8JzdIztp54p8NLWdxMbMoShS6Fg8DzbAjcw4LFqVQhEZDItGONy/Li9x6mKo1gMNm6E48dh61Z7TERERERERESWDoVHK8jsrN01DWBsDI4dg3rd7mzW02Orjs5mDIyOVpidddm8GQYHIZ83bN4ccfm3H8Bz4fDP3cVYMUet5hCPhy/v2mYol13SaWhvX6C7u0A6nSKZtPfMZu1co3rdhkyOYyuOCoW3/nciIiIiIiIiIj+ZwqMVpFi0u6elUnbOUWcntLTYY6dEkQ2NoggWFgzDwxWy2RjpdMTMjEM87rApeJHC/meoJTLs3f4+Jg565PMGY2zLWqViv9/eXqdQcMnnm5ietuFUPG7Do3zehln5vD0mIiIiIiIiIkuTJsysMJmMrT6q18//+fi4rQY6fhyOHKkQBBGO4zI761KruRQKAduefpBazeHA1juYqDWTThvWrg1pagLXNczOei/PUarS2dmO53k0NcGWLTasGh09M9uouVlzjkRERERERESWMlUerUBTU3bGUew8f/vG2IAnmYR4fBbHSeJ5hiCAatUhdXKYzPe/w0IQ56vZeykd8ZiedigWHdrbDbmcYf36gJ6eBbq6UuzblyGTsaFVLmerjbJZe696XcGRiIiIiIiIyFKn8GiFKhTsLmdnm5mxs5DicfD9GpVKHdfNEASGet2QyUS8c+xfyKYjxnbdRqK3jf6WOq4bY9WqkL6+iGzW0NISkEpBodBOEMAVV9iKpkrFtszlcratbe3a8wdYIiIiIiIiIrJ06J/uK8j8PNRqdkB1rWarjJqabJBTKtmAp1az748cKTM6miQIHObnbetacnaCvkOPEmRcDlx9D/F5WLPGUK0aVq2KAIcwtMFTItHG9HTs9CDsAwegvR1aW21gFASN/m2IiIiIiIiIyIVQ09AKUi7bdrTubttG1tpq/yyXYXLShkv1OnR0BDQ1zdHT4xKLgTEu+XzIO04+RORHDKy9mccPradadUgkDPG4IQwdfN8hna6Ry6V58cU8hw5BV5e9t+fBunXQ32/DqULhzKDs+XkbZImIiIiIiIjI0qPKoxUmmbQzh17ZsuY4dhZSvQ5TU2WamyEI7M5pzc2GheESd018DTcBwa/8P2yarrNrly0fmplxiCKHlpaI9nafbds6iSKHm26y167VXr2O5mZ7T4CJCTtnSfOPRERERERERJYehUfLXLkM1ar9OQxf/XkU2XNKJRsodXREFAqzNDcnOH4choc9MpmIaw58maRT41jv1cy0baIzFuH7DkePeiwsuHR2RqRSFZqaWhkaSrzmeo4ds+s4FRyd0tLyJj60iIiIiIiIiLxpFB4tc9PTZ3ZWy+Ug8Ypcp1KxwVE+b4dZx+MVksmAajXJ4GCMWg3qs2U27/l3gsDh+d2/TFvZVhkdPeoyMBCjoyMkl/Npa4tRLheoVmH1antdsNVMp5w9KHtszH4WRa8Ok0RERERERERkaVB4tAI0NdnZRvW6DZJeKQztyxhDsVikqSlOtQrT0w6FQsTlR75OzhSZWLMTLttGLmdwHKhUHFpbQ665psb0tM+6dV2cPOmeDqLm5+315+bA92172tnVT6WSnYnU3q6WNREREREREZGlSuHRMjQzc2am0amWtZ/E923AlE77lEo+rhtnaMjh4ME4HU1lrjr4r7gOfLv/V2hNQDYbMT7uMj/vUChAqRRQreaYmkoxPw+bNsGqVWeuPT1tB2THYmf+PCWdPn+gJSIiIiIiIiJLg+o9lqFy+cxuaqtW2YDmp4nFYGGhSKUS49gxl2efTTIzA1eOPkxTMMVU+0amNl/FLbf4RBEcP+4xN+cSRREDAx6elyWKbCXR6tVnrjs6asOs1lbo7Dx3ULaIiIiIiIiILH2qPFqmkkkbIF2osbE6w8M1jh/PsLDgMDjo4UQBNx19iHgcnlj3S6QzdmaSrWoytLSEVKsBbW1J1q5NUSjYdrWzK4mGhqCtDdasUWuaiIiIiIiIyMVI4dEKYIydOzQ7C0FgX7OzNghKp+3A6n37yriuw4kTLo5j291u8r9Fe22U+fZV/Kj559mdD3n22Tjf+16MiQmPvr4AYyI2bMjS1ATd3VAs2nuOjUGtZl/r1ik4EhEREREREblY6Z/0K0C9DpOTZwZjz83ZkCcIbKiTyYSMj1eYnk4wNRWjuTkiETe8Z/oBEgnD87vupaPLYfXqCM8zFAoRbW0hbW0++XyS/v4U2aydm3RKpQItLdDTY6ugREREREREROTipMqjFSIWs+1j+bydidTRYV9TU/D971cYGHCZmEgQRYYggHUjP6SvegRWt7Fn1TsJajA56TI3BydPegQBlEoRTU05ZmbsPZJJu4NasWirmRIJBUciIiIiIiIiFzuFRyvQ7KwNkKIIXnrJMDRUJp328H3IZkMcx+FdE/9MMmEwH7iTYDJBS4uhrS0in4+YnIRSydDREaOnJ0FHBxw/bodjJxI2QMpkIB5/9b2np20lFNj7i4iIiIiIiMjSpvBohajXzwyyNsa2mK1dC08/XWN+PmJ0NEWt5tLTE7C2tI8tC88R70kz/Y5foPR/HDZsqJPJQLHoMj7uUavVyecL9PY6rFplW+A2bPjp65idtTuueZ6dt3T2cG0RERERERERWXoUHi0zpRL4/quPz8xAV5etDDrb9HQJYzxc19DTE9HZabjqsS/iujBx4y8wMJSnXHbwPMPcnMPcHJTLhpYWj0svTdLd/frXWCjYNjoRERERERERWfr0T/hlZm7OtoylUvb9qZ3WAFpbz51B5Ps+c3M1JiZyBIFDNmtomh9m3eCThJ7H4LV3MTZmS4NGRmIkEoaFBY943Ofqq3Ns2eIAturolJER274Whvb9qflHpyqMggAcZzF/AyIiIiIiIiLyZlJ4tAzlcueGNXNztlXsFGNgfh6CYJ7h4TgnTnhkMhGOY9jyzJcxkeHwJe8gvaad4ACkUublgdsRhULAmjURvb2p8967VrMBVXe3DYlc1w7pPsVx1KomIiIiIiIicjFReLSMTE1BpQItLece9zzIZs+8DwKYmAhx3RKzsy14HmzeHOKfnGPn4MN4LhzY/Yv4z8YYG/NeDoAM3d2G4eEa3d1teN5rlw95nq1yct1FelARERERERERecsoPFpGqlVob7dta+dTKsHkpB1avXfvAidOZBga8kgkIJMxbNn/VVKOz+E113HMW09qxiGdjnBdh1wuAgISiTjt7elzwigRERERERERWb4UHi0z8bgNiObn7ft6HU6ehFWr7O5mxsD4uGH//oCTJ1PMzrp0d4cExQqXD3yFugOPdP4yxaJHW1vImjUhx455GOMwNGRoayvQ3OycnqkkIiIiIiIiIsubwqNlqF63bWO5nP3ZdWH9eju8uliEIKjR1BRQLMbYsCHkPe+p0vedb5AzRaZ6t1G7ZBuX9AVcdllAS0tEsegQhhHptMuuXWl8HyYm7FDuKILhYSiX7S5vs7PnzjgSERERERERkYubwqNlJgzty/Psa3oaYjEbIs3N2cqjF16oMDaWoFy2AVNHa8D673yZRMLw0tX3kEw5pNOGKII9exIcPerhODW2bcsxN+dSLkNXl22PCwJIJOyQbM+zx9vbNe9IREREREREZLlQeLQM1Gq26icIbMua49j2tTC07WtdXfaceBwWFuocOWKoVmN4np1plHrqSZLTY0zn+/i/tRsJjp/ZDm121iWVikinYceODF1d9pqXXGIDoiCwlUaeZ1vjEokG/iJERERERERE5E2n+pBlYGrKtoslk7bKqL2d0zOJ7E5pdpj2/DwMDpYJQ8hmIy65xCeVNKx78v8jMvBE3z1MTseIxw2trQEtLSFzc1Ct1tmwIUtTk0s+b0OosyuLpqZsZZPz2huwiYiIiIiIiMhFSuHRMtHSAoWCnUE0NWVnEk1N2c98H154AfbtMzz6aMjERJzZWQ/fd+gZ/jFtEwMsJFr4Ufe7aWszrF0bsn17BLjE44b+/ogrr8zQ1HT+eUaViq1uisff0kcWERERERERkbeA2taWkbk5G+AcOnQm5InFYN8+GBqC5uYqXV11JibiJJMR5bLDLXsfZKHi8mjXLzKzkKSpydDTE9LSYl4OhWps3pwlHnfPqSwql+38pDC077X7moiIiIiIiMjypPBomclmbaizdaudP1SpwNGjtiLp2LEyo6MJRkc9tmyps7pyiG3Fp4myKV7a8R56cwHd3dDWFnH0qMfYGDQ11UmlssRi0NRk73Fqh7Vs9sw9RURERERERGR5Uni0TExP2/a0atW+d11bibRnD4yMwIkTdY4cgdlZD9c1rFoVcvl/fRHPNXx/1R2MV5toShrCMGRuziUWc+joKLN5c54o8kgmbVVTrXbm+r299ud6vTHPLCIiIiIiIiKLT+HRMlGv27lHU1PQ1mZ3QVtYsJ+tXg1hWKFcDujudikUHK7qG2Hn6LdwYi7fW3cPsciwfn1IFDkkk+C6IYkEhGGe+Xm7m5qtXoJM5kyIVKvZ4yIiIiIiIiKyPGlg9jISi9mWtfFxePpp2LvXDs4uFg2+v0C5nMDzHBIJQ/e3/o0ojHim8x0Usx0kEtDeHuF5sHp1wMxMCDRRrXp0dtpgCs6tOAIYHT2zy5uIiIiIiIiILD/6J/8yMzUFhw/D2rXQ3Q0bNsD8fJVi0WdsLMvcHCyMFOna+zBRBA+3foBk0gAO8Th0dUWsWRMwOOiyc2eGzk5bWWQMnDx5/nt2dNhQSURERERERESWH/2Tf5kxBgoF2L4dLr/cVgwdOLDAkSNpJiZckknDnfWvkPEqjG/YzWTrJvJ5w+rVIdPTLvG44bnnIJfLkkyeyRajyO6w1tdn38/Pw9iYbY8TERERERERkeVrUcMjx3He5TjOS47jHHIc53+d5/Nfdhzn+Zdf33Uc57LFXM9KNDMTMDtbI5u1u68VkhWuPfZlHMdh8IZ7aGkJaW+P6O0NAejtDUilQq65JnveVrRUyv55ag5SR4cdpC0iIiIiIiIiy9Oita05juMBnwZuBYaBpx3H+ZoxZt9Zpw0CNxljZhzHeTfwGeCaxVrTcnf0qN1hLQztAO16HQ4fLrN/fxKIE48bLh9/jFx9hqnOTRzvvJy5IZfpaY8giKhUHCoVn+7uPIVCjNFRu4Nbc/P575fP23lHIiIiIiIiIrJ8LebMo6uBQ8aYIwCO4zwE3AmcDo+MMd896/zvA32LuJ5lb3jYhjlzc7BnDwwNGX7wgxqFgkdPj0+plGLDD79BrebwaMsv8uyeBGNjLqtWOcRiDrGYwXUjVq3KE4/blrQgsNcNAjsce3jY3isMwXEa+7wiIiIiIiIisvgWMzzqBYbOej/MT64q+jDw8CKuZ0VoaYH2dujpgebmKqlUQLkc4/DhOO7gIJ1j+/BTGSZ3vY0W3xCLhWzbFpBMGur1Olu3ZmlpiVOp2Mol17UVRk1NdgB3f7+9j+vaNjgRERERERERWd4WMzw6X12KOe+JjvPz2PDo+tf4/DeB3wRYs2bNm7W+ZWF2FioV+6fv28DHcWBmBo4cKVOteoQheJ7h+on/IObB8Z23EC9kqI+al8OmiHodZmYMlUozk5NQrdpXLmfvYwxs3Kg2NREREREREZGVZjEHZg8Dq8963weMvPIkx3EuBf4PcKcxZup8FzLGfMYYs9sYs7ujo2NRFnuxKpft7mqhnXfNyIjdBe3AgYD9+wOSSc+2oJUDrpn+v7guLNz6btJpSCQM6bRhYcHF92vkclna2uKsXm13VQsCOxg7lbKBlIIjERERERERkZVnMcOjp4FNjuOsdxwnAdwLfO3sExzHWQP8G/CrxpiDi7iWZa1YtFVCw8MwOGirhKanfRYWHHzfYXrapXPvk+TNPLM9m6j39xMEYIyLMRBFIbOzDm1tGTzvzHWNgTVrYPXq1763iIiIiIiIiCxvi9a2ZowJHMf5n8A3AQ+43xjzouM4v/3y5/8I/CnQBvxvx05fDowxuxdrTcvRxIRtUQsCiCK7M5rnGaanS7S3Q2urIQwjbv7Of5BIGA7vvJ0DB2L4vsPMjEtbW8D0tKG5OcuOHQkSCRtGVSqNfjIRERERERERWQoWc+YRxphvAN94xbF/POvn/wH8j8Vcw3Ln+9DaaiuPHAcOHYJazScMIZ+Pk8lE5GeGWTu1h1osxd6+dzA/4+I4tiqpuzugVgvZuDFLfz8MDEA2a6+Xz9vqo5EROyBbRERERERERFaeRQ2P5K3huhCLQTxuK4/i8Qo9PT5zcy5NTRHJr34DB3iu6xYWyJBKgetGZDJQLIYkElnSabt1mm1ns9fr6LDvfR82bWrsM4qIiIiIiIhIY6ieZBk4ehQOH4bpafD9kPn5KplMnCCAwYOw7cg3icUMP15zO8mkQ0tLRLHo4HmwYUOVG29MY4xtgfN9O3C7WrXDsmdnbUVTItHopxQRERERERGRRlB4tAxMTdlKoSCAoaEag4Nxhoc9xsc92vZ9n2xthpHUep7xL2VoyGN01CGKHDo7a7S2ZkgkkkxMQL0OLS1nWuFs6xu0tzf6CUVERERERESkUdS2dhELAjvYenISPA+iyFCt1ti0KWTXrpAf/chh5+H/JBaHFzfdTld3RG+vbVcLgojm5jrNzW2MjNih27WabYFLJiGVglwONmxo9FOKiIiIiIiISCOp8ugiNj1tQx+AdBoSCZ+2Np9166BScUlOj9J99GnKfpwncu+iVnOYnHTxfYdSKcCYFPv3p9i/37ap1Wr2lctpQLaIiIiIiIiIWKo8usiVSnYeUToNrlsjkXAAmJtz6Pjeo4QBHFx3I/m+PO6CYWHBpa2tzuysYcOGHB0dti2trw8uueTMdYOgQQ8kIiIiIiIiIkuKwqOL1MIClMswN2d3WPM8Q7VaxXVjzM6GzM0YbnjxYYyBZ9f9AskkJJMRExMO/f0LFItZNm1KkkrZ4CmZPPf65XJjnktERERERERElhaFRxephQW7C1o8bquPslmfmRnwfY/paZctE98jVZxkPNXL8Y5dFEJobY2YnPQYHnZobc2QTkMU2XlJZ6vX7Y5rLS2NeTYRERERERERWToUHl3ExsfBGDv3KAhqhKFLOm2YnXW5bPA/cYAX1t9Oa5uho8PQ2hoyPe1Sr3usXZtgctIGRfU6rF177rVjMe2yJiIiIiIiIiIKjy5qJ09CWxvMz8P4eI2mJpexMRcmp9g0+j2qMZeZ628lkbDnV6suQRDQ3JymtdVlzRo7IDsMobUVjh2zYZQxtqpJRERERERERER7al3EymVbIRRFPqWSwXUdKhXYcfQRTBTxYuvbiHW1UCq5eJ6hUnHJZEJaWzPMzJzZqQ1sgBRFsGoV9PbC6tWNey4RERERERERWTpUeXSRqtehUrFVQvPzdapVh4UFl8qC4bqTXwcHjl95O+vXB8zOenR2RgRBQGurR6GQYGzMXieKYHbWhlCOw+kqJRERERERERERUOXRRWt21g7KLpVgfLxOMumysOCyeuxZusIRwvZOOt5zGb7v4PsOY2MeMzMRuVyO6WlwXRscjY1BENgQqlBo9FOJiIiIiIiIyFKj8OgiNTAAU1MQhgFQp7vbIRYz/NzE10nEYfiKd5IruAwPeyQShlLJAC6trSlmZ+2spHQaOjth2zbbqtba2uinEhEREREREZGlRm1rF5Fi0b4A5uYgmwXfr7OwAENDHrHSLDsnv02Ucjh++bsIZxzm5lzS6YhaLcBx0pw44TI0ZL+bzaraSERERERERER+MoVHF5FKBTzPhj7NzTZAqlQq5PMO9TrsOP4YsSjg5LrdON2djJ1wmJjwiCK7q1qxmGHNGjsUu78f+vrs9ZLJRj+ZiIiIiIiIiCxVCo8uIsbYoCeXs4OtZ2cjajWfTCbJxDhcO/ofuC4c3P4LpJOGctmjszOkWo1wXdiyJcGmTdDdDWvW2LY1EREREREREZGfRDOPLhKTkzA/byuFAMKQl4MjQyplaB95kY7SMUqJZva1XcfgoMvkpPvyQG3wvAwdHdDUBPm8giMRERERERERuTAKjy4SUQQdHTb4AVhYgMnJgHLZo1h02XnsESJj+GH37cRSMdraDF1dIYmEwfNg/foEa9faVreY6s1ERERERERE5AIpPFrifN8GPrUa1OtQLtvX1JShVPKZnY0xfMywdewposhhb98t5HIRiURELhdRqxlaWuJs2+bR3AyZjN1hTURERERERETkQqgGZYmbnbXBUSJh29bKZXBdmJjw8TxDterRN/EcuWCWyaY+jnr9MBwxMWE4cSJOtVpn164krgulUqOfRkREREREREQuNgqPLgL5vN1drV63lUM/+AEcOhTi+w5jYx53nfw2ngeTl76N7Tsidu2q43kR+/cHpFIRN93UTCoFQWCvIyIiIiIiIiJyodS2toTNz7+6Wmh6Go4fNyQSVUqlGKMnHC6b/jauC0/nbqJSsa1u8Th4XkhPT4583sFx7LFUqjHPIiIiIiIiIiIXJ4VHS1i1aquOCgXbrjY+bl++XycWC6nXHS51X6SdSaYTXeypbadScZifdzlyJMbYmAskqdXs91z9bYuIiIiIiIjI66S2tSXKGLvDWiplQ5+FBRsmTU9DpeLjOAaAG+qPE4/B4LobuPSygK1b6+zeHfLjH0fU61k2bowxOmq/39mpAElEREREREREXh9FCUvU5KRtWYvFbJBUKp0ZnJ1Ol3Fdj/k5lx3jTxCGsLfzRjzPfrdahakph56eJPm8bWPr6ID+fli1qrHPJSIiIiIiIiIXF1UeLVHG2CqhkRFwHBgetgOzx8cDBgZgfDzB6vJLtPknKWVbmVy1jY7InjM1ZfB9j0wmRalkq47WrbPDth2n0U8mIiIiIiIiIhcThUdLULVqX1FkK4YSCZiaspVHQ0M+1aotGNs9/wQAB1fdQK7gsrDgEI/DkSMG183hOA6+D9ks5HIKjkRERERERETk9VPb2hI0MWF3Wjs1n2hw0FYPGQNzcz65nAFjuHbhcWKe4cWuG8lmDZlMRHt7SLXqkMslGBuDgwftsO14vLHPJCIiIiIiIiIXJ1UeLUHFov0zl7OtZpUK9PbC5GRIve4TBHFa547SUx+inCwwULiC2zYGHDvm4fshra1pcrk4xthrbNsGfX2NfSYRERERERERuTgpPFpC5uZgZsYOx+7qsrujnZJMwvh4jZMnPYLA44aJJ3Adw96268kWwPPsvKPRUUM6nTmnXU3BkYiIiIiIiIj8rNS2toTUajbs6e2FfN4eiyJbiTQ6CnNzFRIJh97eiGvLj2Nw2NN6M4WCAWBhwTA2lsTzUvi+/b7a1URERERERETkjVDl0RITi9nZRqeGW09O2h3X8vmIkRGfubksrQvHaZk6QpEs42svpzflMDzsUq1GXHVVkp07HWZmbMtbTH/DIiIiIiIiIvIGqPJoiQmCM7utVat23lG9Dr7vMzvr4jgOqw89RRA47Mn/HG4qRhjaVrd0OiSfT1Mq2e+JiIiIiIiIiLxRqktZYsbGbGiUSNj5R0NDtvIok6mysOBx8qTHxmNPArCv6yayWUNHh2F4GBKJGDMzCSYnoacHCgW705qIiIiIiIiIyM9KlUdLUHu7HXLteZBKQTxu8H2ffN5jbWqU7c4+0s0Jyrt2k8kYwhAmJgyQwvOgrQ26uyEMG/0kIiIiIiIiInKxU+XRElMswsSE3SltdBSOHIGpqTqrV/tUKjF2TT9BFMFA6zWMTGfoToR0dQWAQ3t7nHXrbOjU2mp3aFP7moiIiIiIiIi8EQqPlpgosu1m69bZ9rViEebn6+zbl+T48QS/M/5totDhh/mbcBxIpQy+b/A8j02bEhQK9nu5nA2PgqDRTyQiIiIiIiIiFzOFR0vEzAyMj9sZRakUzM3ZWUdBAJ2dFfr6QrpiY2z9wfP4sRij/dfQlohobo7IZn1yuRy1mt2dLZezIZQxjX4qEREREREREbnYKTxaIup1SKehqclWDE1O2uAonTZUqyG1WoyNJ76D6xiOdu3GK2SIuwbPA9d1MCZGrQa+b4OoVMq+CoVGP5mIiIiIiIiIXMwUHi0hU1O2WqhahQMHYHgYZmfrpFIwMuKybb/dZe3wmhsYH/eIxyNqNYdYLAHEaW6GtWshn4fe3sY+i4iIiIiIiIgsD9ptbQkJQ+jqspVH6bSde5TNhvi+YX64zNrxZ4lw2dfxNubmnJdb0wLK5TS+b0OnMATHafSTiIiIiIiIiMhyocqjJcZxYGEBBgbs/KPRUUM263LJ2JO4JmSs7wpibQWSRfNyS5rD5GSCtjbo77fhUzbb6KcQERERERERkeVC4dESFEWQSEAmA8WiT3e3YfsTT+K6MLDmJo4e9XAch3TaJ5Hw6OmJs20b7NoFntfo1YuIiIiIiIjIcqK2tSXM9yGK6njVCqtHfoTjOpy85DricVi7tk4yGTE7m6JUgphiQBERERERERFZBAqPloh6HWo1KJXs7CKAMAyoVAztB36EEwQMt+9guNJBrQbJpKFeNySTCVatgtbWxq5fRERERERERJYn1assEcWiDZCMsTOLikUYHg45cSJO29GnCEM40HMjiYQBDBMTDplMgkQiRjardjURERERERERWRyqPFpCslm7y1oUweQklEohsaDGjrnvk0waytdeR19fRC4HjlNnzZok7e12PlI8rl3WqEk2nQAAHDJJREFUREREREREROTNp8qjJWB8HCYmbADk+/Z9pQK+H7Gr8jQpqgy3XcKRcg/l/R6+D01NsGFDgmIR8nlYvx5cRYEiIiIiIiIi8iZTeLQEnDhhq42am+HwYRgYgPl5mJkxXDb1bWIxONh3I7OzHpWKQ1NTQBgmOHgwRj5vW9YUHImIiIiIiIjIYlDksAQUi5BMQnu73TUtm4VEwuDXQvonnqFac/hvczOlkkMQgOME+H6SWg0yGVuFpJY1EREREREREVkMqjxaItJpyOVsu9rgIERRne76EE1mhrCpGW99D81OSKnk0tcXkUwmWLsWLr8ctm5t9OpFREREREREZLlS5dESMT8PIyN23tHYGHhexM7wBRwHTnbtpB44HD8e5+RJh3o9ied51Go2cBIRERERERERWSwKj5aIMLTVR+3tp1rQQjaW9mIMDLXtwBjbl7ZhQ41f+qU4a9bYQdktLQ1dtoiIiIiIiIgscwqPloiZGVt5VK3a1rUoithYegEMHMpdShRBNhtRKETMz6ep1aBQaPSqRURERERERGS5U3jUYFFkq44AJiftTmtzc5CpjtFeGSZKJBlv3kil4lKrhYRhkmLRIwzVsiYiIiIiIiIii08DsxtsYsJWG4GtPpqeBt8P6JjZhzEOo23bKFbiVCoOYMjlUoQhdHbC6tV2tzURERERERERkcWiyqMG832o1yEWg4UF+75QCLgqvodE3HCiYwcnTnhMTrrE49DZmSCft8FRWxu4+hsUERERERERkUWkyqMGm5+3rWsA5bINkZLJiN7Jvfi+w3fLV1AFWlp8tm2Dzk6PRAK6uuyAbRERERERERGRxaTwaAmIIhgagrEx+/LnyrSMHcYPXcY6t9AcM5RKkEikSSSgo8O2rdld2UREREREREREFo/CowaKItuyVqnY9rPubjv3KDv+AlHdMBjfRLwpQ1QzZLOGa65J0tEBqZTa1URERERERETkraEIooEmJ2F0FA4fhvFxMAbK5YhVEy9gDBzJ7aSvLwRC0ukY4FIuKzgSERERERERkbeOKo8aaHoaEgnI56G5GVpb4cknA9bP7cV1YLRrO64LsZhh/XqPnTttq1o22+iVi4iIiIiIiMhKofCogYIAWlpsG1oiAdUqVMt11hf3Ehl4JriUzP4Y8XhAW1uq0csVERERERERkRVIDVAN5nnnvu8qDpCKKkzEephLdhNFhq6uGFu2uDQ1NWaNIiIiIiIiIrJyqfJoCajXYWICwhDah58jDB1eTF1KOh3R0+NzzTUZbrgBcjmYn2/0akVERERERERkJVF4tAT4vn0tLMCamb1EEexP7sR1I8ChUFDLmoiIiIiIiIg0htrWloBKBebmYHKiznb/eWIezKzdSWdnwJYtHqtWeT/9IiIiIiIiIiIii0Dh0RIQhvaVXximNZyg5OUZS6+lWoVsNkk83ugVioiIiIiIiMhKpfCowcplqNVgdhaaBveAgYH0TiJckklDb2+STKbRqxQRERERERGRlUrhUYNVKmAMVKuwfu45HBcGm3bS1lano8MlFvNw9bckIiIiIiIiIg2iWKKBTs06KpXswOye8ecJQ3jOuYyFBfC8OB0dUCg0eqUiIiIiIiIislIpPGqgsTGYmrI/xyuzdJePEjgJqus30tcX0N2dIpGwIZOIiIiIiIiISCPEGr2AlSwMobXVzjzKHtlDFMDB2BaimEcs5pBMxqjXIR6HbLbRqxURERERERGRlUiVRw00NwcvvACTk7Ch+CyuC0fyO+noCFi3Lk5XF6RSkMmgHddEREREREREpCFUedRAMzM2ODIGNhZfwBjYG7uUaMGlWk0yOwvFIjhOo1cqIiIiIiIiIiuVKo8aaHQURkZg6LDP2oV9RBG8lNpJb6/LunUxenpgzRpoamr0SkVERERERERkpVJ41CBRZIdlVyrQOr6fWOhzPLYek8/R1xcjlYJYzL5OGRuzO7O5+lsTERERERERkbeI2tYa5Mc/hvFxGyJtq/8Yz4Px3u1cd12Zq69upVq17WxnC0Po6bEzkERERERERERE3gqqYWmQchlaWmwV0bbaHgBm1+5g61bw/Ti+D4UCVKtnXmGo+UciIiIiIiIi8tZS5VEDBQEMH4+4xH8exzWMdF7C1myWuTnwPKjVzgzUPkW7romIiIiIiIjIW0nhUYPMzdlh2YWZYzQxx2yinblMF+VygnodOjogl4PVq6G9vdGrFREREREREZGVSuFRg0SRDZAuK+/BceB4y056+zx6exOk09DcDJ2dtrVNRERERERERKRRNPOogWZn4ZKaDY8Gm7YTiyXxfbsDWywG6bRtXxMRERERERERaRSFRw12afQsrgsnu3fS25tkYcHOOfI8SCYbvToRERERERERWekUHjVIsQgFf5LucJiKk+Zkrp9iMcHkJGSzsHEj5PONXqWIiIiIiIiIrHSaedQgAwOwufIcGDgQ24ZxU8zM2Iqjvj47LFtEREREREREpNEUHjVIrQY7oz3gwKHcTrq7Y7S2Qn8/XH89uKoJExEREREREZElQBFFgxw+DP3zewhD+F5lF4cPJ5iagkxGQ7JFREREREREZOlQeNQgc6NlNpsDGMdlpHU7Gzc67NwJl1zS6JWJiIiIiIiIiJyxqOGR4zjvchznJcdxDjmO87/O87njOM6nXv78ecdxrljM9SwlfbN7cQg55G2mfXWOa66BW26B7u5Gr0xERERERERE5IxFC48cx/GATwPvBrYBH3AcZ9srTns3sOnl128C/+9irWepaRveQxQ5PBPuolRKEARqVxMRERERERGRpWcxK4+uBg4ZY44YY3zgIeDOV5xzJ/AFY30faHYcp2cR17RkbPf3AIbxVdv5tV9zuPlmyOcbvSoRERERERERkXMt5m5rvcDQWe+HgWsu4JxeYHQR19V4YcjGyguAw3Ps4rI6OE6jFyUiIiIiIrK81et1hoeHqVarjV6KSMOkUin6+vqIx+MX/J3FDI/OF4eYn+EcHMf5TWxbG2vWrHnjK2u0oSGSrs9QtIpVO1dxySXQ2troRYmIiIiIiCxvw8PD5PN51q1bh6P/D76sQMYYpqamGB4eZv369Rf8vcUMj4aB1We97wNGfoZzMMZ8BvgMwO7du18VLl101q3jqoUn2D06yvvW6/9giYiIiIiIvBWq1aqCI1nRHMehra2NiYmJ1/W9xZx59DSwyXGc9Y7jJIB7ga+94pyvAR98ede1a4E5Y8zyblk7JZXCeR0pn4iIiIiIiLxxCo5kpftZ/htYtMojY0zgOM7/BL4JeMD9xpgXHcf57Zc//0fgG8DtwCGgDPz6Yq1HRERERERERERev8VsW8MY8w1sQHT2sX8862cD/O5irkFERERERERERH52i9m2JiIiIiIiIiKv4DgOv/qrv3r6fRAEdHR0cMcddyzqfT3PY9euXezYsYP3vOc9zM7Onv5seHiYO++8k02bNtHf389HPvIRfN8//fnJkye599576e/vZ9u2bdx+++0cPHjwVfeoVCrcdNNNhGF4+thXvvIVHMfhwIEDp48dPXqUHTt2nPPdj33sY3zyk598Xfd7vR555BG2bNnCxo0b+cu//MtzPnvppZfYtWvX6VehUODv/u7vTn/+93//9+zYsYPt27efc3yx1nMh59x33310dnae87v0fZ8bb7yRIAjelDWCwiMRERERERGRt1Q2m2Xv3r1UKhUAHn30UXp7exf9vul0mj179rB3715aW1v59Kc/DdgduO6++27uuusuBgYGOHjwIKVSiY9+9KOnP3/f+97HzTffzOHDh9m3bx+f+MQnGBsbe9U97r//fu6++248zzt97MEHH+T666/noYceuqB1vp77vR5hGPK7v/u7PPzww+zbt48HH3yQffv2nf58y5Yt7Nmzhz179vDMM8+QyWR43/veB8DevXv57Gc/yw9/+EOee+45vv71rzMwMPCa93r88cf50Ic+9IbWcyHnfOhDH+KRRx455zuJRIJbbrmFL37xixf6q/mpFB6JiIiIiIiIvMXe/e5385//+Z+ADVc+8IEPnP7sn//5n7n66qvZtWsXv/Vbv3W6iueuu+7iyiuvZPv27XzmM58BbAXP1q1b+Y3f+A22b9/ObbfddjqU+kmuu+46Tpw4AcC3vvUtUqkUv/7rdgyx53n87d/+Lffffz/lcpn//u//Jh6P89u//dunv79r1y5uuOGGV133gQce4M477zz9vlQq8Z3vfIfPfe5zFxwevZ77vR4//OEP2bhxIxs2bCCRSHDvvffy7//+7+c997HHHqO/v5+1a9cCsH//fq699loymQyxWIybbrqJr3zlK4u+np92zo033khra+urrn3XXXfxwAMPvKH1nW1RZx6JiIiIiIiILEm7dy/OdX/0ows67d577+XP//zPueOOO3j++ee57777ePLJJ9m/fz9f/OIX+c53vkM8Hud3fud3eOCBB/jgBz/I/fffT2trK5VKhauuuor3v//9AAwMDPDggw/y2c9+lnvuuYcvf/nL/Mqv/Mpr3jsMQx577DE+/OEPA/Diiy9y5ZVXnnNOoVBgzZo1HDp0iL17977q8/PxfZ8jR46wbt2608e++tWv8q53vYvNmzfT2trKj3/8Y6644oqfeJ0LvR/ADTfcQLFYfNXxT37yk7zjHe8459iJEydYvXr16fd9fX384Ac/OO91H3rooXMCvR07dvDRj36Uqakp0uk03/jGN9h9nv8NXXPNNdRqNUqlEtPT0+zatQuAv/qrv+Kd73zn617P61nz2Xbs2MHTTz/9U8+7UAqPRERERERERN5il156KUePHuXBBx/k9ttvP338scce45lnnuGqq64C7Ayhzs5OAD71qU+drnYZGhpiYGCA7u5u1q9ffzqkuPLKKzl69Oh571mpVNi1axdHjx7lyiuv5NZbbwVsm9j5tm9/reOvZXJykubm5nOOPfjgg/z+7/8+YAOzBx98kCuuuOI1r/t6t5F/8sknL/hcu2fXT7+f7/t87Wtf4y/+4i9OH9u6dSt/9Ed/xK233koul+Oyyy4jFnt1pHIq2Hn88cf5/Oc/z+c///k3tJ4LXfMreZ5HIpGgWCySz+d/6vk/jcIjERERERERWXkusEJoMb33ve/lD//wD3n88ceZmpoCbFjwa7/2a+cEF2DDiP/6r//ie9/7HplMhptvvplqtQpAMpk8fZ7nea/ZtnZq5tHc3Bx33HEHn/70p/m93/s9tm/fzpe//OVzzp2fn2doaIj+/n7Gx8f50pe+9FOfJ51On14TwNTUFN/61rfYu3cvjuMQhiGO4/DXf/3XtLW1MTMzc873p6enWb9+PX19fRd0P3h9lUd9fX0MDQ2dfj88PMyqVate9d2HH36YK664gq6urnOOf/jDHz5drfXHf/zH9PX1XdAaX8uFrOdC13w+tVqNVCr1htZ4imYeiYiIiIiIiDTAfffdx5/+6Z+yc+fO08duueUWvvSlLzE+Pg7YQOXYsWPMzc3R0tJCJpPhwIEDfP/73/+Z79vU1MSnPvUpPvnJT1Kv17nlllsol8t84QtfAGxb2x/8wR/woQ99iEwmw9vf/nZqtRqf/exnT1/j6aef5oknnjjnui0tLYRheDpA+tKXvsQHP/hBjh07xtGjRxkaGmL9+vU89dRT5HI5enp6eOyxx04/5yOPPML1119/wfcDW3l0asj12a9XBkcAV111FQMDAwwODuL7Pg899BDvfe97X3XeK2dQnXLq7+T48eP827/923nPOeXmm2/+iVVHF7qeC13zK01NTdHR0UE8Hv+p514IhUciIiIiIiIiDdDX18dHPvKRc45t27aNj3/849x2221ceuml3HrrrYyOjvKud72LIAi49NJL+ZM/+ROuvfbaN3Tvyy+/nMsuu4yHHnoIx3H4yle+wr/+67+yadMmNm/eTCqV4hOf+ATA6c8fffRR+vv72b59Ox/72MfOWwFz22238dRTTwE2hDm1W9kp73//+/mXf/kXAL7whS/w8Y9/nF27dvH2t7+dP/uzP6O/v/913e/1iMVi/MM//APvfOc72bp1K/fccw/bt28H4Pbbb2dkZIRyucyjjz7K3Xff/arvv//972fbtm285z3v4dOf/jQtLS2vOueaa65h165dr3p985vf/JnW85POAfjABz7Addddx0svvURfXx+f+9znADt0/Ox2yDfKOV//3FK2e/du86MlUF4oIiIiIiIiF5f9+/ezdevWRi9jWXv22Wf5m7/5G/7pn/6p0UtZ0e6++27+4i/+gi1btpz38/P9t+A4zjPGmPNOklflkYiIiIiIiIi8KS6//HJ+/ud/njAMG72UFcv3fe66667XDI5+FhqYLSIiIiIiIiJvmvvuu6/RS1jREokEH/zgB9/Ua6rySEREREREREREXpPCIxEREREREREReU0Kj0RERERERGTFuNg2jRJ5s/0s/w0oPBIREREREZEVIZVKMTU1pQBJVixjDFNTU6RSqdf1PQ3MFhERERERkRWhr6+P4eFhJiYmGr0UkYZJpVL/f3v3HiNXWcZx/PtLKcotxYghSAWqcrFGQCigUW5CuEaQIAEhGpBERUANwUCUaCKCIJgoUUSspKgEjIgKCBRQsAQo91LKNYQqIhpACQhioPD4x5zFoex0T6U7s7vz/SSbnXPOe877zGSfzJxnn3OGmTNnrtQ+Fo8kSZIkSUNh+vTpzJo1a9BhSJOOl61JkiRJkiSpJ4tHkiRJkiRJ6snikSRJkiRJknrKZLvLfJIngT8POo5VZD3gqUEHIU0C5orUjrkitWOuSO2YK9LYplKebFxVbxttw6QrHk0lSW6vqjmDjkOa6MwVqR1zRWrHXJHaMVeksQ1LnnjZmiRJkiRJknqyeCRJkiRJkqSeLB4N1rmDDkCaJMwVqR1zRWrHXJHaMVeksQ1FnnjPI0mSJEmSJPVk55EkSZIkSZJ6snjUB0n2SvJgkoeTnDjK9iQ5q9m+OMk2g4hTGqQWeXJYkx+Lk9yUZKtBxCkN2li50jVuuyQvJ/l4P+OTJoo2uZJklySLktyb5I/9jlGaCFp8BpuR5LIkdze5csQg4pQGLcl5SZ5IsqTH9il9Xm/xaJwlmQb8ANgbmA18Isns5YbtDWza/HwG+GFfg5QGrGWeLAV2rqotgZMZkmuLpW4tc2Vk3OnA/P5GKE0MbXIlybrA2cB+VfVe4KC+ByoNWMv3laOB+6pqK2AX4DtJVu9roNLEMA/YawXbp/R5vcWj8bc98HBVPVJVLwIXAfsvN2Z/4KfVsRBYN8kG/Q5UGqAx86Sqbqqqp5vFhcDMPscoTQRt3lMAjgV+BTzRz+CkCaRNrhwKXFJVjwJUlfmiYdQmVwpYJ0mAtYF/Asv6G6Y0eFW1gM7ffy9T+rze4tH42xD4S9fyY826lR0jTWUrmwNHAleOa0TSxDRmriTZEDgAOKePcUkTTZv3lc2AtyS5PskdST7Vt+ikiaNNrnwfeA/wOHAP8MWqeqU/4UmTypQ+r19t0AEMgYyybvmvuGszRprKWudAkl3pFI8+PK4RSRNTm1z5LnBCVb3c+SexNJTa5MpqwLbAbsAawM1JFlbVQ+MdnDSBtMmVPYFFwEeAdwHXJLmhqp4d7+CkSWZKn9dbPBp/jwHv6FqeSadqv7JjpKmsVQ4k2RKYC+xdVf/oU2zSRNImV+YAFzWFo/WAfZIsq6rf9CdEaUJo+/nrqap6Hng+yQJgK8DikYZJm1w5Ajitqgp4OMlSYAvg1v6EKE0aU/q83svWxt9twKZJZjU3ljsEuHS5MZcCn2ruzv4B4Jmq+lu/A5UGaMw8SbIRcAnwSf8rrCE2Zq5U1ayq2qSqNgEuBj5v4UhDqM3nr98COyZZLcmawA7A/X2OUxq0NrnyKJ0OPZKsD2wOPNLXKKXJYUqf19t5NM6qalmSY+h848004LyqujfJ55rt5wBXAPsADwP/plPdl4ZGyzz5GvBW4Oymo2JZVc0ZVMzSILTMFWnotcmVqro/yVXAYuAVYG5Vjfr1y9JU1fJ95WRgXpJ76FyWc0JVPTWwoKUBSXIhnW8cXC/JY8DXgekwHOf16XQfSpIkSZIkSa/nZWuSJEmSJEnqyeKRJEmSJEmSerJ4JEmSJEmSpJ4sHkmSJEmSJKkni0eSJEmSJEnqyeKRJEmaFJK8nGRR188mKxj73CqYb16Spc1cdyb54P9xjLlJZjePv7LctpveaIzNcUZelyVJLkuy7hjjt06yz6qYW5IkDYdU1aBjkCRJGlOS56pq7VU9dgXHmAdcXlUXJ9kDOLOqtnwDx3vDMY113CTnAw9V1SkrGH84MKeqjlnVsUiSpKnJziNJkjQpJVk7ye+brqB7kuw/ypgNkizo6szZsVm/R5Kbm31/mWSsos4C4N3Nvsc1x1qS5EvNurWS/C7J3c36g5v11yeZk+Q0YI0mjguabc81v3/R3QnUdDwdmGRakjOS3JZkcZLPtnhZbgY2bI6zfZKbktzV/N48yerAN4CDm1gObmI/r5nnrtFeR0mSNNxWG3QAkiRJLa2RZFHzeClwEHBAVT2bZD1gYZJL67Vt1YcC86vqlCTTgDWbsScBu1fV80lOAI6jU1Tp5aPAPUm2BY4AdgAC3JLkj8A7gceral+AJDO6d66qE5McU1Vbj3Lsi4CDgSua4s5uwFHAkcAzVbVdkjcBNya5uqqWjhZg8/x2A37SrHoA2KmqliXZHTi1qg5M8jW6Oo+SnAr8oao+3VzydmuSa6vq+RW8HpIkaYhYPJIkSZPFC93FlyTTgVOT7AS8QqfjZn3g71373Aac14z9TVUtSrIzMJtOMQZgdTodO6M5I8lJwJN0ijm7Ab8eKawkuQTYEbgKODPJ6XQudbthJZ7XlcBZTYFoL2BBVb3QXCq3ZZKPN+NmAJvSKZx1GymqbQLcAVzTNf78JJsCBUzvMf8ewH5Jjm+W3wxsBNy/Es9BkiRNYRaPJEnSZHUY8DZg26p6Kcmf6BQ+XlVVC5ri0r7Az5KcATwNXFNVn2gxx5er6uKRhaaD53Wq6qGmK2kf4FtNh9CKOpm69/1PkuuBPel0IF04Mh1wbFXNH+MQL1TV1k230+XA0cBZwMnAdVV1QHNz8et77B/gwKp6sE28kiRp+HjPI0mSNFnNAJ5oCke7AhsvPyDJxs2YH9O5nGsbYCHwoSQj9zBaM8lmLedcAHys2Wct4ADghiRvB/5dVT8HzmzmWd5LTQfUaC6iczncjsBIsWg+cNTIPkk2a+YcVVU9A3wBOL7ZZwbw12bz4V1D/wWs07U8Hzg2TRtWkvf3mkOSJA0ni0eSJGmyugCYk+R2Ol1ID4wyZhdgUZK7gAOB71XVk3SKKRcmWUynmLRFmwmr6k5gHnArcAswt6ruAt5H515Bi4CvAt8cZfdzgcUjN8xeztXATsC1VfVis24ucB9wZ5IlwI8Yo2u8ieVu4BDg23S6oG4EpnUNuw6YPXLDbDodStOb2JY0y5IkSa/Ka+8pKUmSJEmSJP2PnUeSJEmSJEnqyeKRJEmSJEmSerJ4JEmSJEmSpJ4sHkmSJEmSJKkni0eSJEmSJEnqyeKRJEmSJEmSerJ4JEmSJEmSpJ4sHkmSJEmSJKmn/wKxW6pkGXBV9gAAAABJRU5ErkJggg==\n", + "image/png": 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\n", 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" ] @@ -2077,7 +2259,7 @@ } ], "source": [ - "#- create plot instance\n", + "# #- create plot instance\n", "fig, (ax1) = plt.subplots(1, 1, figsize=(20,10))\n", "\n", "#- go through all n model executions\n", @@ -2094,17 +2276,15 @@ " \n", " #- append per model execution\n", " out_X_df = evaluation.fill_out_df(out_X_df, X_df)\n", - " out_X1_df = evaluation.fill_out_df(out_X1_df, X1_df)\n", " out_y_df = evaluation.fill_out_df(out_y_df, y_df)\n", - " out_y1_df = evaluation.fill_out_df(out_y1_df, y1_df)\n", " out_dict = evaluation.fill_out_dict(out_dict, eval_dict)\n", "\n", " #- plot ROC curve per model execution\n", - " tprs, aucs = evaluation.plot_ROC_curve_n_times(ax1, clf, X_df.to_numpy(), y_df.y_test.to_list(),\n", + " tprs, aucs = plots.plot_ROC_curve_n_times(ax1, clf, X_df.to_numpy(), y_df.y_test.to_list(),\n", " trps, aucs, mean_fpr)\n", "\n", "#- plot mean ROC curve\n", - "evaluation.plot_ROC_curve_n_mean(ax1, tprs, aucs, mean_fpr)" + "plots.plot_ROC_curve_n_mean(ax1, tprs, aucs, mean_fpr)" ] }, { @@ -2142,13 +2322,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "average Accuracy of run with 50 repetitions is 0.849\n", - "average Precision of run with 50 repetitions is 0.522\n", - "average Recall of run with 50 repetitions is 0.289\n", - "average F1 score of run with 50 repetitions is 0.371\n", - "average Cohen-Kappa score of run with 50 repetitions is 0.293\n", - "average Brier loss score of run with 50 repetitions is 0.111\n", - "average ROC AUC score of run with 50 repetitions is 0.788\n" + "average Accuracy of run with 50 repetitions is 0.854\n", + "average Precision of run with 50 repetitions is 0.556\n", + "average Recall of run with 50 repetitions is 0.267\n", + "average F1 score of run with 50 repetitions is 0.360\n", + "average Cohen-Kappa score of run with 50 repetitions is 0.289\n", + "average Brier loss score of run with 50 repetitions is 0.106\n", + "average ROC AUC score of run with 50 repetitions is 0.819\n" ] } ], @@ -2158,6 +2338,28 @@ " print('average {0} of run with {1} repetitions is {2:0.3f}'.format(key, config.getint('settings', 'n_runs'), np.mean(out_dict[key])))" ] }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plots.metrics_distribution(out_dict, figsize=(20, 10));" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -2167,12 +2369,12 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -2199,11 +2401,11 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ - "df_hit, gdf_hit = evaluation.polygon_model_accuracy(out_y_df, global_df)" + "df_hit, gdf_hit = evaluation.polygon_model_accuracy(out_y_df, global_df, out_dir=None)" ] }, { @@ -2215,12 +2417,12 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -2251,7 +2453,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -2279,12 +2481,12 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -2308,6 +2510,48 @@ "selected_polygons_gdf.boundary.plot(ax=ax3, color='0.5');" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To get the variation of CCP (chance of corret prediction) per polygon, we split up the entire output data in 10 parts and calcualte mean, median, and standard deviation of CCP." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "gdf_CCP = evaluation.calc_kFold_polygon_analysis(out_y_df, global_df, out_dir=None)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(20, 10))\n", + "gdf_CCP.plot(column='mean_CCP', ax=ax1, cmap='Reds', legend=True, legend_kwds={'orientation': \"horizontal\"})\n", + "ax1.set_title('MEAN')\n", + "gdf_CCP.plot(column='std_CCP', ax=ax2, cmap='Reds', legend=True, legend_kwds={'orientation': \"horizontal\"})\n", + "ax2.set_title('STD');" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -2317,24 +2561,24 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 21, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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" + "
" ] }, "metadata": { @@ -2344,10 +2588,8 @@ } ], "source": [ - "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(20, 10))\n", - "sbs.scatterplot(data=df_hit, x='ID_count', y='chance_correct_pred', ax=ax1)\n", - "sbs.scatterplot(data=df_hit, x='ID_count', y='nr_test_confl', ax=ax2)\n", - "sbs.scatterplot(data=df_hit, x='nr_test_confl', y='chance_correct_pred', ax=ax3)" + "fig, ax = plt.subplots(1, 1, figsize=(20, 10))\n", + "sbs.scatterplot(data=df_hit, x='nr_test_confl', y='chance_correct_pred', ax=ax)" ] }, { @@ -2373,12 +2615,12 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 25, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -2390,15 +2632,44 @@ } ], "source": [ - "plots.plot_categories(gdf_hit, out_dir, category='sub')" + "plots.polygon_categorization(gdf_hit, category='sub', figsize=(20, 10), legend=True);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Last, we can determine the relative importance of each feature, that is variable." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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Hoch^[corresponding author] + orcid: 0000-0003-3570-6436 + affiliation: 1 + - name: Sophie de Bruin + orcid: 0000-0003-3429-349X + affiliation: "1, 2" + - name: Niko Wanders + orcid: 0000-0002-7102-5454 + affiliation: 1 +affiliations: + - name: Department of Physical Geography, Utrecht University, Utrecht, the Netherlands + index: 1 + - name: PBL Netherlands Environmental Assessment Agency, the Hague, the Netherlands + index: 2 +date: 30 September 2020 +bibliography: bibliography.bib +--- + +# Summary + +Climate change and environmental degradation are increasingly recognised as factors that can contribute to conflict risk under specific conditions. +In light of predicted shifts in climate patterns and the potentially resulting battle for increasingly scarce resources, it is widely acknowledged that there is an actual risk of increased armed conflict. To efficiently plan and implement adaptation and mitigation measures, it is key to first obtain an understanding of the the impact of individual climate, environmental, and societal drivers on conflict risk. And second, conflict risk needs to be projected to a given point in the future to be able to prepare accordingly. With CoPro, a set of functions and a workflow is made openly accessible to perform these steps, yielding maps of relative conflict risk. The model caters for a variety of settings and input data, thereby capturing the multitude of facets of the climate-environment-conflict nexus. + +# Statement of need + +There is increasing consensus that climate change can exacerbate the risk of (armed) conflict [@koubi2019climate; @mach2019climate]. Nevertheless, making (operational) forecasts on the short-term is still challenging due to several reasons [@cederman2017predicting]. Building upon recent, similar approaches to use data-driven models [@colaresi2017robot] and statistical approaches [@witmer2017subnational; @hegre2016forecasting] for conflict risk projections, CoPro is a novel, fully open, and extensible tool to combine the inter-disciplinary expertise required to make long-term projections of conflict risk associated with climatic and environmental drivers. Such a tool is needed not only to integrate the different disciplines, but also to extend the modelling approach with new insights and data - after all, the established links between climate and societal factors with conflict are still weak [@koubi2019climate; @mach2019climate]. In addition to scholarly explorations of the inter-dependencies and importance of various conflict drivers, model output such as maps of spatially-disaggregated projected conflict risk can be an invaluable input to inform the decision-making process in affected regions. + +Since conflicts are of all times and not limited to specific regions or countries, CoPro is designed with user-flexibility in mind. Therefore, the number and variables provided to the model is not specified, allowing for bespoke model designs. Depending on the modelling exercise and data used, several machine-learning models and pre-processing algorithms are available in CoPro. Catering for different model designs is of added value because of the non-linear and sometimes irrational - 'law-breaking' [@cederman2017predicting] - nature of conflicts. On top of that, the analyses can be run at any spatial scale, allowing for a better identification of sub-national drivers of conflict risk. After all, conflict onset and conflicts are often limited to specific areas where driving factors coincide. + +Since the replicability of scientific results is important when developing forecast and projection models [@hegre2017introduction], a key concept in mind when establishing CoPro was to be able to produce reproducible output using transparent models. Hence, by making model code openly available and by including dedicated features in the model, we hope to make an important contribution to the existing body of tools developed to project conflict. + +These functionalities altogether make CoPro suited for both quick and in-depth analyses of the relative importance of climate, environmental, and societal drivers as well as for assessments how conflict risk can change both in time and space. + +# Acknowledgements +This research was supported by a Pathways to Sustainability Acceleration Grant from the Utrecht University. +We kindly acknowledge the valuable contributions from all partners at PBL, PRIO (Peace Research Institute Oslo), Uppsala University, and Utrecht University. + +# References diff --git a/scripts/run_script.sh b/scripts/run_script.sh index df9a72d..62d9d84 100644 --- a/scripts/run_script.sh +++ b/scripts/run_script.sh @@ -1 +1 @@ -python runner.py ../example/example_settings.cfg \ No newline at end of file +python runner.py ../example/example_settings.cfg diff --git a/scripts/runner.py b/scripts/runner.py index fe84fdb..97a0835 100644 --- a/scripts/runner.py +++ b/scripts/runner.py @@ -1,4 +1,4 @@ -import conflict_model +import copro import click import pandas as pd @@ -7,7 +7,7 @@ import matplotlib.pyplot as plt import warnings -warnings.filterwarnings("ignore") +warnings.filterwarnings("module") @click.group() @@ -25,36 +25,38 @@ def main(cfg): """ print('') - print('#### LETS GET STARTED PEOPLZ! ####' + os.linesep) + print('#### CONFLICT MODEL version {} ####'.format(copro.__version__)) + print('') #- parsing settings-file and getting path to output folder - config, out_dir = conflict_model.utils.initiate_setup(cfg) + config, out_dir = copro.utils.initiate_setup(cfg) print('verbose mode on: {}'.format(config.getboolean('general', 'verbose')) + os.linesep) #- selecting conflicts and getting area-of-interest and aggregation level - conflict_gdf, extent_gdf, extent_active_polys_gdf, global_df = conflict_model.selection.select(config) - #- plot selected conflicts and polygons - conflict_model.plots.plot_active_polys(conflict_gdf, extent_gdf, extent_active_polys_gdf, config, out_dir) + conflict_gdf, extent_gdf, extent_active_polys_gdf, global_df = copro.selection.select(config, out_dir) + #- plot selected polygons and conflicts + fig, ax = plt.subplots(1, 1) + copro.plots.selected_polygons(extent_active_polys_gdf, figsize=(20, 10), ax=ax) + copro.plots.selected_conflicts(conflict_gdf, ax=ax) + plt.savefig(os.path.join(out_dir, 'selected_polygons_and_conflicts.png'), dpi=300, bbox_inches='tight') #- create X and Y arrays by reading conflict and variable files; #- or by loading a pre-computed array (npy-file) - X, Y = conflict_model.pipeline.create_XY(config, conflict_gdf, extent_active_polys_gdf) + X, Y = copro.pipeline.create_XY(config, conflict_gdf, extent_active_polys_gdf) #- defining scaling and model algorithms - scaler, clf = conflict_model.pipeline.prepare_ML(config) + scaler, clf = copro.pipeline.prepare_ML(config) #- initializing output variables #TODO: put all this into one function - out_X_df = conflict_model.evaluation.init_out_df() - out_X1_df = conflict_model.evaluation.init_out_df() - out_y_df = conflict_model.evaluation.init_out_df() - out_y1_df = conflict_model.evaluation.init_out_df() - out_dict = conflict_model.evaluation.init_out_dict() - trps, aucs, mean_fpr = conflict_model.evaluation.init_out_ROC_curve() + out_X_df = copro.evaluation.init_out_df() + out_y_df = copro.evaluation.init_out_df() + out_dict = copro.evaluation.init_out_dict() + trps, aucs, mean_fpr = copro.evaluation.init_out_ROC_curve() #- create plot instance for ROC plots - fig, (ax1) = plt.subplots(1, 1, figsize=(20,10)) + fig, ax1 = plt.subplots(1, 1, figsize=(20,10)) #- go through all n model executions for n in range(config.getint('settings', 'n_runs')): @@ -63,58 +65,47 @@ def main(cfg): print('run {} of {}'.format(n+1, config.getint('settings', 'n_runs')) + os.linesep) #- run machine learning model and return outputs - X_df, y_df, eval_dict = conflict_model.pipeline.run(X, Y, config, scaler, clf, out_dir) - - #- select sub-dataset with only datapoints with observed conflicts - X1_df, y1_df = conflict_model.utils.get_conflict_datapoints_only(X_df, y_df) + X_df, y_df, eval_dict = copro.pipeline.run(X, Y, config, scaler, clf, out_dir) #- append per model execution #TODO: put all this into one function - out_X_df = conflict_model.evaluation.fill_out_df(out_X_df, X_df) - out_X1_df = conflict_model.evaluation.fill_out_df(out_X1_df, X1_df) - out_y_df = conflict_model.evaluation.fill_out_df(out_y_df, y_df) - out_y1_df = conflict_model.evaluation.fill_out_df(out_y1_df, y1_df) - out_dict = conflict_model.evaluation.fill_out_dict(out_dict, eval_dict) + out_X_df = copro.evaluation.fill_out_df(out_X_df, X_df) + out_y_df = copro.evaluation.fill_out_df(out_y_df, y_df) + out_dict = copro.evaluation.fill_out_dict(out_dict, eval_dict) #- plot ROC curve per model execution - tprs, aucs = conflict_model.evaluation.plot_ROC_curve_n_times(ax1, clf, X_df.to_numpy(), y_df.y_test.to_list(), + tprs, aucs = copro.plots.plot_ROC_curve_n_times(ax1, clf, X_df.to_numpy(), y_df.y_test.to_list(), trps, aucs, mean_fpr) #- plot mean ROC curve - conflict_model.evaluation.plot_ROC_curve_n_mean(ax1, tprs, aucs, mean_fpr) + copro.plots.plot_ROC_curve_n_mean(ax1, tprs, aucs, mean_fpr) #- save plot - plt.savefig(os.path.join(out_dir, 'ROC_curve_per_run.png'), dpi=300) + plt.savefig(os.path.join(out_dir, 'ROC_curve_per_run.png'), dpi=300, bbox_inches='tight') + #- save output dictionary to csv-file + copro.utils.save_to_csv(out_dict, out_dir, 'out_dict') + copro.utils.save_to_npy(out_y_df, out_dir, 'out_y_df') + #- print mean values of all evaluation metrics for key in out_dict: if config.getboolean('general', 'verbose'): print('average {0} of run with {1} repetitions is {2:0.3f}'.format(key, config.getint('settings', 'n_runs'), np.mean(out_dict[key]))) - #- plot distribution of all evaluation metrics - conflict_model.plots.plot_metrics_distribution(out_dict, out_dir) - - #- compute average correct prediction per polygon for all data points as well as conflicty-only - df_hit, gdf_hit = conflict_model.evaluation.polygon_model_accuracy(out_y_df, global_df) - df_hit_1, gdf_hit_1 = conflict_model.evaluation.polygon_model_accuracy(out_y1_df, global_df) - - #- for both, plot number of predictions made per polygon and overall distribution - conflict_model.plots.plot_nr_and_dist_pred(df_hit, gdf_hit, extent_active_polys_gdf, out_dir) - conflict_model.plots.plot_nr_and_dist_pred(df_hit_1, gdf_hit_1, extent_active_polys_gdf, out_dir, suffix='conflicts_only') + df_hit, gdf_hit = copro.evaluation.polygon_model_accuracy(out_y_df, global_df, out_dir=None) - #- for both, plot average correct prediction and number of conflicht per polygon - conflict_model.plots.plot_frac_and_nr_conf(gdf_hit, extent_active_polys_gdf, out_dir) - conflict_model.plots.plot_frac_and_nr_conf(gdf_hit_1, extent_active_polys_gdf, out_dir, suffix='conflicts_only') - - #- for both, plot distribution of average correct predictions - conflict_model.plots.plot_frac_pred(gdf_hit, gdf_hit_1, out_dir) - - conflict_model.plots.plot_scatterdata(df_hit, out_dir) - - conflict_model.plots.plot_categories(gdf_hit, out_dir) - - #- save some dataframes to file - df_hit.to_csv(os.path.join(out_dir, 'df_hit.csv')) - pd.DataFrame.from_dict(out_dict).to_csv(os.path.join(out_dir, 'out_dict.csv'), index=False) + #- plot distribution of all evaluation metrics + fig, ax = plt.subplots(1, 1) + copro.plots.metrics_distribution(out_dict, figsize=(20, 10)) + plt.savefig(os.path.join(out_dir, 'metrics_distribution.png'), dpi=300, bbox_inches='tight') + + #- plot relative importance of each feature + fig, ax = plt.subplots(1, 1) + copro.plots.factor_importance(clf, config, ax=ax, figsize=(20, 10)) + plt.savefig(os.path.join(out_dir, 'factor_importance.png'), dpi=300, bbox_inches='tight') + + fig, ax = plt.subplots(1, 1) + copro.plots.polygon_categorization(gdf_hit, ax=ax) + plt.savefig(os.path.join(out_dir, 'polygon_categorization.png'), dpi=300, bbox_inches='tight') if __name__ == '__main__': main() \ No newline at end of file diff --git a/setup.cfg b/setup.cfg index 4c7ab76..1550173 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 0.0.4 +current_version = 0.0.5 commit = True tag = True @@ -7,7 +7,7 @@ tag = True search = version='{current_version}' replace = version='{new_version}' -[bumpversion:file:conflict_model/__init__.py] +[bumpversion:file:copro/__init__.py] search = __version__ = '{current_version}' replace = __version__ = '{new_version}' diff --git a/setup.py b/setup.py index 31b69de..bccb6cb 100644 --- a/setup.py +++ b/setup.py @@ -23,7 +23,7 @@ author_email='j.m.hoch@uu.nl', python_requires='>=3.6', classifiers=[ - 'Development Status :: 5 - Production/Stable', + 'Development Status :: 4 - Beta', 'Intended Audience :: Developers', 'License :: OSI Approved :: GNU General Public License v3 (GPLv3)', 'Natural Language :: English', @@ -35,16 +35,16 @@ description="modelling interplay between conflict and climate", entry_points={}, install_requires=requirements, - license="tba", + license="MIT", long_description='blablabla', include_package_data=True, - keywords='conflict, climate', - name='conflict_model', - packages=find_packages(include=['conflict_model', 'conflict_model.*']), + keywords='conflict, climate, machine learning, projections', + name='copro', + packages=find_packages(include=['copro', 'copro.*']), setup_requires=setup_requirements, test_suite='tests', tests_require=test_requirements, - url='https://github.com/JannisHoch/conflict_model', - version='0.0.4', + url='https://github.com/JannisHoch/copro', + version='0.0.5', zip_safe=False, ) diff --git a/tests/test_conflict.py b/tests/test_conflict.py new file mode 100644 index 0000000..976a65a --- /dev/null +++ b/tests/test_conflict.py @@ -0,0 +1,41 @@ +import pytest +import configparser +import numpy as np +import pandas as pd +import geopandas as gpd +from copro import conflict + +def test_split_conflict_geom_data(): + #TODO: would like to do this with actual geometry information, but np.equal() does not like this... + + X1 = [1, 2, 3, 4] + # X2 = [['POINT(-58.66 -34.58)'], ['POINT(-47.91 -15.78)'], ['POINT(-70.66 -33.45)'], ['POINT(-74.08 4.60)']] + X2 = [1, 2, 3, 4] + X3 = [[1, 2], [3, 4], [1, 2], [5, 6]] + + X_in = np.column_stack((X1, X2, X3)) + + X_ID, X_geom, X_data = conflict.split_conflict_geom_data(X_in) + + X_out = np.column_stack((X_ID, X_geom, X_data)) + + X_false = np.where(np.equal(X_in, X_out) == False)[0] + + assert X_false.size == 0 + +def test_get_poly_geometry(): + + gdf = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres')) + + list_geometry = conflict.get_poly_geometry(gdf) + + assert len(gdf) == len(list_geometry) + +def test_get_poly_ID(): + + gdf = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres')) + + list_ID = conflict.get_poly_ID(gdf) + + assert len(gdf) == len(list_ID) + diff --git a/tests/test_data.py b/tests/test_data.py new file mode 100644 index 0000000..b94561b --- /dev/null +++ b/tests/test_data.py @@ -0,0 +1,31 @@ +import pytest +import configparser +import numpy as np +import pandas as pd +from copro import data + +def create_fake_config(): + + config = configparser.ConfigParser() + + config.add_section('general') + config.set('general', 'verbose', str(False)) + + return config + +def test_split_XY_data(): + + config = create_fake_config() + + X_arr = [[1, 2], [3, 4], [1, 2], [5, 6]] + y_arr = [1, 0, 0, 1] + + XY_in = np.column_stack((X_arr, y_arr)) + + X, Y = data.split_XY_data(XY_in, config) + + XY_out = np.column_stack((X, Y)) + + XY_false = np.where(np.equal(XY_in, XY_out) == False)[0] + + assert XY_false.size == 0 diff --git a/tests/test_machine_learning.py b/tests/test_machine_learning.py new file mode 100644 index 0000000..2d2e8bb --- /dev/null +++ b/tests/test_machine_learning.py @@ -0,0 +1,33 @@ +import pytest +import configparser +import numpy as np +import pandas as pd +import geopandas as gpd +from sklearn import preprocessing, model_selection +from copro import conflict, machine_learning + +def create_fake_config(): + + config = configparser.ConfigParser() + + config.add_section('general') + config.set('general', 'verbose', str(False)) + config.add_section('machine_learning') + config.set('machine_learning', 'train_fraction', str(0.7)) + + return config + +def test_split_scale_train_test_split(): + + X1 = [1, 2, 3, 4] + X2 = [1, 2, 3, 4] + X3 = [[1, 2], [3, 4], [1, 2], [5, 6]] + + X = np.column_stack((X1, X2, X3)) + Y = [1, 0, 0, 1] + config = create_fake_config() + scaler = preprocessing.QuantileTransformer() + + X_train, X_test, y_train, y_test, X_train_geom, X_test_geom, X_train_ID, X_test_ID = machine_learning.split_scale_train_test_split(X, Y, config, scaler) + + assert (len(X_train) + len(X_test)) == len(X) \ No newline at end of file diff --git a/tests/test_utils.py b/tests/test_utils.py index 291662e..c4989b7 100644 --- a/tests/test_utils.py +++ b/tests/test_utils.py @@ -1,8 +1,7 @@ import pytest import numpy as np -from conflict_model import utils - - +import pandas as pd +from copro import utils def test_create_artificial_Y(): @@ -10,4 +9,18 @@ def test_create_artificial_Y(): Y_r = utils.create_artificial_Y(Y) - assert len(np.where(Y_r != 0)[0]) == len(np.where(Y != 0)[0]) \ No newline at end of file + assert len(np.where(Y_r != 0)[0]) == len(np.where(Y != 0)[0]) + +def test_get_conflict_datapoints_only(): + + X_arr = [[1, 2], [3, 4], [1, 2], [5, 6]] + y_arr = [1, 0, 0, 1] + + X_in = pd.DataFrame(data=X_arr, columns=['var1', 'var2']) + y_in = pd.DataFrame(data=y_arr, columns=['y_test']) + + X_out, y_out = utils.get_conflict_datapoints_only(X_in, y_in) + + test_arr = np.where(y_out.y_test.values == 0)[0] + + assert test_arr.size == 0 \ No newline at end of file diff --git a/tox.ini b/tox.ini index f35cc26..d8540c5 100644 --- a/tox.ini +++ b/tox.ini @@ -11,7 +11,7 @@ python = [testenv:flake8] basepython = python deps = flake8 -commands = flake8 pcrglobwb_utils tests +commands = flake8 copro tests [testenv] setenv =