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PINA/docs/source/tutorials/tutorial23/tutorial.html
github-actions[bot] 6d7ce0e4e2 export tutorials changed in 62fe6f8 (#670) 
Co-authored-by: dario-coscia <dario-coscia@users.noreply.github.com>
2025-10-16 15:59:25 +02:00

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<title>tutorial</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script><script>
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/* Icons urls */
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--jp-icon-add-above: url(data:image/svg+xml;base64,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);
--jp-icon-add-below: url(data:image/svg+xml;base64,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);
--jp-icon-add: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDI0IDI0Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE5IDEzaC02djZoLTJ2LTZINXYtMmg2VjVoMnY2aDZ2MnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-bell: url(data:image/svg+xml;base64,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);
--jp-icon-bug-dot: url(data:image/svg+xml;base64,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);
--jp-icon-bug: url(data:image/svg+xml;base64,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);
--jp-icon-build: url(data:image/svg+xml;base64,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);
--jp-icon-caret-down-empty-thin: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIwIDIwIj4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwb2x5Z29uIGNsYXNzPSJzdDEiIHBvaW50cz0iOS45LDEzLjYgMy42LDcuNCA0LjQsNi42IDkuOSwxMi4yIDE1LjQsNi43IDE2LjEsNy40ICIvPgoJPC9nPgo8L3N2Zz4K);
--jp-icon-caret-down-empty: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik01LjIsNS45TDksOS43bDMuOC0zLjhsMS4yLDEuMmwtNC45LDVsLTQuOS01TDUuMiw1Ljl6Ii8+CiAgPC9nPgo8L3N2Zz4K);
--jp-icon-caret-down: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiIHNoYXBlLXJlbmRlcmluZz0iZ2VvbWV0cmljUHJlY2lzaW9uIj4KICAgIDxwYXRoIGQ9Ik01LjIsNy41TDksMTEuMmwzLjgtMy44SDUuMnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-caret-left: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KCTxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSIgc2hhcGUtcmVuZGVyaW5nPSJnZW9tZXRyaWNQcmVjaXNpb24iPgoJCTxwYXRoIGQ9Ik0xMC44LDEyLjhMNy4xLDlsMy44LTMuOGwwLDcuNkgxMC44eiIvPgogIDwvZz4KPC9zdmc+Cg==);
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--jp-icon-redo: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIGhlaWdodD0iMjQiIHZpZXdCb3g9IjAgMCAyNCAyNCIgd2lkdGg9IjE2Ij4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgICA8cGF0aCBkPSJNMCAwaDI0djI0SDB6IiBmaWxsPSJub25lIi8+PHBhdGggZD0iTTE4LjQgMTAuNkMxNi41NSA4Ljk5IDE0LjE1IDggMTEuNSA4Yy00LjY1IDAtOC41OCAzLjAzLTkuOTYgNy4yMkwzLjkgMTZjMS4wNS0zLjE5IDQuMDUtNS41IDcuNi01LjUgMS45NSAwIDMuNzMuNzIgNS4xMiAxLjg4TDEzIDE2aDlWN2wtMy42IDMuNnoiLz4KICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-refresh: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDE4IDE4Ij4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTkgMTMuNWMtMi40OSAwLTQuNS0yLjAxLTQuNS00LjVTNi41MSA0LjUgOSA0LjVjMS4yNCAwIDIuMzYuNTIgMy4xNyAxLjMzTDEwIDhoNVYzbC0xLjc2IDEuNzZDMTIuMTUgMy42OCAxMC42NiAzIDkgMyA1LjY5IDMgMy4wMSA1LjY5IDMuMDEgOVM1LjY5IDE1IDkgMTVjMi45NyAwIDUuNDMtMi4xNiA1LjktNWgtMS41MmMtLjQ2IDItMi4yNCAzLjUtNC4zOCAzLjV6Ii8+CiAgICA8L2c+Cjwvc3ZnPgo=);
--jp-icon-regex: url(data:image/svg+xml;base64,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);
--jp-icon-run: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTggNXYxNGwxMS03eiIvPgogICAgPC9nPgo8L3N2Zz4K);
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--jp-icon-save: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTE3IDNINWMtMS4xMSAwLTIgLjktMiAydjE0YzAgMS4xLjg5IDIgMiAyaDE0YzEuMSAwIDItLjkgMi0yVjdsLTQtNHptLTUgMTZjLTEuNjYgMC0zLTEuMzQtMy0zczEuMzQtMyAzLTMgMyAxLjM0IDMgMy0xLjM0IDMtMyAzem0zLTEwSDVWNWgxMHY0eiIvPgogICAgPC9nPgo8L3N2Zz4K);
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--jp-icon-toc: url(data:image/svg+xml;base64,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);
--jp-icon-tree-view: url(data:image/svg+xml;base64,PHN2ZyBoZWlnaHQ9IjI0IiB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICAgIDxnIGNsYXNzPSJqcC1pY29uMyIgZmlsbD0iIzYxNjE2MSI+CiAgICAgICAgPHBhdGggZD0iTTAgMGgyNHYyNEgweiIgZmlsbD0ibm9uZSIvPgogICAgICAgIDxwYXRoIGQ9Ik0yMiAxMVYzaC03djNIOVYzSDJ2OGg3VjhoMnYxMGg0djNoN3YtOGgtN3YzaC0yVjhoMnYzeiIvPgogICAgPC9nPgo8L3N2Zz4K);
--jp-icon-trusted: url(data:image/svg+xml;base64,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);
--jp-icon-undo: url(data:image/svg+xml;base64,PHN2ZyB2aWV3Qm94PSIwIDAgMjQgMjQiIHdpZHRoPSIxNiIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTEyLjUgOGMtMi42NSAwLTUuMDUuOTktNi45IDIuNkwyIDd2OWg5bC0zLjYyLTMuNjJjMS4zOS0xLjE2IDMuMTYtMS44OCA1LjEyLTEuODggMy41NCAwIDYuNTUgMi4zMSA3LjYgNS41bDIuMzctLjc4QzIxLjA4IDExLjAzIDE3LjE1IDggMTIuNSA4eiIvPgogIDwvZz4KPC9zdmc+Cg==);
--jp-icon-user: url(data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMTYiIHZpZXdCb3g9IjAgMCAyNCAyNCIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KICA8ZyBjbGFzcz0ianAtaWNvbjMiIGZpbGw9IiM2MTYxNjEiPgogICAgPHBhdGggZD0iTTE2IDdhNCA0IDAgMTEtOCAwIDQgNCAwIDAxOCAwek0xMiAxNGE3IDcgMCAwMC03IDdoMTRhNyA3IDAgMDAtNy03eiIvPgogIDwvZz4KPC9zdmc+Cg==);
--jp-icon-users: url(data:image/svg+xml;base64,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);
--jp-icon-vega: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIxNiIgdmlld0JveD0iMCAwIDIyIDIyIj4KICA8ZyBjbGFzcz0ianAtaWNvbjEganAtaWNvbi1zZWxlY3RhYmxlIiBmaWxsPSIjMjEyMTIxIj4KICAgIDxwYXRoIGQ9Ik0xMC42IDUuNGwyLjItMy4ySDIuMnY3LjNsNC02LjZ6Ii8+CiAgICA8cGF0aCBkPSJNMTUuOCAyLjJsLTQuNCA2LjZMNyA2LjNsLTQuOCA4djUuNWgxNy42VjIuMmgtNHptLTcgMTUuNEg1LjV2LTQuNGgzLjN2NC40em00LjQgMEg5LjhWOS44aDMuNHY3Ljh6bTQuNCAwaC0zLjRWNi41aDMuNHYxMS4xeiIvPgogIDwvZz4KPC9zdmc+Cg==);
--jp-icon-word: url(data:image/svg+xml;base64,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);
--jp-icon-yaml: url(data:image/svg+xml;base64,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);
}
/* Icon CSS class declarations */
.jp-AddAboveIcon {
background-image: var(--jp-icon-add-above);
}
.jp-AddBelowIcon {
background-image: var(--jp-icon-add-below);
}
.jp-AddIcon {
background-image: var(--jp-icon-add);
}
.jp-BellIcon {
background-image: var(--jp-icon-bell);
}
.jp-BugDotIcon {
background-image: var(--jp-icon-bug-dot);
}
.jp-BugIcon {
background-image: var(--jp-icon-bug);
}
.jp-BuildIcon {
background-image: var(--jp-icon-build);
}
.jp-CaretDownEmptyIcon {
background-image: var(--jp-icon-caret-down-empty);
}
.jp-CaretDownEmptyThinIcon {
background-image: var(--jp-icon-caret-down-empty-thin);
}
.jp-CaretDownIcon {
background-image: var(--jp-icon-caret-down);
}
.jp-CaretLeftIcon {
background-image: var(--jp-icon-caret-left);
}
.jp-CaretRightIcon {
background-image: var(--jp-icon-caret-right);
}
.jp-CaretUpEmptyThinIcon {
background-image: var(--jp-icon-caret-up-empty-thin);
}
.jp-CaretUpIcon {
background-image: var(--jp-icon-caret-up);
}
.jp-CaseSensitiveIcon {
background-image: var(--jp-icon-case-sensitive);
}
.jp-CheckIcon {
background-image: var(--jp-icon-check);
}
.jp-CircleEmptyIcon {
background-image: var(--jp-icon-circle-empty);
}
.jp-CircleIcon {
background-image: var(--jp-icon-circle);
}
.jp-ClearIcon {
background-image: var(--jp-icon-clear);
}
.jp-CloseIcon {
background-image: var(--jp-icon-close);
}
.jp-CodeCheckIcon {
background-image: var(--jp-icon-code-check);
}
.jp-CodeIcon {
background-image: var(--jp-icon-code);
}
.jp-CollapseAllIcon {
background-image: var(--jp-icon-collapse-all);
}
.jp-ConsoleIcon {
background-image: var(--jp-icon-console);
}
.jp-CopyIcon {
background-image: var(--jp-icon-copy);
}
.jp-CopyrightIcon {
background-image: var(--jp-icon-copyright);
}
.jp-CutIcon {
background-image: var(--jp-icon-cut);
}
.jp-DeleteIcon {
background-image: var(--jp-icon-delete);
}
.jp-DownloadIcon {
background-image: var(--jp-icon-download);
}
.jp-DuplicateIcon {
background-image: var(--jp-icon-duplicate);
}
.jp-EditIcon {
background-image: var(--jp-icon-edit);
}
.jp-EllipsesIcon {
background-image: var(--jp-icon-ellipses);
}
.jp-ErrorIcon {
background-image: var(--jp-icon-error);
}
.jp-ExpandAllIcon {
background-image: var(--jp-icon-expand-all);
}
.jp-ExtensionIcon {
background-image: var(--jp-icon-extension);
}
.jp-FastForwardIcon {
background-image: var(--jp-icon-fast-forward);
}
.jp-FileIcon {
background-image: var(--jp-icon-file);
}
.jp-FileUploadIcon {
background-image: var(--jp-icon-file-upload);
}
.jp-FilterDotIcon {
background-image: var(--jp-icon-filter-dot);
}
.jp-FilterIcon {
background-image: var(--jp-icon-filter);
}
.jp-FilterListIcon {
background-image: var(--jp-icon-filter-list);
}
.jp-FolderFavoriteIcon {
background-image: var(--jp-icon-folder-favorite);
}
.jp-FolderIcon {
background-image: var(--jp-icon-folder);
}
.jp-HomeIcon {
background-image: var(--jp-icon-home);
}
.jp-Html5Icon {
background-image: var(--jp-icon-html5);
}
.jp-ImageIcon {
background-image: var(--jp-icon-image);
}
.jp-InfoIcon {
background-image: var(--jp-icon-info);
}
.jp-InspectorIcon {
background-image: var(--jp-icon-inspector);
}
.jp-JsonIcon {
background-image: var(--jp-icon-json);
}
.jp-JuliaIcon {
background-image: var(--jp-icon-julia);
}
.jp-JupyterFaviconIcon {
background-image: var(--jp-icon-jupyter-favicon);
}
.jp-JupyterIcon {
background-image: var(--jp-icon-jupyter);
}
.jp-JupyterlabWordmarkIcon {
background-image: var(--jp-icon-jupyterlab-wordmark);
}
.jp-KernelIcon {
background-image: var(--jp-icon-kernel);
}
.jp-KeyboardIcon {
background-image: var(--jp-icon-keyboard);
}
.jp-LaunchIcon {
background-image: var(--jp-icon-launch);
}
.jp-LauncherIcon {
background-image: var(--jp-icon-launcher);
}
.jp-LineFormIcon {
background-image: var(--jp-icon-line-form);
}
.jp-LinkIcon {
background-image: var(--jp-icon-link);
}
.jp-ListIcon {
background-image: var(--jp-icon-list);
}
.jp-MarkdownIcon {
background-image: var(--jp-icon-markdown);
}
.jp-MoveDownIcon {
background-image: var(--jp-icon-move-down);
}
.jp-MoveUpIcon {
background-image: var(--jp-icon-move-up);
}
.jp-NewFolderIcon {
background-image: var(--jp-icon-new-folder);
}
.jp-NotTrustedIcon {
background-image: var(--jp-icon-not-trusted);
}
.jp-NotebookIcon {
background-image: var(--jp-icon-notebook);
}
.jp-NumberingIcon {
background-image: var(--jp-icon-numbering);
}
.jp-OfflineBoltIcon {
background-image: var(--jp-icon-offline-bolt);
}
.jp-PaletteIcon {
background-image: var(--jp-icon-palette);
}
.jp-PasteIcon {
background-image: var(--jp-icon-paste);
}
.jp-PdfIcon {
background-image: var(--jp-icon-pdf);
}
.jp-PythonIcon {
background-image: var(--jp-icon-python);
}
.jp-RKernelIcon {
background-image: var(--jp-icon-r-kernel);
}
.jp-ReactIcon {
background-image: var(--jp-icon-react);
}
.jp-RedoIcon {
background-image: var(--jp-icon-redo);
}
.jp-RefreshIcon {
background-image: var(--jp-icon-refresh);
}
.jp-RegexIcon {
background-image: var(--jp-icon-regex);
}
.jp-RunIcon {
background-image: var(--jp-icon-run);
}
.jp-RunningIcon {
background-image: var(--jp-icon-running);
}
.jp-SaveIcon {
background-image: var(--jp-icon-save);
}
.jp-SearchIcon {
background-image: var(--jp-icon-search);
}
.jp-SettingsIcon {
background-image: var(--jp-icon-settings);
}
.jp-ShareIcon {
background-image: var(--jp-icon-share);
}
.jp-SpreadsheetIcon {
background-image: var(--jp-icon-spreadsheet);
}
.jp-StopIcon {
background-image: var(--jp-icon-stop);
}
.jp-TabIcon {
background-image: var(--jp-icon-tab);
}
.jp-TableRowsIcon {
background-image: var(--jp-icon-table-rows);
}
.jp-TagIcon {
background-image: var(--jp-icon-tag);
}
.jp-TerminalIcon {
background-image: var(--jp-icon-terminal);
}
.jp-TextEditorIcon {
background-image: var(--jp-icon-text-editor);
}
.jp-TocIcon {
background-image: var(--jp-icon-toc);
}
.jp-TreeViewIcon {
background-image: var(--jp-icon-tree-view);
}
.jp-TrustedIcon {
background-image: var(--jp-icon-trusted);
}
.jp-UndoIcon {
background-image: var(--jp-icon-undo);
}
.jp-UserIcon {
background-image: var(--jp-icon-user);
}
.jp-UsersIcon {
background-image: var(--jp-icon-users);
}
.jp-VegaIcon {
background-image: var(--jp-icon-vega);
}
.jp-WordIcon {
background-image: var(--jp-icon-word);
}
.jp-YamlIcon {
background-image: var(--jp-icon-yaml);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* (DEPRECATED) Support for consuming icons as CSS background images
*/
.jp-Icon,
.jp-MaterialIcon {
background-position: center;
background-repeat: no-repeat;
background-size: 16px;
min-width: 16px;
min-height: 16px;
}
.jp-Icon-cover {
background-position: center;
background-repeat: no-repeat;
background-size: cover;
}
/**
* (DEPRECATED) Support for specific CSS icon sizes
*/
.jp-Icon-16 {
background-size: 16px;
min-width: 16px;
min-height: 16px;
}
.jp-Icon-18 {
background-size: 18px;
min-width: 18px;
min-height: 18px;
}
.jp-Icon-20 {
background-size: 20px;
min-width: 20px;
min-height: 20px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.lm-TabBar .lm-TabBar-addButton {
align-items: center;
display: flex;
padding: 4px;
padding-bottom: 5px;
margin-right: 1px;
background-color: var(--jp-layout-color2);
}
.lm-TabBar .lm-TabBar-addButton:hover {
background-color: var(--jp-layout-color1);
}
.lm-DockPanel-tabBar .lm-TabBar-tab {
width: var(--jp-private-horizontal-tab-width);
}
.lm-DockPanel-tabBar .lm-TabBar-content {
flex: unset;
}
.lm-DockPanel-tabBar[data-orientation='horizontal'] {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* Support for icons as inline SVG HTMLElements
*/
/* recolor the primary elements of an icon */
.jp-icon0[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon1[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon2[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon3[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon4[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon0[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon1[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon2[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon3[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon4[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/* recolor the accent elements of an icon */
.jp-icon-accent0[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-accent1[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-accent2[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-accent3[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-accent4[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-accent0[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-accent1[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-accent2[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-accent3[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-accent4[stroke] {
stroke: var(--jp-layout-color4);
}
/* set the color of an icon to transparent */
.jp-icon-none[fill] {
fill: none;
}
.jp-icon-none[stroke] {
stroke: none;
}
/* brand icon colors. Same for light and dark */
.jp-icon-brand0[fill] {
fill: var(--jp-brand-color0);
}
.jp-icon-brand1[fill] {
fill: var(--jp-brand-color1);
}
.jp-icon-brand2[fill] {
fill: var(--jp-brand-color2);
}
.jp-icon-brand3[fill] {
fill: var(--jp-brand-color3);
}
.jp-icon-brand4[fill] {
fill: var(--jp-brand-color4);
}
.jp-icon-brand0[stroke] {
stroke: var(--jp-brand-color0);
}
.jp-icon-brand1[stroke] {
stroke: var(--jp-brand-color1);
}
.jp-icon-brand2[stroke] {
stroke: var(--jp-brand-color2);
}
.jp-icon-brand3[stroke] {
stroke: var(--jp-brand-color3);
}
.jp-icon-brand4[stroke] {
stroke: var(--jp-brand-color4);
}
/* warn icon colors. Same for light and dark */
.jp-icon-warn0[fill] {
fill: var(--jp-warn-color0);
}
.jp-icon-warn1[fill] {
fill: var(--jp-warn-color1);
}
.jp-icon-warn2[fill] {
fill: var(--jp-warn-color2);
}
.jp-icon-warn3[fill] {
fill: var(--jp-warn-color3);
}
.jp-icon-warn0[stroke] {
stroke: var(--jp-warn-color0);
}
.jp-icon-warn1[stroke] {
stroke: var(--jp-warn-color1);
}
.jp-icon-warn2[stroke] {
stroke: var(--jp-warn-color2);
}
.jp-icon-warn3[stroke] {
stroke: var(--jp-warn-color3);
}
/* icon colors that contrast well with each other and most backgrounds */
.jp-icon-contrast0[fill] {
fill: var(--jp-icon-contrast-color0);
}
.jp-icon-contrast1[fill] {
fill: var(--jp-icon-contrast-color1);
}
.jp-icon-contrast2[fill] {
fill: var(--jp-icon-contrast-color2);
}
.jp-icon-contrast3[fill] {
fill: var(--jp-icon-contrast-color3);
}
.jp-icon-contrast0[stroke] {
stroke: var(--jp-icon-contrast-color0);
}
.jp-icon-contrast1[stroke] {
stroke: var(--jp-icon-contrast-color1);
}
.jp-icon-contrast2[stroke] {
stroke: var(--jp-icon-contrast-color2);
}
.jp-icon-contrast3[stroke] {
stroke: var(--jp-icon-contrast-color3);
}
.jp-icon-dot[fill] {
fill: var(--jp-warn-color0);
}
.jp-jupyter-icon-color[fill] {
fill: var(--jp-jupyter-icon-color, var(--jp-warn-color0));
}
.jp-notebook-icon-color[fill] {
fill: var(--jp-notebook-icon-color, var(--jp-warn-color0));
}
.jp-json-icon-color[fill] {
fill: var(--jp-json-icon-color, var(--jp-warn-color1));
}
.jp-console-icon-color[fill] {
fill: var(--jp-console-icon-color, white);
}
.jp-console-icon-background-color[fill] {
fill: var(--jp-console-icon-background-color, var(--jp-brand-color1));
}
.jp-terminal-icon-color[fill] {
fill: var(--jp-terminal-icon-color, var(--jp-layout-color2));
}
.jp-terminal-icon-background-color[fill] {
fill: var(
--jp-terminal-icon-background-color,
var(--jp-inverse-layout-color2)
);
}
.jp-text-editor-icon-color[fill] {
fill: var(--jp-text-editor-icon-color, var(--jp-inverse-layout-color3));
}
.jp-inspector-icon-color[fill] {
fill: var(--jp-inspector-icon-color, var(--jp-inverse-layout-color3));
}
/* CSS for icons in selected filebrowser listing items */
.jp-DirListing-item.jp-mod-selected .jp-icon-selectable[fill] {
fill: #fff;
}
.jp-DirListing-item.jp-mod-selected .jp-icon-selectable-inverse[fill] {
fill: var(--jp-brand-color1);
}
/* stylelint-disable selector-max-class, selector-max-compound-selectors */
/**
* TODO: come up with non css-hack solution for showing the busy icon on top
* of the close icon
* CSS for complex behavior of close icon of tabs in the main area tabbar
*/
.lm-DockPanel-tabBar
.lm-TabBar-tab.lm-mod-closable.jp-mod-dirty
> .lm-TabBar-tabCloseIcon
> :not(:hover)
> .jp-icon3[fill] {
fill: none;
}
.lm-DockPanel-tabBar
.lm-TabBar-tab.lm-mod-closable.jp-mod-dirty
> .lm-TabBar-tabCloseIcon
> :not(:hover)
> .jp-icon-busy[fill] {
fill: var(--jp-inverse-layout-color3);
}
/* stylelint-enable selector-max-class, selector-max-compound-selectors */
/* CSS for icons in status bar */
#jp-main-statusbar .jp-mod-selected .jp-icon-selectable[fill] {
fill: #fff;
}
#jp-main-statusbar .jp-mod-selected .jp-icon-selectable-inverse[fill] {
fill: var(--jp-brand-color1);
}
/* special handling for splash icon CSS. While the theme CSS reloads during
splash, the splash icon can loose theming. To prevent that, we set a
default for its color variable */
:root {
--jp-warn-color0: var(--md-orange-700);
}
/* not sure what to do with this one, used in filebrowser listing */
.jp-DragIcon {
margin-right: 4px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/**
* Support for alt colors for icons as inline SVG HTMLElements
*/
/* alt recolor the primary elements of an icon */
.jp-icon-alt .jp-icon0[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-alt .jp-icon1[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-alt .jp-icon2[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-alt .jp-icon3[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-alt .jp-icon4[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-alt .jp-icon0[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-alt .jp-icon1[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-alt .jp-icon2[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-alt .jp-icon3[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-alt .jp-icon4[stroke] {
stroke: var(--jp-layout-color4);
}
/* alt recolor the accent elements of an icon */
.jp-icon-alt .jp-icon-accent0[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-alt .jp-icon-accent1[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-alt .jp-icon-accent2[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-alt .jp-icon-accent3[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-alt .jp-icon-accent4[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-alt .jp-icon-accent0[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-alt .jp-icon-accent1[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-alt .jp-icon-accent2[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-alt .jp-icon-accent3[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-alt .jp-icon-accent4[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-icon-hoverShow:not(:hover) .jp-icon-hoverShow-content {
display: none !important;
}
/**
* Support for hover colors for icons as inline SVG HTMLElements
*/
/**
* regular colors
*/
/* recolor the primary elements of an icon */
.jp-icon-hover :hover .jp-icon0-hover[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-hover :hover .jp-icon1-hover[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-hover :hover .jp-icon2-hover[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-hover :hover .jp-icon3-hover[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-hover :hover .jp-icon4-hover[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-hover :hover .jp-icon0-hover[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-hover :hover .jp-icon1-hover[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-hover :hover .jp-icon2-hover[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-hover :hover .jp-icon3-hover[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-hover :hover .jp-icon4-hover[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/* recolor the accent elements of an icon */
.jp-icon-hover :hover .jp-icon-accent0-hover[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-hover :hover .jp-icon-accent1-hover[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-hover :hover .jp-icon-accent2-hover[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-hover :hover .jp-icon-accent3-hover[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-hover :hover .jp-icon-accent4-hover[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-hover :hover .jp-icon-accent0-hover[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-hover :hover .jp-icon-accent1-hover[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-hover :hover .jp-icon-accent2-hover[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-hover :hover .jp-icon-accent3-hover[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-hover :hover .jp-icon-accent4-hover[stroke] {
stroke: var(--jp-layout-color4);
}
/* set the color of an icon to transparent */
.jp-icon-hover :hover .jp-icon-none-hover[fill] {
fill: none;
}
.jp-icon-hover :hover .jp-icon-none-hover[stroke] {
stroke: none;
}
/**
* inverse colors
*/
/* inverse recolor the primary elements of an icon */
.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[fill] {
fill: var(--jp-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[fill] {
fill: var(--jp-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[fill] {
fill: var(--jp-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[fill] {
fill: var(--jp-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[fill] {
fill: var(--jp-layout-color4);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon0-hover[stroke] {
stroke: var(--jp-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon1-hover[stroke] {
stroke: var(--jp-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon2-hover[stroke] {
stroke: var(--jp-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon3-hover[stroke] {
stroke: var(--jp-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon4-hover[stroke] {
stroke: var(--jp-layout-color4);
}
/* inverse recolor the accent elements of an icon */
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[fill] {
fill: var(--jp-inverse-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[fill] {
fill: var(--jp-inverse-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[fill] {
fill: var(--jp-inverse-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[fill] {
fill: var(--jp-inverse-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[fill] {
fill: var(--jp-inverse-layout-color4);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent0-hover[stroke] {
stroke: var(--jp-inverse-layout-color0);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent1-hover[stroke] {
stroke: var(--jp-inverse-layout-color1);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent2-hover[stroke] {
stroke: var(--jp-inverse-layout-color2);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent3-hover[stroke] {
stroke: var(--jp-inverse-layout-color3);
}
.jp-icon-hover.jp-icon-alt :hover .jp-icon-accent4-hover[stroke] {
stroke: var(--jp-inverse-layout-color4);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-IFrame {
width: 100%;
height: 100%;
}
.jp-IFrame > iframe {
border: none;
}
/*
When drag events occur, `lm-mod-override-cursor` is added to the body.
Because iframes steal all cursor events, the following two rules are necessary
to suppress pointer events while resize drags are occurring. There may be a
better solution to this problem.
*/
body.lm-mod-override-cursor .jp-IFrame {
position: relative;
}
body.lm-mod-override-cursor .jp-IFrame::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: transparent;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-HoverBox {
position: fixed;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-FormGroup-content fieldset {
border: none;
padding: 0;
min-width: 0;
width: 100%;
}
/* stylelint-disable selector-max-type */
.jp-FormGroup-content fieldset .jp-inputFieldWrapper input,
.jp-FormGroup-content fieldset .jp-inputFieldWrapper select,
.jp-FormGroup-content fieldset .jp-inputFieldWrapper textarea {
font-size: var(--jp-content-font-size2);
border-color: var(--jp-input-border-color);
border-style: solid;
border-radius: var(--jp-border-radius);
border-width: 1px;
padding: 6px 8px;
background: none;
color: var(--jp-ui-font-color0);
height: inherit;
}
.jp-FormGroup-content fieldset input[type='checkbox'] {
position: relative;
top: 2px;
margin-left: 0;
}
.jp-FormGroup-content button.jp-mod-styled {
cursor: pointer;
}
.jp-FormGroup-content .checkbox label {
cursor: pointer;
font-size: var(--jp-content-font-size1);
}
.jp-FormGroup-content .jp-root > fieldset > legend {
display: none;
}
.jp-FormGroup-content .jp-root > fieldset > p {
display: none;
}
/** copy of `input.jp-mod-styled:focus` style */
.jp-FormGroup-content fieldset input:focus,
.jp-FormGroup-content fieldset select:focus {
-moz-outline-radius: unset;
outline: var(--jp-border-width) solid var(--md-blue-500);
outline-offset: -1px;
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-FormGroup-content fieldset input:hover:not(:focus),
.jp-FormGroup-content fieldset select:hover:not(:focus) {
background-color: var(--jp-border-color2);
}
/* stylelint-enable selector-max-type */
.jp-FormGroup-content .checkbox .field-description {
/* Disable default description field for checkbox:
because other widgets do not have description fields,
we add descriptions to each widget on the field level.
*/
display: none;
}
.jp-FormGroup-content #root__description {
display: none;
}
.jp-FormGroup-content .jp-modifiedIndicator {
width: 5px;
background-color: var(--jp-brand-color2);
margin-top: 0;
margin-left: calc(var(--jp-private-settingeditor-modifier-indent) * -1);
flex-shrink: 0;
}
.jp-FormGroup-content .jp-modifiedIndicator.jp-errorIndicator {
background-color: var(--jp-error-color0);
margin-right: 0.5em;
}
/* RJSF ARRAY style */
.jp-arrayFieldWrapper legend {
font-size: var(--jp-content-font-size2);
color: var(--jp-ui-font-color0);
flex-basis: 100%;
padding: 4px 0;
font-weight: var(--jp-content-heading-font-weight);
border-bottom: 1px solid var(--jp-border-color2);
}
.jp-arrayFieldWrapper .field-description {
padding: 4px 0;
white-space: pre-wrap;
}
.jp-arrayFieldWrapper .array-item {
width: 100%;
border: 1px solid var(--jp-border-color2);
border-radius: 4px;
margin: 4px;
}
.jp-ArrayOperations {
display: flex;
margin-left: 8px;
}
.jp-ArrayOperationsButton {
margin: 2px;
}
.jp-ArrayOperationsButton .jp-icon3[fill] {
fill: var(--jp-ui-font-color0);
}
button.jp-ArrayOperationsButton.jp-mod-styled:disabled {
cursor: not-allowed;
opacity: 0.5;
}
/* RJSF form validation error */
.jp-FormGroup-content .validationErrors {
color: var(--jp-error-color0);
}
/* Hide panel level error as duplicated the field level error */
.jp-FormGroup-content .panel.errors {
display: none;
}
/* RJSF normal content (settings-editor) */
.jp-FormGroup-contentNormal {
display: flex;
align-items: center;
flex-wrap: wrap;
}
.jp-FormGroup-contentNormal .jp-FormGroup-contentItem {
margin-left: 7px;
color: var(--jp-ui-font-color0);
}
.jp-FormGroup-contentNormal .jp-FormGroup-description {
flex-basis: 100%;
padding: 4px 7px;
}
.jp-FormGroup-contentNormal .jp-FormGroup-default {
flex-basis: 100%;
padding: 4px 7px;
}
.jp-FormGroup-contentNormal .jp-FormGroup-fieldLabel {
font-size: var(--jp-content-font-size1);
font-weight: normal;
min-width: 120px;
}
.jp-FormGroup-contentNormal fieldset:not(:first-child) {
margin-left: 7px;
}
.jp-FormGroup-contentNormal .field-array-of-string .array-item {
/* Display `jp-ArrayOperations` buttons side-by-side with content except
for small screens where flex-wrap will place them one below the other.
*/
display: flex;
align-items: center;
flex-wrap: wrap;
}
.jp-FormGroup-contentNormal .jp-objectFieldWrapper .form-group {
padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent);
margin-top: 2px;
}
/* RJSF compact content (metadata-form) */
.jp-FormGroup-content.jp-FormGroup-contentCompact {
width: 100%;
}
.jp-FormGroup-contentCompact .form-group {
display: flex;
padding: 0.5em 0.2em 0.5em 0;
}
.jp-FormGroup-contentCompact
.jp-FormGroup-compactTitle
.jp-FormGroup-description {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color2);
}
.jp-FormGroup-contentCompact .jp-FormGroup-fieldLabel {
padding-bottom: 0.3em;
}
.jp-FormGroup-contentCompact .jp-inputFieldWrapper .form-control {
width: 100%;
box-sizing: border-box;
}
.jp-FormGroup-contentCompact .jp-arrayFieldWrapper .jp-FormGroup-compactTitle {
padding-bottom: 7px;
}
.jp-FormGroup-contentCompact
.jp-objectFieldWrapper
.jp-objectFieldWrapper
.form-group {
padding: 2px 8px 2px var(--jp-private-settingeditor-modifier-indent);
margin-top: 2px;
}
.jp-FormGroup-contentCompact ul.error-detail {
margin-block-start: 0.5em;
margin-block-end: 0.5em;
padding-inline-start: 1em;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-SidePanel {
display: flex;
flex-direction: column;
min-width: var(--jp-sidebar-min-width);
overflow-y: auto;
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
font-size: var(--jp-ui-font-size1);
}
.jp-SidePanel-header {
flex: 0 0 auto;
display: flex;
border-bottom: var(--jp-border-width) solid var(--jp-border-color2);
font-size: var(--jp-ui-font-size0);
font-weight: 600;
letter-spacing: 1px;
margin: 0;
padding: 2px;
text-transform: uppercase;
}
.jp-SidePanel-toolbar {
flex: 0 0 auto;
}
.jp-SidePanel-content {
flex: 1 1 auto;
}
.jp-SidePanel-toolbar,
.jp-AccordionPanel-toolbar {
height: var(--jp-private-toolbar-height);
}
.jp-SidePanel-toolbar.jp-Toolbar-micro {
display: none;
}
.lm-AccordionPanel .jp-AccordionPanel-title {
box-sizing: border-box;
line-height: 25px;
margin: 0;
display: flex;
align-items: center;
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
font-size: var(--jp-ui-font-size0);
}
.jp-AccordionPanel-title {
cursor: pointer;
user-select: none;
-moz-user-select: none;
-webkit-user-select: none;
text-transform: uppercase;
}
.lm-AccordionPanel[data-orientation='horizontal'] > .jp-AccordionPanel-title {
/* Title is rotated for horizontal accordion panel using CSS */
display: block;
transform-origin: top left;
transform: rotate(-90deg) translate(-100%);
}
.jp-AccordionPanel-title .lm-AccordionPanel-titleLabel {
user-select: none;
text-overflow: ellipsis;
white-space: nowrap;
overflow: hidden;
}
.jp-AccordionPanel-title .lm-AccordionPanel-titleCollapser {
transform: rotate(-90deg);
margin: auto 0;
height: 16px;
}
.jp-AccordionPanel-title.lm-mod-expanded .lm-AccordionPanel-titleCollapser {
transform: rotate(0deg);
}
.lm-AccordionPanel .jp-AccordionPanel-toolbar {
background: none;
box-shadow: none;
border: none;
margin-left: auto;
}
.lm-AccordionPanel .lm-SplitPanel-handle:hover {
background: var(--jp-layout-color3);
}
.jp-text-truncated {
overflow: hidden;
text-overflow: ellipsis;
white-space: nowrap;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Spinner {
position: absolute;
display: flex;
justify-content: center;
align-items: center;
z-index: 10;
left: 0;
top: 0;
width: 100%;
height: 100%;
background: var(--jp-layout-color0);
outline: none;
}
.jp-SpinnerContent {
font-size: 10px;
margin: 50px auto;
text-indent: -9999em;
width: 3em;
height: 3em;
border-radius: 50%;
background: var(--jp-brand-color3);
background: linear-gradient(
to right,
#f37626 10%,
rgba(255, 255, 255, 0) 42%
);
position: relative;
animation: load3 1s infinite linear, fadeIn 1s;
}
.jp-SpinnerContent::before {
width: 50%;
height: 50%;
background: #f37626;
border-radius: 100% 0 0;
position: absolute;
top: 0;
left: 0;
content: '';
}
.jp-SpinnerContent::after {
background: var(--jp-layout-color0);
width: 75%;
height: 75%;
border-radius: 50%;
content: '';
margin: auto;
position: absolute;
top: 0;
left: 0;
bottom: 0;
right: 0;
}
@keyframes fadeIn {
0% {
opacity: 0;
}
100% {
opacity: 1;
}
}
@keyframes load3 {
0% {
transform: rotate(0deg);
}
100% {
transform: rotate(360deg);
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
button.jp-mod-styled {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
border: none;
box-sizing: border-box;
text-align: center;
line-height: 32px;
height: 32px;
padding: 0 12px;
letter-spacing: 0.8px;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
input.jp-mod-styled {
background: var(--jp-input-background);
height: 28px;
box-sizing: border-box;
border: var(--jp-border-width) solid var(--jp-border-color1);
padding-left: 7px;
padding-right: 7px;
font-size: var(--jp-ui-font-size2);
color: var(--jp-ui-font-color0);
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
input[type='checkbox'].jp-mod-styled {
appearance: checkbox;
-webkit-appearance: checkbox;
-moz-appearance: checkbox;
height: auto;
}
input.jp-mod-styled:focus {
border: var(--jp-border-width) solid var(--md-blue-500);
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-select-wrapper {
display: flex;
position: relative;
flex-direction: column;
padding: 1px;
background-color: var(--jp-layout-color1);
box-sizing: border-box;
margin-bottom: 12px;
}
.jp-select-wrapper:not(.multiple) {
height: 28px;
}
.jp-select-wrapper.jp-mod-focused select.jp-mod-styled {
border: var(--jp-border-width) solid var(--jp-input-active-border-color);
box-shadow: var(--jp-input-box-shadow);
background-color: var(--jp-input-active-background);
}
select.jp-mod-styled:hover {
cursor: pointer;
color: var(--jp-ui-font-color0);
background-color: var(--jp-input-hover-background);
box-shadow: inset 0 0 1px rgba(0, 0, 0, 0.5);
}
select.jp-mod-styled {
flex: 1 1 auto;
width: 100%;
font-size: var(--jp-ui-font-size2);
background: var(--jp-input-background);
color: var(--jp-ui-font-color0);
padding: 0 25px 0 8px;
border: var(--jp-border-width) solid var(--jp-input-border-color);
border-radius: 0;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
}
select.jp-mod-styled:not([multiple]) {
height: 32px;
}
select.jp-mod-styled[multiple] {
max-height: 200px;
overflow-y: auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-switch {
display: flex;
align-items: center;
padding-left: 4px;
padding-right: 4px;
font-size: var(--jp-ui-font-size1);
background-color: transparent;
color: var(--jp-ui-font-color1);
border: none;
height: 20px;
}
.jp-switch:hover {
background-color: var(--jp-layout-color2);
}
.jp-switch-label {
margin-right: 5px;
font-family: var(--jp-ui-font-family);
}
.jp-switch-track {
cursor: pointer;
background-color: var(--jp-switch-color, var(--jp-border-color1));
-webkit-transition: 0.4s;
transition: 0.4s;
border-radius: 34px;
height: 16px;
width: 35px;
position: relative;
}
.jp-switch-track::before {
content: '';
position: absolute;
height: 10px;
width: 10px;
margin: 3px;
left: 0;
background-color: var(--jp-ui-inverse-font-color1);
-webkit-transition: 0.4s;
transition: 0.4s;
border-radius: 50%;
}
.jp-switch[aria-checked='true'] .jp-switch-track {
background-color: var(--jp-switch-true-position-color, var(--jp-warn-color0));
}
.jp-switch[aria-checked='true'] .jp-switch-track::before {
/* track width (35) - margins (3 + 3) - thumb width (10) */
left: 19px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
:root {
--jp-private-toolbar-height: calc(
28px + var(--jp-border-width)
); /* leave 28px for content */
}
.jp-Toolbar {
color: var(--jp-ui-font-color1);
flex: 0 0 auto;
display: flex;
flex-direction: row;
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
background: var(--jp-toolbar-background);
min-height: var(--jp-toolbar-micro-height);
padding: 2px;
z-index: 8;
overflow-x: hidden;
}
/* Toolbar items */
.jp-Toolbar > .jp-Toolbar-item.jp-Toolbar-spacer {
flex-grow: 1;
flex-shrink: 1;
}
.jp-Toolbar-item.jp-Toolbar-kernelStatus {
display: inline-block;
width: 32px;
background-repeat: no-repeat;
background-position: center;
background-size: 16px;
}
.jp-Toolbar > .jp-Toolbar-item {
flex: 0 0 auto;
display: flex;
padding-left: 1px;
padding-right: 1px;
font-size: var(--jp-ui-font-size1);
line-height: var(--jp-private-toolbar-height);
height: 100%;
}
/* Toolbar buttons */
/* This is the div we use to wrap the react component into a Widget */
div.jp-ToolbarButton {
color: transparent;
border: none;
box-sizing: border-box;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
padding: 0;
margin: 0;
}
button.jp-ToolbarButtonComponent {
background: var(--jp-layout-color1);
border: none;
box-sizing: border-box;
outline: none;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
padding: 0 6px;
margin: 0;
height: 24px;
border-radius: var(--jp-border-radius);
display: flex;
align-items: center;
text-align: center;
font-size: 14px;
min-width: unset;
min-height: unset;
}
button.jp-ToolbarButtonComponent:disabled {
opacity: 0.4;
}
button.jp-ToolbarButtonComponent > span {
padding: 0;
flex: 0 0 auto;
}
button.jp-ToolbarButtonComponent .jp-ToolbarButtonComponent-label {
font-size: var(--jp-ui-font-size1);
line-height: 100%;
padding-left: 2px;
color: var(--jp-ui-font-color1);
font-family: var(--jp-ui-font-family);
}
#jp-main-dock-panel[data-mode='single-document']
.jp-MainAreaWidget
> .jp-Toolbar.jp-Toolbar-micro {
padding: 0;
min-height: 0;
}
#jp-main-dock-panel[data-mode='single-document']
.jp-MainAreaWidget
> .jp-Toolbar {
border: none;
box-shadow: none;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-WindowedPanel-outer {
position: relative;
overflow-y: auto;
}
.jp-WindowedPanel-inner {
position: relative;
}
.jp-WindowedPanel-window {
position: absolute;
left: 0;
right: 0;
overflow: visible;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/* Sibling imports */
body {
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
}
/* Disable native link decoration styles everywhere outside of dialog boxes */
a {
text-decoration: unset;
color: unset;
}
a:hover {
text-decoration: unset;
color: unset;
}
/* Accessibility for links inside dialog box text */
.jp-Dialog-content a {
text-decoration: revert;
color: var(--jp-content-link-color);
}
.jp-Dialog-content a:hover {
text-decoration: revert;
}
/* Styles for ui-components */
.jp-Button {
color: var(--jp-ui-font-color2);
border-radius: var(--jp-border-radius);
padding: 0 12px;
font-size: var(--jp-ui-font-size1);
/* Copy from blueprint 3 */
display: inline-flex;
flex-direction: row;
border: none;
cursor: pointer;
align-items: center;
justify-content: center;
text-align: left;
vertical-align: middle;
min-height: 30px;
min-width: 30px;
}
.jp-Button:disabled {
cursor: not-allowed;
}
.jp-Button:empty {
padding: 0 !important;
}
.jp-Button.jp-mod-small {
min-height: 24px;
min-width: 24px;
font-size: 12px;
padding: 0 7px;
}
/* Use our own theme for hover styles */
.jp-Button.jp-mod-minimal:hover {
background-color: var(--jp-layout-color2);
}
.jp-Button.jp-mod-minimal {
background: none;
}
.jp-InputGroup {
display: block;
position: relative;
}
.jp-InputGroup input {
box-sizing: border-box;
border: none;
border-radius: 0;
background-color: transparent;
color: var(--jp-ui-font-color0);
box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color);
padding-bottom: 0;
padding-top: 0;
padding-left: 10px;
padding-right: 28px;
position: relative;
width: 100%;
-webkit-appearance: none;
-moz-appearance: none;
appearance: none;
font-size: 14px;
font-weight: 400;
height: 30px;
line-height: 30px;
outline: none;
vertical-align: middle;
}
.jp-InputGroup input:focus {
box-shadow: inset 0 0 0 var(--jp-border-width)
var(--jp-input-active-box-shadow-color),
inset 0 0 0 3px var(--jp-input-active-box-shadow-color);
}
.jp-InputGroup input:disabled {
cursor: not-allowed;
resize: block;
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color2);
}
.jp-InputGroup input:disabled ~ span {
cursor: not-allowed;
color: var(--jp-ui-font-color2);
}
.jp-InputGroup input::placeholder,
input::placeholder {
color: var(--jp-ui-font-color2);
}
.jp-InputGroupAction {
position: absolute;
bottom: 1px;
right: 0;
padding: 6px;
}
.jp-HTMLSelect.jp-DefaultStyle select {
background-color: initial;
border: none;
border-radius: 0;
box-shadow: none;
color: var(--jp-ui-font-color0);
display: block;
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
height: 24px;
line-height: 14px;
padding: 0 25px 0 10px;
text-align: left;
-moz-appearance: none;
-webkit-appearance: none;
}
.jp-HTMLSelect.jp-DefaultStyle select:disabled {
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color2);
cursor: not-allowed;
resize: block;
}
.jp-HTMLSelect.jp-DefaultStyle select:disabled ~ span {
cursor: not-allowed;
}
/* Use our own theme for hover and option styles */
/* stylelint-disable-next-line selector-max-type */
.jp-HTMLSelect.jp-DefaultStyle select:hover,
.jp-HTMLSelect.jp-DefaultStyle select > option {
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color0);
}
select {
box-sizing: border-box;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/
.jp-StatusBar-Widget {
display: flex;
align-items: center;
background: var(--jp-layout-color2);
min-height: var(--jp-statusbar-height);
justify-content: space-between;
padding: 0 10px;
}
.jp-StatusBar-Left {
display: flex;
align-items: center;
flex-direction: row;
}
.jp-StatusBar-Middle {
display: flex;
align-items: center;
}
.jp-StatusBar-Right {
display: flex;
align-items: center;
flex-direction: row-reverse;
}
.jp-StatusBar-Item {
max-height: var(--jp-statusbar-height);
margin: 0 2px;
height: var(--jp-statusbar-height);
white-space: nowrap;
text-overflow: ellipsis;
color: var(--jp-ui-font-color1);
padding: 0 6px;
}
.jp-mod-highlighted:hover {
background-color: var(--jp-layout-color3);
}
.jp-mod-clicked {
background-color: var(--jp-brand-color1);
}
.jp-mod-clicked:hover {
background-color: var(--jp-brand-color0);
}
.jp-mod-clicked .jp-StatusBar-TextItem {
color: var(--jp-ui-inverse-font-color1);
}
.jp-StatusBar-HoverItem {
box-shadow: '0px 4px 4px rgba(0, 0, 0, 0.25)';
}
.jp-StatusBar-TextItem {
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
line-height: 24px;
color: var(--jp-ui-font-color1);
}
.jp-StatusBar-GroupItem {
display: flex;
align-items: center;
flex-direction: row;
}
.jp-Statusbar-ProgressCircle svg {
display: block;
margin: 0 auto;
width: 16px;
height: 24px;
align-self: normal;
}
.jp-Statusbar-ProgressCircle path {
fill: var(--jp-inverse-layout-color3);
}
.jp-Statusbar-ProgressBar-progress-bar {
height: 10px;
width: 100px;
border: solid 0.25px var(--jp-brand-color2);
border-radius: 3px;
overflow: hidden;
align-self: center;
}
.jp-Statusbar-ProgressBar-progress-bar > div {
background-color: var(--jp-brand-color2);
background-image: linear-gradient(
-45deg,
rgba(255, 255, 255, 0.2) 25%,
transparent 25%,
transparent 50%,
rgba(255, 255, 255, 0.2) 50%,
rgba(255, 255, 255, 0.2) 75%,
transparent 75%,
transparent
);
background-size: 40px 40px;
float: left;
width: 0%;
height: 100%;
font-size: 12px;
line-height: 14px;
color: #fff;
text-align: center;
animation: jp-Statusbar-ExecutionTime-progress-bar 2s linear infinite;
}
.jp-Statusbar-ProgressBar-progress-bar p {
color: var(--jp-ui-font-color1);
font-family: var(--jp-ui-font-family);
font-size: var(--jp-ui-font-size1);
line-height: 10px;
width: 100px;
}
@keyframes jp-Statusbar-ExecutionTime-progress-bar {
0% {
background-position: 0 0;
}
100% {
background-position: 40px 40px;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
:root {
--jp-private-commandpalette-search-height: 28px;
}
/*-----------------------------------------------------------------------------
| Overall styles
|----------------------------------------------------------------------------*/
.lm-CommandPalette {
padding-bottom: 0;
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
}
/*-----------------------------------------------------------------------------
| Modal variant
|----------------------------------------------------------------------------*/
.jp-ModalCommandPalette {
position: absolute;
z-index: 10000;
top: 38px;
left: 30%;
margin: 0;
padding: 4px;
width: 40%;
box-shadow: var(--jp-elevation-z4);
border-radius: 4px;
background: var(--jp-layout-color0);
}
.jp-ModalCommandPalette .lm-CommandPalette {
max-height: 40vh;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-close-icon::after {
display: none;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-header {
display: none;
}
.jp-ModalCommandPalette .lm-CommandPalette .lm-CommandPalette-item {
margin-left: 4px;
margin-right: 4px;
}
.jp-ModalCommandPalette
.lm-CommandPalette
.lm-CommandPalette-item.lm-mod-disabled {
display: none;
}
/*-----------------------------------------------------------------------------
| Search
|----------------------------------------------------------------------------*/
.lm-CommandPalette-search {
padding: 4px;
background-color: var(--jp-layout-color1);
z-index: 2;
}
.lm-CommandPalette-wrapper {
overflow: overlay;
padding: 0 9px;
background-color: var(--jp-input-active-background);
height: 30px;
box-shadow: inset 0 0 0 var(--jp-border-width) var(--jp-input-border-color);
}
.lm-CommandPalette.lm-mod-focused .lm-CommandPalette-wrapper {
box-shadow: inset 0 0 0 1px var(--jp-input-active-box-shadow-color),
inset 0 0 0 3px var(--jp-input-active-box-shadow-color);
}
.jp-SearchIconGroup {
color: white;
background-color: var(--jp-brand-color1);
position: absolute;
top: 4px;
right: 4px;
padding: 5px 5px 1px;
}
.jp-SearchIconGroup svg {
height: 20px;
width: 20px;
}
.jp-SearchIconGroup .jp-icon3[fill] {
fill: var(--jp-layout-color0);
}
.lm-CommandPalette-input {
background: transparent;
width: calc(100% - 18px);
float: left;
border: none;
outline: none;
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
line-height: var(--jp-private-commandpalette-search-height);
}
.lm-CommandPalette-input::-webkit-input-placeholder,
.lm-CommandPalette-input::-moz-placeholder,
.lm-CommandPalette-input:-ms-input-placeholder {
color: var(--jp-ui-font-color2);
font-size: var(--jp-ui-font-size1);
}
/*-----------------------------------------------------------------------------
| Results
|----------------------------------------------------------------------------*/
.lm-CommandPalette-header:first-child {
margin-top: 0;
}
.lm-CommandPalette-header {
border-bottom: solid var(--jp-border-width) var(--jp-border-color2);
color: var(--jp-ui-font-color1);
cursor: pointer;
display: flex;
font-size: var(--jp-ui-font-size0);
font-weight: 600;
letter-spacing: 1px;
margin-top: 8px;
padding: 8px 0 8px 12px;
text-transform: uppercase;
}
.lm-CommandPalette-header.lm-mod-active {
background: var(--jp-layout-color2);
}
.lm-CommandPalette-header > mark {
background-color: transparent;
font-weight: bold;
color: var(--jp-ui-font-color1);
}
.lm-CommandPalette-item {
padding: 4px 12px 4px 4px;
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
font-weight: 400;
display: flex;
}
.lm-CommandPalette-item.lm-mod-disabled {
color: var(--jp-ui-font-color2);
}
.lm-CommandPalette-item.lm-mod-active {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.lm-CommandPalette-item.lm-mod-active .lm-CommandPalette-itemLabel > mark {
color: var(--jp-ui-inverse-font-color0);
}
.lm-CommandPalette-item.lm-mod-active .jp-icon-selectable[fill] {
fill: var(--jp-layout-color0);
}
.lm-CommandPalette-item.lm-mod-active:hover:not(.lm-mod-disabled) {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.lm-CommandPalette-item:hover:not(.lm-mod-active):not(.lm-mod-disabled) {
background: var(--jp-layout-color2);
}
.lm-CommandPalette-itemContent {
overflow: hidden;
}
.lm-CommandPalette-itemLabel > mark {
color: var(--jp-ui-font-color0);
background-color: transparent;
font-weight: bold;
}
.lm-CommandPalette-item.lm-mod-disabled mark {
color: var(--jp-ui-font-color2);
}
.lm-CommandPalette-item .lm-CommandPalette-itemIcon {
margin: 0 4px 0 0;
position: relative;
width: 16px;
top: 2px;
flex: 0 0 auto;
}
.lm-CommandPalette-item.lm-mod-disabled .lm-CommandPalette-itemIcon {
opacity: 0.6;
}
.lm-CommandPalette-item .lm-CommandPalette-itemShortcut {
flex: 0 0 auto;
}
.lm-CommandPalette-itemCaption {
display: none;
}
.lm-CommandPalette-content {
background-color: var(--jp-layout-color1);
}
.lm-CommandPalette-content:empty::after {
content: 'No results';
margin: auto;
margin-top: 20px;
width: 100px;
display: block;
font-size: var(--jp-ui-font-size2);
font-family: var(--jp-ui-font-family);
font-weight: lighter;
}
.lm-CommandPalette-emptyMessage {
text-align: center;
margin-top: 24px;
line-height: 1.32;
padding: 0 8px;
color: var(--jp-content-font-color3);
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Dialog {
position: absolute;
z-index: 10000;
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
top: 0;
left: 0;
margin: 0;
padding: 0;
width: 100%;
height: 100%;
background: var(--jp-dialog-background);
}
.jp-Dialog-content {
display: flex;
flex-direction: column;
margin-left: auto;
margin-right: auto;
background: var(--jp-layout-color1);
padding: 24px 24px 12px;
min-width: 300px;
min-height: 150px;
max-width: 1000px;
max-height: 500px;
box-sizing: border-box;
box-shadow: var(--jp-elevation-z20);
word-wrap: break-word;
border-radius: var(--jp-border-radius);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color1);
resize: both;
}
.jp-Dialog-content.jp-Dialog-content-small {
max-width: 500px;
}
.jp-Dialog-button {
overflow: visible;
}
button.jp-Dialog-button:focus {
outline: 1px solid var(--jp-brand-color1);
outline-offset: 4px;
-moz-outline-radius: 0;
}
button.jp-Dialog-button:focus::-moz-focus-inner {
border: 0;
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus,
button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus,
button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus {
outline-offset: 4px;
-moz-outline-radius: 0;
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-accept:focus {
outline: 1px solid var(--jp-accept-color-normal, var(--jp-brand-color1));
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-warn:focus {
outline: 1px solid var(--jp-warn-color-normal, var(--jp-error-color1));
}
button.jp-Dialog-button.jp-mod-styled.jp-mod-reject:focus {
outline: 1px solid var(--jp-reject-color-normal, var(--md-grey-600));
}
button.jp-Dialog-close-button {
padding: 0;
height: 100%;
min-width: unset;
min-height: unset;
}
.jp-Dialog-header {
display: flex;
justify-content: space-between;
flex: 0 0 auto;
padding-bottom: 12px;
font-size: var(--jp-ui-font-size3);
font-weight: 400;
color: var(--jp-ui-font-color1);
}
.jp-Dialog-body {
display: flex;
flex-direction: column;
flex: 1 1 auto;
font-size: var(--jp-ui-font-size1);
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
overflow: auto;
}
.jp-Dialog-footer {
display: flex;
flex-direction: row;
justify-content: flex-end;
align-items: center;
flex: 0 0 auto;
margin-left: -12px;
margin-right: -12px;
padding: 12px;
}
.jp-Dialog-checkbox {
padding-right: 5px;
}
.jp-Dialog-checkbox > input:focus-visible {
outline: 1px solid var(--jp-input-active-border-color);
outline-offset: 1px;
}
.jp-Dialog-spacer {
flex: 1 1 auto;
}
.jp-Dialog-title {
overflow: hidden;
white-space: nowrap;
text-overflow: ellipsis;
}
.jp-Dialog-body > .jp-select-wrapper {
width: 100%;
}
.jp-Dialog-body > button {
padding: 0 16px;
}
.jp-Dialog-body > label {
line-height: 1.4;
color: var(--jp-ui-font-color0);
}
.jp-Dialog-button.jp-mod-styled:not(:last-child) {
margin-right: 12px;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-Input-Boolean-Dialog {
flex-direction: row-reverse;
align-items: end;
width: 100%;
}
.jp-Input-Boolean-Dialog > label {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-MainAreaWidget > :focus {
outline: none;
}
.jp-MainAreaWidget .jp-MainAreaWidget-error {
padding: 6px;
}
.jp-MainAreaWidget .jp-MainAreaWidget-error > pre {
width: auto;
padding: 10px;
background: var(--jp-error-color3);
border: var(--jp-border-width) solid var(--jp-error-color1);
border-radius: var(--jp-border-radius);
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
white-space: pre-wrap;
word-wrap: break-word;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
/**
* google-material-color v1.2.6
* https://github.com/danlevan/google-material-color
*/
:root {
--md-red-50: #ffebee;
--md-red-100: #ffcdd2;
--md-red-200: #ef9a9a;
--md-red-300: #e57373;
--md-red-400: #ef5350;
--md-red-500: #f44336;
--md-red-600: #e53935;
--md-red-700: #d32f2f;
--md-red-800: #c62828;
--md-red-900: #b71c1c;
--md-red-A100: #ff8a80;
--md-red-A200: #ff5252;
--md-red-A400: #ff1744;
--md-red-A700: #d50000;
--md-pink-50: #fce4ec;
--md-pink-100: #f8bbd0;
--md-pink-200: #f48fb1;
--md-pink-300: #f06292;
--md-pink-400: #ec407a;
--md-pink-500: #e91e63;
--md-pink-600: #d81b60;
--md-pink-700: #c2185b;
--md-pink-800: #ad1457;
--md-pink-900: #880e4f;
--md-pink-A100: #ff80ab;
--md-pink-A200: #ff4081;
--md-pink-A400: #f50057;
--md-pink-A700: #c51162;
--md-purple-50: #f3e5f5;
--md-purple-100: #e1bee7;
--md-purple-200: #ce93d8;
--md-purple-300: #ba68c8;
--md-purple-400: #ab47bc;
--md-purple-500: #9c27b0;
--md-purple-600: #8e24aa;
--md-purple-700: #7b1fa2;
--md-purple-800: #6a1b9a;
--md-purple-900: #4a148c;
--md-purple-A100: #ea80fc;
--md-purple-A200: #e040fb;
--md-purple-A400: #d500f9;
--md-purple-A700: #a0f;
--md-deep-purple-50: #ede7f6;
--md-deep-purple-100: #d1c4e9;
--md-deep-purple-200: #b39ddb;
--md-deep-purple-300: #9575cd;
--md-deep-purple-400: #7e57c2;
--md-deep-purple-500: #673ab7;
--md-deep-purple-600: #5e35b1;
--md-deep-purple-700: #512da8;
--md-deep-purple-800: #4527a0;
--md-deep-purple-900: #311b92;
--md-deep-purple-A100: #b388ff;
--md-deep-purple-A200: #7c4dff;
--md-deep-purple-A400: #651fff;
--md-deep-purple-A700: #6200ea;
--md-indigo-50: #e8eaf6;
--md-indigo-100: #c5cae9;
--md-indigo-200: #9fa8da;
--md-indigo-300: #7986cb;
--md-indigo-400: #5c6bc0;
--md-indigo-500: #3f51b5;
--md-indigo-600: #3949ab;
--md-indigo-700: #303f9f;
--md-indigo-800: #283593;
--md-indigo-900: #1a237e;
--md-indigo-A100: #8c9eff;
--md-indigo-A200: #536dfe;
--md-indigo-A400: #3d5afe;
--md-indigo-A700: #304ffe;
--md-blue-50: #e3f2fd;
--md-blue-100: #bbdefb;
--md-blue-200: #90caf9;
--md-blue-300: #64b5f6;
--md-blue-400: #42a5f5;
--md-blue-500: #2196f3;
--md-blue-600: #1e88e5;
--md-blue-700: #1976d2;
--md-blue-800: #1565c0;
--md-blue-900: #0d47a1;
--md-blue-A100: #82b1ff;
--md-blue-A200: #448aff;
--md-blue-A400: #2979ff;
--md-blue-A700: #2962ff;
--md-light-blue-50: #e1f5fe;
--md-light-blue-100: #b3e5fc;
--md-light-blue-200: #81d4fa;
--md-light-blue-300: #4fc3f7;
--md-light-blue-400: #29b6f6;
--md-light-blue-500: #03a9f4;
--md-light-blue-600: #039be5;
--md-light-blue-700: #0288d1;
--md-light-blue-800: #0277bd;
--md-light-blue-900: #01579b;
--md-light-blue-A100: #80d8ff;
--md-light-blue-A200: #40c4ff;
--md-light-blue-A400: #00b0ff;
--md-light-blue-A700: #0091ea;
--md-cyan-50: #e0f7fa;
--md-cyan-100: #b2ebf2;
--md-cyan-200: #80deea;
--md-cyan-300: #4dd0e1;
--md-cyan-400: #26c6da;
--md-cyan-500: #00bcd4;
--md-cyan-600: #00acc1;
--md-cyan-700: #0097a7;
--md-cyan-800: #00838f;
--md-cyan-900: #006064;
--md-cyan-A100: #84ffff;
--md-cyan-A200: #18ffff;
--md-cyan-A400: #00e5ff;
--md-cyan-A700: #00b8d4;
--md-teal-50: #e0f2f1;
--md-teal-100: #b2dfdb;
--md-teal-200: #80cbc4;
--md-teal-300: #4db6ac;
--md-teal-400: #26a69a;
--md-teal-500: #009688;
--md-teal-600: #00897b;
--md-teal-700: #00796b;
--md-teal-800: #00695c;
--md-teal-900: #004d40;
--md-teal-A100: #a7ffeb;
--md-teal-A200: #64ffda;
--md-teal-A400: #1de9b6;
--md-teal-A700: #00bfa5;
--md-green-50: #e8f5e9;
--md-green-100: #c8e6c9;
--md-green-200: #a5d6a7;
--md-green-300: #81c784;
--md-green-400: #66bb6a;
--md-green-500: #4caf50;
--md-green-600: #43a047;
--md-green-700: #388e3c;
--md-green-800: #2e7d32;
--md-green-900: #1b5e20;
--md-green-A100: #b9f6ca;
--md-green-A200: #69f0ae;
--md-green-A400: #00e676;
--md-green-A700: #00c853;
--md-light-green-50: #f1f8e9;
--md-light-green-100: #dcedc8;
--md-light-green-200: #c5e1a5;
--md-light-green-300: #aed581;
--md-light-green-400: #9ccc65;
--md-light-green-500: #8bc34a;
--md-light-green-600: #7cb342;
--md-light-green-700: #689f38;
--md-light-green-800: #558b2f;
--md-light-green-900: #33691e;
--md-light-green-A100: #ccff90;
--md-light-green-A200: #b2ff59;
--md-light-green-A400: #76ff03;
--md-light-green-A700: #64dd17;
--md-lime-50: #f9fbe7;
--md-lime-100: #f0f4c3;
--md-lime-200: #e6ee9c;
--md-lime-300: #dce775;
--md-lime-400: #d4e157;
--md-lime-500: #cddc39;
--md-lime-600: #c0ca33;
--md-lime-700: #afb42b;
--md-lime-800: #9e9d24;
--md-lime-900: #827717;
--md-lime-A100: #f4ff81;
--md-lime-A200: #eeff41;
--md-lime-A400: #c6ff00;
--md-lime-A700: #aeea00;
--md-yellow-50: #fffde7;
--md-yellow-100: #fff9c4;
--md-yellow-200: #fff59d;
--md-yellow-300: #fff176;
--md-yellow-400: #ffee58;
--md-yellow-500: #ffeb3b;
--md-yellow-600: #fdd835;
--md-yellow-700: #fbc02d;
--md-yellow-800: #f9a825;
--md-yellow-900: #f57f17;
--md-yellow-A100: #ffff8d;
--md-yellow-A200: #ff0;
--md-yellow-A400: #ffea00;
--md-yellow-A700: #ffd600;
--md-amber-50: #fff8e1;
--md-amber-100: #ffecb3;
--md-amber-200: #ffe082;
--md-amber-300: #ffd54f;
--md-amber-400: #ffca28;
--md-amber-500: #ffc107;
--md-amber-600: #ffb300;
--md-amber-700: #ffa000;
--md-amber-800: #ff8f00;
--md-amber-900: #ff6f00;
--md-amber-A100: #ffe57f;
--md-amber-A200: #ffd740;
--md-amber-A400: #ffc400;
--md-amber-A700: #ffab00;
--md-orange-50: #fff3e0;
--md-orange-100: #ffe0b2;
--md-orange-200: #ffcc80;
--md-orange-300: #ffb74d;
--md-orange-400: #ffa726;
--md-orange-500: #ff9800;
--md-orange-600: #fb8c00;
--md-orange-700: #f57c00;
--md-orange-800: #ef6c00;
--md-orange-900: #e65100;
--md-orange-A100: #ffd180;
--md-orange-A200: #ffab40;
--md-orange-A400: #ff9100;
--md-orange-A700: #ff6d00;
--md-deep-orange-50: #fbe9e7;
--md-deep-orange-100: #ffccbc;
--md-deep-orange-200: #ffab91;
--md-deep-orange-300: #ff8a65;
--md-deep-orange-400: #ff7043;
--md-deep-orange-500: #ff5722;
--md-deep-orange-600: #f4511e;
--md-deep-orange-700: #e64a19;
--md-deep-orange-800: #d84315;
--md-deep-orange-900: #bf360c;
--md-deep-orange-A100: #ff9e80;
--md-deep-orange-A200: #ff6e40;
--md-deep-orange-A400: #ff3d00;
--md-deep-orange-A700: #dd2c00;
--md-brown-50: #efebe9;
--md-brown-100: #d7ccc8;
--md-brown-200: #bcaaa4;
--md-brown-300: #a1887f;
--md-brown-400: #8d6e63;
--md-brown-500: #795548;
--md-brown-600: #6d4c41;
--md-brown-700: #5d4037;
--md-brown-800: #4e342e;
--md-brown-900: #3e2723;
--md-grey-50: #fafafa;
--md-grey-100: #f5f5f5;
--md-grey-200: #eee;
--md-grey-300: #e0e0e0;
--md-grey-400: #bdbdbd;
--md-grey-500: #9e9e9e;
--md-grey-600: #757575;
--md-grey-700: #616161;
--md-grey-800: #424242;
--md-grey-900: #212121;
--md-blue-grey-50: #eceff1;
--md-blue-grey-100: #cfd8dc;
--md-blue-grey-200: #b0bec5;
--md-blue-grey-300: #90a4ae;
--md-blue-grey-400: #78909c;
--md-blue-grey-500: #607d8b;
--md-blue-grey-600: #546e7a;
--md-blue-grey-700: #455a64;
--md-blue-grey-800: #37474f;
--md-blue-grey-900: #263238;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2017, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| RenderedText
|----------------------------------------------------------------------------*/
:root {
/* This is the padding value to fill the gaps between lines containing spans with background color. */
--jp-private-code-span-padding: calc(
(var(--jp-code-line-height) - 1) * var(--jp-code-font-size) / 2
);
}
.jp-RenderedText {
text-align: left;
padding-left: var(--jp-code-padding);
line-height: var(--jp-code-line-height);
font-family: var(--jp-code-font-family);
}
.jp-RenderedText pre,
.jp-RenderedJavaScript pre,
.jp-RenderedHTMLCommon pre {
color: var(--jp-content-font-color1);
font-size: var(--jp-code-font-size);
border: none;
margin: 0;
padding: 0;
}
.jp-RenderedText pre a:link {
text-decoration: none;
color: var(--jp-content-link-color);
}
.jp-RenderedText pre a:hover {
text-decoration: underline;
color: var(--jp-content-link-color);
}
.jp-RenderedText pre a:visited {
text-decoration: none;
color: var(--jp-content-link-color);
}
/* console foregrounds and backgrounds */
.jp-RenderedText pre .ansi-black-fg {
color: #3e424d;
}
.jp-RenderedText pre .ansi-red-fg {
color: #e75c58;
}
.jp-RenderedText pre .ansi-green-fg {
color: #00a250;
}
.jp-RenderedText pre .ansi-yellow-fg {
color: #ddb62b;
}
.jp-RenderedText pre .ansi-blue-fg {
color: #208ffb;
}
.jp-RenderedText pre .ansi-magenta-fg {
color: #d160c4;
}
.jp-RenderedText pre .ansi-cyan-fg {
color: #60c6c8;
}
.jp-RenderedText pre .ansi-white-fg {
color: #c5c1b4;
}
.jp-RenderedText pre .ansi-black-bg {
background-color: #3e424d;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-red-bg {
background-color: #e75c58;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-green-bg {
background-color: #00a250;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-yellow-bg {
background-color: #ddb62b;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-blue-bg {
background-color: #208ffb;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-magenta-bg {
background-color: #d160c4;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-cyan-bg {
background-color: #60c6c8;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-white-bg {
background-color: #c5c1b4;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-black-intense-fg {
color: #282c36;
}
.jp-RenderedText pre .ansi-red-intense-fg {
color: #b22b31;
}
.jp-RenderedText pre .ansi-green-intense-fg {
color: #007427;
}
.jp-RenderedText pre .ansi-yellow-intense-fg {
color: #b27d12;
}
.jp-RenderedText pre .ansi-blue-intense-fg {
color: #0065ca;
}
.jp-RenderedText pre .ansi-magenta-intense-fg {
color: #a03196;
}
.jp-RenderedText pre .ansi-cyan-intense-fg {
color: #258f8f;
}
.jp-RenderedText pre .ansi-white-intense-fg {
color: #a1a6b2;
}
.jp-RenderedText pre .ansi-black-intense-bg {
background-color: #282c36;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-red-intense-bg {
background-color: #b22b31;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-green-intense-bg {
background-color: #007427;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-yellow-intense-bg {
background-color: #b27d12;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-blue-intense-bg {
background-color: #0065ca;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-magenta-intense-bg {
background-color: #a03196;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-cyan-intense-bg {
background-color: #258f8f;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-white-intense-bg {
background-color: #a1a6b2;
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-default-inverse-fg {
color: var(--jp-ui-inverse-font-color0);
}
.jp-RenderedText pre .ansi-default-inverse-bg {
background-color: var(--jp-inverse-layout-color0);
padding: var(--jp-private-code-span-padding) 0;
}
.jp-RenderedText pre .ansi-bold {
font-weight: bold;
}
.jp-RenderedText pre .ansi-underline {
text-decoration: underline;
}
.jp-RenderedText[data-mime-type='application/vnd.jupyter.stderr'] {
background: var(--jp-rendermime-error-background);
padding-top: var(--jp-code-padding);
}
/*-----------------------------------------------------------------------------
| RenderedLatex
|----------------------------------------------------------------------------*/
.jp-RenderedLatex {
color: var(--jp-content-font-color1);
font-size: var(--jp-content-font-size1);
line-height: var(--jp-content-line-height);
}
/* Left-justify outputs.*/
.jp-OutputArea-output.jp-RenderedLatex {
padding: var(--jp-code-padding);
text-align: left;
}
/*-----------------------------------------------------------------------------
| RenderedHTML
|----------------------------------------------------------------------------*/
.jp-RenderedHTMLCommon {
color: var(--jp-content-font-color1);
font-family: var(--jp-content-font-family);
font-size: var(--jp-content-font-size1);
line-height: var(--jp-content-line-height);
/* Give a bit more R padding on Markdown text to keep line lengths reasonable */
padding-right: 20px;
}
.jp-RenderedHTMLCommon em {
font-style: italic;
}
.jp-RenderedHTMLCommon strong {
font-weight: bold;
}
.jp-RenderedHTMLCommon u {
text-decoration: underline;
}
.jp-RenderedHTMLCommon a:link {
text-decoration: none;
color: var(--jp-content-link-color);
}
.jp-RenderedHTMLCommon a:hover {
text-decoration: underline;
color: var(--jp-content-link-color);
}
.jp-RenderedHTMLCommon a:visited {
text-decoration: none;
color: var(--jp-content-link-color);
}
/* Headings */
.jp-RenderedHTMLCommon h1,
.jp-RenderedHTMLCommon h2,
.jp-RenderedHTMLCommon h3,
.jp-RenderedHTMLCommon h4,
.jp-RenderedHTMLCommon h5,
.jp-RenderedHTMLCommon h6 {
line-height: var(--jp-content-heading-line-height);
font-weight: var(--jp-content-heading-font-weight);
font-style: normal;
margin: var(--jp-content-heading-margin-top) 0
var(--jp-content-heading-margin-bottom) 0;
}
.jp-RenderedHTMLCommon h1:first-child,
.jp-RenderedHTMLCommon h2:first-child,
.jp-RenderedHTMLCommon h3:first-child,
.jp-RenderedHTMLCommon h4:first-child,
.jp-RenderedHTMLCommon h5:first-child,
.jp-RenderedHTMLCommon h6:first-child {
margin-top: calc(0.5 * var(--jp-content-heading-margin-top));
}
.jp-RenderedHTMLCommon h1:last-child,
.jp-RenderedHTMLCommon h2:last-child,
.jp-RenderedHTMLCommon h3:last-child,
.jp-RenderedHTMLCommon h4:last-child,
.jp-RenderedHTMLCommon h5:last-child,
.jp-RenderedHTMLCommon h6:last-child {
margin-bottom: calc(0.5 * var(--jp-content-heading-margin-bottom));
}
.jp-RenderedHTMLCommon h1 {
font-size: var(--jp-content-font-size5);
}
.jp-RenderedHTMLCommon h2 {
font-size: var(--jp-content-font-size4);
}
.jp-RenderedHTMLCommon h3 {
font-size: var(--jp-content-font-size3);
}
.jp-RenderedHTMLCommon h4 {
font-size: var(--jp-content-font-size2);
}
.jp-RenderedHTMLCommon h5 {
font-size: var(--jp-content-font-size1);
}
.jp-RenderedHTMLCommon h6 {
font-size: var(--jp-content-font-size0);
}
/* Lists */
/* stylelint-disable selector-max-type, selector-max-compound-selectors */
.jp-RenderedHTMLCommon ul:not(.list-inline),
.jp-RenderedHTMLCommon ol:not(.list-inline) {
padding-left: 2em;
}
.jp-RenderedHTMLCommon ul {
list-style: disc;
}
.jp-RenderedHTMLCommon ul ul {
list-style: square;
}
.jp-RenderedHTMLCommon ul ul ul {
list-style: circle;
}
.jp-RenderedHTMLCommon ol {
list-style: decimal;
}
.jp-RenderedHTMLCommon ol ol {
list-style: upper-alpha;
}
.jp-RenderedHTMLCommon ol ol ol {
list-style: lower-alpha;
}
.jp-RenderedHTMLCommon ol ol ol ol {
list-style: lower-roman;
}
.jp-RenderedHTMLCommon ol ol ol ol ol {
list-style: decimal;
}
.jp-RenderedHTMLCommon ol,
.jp-RenderedHTMLCommon ul {
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon ul ul,
.jp-RenderedHTMLCommon ul ol,
.jp-RenderedHTMLCommon ol ul,
.jp-RenderedHTMLCommon ol ol {
margin-bottom: 0;
}
/* stylelint-enable selector-max-type, selector-max-compound-selectors */
.jp-RenderedHTMLCommon hr {
color: var(--jp-border-color2);
background-color: var(--jp-border-color1);
margin-top: 1em;
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon > pre {
margin: 1.5em 2em;
}
.jp-RenderedHTMLCommon pre,
.jp-RenderedHTMLCommon code {
border: 0;
background-color: var(--jp-layout-color0);
color: var(--jp-content-font-color1);
font-family: var(--jp-code-font-family);
font-size: inherit;
line-height: var(--jp-code-line-height);
padding: 0;
white-space: pre-wrap;
}
.jp-RenderedHTMLCommon :not(pre) > code {
background-color: var(--jp-layout-color2);
padding: 1px 5px;
}
/* Tables */
.jp-RenderedHTMLCommon table {
border-collapse: collapse;
border-spacing: 0;
border: none;
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
table-layout: fixed;
margin-left: auto;
margin-bottom: 1em;
margin-right: auto;
}
.jp-RenderedHTMLCommon thead {
border-bottom: var(--jp-border-width) solid var(--jp-border-color1);
vertical-align: bottom;
}
.jp-RenderedHTMLCommon td,
.jp-RenderedHTMLCommon th,
.jp-RenderedHTMLCommon tr {
vertical-align: middle;
padding: 0.5em;
line-height: normal;
white-space: normal;
max-width: none;
border: none;
}
.jp-RenderedMarkdown.jp-RenderedHTMLCommon td,
.jp-RenderedMarkdown.jp-RenderedHTMLCommon th {
max-width: none;
}
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon td,
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon th,
:not(.jp-RenderedMarkdown).jp-RenderedHTMLCommon tr {
text-align: right;
}
.jp-RenderedHTMLCommon th {
font-weight: bold;
}
.jp-RenderedHTMLCommon tbody tr:nth-child(odd) {
background: var(--jp-layout-color0);
}
.jp-RenderedHTMLCommon tbody tr:nth-child(even) {
background: var(--jp-rendermime-table-row-background);
}
.jp-RenderedHTMLCommon tbody tr:hover {
background: var(--jp-rendermime-table-row-hover-background);
}
.jp-RenderedHTMLCommon p {
text-align: left;
margin: 0;
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon img {
-moz-force-broken-image-icon: 1;
}
/* Restrict to direct children as other images could be nested in other content. */
.jp-RenderedHTMLCommon > img {
display: block;
margin-left: 0;
margin-right: 0;
margin-bottom: 1em;
}
/* Change color behind transparent images if they need it... */
[data-jp-theme-light='false'] .jp-RenderedImage img.jp-needs-light-background {
background-color: var(--jp-inverse-layout-color1);
}
[data-jp-theme-light='true'] .jp-RenderedImage img.jp-needs-dark-background {
background-color: var(--jp-inverse-layout-color1);
}
.jp-RenderedHTMLCommon img,
.jp-RenderedImage img,
.jp-RenderedHTMLCommon svg,
.jp-RenderedSVG svg {
max-width: 100%;
height: auto;
}
.jp-RenderedHTMLCommon img.jp-mod-unconfined,
.jp-RenderedImage img.jp-mod-unconfined,
.jp-RenderedHTMLCommon svg.jp-mod-unconfined,
.jp-RenderedSVG svg.jp-mod-unconfined {
max-width: none;
}
.jp-RenderedHTMLCommon .alert {
padding: var(--jp-notebook-padding);
border: var(--jp-border-width) solid transparent;
border-radius: var(--jp-border-radius);
margin-bottom: 1em;
}
.jp-RenderedHTMLCommon .alert-info {
color: var(--jp-info-color0);
background-color: var(--jp-info-color3);
border-color: var(--jp-info-color2);
}
.jp-RenderedHTMLCommon .alert-info hr {
border-color: var(--jp-info-color3);
}
.jp-RenderedHTMLCommon .alert-info > p:last-child,
.jp-RenderedHTMLCommon .alert-info > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon .alert-warning {
color: var(--jp-warn-color0);
background-color: var(--jp-warn-color3);
border-color: var(--jp-warn-color2);
}
.jp-RenderedHTMLCommon .alert-warning hr {
border-color: var(--jp-warn-color3);
}
.jp-RenderedHTMLCommon .alert-warning > p:last-child,
.jp-RenderedHTMLCommon .alert-warning > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon .alert-success {
color: var(--jp-success-color0);
background-color: var(--jp-success-color3);
border-color: var(--jp-success-color2);
}
.jp-RenderedHTMLCommon .alert-success hr {
border-color: var(--jp-success-color3);
}
.jp-RenderedHTMLCommon .alert-success > p:last-child,
.jp-RenderedHTMLCommon .alert-success > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon .alert-danger {
color: var(--jp-error-color0);
background-color: var(--jp-error-color3);
border-color: var(--jp-error-color2);
}
.jp-RenderedHTMLCommon .alert-danger hr {
border-color: var(--jp-error-color3);
}
.jp-RenderedHTMLCommon .alert-danger > p:last-child,
.jp-RenderedHTMLCommon .alert-danger > ul:last-child {
margin-bottom: 0;
}
.jp-RenderedHTMLCommon blockquote {
margin: 1em 2em;
padding: 0 1em;
border-left: 5px solid var(--jp-border-color2);
}
a.jp-InternalAnchorLink {
visibility: hidden;
margin-left: 8px;
color: var(--md-blue-800);
}
h1:hover .jp-InternalAnchorLink,
h2:hover .jp-InternalAnchorLink,
h3:hover .jp-InternalAnchorLink,
h4:hover .jp-InternalAnchorLink,
h5:hover .jp-InternalAnchorLink,
h6:hover .jp-InternalAnchorLink {
visibility: visible;
}
.jp-RenderedHTMLCommon kbd {
background-color: var(--jp-rendermime-table-row-background);
border: 1px solid var(--jp-border-color0);
border-bottom-color: var(--jp-border-color2);
border-radius: 3px;
box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
display: inline-block;
font-size: var(--jp-ui-font-size0);
line-height: 1em;
padding: 0.2em 0.5em;
}
/* Most direct children of .jp-RenderedHTMLCommon have a margin-bottom of 1.0.
* At the bottom of cells this is a bit too much as there is also spacing
* between cells. Going all the way to 0 gets too tight between markdown and
* code cells.
*/
.jp-RenderedHTMLCommon > *:last-child {
margin-bottom: 0.5em;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Copyright (c) 2014-2017, PhosphorJS Contributors
|
| Distributed under the terms of the BSD 3-Clause License.
|
| The full license is in the file LICENSE, distributed with this software.
|----------------------------------------------------------------------------*/
.lm-cursor-backdrop {
position: fixed;
width: 200px;
height: 200px;
margin-top: -100px;
margin-left: -100px;
will-change: transform;
z-index: 100;
}
.lm-mod-drag-image {
will-change: transform;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-lineFormSearch {
padding: 4px 12px;
background-color: var(--jp-layout-color2);
box-shadow: var(--jp-toolbar-box-shadow);
z-index: 2;
font-size: var(--jp-ui-font-size1);
}
.jp-lineFormCaption {
font-size: var(--jp-ui-font-size0);
line-height: var(--jp-ui-font-size1);
margin-top: 4px;
color: var(--jp-ui-font-color0);
}
.jp-baseLineForm {
border: none;
border-radius: 0;
position: absolute;
background-size: 16px;
background-repeat: no-repeat;
background-position: center;
outline: none;
}
.jp-lineFormButtonContainer {
top: 4px;
right: 8px;
height: 24px;
padding: 0 12px;
width: 12px;
}
.jp-lineFormButtonIcon {
top: 0;
right: 0;
background-color: var(--jp-brand-color1);
height: 100%;
width: 100%;
box-sizing: border-box;
padding: 4px 6px;
}
.jp-lineFormButton {
top: 0;
right: 0;
background-color: transparent;
height: 100%;
width: 100%;
box-sizing: border-box;
}
.jp-lineFormWrapper {
overflow: hidden;
padding: 0 8px;
border: 1px solid var(--jp-border-color0);
background-color: var(--jp-input-active-background);
height: 22px;
}
.jp-lineFormWrapperFocusWithin {
border: var(--jp-border-width) solid var(--md-blue-500);
box-shadow: inset 0 0 4px var(--md-blue-300);
}
.jp-lineFormInput {
background: transparent;
width: 200px;
height: 100%;
border: none;
outline: none;
color: var(--jp-ui-font-color0);
line-height: 28px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) 2014-2016, Jupyter Development Team.
|
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-JSONEditor {
display: flex;
flex-direction: column;
width: 100%;
}
.jp-JSONEditor-host {
flex: 1 1 auto;
border: var(--jp-border-width) solid var(--jp-input-border-color);
border-radius: 0;
background: var(--jp-layout-color0);
min-height: 50px;
padding: 1px;
}
.jp-JSONEditor.jp-mod-error .jp-JSONEditor-host {
border-color: red;
outline-color: red;
}
.jp-JSONEditor-header {
display: flex;
flex: 1 0 auto;
padding: 0 0 0 12px;
}
.jp-JSONEditor-header label {
flex: 0 0 auto;
}
.jp-JSONEditor-commitButton {
height: 16px;
width: 16px;
background-size: 18px;
background-repeat: no-repeat;
background-position: center;
}
.jp-JSONEditor-host.jp-mod-focused {
background-color: var(--jp-input-active-background);
border: 1px solid var(--jp-input-active-border-color);
box-shadow: var(--jp-input-box-shadow);
}
.jp-Editor.jp-mod-dropTarget {
border: var(--jp-border-width) solid var(--jp-input-active-border-color);
box-shadow: var(--jp-input-box-shadow);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-DocumentSearch-input {
border: none;
outline: none;
color: var(--jp-ui-font-color0);
font-size: var(--jp-ui-font-size1);
background-color: var(--jp-layout-color0);
font-family: var(--jp-ui-font-family);
padding: 2px 1px;
resize: none;
}
.jp-DocumentSearch-overlay {
position: absolute;
background-color: var(--jp-toolbar-background);
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
border-left: var(--jp-border-width) solid var(--jp-toolbar-border-color);
top: 0;
right: 0;
z-index: 7;
min-width: 405px;
padding: 2px;
font-size: var(--jp-ui-font-size1);
--jp-private-document-search-button-height: 20px;
}
.jp-DocumentSearch-overlay button {
background-color: var(--jp-toolbar-background);
outline: 0;
}
.jp-DocumentSearch-overlay button:hover {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-overlay button:active {
background-color: var(--jp-layout-color3);
}
.jp-DocumentSearch-overlay-row {
display: flex;
align-items: center;
margin-bottom: 2px;
}
.jp-DocumentSearch-button-content {
display: inline-block;
cursor: pointer;
box-sizing: border-box;
width: 100%;
height: 100%;
}
.jp-DocumentSearch-button-content svg {
width: 100%;
height: 100%;
}
.jp-DocumentSearch-input-wrapper {
border: var(--jp-border-width) solid var(--jp-border-color0);
display: flex;
background-color: var(--jp-layout-color0);
margin: 2px;
}
.jp-DocumentSearch-input-wrapper:focus-within {
border-color: var(--jp-cell-editor-active-border-color);
}
.jp-DocumentSearch-toggle-wrapper,
.jp-DocumentSearch-button-wrapper {
all: initial;
overflow: hidden;
display: inline-block;
border: none;
box-sizing: border-box;
}
.jp-DocumentSearch-toggle-wrapper {
width: 14px;
height: 14px;
}
.jp-DocumentSearch-button-wrapper {
width: var(--jp-private-document-search-button-height);
height: var(--jp-private-document-search-button-height);
}
.jp-DocumentSearch-toggle-wrapper:focus,
.jp-DocumentSearch-button-wrapper:focus {
outline: var(--jp-border-width) solid
var(--jp-cell-editor-active-border-color);
outline-offset: -1px;
}
.jp-DocumentSearch-toggle-wrapper,
.jp-DocumentSearch-button-wrapper,
.jp-DocumentSearch-button-content:focus {
outline: none;
}
.jp-DocumentSearch-toggle-placeholder {
width: 5px;
}
.jp-DocumentSearch-input-button::before {
display: block;
padding-top: 100%;
}
.jp-DocumentSearch-input-button-off {
opacity: var(--jp-search-toggle-off-opacity);
}
.jp-DocumentSearch-input-button-off:hover {
opacity: var(--jp-search-toggle-hover-opacity);
}
.jp-DocumentSearch-input-button-on {
opacity: var(--jp-search-toggle-on-opacity);
}
.jp-DocumentSearch-index-counter {
padding-left: 10px;
padding-right: 10px;
user-select: none;
min-width: 35px;
display: inline-block;
}
.jp-DocumentSearch-up-down-wrapper {
display: inline-block;
padding-right: 2px;
margin-left: auto;
white-space: nowrap;
}
.jp-DocumentSearch-spacer {
margin-left: auto;
}
.jp-DocumentSearch-up-down-wrapper button {
outline: 0;
border: none;
width: var(--jp-private-document-search-button-height);
height: var(--jp-private-document-search-button-height);
vertical-align: middle;
margin: 1px 5px 2px;
}
.jp-DocumentSearch-up-down-button:hover {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-up-down-button:active {
background-color: var(--jp-layout-color3);
}
.jp-DocumentSearch-filter-button {
border-radius: var(--jp-border-radius);
}
.jp-DocumentSearch-filter-button:hover {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-filter-button-enabled {
background-color: var(--jp-layout-color2);
}
.jp-DocumentSearch-filter-button-enabled:hover {
background-color: var(--jp-layout-color3);
}
.jp-DocumentSearch-search-options {
padding: 0 8px;
margin-left: 3px;
width: 100%;
display: grid;
justify-content: start;
grid-template-columns: 1fr 1fr;
align-items: center;
justify-items: stretch;
}
.jp-DocumentSearch-search-filter-disabled {
color: var(--jp-ui-font-color2);
}
.jp-DocumentSearch-search-filter {
display: flex;
align-items: center;
user-select: none;
}
.jp-DocumentSearch-regex-error {
color: var(--jp-error-color0);
}
.jp-DocumentSearch-replace-button-wrapper {
overflow: hidden;
display: inline-block;
box-sizing: border-box;
border: var(--jp-border-width) solid var(--jp-border-color0);
margin: auto 2px;
padding: 1px 4px;
height: calc(var(--jp-private-document-search-button-height) + 2px);
}
.jp-DocumentSearch-replace-button-wrapper:focus {
border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color);
}
.jp-DocumentSearch-replace-button {
display: inline-block;
text-align: center;
cursor: pointer;
box-sizing: border-box;
color: var(--jp-ui-font-color1);
/* height - 2 * (padding of wrapper) */
line-height: calc(var(--jp-private-document-search-button-height) - 2px);
width: 100%;
height: 100%;
}
.jp-DocumentSearch-replace-button:focus {
outline: none;
}
.jp-DocumentSearch-replace-wrapper-class {
margin-left: 14px;
display: flex;
}
.jp-DocumentSearch-replace-toggle {
border: none;
background-color: var(--jp-toolbar-background);
border-radius: var(--jp-border-radius);
}
.jp-DocumentSearch-replace-toggle:hover {
background-color: var(--jp-layout-color2);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.cm-editor {
line-height: var(--jp-code-line-height);
font-size: var(--jp-code-font-size);
font-family: var(--jp-code-font-family);
border: 0;
border-radius: 0;
height: auto;
/* Changed to auto to autogrow */
}
.cm-editor pre {
padding: 0 var(--jp-code-padding);
}
.jp-CodeMirrorEditor[data-type='inline'] .cm-dialog {
background-color: var(--jp-layout-color0);
color: var(--jp-content-font-color1);
}
.jp-CodeMirrorEditor {
cursor: text;
}
/* When zoomed out 67% and 33% on a screen of 1440 width x 900 height */
@media screen and (min-width: 2138px) and (max-width: 4319px) {
.jp-CodeMirrorEditor[data-type='inline'] .cm-cursor {
border-left: var(--jp-code-cursor-width1) solid
var(--jp-editor-cursor-color);
}
}
/* When zoomed out less than 33% */
@media screen and (min-width: 4320px) {
.jp-CodeMirrorEditor[data-type='inline'] .cm-cursor {
border-left: var(--jp-code-cursor-width2) solid
var(--jp-editor-cursor-color);
}
}
.cm-editor.jp-mod-readOnly .cm-cursor {
display: none;
}
.jp-CollaboratorCursor {
border-left: 5px solid transparent;
border-right: 5px solid transparent;
border-top: none;
border-bottom: 3px solid;
background-clip: content-box;
margin-left: -5px;
margin-right: -5px;
}
.cm-searching,
.cm-searching span {
/* `.cm-searching span`: we need to override syntax highlighting */
background-color: var(--jp-search-unselected-match-background-color);
color: var(--jp-search-unselected-match-color);
}
.cm-searching::selection,
.cm-searching span::selection {
background-color: var(--jp-search-unselected-match-background-color);
color: var(--jp-search-unselected-match-color);
}
.jp-current-match > .cm-searching,
.jp-current-match > .cm-searching span,
.cm-searching > .jp-current-match,
.cm-searching > .jp-current-match span {
background-color: var(--jp-search-selected-match-background-color);
color: var(--jp-search-selected-match-color);
}
.jp-current-match > .cm-searching::selection,
.cm-searching > .jp-current-match::selection,
.jp-current-match > .cm-searching span::selection {
background-color: var(--jp-search-selected-match-background-color);
color: var(--jp-search-selected-match-color);
}
.cm-trailingspace {
background-image: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAgAAAAFCAYAAAB4ka1VAAAAsElEQVQIHQGlAFr/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA7+r3zKmT0/+pk9P/7+r3zAAAAAAAAAAABAAAAAAAAAAA6OPzM+/q9wAAAAAA6OPzMwAAAAAAAAAAAgAAAAAAAAAAGR8NiRQaCgAZIA0AGR8NiQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQyoYJ/SY80UAAAAASUVORK5CYII=);
background-position: center left;
background-repeat: repeat-x;
}
.jp-CollaboratorCursor-hover {
position: absolute;
z-index: 1;
transform: translateX(-50%);
color: white;
border-radius: 3px;
padding-left: 4px;
padding-right: 4px;
padding-top: 1px;
padding-bottom: 1px;
text-align: center;
font-size: var(--jp-ui-font-size1);
white-space: nowrap;
}
.jp-CodeMirror-ruler {
border-left: 1px dashed var(--jp-border-color2);
}
/* Styles for shared cursors (remote cursor locations and selected ranges) */
.jp-CodeMirrorEditor .cm-ySelectionCaret {
position: relative;
border-left: 1px solid black;
margin-left: -1px;
margin-right: -1px;
box-sizing: border-box;
}
.jp-CodeMirrorEditor .cm-ySelectionCaret > .cm-ySelectionInfo {
white-space: nowrap;
position: absolute;
top: -1.15em;
padding-bottom: 0.05em;
left: -1px;
font-size: 0.95em;
font-family: var(--jp-ui-font-family);
font-weight: bold;
line-height: normal;
user-select: none;
color: white;
padding-left: 2px;
padding-right: 2px;
z-index: 101;
transition: opacity 0.3s ease-in-out;
}
.jp-CodeMirrorEditor .cm-ySelectionInfo {
transition-delay: 0.7s;
opacity: 0;
}
.jp-CodeMirrorEditor .cm-ySelectionCaret:hover > .cm-ySelectionInfo {
opacity: 1;
transition-delay: 0s;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-MimeDocument {
outline: none;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
:root {
--jp-private-filebrowser-button-height: 28px;
--jp-private-filebrowser-button-width: 48px;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-FileBrowser .jp-SidePanel-content {
display: flex;
flex-direction: column;
}
.jp-FileBrowser-toolbar.jp-Toolbar {
flex-wrap: wrap;
row-gap: 12px;
border-bottom: none;
height: auto;
margin: 8px 12px 0;
box-shadow: none;
padding: 0;
justify-content: flex-start;
}
.jp-FileBrowser-Panel {
flex: 1 1 auto;
display: flex;
flex-direction: column;
}
.jp-BreadCrumbs {
flex: 0 0 auto;
margin: 8px 12px;
}
.jp-BreadCrumbs-item {
margin: 0 2px;
padding: 0 2px;
border-radius: var(--jp-border-radius);
cursor: pointer;
}
.jp-BreadCrumbs-item:hover {
background-color: var(--jp-layout-color2);
}
.jp-BreadCrumbs-item:first-child {
margin-left: 0;
}
.jp-BreadCrumbs-item.jp-mod-dropTarget {
background-color: var(--jp-brand-color2);
opacity: 0.7;
}
/*-----------------------------------------------------------------------------
| Buttons
|----------------------------------------------------------------------------*/
.jp-FileBrowser-toolbar > .jp-Toolbar-item {
flex: 0 0 auto;
padding-left: 0;
padding-right: 2px;
align-items: center;
height: unset;
}
.jp-FileBrowser-toolbar > .jp-Toolbar-item .jp-ToolbarButtonComponent {
width: 40px;
}
/*-----------------------------------------------------------------------------
| Other styles
|----------------------------------------------------------------------------*/
.jp-FileDialog.jp-mod-conflict input {
color: var(--jp-error-color1);
}
.jp-FileDialog .jp-new-name-title {
margin-top: 12px;
}
.jp-LastModified-hidden {
display: none;
}
.jp-FileSize-hidden {
display: none;
}
.jp-FileBrowser .lm-AccordionPanel > h3:first-child {
display: none;
}
/*-----------------------------------------------------------------------------
| DirListing
|----------------------------------------------------------------------------*/
.jp-DirListing {
flex: 1 1 auto;
display: flex;
flex-direction: column;
outline: 0;
}
.jp-DirListing-header {
flex: 0 0 auto;
display: flex;
flex-direction: row;
align-items: center;
overflow: hidden;
border-top: var(--jp-border-width) solid var(--jp-border-color2);
border-bottom: var(--jp-border-width) solid var(--jp-border-color1);
box-shadow: var(--jp-toolbar-box-shadow);
z-index: 2;
}
.jp-DirListing-headerItem {
padding: 4px 12px 2px;
font-weight: 500;
}
.jp-DirListing-headerItem:hover {
background: var(--jp-layout-color2);
}
.jp-DirListing-headerItem.jp-id-name {
flex: 1 0 84px;
}
.jp-DirListing-headerItem.jp-id-modified {
flex: 0 0 112px;
border-left: var(--jp-border-width) solid var(--jp-border-color2);
text-align: right;
}
.jp-DirListing-headerItem.jp-id-filesize {
flex: 0 0 75px;
border-left: var(--jp-border-width) solid var(--jp-border-color2);
text-align: right;
}
.jp-id-narrow {
display: none;
flex: 0 0 5px;
padding: 4px;
border-left: var(--jp-border-width) solid var(--jp-border-color2);
text-align: right;
color: var(--jp-border-color2);
}
.jp-DirListing-narrow .jp-id-narrow {
display: block;
}
.jp-DirListing-narrow .jp-id-modified,
.jp-DirListing-narrow .jp-DirListing-itemModified {
display: none;
}
.jp-DirListing-headerItem.jp-mod-selected {
font-weight: 600;
}
/* increase specificity to override bundled default */
.jp-DirListing-content {
flex: 1 1 auto;
margin: 0;
padding: 0;
list-style-type: none;
overflow: auto;
background-color: var(--jp-layout-color1);
}
.jp-DirListing-content mark {
color: var(--jp-ui-font-color0);
background-color: transparent;
font-weight: bold;
}
.jp-DirListing-content .jp-DirListing-item.jp-mod-selected mark {
color: var(--jp-ui-inverse-font-color0);
}
/* Style the directory listing content when a user drops a file to upload */
.jp-DirListing.jp-mod-native-drop .jp-DirListing-content {
outline: 5px dashed rgba(128, 128, 128, 0.5);
outline-offset: -10px;
cursor: copy;
}
.jp-DirListing-item {
display: flex;
flex-direction: row;
align-items: center;
padding: 4px 12px;
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
.jp-DirListing-checkboxWrapper {
/* Increases hit area of checkbox. */
padding: 4px;
}
.jp-DirListing-header
.jp-DirListing-checkboxWrapper
+ .jp-DirListing-headerItem {
padding-left: 4px;
}
.jp-DirListing-content .jp-DirListing-checkboxWrapper {
position: relative;
left: -4px;
margin: -4px 0 -4px -8px;
}
.jp-DirListing-checkboxWrapper.jp-mod-visible {
visibility: visible;
}
/* For devices that support hovering, hide checkboxes until hovered, selected...
*/
@media (hover: hover) {
.jp-DirListing-checkboxWrapper {
visibility: hidden;
}
.jp-DirListing-item:hover .jp-DirListing-checkboxWrapper,
.jp-DirListing-item.jp-mod-selected .jp-DirListing-checkboxWrapper {
visibility: visible;
}
}
.jp-DirListing-item[data-is-dot] {
opacity: 75%;
}
.jp-DirListing-item.jp-mod-selected {
color: var(--jp-ui-inverse-font-color1);
background: var(--jp-brand-color1);
}
.jp-DirListing-item.jp-mod-dropTarget {
background: var(--jp-brand-color3);
}
.jp-DirListing-item:hover:not(.jp-mod-selected) {
background: var(--jp-layout-color2);
}
.jp-DirListing-itemIcon {
flex: 0 0 20px;
margin-right: 4px;
}
.jp-DirListing-itemText {
flex: 1 0 64px;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
user-select: none;
}
.jp-DirListing-itemText:focus {
outline-width: 2px;
outline-color: var(--jp-inverse-layout-color1);
outline-style: solid;
outline-offset: 1px;
}
.jp-DirListing-item.jp-mod-selected .jp-DirListing-itemText:focus {
outline-color: var(--jp-layout-color1);
}
.jp-DirListing-itemModified {
flex: 0 0 125px;
text-align: right;
}
.jp-DirListing-itemFileSize {
flex: 0 0 90px;
text-align: right;
}
.jp-DirListing-editor {
flex: 1 0 64px;
outline: none;
border: none;
color: var(--jp-ui-font-color1);
background-color: var(--jp-layout-color1);
}
.jp-DirListing-item.jp-mod-running .jp-DirListing-itemIcon::before {
color: var(--jp-success-color1);
content: '\25CF';
font-size: 8px;
position: absolute;
left: -8px;
}
.jp-DirListing-item.jp-mod-running.jp-mod-selected
.jp-DirListing-itemIcon::before {
color: var(--jp-ui-inverse-font-color1);
}
.jp-DirListing-item.lm-mod-drag-image,
.jp-DirListing-item.jp-mod-selected.lm-mod-drag-image {
font-size: var(--jp-ui-font-size1);
padding-left: 4px;
margin-left: 4px;
width: 160px;
background-color: var(--jp-ui-inverse-font-color2);
box-shadow: var(--jp-elevation-z2);
border-radius: 0;
color: var(--jp-ui-font-color1);
transform: translateX(-40%) translateY(-58%);
}
.jp-Document {
min-width: 120px;
min-height: 120px;
outline: none;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Main OutputArea
| OutputArea has a list of Outputs
|----------------------------------------------------------------------------*/
.jp-OutputArea {
overflow-y: auto;
}
.jp-OutputArea-child {
display: table;
table-layout: fixed;
width: 100%;
overflow: hidden;
}
.jp-OutputPrompt {
width: var(--jp-cell-prompt-width);
color: var(--jp-cell-outprompt-font-color);
font-family: var(--jp-cell-prompt-font-family);
padding: var(--jp-code-padding);
letter-spacing: var(--jp-cell-prompt-letter-spacing);
line-height: var(--jp-code-line-height);
font-size: var(--jp-code-font-size);
border: var(--jp-border-width) solid transparent;
opacity: var(--jp-cell-prompt-opacity);
/* Right align prompt text, don't wrap to handle large prompt numbers */
text-align: right;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
/* Disable text selection */
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
.jp-OutputArea-prompt {
display: table-cell;
vertical-align: top;
}
.jp-OutputArea-output {
display: table-cell;
width: 100%;
height: auto;
overflow: auto;
user-select: text;
-moz-user-select: text;
-webkit-user-select: text;
-ms-user-select: text;
}
.jp-OutputArea .jp-RenderedText {
padding-left: 1ch;
}
/**
* Prompt overlay.
*/
.jp-OutputArea-promptOverlay {
position: absolute;
top: 0;
width: var(--jp-cell-prompt-width);
height: 100%;
opacity: 0.5;
}
.jp-OutputArea-promptOverlay:hover {
background: var(--jp-layout-color2);
box-shadow: inset 0 0 1px var(--jp-inverse-layout-color0);
cursor: zoom-out;
}
.jp-mod-outputsScrolled .jp-OutputArea-promptOverlay:hover {
cursor: zoom-in;
}
/**
* Isolated output.
*/
.jp-OutputArea-output.jp-mod-isolated {
width: 100%;
display: block;
}
/*
When drag events occur, `lm-mod-override-cursor` is added to the body.
Because iframes steal all cursor events, the following two rules are necessary
to suppress pointer events while resize drags are occurring. There may be a
better solution to this problem.
*/
body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated {
position: relative;
}
body.lm-mod-override-cursor .jp-OutputArea-output.jp-mod-isolated::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: transparent;
}
/* pre */
.jp-OutputArea-output pre {
border: none;
margin: 0;
padding: 0;
overflow-x: auto;
overflow-y: auto;
word-break: break-all;
word-wrap: break-word;
white-space: pre-wrap;
}
/* tables */
.jp-OutputArea-output.jp-RenderedHTMLCommon table {
margin-left: 0;
margin-right: 0;
}
/* description lists */
.jp-OutputArea-output dl,
.jp-OutputArea-output dt,
.jp-OutputArea-output dd {
display: block;
}
.jp-OutputArea-output dl {
width: 100%;
overflow: hidden;
padding: 0;
margin: 0;
}
.jp-OutputArea-output dt {
font-weight: bold;
float: left;
width: 20%;
padding: 0;
margin: 0;
}
.jp-OutputArea-output dd {
float: left;
width: 80%;
padding: 0;
margin: 0;
}
.jp-TrimmedOutputs pre {
background: var(--jp-layout-color3);
font-size: calc(var(--jp-code-font-size) * 1.4);
text-align: center;
text-transform: uppercase;
}
/* Hide the gutter in case of
* - nested output areas (e.g. in the case of output widgets)
* - mirrored output areas
*/
.jp-OutputArea .jp-OutputArea .jp-OutputArea-prompt {
display: none;
}
/* Hide empty lines in the output area, for instance due to cleared widgets */
.jp-OutputArea-prompt:empty {
padding: 0;
border: 0;
}
/*-----------------------------------------------------------------------------
| executeResult is added to any Output-result for the display of the object
| returned by a cell
|----------------------------------------------------------------------------*/
.jp-OutputArea-output.jp-OutputArea-executeResult {
margin-left: 0;
width: 100%;
}
/* Text output with the Out[] prompt needs a top padding to match the
* alignment of the Out[] prompt itself.
*/
.jp-OutputArea-executeResult .jp-RenderedText.jp-OutputArea-output {
padding-top: var(--jp-code-padding);
border-top: var(--jp-border-width) solid transparent;
}
/*-----------------------------------------------------------------------------
| The Stdin output
|----------------------------------------------------------------------------*/
.jp-Stdin-prompt {
color: var(--jp-content-font-color0);
padding-right: var(--jp-code-padding);
vertical-align: baseline;
flex: 0 0 auto;
}
.jp-Stdin-input {
font-family: var(--jp-code-font-family);
font-size: inherit;
color: inherit;
background-color: inherit;
width: 42%;
min-width: 200px;
/* make sure input baseline aligns with prompt */
vertical-align: baseline;
/* padding + margin = 0.5em between prompt and cursor */
padding: 0 0.25em;
margin: 0 0.25em;
flex: 0 0 70%;
}
.jp-Stdin-input::placeholder {
opacity: 0;
}
.jp-Stdin-input:focus {
box-shadow: none;
}
.jp-Stdin-input:focus::placeholder {
opacity: 1;
}
/*-----------------------------------------------------------------------------
| Output Area View
|----------------------------------------------------------------------------*/
.jp-LinkedOutputView .jp-OutputArea {
height: 100%;
display: block;
}
.jp-LinkedOutputView .jp-OutputArea-output:only-child {
height: 100%;
}
/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/
@media print {
.jp-OutputArea-child {
break-inside: avoid-page;
}
}
/*-----------------------------------------------------------------------------
| Mobile
|----------------------------------------------------------------------------*/
@media only screen and (max-width: 760px) {
.jp-OutputPrompt {
display: table-row;
text-align: left;
}
.jp-OutputArea-child .jp-OutputArea-output {
display: table-row;
margin-left: var(--jp-notebook-padding);
}
}
/* Trimmed outputs warning */
.jp-TrimmedOutputs > a {
margin: 10px;
text-decoration: none;
cursor: pointer;
}
.jp-TrimmedOutputs > a:hover {
text-decoration: none;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Table of Contents
|----------------------------------------------------------------------------*/
:root {
--jp-private-toc-active-width: 4px;
}
.jp-TableOfContents {
display: flex;
flex-direction: column;
background: var(--jp-layout-color1);
color: var(--jp-ui-font-color1);
font-size: var(--jp-ui-font-size1);
height: 100%;
}
.jp-TableOfContents-placeholder {
text-align: center;
}
.jp-TableOfContents-placeholderContent {
color: var(--jp-content-font-color2);
padding: 8px;
}
.jp-TableOfContents-placeholderContent > h3 {
margin-bottom: var(--jp-content-heading-margin-bottom);
}
.jp-TableOfContents .jp-SidePanel-content {
overflow-y: auto;
}
.jp-TableOfContents-tree {
margin: 4px;
}
.jp-TableOfContents ol {
list-style-type: none;
}
/* stylelint-disable-next-line selector-max-type */
.jp-TableOfContents li > ol {
/* Align left border with triangle icon center */
padding-left: 11px;
}
.jp-TableOfContents-content {
/* left margin for the active heading indicator */
margin: 0 0 0 var(--jp-private-toc-active-width);
padding: 0;
background-color: var(--jp-layout-color1);
}
.jp-tocItem {
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
.jp-tocItem-heading {
display: flex;
cursor: pointer;
}
.jp-tocItem-heading:hover {
background-color: var(--jp-layout-color2);
}
.jp-tocItem-content {
display: block;
padding: 4px 0;
white-space: nowrap;
text-overflow: ellipsis;
overflow-x: hidden;
}
.jp-tocItem-collapser {
height: 20px;
margin: 2px 2px 0;
padding: 0;
background: none;
border: none;
cursor: pointer;
}
.jp-tocItem-collapser:hover {
background-color: var(--jp-layout-color3);
}
/* Active heading indicator */
.jp-tocItem-heading::before {
content: ' ';
background: transparent;
width: var(--jp-private-toc-active-width);
height: 24px;
position: absolute;
left: 0;
border-radius: var(--jp-border-radius);
}
.jp-tocItem-heading.jp-tocItem-active::before {
background-color: var(--jp-brand-color1);
}
.jp-tocItem-heading:hover.jp-tocItem-active::before {
background: var(--jp-brand-color0);
opacity: 1;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
.jp-Collapser {
flex: 0 0 var(--jp-cell-collapser-width);
padding: 0;
margin: 0;
border: none;
outline: none;
background: transparent;
border-radius: var(--jp-border-radius);
opacity: 1;
}
.jp-Collapser-child {
display: block;
width: 100%;
box-sizing: border-box;
/* height: 100% doesn't work because the height of its parent is computed from content */
position: absolute;
top: 0;
bottom: 0;
}
/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/
/*
Hiding collapsers in print mode.
Note: input and output wrappers have "display: block" propery in print mode.
*/
@media print {
.jp-Collapser {
display: none;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Header/Footer
|----------------------------------------------------------------------------*/
/* Hidden by zero height by default */
.jp-CellHeader,
.jp-CellFooter {
height: 0;
width: 100%;
padding: 0;
margin: 0;
border: none;
outline: none;
background: transparent;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Input
|----------------------------------------------------------------------------*/
/* All input areas */
.jp-InputArea {
display: table;
table-layout: fixed;
width: 100%;
overflow: hidden;
}
.jp-InputArea-editor {
display: table-cell;
overflow: hidden;
vertical-align: top;
/* This is the non-active, default styling */
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
border-radius: 0;
background: var(--jp-cell-editor-background);
}
.jp-InputPrompt {
display: table-cell;
vertical-align: top;
width: var(--jp-cell-prompt-width);
color: var(--jp-cell-inprompt-font-color);
font-family: var(--jp-cell-prompt-font-family);
padding: var(--jp-code-padding);
letter-spacing: var(--jp-cell-prompt-letter-spacing);
opacity: var(--jp-cell-prompt-opacity);
line-height: var(--jp-code-line-height);
font-size: var(--jp-code-font-size);
border: var(--jp-border-width) solid transparent;
/* Right align prompt text, don't wrap to handle large prompt numbers */
text-align: right;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
/* Disable text selection */
-webkit-user-select: none;
-moz-user-select: none;
-ms-user-select: none;
user-select: none;
}
/*-----------------------------------------------------------------------------
| Mobile
|----------------------------------------------------------------------------*/
@media only screen and (max-width: 760px) {
.jp-InputArea-editor {
display: table-row;
margin-left: var(--jp-notebook-padding);
}
.jp-InputPrompt {
display: table-row;
text-align: left;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Placeholder
|----------------------------------------------------------------------------*/
.jp-Placeholder {
display: table;
table-layout: fixed;
width: 100%;
}
.jp-Placeholder-prompt {
display: table-cell;
box-sizing: border-box;
}
.jp-Placeholder-content {
display: table-cell;
padding: 4px 6px;
border: 1px solid transparent;
border-radius: 0;
background: none;
box-sizing: border-box;
cursor: pointer;
}
.jp-Placeholder-contentContainer {
display: flex;
}
.jp-Placeholder-content:hover,
.jp-InputPlaceholder > .jp-Placeholder-content:hover {
border-color: var(--jp-layout-color3);
}
.jp-Placeholder-content .jp-MoreHorizIcon {
width: 32px;
height: 16px;
border: 1px solid transparent;
border-radius: var(--jp-border-radius);
}
.jp-Placeholder-content .jp-MoreHorizIcon:hover {
border: 1px solid var(--jp-border-color1);
box-shadow: 0 0 2px 0 rgba(0, 0, 0, 0.25);
background-color: var(--jp-layout-color0);
}
.jp-PlaceholderText {
white-space: nowrap;
overflow-x: hidden;
color: var(--jp-inverse-layout-color3);
font-family: var(--jp-code-font-family);
}
.jp-InputPlaceholder > .jp-Placeholder-content {
border-color: var(--jp-cell-editor-border-color);
background: var(--jp-cell-editor-background);
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Private CSS variables
|----------------------------------------------------------------------------*/
:root {
--jp-private-cell-scrolling-output-offset: 5px;
}
/*-----------------------------------------------------------------------------
| Cell
|----------------------------------------------------------------------------*/
.jp-Cell {
padding: var(--jp-cell-padding);
margin: 0;
border: none;
outline: none;
background: transparent;
}
/*-----------------------------------------------------------------------------
| Common input/output
|----------------------------------------------------------------------------*/
.jp-Cell-inputWrapper,
.jp-Cell-outputWrapper {
display: flex;
flex-direction: row;
padding: 0;
margin: 0;
/* Added to reveal the box-shadow on the input and output collapsers. */
overflow: visible;
}
/* Only input/output areas inside cells */
.jp-Cell-inputArea,
.jp-Cell-outputArea {
flex: 1 1 auto;
}
/*-----------------------------------------------------------------------------
| Collapser
|----------------------------------------------------------------------------*/
/* Make the output collapser disappear when there is not output, but do so
* in a manner that leaves it in the layout and preserves its width.
*/
.jp-Cell.jp-mod-noOutputs .jp-Cell-outputCollapser {
border: none !important;
background: transparent !important;
}
.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputCollapser {
min-height: var(--jp-cell-collapser-min-height);
}
/*-----------------------------------------------------------------------------
| Output
|----------------------------------------------------------------------------*/
/* Put a space between input and output when there IS output */
.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputWrapper {
margin-top: 5px;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea {
overflow-y: auto;
max-height: 24em;
margin-left: var(--jp-private-cell-scrolling-output-offset);
resize: vertical;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea[style*='height'] {
max-height: unset;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-Cell-outputArea::after {
content: ' ';
box-shadow: inset 0 0 6px 2px rgb(0 0 0 / 30%);
width: 100%;
height: 100%;
position: sticky;
bottom: 0;
top: 0;
margin-top: -50%;
float: left;
display: block;
pointer-events: none;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-child {
padding-top: 6px;
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-prompt {
width: calc(
var(--jp-cell-prompt-width) - var(--jp-private-cell-scrolling-output-offset)
);
}
.jp-CodeCell.jp-mod-outputsScrolled .jp-OutputArea-promptOverlay {
left: calc(-1 * var(--jp-private-cell-scrolling-output-offset));
}
/*-----------------------------------------------------------------------------
| CodeCell
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| MarkdownCell
|----------------------------------------------------------------------------*/
.jp-MarkdownOutput {
display: table-cell;
width: 100%;
margin-top: 0;
margin-bottom: 0;
padding-left: var(--jp-code-padding);
}
.jp-MarkdownOutput.jp-RenderedHTMLCommon {
overflow: auto;
}
/* collapseHeadingButton (show always if hiddenCellsButton is _not_ shown) */
.jp-collapseHeadingButton {
display: flex;
min-height: var(--jp-cell-collapser-min-height);
font-size: var(--jp-code-font-size);
position: absolute;
background-color: transparent;
background-size: 25px;
background-repeat: no-repeat;
background-position-x: center;
background-position-y: top;
background-image: var(--jp-icon-caret-down);
right: 0;
top: 0;
bottom: 0;
}
.jp-collapseHeadingButton.jp-mod-collapsed {
background-image: var(--jp-icon-caret-right);
}
/*
set the container font size to match that of content
so that the nested collapse buttons have the right size
*/
.jp-MarkdownCell .jp-InputPrompt {
font-size: var(--jp-content-font-size1);
}
/*
Align collapseHeadingButton with cell top header
The font sizes are identical to the ones in packages/rendermime/style/base.css
*/
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='1'] {
font-size: var(--jp-content-font-size5);
background-position-y: calc(0.3 * var(--jp-content-font-size5));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='2'] {
font-size: var(--jp-content-font-size4);
background-position-y: calc(0.3 * var(--jp-content-font-size4));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='3'] {
font-size: var(--jp-content-font-size3);
background-position-y: calc(0.3 * var(--jp-content-font-size3));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='4'] {
font-size: var(--jp-content-font-size2);
background-position-y: calc(0.3 * var(--jp-content-font-size2));
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='5'] {
font-size: var(--jp-content-font-size1);
background-position-y: top;
}
.jp-mod-rendered .jp-collapseHeadingButton[data-heading-level='6'] {
font-size: var(--jp-content-font-size0);
background-position-y: top;
}
/* collapseHeadingButton (show only on (hover,active) if hiddenCellsButton is shown) */
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-collapseHeadingButton {
display: none;
}
.jp-Notebook.jp-mod-showHiddenCellsButton
:is(.jp-MarkdownCell:hover, .jp-mod-active)
.jp-collapseHeadingButton {
display: flex;
}
/* showHiddenCellsButton (only show if jp-mod-showHiddenCellsButton is set, which
is a consequence of the showHiddenCellsButton option in Notebook Settings)*/
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton {
margin-left: calc(var(--jp-cell-prompt-width) + 2 * var(--jp-code-padding));
margin-top: var(--jp-code-padding);
border: 1px solid var(--jp-border-color2);
background-color: var(--jp-border-color3) !important;
color: var(--jp-content-font-color0) !important;
display: flex;
}
.jp-Notebook.jp-mod-showHiddenCellsButton .jp-showHiddenCellsButton:hover {
background-color: var(--jp-border-color2) !important;
}
.jp-showHiddenCellsButton {
display: none;
}
/*-----------------------------------------------------------------------------
| Printing
|----------------------------------------------------------------------------*/
/*
Using block instead of flex to allow the use of the break-inside CSS property for
cell outputs.
*/
@media print {
.jp-Cell-inputWrapper,
.jp-Cell-outputWrapper {
display: block;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
:root {
--jp-notebook-toolbar-padding: 2px 5px 2px 2px;
}
/*-----------------------------------------------------------------------------
/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/
.jp-NotebookPanel-toolbar {
padding: var(--jp-notebook-toolbar-padding);
/* disable paint containment from lumino 2.0 default strict CSS containment */
contain: style size !important;
}
.jp-Toolbar-item.jp-Notebook-toolbarCellType .jp-select-wrapper.jp-mod-focused {
border: none;
box-shadow: none;
}
.jp-Notebook-toolbarCellTypeDropdown select {
height: 24px;
font-size: var(--jp-ui-font-size1);
line-height: 14px;
border-radius: 0;
display: block;
}
.jp-Notebook-toolbarCellTypeDropdown span {
top: 5px !important;
}
.jp-Toolbar-responsive-popup {
position: absolute;
height: fit-content;
display: flex;
flex-direction: row;
flex-wrap: wrap;
justify-content: flex-end;
border-bottom: var(--jp-border-width) solid var(--jp-toolbar-border-color);
box-shadow: var(--jp-toolbar-box-shadow);
background: var(--jp-toolbar-background);
min-height: var(--jp-toolbar-micro-height);
padding: var(--jp-notebook-toolbar-padding);
z-index: 1;
right: 0;
top: 0;
}
.jp-Toolbar > .jp-Toolbar-responsive-opener {
margin-left: auto;
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Variables
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
/*-----------------------------------------------------------------------------
| Styles
|----------------------------------------------------------------------------*/
.jp-Notebook-ExecutionIndicator {
position: relative;
display: inline-block;
height: 100%;
z-index: 9997;
}
.jp-Notebook-ExecutionIndicator-tooltip {
visibility: hidden;
height: auto;
width: max-content;
width: -moz-max-content;
background-color: var(--jp-layout-color2);
color: var(--jp-ui-font-color1);
text-align: justify;
border-radius: 6px;
padding: 0 5px;
position: fixed;
display: table;
}
.jp-Notebook-ExecutionIndicator-tooltip.up {
transform: translateX(-50%) translateY(-100%) translateY(-32px);
}
.jp-Notebook-ExecutionIndicator-tooltip.down {
transform: translateX(calc(-100% + 16px)) translateY(5px);
}
.jp-Notebook-ExecutionIndicator-tooltip.hidden {
display: none;
}
.jp-Notebook-ExecutionIndicator:hover .jp-Notebook-ExecutionIndicator-tooltip {
visibility: visible;
}
.jp-Notebook-ExecutionIndicator span {
font-size: var(--jp-ui-font-size1);
font-family: var(--jp-ui-font-family);
color: var(--jp-ui-font-color1);
line-height: 24px;
display: block;
}
.jp-Notebook-ExecutionIndicator-progress-bar {
display: flex;
justify-content: center;
height: 100%;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
/*
* Execution indicator
*/
.jp-tocItem-content::after {
content: '';
/* Must be identical to form a circle */
width: 12px;
height: 12px;
background: none;
border: none;
position: absolute;
right: 0;
}
.jp-tocItem-content[data-running='0']::after {
border-radius: 50%;
border: var(--jp-border-width) solid var(--jp-inverse-layout-color3);
background: none;
}
.jp-tocItem-content[data-running='1']::after {
border-radius: 50%;
border: var(--jp-border-width) solid var(--jp-inverse-layout-color3);
background-color: var(--jp-inverse-layout-color3);
}
.jp-tocItem-content[data-running='0'],
.jp-tocItem-content[data-running='1'] {
margin-right: 12px;
}
/*
* Copyright (c) Jupyter Development Team.
* Distributed under the terms of the Modified BSD License.
*/
.jp-Notebook-footer {
height: 27px;
margin-left: calc(
var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) +
var(--jp-cell-padding)
);
width: calc(
100% -
(
var(--jp-cell-prompt-width) + var(--jp-cell-collapser-width) +
var(--jp-cell-padding) + var(--jp-cell-padding)
)
);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
color: var(--jp-ui-font-color3);
margin-top: 6px;
background: none;
cursor: pointer;
}
.jp-Notebook-footer:focus {
border-color: var(--jp-cell-editor-active-border-color);
}
/* For devices that support hovering, hide footer until hover */
@media (hover: hover) {
.jp-Notebook-footer {
opacity: 0;
}
.jp-Notebook-footer:focus,
.jp-Notebook-footer:hover {
opacity: 1;
}
}
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| Imports
|----------------------------------------------------------------------------*/
/*-----------------------------------------------------------------------------
| CSS variables
|----------------------------------------------------------------------------*/
:root {
--jp-side-by-side-output-size: 1fr;
--jp-side-by-side-resized-cell: var(--jp-side-by-side-output-size);
--jp-private-notebook-dragImage-width: 304px;
--jp-private-notebook-dragImage-height: 36px;
--jp-private-notebook-selected-color: var(--md-blue-400);
--jp-private-notebook-active-color: var(--md-green-400);
}
/*-----------------------------------------------------------------------------
| Notebook
|----------------------------------------------------------------------------*/
/* stylelint-disable selector-max-class */
.jp-NotebookPanel {
display: block;
height: 100%;
}
.jp-NotebookPanel.jp-Document {
min-width: 240px;
min-height: 120px;
}
.jp-Notebook {
padding: var(--jp-notebook-padding);
outline: none;
overflow: auto;
background: var(--jp-layout-color0);
}
.jp-Notebook.jp-mod-scrollPastEnd::after {
display: block;
content: '';
min-height: var(--jp-notebook-scroll-padding);
}
.jp-MainAreaWidget-ContainStrict .jp-Notebook * {
contain: strict;
}
.jp-Notebook .jp-Cell {
overflow: visible;
}
.jp-Notebook .jp-Cell .jp-InputPrompt {
cursor: move;
}
/*-----------------------------------------------------------------------------
| Notebook state related styling
|
| The notebook and cells each have states, here are the possibilities:
|
| - Notebook
| - Command
| - Edit
| - Cell
| - None
| - Active (only one can be active)
| - Selected (the cells actions are applied to)
| - Multiselected (when multiple selected, the cursor)
| - No outputs
|----------------------------------------------------------------------------*/
/* Command or edit modes */
.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-InputPrompt {
opacity: var(--jp-cell-prompt-not-active-opacity);
color: var(--jp-cell-prompt-not-active-font-color);
}
.jp-Notebook .jp-Cell:not(.jp-mod-active) .jp-OutputPrompt {
opacity: var(--jp-cell-prompt-not-active-opacity);
color: var(--jp-cell-prompt-not-active-font-color);
}
/* cell is active */
.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser {
background: var(--jp-brand-color1);
}
/* cell is dirty */
.jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt {
color: var(--jp-warn-color1);
}
.jp-Notebook .jp-Cell.jp-mod-dirty .jp-InputPrompt::before {
color: var(--jp-warn-color1);
content: '•';
}
.jp-Notebook .jp-Cell.jp-mod-active.jp-mod-dirty .jp-Collapser {
background: var(--jp-warn-color1);
}
/* collapser is hovered */
.jp-Notebook .jp-Cell .jp-Collapser:hover {
box-shadow: var(--jp-elevation-z2);
background: var(--jp-brand-color1);
opacity: var(--jp-cell-collapser-not-active-hover-opacity);
}
/* cell is active and collapser is hovered */
.jp-Notebook .jp-Cell.jp-mod-active .jp-Collapser:hover {
background: var(--jp-brand-color0);
opacity: 1;
}
/* Command mode */
.jp-Notebook.jp-mod-commandMode .jp-Cell.jp-mod-selected {
background: var(--jp-notebook-multiselected-color);
}
.jp-Notebook.jp-mod-commandMode
.jp-Cell.jp-mod-active.jp-mod-selected:not(.jp-mod-multiSelected) {
background: transparent;
}
/* Edit mode */
.jp-Notebook.jp-mod-editMode .jp-Cell.jp-mod-active .jp-InputArea-editor {
border: var(--jp-border-width) solid var(--jp-cell-editor-active-border-color);
box-shadow: var(--jp-input-box-shadow);
background-color: var(--jp-cell-editor-active-background);
}
/*-----------------------------------------------------------------------------
| Notebook drag and drop
|----------------------------------------------------------------------------*/
.jp-Notebook-cell.jp-mod-dropSource {
opacity: 0.5;
}
.jp-Notebook-cell.jp-mod-dropTarget,
.jp-Notebook.jp-mod-commandMode
.jp-Notebook-cell.jp-mod-active.jp-mod-selected.jp-mod-dropTarget {
border-top-color: var(--jp-private-notebook-selected-color);
border-top-style: solid;
border-top-width: 2px;
}
.jp-dragImage {
display: block;
flex-direction: row;
width: var(--jp-private-notebook-dragImage-width);
height: var(--jp-private-notebook-dragImage-height);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
background: var(--jp-cell-editor-background);
overflow: visible;
}
.jp-dragImage-singlePrompt {
box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12);
}
.jp-dragImage .jp-dragImage-content {
flex: 1 1 auto;
z-index: 2;
font-size: var(--jp-code-font-size);
font-family: var(--jp-code-font-family);
line-height: var(--jp-code-line-height);
padding: var(--jp-code-padding);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
background: var(--jp-cell-editor-background-color);
color: var(--jp-content-font-color3);
text-align: left;
margin: 4px 4px 4px 0;
}
.jp-dragImage .jp-dragImage-prompt {
flex: 0 0 auto;
min-width: 36px;
color: var(--jp-cell-inprompt-font-color);
padding: var(--jp-code-padding);
padding-left: 12px;
font-family: var(--jp-cell-prompt-font-family);
letter-spacing: var(--jp-cell-prompt-letter-spacing);
line-height: 1.9;
font-size: var(--jp-code-font-size);
border: var(--jp-border-width) solid transparent;
}
.jp-dragImage-multipleBack {
z-index: -1;
position: absolute;
height: 32px;
width: 300px;
top: 8px;
left: 8px;
background: var(--jp-layout-color2);
border: var(--jp-border-width) solid var(--jp-input-border-color);
box-shadow: 2px 2px 4px 0 rgba(0, 0, 0, 0.12);
}
/*-----------------------------------------------------------------------------
| Cell toolbar
|----------------------------------------------------------------------------*/
.jp-NotebookTools {
display: block;
min-width: var(--jp-sidebar-min-width);
color: var(--jp-ui-font-color1);
background: var(--jp-layout-color1);
/* This is needed so that all font sizing of children done in ems is
* relative to this base size */
font-size: var(--jp-ui-font-size1);
overflow: auto;
}
.jp-ActiveCellTool {
padding: 12px 0;
display: flex;
}
.jp-ActiveCellTool-Content {
flex: 1 1 auto;
}
.jp-ActiveCellTool .jp-ActiveCellTool-CellContent {
background: var(--jp-cell-editor-background);
border: var(--jp-border-width) solid var(--jp-cell-editor-border-color);
border-radius: 0;
min-height: 29px;
}
.jp-ActiveCellTool .jp-InputPrompt {
min-width: calc(var(--jp-cell-prompt-width) * 0.75);
}
.jp-ActiveCellTool-CellContent > pre {
padding: 5px 4px;
margin: 0;
white-space: normal;
}
.jp-MetadataEditorTool {
flex-direction: column;
padding: 12px 0;
}
.jp-RankedPanel > :not(:first-child) {
margin-top: 12px;
}
.jp-KeySelector select.jp-mod-styled {
font-size: var(--jp-ui-font-size1);
color: var(--jp-ui-font-color0);
border: var(--jp-border-width) solid var(--jp-border-color1);
}
.jp-KeySelector label,
.jp-MetadataEditorTool label,
.jp-NumberSetter label {
line-height: 1.4;
}
.jp-NotebookTools .jp-select-wrapper {
margin-top: 4px;
margin-bottom: 0;
}
.jp-NumberSetter input {
width: 100%;
margin-top: 4px;
}
.jp-NotebookTools .jp-Collapse {
margin-top: 16px;
}
/*-----------------------------------------------------------------------------
| Presentation Mode (.jp-mod-presentationMode)
|----------------------------------------------------------------------------*/
.jp-mod-presentationMode .jp-Notebook {
--jp-content-font-size1: var(--jp-content-presentation-font-size1);
--jp-code-font-size: var(--jp-code-presentation-font-size);
}
.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-InputPrompt,
.jp-mod-presentationMode .jp-Notebook .jp-Cell .jp-OutputPrompt {
flex: 0 0 110px;
}
/*-----------------------------------------------------------------------------
| Side-by-side Mode (.jp-mod-sideBySide)
|----------------------------------------------------------------------------*/
.jp-mod-sideBySide.jp-Notebook .jp-Notebook-cell {
margin-top: 3em;
margin-bottom: 3em;
margin-left: 5%;
margin-right: 5%;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell {
display: grid;
grid-template-columns: minmax(0, 1fr) min-content minmax(
0,
var(--jp-side-by-side-output-size)
);
grid-template-rows: auto minmax(0, 1fr) auto;
grid-template-areas:
'header header header'
'input handle output'
'footer footer footer';
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell.jp-mod-resizedCell {
grid-template-columns: minmax(0, 1fr) min-content minmax(
0,
var(--jp-side-by-side-resized-cell)
);
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellHeader {
grid-area: header;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-inputWrapper {
grid-area: input;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-Cell-outputWrapper {
/* overwrite the default margin (no vertical separation needed in side by side move */
margin-top: 0;
grid-area: output;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellFooter {
grid-area: footer;
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle {
grid-area: handle;
user-select: none;
display: block;
height: 100%;
cursor: ew-resize;
padding: 0 var(--jp-cell-padding);
}
.jp-mod-sideBySide.jp-Notebook .jp-CodeCell .jp-CellResizeHandle::after {
content: '';
display: block;
background: var(--jp-border-color2);
height: 100%;
width: 5px;
}
.jp-mod-sideBySide.jp-Notebook
.jp-CodeCell.jp-mod-resizedCell
.jp-CellResizeHandle::after {
background: var(--jp-border-color0);
}
.jp-CellResizeHandle {
display: none;
}
/*-----------------------------------------------------------------------------
| Placeholder
|----------------------------------------------------------------------------*/
.jp-Cell-Placeholder {
padding-left: 55px;
}
.jp-Cell-Placeholder-wrapper {
background: #fff;
border: 1px solid;
border-color: #e5e6e9 #dfe0e4 #d0d1d5;
border-radius: 4px;
-webkit-border-radius: 4px;
margin: 10px 15px;
}
.jp-Cell-Placeholder-wrapper-inner {
padding: 15px;
position: relative;
}
.jp-Cell-Placeholder-wrapper-body {
background-repeat: repeat;
background-size: 50% auto;
}
.jp-Cell-Placeholder-wrapper-body div {
background: #f6f7f8;
background-image: -webkit-linear-gradient(
left,
#f6f7f8 0%,
#edeef1 20%,
#f6f7f8 40%,
#f6f7f8 100%
);
background-repeat: no-repeat;
background-size: 800px 104px;
height: 104px;
position: absolute;
right: 15px;
left: 15px;
top: 15px;
}
div.jp-Cell-Placeholder-h1 {
top: 20px;
height: 20px;
left: 15px;
width: 150px;
}
div.jp-Cell-Placeholder-h2 {
left: 15px;
top: 50px;
height: 10px;
width: 100px;
}
div.jp-Cell-Placeholder-content-1,
div.jp-Cell-Placeholder-content-2,
div.jp-Cell-Placeholder-content-3 {
left: 15px;
right: 15px;
height: 10px;
}
div.jp-Cell-Placeholder-content-1 {
top: 100px;
}
div.jp-Cell-Placeholder-content-2 {
top: 120px;
}
div.jp-Cell-Placeholder-content-3 {
top: 140px;
}
</style>
<style type="text/css">
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*
The following CSS variables define the main, public API for styling JupyterLab.
These variables should be used by all plugins wherever possible. In other
words, plugins should not define custom colors, sizes, etc unless absolutely
necessary. This enables users to change the visual theme of JupyterLab
by changing these variables.
Many variables appear in an ordered sequence (0,1,2,3). These sequences
are designed to work well together, so for example, `--jp-border-color1` should
be used with `--jp-layout-color1`. The numbers have the following meanings:
* 0: super-primary, reserved for special emphasis
* 1: primary, most important under normal situations
* 2: secondary, next most important under normal situations
* 3: tertiary, next most important under normal situations
Throughout JupyterLab, we are mostly following principles from Google's
Material Design when selecting colors. We are not, however, following
all of MD as it is not optimized for dense, information rich UIs.
*/
:root {
/* Elevation
*
* We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here:
*
* https://github.com/material-components/material-components-web
* https://material-components-web.appspot.com/elevation.html
*/
--jp-shadow-base-lightness: 0;
--jp-shadow-umbra-color: rgba(
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
0.2
);
--jp-shadow-penumbra-color: rgba(
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
0.14
);
--jp-shadow-ambient-color: rgba(
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
var(--jp-shadow-base-lightness),
0.12
);
--jp-elevation-z0: none;
--jp-elevation-z1: 0 2px 1px -1px var(--jp-shadow-umbra-color),
0 1px 1px 0 var(--jp-shadow-penumbra-color),
0 1px 3px 0 var(--jp-shadow-ambient-color);
--jp-elevation-z2: 0 3px 1px -2px var(--jp-shadow-umbra-color),
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<h1 id="Tutorial:-Data-driven-System-Identification-with-SINDy">Tutorial: Data-driven System Identification with SINDy<a class="anchor-link" href="#Tutorial:-Data-driven-System-Identification-with-SINDy">¶</a></h1><p><a href="https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial23/tutorial.ipynb"><img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg"/></a></p>
<blockquote>
<h5 id="%E2%9A%A0%EF%B8%8F-Before-starting:">⚠️ <em><strong>Before starting:</strong></em><a class="anchor-link" href="#%E2%9A%A0%EF%B8%8F-Before-starting:">¶</a></h5><p>We assume you are already familiar with the concepts covered in the <a href="https://mathlab.github.io/PINA/_tutorial.html#getting-started-with-pina">Getting started with PINA</a> tutorial. If not, we strongly recommend reviewing them before exploring this advanced topic.</p>
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<p>In this tutorial, we will demonstrate a typical use case of <strong>PINA</strong> for Data-driven system identification using SINDy. The tutorial is largely inspired by the paper <a href="dx.doi.org/10.1073/pnas.1517384113">Discovering governing equations from data by sparse identification of nonlinear dynamical systems</a>.</p>
<p>Let's start by importing the useful modules:</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="c1">## routine needed to run the notebook on Google Colab</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">google.colab</span>
<span class="n">IN_COLAB</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">except</span><span class="p">:</span>
<span class="n">IN_COLAB</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">if</span> <span class="n">IN_COLAB</span><span class="p">:</span>
<span class="o">!</span>pip<span class="w"> </span>install<span class="w"> </span><span class="s2">"pina-mathlab[tutorial]"</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">torch</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">matplotlib.pyplot</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">plt</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">warnings</span>
<span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s2">"ignore"</span><span class="p">)</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">scipy.integrate</span><span class="w"> </span><span class="kn">import</span> <span class="n">odeint</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina</span><span class="w"> </span><span class="kn">import</span> <span class="n">Trainer</span><span class="p">,</span> <span class="n">LabelTensor</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina.problem.zoo</span><span class="w"> </span><span class="kn">import</span> <span class="n">SupervisedProblem</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina.solver</span><span class="w"> </span><span class="kn">import</span> <span class="n">SupervisedSolver</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina.optim</span><span class="w"> </span><span class="kn">import</span> <span class="n">TorchOptimizer</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pina.model</span><span class="w"> </span><span class="kn">import</span> <span class="n">SINDy</span>
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<h2 id="Data-generation">Data generation<a class="anchor-link" href="#Data-generation">¶</a></h2><p>In this tutorial, we'll focus on the <strong>identification</strong> of a dynamical system starting only from a finite set of <strong>snapshots</strong>.
More precisely, we'll assume that the dynamics is governed by dynamical system written as follows:
$$\dot{\boldsymbol{x}}(t)=\boldsymbol{f}(\boldsymbol{x}(t)),$$
along with suitable initial conditions.
For simplicity, we'll omit the argument of $\boldsymbol{x}$ from this point onward.</p>
<p>Since $\boldsymbol{f}$ is unknown, we want to model it.
While neural networks could be used to find an expression for $\boldsymbol{f}$, in certain contexts - for instance, to perform long-horizon forecasting - it might be useful to have an <strong>explicit</strong> set of equations describing it, which would also allow for a better degree of <strong>interpretability</strong> of our model.</p>
<p>As a result, we use SINDy (introduced in <a href="https://www.pnas.org/doi/full/10.1073/pnas.1517384113">this paper</a>), which we'll describe later on.
Now, instead, we describe the system that is going to be considered in this tutorial: the <strong>Lorenz</strong> system.</p>
<p>The Lorenz system is a set of three ordinary differential equations and is a simplified model of atmospheric convection.
It is well-known because it can exhibit chaotic behavior, <em>i.e.</em>, for given values of the parameters solutions are highly sensitive to small perturbations in the initial conditions, making forecasting extremely challenging.</p>
<p>Mathematically speaking, we can write the Lorenz equations as
$$
\begin{cases}
\dot{x}=\sigma(y-x)\\
\dot{y}=x(\rho-z) - y\\
\dot{z}=xy-\beta z.
\end{cases}
$$
With $\sigma = 10,\, \rho = 28$, and $\beta=8/3$, the solutions trace out the famous butterfly-shaped Lorenz attractor.</p>
<p>With the following lines of code, we just generate the dataset for SINDy and plot some trajectories.</p>
<p><strong>Disclaimer</strong>: of course, here we use the equations defining the Lorenz system just to generate the data.
If we had access to the dynamical term $\boldsymbol{f}$, there would be no need to use SINDy.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">sigma</span><span class="p">,</span> <span class="n">rho</span><span class="p">,</span> <span class="n">beta</span> <span class="o">=</span> <span class="mf">10.0</span><span class="p">,</span> <span class="mf">28.0</span><span class="p">,</span> <span class="mi">8</span> <span class="o">/</span> <span class="mi">3</span>
<span class="k">def</span><span class="w"> </span><span class="nf">lorenz</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">t</span><span class="p">):</span>
<span class="n">dx</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
<span class="n">dx</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">sigma</span> <span class="o">*</span> <span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="n">dx</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="n">rho</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="mi">2</span><span class="p">])</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
<span class="n">dx</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">=</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">beta</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span>
<span class="k">return</span> <span class="n">dx</span>
<span class="n">n_ic_s</span> <span class="o">=</span> <span class="mi">200</span> <span class="c1"># number of initial conditions</span>
<span class="n">T</span> <span class="o">=</span> <span class="mi">1000</span> <span class="c1"># number of timesteps</span>
<span class="n">dt</span> <span class="o">=</span> <span class="mf">0.001</span> <span class="c1"># timestep</span>
<span class="n">t</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="p">(</span><span class="n">T</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="n">dt</span><span class="p">,</span> <span class="n">T</span><span class="p">)</span>
<span class="n">dim</span> <span class="o">=</span> <span class="mi">3</span>
<span class="n">x0s</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">rand</span><span class="p">(</span><span class="n">n_ic_s</span><span class="p">,</span> <span class="n">dim</span><span class="p">)</span> <span class="o">-</span> <span class="mf">0.5</span><span class="p">)</span> <span class="o">*</span> <span class="mf">30.0</span> <span class="c1"># Random initial conditions</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">n_ic_s</span><span class="p">,</span> <span class="n">T</span><span class="p">,</span> <span class="n">dim</span><span class="p">))</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_ic_s</span><span class="p">):</span>
<span class="n">X</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">odeint</span><span class="p">(</span><span class="n">lorenz</span><span class="p">,</span> <span class="n">x0s</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">t</span><span class="p">)</span> <span class="c1"># integrated trajectories</span>
<span class="k">def</span><span class="w"> </span><span class="nf">plot_n_conditions</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">n_to_plot</span><span class="p">):</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">6</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">,</span> <span class="n">projection</span><span class="o">=</span><span class="s2">"3d"</span><span class="p">)</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_to_plot</span><span class="p">):</span>
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">X</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="p">:,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">X</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="p">:,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">X</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="p">:,</span> <span class="mi">2</span><span class="p">],</span> <span class="n">lw</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">"$x$"</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"$y$"</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_zlabel</span><span class="p">(</span><span class="s2">"$z$"</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
<span class="n">plot_n_conditions</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">n_ic_s</span><span class="p">)</span>
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E8u0Hs3fBY0FhdN3DXmTfLc9blayAqCQFdXFz6f77yR8mIhCAJjY2N0d3efMw0fv28yFxN1JqeSZ05dGxkZoa2tDZPJNE1wLtSJbylzObwCZvPF93g8uFyud/jix1P5i7m9MVex18bbalwsmrhrzAtFUZAkaV4Wsl6vl2AwCMCePXvmNEFsoYnXBPT09Mz74mKhTWxmm7oWt2vt7++nqakJq9VKRkZGQnQWy671UnO5RUqn05GRkUFGRgYw3Rc/fuwNBgNGo5GxsTHS0tIWteUxWezjnzFFUYhGo9Pc8zSx15gvmrhrzInkCCMe2czFQravr4+2tjaMRiMVFRWXRdjjaXhVVVm3bt28swaLfSKdOYgl7s3udDrp7OwkGAxOq8RPS0tblpX4S9HlbzZf/ObmZsLhMN3d3QQCAVJSUqa13i2mLz6gib3GgqCJu8Z5SU7DA3MS9mg0SkNDA16vl61bt9Le3n4plvoO4nv8paWlDA0NzTkKu5yDY2Z6s0cikURxXktLyzQHt+QU/ruhWn6xMRgMieLIFStWEI1GE5H9bBdai+2LD9PFPn6LRCJEo1ECgQCSJJGdna2JvcY0NHHXOCfJvevJLT/nwuVyUVtbi8PhYPfu3RiNxrP2uS8WsizT1NTE2NhYIg0/MjKyLEe+Jtu1ns3BDaCvr4/MzExSUlKW5Ml9KUbusxGvI4GplsecnBxycnKA6Rdal8sXH/4w8c7pdBIIBHA4HGcdgqNNvHt3oom7xqzMpXd9tsd0dXXR1dXFypUrKSkpmeb0danEPZ6GNxgM0/b45xuBJ699qTCbg5vL5aKmpgaPx0Nvby+CIEwrzptvn/dislTWcS7OlQGZzRc/Htkn++LH0/iL7YsPJCrtkyP7+Cz7ZLHXxtu+u9DEXeMdXMjc9XA4TF1dHeFwmJ07d+JwOKb9/lz2swtJchq+qqpq2on1QtPrl/LCZL4IgkBKSgoA69evB5i1zztenDdb65fGdBRFmbP4zfQ3SB6CMzQ0tOhmRslrnS2yn03s4xG9JvZXNpq4a0wjXrwz12gdYHx8nPr6erKystiyZcuse5CLvW8dHyubnIZfyDUsl5TybH3eZ2v9ysjIWPRq8GSWQ00AXPg6z+eL39/fj6IoiU6JuNhfzDGJf0/Ptp7ZxF5RFE3s3wVo4q4B/CENH6+Gn8sXXFEU2tra6O/vZ82aNRQWFp71vou55362NPxMLiZyX66cq/UruRpcG4DzBxbqIuRsZkbx49/b2wtwUb74yfUBc1nP2cQ+EokQDocRRfEd1fia2C9P3t3fYg3gwtLwwWCQ2tpaFEVh165didTw2VisyH1gYIDm5uZZ0/ALtYZLXS2/mMxs/TrbAJx4Gt/hcCxYgdhyOYaLlWFINjMqLi5GVdXEFsqF+uIrinLB78/Mrpe42MuyjCzLZ22908R+eaCJ+7uc5Gh9Li1uAMPDwzQ2NlJQUEB1dfWcTi4LHblLkkRTUxMTExNs3rw5IVbn4t2Qlp8vsw3AiYv9YuwZLwdRuFTbB4IgzNkXPy74M22Kz5WWv5D1zByCk1xYG//9zDT+XM8bGpcWTdzfpVxI73rysJX169cnBGEuLGRRms/no6amBqPRyO7du+dcIHalR+4LscZ4gVhBQcGCD8BZDscQLl9twMx6CUVREvUSo6OjCTOo5OM/n7T8fDmb2Mdn2Wtiv7TRxP1dSLx3PS62czk5+Hw+amtrMRgMcxq2MpOFqJaPD55pbm6mrKyMysrKeZ3Y3o177hfDbHvGyWnkmQNwMjIyFnwIz+VgqRT+iaJ4Xl98QRAIhUKJ2QSLOZNgPmKfPARHm2V/edDE/V1EsoXsfHrXBwYGaGlpuSBBjXOxkfuFpOFnW4OWlr9wZksje71enE7nnAbgLJdjuJjR8MUwW3HkmTNn0Ol002YSJBdHLrYv/rnEHpjVKncpHtsrEU3c3yVcSNFcLBajsbERl8vFli1bEt7nF4IoionXni8XmoafyZWalr9cUWbyABxg1gE4NpttWgp5KUTE52O5rDMumrm5uRQUFCRmEiR3QiQf/8UeQHQ2sY9PvAPweDw4HA5sNpsm9ouMJu7vApItZOda6ep2u6mtrcVms7F79+6LTvddSOR+sWn42dZwJYr7UmG2ATjx/frOzk5CoRCtra1kZ2cv6QE4y0XcYXqWYeZMgnP54scvyhaz7XE2se/s7KSsrCzxM0EQtMh+kdDE/QrmQi1ku7u76ezspKqqirKysgU50c13z30h0vAzmY9Ix4+d1vZz4RgMhmm+7EeOHCEnJ4dIJDLrAByHw7EkTuzLSdzP5aZ3Ll/85LbHS+GLD3+4wI9b4c42y36m2Ov1+mXzXiw1NHG/Qomnw06dOkVZWRnp6enn/ZJEIhHq6+sJBAJs3749kW5dCObTChdPw5tMpotKw89kruIejUapra1lcnIy0ecty/KCth29W4n3z882ACfu3hYXm8s1AGc+9rOXm/l8Jmf64ofD4cTxj/viOxyOaWK/0J/35L78ePFdnNnEXhTFdxToLZf35nKjifsVSLx3XVEUgsFgokf1XExMTFBfX096ejq7d+9e8L25uQjrzDR8VVXVgn6R57IGt9tNTU0NDoeD7du34/f7GRgYwO/3c/DgwYT4ZGRkLNnpa0uZZB/0mVatgUAAp9OZ2DMWhMszAGc5Re4XU/xnNpvJz8+f5osfT+Mvli9+PBs2G3MVe22W/dzQxP0KYmbvevyq91wRs6IodHR00Nvby6pVqygqKlqUL8v5IndJkmhsbGRycvKii/fOxrnEXVVVent7aW9vZ8WKFRQXFxOLxbDb7SiKwvj4OCtWrEiIT09Pz7RWpbm0gS02S70u4Fzriw/ASUlJoaSkZFZDF4PBME3sF2sAznIS94XKMiRfbM3mcRD3xZ8p9vN97flkGpLFPv7Zic++OJt7nib2f0AT9yuEmb3rycUsZxPVUChEbW0tkiRx1VVXYbfbF2195xLW5DT8nj17Fq1X92xrkCSJ+vp6PB4P27ZtIz09fdoxi58s4j3fxcXFCfFxOp0JgxGTyTRt+tqlGsiynJjrifdyDsBZbuK+GFtFs3kcBAKBhNgn++LHs1nny2TFI/EL2ddP9sSPPxdoYn8uNHFf5pyvd/1s4j4yMkJDQwP5+fmsWrVq0auWZ1tHcg99eXk5lZWVi/pFnE3cvV4vNTU1WK1Wdu/efVaBmPm4ZPEpLy+f1gbW29tLY2MjKSkpCbFfqpXhl5KLySxcygE4y0ncL1VPfnJmJdkXP/k9OJ8v/nxMs+ayHphd7CORSKL17t0s9pq4L2Pm0rs+U1RlWaa1tZWhoSHWrVuXKK5ZbGYK66VIw59vDfGhM+e7sJjLXv3MNrDkgSytra1EIpFESjMjI2NB53ovp5PVQq11MQfgLCdxv1xFnsmGRmfbRtHr9dPEPn6xtViZBiAh4Mmz7CORyLTIPl6cp9frr+huGE3clylz7V1PFne/309tbS2iKLJ7926sVuslW2/yOnw+H2fOnMFsNi9qGn4mcZGWZZmmpibGx8fn1GZ3IV/+2QayxPfr45Xhyfv1l6pY7EplPgNw4sWQZxOZpepQNxtLpbL/bL74brc7sW0VL9IdGxtLDMFZLJL97WeKffIs+7jYX4kT7zRxX2bMt3c97gwXj1JLSkpYsWLFJT95xXtc+/v7L1kafrY1RKNRjh49mvDIn2tR1sUWq1ksFgoLCxOV4X6/H6fTmfBo1+v1iSgzIyPjkl3wXEouZUR8vgE4cPY56sspcl+qFyLJxabxbauxsTGam5sZGhqitbX1nFbFC827Uew1cV9GXIiFLEyNaI1Go2zatCnhXnWpibfadHR0XLI0/EyCwSCTk5OUlZXN6wJnoR3qBOEPc73jHu0ejwen05koFrNYLNOK8xbTSexKZz4DcDIyMpZMNHw+4uK0FMV9JjqdDrvdjk6nY9u2bUiSlCiQnOmLH7/ouhS++PG1nU3sYWoL6MyZM2zcuJHU1NRFW9NCo50xlgnJvetzFXWPx8P4+Dh6vX5BzWDmi9frpbm5GUVRuPrqqy95VKooCi0tLTidTrKysqiurp7T45J7sheTmdO/kj3C47atyfvHi2EucilYKq16sw3AiQvN8PAwkiRRW1tLZmbmJYkqL5SFLFC7FCRXyuv1+ndYFc8sSL0cvvgwXewHBgZwOp3cd999vPzyy2zfvn3R1rDQaOK+xEnuXY9fpc/FQjbes22323E4HJdF2FVVpb+/n9bWVvLy8picnLzkJ8lQKERNTQ2qqlJQUDCvE2FcjC61t/xMj/BkJ7HGxkYkSSItLS0h9vH3dqmI57lYihHxzIurN954g/LyckKh0KwDcBZbaOZKctvrcuBcBjZz8cVfqG6IuRAXe1VV0ev1iddfTmjivoRRFAVJkuaVho9Go9TX1+Pz+di2bRtjY2MXPI3tYpAkiYaGhsREOVEUmZycvKRrGB8fp66ujry8PFatWkVnZ2diFOV8uZzCOdNJLBgMTnNyi58wh4eHyc7OvuxmOmdjOVx8xElPT6ewsBB45wCc5AEsGRkZi+7Jfjbix3M5Ru7n42y++G63+5L64suynKi4X0wfkMVAE/clSHLvery4Zy5X506nk9raWtLS0hI92xMTE4mez0tFvHfcYrEkJsp5PJ6Lmuc+H5Jd99auXUtBQQFwZUyFS94/jpvpxC1zx8bG6OzsXNJmOsshypxZUDdzAE4kEklcXMU92S/HAJzlFrlfTNvefH3x59P6eC5kWSYSiQBokbvGxTHTQnYuwh4fpdjd3U11dTXFxcWJx8xnYMvFkpyGr6iooKKiIrEOWZYJBoOJPeRwOJy4RaNRFEVBUZRpLlZ6vT5RuWo0GhP2mPGbw+F4R3o0EolQW1tLJBJh165d076QFyPuS5V4CxLAxo0bEUURt9uN0+lccmY6S+UC6VzE91rP9Z6bTKZ3eLJfjgE48cK/pfz5TOZcafn5MjOblSz2ya2P8ffhQi+4ksXdZrMtyNovFZq4LyGSe9fjbRnnIxwOU1tbSzQaZefOnTgcjmm/P5+3/EIRt3AdGxsjNzeXsbExGhoacDqdeDweQqEQAPX19Yl1mc1mzGYzRqMRURQTt3jbXCwWQ5KkxOCIUCj0DoGw2WykpaWRmpqK2WzG5/ORn5/Pzp073xGxXkwEvhyECc5upuN0OqeZ6cTFfiHNdObCUhei5DqLuTDbABy/358QmpkDcOIzCBbiOCy3KYWLaZV7ttZHt9uduOBKzq6cy+cgGVmWiUajWCyWZecwqYn7EuBC5q7DlBlEfX09OTk5bN26ddYCk8WM3BVFYWRkhPb2dlpaWvD5fIk9baPRSHZ2Nrm5uaxcuRKj0Uh3azMbV1UT9XqI+H2E/T5CPi/hiTEioSByTEKWYkixGIoso9OJGPV6RJ0BUa/DaLagt1jQGU0IBgOKTo+sMxBRJMYG+nEHgkiyTHt7O4cPHyYrK4v8/HwKCgoSX/q5inTy8V9Kafn5kmzuMjPK7OvrQ1XVhOgs9uS15XAM5yvuM0luc5zp3DY2NragA3CWSxtcnAv1lZ8vc/HFV1V1TtkVWZYJh8PTfBCWC5q4X2YupHddURRaW1sZGBiYtqc8Gwst7j6fj46ODtrb2+nr6yMWiyGKIllZWWzfvp38/HzsZhMR5wQTfT2MdzbSPdCHd3wMRZJ49ZWp5zHZUrA4HFhSHJjtdlJz8tEbDej0BnR6PaJej6ooyJKEIkvIMYlYOEQ44CfgnCQS8BH0eJCikcTabHo9jpxczGmZiJYUYmE//W0t1Jw5A4KQsMMMBoOUlpaSl5c3p5Pjchb3ZM4WZTqdTiYmJhKWoYtpprPUT5AXK+4zmesAnORtk7nWSCyXfvw4C5mWnw+z+eKfK7uSlpaWEPNkcV9IBgcH+eu//mtefPFFgsEgVVVV/PjHP2bbtm3A1Ofwq1/9Kj/4wQ9wu93s2bOH733ve6xYsWLOr6GJ+2UkPtFoPtF6IBCgtrYWgN27d5/3Q7cQ4u52u2lsbKS9vZ3h4WEEQaCoqIjy8nIMBgMbqlcQHB1msLmWI8/8Er9zAgCj1Up2aTkl6zdhy8iiZ3iU6269ndScXPQLUOTldrs5efwYJlTyMtIJupy4RwZxDQ3ibG8m6HYBkG4yYc8tQDZZCI4FObx/jDcEEaPRSGlpKVVVVVRVVb2jYOZS9blfLmaa6ciyjNfrfVeb6Sy0uM/kbANwnE7nvAfgaGn5C+Nc2ZVkX/x4ELPQGS2Xy8WePXu4/vrrefHFF8nOzk68Tpx//dd/5Tvf+Q4//elPKS8v5ytf+Qq33norTU1Nc870XNnf1CVKPA0fr4afq7APDQ3R2NhIUVER1dXVc/qiXKi4RyIRWltbqa+vp6+vD4PBQGVlJdu2bSMrM5PTB/YT6GnFNdjH734zDoJAdkkZVTt2kbeimuzSchzZuYm/KxqNMr5vH6l5+UgRFfewj/BoiIgrjByQUMISSkhGiSmoioowdaBAEEAnIBpFBKMO0axDtBnwq36GvENUrK5i5ZpydPp3pvsigQDjvV2M9XQx3tPJUFsrknMCM5CRnok5OxdPZ4iXW5p5UacnPz+fqqoqVqxY8Q4nv+UQuV/sGuMubTPNdJxO54KY6SwHW9fFFveZnGsATltbG5FIZFoVePIxX25peVmWl+S+9Wy++HHjrf3799Pc3Iwoinzwgx/khhtu4Prrr6esrOyCX+9f/uVfKC4u5sc//nHiZ+Xl5Yn/q6rKf/zHf/DlL3+Ze++9F4DHHnuM3Nxcnn32WR5++OE5vY4m7peYC0nDS5JEc3MzY2NjbNy4MdGSMxfmK+7j4+O89dZbNDU1EYvFKCsr4+6772ZFVRWjHa3UvPYChxprkSNhbOkZVGzZQfG6DRRUr8Gc8oc+UEVRcfb78bR7iAz4kSdCFLhT6X7zFGYBzKKACZiZ9I2vVH37JgDi2/8mkwYU4SDWOEm3MklUJyBb9AgOI/psM9ZyB+nlDgpXr6NozXoA+vr6GOrtIdtsZKi1iaHWJkLtzdhUlZScPJDDnOjt5tDBgzhSU1m5ciWrV6/GaDQuC3FfaM5mpuN0OhMVyclmOueqCl8ux+9Si/tM5jMAZ7n5ni+VyP18xEfX/smf/Alr167lxIkTPPXUU5SWlvLDH/6QT3ziExQVFbFv375pojxXnnvuOW699VYefPBBDhw4QGFhIX/6p3/Kn/zJnwDQ3d3NyMgIN910U+Ixqamp7Ny5k6NHj2rivhRJjtbn2sLi8/moqanBaDSyZ8+eeRffzEXcVVWlu7ubEydO0N3dTUpKCrt27WLdunUIsQgth97g8f/7L/yTExgdqVTvvY61e68jp7wS4e0vazQs0X98FF+zC3U4iDkYI0UAuyBgByIChHSgM+qRgICsoJNUjKqKmDx/HkAvIOjFhKKrAIoKUQVUUFSVmAqSCgoqAgIWRUUXlDAFY4ijQWhw4lVUhoCoVY+QYyWWo6LYzVRs207l9qsACHk99NXX0Ft3hr76Gox+H1azBXNuAY1jw5w8cYL0zExsNhsej2dZeUsvNDPbj5KLlOJmOsnFebOZ6Sx1Mbrc4j6Ts1WBO51OnE4niqJQV1c36wCcpYaiKEvKc2EuyLKMoigUFxfzjW98A5iarvnmm29SVFR0Qc/Z1dXF9773Pb7whS/wt3/7t7z11lv8+Z//OUajkQ9/+MOMjIwAJC7w4uTm5iZ+Nxc0cb8EXGjverxnvKysjKqqqgv60p5L3FVVpa2tjUOHDjE+Pk5ubi533303q1atYri1iYM/+C9662vQG43YSytZe8Pt7L7ldkwmE6qqMtnrY/L4KFKXF3tQwiIKmIGQTkCyGwnrBYwRGX1YxqSCQRDRpxow5FgR00zoHEZEhxHRYUC0GhBMU6l3Qf/Oq/vBwUGampooKymlorgcogpKIIYSkFD8MRRfFMUdRXKGkCbCRLwxoqqKHrCGJMx9PuiDqKLStO8t5Cwz1lXp5G7NpnrPtVTvuRZFkRnv7qKn9jRdp46j7+0kzWhC789jVGfkh319FBQVsWHDBlauXLkkLEjh8gjRzCKl+L6l0+lkZGQkMfUrvr88s0VzqTKfC+9Lzcwq8OHhYfr6+khNTZ02XTC5En8puRVeroK6i2G2grqUlBRuu+22C35ORVHYtm0b//RP/wTA5s2baWho4H//93/58Ic/fNFrjqOJ+yIT79eez5CHWCxGQ0MDbrf7oieozSbu8Uj9wIEDjIyMUFZWxs0330xRYSGdbx3lqa//f4z3dpNZUsbGex8iaE5hxapVlJeX4+r10/VGN2KPl1RFJUMQCOsEpHQTMYOI3hXGIqsQkzHk2NAXpWAoSkGfY+HV429w7XUb3nHCkRSJ8eAEI54RJv2TBCIBQlKIUCxEVIridrkJBUPk5+XjiXjoHugh3ZpOui2djMwM0kyZiML046rGFOSJENLY1C024CfQ5yMqq1hVsE6EEA+H8Rwaok8UUPNtpGzIpGBLObmVK9hx/0OM9XbTdfI4HSeOYB7sxWY0EQ04eaWjjf1pGaxZu5YNGzacdx78u4Hkfcvy8vLE1C+n00lPTw9+vx+Anp4esrKyLquZzrlYDnUBycSLQmcbgHOpx6qej+WSlo8TN9RaaF/5/Px81qxZM+1nq1ev5qmnngJIuPCNjo6Sn5+fuM/o6CibNm2a8+to4r5IJFvIzqca3uVyUVtbi91uZ8+ePRedxpop7sPDw+zbt4++vj4KCwt5//vfT3FxEW1HDvHz//x/+CbGKF63kTu/8Le4FAGPx8PGqrV4j3lp/tlJMmSFTCBo0RNNM2GJSJhdUfDHMBSnYNyUhaEyFX2eFUH8w98bjAXpinTRfqKdoeAQQ8FBxqJjeFQvUXGO9rgDs/9YUAVs2EjVpZJpzKTYVkxFRgUrc1ayuno1aRuLAQgNDuJuGWB1egWxPh/BTg9RVxSbrGIZ8iMOB+h7oZdgqhHzunSEUpWV19/Cyutv4dj+10lXY7QfPYRtogejO422iWFq3jpBXnEJGzdupLq6+oqvJp8rM6d+hcNhjhw5giRJS8JM52wsJ3Gf2Qo3cwBO8ljVvr6+yz4A51L1uS8U8bqohRb3PXv20NraOu1nbW1tlJaWAlPFdXl5ebz++usJMfd6vRw/fpxPf/rTc34d7Uy0CFxI0ZyqqnR1ddHV1cWKFSsoLS1dkJNMXNxDoRAHDhzgzJkzZGdn8+CDD1JRUUFvzSme+N9v4xzsp2LrTu7487/CmJ7JmTM16H0WsrsyiO3rJl0UCBlEork2LJKCbTwMzjCm6nRMt2ZgqHAgmnSJv6VppIl9HfuoGT1DX6QPt+hGFYAhsEpWUiIWHBEz+aF8LBEd5oiINSpiU41YBBM6GYjKGAQdOoMeSYoRjcWIKlEiBoWIQSBmhLBJJWhWiNhUQiaJUf0w7f52fj/5e2ifOgZ21U6JuYRScym5Qi6F1WXkbqnAASiBGNEuL5FWF/4WF6KskO2Loj82RvCISrc4iis7hlCcRuGmatbdcheTPZ20HNpPz+m3SJFlIp4xXm1v4VBOPps2b2bDhg1YrdaLfu+uJOIisnLlSvR6faJQzOl00tfXBzCtOG8xzXTOxXIT93NdEM02VnW2ATjJ3Q+LKb7LLS0fP3+HQqF5FTGfj89//vPs3r2bf/qnf+Khhx7ixIkTPProozz66KPA1PbL5z73Ob7xjW+wYsWKRCtcQUEB991335xfRxP3BSZuUmE0GtHr9XM6UUQiEerq6giFQuzYsWNBi7YEQWBsbIxHH30USZK46aab2Lp1KxN9PTzzj19huL2FwtXrePCP/4yciip6e3upfeo0uQM2siUVhAihLDNkmLD0+WE0iHFlGubrizCuSEUwTp0MJvwTPHv6WQ71HaBL6iakCyOoAmnhVDICVlb6MsgJpbA6rYKiojIchTnY0tOxpWdiS0vHZLWiM0xVpbe2tjI4OMi6desSKao4qqoiRaOEfV6CXg8hr4eA24VvYgzP2CjeoTHcYyN4pQheh4A7XcWVJjNhGafd2E5UF+XHz/8YBw5W21azs3An11ddT9G6ShzAeMsgw8e6SB83I3khX9FROq7HP2JmpHaIxrwOrCsMFF93K6tvu5fJtibaDr9BrL8dg3uUk0N9HD9ymDXrN1z0lsqVyrnMdOJ9xnEXt7jwXKp08nIyhplvK9zMATizDV+JV+JnZGQseDZluaXl4xcjwWBwQU1stm/fzjPPPMPf/M3f8Pd///eUl5fzH//xH3zgAx9I3OdLX/oSgUCAT3ziE7jdbvbu3ctLL700r4JqQV0uPSpLnOTe9VdeeYVrr712TsUsExMT1NXVkZmZydq1axc0revxeHjuuecYGBhgzZo13HjjjRh1Iseeepz6V18ivbCIPQ9/iJL1m4hFY5x8ugZ7s0yeoCMsAKV2bJKCPBBAdBgwb8nBvDUbnWNqq2DQNcgvT/6Cw6NvMqgbRhVU0kOp5HkcVEo5bMtcT9XKdeRWrCA1J483Dhxg69at77h4UVUFSfLg9w/R1HyCUCxAWk4uUUUhHAu/fcIFvajDYhSwm83YLQ5sJgd6vR2jMRODIRNR/MMWRtDrwTnQx+RAP+O9XYx2tjMxOow/1YgzR2QsM8qweQK30Q0C2LFTqa9khW4FD2x9gMriSsLOALEWN4GT44TGI1hEAb0g4JJVnKkC3rIQij2Mw2FHDPoYrT3FQP0ZBJ0eOT2bgD2d8lVr2Llz5zldBC8WRVF444032LNnz2XdUz0XkiRx8OBBrr766vOmgpNd3FwuF16vN5FOzsjIWNRZ3h6Ph/r6evbu3bsoz7+Q9PT0EAgEWLt27UU/10xrYpfLteADcE6cOEFFRcWyqVHx+XycOXOG73znO9x111189rOfvdxLmhda5L4AzJaGP1/7maIoCQvX1atXU1hYuGARg6qqNDQ08Oqrr2I0GqmqquKOO+6g5/QJDv3ix8RCIXY//EE23HwHOr2ezgM9BF8fYYUgEtbpiVSlYvVHUHp8CAVWHA9VYVyVjqATiMQi/PLoYzzX+Vt6dFPp1JxQBrv9q7g6fSvbt15LQfVqDKZ3XmEKQpCOoWN0N47TNupm0C0xGRQJRI14o3a8UTtBqXhOf6NBjGLRD+MwtpFq8pJq9GI3hsiwRshOMVCalU5FdimlO1ew5vrdGAxpDPR0U3/sCJkmAyMdrQydbMVjzGO8UMdIRpguaxc1xhqeOvwUlcZK9uTv4fbq28laV0HTweNsT1+D79gYBneMCp+KXG9mTLAQqTZBuRHbxh1UVK0h3NfJeGMtwtggE+4xftVYT1H1anbu3DltYt+7kbn87TNd3JLNdDo6Oi7aTOdcXElp+fkwlwE48f7v5FbH+Ryr5ZiW1+l0BAKBZTcRDjRxv2ji0Xpy0ZxOp0sI/WwEg0Fqa2tRFOUdY0kvlmAwyEsvvURrayvr1q3jxhtvZP+rr/Dy/3yLntMnqNi6g6s/8DHsWdm4er30/7KV3JCCQRSJrUnH5o4gt7kRS1KwP7ISQ1UqgiDQO9HLd974NscibxHRRUiPOdjtXMM9pTez/eZbcGRN35NSVZme0SbeaG7kTN8EPS4T/b5cgpIOyEMgB7vRj80QwaQDh1GlOE0l06HHYUkhxWzFqtdjEgV0wtTAF0lWCasCAUnGFw7iDYVwBx14w1l0+WT8ERF/7A8XFRZ9iFzraYrsv6PANkmeXSQ7zcTGLbez+a5bEAUbnTVnOPPG64Q6B/GNK3jSCxiu0NGbMsFj0cf4Sd9PyBPyWMUqqvZUk79jHfJkmMiJMVw1LjIlBVNrBHeTiik/h5S91cir1zCxeScDtSdxN9dh62nG7Rrl6aZ6squq2bVrF+Xl5ctGRBaCi0kQLqSZzlzWuVzel8V0qDubRavT6WR0dJS2tjaMRuO8BuAsx7S8Xq8nEAhgt9vP/4AlhibuF8jM3vXkorlzRe4jIyM0NDRQUFBAdXX1ghawDA4O8swzzxCLxbj//vtZtWrVlDnLC0+hF0Vu++xfUrV9F7GwROOjjaT1+8kSwFdqJdNiRGp0IeRbSf1wNcaKqdT50dbDfO/E/9Ci70BURSrdBdyZeS133fUwjuzpJgsu/yQv1R7hjdZhmsftjAazgSwcRiOppgDlqW6KM01sKV3BFqtE7lgPIydrUCf6ccQiMOlC9fhRAxEISgixs2c/VIMAFh2q3YDgsCCk2hBzM5HzixnLqqbNVEZLJI1ul5VWdx5HhgwoqohOkChq6KQ8dR+ljlFyzSLV121l+/o/QYka6auvoevUcXoOnyZgSGO0ykJH+gQHzQd545U3KNOXcWvJrdxz/T0U3FpMrMuLd/8w+uEQ+aMhor8JMW7WUXBzBZs+ugW3y0XrscN0Hd6P2t9OYHKE59ubSStfwXXXXZeokL0YlosYwcKs9WxmOnF/9rmY6ZyN5STul1IsZ7Y6zhyA09zcjNVqnSb2M7dflmO1vCiKBAKBZVkgq4n7BTCzd32m6cVskbssy7S0tDA8PDxrodjFoKoqNTU1vPLKK+Tn53P//fdjNZs59PMfUfvK77HmFXL3X3yJ7MIiho6PEnyhl2xVZcIOuauyMNQ4UWwS9vsrMG3IRBAFjrUc4VvH/50uUy8WzFzlWctHN3+IjduvQRT/8AUdcY/z7MlDvNrioWUiH0m1kGFOI8McYHWen6sq1rDbGCG3p5GBfb/HMjgEw04EScUPWE0qchqE01SUdBFKrIgpaQgpVgSrGdFgQtDrUQUVVAFBUlEjMYjGUANR8AZRvUHwjCL09KObPENuTCAXuBpQUnVQ7kCuLKczdwP7YoUMmco4M5bNGwNTkUZR2yCra79NSZqbtfnZrHvvjVz/x5+it6aWrlPHqTx2Bp9uBUPVZjpSR3m081F+0PkDNlo38vDah9nzx3vAJxE6PELgtJP8iAy/66fj9wMYd2Zz1W33sPuue+mtq+HU755msruDsHOUZ7o7cJSUs2XLFqqqqpa0u9jFslilPecy04n3epvN5mlif649/+Xk1345xfJsWyfxFH5DQ8M7BuAs57T8cozctYK6eTDX3vU333yTlStXJqpS/X4/NTU16PV6Nm7cuKCuUZIk8fLLL1NXV8eWLVu46aabCHncvPhf32S8t5s97/sgo4KRrRt2MPJkH1njIYKCSmyDjawhFdkVwbo3H+vefASjjjOdp/jmoX+hzdSFVbJwTWQTf37nX5GTX5J4zUgsyu/PHOJXpwapH81FUQUKU4bJsilsKlvLbdl2StvOEDz8KtHTDRCKoYoQK1SIlYJSlEYwMx3LihJSirMBFVkOEI1OEIuNE5M8SJIXVT1//7tOZ8dgSMOgT0dvSEcn2ND7DYjjMdQxH2qfE6V7FKHbh8419VFXTBArt+DduImG0hs4GM6hcTSIL2JAL8ZYm9HK2qxWVmSbWFd6NYXpO9j/9PMYvE76G2rxp1vpWynSbOvBZ/SRSiq3FNzCBzZ8gGxTFpE6J659w1N2uKLAuKyibMyg/LYiDCYdQy1NnPztrxlpbwWbnWBGHraCYkpLSyksLEycNOdaHKeqKvv371/SBXXRaJQ333yT66677pKe4JPNdFwuF36/H7vdnhD7me1fExMTdHV1sWPHjku2xgulubkZk8lERUXF5V7KO4gPwIkf90gkgqqqFBYWkpOTs6B1EovFwMAAk5OT3HXXXbz++uts3br1ci9pXmjiPkdmFs2dy6Ly6NGjlJeXk5ubm0hZxUeLLuQHOhgM8uSTTzI2Nsatt97Khg0bGGpt5qX//jdEnY7b//xL5FZU8frP9lPWbiUFGEqVKCrOgEYf+iIb9nvK0edacXom+Lvf/g0nDLUYZAPXSFv44p1/Q1b2H6q8B5wTfH//AV5o1uOP2SiwDZNjC7KlYjP3pJvJOfY6vldeQBkcR9VDtEIhukaHYcNKjKurGXGNA25UdQBBmEw8r8GQhcmUj8mUj8GQQ0A14ld0BBSBiCoQUWQiioysKqCqqKqMKKgYBRUTMUxCFJMawqgGMasepMggkuRKPL9e78BiWYHsdhBudmIfi2HumkRocSEGQdWpyBVWxrZs5XDxzex32uhxTn0tylN72JJTR6ndx9bqO6nI2EXXWydpO3KQ8aF+JirTac130WPpQxEUNtk28bGNH2Nz7mbk/gDuFwaQJ8JYRIFJWSW2Jo2yO4sxmnUMtTTy1rO/ZqyzHVJSCWbkkl+9hoKCAmKxGDabbdq41bNFactB3CORCIcPH77k4j6TaDSaEByn05lo/4pfUIXDYXp7e9m+fftlW+NcaWpqwmq1XtSEsktFIBDg+PHjZGdn4/F4pg3AibfdLbWsVW9vLz6fj2uvvZb6+nqqq6sv95LmhSbucyAercfTSuf7EJ44cYK8vLzEcIfFsCh1uVz86le/IhKJ8NBDD5Gfn0/96y9x6Oc/Iq+qmts+80XM9lTaf9mGo81NWFDxrhEpGjWheGPYbirCsiMXRVX472f/laeCLxDWR9geXMtX7vp78nL/ULVe09vL/+w7wpu9GRjFKJVpPRRkFPO+VetZfep1/L/9DcrgGIoNQptklO2ZWLbtRLRYCYa68PlqUNUYqmpEEMrIzd1JzFTEYFSkLxRgIDDMkGcIp9OJ7JOxSlaskhWTbMKgGtApOkRVREREnRojgyqoSIJETIwRFaNExSgRfQSvwYsuVUe6PZVsi51Mg4EcA6SER0mT+7Hopy4qRNGMzbIG60Q2YosbpW4AoW4cMQSyAzxbyji5+lZeU1bQNKYgqwKr0tvZmlfL6hwrGyvvwBrOp/nAftqPHyZoMdK71kh9Sgd+g59CXSEPr3yYu1fejeiS8TzfT2wggEUUcMoq0epUyu4uxmjRM9BYx8nfPsl4dyeqI51wdiEbd+2hqqoq0f+d7Og282QYF/fdu3fPe7DQpSIu7tdff/2SOYknt3/FBT+ekauoqLisZjpzoaGhAYfDQUlJyfnvfJmJxWIcOnSIa665Bp1ORzAYTBxzt9sNMK3tbilsUXV1deH3+9m7dy+Dg4OL2s66GGjifg7iveuSJM3LQvbo0aMEg0EcDgcbNmxY8GhqeHiYX//615hMJt73vveRlprK4V/9jJoXn2P9Tbez9/0fIeKV6Pl+I9lhmWFjDOtKC6nNMrpsC473VqLPtlDfcoqvHPkqA9YRikK5/M3WL7Fzw7WJ16nt6+NfXjzBqaE0MsxOiu0jbCrfznsNMezP/4rQm0dQ9RDaIiHtSsO6cy/oVNzu40Rjo4iihVTHdmR1Faf6Q/SpYUbVcSadk1i8FjIjmdglOwbZgMg7o7n4J1MFlBlDXwVAYGru+2xviYqKIqhIooRf58NtcjNuGUexylTk5lJmsVCq95EptaJTvAiCnhTzOmz9mQinR1He6kU3GEE1qHg2ZfNK5XW8ad1Bu1NAJ8hszqlnR1491YWr2VR8D4Nn2ml641WckxOMrk2nLnOAEfMINmy8p+Q9fGjjhzAH9Xie6yPS48cqCrhllfAKB2X3lWI06+itOcWx3/wS7+gwUloWFJaz54YbWb9+PZFIJHGx6HJNZSWS95GPHTumiftFoqoqvb29DA0NYbFY8Hg8l81MZy7Ep8EVF8+tffRycq7Mjaqq+Hy+xEWWx+NZEgNw2tvbcbvd3HjjjXg8nmUz/CiOJu5nYT5p+OTH9PT00NraSnZ2Nlu2bFnwE1l3dzdPPfUUWVlZPPTQQ5iMRvb98H9oPXqIqz/wUTbecicTzS68T7RjVVX6C2JkxEQcE3osV+Viu6kYGZl/feKr/E7cj6CKPJL2Hj515xcSa20dmeBfXjjA4d5Usi3jlDmG2Fp5Pe8NDqL+7IdInb3EiiG4R8F48y70jgw8npNEo4MYDJlkZd6Czr6TWo+Pl5teZ3JskpxADpmRTIyKEYF4xAkxRCRJwCpJpIZDZAT8pPtdpHqcpHjd6CNRxJiEKMkIsgoCqIKQ+FfV6ZBMRkIWK35bKt4UO96UFLxWGwGziajRAIbpF2UKKiF9kAnTBMMpwzhyzFSl2qkwRChUWjCqAYzGHOyhdehPeODNTnTdQRSDytjWIt7YeD8v+EsYD4hkmSe4uugo63KCbKi4G4snh/pXfs9gazP+ihxqiyfotHRjxMid+Xfyx1v+GHvUiud3fYQ7fdjeTtfLGzKouLMYQVRpeXM/J599knDATzQtG9vKtVx7w42J9rn4yTAu9h6PB1VVyc3NJTs7+7xFY5eDuLf8DTfccLmXck5GRkYYGhpiy5Yt0yrCnU4nPp/vkpnpzIXa2lqysrIoLCy8bGuYK6FQiGPHjnH99def977JA3DiJkbJA3AyMjIuyejYlpYWxsfHueuuu4hGo8tuboQm7rMwW+/6+YhGo9TX1+P3+xMngMrKygVdV1dXF7/5zW8oLS3l/vvvB0Xmpf/6NwaaGrj5k3/Oiqv20L9/EGH/ABLg2iRQMmQm5gwh3ppLzs4y2jrq+dv9X6bHPkhlpIR/v+PbFGVPtWN5QzH+9cV9PFUnkG5yUZHax+aK63jQ3Yf6o/9FHh0nvE4leKsJ+46rick+3O6jiKKRrKzbSEm/iZMeD68378fX66MgUIBN/oP5g6QKRCUdWaEQ5ZODlPR3kjI2iSi9/REUVAxWGb1FRm9W0JsVRKOCqFcR9SqCqIL69nx3VZia7S4LyFEROTL1byyqRwrpkIMiJHXSBVNsDBYUM5yVjSstjYjVhKoTQRBQUYmJEhOmcfrsfWQWWFhjN1MuDJCjDqHTWZEHS8jtMCMc7kbXF0JyqDRdu5PnCu7i+LgZRVXZmlPL7sIzrCraQ6X1Khpf3U/XqeMECtJpqAzQZu1EEARuzLqRT2//NJlSGp7n+4h2+bCIAmOyin53DqU3FCBHI9S98jtqXnoeRVEJZeZRsGk7N9x4Y6JCOXFc33Z/y8/Px+v1EggEcDgc04rGLnfxUigU4ujRo0te3IeGhhgdHWXz5s3v+F2ymY7L5SIUCiWO80Kb6cyFM2fOkJubuyzSxX6/n1OnTnHttdee/84zmK0o8lIMwGlsbGRkZIRHHnkEr9d72b9D80UT9ySSe9fjLTFzEfbJyUnq6upIS0tj3bp1tLa2YjQaWbly5YKtrbu7OyHs73nPe5CjEZ775j/gHBzgzs/9NYWr19H+eDuOFhdeUcGwNxX7yTCCRUf3miCF68o4cOI5vuf5BVFdlA9mv49P3/w5BEFAUVR+/VY9//56LxFJZEtOLTkZ2/i4ScXyw+8g9Q0S2qYSutOGY911BAItBIItWK3V5OU+yKiugmcaXmCgbYAiXxEW2TK1N64KBBUD2cEwG/qbKGxvQx+SQFAx2iXM6TEM6SrBjFTGUjJxC0bkiIQ1FsGuBLAQwyBIGEUJvU5Br5PRiQqCGhd5ARVQVQFVEZBUkZioR9aJoFOxyFGsoTCqXyDiNRByGwm5jBCZOqYRk5G+sgr68wtxpjmQTYaE2Af0QYasg7iznKzLcVAu9VJlmcCgt5Pm3IDh4CQc7EEMKLhWpLBv7wM8E1nDZFBHeWoPNxYfojqviPUF99J98Awth98g6DDTvFqhydqGLMpcm3Etf7HzL8iU0nD9pgdlMIBRgBEEbDcXULQjm5DXw8nfPknLwf1gsRLKKWLztTdw1VVXTYte9u3bl0jLz0zhS5I0Leq5HPuZ84ncLieDg4OMj4/PabRmOBxOHGOXy4Usy4l940txnE+dOkVhYeGCttUuFl6vl9raWq6++uqLfq7kATgulyuxBZp8kbUQLYJ1dXX09/fzF3/xF4yMjCzZ7aSzoYn72yiKgiRJ80rDK4pCZ2cnPT09VFdXJ6xFm5ubEQSBVatWLcjaenp6ePLJJykpKeGBBx5AicV47pv/gGtogHv/+qtklZbT+r+NZI2GGDXL5O3NR903jqHMjuPBKo6ePMyzdb/gQEYNaZKDb133LdaVbACg3+nnL598g5ohMxuz60kxp/Lxqs2U/vDfidY3EFkL/vuN2Ddcg9/XQDjSR2rqVeQVfIQjThcvn3wZ26CNjGgGKioCAj7JQLnHybaWEzgGJhBUFXNGDHOOhL8gg7aMCpwehbzwJHkGD1lWL+kWH2ZdLPE3e1QrY2o6Piz4Vcvb/1qJYECHgoiCiIpOULAQJh0/mfhIF3ykCn5MgpR4rpikIxIxEJENRHUiRiRMvhihcRO+cTPhSQOCDJJOR095JV2lpXjSHCiGqTRcRIwyYOtnMn2MVXk2NhpHKRRGMImFpLeXIrzahVjvJGqHEzddy5Npt9LmMpJhdnFj8QHW5UtsKHkfk2/10bjvZYIpZtrWCtRam1BEhVuyb+EzOz6D3Wdh8tddiM4IOgGG9CJ5D5WTVeFgoq+Hw7/8CaMdrciOdMTSlVx7621UV1cjCMI0cU8mbvISF3u3241er0/sIc+n5e5iCAaDHD9+fMmLe7z9aePGjfN63EwzHbfbfVFmOnPhrbfeorS0dEEnli0W8eE0u3fvXvDnTh6A43K5FmwAzpkzZ+ju7ubrX/86nZ2dmrgvN5J71+PuVHN5E0OhEHV1dUSjUTZt2jTN5KC1tRVJkhZkoEN/fz9PPPHEH4RdivH8v/0jk/29U8JeUkHLd2rJ8cQYylQp31RA5PVhzFuySbmrlNHhPj7/3Bdoz+hjo7qW/3rge1iNVlRV5efH6vm3VwewGvxszG5kVcG9PFjzKpEnn0Aq0OF+bwT7VTcQDvcTCLaQnn4deQV/zGtD7bx+9HUKJgowKVPCEFF0pPhCXN1ylOyeEQRBxZYXQSlLoaloLb1OkfLIEFUpwxTbJzCKEpIq0qKW0KyUMKjm4ZWyiEXs4Bex+f2Yw270sQA6KYBeiSIgoQogCSKKKCIJOlTRQFhvJaS3ETDYCZrs+E0OIlY9emOQNJ2TYmGMEmGUdUIvK4V+zOLURUQkoiccMyLpRCzhCKERA56RFMLjegQFPGmpNFWvZiQvl6jZBIJAVIzRm9KDN8fJlmwD68ROMnRRUn0bsOwLIbzRAzGF1l1VPLnqYY45UzGIMW4qeYMt+WOsL/0jPKeGadr/KgG7ieY1Kg22FgRB4O6Cu/nk1k9iGREY/003pqBETIWJDBPlj1RhcRjoeusYR371M0I+D5H0HHI2bufGW26hrq6OXbt2nVdA4vuZcbGP7yPHq/DT0tIWxRglGAxy4sQJrrvuugV/7oWkv78fl8vFhg0bLup5FEXB6/UmxN7r9c7LTGcuLKdBLJOTk7S3t3PVVVct6uvM7IBwu90XPADn5MmTtLe381//9V/U19cv6roXg3e1uM+0kJ2rsI+NjVFfX09ubi6rVq16R6FFR0cHwWDwok8QExMT/OxnPyM3N5eHHnoIVZb53bf+kbHuLu790t+RWVJB87+fIT+sMl5qpKQkk9ChYSx787HdVETN8Tf4u4Z/ZcQ2wX2Wu/j/3fdVAJyBKJ//1Rsc6xXZnncaqzmPT2UVk/Htf0AOePDeGUG4cw2i0YLX+xZ2+0aKiz/Ha8O97H9zP/nOfPSqfipKl41sHu1i04mj6MIK1uwI6go7R0t2MD4UYru+ner0ATIMfkKqkePKapqVlXhDuZiGZQqG23CER5D1Ck6bhYDFTNigQxYBRJhWJT9VN/9OhLdvyfdXEZQYggIxzPjFVMYsJYym5COnKBTrh1gvdrFbaGaN2I1eUJAkkXDUiCIKU+1rA1a8Q1YIQdBioXHNOgaKChJC79cH6HC0YyuUuMoRoFrsw6YUk3oqB+HFNsTRCMMr03hmzyO85ClBQOKGkoNsyx9kXclD+E6P0fDGawRTrTSsjtJsbUMv6Hmo9CE+tvljqI1+Jn/fT4oCHlkltCqVqvvLUJQotS8+T82Lz6HodISzC0mtWMl9990373HB8RRnXOzP1XJ3MSwXce/r68Pj8bB+/foFfV5JkhIObk6nM+F6djYznblw7NgxVqxYsSzGCo+Pj9PT03PJ/QNmDsBJzqgkV+LP9hk/fvw4jY2NPP744xw7duySrnsheNeKe3LvuiAIc0rbKIpCS0sLQ0NDrF27lvz8/Fnv193djcfjmdO+3dnw+/089thjGI1GHnnkEYxGAy/+5zcZaKrnnr/6CmmFpbR/q5a8mIBvfSo5VjPhE2PYbi7Gujef3z3zY/7D8zP8xiAfSfsQt66+nfLyck71TvDZJ44TicW4uvAoWRnv4SOnXyL67DNENxjwvB8c5XtxOg9gMKRSUf7XtIRS+NXrvyJ7JDsh6gHJyPXdpyg/3YSoU7BWyHRu3Mbrrjyuk0+zObOTDL2fYTWDQ/JmxoIVWDq8VPXXEjGrjKWn4rSZiYkqvN2/LhD/KOpAZ0cU7CDaEQQLgmAEwQCCAUGYinhUFFAVQAFVRlVDoIRQ1TCqGkJVfKD4mH5BMPVYWVHwi2kMWcvpc5SQbp1km9jGDUItm3Tt6ASFaERHWDWgD8t4u824+u0QBF9KCrUbNjKSn4tkMKCiMmwdYii7ny15Ipt0HWQazGR0r0f32y7EVjeTpVaevvb9/C6wElWVua7oTXYU9rCm6L143xql6eA+IvmZnKl002rtwCE4+PS6T3NX5V0EXh3E/9YEVlFgVFEx31BA8e4cfBPjHPv1z+k58xay1Y5QXs0Nd97NihUrLkiQ41FP8j4y/KHlLiMj44JTy4FAgJMnT15QQdWlJG5csm7dukV9nZlmOrFYbN6mLkeOHGH16tWkp6cv6loXgpGREQYHBy+7y1uyPbHL5cLj8UwbgJO8TXXkyBHOnDnDq6++yuuvv74gr/+1r32Nr3/969N+Vl1dTUtLCzC1xfDFL36RJ554gkgkwq233sp3v/tdcnNzZ3u6c/KuE/cL7V0PBALU1tYCsGnTpnMOEujr62N8fPyCP8iRSIRf/OIXBINBPvShD2G32zn4sx/SsO8V7vr832AvKqPvu60UxETC27PJMOgJHR0h5e4yzFuz+cXPvsX3hWcRBPiPa/8TvUuP1WrljeEo33q9nzJHH8WOSe4uuJ4N//11YpNjeB4Io7t1HTHJTzjcS0HBIxgzHuS/X30UY6cRs2JOiPpNHScoqW2ZqmZfY+T31Xcj9vZxc0YN1bYBvKqVffIOxj3lFJxpJz0wyHBmOsPpdiKiwlSEraACoi4LUZeHoMtCNGQhiumo2BAEMfF+QQS9GkZUowiqhCjEEFAQEFESO/A6VMGEjBWS5rqrqoKqeFBVD6rsRpUnUaQxVHkciO/LG5EBv2BlwFJFV3o51eZurhdruFk4RabOixQTCct6dGEZV2cK7l4bQhQGCwupX7MWT0YaCAIBfYDW1FZyimWusgxRpveTObIJ4/OjiDXjuPLMPHPDgzwfXUdMVrmx5AA7C/tYk/9HjLzRROfJ4wRXFnCksI9ByyAl+hK+tONLbErdwOSvulD7A+jf3o8v/EAl6cUpDDTW8coP/hsp4CeSkUfh9l3cdMutF92Xm3wiTE4tJ7vmzTW1vFzEfSFnpM+V2cx0gGmCM1t0efjwYdatWzfvbM3l4FxdCJeT5HbHeNud1Wqlrq6OiYkJotEoHR0d/Pa3v12Q1/va177Gb37zG1577bXEz/R6fWJr5dOf/jS///3v+clPfkJqaiqf+cxnEEWRw4cPz/u13lXifiG96zBVQdvU1ERxcTErV648b5Q/MDDA8PDwBaWgFEXhySefZHBwkEceeYScnBxOv/BbjjzxGNd95JNYy6qYeHyY8qiB8JZsMuwGggeGSLmjFOPWTP7vh//IYymvYsLIT+96jKK0Is7U1fPoqRH29QhcW3SYmLCSvzLoMH/nX5HK9Dg/FMKx8hqczgNYreVUVv0jz7WdofZgLZnhTFQgrOjZOdTCqsMnMZgVpPUp/KL4blZN1HFDVg0FBie1cgV14e2knRojb6KT/twc+jNSkFDejswBXRY6fRmioRidPg8EC6qqolOcmNVJRHkSWZ4gpniIyn5iSngqQp8HOvToRCNG0YpJn4Zen4EiZhBVU4iKWaii9W3Rd6LKoyixIRRpEFVxvv0MRiKCjnF9Nk1pG7GmBLlTd4J7xCPk6NxIMZGoqkOZFBhrTyc8rCOmN1CzcRN9pcXIBgOyoNCd0kW00MnedCer9eNkODdgfsGLcGwIb6aJp295kGcjGxCIcXvZa2zO91Kd8R66XjzKUHsrExvzOJzVjNvoZottC3+9+6/JD2Yx/ssOzAGJkALuIhsrPlDJwUP7sHkmqH/l9yh6A9H8MnbddidbtmxZsBaeeGo5Lvbzmat+Ma1Ql5Lu7m5CoRBr1qy5bGtI9jGIR5ezmekcOnToHfU+S5WBgYGEW+dSJt7u+N3vfpcnn3yS/v5+UlNT+fjHP86NN97I1VdffVEjur/2ta/x7LPPUlNT847feTwesrOz+eUvf8l73/teYKrXfvXq1Rw9enTe9QrvGnFXFIVoNDqvaF2SJJqamhgfH2fDhg2JedLnY3h4mN7e3gsqHjlw4ABHjx7loYceoqKigo4TR3jpv/+dTXfci2XFWmKvhakMGgitSSerwEbgtQFsNxdj2pnFd//nKzyRdQibYOWxu39GniMPdzDGR//vFdomddxV8RJh3Z18ruEg6gvPE7xRR/BBB0ZrNn5/I4UFH0aX/l6+89vvkjaUhoAIqkCuz8d1+15CL0no1lv4Xtl7WOes5/bst8jRuTkkb2Z0rIrKI2/hsZtpLyrAL0bflnMVUV+IzlCNzliBIDpQlSBmZQid1E841kdIcp1VwI2ihEmUMOpUDHow6EAnquh1U/vrCqAqKjFJIRyDqCwSlXVElamIfjZMohWLPhOjsQBZl0eQPFTRhqoEUeQBlGgvcqwbVD8gIgkmxvVp1KduxmyP8YD+Te4XDmHXhYhGdKgqeDstTLQ7IAy9paXUr12L354CAgxaBxnPH+CqLB+bDCNk+dZgfS6IeHSIyXwrj9/4fl4KrMSiD3JXxUusz9NTab6VxmdfwTk5Tt/2TI6n1BHRRbg993Y+t/NzCPUh3C8OYAPGZJX+Ej9XPbSVqNfDoZ/9kOHWJmL2dFLWbOLWu+9ZlHap5LnqTqczUbgUT+EnW7f6/X5Onz7NNddcs+DrWEi6urqIRCKsXr36ci8lwdnMdILBIFVVVeTn5y95g5W+vj68Xu+ib3csFHFL52effZbe3l4qKyt5/fXX6e/vZ9euXbz++usXVBD5ta99jW9+85ukpqZiNpvZtWsX//zP/0xJSQn79u3jxhtvxOVykZaWlnhMaWkpn/vc5/j85z8/r9e64sU9noaPV8PPVdi9Xi81NTWYzWY2bNgwL1vPsbEx2tvb2bNnz7zW2tbWxlNPPcV1113Hrl27mOjv5Tdf//8oXLeJlI07SGm2UTYKgTIHeZsy8T3bjfXaAszX5PLd//kKj2cdxIGdn9/3C7JsWfS7QnzsJweZDIS5pWQf6fY/4uEn/hO5ux3nB8IYrt9AODwAQPXKb3JwYJTDLx8mNZqKgEBY0nPvyZdI65nEXKny220PIA0P876cgxTrx3lT2oynq4iSM6fpLyiiLduKrMqACrpU9Mb16E2rUUlBkEexyN2EI22E5Mlpf7eASqoxQl6mkbz8LFKzyrGlrcBsLUWV0lCCIlF/DP+EB50sYkI/1bqIDCqICIg6HaJJj86oQzSqiPoo4CEaGyMcHMTl6mNovJcxfxRfzDzDzlbAokvFZipENZQQpBhFsKEqE8ixHpRoB6o8DAhIooURfSanMraz2tbLB8V97NLVI6gQlXRIkyLDTRlI4yIeh4O3tm1jMjsLBIEJ0wQ9OR1syw+ywzhItmsV1t8GEU+OMFSaxmNXf5CD/hLSzS4eWPEcK3MryfWsofb53xG2mGhcp1JjbcAsmvmztX/G3RV34Xm6D6nNM9U6ZxQp+XAVjhwrnSeO8OYvf0I0HCaclc/a629h79VXL1rbW3LhUrxKOTnaNBqNNDQ0LHlx7+zsRJKkJT0kJF4E2dDQkPA1SDYtcjgcS85wZSlkROZD3BjqueeeIzU1lW9961vA1N9x+vRpHnjggQt63hdffBG/3091dTXDw8N8/etfZ3BwkIaGBp5//nk++tGPEolEpj1mx44dXH/99fzLv/zLvF7rihb3C7WQ7evro62tjYqKCioqKuZdnDQxMUFzc/O8DBsmJyf56U9/mjCpiYaC/PqrX0JBIO+GOygIl5BzJoA/y0LRXaV4f96GeWMWljuK+Mn3/oGfZOwjRbDxy/c8ToYlg66JAB/80ZuIipNdBcdJk27jA7/6NlLMy/gnvdjWXoXHcwKHYyNllf+P77z0E9RWFREdqipQOTnMjn0HMNoUhm/eyc88FXwi5fdss7RzRlrJSFcFRWfq6S0poy3dgKIqCKiIhgp0ps2I+mJUxYUl1kIo2khU9if+Vp0gU5gqU1ZVRH7FdlIytyH705CGg0QHfbgjflyCH48QJGCMEdCF8ckhIkKMGDKSIp31OIqImHVGzIIRk6LHIhlIUcw4VAspqhmL3kROlg1BP4HP20zfcB3dk5N4Y6b4xgEgkKLPwGquJCRWEBPzUBQ/itSBHG1HlQYBkaCYQqeljLasldxjOMrHhJfI0buJRXUoUZXRpjT83WbCJhMnt25nuDAfVRRxGV105rSxvcDPDuMQ2RNrsTzjRqwdp2NVLj/c8TFqvZlUpXVyX9XLlOfeDHUyzYfeIFZRwJsl/fRZ+qkwVvCVXV+hSimh//+aSJVEggr4quyseLACKRbixNNP0PzGayhmG0LFKm685z6qqqrm9Xm+EOLRZjy17PP5ACguLl7UlruLpaOjA0VRFtSAajFIHhYETCvOS279ulymRTNZDhdNycS98H/9619TWVnJ3//93y/K67jdbkpLS/nWt76FxWJZUHFf2rmciyA5Wp/r3no0GqWhoQGv18vWrVvfYfM5V3Q6XeKCYi5Eo1GefvppbDYbd911FwCvfv87+F0uKu99H6tzNyA8O0jArKfowUp8P23BUGrHekcxj3/vn/l52gGMgoGf3PNTMiwZtI76+dCPDmPVjbE1v4bS2I3c9sOvE8sSGPusj5TS7Xg8R8nP/wCm9Ef4p5/9N6nOVBQgqui459SrpHeNoV9v5d9W/zHXOF/mv7L+h0nVwSsjt1D4Rj36Qg+vbqpGUSRQFfTGNegtW0FIRx9rRwk8Tig2Snwiu0UXozzfQHrlWtbs+AixIT3RDg/et1x0iD2MmDxMGPy4BC+yPooYCWNGRR+VUWNRLDoBi6qCIqPKf7gJooio0yG8fRMNRgSjCfQGFJ2eoElkQlbxSTKqOCUmepeODMFORjSbjJT72JaWRm66CUnqpHf4GC2jA3hiE/j9k8AJTKKVVPMKorpqIimbUBQfcqwZW6SJ9YE61gVamDCk8Ufpf0O5fYxPi79ja0orhVtcyBtFnK1W9h5/E1kVObVlK0JZKekDO3GOufif3BS2502w409GyR1cT8Xjw/y/x/6ZY7vX8Kj1/fzbyU+zp+A415WcYeufPcTwK3UY3tAzsWUvBzNq+dgbH+Pm7JvZsX0Hu/XrEQ9Nkt/tp+P/1WK/q4SrH/k41buv5Y0ffx9382leHB2kbPe13HjzLecsCr1YdDpdIj0PUxevDQ0NSJJES0sL0Wh0mgAtlZGf8fPFUicekwmCgMlkoqCggIKCgneY6XR3dyOK4rQiyMsxhCU+UXO5EF9vIBBY1O9JWloaK1eupKOjg5tvvploNIrb7Z6Wlh8dHb2gbbUrLnK/0N51l8tFbW0tDoeDdevWXdRgAo/Hw8mTJ7nxxhvndP+XXnqJ+vp6PvKRj5Cdnc2bT/6SmuefYtU9D7HjmjuY/J9mdAJkf2ItwSc7EHQiqR9bxe+f+F/+S3yWsDHCT279KZWZlTQNe/nQj4+SZhxmXVYr19tvY90//yXRKgPuT4SwZq7G56+jsuLL9IRK+d0zv8MatU5FvOEId770PCYxyvDd1/PEeA5/nv4MK/UDHAntwv7SEGFrGicrconIIUBFNFZjsOwCwYYuUkMkfBJZjQAqOkFlZYGONVffQnrxXbhOj0NviFHVTY95giG9C0/IjS7ox46MMRZB8vuIBXyJYyMaDJhtdowWMzqdHkWRURQZVZ1qg1NkCUWZcsZDEFAVFVVWUGQZKRpFlv7gemewWFFNZlLzClAsNgIKuCISiiCgF3TkqKnkSqnkk06qIYqstNI2dJJubzSRxjeKFuyWKiLiamJiAYoyhBxpQom2AVGCOgeNtmqcGTn8sf5l7tMdRI+CJIt4O82MNaehxODUlm30lJeh6t6O5PNauTrfzWa9k7zm9eie6EDxxvjdLdfxc9ttRGWZOyteYUu+l1Ld7TQ/+wreWIS2zWZO2erQo+dPVv4JD1U/iOuJbuj3o6owmmak8qMrMZkFal56nlPPP4WiNyAXr+C6e+5j9erVl0TMvF4vdXV17N27d1rLXTziXGw3t7nS1taGKIqXJLtxMcTTxldfffU5937PZqZzIR0PF0NLSwsGg2HB520sFj6fj5qaGr797W9z77338pnPfGZRXsfv91NSUsLXvvY1PvzhD5Odnc3jjz+eSPu3trayatUqraAu3ruuKFPFWXO5UlRVla6uLrq6uli5ciUlJSUXfbLz+/0cPXqUm2+++bz37ezs5Ne//jW33HILW7ZsoebNgxz+4X9Rufd6bvnop+j8Zg32kIT1kWo4MUpsMED6J9by1qHf84+jP2TC5uS7132PzQWb6RwP8Ec/PEyGsZ/VmS1cbbmDTd/8EpG1RiY/GsDiKCESGWRV9b9zqNtDzas1iOjQKTqqJ3rZ9PoxDMUCP7nxcxQP7uejGa8yomQyVF+CrX2ExrUbGBQ8U5YxhkIM5usQxFTEyEki4dMob7eWOYxRtmyvpvKGTyJ3mQieGWcwMkaXZZweeQTZ78QaDWEMB4h6ptp+bOkZOLJyEESRUNCD3z1JzB+GpE+nzqSgt8TQm2UEnYqoUxB0KoIAqiKgyAKqLKBIIlJYjxTSo8SS3ksBBJ2ITqdHisZAVRFEEUdeAabMHMJGM2OBCDFBwCDoyJfTKZIzKLNlEAvW0zN+hnaPB1mdek6rLg2bdT0+cdVUG160CTlci6pMIgtmekwF1GZv5gOm/XxEfAmzEEFWRHy9ZkZq05ElgVNbt9JbXoYqioxYRhgt6ObGrBHWiDI5R6oQn23DZzLy81sf4PfSJlKNHh5e9TQVOWuwd+fQ+PprSGUFHCzuo8/WT5Wxiq/v/TpFvizGf9mFTVKZkBV0V+dTel0enpEh9v/4+4x3tRNNyyJv+x5uuf2ORR9n6fF4qK+vZ+/eve/43bla7uIidKkKxlpbW9Hr9UtehOLz0a+99tp5bW8suJlOXD7Oc85samrCarVSVlY29+e+jLjdbhobG/n7v/97PvGJT/CRj3xkQZ73L//yL7n77rspLS1laGiIr371q9TU1NDU1ER2djaf/vSneeGFF/jJT36Cw+Hgs5/9LDDVcz9frghxT7aQnU81fDgcpq6ujnA4zKZNmxbsBBcKhThw4AC33nrrOdcRDAb54Q9/SG5uLvfddx+1Z85Q84sfYE9N46Gv/Qvdv+ggtctLdG8+aSYdwX0DpH5gJT0TDXzjxLdpyunl65u+zp2r72TIHeZ9PziEXh3hqvy32KC7h53//v8R22Rh4sNBVF0aen2QtWu+z9Mnz9B/rH9qZKqi44bmIxTU9aLsyOXr+X/Enwq/5DpzLScDW7D8fgRXXiXH80yochRBtGAwX4tgqEQXrScSPoKiTkXH2bYYO2++nvz1jxA65sTTMUabeYRW/SAh5xDmkA/R60KVYtizssksLkWRY3gnB3EPTUzV4RllLFlhzGkR9GlmlLQCArZsgjo7YdWETzXhFcxE0E21s6kgCyI6VcEuB0lRI9iI4SBEtuIjTfFgkryIgUm8wQjekIGA30TIaSXme1swhKmCPOXtbI8jtwBrYTE+0chYIIQCZKkOyqUcKoxZmHQd1PYcossXmHo4IqmmYhTDRiK6chR5ADlSgxLrQkXHkCmX41k7ucdynE8Jz+PQBYhJIr4eM6P16ciywPEdOxkoKUYVoM/WR6h4gFvS+lkRSyXjlUyE17rpK83gu1f/CXW+bNZnNXJ3xX7KMh9g7OVGRro6mdhezBuppwjrwzxQ9ACf3vppwi+PEjk9OdUbb9RR+tEVpGSaaD7wOkef/AWSqhIrKGfv3fexcePGRYviPR4PDQ0NcyoylSQp0Xc8s+VusQvGmpubMZlMVFRULMrzLxTnmo8+3+dJPtbvMNOxWdA5OxDHGhBdXYjuXlRnDwTHEaM+dLEgoKKIBmTRSNScTdSah5y1Gn3VtejLdoPBQn19PampqZSUlCzYMVhMJicn6ejo4C//8i/58pe/nGhNu1gefvhhDh48yOTkJNnZ2ezdu5d//Md/TFxMxk1sHn/88WkmNu/KtPyF9q6Pj49TX19PVlYWa9asWdDIIBKJsH//fm655ZazfvFUVeXpp5+mr6+PBx98kI6ODiZPH2WssZaH/+HfiAwY4Hc9BHKtFN9RiuenLVivKcBfGuKffvU1Dle08keFf8QXr/4ik/4oD//wEMHwBDcWH6Bc/z6u/eZfIm1JYeJDXkR9BpLsYdOmx/jx66/ib/QjCQqqoueeoy+SNuxk7J7r+KmniC9n/IxMvLR2rsFyZoym9VvpY6q6XTStwWi+FkUeQQm+hqRMpc+zrDF233ELuSv/iOChESYGx2iwD9ER6EDvHsfkc6FEwthz8zGkpmO3GhhubyYaiKK3SFiLQkSKcvCmljFkLKDDXEKXMRev/g/9pKI6NShmagycgqCooCqIqoqgqlPGtKIOVRRRBQFZ1E2LJgRVIT3mpTLYx/pgJ+uUYUqlIXT+UYYDMk5XCr4RG3J4KmoRRBFVUTCYLaSVVuBUdfh0JmRUMrBTGcthpTWdUOAkJ/vrcUWnimAsOgc262Z84lpUNYwcOY0caUBFYdyYw5HMq7jeWs/nxd+QpvMjySKuTivj9alEdEaO7N7NeE42qqDSltqGrWScW+y9lDnLSPllEKHNxYGrN/JowcP4ogJ3VbzM5gIPckcVgZpmIiYjNRtk6qyNZOoy+fKOL7PVspGxn7RjCcTwKhBZn07lvaUE3U4OPvYDBhpqidnTSd+0g9vuvueCa03OxXzEfSbx6WvxFL6iKNMMXpJb7i6WpqYmLBYL5eXlC/J8i8VijNBVVZWwZ5xw+wF0fYexjtfgCPaie/vi3Sem4lQcOHHgw0YEIxHMiDodRlFFr0ZJkV2kqh4KGcFKmChGBjN20ZV1I3kbb1o24j42NkZvby+f/OQn+c53vsPtt99+uZc0b5a1uCuKwsjICLIsk52dPacvuKIotLW10d/fz5o1aygsLFzwdUmSxGuvvcaNN9541v2sxsZGnnvuOXbv3j1VXCSqHP/p97n6kY+zctsNjP5HHegFCv9sPZ4fNaPPsWC8N49vf/tLPFddy+aUTXzv7v8lKik88qMj9ExM8MCK36LKf8zD3/kS8kozox93YrTmEov5EPgCb40OEWgOIAkqgixw//7nSPEHOPXwh6gbGOdvMn6FT7bhfMOBHEvl4Mp8olEfgmjGYLkFUZ8LwX1EYh0IqJj1Mntv3EH5nj8juG+Yib5RTtl76XU2Y/GMI3jdmKw2KrbtRNCpdJ46QsQbwZQaQV5pxl26mTbbSo4bK/DrrAiqilUJoyAihiOkel1kOUfJHe3DHuhHVN3I+AibJGJ6BUmnENOryOLbxUUqCAjoFDDERHSKEUnvIGLKJpBSjDu1Ao8jn4DNTsww1RKmUySKIyNc7TrNzeE68mJD9HtDDI3b8Q3aUWUBQZzayxf1BrJWrEJyZDDgDaKgUqhkslLOp9gao3XgNZqco6iATjCQZllNUL8FRTAjRc4gR2pAjTJpyOLNrF3cZjvDn4vPYBVCKLLIWJMdd4sNjyOVI7t24U11IIkyDZn1rCqZ4FrzCIVN6zH8spOQJPDY7ffzvLKdDLOTh6ufojhjA5ZmK21HDhNcW8y+vGYmTZNcnXY1f7vnb9GdDOHfP4wZGBIE8h+pIq3ERtdbxzj08/8jGokQyStm++33sGPHjgWNjt1uN01NTRc9FSzechcX+7jBS/KUu4upl2lsbMRmsy359PGCefWrKqKzE13Xq+g7X0U3dApBlQnqHHSrhfQrOQyTi9dWhmCyY7fbycrKSsyRdzgc7zjvxmIx3C4nod7T6NteoGD0deyql3r9Bnw7v8ia7dctyU6JZIaHhxkeHubhhx/mySefnHU7aamzLMU92UK2paUFVVXn1D8ZDAapra1FURQ2bdqEzWZbtPW9/PLLXHfddbP2x4dCIR599FFSUlKoqqpi7apqfvfPf0d6fiH3/NVXaP/3Wuy+KLaPrEI9Pkas30faJ9fwxPe+wf8VvInFaOGpB57GrDfzl785w8tNo3x83c/p832cz/7kH1CzYORPJzCnlRKLTZCf920e2/ca+hE9kqCik+D+l5/FQoTfPvAX6EZP8jn7U3SFS5FfCDNRsJGjGVEERUJnKMJguR1FHkQOvIpKFBXYsiaLLY98jeixEK76IU6l9NLpqsPiHIWgn+zySso2bmGovYbBxnZEg4Ky1kh/5XZOpm6jw5iLTpVJk/wEMZLqmqC0r4PCkTZ0UiceWwiXPYrLIeG1RVGTzh9mwYhNZ8MimrAIRkyCERWQVRlFVYgi4ZeD+OUA4US9/hSGmIgjoMceNCOSjc9ezWTmZiazKpH0BgRVJT8yxm2Th7k1fAaTb5Aej4GxgVRiPuNUNkBV0ZtMZKxYjc9kZywYwoSBKimXNcZcIr5jHB9sJihHAYEMSyURww4kMQMpUoscPoWqhhg35nA4axcPWI/yKfE5TEIUOSoyWJNOqMfEUH4+J3ZsJ2Kx4DX4aM9v5LrcYbYKKtmvFiO81EVXaQ7/vfvjtAQz2ZJTw+0Vb1LqeC99vz2O2zVJ1/Y0jtnOYNAZ+Mzaz3B30Z1M/KwDw0SYsAKeshRWvr+SWDjA4cd/Sufxw0g2B7a1W7j9vvsXbJzoYo38TG65czqd+P1+UlJSEin8+e4hNzQ0YLfbKS0tXdB1LjQXawokTnagb3kGfctz6NzdSIKRXl0ZzVIRfbpyLIXrKCouprCwkNScXPpllY5AmHavn6FgmNFwFI8sI+j06PV6zAY9OWYTWUYDFWYDa6wmVluNmEURFImu33yN6sFfE1MEXkr9IBvv/PhZZ3MsBeKjf++44w4OHjx4UXNCLhfLTtxnpuE7OzsJh8PnneI0PDxMY2MjBQUFVFdXL/qV48svv8zevXtnvYD47W9/S2trK1dffTXbtm3j2K9/TuP+V3j/P/8n7lNhLEdHCG7KJLciFd/TXTjeV8Vbdb/jP11P0582zE9veozq7Gq+f7CTb73ezYfXPEGH/x7+5rc/Qq94GfrsCNbcakKhPtat/T9+/PIBgh1BYoKKQVK576XfYjFE+e4dX2SVez+fTvkdLa5q1Fd99K6/hgYGEQCdeSc64ybU0D5isXZAJdMqc9PHPkWKugXf6300iQOcDp9BP9KHGPRRsGot5Zu30XFqP6NtfYiZCgN7NlCftZs6YwlmOUKW7MOpWijpa2dFVwPWQD2jGX5GMiM4HRFUAWyilUpzERWxNEomRbIHfKT1u0jt92B2+mEurYaCgGwx4stJwVloZ7LATocpgqvYSoc8ypjgIipO7bPbA3ocwVRkQyXjWTsYz96MbDBiUGJs9Tby8ZFnKZR66XDpGenJIBYw8LYBH/bcfKxlVQwGYoRkiSIlkzVqIVnCIEd73mQiMrU3n2YqQTLuJKbLm4rkwydR1SgjpnyOZm/nw+Y3+KjuBURVQQ6K9JzIRh4XaVy9hqZ1a1B0OgasA/hLerg9rZdV7mLsT0Sgxckre7fwf/kPElEUHlzxW9bkWcgcWUfTK68SKyvgUEkfvZY+VptX8w/X/APp3WZcz/VhA4YVlfT3lJG7Np2Bxjre+PH3CXrdRLIL2XjLnezes+eit61cLhctLS3s2rXrop7nfESj0WmuefE95LjYn2/c53LZG/Z6vdTW1s7LS0PwDaNvfQ5D8zPoxhqIihZahJU0yKWMp6yltGoVJcWljAppnPJGqQtHaBMURpISIbaoij2i4pBVUlQBg05F1KvEdBI+Hfj1BkbQIQMWUeDaVCt3ZqSQ1t7EyjwHOW98EcN4I48L97Hqjk+xatWqhT84C0Bvby9er5drrrmG5uZmVqxYcbmXNG+WlbjHe9eTi+bON4FNlmWam5sZHR1l3bp1FzRd50J47bXX2Llz5zTfZ1VVOXnyJK+99hpbt27l5ptvZrK/l1/93V9x1QN/xOrddzD5n3VELTpKPrUGz/82YVyZhnulj3977pscqWzlsys/y4e3fJgDbRN88hdnuLP8FUbC1fx1bQP2hhOMfNGLqbSKUKiL1av/m5dODdD7Vi9RQcEowb0vP4dVH+Vfbvki14d+zwctr9M6VI18OEz9tr0MhPtQBR1G6+0IYhqy/1kU1Y+KyraNBWx55B8JvjDESO8QBy11BPoaMPjcZJWWs/6m22g+9HtG2vqIFRrp2r2bQ2m7cIsWKsODjBqyyRzqY0PTcSzBWvpy/fTnhYkYZDL1aWzRV7BmWMfKIwNkNQ4hnEXAFaMJyWojZjQT0ZuQDEZkUQRFRVAUDIqEIRbBEAlhiITQRSMIyjvtbRVRZLIig+5NObRX2WgwjNEdG0IRVMwRHWn+TEK2TQwW3kzIloeoyqz2d/H5oScoinTSOGlmrCsDJTaVvhb1erKq1+IxpzIRDOLAwtpYMZWGCGf69tMXmPKud5gKUIy7ielykcKnpyJ5ZPrNhdTmbuJLhqe4w3AMWRIIO/X0HstBjggc2bWbocICVEGlKb2JgtJhbrGNUNS4Dv3POgiIBh698/28Hl5LRWo3D618npKMexh/sZnxgX7Gd5awP+U4kk7i4ys+zvtX/xHux3sQ+vxIKkzkWFjx4SoEJE48/QSN+15GttgwrlzPrfc/QFFR0QV/H5xOJ62trYsu7smoqkowGJw2kCW55S4jI+MdmbW6ujoyMjIu6m+9FMy5hkGOou94BUPdz9H1HUYR9HTpqjgtVTKcsoHSilWIxnxOhIycVmVaHQJBk4ioqOR7ZcrDKuWSQgk6CgWRNJ0RURCJhmTC/hi+iQiesRCqCrZ0A9lVJszlMi0RP02ikTOmFLpUHXmqxJ/mOHi4IB3Lbz+O2n+cHyoPsvX2Dy5J17qurq6EuA8PDy+KffNisyzE/Vy96319fYyNjbFt27Z3PM7n81FbW4vBYGDDhg2XtHd2//79bN68OWFGEI1Gqamp4dixY1itVj72sY8hAE9948tEQwHe9w//Rvu3G0j1RbF/Yg3S/iHk0SCWD5fzvW/9Fb9Z18B6+3q+f/f3GfVGuOe7b1KW0kBByjC3j5Sz4slHcf65DmFDHqFQJyuqvsHpHgtn9p0hKioYJJH7X3kOixDh/938RW6MvsAHza/R2rkCuU7Hic2bmQgNIOisGK33o8gTSMFXEFEw6WVu/dD7yUq/Ee/vujhj6KZh/Cim8SHMNhtXvff9jHbX03LgMOFcE/U33Myb9m0YlBil0XH6hAw21h+nsusIQ9kjtBcHCZkkikz5XBMqYtuhUQqPdiOoaiLtrYoiodxC+nNKabblU2/IoNuYzqQ5lajOgCBAqsVAmsWASS+iFwV04tRnIiIphGMywZiMJyQRjcmkxELkBp3kBiZZHxplrW+IfM8IVq8TMUn4IxY9PdsKqd+WxXHbKL3yCKiQGrChE9YwWHg3fkc5ekVir/s0Xxj9FUH/BK0DGfhH/5ClySirhPxS+lxeTIKRdbFiVhmNNPS/SqdvBIA0cwkx424kIR0pcgo5fBoFgaaUlTiz8/mG7qesN3QhSQLuTitjtal4Uxy8uXcPPoedkD5Ec1491xUMsykqkftCAbqD/ZzeWMF3Vn+MiYiBOyteZluBk7zAdTQ9/zJyVgZHqp20WdqpMFbwjau/QYErk4nHO7EpUz71ttuLKNiezWhnO/v+77v4xkeJZOSx6oZbuea66y7IwtbpdNLW1nZB8xYWinjPd1zovV4vFotlWs93Y2MjWVlZi1KLs5CcLxMieAcw1P0CQ/3jiMEJRkwVHI9U0q5fTW7haiLkc1S2UZMqMpilR1BVCoNhKoNeSvwTpDtHkIKBRFtxMhaLhfT0dHJyciguLqa4sATXYIS+ehfdNU5kSWH13lyq9qTi8bp5a9LDL8NQZ7CyU5T5chpsPvApfMEQ/xN9kIff/4FLFnTNlfb2dlwuFzfddBM+n++ihsVcLpa8uM/sXZ9ZDT80NER/fz87d+5M/ExVVQYGBmhpaaGsrIzKyspL7o504MAB1q1bR2ZmJk6nk9raWrxeL01NTXz4wx+moKCAxjdeY/+Pvsf9f/v3MJyG8Y1BQuszyVmVhu/JThzvX8ErLz/Ko9YDeG0Bnn/P81j1KTzyo2P0Tgzx3hXPYHB9gLv++28JPpJB8DqIRscoKPggruhNvPT0S0R1MkbJwJ0HXyDV7+Pf7vg8V0X28cfmF+loKyfabOPwpnV4gkOI+lQM1vegROuRwm8hoJKXJnDrl/4N9RRMnO5nn/kU/p4z6MJB1t94G+mF+Rx98jECgkjTLXs4mH0NFjlEeXSMDjWbbXWHKRh8k6bySQaygxgxcH10Bbcd9lNwvGvqvVRVVEHAW17NqYK1vKrPp9FeiGowsjI3hTX5dsoyrZRkWChNt5ArRrH7J8E1iuAZR42GQIpAbMo8B71p6mYwgy0dvymNM8MeOiMiw2EFwZHDWFClfcxPz4SfAt8EWyfaudbZRpmzH0vAm3gf3dlWGq8uYn9JlCbzMJIg4wikoOo3MlB8D1FzASmSnz8efJp7ffupGzcw2JmFKk193qwZmVhXrKXXF0Kn6lgjFbLWYKah71W6/WMAZJgrCBn2oIhmYqHDKNEmYqKFo6lbyE2P8A/iT8jRu5CiIgMnMwj3G+moqKRmyyZkvZ5+Wz++vDYeyB2mcrAK60/GiLqiPHbH3Twr7CHbMsYjq39DccY1hA5OMtjagntHGa853iKsD/PB8g/ysU0fw/t0H3KzB0GAEbuRyo+vxGiC079/lpoXnkU2mBDKV3Hze94771axpSDuM4m33MXFPhQKodPpSEtLo7S0FLvdvmRd1eKtWsnnPVQFXfd+jLWPoevahySaqRNWc1xei5K+FqNYyAkyOFVgZDjDiF5WKPOMUzw2QOnkCKk6MWENnJqaisViwWLRo9crCIIeRTEQiUQJBAJMTk4yOjqKy+VCr9ezatUqduzYgc1sp/nQKPX7hrFnmbj+wytwZJs5ePAgQ4Vl/Js7hkWV+YfRw9zV8nccMN/KaeNOPvjBD85rfsdi09LSwtjYGPfccw/RaHTJFwDOxpIV9+Te9XNZyI6OjtLZ2Zko1InFYjQ2NuJyudiwYQOZmZmXeukAvPnmm6xcuRKfz0dXVxfl5eW88MILlJWVTX1gQiF+9ld/Rsm6jVz/0T9j4J9OIxtESr+4Ec//NKAvTGG4eJD/PvgoxyrapvrZV93Jv7/azg8Pd/OnG39Eo/Oj/NUP/x62pTPy8ACizojdvoHMnK/xgx//CBkFo2Ti5tP7yO4f4yf3f5aC4An+3PIsne2lRFpSObhhFf7gCDpDJnrLvcjBA8hSBwDrVmaw+1PfIvCbXrrG+zgUfAP9cDe29Ayu+9CfUPvak/TXd9J+7Xr2Vd+NrMKGQBcNxlK2nzpI4eAB6qpcDGeFyCOTW9oc3PBiN9bg297wOh0ja7by+8y1vGitIGa1sb00jb2VmWwrTWOlKYyh9S3oPYXo6kQI9oA6SMwcJGISiRhFZJ2ArBOQdEJiDxxAVEEvKehlFb2kYoooGMM6xGgOirEINaUUNa2caP5aOtKrqQ1Aw7Cft3pdeMac7Bht4p6RWirGuzC83eYWtuipvaGEN9cbOUU3EjJpgSx8qTcwUnAboiqyzdvIV4d+wJjbR0dnLtHAVLeE2ZFK6ppN9HrDKKrKaqmQ9Xoz9X2v0xsYAwQybdUE9HuQlTBS6CCq1I9fl8qBrD3clXKGz+ifQq8qRL06uo7koPgFjuzexWBREbKo0JBZx5qSYa43+ig4sALhuXbaS/P4j6v+mO5gKjcUH+Ka4iYK1HtofeZVIjYzb60L0WRpodhQzDf2foPyaCFjj3VgiylMygq6a/IpuTYP19AA+//ve0z2dRNNz6F0z/XceMvcLWxnFaMlRjgcpqamBr1eTygUSrTcxVP4s81Uv1yMj4/T3d3Njh07QApjaHoKw6kfoHN24DQV82ZkFS36dditVbTEcjhZnEJXrgUBlRLnKCtG+9kqylQW55OTEyUlxQsMEY70Eo2OEI2OIkkemDGtUadLxWwuwmwux27fDOpqurt9nDlzhmAwyLZt29i9eze+iSgHHuskGpK45ZOrqG09wbZt23DqjXyodQgVlZe7/pWU/sP8a/QD5BeWUFlZOW188OUU1MbGRoaGhvjIRz6C2+1eshd552JJivt8etcnJiZoamrimmuuwe12U1tbi81mY/369Ys2AWsuHD58GJja89+4cSP19fUcOXKET3ziE6SlpXH86V9x+vfP8Mi//Bejv5vE0eVB/9AKjIN+Qm+NYflwKd//j7/mqS0trHOs49G7H+Vkr5tHfvQW71nxPD2+NfzVkZOkTXYz9MVhjKlTacQ1q3/Jt//v+8RCEmbFxI7Ok1Sc6eC5ex7BGxvnG7af0NNdTKghnTc3rcfj70dnyEZvuRsp8DKqPIAK7LlmA2tv+wLeX7ZTq3ZS1/8KBq+T6quvp3zzZvb933cYszs4eOt7aLWUcZ3zBA32NRS1NrKh8UXqKocZzAlSasjnzuM6rnm5Z+oLoiiEC0t4qWovP7etBnsKt6zO4fa1uWzPEjDVvIbY9jqC+wRR6ygehwGPzYTHZiRsBdUw/eOqyDoUyYgim1BVkbi6i6KEaIig00+vlkcR0EcErGEZRyCCPRDD5lcwhfJQTWtQcjbhLN3NYWMxh3tdHO2cxDbcxz39J7hmuI6Ut6P6kEXPW7eV8crqGG3qIIaYDpOymqGiPyJiLiY3Osk/d32HtFAPNR3ZhJxTW0ImWwrp67fS4wuDAuukYlbrdJzoeY3R8CQiOjId2/CwDUUZQA4eQlGcDJmKOJO7ha8ZH+daw2lkWcDVbWXsdBrO1DTevHovYasVt9FNd0EDd+b2s8Gbj+PnUZR2N0/dci2/sN+BRe/jQ2ueoDRzM7wFPTWn8W4t57X0kwQMAR4sfpBPb/00oZdHCZ+awCDAkFlP2cdWYE0z0vD6S5x46glkQUQuruT6+9/LqlWrzit6y0HcAU6fPk1BQQG5ublnbbmLC9DFtNxdLGNjYwx3NrCdWgxnfooQmqTbuJr90XU4jauQpEKO5mZRW55GxKAn1zPJOvcYtzh0rMz3Y7X1Egk34Q80oqpTF69GYwEWSzlGYz5GYy4GfTqiaEEUTahqDFkJIcWcRCKDBIOtBIItgII9ZQuZWQ/Q3ZXBkSPHyMnJ4f7770dQDLz6/VZiEZnUrZPsuWYXFouFoUiM9zQPcpvUy78f+ABHiz/FoclM7r333kTnwzvMdC7x7IG6ujr6+vr4whe+wNDQ0JK5qJsPS07c49F63Lj/fAfV5XJx5swZysrK6OzspKqqirKyssv6ZjidTt566y3+/+z9d3gc5dn2j39mZvuutFr13mUVS7Zlyb3bFBsDNgYDoZeEnlASQhIghTzpJJDQIbTQTC+2ce+9yLK6ZPXeV9v7zPz+MDjwJk+eQEgevu/vPY/Dh49jd2d3dM/Mfd7XeV/XeUVHR1NZWUkoFOKpp56ivLycZcuW4XVM8Oq9d1C67FymzF+D+9kGfAlGsi/NZ+LpesxL0tnX8BbPSrsYihrjg1UfYNHEcsGT+9EprcxMPkZhzyxmvf0k498HsSAZv7+bKWWv8ML7u3ENuBDRkuvoYdbmQ7SsXsHmsIXHLY8zPJKI+7CVIxUzGXN3Imri0BkvIOzdjKoMASpnX3QWWSXfwPF2K3ukagY79qGRwyy94VbGepup3ryN6sVz2TvpXNIDQ2Qoblp80Zy95y2GYlupz3UTr7NxVW0sMz9sRhBFBEVhsHg6T6TOoyoqi3l5saytSGNJqoT2wDuILe8hCw2Mx0sMx5hxWUXQqKiKiN8Xj9+dRsSeScSVRMRnI+y3EQhZ8eq0BDUiQa2ALJ2mdhGQVBVdWMEgy5hULybJgdZk/+u/6EH01n505rHTXjcqGDwi8U4fNleIKIcJpOmEk2fTkbGI59qc1DtEQn39XNR9iGUDJzF9QvSDWVHsXpnJ9uge3IKfKF8y44lrcNpmY4l4ua/3JcodhznemYh39HSkqzOZsJVV0ukOoFElpoQzycHFvq69eCJedKIRi3k+HrEIOVSD7D+MIqiciJqCNl7Pb6XnSJLsyCGB7iMJhAY01JaW0VRShCoKNFubsaV1ckGMneQjhRjf6WIwNppHln6Lem8S81MPcVZ2NRm6tbS8sxWfJFI9VabO1ECSJomH5j5EsaaA4RdbMflOm9+EK+LIPS8D99goe1565nTP+OhYkmbO55zzVv5Dh8exsTHa29u/9uReVVVFenr63+wBy7L8OdvWf7Xk7l+B4Owhsuf3RLWvB6BWLGNfpIywppAeIYFDBYn0JFgxhINMsQ+xKsrDtORBVOpxu4+hKAG02ngslmlEWaZiNpdhMhUgSV+sNDgSceNw7mNs9ANc7qOYTCVER9/Gxg11GI1GLr/8ciI+gQ2PNiBZA6z6duWZBdEBl4/rTw1SW3crhuhMft9VzKpVq8jPz/9c74FP3fOAzxkX/btVlOrqatrb2/nFL35Ba2vr/yP3fxWKohAKhb6Qhez4+DjHjx/HYDAwderUz3XT+U/jsz71BoOBrKwsMjMz2bJlC42Njdxyyy0YjUZ2v/QsrYf3c/XDT9D9dDtRrhCxd00hsLEbZSKAZ7HKU2/+nm1lTWey43+5qYXXj3ZyZ/nTNA7fxh1P3EfkinQmFo0TiTjIzvoutZ0p1OyvISAqxAb9rPhgE64ZhTwct5CXLL/G7zLh2BlD/Yyz6HY3IGisaE0XEfZ8DMoIAiorrl5LSvI5TLzXylbpIK72Ixijorjgzvs48M7TnOoaY/vqS2i35HLhyE52x81lcvUhMrs2c2jqOCGDyqXuYs59tgZ9BARFYWD6PB5OmEdHVDKV8TI/WjOb3N6DcOh55PBBhpM0DMSbCVlUFEXC6cjFP1xMeLAQvz2HUYuB0RiJYLwOTbwBS6yOKKtIqmAnKTiKKezGEHKjD3tQwiHGJuyEFQVNTDxOrYVhwciQYqAvYGQgFIsYMmHzKGS6ZVLcbmLpw2jtwxDfhinhFDrz6ax2nVci2e4h3h7C4MwiELMQe+F5vB9JYn3TGFJ7G9e3b6d8sAlJjhDWCBxZkcWHpSG6GcEYNOO3nMNo0nnoVYEb+99j1ehGjvTE4x4+naBjtNqImlxO54QLA3oqI7nYAm3s66sirIawaOPAsJiwGEfYvxcl1IxPimZnwjxWmU9wu+Z9RFUhMKql+1ACAXTsXbSQiVgbfo2fxpSTLE/uo8Sjw/a6AX2Lk/XL5vBCzGr0kpdrS9aRlTAVTY2BtiMH8U7LYXt8NU6tiwtTL+SumXcR2mfHu28IvQADkkj69flEJ5loPbiX/W+8TDgSIZySzdwLVlNeXv53n9uxsTE6OjpOy8hfYxw7doysrKz/sb4/FAp9zjXvi5bcfRkI9g70Rx9H0/guQdHEYXUqR5UyZDWbuvgkjhak4NEbSHFPcJ7WyfkJTRDZj8/XjCBosFjKibHOxWqdh06bh3ssiNcRwucKE/RGkMMKckRB0ohodCImqw5LrA5bigmt/h8vXNzuE3T3/Aa/v4P4+O+wcYOT9PR0Vq1aReuxEQ6/3cPZtxSQkhdz5ph7O4eZfuJRvjm8kafM9xAXn8DKlSv/5rtVVT3Te2BiYuIrNy76ezh+/DgtLS089dRT1NTUfKXf/Z/C147cg8HgP20hOzY2Rm1tLaFQiKVLl/6vymTBYJDa2lr8fj/Tpk2jvb39zErz6aefZuHChcyZMwfH8CCv3fcd5qy9kqzMBchvt+EttpE2OxnnS82Y12Tx5qs/5/XSFgxGAx9c8gE1fW6ueP4Yayd9QJtzKj/avoMovZe+2zrQ6KxYLJOJinmAV195DZ8UxBw2cMGWDWiiNfxg5l08Kv6CpNAEIx9H01t5KTXeKhAN6MyXEvZtB3kAQVA475pvkBSzGPv6NjaxE3/nSWIzsjnrxtvY/ORD1Bvj2XL2ZRjkEAtdNeyQSlm+cx398c005riYqsnhplfGiO92IKgqzpxCfld4PrXmVK6Ykc7VU2OIbHiCDOcmPDGDdKVE47FBRNYxPlZGsGMG/sHJDFnMBLOM2HKiyc+3UiH0kzpejzTaiDDSCGOtiN5hBD5/68poUdRPJiFBRCKEyN/2fg9rzXgs6YyYUqg3ZbNPm0WnnIXsSaZoArKcg1hNbZiTGjGn1qI1uCEsEj8RJGXMT7Q9gUjc+XTmXcAbbjObagepbD3CdZ27iXWOogKnpsax4ZxYjkqdaGQtqnYhQ2mXoVElbu5/h1X2jRxoS8I7djqSj0pMRptXQrfDRbwaxWwlF6/9EFVjTaioxJuLcWsWoMgTRPy7UOQxBgzpnEwq53faF6jQNhOJCAzW2PC0GujIyaGqogJZI9Ie1Y45p5eVlj6SjhZgeaeHYWs0Dy++nsZgOvNSD3N29gmyTZfT/M42vJEIdeUS1eZaYqVYfjr7p0yLKmX4xTYMjiA+BbzFVvIvziHgdrLv1Rforj5GxGLFOnUmyy9c9Te5Lp/bI/4a4+jRo+Tk5JCQkPBPH/Npyd2nZP/pHu1nyedfSRYTx5rRHXkMTct6glI0e+RyqtQyQpFUqnJSqc5KQ0VgRmCMtTFN5Gp24vM1IIoGrNb52KznEHZNZaxbYWLQx8SgD9dogIii4hcgJKoIBhGtVkIvChhkEIMq4cAn26IixKaZySy1kTs9DnPM359nFSVEd89vGB19F7PpZjZv9nHeeeeRk53D+787SUKqjbO++dd+7n3BMP+19x1eq72XnWWPUNUxzs033/w/zv2fNS6amJjA7XZjNpvPjHdMTMy/7Mtw5MgR6urqePvtt79U05avA75W5K6qKqFQ6H/8nKIotLW10d3dTX5+Pi0tLf/Qx/3fjU+z4W02G6WlpWg0GmpqaoiKiqKtrY2GhgZuv/12dDodO59/iq6Tx7nm90/S+ft6dAGZtB9Nx/1yCwDtyS282PQeR7KaeWzeY8xIncVFTx8iHGxlcfpuEjqWsOTdxxm7H8SMOMJhO2Wl7/Gn5/+CL+TDHDEzt+EgGe19/O6KX3Oh4ylWiEfp22xjPHcte9V6BAS0lkuI+I+A3A2onHftZaTEL2P8/VNslLcQ7K4nvayceWu/wQe/u5/DxRXsLF/JbGctEV009mE/84+8zoEpQ3gtEa4byOeslxsQRJGI2cy6OZfzunESa6an8u0FmSQdXwcn/8B4spf29Chkg4rdnYOrdRHBzkpGY01ETY5l2vQEZsYE0LdvRujci9B9CCl4OpJ2C7GMR6JxurR4fBJBl4jsURH9KlJQQRNWEBXltA2tqiKLIrJGRNGKqBoR1SAhmkT0JhGTTsAaFSLBOoxZGAMgIunpsk1md1QpB7WTcfgnUTQqke1tIzqhHktaNUZbL0REEseCpIz5MDsKCKatZmf6ObzU4sbV2MwdzRspGW5FUFVGk4x8dFk2203tCLKIqp3PcOplaFUt3+57g8Xj2zl6KoWA83R+iC07F398BqNeLzlyIjPEOOp6ttLnG0YStNii5+Oi7BOp/hCyAAdjKsmzOXlI8xJGIUDYLdG+P4mIT2LfwgWMJCYS1ARpSKlhSUofM0MmbG8YEGpH2LBkFn+2XYRe4+faknUkRxUQ3RbPqYP78Jdmsz2pDrvOzoqkFXxv9vdQT3pwbu7DJAgMAElX5hGbHUVX9TH2vPwcQb+PUGIGFeedtrD9VKoeHR2lq6uLGTNm/Mefzy+CI0eOkJeXR3x8/Jf+js+W3Nntdtxu95mSu0+z0f8Z8hFHG9EdegRt6yZ82jh2RaZRo07FTSKHCzJoTknDEAmzQurnoqjtSN7tgIA1eh46dRHOnikMd4Tp63IzqMrY9eCyiIxJKmNyBGdI5r+b/KMNGnLjTJTYTJTodESPhhlocqIoUDAznqlnp2GM/ltrbVVV6en5LcMj6xgfu4beXjNXXHEFu96txtFg4OL7p2Ky/nVxcH9tNX/adgGdc3/LywcHueGGG7DZbF9ovMPh8Oea3wQCAaKjo8+Q/ZdpNHTw4EGqqqrYvXs3W7du/ULHfl3wtSJ3OB0B/yP4/X5qamqIRCJMnToVo9HI9u3b/1ci98/K8IWFhWRkZJxZddbX16OqKps3b2b27NksWLAA9/gYr3zvdmZf8g3SEucgbujGV55A8iQrrjfbMKxN5/lnfsQ7s9ooiSnh2fOf5dUjvfzXx83cO+Nx9vR8kx8/91OUy3OwL+4jEnGRn/czth7209PUg4JInrOP2ZsPcOjG79Az1sTPDH+h50Asbv15fGwdQowE0ZjOQ430IofqAFh20TnkTlrL+NvNbAxvItjbSPaMuVQsX84Hv/8Z2+ecw/GCeVzb/wE7khaTfeIY6b2b2DvdTqo+gTvf9pPe6gBZprV0Dg9krSA5PZGHzi9kSt9ulP0/w55spy0jClkLA2MzCZ5YjjuQjqbUyvyFGZQmBJHq30Gt/xDtSDUKImNSHMNePaP9RuR+ieiJAFH+EJ+u6yOiiE9vIKTRE9bqCUt6VFFCEU43jxGVCJISQpLDSHIYQyiIMRRAJ/81AzgsibgtRkIxenRWHYnxYdLjezCKThRE2mJK+NA6k5PSDGz2TIrHu4lLqCI68wj66CHEoETGkJuUIQG0y+kp+gZ/dtvYU93FZQ1bWN59BE0kjD1Ox4bLctkS1Ymigqqdz0jqN9ApEj/uepZJ9mNUN6cR9mlAEEiZWkm/qsUfilAWyaBA9rC3ax9+xYdFG4dqXEpEiCHs24kSbmdCG8+e5Hncr3+H5drDyLLAaEsU9joLvWnpHJ09C1mjodvcjZDdwfnWPvLqy9C+0spIlIU/LL2R2kAac1KOclbmIXTuZbj21+MLB2muMHLcfBKrZOWBmQ8wK34mo39pRTPsJ6yCI9NCwZV5REJ+Dr31Kqf270Y2WTAUl3POhatIS0s704jj607uhw8fpqCg4CutsgmHwzgcjjNk/1ny+TRZ7LPkI9g70B/8PdqWD/HqEtgRKqeWUhyaBPYU5dEbl0RcyMtKoYpzDO8iRPowGgrQqSuYaJ9Ba32EVl+QAYPKoBH6wmEUQCMK5MQZyDQLJIh+DAEnOt8EQsCDGnAjRxSCikBAY8KtszIs2eiUo3BGRFKjdVw9I53JPoGWPcMIgsD8y3NIK4r5m79XVRVaWm7B6+tk396lnHXWBYwOjdO3zczM1ZkUzvnrlsdmu4sLXprGyMx7eOFIkIsuuuhf7sjn9/s/R/aKohATE3OG7M1m8/+oDuzbt49Dhw5RX1/P+++//y+dz/8W/j9F7sPDw9TX15OcnExRURGSJJ3xcV+0aNF/1KTm/5Th/89kosbGRpqamujq6uK2227DaDSy79UXaD6wh2v/8DTdv29AF1FI/1EFzmcbEKN11Kj7+MvETuqS2nl35buYxCTO/dM+yuMPoJdCXHLYS85oC733dKHRx2A2F4F4N+s/XI9bE8AW0nLBhx/hqpjM7+Pm8KbpIZy9UThay9iUn0DEN4xGPx1BtBDx7wVgzuIKypbewcRfmtgQ3oy/u5a8uYsoP/ts3nr4ITYsW0NbSjG39bzB66lrmL/jPQLiEU4UOpir5nLzo60YZImIVseLC65mY3Qh31mSy3UFIK+7g5DxJI25VsIG6B5egFy1HA8JZC1K49xFaegGD8DRl9B0bkFVYVAXQ++gCU+jmfhhL4aIjCIIOE3RuM1JjFmzaE5Moc1mYMio4BUVgkiE0SIjoSKiqgIqEoIgIwphJCGCBhktEaIAWwhS3V7yxu1k2EeJ9o4R7XEQ7fMhAmFRxGkzQ4KRpOQIWUkd6AUfdn0cG+Pms0e/GJujgPzxU8SlHyQ66zCSNkC0HTKHXETbC/HkXsmrljm8eqKf5bXbuLR9D7pwAKdVw8eX5bPB1omqCESM5zCadDExET/PnPoFLscYrU3JqLKIRm8gsWIO7Q4velXHHDkPHCc5OlKHikK8pRS3tAA50kvEtwtVDXIyqhQhwcQj0tPEik5kv0j7nmQiHoF98xcwlJJMWApTl3yShWm9zArriX8rGk4MsmnxLJ6LX4NW8HFNyToSzdko1QbGG+tx56WyL6uNUcMoS2KX8MN5P0TTGmb8/W4swJCiYrs4m8QSGwPNDex64Wm8DjvBuBQKFi6jZPLk/9Zs6uuEQ4cOUVhY+G/pjPcpPpssZrefVqViYmJI1AdJb3sNQ8v7+DVWdoQrOKmWMaGLY3dxIQO2BLJlJ5cb9zI5+CoiGsy6c3B2LKDmhJVmRabLpNJNBBlIitJRGq8jJuJEdY7iGRvC7pPxi0ZkQULSGTHrdURrJRINAil6mWxTEFENEPJ58U7YmRgaoDMSRYN1MqfM+aSaBX6xsgTHPjsDzU7mXZZDbsXfqhzB4CC1dasYHZ2Jz7uYpKQk3NVxRMXrWXBF3pnPOSMyuifL6Zt8JRvr9CxcuJDp06d/ZWOtqiper/fMeDscDiRJ+lxy3t/bMtm9ezd79+5lcHCQV1999Ss7n/8kvnbkHgqF+D9PSZZlWlpaGBgYoLS09G+sALdt28acOXP+Yy5Cf0+G/z9RV1fH5s2bqaioYOnSpfhdTl6+5xbKz1tNVsoipM09BGcnkZAVhevNNqTV8bz45x/z7twO5sXP43fn/o4HPmzk47pO7ix/isbO27j5uR/h+X4igUkRQqFxkpOe4Y0Pt+FX/ERFolhQvY/E0XG+d+6PeVj+GVnBUQa2pVA/Yzldjho02jQEXSUR74cIKBQVprHwW7/F8XwjWwM7sHceJatyNrMuXM2bv/0Jby+/krHYdG7vfpWnUi/nvC2v0xN3gvYMN5eP5rP6z80IgsBEahbfL78GfXIyj1wymZyjzyG0/5HmSSZcNol+Vym+Q2sJhFMw54W4/Mo56Lu2ou7+PXpHM06tiTZ3FPbjNpIGPGgVBY/BxIgtj7q0qexNNzGoBY8aQzgSjxGRXCRSkckUIqQhEqMKWJAwI2FQT0dBKqerdCOAFwWXCg5ERoEuQaFPUBiQHHi0I0RJPpJCMpWDY0we6CXeMUSCYwKtohDUSDiTorAk6yjI7iNaO8a4PoF34xZRpVlG1lAcGeJRYnL3YorvQApI5Ay4SBqwEki5lo9Sl/PsyVEqq3dwbesODEEfEzYt712ZyzZLB5Ksx2Ndg8t2Frn+QZ5re4jqQR3DXacJxhKfiJQ/mT6nmww5jtliMjXdmxn0D6MTjRgtSwgI2YT9+1BCdXglKzsSF/BN806u0mxBUQTGW82M1UQzlJzMwblziWi1p6P4nE5WRfeS3VSG9uU2RkwmHj37Rk7605mVfIwVuYfJMF9J63u7cLucNJWbOGGrwygYuS3/Ns7NPxfPe30I3R4UFcYTjeRdl4+IzLEP36Zu28coehOR9FyyJpdx/vnnf60zjw8ePEhxcfEXloa/LFRVxTvcgfbwY8R2fEAAPXvVGRxXpzFmiGdXUTHDMfFMUse5VPcBRaGP0WmycPcvpuFEJbUhiVNGhREUNKLA5GQTFtmHa8LJgE9mQopGEU5vjUioxAkCMYjoVQFJhQAqLkFlGBUZkIAyQeK8KDMrcm2YcqLxxwToP1XPgcM1vOHLwa6L5b4KI1nuJNqPj3H2TYUk5/9tpUR3928YGv6QY0fXMm3aDHTjGQy0uFj9/c/3AXE+NZvm9KXUDuVQVFT0hfzyvyj+O5fCT8neZrOh0WjYtWsXW7duRZZlnn766a/8PH7961/zwx/+kDvvvJNHH30U+Gsv93Xr1n2ul/uXde/72pO7x+OhpqYGURSZOnXq3zXN2LlzJxUVFVit1n/ruf0jGf7/xIYNG87stVssFo68+wYnN2/gmj88Tf/jp5CCMpkPVOB6oRlBK3LIs5G3OUF9fBsfXvAhXl8UFzx5mMsmvUOrs4i71+8lPlui78pGQEKvv5CjdSlMDE0QEQRyXUPM+3gv67/1AMbx7dyu+YCerXGMFX6TPf4DCIIenXkNIc+7SEKABJueC3/6PO6X2tjvOkhP+w6Si8s4+7pv8uovvs+bZ32D8bg0ftDxLL9NvZ4LN71MS3oDvSk+vnMymblb+kBRqJ++iB+mr2BVRSYPzI9FePVaPDFNtORG4VatDFRdg9xXSuGSVGYtTaNp/cNMG34Pg6+XEZOB+qZUjDUqMb4gfp2e3sQpbJpUTlWsgF1NRJatZKNSIfqYhZZ8xUwCBoRPxPmgouJXIKSqhFUIqQrh003fQVARAI0qoRNEdALoRAG9AAbxr9ctoCr0qhFOqXBSjFCvcTCm6yMJH/P7Rynv7iJlrB+b14csCNiTojGn65mU1U2UdoLGqEm8EbcSX2AhBQNdJGbtJDrrKIIC6YNe0vs1yFGXsjt3Lb+tcVJxYjs3nNqKNhRgOMXIusvTOGjoQhexMp54IyHTFBY4qvhJ56Ps6UjGN376nk8qncawxoIvGGJaJJuM4BB7eg8RUcPYDLn49EtRZAcR3w4UxUGLeRITSSk8Lj1BkmgnEhBp25OM7BI4MH8+A6kphKQQdaknOSu1n4qInri3rHC8n82LZvBcwiVIgp9rStaRk1hMTG8mtVs+xp+bwu6MdoaNw5RQwpWpV5Itp6DdEyBKhdFPLGxTZiQw2tXBnpefxd7bTSgmntgplZy94rwvlLD2n8SBAwcoLS39t88lAPgn0B17Cl31i0RUkf3KdA4p0xgxJLCzuIwRayyTwj1cIr1KiXACKVJBb9O57GlPo9mg0C8q6CWRvDg9IZ+Hfo9MEA159LOQTqaIQ2QowyQxikVwoBHCiEIEUVAIK3oCahROJR2XnMOEPJkBYRKDZg1HNQrH/UHiRZGbFR3nSjp0k2PRz01k1D3EPetOUB+J5Y6kfrIiU3GOhFn9/TJ0xs8HOX5/J3X1F9HYsIiMjAtJ1ZdStbGXK39RgfCZ58/79FwOJi2k31lEVlYWS5Ys+feP/SeIRCJntkwmJibwer289tprKIrCxMQEpaWl/PGPf/xKf/PYsWNceumlREdHs2TJkjPkfuutt7Jx40ZeeuklrFYrd9xxB6IonvFM+aL42pK7qqr09/fT1NREZmYmBQUF/21SxN69e5k8efK/1Y3uf5LhPwtFUXj88cexWq1ce+21yJEwL911M/kz51BWcTHyW214p8SRWh6P8+UWhOU2XnjlZ7w/r50lSUv45Vm/5I51NVR3tXNj6UsMNFzJFe/8nvGfaVDjjYTCfoKBH3Pk2AkcOjexAQvnb9yAu6SQPyTN4V3TT5lotmB3r2R9nB0x5EVjWkEkUIWkDqPVqFz2qydQtrqpaztBddf7RCWncsl9P+a1X97F63MuYTgxiwfan+LXGd9k9fo/U5fbzFCCn+/ti2H6ETuEw2xacgVP2ip4YEUha3VNKNtu5VSRhDNWon1kEfL+i7FkRnPe1VOJirQR/vAezGPVjJj01NRkE1vnxxSKMGpNYdeks/g4w8woKQiKmXLJw7mCwtxIAlb0KKqKQ1axywrDoptBwYVDCBBRwShbMEZMaCIGJPW/T1SShTBByU9YCqFIQcwi2DAQr5qJx4RNFDFLpycdtyrTqCgcEiIc1A/h0/dR5nBzTsspcge6ifV6iYgCzhQribkqeakthDU6PohfzGHdKrJ7daQm7CYmbzeiJkDycIicHhnFfDlbci/nD9XjLDu+kUvbdqORI3TlR/HCxTaaxQH0kRwG029FkOL5YdfzlI0foKo+AyX0iVQ/Yz6t4w6iVBML1FwGBnbR6u4+3UM+eiFuSpCDh5EDx/FLFrYlLORbll1ceSaKtzBWE8VAcgqH5s5B1mrpsHRgyOnhguheMpumoH2plVGTiT+ecwMnfBnMSKpiZd5B8uNupO393YwODdA9M56Dliq0oparkq+iQC0gtk5D3JgOSYAhi4bcbxaiN2k48tF71G/5CFWFQGIaZUvOYd68ef+rFS5/D/v372fKlCn/8Pn+lxH2o6t+Ad2RJ1AiIQ4znX3yNMb0CewqLKU/NpEpQj8Xq89RoLYQmFjM/mNLOR6y0KY7nS+SYAQ5HMYbkZkhtLBCPcl8GkjRDqGRTleIhH0SYZ9IxCcR9kkoEQFVEUAFUaMiGRR0Fhm9LYJGJ+OPRNEYOJt2/4Wgt7IlRmWHL8DZiVH80KtB55PRz0lEmpvIdX/eT+t4kHvMDUTG5lO8IIWK8zL+5k+trVtLd3cESfwWpZlz2P1yG2t/Mg2j5a/JeMqTFbyZch6yt5CkpCTOPvvsf9/Y/w8IBoO88sorrF+/noMHDyLLMosXL+ass85i2bJllJeX/0t+Bh6Ph+nTp/Pkk0/yX//1X0ybNo1HH30Up9NJQkICr7/+Opdccglw2gK3uLiYQ4cOfSnb5q8duYfDYUKhEA0NDYyPj1NWVvY/rvIPHDhAQUHBV9Z7+v/E+Pg4tbW1/1CG/yza2tp4++23mTVrFkuXLuXUoX1sfepRrvjVo4ytG8foDJFy/3Q869pQ/RGOytt4Wz5GbUIbG1ZtYGhCz9pnj3HD5Fc5MTqXB9atw3JWBv1nnQBkLOa7OFKn0j/Qj14xML2rlvy6Vr5/0S95KPhzioK9DOydxNFp8xiaqEOrL0HFhBw8DsAFt95MfKCE7l31bB94BZ1ez9W//AMfPPoDni86l/60XH7a9jj/lX0rF2x8mcbMk4wlhPj+NhNlJ52oispLS69nU9xkHr10CtObXkbsepiTk224NSZ6qr4J/cXMX1NA4Qwb8vafYzz5Z7x6keOduUQdDmEKhRmIzeaV6cs5ZjXik9PIEH1cLPk4N5xGFHq8ispgSKZdtNMj2dHJFqL8cWcIXCN5MUTGMQWGMfjH0fk8aANeNCE/ohz5xLEOVFFA1hkJ682EDGYCRis+YwIBbRxhYjgtRoJf4yWidZMoaUlXo0gRjFglAVEQGFJkDqoym7R2BoynmOZ0cU5LM5N6urEEg3iMOiK5VgoLBok1jHAwZhofWi/BNphLpmEfcUWbkXQekodDZPcoKFFX8VHmJTxeNcTao++xvOsIgqpwbHEKL87yY8eLqp3PWMpVxIUDvNzyAM2DKkOdpxewsZk5BJJzGHa7KI6kURIKsa9vL37Zi1WfRlC/DFkNE/FuQVEcNFkKcSUm8YT4OAnSxOkofm8yslNg78KFDCcnEdAEaUg7yYqUAaaE/xrFb11UwbMJlyIIAa4ufpO8pALihidxcuNHBDOS2JPdTb+xn8qoSu6dfi/0hVE/dmJVBOwRhfFikaipRuzDQ/iaa2k/ehDZFIWYU8iiFSspLCz82kj1+/btY9q0aZ/r5viVQZHRNL2Hfv9vwTtCtVjBzkg5Y9p49haU0JmYTpEwwFrlWYrpZLD3fDbXzqJWo8EpqNiMGgQ5gjU8yHnqEdZwiGxdP5KoEAmI+EZ0eB1GJvTxjJjjGDKacBtkFI1CRJYQIyB7tTi90fh8FiKSFj0yWZ5BZgYaSEu2E5UbQBU1HPRcT1/oXOwmlcc1QaZnWXkkIwH54AhSspHgBRlc8PxxMieauNTsJRBYyNoHp/1NPXx392/p7lnP+Ng9zJq8lO3PnWLND6dgif2re6j2sRIeSbucaE82aWlpLFu27Ksf+y8An8/H0aNHefbZZykqKiI7O5vt27eza9cuCgsLOXLkyJf+7muvvZbY2FgeeeQRFi9efIbcd+7cybJly5iYmPicV0tWVhZ33XUXd9999xf+rX+tGPDfAKfTSXV1NUajkblz5/5T9aGSJJ2xqv0qoaoq7e3tdHZ2UlRURHp6+j81CVVVVZ0xsgCo27GFtOJSdNiIdg7gzbWCI0S4w4V4lo3GV6poXtjDXNtcEk2J3Pf2CdKixrHq3cxwmrBE/AzOrkdVzBiMyZgsi7H3vUtQp2DzB8k71srRtdcxxbubSv0pug/H4SldzdDETkTJhKCZRMT7AQIq0+eUkZIym7EX69k18T6iHOHiH/yKg+88xtspM+lMn8QjLb/iZ/l3s3zTG3Qk1zKc4OcHm02U1rtQRZHHz7mF47H5vHHVVJI23UeQjTRMszEYysW9+VtEWWI574eVWPyNKE+cjTEwQr2cgOP9GJJdXkaik/nDolVURdkIKvFUSMPcKHiZEkkhKCv0hVR2igOMSD7i5VTEgI0kwUhUqJX40QPEDHcS5e5DUkJozDJylIaARYfPbMCVpMep1RLWiEQkEQXQhxWMoTH0oQixvhBmewC9O4ToVYgEJAKGWDyWNFxxmUzEZePWZ9Gq6mghhF8/QYpGIocYzpe0rFGScXkS2SNEeHHKdCZmtXBuzyALm5tIbxxhoFFLY/pkMoud/Cb2AdpMmbwWcylddb8kS7MPuXgTQ0kekodfZ03dG5yfciPPf/N2rjt4Dvcdf50Zu1uZth82fiOfd1IPktx9FLftCi4o+RML0k/wYPwj7G5Ox97TidDXzaSK2bT5huiRNMzPW4tn7CC19lOIwdeIi1mIM+oK5MBhSjxV+Px9XJz0Q243beUy43YmnT3IaKuFxXv30JOeydFZM6jomcVBRxsNOQOsvLaT9JlTOeelk1SYWvjjOTfwdO0NVCRVc37uOmZ++yY6P9zP0n16+mfMYb9cxXV7ruM7pd/hgvsuwLm5D2PVOLmnVHra3HinKljLZ1OeX8SprevxNlaxfbCX6imVLD377K9FZ7BP+1h81ZC69qLf+19Io42ckiazWV3OkJrEoUlFNKXmkCsM8n3l50xV+qhtuIjfdX+LFi2IOoEovUhhsJPL/Lu4QDhKgn4CJSLgGtPRIcRjj7fhzowglweQbEEEzQQwQQLw34VFghv0p0SM1QIT4/FsjJvFQCSBc/cdYW5mM4vzn6ba38Rh57f5kUXPz7scPBZv4t6r8/G93YnuvW5unZ/N73YpdPa8QqwxkZ66LPIqP59cZ7aUYjC8jqr6kDSnF9ty5DN+9ZEAhpCLQV0chlAIrfZvy+v+05BlGUmS8Pl85OTkcNttt3H77bcTiUTo7+//0t+7bt06Tpw4wbFjx/7mvaGhIXQ63d+YsCUlJTE0NPSlfu9rR+5tbW2kpaWRm5v7Tz9k/w5y/6wMP2vWrH9appuYmKCjo4O5c+eiKApjPV0Mnmpi+R3fY2hjN2YgfVU2/gNDiBYt1U1b6ZykIaAJcPvM26ntc3Kww86tUz5kR8+5PLDhOVyLk1EsHQj4ycv9LS+9uQGH1kFMKIbpdQcJJkbxfCCN9bpHsPdYCJnPZlekGgGQ9AsI+7ajERSsUToqr/4hrmeb2RnYguocY8GNtzPcUcUbY3qqF8zhZx1P8XjezczZvYGxqGo60tzcsTeasno3gqryx7Nvpzouj79cXUrcuivwxDXQmRNF29hClN2XkV8Rx7xLS4gc/AO6ww/jMkjsrZ5GessoZq3Cc3Ov4eOkZAJqIjO0/dwuB8gPFeCUFY6EfNTp+4hVU5G8CaSKDhLGd5LaWUO0qwetJYIn3UzbzATqUybRHKNHpzGTHhSweVWMQRGCEYJBP+FwkIigoKAiSipaixaNRnvahUsv4rWIjOpUFDlMui9IrstBznA3eac2otpVvIYUHHF5DKcU4zQVUYPAEWmCKEOIfDWGczR6LpBTGXQlsSkmxI+XlZAYGeKS2gbKOjrw9oY5EDcJW5GGB7y/Z8iYxPO2K+mt/wWZmn3IxR8znOgnq+9pbmtYx5Xl9/CLKffz3P7jPFj9Ohe90sZCm4a/XJfOIdeLWCe2sT/9O6yY+jK/s/yBqJEWmptSGTx2kLi4BHwpOWyR68mPn8SKuBJ2d2xj1LGLGEMbfv0yRF0eZu9WVg1sZIulmPcTZ/O49DiJkxzEpnsRdkPq+/3sXrwYyMfXkMYz6TrOK2hl8k9NxL0VzUOv/4ntC6fzjPYymsYLubpkHfln5TB7Yi0nPnyP1ORy9uYN8pv637CpYxMPLX6I+DnFDL/YSpYP4qpicBQZECebyFxxMaN1Jxivq8J9YDvrTjUyac4CFi5ciNn8xWxQv0p81eQujjSi3/sLNN17GNRks5HL6VIyqcrOpzqrkAxGuUv9DdOCg+w+cQkP2nMZ0KiYTCJp8iirlD1cFdhFsmGccEhkKGjiuCUdTx7IiwIgKQjBcfQ9AsopI2FXFgFPOk4yGTKmMWROZ9wSQ9CgIEoBYjSD2CxtpFnrSJvSQaDCh+xxMGfDMRL2hqhPyOMF93msPbyTqbP2MCQJNNm/zXVROp4/PsCSSXHMuDIPz8utnNur4XGdhv78pcR07qO3sfJvyN2gTz89DuIEivxJ3wfNZ8r+PMMADOrjSQvbvzbkLooiXq/3c0naGo2GrKysL/Wdvb293HnnnWzbtu0/1v3ua0fuFRUVf7eH8D+CRqM50+v9q8CnMnxsbCzl5eVfyO3o5MmTGAwG8vPz6e7upn7nVkwxNjLLKhjZeBJ3rIEkkxZ3zRia8hia3jtA44IRSowlFMQW8O2tNSSbncQYXEwe12JSgows7UarjcZoyKJ/wEbQEUTQGogJOkhv7uXVG3/MVc6NRKs+OhuzOFWRgzq2H60uFyUyBKoHGYHyq27Dv6Wf+okaJgbrSZ85j8xJefziqSfYee613Dj8MXuSFhHT2IwUPEDDJAdXV8ew4IgDQVF4+qxbOBmfxytXTSbm9UsZT2tnIM1Ec++FcGglcy7OYfJsG97XVxI7eIIWNYGRd6xkuUc4njOTP02ZwaiQQ5Z2iLsZpzJYjD2isCfiolNvxxZKJSGUgc1zjLxTe4lydSMlQ2tFGi+VlDNmMlLu1RNjV2GoH9vYKBPRIWrMMn6rgkcfJiD9D4s8FQyyhCmsweSTsLglCGtwqTr6kzPwZQsMmBQyQyEqBk5R3nkQRsERnc9IahlDCVNpEiRqJCcxhiBFxHKtxsC1vqkcV0p5ZXI5T1fUcWlLO7OamxAOODhuycFcauB+/x8YMCbxku0qBqp/Tkb0dpTCrfSkyBT03M9vhwrpXvF9flD2K1IObOXWhvXc/Ug7y2Ym8PQSJ+H++5AN53BXwd0UpA3wouUBdnYm4B4BxkfJL59Fb2SM/ojIvLxL8I0epG6iFSn4KjbrEtzRVxHxH6TUU4XXH82apPu5y/QxF1t2MWn5IEMNVs7esYP2vFyqpldQ3jWb3RMtNOUOce61naTPnMZZL9Uw3djCY8tv4Jna6ylPrOHCvL8w89s307XhCEv2jDI4cz57Ise4bNNl3Fp8K2vvXsvAxlakai8ZpwL0twkUfaOc8ooK+jqWULfhfeg4RffHozxfXUXp7LnMmTPnP1raeub2+IrIXXANoD/4OzQN7+DSJLKJC2iMTKIhNYuDeWUkiU5uUx+lzDvIx8cv5dVAMh4BYo0hLons54bQFooNPURUgX7MHE5IxZsTBoOK4A2gbxbRHInDa59El6aCk1k59KYYsefrGLaZ8er/mssgqCqmYAhJ1iGLNiJSGUHd6X3dNLWHyyyvU3H5MTrOyyPhEQ9Fp46wMXsOF1YdYEXlbrbbpmD2LCTXJPKjNxv44K7ZmM7PhHe7WJBuocufR1FoA331h4HCz42DVpv4yf/eM453n5XuRVcfAIPaePy+vq9F33RZltFoNPh8vq/sfKqqqhgZGflcmZ8sy+zdu5fHH3+cLVu2EAqFcDgcn4veh4eH/6Y67J/F147cv8yD9VVF7l9Whv/s8Q0NDRQXF6PT6QiHgrQe3k/psnMZ2TeMHtAvTiNYO44aVujw1NKfocehd/CT8p/QMeZlW9MoV5d8zLbuZdy97S8oywvAXEM4PE5Bwe944dUtjOvGiQvFUVZzFPukLI6MefiZ4WMmGkwo2ZfQaD+MiIignYziXY+ASm5pHtFqOvaTvdQObkUbE8fKb97Kc7/+LhsW38BC3ynMES/tdh2Lm9azeY6DpZ0xnL9tAkGWeXv5t9gTW8i6K0uIfm0to1ldDCYZOdXyDYS6hSy9vpiM3ADBpyuw+u3s7p+C9dAEZiHCr5fcyL6YbEQhwi36Ni73TyOowKGgj1OGUWI8KdhCNjIHPySrbT9Gk4fuKSk8XVGJoDUw3W4ipaMXv6GHvYlBhrMCyDmno4CYiAFrKJb4kJV0jwV9xIRGlZBUAemTjHpFUFAEGRmVkBghKAUJikF8Wg9DKQ5OaZ0oogIMYw5qiHPokIM6giYLx6cXMWKBYo+fys4tFB18G5c+i4HMmQwmzOCEAIe142TrNEwWrTyuJNHviWddxkxeKTrBuf09LK+uJfqwg+MNOZhKjTzgf5g+YzIvGm8k5tBDpKVtpCXvAJ2pwxS3X8/r/rPYceWdfPP4bG4++CpzjtbwSLXA+9fk80HCVlK7DtGdfCuLy17i+9YXmDp8gNr6DIarjxAbl4CuqJzt9gYKEgpZEVvM7s7tjDm2EWtsxaNfiqjLw/JJFP9edBkb4ir5o+YJUkodxGZ6UPcKpPX2sXvJEgopxFOfxjPpei6cdIrCn1mIfdPCT197jB2Lynlaezm/PTaJK4veZNKCDObOuILj77zDWlsZBwvHebT5UTZ3beaO4juQ4gWSTuhJsQcJvNLOcLKR/CsnU/SjafQ11rH/9ZdwdTTQNDZIw8kT5BYWU1RURFxc3JdyGfsy+JfJPexDd/QJdMeeJoSej1nG8fBkuuJS2FFciUET4lr1z0x1dbOhai2vBBOQBZgk9XONspE16gE0hjADkomj8Ul4shXQqWj6w5h3agj05tHKLPYXFdMxI4bBFCserQ4BlSzJSZ40zkKpgwzJRbZeIFFnIsGcRbS5FL8f7CMjuE6exHWshR5fAnV5FRxMuo2jOSe5JvrPDPwkEef6s1m8aTN7kqZwQd9RfpTyIgtN05knm9kqhLl7XR3PXTsNTUE0Ff0OtvqCXJRZiq+/hlBARmf4K3lL0ulKD41GIeg/HYDpDH+9juJYExFRh1M6Xfb5b8l1+IL47yL3fwXLli2jrq7uc69df/31FBUVcd9995GRkYFWq2XHjh1cfPHFALS0tNDT08OcOXO+1G9+7cj9y+CrIPdgMEhNTQ2BQIDZs2d/qZusp6cHt9tNaWkpkiTh7O4g6PNSOHch9pdHCIsC2VPjmHi6AW2Bler9z9I6xUmcGMf8jPk8+FETVkOAPGsPffULiQ15GJ/fhUYTg8GQTne3nrAnjEZrJjYwQXLnII9e/0tucT2PHBKZGC7h2NQQwmgESV9B2H8IjaBiMWuIn3sxmv0Otng3QCTE+d/5KQffe4o3Sldi1sjc0PoS3866j0s/eoyts8bI8pq58a0xBAWOLFzDa5ZiXryslKh1V+JI72IoSc+p5quRmmaz/PapxBgaEf58KXo5zLZjlWS0DtAXm85P5l7EkCaLQkMrPw1nkuYrpy2ocEjbS4ycjNVtI2vwA7Jb96JPDLB7dTFv5ZhZNGoi79QEjVGdvJbux5MURquKpAXjmT42Bas/HpOsRftJDS8qqLKKEIkgyGFERUZSVURVRVVAVkVUQUTVGFA0NpA0oJFAEFAFFa/Gi1Prxqn1MGEZpyZhiCrRgT4ikTyuJxwwMJaSjL04g1xfkLldmyk8+C52SxHdufPoj5pKj+AjyuShjDi+K0bzLfdC3ooKctcFuZzb38WKEyeJPjTB0fo8oqdoedD/C05GF/G+cDOpexeTWvQutWXNxIwdYUnDJczL+Da/u/4e3thbxc+P/4XLn29lfqaJpy83Eh77DYI0g19lfZPklNW8rPkeR3rjcI0AB7dRVDmHDv8oA7KWhfmXYR/ZS6OjHSnwCtaoJXijryLs28N010kcvjiWp/wXv9a/wkJbNZNWDjBwIpblW7bQWFRE3ZQypnbOZpOjgebccZZd10nqrHKWvlhLubGFJ5bfwJ/rr2XqUB2r85+n8ts307e5GmnPOIUz5rM7poo7T97J2eaz+dEtPyJS6yS4sZeM0QD9D9cjzE0kZ1kplz70O1r27+Lou+sItpykY2SQ/p4eUtLTiYqKOuPoFhsb+0/3kf8i+LRK50uRu6qcTpbb+yvw2TmoVrJXLaffksD2yTPwGQ2cp35Apb2FTScv5K3wSvRCmJXSfm6W11Ok68Vu0NEYFYUjV0LVq2h6FCybNXi6StgbO5/d0woZWBzNhDkKUZUp8J9iZf8uSvrbKOzuxTLuA1lFkRRUnYISB+Fkme4smUgamC2TiY87n4yLVqGuXk3h8DDlr7zPqV3xOKuK6Fgyh4LE/dRekEi/9VqWrnuZBjKYnd7KN6R9/IVlaFVw9XtZd3yAyxYkk/fCBCqgK5qFt+fPjPeMkDIp5TMDc/r51GgEvBMhjNFaROmz5N7CuDUP2ye24//WKoV/Ep/uuX+V5B4VFUVpaennXjObzcTFxZ15/cYbb+See+4hNjaW6Ohovv3tbzNnzpwvlSkPX0Ny/9+I3MfHx6mpqSEuLo7p06d/6aYDDQ0NxMTEkJaWhsvlYqKthfjMHLSKjejAAN7JscjDfuQhH87UMGNqiF5TH1dnXY3DH+bDmgHOz9nO7r45rD25Gc1ZZQSNRyCskpv7IK+8uYtR/SgJwQRKao4xXFJI5/goawz7Ga2JIpJ3HoOjO5FEA4hRoIwRQWDBdbciN0u02OvwjnWSu2Q5WinCc6Ma+iqzeanxQe4reZAVG17ncOkAokbg+89NoJW0DJZV8FDsbP54cSmpW76HL7mFgTQjbacuQ2ycw4rbp2HmIMZ1NxBCYt+uMrL6B9hZuIDHi+fjF8ysNVdzm2ceXllgc8iBXytidacQ59xPSd0GjDYXm74xlS2pOua0Skxq7GNHtouxaUGMqkieN4uk4WKsYSOCCCgCYiSCTa8hLSmOnGQLiXovFlwYQqNoAnYIuhACDgj7PneN3EGQJROS0YpPMTLmk2gbDTM4rmFCtRA2p4M+H0VUsevtjOkmGLWMciRxCBU7SS4DngEjE+kp2Eskprr8zGl4iYjdzED6HLozFnJUUME4whTRyg0aA1e45/GBpZJ7L8hhSX87K6tqiD7g4nBsASmVAR5y382m+PlUOa4jvaOd8NR3cFQ6ye79Iw+2v0f3uT/mnkm/oGLvB3zj1A4e+m0/u1Zl82JRNSnddzOeeCsrpr/IdxJeZcbgTk7WZ9B/7CCxsfGIk6awyVlHSUIZK2IL2dG5HbtrK3HmLjyGxcjaHGJ827iobwMP25az3jaLn0vPk1ZhJ5ClQT0gkNXTw64li5nMZJx1Tp7J1LN6UjN5P4si9i0zD772OLsWTeUp3RX85lgBV7jfpnBWMgtmXMexdW9yiamI4yU+NrOZ6o+qeWDWA5TfNw3XBz1ENTnQHhmh8fgoyZfnUbxwGXmVczix8X3qtm8Ct53OgW7iCkuJjo5mdHSU1tZW9Ho9cXFxZyxF/9VGIcAZf40vOgeJA1UYdv0EaegkLUIJm9SV9OmS2FNcTl9MAovUncwcqWVH3TlsjswlQXBxt/AW14lb0JqD9JhN7EtPIGxTEcfBvF0k2JzHvvgFbJoxhcFzY/AaLMQEXMxpqmFW1QkqGmuw+H0giAiGGARdFII2GUQJFBlVCaK02MHvBERCBhH/5C76V/yW/sxnycz8LvGp55HwgzvIrm1g92NHGd+5BmFFNTOtR/jTggXouhZSefQQ3mEdN6e8zXvus/BJKhYEntzXzcpbE8lMMMGol3D86TK4gVONnyN3v98NgE5vxDMS/FyWPIA0XE+PtYC0gAdJkv5Xu3p+in8Huf8zeOSRRxBFkYsvvvhzJjZfFl+7UjhZlr/w/nlrayuBQICysrL/+cOfgaqqtLW10dXV9aVk+M8iEonwpz/9icrKShYuXMj4yDDrvv9t5l52FdFDBZg7XdjumUb46DCB6jH2hd9ne0w/x+Lq2XDhBv6yq58Xjo/yq/kP8XbNvTz0yk/x/Dobf+wYGikKi+X3vPfeB4zrPeS4Fc59fxO/u/6XXOD6M+dHjtBbtZDd+Xk47U1IxgXI/uNoBC9ZOcmcfccfGP5TFe8PPo1oMHLTH57gN79/gOfmX8Md45vp1CUz0ukncfAtjkye4MEPtEzpglBCMpdN/SbfOquY1QMvoAv9hZYCC62dq1GrzuXcW6ZiFHcS++Ft+BU9x7fmkDbq4IUZa3g3rQKt1smPNT4W+afQGZTZrxnA4k5AVEeoPPkSseFuTizL54XSOJa0amkLtVOf78Krj5ATiSZ7pBKbLw5BUkAWiDPoKCspYGqOhSh7NUL/ccSBagT/+OnrKUhgtKFq9AiCiIqAoMpw5hZXCYfCIAhoJQE1HEAIuc90l1O1JvzmLCbUWNqcZmpH9EwYE1HNUQQ1YQaNQwwaRhiy9CGLMskTBvJ6zCQGrYTMcE73KMkNDkZjp3CqYAUhbQaKwUGpZCFXYyAMvKMEeNN6jFVdbSyvOonVH2A8PYbC6aPYzHZeSF6L03UemaZtxBVuRRuEya0ODOELeX/St3hyXyc/PvQC2eO9jMXrePKGFOqlfkShkpHUb5EWcvJG0/fZ1ROLeygKQRBInb2QVqcfi2JgEfl09m6iyzuIXjSht5xLUEgk7NuKEu5kUJ/KsZSZPKF5ksmadiJhkb7D8QQGNJycMpWW4kIUQaUuro7iHAeLDD2kNFWgebERh0HHk+ddz35PLqXxDawp2EpR+q0M7Wigo+oojsnp7Etuwq63szh2MffNuQ+LV8/oq+3oXCHCKozGG8i5IhezVY9zeIhjH7xJx7HDCEYzvthkMqdVMHv2bHQ6HXa7nfHxcfx+/z/0av9nIcsye/bsYf78+f9U/b3gGkC/7xdomz9kVExjgzKXNjGLw/klNKTkMU2tYt74QfbVLuVUOIYisY9blA9YqTuM06qhK9aMM0OCCBirRcQqGyeVJbw9exa9RXG4oqzEOydYWHWEhdVHKBsYQWfNQGuLQRejQW/xQ1QERRNEwIcGGb0SQsGErCYRUiYRCBUSmRgkPN5AsOsAYsCLZ7oBz5UuEjLXkpX1AwRBwtfQzOYnmlAtejLWPoCizeRuz0M8f/9dpGWOkjLVwYPOp3ndEIUNAbMgcPnSbC4NSczZ18o9C7IIvPpLcitnc9ZN158Zo76+kwwMXoco3MPQ/gpsKSbmXZZz+s2QB8vjJTw/9UfU2ZMpDLi5+uqrv/B1+6rR3d2Ny+Vi/vz5tLa2kpeX9z8f9DXE/xXk3tnZidPpZNq0af/0MZ/K8MFg8Cupa21ubub999/npptuIi4ujpPbPmb/K89z7SPPMP54JyGDRMG95dgfqYEMHa9u+ikfLR4n25bNbWm3cde2CXJi6pgU00D2rhQW003XNafr0vPyfsIHG+10ODqwBW3MrD+OKQwPFV/EDsP3GDkRxUTy/Wx0bUQSTaAtQQkeQ0Dlil89grgnyJaqNxgereOsu36Aa6SB28KZxFpU7m19ih+k3sFFm/7Ihnl9LO+J4bqPvKjhMN8753vYCvP5RXY7lvq7qJ4SQ+f4XEI7r2PZ9ZOwRu3D9uFtBCMGjm/JJmXMwe8WXs2u2DJs5lYeDieRF0yn2h+h0+RC77CSaN9Bcf2HKCUafnJeObNcJvp6m6kqsOM1RCgJx5Pdv+C0hawqEKXTsWjeTMpSVTSN7yG2bUXwjqJqTajmRARVxeX1cioUR6eSzBBxDGnTGRdsBAQjfvSEVA0aQUErKEiyn1g8xAlO4iND5Ki9ZAtDZAvDGLUC6KJAjYDfgYBKyJDAmJjO8WELTYFkArZkwloYMA3QYxpg2NyPRhHJHjRR3GclYNYxZ9xDac0Adl0RrYXn4jUWIutclGpN5GsM+FSVV/CxNfow19Y2Mq+xCa2s4JlkY9qUU4ybYng++Tbiu2JJL3oLc1IzCUMyBe0axvN+wncd2cTt3sxt9R8iKjI7V+fwwqR+UA2MJ92GrC/hp51Pkj5WTUNdGigCtvQs/Kl5jLldTI1kkxXoY3fvURQUkqJnMMFMlEgzEd8ewqKWrXELWRHdwD2aN0FR8Q7q6TsSh8sUxe7FiwiYTIzpxxnMamVNfC9ZQSuxb5kRjvWxd2EZTyRfSUiO8I2idyhKTiDOWUnjxo1ERIm2CjOHjMfRiTq+XfptLiy4kGCtHfvGXswqTMgqgeIY8ldlotFJjHZ1cPS9dfQ31oElGl9sMlll05g9ezYpKSkEAoEzTVk+9Wr/1Dc8Njb2n07Mi0Qi7N27lwULFvzjrO2wD93RJ9Edf5qAomOrPJsTQgl1abkczJtCNl0sndjG8Zo5nArZWCTWcYfyHuXmVvpiDfQmmwnZQNMvYNorMdo9hXfLlnCiIpfBlGSMAT+LThzh3KpjVDgjGJOMuLIM1KVFc8IaxSlzOn36GMZFkZD41xbHimBEK+hIDU1Q7mrk7NH9rBg/giin44zcTFAuIDi0F3/V28gmAce9AeJKLiE760cA9Dz3LrtPZZJd+SiG3AZCmS+y49kd3HrgNfLOHmVd+DZ+H1rAqKhyu17LhwaV1xZlsXJ9O9dMSUG78XkScmJYdd8PzgxVbd0GAoEHMBt/SfWriVScn0Hx/NMlj1L3PkzvfINr579BRkM7U1KSWLFixReder9ydHR04HQ6WbRoEcPDw/82/5R/N752svyXwReV5T+V4ePj4/8lGf6zaGlpISkp6YxLXvfJKgyJyYSHBcyKijgljnCPG8UVoj/YyUR6FE59B9M002gYDTPih+sm72RDxyWsPfIn/PdOR5IsqKpCJFyJY+QtQiYVfSBMRksPz17xI67xvYccFnEHZ3JI24WAiqgrJxI4hCQoFE8twhyy0dNwiOGxegzZBeQUFnLL/n2MV1Ty57rvcnPxz1jx4SvsnzJOAhYue3cUNaSyYcmVjMWm8OhcA6b1P+Dk9BgGAgWEdl1NxfIkYpLqsbx1B+GwnmPbc0gdm+ChxddxOKaUtKiT/NE3mZhIDLv9Xpwa0Dh1lDU/RYqzhn1rJ7MtN4rKhgA7k+oZnBJgkmxhUvdZ6BUJVJHslCRWrzoLS8s7SDX3IOzpQjUnoGij6BJNHPLnczA4nRq1gP7wX6WzWJOWpGg9cWYdJp2EVSuhlUQiikJEVhmxO2jyhXEGFbyIeMN/rcxIEUKUScNMk+uZJldRJnZiVgIk08mFUQ4uiBJxGPOoscdxfCSNrLgZeHRl9Jj66ErspC29n2SHkUjIwrEFk8iLBFhY/RiucAYtRStpMpfSqB9nqjaKWyQzl7qW8mReOe+UHOamozVMOdVFQ3cKxkojPw7+lJ2xMznkvJnM7gbkae8wFhuipP0eXnAtZdNV9/Ct/VN5cP9zLPugk8lxGp663kp4/GHQzOaB3JsoShngGf2P2X4qhYm+bqThAYrnLaNmuJsBUxTnFF3FsY6PGHYdI0rXiWw4FyH6KgTvZs4b3Uq7N5eVSb/gWelRMtKGyT9/iO4DES78aD3HKitR83Kxtc7gLbuO8hwPc6/tIHlmJQtebGCK4ac8dd71vNhwFSWDzVyU/yrJF5+LoS2CsmcfuYXz2Z3awW/qf8P7re/zk/k/Ifu+Kbg39GKotWM75aTj17VoF6WQvSCHlff8iP6meo6++wajXacYc42zrqGWzOJSZs+eTVpaGqmpqaiqitvtxm63Mzw8zKlTp/7pdqv/oyyvKmia3ke/71eo3jEOqBXsoZL2uDS2FVdilVxc6niNpppS3giuYIV4jCfFt0iNHqYz3sze9DhUCQwnRSwHrRwRl7BlTgWNF+cQ0GqpaK7jxl3bWGYfI5htYs+5k3go0YzMBOnBPlJCvRSHXFQGfQiKiqiKKEEtajgKQUlBl7IAfUklndGZHHKm88OkuXxPFrm+9zW+3/0AcmQq9sz70SVOZXzHz7H9FsYeeIvoqBnExp5NxnUXEvedd7FXXURqbhPZ4cOYzz+fyKZ1AEQZOsnzLGLUKBMtaulz+Tgw2IUMuAfGiRMtBDyOz+UtOB0d6A1AIBlFlolN/WuuhNR7EMUYy34SuNpxjNSK8i87/X6lkGX5TAOzr0P2/pfF1y5yVxSFcDj8hY7p7++nr6+PWbNm/cPPfVaGLy4uJi0t7Sspe5FlmT/96U9UVFSwcOFCwsEAf771OmLKplNhXomlz0PCD6YT2N5HqN3Jht5n2D3JTUt0By/OeJGnq4PU9rZzU+lTnDx8LTfveYGBh+wIGg0JCedzsm4yJ0+dxCAbmNLdTGZHP3fM+TZ7dd/G26RnLPp+1ns2oRFNoClEDVUjigpX/f4ZIh+Msr72eRyuPmbfdBdtbXt5MGs533AdwRCc4MhEKlldr3Ck1M5P1glMHpSw50/mirzLeeHqUvI+WEV/mZtBYwKjH99H5qQkKi4SkN66iGhHhN37JpPRN8ovFl3NfttUMqyH+JNnFsZwFLsDLoKqDjFsZ+7Rp7Hahvj5ZQvI9WvpGWqmapIdqygyY3g+Fs/p1fGknGxWnTcf/YnnkE68BKqMEp1Js1NiQ2AqG4RF9EZi0IgwJc1KeWYMRckWCpOiyIkzodP893JsKBTiwIEDKIrC7NmzMZlMTPjCdNt9dI/7aBv1Utfvom7AhTcoIwkqU8wOFgo1LAzuYorQgWSMRgi6QFUZ0+WxbySBJiGfYLSNAfMA7VFdjJmGsQQ0TG6PIsEXTZqqsKyqE4eSS3PJKnyGfESDk0ophhSthlZZ5lf6bpKDVVy3/ygpE07sSdEUzBzHanHw55QrCQ/PJSvjPaIzj2Mdh6JW8GTez/e8hVh3bOTWug8RVIUda3J5saAfQbEwkno3giaDx9t+TXiwh+6W0yU1ScVlDBtiCATCzItMQnIe5+hIIyISCdZFTDAZOXgMOXAEv2RhU+IybjJt5xrtJiIREXe3gaETMdhjYtm7aCEhvZ5hwzDj2V2sieshIxiDbZ0J4XgfBxZO5snUq3GFVFblbWJ6qp+SmCuofvtD7EMDjM3MZJflKAFNgJXJK/nOzO9gCGiZeKsDZcCPVoBBUSB2VRbJk22oqkrniaMce/8tnEMDCLZ4PNHxpBUWU1FR8Tf+GJ96h4+Pj59pt2q1Wj8n4X/6+VAoxP79+1m0aNHfWIyKA1UYdv8UabCaJorZwhy6jKnsKK3EYzKwYGIbg3UZdPpjuUjcz13Cu5jjnHTEm5lI0yJ4BMx7Bfw1OWzOW8zBuWWcyswg1jnB+cePsaqnE0+BxJHJApI4RBadJJgdaKTT03NEAZcs4lXB/8l6VANESRAjKWhFkGVw9FoIt2eQV3kNxUvOoTEQ4fud/YTsPbx78k4SgxaG1MdQZTcTH/0QNU+L53sGpkzZgChqqfvdO1SPZDFpzS1YbdNIyX+W1gsuZMmSGjYIS9gycRsbzGHWSDo+UEI8uCKf//q4jZvjLehqdyDqOsi76BtnlJOamoeJjduHOvIq7Qc8XP5QORrd6bE1vbIcV0weywxXc2HtAa699lri4/+2w9x/Gs3NzQwPD3PRRRcRCAT+JbvZ/038/03kHggEqK2tJRgMfuls+P8OfX19BAIBCgoKAOitr0GOhDGnZaFr9OKN1pFi0BBscRBKU3DUTdBpGmJ69HTSMvPYuW4vK3P2cmCggvOOfIR0TgmKsAPkIDHW1bS2fIzd6CDDm0ZWfRebzr2W1epedEQYcM2gJsWB6FERtJORgyeQBJnSyqnoJ3R0t7bgmugiuqwCUfHyZ00B0bKPb3S9xsUlv+fKHX9g01wXy3pjKB0LoggR7s25gMtmpJO85xeE0kfxWsw4D1+C2Whg1tokPO8vI2MiwPaaGWT09fPInEvZb5tKmvXwGWLfHppAjhjRhwaYc+RJpMIgd1w4m4VNYfbE1TJQFGBGJI7MjnNADGGzxnDt1ZdgqXsR6bm5IIgEorL5aCSRF/0raZbTiDGInDM5hQeLEqjIisGi/+vtK4fDjPd2Mt7XjXNkmImhQTz2cYI+H+GAj0g4TCQiI4gCkkbL2N6tmK0xmGJiMMfEUpycytz8VGLml6DRG+gc93G0087+tjFe6E7gj6HFWDVhlqutrJTXM1toIF4YYU1MK7J0gubIJLZ3Z5ERNxe7wUl7VBdHSzowht1MbouivyKPDFVmyYlHGBeKaSpZzVGtFbN5jFliLH8O57CddH6wIpU1bXWcU13L8EYdnUVF3Cz/heaofbzu/Q4FBytJmbaOIxVuStp/wDOOhWy++ntcv6uM/zr0PGe/18HkDBOPXqkjMvwzIsaV3FLwIxYnHOcH0X9kd30Ww0116M0W4svnsHu8kfyYXM6PKWFH28cMO3cSZ+zEo1+GqM1C8G7mosH1bIsqY2PCAzwt/YmYHBfmlCCa/QqrPviQQ7Nno2ZmENcSx6sJInNy/cy8roPk2TOY+0I9U/UP8sLKK3iv9QIODQxxRdEfyb9kOZMGF3Lio/e41FxIXanKx4Mfs2v9Lm4puYWLbrgIecDH6FsdJHkjqO93Ube5j5Q12eRWzCK7fAadx49wYsN7qN3NuF1jrG9pJDotk4qKCkpKStBqtWg0GuLj48+QxqftVu12Oz09PQiCcIaIPo3SPtdb3TWAft8v0TZ/wIiQykbW0iplc7ColJb4TGa49uPdb+Got5RviDt5Q/oAJTlIR6IZb0IM0pBA9OsS/d3lfDB9DlvunI7TEkX5qWZ+vvEdUtO66Jjhp29OO/FGN/OA8bBAT1jkqFuDyxeF0ZtGtD+F2EgM1ogFvapFo4oExDA9kpt9ukGc0e3YokeZleolJbuJnt6f0/Kz91h884/5aHIOv+yN4nzpGXYfvZbY0J+wC3ejWXwl0vaX8Z5wYc/YRnzceaQvKqL6bT/KeCwBYy8xGolQVg6KXEsIgcgn66ZmOUJGrJG6Ac/p9rKCDocgYTDomDp1Kna7nYGBAWS5h3A4nrF2NzGpelRBASQEzzDSSD0tRdeS0j2O7pMEya8DPo3cTSbTf6T88t+F/yvIXaPR/ENyHxsbo7a29iuV4T+L1tZWLBbLGbOBzhPHsaWkYY7EYVYhUBZHZMCL6glT23mEiYxoPLo2LplyCTuaRwlEFGYmHeOVujsp6N+Eq1KHRmPFYMikvT2AoirEhGJI8QxhCvpZL2axXnkYd7cBEs+he2wfGkHzSdNGGRWBaZffhveDfo57d6PoDJSffR6bDn5A+7TL+F3rUzycdysLj+6gKWsYSRK59P0xFC9sW/INZFsc1yT2E9/7EbVFFoYG5hLsn8o595QwuGc1pQMODnTOILV5gLfKzmJr0gxs0Ud5xFuOMWJhR9CJHDJiDnUy+9BTuOcZeWjhVOY1hvgoqwUMMuePzUXvSkUQFVZfdBElmm40r50L7gG8McW8PJLLC56VjKsWlhTYuHtmFvPyYtF+UkYjh8P0NtTSVnWUnvoa3CND8In5kaLRomp1KBodqiSBKKFqtaBVEdTTHeM89gmEkREkVUGMhFFDwTPXMyohkZSCIkpy81lQkYttdRFbjjdzpC/AgeHpvBkqIUYrs0qt4XLlTYqkEUq0p5icUMuIlM3WgQziossochbQEt3G8eIO9GEXZe3RdM/IozjoYcHRX9Jvm0PzpNVsFX1km2SWaqKZ753Lc6ml3J2fwW0HT1DW2EtVbw4p88I8FHMPf069nPoT3yc3/SMaiw4TO3KCFTVXkpF1Bz9N+xFlBzZwbdNmfvlbH+98q4j32EBqdzV7Mu/l+JRneV/7XaoGtIx1QXD/NopmzKXdP8awrGVJwRX0DW6i1dWJNvAKUdHn4o2+mrBvF+XukzgCcZyb9AseMrzBCvNBspeO4jhlZO7hQwx3dHBg/jwqR2bQ5emnIcfIRYW1pD4US+w6I9959WWWzM3kyYJbebjqdpaO7GNx5nYW33sXnVuPou45QEnxAvYmd/Bw48O83fo2D8x+gJK7SgnV2xnf0Ee6P0Lo1TbqrTrSL84mb+Yccitn0Vl9jBPr30PubkH0TLC7v4f9+/YxrbycadOmfc7xzmg0kpaWRlpaGoqinJHwBwcHcTqdZ57neKuJxLa3MBx/koCi42P1HE5QQmNmDvuzp5LnbaL0yHHaHalcK27hJt16PKkqzckmgtF6tK0i1vf0NHnmsmPuDHZcNg1JlllVf5TF2iM4ckZIzu1GJ8mkRARaAiI7Ri1o7QXku4tJ82eSHEyiTzEypMo41QBDhAgBPrQoopFoBDJVOEcJUSpZ8Ek+1lv3sj1jKxemuImNP8HHf7ybs771Cx7Mn8RYWOb+ou/yRONDjIbWEh01lwHzO1i2h7Ev2Ep83HlYywuR3jiM7LAhp/QAEJeSjCCp2JUowoAItKEw22agY+x0NYotouLRC4iSBqvVitVqRRRF3B47glCIdwRiJ/nZt28f0dHR5Dn3YxZEtsZUkFdzgMx/0GHzPw1ZlgkEAv+fluTha0juX2Up3L9Lhv8/f6O1tZWCggIEQUBRZLpOHqd44VKkXgMRVSVpfgrj29tQNQp9/SfomSZjwMC8tHnctreeorgRJkJxzBgZQ1c8iUFjNUQgMeF83v3oKEOGIVL9qWQ213GicjEFkSZSdBN0D+bQXaRHGg4h6UqJBBvQCDIFpQUYfEZa2prxOPtInbsEJejiw+TZZHr6KPA08IvES7m49w3Wz3dx1TEDsVI0/sw4Ho2axp/OzsS49WKayi2MB7NwHbia2aszGO3/PpOb2+n0FmCoHuZEajEv5y3FYGnkN6EcYsOx7PR7CEd0WEI9zD78JONLYnh8Vg6T68Z5t6iXRElgTtcqBFUiOsrGTTdchnHPz5BqXiMUO4m35bN4dHAVDqJZW5HGtXOzyY47vU+nKgrddTWc2PYxg/U1KJEwiqRFNkehyyrAlpZJYnYOsfEJmEwyGo2T8fFuHI5BUtNiMZv0jIyMEw4rxMYmEQzp8Hkl3G6BsWEv4319hN1OQgEfrppqTh3aD6qCzmwhJjOHs7Lz+NE1K+jyimxqGOHDOgMvh6ZTpndzufwxq9XNJEjjXBXfhVfTzJbRAqzeKRS68jkV3cbxog7MQQ+eJiuNC/NYMtbGokM/oT3nPHpTltCjdVCuM3On1kqbezk/m5lPacFxrtx/BPeWCEcLJ3Oj8iadlv28LX+PtENlRKa/zkRFkLLWX/KXwEqeWXUtt6SU8ttDz3L5M81MmZ7Ao2c7SOz9Hu7YGzh38pPcG/0SFQl7OHEik/5jB0lOzSCYWcB6Zw0VifM5N7aXrV2HsTs/Ijl6OhPGxcjaLGJ8O7i0/0OesC3jo5gZPCw9Q1yhl+j0ANJ+WPXBB+yfNx81JY1IUyIvJcGibD/Tr+skpnwKk19r4Y+1P+LDiy7h1YEFHBsu50r3kxSWF7Jy/vc59MbrLGnR4Ji5lJ2W43xr77dYFLuIe+fcS8r3p+DfN4j/wAjprhCBF07REGcg45LTkXxO+Qy6a6qoWv8eoe4WDD4n1c4Jjh09SlFxMZWVlX8j+YqieIaIcnJycLvdHDt6lJj+XSRueQpdaIKDagV7hEq6YlPYWjyLqMg4k08eZWAkjuvEY9xkWI8jDWpSTEQMAoZqkejdFur0c1m/aBaHpkwhyTHKd9tfITm5ltjyPiRRxRES2eaW8E3kkmevIMkzCSkYj59h/MIwE9IARs0gKaJAogBBQUFFQRBC6FQ3JtmBgIxDsPK+v4h7lVzODsvcyjL0E2fxh4wXmZd3lNTzO9n2p4e4+OeP87OsBM5xnkV7x/MkRd5kXL4HoWg2uhM7GBs+iZqvImq1GCNOIj4bitIKQKItGjEMLikaj6gSJQg4VRWzXkPnuB+A6KCKVqeg+UwiYm9vO2azg5AnDyUMMxZPJjpFi91ux1q3nfGoErYP+1jitGOblIfH48FsNv+vk/yn5P6/aYP8VeBrR+5fBn+P3P+dMvxnYbfbcTgc5OfnAzDa1Ynf7SJ7WgXuJhcunYi96xRRLS6EJBFfh49u/Rjl1nLcAZUDbeNcXrSHQwPlXH50E+rqHKAJUFDVGXgm3kexCGiUMOmdfTw/52au9z5JwKVBjjmPas/pJgSqaAECRFSRqZfeiu/gECc8e1F0BuZduIYnN7zIQOkaXm7/Pb8u/h7zD+ykqtBFkmJm+X4PSjDC4wu+ydyCBFKOP4aSNkZQH4V3zxoS08LE5O8jZsNWQiEz3fsFJMnEryrWgmGEHwgCkwI5HPAF8ahgDg8x6/ATjC2N4YkZ2SQ1DrO1ZIAiQcvktktQxTClZVO5cGY6mleWI7gHaIiaxw8GV1Cv5nDB5Di+c3YxGbbTWc7hYJBjH39E3faPCbtdKFo9YlI6WdMqmDRtOgkJAqFwHR5PAx7PLvy+dnz+v9a3my3gdAo4nRIQQRBhwvHJmwJERYM1xkjptBy0mnQikUyczli6u2C4vYeg20Gwu5ORpjpObf6ItJJSVs6Yw003VHBkIMh7NUM82H4Zv9Gs5QoOc736KomCjzW2g6zQNLFttACrt5x8dy6N1mb2lvcS79KjyjY428ra5s2kHTlAY+laaswltJrGmCvF8mJwEm8aM7j74ji+fegEU5u7qO7LJGGeyn3+u3gm9Wqajz9Ads7r1JbWkTS4k7vaTzK9+A7ujP8R1x58k8UnTvCHZonnbs3lkPNZLK4qfp1xC0XxS/iz9CBbW1JxDPQijQ5TNH8Zx4fa6ZNiWFl8FQfa32PIdQKLtgeN8RzE6KsIezezxL6bfm86S5N/y2PaZ5hpbSD77GHsjRYW791LT0YGR2bNZMbgDJpc3dTnmlhV1kjsj2NI/jiOta+8zdzSHTw9506err2BsoEGLsj7FVOvvxG5XeHER++yRsikdbqRg8pB1mxcw6VZl3LjghtJmZOEd9cA8rEx0uwBPM8005dsJGNNNtnlM8iaVklPzQlObHiPQGcjtqQUumsDNNTXk5WdTWVlJVlZWX+XQPT2Fua3/ZI4TwunmMRmzqfbmML2yZU4tQayW+oY7Y/hbKmKm4wfMZEOJ1NMyBoB02ERw24b1UlzeX3tYk5lZrFk7AC/GX6A+NhWDIUReoMiGxw6xPEScsdnkObNA8VPjBhEEHzodQ0ERB8hYAQwqTqiFAMGVYdV1SJ+4rgYFmQmNH58Gh+ecJgco505Qht1gRxWyYX8ngD399zKY6qZBYU7MSzoYt8zj3HufT/mG4lW3kk5j+91vIybO9Clz0Go2oHU4CQ0Yxi9PhlJAkEF4RODKE3EdXpuM8cy4VJIFkScqowoCDgDEeIEATwyksaPKcZ2ZjyHh6vIyFTxDmahNYjEZZgQJZHUKBGzvQbXsl8h9k0gAHq9nuPHj6PRaM7kQ9hsNvR6Pf9pfCrLfx0WGv8K/q8h98+Wz/27ZfjPoru7G1EUyczMBKC/uQGNTo8tIRtJqaMrKoQ4HCHRKzEQ008gxYZT386y3GXsbBlFUVUqE6up6ltG1vgHuMosaDQWzOYimlv6CUkhEn0xZI734YqNpt0d4hxdFfYOM4H0MhitRaNJRA63oRUhMTkGW1QKXbW7cLl6sU6ZQXXVQT5OnUuhox29d4DmYBRrhqo4UuDm1i0Cer2J0cIidupSeblUIvXA+zRMMuEYnkJgtJAld9rwHb2ZOEeY7SdLSZ0Y5pZz7iSgEbnIUsdZY5dR7YvQL3kxB2RmH34S/2w9j1VkkdQ4xJ7iIaYJevJb16AKESoqZ7I8O4jmlQuImJJ4PLSaJzwryYnR8ObaSqamWwGIhELse3cdjds3oYRDqLYEclZcxIwlZ2EyjTA29jH2ib8wOtYNiEhSGqFgCr7hqfi7/WgGQ+gcEbRuGb07jCSflu1VQUXRCYRjJCIxAhGrACkafClhtLZmJP1eJE2A3HyRktI8BGEy3V1pdLepyGNj9HZ309dQiyBJZE+r5IeLliGeU8nrVUO8Uq3lz5G5XGBo43blafIEBxfYjnG21Mr64RJiAuUMe3Koj2lk88whModNfORNxpojcv6Rxxk2VdBQdClbJA9FRokrNCaWus7mZ9Pz2V9whKv2HsW3JcDx4hJukf9CtfUoH/u+R+7xWpRpb2G3+pjbdD8b4m/mwTU3suvINB449gp3/b6VspWZvFBaTVrXvbRm3MfS0hd5TfMA/SMj9J9KpG/XJoqnz6RXCfJesJXF2ZcStO+gaqwbMfwmCbalTJgvRg5VkeY/yOrejdybcC2LLE08KP2FhMluYjK9sB+SPxhkz6KFqGoWoYYUnkuOsCTVQ8Vlp0haOJ+UZ0/ysxd/zJ4LF/Gs5wJ+c7SQFaPbmZ0+zrn330Pn7irEnVvITp7GiQIXr3W/xkc9H3FTyU2sPnc1poUpeLb2otY5SBsJ4H6yib40M5lrssiaVkHm1On01tdwYv27eE/VkpqShqdP4N2uLuLi46moqKC4uBiNRoPgG0O3/7dY6t5gnHheUdfQLOVyrLCEOmsmuZ2NyN0mlkvH+JbpQybSBU6mmlAEAfMBEeVAElXps/jzLefgjTdw1fhb3B3cT3S8B0dE4IBXg3usmKyxuUxyFWARQiC6GdGcwieE8KgCsaqF+Eg0mf44DEENuqCIgpaI1gxaCzpRwCQK2LQCUaKAGlZRVQinSgwXOGiu3UO86uYG4Tj3+6fwK80gd/RezROxLSzN7qf+8Ens/b1cGJfED2yV3Cc8h1EZQ9KmEdKKaIYEwuFR9PpkQEWVTu+NA0ieLjBDo62AiRGVMiRakFFUlVBEoRSJQFBBVT2YrLkAuFwuInIDoGeiLZ2UQssZZzrNqQ0gajiQspSM2j3YEpOYNWsWsizjdDqZmJigt7eXxsZGzGbz5yod/hPJbbIs4/f7/1/k/lXjy6yUNBoNqqoSiUTo7Ow8I8Onp6f/G87w8+jp6SElJeWM6UV/Uz0pk4ro2dVNrCAgTNIyOSYbr9BFU+t+hnNFUGFR1iIe/KCHwngHrnAsU8ad6MtKGNTVQUQhPm4F23fWMmQYItObSUprP7srL2SZVIVGkPGqMzgptAGgSpmoweOEgdKVl+GvGuWE5wCKpCEqO59aVz9jOZP5XcvveCL/JhYe3MHJSW4SI2YWNvlQ/C5+l7qIi6elIO17iP48CX/ExviB6ylbZGOo/7tUtHtotk8msX2UpypX02PKoDjuQ24fu5zukEyjZgyT38LMYw+jLfbz/UVTKKofZ1fJEJWijpxTa1AFhemVlcyUD6F590+M2sq5c3gFR5VibpmXxi1Li89ku1dt38KRt19D9nvRpGQwe9VayirLGB19n/6BG/H7O5GkWMKhEhyNmXDIScKAnRR7PZpPFnqqwQBxcYhWK1JODJLRiNfnIxKJEGUwEHE6UXqcqA4H4if7rQB+o56JAhu+Qi2BwjD65B0kJrlJTNJjNEzH6SykoVohMDRMV1MDnVVHiIpP5KxFy7j+xoVsaPXw6lE9H4Qe5gJjB3crj5OtcXJp7AEcQivv9pWR4F9Ar7mfuth6Nsb3M7U1mvGZecx39rHw0M9onrSG1vi5dBnGmauN5clQHm/q0rhrTTx3Hj5BeVMnRwdzyV0wznd9t/No6q24DvyArCkvcqxcZVLHMzwyfJhdl/0XNybl8vN9T3PWxh7ya4389lKZSP/9BKKv5NKS33CN7UMusr7LoZOZ9J04SlR8Apqi6WwZr6XMVsEFsYVsat3J8MQ2Es09OHULEDUZCN5NXDD8MS3ufM5K+i3PSX+kwNZD9vIRxk5GcfaOnbTn5lFVUc7sgdk0uDpozY9lZfIhEn+WStyOEha/v5fKpMO8vepm3us8l/39TtZOPExZQRFrFvycqg8/QLP7KFMK53EwrYuHGx/m9ZbXuXv63cxbPQ/L0hDuj3tQT7lJHfTheKyR3kwLmRdlkVk2jYzSqfQ31lH10bu464+TmZGNkJTA1q1bqTp6iLVZDhKbXiQcltmkLuaYUMapzCx2ZZST3NNO/MlOVoqHucn8AfYMqE0xoagC5r0iyqEUDufO4Nk7VpIc3c/Nnj+Rp7ag2FRO+iW6R1PJHljKJFcZOiGIWxxjSNfImKASHZJIGg8RNzRCQn8XRv842rD3784xsqQlaInGYbVyyDoJIWEmGdpk8g0SmgGZtHErJdd8l+Fjj7GpxcdafS0/DxbxjMbN2W03Ekp4CGHKGK27tjPzyuuwR502kTGpdvSRVPr0WrTjYWT5tJtcRNChMTrQaE6rnZK7C9UInVEZeEUv2erpZzQUkQnJCkWqlrCqEvI7MX8Sube2thIbO4hBV0HYoyVt8l9tZbXNHyFnL2a7VyRzYoTimTNP/44knSHyvLw8QqEQExMT2O12WlpaCAaD/22lw1eJ/0fuXyN8upo7fvw44XD43yrDfxaqqtLd3c3UqVMBUGSZgZYmsmYvwN88gUeVyJqejXzIgxCrZbSjm85imUxdJiYpmgNt4yzPPsLxocksrNkJ56QBJwEIBicT8LYjWiQ0Spjk/iF2zZ/ML/0/xzeqA+sC+iYOICGiKj5ERHQ6yJm5mJE/HGfY2QIpmSxZuoRHdx0iy9VLlruRk8q3uGzoBIcKXHxrp4hG0jNUPoNGczL3xnSRN3SIepsFb/MsdDqV+LJ9RO9tRo3oGToWwhmdyoa02ehjDvAj5xL8MhxW7FgCcZS2PE+stYfbzp/L1AYHW4r7KBM15Jy6GFVQuPTyy4g++RhJp16mOnoZtw6uJqyN5qVrKpiZczpTdmJ0hA//+Ds8PR2ItnjmX3sTpTPK6B94gaoT96AofgRhBqP1eRi3D5DRV0+6z4dqNiNPKsA5cwba+QuxF5XQpTfRGQgzGorgiMg4IzLeYAhVkTEajZhEgRiNhE2rIVmEdK+HtPER0poaSK86RmRTM+LbHiKiwFhpIu5yHZGyTnSmQ1TMNaLVVDI4WETLcQ+yY4xj779F1fp3KV64jLcuX87WngjPHtBxVvgPrDa1clfocdL1Xm6M30G/eoq3eitJ9p9FU0wzJwpbsfp8RBpj0ZydypXH15HWd5SaKVexQ/JTaFK5XGNmnussfjg9k5kZVVx24BDDH2vpqyjgfvkPfBy/gIaee8g2bqR10nZGre0sOf4N3p31MLck3c+c3W9zyamd/OHxIM/clMsB6RVS3dW8nHknu20zeF28l20dKXhGRxEPbWfy/GU0jPQwrFpZXnw9JzrfYsDbgl7qw2xZjj/6asK+nRT5GsnoGeKq5Hu52riH2zXvkjTNRWyWBw5CWn8vuxYvIYdcgnUBnkkJclZGmGlLDpM4azGW55q54anHWLo4gz8XfZvn6q6jqO8Uqwt+wLTlV1O6bDmH33oNwy4tjmkL2B/bwL3H7qWkroT7Zt9HweUFWMYCuDb2oHZ7SenzMvHHBnpzoshanUX65CmklZTR31jHgTdexr1/G8sWTKNs/Cmia8aoUqeyU5hNjy2ZjyfNxDDqIHZPB6vVPdxiep+JLKhNMUJYxLxdQDmSwoFJM3jxu+cyU3+In8rfI05wMmIQ2DxhwDQwh4LRRWTLMCGN0aWtRwDinEGm9PSQ2dmEye8nIuqYsMbTmaBl2BbLcEw09iiVkDZCSBtGK6tE+RRS7CJZgxEK+3qY29OBI/4AtfGJDOZcyBRNIbFBhdG/tJH67e9yY+hW3ugKcbbuFJtDiVwTmcx6XxRRGX56Nx1n1lXXk2ix4hcNaAUXsgqyVovO/6lPI4QEA1K0A90nHd00kUFCHg1ukwUEL1nqaUKd8EdQVChBQjGr+IcdxKSkAnCqtZbc3FFC9jWIWpXkvNPzsTDRgTRYhe+8x2jp6GBGJMKkSZP+7vyq0+lISkoiKSkJVVU/V+nQ3d2NIAhn5PsvYlb0P+FTcv9/CXX/BgiCwBcpv5+YmABO79tUVlb+W2X4z2J8fByfz3emx29/azPhgB8h2oatR4PDoKCXZUJdbrwmDxGTmUH9KS5KvogjXRP4wgpT46t5rekqbhrYhbfYiiRFYTRm09U1SlgKk+SLIX28n7GEeMZ9Hip0pxgdiMWdlYw0FESjzSYSbkUjRCisqMBdO0LLcBWqqlKx/Hz21u+hO6WYh7pf5amsa6isP0JDjocYxcCiuiCq38OjaQtZXZaIevJ+2ovN+IMJjNeuYeZqI86OxygaDnCgZRoJE6P8cPmtCLoJrpciZIXS2O0LoJFNJDmPkOY6yq9uXsisVj8f53eRLQoUt15CRJBZddFqCobfQ3PqZXYYzuHbI5dTEKvhsesXkxR9ur/x8Z3bOPzaC6iKQv45F7Ds0ssYHXubqhP3oihB5MgCBj8OkX20laljY6gxMVgvWk1o4SLeEHScCEOn3kx/WIZBD3rBS5ZBR7JeQ4JOQ75Jj98dIRgME2814ZUVHBGZ3kCIo6EI/UEZVR8H0xaSPmsZZWY9xT4X01said34EQmvNyOFw9hzYplYZPz/sXfW0XHc597/zMwya7ViJkuWTLJsmdlxYocZ23AaTkNt0sBNmzTcMDXMzHHiOImZZVuWZUu2JIuZVss8M+8fSnJve7lN7837nvd7js7Rnl3NzOo38/s+z/chdFMbcSZvYeFxWUQi1RyozSbUOUjDpnU0rF9L8ax5vHv6yaztVnhxu5bPE49zgX4n16ovkKkb5deuz9gRKMcYnk1uMIe6pHrWzhxgQpeFdyfmMikWZsGOP3J4wsm0piyk2zjCAk0yr0bLeN6WzS2n2rhh/S4KaobZ0juJBXP2MclyMy847qBwewmJqtfZWRVl6uFf8Z7+Mh469yJu/raMe3e9xHVPHmH6icU8V3aI7LYb6cv5LUsmv8pb0q0Mpg3QeTCdrk3fUDhxMoPGGB9HDrIw+1SKg9vZ3HeYmPdjMhxzcZuWkdDmYQ6t44y+T9lmncpa1928ID5GWsoI+auGGdxtY+XatTSWTeTglEnM6plNna+V/QVGTrTuJuUGHWl1C8h7fRu/33MzNaet4tnYMh7cXcyywU0syPmE+VfejK91jD2ffYit3kF/VQk77Ae5YMMFLHAs4Oa5N5N8/gSsfSG8qztRByKkdwYYefQg4WIbuSfmkl0xhdOvvoSa5++mZuNepOxk6qzH0K7PYkP5NEZCBsw7+jhe2cm1+g8I5CU4mGGAuIjlK5HEnkw2llfxwa0LWSat4UHxGjRCgvqoxLbBPKZ0nsz8SCpj0jAd4hEQVVJHfMxobya7p4eoxkxLppmP5rhoyo7T4woT1o18Xx72lxAVDcZoMmrMTqLIRKpFJB7vovDQEGdu8TOnxc8O0xvsSZ7JbPPJGCIyo2t6SFl2J+e9tII/iZfQrfXjTQQRg7kkJTfS6RtDVVVcWomYqENgXOESBBUE0EgW4tEEccmEaPNjMFajqipGSxCvZ5w4DYKA83tyH/JHEYBpSDSleKENknPy8Pl8RCL7EQSF3v2FGNMSaLTjDphu/5sohiSaspeTXPMFpmTXf6kEThAETCYTJpOJ7Ozsv6h0GBgYoLm5GYPB8BcS/t86G/7/J9T9DKAoCkeOHPnRiispKfkfI3YYl+RFUSQrK4vR0VF2fPM1okbLnDkriB5oZjAZZG8MZSxKv3yESGEycSnO4sLFfLNvlDRLjGSjH5ffgj41hX77fhQlgtO5mG07G+g39JMbyCG1Y5DNU49huViLKKiEdfOpU5oAFVW0A+0kVBHHtMUMb+ugJbQP2eagavYczlr9GQ77GMf3f8a9VW/wy5aH+WJ+gJP3ChhNNtwFudRrXVxh6aTIvJ9DFjO+uoVY7UGUpBcp3B7Fm0hBd3iMtyctp9+QTqnzfc4cvIDWiEyf5CMpAWX1b7PzzHIcvjgb0g5j1kB193HExQTzFyxhUngLmk338pnuOG72nM6cDJHHL1qOUTeeDPnxs08wULMVbXIKJ994G+akIA2N5xEMNiFJC+laLTBhWz0zxsbQTpuG9dZb2Da5iveHPGz1hUkIAuUWPUfbTcy0mZhkNpCl1yL9lWzX3h7G4wlSWfCvZyRHFYXuSJxDoSj7A2H2+8M8G5MI503CcdUkphBnZdhH5Zef4nhnC8KrEYYqXfhXqBhyv6CyWkSaPY+G+kmMNQ/RWrubI7u2UbZgCR+ecyIfNIV4ebvIx1I1N6kfcrq6mjnWw0wXuviofyqO6DxarZ0czDpAb2o/kQPJ7D8qh/P2fkB6fz31k3/BN1KAyUYdV2mt1AdWcdfyFM4+XMuyfQdoXp2Mc6HIndHreCTnVwRrbiO39BVqp8oUdrzIrc01bDvtXi5Nyeb3m55lwWdHKKy38fBZWuL9dxC1nM0Zkx7iV70fsNL6OTtqx2vidRYr1kkz+NZbzyTzRE6eWMGapi/o82wjSd9J1LAU0Xoe8dBaZvp2MxpOYWX6H7lV/wFn6r8jfaaXWJ4GteYQed2drF+8hCKKiR2M8nxajCX5RmZMXofjgSosH4eZ8+oapuSvY/VJN/BW12K29oY5Yfg5ZuU7OfmOO2jfXcfeLz4iLZA53spW2cEpX53C6Tmnc2nVpTgvLSPR7MO3pgt8CVLb/Iz+aSeO9I9J9X/CTJONw6apbHYXsnHaQup1WTjqBjgxtpnrDe+TyAvRlGFETWgxrxWRa7L4ZtJMNtwxiVV8xP3Sp4QUga1+Labu5UwcXESmEKJT7KdbN4rD46OytYWs7j76nXZqShI8vlxD2CJii2lJjqSSErOSM2BAq0hoFAlJBRQFVU4QFmL4tHFGbH767K3EdH5GPAX4Rs9h0fxyduZ+TdY3XzO/doTXVmzCZHIyL7iQ3jo3zpVTMBfMZulgM98FJ9Ck9pMazMaS2oDHFCUa8CMBGiVBnHHyE1FAVJEkK+6mQSS9H9EUwWadidzaiN6eoH8wGUVRKdPrCEbGn5fRYByXVkKKgWhyI2m12NMy2FVTQ0pKD5KQjbfXQcrs4Hi9eDyMtuE94pPOZp07SN7oIJULF/xNe+9fVzr80KzI7XbT2tpKOBz+i0mC/9WRwaqqoijKTzrL/X8L/9eSeyQSYf/+/T/K8Lt37/5JZrr/d9DT00N6ejrd3d20tbWhiYRILyrBd9CHHiBPQugbfxIOt+5goFJCVEWmpEzh7vZ9lCd3cMhdzJSug+hmTSIhrwFAEmfgc39H3BoDQSC9d4Dt1aXcFvoTYZ8WTNUMjm1Gg4Qi+9AIIiazyIgvSuZggFjES2rlEvpHuqlPK+cXg5v4NGUpRW2H6E8eRhYVluxOIPsivFl5OkeXueDQfXRNMBINpTPWfAzVp0QRe7eR6g2w8UABJjnEB4WL0Np3c5V/DhFVpVb1Yo06mVz3KMJkeD/TiG6wlUBygjMDlUQSOnLzS1mYHUbz3u2st53IjUOnsiAlzBOXnIhOIxIOhXjrvruIdLaSUVnNSVffwMDga+zf/wRabQ79DSeS/uk+qnv70FZOw/zww3yQkc+r/W76WgcolKNcajNyfmkBGYbxvAdVVemJxvnG7aclFKMvFqcvGmcsLuOLRgnJOoy1R9ALIkZJwKXVkKbTkK7TkGvQUWbSc7TTigaVQCTK/nCML7v62RWRuNWQjP60S1hy4VUs725nytuvkvZAPZEkPX3H2dBX11BaEUYzdRaHDpYyemiUw9u30LRtE5VLj+bjC1bx9M4hbj14Bm9YVnFP/GEqdT2cm7yFdrmb9/vmkh5eTm1yHd9878W/VZFPVdjD/B1301B+No2OKrpNo8zTOHnVP4s78/LYm5PG5d9tJfhtmH1TK/iN8jRrXAuoG76OouG1UP4FY9YjzN99Fh/Nephfpf6OORs+4NTm9dz/pwCvXlfButBbZAQaeC7vGtYlzeJN4TbWtKYRHITYro2klE6hQepmQLWxrPQimnve5Yi/B03sXZxJK/BaTicRrSE5vINzej7i9aT5rHbM4CnpSSwZIfJXDTOwK4njv/ySgxWTaawoY07fXJp9XezLn8ipzm5SzvCSftQKjM9v48zH7mfxolzerLye95pOZkPXCI19v2XxxCWccffDHN66EdvqT8gXi6mfnOCd7nf4sudLrii/guNLj8dZVEFs1wDqltdI17+B6I3RHjuTtzXpJAxtjGkstLSZOC76LTfq30UzwUt7hhFVMWH+VkTZlcl3k2dQf0c6xwgf8zvpYwbiAmuGHUxuPYtZoSy6hR4OaJsxRGIUtLeS1d1Hr0PP1xUBepel4EikkxJOZa7PiOAbNzQ1GhFJJyEYRUBAK2ox6UwoikI4HEYbCGADKmJZKHuT6LPq2VtQTzTnad4+eDKT7SvImlFKt+9NTt/cya2//JAKw1xcIxo6N/UzoWAJc9vv5BN5Ep3iCJUxG7IAUb2MLCcgEcWshPCrSSio6OIxZDvo9VmMHNiL0Tmey2OzzURd/SSCADXGKSQUlYUaLf3E0YgQjitM0erwKxAN9uHMygVB4ODBOqZM6SYyfDz2NAM6hx9JktAc/gwh4iU29Tz27TxMsaoyeeLEn2Qv/utmRT/MGxgbG+PAgQMoioLD4fiLkcH/Vrz+Bw4Jh8OkpKT8JNf2v4WfJbn/Z7L88PAwBw4cICUl5ceM159ipvt/F/39/ZjNZnp7e5k1axafrv2EgsqZRI54UVTQpmkQDsVQ7RL+9lF6JJUcfQ6hqEjzUJCFk3bTOFrM6U01JJZOZzzj20Z///iM8fSYg+TQKAmNSEdYoFp3GH+biVBWOpr+MBptLvF4B6qQwFFQwYykiWwKvIwiaahcvJRX6nahOKZxlfcrzi+6mcrVn7CjPEL1gJk0nYZouo4vzYU8lDTMlLFdNFpN+A9NxWzxEzU9w4T9IsORTKxtXp6cfjpxSWCxsZXp3mXsDiWQZD3pnl2kqYe4+ZgFlHcH+DLXx3GSlchIEQadnXNXTEb7xkpqLYu5auhEZjv8XL2kAp1GxOvx8NY9dyAP9THlhNOZd9JxtLTcyKj7O0RhFe0v+6jc/Q0au53khx9i9eQZPNY9grtriGU6gUvCgxxbUUZ6ejrueIKPh7xs8ATY6gniTozfC0kaiWy9lky9lnKzFllIIIdjpCXbiCoKIVllOJ6gPhDh21ic4biMNhHHoMgUGbRMNhuYmWzndLPEGWoIR0kpX7kDfDUW4CZ7BsnX3M4pOpWV69aQ/947KO8n6Dk2BWVhAyVlO5g4aRYH68rxNQ1xYP1amrZv5oJTzuKsX07n3m/aOHXgLn5p2MfN6pPk6/q5UfsJnw5Nw5yYTatt3IvvS+1D3p9C3fJszt36Mv2WgzROOJuv9G7ma+08ImfwjnosN59o5Deb9lBW18vW4QoWztlHheV6nk+/k+JtuSjVr1AzPUZlw6W87biBu8+6kN+sL+XeXS/xq4cOUH5WBc/m15PbejNtubexsPwVPhJ/S3vKAF0H04kc3k9uUSnDZi0fx/exIO0kliXtZl1XA0Pu1WRYK3FrZyFpcogHv2apeyNdgUyWZjzMg9qXWWbcTfrsMeIDEuregxS1tbB+0RJyySPRmMXLKbuZW5zLbPsarHfk49w7g5TXNnP9rus55ayjeUq/khcPnMvmniOsKryeY2dewlnzHqNh/TfY13xOiaOCPaWj3N94P+80vcOfik6muPVFJG0jh5SpHImfzlRlKq6xgwTdNYymJvOx+jssJcN0ZRpRVRPm9SLq9lQ2TKmi5XY7K8XPmC0GORQW2TJYztT205gpR2mT+ujQNpPWP8Ds1naCYoIdk+J8WZVFejSXVNlEqgcS2gSJpAS9hl461U684gg6KYpZVNFKIIrjsW5FlTCJmaRSxCzzbGyyjc7OTrzpcUptFtJ35FMzOYfDGR/R0G8irJvIOZN/Qfa6+zmmTub5ma9wq3gZLbVuin9Riqgm8MQN2PV+9LKGEBCXVFRFRfD3AxARTITVCLqIQsRlQxR1jLR5sWXtRxQM6HSZ0LaWqKBhW041RBIsiom8rQW7TstoMM78uEAiSUd/cyPFs+bR2dmJVnsYQYzSs3cKFfOdDCnDiKKIbv/rJPIX0aLPxNK9AWtW9j9M+jYYDGRmZv44byAQCOB2uxkZGaG1tRWtVvsXw4V+SIj+l+T+U+VtPfvsszz77LN0dHQAUFFRwZ133vnjkJxIJMKNN97Iu++++xejXtPS0v6u8/4syf3fw7+U4cvLy8nKyvrxvf9pch8aGsLtdpOZmcmcOXOQoxF8Q4OkFhQjrYsQsWjQaDSIozEiuhAYLQzr2lmWvIzdneM5AqXOJjZ3LyHP9wX+/BEk0YTDMZOGhg7cOjeuqJXUgVZ2li9gqnAEgxRnWJpKi9CFCsiCBVCQVZFZp5yPvMNPb7gZxe6kuLiEda09lI20EAi66Y4ZmBVpw28KsfQLGXlMZOfi0ylMsaC2v8NgpgY5Zmfk4IlULPWgdR8mNehh86FMZK3A5vSp6JLXc4n7OIbkGIekEexxKyUHP2LfyROYGjSwOq2WMhVMzceiqAKXXHwm2o9PoUfK4eLhM6iwhrluxSQEFLweD2/+4TbU0UHm/fJSJi2sov7AL4hGe/G7z8bw/G5mdnUROfEEEtdez/l9Xva1DXBCspVj/MNYg36mzJxOrSxy5+Ee1o35Sagw2WzgnHQH0y1GJlkMpOnGpUclGkUeHqGvvYOxoWFKiaAqMhFJosPnY3BsCEYa0Pm7sMpu9MTQkEBFIIIen2BmQJ9G/GAxBdmTeKawBF9uJu+7g7wz6ufFOUezePnxnFu3i/wXn0P4NEzPqlSUoxopm7QbYfJC9u0sI9Q5yObXX8CVW8BjZ5/Pt+5Unt4k8o3mBe5RnmGptI/TkncwQ+7lvZ75pIeWs8dVy9fV/UxrdvDqzAKO7z3E7Jr7qa28hC1aAyUWlXMkM5X+o7ljYQpnNe1j+b5aGr9KIW0R/FP0Wu7Pu57w9lvJnfoCuysVylse5e6uej47/RYusKfz6NanWfBuA7lT07l/VYy0nt/iT7qc48sf4aau15htXU/NnhzcrU1Yk5wYp1Szfugg5UIJx0+cyMaWT+n378Oi6UQ0rUCwnUc8tJ7c2CFO7f6cP7jO4gtrNfdpX8CcGaMgbYj+3U6O/XoNTWUT2T+5gjmDc+jz9fNs/gTOSIsRnvQtrieOQfN+J/mvfc0Dmeto+OWNPNJdyGN7i9nRu5FjJnzCcUuvoXzRcuq+/gLXujX484zMt+yl9MgWOknlG86mU5/DzEQefwzXUzK8lnRnkJMr36Ir08SoYMK0SUTc4mLrlMl03mFkmfgN04UYe4MarO2ryBuag0btYb+uHV0iRmFzK9ZRD3VFMvuXZJMSz8GChC4Sx2MdZUzYyyTVzTwhQnY0jC0QQhePo5X/Ob6uAjGdSMgo4bFpGErxMWY+Qk/sWzqlbLKKTsYymENPTw8pVaXM2t1IZMYketI/5kDLDQxVF9N/cDbLDu7i6nmHAZADceKa8Yz1aEJCMah4JD8JBcSEiMFixTbWBEAEGz5/B7a4ipSbg6qqDHr15Mw+gMlcDtEIJuMonlYTBypLsEQU0mLQa4K4PO58zUaLNlcgtH+MrIkV7DtwgOzsfgS5gEQwk5zJNob2g2agDmmgjvCJL/F5WzcZPjdz58/+H9mrBUHAarVitVrJy8v7seTuhxbEjY2NWCwWnE4nnZ2dxONxQqEQJpPpPz/4fwHZ2dncf//9lJSUoKoqr732GieeeCL79u2joqKC66+/ni+//JIPPvgAu93O1VdfzSmnnMK2bdv+rvP+X0Pu/1KGnzNnzr+Kh/x1rfs/Cj9kyNfW1gJQXV2NVqulv6kRgJScfOLxPny5NiQhgTQmM2juR85LJaRpYG7eXHY2jJFpjWHSJnD6jehycxiR6pETIWzWKjo6OxjTjZEcTSa5Z5Q1s1eyXFlLIiIiG+bR6m8EVFCjiIKE2SSSkl1AU+Nq4rEgKWWzONDXRo8zh1vaP+CDrBOY1FJPW1YYq6xj2ogIcoAX9RM4J1+goms7/ck6Ql0laDUJxJRXyNxrxJsQMXQEeKTqbJDCLNV4yYtlsikUwyo7KexajSXHy/MTJmLvPoiSoTJzbB4hIc6c+Utw7H+G2HA7V8b/CatG4ekrjmO4rwev18ub9/0edWSABRdeTumccuoPnIcsR+hpOI6CNzdgC4epv+pK3jPYqWkeIN+o4/WiVMTmRnQGIz0TJnFK6zCt4RgTTXpuz0/j2GQbqToNit9PeM8eIrX76G9uJnbkCPLIyI9raAX2paXRUZZPWtoYk4QmqhlAEsZrh6OKGVljRtWbELQaSLgRox6MkRD0QqJXpH9XGiNCDktSZrBq8koOZ+Tw9liIS0oqmfHUq5x/pIGyxx9GWBul+5QUtAt2UjkbotOWUbvZyehgP6sfuIvyJSt4/5cncv+GXi5uu4bjbUe4R32APP0wN2g/4YPBKkyJuTQ6mtk3oZGBsSg6OYXMbJWFW+7nUPHptLGAAdMoCzTJvBKYwS356TSlJXHBhq341kYZrZrIneqDvJZ5Igdbf0uJ820ay7aR0buNk3deTMXKJ7k86TYu3PI68/fv5aEOHU9cXcB+31NY/Ut4KO8CqnwzeUK8CzNh5wABAABJREFUj28OpxMadRPe8i2TFy2ncbCPQcXMstLL6O5/k4NuN6LvfdLsixkzrSChzYfQOo4f+oomfyFL0x7mGe3TVOqaSKseIzEoouw9TF57GxsWLkZ1ppN6OJU3h/cybcJcFglbMJyqI+2Y05Gf/pKp9z3AC3MzWL/qTl7YP5W9W2Bn5zOcXJnJnGPPZJatCeP+lwgGdXworqBWKOKwPcpucRaeri8oCzZTPrsb/cQg7aIZ8yYRaXMSu6aV03cHLJA2UKYq1PpN5LWcTflYLi1CJ3t1zSQPjzC9o5sRU5i9JS4ME6uRkLCqIWLmQ8ynj9lKN06/H0lRUYGwQSRokhi1SUR1JhIaDYoIqiAjySr6qIzNqyW7N0pBt4eQM5t9xamM6boxio+TMrGStLST2LPnCM4JGcw5rOH92YfIyqzhw54krkyuILtvKzMaLCRMCjpBwD0qYgeC8vj2HhADRGUBkywRFiWyvC2EBBuSaiA2dAAA06TZ+Pr9yJYQksNHiutE5O9eQaNXGBmx0JuZyqzuKCpxmhIJ/DEZLZCGQL++F0GSMKVl0r7ua+bM7WCs+UTypzrRGEQkSUK3+xnkpCLihcvp+OBzcgxGyv+dLPl/NP5lyR3wY8nd6Ogo119/Pb29vRiNRjQaDUuXLmXatGl/V4/5448//i9e//GPf+TZZ59l586dZGdn89JLL/H222+zdOlSAF555RUmTpzIzp07mT37bzeAfpbk/texkOHhYerr60lNTaW8vPzfbGTwn/WX/ykQj8c5ePAgXq8Xp9OJRqP5MS4z3N6K1mAEvxFREDAVWAn5xxBk6Bk6zFjBuKU7OWUyz3Z3UprcR4cvlwn9R9BOKyORGI9zxeKlxKO9CPpxC981MsJBTQq/i9QTGtWBpRh1ZDta0U4i0YdWSJBXMY14h592XwOKRkt59RxeOXQQvb6AX/rWcVTuQxy15RXWV0aZ1wwao5nRzCLcRjtW7y6MjhFU1c7ggVPImeiFSBOZPi+7WsqQBZmalAq0yWs5x300A3KMTs0oyYqB3M51fHRpFfMGNXyY5eFYjY6QJxOjPoklRQLSm09yp3QDTeF03ju3CIfZyKCisOvzj1H7u5h52jmUzZ1K/YFzUVWB9t3LmPT2WiSLlQ1nncW76cW0uTK4OMPJRSY4fGAfY+nZPB/X0tw2yBKHmYeKM5huMaL4fAQ/+5S+NWuI7NsHioImIwNdWRmmk0/Gm57JoM1OYzBEoLOR+eGNnMcXSCh0W6dSb1pONOoiMhjF0DuAsaUZ3ZgbiBFMTcM/+SiU0hymzC+ne7CReOtmysb2kzxUQ2jdSyRRRH76Ujqmn8onKlyTUcyUx1/iyoa9lDz9OImvoOc8B4bJa1iwMov29jn07PVwaPN6Our2cOsvLqZ+Uin3rZU4WniWh+XHmSc1cI5rK3WREbRDC0mNutjt2sOaGb3Mr0+m7agCLtjxHq7RZg6UnctXOjeLdA6eTOTwjNbJracYuGldDYW7h9jqnso5M75kn72Vj7mDSbsLUaa/jdfqYcqus/ik7EF+7bqc2o1ruWb/R9xybxOfXDOd98wbKGxuobb4No4p+zNfqtez2x1g4HAKHRvWUjxpGgMmI58Ea1noPJXj0w7w5aHd9HvXk2rqxq9d+GOyXVn4MDldfVyVejXHWHZzq+4ttOkyRasG6NvrYuW3a2kvmsDuyilUj1Qz6h/libwszs52kNC/jfXOmVj3OpBe3sSKvVew9JzlvJx5BqsbF5I8sJ45mhkY5Bjb1Cq2iDNpSclgf0AgvS/B7e6HMBZ6yZo2jKAF/RYNug129kyfwOjtUWZotpKjqNSNplDWdB4lATiiGyahbSOnq5uCkVGa8iR2zShHK+gRpQAu7WGWCc2URbvQBBViWgGPXUtrupmAxUzIqEcVEihCHFmj8n15OIIqohWsaA2ZaPVpDIf9BCO1pA5qKW6Dubv3M7LgJu4PrmGOfBCnuZGCwksYGpQxhg9S4J7CgOMAvT2L6U22Mw2YdkSHMkVBQiA4EgAgJIyrVkGtn5G4SAYODoSizPHUEVKqMaoGhGArsk3FnjuP9s8OY82sBVXA6TwKad9iorLEDsMMkEROCwkMoDIWG99nS1WJmFFD95H9pBWWcKChkYzMblATjDTNZOYV6chyAmu0H+2RrwmveJg9YwEy+zrJnVb5s5m29i9L7jZu3Mg333zDH/7wB7q7u1myZAk6nY5ly5Zx1llncdJJJ/1d55JlmQ8++IBgMMicOXPYu3cv8Xic5cuX//iZsrIycnNz2bFjx/975P4DFEWhpaWFrq6ufyXD/zX+0bK8z+ejrq4Oo9HI3Llz+frrr0lLS/vRohvp7sCVm0+gxY8RSKpIIrHbjQr0DBxiYIIFAwYcWhfNgw1UljXS4s5hett+1LnlAIiiiZHh8Xh7ZsxKUniMMbMVfyxOoaGfUX8ablscDSJILoi3ElcFcmYuI9bipTdyhITFQXFJCbuGvFSMHGYwHiUYiCEkugnrI8yuk5EHQ2yYsoq5uRaSfTvoLjWj+tJJhFIw5r9FSocD8CG3h3mr4lgQY8zTeCiIZbMtnMCWcFLQ/jH64hhbk7SERg/iiovYO1cSU0XOOfdENF+eyTrj0bztns49VUHKJ0xAVVW2ffM1SmczJfMWU7VqOfUHzkdRErTtWsLkd9ZCaiprVq3ivfzJeK12/jwhixLPMHvr2/k2rYAvfDGmWyU+n5zPVKuRWEcHI4+8RmD1l6iJBMZZs7Dfeit1E6ew0Wxnrz/EoWAUBSjt7+TC5i85j2/Qi3FezT2Xl7NPoVdyEPvrBVcVUsbcTOxso/LwQarr9pO57lt6X9ByaGoV7sVn0HrG48TdzaiHvmBZ/3dMG3iK0a/epFxXRX3VpXxmzOXywiksfu4NLt6whoI/v4y30IL3ghDZOe+TmzeLvdsmEGjvY+0TD1E8ez7v/eJsfv9dD+d13MiF9lp+G3+CqaYjFKgjvNYzF1t0KbWuOtZV9TDliI3Xp+VzQm8Lc2oeZE/V5WxMBJli1HKN1sIG30ruWG7h2j37qT58iF2+YiYv7OP6yFXcl/d7KjbfRHb189RM91HZeDV/Nl7J02edypVJuTy6/TlOfaKW4pUlPDK1l5zWGxjJvJnFk57jmZb7mOo8Qv2uLPoa6jAnJeOcPJN1QweoSORwWtVk1h18haFQC3qxF4d95ffJdrswh3dyyuBnNHknsDL9fp7SPEWp1EnKDC9qroqyp4Ws7g42zl8EKU6Smqv5cGQ/RaWLWBFpJlC2n7SnT0V5exfaV7/l2pLvuGeeHmu4na9i1TyfOJEc+yjfOKpJ6Rrg+ugHaJ0jOBd60OhlLO3TkT72sb/CRuAOP5M0u3AmBA72FTGh+QzSokPUG4fRijEKWjqIywE68jPoyp9OQoiRo+tgOfspjvagyOCzaehINeC2G/BbBNCMOya6aAyjP4Lep6AJCWjCKmJCRdQAZpAtAYLmITwOIwlJwWAqwpcvsiO1jWk1s0jZ/AC/PvpBzmh7nhuyU3E43qG97VgKK4rJ9MY44qpFp4nR/n1c2BhX0CCSQMXT34+sCsS/jyOLugB9YYnFqXkc9Hi5xteAJ3YHAAZ/L9EJEhZLBZ0NG3Au3ITRWIwQDGPW9TPSaGFr8XRQVWb1x9luE8E3PjxmtiqhKTHT81U9lcefytb6/VTPaicyOp3U3HySMkx4PB6KBr5AsaSTmHgyX27YiVlVOGbG9H/YXv33QFVVCgoKsNvt3HbbbRx//PHU1NTw7bff0tXV9Tcf98CBA8yZM+fHgTSffPIJ5eXl1NXVodPpcDgcf/H5tLQ0BgYG/q7v8rMl9/9Mhv9r/CPJvaenh0OHDlFQUEBRURGCIDAyMkJGRsaPn/H095FSUESsN4CqQkqyEY1XIaaLE1djDDJMjiGH5uEgcUUlz3KIL4eP4mz3LiLZBYiiAYulgo72Afx6P0lRK8mj/ewprmaK0IZGVPBTRovahawmEJEAAQGV7EnTGHx2L9GYD0tJFcNKggFbOmcPb+Vb13xKOpvoyIhgimuYPGYEMcjb+kIutvmYGt1Hq0HDSEsVNscoin4D6f0SR0byMQcTrM+cjsa5g+N98xhVorSLYySJFrJ6t/DepTOoGFH5whXhLMlBVNHgSs0mvW8NwcF27ohfxSJzF6cddwEAWzdtJFC3E5MzheUXXcbhpmuIRgfobzmFive+QExJ4ctjVvJ28XQEs4V3y7JQ21rY5gvxfFIunnCCewvTOTvNgTI8zNADfySw+ksSDgspv7qM5qUreD0u8t1YgIhfISPqJ02nodJixNFUz9lH3mYVG9jimM6vy26hX5/6l/cQkKyV0Mdj6AQVbWYGe5JdbK6sRqeqVA33svhgHZN2bGH6w/fif9rMd7Pn033MSbRU30Cku4ZFLe9yjHszs3dsZoY0nY1V1/GJLpfzq5dx1oJlnP3MI+TeXkPfMS7kYw9QNe8QIxNW0LTNQeveXfQ3HeIPl1zFd8WFPL5BYJvhGZ6J30GR3svVKV/xxWglemUOTdEkDhQdZDQpgV5OpSg9zrxt97N/yoU0KBUMW9wslJIo8C3ipmku+pOcrKrZQfNXdlIXSTwUv44/FF9PdPet5FU8z56pChUtz3LdoQYmn3UXF9ld3L/1WaauaeHBww4eOsdMbPgeLPozuHzCbZw+sJYrFr7D+ro0gu5Rwlu/ZdKC5TQO9jAU9LF8wnUMjbxKTb+XobGPybXPY1BX+X2y3VrKwo1kt3dwWcZvOMW8nmt0HxN3aShcNcjgPicr1n9Ld0EhO6ZPZ5p7Gr69Pv6UbeLsokkQ/ADLialMKHHiGG7A7bHxqu5UtoiTOCRk0jdm5zb/n8lMaiFelkBrTGBsq8DZfS71idV4bhiiWHOE/pjIoY7pFBxZhVbuYo+xG2vCR1lDLyPWBEeKSkloNSRp+1kkrGFqrAkhpjKapKMhz8KIU0dCJ0JCJeRTGeiRaI7qaJH1DGtEwtoEIiKiUcIqmnEFLRQP2ZnTLFI40IwraYDiiRHCRWGOFA8TNPjQGbPYP6Of6l0zydr6MCfNOpvHe7/j8dKZNBwMI1uTsQ2M73PZKWFG+s2ogEaVEBGJKQlinh461ExcmtD3e2OCsRE9aZOnsK99Mzo1jk/IIxTqxDQSI3zSRILuOCFzgDTXCOnp18Cn9yNIKp5OI1uPnow9rGBKwBaDCj5QgEpRQ8A4hJyIEzSYMJsHEcU+hhrOYN5J46Wmgq+PzJGtxBbehkeVUFoOo83Jx/4/0GTsb4Esy4iiSDAYxGq1otFomDt3LnPnzv27jltaWkpdXR1er5cPP/yQ888/n02bNv1EV/1v42dJ7iMjI9TW1pKWlsbEiRP/S/LNPyLmLssyjY2NDA8PU1lZ+WOZhaqquN1uJk2a9ONrz0A/E+YuRKiNETWOX6/oU/ALQUSrHY+2jSmOKRzs9SOJkG3tIxDMwi4k8Cf1QkTAYimnp6+HYe0w9nAB9kEv68sWMlfZiRIXkKxz6Q1+33JWDSOJEskuExpFS1/veEJN/pRpfNC4F1FO55RQLTdMuIKiA9+xpzjOtDYVrcWGOz2fkNaIHNhHNCmOGLcz1nQUhdWHsXgtJAmd1Lc42JszjZiko9B8mKrR46iPqJgSdrJ712HKC7PLLhHwHCI7JiL0LUOU9Zx36lI0ry/iQd2VeKNG7jp9EoIo0tvby55P3kOnqpSfcDq9/S/g8Wwj5LuIrNe+RqvTsXbVKt4trkSyWHi9OA33gTr2as08rUumWKvhrUnZ5Oo0eN98k7GnnyGuFXhvlZnPZ07BmreA1oEgWXoNZSY9XZE4/bEEo3GZhcNdnHbkfY5jPbVFZ/JPWRfTL+iZaNJxSoqDEpOOgKzS7fNT2zuAW6unV9AzEIkD4BAEUgToSs3gvqXZSEuP4wTvEEdv38jK9d9h2LCWXeVT+WL5Kvqrfs8bcT9Lmt/gwv7PmFnzCxZoZvH5nFv4MO7gm1/dzPVn9VN9950kdkL/5UacuR8y/+RqajZPINjZw+qH76by2JN46/yj+c1nzZwQ/RP3K69yvLSZE527KYz5+Gx4EY6Ynd0pu/muso/4PhetK3M557vnOJKxks6c41hrGmaJJoVXQpO4OdNJ59EWLtywEe+3EdzVU7hbfYhnc86iseMmiv1v0li6lezunRy18SLyj32Gy2w3c/rODzm6eTN/fCTAizdNZlPiXYqam/hgwq+pcUziA+UO1vcZGW1x0rlxLSWTK+nTxvg4UsMi82mcMq2Zz/dvosu7lSRdO7JxGYL1XOLhDVhihzi+/xMOGSZycsbdPKF7khyGsE0NkZwbQ90tcPLn3WycvxhSk5jdNoe17v2caU1mQW8DcUXDapZSq52I0OGjw2niJst7zEyrYbBACyYZoTmd3KFr8Fha2Tv/UTK0w4QiEm1ti8lom8Wg2MNuQycpg0NMaB2mN93KoYoyJCnILM0+5sf2YkxEGU3ScjjFzLBTR0Ij4A8KHPJI7FA0dMVFUAScYjpGawaKNhWDJhVZl41P7yIqGukT9TQisVkJ8+oxYZxEKe2LsHTDBpZv2MTM0Q4OFExiNLcXQauhM7mEsuE9nB4VeTPmJ+I4FZPpE8JKHF1inBgtBhUlEkYATMZxQ9WvqKTrR9kTnEG+Oi7PK1KURK+Z3iwbFV2fMiwWICo2An2rSVIhaeFxtHx1EHveFpA1JDtXou+4kUBAT725An9mEisD441udnpCaEQBjaxSptdSf2QrybkFNLS0MmnSAHI0DaO26seOdNYDLyNLBuJTzuG9+kbs4QBHzTzmJ92nf0rIsowkSQSDwZ+0zl2n0/04XKyqqordu3fz+OOPc+aZZxKLxfB4PH/hvQ8ODv44Qvxvxc+S3FVVpays7D+U4f8aP3XMPRgMsm/fvh8tN4PB8ON7fr+feDz+Y0JGcMxNPBrBkZ6JLiYTSB/PshR9Mr6EG116GgFtPZPSJrG/2UeeI4qKHmcQtCUlBKNNKEoYnXYi3rEGIo4wqiDicHs4rEnikvghIgEtoqEA2b0DrWhCTgwiigkySiYS7/DTG2lDNprJLSjk0a4ucn3tOIPN7JPSmTHajndKkKktMomhIWqL5zEnS0d25ACD2UZkXyqqokdwfYKtwUEoMYJpMMrn8+ehMbZwXKiCOAqtSgCNYiKrfRMbz5zMJI/AF0lRztZYiKmQlpmFpfENWiJ23gpXckthO5kFx5FIJPj8zdfQjg0z6fhTkcy9dHc/i0F/BoGXd+L0eNj+q8t4P6echMXKC1k2+mr3UO/K4okQnOiy8kBxBpqREQbuuIPwzl3smZ/Ko3PNRAtuxBvzYw7WkWOqojsaR1Xh1FQ7S5Is5IZ8bNi8lhNYh3fyufwq9Ve4EzJPTsjk+GTb92N6VRp2tRPc3sVSv4HQ2HhvAr9BoM+poStVw5F0HSN2CVFRyYjCbksan6w8g9RjTuG6Q/uY/tXnzHriPg4XFPPqqlN5v+wiPi44j+M73+WK3vep3HIms2wn8n715dxmTmXW4y9xw6dvUXD/J/QtcZE45SAzFzTTV3gUnTvc7PvyU1Ia6nnxwqt4uMbDtQ0XsMsxgzviDzFJf4QsPLzUtxBLfAm7UnazZtYAc+udPLu8kEtqvsF2sJv6yRfypXaEpTonTyayuF+3nD+coOX677aRuWOAbZ4ZXKa+x7eubjYkbmZKbTbqtPfwm0aZtOFMPqx+mmsdv6DensPNe97hyrv3UXzdXF421lBy6Cbai+9i/oQ/84lyK32uXlp2ZdF3sA6L04V24jS+Gd3P1GAep1VfxZYDT9Eb6kUTf4eMpFUMm45G1uURD6xnQqSRnNYWLsm+g7PNX3KhYQ0hm568Y4YZqbNz1IZv6cnPZ3RGEr/21GL3+NkmlLON+dTa82nypnBp7uf8Oe0eOnKNjJhFos0mHN3nk5oRoKn6QUwGL6GQjr6mE3B0FdKkG6LX2EtWbz+uoIeBzGyGJk0kW9PDyepHFMndBLQSvdkGBlLMxHQCPQGBrV4d+yMShriEXrIQErUgRJHFECMMgDwA329DAhJJgpkMwc7UeBKZCS1jtlx2p05kTzTCrsxstp5/KQ/EzueExg3c0v8Co0olan4dI0UNxD2TyBoaz2zvCg5hNmcQDrcjan+YlCZgDo8TuMMyPrAlIIMcaqAmXEmRTsMQ0KtGyPM66cvI5oL9W/HEr0GHFo1nP5FCSMpeTutru8g+dit252yEvV9iMEcY2u1kTX4VikXL/CNhDjs1BEdlzKLADDSYJtro+qqOtMpq4pERdPp6hvafxOQl46O1BV8vtuaPaM89A5fWTHddLSani/K83J9sn/6p8Y8i97+GoihEo1GqqqrQarWsW7eOU089FYCmpia6urqYM2fO33WOnyW5p6am/re9cEmSiEajP8n5+/v7OXjwIDk5OUyYMOFfZUqOjo4C/EjuY309ANiS0lDoR+MyoCYUBL+MJzxAMFcLAkxwTeCjrUHy7KMMhtLJdfeiLclDlvcBEAyOJ+fZFBFUFYvPx6BqolTqIeIzEE01o1MFkByg9BFXIH3KbOI9foYjXSSSnKRmZNI8HGNV33r2movJGOxmxOEHASZ1ixCP85khn2pbhKqxWrr0MNpaitk+jMbUS3pAS/tgJmNaEx3WLAxJb7Jg+HT64gpxQSE9egSHfYj3ckuRBptwRSU0PUuJyzpOO3Ep0hsLeFi4lkxhlLNPPgWAbVu3Ej/SQGp+EfkzZ9Ddexkm0xQOvT7GnOYWmi+7lHed2QzanDxq1+BtPEhjTjGPuyNckJ7EPxWkET90iN5rryMqR3n0XCt7qk5mVFdFivdjkrzrcOtLmV46h/uLMphrNyF+3yvhzU8/4GThOxIpZRyT9isUVeBu1ccJLjuqqtK2b5gdn7YS9siYHCbyKpJx5VqwOvXozRoSiXFjoa97iIaeMZptTjZJcTolFV1cRRMSuKd0JrGJM7imp5ljP/2A+59+gCMFxTx18tl8UnQBH2Yez02tz3Py6HvM/W4db5Xewts5s7ho5ZncuHQFC+68lcR+6L9aR3rGB6SdvIKd35YyMtDFV/ffztWXXsOMnGLu/1agzvgUL8RvJUPn59cpX/F6/0wM8gLqkuvZMq2NKUfivDYlj1M6O5hV8zC7Z1zFOsXLLIOZOzR23gyt4HertNy8tY5Jh9rZGpzC4jm15Fhv5vG0e5i9NQ1l9vPsroxRWXc+L+bcw33HreRKSxqPb3+Wox/fTu4JU3igopXs9hsZS72R48of4raOF1iweDs7dmUQdI8g7NhA+bzF1A93MujzsSjv1+QHXmdbt4du92dkWyoZkaoRbOcSD67FSB/H9H5ErX4a63Km86jxGZJVL4bJcVIKxsgRRrFoohyRc3lbOpGmRBY7VSdnjNTwYMYaunL1dFr0+FpNUFtJbkU6IwteIaoL0hM046o9D0efmWaTH8U4RE5XD7ISYTCnAFXvZIbmIPPjteiEMANpempSHfgsGtpDAut8WjpCIhr0BEUFGZmwBmSNBUWbAZpkZNGGLDlQBAMIIMoBtIkBhEQX7bEOmqRuqnUxfj+0gZsOe+itvpwrA5/iVQxMcVzNN0Wz+cq4kJuPfEBR/DAxbS/R2DzMQ3XY0+24o27M2lTCkTYsWb0AhMIGJnvH48DOlKnEUJEBfayePmEZU7URhhSFI3KIkzOOpqF/JxY5zKA8mUioC0tvgI7Tijjy8W60uQ2IuhgWy0VIH15ONCbhHTSy7bgqUFVmuhPc6xxPCg4qKgsFDUNCD4l4jO5QjCmVI6iyFkJHkztpvBRPt+NRZK2FvtwTqW1uI8kzysQVq37WY1RlWUYQBEKh0E9Wg3/rrbeycuVKcnNz8fv9vP3222zcuJG1a9dit9u5+OKLueGGG37spHfNNdcwZ86cvyuZDn6m5P63LP5PIcsrisLhw4fp6+tjypQp/24TgdHRUURR/FFG8Qz0I0oa8I9796YsM7I7iqCC29fNmGE8azXLnEXbSAMrC7rp9LrI6TuCOvWHyXUSPp+IKqikxszYoz5aXbkYCZNs9DOgljKiDqOioPLPKkJaSRnudw+TkKMYUtI5kkiQkLTMlXvZnVRJUW8r3akJ0sMGHGiQnRKHDSlMU3uRrH4E2YG7eTkZpc0Y3LkkSbUc6CphU/Y0RKJMlAJkxFPYHk1gTFjJaHmboUkuJgck1rqCnGAQCPXqsFicJLV+zL5QCt9EJ/Bw6WF0thRGR0fZ8/Vq9NEISy+6nMHAa8AYHQ0nMH3HB3iWLeUDvZXGjHyu1sWxDQwyUjaZR7vHuCTDye35qYS3b2fwhhvxZtq5/gQNvgl34o+6SR68nbgcJi3jQu6v/CVTbX9pabe3t2Pr24SLfn5Xei8BRF7OtuFrGyYWSbDprWY668cwp6ssv6yE7NJkurq66O1tpuHgMMFgkEgk8hdhoaPSizknJYVoUgrv9Qb4TAoTFlRSvDIvpE3gsatv4/LuFk7/5F0ee+RudlTN5pmTzuaJyrt4fvR0nmy8lxuabmJa20Jemn0Lf9A6WPj4S/z6zT+Tf/daus5IQ7vwOxYeW0JtzVSih3v5+vEHmXHiabzxi2Vc//FhTuAJ/hy/l+naLi5K28JX7iCSMhtr3Ep90X78gzJrEmlUJoeZt/1+9sy8kt2yHo85xnkaKzne5fxxnomrzQ7mHNzH7lA+kxeN8Mf4Vdxcdg9ztt1CTtUz1FSqTD10K7eLF/HhqRfyS3MST257momf1/NQSwb3nSYSG7sPu/dU7in4FfPHqnhw1tN812TH32uhe/N3TJhcSY8U4rPoXpbozuDMWV18tns1PYHxmniT9Ri81jOQoztJhHdRGDuA0ihxYeEfuML0JsebdqEaIYSWt9UTOBTJZU8si7nmg7yb8QwDeSJtFgPeDgvBL1ykTiyBkzbj1kRp8yXhqD0Xy0iMRmscjcFDdmcvYZ1Ad24OSbpRTlTXUq604jVpaM8wMOxy0h8X+NynpcOtIS5oiAsyqqQnpi8joS8hri8lrisEUYtTiJKqSZCiFUjV6kgx2DFKOoajfjpDXg6HQvQqVvThPezxvMUvXQket4tMrnmOPy25nbO636Mwey9/erOFzyoLuWvyL/mVR2Kh/WNigg5LxIOiWpAEiVAojk4jo7EOI6giox4jBd4eEgYNDlMmQ1rw69z0Ci6StWFk0ygGOcZYlwnXMScxe/NN9EnT0Sg2vP3v4VBVXCdfQejtKK7ZaxGVVEb3HKRU10ffYTvbM6chZyRR5lfQqwI1w35Mkkg4oTDHZmTfga+wZuUyLEQxGXczcnghU5eXIIgCgrsNbcMHDE69BnRmdtXsQrXYOKai9O/ao//RkGWZeHw8HPdTNbEZGhril7/8Jf39/djtdqZMmcLatWs56qijAHj00UcRRZFTTz31L5rY/L34WZL734K/N6EuHA5TV1eHqqrMnTv3P2xgMDY2RlJS0o8evd89gsXpJNwbRg9Y8m3IP0i7kRHcohktWpCt+CIJXPomWsaymTzWQCI1CxAwGHIZHBghrAtjj5mwBvw0ZZZSLPQBIBvK6ZD7vk+mUxAEHXqtjCXJRXN3OwCZxRPY0NmEJm5iQbSJmwquIL92PbsmxJnRGgVBy1BOCTa9gD3SgjtFhyaYjhKzo0nZjLHVRELVoBuOs2neNCTLYZaGphEiThd+LIKRZE8Dr1VW4vYNIOkFUodm4gaWHbUAafM5PCdeQLHQy7HHnwbApg0b0I/0UThzNtY0Dc29nxAMLsbyyTYEjcS3E8rYWlrJbCXKQjmGNHU6lzX1cVyyjdvyU4nU1DD46+vpK0/l+mNUQnn3o/Wvwzr2HophIjfP/ifOyir8Nw3C/fv3s0B7iMHkal6WCnmzJJOMeBh3VGX1kwfwDAbJX6hl5vIyamtr+eSbOiKRCEajkbQ0B0lJMhqNiqIm8PtkRkai7N27l0hkfG2LUlJ4rKSE1vQ83pViDCsyKd4Eb6QW8+LVt/O7w7Usfu91qn9/E++uOJ41x5/KRQvf4rjDL/Hr7jeZsuU8Hsu+no8L53HBqRdyx4xZTH/oPsYO2ghd2s/Uqh76Mo6lc5uBPZ99QE7bEV4/9zJ++1UHZ/Xezr3adzlNXMuxSbtJDvgR5aWY4yZ2p9YQMA2iaUin+ygzy799hPrJF9CmTsVrGWW+5CTDN4+bJ1vwWGysqNnC4bU2char/Dl+HTdM/B3R2lvJK32BfZMamXjkVc6qOULRafdxveU3/HrH68w4VMe9Txh55oZydoY/oOJAM1srbuAE8yN8nriVmpQgvXVp9Dfsx57sIpJdzNfsY/poIafMupFdDY/Q6nMTGnuXfOcK+vQzEb9PttMbvdwZeZDpln5Cqh4JhTHVzLrEBNK1Izye8yDufJUOixZ/p4mhr5OxuJyknt6AKnbQPpZO7sFT0Pm9NNvCGLUhctsH8FlNdBTmMkHbykmJt3EJo/Sn69mVYWdIq2G1T8vBXg0hVUQRVGRdBlFjJTHDFOKGUvTxGOl9feR1D1HU10HWaBhzLIFGVZCVKHGCDBlH6c9TyD66iiunnk2KMYVmXxfX1o3Sk3w18sgT3Gkp4fmsDgp3PMUxs85idedq7lxwLr957o8UXdnDd7lTWcjHKFIclAShRAijZKTX00uKMwZmL45gGl0RhaKxVuKWZAQEetQ4I+YedkaWUC5JuAkTMfgp6nRwMOHhYs9eemKPgQqGkQP4JhrIME3nkOVtkpKGKCh8kJRt95OIiPibTKyeO5tQqp6lbXHeNEdIeFXMikqFqMFWZGDgkybk/FKmTvWhKBGE4PFkT7QDoN/+J1RzKu7CE2ntGcY81E/ygiV/V734/wRkWf5RAf6pZPmXXnrpP3zfYDDw9NNP8/TTT/8k5/sB/8+Q+98Tc/+hjj49PZ2ysrL/NIHP7/djs/3zfOKgexRzUjKxwRCiqpKcZiTaG0QVVCJykBElhkvromM0DEC6qZstPdNJD24h5gohinq02hza29vxaD0kRW2YvW56kysoVzoAkPXlDEfGJThFDaEVVFzpLlRPjNFgL6pOT3p2Dm95Q2SMuEmPtrNPl8W0sV4CxhBFPQkkn4+D9hyqU1XKE034bFrCAw4EMY4+6QhJdRn0hdMJYqHHnIbB/i3Th09iIK4giRIuzyGsGUEOGAS8cj/lsoDXnYdGtlJhHabbHeLbWDF359QiWtMZHBykrWY7hniMOaedQ2fXI0iSnd6tJhYdaaXlsktZm1mEToAbk/SUTZjEsfUdlBr1PFySQayhgYFrr2OoLI3rVkmEcn6P2fsuqvdbklJO5bX515OpN/yr9YHxh7Sn5QCZcgf3OU9jRZIFRyzKy63d7BlJMFISJDxNS1SSiNa2IipW9NNmYZUCpIr9uIQ+cumkgFYy6MdmU8jKFtDrc9BqC4hG8xnoV6jfvZt4fDvnZ2QQnlzFB8l6hhPjJH//hCqe+t0kHtn5Hed89B5H1dXwh3Mu5ZvJV/BN2mJePHA7v++5iyrPyTw/7RJuzi3n+D88yOVPPIjlzhH6fm0lPf0DXCecQM23xfQcbsD/+D08ctVNPL7HyM37z6LZXsRvlaeYZTlMmhLh7eGlmORF7EjdwdeVPSyrS+eNE4q44KsXaM47ke70o1lrHmKZlMrzwWlclWNlxGzi9C3fMfgN+OZN5EnlLv6p6BpC3ddTFHyTwxM2ktu5i1lrf8F7K5/nCtuvOLTzS86rX82vf1/PF7+dz1v27VQcuJGW0rtYWPYUrzX9HtfCbg7syCLoHkV1j5I1eQZ71VYGPV6W5N1CUewtvm3qo839NenGVsL6eUxOT6Xasg6tGGOXMo11zGG9XMJs9QA3pb2KLz9Bt1VDpMtA93dpiKqWnJWdKMYeOobzyK4/DiU2wm6rH6saILd1hDFXMr3FWVSL+5krf4ZsjNGbYaAh2cmmsIaNY1p8sjRO6NocIqbZRE3VqGIK2X0jzKgdpnh0L6peQ1yXQJZiyC4YTdUwIgggAOgRlCREuYickErGCx2sVi4h8/rzOHrK6bxdfSHnrLuQsGMpLWNreCszj1/31jBX1vBZeBAmZKBERH7T8TLu3N+OP+eih7jehqzKuBQX7bF2tEoI1eAlIzyVsViQNE8n6uQTUQXoHVXpy2vC6CtmvsNPjc9Bd3I7pxeuwLf/NcbEZCJqNu6hdVj74zSfcxyjH9Xjmvg5mpgNZzgTk9pMX5eNHmMKAxMqkDUiCwdiXJ0YLxb1irACDbXdmxG1OkImEybTWsbaZzN5yWQEQUAcakDb9BmRox5AFrTUd3QgGk1cOX3q37Q//09ClmVisRg6ne7HlrT/t+L/GXL/Wzz3f9nOtqKigszMzP/S3/l8vr8YKhAYc2NJcqJ6Y0QEAVESUXwxZK2CIoBP8JFpyKR9JIQoQKppBF80CYcSJerwoXhk3G4t0VgUj8FDTE3H4vbTnZ3C/Ngm4iERVcghEt2PBgFkD4gJkvMKifcHGY32kzCYSE5O5nC/lmmeJtolK7pAgLDOhyqoFA6CKMts02eSZFco9zTSJYJ3qBRzUjdyNI0MTQsH+jKoTS1FUGXSdAPkxTLZE0ugi5twddbQPzmNigCstSSYZtAS7FVIz05Fqn+bV6WTcRDkhMXjiSBbtmzB4B2hoHIGOluIkbY1yIlzKdm9jVBREV+JelpdmdxphuqKidzQ0sdoXObNily0Yx56briRQG4y166MEs55EJPnbRTfesrzr+aVWeej+Q/CN4ODg6TJvQgofGaZxvCQm2/GAqAasLlUUqJR8kI+9EEvSVo/OtsQcY2CR3UxIGTRJJbxpXbcgDOLKlM0AcqirSy39qON7CWReItkV4Ks7GKgmiMtYQa/Wc1JZjPxmfN432lBiStoAxouWHwcR5VX8dt3X+DJP93FF0uO5oPTzuPihW9y2b77OH3kA4q3NfDWkkd4KymDjrse5uaXnyT/7p20XZyGcfpnzFs1i50bSqC7ndX338mVV99ISWohD38HHdZ7eCJ6O/maXq60reH5/gUslhezI3UXa2b0sWxPGk+tKuPqbz/HFBzmcNE5rDb1sVKTycvRYq52mBk+RstF675Ds2mE2upq7uYJnsoepjZyEZPrUlCnfkDQOMzEr0/nrcUvcIP1ZG63ZHJ3zSuceN9m8n4xmz9l1ZHbdiNe1/WcW/YHruh+j1MWr2XzXheRMT3eul1MmDSNbtHHx/JOlsoncNaCQVbveBeLZgerkt/FoQ1Tr05mLbPYHs4hVzvAU6n3EykI02fTIncbaV+fQdSrJ3tpL5qMMH0D5aRvXERIHGW32YvT7yN7JMRwugtPSRKL1F1MUQ/jdmo4lGWgUW/ic6+O9n4NcQEUTTph63yiplmIajKTWoeo6h5CkHrpdwr05us4XJZCwGAerzIRNSiCiD6hYIrIpHmjFLgDTBSiSOY4Q6MDNNvTEOR07E9+x/pzgyxdfAHnFp/GC42vIKDwurqIS+1t5Lm7x/cQQxy+txNO0DQznLDi1oWQjDYgjMarQRAEDMYAATGGEi5gfv9hBFTMWXMJ23SoY3F8QpQJmgghRxP4SokNh/CcupjjP3uIYfkqDKoBYeQ7Yi4B15zL6f3wM7JdPWTl3Yn01vUkIiKeegtflc0hkGmi2C9zUKcSCKvYFYiIMD/DxDe124hakygqGURR3cTHjsWWKaIqCvqNdyE7i4lXnEHbvnqsQ/3oq+dh1Pw8mtb8R/hh3Ou/N1jm/yb8LMn9b425/3fIPRqNsn//fqLR6H+pjv5fIhAIUFBQ8M+v3aOk5BcidCWIa8dlJ9kXIy5GEa12ItIYqaZU+n0RXGYVjSijjZrQpacx5GtHVeNkZEwjFh0iboqhCiKWQIA+0coEtZuYX4NoTkHvjiGIVhKKj7ii4iyaRHwohCc+hGxPR3Ak4R+RKYkP0mzOJ324l1F7DFEVKJCdqOIY+wzpzBN8aE1BRNmOr6uapPwaTMO5GMT9hIdk9uSVotP3MDNSjIJKvxwDNDg9h/m8vJTRyDB6g4BxcAZBRWTJgioSn/yWj6OPcYa5Bn3R7/F4PLTV7cUUDjJ1xbH09r2KTpdK49dBFvb1sfUXv2BHQTkVXW1ccOJStnqCfDTs5eHiDHJ1GvqvuYVELMJNK1ViBQ+h864G3zpmFP2a52ac+x/eI6qq8tGRTpTMJCL9Onr0aSzwe5g/cID53ZvJFw7h0PT/h2usqCLdYjF7k+ayL72aXc4iXhOn8sroNKosJ3N8jo4FUgMx7xrGxj4iJ1embOIienvKObDpW86yWumfsYDPkrRYYiq7zKkcc9XtPLx3E8e/9SrVTQ387sJreGPW3Ww4MpPHmh/kuvXnkz/jAZ5zFPOby27kvhlbKHrmSXqOSoET9zJ9fg8Ha+cRaelk9cP3sOSiK3ni9Apu+ljkdOkh3pRvw6H1cE36Rp7vnslCeT47U2v4pnqAxbUuHj+qmKs370LXGGB/xcV8buhjpSaD5xOZ3CQa+dOxGq5ct5GMnd1sic7jKt7ls7QRvnLewLztLtRZLxKZkmDalnN4cuoTPLRqMReak3lu57NMe2MnD84t4Y9Lveh9D1I6dgLPlp7FLu9knpr+FJs6w7hbHAw0HiDJlYJcUMaXSi1HDYicX+ZHLx+mI+DgY/cM1tmOxiX18/vM54gXBBmyaxF79PRsTGNkwEbaNDfOFX0E+iuxr57KqNFPt9VP6oCHzNE4g5lpmNNCnCl/SZbQQ1+Wga3pNr6K6tnq0xJUBRAMhK3ziJgXAtlUtvdT4B5h2DFGd7KFdwqKCRrGQ3NSQkYrqyiCiCKCIggoIggqCBbocVnYNcGFyydzdG2QM6qq0SYrfPP5FtpLVZLWHma4tIPq1GqebXgWizaJwXiUTc4plISGQYBowIf0fVdKrdDHCCnMTPTQok8l25zMYPcgJr2OhDVEXBXp7S3knO43kR1pSAYHvXqBkKEfW7CYCkuM4ahEVOdjYbAApf41BFVFjlXjDTRhbhuj5uRKMr9pw1W+GilsITVSjClxiJ5+G2HBwOHcuQTSDZx2JMpL0XHFUQXmoyHu9JCIhBEKS0lLXYu3cxbOCRnU1taS4a2lqnsHvYsfxyCr7Go4RNho5sbqn2fTmr/G/yuz3GG80dD/E9BoNP/lhDq328327dvR6/X/bWJXFIVAIPCjLK+qKsHvPXcxKqMaxu0lxR8jooYQzVYiUoRUcyoD3gjJphhxRY8tlCBoMKAowwgCaDXjqoFBHX/ADeEwblkiSxwlHjYQExQ0KiD+kAsgYE/Pwt8/hKIkwGimXxovkalQR2iyFJPhHmDIoZAV0GMwWgk6XSQkCYvch9+iQQw5kSNJ6JNb0HRpUVUBjUflQHIRqrWFyaESRokQ0kSxqSNYrR52WTW0aYcojot4xrLQyFYKhDa2RovxKEZOKLOBILJv3z4M/jEcGVmkFKUxPLwaSVxBft0BxrIy2WFNYsiWxPU6BUVv4K72AWZajZyWYsf/4YdEamp49mQDY0VXEQs1I3k+pTT7gv+U2A8MjXLs11t5WOPArIYJSwY+qv0d7+w7jSv6/4DN2klzQTrfTpzEulk5rFuQzLqFKd//pLJhUTZbFk5k19xJjFYYqTBu4YbO61m79Whqt5zNXa1fovWM8oduH8d15fKW5iacE9eSk309sVgjdseTHH1MO8XZGpLXf8lV7XWUWzX4zBLJfoVfz1zMvbc9QJpexwsP3EbGl5/TWXg8Z1c9g0GKcd6eq/htyze4NBJXTp1H7SNPkrk5guEZG5LgZfrs9Win5BEz21n3/BMoe77ksRMLaJdTOUV6kr64ESMBrszdTvZAM3OHZpMezGV91TCE/Ty1sBCb/jBVdU9iiNj4Mj6AX5Z5TE3CFp3Lg8cspiM9E9e+dtbXz+X4oY1c6LuDL4qr6dx8A169mV2VFrQNV3BLaCsXnTSTcxffTG9GIRnbW3jgVZlyRyljhk+ZsfsB6qxlrMx7kCkZWvJn96OqMqGxUaJ7t7IkspXZ0sMEEh6ORG/lT8JNtNgKuSXtKc6f+Toj02KEAjrGVjup/XICYUVH+ok9SJZJiF+fQ09bEXX2MPbRUVL7+xlOdeLM93CF5k3O0H9CpGSMj6qc3Gx2cv2wjbV+HWP6KXhdVzOS8QSFnuUsO5xg4lAfh/NcvD93EhsmltFnT0MVdVhU0AGyRiKi1xDTiYhaEbteIlWnwaKVQBJISOP3o9sq8dYiKy80DiEENZzxy+Owu6fgdSTz1euv4zSMV9foRRETYbabJuMRxjPQdUeG0dsTKAIEEl3oojJZ0T7WE2amcyadnZ0kRoNoTB5Qk4l5opSONGHMW45qEGlu83HIcZg8ZFKzDzA8ksuIOkj6qnM5oeN9ergEvWoiPPg2qiTgPeo6Bnz7Mbg6ySq9Bs0HV5OIiLjr7KzJn8NgroOECOJIGE8kgVYFnwjHGY3s3vsZCYudGfNUVDyYxF8wZ0klC+ZUM2XgfXyp1TQpuXy69ht0I4Mk8ouQgwEURfl3ntqfD36IuVsslv/vuf9c8F/x3FVVpb29ndbWVkpLS8nJyflvL2AwGERV1R8Ngng0QiIWxWR3oJFVBNMP5B4nFPOhGE1EpSgZtgzqDkVxGYP4YklYfaNo0lKB8YEzkcg4aSd9/wAEVS0qAnZtkDAphBK+8e/AP0tb9tR0egZ2/fh7o3cETSJOaXyIdY4FuA410pChUjwQRVUUhpPSSTdEyVL68Zu1JMLfJ784+rEEtYxJSbi1SYS0RozmdooH5uCNSegwYB/ag5AukBwT6LDHWKqDxICKNcmK1PodnwtLmCB0UzJtPrIss39fLTq/h9KlpzE8shoQaNqlo7q7h52nnsK+3AlUdLWx9KSjeGfIw5FwjNVTCpCHhhh99DE6lpSyrjANj5CJc+R3WO1zeG3ulf/hej1Z28AT/gTOuMJVmz5kktpKkuAjyTTIrqnzCNn6UUUvihImFDJh0UfQ67MxmUpAlb8vJAJVkVHUKGGrmzGnnx6siGoaereRlcOvcOmOB+kUi3mx5Do+Uafw1jCsSFrGdSWnkB1aR0/v0yS7tnP0McdQu9fC9G8/pnzOIt5PSsIcVdhpSeGka+/khXUf8+t3X2FTWzNvXXgllyx4nXt2Xc/pnfdhCA7z+ZwLuVFxce2zL3PCDVcRfEDGc6PC1Mqv6XKeQO8uHS3r1pA8NMS1FZW80GzkJB7jjdgdlOpHuTR7O6/3xhHVKupkHVuntjDjkMxLVfmcd7iP6ppH2F19Dd8qoyzUOvmDxsqj/oXcf5TK9Zv3M7GxjfXR6Syc2cD98Ru5duofOWHrLeRUP0lNpUpl412c6+0i94wruc5wFTfv/4BZzTv57b0B3rtjEZ8Im5hRczMHJ/8Tx0/8Ew8feZQFS/Zjbg7R67dT055Bg30xu1LnkyX0cVnWV0TzwgzbtWj7dcR3mjnQnzn+HMwexRGfSWybgyMOwB4nfWCIkMHASFYSs8V9nK98Ssih0J5lYK3kZK3fgGdYQBWthOxLiZgWkjsGk7r8DDncHM5JpV6rQxeLo1dlzEqEoGggZNCRjJsC9QgF6hGy6CGFQVIZwiIomA0VJDmWkJJyEohmemMJPhrx8UK/BwWB1dVmrDsGuHPGZAwZGST6PIy4uujs7AQgEA/gtIi0ijm0RfcgKRJJDcMYk+OMpmegqnGKh93EBYnP9XaujZXSIrcgRzQ49FFah4o4pqsGJA267Fl4s80kBsIEVRMTzUEGNKMoso78gEqw7VMkVUUTWchYsA1rcx91i4vJ2+lDP+VjpKCFNLcLE2209SchJKA5dxFyoYWZQ3E+i0XRCGBTBIyCwOQCic8ae9BXTAH1a/w9c5h71MzxfWT/q2gCfUinvsbM5Alsfv0t3GYbi5PtNDY2kkgk/mLM6s9R+v6Xsvz/7fhZeu7/CFk+FotRW1tLd3c31dXV5Obm/k3nCQaDwD9nUsZC4y0edUYzWlVFso6XvakRmUg8QNgACJBmSaPfG8EsDjMWsZEc8WMvymZc7IJwWAMCJMl6tHKMQasLDQmMuhiylIxPDCKr4yNIQYcogtnpxDc6AAjYU1M5MDaK0zNMihSk2ZiN3TNK0BgjbURG8fnos6aSbJUpDbcRNoqEQ1ZETRiDyYJL08WQ20qbfbw0z6YZJieWhj8hIsY02EZaac/PwvK9RJeeGO+eVFJagHxkHevikzlWvx+yZ9LR0UF8eAAlEadk1lyGh75AI01HV9NFb9Y8DjiS6bcnc4EaRdXrea53lOOSbUyyGHA//QyqXstd0/uIOS/EOfYqgmTkjUX3oPl3Mm1lReGy9Tt5OCKydO92Ptp1P8eynoBgQREEeqb6iST3o4SnEBmuJh43Y7F4AJVotI9A4AChUCuRUA+hQAs+/z78/joikS5UBWK+TEJjGXj1Go6UqWycm8nIBA039vyGPZuO4Za2r6n3BDiusY+H/dWkln5ITva1RCIbmDzlQ+bNNWHauZnLWvZQatUQNEoYQyJnrjqLDTfcwsL6vfzuvttxe2TuXfwyNdZJnDjyPGdsepwrUiw8ERV58YkXMIkuUv4QJezWk53zPiVLM4imZjN6YC/aQzu5e5EDg07LaYm7qY+Or8/5GduZMLKXSvdkJror2DPRw5jGzXslGQRLQszZ8RDWOGyN+mhLRLlRNLHIu4T7F1Wyb8Ikslu72bx1Ahk+N6+2XctnVUbad99KwF3M3slJBMVXWbz+Nl4/YyLPzT6Xt6efhBCOcvZt67lWPIbOjBGKmm5matcOZFWhqr+LApuPaHo2BzJn0ZuUzfWpL3DCrI8YmpIgGDIgfaejYVcuDZ25aDNi5BZMRNO2mIZAEh3WBKkDAxjDYfy5Jua79nKj+AJ5KY1smmrm1kwnlwaSeM9rZFhbjtd1DVHHvVSMVFE6HKPP6WBbWRG9SS4MxJGQiem0GHReZgpbuVL5M0+pf+LB0Btc4N7P7AGFCZ6JFAqnUpT+GzIzL0eSrHT3PEb9gZMJBfaRq9dyfVYyL00Yb0ctIvD+LDPr9w6SXmrDmMjDPualYfd4P4uoEsUs6YmoWg7oJApthVgaWjBnKfTnOBAVA8VDAXbZp6BaShlrHUMrSgwUtaEV4FBHGSe2bUOTPRsMBg51D5MwtlKgJsgr3EfPQBEBycvEo87huI736OIidKqJ0PCboArULLmBoLAFrX2Q/Irb0H9xPeExLSMHnGzMrqLLlcSATYO1LUAwoRBXwSOqnCDq2NH4GbLOwLQFAqrgJ9lxESa7DiE4jH7n48Sn/gIleQKNbe0wPACFEyjLSGfevHnMmDGDpKQkRkdH2b17N9u3b+fQoUMMDg4Si/2r6Q7/K/iB3P+RDWz+p/Cz9dyF75uQ/FchSRKKoqAoyr8qt/B6vezbtw+bzcbcuXPRarV/83X9UCah149L4NHQONlL6BCFBJJtPMNSjSYIR/yEk8cNDqtkZcDrZobTTSBuxuYbRXDm/HD1hEIyqlbFmDBhjIXps6eSghdBAEWbhhsfCTWOoCoIgoTZpEeQBfz+UQS9AavNTms4QfLYMA7FTbfkwBgcI6INk+5RUTwe2ozJiFaJrEQPfgEC3iwMtgHUSBFOzRf0jKTR6shCL4xSlEhFRGQs8f31+7vYmJ+OJ+rBqhWJBcsRZR3VE1Kp360joOpZmKsFUcOhQ4cwxSM4s3ORzAGCoSYGB05DFzVxaFIhB9NM2AM+jlu+gK9GfXRH4zxXmk2svZ3AF1+w9ZQSIpkLkcP1COH9XFh5L9km+7+5HrKi8It1O9hudPDrz1/nCuNXmMyjrMtfyViHgKiqBIQlpBkGCMpb0GkdxIZsZAmDpMfTsUV1CL4+hLD7n9dYMRHFSsTkYsRkp9ekx+two9d70cpG/L1VxJKa8Vea0fiTOLXrOS7Z+BhP5f+GV4WlfD0W4LrMEzmjYgU9XfcSjz/HihXL2L3byJwNnzNh8UreS9Lg8sncXTSFvb/7Izc88xAP/fEW7vnV9Xyw7Dl8m25i5djbaL4K4TruDv446Md33+P8+oE7ybqrke7fukhKf5cpx5zL/m8kxpoOYjEaeOuiK7ny/UOcO/x7XuOPTNZ0cFbqDt4fUhGoQqNo2V9Sx5RWWJPlYpnWw9ytD7Jz3g3sQSCOwuVaEybPYh6creFavYlZB2qo2ZDBtIVjvNd8PWdNf4Cj6m8kN/wyDRN3UXxkAxWfXsI7Jz/HNeaVtJpc3LbjFeb/cTWZF8zjj+m7ccWfpGrYxx/yL+fz6FxWda/jhqLXCOXFGTZriPWbCXVY8Ucl3B1JYFDJzCrGF9FxwGTCZAiR1j+AO9mJlCdzkvwtGVIPNcn5vGdP5cNYEh0+P6pgIGxZRMy0iMJRAe2oQkeKjt3FBejiMbRCgjhawjotpRxhutJEWXAIZUBgdNhGPJ7GQdJQRBFVlEBVkeQEMIQiuTGnpjG3/ELS0y7C53+MpuYrqSh/F6Mxnzk2E2VGHYGEzGA4wT1ykD/YzQgIpA+4aXHZ0Fl0xNQYetGBIMvsTLiZ61qCyfcpUlKYEcMYhqBMSmCYByacT5U2hZHhAbTDoJbWoargPODDHAtiKDmGRHkSQ1uGaEuKMM3hJWTtwNcwHVN8AGPHe8iqFl14KWOhViyHu9m7sIwZdW5Sqj/DEEzDdbAdveTmwGgapkiElrylyCU2HJ4YNYEIVgRkIITKinwD69Y1klQ5jUTiUwK9S1l0/LTx/XDzPSBqiM69EVVVWbNxE8O2JFalOhBFEUEQsFgsWCwWcnNz/2KmemdnJw0NDVit1h+9ervd/r9SNifL8k/awOZ/Ez9bcv/vQqMZ/yo/NP6HcRm+q6uL5uZmiouLyc/P/7tloB/I/Yd2tD947pI8bjBIZi2qrKJGFUIRH3HNuMx+6EAz4YSLJEsET8SIM+xDNYvfX7sNbyCMrJExx7To4zG6LS5S1bHx76HPxBMf/x01jiiAyWJGCcTxxz0oOgMWi4UhRUNJYAw57kWJJ0hIARAg1TP+px16J1GLHpd3GD9aIu58NNZB4kNpGMQAcV8KTQU5iMZe8mJpyCh4iaFDxMIgB+yFDI51kiGL+IJJiLKZ5GgL78iTsROgvLhofJJfczOmoI/0yfOpr38T0BFpNxGxlqE4Bmh3FXNCexOmFbN442AH8+wmJlkMDD34KmpyEk8V9eM2LsDWfxsO23SuKl3x767HtZt2s93o4LbPXuRC25fE9Tq2zapElfcyOrAIIlA8+DWRogVkNS0ldbAWJ7UoAsgp6aiZlShlJ5DQJlG3boBoMIaQ6uPTsWR2jOXT73H9xfmcgpdMbZzJyScxxenGaviYpooxJH8m57c9ykWdT/NPkx/iPkXlk1Ed9+Y/RIHzGzo776Nyeit9fcfR+O3n3DBnAS/ZXVjCMhvs6bTcfA9PvfE09zx+L/ddeBXbVzxGcNPvOHX4E5QvJR468Q5u6fPg+80fuP3Zh8i9bxedN2dgzH6TGcf+gt1fa+iur0X75p/58y+v4OoPDvHLwdt5RX2IGZojnJm2iw+GQFWrEFWR/UW1yO0qG4VU5s70MHvbw9TMvYH9qkhckPmlxorRM58/TdFyjdbM/H0bOfidldIlOj4+fANnTbmX6sOXUxR2wMS1RPTNFHx4Gi+f+Bq32edzs17HK2N/YoL/Q0pjOn6Vkcm56UaW9hzhjeQP8M2RGTZKGFo0aAclvHlaBg7bCLv1OJJzCOmtNNnM2Lw+0voGGElJwpXj4WTlOyRDkI+1s9hlyKBPM0CPrEHRmgjaT8GoTqF4LMyQaKIpKxlNIoFBjSGoCrJGpJxDVEaP4OoeJTKURFhwsNs6jQGzjZESByGTGafNhtNkxCRJ6ASBYCxK1O1G7O2irLeNT71ekqdUUh49A6vlYZqaHiQUOo+xsTEmls9khy+EVlYZ0Amsi8YoAaz+AIosYNfasen1hNVUUqMHaYn7qKhVsWd56M4cJ5SM4QBRtHySuoxLOxpISBJH0saYYIwx7E3llKbtaDKmIThSOdTbjVYKYNO4yS/azYHuiSioTJ6ziKP3XM0h4S7sqoHQyCtYZIEN1Vex0v8ZojZM4eSnMPz5FLxuA8EDVuqyy6lzptKTrie3ZhSfVsQdlbGKAkcpWupbPkfR6ZlQ5SUqQ3HpVWh0ElLXNrSNHxFZ8RAYk6ipPwBjoziXrsSqRv9Nkv7rmerRaJSxsTHcbjcNDQ3IsvwXEr7RaPwfkfD/v+f+M8QPtemyLKPVakkkEhw8eJCxsTGqqqp+vIn+XvzQwOSvPXeUcY9dY9agRse93ZgcIS6Nk3tWejHgwSCOMRI3kRdzI38f1tFobITDYeKaOJqIhCaewG+0kqJ6xw+tTScY/j7mrkYRRQWj1YoSThCW/SR0EmaLhbGQFkfcy5DWijkcIKwfvw5H3ACE6RRt6LUyGk0UUTYS9WViz9uF3OsYP3YI+iwuFGMLWbE0fETHDY6wG6M9zqCqMmqJUC5CPCGg12sR+mrZLkxljtiIkL2CwcFBon4v2mAAHxJp0mGMphloGgfxWedxxD5M0GBkZbqT7kiMGl+YR0sykb1egl9/zf5VJagp09GEahAT/VyetxxZDiNJxn+1Fs/UNbJab+Oq1W9zgW0NYZON/TMdIPWTl3MOGu3reGr1GPtdlPfug8AQHbGZ7HBl0VncSL9tIScVLCdDJ3Boxz5Gk4fYbxV4f2gpOlFhboaXs1JjpOm0CCONBAZbcMdF6hP5fNhn553+dIo1v2BFQZyKpLdpmOpFP2rn4aZLOFOziNurbuOMw71cn7WAcyZOoq3tt6SkvMiChRewdctWrpxQxrs5FfSG4wypBs68+Abe+PgV7njhcZ70+2g54wG+WCdz3MhHrPlcxzOn/I5fd7u57Vc38UftE+Q/sJmOm7Iw5r1OyaxVtNQU0LZ3N4Io8swvLue6jw5xfu/NvKR7hDnaFs5IreHjURGBSkRVYF/BXpQOFZRUYnM1zNr2J3bP/TWHVAdxk4fTNQ70/lk8MXEPce0qFu1eQ/M6EwWLs/ig8TdcMPEPBDvPo2JfEuq0d4nqfJR9djKP5ixBSvkSyZVga6KSF6PHsqpnD/GyvZRU1zGoAeNhCcGvYaxCZWTIxcgaJxp7Omqukx6ziST3GMlDIXwuO5MdhzhX/Qy3XcOf4sew3RQgaDxMQkxQHU5QLZey03gmUb+V1hQH+22pGOMRJFUmodGQrTYzLXSYjO5hwqMpdNvzqLFVMVbiIkVvxRFXSVcEUrw+7CEoNhiY6DRTmWNHI/5AKLkk1Kls7O5j72ef0tjaxvCCJZwbPw6v9x26uhYwPDyCJ6OIhKpFkmGqX2WbJkoJYAj7iQtxxuJjHJVSwetqDhY+x6l3MnHNQayzohzKTUYfdJHVP8xn5jRMoRjRnl60boWDU7Zymkmk73MXacEj6GdegTDDRcfXEQasHioyB0iYexkYnIVBCZDX+jJ92lxMgSkM+fdgrR9k8/LpLGrqxLl4LVa1HPvqZxCFOHvHCnHFQrQWH4Op0ErCE6XLHyUXiZgg4FdUTk3TU7ezgex5M4gLb5Nwn03evHxIRNF/9zsSmTOJTzqTeDzOlq1b6UzN4veTSmmvr/sveeB6vZ709HTS09PHk5SDQUZHRxkeHubIkSPodLofiT4pKenvUl//I8iyTDgc/v+e+z8S/11ZXhAERFFElmX8fj91dXXo9Xrmzp37IxH/FIhGo2g0mh+Niej3nrsYH/9Xai3/TO4JJUpMHCf31NQ8xsl9lFCiAGOiH8U4/jmNJolwOExMjCGqGjSxGH69mQy5AwBVTCaiDI5fgJoAVcZoT0INJ4jKYRTJgGIwooRVnDEfgzYXpnCQiG783E6NFQgzarAyAT8RvYQmbiERcqI1jSJ2mcEK0bgOn86CQT9Cpm8CPlVGEjQYAgOIDrAnVHq0Ktk6kaCgYrSZoL+eRvkCrpb2oKZNpmN3Lbrv4/IVs2cyOPoYicR5GMIB3M4x2pwp2AI+5syZyfMjPoyiwNFOK4F33kaVZV4q6CJovgnj4P3YzcVk+d9CVS/+V+vQ7PbwxFiUZfV7uFL/FYpWpK7KjqQNk5p6Ev39L6NJTCce3kOh2kGo6Gi6Zl/GvZtWE07fwFREqhJf4Gn9FA+gWDUMJJXw9oFfMTujnvMmvoNBM/49xIQJIxPRSeWkWeZxueYI8f6n2Tys5fXEUTzTMoEULuT0Ei+T015ge1UKmZ1NrNl8LHeWP8qDajlbrUYeKnkVX88fcLufY8WKX7BuXTPnhIKsr5jNTimKM6BwymkX84YjiWvfeZnX/V46Lv0T69ZewzHud/nycyMvnHITl7YPc8fF1/FHSUP+Q+tovyEHV+GXWJedTe13BbTu3gkIPHn+5Vz/8WEu7rqBN7if6bouTkneCW4BmIaASG3+btROENQ0Yoslqjc8Qs3c62gNpZAwjnGCNgm9fwZ/KqpF4UQW7/mMzvUGYotKeaPxVq4pu4MdIyewYLtIcfqLSGIIY/cnbFJm8kpiGcv1O/hd3mMMZWhJSCK9AyLPCnpKU2UW6vX0fZhL1JiGXJBCQKfDNepGE4viNesxqQqqCA6TzBfKpfyRI2iSdwESIdtiLhsYwCuU8EnmYobsTrSJOOL3z1uSZoRZ0VpyewYIj6ZyyJrPZu0s9CkGJHeQgT6RhBrETRCLECVJDKEXEkTQs6bZR0QRcZl1XL0oj1OmpSMIAhpBYHluFq4F81i3bh2vDLiZll5ANlGys5PweLz4JB2EEyQFFEpjcT5KNxCXfSg6lXbreCfJnNgAHr2OjkQbp5iPwim8x1CBSFxIkDbajTYu82J2NjM7DqFqtLQ5PWSbwxgSUaZu6UeTNRM1LZvGww0Ioh69rYOUwu3s7pqALmGicFIGsxpfoUV+Gr0ioQ6+RcIksbfgQk5IewQhJFFWfDmmrWfRN2jFcjDOrpzZbLImEc0y4tg7gsuspzMQJUkrMS0u0Nm5GnQGXAVNJCJ2psy5DADdnj8jejsJHf8cCCLrd2xDjkTIXzYbp1aiVVH+S1M9/yX+pYSfl5eHLMt4PB7cbjft7e1/IeEnJydjtVp/EglfVVUURfn/5P5zhCRJ9Pf3097eTn5+PsXFxT+5lBONRv/CWJAT432I1e/zQbQWHUH/+KQmWZWJi+MEHomP3+AmjYeorEMnx8EkgSyg1dqIRCJEhAiKqkEbDRIwm3CpXlQVVMGBnIh8f8bx8RDGpBSUcIKoEkaVLAREDRDHmQgwqEvGFA4S1cmgglUYJ39Zo0EvRIkYRMS4BRDRmkMY1RCyKjGmdQAg6kZJjjuIJiQkRcLo7cefYsYWi4IWHIKZIOBKc9LZ6yeo6im3hZAFDY2NjejkOJbkFNIyVQZGEowO21BFE5LZzYCtiCmdbWiPqmZ9byeLHBbMkkjvt9/in15Ct01HJDaAKXqE5fY0UlNPQqP51xLZzTUHMcsCtw+txm7uZ1PVTERdN+lpZ9LX/xqFzvPI2fApcTVAHIlNqsLr/bewvNJPviFBQoVkx0KyMs/G25fB2ic+521nJpNzTDziOIHE+vkoqUG82QP06Y4QNtahS3qLMd7ENDIJR2IV81wuVmo/pnngNe6Pn8MzLRUUdtzAhRV1UPghw8lZ3HP4Ghb3ncitlddyWlOcZ4ruIlOfQ1//iyw/6jg2rJdYGt1IavUyPhXCZI4lOPuoU1mT7OSXL77Am0DyFU+y6/OLOdrzBmu+SeXFlRdyyZEB7rzwKu4WBQoeWceRG3OwFrzHnGMvZceXKq27dyBKEo+edylXvt/Ihf238Lb6eyr0Q5ycvIvEiARMRlBF9ubtQqOIaILpyEtFqtc/xu6519ClZiCb3KzQJCEGqniwsI6EeDrLdn/IwEaV2MIqnmq8ix1JVVTJ9Qi9sDctky8C86lMtPPbvCcZStXRn9BjqoWQVUP6xASzhyC6MY9W8klkp6CKIq4RNyGTAY1LxyJ5I4cH9HT5nMjpLlarszkmXsllgpG1bpWKbgtHpk7jmeJSIjoD+nh0PBdFkpmp7KG85wiaPiO1+lJ2iFUYlRiD3RoUIF9oZ7rQwjSpjQqpiwKhH4fqQ9BoSYh6VEmPGPPTqOTwsvU67voqhi+S4MI5OT/ee7m541PNTtckWOv2cjHg84WwORy0yOPT4NI8cfKzTSQ08H/YO+s4O+sr/78fu65zxy2jmYm7JxAkENyhSFsKhQq0i9SWulKhhQrUoFAKFAoUCyQQiBD3iSfj7nPnujz6++NO0na73a3t/th97flrrsxj9/s8n3M+53POEY0emktstPhbWOSrZyThwaVuwMBgxe968c9Osr/Kjytex6T+nWzw+HFY5zApPAQxiaZpm7jFXYz0ziCeTBr7lMuIzoDWt/2EPV1MrzqJjsbIQAMhSWNV6485Yl+FN1rOUPwNPEeSPHPdVaxMbcVV2Eyp+wM4X/gXsjGZDSOzmWF20dl4HnVlHjaPpVHSOtW6haIIhDWDS/02ejuOU7V8FqL7WeypT+PP9yFEOrHt+iHqvNswC6YQj8c5vH8fzZV1PFSXu0Z/nCb9e02SJEKhEKFQCMg9g8PhMOFwmEOHDmGa5umo/hSF//fYKUF2KpWipKTkHzrm94L9rwF3wzAwTZPOzk5mz579Jx3k/pmm6/qfUEKWYYAgYGZyLMN4KkJvSwuNeLEw0QUDCQl1ogTfLqXRTRm7oWHZgLSAKDrQdR1V0LCwI+k6KcmOX0tiGQLgQDCNCV29jmWB3RfCiGfRzSyWJBPL9cAkqMWJSy486TgZm4nLkJElhYzPj8um4zcTaIqIaeRuAIfDhUNIkDEdjNtyojVBiRDU/QzqCpZmYU+PMxoMYBlqrnFHohIsgUkVhRw7nnN0GvNkdu/eTSQSIYhJYVUNicRRBEFm/GQK1VNP1tvPsDfIhaljRFWNpniar9UUo4+Okj14iP3vn4EjuBorvQtR8rDU1kFR4QN/9hu82dlLky/EF17+JZMDu9k/aQW4jlBe9hF6en9BVd77qNr0exAEXqv8HPl9L3NW59u4FwXJWDV0bV+FMmkTqbiXGdPPZLxzhKTewZB9NrcZMnpLhPgyHz8ekXnrgIVhFQHLcMkp5hcd4Mzy3VTN/gk9mWKKWy+gxHEhT+Q9xZ6xl/iU+hG+cmApV1ZO5exJD7N9XhFzTm7g5a2HuX3Jw1x/coBvV93MgknFdHZ9k3POuZCNG0Vm7d2IZ9HZPEWKeT0qBVe/H82mcNMjj/CcIOD/6M/oef5qzur9CVt3lPDo0gu4tWWAr9x8B19LJqh5cDdd/1qOu/QxFq7+CLvXWrTs2ILT6+Pha9/Hbc8c5gNjX+a57Oept1tcU7SHZwZlEKZiDM+nqXovSouApZSgnFnEwk0/Ys+Ke+hL57PNFeZcKQ8zOYvvVh3GEK/jomNPEwgfw/LB0vG9vGku4G1tNpemN3Jl9TrCeTZGE3acWwWGK2TMhRqaJjC4bgkuPYgcCqIbBmKiA9VdgDNUwmXCb7D8aYZLDNYX1pPqzzKnfZSIlmVtgUC9uRQqFvL07CACFrKVexiXy13Mjx+kuDPGIW06a8UzIWMyMu7AQ5qZ4mFWuLuY41cxLQ974yFMtYA200Gn0EDQAVUhGZcZJhA+gILBlKpyHur8BHk1j/CTzZ1cPquYoGtCVzMRia4OOHk50o0pBejtHcFqmE7MtECGOcMaJwoEcNkpHTnKy0t1MlKGlbYRnjdW4ok9yWJmUT26lcGLZExRoXCkE7tq8sOQl+mjNkbdNkYcJ5FlgUnpIUJvga1qBZnyPLqbTmCKZQRKD+ItO8DrHbX4ND+NRUN4RpIkM7ejGmmUjjWkSl3I0gwKZn0TZSRAZcTAZg2xJ1PG9JZuDlSewRsON+5SB/aDoyxwOzmYSBOwyeRlTcLdryE7nLgrN6NGGpm78n1gWTjWfw7LmY+65G4AXt+4ibQos2LRYrxSDtD/PYHzP2p2u52SkhJKSkqwLItEIsHY2BhDQ0M0NzfjcDj+hMI/pcf6z+wUuKfT6f/Lub9XLJlMnh76MnXq1P8yYIc/X6ymYSCKEpaaWxjNHc3Mrm+AAwOYlglYiIioeo4ulEUd3ZSxmTqmnBsvKAo5jYAh6giAYFpogoTDVLEMcoBvCZxq0WMBks1OJjaRh5dkUhPg7jZSxCUfjpRK2ibgUkUEWcaw2ZGcAkEthuYQMNWJB5Xsxi5GyWh24jZ3Th0spAkYHronGurY1DijfjdpI40rK6JpIURTYZLb4IBVTJ4QJ62BoiioqoqRiJFXtohE8gQuZx1aWx8Zx0J6nAMYkkSVaLAnnsYAlvndpN9+EyyLl4p6SNoaUcaeZZKnHK/Li8cz5c9+gx8d76AmnuRKZSdRKZ9UbQ95/nMYHHqePN8SqndvB9Ng/LrfsnbHd7nMk0Zshpq+SoamPsCu9HqMtsUUFrWx57XnaN6+jxQ5Cj4wlmXL8Nt8b/NCMpKT6w0bFaqIzRTQBAfJxDkc7lrJ+rw25lW/hTT9cXrTZVQdeR9TfVHeFH/K3bFbeL67jKMjd3Hr1Ddpnr6Fws40r2y5nDvnPc5d7RafrziXi6oVOjq+wsqV57Nhg8nkvZu5fcFZ/IIE973VwXevuhHNsrjupz/lBVnGc/OTBJ+/jDlHvklbqIyfT57JLS39/PATn+O2z99DxXe76ftiCc7Qo8w65zYOvaVz6K3XcfoD/PR953PLU4e4Mf4Nnk9/ikpnhutL9/LrHgGLqRiCyYH6/cjHBfSCUmwrDOZvfYg9Z9xLXyrAdleY8+UQ/lQ1vvJvM7V8ADUr8Ur3IoZLAiwp38fV5S0kPDLxYRvCqEU0IOA5w8JK2Bhdt5J2PKhuD0omTWhklMFCB1umdWKJh/liIsZXym9jTfACPOO/x+59Fb1qBklvFUsPHabPNsZnl4ewI4IAkq6zyNzGzL42YgPF7FBmkk3KjKRygH6utI8zPf0Iuo02I4/jRgW7xiEl6ES9HeAxsBt2gqqfUDbEu32gxD0Y/hncXNJKZecbaDXncuvgj/mV8UX2d0c5pzEnrhwfz4lbGwrymR09zJjQQDyeoCdUQiBhkTZNzkLm/s4UBO3kD+3leLHFdGEyDcOHOegfwk2W972m4lyaoKXUg79/BpVDb/JOwEvp6PnYtBgnK2cwJD7BteI8StZuQ7a82Bovpa+4j86dNSQDx5nbsIOhuB9rcApOp8jlQ7+lSb6PQtNJT/T7BDpMHrr5E5xXsAZRyDJ51jdwPv1BxgZcHOqayjSpi6aZq1ha5OXVvjg+SUQYVdFcMJzVucGmkQ63U7lkEoq7iYqC7yArEsqhp5C7t5K66mlQXPT09NDX0kzrtHl8tuwPItRT89H/q0wQBLxeL16vl6qqKnRdP03ht7W1kU6n8fl8p8He5/P9RTb3FMvwf2r5/2L7a+n0wcFBjhw5QllZGYIg/JcuJPh3wN00EESRwcEhJiEyf8F8fLpMhAEsDKyJ09CMXNwtCzqaKaOYOqaoAwKCmAN33Z57LeoGqiDhQMUyBQRkBMsi13nawrJAVBTU9MT8elGkpa8P7HkEFIFhyYVN19AlULSJeF+xIyoCfj2OLksY6dx1EmUnDrGXVNpG1O7GbqXwWI6cQ3IK3LU4YZeThBXGq0momhvRtBEQk/RbIUqFUdzFtTnazLJQE3E8oXwymbeR5VLsUUgFNEYcObYg3+3kSCKDXxapciiMHjyENamMbodASk8T0vpYaA8QzFv9Z9f/2Ng4R315fHrTy5QGWjm84DJMay+y7MM0s0wdLkIYXEv2xlf43OEHWebdhyLJrJeXYu+Grd2vYFdceCKjTF6+nQP729hVXspAySCMwYMFrxPxnkcyDlekFRy23czzvEa12IuERdjMo1OfztjgIgaG7uCF/A5mTn0e+4Lv0zu2kIYjX+H+pfUsGj7GDw4pfH3/xdw7oxaqniDpKuF7uz6NfdFv+GbPGLGSFVxf9XU6Or/AOedcw/r1FvWHd/CR6Uv5eX0cz5ttfOMDH6RfVbn6scd4MT8f96WPM/v3VzOw+asUlT7KA9VF3NU+hH7XZ7nnoW9T/J0Bhr9UgNf3JA1n3ErLRoNdzz+N0+vj59cv5kO/Ocj7s9/lpfQd5Dkl3j/pII+1C8AUdEFnz5RDLDkssL2iFNsSk/lbfsCeFZ9mMOXkmH2IxfYi4tlruYthFrqOMGvlIfKKJUZkEXu7DG0Cialgk0EbrGRs7xxaHHY0tx0lHiUwOICWX0ltYCar1QNcI3TwaSXIZ7w+VmzeQPFCkcGyqzHFs2kMD9A0t4YTjSsRLRNTlvEkU1zf0Yxr/2v0lSznde9KwjE7hgVniwc4w95D0nLRbLPxO8VJf147YffO0+vHiYJDsIFgkTCzaBgEdDeLus/H489Disd5gsnc596PYOrkJ1sAiGf/0P2yp6cHh8OBw5Gg2jrJO6nbsAecrM9YCILFvI4sJyp0/BEbiqbzzDkqBiKrFAfrMytwxNdyrriYyek36Jhnx2YWUxzdD5bAD+zlLIoEOVFYyoiznQKtiJq+Hlw7Jeyzr8Kxqoq+t3rQpQyTpmxCsCX4fU8F07Ugy8R3abdPIRibz1jmGN79J+haMo3F2hCB6u0E04sIvvRVjCz8XlzI8p6jbJ9+LdsEG0pAQmqJczZO3nFlCNlkPFkTeWAdSiCAv3EDYvpSSmtmIsT6sG/+BuqM6zGqzsQwDF57az2DvjyuWzAPm/iHZ/d/ReT+H5ksy+Tn55Ofn3Mw0un0aRV+T0+uj/8fU/inqp7gD45IIpH4XxG5vyeb2Pw1Zpomx48f58iRI0yfPp0pU6b8TS1o/5H9/vFiTcTjWFjIE06F2+MGMweolmWRg2QBzTgVuRsYlpRrRiPnboJTkbuGjomIaFlogojd0shheq7eVpjoTmcBkqxgnmraIwiITg82XUMWLFJK7m9TEpBNwDQxbHYEBWymhi6DqefU/SJuZEFD00SiNg82K4VjQvmvT+gZZT1N2G1DRcNpgabZEEyFoZ7j9Fn5lDNCoLSGeDyOoGtYloU3L59MpheLAmTdjiGnibi8hKLjSPkhmtNZGlx2BEEge+ggkfpidFststoKwFR5gIqjJ5C2P/Qn1//nB47iyGa5VDxCXMwj7DpMfv4FDA+/So3vamx7n8BYdje/GN9HnbaDcpuAt/hH7DeWsZUFrBR2Utr9NuFkLz/qz+cXRXGa8jpBBL84jju8lNK4iM0Cm/MtvuD+LlOjbVgnLbQTEOofYTlvck3el3mf53YuCrehb76XVw99kIzvCEeWfoGhQ29yiVbFYxdPQjJUvnVoGp0DnyWel6RpbgWz1/ZzzbjAjwfGeTK7hMqKe4knnueccwTa29uZ33ec9zldvFCt8IP1nZTdfhuJSy7l8sce4UDTMIeWfpn5HOLIi99gpUPk8xUh3rD5WPPlb+F0ePB/P4OWdVBU/DvKF89Gzytk8xM/J9N1gp9dP4MUDm51/IBsOolsZvhQ/UkCAyeZEqtjcngaO6aHSY0Osrk2iHJWhqsdn6VIDHNQhQOZcYQCmRvmbqN4+XGGCxWUwyKZTkjXQHa6QKp1PgOvXsOxE8s55vVAKoanvwuPo5h5eedxkVZDZc0P+M28V/iIo4RBS8QQJDbNHWbG8S2UDfWS8gfZXz2VrGInEgjRkOnimtd+xfVvPI6tQ+GFvKtYa07GFYtwu7SeOx3voHjG+W1elJ9Wv8v6ijfpC+2jzojywTaJL+2Cn75t8tBWi88PF1PjLOcz8z7Hz874GSX5pbxb8zJW1oPh8mAikLCXIGTG6bNyIFHky6WftrWN8cKBQerq6hke+R0ZXBwdraB/xgIUzUQV4aoejbePR4j4ZUpHetnZAI2RRhaN7+Zpt44iSrzvqVa0i1RiPoWC5qmUjA7z2zwPswYuxBAsdtROJ8M2pncvZPq6PsS8Kpi2hLHetxjK1CNUbKGgoom3wi5qhmcRcGZZoDZhJj6PaIpoI79AMCQ21FxL6dxnkfrdNAjTsGdbOTZeSOGhFAO+ctbNXMIlIQ/9PXEmeR1EVQ1VyEXtFxAjG+slNDUDlpuZi+/N0fFvfQbL5iV75hcB2LtvH6lIhMGZ87kg709B0fw7BHX/THM6nZSWljJ9+nRWrFjB7NmzcbvdDAwMsGPHDnbu3ElzczOjo6PE43EkSSKZTP7TZrnff//9LFiwAK/XS2FhIZdffjknT578k+9kMhnuuOMOQqEQHo+Hq666iqGhoX943/8jwT2TybB7927C4TBLliyhuDjXjesfnen+19gpcD/Vyra3txdRlMjLy4k9BBGY8FwFQcDCmgD3HFJKgjERf4Mgncrdn/J0rVMN6zAQEbDAEkAQ+Lc8hihJRMZzjVcsQcCdH8KmZxEEAVVQUAwdQwTRBMs0MRUFQRGRLR1LELCsCUdBdyMKBqYJWUlBQsU+Ae4Th4xoasQdCrpoYhcENF0CS0RPjDBo5VEshMEZJBaL4VJyZJDTH0BVB9E1D5Kh0F2gkbI5KIhFsGw2WtIqk512LMNAbe+gu0jE6Z6KTW3HJgfwSxbOrv0w0VzmlDO3L2Oy8NhBytxt9NfMRTdiCEhIkpvS1g5wF9Ax9RJ2dfyCeW6dTu1OHvxdC4amIWJQbXawuuowOxe10m7YUQeuINvyGWYPX8I5kRGaDQ92QAU+xfNEexys2z+HA23VHGqv4u2Ts3h+zzIO7JyEYyDJxf6fcrXnTpa25bHv3S/SFi1mcO6DdJhPM2mvxW+um0O+GefbhwrpHPo8gquDuvMeZuqGPm6IiPxsMMIr1sUUF32AZOpXnHFmiH1793KtOcb5KDwaMnlh1yANn/9XRhcuZuH3vsUQ0zleeRGXqG/w8ouP8oFCPxeaKX6YhpYf/Bh/REV8REFV49RPXo93+kxMb4D1P30IdybMw9dNpznl4U73AxjpKLb0IB+eMYC3v43pkQbODJdxRkUzX09vYFJwmJccizEKXuaCufcSXHUXfXN+iK7Y0U9cwJDuIj0X1CIvkS0X0r7uao6MNNLlEpDHBnF3nsQfNKi98BjLK4dxFazjF7O/yg12iZcSDmJWAdnRq4kNfRWkJTRN7iFi2wkTlTKKofLooS/wpcM/wR7NYhsbYJOQZiojfMa2jrmeY2zMH+bxqk1sLd2Ag3ZuPKDyyC9Vfv5Agk89HGP17zNM3q0ROGmQtzNN5aMnue97B3n7pZ/x4IYuvrf0QVRMhoJtMNEnXsmOgZ5lo+1MZFFgWokXy7J4cH0zRxNOpk2rZHj4ed6yVqPhYJ3owhQE5nSoNBemmRt3MhDQSSitFAgFLNQK2CBMwszs5+LRxZRPOkZ7nZPgyFmUpdYQdSpstM7BLpp0uYvJygaLMiWs7NiNPCRgm3kDI1XtbGuqQHP30jDjHSKJIC1D5bhMD9ekX2Cf7S6cho++zNO496V46+IPsbj8JSQhRf2Uu3DufICxLhfPJlYzOdLLyVmXoqbgFcVAVE1W9pnsd5kEJZE6RBwjb+LOzyN/+gGKQp/E7vAiH3kOuWszmfO+A3YfsViMbTt2cLismnum1f8J42qaJpZlvWdmuAuCgM/no7q6mnnz5rFixQpqa2uxLIujR48yb948PvWpT9HZ2Ul/f/8/pRf+5s2bueOOO9i5cyfr169H0zTOO++8051OAe6++25ee+01nn/+eTZv3kx/fz9XXnnlP7zv/3G0/OjoKAcPHqSoqIgpU6b8iVf4j8x0/2vtVHleU1MT0WiUSVXVhA/tPf0wEkURYUJMIiIjCDoW1im8xwJEwcASBARLBMvCsnK5d0mQkAQTQxQRLAvTEkG0ch6DIAF/WGw9vb34Y6e8ZIGsbiCZei6Hj4FgiZiikOt3L0lYpoUlizgMdSJVMMEuGAoCJpYloEkygmBgn1gWpyR8oqWhiiKqaGADTDPHR9SWFZA45MJHCsvmJR6P47LbyACyTcCydDTdDjjJOHVSNh8VyXEEwc2wZlBmVzCGh0HT6PGpYK9ETDSR5/DjEnXE6DGMohmoqsrBgwcZS6XpDYa4cecanO4YiUoRt30a4+PvUuo7F2nz46hzPsUvjj/J5QEN2bmIX63JY5VyknHXJI6Mg8d+MTfyDI/3h/mAejcVyFw843HSTYvJ9r/JXZ2VFCTDOFWVuKRgaQoVmWE6zilGLRFwjWRo2N2HrdNgXXwu1b2DTJvcwzWhz/Nu8nKatt3J+ulrOK/2BZqH+6h/52P85qZlfODp7TxwxMt9M79ESegb1K5+BGvtnVx1QRkP9IXxVd7CXH8HicRjzJz5MTZseIcv3HADfSd1vi4maehPMue797Pn1tvxfemLyI//nPHRw1w6/ASv7pjPdaJI1O3jU2mTZ773fUr+5RO0/bYUrj/BgkWFbI5PQT95kHU/+i6X3/cNHrhyKp/4nclX877MV1Pfwj12kFsbskQju6mKDbGPcn4uzGVWqI9ZpTsIBxWGDBltqIK07kc/divTpCDN0Ur6x0bpttlQbTLB7CjuSC8kI4Ty3UwpfB/lmRBdYxqR+pfZmbCxYVwma6/FNjabRGYuQpUbNc/FuH4btmQ57ujzVPQfYdlAEVsaz+YO7S6wVKrzhrko+TKXJvawt87kV3mHyMopJkUVPrRNZeE+hZHyyUQnzWRgcQVJ/NixoWLQL0XYFNxBpn6ILwlnY3zvF3x0XZirV/gZicn4BYmUmAELXEISd7IbQ/PxvHkXy2uD+Bwy77aMcnJM432lBrr+IqYloO3yc/OOp/n6R+9j3CZxfVuaVzM6sxwKowE3/pETzOifwXSO8BmfiV2u4+ZX36TnkxKymUdJdz/uVIrPllczqacWUzN4d8ok3OmjlOyqpmHHJuyTL8J5yRy0Hc+SMc+kdN6vkJQUPxmVWT42nVqpk3F7KaXjy4honXgObCFRX07AmcY/aQ/B8QUUrHsIPSXwlG85l+3bRmfRHH5bNpkzbA6ahhLM8bkYlCCtqyQsuNwYQU0MU7I4gqDNpLrxcoRYL45NX0Wbdg1G9dkArN+4kZQoUTx3PnM8f6C4gdPg+F4B939rsixTUFBAQUEBDQ0NvPjii6xZs4ZHH32UL3/5y9x///2sWrWK8847j/PPP/+vHgn+x7Zu3bo/ef3EE09QWFjIvn37OOOMM4hGozz22GM888wznH127po+/vjjTJkyhZ07d7J48eK/+/zem1f93zHLsmhpaeHAgQM0NDQwffr0P6N7/jsi91N19Lqus3TpUjw+L4amnXZGdM047f2LgogiyOiWjjzxnmHlANwURARDwAIs/gDuIgamJCFgoSEhCOTmPAsS1qmwHtBVlYKCHFuAICBZ1kTfeZBNA12SEE0LEwtEEUHPRezShML4D1uyIWCCCaooI6Kf/uwUXyBgYggiumSiWMLEJwKiAAnLgVvIgCCSzWZRJhwbQcrVBhq6DUu0YYm5yD1o6JiiSNQwyVdktL4+ADrcKTQxiKgPU6jI+PQAAElHKTt37kSSJLIlFViCyCxrAN1SSNCO2z0ZVRuhOGIDy2Rs2wysgV3kSTpr2i9mia0Xpz+fV8IFBAP72ZrXwdPmDcimg+dd3+JaaRD1WR/T33iO5ScGmBHeR0ZU6PEWkBUVRNkic1WG0MUthGZ14F3dQ/RLaY7d7ye/dhhbd5aXjy5h6IifM1wvc57zm9QdvIDnDn4INX8PzbUPIq0d4FfvX0LIiPPdQwqR4fsQbG3Un/8bprw+xMW6wle6xxgs+DKy7KW45BUCATfrXn+dn88qwavDxzqGiAgy9d//HpJl0vq5L2G/+EcUMkrpzgcZzKh8tdBNgSLxL54ipE99irotvYxvnUws9jZnny+TqagnPj7O2z97iOVVPr6wup4dYRcHrTrAhHgXe8x61jpmYquNM2vpEfTpUWKqA+mwSCojoJT14AyMEnNt43lxD+9mU/Q4nIQGBwl0taKPdOLVx1hUMpOz3B+nQArwo7KtfEw+xDNhBwvcGp8IhnAMX8dIxVlocwsw/TmmKJQY54zuAi46VMiYp4038mJ0H3UhJ7KYUzws93ZjyjKH8o7RHtzLuSeSfOPXdi7cPY+Y65PsXfQA9Q0f4xz3chZIlRSJPpyijSLJybmU8/nwNczcfzYv7XPROu+TuMc0HHqW48O9hC0Du+oGC3QUDNHBO+l6TqR8fGBRObppcf/aExQJMa4/08/wyAscHV7BLb/7PfvqpzDmkDirOcNvnSMsSttpKj8Kls55gpuQ6uHFPBXdiHDrtnz066MkvAplhy6nML2dXYUuXJGrMTHpdTlIu4qY1W5y7eEXEb2liEtWY4Wfp2l0Jc7GNYSKT/DyiIdJA1ORBZmzra3YYp9DsCA9/kPksMj6Be+nbM7vkLq9NFgVKGoXB6OlWMed2E2DXSsvZ04Gns2mcfhsLOsz2SZk8QsikxHwjb6Nu9BJoGqUabO+imCZONb+C5bdR+asrwLQ2tpKZ2sre+tmcG/Vn5eOnQL3/5+0/N9i1dXVXH311bjdbt566y1effVVGhoa+OUvf8ljjz32T9lHNJprTHaqqdq+ffvQNI1zzz339HcaGxuprKxkx44d/9C+3rOR+x9bNpvl0KFDpNNpFi9e/BfzIZIk/Zfm3AcGBhgeHkYURebPn58DZHmCWpdykGhkDGynwV1GEcAUzBzFDhimhCiYaKKMYIrkBHK5iFtCRsTEnIjcdSQE0QLRRBBy3z1lFWVlyFHb6deCaWKJIrpuIlsGuqSgqJBw5v5PsnJsgUruf04Bt2XZMVAQJQtLyO3XmGAITicLBGkiRTDxpiDk0gUIpLDjIgfuqqoiiafAPedEaJoI5IZfG6KIA4uEmLvZQ4qEOaH475PipHHiMmMUSG5cRi7Hube5n5L62dTV1fH6nkMomkAD3Qx7a9D1MUY6OsBtx917Et09m5TgosI/jGyfyo6jFufakrwTLqFKb+FE8U6E9FRUaSYvTT+DHx74Jg3rHiWdlNg2R0E+L0N2Zy3HnR/idVlgv7GIx51foGdOCLWzlL6tt6O6dNJzD+OfdIS8m9toPr+IqT9pY3fvZOoT/UyefxSP73PQ9k1+q9/O+2b/krb6B6h7+7P8/IZ53PjbIzx0XOIzxt14Kr/L5PNC8NLlDL+viHs74zxZ9X2Sbe9n8ZJZrFvr4tCubfyscSE3dg9x554enl5eTcvXvkHZPf/C3l+9ydyVd3Dm3p/wgxOzkKZO4Wd1xVx1vI9vzFnGl89bRcPvNtJWPR34Jasu+TLrnk8Rbj1M849v4yKaucHWx0ZtFi85F1Bb1k5Z4VHSTomRtA1bs0UsCI4SE6NAIN49g+iWRroVKRelx3uot81nuVLOYcdujo+9S0OhSqntExQrATqMIT4/+QEychLTdQ7hoVn8LKFysrKKsRlFiKYBpkH5eAtzOwcoioRxtw7yVtXVpAeGcZa8QL36Q4JZLwOagZSZgqSpzO3IcvaJyXRWnEnX5MkICCQNk8N2k4PGIEayFyE7jKEIdOeHGBA9hNRKHhVsrExN4SXHAZLZABagixIDifWIpkCe7gbBYonQhCY5+bb+YRZM8rNgUoCHNxyjL27wiUaRVPpnQBmhZ4dJOJ2sOecK8uIG0wfH6Iz4UeUR9k0Okqf2UNZiJyi28jvHOCHlSi6wP0ZbrYOinqspMh4jYxN50X4Z7mEdKW5jy7IYoqlz5TsHcI4nsJ19O6Ezk/zumXrkQAeTpr1J71g5+5NZzs80sJS9dCn/QkXKTa/+OP4dKXZdfDMzGn6LmDUIei7FdfgnDHd6+JFyPfd1P8XhmZexXvVS6BTRVI3zDAedDQraUJaEaXGN2YOWiVFzSQsFebfj9lRj2/0wUu9u0tc9D/ZcX443336b7rwiLpg1g0Lbn0PJqUDrvTb57S/ZKUFdMpkkEAgwdepUli5dyle+8pW/qaHaXzLTNLnrrrtYtmwZ06dPB3KCcJvNRiAQ+JPvFhUVMTg4+A/t7z0buZ9aEOPj42zfvh1FUVi6dOl/KHT4r4rcT+V7jx49SnFxMZIknT4+aaLm3ZroBmdkDJBzl1USJGwT/pMl5JwOw5JQRI2UbEe0HICJYeS63inIiBgYioRsGaRwIEoWomjAH1FbogC6piI77acOENEyQRBQdZCMLLokI+uQVQALpIk6+axoQzQtRGGC4jcldMuOohjIpo5gSZgTM6ZP3ZImMk5DQ7RyQyQm3IJcfT8C4oQzoKoq8sT1+ON81WnngNyCsybA3S6KmBO5p5ii5ZgKM42bFGYsi4VA/eyl1NfncnmDyTQFkTAOOUkyGMz933gXQrYAceAAGW0KJ4JtNDpNMv3zuF6K4PAGadYCOGsP5ILTnotIzK0jbnjQXzfJmAqTzx/m/DKN0sOfYanrXj4j+/iO4GS3XM13jI8TSmRwFw9THZAoCGfxbllO5vnPsa/jaoQSlZ6vyuSVjjE85KdpVxWl9HGu74ss72rg8f0fI+s/QVfxI+Q3qdx/TjHDhp3nB4NEm9+P5H+dSQsPcf2hLHmyxKf6XOSX3kE0+jzLl5dw8OBB8ohxl+Fgj9PiF80jLFq6kJ23fISyNa8wos0l4avlxuTv+dWBw1Q7bHy3qpD1kRRvffxu5PJySn7Sj5kqw9H+Va7zbeUDtXtRs93sI8jxiiDBxW34l3YwViKi9yqoHaDaLLLTIOUoYfjdSzi+/jqae2bRK5oU9/dT3N9PzOtjOLabo+GtzPYtRqy4hR+67kaUvRztfQnv2i8yZaCAZ/ti3BIx2Vs7le2VCxmjEJuV4SJ9DdsOvI8HD/8UazDD24kaflJ9BUExwWXdg9T1ehgsGeJEVRsrBqYhj45huRaRzr+PeNFHyBr1bHZk2ZndT+XJJ7hn4xe4950vc8/eX/HxprV8btPLfG/N09zZYyOpReiy0jhEyE+W44x205NfgMMTZ03v81TEq3HpTmRBZ5FwiIfTq+jW/dx3fh0nB8d4dOcgy/MPc86cI6RSrQy/VsDc40f56m2fI+yQuPlggjczJlN02FT3FGnXVM4zBsioLl4oGkK1T+Prm96ie5WCJ1lPaU8LzmyYnxVOxt1bAknYVLsV1XMGq3Y0MefkZmwNl+C8tp49r2xCNUOULXkcM+vjh+kxVg4uwEMSwVNAaWwGEaMVz+4dZKZMxlnZgzPUSn56AVMOP056VOHboav5QNObjPmreHnBSlZbMgfSKvmlHmY67bw1FMVmWMwGHL1vkteQwuWrorr+Q4hDh7FtewB14ccxynM08ebNm0lms7RPn8/NxcG/+Nw8NTTmf4Kdwo5MJvNnpXD/jHO44447OHLkCM8+++w/vK2/xt6z4H5KsLZ3715qamqYNWvWf9qM4L8i5/7H4r1TzsUfswOnwIyJtpdG2kCw58BLFu0oTHx+Ctzx4VQyZGQ7knZq2E0URVFwCk5kVFS7DYepERXcCBKoWhTEP4rSETBUFcWVy3EJlomga5iCiGqA20ijygo2zUKVAVFEzqSwBIG0aEc2LKSJgTamaeXAXTaQTQMsiYyQK7GbICAwRQVvVs+BuwWSZCIApiAjY2IgIajJCfFM7tzNiWlykiQinEoFCKfcglPMBljpDIgi6VNlgZaKzUijpTIgKRSXlp0+73BGJRiLYJfiqF4HgqAgKmlcFCCkRlGTFbS69iALJnRXEZbCDOpu8tQRelwtaOPzqast54TLzWd+/RCWleLFcy/k965rcUm3MlNqJE+KkLV0ZplZVlgyvxGW8duTVyAIKq6VX2ZBQ5YZ+QGqskfx7TiDnrWfZEgqJnlnCmOaTnLUxsE9lVQIPSz0PMDZvVP59eH3ky7cyaD5BJNjbm4sS7At6mLQs5xY12Jc5b9k5ZUCD9cV053VeVK7ELd7KrLyNCWlBaxfv573LyxmeZ/Og9EYR+MZLvzQTeyePZ/Et76DuOyLlDLMkmNP887QGOcG3by/0Me3B6O037CKydP6mLvzJOGD+XQoEq21HoQlw9iX9xKutMgOOzBOQgrQ6k1ShV7CTefT+sb7OHH4HNpML67xISo62pB0nUyNnVkFR5nUvwMz1k67FeFEWuU6OZ8zkbjO3sNnz9I4MamY/LFpnDP/WR6ovRndZkMydMpHde55q4vL1TWcmKbwC8dK1iqzqHYNcr/0UwLWerbN2klreYJQ3Ildd6FEQgSEq7HZl9ApuNggdFLQ+hT3bb2P74/8mA9WrWf6xf3IFznonOVj2oVDdJ4zBW8mgye8C1F0UI+XMVPDq+ZR3L2X31SvZqbzaWIITIlNxhLhQjZySC/jEf0yPry0EldqjF8+9DCFzmFuWyIzOvYMYycamfbWCR658v2cmFTOWS0ZXtAGOSdpZ3PVL2kvn4NdMCk62EHS3suAU+W8/jpsF/UjmG4m7VlBnv4OO8uCZMYuRTeg3R9mKGjHlXZw7wu/QC5oRLuoFuPgLzkeXU3+4l/gco7zcFhn8kAlNjPELOUo1eGbMU2VTOSHiBGZfQvOIH/KOhwn85kyNoCkptigNuJsh5LkGHvPuADG4FlRwwzZubjPYm+BiWxBHDjHOo4gmZQs7GHK9G8i6BqONz6Bmd+AuvReALq6ujhy5Ahbq6fx6cmV2MV/H/j+fyvl/1YzDOP06Nl/llr+lN15552sWbOGjRs3Ul5efvr94uJiVFUlEon8yfeHhoZOC8X/XnvP0vKjo6N0dXWxYMGCP6Ms/pL9syP3sbExDh48SH5+PtOmTUOSpD8rt7O5ch6eLkzkmDMagk3EEsAm2nFMgL4k5trUqlYeLjmdi9zTp/L0MWw2G3bNjiSMk7X5cOhZwuKpBTaOKP/xoAQRPZtCcU20WTRNbKqKJitoukVQjxG3O8nTISsbCJKElEhgGRZJxYmkm5gTbXExdVTTic2mYTN0TGQS4sSM+lM1+rILb9ZAlAV0C2TFICvqqEIIGR0dCbLR3NhdTm32lMDQQDRVTEtCMk00BIQ/FtjIMpgmknUqtpcwLRO/3z8hIvyD6ZaFTdOQxSzRuIZU5EV2xnGT+w0MI4+ofT0AznAQQ+nkeNxOsfsIPSTQYrNwLgow/9Bh5rS08soZeeTH0tS43kdGEkjLzzNZ+Q2mq5hWKciikSqO2S7jHfsKevaEuGXuU3QueYjStgqKpE/ilwVauwQSv7+Dzst/TtUtbSg/8zHcGaRtf5aZiw4wpL9ArOcaXnSOcvXk13Dun8zS0kls6+nnJ4fz+FrDh8kmvkRb2+eYMfO3fK4ixFe7R1lc8RWC3deycGGC117NcqBpP9+YPZXrmvu56/gAr8+vQvncfaRvv4WWH71IwZIzWD26ma+99VuK5Dg3Dexg25y7+WLeVL4/t5RQaAghbwBZERnPiAi9NmIOsBVpOKp1UhknkbYFGF1l9NtFDEkklBlj0lCEpNvNUEkRbb4eGsUNnDEWY0NXPZgWyaLJuNTVDOkCQkbnFoeTjBrixa5z+fTHb0J3KFiiiCuV5DOdj3PdwBvcW/UZnq+aj3vHp7h2wc+4bsFz3HryVeLxCN/2hgh7VRq77czumUyR62qSWS+WYNIj9rC2ooyvrHmIhZ5mlEaDjupaDsqNxLLlDPatYH8owYzUi4TCKUpMOygutoQCfFDwYUOkXcsSiHUxJibpLosyXtjLjLGZuDUXVUIPJdYAl2jfYFp2iKv7+nnuhY3kGxK3rLAwtfXEhwuoeLyfpvoprFmxmoqwjtjXybxoHm0lb3OyuAXZ+0lmRfeTVd3sKN2J7r2VW6yvEnHJVO27gzzbVxlxK2zUbiKb1MhmFQ7UbsQvfJ5P//LHKAiY566goKiFZ966lGDDW4TKDrGhdxLDqQiXZmdSTC9B7aPYTYlO8UeEtqocueZOKmb8CqHPxezK87Dv+yHNnfn8yH893z/5Uzpql7HO20ggbZEUodbvosCd4cn2OHYEVgo6ascmKlYOUFJ6C253Pfa370OM9ZC6aR1INjRNY91bbzEcyKdm2nTO8Lv+4vPzn9F69r/T/hjc/1l17pZl8YlPfIKXXnqJTZs2UV1d/Sefz5s3D0VReOedd7jqqqsAOHnyJN3d3SxZsuQf2vd7FtwLCwtZvnz5X906EP554H6KNWhra6OxsZHy8vLTtIyiKGiadvq7DnduEVgT4K4lcvlzwS5iEx14TkW/Uo5+Vq0gTilDSrYjpAEH6EYCm82Goiog6GiKgj2dIWLzAeC0p7FJDiaGy4IgkYmOo7gnInfTxK5nUSU/aQ3KtBhJnwenKqFJJik0xEQMy4BhexDZsCYa6AC6RsoI4HGkcetpNJyoYhYDA3mCntcUN/5MErtLIiXqKLJOWjCImTbsaKQFJ2RiiKIbQckxDFr61PXSsDAQDQmHlmVclHBObDdhmAgTzIcbB6KpYwkyyDKCAbn2fDn6H3K1AqKVkyCamICEKJvYTmUY8CIoKSzBgTTRgKdXd1OZN8KsVoFUX5yDmsY9W9cR9oCe8lJdfQllmsSokOKlQA35yZsoSY3QTDWqw8651nHIQFZUeHn7jcxrfBdjcjeOyk9R0F2CW7+YI92FRF++jd4rH6Hw9mHKvpJhd6aBvKNxzp76HMNjCzjafj5H89oQZjzKlPYH+OLFU/jwGyO80NnJ6p4PYVtxP8dPPMTllR9jk8/J1wdVfpF/PdHxZ5g9+9Ps2bOHmbfO5OP7Fb7qN/h5b5g7a8r4yq2388mnvk68uICsM8jFAy9hBFWM6hh3i9/mHteDPDn1Mm4KP43UChmnjlRuodRpGGkXoy2L0XsqGFAEdFkkkB2nsi+MZhMZKilDLtJYYhxkCi084fKyu7ucNzvKGChScIZmc3PyLIYUnf1Jk25lBLLFfNzuJVkk8pzLjpDUuO6dl7nlzd8zVu+kd04Id/sIfWYUxe5D2D2DvFmtxKfqbI/bKW1Pcu0rfkzPueBeSTIjkNX28dL8V4l457A8FqXxin5OlldgFQwiiD0I5gBBYS+Omj2oG76EYJNQNTuV7ps4Mr8FLVTH1YKNY2oWIwt1J5/lrpWXoE9+mpJEKZMjtbjFFOdbG/io9i+Ypp1Pb/4xv09Nwcqq2JaU0FhxgPi4gO8xBU0U+P7770EAVh3upykRpNB7hHcr1zEnei7rK71UtQ7S5+qjv/B8fjX0I8L1MmXNH6FY/wWmmOXXngvR+mSkqJ0N01+kVp3NtKajNLYdRznrFvQV7bzyeiWevEGKZ7zC4MAUXrW6uCa6CM1UyHM0UhAJ0MdbBN5pJbx4FfapbyCToqHgGtw7f8Rop5u7Sj/J3Vt/T8pVwLaLr6aq02IdOkZjkPdHbKyTTFyk0IAZY5twhgx8k1yMjc8jsOUxKg8+Sfrc+zFD9QBs3bqVeCLJjoWLebHyT8ch/1v7725g84+aYRhks1kcDsffhDv/kd1xxx0888wzvPLKK3i93tN5dL/fj9PpxO/3c+utt3LPPfec7qD3iU98giVLlvxDSnl4D4M78Ddf4H9GExtN0zhy5AjRaJSFCxfmIsg/MofDgWEYaJqGoig4PLno2pAygIIay4G84JCwSc7T4K4TByBr+gk4BojaQ7nI3QG6HsPhcKDEFExJJWuz4R5PMuTOqeFFrR+XlEckd5aATGp8BFvAjYCIjIVNVcEO47qd6fowKacbZzZ3Y40LKfINA0nVGbLno2gWhpJrt6pnVFJmALuk4jTSZEQndhGiUgJRlkG1oSkeimOD2BwyMUXFLqUwRZXRtECeECcshRCSw9hsDaQzue1mE1lAQlE0TFFFNBScmkpEseGdoPGiuoHoznn+rgTIgoEluklZoMomgqGCmgR7zoFyCgIjDieWJU40CjKwTAFLOiV2MRFFHbBhMCHoQ8Jwxbhgo4Bm7GO7tYqa3mZayhUC9kJKMy5SgkXlyjo+2+Djid+0coQGnKRZKOxjrnGUpOBijzGT4456mttX0nFymMlTm8hMHkKse4wZIyZ6ZxED66ejrxqj/d4Q8+47yRr3Yt4X3cxS/w9RIz/g50du4kvL72fQ+zjTlW9yWVE3Lw7nc+3CQsZOnA+Nz7FvXwWXKlXstOXzW/VKLuc1KioPceRIgI0bNzI1VMQHD+3G33SCPeEWrnSnGLzBgT04yLhPIOvIOZ7ZpEReX4SrfM/xXNFNLMrbTm2wmWg8j+TJ+dBfxJBsoksi/kyE6u5hsrLJWGE57XXVzJMOcrm5CZcSo7/CwTqphtjGWqam4uxuHGeV/iHOT01mxMpyLP46R+qWEIyU8kCVjU+fyPLpHjAj47yeGkGkjIG8InaaDTyTOg+XmOGbwqMsUk/yTmGCj6SDrByWuSg/ymJnCW2FH0OihGYpS37kBQJWP2WWh6S1h8vKdjPgTWOLQH6nSNfoNH5dtYozCl6nQoxjsh4hlSbouZx+BJ7Iq+B+0cewbtKagunHn+D++WdjTXkWu+5l/ug8RMHkausN7tNu4aRZxbc3P8y+pbNhpJ+RmdVcv2iIeLQfni4lb3CEj/7rQwwHHNy8O8zatMhZ9mbern+SZSdEjpyzmsZIM+6Ezp5qi08lDmPUxynsX03Z4D7sQjvPls4m0V2PGBd5p34DXtHHvGNLuWrdj7E1XsDo6i2MbwqiUcmkJd/EGK/iu1oX80aKsdKllNkTzI6cQ9zsx37yeXRHCX2LVPIKThJsmU7J8K/IhGV+mHcx81vbqIwNsuuaj3K00+AEJmaZizOTEp5Zfna/PoSMwCW2LERbqLiilynTH0EfSlO69dv05S3lYHQSeRMz1vfv38/Omml8bHIlBcp//Hz+n0jLZzIZXC7XP00n8NOf/hSAlStX/sn7jz/+ODfffDMADz74IKIoctVVV5HNZjn//PN55JFH/uF9v6fB/W+1fzRyj8fjHDhwAJfLxdKlS7HZbH/2nVMTh9LpNIqiYJ+I3A1BBRSMWO7hKrrkXOQ+kV/OmhHASdYIEnS20eOoQkwCQTCMOC6XE0mT0MQkGZuDYDpGq5RTVIpqH0G5jgFELEHCEmSS42NIfgcOyY1lmojZDNghYbnwZ6OkHB6c2dyNNS6myAdc2SwjtjzsSZOkM44gZdEzKlkzJ4jxGClUyY7NlBhRxrFreQgyZBx5VI5HkYqCpCUTt3cYU8qnKyKRR5ywkIcQbcPlmsN4OIwgiKRiEWzuPCQ5gSWkkTU7DjXLsMeLDXALMKrqdCcS2IHJQgFHyWDKeYwZcTLKBDuSGj0N7gG7QpvHS1Z3o2R1VDOGqYmoQm5inkAWwbABKTKnugQCsi2BIwtJb47pCCTitFXYCJXNJJgF1QTH3AJOvvA1hqnmrCNHOFk+BY/nVrK6hF/azoXSBq4w17PRWsxOZR59bQsY2TGEp1ElW3kSZfEobmtjjmUIRBn7osSMXc2Mj7moDnRz2LGOC1Ln8fSJS7hl+jOMNW3g7mtW8daPt/Lbox1co1yHmdlPMO9tHJk7uKivhb7MKB19dRSyk6W2NPbBNIo3yzXlWdIukYxTIgtkDUiMu6Bdwu5JEfMKSD4LpT7LCu11tmhn8RPjX7l127tE5dx1DcVGqRsdIyXrjBeU0jK5jhK5l4vNt6mzutlszODkFBv+pJuNY4sZParhzMbJlk3h1vQZTBUDHBNGeHLSGNtqryVtd4IgEIrp/HYgyo0RB59FRkThZZeXt5bdQRqFS9u2clX3VrwX9/LpEgftip8pPaXMOrqK1mI3ulpNQhTZ5I5w5sjzBMwwF9S0cLhiDla4H0FLUrXXjfBimr3eKlpnyqyc9xqT6GRg63LEkaM0KFXEQwt51EzyLamAhGGxN2nSePIZfjm5hsF568BSWDa4FLspcw2v8RPtIt41ZvGVHY8yOK8GY6SXrtpabjp7nERiP8nXJtFwoJe77/4mnSV5XHg0ycvRCKukITZMfoJZ7SZLGq/kZamI1d0n6AuMMC1QRINnA3kj0yk7HsSrPMXW8kpa+s7GzEJTcStx5xi37/kAS7Y9hlw4jfErhxCHYrTGbqR65Q9RdCffiEUojtmZl5yCJiY5M3YxpqWTUB/A3SJx7ENnEWr4NdKeEDPso1jpJBsS09jumMcPm39Ee8MS3nBNJaqqSE4ZZ4WXu8sK+di6Y/ixkBEobn2G/Olh6mfdSp63EddrlyH4ivFc/ygzMibDw8Ns3ryZcY+fdFkl8yIjjMu59Nlfis7/J9Ly2Wz2n9pX/q9R2TscDh5++GEefvjhf9p+4f/A/bT19/dz9OjR/3RU7B+Du8/nQ7bZkBQFVU1hWm6MRC5yl7x2XIoXmxFDNmUimVHc9iqSeh5lnhhRbwhrPI5Yacc0swiCipk2ydjjWIKYm8sueDENENRBCmQPDslFxhKxLEjF4gguGafsQTdMrFQSfJB2OAloOimnC8cEuIcnCP3iZIJ9tkrsWQNdTiA7I6gZSBk5es1v5kbVWrqPYSVMpRgE0STtLcIfSaDLxaTtBpI4AMIUekd0QlKSUSuAEOnGVeUincngy88nOjSId2oFkhhGVyw8aQeB9CDHS6og2kVxYQH7e/qYLYgUATVGAFkfRpeCjOpx4mKuHlSIdjNkdxHOhClwOxkVXWR0Jw41Q8LS0TNuEvYcKyIJI4iaG8EaRJ+4qRyCjmTKaIqFpE4IBU2LJYdTDCtRpCIBWQbRY3Jy1KRczlJ4ooXiKR9jQBji59Mew+OMIMbLqOm8DJtwgKXGYbYzg7Pyj3PGyG56er/OMbuLsPM5nKURfOVjqCUG6uUpoii0qnkUqS9wafZ3WJoEfQIJ99eJrf8WP5smIwkmMjpC2IR4Hy5lOzd7RdQ8gWy1CEKuSiEFkJYwx72Y/TJi3CDr18iWgi+kIubDuCHQP16IfnIm8mglEV1nma+ZF+atZGdREde9s5aYXSNcWsaJxsk4lSizreO0tUgElSi2pUO8GSrjM/vuQO9UKfFu5oJ9fRgug3eWz+P+tlUUChIPFR3iucZSNMcCALzpCLe98DuOe5YxWy1hl9GOSDWfsoXQ9DTrBJWzOc61XbvZXT/Ok+VeilSR50b6Keoa57fu1ViZyTTZdAZD7VynPEW018eU+T20zpK50DzIDsvJ3uMeujNu3rhFQnKO87GybsaNPPpfm8L4wCA1tmpGii/hXVPj61KAsGGxO65Sd+IpHq8LcXLJRkRLZMXgcpyGg8tYx8+01bxmLuXefc+QnFJIcrSP5op6PnBxkmRqO7F11UxZ38v9H7qbpvpqZnRn2dHfxVJibK1/nLohgXvDDXyqYDLB5CCl0WFOzKrmE66f4Rkvouzg+fjtX6AlP8Cm0SvQNBh0pGgrPMBVx69lyb5XcCge4lc1oOa/yq7191C76AmczhhP9RSR0ce4NVlLGwHO0OfgtBQ63d8l77UUXVfdTHDmrxFO+JhXNgOl+QWOtRbz6Un/wsPv/pSkp5DjV9+IeSTLACaJufncYzlZ1zfCSFLHQuCGdDsOe5LaFcWUlt2M/Z0vIoZbSd3wGqLDR8CRq8dOqyrvzFnKAyUB9HiEoxPRfDAYPN2r3eX6Qw7+fyItn8lk8Hg8/2MU/v+RvWfB/e+5uH8PuJumyYkTJxgYGPirRsX+MbifOk6n10cqGkETCjBTubSA6LfhUvygjeKQHQzEByj0NhDJ+vEEIoy7g+jD7chyEFUdZHS0B3SIuLNIQEBPYlgiWlpG0kfxyh5sopOskcW0DFKpDAjgtHtI6gnUWAyKIe7xY4l+vKKBIfuQTJkhRwYkidpEmK2SA0F3oitpFPcwqYSduFGIYUkUSWMAWGoew0qYqUIDpmGRcReiDGtokhNThLiZi5QT4ynKnRpvpwMIkU68Xi+JRIKK4lIiA/3kzy0nk+lGC1YSisl4MikMSWJsLELAl2RIsTH/vFX0fuMbVIxL6JkWDLmUwdRhxv2judnaIyf55cgWjowd4dqab6EaGdrESqoyrYwCouAiJY5i2dwoDBDKTAbaENwJMCEgpJBMB2GfQWlf7vxibheBeAwhEYEiME0gmySJA7eWRZi5BLdmY+3cBzkvP0wiK+PJO0pH0QmONV1AfdaOPauySVlMfETBUbiTadlbyQpzKel4HHVUZ//sALZWO/GoD0FOU1gwwpDsI6PICE4TQTIRRAvLMjGQMS0FRTexVBEzIUFahISAGLWQUga6xyJaLECxga84i1I68RuoAgOxQjgxE/v4JFJZk4SkgWURHB+ianCIhlSaAcliy6yzKE2N489EaVBauNp8hwp9mHBAQZmfz4FtdRwZXcCzReegVzdTdcDH6pFBhgo9XO8b4dq2VaRdMrdMyXCkeBlYJoKRYPG+tVSH+llfPI+BjI0Vve9A4Tm8aES5Wg1wn91FBTqPmw30XtVJX8ko5+2zuOkdDQpLeGvaxzH0Ol53qUyzpynXeogd91JcOY41J3c/eEVY4jB4oVICElTbDOb4POzoOofyza3EMiqN3iVsCMxmITKfkBU6sjqHExmmHfsV31lQyeCMTTgNJ8sHl+EybFzKOn6hncebxgI+u/cpspU2MpFBmsvquOHyJJnMO0Q3VjP1tV5+cMPHeGfeAipHdHqHemkUxmmqf4LymMLntyo03ahx2DmNCw9tI1pqcafz5ziTLsoOfIQ8x78y5HHwYvoasmmZlCayq/YNlvWfxXU7D0MqQs+VtyFMe4Cjm29h0vR3cBe0sbt9NgeU49weCdCuTaFcLKIuHaLb8TL+dS2MLDgX5r+MEJWpCJ2F9/hj9B338fGqe/no8bcpTAxz4IMfY9uRLAcxcNb5qTclVk8LcMVj+3EjUi1C3uCbVJ4fpnH6r1FOvo7t4JNkVn0bs3AqAJ2dnTQ1NbGjbiZX1VawrDwElJ4etxoOhxkZGaGlpeX0uNVQKISu6//jaPlsNvsnDsr/ZHvPgjtM9Gb/G5oH/K1NbDKZDAcOHMCyLJYsWfJX/aj/FtwBPKF8EuExdHkyVjq3f8lnwyl5IJPGpbjoi/dR4LETzrixSzHGHU70oWEMwwsMUlWVR1dXjDEZCgH3hEAvnnFgZxyH5EYSFTDSYKkYhkUmHsPp8iPEx4hHI3hEi6g3QMT0UqGNk/IGcWZd9OWpSKEQU2MjufM2giBEcYU6iPfMR3LaiBuFlNjGECwTeyKfbscAQcuJZBik7Plk4zJuW+5GHU3njk1PaFSVy/TG/eiJMEFn7vdyBUMMNR/H5ZxOOLwBqWYJ3sPj2CaG53RFYlTZZLZJdhS7HaWmhtJhHTLN6O6VpGMpIqaAEaxAGDlG4+TlvNr+KrOKfDCa4ZhcxqLsVo5bJdicfrC3YhZOxT7SRk3iCixrLVagB2FUpkaOMZypoLvwOEuODeDWdfoKSvElYjj7jpKutjAsMOJ2vEaaUcuHIuauU5krxvCYnVV1zxAO9LGp6cu8W3aS77bvoll6hle0rXSbFbQEZ+AcHqYws4qv2hcxJNi5wPw6mYCPs55qYW/xVJZN6iXrc7NBWIic0ZF1DZuZQUNirTyfNquMD1c+heDPoPhT+AvjhJQkkjix/i1QdYGejINMz3Tc4cnY4vmkLY2skKPavfEwxQP9FA4PU2n1sbW0np1T/PiEBuqTKZr0FK2Ti3np0LexLJP+Ygc7SoOMKU6eSJ+Nc9zFjKYTFLifIj/mZPmwjzZ3DSFhCnJ2Cq/XOHhksg1d9CCYJpP7D5PUf07Up3EsfBVdlPHZ5idZ0nqCVn8cuJz17k6WZcp5v8PHJGGUL0cuYnbSz/Ub3kCyRHaX3s24VsKzHpWP2Y6gyja0eCcpS2SgK0gwm2TMLGad8yx8+VEWWCoxIYSnV6ZszSai4R6itgDu0ktZJ+fzUcGFSxDYl1QZiwzQ0PoU951fRbxqPQXpQhYNz8dlSlzAer6tXcU+o4H7dv2aWI0TMzlOa3ktV14whJbdTfTdKqa+0McjV3+IdUtWUDquE8nGqUj00ln7JJWJIF95bgzllkG+E/gkBbEhqrQWllW+jistU9b0BfIdXySiaDwrXE0y6cWKO9gw/bdMCc/iX7aLMHiEgVV3wvJfMNw2j4LQKIHq7Qy2ncEz9r1cOO5ATkxFERXOTk1hVDqG6+Aako7JRFe34ZSjCL1zqB1+gki3ky+VfYCKcIxVbe9yfO6ZrDEbOUmGKreNk9Uufj6pmC+8sBvZkkkB8/tfIVAVY/ZZd+NIZXGs/wxa4+VoM248/Zxbt24d0YJiwtX13FHyh5r2Px63OmnSpD8Zt9rS0nI6ddnV1UVeXt57PiI2DON/zSx3eI+D+99qsiyfHlbwny2isbExmpqa/t0e9f+R2e12ZFkmkUicfs+bl08iPIpllxDTOeZA9NtQsEEijcvpYjA9SJXXTl8413hGdWmM7+/CMEqAFgKB3AN6HAdllopdzm1nWAtQ7RpFFEQEyQaqSm6sCUQGB/Dm5aONHCaVTFIpQSLoY6TfRmW6j4QvD29SoadARvT5qIoMomgaI2YxEMXtHWI0UUio3EEkXkog2EdBOoojUkD3pCOIiHglg6jhJJYMUY9Cmy4wlFYotIGQMqgoCGH0SPRYBYS0AQBswRCRwX5s4uUYRoJgfYDkzh6wPDjVDF2yg7kBLy+OZRjMatjq6vCcPI5t3gjJ4M0A9Gg2kqFCvD07mbvskxiWwXCqhYI47PXU8GHVQowXYfdYGAIkQuV4BzdSG76bTZpEaekJPINLKZJS7Asvwl6+CYeR4ezjxzjQuID5x0/gygwQFkzyEckcjVA0lOZYqZexoTSh8gyJSBnTSrtYu/HjFKZWIplL6V9yKXrHTfiNISqSKv0BD3OTT2K4zuSIGGZRYpQY1ZimQX6omyNXyBiBXkaHFer0DprnZrHLGk5RPz1vQIgMcv/ueyA/Q8jXTlQX6FTtnBgvh2glcrIMZyKAZVqoQgZByOkEPNERSgZ6yR8ZwplI0VIms7M+gzm9hlp1FnE8eOQE05z7OCfTxJLWvdw27Ws8OWMF1f7D9CVCPCtexjFpORbbCVS+RHV3Hufsr8CbVDHtBXTkL2WVu4w7Zztp9eUeF8FEE76R37Oyaw5JaSXrK99ANfdySWs787tPMrLATd2O9QzN91HE2bRpzcStCpY5QjxDnHvV5dy1so552WPMHx+ksncd19tkljRcwCt5rZQTJQXcWNVE4ojIZD2MzeFiUMwjODyM0ZVmTHMQkewMFtTS51rOLVaAiyWJIc1gV9og2LsFPbufT1/nRgtuoz5Sz4zwNDxChuXWVj6l3cqYEeRb235O97QirOgoLVWTuWpVN5LQRHz9JKa+3M8vL7uJV884l6KYwZgDik80MVb1FFXpcr70aCuOD+p8y76IsLOWqzvXsXjGOlwZKGu6nwLxfrKM8rzrEqLjxSjjLl6b/nuKE2V8cWc9tDxLetbVHL74IJOzJmpkMuXzf0umcznfVfaxaNzBeZF8tlDExZnZqFYMLfYj5A4/A58M4M3fibWliJXKZjJjIk/KZ9LENH655yGGC6o5ecFNtB2NkS+ItM/P43K7i0NNxzgYUZCBM9QxfHovUy9sIOQ9E+dvL8NyF5JZ9W2YCKzWr19PStN5pXYWv6wuwin9ZZr9345bbWlpIRKJEI1G6ezsRJKkPxm3+u9pmv5/2ilw/98wyx3+l4H7KYA2DOMvKu0ty6K9vZ329namTJnyJw0F/ho7NVkoNtE2FcCTF2KooxWrxoaSyOW3Rd/Ewo2reEIeOtVOFgXsNPXkjivkGmM8bVBRMZeenu3ISn/u/5RiQkQwnQqSZdJFEQ3OPrCJGIoDM6We3u/4YD/B0jKMY1kEQ6fK0GkNBhltFaiJNnM4r4T8qEVbuYjodhMc6MaRynCCchq0E7g8SbBkfIE0o+NVTC44zqSBAYaEQrqVXMmGWzKJGiJRZxUzRxNs8ygM6CJ1vhTRRBLFnruRj0uTOS96HJvNhunMeb6pkZyALVSQJG2OIaulFEfHOBoo4PqJIvr9iTTL58whsWYNM5U6tssuTLmQDkMn7LPwn2yjCht59jz2DO9hJrPZXTebRFMA5yAkJ/eSjSl0McZMPYJbP8loLJ/yvENUmhcSU9ows3ZSykyG/PuYt+EdHrjtdm5+7SlkwyIyeoCygvmMbxtg5pXXsfetneyePZvVZopLj9/LOucXmTN7iKz5O+pMJz+03mLjMjc26eswUEeqZQkli8fQhBfxTfwuLvMwOuAUoLtRIG0miQ4plGlpeqMmUdEHhh3VMYozUYEtXEepGOHo4cuYJKTAMkHQkSYicskS8agGvkgM32A3+QMdeGMxegu8HKiVeHpeAsFRRV2sgXzDhZxUKbefZLF1mHJ9CCsJg4UOCkoOMtU8zIO+jyEmWxjyLsGV3E7e2OdQjSQJ70pa6gqZ37QLZBeZympmllZyZ4MTS4CCbISZw49y3Gzi4vZqYnYFtwFVA6toL3mT7jIXO+ZW8sKZcVYEBK5Z/yLHG5MMFV5It9lGSrOzQKrhCcniOUeIxz1nsz3Uyrk2B0v7h5BVDX/GRo9Qi8Ns5pmO2XjaVCTLJC1m0MQhhoGss5CeYDVx5yJusLzMFGWShsXOhEYkPsyMkScZW3qCR4uDIMKi4UWUJ8ooF/opNDr5uHYHLlXn29sfpmlqGVIsTE9jNVcsOYxEJ6nXK2h8Y4AfXXc7a5eeSShhMOoSCba9RaL8OepSDXzxZ0dxXmzyss1gU/HNVEb7uajmN3hUjdKD3yUk/hTMFl4MrWJwpBol4ubNxnXYdTtf23sm8qEnMGvO5Ls3NfJh+Rn6jlxF2dxnMfoW8BUOUxOz8blIiqdYyBy9hpDhot/zefyvSZz48CKC1W8gvRVgUV4MYyTFlpEGHpx0Iz/d8WtEwWTo9ltZczRGEgt3fQCPTeJ9rgyf2BfDjx0RaOh/ifIVaabM+DLOtfcgxvtI3fAa2HL377Fjx2hpaWHjtIVcXVHMQq/zb3pWSpKE1+ulsbER0zSJRqOEw2G6u7s5duwYXq+XUCh0ugTs/3d+/v8i9/9G+3toefjL4K5pGocPHyYej/+7ZW5/rf0ZuIcKSITHEOfI2AYtdM1ACuYidCFu4Bf8JMwExT6J/qiGZsgUukYZFFzUqSHARFXbcbmmERJLcQthYn4feUaK41IVF9j2IbvHkGy+0/uUBIVIfw/V1fMAENUMpek4e3yFjEcNpiVaeD00l3ndIodrdSKyinN4EHsywwFvA3NT61CVCUfE7GFYq2O+J0V5cojmvLmYcoZe2xBO046gu4h5K2ns3YS3xkG/I0XA283YiJvOcDlljHBQmskFfbspLr6EcDqD3eVmpLMPW1kp8fghsnYPwZiP4ugoe6oacQ8NUW4PsTuWYtX8eWCarI5OYre/haxjFk3JXfTm91AliEgdG1hWuoyNvRu5uuYC3hnX2G/OpDF8lMMImJkihgJtmL5y3Ml3qe2/BDH/UTzFnYhhiXlKPz3pqaydv5ebNuzhicQNbJq3jLP3bKVo568YvHAueZZAtqeBVcIrvGKvZlPmAGcZ87liz3fZVvgO/cVbke1xRFNE14NIWhAtquP0NrHrxFKcuheXFsCjBXAabjKhIVwNTxH8/XRqO9MIWoTMygxT9t/MdqmYsJQmII1hAGlB5TxbC5YFDstBnuUhqNnxjI3h6m3G130AWc8Qd9o4XKXwzlI7u+pFPJaHhvFpzE4HEdKge0aY7N7F+YnjhJI58WBbiZvuSXZk06JlsIY+QSLqLcbmgGk99zIshNEd9Xw6/zDDzaNYB7swFTtpCTbMXMXJAidYFnJ3ghnhfRwKHeRTwxkuUQ7yk0A5W4fnsTTbS1H/Weyo2oAiCly4J5/W8lK2LdNZtn0dpSMtHJlxKxlN5FFfMxdna7nRlsdFqDxLNa9U1rGmfJR6ReNiYw5h92GEBj+u8WEymTSaIJKU3Qzb8onbGpgrhLhNsFEoisQNi71JlYF0mtqe1ymv28KaBUle9nooTAWYPzIPp+liPk1sNov4pvZJ5kS7+PDJV2mqC6FnVKJzKrhu2WHSyQHU35VR/+4g3/vg3bw9fwElCYMxI4N7bC269zVmji3iU7/eh2OhzmslGX5Zei26UsBt/Ct+NUPpwfvJ59coxh6eyz+LzpFpKFEH79RvQJVTfGfv+/Du/RUUzeCHH7mBK5yfYaxtGaUzX8EYms330n14dfhhZJinxRvJ1wPM0ibRXfQ98p6M0XbNJQRm/R5xe5CaIg+20SYOt5RxZ/1nuKtzF5NGjnH0sqt5rMVDHzqXeF08X+3i20UefvjcFhJWISZwaXQbeSVRll72VVz7n0RpeYP0ZY+drmePRqNs2LCB0fIq0mWV3FuW9zc/J/9YLS+KIsFgkGAwSG1tLaqqMjY2Rjgc5vDhw5im+SdR/an053+nnRLU/V/k/h60U32MdV3Hbrf/yWenytzcbjdLliz5hyghn8/HyMjIH17nF2DqOoZHRxEEkkMpfKUeLAnc+MibGNYyOnoc07ITMxopco0w4MnHNpJr4pJOdxIMLiehJxClbuLeMkojI+x1TgNeRE7vJs9eyhgCIGEJdsa7W5h31hUICLgBdzzKaKiKSErizHgbQ1VlhGK5fR8z+pgHBCMxdlbN4K6wzkje2ISoLkJcqwWgQh8kavPj0V0cc7YxS5tBq2ASD1ZT3Ps8ZuNUou4YltAJQiO9XWlmOkc4qJUj9PyKkjm3cvxEM1WNU+k4uJ/i4CRstlbUymWUjBgMFcbQZYUDzcc4Y1klG8cTfHlOLXJpKTNbNCT/WjK+8xhPrKfLyLKwdCrKsZc5d+U9vNbxGtMLNDz9KV7yLOJB9V3ExEzceTZMeYhw2TyCJzayYOgm3kjZqK7fQPGWGzBsQxxP1tBaPYmko4ubn3mK79/2Ec44tANF1Rk5/DjBmbcQa45SvPjznL3ubjYWz+cVfTuLrRksH16ONXwWCg5E/pDusdQESVFlxGEypgr0APbRflR3PTvdSS4HOgP5tNe7yPqcZLkAXClEqx2vZafI8FJsuQlZbrZbdjYlonx8eDNlvf14wj2IlklnocTmBQpHq4o4UhHGZShMHZvJuYP5yIKEKalIZe2cr+xl5tAAriGTsF/hULmXyQMpwgM1dGohHiy9muHqGTjVPoqShxi1lzAgiejuj3LFziHsxeNwKIOp2OieupjX56wgY7PhU00eslzsy8vy2IlGaoyFrFY3gGJyRCulxwqQN7ATSspZMriCHZVbSEswKzmNnpCIYEEo2cw1rrt5Jf0ZamKN7KWbQxYsEqv4qBLgI1i0mRLbNYNNosiYPpMsFnavgN8jUG+JzLUkpgkSQVHEsCz6NYNtqkE4k6SydxMLAxs5vCrMl/M8aASZMzqdmtgknGSZz0Ye1i+kyZjKjc1vMl3o5kihk6jowXeGlwsm7yARyWL7VYii5jG+ddvn2ThrGlVRjfBgP7bQekTjXVYMX8JHXt6Oa2qK5+dkedpfju67irPMd2jIdFLU9E1CvIDT2swzoZW0js5Cjim8W72LuHOMbx38IEU7fo3gK2P7bR/G7n0Nx7Af16S96GOT+XU0Q1yJ81gswnrxfAzdxTnqNHpCTxN4pZ3eJWfjXLoGoTmA7C6hIvIu7Qfzub3xs5yRDXPu4Vdpb5jFzprVNHdEuFywsXaunzPcdjrffIeD2TKcQJmRoCrWxKKbzyM4Fsa29btkl9yNXnc+kBMZv/HGG+iKjVcmTeOJqkJc/wEd/5fsP6pzt9lslJSUUFJSgmVZxONxwuEwg4ODNDc343Q6TwvzAoHAf7kwz7IsTNMklUr9H7i/V+3f6y/f19fHsWPHqK6upra29h8Wdfh8Ptra2k6/DpTk5vxqShRQSHQl8Jd7EQIy3vE88o1cfl4VeoFaYkYjVf4WTngnIw7pUADZ7AChUB7DXcOklDAZu5OaSA9vB5di6gJidj/lzGRA9pM0NCxkRru7sBV4cSl+TN3EiIxh5VczFizEle3BcDqQTR+yMUqHO848SaJueIC1U2tx9DrJlsVwFpwkHi0jYeWTMv1MkToAUCJVHHW1cW50MYphEPXXkeqyE3B66QV64tnccLi4zsw6Bz/qLEJFpdyZYVcshq2yhJEDe5l2+SVEEt+haEk9iadakSwvnkySrVmDy4MenhmK0JFR8Z9zDubaNyieK9HqmAKihwOqlzOLPJTv38pC90OEHCHWdr3KMmMZ62Ys5ys7f0OwU2Ns+gCpERdHxS5WYOBT1uLoPw+pbg2VoTCDcZ1X7V9if6KMp88S+Pgbe9nesoxdn6th+Y+aKevcRWvhVBpKFjO+e5S8aZdyfvfj7NYW8lbBSfzJNNUJO0WqC1csjDV4FGm8lw0Vs3hm9vlUm2OU2eL4pTTxIgHVPswUe259ZO0BnCmNonCS6aWbyWZWE7LOxC7IqKbFWCpOtm8Hywd2clWkD10UGCoq5OWzHRyuKGAoFCNji1MVCbG6dzFO04EgQNY7QH7lIVbq3dR0pXFmDUbybRydHCTqNSj6msTQbBv1BR1cNvWHiPoI17d/jQHrBAedFRgl96OXfIbPvf4a+S0RjkWqkLNjjJ8xjd/Xn40pCswaSXDzge0s/9eP8dzab6O4Z9IZuZwRx36ai8rY3TKXTxTu4uw129hy7gqwyjijbxVbSteTTO3njP15DPtdsFqkxmzl/Lb7OZpZztFJlyFlClnv6EW0sszQyigXndyAgI1/c28KoGMRNy3GdZ0TmkVYF7Eleijv30pNYB/HVyZ4OF+iR/FSFatixtg0bDiop40+Ictd2Y8j6yZf3/lzRid76EuY9PgqmX++RXnwLeIjHkKPOBDiGp+/67vsrSmmNpxh9PhhpOo3kdNtnD/wAW7ctAV3fi/PLDN43uul1nUbRySdq6KvUHrwG4Ss1/AKb/KbvBW0jc1BSUrsqDjCiK+Lrx25mcotz4Ls5NANt7PG186t8a3I/iRarJw3hv2c8BziwXCGAWMKPXoZK9UGop7teLa/y0jRfISLtyOMOolES7gq8y79B/3cVXcnbtnBx955lLg3wOgHP87ruyPMQaK32kvWKbGkuYnnR4M4EchasLj/FWrP8lJXvBrnM5eg165CXXL36Uu+fft2BgYGWDN7BdeX5v/NdPwpMwzjrwqiTqU6fT4fVVVV6LrO+Pg4Y2NjnDx5ElVV8fv9pyl8t9v9TxfmncKMdDpNKBT6p277/5e9p8H9Hy2HOzXNbXBw8K8qc/trze/3k0wmUVUVm82Gr6AIUZLIEAEKSPXmWs0qhW68vXm4tSQO3YG9II1NFhnNVtHo3cKb+aswuvqxlRWjqoP4AyLGUYNhdwQyMEkdJW7KpOI2FLGDPHsIh+QhZY5jWjrxWIpsOkmev4SxxDiJ0RGEWpOR/CIGKKIx008sUIg3NczJcg2lqoIzmg+yduVyYkYl0I2/qJne7kV48+z0ZWcwpfAEoXSEwEAtxybvQkQkIBuM6jZG9FqWp0zabCLNGTtzAirJbJyygJ80dvZKc5iZOoQgSAxldLAslHQ5IFFSEaXF6scZX0r16ABbKuv4lmDgFAVeH4tz26pzif7mN9yoncd3tC7SriXsTGynLb+LcsWJ49BvuaL2Cp45+QzfWvw+3upK8LR4Lh8JP80mrQZBtqMHh4nKc/GLL3N21095o3Q9NTN+z6TNH2GPbRaX8TY78s9kf20bH3/+p3R91UnPZ2Uqv6ZTuftxTi6E2uLFyIMzCHjvZ3HxIySPHqTNmMyR/FKalAzggmkLgFx99wW0ABAQEgTRGUtVkWeK2Gu2EdZLubq9EKlgKjavRim/odW8ivaMRfvIHqp7tlM2dhwnJk2TXDxRewMd0ztYqBWhyWkGC7YzbWguVal8BFnG45XQQ1spL+xiWipJbXsWXyrLSJ6dg1NDxD0CNl2nvMXkp+fdRMfUWl499AluPfoCC1O/5uvF+aSkPJKBa6lVkgxmAmgROwenFOPqbmZsyiweb7gKBIFrO7NcuqeJg2NbeGWNi/3aPipDQdqHp/Ip+9fxxfYRUKJ8MvoTInVOGqZE0ZImjJVzRu95bCvbwJtzR0mTT9WQgzn+bvbUT6FwVzPnbPk6/UWz6Co/i4y7mh5BpF1IoQtJnIg4EHOshCVhWDaylgiWgSfeTX74OGWRA2TqorSsTvB6EDpsdkqTpZw7NJWA6sVFills5lf6Wew05rFyeB/XNb/JgdpyxGSGjqrJXLl6FNnaRvRkCZN+GWfIX8D993yJlhIfim4w0NGEq+JpnBmLS3vu4rKj63FLR3niPJNX3B4+qC/j+8GZXJN6gSlNd1MgrcNvvsJvgitoC8/HlpbYW9ROT/A4nz/5Aeo3vwymwdYr72RYOcCVti0oVgItmc+O/mre9W/nyxGTwqyHF7Ul1Bj5+OUxjO5nSKQaUD/UhpSBzIkAV4rvMtbs5qtlN9LlqubBLc9i02K0ffQufrA7QQiRpYqTH9Q7uCI1xt6TY/Qb1QgWnJXcR3nRGMsv/AHOFz6I6Sogc8EPQchF5p2dnezatYuehlkIBYV/Fx1/yv7eOndZlikoKKCgoADLskilUoTDYcLhMO3t7SiKcjqqDwaDKIryn2/0P7FTmJFKpf4v5/5etVPlcOl0mqamJizLYunSpf/UHM4pzy4cDudGwMoy/qISYmODFAgF6MOpHNUkZ/HZ8yF5HK/XS+t4C1WhxfQlSlgQGGIg4CfTvA/PeVMIhwfxuGOYhkmPIlNlqXjlnHiuL53PJP8osmhDVFxY2UEgV3I33NFGQXkN/YfeIpspo9HSGC8vpOuYxPyxPXSWVlMycpSWMhGxNcCsk4ewqSp7xGnUap14fWEs04bfn6ZvYDor8rcxtaOD9mAlw8prhKUoXqfFaNJFODiVZS2beK3aSbtN5bxAM5Gwjb6hQvKFKJvlxcw5+gJe74exeX3kV1bRue8gpWfMw7L2kCguomrQQdTfzuHyOrZv2cHqKTN5cTjKHbOmI5eWsKxJxbbgGRKhm4kl1nNAE5ldPR3//ie48pa3ePzY43QmtjAnUsFjMy/m5sNrCLbZoXGE9Kib41NiLD5ikWd7isq2D2NMf4TCybtoal1Mg9zBp7J7uevMRm55YYjAD0TS98p03ydQ+R2Nit2P01ndQv70m8jXHBidd+MrzBCctJHZwgbUeBzVcqEbDmR7ALe3hrzyefjL5mGNSOx/4Cm85bOo8J8gLvaT13UeSuFURlNxCroeQ28Q6TrSQkn/S5Rnxhny5NNSexVb5qtskxUGE3NxBbdxSB9myeh8Lu65EIDi8iJsZT24bC9QbqhUtxqUhWNEPC72zMoj4vAi2JK8IVzOtL0j3D7zg8Qn+/jgGy+RccssjK/jvrIQWcdsdP/5PNrQyDtvvsCT9dewfvEslrz7Bgg2frXiShAE7jmW5pJuld6CQkQjRM9bb+Fb4qKj6ko+PkngF9simNZsFipHiYYLKZg+wIyQhTlpM29uOJt8oYSze8+mqWAra5YNML3Tx5TxEGcFDnLpiq9yibGV5YeOUry/CQQb4/5aor5JpFxF6LIDS5BQtCR2NY47NYw7OQD6MIkiicGZIodLB1njsxMTFUpSJZw10khBxo8pCMzhELvxc7f6cSTD5PN7Hkcp1ThcHiJu2rEWFXHT/MNksl0k3q5gystDbJs5n0du+CT9fgV3Og3H1uEqeIW8dCUXdt7K6t5XsCe389ClElucbr6klfJw7XIK9RGu3j2dMmUNPuP3/Mp3Ft3js3GoAntDXbTm7+Pe1huZueFNLDXBS2fdTrW4HmFShkKG0JKFHO2YxysFb/LJqMCyRJpHrffjMQVm6j4y0jcRjpQTuyeBIiaxb3FxTuAAsS4nP3Oczyb/Yr52fA+lIwc5csklPNxXgo7OnYaDh84OUIGOe/cONpuz8QBBkkyL7GLlZz+O752vICYGSd64Buy5FtqJRIK1a9cilZTxRlEVT/+ddPwp+2e0nxUEAbfbjdvtpqKiAsMwTgvzOjo6OHr06J8J8/6eoPCUPuD/wP09bJIkMT4+zqFDh/7mMre/1k6B++jo6OmxfMGSMsb7e1EdcxCiKvv370ckTbnoQomlCOQH6Eh0ML3YQ9twFsrB6wsztKuPkOd8wuFN2O29AGTttRQxiuXOKeYPCdVMdvchuMCMerEmgF0QRIbbWyhubGB/0+uIaoaZqSjbC6sY3mqyNHqAdRUfZuU2iWM1Bp1ShJJEDG8kwXrvLOZHXibuGkO0JUAfpFedjiRaNKQ62V4yEyc2dnuOMD82i3YsxgqnM6ftBZgyjYirl5TWAcJ0on0qy4JxNsUncZ+tj5lzS9lztIMVC5ey79UXmHbJZXT2fJ3Ccz6P55ljHKv140/FeW48ya0FAV4a6eZAKkvt1dcw/vOfs3RxPW/LBej2RjalBlmeN8r85jGKW9/h4uqLeeL4E3xm9i+4bSDLY1zKHSNPsql6Mq6Ag5TUz4B7DqXxN5k/tILfFtQwbdLbzB6ezCvJ1dwiPMPnk/187Yogd7wQxfxxkOSdGbq+ZFH2sEZR11b03j0cW/wJygP1eDJOpOMXkLUuwC2BwyciuxwIhoA5oKO36AxHu1BNg/rJq5AEge7ynZhYDG9VEHb/K0fqJ7F8qJOWk0UUCTsZq5jF16uXM9s/hF1VOJx3mJgtC4nFLO6YT41pok+k/cpqPXiLHqZAShHsU5jVEcMQFY40ehnKKwQ5ij8WI9hk53cLrsdcKqOkjzB18Bfc2rSbA8tsTLe68ZtX05p/Gx8r9rDnjQepPOyjNtDP4fJ6FhoZfnPVx0CUuPVogqt6VZIVWyhZeDnvvroXV8cIC05MIlSZZlVZIW0Vu1jX1QhyISNNJtoCLyVNb9JQmUfzkmoOHemkOFvMit5L6VXa2Fe1h7sqFW6Iuvlu4gF+nL6F7qJabNV9TNLHKRqM4IgPkRfXmJgphGpTSNhsjJU6Ga0y0fNSNHlUTtht2AwPlYlqFkdrCWhOdFGiQWwmQowfqJfQZZayun8nl7du5EBDJXIqQ0d+NUtXGZT53yY+LmN7qpC6w8P84vIPsObM84g7JHzjQwi9v8FWcJC68DIW9VzFpP6nsGc38Y3L7TTb7XxLCNJUm89xYTofP3qCmcpafMarPOJZzUhsCm7dYlewh+aCPdzTeQOLN2zBTI3y0jkfo6r4EK2lCoul7aixItpbz+A3Jb/n+qjIddERfqx8GisdZ6laS6Lo2zifCjBwrx27pxPPqy7mFHaQHpB5NTmPx2qu5N7IMNNPvETrtJmsKbuInsEEX7McbJwXoFsxuWLfu7S5ZqOFQcXiov43mLF6ClWdW5Hb3yZ9+eNYeTmtjWmarF27FgP4dfVMbi8JsuDvpONP2X9F+9k/Lqerq6sjm82eFub19PQAnP48FAr9mfbqPzpWSZJIJBL/a3Lu/3N6A/4VZlkWmqbR2dlJQ0MD06dP/y8RYjgcDjweD2NjY6ffC5aWEe7vRfdK2LMGlmUx5czZAHhSNipsFQxrw1QX2GgbNTAtmXJvHycNJy69ErBQtSZ8Ph8lYg1+cZRwQYjSTJitrrkIItis7eS5ihEQABFBcDNwrIniedMA8Fng7emgz1NKQrMxdbydwcJyQhEXgiVyQOrFAupGhtleMJNATCbjDOMpOUQ0KhM1SokZRcyxNWOIEr7Byez2Hibf8uBBJOaexOhQAbMlL4IJRyMKbreJKcYpl9M0m6W0irVMs06QzWaxFZejqyqxrgCCoFBZPYIl9pA3XsLUgS421zRS099NhV3hiYFxvFdcjmWafLirBiXye5K+i2hPRdhnpkhWz0be9gNua3g/KS3FtuZfM2+4lx8vupbhbDVVx1JYcj/Z0XxOzGgmIzWS5/wBlx37OC0JF7Z5v6JBqOZ3XEIJUe7LxHjkSh+e/nGKv2kSpoCRew0i14AipSnd+gCZdXdxvHcHQ0YaC3BYIMYszME0Rl8KK6wiqSY2hxvD7uWkmmb7jJ+TLt/KnhMzKdn9OqossqC5DdMQiMzI58Dyb/K7OTfRGihlf9lRXp39DKqcYm7nFQAUOF1YTi+TyxvwhsYY6hrDituZdzzI3PZBhvID7FjgozeQD2KUurYk2W2VXFv/YyzBxDv2S/5l/DnWtazju5c4eanASbWms2o4wGX5PrbuPkCoyclIkZt5fYNEXW42LLuIkfwS3rdhMx/pMYn6OxhrfJ6SWg9Wg4Pd/4+9vwyP68qy//HPLeZSqcTMLMsyyMwU20kcZqYOQycd5jjcYe4wOQyGJOaYmQSWZDFzlYq57v2/8Dee6X/PTE+mM909/fzWu1v1yOfW9blnnb3P3muV2Env97FUKZKbm4tJN4qAyG5fMl8mzmcwqGHQkklal52z+jbTFnsYCYmITCRNymBJ6/kUuAv4JNbA5ZlaQtkfoK78lmBmP0dS9Wwoy2XV5BJWzy5m1UlZrDvVzKbTAmw4vZcP5rbzSX4P31hkeMPZTB6czMntpzB+uARD1ECOrIMM9vNZpJwnAteh8UR4cctLZMu7qE6Pwx1W0j02n/POHyDFtA5HYyxxjyvQtYd59OYn+HL+SbjVMoz99ShtT6A2NjCv+3ImdJ9L4sgKSuSbuWuJlkGdjuVqLbKUIT4OX03eyDA3eL7DFF3NC/plDHuKMRFlj/k4sd/RcSFTNu5BdPbw9YyrSU6sZ0AZZFLSFkKuRLobFvN20ncsdgvc4hjgFcM9hANOJoQyCGQ/j+5TFb03JKOJb8W8Ukdx4gCSXWT7YD4PZl/LpUqYtvNt7LHx1J5+I1sHPNyIGpdVx5pEGeO6mzHrUjloh4gEk3y1FCa7mJGRhergnwjOfphozrwT69fevXvp7u5me8lEMs1Gbk75n6fjf8HfQ35WrVaTkpJCWVkZM2bMoKKiAr1eT19fH7t27WLv3r00Nzdjt9v/S/XSX8jd5/P95l7u/yj8U0fuvya9Eg6HqampIRgMkpWV9av7138t4uLiGBkZOXEdn5nNwdXf0h/qo0iIJS6zBHWcFqdSwiiZyDMkszm8Ga3Whj8s4pbGUWjpodGSwdIeFcjA46knOfl0ArYAYdUQPmkMpf1tbE8fTzQsoPBsJJsbGFLF4wx7EJEz0NqCNt6ESW0l5PKg8zgRBTkDiak4RQ/ZogNPbComr5Mj6Q7mtyex8NgR9pYW4Y3kgqyDmLQjdHVOxhirpC1QxbT0TaS5h9B7SzlU+R0hIUysOojXr2LANIFlLTXsS1VTJ4tQmXiMdo8ctZSOAT+rVQu5teULEhJuoq23j7SScuq3bKPs7Dl4fRvwV8whr8mL3XpcO/79fTVcuWgBj7UPck9mAobFi5Gv2kXpTUYOqc8hqspinc9BZaKdqs5h4o58zVTtVNY71vPHaedxRUuQByyX8CfXo/T2lUHKKCGXguoSmHg0QpL6BabVPETdhPuIm/oWcdt/xydykYv4lkdCIR4/K4VT1g8z9k4/+68uJGVGK55JcmLWixi3eEmsfh8kLTVFlyDKNSjVGpQyNVG5moBSj19QIkZHiB2/gkjyIPGGIUJbTSz7ohoJGI7RkqxxkDzFwQ7bfaiNTjYpRRTqAUKqEZY1n4/ZJrLfIiAXo0weW8pQ749Yst5FFVbRcmgZ3roqNKzhcKmVUYsGSRZF7/cypsbJ58Mn8+iim1CF+rEOPoxoOo2b6z5lcc40BqVe7lslQjmU+LuR925jyvrddBSmo/Ul0638gewuI7VF45ht0nKONxOUEOtOxS3X0NX9HG3KCAMJAhFjDLu/+Ii0kjJ8IRG1PMilUwp5i6V4Ayqetr+PLVaJZaiaTwSRDxSDeMNJDPuUZOClwFFKrm0MIxob9pg69hqGGInpArr+w/fLFFZgCaaS4oxjTDCeOJ8VbSRCUCkHGRQLLbgEB6vCU9kTmUBqdIi7Dn+ISeukNs+CyuekNSGHyhlhihK2EPCECP+QTvGGQfaWVLDi7JuoSdQhkyRM7T+gkn+NSUrkjOZb8IdiMbu+JF+3iVsnGkjRarlZF0SucvHt0M04k0y82/kqpuh6/qg/C583BQuwzdBLc9wB7m6/mPEbtyM6uvhi2lUkpbUyqvRTWr6NsCuJjoaTeCdtBVN9Eg/Yh3g2/mHkA8PkRuPR5L2D8d0IPVflo8s4guG7GDKSbWidAfa3ZnJzyZ3M1UrMX/seEiHqrrqTd+pcnIqSPFHBH6fosbiczPK6+KQnFRMiSsHHeOceTj3nVDSb/kCo8nLC46448ay7u7vZvXs3vuIx1Btj+T47EZXsby9Y+3u7wgmCgNlsxmw2k52dTTgcPlGY19DQQDgc/gsd/F845hdy93q9/zLys/8SkbvL5WLXrl3AcdL9LQos/hqsVusJchdFEVf0eD5Rl3JcHc9RP4ogCMjiVVhUiaTK4pCLcjwcA2AgMIFCaxdNCTlEjrahUiUiSQHi4tREnVHaNXYACoL92KNKnDYdqkgTZkUsGoUZiIDoJRgMc3jXDkzmNCT3KCGfj+RQgMHcdFo9emaM7KIzs4DMARlHM2WEzEam79qEPBJho2w8Gn8Ui+n47zDrRmgPVhGj8zHO1kCfMp+ALMxhfSMJmgiSTGIwZSKZDX3IVXEMmoMEoy0gSESGBObG2ljtKgBXH2VJKlpaWiiaNZ+B5mOoIvPw+9sonBWP2XUQtT+Z4v4OPknPY3HIi14u4+0+G5ZrriY6OsodXaWond/gjjmfFq+D7ZEIw1llqPe8xBUpC4nTxrGi+VWu1EisnjCXb0KnMKntKEJQi8Zgwa23cyw1H5V4lJzICrKP3MMoLmKnv0O8OJb3ORc9EZ73NVE9L52vpsuY+Kc2NE8YGLBn4zpZpPcZiaEbZYSqPJTY36Dk2FtkNH6EtXUFCa3vkjn0BIXK35Nf/BCWrFoSGMLwvorkryO4lVo2VCwmX7SRONnNT+IMvsvdwKOZXxAIW6n0ijzRcjOZOj3exAgjooZEQigMy8kp2kiTN4ZZw0VcEP6OXimeFSkTCaSWIsmCxNqCjNvj5pHgTTy05FYswUNY+57keikLu24iN+ZnMyD14rTegD6QSDBiIINeYj/fQkdBOhpvAlmliaR3JJDV1UJUoSRDbEGviMUb9CKElYjSmdjt61DRhD4aSzApk3AoxOZ3XkMmiUjIuH5mJpd7D/ClZgE3xr2KdlRGRKdCZc7i95EvSBEGiNeG6FSaSD/WTFZPD2leE8XD05nVfQandpzKwq6TmNMzl9m9c5jdN5tF3YtY1rGMRZ3LmNE5lar+DFJ8ZgSZDJ3KyxT2opPX8EF4Ao/4b6Y9lMPvj3zGw7v/xGCGmgGdkmGVlb5JuVx0Xif5cWuxt+swP6Ulc/MIb555OS9cdgc1SXpUIQ+m9kdRyb9ifHAG59XdgS9qRe1dRbJ1DbdOMjLZaORyqxtdxEu0bgGrE6dzft9mKjyreVZzEX5fCrGSki3GNprjDnBf+8WM37gV0dnN+1OvJDajm6B2lNKKzYQc6TQ3zuPd1M+pCER5amSIx9MexTjgxChpSM5aheETJ70XFqLLP4JuZSwpiW6sPid1tclcU3QvlSY4e8c6YpxNHDjrAl5u0lCOnFOiSvYsS6QlHGVpTxM13jwCUREXMLN/A4tPm45124NEs2YRnP3QiXXM6/Xyww8/oE9K5qO4LO5Js5Kr/W2U4/7RxjFKpZKEhASKi4uZOnUqEyZMwGKxMDIywv79+9m9ezeNjY0MDw/jcDiQyWR4vd7fLHLftm0bp5xyCikpKQiCwPfff/9n30uSxIMPPkhycjJarZb58+fT3Nz8m4wN/wLk3tPTw969e0lLS2PcuHGoVKq/2dP9v4PExETsdjtut5v9+/fjjYio9XqiCjeiBL7W4yI3mqxYYtXJyD0eLCELTaOHyIjV0urMwazspSsuDl91NSbTBABM5lGi4SjNqhjMkhOj6rhKWW0wC43BiaAFNEYkKQSEERBoO3KQ3AkTCYZcCKEgU/wOejKK6BmMMH9oOzVZJWQOqAgrojTpbai8HuLtDr62TCHeFiaqHkQb14zXN0J/qJiAZGKKUItbZcA4nMVm817SpBiMyHAashkeSGImehQRgYN2FbFxQULqYfLNGtrERPbqZ1Hu2kw0GsWjUGOIjaNtdwd6fQlqzXZG0yIUdKjIHunHr9HwxdbdXJUSyycDDgbjkzCeeiqJ3+1imtgBqkxC2kpWOY0ciu9B0hgY0/oBd0+4i72De8mxtjHGMcz9U66iM1hEWY0NUbAjReLpy+qg3ToBPZsoC6wjtfoP2AUHxhmvEFVk84F4Ed2k8VBoD9NSzDx/cQytJh+TH2vD8JCB/toietMTGb1QZPj+CCPPuXA+2kPgzmME7z1G8MYeQqe58WYr6avNxfdqHqb90BKTxsoxs1ncvYb0mXaaVToezW1nSNeHqutiEsMOTo8xs1VfjVMRYt78GfQJWsbnbCXsUlJzaBzXt4Sxtu8klGoiM7Oart5yevtHyej2k30ozGUJj/LZ1FPI8a/D5PiQhzqSOKvjJ7TudeyORPDEXopCnUbZ3KX4+wXSpV5GMnJRhswE1B6GagWM7l4G41Mw4+KroQhmASSNHMnWwoGfBgnIs1hs6cMYVZOdGIc7MYO+xqOktvQSjKio7/dw9eRs/nDgUzb2mzlV/QZHgomYbU3UplUwV/E904X9JCq99BdkM5AWg85pI6++gfLaI1TWNFLZMMj4Y27GtAYo7wqSbfcSE/IjyiT8OgUKXYSxsjpy5DtoxsvD4fN4zXcNgZCBuw9/yLPbXsSRpqAm1Uo4JHGsqIC55ys4dexaPI4WfN9lUvS0Ha9o4LHbn+WbOQsYNMjROhswDNyIUnRyU/BuJtWdybBeicn9OfLM73i0xMTvzAbmxdmI6w+SXn0yT6QvxRT1cn3HW/xRdRmRsAlLRM9aSy3t1hoeabuCsRu2IDp7eWPqFcSl96Mw91Ncvo3gcD71x2bwScq3lAYjvDAyyKOZj5PXEcJPiLyUQ5i+7Wbg1GL0xQfRrI4jM8FJsn+Ypv2JXF16DwWxCs45VEdmz2b2TJrOG8ESYiW4RdLgWZzCh0E/VQPt5MRWsH3ES1SASk8d80pllLS9j2hOx3/y6yA7nrCNRqOsXr0aEfg0dyxzYvScH2/6y8Xuf4h/JstXQRAwGAxkZGRQWVnJjBkzKCwsRCaTcejQISZOnMhNN93E8PAwnZ2diKL4N4/p9XqpqKj4T61cn3nmGV5++WXefPNN9u7di16vZ9GiRQQCgb95bPgnJ/f/Ki0fjUapq6vj2LFjVFZWnuhf/1s93f+7SE5OBmDz5s2o1WqmTJlCQnYeI13t+FUypMHjxjKqTBM6hZFo7whx4TiOOo5SmWamYdiIIEgkWPpoau3HbKwCQKmsRi6XY9KMI0PowZ1gwRp2s14zGblCQmuow6hLAgRAQJCZkNv7yZs/FQEBqySRaRugTZ+OR9KQ7bDjtcSiDVtQhXUcSHCCxcKMjlaa4jLR+NOIqEJYcrfhcGSi1itp8k1nQXo1loCL+I6x7NbX4JH5iNced6LrjZ3KedX1WDxaanUB4mP3ElX68HQIZCnsfOqfSkzHjxRmpXDw0CHK5i2iafd2LLozcTp3kjgvm8SRfSiDCRQOdPFWai5nhjyYFTKe7x7G8rtrkHw+bq9ORTvyKu6YCxmNRvghEEt7cQry1o3MGOrgzLwzef7wc9xVYUEuCFxR9AfUHjlZtTLkukEiriTaS5rptExBz0+M9f1E0YGH6fRrKZnyGtHEAKvD5/Mti5gqtvN6oAXVuESeusTInqwAZR+2UvX7fvT3mbB9mk/P3rF0tVbSNVhJZ9MkenZPxfF+JdZHNEx4pxutzct7pYuwxUjcaPuG7HlDdOniuT+miBntF5HbejtWwc9p8b20+IeosORzyulJ7Oj8EwFJQ/Kwm/idVdzq2YzoFTlYlkZPXoi8Ah8WywCtdVNRNBi4IOtpdhePI2P4fXCs5CXddE5RbGRLBugdK/AZlyKqsonXpWKcOJnAsEACdpBL6FTxjBoMHFN2EZXJMJZW8Me8Avy6TI5YFbyT8i29yk7GHq7lq6YsTPIocxJ6SDYayB9fRSA5C0XnKNNGd/Px3nYMJy1lbrCZp5tfQK7ScoHrYX6nvgH9wChywtQldjFG/Q3jhGpi5R6c8fG0lBRTWz6WuvJyWgpyaM/JoDc9hYHERDDJyVT2MkG+k2TlVjpkw7wdmcFD3ltYH1xKobubP257hQd2vsNQhoF9mclE/UGOZhaReZqVi+btRi9bR1ubGfs7MjJ/HubLhafy4E1Psi0riaggYhz8AL3jKeIcE3hefJLwkSTaEiLke16mrXgDq1O1LLeqyDGOkH00TGLTjXxqKuFoUgZXd6zgQ+Fc5JIcc9DK6oSdDJpbebrpd5RsWEfU3c8r0y4jMWUQS3wr+SW78PaVU9c4g6/SVpIfCvHiyBDLM59gWoucHpmNLGsP8ZurGZpVhq7iIMofk8iPdZAQGKZtdxzXld5OSryec1ocFB37nMa8Qj7JO4NIBJ6QdAzG+3kkMESM38u1iZm8fmAIA2AW3SyI7uUkQz2IYfynfXhCWhaOR5b9/f00VE4lpNbyRFb8b9o//vdOy/8ayOVyrFYrBQUFLFq0iDVr1rBo0SJCoRA33ngjiYmJXHjhhXz00Ud/Jlj2a7B48WKWL1/O6aef/hffSZLEiy++yP3338+yZcsYM2YMH330EX19fX8R4f9P8U9N7v8ZfD4fe/fuxe12M3Xq1BNGBfC3ebr/Gvj9fmQyGSqVioqKChQKBQnZuQy2txC1qFH7w0iShDLj+MukGI5QYizBGXWSnSBxbDBEhHgKLG1U61Iw2BIBcLt3kZqaSlI4BUk5gMtootzeyqbYaYhhAfngSgqETGLVSQiCGgkZA23tqMw6rMZU1E4Pof4eZKJId042bZFUZrpr6csqJnNAy+5iBVJ6KmduXoUkyNghTkIVFLHG9iGJciymUY4FZhGn8zJ9+DBt6nJCgsRW00EyVHIkCXrTZ6NsCBFjSMOti9Bkd6FUAqKbxalh1vqLGVZnMElWh91ux5BbiFKtoWOXC40mnVjrDkZT3BS3qikY7CGgUvPWtr3clBbHt8NOGowxxFx9FapvN3C2TYEiOoon5hy2uAL8LB9iMC0BxYZ7uD1tKVmmLJ4/8hBP5sfSlZDGtfF3kG63kdBoQmkeIOSIp6W8mfb4iejYSlH0VeYfuIMjgwVMKvkW89gNdImzeU26igNUcHaklreDrRTnx/DlhYksP0/J5pIAoYFesr5vZuxbR5n8xxrGvVlN7td1RHqG2JZn5fW5OfSkernBsZILcg6QMtnBIdky1J63uLb5HmSRdOK1dcxUtZMsN3OKKhfLxM/p7nqYNU1zyaCPW6wDzDC+T5MwgV2TRIIJBuQKLdHgEGcF10FU4MWYq2nIySNn+H0iwV28kHE+E2reYn9SLM9jJqwpxW+Yw2nWGAbC0JGsZFCMRSFEKUneh5Nm4kbjESOd9CRlcnNuGrPMOnL8Eu/lqGhRd3LblHW0xfST2ZLAaruFUquNXt9a5i+cT3J5JWQkM85ZTWTHN3ijYH34CQqODvD4kTu5eYrEwfBkFnmW83vuJcY9kfgIdBsP0xe3FoXla+K060lXbyFbuY1M1Vay1BtJ1P6AVruObkUvP0ppPBc6myfdd7DKfw5SRM1NzV/x6epHOLvlZ+qLE9mfnozo9dGYXohpSTJXnd5Ibuwa+ntFPq3W85LSy88lOh695Uk+WHIurXFaVKFBLL03onS0cHLvFdwhu56mIz5a8l1Mc9/J12Ma8CYouS9RxBRyMeaAHE3fEzTJlGwuiCXH08nIYBIaeQidJ43vUtbh0g3yYv11ZG38hqhniFemXURS8ghpqTXkFB7A2TGVo40z+S7nK1IiIs+PjPJI1jOc3GymVtaJRT9KTu1WRsaUop14EPmGFMpMdmJDQ3TsiOWW0ptRJcRw9qCckkNvMBxr4e0pV9LrifKCpCWcqmdtrsCgxsCVfjfvrB3CL0h4kJg3uI5Lyt3IR5uPV8abUk6sXw0NDRw6dAj1uEmslet5Kiseq/K3LcH6Z4rc/xpSU1M5/fTTkSSJ2tpavv/+e3Jycnj11Vf58ccff/Px2tvbGRgYYP78+Sc+M5vNTJo0id27d/8mY/zfePL/DsPDw+zevfvEg/j/71//3yb3XzIGra2txMfHEwwGT+x2k/IK8TlGicSFMAgCji4PMp0SvzqIWYyl0lqOIAmgaScqSQxF5jM+qY3qxALE6i6USiuRiIOUFDOSXaJJd3zHWBLqZTCqxj6sRxmuwaAwoVHFIkkhJNFBVBTpaagjLa8c32gf0VCIST4HPcVFNPdLLOpbx8G8MeT1KPBqojRpHSR2tmFxOPkwZjqJw2Ek9SC6pDq83lGGwvk4xRSWyHfhUelI6hjDhphdxEg64pUiIYWRrugErul3EONWsicskJV1jKBmmMiAErUQ4V3pZDLbPiUp3sqhI9WMW7KM+m2biTNeTii0j/g5KSTZ9qJzp1HR08KK3FImdLVRqFNzd+sA0mmnEbZaOWeNjTzH+wT1s4moi/jEYWFvWhSvWkK38hqemfgAzqCTr9ue4a4YGVtLJ3JdzN0UDfSQ0GhGFTNMxJ1IW2E7RzPHoJB6SFfcxRVHF9PReAZxhgGKZr6ImDbCwfDZvCRdwxamMEHs5xnfQd6QhpidqSEwNZaNZ1t45Woj992i5u5bo/zxOj8bzh5EnNrBqUmNnF/WQdYMOz2WJD5x3Mch21lEBBGZwY5e1UKMxcIZpbOosDRgm/QIfd563jm4mN5gGo/rv0Y9WE9z7AL6ZrbgdRQQiowiC0lM3NODvz+OrRkVmANelravwhXcyZWyhVRte4ohSwyPGY34BCMuy5WkKCNUxeYTlCRWf/UM+7KPZ4UKLXXk5h2kxxxP8lAXnrQcJho0CILAWV1h9lkVXO64kxnG6bx6ipxOzXoOehJodOtIyqnh7h0Xkzk1E1NBFeFSA/nOZt647x6ieflYHn0I/WGRea/cwZu533D3PA0YUnnEfgYXeZ/hFftz7B35A03ui6kNLeZAZBZbInNZHTyF932X8tzo/bw2+hCfe66iURpDVmiQP7R/xBerH+LB9W9jNkVYO66QBpMBT0hObXYpplPSuersLsYmr2RksJdNh2N5IuClSy5SMrSAmoqn2ZGbSkAloHN8j6HnUVQDc3ht6DYK5JPobHAyXNlIpff3PFcSZHacxAXxIczNYcZVxxJ0vYBT3UdPyj6qTUWUtnRhVHkRRvP4NutroioPr9T8jvjNHxEOuXlh1gUkJo6Sn7ubtNyjDB87ifqWKlYVfIBcZuLlYRuPZD3HZY3x7JYdQ6H2M7ZnLY7sUjRTDyNsSWecZgRjaJCu7bH8oew6vAkJXBxOoGjP60SFMG8uuZlGt4wn0RLSKanNHGKDKYEzFCLDBzUclItEkRjvPMzvchvQDR3kaNk9dIZj8fl8J9bQ9evXk5RXwCv6BK5MNDM75rdv//pHn7n/GkSjUUKh47oiMTExTJs2jccee4x9+/Zx6aWX/ubjDQwcN+ZKTEz8s88TExNPfPe34v9MtbwkSbS2ttLe3k5JSQmpqan/4d/8Wk/3X4NfhHEApk6diiiKf1YAkVJQDIJAQDMIxGE7PIIl00g4XkG8O51oJIo5ZKbVvZ0Y7ck0OSqYZf2CY8mX4t6zGUvVdIaGV2KxjBAOhWmLTWGqYxBJG0VCYEukgjPNOxnVu5D7EsB9FACZoKZ59zbGzF3MkcM/YRZFyh2DrEgrZZZ3JfOHWxgqSMfks6AKu9gS209JUhKzW4+xaux41G0FRFSdxBduonPrbRhjBOo8C1mQ8RGFw51I8kqOZb1Ho6adVCGGYaeO7ow5zN3zBJpTiukx9jHqPoZMUYjc5efUtDCf9o/jepOVGfp2vuowMenMM1FpV9O6bQTDmCxiYjfTPnYq5S0BfEYHxxJD3Nc7wJPzczmjeYAn6wa55uabkT/4IE+3LeUi+Rs4rdehHHyQTz0JWItEJlV3krX+fl6Y9yzXbb2JWM0n3K65gD9WzOSmwxFeHngGhZhEX/EIUjCO/uQ+3OZYKupkxKvu5ZzBU+gfvJ/v8z6hMnsz0aytVHfOorbzZPYzg1hFF4W0kRwd5HyxEX04AN6/nBdhSU6nlMIWaT49nrEMy2IRTQ6CsoPsi2QwLZLHYImFMuNGbLJXiFiCbHIrUYbOo8ZWwpnybUyUfBzJHYMz+Qj+gRI6t91IWulPzHS8Q4OtlEumPUTQpCUjsp6kviwWaGZwGd/hU8p5NkVNuwccCdehk+wk6UsxygQEUaRwT4imcakEwipC3YkkVzbQreyioNqHNSf/xDs2ZTBCZpqCFVlG3ky8jSpdNi/43yEo9PK+XcaDehWnWNp5cP9NVGbMZax2CrWqRiw1dj665/dMPf1sCt5+h9HH70X52D4mZ+xh4tQEwlVTaTbksq/dixc9o4FE7BGJqCRDJYtgJEByyMZCTy3p3Z3kNvUQO+ojoFfSVpLNj5PGovOMEPF76TZkIeYpqSoTOTOtA4/nACODZqpbE1ijcxMxRhjTlUdvxqXsSs0krBCQRWyYBp9HHMphmvtqbtGXsCEcgmEfMZO/YnB0Pd/la7gjJoJRgNStYVKjk3BGridk+pGkyGc8nPMZOcO9lITasY/msbbwXawRI08dvAjNrrcIKpS8PvtMMqw2Soq2YLQM03v4ElqG4/mx+C18qixeHRjh0awX+cNRI+vkhwnKA0wdXY03uQh1VTWynzOokvWjjhwn9ntKrmIgLo0bDZmkrnkTvbub186/k70uLXdIGmJkcuxjXbypMJMlkyj+2c/roh+DAOqIkweta8kVG3DMfRbBOo2RkRFaWlpQKBQcPXoUvcHIexkllGrU3J7628utSpKEJEn/tGn5/39Eo1GCweNmS/8qfe7/1OT+C0KhEDU1Nfh8PiZPnvxfVjP+R9ryvwVsNhvV1dUkJCRQUlKCTCYjNTWV/fv34/F4MBgMqPV64jOyGBpowSrEEW473u4VTdFg6bHS1XmYBHkCR2yHmZx9MUcG5MyOE0m1dlG3a4DxxpMYGl6JINuBRlNKqmoSybIa6pLGkuvo4xPTEs6UdqL3fUeGcj6jihg8UR+SYKRt/27mXHkDRo0VwenG19uFJ7WInpxMOsIy5rkO0ZlfQV7PMNtLQ1xrT+W8NV/y3biJfC9OYYq7FbVxgG6lD4PSRoNzLpNMnzLXs583084g0WXl+9jN3N13Je2EcZgK6Got5hK3kleQs8mr4rSMLtrbBHSjWYRQ8J5wGrd0vE1y/EPs3LOHqtPPYdvH7zIp70wk5XOMXXoKzU/tJHngZKYpalhfNpk9K1czN7+IlWoz11RVEtPVBe++y733n8pDgRpGrddRP/Q0n8mtaIpFKut2ULnvAx6f8jh37byL2Wlws/JcXqmci6PByJ+GnsIUlNNQ7kESNYwS5pWcQip6S1kUWEuusJOrGi+kqftMtmV8ydjMLahyNnBspJDhnip89jEckPz4FS40gpcYXKgIIxclwqjwosMpaInKFKAGVGGikoseLHRE1YTzHUxu91DZ28BA6So67akcS8jjTNMUbl8fIUk2yg36PvaMDRBWjGLST4ek7Whjd9NTt4CfVT3cMu9a5Eo1U8PPsEvTwiVJpSgHwrjkUX4oVLLOpcQbcyYGbxvjshcyJMqIVauYcXgfg9lF6D0gBkCuVHH06Cl49MejqZF/p6Eti8LFnWGWl6ipC4RYMv1K8vb185z0I7XZ8Pyokav1fh5MV/PmcDVbI1s5M20qPeo0QkcVyL5ewUG9kbHnX0qKJEOz6Xui3zSh/XwV4wSJsUYQ9dLxXKEIMq+AzAtC9PjmIqyR48hPpG3cGLYERDQeG2JIZFSmoiWtDHM2LC0IolfsA3oZ6jNxtC2RNRoXHnOIsm4r3RmXcKiiGJtZB5KI1rkKZUcPSs/pLPenospK5MdjbgQxQnrVo3wfGKA4S85NpiD06Cg/4kCuuQqnOItI7OvE+7ZzaeaTeJQ6Lu76mS5XMj8XvU2pL5e7D81Dsfd1PHozH82YT2bsECWlm5FrQvTtvZUWl8BPJW+CMpVJwjTeTyrlwTodO2X1jMrcFAbWEk3IRT2+DmFDJpPlnSjFUbq3WXig6Ao6E7L4fUIu2p++J6l/D+8uvZKfvFYuQMUEQYG9ys9r3jCBJD0X1kb4zutGkIFXEnk68jYVijoCsx9CXnk+GUBGRgaRSIRvv/2WYDDInuLxjERE7vSP0N8jYrVa/6w17G/FL2vw/7XIXafT/V02JL+Inw0ODp6o3/rleuzYsb/JGP/0T97pdLJr1y5kMhlTpkz5q20Kv3VaXpIk2tvbOXToEPn5+ZSVlZ2YsBkZGQB0df1br25KUSl9xxoIWTSoHCEkSSKSrERCItrmpsJUgSPqID8lytH+ABEhh8qEY+y15KDtNAEyPJ79ZGdnEuOOYVTbTVihZKqjgXpdFl6bCqVzCymKZMzqJAREJNFFKBSmv6mB7MLx+Ed6CQf8VLlstFRU0tQb5Yye1ewqmUhRp5qQMsouZQcJA72kDY/wScIMEkcUBLV2LAXrGRqNJYiRJv9MLk7ZjDHkI6lxJjuMhxlS2Ek0uUAm0p65hHm7ajFE42ixevEEjiBTSCh8fpYlOXjbWcWIJpM5ymp6e3tRp2UTl55F0/o6YAJe3weoTq+guO0oer+J/MFuXsot5zpZmHSNihuaetFeeSXqslKmvLadU30HEeQxuC2XsdUV4nulmYYCPYraz5lX9wNPT3uKrb1b6Q1+yv36KLsKKjkj60kiDhOTDg6j9KtRmQP83DWba0fP5VLdzXQIRcQqX2FC9Emubigne/cjNLTPRKOxM63yI8bMfRbrxO+RZ7fjjlHRoyykU5xAR3Qq3ZGJDEVKsUdy6ZVSqVfEcswCoaxW5k/6lvtmP8Hc9FdxJm/GNFhF3/A1zCq/iSubPdy5IYQfLfen7KB9yi483hgU8kw8vl2k9aQyL/w+3ZYQ1yy9Aw0qyht+YK+thevz53KWrBojHj5SLOEDjxVJXYo1sIhzEqLEauJQCAIN9hpO270Zp8VIbCCOsFdGjOikOlKF2TVKWKlkYvhxRr2DRKNRJIXAor4w2X6Jp0U/kiSRf+OdXLYrjXiHwKjKz9PDIt/Zolxu9XNf2VnsVLfRE7ODlKkjrMw+mWpZKntXf8/q1V+xSWuh6dILGLjuSkYvPpuucZW4yqrwlE7EUVbFwIxpNC+Zx5ZF81k5ZTzrCrPZL9PSaXfTI5o4mFZB0+Ryxp2dzG0XRzizfD16+Wocw1F2HEzm2Z4wKywuMkZiMEq/o6Hobo5ljsNm0iIL92FseRsOZTNTXMJX3kJqChNpqHEiV7mQl9/IN4phzsqIMlUvod6oY1KNRFT9FH4mEo39A4KvhsfV17M3vZzJXR10+vxsLPiIk0an8uDuKhS738AeE8+Xc2eTkdjHmLHrCCpkjOy5h0aXxA8lb5IiUzEQfz8exvFwnZ5GuumQD2OO7iDGmoh6fD2ydVlMlbejEBx0/2zhkfxLaUnK4c6MAtiyg7yWb/h8yql8oyxmHgoukJQ0Z9lY0ddFY3Im5/ZKHO4YpVUm4kfi5sAKlsYcJjThWsLjr/6ztewXoRr9jLns1MeyPN1KSbwVu93+F61hf2v285dq8/9L5B4IBH7TDc5/hezsbJKSkti0adOJz1wuF3v37mXKlCm/yRj/1JF7MBhk37595Obmkp2d/d966L8luUciEerq6nA4HEycOJGYmJg/+16v12O1Wunq6qKkpASA1KISqtetITI5isUOzm4PglZOQBfG4omnKj6Jbwe+JaSsRpTS6AycxPikr3k57UqCOw9gXDAGt/sISUkiDQ1+DlkFsrwu1EoPIVHgiCeXqRmNOPQigi8RydsIHE/NN+3aQvG8edRUrycOOeNGeng/bwwzgqvIsQ0SLTWDMhmT18dPWW5muco5e/82Xlh6Jv0jM5BHt5GYeQDb0VMxGQap9p7C+XGbWNS8m1XJs9CE1/J97GauHDqdXkRsseX0Hs7j0oCa1+QyNrpVnJHdRGszmAbzUMokXggt44m+F8hJfIhNmzdzygWXsfKphzA2TCO+rIGc0kb275VRfiyLiLKbPrOV+wc8vDLdyGmddh7ptbP8uefoPf8CbvrKR8c5b3PQege+6Ajfj65GH2tGyIfiwx8yT5J4evKT3Lv3fkYCIzyWcitPhlI5yfo8L+x7hYXVGzmcms/tVa+yvWc237TMY6lUzCmxY7nJt5905WuYZWbSu2fha72GHoOKA4k/EzS1kx1fQ3zGduS/6KP+F/AH9ajcaSS1X4wwmsdAKsTrQyxqNXOg8WXuCv8OgyzKHya9CcYRXF2TMKbWIFfqKDwsJ9HeyBe+Raw4NZEEp8S5PS18FL+SmcPTOC8lgZi+D6hMzWFD31IKhirZVHIWp20f4KYlN/BApxOFAI1r3iYvIQF5WE/FtAmEv1cQg4t+q5GEjmYilliShEM0Nl1Oae7ziCoBjU/iDqfADUkSP456WRproPehRznv+et45dQgGa5U9osD7PeEmWZYwf15pzKoKOPbjh8pUX6E3Due1YNLUI6EyfB3k1TbTEzIiUoM/8UzEhHwyXWMKmOwq9IIJueiiBOJj5dYmGMgP1nC5d6K39/MyJCe/q44qgfVbI93EbJKlPSaEbVn0laUTqc1G0mQgRRGN7QF8WgKevVslsckogqreCpPwfg9TuRp+6lLeYeMOIFr9VFkfSZS1rhIycnEobiZiKoTjepumv3FbGUJuzPHoI6IYN/I3swdXNt9PgsPu4kc/YCejCK2Vo0hO/kYOQUH6XanoDh0M/XRLjYUv0upIsz++BdJCyh4ulZOrzjCAXUrUekoRfEq1GWNyH7KZqq6GZngpXtTDI8XXURDaj73F5Yw+sNhxjW8x49lM/k4aSaTJTn3SRo2JbhoHG1m56QFTHSBZp+dzfowRkRmRXdyi2Ud4ZKzCM6898+e97Fjx9izZw/5VZO5W9JxcYKZU5JigdgTmu0OhwObzUZrayt+v/+EE5vVav3VTmz/V8n9t0zJezweWlpaTly3t7dz5MgRYmNjycjI4NZbb2X58uXk5+eTnZ3NAw88QEpKCqeddtpvMv4/NblrNBqmT5/+q0xffqszd6/Xy+HDh1GpVEyZMuU/1SjOyMigs7PzxHVqURmCTIZP3YuFBIb3DiKvkBNJV5PoziLsc5DgT+DQyEZy4q6nZriU3LTX8SdJdO7YR+J5S3G7jxAK/4wgpCPTTidPaOVocjFxficfWE5nuvwJdKEvyVPPw6msxR3xIAp6mnfvYOYlv8Osi0cYHkGSC0gZpXSX51I7DOf1reZQ+WTKWzrZWRGlpyPCSWtX8tqCU3hONYvlgxvpT7BhSDtI2JaOK5JJR3gSV1rWslKYTV71DH4c/zNn2RaQboxyzKWnNfNUFmx9jo+XFNES38+QswmlugAhaOeUJBMr+sdzaeJ0lni/4g3/EtqGbWRXTaNz9z5Kp15Hv+2PWGZeSPTzn0nrO5lZsiP8VD6ZT3/axKOLF3FX+yDFukTOffEF+i+/gmc3T+TqmU/QkvgAsqibT+1bEWNNUADFRz5mjmeIN6e9xO177uXt+jv4fdrNfDpq4fK593H+gUoe6X6biC2MMr+a8TN28UPzaazsq2IlE5lrreaSQD2T5NswqlcSJyVR1DuWQNs8QlI+bpUOm6kTh6Yfj8KGIAsjA7SiFmMwgXhPGhpvCkhKookDmKztKNRfU9izk47gSUjRq3iNOyiw1nDpmI+JUY7FYVNgytiLOZhH2e7DiH4zD3I17551NuODbubtPoLKV8SSinKmdhVi8jxKS1wsP8aLHAkdYtJwFUsPt1OcVIBOocMVGSUUdjJhxwhN44swutPJm1+E/zMFFsFJv0lHht+LKSaej7UvcFHoMZpbrkJhfg7BoWaaRsXMYR/L5cNM1ClZUpzL1Wc+yNSa+zmQ18uMriqGjcPsFnrYWvMjVYZ1XJR1EomlV/FT7y4csR9j9RuRAtn0h1I5FirEF9QgD4lIkoBGHkCuiqLRRLFoQyTpVSxKjycnSUs40oXTuY1AoJOBQSWjw/F0duVwIGSnPnUITbxA/kASLXkLaSlPoNtYhCQoQZBh8DQRqQ6Cr5Bzi9Rc2KPnPauSkdEoUw54CBa9QltqPUtjRFRhsKxMIn2oD0Xu+Tijiwlb1xHjfZtvxFPokdJwaA00JWaQPPQjbdZdPNx0K2MO7iXSsZ2jZROpK82kMGc3Kekt7OmZSErd5RxWHWFL4aeM0YYxyc7Do7Dw0R4HzqiHTdoaglI3M9NGUWV3oViTxRTdMQQCdG2IYXnpRdSn5fNIxRh6Vh1jYsMb7Mwo462CUxkrynkSHdusEbrdh9g5eT66iIypm+2sNIUwRaFIaOB53dtEs2YRWPjsCZc3OJ7qXbt2LbkFhbxsTqNAIeOutD8/Z/+lNewX3wy/339Cs729vf1XO7H9Uin/94iCfwv8e3L/re75wIEDzJkz58T173//ewAuvfRSPvjgA+688068Xi/XXHMNDoeD6dOns3btWjQazW8y/j81uQPodDok6a9HS7/gtzhzHxoaoqamhrS0NAoKCv7L3WdmZiaHDx/G7XZjNBpR6/UkFxTT21ZHrHwekVYXqnFmgslKjMe0+I/WkhOfw27Pbpblm1ldPcLp6QbGJ9SwQ7RwweBx2VyZbDdZWdPRurR4tNsJUsn8niN8nz4Lz5AateYnEpTnY9Gk4XbXgeQkLEZpP7SfwvEzObD9e4S4GOY5+jlaMYOcjxo5O/ZH3q16i0l716KIePjO1ML1VgtzG4+yuaSMaH0e0ZRukkp+oGX9w1itfvY5z+acuDuY3X6A3dZJKMJb+DxuLdcOnk2vEMUWW05HdQU32/w8FaPgxwhcnbWXxqZJ6DstZBg83D+ykC9UjzMlJczuvXtZetIieutr2f9FI0lzSrBa1+C54BaKP9mHzVzKpLZ6Pikay2M//8yVU6bzcPsg6cVZTHr2GQZ/fztvaGZwxaQn6U64D0mQ8Zl9M+HYGE4rlVHWuJ7S0U5uSL6YFcoNvN79BNeUXkvriJIvKxex1TGBR2veY3HNejpiEzHm/sSSvJVsal/Klt4K1kaqyDTOY662jUXBDsYJdehVawFIlOnJDmcQjVgZiZgR0RCrVCEow8hkzchNh5Hp+pB72hFG/fjsGjZK8/ks+gh7oul8JAR5RGdnuGwHEW8mQfNudLo4custZI3s4dhoJXflXcLe0rFcrAhTbu3kzfwPOf/wHWTVncqC+D/QEyxnnVXkR6cbf8pYzIKGosF+4vPLABgIRQj3VBO0piNE1WSXFaHUKbGhRS448OjUaAM+zNYUpsfncX/Pcj40vsWAcgVZXI6kVnDPkQDnxyu5v8vGK5lWrpgyjqciD5DW/xi7UvaxoLmEnNE5hIpc7A4eZnfdjyQr1zAtJo5r8mehVidxxDnAEXsrzaPNRMUAahnEKg2k6uNJVKmxKsLECF4MkgNl1EFPLwTCKuyDcYwMFtHqdFGT5GA0EVJHBLJHchnIKeJwYiKjhslIghoQ0ER9SA1tRPqslKcbeHJOEXuPDHPxWCVzDrmpHBykd+qjFCQEqFBJKPfLSNxkILk4gjfrSXyiFX/i05icx3hDdjleSYcSkf3pY5BFR9H7f+Lxo/eStP8rwsMN7J00g+68WMaUrMdgtrOq/kzGty5kR8xWdmd9T5U+wnixjCctp3J2VwCzN8jXhj1EpFFm5rShTBxE+00aE+MaEaQwHRvNPFZ2CcdSc3l84lhaVnZQ1fQ6R81JPD/2AgpFOU9LWnarI7R6t9E6popOlY5LfnbRkiwy6pAoFFp5X/kMYvI4Qsv+BPJ/I16v18vKlSuxWq1sLaxkxBPk3YIU1H9FXlar1ZKWlkZaWhqiKJ6I6n9xYjOZTCc2AwaD4S8I8f9SpTz8W0Hdbxm5z549+7/kLkEQePTRR3n00Ud/szH/Pf7pyf3X4m9Jy//7ivyysrI/K3T4z/DLuXt7eztjxowBIKtiHPu++5KiqsUYuwP4wxIBs0hUKaIcFJhRMZ2djp3EWDoY9akZjJzCtLTdfJpxGtO+XIf8tCyi0Q5ycjS0b/KxJ05JgdeGpI4QiMJWTzlL4g/gNjpRBpPBXQOATGaiZt33LL7hXg5s/47ksIS8p40fK+cwPdaKLSgw1ddIZ95YirqcbC0LcZU7k0u++oC1j77In9SncuXI84yahtEl1hFwW/FGcumJjueGmJVskU+gsHoeayds4EzbfNJNUO800Jx/DvO2PEDi2RW06Nuo7nWSbA0xGu1muiaVT1x5fKw5lwt636DBfCc7du8haepsutevIrFwEfK8j0lKX0vthDFU1Yzg1+goHOjk4fRCPmyqozOjgBuP9fLp+EnkL3+MoXvv4z31Aq6qXE5n/H1Igoqv7WuxmaxcUC6jsr6JM7xPs/jk13nDU88bda8xLn4cL2ffwPMeOVfOu5fJxxbzQO+nzBndT7slGXPGJk7O/5q6kfHs6Kri09EpvC/OwqJ2UKDroZxRiqJ2skM2MoQRYqVuolIYlSghC4IfE21iPG1SGXXCQg6RRE04iaCoItPUxdXpKzGZ07Humk3II+HSDBDfmkxZXy3hkIU3vefz3IKLEGQynknQ0uH8mmcPf8nppSeR6vmQvtbb+Ml5LYN6LZ94vkVmzidinIOy/yeUoQwOtmyjxJ5BZ8DPnKPddGZkoPekUjYjBY/Hg1c6Hg2oCaEJ+rGajFTFGni2W0tn/BPkVazA0ShBbTXx6Uk81Bbhthw/rw17uCU5hoaJE/ik/ilKmh9iVVk90xo7SK+eyHzVPITMIO3GVr4f6eTr4VXEK0SKNFHyVCKz40XiFRLHuSQAHJc6DosyXH4tTpeJ3pE07HaBvvAwjYkOhhMcqM1gDmhRi7F0p+rwGOYS1E1GkECOgAgoepuQGgzEG8w8dE4xCS6Re/vt1OUouX7XCAHTl2gXbWWeTiTskGN9WUZcOIxhwgRc0gX0aQYxKK/B7sziMy7ApjET5/bRbzTRmpxAWf8qXjp8I4q9bxPyDbF19mxGc1SMK/mBiFxgxb4bmTdQzLqk1VSnbmahPsRYbSpf+u5EDlzQ6mFNzGakaIhphYeRm1yYvohjfEo9YlRG+0YzD4+5nM70NJ6ZOo76b3oZ3/EB3chYPuUqslDwmKSlRSZSz07M46vYbEhmxtEAKZlKvmhxUy508InyCcSYHCJnfwyKf4v6IpEIq1atQhRFpGlzWWPz81JOIpmaXyfPLZPJTuixAwQCgRNRfWdn5wmntl9sV5VK5T+1gM1/hGg0it/v/5exe4V/YXKXJOl/ZDzj9Xr/akX+v4deryc5OZnW1tYT5J5ZMY5dX3xMMNGJqVeDvTGImC6hzDeRWp2PSiFgDVipHl1FvOFCqm1VLEz4jMFUA9LeDjLSL6S943H0+t0oFPEYjAvItx1iX9Ikchz9vJFwPoujB9E63qVIeTVOdRq20BCiJKO/tY0IYdJTS7H1dRNWySlxDNE0bSKJ69dxeewKbqm8k4u+3sfRbFgpq2WZT0ZFRztrMidzR28hQ/EdJFd8Q+v6h4gxB9ntOIezrXdxUtsu1idMxhDYxkcJq/lD32UMyoPYdak0BWfz5NEDXJOrZZPJx42aDdjtSzGOhliSZOPZ4VnMS6jhjOhq3nHNQ6lMoGzBEo6uW8u8vJsYcT3GuCW5HOyzM+HoJATZIA6tgWuVZu449hODWbO4pL6LFTPnkPngA4w8+hhve6Zy47TlNCfeRVSRwM+jHzOksXL5WBkTmjzEfn0Rt06+mUnTXuDJI3/ksQPXcmH+RSik6bybnM3J+c8wu34vNw6vZrZ9Fw6dFlNCJ2Mr6gnLglSPllM7MobBUSsfe/MJiv92NCMToqhkYWSCSDCqIir926ukVfjJMXRzcsp+ZuY4idf24Q80MCxF0OpySK45j4nCDUiigU3OhTw99iyO5hQwdnSQU4Qhvq79mo5QB9flX8Pk4RWUhY7xlWwD3aG5rC59HJ9Swmb+HaahV1kUug20cmy6Q3z5zbeESqZQaHPhscQxaEwjNVlPc3MzAY4fbanFMMpIBK1aTaZGRZlezQ92H6+XXs9B9V7SR+NoH38f4w9exB8KZvPsgAODUsENqVa0ynKeNb/BvJpXOJR9iAPCFsa1a0ivTaVAk0eKpgiX0c6waYja8CDbheMqjUpkGKNKDJIadUiNEBKIRMJEBD8utRuX0YEYIyAT4Zc4J6BR44ufiWiah0OWjDYYxhiV4VbIsI50c0adhs+iOq6fk8FJY1J45VAf36qilMnC3HJgD4rKd6kw+wmEBYxr4jCudRI/XoOYdjNuqZT98RsY5/mIDaEF9JJOqzWb4h43Qa2TDcUmYgIu3ticTGTfH/ErBDYtmItYOEpV3i663Kls238NC9xWvs/4nKaE/ZyvClIWo6W38S7qCuWc2eHlgGUN4YDAxNIdyFQR4lcYGZPVSDiopmODgQfHXclgRgLPz57M4S97KR/4FptjmPvm3UqioOT+qIaAILFdsZ8xE8byuC6FVFuYU3USTzTbKRf6+ED5JKLKgnDxt6D6t6hTkiQ2bdrE4OAglaecxnV2PxfFm1gS+7eTl0ajITU1ldTUVERRPOGv3tnZSX19PUaj8YT5yq9dh/9R+IXc/1Xa4OD/ALkLgvCr0vK/7Baj0SgKxX/v57ndbg4fPoxer2fKlCm/2ngmLy+Pffv2nXAWik1Nx2iNY9jRRAxjoCVANCWKcUIqYr2HnoYacnW5HHQcZF7+9WxsDDMvTsOk5ENsJ46rR/MBAYdzI7m599Ez3MuQrpOodyqzXXV8lDIfW58Bk3UXes0d6PSpjAR7gBACcuo2raNs8WJ+eOcZ4mV5zBjq5JPCyVRGN2MZ9pBY6MeRXExWv4/vJzg4JVjEzV+8y5V3P84bkQWcO/IqDuMwuoR6gq44HOECWsIzuS3uWzZKVWRVL2Tz5O9Yop1OoZDI7lE1zYVnk7TnCLOLMlkjb2L1kJxluS20tEBSXx5GrcjtttP4SPU0E/RF7B+UmHnWWTh6u9n54U/MuvFGBmwvMf6qOzny/HZKm+YjCcfYnl/GC7oKKvY8QnTSg1xY38XHC04iW6tj5P77edNTwX2LnmVf7JU443/PUdsbPOFM5NJCObMGvWTvfZnpTav5fOGzvO+q5eNjHxOjXsOtBZfTOZrNdxnFnFk2hfL2Rs7u3srZbRuI6Rxm2GCmoUDH/LztpMu7EIniCJqx+9OxB5LxhzTYQwqCooxEtYhOFSVO5yXRaMOkHEAU+wGQokq8XQmYRxMoHG1HHX6TkfATbAvfyPO5BRyYN4Y0t4OXE3VICQ5erH4drUzLHRm3U97xFuXN9bjNqVgXrebT9npGZQF8lntYclhLZc45uJslxi9NIbk8i3c/+pCFR/fhiTGj9aVQN8GMIAj09/ej5fhiK5dE5PzbgntyrJEXemx4oiK6CanI9gxg7juZ7olPM6vjAL7y23m2e4SeYJgHMuMZa9DykOEuBkb7mXHsHZpSG9htaEMZaSV9WCDWrcRqU5EgKonIVTh1YZzaCD5VBJs6SEAN0f9nuiWIoIoKaCI6IrIE9HGlxJvKiKiyqQkaCEhQqddg8/roVCuJcY3wwFEFy1wxDGsFzr+0nG/9AU6q60Ehl3jAthul9AnpUwcJiEBXCvnvqlCFu4hZMg2/4kLCMj+tcQ+S7/TxCRcRUOnp146htG2UoHmEA0n9+HXL+OOXawnv/BR7Qjw7po8ntrye3IQmNnTOwl57OgsiMj7PfY9ecwPXi1EKEqOEGq+lXWNAAgoin+AW5Ywfuw0prCVthUBx3jECbgPtWwzcN/5qPJlmnps7nYOf9VDg3IKvp447596KRaHhvogGCwIfK+qYPqmE9+XpuKJR7nZ6WdHlJE0Y5S3lk4goUVy+GjTmP1uTDh06RF1dHdMXLOAOD5Tp1NyTHsdvDZlMhsViwWKxkJube8Jfvb+/n2AwyI4dO/4sqlepfhtTmt8a/4qR+/+dQ5H/Jn4h9P9uar6/v589e/aQnJzMuHHj/keOcnl5eQSDQXp6eoDjG5Kc8ZNoPbiHQKwagzNCJBRBmWUkKo8idASZkzqHKFHC4d3Y/BLD0lnMzjjMlqzxBDfsxGQajyQFyMgI47V72WNMJkvqxmgSEUWJFcIC1Pog+pjdpOhz0MoNgAJkMdSuX0NqVQUxhiTUvf0w0IfG56d5egWHhozc3P4u6yYtZHyjhqBS4idtI7m2QYp7u/kqfTqx7iLCqiCp4z/FH4gj1uxm1+iFZJgcnDGymUPmCST2pfBa0ufESXpS9QEicg31yedy7ab9WKOJNCZ4aR9qwRwTQdJ1MUvh50A0j5c5n8WeL0jURlm9Zg2TLrwCuVLJoc/biI05Fbv9eYquryTBvo789mxmNNciyuUczbgB675HSFVKnHe0iwMTp5Dw8ktItQ088KaDZe0fIAsPY0t6jCESeXFIz9uWOHaPjcEb7sb8+Vnc2NPMZ9NfZXz8eF6sfpbdI49yS2Y7d+tCRE0WHppxNZXTPuFiyxP86F1M52gZHwSvY/aOAcYeDlDaGqXCPsQ0qYa5sr2cHdzCGambmR23g0mGPeRF6zD1D6NqlhFfG0fJPjlzd/Wz4Fg1Y3q6aLKN5VFhNtWGCFgWM5SSzn0mOS9XaPm29UGWH1jO9OTpvDf9NWY1P8fYpjqcKXnsLgnzpkdPj6WXhY0XcvHPQXK93QjbU5EpBAomxxMbG8vBjBhSHcMgkyEI6ajyj2eferp78UvHF3+5JCKTRI57E8ASq5GgJLF51EPOjCT6RDAdm0pm3D24knYws/8S7rMM8+2wi5NrO/GJEqvKMni2rBTX9Ic5VvweIdM95Hgno5MnYYtRUJ8W4FC2m0NZLrpjAwSUUXQhBZmjsRQN5JA9Ohul5k4Siz9j7uTvWTrzSyZWvsiQ+UJ2iuX0ijFcmGBmmi7IIY8PW8DPHUfcbNitZnxYjnNxCnsvzOTsvmFeG3Rw+VANjwdvIs/6HBbLIEMDCko2Xkn66yIxyR70c+/Ap7iSAWsNdv3N2J1JfMNSNJYUzK6JJPb3MGKtRqGIkKw9n3s+eYfirR/TkpfLjqXl5E7ZQkpMF28eugx143lMlsK8X/gaQ6YGrg0byc4QUfTNI7mvkK8ytZw69BPBcJiKMRuJuOPI/9xHSV47XpuJli0mbqu6iUC2kecXzuHgFz1kBw8Trd/MHbNvwqTS8UhYTTYy3pd1MGtqNgfDmezSSNyIlnZHL67QKO8olyOXokTOWYHM9OcqZ83NzWzZsoXxEybwqtpKWIKXc5N+ExvXv4Zf/NXT09MxGo2MGTMGrVZLd3c3O3bsYP/+/bS1teF0On8Tc5bfCv8b1fL/aPzTR+6/Fr9UaP41chdFkaamJnp6eqioqCAhIeF/PGZiYiIGg4Hm5mYyMzMByJs0lSVydNgAAQAASURBVOr1PxBIcxNvV9HdISFMl6HIM5Jal0ck6McasNJr3E6KuYx9g5M5NeUTfKlw9Od9FF94OS7XAeSKVRgMU1Ao55Gs+IkO60Jm9tTyYcoZ/M6xCpX7bTIU7zCgz6PDVY0kOgiLUY7t2MLYuUvYsuo9jGmJnDLQzqqChRRtPcykri40eQp81kIyBgJ8U+lkWbSS2z55i2vufIxno6dwzeCzDFvtmHO24+oeR0RMoNq3jLvSvuJn50Qk9zLaUt5gjWUbixzTGPXDYOIk2mr281RHB7ekqVijD3Cdeh0u11LMPjdLzWHecM5lkrWPS7zv8I7xNn5Yt57FN9zOmmcfpXVtCZkLJ+H1Pk/6jXche3kdUflJwGF+LhpHbdbNjN31KLpp93J1cx93xaVScOMNpK/4jBvf6WLmlZk8GHsEV8JdaFyr+cHxIwfVyVxQMsy0ER/Z9Z+TX/81j0+8nktnv8V7rV/xSs1LqOVqlmYt5UbLHLb1SOxOK2DjmGkgSajDIW7U30elp4NiRy/5UgdWYRhPp8TA/hiKzun794XJREUlkYgeeziBBvkYvpalcDAml4PlZQzHWtGGgoRHfNxSK/KqUeCtoRf5U90+8s35vDn7TfJGh9B+Ng+Dz0tX6RgOmXt5e9hKTyTKaOKdeI81k+6uQG2xEwxHURlk2EdHaBXbaDYVMZYdyAXoTh4lT1+IJEkMDg6SxHG3LxkCEgKiePz9SFMrGWfQsGLIySnFRuSTE5H2DaLaM4Hy+Z/TevghSuzX8rxqIe/KruGKY71U6DWcm2DizfwUokjsdKbQUDyNJn8IXziCKxwlIknIBQEE0MsEJJeD9Pg4MnQa5HKB4bDIAU+AFSMuIhJkqZWcH29inDbCZ731vN+fiEKUcW1LkIu7orTrZIwsSeJwipo3BxyMdtn5neEQE8SPUST2Y4sIHBmExa3j0fdMJ3zkHeKmTSGgOYeI4GZX6svkj3SyiXPxyHUYVdkYGhM5kLoRp6GN80eWkBWMo23XCxR2trGvagKjM8JUZq+jx5nC2wev55RQMjJxkLeL/4RK5maZWI4hexCNL46Mo2fwSoFInGeQMm81OSUH8XUVMWFTAymFNhw9FloOm7h1ym3EpAV5ZuECdnzcSbrYCoe/547ZN6HXGngipCZbkPOKMMz8GQmMOtN4NzbCvIiSwmgTK0fCfK5ajiBFGZ39AqmZZX+2Fg0MDPDjjz9SUFDA/pxS9g86+bAghSTV33ep/yWL+Yu/ek5ODqFQCLvdjs1mo6amBkmSTpzlW63W/7Qj6X8bkiQhiiI+n+9fKnL/pyf3/8l5zV8rqgsGg1RXVxMKhZgyZcrfvFsTBIH8/HyampqYN28egiCQlFuAIdbKsLuBGCrQdR3/HcbJ6UjHfDgPHKYos4id4Z0sKzay6sgop6YlMj9jDz8Z8xjXoEKu1uP1HqG09EIOHqpnt2kEg83DWHxsCVewc6SUubnVeI021OF0ZK5aREQEmZWD33/OhX98kz0/fYl+2IVb6iCSlEvrpGJMdRFuaXuXZ6dcxBk/HOPb2aN8o6jmLKeaqrYWVmVO4qbuiUjx1aSU/EBj52TiTIMccJ9BUdLP3Or/gj/E38SE6il8UL6SKk8ZhWYFhxxaGkouZfqWh1hwSS6rZC18ZRe4IHs3za1TSBnJZHysi1ttp/OpoYfzIl/xnvM0th04xMLrf8+PLz6FPmYWlvEOgsHnSbj+Jnh9LSKLmMNhduSXs6/odib+/ATjJl/P4zYrZ4yZzPKlJ+N+7FHKX17HZ/OncM+Eh2hMvJRR3SQitnd4fsjLVmM8Z4wbpKLPR/relyg58AZPV1xK76y3+HZwJ9+3fc9XLV+RZkjj3PQFZBnHcd+AAaUYZV/uBL43L0D6f3PR4PMQU+bGMNeLPuhDhkRUkBGWKXEYjNhNMXh1x+eUIIqkuh1MUAnMtCgZG6dg+8BeGjosqLbJcVY6eXzy48yxlBNefxuWlp/x6JVUVxVyRBjm7YFYvJIcW9JdGCLd9E04QvEGLYG+ShRqiZBHYs8PLXyi/YpE/cnIAY0/kVgayBlKx66XEYmGUch0iAggkxFRKgn7/Sfm73UpsVzd1MdOl4+pC1PZV2enoM1NtDaR0qnv0//TV6jiP+D3+rNo013GOuFk7m8PcG/7EEU6FaU6DZkaJSdZDOjkMlSCQEAU8YkiA14/Nf2DjKo1bPSGGHAcH9ckE5goyvmDDaq0SoaS2vmwp50PxUqCinTO7gpxQVuAdp1A3+kZ1FvkvDswirarjms0uymUrUPwuDnml9HgVLC0S8GFtt/h76lHEfoJzZy7CJBKq/kgNvm7CCPj+YElaCxxJPcX4B/082PJ20gKLw91X0fc0BAjh5eTJJez8+SpGCbVU2oeYG3bPLpGlnBlREk77XxZ9D5pEZEE/ekojW6ShX2kVD9Aj7GfDYnp/GHkFVLzjuGtHceMmp3E5HoZarDS0mHhlmm3kZVuZ/mCZWz7sINkeT/K3R9z54zr0GgNPBvUkCVT8A5uZs40ILen8qwmQJxcye8TBnlshZ3PVY8jAg3ZtzG1auGfrUMul4vvvvuO+Ph4lJNn8KdOG3elWZlk+u+3Ev9W+I8K6lQqFUlJSSQlJSFJEm63G5vNRl9fH8eOHTuhGxIbG4vZbP67Vdv/whV+v/8vtN7/L+Ofntz/J1AoFP9pr7vD4eDIkSPExMQwbty4//a5/F9DcXExhw8fpq+vj9TUVASZjNyJU2jes4Pk3HHE2ySCgRDH3B1YZAGSPPGcnFvJnv49KIyHcAXSaQ1czKSU17kv5x6u/24liTefQV//xyQkNhKNRPHHLGXqaC17k6vIdvbzTOpVzArdjHbkBUoVD+HV59Pra0ESPXhcQbqPVlM+eQEHtq9EYx3H/M56tpctIXdvPVP6ezHkKHEnlJHXE+Cb8aMsjhZz+3svccGjL/GA7GQe6ztEV6qD+DHfMHTkHNRqBZvtv+Ps9CdY1TWdIzHzMXrqeCH5E57uupUhrZteDNSkXspVP77IgVPH0GHtYFevkgmZ/XR2QLk9n2G9xI3ey/jW/BLn6nfzafdxA6A5V1zH5ndeo1y1AFPZRoK8RPx1NyG88SOqyBIEjrInp5Cd4+9m1o43WTxzIas9hbR32Xnp0eVYZ8zA/uyzvFSj4+czN/FCghdvwp3IvbvY71rJIY+FSmsW56V0UNzvI+3IO2QefJub8hZwTdmtHDCYWd+ziW9avsEVfh+ZoKHYWsm09DJS9flEovEM+hR0RsFl8yL2dNFYVIJbqSYrGkQjCKQp5Fi1Aik6KLHoidG46fKMUGur5bPmvTxf3Y9OoePC4jM5Y98U3ol/CE3D6yhrLkMSRFrzEmlLktjsk/HTqBpkSYwk34bRu5mx8jauV5zDAefnKLSJKGRayqriOLJPQCibxJSBOhTBODAW0BKrRLZlI/tHjkd2eoWeoKBEFOSE5UqC/n8TyZ8bo6fSoGF55zCryjIpu6qI+pfryNs9iNsXIeWMc4ndN5OBxm9QZawiV/cBVwmz6LCcw1F5Hi3+EJsdHkYjf5lm1UsiyQot2QoNE4ISBTaRwq4AKcMhBEGi3zjKGlM/P0XK6TalMWcwzIX1HtyA4+wMauRRXhuppcS7j4dkOzHTScivYIdHotql4swhH7cML0ElVOKr+QJD6XzCqgsJSs18mf48422jNErLEBRqxoq5OI6l0miqZ+vYFcx3j+fy3mUEm9bhq/+Bttx8Vp2/gAsSXsUVMvL0/lsYb63gilEHPxv2szbjGyp8ejrTb2GSM8wE7SPEtZyOTz3C52OGud/5IdbUHny7q5jfvxFNmkjvvniaXAn8fupNlGQM8sD8M9n2fhtWlRP1jne5e8o1KHVGngtqSZfL+R4/ZTO16GzxvOZ0M1Ss5YPMAJ992MSrqj8SlWR8KZzP78667M+eczAY5Ntvv0WpVFJ50hLO77CzyKLnykTzX/yf/D3w11rhBEHAZDJhMpnIzs4mHA6fiOrr6uoQRfHPovrfqvf7P8Iv5P7/Re7/B/CfRe49PT00NDSQl5dHVlbWb1rFmZ6ejl6vp6Gh4YSpTf6kaVSvW4M3yY5l1Mzezw+gKpKRXBlP2n6BAZ+LVG8q2we/YnzGI2xsL+J3hT4K0hrZtMrBWfJL6ONjXK7PyM29kwH7IP361UieKha6a/mTbgEdPQlkZ9TgigFNKAvJewyIIMhM7FrxHqc98Aw1u9ZhHLQTFASCWSW0TCvDdKSOu4+9zB+m3cbFXzfQlurmQ2MdNxqTOPnwXtZUVtHZdgra4BqS0vfiaJmFMiKjMzCRtsgMllvfY1n4CWLqz6J68nustPzM4tHpOAISI3EVNBxbyCv7t3Dp2ES2JzpJdVYTY4nDIbUzM5TJSiGG6z1X8F70Jc6wmPm6UURRVsbMi69i28fvMEZYiLFsMwHpZZJvvpnwG2tRheYjSi00piSzadpNzNq9ktmltdQqzmVJbRf3T5rJ6Z9PYPSpJ5n1xk6mVBbz0swn2JpYiTPladTOHznoWs9BIZb42ClMSY0yc7SDcX07iW9eR6U+GW3BefiznuAr1wgT5C0YIk180fwFrpALAJVMRYI2gdmdMk79tI2Hl8+iRlRRHm8kGA0SjAbp89k4PDLIR8dsRKXj8zDLmMWMlBlMSpzE+JhiDN27cdR2ElzTjE77GZ1pBrpTjdRFZaweNtMX9BI0LiEYcwqGkVeZGxvD8kmvMdRoRxI/R6WqJSAuwFG3Cy9+VOoiVNEoMZ5cDixKZkQRx9TqHdTW1iKLqNFKAYIyFXIgrFDhd7lOzF1BEFielciyo5282DPCnRnxFF1fytE368k/MsJIu5uYZZlkTbiRpENnM9L9AzbDTxRIN1AcMmH0VGEOTUYbqSAoKAlKEnJHAEZ9aCMKhLAEeJDk4LT4aVF2UWMexRJM5efUXL5LzyDfJXL7TjdylYBtqYZWagmNfM44DjKXYRA02KV4PhhR0+QTuNjh5snhLCLRK5GP7EcROYi88k4iUogm8XM64nYRM1LFNsaRb4zD3J1HW0hiV87XOEzHeLznOvJd8QwfegXtQBOHqsZy5yV38IDsAfZ3j+PbptP4XWUOY3f38m7CevYlbWOaJ42tOfdye1OE/Jx7UTiziaCgZ+yHLPIrUcd4CG0ax6LQOrAo6dhk5qg8g/umXkN5xgC3zzqDnR+0E6MJoN73LndVXYlCp+eZgJZkhZw9RDBM12IajOGndju7Z5u4JUlG93druVX4iKgk41H3Rdx73fl/tnZFo1FWr16Nx+PhtHPP5Zo+F4kqBU9lJfzDKtV/rd2rUqkkMTGRxMREJEnC4/Fgs9kYGBigqakJnU53guhjYmJ+06j+l3v9/8j974zfIi0viiL19fUMDQ0xbty4EypMvyVkMhlFRUU0NDScSM0n5uYTk5xCZ+9+rNI8zD1yyi+ZiDQawn7QjWdfO5OLJ/Nl+EsWFYR5faOPi4sXsCRnL5/lnMqpP+7BPGMSTudesrJ8tLR46Ewbw2xPE80JWegjfh6P/R3vyh7F4H2ZMuUN+HVt9PnbkMQwjmEXP6/8hozSybTUbEGfHMep3Y2sKl5Kzu56Jgy7yclz0pM/iYrmn9lcNsJpbj3XfPI2G0srudeylO/7dlKf6yJ92pu0rn2EGKOTLfYruDDxJm7rXMFDCb9j4uEZvD/2e8b4ChhjNrF3VM2xgnMwVXeyPMnNPQkqvtX7uUpch1p3MmGxl/nROH6I5HBT8Dpes7/EskQ9K+sgWlzMjIuuZPsn71IcmoN1nBKv71kyrr+a8DvrmVgzDZnoxOpxsnXiqRR1NFLc/RiyiXdyd/sga2P0PPT0s8Tv28voc3/kDy/3ccVUPS+M3UN1xlwcqc+icW9i2L2RVa4QX2srCRRfS1hdhiQ7/jpY3aPc37eBK+hESJ1EpPx0BkxJNAdt9Pn6GfANkP/TJkbjNIzKXQgBD61OHWq5GrVcTYYhgwkJE0jQJpBrziVPl4ZxtA1Z3yHY/gKK7n3IxAhKVSU+/2Mczp3LIUsDW9wJ1HvtyGSx2JLvwkIIVf893FhyARcWXoij38/2z3rRxxYjV4xA9ACdvql0pXZS3tuG3pNJ3uQMniLE/SkJnFt6Aa+++hpReRiPTkVQrkIWDePX6bEN9OJwODCbj1fUF+vV3JYWx7PdIxTo1JwWb2Lc7WM4/Ekz8T0eFB83EzGr0FfFkzrvElIVl+Lprmd4dCVO8y4c8o0IohJtMBeVN5eQwYoQm4BbpqHf68Tl8JHoSaDQls4EqZDqGBl3V2lxKWFG8wCzLQewzG5HHjqG1TtAGhCSJxNjnEq1x8vHnXvwRUc40x3kCXuURvsVRNVmDK0/o8pdiiiLR+HewCY2IiSk0+U7FatSYLp7DL1DMRzSdLN17ArmucZyQdv9RHw12Ha+hCwcpv+8DL6bMZkEBlh7aAYubzm/zzVTuq+LxzM+o9V8jCrfZHZkX8srh/0Ykz/GqxlF7c/Glr0aTVQkJBMIrytnsXo9EV0MXWuU7Iov5Y/jzqUkY4SppmL2vt2MThtGXvMh95RfgFar5omAgRSlnHZE+sepyOvWU9M4wk/LYqkyypi450WK3FuISjKu893MZROtqP9fmxn8W8tbd3c3Z5xxBs+6ovSFInxdnIZB/o+rl/5bRGwEQcBoNGI0GsnKyiIcDjM6OorNZqO+vp5oNIrFYjlB9r9GwfQ/wi/1AV6v9/8rqPtnx78n90AgwOHDhwGYMmXK3zwR/iuUlJRw8OBBuru7T4jbJJdV0rh5LUlFE8nwmvDZAhjidUSsEvG9ycxNT+Cn1p9o9n2FWbuM3UMnMy/uFjxZMg79uI3xZ1yH07kXUfqYuLjz0EemINN+QEAo5ozOvaxImk1vVyzJqdvwmm9GG8pC8jVxPHq3MLx/G+c//SrdN+9DPziKRxTRJWbTOK8K3ZZd3G94jguqnuXqT4/QkBXghZxWnncXc9fXH/Lgxdfypu1czh56lRHLMJbCdTib5yJXqNlsv55LM55hR8dYtsUtJHWomcdT3+aV9rspNPuod2mpLrueqRse5fzzUvko2s2nUZGrkn6kq3sJsX4nZxrlfOUq5vfCTbw48BzylLP5rlEgkJXFtAuvYNeK98l0jidlhgVf8DUyLzud9lWHmHEwj/2l8cT497Itfyyd0m1MWfcap86czj5vFYtqu7g6p4Rrv/gS8Yc1yN97j+W7hhgat5uPizewtWQW3oSnkUL7Mbo2ox5+Do3CQIbWTIk6wHyxixS5H6crQsyBfWh3R8gGMlV6xNhcQmIyXXv7iFlUzq3KsRwMhrgz7vhZnRByIwRc4OiA0Y0IjnbkrgEESSQqE3CaFIxkqbFZrQwqu0nb10Ko9Sxez3gSmUyFK+4W1KoiDKPvk6eyc++sZymzljHQ6mLTe8cwWjWUzlzC+teeoWe8jYxjZhJDbsJyA3pPOse8AWQoWGo1EA2HiEYjyEQVu7NFkiUzWpUSr95EsL2ew4cOIchkxMXFERcXx5VxsbT5Q9zROoBfFDk/IYbJ1xTT3+Sg+adujCMBZOt7CG7oJaIQCGhFApp5ROVTiQpuFBEfYlhEiGgwh8yoI0ZSRTXFCIiShFsEh+Dli9wh3s/PIldq4QHhj1jzbTgx0x9KR6GdTIJ1IumGPL7r/Jkv6z8jEg1zplvkSvsAXv98dvXNodJfjT4lHSn/SkTZEfw1L3G0UEu3cQ6SJGdKNJGwvZDGkMjRjPXYY46xvPsaUkKxuEZfQ7ajHq/VROTKIOGMDvZLk5B1eJlqnMqZXhsZ7d3cnvsnvAofudHzaU9eyCf7fcjVBxnK3IoikIDT1IxcHmDUlYx4MINzDGtwBeMZ+FbOd/nT+bJ8DjkZHk4rWYL7iy6MVgHh6Gc8WHAGBgU87I8hXS3DgcSWfDnje7V0tTjYdU4CUSHCbd2PMaZzL05Jy4XBu7h3bgYygn9Gmvv376e2tpaTTjqJn1Qmfhy280puInnaf2zL2W8pYqNUKklISCAhIQFJkvB6vdhsNoaGhmhubkar1f5ZVP9rx/2F3D0ez39b3+T/Av4lyf2XM3e73c6RI0dISEiguLj4f10xKTU1lZiYGGpra0lLS+Po0aNELPEgSXTLj5LDFPrW9VBwUQExs3NQfCPQcrSRUnkpe0d3sLjsEn6odTJ3TjbLcrfyfe0YqnbZUaenEQz2MGZMLJs3N7EhOYWZfc10xaWgioR41HANb8mfwhB+nWLVVfh0bfT7OpBEHz5XkK7qQ4yffzo7f/oYS+IkFrXW8MW4heTsOYJ7VM5prl3smbqUWYc+Y+0UD2vbOph/MMzYjjY+zJ7D2d1HkFn2klawHk/3BNSEafNNoT64iKeT32GZazmBngtxWF7hxZRPuaf3SpxaF30YOZRzA0u+fYrWC8ewVd7CRy4Zl2dvpKVlPgaXkvNiJVbYyxDVd/B834ucl7KEr3sUuFwmZlx5Azs+eIuBnljGn38B3uAKyi+YSf3OGGZs6+Vo3hRUkUPUpWaxeeotTDyyk1LVo5ir7uDt/lG+HHZy7fR5nHfyyUR++BHlF59z+yfDXJ+4kS1FG9haVEFrzs04NEG07m0E3QepaZ7OmhgrY+J7yYxxkaMKkRuNYPZF0fkiaHqa8a0aQK4Di2Ejiw6u5SRJQnbcv4eoXEZEISOsAL9Ghs8gwx+vw2XS4NJK9ERltIbNHHWpaAl6qLT8xOPdN1GkfJgj8Yno3KuxOD7mImaTEH89fncSjY0D7P2+k8QcI3MvKyAk+RDlkLs/QHepDZ0oI26olJyxetoPObkkPh6rUsFLdU10WJOYb8uhO7ybVeGFyCQBnzEGRJHK0mJQaxkeHqa9vZ26ujrOMpmJaC3c1z7ELqePBzITSC6IIbkgBtdIgN4aG+4GB3JbAIVNRCfToBe0yIlFAiKSREQCpyARVkpgDiPEB/DHDlMT6OZn0czB1JlkB3vQKdy8JNxFjimDuXFpnBVrYMjbwefNn/NT59MIYpTT3Vp+Z+/ALGayT3qcaF0XU5ICyJIvQC60stXyPsa6VlrGjccus1AqBkn0TaPBI8OmHqS2/EcWucYyv2sprkgzjmOPomoOMTzJQvD8YYJhDY833UeoUMNpCg8nN/ThjBnh9vQPMARjUWvuIU5M4+laJ7Kgl56JH0FUgV+QUKrsdHeXQFs8l6m/oWsoAc8WOW+OWcah0jwSMiVmpc3E9UUXsUkaxNaveDhjMXGyMHeGEsnXyPAh8arexfQWDQPuMMNnxrFLDPOi71WqqnfQIcVxcehulqQIzJpRxdatW09kMxsaGti+fTuTJ09mMDWL51sGuCHZwkmWf3xq+RfC/K0hCAIGgwGDwUBmZiaRSOREVN/Y2Eg4HP6LqP6vZX9/uVefz3dCfOdfAYL0axRi/gGIRqO/2gjm8OHDiKKI3W6nqKiI9PT0/6W7+0vs3LmTXbt2MXnyZBQKBZWVlax/9TkGe7qYl3QNUX+U3IcmIkgSA0/sodvZgHNpGg/0P8TJ6ZewYnMhN0wZZYzuEe7Zej+v1PxAystn09xyFzptOXv3ziZsCFM6/AH7gmcT6vTxVdJMtvTeQGKqi271Z1SPNtE2sAEJEGQxaLVBLnzuLb66/Q5ESaA3I5U95ZNQKEaY8/kXnFzczynTX+fcb97lYFYzg7EO3jkwBt+hJs5f/jJZ9n4+89xPY46PiCuJlnUPYzHYcbtNnJt0J/Ujaq7U3EOeu4X2KZ9wzdCZnGafwy5vCFtYRsLQQab43uDOs8bTIDSR7FJzgdVIS9tMVIFYAlYjn9ssVCnbeVP5PO6kKXzmmUQwGCLVbMR1cCcqjYbJF8/EHnwJudyI13kuox82MWqaw5FCLw5jmD05pchEkakHP8FYqSeSfDFrHRFilXIuS7JwdpwRQ/1RPN99h+/nLUgeD65YDUdS5RzLGsux3Kkc7Y1HSOjFGLsWIp1IRFAgIxU1aUMh0hpDmJFQzItgiJVQy0AlSCiQiEoQQUZYAo8o4IwKuCUtI6KR/rCMLr+HgBhGQAHyXNzGKYQ0E/hoX5QwozyW9xLn55/DWdlnsPKh+/nctAC/zMKFI0pKpiVRtSwTV9TJfetvYdxXbkbi05GSMjB02xlNXMYUqZp1hvGU90c55eZSLmluYCgi8FKThobBrUT1PXxRvghtJMKSb99iwbW3kjdp6om56/f7GRkZYXh4hLXuAJ+pLYQEgVOMas5LjWe86c/tML0BH2JARsgb4dixJoKhAOVjSjFbDSjVcgKiyBGnnze3dbC/Zgg0coL5RmTJeqaZdZwUa2ShxYBZIbBnYA+fNX/GvsF9xMq0nDYaz6WjdcRIQXz5N9DclIWpcxR1YgVyYZhR/Q+8aeyn2JbPoNxKtmSnKDqeepsJr2SkOXML8cog59oWIUgiXY7vSTiwGVGQ4blQxFsWpaFtDK90XATZsagy9HyyoZ0fk/byefw6su1jGE66louG5cyzOzAEjHSOfZ5AfA2RsAmZ3EfLsUmoh1WcL6ykud6EUK9h+YRLCJTI8WRmMdZYRP5PI8Rn6Ah2/cAj6rGkSF5uiaRQoVUQBp4whJkZ0RJxhNAv1nG3UsnVo59zT+371IrpXBW4nWRllBV/OAWZXM7PP//MpEmTGBoa4rvvvqO4uJi8mXM4q7GXySYtr+cmIfsnUIRraGhArVaTk5PzdxtTkiR8Ph82mw2bzYbD4UCtVp/QwLdYLP/hhmNoaIjOzk4uvvhiPvvsM2bOnPl3u+f/TfzTk7soioTDf2kZ+Z8hEomwc+dOQqHQf2jT+r+N7u5uPvnkE8rLy1m8eDFyuZzWg3v56aVnmLX4FpIaNQQWpJM+PZnRn1oI7BqkZ9wQz498SZ+5jwrpJRoGPDw08fds7JhEcI2Z+6+ZR53uYcLhYWTCU2zdepTR5J+Z1JdBjzeJ94UpzPA38qblaQZ9EwjI7+GgbSOdnnqO6xRFqTr9bBIScljz1lOoMstxxMXyp8rZnLftHUrtA0jlJv4YfzHnff8S384ZpLQzwiN1ufwUl8ry867gkqZNXG54kYEENbaO6QwevAidLoIm1M9Z1jt5v2sWTyRezgTPBprHb+bB3mup8Bay0wkeEdK6NzFR/Sk3njSGVmUHmTYt5yWZaGqZjioQS9Sq5wt7DNnyIf6kfhmZ2sQXirOwu7yMKy3BcWAH9p5uJp9/JkL813h9Dej1Z1H7ZRhDZwK1+aUMxXfQlJjCseRMMvu7yG//jLQZVYyaT2LtaAgJWBxr4Kx4M1VaBZGDB/Hv2IH30EGizS0IosS9U69BJYa45ejX+NQqBs0+BixBuuIF2pKV9FtlBBX//fkooEAuiyesSMWnySasKURSZBAfGibk3cNtX/xMqbyA9Jyr0Fyagy7TQjgY5ecPVrLz0Ga+Sj2T349P56qledTb63n+x7s4/bswNbnFGFx2msZeTk2uhW6TlqvWOylPaUR0VBD0hdmZ2MDqiipeaBNp7tnDZbKXuKrgGYbVBi7+7i3Kps9i+oWX/4f3HY1G6Rqx8X6/nTUBCYcgx4BEmVpOoVFHuk6LWSGDaJTOzk78ggxTcgqjUYmOYJiOQIhuVwD5QRuCO0xCSSwnjUtmjtVApUGDWiZj2D/Mmo41rGpfRZ+3jzx5CqcPFHGG8yAGeS2h5EXY827A+W0bOkMOcsGGRvEd3+mUBEJWhtGTJI0wUTDT5CrD5rXi0vfjSKvmzNFpJIXjaKaRaOO3ZDR2ESgDx8UhfMFY9rXM4SPXDCqSjZzs7WOiR8MrKSvYazjG+N6l9Kefzh86QyR5bZilWPpLP8edtg5RVBDxxdBcPwGFD05WbGR4q4Bo03LvpN+RUdxHW9500kMJTN08SmK2AdfgzyyXCsiKOLhWTGeiVkkUeEAZYIKowRQWmHFVPlfZbVT0reWF2sc5FCni2tAtBEQZD05SkZOZQmxsLHV1deTn5/Pdd9+RlpbG3KUnc07TAHIBvixOw/gPPGf/96irq8NoNJ7Q/fhHIBqNMjo6eqIKPxAIEBMTc4Lsf/Fu7+/vp7+/n2XLlrFp0ybGjx//v3ZPr732Gs8++ywDAwNUVFTwyiuvUFVV9b8y1r8Uuft8Pg4fPkwoFCIxMfGEx/rfC93d3TQ2NtLX14ckSVx22WUAiGKUP91wJRkl5YyxzcCtVlB8zzhEd4jhPx6iKXiQ7hkWXnC9wDnpf+CdDbE8OLeDNPkb3LP5Ht5uXIP1+VNpab0frXYMO3dMBStUDHzIrtBZRDq9fJY4kw29t5GZOcKg6ROqBwdo6v2RiBRBkFsRJBuXPP8mG595iZHBThyFJXRn5rE/I5Vz3nme2Tk+npp0Bfpj/Vi6fmDL+CFu2Gli9qEQD1x5K7vyi/i45U20aRuIyIy07ruSoC0LUTSQrdjNSZY/ckfblXydMo8K8Uv6C4/yx67bsYQs7HOoCEiQ1/otZTFr+N3CMXQr2kkf1XJeoomW5ukogzHIzHpWunREJXhN+yfGawfYVvgw2480Y421kBRw07F/F/lTppMzW2Jo9APU6kxsfQvxftmDUz+N2kIJj87O4cwChkyxFLfVkzz0FYUzp6G0nsJKe4TOYJhYhZyFFgMzY3RUGXXEhIOEOzt5YmsX20ci3Cl+w6Crlx4hxKgpne6UUnrTyvCr43ArNYi4kUWdCFIQQQwhSGEkQY4kqEBQIsoMSLIYtKIMbdSLKtBPONxIJNqIRbAx1lrG9JTpTGkSCNz7GKaL/4Qs0Uh7vJb6bQMEfSECnrdYl7QQZ0wWFyxo4ej3r7OgJpOtM+bgDwc4UDCOwfhkxunUJPy8ispWPRpFDvPO0LBxtYQfF+8tyKDSJ2HpPcJD3kdYnvEUG+IyuGDVu5ikKJe98OZfTVtGRJEdw6NsHXZQ7Q3SJ0o4BAWhf/d3csCskBOrkJOpUZKhVrBjfScuV4i3LhjDmBTT//u3Iuwe2M3KtpXs7N+JUqZkpjSOhZ3jmBzcj1nxHSFdCrtzH8FwQE6SZAXRjk5xkAaZgXqZSK8sgBU7VZ4u/H3Z1BlmIcm0+LPqqAzEUxzIplPeT4P7MBV716L3+XGeHkWsCrOlfx6+nkxqI0lkF1Ww8MgeYvQJPJ72OoMKPzPaLsWdMZEb2rzoIj7Uci1D4z/Fbd2GIIC7Zwy9zWn4ZWrO9/+IbVOUXlUCj0y6klkFDdQUnY5qSMlJ212kFJjotu/leX8axYEBLhWymaw9LtTykBAgI6okR6FiwTUFvOh14zi6kjcaHqE2UslF4ZvwSCqeX5jIuNz4P4tGm5ubMRgMLDv9dO4c9nPEG+Tb4rT/H3t/GSXHdX3/w5+q5mmYHmae0Wg0I82I0WJZkmVbZtmWmTl2YoxjduIYEjMzxZJRBtkiiyymIQ0zUzNj1fNC0ST+hRM78H3+e61eWuqprrqru+7ddc49Z+9/2BDmx0RNTQ1xcXH/1qzp38LxqN5ms2G321GpVMTGxrJr1y7KyspYuXIlR48eZcyYMT/K9deuXctFF13ESy+9xPTp03nqqaf46KOPaGpq+pdE1P4S/s+Q+8jICNXV1cd6zH+vUFdaWvpvGOGxMTY0NDA0NERFRQUWi4VPPvmEyy67bFQU4cNnfoOlcj+L59+JqS2M+pIS4vNNDL9XTaDBim2hzAMdz+E1e0l2/wpPIMitE27k6/b5qL9Scdu1Szkacx/hsBVZfohd3zUznPYd8/pTaQ9k8lFkIjmCi49Ud+CXCrDxBEfs22h3HgFkBEFF3sRyJp9yLp8+eBfmlEI64/R8Pmkexa4qpn/zLUtK+jl1xotc+PHLHMxvYzDByYuHSlHvOsrqh58FUWLD0P205XQj+ONo2nYHGiGE15fOdOMaJmrWcnHf7exLLCPP+CaRNAtPdN+KGNFwyKEhJENRy0eMS9rAtQuPEXyaU8PqBD1tnfMRg3pk2UClUqQulMLPDeu5SP6C7hkP8XVLhOHhYQpi9dirDqDWxTBz9Sn4VW/h9TWi1y+h6VszMYcUdKbPoiXHgkcf5HDOWJwxRko6Gkkb+Jz0KSlMzF9NczSZDTYPXcFj91aRTk12RCDc7eFAzTBPXjuJBK0afzREu7ufo64R6n1hOqLxBAQ9umA9WttaBDmCKGtAUCAjIhAkKntRECJOKRCviSVWjsUcNTO1YCqT0ieRY8xB/L2sXdgXpP+UUwiPPYO45Cls90VJn5ZM0cw43nv+EfzDVt7LOpcFIxsYpxQ5WDGJ2swCbIZYsgZ7eGj2NDa4vGxrbuWij14iLn4ValHGFtePODyBQ5NM7MhTMaullhesP+f54kd41zSO8799n5juZvJOPosTTz/rH6psDofD9Pb20tzejoSAIIqkxceTnJxEQkICarWaw90OLnyrkldXlzMz30yVpYrN3ZvZ2rsVR8jBGGU+S62zmDc4EZ26EbPqBXRhK5vi7yJ5uJy0iBoiXlCG6RWjVCs6GFA4ScLKCbo2GEqjanAWblMeioReslUyEwL5dKsGqZW7yazfSF5jD5FUCfulERL8Ao9WXcpAXAazlZ0QX8r5vXb2xbl4Nu09tKEkFrRcQUxGFif2WYkTtURUPoZmPUlQMwhCGFfdCfj6ZTq1mZzl3oP89QC7Mkp4ZdppnFXQREPZ+Qw3+jh5v4escXEcddbysjuB6a5WTlOVMFunQUTkMfxEQgJz440svGwMe6Mhtu16g982PUabNIvloauJyCJn5yu59/w5o9+7y+XinXfeOdbLPnEi70ZUbFQZeSBGYklK/F9MO/8ncLzWKT09/T89lD+LaDSKw+GgtraW6667joGBAaLRKD//+c9ZtWoV48eP/8HbCKdPn87UqVN57rnngGO8kZWVxY033sidd975g14L/gfIXZZlQqHQX/37cZvW0tJS0tPTaWtrw+v1jrq0/ZgIBAJUVVUhSRITJ05Ep9MhSRIvvvgiubm5rFixAoAtG76h5eN3mLjkVHLrCrAn6yi5YTwRix/bszU0yYepL1fwavhVLsh6kBc3qbl/UStp4mvc9e3PebX5SxKeOIm29vvQ6Uo4sH8xHsHDuMC7HPWdg6rHxcvJJ7Km+36mFzVjMf6WxkEd9QNf44l4QNCB7OakW+6i9uud9DTtRj1uGnazmVfKZnHBphcp81kIlMXxm+TVrP70GT6bN0S6LcRvG8tp7RniytsfptjaxRuOO2gdIyO50mjZfDfmmGHs7gyWxz9GolTDuba76TakEp/yGtr4EE90/oywJHLYoSUsQ1HLh5QmbOCmRRNoU3YS71VxQayK3u4TkUNa1JFUXHEuPrAVsVDbxOPybzFUnM7+uNPZtWcfcjBAvHMI30Af4+YvIm9uDEPWV5CkIALL6f44gHowm7acMjrSBvDGSNRmFmIxmskYHqC4dQO6lD5mTVnOhNRFNAe1HPL4OdzlpMcdQK60EpyZhGz6Q8WxSoB8rZrZsTGckmCi3KBFlmUC0QC+iA9/yI5aZUIhKFCKSowqI9FIlJqaGsLhMBUVFWi1WiKhKNY+H5ZuD31NDgZbXWS1fkVO33aMpz2NpiQO48pc1m5YS29lM7rWSnanLMZVkktvdhounYGskSBLGncxPjpMw3nX8cqAnUfzU0hav4aOw/Vo1KdgVPUwEs7HatDx4klmyjpb+aLnBj6b8xt+JpRy9c71mNtrCKrVpM1ZzIoVK/7uYiKbzUZ1dTW5ubnk5OTgdrsZGRnBYrHg8XgwmUzUubX85nAV46f1MODYjT9sJSEazxzPFJZYJ5MdyqI3JopGaCXPa8cnjEGQ4hB/r3kfkUO0KxuoVI3gRiARKwuF/cRlTOLrI1MJSHmYxSHikiQmBLPpUw1zUNlMkuUgRUda0NojeJZE8Z8YxvrtGB7kctzqGBarm8mTXZwdKeWllG/YEHeQbMc05rafQ0GCjlz/AClSGi5TB0PTHkESBBBCiHWFRIaU7FFNZclILfHf1vNuyWJ2TBrHpQUOesvP5vBuC8uO+MifnMAOWzNr7DGcaKlmnqGcOVoDCkReJUBdUOKCnETmXlCAnShfrH+QWzreYkC5mIWeS4hIEbJiZD6+eRGq36fZQ6EQa9euxWazceGFF7JbVvHTjmFuitNyYuRYT3goFPqTtPN/CocPHyYjI4PU1NT/2Bj+XrS3t1NZWcmll17KSSedxI4dO4iNjWXZsmXceuutlJSU/MvXCIVCxMTE8PHHH3PaaaeNvn/xxRfjcDj4/PPP/+Vr/L/4nyb34zatHo+HSZMmjbYxdHZ2YrfbmThx4o86NofDQWVlJQkJCZSWln7vqXnfvn3s3LmT66+/Hr1ez86dO/HVV9F3tIp5JTeiHQwR95Ny9IlaBl85hK/TgmOphnvbfgOxAkbHvYTCIW4ZfwMbOuYT/sbIPVfMo97wMKHQEDbr9dTVuRjJOsqK7hCHoxPY7swlZIpjs+8qJNGAVfceh+17abPsBI4V12l1IVKXn4V7yzb8Pg/DBQV0F5RQmZ7CWW88xbxcHy9MWYW7P8rYmo/4euYQJ1UpuKIhhY1ZhTx8/uWc0fEdN6sfpyddjW+ohO6dPyUpbgC7PZ7TEu8jHBjmIu9djOjMGDNeJd4g8ljXLXhliUqHjrAM+e2fM177OXeeOpUmqRmlJLBaqcJrW4bfq0LrzSZ7rIPHW1MRRYFfKN/j1BQrzkVPsL/DyZHDhxEtg2hG+lCp1cw4+2xicmoZGl6DKOoJB+cw8EkYjTWPtuwJdKYNE9D6aE7Npis+FYUkUdF4kFjXLuILVWh0yzh9XDnmaDwr3jzExZkJ6J0SAXsIVVQmNgxxyToM8ZpjrzgNmhglap0ClQb6HBdiijmJOMNFSFEZt9NPa1M7gqTEpE3Aaw/jtgRwjviRJVAoBZLzjGSWxJGeHMF98ZnoLroXwZXCk8kvM2eHH7tSy3unnE1nSgYhpZrEERdnNIicNjeN7966i5Gp83i3aAq/8lmY39OG7cgRNgXt6BKLkCPLyDG3Y9aXc22pTFgIcLT6DPYsepazI2XcfqQOqfsgwmAbkTHjEYxmli5dSlFR0V+837dv347P50OhUDB+/Pg/icpkWaZysJIN7RvYMbQLR9SKNmpkum8Kp1onMcafd6ybQARZDqGXfIiSCokYBCDq7sMjHaIraZBqMYsgGpIZ5CS+IzHWzMb+UxlwTSZFDJJpcJGlyKJPNcw+7VHyggeJb+0ivipCJE1GvdSDzmPmgZ6z2JoyFb1KJC08xAmaDgqEBD5K+4wurYPx/auY3DedyfESBu8Iicp0BjO24Rz3HoIoEQ1pyegKEOpL4nNxGZN6W8jdW81jk85nuCLEjWMzsJcs58uve5h/1M+YE5L5pL+NDVYlZ/Xtoix+JvN0JpQo+EwI8VkoxB2lGcw8IxeI8t3H13By7wZ6zWdw+eDZdMhhEOCza6aTnXCs5zoajbJu3Tr6+vrIz88nZ/4izmsaYHm8nsd+L1Tz54rJtFrtKNH/My1i/woOHjxITk7Oj5Ju/qHR0tLCwMAAp5xyCqFQiGg0yu7du9mwYQOXXHLJD7K9e1y5dM+ePcycOXP0/dtvv50dO3awf//+f/ka/y/+Z1vhjtu0xsTEMGvWrO+5uf0tbfkfAsfV7oqKisjJyfmTFE55eTm7du2isrKSOXPmIIoiRXMX0rb3O1xp3RiHUun+rI2SK0uJP6kYxasSPdsOsrR0KW+H32bBmGFe2aKhZ9z1LMl9np+Pu4umV94j7dc/pav3DuLi15CaehlGv5Eh4/OoXONYEajiGf1y3rMv5orcDQTVaykJnkQwZog+Xwuy5CXgjWKrOsCiq69l3WP3kO30IbU3UhObxL7TVqD5dB13q1/gvFlPkt9dwaTmQ3w90cIYm5MFh3bTnDeGD2fNpaypj5mO36FIbCal4ncMVZ1PQrydL62/4Iyku3k1+gSXB27H0Xs5kdxXuCvnaX7VfRNTzEGOODS0568k2BvLrz58lyfPmM6BaDNvKIOcottAom42VkGiuymDn4+1sb3bzi3Ba/h4sJkH117ForkXM/WqK6k5Wkf1oYN4W+rY+fZbJOcXMunUp8C0m6HhT8g6T0U0HCa6sYXCvVn0pUzE6PFRqt2PxWSkMX88zpiZaIJBIpYIhz9eR55pP4JwBcFsK5fPHo8RM/Y+H9Y+L84RPx5bkL5GB15HiEjomNyquWAbqZO7OfRJIkFH3R/dBQIKpYQ33oUxQUtaUSzj5qaSmG0gLlWHLMq0Odv4anAfScUxfON5nNWax1CFV3LvJanYjLFoQ0GyRgaIqxmmQcjgjEsmMbjzC0JBP0XfbmX9yy8jRiK4jUZixo9HY4rDa++gMPEonY5yZoSrmDacyqaidBRI5KmBCBjmVtD/VTOpzkSEkX60ufl89tlnjB07lnnz5hEb+6eypV6vl4aGBkRRRKvVYjKZMBgMNDuaWd/6FVt7tzIcHsEsm5jlLGeOcyJZvgKENA2+Aj9HY5wkKroxdwxiGpqGJMchGMN4OrbS7ThER0k6g4p0lIKW5BgfJ3k/JUV0cSh4Ol83riRdrWBWfJRkOZY2jYvX9Z8yQz7A5IAV005QjoA4J0x+lo91lTN5PP08pIwYElQil3k/Z6KqkDf0fXyV9CVhZTzzW26j0JrKBLODFJ8GpSqe9glPEk5uAFmBr6uUaZ7dBK2JvCUsIa+nm4Qjzdwy9zqkcUf45eTTCedO5dM1rcxvDlCyJI3X29rZZxG4vHMDqenzmKs9RuzfCRHeiQR5ZEYu05dmIkQC9H14DssHq9mfeymfN66gRQ4iCUp+uSxnlNhlWWbjxo10d3dz8sknU9fbx/XtwxTr1DyUkzS67giCgF6vR6/Xk52d/RdbxI6T/Y+p9wE/bJ/7j41oNEowGESv1yOKIkqlkoULF7Jw4cL/9ND+JfzXR+5wTDf5jzE4OEhtbS25ubkUFhb+CbH29/fT3d3NjBkzfvCxSJJEY2MjAwMDVFRU/FW1uw0bNtDc3Mx1113HwYMHycvLo/rTDxhsbWJO9tWorCGSbq1AF6th8MWD+HqsuE/Sc0/T4wRjQ6S4H8biCXL3lNvY1zuOtq8LuTgvhLz0EJFIKzG6n7Jx4wj+PCsndh7lO2kuvX0q9qRUsH3gGuJTvQwZfkeVpYu2gc2EpWOytLJk5+Tb78VysJF92z5EWzINu9HAyxNO4JQjHzKhtYlxYxxcWP4Yl695mu/K+rDGuvjNnhxS9rRw208f4EhBIa+0PEdy2hYCKj39jSdha1pGXJyPkDPImYl30WtXcZV0K06NgZiMN4k3RHik5yfIUSWVTg0+SSZp5AhTRl7l25WF/E5txWLyMcmq5YTYbHp7xqMMmTAbDIyJa+bB7lIG5QTOUWzj+sx24k+6DymxmJ6eHhQ+N/s+ep/h9lYyx41n0srlRLTfMTy8jkjEhiAUY6uNRd6Xgk+cREt2EkPxI4TUfhr06fQkpSIbVSDLKJ1BMvpbKbRvRq13kKI1kxiNJW/RPHKNuSTHJGPWmCEqYBneSUfPrZj0y0mNvwu73UZLawt5Bdnkj8lFqTqWVnWH3XS7u+l2d9Pp7qS1/yiho7UkDutQKEpoy57CvnH5hDRJaCMySc5hMhxBph/VkqrsZLD3a9bmXMwcRzUF9kOkOD2MiSSTvnIxMQtmoszN5cuvvqKtthpd21HGLbgSZUc/rc58BkotfFicReOeU2grfpxVObNYEmegZN8Ohls70XbUo4uLpei0M9lfVUMwGGTy5MlMmTIFvV6PLMs0Nzcz3D1AYWoeDc2NVHfUEZYiuHQOak11hFR+ZrsrOCE4hfLEcjR5ZsKZMVzyVQMZAZlHxmcQONqL6FIhYiOsqWJ30IPHYmMoLZWoQkmWOEBRaQlZLR+TFzhKe6SC/bYbSFEnkK0R0ApKKmMa2RKznROlw5hTI6gOiBi+VSCmymRMttLtzuPByNnsTxrHjBwTQn8VvwxvRMElPJj6KQfiaolqpnLOkbNJ82go0PUxRpmNzzBC/5SHkNQ+Qq5UxCNlLNCuwRPW81rkQvQ2Fym17Tw+4zRCBV/w4qzbMaeU8eKbjYzpDDL25AyeqeugecTHdS1fospdzBJ9OhpJyVEhym1RL4/NLeSEeengtxP+cCU6Wx/vjruB5CNzuVnyIkpRTiwy8fi5x6q1ZVlm69atVFVVcfLJJ5OUnsF59d14tDF8XJJJ2t/p9PbHwi9WqxWn04lOp/teVP9Dm7Ts2bOHkpIS4uLiftDz/hioq6ujvb2dW265hcHBwR9Fsvf/S8v/BRwnd0mSaGlpoaenhwkTJvzFlM9x5aLZs2f/4OOoqqoiEokwceLEv7mnZbVaeeWVV1i2bBnhcJiMjAw0UoQ1d/+UE864grQj8djzTBRfWkK434Pj5XoaOEjjBBWvhF7h/Jy7eHljLLfNs1Osvp97d9/JPds/Z8qbd1LTdhGCoGVk+C7aO3pw6d8nZ2QuHo+WNxSzmRAZ4D3tPfij2diFZzjk2EGH4wAAgmhCq4uw+vEX+Pr+X2Gx9uIuHoczI5cP88tY/ekzVKidDIxL48X4Mzj/s+f5avYwqqifZ6vKUO46wtV3P0FHajKftT5MJLsKSTbTWXsG7u7pxMUHidg9nJZwDwM2JddHbqHXkERc8rsYzA5+2XMThoiBIy4FjigYPd1MbHkB+2IVv0rX0R8zTIpbxZmxOka6FxENK9H4M5lb1sPRjm5eDJ6IX1ZznmIbF1SYiZ9xDYLWgDpGQceRgxz4dA32/l6yysqZsHQ5upRBhkc+weU6CIhEAnl4qjXQkkeXPJuXU/QkaIIUx4/g06jZbywkGq8hrD22564L+EmyDpA11IY2MATSMEqVlZJsL+NThrAFtBx2jSUkiTgDXgwaDWJIRXP1dFLjdqGhBzFsQimbUUoJuE15dGTk05eUild37B4y+9wYvb0Yggd5teF0DnvCaPResoZ3oz20gZ15KdSZxpIsD6GTQ5x1/+NoPrMiGlToLyhkw4YN1NXVEe8tRbBsJLM4h0meORzxtrM2t4juHAd7qi7kS9s9vH/KMgaNIh/kxPHWW2+REFQgtdQQxMf4RSvwJyRQdbQOSZIoTswjy24mzWdEGfkDAbyTvJ79qgZKXGPRhnWoFEpys3LIG1NAiiGRWI8GqdNDsNmJEIgiaaHPsIOAp4kWUc9AJAlZVKAKOJEz9CxSDGNSKynq/ZBAJIGjvtvRigUkKUQCQpjN5r18l7iVU6PdpMXJKJwC5nfUKG0yiWUu1DlGnuuYxzv5J2HWa7h8YgzZux9mhmIcjYpZPJL+Gh3aITL8c1nSfAbGkEyxcpB8XRa2op0M57yJIMrYm+dT2txFiekgQzE61lpWE5BFgi0eNk8dgzX1Q35WeiULslbw6pstpPWFyDolnWcqOxmxuril4RN8xUtZbsxHHVbQhcRVsocHFhSwbHYGgqsP5Ycr8Xs93DnhXq6pKeMKrwNXNESiXs26G2YToz4W8e7evZt9+/axZMkSxo8fz00t/Xzr9LNmXCYT9P+8kcpxga/jZH9czvU42f8QJi27du1i/PjxfzYD9N+Gmpoampubeeihh2hra/vR9PinT5/OtGnTePbZZ4FjfJadnc0NN9zw/58FdXDsqec4sYZCISZOnPhXNYCtVit1dXU/qBiB0+mksrISs9nM+PHj/+6U07p16+jv72fKlCmkpqaSnZ3N+id/jX2wj5kpl6Gyh0j8WQUxZg1Drx3G327DvkjgoY4XcMQ6KIk8zpFOBw/O+iVdriQ2b1jI83leLKf0Y7F8g8m4ki1bEiEZJg29x77gmai6nbySciKvdj/GkjFVWGN+ysDIJGpGNjPo7zombgPkTazghPOvYs1dt6CNiac3PYWmcZNoTDBx1tvPMyPZwoczzqDJm8T8bW/z+Twr2cNhHq8bR6Cmnot//jjWeBMbWu/Akt+FGEqktXIVvqFS4hIChK1BTov/BTanxE2+m2iIyyXZ9ClCWgv39F1NkT+HI94oQxEBVcTLhNoXSCrr5LYpY+kTuggroywOqsgIz8BuT0IViEdvCHOyfhtfWpJ5R1qGQ9YxQXZSGEpi5dwcyudngFKi48B+qjd8gaW7k4SsHCacuILsijG4PDux2jbjdh/BHojh6cPX4gyYuF23DrUrkyFVCa9KSRhVIYribYSUIo4YA1aDCZdWj0unJ6L4fsSkjIRRR8KIkoRCOpaqDytVhJRKIsrvtycJsozJ7yXO58Ls86ALhYj1QoLTSPqwjs9KH+DJnptJGLAQPPwinvET2FI8nkYpwPjGg4QVWkI5hVx23fUY7Uqsv2tgV3YHnSO9JATGEa/NIjn7KI1bN3Na0U/QnZ/CioODlHi7eLP3WqryX+P1rlQ+mmPk69JsdNYhPvnkExI0BpLarfTYqkEQSM0tRjummNauYbxCEL06htyUTDIzM1GmarnyyFVcWnopl2ZdyFBrP22trXQMdjMUtAEgygI6UYNCrSQiRvEFvCCLCLKExu9H7/OhKchBGZuI2tHKfPtm4shgKLQSBQWIQJ/g5tvkzQxmbWaONkhijITgFjC/p0Z3FLQJIZKnyWzrKOTx7PPpjUni0mmJrLD9jqLOHbgit/CNqZ8X0j8moIxjYVcFJYNLUERFpmiCxGnUDM5+Bl9MI5FALN7DJ3Ki9330GidtSXq+qzuJvsRUOga0KKeMUBuzj9Lk8Txc8WveeKWRmOEQuqVJvHykF7XNws+OrmWwfDkr4ieg8oFFkrhI8HD9CbmsnpuNOFSL5pPzsEky5054mod7s3mhy8K+SABJVPDBZZMYl3asbujQoUPs2LGDuXPnMnXqVJ7tt/FMv51rgzZ+Onvqv7SW/TH+2KTFarXicrmIiYkZJfp/1np1586dTJo06X/CiKWyspK6ujpeeOEFamtrf7TrrF27losvvpiXX36ZadOm8dRTT/Hhhx/S2Nj4o1jN/k+Q+8jICEeOHMFsNlNWVvY3bVqPF7otWLDgB7l+X18f9fX1/5Sb3PDwMK+//jplZWWMHz+e3Nxchjvb+fDe25hz+uWkVyZgzTBQcnUpkWE/tudraAwdov+EBJ50PslU1XK2183hnPIwC5N+xhOHrmfl5sOc89SNVI9cjiQFUIiPsX17LZasak7qjnBIquCINYnO+Fx2WK8ixhRiOPYDaixdtA1sISiFQIgB2cWiK29AK8Xw9euPY8osoS/WwNfls9FKI5y89j1WFFu4ccbdJNe3kdO0nq9njTCjSeb25kLc3T1ccuuvcMXrWd92KyN5AyhCibRVnY13YDyJGRYCfUpWJtxDwBvgjpEr2Z4xmWxhB+7CLdw6dCHzXFOoCXlp9ysRZJni5g8Zo97C6yumcohBuk12sp0qlhtjsXXPRYoqUAdTmTFmmPKhNWzxFfC2fBL10UzUMhRJIjHmXiZPU3PDzDPpb6ynesOXdNdWotbpKJw+m+RJJ7DTruSNvb2oxDB3zd5EonIvknTMKe3+vbdTGNvB+UXrkCQloaiSQMCI33/s1RvKZVhIxS0YiAoKwkolEVGBLIhIooCMgEKKooxGEWUJQZZRRmXUERlNSEATMmD06kl0qonz2oi1txJvayDe2876CQ684+dz9fAqLp2jpVEjcGb9XnL3b0UQwJU3HVkZpHjafKYUZfDl2nX4w0FM/lLitCksu24cgzsOsPHTZzjz0vsJmiUWeBTcdHg3d/rvwXbWBpoHklkddjIhIPDm/AKs9hG+/PJLnE4nBaY0kvu8DI20Uhw7lWRTPpaokw71CIMqB9bIH9zkjOogsQYbfns2YUlFVCERIkJY+oOipCRIRImikqPoohLRsIhKENAnppImJjDWbiU+rCMsFwMiNilAr6GFppyvMCa3kKs+9v0Jw0rCR1LJ/sYCkkRSRYARycyT6jPYlDGZ8lQtT45tIH7vYwiRefRLq3gqfQ17TNX49XM5ybKSgqMBVFEN8/RqhKQOBic9gawI4uyYRXqrwDTVF4RcClqUcbR0llFTVkGLx8Ckibtp0uioDrbx5oz32PzmEGFnGO/CBD443EuWpYfbaj6gaeapnJw8HaVdwiPLXCx4WDwxlbtOKkLZ8g2ar69nUBfDstI3uDaUTHTvME/IAQB+tiCXS2Yd86Ooqalh8+bNTJ8+nTlz5rDe5uHm9iGuidcxY6DjB89I/jGOm7RYLBZsNhvRaHRUyjUhIQGNRvN3nee4kt7/gpzroUOHqKqqYu3atezbt+9HvdZzzz03KmJTUVHBM888w/Tp03+Ua/3Xk7skSWzdupXMzMy/m1jdbvdoOutfvXZTUxP9/f2Ul5eTmJj4T53nk08+oa+vj+XLl49WI2947gmG2lqYnX8NupEQpuvGY0yNYeSDGoJ1djpKh3jF9SXNpmZWxr/M7/ZZeXzJZ8iheh7ZfC1vWncQc+9s2jseQqPJpO7oebgDHhTSS8j2UxFsEV6Kmc/UUBdv6R4gEEnHpniRg85ddNr2AgKCaEbEyapf/paWr3ZwcPdniLlluM1m3p44nwkDB5i3dSNLxgxz4fTHmL57G4JzF99VjLCsSuTq9hw8Q8NcdvOD2JJMrG+5GUv+MIpQEu3VZ+DpryCtsAlHawYr4h4iJtLHI22r+F3BUjLCzThLP2S1fQHnW5bTK/s46lIRlkUSrdWM73obyyIDT2aa6Vf1EVRGmRlSMsZfgdORjTJiQKc3cUFxB4kNb9MeSWBddD5fB2fSKcQiC6AWBbLidCQa1RhDTgw9VSQM1BAT9uBUmVDkTeD0UxdTMO5Yq0s4bCEYHOD010eYlu5gZVY9gaF+PF3DuDwe4mzFSLY0opE4ghrzsZdKi1enISpKREWQRBlBBnVERBUR0IZCaEI+VGEPKSe/hNycguK7NAxKL4kZOmLysnFlZ9OclsXmhFS2DXYTO3A/a1p+zf7kEYYaPiXi9VCxfCXGxCS2v/UyzpJptAnpFEq9mHXxqHoKSDWbWXzzeESLn4E3D7C+62VOvvUXrD3SzOu5Yzm/bwuPdD/KB/bnWXzLPF7vC/B00MMVVUGuPrUAY5KampoaamtrOf3002nYX0uSZCJVFY80HCDc5YaQRNgs4koIs9t5EFXCYfJzDiLLCkKRHBzBFHr9CirddtqVevzGHJbEhZlmTmLJ737D8MZkNBWTUc+5GanDg6wIEdV24DI0MRDjImzqQ5XYikoRwR8F2S1hatPS157P5CEbUr0DQZQhXuTjhLl8MHY5Sq2SZ0pbmdrxEhqfnx7/7TTrY3g4+01sCj+i4RLua6nA3ufGH5GZqI+gnvQ5ruStSGET7gMrmBf+mARxAGujniF7OkNhIzvnzmVQoWTm2O8wZF3A/c2Pc0v2XQS/zsQWlWiZYmBn7RBThxq5qeZDapeczcnp85D7AoRkmatFLym5Jp48fQyG6lfR7X6M3kQDy0veZ6Iigas2WLgMN7IsMTUnjpcuqEAUBJqamvjqq68oLy9n0aJF1HiDrG7qZ2mcnp/HKmlubv5etfWPieNRvcViwWq14na70ev1o0RvMpn+bFQvyzLbtm1j9uzZf/fDwH8S+/fv58CBA3z77bd8++23/+nh/GD4ryd3ONZL/o9Ey36/nx07drB06dJ/ev8kFAqNbgNMmjTpX3oCHRgY4K233mLKlCmjDxz2/l5+d9ctTF95PplVGdgTtZTcNAHJE2b4iYO0uWsYnJvAk+6nmZQynfq6M0g3yVxZfB3ftC8musHA3edMpi3nHbzeBvT6q9i0MYiUGWH2wHp2h09B22HhpbTlPNH7PGcV7sauOJcR9+lUWr6l19vIMXGbGPRGBSfe/gC7nnwRq62TSPEEgkkpvDB2OguOfsOs2v3MKhjkvKlPs3zTxziFSg6UWjjzgILVran43R4uu+bnWNITWNd8M66CQcRwAp1HT8XZNZPkwu3Y26axLPY3pClqeb12Mc8VnIMohIjk/46pxHB732UgKah2q7BJEdRhP6V1r5OVUstzS6bQEbHTbBpEH1awWK1B3bOASFSLMmgmOy+Oc9LqUFW9iV+KMCwk863rLPaFZ2MTRYhVoEvQkRCvJSlGSWF0gJj+evpqDhNwu9DHxZNVOoGMcePJKClj0StHuXxWNlfOOSadWb9jCzveeoULn30Dl8uF027H09VF4r33MVxeTqS4GMEfhrAMSCgFUIkK+iMKNg/IXLcwh5iURHqMdyEZLqAt/iI6wxHa/CFqPAGc0WOp/BKNyPzuZqrbnuDy8GWkOmIYLBhk0slnEJuSitfjYc0vfooltYCD0WyyFGYmjJgZVxhLgdWP8ZRcvF93E0wIs27vE8xbfQWriWes14UyKcrTTev5tn4JokJg4XUV3OiIcMTt55w9Hk6vSKVsQRrPVz9H30Afk9ImMaVgCokxiahEFUTBdrCLkaNdBE4ycdRdx7tN75KglClWh8jQqPFoy2gSyqmlHLuQgB4fr+ufR+3rRa7pJ2SMx28yoxVdiDE2oqo/RPg+v4m+aJjGSIQEe5hZDWos7jxmxEYJfdtJNCigzxXZ4h7LqxPPYFhr4ub4/VwY/ZTYYD9tnhOJipexJnkbHydtJKQuYGboCm6xx3Gg2UZU1uDJ2kLFpI2gduHumUFqk4ppqnWEXQr6D5jxhJPwCRE2LVtKQBdlfH4Hs2b9mp8evg2zNZ0pNWfQp4XdBSra2xys6D7ApfVfUnfGahanLkRq9xCVZX6uCTIcq+TdC8YRv/MXaOo+pD1Lz7VFrzIoZ/H2t05uDjvoi0bR69R8ds10Eg1qOjo6WLduHcXFxSxfvpyBUIQzG/rI1qh4pzgNj91Oa2vrjxbp/S2Ew+HR9L3NZkOW5e9F9Wr1sRqVaDTKjh07OOGEE77XxfTfij179rB7926qq6t/lMK2/xT+J8g9HA4j/X4v8+9BKBRi69atLFmy5J9qx3C5XBw5coTY2FjGjx//N7cB/h68/fbb2O12brjhhtHzffva83RWHmJexU3oe0IoVhViEYYI7R4krUdHc1o9n2sb2K7bzhW5T/HkNwF+saCHHOWT3LfrNn6x4wumvXon1V0XAzLRyK/Zs+coAxlHOLlPoFKaQOuAnoPJZXzbfz2pGU5GYp+nZUigZWgb9vAIsiwjCBCTnMj8K25m79PP4g04cRSOIZpbxIs54zll91pmDjQwNs/CBRW/ZdUXb9IT20R1kYULd6s5vT2eoNvL9Rf/lK6iTN5pvRMxpxNJMDLYdCIjjStIKt6Me6CMWcLHjNVuZUtNKU8mnk9jfDaxpi3EJlXz84HLKPbn0hAK0eKXEWUl6QO7GDvwMbYT9Dydn4kn0keP2U1SUMlspRllz1xkSUARiqM/7jCnG2pYYhsAWSKkSabdUsAR39k4IhloDRKZ5fGMm5lJQroBSZIYbG6ko/IgvfW12Hq78YtaXsu5lMvM3Zw4NomkvHz6Go5SveErLn/hLeAPIi55Tz6FcfYsEu6448/+5rXVe9jz1e/4zdRr0Ju8vMAVPM3PqBRnka1Rk68UKHONkDHSi6qzlcG6GiKhAE5zEF9JPj8ZWo35p+UMuyxUVVVRX1+P6LIR1sfS4s2iSpnG2lXl5OaacD5di+yPosgz4pkU5ovH76d71ko+G1dBnlrJdaHbSOvpIit0NbvrMwlIRqadn80DGg17XH4mdAWZOxLBot/IYfN27BH7X7yXJUGLoM5Coy/DLqQQVucTVqUBMEYrME3rYLK6jxK5iYBzBEdzKyGlBknWYKafVKELny+Ng47lBOQQnbF72KqzkxuOsKpLRGtNZ0auCDuacbbrUJsFOojjxZmXc1QTxx0pB1ktfYXG3UWLNwt78AqUpjzuyXqTLm07Kt2p3NO7lGytldpaFVGFSOaU91Fk7kMKm/AeOIl50ifE04+1wcDwUSOSqGbEqOfwKVMIoKNkrJrFi25jXdc61m3eypL2i+lIVLIhLop30MeFLd9yesu3tKy+lJnx85Hb3MiyzLNmmS3hIB+tLiBv+w2IffupL4rhd/kP8YZvIi8dDfHdsJ1PQiFkQeS5s0uYUxBPf38/n376KdnZ2Zx66qkEEDi3sQ93VOKTkgwSVMpR974fS4v8H4Esy7jd7tH0vcvlwmg0jkb0NTU1zJs373+iHe67775j27Zt9Pf38/777/+nh/OD4f8kuUejUTZv3szChQtHnyb/XvT391NXV0dBQQF5eXk/WOXkoUOH2LJlCwsXLhydnB6blfduv5Gy+UvJaynBJkg4F0eZOL4c1wu1WOw9hFdmcHfzwwixAln+h2kY8PDg7Cfoc4r8btMZvKI4SuSGTHp6X0Krzaeh/hysThsB5ZskWhfj82pYI0/BpJbYEL4JWVDSr32bGncLPcM7CckRkJWAn8krTqVs9nI+vu9OZKWCoaxs/KUTeTclj1O2fsAJzmbi88NcP/YXXLDuNZpS22nIs3LRTgWn9aQQsju49awbaZhYyG86HiEzrQq/Roe7cz7dledgyt6HzmwjpT3KbP1btHYl8or7VD4tnI+eAcj9lNXecs61LMcmhzjqVuKQIqgiXsY1fkiudj+bFpexWRXFrhhhMM5PclhkopSOvm8aAgLKSCzjxqezIr4ZdeUb4LcjG9KwOdVUu1fQFppDWNKii4P0EiOFE9NIy49DEAR8Tgff7KrhnsNRbmAPyp56opFj8rSCqCBtzFhURhOeUASr2YWnu44V/Ymk3XsvCrUapUqNQqVCliSikQie6nWYdj7EM2OfoVjfjGLwM1SaC5BtLlxDgziGBpAiEUSlkuTcAiKRLBTqfBaOcfKzodd53PIQe8yt1Ae6UKliCDiSMEZFfMZ2DE4frxsXsqoslWucApF2NwCqxRls2VlFz/BBnlq1iitDLl5Vm3g+w05c91Vo90FOyvUcblDR6xtD6XQl9ScU8XyPBQugC0pkBiDDqEBnChGSA4RkcEdFfLKKkagKe/TYnFAKUKhV4HIewOM6xAVZpVxfvBpLm4+uGiud1SOEgwJav4UCxU6yk5vI1x7gi+DZHM5ZRZr4LGsUrfhEgZUDUN5nZkauiKa5mYFDZqSQiEup5Y0TLuWQIYnrjNtZLWxCHXLQ4Mug1VZBgfk8DsW18FTGBwSVWuYGr+BKazJNXdtBXkA0pZ706W8iq7z0dZUyvklNhW4zAZ+awe+MON06tJEom7KnIK1Q4XJkMGVKAfPnn401YOX+159hcvtJNOWpWR/1oXCHuf7oVyzo2EXnxZczTj8XTZcHBIEvMlQ8OWBjzWkmJu29Edk3RNVYJd25N3CT80QusMhMqXbws7APEYkLpmVy8/wchoeH+fTTT0lKSuK0005DoVJxY8cw+1x+PizJYMzv9eiHh4fp7u5mypQpP8ia9EMiFAqNRvRWq5VIJEJKSgoJCQnEx8f/w+vwvxPbt29n48aNhEIhXnnllf/0cH4w/E+QeyQS+YdEaWRZZtOmTZxwwgl/dzpdkiSam5vp7e2lvLycpKSkf3a4fxatra3s37+f4eFhrr322tF2kwPrPuTQ5x9TVnEhJbYU3DNTyF+WQ6DRhvuDVo5Ke2ibaOCV4CucnnUZH+0sZn4BnJF5Pe/UrSLjWy8/vXIRzfHP4ve3Ext7OZs2AslQZnmPKv+ZmLuHeTr5ZE5x7+O38c/j8KTh0b7EHucO+mwHAQWIMSC5WHDZtSTF5/DZb+9DrY9jMD0dZ8U01prTOeXbNSzwNhOTH+Hmop9z3hev0ZLaRkOujbP3ipzbmUZkxML9S6+kfloRV9s+YHbsBhyxauT+WTTtPw+NcYi0ab+DI5NYIL5H0CvzdWUFLxefQY8pGXX8DsYaW7h1cDWZoRSaghFagxJISmKd9Yxt+Zi47H5enzeFZlcvTr2PwYQghqjIhEgyCYNTUUtqxKienII0zsz3oGtYg2KgElltRFLo6HWkUBc4ie7gZKKSCqVWJiFXS/a4BL50+Pm6aYQdP52NHI1i7+9l04tPIiCgjU/EPthPNOAj7PMi8A8++AlgTEgiNiUNc0oa5rQMkvMLSczKQaFS0XJwhF1r2lh6TSYPbHmIm+1nYlNGqXcJKPyxDKjDqBKqyUwy4tz+NZbyK/jIpeJ9QxzFp+QRbnRgrWxni13JztIYpOwgyfl5fOfysbMiD6flS9raf0HsWgWZ5dfQNeLiyMAsYmJCqIoVaOcVc9AWoWrAw4gUJaISUWoU6DQKErVKkmJU5MSoydOqydeqKdKp0QgCgx1Ovtq7lb4OG5nOYpSSClmWEASRlIG9FLV+yLgze1CKURqKr0epGuAx6272azVMtUuc1atlfpwLjXeEgapU3O0CEVHkk5ln05qq5wLVNpYIBxAVCmpDY9nfriXFeCLFseN5LPNjDhj3olFO4cGhC0iIGcFa1U4wNg+x7CMMGdWEPEnIhyZxgrgOnRBguCEWZ7WGgFINErw66WQK5nXi7h1DRYWRE0+8FkmSeeHVj9E3ZVEzVslGqwdTJMpPq9YxuXs/3RddTKZyPgkjxwriqscYuL65n7dmDDGv/h7COgOHxgRR51zITe5z0Xgi/HabgwsjNoKiSEGyiTVXTsXtsPO73/0Ok8nEGWecgUql4vE+O29b3Dyfl8QCsx5BEBBFkcHBQfr7+5k0adIPujb90PB6vRw4cICcnJzRvXqTyTSavjcajT9au9k/iuP1AZ9//jlms5nf/va3/+kh/WD4P0nuAFu2bGH69OmjkrR/DaFQiOrqaoLB4N9ss/tn0dHRwdDQEN999x2TJ08eVT/q7e7mq0fuIT4ji2nCaUhBiYw7J6KJUTH8RhWBNhv9E228ZP+KemM9F2e+zDObrdwz/yhZqne4d9fP+Pmur5j9/K1U912KLEdQKn7Ftm0NWLN6Oamvg/3SCaharbyauYwn+p/nrPzd9LrmElb+hIP2rfS4aoBj8rRIDk6+9RcIdon1bzyOJjaJoZRUHNPn8qEunlO+XcNifzO63Ag3jfk5533xJp3xLdQUWVlxSGB1fSLi4DCvzLuA6unFlKvquSb6Iv0ZGjS2cdTtOw9CetJmvoJO8lHa6CWVJg4dzuFz1XzWFC9CIXrRpG3iolA6Z1mX4CVKo0fBkByFqEDGwE4Kur5ENSbA67MmEArK9EZ6aEvzIIkyOVEDabYykn0pqKI6YuOTOHVGLllDX6NsWIcQsGPHTIxaxO6JpyWyiI7QdJwBM6+aguQhcnFGHOn5cZhT1Gx45hZyZi9AlzcGY4GRuw7fRZImkV+1TcP5xXoSnn2aaChEJBwmGg4hCCKiUom6dT2a2vdpK5xFMKuS8eUvYY77g7CS2H8Esf8w4UlX4LIG6G9ysu/TTvRxaoZ9vWQlDZMdykYxtZSsCbG88ekn+B0WTs9bTOP29/BE/byTv4riLBMvnF+Oz2Ln5Ud/izPuFNRilBOuLuPi5gHuz0nmolTzsfuw81EGB94n/lkFieXn4E9y0NySRVdwCjFGBTnlSaQWmlBrRQaaHcQ3PUfl4Eyc0Yxjg1aAqBJBAikqQ/QPy0dIDODQDhLv0jEs+hlKSWBV3SeMS24mI7WBsACvxsbymtlEXEjmiv4IZws2FESxDRUwssODFIX6CVPpGqPjdMVO8oV+IuZ8GqTxbD7iRIuZacmn4zC5+UXOW3gUTmYHVnGbbg6HK9cxRixlqGgfyvwtyJKSQNMCygeqydbU0kAh9t1KYntcyIJAhymdTxfMYvHUrbTVzSc52cIFFzyGFBH55u1qhhv87Bxj5+BIDBlShFuPfMqY3oN0rDoPs7CIXP+xNWmwLJZVdV28kbuVeQNv4M2ewMHMXpIyVvM6l/PpsJN3d3l40jdAtaRBoVTw6dXTiFOE+OCDD9BoNJx//vnodDrWDDn4eecwd2XEcWGikT9enoeGhrBYLD+6rPa/iuPqocdbkYPB4GhEb7PZEARhlOjj4+P/o/vykUiEnTt3smbNGoqKinjwwQf/Y2P5ofF/lty3bdvGxIkT/6afu9vt5siRIxiNRiZMmPCD7K//OXR1dWGxWPD7/ezevZvLL78cu91OZ2cncXKYfe+9zsJzfkLiAQ2WdAPjrikl6gxheeowHa6jRE4r5N6OhzCb4kj03M3RfjcPz/4tFm+U17as5mXbDjQPzKe980EUilgsI7fR0NhKV8IWFg+m0xItoHNAy87kCtYP3EpR9gBW7e0M2SZQY91Gv68FkBFEE6Lg4cz7HsVTN8CGD59GHZeKJSUV2/S5fKSJY+mOTznZW4s2K8oNY+/m3C/fYsDQxOESK/Nq4PqWXGhuZeOsM9hUUow50899rl/TVyCiCCTTU30Kzp5ppI7ZQ+z4d0mrN1Ji66B3IJ7a2kzeL1rGnvQJKNW95MXt5yfuGVT4SuiNBmn0CngBUYqS1fMtuX2boDjKe9NLiQYUuNwDtCY7GY4PopQFUgMpJHnSSAmkYJTiGTduLPHOGlKGtjNObEcIOJBVelCo+MRdwa3Rq7hfaEAZysbtjyMcaCHs/Rox5VxaixrYbfyadDGL25MfILaxFf/ad8l+5zU0ejVKtYgoCgiigKgA2nei+/w8ujNicJRfiln3E/zuMH53CJ8zTHzXu4x1v8Sb1vcJho8tcAqlgEavYnyZTEf1Rop009GfU8iGDZtwel1sChYyT5nC6iJYv/63qE++lt/UwVPlUT7p6Wbz1Dlcs3GQfLWRR5eYKNCpeb8kE8XvIyVZjtDYeAMu+0HiHpdBO5bcW04juOs9mhyTaI8uwOv/Q4WzSAQJEfh+VXQAGZ8gIcludMEOVKF2AjEK1KUTKZs7l4l5SRiUMvZrTiG9sBqbQuTq1GRa1SoudHq5zmHHK8USdWZj32JBjkAwxYg4LcIEfRthQU24YCk9msl8+sVB1CEX8XHzmBs3hXeTt/BJ/Hr0ZHO350oM9OOp6SdnvMBwwTpkRRBfXymZTVoqNN8Q0mhwxJxM9foO0vsHUESjfF50Av5TAkzPqKS25jREhYfFi7PIybiUbW+10tdt44PUdoa82ZSHI1xd8xm5vQdoWXEqWsVJlAoCMhAsNXN+cwsvGV5hon8f9oplVBoPkJp2IW2m67iqZYA7GwNIQyM8Ezj2Hd63YgzLCg188MEHKBQKzjvvPAwGA/tcPi5q7OXspFgezk1GlmVkWUaSJKLRKA0NDQCMHTt2NJo//u9/E5xOJ7W1tcyZM+dP/iZJEi6Xa7Qwz+v1fi+qNxgM/9aoPhgMsnv3bt58801mzpzJHX+hfuZ/Ef8T5B6NRolEIn/7wD/Czp07KS0t/avysAMDAxw9epS8vDwKCgp+1Juqt7d3VLL21VdfRaVSUVRUxOTJkzEYDHz+6AO4RoaYXXgVMQMhFGcXkjw+Ac+ePvwb+6gSd9FQrORd+V1Oz76Ez78rY3KWwHk51/Fl+zLYpOeu+Vn0zTyIw7ELg2Eahw/Nwe1341W+Q4p1AT6flg2BYoYNCex034Ap1o/F8CRtNg3Nw9uxBYeQiSAIelSqIGfe/zjWAy1sXvcSmrgULCnpeGfM4x1tPHMObubM/u9IyvZzbdmDnLTpQ4JSFXsm2Cjplvl5dTbqujYaK+bxbN4M8nO9XBl9k2i2BZ9GjbdnDr0HVxFrHCJ9Zj36yCeUNblQ+cPUHsig3ZvJyxNW0mrOQtT0cqKumys9U0mKxNMVitAQDBOSFCjkKNk9W8jq2Yo208vX00to0seS3uehXTPEQEaYAaMXSQBdREdcMI74YDyx0VimFkxlTkIMec5KXO37WTZwFZPEFl42vEY4EqRPkHjLW0hDnEh7cpAIElNcc5k+uJKwU0SW/vLUUWgdpExYw0L7t9jlONa3vQTysUVYEAV0JhUZccOc6L+UpuJnEYsXk5hloGnvENVb+jjrokIaX36JlMT5PG7+kBJfESemz2CNSsOnXTa+/cks9rz+NPb6OlpNBXy2YAkBjYaf4MO8U02tRmb34ng+Hp9DvOr7RU1+v5Oq6osgMkjKcwZUIwKJd96MUXkE1ZHX8YqZjGRdhCd1ISFJh3LgIKqOTejDXaiTUggVTKW+O0jT/sPIskTh1JmULlpKSn7RsTkUdKGseg/FwZcJD9jw6GF5QSqZkQi/HLESb1LR3j6OkYCRsXuakCMyKRVOYvKDtJimkzjtHILGEj578XWizgEc2myWp5+ERhHhzrx3GFS2Mt29lBXqhbiOfM7YvCRCJTsIGfpwds4goSOGqcIG1KIP+7gT8O7JxLfhW2QELLpY1s2Zzazl2xB8ehwjF9A/0k95xQYU0Tvo22XEGZZ4w9xNMJTC4oDI6c1fkNe+k/q5SxC1pzElRoUgAGNiub2/mkeivyZL6WRo9lnUR78kLe0iYlJv5qTaLspGwtxY7+JStxNBoeSEMUn8ankOa9asAeC8887DaDTSGQhxRl0342K0vFmcgUr8w1okSRJHjx7F4/EwYcIE1Go1kiR9L6oXRXH09Z+GzWajqanp72rZCwQC34vqFQrF96L6HyvYOg6fz8eBAwd45plnWLlyJTfccMOPer1/J/7PkvuePXsoKCj4s8o/x7Wy/5aM7Q+JgYEBurq6mDBhAps3b6a+vp6VK1eOOg45Bvv54O6fMn7BcnJaS/ALAgV3T0IURYZfOoK/z0bveAtvuDZTa6rlsuzneWqji1vm9FMa8xi/3HcLq7/dwekPX01d+A7CERtxcdeycUMYOU4mzf0uA57TMA06eEM/F70ywqbwLSiUMGJ8jVqnhZ6h73BHXMhyGFGMQa2OcNaDv2H4u0a2fPUySlM8trRMVLMW8Iw6jgmNB1lV9xXjM4e4dNLjTN+3nfiBHWyZaiPRLXH/tjgS2qy40nK4fdxZlKe6maPdTlnyXgZStQx6x+PeexqyM5mKqSG8ikGyh16h0NPGwHAcfftNtMbk8ub4FbSYMlEpLZyltnNhoIQYSUt3UKYh5CcoKVDIMimW/eS2byVW20/ThHS+zksl269H7LTQb3TjzlXQq/cyrPYTUfzhflJEYvD2XEY0HE9O4WtI4gh2OYz8+/W1IBRmiS/A2S4XydEoEUGNU5eDbSQP55Zh4n95J2FzPhGUBKLVBCJbCMjbkGUVM/b3IYsZjJy0CY1Bic6oQqNTIogCki9MzBvTCKWciDflZiKDPro6Lex0DhCjHyEJAxOjudw39mVeOOllVHoNw+4gS57Zy40nZDFj8+vov97Ihulz+WbqHBbnFKPPTkF6qY36Yi03qrTkXViMoPgDUfh8PiorKzEYQJIfQ4p4SPmsgOg3h9HNmU38VeeiG/waZe0ahLCXaPpkovmLkFLGIzv78O95C7O3EVEAjzodZcEcxMxJyNpYBHc/iuZvEPuPABIeQeBRbQIN8Uqm+rVc0R4iTj8AShlHo57hGhOKeJm66QV4xi1h5sLT0Ctg0/PPM9LViEMVS0LibFYYJ7DDcJDnUz9AK+mY2H0e6kCIxYoq4iZ3EYztBH8SgQOzmRndQJyij8HEPFQLH8J6y7NEu7sRgK3ZFbhOE5lctB+7ZQF9exfjim+gsKiV4oI4aj85hwFFlLcVw0SQOcdpYlbfBooaNnF00ixIOJ8ZejWCKKDI0fOB/1uudPwGTWwqg/POoMXxFmlpl5CddQuXN/dTa/Xx7j4PN9jbsajjiNVr+OCiUr5e9zHRaJTzzjuP2NhYnJEoZ9Z1IwOflmYTq/zDw1g0esw2OBgMMmnSpNHCtOPkHo1G/yzRC4LwH4vqLRYLbW1t/3DLniRJOJ3O0aje5/MRGxs7SvZ6vf4HD8DcbjdVVVU8/PDDXHXVVVxyySU/6Pn/k/g/S+779+8nKyvrT2wpw+Ew1dXV+P1+Jk6c+G+TRxwaGqKxsZFIJEJqaiq1tbXYbDauuOKK0Ql76ItP2P/pGpaccTtxh2Ws+SbGXjyWqC2A5dkq2p01RFbk8mDP46hNaiaIv2Z97QgPzv0IHXU8tONGHjv0CWXP30RN99VAFI3mAbZsbsUWb2GB5xDVwaWkdvTyVOoplEa6WaO6j0hIiyX2bQ47mxgc3ocv6keWQ4iCFm0MnPnAb7DsamHz588j6o3Y0rNJmLuIRxSxZA60cd6BD1mW0sKlkx8nvb6RcbVfsXGGHUEIc+s3CiYMaoiEIzw+7QLsyfGcod7FCbHr6SlQ4lNoqe08D/2hWajj7UxaPh7P/oOMdzxCrNhHXX0mcoNMszmbd8pP5qgpEy1wvtLHWZFk9KjoC0nUhwO4ojJqSYMyUEdx2y7ibbV4skVqxuVSmxhHoUOJ1GU5VuyVZcISK9MtZVEZnExA1lIc/w16tRUlArGCElMwSJmkYaJCSUqgD3OkCzVWjiVkQUIgEFEQNcn4YhS4DUrCKhHQ4IqM5yXVqfy6+QESRbAWfI0ckJB8EWRfBMkbRgpFQPkydtFOs3g2w0oXIxEHyBBvSGKJvhS53cL5ZQ+xfuXXmNVmrD1dvPnuZyg7q0h2OUiXRTrNevYu/hl7W5ycrDRQ4JQ445IxsLYN7exUqnJ1VGTGEgl4qaysJDU1lTFjxhAKD9NQfyWRqJt81xX4Hv8d0aEhYhYtxHjmKehjBlC0bkDRvRsheEyZLioLhBUG1GoVQjQIkQDI0T8pLRxSKLgqNZlhpYJHhq3M9/uJRjX4lSl0bpdRDETZVDSFnrPP55ol0zFJPna/9TptNYfwiVq6TWWsKlpIts3Pg9kfUaPbx3R5Bo2tS5ioruGskn1EEjrQBLKIDMsUNkXJ1NQypEwnuOR8DOIyuq++Do3PQ0Ch4qPZM5l06mG0QgSD/mbCvRXsa/mG5HQdBYXP0bfrdo5Gi/g07EHW9LI8EGXZ4DCF+z6iftwkQtmXMEurQRQF5DiBPu1bzLR+xHDGYjxz5tAx8Bzp6ZeRnXUza0ac3N0xzFNHfGztr2GzMhNZEHjx7DG07tlAMBjkvPPOIy4ujrAkc2lTH3XeAJ+WZZOn/UNVeSQSobq6mmg0ysSJE//q3vTx1P1xoj++rP8n0vfDw8N0dXUxdeq/JpPr9/u/F9WrVKpRoo+Li/tBonqHw0F9fT23334799xzD2eddda/fM7/FvxPkLskSYTD4X/oM4cOHSIlJYWsrKzR944Xeuj1eiZMmPBvK+SQZZmGhga6u7spLS0lKysLu93Oa6+9RkVFxaiwTTQSZu29t6NQKpmSuBqdJYhqVSFJpQn49g/i/bqbw4GtDM5K4UXvS8xPW0JT48l4gyHunHwfPa4EPtp6Ks/Zv0P74Im0dd2HLCsZHrqF5uZBBtI7OXmwl8PSHJIau/lNzumc5NvPM7HP4XObscW+yR7HQawjhwnJUSQ5gCBo0Grh1Lt/hadmkC2fPE9EKeDMyENdNJa3ckuQfH7O3vkBFxsPc3f5zQzYVCze8QHflQ9jMbtZtVPizK5U5L5+dk09id+mzeKSjCGWet5EWdDPULKWbn8Jw/suRmtNoHacioESAytb17B68B2CEQXf9k6m6FAHNq2J98sXszs1GzmSwskouBANiSgZDku0hUMMihHEgAYEL+mW/WS27cHg78edaqA1uYC6HDUeZQYN3gyatXkkROwsCx4iPhSHoMwkohVAP0xU7SEkKZB/n04XxQharQe90o1e9BIj+9FHApikMIawH3UkjIoIIsfILoKS8O9fQdR4MODBiEcwYseEXdb/fj8b4rSQkaAnKzWB5oMZpGWaKHWLePsbOavsCVZEZ5JTGcZtGUFtMHFAzGXWiuVoCpIYfuxuavNnkm6vIDsssvSKYjJL4vB/N8DAtl7OVvpYNMbMsnjrMT/wP7IoDoet1DdcRSg0THHeEwg7+nC9/Q6Rnh4UKSnoZs1EU1FOa181zo4DTF08l1gdyNEwgq0DofcgSv8Q3oiKDo8ZizsB/G5+OUsgqhB4tHcMKS1OWiMJ7Fh0MbPeepyEgJMj00uYXVCFNPcX9B0eoG73DgKCkprYCUwZO5MT3HoccgcPZL9BRPBwmf4MjnQ4OLHgEPFxnWg8Weh8WlKbBsiQO7FEshkYW0bGSQ/j/mATIy++gj4SoMOURN35SUyaUIXdVkx5+aNkZBTw2lNrcIT7mTXVTUj6lvf3/5Ld4QimmEbMCVu5rmUB5Rtep7moFMWsm6nwARKgtSAqf0lSoI2N8ReSND0ej+8d0tOvIDvrJvpCEZZVdbK0J8j0liYeCMUhiAIXTU4hefgAXq+Xc889l4SEBGRZ5hedw3w04uSdsZnMMP2hsyccDlNZWYlCoaC8vPwfIrK/FdUfJ/kfi+wHBgYYGBj4Qav6JUnC4XCMRvV+vx+z2TxK9jExMf9UVG+1WmlpaeG6667jmWeeYfny5T/YmP/T+D9L7pWVlcTFxZGbmwv8bZvYHwuSJFFfX8/g4CCiKH7PI/i45OFFF11ERsaxauSh9lY+fvAuJi0/ncyGQgJA7p2TUGoUWN8+SrDNTmNqPd/EtLJdt51ri+/hxQ2xTM6UuSDvBr7pOBHP1mRuzfDSvmQApXIvKlUyVsst1NQ00JF6kJMHVNTJ4zHX9fJU4Rlc5N7IffHv4HUlY9O/zA7XbpzWGiKyjCQHEAUtKlWEU+56GKknyJZ3n8EjufBk5FEwYw6vJ6XTEFayaO/X3BHdwscFc1ljWMBZX79DW2oHRwvslHeI3LI7lpg+K67MPO4YexamzCSu031LqbyWzkI1IbWCoeFpOPaeR0Clpn16PP7EIOcdfZ6F9m8Y8iTSediIaSBAQK3m8wllbCpMxCFmc4K/mLMkPaWCEr8k0xmK0iyHiEZUKKIQFAMMh220CwGqjQkEVWpSAxbKIrUUq3rQebUEnXaOreAComACVSaCIolQrAJlmoL4FAP6GCVevx+/P4TPaifgCxD+O3p4FUjoxSAGvBhlN7Gyg0RsJGEjGSsx+Eej3w3221ALqYzRFmNWPsgdqZ30qdQ850hGkTGOnswpPDpiZr85EwElV+xpJqHfiKDV8aEywF0XlTG36Bh5eNa28Umbhceifu5bnM6qWcV/MrZwxElz7RW4A43kZ9xMUtZlBGtq8G3cSODQIcKtbUhASKlAG4kSky4RX+bAGB+g32fkkCWDQI+afFGLflwxd5bX4VPLvLjwFXqsel7fXM9QQxu/3PsqithYUp9+Eg191Lx2D7W2FIKoOBg7CVPmeCbFpbO0P8TvkrbxadxnjFFnc4pDxJDahcnsQmcvIt5VQOzgZtKCQ9gimRxwryL5zAqKxs3iwHW3kVx7AIUssXlcLtmXDBKj9REMnskJc25Do9HQ1dXF2rVrSVOWkjjuWV6uu5gWbwpTFU7qi37N6R3LOffDr+jKzse0+gFyO4MQltGqDmNW/obhoIL3M+9l/sReXK43CYeXgnwK8QlJPBDQ0OcJ83z1CNeO2AhoTBQmqjlZ14rb5eK8884blbF+c9DOQ10jPJKXwqrkP7inhUIhjhw5gkajYcKECf+yEMy/O6rv6+tjZGSEioqKH+yc/y/8fv8o0dvtdtRq9fei+r/3OzueZVi9ejUfffTRny0C/F/F/1lyr6mpISYmhoKCAlpaWkb3u38M952/hONOdtFolMLCQmpra1m0aNHo3yVJ4p133iEcDnPppZeOPp3v/3Qth774mBNX3UHs3ijWND0l15Yh+SIMP30Im6MPxxwFTw69T4+hh2sLXuJXX1m4cqqVGXEP8PSRq5j9bQtnnFyObeoWPJ46YmLKaG5aSU9fH42xG1gynE+PlI2ufohni07jBuen/CzpY9z2NOzGF9nh2oXLWktYln4fwWtRKkJknXgaabpsWr9Zx5Cvi0BqNpmTp1NZMo41HiV53c3c0fsJUXOYOwpv5cTtX6BxH2T7RDsxEZmbvopSYTEQ9fr4bMqpvJ0yjStL4eTBZ9DE19CZpUeKarB3zGG45iwS4u3MOHcmxkgnwrePEO/Zw6A9hbYaI7GDPiIKBdtLS9hU5qPfLJEWHMvpjiksDGeiFUTsEYn2SJTGSAR1RESNSFj0Yww0UdC3h/i+VlSRY5bCfpUSh0GDI16PyerHnmjAJwtEBIGwQkQWlAiiEZQadFolCV4/pqE+YktLkC0j0NmNFI1ydMk43syx0Fn0ADsrrybe28eWsb/B5/Gi12qI0aiJBF1sallPqZTM6eK3jPi1fNNXhFYRQRezhFlxU1DK7Yia37BHB7/KVPCEQ8tkzzAJIQfWSC5H/YtoDiwiImuIVVShjx9gTfrp9DqCfHHtNDRKka6WDlTrRng4GqZSIfPZ1VNJi/1TS095sIruQxfTnyiRrJ9L7rjHUCiOtYRKbjfhnl4infUoml4hPlzDgN/AEVcx+rxFlMxfgmHMGAS1mocPPsyWni2clforNtcoaRn2ciLD3Lj+KRSRCMYnHqWhv4u6rZuISDLF8VYmJQ/wQvajFLkymTHi4uHsd+k2VLJKG0ehdhhVTBTNyHiSuwpJjn6NOdiHLZJBjWIW9UPnUL40nbgYK533P0SevY+IILLxjETKF/Tj98eTmXE/Y8fOA46lut944008w1FEKZ7PdAKeYCynBw3UZr2LKtDBA+/aGU5JIfmuJ4k/6EX2BzGJ72MS1rJbnMSzxp9x97I2hgeeITPzOjLSr8Zut/NmzwgvBEWePOLkg/ZDHDUWo1VIXJPeh8/t5Nxzzx2t79nu8HJFUx+Xpcbx85w/aGoEg0EOHz6MXq9n/PjxP3h0LUnS914/RlFeT08PDoeD8ePH/6vD/bsQjUa/F9UHAgHMZjOJiYkkJCSg0+n+YjB3PMtwyimnsHPnzh/1geTfjf+z5F5fX39Mdcznw+v1/tvtB49L2B63iPX7/ezdu/dPzGxGRkZ44403mDZt2qiLXTQS4eMH7yISCjGz4HL0PX6CCzLJXpBBqMuN44166p37CC/L49dDT6M1aplneII3dvdxw6RtjIv7hl/u+wlXbtvEip9fQoP2EUKhIQyG+VQemcKwdZjW2G84YWQ8w5FEhCY7rxSezM+ca7gh+Qtc1nQcpufZ7voOt7WOsCwjyX4EQQf4WXDZNeQVTGXnb1+ixXKQaGwC+rLJJC9axC/67ASjImfXf8WF4U3cXH4/YtcIMw98yu4JFkbiPCw7JHFhVSyqETuO7ELuK1qJNyuPh8bbKKn/JbbMEQZTtET8BiwtS3A0nUhGlofJZ84hQToKW35FjPUgg6502upiMfW4ECWZxsws1k3Ooi63EYXazxTPeE61LKEknIVCFrBFZbolB0NBD/6wHlE0IctRlNE+EsLNZHuPkuhsQ/aECHpViKG/PTUkwKdR4dGqsem1WA063Fo1IZWGpy+/h5Ydy6i1JLPXkvO9z4VVMj5NlIz4POabW8mVGtg+9RUCchxjd0UQIjI/m+DgcFomEhKJvTeSHSphZXcFSnsqgXAiCtFLnP4AJyRsJT1wFICAOoHNgWLk/AXkjqnA3d/COJ2Kwb2FXCwFyErT88Ylk1Ep/swC7h3B9u05tCaMoFSaKSh+nFjzsYpnZ80WjN9ciyIa4Eh0Gqalt5I3eRriH0VI37Qe5P7KG5BGzsBvncbC4kQuSI2Q+oubEbMyOSqE6FSCJCg4YppAc9wEyvISGEw2cE9dGDetfDbmRUoNTsbpwsgRBbH2WWS0GzEEthIr9jIYKuKoPBdXiRt73bnoYw2Eur+i7Lsv0ETDBNQirdeqSSx24vHMYsb0RzEazaNj3LljJ/v278fpqOArrUiS1ssp1gTk1DDbdHfyyDsyAYOZpN+8gPE7P4Kjn3jxCdRiHb8zXMRvvct5+pRmgo6nycy8jqzMawHoCoQ4qaqTFb0hEvZ9xdum6SiJcq6xGY3kZ/bs2YwZMwaz2UxLIMzZdT1MM+l4eUz6aJui3+/n8OHDmM1mxo0b96PvkR8n9z8m+h8iqu/s7MTr9VJaWvpjDPtvwufzjRK9w+FArVaPEr3ZbP5eVN/b24vFYmHBggU0NjZSWFj4Hxnzj4H/CXKXZZlQKPQPfaa2tpahoSHMZjPl5eX/VqGE4y12+fn55OfnIwjCXzWz2bdvH9u2beP8888nJ+cYCdj6elh77+0Uz5pL/uA0xGAE89WlmDIMeLZ249sxwF7XV9hPyOXlwGtMjJ+Eq+Msqoej3DvnQ0zKBn713Q3ct+MDpjz2E+qCdxCNejCbz2TH9lTcATd9hq+YaJmCIxILTQ5eKTqZWzwfcWP8OtzWJOzGF9nu2YvHVkdIiiDJQQRBhyz7mXbKqVQsOYe65z5nX8s6omol4byxLDjzbB4b6mG3MoOCviZ+Ofge36ZN5EPDfFZu+gCLoZnDYx0k+ZRc+3mAMqcRyeVm95SlPJ5yAvPK0rk35Qi6+sfpywwxkqQh5DdibVyKq30+psQAE1eUkW9oR3XgRZSd23CHEqhtzETZ7sQYCOGM0VFXWER/XhYRnZ5uQyfJgpH5jlkUh9JRCwr8kkQvXhwKH0FVFJc7lrD/WHo9RufEFG6hIzOX5kQTw/jwSCHE0UK6KF5tlDRrFHVEQB8IkmlTkeAxIshRonhwar1sWZbLd4cuZiQQw10Tf4JDZ8YW6cPm/pYoUSIJq/Gri5jpbOGd2pf4IO4Z5g9p6FPKHPQE6dX24leHSXXqqMrYQb+pjXOO3oheX8MYzR6mC4fRCBFsoki1Wo29L51UpZ/4eImx0SEAZEAAQuSxJfArbkLinJR+fnHBUtD/GRXGSJDI1p/RIm3BYVYRZ5xJqH0M42ufISAYsC14kvTpJ47ew4FwlC2NFtYe7qMu+iJq3QDnpz3NOZMzSCJE36pzCYQC7MyMR1KoyBxyoAooWXPuz6kdE8dEe4S7uo/iztjNcOp2YhQguQRMzhmM7Y5gjOwA/HSGJlMdOAlpbBe6zHik/pMZ3tNKXMv7jLW0EhUEvLHguFlGMosYjTcxseKC7821vu5B3v/gPSzBVL4igwlqFQuGFZhLYnnR9AGPv/QNGtlA7FPPEntQgcbyLXHiM6DT827WL3jwaCKPLu8kLvIbsrJuJDPjqmP3gyyz6mAHg94Qd+zazUPRVCIqHSti2ojDw+LFixFFEYvFgj0q82tDKkalkrVjM4iP0QHHCOnw4cMkJiaO9rH/u/FDRfXt7e0Eg0FKSkp+zOH+XYhGo9jt9lGyD4VCxMXFjbbajYyMjJL7wMAAqampP8o4fvnLX7J+/XqqqqpQq9U4HI4/Oaa7u5trr72Wbdu2YTAYuPjii3nkkUf+6cLB/5PkPjw8TFVVFTExMcyePfvfNlFkWaalpYXu7u4/abELBoNs27aNE0888U8miCRJfPDBBzgcDi677DJ0umMTvm7bZra9+RILVt9A3B49bqVIwZ0TUShEbG8eJdBp54hyJwdyg3yj/obFpuW09Z1Cv8PH3dN/iy8U5sWdl/DE/vfIe+ZG6my3IcthlMrz2L/PRFgI0639jDLLTHxBHaqGEZ4rOZMrvV9yZ9waPBYzVuML7PfXYbNUEZD8SDIgCCCHyC8tZv6Vd2L9/Cjbdr2NK2IjkJTOjJVn0R0v8mg/uLQmVvZ9x8nOLfyi+DbyjlYxtnETuydYsZl8LKwVuHCXAr07TMgUx+vjlrMhZQIXTknlRvVOhMbn6M4MMZykIRrRYGufjatlCb6IEhJtpJi6mBTcTaG/krCspH44H3erlvg+CwpJYjjWyKGcAraNMTOY2ooUY2GKu5yF1hMoCeaQgPpYhkeOMKzxEDCKhCMituYhPIYsIuFj946gAIU2TETpxZ4kYpEHsYbbcegGCSncBFVaUocNTGmNwZ5YgcucT1r2l9za+RbvDr1Me7xAf0wTNl0dmf4CBGU6ckIOEx0KSp1KsiJKAnKUpkiETq8ACCBL6LQhzEXx9FY+y6tza3h/yfsUmo9FF3LQwwOv/o7ZimoWiwfxDtt4r30iE5N6+Y3pIiYqmjjJ8BUTwhH0kSCS0sA7/vO4P7qAh/WfcsYtT4L45xcOsWUDjoO30ZYuEdCIxNslkioeIy5tGSBS3evis+pBvqkbwhOMMiXHSIfhZ1xacimXjr2I7toqbA88iLG7j4Ol+dRpx7AubS4ViQr6i2NIMLRwle0gZn0VEa2diF+DrVPFDL9EhiuIWhwiLJuoDp1AvetkxOxWcmYEcLon4QxkY35tLVndmwgqlOgjATyZSjw/8eGQMphS8TyJiQXfm5eV++vYvnkfPpWbj0LjmeHXMCOsIqHAyOMZbh5+4UbivCLaR54krS0Gw8CT6MVNhJIWsW3K/Vz9WQ9XTBlkZvyvyM76CRkZV4ye/42WIR62OXmipp81LfU0GYtZoGolS+3lnLPPHi3qDUSjnF/XTWcgzIOyE43LgclkwmQyMTg4SHp6OmPGjPmvkGb946K84xH93xvVt7a2IkkSY8aM+XcP+69CluXvRfVVVVU89thjVFRUsH79ekZGRv5pW++/hfvuuw+z2Uxvby+vv/76n5B7NBqloqKC1NRUHn/8cQYGBrjooou48sor+dWvfvVPXfP/FLnLskxbWxsdHR2kpKSMtpD8O3C8beUvbQFEIhG2bNnCokWL/mwWwel08vrrr5Ofn8/KlSsRBOGYRv4LT9JVU8nilbdj3O/HkqSj5IbxSL4wluercdqG2Kvey66MYY6YjvCT0nt4c0sCWmWEn0y4h25XOuu+O5XHmz8l6YmLaRq6C5CJhM+mvj4FT9hDp3Y9E6zTCQQ1GOoG+W3pOZwd3MqvDK/jtcZgMz7F0ZCF7uHd+CNeZEEPsgcRCVOcnqW3Poy6S2b/2g9odh4kqtOTMPUEFpy6nIe/28SmpClookGu7P+SEZ2Z9dqpnLTtE9yaeg6VuNDKIhduDDC/VYPg8+PIKuCJwuW0pBRy3awULvB8Ay2vMZDqoy9VT0Qp4xspwtG2AL+lCF2miuQMK4We78i2bEcdsGCTiqhpyUDutpNqHUECbAYt3YmJHMrIpiU5gj1hEK0GZjtnMdEzjuxwEmaFiOb3AiIBIcSg0oZV4cYtR/BKMtGIGsJaFEEDQkRPVD6Wmv9zEAG1AGoRNIKAXhQwiGBQCMQpBNSiQFSWGYzIuGULUYMLXdlMGncPEp+jpujze/GUFBI4+2zi1/yOq6cf5ILyK7iicBXiwBHEvkN8UGXlAesidmlvJik9j00tRpp7w0yeksBlI2dwneJzslL38KlGYllYyck+BU86FrE2uoBXk9cxq3wM0YIlyEklxx7a/hgBB4qdDzMy+DF9GXo8epGIbKLWOoED/QV4ooXMHTueleVpBMVeLtx8IXeariCwvQ6xtY0Zbf3UFpbyxoz55Ga4SE/vI03VQq7cgShIqLypKAbNBLq7KVWESWEQUOKJTqI2VEa1cxnq+G5Sir8iN38Fm7rT6T7SxXlb12AI2PBotJiCHryFChzXBBmUZrJy/vMoFH94YBkeHmbT5zsZ6NAhm+s4EMljfCCLbA9o9Aq+HKPgyk8eJmOwl4E7b2CGNwFj770osOLNvY3BEy/lzFcPMy7JxhVjf0FOzk/JSL909Px97iBLaztZNhRCs/kdPk9dxnxVGzkqN+ecfdZoJk6WZW5tH2S91cMHJZlMNOoIhUL09PTQ0dEBgEqlIjExcTSF/GMLuPwjOF6UdzyN/9ei+ubmZkRR/K9PcTudTt555x22bNnCtm3biImJYdGiRSxfvpyTTjpp9Lf7IfHWW29x8803/wm5f/PNN5x88sn09/eP1oW99NJL3HHHHYyMjPxTxjv/E+QOxyLfv4ZIJEJNTQ1ut5tJkybhcDgYGhr6tzgoeb3H+oc1Gg0VFRV/lrwlSWLTpk3Mnz9/1DTm/0VDQwPr1q1j6dKlo20kIb+PNffcikYXw9SCSzB2+HBNTCR/ZR6dR5rRfmlj0NPK0PgQb4Q30mno5O7yZ3nkiwBpxgjXld5BjWU8u787gUd7NmL69Vm0DN8PyCQk3MiO7QJOv5N2/UYmWSbhDetJq2zj0QmrmROt5kXNU0S8SkbEe+nERM3QJgIRJ4IYjyzZEAUFCjHKwitvJDtjIh1v72BX9zr8YTdyWjYnXnQ5A85anmoJUJ0/GXPEy2nDm9medALGti6mVq6nqnCI7jQPue4YLv7CTdmQGjkYpLt4Ek+kz8OWnsfl01NZHd6DpuZlrHG99KeYcMXKSBE17p7JuPsnEhc3ibHT88lSHyFU8yEfB7Rc0v8F/YGJNHQkIQ3ZyRjqQSlJuLRqrAYdVoOOgVgzthgNLo1AxGQmRSigIFRAmhRHjAhqVYgYUcaEFgV/GqnIskxEiBIWoigQEWURJeKfGMvIyHjVURyRII6AxEhUxhfUUWVwsCj+LZapGzk64zMOvzfESTeWIj98C2KCCc2q2fi+/prHpBrsBQJr+3sRkJE1sTgy5zO76WzOr0hgisFFXKyJmvdfw5CQRM/U1by8u4c1Z6cSTQzzZeeXbOjawCRPGt6eVVRKRt7VPcEUuRbJmE60YDFS/iKiWTNBc8yTwdZRxeEPHiQmJoYKzW6siSoGkwxEtcdqYERRi1IRj8MTpke2kmTVYtRq0YZdRPQygvEPstGOaCqJ0RxS+wXiBzyY3AfRaL1IsoKwYQoO2wyOyOW0O02oYuwkTdiOc6SbsV4XrzsXMLGmhQW9ldhji1DoIhiHO/CPk+m/UEmXbhmXzfmDLrjP52PPnj0c3deB1T0Wr7kOvSKC2TKJNLWaoC+CpyiGxAPPMr22CvtNNzJJ6Cam/yXCch7unIcQzzqBC96qxOK2cPfUexlXcD3p6Rd/73e/fGcrR4Uol332Bu8mLmKioptM0cE5Z51Jfn7+6LEv9Nl4otfCkwWprEw0Hfs+HA4qKyvJy8sjOzsbh8OBxWLBYrHg8/mIi4sbJft/ttXrx8DfarVrbm5Go9FQUFDwV87y34HGxka6u7u55JJL2L17Nxs2bODrr79m9+7d7Nu3j8mTJ/+g1/tL5H7vvffyxRdfUFVVNfpeR0cH+fn5HDly5J8KUv9nyD0UCvGXhur1ejly5AharZby8nLUajX9/f309PT8wypJ/ygsFgvV1dWkp6dTXFz8V/ekNm7cyJw5c/6qMc2mTZuoqqriggsuGBXgsXR38vGDd5E/eQYF3rnEuEL0TFLiM7spNxUR+byPo/ZdBGYn84zvfTwxHu6d9Cp3fjRAUWKIq8bewb6B6dTtmsTDg1sJ3j4XS+h5ABITb2TnDgV2j51G42ZmjkzAHTFRvK+GX0+9lFRpgLXigyijUUb8l2HTzObb4U+IhpyIYjySZAOUQJjSqeVMP+8n+L7p4eCBL2hzHUFSqsmYNY/5py7js4+f5VPtJBqKJqCVw5S5m2nS5jH10A5S+3ZyoNSB3eRn2oiZ8z+1kO5SQiRCd1E5v81cwFBqHhdNz+BCbTPGQ+8SjXzHYLKagWQjwZgwUlSJd7AMh2csn+RPo0GVxTeKg+Q3rUXRf5iIoKE7UEF7byYOZ5TUoVYSnDYkQWDYbMZpMODRqHCpZPxKEVmhJ2BMR9ZkEiPnoo3GoRIgrHHg1w8T1tiJaDwoVWFiZSOxUSPmsJG8gJsseR+bE6Yzzx9AH91CcPValMk6BCQ62pr56LMvOe2UqTSPtPNRPaTZu3lG8QrPOJ7ArpYJjXmBUz/2YQ5HGHOClUgkhhdb43h9mYIPzWdhEXKwYiY+IZF3GsIc7PXy9pnZFBQU0Ftfy1dPPMycS67lviYDoYjEh1dMIUatwBqw8lHrR2ys30Kk+QqGJA1PpfQzN6sOZe9WREcXsqBgxFTKrmgpH9kKqJLymZSu47SyRJbJO4lpXU90pBK3UYk9xoBdEPFoRawxUdJDiYQCWrStg1gz0rDFmcl0+ZngcxLn6UGM+JBlAY8URyhrOvJgAu6h6bQrM2kOh0ERIql0M+ULp/LYngJ2NFk5sW0vlzV8jVKO0pu+GEdqMeWHniZYEeXIaWZa4mdw78xHEASBUCjE4cOH2b9/P0p3Ikd9OTTG2DlJ04jOXoJZTkGSJfJnJFO3/x2Wb/oS6zlLmB5Xi9JRiZuz8CVeifHiUn65uZUPD/dw19TfMG/CuaSnXfS9ufplZT8/CXm4/lAllcM+jNooOaKdRctPZuqEP+w3b7C5ua5lgBsz4rkl81ja12azUVVVRVFR0fe0OI7D7/eP7gfb7XY0Gg2JiYkkJSURFxf3XyEzexx/3GoXjUaprq4mMTGRrKys/1r9++Ooq6ujtbWV2267jf7+/tEHKKfTicFg+MH96P8SuV911VV0dXWxcePG0fd8Ph96vZ6vv/76n+q//58n9+HhYWpqasjKyqKoqGj0JhoaGqKtrY1Zs2b9KOORZZmuri5aWloYN27caJ/6X8Pf41QXiUR477338Pl8XHrppaP77817v2PTi08x7fTzSazKRJRAf2EhSWMS8O7ox7e1l30jXyEtLuYpz2sodUpun/ASt33UxYS0IJeNuZ1t3fPp213Enf3bGb5uApL+QwAS4q9k795Yhi3D1Jh3Mc9ahCsax4R9lTw74Vw8Spl18j0kKl0MD8zCG3cdXzg+Q/BZEQQ9UQnAjUAUk1HD4ht/Tqw3mf7Pj7DLsh6PZwBiE5h5zmpi1CN88+lXHMicRu34qXjUBuLDToIhkTn7N2Jw7+ZQiRO/JsK8kUROWzdIug2QZQZzxvJi1jxqUsZwSnkal4xRk1v1CequTwlpu+lPMFKXlo5Oa0UpRAmH9ITsBeg0YxAjStKCvRR62lEP1SAj4FCX0jpUwpDFhM/tIMneRepIPwAerY6gQqYnfyyOrGICBhMF1dWofCrc+lQG0koQ5WREFESFCFZ9DwPGToaMnbhj2jEo/bh0RVwxtIeicJhCSSA+FESQozgx8CRXch7rKKaDjdEp/Dp0Cdt0N7DReROVY6s5rLdw2gcOoiK8fn48E5MnY950iE/GuXjqhKeYmToTr9dLR0cH2xsHeaFewb3T1UwpSCExMZHDH75LZ9Vhptz8IJd90snC4kQeO71kdPHyRXx83LSe179U4wmZuAsNlmSZHqzorQeYKR5lrrIBo+xCBmRTJtExKwjGjaWp20fj7t2YAu3kxkZJ18joVF6i4iBaWcTVoGXkqImUs72oYmJRmVIYtIYRndmoFFOwl+eSuWIRgX0jNG/oocEfJiRLmAu3MWaugl7hIl7bM4iy+ghX1X1JnqMftCqcugwOl9/GhNoX0OUd5eMVSfQYs3hu3vOoBBU1NTXs3r0bv89PpnEqH/YKNKqjrNK0YogGibNMJmOMmdnn5PP5Z2uZ8/xTSEtTGJfQSDRixi7eQjhmEqbLxrK508YtH9exeuyHXHbCHNLSVn9vnjqGfSxt7KbA46dww/sMpI6jQGEho2IuFy79g/PfUW+AVfU9LDDreaYwDVEQGBkZoba2lrFjx/6JguafQzQaxWazjZJ9JBIhPj5+NKr/S5nAfzeOE3s4HB5t4/t3C+j8o6ipqaGxsZFHHnmElpaWfyg7cuedd/Loo4/+1WMaGhoYO3bs6P//P3L/M/h/yV2WZdrb22lvb6esrIy0tLTvHW+1Wqmrqxu1HfwhIUkSdXV1o/aLf8t57jj+Xqc6p9PJG2+8QWpqKqtWrRqdCFvfeoX6bZsoW3o+hU2ZBIG0m8aji9fiXtdBoGqYXSOf4V8whpcDb2PUG7mx5Hlu/aiNyRl+Li66m01dCxnem8dPOzcR+8gpdHmeBkChWErlkUKcLhd1cZXMtSdikzKYeOgIX2bMYW98AW9FH2VyTAuWtjQ85gfYLtXitNUhIYOYihztRRREZDnKlIVzKF9+Bb4ve2ho2ke1YztS0IcuPZsFF1xIx5HPOLqzic7CIgbGV3AotpiwqEIZDpPXXUfCyHp6E9sJqcLM92Wz8pN+0vv8AARMZj4ums/HadMoL0xmZnkyroCNz0IRhlQ6Lhj8ghtH3sRiTMJiUiHH+FBqPQDIsoAom9CgRhcKofTaEKNhZFT4lCZ8kgbd+hB9g3mYHb2IWjOJlkGUv3cljIoiXakZOBKTcJrj8epSicjxGCUdmqiekHzMqMij8eEwdtMf00i/sQuLvgeTWkmpN5FMyUyrX8W8rLGcPHEe9XU69m2wcXXSNTDuFJSnPgxA76pVuApS2H7eWCpHKqkbqSEqglpUMzVlKrnKXOJccSyesJTT32ni9FIzJ2UfyyZJ4RBd6z9GHxdPzGk3cccXzdy2pIBLZ2aP3md2X4ivagd5Znsr3uCxqvqJKJkvKlmYYiI5UYdS6MTYfT8h3xAgoBePydAGo1pCchaCppCQXUWLKodrxm3BaVrEPWv7KAt6yXr2t1R++QmN321jaspJ5GhK0J+bjyrNQOObTdR3e/FIYMw8TPLEBtrU1/FRlYtoZyc3Na2nrLcef1IKOtsQSkOUvVNvRnKaKAs+zmurcmmX/Lyx8A0GOwbZs2cPNpuNkpJxRF15PNU0gkMFp4RCGI1VxHnGMW/FNIqmJdGwaw+GX9xI0lwfCUYnnugKXMorkNFiumwsw0qZlS/uoth8lEdXppCedv735qcclfj5hma+iBO4aM2z9GVOJkMeYSCujCevXD5KEEOhCKcf7SZJrWBNSRY6hcjQ0BBHjx6lrKzsn9LckGUZj8czmr4/HmEeJ/rY2Nj/SPr+OLFHIpHvSeX+N8ni/jlUVlZSW1vLK6+8QnV19T/02ZGREaxW6189Jj8//3v75f9fWv7P4I/JPRKJUFtbi9PpZNKkSZhMpj85/vh+1vHe8R8KwWCQyspKZFlm4sSJ/9BT844dOygrK/urTnXH0dXVxZo1a5g4cSInnngiAwMD1NbUYD+wE0dPF0svuB31lgAelUDuzyai0ihwftBEoMXO9uG1uOYU8v9j773D46qu7+/Pnd6lkTTqvRerWO42tjE2NmAwhN4JLUAgQCAkEFIJJCQkfEkgjZLQe+/GGBv3JsmSJVnN6nVGo9H0fu/7hyJhYwM23fze9Tx67Gc0c+fcq3vPOmfvtdd+XHqWREMi1xT/jZ+82EZxgpcrSn7Fxv5j6NxSzK0tryH+dBkuw2NIkoTBsJihwZXU1+9hX0wH5V7wRfIpbW6iJ2LmwaKT+Un0Ga7SvY2rX4s9ejXdplRqre+AGEamyECMOAAvIGI2Kll8xY2Ywzl41vSy3b2JntFdCKEg5pwCyo9dxN7NL2FrG0eeKqCoLGSnPof1cbMJylQghTA63kfjeQtwYVaWkuYoQms3EdBoGYmz0JmWiV+jQQiL5EUFbkgxc/xID7LG91GOb0Mt24NM8GOVpdKhz2dUlUAAIzK1B4XWhVoZQit3odEHUIe9KP3jpA/60I4LDIcSGVcuZsCegq6tidjhvYTUOrqKZ6LzjmF2DBI7Noo8/FFeOagy4TJmY4svwGPMxq9LIypXgyQiDw8TiQ4RjQ6hCNcQltsIKgQEQYcoiyVNNUaaWoGr8gcYtEaC//kP8ccfT9L3VpFgSWDs+ae5PPBv4o3TiSGWGvkmZiXO4t7F93LFk7vRKuXcf075lFVnx+4aap58mLiy6dSmLOKNjiDnzUgmPU7PhnY7u3qcSEhUZ8QQESV297vIix9mrqyZykgu+VImTnsvXdbNOAIujBodpQWzKMk2oJV6obsWKTyIUj6ESgpzfnoF3Xodj76gxyWDTRoJpVrDMbPPI77LjO7kTAbdQere6scVAVN8N5GSD6jnXFa3KtB5ndwy9CEV9R8SijWzWZfJkv46yNXTtdBET9etZPvWUHOZklcG3uXWzFsZ2j2Ew+EgJyeHhccs5K137Pyj14pWIeeUcQVaQweiwckPfvADdCY1gf4+PLeeRFrpGKIpmXHf9YQUVUj+KMYLC5Bl6Lnw4TfodYj855wARdnnHfRsOt/r5RLJS2b7duIDfrSim62RHP52zclkmCcibf6oyLl7+7CForw6LZNElYLBwUFaWlooLy/HYjlEGeLnQCgUwm63Mzo6OkU0+4vyvo4S4Gg0OmXWVV1d/YlCwK/DQOdIsWvXLurq6njxxRfZsmXLV/59nyWoGxoamqqyevDBB7nllluwWq2o1epDHO3TcdSQezgcRhRFfD4ftbW1qFQqqqqqPlFF6Ha72b59O8uWLfvSxuB0OqmtrSU+Pp6ysrIjzsds2rSJoqKiw36wa2trWb16NdXVE93hKisriTUaeeX3v8TncnLcqpvRfOjEoVdScHMVMlFi/LEW/AMO3h96CucxBTwje5FMYybXld3H9c/uJTPWxzVlv6JmZAZ7ts7itpqncVw+F1n+GwiChFpdht/3AzZv3oldN4aBEdS+EtIH+7C09vPHhVczLVrP3+QPIAuIDHdU40n7Pm973kUWcCGTGZHkKYjhFoQJ2Rdl0zKZdcGtRLe4GNszwCZxE2MjLciDfoxJKWSVl9CzZyvuET9xGV4WpYfpFTQ8kHUx9YpsTOMjCNHdhISdIA0hV6YTozyGjIFYsrr7Ke1qp6Snk+6YNN5Jraa/eAZVRYnkhuwca0wgfqgNYXAn7lA7qdq9yHBij2QzFCpiKDSd4WgOnshELlSBnyzZDhK19aQbhzBLPSiFiYhBJCwnImmIamJQRcdQCgEiopw+bwV9miz8OTWMjVzE+6ip8rhZ1v8uKs842zTLiIpxhJUWfNpEZPI4AOQRH3H2naQNvI4yFEIdFlFFP/F2wKvV8YczJVSSjssbZlFw9nxk1aXEJ+fw6zdbaBpy8+KVBzbrqHn9JXa88hxVZ17Iak88r7YHkRAoS1SzvDSRk6sySDBMTByv1Q9zx9utGJQi08MbyN23B7koIOXGc6phgPSCEwgYTyfUPIZjLMDD2TKez9GhDIUp6+vh0jIPv+m4l3/fL8OtN6C56krKZx2P7/FuwulaNnfZcI4rMaoD7MvawYZQAV3jsaRo4BZXLcXrXkVCRLZ0Fu7mRoydDqzzswkt7kF65hg6ss7CcvEYd3TcyXzvfFKsKeTn5zNv3jwsCYnc+e96XrQ7yULOSpcSowZscVuZM3cOCxYsgOG9hO8/lZgYN51JJ6L1XIMYUCF5I+hPyUJVFc+9bz/Jf2pSuWelg5NmHNxEJNThxPN0B02RXexQ2oiqVWwJZ7FqyTwumz8RFRElies7hlg37uX50gzK9Br6+vpob2+nsrLysBb3nweTvdInw/der5eYmJipXP1X0VVtkthFUWT69OmHrfD/qgx0jhTbt29n+/btrF+/njVr1nxl39Pb28vY2Bivv/4699xzDxs3bgQgPz8fg8EwVQqXmprKn/70J4aHh7nooou44oorvtulcDBB7iMjIzQ0NByWeM3n87Fx40aWL1/+pdzQg4ODNDU1kZ+fT3Z29uc65pYtW8jNzT1so4RoNMqzzz5LX18fp5xyypTjk8cxxkt33IZKp2fenKvQ1zgZjVVTeH05QlBk/JFmfHYH7w8+hWNhPs/JXybbkM0N0/7CDc+3E68NcPW0O+hw5LN5+3H8ZvsTGG48hcGkx5CkMJJkwu+7jj2Ng3jwYNPuJXu8DIPXy6wNW3l04cXsVel4WPgLhYo+bE1mXOofsD3Gz8hYHSAgVxYTjY6BOIKAhEouMXvJHPJnXU5w7RCDtmG2yHfhG+5A4XEiUyiJz0jDZesn6IlgTvcwP0fE7LXySMoqnjMto3BvLUnDm+hMs9KX6EctKFmSuJDjm+VkvVGLODwyde1cKj2tsekMJOdiLsxE4enEOdTFqcffgHHEhcw7hELoRyH0IlO3ECKAOxCLM5SGI5rBWCQTZyQZr2jGILeTpOwgUdlOorKdeEUvGtlEmD8qKXGSjkMyMyal0R6twBbJROU2oSRCUJooiZQkibD3ZZDGKVp4Iza3DY/Lw4Ilsymcm8i97+/D2fA6PxTvZfucW6hZ8zIDiTK8khejVyQlHEuSx8wHWUPEexX85CUJVcgNgCI7i+0JhTRkVfLrn52F8L8JdmzQR8gfofH9R+nctZ2TfnwblvxCbLZRHGMTuz2ZTEaiPp4YvwK7vZMtu3bxajSHHm06ZZoQSxL8pLntlHqziY/EElJKvJzo4cFcM2GNmpiRIJo+L7/KGqNzzcu8ML2dW1+JUDRtCYl33cnoQ82ErT7WOkTCcoka0zgfSioUMoElhQmc595L2kuPE7XZcM+bRWaJh8DLtXjGNaw/sYjShfVY/qKnOeuHONMy+VfRL0j2JXOh+ULmz59PYmIiXm+Y6/5ew/aAnxlBOcf6leRWxGOa5uaDdR9w9RWXEdf0X+Sb/4+wR+CZ1Ms4wXQRkT4PRCTUMxLQnZDBB3X/5Ma3CjijPMBvTjvloOdR9EVw/qsJZ8TOa463CJqT2BHJQozP4fkrZ6L433z0f/2j3D8wxj8LUlgRZ6Snp4fOzs4jSuF9GfD7/VPh+7GxsSmntoSEBOLi4r6wWCwajR4QxfwipXtHUmr3ZWLLli1s3LiRpqYmXnnllS/9+JP4/ve/z2OPPXbQ6+vWrePYY48FJqK111xzDevXr0ev13PJJZdw9913f7dNbABaW1tpb2+nrKzssEQooVCIDz744JCmMUeC/Xu/V1ZWfqFw2ie1oT0UAoEAtbW1CIJAT08PAwMDXHDBBVMLA3t/Ly/deTtJuQVUZp+DvsnJaJyGouumIXkijP+3Gf+4kzX9T2JfkMNLqjdI06fxs+n3cdPzHQRDPm6o/hvesJHXdp3BL95/iNzLV9I97VXCEQegwO+7nMbGML6gj1ZTMxXObISIkjmbt7PPksM/C07mKl7kKsWbeIbVjHTPxJG1gvXeTcgifmTyGARlKdFgI0huQMKkkVhwyokkJ56Cb/0g7eF+ahVtBEf7MQQ8hF3jyBQKBJlENBTFkORlRm6QkvAoa7UlPJB5MQGrj6KOTQTlTbSne/HoIqTILazMPIGizaMkra1FPTiES62gNz6GAbMBZVSkdGCUZKePqFqNtuhkNLnL8dqa+WFcClcJOubL1IwHhlg7/Bhl+nQy0wRcWYO4dQG8ogz9w/EE5qQiFuWiCipQ2Nug/wPSk2MwYSVGsqPBB0BUUuAnFod2Bg4xk/o+P7axXlZl3USzH9q0Pfh1g8zNWoU5RcuuoJ8nt+1ik/oGBtun4elTkPzE4/hjNNTaatkyuIUtHWuxKtwICOTYp3FqylyWyy2MbqnDvX4DCQEnsrg4DKtOwfC977F+tRd7v5dTbihh3SP/x0BrEwvOu4TSY49HJpMRCgRo2b4Z1+ZuSiNVH93zSGwgwmMEaUMkRyFnlllkwLyXDck5hDXZlAbbyHQksbXRywWOdzGM91Ky6DhC89IZ/fWvKAvl0Fd5PfPQscYX5AllmF5lmNLEfk6umskJkp/wP+4n1NSE4phjGK8wU2Z9hcHVAgFJT/tFGvTFoyT/PRlpIMDGWXfRnLKJ+py1PLzwYbKSJmqQB0Z9XPbPXQyKUZb7lFQJKpZcUkh6SSxPPfUUGsnHBYHHEMa6sDfp+G/yGZy2+Gq0u+wIGjnyRC2GCwvY13sf176aiFqdyEtXLUOlOHjO8LzUSbDNwTPjz+GLT2BHOIO90WReuHImpSkTItk37W6u7xjilowErk4x09nZSV9f3yemD78uTDq1jY6OYrPZCIVCB4jyJoW7h4tIJEJdXR2CIDB9+vQvVVX+RQx0jhQbN25k7dq1WK1WnnjiiS98vG8Tjhpy7+rqQq/XExMT89lvZuJmXrNmDccdd9znMgCAiWhBQ0MDPp/vS+n9fqg2tIfCpF7AYrFQWlpKJBLh6aefxul0cvHFF2M2mwHob97D6/fcSe6MWRTHn4y+xYU9QUvhtWVI7jDj/92L3+Xmve7/MDY3l5f172BWmTlLcwUv91joHQ9wZfmjJGptPFJzKTe98wTli8sZWtWCL7QPiJKQ8AN21yXR1dXNgG4AS0iDKhJPcdtectr28cCJN0Ckn/sUf8co+hmtM+ASTmJbmg67sxUAuaocZEaigRpgwq/Aoo8wd/kK4gwn4d1hpZUBdiu7CfrHSTdokbvHGe3qmHqoZcoosXEBCkwh1FEfb6YuYaOhGvPIAOaxndhi++lN8hFRSCQE9OTaTKR0QZJPQ86Yh8y+YWSCnLFYC96EKsqKT6V5rJVnVUE2GHL4Y8Io5bs2sUlyIGmUrMxYjhRNQ2KiDacYGsf79k9RHH8uYnESQeUANQ1N+CM+/GcZ+C9XE0TF7wMPsLJpA+pAEFdSMoI3xNbWeJrHEzk+JUqc5ucYzPcwKnexz2NCMM2m357GQEDFY0oTbaqLGG7LZWTJX4grzcUUoyLkC9Dd2slo23puLXyVY12LULq0rElfjVJSke0uY3pgFhdp0qF5O4Eda5G8HpQzZ7Mp/nxicywc9/08Nj/7KM3r1qDWG9AaTbhsI4jRKPEZWZTOXEJKail+TxC3y40r5EEeo6JLbWTLUJS1+8aJRCSQSZg0bgiP4Qpnk+bvx2LwE5NVgkxuItrr5sRd7zOt+z18J/wfIYXA80KQgqz3mDVbokhzMa4HHsS/bh2q0lJkF5yJcuAJEvZtp3tTKn6VCvuPfPjjtHQ/XMRxTfVsX3kBfs88Xp52Lz8/6cfMS57wu9+8e4SbXtuLJEmc5lUzLcXI8h8UozEocVt7+eejz3Ia71IaAz3PO6hPnob1ol+xaocLmWkiF228opg++/08uGmI1ztP4vkrZk0R9f4INo3hfamLt6LvM6QXqJg5l1u3ipw9I42fn1AAQJM3wFnNfawwG/hLbhL79u1jcHCQGTNmfK19LT4LkiTh9XqndvXj4+PodDosFsuUKO/TiHOS2GUyGVVVVV96udjH8VXu6tevX88777yDKIr861//+rKG/K3AUUPukUiEaPRTEpIfgyRJrF69msWLFx/xqhQ+qp3XarVfmjd9bW0tcXFxU21oD4XJ8H9BQcEBfbd9Ph+PP/44kiRx4YUXTpXTddZs590H/kL+nAUUmk5A3+pkLFFL/tWlRJ1BXI+3EXJ7eLfrEUYqUnkr4UOMKiP3HfdP/vreOOvaRjmr6H3mJm/k77VXcsH7a1mUKOC8UoVDmBCYmEzzQPoBq9dswB11M6YeId2bSYLLzpwN29hTWs1j6Yu4TvE8Z8o3YLcZGaux4MhaxkZlL1LYiyBTo1DPRxQjiMEdTJJ8nDbEgoWziYs7C0+dk2apjwZVL0ExRH5ODnnJFuytTXTX7yLg9vCRW/rBiMhEBiwBepJ99CX6CCslYkQDM2MqOcZQzvQuEfluB3LDMURGGrHWP8mVS28hy2vlmN4aMiP7GIgz0TjjUtLzcpmlt1HqacZi6yPS1IPt/UbMS09GsFTRH3Kxft9b1C+ZzXtFq5g9GuGO5nqmiX9AIMBI5Bd0+SI02DYTiPiYmVZBri4PKZyBSf0XELrRMowrehae0KnIRDWCXEWS6koC4hyckSsOOLeAEOJnWf+HV+bj8oGL2Es/SkcxjvTdNJnr6FX1YRB1HOOezrGjlRR3uiDYTfD7N7HujT5mrMygYmkao73ddNXuJOT3EpOYTHpZBbHJB0eSwuEwo6OjDNhG+YNbpE7QUNi+j5TOfvyiinbBQlChwaDxERT9VIaUzPTFow+pUEd2smDTo2gX/hS5JYe+6j+TmLcM9WtOPC++gDwhgdhrryMaO0Lc9rsJWWX0fhiD3yzD/WM3tlA6nWsrOXX9GsIXX4J/zmnsemGQntPf4zfH/ArveIgHX2jhv4N2LFGB07xq5ixKYebJWciEKIrdj1O7/k3ei8ziRwvi6Prlc/jlCv543V38vVGO3KxGdAQxXlrEQPhf7Gp/lzu23cZl87O58bjcg66F6A7j/FcTWyMNNMqHmT1zBu84U9i8b4y3r5uDSaPEHo5wamMvcUo5z5Wk09Pejs1mo7q6+lN9Lb4NCIfDU6K80dFRJEkiPj4ei8VCfHz8AZujSCRCbW0tcrn8ayH2j+OzDHQEQTjsXb0kSaxbt45XXnmFhIQE/vznP3+VQ//a8Z0ld4A1a9Ywb968I14122w26uvrycjI+FK9nuvr6zEajQc4V01if1/6Twr/j4+P89RTT6FUKrngggumJo2OHVtY/ff/o3jhseRqlmJodzEapyb7B0XI/SKux9oIuN283/M4jmlJvJqwEUElcN/iv7GmXsPDW3qZnbqP8wof5cnmMyjb5ea8rg3IbpxHv+U1BEGBQhFDSvLvWLuuk+HBYQZ0AyT7LWgiML2mjrTRAR5ZdhXBiJXfaB7HLLkZbDQT6E2krbCCDnHCVU1QJKLQLESM2JFCuxDFidy1XhFmVnEiWTkX4e3U0Rrso1HbjyviJSMjg1mzZhGn09C49l1aN68nEgyhjY8Qk+wgU+cmMSAwrIjnobxz2KGdRsrQPuJHtxCVOhiNdeLSRxBEsPjM5IjZzEopobY9kU3jCTzU8jSD4gA92hiqekcwRlUM6+PpVsUyrItjSB9Pkaufck8X684/kRGLgozVtYTkaupWHMdV1l2sGHkZU3CUAeUMmoWldHW14nGPkZZWwqzq0zAIesLNblCFgVH2ufpYb3RydqOX18zZmGPVtKkyuUF3BxqtjO3pZ+Lz24lG7HgVA7xGJ0NIXJsYxORLpHHP8ZhHqylZ6KTquBKsEQ3v9b3He73vMeAdIF5mZrF3FouHpyNKubSOBDj24gJyqg5fzOWLilzeOkCDN8Bt3XtQvvAYY3o1Aa2J/ySdy+mpVuYoo4y2phAN6ojJ7KL8uARyShYzsGQlyqQq1p9hZYk7h8jTG5BEkZjLLsV4ylLCb92MeWQTre5yQqvHCWbC+DVBXJHlZOhWobv9l2wzZDL9kb+z7u33iHTo+N5PqhjYHOTB7X1sVUcoDck5MahiyXn55FYnIOvZjGrtLxBGW+nOu5iepBUYn34R5a5d3Hv97fxkJBOzSoHkCKI7KRNr4tP0DTzCvfX3EBRjeekHM1ErDiQrSZLwPLuP2p49bJe1U5ydRdqc5Vz02G5+d0oRZ0xPJSxKXNzST4c/xKtlGYzva8fhcDBjxozPtbH4JiFJ0gGiPI/Hg8lkIiEhYaKjXXs7SqWSysrKr53YD4UvUmoXiUTYsGEDTz/9NCUlJfzmN7/5Gkf+1eOoIfdoNEokEjmizxxuXfkkJEmiu7ubjo6Ow87tHwkaGxtRq9UUFBQc8Pqkda7H4/nM1rRjY2M89dRTaLVazj//fHS6ibBx65YNrPn335i2ZDlZqsUYWp3Y9Qosl2azt3YPuXu0yAMS6wefYyRF4I3MBjxqD3fOuZOIr4zbXm0mVu3iqvK/0WArY6Sxmhvf/zex5yyib/46RCGCJAVJSf4+o6PHsO7DDXglLwFFiLhQLOnWfqq37MKdncBf8s/iPPU7nKNYz3AojtGdOiLuBGpyU3GJE3XSMlUucvUCJNGNPLiNYGR44nUgPybMzLLjEH1z6HTb2aPpwyqOYzQYqaisoLS4GFvbXvZ8sBprRysyhUBcrkBMRh+ZhlESvHLapDJeNyzg7YRFCIEIGUO1aD11hIQ+XPpxfJqJhaLRq8LkN6IJxWIU4jAZSlFE9fgEGR5BjkuhwhYTw6jJzPw2aE0RWLD7OdJ7ukk2RSgS+vDJFFh9Bob9RkKCAkU0Spw/RKIjgNkTQB/yo84/HnXp9/B98FvsES/1eaWMlGdTNxhLvTl/ytf9HsW/yJMNcolwBzp9BzH6rYzomkh0wjnihaQmzME+tId9fjvx4QT0qMlaejcaTSbx8SdgSTiNfT4nq3tX837f+4wFx0gLJ3FC66WovCksvbyIjBLzZ96r0n6K79vs+/A+91+UwPyrvk/7+CDWxgiy4VIQRJSJTURjfZgseSQmJpHUr0D74iuEutZhM4SxuAU88+YzsPAY9OO7OGb8RUQE3hpdROmHTYSzojiu1VJS+QAxMZXYbr6ZQMMezpx7Izd+L5/G994jM1SEKhjLa4oA7Yoox4aULFJpWX55MfGGMZTrf4ei9Q2iqTMJLbsTKbmS3meeQbrnzzSecRaRuBNY4JQm/P7zYxifu5a+/r9R4/4t/9xq5slLq5mecXDKL7jHzq7XN7FZ2UqyVsX5P7yesx+pQSETePbyGcgEgd90W3nGOs4TRWloevZNPcffFnOZL4JAIIDdbsdqtU4JMJOTk7FYLMTFxX3r/O8/bVf/8fB9MBhk8+bNPPLIIyxcuJBbbrnlmxj2V4bvNLlv2LCBsrKywyo9iUajNDU1Ybfbqa6uPuzc/pGgubkZmUx2gGOR3++ntrYWpVL5qaV9+2N0dJSnnnoKg8HAueeei16vR5Ikmj9cy7r//JOSxUspsKxAvWuUUZmIcFos+Xk5eJ/bR3jIy073e3SI/XxQOsigdogflf6IBSnf44bnG+lzuDmr4EWS9VbeajqPH739KAXpJsYu9uM2dgKg1eaRlPhL3v1gN7YBG2OqMYyhGHTRKDN37SJzqJfWhfN5V5bOVaY3mS7fR423COd2Beog1GUnESSChIRCVYpCM5FDVYVrCARbCIsBADRyBeWx2eQnzcAaMrNXNsg+xQhRSSQ1LRW1Ws20gnx8fV3s27mN0d4uFCollgITMeke9PEdGMPj7AuWsFG9kA3GOYyoEtAN2onZ00yivh5B24dH68Kj9RGVT7SA0QbkxHqUGH2K/X5MxKuvQBh/DyncNfW3EJDQygUU0QDxghaLFCE5bEMXtqOQRUCrwB03C7XphwwbnGydlobCaCBq78PevJmS5efz3O5hXGE7So2NyshLuJWD1ChUeOUhLOMSp3SaOffsO4mZPlHmJkZF/nLvvaSqSwl1x6FJaCelfAcay04k/MTFHUdqyiVo9dOotdWyuvtdPuzewIK2c8kcL0G52MYJx88nUZvIJ+Ftu5vrOoa4qO5dCgfXkBLjQzTPwDZUScCeB2o3RXMhrTyPzp4eBgcHGR8fx+RTsmIghkDDM0jjfQybFdxzhkCFYjGXBRsp9NfSqalgt+xECp58imhGFP8tJZRO/xtKZTze995j9NbbSLjnT5zWqEMhb2eeXcToKeBdC1iDYU7xq7j2ynIsljDqnfejqP0vkiaW8LG/JFp6OggCvr4+Bs86m/GcHHZ973bObgkgi1ODBP5Ve+ge+j2G+B9x+cvFnDQtid+sLDroGoj+CDseeI8NUiM6n4srf/pzXml2cMfbbTxzWTWV6TE8Z3VyW9cId2QlUDbUQzAYpLq6+nPrfL6NCIfDU3NUZmbmVAjf7/cfIMqb3Gh8W/BZu3q/38+uXbu47777OOOMM/jhD3/4DY/4y8V3mtw3b95MQUHBAa1XD4VAIEBdXR3AERvTHAlaW1uJRqOUlpYC4HA4qKurIykpiZKSkiMShYyOjvLMM8+gVCo599xzMRqNiKJIy6b1bHj03ySXVhAfO5+iASM+uYzEq4rRxmrwvNRJuMNJq6yOXX0b2TkrSquxneVJy/nJ7Nu59/0eXqgdpNLSypkFr/JC62ksrelj+d51cHE5g5VbkCl0iGKQtNQrcLqP4d21a4gEIviUQYxhHaljg0zfXEuMwcvWhSfjGLdxQdwHmAQf7/jn4WpQY3H205ZuISKbyKIrVCXINbNAiEUZbUEta8fl6SMiTjQo0clNFMfMIMVQQJ/KS6t8gFGZB5UgJ9eYTGFMNgavjJ7uenptjYyHrAgIxMcnk1RkxJLpQhB6eaq1mFfGlpHp72OZ/QOGi/K4J/ofNiVU0qbRE+NtZVgK0qVQMaBUMKSS4ZN/lJaRiQJGUYlFl0C8IZUYfRyK6BgB91Zy0y7DoI5HLsgRpCiCawCG+vH3JBMU7DTFdpAbGSBkSqITA90eF5oYBUMBO1Fh4jwVokCVL0BmvZK5Qh7Vx12I4cQTpsrbJnHfffcxZ/ZcOl6TkTHNjN8VZqTbRlH3vaB3wtV2YmMXkplxA3p9EcFokPVbVtO0zoV5PJ9Wyw5807v40/F/QCM/8H6XJIklO/ai7u7kGtv7iGI67v5qxIiWhJwgfWYDr9nDrL5h3gGfC3b3Yvvxb4n27EZmSsefYEQ50sP91yZTI+vhXpsLTdLFNNnjmf7MIxATRvH775FVchsymRIxEGDw9NMRsgvpXnw99zZ10aob5ayQmbdlajRyGac45Jx7UQ7ZvpdQbrsfxCjh2T8kMusqUOmnxt90wYUoenrw3P1vstYFCKZo0Y0EiHxvkH3u20hJ+T6P1J/EmpZR3rluDmbdwWS8+6kNvNe/DY3Twannnk1CUTkr7t/Gwvx4/nBaCbVuP+ft7eOMBBNnOAamulB+HcYxXxfC4TA1NTWo1WoqKysPmKP2F+U5HA60Wu1UTX1sbOy3xmIWDm2g43K5aG5u5vbbb+eGG27g0ksv/ewDHUU4ashdFEXC4fARfWbbtm1kZWUdZE27PyaV6QkJCZSVlX2lN2R7ezuBQIDy8nL6+/vZu3cvRUVFZGZmfvaHDwGHw8EzzzyDKIqcffbZUyr6TW+8SvPrz5NUWML8Y69AeneYiAC6M3Iwl5jxvtlDaLcde4Kd9+oeo226kR0J9eRoc/jr0r/S2CfwyzeaiUS9XFD0FDZ/AuP75nH163/DVJ6J7YwBgvE+JCmMWp1BZuYv2FgzRGt9K1GiSMhRiVDe1kRR/V602bCtYgFmVyfHJuxBFASeCC+noy+HXGsjEUOAiEIOSMiUBSg0s5ApkpGiw5iTRlBKVmz9XQQCE/n5GKWFDH0xZmMOQxo/+2TDuGR+lKJAYjhIcnQUY7Abl9eNLaDDGVYjISMsyBnQpCEpVCy2tZHltTJtiY0RYyaXzPgbbaEJEs8UI1S77FT27COvdQ9j/c00ZhThjy0hZugJREWQcT2Mxyjw6+T41FECCpGgSolfEUUUJhYsEiD9b12gjAoowmAIi6hDInJJh6iKo3xvH/2aHHbGHsM8q4tjYjq5WLcV/yWbkH9CxCkUCnHfffdx4oknMlavwTHk57RbKnAM+2i98VosHY00nnEWCQvWIFONkJBwMtlZP0WpjCXc76H2P3todolIAuRXJZFaGIMhXo0gCPjdYbZt3UO9y0CBNYgQlWGMlxFX+yalp88g+YJTue+DTt5qHGHN9RPkLrrdOB9+BNfTTyMoDcjPW4hm7GTkx+pw3XoZ+nQXvz3VzE61xNzRGXz/5TZMUgDd/T8gqeTCiWNEJXr/+E946VG2zfoFJKfxYX49H3bmoAISBTnfG4ezFzWRNvAQgs9GpOpiwvN+DPoDe3B3P/kUwr334r3mh6jdM3AJElkeEXG2l/aY60hKPAuv+nrOfaSW208s4PxZ6Qdd47atjby24R3MAYmcVB1Lr7yOB9Z38fDmXt65bg4yrYJVjT1kqhTc5LOilAlUVVV9q8LUXxShUGiqIVdFRcVnKuj397+PRqPEx8dP7eo/j8PaVwVRFAkGg9TW1jI8PMyll17Kz3/+c+64447P/vBRhO80ue/cuZPk5ORPLD0bGBigubn5IGX6V4XOzk6cTidarZaBgQGqqqq+kFuVJEmMj4/z/PPPEwgEOP300xkaGiIUCpGoUfLBv/9KQkY2i07/Ib6XhlBFRcLzk0lblkZgywj+tQNEUgVWNz5Me5LAh9mNKBQK/rTwT2Qby/n1Gy180GanyrKHJRmbeb/rNC7cupGKzloip2VgXdCCXGMiGnVhSViFPuZiXlz7Ht5eL1FBRC7JUYfCzNu5ldTBQYzFUXbnTyPJ1UelpQsvGv4TPZG3/ceQOdpDWriDGNGFgIhMkYFcXYVMmQeSD61hGH1GCDHqJmwbYqyvFzEaIVZtId1QiEqXjFMNvXI7YzIPggSGkIg85KNTlUBjIJYk/wgz3a3Ig+NE5TLkgohFHyGu8jgS8kpQpGfSYbSww+2ls2UvxqZaCjub0IQCaPRLiJhnkH6GgTLXGOZxB1HnOKLTia3zeZSSGYO6BCkYAhKQ6auQqZMR/R2EvTvY6vGg1+uZmWpBZjSxKRpiNBLkYl0bq8dEfhK9hIsVaymXd3OGsZnA5R9OtV3dHzu6HWyva8TfvpXLL78cVx+sf7yds345HYNZTeuad5Df9iukBSeyJ+1UBP0a4gu3kKD7GwUzMlBq5ESsfuyPt9IdEBlUyBi3Bg74jqgQoSdRw6lVSeSWx2NO0dJ/3FKMF5xP7BVX8MjmHv65sYcdN83D89KLOB98CCkURJG7GPG4ElK+dzbOvzViTnma4I7XGakx0XreufwnvoYuYxcn7NVzfP6lmCur0cpisO+L0r19gOnv/hRX4THE/uQnZJbHsuzJ32LtXUKeJOenoQ851vIK6tAwkaJVhBfdimTOOej6+K1W+k77Hp7MTPLO/wOeBjsRnQKjPkhbxTXEW1aQl/s7Lnx0N75QlBd/8JH5zCR6u3t44fkXSBaNhIZ2cd5d/4cHFSvu38a5M1O5cWkeF7T00xsI8duwnUSVkoqKim+FwOzLwmR3PZ1ON9UE5nAhSRJut3uK6F0u15QoLyEhAZPJ9I22rw2FQuzatYuRkRGuv/56br75Zm677bZvTUvdLwvfaXKvq6vDbDYfVHomiiJtbW0MDAxQWVlJQkLCoQ/wJaOzs5Pu7m6USuUXLpHZXzgSCAR4/vnnGRsbo6KigiVLlqBQKBjp7OCte3+P1hTD8VfchPulMUy+MM4sI9kXFxBpd+F5pQvBpGCX/31qhxrZUDmEXT3GRbkXcXX11bzfYueud/biCQRYlfc2rpAe3XAlF75yP/pEA2NnePEX+REEBZIUJS3tMrziMbz4/muoRlVEEZEjw+DxMH/LZuJcY5gLfdjyLcT4x0mNdRAW5LwkLuWvkVNwRA3MHK+l0NuOKepGEgwo1BUoVKUIMiNE+0jKg/Ljy5DLBQb2NjLU1oKtpwspECFJk01cbB4+rQab3MOQbJyoIKIQZSR4RZICQdLSBXT2N7FJFkZ0lYzb7HjHx+Bjj4JSp0Mbn0zehs3UL7qDgZgYnjxmQuyYplJQZdBQovJi6P8lx5uuJWYkh9DecURHEHmKDt2ydJQ5Ru7osfLMiJO3K7LI0UyEfx9//HHi4uJYunQp/1m9k783RDk/ZYhj7c+yXLYTSaZEzF5MpGQV0fwTpoj+sY1t7NvyNqXZKZx7zjmE/BGe/mUNc76XRVqRjI2PP4J2wybyhuykvvIyNq+elk3D9DY5UCjl5M1MoGRBEkaVDPcT7QBozsklIMhw2228+9c7aD7pDLZkFLK9+qN+3MPfvxRFWhoJd93J+3utPPPX5/j14FqkwQEMp67CO82IYc9C9D9IR+PtwP6UhljDwzQVVCP+523UI1ast/6MgSIv9++5n0whl2VdFyIfjEVQSBR61pO64xUsL7+ILiODX7y9lVdqgszXDvCP8B+JkduJlqwiPO9GJEsxn4SGa65BW7ebuLsfQtgQZEecnFnOCD3zfoM+LZ/Cwj+zpmWMG19o4r8XVTEn50Bx4fDwMM889QwJYQOyrt3Mu/JicmfO4c532nijYYTV18/lH9ZxHh128HPRyXSd6ojJ79uOL0Lsn3S8yfC93W5HJpMd4H//dUY7wuEwu3btwmq1cv3113Pttdfy61//+jtH7HAUkbskSYRCoSP6TENDA3q9nry8jyapcDjM7t27CQQCX2sNqs/nY/v27YiiyKJFiz53Xm5SGDKZO5LJZFO5+/7+fqxWK8uWLZvqIuQYGuSd++4m6POy/Ic3EdwsI3bQh0MrJ+3yEhQREc+zHUghkbF8J2vWPcG2Eh974zoo1hXz5+P+jEZm5t61bTxfM0yKfpjjMjey134M5+7Zy7St7yBOtzB68gCyzCRCYTsqVRyZGTfSMKrlvQ1rMDvNCAggCZjHXSzY/CGGgJf4Ag/agghBUUGcxgMyaBUreEE4jdeCecjCDspdjRR625FJElZtDg5NEV51NipRwhAYQY0TtVrEr9bhiETwh33Ioj5iwi4yQi6y5Ua0piRCOh3jqgijMg+iICGTBGJFLcawAl1IRBkOoVEqkCkFRLlIWArh8zjxOuyISIT156COdmDWWVFq45ArzchlRmJEPSkRHQoE3AqRXouAq1hPekE8RbEmXhn3cXvPKL/MsnBp8gSRBINB7r//fhYsWEA4HGZQNHHHBgcnlVm4qfsqMvPKCCRUIba+S3SwkbCgwZ80i1bdDHYNR/CFIlSlp2BWRAm43fQ09hAJOIiG3ai0Oo678HIUv/wt2vnzSfjdRKjROx6kdauVtm1W/O4wyfkmSqvjiamxIQWjGC8sZP0rDzHUtpfR63/Ds3bPAeQ+9qc/4ftwAwl/+iMj99wLDbvxlleTf/tPiWaosP33A3SKPJLm9KFacyuDgecYTg+wJdqFb3CQlWvWEo3PoGnWDbQEOlhT+CghlY9zEy/hvGmn4brgAoK5ufSefjpv9Yq8N6DkeuXz3CC8zt7gMdT7z+LU35+BTPbJk7B15058V1+D+7QzSNevpEsDmaMhxopfI1TWS2nJg0ioOPVfO0gxqXnowqoDPj86OsozTz+Nwa+mxKlkPMXOCT+6hd4xPyf/Yzs/OjaHjNI4ftg+xPlRD+eaVJSWln4niV2v1zNt2rQv/dwmmxpNkr3P58NsNh8gyvuqiHZSP2C1Wrnxxhu57LLLuOuuu76TxA7fcXJvampCqVRSWFgIgMfjoba2Fr1eT2Vl5de2YrTb7ezevZuYmBjC4TDz5s377A8dAvuTOkyoPgcGBmhtbaW4uJiUlBTWr1/Prl27qK6u5rjjjkMmkxHwuFn993sZbm9h8fevwujNQ7FthIggoDopk/hSM95XugjvcyGfFcumlpfY4GtlW24Hglzg9hm3c3ze8TQOuvj9Ow3sHggzLb6ZdOMACt8CLnrvSUy9HQQXahk/3okiJZVgsB+tNpeUlCvZaPXz4bYNpI6lIkMGkkDcmJN5Wzdi8HnRZEmkFlpRxYgggkwhEQrpGVCeyIbACvZ4R/H52kkIWomJOPHLNOzTF9BqKGRcaUEB6CMBksIucmQeKvRRKlMNZBZkoMrJQOnZQ6TmGUJd2/FqSrCmX4gtYmLUPc6ofxxn1Pu/CwwmSUuspMcs6YmRdBgkLbKImm0uBfP1ChKVE5NdkAB+0Y3DP8SYfxh7cIjx0AgSBz9OkiAgyBUolEoUCsVUtEUhlyOTCUgSBEIRdPIw1+ZvZt1wLrvHU5EUSqJaA1G9kYjRjKRQonA5UA73oVYpMZljUeuNREI6XHYVS75/DOml01Bpdbhfepmxu+4i6ZGH0ezXLjIaEelpGGPv5hGsXW5iYpQsSdQgecKs6fwvxacdT/P0Y/hll5W9swpQ/o9MPW+8gf3XvwFAmZfHn3NXELtoAb9aWUz3vnswPHMMxqwOzEM/xVd6Hn1tZ2MLu/hAaMQ4VkaCzc70+r8RKJyF7qe/JjZPxcMdD/Jix4ucYE/n0gc7Sbnv5/xhj5Pn7Ln8SvkfyqUI7d6zqE9OJbMLFv2wiLz8Q5fxiaJI45lnonCMk3HTQ4T3OOnUiqQwjO3YhykrfwylIobXG4a59dW9PHf5DMrTPrKDHR8f5+mnn0YVkrPCW8b7vf/hjLvuxpSQSCAc5YXaQWaWJnBOSz8lET+/MikoLS35ThFDMBikpqYGo9H4leuPJuH3+6fC9w6HA7VaPSXKM5vNX9oYJs13rFYrP/7xjzn33HO55557vlMLs4/jO03uLS0tiKJIaWkpVquVhoYGMjMzKSgo+Noeyr6+PlpaWiguLkalUrFv3z7mz59/xMfZ32sZJoi9ra2NoaEhKioqiIuLm3pvXV0d77//PtnZ2Zx88slotVqikQgbHn+Ylo0fUHXiKkpmrmT8mS4MERFPromM8/MIbbHiXz+IIsuALcfOW6ufYW1+N8N6K/ON8/jtkjswqoy8t3eYe1bvYcgtpypxDyq5jIWhNI576R8IHhe++eA9QY4iJRm/fx9aTQ4JKZezxmpnw86NZDmy0UW1SJKEyelhzs7txNvtBJMNqAtEchK70SgjU1HyiBRLQDmdYWcOzePD9HrdhEQFEEGQxSCo8pFrsjHIDOhkDmLkraTF9pFhGiTW34YQDRJNqSYy/ZKJUinZgYu6YDCI3W6fmGSso9hto4zaR/H4vfv9AcBoMGA0GNEZ9Oj0OkKhBsLhevLyrkMpNyBEI0iRCD0eL28M2xkJhEiSC4jRMK5gGJkUJVYSyR7pQyZBSmYWCXodVk+QnT0OijSjZCtHGNBV4g5GiPzPtMloMJCdmUFJaiyZ3l0sXF/AJdNN/ODkRQD073Ww5qFWzry9CmP8hPJdEkWGv/99pECQlKefOkhtD2Af8NK7Z4yKRcmMPdJAdDSA+vR0WrItXNDSz7vlWeSLYZz/fRT3U08hhUJojzkGy71/4ffvd/Jes433b5jN3nWXkL7lZiyqm/DPP511viLMe0QSgyZas3TkFmeQmGVA0bCZ0Z/diuG0U4m7/XYEmYy9/RsQ77+eQtUYv1VfzqviMfyypJstA41U9Z7DvPPScOKm+RkXTUlBzj/eiMViwWKxHFDVsu/5F1DcfTfRq28idqQYV54OU4eP3rkPULL496jVKYSjIif/YzuFiQbuP6d86rMej4enn34aKSKycrSCvWMbMB+Xz8xVH3WF80dFTtvTjdsf4AGznOlFX5651bcB3wSxfxzRaPQAUV4kEjmg1O7zVjFN2uVarVZuvvlmTj31VP76179+p4kdvuPk3tHRgc/nw2AwsG/fPqZNm/apyvkvE6Io0trayuDgINOnTycuLg6bzUZLSwsLFy48omPtn1+XyWREo1H27Nkz5Xl/qPrS7u5uXn/9dVQqFatWrSI1NRVJkmh47y22Pv8kKQXFLLnsR9heGsFs8+NSyog/Lx8N4Hm5EyTQnJBKTfN7PNf3HrVpHahR8dOqn3FC0QmEoiIv7mrlXxs7sfs0lMS3oVPFcF5ETtkL/0Z0u/DNixA8MR5ZWhw+XwtqdQaG+DNY5wzwXuMH5FvziQvGIUig8/ioaNpDVncPQZWKwbxMIqkic3R7sGhcyOQH3qaiBD1eM+3uePa54/FFVegVQXINY2TrHVg0UVxSLr2BYvojWchT0rGUJNKkSuD7iws/9cGWJAn7L3+Fa/069P/4Bxs3OAhJftIqtHi9Xnw+H273KC7XIJGIgSM0TjwkQpKcBBzolAKWkvnExcURFxdHSkrKQaZGJ/9jOwvz4vjZigkzpPERP6/8sZ6TrislKfej3Whw716GL7qYmCuvJPaqH3zq9zevWYN8nQ+LKRPZ2bnMGxnkb827KH7mcSSvF+OFFxK12Qhs3UraW2+y1+bnzId28ZdVejK6HiJ1z9Woj61ncyCdrq4ukn0mFroLibluGvK4j5TSnjfewP7bOzDMKyZloYS890OiYZEfR27kTakaTeqzlKdHSK+bzfKiY1l0egkAL7zSwV9293PV4gSmGf04nU4MBsNU3rb/3HNBoyVj5e8hKhIcd+Ky1JJy7vEYDBM5+nBU5KW6IWZkxlCQOHFNg8EgzzzzDD6fj1WaeUgDTjZ6XubsO/+MQvlRedyPW/t4x+Hl/lg5y4ryv1PEHggEqKmpISYmhrKysm/FuUmShMfjmQrf7//3nvS/P5xxTnaus1qt3HLLLaxYsYJ//OMf33lih6OI3GHiQTwS7Nu3j76+PmCifv2rMKY5FCbz+pOGFpPkOzY2RkNDw1SLv8OBJElT9f2CIBAIBNi9ezcqlYqKiopPzd27XC5ef/11hoeHWbx4MTNnzkQQBAZbm1nzz/sAWHb1DQjDZqQPh1AiESiLI3V5Gv63+gi3O1FPTyAyQ82LrzzMa/ptjOhtTJOKuOvEP5FsTCYUFXl66zYe2WrD7jeRbhgg2RTDdVE3yc89hOh0ESwTCS1PQFaVjstTh1yuxRC3kq0+Ey+1vUumNZMsTzZySYY8HCarp4dpexrRBoM44uJozZ2GUx1kpWobuXHDyJUSkbCKsCwVv7yQEZecHo+DAb8ST0RFRAwBAiiSCepzQJWJEEngVYOIQy5xrs9DhjFIeqaBzPJ0Ugqy0exHoOMPPYTzn/8i4fd3IV+4lOd+U8usVVmULpzoyBcKjbK78WKs8kKCqb9m65iXHQ4nzkCIHKWM02K1LNKrESQRSRSJ9PSgyM6mq6uL3bt3Ex8fz4Jp5dS8/Dqtp53J2lGJy3c/wBXKt7lh3n8pz5/JiXFGElWHThud8/AuCpMM/O6UCdIaG/Tx2p8bDiJ3gPF/P4jzoYdIevBBNNXTD3U4AOpXv0nNqy9xxrxbCe7cSnfnKyQN9aM/eSWx116LIimJUEsLQ+dfgOUvf0a3ZAmnP7iTmFAzt5kbSeg+i9o5Lvr7+3G5XFxw1nkI/+lDe1wa2nlJE18SDaF+/lw8m+sZ3BqDLktL3CUn8qtXI7yas5g/nFaM0dzKP9f/hx5NK2flnc1Pqm+eGuMtLzezvm2Upy+rJtusnupwZn3nHQqeex7fedeT5J9GKGsY+YCJR5a7uHXmyk8852g0yosvvsjw8DBnLzwV9Zt2Ngy/QOWVZ5IzfebU+57tHebnQy5uMcq5pjTvE493NGKS2GNjYyktLf1WEPuhEAqFpsxz7HY7wAGivEPNg5O95m02Gz/72c9YuHAhDz300HeqquHTcFSReygU4nCH6/f72b59O5FIhIULF35tdZaTDWd0Ot1BeX2n00lNTQ3HHXfcZx7nUMI5p9NJfX09iYmJn9nPfhLRaJQNGzawc+dOCgoKOOGEE9Bqtfic46z5118Zam1m9unnUjz/BAYe7yDeFcKtkhN3bi7KsSC+1f3I9Ar0p+VgCw/x1zX/x5bYPUiIrFQt4aaVt6NWawlHo7y6cy2PbbfR6UzFqHSTHafjWkOA3FcfIrqvn3CyRGRZIrJFhYxLNUSjLtSGmewOZ/BWfyMym5yS8WkYIlpCkgyLw05xawvp/QMoolHs8fF0ZWUjMwepUrZToOtDpYoQDinxiTm4VNPp8mbR6bRhD40jSVGEsJshVTzvWZYRkak43tdJjDIOYzgZXXTC99ujFnFrI4T1USrb1jB952oaTjuLnosvQd7gRb1hlMHLsxhTwlAwQJ93EJsUS5iJCaVEp+aYGB0nmA1UGTRTE6To9zP689sJbNvG6O/vYmtzMwBnl5QQ+N2dyC0JJP7tb+zd+DBzuv7O3+KvYPOCq9js8hGVYLZRy8p4IyfGGYhXfnQfnfLP7czPjeO2FQVIksSO13po3Wrl3N9Uo9IeuCCQIhFGrr6GcFcXyf95BGVW1iHvk70bPqD2739laUwywV27sKcV84uLL+aJ05Ye8N2e119Hu3AhcrOZt95+lVt2xfB4aj0ZtgVsLRmgs7OTc845h7S0NDwvdhK1+TFd/RFpKNf9FjG+AM9YPKO//gNOmZobZ13OZafN4vz5OTRvHGb7q92UXq4lLTOedMNHNeieYISLHq3F6Y/w7OUzSDSqiUajNJ5yCjKZnKRFv8Gnt2EYi2VdXj8dVdX8ODf1kOFcSZJ4++23aWlp4cwzzyR2jQ97fy8N6i2ceutvpsa7Z8TGuV125msVPFiR960lv8+DQCDArl27MJvN32pi/zhEUTzA/97r9RITEzOVq5907Kyvr8dqtXLrrbcya9YsHnvssf9niB2+o+Q+qR43GAyIosjcuXO/htFNqG3r6+tJT08/ZMMZt9vNtm3bOP744z/1OIcSzg0PD0/V5GdkZBzxg9je3s4777yDXC5nxYoV5OfnI0aj7Hz1eWrfepWUwmKOu+JaXA1hhI3DqJDwZRlJWZFB4N1eIn1e1LMs6I5LY1fDRu7b8086jN2Y/UbO06zgrBVXoouJRZIirG14g2d3dlEzUkowqiLFKHJ6qo4lWx9Ht3knIBGp0CFbVoGvxIs7UEtU1NAeKWZ7CPoHHRS7S7B4E4hIMsaiOoodw5S2NZIy0I9cFHEbDAylJCNlKUmKGyNX1ksSEyv6YSx0kUGblMnbwTnskDJJDjlYMboLY3gYpIlcuqAwIRqSCegsCFED1Xs2kjW0h86cU+nJWo5XBaoIBFTQlS4jrBMRlTZUGjvZycVUpmdRmRRHnObghWOwvoHR3/6G6IiVwQvOZ0ckgiCKLLfZ0LzzLpr580n8+XWot9+Nov1d/ho5nYIzfsOxRRbGI1HeG/Pw9pibzU4fMgGWmw2cmxjLTL2a+X/cxHUz01kQY2RfjY3hfW5mrcpi2rGHTjlFHQ6GL78CyefD8pc/oy4rO+D3oX37GL7nHqQdO5GlpxF3448Zc2WyNCnCzWj5wdyD7zfB3oHy0eUsEu/mQgycFE3kUdkHnHjiiZSXT+Szw50u3E+2Y7ykEGXWwTX7a9bUIN59J51ZpVzzn7vwu0O89Pt6cqvjmX/Wwc2VAEZcQc77Tw3JJjVPXVqNbdNm/DfcgPKiW9B4C3BbatCOl7FkQTw3qfxkuexT4VyLxTJVY71hwwa2bdvGKaecQp4sBc9z+1g39CzH3HIVSbn5E/eRzcZF7cP4VBreqcrFpPjuEIPf76empoa4uDhKSo5uYaDf758K34+NjfHMM8/gdruZNm0ar776KhUVFTz11FPfKYOhw8F3jtwnnd8KCwtRq9V0dnZ+LgHbkaKnp4e2tjZKSkpITz/Y8QomyuE2btzI8uXLP/FhOpRwbjK9UF5e/oVq8t1uN6tXr6azs5Np06Zx3HHHodFoGNjbyAcP/52gz8cxF1xKVvk8+p/uINbqJywTUCxMwaiR4V83hKCRoz8xE2VRDC9ueIZH+h7DoR4n3RHPquAMFi88lczy6SBE6Oh9jZdqdrBjsJA2Rx4gUJ6kZ2GwhdLtr5GztwdJJ+ArSYRZqYTKegjIh7GJJmrDadRavcQ5LOR58lFHVIyJGvoiZuYG7VT07iGxsx2d10tUJmM03sKIxYwx3otZ62K7toRHhRUEUHGN9AYXR3bhJpWBYCwd3njsYQ0SApLoRYgMIwoTqQ+5oEBnTEajiyMsZRIIFSKXDyOKakTRhCB8rGuYGEAQAgiyMHJ5lBjvIBldm4gbbsUbl0rNzHkMmRXoghKlDSNoBTmmGQmkmVtIdq0lLNPzU99l7JDN4d45GQgyGQJyolGIBEXs4QgblFHWG0WGNAJmr0hlh58ZnSF0YYmkHCPlS1LJKPv0ZjARmw3bzTcT2tuCbvnxqMsrED1uAlu2Ety9G1lSEruVIsW3/pyC+YuQJInrNnfSEA7zZkiHafl+BC+JqJ88mbBrlHtTFjDSeAY3o2HHDCsnrTzpgHvZ9e+9CAYFpgsLDxjPngEXFz9WxyLXPn4ebibpL39m2yvd7Ntp48zbp6PWf/JE3DbiwROMUJ0Zy+gvf0Wgtg7twt/gtuzAODCToUWJrNIG2ViVg0WQpsSSkzXWXq+XxsZGFi9ezOzZs3H+uxnrQCfdKe0s/+FNAFitVu5s7eEdVQzPlWZQbTy6urt9GiaJPT4+nuLi4qOa2D+OcDjMf//7X959913Wrl2LJEmsWLGCk08+mZUrV35uN9CjEUcVuYfD4and7MchiiItLS0MDQ1NOb+Njo6yd+/eIxawHQlEUWTv3r2MjIwwffr0KQvYQyEYDLJu3TqWL19+yJD65I49Go0ik8kQRZGmpiZcLhdVVVVH3Lr2UJAkicbGRtauXYtKpWL58uXk5+cT9PnY9NR/aNuygZwZs1l00RX4+kXGX+0mLirh0cgxHZeKvN1FuN2JsigW3Yp0Ijr45wd/5zXH6/jlAfKtSczrTqC8Yh65M+eSUliIbex9dux9kiarkS1Ds+l2ZhOVZMSpohT5Wikdaqess5ds7xCGskyiZUZcGb2MJw3RFFWzyx+LzaYjx5NLijcFEBgSDXRF4skTIixytKEa6KMzYqAuoYAdSSXIJJE5jr2sCm2mRD9EutZKjN49JcyLBGT4vTqCDhkRFwzJ0+iKW0SMdhp7nHsQo2ModcuRpABhzwsAqGRatHITKoURpcyAXG5E1GgQwg501gHMg22YXKOE1CZai6roKEgEGSSHg+R65SSrO8hS1WJSWHFH42nyraDWt5J7TQLHBBTMDMgBceJHigBhIIwgRECI0JOkZW1eGkOpGuTAcUEn5+sFpmWkEZuUgvAZaRopFML9/At4XnuNcE83Mq0OVUUFhpNXoluyhGd/8zOS84tYctnVADR5A5zS2Mtd9X5WZZjRnzgxMcoaX0Dz9vXsLP8dweS3ePndq7kpnID8mkJiLAfu0EN7HXhe6MT4/SKUmRP3r90b4owHd5Ji0vD71+8i9thFKC+5hpf+sJuqFelULks7rHs5Oj5O/wknoj/xfATZHHqX/J7itL/zgkrL7wfsNM3KR74fcYmiSH19PWvWrCElJYXU1FRSI2aStkusG36Wpb+6idjkFIaGhnitdR9/1iZyY3o816V9fhfJbxsmm6UkJCR854h9cm4bGRnht7/9LcnJydx1112sWbOGt956i82bN3P66afz3HPPfdND/VrwnSD3UCjE7t27CYVCBwjYHA4H9fX1RyRgOxJMfm84HKa6uvozezeHw2HWrl3L0qVLDxKAfFwRHwwGqa+vRyaTUVlZ+aV3mXK5XKxevZquri7y8vJYunQpsbGx7Nu1jQ2PPYQkicw7+yIK5i+m751+5LWjGATwxKiInR5PtGYUyR9BMy8Z7YIknCE39224j/fd7wMSpbYMSvaIxKqMZEyrJK2sHGNGiA7ra4jBnbSM5bGxfxH2cBFWj5xQdOI2TAg7yHRaSfQ4MIe9xMeCMjaA3zhGryFMk8pA1JeIIZAMYTNuSY1NNBBCAZJErBBifmSI44dqsAx2YxwdRfU/Z8OoXEAyy9AZghgNfjSxYVSmKCp9BEEmYAv9kagUh1m4iQb/EnYGLmG29hE02AlHJMLRIJFwkIgYISKJiDIJUSZDEEAhRFHJoqjlUdTyMCZliBhlEIMigFI2cc96ZWZGNUXYdGV84M5mw6CIQqtlKKTk9mMSyIhVI5fLEKNRIuEw0XCYaCRMOBRmxyg8PWRAlOBifQt1CRY2ZxbjV2sp7GxmfmsNsxNiyZ05l9wZc1B8jvtly7OP0759Mxf/5Z9TC4Xvt/Qz7A7yWloy6lQ90XAI5T9n4zbkoLzwObZt+xGbNk/HEZ5G5txkfrQ8/4BjSpKE6+EWkCRMV5SAAFc/00DzkJuXfzCLwKoTMV1yMY26RfQ2Ojjz9iqU6sMLf7uff56xe/6MbtWduFObiT9zPjExs7mj28pGp481ldkHvN9qtfLUU0+Rk5PDqlWr8Pl8eJ/eh6dvkK3KzeQvPxm1Wk3/mIPfx2aSpVXzVEn6AQuEoxk+n4+amhosFgtFRUXfOWJvampiZGSE3/3ud5jNZl577bUD9Bbj4+P09/czbdq0b3CkXx+OenJ3u93U1tZiNBqpqKg4IK/idrvZsWMHS5cu/dLHMmmIYzAYDvreT4Ioirz33nssWbLkAIHf/t2KZDIZbreb3bt3ExcX95U6YEmSRFtbGx988AE+n4+5c+cye/ZsIgE/W559nLYtG0gtKmXx93+ALiaRnpe70LY70QjgS9BiTNUhNTuQ6RVol6WjKjMz6BjkL5v/wjbfNmTIqAoWM6PPTGBfL0gSxoRENEl6xGw75sRWDKpxBj3JdHhPRKNfiNs/RvvwMDYHOAMxOCUjonDw+WsjfoxRFxp5gFhFmHilRJLgRhf2ER6XiI6FiHU7yY66SfPaiBmzIhdFJCCkUiEJAjJR/B/xS2jKT0ORewJC+++IyEZZHf97ssWtHCP/N3KNiEwpIZNLyBQTPx9HRJITkBSERAUhUYkfA26MjPiViLo0XDILTj+Mj7sI+bwoo0FkhzC8QRBQ63QodQaiKh0umY6egJrBqJb0jFSuWjWXvJz0iSYv0SjPD9h4ZHicQCTCLeueZbSjDa0phukrT6N82YlHdO8MtjTz2h9/w2k/v4OUggklfp3bzxnNffwpN4lTY3X0rvkX5Y2/x3PBW8jSqvnvo3cQ8MuQTbuQv63r4j+HsHSNDHhxPdKCbkUGLxDiD6vb+ed5FSwuiKdnzlzMP/4x8hO+h9PmJ7Xg8Ctahq+4kkggiLbwR/jPaCS9bKKrV1iUcESiB1QbeL1ennjiCTQaDeeffz4qlYrIkA/XQ3vZYn2d2T+9lBGnm5GRER7XxLNLoeUfBpHSxAk19tEuxPL5fOzatYukpKRD6oGOZkiSxN69exkaGuLuu+9GrVbz5ptvfuta0H7dOKrJfWRkhIaGBrKzs8nPP7j2dDLHvWLFii91HDabjfr6+s9liLN69WoWLlyITqebUsRH/1coLQgCNpuNxsZGcnJyyM7O/loewlAoxLZt29ixYwcGg4EFCxZQVlbG4N5GPnz8ITxjdqafuIrpJ51G2A+9L3ZhHPBOkHyMGp1RgTDgQ56sRXtcGso8E732Xh7Y9gCbvZsREJgpn8FK40I8ezvxWocJjI0SCQWQZ4ioSyJkpvejUYTodWbgHsslLmgiPqYPmbkdSRXEZzXg361D1iagdUSJV6oxAjIxSCTgxS/KsSUkM5SWii0xCVGuQOvzYBh3EPWIdEUTaDdm0BWbjMHkJUk7QppmFIvgpHIsnzm++eyRGmj1dyMPzQNJhT+4FkkeJSKTE5IrCWq1+PQGokoNBoUGvaRHG9agHtciC07slEW5F7nKiSAOM6YLIIXs6Po7AIgIctxKE/IYC5bUFIbUSbw2pGJ5ppJYlQyn043X5cTrdiMGvGiiAeLwk4AXZcCFFJmIQKi0OvLnzGfxJRO166IkMRCMkKFR4hwZpvatV2nZtI7kvEKWX3sT+thPz8dPQhJFnvrpj0grncaSy66Zev369iG2u3z8ITjCvLZ7iRU8BC95F4fDwUMPPcS0aS2sOOERLn9iN91jPl65atZBLVS9b/fS0zzKhSE3p09P4RcnTuTge2bPIe7mmzGec/YR3bMRm42BE05EPn8lsmlVpPxg1UF6iKn3RiI899xzjI+Pc9FFF2EyTZQLul/ah3NPH82JdeSfcCq9vb14C0r5Uf84t1v0HBP2YLPZCAaDU2YqHzfPORrg9XqpqakhOTn5azXw+jogSRItLS0MDg7y5z//eaoK4stIYR7tOKrIPRKJTInN9u3bR1dXF+Xl5SQnJx/y/Z+V4z5SSJJET08P7e3tlJWVkZqaesTHWLNmDXPnzsVgMBwknOvu7qarq4tp06Z9Zg/6rwJjY2Ns3LiR1tZW4uPjWbhwITlZWdS99Qq733kDjcHAnLMuoHDuMficIXpf6UHf68YgE/Cp5SjUMlSuMIpMA9qlaSgzDIy4Rnhg2wOsc6wjIkTIDeVyXuF5LK9cTmDcgdM6jMs6jNM+RE+0DdHQQXpcJ2p5CLsvjnF7DgkyLTExY6DvAsGPWpVOQsIJxMUtQ6//qIQnEAmwy7qLTX0b6OjqQOlQk+hLRB/VIyEhNwoIBhMeeRL94Vh6nTKqxuXcgoaXCPE3KchpATXZIRl7ClVIsUpk/zt2VJIIhkVUdBEj72Db4Cz84SihqEAoCsaoQFpURlpk4idBnLjfPEKUEVkIB+N4o8NooqPEhJ2oowHeSVpBbNjJ94ZfJ6TQEjAmIcSlok/PIaesjLLcVLLitAiCgCRJeMcd2Hu7Ge3rRqM3ULZk+Sf+LYfaWljzr/uQKRSs+umvMCUc3v2067UXqXvnNS75vwdR/S/N1OZwckrrMOeowtyz4XuE51xHZN4NbNq0iZ07tzFr9lPMm7uZUa+cMx7cSW6CjocvqkIl/+iZi/rDXPdCEy12H2/+cDZ69cSuunfRYmKuuJyYiy8+onvV/fLL2O/6PcYT70VzTib68uxDvk+SJN59912am5s577zzDnhme5/fSuOG1SSftxR3RCS/soqzOu0U6lT8tyjto+v+v77lNpttykzFYrF8KzqcfRa8Xi+7du0iNTX1kBugoxmTkcf+/n7uu+8+fD4fq1evnlq8/b+Oo47cg8Ege/bswel0Ul1d/al/yEgkwvvvv3/IHPeRQhRFmpubsdlsTJ8+ndjY2M91nA8++IDq6mqMRuOUcE6SJJqbmxkbG6OqquobvzmHhobYuHEj3d3dJCcnM3fuXJJiTWx/8Wn27dxGYm4+88+5mJTC4gmSf7MHebuTeJlASICIQoY2FEVVGIt2UQoefZitNVvZGdjJRu9GXIILS9DCUvNSzplxDqnJBy6SXH4PW1rWMmxbS5K6hli1i6gox08RRn0WJqULj7eBaNSNUplIbOwCzLHHEBMzD4XiI0GX1W+l1lpLbU8tfb19KJ1KLH4LalENSMyWF1LhzcSWHmWw2sLgBjfBHh/jFQZ6deAORPAEI/hDQZK1jcxKXM+0+EasPgt37vgFoiRHLRdQCFGUgoRWDgkGFelKLzHDTZjjq0jUphEcCuAZ9oME2jgVmkw9D42NMR6O8N/vZaFwDmPv62a0txt7bw9uuw2A2JQ00orLyKmeRWpxGfIjLOVxj9p4/U93IFcqOf0Xd6LSfnaY0mMf5cmfXsf8cy+m4viTptJe3fEprIr1kfb0iQQufAsxtZpHH32U2FglScl3U1b6KCbTDGp7x7n0id2snJbEXas+Emxt6rDzg6cbuO+sMpaXfLTQ6D/pJPQnrcR83bVHdG4DN11OeG8vxqV3EffjWQjyQ5NWc3Mzb775JitXrqTsYyWAL9/5C0KRCKnHncSMGTP4zbCb1Q4P75Znkao+9Hwxaaayv/p+kui/beF7j8dDTU3Nd5bY29vb6evr44EHHmBsbIz33nvvUwXN/6/hqCJ3l8vFrl27UCgUTJ8+/TNFZpIksXr1ahYvXvyZYrdPQygUoq6ujmg0SnV19RcKy61fv56ysjJiYmKQyWSEw2Hq6+sRRZHKyspvVcivp6eHLVu20NfXh9lsZvbs2cQpZWx77klGe7vIrJjO7NPPxZKVQyQs0vPhIP7tNhIjURSCgA9QiBLB2CiKufGkzslDROSdtnd4au9TdIY7UUfVFEeLWZm5ksXliw9aNI15g2xq3U3vyGbkkTryY9owqHwARLCgVhoRpHEikTFAhsFQQZx5MSbTTPT6MmSyjyZpe8BOo72RruZ2qndnkOaPZ5OqmXZxDKOzGGXYhDezjZgigYL0ONLj/AQDDTgcHxKJjKPV5pOWeinx8ScikymJRqM0NDTg9/uZPn064XCYhoYGtm3bhslkorq6msTERCwWCzJJyVC7k631Vv7ebcUnipwX1FBdGEd2eRzpZWbU/zOg8YzZGWrby2BrM32N9bhHbai0OnJmzKZ08TKS8g4/tOoYGuDl391OWuk0Vlx782F9bu2D9zPY2sxJt/2Ohj17plJE8oanUb37E/w/7iAoyvnrX//KCScsJxj6EUlJZ5GZcT3AVHOWy+ZlcPOyCUe3cx6pQSkTePLS6gPGMHzZZShS00i483eHdT4A4fA4/cuWoUpfSuxF16I/4ZPLm6LRKB0dHRQVFR3wurVrHy/dcRtZy1ay5PSzqQmJXNwywB9ykjgn8fDy/qIo4nA4pnb1k+H7SbL/Jp/lSWJPS0sjL++7Zb4DE9bivb29/Otf/6K/v5+1a9cSH//dqWr4MnBUkXtLSws+n4+SkpLDDrOvWbOGefPmfe4czOTOJSYmhvLy8i+0MhdFkR07dhAKhUhKSsJoNNLW1jbl6fxtWvXvj8HBQXbs2EFbW9tUK0izGKbxvTdwDg+RN2suM089m7i0dCRJwtruYmT9IKp+Dxa5gAQEJVCZlBiPTUVdlYAgE2gba+PJ+ifZMLoBP37iA/FUyitZkbOCiqIDm+EAhCIiu7odbO9sZHC0DpO8gyxTL+nGEbSKCcKXJprLAhIgR6WyoNFko9PmoRXyUDYkwR4d6EUix47SanPStT4FSYqgqXwBY3wzJo0HhWKi7t3tjcXuT8ItK8FkKSUvPZ/MmExi5DE01DcgCAJVVVUoFAp2797N2rVrycnJYfny5TgcDmw2Gw6Hg6Bcx/oRJe+0eyhMNHDn0nyivX56Gsaw9XqQyQVSi2IomGUho8yMXDFxf0uShL2vh86aHbRt+RD3qI249ExmnHI6+bMPz79h365tvPf3ezn+6hvJn/PZn7H39fL8r35C8vwlzDrxlCnfBuXGPyHf8yyBH9bS09PDc889x+WXX4597I8EAt1UlD8/dYwntvfzh9XtXLkgk4o0Ez96vvGQ/dNtt99OdHCI5P/+57DOBaBzy63Irl+Dbt6PMd9y2lSJ3eFCFEVeufcPOHo6Of+P9yPXaDhxTw9JSgVPl6R/LiL8NoXvPR4Pu3btIiMjg9zc3O8csXd2dtLd3c0jjzxCe3s769atw2KxfNPD+tbhqLLsyc/PnxKfHS7kcvkRf2YSVquV+vp6cnJyvtDqd3/hXGVlJXa7nf7+frq6ulAoFKhUKpxOJ2az+Vv5IKampnLaaadht9upq6ub8s3PqpxH8XSRvm0bee6XN5NTPYvqld/Dkp/DWBSGBnxEohmEmzzoxoPEu8P43uzF8WYvimQtmQuS+e2CXxOWR1nbu5YX9r7AB94PWN+3nsS2RAqlQo5NO5aygjLS0tJQKZXMz49nfv5iYDEjriA7e8b5sGeMpv4+IuFuUvRW0gyjpBnGSTI40ImjSKODaPoLUAylIAFjWa8xaGrGuvokvCNlGNL2kDV/DTqTFrV6IYIylSGvwL4hCeuIj6AjiNKnZFzqo4tuxtXjONVOovoocSlxrKtdh7vPjX/Qz5zyOaxaugqlQolSo6PNp+WtThXvt4yiloc4NVtiWYYPITxMSoWFsmNL8bvC9OxxsK/GxrrH2lHrFORWx1M0Lwlzio6EzGwSMrOZdeqZ9DU10Lz+fQIe92H//fJmziVv1lw2PvkIaaXT0Bo/Pe0TlCvQp2XiaWsi5dIrP/qFfwx0E7uj8fFxBEEgNjYWSTqW9o6f4Q/0otVM7KIvmpNOVBT505p95MTrqEo3HUTsAKqCQpzrP0SKRhEOY3Hr9e5lRPY2uTffiWIgDUWG/rCvA0zs5Gt3bMfW0siMVWei0+n4a7+dgWCYBwtTP/fzJwgCBoMBg8FAdnY2oVBoyjWtp6cHuVw+1c0uLi7uK1vIu91uampqyMjIIC/vu+WDD9DV1UV3dzePP/44ra2tfPDBB/8/sX8CjqqdezQanWqicrj48MMPKS8vP2gX+GmQJImuri727dv3qYK9wz3W/sI5mHDRa29vn2oDa7PZsFqtAFgsFhITE7/SCeCLIhwO09LSQn19PYODgyjlclJUMgJdbfgddmIysokvr2bhylVT5SgBT5jeGhvOnTZU4yESFAJa2cSuPqpXoMo2oskx4okJsc67idf736TN24ZMkpHkSyI9kE5VTBXFGcVkZmaSkpJygI5CkiR27WnlpfU12N0yMnTppPqVzIzIyESOHZFN6gCDSgdxLgUaVxySzo6hdDXZJWPEmbLRaQvQ6fLR6vJRKRMPmOgjkQgDwwPsadtD2742Iv4IBCZ+F5KFGFM5GFUGsCEwJloQQ/n4vUmIopzEmCjLynRcMDObDGMiznEnVqsVm81GJBKZUmEnJCTgtYdp32lj365R/O4wqYUxlC5MJr0kFkH2+Rd+PpeTZ269nuKFS1hw3vc/8X29vb10dHSQmRDHmvv+wKKLLp8S7qnevhHB0UnwgtfZsGEDTU1NXHPNNUTFADU1x5GcfO5UaH4SD2/q4d4POvnj90o4pfzg5yiwcycjV11NygvPo/oMMpIkiabm7xOJOMneeheKFD2GU7MP+xpMNhIJBwJofS4K5y5gWKnhxIYerkgx85OMz+/++Gn4usL3k8SemZlJbu6h7XuPZvT09NDR0cGzzz7Lzp07WbduHWlph2d49P8ijipyF0WR8P8MSQ4XmzZtorCw8LDV59FolKamJux2O9XV1V+ok9zHjWkkSaK1tRWr1UplZeUB+WVJkhgfH5+a9EOhEPHx8SQmJpKQkPCFBYFfFex2Oy0tLbS0tGAfHUXldaIZG0HyujElpVC5/CQK5y2aUl4DREJRBhvHGNk4TGjEj04QiFUImGR81HRFI0c0yrCp7bREOuiJ9uOT+ZGJCowhI7GhWFK0yZh1McgjMsJOP5qgnDiZCW1k4loJegX+JC3dokj7iJ+INYgsCiNqie3yEK1Kkf/F8NEqguiVXvQKL3qVF4MyhEalQ6PSo1HqUKsMhMIqrDYfUZR4/EE8Pj96WYQYeRiD6MUi86AWokiAV6bCo4kybuinV7UHt8INAqjlajIMGeTF5JEfk0+6Kp3YUCxBRxCv14vZbJ7Y3Znjsbb7adowxGivF5NFQ8XSVPJmJCCTf77Kj5rXX2LXGy9x3h/uO0g9P1mB0t/fP9VBce1DD9DXWM/5d/8NlVaL6t2fIFibCF78DmvXrqWnp4fLLrsMgM7O3+EY/5Dq6e8iCB8FBO/7oJPnagb48McLUCkOHrfo89F37BLMN/0Y07nnfur4x8e3sLflKkqyH0J8UIn+1GzUlYeXZ53s6Q0THSIVCgWSJHFJywA9wTDvlmeh/ZzX9UgwGb6fbHqyf/jeYrFgNBo/V/TA5XJRW1tLVlYWOTk5X8HIv1n09fXR3t7Oiy++yIYNG1i/fv3/U1aynwffeXLftm0bWVlZh9XHPRgMUldXhyRJTJ8+/QutqD9O7JFIhIaGBkKhEFVVVZ8q8JvsZWy1WrFarXi93qmVfmJi4tfW4e5I4Ha72bx5M8FgEI/Hw3B7C8oxK0r3OIJCQWJpBdOWriC7uPQAIaQkSrjq7QxvG2G0z0tQlJAEAZ0AWpmAVgZ6hQyFAHJJQs6BE1+YKAEiBIniE0X8goQXOc6oHLdPhiSCIIO4dC3pJWYKZiZijNcQjopY3UGGnEGGXAFs7hBOf4gxj5MxjxOH14s/HCAcCRMWRaKiDJkgopBFkCGhlIFJIyMxRkeCwUBaXAy5CUlY1Fr846MMDg4yODjI6OgoAFq9FkOSgUhsBLvOzr7APjqcHfgiE1qBBE0CZeYy8lR5JEWS0Hl1GA1GLBYL8qCBrh1OevY4MMarqTw+7XORfDgY4Kmf/oiMaZUsvfK6j/4G/6sVttlsVFdXT+lT3KM2nrntRqpOWsXs752Dcu0vkHdvIHD5BlavXs3w8DCXXHIJMBEub9hzNgX5fyIh4cSpY5/yz+2Up5r4/aklnziukR/+EBBI+sffP3X8E89FA+qBTDzPdxJz/TTksZ/9LITDYWpra1EqlVRWVk5FxD5weLiibZAHC1NZZv5m6qL3D9+Pjo6iUCimIjmHG71zuVzU1NRMCR+/a+jv76e1tZXXXnuNNWvWsG7duu9kZOLLxlGVc/88ONyc++TK12w2M23atC8snNvfcc7n87F79250Oh2zZs36TDc7QRAwGo0YjUby8vLw+XzYbDaGh4dpbW3FZDJNqbD1+iPLOX4VsNvtNDQ0UFhYSE5ODoIgEAwG6enpobNlLwN1OxhuqmekoYaoVo88KZ24gmLiLIno9Xr0ej26ZTrSI1pUXSEU7QFCjghuOYwZBDqEMO5QmJAvSsQvQVQOkgCCgCRNkH1YFiYiDyEpI0iqECgjiCo/Ij4iCi/WkEhLPXywR4ZSqUSpVKJSqaZqmUVRRCuKJASDGINB9m+Mqlar0OhEcnMNpKQqMRj8RCJDBAJ9BIP9hEIj/7sQYBdUaNRpZGVnUFScgUyWhnM8lhGrxEC/HUenAxky5sbP5f4L78cWttE+3s5ex15223bzxMgThMUw8ep4qtXVFFmLSPQnos3TUl4Qh61JYtOzndSvGWD6CRnkTo8/7HC9Uq1h5qlnsfHJR6g64RTiM7IQRZHGxkbcbjezZs06YNFpTLBQsWIldW+/RuG8hSQYUhA8E+c6ed0modeXEBOzgIHBh4iPP2HCt8HuY5/Nxw1LPn0i1h5zDI6//g3R70f2KYveieeiEt/AAIJReVjEHgwGp1owl5eXTwlxI5LE3b2jzDNpWRr7zT1DKpVqwuM+NXUqfG+z2WhtbT2s8L3T6aS2tvY7S+yDg4O0trby9ttv8+677/7/xH4EOKp27pIkEQqFjugztbW1xMXFfeqNPzw8zJ49e8jNzf1C6tJDOc45HA4aGhpITU39UtyhQqHQVOjebrej0+lITEwkMTHxc4f0vggmV9WlpaWfGh0J+H00blhPx/ZNOLr3gSAgi0skHBOPT6GG/asfJIiXjORGE8kVkzBKWgKyMKMxfsJZKmJLkkhJS53K5wejQZrHmqm11dIw2kCzoxlXyAVAojaRfMNE+Nsis5AgJBArxSJGxCnHQ5lMhiAIyGQy1Go1Wq0WrVaLXq/HbrczNjbG9OnTP9F/QBSDBIIDBAP9BAJ9BIJ9//t/L4FgP5I0GW2SIwhZeNz5+HyJzJ1biE5XiEeIYU3fOsJimPOLzqfJ3sTmoc1sGNxAn6cPo9LI4sTFzNLMQufR4RuL4usy4OyLEp+hY85pOSTlHNxS9VCIRiI8d/tNxKaksuJHt1BfXz/Vk+FQpaWRUIjnfnEzhvgEvnfyNDRvXYfvhjY2bK+jubmZq6++euq9Ltcumpovpbjo75jNi3ipbpBfvdHKjp8tnDKtOeSYHA5EpxNFVtZh3b/uZzsgKmG8oOBT3xcIBKipqcFkMlFWVnZAhc2TI+P8utvK69MyKdN/e8pPJ3E44fvJDUlubi5ZWVmffdCjDENDQ+zdu5c1a9bw3HPPsX79eoqLi7/pYR01+M6Te0NDA3q9/pDKUUmS6OzspLOzk4qKCpKSkr7Q2D7eg31gYIDW1laKi4u/EuFHJBJhdHQUq9XK6OgoSqVyKnQfGxv7lXnSw0c52r6+PiorK49IsOhzjtO2dSOtmz9krL8XpUZLWlkF6eXTSSosQVAoUCgUKJVKFAoF8tEI4eZxQs1jiK4wgkaOMs+EsjAGZX4MMu2BxCFJEkO+IfaO7aXZ0UzzWDMdzo4pwpcLcjIMGWSbsknRpZCiTyFZl0yKPoUUXQpGlXFqR+tyuQ5oRnTk1ylKKDQyQfSBXnz+Xgbd7exzddHuGaUtIKMnJEMhCCyMT+PHZRdhNE5Ho5kgui5XF2/3vM1b3W9hD9iZaZnJWVlnkR5Np7vJxnCdSNglJ7FQw5xVOSSkfrZGpGPHFtb88z4KTz2HmPSsqVK+T0JfYz1v/uUujjtzFdObbiFwwetsG5DYsmULN9544wHXfWzsfczmRchkan79Zgu7+128dvXsz3XtPgnj9+9BVWRGt/zQrZXhoyYp8fHxB/Urd0eiHFffzbGxeu7J+/xi2a8Tk+H7/c1zIpEIqampFBUVfWvFt58XIyMjNDU1sX79eh577DHWrVv3/0zDly8L33lyb2pqQqlUUlh4YD/paDRKY2MjDofjM53uDmdck/l1QRAQBIH29nYGBwepqDi4XvurgCiKjI2NTe3qJUmaWuV/2c5Zk6JDl8vF9OnTP3dqQJIkHIP9dNZsp3PXdux9PciVStLLKsicVknGtCpikpIPeH90yEeozUm43Ul0yAcCKDIMKHNNKHKMKNL0hwxTS5KEI+ig291Nl6uLblc33e5uhr3DDPuGCYkf3VdauRadoMMgM5BqTiVeG0+MKgatQvvRj1yLRqFB/jE/c1ES8Uf9+CN+fBEf3rCXscAYVr8Vm9/GkHcIb8QLQIzKRFVcIRWmBKp0EPU34/O1AhIqVRJm87HEmZdgMs1CRMaHAx/yWMtjtI63UhFfwU1VN5GpzmLPhl7aN44TCUkkT4eCOZZPjeT4fT6e+/VPkSuUnPe7ew6r6dH7//4bvQ11XJy+Ec2K2+lJWs6+fftYuHDhJ+62z3hwJyXJRu5c9eXttqSIiOP3dehPyUI9/dDq9kkv9U9qkvJ//aM8OOjgg8psUj7Bie7bjLGxMerq6oiJiSEQCHyrzHO+DFitVvbs2cOWLVt48MEHWbt2LVVVVd/0sI46HFXkDhM5tCNBS0sLkiRRUvKRoCcQCFBXV4cgCEyfPv0LCdQ+LpyLRqPs2bMHn89HVVXVN5ITlyQJp9M5JcgLBoMkJCR8Kcr7UChEfX09kiRRVVX1pbaidY4M01mznZ6GWkY62hCjUUyWJDKmVZJaXEpyQTEG80cLJdEVItThJNzmJNLjRgqKoJKhzDKizDGiyDEhT9R8ZqhXlEQcQQeD3kH6xvvYvW83ASGAMkaJM+TEEXTgDDkJRAJTxB2VPl3HIRfk6BQ6dAodcZo4LFoLFq2FJF0SeaY88mLySNYlHzS2SMSN21PP+PgmHGPrCIYGkctNWCwnk2g5HZ2ukK3DW3mg4QE6XZ2szF7J9ZXXo5MM7F7Thz5JIqJ2Y7fbD6qtntR/1NTUILjH2fPCE5zwo5+QU/3ZO+uAx8Pzv/oJZmmE7y1NI3LyA5/5mTl/3MiVx2RyxYIvL2QcdYZw/nUPhvPyUR2ig9xkOVh6evohvSlckSgLd3dxlsXEL7K+/v4NXxQOh4O6ujoKCgrIyMj4ytT33xRsNhsNDQ3s2LGDv//976xevZpZs2Z908M6KvGdJ/f29naCweBUSGdSgBIfH8+0adO+UOj648QeCATYvXs3KpWKioqKb0X52v7Ke5vNhsfjwWw2TwnyjmSV7/P5qKurw2AwfGHR4Wch5PcxsLeJvqZ6+hsbcFqHATDGW0guKCK5oJjk/ELMqenIFQokUSI66CPc5SLc5SbS54GohKCVo0g3oMgwoMjQo0jVIygP/Tf3eDzU1dURFxf3mS6IYTGMP+LnoMdHmNj5K2XKLzypSpKEz9fG6Ohb2EZfIxweI8Y0h7S0q9AZqni9+3X+ueefqOVqfjHrF8xLnjf12Ulx1v719DExMTidTlJSUiguLubNv9yFZ8zOOb/7M7LD+FsO7G3k9T/dwYI0GxW/+wA+5fxcgTBz/7SJv5xRyollnz/d9XFEBr24Hm7BdGUJipQDUyWTz3Z2dvYnloP9td/OvwbH2FCVg0V1dOmJJ4m9sLBwyjXw4/h4+P7zqO+/KYyOjtLQ0EBtbS333nsv77zzDvPmzfvsD/7/OCSOOnIPhUIHT6ifgq6uLpxOJ1VVVQwNDdHY2Eh+fv4Xaqc6KZwTRRFJkhAEAafTSX19PYmJiRQVFX2l+e4vAr/fP7WjdzqdGI3GKUHep0UZxsfH2b1795cmDDxSeMcdDHe0MtzewnB7K6O93YjRKDK5nNiUNBIysojLyCI+PZPYpBT0pjjEQT/hXg+RPg+RAS+ERJAJyFN0KNL1KNL0KFJ0yOLUOJ1O6urqppy9vm27HVEM43B8QP/Aw/h8LZhMs8jO+hlemZk7d97J9pHtnFNwDtdXXI9CdrAGYWBggJaWFpRKJeFwGLPZjCocZNO/72Px96+idPHSwxrH9of/wO7NNZx67VUkzzz+E9/XbvVy6r928OT3p1OdGftFTv0AhNqdeJ7pIPbGcmSmj6JGDoeD3bt3k5eX94n1z65IlEW7uzjdYuJXR9mufWxsjN27d1NUVHTY+p391fejo6Pf6vD95Pk1NDRw99138+abb7Jo0aJvZCx33303t912GzfccAP33XcfMBHtvfnmm3n22WcJBoOsWLGCf/zjH19Ip/VV4+haun4OyOVyIpEI7e3t9PT0UFlZ+YXaqR5KODc8PExzc/NUqOzbRgz7Q6vVkpWVRVZWFqFQaModr7OzE61WOyXI298Le1LcMnl+3wT0seYJG9WZcwEIB4OM9nRh7+/B3jfx01m7g8j/IjuCTIYx3oIpMQlTQiLawhjUghb/LzomAABNTElEQVR1UI3SrUS+W0K2CRQyJTKVioBOpDgtHpPJQHDAiSxeg0r77Zn8ZDIl8fEriItbzvj4Bnp6/kLDnrNJTjqHv8z7HS93v8tf6/9K+3g7d829izjNR+mL0dFR2traKC4uJj09Hb/fj81mw2azYcjKY8vzTyJPTCE5Ne0zPdBnXnAdI3XnsPrRJzgjtxpD3KFNZALhibSF7sveHUcmnjv2i75M7vg+i/geHxknIEpclfLVa2C+TNjtdurr6ykuLj6iNtMymYz4+Hji4+MPCN8PDg7S0tLyrQnfTy7Mmpub+cMf/sDrr7/+jRH7zp07+fe//01FRcUBr//4xz/mrbfe4oUXXiAmJobrrruO008/nc2bN38j4zwcfOd37n19fbS1taFQKKZarX5efNxKVhCEKcV4eXk5CQlfjX3l14FIJILdbp9S3k/mayVJYmhoiIqKim+9h7MkirhHbThtIxM94q0juKwjuEdt+F3j+N0uxMPsMxCrTuSkWdehSNEhT9ZN/GvRIBzCZe2bgCiGGR5+muHhpykvfw6lMpY6Wx23bb0NlUzF48c/Tqw6lqGhIZqbm5k2bdohdxn2wQFe+NVPyJy7CG1e8SHz9B+Hb8zKS3f9Gq0phtNuuwPFIXQXu3rGufixOt764RxyEj5fpcGhEGp24Hmxk9ifViLTKKbEV59VigkTIXm/KHJr5rf7Pt4fn5fYPwvflvD9+Pg4tbW1tLe388tf/pKXXnqJFStWfC3f/XF4PB6qq6v5xz/+wZ133klVVRX33XcfTqcTi8XC008/zZlnnglMaLlKSkrYunUrc+fO/UbG+1k46nbuHzfP+DT4/X46OzsRRZF58+Z9IfHX/sQuCMIBpVKzZs363F3nvi1QKBQkJSWRlJSEKIrY7Xba29vxer3I5XJGRkaQJOlb17N6fwgy2cROPTEJyioO+r0kSQS9XvyucYI+Lz1dXViHhshIT0OjUiHIZEhhEckVRumXI1epifS4CdbYJprMyQTkiZr9CF+PPEn7iTn8rxIymZLU1EtITj5/qq3tdMt0Hlv2GO/3vU+sOnbKJ76qquoT22HGp6YxbcnxtG7+kPPOPh9/OILNZqO5ufkg3/tJDYkuLpETrv8pr/7+l3zw8AMsu/rGgxYBEXHiGVV8Qp/1LwpBEKYWLuXl5YcVjbsh/ehqCToZkSgpKTksh80jwSeZ57S0tBAKhabC9xaL5StzxJxMhXV2dvLLX/6S55577hsjdoBrr72WlStXsmzZMu68886p12tqagiHwyxbtmzqteLiiR4X/z+5fwOYXBFOhhm/TGIPhULs3r0bmUzG7Nmzv1TF+LcBoijS19eHIAgsWLBgyjinra2NYDA45XlvsVi+FaLBw4UgCGgMBlQ6HXv37iWk0bPk9LM+c2EmhaJERvxEh31EhnxEBn0E6+0gAgLIE7UTefxk3dS/Xxfh79+vHiBJl8T5hefT0dFBf38/M2bM+Mz+CDNOOZOWTR9S99arLDjvEuLj4ykqKsLtdmOz2ejp6aGpqWnK995isWDJymHplT/ivX/cy8YnHmbRxVceENbVqSYWgL7Q5+vI+MknPPHPYP8grT3tVFZWHtURs0/CV0nsH8f+4fuioqKDwvdGo3Fqkfdlhe8nDXi6u7u57bbbeOqpp1i5cuWXcDafD88++yy1tbXs3LnzoN8NDw+jUqkO6AUCkJSUxPDw8Nc0wiPHd5LcBwcHp3LEJpOJhoaGz3Wc/YVzk4p4t9vN7t27iYuLo7S09FsrnPu8mCwTVKlUzJw5E6VSiU6nIzY2loKCArxeL1arld7eXpqbm6cm/MTExG+VQOeTEI1Gqa+vJxgMMmvWrMMas6CSo8wwoMz4aBEgRUSiI34iwz6iQxOkH2oYA1GaIPxk3ZRCX5lhOED89VVif5/4mTNnHlZESWsyMf3EVex64yXKjz8RU8JERzyTyYTJZCIvL++APH1bWxt6vR6LxcLscy9h+zOPotbpmXvWBVPHNKgnyN0TPLIujp8FQTMxZXW3djJ93nTM5oPbyB7tsNlsU6mGL9KR8vNg/9a1OTk5B4Tve3p6vpTwvdvtpra2lr6+Pn72s5/x6KOPctppp335J3OY6Ovr44YbbmDNmjVHxRx2uDjqyP3TVo2SJNHW1kZfXx9VVVVYLBZcLtfn6uf+ceGcTCbDZrPR2Ng45eP8bRbOfR643W7q6uqmXL0+vnDZ/8HPzc2dmvAnd/WTynuLxfKtTFOEQiHq6uqQy+VTC5fPC0Ehm1Dbp31UYSBFRKJW/8Tuvs9DuH2c4I6JVr6yWBXKHCPKvBgUuUZkmi//0fs0n/jPQsWKlTR+sJodLz3LsquuP+j3Wq2WzMxMMjMzCYfDUxO+U6klefZC6t5+DVNmDsWz5iKTyTD+z27W5f9yyX1wbBgjUJZXTOx3lNgbGho+USPxdeOzwvfx8fFTZH844XuPx0NNTQ0DAwP85Cc/4d///vdUHvubQk1NDVarlerq6qnXotEoGzZs4IEHHmD16tWEQiHGx8cP2L2PjIx87YuvI8FRJ6iLRCKHJOvJrmuToohJcvF6vWzevJnly5cf9nccSjjX3d1NV1cX06ZN+//aO/Owps70/d+BuoDsEraKCqK4IaviUlu0VnFUgmN71U5brW3t1IVqbetenfnaZaxO69Ral05HnGm1VFm04q6AbbVWkrAq7oJsSSAQIGTP+f3h75wSRWVJOCfH93Nd/aMhwBMTzn3e93ne++7UtD1XqampQWFhIfr379+hGxf6Dl8ul6O2thY9e/Zkjtg9agK7K2hubmbaNJ31N2gP5kbDXaEva4LhZgPMNdq7rnpP9kK3UA90H+oJR8/O9zTpHYmH+cQ/imsXfoXJYMDgp+La/D30Bf+aNBeGHs4wGAzw9vZGb29vTNt9Fe8/F4JXRj3YJrat0HbHVaUVCHsiCG6Rfl22G9JV0MOBXBH2h9Fy+l6hUKChoeGR2/dqtRq5ubmoqqrCkiVLsHXrVsydO5f1a0NjYyNKS0stHps3bx4GDx6MFStWIDAwEEKhEPv27cOsWbMAgLEV53LPnRfirtFoIBaL0b179/tc07RaLbKzszF58uQ2XdBby2C/dOkSlEolIiIiOmVTy1XaGv7SVkwmE7OyUygUzAS2j48PPD09u7yVoVKpkJeXBz8/v1btSLsSk0oPww0VDNcaYLihAowUHAOc0WO4F7qP6A0H5/av6A0GA6RSKRwcHB7pE29LKIpi+vQKhQKrfm5GuG93LIvrC6FQ2K6dhHt/7tWrVyGTyRAdHc2JJERrI5PJUFRU1ObhQK7xsOl7T09P6PV65Obmorq6Gu+88w42bdqEt956i3VhfxBxcXHMtDwALFiwAEeOHEFycjLc3NyQlJQEADh37hyLVT4cu9uWvxfatcnPzw+DBw++TzjoC53JZHqkqNwr7AaDAfn5+TCbzRg1ahSv+jHA3dd7/fp1VFRUICoqymr9S0dHR4vJe9opraioCGazmRnK8vb2tvnkPT2YFBwczIlITEf37nCMEqJnlBCU3gT9NRX0xXVoPl2B5tMV6D7EEz1ihHgisFebLnz0jISTkxPCwsJYPclwb58+9EYe6rS6+/r0QqGwzbs5FEXh8uXLUCqV7W412Au0sNvDcdMH8bDt+6VLl8Ld3R0DBw5ERkYGPv30U04Le2t88cUXcHBwwKxZsyxMbLiM3a3cTSYTjMa7fbzy8nJcvnwZoaGhD3SloigKx48fR1xc3EPF+d4MdrVajby8PCYukqvHvzqKtcJf2gNFUWhoaGAc8rRaLTN57+3tbfVTB5WVlbh8+bLVdiRsibnZCF1eDXSSGpiVOjwR2As9n/JHt5AHiyDdavD09HykXS4bbDlzE2l5Vch5dyyTYEiv7Npynt5sNjOf0ejoaN7dXAN3J7GLi4vtWtgfhkajwf79+3H8+HEcOnQIABAdHY0ZM2ZgxowZCA8PtyuRtyfsUtwNBgOuXLmCioqKh57hpTlx4gTGjRvXqoC15jhXW1uLwsJCzlqRdhZbhr+0h6amJmYgr7GxER4eHsxAXmdWaBRF4fbt27h9+zZGjBjxyM8Hl6AoCoZrKmh+roapQg1Hf2c4P9cH3fpbmi/RE8f+/v6s2AG3hawrNViUUoiT74zBkx5/CHPLlZ1CoWD69C3P05vNZhQUFECj0SAqKspmZ63ZhM4rHzFiBC+P82m1WojFYtTU1GDx4sX44IMPMG/ePBw9ehSHDx/G8ePHIRKJ8N1337FdKi+xO3HXarWQSCRobm5GVFRUm1acp0+fRkxMzH3nfVsbnLtz5w6uXbtmF6u9jqBWqyGVSuHq6mrz8Jf2oNVqmZCTuro6uLi4WHjet1W8KIrClStXIJPJOu1IyCYURcF4uxHNZyphqlCj22APOE/qA0evHoxdZ0eHH7uKWrUe4//5Kz6bORTTw1ofELu3T9/U1AR3d3fo9Xo4ODh0+lQDV+G7sOt0OkbYk5KSsHjxYqxbt87is6rT6VBTU9Nmr3xC+7A7cS8vL2c84tv6R5+Tk4OwsDCLXHV6xU734mlRkMvlCA8Pv8+wgA+wHf7SVh40eS8UCuHu7v7Auk0mE4qKipgTE3zoz1IUBX2REs2nKkA1G2Ee5Y4Ch1IMCn1wMhiXmLnzd4T6uuAfiUPb9Pympibk5eXBYDDAZDJ1qE/PdWhzmPDwcLvaVWor9PBcXV0dkpKS8MYbb+Cjjz7ixXtnT9jdQF1AQAC8vb3b9UFxdHS0mLC/d3COPkan1+sxatQoXojCvdC9vUGDBrEW/tJWWg7nmEwmxvOenginV/QtJ+8NBgPy8vJAURRGjhzJG9dAgUCAHmG90T3UA4rD1+B4vg4jfIXwDLeP1d7TIb1xQFoFk5mCo8PD/2YNBgOKi4vh7OyM8PBwmM1mpk8vkUja1KfnOrSwR0REWCw2+ILBYIBYLEZdXR2WLl2KV155BRs2bCDCzgJ2t3I3m80wGAzt+p7z588jKCgIfn5+9w3OaTQaSKVSODs7IywsjLVjRLaC7j/funULYWFhdj2007JXK5fLYTKZ4O3tDQ+Puz7qvXr1Yn1i3FbQPvHhwlA45tTB3GhAr+n90COM2wIhvaPCy7sl+O/cSMT083jg8/R6PcRiMZycnDBixIj7hLstfXquU1FRgStXrvBe2Ovr67FkyRLMnDkTW7ZsscubMD5gd+JOURT0en27vufixYvw9/dnVoLA3RVRXV0dCgoKOL9N3VHMZjNKSkpQU1PDuzP69OR9RUUFKisrQVEUvL29me17vqzcKYrCzZs3cefOHURGRsLd3R2U3gT1kTLoC5ToESOE8+Q+nEmruxczRWHK1t8wOsgTG2YMbvU59ByNi4tLmwyGWuvTe3h4MF4KXNx5Ky8vx9WrVxEZyU/LXKPRCIlEgrq6Oixbtow5KkaEnT0eC3EXi8Xw8vJiepQCgYDZHgsNDbWL3mV7oVsNOp0OkZGRvDxGpFQqkZ+fj759+8LX1/e+yXsuX+zbQss5kJaui/TXdJIaNB+7gyf8neHy4gA49OLm6nVr9i3897c7OPveODh1s9xVoQ2oPD09MXTo0A7dYLf0va+rq+Ncn54e0uWzsEulUiiVSnzwwQd45plnsGvXLl7uoNkTvBd3iqJQWFiIxsZG9OnTB0KhEKWlpaisrMSIESN4uT1GG5v06NEDI0aM4F2rAbhr/EHPENx7c6bVahmhbzl5T3ves32xbwstz3g/bDjQWK5GY8p1CHo4wvUvIXD04t5NXJlSg/ivfsOGGaGYFflHJrlarYZYLIaPjw9CQ0Ot8r4YDAZmRqOt5+ltyZ07d3D9+nVERkbyckjXZDJBKpWirq4Oy5cvx6hRo5CcnEyEnQPYnbgDd49QtAV6cE6r1aK6uhoymQyNjY1wcHBAv379EBgYyLvzs3T4i7e3d6uOfXyA7j+3ZYbAYDAwq7qamhr06NGDGch72OQ9m7TXJ95Up0Pj3mugmo1wmR1ikV7HFRanFOJ2bTMOLRgFB4GAOacfEBCAkJAQm7wPrfXpW5om2bpPX1ZWhhs3bvBa2PPy8lBXV4dVq1Zh+PDh+P7773m5mLBHeCvu9w7OabVa5OXlMXfyNTU1UKlUcHd3Zy729rp9S0NbrfI1ta6lXS7df24PLSfva2pqIBAImK17rkxfd9Qn3qwxoinlBoyVangsHs65UBV6sO6rF8MQ7dcNUqkU/fr1Q1BQUJf8/q7u05eWluLmzZuIiopq9+fUHjCbzcjPz4dSqcTatWsRHByMH3/80S4GGx8X7FLc9Xo9HlQ2ncHecnBOpVIhPz+f2f6jL+I63V3fa5lMxmzf+vr6MsYp9gQd/jJs2DBOxxB2FLPZjEuXLqGurq7N5kWP+nn19fWMcY7RaLRY1bGx+tDpdJBIJB32iaeMZhiuN6D7YA/bFNhJXtktgZ+LI6Z5KxEcHIx+/fqxVost+/T06RQ+C3tBQQFqa2uxfv16BAQEIC0tjTdDrHyBV+LemuNcdXU1Ll26hIEDByIwMPCBf7T09q1MJkNtbS169erFrOi53KdtuZoNDw/n7cAO7UMQGRlp9VYKPXlP9+mbm5vRu3dvZlXXFRct2ifew8MDQ4cO5cQugrW5Xi5D6ZVihHLMgMeafXpa2KOjo3l1OoXGbDajsLAQtbW12LBhAzw8PHDw4EFeDuzaO7wR95bGNAKBAAKBADdv3kRZWRnCwsLaZfFIh1zIZDLU1NRwLpucho3wl65Gp9NBKpWiW7duCA8P75IVNZ1TLZfL0dDQYPPWDd1/5kIkra2gs8q5buvcmT79rVu3UFpaiqioKF4KO0VRKCoqgkKhwCeffIKePXsiMzPT7tuZfMUuxd1gMDBBL8D9jnP0pLFKpUJkZKTFEaL2QvdpaaF/4oknmAu9h4cHaxdivV6PvLw8AGA1/MWW0D747u7uGDZsGCur2Xsn7629o2MvPvGdgXZHtLes8vb06emFRHR0tN3mGTwMiqJQXFwMhUKBzz77DACQmZnZqWsrwbbYvbjfK+y06Dk4OCA8PNyqomc2m6FUKiGTyaBQKCAQCFq1QrU1tOjxNY4WAFQqFaRSKZ588kmbTVO3F4PBwHje05P39IW+Izd6CoUChYWFrR7n4wu0KxsfAlIe1KfX6XSQy+WIiYnhrbBfvnwZMpkMn3/+OTQaDY4dO8bL3Qk+YbfiTvfWWw7ONTY2Ii8vD15eXjbvW9IDWTKZDHK5HBRFMRf63r172+x319XVIT8/n1OiZ21o0QsJCUHfvn3ZLqdVTCYTlEolM5BHT94LhcI2vf9VVVW4dOkShg8fDl/f1hPT7B36yCIf7VbpG71bt25BrVajW7duzI0+V05eWAOKolBSUoLq6mps3boVSqUSJ06c4OXRPr5ht+LecvUuEAigUChQVFTEyjEwiqKgUqkYoTcajYwVqre3t9VW1nRMJN9XeiUlJXY19U/f6NHb97Tv+YMm7xmfeJ6mggF3+8+3b9/m7RlviqJw48YN5lhmSz8Fuk9P3+zZ6/EwiqJw9epVVFZWYvv27aioqMDp06d5d6PGV+xO3M1mMz777DNMnjyZ8YNfv349/Pz88MILL7De06P7dLTQa7VaC8/zjgyEtQx/4cP2ZmtQFMUMJIWHh9vtBYR+/+kVvVqthpeXFyP0FRUVuHPnDiIiIngteuXl5bzuP1+/fh2VlZWIiYmxGGSlKApNTU3M+28PvvetQVEUrl27hoqKCvz73//G9evXcebMGbsOnnrcsDtxr62txauvvorTp09jwIABMJlMkMvlSElJwVNPPcV2eRZQFAW1Ws0IvVqtZiZv2xpuYjabcfnyZdTW1iIyMpK3F8vLly+jpqaGd6+xubkZcrkccrkcKpUKAoEAffv2RZ8+feDs7Mx2eVaFXunJZLL7vPD5wsOEvTU0Gg0zp8FF3/sHcf36dZSVlWHPnj0oLi5GVlZWl7WPPv30U6SlpaGkpAROTk4YO3YsNm7ciNDQUOY5Wq0W7733Hn744QfodDomqIavLa6OYHfiDvzxBzZ9+nTIZDJotVr069cPIpEIiYmJrUZGcgG1Ws1c6BsbG+Hp6cn06Vo7u20wGCzOd/PxLKnJZEJhYSGam5sRGRlpNyub9tDy9EZAQADq6+uhVCrtxkuhLdA3aLW1tYiOjubdjQvwx2q2uroa0dHR7T56Sp+np62QHR0dmV09LvXpb968idLSUuzduxcXL15EdnY2AgICHv2NViI+Ph6zZ8/GyJEjYTQasXr1ahQVFeHSpUvMv/mCBQuQmZmJ5ORkuLu7Y/HixXBwcMCvv/7aZXVyHbsU9+LiYsyYMQMxMTFITk6G0WhEZmYmUlNTcezYMfj4+DBCHx0dzZk/mpZoNBqLFd29Z6kfh/AX+mSDQCBARESE3fYmH0ZLn/iWBjz0QBZ9oW85kMXmEcuOQLsHqlQqREdH8/ImtOWuRExMTKdvXh50np7tPj09K/Hjjz/il19+QVZWFutDrQqFAj4+PsjJycHTTz8NlUoFoVCIvXv34vnnnwcAlJSUYMiQITh//jxGjx7Nar1cwS7FfcqUKYiNjcXf/va3+4RbrVbj6NGjSE1NxZEjR+Dh4YGEhASIRCLExsZy8tgYfZSG3rpzdnZmevVtybe2RzQaDaRSKXr16oXhw4dz8n3pLAaDwcKL4EEX7Hsn7wFYeN5z+d+Gdixrbm5GVFQU74KYgD+idxUKhU12JR7WpxcKhV22C1JaWoobN24gIyMDJ0+eRHZ2dpd5/z+M69evY+DAgSgsLMTw4cNx5swZPPvss6irq7OYW+nXrx+WLl2Kd999l71iOYRdirtOp2vTRUSj0eDEiRNITU3F4cOH0bNnT8yYMQMzZ87E2LFjObkarqqqQnFxMZycnKDRaJitW19fX/Tq1cuuVnQPgnZk8/HxweDBg3nxmu6loz7xFEUxnvctJ++FQmGXJJm1B3pXwmAwIDIykpdGSi2FPSYmpkvaRq0ZJ9m6T09nzh85cgSHDh1CVlYWBg4caPXf017MZjMSEhJQX1+PX375BQCwd+9ezJs3774AsVGjRmHChAnYuHEjG6VyDu6pWxto6+rAyckJIpEIIpEIer0ep06dQmpqKl599VUIBAJMnz4dM2fOxPjx4zlxYaL/wIYPHw4/Pz8YjUbmj/z27ductcFtD0qlEvn5+bx2ZOuMT7xAIICnpyc8PT0xaNAgZkV3+/ZtFBcXM5P3QqGQ1VWy0WhEXl4eKIpCVFQUp246rAV9xrumpqbLhB0AevbsicDAQAQGBlr06SUSiUWf3tPT0yq7OuXl5bh27RpOnTqF9PR0zgg7ACxatAhFRUWMsBPajl2u3DuLwWBATk4ODhw4gIyMDOj1ekyfPh0ikQgTJ07s8osmPahTWVn5wCNSJpPJwh2NtsH19fXlbC75vdA2pEOGDOnSAZ2uxJY+8fTkvUKhgEqlgpubG3Oz15UDbHQsraOjIyIiIjjdNugo9ICgUqlEdHQ0JwY9bdGnr6ysRElJCXJycrBnzx6cOXMGw4cPt0H17Wfx4sU4ePAgzp49a9EeINvybeOxFPeWmEwm/PLLL4zQNzY2YurUqRCJRJg0aZLNL5omkwlFRUVoampCZGRkm36f2WxmUqzYtMFtD3Q/j6/n9AGgvr4eUqm0S3Yl6LhiuVzOTN7TfXpXV1eb/W69Xg+JRMIMevJV2Ol44ZiYGE4OCFqjT0+bYp07dw47d+7EmTNnEB4e3gXVPxyKopCUlIT09HRkZ2fft4tAD9Tt27cPs2bNAgBcuXIFgwcPJgN1LXjsxb0lZrMZv/32GyP0CoUCU6ZMgUgkwpQpU6x+brfltHhHffDpu3m6R9tVNrhthZ4yrqqqQmRkJC/zrQF2feLpFEN6V6dbt24WnvfW+gxotVpIJBK4uLjwdtCTFvb6+nq7mvyn+/QKhcLiZu9BfXqZTIbi4mL8/vvv+Oqrr3DixAnExMSwVL0lCxcuxN69e3Hw4EGLs+3u7u7MDsqCBQtw5MgRJCcnw83NDUlJSQCAc+fOsVIzFyHi/gDMZjPEYjEOHDiA9PR0lJeX47nnnoNIJMLUqVM7LVK2CH/pKhvcttLyfHdUVBQvzz4Df/jEc8Eyl97VoS/09M0e7Xnf0c+ARqOBWCyGp6cnhg4dahdtoPZCJ5/Z+5G+e8/TOzg4WOzqqFQqFBYWQiqV4vPPP8exY8c4tdp90Gdr9+7deO211wD8YWKzb98+CxMbtv/+uAQR9zZgNptRUFDACP2NGzcwceJEiEQiTJs2DZ6enu262NExn3369LFZ+AtFUWhoaGBW9NawwW0PRqMR+fn5MBqNvJ2kBv4YguRiu4GevKe37/V6fZuzyVuiVqshkUggFAoRGhrKa2FvaGhAdHQ0b470tezT37hxA/PmzUN4eDiEQiFOnz6NI0eOYPz48WyXSbABRNzbCT1oc+DAAaSlpeHSpUt45plnkJiYiOnTp8Pb2/uhFz96lRcaGtpl27ct+3NyuRzNzc3w8vKCr6+vTQwzHgcDHoqicPPmTbvxib/3M6BWqxmHRKFQ+MBValNTE8RiMQICAnibQkjvMDU2NvJK2O9FLpfj4MGDSEtLw88//wyBQIDx48czJ4qCg4PZLpFgRYi4dwLaBpcW+ry8PIwbNw4ikQgJCQnw8/NjLoZmsxm///47NBoNwsLCWF3ltdcGt70/WyKRMNu3fO3LXrlyBXK53G491O91SHRzc2O2bmmLz4aGBkgkEvTt2xdBQUG8FfaioiKo1WpER0fzdodJqVQiLy8P165dw4cffoi0tDQMGTIEhw4dYs61r127FuvWrWO7VIKVIOJuJejkttTUVKSlpeH333/H6NGjkZCQgPj4eKxduxZXr15FdnY23Nzc2C6XoTUbXF9fX/j4+LS751hfX8+0GwYMGMBbMWjZl+XCEanOotfrLSbvnZyc4ObmBrlcjuDgYPTv35/tEm1CS3c9Pgt7XV0dpFIpbt26hVWrViElJQXTpk2zeI5KpYJGoyE9ax5BxN0GUBSF8vJypKWl4ccff8S5c+fQs2dPLFq0CPPmzeOsecu9Nriurq7MWfpHDcPJ5XIUFRVh4MCBCAwM7KKKuxaTyYSCggLodDoLn3g+YTQacfv2bdy+fRsCgQDdu3e3yeQ929DCrtFoEBUVxVthr6+vh0QiwZ07d/D+++/j+++/R2JiIttlEboAIu42pLS0FNOmTYOfnx+mTp2Ko0ePIicnB2FhYUyfi86k5xotV3O1tbUPtcEtLy/H1atXMWzYMN5GLrbVJ97eoY/0DRkyBL6+vhae9xRFMUOZnZm8Zxt6QFar1fJa2FUqFSQSCSoqKrBs2TLs3r0bL7zwAttlEboIIu42Ij8/H/Hx8UhMTMTWrVvxxBNPgKIo1NTU4ODBg0hNTcWZM2cwaNAgJsFuyJAhnBR6OsGMPkfd0gZXLpejvLwcERER8PT0ZLtUm0D7xPfs2ZO3xi3AHw6Cw4cPv+8mjT5mSe/s6HQ6xvOezRSz9mI2m5Gfnw+dTofo6Gi7qbu9NDQ0QCwWo7q6GkuWLMGuXbvw0ksvcfL6QrANRNxtRHl5OQ4ePIiFCxe2+gdFH1M6dOgQUlNTcfLkSYtM+rCwME5ugdI2uPRZegDw8/NDnz597MYGtz10xifenqBtSMPCwiAUCh/6XIqiLIYym5qa2jR5zzZ0W0Wv1/PWDx+4a4EsFoshl8uRlJSErVu3Yu7cubz72yQ8HCLuHKGhoQGHDx9mMun9/PyQkJCAmTNnIioqilOiQl8kNRoN+vfvz5yjpW1wfX19edGftaVPPJegz+pHRETAy8ur3d+v0WiYFk59fT0zq9Fy8p5t6AQ72neBr8Le1NSE3Nxc1NTUYPHixdi8eTPmz5/P288u4cEQcecgTU1NFpn0np6eSEhIQGJiIkaNGsXqtrBer2dCQ8LDw5mL5INscH19feHl5WV3Qk/7xPfr14+3x8AA4Pbt27h16xYiIyOtcla/tcl7eiCPrSTDx0XY1Wo1cnNzoVQqsXDhQnz88cdYtGgRbz+7hIdDxJ3jaDQaHD9+HGlpafjpp5/g7OyMGTNmIDExscsz6ZubmyGVSuHq6vpQy9x7M8mNRqOF3z3Xe9Y1NTUoKCjg9eR/SxOeqKgomxzPNBqNTMBRTU0NHB0dma37rgo4MplMyMvLg8lkQlRUFC8NlYC7f5u5ubmoq6vDggULsH79eixdupQI+2MMEXc7QqvV4vTp00hLS8PBgwfh6OhokUlvyxVJQ0MDpFJpu7eoW9rgymQyZhDL19cX3t7enLvYcskn3lbQEcNVVVWIjo7uEhOee3d2zGazzW/4aGE3m82IjIzk3GfNWmg0GuTm5qK+vh4LFizAihUrsHz5ciLsjzlE3O0Ug8GA7OxspKamIiMjAwaDgcmknzBhglXPYNfW1iI/Px/BwcHo169fhy8aXW2D21647BNvLSiKQklJCWpqahAdHc1KmA89eU9v32u1Wsbz3lqfA5PJBKlUCoqieC3sWq0Wubm5UKlUWLhwIZKSkvDhhx8SYScQcecDRqPRIpO+qakJf/rTn5hM+s64qNEr2aFDh8Lf39+KVf9hgyuTyZiJa1rou9Ight6iLisrs1rvmYuYzWaLOFMuuOs9aPKeXtV3ZPLeaDRCKpVCIBAgMjKS822gjqLVaiEWi6FSqbB48WK8+eab2LBhAxF2AgAOintCQgLy8vIgl8vh6emJSZMmYePGjQgICGCeU1BQgEWLFuHixYsQCoVISkrC8uXLWayaO5hMJotM+pqaGkyZMgWJiYmYMmVKm6eXKYpCaWkpbt68ifDwcPTu3dumdVvTBrc90D7xMpmsy7ao2YB2ZKM91Lnqrtfa5H1Lz/tHCRct7A4ODoiIiOCtsOt0OojFYjQ0NCApKQl/+ctfsHHjRrsbXCXYDs6J+xdffIExY8bA398fFRUVeP/99wEA586dA3C39zto0CBMmjQJq1atQmFhIV5//XVs2bIFb731Fpulcw6z2Yzc3FwmqrayshKTJk1CYmIipk6d+sAhqpaCFxkZ2eVe+K3Z4NJCb81tZD76xLdGS9tce3Jk0+v1jHlSbW0tY54kFApb9VQwGo2QSCRwdHTktbDr9Xrk5uaiqakJSUlJmDlzJrZs2UKEnWAB58T9Xg4dOoTExETodDp069YN27dvx5o1a1BdXc1cpFauXImMjAyUlJSwXC13oZ256GCbmzdv4tlnn2Uy6T08PCAQCKBWq/Htt98iOjoaUVFRrAteaza4tNB3ZpVNCx5tQcrVlWxnMRqNyM/Ph8lksutjYLR5kkKhgEKhgKOjI7Oi9/T0ZHrsTzzxBMLDw3kr7AaDgRH2JUuWID4+Hl9//TURdsJ9cFrclUolFixYgIqKCvzyyy8AgDlz5qChoQEZGRnM87KysjBx4kQolUreWqBaE4qicOnSJSaq9vLly4iLi8Ozzz6L7777DiaTCdnZ2Zzbor7XBtfJyYkxS3F1dW1zr/Fx8Yk3GAyMJwGfVrItJ+8VCgWMRiMcHBzQo0cPXqe7GQwGiMViNDU1YdmyZXjmmWewa9cu3ryvBOvCSXFfsWIFvvrqKzQ3N2P06NE4fPgw0/OdPHkygoKCsHPnTub59NGlS5cuYciQIWyVbZfQx6K+/fZbfPnll9DpdBg3bhxmzZqFhIQE+Pr6cnJAp6UNbk1NDbp3784I/cNscB8Xn3i9Xg+JRIIePXrw/nXm5ubCbDZDIBBAq9XCy8uL2b7ni9DTLYempia8//77GDlyJJKTk3n7vhI6T5fs5axcuRICgeCh/7XcUv/ggw8glUpx4sQJODo6Ys6cOeDgPQgvEAgEMBgM2LdvH/7yl7+gpKQECQkJSElJwaBBgxAfH49t27ahvLycU++Bo6MjfH19MWLECDzzzDMIDQ1lVqo///wzSkpKoFQqYTabme/RaDS4ePEiXF1deb11q9PpkJubC2dnZ16/ToPBAIlEAicnJ4wdOxbjxo1DbGwsPDw8UF5ejrNnzyI3NxdlZWXQaDRsl9th6CHBpqYmrFixAhEREdi9ezdv31eCdeiSlbtCoUBtbe1DnxMcHNzqXXZ5eTkCAwNx7tw5jBkzhmzLW5kbN25g5MiReOedd7B+/XpmxUtRFO7cuYO0tDSkp6fj119/RXR0NBITEyESiTp13t2W0Fu2MpmMiSmlt+1v3LgBf39/XvvEazQaiMVi3gfd0DsT9A5Ma69Tq9UyW/d1dXVwcXGx8Ly3h88APUvQ2NiIVatWISQkBCkpKay3krZt24ZNmzahuroa4eHh2Lp1K0aNGsVqTQRLOLkt35KysjL069cPWVlZiIuLYwbqZDIZ8wFfvXo10tLSyEBdBzCbzcjKysKzzz77wOdQFIWqqiqkp6cjLS0NZ8+eRVhYGCP0ISEhnLxQ0ja4d+7cgUwmg4ODAxNsYw82uO1FrVZDIpHA29sbgwcP5uR7Yg30ej3EYjGcnZ3bnJ5oMBgsBjN79OjRpjYOm9AOew0NDVi3bh0CAgKQmprKeqshJSUFc+bMwY4dOxAbG4stW7Zg//79uHLlCnx8fFitjfAHnBL3Cxcu4OLFi3jqqafg6emJGzdu4MMPP4RMJkNxcTF69OgBlUqF0NBQTJ48GStWrEBRURFef/11fPHFF+QoXBdAZ9JnZGQwmfSDBw+GSCSCSCTiXCY97RMfEhICd3d3xjRHr9fD29sbPj4+nLTBbS9NTU0Qi8Xw9/fHwIEDOfUeWBNa2Hv16oXhw4d3aGfCZDIxnvcKhQIODg7M5D1XQo7o0y0qlQp///vf4enpiYyMDE7E6cbGxmLkyJH46quvANytNTAwEElJSVi5ciXL1RFoOCXuhYWFWLJkCfLz86FWq+Hv74/4+HisXbsWTz75JPO8liY23t7eSEpKwooVK1is/PGEoijU1dVZZNIHBQUxmfQdvfhai+rqahQXF9/nE9/SBlcmk0Gj0Vjd/rQraWhogEQiQWBgIIKDg3kt7Lm5uXBxcbHaZ8tsNluEHJlMJuamr3fv3qzc9JnNZhQUFKC+vh4ff/wxevbsicOHD7N+LBW4+x44OzvjwIEDSExMZB6fO3cu6uvrcfDgQfaKI1jAKXEn2DcqlYrJpD9+/Dj8/f2ZTPrIyMguFfr2+MTfa4NLT1v7+PiwvgX6KOho2qCgIPTv35/tcmwG7chGJxLa4rNEhxzR2/cajabLJ+9pJ8H6+nr84x//AABkZmZy5lhqZWUlnnzySWYGimb58uXIycnBhQsXWKyO0BL73oskcAp3d3e8/PLLePnll9HU1IQjR44gNTUV06ZNg5eXF2bMmIGZM2di5MiRNut3UxSFW7duobS0FFFRUW3yie/VqxeCgoIQFBTE2OBWVlaipKQEHh4ejNBzYUu0JUqlEnl5ebyOpgX+EHY3NzcMGzbMZjsTAoEA7u7ucHd3R0hICHPTV1FRgcuXL8Pd3Z35LNhiFU1RFIqLi1FfX4/NmzfDYDDg2LFjnBF2gn1BVu4Em9Pc3Mxk0h8+fBjOzs5ISEhAYmIixowZY7Wtz5a2uVFRUXB1de3Uz9NqtVAoFJDJZKivr4ebmxtzcWcjTa0lCoUChYWFGDx4sEXuAt+gw1Hc3d1tKuxtqYNe0dOT93Sf3sXFpdN10cJeW1uLf/3rX1AqlThx4gTnQozItrz9QMSd0KVotVqcOnWKyaR/4oknMGPGDCQmJnYqk97WiWd6vZ7pyyqVSotjVV29spLJZCgqKsLw4cPh6+vbpb+7K6GFnT7Wx5VZgnudEjs7eU9RFC5fvgyFQoFt27ahoqICp0+fhpeXl41eQeeIjY3FqFGjsHXrVgB3//b69u2LxYsXk4E6DkHEvZ3cvn0bGzZswJkzZ1BdXY2AgAC88sorWLNmjUVPjiTXPRo6k55OsDMajZgxYwZEIhHi4uLa7Pfe1T7x9MVdJpOhtra2wza4HYFuF4SFhUEoFNrs97ANnVPu5eXFuRMYLaEn72nPe4FA0K7Je4qiUFJSArlcjm+++QbXrl1DVlbWI+dE2CQlJQVz587Fzp07MWrUKGzZsgU//vgjSkpKeH2zaW8QcW8nx44dQ0pKCl566SWEhISgqKgI8+fPx6uvvorNmzcDIMl1HYHOpN+/fz8yMjKgVqsxbdo0iEQiPPvssw9cibPtE280GlFbW9tuG9yOQA8JRkREcHZVZw1oIx6uC/u9tJy8VygUMBgMDz1uSVEUrl69iqqqKiQnJ6OoqAhZWVl2IZBfffUVY2ITERGBL7/8ErGxsWyXRWgBEXcrsGnTJmzfvh03b94EAJJc10lMJhPOnz/PrOiVSiWTST958mQmk76srAzp6el4+umnOeGfbjKZoFQqGXc8R0dHRug9PT07JVK3b9/GrVu3EBkZybk+rDXRaDTIzc21eyMeiqLQ2NjItHKam5vRu3dvCIVCZvL+2rVrqKysxPfff4+LFy8iOzub1/MThK6FiLsVWLt2LY4dO4bc3FwAJLnOmpjNZly8eJHJpK+qqsJzzz3H9PxGjhyJvXv3csJ4pCUPssFtr1EKRVG4efMm7ty5g6ioKLi5udm4cvaghV0oFCI0NNRuhb011Go1M5CXlpaGM2fOIDY2FkqlEgUFBcjKykLfvn3ZLpPAI8hRuE5y/fp1bN26ldmSB+6apwQFBVk8j95qq66uJuLeDhwcHBAbG4vY2Fhs3LgReXl52L59O9atWweKomA0GrFv3z5MmzaNUzaiDg4O6N27N3r37s3Y4MpkMly6dAkmk4npyz7MBpdO7KuqqkJMTAyvj0Q1NzdDLBbzUtiBu8cte/Xqhf79+8NkMsFoNCI1NRVyuRxDhgzBf/7zH8ycORMjRozg3WsnsAO3ljss0t7kOgCoqKhAfHw8XnjhBcyfP5+lyh8fHBwcoNPpkJqainXr1iEvL49Zwffv3x9//vOfkZycjJqaGk4l2AkEAnh6emLw4MEYP348oqKi0L17d1y9ehU5OTkoKChAdXU1jEYj8z30oJVMJnsshD03Nxc+Pj68FPaW3Lp1C1qtFgDQrVs3iMVirFmzBkVFRRg7diwGDBgAsVjMcpUEPkC25f8/7U2uq6ysRFxcHEaPHo3k5GSLbVayLW8bLl68iIkTJ2Ljxo1YuHAh8zg9mJSamoq0tDTk5+dj/PjxEIlESEhIgI+PDycFg7bBlclkjCMa3Zetra1FQ0ODTY71cQm1Wg2xWAw/Pz9ee+IDQGlpKW7evImTJ08iJSUF2dnZCA0NZb6u0Whw6tQpjB8/ntdzFYSugYh7B6ioqMCECRMQHR2N77777r5tVZJcZxu0Wi3Onj2LyZMnP/A5dI86NTUV6enpuHjxIsaOHYuEhASIRCIEBARwVkDUajWqq6tRVlYGo9EIT09P+Pn52YUNbkdQq9XIzc1FQEAAZ5MFrcWdO3dw/fp1ZGdnY8+ePcjKysKwYcPYLosT9OnTB6tXr7a4YT937hwmTZqEy5cvo1+/fixWZ78QcW8nFRUViIuLQ79+/bBnzx4LYafDSUhyHTegM+lpoT937hxiYmKYYJu+fftySlDo8/o6nQ5DhgxBXV0d5HI5GhoaOG2D2xHoFLsnn3wSAwYM4NT7YG3Ky8tx9epVnD9/Hjt37sTp06cRHh7OdlmcYdasWXBzc8Pu3bsB3P27jY2NxXPPPYePP/6Y5ersFyLu7SQ5ORnz5s1r9Wst/ylJch23oCgKlZWVTCb9zz//jBEjRjCZ9GwLDJ3dbTKZEBkZaXFeX6vVMkeqWtrg+vr62uWW/eMk7LTp0MWLF7F161acOHECMTExbJfFKTZt2oQ9e/agqKgIAPDf//4XK1aswLVr13g9a2JriLgTHjsoioJCoWAy6bOysjB48GBG6Lv6fDVtxCMQCBAREfFQr/0H2eD6+voy5/+5TFNTE3JzcxEYGIgBAwawXY5NqaqqwuXLl5GXl4fNmzfj2LFjGD16NNtlcY6ff/4ZcXFxUKlUEAgECA0Nxd///ne88cYbbJdm1xBxJzzW0Jn0Bw8eRGpqKk6dOoXg4GAmqtZW8aI0er0eEokEPXr0aLcRj8FgYM5Ot7TB9fX1tUqYibVpbGyEWCxG3759ERwczHY5NkUmk6G4uBjFxcX45JNPkJmZiaeeeortsjhJc3Mz3N3dcfr0aZw6dQo//fQTxGIx57wr7A0i7gRCC1QqFX766SekpaXh2LFjCAgIgEgkwsyZMxEREWHVC45Op4NEIoGzszPCwsI69bONRqNFmAltg+vr6ws3NzfWhZ4W9n79+t3nAcE35HI5CgsLceXKFfz973/HTz/9hLi4OLbL4jRRUVEYP348vvnmGxw5coT8e1kBIu4EwgNobGzEkSNHkJaWhiNHjqB3797Min7kyJGdEmPaP51OPLPmTQMdZkJ7nFvTBrcjNDQ0QCKRPBbCrlAoUFBQgJs3b2LNmjVIS0t76OkOwl0WLlyIHTt2QCQSIT09ne1yeAERdx7z8ccfIzMzE3l5eejevTvq6+vve05ZWRkWLFiArKwsuLi4YO7cufj000+tlrHOF+hM+tTUVBw+fBguLi4WmfTt2U6n3di6wj/dbDZDqVQyfXo6tczX1xeenp423/psaGiAWCxGUFAQ+vfvb9PfxTY1NTUoKChAaWkpVqxYgR9//BF/+tOf2C7LLti5cyfeeecdFBcXIyQkhO1yeAERdx6zfv16eHh4oLy8HN9+++194m4ymRAREQE/Pz9s2rQJVVVVmDNnDubPn49PPvmEnaLtAK1Wi5MnTyItLQ2HDh1Ct27dmEz6p5566qHJdPSkuJ+fHwYNGtSlq2h6voAW+rba4HYUlUoFiUSC4OBg3p9VViqVyMvLQ3l5Od577z3s3bsXIpGI7bLshgkTJiAqKgr//Oc/2S6FNxBxfwxITk7G0qVL7xP3o0ePYvr06aisrGS873fs2IEVK1ZAoVDw0jjF2hgMBmRlZeHAgQM4ePAgTCYTpk+fjsTERMTFxVn8G+bn56Ompgb9+/dHcHAwq31wiqKgUqkYodfr9fD29oavry969+7d6Z2bx0nY6+rqIJVKUVVVhXfffRfJycl4/vnn2S6L85jNZigUCnz77bf4+uuvcenSJV4HI3U1ZBzxMeb8+fMICwuzyI+eMmUKGhoaUFxczGJl9kO3bt0wefJk7Nq1CxUVFdi/fz+cnZ2xaNEiBAUFYf78+Th8+DCOHDmC5557DhUVFZw42y0QCODh4YFBgwZh3LhxGDlyJJydnXHjxg3k5OQgLy8PlZWVMBgM7f7Z9fX1kEgkGDBgAO+Fvb6+HlKpFAqFAu+++y6++eYbzJo1i+2y7IKzZ8/C398f3333HVJTU4mwWxnSWH2Mqa6uthB2wDK9jtA+nnjiCUyYMAETJkzA1q1bce7cOaSmpiIpKQlyuRzDhg2Dm5sb1Go1p86kCwQCuLq6wtXVFSEhIWhqaoJcLkdZWRkuXboELy8vZiDvUbs5tNiFhIQgMDCwi14BO6hUKkilUiiVSrzzzjvYtm0bZs+ezfqNm70QFxcHs9nMdhm8hazc7YyOpNcRuh5HR0eMHz8ekydPhlqtxtq1azF16lSsW7cO/fv3x8svv4z9+/ejsbGR7VLvw8XFBcHBwRg9ejTGjh0LLy8vVFZW4uzZs8jNzcWdO3eYZLOW1NXVQSKRYODAgbwXdvoEQF1dHRYvXozPP/8cc+bMIcJO4Axk5W5nvPfee3jttdce+py2GoT4+fnh999/t3hMJpMxXyN0jtTUVMyZMwf/+c9/8OKLLwIAk0l/4MABfPrpp3j77bcxadIkiEQi/OlPf+JUJj0AODs7o3///ujfvz9jgyuTyXDlyhULG1ytVgupVIpBgwahT58+bJdtUxobGyGRSNDY2IhFixbh008/xZtvvsmp941AIAN1jwGPGqirqqqCj48PAGDXrl344IMPIJfL0aNHDxaq5Q/ffPMN/Pz8MGPGjFa/TlEUioqKcODAAaSlpeHq1auYMGECRCIRpk+fDi8vL84Kxr02uBRFQSgUYuDAgZxqOVgb2j63sbERb7/9NtavX48lS5Zw9n0iPL4QcecxZWVlUCqVOHToEDZt2oSff/4ZABASEgIXFxfmKFxAQAA+++wzVFdX49VXX8Wbb75JjsJ1MRRF4cqVK0wmfUFBAcaPH4/ExETMmDGDs5n0tbW1yMvLg7+/P/R6vV3Y4HYUOqJWrVbjrbfewooVK7B8+XLevD4CvyDizmNee+017Nmz577Hs7KyGHvH0tJSLFiwANnZ2ejVqxfmzp2Lf/zjH8TEhkXoTPoDBw4gPT0dubm5GDt2LEQiERISEjiTSV9bW4v8/HwMHjwYAQEBAFq3wfX19YWPjw8nbHA7SnNzMyPsf/3rX7FkyRKsXbvWbl8Pgf8QcScQOAxFUSgrK0NaWhrS0tJw/vx5jBw5EiKRCCKRiLVMetqNbciQIfD392/1OQ+ywfX19YWHh4fdCKNGo0Fubi40Gg3efvttvPnmm9iwYQPr9d++fRsbNmzAmTNnUF1djYCAALzyyitYs2aNxamGlvHTQqEQSUlJWL58OYuVE7oCIu4Egp3QMpM+NTUVv/zyC8LDw5mo2q4yxqGFfejQoW0evGTbBrejaLVaRtgXLlyIl19+Gf/4xz84Ue+xY8eQkpKCl156CSEhISgqKsL8+fPx6quvYvPmzQDuTvUPGjQIkyZNwqpVq1BYWIjXX38dW7ZswVtvvcXyKyDYEiLuBIIdQlEU5HI5k0mfnZ2NIUOGMEIfGhpqE6FXKBQoLCzEsGHD7vNIaCtmsxn19fX32eD6+vrCy8vL6ja4HUWr1UIsFkOj0WDRokX485//jC+++IITwv4gNm3ahO3bt+PmzZsAgO3bt2PNmjWorq5mVvMrV65ERkYGOTLLc4i4Ewh2DkVRUCqVTCb96dOnMWDAACbBzlqpc3SU6fDhwzss7PfyMBtcb29v1oRep9Mxwp6UlISpU6di27ZtnBZ2AFi7di2OHTuG3NxcAMCcOXPQ0NCAjIwM5jlZWVmYOHEilEolPD09WaqUYGu4/UklPFZs27YN/fv3R8+ePREbG3vfGXxC6wgEAvTu3Ruvv/46MjMzUV1djZUrV6KkpARxcXGIjIzE+vXrIZVKO+wIRgv7vXbF1qi9pQ1uTEwMY4ObnZ2N/Px8VFVVdcgGt6Po9XqIxWLodDq8++67mDRpkl0I+/Xr17F161b89a9/ZR4jLpSPL9z+tBIeG1JSUrBs2TKsX78eEokE4eHhmDJlCuRyOdul2R0eHh549dVXkZ6eDplMhg0bNqC0tBTx8fEICwvDqlWrcOHChTYLvUwmY4Sd9kOwBQKBAG5ubggJCcHYsWMRGxsLV1dXlJaWIicnBxKJBBUVFdDr9TarwWAwMMK+bNkyjB07Fjt37uxSYe+IC2VFRQXi4+PxwgsvYP78+V1WK4G7kG15AieIjY3FyJEj8dVXXwG425cNDAxEUlISVq5cyXJ1/KC5uRnHjh1DamoqMjMz4erqioSEBIhEogdm0stkMhQVFWHEiBEQCoUsVH2X5uZmZuu+oaEBnp6e8PHxgVAoRM+ePa3yO2hh12q1eP/99xEeHo7//e9/XX4sVKFQoLa29qHPCQ4OZnrolZWViIuLw+jRo5GcnGxxI0K25R9fiLgTWEev18PZ2RkHDhxAYmIi8/jcuXNRX1+PgwcPslccT6Ez6VNTU3Ho0CH06NGDyaQfN24cunXrhn//+9+4cOECPvnkE1aF/V5oG1y5XI76+nq4ubkxZ+mdnJw69DONRiMkEgk0Gg1WrFiBgQMH4ocffkC3bt2sXL11qaiowIQJExAdHY3vvvvuvhs0eqBOJpMxr2X16tVIS0sjA3U8h4g7gXUqKyvx5JNP4ty5cxgzZgzz+PLly5GTk4MLFy6wWB3/0ev1Fpn0FEVh4MCBEIvF2L59O2bPns12iQ9Ep9NBoVAwNrguLi6M0LfVBtdoNEIqlUKj0WD16tXo06cPDhw48MgEPLapqKhAXFwc+vXrhz179lgIO31EUaVSITQ0FJMnT8aKFStQVFSE119/HV988QU5CsdziLgTWIeIO3cwGo348MMPsXnzZri6uoKiKEybNg2JiYmYOHGi1bbAbYHBYIBCoYBMJoNSqYSTkxMj9A+ywTWZTJBKpWhubsa6devg5eWFjIwMTr9OmuTkZMybN6/Vr7W8rLc0sfH29kZSUhJWrFjRVWUSWIKIO4F1yLY8d9izZw8WLVqEjIwMTJgwAb/++itSU1ORnp4OlUqF+Ph4JCYm4rnnnoOzszPb5T6Qttjgmkwm5OXlQa1WY8OGDejZsycOHz7c4a19AoFLEHEncILY2FiMGjUKW7duBXB3oK5v375YvHgxGajrIsRiMeLi4nDw4EFMnDjR4mtmsxkXLlxghF4mk2Hy5MkQiUSIj4+Hq6srS1U/mtZscDMyMjBkyBCEhIRg48aNEAgEyMzMhIuLC9vlEghWgYg7gROkpKRg7ty52LlzJ0aNGoUtW7bgxx9/RElJiVXPVRMeDEVRuHXrFoKDgx/6PLPZDKlUykTVlpWVcTqTviVmsxkVFRVYsmQJzp07B41Gg969e2PHjh2YNm0a5wfoCIS2QsSdwBm++uorbNq0CdXV1YiIiMCXX36J2NhYtssiPAQ6k37//v1IT0/H1atXMXHiRIhEIkybNo1zmfRmsxmFhYVoaGjA5s2bUVZWhqeffhqZmZnQ6XRISEjAiy++iPj4eLZLJRA6BRF3AoFgFSiKQklJCZNJX1RUZJFJLxQKWRV6iqJQWFgIlUqFrVu3orKyEqdOnYKXl5dF20GtVmP79u2s1UkgWAMi7gQCwepQFIUbN24wQi+RSDBmzBgkJiYiISEB/v7+XSr0FEWhuLgYdXV12LFjB27cuIEzZ87A29u7y2ogELoSIu4EAsGmUBSF0tJSJpP+t99+w6hRo5hM+sDAQJsKPUVRuHz5MmpqarB7924UFhYiKyuLzHIQeA0RdwKB0GXQmfRpaWlITU3Fr7/+ioiICEborZ1JT7cKFAoF/ve//+HixYvIycmBv7+/1X4HgcBFSHAMgfAIzp49ixkzZiAgIAACgcDCpxu4KyDr1q2Dv78/nJycMGnSJFy7do2dYjmOQCDAk08+iaSkJGRlZeHOnTt44403kJOTg+joaIwbNw4bN27ElStX0Nl1B0VRuHr1KhQKBX744QdcuHABp0+fJsJOeCwg4k4gPAK1Wo3w8HBs27at1a9/9tln+PLLL7Fjxw5cuHABvXr1wpQpU6DVaru4UvtCIBDAz88Pb7/9Nk6cOIGqqiokJSUhNzcXo0ePxqhRo/DRRx+huLi43VG1FEXh2rVrqK6uRmpqKrKzs3Hq1CkEBgba6NUQCNyCbMsTCO1AIBAgPT2dcdKjKAoBAQF477338P777wO46+ft6+uL5ORkTvuycxWKoqBSqXDo0CGkpaXhxIkT6NOnD0QiEWbOnIkRI0Y8MoL1+vXrKC8vR2ZmJg4dOoSsrCyEhIR00SsgENiHrNwJhE5w69YtVFdXY9KkScxj7u7uiI2Nxfnz51mszH4RCATw8PDAnDlzkJGRAZlMhv/7v//D7du3MXnyZISFhWH16tX4/fffW13RFxcXo6KiAidPnkRaWhpOnTpFhJ3w2NG1QcUEAs+orq4GgPsmr319fZmvETqHq6srZs+ejdmzZ0OtVjOZ9CKRCO7u7kwm/ejRo7F+/XqcPHkS8fHx2Lt3L86cOYPQ0FC2XwKB0OUQcScQCHZDr169MGvWLMyaNQsajYbJpH/xxRdhMBig0+kwadIk7N69G6dPn8awYcPYLplAYAWyLU8gdAI6N1smk1k8LpPJmK8RbIOTkxMSEhKwZ88erF+/HgAwYcIEnDhxAqmpqQgPD2e5QgKBPYi4E6zKvn374OTkhKqqKuaxefPmYcSIEVCpVCxWZhuCgoLg5+eH06dPM481NDTgwoULFtn0BNuxa9curFu3DidPnsTx48fR3NyMZ555hu2yCARWIeJOsCqzZ8/GoEGD8MknnwAA1q9fj1OnTuHo0aNwd3dnubqO0dTUhLy8POTl5QG4O0SXl5eHsrIyCAQCLF26FB999BEOHTqEwsJCzJkzBwEBARbZ9ATbUF9fj08++QSZmZkYPXo0AKB79+4sV0UgsA85CkewOocPH8bzzz+PDz/8EP/85z/x888/23XvMzs7GxMmTLjv8blz5yI5ORkURWH9+vXYtWsX6uvr8dRTT+Hrr7/GoEGDWKj28UOn06FHjx5sl0EgcAoi7gSbEBUVheLiYpw4cYJskRIIBEIXQ7blCVbn2LFjKCkpgclkIuEcBAKBwAJk5U6wKhKJBHFxcdi5cyeSk5Ph5uaG/fv3s10WgUAgPFaQc+4Eq3H79m1MmzYNq1evxksvvYTg4GCMGTMGEokEUVFRbJdHIBAIjw1kW55gFZRKJeLj4yESibBy5UoAQGxsLKZOnYrVq1ezXB2BYHt0Oh0iIiIgEAiYkxU0BQUFGD9+PHr27InAwEB89tln7BRJeGwg4k6wCl5eXigpKcGOHTssHs/MzMSxY8dYqurx5NNPP8XIkSPh6uoKHx8fJCYm4sqVKxbP0Wq1WLRoEXr37g0XFxfMmjXrPiMeQvtYvnw5AgIC7nu8oaEBkydPRr9+/SAWi7Fp0yb87W9/w65du1iokvC4QMSdQOAZOTk5WLRoEX777TecPHkSBoMBkydPhlqtZp7z7rvv4qeffsL+/fuRk5ODyspK/PnPf2axavvm6NGjOHHiBDZv3nzf177//nvo9Xr85z//wbBhwzB79my88847+Pzzz1molPC4QAbqCASeo1Ao4OPjg5ycHDz99NNQqVQQCoXYu3cvnn/+eQBASUkJhgwZgvPnzzNmMIS2IZPJEB0djYyMDHh7eyMoKAhSqRQREREAgDlz5qChoQEZGRnM92RlZWHixIlQKpXw9PRkp3ACryErdwKB59C2v15eXgAAsVgMg8FgEVM7ePBg9O3bl8TUthOKovDaa6/h7bffRkxMTKvPqa6ubjU1kP4agWALiLgTCDzGbDZj6dKlGDduHIYPHw7grqB0794dHh4eFs8lMbV/sHLlSggEgof+V1JSgq1bt6KxsRGrVq1iu2QCwQJyFI5A4DGLFi1CUVERfvnlF7ZLsSvee+89vPbaaw99TnBwMM6cOYPz58/fZ38bExODl19+GXv27IGfn1+rqYEASHIgwWYQcScQeMrixYtx+PBhnD17Fn369GEe9/Pzg16vR319vcXqncTU/oFQKIRQKHzk87788kt89NFHzP9XVlZiypQpSElJQWxsLABgzJgxWLNmDQwGA7p16wYAOHnyJEJDQ0m/nWAzyLY8gcAzKIrC4sWLkZ6ejjNnziAoKMji69HR0ejWrZtFTO2VK1dQVlZGYmrbSd++fTF8+HDmPzosaMCAAcwN1V/+8hd0794db7zxBoqLi5GSkoJ//etfWLZsGZulE3gOWbkTCDxj0aJF2Lt3Lw4ePAhXV1emj+7u7g4nJye4u7vjjTfewLJly+Dl5QU3NzckJSVhzJgxZFLeBri7u+PEiRNYtGgRoqOj4e3tjXXr1uGtt95iuzQCjyFH4QgEniEQCFp9fPfu3UwfWavV4r333sO+ffug0+kwZcoUfP3112RbnkDgCUTcCQQCgUDgGaTnTiAQCAQCzyDiTiAQCAQCzyDiTiAQCAQCzyDiTiAQCAQCzyDiTiAQWGf79u0YMWIE3Nzc4ObmhjFjxuDo0aPM10lELYHQPsi0PIFAYJ2ffvoJjo6OGDhwICiKwp49e7Bp0yZIpVIMGzYMCxYsQGZmJpKTk+Hu7o7FixfDwcEBv/76K9ulEwichIg7gUDgJF5eXti0aROef/55ElFLILQTsi1PIBA4hclkwg8//AC1Wo0xY8aQiFoCoQMQ+1kCgcAJCgsLMWbMGGi1Wri4uCA9PR1Dhw5FXl4eiaglENoJEXcCgcAJQkNDkZeXB5VKhQMHDmDu3LnIyclhuywCwS4h4k4gEDhB9+7dERISAuBuct3Fixfxr3/9Cy+++CKJqCUQ2gnpuRMIBE5iNpuh0+lIRC2B0AHIyp1AILDOqlWrMHXqVPTt2xeNjY3Yu3cvsrOzcfz4cRJRSyB0ACLuBAKBdeRyOebMmYOqqiq4u7tjxIgROH78OJ577jkAwBdffAEHBwfMmjXLIqKWQCC0DjnnTiAQCAQCzyA9dwKBQCAQeAYRdwKBQCAQeAYRdwKBQCAQeAYRdwKBQCAQeAYRdwKBQCAQeAYRdwKBQCAQeAYRdwKBQCAQeAYRdwKBQCAQeAYRdwKBQCAQeAYRdwKBQCAQeAYRdwKBQCAQeAYRdwKBQCAQeMb/A3IOtEBnBuplAAAAAElFTkSuQmCC"/>
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<h2 id="Sparse-Identification-of-Nonlinear-Dynamics">Sparse Identification of Nonlinear Dynamics<a class="anchor-link" href="#Sparse-Identification-of-Nonlinear-Dynamics">¶</a></h2><p>The core idea of SINDy is to model $\boldsymbol f$ as a linear combination of functions in a library $\Theta$ of <strong>candidate</strong> functions.
In other words, assume that we have $r$ functions which might be suitable to describe the system's dynamics (<em>e.g.</em>, $x,\, y,\, x^2,\, xz,\, \dots,\,\sin(x)$, $\dots$).
For each component of $\boldsymbol{f}$ at a given point $\boldsymbol{x}$, we want to write
$$
\dot{x}_i = f_i(\boldsymbol{x}) = \sum_{k}\Theta(\boldsymbol{x})_{k}\xi_{k,i},
$$
with $\boldsymbol{\xi}_i\in\mathbb{R}^r$ a vector of <strong>coefficients</strong> telling us which terms are active in the expression of $f_i$.</p>
<p>Since we are in a supervised setting, we assume that we have at our disposal the snapshot matrix $\boldsymbol{X}$ and a matrix $\dot{\boldsymbol{X}}$ containing time <strong>derivatives</strong> at the corresponding time instances.
Then, we can just impose that the previous relation holds on the data at our disposal.
That is, our optimization problem will read as follows:
$$
\min_{\boldsymbol{\Xi}}\|\dot{\boldsymbol{X}}-\Theta(\boldsymbol{X})\boldsymbol{\Xi}\|_2^2.
$$</p>
<p>Notice, however, that the solution to the previous equation might not be <strong>sparse</strong>, as there might be many non-zero terms in it.
In practice, many physical systems are described by a parsimonious and <strong>interpretable</strong> set of equations.
Thus, we also impose a $L^1$ <strong>penalization</strong> on the model weights, encouraging them to be small in magnitude and trying to enforce sparsity.
The final loss is then expressed as</p>
<p>$$
\min_{\boldsymbol{\Xi}}\bigl(\|\dot{\boldsymbol{X}}-\Theta(\boldsymbol{X})\boldsymbol{\Xi}\|_2^2 + \lambda\|\boldsymbol{\Xi}\|_1\bigr),
$$
with $\lambda\in\mathbb{R}^+$ a hyperparameter.</p>
<p>Let us begin by computing the time derivatives of the data.
Of course, usually we do not have access to the exact time derivatives of the system, meaning that $\dot{\boldsymbol{X}}$ needs to be <strong>approximated</strong>.
Here we do it using a simple Finite Difference (FD) scheme, but <a href="https://arxiv.org/abs/2505.16058">more sophisticated ideas</a> could be considered.</p>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [3]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">dXdt</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">gradient</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">edge_order</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
<span class="n">X_torch</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span>
<span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">dim</span><span class="p">)</span>
<span class="p">)</span> <span class="c1"># X_torch has shape (B, dim)</span>
<span class="n">dXdt_torch</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">dXdt</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">dim</span><span class="p">))</span>
</pre></div>
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<p>We create two <code>LabelTensor</code> objects to keep everything as readable as possible.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">X_torch</span> <span class="o">=</span> <span class="n">LabelTensor</span><span class="p">(</span><span class="n">X_torch</span><span class="p">,</span> <span class="p">[</span><span class="s2">"x"</span><span class="p">,</span> <span class="s2">"y"</span><span class="p">,</span> <span class="s2">"z"</span><span class="p">])</span>
<span class="n">dXdt_torch</span> <span class="o">=</span> <span class="n">LabelTensor</span><span class="p">(</span><span class="n">dXdt_torch</span><span class="p">,</span> <span class="p">[</span><span class="s2">"dxdt"</span><span class="p">,</span> <span class="s2">"dydt"</span><span class="p">,</span> <span class="s2">"dzdt"</span><span class="p">])</span>
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<p>Now we define the <strong>library of candidate functions</strong>.
In our case, it will consist of polynomials of degree at most $2$ in the state variables.
While the <code>SINDy</code> class in <strong>PINA</strong> expects a <strong>list</strong> of callables, here we define also dictionary, as its keys will be used to print the retrieved equations, enhancing the model interpretability and allowing it to be compared to the original Lorenz system.
Notice how readable the code is as a result of the use of the <code>LabelTensor</code> class!</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">function_dict</span> <span class="o">=</span> <span class="p">{</span>
<span class="s2">"1"</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">u</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">u</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="mi">1</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="n">u</span><span class="o">.</span><span class="n">device</span><span class="p">),</span> <span class="c1"># 1</span>
<span class="s2">"x"</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">u</span><span class="p">:</span> <span class="n">u</span><span class="p">[</span><span class="s2">"x"</span><span class="p">],</span> <span class="c1"># x</span>
<span class="s2">"y"</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">u</span><span class="p">:</span> <span class="n">u</span><span class="p">[</span><span class="s2">"y"</span><span class="p">],</span> <span class="c1"># y</span>
<span class="s2">"z"</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">u</span><span class="p">:</span> <span class="n">u</span><span class="p">[</span><span class="s2">"z"</span><span class="p">],</span> <span class="c1"># z</span>
<span class="s2">"x^2"</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">u</span><span class="p">:</span> <span class="n">u</span><span class="p">[</span><span class="s2">"x"</span><span class="p">]</span><span class="o">.</span><span class="n">pow</span><span class="p">(</span><span class="mi">2</span><span class="p">),</span> <span class="c1"># x^2</span>
<span class="s2">"y^2"</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">u</span><span class="p">:</span> <span class="n">u</span><span class="p">[</span><span class="s2">"y"</span><span class="p">]</span><span class="o">.</span><span class="n">pow</span><span class="p">(</span><span class="mi">2</span><span class="p">),</span> <span class="c1"># y^2</span>
<span class="s2">"z^2"</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">u</span><span class="p">:</span> <span class="n">u</span><span class="p">[</span><span class="s2">"z"</span><span class="p">]</span><span class="o">.</span><span class="n">pow</span><span class="p">(</span><span class="mi">2</span><span class="p">),</span> <span class="c1"># z^2</span>
<span class="s2">"xy"</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">u</span><span class="p">:</span> <span class="n">u</span><span class="p">[</span><span class="s2">"x"</span><span class="p">]</span> <span class="o">*</span> <span class="n">u</span><span class="p">[</span><span class="s2">"y"</span><span class="p">],</span> <span class="c1"># xy</span>
<span class="s2">"xz"</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">u</span><span class="p">:</span> <span class="n">u</span><span class="p">[</span><span class="s2">"x"</span><span class="p">]</span> <span class="o">*</span> <span class="n">u</span><span class="p">[</span><span class="s2">"z"</span><span class="p">],</span> <span class="c1"># xz</span>
<span class="s2">"yz"</span><span class="p">:</span> <span class="k">lambda</span> <span class="n">u</span><span class="p">:</span> <span class="n">u</span><span class="p">[</span><span class="s2">"y"</span><span class="p">]</span> <span class="o">*</span> <span class="n">u</span><span class="p">[</span><span class="s2">"z"</span><span class="p">],</span> <span class="c1"># yz</span>
<span class="p">}</span>
<span class="n">function_library</span> <span class="o">=</span> <span class="p">[</span>
<span class="n">_function</span> <span class="k">for</span> <span class="n">_function</span> <span class="ow">in</span> <span class="n">function_dict</span><span class="o">.</span><span class="n">values</span><span class="p">()</span>
<span class="p">]</span> <span class="c1"># input of the model constructor</span>
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<h2 id="Training-with-PINA">Training with PINA<a class="anchor-link" href="#Training-with-PINA">¶</a></h2><p>We are now ready to train our model! We can use <strong>PINA</strong> to train the model, following the workflow from previous tutorials.
First, we need to define the problem. In this case, we will use the <a href="https://mathlab.github.io/PINA/_rst/problem/zoo/supervised_problem.html#module-pina.problem.zoo.supervised_problem"><code>SupervisedProblem</code></a>, which expects:</p>
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<li><strong>Input</strong>: the state variables tensor $\boldsymbol{X}$ containing all the collected snapshots.</li>
<li><strong>Output</strong>: the corresponding time derivatives $\dot{\boldsymbol{X}}$.</li>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">_lambda</span> <span class="o">=</span> <span class="mf">1e-3</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">SINDy</span><span class="p">(</span><span class="n">function_library</span><span class="p">,</span> <span class="n">dim</span><span class="p">)</span>
<span class="n">problem</span> <span class="o">=</span> <span class="n">SupervisedProblem</span><span class="p">(</span><span class="n">X_torch</span><span class="p">,</span> <span class="n">dXdt_torch</span><span class="p">)</span>
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<p>Finally, we will use the <code>SupervisedSolver</code> to perform the training as we're dealing with a supervised problem.</p>
<p>Recall that we should use $L^1$-regularization on the model's weights to ensure sparsity. For the ease of implementation, we adopt $L^2$ regularization, which is less common in SINDy literature but will suffice in our case.
Additionally, more refined strategies could be used, for instance pruning coefficients below a certain <strong>threshold</strong> at every fixed number of epochs, but here we avoid further complications.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">solver</span> <span class="o">=</span> <span class="n">SupervisedSolver</span><span class="p">(</span>
<span class="n">problem</span><span class="p">,</span>
<span class="n">model</span><span class="o">=</span><span class="n">model</span><span class="p">,</span>
<span class="n">optimizer</span><span class="o">=</span><span class="n">TorchOptimizer</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">,</span> <span class="n">lr</span><span class="o">=</span><span class="mf">1e-3</span><span class="p">,</span> <span class="n">weight_decay</span><span class="o">=</span><span class="n">_lambda</span><span class="p">),</span>
<span class="n">use_lt</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
<span class="p">)</span>
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<p>Training is performed as usual using the <strong><code>Trainer</code></strong> API.</p>
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<div class="highlight hl-ipython3"><pre><span></span><span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span>
<span class="n">solver</span><span class="p">,</span>
<span class="n">accelerator</span><span class="o">=</span><span class="s2">"cpu"</span><span class="p">,</span>
<span class="n">max_epochs</span><span class="o">=</span><span class="mi">150</span><span class="p">,</span>
<span class="n">train_size</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span>
<span class="n">val_size</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span>
<span class="n">test_size</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span>
<span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
<span class="n">batch_size</span><span class="o">=</span><span class="mi">512</span><span class="p">,</span>
<span class="n">enable_model_summary</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">trainer</span><span class="o">.</span><span class="n">train</span><span class="p">()</span>
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<pre>💡 Tip: For seamless cloud uploads and versioning, try installing [litmodels](https://pypi.org/project/litmodels/) to enable LitModelCheckpoint, which syncs automatically with the Lightning model registry.
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<pre>GPU available: False, used: False
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<pre>TPU available: False, using: 0 TPU cores
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<pre>HPU available: False, using: 0 HPUs
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<pre>`Trainer.fit` stopped: `max_epochs=150` reached.
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<p>Now we'll print the identified equations and compare them with the original ones.</p>
<p>Before going on, we underline that after training there might be many coefficients that are small, yet still non-zero.
It is common for SINDy practitioners to interpret these coefficients as noise in the model and prune them.
This is typically done by fixing a threshold $\tau\in\mathbb{R}^+$ and setting to $0$ all those $\xi_{i,j}$ such that $|\xi_{i,j}|&lt;\tau$.</p>
<p>In the following cell, we also define a function to print the identified model.</p>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [9]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="k">def</span><span class="w"> </span><span class="nf">print_coefficients</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">function_names</span><span class="p">,</span> <span class="n">tau</span><span class="p">,</span> <span class="nb">vars</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">():</span>
<span class="n">Xi</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">coefficients</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
<span class="n">library_dim</span><span class="p">,</span> <span class="n">dim</span> <span class="o">=</span> <span class="n">Xi</span><span class="o">.</span><span class="n">shape</span>
<span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">dim</span><span class="p">):</span>
<span class="n">terms</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">library_dim</span><span class="p">):</span>
<span class="n">coefficient</span> <span class="o">=</span> <span class="n">Xi</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="n">j</span><span class="p">]</span>
<span class="k">if</span> <span class="p">(</span>
<span class="nb">abs</span><span class="p">(</span><span class="n">coefficient</span><span class="p">)</span> <span class="o">&gt;</span> <span class="n">tau</span>
<span class="p">):</span> <span class="c1"># do not print coefficients that are going to be pruned</span>
<span class="n">function_name</span> <span class="o">=</span> <span class="n">function_names</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
<span class="n">terms</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">coefficient</span><span class="si">:</span><span class="s2">+.2f</span><span class="si">}</span><span class="s2"> * </span><span class="si">{</span><span class="n">function_name</span><span class="si">}</span><span class="s2"> "</span><span class="p">)</span>
<span class="n">equation</span> <span class="o">=</span> <span class="s2">" "</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">terms</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">equation</span><span class="p">:</span>
<span class="n">equation</span> <span class="o">=</span> <span class="s2">"0"</span>
<span class="k">if</span> <span class="nb">vars</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"d</span><span class="si">{</span><span class="nb">vars</span><span class="p">[</span><span class="n">j</span><span class="p">]</span><span class="si">}</span><span class="s2">/dt = </span><span class="si">{</span><span class="n">equation</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"d(State_</span><span class="si">{</span><span class="n">j</span><span class="o">+</span><span class="mi">1</span><span class="si">}</span><span class="s2">)/dt = </span><span class="si">{</span><span class="n">equation</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<span class="n">tau</span> <span class="o">=</span> <span class="mf">1e-1</span>
<span class="n">print_coefficients</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="nb">list</span><span class="p">(</span><span class="n">function_dict</span><span class="o">.</span><span class="n">keys</span><span class="p">()),</span> <span class="n">tau</span><span class="p">,</span> <span class="nb">vars</span><span class="o">=</span><span class="p">[</span><span class="s2">"x"</span><span class="p">,</span> <span class="s2">"y"</span><span class="p">,</span> <span class="s2">"z"</span><span class="p">])</span>
<span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">():</span> <span class="c1"># prune coefficients</span>
<span class="n">mask</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">coefficients</span><span class="p">)</span> <span class="o">&gt;=</span> <span class="n">tau</span>
<span class="n">model</span><span class="o">.</span><span class="n">coefficients</span><span class="o">.</span><span class="n">data</span> <span class="o">*=</span> <span class="n">mask</span>
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<pre>dx/dt = -9.99 * x +10.00 * y
dy/dt = +27.99 * x -0.99 * y -1.00 * xz
dz/dt = -2.67 * z +1.00 * xy
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<p>Good! While there are small errors on some of the coefficients, the active terms in the library have been correctly identified (recall that the original system reads as follows):
$$
\begin{cases}
\dot{x}=-10x+10y\\
\dot{y}=28x - y-xz\\
\dot{z}=-\frac{8}{3} z+xy.
\end{cases}
$$</p>
<p>That's a good result, especially considering that we did not perform tuning on the weight decay hyperparameter $\lambda$ and did not really care much about other optimization parameters.</p>
<p>Let's plot a few trajectories!</p>
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<div class="jp-InputPrompt jp-InputArea-prompt">In [10]:</div>
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<div class="highlight hl-ipython3"><pre><span></span><span class="k">def</span><span class="w"> </span><span class="nf">SINDy_equations</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">t</span><span class="p">):</span> <span class="c1"># we need a numpy array for odeint</span>
<span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">():</span>
<span class="n">x_torch</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span><span class="o">.</span><span class="n">unsqueeze</span><span class="p">(</span>
<span class="mi">0</span>
<span class="p">)</span> <span class="c1"># shape (1, dim)</span>
<span class="n">x_torch</span> <span class="o">=</span> <span class="n">LabelTensor</span><span class="p">(</span><span class="n">x_torch</span><span class="p">,</span> <span class="p">[</span><span class="s2">"x"</span><span class="p">,</span> <span class="s2">"y"</span><span class="p">,</span> <span class="s2">"z"</span><span class="p">])</span>
<span class="n">dx</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="n">x_torch</span><span class="p">)</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
<span class="k">return</span> <span class="n">dx</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
<span class="n">n_ic_s_test</span> <span class="o">=</span> <span class="mi">50</span>
<span class="n">x0s</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">rand</span><span class="p">(</span><span class="n">n_ic_s_test</span><span class="p">,</span> <span class="n">dim</span><span class="p">)</span> <span class="o">-</span> <span class="mf">0.5</span><span class="p">)</span> <span class="o">*</span> <span class="mf">30.0</span>
<span class="n">X_sim</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">n_ic_s_test</span><span class="p">,</span> <span class="n">T</span><span class="p">,</span> <span class="n">dim</span><span class="p">))</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_ic_s_test</span><span class="p">):</span>
<span class="n">X_sim</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">odeint</span><span class="p">(</span><span class="n">SINDy_equations</span><span class="p">,</span> <span class="n">x0s</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">t</span><span class="p">)</span>
<span class="n">plot_n_conditions</span><span class="p">(</span><span class="n">X_sim</span><span class="p">,</span> <span class="n">n_ic_s_test</span><span class="p">)</span>
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<p>Great! We can see that the qualitative behavior of the system is really close to the real one.</p>
<h2 id="What's-next?">What's next?<a class="anchor-link" href="#What's-next?">¶</a></h2><p>Congratulations on completing the introductory tutorial on <strong>Data-driven System Identification with SINDy</strong>! Now that you have a solid foundation, here are a few directions to explore:</p>
<ol>
<li><p><strong>Experiment with Dimensionality Reduction techniques</strong> — Try to combine SINDy with different reductions techniques such as POD or autoencoders - or both of them, as done <a href="https://www.sciencedirect.com/science/article/abs/pii/S0045793025003019">here</a>.</p>
</li>
<li><p><strong>Study Parameterized Systems</strong> — Write your own SINDy model for parameterized problems.</p>
</li>
<li><p><strong>...and many more!</strong> — The possibilities are vast! Continue experimenting with advanced configurations, solvers, and features in PINA.</p>
</li>
</ol>
<p>For more resources and tutorials, check out the <a href="https://mathlab.github.io/PINA/">PINA Documentation</a>.</p>
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