From 276442d1d6a5d8eeb9a855dc4feafc8b7508fe45 Mon Sep 17 00:00:00 2001 From: Joe Schoonover Date: Tue, 27 Oct 2026 15:52:17 -0400 Subject: [PATCH 1/3] Add example of limiting particle timestep by local cfl in schism tutorial --- .../user_guide/examples/tutorial_schism.ipynb | 4306 ++++++++++++++++- 1 file changed, 4271 insertions(+), 35 deletions(-) diff --git a/docs/user_guide/examples/tutorial_schism.ipynb b/docs/user_guide/examples/tutorial_schism.ipynb index 406938c96..3226fc3f8 100644 --- a/docs/user_guide/examples/tutorial_schism.ipynb +++ b/docs/user_guide/examples/tutorial_schism.ipynb @@ -37,10 +37,1186 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "2", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " const force = true;\n", + " const version = '3.8.2'.replace('rc', '-rc.').replace('.dev', '-dev.');\n", + " const reloading = false;\n", + " const Bokeh = root.Bokeh;\n", + " const BK_RE = /^https:\\/\\/cdn\\.bokeh\\.org\\/bokeh\\/(release|dev)\\/bokeh-/;\n", + " const PN_RE = /^https:\\/\\/cdn\\.holoviz\\.org\\/panel\\/[^/]+\\/dist\\/panel/i;\n", + "\n", + " // Set a timeout for this load but only if we are not already initializing\n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", + " }\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks;\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, js_modules, js_exports, Bokeh, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + " if (js_modules == null) js_modules = [];\n", + " if (js_exports == null) js_exports = {};\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + "\n", + " if (root._bokeh_is_loading > 0) {\n", + " // Don't load bokeh if it is still initializing\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n", + " // There is nothing to load\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + " 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ensure no trailing comma for IE\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " if ((root.Bokeh !== undefined) || (force === true)) {\n", + " for (let i = 0; i < inline_js.length; i++) {\n", + " try {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " } catch(e) {\n", + " if (!reloading) {\n", + " throw e;\n", + " }\n", + " }\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " }\n", + " root._bokeh_is_initializing = false;\n", + " }\n", + "\n", + " function load_or_wait() {\n", + " // Implement a backoff loop that tries to ensure we do not load multiple\n", + " // versions of Bokeh and its dependencies at the same time.\n", + " // In recent versions we use the root._bokeh_is_initializing flag\n", + " // to determine whether there is an ongoing attempt to initialize\n", + " // bokeh, however for backward compatibility we also try to ensure\n", + " // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n", + " // before older versions are fully initialized.\n", + " if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n", + " // If the timeout and bokeh was not successfully loaded we reset\n", + " // everything and try loading again\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_is_initializing = false;\n", + " root._bokeh_onload_callbacks = undefined;\n", + " root._bokeh_is_loading = 0;\n", + " console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n", + " load_or_wait();\n", + " } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n", + " setTimeout(load_or_wait, 100);\n", + " } else {\n", + " root._bokeh_is_initializing = true;\n", + " 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dependencies at the same time.\n // In recent versions we use the root._bokeh_is_initializing flag\n // to determine whether there is an ongoing attempt to initialize\n // bokeh, however for backward compatibility we also try to ensure\n // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n // before older versions are fully initialized.\n if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n // If the timeout and bokeh was not successfully loaded we reset\n // everything and try loading again\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_is_initializing = false;\n root._bokeh_onload_callbacks = undefined;\n root._bokeh_is_loading = 0;\n console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n load_or_wait();\n } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } 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scripts[i]\n", + " if (script.src != null) {\n", + " existing_scripts.push(script.src)\n", + " }\n", + " }\n", + " for (let i = 0; i < js_urls.length; i++) {\n", + " const url = js_urls[i];\n", + " const escaped = encodeURI(url)\n", + " const shouldSkip = skip.includes(escaped) || existing_scripts.includes(escaped)\n", + " const isBokehOrPanel = BK_RE.test(escaped) || PN_RE.test(escaped)\n", + " const missingOrBroken = Bokeh == null || Bokeh.Panel == null || (Bokeh.version != version && !Bokeh.versions?.has(version)) || Bokeh.versions?.get(version)?.Panel == null;\n", + " if (shouldSkip && !(isBokehOrPanel && missingOrBroken)) {\n", + " if (!window.requirejs) {\n", + " on_load();\n", + " }\n", + " continue;\n", + " }\n", + " const element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " for (let i = 0; i < js_modules.length; i++) {\n", + " const url = js_modules[i];\n", + " const escaped = encodeURI(url)\n", + " if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n", + " if (!window.requirejs) {\n", + " on_load();\n", + " }\n", + " continue;\n", + " }\n", + " var element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " element.type = \"module\";\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " for (const name in js_exports) {\n", + " const url = js_exports[name];\n", + " const escaped = encodeURI(url)\n", + " if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n", + " if (!window.requirejs) {\n", + " on_load();\n", + " }\n", + " continue;\n", + " }\n", + " var element = document.createElement('script');\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.type = \"module\";\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " element.textContent = `\n", + " import ${name} from \"${url}\"\n", + " window.${name} = ${name}\n", + " window._bokeh_on_load()\n", + " `\n", + " document.head.appendChild(element);\n", + " }\n", + " if (!js_urls.length && !js_modules.length) {\n", + " on_load()\n", + " }\n", + " };\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " const js_urls = [\"https://cdn.holoviz.org/panel/1.8.7/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\"];\n", + " const js_modules = [];\n", + " const js_exports = {};\n", + " const css_urls = [];\n", + " const inline_js = [ function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + "function(Bokeh) {} // ensure no trailing comma for IE\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " if ((root.Bokeh !== undefined) || (force === true)) {\n", + " for (let i = 0; i < inline_js.length; i++) {\n", + " try {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " } catch(e) {\n", + " if (!reloading) {\n", + " throw e;\n", + " }\n", + " }\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " }\n", + " root._bokeh_is_initializing = false;\n", + " }\n", + "\n", + " function load_or_wait() {\n", + " // Implement a backoff loop that tries to ensure we do not load multiple\n", + " // versions of Bokeh and its dependencies at the same time.\n", + " // In recent versions we use the root._bokeh_is_initializing flag\n", + " // to determine whether there is an ongoing attempt to initialize\n", + " // bokeh, however for backward compatibility we also try to ensure\n", + " // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n", + " // before older versions are fully initialized.\n", + " if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n", + " // If the timeout and bokeh was not successfully loaded we reset\n", + " // everything and try loading again\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_is_initializing = false;\n", + " root._bokeh_onload_callbacks = undefined;\n", + " root._bokeh_is_loading = 0;\n", + " console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n", + " load_or_wait();\n", + " } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n", + " setTimeout(load_or_wait, 100);\n", + " } else {\n", + " root._bokeh_is_initializing = true;\n", + " root._bokeh_onload_callbacks = [];\n", + " const bokeh_loaded = Bokeh != null && ((Bokeh.version === version && Bokeh.Panel) || (Bokeh.versions?.has(version) && Bokeh.versions.get(version)?.Panel));\n", + " if (!reloading && !bokeh_loaded) {\n", + " if (root.Bokeh) {\n", + " root.Bokeh = undefined;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " }\n", + " load_libs(css_urls, js_urls, js_modules, js_exports, Bokeh, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " if (Bokeh != undefined && !reloading) {\n", + " const NewBokeh = root.Bokeh;\n", + " if (Bokeh.versions === undefined) {\n", + " Bokeh.versions = new Map();\n", + " }\n", + " if (NewBokeh.version !== Bokeh.version) {\n", + " Bokeh[NewBokeh.version] = NewBokeh;\n", + " Bokeh.versions.set(NewBokeh.version, NewBokeh);\n", + " }\n", + " root.Bokeh = Bokeh;\n", + " }\n", + " });\n", + " }\n", + " }\n", + " // Give older versions of the autoload script a head-start to ensure\n", + " // they initialize before we start loading newer version.\n", + " setTimeout(load_or_wait, 100)\n", + "}(window));" + ], + "application/vnd.holoviews_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n const force = false;\n const version = '3.8.2'.replace('rc', '-rc.').replace('.dev', '-dev.');\n const reloading = true;\n const Bokeh = root.Bokeh;\n const BK_RE = /^https:\\/\\/cdn\\.bokeh\\.org\\/bokeh\\/(release|dev)\\/bokeh-/;\n const PN_RE = /^https:\\/\\/cdn\\.holoviz\\.org\\/panel\\/[^/]+\\/dist\\/panel/i;\n\n // Set a timeout for this load but only if we are not already initializing\n if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, Bokeh, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n // Don't load bokeh if it is still initializing\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n // There is nothing to load\n run_callbacks();\n return null;\n }\n\n function on_load() {\n 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!== -1) {\n on_load()\n continue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } var existing_scripts = []\n const scripts = document.getElementsByTagName('script')\n for (let i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n existing_scripts.push(script.src)\n }\n }\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const escaped = encodeURI(url)\n const shouldSkip = skip.includes(escaped) || existing_scripts.includes(escaped)\n const isBokehOrPanel = BK_RE.test(escaped) || PN_RE.test(escaped)\n const missingOrBroken = Bokeh == null || Bokeh.Panel == null || (Bokeh.version != version && !Bokeh.versions?.has(version)) || Bokeh.versions?.get(version)?.Panel == null;\n if (shouldSkip && !(isBokehOrPanel && missingOrBroken)) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (let i = 0; i < js_modules.length; i++) {\n const url = js_modules[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n const url = js_exports[name];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n const js_urls = [\"https://cdn.holoviz.org/panel/1.8.7/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\"];\n const js_modules = [];\n const js_exports = {};\n const css_urls = [];\n const inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (let i = 0; i < inline_js.length; i++) {\n try {\n inline_js[i].call(root, root.Bokeh);\n } catch(e) {\n if (!reloading) {\n throw e;\n }\n }\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n root._bokeh_is_initializing = false;\n }\n\n function load_or_wait() {\n // Implement a backoff loop that tries to ensure we do not load multiple\n // versions of Bokeh and its dependencies at the same time.\n // In recent versions we use the root._bokeh_is_initializing flag\n // to determine whether there is an ongoing attempt to initialize\n // bokeh, however for backward compatibility we also try to ensure\n // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n // before older versions are fully initialized.\n if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n // If the timeout and bokeh was not successfully loaded we reset\n // everything and try loading again\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_is_initializing = false;\n root._bokeh_onload_callbacks = undefined;\n root._bokeh_is_loading = 0;\n console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n load_or_wait();\n } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } else {\n root._bokeh_is_initializing = true;\n root._bokeh_onload_callbacks = [];\n const bokeh_loaded = Bokeh != null && ((Bokeh.version === version && Bokeh.Panel) || 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OutputArea) {\n function append_mime(data, metadata, element) {\n // create a DOM node to render to\n var toinsert = this.create_output_subarea(\n metadata,\n CLASS_NAME,\n EXEC_MIME_TYPE\n );\n this.keyboard_manager.register_events(toinsert);\n // Render to node\n var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n render(props, toinsert[0]);\n element.append(toinsert);\n return toinsert\n }\n\n events.on('output_added.OutputArea', handle_add_output);\n events.on('output_updated.OutputArea', handle_update_output);\n events.on('clear_output.CodeCell', handle_clear_output);\n events.on('delete.Cell', handle_clear_output);\n events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n" + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import matplotlib.pyplot as plt\n", "import matplotlib.tri as mtri\n", @@ -71,10 +1247,981 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.Dataset> Size: 32MB\n",
+       "Dimensions:                  (one: 1, nSCHISM_hgrid_node: 295484,\n",
+       "                              nSCHISM_hgrid_face: 549476,\n",
+       "                              nMaxSCHISM_hgrid_face_nodes: 4)\n",
+       "Coordinates:\n",
+       "    SCHISM_hgrid_node_x      (nSCHISM_hgrid_node) float64 2MB dask.array<chunksize=(295484,), meta=np.ndarray>\n",
+       "    SCHISM_hgrid_node_y      (nSCHISM_hgrid_node) float64 2MB dask.array<chunksize=(295484,), meta=np.ndarray>\n",
+       "    SCHISM_hgrid_face_x      (nSCHISM_hgrid_face) float64 4MB dask.array<chunksize=(549476,), meta=np.ndarray>\n",
+       "    SCHISM_hgrid_face_y      (nSCHISM_hgrid_face) float64 4MB dask.array<chunksize=(549476,), meta=np.ndarray>\n",
+       "Dimensions without coordinates: one, nSCHISM_hgrid_node, nSCHISM_hgrid_face,\n",
+       "                                nMaxSCHISM_hgrid_face_nodes\n",
+       "Data variables:\n",
+       "    SCHISM_hgrid             (one) |S1 1B dask.array<chunksize=(1,), meta=np.ndarray>\n",
+       "    SCHISM_hgrid_face_nodes  (nSCHISM_hgrid_face, nMaxSCHISM_hgrid_face_nodes) float64 18MB dask.array<chunksize=(274738, 2), meta=np.ndarray>\n",
+       "    depth                    (nSCHISM_hgrid_node) float32 1MB dask.array<chunksize=(295484,), meta=np.ndarray>
" + ], + "text/plain": [ + " Size: 32MB\n", + "Dimensions: (one: 1, nSCHISM_hgrid_node: 295484,\n", + " nSCHISM_hgrid_face: 549476,\n", + " nMaxSCHISM_hgrid_face_nodes: 4)\n", + "Coordinates:\n", + " SCHISM_hgrid_node_x (nSCHISM_hgrid_node) float64 2MB dask.array\n", + " SCHISM_hgrid_node_y (nSCHISM_hgrid_node) float64 2MB dask.array\n", + " SCHISM_hgrid_face_x (nSCHISM_hgrid_face) float64 4MB dask.array\n", + " SCHISM_hgrid_face_y (nSCHISM_hgrid_face) float64 4MB dask.array\n", + "Dimensions without coordinates: one, nSCHISM_hgrid_node, nSCHISM_hgrid_face,\n", + " nMaxSCHISM_hgrid_face_nodes\n", + "Data variables:\n", + " SCHISM_hgrid (one) |S1 1B dask.array\n", + " SCHISM_hgrid_face_nodes (nSCHISM_hgrid_face, nMaxSCHISM_hgrid_face_nodes) float64 18MB dask.array\n", + " depth (nSCHISM_hgrid_node) float32 1MB dask.array" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "grid_ds = parcels.tutorial.open_dataset(\"SCHISM_LakeOntario/out2d\")\n", "u = parcels.tutorial.open_dataset(\"SCHISM_LakeOntario/horizontalVelX\")[\"horizontalVelX\"]\n", @@ -106,10 +2253,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "6", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "n_node=295484, n_face=549476, n_max_face_nodes=3\n", + "x range: 1364569 .. 1722587 m\n" + ] + } + ], "source": [ "node_x = grid_ds[\"SCHISM_hgrid_node_x\"].values.astype(\"float64\")\n", "node_y = grid_ds[\"SCHISM_hgrid_node_y\"].values.astype(\"float64\")\n", @@ -159,7 +2315,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "8", "metadata": {}, "outputs": [], @@ -174,13 +2330,2013 @@ "U = u.isel(nSCHISM_vgrid_layers=slice(None, None, -1)).rename(\n", " rename\n", ") # reverse to surface-first\n", - "V = v.isel(nSCHISM_vgrid_layers=slice(None, None, -1)).rename(rename)\n", + "V = v.isel(nSCHISM_vgrid_layers=slice(None, None, -1)).rename(rename)" + ] + }, + { + "cell_type": "markdown", + "id": "3050dc4e-da26-49bd-b743-1cccea6e426a", + "metadata": {}, + "source": [ + "## Defining a cell size for local time stepping.\n", + "Unstructured meshes are often strongly refined near the coast, so a single `dt` that suits the large\n", + "cells in the basin can carry a particle across several small cells in one step. We add a `cell_size` attribute to the dataset that provides a measure of the length scale of each triangular cell in the mesh. This attribute will later be used in a custom kernel that reduces a particle's time step size based on the local mesh resolution." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "0d9873ca-b019-4695-be90-196044774460", + "metadata": {}, + "outputs": [], + "source": [ + "# width of each triangle (its smallest altitude), used to limit the timestep by the local CFL number\n", + "p = np.stack([node_x[face_nodes], node_y[face_nodes]], axis=-1)\n", + "e = np.roll(p, -1, axis=1) - p\n", + "area = 0.5 * np.abs(e[:, 0, 0] * e[:, 1, 1] - e[:, 0, 1] * e[:, 1, 0])\n", + "h = 2.0 * area / np.hypot(e[..., 0], e[..., 1]).max(axis=1)\n", + "cell_size = xr.DataArray(\n", + " np.broadcast_to(h, (U.sizes[\"time\"], zc.size, h.size)),\n", + " dims=(\"time\", \"zc\", \"n_face\"),\n", + " coords={\"time\": U[\"time\"]},\n", + ")\n" + ] + }, + { + "cell_type": "markdown", + "id": "e1acee60-ea55-4391-ac7d-4629d4250c50", + "metadata": {}, + "source": [ + "Now, we can construct the `ux.UxDataset` object that we will use to create the `Fieldset` in Parcels with `Field` objects for `U`, `V`, `UV` and the `cell_size`." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "247ed1c4-8138-4a53-864c-a482d76b1936", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.UxDataset> Size: 1GB\n",
+       "Dimensions:    (time: 6, zf: 32, n_node: 295484, zc: 31, n_face: 549476)\n",
+       "Coordinates:\n",
+       "  * time       (time) datetime64[ns] 48B 2025-08-18T01:00:00 ... 2025-08-18T0...\n",
+       "  * zf         (zf) float64 256B 0.0 1.448 4.097 7.526 ... 226.2 238.0 250.0\n",
+       "  * zc         (zc) float64 248B 0.7242 2.773 5.812 9.557 ... 220.4 232.1 244.0\n",
+       "Dimensions without coordinates: n_node, n_face\n",
+       "Data variables:\n",
+       "    U          (time, zf, n_node) float32 227MB dask.array<chunksize=(1, 16, 147742), meta=np.ndarray>\n",
+       "    V          (time, zf, n_node) float32 227MB dask.array<chunksize=(1, 16, 147742), meta=np.ndarray>\n",
+       "    cell_size  (time, zc, n_face) float64 818MB 137.5 99.14 143.6 ... 10.0 9.731
" + ], + "text/plain": [ + " Size: 1GB\n", + "Dimensions: (time: 6, zf: 32, n_node: 295484, zc: 31, n_face: 549476)\n", + "Coordinates:\n", + " * time (time) datetime64[ns] 48B 2025-08-18T01:00:00 ... 2025-08-18T0...\n", + " * zf (zf) float64 256B 0.0 1.448 4.097 7.526 ... 226.2 238.0 250.0\n", + " * zc (zc) float64 248B 0.7242 2.773 5.812 9.557 ... 220.4 232.1 244.0\n", + "Dimensions without coordinates: n_node, n_face\n", + "Data variables:\n", + " U (time, zf, n_node) float32 227MB dask.array\n", + " V (time, zf, n_node) float32 227MB dask.array\n", + " cell_size (time, zc, n_face) float64 818MB 137.5 99.14 143.6 ... 10.0 9.731" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ "\n", "uxds = ux.UxDataset(\n", " xr.Dataset(\n", " {\n", " \"U\": U.transpose(\"time\", \"zf\", \"n_node\"),\n", " \"V\": V.transpose(\"time\", \"zf\", \"n_node\"),\n", + " \"cell_size\": cell_size,\n", " },\n", " coords={\"zf\": (\"zf\", zf), \"zc\": (\"zc\", zc)},\n", " ),\n", @@ -206,10 +4362,26 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "10", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "| Name | Type | Grid number | Interp method / value | Parcels backend |\n", + "|:----------|:------------|--------------:|:------------------------------|:------------------|\n", + "| U | Field | 0 | UxLinearNodeLinearZF(...) | WindowedArray |\n", + "| V | Field | 0 | UxLinearNodeLinearZF(...) | WindowedArray |\n", + "| cell_size | Field | 0 | UxConstantFaceConstantZC(...) | NumPy |\n", + "| UV | VectorField | 0 | Ux_Velocity(...) | - |\n", + "\n", + "mesh: FlatMesh()\n", + "time interval: (np.datetime64('2025-08-18T01:00:00.000000000'), np.datetime64('2025-08-18T06:00:00.000000000'))\n" + ] + } + ], "source": [ "fieldset = parcels.FieldSet.from_ugrid_conventions(uxds)\n", "\n", @@ -227,21 +4399,22 @@ "\n", "Because SCHISM's LSC2 grid keeps below-seabed levels as `NaN`, a particle whose (fixed) depth ends up\n", "deeper than the local water column will sample `NaN`. Rather than feed it a fabricated velocity, we let\n", - "Parcels flag it: sampling `NaN` sets the particle state to {py:obj}`parcels.StatusCode.ErrorInterpolation`, and ending up outside\n", - "the mesh sets {py:obj}`parcels.StatusCode.ErrorOutOfBounds`. We add a small kernel that runs after advection, records that the\n", - "particle went out of bounds, and sets its state to {py:obj}`parcels.StatusCode.Delete` so it stops being advected (its trajectory\n", + "Parcels flag it: sampling `NaN` sets the particle state to `parcels.StatusCode.ErrorInterpolation`, and ending up outside\n", + "the mesh sets `parcels.StatusCode.ErrorOutOfBounds` or `parcels.StatusCode.ErrorGridSearching`. We add a small kernel that runs after advection, records that the\n", + "particle went out of bounds, and sets its state to `parcels.StatusCode.Delete` so it stops being advected (its trajectory\n", "up to that point is kept).\n", "\n", "```{note}\n", "Most of the Lake Ontario mesh is shallow nearshore water with only a couple of valid vertical levels;\n", - "the deep central basin has the full set. We therefore release particles in the deep basin (nodes with\n", - "many valid levels) so they start within the resolved water column.\n", + "the deep central basin has the full set. We therefore release most particles at 2 m depth in the deep\n", + "basin (nodes with many valid levels), and a smaller set at 1 m depth in the finely resolved nearshore\n", + "regions.\n", "```" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "12", "metadata": {}, "outputs": [], @@ -250,6 +4423,7 @@ " parcels.StatusCode.ErrorInterpolation, # sampled NaN (below the local seabed)\n", " parcels.StatusCode.ErrorOutOfBounds, # left the horizontal mesh / below the grid\n", " parcels.StatusCode.ErrorThroughSurface, # above the surface\n", + " parcels.StatusCode.ErrorGridSearching, # left the mesh during a step\n", "]\n", "\n", "SchismParticle = parcels.Particle.add_variable(\n", @@ -269,15 +4443,55 @@ "id": "13", "metadata": {}, "source": [ - "## Release particles and advect" + "## Limit the timestep by the local CFL number\n", + "\n", + "The `CFLLimitedDt` kernel below shrinks each particle's `dt` so that it moves at most `CFL_target` local cell widths per step, $\\Delta t \\le C\\,h/|u|$, using the `cell_size` field built above. The `dt` passed to\n", + "`pset.execute()` then acts as the *maximum* timestep, and Parcels sub-steps each particle until it\n", + "reaches the next output time. Place the kernel before the advection kernel." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "14", "metadata": {}, "outputs": [], + "source": [ + "def CFLLimitedDt(particles, fieldset):\n", + " \"\"\"Shrink each particle's dt so it moves at most CFL_target cell widths per step.\"\"\"\n", + " h = fieldset.cell_size[particles]\n", + " u, v = fieldset.UV[particles]\n", + " dt_cfl = fieldset.CFL_target * h / np.maximum(np.sqrt(u * u + v * v), 1e-12)\n", + " particles.dt = np.sign(particles.dt) * np.minimum(np.abs(particles.dt), dt_cfl)\n", + "\n", + "\n", + "fieldset.add_context(\"CFL_target\", 1.0)" + ] + }, + { + "cell_type": "markdown", + "id": "15", + "metadata": {}, + "source": [ + "## Release particles and advect" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "16", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "releasing 1500 particles in the deep basin and 500 in fine nearshore cells\n", + "INFO: Output files are stored in output-schism.parquet\n", + "1938 of 2000 particles still active at the end of the run\n" + ] + } + ], "source": [ "# number of valid (non-NaN) vertical levels at each node\n", "valid_levels = np.isfinite(U.isel(time=0).values).sum(axis=1)\n", @@ -290,9 +4504,19 @@ "idx = np.where(deep)[0]\n", "idx = idx[:: max(1, idx.size // n_max)][:n_max]\n", "\n", - "x, y = cx[idx], cy[idx]\n", - "z = np.full(x.size, 2.0) # release at 2 m depth\n", - "print(f\"releasing {x.size} particles at z = 2 m in the deep basin\")\n", + "\n", + "# release 500 more on faces where the CFL limit at dt = 5 min is below 1 (small cells, fast flow), at 1 m depth\n", + "surf_speed = np.hypot(U.isel(time=0, zf=0).values, V.isel(time=0, zf=0).values)\n", + "dt_cfl = h / np.maximum(np.nan_to_num(surf_speed[face_nodes].mean(axis=1)), 1e-12)\n", + "fine = np.where(dt_cfl < 300)[0]\n", + "idx_fine = np.random.default_rng(0).choice(fine, 500, replace=False)\n", + "\n", + "x = np.concatenate([cx[idx], cx[idx_fine]])\n", + "y = np.concatenate([cy[idx], cy[idx_fine]])\n", + "z = np.concatenate([np.full(idx.size, 2.0), np.full(idx_fine.size, 1.0)])\n", + "print(\n", + " f\"releasing {idx.size} particles in the deep basin and {idx_fine.size} in fine nearshore cells\"\n", + ")\n", "\n", "pset = parcels.ParticleSet(fieldset=fieldset, pclass=SchismParticle, x=x, y=y, z=z)\n", "output_file = parcels.ParticleFile(\n", @@ -300,9 +4524,9 @@ ")\n", "\n", "pset.execute(\n", - " [parcels.kernels.AdvectionRK4, StopBelowBed],\n", + " [CFLLimitedDt, parcels.kernels.AdvectionRK4, StopBelowBed],\n", " runtime=np.timedelta64(5, \"h\"), # the dataset spans 5 hours\n", - " dt=np.timedelta64(5, \"m\"),\n", + " dt=np.timedelta64(5, \"m\"), # maximum timestep\n", " output_file=output_file,\n", " verbose_progress=False,\n", ")\n", @@ -311,7 +4535,7 @@ }, { "cell_type": "markdown", - "id": "15", + "id": "17", "metadata": {}, "source": [ "## Plot the velocity field and trajectories\n", @@ -324,10 +4548,21 @@ }, { "cell_type": "code", - "execution_count": null, - "id": "16", + "execution_count": 13, + "id": "18", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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4BsySepxR8FSrVk3tJx4zFIj8PJ6ruazJkyfHux24fSks+f243QnPE7bwXMbtwIEDfgaPR4q0pJy3E7O+/E20bNlS/RZ4nuD5k8/xPHD58mX1e3jaeZXXLM7D9eU5kwKP5wEKYx6bn3zyyTO/J9c1NrxOtGjRQu0fzsttx98Mz6cUZprwZtYMhR+/F0UcjwX+HrSB0/SIGIcIycaRaYq6DCr0zUKiuHPnjrlOnToc3leTs7OzuVatWuYRI0aYHz9+bJ1v5MiR6vVVq1YlaLkXLlywLvNpE+fTePnll82enp4xlrN8+XKzr6+vdf5s2bKZu3btal66dKndzxs9erRaby8vL/Pvv/+uXvv444/NBQsWNJtMJvNbb72l5nsW33zzjZrv9u3b5oQSFRVljoyMNDdu3NjcsWNHu+vGv0uVKqWmixcvWufZuXOnmmfMmDExlnnlyhWzu7u7+ZNPPon3c2/cuKHe26NHj6euX/fu3dV8N2/ejPEdR40aFWO+QYMGmd3c3NT20uB+4f5J7jYoXLiwOSIiIsZ7tNcmT55sfa5GjRrmHDlyxDgGuewyZcqY8+bNG2PdYvP222+bfXx8nrqe2nePDdch9nGZP39+s8FgMJ8+fTrO/PXr1zeXLl36qZ9lNBrVNhk6dKg6frV1P3/+vFpu7969431vcHCwOWvWrOa2bdvGWWb58uXN1apVe+pn8zP5fdauXRvvPBs3blTz8N9n7RceA3zun3/+ibMcPp85c2bzvXv3YjzfvHlztc8ePnwYZz/xONPm19ajVatWMeabO3euep6/EY3WrVur/ZKUfW+PdevWqc/YsmWLejxjxgyzt7e3+i00bNjQOl/RokXNvXr1eurxEt+6aduzbNmy6ljW2LNnj3p+1qxZT11H7bNsf1dk+/bt6vlhw4bZfR+PNx5/ly5dUvMtWbIkzu/g66+/jvO+p50r+f1szwcJOc4I5+FnarzxxhvqXM11s+Wnn35S8x4/fvypy+Nvj7/B2GjHUr169cxJPWclZ32nTZumHk+YMOGpnx3feZXncldXV/Ply5djPN+yZUuzh4eH+cGDB8/8nvZ+1yVKlDBXrFhRfV9b2rRpY86dO7c6rxCeZzt06GB+EeB5h9th87E85v2X/B0ycVlcZuxzmvBioh1Drg2+Nbs1GemQybXBtxnyGMqY8cNkwBE6jvYxpYepcBytP3PmjBqZ42hxct0NWQfFZcee+HxC4AgzRx450sn0i9KlS6vReo7kM7XKHkxhoYkJI0EcvZw2bZo1Pc3RcDSS0UemhDCtkCPUHI3lqL+9aAxrBDgSzxoyulRqMOWR6/fSSy+pddYmjvQydcsRDl1aql3s7cBtaQujV6wlunXrlsO3AT/LXqTWFo7a0nGUo+S2bp+MotBIhsYotulvseFIN6OVTOFcsmSJQxw6uU0YAUwojFgyOsORaq43vzNH3jkSrW1XRmgY1WTUNz4YAWa0kqmxtscFI9EcEedvidsrPlauXKnWm+viSBh9tQcjA4xea/A44rHAmkimadp+B/62+XrsVD97xyOxjS46et8zcsfjl5Eybd8wosJtzH3AKAOjVkzbTO62ZFqlbSQ7Md+PxK5/ZMSF5xJGSTR4jDEqxgi69pvUzjf2fpfx7c+EktTjjOc9RpKY2mp7bDAKpUXUk0N83ysx56ykrC+3B5fN1PGkwPMHI+Tcf7Yw0sVjMbZbb0L2HyPKTD3Vjp/Yv0VGPLXzKn9H/A6MlPPa48ha89TCCL1DJyEDIumOyUZ+OUmEqXJMU6ED4rVr1/DBBx+o9A3NPERL22JKTmJg+h2XHXuKLy3PHkw5Yprl6NGj1UWQFxumlTFtiDUJ8aUEURT98MMPKr0lKXbRz4LpQ2+++aZKHWEaJW82edPMGzt7FzXe+DFVhSlIWlqSBp+niKKA4w2D7cTlPu1mkzWFvAF+1r7h/uR8rC+ILdRt0VKGEnJhTuw2iC9dyhamqXJb2JuXN0fkaWk3FHIU6Lzp5c0LU3+4ftz+SSUh662xZ88elZpLJkyYoAQ5twnrrIi2XbS0q6f9FnhcEArW2McFU2K5nbSUU3vwMxLzW0sIPIbic0mNvZ24n3gTSOfR2OvPG0MS+9hOzvGY1H3PG2oKNU2kacZDFGoU0hzI0paRXJGWnO9HOHBj7zntN0EBz+OP9XNMi+N34TGpieGk/i6fRlKPMx7fdOyNfWxwMI4kd4DF3vdK7DkrKevL7cFzlb266YTAfZmY819C9p92LuFgZ+z1Z4qw7fozxZL3AxwQpSjlNYPXYA5SCIIgJBWpSXMAPGkzX5+24sxDJzxR83metDlCm5pQMLLug7n+FGnaBdIW3nDRRIQ1XbzZij0i6QhYI8CbOBoVxK7PsAfdL1krwvoi3rjaGrBQaDHCxZvB2HUVxN5zGhyV5/5ZtWqVijLZu1ni8/v371cjvraj+Cm9DRISzWQkhjc3HNmNDQcQtO31NBg55cQoE+tieDzT/INRYkYUeFOuFffbbtv4bgoTE4VljQd/Kxx11z6HxLba1lwBuW/iOz6170mRE59TW3y1itpncPlPw3Zb2JKUbRH7Ne5LLQIaX8SQNX6O5Fn7Pj4YuWC0k4KG24znDRqPsB6NAo3HHqNFz+Nckhjs1RrxOZqDEJ6zWcPK+lZGYDU4uBUfyc0ySMhxFt/xzUgiB9PsoYmSpGLveyX2nJWU9eX2oPERBXNShBqFfGLOfwnZf9p7mCXDGkR78JpJaEjDWnBOFHdaVI21oc8ygkmrmB1o+MFlCRkQqUlLNhJJSyT2LgRES/vQLjocqWUEiAX/TB+0BwUIi9cdBS+aLOpOyPrZgwX1vKjYa8rtCHhhjC2e+P3jaxzNizUNH5jqycie7U0CbyIZFaGxhL3IY3xGBRq88PL9HBHlyL8tfMyRY76umYIkFn5Pe6PMid0GCYE3CBzlZiTA9jN5w8MbLIrQhKYeclkUpoxi0fBCi7xqBjSxj1dH9PnTbL5txTC/BwvxbWG0g/PEvlmMPdjAqCuNL+wdF5zoMBcf/O4UJ0yfio/4tsXSpUvhiKgbBxAOHjyobm7trX/syFJyjseE7Pv4YISMgyc0ceAxppld8HlG2LQUVkesW3LQTGo0mI7JyKFmeKHdsMf+XfLckxgSE+FLyHFmD573tDYW9o6NZ4m0pGzr5JyzErq+3B5M5X1WD7f41p8DBtyWmijT4LWXv6mkWOtTgNGoiQI+vnMJByXsDQLxesUUYqZDMt0yPSJ90oRkI+mOyUYiaYmEDnG8IaGY4U0Jb4QPHTqkXNhYD2RbO8Y0EVo984RNscY6E57AOeLOkWY6WzGK4Cgbfl4QuH50Hatfv75K6WAqHC2u//77b3VTwnqM+GB9F6fkwJt2excupp/xgk1nPo7Uc/24vozcMTLwNPtoblsuk4KKIpQRNt6MMzrICAAtkuvVq6duMimiOSJLkUahFR98P93iGF2kyxrr9RhxZD0f00JZ48XXn7a9ngY/n7UJ3B7cD1x/XvSTug0S0lKAkQze4DM9h0KEDm68QaK749NGjtlDjymy3CZcV0YZuDzWh2kufUy1YwoP02K5vhRVvKFi3VFyYc0Rfyu0nOc+ZWoSnQZj3xhSHNHJkNuPN2paGwQKMv6mOIrN3yCjaIyIMK2Rx53mUMebLf77NJHH44E9AllrypFw1prws5g2zH3H7csBGIoPbiNGvhhtYoocRbIj+OWXX9QxWbduXXUM83tzAIaRHR5Pib2x145Hrh+/O11LOQDCm8yE7Pv44HL4/desWaN+hxrcNtxH2t9JXTdHwfMDB8xYd8vjlSKU1utayhrP4xQR3N8cmOFxzu2c2HRfbWCIabVaBJ7ndnuDAgk5zuzB3x7Xi+clun3ynEJxw9RsNtNm7djT0ii5jrzm8LNp/c+o8LMGtJJzzkro+vK3zOshs064fH5/Xlt5HqZrMa9pTzuvct20+jdGd7kPKc557WMJQlJbyVCoc1/yusrrOI8bnlc46MnyAJY7EA6ScTtxf/M3wdc5yEQHyWf10BMEQYiX1HYuSW/MmTNHuZXRtYyuVXR3zJcvn7lPnz7mEydO2HXCmjp1qrlRo0bKdc7JycmcPXt25To1c+ZMqzuUraOhPfj8s9wd79+/rxzL+Fl58uQxu7i4qNcrVKigng8JCbHO+6zP00isu2N8EwkPDzcPHjxYrRtd6ipVqmRevHix+h627m7xrZu2DWyd1eiaV716dfU96epIN8S+ffua9+3bZ04IdMDr0qWLOWfOnGrf0CGxU6dO5h07diTYwdKeY92hQ4fMtWvXVs5ifE1zVEvuNojPRZBs3bpV7XttW9DxcdmyZc/cBjw+6cjHbcBjxs/Pz9ytWzfzkSNHYsxHVz06mXL5XH9uj4kTJ9p1d6Rjnz3ic3fkfixevLhyaCtUqJByS500aVKcZWtOcFWrVlXbj79Buq/F3habN29W68DfHH+jXF8+njdv3jO3B39H7733nvpd8708JvjeU6dOWee5fv26Om64fDo0vvTSS+qYs+fuGNuBVYPz8vdlD37nfv36qfXmOvCcwW1v60ioudHF/k72jg86QnJ96eSo0+msv8mE7vv4oLsfl/Xvv/9an6MbKb+zXq9X2/JZv5X41u1pv4HYLoL20D5rzZo16vzM5fN3QTfMgICAGPPy3N20aVPlUJklSxbliEunwNif8zQXW/62BwwYoPaV9j207xnb3TGhx5m978nPfvfdd5UDL9/HY7By5crmL7/80hwUFPTUbUKH3GbNmqnvyWVr55z4jqXEnLO09f3222+TtL6hoaHq3M5rK49FOrvyfGZ7Lo7vvEqOHj2qXF35e+T76eYa+7zwtO8Zn2vr4cOH1W+C+4frnytXLrVef/75p3Wezz77zFylShV17GjnsA8++EC5QadXZ76VRwqat1wo7JCJy8qIznzmjO7u2GS42a3FWIdMrk2GZ8hjSMf/i1/CCYIgCEL6g5FeRvhocuHIyJxgH/Y/ZKoxI9nxOQkLaR/2WmTkceWRgvD0dkxFTPBjE1qWu6COkfhMlIQX7xhybTIcOqcndebJwRwVhvB1X2S4Y0jSHQVBEARBSDJ0fGQKJWGKn5D+MUEHk4NsC0wqoUbIeOgtdWmOWlYGRESaIAiCIAhJhvWkNFxi/TDrCoX0j2Yc4qhlCRkQcXdMNiLSBEEQhBcOGj08j36PQlxokCUIgiA4FhFpgiAIgiAIghWjWa8mR2AU64MMHElzUJqiLmNGYzNmkqcgCIIgCIIgCEIaRSJpgiAIgiAIQizjEMdELxy1HCGdNrN21LIyICLSeAIxmXDt2jXVGPNpTX8FQRAEQRAcDbshsWm9n5+fauie2tDZ0SjujkJyEOOQZCMiDVACzd/fP/lbUxAEQRAEIYlcuXIFefPmle0nCIKINMIImnZyzEhN8gRBEARBSBsNgDlYrN2PpDZiHCIkG0l3TDYSSVMRWUuKIwWaiDRBEARBEFIDKbkQBEFDRJogCIIgCIIQoyaNkyMwwSxbNiMiNWnJJvWrUwVBEARBEARBEAQrEkkTBEEQBEEQrBjNOjU5AkctR0hnSE1ashGRlgiMRiMiIyOTv9WFJOPi4pIm7IkFQRAE4UXF6EALfqOkO2ZMJN0x2YhIS2D/khs3buDBgwfJ3+JCsqBAK1iwoBJrgiAIgiAIgvAiIiItAWgCLUeOHPDw8BD3pVRuOn79+nXky5dP9oMgCIIgPI/rrVmvJscsS4xDMqpTqcPcSnUZM2VWRFoCUhw1gZYtW7aU2StCvGTPnl0JtaioKDg7O8uWEgRBEARBEF44RKQ9A60GjRE0IfXR0hwpnkWkCYIgCILjkZo0IblIJC35iEhLINJgMm0g+0EQBEEQni8mB7oycllCBoSHj6OyFHXIkIhNniAIgiAIgiAIQhpCRJoQgwYNGuD999+XrSIIgiAIGRQT9A6dhIyb7uioKSMivxxBEARBEARBEIQ0hNSkZSAiIiKkv5ggCIIgxMPufYfw+28/o0SDW+hW9yYuhWSCh+vPqFW8fIbaZkazXk2OWpaQ8RDjkOQjv5wUYv/+/XjnnXfQo0cPjBs3LkUaYzN18e2338aHH34IX19fNG3aFCdOnECrVq3g5eWFnDlzok+fPrhz585Thd0nn3yCPHnywNPTE9WrV8emTZusr9+9exc9e/ZE3rx5lQNm2bJlMWvWrBjLmD9/vnre3d1dtTFo0qQJgoODra9PnjwZJUuWhJubG0qUKIHx48c/py0iCIIgCPYJCgpCz+6dEeR5EJ+3PIvCXo/RMPtVZHV+FbfuPsxQm80EnUMnIeMh6Y7JR0RaCvDrr7+iSpUqWLJkiWqM/emnn6JcuXK4cOHCc//sqVOnwsnJCdu3b8fIkSNRv359VKhQAfv27cOqVatw8+ZNdOvWLd73v/rqq+q9s2fPxpEjR9C1a1e0aNECAQEB6vWwsDBUrlwZ//33H44dO4bXX39dCb/du3er19l4miKuX79+OHnypBJ4nTp1gjm6ueWECRPw5Zdf4ocfflCvDx8+HEOGDFHrLQiCIAgpAXtvDhw4EBfOn8fUL0NjvFbYPQjf/TlRdoQgCCmKpDs+Zy5fvowPPvhAmXH89NNPMBgM6rl69eqp5xcvXvxcP79IkSIYNWqU+vvrr79GpUqVlBDS+Oeff+Dv748zZ86gWLFiMd577tw5FRULDAyEn5+fem7w4MFK3DH6xeUwwsbnNBgt5Ovz5s1TUTeKNF78KMzy58+v5mFUTeP777/HmDFj1OukYMGCKtr3119/4eWXX36u20YQBEEQfvvtN3UdY+bI3tNl4KkPt24U+hWYTMDh3Scy1IaSdEchuUi6Y/IRkfacYaqfq6srhg0bpgQayZcvHz766CMl3Jj2xzTC5wUjeLYplxs3blSpjrGhIIst0g4cOKAiXrGfDw8PV2mLWlNpRujmzJmDq1evqtc4ad+pfPnyaNy4sRJmzZs3R7NmzdClSxdkyZIFt2/fxpUrV9C/f3+89tpr1uVT1GXOnNnh20IQBEEQbBnyzXcYNvRbuLnose10BVT0DlbCzJa7Rh3O7dsoG04QhBRFRNpzJjQ0VIk01lvZQpFiMpnUyN3zFGm2y+bntW3bFj/++GOc+XLnzh3nOc5PYUlxpwlMDU3oMQrGGruff/5ZCTF+HsUnvxfh+9auXYsdO3ZgzZo1asSS6Y1Mh2QNm5byyKibLbE/TxAEQRAcAQcfOZjI69TI4cOQp3RhbFzugUIucQUambShNEJDNmSojW+EXk2OWpaQAZFm1slGRNpzhmYdX331lUobfOmll9RzkZGRKp2PUS6KtZSCqY4LFixAgQIFVJ3as6hYsaKKlN26dQt169a1O8/WrVvRvn1763ejsGO9Go1AbEPetWvXVhNTLpn2uGjRImVownTJ8+fPo3fv3g78poIgCIJgn1lzF6jr8OiRP8BojMLcpRRoYXYF2tkH7vh+wDKUKl06Q21Ok1mnJkctS8h4SLpj8hGR9pypWrUqunfvjldeeQUrV65E0aJFlVA6ffq0epySvPXWWypqRSOPjz/+WDk+nj17VpmC8PnY0SumOVI89e3bV0XMKNroBLlhwwYVNaNLJGve+H0YKaPgHDt2rDJH0UQaI2br169XaY45cuRQj5nmqL3+7bff4t1330WmTJnQsmVLNbpJU5P79+8rEScIgiAIjoDCLOD8ZfXv77/+jOPHj+PnLQ1Q3f2qep1+VppQ49/3jUDdKlcQGRWlDL8EQRBSEhFpKTCSMGPGDFSrVk2ZdKxbt06l9lEU1ahRAykJzT/o1MiLDevDKIgY1aJbo15vPx2BBiGsp2MNHWvOWItWs2ZNJdAInRjpUsnlMX2R7o4dOnTAw4cWu2KKry1btqh0yEePHqnPo+CjICMDBgxQ7xs9erSy+me6JAUgUyYFQRAEwVEcPXEGR44cxppVK7Fv7x4U79sUbxe5GCeCFmoCrkUY0KjeWdwKjlKOxWyfk5EwOTDdkcsSMh78XfEe2DELQ4ZEZ9a80DMwFA80qqCwoKiwhRbzFCF0HYxdVyakPLI/BEEQhKRAo6qKlSrh3v176D63JwZU3I+G7sYY8wQbgQpvGnB+2SlVIjBx4kSVRZKa9yEpibYeI/fWh5uXY8bxw4Ki8FnVzan+3YSUPYYyd/sbOmeL90ByMUeG4OHc1zPcMSSRNEEQBEEQXmhOXwlEg3cGI9PLr+GTbkfwZt49MNBe3wzobVIcm01qjPPL/lSlAIULF0ZGxWTWq8lRyxIyHjr+56hIGjJmKC1VfzmPHz9WaW1MgXN3d0etWrWwd+9e6+us44rdsTx2iiBT9tibi/VVTJVr166d6uslCIIgCIIwYc4itJo7G+5NqqBVu+t4z/8MPHSAa/StX7DJkuL446kSOPDjbJW+n5EFGjFC59BJyHjEvn9P7pQRSVWRxnok2rNPnz4dR48eVeYSTZo0UbVPGqyXYkNkbVqxYkWMZVDk0SmQ5hfbtm1DUFAQ2rRpo1wJBUEQBEHIuMybNw8/rz8Cs7MOA6ttx6/FtqsUIku9jGU6HAGMuFACc/5XAV5ueixevDi1V1sQBCH10h3ZP4yugEuWLEG9evWsTn88Of7xxx/KrIKwx1iuXLnsLoO5qZMmTVIij+KO0KTD399fGXRwNEwQBEEQhIzHqVOn0K1bN5R5+0fkzXILXXOfipHeSK5F6fDZpK6IOJ0Jx5YMwcL5c6X+XNIdBUcgfdLSbyQtKipKRbtim3Ew7ZERMY1NmzYp63bawb/22muqZ5cGmyzTSpcROFsHwzJlyihL+PhgiiQLG20nQRAEQRDSP2xSzawaOgUXyOeEGQPm4b9Gi+BrMCmBptmlzbpRAC+/3hsu2z1wbs1ElC9bGq1bt07t1RcEQUhdkebt7a2s3L///ntcu3ZNCTZGwdhHi2mNhDbt//77r+rLRdt21qs1atRIiSzCflwuLi5xGkLnzJlTvRYfI0aMsDjPRE+MvD0LNmkWUh8xIxUEQRCexr+z5yFv3rww6szYvLEIyuR4CC8DVB0aBVqIGVgflBnTulaA05nHuLBvIcIir2LNmjVwchI/NcKCEcfVpAkZEkfWo+kyZk1aqp6NmKbYr18/5MmTRzVSpt1tr169cODAAfU6m0BrMDpWpUoVZTKyfPlydOrU6ak38k8rMvz8889jNEpmJC0+oUYRyB5iFJLZs2dXjzNqAWNqw/3KRtjc/s7Ozqm9OoIgCEIaZM6smQgymNFg/kBkd1tjvb/T/mX+zpieRRBx6TwuO53ApbBT+Oqrr5QBmWBB3B2F5OJIww9dBr3vTlWRRvekzZs3Izg4WAml3LlzK2HGnmT24OsUaQEBAeoxa9WY1nD//v0Y0TSmRNIpMj5Y58YpIVCgcX0Y3aNQE1IX/lA5QkpRLwiCIAga9+7dw8yZM7F2wzoU+ftTfFFqPVzt5AvxqW37/0OwOQiIBKpXr47PPvtMNqQgCGmKNBHXp3U+J4qt1atXY9SoUXbnu3v3rmpGSbFGKleurCIqdIhkcTChmDp27Fi8y0gKjJ7ly5fPWkcnpB7c3yLQBEEQBFtYn/7TuF8weuRw5On9Gl4qtxf1PW/b3Ug3Ql2UQGPkjCZlrHfngKzwBKNZryZH4KjlCOkLiaSlc5FGQcYUtuLFi6vGkR9//LH6+9VXX1VFv3R77Ny5sxJlFy9exBdffKFOqh07dlTvZz1Z//798dFHHyFbtmzImjUrBg8erIqFNbdHR6Gl2EmanSAIgiCkLVauXIkRw4bCRe+OYvVd0d33nKqF0kebhOhsDEOmzbwPHx8flR0j1/S0D30EeP/33nvv4eeff07t1RGEjCHSaKHP+jA2n6bAoiD74Ycf1EmTUSv2Tps2bRoePHighFrDhg0xZ84cZTqiMW7cOFXoy0gabf0bN26MKVOmSLRFEARBEDIA48ePx1tvvQW9zglt3uyP35usRo7ouxtafgWZgEcmwF0P7D9hwsTJzspFWgRa/Jihg8lBTai5rKRCw7i///4b5cqVc8i6CCmIWPCnb5FGYaWlKcaGVvyMtD0LWvj/9ttvahIEQRAEIeNw+PBhJdBc4IrPFrbBV9VXw2CjCVi9PPFWYcyb8gDXV57AyG/G48yZHjKQmw5gRlXv3r0xYcIEa+9cQchIpImaNEEQBEEQhMRSr149lcr4795q6OB3JEajamW3b9Jjyo5qOD9hNO7cvq3q34X0UZNG8c2+dSxfEZGW/pCatOQj1ZyCIAiCIKQ73n77beUMffREBXTKcyOGQNNYeTk/zgz5H7768ksRaInAZNY5dCLcV7aT1vPWHrNnz1btmFiPJqRPHNUjTZcMK3+mQtOhnVl3NBvcunVrgt63fft2VUpVoUIFpCYi0gRBEARBSFcsWrQI//vf/7Bua0mUyBwc53XNJGT8Z3vhY9ApYzIhdWE/Whq+aVN8Aowu3jQJmTFjhrq5FoSkQA+L999/H19++SUOHjyIunXromXLlrh8+fIz/TL69u2rPC5SG0l3FARBEAQh3cBWOOyp2vbDomhQOMrapFoj0gQEmYGvZxhw/UZ2HDu2RbXSERKxjaFXk0P2V/RyKL4yZcpkfT6+frX79+9X/W4Z+bAuw2jEli1b8Pvvv6sInLTiSfukdrrj2LFjlQP8gAED1GM6g9Lr4o8//nhqhPaNN95Ar1691DG2ePFipCYi0gRBEARBSDcMHDgQRjdnLBhssda3xWgGuh5tjAu7fHB+1K8IDo4bZRNSBwo0W5EWH4xg0N3bFrZmKlGiBD799FMRaBmYR48exXhMoW9P7EdERCixH7tJfbNmzbBjx454lz958mScO3dORXHTQh2kiDRBEARBENIFEydOVNPtS0VjuDhqKY7/u1AIx948hwsX1mL69OmptZrpHttaMkcsKzGwzVKZMmViPEfDF/bDjf28kLEiaf7+/jGe/+abb1RP5djcuXNHRV9z5swZ43k+vnHjht3PCAgIUKKOdWusR0sLpI21EARBEARBeApMPXrttdcwc3NVZHF+EOd1pjl+1GwrTMEh6Nn7JRQuXFi2ZxIxQa8mR+Co5QjpjOfQJ+1KAlNmrW+LJRLNZrNd4UhBxxTH7777DsWKFUNaQUSaIAiCIAhpmjNnzqBjx44Y/mMBdC8WV6Axilappwt0YeG4f/8+lvy3Ek6uYrf/orBp06bUXgUhHaXM+vr6qrTY2FEz1jrGjq6Rx48fY9++fcpghK6xxGQyKVHHqNqaNWvQqFEjpDQi0gRBEARBSLPwZon1SB65vfD2S85KkMUeDD99X4eTW4+rmzAfHx+8/FLP1FrdFwKjWacmRy1LyHikpnGIi4uLMp5Zu3atGtzR4OP27dvHmZ/CL3YdJO37N2zYgPnz5ysb/9RARJogCIIgCGkWjoqbocOmLcXhoXsUQ6BZGlYDpUufQatWrZA9e/bUXFVBENIIH374Ifr06YMqVaqgZs2a+Pvvv5X9Po2HyOeff46rV69i2rRp0Ov1ceodc+TIoVpApGYdpIg0QRAEQRDSHEw1Klu2rEpfPBtQEgU8Ywo0kxnYEwo0rX5JpST9+uuvqbm6LxSpaRwivBiktgV/9+7dcffuXQwdOhTXr19XYmvFihXInz+/ep3PPatnWmojIk0QBEEQhDQ5En78+HFs3F4KBTwj46Q47g/1Qp9/iiH8/nllty1GIY7DbNbDZNY7bFlCxiO1RRoZNGiQmuwxZcoUPA26RtpzjkxJ5JcjCIIgCEKaggX/bD7b7ZVcqFswrkBjFK3XsjY4/8McbNu2DeXLl0+tVRUEQXguSCRNEARBEIQ0RZEiReBf2hMzh3vHEWisQ2szrxnOv/89qlWrhho1aqTWar6wGKFTk6OWJWRAnoMFf0ZDImmCIAiCIKQJzp49q1Kbgg0mBKzxsyvQ5l7OhtXvjVePd+/enTorKgiC8JyRSJogCIIgCKnO5s2b0aBBA+gMBjw6nhfO+rgC7UEU8FqN43yk7LGF5wPTSR1nHOKQxQjpjLRQk5beEZEmCIIgCEKqcuHCBSXQSNjlQnCyk+fzwAgUyH8PwXisatAaNmyY8iuaQTA50DjEUcsR0hci0pKPiDRBEARBEFKN4OBgFCpUyPJ3YFG7As1oAnIXu4lI8yPVrPrQoUMpv6KCIAgpiAxvCIIgCIKQanh5eal/d50pClc7dyVMc2w9MAKRoY/QokUL1TdNeL6YoHPoJGQ8dPxP56AJGfMYEpEmCIIgCEKKEhUVpXoQ6fWW25AfttZDFS+mSMUVaD8vBNYuu4QTJ05g5cqVsqcEQcgQSLqjIAiCIAgpRkhICCpUqICAgAD1uEjHN/Fp4XV2Bdpvm50w+O2TqFu3LkqWLCl7KYUwmnVqctSyhIyH1KQlHxFpgiAIgiCkGD/++KMSaOO3NMGAIpegh32BtvGaCz7oeRz+/v7YsmWL7KEURIxDhGQjfdKSjaQ7CoIgCIKQYkycOBFFaxbDa0qg2U9xvBAKNK1yHAUKFMDly5dl7wiCkOEQkSYIgiAIQooQERGBa9euoVhVf+h1cQUaMZqBYsUuIE+ePMqaX0h5lOGH2UFTBjV9yOg4zDRE57h+a+kNEWmCIAiCIKSok+Ogfo9VxMye1b5b3oswG6MQGBhoff7Bgwcw23uDIAjCC4qINEEQBEEQHM7jx48xa9Ys6+Nu3bohMjISg35qhuY57ttNcyzcjv9GYtOmTTFeo6vjw4cPZS+lEGYH2u9zWULGQyJpyUdEmiAIgiAIDue///5T/1Konbt0FfPmzVO3HeN6XrAr0M5cd8aV/QHo0KEDsmTJgoMHDyqr/qkzZiHCCNXEWkgZHJbqGD0JGQ/+xh05ZUREpAmCIAiC4DCMRiPOnDmDOnXqKHFFShUrpP49fbEwnPRxBdrNcKBF+zPKKOTYsWMoX748KlWqhDx582L/vr2ydwRByHCIBb8gCIIgCA6B0bJPPvkEFy9eVI+LFCkKT08PZRjy2vSOKOxyLM57TGag86A7yJ6zPI4fP47ajevhq38LwqA34o8hUfjfb79gxI+jZQ+lIGLBLyQXSwTMMSEwXQaNpIlIEwRBEAQh2axbtw7du3dH21d74NPXSuLmAw/81nsTzp4NQFa/PPit0TG7N1t/b3HC0S0RePnl6sr58e/xV1HAJUK91niCAZWq5sT+vbtlDwmCkKEQkSYIgiAIQrIZNWoUqjephUlDDyCrwaSeq7uzMBoXv4vN2zLDWR8ZJ81xX5ABb/c8CZPJhIYNG6JOs7oo4HLQOk9OJyNavtkYe+cdkj2Ugjiylkxq0jIojqwl0yFDIjVpgiAIgiAkm0OHDqHNW35WgUZqeN3HK0t6oaRbTIFGQkxAs1rnVASOaVH58+fHge0H1fMUcJwizMDJTefVa4IgCBkJEWmCIAiCICSasLAwvP3228idOzd8fX3V43P7w60Ci1OwSY+/q8Y1/ogyAcU7hqNh7VZo3Lixem7gwIE4f+4sPllUDhcjXXA50hlDN1fGro07MGjQINlDKYij7Pe1Sch4iAV/8pF0R0EQBEEQEgxTEynO/vjjD/W479iG+L7zddyPdEGd6itQo1FDdC56GSEmPYKjopDNKa5RyIAVhXB972osNl+y2vQ3adIEr/QbgH8+moY/3g5Xz7u6nsOYMWPQqlUr2UMpiKQ7CsnFkdb5ugyq80WkCYIgCIKQIGjsUbduXZw/fx5fL2qCT6pdgpsuUN1E5XUJxfUjBeGdZy3eYKpjzXexbcHKGO9ndG3QkTKY/toifPfdd9bnadW/YvU61G/QEFWrVcfpE0dRs2ZNJdyyZcsme0cQhAyHiDRBEARBEJ6J2WxGmzZtcOHCBZTp8z6GVF+uEtlsR7ndbf5uP+xknBFwRtEmtFgEg8GAIUOGWJer8fJLPWVPpAEkkiYkF71epyZHYHbQctIbUpMmCIIgCMIz2bJlCw4ePIgi7tVgqOsZR6CpOjSb+Zv4X4nxfr7+z3rL3/fv37f2UJr27+wYjbAFQRAEEWmCIAiCICSAkydPqn99vQoi4rY3wswxBViUGfhibXar+MrlEldwfT3B4vzo7e2t/t138GiM12M/FlI3kuaoSci4NWmOmjIiku4oCIIgCMIzKVy4sPrXLVMoMu81o0G2rpjY7D8468z47OsyWDljPqLMAdb5c7nEXcaDcw9VqiOZOmNWnNerV6kgeyINIOmOgqPcHR2BLoOqNEl3FARBEAThmTRq1AglS5bExagjiNqzDk5jb6NXk8IoXfAolk2fBbPehM49XlLzHthXFLHLSIJMQMS1O2jXrp1dgSb1aIIgCE+QSJogCIIgCM+EEbD//vsPXbp0wb6DLC6zFJjl9vPDgNcGonCRIvjyq6+Q3VePcn5x3z/xej4AAWjRup1s7TQOM1kd1d/Mtk5RyDiIBX/yEZEmCIIgCEKCKFSoEPbv34+9e/ciMDAQZcuWxY7d+9RrkVEmXL10HuFXi9p1dfyulaUnmqura5zl1qvfQPaAIAiCDZLuKAiCIAhCoupDqlWrhk6dOqFo0aJWG/1tew5g0h854RTrzoKmIr9ey43Ht8/CxydLjNfq1K2n/i2QN5fsgTSEGIcIjqpJc9SUEZFImiAIgiAISWLWLEttWXC4EVP/GIu/rlpEmy1GirSmoervjz/7PE4NmjG8coa9CUuriHGIkFzEOCT5iEgTBEEQBCFBsI/ZkiVLsHDhQvV3rVq1kCmLL6ZM+ht5/AxwsqO17kUBl+7vVX/7+eWJYxJSrFgx2fqCIAixEJEmCIIgCMJTWbBgAd544w3cvXs3xvOzZ89G46bNsG/XNqzbWRpARJz3/rSrlDIMqV23nhpd79Oru2ztNI5E0oTkIsYhyUdq0gRBEARBsIvJZMLnn3+uHB0p0F79sRUWH6yBoKtF8TCwKD6b1RLr166h9SOy5owbRmM92v96WFwg+/d/3XLjoZdbD0EQhGchkTRBEARBEOKwcuVKvPvuuzh79iwKVy+KowsBV31ADAE2tP5ZjASQs1UH3DeetOvqGGYOQoFChaA36KUXWjpBImlCctHBgc2skTFrVmU4SxAEQRCEGNBmn02nfTLlQPk2n+DfGd5wjXXHwPsvPuXk5Qxvv8qo7RkZZyvuPReu/v36m6GoVbuObOV0gtmsc+gkZNx0R0dNGRGJpAmCIAiCEINx48ahQP4CiKjZCVHeeuXQaBtB026aws1AVFAk+nfcGeeGglG0OvUv462331MpjkUL+stWFgRBSCASSRMEQRAEIQZHjhxB3VpNlEAjH85tjhDTk9cp2m5EGlC0VTjaN6+MweVOxRnt1uuAIoWcUbV6dZQqRVMRIb1ggs6hk5DxkD5pyUciaYIgCIIgxMDf3x+nAg5Dl6MozE7A48e+qPHzQJj2T8XJLcctCiwiCmPnl8K7tR7ZTUdixK1jt7fU31UrlZMtLAiCkAgkkiYIgiAIQgwGDhyInbt2ovTNO3B5ZILTYxMi12/DyQ1HgCijEmgfrW6Jd2tFxlsvwnTHUqWqWf422YThhHRjHOKoSch4SE1a8pFImiAIgiAIMWjbti2GDx+OIUOGqKbVtrhncUbAoULI6Xw23q2momifBaNrM8DFANy7dw++vr6yldMJjjT8EOOQjJ3u6KhlZUQkkiYIgiAIQhzYHy1LliwxnvP1K4EbRwsgl7NJZTzGl+Y4abcTIm9ZUhx79uwpAk0QBCGRSCRNEARBEIQY9OnTBzNmzFB/u/vkxj9rCqJjnttw0hmfaodNgebkZ+ml9s/UL2WrplOkT5qQXBxpna/LmIE0EWmCIAiCkNEJDw/HhQsXUKdOHdy9e9f6/K97amJQ3jvQ6W4/cxkUaLPXPVR/j/9rorLdFwRBEJKGRNIEQRAEIQM3rX755Zdx/PjxGM83Hz8I/7Rei5zOFGgJW1ZoFPBS31sY8eNP8PDwUM/lyZv3eay28JxJTzVpH374YaLf89VXXyFr1qzPZX0EC1KTlnxSdZjr8ePHeP/995E/f364u7ujVq1a2Lt3r/V1s9mMb7/9Fn5+fur1Bg0axLmQcPTvnXfeUfnunp6eaNeuHQIDA1Ph2wiCIAhC+uHYsWOoWrUqThw/gQJu5VC2SB+8tbYX7lwpiuUd1iKXS8LSjBhB2/kQ8M4XgM7duiO3n5/1tauBgZg1a9bz/SKCwzE70NnxeYu0n3/+Gbt378bBgwcTNP3222948ODBc10ngSrNcQ6PkHTHlGfAgAHqIjF9+nQlxJj/3qRJE5w4cQJ58uTBqFGjMHbsWEyZMgXFihXDsGHD0LRpU5w+fRre3t5qGRR5y5Ytw+zZs5EtWzZ89NFHaNOmjRodNBgM8jsRBEEQBDtw4JODodX9+sDpK3+832gDWnnfhWsiakko0K4GA3VKBKBM2XKYOX0aZs1dEGMeGocIwvNk0aJFyJEjR4Lm1e4fBSGtk2qRtNDQUCxYsEAJsXr16qFIkSIqalawYEH88ccf6sLB0ZEvv/wSnTp1QpkyZTB16lSEhIRg5syZahkPHz7EpEmTMGbMGCXuKlasqITe0aNHsW7dutT6aoIgCIKQZlmweJm6TrL2rGX1Qpi07hjWd5iHTpnvwk0fv2MjJ3vkL2oxChn8yWdwcXGBj4+P9bU+vbo/t+8hPD/MNvs82dNz3lGTJ09G5syZEzz/X3/9hZw5cz7XdRKepDs6asqIpJpIi4qKUr1X3NzcYjzPtMZt27apAuYbN26gWbNm1tdcXV1Rv3597NixQz1mtCwyMjLGPIzIUdBp89iDKZKPHj2KMQmCIAjCi8jUGbNUM+ljJwOUMNu4Yb0aHPUtmwuzFxpQwicIzjr7Ykx7HBXPsh+EWf79c8I/6t8Vq9ehfZuW1tc5mCoIzxPWVPL+MKH06tVLlccIQlon1YxDGG6uWbMmvv/+e5QsWVKNajBvnXnFRYsWVQKNxB7t4ONLly6pvzkPR+1i93HhPNr77TFixAh89913z+V7CYIgCMLzZv369SqCcOfOHdSoUQMDBw5Erly57Ao0cuL0OezbtxfDhw1FwJnTcHL1xgcTq8BTdzpO5MwEQCsW0F5ztrMOJjOQvXAAsvn6qgFXRs04+Gpbgxb7+iykD0zQqf8ctayUJiIiArdu3VKDE7bky5cvxdcloyIW/Onc3ZG1aP369VP1Z6wfq1SpkhrhOHDggHWe2CFOpkE+K+z5rHnYoNPWDYiRNH9//2R9F0EQBEFICTjIyPIAlgnodXps2LBBlQds374dpUuXjiHONDZv3oQvPh2srne+zvmRZdxreDv39BgCjRGzCAB9JzaHT9bb+LTRMRT04TMWYs9b/yPLv2PG/YqXX7LUndF2nwOvh4+dRMd2rZ/7thAEWwICAtR9ZexsKu2+kIMIguAIkpKFlylTpvQj0goXLozNmzcjODhYfdncuXOje/fuqi5NGxFkRIzPa3BkRIuucR6Olty/fz/GaB3noVNkfDAsnpjQuCAIgiCkBc6cOaMEWpOazRGyUwd3nScye+XC3odbVI+zy5cvY+GS/+LcoGoCrXTuVoh8vRGyFbwBH8OTKIOW4vjDT+Wx6udZCDLdxQw3HXYeLo2y3uFxBFpQFLBjVgD6DXg9zjpWqFBBTUL6JT1Z8NvyyiuvwMnJCf/995+6d8yotUxpgRfdgt/HxydR68V5ef4uVKhQ+uqTxtxgThRbq1evVmYimlBbu3atMgQhFGQUdT/++KN6XLlyZTg7O6t5unXrpp67fv26cozkMgRBEAThRWLhwoWqB9mdncHw1ecCDAb4mAqguCEYpx/sR7HixfHlkG/g7Z1JibNbN29iw/q1SqCVcqsD71r1cccViDTqcS1Sh6IujDBYlr39eCR+GDvf+lnTdldGWe+HcdIhKdJ88lnMQiZN+CtFv7+QMtA6X+cgccVlpRSHDh1SfgUlSpRIsc8UMm664/z58xPUb4/n4latWiV6+akq0ijIuOLFixfH2bNn8fHHH6u/X331VaU4aa8/fPhwVaPGiX/z4sSUSEI3n/79+yvbfdrvc0MNHjwYZcuWVW6PgiAIgvAiYTXdcnZDlLsBYw6eRkm3YDw26RBpLoEIkx5ffjsG1at8hMmT/sbhg0/KB3J5F0eIWQdDEHD3Vib8cr0iPslzADkMwKVQPRq3vGidd/beuuiU/Ybdm6NaY5ndEoB58+al1NcWhARRqlQpVacpCM8b9nimARP1R0JgBI2BpXQj0uj6xPowNp+mwOrcuTN++OEH65f45JNPlFX/oEGDVJStevXqWLNmTYweF+PGjVOhbUbSOG/jxo1VXzXpkSYIgiC8aLRs2RJDhgzBbd8rGLIcqOARrJ530TFfkfU2Rkz4AShXb7RKfSycuTQ8W7VBm7cD0CL7IVy8dAm/zGiGYKMb1tyviC3exXDr3wVwPx+EqGgLx0NnS6OMh32BFmUC9o7Zoq67Xbp0SeFvL6QUT2u5kJRlpVRtEDOteO/IQX0O2Me+KU5sTZCQdF70dMcLFy4kan5m+SWWVBVpFFZammJ8O4W595zig45S7B7PSRAEQRBeNGhrz9rtDm1b4djJMyheogROnzqFbB6+6gY4dlqRuw74c7oLyuQshMPnfLHe+xy+zn9UXfBrl3mE3K8swrCPG+Dk8YU4H3oamTP74M7DB+q9Vy+WQE6XCLspjidCDShX+JR6PHHytBTdBoIQH7Frg5ihxQF7W8Q4REhpHjx4EKNnZFJIEzVpgiAIgiBYaq/v3bsHX19fFa0KCQnB7du31aaZOXs+6Gb+4eBP8dnHH2Ho9yFoMA7w0FlElHafGmwCGhe0hMWalrmGmqZr1j5opHzBu9i8b4T6u2DBQrhw4bz6O+BCceR0MdoVaP+77I/3amywmnMdOX5adtcLTHoyDtm4ceNzXb6QNF70SJotjOAWKFBAmR8SBqAWLFigvDVWrFiB8uXLIymISBMEQRCEVOLatWvKECsyMhJHjx7F33//bbHJ9/VVddksCbCiA0wmM5xdXPD98JEYMWwoSrQCXv26Es6F5UCr0mfRMftVeOpt3qIDvPQxU85OXzajYtXqqFKlKib88bt6bvaJSijo+jhuzzQT0Gx6Y2z87E/1mGUFzGBp3CD7c94yQmqSnkRa/fr1n+vyhaSREYxDNP766y/MmDFD/U0zQ04rV67E3Llzld8GS7WSgs2pXBAEQRCElGTths2IMFou7L/++ivafvoydp+thPW782Df9X/w5lvvANECy2g0wWg2w2g0w8XVA4M++gKe4d4Y1nkpZvWeiKuRXnDXP/1maflhYOvu/ji4d7dVoO06VQFdfOIKNAq7PJU8rALtn6kzsGlrzP5TgpDaHDlyJE7T6qdx/PhxZcAjCI6CzvJav2W2f2AkrVmzZqo+cu/evUlerog0QRAEQXAAjx8/VpGmxEKbfI7Ctun5NX7quxaVPR6jlHsIZn1pwNL/pqh6NNbUGAx6OHNy0sPFWQ8/38z44MPBKhUoT5aKuGtyi9fwgc9dCnFC+5YB+OLjz9Rzdb+sjYjAoqiSKdiuQGs60B+3bh5Wj6dMn6kaVTdv0jCJW0dIT9A235HT84Rtmu7evZvg+WvWrKlMdYSUSXd01JSWYa/mK1euqL9XrVpldZjneTs5DdQl3VEQBEEQksHQoUOVMzHrybQL9vLly9XNYELQasIueOmQzWCpCeMtiQuA6s19cO1aIIoWK26dnxE1k5k30mbcvHNP3Qj4uuXGiuNl0CLbOdT2CIKeYi16JPZmlAGbj+rwejeL6UeNt17Dwk82IYfzLbtpRHeigHZvFMbuFausAo3UqVsvzd8sCRkPHv90PGWLpoSg/U4FwVF06tRJtQdjuzAOGNCFV+vbV6RIkSQvV0SaIAiCICSjYPybb75BkZqFMfx/eRAc7ozXm25D7dq1cfHiReTLl++p7y9bqjhOnjiu/s58KQyBkc7I5xypHoeYgbXzrqPmEIttOFvVtG3VHP9M/RfhUSYYTWZ4eGeCk5Mzzt/YiVJLamHgoy7wzBWM8MuuOPnZt/DImQUh1+8h98uNMHZ3ZryU5S5cdZvU8uzpLaMJKFvzEW4Frorj4lg4fx45TjII6cmCn72qTp9OuJENB0/c3d2f6zoJGasmbdy4cco4hNG0UaNGwcvLy5oGyTZiz1WkLV26NNELbtq0qfwIBEEQhBcatohxzeyG3fMM8DFcV89VP1oMpQoeRc+ePbF9+/anvv/oidMoXqIkcuTIifNHpuP1Ub3w3pub4WGIwndfP0CeXEWRKxebR0O5PoaHh6toVgQblgFwdnZF3QaNsHHdapxd/jtK7quPkPAHOHlntXqdAq3QmG/xZtMN6Jf1LvS6p99MZ6p0D2E3Laljf/w9UTlMvvxST0dtLiFdiTRHGYfgubJpk2XQQUhbZAR3xy+++AIdOnRAtWrVMHjw4Div0/wpOSRIpHEFErsxAwICVHdtQRAEQXiR2LlzpzWVMSwsDAOHt4eP4YT19SKuYap+6/BhSz3X0yhVqjROnDiOQe+8i5/HjMa6/w3H7mneqr6N4uyjTz5Dj66dMHveQuXsOH3WfIRFGmE0mdS11tWgR9duPREVEY5tWzdj29U5MZZfpdOXmNhxLsq4RcY7Gs2b6BAjkKPQZYRFhsPFxUWJwVmzZiV3UwmCILywXL9+HW3atIHBYEDbtm2VXmKPPldXV4csP8Hpjjdu3ECOHDkSNK+3t3dy1kkQBEEQ0iQULnRjpEhjOiPZMfsKonoABgoeAI9MOuU2Z+9CPXXGLPTq3gXOzs7KEOT48WNKfBUoUBC79h7Evt3bsXDxUvjl9sPYMaPUfITCjBNN7KKMJvU5znod9HodnA0GvNJvADp37QaDXo+JE/7E4UOHULx9b0wZuwglXSPjNRNhPK581yic3H5BPceUnQsXLH/36NEjzY5gC8+X9GTBL6RNuNcdlu6ItMnkyZNVTeS2bduwbNkyfPjhh7h69arKJmzXrp0ScGyn8lzdHV9++eVEpS6+9NJLyJTJkkMvCIIgCC8CFFgUaITucDVq1IBep0dQbld8u6sMLkU642y4G976tYya57XXXovx/qCgIPUvUwi5rHkLlyihRNfG7l064sbVS1ixag1CQ0Pg5BSpbkz4nolT/1VCLirKrNIcaRrCtEVXZ7217iPKZIaLuycm/zNRCbSchUpjxthjKOFiEWj23BuDjEDBKhesAu3mzZtWgUZEoAmCIDwdnifr1q2ratFOnTqFPXv2qGvDhAkTkCdPHlUz+dNPPynx9lwiaVSKieGPP/5I9IoIgiAIQlrFNvWvb+8eeOutt9QI6pYzFVHd8w4icQe/nSuGT+suZ6WZ6pkzcuRI63s4b8B5i+03BZrFeZE1G8Cj+3fg4+OjUgzbfFIF00c+RBbDaRjvlMbhiwUQGvGSRZzBrMQZ38OIGf/W63RqtHXl2nVYOn8WIiMjUHVET6ztsw/eBvsudhRof90oiI+7HoZLaCaYTHdEkAkxj5HoyRE855I0IY2izk0OCqXp01FEv2TJkmpij7Rbt26pCJvm7WGvbu1piLujIAiCIMQDG5OyPkyLoLFea9euXVizZg1eHt4ENb0sjUpdzMAbhc7gK2dnVY/NEVXy8OFD3L73CNu3b7N707pnzy6M//1XeDlnx5IThdDE55416mXQATULXsTtu4dwIbB8tDW/5UUXJ4o0HR4/uIcRP3yPu3fvQOfkiqZz3sLMWmvgzdxL7fNiRdKuRhrwYf29aNeiCebOnSv7XoiDpDsKySUjuTvGB8vE+vfvr6akkGiRxiLp3377DRs3blQKMXaX9wMHDiRpRQRBEAQhrVG5cmWsWb8pRo+lM+cuQqc3wElTbtFQF5UrV071ymGNAkdSaTLCdJhKVaqiefdO8PPzhHNYJuhggJMTsGTRQhhgQNEhg9DIx9KPzBYKLFfnozDoKygzEg0ngw5HDx3A/377GS9/WwQ/vpoFngbATbcmzg0NH9+O1ONImAfOBmfBoIobVO3ZmDFjnscmE4RUZfr06fjzzz9V6i5/f/nz58fPP/+MggULon379rJ3BIfzvLRRokVav379sHbtWnTp0kVZTkrOuiAIgvCikju3xf5eQ7Ojv3Q+AD+8Pxy9mpVAKc8QFR2bGVAE+/evVE1NWThernQ5tOjyPc6XdYVrpVtoXWomqrqHqnk3Hm+Iw6dq4Nr1a8hmyA1ksVzUYwssysClS5xQuZpBCbNr129g/pxZOHRwP/SuBpw5XwwFXen0GP93YA3bn4dLY+QbBxF27aCqkejbt68SkmwTIAgvSr4jy22+/vprZX3OBvNGo2UghenEFGoi0lKOjGDB/7y1UaJF2vLly7FixQrVqFMQBEEQXmQYObMHXbymT5+BskUOo3nbWrh+/QGO7FupjLNYOJ43T15kcWmBy4XcEZU3Ei39T6Cae6iqI2N0rGHpjThwsirc3D3wMOQO8u51x5JGOdAhyy2V0BhsBjbf98W3g06iaulmCAsNwqeDP0RISIj6/H2ny6OCdwh0upgjtrHhZ/Ezv6p8FPkXFsSrNS6gTbuOSU6/EYSUEFqcNPfU0qVLK+HVsmXLZ76X0QwaNtAK3bYmtEqVKomuBxKE1NZGiRZpdCoRi31BEAQhsYSGhmLdunVKaNSvXx+5cuVKM6Yg8UWUZs1dYP27Y7vW1r+9vLzw6RdfYfeunThy+BC8XLOq4vDWrVujSJEiKJavNEKdnGGKvsrqYbbaSHOQVc86MQC16jXG+pVLcHv2VIyIfAk/1Q2FPsyEiDnhOLR7PPTOJpQtHIZ3Bg1U7z10tgTKeDA6QIH29O8Vuxatqd81lTJ58viRpG8sIWPgQAt+Lisx5M2bVwks/o7I1KlTVQTs4MGDSrA9DaY4VqxYMc7zbIfBlhdCymExNnLcstIyz0sbJVqkMYf9008/Vfm+zPMVBEEQhGdBAfPqq6/i3r17louPk5O6lnz//fepmspC0cjSMjouVq1aDUUK+mPBggVKtN29ezfGvLFby9A2n33M6tStpx7fexCE6TPnwGTW4ca9G/DVh8DtjjsifJyw7GIZtMp8BeXcwpV42nehBnJn8UTvHl1x7VIATp44gauzhgCx+kcbI4GpkyehWse8WP2rOzI5xayDi02YEbhr1CHMZMCm87nQv1SgtUfarUg35TKp3fwKQnzwmLHXWy8pJHY5bApsC9MWGVmjYc+zRBrrzg4dOhTn/nTlypUoVapU4lZESB7KOOQFb5T2nLVRokUaQ8YskKN7lYeHh7XRpoZ2ARYEQRAEcvbsWXTt2hXNG7dAnbyNYYww477HdXXzRcHwyiuvpNqGunrjtvXvvXv3qIlQtD0L68gpb0KZxggzooxmVK1VBwtmTUe7hqXgtM8MjxueiDqsR9U3buK7j3uiYN4yiIj0Um9lZOvTz7/CsO++wdmzAeq5PLmqI9PHjTGh/X+o6B6qDEmcEuCUFm4Cmg/qhO3LxsBsjoK72yVk2VUVdbPdxM1IF3z5VQEYDMfi9G8ThLQKa8rmzZunomBsIP8sPv74Y9Ueg/epHJBg6jEj5SNGjMDEiRNTZJ2FtMP48eMxevRoXL9+XQl81iWyp5k9WKNLoUVnXmZ7UGy98cYb+OCDD1JNGyVapHF0kQ3Zhg8fjpw5c6b5Yj5BEAQhYbBPF29m/vnnH2UdX7ZsWTRq1Ajfffddss71kyZNUumBJY2VsX7ydnXz5JnZA21atMX//ve/VBVpFEmaE1eHtq2weNmKp87Pdee2UCKO0Qb+Z+bNpBlhkUYYzWbUrN0Al86fw5IN09QF23jcqGrbOnfphjw5ayAiMuYy586ZpQRaVtd8qDGxNX6svQVFXefB+YmZYzzrAjw0AnvDvBEe5YrXah3Grfs/qtcGvf0upk75By9V34VixUvg2tVA3Lt3FH/99ReyZ8+ezK0mvOg8Dwv+R48exUlB5GSPo0ePKlHGG1+eOxYtWpSgSBij9VFRUcpZlTfaNPFhKtovv/yCHj16OOT7COnDgn/OnDnKQIZCjbViPPexrvHEiRPIly9fnPk9PT3x9ttvK4de/k3RRpHGv19//fVU0UY6M684iYAXHFqali9fHi8KPHFkzpxZ3ZTETmcRBEHICPDGpnjx4jh//jxc4AZPgxeM7hEICglSNzwUb0mFF7AbN24g86F8CH5oMb4glQcVw6Q5f+P27SfRrOPHjyvhdubMGRVlGzRokLpoJhd+xtatW1Wfs8aNG8Pd3V09P3X6LGsqjebcGF8krV3rFli6fJUSZ+FRlrRDXkEjKfKUYHti1OHspMflixdU/ZezkzOqVK2GHDlzxlkm+5t99P67yJS1AIZuKIK3clxKUP0FHRunX8iF0UvbIWzrPlzYMUc9T2E9/McxarkPHtzHpg0bcOnSRdSoXg0DBgxApUqVkrwNhRf/PkRbjwL/fAW9h5tDlmkKCcPFfsPiPP/NN9/g22+/tfseDmpcvnwZDx48UOnHjIJt3rw5USmLd+7cUQMw7FUlpPwx1HTceji7WzIGkktkaBDWftA4Ub+P6tWrq/MdU2U12GSapjIJvZ516tRJiTS2dUgNbZToSFqJEiVU8bcgCILw4sCRRaaEfDipPd5vegaMLY1bVhozv96iGjcnR6TxxmrZsmV4r0kT7Fl6SImiHP6+2HV4e4ybrj59+uDff/9Vf7s4u2D37t3q5owjop07d07UZzLFSWP8H39i+7atKgpGeNGdMmUKgkMjYYIZeujQqnkTdW2bu2Bx3IWZgSiTCQuXrlDpjJEmvodCybI8/suInJOeAk0Ho8kMg06HYkWLqMkeRqNJzffTjxYHulozWuO17GueWnqhDanOvZoLn9V/iMjI67gR+YmK5rGf2969e59E+ZTteBZ06NQZndq3SXBRO1NTpWZNUGYfDjYOuXLlSowb7PiiaISDKdpxyFQyHtuMhjEa8jT4G+bvnDfNvr6+uHTpkkpx43mmWbNmsmNTEF30f45aVmKisRT5+/fvx2effRbjeR4DO3bsQEKgUQ3nHTYs7gBDSmmjZyRTxIWOOx999BE2bdqkiqq5wWwnQRAEIX3BdEMKtNd+b4sfW56An1MU8jpFYXiHw9Ddc1WNODmCmVQYwaGQmXVkCvI08UWTN+pAVy0Ym7dtVrbYFFSsT5sxYwZK1yuJwEvF8OhiPhw5ng9FqxVXKSdMxUwMvD7Nnz8f7773HrZt3YJBE1rj/KVSOHa+LGq/VAbdunVD4NUrMJvMSjAtW7EGc+YvUjd42mQ0mRAZZcKD0AgEh0chNMKoBBpfizCaLCJNBxj0ejjrdXDmvwYdPF2d4GzQP7U/FCNhW7ZsxvXr11Cyx2CML70ervGkB/FjWG92zwT8uLgE3q95GZdDjuB65Fn4ZPFR223fvn12U2zKlS6RYIHG/cCbYUHQjEMcNREKNNvpaSIt7m/AnKBzAF0gp02bpv5mFI49q2jqwOdtIypCyrk7Omoi/v7+KkqnTfENHjKKynpGph7awsfM6niWuyiPTQ4OsL6R16/U0kaJjqS1aNFC/ct0EXt5+lrjQEEQBCHtwwsILa4NcML4TqdipNq56YDMxbxx96whzg0Vz/WsNaNrWpYsWZQxCK8P9oTCmvWb8PEnn2HihL8xde2fwNonzWVz5y2A48ePKaHhntULO2ZGwjN6+DCfcyR+m5QVTUudUKmKTZo0SdB32rhxoyoANxgMePz4MXqNbotfWp1SAshsjsTcIWHI8jewft1a9O5jqYfTxbKsN5nMSkgx2sVsRgoy6i6KMDaV5r/a/E56PQx6nZpHjfhq4kxnGem1d3PJdMglC+aqv+u9chP5nI0xBBqXffkhMHZcJWy9WxzXD6/GrbO7AQRYU3m2bNmiIg7xRRBt0zdjw/33+++/4++//1Z1PyyS7927t4pACEJq8sUXX6jaId6Q8/c7e/ZsdfO7atWqZ76XA0rjxo1Tf3OQhm0+GBFhyiR7rb355psp8A2E58WVRERjSezrkaZVngavNUFBQcpNlJE4RnTja9HyvLVRokUaL36CIAhC+oc3QNpF5fC5EtDrYoqJKxFOCDh9QvU0c3Nzi9G4s2PHjoiMtDhg8CI0efJkdSFj7j7FUWwKFS6CL7/8GkuXLMDatWvVKDed2Oo1aIievV7CtWvX8OW/9eCpt4gQDS/nKGvN3NNgLR3TIykW2VC63kt1MGnIZWQzGBFqsgg0y7oC3gbAydmMK5cvW2vItNdiwCgZBZmTDmERJkREWtQXUxsZNdPeo97HfzWRpwMKFy6COjWrWhd1//59BF6/jcw+Pti4YX309n+EXF4l0KPgSet8KvIAoEb7K9i/N8wqyrTt7JcnL3779RdVV2HvZoP7gKk+vCmN74aEdTpVq1ZVN6/cV3Qi4/bbvn27qgUUBEuBpYO2QyKXc/PmTZX6zOg+oyWsSaVAa9q06TPfS7MQLXLMNG3WFPH3WqNGDZX6KKQcPPc4zEBDZ1mOFoV9Fkx15bktdtTs1q1bcaJr9to4aPW9PBZZN/kskfa8tFGiRRrddmKP3NmGFwVBEIS0D2/UKdCYJjdpS2OU9Lisnre1kipX09InjJE2wpz7sWPH4quvvoJOp8eBs+WRxTkCa27kw8hOESqKwx5Hthc0CgbLgoEpkyfh7Nkz6PbdB2jR4gguXPfC0PaLsXPHdkRFRuH2rVijnuw/MzmbEhHx2Sbbjn4yMseRcqZmLvs0B3IaLNEpZ8OTKBn/DTbpEBkBZI82FGDEjGKM0TOjyTIfo2LapnDS61RKY0SUEQbOHI1Kw4mOoBGDQY88efOiSYO468poI6c4z3saUdgtOIZADDVDCbRPvxmJO3duI1sWH+QvkB8eLgb06dXdrgi2hdfop91U0JiFAm3pkVpomO02Qk16vPNTDcz5ZapKA6XYFYTUghH6pMKox+LFi9Ug0urVq6326bw5F2O4jIOLi4uq0+WAII8FDT5m6quj02w5kPk8SHRNGk/gml2xLVSbDRo0cNR6CYIgCM8JXnhoScz6ow79XkXfIpdjvg5g2jU/PLp2S0WlmAoXGBioRrQp0Jw9nRAcWBjlPUOQzyUKA/Kdx7tzPeFkcFJCzSrMmH43d4H699Lli9i7dzfqvt4HE/otRZ+8F/F11WNYcrgWQoNDERERjl/6L8emB1nBgFWwCfh8XXHMH75G2SjT7CM+2CKAdXUnLp1B7pr+6jkP/ZP0EmqoIJWyCDwy6dBkoCVFpkOHTirtkBMt9FlvFmU2KbdGWulbUh4tAszNhcYgFiFnqT3TWwQaTUL0emUYQvLmerq9/eVrt6x/FynqgT37gDwuMaOEd6Kix091BpQrVxa58/orgfZKn17PFGjPgo557Bv0xdwmaOV7G+46IKvBhAmf7ECVwg2VaBcEzYLfUVNKwZRG1rkWKFBApQRrvdUYVatYsaLs2BREyzJw1JRYPvzwQ2U8xZYyJ0+eVIKd57+BAweq1z///HP07ds3xuAVDa4CAgLUxOyQn376SV0D7XHkyBG7eig+6Fz8rIyQZEfSGH7u37+/Wnnb59hL51md4AVBEITUhRcVnqvZsPO9Oe3xTe1tcSzfJ1/Nj9errlORH0bR2IiTkawrl65gxt5GqJH9Blz1T5p9UcdUy3Fd5d0HnD1nFWa2XL0SqP5t2u4cPGyGB5v63sKtwKLYeS87OpTbicYld6t0JUbtoqICVERo1KhR8drqd+/eXaWavD+1DUY0PQ0XXTgizUWx7aErCrmGqYtciBlo+0kObJ253fre7j17I2euXDGWR6FmMQPRwdXVHWFhIUp8WerOdPDxdFaPKeoiIi0XZ5dYzcx27zuIO/cfW1MdlclIRIS1doJRQ43vf8sHD6cnVv4a044VAHASeXNkhreHC17q2S3Z4oyjwRxIZZ0FaVaOvXyevM6GBN7uudTxkZC6DUFIi3Tp0gV16tRR96W2dujMGrCNqAgvPt27d1cmHkOHDlXHQ5kyZbBixQo16Ej4HEWbBs99FG4XLlyAk5MTChcurAxBaFxlD4p+plMmtO8kBwwOHTqkGl4/N5HGL1ivXj2lSFmcyeZtFGj8MbC4UxAEQUib8OZbi4p9MbsphtY9Yb1R19IBj4a6KoFGAXPh/HmVOsgcfRqMrDxWHc2yXYkhKLS/N1zICzP2o3SZMtbPol09BQ2FTzbfbOr5s+eywWxJ+Vc4wxLJaZ39Jn5Y3gqft16GmrVqo3SpkkqgsXbKFo5E/jt7nhI+X3z2Me7cvo2fN7bAy0VPq2WpZeqABpkf4u2FxeBsMGPL1Js4vGs7smXLhiLFimPypImqX87Zi4HKmj/S+CR6RqHG4jJ9ZKTFCEQ5iuhipD3SDdKSRmk/GaVC2ZLWbTDt39mqBqJF00bquW6dO2D1uo1KJGcry/RHS5mArSZaPGQbPD294O3thfoNGiZboBGm/nAkN69naeTNWxv/zL+OOv0eWj/7rtGA7acWwc/PTwSaYMFRNWkpDM1CONlCl0chZeGAlpZh4IhlJQX22eRkD7ZhseWdd95RU0Lh+X3IkCEJNluyzTB5biKNFznm+XKkQisgZ7M49rZhcaYgCIKQNmnVqpUSaP3+7IFv6+2Pk0Iy9XgBvN5qLQoULIgfR49VDZ9ZrK8E2vEaaJrlbgwHRE2g7QvywpBmS1S0qFHjJpa+YbAYbmgX2KLFiiNvXn/8+8FKlP+vHHrnvwxKD9t1KOJnsSquW78+/P3zw8U9rnU8RzgnT5qAzZsshdobTlVB/czn4szH5fpkM2Bkz6UoWKgQBg56G7/+PBYz58xXAo3kyZkNYdG2+hxFpahU30kHhIaHW9JsWGumxJkOOr0ORrNJ/au3VaqxWLB4Gdq2ao5lK1arx5pAIxRtmzZuwLQp/6D16tdRMfMmlHKLmZp5/OhjlCxd8anujImBvc8o0IrU7onGI8ww6R5h865q+HqrHm/UOIPbka5oWCkQEVFhqq5PEByZppiS6Y6Eadzz5s1TUZLYN8YLFy5M0XXJyCQ1TTG+ZaU1GLA6ffp0gudnJI3X1Ocq0rQeAiy+o1DjBZxuXpIaIQiCkHY5duyYckhrNbwtxrbZby1I1rQGk/f6NV2nmkh/OPhTFfFhFI2Of91+aIGmWc7FEWefriuJMX2Xqr/dPTzw/bAR8PTwUs2VY/cwfbVvb9SrXUOlTU7/+ST6jotZY8Z6sT9/t0SM/Pzyqn8PHTqI8mVKWNP1mGbPepPg4GD0HdMc77W/gbIe9vu33Y8Cfh24EfkLFMQ331makdKApHz5Curvzdt349zZs6rfGcXZgwd3EHj5Mjw8vVG41A10argD3s5GHLiix7uvh6BRw06oXLmqjWPZ0+8aNIFGjhw/jXKli6u/9+/biyn/TEROv1LwN4Zh4b0iyJLjNHJHX41Ph7uAppmff/pJnGVq9vrPchqLjZYuumP2PmSliQrTLv2O4/Xfu2N49yXR29wPkybOVe6YgpBeYUYX64zYtJj3qfyX9UVMS5N0R8GRsC3E8yZBIo11CfZEGK1OWWTH6JoGaxcEQRCEtAUL6rPlMmDxK6eUQLM9pVOgDVmdBzAH4J33PrC6oNEkhPzQ+2Kc5f12Mr8SaN6ZMqFn75dQrVpNlU1BgWZ7vejepaPVvp85/v1fewOPM8+FTvekpo1cCtdh/aQN6rMNeotY69G1k/qXoqxhw4bWRsuLj9REG9/z8Y6uUvB1/zovQh4GoMvrb6l0QdZ1aamIC5f8h4cPH+F+UCguPZqHAV2uopRXhNoO4/dnxoBKD5WhBpffIL8Rm1a4IWe+n9G4SXP0fKmPUqkGnf5ZOs1KmZJF1b9/T5qCKZP/wYhlVTG48gPodZb6tC1BmXCY11SjMz55+76KSLK2hrCmgjUSO3bvQ/asmZFYaOq1aNEiTF1UFNk0PxJa/LuHIUulB+oxyxfo2ikIacGCPzkMHz5cleKwCTFrW3/55ReVrs26oty5c6fcigjPxYI/o5EgkSbpD4IgCKkPmw7TmW/atGmq7xYdGimkYtdt2YOpP0f2FIEelnoqjdtGHUrXvI97gQFo2aoNypYrj949ulpTg8q2KomCLlExomg3ovT4oPE65Mrth8+//h4uLs6IMJrhqnsi0Fo2a4wc0Rb3GkwpLFykKF7vH4AfexSA5rnBMrAy5S3GIt8PH2kVPxQrzPunSxvT9ZYcqY2Wvregx52npr+svpMd6ydvVKPoZcuVU4YmU2fMQuXKVbB//z61zMchYQjLMhFjO9170ifNDLxZ+aG6MNr2VcvmZEb7rzpi8feLULVmbRQuVAgmmBNcJ8F00dffeBPz5s7Gu6s64uNyx2Ksf23PR6i8swdCjkfgwrofVfkAa+94o8noIfvRab2e2Dw8MXAZ/P5VSzDNJlQ9p3rDUQAuv2x1xxSEF4Fz586hdevW1vMHB3h4TuJABP0T5FgXXjiR9vLLLz//NREEQRDihQKH6Trr169H4z5NULCSF9b+fEilD/I5GoJw1Hjz5s0qGsV+QbQU1kwn6ESVxbA5hjjgzfpbv+XBvcAzaNGyNbr37IXOHdqqui8KGbpfjV5SFDrdtRjr0qSTxdnw/cGfI7OXuxopp/kGB8wrVaqCcqWL2f0Oq9ZuUDdMQ74ZCq/8X2LR3soIiXJG96o71Ou9evdB5sw+Md7Tr18/JdB+29wErX0vWXudxYbPhZmBlTdzo2ulLfDw9ETnbjHTAjWBZjSZsXfPLnzzzeMYwTBVQ2EGzka4oKhrhHW5/Ot2VAmVLsl0Rf/8BWDQ6eDEWhtlLGIJT1mcIGMKt6tXA1Grdh007ByENYdqoLJvTIFm+RAA6z1xbvz3qhC9V69eGDBggBJrA0f3Q9HyV7F3RTYs/XuxsoNeunRpnGPjypUrqoDd1mmMQp5RtCmH6sPH88k+5OdfjzDgzOy5eP31163NfwXB5tfwzJTehJNyUZCsWbPi8ePH6u88efKoNG82JX7w4IHK/hJSjhe9Ji3NiDSOAiamCSB/IHLSFwRBcBx01mVN2di1LfFO6bMq+nO9nQGN2hZQ/WACzp5ViqJp85Y4efSoEm7Xb95Cx05dlHAoXrIM9l3ajNrRzooUH6tv+WLhqI0oXboMevTqjcyZM+PGnQfYvniZmoc3/feDLdbx2nvYZ+zUvjMoVKgIcuWITnXXWZpBR0aZ4hVoAReuKMt84p8vH8b/OQn/jlqLw4cPoUmz5ujatYfVpl7j+Kmzqub5oxmt8GbRgBjRrdjQZr/9lzmxccoWZMmaFV989U2c5WnfgXVox48cgZs+2r3R5rXlD3Ji2IQG+O61dajifQ8hJgP+uFAOWB8FnXJ2NKqG11RzyiCFwoz/MfsxWrNpHDt6FOPGjsa49XUxqCil3l2ryLT93JV7c+Do+M/UdZYijSmKbH0wZH5nfF5tAww6ILI4kMm/Pf737jTV80czP6FBwscff4xLly6px6wTHz9+vBLpvDH9fGoF9PK1RCm1Rt47TuVAyybb0LlzZ/z1119POeqEDEs6TXfkoBVr0SjM2Nf3vffew4YNG9RztOEXMpa7Y3onwTVpHFGNnboSHxy9SGwvAEEQBOHptRakb8lzViGQ29mIN0YXwUfNVqJopWJYu8gJeZ334qFJh08n98XEIdNQsmQplCxVGtlz5MCc2a1xvOIS1K7hjt/nReLvr3eiWo0aeHOQxXZYGYVs22r9zDr16mNwm01odLQwirmGKSH0wSye189gwOv2e8fEx47t22LcsxmcndGsZWs0b9nabr0Bo0A9unZUoqh/7ctxxBSjZoceZ8LZu5mwbw/wx8cbYYwKQMPGTdCn7yv23YbNrFczIzLKjKCgxwg36a2Cif/uDfZEEUMQdn48BzSmvBtlwIDxHRG52xln9v+DCGM4SpapoCJX1Gm044eeQo3i7MkKMlrHadKEP5GtYFW8VNgikmJ/TaZ5TjiWBW912K6il7yRZLSOjmFMd+xU7qR1qbxYd2t+Ev+LNoGhSKMhyKeffoqyTcvh3wUNcOuhO0a/dFjV73FZTPF6Y0hkjFTV+yYDZvzFdLBtyoRFEF4kfv/9d5UWTtjzir+nbdu2oVOnTmoARBBeOJHGiw27dnt5eSVoocyfFwRBEByH6nFVqSkizFd4e299/tFjy2l85D+5kNf5urohz6w3453eh7HoF18cOLBfiTSKk3IVKiMivCwm/HUchohIjPvlfWTJmiXOSDf7gJE27Tvh/LlzKFXwKHx8MyPkUSgiI8/izz//jNHgc8r0mSqKVqiApUlobJavWmddJqEoo/FGiZIlUb2KRfQcPnYKBfxzY+nyVeoawh5ooSEhGLayDTIZAqzvpdAIMQGZ8j55jvjlyaPSJcuULWd3HShAN2/cgHMXziNTJh9EGaNw+EEOFMx5UxmNUMfkdQlTwlcjq8GIL3uvQbMfD4CyrE7DZvAvUFiJPEYONRmopyU//4VONbnmPrhy6aISmqXeawWDbloMgXY2whnrH+XGP0uqYv+QkWjRogXatu+Ek2fOoUKFCvD391fz3Yt0hc7NUkfG998KsfTjYWrr0aNH8dlnn6FIvYrYPiUInvqrQB6g6mY/1C95UNXf6HV67F1aDm3eO2tJXtMB26/kwuIVw9C8eXNV6ycIL1IkjemOGhyo+eSTT9QkpDzpM2E24cROO38a7dq1w3MTafny5cOECRMSvFA2EeTohSAIguAY2O8na5fyuBl1AzmdLEIi1ASM7rtC/e1isOm1pRo6m9QAGyM8/FfDxcUFlSpVVn+r6I+ZER3Tk/ks/1MXRTdXNwz+9EscP3YYZ8+cgZu7O0aNHK5cGjVY58H3shF0xXKlYqwzl0fDDlrcOxks9VoNGjZG/jwxszJ4M2X73vVrViqBdulSceR1sfShiZEiqANuBxbD0uv58UHj3ShdpizeePOteLdd4JUr+HHEMHT4qSba5PPD3x8dxe2zF9G74WNM2lQCpbzvYe/9HOib+2KcaJezGz9XD7+8/mjRvity582HkKBHCHr8CHqdGWYVhgOizGaERESqtByz2YRdu3ZYInQRzrgXZYCXy5P9s+xMccycXhUBM39Sy+7YuRtcXd2s+4dudPXqN8DLvS9jxTxPJR7PhHri3fZnVVNqGsX0798fXlmcsfPfYHjaBA0rej5UA6qqnnBtR9QteAnLb+aE+91IrN9yHaO/34Q333xTReEyqmOa8OKbh9Bwh/+yTpdZYEwV5+BH6dKlU3v1hBeEDh06xHjM86nttdb2/MqMkKSQoO7TFy9eVBbAiZm0kUBBEISMCPuLMULCqAfTz9asWZOs5dHJUXftIoq5WFJ5iLseaN3aE/ny58fQLyJUvRhhLsPEdWVw7+5dVKpcRUXRaJahagT0OusgOa0+jCZLhMtseiLQEJ3KR2Hl4mxQom7B/LlYMG9ODIFGOCBH0xB+sm07FjJlxiz1uVzOK316KRv82ALNHkuWLMG7/9RHHmfb6JvFWp//euiALHoz+ua5iM7fd8Ke3bsQGhq/KQAbR0/fURaT217A0AqnsH+VG8rVaISw+9cxppcX3nmtAxpnuxZn1PKRCRi7ryaKZq+Ia1cuoWiJUtAbDPD0ymQ1IIk0mhEaaURElEn9febMaey/OhYLJgUg8mpRTHtpLvycjVazE/5bx+cyAqaPQpDxHtp16AhXtijQwdom4N/Z89ClWw+4PHJWUcxMeQJQpcgh5MjiiwULFqiL/4EDBzDqrwrI6mRZsNLXZuCByaDqyL9d3AwflD6GKh6P0TbXTdzw8YJT4Gtqvb/99lt4esbsUycIMaApjiOnFILGSaxH2717t3KnDQoKUs8fOXIE33zzjezkVLDgd9SU1lBp79ETr+/MgqD7LmuBmbnBOvJKlSqpAYKkkqRm1oIgCEL8TJo0SbnzERe44srlK6rx5ciRI1UNUWIJDAxUVvtNmjRB8KdF4Kp7Il7u3fXCawPfxE8/jkT+CmY0H1gDm2Yexp3zs9SNOM06ihQrplLxogNn1ggb0eljjv5pQo42/KyTehZ7DhxWIlD1DbPhwOHjMCmBpsfLL1lcFjWnyafRoW0rvBYVhS61g+LUoZ0JdUMhtzC4RH8UX86fP1iNUtJq293dkg5oCy+YFE5Ns1p6lZE8zka0HpwDR7rocOD4Mnhe2oyszrnimohcz4dbM3IiOPy+2hZ6gzMuXzwVvY14kTarSVuZx48e4q/fxuJ8QH5rn7VKWR5bxaWaTQd4egbjzW88MeFXHWrWrGX9zE1bdyIwkOmsUCYi8xYuwcN7tzBtxkz07N5ViX3erJwKuKDWL+ihxYFSg3V6/X4qALP5FBqXtPQs1ertqma7hX3GByrKJsZewrPQRL8jcNRyEgJTgIcNG6bMlGyPc/52GFUTUg7W6mrtTRyxrLTM+++/r8oA6tSpY32OKeU036KDLs2enlskTRAEQUh4WuKgQYPgBGfURkvU07VFHbSGu84TX375pRphSyxbt25VJ/9xv/wPb7wXhauPTHgYbsakpe5o3fYL+PnlRd9X+uHxnUeYP2w1zFGP0OzV6ggPtZhXzJ01UwkvCjID66fUyKRFWFhqlXQwGPRq4ny9undJkEAjZ06fUTdhhQtH20ZGc+TIYfUZUTa1aE+DrpKsbVu0dDmy+fpi/UH29XpCsAkoXfgott5/Eq27b9Rj6kfH4OXtjSw+T2pRbEVneFi45d9Yo/m3zmVS37de09ZwcXXBrsdP3k+47j3yXMbjzUtwLfiimu/m9WvIlccfmXyyqigaUzxVNDI6qrZv1w7os+SAk42IJlejbE1FgFJZjBg50AOTFufDsKHfqNo1QoFGwUsYVStXujjOXwpEnbr1VI2ZNpq8e/cu1G/YCJ++fginHrOXnMXd8t0ZBbH6l1Vo3rIVtp3JFCP6ePR+NkycOx6vvvoq5sxfhNBQS62bILxIsFaTrUpiw9YUbAwvCM8DptbSHTk2fI7ZiElFRJogCIIDYYoNhVoxlIe7Wxbo3N3hqnNTjxnxYSPqxDBr1ixEGC0pcJ5eXmjV7jss2vAZ5q77Ck5unyCzjw/OBZzBbz+Phd7FgPMXS+LmrjxYOfweQgLzoGLfjlizeiVu3LhhLb6ONo239vVq27JZjM9MTE0xBQr/uxNtrz9zznxVh6YEhZlpk88eAqVpyKqVK5RA4dSufSd812MbNt7zQbiJLot6dB3qp+Y9fs1JPRdpBtbczIkL507CGBWFiCijSrukgUk4Uw+jTCqVM1OWbMiRMxe+nldQpYPyvfMD86KY60XM/K8ImrXzUaLr85/r46+b+WKkJfLPO95BavndX3lTLS9bjlzIk68A/PMXUsLMzd1TrTPnv3P7FrJ5eGLmzcJWaxeKpLxOZgSEuyAg3ClG76BGhUNVOtaK/ywtDwj3CSOPjDpyO8auaZg6fZZaMfaja9OuI8oUPw63fOeQOe9ZTP5sLdp36ISePV9C0J56+N+JvDgR6oFZgbnRvdImS3PvCpZ6RHf3mCJYEGJgdvCUQvj4+Kh6zNgcPHhQOY8LKceLnu5oC+uEGU2zPfZ4zf3oo49QrVo1JBVJdxQEQXAgTLUhOX3LwZjLE65hbjCFhsLj6iP1PJsOJ5SYN+mWZtG8VPl4e1ojRoGXr2D4sKHq8aWzReDnHGV9D/trrfrhBHLP0OPYkSPInTt3nM/o27sHpv07G2FUggBqVKuSqO+r9XIODgmOsb4ULozcPeviumHLdly8cFGJGW2B1WvUxLWrgWhaZqk1KqbTnYHeAAwqcxNa0mTX3Ncx4dXXsHHyBNWoumJly8WQcaxIxrhoimIyo02n7hj/0W9YMDovSvhXRuePLmFw98cWIVZ+D/YfDcOySeMw+fyHKPa/R6jv+UB9p2UPcqJwnsq4des01iydj1cGfYiDe3agYpXquHTxPPIVKIzLF87BO1MmuLq5I1v2HNi/Zztmju6J5e2KY1695fCK7p/G5tiPop4YoPBfZeOvc8LBg/vRu09f63e13Y4ap89exN69e6w2ZxTZnTp3VQYjRw4dUgYk5SpUsLrbFS1aDJEXC2Li0kOqd+nQYS1V7WJsaFd+5swZVU8oN7FCeoeN4JlSzv6BPPewXoj1wWw30bdv39RePeEF5Z9//lERXNag02yRXL58GcWKFcPixYuTvFwRaYIgCA62yq/StTTW/LLVGrmaeTk3xtQzABFAjRo17L6PkRLeVNDpkLVIdE3kTbu15ilaEDFFz/pYp8O4saPU36N3t0Rup7Nxluupt7g8GpwMT2wbARWt4Q0MBRoFoJuLRfqUL1MiUd9XGZLE7hGWQMvkK9dv49y5iypl0JJ9yeie5bUuXbujcZOmKm2SKZg5cuTCsk2/KoFmre9iRCi/pQ7t1MkTKFOxiiUSFh0F0yJzJcqUx2vvfIJNa1dg36mN+KtanidukWZg0Pt+WPT3FexdMxIf/PUD/BtcQ0SkE25szQP/0Ctqnzi5uECvN6BS9dowG43w8sqMa4GXUap8ZRw/tB9eJqBJm87qM65u+wfmk6VhqB/z+3obngg0/rv+fk44OV+yRMmia4BUimJ0TwAtFZUogWZL9DbwzZZd9YZTaZLqbU+2vLOLMypXqRpnu3Pfcz/99NNPGDFihDXdko2wWU8pxl+CQw0/UtA45IcffsArr7yiBhx4jJcqVUr9vijeWNcrpCxpPADmMIoUKaLMadif8tSpU9Zjj3XkyYkCJlqkFShQAP369VM/Ak0tCoIgCMCOHTvUZlg/LsIqNnjv3DPfdbxnfKweM+WMKYw9e1rMNCiUKAJmzJoLPz8/eHtnUgKNqXXqpj16w9qe6HmTzWhLwJnTuHfvHvJnL4YGvoF2L4jrL7I2SYeKFStbF9ajayf17/SZc6xOjoyktImV9pgQXJz0CIs0WoTaEw8N6zqznio+NqxfB/qN6E3RNXLRF3Wm/HEhWbJmRf0GDdXzly5ehG8ejxjfkVrm1sHMVrFIq39boeifr5CKeDk5OaNIyTLIV6go9uzYjCthp1DIJcIqik48zoZyJavjyMndCBg3Epn3vA+4uyD3xRvIUt4ZUSeiUK9pG8DghL3bNqBS1Vpw9/JG7nwFceTgXpQoUwGP799D5qzZ0Of197B2xUSsWX4GHvqYpgn8rN1BXsjrGoqToZkx6of6CI/YirJFKqjvq7631ewjYTlilm9q2RbEYPO8rWCLzR9//KH6R73SZRC8Tf64evs4/ts0V13jWexO23Ja9b/77ruqLYCQsdDxt+GgNEVHLSchMFX733//xdChQ1WKI8+vFStWRNGiT4yDhJTBkWmKunSg9riOvL7Xq1cPrq6uDlnnRNekMb+S9siFChVSo26zZ89GeLilMFsQBCEjs2XLFvWvs825OVpv4L7xhnq8bNkyVWNGkcWJQklLb7t27RpOnz5lrXF6sgxL/ViDhg2VoQTn583H33+OR5kmpXHwIFDJIyzGe1h7NWxGBNrX3o/uPXtbmlZHM3vewpgpdTokSaBZ3mpZN4pKtd5azZtOhzJlyqJw/jxYt9GyXWzh51OIUMwyOEi3RNUgOp4Le9Zsvtg09xpuRz65bEWYAW+3C+pvjpZnzpodRqMZUcwj1Blw8eI55MjlhwJFiiGzTxb4FyyKe3du491RRbAjJBMCo5yw+mE29PI7j4Mb7uHMqeLQuQTj6rX5yOpyHvd8DmLm3LFo0q4rrl27AqMxCmUrVUekyYjwyEh1IS5fuSbc3NwREhYKN3cP1KzfFJ//WQSZDE92hrZf9oV44r1+jdHu0x74sk9VHJr9oxLoPXv2jiHKrCme9kSWirhZIqycVNpk9Ha0RBCffkdMgc5jhzexpRt3x95mubC2gQlXcpdEAX156N08YTS54+a1IHz88cfKDfLYsWMJOhYEIa3AViFdunRBt27dRKAJzx2eU7///nsVweU5k63IyJAhQ1R2QopF0t555x01HT58WOVgcpSNTmYMJTPCxp4AgiAIGTXVkay94YM2fg+sz1NzvDKuGaZ8sAYDBw7EL7//8USIqLopCpzoh9HRHWVfTDdGg6VPWb48OXH+0lXM2LxJzXf+3Fllrz9xbHFk0t+0ftZjI3AwODMaFt+nHn/08WcoW66c1WnKnrukFllLLAePnUYkI4Gs/VDiNFqRRnPs2FE1xcZWIGpRM359rU2ALcFBwViyZDH27N6p6q5YZ6dtIzc90GPwTRTMnh8de97Htj3fYv1cd7Tt0hsly1bCmRNH8ejxY/j45sTNG9dRsqwfylWugfGjv8UnIcPwOK8LZrzxL3yiG4EXymTCH/NK4aN+d7B153IlugZ9/gPa9+qPuzevI4iNu3U6uLu6IioyElFm4OqlC4iIDEfBwsVw5OA+9Z6wrF70j7R+h2tRBnx3rip2bigJw5ENOLp1nXqezcHffOsD5WbJY4DyUzsulE7TxYyGxWyU+mReRhFj5JjyNZWuFjfvlMKSjawfG0Lw4dj7KOy2DKdCs2GBbxnsHfsAnvpcYFVjgykt4DrTGVuO/YwGDRrg5s2bCWqhILwgONLw4zlH0mi3n1DGjh37XNdFyJgW/MOGDcPUqVPVufW1116zPs+efePGjUP//v2TtFydOaE5FfEQGRmJ8ePHq0JN/l2mTBm89957yuY3PYQnCRt/ajcv7E0jCIKQWOjqxBTwuj1rY9nIa6rRtO3ZlRbyff6siqXDZqo6oXfe+0A9z1NwVPRNNqNJKmoGHZo0a448OZ/Ywsc2kzh29Ah+GjUSs/c3QFe/q9HLAk6EeaBcocPq8bff/YAChWJa48eH1sssMdAyPzzSpASDK2vennLKZzpliZKlsH3b1idP2l597LyXWRpLdo3D6C9NyOkcgZuRLsisj0IuZ9bvWeZZdDM3OuR44qg1en9efN52I15//3O07dwbAaePI8JoQuGiJXHs0F4UK10eb/VsCS/vLCiTtR7GLtqLoi5h6iaA22/N/exoU243urwyCK+8/wXu3LiGLFmyWgXljo2rUbxcJfhk9UVYcBAvosogxd3DC+aoKCyeNRlrgy9h6mcnUdH9MYJMegze1wAXJ/gDR87iTMhKBIc8Qpfer6Ba1SpwcbakEvL7MHVUO2ZU7zkb4xUVpTRZPktLi7RFRdfUe6IjjXYEGvfxnTt31Gjvt8sq44Oyd+CiA0JMlsnXZtiWnRMa9++HO5v/w8nQ7Vi/fr1qAyA8H9LKfYi2Hv4/D4Xe3c0hyzSFhuHK+18/t+/GHmgJgb+lDRs2OPzzBfvHUM+J2+HiwQGr5BMREoRZA2qn+u/jaTVpf/31Fxo3bqz68zGQxYxD1qfVrFnTWvebYsYhFGSLFi3C5MmTVaEci+GpFJmuw15A69atw8yZM5O6eEEQhHTF7t27ERUVhfcGG+FmR3B46oGFg/bi60btMLzRUjUvIxNMWePsTk5UdcDLfWKKpYNHTijzjNgUKlwELi6umDIkCyqPv40CLhF4QEEwwpLWOHzUWPjlyhX3hj3WzTv7obFxdVLSOyKiLFE0F+dnZ86zR5GtQLM21I5O0+vUvg0WLvlPvcYL8fVr13Dy5HFM/S0cWfSWvmM+ruGIZIwqSg9vgwnbH/kin3uQek3rCday9D2srtsFE38dhYo16iGPfwHonF3h7OKCGg2aYc+2Tfhk5P/w58ivsergPyhzoSuGFj8EV0YhTcDve6qhckUPbPhvPnoP+gie3plwaO9OFCleCh6eXihXrQ58smbD44f3cWjvDlSoWlsJqx2b1sAvfyFk9s2BS7+OxMB8P8CtUAhC77khywYdAtdPRmB4AAwGJ/TsPwjFS5ZDUDigj4xU4oxQrDvpdWqyFWjQooxUktFP1a5TV7U9qFS+NGbNXRDdVCHudtXmp4snWbVqlWoR8Xqpu0qgETbedo0VJONHGQ2AByw3WSxzEJGWgUhHxiEbN258rssXkkZGqkm7evWqEmr2rpPUS0kl0SLtwIEDSpix8J03GH369FGhvBIlnjiCaYVzgiAIGQX25yE3H3lCl+PJ87GvLUNLnMTfefRqZC1rVktjZqdox8aatWvHmJc33PYEGqG5Q9v27bFg3lx0b1sV/tkrI/DOKew/sgkdO3VBrlw5lWuinjdItusQ/XfnDm1V7nxS4HpN/3eOEgOsgaI7pK3rpGWm+C0etQQOq7mFDmr0MXduPwwf9h22btmsLm5k/v+KxtiGjDv9fqY81o0sDOd7ERgwbjcqZ7LY6VNYnA3NhExRJdQy92zbiEZtusDJDOzbtQ1lq9ZEnvyF4JnZByMnzcdPX7yNhd/rcPS9liiT/Tq2nisM/bLMyOxyDXdv31T90biu4WGhCIuIhEkfqoxdHty7i6iIcFSsWR/uHp6ICg9HpZo0AYlApVrZlNGGx5INyOpRC6aQIJgfXMBN02VkyZYdvV5/H1l9syOKkS+jGTqTTkXAnAw6mCPNcHEyWBqPa6YxNimMtlDwVq5cRYn4GNuVN0axtjebkz9Jo7Rs+8w2NXOay6XV8VL1vwPczt/D6dBD6jHTdIUMRDpKd7TH2bNnVYNh3ouyJ6AavEjjN/ovGhbHXsctKy1TunRpbN26VVnw28JWEDSuSTGRxoZtNAyhM1SHDh3sNj2l7WSPHpZRO0EQhIxAnTp1VLrjhA/vo8y/mVDO8xEeGvXI5WRJB9Tg3/9MKYxLZ90ttUPRL9IQxLbmZ8fu/QgIOGP3s7TeZm3atlepeGxWfez0EeTMlQv9X3sddepavN+1ZTNKReHAeiRHwM+mwLJk1ukSlr6o+oLFbCfA9evTq7t1pPGXsaOwbd8OTNzTEDk8QjBhYUFcCD+Cwm7h1jTACEYt9xfE5Q2zccN0Adsb6uFzpBbKed/DqdDM+G5WS+R/dEsZcty6eU1Z52fK5INqdRsj6PEjuLq5qbVgDZhf/sI4OHcqCrh8iy3Z8sLlYRS8j1/Drey34F+oGNw8vFW6Y7WGLfDwwT1kzuKLW9eu4PTRAyhbpRaijCacO3Uc2XPkgrOnF+7evYbgoMf4ZNQf+HHwG9A7bUeWrL64ee2KEmgvv/cFfLJkQ1hoCPQ6M1z0eiXQmFrIiKSnlzciQoPUd3Rz1sPIbRxtwmIPfsdTp05aDUO0VFlbYRc7jZWDqLxuB5sRHSOzHJOs9XsYBXixU4QZ6PdpMRw8OQX3cVtlypQsWTKph4sgpBiM2NMshNE1/h4CAgJU2tmAAQPUQNqYMWNkbwgO55tvvlFBK0bUOMC4cOFCnD59GtOmTcN//1kyRFJEpJ0/fz6OUoyNp6enirYJgiBkFJg2SLfbVq1aoWGZECU8OHp7MKAsynmFqXk0obFprQ5lSlsaUvPm3Fag2WtkbE8k2Vrcc8qfvwD8/XIgZ86c1ggZl5WUWrOEwoiPJhCU8UV86S12BBpFIyM8hOLxrbfewooVK7D/XHlU8ListlXDV++g9XcVMLDfLVTLfRv3Il3w2+7qiJwYihD3B/Bx84XZaMKQPu5wLdMH+gggx7F78CphhvFEJNp07QOvTJlxeN8OFClZDk7Ozjh+aA+Kla+K7DmyYchXIfjivSI4fHAybp5vgHP3c+Nc3nM4sHUT3v1uLLasWYqqdRrD4OQEM9M7w0NV0+rSVWoiW45cCA0JUhG3rLnyKMFFAajEX76CeHPIjzh95ABCgh6jYq0GKFauInLnL6TMQUJDQ9X3ZjTNoNOp78pUR4pIpjpG6cwIizSp6BoDlJys8TGbzWvtncbdYIqOgumg2hYUyGtJdV3y30q0a93Cul94fHz33Xfo9+MczP4sJIbF89UoV5T1p/kN91WAeo4CjfVoQgYjnUbSPvjgAzUIwUbCtgML3bt3V6+JSEs5eD2wVz+b1GWlZdq2bYs5c+Zg+PDh6lz79ddfKyNFujkzsJViIu1ZAk0QBCGjwgJhptnMmDFDpdrMn78ANcsew5UzRZA1Oung/AMgn/8H1uha9y4dEyXQYgtD21S22DhaoAXeuIP169ZaH6ssOf6fJTMRxui0PdjURlHAmW0jPTqdigTarjNHvWlAte1UJZR3t/STU+6NOmDBkEOo260UTuzcjJwehWCI3IhHzjcRFPIQX3w9HmEhIfhl2GfIdfccShaphHseN/Dp+7cx/beiCDe/jR/m+uPOtfrIU6g4smTPoQSWu2cm5HTrhfLet4CsQPUCvBRuw6R1RiwYeBsDPvkOVeo1we3rgQgOCUZQ8GMc378LRUuUhV/Bwrh/55ZKhXz04L6Kst26Hgh9qA7ZcuZGVlMwMus3oHGTgihfo56y5w9+/AgmkxERYaG4duk88hcpjivnTqlkz9wFCuPaxXMw6JyUc8z+fTuxc/M63Lt7Bzlz50azZi1VuozqJ6fZYMba3ZaWDYxs6q37nC0J2HuPrN2wGc0aN7DO7+dfAPnvNsP/5i/DO10szpaRZqBH/4eq4L99p05oULcO2rVrpwxfBCG9sGbNGqxevRp58+aN8Tz7pF26dCnV1kt48WnevLmaHEmSjUMEQRCEuPCmlg63pHK1mnj48BFee28tIsIfokjxcihfviIyZ9areqIDB/ZjzvxF8W7Gnt064/ipswgKCsL58+eea1QsIdy9c8f6txJZ0XVTJuVkaTFA0RpbK6fK6Bm0Xmp8j73vwHYuoxbVRs3MT2zrNXycgA9+D8bHVbPjZsh59Vxev0Lo0fld1Zw6u19e5CtaHDP//gV7D25E70F50biIRTXSm+7DrleRPe83OHl4Hxq16wZ3NzcUKlEO+TzvxKkX7NHICQPDQuDm4aVSVvIWKq4iaJERYShaugLcvbxw++Z1Jbi2bViBRrUfIxPO46GuCQ7tuoZyVcuiTbEByGQwKmH651ofzF5SDF0HvIOzJ46gRNlKKFa2Ek4f3odCJcvixpWLuHQ+AIWLlkBY0GNsXfsnfh56VrksXo/KhQ4vOeP3X8agzyv90LBRY6vQtUU17qb5jE6HyhXKqsd0V1u8bEUM51EOAGhpspynXPkKACpg/rbbCA7diy2bTOhYpzg+XfJRkmsVhReIdBpJCw4OVvW6saGrqaPSvYWEYWkT4pitpUvbgTTFgwcPMH/+fJVxOHjwYGTNmlX5eDB7gY66SUFEmiAIwnOADoW8Gfby9kKHjp1jvObm7qYEmj0KFiyEerWrWx9XLFdK3WBcD7yY6vupSEF/HDp0UP2dI0cOtGzWOM48+w8fx9FosxMtRa9P7+4qyhMfbPz5ejFLCqA9qvjcQgGPSjgUtBpvfTkCNRu2gJPBgExZs+Lgzi1wcnLGsD/+VRGuG0FD2LHO+l4nmNGwzafY+N+PKFu1Nhq06Yz1i+cg/+vuyOoRHKNNQohJhzLFi6JWiV9RJMdmnLn7Pg7sOoXq9ZvC09sHwY8fwsPLG0GPHqBx3cVolPe0el+5rKuwbkVteHhvUQJNo3vjR3jnlZlKoL3x5Y/QOTnh+IE9KFelBq5ePq/SImkU4unhgXOnj2PQB5fh62RpL5DbKQoj/sqMb/o0xMJ5c5Wbo6uLS4xIGg1btIcUcPsPHsX+Q3H70mlQoNFNVO2baPGcv0A9nD6VAw0bQdUHPm0/CRmIdOTuaAuNQlgHxMbChIMXHHAZPXp0gq36BceQkdwdjxw5giZNmqhMhIsXL6oaSIo0uuAzgstjMinI2VgQBMHBsB6NkQxNpPAG2orOkuJoDzatthVoGr6+vqoYPjYUgTt37lSuUrRVf57wRmf+oqXWx/YEGqlcvjRe6dNLTX1f6qFaCti78ee6b9u5V/Vac/f0wvkL4XaXRxF1J9IV3lnzqceH92yH3mDA4X07EfTwAfIWKoZMWX1x8ewZtY7TxlzEQ2N0bzEAC+75IyLCA8XLVsKuDSsRHPQIF8+exNtLGmPt4yy4btQrE41bRh2+P1cJ61eZ0a2eCyplO4lmBd/EmcM7cOf2Ddy9cwMHd21RaY6Zs+VAhVyWmi3iqgeqNjqG/ecuxFj3EJMerVp9i8DzZ/Dfv3+B8q1EparQOzmpdadAY83agT071HLd2VzPBnenKOQ2VEBwcBAunj/3xFpfQwfVAy7SaAbNMKPYFN1kSX2Mva2ZEqkJNNv3F8qfBzly5lARThFoQnqHYoz9qlq2bKnOiZ988onq37tlyxb8+OOPqb16wgvKhx9+iFdeeUUZ1bi5PekvyOOQx15SkUiaIAiCgwgLC3uSvhgd4tDHEmqacGMqI/tbadCBkTb0zyIkJET1oJw4cSL279+v+q0RpvKwaJkXi+eB7Q08a+GSM/q5YvU63Lp1y2KYYTSjWIlSuHXvit15udUm7KqB8EeB6nHhkmXh4uaBOg0eoE7uTnDWmfHfjazoWX0/SpavggWzw5FJT1ECJYqm/FcDrleD4ObpiaCH11E8z2bUqf4I437chg9uvY2InFHwzhmMiFBn+F0OQ9bi+6yfnc3FhCVjd+N+5B6MmN4MBUp2UYLp7p2buJvVCVkMT4Rxx/LB6PBmJFpU8UZF9yA46QA/pyj875d5+PSL3Fi9YScK+k5B3Vyr1Hf69YIB7/S4hSbtu6Fx2244vX8xzlyMQunSgKsOSjj+eqgaDHqL86Uzm17rnogu9qjjtqNIY08152gXSJYE0s/Ftqe11otPSz21dRWlKUjPnqmbRiukPVQLCAelKTpqOQmB7uKMatCBnLW+TH/s1KmTMibKnTt3yq2IkKHSHffu3asGB2LDNMcbN24kebkJutIm5qI/duzYJK+MIAhCekKLXu3aexAXLpy3CrU1q1bi9OmT6vUCBQqhddu28PGxNJm2dV3kxOgPp4QIH57smbJz6tQp9bhsy5KY+rsLokx6fPSVBz766CNl7tS5c8z0SkfTpmWzRM3PGqlFS5dbHzNNjyKBYuPK5UtwKroRPRoYEWWGEjcaFHGBkQacX5kb18ItNsbV6jfD3q3r8GXvSfCIvvvrlPseXp37Emb2XYD8nrmiU/ksPdUaVjqDOd9ewHnTAVw+Wxw5Xf9AjT5AlWpuGNR5Frr2LolXmx9HcIQzRi+tpBpae8VqmeDjZEavzpvRqNZsfDhyPA7t3Iw1ETXxS/VtyOdsSW/M7hSFOb87o/lfrTGl/0pU9Xyk3uvvGY6Zvzjj0D1flMuyyhoI+6C5Ecs6tsSS6RNxK3AvVk57BI9oYbX1kQ8+W94MukkPcPXRCvj6Zkf+ggWV4qJ7JC376f4YaeTfZiXKIo06S1NsvR5mblub+K0mr63um6nQt0oQUiKDgS0meLNMB1NBSCkYPeN1Lja04c+ePfvzFWkHD1pqEDQ4ekvnqOLFi6vHZ86cUSMWlStXTvKKCIIgpBcoLjQb/NgNhidN+MvaiJkEnDmDtWtWoUnT5nip78sxBNdnn32mbHsp7Ci+hg0bhlq1asX7uUzdCQq9j3/3NUQ2jxA08LkHZ50lkrZ6bBDybPfFF1988dxFGvPuE8PD4CepjIzqcOvoYUZoRCTOPJyKGa9HR3ps2hRQS4SZgWH7a8Pr+D3cCg2Em4cnjh7YjWJlKsJFR7OMJ5+RLXsQGpbvjWuRW5DP2RJ9ooTecysvHuh2oU2v7MjpatlWpHExE8Jdj2DYZ4+hdaebNH4Ddj3OipxuQchuiER2m4bP7q5sG+CGP77/BB1eGYSpb43HppWF0NfvSQQwq0sULo8ZD6/X8sYxYayQlS0ZnowI682AZ5PsaHq+D2p12AQP/ZPLcVnPhzAvN2L3ifHq8TsffqpSGqNMRrXMkHCjiqRFRgs0k85yMee2jYRJ2fqziTk/S1lXU7vZbKwqVati3769cDFAomjCC2McQuv9Y8eOpfn6pYxCRrLgb9++PYYOHYq5cy2OujwG2QaC1/jkXI8TVJNGe2RtYi+ABg0aIDAwULmWcLpy5Yq6wWjdunWiPpxpOl999RUKFiyoOsKz4SC/pO0NDnM8teJDbWLfFlvCw8PxzjvvqLoN9mijbTDXTxAEwdEw3dCeQLty+TIm/v0nPvirA3YGVMTjwKKIulYUYdeKYsB3DbBu7WrMm2d5X+sWTVUPlZUrV+LdVz/AN+98j4f3H6JRo0bYt2+fOqfRSnrJkiWqOat2vuQFYNXGnOiRJxBNlEBDjLqonl/UUufj50mPrp0SNf/5y9ewYf069TdFBMWFs0GvzuXHjhzBhI8sQkNLjbFNkZl7Jy86ZA7AvJXLcOhCcVR+vxbmjP8C3Wu+G+O7X4x0wsqDZWC864Tuf5TH0TB3BEY5Ydj5cri5KRdK+FfHjXAPlQKp2gGYoYTZub0FVeRO+0x3HdAw0z1k0xnx5ZGaeBh9KaLE/PtSWTQs1Vc5Mt64fAGR96/B34nmME/WI9SkR4Vab+LP3dmhyUHt8xgl3Bti6Y1HDoR54OKlnHB76IujJy0CTpseGA0Iz5cZxfKUg4uLK/IVLq62W2i4UblnPgoJw+rlizH6m4/x9YdvYMKvo3Dy+DGV/sjJIugskTRtWzLNUbt5pUBr0LCRCDThhaNv376YNGlSaq+GkMH46aefcPv2bWWoxT6Y9evXR5EiRVQJww8//JByNWlsBMibhyxZnqTu8G+OADPMzHSbhMIizj///BNTp05F6dKl1c3Jq6++qkZpNQtr0qJFixjNsdkE1Zb3339fNYxjI1naX3Md2rRpoyJ+Wv8hQRCE5LB+0zYEBsYvgDZuWI+Ac6VQ0P1ojIgJ26ONf+0qNm4tg+VLl+LyxYsY+s1XKpL28/t/YNnPFgFTt04rhBUKw9tvv63cDlmzpaVRDBkyRKWdU7wVc7O4IGrL10QC/1k/7QwyZcr0XHa01sMtMTbWjBBu2rgRBr0eRjMjPHq4MXxD4RNpxI0bV+Fp5xRt6asG9MoeCOcclueyGMLxv9eu42LTOsjpct0637lIZ3Ra1B2Z1zohNOw6+hQ7iHLuloV+XvAITl/PgbP6mzg87xJmDqmLTlmuKTHG7cfaL205tuIwl4sRv1bYgV57G6Nozrs4cisXbq7yR4G7lv3PptQte76KO1GHY0TzLke4w9nkhAVv7cZ3R/zg4mTZOaFmYPEDPwyb1xyNGpyAi1Mk1hwtDZ8DTEsMRrOm3gg3R6l6shtRBnx8qAG8LoQj4Np5mJ3MCA4JVa0DKG4fhUZB5zUJCyY+hBm++OtMXfzd/xQm/zEOfQa8hXIVKyOXnx9u3byu6tLMjKgpExVLtFITanlz+Sb2EBCENA9TzFmvu3btWlSpUkUN3NsiJTkpR0aqScuUKRO2bduGDRs2qOAVg00ciKXjY3JItEhjzuXNmzeVqLKFNxSPH1uakCYUupIxRKhF4AoUKIBZs2YpsWYLbwpy5coVr801R02mT59u3RhsJOvv749169Y5vLGcIAgZiyvXb1sjQRqqJ1isq0aDDrdQwC0ihkDT4M332F8zoX0pwLV6dkTe8IL5/Hks/2O9dZ7j207hsvkqgvAQRWtVRJffW+PMwdwwbD+JL7/8EleuXkeRosVwL0qvbNoJ/5/BHkZpfj9UFKd3rXhutRg1a9VGsUIWh8WEQhMVvQqTcRvoEWU0wclgSeBgXZVX5uy4GWFATpcntvUnQl2QWW9GHtdIlephuz2zOEUhMFamZbhZD+djLtAd2I1dd1djftN8MJtZ8wZV49X62zPoV30rXFzdMObnusg9eC0aZboXZ11t0ywJjRab5b6IKb82hD7CjBzHbwP5Q6E7qkdURASad3sVQXfeAvyevHfh5SLQh0bh23E54GOTKnkryhlDl7RC9v1G7Bh3F66VyyN7eAQyPbgNl4rr0K+GZV4ux9dgxMTK63Hib290a1MEN84ewZQ/f0HFarVxeP8uwBSGE5sN1hTND0qcwKLe3eA0eylWLVuIZq3bwzeHL27dvAYz8yBt8mXUp0Qfu+y9l9i0VSHjoAS9o4xDkHIw3ZE3x1opToz1SOt3+i8YGcmCX4PZMJwcRaJFWseOHVW0ixE1Le1w165d+Pjjj5WDTmKoU6eOiqTxh1SsWDEcPnxYKdGff/45xnybNm1SIUQfHx8VQmTokI8Jo2VasaiGn5+fslzdsWOHiDRBEJIEUxZ4YYgt0FR/ZjsXjOqVDE8d7TPqdNhxthKqeVxWwmrakCb4u9o9eCMzgn/Ii/AcXii53QAf42EsGhkEd/02BNcG3qrYAGXvlMe6NavRuVt31G81DnMWFYW7cxT+3lUIY3potvgBaNq0qYq6JQUOkGmDYvbO5YkVaLEv1BFRljqq8CiTSm98HBaJoqXK4cSNTcjhb+kNRpGSxyUCbtF/x96emx/lxJSFdVB74DxkMphVhOrPC+XhcSUK+66vRoQ+HPeNFtdF7f2XIjOjcK6KOHfjEE5MHY0JVfuiWptN8GYtl9nihBj7c7RI3qnHWRE4+y8465xgKF8QG9esw7SF1dCo4kxcf7QI2bxDrJ/Df2v7Xseeu34wurtAp7MITy6HqY8eF80wbtmH4w/XIWrDSvj45kDQw/t4u4c/Zbz1s/nd3fVm1PR+hDEL8uDv3t3gXH4rRn+/S93tjlvkCyfdfev8DNZ5FQ7HvRsG3Aq6hof378HDzUV9bo6cOXHvzi2LULb5blxfEWjCiwjLcgQhNaBT7rhx43Dy5El1zStRooTK9EtONC3RIo2iip20X3rpJSWO1EKcnNC/f3/VnyIxfPrppyoSxi/CtESakVCA2doBs8dA165dlWMZU4B4A0KVSnHGmwmmDDH90Tb9krDDd3y2l0wZ4qRhz5FFEISMybpNW3HVXk1rfKPK6obejFOHWqNRwdnqpp88NAIuOstNd2CUAesuFsRvFXZbTSN65b2En8s9wrZVmaCHpQGxrs2TqAzx0AGDKu/DiFxlsPv4Ooz84Xu0bdUCn70zTA1oeXjcUgNSzGxgOmS1atUSJMbYc01LBdfEWQTX1wCV2aA9Rxxhz87Io9FoRngk3QhNiIyymIfo9AZs2GBAw1eeiIdM0ZEfay1VtADaGuyFYfNaIPfqIBQZE4ZGv7fFuYe+0O9yQ7YL5+Hk5Qy/3AUwaGYJ/NX7BDIbjNgVnBXzV1RDteIlce7GQbh5uGP+21Nwx/dt1Ml3HufooljwAEq5hcURanxYJustzDGH44bxPG6fCMS3f9RGr+rX1frkzBaBO0bLylLscf7jQVnx8N4FDH79LJofKYb8zpHKLfKXSxXhFKrDg9DLiEIkSpSrjEyZfdS0ZeUl3Hv1MbIaTLG2GZDH7TGylcuPWT+6Q6+z1K2N7nYfgRF65HWxzE9zlceBbgg3BavHrm4eqmCdDbJv376pUiRtt6fZJn21b+8e6WaEWkhh0mkzayHtoHdgM2Y90ja///47PvjgA3Tp0sVarsUAVqtWrVSKLcsYUkSkeXh4YPz48UqQnTt3Tl18WRwXO+83IdDVjKmJ7PnDm4xDhw4p1clI2MsvW1zQunfvbp2fNyPMMaZgW758+VMjd/bSkTRGjBgh9qyCIFiZPnNODMOiuCcU2z8tYRaeX2glr+XyuLsXx7Bp9dG81S5cuOeE3g0OoWz3t+Hb1hV3z/ugcuRZoELMZe5amUmlQj6NcKMBD8ICrW66tWvXVoYjSYVijPW7NFf67bffce/+PeTzz4dWbdqifIWKmD1voXVetghIbPTxwYMHynL439nz1HPKcZANl02simKjZYozQGeyOHadO1Mb9yPXI4tzdB85O9uDr/i7hsHJ2YzTe2fgLi5j0Rt/o1a1NtCbgH33d8JkMqJNr/747YvB6HhzBMLzAYbrBmTfHQK9j2XfNu7YG6vmTsGFz0/gbpMm0Bl1+F9tJ/yvyZNmo7aRsZpZbsI9ix9w9yo69u6P0lX2WteRr0eagZ2hXijhGgx3nRldc13A6VplMWVUIfg7R+JapBP6726Gq/vyIOepRwjNrgeuAu0691QDixR3J44eRKlmi7F1uQ+KuMZs6L0ksDC++36fVfjzc1mRncPJZF1PpmW+0movfh9Fm+cAHDm0F6VKlUZYWChcDYboSOGTjar9WaZMWRFogiAIDoC6glE0WzH27rvvqus1g08pJtI0rl+/rqZ69eopZ8aniaL4YIok7Sl79OihHpctWxaXLl1SX1YTabFhM0KKNHb1JqxVY6Ho/fv3Y0TTWCMXn5X1559/HqP3GyNprGETBCFjoZlhxMBqxGFzTtM9iZip18xAaESU6kvFug3ebEeZTPDNWhc7t9VC4OVLyJLtCo7O+R3Oc13gZvbAUTzCK72qoHbm+yqKNOVUEQwocdbueimLejNwM8qAPydVwJYdE5XTY3LggNidew/VQNu02bOwceN6jNnWApV8b2PdmTwY1mY03njzLVV7lliBxoaxPJ9PmTJFCTWei5u1aIUWLVtZvk90/qCTXnkMQsfecDpLI+tSZSoiNGqD6kUW2wzFalevA65EuMPphh6hCFIvlK5UDXsPrVEZGOWq1ESP19+Ds6sHfHP54cGyKaji3x2RDyKgc32INfv+Q/7ipVGrVUe4eHph3v9+REVXwHxZh7WTruLjJZUwouIB5RipCTD+eyY0M8JDb+PHRVUxsNpqdZ2jMNPm2/EoF1btKYGJLTeo9fR3DceYCfvhrbd8lzzOUVhYewV+cyqB/405gWvGcyhUrCQK++dUh9SZU8dx7fxJPDh7C94GrxgClX9HBTujiEvMOkf+betsSR5FusLLzQN4DERGRCjBym3NIJpmXc3tro7p6FGFyhXKJOk4EjII6dCCX0hbZKSatEePHimTw9iwFItZg0kl0SKNdtBMlWHeLzcaxRKt8wcMGKBqxlirlhgraz3tp2xgCs7TRrT5+bSY1jrHszcbe2PQyYfrRSgeWTw6atQou8tgmmRiHMoEQXixYKr2zDnz1d+88eaNr5H/miwueAYlJiziwFrPo/wvom94aUrh6qTeGxppVKl8fL/lNT388xfEl0NHY8Oqpdi2ZSNCQ4LBEqWWlY6jSd26eBgUjO171qLekYIo4RNTGJBfjhXDJ82Xq+eyZLmpshfYWiSx8HzJASlGzrTG2xqT9jfBK34B6jPqVHoA/cIO+P212ahWvQa6de5gnY8iiPb/TztncqCN14TJW2ugTe5ARJj16P/5GixfFoVmLdta7tGU0OVF2wwnuj1S2RoAg94Jw3+6h9+H+NhdNtdvX6gHPlrcBi4LDyHKMxKlilZGq6590enlN5Ete054eXnjzInDqFavCT4Y9ivGfP42Fm4eCq/MPgh6+AC+ufOi78ffwcXNHb658qBJ177YvGQOIiMskatxrY9hT4c30PWTKyiT5TbyuIfgRIgPRo6sDo/SM/BBdZMl3YZNowGsepQVp4KzYtKi+njT3yLQtK/oGsttgSmrg2ucwqavWuLad78jMjwU1apUxrtvv4mtWzbDy9tbCav9dzKhde77VoEawTTGe3TEjBldtP2b8+4P9cLs6dXwMPxfdU3Ols1XLc/N2WA9dq3HreUgRu8eXZ998AgZGxFpQjKx9Gl0zGbUpW2Npq7PixYtUoOVtnBwla3LUkykMeeSoog57yVLlrQ+z7REvpYYkcYVZxgwX758Kt2RTbOZu9mvXz/1Ot2nvv32W9UIjqLs4sWLqlEr+6HRwISw+Jn1cLTdp/1+1qxZVc0co3LJtb4UBOHFgpbwtLSnQGMKHt0GmbFIsaWJMKUlzOzdpVNpeRbxFPcKERwepSJBFBva+23DbhyAat6mI1q27Qh3FwPu3b2N5cuWYsfB/XB1ccVb77yHtWtz4kThv1CzlAGTV5txLig/lv1+BPcuLVe1vhRXHJ1LSjo5z9GlSpVSUS69mydyZS+NXCXr496hLbj86ABqZr1pNc7g6jcpdRVD795Vn+vl5aWWcfzUWdVTi7CvVv48OWN8BgfUeM7+77//0GdCX3Tx26med9OZMHlEFvgV/w8NGjeHwdnJKnz5of9n7yzgozrTLv4fj7sbIS6QhCQQ3KGUUhfq7u5bd9+6y3ar1I3S0lJocQ1uCUkg7u7J6Pd73kkCtP1Wut3udjunm81wZ3LvnTt37n3Pe85zHpmG0+k0GDQatQ8rVgTRfZtVpTEKuhzOeHwJSFzV6c9NV4xl97JHsGDB08uL6Uceh9Vhp6e7i4DgEEXQ0rLH0tnRoT6LR99ayIqvPqGju4vw2ARyph6BubeHfds3kZw7ntgRo4hMTKOlvgZzfz+rv/yQtV+8zNovDr43rfyn38h9H2Sg0xysWxZX5m3PH4+2T0dwYTdf9Ds486iDtXT5vd7kuneqWsTB00ZutBedvJ2t94dTWV5Gdma62s/XN87kiIgqOmw6Nre5saQxkCz/NlotBh79Oo9b5q3/m4OTVruGS+86hYoPn6PVWsOYcRMICw3BqNOi1w+czT/6++zsHPUZu+CCCy648OtA+JDwGQk6HDdu3FBN2tq1axU/efbZZw+zQf6j+Kev1NIjbcmSJURFRR22PDExUVkV/xk899xzKgjk8ssvV/ZEqUW75JJLuOuuu4ZUtV27dvH222+rOgchatI0W2rZpEHcIMQHKjcdUdLEajNjxgxlu3H1SHPBhT82JABjMPhixer1lJeXqcGxavg7EGCh/lMpFkJYhFxJrZkoPM7JZJNWo+qq+qw2LFY7IvSLtdFk0Ckb3+DPoIDi6emlyIND41wmJKTXYicwKJjzzr9oyEYpdkLZl9vuaOfcU55SzgKpKRJyJxYJ6Q259IeVfPL5l/90bZhAJq/e+SqOY5L7BpZ0Yedr7i1NY9FZiezrqCE5pG5Iwdt+wEnApk46aBMfJGjy/lYs/+Gw/ZB9FwfFYA/LyDhJwzy4fZPWQU93N01NDURGRimSJoTW5nAeT5sD3PRaRRLnHXsSY2Y/yl8+ycCh0/Dox3msvvsT2m11mIxu9Js3qeOSPXoCY2fOxdM3QDVr1uq09HR1E5c6km2b1jEiZyw2NLj5+DHt+NPx8AugoqSQHWuXM2bGXOKzxmC1mDmwextxI3PRuxXg6RdEaFwK5YW72Lt+OT0drYrcePv4EBWfwsVj5Zw5SLiK+k34Launtmwd1gA3KnoLOOWHEzg7ey+1Zk/e2JZHWHsvH5/0Gf4Dd1j5+zE+TUy+ZBQTT8ti+dpgwg37OSfaec8M09lIDq1V58ojO9O4c45YW3dx59Fphxzvn84mf9UcgWn9fkXQIqOiOP+8C9Qx0es0aA8haHLvlEarMTHDGJmW9E+fSy788SDXrl8tgv83tjtKSyYJuZOwOWn1JCUykho+fPhw1fbJhd8GyonyKylg2v9yJU1agYnNf+/evepnEOIwPLS5utz7/60kTWZlpabhx2hqavqnLYRCtOSL8+PI/UFIrZsQwr8HmRkXwic/Lrjgggv79u1TDSUlJOOrb75Ttj+B1JHJ4F5IggyI5bcKALFLLLzGmTgoWSADYQuDF0hR3VQyoc1JyGQdFpt1SKSQMYhS3pQDoJOklDSK98mFWpQiIYV2+izO9ESD3im5vPXO+2oQnZKazouv/GXoQzv15BP44KPPWPr9SvW8JPANvgexqf09FURsjaIUShzwt28nqGWDg3vJc7wtdi+fn3o+p2R+wcdbx5Dq38aG8nAevXCHaoUizobD4IA+s03ZOw+FNO0UgvbwV8dzTfZuDGyn0wbeA2nyy5pC0GhK8PHyOpgwqJObjmbI0jdox0tLTaG+9gymZLyDzSqB9fmKlEVERuLt40tUbAIjxkzC09tHkWv1GeL8DLQGAw31dSRnZKtarGGJKcriWLRrC4lZo5XFMTw+mdbWZoq25RMWl0hMejadLY14+vjS0dyA0dObYalZxKSIaqbBw6DFKuS7vxctB2+wgo9Lk+iv2k+ZbRPvPxNNZpofC79dyKMvX4XVy4BHPWi2mnkrMoRrJzkbkqtzyK7jwzuLlX3xsoQSljXL8Tn8UMs/T0o+wD0DaceflEZyU3LZzzaFrbLoePn68Ww+8Jg6V2+97S4MRokVOfy1Jxw777BJTRdc+F/GSy+9pCb6JYROlA35Hg0OlmWs6SJpLvw7IBMC/w780yRNgkJE2br//vvVv+XmIJYXSXsUlcsFF1xw4beAKE8ff+YM0xAL9KzpU1Q7DoEkIXb2mNmzZ/cQQRMVzGx12hNVkMWAQqRRSpgzFEQRNbudgKBg+nu6MVv76bPYDqYUSuCFskcO7MSAWOHj40tnRzsGo4GE5DTqa6rUOno6O+kfqHuSHmGyDrPNjrtB51TuRFUa2O4gVLriIYPstxd8MPS4ur75J5bDQ/HmO+85S0lUkNPPpyUKSbDr7Fjo56S8DQyPHU5p6Q9q8m3JdwdTI1UN28BxkRqywaCVjIxMRmWk8dlnnxEfH8/lo/aoxEHZjhC0t2qiyS8O59Nrlqm0SP8A/yH18NwzT1frGNwn6XcpLgp5bvqMWWTnjmHXzh1YrDbik9Pw8fGnx2xTx6zbYlU/Axku6pgFR0RTWVnOsNg49u/fh8NiISQiGr/AYMIS0jB4+qLVtDAu8RPMdi/stuPoMevobG2mrakBvbsnnn7+dLS2oDeasFn61efRbbGp9Xe0tfJG8TCuSi5TBPeA2cgXX+Rg0ubz8RdxHJWlVcf52tO8OKvvDY49Jg4/QzL1PYXccMpasveMIcevlQarEYtdDJROqIRG9x76B2ydh6Kx300NLF/Ln8K5kU6C9nO4/utpbPz+IfX4iiuvwdPL0znpcMiU84nHHT1kXXXBhT9CTZpM1r/22mscd9xxPPLII0PLJRlcSmFc+O3wRwoO+THkGi5OQFFxf9wi7N9K0oSMTZ06lc2bN6ub+M0338yePXtoaWlR3ksXXHDBBaknlfpUsSaLBVnse5LkKnaTXwIhTqKsHNrT68dK/vsffapmS8UaLYMCIWAS5iEqmGaAJNkGrIqDJWSD5CwgIJjWliYVqRgRGY1Wq1PEpLGxF4NOoxowD5IzxyC5U0RBS2h4JHW1VerfkTHDlRLU0tKs7H0enl64uevp73X2sBKLn8h1EjZi0GrRaB1q4G4/JIXvb0Esh4MYtB7KsZEWAkImZZAu25V1hUdEU9BhJM33YGCI7P/WHk8qH31K/TtvwlTsll4uvvgizjvvPKXYefgEqGv7hvXrhur0tBI1CZx1+nxn/Z00aLZaFSnWqVbNB7FlvYmXrlxAdMwwzj3vgsPqon6cpikEbRBmix2dyYPUrDxlR5XPq73XooixeeAzU+934LdvSBj9FgvRiSkYvbyJ8Q90Hl8Jc7FaCB0WR1N1ERfmXo2X5PRL/0z3FTy36FpsFjOB0fHUlhYRHB1Lb0cD/f0OwoYl0Fq9D5PBSk+/G54+/tw8awWL7ruG4PhedAeMXB63gW8y60lPFeeIs1eoIMAE1z5Ty/zpTveHf0gY09I3YTA4G0sv3ZxOkpvztfJRV/Z5c9UZjVz3+DCyIjsIN/ZT1e/O6UdUsq8snQRTzU8+/0HL48ZOX1Ze79yO1AT6B4UOKZODISFnnTH/J8FcLrjwv07SRNEYNWrUT5aL00ucYC78dvgj2R2vvfZalYUhZQZC0ETQEqutTH5Kzbbwpt+EpEkh+s6dO5WkLDVfctJLv7IrrrhiKHHRBRdc+ONCGsULKZO+hycfdwre7j58uvBjlXwkhbSSBvuPQMiA9NoS27OQvp97fujePzB4bWttO1gnZpceY0KuBuxxKuDjcKIlj4NCwrBa+hmelMqBfXsxunnS2dlOS1MT4dGx1FSUqnWpNELZ1OBvsdAEBmO129Dp9CSKxbFgF6kjs8jIHkNPTzcHivbi6eWt/lZZ1sT+KOmRikTa0Ds06MUKaJP6qp+GPPx/mDzFecGvqGngu6VLFaGRH9mGziEDcwdnnHsBI1PuYdb8UOZfmUhGSCdfbPflofnOnmCnnnYGc+YepeyUciyF6AlWrVzxk+1dcM4ZP1kmTa9fffVVPq6ZyZmR5WrX9/WZePe2daSkpnHzLbf9QyRBkWmbg65+q7PRtWJaQqYH6/0Otj8ICaoiPX0PJbVJbFlVi4e3D3EjsyndvhlfH1+yUzczMmYL+6t9KW66Aw/TarwPaRId59nFSzedT8bkOZx43b1MHl3NqSOfRo+DNRXR1PRkcNLcr5XauLUpnHdWXsbIiTNZdefT3HH7TO68dL8aLJx7Cqxs8yXW1H7YewmIdGd8VjRPv2DAw8ed1z6bzMIP99HX3ckJ07azfvMIokx9FPV58spt2WzdvJbTJ1erk1JmiuVzWLgpmwRT588eK/l8r/44l5ev/hQbZlXPLfUN7773EZOnTmXVioHPTqWSugiaC388yESg3HtEwTgU0ltSxq8uuPDvwCeffMKZZ56pHi9atEgFHRYWFirn4e233/6LRSz9L0kMk55i9957788+95N6BhdccOF/DvJdf/zxx1XdkyQPSgS7TNTIbKWoZzKDdOeF97Pu9e1o6CZYN4wyt7089NBD/OUvB+uvDkVJSQm7C4pobz984PtjgtbY2EBbWzth4eG4u3soAnWwh5QzCETF4auaM0lwPDjYl8WDKphwgbiEZPYXFZIpNrut+aSMyMRgNLG/uEARrZ1bN+HvH0RnZwcGnQ5f/wD6+sS+6LRxNDXWkZSWQUhoBHu2byYzdyw7t2xk1JhxFBfuISU9C3NfN9V9fapeyuTuoUJFJNZBVA8nIXGSiMH0w0Hl6W/1nlyxfDlLrDZaW9tobGrE1z8ID09n3ZGoXvJX4ZGxXH/LXbzxygss/XDN0N+GhIZx7XU3qHovCZKorG1k+Q/fH1y57NIhm01JOZji+2OSNnfuXC4cu4TFt56JX7iWL+75CqPJyHkXXPgPkYS+AStjb7/t4GekrCJ2J4lmoAbQ4SA+ppiLp37ltGvGFnC/KYaHjl9N3hHHcNxF1xIVsJwTEr5S60hMqsVWfh3fbJmGOdN5o5O31GbXkHPmLWx7/3G62lvY8mWzImhymCcNq6TXXjlkScwOquWpgse46spITnt3OHrt/qH9lnW5YeWrDn9me7di0kK7Hf5SMYJvFrXhqYihmYcu3MZrT5Vit7gTFjOClLhduHt64eHlTXP904RHDePi6++kunw/tRWltLQ2Myq08ichIYMqovza/EmHImjX3XATGZlZ6hw/5yynqjrsjPnKHqtx/JdPO7vwX4/fa3CIRKDLvUiSfOUaumnTJuXAkP67/9+9x4V/D36ulvZfWdd/M8TNI32bBYsXL+bkk09WNd6irB2a7PhvJ2kySyF9yKSW4FBI3Yc8N1ik6YILLvxvQuwkY8eOVYPD4+aeQFtHi2rWKCE/X3/9Nd9++62qVVr5l00YpPpGA6G2aPZ37VGpq4feKKUB5Odffq0eK1IywA6cw/NDGkg7oLW1hdf/8ioFe3ar14jVTuLdjznhRNWbTJEy54qUCjNIyA4NCVHQiCoGMcPj6OntITo2npbmFkIjoincvYOk9EwycsdjsVgVAYwaHk9fby+Fu3cSFRtATdVOVS+l0ekxmNwoLd5HRFQM/kEhapt+AUFKOUvNyKFgxxZS0jOIT0ln3+7teHj64OvnT211JVjF7iiKkbPJs1Lq1Ns/2KdtkFCqPm72g4mU3T0daL3eos+/j+fvKsTW5yArdyzHzj8Do9Gkkv2ErIn98q6Hn8Ck12IyaNH9iDiJ2ve3CJp46fNys372PBAnhaij4qp477332NPVpVqxSN3HitXr/uY5pGrzrHZVbya1gkKqhUx7eFVhDFzJxx/Use3bGqVkTpxzHNHJ6YzJfPswofGk9AYWT7uIjUteo7G2hlcXuKvjNNhSID28jWOueJDovKM4NWS/6t32RHkONrsX06ZfwPfLXkWr+dv225jZ0Zw9umBou0O9zTVQ7/DiT89MJPW4NkYG1LG1JZLK7RF4jXAqlQKJ4T/h9XPZcuc+CvauJnvaHNzc3OlsaWLOiWcSFBGtmnqnZI0mclgcleUHcDiqDmtcPfhYmmi/vD6eTasXk5ySqur9BNISZxCihgqxH1RaXXDhjwaxbYsVW0pxpG759NNPJzIykmeeeUZNJrrgwr8DoaGhKtVRHIUyBpLepgI5B/+VpPl/2g/x/83uymy3pCy64IIL/3uQGiWZiZRWGykpKbS3tXNGzoWUvdNC12IdT936vGrPIY0bRU3bv38/Nqw8WLKfxdU71M8LG0apSZybb7lDzTpJfZIQNLmmiM1NxbIra6LTnmgb/LFJPZmNrxc/xldf26mtTOa1HTPInXM2S7/9isWLvlTpiVI3Jn+vAjoUUXOu034I6ZPHwoXcPTwwGN1UvVBDXY2KLQ8ICiEhNQMf/yC2bFiLzWpjxKg8Orp6KNi1g4QRo5wkbkQWRYV71D6azRaGJ6fj0OrxDw5FZ3IjJiEZm83Krm2bGTV2CkYPb/bs2EZSWiZavR6NzkBkdOxQbdzgj8IAGRNLpaRJ9vTbVF1WW49F/e7osaqEypPmvcRN89q5e24/O/cmM37exezans9n772tiKVYKtUxHGrULcTIqVAdCvkc/haOOWrO33xeiPI111zDxo0bVW2yFO2LzUjq5X42hVL2RUJAzFbVZ07q6ERJk7rB8OhdXH3UAq4YV8V3T1s5772jaWlo4O1nHqShuoKqFo+hugT53WA1YY2KZsaMcynZvpGN9WEDoSlOYrOvz4fnX5zLtWHFhGgdvL4vm1VLM/Cst+Fj9cdutbKkI3hAx4Ris57PWsNUhZ2sY3e/kaKeSLWtwRlhWd5skwbS7tyfP4WIDXYqHjHx2acTqPh+OJ7bDSp1cej42jTs6wsizG0iCSm5HNi1lZzpcznj+rsIjIolaeQoDB7e9JgtuPv6q43safM4eD4MrUfHUZdN4rqTvlX234svueznPw+d82fDmp9aVl1w4Z+CqLG/5s9viIsuuki1hJKa17q6OiorK5Wi4cJvC6mN/jV//tsnB6QN2IgRIxRHmjVrllou90YZM/3blbTrr79e/ZaNS2+zQ2P4ZeAlO5KV9fMzri644MLvF0KiZDbyyy+/5LQTTqe9qhsPTw/2fFeinrdabKx7cxsZGRm88dbbKmlRMHeFntGeBwu1z4qpY8kDE3n50WdJS08bSiFUFjf7QSLV3dVJZUWFalosIR5if3z5uafIX+VJoMEZ1HBOcAVbrg9DVzeXFd8vYeqsuWi0WiSIUalSA02m3T08Va8uiVr39fVXSYutzY34BwZTUlSg7IihERpF1nRGEzu35ZM6chSj8iZiNBhZt/p7pZqlZo1W6xs1biqtrU3kjJ/KpjXLSRk5CovVSkdbC5Gxw8lfu1z9fXBYFCNyx1NXU0ll2X5GjZmAUa+hYPd2AgKCCAoNw8vbj+5Op7VTYt+dZECD3eagx2JTypKQT2dfNueoXalp3SXEex0MrEg0mvE+08D05pP5bt17zD1+PmGR0fR0tTtr4bAj7juLHRVWov3xRNuAWvlzjY9/KZavWqdmsweLBmX9g7ZTIWVCpMXqObhMMHrE6qHNizZ0Ruputo26mP0F77D4/b/S3XsyQRcsJtWznXKzO7etn4Vbq4Ojp7Zw280x7C0r5gWf4Uz2q6PM7Mkzmyaw7LiFQ9rs/SM2sv6pVNyKGulMsSpCdOt7o1l+ZB1+xj6WVaSgOWBgzvxPCdRbCdM4aC30Z984A8km5/He1OvJNTtn097mjX6XG3pNG+XL/4ptnY6c+PnQ0cPpT47g9ssrMGht/LUqg/aSADzdu0n0z6GkcDNdbS1oE1JIyMikZM9mEkaMA6uZssLdpOaM54KTX2Dz9+GE6m202LRc/PUc9t2whYLuv6qJ0Lvue4DAQOd3TCCTHUKKd+7ZpwJ1hKQN9gZ0wYU/YnCIXHtkQnHwXiQoLi5WqnNsbOxvtzN/cIgK9GtVxmr578Y999yjCJpMCIjVcbAlmahoEpr2bydp27ZtU79lUCWxkoNR1wJ5nJmZ6Yo3dcGF/0FI2Menn37KY7c8xbLH15Fpm4DJU0//YKqfRvqP9dHQ2Ih/QCBjRuepxWlBLYetR3jBFSf38vn9Flpb21mzeiVVVZVqAB8ZFUNXZwcb1q2hv78Ty0AgoSy//HoTRev16HEGYwhEq4jzbqFWH09P99d4ePvS093pVI3QERYVqSyFEmyUljGK3du3EhIWqSyTQaGRVFaUkjt+Cq1NjfgEBrN901pGZueRkTsOX18/Gutr6dJqGTV2EhaLmd6+Pop37yBrzASK9+4ifdQYRuSOVemO/X09RA6PVyqewc0dnd5IdWUpNRVlZOVNwDc4VNWhbduzg6zcPHZu2YR/UJBScMKjh1FfXaGaDwsRkyRJZ181hzP6f6AZttPuaFd/U1rRitXhPAYCiXFv6vIkxqp3NuoWQmY2o9ObWPLlh5QWF9Hb3YrZ3ElLaz8BAQGMSB/JkUfNIzQsbIDIoayX0hLgx0RtybLlajb67zXUFrIg6Y9rN2ymoqJ8yGo62PJA3oPqL2d1KqUHFU/nCK6pQ4vG5+C50mI1YfZ146KzUjj51BL6NV9y/Jx9+B17N1Y3LV4VDuYlb+Syc3bicOiZmNrKB3vcOWX56WDWkGOsPiwRTO+Ap29awMsvGXhn8QGSx0zlwON/4Yf+e7D6gKFVw3Mnf0aAznley4TAHTNXcf76ozgxdZeyS35UmI1tvR+eXQ48ayxoq5vwGRZCRfleVux9VsX4W5/u5y2/k7j/jBLuCd/OI32+VFbb6RjWgsFkInbEKPxtb3F23kp02fD9/je4+AILY6bNITYhmqS4HGKT8xlx5hXoGg30r99IUe8GFUBz8x334SsplnY7uoHec4PHfhAugubCHxnnnnsu559/viJph0KEBLHarxgM13HBhV8ZJ5100k+WnXPOOf/SOv9hkrZ8+fIhSU+8vT4+A3dTF1xw4X8a0rRYou1r17UM1XX1t1gxxmjpK7fi5mnCa4yeukW1nH7G2UQNpGrdexsc/fJBm5ha115fbA4736+5n9z5wyn8ykHxx/mYTLt47tVYkr3CMGrCqLVpueT7meTf+A43nxr6E4Gn1abh6+0jcNOXYzSZaG1pxuTmzrDhwzmwv1g6j6l9HZE9WhEd94FeUR3tbaRl5hIcGk5jQwOlxQWMnzqbzNETVH2ZKGEZOWPp6u2jtHivWt7d0aEGxRNmHUVzYz1p2WPo7+ujfP8+UjKyKdy1jZE5Y1XT5FHjJtPZ3obRw5PcCVMp2LlVNWOWwJHgyGjVNHlkzhgKd24jNT1d2ShDwyPQ44ztV+mPopyJLXGAoKnHQ1ZNB26ewVz3lpG7z7SqCeqXq9KwL/cB7+qhOjOjoY2Tpz/D9cfaabdr8Nb6osWXBquOH8o8uOiYtaxcuZzjT5rP7COPQqeRKjZnTZw8kv+ddsqJan1C0A5VbH4Og/3qBhMilW11QCkbSmkc6BEnmxEVTayYytqp1WG1Wnjl5TTC79hGjKmPUrOJVSVxHDdyKzdeWDwwi9rFmhXDSEy6h8lp5+OJJxNurBqyN8rv0QlNBN5YiSkonEaHO/tO1JNstA6df1kpFl56xkLGWD8mzTDyxltxfPH5J8RFzBV2j8clvYe9L/eQXmrO2cIrF8/BoQdjnYbAIjMeRfV0NFVwwXNlnDTLgtmWxO2vxLB1fwL+Ab68edFnGAZO2ueuXMzY90MoWLuRvDnHYTB5cGreKkWyZb9nJvQw89Jksjw/5pJxi7hkHLy7LoxzTzrY40nssWdddDlePn70WcTM6uy1NmQDOuQL0tnZ6Wpe7cIfNjhEBIUJEyb8ZLnUUV955ZW/3Y648IcKDvl34Z8ODpGO7crG8iNInzSpQXCRNxdc+P1CapSEkB1aTyTWZknK8vR3V4l99gHSsKFiBS00MCxwOOWLShk7fiIpaSPUgDglNZ3tX67ljiPzuP/YFjWGbLXD0qKRPPFMMVceJ/Wrjdw5AawPD1fP6+gfuhhH6O1cP3ED9044Bw3fHhaksLAtmBc/G0/poz9Q27+L2Ucdj5u7p0pmlP3MyB5NwZ5dikCJajVi1BiCQsLx8PIhb/JM9u3bQ3tLM2OnzMLHz5/e3h62bFytCNnYyTPV9c3T24esMROVamG2Wanfv08RrfKy/biJGpKcTqKHB3o3D7InzsDa38uuLRtIycqlo72V3m5nIqXJ0xOHTo/WzYPQ8CiqyktpqConKXUkWoMboVGxNFSXEZeURojJg5qqCqUwiQI0GHaiyBkaTO7umPv6CI6IYsHLFj54xkrSlHMxtTpI0LTyzeb3GJ6UxoRZ8wh3P4dgo1N59B3ocSaPQw02TkvsZOS2ZOaN0/L5Jx+SkJyq2iLo7FocOqflNMA/4DC3xN/Cj3ufCakU8mVWllPnY2XTtDqJmlgtBwkaOr2y8HkHRnDOMa+S4NZHs1WHj83Bg9mbIfvwbQUZrARMnsKypS+of2eWjWdS2ME6tMI+H0pr19C7vZy4xNFcvGUuJybs5MLAMjwGhCc5la443Q2H4wBP3QzV5eWs3dZBWuIUPqyOJzlxB7466HLAG9Vp1JV/RuTLGiJSZqDvt2Hc38jOioVE5TVyyuxI5+esc3DfpZVc9+F5+Hk1YDzEm+OucdA/ohtbmYX6qnL1eSpCfAhCc924NMFt6Dw/czy8Pf8kitYt5JW/xKkG1ddd9RBmawjBIWEquCt39GjCwyMw6oVWHxzBfLbwK/LyxhIdEaKSV11w4Y8Eub7IRMWPIbZ5V7CdC783/NM2T0nH+eCDD36y/KOPPnIl57jgwu8cS5cu5eOPP1aPJb1x0eIlzJs3D4vFwrqm5fgP98XkbSRycii9bl14+/jgHxjIRZddyZnnXkiv2axmMidNnUZCYjIn5LaqdcngM0AHNx23kfOPdh/aniwXOqg/JJxBIINuAw66vUP4bOvB/dva58E9nx7J1rvepaJzCwnJ6Zx4+vlED09Ql7N9e3fh0OhVJL7eYCRj9AS2b9moEhe35a+jo62V8KgYZXXcv2+Psj9KgEfG6PEYTW50dHawcfUyFSTi5uFBVWUZBrFzj5tCX7+ZmLgkUkflqYbVjXU15K9aRl9vDxq9gbj0LEye3nR2ddFntWFw88DLL5BISY9srCd/wxpiE5IZnppJUVEB3X1m2lqbiUlMU7516aticPdWB8FsdRAUHqkSMkLCI/ENCsYvOBSz1YJWb+CCm+7D00PPhg/vYuV3d/PhkscIiYji7KtvZeeWDeiNP51IOxTxxj6CzjleJU1uXLfmYMS7EtM0Q4EhPyZgP/73198uPezf0pBaQkBEMVM9z6x2+sx2zBZnkItlIKGy32YjZFgc3sFhtHV0kBzzJsm+nSpeP1hvI9rz8Abcg/snCltAzlQSUyeh1elZ9GkCrzdHs7vfxJcdgdy9ZQZJI46nR9PNjuKllD9fzfNLZ3HA7KwPGAxROVR9u+jmZDQ6LT989wrvv2rhurJxPFyXwGX7J7BiWzrjUi+htOx7Cja+jLumhdbwGpqM9eQcH3/Ye9dp7Lx+wxm8+8iL1FoP3lorLFqM047nmHk3c2BHPhu/+5LPGsKdgTYO2NdvYFlpwk+i9jXThrFjXRxHjLQzO91G/rIQVi7VsODtRlral3LP7X9i0cLPh3oAHsr7Nm7coGpIXXDhX65J+7V+fiNMmjRJhVwdSsjksSybOHHib7cjLjhThn+t4BD+mFLaP62kia/3ySef/Mly6aYtDdtccMGF3y8keGAQoppJa43VTU3MP/0s3n/3Lby9fQgICqJidSk+vn6qgfOB4n1UVVawccN6qqv30dLSjcMqzZl1eLonHKYaJJna6bLqcdNaDqsXOjTNTgbP0nPqxaJcNOsLOeXdYqYeO4rIuWMoXhdJwLY9FOiayRkzkfuefA0vLy9Wfb+EiOhhZGbnKTKWnTeR/A2riUtMZfT4qUqVGj1xBn19PdTWVGEPFyJkxcffU5FRSVO0OqRWykbKqDGqTs3c3U3Rnu2MzB2nwkbsDju789cxImesem8SDy8x/FabDQ83dxW129pYT3x6Fh2tzeq97JTXjxqjkiMTR4yiqdG5ntSMbJUAaXD3xNzfR0NdG4FhUSrkw9svkIrSElpbW0Grw+bQ0N3RTkh4FHFpmbS1NNPW3MiV9z1FXfl+ujraVV3fpBnz1G+J2b/h+ltZ+X4Qxp+5r8mxbrDpsXfoFUnr7u4a+oSkd1t8QsJBMnbo4OqQda1au5HS0gND/x5MjRQiJiRI1MBB9UwgpDUwOJSWtmYsZgthEWbGjniSlnYLm20XoTE1HRY3f+j50OuATT2+tNuMPLpzIqYGHUm+Eym2raZp+x6eevs47CkabP06TPv1+PZ0kpNzLJs2f0LlDx8wUZPI7emTuDZhIz46M1a7ljyP3qFtbOkLpL50K1PPuZaa4t2sXz6B1QEONN0avA9o0dv1xCeO48D+jXz7w1Po9AZSJszCGn8MpZanGG5w2g9Xdvsx5uS7KFn9Bpdumc2laTvV8r9WZWFrdaOnoIX4jDy2LFvEnt3BfHPPJEI8O1lTkYBbgQnbrIM35DqrDkubG376g2mcnjoHHkoVtfPVO6GcNH8mXy38lKSkZNLT01WU/x91IOPCvwG/ot3xtyRpjz32GJMnTyY5OVkRNsHq1atVuxex7rvw28Fld/wPkLT+/v6ftTvKTHtv7+F+fhdccOH3g8Em0hI+8eY776lBrGUg2j5v4jSlCOWvX6OsJJJgmJG9lZkn9rG6eQLfvODFO/fkk+gfTpcdHi7PYPXtntx0y+csfDVsqNdXotHK+y1hzPRpwl9vVXU7cv9e3+0FNj19aPi4OJUdy4bRt6iQAw1L8PbxY/f6WlYsfGVoX3PGTuJP9z3Blo1ryc6bQGJ6Bu5uHnj6+jMye4x6zajR45VdsbSkkLL9xWSNHq9i9SXEQ6x8oRFRBIaE0dzcxPZNK0lMzyQsMoburg6llLW0tzJ+1tG0t7VgMnnQ228mKWu0sh7KTpuk51lQKD5+AdSUFVNWXED2hOlKFZNj2NnVSVRCstO2KHZFN3fcvb3IX7GUYSnpBPsH0N/XS3BENEF6Ew31NYRFx6o6NumbtXvrRuLTMikrKSAiJp492zYTGjNMNcROTM9SlkGxz42fOY/mhlocWg1Fu3eQnDaCtpZhVPaYifO0/MTLX2rRc8XqOfDlFiprShk9dsLQIEoG+fv3O1M7BYMNpcVCpGpUNJrDCJpK5xQyJomUZpsKPhEVzSrWRmkqruyaGpVmGRu7keHabpZ9Y+L20z/HTVboCzEh93LC6fVs+DQAb41DxdGs7vQlx7MdKxpeb0ji9a8mobVrcWvQ4F/cjUYkN4FGQ/mLT5M55ybsJi2mRjOG0gYsCQ48fAPwDAhm25aXiXz3DK6eezQ6g40Qzw7+lLSaSEMfO3oCWLB7PBmjvVjx1lPEj55C35ufEznmePV+3et60Da2oo12IzAqnvn3vIjJw5uaA4W490ZxXdE0ZoQW02Ez8VlRFlovLyamnsk3F7xG0QPXgZsDe70Bv1LQmK14ePrS291ORsZ4vjjlLVKPvRZdv4aTJq8dqmET+Ops9Oe70X6mBp9D7KqDn6WX1kF32EhCw9ezbu1qklPT1M1cEbWB2Y/jjjvu179IuODCfznS0tLYuXMnzz//PDt27FAtK84++2xVjyahSS648O+CtB5644031G/J7hBbuvRMi46OVhNpvwlJGz16NK+++qrqh3MoXn75ZXJycn7RTrjgwh8dFRUVvPbaa9TX16tZQEkJGuw7KFaNkpISVV8SFRX1q297UDVRA3JVP3QwMn0wgU+sa1qtnrGTZuAfGESI18ucfYSQkXamBLQz5QE/Erycs/6eGrg4ag+LTzyNknsOBgwNDjBDTV3Mvv8sit54mFGjEvCbnkfdBiPlaz6i1SYhFZuG/iYsIpprbr1XERJLv5migt2MGDVaxduKsuTjF0htjcT1e6t9Xr/qe9KzclVS5N6BNEYhUiP8AyULV5HFUWMn09PVwdaNa0kekUVgaDgjcyeoZtQdrY2Y+/vZkb+B5Ixs2lubFWkSm2PEsDhlW5R+aFZzPyV7d1BXVa6i9kOHJWDydtby1VaWUbRrm6oNk5orb78A+jrb2Zm/ltyJU0nNGYebuxvdvT0EhEaoY164by9po8ZQvHcHueOnqufEgmm2WAgOi1SBET6BQWj1RsWnpP4tI28iiSOzsdikhs5XkSWD0YTe5MGFN95DQe2dxCVYDrP2lZgNnP7dCejvLmFH7ecq1CQ7b5xKdjToRfN0oHGInncw8l+lP2ocavBv0GoOU9C6+q1DrQLEJtlltangE+EJQtakZs/D3YNpo+9nhG+b+pvRF+twHyAeguFuZkyZZzL9VTNHzaljb3swOzbFYYjoQ2t0YK7wIGibHfeyFrRmK/aaeioyejC6mbjjvvGUrS1n6fpF+LdmYdS60Z/jyc7v/kr23FPJOnI+nz10DUULniPL9BAWPx01Wh9u7D4KT/d+Wlq80O93J6x9OJ7+wfR2tFOzfztBwREEt4Zj0OrpztVT/O0KRs48Ho3JExtaZ7+0unq2f22mYMYMHHYNumo9wU1WtC12bG2t1NzxOiOmXozWYsf9QBt+cX6s3ryOuIzRxKSMJDDQn13v3c2I3Cns7ZDv2UGxstmmo99fz2Wrx3JT3g4lRQwz9irLsKCw34TDoiMwMFgpBHLsxfaoPSShczAC2gUX/kgR/IKIiAgeeuih33ajLvwEch841DHzr0D7X24SWLlyJUceeaQKrVm1ahUPPvigImkyYSCpop988slvQ9JkwzNnzlQzFDNmzFDLvv/+e/Lz81UzWxdccOGfg9iHb7zxRqVKCISsiXV4/fr1KlX11ltvVb03BrvaDzaUP+qoo1TPwn+l78sgQRsMexhM4pNRnpCV/E0bKNyzi5KiQkV8BH7+gaxf4ZyRlMG/jBtjTc6gDIH8tVb+3+AgNS4LDUWHbbOy3xNDF/RbO9mQvw3kRy5GBiNRUcOV4hSXkEzKiCyOOPYUNFqdUr4kjCM1I0dtX2rGVi79WqljJjcPFRwi+y31ZhIGIgPe8dOOUKqYkIbg0AhFsLZvWsPInHGq/ixjzARFqqROTSyPErVvsdjQaPXKzmgwuasAEbEv+nj70NxQx+7N65Xi5u7lTXRSOu4+fpgtZkxmZ+hJd2+vIiZxGTk0NdWj0+pUL7T+3h6ik0fQ092DXm9QdW5ioRT1LS0rTyVGyj3I1y+QHouZ7ZvXMywpXVlOK8r2ExAerZpv+wQEYbNayJ40g+rSEvyDQ9R29+3ZrlQ/aawtH4rR3ZOzjinjkw1pxLt3sr3Hl+f3jqahIBS/z1vYVPuZUvwuvfYWjEY3VTcm5FzdCAei8kUVE4iSKsv1Wi0aA+h1WtUeoKPX4uxHNzAAs9ltiiwIoe7t6aG6qhxvX388/LxJ93ESNEGYwYZloIWAbKHJpiU100ZOwxI2vzaVyr44whstaBu66I8LQN9jxVTcSEnNd1T3FeEZHEL7ymrWbhjN2GHf4Bjrx/W9DUSmvYjNbsC2x0xEShZ5MzMZm7iBuOfv56ELb6T+mwWkhR2F3QrNnf60BmkxdIPPASv2ti58QyPJHOnNnJMu4c1HXlcHQs49W4GZ1CnzmHzuTeiMblh6OokaMZq2uirqFn5Adt/N2Hw9MbbbcS9uhUgJ17Fh7W9mz/InGZl5BL3BdpbsXKZaNEw983I8g0K56MEXWP35e2xb/g3lT9kZNzeJmb61dNt1PHggD61dx57zSjn92GkYosMJi2nkohkb6bYZePabKSQ0dbOoqIBZR85Tiamqx56QaumLp9MqZdzf3/8XXxtccOH3ira2NjZt2qSaWcu1/VCIquaCC782pBfaAw88oHpKe3t7Dy2fNm2aUtV+Kf5pkiYsUQaP4vuVsBCRkqWJ7euvv/6TvhQuuODC38bu3bu54YYbMGncuPydefj7Wnn77BJKKnarWRmZhYkKjSaSOCyYqa+vImL4BHx8Avjk409YvHixmiD5ZxU2sSev37R1IA7dSdCkbmhQdSk9UMLSb1/AP8GdN9/yIcovjG09ieQXRBAVWE+52Uqi42CC1pYuX/x8WlUNjUQ+LGhMxLhSR01bBasL7UxOdQYpNNvgo7JMvAqb1L8l+OP6Ox9ix+ZNTJg2W9kTDUaD2glRAqxmCxvWLFc1ZtLNq2jvTlJHZquwkqS0DBwOOyEhEj7RrmqxZFlddaVqMC2ygtViZce2jar/mahtqdl5qvZMgkoEYlVsaW5i98bVKhkxMj4Jq8VCYkY2VouZrg4nuTBL2IXFTHxGjorzF5uih5Ahkxt+QSHUVZSyv2AnuZNnqfh9a2M9AcGhFO/aQmdbq1quVLiQMCqL9rJ7ywYmHHG0IlNCZNYsXaRUMZ/gMOqqq8geP4UDxUV4BwSRmTdZ1aAFR8Wwf+9OTB6ehEYNo6mhlsCIKGVRHDvzKFoa6zB3d6r11VWXM+mIEzkm+1PST7kZu12Lx5Za2hpeZ0/jATWgP+XMi/APDFGEzBmZf7APnZDcfquzybY8L78tGpt63NvVSkNDPW5evrh5+au/lT+UcyguYTOnjP5BWfdWtPpxRHo+foHB3H+2H4O6jpQ9PlaWykkRB+h1aFleP4x3j5METy02xyquerCYbfkB7Cz+Dt1OAyPjZ9Hp2UeVtQitm4HAYfEcceU95MQ8djCUxgOufOBENu6IJDQ+jQkTvbkq/W4VRCLndP3luTxz31dY9H0Ye/X0L+hjRMaZioQZatqxBtp4+NomzjxKmq/Xcd4xR3HPG1n0dLQQkTqKYSNylYrZXHkALz9/wj0rCQiuJ23yXDYvfoiJEy7C3xJIb6iZ77d/gG9IBCfd+gTrP3uTrfnO9gQJOROYdOK5RCdn0NncgG9YDOOPP4tJJ51LS0URN1z0F6Iun49V+t0VuxNa0oM9NojVHz6tmrHv7exgvUcw8dFTCXTfy8qqFbi5ezBu4lTVG0+vHUjOtCvRmE1bthMfG61meCV1ee7cua60Rxf+55W0RYsWccYZZ6gemTJYlu/EIOSxi6T9dpBDr1qE/Err+m+G9I9+7733frI8ODhY1fb/Umgcg9P3f2CIXcTX11fNPLpaCLjwW0HaVqSmpqrZvu8L85jq62z+XGXRkxXTRCuN+Pn4k945lol/9WT22ErcdFZyvDrUPe+d8jgunbCUyy67TPnv/xF89c13NDY20dbaynfffcvePXuUSpU9Oo/ccZPR6XV0dXYxZtRzzB7hbED8cxfJTjts7gggxr2bkl4vZvg2K+IjOREvN8Tw7n3j2P350/Q6uggODeOi28OJHx/Iwv3JXBW5naCQDj4oCuGxE1fhYXDjnideISElnb7ePry8fdi6aQ0jskYrJUsaTgvBUsETzY3odc65JYvVgoe3D0211RTs2UGmNJfW6mhqbqK2qpwxE6crElVfV61mU8Xa19ndpdYjyYw78teTOmoM/oHBtLe14u3rS1tLk2pILINf6ZvWVFPF3h2bVW1YSEQ0Pb3dap1ms5mmqjIqS/eTljsOL18/OttalHImB0qUM4Nej5evP91dnWjsNmVb9fZyzrDJekx6gyKBnp7equF1R2sLHl7ebF27nKSsXLrb2/APCaehppLailKyxk+lo61FpQK6e3op5dFi7qdI9i9lpAogqSgpZPz0OYrUYbVx+8WnUFVW4rRytrWoWrthcQmccMYFhEdGY+7rP+zzFVujzraP1at3UlvdRWRUBBmjkijaV09OTjUzZlVT0aXn0tOKuO5PoXTrPHnwst14uHkpa+nit/bjqciCc53XbMvjyyu2ctwDUdw+uRytxsFHTcN47cOp/PnYb4kLbseksxBqtCq1Ts639e2eTErdjlavR6PRYbP0KzKVPGE2eSddREtVKcNGjObOGRcSOGCbFOI38xE/ir7pY9pVD3HdkY+R41k3ZPPc0xnKn/56CtsXvkFTaaFqmeAbFE1e7un0WbspKfucilUeh53j1yx9mo4uPfUlu4hMH62WVe/J58ZTtzA9erP697oDsVzwJwPF677h1OM8CQ/Ts3htIFOueAFff38ObF1LfJazufuBHRuJTclA4+aJRUi+3kFQRAydrc0EhYRw7+mz0dk9SUk9EV2rGR+3ftaVf6oUXgmrKd23h57ODhrrqtVgMzMnjznHnoyfnz8mvRadTqOaostbMOm0vPXm66xc4exvKpB724IFC1Raqwv/ffhvGYcM7kf8bQ+hG7Dc/6uw9fWx/6HbfpP3lpSUpCYkxO4o7WNc+M+dQ7d9sRU3z4Oq0r+Cvu5OHjou+z/+/fj/IBPlIlyNHz9eTQ6I21Ba23z++efKKSV1ar8ZSRssjjtw4IDqm/ZrFMf9J/HfcnF04Y8FsQuLnfGez47i1rx9atZ/EJd9kMmr132CD/5c8fZ07pu5Uw2+Dm0MLYP16HEGupsrfrYvzI/xhgoDcdDU2MyLz93L+Q8nUK+L5uPbC2ks2UNAYJAiJ0ZNDfs3DVd/M7itn5vFerMlgucem8UdR7zEsVM9hgbZRRY9J399KiVXPYxvcAB3PvYCt115rupHtm1dDKmRygypAiJu3J/D0gv2UV1Twi0PPqOUtaiY4arXmNnSr6x4QtAEm9auZHhiirIKCiEqKSpQRMzb14/G+lrVv80vMEgRLlGxmuprFKFyaDToTSbqK8spLtzDyNzxap0S7CHQ6fVKWZS/aW9vZcuaH4hJSME3IEiRJlHmhCwKOWyur6atrZWkjBx1LPt6ulVKY2BoBG1NDXj7+dPW2EDRzs1kTZyBu4enSnoUi+aGpYtISM0gPDaO1qYGAoNCKdm9VVnjAiOilTXT3eROUGQ0TXU1ilBptFq1H2LJlO15+QfS2tzAvm35pOWMVU2gW+prScnMpb250fm+66oxCsGRUA+rlcId+WxavQyT0Y2Z806ks72VMP/9dHTs5KuFfWj1HozKHUdwaBBnzHueGM9+ZWFcVBXE3Mgm1fOr1qIjTG9zRsOLBdIBbgMp8/k9nlx5QSrb1nxMR/lwTIcEXBT2ulO8K4CTTlxB0mV3Yxvmjq5ex4vHfc7E4Y1D59ahyY5ftIZy8cxaOlvrOP6OFxQZlfpMo2+getzX149DayA0/c9cEFqASeNgWWcYj789m33PPkpociYvv29ljq9z9lLW/X2zL/c8Po3YnCn0drTQXl/Nts9epa26VL1myuVTWXJH9ZC1RL5bR95zDMEpEzD5BKpWCr3tzXj6GHlqwtmHfR9u3/gacyIeZVJ0idpWt83EA+tfpKfHhtHDOZPv5maiu61FkU2/wECaKg/Q1lBDUlo6LXXVBASH0dpQy+t3XkFHcwPe/oGKvPkFhXLkGRcy45j56HHg4WZiz9ZNhAYGsuaHJeSv/QFLfz+R0THMmD2H4JBQ9T384dtFfPrJxwTpojj+wXHU7rbyzbuLQOdQrR7+HbWtLvxvjEN+7yRNardF1ZABsgv/GfwRSdrNN9+sXIbSwkgmCrZu3aoyBkS5lZ+77777t7E7/rg4TjyYv0ZxnAsu/J4vSGL3ldpMuTCJ1UK+I4faLH4M6SUmccCvrpnFBfH7DusFJb+qLBHqcS/dzB5TOUTQOOS3iAgPvRfMBRP2KlVOkquqqqr4fsXqofo2ae5cUlykBod1tbVs376V3q4qdq4NwkvXit3RyuxFAdx2xjG89MI+UqOkF9UIqa76yT4fGmwgg9gDvX6qpqe8QjL4DqLTpsdm1jHvqLNYtupTero6ue/hM0lI+57kSJtTsQGkVXJOQA3bs0+kuPhOVfPm4+9PXU2VIlsSbb953UoycvJUHVdwmPOYCOER8iWWPyEvJjdpAqwlNCKC5sZ6KssPON01Gi2bN65WwRsRMcOJjEtEb3JXpEpnMKh1CakRwiShHqKqSciHBIHoDQZFkMQCKCqUWCD10nQ5IIiw4YmKeOl0enwDg3HY7RTv3ILZ3E90fDIBYRGk6McqK6ZYEDuam9DY7YwYOxk3k7silEKobGYzsWmZTnIVEqb6rZXs2w0Go4reL9y5keRRY2hvb1Nqmihy0kRbkJiZg4e3L90drSRnjVbpjnpR8eS80OlUsEim1OuZTMSnpXPmcV8S6VVASdsuCnZ0cdYMZ6PqM07QkTOliYsv3MO4bDdiPJ09GIR/zYtqUnVjgnCDc/lgSucgQRNkuHfDqQnMtp/Lu7t3cMFIp0VUXpfk1kvy6GpW7RjJ+PR7mTb2Mgyd7sRe0XbYuVxv1aLX2ik1e/DQ9olkDzeytvt5Cld/w9iTL6KmcAdBHgHq/Wi0FpUw/OH3mazJGo5BZ6OyJgiPJhPjx1zAihVP80bFRUQlrSFcb6XRpufJovFsePdJKrevY9Il9xKWkkNEWi7lW1cRlpKLJbiVVT1PM9a9W71HidNf+eGb6O2vM+/OV7H0dePp44/WswYLqtxy6Hvw1RO3c+cHDUPvx0vfj2P/EzhCr1FqrLdlB+NDfqAzLIXlhaPVeeHu7at66pl8g9F3dNFjthKSlMH1L31C5d5t7Fq/XBG0ky++Fq2lgjHRd9FSX8nzL/rQ0+0gZ1wNT92poc+h464nw/j0jXy2bFrHNTfdToC/P599+gmebr5s3OdDrHG7+u6+e+VUzhu7jNNPP13Vqkl5gqjw8fGH93tzwYXfM4444gg2b97sImn/BfgjBYc8+OCDnHvuuURGRqrxl6SMintGrrd33HHHL16v/r+lOM4FF36PqKurUzWZjY1OVcBgMChf8uWXX64siP8fUdu7d6/6PTWq9rD0PQlUeKcmjtLtzkG01KHtqA5msq+zKfSPcXJsDRcAjz7+FMkpKWod/WYzG9evY+UPy1RqpAwKPTw03PDMCMJPiMa7tA8vnX3owjfPt4U5X7Woi4HsR6C+m+J+I/FGs7KRre7yo7TVn+3VYVw+Ygd+bv181x7OwsWjGW13cOtdDeRNCyAjykqNxcCDhRPwX2ajsHwrwxOSSRxu4ejM736iBPY5YHN7BHTZFClavfRrZcFra21hzIRpBIeGK6Ih+y9KlgRSBIWEKatib18v4VHDMJrcKdtfRHnpfjJzx6n1CqGSi6TE66ePGqPUMLESiqoloSRSI1VTUcqenVtIzxmrrINpOeNw2A82iROyJlbE2ooDRA5PUNa7uooD9HR2EhrjjODfvXkdKdl5iiCKwiW2UVG/zH19GN3csFmsSt0T5Ss4IkoN2CWJ0d3dk4qWAnx8/RVBEzVMiKKkRhrdPBQpFNKVM2mmal6tCGl0rLK9CSlsaahV1ss9m9fh6eWjLJ7NdTVKOczIHa/q7JIzc1U/Ly8fX/ztt5HmW6qOfU6gmVHTneeWIMJgY8WycJLc+wZMgwfh+H9Iuqxn8LG8ptuuoddsRNfix6VztrDoz+dx7uwijg+uGyLvKb79eIfFs3zDS2p/N7TncXKI8zsjFtknKzL5oS6R7g439HvcsHU0ERKZSE3hdjyCIglLNeDmH0J/dwet9bWUbV5B06Y1aM8+G7sJTK0aPKvMaGvlfcDW5b7cpJ1BuHsHZZ0B1O4NZ+qEG1i+6jGqdqxFnzNZ1dTF5EzDMyCEjvY6Hjswibzgcix2Hd+XJ5Mz/RiKNr/N0qduYtRJlxGRPobWOjsrerwY796liOyaHh86NMG02xuVoqeOE7C9Yj9rHjqB+ddexP2XfqFUco1mFf6abTy/cALpE2dhs5hVrYK0VPAJCqW9qY6OxkbiMnPJmDKbno522jvbOTfjWvz0VvCCCX/uOOQ75OyZ9uTNDVTnX8ru0gV89uECqqvkO+/gr+vTiDU6az/lczgxupzzBnpGDeKJJ57g3nvv5a677vqb1zkXXPi9QAK1brrpJnWPHTlypLonH4pjjjnmP7ZvLvzvwmAwKDv5/fffr1Q0KbEYNWrUv5zVof9vKY5zwYXf6w1BCNqk6FMJyvOnY7uOPZXf8OKLL3LqqacONdP8MQYTGct7vYgz9g8RtRfLU3lp2QTKPrkXN3d3lbD48LElXLgP3H6kpAmsErcNvP3mX8nIGsXY8RN4/50XmHuxN3+50o+xYQY19JYBpae2D4ejmN2ZEuFwsBbpxxcC2Zd2u45Rz56DdeMu3Do8KNr2GT32dl4ceE1eVjyRwTtZsHIhIeFxzJlZTXhUIrHJx+DVa8PNvIUNu7dy75OvYmldcBhB65IaoV5vPquPp2VLKK898iHaZxN5ZU03T90xn6ZWD0aPn8L88y4nIjqWoOBw6qoq2LtrKyNzxqpAkMJd27GYzUQNiycyNkGlHkqTaElxlJRHsUDW11Qpq6OQIom537JuBe5evlikNsw/kPi0DPVehMRJI+rAsEia62vYs20TKVnOXmsSCCLETsiRl1+A6vnl6eevbHdJWWNU37WAkGClrAnJspn72fTDN0TEJhAdn4TRzZ3kzNEYDEZVO1dfVcaInHGkZYtVUaLzfSjaka/URklzlAv7vh2blSJn8vSis65aWSpl34R8Sv3ZIFGLiktSkfti/5R1ibImzaS7OzsIDY9S7QOaGxtIDW04+NkOULHBBHz5FWbqP+ycEgImBHpRaxjH+dcp+2K9VUOo/mCN4p5ed8KM/fQ5NDxSMhrTZiPuHlKPB1/d+Dqel0/jmDsGSJ0kelpMxB91Gi0rP6apoZQbHw2l/VY3Et3bWdEWxZfrR+G1Vy88RJEtfWMbfd69GDx9VINwS18PDl2rOr6BwxLpt1jI//glMla3YvfyRtdnx7i/EfMwD9gH9W9+gtbvcko8pSm1Fp8y0FeZ8YtOpGjVl0RnjKVLY1RKYV9XO80FuyirDqM8LhS7VYOmxkiIxUJu0sks/f4hPP38uGLs6yT77WVTtw+Pd0RhduhYXpVEYFIQbzX3cWrgfqUOr+sJoDbyaCKG/0B61MfotQcHiWkhW9i5og2tmweB0fF0NNYSERJEW2O9OlJiRQ0Mj1DEvFfTgdHYj7/hp31JD/28PLV26scFkGkfz5KNH6tlO/dnkObuJGiDkM/RO9SXj5Ylk+DdybNLE/nLRd8rG44o/9JexwUXfu/BIRdddJH6fd999/3kORWsYzt8MsqFfx+kQtZZJfvrrOv3ALHZ/ppW23+apPn5+VFbW8vw4c6alUPtWyLzueDCHwEyUy31ZDJjMnrMFD78dDuhehs9drjhnQm8est+3nzzzf+XpElxqcyyXHZCM69+7s9w9y42NIVw59x8etoWKTZz9sWXU1Ndxbdff8kti07gzqP2YNLYMWpQP3Kr2dnizrd78nhxWQKLrn2P7Zu/oXhbAl4625Bl8dB6H8FwYz/7ejxI9uhR/x58bnAALkPCJS3D8NxjZePyD9UyibWfkDWLxJSRqjn01vy1eDf5cO7l13PkcfNpb2nm/luuZOkXTt+1qGCnnX8FMcMTWbvCxolTD66/zGLg8hVHE/x8JQsXLcY04Kn788xGHp81nIJ+I0df28KVZ8zj4uvv4ohjT1bBHLEJyeomK8EfElIhdWUtzQ0q6MM/IFitQ+rHOiR2X/6h1bIzfx2pmTmqz9hwCW3QaBSxsWs0SrEymExUHihSPndJKRT1KWp4oiI+oqYlZuaq14jaJYpZTFKaUq18AgJV3zC/kAhaG+pUzL4ofvKapFFjVBhIW1Ojqndzd/egu7MNk7u7alYtPdrcPLzo7mint7uT+PRRKtRD9qdFratDqaG9jfUUbttEbOpItVxUusbaKgLDIpR9VXqjyXIJewkOj1RkRpIHN32/mKzRE9Tx2LN1I5u7DWRf5rzYy0ewuC2YyT5NSvlZ1R2Al93BJF+peXOeU7eVZrJ0ZzqanR48Y2gkZHovlwzfwZzg+iGi7W2wcMRFR6H19MStXUt4bT373LaoWP/pp1/Mp6+9TtJpR3NydDHNViN3bpuGsUtHduJcvih5EMdXK3l62C30h9nR9ujwKQS/FVVYrZ04+nowTwin7sudzL7+cUWIO+urlNLkEz4cvUaPT0gk0dmT2bj5BTITjiZAE05/gpH8/DcJShipXh+wtAlbdDBasxC/XjT9/fzpMgvnnNhNg+1ZXth6FZ2Ve7DbrXS2d9P4/kfEnHChOlCmFodqZI1RzI1wwYxvyAvZq97/bGMX+/YH8sL+bBx1JoI67SxYP4Yt6VEYtTb21odjbzcR35tBi38vNkfTEFmttxmo2LmJfWu+4Ygr7lXpnhKU4+MZgK+3J5FaLR4+flRXVdFaX0NiShItNg3+h/SV+7E4v7PXE32bg4I9O4eWpbr3/uSaIyp9w9YQDJpWtY6njiog7JtJ3H7kt0pJ++abb/7xC6ALLvyX4seR+y648FtAetvm5uYqt+Gh+POf/6zaQUit2m9C0sRf+ac//Ult0NmXxc7atWtVeokr2tSFPwIktUe+B4OWxT+94iBEkSJw18C187fx6i3w6aefqlq1n4N8d7744gsmT5nC9JTB5s171SA3MTGJY0+cT3VVJUu//Vo98/yln3F4fqOGipIkJgYJ0eph8kmbaD4+mUazEU/t4QO0Qwd1MtTrsWs4+5tjeGnS52QG9w8FlpRa9GxoDWNl1TC2vhODR/0GtfzuP7+o4vF7ujvZvX0rF197iwr28Pbxp7mpnuqKMmKGJ/DKB4sp2rsbu92mIvMliVESFb/5IpWbX67kovM9abIaeLBgPKZFWvY1vIOb/mCPt0ESl2oyc+nd3rxXPonPFrzGzHknKEImNj6x74lCJvViqnGzwcDmdSsYkS11a3o1Eq4qLSFi8kylgEkvNFmxHFeBEKGujnbKivYQHB5Nb3c3VqtNBaYIEZRZ1qDwKEW42lucSoQQPElLLC/aS4z0CtNq2b7mBwJCw53ze1qtskImZuSqOH4JEBF1To7DjnUrGJaQQlR8skp8lHW5ubkrG2Vp4W5V/yY1crKPQsB8/AMZljJC7UtbUz15M+YqRUyWiyUyc+IM1TtN3ntNWYlKcxw9bc7QMRT7ZPakmVj7+9Qxyxg3mVcfXMw58bEcnVvBjs5gFq7NwbPIjDlbg7XeSOD6Hq5/YjnR7p180xzD18tyiVhQx76ad6ntKsP0oieZd49nzgX1Q4S/qM8bhoeS1/sC9z9hUgtvfaqDgNjTmHrS2YpAPnnSx3x0+SXY9eBRpSOwpJXuAGdYS1h8Km3vvUdC8ok4dHZMVZ00VOezy7oOncGI7UszMaMm4h8xHJ3RRGBSFj2tjRi9/elqaaCuYAu5869m/duPsWn7u0Pv3zs0huxTrqR80/dsX/8yU3uvw17TBh1dZF1Wyc0XiKplI8RRxN0T7iDco1393eKSSRzzZgn6dbvw18eg6bVAdR0HYhtV37uEGGfAyCCyPepw3+qGqd2BR0UvtscPsO2yDBwmB7pWLX7VDui18tWaKMaOspDl1k6HTc9j5blkzEyks3ojS1+6jwte/Q6NwUic9yamRb5Ff7g3S0qvRqv1U8EiDaGRXLZqFPeM242/zoqPzo7Hj1TPC747Gr8V5Wzr2qfO80Gl4Mdk7sdKvPy+OmM/twMFBQU/e51y4Y8Lce8OOHh/lXW58MfDH6kmbeXKlT8bDjJnzhwef/zxX7xe/X9LcZwLLvw3Qay70pz9tNNOO2y5pCjOnj2bsNAwMgJy6WkR2+DByHFBoqmPV9dO4+IJy1Vj6kH7xY8RExPDs8+/RH7+JpoaG+k3W9m8aQMlJUW89uKz3Hq/L2886pTNF7cHcuXZ3tTkL2VkZg49XTVEetoPszKFa2yE63sPU8Z+PFCTxsEPFOfS/0wxo6/cjVZr4MyrphI0LZjlq+Jpf2MZB1rfVIM9mYAR2+EHb77C6u+/ZfoRRzN1ztEqnEOUJXleCIOQlPWrvmPxp29TUV5NbHwSdbVVKtJfmhpPn3MsV53zBt9+OophsUdCexcG+waqai1Ud+uIHAirGMRAL21CwyaxY9sKmhvrlN1RiI9cc2Sb2/LXqUbW0ldNVCNppCwWx+7uLiZMn6N6nw3OqAYO1LEV7tpG8shstaynq0uRqKCwSEVcxaoo70saZgeEhCu1q766QiUuCkRhk+AQOS6Sthg/IkvVmwmZEqVHCJoob6KylezeRkpmDp7efqrWTSL+hXCJsubrF4DZ2K0smkJkJLhEQkHE4piUNVqFp4jVTUiff3CYUvfE7lhTfoDopDRFHsv2Fagat+CoYXj4+tPf26vSLkV1Gz1lNp6eXrT2dNPS1EhYZBRTjz6ZB889m7pj/kSfzpeIynYKt39Ew6sV5KTMpKa7ivm5ZaTPvwW9w0DYrjbK6r+numu/Ip2i4D1w57d4TJ7HcTGlhBosjDB1MS95N3edYhoIF3Hw3M3ehIz6VIW5DEsfxeTsZl4/4w30Gg2vPJvKGnMYmwu+JSotm3GnXMIHd5yHzqQjITgPa7Cesrpy9O0m0mefQmzOVILjUunp7VHrE+UQh42+dmlToSEoaRQOrZ4Jlz5AR/V+etqaMHn64hM+DIfBg2GTfVTt2bKNDxOSNIo+aysXzzlYiycIc3cSNMHchNXkHn08+V+8xfDsIwgIiKZBU0rltpVknnwVO/u3kuzWq26YcrZ+V+OO/9JKjA4jNLVQbt2A8eVKIsccha7fjkdZJzqDhgMLVnP/5POICmqlo9+Niv2hBBq0RDRFUCjhO/nLyZ6czfnpjytLMjTiY7yReRcOI3PaUdhtVuKKqkiZah6qBey1HyRc8n22NnjQ31Kr/u3rH6A+d3mNh/an3//DJmwGamAFriQ8F34WvxNy9eyzz3LxxRerFFh5/Ldw9dVX/2b79UfHH4mkdXV1qbr0n6tVk3C534ykDRbHid9XLI6/VnGcCy78pyAJiGJNfOWVV5TCdeWVV6rzXCkzP8L7779PU1MTqbps9C2eOHRaJgdtHyJEg8mF5w+vYvsrc9QNY/K0WSp9cdwYJ0GQSQ1JYByTk0VTUzPRw+Lo6TOz7IsnefDdbFo0E3jnnWBuOCl/6MJ0tG8z3z8dzZtHaCks2oq1z0G7NRlvnVRJHdz2j3HogK7ZDqesPob95y6kxlykLIlhEVG8/ewyeObg3Vgi8EeOyuGEY7Yyb1Y9dVYTN7yr447rLuLYDWdzwRU3sGfnNmbMOZbOjnY6az/h1rPWcM/ZUGwO4PxXo3jgT1dy7mXXc9E1t5I1ehx3//llXvjzvez9+u6hweTc408jNeMDXl05jQT/VjI8uiQhnB39Jj4rzMK/1am6CHGRwBAhQ5LsKKQwZ+xkFaQhdWjymUkNVmN9jYr5l4AQrU7Lrs3rcfPwVOswmkwqbEPsh0qtcjiUMicESdYnFkOJrJdm0ZL8KGqaNL2OcPNQ9V4S4R+blK4SHIU0CcR2KHVmothJ+IPUpWm0GqLikxSZFEIlkNo59T462vAPDFLP2awWrNJrra5aqWvpuePxDQpRfc+kJ1pFcQEGN3e1/2LndPfwUgmXYqcU9VCpaSY36OxQ78nRhwpEEVJp7ulWBHTfjnz0ei0jRo9n7mkXsPj9RxWRlGPRbK1VPebyi75TASYSs7/73XvJnjCDWlszB9p3MWriDC655wnqyvazI38tt015mqurE3DTOPDVWrjzlA1DTcEZSDyc9PB5LLvir3S2NbPjyxCMGicB/9OfdvH4W19htnsy6axr6Gxv47hbnmHF20+xYq2z0jEsOYuRc04lLm8GOu9AtPI59vdj8g6gu6WB+n1bCUgchVdgKLa2Jtx8A7Ga++jtbCcoLh3PsOH0tjWqyHyjpw+p886np6GK5rICTH5BFBj86bEXKfIisP+oNi9q0nzMxnCKv/+Isrbv8QmPJeu06xk2egYLyjU4YvOJNnaxpyeQhTWTKdz3MHaHDa/QSDqayqCtBKObkShrLHZfX/Z47qS3vIGKRzfRftIRYNPgUafBvaEPvdaEVvrktTQSHbzxsPYboV5WGmorWHDvVaSMncrH7zhtyQJ5WXGfO3YtWOxaHi4Yh9deDTZTl3p+5KgxrFz6NXs7PRntdzCh9dDAnkHIP8/8c7Ss8f9V/F1w4feAp556SqUqC0mTx/8f5F7hImku/DswYsQIPvzww5+EMH3wwQdKzPrNSNogJLbXFd3rwn8jZOLg5Zdf5q233lIX5UsvvVRZcWVg+2NIYERWVhYlJSUYjSalGlxwwQWqZuySSy5h4cKFqmlsbFSYen1xcbFSwPrL7Bi0WmZ82U7AYE75j3DsxDY+ur2edevXoUVD4b5CFWAx2Gtq7bp1bN++Xe3XgaL17PghCjetM+Qh+5r6w2aO5PHN0bt4tjgeswPebIhh8kmFvPlOCFHuPQTrnYTg0IGY1JZdXjieIzT78Qpx8Mq2XNrvraLWUkJkTCyPPf8mhXt38tgLb7Jj66YBC6MfQSHhdFY9zvlz5Y3ZCNb38ORZxVzccDMLn3+MKbOOYtZRx9NQV6tUrlOOXDPUGyvJZOGqMyvQ5Z/Bwg/fZu4JpykyOGbiNKbMnsfG1T8oFS4rbwK9XV3kr1/FZTO2EuaRQ1D6eLSnetLa7EvAkj4aLGsJCYsgM2ccnR1tiqiJQqfV6PDxD1CkpfzAPkpLiknLylVHtWDXNjQ6PUFhEQxPHoFGr1NpglqDgdDIaKXIiG1QSExXZzsanY69WzaQPXGGaiidmjNWkcHegR5qQmSEXDVUlRMSFYtOZ6Vs325FsGR7QpB2bVxFTGIqkcMTVfy91IZJ3ZwQQInmT88Zp/qoyX7Ie5Cm0yV7dtDW3EBKRi5aZRu30VxfqwhYeMxwZcvs6+tV52S/vpdhqSNpqq1S6ptsR9S2yuICZZvMzJusWhaoJtt9vQSEhynrpMT3W+0OzFYbJ5x/JdOPnc+yz9+jobqCM666hQlzT1T2SCGC0kNu2RfvcWDvTqzmfuaddyWzTz6L3ZvWqGMyPSaOPeuW4q51picKxDhYatYz3OgMtiiyGChvC2X2pMv5btXjGDWJQxMHcialTA+jtjiMsIR0LDZw6Awcc/fr1OzJxz8yFt+wYao/myKxdgedjbXUFW4jLDUbo18QwSm5GLz86Gqup6O2HG+rTRHqwKRs9B4+KoRDEhPttOCw2QhOH4cjXUOCpw+2vk6W1qwg2KuTVLc2aiwexBo7yHZz1pyt7/HiqzvPJ2HWqZx3y3xuOX69+o7++QsLhb09HFjnw/PWSXia+qlv88FS7cHEuAtYVfYa5r5uRp8vkw8Otn/wFKU9S9U6jV5+xE8/hbrd6wn8KJCgwAz0vTYM++tpT9djLeolMnsaq7bnc04aeA1cnkotBoKPPYu8wg4WffUwtX25pDrnGtTxPGD25oGH5mHV9uNe2Y+pegu7+rcTGhHFtDnHqO/Y2NTtmGsSB9S5wyHXiO09BnITxK5drJLwflxj7oILv6fgkNLS0p997MJ/FjL++lutiP7Zdf0348477+TEE09UfaSnT5+ulklbJpnY/6X1aP8wSZO4fYmVlCaB8vhvwcvLSzW0liK6wToQF1z4rSBNiWXyoLKycmjZxo0bVduIwsLCn6hjksIoBG3WFWdwx9X70GHn/vv9+fadZaqm54yzzmHliuWsHHi9DGYk1t6IL16mEOYlV/+sgiXLNpT4kZicjMVqV4mDg7HlYmH7cMHbbN62Ev/kaOq3VnLhOV64aUOG/j7J1Eu3TYOn7mCiXtRAryoZHJ8SVMGCq84gN+kxdfG65dk8siebaO5247RhcpNy8FlLFLs+jOfdV9/Fjg2DMV+pOv4BgcQMC+KJ+49h2+YOQkIjVFS+9BsThWvG3OMw6QpxODyG3luA3owty6hIxuplixkzfjI6nZYlX37CzB/1r9drbRCSSmvLAmqrKijcvYO0jGxFTpLTM9iycY1KKmxrKObV17wJivLniQVVfP7n79H8oCEhYQTF3W00NdTx8Ivv0NbaRF9PjyJA0pts28a1pIwcpRQzSWmMTdQpoiGfV+aYCep1YlsU+PsHqQbVUqcWGBKuCLz0LpNebLmTZyGUeUTeZKUICpET0iUNqWvK9lNeUkBSpjPxrupAkVK6xHIZHBGjeqOJRVIaUSeMzFYETEiXarbc261SIr19/ZVCJhYI+bfUuIlaJ6Ek0XGJJKRlOGvLyvdzoGAXKaPGYNDrlRXT3csbdy8f6ipLqSzZR3xGjiJw29f+QHLWGPp6uvALDlUKnsT0W7ssisCJArzuuy8ZN3Oe2p7sY1d7qwpQGZGTxznX36X6rrl5eqnIfrFIpmaNISIxhRPOvxAd3ei8htPW2oqHXwDD0rJo7ejCzcOD3CNOobj/AxJNTmWwzqrh9NXzOD19p+pxtrg0BX2RCWuVGXMf7DMbSDE5SVClRUt/8rnUffMEq997kQlnXoPJL4Tu1kYVAqL18KOrqxOTly/Wvi7nd0WrxX94GharhVFeK9F6mtnRPsmpWmt1KuHRZBL2YlF1bDqTO03F2wlJzkHvE4ilrQl33yC1TG/QU1Nl4y+68fi599La5UFqcB05fuWY7Qa+Lh9Jcs4YCr56hS0vJqpgHsEjp33HCQum0fnZetDPodHLga5Lg3elnOduxGYeSc3+dZiCY9DZ+jjysS9p2icNyq0EDE9Fa/IiOCWHDS/eQk3oZiLDR9IT1E3F9z+o+H+jTyAOjuCBqgMcH1xCt13Pc+W5ODR6+nZ3E5OWww0PmHjnERPhhn7KLe48tmsipl4Nli+Xscm8Ru2nEPuTz75E3XMvu+EOXnn6IS65t5Wn7wpAh4MvW8P57Gt/IiOsfPZKG5Vr1qq/u+a6G9W92gUX/lchzhVJJR82bJjqD+iCC/8OSGsHyRl46KGHVL9od3d31UGkAwcAAQAASURBVJ5p2bJlTJky5d9L0sTWKIPfwcd/C/39/apf2tdff83bb7/9i3fMBRd+CUQxE4J2/8KjuDa3SC17cFUCj5z2DRMnTlQ9ggb7psgMh5yj3oHDWXBLPv5apxr10SMdBLyv4YfvlymSdii0BpPqdl/cthN3iw9XPzKWZfetOqwOrM4Ki8pjuPf473jkiWdVfy8pjxqcTFy3ZhVX3VDJiblxqr6lwpJCtMF8mArWatNx7ftH8Pz8pXjrrSqyfpzXQV+zbE5rcJCYnEZlRSmPXL3RWR+m0XKp1ULaiPnEBkfjaPqGOXPdeejxYfTr9Lz7nZ6mdcW8+UQ7ek0oddZwvikI4oikWppsJq5+oZdrzz+FjBHuXHiKx9AFYkuPP+b97soqV1NdqWx/onKljMjkmtsW8N6zoeq1VRYt75Rm4VHlbFbs4+NHYkq6IqYS+iHkZuK02VSUHmB80p+ID5LjYuPda+GsEefy2Tlv0tPXSXhUDJfddDfJ6ZlqPTsLdjFu6izVF0ySHeUAmNzd6O7uJnp4PG0tzbQ29yl1zcvbl5qqMgp3bydjIOWwQTXIDlH1afJ5RMQl0dbSqJpGS42Zh7c3G5Z+TWJGNm02m1Kl4tIyVdx9V1srOVOPoKOlWfVUE7IkFsfujjb6ensJjoimvVn6nIUpFa10706lbgmhk7AQIUT9fb0qiTEwMEQdA7PZrAiepDqGRsXi5umt1DNR+XbnryUyIUXtV2BopGrDIAmTYosUVUuIpoeXryKDsm0h3ltWLiEtO0+RNqmPE4IrREHIqhDcxJGj6LPZsXc5yav0chNyn5A5Br2XD96Wtzh5xFvKdrevw5+3dt6g6vKChyXQIWqbpzfhsXEc82wWd1xQhZvWyl/Ls+jaHsKanWn89arFXBZSRsMIA9eWTpUMHC7aeCQXj8xHr7HzVukoHM2e5Iw9g40r3yAifTQhiRn4hkahdfPC2i9x+76015bTuH8P0VkT0LoHYLU3cueMh0nzKVf7XdiymPs3P4m7A0y+QfR3tdGwbyuBCZnK4uifmI1Va8AstWtWCz0tdRg9vNEYPWh443N0vpfQ5u1A261hY4g3u4MisVp19JV7EmnyYfaFUzFqDk68GDV2fAO80Wq09H+wjNCsGWitDtxr+8iIL+XFBwrB7sfLu9vZUhlLb78Vt/BE2iv2Yda44WVyJyAhi9EXP0DZ6oWUFP6Au18QKXPPJSR1NB7+IfS2NfHeQ1oWzz9eXSP6qzzwr3GA2YJHqD8t2xuYe0ciUcem0NHugX6XGyElLbjnxcAaDcecfSmZueMx90qdpYPQsHDue+w5vvvqc4Jivx24dxerz1tInEykzjnyKE459TTcDFrGjHG2m3DBhf+F4JBrr71W9UcTR4wQtMmTJ7N+/Xo8PDz46quvmDp16m+3M39w/JFq0gZbMsnPr4l/iKRJ1PjPPf7/IN3eZ8yY8a/tmQsu/AJ8/vnn+IYGcuvooqGB1gNTSvggK1Ypar6+vqrJ9Pnnn6+eq6qqImb2NAJ0u4bW4amBD9eM5cSx62moryckNJSUlFQKCwtUnLrMPt93z53ssK4m52M/bpqZykMTC5S1aFc/3LNiGl9d8Co+vn4UFuzB5OZBUkoq9fV1LPzkQ8zdhbz7qDPVUGqw4oxOZUJImjza3+/OXSsmseH+L4n5UynuWm+8DP18s9GbUaH9itgtaouge4kPbW0tZOWO5YbbH+Avzz+hVAdRrgr2fMReh4OUJB+++Es4GszqJ/cksJ0YOmSDCtPbOW+k02IZ7ujh5astHF96Ejs+/5jJp/VxzdMJHDB78dGqXDILzbxbWc5FV99Cd2enIirZYybyxH1aZpyXTOQ5URQ3heLznZ6Gpi+IjI4lLimF7q5OQsMiaGyoU0EiUcOGs275Es7MO1jDJ3VzEzNqKcrIw6G1ce+Trynbm6RDigo5dvJMRYgGe6UECSFqaaS6Qpo0a9Rrt+evJ2p4gnrsHxRKYnqWUqokUCQ5I1t9Diqx0eHAZHJDrzeyY+MqFe4hxCt5lFM1UyEi9TUEBIUrO6eKnPcPUKRr14bVJI7MVuSrYMsG4gZIpKCns0MpaUKk3L281DoKt25iZN5EQsIiMej0iiSKfXLXpjUkjcxRqppYFHs62xWpkl5nqTnjMHl4qnh+qXELDA1X9VNS8yZHS6yT8j4kpERq2wSJGTlYrFb8PLwUAZPAD1HJakqLGTlhukqclGVOVW0tyRk5+IZE0NHqDFiZGPXO0DmR7NNKW82tbF0Sx/33BuPwMPDOV+m4ByZQ9OQC/mx9hP5QLfoWDYE7+rnt8aW4DzRHD/awcMwVP/DFGm9Knyzk/lPn4jCAoU5HcIUZX6P0IbOoujJJNVTqok6Hta9HHVMP/2ClPHkb6jk18XG0mt4hgiZICajGq38XvY4wzD2dqm+aT0Qcff1WjL7S/69TpTF2l6zg2bMWkRDYxM764Tyw9lrs/b34LK9FEx2O1uLAWqSjK85PzZ741IK+y4pWlHJbNcMG7oxlFh0rX3wIg4cvFZu/wMM9gMiucBx97Ty4bheGwWtM+Kuc8MlzWK0ou21I5iTsVjM1pSV01e4nImMSE3JnYe5yWmxDTbWEBmnZXVqGh7snAVZ3Gu7/gajcefh2O/AobsEWYqdk22qmzz+V527cSFzwbspajZz/5wT6PPZwxRUWjj4tmpuueokv33qJ8OhYjjnpTGJih6PXaTn6+JOYe/QxlBYXqs84NS1dDVQHMWnyFMKDXcqCC79/u+OhEBXjzDPPVI8XLVpEWVmZctHIhOztt9+u0shd+G3w/9XK/9J1/RHxi2vSBDIY+jmvqEh8LhXNhf8EZNb4nNvGoNGUDC1TkeGLDTy/50iun/WNmmGT1MVLr7haDZL3LlyC5amIoQGXnNZHRjvj13v7+hRJKCwowC6aj81BVEws9zz4KPffdRtb2hdhecCI/rthij5kucNTs1ZRefUt7Hj2Ef76l5dUQoGod3PnebLoq0i0WgnZcQ6ufwzps3bx2qPIv+jPKrAiK2cMJUUFtPZWk5tl5bhzz6AjLhrNNk/8WjezrbGB+/78IqX7i7jtwcepKi9Xj1ct+5a21maShxUeFkog0P1MiMAg4owWlj2zm1fOmc6Dx/3A+eOamD7lRNxal/P+1jWMnTydaUccpayFK777Wtkfb7rnMe696Qq8832JTUhic8FuNYP57BufqmbKRQU7ycjJU59Dwc6tauP7iwoo7zYR6+lsqi3Nk3d2hJIUlciytQvUNUVq2YTY9fR0ExYZo643B4oLaG9tHdpfSTYU1UtUuhE5Y9EZ9EpNk2j9qJg4OjpaaaitVgqYDFRbmxop27+PtJyxqt4rYcQopVLpDSbVV03+tq6yDE8fX0WKqg8UKyulKBBi0RTyJT9anZ7hqSPVfgoBEpK1b1s+Y2YeRUdLk0qDFAxPHaHqHJubGrBZLCooREJAxAYpyY4SFFK8extWi5XQYXGKZAuEAAsB27xiiVLVxMoogSWlBTtJyR6rXiMNrYV4BYQ4FTx53FQntspGVeMWk5yuLKZNtTVqOzpdi1qemD0WT79AWluaKNi8TtXTORIOPyFiZo7gofML8DU6CdKw0zbz8Lf3E5cxmrpPXyE39nSsbWY83bXofQ4/wfzifOnvLqR249dM9sml39cdY4cZt701lIWWYxBSkjASa2+3svt1NdXSULKbwKRRGHWSjmXngal34K1zHosfn6svz3uA11aM4NvmK/Hy92Zs3Gq0Rk++3tKOzWFQatJtp/1AclCDOudGhe3nxBHfsiEynu1rX2TCqOsw1nVhaW3Gc3Qydk83DG396A7Us7/SyJvNSUzwqsTu0LKgLpO+xm3UVa8iOHMahVs/oEhvInemH0at99A+mXQ2LD3NdHVr8HAz0tdapQamendvfGLS6Ou3YG2sk4JZpge/x23ztqh9K0sP5txnjiR5xkmUbryM3Z8/ROroY+jw6qZk1/dKdbv9xibig23q9cP9zdz9UQ3jgjWYNEa1bOrsLB64bC7r9r7H2688xbW3PYApwE9dt3QGE1mjsn+2nmP1KqeJ26jjJym2Lrjwe4UEe4WFOWvIFy9ezMknn0xSUpK67/+95EcXXPilkDGPhNZ89NFHqiRG3DKHQsLjfgl+rq7470IImMjJ4rkc9F2+8847Q89LDcaxxx77i3bIBRf+FYiV5/Pnt/1kYCcn+uXpJdRWJnPJmyeyYcMGvl+2lCOPPAp7Xzdl/cbDk9CEzMiMeFiEqikzW+3qtwQaWO12RU6efO5V5hx1LPfeHaKk+MFZo2CdjecuWY6lJpHOykTe2jWFCReN4aMXgok1mYkxWDAf0m+ze+CxbHNZZyjmL539B0ePncjw4Qd44qN45tzuTIZc+NZ7/HDXI3z/+Z2s2bCE7NHj+OS9N1m36geK9u7h9WeuYdaUp3nh+SKOvcfIN981q239+HhI+IjU/ZSZtUMx3AKhFhF6K7ePqeTo9y5W4RUbt35HW1czl1xzC+dccq2qmWppbCAtYxQxsfGMmzyTlxYs5Mjj56ukwJyxk3jytQ9VOIk06pUm1NIbTI5ZzriJeHp7Ex4ZzeSpVSxvD2RbnwcPVo1k86IUmroPqNeJVVEsezK0lDCQ+ppKVTMXHjVM1aN5eHiqUI/UjBwVRCJqnZA4P/8gRUwkUER6uIkVcPeWjSrGXVQ1T18/ZQuUZEexIMr6RHlqb21SNsSerk4VoS/ESlIgpXZMlCtR16RGKikjl672NhV5L33SpIZNnpPm1KJmSRCHbL94z3aVpOjh6a1IlJDEwh35UkyFbSD1UVQk6dk2PDWD4Skj1Otk3Xu3rB8IETGSlJmrCJtYH8NihisLpkC2KY89vX1UwqScPW3NTdIMgtbGBrRGN7VvqmVAYBBlhbtUzRwm96HP2moxk5Q1ho6ubt6pG65UXDlP9vUb2FobiZ+z/Zn6CXWz8OZtp+EXFklfXzffrnuI7R2f8tWOp3jtQBLdA+dQk13Dq6XZjJ5ylvp3/oZn8WpvwKu3k/bELvZuW0zy1GPp7+qkra6S7pZ6jL7BBCfnqPqxnrZGNJ2L8dFL8/CD228Z+I4M/vuiqbuxdtfxyOTruHLMx1ye9SaPHfUCZo0BnXcA4QFyTA4izLuI4UdeiFtgBKs2Pcomvmdl5wes+/4++jZtwFZRRWOSjpL3PuLzkmyeqpjMIwem0V/ny4cvBvPEY2nYmgrJueYVYqadisf4I6h05qUMKW4r7j2f0sWvcnTUX/nu3FtZct5tHD9iDW6Bkdj6e9Cb3NU5etWRB0sGYn0ayRm2g/qqCvIuf5SwjIkUbf+WsqJ1JE2ex+wbn8LDwzlhNIhovx7cDonXT3bvZt8EL1K1E+nv62P9yqWHf9etdueE6u8kTt2F/y6746/181shNDRU9TCVQfO3337LzJkzh0LCXDkJvy0kFOvX/Plvxr333suTTz7JKaecQnt7u8rvOOGEE1QZyj333PPbKWmyE5JiIjHlEyZMUBd/kY8lQU9mMK677rpfvDMuuPCvQrq933bbbXxYncBJkfWHR4RrIERv54XZO9l4XCIfffA+L7/2Oou+XMj4uQ0UL/XHT+cM+HhsQS/e3l48+dhDpI/MVLMiJcX71Pku1j1RJKorK+nt6yXtMa/DepIJAZoQ4Jw1kSHxmUE1zL+Dw/ZFggkGiVOdTceLm7OpL3Wn4gtPWqs+U82Vp03ax8PXix2pm7Myu7ljxik8O+Nzps48koTkVFpr3+KBh1qxajt46LsILjrtaMr3JRHp7VzxjSPKKV9wKuOO/Ybn3o0jw7td2QorLHqu2jad1p2+9Ha5E1e+m3PvqObooPqh/RPjWHxsK9GxcaSkZ3L/k68oZa50f7EikEJem5rq8QsIUNbHutoaZs87QalEUrMnZEHUNrEoDhueqNIZ29ta1UEKDA5h+pHH8uFbr3DbOV74hs7D1t1HnOEAX65czDW3P6hUNCF4chyyVQ2aRtVwCZEKChUbYgOdnR2ERERh6TSzY9NafANDlD3QYnb2cBNiI8jMm6DImpA0gVgOhfTJTVxUMFlv8Y4tjJ4+R70ma/xU+np7lN1QFCx0Ouory/Dy9VefvyhYUvsnwSDunt4q+dEnMJj+nm58AoKUqiYR+l2h4ep5UbnkfFF1at7e6oPfvm4FCWmZzuCPvl4VSd/T262i/1W0vszMWa0DiZDhKtlRiJ7Uvck+yDoHlWOl9OavV3VzQuik/YAoeY21NfT3dKm/SRs3BY3OoBQ16f9WVrCL5DFTVJuAipVLeeszN5ZfN50Qj0621MSiyzfSPZGhxsntdkg79Wqun/gBU14MYGd5Crc/EUJ0WjbvP9FNxY3TifNuYndrJBX5UcR3tqhj5O7rz/dLn1Tr0BvdSJt1CmPPuoG+jlbVcFsmPjRmp5pq6etRn68tNohmGwQMTCG22TU8XZ/EveH7FNEYnETxM39FtIez9lEwIrwJL08dPS0NbO3zIdbYpM5jUWnfXtVLV305GZc8TuOOlbTu24hvXAbd1SVsqfvcuYIy8IpKon+dgaK4aGLc2lkw92M1wTM9B2KC4YaPthI8Yjw9HkZeb2pisncl0gTj/bqRpB11HHUbnufqI8IHrgUOrhm3kEUFkzB3tmDvasQ7NgPLj0asVv9qVv/pKvxikkmYOZ8RM44jcJizpU3N7k18Uz2RtMQv1XdX3ssXzTFcG16i9ks20+fQcPMRK/jgwxh1nq1Yulj145s6Y+bQLGy/1Y5Rr1Upsz+G2easz3WpaS78L+C8885TA+XwcPkeapg1a5ZaLuUOKSkp/+ndc+F/FAsWLFAOLalJE8Im11MJsRMRS0SBX9r64Z8mac899xwvvfSSCmgYhKhmkugobNFF0lz4T5M0KRI+Y/QizgA2lYwi28MZljAIGUA99ZAP077oUwP1hx97nJdffJ7Q2B1ED9fS1Wbj0ofTueH9kbx2TyPbt33OHS+MoFYTxVNX78XYuJbH30ql2xTOo3+JZPvejcRPMA4RtU6bjkCd7SdfNFGsBi2Vg/shf+OvtbHFEsHqa51d6SOjhzHryGO45LzNakAur5OI+3kRJWyaeSbb8r/G0lvNd+95o1O2SQtPHnWAorvPI8x7zRBZlG1mRNTz6uYWpqS2kRw6AfeTZmDVaLF8uYWC8hfUzOJOm42FH2rYWzSSJO9e9bfVVg1bK4cREFiukhDFGhceEaVIg5Csuppqenu71aB645rlVBU9jpc3PPpQIwZbKnc+8pxSIluaGlTaohCOwj07VI2ZvGlR2S657jbe/ctztG9a5txfvZ4jjkxn99ZlSq1TlsewSNw9PFRgSPmBYsoOlJAyMNAs3L1NkR5R7+JTR2Kz2QkMDqO+tpqccVPUb7EwSiCHWEe3rV+pepi1NNZTub9IKVehkTFKscueOB2b2UxPT5dSzmRdFcWFhEaLjVWj1LXkUXlKtXNz91SpkJ3trSqKX56TOjJpbC0BIvKZST2cqgFra2XP5vXkTJymCJ+QQsGYqUfQ092liGTZvj1qn8SeKBZLCQ+RfWtuqFVkL2WgZm7n+pVDVkdpESCtAEZNnq32Ny13vFLhBomdED8ZsEszaA+bDU+9QSlnovJJK4G+fjOtLc2kBi3i2Ss+oavbzD0fxrK2PxFjO/hua+P+kzM5N2wvdoeGV2pGct0JOzgx3R2Nxsb01Fruuj2ShZuPZ+s1p7A/8VH2hsWj7dIQUGDDLO0NtFrSjziV8JRRisC6+QbQXFZIf3cnRt8QfBxa1b9MCFvt3nzC0kZj8gulqNzIq8nxzPUrx+HQ8EbtSLbURnN8wAEyTRY1K7++15Ner1L67M7vhtCeXgd0tvfTXlHIBzWZ9Nh3E2LoZVtXGOuLYtn/5l0knXwjJt9AEk65Bb2bF5aOJjrKdiqibvIPx9LVSvlrL5B2wo2cdsa2w6zCUyd74bliGDaDL9q+QD7dl8Om4Dj6bXqqqoLw9TEw58zjgQ0Hv+MSDLT6EzyiM/CNy6Kttoov28M4wa8WoeKSgLnONJ3JEyexadcbHFi1kLhr/4zOMwBLbzeBybkUlRi4oLuJ8dHVyhK8YkcafcnunJZYQKTeiq/WwRnDSpm2pJITT7ma+vIlLPz4XeITE1UarZy/JoNWnZcysbFuzRrq6+sJCw/jwfvvIzbWWR/rggv/LTVpDz/8MJ999pmqJRO3lrTEefTRR0lOTv67fyvjUOlZJQFiYnU0mZyTc3Kvk/GBC78d/kjBIXV1dcphOOjoEjVNMG/ePCVs/VL80ySttrZWfWF+DFkmz7ngwr8bW7duVSmj0q9M+lEcamGQgf2Jp5xGcko6zz/3NGMStvGn9+by0LTiodcIMfputdP21dfTi6e3F1decx02G3yw4E3eXFJNpLuQlRKOed9IoikWk1aIXhe3rfTA7ohBQzcaTTcp17dxzjPHMiV3CUEmsRXBMIONRquOYL2zjmQQtVYNaxujMWktzAutVWqaPF/Y70HnTh9FRsZNmsZFl1/Hs48/SGWDhmF+zgh+eV212RODzVvVN3W1SDpjzNC6vbUQPVbP1joPxoQ7m9922mFl7XAyRo2mZN9eCupWw/OrFXmy2awEhYRiMhlwMzRTWtbHiNSdPLtyLl4+vbxbmIn3+z6s3prPtbfeh0FvoKPdqVoIuZD4/X17duHt7YO35gFeudfZyOniOWGc+UEIF82fy8vvLeJASaEidcGhzhoBseAJGZO0x1PPv4xZ805Udsb1qxbzxN3biAswY3NU8fjmVVx51kucceHVHHHsyUqR0+r1DItPUnbItrZWJkybQ4ckLPb3KcXN6OZBfU2VIjS9Pd1KDdtfuJsRueOcCo3NpmyOopbFJqWpQauQLiGRUoO2Z8sGZR8UBUiSE6UGLSA4jN7eXjLGTcUswRP+gSrgQ14zSLokKERSIKUWrWCg55ooWmJnlO1KIIkirA117N26gYy8SRjd3JXVUUJEQqOG4eUfoCyMotLJ33j6+quWANLIWvZN9jkhIweb1UZQeIQa9eROO1JtQwiGqpszGinanq/ee+b4qRjcPfAJDEFrMlFZUkRtaTGjZxyJQ2ugv6kBX+925sV+oIiEv0nLUxd9wzGzx5EY40vgyNVs+WwcX2ekK6+wpdSD809+b6jHn/wO8t/Dklf24R8eQ+e3nxMXOBMHWtxqmjnj/r3cHxFBYV8bq+uD8QyOUI2ng+PTldJp63AqzX0dLditVoKSs7HawdxST/1XK1gQnceK4CT6LQZqS4MwNGp4KjSPMX5l2OxasnV9vHx8CzVWA+5ai9qf9xvjWXP/qcRMP4PCPUk09Ppi0FlpavbB2+pGSMIEyr55naxrX8PoHagIWUdFAd7x0mMPzB3NuBnd6O9ro2XLGprP0ShVXCzA8v0rt5oUofSKD6SvpY7OzRUUT00FhwZjoxZTu43mPiN7LTpSB9plbOpzp6FwEz1L3iE072iiZp7Dc6vz2Jt7AE+dmfzmYXTU++Ct6yMz+yw2Ln8Sc08XWl0zNpsFv5AIuprr2PxQHfkJIzEFReBfbWfl0zEsTGoi/y8H77mRBiueVxhIvWcWbb4NbFq3muGxsUppFZQUF/PUE49htlgIDwtn5Yof+PKLz1VEdF5e3q9/oXbh943/IElbuXIlV1xxBaNHj1YTbBL4MXv2bGVjlFZQfw8/11binHMOT2p24TfArxgcwi9cj7RZ+vOf/6z4iYhJTz/9NJMmTfrZ18rEgIhQ0r9WkuoHxacjjjji724nKipKbUPGpQkJCXz33XdkZ2eTn58/NFHwm9SkycalMO7HkE7biYlOi4YLLvw70NbWpuKic3JyuPDCC9VFW05+uZh3DUSLD2JERgZPPP0cQcHBvHDdqqG6L4FcNHLGOL/xjzzyIDdcdzX333s3W7bkY+ndTqT7wWKTNDczpoFvyaA9cbD+TBBjMOM9wUB/v/2wGpqd/R6c+tpUCto9lX2yww4vV4/ksSviOXnUKkZOKuPT0nBeqojnurePI2T1HpV8WLz3By47bw5bN63n2GOK2dHhTbNNy/edfjz77VS6W3cSn5jCrkIzrdaD5LTCoqN8XygTcnfwekkC37YFceWuSbS+FqMaVk+YNpuv1+zktgee4IijT+C+x18gKcFIwXoPitZG0VSRyLRbJnHVpG957VxPGu/8FE/PJ/Hx07J+9XLMln5V1/Xpe2+w+IuPqK4oUzVzC/76Imed5DO0H1Irc+bcZkUU1vywhJw8ZwS+1IwJ/AOC1MVPFDaxIBrdTMoGGea9jLgA5wGWw31hdiPh4/NY/u1CtUyImYS8hEVE09xYr0iU2P88PL2U1VEUoq72FnZv3agInYRHyPMpmTlKSZO+WjnjpyqlSrYtKpfUaq1f9rUiOUKgZP2ihomKJaQvNTtP2Qq7O9tU7zSxctZVlOLp46csidtWL1NNtaUeTZIJBdIzTSyEEt5RXVqsWhYI0evu6cbD10/VkUkKo6h3ZSWFKpjEodUqda61oVbZHyOGJ9DX1aGCQkKihqnof9lvv8BgVVPX3tKsCKbUrMl73L7me2Un7e5oJyoxlTiJ4Jf97uqkp6+f1sZGAkIiSM4eR0tzq3qv+3ZswWJfflgtpafeQbf7h7z0xjc8+kAXS65ZyszCOjy+9SJkjZU17aFDYy35vbwzlubqMkWOK/dvZnvZO7TpCzj9z2s4bWYNo9NMnJ2zlBTdW4p4uvmFojV64BkYpoJXRD2TcBSjr9hSNbj5BKjlDTs2ot3gQem2KGq2h+Gxx0DQkk427k3kL4UTSdBYmOTfQKCbleEGC2s7I7m1YgJ/3T6epFGnUb7sHaxfldC8O4jaPaFQ4IFHg504n9HKdthTV4qtv1ftk2/iGHTu3hi8/FUqo9WuIXLGuZTuXsh3NaF80+XDASts7TPwWFkeBz59jN0vXIrd0kvVovcIWGnGf4cG/0I77mWdtO8y8WxNLm+0h/BKawT3H5hE/LwLiEs+lvqNi2gt2krHMli4Ppf3d+RRtCeaSdparjl/PdNS96tjW1tWRO2ejSq5sqe1kebSQkYcfR71iz+k8JnbaNjzCTv7F7FzySqlJKpyM1ER7dBm9sSiN6oJn67OjiGCZrfZefXlF7jpuWxqDsSxaZ0HN3w0n+CgEM4886yhEDAXXPhvgNSSnXvuuWqQnJmZyRtvvKHCGLZs2fKf3jUXfkf48MMPVUsGIfkysS/k7Mgjj1Tn0s9h1apVyh4rgTNyrk2bNo2jjz7677YeExx//PGqebXgmmuuUeqZcCJxHQ6mif8mSpp4LefPn6/ejNSkiXKxZs0atXM/R95ccOHXwqmnnqpmJV5YOZs5sdXUm9049qhqNVPy8ssvc9VVVx02WyYzbtdefyN33PonNrT5M92/dchimB3QTFquN0ddGcK3yzXseiufV154hvBQAw6HM5ZaXjsosf94DDP47yablrYqb97e085tF/uqZf2i1DXFsfe9DkbctZ2RyeF89lUgN0bvJu+vgZx9UiwHCis4ZfwqFaLh77uU4m4NK9ckMTHegc0BH7aEc9bI1UzKLuLIaVeC3Yh37zZ+yF/BPY8+y19fepq5J3pz/cte2Ax2Xto8Bt9PqlQ/tluP28LEUUehM2rZuulZAgODuey6W/Dz9+eUsy5g1lHH8fYrz3H/A254aJ1vxEfr4L4LOln+qJbQYatY/kIoWo0bXY8Fc9prGs4+bgbxCSH86Y4+AiPcuOfxdqq2+NBQV0N9fwwBhu6hY1PZ76X6p+3YspHTL7hc2a1279iiequp42+3U7R3l6o7CwwKUQSnu/eQFAapx3KA39ixbPrmXnq6uyk9UExAUAidHa1sXrtCERax9YmKJnVffkGhWCxmssdNor/PrEiW2DGDQyMUKZEaObH/Sc+xkr2bSM8ZpxS0qLgkpUIJ2ZFrmd5kUjH1Qhak4FfIkdSviXImkHRFIWiiuEm6Y3dnuxrgSnhHVHyyInNi1fTyD8Rcsk+lTAqBFFVOCImEf0g0f1BYpFIzBaIk9XR3Urgtn+Qcp52xYMt6FSgiJFH+bt/2Tcr2KCjZudWppmmc5E7CP6T3myhnYit09/HD5OHBztXfY/T2Z1hqBkZpki0WRL2evq5OgqOH88FnKzklSUOI3nkO7Op346m/jkSvcSqmcuqffdJKdpzrrOd77utkbMc7SHdvYVt3MG+ty2NCTiJLf3iCOdc8SMnGFZQWrSdvtNQkOr878j3JTNrJhnWNmPr7lUokSZYGN3cVtS+pjF2NtUplE6um9DrzCAile+kKwlOm4NBrMdX14thVgveKdHrjfUnJlYCUgxOrbhZYuzsZtwN6Ivoj2e/uRfl375Ln8QAWXz3GDjvuB9rp8HXe7jqrijH5h6LzCVVKZX9bvdMSGDwcbWcL4ZNOwWbuo2Sjnr9EjCXIvYvWPk8K90eSl3sdm/e8Ru3qTwkYOZVtix8le/gZePQYsep1FBuLqV2Xx+aEGIzYGadpIim+goKvomiISqdxy2KGHXUF+++8i9Rjr2VsciXPnrtE7dexs6FHG8DusCTVnFui+vXeAfgOS8E/JIw5t7zA9s//gqWzhcBhSUyafwnrq95jWozzu1fV74Z1swe97Xuor6tm2PB4dZwsdgcHSvbRb27i9iP9hmZm7xqbz/oJp7F6wYOqbY6oFi648O/sk9bRcbDXp0AmWf8RlWHQOhYQEOD6gH5HkBrYn6uD/aXr+iUZGpLqKZP6AlHRlixZotQysdT+GPL8oZDG1AsXLlStHEaNGvU3t/XII48cpuRGR0ervA4RtqTR9W9G0k488UQ2bdqk3rx015YBSlpamlr2996ECy78UjQ2Nir5+Lq/Hs0liYVq2TCDmdoV3vQ7vLnmsxieueoZ1UhdIqevue4GNegODAxU9ro1hWFMH9eqVC1FvOwadn4ZhkbTzoOz4dlr5vDC8T2Ulq9SFiexIg7i+/YARnm24qtzINpVmxUabCbabQYe3DKBxGVm7vyqgcBwL0450kCTTU9dhTd7Ct9QVszPPvVi+EDU/DF+jdz5biq351Xj4+vDsmVhjIqwYZW47oE7mQyijvGvZcbr17D8wmf59Gvnlz84JIz5Z13AcfPPJCQsnKvOP5U7T01mTPo0tI07+X7td0ybPVc1c/5h6WeKxEyaPouzL7qKpJR0WlubqCjbT1BwKFvz13He+V446Dp46ZNasaiRPPhQHxqcBMJLC9ee0cHsexvYvMafKC9Z2seXj5qY/UgIla/t56abInn86QqCDP3k9/jx5rcTqKp4iaRUL9VkWiLyI6Ji6O3toaaqQilpM+YcS7PUb9ntKujivfc7uP6+ODI8ulRt0TtN8Zi2OSPYhTTV1FTh5m4iK+4RrjnVxp46LTdc48P8C25k1LjJSl2z2W0Eh0XQ1dlF8d4dBIVH0t7azK7NG0gckUVfrwl3T09SskYr26JYDWMTUlQKZF+P1IcFK9K1U3qhZeao50UpE+XM189fWQ1HTZhG10CPuL6BoJC2pnrVI62/t1sRDakHk5/MsZOVBVJUux3rVqigEbE9CiS8IzAkXG1DWgA4ujvJGDdZqWNCtpIyR6sQFLFAiqVR/i3NrIUsxY/IUq+RVEp5z8oO6e6htiWvNUtdmkZDUu5Eper1dXfR3NFGffl+YjPz8Jc+a00N7FiwhMuOnc/pMTvpthl4pSCP29IO1jQKetw9WbntDfXYWBzKC37XovO3YG014rNTh7vZaT1qrS5j/JlX4+ETQKH5OuJNzjYJckavbQvgq7vOYfq1f1bhIL6x6Up9o78PnckNTa+O1vJCgkZMwIaG2InHsPWdh3HXmIi0DldfiI39P2D55DvGjLuW3Wd6EmtsU98TOUuX7huG124D3tU2NK2dKsGxu2Y/ZXu+I12bg6ajhz6DhcK2tSppMWDkFLSefjisZno7mumq3Ivn8Gz0A2/c0tVG8KhZNO5dSeGeaPCy4+jX4F6uZdr4TkbmjuPtt34g/vwXVPBIfsErGHxDsfV2KoWt+5lqTOecw+dnv0eMVw+MhmWBwZz5eDTtldsUcTaFDmP7+3fz6A/papuyabk2XXRVGCOTT8A/bgSjT7sGrV4mjeyqTYFXcATjzrlJ1ZK11pRTX7yTKdEHJ0dS3frIOrKEqq+DMGgNKszHanOg0zqUuhwd63ZYjZ3UxMnh/bnBswsu/DsgA9dDcffdd//d5DsZY0pS3sSJE1WtmQsu/COQsDdRw35chygOrHXr1v1D65AAss7Ozv93ckDsjCJQ+fv7c99993HjjTcO9aIUC/mvYSP/p0iaJIldfPHFSsZ79913/+WNu+DCPwrx+srFOjej8yceZ5mHe+aECpJTj2XTD758/NDbvPryS5x74SVo9SYmTJrCw6d9S9CSmUyPreJApzdHDvRQEsjA5bTgA7x10VlwxyquerCD5+/wUY2mN/Z48ae357Ljofvwdfdk6o3HUFYTTuPHy6ju2A5sVyESyYkeXDRPJ3oNfjozD49by77HriL/5ucI8dWi0Rz0W0a7d5A1ajyhfpsVQVP78HPlAG5adZG46KobmH3ksQxPSFJ1VS1NjeTkjeeZvyzgo3ff4JtVH+Hl7c0Nt9/HUcefSv6G1Vx9850YDEa6ujrZu3ObIniCgl07yMgejZ9/APfd08CHr2rx09lVdPoL+3Oor/qAbrsUZx+0j3bZ9GhwEOV1sMZOUv9mnu7D+ud6WfLlYvzd7qTIx4Sh1U5I2252NDVw5oVXqtcKwXn9+ddIin2fqdPd+WGbnXOOM3D1rfep+ra0jBz1uovmJ+Jx+XCsBg39K7zQVi0jIjpWqU8SANLbfDGzRjp7Q02KtvPAaw5OmXAhTy/4muaGelWzJrZGUaZqK8sYnpKu+p6NzB2r6hqEJPXV1xAaEaVq1yTYQhQsnUbL7i3rGTFmoiJC0kNNvd4vQNWcBYdH0lBdqcikEBw3L2fsfX9fj1LnJD1RCLEQKiFdRTvyVcy/KGB2h12pcSmjxqh4fyFsjbVVFO3YomrZZCKhZM8OYhJScPfyViob3Z1D6xIiKDVwgWGRzh5rYvH08kFnNKnwkO1r16tAE023005avX8fUckZePn5K0Kn1DOxU3p4ERwTr9YnP5r2ddz/J3ca9/Vz675jVECHR4mOF2w5xOd9r+qbmmw6HikYS/JIX8r2b6K/pZ7gT5uwDAtF1+fAa28TrSHNimHEj52l7IyNlSU8UzQOR/I6og09bOsJ4tMdU/Dw269UoClXPYrBJ5Ce1gaaDuwhIDZN/TsoOUepV/0dPYSNmsKwA7spWPsF+6R/ncOujoFMIhSUf8n79aPoZxfh+l62doeydtkwgnZ1oWtopyfci64tJQRlTqNux3KavXaoxMaO0t047FYST71dEbX+9kb07l5kxVRz89k/4GAlDy89mlVFbYRkTKbfZscukd2fl2AclYLWAi+etJDxiXXqOJ8xN4RzPmgh4aIXadm+hP6mCqVi672DoKeRxKK/EuN18Ds/dVYjLZfuwicpj/5eM3Gn3EHp53/mgLmT6QMETSaP6rUeZI27nPKqH1j26OUcfe1NeHvZ0A87GpO7Jz39vXS3NuHu48/wzDxsvDqkUqhfbg7swyMYGzyLDbuWDcRWa4iLi+fF5y1UmA3EGJ2TH3v73dCvK1Utc8RC7oILP70J/UrHZGA9EuYh6b+D+EdUNEkS37lzp3JsufD7wr+jmXXHP6jGStq8jJekJcOhkH9LyMc/gieeeILu7m6VFvpzKCgoUM8LSROXoaTcD5K0Xwv/FEmThryff/75v5RU4oILvwSSQCYD2o8WGDjppsPj7FX6IXB9+l4caTD2yKO4aco3nHTa2crONO+E+TSIEvf8ejyuSGJZUTBHHNMwZPtxDKhYDoNTPXrzlWbe+UsbCRNOxNCqpaXxLezY6HGY+fz+d0lJMpC/Mw4/YwK7+zw4974I4utXHZY+5Kd1EJomdWpaPl+p56wZzsaGUpv2ZVUyTQ0rCfA6/A44mFQnQ6gvWiPQLHE2yx07cSrhUVHKqidNm4V8rVm5TIVx3P/4C+jEZlW4l9QRmSr2XnqnCaENDgnF28cHNzc3ujrbWLH0G3ZszWfn1k2kZ4zixScf5rLb7qV5cgctbZ74fd1Mv7WHm2504+1X+gjQW9lvNvL0RlFk1lNrMRBucA7wRO3aWe8kfsnpGbz/4X1qv8TCJ2rR9bc/RO64yfT2dPHOX54jJuJtrjnFA4fDSuYs8I4P5sa55/PQc2+w5POX2b4tkdig7WypL+C0Ke0Y/HXUVJdzy4PPKrLz6bt/4Y4HAsWs5vzMhOx696pam28/XcDxZ19KT3cHnZUfUFPdRmzSySolUZQpn4BAFe5QtHc7vv6BKkmxralRqWwZeRPVfo/Mm6TSD0W1kDoyIVO1laXKBieWQznGBVs3DlkOe7o6qD5QREp23lA9mvRIE0IkSY++QSF0t7WqIJH4tEyl3AlJs/T3qSbaqTl5qvZNIvFLdm9XZFGCTtqbm1R4SOxAP7StG5eqRMfWpnp1ou5Yu5yk7DxFCiX2XwiaxWbFxzdIJUmOmjaH9hax9WpV0mTJjnzSJ8zEzdtPWUjd/QLRdW/iivGvokMsnmsZsaSOVxZMwFjTTNGuRi5wn0eETxvV7X50rgsmMciffbt+IHrEaLbkv8xY7Vn4EUxbZAcbVr3H8JwpeAWFYXDzoKFoJ9VVBu7sm4Obm5m2Jm+8Soykxx3J2jUv0N/VjkPvTEKV2jS7RofdYlY9xITlNBTkq15hGWfeSvSEY2kszKe/o4XwMUeo1MZ9n7/IjoLjqevxVQ2kqxv9cO8xsG/He9j0NlobmpSVMfbIi/GKSKS7vhxzeyNBmdNxD4nBPSKN3tYmuir24BsZzQvnv4pxgOW8eOJfGbv/evW56fU6jEHDKf70AcZ130pQsG2IoAkmj3YnKj+Mpo52fBJGYx6WM1AcZsfW1wn+u9TxHrzGdNs12Pq66Ny/ja6E3fR5+BI183ze3l1B4rBPiDf2UGc18nRZDo6s4eQ2zSXn5s954MqP1fVtX+syjr8iku6WJjJmHEtc3kwcdgevFcZwQUqF2s6qbl82740nvLuLdmu7CvWRCSTZL7kOzDlyLsmpX/HQwhnY9CYev6yCxsL31PVBBsGTJ0923Zxc+LeSNCFoh5K0vwcpYfjyyy9VeY0EM/yj2L9/v6pjk9/irgkJCVF1bqLkSZ2bC7/fdMfof1KNlXHjoXAmZv/9nZK2JLJesTvK+fNzyMrKUi0fROWV9T7++OMq2fHncNddd/Gb2B2lOE5sjiI/u+DCbwW5sMsXYeFTSznX60hevbQE90NmaQ79zl0QV8QNdgc1tVXEDIunv7+P0+Y3ctsFQWg0LZye0sJnTeGcFFQ79MUP1MIdx3zPn96YRXnhUnLyxrFtzcdKPY5PTObiK2/g6BPns/Dj97j2wq8INjqDQrLde7jlpi6uHGemx6bBXeuMzC+1GKkpDlLqy7ln7uHAi2cRObrh/9g7C+goz3X7/0YzmYm7e0IgQhJCAsGdAqVQKHV376m7K22plypUsBZogZbi7kGTkAAB4u6ejP/X+w6Bcu4593/PuUfvybPWrGSSme/75rN597v3szdrz8aiWxVASckCSkogu9GTwV7NMkj4u8Ywvv8yHYu3CsMhOycPfy0Zs8yhI+SM0Kbf1pA6eCgGFxdSBg1Grdaed7ZMScuktbUZJyedlHd6eftSVVkuZ8mFgcRd107h2x99eegOOFBbwxVDDxERHcuP372A6yp3Bgww8vCbkcy6L5H7r9jHjbfcT1OWHzSCT0GBXMcDz43kwWcPY1CbWFQZT89SRw7ZHQ88TkR0HJt/W4WPbwD9k9PkNrY2N0nQs/z7r/htsy92u3DEdIxlBwU2SXORbz6dx9x360nwc+y3UUE9vLkpjNtHHOC5uZ+CUiV7mApyDrP62GCGjD8iWUdpXNESSEKKL2dP5nP8yD6uGv8eiekO9mJVwTbefi2coeOmkDLUMfhsqKnCxz8YD28fCe6CI2MkwBLgVwAmIcfMO7Cb8LgBWMwNki0TjJYAbEJGmJA5QrJTQuooPpcAaF5+gRJ8iR6y6IQUvIXcsrVFyjhFEHhMcjoent4S6ImHsOtPGzFeyiJFILaxu5u0keMlwBPMnWDmXL195Hq7OzukzFGYiTi7uNFcX0NE/2QZDyBZlY529J5emI1GCrJ3S5MRV29/+WWh1RtkRED/5EC05hM0tgVKSabJYiYrfslFkxyjRxfzxHMVoFVRuS0H98g3OR7kh6ZLgXduN0a7g1Ude9tT7PtxPh0t33DvQ55UVVtpNmcxcPYjlOZm4xkShbGrnZqfVhCteox2V3BuAbdTHeDsmF2sPXmE8GFTpQ2+OLaoNLSUn0br7o3G2QWv2DS62tqkC6hbWD90nv60lheiD4pF6xlIR10Vyi3NVGX4S/pZ06DA0GjC1NVEA9V49MsgfOItUlLoN+Qyx71B5MO1N8m+RNHjJWSOhqA44uPycDrXkylKL9wR3fQYVZ60FOxE698PfUgCB46+z/h7J52fRBElpnNqTp3EbIjEVHcW94RRWDtbUBm8UepcyG8ZwdauI6TpOqWU+cfmUJJuuYHyTaspXfk64Zc/jc0/iu6WTB471EmwXyvNPc5UFfvi3iNkK1aeuUf4Sjq2r59nG2NmGvj+pWJ+m/cEI2ZM5q5bNZTnW0haFM2ImUHYm5zwWtvFiZwfqDGfJbZfgjTQsSvt7N27m/z845i6bDw6YROhxBChCMVHkYYmxirbGEQzvbA776u++meXDH2//35JCmzfvl1GSfwlzpDCHEJ4Jghw99prr8lBtpiI+Oqrr1ixYsXfddv76u9b5f9DNtbHx0eOj/6YNaurq/sv7NqfMhwRvWzLly8/H4b+p+qbb76RIPHXX3+VwG/dunVy/PXHJf73DwNpognulVdekZpOIZH4YzvUvzawra/66v9X7733nmxuX/HeVjJGjmZCdAWearOcRfbTXBhsOcZRdkxGk5xJNrZ/xQt3CtbA8X8x0PLXd3Cg3IshoU3ngUO6vh79rGvhtc1o1Fp+3X5IMhzevv6Ogby3D6UlRXhKA4ILOWjuGiOBQeNIHLqdd1dl0qlW8tmeTKJ3NXPEYpHM1sv3fE9svwGgKJes19Dhoyk4nsMtV/QQMnoOrX4KuteUkXf0LcmSiMF6ZHQsDz/1Iq0tTY5+qMGZclv1BgMmUw9e3t40NTZKS/6wiGg5g3M858g5gw4FSoWS7L07+e7LT/h6SRBjox0ZaDNDm/n8wBjuH7aHK6+7hZzs79n1UwRKhLW8heRTaYyM/QjDPhcp+xOGHIkDB/Hbj9+ga3+Axi4dGnMdu7M/YPiYiYwcf4mUYF52xXVSXpiXc5gTece48sY75ecQwdP7SpNITi48b7hyrNOLqNh4cg8fICSw3/n9KSMMvEV+nUWCs0HDhsmBpgiw3vheFW1+WUwOP8Oxdl/W/JhOY+VCGU69ZfnjvHrthRvvtP5mrs/bJXPWBFATwGrAwMGCUJPgR5RgHetrKjl57BD9UzPk34R9v2QrnXSE2mySGRMMm5DbCVljfW2VBDte/oESZAlDEPE8MXMkWp1OAqeqkjOUnzlJUsZwCaAEEyj6zgQQFI6Sou9NMGgnj2bTLy2Tzs52CdoEiPMKDJbLEA8hZxQyx8aaKnkchGRR7D53H3+5DAHMIhNTZc9cSFyi/CkcIsXnE+fAhIRvGeyxU36u/JZo3lk2mZAB6RxvMzFRkJLnqs6mo7I8RxqOCOa5PXstMbpRWDt60BisHKhejV/0AIw9nYy9aibvzy6RQFlcThNn2PjsZISjx0yjJTAxg+wfPsElpwTnTg8UPWbsbc3kKHbhHZVAUNooulubJHMmnB6Nna0yfFrnG44NFWqtMypnDdVHt+HTLx2l3g3vmAF4KAqpt3tJhrB47UJSbY9jMahwarWhO9OE1+DxNB5egv+gSVJyKAxKxMXSXV+O1s1XAjy71YK5vUGeT2p3f0ye2VRZIOjct2CpWUVVzkFcIlPQB8dj17oQOPUPGLO/YGhkIWdMWgI0Jnm/2drhQ+kvH2K3K/Gd+CDGlgbJvpk627GbjdgVQ3nztCspvlWy3+9ARRQ2dx1pqiFkB3VTu28FhohkLO1N1Hxyhvaxg7GrlOjrFeirTdjbO891hV4o78E+pPcbiZNvHSs+2oZeBYp0uOpSDaFODmfI4lFa5lwzBuVJK6dP5XN4/x7Onj7Bwf175T3NxceLdXujCNd1crDJyqdpUdSdLaOhu0EONESuVF/11d/LOOR/WsKxecmSJZLFcHV1PT/Qdnd3//9OJIgepFdffVUSCeK9vSWc+gSr1lf/uBJya4fk+m+zrL+Eje2VcW/atEmSS70lnots5/+OQRNujOKnCKb+70rk9i1btkz+LozGRH/an2Pd/tr6i0GamInw8PCQDXl/bIcqBoZ9IK2v/l714YcfEhQYxM597kRoi+Tfum2wpd6TSX7N54Oivz0l8sNO89G7b0pZ3+ZVYmr64qowuaAr16IIc+Q1ievfW23DLV5I1+xUV1fg5uFBfu5RPDx9cHP3oFGwHW7uvDvfyFsPiz4taLHCkpIkPNwqOHXKxC1jcxg2YjzNZ9ey70QeE6fO4OY775Mywz07tkqnv1ff/USGVW/fsp63X3mWE/Nfk1JiwdqFRUQxccp0BmVkEZ+QzJGD+4iIisE/MIi62mr8/AOlIUDx2cLzn+VUQZ6cTRJ5ZOGRUfR090j2Rtyk6mojyTt2mNhwR8hi7/0yzr1FMowHD+zlgUcSUSku9KD1d+7AN3kAPjYN4yZfymVXXMOR7P1s2fALK359X4I2IWmcPH0Wdz74JHarjfycI5I9WrLgLR57spOkq5x48amvCfSfIU1DFr+iwjovlkzvKo52evHZ4lGUFr0pl7XiZByPp+TK/SmcMX+qisXTu0xmrI2ddrnsyxsxfiofvf40/eZnMs8eg7rLQpD6DDklZ2UgdWurXfb19H4dCPOX1CtuZtcPy5h96/20tTRKow4hvzy0czPhsf0lyynAkehd8/YPpKWxnqT0LGkkIoCycJAUYPHAlnUy66yXDXO4P6okm5a9ZS3poydJUCf618Q9MDgqTgZjt5wzRiktPCF70gQjJ97vpNNL0C8s/j38AmWP2Mmcg+fdHEUJZi52YLqUORp7uqkoOkVMigNICtAoAFz0wMGyV6+rq0uiW5E9J9gii8lIeWEuaVkOgCYqweMsVXkrMVts5JyNIsGvmWRdG01WNc/nDyctPYbjx9dx2aNvs+rtRylTHcYrOIL6Y4VSKjntvhdw9w8hNe7biwLZI9zKyd+8koi0ETgZ3PCLSSI8fQz7dnxMQGwq7j5hlFfsw9jVysj730Zr8ECjt1N+aAvecWlo3bzwjEnC0tPpkOaptNi6OzAERmFVKPFSlPHZrLfx0HbT1KXlFvvdlG5ZREPxMSLbg6Cti44gZ4pPrsUrYThuMYMc8mWDpwTWdpvo97LLDDRxXbcV56IPS5LM2tlGb5a1hjNEX40FJd9VpFCx9kOcfEMJu+JF1Do1Kmc3Dizvxl/vkPmeNjrzTVM0O6piGTh7Oic3L6Zu/bsEXfcJnWV5uMRkSJBo6WiicKmN8lEp8pgo6jS4N9mla6O/z1DOHvqatqIcDF4+eEQO4vTLT5Oa9QDuRhcUjW1Ux6n5+qw/d8TUoBUg26hlc3UMtig3JnkINvvCMQg512MmKtLJxOjXOzh232w8Arayad0vchJn0aExXBZYIa8PncLhlDfDv5rqrQa+GK2SAwzRw9FXffWvUMJ9T9To0aMv+ruQMApr/v+u8vLyJMD74/L19aWxUdwH+uo/pR5++GGuv/560tPTGTp0KF988YVUDIjeMVFPPfUUlZWVfPfdd/K5AGbCMl+A+SFDhpyfHBATA2KC4M+VGLuJ94koqH86SCsuLv6bbkBf9dX/tIR0YegNaURoHe6OopyVMNWvmYIuJ5b/2sPll+gYH1XLi/tmsOxeJQXHVmE0xziszM5Vfo+ad9eOIXX/98wa5pALioGdkE8+O3g7V4b5UHymUAK0wUOHS2B0tvAk7899WQKenyorOFU+hZRbXNlTEor3ZjeO5CziqhtuobGhgfKKItlDljF8JBt//ZmH75hEbZ2VQRnDePy51/hxyTe88+pztLe1kpyazmVXXI2LixuJA1OJjI4j53A2KYMysGFD5+xMU6Nj8CTYNAHUpBWAQoHB4IKLiyuZWSMkgyXyvkSFRURSWV6Oh5cnynN6zg0nI7g71bHfhPxqc0MYCsURmRlWVDgKm/34eYBTY9EQHRKHsb6a2Vff6HBwTR5IWmYWz73+nmTrBiSncGj/Xikn6OhoI7pff26bcwl7dnoRKSwhMbPua3cSL/uJoJCB7NmxBq9n7+Inw3B0Jiuqus1yuZ7evqx+yYzzu/24NeKUXH9sbYPcLsEetZ8L0Pbw8uGSy69hxU/v8MJL/gwb7sK33zUxfvoVGFzcyN5VzM/NAVziUSMZiEUNEeiKnSTwstutnMw5THLGMGmdPyA1QzJSXr7+1NdU4e0fJPvXxP4T2ySkpSdE3176UFRqDRHxiWidnKXTowBmQoooHoLNEoBMMFed7W2cPHJAhkjrXYU0sVb2jAkWTARVizgA8Tibn0NcYio+AUHyNcIFUsgjB42eJH/Xu7rTXFdDWGx/Obh39/aTDJqHrz9mi5niE3nSUTJ8wEDpKunq5SdBXu7uzUQkpOHhHyzBal3zFslN9qr5xI+GnjoOzH8Dm4sHj4ddg693Gy0dekwHPAhRqTH1dKH38GLcbU/QXFVGR3MDwf3T6D96Gv7RAxwAr8MsgbQADqIqzBq2fvIssSOnkXHNH6RxS+b1jxKYkEHpoW3UlOQQmDyEmJGXodW7yPBq8RqPiAFY7QrCVMd5ZsYnuGm6WLInnlX1D2NSqnD2cZFOkPeN+hx3jYMB9nA2cfvwreSMv56zm7+n3N0XrasXHUeFpX4AwWOuleBMhFTbLUbM7c3owxIxtTagMnhJq33nsIEodQYpgWw40MrKkDQOuDXTYXLibEkgQ0Y/Q/b+96nd/i2+WXMYnl5BgOHCJE+MUzf6Th2KSmeUNhUphrHsrTlB56kduPQfi6W7A5vVjsJmpTO/En1VNy4x8Wi67RjKeghxr2Tg2GI2WX0wx2bKHjZ3pzY6R17Jke3vo9TqJJAzF7Wy4t2hZL7tCUobb5wdQsNZb3yNdjqaxQSBY8JF/BQC39+pNulCjTnAjXBTDCdPHmP0nFiuCqq46F7a+97+/k1UIUxPbH2B1n31LxNm/b/J7RMkgjAa+2OJpMi6Cg4O/quX21f/GsYhf0mJuDABzIXzojgnhDuoyEALDw+X/xd/+31m2ueffy7HHYLJFY/eEtFOQtr450pMsgvW96+VNP5NQdqfupD+J014fdVX/9sSMxkFu4uxPuBoyP99P1p/vZE7pqkI1Bvl98GT4flUv5eObVYGDz9+nB/nB54f2FhRoTzZyeI1RTz35gAiXMznL4Yp7o18vm4A92Tm8d4bL3HLXQ9INu6hO6/lvU/sZPXTU2FOYta9p/ntkrP4+vpRV1sjwdyt9/6Bnq4uKaM7emg/rz51Cydy4vDRGGSY9kO/Grhm5kRuusuX8uM+qPDmlzo116R/xD0PP0laxlD0eoNkX1586iEO7PqV4eNcyN7bSXTsMKZcNpvZ19yIsbuHhKQUacHeYjbLWXAhxayuquTUiTx5PWq0arZt/I2BaRkEBAaz9FULVc8NYkhEGdvrQin4PNIBvpJS+XnFMXwnp3Fz/3xU2NlQHkH2+jXyM4lQXBdXNxR1IpNLL0OS4/onSilpcEgYehcXyTIKMFpXU024ywVZqU4BN84dxkdX7ufyq29m9fKvJHMlSmSeSdOQNSvY9OtKtkbGydeLumdECZ+PCpCgyU24FGq0pGYMo6Wpgc+/j+K28Y5B6tg3fLjx9T3UlGZRU1HKvJdv4p3pJjliNe10wVK5lrDofmi0OgaPHI+xp0dakbu5e2I0m6itLJeOjyIEOi97N9EDkiUoE59TADTRCyb3rY8fJrNJGnq4uHlKow4hcezp7CQ0up/sVxM2+AlC3mg2yd4xAagFQBM9amqNWkol21uaJbizKxQyMkD0p4nn/iHhkrkT/xfb6OEbIDOy3Dx9aKiuQKtzxslZR6jmN6KG2zlVF0tTbbVk1Noa6+U+i0kZgkrjRGtDrRxw717+I2vuCmeqW73su9zd6Y7OezrtTc9DUz3uK7U0RASj6gbfY230uHZLd0y9py/xQeEonfRonA3Ul5xCBE8IIClcBQ80ObMoNJDhhjo6bWpePzWM1BHp5O77gYHTb8ErPE4C2QGTriEsfaw8F20Kpfyb6EcLSBmDxdiDzl2Emvfw1Oh38dWa5Dlzy8jjHF6bQ2FnJGq9O3aLBRdXB+sjr3NxfcbmcfRzDfd99we2by7F2FJH5KBJuIYloNLq6GltkAPC5sJduEUmSwZNrLu9JBdDcLw0KhEsl91mxXimmobcJGp9vMCiwKlcidZuITh+OhXHl+PafzRa33rJyqrPrV/sy2diDvFQ+DGu3XgFba0dqAyeJAQ3EBZTxOH6VNrKTmHtasMQP44zSx8kqHgC0c7JDIgp54PFh6Wb7BsPunPPqqPcnbWVgf41dN6l4uq35pBboJayTBcvdzZ9tAOd0ibX+0X/rVy26CYMp1vJeL7qovtivUWBQWVHdLDt7PRk+9EBBDa0UWo6I8/l4HC1lDH3Vu/4V4C7Hzf50sABkpOTpZ10X/XVv4Lc8X9T11xzDU888YTsJ5L3H5tN5lUJe3TBdvTVPzgn7W8ld+SvW84999wjH3+q/hh4if7Hv7ZmzJjxd/Hr6DWf+ovq66+/lohUuEKJh/hdyCD7qq/+niVo6xN78vnoeIwcYPxxBegdZh5iICUkWU9HHsH9ufF4e2gumtGJ0BhxnSys9/XExBVQ1imGNxf+H+XcxoDRN0smLTA4jEfuvYVnnmxn8gAbbio7/Z16+P5jPRq1RkoM3/zgC954/3P8/QNx9/QkKCSUBfM/YP63qXirHeyWYOkenVSJ2WTiwyf0OCvsMovtcv86rlo4i93bttDR1kZbawsfvfs6tZXbqCyIZPUnvpQciaDf5SZ+W72Sqopy+RoBBEW/1KEDe6mqrJAMm5NWi5ubh2TXxLZkDBkus7Yee/419uxdx69PnGXxE4M4/oqFDUvfYs51t8jctfKyYuy5wtLciq/KxkPRhbz081DZCycywRoa6qSNvnAfFPvExc1NhlAHBIVIICXWXVFWgo9fAFVmkevkGAgKo4Wc6hAJSG6480FWbsrmroef4a6Hn+Wbn7eQODBdLlcAISeFwzik9/iNeWAUu7f8JnvdBJMorOe//2we40cI044Lx+rGe0LZvWmt7D07u+NLwr63EP2dDteCbI7n7mX6dbfLvjDBtgn5W311pTRSsRiNnMo5JKWEogdNyByFKYiLu4cEkqJ/TDBbQsIossjE3wQLJtgzU1cnx/ZslX1mvRsiXBn1Lq7ygwtTEmHDL8BZe3OjDMYWAE/IKwXzJtYjPk+MZNSCJRhsrKmUQdnimLY21VNVcpa25gZpoCF6z4b73cLUyK+YGPo1l8bcRVdHKw1V5VSXnEFrcPRd6N3cJfA+cyyblqpKXto5ibuLsrinaCgP7boUpwobehF0bXCl8ODXhGXXE7CrDJ1HJ/v3LiEucyxOehecPf0wdnXQ1dqMR0CYXL7B05f2uiqqFu3g/aNjuOfkJdyZcykF+6Px7Q7BajbSXFlEa3UpVrOJjuZ6CSKrTx5B4+KFXakhOG0s3a0N0mpfyENstlYMGofraW9Nit2PT9smzB2tqF292d7hT5OULF6YlXV3NjP3+h0EDp1B1GX34504Wi5ThmS7eEk2SgA0u1KLxtUbhVqLzWykp70Fnakc386dYDVjam/G/ONeXI+qcc1X4X7GjrauE7VVIc1F1N6RFLRFsbnLQK3V4brae59w0VoYEZFLo6+e5x+CnR8UsujGJfx6y6u4BEWhDYhD7eaL16g7qCrZzK7jc5lxf/ZFX7hPTvxRAjR57FRWPvhDHvW5O2mvPENMtAK9yiavBbE+f40Zp4QGqqqyKWkR7p0XliMyGzOX3MiIlVfxyNczcF9Sh1mbS0HBEWLj+7Py45M0WC6sWUi0TTaHQ6u7pw4VKo4fP05Tk0P63Vd99e9cwigkLCxMsmZCfiZyfIVzaVZWFs8+++w/e/P66v9oxZzz6xBB1iIoW7Tn/P7xD2PShP2+MHAQzjtC4ylq3759/OEPf6CkpEQ2bPZVX/09Spxzorn9kYnr+GZSAocXms6Hs+Z2GzB0dhLre+H1gWob/ZIrqFo0AJu9Tv5NvLzepqKtyYXkpHRyCw4yf0Ejb9zvdl4KmNvuTVbiMfJ3Kbn35jlcfa2Cayd6XrQtXioTgyZfQ+2JvQwbPVZKIgVYOXPqhAQRpwqOo3YZJkz3z69XTCdqtBrprHeeBRS5HSEKFh/aL00rBBBb+/OPbDqUgZPCIXMUEPIPM9oZ+Ie91NfVcPJ4rgRIiQPTSEodhEallqYVAnAI+WRDXS1qlcgMUxAcHCpt5N/5ZAHLl3zD+p2LZKaayFGbeeV1HNjt6Fu67DI9NnunHBSK7Z+Y2MFz+XnU1VVTXlpMRtYoXN08ZE/d3dfPpKutnojYgcyYcx3NzU2EhEVIieJdn9/IM7dsxkVlZklVP9qXWNEbXKR5hjBgmXXNrZitZinPFNsoWMPgsAiyO90Y4uLYV+VmJbmHYqit/kHun8P7duKk00kmrbArlginhvP9Z8JARHzu6dfeyuHd21ixfq5chugnu/PxV3DWG2RWmbTdb2qgq6ODqPhE2ttbSckaLY0/RH+ZOCC+gSFUlZ6lp6fnvDpAZJiJPDMB2hSKVNlXJvLLwvslSnt/AcIEmDubf0w6MUpwZzJKVk1an3t4UVdZRlFBjnSDVGsc2WUCmDl61GokqNPpDdJqX8gbO9tacPXwxNXLcTI7OauIc7vQLxThbmLZG7MYMuMlEoaMorujjabaSpk55+UfTERSGlpnPZ4/tXKwOBG7ClyL7bh2NsjXDpt9Kyf2bOK3PW85FpgPUWnDiR48GrPFgrWpjs7mesmc+UYnSTOR6pNHcXJxo6v4NM4bdNSEuaI0gvcp4azo2DaLyURD8Um8opMwePnR2VRL4MARmGXIswmbzlWirbrTh/FPHoHFpYt8oxMZOqM8luKYTo87wKWx8PSWQPYV92N1RTKddg2D9dVMdLkQ3GzQdmLubEXnEinNRAxBsRJI20zdWHs6Ubv6Sut9hUYHNita30jGJZzl7YkLUCvt5NUcZ3b9GM4seYHBtghcVS6oOox0NdVTrdiLU2C8NBipOKbni4ihxLjW85B/LsEiPPFc5XUXkl+4nofvumAJHe3VynNjv+PJ5Zeg1Dihj8xAF5yAsbqALveDKBSOkG/xec2/t9gUzLPWSviQGZTtX8Omjz+n6w+xcnJHVL1VQXe4Fp/EESx+WcfI0aVSetloVfJu6SCUdU54rmpm9+m3MdIjz83xk6dz7NB2ygr7nZ8sEte2p9rxU9xXXh2Xw4Goq9hRtJhPP/20bxDbV/8Scsf/TQnp2eLFi6XETUgcBZOWmppKbGzsP24j+upfQu74j6y/l1+H+q9p6Pzyyy+5+uqrz/9t+vTpUi4hBtF9IK2v/l4ljDCE7jdz6FDyNuSTcM0gnpzrRUOHjqcu2YK3q5HK3KgL2UR2qGz2oqHYiRtfbOfZp3xptal5Iz8LvzVK9p/JZdS4ybz9xiqU4UMYNqKeHoua233LUDwIz94XwyXPe3HffWJw2HPR982W1iCaCwtkVlHO4YMMHDTYsY0aJ7TCHCAgiO8/9CXrwxr8NFa5LSvLYzCbClhXG8jUgGr5+tMmNQdW+0kwoXPS4S3NKqy0W3u7fhwDuh4x0gZef/4JTuQdpl8/DWXlMG7yFbz89ke0NDXS1dkpAZHWScvG31aTkp4p5YlC7iVuEgKoCdaq+OwZYvr1l4HWQp4nKq/Rl0SXzvOhuic7PeTfqyvKSUpJl46SH859mb3b5nNgaxTuagW15nzSR13PVdc8xZ4dG7nqaldCVd/y7C1TMHqGEWhvZ9uGD7jqprtkSLQASxaLWQZrt7e1cGjfTgJDwqgsL+UPr1/PpXcdxd2ph6WH0uj5bR+hEdGyv0tY+tfXOPbXiwsnYrttA+FO7Rzs8GXld5nAr2iddDz21ifUVVWSd2gvIyZeJhkyEUsgAKHoPxMmIAEhEbJ/TPRxOcxCHLlkLu6eNNXVSAmpcF4ULJnY5sTBWTjpDdKOXxwIAdDEMQ8Oj5KgT8gcxWcS2WiC9XKYhdilzFEsV5RgzgRAEwBMsEt5+3fIfDMBHGvLS+UxiUlMk9vXVFslQVFAeIy05RfHbs0383nlKod8VJQQrvmNuZwlbz/H09/8ipu3n2TrhHxQ7FcxQE8ZM5WD2z5jvPU+FC0atDo7e6t/luAtY9pVpF9yBdXFhXR3duIqWNHoBCn1bG9vk5JHcQ46uXrj5OKO2dhNR1Mdfv1ScPUNonLXMgZ4TgGLDW2PiRNOJ9Ea3AhPHy1NSyw2OxZTj+w9U+v0VOUfks6HzuLC0WjxiU+Xuv/y/Dw+6z+IYu9TDHZuIVpzwTH1iqRfWPLVIZw0A/mxO536kJMk644RIACGcOhq8qDpVDZ+gilTKLCrnbGL66bwIK4RSRhbG7BZzLTl78QlZghqnY6nxn6H6pzuKimgkskjzCzYlcih/Pn4xE3ESWug3n4AY1MFgbNek5LIjhPF5IeFUBgYQKi2mZkeZbIPNr9HzxH/cWCZh1Ew5fYLA4nrMk7y+RtbOdaQgsfwm/Hzc2LVc3sIdeukyyauZcF+qZhXMZC3Iw7hfi7Jvs6sw54ZQtbpWdTFF1PVVUiEwUS7TcHcqoG0NRhwdlXg3u7HqFG59HvpCsxqPT2nXfDN6cFsrcSqsdF/QDqXzbmO6tKzRCW7nQdof2rAI1btkWmAIigqcpgx9VVf/V+o6Oho+eirvvpH1N/Lr+MvBmniy1s4pfxxCatL8cXbV33196qquiY2rF/Pw48+zfbtW1i+dBG3ZpjlgCM82ZWWBg9m3V3Dhx+EYVXY+aQ0ifYFzrS7VrB8YROrFrUzbtS1aJRmjhz4RA7uBg0ZRmBwKG/e+SHOOgNFJ4UzpKM8VHYefVRNRZueONcLIG1bhxufPZdIYeFH3HTn/fQbkCjlhzKjTKmWM3nTLp/Dlx/PI+fIaD5cZWRKYC1PR59g0pkUJiSe5rLPpuMT3M7hTbHkLnxPuj0K58igUMf6F72XTsJr6wnRmqi3Kpm7O0vwRrS3nKS2OBZ3lU3KCW/88CjPPnIvf3jyBY7nHsHb1xdXdw9S04dIRkdkkQnQIMDb/Pfnymt07MQpsjerXdUq2TixH757LhbtuyYS3RrJ7fJgwfxM1OrdhEdEEx4RRc7RQ3z/9SccOJ6Cm8rBePmprSz4NYGpyc+zblci4yIdrkaNd+whJG4h5h6FHCxec/Pd+Pj60dbWQt6xgyQMHCRfF9s/kcFZo1iy4FOqty3meM21ggPA3VLIvpytPP7Ke3R2tEmmTRiUCCbOvnsfL9RMozNUjUuxBWXZbvnZ0oePkf8XrNSQMZdIVtJkNuLt5093Vxc1laV4+ji2Lyd7j2TahLRQ1Imj2TLjLCA0QsodhTwSlYr66grZe+YhwIZaTfHJ4/T0dNFv4GDJhgmgJ9gb73MmIALoCdOPklP5DnYO2L/pF9LHTJZumG1Nwv7dyuCxl8g+OAHarGYzJpOJttZmyTYWHjtI3KAh0o2y9FS+XO/ZvDw+rbuE63zOSAC9qjkUU12szHjbtWoJk264h+DYRNqbGnD28KKm+BQxwhmyrorfNs+V4FFsp7OrO1e/OB83H3/yd28kqH+63AfmtnJoP4UiIAO16Ntra0btpEOjdsLU1S6BV0TGBDqaahlz94usffN+9jaU4hebTH1dPj1tLWTd8hTm7k607r5Yuzooyd6KV0wKRlM9Bp9AGeyscfWip7URrZuP7B0r/3k5ltRbKfAP5LX4TcRoHeeVqKaeVnoaQb1GiXnCYPbbY1jo3E4/XSP1ZmcW5mZRue1t2kvyCJv2ADofH+xWM25RqVhtdmJCerhl4Aq6ejTMPxCHk7IFreqCC6IoW1cpPpMeofXYrzSd2CpZOMF6+Q+7Ho1XKAq1BpWLH00fLCHoyptY6pTB6RA/nFQWjjUFY1EEMDj8Jla1FnG9Z7UEPL11+Z3x7L15L6amcr5cE0WIq4MFFMzYgU4v5pZlUFzsj0vUIfl3cQ9L1nUR7taA2ded1+4pItrg6NXzUNoZZahhyxkNmuYuukyCvW2m4OFv6GlvJSp2MB2eLhRU7pQTExNmXImzs0FKvcpqjdjtf96y3GiD8q2l5y3K+6qv/t2ZNCH5Fllo27Ztk5lYgkn7ff3000//uI35Dy/lX9tT9WeW9Z9YfzFIu+666ySbNm/evIv+Lqwtr7322r/ltvVVX50vcaPdsGG9HIAJS23haHi6sBBjx0H2rI9Ar7JTZ1HwYN5I3nlnJz4D1Sx6ZzP1p36QIOSltz/h6MF97Nq2WgKUMROmcPXNdxIaHiFZGJFJ9uITD9BhVeP7u4SiVouW+ycX8sv+EMJ0nZwwuvDs0kkcW/06gUEhzLnuZmmbL7LAGuvqZI+akJ0NHz2Bn5YtorxqC5MDLsgsBhk6Gf9WIktvXyDBYVnJEhKSU3jihTfI3rsLX/8Aho8ez4Zfv6at4TYaUtxxb7CTs/pj+f4PfkjFTelgaERP20t3K0iJW8Ft9z7ExCmXSebI2GPk+68/5YfvFxASYqKhwUp3t50l65IJ9oO3P97I4m8GSGOQ8ZMvlTb727d+jfuzd7FY7YfSVM3eje9Ji30vH1/q62rZuuEX2X+m0gib9wtW9xqNTU7cjIwQ0QWOElEG938xiiOLXLnjoSfJObT/fOh2bXUl29d+xMDkJs4UBzJu2hO8+O7nfDL3RX5Y95J8jQC8tz7wJMmDs6SrowCbp07kcv29j/Hxa0/hevoYAUGhlNRVy363+559UzKR7a2tEigL4KE3uHJgx0YSBg2RX9rC3TFpcBZawVIFh6MzGCS7JkBsVP9kObhtrKuWrJtgu8QnVCtV1JSX4OkXgIeXPxHyPLSeD50uO7SX4Mg4CdBKC/PxDQwlIDyKSKUSd29fae4hZJEi80z0w504vJ+YpDTJdIn3C6MQAexEr59wnWxrbiRx6ChpIqJzcZUmNMIQRdSqXzJYlZyIQmWn/qQ30eUOx0Nh5y8iFxSqTvk52xrr8PQPRufmRfzQ8TSd3c7BrTsJHDCC/lnjJcPV3txE3NCJ9HS0khm9mxkhX0nZ8NH6BBY2PUxZ7kECEwaD0URj6WmcPbxRaIWJigp3FxvHjw4m0FDPL1ureWnBYOLGXoF7QBg1J4/i3W+QNBzxjU2W7pQ6D1+Zg+bk5kVXUy02iwlrs2AbrZjamjDsUtAa682vflGEanPwV9lptil5OzuW5tPraTDtYaQ6nnqrO8vVabjpjLR0OmM6405i+m0cP/g5dosZm7lHgiyViw/Krkq+u/w1nFUOBml0bCHezo4gdQEWhdSv1Kzk2w/Wo/brxCNtBjr/GDRBCfL1xsp8rF3NYPBF4xZAQ305Xr8dxqk2gU1jE1CobVibnTDUK3Fz8eeTvd70H7eRTJ1jIkeYBB3ySyXcQ0dp0x58PNwuumZ0SjNnjoSir1PAVMf29DJbkQnVFH4fSVD8xddZsL4NTbMJdVEVBzo3YbR1Mu2ep+np7CBvxzqM9c2kDBvD5EtnS0ZWVHRMLCtfrufH5xKYElhFt01Bo0WNr9osJdf1Zg033+nHkdoNMvj19+qYvuor6SL8N9oN/0il2oMPPijHo2LSQYQW9xnb/fNK7Pu/1f5X/IvrHUW22n9XCxYs+Me5OwrjkI0bN8ocAVH79++XKeDCOef3ziZ/DOT6qq/+WoD23eJlEqBZ7SJNyc6urUv59KsW+nuGozsnYfJT2/kgaRd+qeK5mVsm+3DD4hs49OpX7N62iYefeZn7Hn1WygENBldahduelw/rVi9nUGYWoeFRvPxBLHMfK8BNaSXf6MyX67OobdzKNeMD8E+ahbm+jrzc96Xj4UdfO7JYRJ+Y6F8R9vwpgzLxCwhEqSwiMDiEqKhobNSed7cSP5x8giUQSRs8hFHjJnHL3Q9Im3jRdyWcDOfN/4Z7br6SDRvegQ2O94WEOSxjTYoL80niliVszIUZSVlxMXHxCXKg/sbzj7Hxt585fiKBGEO3HJjWmNUEabrk+hc968z4h09wYPsuVi5+k9TBM5gyfRar13wm87uE7f+MOdfKEG4BkIJDw/E81x/15e5k5k3YKwFiiw3mZ6cCB+mwKXE/50Qn7d6V4eQd2yjldLHxiXK7Nq79mYN73mDL4gA5SLTaq7n22VsZMOAlPlv6Gxt+WSk/1MD0oRJ0HTmwR4ItAbxCI2NJTMskadAQli/8lNKzp0hOH8qkmVcTHBkrb+CHdm8la9wlcpuF42Ji+lAJflqbmxk67hIpc0Rkb/n609XdKcGlYLSCwqNkP52Pf5AEZYV5RxiQniWt7uOSHaxfW3OT/AxefoHUV1XI3rP4lAwsVosEbeFxCdKFUQA2YQIiJJAil01sh5unt5QuCoAm7PRbGurp7uyi5OQB4gcNkXLI2vIS3Lx8ZSC1dG60WCQ4dNaZKT0ZS4j7EtpMKm5+fwaa/R1Y3eskGB2QNRZPv0Damuo5fXQ/sYOy0Ohd6enu4PrEBwkbXIt5joJFJ6dyur6T9uJN3DtjH85aK2tPzeKS4K/Pz1Cm+uazonMrYcnjZD6YsII3dnZgV2mk26SQLz4w5RtiPRslqLjmEugMSONgWwZdLQ0EJGdJiaFgBAVIFEYenXVlKLXOdDU30FFXgUqjwS0imZ62RlxDYinf9iMDKi5nR2R/uuxO+Gg6OdXmR1VVJGrdLgnqsnM/I6RwABanKbS72FF2KvAosuPc7Pj6ai8voLuhHOeQRCytDYxOzkb/O4mfAGi9JcDob+0eLKlNJHRUECeXvIWlrQ6fCQ/KE1c4bzoF9cdmV6KwmDF3NqGPyaIobylOJQHEdt2CLcIL525wLbOgbOui4p3TvBo6gtuiDspe1R1tIRytDicsLYye7RV8d0hPwgSjZNEEfDLa1LiWwLUhh2WcQW/fmdinHw44QNXiY5TXK8+TD2LKYENLKN2BGrycDWjtWkwqI+Gpw7HUnGHcJZ9QX1WOp85JsrvOGjValQKDfyApgwZzTfp2HlsyjddGn8JPbZIMfMoVKk7vzZcNiSKQVYSwCta2r/rq370WLVok2bIpU6b8szelr/6DqrnZ0W/cW8IcSxgytbS0MHbs2L96uX/xXVmstNeq9+zZs+dDAsVD/O/fBfX21b9Pfb/4B9nnIkGazY7RZOTVZ0uI8fqvr/VTX5A2hKhtDB9bhN/um1i96QtGT5jM0BFjsVptHM7eK0OihclGWkYWSoVSsmLvvPos7bVPURpmwKnKgv30VtkL19RRxZlfX5fLTUpJ4/Hn38AvIIiD+3cxbtI0aVWfkTWCX39eLmWOrS11iNgywdJ9emoid/Y7IQfDG9u82f1mjsxBe+vDL6iurJCuf/4BgRLeCDBUX1vDe599S01lJfnHj9Hc1Ehiciq3XzuTbz/JIuOlnwlSW2ixKXjvsAg4zsPLx0cal1RXVMgA2+c/mk2M4YjcXrHeQI3F0cR77vnqd5xxV4XIHrS5206yc2k4qzcfYNum3xg7eZoMoBbMoHA2FOCkurIMJycFr4/ffz7MuLzHmVU3fC+B5RMHhvNCxh50ChvrmoMo/GoXXyw0UFk8m5XL47nv8df4ZO5LbMlJRoUj+0ws5pln/BmT8SxDRo5lYPoQ6ZAoZItNjfWkZAyT0k0R0iwCxXuM3ZzKO8g1s48xIM7K5p3lnDq6lgCnQ3RbvHHS3SCZsdyDe0lIGyIte88U5ElDEDHiNXZ3y1y08Jh43LWelBYWEBge5ehpstlkv5mw5B+QNkTmt1WXl1BdVkxEvwTpCFly8rg0ERF1aMcGUkdOkH1col9NyCvlZ1IgjUQEIycAmsgyKz99gv7pQ3FT+0qwJt4jetnE3zx8/CWjVlZYIGWOpoZaujrbKT+WzYCho4n1eZVgh6cNLhorT1y9ilkrbVTtK2T4jGskQBPmJaKiUjJRaHW01tcQ4vwuYc6OYGy1ws7E8HnsOvg4b1/7I15qh+zvjoGOfqrf14Gf5qGOUxM5aBh2uwL3gBA6WppRqbX0mFvwdXMcO1GCAdIb11J9Ig43/xCc9F4yB62t4gxaryD5mvqz+XjGDMTZ01/uHJWzO12N1RLwhY+azZHPn+BYWyMh0Texw9gfldaKpUmLV4WS6JipFBz5VuYFnqndxqDV8SjjI1EZbRiK2mnXO9hZYdfv0S8Tc3cXahcvjN5dtNvA5VzTugA5Fzo8YV11PNmnY3HXqAkNnURXw3pm90+lut2DnacjUOh9oKNR0JTSgMQl5XI0fnG07l/E8RWvMzDmapLjfVC1dHHMbKSxLJv9T7RQ9dxEdDozLa0G7BU67Doz0bpUfnxxJ5mDkrnWp1J+4Y5yaebd239mtP9/DY8W11a4m5Hwc8dcGBl93xDC4twMnNoVKFSif3EER/LWoLGZMPgFU1VUiI+XD3R3YO3u4ucVKzlz0iGVFd/Lop4ZVXgejOuUsGaxmv6RyB7yZ5555n9wF+6r/7j6N5U7iqieqKiof9wK++r/HBv719TPP//8JwkGYf//vzkf/2KQJnS+fdVX/6jKKyiUg3QBzixWB4vW2tpGiOd/dftptIBBqZB27qLErHVtjwt6tZdkiEQmmGC5hByxuamB+AGJ0kpeMGFCZjj50llk79vFLyvfvpDn5e3LvM++I3XwEIrOnJKsjMFgYPCQYfT0dDNy7ETpFCjAzIZfV/Hmi0+yZu8wpkS4yzDh+Uc8eWHqPn68/n5sgTZcsssoy1vAQ/cspLmxQW6PWFdleRkqtYrWlkbJwhw5uE8uO65/ggQeApjGxMWTs/UH7ui+ifaMLpRlWo5/9zFZI8bIzDLhMLlv13bJJNUrft8hA+bfBRCL7XI/51InduEdozp49rpV3P/os0ybdaXM+BJSO+ECKXKWNq//lV9W/sBtz03GTXXm/DL767uxKrqxm6Ho3Q4uG3g9Zi8Fhh3b2P6jSrrHkaIlc1gVs6ZcKber0XohVVysu8WqpbmxntKzZwiJjJasoNxeswm/gGDqaqoke+rrH8QXzz7ETbcf4vIkx7FJvbqZbttuaaihUFSSXfEWr83L4srbHpL5akKe15F/DG/fALI3vc9ds9bjpbey4ZAbJ+ufkMYfoi9MOD6WnjkhbfqF9FGA0u6Oduxt27n3ksUYNFbW7I/C3u9JCa4E89VQV01zfZ0EZ1LKmHuI2OR0fAKDpdugcG4U9v2uHt64evhIICaYO9FzJoCeyEITAK6jtVmag/QfPEza4wvTEtFDGJuWSdHxo8SNv8ACiTJ4a6kqy2Xi9Xcz9qrbOHVwN+H9U/AIDJGZaYLNa2+sQxHiyE/rLZUWfvnsEb64wef8dSPYzH2dejL1XajtcMKkpVs7hS+v+5r+Yd9S1u7LuweeR6X1oL6oQILZw93uBLk2yf4rYYCx6kwIG9+8mzEPzsVDkr12GUKt1xnQ6PT4xQ/CrtJi6hDgzs4dKV8xNnQvNS3OvLT3Mcw3PEf+srcpWvQJ8cqnsbiAvgVcz7TT1tUqkWDSvZ9SsOBxck4uI63lcpzNOro9nClo3Cwt9l0jB3JV6k7uG7was1XFKyezWNXmTYa+CZNdSZlJxzB9pwQnp00aNh7oj1OjFuc6M7HuIfy4OQJPw3q5T+ZtGcq8TaOxdreisllR6L1RKHvQBvTHb848mrZ+wr0PbuPW2Y7Yg69WdnPXIybayqqonnsQz4kTUZrBUGXHqa6b6fdXc++Dwtyk8qIA6gSfpv/Wraz3tQJYDXFtQHnMGfeT3XSVn6XS+yTewRG015RK1kxMRti62uW59MEbz8nrzMPDmfY2M40NjvPgAi/nWLYA7qJEhE5f9dX/pXrxxRd56aWXpLzM2fnP92P2VV/9vUuYggnn+9GjR/P444//Vcvo0zf01d+1ampqeOihhzh9+rRkYIVeXOTq/U9KDJYPHz4k2Z7eXrStG9ezdvVKkqMDmDHC6aKBj6sKFtaEMdO3ArXCxuqWYLLXDUBx9hfCo2Lw8PKS/T+CIRIBz4KOrqmqxGJ1/BS5Vk+++JYECsdzjuDp5c3gIcPZsXW9lEYOGjyUxoY6CewqK8qkQYgAWaL279rOgs8+YPYVk5ga6XBJEzjojrRmntJ1sO9zRxK9kPG9+Ob7DBk+ir27tpM5bIT8e+6xwxI0hkdGY7XWMGzUOGk+IXrMxLaKrLDrb72bb774mPXLnoNljn0kHBxfnfcpWicnThzPZd7rLxAWpeXhScfkLHzvYPrT8lgSPZrx1XZzut2NK/0cfW2iTHaF3Nc5Rw5y+VXXS4OP3KOHiY6Ll+YDAqi1NDdS152A1X7m/Ix8q02BwdmN+MRktu39AX3OWgmAX1w6Qcohe2uAew/lJQ7W/e1lo4i6dRVhWiPVFg2vrh8t5ZKCqRKA2Gg0UnK2kICQMGmPX19bLUFaVXkJv634no/fHSCX03vMhdNeb6UG2/h16ULGTpstnwvgHBIZS9mxq3j5JoXcF+J9s4a0cfUT99Ev8z0pO1WqNYRGxUlQJySRFrORRR++wfL5x/FSOySc1444y9jrr2PsNR8REBZBbEKKlEiKMGrh4hg7MEPmxwlL/dO5R6RU0T8kAr2Lm2TURByCYBz7pWXKLDIRUn065xDh8Yno3T0luGqqqcTJ4IKbr78EcDt/XkJdbCJp7rvxVjlyrRZWDMDLr4HasiIJEAV75uzmJWWWlafz8Q2L5uShPRzRxjMuqI4wtV1K6hbXRqGOUFFhsRChcbDNbVZ4Ln80I0OLUClsbCpJ4OUn9tA/TIQfQ5hrPTMHfM+io7fRVltO0eGdNCZl0hx+hGAhnbXoGB/hzF4fLcUHt5Eel47Z1INnXDqmjlYpfRSuk1almu7meoYGrWJq5EG57gjvdh7Nms8T1rmodC4c++IJ2JePnyqQcN8Wxs44y76Ss9R09Uft7ErsVc9x6tunyT77tQRm5vJmVDoD/lmz8Xaq5eHMn+Q2a5VWXhywkxknJ7LVpZ0Os5O8d5zwLpb3hJ31sejK1biXWHA+28zk+4rxNFw4iW4afoj398zEVH8WVE7Q2YTd3IO5/gyagASCxlzFLbPmn3/9rZc78/yyobS3dFF3dCvJhgJuubofuXV+7Dph4s7VF8BY7zkrflaYtHires5HiPQGTPfW7yM62mxqFGo7liNH2de5CnuXnak33oNaqUCrVOCm1aBSKFix+Gu+/DmKywda5HUhFrm22pcZg/by1YlIHhhQfH6S5qF3gqXUsS/ct6/+XP27hllfccUVLF26FD8/PyIiIuT39O/ryBGHwqSv/v4lgqz/ZmHWin91Lu1Pl1Ac/m9MFftAWl/93We0fn9zFFkSIsLhtttu+/++X/ShCZmjyWqTLNqq5Uu47uZTfDwvUrobiuptrpcDNDH4c23hkodn0XY6nwjfKFw7t7Mnbz/Pvf6elA2+8dxj5B/bhpdHF/knrIwYO5ExE6dwxTU3S3ZN5H2J3C1hCz8gKUUyOsKkRMjXRIh07+yI3lnP+rU/ExIWyYDEZOITkiQb5j5nJtLP+lyJbQtNiyXA5k90bDy+fv6MmeBw++ufmCzDpzVaLYMyhkimRTxECYBYeCJfrj97705WLV8qAaIwFbnu1rulvNLT01uu1+DiIrO9PvtgrvyMB/MHEKJ1GCXI/VgcyRPDNxLqHo/NrsYzMpCoFR2k6tulJfh7p1KAU3R1dVAnrO4FMyUGgFotHl7e0n1Q9OB1H27n7ZIBXBdyCqNdyRs5Q+joWMDYS6Yz+7pbObB7Oz8v+5b8xlgs9hIJ5sQm1FhEZptShn877y/khparsQ+wwFkVqu2b8PUPxGQxS7mmqNMn8nA2GM6FPrui0qjZv22jBDnHuzwI9xDW9I5jL/rtejnDJqsSb78ANvy0hNSho3B2ceWHz+8lZ633f5FKjLqmHx89+R4RcV9itpjxCwqlsbYaN08vTh7NZte6n3FRRUs3xd5KucSHFV/MY8xlV5I0dBQuHp5S6igy6ty9PRzMmac3UQmpEvQ66Zxlr5AwBBGGIsIMRJh2dHe2o3HSEZeWKRk10UdUWXyaxtoqopLSaG2oo6O1hZqyImxrBnG7dixJnlWcavWjYH0cvoGlNNVUyZBm6JImHGKHuPsEoNLqOZW9E3NHIg97jybZo5KKbk/27krAdLKQN8ozuSYgHy02vq9KonlDAEsHBMqd6XxWhfcD7RftJ6XlCAWbV9Bv/BUc+nkBql1DmNc2jrWZPxFqaIdh9UzdEEj6zNOYujswd3eg0jt0UjXH98n8suSoNm4ZtQQfV0dwc2/5uDTQWVOKR2QC4Rkj0JiWYvSKZf7XPWiUcK1CwZBJsXx4sF0Gaifc/QmtZ4/RXpaPs18EhrBEtF4hDBy48iIgpFXZKDoeTJGHFbtZidJipyTIIftrr3HFs0OBZl8hJU2H6AnVXQSQ2rDTuP4tDElTUIisQZ2bNHlxChuM3WLE2UWIL0F57j3id7WmgK7j+UycEsxvX4mZ+zKuvLSMRwM6sWG4yBik92eyc89FbmWCP97U5kmavhUnpU1OTOmVUG1RM/d0JtpGO2ZLD3ZspAwdQ1Rcf3QqFU4qlQRoSoWNK+8ycV3a777S7TAtsB73YB8eHr+RT9JjufyhBL56eBvNdae55pprzssh+6qv/q/UTTfdJHOqhMldn3FIX/2j6vd+HKJkm0h1NWvXruXGG2/8q5fbB9L66u9Shw4dkgAtMjWSPWu0eKls1FnUTLtVy1133SWz9cRM15+rFT//gsVqw2S2YTRbOJ57mK8/LCLcUyPlYb0ljSp+Z8pxptsdrVFF0bFVEiqJvrMX3viAOdffwlsvPUlg4C5++cJXzmDXmFVkTjxM64/NZI0YK0GAkAp1tLfLHi+xHk9vbxrqavDy9pGySOHAGNNvAO+98QI7tmzA1UWB1W5g1lXXS2BVV9DJgQ43Ml3EcA/Wt/pStD2bBvcqdm7dJPu6Fn7xMXc9+Bg33Hr3+Z40IVUUzN76X34mPTOL2poqWltb2Lh2Nd9++TGPzxvCNZcqKak/wE3Tvmfe/KUEhYQ6ZJFjJlJVXkZFWSmZQ0bhrim/aF8GunbI4WRtzxkp+2w4cYrnHnmE5mEKVI1qKhZ/LU1HskaNw9mgl4BMbLxgakR/nHBEnH7FNSxftABT902sislAZ7ZTf2i5ZL8mTpkp89ji+iexZsViTBtdeSs9gTmBp2m3qnlx6xjsthMMHTWBrVtW4HN8N75+gVSWl0hg+MybnxDTL0H2gQlJ3cDBw6Tk08fTG6PRhN7VVT4XzNgLP02k5/JNROna2dkShAI7M7xLJWh8PX8oepedMry7f2oGX7/9Ipm3p6JUlF20PwSDtPZoMiePfcLhPVtlqLVwYBTHu766khM5hyRAPNztwjCD2HfQaFVwqno8+QfncctTr0vmS9jzF+YclBlootdMmJCI5QRFxtLV0SbBn87gSkBEjLTfP7x9A/6hEbj7BuAsDE0a6qRJiNjPPkGhBMf2l8xTa30V1cWn8QkOp+rXZdhtt3MyOBpNs4Kg3c0crCohbvAwaRZSnHeYiMR03HwDsYtQZ08fKZs8s2Ylp7weIM8/GlW7Et893RTVVLBz1+1kR0dhtSkwnzTgs7kI9wJ/7HondCUNbLspgDinYvQKBwO7sj6F7B8+Qe8diM7Vg85VmxigyyBs5IVIihBvK8s/tFGiWkf2ERNPTj6ISgnz/a/geJ2O18Y8g/bcVHpvDp94Jhi+eaOfYkvFWO5e0YSLJhSTtQft75S6k9OKeXtjLaa2enQhSRgiBqIP7k9HeQFoXbD0dFGl0lBihgiN416Q3aVHteIEThlJKKygabHRHu0hQ72dmxQ415ho6SrnjC2XrWXTGZfUQbTGLJnKz2vjof04jWuex2XQVWh8IlH7RGMzdmGuPUl9VwC7ulwYonecF3u7XHC5bBYpVRXce/8Wxz1J4fict9/pxbIKD64JrZVy0t/X73OsxTYXmTQ8svNSNCUazP42bCYwuBuxWNRo8p3wPlBHQ2ALnIGUoSMleyZBmkZMfihZt+Yn7npSAELjfwGEiZMTyPnhMM1Fjcy78RcZuCruzc8/72D3+6qv/i/1pIlB8YYNGxg+fPg/bqV99Wfr35P/+stLBKf/vsRkvpgEe/fdd/+/zo//XfWBtL76u5SQNYrL8+AaDZ7nzDyE2cXCz5wYFG2VTZZ33nnnn3zvN98vkcyZ2WYjL/cYyxZ9Q2ZqD+GewRfJhkSJHx02aLZq2NfhzVe/jSJeVcthlYpHnnmVKZfNljMapcVn+fmH7yk8HozynMV+gMbKy0uSuCVtizTGqKupIWvkWAKDg1GplRKAVFWUy94x0SckXA9j4wdw5/WzUNibqSrtJ4Oq260KLrlzhbTiX7/5W4wP3Yt+jlUOhMs/Pymp7uGT+vHtXC/cVHaqTGpSM5/CTzgEJiSRd+yIlD2qlCopMRQgScgiBYD77qtPePjd63j9qgPysyYaYO3eOO699hU+/GqxtMefmJVMe1sjzjoFRTYDy8vH8mDkCXlzFHbg360PJHFgKp8s/EGGXP/w3ddsWv0qyl+UsrFVxA+8/M7H8mdLc5NkBJ2cnCSjKAKSjx3O5rZ7H6alqYnfVn0BOxz7PiAohAeffFn+Hh3XX0pCM4eNZuv2z1ArHuRn38G4ttuoProMH78ArrzpTm648yHW/PgdJUWnGTZ2Etfeer8MrBYMWG1VhWSYPDy9sdgs0l5fgDa93pGD9uW8V/DfXcabRVPp8VGhP9yEzV/P50NGouhQknAIyou+5rLr7pASlxM5B+lImU2VpYKgc+fgWaOKR/LGUvFdpVy2t+sJZsZ9gavGxm8HncmpeYb2libJnD6wYxq3pu/DQ2NkUWEKqlyHwYhgVgSIE7LYpKGjJSuq0xtkH5uQHYrPI+rEoX0SlAkQLiSNQuro7uMv+84qzhZSXXKGmJQMtAYXuttaJOgbFvIWqWFHMaUq+TZuDvfO2YKLcED0HoNGp+WUbR9tTXWkjZ0q7fcjB2aCUi0llyLPzEObzcuP2vnpm1aKjpaiaPeELhMmVQ0metAtO4o6NU3EwDGos5JjHevJ215GYsZ0jtccpCX/JjoGqIl0buFQawjb9yfjG5nL8XWLiZ8wh91fvESKLvi8MUfv9Th8oJ3h/MJVCRcAyLMjv+CV3Ctx6qWdzn1hr+9wIdGpmzCdmbB4FanxOy4YZygdAKf3tdVGO8aWOnRB/VE5GVBpdZjbmzCExKN0dsNus3C8yJvvIvqR5FxNt03DktJ0yg8vI7HKiqtPJKqWTpwLNNhDPFF323A600C5u1qQkBQcT+a9gX5EGepQ2jTsKY0hdVg6J47vpOXoCjwnP4XCySCBv8YnSrqDPnd0AuNiTuCj6sHVpmKUVyWn/APx8HBDoWiT9yYBROssWuaunkr+1KPMjbrwBS4/3+/Cr0VZ7EqUtVoCf6zm8JlFmJQmFDbBsBkxKN0o0vbQ0dPO0JHjiA0Lc4AzlUNKJNa1e8cW0melMT3mYrayxapgz8K9DM/KZNeuXX/Nrbyv/pPrHwiu/lYVGhqKm9s5552++qeWNCv7G6E0xb842vt7+XX0gbS++rtUTk4O3u7R5w0qei8yH43DT66z82JDhN769vul5wFaeVk5KJewOTuMdpvQlV9wlustMfv9YXV/Vs1LpfSXr7GpPyC3pZE7HniMqTOvkLllG9eukoPu9rY2zPaQi95vVipkhtfRQweYMee6cwHQjsyvjrZWVEqlZIkioqKprCznlisvRaVoZMe+AfiqHWyCQWln/keBjEw9LUHexrXvo1qvktJFwUIZDC689HIXrucGq8JpccGGNN595DtefedjBg8dJqMAhNyyX/8Eaqur6ehol9sktjt1RM15Z0ZR0YZOjh0+xZoVy3jnted4ceFUnpxUKJ3hctp0zBnXSt6Ho0gNqWRbdj9+efJDHnnmFQkyZ199I5OmzeDYoWzOnjlFYlIqkTH9OHJwr8xtE1V0+hSurm4kpqZjrK6UfVtC6vnC3A+58obbqaook6YiglEU2yhMTdrb22QP3fgpM2Vf2srVL8uZJAEC/QODef7t+aRmDKO2uoIHnnlN7hsBRmsqHayf6D8Tss+De3dIV0dRhQW5Um4pysPDm/GXXsH6nxfgGxAsP0tB8Rlp0jG6dDZtnfX8cmK/7BUTLJfobRPgiV0VXDd4CtfFHaPNquWb7Vnov6mlsHgj3v6B3H3FbjmJIPbvZZndfP/g/QQnPCmZsMCfrXyWPxG7RoF3dhtVlWsI75cg3Rlz9m4jMWOEDIpuqquRLJpvcJiUNArHxs72ViIHDETr7CwZ4Y6WJsmyCWdRwZwJV0kv/yCc3dypqyilpCCHiIgiBg10DOaF5O2qjB9YMHYKBQd2UXTa0Ufh5u3HlFsfxjc8Fo3BDaOpAWdXDyxN9fRUb+PesT9I+eekuf58tmw5T7xiQ+fiRkPZWVy8fMnLW04ybSz5spr4kA7sdg0Pv+rP18v2YerupGtND4uNw1DrzBjrnPE7bsXqH0NNxXFCBg4jdtRlHD7RyLKWQCa4VuOuFGHLFyZOBEDr/TLVKOzUmctpsILPOXaszKzi9dPjWDtw9UVfur+XHFZYFKgUdhnr8ObZdE4vfZngCbfjnTIBu8Uk4wBEyLSlqwWUKpp2N/BTWAq73aJpNzrRWOxFetod7N73BoaaIFRKLW2nSwjJG0CA9yAq3bWUV+1H4x1BV24lh/tF88DkAoZ61GMLymVuWRa2/AEcsG2Q9vwqj1Cw21AavGV/2vGPanG5sx+/jFkt9/WNE85SOMCFuGCxPx2fockKH5anYVepOfZULJ1Lj6E/xybWW2F9YwhX+1WgsTuiLL6oSsS5UkF1+QFaaXDoKMUXtFpNj6pNTujMHDOHoSNG0tFjlQBNrz339W230tXZiXeoy0X7VFjtj5nWD2yFUvrVV331n1CCuRAmDZ999pnsSeurvvpHVHd3tyQE9Hq9fF5aWirJiAEDBjBx4sS/erl9IK2v/ua1d+9eCcK8/X1ptjbgpbowiFuUI26aJ5gwYcJ/eZ/ofbLYbPIhM4u61/DJk67Y7Y7+qlarQoK+3h6PNa2ePP/VeMxbiik+/iYmi4mBaRkkpV6FSqWUgc4jx01iyLBR0pVRgLE3Nw7ijSn7EZ0jhSYt3/46GKt1MzFx/eUy/YOCOXPqBIUnjktr/braGrZt/E0GQ+cePYgKE4VHo3FVXZB7iVIq7BLI3P/o0/zhyRdYs3IZOp0zh7L3SqClUjZeFE7rpIWzhSflNvn4+kvGTjA7gq2Shin799LV1Sl7w7aeiOTKkFJHj5cCCntc5DJWLPuOjIyx3D/hzPkLeaBbD1MfaeS72/LZ6elJ8dl1jJ5wCdMvv5K9u7bJbDZRIsTb2NNDbHyCBDwJSalSbukfEES/AUmS/btp9iVy0HjH/f5sWmPC4D6L8ZdcxqAhw3DWOePq4YlarZXgTK1SYTKbuWTGFWQOH01VeSk5R7KJiI4jMq4fWq3DZUsYaezeup60zOGSqRMB1BXlJTIbTTgnxg5IlsBHhFhHi4GxkPC5uUsnzfueeZ3hE6ayd8s66foYl5QqjT4OHdko88emXnUzl998r9zH4rOMmnI5P3/3GRnv3s7HCRNRd1ix7trEgYodkvlqqKlCp3Tsy95KmRLBsg9/ZOjE6Wz47S0y2qbg4exNztld1FWV8cSHC/EzlIO/RvaaiRNVhFTHDUyX5684dsIoRAyuvQJDJFjz9PGmua6G8sICogYOlkYo3SJ/TKGQfxdOkD4hkbQ7/XB+O8RxdlPb6anayKV3PY9XYDg9Xe0MyBwlA4x17l4011ZSVnCM8KQM9O7eJI3Ye5GMbvZMd16d74RfeCyZM28mLHkI+1Z8ycCY3cSHOL5IxBn5ypNu1EW/Se5vi6jc9BWjDfdSrvDEvdmGIbeS420H8YqIk1JMv9hkDv72NZ9fehMbfeq5wvc4s90b5PUqtrneAr7nTsZys4rN+0zEREQy0qUSk13F/NJ0mk56UDpATaKTg9HutglzDPBUQbPokaxOxqTQUNPlRsHJCCITZ1OyZQGeCSOlzNEpsL8QS9JVkY+TTyidBXm4HZhCscgqMCnQVyjQWlR4eA6gpbkApdaAyuBJRWc+FVX5UAXawP64Z92MpbuNhP3fMvSq3r0Bj169l2M/JXHgDNjN3ZjrTqMyeEsWDasZpWs0l3V9f35fi/uRAGi9x80B1BQcPxOBswis7lBww2PePP1ql8ReC6oT2LpnIB8f6cZrZhMtPQaM2W64rMsj13hAOtJt2baLwtOFcplDhmbJ+8QewYQpQO90sRGCiEoQfamL5lVz9wJHb67YjtwuN9rbHfepyy+//H928+6rvvo3Nw4RExJdXV1ER0fLAfMfG4c0NTX94zbmP7z+k8KsL7vsMnmfFe08IhstIyND9vU3NDTIzOi77777r1puH0jrq795LV++XPabXb8sGDdVgxwwCIOHr0ojeObSdcTFxZGUlPRf3rf4hxXnXBxFvoSdQSkCsFzo8RC20b93c4zUdWJz13Py6FLJmL301kds2fArTXXfMWV6MGs3dXLDzHnccteD3HDHfYyZOJVFj/5K7vEHIakbc54LzeuWSft9AV7EIFu4PHr7+MpQ6hVLv+P15x/jpvsjuP8JN3IKfDjdHI+r6kIeYC+b98nBZNTqAlzd3HB39+TG2++V/xPujKKv7P19l/Lh6B0yuFbkm330QxhOuhbJKIlet7ycI0RFx0kTDVtzozQIiSgr4YO3Xsa8zotngtKZHXWS8h4DLz7iRGy//hSfPUNW8hwB1y7aHs8IH9w9eohPSGb0hClcc9Mdkr2JjI7DbLLIzydYprDIGGk0olSrJFvm4+cvjUMaGup56sHbcPfq4MyhKGldzs0GPt66g8ULq3n42dfkINTc2IDJ2CPDnEXfXsHxHNKHDJcgq7ammvFTZ8ogasGSHcneQ/rQkdIpMkEAFYsVv8BgyTJlRERJ9q2nu1sGgPf0GCWLKUoETwsZpBic+gYEEZ+cJuWCoo9MDFwbamtw9/SRodUiA038TzBtLY31TJp9PQd3bmLPvo8IqoqWxh6dHW2ERvcjNWs0W9f8wI4Ob6a5NcjBeb1FwY6DGZw48jHvr94lHTMLcw5zorOdyP7JzLnnfu6a+DrBBrM8H7/YlEin/gFiUzLw9A/E2NVJ6al8nA0ueAeHyR6xns52zMYe3H38iE7NkCybAGi5u7dIZ0c3n0Ap4cveuJrW9DiesNZJl9LeevfjcK6/cQEPf/ETGmcXTu7fhm9oJGarFSdnPQHRCZgtVkoLclBkqi+WCtp0VBfmMnDCTLQ6vWQ2xwnA5/6YsGc5vw6LEla9dCt3PHc1byz0Q6dZQVGFgYeeHEOO8xE6S2sZestT8nN4RQzAVFWFebs7OZEemBI1uKr3EaXtotTkwva2YEa5l2FHyTdlqZh21LEkfTDbPOJoNzlRe8IX731mvhmZwKWep3BRWtncKphyJ3y0HZzoCGDb8f4oNGDtUONapCbIFk6xzUpr4X7cBoxBqXOVIdfOwf0R8zkKtRM1331P3NgbpYuMU50JZVk9dnd3NIQSeOVcyYBZOlowtVRJ0Kb2CpXLUXS0EBAvBnGO7DhRol/1y8W5rIgCpd4LjW+0/LvSyYUb07dx+5ij2K3K872xfzx2EM9PmZxBuJ9WmaGkmnVHc/hlnRMRd9yDk9UN3wIzln1H2bZsLdZz8mtRAqAJ2Uxm5iAyB6fKY9Zb1VXRFBWd5aorLpdhvaKuvvpq6WQXHh7B0fXHuGHtg9w67CDVnS7MXTkW5+BiOAteXn8iVLKv+ur/YL3//vv/7E3oq//AOnLkCO+99578fcWKFQQEBMg+tZUrV8r+339LkCZm64UD4OLFi6VVe2BgoHTmefbZZ89/OYmZadHk/MUXX8hE78zMTD755BMSEhLOL0dImx599FH5ZSUox3HjxvHpp58SEnKxtK2v/vKT7oUXXmDz5s0yG+yqq67i5Zdf/v9+4Yvj4enpyVURp84774mj2d+jTf4eHh4uj6twJDxRWESArycbt2zHYrFfAGl2OHjEncvHtJ43Gyg3aYl3EmyFY5nHuz3QVCJlc6L37NSJ47ga1rLgvQBpNH1Fuo6U6dN5dMIHePn48thzr/HMw3ez+4MX5QBfACQB0L5Y9BMWq4WD+3czeZpwZ0Raws974wXufH4CH9wu7OM7GDoSdjRWSsDZO3RqtMKUeRPJ+/QrJk69DFc3dynRE2HMwrlx/ORpLPvua8oWNDElfw7haXVU7jCw9aP3eeTpl+TrhRxyYNpguU02q1VeF4JdE/1g02bOYdGyt0g+kc4BV39OnDoqpZDvzv+GN154gob2U3xZFs9DEQUyl6zQqGXevblcd9Ud3Hn/Y3JGUUg4RXl4ekmDEgHEco8dIjk1XTI+IqNM9OwNyhwmXRg3/vqTZBO/OzgenbL03HUIc0bCs3fvlFEIInpAmJuUFJ9l4CAf3Dy9ZQ6dm7CTd3KSwdSid0sEUwvQN3L8FMk0CvmnTq9HrzfInjNRArgJQ5Ocw/uJTxROk5B37DC+gUHnEcdP33/GkJQCXF3U9HRO4sCGVxiedpSOYg2Nrs8QGBZNyekT0pBDMHuidyz/yAGefG8BB7auY+/mXwmOjGbs9CtJGDyMHz+fJ1/z3IYpHBx2GH9NJz8VJuN82iL3gbPelcnX3s79D0eQFbaWzp5afjvyOcEGx4BajMvnjCkga9pj3PnK+xIctrc2y7wzwe65eflQX1lKUX4OMamZdHY4pHDCWl8A5JjUITKjrbO1heL8o5SdOk5PpQ8FMwxkOF9w5sTPi7ryA9SWnpGAzjsoHJtSK/vQdK5emEwW9J5+bPnuQ464JpLo08hAXTstVjXP5Y0gJFZFwa4NXPbYOzh5+EjQdsgngGkRxcRpLTI/b0l9BBptBw/O3IrTOXooKqSTqNhv2HIQht32PD5RCdSdzkXnHYDey5/u7TsIPDGEMz2hvGXR4a7robLFg64OJ3Z7x9FjUdNy2pPwFmea97lzOsgdRY8CtzOg2n2KdTMSORnoD3YFRdU+4uOg1lroatSjy9WiUIOqG9yKjJg6xX1DgcVsYXh0ES7Us60kGaPBH1t7Ix4pl1D6/cNUHt5HrC0KRbeRMz49tOYfwD1jDpbOVky1p1H790fj1w9jVT4q90BsdqWcnd3fMoJTpu300zpkr6JcdQq8fZ1p2PY+htQr0CddSopuLW9enn3+/vPHcs3eyaOzJiVvFQ/F1qxGIYCc1YzR3oVB6Urdl5/T3tQg7xEi6kKtVZGUMEi+t198f778fD4uLg529/cATdSIrAz56AVnv69RI0dQkH+cs9u8eeSsI4JCZbZjbzhGSkqKvLf0VV/9JxiH/G+c9Prqb1viDqb8Gy7rX7nEWMvV1ZGfuXHjRsmqiXv4kCFDpPTxr61/Kkh76623pG7422+/laBLOALefPPNMjHeYTwBc+fOlVThN998IxmYV199VUrlTp06dX6HiByuX375hWXLluHt7c0jjzzCtGnTpA1r35fTX1fHjh1jxIgRRIRH8IdbHqPL1MF3S76Rzef79+//b0MiL7nkEubPn0+LcRAKpwuywLouZ4I9k9m0aROvvzWXkJAw+fccux2TxSaBW28emgBmKtcruPP5t7jr0XDOmFx5e+UoJmp+YtocHbkdXny2fjh+Jws41t7G1JlzmPfa83z4RTh2OhwOcnYYF1NCUvIgNvz6M9NnX8W78xeyZf2vFJ8plDLI+KRkvL39pOlFxpDhNDXUy1DpnVs3SqA2dnr3eRt2sbxYtzbeLR7AtaGn6LYreWlzGoff+4TU9ExefPMDGWwsjDc8vbxoaWmiuamJp19+i/fefImOLY7Zb5HHFRAYxKEDe2Rv18QpM/Dy8qHH2MN9t13D0YP7Zf+csNkXYbMiSFsYBNQ0lEvp4oQp0+W2Tbv8Sj7/YC6u+oeYMKo/vv7tlH1XibHpLJOmzmTH1o1Sxijy31pamsnPOcpgESegURMYFILNKvrFgiRrGRIeKe3+nZ1d0DrppHFJSZej+bp3UCoG/u1tLTJ82svLWwKuhIFpcqAr8ufCIqNlj5mbh5cEXgJ81lZXSpmYs7NBLiPv6EHJ4HW0t0mQJqSOiakZlJw5xbZf5zEiuQ2dVsG2kkiCI56TgGvu0/fz+fw6Un0dbEdd91d46RzW+4o0+OnAo+zadR9Z46dKO3vBvgkjmPi0wZJVu+Sqm0kZPlZa4ottFk6L7p7eEkyFbWzit9xMbBoFwWeMHMr/iqTMERKFnT76LY8+mO2QqDrD9aMvpkwsCjiTd5h1i74ga/JMQuMSUAtDEbNJ5qC5e/vLUGrxs7O1mcIj+4lOHoRG5wLmDqwWM8aeLnxDIgiM7MeOn77jk9KbCI7dg4/KTp1FyXtHM1Eostn+wwKufPpdVE7OKDVO8qA011bRXFOBu9VGa20Vmt98ed7tEnw92mhqd8G43Z3A4GZO5W+Txjfm7k6KDu6gXG3hhbCRJHlUUWd0YXt2IolRYWicLjaW8I13J2na5QQkZqJ2ccczagBqgyfxl1zPkcXvUOuVg+epKGy3TqfKxY66UYFznZ26MD0KC3gU21E0ttKyYDGRw66U5hu6klZO1u7CbVMwp1LE9a/AtdbKQP86qiwu1JRr8SzoQV3Z7ADbjS2c9a0VFw0fPlHH5Qlb5baVNm9jyvz7MRutqF288Rp5C1U7F1KtcUKh0mCraMc5YhBuabOw9bShCRyAQuchbfSFAYhdpcPW2YypuoAqYxyvl/XwTuRefM9hmVoLhN77KM0vvk3n0eVylmjsY45hQi8Y+z1Y+z1ga7I6c7wgFLcSFdr6Tlq7HNES4fHJZIydRHvRCRpqKgnw82HY8OHS5GDWjEvPg7O/tARgmzlzJlu3bqV2+2ckjrwNk1aHvrGA3woOyFndvuqr/8tyx7a2tvNmIeL3/676TEX+cfWfJHeMiYlh1apV8l4s3EVFiLWourq6/9U5908Fafv27ZM6zqlTp8rnoslTsGECrIkSg3ZBXT/zzDPnNfUC0InsiyVLlkh3wNbWVr7++mu+//57xo8fL1+zaNEi6fAjGKBJkyb9Ez/hv28JMBwSHMLUkCs5OD9P/u3lx97igbfvlMfoz1mKCgAmwLG4oGaNP86eXVGEO1mkhGhGYCVFawfwVFYuX8z/lJdfe1MaKZitdtmnIwBaL1ATdvWb1v0iwchXX/ZqyHdyGHjjGYiMiaOl+Sg5jQ1Mm3klzs562ttaOdPsxWBvB2shrulyox5/f18ammpx0jqhN7gwbuJU7BOmyFmOgvxc1AkaCZpETpdgmvJzj7H026/kGveUBTPDv0pOBAqwVtRj4OWR29l66b2015/l4P6lEuzN/ehLyYKZLRYZCj1m4iXSZn7w0OFYLRZmXXUD3389ny8+nieB3DtLYgj1bmTu62+y/pdVvPHB5zxy902cyM9l3sqhXJZYTbdFQbdNTUN7D1decpJHnv6IoSPGoFQq6DEaSU7LoLaqkp9+fA/7Gse3oN5g4OW5H+Pp7SM3WKQ6CRljY4OCcZdcSmNDvZRjClmhcE2srXZ8NsHoiRw2kckmgFt3VyfrP0sm/cUqMgxNNFvVPLs6CyenMygVKnZt3UBahugr65HmISmDh9DU0CCljof37yY+KUUGYAuGLC/nsOxBEyWeG80m/AKCsSkU+IWEczLvCM/eewMlp0JlaLOYdk18pIjUSTeTOnQKJ4pzGejjMBAR5fdH8wNj0tXccO1zDJ80XT4X/WoiZNpmsdDW0iSBW3BEjMxBU+ucUZvNDJ86S4LNtYvfIzSqHwEhkWw/vFv2XSUPGcXhHRuJSj99UU6as8pOnlFLvNYkJa7zKwYQk+xGbXkJ3kGhmM1GGWZdlH+UYcP8cXGupaMjyMGeqTXn2bOu9lZOHd5HQHg0gTEDpEwya/pV7Fj5LUdXhXHbVBdCXFowd2r4ImMbLmdjWLShlYa2VszGblRaZ3kOifNXSO7E9eIb2Y9jGxaTqHmSqhAPNO12/PbVc7ztCJ5B4ZQdP0hw0mApraz7aTEnYp8h1zcCRZcKr6N2jB0tbG73Y7Z7DaJbrcqiYH3tJRxcMg+3kGjqCo/hFS5y9hSEDR5PV2MN5Ye3UV62i+TvgnCLTULdZcV24ixukcEodDrUFc2c0RZTXZuDutCHIH0/yqzlVClKqF/2EYNankTjaeWHJ5fh52aUEzOvvzeUbUdhb/NPWFV21F4B9OSdxW/4lUwbcCGENtyzlcSodvbtbkCh98ElfixOgQNoO7oGhbM7uuAkKWm0tFSi9Azj1sztPDZ6I90mNXf+eD37TjhJ2aM2KFFKJ7f96Mu6O0K4zrtCHvMem5YeNx0jBz6EwesLliw4gl6rkAHxvzdH+ZOlsKOyKXEpNaEoLOeo2QEsU4cMx9fFQExGFoHuTrJvVtSN113Miv01JSZztmzZwv3338/qH1+Vhj1RUVHyu3DWrFn/6+X3VV/9K5dQ7ohMKtFmISIm/tSAXowtxN97s0j7qq/+liUkjSJ7UoAzoeYbOnToeVYtNTX13xOkiRwLwaQVFhZKlkw4Au7evfu8pri4uFjKIH/vjCKswUeNGiXNKQRIE4BAmAT8/jVBQUEkJibK1/wpkCbkeOLRW/+/mZf/xNq+fTs3X3EbRz93ADRRK9/5Vd7obr31VvkQ+1nIH8XvQnsrTkwhSe2tr5alEKptkgBNlBh/3x12gqfETHVtrQRoMqhatHbYewEa7Nu9nUum7OWjd0KotWhRmBRoNDbm7whj+RMH6exsx8PDk8yskRJ4CMZGuhEOTOP+y9bgtSeOBEMzRSYDr68eS0H2p8ycc610bRSys+DQMAkcmhsb6Whrk7K33qBqYXv/wdyXqSgr4kBBGqkeB2Xgc7VVy9luF55+JggTx9i06nWZi3bznfcz+dLLyT12mNHjL5GgUrBdggkzdvdI10YBqoSN/ZGD++W2LtsawgiPagkkf57nzsgb81i+aKEEOw98dRN3pOz53dVpRoya9+6LZvr0Txg6fDR5OccoKymSn3nW1TcwYGAqGpUaFzc3Bg7KkNISER8gBmoCoAk3RsHeWaxWySwLG/5BmcMxmVpoa23m1MkC2UsmmlwFsxcV2086MlZnL2Hek9fSEKvBt87KrmWvM23W1fj6+3P6ZD7333Q5o0dV4ePrxNIFE7jlvpcw9Zil26Ng57x9A+ju7pKujmIfi54yAcaFPLWuRljgK+Xva5Z9g/+wFDxVdecHv8L8wD+wjo0/LyPq0svpsO3A9Zzewfo76YN4eaXJSfZ5bVu7Ev/AEJxd3KRkUdTxg3vpnzaE5oY66murcBMAMSiUjrYWZt56P2Gx/Tm4fQMtjXWMnXmNBG8KewfXpD9FsOuFHki5rB49d+yfRkJIJbUdbtSt8cdqLkbr6SX3tfg8ok/sxmlryAxwZLMdtTmzpvBN/EKj5H3K1NMjjT/iUoeg0ulpqa/F2N0lewa9A0Mp/fxjtJ2PU+EdxtZ7F+Crscj13zujjke+WYrFbYR0kgwekCoz2DwFO+Xuw4ARkzi4ZhHVR34kqUK4IJo52bOHupKTzHl1Id6hUVjtCoIGpGP6bh4BexqxqFxRmsw4V7ey7cxavii8n6LwE7ioutlbH0N3dTAuvkGUZm8h+fI7MZstaA2eGNubiZ95DxFjr+TQ1y+SX7yKcC8jaiOcrl+Nvd5OaL+xmHQmaov3YgiIpKb8IOVdW1AoVbjHpNJSeIjSU5t54WGVBGi9x/LGmw7y7mIlRnsHar0PGjdPAsa+gleMP122I9KiX5SYWDi96UdUPrNl4LTKRUiw7fiMvVsCSYVWj7m1Gkt7C6F+Zl6c8JvcjwaNhYXXLST+6Yew9bSj0HuhsLXSvOsskx+pOW/sE641cXlYPrs94vnmSx/0WjHAc1ySAqhJFvePxoHiXKmzwo8NMY6eNSdQK9WoUKMx6Any98NFrcZVpzoP0P6WFRwcLHvVxMRle3u7vD//sWSyr/rq/6LcUbDIvW0Yfy8r9L76y0vcIv9W/JfiX/wAzJ49W2IaMVkwcODA838X42LBrv1bgrQnnnhCfqHEx8ef7xF67bXXzuvtBUATJZiz35d43qvxFK8Rg0sxk/LHr+l9/x/XG2+8Ifvc+urPl5CStnQ0SYBhlW6LdrrtXTjhjFKhwVsfTm31aW677TZ5LITtbU93DzfPm8VzswoIUVtQKpr+64xzrz23RisZNAHQzp4uZMfWTdK0Qwx2r55t5LbJ4oZrkXb10ooReHvyKSqUV7D7kaUyl+ueR57CZDQRFBxKfW01V91wK7+tXsF9l7YSOew61B1Gqg8vke+dOec6DmfvZUBSCg/fdSMb1v5EcqKGsgozMf1GyJywvKOHZN+WCKl+97cZpHvmy/fqlaC12pne/wgW+wFenzcflUbNgMSBhIZHSoAnMtJE75foIxPgTZhlHNizk9TBmXIZwhRjz44tzJ7+CImuDtmj2DdisHfrk3G8/4dN+IrctCSRDfZfj0eQ1kRBXj5P/eEuuZy4flriE5354C0n3v70e7kPhDxM9IoJKeG6NStITBlEY30dleWlfP7h2/L4iO2dMGUGVqsFX/8Qh4xr0jTZQyf684JDIziec1g6U6qVxRhs77Drgw6OGe0MHTmWm+5+SDKNLz1+L/tPpDHYw8Fw1RsPMP6yGcxbsIrElMGSsRSGHyqNBi8fP8km1lSVS3c7kS8mpJa5R/ZJAJdzcC8xl91EpWUtYRqrHOyK7Lum5gg6O8/gVadhbkUSdwXno8bOstpovJy7GeFaS5NFyxNrxQRNrnSaDInpT2djDt6W5TS0hxMzcBoGD0/JZFWWFkmQJLLMRL/ciSPZJA8dReqIcdKRUbpIdnej5zEJ0HqryapgfZs/7+8ahdPCNgri49E0W/FvKCen4BjXTnmJMzn7GD5Ez+Gj2dx704Xw7NSwbm656zamP/QlNaVnCAiPwT8qHmNXhwTOAtR1t5STGbGNDz8Zzu3XLqN11494mYJxefCCoYSolvJlFDebyLr8Rjnoaa2vpqutRZqvePgFMeH2J9i7YgHrCuc6zlsPH8bc9iT+MaJ/145Wa6CnvZWwgUPZsfEtQgZkosWJ2ppCzKYe2te78IM4X0VsRqWWgKJODL4hdDXXSXCl9/Khq6lG2t5rNU44uXiQcPndlB/aRuWB9Zi72jAERqDSGaitzpGsXczU2/EfNB5LTwc2pRMavRs2i5H6nB2UrPsK4oRT44Wy6Oz0dNYTccVzOIck0lGagz4kHpNaw28d3oxzaZS9l4e63ajo0NH424N4j7wF58hBqN0CsCs02DoawWZFpXNDOJAkJZy6KOBZr7HQtP5NNP7x6OKEEYkbSidXUJ7zvT9XY/oXsbclAicnB0DrLfXv5I690kcRzL2l08D3VYPIKQlHW6NE1WXCajai0jvh5euHh5MWtVKBi9OFr93rr7nyb/41JNoFxKOv+uo/pcTEfW9FRkZKJdUfs2liEri83BH50ld99fcoYRYiHr8v4fL4v6l/Kkj74YcfpBxDSBdFT5rogxL9ZWIG8PfNn3/qYvv/6VP/u9c89dRTPPzwwxcxaeKi7qsLde2118pewDuvuI/sZXnSLtw1ZiDjpsRwzfUneH91OsGnrqVs41cSWAtwNXHm1Xx+1aHzzNmfqq/LYoS9Balp6WQf2EdeXg4n8/eRMbMfjR0Kho+xMW6K+/kB0O8PoXBGTOxfCUMnS1le9u6dUmYn3BEFsyRA0heLf+a9119gy7fPyvdkDhvFWx9/hZevL96+vrzz6nPs3bmWsrP98NdapAnI8z808fCdN/Dy2x+zdtVy+T43H0dWWm+J3CqL3cxdDz7O+EsulYN5q80q+8YESHP39KTwRL6DkVOI7DUlIWHhqFVqzp4pZNXyJdIQpPzsGUqMOjycu85PLu7Yj5QJCofDX/bHc0PIGZx7GYNz+6HY5CSfC3OTTzZP444Bp6Qsq9GiIjlzDl8t2caJ/GOkZWRJoJk+ZIQEYgW5x3jw9msZMzOMBa/rUHOMx59dT0vza3LfCIt/J51Ohk3nHjlIRVkpTz90O3N/GMYDQx1Buc0WJYOGNzJxmnBrdObjuS8xYPRUUt0dFuGifJ1sBIWXcjR7DwkD0yWTJR6H9gmgmiVZpI2/LKejYQsRUSGEJ99F/5QMjGYLBld39KXV3H5wIo8n70WrsPPJscHUVa3F08eXvH0r6fn0AVYPGygbwQwrWulO9uGtaBuqKhVxp+rlunyCQli3+Gm+f+0MTnL/7eWjlcs5Xf2adHSM7J8kzT08fP1prK0iLi0DVy8fee4ez95DZMJAFr33Mo986CE8O89/tlarhteWXYrXmnL2HvsI7+JgvAKCyM49RFLWaAaNu4RZsbcSYujhyv4OpqW3B0MM+7t64KdP53LLS+9LNqqtsYH25gZpqR8c0597xryGv9Zxvg052I+BI0oo6colx9ifITrHdjRaFRTZZ7N7+eckjp6CwdMHOwrZkxbg4Y/ezZO4YZNImjiHoqN75P0vODEDs7GL4sM78Y1OROtsRmPwYMQdL1Kes4dTO3+hraUa39gk3DrCqFz1LfF1t2Jx1eBUa0TfZaHxbB6BSUMxmcxYrI1S0tt0OgfPuDS5XcbWJiJGzaLf1NvoahVun0b0fqEo1VpMbU2oXTzpaajA1NqILjBWhk+3FuXhnTwGj35D2NWznuGmA4SrbXTZ4dv6fphaV9NcsAtDdCaG4P6Ye0TmnY6FJZnk+ZWhwM7eukgCBwaiqFbSsPsbvJ1ccFI6ZnNM9UWonF1RuASi0rlSUO5ElQWC1I7rKbdHR9DoYZStXkhP0W7cRj2IU9QwltdUcktwGbpzx32MZyONbx7kt3IvZoU7JpzE+00gs9/clHDGqOXnpkgqerw4VhNC+xlPXEoUuBX1oD5eyuG2dXTTRubQy/F1dUItAqiVCilxFJOSfUxXX/2r1r9TT9rvS4C0XunjH1vvi//1yR3/cfWf1JP296p/Kkh77LHHePLJJ6VroChhyy5YGcF0CZDWi0h7nR97SzTi9bJr4jXCOl3I7H7PponXZGVl/cn1CsmkePTVny8BZHfu3Mn7y96Wz8cF38ONiw5ydWi1HKxcdfcafqj249PaOVTveF2+ZuTdXX8WoBltMO9ULM+O/U06Ch4+lM2undu44QYPdq+MRq2wYLHrUCt0cpDbmyn2+5BbEfp6pDIUc9dZaUwx/pLpdHS0yT6siOgY+WJhf/78m+9RkHOUtMyhslfteO5RYuP7Swnir6uW89G6SfhrHQBDjOUfnG3mzT/kMfuSEbgYxPmhYPHKRC67rxRvtU3K65aVCxvuk0ycMl3ayotBsMHVVQIzyRpVV8k8NNELJmSIAryJ13z+8bss/OxDhk+M5qs1SRzas48HPr2WV+/cir+2m19Ko1n0zGqee30erz7zCOZVVVznPolr03PosSmI1HfQbHbimUeUkm0eMvhy5sQfOU/9e6ut3PdyIEcP7WPE2Ens2raRHxct4OTxHAm8BKsWlzyEH+ZV46JwmLgsfdeb0NTHWPjjLvLzjkpgJ50lxef89ktiYhK4LuOC9EuEPd/7og+lBfUSEBedPknWmDl02k7jdi6gW7y3scWNo9l7pQtfUlqGNPBISh9CY1Mjrz9xDx98rWBylNiGRg6X3838RbOZc8u9DB0zmdVLvmKq+3M8FjQLZbed4NpqaivLmXr1zWz7ZSXFGz8jvWoSJWePc7D4ANrdOgYlT6DL3srPR3YydsZVrPzqAx5/z3IOoDlqzqV2kjPv56ZHXyRxyEhc3T2pKS+RGW9avQutjUJiqSR97GSa6uvJ27+Tb07eRZZnLaFq0dEnBvcmXo3+hhvOVklGTu/mhs5g4JrHXiFh6GhqCh8lJOWCQY7orRKQS2zGhjY//Nzj2Jf9LUqNTppY6F3dsVpM8jwvPLaAgOQLEwIR3lZcnG10NJt5rmAs10UdwU1l4oeKROzlAbLP7uiGnxhz88PSpCQgVoFOY+W6yLsJT66kpC2cLzse5UxOLhZTD04uXgT2Hyxt+pU6F2wdrbgFBNPPOZPggVkYfIKxGLvJ/fU7jq6YT3HucuL9R9LeVkNe/QGUGi3x027FRdPC0LgqyuoNnHAehrmrHWcvf9wiE7ErNZitZinfdPUJxdjaIPvm7DYrPc01OHkFYlVqUbt4YWyuwSUyDaVOL2WKB3J8+cgjlQjnRmqM7mwoSCZxUBDHD8/HI2kchtAElBo9Tfm7MNqcqEobKO8N5jpnPNoV9LPF02DfiLWrFbXeA6vVjMYnUh4Eu1KNpbOZ0/taeXd6EqM8SmWP5081SegHRDM07x6yq5fSlfMTHlNe4K0lk4i7ZyUTXB09sOLeMzyhjD3bgmgOaUKrdDC8onfv41NZBLh00NDtSm2pF+pKFdoOBb7VFgwnm6g5tZMCy37u/YMv7zwWi5I9LDt2kGfvbOexJ4Tgmz5Tq776165/I7nj/2SCvqOjQ/Zu9tU/rv6T3B3/T4I0YVn5xzOJcrAo5HXnZkQECBNmFL2NdwKQ7dixQzpDiho0aJAMKxSvmTNHZEYhZ1GOHz8unSH76q8rYbkvdN5paWnk5eWhMDgzJ9ThUtZbcwLr+C6hHXY4nu9epMP+5oX/994nRZ+ZPljkMp2WN0+bzcIrK4fiEaThMq8qVBIGOWREosQZUWtRkN3mz+kON+IMbbhojSwsSkK91J1NO9ZLRktYWAuZo5D4Camg+F1ht+Pr40fWyLHSAKO9vRV3D0/Ze3bmZL6U3XVqLj7txWBZ1I68QWR5tUh27fWVa7n045mMuqSIM6U+7HxsJaPHT5bAp6W5SbJVYlBfdKaQpIGDZAi0ADDePn40NzVIRu1M4UkJ0K576k6+uG8rTsoubhzkzPL8ddw+wYKnryeHDq2Wtv8iOPvE8VxWLv0Wp33OrOpxDNwNehfJ2IlzXMwAunlE02M7il15QaPdYdNTe+aU/B58/tF7uev1cWz/JQpnhY3lB/V8sD0TF8XP54+HkItFxys5kZ9Dclomq5cvJj/3qLzuTuXnMG7s7XTbN2DHdn4dRoMfyxZ+xukTH/DLplhO5q7mpaI0Ho44KpmvH6qjyTuwjbRUD7JGT6C5uVFKPjVaJ1Yt+Zp2524mRl641geFwu517+Dh7YuPWx5PPxXAwq9fxESI7C872tzI7FvvZ/p1dzB03FTWL/+OrTuXSnfGlCEjJeuYX7QHD28/7n3hXWKT03js6snUqcditzecX0+TTSOd9Nra2+S519XRztnjx+g3aIiM6yg7fVLGB7i4e8noALETO9a4cb1uGt+mrCNMY5agb+ZEM7NnKbEHvkT/wSMkCBefb/2iz+k3RwDyC+dTl13BLYVjZMjwqcNhRBnqZE9eU00lHc0N+IZE4uoXTGdXN3vPZsueR51gjc9l7nWbREcetPzkw5sZk+QFoS3UEtHsAA9B/VPoam1GrdWi1miZEPsKMW5l8vjGuhcxIuBD2i1P0NPVjdrZVcpgXTx8aa0pw9pZzzMjnibStY6Wbi2v7HqKZnsMEcOnoxPW+scWUlz6CWUVFryiEhh99+sEBqj5ZOrzOKsc1+kX+dextnAcreWFOLl5YVcqMbc10Vp+CvcoR4RCd2MVHTXFGMKT6W5rxdLTidXYg9o9QN4YTK2OfVK1egsVUaN5NSMXD3UJY7vbeN88EK1XMC25m1B5C/atC7WzO2UfvUT/u17CqgfXZnCtMGLqapfyS7uIruhowK5QodJ7Ye1oRKHWYuuxoQ1IYtUmN/YmxWC1K2mpdcO5XYFe74y/WypVleuwtFRgLKpg7YFAxo9z7GdHvqOCy8dXnL929nR48U7eGLrPumM74Yfdbsa7x4ahvIPu/ByOdmzEhKPHTqlS8sFjHuffe22KiWU3BPHAfXfLHtYvv/zyf3o77qu+6qv/T/Wqo8R9/rnnnpNB1r0lvjsPHDgg4yj6qq/+neqfCtIuvfRSKZULCwuTckdhPiEkdr3OgeJiE/LH119/ndjYWPkQv4uLT7ioiBLae2FcIWz3hf2+aB4VmWmClet1e+yrv64E4yWYTiF9bGlygIDeklJEwZ5NymXz5yp5rDZ8/yMf3zyJW+POSuMHUU0WiIo/I/8fEKii/7RoPn1MRayLo1/w94Pb88sWwMOu5sUlE8l9/Tn5NwHmff0rJGMlZHp3Pvg4JmO3tLsXwEmEJwv2KC4+gaCQUOlUKACakF+Fhkfg6uqOp4+fXM6mbxOZ8Hwx/Z265QD5vbwUbng1niwvRw+agBKPXm7jxeA3yfnQWUob4/on8NCTL8iMshN5x2TYtACBIgTbw9NbbofDbc/uADsnjvPzD4sleBszq/gidmd8vJFrK87g4Z/JlTfcygOPPScDpu9/9Fmuv+0eln7zhXy/2WhC66QlKjaeOTfcwgM3X42xq5BX8zN5NWkfBqWdI51uvHnHYa69JZNP332drJHTeeWGU7grHZlP12Xa2HawghKzhkitw8K+0aoke3cbI0bV8PAd19LWfpLNW2II1JnZmhfMAzet5dWTw3htwF5cFHaOdbvywvX7mXJzLD89b5L7Z0piF2vyipny1Y2oTOCx76iUVwaGhtHR1YVKo2Xbxl9IGZzFZtH/98hdmFiF07njLX4IMBIaPp8HbhfnkxNP3hHFsMvaCI2fRerQkYTHDZByR5Gr5uUfyP2vvC/jAeory7HYbPgHh2Hs6aa+plKCb5FV9v2eTJKm1jLQuZ1mq4andoxBrTkpbfdFALR438CRE6Tjo7uXD4Emk3TkFDJIYYkf3i+Bkxu+JK72ZgwLrRc1Kw+ZGcGbjy8madg4nFzcMDU10FBdSW1+ArtTahik68Rkh0+r+1G6NFpKfMLyWslv2kJEQipaAewaLPSYzdiEYcvBXZQe7mRBYziXeZTLffJtbT/SBkSzbed7VG3+noSzV2FWKjA0t5Jv3IHe3YuYwaPkOXYmezuewVG4p13IYBHL8HQ/y+annmPyw29zeu9G/PulYTLXYzWbmDl0pQRo8t6pM3Ft0qd8kPu+lL3OvSeXodKDPpIfTkxiVfEN1Bce5ZKENecBmrhep0Ys5+fD6fS01uOss2BxDkNl8ELvH4Vda0AlIgLMFpyDE6Q9vt1qwVIv+hFV2FVaeY20FeehD0vCWF7Kh8mb8VCb5fk6NbaY7BQ39tY5Y25rwGbqQuvpyMtTGryp+XkVCUFj0AiHtrIGznj3QLUZbWA8PdUn0QYMwNLRiN1qwlJ+FE1QMthtNPx8Bm1DIjYPLU7tClwqbSg7jWhdzvU726w4hQ/mu6+t3DysiIHODpmpl8p6EasfoWunp16P1zEbrqdaaTqxn0Ombdixo5LTTY79JAyDrr/hChSKzRfdM/9wvZmcr9P56quv5Kz+Rx999Ffdm/uqr/7u9W/GpInxo1yV3S4nloVXQW+J34WZgxgb9tU/rvrkjv/mIE18QYkZj3vuuUfKE0UvmnBsFFaWvfX444/LGW/xmt4wa2Fp2ZuRJkqkfAtAIZi03jBrkavWl5H2vy9h4iJmqA7V/sobeyfzXJYIdj7XOA9s/qlSSkeHjxzFxvXreP/OnawdNYzspado7XAYKAjw8uF7ftw9xxWFQrCkFzfo/7EyQdglfFg2ENOyA/L51JlXSqOH5sYGHnziRYaNGktrSyMatYb0zCxc3T3kAN3PP0CuS1jpC2AlXCLDo2KY+9LTZO91ZEAJMLRz2Tzu67wH+zgN1lI1+19/lTuX/ekATGFXL3q2RM6XcGcUgdWp6UPo6ux0MC/nvgD0Li7s2b6ZpJRBBIdFSHZt09o16JydKWj2wR5UfH6Z9RYNGq2WRas2UlfrkBUKkCnytcT6rrv1bjo7O6TLojBYEXleIrds9rU38fE7rzFVczPTYq/Hru2hdMk3RETHMnHaDBYvmE+/SXehU5y46DMYVNlcu+IK/jB5D1qFjQWLElCrS9i3ayvFZwvZdzye2HMBypelwIEHjLStPMlr9VnsrgmDnwqwGY9w073eqBQX2NTM+FZOTH5WsmUWi5mHnn6d8Jh46dgoKjymvzSPEBlqTic0fN8YxlVeZdIsZU1TEN8uUzM6wnIeqAs52X1PurN6tUJa6J8pyJUskKjT+TkS+AnmqK7OAfA1zoLNMlF88jixCakyB023soT77bMwBHXSXetMwPJmyXj5BYZQfuYkAaER8ph0tLbQ3tKEq6e3lITq3Txoaazn6j88z7yHbuLA5jfY2TGMme518vi0WWHtySzKTn1MXXkp3e3tMrBasEHGdYU8EDWduJAqWrr1VG0LpmXll/T0dFLhqaWxpoIbX3gPg4cvPnYlrt6+0na/4nQ+XcdO8MnOK/kpqhGzRUVjjg9ROJjA5voKdta8SUBUf+pKT8trIHPGjXS3t6HVG6RT4+lDOykxuZDo3C33q7h2fmtOpOTQCnJ+W0JU1mRMFguuPr5Y7HbcfaouOjd0+hY2vnEnE28cw1DfY+f/Pjt+Az/kTMHJK4BOF4eUs/c4GbRmbNvvYfXHbvjoeyhq9ef+1Q9g94ugRxiLuHiiVGtQ6twxdwjXVDvOgTEY21slmDO21OIcmoxS54pbTAYu+uKLtympkp7vzuA/4R5UenfM7Y3yy94942oa1r/NkCvLefkBrWTob324ltXWMWg8gtH4xHBn1jZuHHqQ4no37vpiNM09DudehVLD6feeZ9CIxzEondHUttPV1kG1fT8qV38UWoOIYkPp6k+U+oJ0VfSGCvmq/PzCnqbbHTnToFSgrG1m4E1n+PKJZOosWlyUdnzURpbnRvDCZb/w04pfeftxIeE+93477G0PJGDqKBTLe/j4449l/MzkyZP/5L2nr/qqr/7n1evqKLJ2P/jgg748tL76P1H/VJAmgJaw2++13P9TJb6cX3zxRfn4c9U7I9k3K/m3L7H/RZ9g//79eWn2epZkBbFqkTfuajP7m31oqI2iq+s7CdB+3tSfSxOEZXgJB5/0Yv436XhGNLFuiYq75zjkWP91+Rd+7x0EVlmU7Nkdz8miF+TzbRt+ZdKllzN91tUU5B1l/66tEnzNuvpGXN3cqCovlQBqz47NtLW2MXr8JIaPGk9IWAQ3zZ7CVXdGsOnHOJyUdlbmOnPt5Fz2LH8X+48X1p3/gwdHMvSk6rrkXPjSmnApz0zM8mLeW2q0im4effwlqivLJdsl8tSaG+o5sHcXg4cMl5JKERQt5HgiH0zU8DHjWb7kG/I+v4bFz1cz3rNKuhHe+5IHaYOH0trSIhm+rq4ODh/YS2z8AKLj4lHUKIiMFjlwjVRXlOPu6SVfO2rCVMpLitm66WfaNzgiA0Q/2WvzPpNB2KLcmnrY0ubLNPd6+bzGouKLt0/hpv+ar38bSUn5CU4Xfs49jzzLLyuXMGrkLDw1hy46Bg9d74yfRnyGPRyt2U/6Iydl392xVh8u864+zy6V9BgkozPjqpuYc8Od0kZe7+YuYwiMJhOhkTE0NdSRnD6UsiM/89ln17NgWDt2k4Kk+gK+vO5iwCCqSRfNvi2/Mf2Gu3D3DUDjpEOhUpGSNVrKIIVxSVftUh688gh6tZ2fd/sRnfg2Gp0z42dfx/plC5nofAcaWwAqZTs2z2U89FAMg8aO5MSxAjraWqX0RbBmeUcP0D99qARtdRWluHh4EZ2UxqW3PMCy91/mt4IBTMysR6e0s7UpiK5tPnIbuzvaaKmvluxYZGIKv3zxHsNdUjgd3Q9Np43AnHJOthRJUBkTMpix191NWMIg2psbZZ9WR0ujZP5Sxs3g0PqfCP61lZbQADl3MU1VwB0fHODV9mjWVT3O1vUnKT66j9RJs0kae6k0/ug2m9GLQOzOTnStG7jUvf4801PYY+DXfSmEJlVSlL2N2FGX4ezqSXtDNRZjF+uagkl1acZL5XAkXN7Qj6aS9Wi8/CQY6T224hrY8OL1pF7/JKvLI0l2rybZySyBoJvaxq9fCqdCxzkX6VbLnMRVfHXY0VvckLcD18gUMLXSVnIcnU8oKle17MkTJiJad1+sqDG3N+A96BKyu79jgqFdfhnVW+HXVodjqNXUjVKrx2bqoassF31EGgNueo7XHlricEZVwsIP/Al/9DJQOzE87izPTt4i3xvi1sbCBzcw64tHpNW+LiIDa2s1h3a+gS4ggZce0jJ+WBvbdrXz8i+T0ZwLW1fYrHTZVbjYLzhrrm71xktjpMjoyrclg7HXa1GZbCSkNfHOi2KipguFouv8/evpwScpfHUKS59fz+ylk/juyjNoFLCr040lOZkYlAriAyfSbi+TETR9IK2v/hXr39U4ZOHChf+4lfXVf1v/SRb8/ydBWl/9e5RgyoQstb3LyAP33kVHjy/xnlZm+tUy9It6psx9hvuzljE98cLAJt25kwX3ODLWHhj//7+8aiziNUrabCpeOTGE1BO/saksHo3SzpK8cB6YtpSKouU8+GQE2QfNfPjmMplpdus9D/H0H+6iovgg3/+UgM5ZwT23PsPKZd8THddPgqa3HzJKaaA0PBnYzcTyfniqbFQYNQxMPUFAUAL5Oxfz1Kv3o59YR0+Djs0PvI+3Tzg/fGjGQ+noMVn5sS8BCR8wceoMydhZLVZS0jOla2Mv4yN61QSLJ2z8E5JSGZg2mO2/zIWWy5nfE8LhA8uxWIyMHDtJ9p8J8Cn66QZlZEmHyKqKcpQKpQQ62zauY9GC+fT0dMvogEsvv5qX3vmU20uLqaosIzKmn3zP1vVrScsYyuChIzhwYCENb9zFphtO46frYMsXLiisRSQPGszpMzkEhoRy58NPkpiSzuofF6FWqNjUHMRNvsI1zzFw99NcYDpTA6x4eytpaupk3bcphD/Qyki3aqpNel58Kw2DSyFzbrqT40cOSomicHGsr6nCrlRJhk3s8+TBWSz94n2svy0k8kAKR49tZ+ivYy86/gIgbO/wYMU8L8kcihJyxKa6GtmH6hsUgtlo5Inrp5CzS4XHueN57ag6Rl89iym3fcXE2TfISIaNP38pQdj3P8VyzVDH4LuxZxb762/BPzQSdx9/GmuqiEnJwMXLF0tPN8Un84hLyZCB1H6h4dJM5J2MnZIdEeuZ4VvFAvMP8jh7BQQzPnU9Q7w+xjpEwR8U4SxcOI80y1RUCjX7SzfgpDdw/8fL8I/sR09LCaOif8ZqMrJ0XSCeERmyJ80/IobUCTPYvvFd+g8chZ+bgdeWnnTclP2VRIbPo7T2FSKSB+MaEIne3ZPO5nqcXTyoKMyV7O6M67ouCtwO0vTgdsSOW4A3ProqnMzldLXaUKjU5P76PXmqWFROdqJ1TZzp8mFt9iAGpOo5XNbMEaNGAjFx9H9r88XgoefgVy/gZ53DJx5pfB3jYLbllapyHLPeVUd75kBNJPaAIRiC41HqPaXM0DkgBptSI903zZ0tdFaewq5yMNAdJbk4B/Xj85JMqoLzcFGZ2dsaTrMhFb+oLup2fIM2oB/OAbFoAxOwmboJi3OcU3I7FA5pcuuer1B7RpM15eKQ2hj/RuqW3i23xZAwBX3K5ag8w7hj5A4evVF4NCpJiXHHK7mYJx9+i+ZWO/rooTz7axpvXpYt+wQLTE58WZHOmUMhqEQzZ6sK92I7+qJWBt7gUAr0uj6e3y7hDDnGxGKbjV8eWceQnAdQjPKR4eRO5Rr0tRaU3RbiovpRUVHxP7gD91Vf/RPq30zu2Ff/evXHDt3/22X9J1YfSOur8yUGw8Js5ev/x95fQEeVtdu/8K+8UpGquLuTIAkkuLs03jR0N9BudNPu7kobDU0r3ri7u7uGJCSEuHtSSek39ioS4D3n3v8Zt99v3HvezmRkJKSq9l5771WVNfd8njn/+EOETXfp0oW3335bBIKHRkhh4+eQyUx0Ntx2o/NT2Xh3xm5G6/+vvXdC1fa7FnR3Lmgk18dPbrZj0/fRpK2ag9zJCWvTAmryItHeuv32RMcbXP95BF+OSkOOlSk95HQZNYhpvRaInq1zp45TmBuPj9LRR3J8WzDBidcoLiogOak3atnlu8YjETRp/0EaM0t3pfDaIyYio+PY/ef78Oft58VMfgi93HHXXoK0Rkvu6caqpfN58Y0P8PTzFaWVkqomfa+plmy6ZSIDLDQiUhzkHys2M/urj1n113xRIvn0l714dmItNQ2FPDDuSyJj49EbDLd6AFXCsv/U8UOkp13h959mMe3dvrz5MFgtaTz+yHTMlt+JT+xIVWUFkdLC12QSAdYKhVIQuIcnDuXEkg8oPxknCJ+U2/bWJ9+R0r0Xvn6BQrU7enCvKK1MSunO4X0bKfvuea49eoUEt3J2ZEewoOsBcawSJNpdW2tD6+RMw5F1LCufwDxfBT4l9RzZ8jUTpz6B3t2L4Kh4lGqtIDFGswm1VJqo1aBVqeg9bCxxnVJYt+gXjp/cRLOliYOnojkfe4UOmmZBCpaWBTP7q95cP/MjYTHxXDy+k26Jh3FBxsHzKSSkDBLB1GXWOrQyRzllC6I7alk/fy69R4xj7GMz6TtmEl89N52xjog6AU+tnbqcr7li1RDbKUWUOcrVatGrZrfb6Nx/GDXVVeg9fQiMjEXt4ixiF+7EK28388gTwWQ176WnhyMcWYGd795RsHl3GJnXToiSxLjUPqSOmoTW1UBNeQlPJr+Ar8ahOsVMVvHD6d7UVlWRl3aBQdNm4uEfzJkda4ntrUElc5B9CW4qG/NfeYARL3yGq38E1SUFIsC6sbqS5oZ67GpXMpS+mO214oNcGk9msw6/3AMs3pCNTqXEbPuIz858ys3aSGEiUvTHUdZrRqB0NaOtt/N+xDHcXqzgncVVfHGzD53d86izatie3p52/mYO512meP5KsnrOoCIcPG69zetvBTrrbr03eoWb2PHaCka+k44p4RlByOxmEwo3X2xSb5l0KhUanEI6OVwmLSZ0we0FgbuwQ0Ne7z4oFVZqKp1RlSlpRzvKNSdoyDyBNrADyIwoXT3ILqwi0yQn6taNhPPNGoLGDCHrl3ns3B3IY6mOEkUJl01ORN87gZtbNlC99zuc4gaiDUlhxAR/bPZiQW6lz6JpycVM2w9Ljqh46N4FzD+h4kzFRBL6acird6fwhg8ueUo8ztfTdOY0Z6z7UeqcsK1vYupkP/HZ1kKUpe1JVHHjKqUog5Z6pxcs+BHVXy507f4CCrsSdWk9DeXZlNiKGTS4rW+6DW1oQxva8N/jn+pq2Yb/BpJBiFRWGh4QydNPPo/NYmP48OHMfOFlMjMzhDJis/3XKTPYrRLzrXDXfyVhLfhXgna4wZmF+WFMP9if5Y9YubTyG1Ba8PE2YLNb0cgcCoa4Wy6D8f0KxGRtuWvdJ6SA+PgO7Nm2mbiEBHyUUpml43FJNXvg47HCYbG8ooAdNbfD0CUL7Ttv6rm42snKuMZvS9cx+49lvPjmh3z63c/iMXVBEzfNt+9j1FhlHNpdTUx8InKFUpiYSBuTVC+7zbEdKaDY1c1Abs4NKirKqCwvo3PXHoKgTf70eb6fWkKsk5FULyP79wSy+Lc54rGTxw6K4GnJ3CQ8Mo75835g6KPPMfepQqK1RuJcmtm5wp+vPnxd9LNJOWhSD5bFYhVh0UqVUvRr/bX5EK+8/yVePv70HTyCz77/ne69+3P5/BnRe+Wkc6VTl+5CKXrqpbfEcWRs/JFzb1uYkXSKS1+Y+a0kghob1NhkzL4Rh9kMkx9+moqKEvaue4cz895k27pP6dFvKJMfmSGMQbavepXanMFcPTSaotxsPHz8sJrN1NVUExQWSURMO176bDa/bjmOs6sb+n1FPLRzIo9c68nY00P49YVkzi/9SLg2evoH8fz9C5jU7RoTu6XxypRFHN6xntMHdxEU1YWTxtv9qCUWOTcze5N56SyhCZ1wdfci/eJZmnRK6m2y1tBhMe+8OrJp/myyLp8TZLW+upLsK+dF6aFkNS/mR3WV6F1rbm7meONtMigpjL3jFIzureKZAevvUnOknqOirAwSew9m5pwVTHn7W7yDInAxeFFZchg/bVPr3PTRmfnrtWHcuHQKg28gFpmSLmMf4tFv/yJXFyPyt1qQbVYSEtudvX98JcZYkHaexsYGnNx90AdGUF9WyMZzoSyr8eGqScmBRmfevtiHZ2cX4HSrEUohszPE+3OqC7LxiOpAxYXD+KxrRrdbx6pe67k3NZ2hvcs5OMfCjZPBLLrQg9VnUjGdd0PdaEfj5onN1EzN5gYWVIZx1azgqknBN8Vx/FQRTpZJoqkOOKllPDXsBE1ledRknhGlnea6SiyNNdReP4VdoUUpeswkQxCjMAKZ1P4g8/us4wl5BnUXPVBe1eGWZ0PeZEPp5oPVWI2lrgxzdYFwbxyZWET4LYJ2rsmJr3O7IfP1pUfYo+xda2dOeThHjFo21uuZk5eCLdSdbj4j8Y6/F2P6PpRuHuwvjLr7s+nWtXmwp5na/CgKM8MIzzvEmnt3UrpSg+EYGC7Vw80CsjzyMFnqQSknz5TKW/P8OFmgYG2+J8sLAzhca+DJRbFsmb2L3r17i9Krt956C7OlnqOHPuP64YXUGU9iS6igpLREGGO1oQ3/X4TklPzv/GrDPw9yZP/Wr38i2pS0NgicPn2a1atXM+3Zh/jq9eN4K3Opssp46LNhrFq5DLPFTEZ6Oq5u7lwuV9De+/ZqUi2DL9I68EbcxVYF5k7cSdqqbTIO13ny6Y6BZLz2OzWmXaJ0UAo8fvrltzE2NvDS41M4Uaenu1uNeE2+Rc7RogB6xNS2EsFiswa/gACKivNRqjSUWS14KxyLNykUNzvd4OijOneS3z5/kx1T8/HRNVDVqOGLhNMiGLvBDn/saoend4kgdH0HDiUppRvOzq4s/OUnCq9s4tGVY3h+5CG0ciu/ropDQR7devXDTW8Q4dknDh+gZ79B+Pj7i/6wdSuW8MuPX1NfV4OHuxydawjevgF4evsQ2yu/1URAgo/awpEDe7BYrSR2SsEkuf5ZrSKwWlqU6/rZWlUBCTqZndqqm1xPTyO1Rx+hFJqamkXZpdQbdvr4YTGGDkld2L5hFVcu7MXPaxdbVjnRe9jrIvJCspuX1C5Pb1/KSov4/o8VbF6zjCP7dmJRmsi9so51n73Cr517oayC5k3rhXtm+6SujLlvOqePHuDyhTMMuWciQaERzP36Q/JKd3B6tZe49jJZHRtOfcGhnXV06TVAmPhL5YtWm41TB3djb8pgzpwALl/YwKmFQ8mx+FGZl8aVoq3CuXHYfQ9xvXE/obrb8ytED7uXf41veA8aCgt48cBU7ks+jV7RzNJTXZA1XBdh4JKCWVqUT3lhPm4aF34sSmSG/2WcZHYO1HtTcr4LRTf3EpLYSZh3eLKHoE43KDTFUl1egqnJSMbZ49RUVkiyMq+dGM6kxDPoFU085umwYZcun5MCbprkhKptDjOIBld69Luf45tX0GPcNGorSslPv4xveAx7D22ibgy4SDcXgCY7qPWJbJ3zCY//uApXbz+a6ms5tXUVV89c56OxnRnvnU6zTcnszK4EO2nJrjxIWU46fgkpIvuroaZKnJfym+ncPHyAb/wn4mWop7peh+mMHvkjUkmgVM7nGK/F2cq2Dx+m59OfYQiO4szR2SR1HkOIwWEWI+aWWkb4iV3kOY8Sb1ZdjhGbi4qm6lLcIztycfnPLB77Dof8ojBZFGTn+qHUWRiYWoJMdVtZ14a5c/3dbwkZ9hQB7rXEBtRx6ro7ZbIwUf4o5ZY15F1FG5TI8NCdvDdkK3a7mr5cwLWymaXHk7GkN1Dh64rpXA4u7QZjszSLmwoKjRufjVovFDxp3MlORvLzvFFVK9AYDAQo+zJ7kQnLva50cKnAUKdAWSfDrncmNN+HMrsNc1k2f2zqT1BkDskupXTSmFrv2ogbPArQae38/r6WoR0mofm5mqKMzZy1XhWRFNIFj+w2mNRBI3BRK/D0cGHRn2dYsmgBDQ0Nt7Yj48EHHxQGVhKkUnHp56eeeorMzEwK8m4Q4xTDpk2b6NChQ9tfoDa0oQ1taMN/izaS1oZWZyQpG23qjGt43bLblvp+3nmxlG5zi5g3Z7bIhpL6rbokl1OcHYv7rTval5p0LPvchQ93ZyK1Zn3zaywzR9haM8haiImktv1SGs3KR/24cO4T8bt7pz1ObHx7evYfTF72dWHC0WfgcEb2PsGLa3rh4dzIytOdOP/C74SfTKCbvlQQtLd3DuL40bmk9uzDwT07eGbbTF4beBCVzMbPV5M4tWw1/QYOxcVNz9I/P8dpjbMggM4ab678NJXk6AIunQhhz9vfMWTEGBrq62/JdLBn+yY++mYOj00ZTeGHc/hiXSeyr1+nsvwkr773mbDHlwigu4cnXbr1or6hDhc3NzGObz55h2nvTuHHJ8/gqrBTaZGT1OMszU1qDl2NoDHqoiCI0q6ymrSCXHh6+VJZUYa3rx8FuTfJyZYy5SDvig+l/eT4KB3nssisoLbWLnrgiosKqa2p4WZWJv2GjBSvkVwUz508xrefvk1kd1/yNkWLniqJSLz58+dcvWTg0oWzxLXviK2iTCw4b2ZnMf2pF3l4xiucPXmU2Z+/y75V7+F1wE+Yfji7uDLrj5X4B4SIYPDUXgNI7jlAELfi/Fz2bd/A3CM9UMsc/TkS+iWrmPrAh3j7BVBTU0NK74GCgO5aO4sTmzSOTLDB7uy6dJxhQxxuocFRccz4+AcWfPUurpP60WjbI85Ti4ql1AWLOIWS/Bt0XNXE2pM9cFc345shZ/vpHXQbOoa0cyeIS+4qXDer83LZuPJRdnWNQy6z0XjcHW/zRZxcXFEoVETIHqBPkMOKvqRhFd9sfp2A6ESiOnWjrtph/KJb1MzCbgOwO1kY8+B8fBWO1bxEtGam9aeffzYNVhWrT6UQIm8Qjo2SuYnBNwi/yHhK826QsfsKP5V2Y5JHtrjmi0piCfZL5vrF97l+9ihRXXoJy2iPgGCMS6+za/fj7IuMw1fRyFMel+FxG2fT5Pi6FjMy7jhllnh2X4qjOPMqbn7B1GdexXmdhrIwN6RqX5/zdawYEUO40xl85FJOnIw5Od1QO1dwZctCHnr3Md4Z+Ceu2kMY7TJcbl0z6Zj2HT6JvSaL+JBBGL1cuHxtLRqDN9H3vcHFX1/BuLKaqz3DxXtEmy9H2WRntZRlGXBFlEGWWWUsLOtBY+FC4qq+YsW7SqGCG/sreHjVTNJK3EQMgFN4iiBsI1JOtd7Akb7fN+ga9w+5xqHzLgyZdAOFszsu8f2EIqfy9cfaUI78XxwIwqgmK98dRV0zcpude5s280aolyhBHO5RwJsZFs7W+mAy3s4+M+Vf5IM5Y/AfWMo7CQcYZXA4eN55n1Yjg+B25WQNiiYSZzQlBq5VHKLT0ImEd+qBp05FlKcLHeNj8NVr6d6jJ5FhwdTV1ZGYmEhwcPBd4xwwYADp6elkZGSI6x0bG/vfBu62oQ3/n0FbT1ob/ibaetL+PtpI2j8YZWVlLFy4UNzdlX6WSryUwiL/NhQyG7HJbrz2SyoZRgNOeXBv93SaMVNqkXOhwY3XfxtO4d6fxPNtdjmvP53DsUd9GfJwDD6qJkb6lYjHpJDoi9mBXDr3h/h/cteeohwwLyebhro6QVjqamto174jRw/sZtnDm8ViKzNrh3j+U32uEj14Om4oubh3gXDle3zGS2Ib22b+SvOgKaIc8/ixtaLscPL0xwkICmH0hMns2rqB3Js32L9zGwee/J7DSqXo5xo8YgzvfDKLpqam1t6yQSNGU15Wyu9/bWDz+pXk5+aIXLQxE+8nNDyKmpoq0QsnlThK9vzeej8O7d/N0vnzSE7uxcyH0gQ5aul/+3lZNPf0uoR6XQ2P+/fn8XbnqDJpeeXBYmEgUl5aQnV1pVDDXFxduffBR1i7fCGeZzJ5cNc9PN/9CFabnC8/dMEvoJ6wiGgxVmkPyd168czUcZw8up93vgwRPVLNxmJmfhSLi9xxZ1/CC48ZGDzqOz6Y9YtQLvUGD1E22TFFLvLNpP936NyVpduPsXXNX8JV0i8giGFj76O+voYrF87QsXM33EVoeDE1VZVcvSSRTyNXG6RF8S0TBUEm1WCtoyDrMAm9JtPYZGTOR68y7asYnOS3M716JchFueXzn88Vhh0GLx9RHulyUcf3RXE86JMptvdzTnt8gipobmokWco4M/3M/vf8hMqYXwM9h7gw9P4n0OichClI8oARbFk0D9XBfRjO9cJituDnVMH2o2vpNmwsS2a9x7N/OQiaBF9nG9f2voix+WvC23XCyz+YuJSenD40l6Ty4VTlVvBerxSeCboggrsXFcVTsCSIX9pFIG+S4XncSEHdVVwMnrh5+gqlS6FSiblrKatk8e7ebI5NEHOz+ooHkfUNdO2soXfYHurUcVh07fCPlXLUXNBtvoBreDwbvtqITlKG20HHzmGE+y+4pSDtx1vdk7/UD4uwakNgOGn7fiY17kHk9RZulB4n/2B3GpUaArU1XKv2Ie1sBInR93D86M+8OawRg1IqJZYhFY1eN8mxIGNDVQQRfR/g7MoPOJ6xEDLAENmJmPHPonb1wD91JNfXz6VX9TvYnLWoKxtpTrvG9g6J1KPFR1PHtVpfrmaH0TliOh+9vaeV9GgVVpZP+Y5dV/x5cfMTyNVaLHWVpJs09JU+Y+4wAZHQu1M9Dz8WyJaKZwWZcywWpc8lOSeNTnSTMswkJ0uzgiy5AZcrlTTcSCfHvJv7FwUIwtfSbzbmnrMceTuIa007xeyUqbSofaNR27WU/HYFr/fM2AxSLIZc/DFsMc25alJT3OCGTQM2NycCzfGCpCkVCqI8nIj3c0Mul5xvc5j+4JT/0eetdM4lctaGNvxvwP9Wd8c2/H8Hslv//l3b+ieijaT9wyDlzS1ZskTkyUmKjAQnJydhGiJZk8/60YtOb1XjprCLssFfV+g4v9kXtewmNvtNZLfaOVrufg9yq2b1zFV8Pvgezr5o53zaIlEGuPLnXPFVcTOmdd9aOczuth/3Hydxcv5apk7N5dzlKhb/toltG1by6fe/ijFsWLWU9TuiGBLrcFXcV+bBiJTzaJy0nFv/kzDJGDB0JPeMvw+/gEC+mv07fy38jQN7touSN8kJUQqRnjPrM4aNGkevAUOY/sRzInD6pTc/Eplpkr19bHwiHZJThCOj1OsjlQ9KqK+vRaVSCXI2/cnnhAmGZE4Sl9BBEBxXvV4YRGRlXhOKktFYhH9AkNh+57ghyGQZd51zjatWRAZs3/kr4dmxZHn5cPH8Kdz07jz+yauYLSbxWoO7Fy5uBtybTbz63hd89s5L+F0N5n3fIG7ezBBj/OS7X0WppUTsJHz2zoui/PDc9Y601znKzh4eG8OKsttBnhLqbAquZ1wVGWbSmMvLikV5oZTD5uHlTXlJETeyMgmPjqP34FFkXD6H3t1TkDCNWusIjraYaSot5vzJI0TFJ2K1ORTX3esTWPRIKf3diqm0qDiS5k/V9SYUsp2cz9/JD0vu5cyRfSTbHsBqv9m6GJfy4qSP3ZrKMlIHDBfnNjA8ihsHVrPS62mWdUjBZpTjt8XK9cvf07nvYLQ6F374rBDtrXK+QDd47R0Np04cJKnfUCpKCvELDueJT2bz27szsVr3oHHSYayvI65LT5L7DeOXn96kweaM6o5S0lVzfbhR8jVzNt+Pd0R3pr4zi43zvuLkznWiBFW56lOOdo4WfyoU57XYt+1AtVVOWEQSDYZyLpzcRt/JjwulyJS3Dd+wCJqDY9DoXHDdlI7pSjvschkBaTX0nXiCV6aEIJPdxGx7jY/2vAqyCLpNfJyDi75jeu+OON9STyVE+ivucnDs4HOM5/+qJ/XBl4kbdB/X9qxkz6EvWh93+j6HY5qZ2JytyGsUeF6yYa6tQSaXCJMj0LwFq8vi2F8Vws1cH9zNCgLbD6CyOIMOj3yCUqND7uKBrbkJtZu7IGsnTs4mPHY4TaV55FUeRvtVOI1vP4pCZ8FcrcYlR4mrSYvNWZp/t0oub419cEIRnQ4f40xVbxpzL7HsShf89RXEaOoIUNi403uoXR8VC1/4HZe4voLIqwPaC2XtvfODGR93Bo3MwuHqCCpr3VCF2CjLKsNibSC70ZVkWV2rUVGBTUPNjO6E/VpOtv06Vfvn4T/hU1S+ITwxsZgeEVVifP5KG1eaNayt9MMmt7O5JI7SG14YSu3Ia4xY3B3GLwmR4UR5u6CUWTlw8Ajnz51l/ZqVjB49WvT03hmg24Y2tKENbWjD30EbSfsHQLJ5lkKpDx8+3Pq76NARWLXNLN9SQbxTA4VmNcMmNLF57lZClrnRd3p3dv5xgL1brajEve7b5UB3miZICFdZmNvhKJ8tjCPppwf47tNTOCvsXDTqKGm2o1c5XBcleMjtfDnhNLqJIWLhaRtvJnHSKL6ZcopvPnqTma9/QENtLkNiI1tf08+rkoHPTGfP3IUcPJ8lFASJ2Pj4BYjcq4CgUGF1P+2xZ/nhqw/Zsm4Fs36JIzxMwQevvczRQ6N49f3PKCstJjAkhP5Dh1NXU8OVi+cwGhsFqZTI4ZkTR+jctSeurgYRztytdz/R7+XmZhDuiMbGRqE6SURHKvssLMgTvV2+/gHCel5Swg6f3Milmp4kaBtFj1aVTcZLzxXTo89wDO6eXDx3ihvX03H38OL+h58irl17YfihUmkFWZLCrc8cP0yfgcOEardq6Z8ixLv3wKHcN/0JfP2DBLluaKjj2KF97Nm6gZ7vvUW804rb51hl49S5MJINpSRqG0TJqcxq5/1PvZnz9QfMeNWROZiTlSG23a5Dssgik1i31AsnhcAbTSacbXasyNB7eNMsBSIbPKgoLSamU4owK3Hx9MXN4IHi4AHm1AxiVqgcdZqRfV8vbyVinYLAWDxXhD6f3B7DwoA8xhsKxePrMyJRqnMoK8pHq3Om2Wym++BRnN6/A/d964i/MoD62goya46IsPKEngP47d3nkX95e25Ic9A7MZTVL30lstLikmIYEvAEj0xt4sVREbw8qxsmi5MogUzuP5z0sycwlTbwU0lnnvC5hrMcXAR5gTh/uLf/XyzYpadjnyEMnPwYEYmdWf/zl5j2bsH/4kARLeBaU86u2qOYzU1crdwtVLPUUfcxYNpMBgW8S9fejuiJcyUBnJn0OHsWfEd0dW+CfBIoNl1nwljHzQAJUilwO5ev+eibcAY99ykeobEUKldgtDWKslBuzSH3W8qsCD63abh+eDP15UV0f+IDgroPp+L6RUz11Si0Lhz8/kXcNxag9PBF0WhCm1PBBetVnH1CON3kTB8puPxW7MXK4x1pqHFFVyDDObtcZKkpVBq0ei8qM8/iGpEkQqldI7sSOzWcwkMryTy/ErvVjHNQHI152WhXliCLC8apCVxvNIv3wV+lETwdeA1/hUMha+19M2+hcMtpfPo/QtFZGV979cfPtY57fS4yXl+GRHFKLHBAk4q9ZiflO75FnzwOTUAC2Kxc39Oen5tcUTpZaKzVIi9UYpdbCVZHc0OTy4tv2/BbrCNIZeSG2YnlxR0weSjxTxmOd1YJx0oWUn95K2q9F2ERjigACdLZdVFYmJfWHcUuZ9GT6F5RgyKjkCZ3I2eubCEgLJKkhFjk2Pjiy6/IKsjis9V9xefHoyMfY9GiRWzbtk3kdrahDf/r0Vbu2Ia/ibZyx7+PNpL2H45z587RuXNn0QfhpPFkzZloEt1q2F3cjEZlp7OzoyQuUm1i9TItnWNAp3Hm4J/HkZkhIVSJ7FatQot69q/ujcLhzg6P+mUg+1CFi8LhzNhJ18hfFX7Im21Eax2qmATdv/R/jIq4zpGUh9i45XMO7d2B2SIXpZEtC31JrzEHu4mepGtXLopyu+59+gu1SyIsElmSDDOOH97P5rUrOHAllV4eVdjtVoZvDSau9wZ2b+3O5OmPCQXK2cUFmUHGiLH3UlxYIMhRcUE+I8Y4/i9tV3JalFQ6ycGxsqIcV4OB5mYT58+coGdfySgkgA6yVAxStllBHts2rBbOhG9uGMeDvpccf9/scCTLiatHsihN3ySI4JG0ZLq41tBgkzP+4e84crAd8YmdBPmT9ildpw7JqaI0Kr59J1774CvRqyaVgR7et1NkqIWERxIQEo6PX7pYEDda1dTZZKKHsOV87X13OecGP89bLx/kXp9C3HQm3njAiXcbDnDs8D5GjJssCFhIRIwgn95evviHGPnzxy/Que/hk1el823jg0919Bv9BToXF2x2G+6+/sIgobqqUpz7Fz/+nk9efASX7AtClTP5eWH7l1Ac39gwNNp0atavwX+aC/pb43wu4RoHR6qobainorwUg5cvYe278Nh7s4QL44bLDnUoKDKOmd/Op7qsWJC1+UVxvBF8SZhxFFnk/LmlO8b6g8KhsVPo+wTrHG6K4e4Wpo49yOp9D9Kuez9heiPlp1lra1ixvidbk9rxWeJe+rlUt87nwGANiz99BZ3rb8R27onWzQM3H3/+ePtpbl4/h194DIXX00RQdZ9xjxIY0178rr6qnObaUlI7OgiahCTfQoouZBHfczDl+TlkXT2Oq4cPtTIprNnS+j5qDAgj4+hOfKLa027gONYunM/8CcEMdi3AbJfza1F7hnpl0V5bS41VxUcZ3eia0p8jh3+gpjAHn/gU/Nqlknt6r3B9DOs5klOHfyQwsS+uzr4UNp6hrugGYf0m8k2WFxmBl3CWW9haFoPtmhOB5+tRVjZidJdRdvUsQf2mIHPS4xaR7FDbzU3iDesa0o7we54lePAjqAx+YoLfWPsNV/bOpUvVc7jWyjA11JDmlkfejhAqh7kyzvMK/XSNqOxwwyznSsBY6rN/oqkkC+/+j1Cy2kRpcjhF/noK4s7goWjkQn0QV4qCSUl6iIzi85Se34hr0hgas46i9ouj8PNd+I8ch8YKTiV2tCWNWNUa7MZmqstceG7HCIJiC6g3aygo8EJdKwOVAl11A7rABJqKr+PsrGHxid6Mjr8geh+l98yRBk9MZiU6uRKvU+VcSF9OKY4cs8h2HRg3+WG0aiUHD+wl7epVsnPiCVFni8dHZCWSHH2I3377jeeee+7f9vndhja0oQ1t+OeijaT9h2Ps2LFgl9Gv8+t8tXwHnV0qHNlAQbnkNCtbF4rSV0cXEz/v6cbTA48TFBSGi9xAcU0Drp63SdnuWgNOzVZcnawkODdKTtStkOy+VbdMR1qgUtiY9vAQNizaho/KUV5ZbpXhI7E6qctEJpW9aTDJVYKgSISkvt7C8tJgJvrkiedsqvZBdsQqjCs8PL0JCYsUDowSoTp74ihDRo2jtraKLetWktylOx0NDuMHacySmvXCt91Z/NlaYRAiOSMqlUoiomIpLykRpY1nNx4ltUdfUU7o6uZG3s0bODm7UFpSgsVm49ypo6J3TFLMunTrI0wwJNIkwWR2lHRtWb+Srj360Tu2sNUFUDq3HUPN6PXuVJSX8cm+kXR1uyqe7yq3seg3f6Y+voBXP/iSi2dOkNqzH8f27xG2/CVF+QSHRdAhuSsPPjZDlDhKhGzzuuWi327kuPsIDo8SfXx+56p5LzOFlyPPosbOgrR48ooyyVv0CYkfJbbmOAkzhXG+vPH8etEPKJMr0bm4oVZryc5MY/mCeZy7vovrm11QSQlpOvjtqwbiezzFw8+9TofUnlSWlVBSVkbxzWwSkrsSk5jE1JlvkZNxlTOH92CwurKs0peHvXJQ2+FysxOZZ5NRaXK4kX2e9h7xrddGOj/3zwjjlafPoVSqxfikPrnuQ8cQ1aEztZUVuHl6iXLD2upK1Bon8dpzu6NJuy8XtdzMhyf7ojzomEtHt6zmqQfuJoiBMQZWjf2Ej/sMEZlx7XsNZO3cL3HZcwrlyQ6seyOGbjEnxUJdKjDcWBqKi6GEs/u2Et+9H2ZTE37h0by+eBeH1y6ivqqC6M496TZ2KjabHRd3L+oqSqitreHyhd2YeyMIiQRpe7rwCC5tP8a0b1eKsssT6xbw3Q0770adwENhJcvkxC/nuxGTDJd2rsQzNJryvSeYc/Rj1oRUYjSrqLjmwZHwKPw8aqhq1FFx1ovwpjqxj9xTe3HxDUGuUOERnSRCplf/bKa9ZxTZhQUMve8ycoUXXZ74lNIrx8ncamB2twHixouxUId3oZ3rl9ZRWHMJyfXH2S8cv9SRGCuKULp6o1DZaCovoLE0B5eQRLHPhoIMdFLZp9YZ395TaCzL49Tpb1G5emJpqsdeaKJuUXv2eE/hWpg3F4Ov4iQ3c7wqnMoGf1L87uVs5WZqLuykOP8yyWVvY/b0YL6pN2qdicZ6DeRpQWMmwhRMqc1KY+YRnMI7o1QqwCWUrB8+oXPSszhVN2MuryDDuxp5ZhnunZ6nMbMdlw7n4xTrj7PRxo/DNpP6bCEFtWoG3ltGYbOVjN+eJdtZz6DCZB5+soICizPb8hKw5urQVFuhrhHXuBCqcyqY+OwbBHr74O2sobaqnB3btjL8ub6EqG8roglaI0PuGSMccttIWhv+E9DWk9aGvz2H/o3W+bK2nrQ2/KehqKiI3Nxc4r2HIHPXE6erv8tNzf1WtlgLpJ8fi6/A60wvfNyMrCqO4Z3ffZj9wnYMGhtnG1x54fVIrm1YIUw7QgItnN4fJkobJfq1uTqIojMevD3kgiiQLLHIWJbTnurrZ4ntnM3cXd2xK+38fi6Jd1OOkeBcRYFFywfH+1NfeICwyGhGT7yf3Vs38NLgq8x7czoKA2j2wv4NsxxEyS+AJX/+zKVzZ8SYe/QdQElxoSBekuKFWbLnV+GidpAnab18Lc8Xk+mGsMEPt1hE87/e4E5TcxNudneSU3sKNa2psYGiwnzSr16mU5duwjhDckzs2WegIGVqtQaVWoWzixvXLl/g6KG99B4whNCwSEGipL0drghikFuFwy1OBhcq3bFaC2nXIQlPt9tW5RK0ChvnzxwX5iYi4+zPufwxZxbf7xjC44nNyGV1zPprM+tXuHH62EEunT/G6oPJhBma+e3XZZRWjGXg8DHs2f0zg+0zuN//AfRGGye3/oDO2Zmw0ETO1muJ8yh0XHfgcJofxUV5opxz/Yo/CQwOIyahI5VVlezetJoHl09ELTvWOkZJFS0tvMHli2ewG+cTFdHI+WOxyFXOeOnWUFAWR0LKMPyDQ3l0+iXiI8rYkdaJcc7x6BQmbm4KpCJtqSiZrK+pJr3JhSDXaociK0U/lMVz89pyGmqruXLuBLGdu9FcWSayzGKTuyGXySgrLRFB2TGdu6Fz1fPX9HWiZ1J6/aLe2wl9phKDtx/XTh9lRck44kPPi1JByRVywdUOKFRXOLJxOYGRcYTGd2DKKx+x5PM3kMnXUxnzOi9PttPTPZ8LtT7sXJZEcEwjVSUFlOXdIDf9MuEdu4qbEUExifiERKD3DUaj0+HRvFnsJ89jGHaZnJ1/fs2GqT6McHO4Be5r8ECuG4TVepJLu9eSMnoadWVFHF0Vz+OjR2LQNpBb7ontnAt6mTcZxbtwD41D5+6N+q9CyjpHioWST5YJ00kt1+PcUTSDd5oZq9pxw8MtIJRmswVnF09k5gqmpK4myfuGeCw6EJYsb8cHO1/EJpOjLcknc+53dKr5ALOrHM8KGy6XS6i1VwmC5tdlCMEDp6FQa6i+fg6dfzQqV3cULh7olBpQalFodLiEdcAqSd0KJxRaMzGP/kDVpT00Fmag99DxwTNG3CyZ/LJsH9k5g5nfyQOl2kpjpRZdkQI3QxAehj5UF5xG334wZ7d/SlDgQNzS/WkelCjFJeJcbEdTYcTYVCuORenshlLrjNLZHde4PhhzznDs2Cco3XxR2BvY+rmBfqnRVJv+Ytqf4zh+ppHiNR/zxYc96BVbcEtZbWbDFh/GvtIZ28US6kxFHJ+ziqvbOqGNdME7SINPaTO6/EpqAwvIPnOclP7DCfX1Ezc5ju7bwYa1K8XNpFNbrFjecL9VCO6YayqbSvT2tqEN/xFoK3dsw99EW7nj30ebkvYfjJYFg9rmuMwVFhU6lbmVqKU1utLN1XFH/k6yNj6gRDwnOeI0T47uzcheiZwrWCMek8vP063PAN7+9DuaTWaiU+6h4whnTNFdyF5TQf7ZdSzr7s3H38Vgk8mo+yWfjPz9juygTvtxddPTUH+YQTYr8WOm4usRQcmJTVxLO8fH384T7PGBR5/hy/df4+hLXzrGJpczePhoJk97jEkj+hIaVsa3P4bSYIRJ97zB1YvnmfLwE1RVVlBWkk9tcxJmlUnYFiwsiGTha1sYd99UYVvv4+dPbU0VB/buEKTQw9NLjE1SuqS+soDgMFz17sIAoKa6UjgDevn4CsVp5+Z1JHbqzJI/57Hk9zlgr+PA1i+xKeLp2nMAC3+bjfqHN/jqlWYGeeaTXuvO4z2OERkTR2lRAYtP9uee4bnCUl/6+/fX1TBcXc2iL04qH1z062z6v/kiT7Xf3PrGfP1+LQEdfqC2XsaeK13o6eJQ8H54Vc/4GSsYOeFPoaZt2fCtUNokdErpIcxBzh4/xDd/PUfT5AO0d67kQFEwXz51lLgOScy4fxRLNnrS3tfMyStW/lqTIAjpxexgypKlnDyHHJTVrMZmUzB++mkeTKgXv7t/wAVBQqR+Kqv9OmOfXMyTbwUzMtSx/6SAc9R/E8KZwx1RKY6Sm3WNAeMfoOBGJm/sH857fXcRom5gd0Uwp39xWJWXlhYTEpsgSh4rSkto33MgZrNJlJj6h0fTWFuNvSmHOX/4or81NtktEuniWo0+qA/VR/eyfV0SRSOdSdIXc6g4jLLf/ISCJc1n/8g4ocoldOvHIx/9yMpvPyBv/i8ctb/GPt9OaEoh6Fg1BzPP06nfcJxc9IKguXn6iOy0oPhOwsFRwlD/p+no4VB6s6oX8sHRJynNyuDj/a+xIeGGWNSfzQzDs8CKR0AYNWXFKF30+EQncvi32bjZPqbUU46mWnKHLCefUlw8/cTdwiEPjifFfRVmSzuO7+5OQc4ZrpTtp0PAKLw8YzFZqjlTtw9nrwD8O/ZFrfemoaqExvJCvA2X7ypH7uBfzL36l1hZ8hZe7bpxfcvv3DywgvaGgdjqGshzq6TuegFhg6fikdgfhc6A0skF1/BOIuPObpdjNzeh0vuKYGprUwMKJynGQENTeT7mugrUHuAanoRMrmD1+3tJ9CwX+x7S5QYpg5ahyh+PMcQZ50boYi/ivUU7UTqZeP1LJ046T0KS//LOb4dcC17X42kXORZVvRVrRS039YXIFCqcfMKwmZuQmWqhqRKvQc9CYzl1mUd5dEIz/VKLxD71KjMbnlxJ8+PwxlxXtE7nJd1aPCbNGr3ChOd9gci17Yjdn0NeaiLpJ5fgER5PzubfaShzqGOSiU371N70GDgchUxGef4N1q9ZwYx5I3l7RJaIAthW5kV3j3JxnuYc7cKuXWt48803/+2f421oQxva0IZ/JtpI2n8wQkJChAlEesV+epS2Z9pT41k8by2eSjPZRh0TpwdwfkU63rcMyVrUDQnSIk8ng57eOdzwaI9TsZ7Y4I5Y3Zo4fnAPj903QrgehkRE49IUyfk/j6GWK0ju2psPX89hWFCR2N6IOTCpx0tcnbNB9DRJZXoqpZKyshLRY5VbtY6YuER++GM5Xt6+7Nyynp++/oit+6LpGtxEmVnFiHElZFy7wsY1y7HZK9ix1AclRrFIP3MyhqDQpYRHxVBcmM+Kk73p7FYsjkEqO4uwlGBqNonHc3OyBCGTSiY7JKWK0kqJnJWVFJKdeY1uvfuLkkpJNdO7ewhzkaMH9oosNGnR1imlG1vXrWTed5/z1rIJvNf3IioZlJuMdOu/VJRhntjwNaqK4RxQxXDo4GbR1zZoxBh+/OIDUjfUMqb+XvolZ5CX4cuqZ+bx1EtvCfOOjSsWC1Iij5W1WpKL6yAdh8pCp/7TiXRyGL+0PCZdv11bD9BvyGiGj50i7OudJRJcWyOuy6E9WzGtX8eGc6PYrFaReX0jDQ21nD95mOUnkhjoXSa2M7KTjKJJFzi4Q4VuayXTw4bxVPxpmqxK5nyfis12haGxja2Lf+mYW0LFpaG896kfPgZHz2GLStttfAWfz/oWF7079z37Bh179mPfur9wWpzP2xnjsDrZcT/VREPNPjz9AgkIj8bF3YOS/FycnF2x2uxcPn5QKF/SNbt4YC1zXliH861+tpb910imGm79yDx/nMCoeBo3b+Ra0RgueCTgcqOZYK2JI9WV+IdF4RMYLMiWs7sXoe068e730xiauAmzZQE/fNCFuqYALhr30NRQT2LvISidnDE31FFRUiRcJZ31HiKo2mZtpoO7g6BJiDQYubzlNZQaJ+yL0zjfKxm7Elxy7LhWlFNdkk9QYgqN1RVEdR/MiVW/UrhjAR18R6KWO1HuWUrmvj10nfwsNGSx9I39aGTuyGRFrE5Yyn0P5ItyxvMF61GWO2FpNqI1eNHrmS9EyHNTbYX4brNa2FHhRxfXctGvxy0S+/gEJaGnPuWz058TNnAKJSfWceDGGcc5lMnw7TIUn9RxqF0NmI11mBtrBeFS6/Q0S+SvOButn8PWtfbGRXTBCcgUSoctvlIjXBftFhPOwQnEeK5snZ8qBaQOK+aP79+hffgEvF2j+HbDZlw1DjK/4AsVvb83Yo7rjb7jcOqzTlF+5C+OXJqDLrAdzeZ8TBn5ePd/ArvFjJObJ3KdAWRh4nMNmR9Owe0J7ijZ6ztIWsu+NXL4bIaOhzd25SH7CaF4SoXYp4zuNNsUyD3l2AO88CuzkalUITM1kjL5WWxVRWjtRqEwe3l4oFUoBEk7fnCX2O7XozOEuYm0n5HepUT2t1OdUw6ajeLz9tlnn/03f4q3oQ3/76Ct3LENf3sO3Wql+XdA9s904G8jaf/JkBa3jz/+OPPmzePkxXmEXopjVKgr2VylEUlBu4BfKJxOSyDazcTpci29vZvuuhPfy6WMCVu3U2IJ5v20eEp/8EV79RxVZWUM6DeOa1lnOXXkAP5BIRTl5woyMyDZ4b4nbUNaLI4cchnD/oms2PqlKM/z8PAUpYfNb33MgV1biW/fURA0ye5dclh8/6c4+oQ6VJtAtYllqwPpFH1JmH488eNw1LKzrcco9bmFhEUIcie5LgZ7NNwu6ZRMJ3ztwpSjW+8BwuRDsuiXFLfFv//EoX27uJ5+Fb27gSEjxtOjz0AK83O5eukc7ZNSkCsUYmzSMUlqWklxEetWLqZn77E83vNq65vHS23jxXdduH5tssia27NtIxazifGTpzN28lTKSkp47LnX+H32VzgfcCXLSUdFWQmdu/Vi0Mhx6FxciUnsKLZVd9KDk72d6aZzGLqcrXehsMhCbCc915pc8XepaSXTO3bKqC4vx+DpzZmj+4Vy6hcUwsBhY4Thw9tf/czCOd+wZdvHYluhETF07zeEo/t2Eup6R+mrpH6luKPSlHPkwJ+MVD/Pj/IRGKwWzh38FrlGS7lVhZei+a4eRnGNpYW73IVyo51Qt8rWsR3Lk/KgzjPzi7mojevoHHCQl95sz6zP/qRT8wBCfKJJu3GcmxkXGTZ9higXrK+pIevSWWKTu4PcQlB0Aq4e3pibm3AP2SsIRwukn8426fj6SneCPDRcurybfhOm89dXbxJibiQ+qhcVNXmsPbOT6KSuokStvroKT6dsQq0fYfRtx4jukmIpHYGFWfNO4BOagWdAMJNe/ZTA6HZYTSaqiwuoqawkMCaBZmMj2edP0NxUT1NvaPHwkxb/ASOmcPHD37l2fBnzH71OaicLp04F8N7FCmwWM+2HTKAg7Rze4fGMe/83Nn/1ArtPfuM4h3IF7YdNIa7fWJL8f0Mrv22/P6qfE86e/kT3Hy96zxqrSoQ1fliPkdQWZlOWcQ6fpP5YpNLdkHas3X4WzbhYRhly6OJ026yna7Kac0+/w9rlEQyM8qbJ6ssTc7twXT4GpZOOxjJJsZIL4lWVcRpdQAwKi6S621A4G4TCJoVKS26PUsyAVHZotlrRunpjbazFZmkWaluBRUGEyirmgbT3mm5DgflcurEGld4HZ42+de5INyNClHM5vaEA945D8eo2EX10KlVnt0DtTbr396NMNZw6n0FoJAJZW46loUpEAUj7bMg5i3NIe/462ZMHU/bjecf8kCCpmU6JSiatvoeJg05TYnFia1E7jCXO6KXKY6sNm90knEc1ShkuOh3ObuG4OykxaFQoZXKUchnOGqXof3X21rcStJbtvzovguf6X+f1F17nlVdewd3d/W9/brehDW1oQxvaIKFNSfsPx5w5c6irq2Pp0qVcsZ9o/b23tzevvPYmO7ZvY0TfiyIzq137OFJ+uYaupdECSJR8tSUiomjmnfjDVH1toL9XmNT6xcKycn778gGG9v+JSU/oOV8xkmVvqikzXSNAY2ldwOYY3aitdfSWyBVyTh8/JAiKZFUtGVhIiz+tk06U20nuiU9/JplLOEiaBDeVSfR0Xbt8ketpfjQMcah8EgosSpx0WlGqKBlDrM6NITnujDAMkZZs6zIjkcsvivDnhvo6oZ6tW7GE+fN+4MMlg3ltgFm8CTZePMZzj07my5/mi7voLi6uKJQqQdA0ao1wcLRYLeTeyCIwbBgW+91ZaEo3N/Lzcnj21fcZP2U6Z08eYcDQMShVKmFdn9AhmV79hrBnx0Zh2S0FQ4tyPVc9rm4GklK6C1t764mdzPhlHL2GZmA3ytn1ahoarRNFOft4be1oXrtnL6GaejZejmPp3GWMm9KN56eP4aeN7RgZ20BRFTz11Dz6Dn+MTqk9+fr3lVy7coEl876lc79SZjycTVZmEHsrAkgIyHKodtJi2cXIL3948/ZbCjZs/VqQGgkubno83D14/Xw/vuy0D3eFhWN1nrTTVROkMovoho++T6Y+0Zv6oXuI0NSxqyyUSwsixOtrir/mhycdJbWDJOdQlyB++u4qGWlnCIqM5cmPf0Tj4iaMWiT3zk59htJQWyWIgF9YJBVF+ZzZuwVTu1As9upWlVEac7S6idK53jTZLuGsdyeyUxee+34RG3+dxa7dv+Fi8KDX6PvoN/EhEcJtrzvIw+1n3drG9buun7vKLvK4JMv97iMnUlFcJNQir6BwnD18BVmU+tSCEjqz4ft3mT81jMleOWIcO2r9KC4OxyMgnE8/VPHA8GqxzZgxGaSVNLL7woO4+4ei03ug0ulRaLTc98VSKvNzqKsoxmpqJrzrIDR6TwrUrq0ZXxI0Mhg+zJO1K35l8Fu/YQiJEuRRUrzU7n54eAZhrCyV6vOQO+nJnvUXy4PeoqG9lo5hF8Tcls5XttmJIT2LGBSd09oPOeuJMwz5MgVn3zCaq8tw8g1HrtLgHNpeEBeFswfW2jKc/KIx1TpKGFVu3shMTRiLMlHrfbE1N1KfewmNRyDIFHx+owtPh5zDSW5lX10Al6oj6JX0Gjerf+fwRlcUd9wNLbVCaafB+ARfo+jYSkzVRejj+xI6YCKbn/pB3JCw2ffz8X41q0/3wVKVh6mpCbk8Bq2bO4qIjshlNowmDVO2z2BU6kaG6wuJVlvEe/98k4a8RgNFFQH8/uoQqiPMWAw69EVy3LIasReXkqe/LuZ6SFwH9Gobeo0Sg1aNWi5HpZCjECRNgaubK8UZRZjtPqjvOIbKWsef0E8//dSh7rWhDf8paOtJa8PfRFuY9d9HG0n7D4dEMqTw6lmzZnHixAkMBgM9e/YkJ7+Yw4cO8sDU6ZitdpotNiwWK7+tms/MycVikVhpdeQztagtfkozSd6lraWEkzxvUv+cjhfDDNjtTfQNzsCwOJgnX0hg1vfpuCjM7KnzZe+WjlTmLSC1Z19CQiMw6CUzDYsgJ81NJfgGBHPzRibVleU46ZxZuTOModOKRIaVpClsrgimoiwN/8Agjs5fzsyeI3k88RxNNgXfbO1P+tWvefm9z/juk3e49K0Lz8zoSd+gHI7khrJm+ja69eqPUnGrL6+8jD/nfEuXfmN4sf9VQeak4xvb0cKXivNcPn+a/kNHUVVeJoxF3D29KC0tYcWCX8XKWVInC7PWUdgUQICyRtxZzzapeWnaJYaMSMDZ2YUmpZKe/YdSXlYi3AqlPjzJ5r6+oZ6uPfuR0rOfWNCVSmV0Wq0o0ywtKuT5tz7h0zdnoko/h213PBlpl0QZ28PPvMyvP3xOuyUqVu7rj0XWwP5jSwWZ3LZ+Oa+uG8pDCVfE8Xl7w2+/yXh65i66DRgucsy2rFpC1D1K/nhagwwzXbwVnKko5/2bHZnqn0asxoSPysoDfZVUvGZm+64HiOmQTENdLW4Gd75/53msf+qZ1OlBYZfpeqCe2sHOaLyasJ9Tk73gO5x0nnxx+WGsLnK8zzdws3ij6OO7d4pjRSudY4l8TJnszidvX2HyC+/QddhYtM3bGJYwD5ndxufzXIlN6kVS4GEuXPMko3AaNeWl5KZfofy6kl96hfG0t4MYSdvTK2z8OmslZVVWPv4mnpzL52jXtQ9TXvlYhFpHtOvEjSvnKcvPIcT9IA+kLBV9dC2Q8uNa/p9jVtI9ZQrH9y5j0NSnMTY0UF9TSWB0guiHK8q+RkSnbjQ2NNA/tZAnfByvPVmv54N9Q/HJtODpH0LPvhXYkUxfHCWZoyb78Pn7fwjCnzTqfpRqjTBByT1/lIDEVAI7dKexqgyb3Y7Z2MCW3RZeSgBPqZrv1tgefNadNctsnF89h6T7nscuVyLXumBprEPlLClTMoouHEQf3gGtszuqv26yd2QHlhhKSNWVU2VV8+X1ngy6VyJoma3Hr1HZuDTvBfRRycRN+xhzfTWotCh1bshkCprK85CrtZgbqrAa62iqKEAXLAerVfSjqT2CUWrVOAfGCRVO6eLJ7lV+ZI4YhpPaREGFO/ZCrcg0WzQrggBPRz+ldF6um5XMK02gsNKLKP9uOOv8uH52Pt5d7mFs5wv4uziUZOkUzOi9m89nrMZmbMQ5pB1OLjqsaiUaZzfMjdUiGLtC04XfbkxijmcJ9/c6jVZj4lhlGHm5PjjVgbIZ/BffZE/dEhHNYQiKprmhHGNhJQkDxuDr7YG3To1GoRAljpKCplUr0KkV4vuAgYPIzMjgmzPRvNYlU1z79CY1H47dQVJSUhtBa0Mb2tCGNvzb0UbS/iHw9fVl9OjRrf+PCAmgJdq6vqGRDetWc/LoIaFGvf+uDFdXOf6+So5vC2l1MLtq1OPv6lAJJEgL0b5eBa0W79LiK8WthG9jBtMufDUuYTG4yGupLflSLGLe+GQW1VUVIoTa3NzM+dPH8fUPpLS4SPSNaTROjJ4whd/fn4XRcwZDUq5ytcqbG3/4U1Swk/e++JGfvv6YddPXkdNxMHaZhaNHfqB9UhcGDx8jiJhkOOJ9yo/TgcFcvfQX7h6evPP598JqXzq+oNAwcrIzRXmaHIcdfguCoz24cOYk3fsOpKy8lA0rFwt7+jXLFhAYauKF1wNwcQvivZec8VU4Fpw1VjndulQht2t48oXXqa2pxmqz4u3rL3LRju7fTVxiR+HgGNe+E2qVirKSIkHcJEgqp7Qal857ctdeLNp4gHXLFlBZXkp0u45ExcaT0msgAaERrPhzDmu3fylUz54Dhglzk12bVtMuqPKuem1/vZ2TB3eL3rT8m9kc3buNP7/tj0LmiCaQEONex6Z77Ny3T9Fawihdxx59PHj3tU1Me+Etzh7ZT2jQr2RkxHEtewXPPN6MzariamE2rgc96NtrMqVN2dRZKqirrUC583d8AkI4nXGJ5sYGkSWWaXSnt75W7EOaIznNLji5uFJWmEvG2WN8PW2BUIskfP9SFUo2iZ8HxVbx9cZ3OHQkgcCoOM7/8T2//PE+k1+7KQLRWxBpsBFpkLH0xwqik2fh4etPcHQ7DJ5ewgQ/KrET1eWlTEr8/C6CJo0nw6Sm1KLFaFPw1dk+eKnVIsy7uaEODy8/DF4+uHv7gtUisvNMxkbqygr54nWpb9AxhlSXGsba0zmZIaeg9iKna9vTzsXRHyXcKxt8SO07jeOrfsHJzUBU96E46T1Ej5pUEtvSXOdk8KIiJ53CzYe4/JKefi6OcyY9esHuiYvGk9K0M6icXND5hNBUU0F90U00ZovohfOI7ozFZiek9ziurp1NQFoXvvUbhY9vDXVGLdXpBhR2ORO6XydIKYWUw646L5KHjOfCgR/JWvcdocOfoDbjJG4RSfSJuMjo3jvJro3ktwvTaLJZcXaKQ+nigbmmDI/2/TA3VGNuqhPGJa62PJ7pPg9ZYyFzD6aSrQ9B3ghuN0FR24yH/92uh0UmZ7akdUSWr8bDuxHf+mayFCqay7JoFrc+bsOEnXt+nMRI4zmOnLzJgkXv4t/3Qdw7DEDrqkcTl4rM0oTM7ELxH4uZ/VUlfiPGYAsyoKtS4JpjQXWjnKow4JINQ3C0cIN1CYkmrnN3QsPDhWomOYlqlXK0KjlOGiVqhQyN1FgnlYt268HOHTt4f+x2fvD2IaRDMOmHryKTw/fff/8/+xBuQxv+l+FWRGob2vD/CNLffOnr3wF5W09aG/5JkO6+S5Dsu+f+OIuCvJv4uUZixYZK54GL3Ju8tDN0GnCTp94JI0sWwqZf7Sz7uoYuwbcXeQXZviQnXWld6DdZFex5dhGmGe34eFUsi97ejtVm4Ys5C3AzGETPWZduvcW+pRJFabEkOS7K5TJRiiiVGR47tI/NT3zHmcBgjI2O4OTpT86kc7ee/PjnCjat+Ysj+/fg4uoqMsSkzDMpO2zwiHGCAK5eOl8QmOdefY++g4YLe/3a6ipRMqlUqEQJoiG/ge213ozRl4m79enNGjYsz2HY6DJ+n/2NcFocfZ8bXXu4YPOMZd6MSgeZGCB1It3OgjMobeh1pUx4+mP8A0Opralk9YIFZKVfobK8jKDQCILCwkU8gEqtQa51ws3dg8LcHDKvXaHPoOFonZyljyDhyKhWVwiVN46fAACNY0lEQVQ18Xr6Fdw98vB01zHn87U89OznvPH5HNIunqVzj77iub9+97EoE92UG8s97kU43cqs21/kh8Vyjaz0q+TezBLlXMfKApnindda/pbe6MLlnDUcqhlCgs+N1vK6HVfDqa89y4pfviOi60lmDHQYhkR0kLFstY5Rg7MIj00QeWmb987FNyiUIfdOxz8sgvTzpygvyqdL3yH0HDGOz595gDnre+F7fz3tnaq52ezM+4sG4+5dTkH2dTIv7Gb2Q47sMwmiRPWOiIhnR8l5dlQaJ/My2fSrlYyfPuGN0ffxWvQpnGVWAlSSr54D7gobQcFm5n/4Eq/8vILywlxh9mExNZF26DOcht09/2+alTx/bBh5N31EaLvnCTNN6nzhJFqXfwaD51DsKDi/byuxKb2wIRclmN7BEWJhfifeH3ecj4rqOfh5De/86IbyDTux2houGd359Wx3AmoaUao0GGsqUchsQlWTDtLN25/izEvI1E4ij09n8MQQFMnHJyOxdT2Gn6qJs42erLicRIKXK8fzFpN3ei9RQx4QJiE2m1X0TUpui9JND63eC8+4VPw69afwwn7kP/hhH9qXT4fuYuDkXPKLnPg0twsdDIWUm3VsyOyEyuBKaOQQblzcTMjQx3AJbU+H4Fy+Hr5UHFtvyvB1L+bN1VPReATQWJSJwslNELS67PM4+UeJPrHFj39PgGTfKLk6Jm9m+LQxqJR6VOVGrMUl/HXNk/dS84WBR50dtlSGorjqxJORZ3jumdPimu+/HMS0b2ycvB5HZs9dBKvMNNlA0n9XDtwutv3QPVqGTI3l/iF/UXx4pVAS/XuMResZgJNnIHETX+DGll9Jm/+FmESSEu3s5I3Wx5fKy1eFI2bq2OnYFWr0Wkkpc5Q06pQKgg1OaJQO5Ux6z9yZy6PX63njzbfZuGE9hw8f5OqhS/Tu3Zv3339fVCa0oQ3/cRB3if5NLO3ftZ02/K9CW7nj30ebkvYPxtHDh1m5cjkmWw1v7xlJuFsNia5VVFmMLClw4fjRJ/FeVcurD86mmQySuvbi/S+6kFeyC59hfai56s3V9YtQr46nX0IzOSYnBrtUty5tvppymcvFr3L1z584un8XDz39Ih2TU1Fr1OgNHkJrMBg8RLmfpLTVVFej0joxaepjTHnoCZGFJqlSYyc9iJtez4Uzp+jctRdPvvAW901/UmSB6ZxdhGLV1NiIxsnR49YhOVUYfVSWlXLq2CE8vLzw8Q+krKQYhVzBoOFjOHJgPk3fvMKacdm4Kpu5+rO0oMsgOi6B7z59h7kHhvFEtOQGKdnMS4vr2+dNioiS1un2W/lI+YUWMc7S4kL2bNvAr99/xltL+/Jcrwqs9gqefnErA0bOo66uRrhMSuWd4dHxuLi509jQKI7bYjYLhS0z7TKLf/2ez7YN4KUEq7h7ZLSV0nX4WF7+eC3J3XsLgi3FCHRM6cHSX77n+ndOPPFyH8YFp5NW7sOm14z4BgYT3SEZV6Eowel5fuz6yJNU1yqKTRp81Y2U5cay5IyGryxxdHErYW9+OPs+MwkScebwXh5/yxdobCVNPUJslF0L55nPy6lunsrAcfej0mhoNhqF+UlcxDW6djBzNf0KS1fUERQZQ93yTbxVMxG/+EpeTz7GB323MvXXLLr19Oa9V51plMjJLdJTYZUJ84cWoibRYel731ALP6xP5uNHzvKo/jJWi4rvMzvwTuIZXOW3ywL3bvBiz7FmDN4z+G6FK15hI3D39uHDN28bcbRcv/F7xuK8Sofh4kkUMh1BSYEcuLyMvIwY/J1X02hbw1Nf+mJWDRZlwEXZVxiWchK9JptdlT6M9iyhxadCIh6fznChXZSCiorTfLNlBmZfG+Z6Nc4XlNjrK0RMgnRgbj6B1JYV0lBVKfq+JGg0akHQjDVVtBsyiV1vfsRLX07H2aWJqipnlGk6NHYntHpPStPPEtrzHpw8fEUfmkztjLEsD7PJJMapdnYjfsqreLXvxeXFH/P55CbGxNwU+4kNqWdqaSaPnh6N1axAeVOFT3UzXs7hZFstNFWVYIhMYnDCkruU2eTgXC59Nw2XkAQMiX3xSxkBchV6qSdMqUSpUhLocjsD0FUFvr12s+XTa+g9ozEqmznyVCmmTQPpo8+ng7ae+wy5ZChjeWr4mdZ99UtU8uy9h3l5+F4kDxNJpW6wKghQmVufI82NvpFG2n/1AtWf7KXMnM+NjbPxTx2B1z1PUJV1gaiRjxEz5H4Kz+yioTSfusIbNDdWENVnNCEJyaBQ4+OixFmtEGWmEkHzddai192t4Dl26Ki5HD9mFAuXLOOB+ydz732TUStgypQpf+vztw1taEMb2tCG/zu0kbR/KB5+9HEW/Pk70aFhHD3sjYcy7batuhZ6xZxko38W73uMIPnrqZzOXUhy9774B4UywH08uzasoDbzMH2G3sNPb2fxzPnLdEl2YuiWoNZ9SMqOa7daEk934crFs8yf+50wzYhP7Ej3Pv1xdnalprpKOBGeO3VMqF5SWHVqj764uLmKQGnpcYOHJ17efvj4FfDDF+9z/NBeZHIZY++byj0T7ic4LIKihgYunD5B++RUse+KsjKsNhvtOiZhMpmFaYhE6pxdXOnVf4gIo977x1v4bw+mqrJcjOHV975g24ZVdEzqw9Dw3NbjkP/LjcCbJhVGu0IsHOdsS0auyCUkNJLGxgYRHzDkgyd4t9/e1jfXstkexPZ4lZ//2oqTTif6miTDEAlSz5jk9Cj1wsUmduKTN2YQlBTEU/G31S2tzM5Lb7qzc+Mqnn7tQ+qqq9mxeRWbli/kvQWdeLDPHopKZbx1byCN2nLOnT3IyEnTaayvIyAkTJRHznjhKCPcK8RxeDoZW4/lua7XeHBGElurBjH+4T3s2liF2R7BU6+XsasolSGGMlEm2OpoB3z8qjv+Id9hrzsmssSqm8Jx1x/jz7caxZj7RpjwDs3hyUml1FSWE26tY+0roJPKFAMh7VwUWnl5q52+yQ6bqn2QNSsY71fUWnp5Z3VDx1g7x47FEObsMKD5vMMZZt+M5IWwLMeclYGHwsa9vSQ9zkzfHyupMS8lr05JgofDxKYFdTZwWqHm5p5FFFgyUatlPHlvMN9+74ufk0MldZLZefvFKj56/WuKDm7jkSlauvrni/Mnmea8eaMjX4VfuMvl8sGhDlVwnPEvHnj+fmTY0GUWQww0X6/HLypB2PBLG2mqLsMnMkEodzqDF3XlRdhNzej9Q7GXV9L0Uw6kdEC6VG7XGmimhqbaSnxiksBqwmqRiIscq8lIY2WJsKZ3cvcW25XcDz2ik/BK6EFk8q0g81vjDHRvwHW9FfRatOUWtNeKyfcuRaZUC9MQS10pvQIdYdgtuGHW0mn026Qdmk/JoRW4x6QiVzuhNXhTd/MyE7un3/X+aJCcHVN74u0uo7D8HAqtMwEDprN1mYzPXrmESmYnVGViwZNrsMpuk3Lp+9TBttayFqnnUCuz/Rfr5UqrAlWIHc9RE4jamUW6TzoFp3cQ0XesOH8YazBWl9JhyCQairJENp7eyVHW66SSY7LacVE7+s4MGg1uGhXees1dpEyoaP+y3+kPTmHZsmVtBK0N/wi0WfC34W/PoTYL/r+NNpL2D0TmjTzWr13NpG8m8tDIAjyUDuc2CXcuxvs7V7AospDyMD+cKpwpKS5k8Nj78PL1JyQyhqwrF0hISsHg4cWhnZuYN+sDSswKfFWOha7U81OS607+lfMM6NfEMzOauZalYcYjK4Tl/pdzFtwiYpWCoElljRKhkMxOJKt8aZWUn3sTvbunIHkzH5nEvBURrPnJDYtdxszPl/D6s7v4fPZ8dDpnuvYaQHV1BWeOS86K94jcMcnIQ7IRl6z13T28qK+vIzg0nF+Xb+bcyaOcPHoQ/8BgOiSl4B8cwm8/fkXnTvdQbq4lVHk7+Pt0ozOBaiNVFjXPvORHXbYvzjojR48vYurjz9GuYzJnjh0S5Zn+XUwiS6wFktJSVnyT3BvX6dK9D84ubuTlZAmiKPWheXr7CifGdX/9SWVVBUfPeOMsv93DI+2/pkkvwqmlTDeTycL2NX8x+J0I3h2cIdaSESEwZ2UeXTplMuOtz+g+aIRQ3HKuX8PU3ETP4Oq7egfvXPjGpRzh/J4jzBysu7UutbPwa0+Spzvh9JFkLnKNeO1tO3cLMnYfa0f/MKnHrYK9eYXUy7TIZQ41Rahu0Wbq66r56sdwnptgv+t8eCodZjQtkPSLojI9D0Q4CJeYf3dksUnfvdRNBKitd9m3280y6m3gfOsPwZ3blEpTfTR2vNVmGu2gvuOYDQroMOQSx3dkihy3owf9aectUa+7S3JC1M0s/cEPKBdEsuVaSONtp6vitNGFFN1tF9KW7QdLRhlfL8XTycq6wwoenZpOQt+Rgiw4SeqN1oCufQpNlcXCEdEm9VPJ5JRkXSUwIYUuk57h6IIvia8cgbstiCbqyOAsWld3QlIHofP0J//MPtQeAbj4heLqF45Cp6epqhRLU0NrqHnClFfZ17ieEfajOEnEFzhc74UlJ5eqa2dxVbtTFOXLjXOr8esyHK2bJ53Dsgm85egqQTruz290xx5koKPLQE4VLKPo4DIC+k7BVFtBovc13huy667jX1PlS3aZHxGdx+Pb0IdzR3/A2SeAWYNWo76jn9BVYeOvEn8m+hSJ63m1WYUTCvy4TaqlvLM7x3LdJGd+eTw1NTp0WhkyXy+8sm6Qb7NSdG4/PvEpaLQqrHI713avwuDqRHBkjHBolOaRWikX0daSg6NKLkfvpMLgrBL9aJLjbVmZIztQeiNIpGzN+k3U19++xpJ6JhG1NrShDW1oQxv+/402kvYPxPK/lvL0q258dP+Fu5ox//WOtbScamxWYy7NFT1dMYmdaGyop6QwX9jFRycmCXv48tIi4hKTuP/R52nX/V2+3dwViwIWnE/Fc0suAd2MLPvRDzs2+kQZCTzdi2mDrrBy8e+i/E/K9zK4ewqCtnPregKCQomUygL9JVtvmbC9//L9V+k8wo8pSQ7XN8m44Yc3XXH56TwnDu0jIDhElCpKPVpSJpqkTkm9Zy5uBuqqa0UeWr/Bo6ivq8XbN0CUPUplkd37DMBoNAolLzQymqi4duTmn+aNgwP5rt9OfJXNnK3z5JXxgejiI6m+fICsTMeiVArFnv7Ui9z/8NPC+KO21mGqculcCHntFQTfIqtXGp1obrYLtSw0Ilr8zmazU15azBfvvCB685JSe7Bmye9ETZqGr+LwXdciu0nDu89lkNStDzpXPdlnT5J59SJvJ3nedf1CDVYsFjOBYZFcPnMcV72Bnz55kWde9afKrEauNv0Xgib9f8ZUZxrjI5DLbpMkiYhc37OQHaXT2TlhAkumryZabcJoh7np7fgk8WLrc/sHNXG6TnlXhpq0tvZz1fLiBPldpWotP9fawO2OBfiM6ExKLI6F9H8HC3LSm3R00Dl65KRx7M+J5mhpOM93OkGzXU4nbQ0ed2Rl3bkvjYLW8kSJrNSFeIqfY9onE++d+1/mvrT9ljLMO/vlWlyp0xs9+HFxElOnXsZN2cRUjwJBRB2paxCudxDKhwZaOfN1Iku+PEt0l96CQJmN1Ti5+6OxlfJM8hsEuBjJb9LzUeNMVDoXYnsMoTjtNBlnd5MmmYtIiqt/KANfnCVMQiTlTB8YCWqtKAuUYDU1YW6ooVFS6OK6YKyvRePmyZE9sXzsX0t3t3xymt1YcLUrmig3zBf2ccV4HtkFFf5dRxMx6klkSiXNVstd10AiRpnZAbhV23FuUKD1CgSbBa2ziyD9sx87eNe5lpDZ4I09RwtyE5rLeciUKpINhxmW7HjvtqDAIuPnrFT215fgo6vjcnUAulobc1L24iKXOgJvu29K2Frrzk853Sko9YQcLZpqO7JmC00mh4mPUqlAbjFy48Amck4fENEeEqRw9GGTphERm4i12cjJvdu4eO6kyN+LiIzk/gemERwScpug3UJpZS0Txt4jSJn01VLe2Fbm2IZ/BNos+NvwNyGcmP+1JOFvbOufiDaS9h+K0tJSdu7cSWVlJeHh4QwbNkw41C1fuZZf583lzCEnZHcoBy0LaJMN1HLJUQ2WlkZwc3YdN679hYe35Hbny/W0S3RI6Snyipxd3Wg0Nohg67LiAkbdO1UoRI8kzUGt1mCzHRRlhCv3tAeaWtWRjl5l9Ov2IFu3/yL61G5cTyc51dF8HxXbTqgKdfV1VFSU8+GrzxAXl86iJV40Kd0kP8XWMStkdiJj23Hp/Cm69uqHUqmmyWgU5iGSS9/B3dvpNXCIIIBWq40pI3vj55OHu7uKJksvuvUeyLDRE8Tzpf1LpYhjJk3lzecewX9RBC/smITRauTK5rnUG4/BNYQl/9MvvyNMSrz9/EX5Zl11FZcvnhNKnmS573conyke43mox0mMTRqWvmbBx6+cPgNHiDFK2WOfvfU8mYUn2bs9hFBNE5dL1nD4ghOLP74d1N1SWvfAOJMo15w4/SmO7NlGUb6jx6iywQmzl+NNLBQemY2tB9vxwPhneeLVj/jirce4djYIP0EW68kzKTEjI7dJRz83x3mUXueusPNJV8lg5PZi+1SDKxq5M4+8epjhPZSkV3vwQlYy5cUGvui0/a6FvLR1s/12RpS0eC+3KnHWOUpCW9BS0iZ9X1sWyABDqTCHaIl4aLDLSDdpcFeYOdXoTjddFV5KmyhPnH09idNrPHh35ik8JIUrtx0VCw2kn15K1n2PYVMpCOlQwAeD9+MitxCuNgliJeF4vTeXKvx4PuySWPTvrPMmbW+o6KNLv3AKO1Lv3W1sqHFncXZnVnba3Wr3L6HMKqPBruBArS+bjyfhvPAUC5v6YPJXkt7rLE9GXBDnwk9hRXWHYtRzuDs7FxrY8N1b3P/J7xhrq/GLlTG968/4OztKTwM1NYzu/A2Th+WROHQyvR58ge73v0BVeTG+LuUM6N7MkWPp5FRr8QyPx1hdhtLVk5r861gr0nhgZBUNzWp25o4SlvkTQ+YTHKzktyxfVq2M42DnWO4PusYUdTbb6+IJjR9K0ZV5BPW5l9B+E5HXXaessJL0uK402ecL9bdFkXQzNaG7aaexqRyjMQ/3mC7U5lwS4dla5d2ujRL6uhWyIw80hfVU1Oei01oI8L3dsybNgUYbfFWYRHmZJxc2epI4tIAnY65ypdKH+zaMITqpgI+Cz+GluK2qFZuduZkWgHO6AucSC7qsGmqyL3OTDJRaHaHR7Si8dpYbJ/cy7uXxPPFIMZVGLR8+UsWmxb/y5MvvsnbJr6I3tV3v9ljqbVw9dYF3335DWOzf/+A0YWQkQVLRWtBGytrwT4TM5vj6d22rDf88tLk7/n20kbT/QHL28MMPs3Xr1rt+LxG0KQ9MZfeuHdjtJbiqw+96vGUhWm+HB84Oo/LFak5nLBa/kxzkGhvqeO+pyQy/dxqpfQZz8uAu4jt2xscvEJnVRlR8e0qLCpj80FMMuWcCR/ftFEXtBTdvcCQ9l/HxTa0L9OxmHc1mhSjDk9SehI7JeHr7UFVViX9QCLnZ19m7fQMbVi6lY89mFn7hIfp7JIJWbXWUq0nYVeNFY73UJ2QXvXKSbf3lC2eoqaxgyR8/kRBbxNGdb1PVkCiUsm3nujLY17F4zqjJYfDQn0jt1Q+NVidKLCVzh+i4RCY+8Ah7tm2kqnKteK7U8/b8Ux8SFBJOUpfuNDUZOXZgN5WV5cJeXx/mgcbJWbgyPvjYc8yfO4vYvI5s2d6RcxeOUJifw2sffUtYVCzVlRWsXvIbR/fvZH9GF+K1NeKcpPqZObDABb3kW36L6Jyod+On5e04eX6xONeBoeGotFp++Og1dqel0N/gyLySiLVESLRyGBpt5v2vPHhr5ms8t6I/fqprrdc4SGUR+8qvc5QJutxSYaTf/WsM77dzUnnlJyMzBknKiplwpxJk1lN88kY9gw46yuFaiNryigD2nAij8/CjYlEvLauX58dRkl9CoVkyfrC2HpNUerizxocflg/E2OcYT3fKbLXnzzfpeOWjMRij1DjdsGEzNBM6oIyCMndUyxWk75rFZ9eexB7ug+6GEVXZeSprsrCv+hZXhQd7fymi4IHXMPmqSUy+weSOF7lu1LNoRw9U8zNY/dw01HoTTemuuG9OE4Yz0rTfVeXFMA9HyW+FBWad6Y39L3eyZmuJ0t46VqDapmLM1ilQocLrqIXK5kKuzX2bHjEPcfgvV7a+cD9yZytvJx7gPp/8VhVvV3koAR4RlLpncnL9Isa99InICVSry1paoAR8fOVEJQ7j1KqfxXzvPPFpwr2LeLffn4JcTomCT7ZcY+/xVAzhHTCZS3BydeW3qatwVzWL69gtaBcN9Sp6hleJbQ5+CWJ75rDp6SgMGguyCBgVfZUhQzWiH+6eifF8M+ZNNHIbtRY5T8++IAhay+eBNK96J2ZxvjqM642nhQ7pGdsZt+A40Y+2rSyEib6OmwYt6OVaiapdDaqtBSw9VEHHiCgarEWUW2V4KSQ9HQ4Z3dhzPQ7lDSU93HP4vv9O8dqRQXlEF+bz2gvBmB/tzdeD9onxXDWp2Voaj6JBjluuGc3xTI5ULafZ3ohkt9l7wkP4GLScvniElOE9WPzSJcdxeEC7dTq6JyjZu2UNRQX57L2WSh83x/m5aW5Hlx5l7N2zW+SgvfXuezg56f5nH7ZtaEMb2tCGNvz/EW0k7T8I0qJTUsyuXr3KwhMDCNXXsWpXDGe/1XAubxWLFvyJQqsg+1oMatntO9QtZVzSQjnXrKX8mCd19mWcOBlNoJ+S3ZX+zPmhH975uWxd9TvRCR3p1newaLyXiJYEKfNJcnq7cOYYnbp057GZb1BRVkRWRhozp48nKnUY/bzyKTA78f7OIVTlbhYlflLflF9giHB4lMigRLRmPjSG9Vt9+fwFFXVWqdfp9ljNdjlvZbenyuhEwZJwigo+omOXruJ1Ur9ZeUkxX77/Clez2hOr8xev2ZFRzcPPd6C/zx05YXoz/v7FIqstTXNeKHgSkZUCtbVaHcPHTiIqNgH/oGARGVBeVszZE0cpLsrH08tHlFTK5Apqqipp0kg+hAi3vokPPiYIn7Td85eOEBoVzePPv0lchyRRgilByjaLie+Ih6r5rkW6ZKxxpxHF5t8aWfXtMuFM+cL732A2mVmzcB7OXdvT3c2xLQmS8nln/9akQTJeaaqjxGS4y4CjZdt9PKsx2u4uP7xTGauxybi6PJ2n97pit1e1KmBRnnUU2iRSFdL6Ool+zf6rJ2lfzaV88XQGxGZyuiSQnNn+1NnXc8+7I9n2yVF8lHaa7PBZTid2zUvm/l7bCPOtZ3OFB0luNeSZnXhrx1CKVy6mojlflK3WGCuo/jMJX30o1apcjDRw9uD3xJW1p9rULBRYiThL6mVRQR7NViPpKz9DZ9dTLIMbqdOEwuKRkcHhG0vweDWISN++yOorKHC+jsVkIjAkjMmjanh6YSeC3WpYndke80oDV7Z+zQy1O1vmqARRkYjFrqpA9DtBcyGLxrocCtXZyBVyjmbMF+fC5532RKZOYo6tLzc+PkO0SwX7KkI5cj4ef2szCZ36k3b5oJjzbp4+LLkQycfdKgSxlc5nvKaBkPbB1Ff05NzmJcQNnMjE1NV3EejJgzP54PH1aN08GPDS98R3tAhlsQUdvOsxed6+rmoZ7NkVjbtW0mQdiPYwokp1xr7Oxsv9FqO+FYbkprSx8IVLlJjl+Kkdt77Ndsg2umHx1GITZ0EqZbXhrFWii0pk/u54Rt7/FpJlSss+pRJJeYSJETOr6Rjh+BMjlY6WW2QsrwymzqZhW0E81hwXvDNtDBrvCGJvmWcpPmU4jRzOuZeO0KNrMO1ejKakyZXSHC9c82WoK5uoqcsTBE2n96Tf/U8SEuiPWi6nsaaS0U+k4CS/XboYo20kKDiY0uICUu/tRF+9g6BJCFWZKT5l4JeMLszst413336Tb7794b/5dG1DG/5haCt3bMPfRJsF/99HG0n7D4JU3nju3Dn2pHWlnyFPLHh6TTiJaTx8dnIQc6ft5OrVYLyVjr6TlkXVxSYNdRWu5NU0MOOZAmoyPuDiqSjaBUqPWnjAJ4+8Z0+y6ZNuxHfswqHtGxg4aoKwzU87J1mYy4hN6CQMMLp06yMUpaKCXHIyrxEdn0hSak9e7LabmL4T8TEEU3p+Nfm5N/h89p9onZwoLysj+3o64ZExfPzGTOati6RbYLUYn7Pc0ko0pP9nNLnwTd/1wiikrrZGGISk9OiHt18A9uJC1i5bwP1fTSBWd7tnaki0WTjdNdsPtC54pb8/Tm7BnDl2mGdfe08s9N975Wkunt/Jxj2JeDuZ+WHuGg7vTSUyOh4PTx+6dO8tjtnY2CjKOUXGm68/hQW5XDp7WiiCgSHh3P/oDKY//RIajVYQs9PHD4vVpxQ7IPUkaXXOKOTNrC/xIzbkqujfksjO9WYN7W4ZdEj5UH8uzMBV785nc5fQbDYLE5BTh/biOWQYjfZSNP9NA5d0jnyUVlbt7URiyNm7DDhaIFzu/iXrS1p+XzI6UWXV8N2OXuSWzmdrZn/6pFS1krxj1T4UZmWwt9aT/m4V4hxurPZBvr6IBms1Bx9dRGXoeKz19Vwr/JEeD3Tlys4DDDNPIPy+Bkpq3LCtcGLfL3/icutCSNd24upeFOwLI7CwhLP2m4JZKHQyvF19ySk9R07tOXG9h4wYjZOTE1cvX0KtVjHpwYfp2r2nuCaSz4xUxrZ7+0auXLooDFxOHfgKP/8AykpLkClkVJjyKb/pUIfV9RpB0CQzj7rcq6yYZCCw01BUlUYqL66lwV7DnnU13NvjEcYMucnFOm927u2I15lsDuf+Jrah9/DkgefepL6mioyLZ7ly5hjNx0tQoSb32WR094wFkwxDph1NbiGZ8nO4GDwoTDtPQHwnds9vYkpHFzrq6sV1kpTNl1/cx8O/N2C2NlBbmE05urtKRmtsCrqP+5i0E/M5OOdNDG+9hrnr7Q9ySbmrtKqIkN8mZeHODgOc29sA7/H9CSntjUq78a7cP0mx08hvOy5KfXbjgzL5xTWcIHUMVaZSarMviuOQypIt9ZWYrDKclLd3cLhBT3m5Ho3/3ZNM2vavZ3vRXKFDXidHnw26rGpOHLEwaqBjLkjnocisweJpxz25Bw1717J+26/4dRhAkH8qrhVgLc/nplc2FIHey4dzW5dTGR7F0JHj8PEN4Nj2BqxdHX2REsosSpEXGBAQKN67d372CRXZDk/HXKdx2yDeGL6bb778Qjg4SmgrdWxDG9rQhjb8v4U2kvYfhAsXLuDq6koHV4eBRevddOCDrpfxn9MNb2Xuf230b9bx3o7ReM7Pwly0gsj49oT4SOVTjoWX9NRYXSUrwtT41AWRfu2csHeXwpklIwwnrZNQFBqqK4UTY01Vhchtknq2igvzcNEU88nHHpw8uYW1a+oICA7ls9kLRNlgXW2dMPLomNydlYt/4/K5k4T4JbWOTRrBDbOKepuCQpMzn8/ri9Vyhqi4BB599jVh9qHVaEUZoRSInXntMnH6Pq1ZZtzKMqvcdYJ5RTE85pchFoubygM5e+wsk6ZKQdoKdm1ex6E927mYlUCcxmFwMPtVN/pO3suZE4dF6HSLWYg0bul3SqWK8KhY/AOCBSGTXC4lUiYpmpfPnSYiJl6obtJYTx3dz86Nq7mefp7u/bScP1HHlnee4/qLXnTzLWD3phBy7L48O/Ew3spmFs5vR1lZFtNnPCzI3Z+zv2LvjhWcuhhPvNNpQeJa0KJA3Ink0GaC1Hdbz4vzeYfdect3aYn++LFeXPvQBcxNGBuPU2+rZs4D+1BvGsLgoBtcqPFi5fvJWGT7ePweOVFvj8amgIa/tFzN+kmcC5nKxvFrfxCdpOfmcV/0ilLqbSqeWFnJ9glbcFf6UmbNwFke3DoeaVH+3ZjDRMycj1RMFxwcwkuvvoHBoBd34erqaqmrq8PLy0sQaQn33HOPY/5K11guEyYs0gLfLSyI6KdnYMdOY30Dx48dpbi4EO9+/Ujp1guTxcKGdas4ffwopuZm4bbponcVyufN4qPc3H60dVy+/gGEhEey6dU/uTZnGF4BobjdvMR1o8MoY+iY++jQvQ9KhRICg4lr14H2qT1FvlxpYR7lxzcSW1FNqEsqWpmc0qACio5eY9zM94nskIzFBvHJPWiqz0B2R3WdUmnFv8893Nx3lYN/fMFDw5LuMmTJb3LB6K0hWpXMqcLVFObZWFUZyFBDAQ02OQvKYziTFcIXKfuI19wmai2w2MEgh5W9N/DSxiHM2+vKRyMcnxct0Cvudt90VjZh9JKjtDm6/GyN1Wit9dhlSjyCwvh6mx/v3VOEyg7XTEpm3+iK/IaadSfjuGdwGr4qm3gPbqsJwFSrJWCDEVtjPcqKRkryL/DlxWME39+NwaFVlFjVfHszBVupGrnMRFhECplpZzFVZHP64h6hQkrlzZLqLkHjWkZAuIGj63Zy+vA+xk64l9W//MVHA8cyNfU6dVYVL39oQKm8yfCR9/DznB85XNOFXnpHmXHL+0f68ZWON2laP4QPxu4UZj6Sst6GNvxT0WbB34a/PYfaLPj/NtpI2n8QAgMDxYL2ZpMT7rqGuxYhEsb3d/TJ/CuGuVVxaNA5DhZ3pseFkRw6vZGD19ozskOleLzBBvsqQnDJN3Hu9EG69x8inNP0rm7U1ljFXfXayjKunj1Juw7JwvlRUow8vLx57fEuHN1oQCXTw0N6lj3dlalD95B26SyjJ02lob6e2V8+gotiLxOmeDKrIBoZ9ULZkZZh0vcFWe3Y8L4H7nYLV678LkjPe1/NFYqdq5ue5iYjR/fvpkPnriLc2rhdxepe/ow0FAmy9vONdhSVbmD1cyn8NTYVhQn0+64Jp8p+Q0Zy6dxJocClDJiAv+p29pWECU/EsnftTmLi25N+5QKdpTBpZOjd9GzftJYVC37B08eXQSPH0UFvEHb/VqvZQeSOH2Ld8gVcPHuSbzck8/04C508QnBT2LHYvXn4/WUce86Xc2odl65t58ttfZnsVSjelNX9j7PmGziyaxunjxxAG1pIUXo4eoWjvLRFCfvXa9yCC3XuBHneLvmS6FrLkrNl0S8pZ402JQsvdmTHffspsTjysaSFcFLnVC5dOMv6J9O54DcEjdVEfZWjz/Fm5jFMb94kMiyGm9nXqDfVMOWB6Xh6eTN39rfMWxSDm9yx8HeW2Xl59FnWv1RDjqWEW2vru9QMs93xwz1jxjJu/ERBmlrg6uYmvu6E8s5kcWmeKGStCqmzszMNDQ10Skri2WeeoLi4mB2794nfvffWK+K7hAXH+3NvcL4oNUxv1tKjSy5KmZq4donEtUugQ8dk0bOlksoZD20nK3enmNOSejp56sNCMZbQZLFhsdrEzYQIqfeqqoLmxgZBIjKyDpNuu+V+KJfTc/QUPH39aWqopyDzCmGJnXlr1jzWfQ56uWRMAguK42mO8KTD1UFcLNhNiN6ttSRWOmch2gZUVTZsZQ5b+EHRh5niUeAI/5bZ2XMpnrpDXkyumsjhkctxkd1NuKTzJP0/WG3i1S/28dhwAx+OcATQt5LBf/l8qLcpsegUuDv7Cd8epd2Em5NGmPMo64vJrhtJz9/OkdBXw/VqX8qveOKVYcV8qYJ2/et5aFFPKq1aTuVEos1Qoi6v5PjV36gXJkAyVBotq+d14HNDE84dowRBM6SB6kYlde6O0sThkx5EjoyCGxlYrBYOblrN3qsp9DE4FPeqH2PwDslk945tPDjtIb57eBWf3LrWAYGBvPL6m4SHR3DoYAf6xZ/myTnD+XB0Ft53KIDSdh5LzuUDYM6cOTz//PP/ciba0IZ/EEQfhP3ft602/EPdHf992/onoo2k/Qdh/PjxvPjii4wZXsGijV701dfftUDTyW3/RUmRIJVZpeoL2ePWhUZro+gHOnLlCQ5f/oquQ7zZUhzBpdXRlJ5dIrLH7nviRUGQDuzYSIeU7lSUFgsLeul30mJUCoeWXB6vXDjNM+/5opI5SvikfQ6Iz6dXj9FsWbuMBx+fyYuPTmL7FgVRblIe1e1xScrIigpfDhaHsXtGOdfTVwtjj14DhvHmJ9+jUikFMUvu2lMEVHdM6SZK10aMm8yWtb+jdn6LbzqboFyO7sAZQTxOHvsTt6sGjMZG0T/2yntfUFdTTUVZKeVlJbi6RnGt2ZluuvpWZ8V9O7WUlRSh1+vp3K2nIAFSL9TMR+5jwhvh/PJuE03mXO6fuIyBI99k+hPPU5B3kw0rFlFsusDCxUFEOcfgo6q565xLi+VP3/Ii4vfLouTTkBTPsx0KheopPef+pGaSridgUFlYdaSR8T1ccJPfLkv7v/obWGqV8835FNa/XULw+noStUbRI/TxpU4czQhjQvdLdPUo4VhZAL9PVGI3Gckr30CdrRJvHx/GjJ1ATFwcnh6eXL58iaWL5pOW8bXYtqeXF8/OfEGotbt37SS/KAeDu4HmZiPLli5sHUu0vv7usSEjsUMHsvOuU1VZSYFJQaDacSxSmeJHOSnI5ddZtGA+BoPhfzzfr1y7TkxkqFA8isurBYkK8PG46zl+fn506ZJCv97dBUHr9sFT7H9iDyrZ7RsWcdomPlnTjZn9dzJt2jQ0GkewsaTYPPbYE4wcMYorVy6JSIekpGRxY0DK1ZL+ahibrZgsNhqamvnpq/fEXLoTbu5edOw9kISUng6yJbOhUStp17kbJqsVrWwwI3do6BBfQn69gfS0ELyrbES2j8cl7DAH8/1p7+6IRpBuWJxs8MbiIkPp44wiD2aMuty6Lykc/Lueu3j/z0HkLjnNDHVv3uh3nDi16b/9A+eiMGN7fAgbcjcxNqT8v51PEsrNzrfc2RxU2N5Yi5vajkKjRKWQoVFoOLssg50LFIR0iiSg2ojyWh7n6jdTXV7Cj33XkzzxTdxMKpyzKtA512PSNOPlHkB8am9iOnQWUR61uzZxZt5iUjtNxKA0UG3I4/S5XeJxbx8/dColQQGB7Fn3lxhHb8NtBdBdaeenvYOZ0X8nHTt2pE/ffuTezBEKt9SPJr3/Jbz86uscPbSfX2b8xi8zoKkgutXm3xGIbuWVRaP4ZtpmAgIC/sdzsQ1taEMb2tCGfzfaSNp/ECQCsWnTJkaPHs3A+HP8vKM7j7e/vfhKN7oSaK3Fz+2W+f4duVFX67zxvFLHmfN76T54JO1TepKV9hHvTf+OK2cXieeFRsXy0ic/iAWVVDrWrlMKVy+codnYKIKio6LjKSkqQKVS46rXiwVrruRiQGHroq/cokLvFElJ0Qb279iMf0wlUW63F+Z3GmfM/zSG/SuWYbYZGTF+Cg88+hzFhbkiC0wibPHtk1AolGI8knLl7ufFiLH3cf7UUbYueRuPbd7U1UnkyM77X8/F1cWNzPQrt0iqnTVL/2Tg6DpGjnTDZFIyZGQW9bUurG3S4aEysexkR3YsX8wTz7+OzW7Dzz+Q4qIC0TeXMCmVn6Zed6hTGjiwJYTgmC/oO2gEm1f/xYmTh7iRHkaAsk4cz7/mk0mQsr0k5U0qvRv9aAIq2YW7Ho+7FSo8s59FKIL/+vrzRieSdA4LdwmSc+IDM/pzdOMimmnkwUnjMUyIoTldRsbi36i1lnNYCgvWxoD2MoXVDlc+qc/rnsFjGTNufKsFuQRpsdv+62/x9fXl9KlTIktKUrnq6+qIiIzCw8OT7du24BYYS7s3n2LxxO0YFM0Eqm6XWUpz67Ml7Tl/eWnr7/pvmk7HhOvEuJWTXu/LpQuh4npIjqT333///3i+J8RFtf7s5/V/Q+6szZSXlxM75il2PLbnv/3Q06isYgwtQdASpIW9dM4DgwLF179Cipc4ffwQp0+d4GbOTWpraziRmUSSs0MJnnctihcGbMPUWI9a6puT5lB4lCT9kXnuBP4xCXj6BbHr8fcwPvohVhcNHkVW+rmf56OfTqOQBVNrzeaXklASXCu51OjOb5e7ozHLsJU1MP+PIBEIfSeSnetZvHQDXR9Ws/ShfZx841WemXCFqf6ZuN/hQCK9HffU+mO1Kpj7cA9WflHJl0nH8FVaqbDK0GAXbqHnmpxZlpGMutqGXe2Yjz4BQeg1KlFWqpYrhIHQ8DGTWDz3G86s/0BEWUjqtlT227lbb6GUHV/+ocg9lAjujcvp6N09RMagQe+O5daHw7BR43Fz1nH8wBahcqs1GlJ79GXAyPHotBoUcpnIhWs2Ot5T/wqp71CMz9fXYXQTHSPm6pJFCzhx4ri4iSN9Nn7++ecMHz5c3NSa+ksIi57MFeY7LUYrbw/IYH1UFMuXL6dfv37/1/OqDW34D0ZbuWMb/i6k6gdxQ/PftK1/ItpI2n8IpEBmtVpN9+7dyc/P56uvvmLG8A+4/G4kT07VkVcn2Zu3w0XhR2RVGpfydvPzb14EBGvZVBjE8jfqyDn8MeGxicQnpQplzNM3kGGTpjNTImYarchVk9lsou8s/cJpLu57hZjIGpYsrCIvz8K0Bw3U1VlYsaqOhE4pJHTqwqfTjtP5bDIpzhVUWVW8cbYfRksevgFBnD15GEVwFFZ7eWv/WAtOGp3JOVEgCNoTL77N8HGTaTQaCQ6LwtlVT1Njo1gsWs0mMtIuidJKKRzaw8eHj7/7jZvZmcJZUiId46c8JAKzL545zrj7pornjumXzPM/hvFKd2lxbmFknIvIcpO+Ss1KunfQYNRuxeDhSbsOSdRWV4hFYnHeTTLSLjP8245iQdcCg8ImFLpdm9eybeMqOj/5JN7Krf8lOFp8v9UbFKltoio/hvdW6/h6/AVxDv674GcJd1b4SY9dbHBiwkAPftllpIdLpejZe31lL/ZtnCeeExUVzZXTa1GeVwriIX0FBgXR3NRMcWU6LmoXhg4bQb9+/fHy8bmr/8bb25vhQwa2qg9ie9ExhAb6kpycLNxDWyBX6Yj+bCJHB6+8K3i4ZZySo+OG9xfh4uJCfX09/rJwFNUqzqfFcl4TBWY5TjlSiLVdEKk7Q4P/XTh8+LBjrO2DBPH4V5RaZLz30DViYuMEYf2fQCJoX37+KZkZ6aSMvoc/F+qJ11cR5+RQYaXr9Uzcdd7QunD11FF6DhqJTucm+jYlR1RJlawpyiMhtRed+g3jwp/v0aPHFFxMWh5ZcKn1/SCVxoY51fPk1nux2mRocxQ432igwVVOn17OQpn7VxgUdl762o8/H+jKmS9m8d3Kfux85R42jt3U+meuyAprctvjdFOBosHEmjGLOT/0ITymedJkV9N40wnXwEbqG7VoLmnwuljMqbK94rXdu/XCRaMSf3yVt+aIu68PL731AWeOH6HgZpYoO07p3pP28fFYbTZ6de3MkSOHhXHH+HvvI7V7b9RaqRnPjtki2fJLequCoSNGM3DICGpqa9HpXHDSqjGarEKxc3VSijmZnNyZC+fOcrjWQG83h5pWZZXx3phs8bNUdiuZEUmfiVIGWr25kVmb+qJW2nll4lY2JmwkLS1NELZVH20kMHQks0ZktJ4/ye3S3d29tTS2DW1oQxva0Ib/N9BG0v6XY8GCBTz33HNiASzBzc2NSZMm0b9/fz75/Cvef+ctbl5z5ZdvvNn34yE21gQya+tgAub70Lf/r4y8d5pwYgx2dWPwG5/QqUd/4T4oETGbzUJK38FYLWZMTY14+QUKw5DDOzfiLvuGPz+XlpJ6Xn5UT4VRiZ/OoaC89EEs44aWs3PDKjQyNS9NluF63wPYahSEp1Wwdf8qZr71KRXlpexdupEVzyUz0r1IlDhuqfbjVGUQh1dGUd+8iLjETgwbM0nsWyJhXj5+VJYUCRIpWYJbzGZh1qF3d8fTK0CES7u7ewrTh8SOnSnIy8Fms4q+ptQevYUj3ZZ1KyjMz2VYJ6mH7L8qVL5qC3l1aYT7xvHJrLniCS6ubrjpDa1PPncmlOr2p8SCWEJWs0YsIMUi327HuURGvllFuMph3iAtpauscpbdiMJJ18xjgQ4Vy1Vu570JjcJFrwV3mp5IuLNEVbJEv2zU8dwTcdzMXcHkLmGE9RqP9UYJV67NF2N48ZXX6dChAyUlxVw8f16UoH784fuEhoYKdaAFEyZMEMT+f4Lo8GCioqLIzs7GWxVC++hJwvUjz6WQr7vt+i85ay1Ymx8iWdOQmprK3r17iXPugfGUmYoUFTaVHFUduFxx9B2NGjWKiIgI/t3w8fER3xUHbpL7mIqIW4Ya0vnMaFLTLuKKUGQfe+fd/9H2zp45LQLhm5qauHfSOBZ+dxnNHTEILfNJuobuPr5UlRWhkuzhxXu0HoVaLfqqJNMRY30tnaQQdJWcd2YeYVCS8pbR/W0EqBt5P3Ify2eHUXdTh6kyh/Sm01ws9SM43Phf3Tslxdqqxdo1htS6UZzI3kjuM3t5s6Erz9xXS6NNzryiRIqv+uGfbqTJmo8VCxk7focdEOybgpc8iLKyaxg1JnR2V4pUpdRRSY8+A4gI9nVYK0vuj7f6ByWFS6bXEDlxvCD5hYWFd/UIJrbvwOuvvsyW7buYMPYe1qzfJAYqkTOr1Y7FJvX23bJx1ShxcVKj1znmZkOzRdwgUcllwihGKmVcvHA+/eNO8fzS0TzT8zo5Da5UNpwVSu/Avr1Yu2EzK5b9RVVVFbm58QSqHP2Wk8744RGUIW4EHDlyRHxO/vzcXmYOCidU7ZgXm0qCOHVqH88+++z/swnXhjb8J6DNgr8NfxNtPWl/H20k7X8xFi1aJIKrXd3DSJk+nYEjivjz3T38/vvvLF6yBE9PT+K7OLHmOw8Ut2y2p3rkczA1neztISiuK7l4+hiTnniRHoNGcnjXJtRarcg8O7prE4ldutPYWE/62RMEhkehVKnRap0EmZo8UYXdbm216W4haBKSDDVE3TONQ/M+ZvLDMzi0Zyvn33xfPJamVnPPvVPpN3wsZUWFLPt9NvPeiuP7UX2wmhTIFudx5eRyUNvQaLW89vmPuLp7iowjuUxOdVWlKI9Ku3iW5K69hOW2UqEQ5K2irBhTk1GUP0rKjFKtFv1F0geF5EBpMTXh7esreuikbV9vciPRydhq/d2y2K2wytG7e9GlWy9hq19VUY63rx8F+fmC0EplW9at55gWPJynUk/SYNaw8sv22O2XWTb/Fyoryzi29hceaf8cP0zeQQdtoxiDl9KGp7mUHl5336G32R2OdS2QVLY7VTrrHW/UNKOOt94P5Pi+FcJ6vslczPlt34rHDAZ3Vq9excCBA8X/JSVBWiBLzogt+H+qUkkESyJo4dpOhCeNxe6sESfMz+6GXnlbWWs5jPcOR3JiRxP7F+xn6tSpZGVlOQxB7HZcCo2ojsswa+UojRZO7PpOmN6Eh98dsP7vglTaJil5Vw/9ycSnn+HH748Sr6tjR54PU3scFv2GL7/6BiGhof/HbR09clgQtJCOYTz6UUdmdr7ceq3+lexLkQpFuZcJj4pBp1QIQmO0WLFJNz2sVkHGG+tqUauUPDWzO4OT08Tr5HaH0Qu3lMiOTkY6JN1g4p83qDaDp0qy0XfngW+1WB93IdyplnSjG92dK9HJrZxsNLAmoxPqevA1BEEuBEVE8+3rp/jxG18inpiBvEmDz5VmuHCZwxXrhVL+5PMvs3X9Gm5knyPPckqMRYmSMosFvcGd8RMnMWLkPSiVDkoeFydFU3iKcyJh+oP/57nV8pw7n7tl+27Kyx0mN5L1vTRHFy5ZJo5fKqnUqRVCbZMImoQWZXjsq4P4pn+aeO9GaSq5eT2S4JBrPPDAA6xZs4aXnn8WfaDnXeW3knPls78OZe5Tu8T/586dS7du3RjY18i9H/WipljB0o9W06VLF+67777/4/G0oQ3/qWgrd2zD359Ebc4hfxdtJO1/KaRFveQ+JhG0GUu78nGnnWKx8vF+Hy4bQ1iRHsWaF7Zwck3oXWVo0r1pH3UjV0sLBBkryMnim9efos/IiXTs1psLxw7iExRCeFwCBi8frM3NJKb0FKWOksJmrK0RPWilZjWBWsddfGlxeqf6I/VG1QTJ8Q8KxWI189OSTaJ3zWKzEhQaiampQZDDjl2689xbnzH787dR7lAJYwZJqZOMS3oPHs30Z15B46SjyWLBYrZw+fwpuvcbDM2Qk5VOxtXzhEbECsdFKRfLarWJUGOJpAUEhnD0wG4qSovoP2SUsG8/dewQiSLLLIzmpia+/W0gTk9tJ0Zbx81mJwxKM2a7gllr+1BV8YNwOCwtLuLCmeMkdemGi7OOTp1TefzZl/nk7ZdIrC1hSUR3ruee58z52SSNjmTh9y44y/V8u8zOnDe/om5iinRGWkngoOg6fFS3DUAkTjP7VCKRUVX0dy+i1Kxlc24oL8dckVrdOFzrwdLzibzX7QghGisdnRvZ+FUmKaWJpO9PZ+nyVehdnNDpdEKtkohbCyRV739avvd/gtQvJiHCozu2WwqHdOGVMiV/LIvi20fOt7pH7ij35LNJ2/Hw8OCLL77ghRdeEHP16NGjpDUcJjHXDa3RgNpu5XjmfMz2Rn77bfVd5ZX/Tmi1WtGrKQW9X9g2m77bWoafyUsvvcSsWbOEKrZi9Trxe0mpkXrcquub8Pd2F7/7Y8Fi5v40m7NnTpEyJpk9c+twll/9L0qsRLCzmlVcqvBiSsoRcUwTJ0/DSa1AbpF0IzvNVptDgbLZWuvslfLGu8bcaIPpaQNZnbCn5VSLD2uJoEk/u8ltfDuzkUkP9sA8LAwpD0FbbIOkJpqMarRX1bhdKqHBo1SM4d4HHxNzZMmvP3Lt43fQ6z0oQ01VfTkKpYLnXniJ+HbxdEx4R7g2FhYUiLkjmclIvWVS2XCPnr2IiZCU0bsRHf73ylNHDhskvgtiJh17461zcStmQVLt1ErpE8hxB0AqZZRI2sv/v/bOA76psgvjT1b3HnTQ0jJKW1YZhbL3FmSDDEEZKiJDEBFQQcAtMj+WbAVBZcjeG8peZZbVUqClg+6ZJvl+5w0JKVsa6Mj5+92vzc3Nzb1v3tD73HPOcwYmie+VDnc53TSSIDo6Wjym7ALal0ZDPd0ebRcSlInZajJR0iAwMBBHjx7FpEmTsHjkVhH5+/jjjzFu3Di9gQzDMAzDFAQs0oooycnJSEpKQpU2/TGqyib9xQr9rGKVhcpVL+DLPT550uiIRBXQxeUm3vpHhqlnhyJhoR1Sr+/Ggc3/iEVH7eZvoe+IcTCTm8HKxk7U0ZzcvxOlyvjB0bUEenyQgA3LHOEsz8GFTFuEpzmhq2ukEGuLYv1heRq4H30H1jZ2UGk0yMjKRN3GLWFlYyt6Vzm6lYSDqzvadesjxBn1N7OxtUdAleoIqkWOjXY4c2Qf1NQou1JVOHt6obJcgV2b1sK5xDzMG68VhfO3b8WwftNE37XASkEiKnEy9CC2bOiLnyY4QK2WYNCQWZDLGuOLCd8LB8rgWnXh7VMaEX8vxdTTHfFAoYDm+mXA2gXW8lycu75YXOx9MfwD+PlXQL9Bg8WFPhl8pKcmo9VbbwuDlKOH9mH9jkUi5ZLYNFsBN7n2AnNaP+DYbic4y7XGHrqLeUeZgUDTaKN2P3XZAitzJ/iXa4G7EWdwL30z/m03BLC3RMbWUHhV8oVnQ62VO0EmBz9Ns0XbSkpUruAPPz+/1zrXxHs+TIvUqHMhyVFBo+v2q9bgn2/PYvvvd9CxSyls+ecBLodfE6mVFHnT2elTtIKicdeuXcOBuCVArAQ5yBLjvHjxYhHtep2QAQSl4K1YsQLnz59HxYoV8dFHH4nPlaCfhtEdqo0jUlJSsH3nLmzbskXUHHo4V8a/s9Jh/ZTatmw18OFvlvh94nl96vEHH30MX99SwgGSarjI0h/ZSmG2Ya6RISNXG+U5fMwOdQLNUMY8R0ROt6eWwNUzPkj0l8FFrnqi5wz9UEhUQK0ySPh6JjRmcjhZlEDknAuwtiwBH2d/pLmpcCJ0H2rXb4xSnm7i/ceM/RKnjh/B4UMHoVblol3nNvjss89w4rTWtKZb5w5CnJDYp39f/ovbZn6hKUVmHjqRRS6iNP46cSZEvAawsbUVj8/cc0ZdO61rqhh/4Riugbe3tg8fRWfDw8PFeguDfwdPnrfNc0OAhJru82YY5iFswc/kE5EWbyTDDwkbhzBFCborTmTevyPS5fRWjQZYPqVQiBzeQmxSxO/l6+1AH2l7zC+bgzLu5XE9ywrDFrSF+yUl/t0+E8qsTLz36VeiPs3KyhoVatQBVLnwLV8BK+f9ioZv5aBU/15QxcjwYMl6LBjZERJHC1geNUfqtU3C5bFD7wHi3/q6TdsgPTUJUoWZuCtPpgDJiQ+Qlp6GWk1bo0HbTqK/VHpqKtJTUpCZng7v8hVELQo5vVF0LTEhDnN+GY/kq976fk8ftZLhx29i8dfy+fhwxFjcj47C9199gLgrZaDQJo1hw+IScCi1CRUqVUHfgR+Lu+Xf/DQbEz4fgt37ZzwxRpXqu2LbSi84y3MRlmKOkMCh4rg6dn0HSYkJ8C7lg57vvocjB/bAtbQ5Fv0VBHOZCk7yRw1y6fjWLS4BDzk1BX+0b4UUSFFJhCEEfWJrIkpj6j4fpGXIMLbtUnQc1xQNmjTF0qm7EbYiDI2CRgMKmahTytNbTKX9cKnm5k3QtWtXERULS9iOqlZdoHaxE0ohKeoSYjOvIfOeLab/eF2M7eDBg/HLL7/k6XdGn/np06cxc+ZMrFy5UgiARo0a4dtvv9VfVL9uKLJH9ZsvCxmZjB07VqSMKqQWKG1VDQfPZIrmzIbcVcoQmuaCGcsscHHeSYz/eqKoy6L0Ux2UHZqcoQR1sbYxk4v6K4qo2ZkpxE8oLFC5diz6/NEG6VIFTl8tDbtzMgy9WB6zplyFq1z7nrrU3BwSkrHlYBavgY93eZyK3IeErNvie5IlicfZO7dhl2qP9h06o2fPXujRrdOjAx7Y94lzrVChwhPr3qRAM0zF9fX1FfNoy/Zdj8SUQX0MPefh4YFhTbajZnh1VLVJFQL542V0s+IaJk+eLLYjF0equ/z2UAC+bHBFRHqPpdlhxqDNaNiw4WuL3DIMwzCMMZBoDIthTBS6W0t1KRSdorvfRYVKlSrh4sWLGLS4H2a3PqIXLgR9qnT/XafTnnY9QiYUh1Oc0cguQf/8rlQHjJnaGV5RN7Br35+Yv+kIzMwtkJmeBlf3kkhPTcH5o/tRJqAiNiwaiJnfKWFjIcEvi1Pww6QY/b4dXVwx/pcFKOVTRrw5vTYjLUUYeTi5uok+ZWdPhKJmw+bC3p7u3Gfn5OLqmaPw9C0nGmJThMrcykqIvYirF/DP0nm4lHwWkavyuh32/aYh/lm6El98Ox1rl01Emfo2WPuYB0S7T4Jx9ughfDZ+Euo3bg5HRwchEi+EnUPEjXDcuB6O40cOI/zKRYTdrIJAi0z9mCwMK4Vv+ofjz3XbEBlxC1s2rsOaVb9DmZODqNuB8JBrxaBowP0wrTFDQ151WhtzHdr1QJvJjdGiewIuhzvh17aH4P4w/fF2jgzeCm2dn1INvDXRFbkn6kHq7IjBP29DZ/do8VymGgjpaoVLR8+LuUv1Vm+CUaNG4ddftfVvhgQEBODChQt5Ui2LA7rvV/9x76BR+3gcOeSNmb0P5UkfprTEnrObYPuctTBTZeHb7396rrjJUqqgUmuQkqmESkVpwtrehVkqFbauWYFrF8IQ3GgEkK6BbWwiDkeuhKS8Pz6f44zKTrHYGVcKymwFbiS74O4hT7j+G4k7kn1Iy0zBiNFfwsLSQjghkqwn8w0SIsZ2y3zT6NIgdTVqdE7xcfH4avwYUXdJj3V/xiZOnIgJE7T1r7SOInPr16/X34ml19PnQzcMXlcNJMMU5esQ3XHUaTMJcoU20yC/5CqzELr16wI/N+bNzqHdZ28L0zVjkJaagmZVS5ncHOJ0xyLMzp07RVrZb/2X4TfqG1WyGvYdS4eDVCMMB9790QKLRmXBXvGMJrUioqPM85yLIhsZPlKYX7dBVkY6Eh8kICbyJtxKeguxRDViAUE1hWPdwmm5cBL71mDKR7aIy2yNRb8sQ1DNehg1ZQYU5maIj7mLlORkSKUyXDmzBVXKLIQsUYWZ8+zhV70HlDnZiLt/D1Sd4+LmiVIBlYWIy0pNwZWw03D38hEpkm7epWFr74DMY6k4mO6FRtbJ4phPZtogNsxM9GWqGDQTX2/XCpZ0NTX31Z7XLWqim+MhomC169VHTnYGHsTniNRHC3MzTP1+Et77oiT++NwCF25WhY08O8+YuLoqce9OFO7fi8Kfy37D7h1b8PexWihnnwIPOaXsabcliZKUCxxKdsPcGd74ZdwFBJhn6QUcuTL+tLIqDs/7DYfnSdB9Ygu9QCNIoBlG3H4dk4pWQRsRaNcbcz9vgz0drqOs333MH3UD1y+eEzVWb0qgERQda9myJX7++WecPXtWRKamT5+Otm3borgRFRUlBNqI+R3xU/tTQnz38okU84qav+uYe94Dm75fAE/Pkhg1+usXRp8sFFohS+mOadm5yFVpJ49CJUXbt7vi9+i7OLB5IuwdnIRpD9WHyS+exNg62aga8j7MbUpCei0KN2I2QaXKRqxTLuLi7+Pj4SPhaGcjXBZ7dO0ook3FBUpDjY2NxdYdu/Fen15CtJEZzuw5C/AgPgY7duwQTcuproyicDpIvK1duxb//PMP5s+fL/64t2rVSkRTqfcfwzDPgd0dmXzCviH5h0VaEYZSfijdje4Wk2C7ePcMXL2Ant+2Acp7446ZMx5kb4K9QisUiDQ1cD/XDHFKc0y7FAzHfZGYMzpFCAySa9sSvWEeI8GdtHA4OLnAytYWJUuXxdn9f+HIvlBoIEP95u1wJ/ImBjWiu9qPjse9bRoaHG+HiNtXxAWSk4sb1GoN3EqVxZ5N/+DLQUvhakZyRYIG81Ph5Pu5ED4hzd+ChbmFEGxEZnY2ktNSYefqAbm5BaRyBZS5uagYXBfr//gNY6cPRqUuNyDVaHB6lR9yUzbD3BLoVIGSwLSQQNuQ5IoMlQKz19RHeuQOBFasAnt7ByiVOTiwZxeqVK2Bmb98jz5fB2F67xhokIYa1YCwDCuUlOeKMUnXAGv+rQyZ7DDOnz2N7Vs2YktYCJo7xj4lwRSwlQGdKoVCjUMID6uDGYts4WiWjcXbK+L34augVJ2DvYMDlDlKRJ1Oe8Ju3xAvi2zEpIdDdXEmslI12LvrUWNyShXctGkT3iT0mdJFLi3Fnf3794ufPZpG5fl8InLM4SRXwU6mwoEEJ3ze5oAwRiHTlpxHGvuFmCtkYlHmqqGmms1sFRRyW3wyahyuXgoT0V3qNRZUI0R8h1YumYuzx5bk2QelkJZz8Uff/v1FjR1Z2584fb5YCTTDNgo+Pr560UZCjQxPyCafauqehTBN6dZNLAzDMAxTlGCRVsShC7Lt27djwcIlmPDVOOzZ7wh/u+vQaK5DUv/RdiQGruWY4eMdbXFy6GKkZ1OK4xkRGbtywwm9v/LH6VQPHNsZCJfzZ5Gl3gNLRS6GdaiF8yfK4eM6QObnEgz8xgaLp0+BjZ09TqX7oq5Nqj4qty+yLGwld0TtmLObO2Lv3YFULofCwgJrV/2KGUMc9KLOWqbBO4O6YNXC+WjUvjvcvHxEdOHgjo3wLuuPUuUCRPTNwdUNOZnpOHVwN8pXroZyFaogbOnPcLveC/YWJYA7O3E+7BgsbBXaG38GDaPnzQlG1OqrsCl1EOfPn8CHQ0fi5vVw+PkHokGjxqLBdeih/Rgzp77WlOHhWDkrctBnZzNUKn0fx7eVx8E5C9CgEfWyUghXufI22iiezrGR6oR0r43NpT5X2qv1m0dD0b6i7hM4JQxS2rZuh7favY3t27di147tmHmhNd4NvAilRgoXWW6eVLqEXG3URSPRwKe8O9zcglC/fn0MHDgQXl5er29SMfqazzup1qj1sIaTPpp7mbaoWjFU+1giwYIFCzBgwABRf6czn9BbyL8EgQH+uH79GszkUmEuQkvVatVRM7gGlCpKztOIOTZq7NdISUnGpbDzYt4FVakKJ2dHYUv//ru99Ptr2qhesf30Gjeo88Q6cuR8Get/hmH+G2zBz+QbDqXlGxZpxYC5CxZh8sSvUcE/Df52tk+tQaP41aRbIcjeaA8l0lE6oBLGz1kJtUqFuOg7mDv0Z5w/+jtsrCXYfq4cSlh7C2F3+J4DyrokiX1YSDSYMj4bN490x/ELf2LbJneU6GiO2Fwz/HQtBNmbbRB56xi8y/gJ0wWKjF06dQyW1jYo6ZGlrZF7KKIoQhWZXRG5yjW4dOY4HNw8EJf4AIE164kauKSEOFy/eBZlA6uIi2GP0uUhlckwZeE/+O378di56w9kZWagVOlyqN2wGarXvCiaR5dUKIVA25pUAhFrr+Fq7Ha4yTzx7dT/oV7DxrA0N0Nq0gOcOHYE3t5aO/HDkaXwlst98TtdAF/NsMNf/eZhh6MjkhLXoZSPL9q81V5vhHE62Rk+rjFa8ysAC26VQV2PGGSq5DgQ7oqkuyqYQSNsS3I0Usw9VRE/9toBr1Le6P5OL5Gi+PuypWjatCk+b70ei/z9cfnyZaw80xDd3bTOdiT85hwPps5oGDNmzHOjBYzxoWghuQv2b3IB7ifKIsAyBTezrdG9+TVRe0dGKj/++KNIN9ZhWPtFwoEs4Omz1ok3irTpokA66tUOFiKN5ri5XCZuVJCPCJn1U/81ciclaJ45OTqiQaNGMJdJYWtrIyJnhuYsDMMwDMMUH1ikFXGWLF8hmuv2GGKBj3s7kRF1nud1kaVMDRCfZovciEjk5irhXS5AGHOo1SrE3r2NTybPQFzMHThk/4AS1rHiNXT5V9VdK9B0wq+EPAc5tStjcp99GPeOUoiJchbZCLp4G1v/XoRcKPH5kHmwc3BCgioXNRu1wI41f2DdHyVFQ22deFx0xw/KE1qjkahb1xF9+5aIoFGxf1pKkohYla1cXTxvZmYOZwtLWJop8CDmHt4bMR79ho9FdFQkYm6GQ2qxAD/1t4VGoxT7X3y3NH4bVw05irXwKV0GS1dvhKWlhWjIe3jfblSsEoTgWnVgZqaAu4cH9k2JwU+/VkBbjwjcyrTFb5NrkA8c6jdoBHd3TyHuVLk5UKnVcHN3x6ft7yHx77Ko4JiALZdK49sO2tYFMokMyXfK6O2+ybTeSqLG6JphONasPzZtmIkmDeuhVCmtODx48CD++OMPbN68GVeuXEGfaocRuqQn6gTdw85jZbFyqLZh9aeffvq6pxHzlAg1NYunNLnmlc+Lz4FMKqh3GPV7o/TGF6GrF6SmyKtXrxYW88TjkR+a8yTSvLy9ERJcFX+v2wCNGlCpJZCSC+jD7zDNbYqcde/S4Y3WIhZGOHrGMK8Z+uNOi7H2xZgcbMGff1ikFWGoCeunwz9BnRAlfunvSW1yxXpDq3b6pzFBJcHcOxVwe2YqIq7+IZwWe3w4UkSmaItq9ZqKtCrnEh7IiaVInFak6WrY7AxM+6jWy9Y/BZ06OkGjydGn/LXqcB8zv7RHliQV5avVRPjl83D1KAkLa2sc3PYvrEfktS1XPVDgVNhSkW5Zv11X2Dg5IyXpgWiwfeXMCQRWrwVLSzvER56HVc4SREebI0PWChISfg2aiXRLarJ74N9x+H227OGFrvZvQYhzDD7aNRUaqPH99PmQyeQ4duQgatWtD3tnVzEmx48dQeUq1TBqzJcYM2oYHvQriyNe1fEgIxpHT8xEo8ZN8dnn4xARcRO5udpaN7lUio+HDMe0qT9hUK0bwmEoJeUU7OztRXNsLydfKCTqJ6KY5K1i6acdxISEBL1Iowv+QYMGiWXbtm146623MOv9PzBLPLtHXLivWbOm2LkmFhU6duwoxPOiRYsQGRmJypUro3///qI+6r9A0a7nOSzS50wCrlljbX5yx3ZtsGHzNkilJNC0joTij53okyYxeYHGMMwbgI1DmHxi2NvTGPsyRVikFVHoorFJ06Yo4euCRQvornquXjDFq4A9sZ6IuJuDqZ+HI+FKAoBwIVZqNm6JyiH1YWlrJ6JXtvaOkCvMcfXscbh6euH4wfKoX++esKAnJ7tFsQH4wvOKfqKQXMl1Aa5k2CHQJl5/l/9ihgOa1GqJfw9+h6jrV0UDa3MbW+TkqnDj0nkcTKuFtnbxIkWZ0iiHVrkE+wWu+GqSAu6lSiMt+QGs7B2RlRCPclVrwtrRFYc3L8J3H/wFB5lW4C3fdxrTZ3iJ5taU6rh11RL8MVsFW6lWoNGx0BhcTndAGa8AxKdHw6uULxRm5qjfpAX2796JGrXq4sTRwwiqXhtSiRpW1raY/OM0bFi7GqFhO8UFcN/3BqBZixa4cSNc/KF61EBYIlIWv/95Kk6fPIG42Fi4e3iienAwfv35B0jUUuxPtkUzBxrvR1zNModFVLZw/vP393/q50lOjbdu3cKMGTOEPXhQUBBGjhypF3RMwVC2bFl89913r23/dKPhcTZt3SF+kiDr3OEtkXa5fMUqsY4jSAzDMAxjGrBIK6KMGv055q/zR68q6ZA8bNqsi6BdyrLDt6P9cXHPApQuXwEdRw2BmZUNKoc0gCpXiVy1BmYWluICkSJQZHFfOqAyNc1Dyy79EBK0CI1/G4AMqQUSTzrBsUsOepe8qW2+nOiN5GuOGP27HOZzHVHWIg1hmQ6YdbAhKppnw95eir5NpsDLLgdXoyUY8Y2/6HU2cVUznH7rHEZ4XIGtVNtPbEB7K/yx8i6mj/4ATTr1glcZP7h6+SIp/j5u37oGr+q79QKN6NpQjg/6HcPqxf9DxarB2PLPcth956F/ns59d6oDfp7TDBrFKnh6eovG06GH9qFy1RqoWs0LIe5vof7b2rG6mtgeDs7NxWuHjfgcapUSNjbWSHxAEb1cbV8lqp5+iLb9NGBuZo669bRRD9qG/teseUv8b9YM/PxhB6zp4wcb+wzY22RAKpNj/zQ5dm6fI5pB6wwpngYJsqlTp76G2cIUVp4WJX23Vw/xMzU1VQg0hmGYAvF8MFKWookGQUwe9g3JPyzSihh04bZm/UbkZN1GbxJoj/3rdz7TAp9/3QQX9/wiLPAnz12JtMxM0VAwKSlRpBc6O7og7l4USpXVRnWSH8SJOrX0pETcvxuBwWO+x/z3xohmzXIzMwz/JRu/z/kcMkcg5ao9XLdE4uC5Qxj2WW9YNg+EOlEOr70ZOBO7Fau3BMDHLkccVwUPDQZ9cBP7N2fiwnc/A4eHYOTSK3mOt1n/1pjQdy2qNmyJ0hWChEBLiLmHLX8sQJ2R7tBo4vTbpqsluHixLGwVJzHz9wNIS03D7Rw5SplpReoDlQRfzGmLyIXzkZBzDz37DQKkMjSvG4byLt9BKtHo7dTp+PwdN+JASnlIpVZIS0uBVCKBUpn96C/KY3+gdIJM/MPzcOBJdHXr3EFEOOLuR4u+TDsPaI9Hh7e3N2bNmoUhQ4YYZQ4wpoFOoJELqQ4yHSERx4YhDMMwDFO8YZFWBFAqldi3bx+aNWuGf0ig5apRwo3s7POm1VEa4axbQTA/niYek8uiUpWLaxfOolJwHcTciYC1vZMQLpSCSA6PZvIsHPprDLZtvojERCUsrKzRoksfTF60DjvWLIdzCXekPEjA1o9+gKuHFxxdSuDwpfOwc3RG1La/YL7PAj5+gTgSfkm4Obq5B0ADpV7nePlZwc3LFwmx93Bm5684mF4LrWwSxfMxuVJsO1wBNvZ7EB99B0qVStj125ZwR/8P7qBPUIZoyk0JYSlqKRQaDUpba/c9eYA5tm6wxjtTG2DMRxdhJlVh1vE6yPnjhBBolYKqo0vPfgg/uw7vt9rw1GbepLM6NZiHjQcGQ6WxgkwmZJh2O902D9foUx4NVHHP7l1gZkb2II9qmMix0dHRUaxv0qSJ/mKbL6qZp6FzfnznnXeeOUCGc4zIyMjgujSGYV4vwr7YSKE0Y+2HKVpwKC3fsEgrAvzzj9Y98PeVq6FRa0TzW++yLRB6OwJ1SlHKolZEUAphLdcYXKrUBKXUfsjKTIcqV4WaDZri+MHdKFexqnjtpZNHEBRSH3JVJDoHjsJHNYGcn3zxxb/1cGFNDjat+A0alQp9hoyBhaUVMtPThKC7eDIUKlUu6rZsj1qNW+JBXKzoXxZ5/TKaduyJrIwMrIlJhX/pSzAnn0kN8EdkIEIqu2Ddpl+FwBm7rhWONA2DsyITf4VVg9UppYjYqVRK3Lx0Dt5+gThx7DusGpquP3/aj1olh7OZ1qhER6fhzTGhzwLMOjUAcpkblHE3cVd1DPYOThj95WRE3LgGF6dHUQjCMPJI4+ZimY4mdZbjwLGPn0zJ0Nei5RVnXl7eepMHQ55nDsEwz4JMQwzn14ugSDrXpjEMwzBM8YZFWgFDtt5TpkzBunXrIJfL8f7772Po0KHi99zcXFy4cAFpmTkwUxjcTdcAjk7O+H1FOwSM2gAHxaO7VDlqGWRZSmRkpIlG0BnpqUhJSRImIdRcOrhhUwQG1YRcJkN5pzmwlD2aCIPanMT7+95BYJma2LVuJdr1GiCOgyBHyK7vvYeQsnNhLlmD+YtX4lJkVSHOKtasK9Ioj+3Zit/G3cP9KbVQ1f4+DieUwqW1fvBURQjTkgoh9XHnl0XYe/oTZFtKYR+eBrX9TWRnZqBuu27ISEnB/agIuAVrnex0kOAraZZXbKWoJDiwPxByxRbsO7JY1NYRJb19MOTTL5AQHydqyO7FlUBktgI+5so8VuaGP+0t40R9nkLx8OtgYBbyOHxxzBgTYe2fo0J2djbMzWmmP0lWVhZSEuPx66/TkKvKRXDNEHTt9LZoE8AwDFPcmlkfOHAAP//8M06dOoXo6GhxfUSZKkzRgi348w93Qi1AUlJShFkEuceFXw0Xgowc/ahBLjXKdXFxQbVq1fDJ4A+xfNliZOdo66V0AsIvoCKWbAoSKYFkPX8+ywK/b6uFjNh9eBB3Hz0GDcemlYswsmdrrJ73K1bM/gEjujbHkA71MaBFNUTcidIfC+3SXpqLVD8zqO9KhHvi4e0bxZu5unuijH9FNKw4CdU9rqOiezZmjAMUmiOYPLgnkh7Ew8ndE43ad8P9/Xtw+VcvzJ/XHNfm+sHrdByOHF+PynUbo2azt6BWK3Fi7USknlmD87eWYv/ulWjTdzAsrGzgE1AZV06GYs8xF0QqHxkqKB+KJt15H06zQ/dd7SE7kgaNWo0W7bui34fDMW7yTxg5diIsrSy1PaUkEpB53sz1A/BXkitiVBLEqIBkVd7si9BoS4z7wqBZ9MP36d6lo0hVJGFWpUoQGjdp+rqnBGNidO/eXUTSqPn70yDxVqdOHYyZNAYnDipw85gFFs88hxr1/JCcnPzGj5dhGBOz4DfW8h9IT08XDsezZ89+XWfHvAF0123GWl6FOXPmoHTp0rCwsECNGjVEf9pnQTcEevXqJVy4qURlxIgRKGg4klaA9OnTR1ycrT7dEO3dokXt1dTjAZjYaSO++OIL9Pq+F6rWScORba7Y8usfSExMxLARI4X4oAkkU6uh1LRBn0/NsWfveqTEUS1aGGzt7NF/xDhEnxuNldPNoJ7pj3kXK6C25h7sSqRi+mIr3DlWEtO/C0W3NXbiWOgL4CZXwc49CWnQCiR7J0fIpTJcPX8KcjNzePmnGNjRAz2+rIg7kcn4a+4vmLJ8I6ztHdC+70fYuPxHlPDygWMJd5y5cAY29o7oNPgzWNk6YLhfBZzetx03L5yGZ+ly6PXZN3BwLgHLlEUoaRkBi+x4XJsVji9CeuHDSqcRluqMGg73UddaW2eXqJJg3HdtoNx+C7dVhyCVyhAUXAfOjg5QyCTasZFIROpnTq4SZnIJrLNtsGFVN0yvEgMP50SUsEhGTbs7KG+ejpuZjpiypDLiYmciNva+EGMP4mKQo9L2MevcoZ1432pVKhTUNGFMoCatZMmST31+5syZOHv2LK7eqggnuTaabCcFdm5wQJs2bURjbYZhmOIE/dtGC8Pkh9WrVwuhRUKtXr16mD9/vphXly5demp7I7op6urqivHjx2PatGkoDLBIKwDUajX+/fdfbNmyBc36N0QX92j9c+NCrmAigLGr2+KbBieE2Bjidxkfe/bFsmG/Ier2bXh4eUOq0kBKcVA1UKt+EzRs/hbOnDwqxFSj1h1w98IgjOmreHgLS4UvqoSJsCk9Wjo+B52318NQxzh942pR1wbAuVQKLH1qAFcO4+r50whp3AoyuRxXzp7A1WrWCLFOE9sqARxKKokyFmVx+e5cXDt/SkTfmnXrB9+KVbF91WIhoDZtr4Em/vHIyB2Oqf80gsKtK1r1HoiMtFREXbmAqnWbQJE6CL0r39Y2xf4VGFfBDt/W2SPOvZFtEsYcrIXjfglwMsvG4iMhUG2/gWP3/hRCtXvfD2FPja3VGshl1PgXOH54PzZtWIvkpCTIFQr4VwhCVOQNWNqWQ9z4jpA4qHBA7o8cpQyaJHPAXw4zawekJCagVfMmwkGvdQuOmjEFz7x58wCJFF5mOXma1NvJchEaGor79+/Dzc2toA+TYZhiBrXkocVY+9JlDxlCKd7PSvNmij4F7Rvy66+/YsCAARg4cKB4PH36dGzfvh1z587F999//8T2vr6+olctsXjxYhQGON3xDZOQkIDGjRujc+fOUKnU+PATdZ5wru4D6RdyW/+7uQTo3SJM/H7r1k1hnkFOhIRMIhERpKysDDRo1gY+ZfxgjU34op/yif1qUwABhQRoGnQVll55G+nGqiS4da8EJGQTCcDC0lLs38XVDZZW1ug/xxdbUx1xKssSP0UHwDzKAh+NuoqmjSyRmZqK8tVrw9wsBZ/3+A3nNiVh3dJktAiIh1wC2MrVGNplP6a83x6xlzeghIMG/tVr48iWtWjgH62/AKWzmjDASn/udCTvVr2A1SOqYMGYJlD8ko7bquPCaGHI6C9RuVqwEGfyh44i+3fvwIrli1GvbxB2XKqNpUfq4fLlc6jaMQDnjqTi8ttLsTHkb2jSJdAkWgDZcvEmtnbe+jsrlH7GF77Mm4DSL57HgwcPYGHpKJxbDWspE5Tab0iVKlVE7SrDMExhh9rR2Nvb65enXSgzzPNISUnJs1D062lQ6xqqaWzZsmWe9fS4KGWgcCTtDUHGFpMnTxYmIWSpX9alDjovL41O7ifybJf2sHdzco45YJatvyiLzdA2QbazsxPpfAopIFHIkC1RI1elEdG52Ji7cC3hDgeb3/PcdRf71QA2D3+nGrYzye64uNcHwR/uhqVE66C4JLYcpBfNkZVzQ2wXUr8Z7t2+hZzsLARUqYaZnUfiy+yxyCxticHlTuDLdrvE+7Rp6IXeoyfiyLZS2PpnDpwVueK9/Zzzmn3YydU4fswXVdyXQaNZhmn/WGHL8jQMfM8W3gqtsQe9zsLQ3IPEY64Vjh/4CZbWNlAozJCS9ADtu/ZGGd8yyFWrIRMhRYpQ5mLzv3+jSsuqWPvFPTG5JY5Atav+UGky4CJTafujWWThqyqH8NX+NkKgmSUBTgHB6N+/v9gPuzQyb4ry5cuL5VnQnb1z58JwJaskalhnPlpvocaCQy3wQf2d+Oijj7Bw4cI3dMQMw5gEdC2iNuK+AERFRYlrGB0cRSvmvIZQmre3d57VEyZMwMSJlH+WFyolIkO4x2+40+OYmBgUFTiS9oagXFiaTMN+aoD0u364ej4en1U59agvlwZIUkngVuWeePxujyhE5pghUw2cSbfGxN534ODoiMpVgkQUSSKlurRHESSCfiPDkCsR1KvskTnG2UxzdDncGrtTHHE6ywrf3q2I03vLI+mwDVrMLoVfo8vikxu18fvOBnDYG4GjkVvg5umFcoGV4GDvCP9K1WBjY4eeH43E2f9NwpeeyzE0RBvZ04mp4V+XwbrlWUKgPavNCtWTVXF/9K/+4C4ZiI68gXHHmuBsliUS1Xl7klH04EK2BSYsaw4Pd19hElK+YhV8NPJLNG/RElbmMlhbyEUk0UwuRXJCPHKVSoz8xkFEC3X7KW+eDQvpo6ghHZOdIhuWMVJY3pdCppRCYm0l8pYZprD9u6HRqHD8jkue9TSH+5aJQJshjbFkyRLExmrTlhmGYYyZ7mishSCBZriwSDMNd0dj/acT+mSapVvGjh2L5/F4exsKmPyXljcFDYu0N8CiRYswZMgQmMEcX3S7K9IXaY64yLSpjjohczDaBvYKG4waPQaZ8RYo63sRbuXvIbjcWdy/G4Nhwz8Vlt3igyNzDKl2oUASLQq5VrwlJtbC15vdcDLTGn8nueHDHR0R9dl1tAo4jlp+FzC3/Wk8+G021u3+BeELwzC6+jZsfCcUsT/OwLErv8HK2gYdevUXqY63rl1CdkY6wk6Gok3XPuj83sfo3jhvehWdw22lNTytHqVuEhSdo0X8DmBDglee1+VCAl/PqjgxdD16/9kLn1+ugxwDYXcqwxZ9ZvcGlt9EakYiKleriZ69+yHQvxzsrRQizVEhlcJCIYOlQgqpRntcpR1T8x4f1fbsLS2MWYg0jQRz/gp5tIFGA9v7KowaNUo0CmaYwkKtWrVgZWWFresz9N8LXcSZIsU/jkoUUXSqb2UYhmGY4ozdSwp9cken6+XHo2Z0Q7MolbNwuuMbuBNO6Ujl6vhhyuySsJDczfP86XRruJrl4GqKNf6aVR4//aK1gq9YqTLOnzuLO1FRsHdwRK2QEO1kNIhMibRHmVRctFHKX06uCuZysuOXQJnYEx90W4awM4eh0RwS25fzr4j6TVsh4kY4MjPS0eKtzvALrIw7URE4cXgfUlPMUalGdbzdvS+8fcrg+uUweHn74PK5k6gWUg85ylz4+gVCqdn50P9Ry/EsS/xwtBEatPoLbjK1PqVy+PVg5ErkCLaPRmhCKYQdKYVqvdaiqkWmsNVfFF0OAa7+2HZuGhJ+mYMTfk0waWZldHC9iZgcS0xa0RqOq47jUMx6yBVyNGnWCgq5FJYKGeLj45CakgoPT09hrUrY2duLn+einVHf/lGBcroG+Pf9m9jVxBrN3/XDiq9DUbqCDcxKa6BWAPJ0DRRlfKE8oRTRtM8+M7DjZ5gCZty4cfjyyy+xpX9dtHaJy1OvKZdov2+U1sEwDGM0XsE6/7n7+g+kpaXh+vXr+se3bt0SLrdOTk5PdeVjCif5sc5/2r7+C2ZmZqLme+fOnejUqZN+PT3u0KEDigos0l4jFFYdM2YM7J2dcPRvCRxlWoFGPc1ovkXkKNCpnQzxETfF3fKwsPXw9PTUv37ZH1JUrVY9704fm6gk1MwVUshUGuGGSC6HVKNma22J3u9/hKSO3ZEQHwsHJ2c4OrmI11N/NUN8fMuilG8Z4cYok0lFGuXVi+dgY2cHG2sb+JbxQ05WFi6eO4VbVy5geZwv+rhGiPc7lG6PoXvbw3GHGT71bIBRAcdgJtFgWXRFhP5dFTb3cnCyVGVYJAJOB6MwwLEzAgPvIDHdGvd3eaKCdaI4hpTMOMQfXwbl0N7YVKcnFA/UMNtxDodi10FupsDAIZ+ipJenqEdDzW3oXS4SaSoZBv9kB5toT7zdsZP4B5zukIxsvR+trvihnEW2iORN3lQVElzG+b1nxUKU8UuDIssOyHr4B0Spvcg9d+7ca5kLDPOqUDuOlStX4u0qR1ClVXXsXZQGB5lG3OiYsZG+txfRunVrHmCGYYoFJ0+eRJMmTfSPqX8s0a9fPyxdurQAj4wpSowcORLvvvsugoODRb/RBQsW4Pbt2yJwQlCq5N27d7F8+XL9a+hmgO5GQVxcnHhMgq9ChQqmJ9KoKD4yMvKJ9R9//DH+97//4b333sOyZcvyPBcSEoKjR4/qH5OzC0U+qN9QZmYmmjVrJqIhXl55U+sKAjo3ypkdOrsHHGWn9etJE/Td0hAbJuxH2t3LaNCgAVasWJFHoBHURPnIsVO4di38iX3XDQnGkWMntc2toXV4pPS/XCHS1JCrtGrO3M0FJVy14ozWk6jLpSOQkFjUiNdqQMYjlHephipXDTsHS2SkpkIukyMhLhbWNrYIDwtHmfKBOHVoD74alIY1X7eFpXkOrl0tCZfNGmQf3YdtJ+7g3PDe0JgD5lcVcN92F6HXF0AhtYKNxB5xqiiYjbKFbbPhkKgl8LoVjUuKEzC3sMT4Wcvxx4xvcfXECpRLPAuFrRNOPjgqjk2Zk4OVS+ajZet2yC0djb/8bwut6ipTYdnYRJT0DoWZuRlW/7kSvt6e4h/3ymWuIcS3CaQRlsjRJMMmUAG7u3bYt2+fuLuSdGMPbDx6AgptTFAekwqFQgEPD4/XPi8Y5r9AKRvU6P79998X/x6WKKtA+2GNcXFXJK6d+RedOnfFgQMH2PCGYRjj8XhReX739R8gB2y6yc0UbQragr9Hjx7CUX3SpEmiUXWlSpVEaYCPj494ntaRaDOkWrVq+t/JHZJukNL2ERERKAgkmgL8JpBKNUzToQuRFi1aYO/eveJLSiKN+gBRYbwOUrQUMdExePBgbNy4UdxdcXZ2FnVFZFtNg6ur33oRZONJdrAkqAydh/ILfajU6bxlx7ewcU64PkUwSS2Bi1e4SNOjc61du/Zz90NWonTej0P9vJ4GfaQUUaNJTclQGjX9JCGmgUqj/Umo1VrBSA6J2t/pH2VtpI/W03b0vpmZGaL/mo2tnbi78M2nA1GpamtYOlSFPD4Dty9sQ2TuRbHPsmWC4WleA1lxcbgUvxvpSIZUJoNapYK1rT2yMtJhbmGBUmUDEH0nQvQm6zdsLEp6+0Cj1uDSmaM4c+ww7t6OgEYGrD5aG1426VixvyRmDdyIr9e2woQ6N/XnSsYqQ4Y1xrpdfyEhPh5yuVz0xiDhbmFuAc8SJaGS5CIiMkLUBpKDI4W+N27cigZNJkIjByQ0BdUaHA+dhtDQXcLWnGEKI6dPnxZNNiniSw2wP/zwQ3Ts2LGgD4thmHzyuq5DXvU4GtX9CnK5tpQgv+TmZmH/kckFfm7Mm51DoZfviutGY5CWmoI6gSVNbg4VaCSNOnsb8sMPP6Bs2bJo1KiRfh3VYbm7uz/19fRh0YX377//jubNm4t1f/zxh7Do3LVrF1q1aoWChNQ3XUjtWr8V3/bshPdqX0aORoZvFpYGEC6ify8SaMTTBBq9VhdtCz1+GuHhV/XPkXMNRdUIme7/hPASMgyqh33Q8FCg5eRSBE4NFQk1oc40uH3rBrZvWoub164IsRtYuRqat+8Ke0dndO49AGtWkOX3VpiZWyAzNw1Oru6o2ag59m76BzeyTuqPg5ph123RHlDlQmFmjuQHcTh/4ghioiKFEUj5StUQVLMuUhPioFarULN2Azg7OmHRnF9x6FIw6tjGCNFYve0V3B3XHHPHnMHIfQ6wlWrP4WSqA0q7+CElOVmI8xIlSogQN4W2qSnh1atXUa5cOSxdtlQ/ryi03aRJM3Gy0txHzac+GTqKBRpTqKlevbr4945hGIZhmOJNoalJo2gRCSy6wDa0x6T0NLrwdnBwEBfZ3377rXhMULSMeo4ZNqujlEEKaVKzumeJNEqRNGyAR6r/dUDnQYKAjm9SjzX4UWqBbDUVQYWhXbt2r3wHnARajkor0AidQKPHNB4nTp9/MkXyYVokjayUBNzDIVZACrlMjWzlQ6Gm0uD2ndtYOPsXlKtZAQuWtUJ6phwTOx/B0tk/4+PPvkblqsHwLeuH86ePIzM9HV4+ZVAmoCLkUimq1wjBjauXhBW+r58/bO0chEskpWGSTb61uwdKtu8qRGROrlq8JikuGhpltoiqWtja4tSxQ+L4gq2TxTHqugx0fjsHa7+LxehJfVB/wDncf2CDbX2cUaVjDGxtbcUc0UEijZanQdsePXoE7/acjvtJWkdIM5kEkyeNeqXPg2EYhmGKFQWY7sgUDwyt842xL1Ok0Ii09evXIykpSaQ46mjTpg26desmIlLk7vPVV1+hadOmQpxRhI2sNSnK5Ojo+J+a1VGX+2+++QZvAjpeSk2iZnvHjh0TQoJS8fr27Zuv/ZoZZHLqxBpBdVV1Q2qI5fG+EFQgeeDwUSGIDSGHSLLyz1YCSokGB3ZtgZOrI/auzoKrXJta2Oh0KdT0v4hzJw+jQdPWcHJ0RMMmBp3cJVoTE7nMCtVr1BSrqC2ASLnUANZSiaiBU6ll+q8aWefHxcZg45qVCL90QazzKOmF7KwsVPu0PuSS+3mO082KBC5w+vh+lEVfZCUq0ayfCpP/N0HUMT4t4vgsKC0y+VwsFAoZNDIpkKXE/6YtxPDRH0D6sDk2wzAMwzAMw5i0SKO0RRJlhuYZVPSng6Jj5NBCgm3z5s3o3LnzM/f1omZ15OiicwvSRdIe72JuTCpWrIi///7baPvr2fORKHsZdGNBqZc9u3fRr09MTMSGzdvE7ySwLBVyEVWLuHEdPac0h6v8jH7bSpYZKFuuvEiDpCbShjfHyA2SxpwiZoaWq/Q09TETdXAajaiNE/Vvou5Ng8y0dMz79TuUCXHEmY1VYSXLxay1Npg98ih2DU7PY7lK77V5p7mo44uNj8UX84fnmScUYf0vkPkM1dxJKST5sIPa5InfYc+hzaLGkWEYhmFMFeru8bDDh1H2xZgeBWnBX1woFCKNXBCphmzt2rXP3Y6c90ikXbt2TTymWjWKCpHYMIymUbO6unXrPnM/FIXjTvcQY2YYhSMoXXLaT98hMVwGKl3TxZTS1RIkJSbA3z9A9CkTwaaHIo0aaIufhiFpgy+UQkTTtIYlUpVWcJGxyY59O5GenobtS71QQp4utp32TjZ2/e2JspZp+qa9IusCwPRRB0Vz38OHD2P37t3ic65ZsyYCAgLwX6HImybdC+422tdqlEpYy+TYtGkT1qxZgy5dHolZhmEYhjEpON2RKeLujsWBQpHXRe6NVGf21ltvPXc7stKMiorS26STlTql91FzOh1kqUkukc8TacyzofEcOHAg/pr9F6adr4BYlQx3c+WYvLUOYu/fR/2GjdC6eSOU9ysveqqJvmoSiVgoYqcwUzzxbercod3DVEhqRC0Xfd0szGQ4f/qEeN5VrtLfcSG9N3uhJxJV2qgcQT9zSKVJZMLdjqB6Q+p/8SoCjQxnzpw5g/gHF5B17w46LA7DiC3H0HxIiD7SyjAMwzAMwzAmG0lTq9VCpFGTQqoT0kFW71THRRENEmVkZz9u3Di4uLjou4eTxeeAAQOE7T7Z75M1P9V7Va5cWe/2yPx3PvnkExGtGtN6Daa5uyMrKwtJSctEHd/XX38ttqE+dPXraGvPXgZdxI7aBsgkUmE4qVI/ar9gSA37ZPx93xsDPKP0N/Sic2Vo/+X72Dh5obBfpcjrqwpxXc1ZjlKJ8eduoqnDA/EeTUbE405iQ+xbckTMS65NYxiGYUwSujFqLL8P9g0xTTiUVvQjaXSxTc3kqH+VIWT7HhYWhg4dOqB8+fJCxNHP0NBQ4c6ng3oGkUti9+7dUa9ePVhZWYmaopftkcY8PZpGNXT79+8Xn8unn36KS5cu6QVafuja6W3975UqVtT3OjM0f6JP7oMae7AzxRlJKomIopU2U2Hd4P3IvueH7l9VEE6fdEyvAs0fEvixmjuoZpuoj9YpJEDP982Qm5v7yvtmGIZhGIZhmCIfSSN7+qf107a0tMT27dtf+Hoykpg1a5ZYGONBqYsNGzYUizGhz0vHvHnzhPBefsEDg4Oi9evNpYDM0QmjhgTjk++u4wPvGw+PSTthF72XgmXjckXUlLrHvwpkNrJgwQLcy7GAg0Wmfv2xo1biJ0XSGIZhGMYUkZABm5Gs8421H6ZowRb8xSCSxpgWf/z5l/jZt/c78PPzEymFS+bfE46Pujplipw5+VTEpd1zkPTA8ol9kFir36+RSMl8FUiAUTot0alTJk6k2yFCaYaZF/xwaN4N+Pr6CkdOhmEYhjFJdH+QjbUwJofOa8BYiylS4JE0hlFn2UGCVP2XkGRZjaoO2HZWjbGt16P1tQqobK3t7aZzeww/n/DUCOzLsHTpUqxcuRIdG3dF1L44fFIeuI4YJGsuijRZchnldFmGYRiGYRimoOBIGvNG0TlzxsfH69NaMzMfpRvqhNj7w5IePtJgcO82+Pu+m2gJkK0GvjgfhKSb0fD3939lkda6ZRuoTlvCUeIKB7igmryGaDTepEkTvP32o7o5hmEYhjE56B6o2kgLB9JM2jfEWIspwiKNeaO0bNYYZjLA1dVVPCYb/Sv7LiNeJc2TEREV98gcxipRhe8XdETlBR+i6m8fYvvG2shJTkBIiNYy/79CrRx8PH2QmZqpz5tWqM3RpEnTV47OMQzDMAzDMIyxYJHGvHF69nzUQHv06NHiZ4dP7HBbKUeaGtib5IQprY7pt1HEx8L5TCqcwlRwPq+CxdqTYn379u1f6f3r1KmDzTs3IbhNkH5d0z71sGvXTu6vxzAMw5g8OuMQYy2MCcKhtHzDNWlMgbtIElH/xuGDDcHidw00KC1T4JxG269sT9LfaHyxM+yuWkEiz8T2uFUwNzcXDa1fBXKFXL16NbZE/Y3On/SASp2LRdtmi9TLwYMHG/X8GIZhGKZo9kkzkrhijWaSsLtj/uFIGlOgkDAiuvfqlke4tXm7lUg97Ny5M5SaHOxMXYUdiYuxPe5P4Qj5Mu0ZnkVAQAD27t0LF1cXTJw1HlPmTERAYAAOHDigr5ljGIZhGIZhmIKCRRpToLi7u6Nx48bYenIDWvRvCFsnG1SuH4gI2VURLfvtt99w9+5dtGvXTtjiDxw4EBkZGaKZdX4IDg7G7t27kZ6eLvZHDdBf1YiEYRiGYYoVbMHP5Bdj2u9LTPPj4HRHpsCZO3eucFX86vfPULNmTRy6vBkPDj8QLoxOTk5iGxJRrwMrK23zaoZhGIZhGIYpLLBIYwocSj+8ePEilixZgjNnzgjzjv79+4v1DMMwDMO8YdRGjF7QvhiTw5gBMAlMExZpTKGAImajRo0q6MNgGIZhGIZhmAKHRRrDMAzDMAyjx5jW+WzBb6JwKC3fsEhjGIZhGIZhnjQOMQbcJ80kYQv+/MPujgzDMAzDMAzDMIUIjqQxDMMwDMMwj+BIGpNP9Pb5RkBios4hHEljGIZhGIZhGIYpRHAkjWEYhmEYhnkER9KYfMK+IfmHRRrDMAzDMAzzCO6TxuQXVmn5htMdGYZhGIZhGIZhChEcSWMYhmEYhmH0cJ80Jr+wBX/+4UgawzAMwzAMwzBMIYIjaaI+VtuwMSUlpaA/D4ZhGIZhTAzd9YfueqTAYeMQxhglacay4IdpwiINQGpqqhgMb2/vgv48GIZhGIYx4esRe3v7gj4MQK2hnEfj7YsxOdg3JP+wSAPg6emJqKgo2NraQvJQ9tNdLRJttN7Ozs4IQ1304THhMeF5wt8f/jeF/53lvz3GhyJoJNDoeoRhGIZgkUaFeVIpvLy8njojSKCxSOMxeRE8T3hMXhaeKzwmPE9ejeL+3SkUETQdnO7I5BOKeRgt3VECk4SNQxiGYRiGYRiGYQoRHEljGIZhGIZhDNBoo2lGgWvSTBOuSssvLNKegbm5OSZMmCB+MjwmPE9eHv7u8LjwXHl1+PvDY1Io4HRHJp9wumP+kWgKjd8rwzAMwzAMU5AGYVQb17z0UMilxrlJnavOxq5bs5CcnFysawqZvHPocmQcbI30eaempCDQx9Xk5hBH0hiGYRiGYZjHbPPZgp95dTjZMf+wcQjDMAzDMAzDMEwhgiNpDMMwDMMwzCM0au1iDIy1H6ZIwTVp+afYRtIOHDiA9u3bi8aQ1KB6/fr1eZ6fOHEiAgICYG1tDUdHRzRv3hzHjh3Ls03jxo3Faw2Xd955J882iYmJePfdd0X+LS30e1JSEorquBjy4Ycfim2mT5+eZ312djaGDh0KFxcXMX5vv/027ty5U2THxRhjUtzmyovG5L333nvifGvXrm3S8+RlxqS4zZOX/f5cvnxZfP50Pra2tmJcbt++bbJz5WXGpLjNlReNyePnqlt+/vnnYjtPioRxiLEWxuSQGPk/U6TYirT09HQEBQVh9uzZT32+fPny4rmwsDAcOnQIvr6+aNmyJeLi4vJsN2jQIERHR+uX+fPn53m+V69eOHv2LLZt2yYW+p3+KBTVcdFBf0BJtNIf1McZMWIE1q1bh1WrVomxS0tLQ7t27aBSqYrkuBhjTIrbXHmZMWndunWe892yZQtMfZ68aEyK2zx5mXG5ceMG6tevL26K7du3D+fOncNXX30FCwsLk50rLzMmxW2uvGhMDM+TlsWLFwuR1qVLl2I7TxiGYZ6LxgSg01y3bt1zt0lOThbb7dq1S7+uUaNGmuHDhz/zNZcuXRKvOXr0qH5daGioWHflyhVNUR2XO3fuaEqWLKm5cOGCxsfHRzNt2jT9c0lJSRqFQqFZtWqVft3du3c1UqlUs23btiI/Lq8yJsV9rjxtTPr166fp0KHDM19jivPkRWNS3OfJs8alR48emj59+jzzNaY4V140JsV9rrzM32T6LjVt2tRk5klhQXct1LzkR5rW3sONstC+aJ+0b8Z05lB4VLwmOjnHKEt4VLxJzqFiG0n7L+Tk5GDBggUiNYLu9BmyYsUKkVpRsWJFfPbZZ0hNTdU/FxoaKl4TEhKiX0cpK7TuyJEjKIqo1Wpx13H06NHinB/n1KlTUCqVIuqogyJLlSpV0p9zcRuXF42Jqc4VigCUKFFCRKXpjn9sbKxJz5MXjYkpzhP67mzevFmMR6tWrcTY0LkZprqZ2lx5mTExxbliyP3798UYDRgwwGTnCcMwjEkbh2zatEnk+GdkZMDDwwM7d+4UfxB19O7dG6VLl4a7uzsuXLiAsWPHirQU2o6IiYkRf2Afh9bRc0WRH3/8EXK5HMOGDXvq83ReZmZmoo7PEDc3N/05F7dxedGYmOJcadOmDbp16wYfHx/cunVLpGo1bdpUXEhRM15TnCcvGhNTnCckUikl7YcffsCUKVPEd4lS0Dp37oy9e/eiUaNGJjdXXmZMTHGuGLJs2TJRp0djosPU5kmBw82smXzCFvz5x6RFWpMmTUS+enx8PH777Td0795d1Bzp/pGnO+E66G6dn58fgoODcfr0aVSvXl2sp5z5x6FsjqetL+zQxeSMGTPE+f3X43/8nIvLuLzsmJjaXOnRo0ee86VzJXFCd78NL6xMZZ687JiY2jyhqBHRoUMHfPrpp+L3qlWriqjGvHnz9ILElObKy46Jqc0VQ6gejUTq4zV6pjRPChyRXGYkww/2DTFJ2N0x/5h0uiO5Q5UrV06kQyxatEhES+jns6A/jAqFAteuXROP6Q4npWU8DpmP0N29osbBgwfFXd5SpUqJsaAlMjISo0aNEsYqunOm9FBy0DKEXqc75+I0Li8zJqY4Vx6HItEkSAzP15TmycuMiSnOE8pMoO9MhQoV8qwPDAzUOxma2lx5mTExxbli+G/u1atXMXDgwDzrTW2eMAzDmLRIe9rdNrL4fRYXL14UOfF08UXUqVMHycnJOH78uH4bisTRurp166KoQXVX58+fF9FF3UI5/1SLtX37drFNjRo1xIWCLuWGICcuSsfRnXNxGpeXGRNTnCuPk5CQgKioKP35mto8eZkxMcV5QulpNWvWFBfdhoSHhwsBa4pz5WXGxBTnig66UUpz4vH6cFObJwUOW/Az+YQt+PNPsU13pJz/69ev6x9TjQhdYDs5OcHZ2Rnffvut6LFCf/DoYmrOnDmi3wrVlOgskqlou23btuLO56VLl0T0pFq1aqhXr57+zidZblNais4a+YMPPhCWwP7+/ihq40LRIhobQ+iPIt2d1J0PFWBTMTeNBW1Lr6OC9sqVK4tec0VxXPI7JsVxrjxvTGihPoNkjU3fn4iICIwbN06ce6dOnUxynrzMmBTHefIy3x+6oUGpoA0bNhQp5lR/tXHjRmGyYopz5WXGpDjOlReNCZGSkoK///4bU6dOfeL1xXGeMAzDPBdNMWXv3r0io/rxhWyyMzMzNZ06ddJ4enpqzMzMNB4eHpq3335bc/z4cf3rb9++rWnYsKHGyclJbFO2bFnNsGHDNAkJCXnehx737t1bY2trKxb6PTExUVMUx+VpPM1unsbvk08+EWNjaWmpadeunRivojou+R2T4jhXnjcmGRkZmpYtW2pcXV2FJXapUqXE+sfngCnNk5cZk+I4T172+7No0SJNuXLlNBYWFpqgoCDN+vXrTXauvMyYFMe58jJjMn/+fPH5k93+0yhu86RQW/CXGKhp7f6xURbalynap5v6HLpxN0ETm6o0ynLjboJJziEJ/d/zZRzDMAzDMAxT3KFoJkUtm5cYCLnUzCj7zFXnYFfsQpF2amdnZ5R9MoV/Dt24mwBbI33eqSkpKFvS2eTmULFNd2QYhmEYhmFeAbbgZ/IJW/DnHxZpDMMwDMMwzCNYpDH5hC348w+7OzIMwzAMwzAMwxQiOJLGMAzDMAzDPEKt83Yx1r4YUzXhN9a+TBGOpDEMwzAMwzAMwxQiOJLGMAzDMAzD6NFo1GIxBsbaD1O04Jq0/MMijWEYhmEYhslrHGKsNEXu9MQwrwSnOzIMwzAMwzAMwxQiWKQxDFOkady4MUaMGAFTOTZfX19IJBKxJCUliXVLly6Fg4MDjM17772nf6/169cbff8MwxRyC35jLYzJpjsaazFFWKQxDFOkWbt2LSZPnmwSok/HpEmTEB0dDXt7+9f6PjNmzBDvwzAMwzDMm4Vr0hiGKZTk5OTAzMzshds5OTnB1LC1tYW7u/trfx8Sga9bCDIMUwhRqwGJkQw/2DjEhA34jRMCk7AFP8MwzOuBolOffPKJWCgtz9nZGV9++SU0BmkwlMY3ZcoUkWJHwmDQoEFi/Zo1a1CxYkWYm5uLbaZOnfrcyBeJu88//xwlS5aEtbU1QkJCsG/fvjyvOXz4MBo1agQrKys4OjqiVatWSExMFO+9f/9+EUHSpflFRESI11y6dAlt27aFjY0N3Nzc8O677yI+Pl6/z/T0dPTt21c87+Hh8cRxPg6de/PmzdG6dWv9OFD6YqlSpTB+/Ph8jXdCQgJq1aqFt99+G1lZWeL86Vy2b9+OatWqwdLSEk2bNkVsbCy2bt2KwMBA2NnZoWfPnsjIyMjXezMMUwzgdEcmn3C6Y/7hdEeGYd4Iy5Ytg1wux7FjxzBz5kxMmzYNCxcuzLPNzz//jEqVKuHUqVP46quvxM/u3bvjnXfeQVhYGCZOnCjWUw3Ws3j//feFCFu1ahXOnz+Pbt26CSF07do18fzZs2fRrFkzIfxCQ0Nx6NAhtG/fHiqVSoizOnXqCIFIaX60eHt7i58k6qpWrYqTJ09i27ZtuH//vjg2HaNHj8bevXuxbt067NixQwgjOv5nQaKJxuT48eNiPIiPPvpICEA6z1flzp07aNCgAQICAkQqqIWFhf452u/s2bNx5MgRREVFieOfPn06Vq5cic2bN2Pnzp2YNWvWK783wzAMwzDGgdMdGYZ5I5DYIWFG4sTf31+ILnqsi5gRFN357LPP9I979+4tBBUJM6J8+fIiokVijqJej3Pjxg38+eefQqh4enqKdbQ/ElVLlizBd999h59++gnBwcGYM2eO/nUk2HRQiiVF2AzTCefOnYvq1auL1+tYvHixOKfw8HDxXosWLcLy5cvRokUL8TwJMC8vr+eOCUX75s+fL6JyJPo2btyIM2fOQKFQ4FWgY6H379Chgz4aaAhFKuvVqyd+HzBgAMaOHSvGrEyZMmJd165dhdAcM2bMK70/wzDFA41aDY2R0h25T5ppQn99jOX3IYFpwpE0hmHeCLVr184jGihiRdEtimDpIPFkyOXLl/WiQgc9fvx1Ok6fPi1SB0nMUdqhbqEURhIjhpG0/wJFxEi8GO6TIlUE7ZcWSrOkczKslSMx+iIo0te5c2d8//33IkWSjv1VyMzMRP369dGxY0cRmXtcoBFVqlTR/04ROxKjOoGmW0cpkAzDMAzDFCwcSWMYptBANWSGkOB6XGwY1rE9jlqthkwmE6KKfhpCwoqgeqz/Cu2XUiJ//PHHJ56j+jNdKuWrQDVguuPNz36oZo9q3ChtkVIvnxbFM4zQ0bg+HrGjdXSuDMOYOOLfWW5mzeQDDqXlG46kMQzzRjh69OgTj/38/J4QU4ZUqFBB1IwZQvVUFG162uvIFIMibBQNKleuXJ5Fl75I0aTdu3c/8z0p3fHxKB2lOl68eFEYlzy+XxKW9JMEj+E5khEJpR++iFGjRkEqlQoDD4qA7dmzB68C7eP3339HjRo1RNrovXv3Xmk/DMMwUGuMuzAm6+5orP9MERZpDMO8EcioYuTIkbh69aqoGyODiuHDh79QwJCgoj5oJHiozouMLwzr1gwh8UZ1bOSySKYZt27dwokTJ0QEbMuWLWIbqsOidR9//LEwFrly5YqoOdM5NZIQI3MTcnWkdRRZGjJkCB48eCDcD8no4+bNm8IcpH///kLQUZSOarwogkXHe+HCBVEzR8LpeVDUi2rbVqxYIWrJvvjiC/Tr108IvFeBhCvtKygoSAi1mJiYV9oPwzAMwzAFC4s0hmHeCCScqG6KrOFJ9AwdOhQffPDBc19DEay//vpLODWS6+PXX38tGjk/zTREBxmE0HuRwKOaMLKhJ9FFJh86IUcC69y5c+JYqI7s33//Fc6TBAlAEjsUxXN1dcXt27eFMQg5RpIgI7t+OhYSmNQqQCfEyMykYcOG4v0o7ZDqwyiq9Szi4uKEsCPHRTpPYsKECeK9yOXxVaHzIBFMZig6m32GYZj/bsGvNtLCkTRThC34849E87wCD4ZhGCNAvczIvp7s3o0NiSwyAiHnQlOAIn3UF86wN9zrhmrVqLUAmZIwDFN8SUlJETefmpp1g1zyai6zj5OrUWJPzt9ITk4W/RgZ05hD9+KSjPZ5p6SkwNPVweTmEEfSGIYpkmRnZ4ueZVQrZmihbwqQRT6lWNIfrNcJRfR0hisMw5gOGrXGqAtjur4hxlpMEXZ3ZBimSEJGG5TWSK6L1N/LVKB2AkqlUvxua2v7Wt+LUkt19X/kYskwjIlAaYpQG3FfjMnB7o75hiNpDMO8dvbt22f0VEdKvaMUCDLKeNXmz0URHx8fvbPki4xJ8kuJEiXyuFgyDMO8KebMmYPSpUvDwsJC1PcePHiQB595rXOIboLSdrQ99RCdN28eChIWaQzDMAzDMEyhSXdcvXq1qLsdP348zpw5gwYNGqBNmzbCyIkpGhS0Bf/q/ziHyA26bdu2Yjvafty4cRg2bBjWrFmDgoKNQxiGYRiGYRi96UNjSSejGofs06z7T6YPISEhwvWW2qPoCAwMFBkU33//PX9SRWAOxcQbz+QjJSUF7i72r3UOUa33hg0bcPny5Tx12eQEHRoaioKAI2kMwzAMwzDMI4xmv/9w+Q/k5OTg1KlTaNmyZZ719PjIkSP8KRURCtKCP+cV5hAJsce3p5Y7ZFCmqwN/07BxCMMwDMMwDKMnF0pAY8R9PYyGGGJubi6Wx4mPjxc9Kd3c3PKsp8cxMTH8KRURHv+8jbGvlNc4h2j907bPzc0V+ysI8ywWaQzDMAzDMAzMzMzg7u6OQzFbjDoa1MrD29s7z7oJEyZg4sSJz+3PaAi19X18HVN455Bf6byfd1GYQ5KnbP+09W8KFmkMwzAMwzCMcLUjAwVKFzMmT7s4floEhHBxcYFMJnsi4hEbG/tEpIMpfBTVOeTu7v7U7eVyOZydnVEQsEhjGIZhGIZh9BfZtBRkJIZs0Hfu3IlOnTrp19PjDh068KdUBCiKc6hOnTrYuHFjnnU7duxAcHBwgbX5YeMQhmEYhmEYptAwcuRILFy4EIsXLxZue59++qmwTie3PYYxxhwaO3Ys+vbtq9+e1kdGRorX0fb0ukWLFuGzzz5DQcGRNIZhGIZhGKbQ0KNHDyQkJGDSpEmIjo5GpUqVsGXLFvj4+BT0oTHFZA5FR0fn6ZlGTa/peRJz//vf/+Dp6YmZM2eiS5cuBXYO3CeNYRiGYRiGYRimEMHpjgzDMAzDMAzDMIUIFmkMwzAMwzAMwzCFCBZpDMMwDMMwDMMwhQgWaQzDMAzDMAzDMIUIFmkMwzAMwzAMwzCFCBZpDMMwDMMwDMMwhQgWaQzDMAzDMAzDMIUIFmkMwzAMwzAMwzCFCBZpDMMwDMMwDMMwhQgWaQzDMAzDMAzDMIUIFmkMwzAMwzAMwzCFCBZpDMMwDMMwDMMwKDz8H+/Upe9oKU7NAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "df = parcels.read_particlefile(\"output-schism.parquet\")\n", "\n", @@ -388,7 +4623,7 @@ }, { "cell_type": "markdown", - "id": "17", + "id": "19", "metadata": {}, "source": [ "The particles move with the SCHISM surface currents, and any that wander over shallow water where\n", @@ -406,7 +4641,7 @@ }, { "cell_type": "markdown", - "id": "18", + "id": "20", "metadata": {}, "source": [ "## Adapting this tutorial to your own SCHISM setup\n", @@ -420,7 +4655,8 @@ " $\\Delta x$ approximated by each triangle's shortest edge) is well above 1 in the narrow channel, so\n", " particles can jump across several cells, or out of the mesh entirely, in a single step. Choose `dt`\n", " from the *smallest* cells and *fastest* flows that your particles will visit, not from the domain\n", - " average. See [choosing a timestep and integration method](./tutorial_dt_integrators.ipynb).\n", + " average, or use the `CFLLimitedDt` kernel from this tutorial to adapt `dt` per particle. See\n", + " [choosing a timestep and integration method](./tutorial_dt_integrators.ipynb).\n", "\n", " ![CFL number for u and v near a SCHISM river inflow with dt = 5 minutes](../../_static/schism_inflow_cfl.png)\n", "\n", @@ -437,15 +4673,15 @@ "\n", "* **Particles leaving the mesh.** Because of the two points above, some particles near the coast may\n", " still exit the mesh. Decide how to handle them: release particles away from the boundaries (as done\n", - " here with the `valid_levels` filter, whose threshold depends on your mesh), or catch the relevant\n", - " status codes (e.g. add `parcels.StatusCode.ErrorGridSearching` to `OUT_OF_BOUNDS_STATES`) and stop\n", - " those particles. See [working with status codes](./tutorial_statuscodes.md)." + " here for the deep-basin set with the `valid_levels` filter, whose threshold depends on your mesh),\n", + " or catch the relevant status codes (as done here with `OUT_OF_BOUNDS_STATES`) and stop those\n", + " particles. See [working with status codes](./tutorial_statuscodes.md)." ] } ], "metadata": { "kernelspec": { - "display_name": "Parcels:default (3.14.8)", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -459,7 +4695,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.14.8" + "version": "3.14.3" }, "mystnb": { "execution_in_temp": true From 3d7d844df2d7e5d6e582b796ef2b160fd1f530e6 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 27 Oct 2026 19:53:51 +0000 Subject: [PATCH 2/3] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- .../user_guide/examples/tutorial_schism.ipynb | 4217 +---------------- 1 file changed, 35 insertions(+), 4182 deletions(-) diff --git a/docs/user_guide/examples/tutorial_schism.ipynb b/docs/user_guide/examples/tutorial_schism.ipynb index 3226fc3f8..f1893092a 100644 --- a/docs/user_guide/examples/tutorial_schism.ipynb +++ b/docs/user_guide/examples/tutorial_schism.ipynb @@ -37,1186 +37,10 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "2", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " const force = true;\n", - " const version = '3.8.2'.replace('rc', '-rc.').replace('.dev', '-dev.');\n", - " const reloading = false;\n", - " const Bokeh = root.Bokeh;\n", - " const BK_RE = /^https:\\/\\/cdn\\.bokeh\\.org\\/bokeh\\/(release|dev)\\/bokeh-/;\n", - " const PN_RE = /^https:\\/\\/cdn\\.holoviz\\.org\\/panel\\/[^/]+\\/dist\\/panel/i;\n", - "\n", - " // Set a timeout for this load but only if we are not already initializing\n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks;\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, js_modules, js_exports, Bokeh, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - " if (js_modules == null) js_modules = [];\n", - " if (js_exports == null) js_exports = {};\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - "\n", - " if (root._bokeh_is_loading > 0) {\n", - " // Don't load bokeh if it is still initializing\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n", - " // There is nothing to load\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - " window._bokeh_on_load = on_load\n", - "\n", - " function on_error(e) {\n", - " const src_el = e.srcElement\n", - " console.error(\"failed to load \" + (src_el.href || src_el.src));\n", - " }\n", - "\n", - " const skip = [];\n", - " if (window.requirejs) {\n", - " window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n", - " root._bokeh_is_loading = css_urls.length + 0;\n", - " } else {\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n", - " }\n", - "\n", - " const existing_stylesheets = []\n", - " const links = document.getElementsByTagName('link')\n", - " for (let i = 0; i < links.length; i++) {\n", - " const link = links[i]\n", - " if (link.href != null) {\n", - " existing_stylesheets.push(link.href)\n", - " }\n", - " }\n", - " for (let i = 0; i < css_urls.length; i++) {\n", - " const url = css_urls[i];\n", - " const escaped = encodeURI(url)\n", - " if (existing_stylesheets.indexOf(escaped) !== -1) {\n", - " on_load()\n", - " continue;\n", - " }\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " } var existing_scripts = []\n", - " const scripts = document.getElementsByTagName('script')\n", - " for (let i = 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injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " for (let i = 0; i < js_modules.length; i++) {\n", - " const url = js_modules[i];\n", - " const escaped = encodeURI(url)\n", - " if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n", - " if (!window.requirejs) {\n", - " on_load();\n", - " }\n", - " continue;\n", - " }\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " element.type = \"module\";\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " for (const name in js_exports) {\n", - " const url = js_exports[name];\n", - " const escaped = encodeURI(url)\n", - " if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n", - " if (!window.requirejs) {\n", - " on_load();\n", - " }\n", - " continue;\n", - " }\n", - " var element = document.createElement('script');\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.type = \"module\";\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " element.textContent = `\n", - " import ${name} from \"${url}\"\n", - " window.${name} = ${name}\n", - " window._bokeh_on_load()\n", - " `\n", - " document.head.appendChild(element);\n", - " }\n", - " if (!js_urls.length && !js_modules.length) {\n", - " on_load()\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " const js_urls = [\"https://cdn.holoviz.org/panel/1.8.7/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.2.min.js\", \"https://cdn.holoviz.org/panel/1.8.7/dist/panel.min.js\"];\n", - " const js_modules = [];\n", - " const js_exports = {};\n", - " const css_urls = [];\n", - " const inline_js = [ function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - "function(Bokeh) {} // ensure no trailing comma for IE\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " if ((root.Bokeh !== undefined) || (force === true)) {\n", - " for (let i = 0; i < inline_js.length; i++) {\n", - " try {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " } catch(e) {\n", - " if (!reloading) {\n", - " throw e;\n", - " }\n", - " }\n", - " }\n", - " } else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " }\n", - " root._bokeh_is_initializing = false;\n", - " }\n", - "\n", - " function load_or_wait() {\n", - " // Implement a backoff loop that tries to ensure we do not load multiple\n", - " // versions of Bokeh and its dependencies at the same time.\n", - " // In recent versions we use the root._bokeh_is_initializing flag\n", - " // to determine whether there is an ongoing attempt to initialize\n", - " // bokeh, however for backward compatibility we also try to ensure\n", - " // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n", - " // before older versions are fully initialized.\n", - " if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n", - " // If the timeout and bokeh was not successfully loaded we reset\n", - " // everything and try loading again\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_is_initializing = false;\n", - " root._bokeh_onload_callbacks = undefined;\n", - " root._bokeh_is_loading = 0;\n", - " console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n", - " load_or_wait();\n", - " } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n", - " setTimeout(load_or_wait, 100);\n", - " } else {\n", - " root._bokeh_is_initializing = true;\n", - " root._bokeh_onload_callbacks = [];\n", - " const bokeh_loaded = Bokeh != null && ((Bokeh.version === version && Bokeh.Panel) || (Bokeh.versions?.has(version) && Bokeh.versions.get(version)?.Panel));\n", - " if (!reloading && !bokeh_loaded) {\n", - " if (root.Bokeh) {\n", - " root.Bokeh = undefined;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " }\n", - " load_libs(css_urls, js_urls, js_modules, js_exports, Bokeh, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " if (Bokeh != undefined && !reloading) {\n", - " const NewBokeh = root.Bokeh;\n", - " if (Bokeh.versions === undefined) {\n", - " Bokeh.versions = new Map();\n", - " }\n", - " if (NewBokeh.version !== Bokeh.version) {\n", - " Bokeh[NewBokeh.version] = NewBokeh;\n", - " Bokeh.versions.set(NewBokeh.version, NewBokeh);\n", - " }\n", - " root.Bokeh = Bokeh;\n", - " }\n", - " });\n", - " }\n", - " }\n", - " // Give older versions of the autoload script a head-start to ensure\n", - " // they initialize before we start loading newer version.\n", - " setTimeout(load_or_wait, 100)\n", - "}(window));" - ], - "application/vnd.holoviews_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n const force = true;\n const version = '3.8.2'.replace('rc', '-rc.').replace('.dev', '-dev.');\n const reloading = false;\n const Bokeh = root.Bokeh;\n const BK_RE = /^https:\\/\\/cdn\\.bokeh\\.org\\/bokeh\\/(release|dev)\\/bokeh-/;\n const PN_RE = /^https:\\/\\/cdn\\.holoviz\\.org\\/panel\\/[^/]+\\/dist\\/panel/i;\n\n // Set a timeout for this load but only if we are not already initializing\n if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, Bokeh, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n // Don't load bokeh if it is still initializing\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n // There is nothing to load\n run_callbacks();\n return null;\n }\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n window._bokeh_on_load = on_load\n\n function on_error(e) {\n const src_el = e.srcElement\n console.error(\"failed to load \" + (src_el.href || src_el.src));\n }\n\n const skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n root._bokeh_is_loading = css_urls.length + 0;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n }\n\n const existing_stylesheets = []\n const links = document.getElementsByTagName('link')\n for (let i = 0; i < links.length; i++) {\n const link = links[i]\n if (link.href != null) {\n existing_stylesheets.push(link.href)\n }\n }\n for (let i = 0; i < css_urls.length; i++) {\n const url = css_urls[i];\n const escaped = encodeURI(url)\n if (existing_stylesheets.indexOf(escaped) !== -1) {\n on_load()\n continue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } var existing_scripts = []\n const scripts = document.getElementsByTagName('script')\n for (let i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n existing_scripts.push(script.src)\n }\n }\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const escaped = encodeURI(url)\n const shouldSkip = skip.includes(escaped) || existing_scripts.includes(escaped)\n const isBokehOrPanel = BK_RE.test(escaped) || PN_RE.test(escaped)\n const missingOrBroken = Bokeh == null || Bokeh.Panel == null || (Bokeh.version != version && !Bokeh.versions?.has(version)) || Bokeh.versions?.get(version)?.Panel == null;\n if (shouldSkip && !(isBokehOrPanel && missingOrBroken)) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (let i = 0; i < js_modules.length; i++) {\n const url = js_modules[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n const url = js_exports[name];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n const js_urls = [\"https://cdn.holoviz.org/panel/1.8.7/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.2.min.js\", \"https://cdn.holoviz.org/panel/1.8.7/dist/panel.min.js\"];\n const js_modules = [];\n const js_exports = {};\n const css_urls = [];\n const inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (let i = 0; i < inline_js.length; i++) {\n try {\n inline_js[i].call(root, root.Bokeh);\n } catch(e) {\n if (!reloading) {\n throw e;\n }\n }\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n root._bokeh_is_initializing = false;\n }\n\n function load_or_wait() {\n // Implement a backoff loop that tries to ensure we do not load multiple\n // versions of Bokeh and its dependencies at the same time.\n // In recent versions we use the root._bokeh_is_initializing flag\n // to determine whether there is an ongoing attempt to initialize\n // bokeh, however for backward compatibility we also try to ensure\n // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n // before older versions are fully initialized.\n if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n // If the timeout and bokeh was not successfully loaded we reset\n // everything and try loading again\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_is_initializing = false;\n root._bokeh_onload_callbacks = undefined;\n root._bokeh_is_loading = 0;\n console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n load_or_wait();\n } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } else {\n root._bokeh_is_initializing = true;\n root._bokeh_onload_callbacks = [];\n const bokeh_loaded = Bokeh != null && ((Bokeh.version === version && Bokeh.Panel) || (Bokeh.versions?.has(version) && Bokeh.versions.get(version)?.Panel));\n if (!reloading && !bokeh_loaded) {\n if (root.Bokeh) {\n root.Bokeh = undefined;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n }\n load_libs(css_urls, js_urls, js_modules, js_exports, Bokeh, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n if (Bokeh != undefined && !reloading) {\n const NewBokeh = root.Bokeh;\n if (Bokeh.versions === undefined) {\n Bokeh.versions = new Map();\n }\n if (NewBokeh.version !== Bokeh.version) {\n Bokeh[NewBokeh.version] = NewBokeh;\n Bokeh.versions.set(NewBokeh.version, NewBokeh);\n }\n root.Bokeh = Bokeh;\n }\n });\n }\n }\n // Give older versions of the autoload script a head-start to ensure\n // they initialize before we start loading newer version.\n setTimeout(load_or_wait, 100)\n}(window));" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "\n", - "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n", - " window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: 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- " document.head.appendChild(element);\n", - " }\n", - " for (let i = 0; i < js_modules.length; i++) {\n", - " const url = js_modules[i];\n", - " const escaped = encodeURI(url)\n", - " if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n", - " if (!window.requirejs) {\n", - " on_load();\n", - " }\n", - " continue;\n", - " }\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " element.type = \"module\";\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " for (const name in js_exports) {\n", - " const url = js_exports[name];\n", - " const escaped = encodeURI(url)\n", - " if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n", - " if (!window.requirejs) {\n", - " on_load();\n", - " }\n", - " continue;\n", - " }\n", - " var element = document.createElement('script');\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.type = \"module\";\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " element.textContent = `\n", - " import ${name} from \"${url}\"\n", - " window.${name} = ${name}\n", - " window._bokeh_on_load()\n", - " `\n", - " document.head.appendChild(element);\n", - " }\n", - " if (!js_urls.length && !js_modules.length) {\n", - " on_load()\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " const js_urls = [\"https://cdn.holoviz.org/panel/1.8.7/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\"];\n", - " const js_modules = [];\n", - " const js_exports = {};\n", - " const css_urls = [];\n", - " const inline_js = [ function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - "function(Bokeh) {} // ensure no trailing comma for IE\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " if ((root.Bokeh !== undefined) || (force === true)) {\n", - " for (let i = 0; i < inline_js.length; i++) {\n", - " try {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " } catch(e) {\n", - " if (!reloading) {\n", - " throw e;\n", - " }\n", - " }\n", - " }\n", - " } else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " }\n", - " root._bokeh_is_initializing = false;\n", - " }\n", - "\n", - " function load_or_wait() {\n", - " // Implement a backoff loop that tries to ensure we do not load multiple\n", - " // versions of Bokeh and its dependencies at the same time.\n", - " // In recent versions we use the root._bokeh_is_initializing flag\n", - " // to determine whether there is an ongoing attempt to initialize\n", - " // bokeh, however for backward compatibility we also try to ensure\n", - " // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n", - " // before older versions are fully initialized.\n", - " if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n", - " // If the timeout and bokeh was not successfully loaded we reset\n", - " // everything and try loading again\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_is_initializing = false;\n", - " root._bokeh_onload_callbacks = undefined;\n", - " root._bokeh_is_loading = 0;\n", - " console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n", - " load_or_wait();\n", - " } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n", - " setTimeout(load_or_wait, 100);\n", - " } else {\n", - " root._bokeh_is_initializing = true;\n", - " root._bokeh_onload_callbacks = [];\n", - " const bokeh_loaded = Bokeh != null && ((Bokeh.version === version && Bokeh.Panel) || (Bokeh.versions?.has(version) && Bokeh.versions.get(version)?.Panel));\n", - " if (!reloading && !bokeh_loaded) {\n", - " if (root.Bokeh) {\n", - " root.Bokeh = undefined;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " }\n", - " load_libs(css_urls, js_urls, js_modules, js_exports, Bokeh, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " if (Bokeh != undefined && !reloading) {\n", - " const NewBokeh = root.Bokeh;\n", - " if (Bokeh.versions === undefined) {\n", - " Bokeh.versions = new Map();\n", - " }\n", - " if (NewBokeh.version !== Bokeh.version) {\n", - " Bokeh[NewBokeh.version] = NewBokeh;\n", - " Bokeh.versions.set(NewBokeh.version, NewBokeh);\n", - " }\n", - " root.Bokeh = Bokeh;\n", - " }\n", - " });\n", - " }\n", - " }\n", - " // Give older versions of the autoload script a head-start to ensure\n", - " // they initialize before we start loading newer version.\n", - " setTimeout(load_or_wait, 100)\n", - "}(window));" - ], - "application/vnd.holoviews_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n const force = false;\n const version = '3.8.2'.replace('rc', '-rc.').replace('.dev', '-dev.');\n const reloading = true;\n const Bokeh = root.Bokeh;\n const BK_RE = /^https:\\/\\/cdn\\.bokeh\\.org\\/bokeh\\/(release|dev)\\/bokeh-/;\n const PN_RE = /^https:\\/\\/cdn\\.holoviz\\.org\\/panel\\/[^/]+\\/dist\\/panel/i;\n\n // Set a timeout for this load but only if we are not already initializing\n if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks;\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, js_exports, Bokeh, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n if (js_exports == null) js_exports = {};\n\n root._bokeh_onload_callbacks.push(callback);\n\n if (root._bokeh_is_loading > 0) {\n // Don't load bokeh if it is still initializing\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n // There is nothing to load\n run_callbacks();\n return null;\n }\n\n function on_load() {\n 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!== -1) {\n on_load()\n continue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } var existing_scripts = []\n const scripts = document.getElementsByTagName('script')\n for (let i = 0; i < scripts.length; i++) {\n var script = scripts[i]\n if (script.src != null) {\n existing_scripts.push(script.src)\n }\n }\n for (let i = 0; i < js_urls.length; i++) {\n const url = js_urls[i];\n const escaped = encodeURI(url)\n const shouldSkip = skip.includes(escaped) || existing_scripts.includes(escaped)\n const isBokehOrPanel = BK_RE.test(escaped) || PN_RE.test(escaped)\n const missingOrBroken = Bokeh == null || Bokeh.Panel == null || (Bokeh.version != version && !Bokeh.versions?.has(version)) || Bokeh.versions?.get(version)?.Panel == null;\n if (shouldSkip && !(isBokehOrPanel && missingOrBroken)) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n const element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (let i = 0; i < js_modules.length; i++) {\n const url = js_modules[i];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (const name in js_exports) {\n const url = js_exports[name];\n const escaped = encodeURI(url)\n if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n if (!window.requirejs) {\n on_load();\n }\n continue;\n }\n var element = document.createElement('script');\n element.onerror = on_error;\n element.async = false;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n element.textContent = `\n import ${name} from \"${url}\"\n window.${name} = ${name}\n window._bokeh_on_load()\n `\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n const js_urls = [\"https://cdn.holoviz.org/panel/1.8.7/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\"];\n const js_modules = [];\n const js_exports = {};\n const css_urls = [];\n const inline_js = [ function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (let i = 0; i < inline_js.length; i++) {\n try {\n inline_js[i].call(root, root.Bokeh);\n } catch(e) {\n if (!reloading) {\n throw e;\n }\n }\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n root._bokeh_is_initializing = false;\n }\n\n function load_or_wait() {\n // Implement a backoff loop that tries to ensure we do not load multiple\n // versions of Bokeh and its dependencies at the same time.\n // In recent versions we use the root._bokeh_is_initializing flag\n // to determine whether there is an ongoing attempt to initialize\n // bokeh, however for backward compatibility we also try to ensure\n // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n // before older versions are fully initialized.\n if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n // If the timeout and bokeh was not successfully loaded we reset\n // everything and try loading again\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_is_initializing = false;\n root._bokeh_onload_callbacks = undefined;\n root._bokeh_is_loading = 0;\n console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n load_or_wait();\n } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n setTimeout(load_or_wait, 100);\n } else {\n root._bokeh_is_initializing = true;\n root._bokeh_onload_callbacks = [];\n const bokeh_loaded = Bokeh != null && ((Bokeh.version === version && Bokeh.Panel) || 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"application/javascript": [ - "\n", - "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n", - " window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n", - "}\n", - "\n", - "\n", - " function JupyterCommManager() {\n", - " }\n", - "\n", - " JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n", - " if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n", - " var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n", - " comm_manager.register_target(comm_id, function(comm) {\n", - " comm.on_msg(msg_handler);\n", - " });\n", - " } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n", - " window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n", - " comm.onMsg = msg_handler;\n", - " });\n", - " } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n", 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<xarray.UxDataset> Size: 1GB\n",
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-       "    U          (time, zf, n_node) float32 227MB dask.array<chunksize=(1, 16, 147742), meta=np.ndarray>\n",
-       "    V          (time, zf, n_node) float32 227MB dask.array<chunksize=(1, 16, 147742), meta=np.ndarray>\n",
-       "    cell_size  (time, zc, n_face) float64 818MB 137.5 99.14 143.6 ... 10.0 9.731
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"code", - "execution_count": 8, - "id": "10", + "execution_count": null, + "id": "14", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "| Name | Type | Grid number | Interp method / value | Parcels backend |\n", - "|:----------|:------------|--------------:|:------------------------------|:------------------|\n", - "| U | Field | 0 | UxLinearNodeLinearZF(...) | WindowedArray |\n", - "| V | Field | 0 | UxLinearNodeLinearZF(...) | WindowedArray |\n", - "| cell_size | Field | 0 | UxConstantFaceConstantZC(...) | NumPy |\n", - "| UV | VectorField | 0 | Ux_Velocity(...) | - |\n", - "\n", - "mesh: FlatMesh()\n", - "time interval: (np.datetime64('2025-08-18T01:00:00.000000000'), np.datetime64('2025-08-18T06:00:00.000000000'))\n" - ] - } - ], + "outputs": [], "source": [ "fieldset = parcels.FieldSet.from_ugrid_conventions(uxds)\n", "\n", @@ -4392,7 +266,7 @@ }, { "cell_type": "markdown", - "id": "11", + "id": "15", "metadata": {}, "source": [ "## Stop particles that end up below the bathymetry\n", @@ -4414,8 +288,8 @@ }, { "cell_type": "code", - "execution_count": 10, - "id": "12", + "execution_count": null, + "id": "16", "metadata": {}, "outputs": [], "source": [ @@ -4440,7 +314,7 @@ }, { "cell_type": "markdown", - "id": "13", + "id": "17", "metadata": {}, "source": [ "## Limit the timestep by the local CFL number\n", @@ -4452,8 +326,8 @@ }, { "cell_type": "code", - "execution_count": 11, - "id": "14", + "execution_count": null, + "id": "18", "metadata": {}, "outputs": [], "source": [ @@ -4470,7 +344,7 @@ }, { "cell_type": "markdown", - "id": "15", + "id": "19", "metadata": {}, "source": [ "## Release particles and advect" @@ -4478,20 +352,10 @@ }, { "cell_type": "code", - "execution_count": 12, - "id": "16", + "execution_count": null, + "id": "20", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "releasing 1500 particles in the deep basin and 500 in fine nearshore cells\n", - "INFO: Output files are stored in output-schism.parquet\n", - "1938 of 2000 particles still active at the end of the run\n" - ] - } - ], + "outputs": [], "source": [ "# number of valid (non-NaN) vertical levels at each node\n", "valid_levels = np.isfinite(U.isel(time=0).values).sum(axis=1)\n", @@ -4535,7 +399,7 @@ }, { "cell_type": "markdown", - "id": "17", + "id": "21", "metadata": {}, "source": [ "## Plot the velocity field and trajectories\n", @@ -4548,21 +412,10 @@ }, { "cell_type": "code", - "execution_count": 13, - "id": "18", + "execution_count": null, + "id": "22", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "df = parcels.read_particlefile(\"output-schism.parquet\")\n", "\n", @@ -4623,7 +476,7 @@ }, { "cell_type": "markdown", - "id": "19", + "id": "23", "metadata": {}, "source": [ "The particles move with the SCHISM surface currents, and any that wander over shallow water where\n", @@ -4641,7 +494,7 @@ }, { "cell_type": "markdown", - "id": "20", + "id": "24", "metadata": {}, "source": [ "## Adapting this tutorial to your own SCHISM setup\n", From 681ca7a38e98edaff2d6e35be74c4bcc14e17091 Mon Sep 17 00:00:00 2001 From: Joe Schoonover Date: Thu, 29 Oct 2026 12:18:46 -0400 Subject: [PATCH 3/3] Address review commments --- .../user_guide/examples/tutorial_schism.ipynb | 144 ++++++++++++------ 1 file changed, 95 insertions(+), 49 deletions(-) diff --git a/docs/user_guide/examples/tutorial_schism.ipynb b/docs/user_guide/examples/tutorial_schism.ipynb index f1893092a..f08cf2547 100644 --- a/docs/user_guide/examples/tutorial_schism.ipynb +++ b/docs/user_guide/examples/tutorial_schism.ipynb @@ -182,9 +182,7 @@ "id": "9", "metadata": {}, "source": [ - "## Defining a cell size for local time stepping.\n", - "Unstructured meshes are often strongly refined near the coast, so a single `dt` that suits the large\n", - "cells in the basin can carry a particle across several small cells in one step. We add a `cell_size` attribute to the dataset that provides a measure of the length scale of each triangular cell in the mesh. This attribute will later be used in a custom kernel that reduces a particle's time step size based on the local mesh resolution." + "Now, we can construct the `ux.UxDataset` object that we will use to create the `Fieldset` in Parcels with `Field` objects for `U` and `V`." ] }, { @@ -193,40 +191,12 @@ "id": "10", "metadata": {}, "outputs": [], - "source": [ - "# width of each triangle (its smallest altitude), used to limit the timestep by the local CFL number\n", - "p = np.stack([node_x[face_nodes], node_y[face_nodes]], axis=-1)\n", - "e = np.roll(p, -1, axis=1) - p\n", - "area = 0.5 * np.abs(e[:, 0, 0] * e[:, 1, 1] - e[:, 0, 1] * e[:, 1, 0])\n", - "h = 2.0 * area / np.hypot(e[..., 0], e[..., 1]).max(axis=1)\n", - "cell_size = xr.DataArray(\n", - " np.broadcast_to(h, (U.sizes[\"time\"], zc.size, h.size)),\n", - " dims=(\"time\", \"zc\", \"n_face\"),\n", - " coords={\"time\": U[\"time\"]},\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "11", - "metadata": {}, - "source": [ - "Now, we can construct the `ux.UxDataset` object that we will use to create the `Fieldset` in Parcels with `Field` objects for `U`, `V`, `UV` and the `cell_size`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "12", - "metadata": {}, - "outputs": [], "source": [ "uxds = ux.UxDataset(\n", " xr.Dataset(\n", " {\n", " \"U\": U.transpose(\"time\", \"zf\", \"n_node\"),\n", " \"V\": V.transpose(\"time\", \"zf\", \"n_node\"),\n", - " \"cell_size\": cell_size,\n", " },\n", " coords={\"zf\": (\"zf\", zf), \"zc\": (\"zc\", zc)},\n", " ),\n", @@ -237,7 +207,7 @@ }, { "cell_type": "markdown", - "id": "13", + "id": "11", "metadata": {}, "source": [ "## Build the `FieldSet`\n", @@ -253,7 +223,7 @@ { "cell_type": "code", "execution_count": null, - "id": "14", + "id": "12", "metadata": {}, "outputs": [], "source": [ @@ -266,7 +236,7 @@ }, { "cell_type": "markdown", - "id": "15", + "id": "13", "metadata": {}, "source": [ "## Stop particles that end up below the bathymetry\n", @@ -289,7 +259,7 @@ { "cell_type": "code", "execution_count": null, - "id": "16", + "id": "14", "metadata": {}, "outputs": [], "source": [ @@ -314,14 +284,69 @@ }, { "cell_type": "markdown", - "id": "17", + "id": "15", "metadata": {}, "source": [ "## Limit the timestep by the local CFL number\n", "\n", - "The `CFLLimitedDt` kernel below shrinks each particle's `dt` so that it moves at most `CFL_target` local cell widths per step, $\\Delta t \\le C\\,h/|u|$, using the `cell_size` field built above. The `dt` passed to\n", - "`pset.execute()` then acts as the *maximum* timestep, and Parcels sub-steps each particle until it\n", - "reaches the next output time. Place the kernel before the advection kernel." + "Unstructured meshes are often strongly refined near the coast, so a single `dt` that suits the large\n", + "cells in the basin can carry a particle across several small cells in one step. This is measured by\n", + "the CFL (Courant–Friedrichs–Lewy) number\n", + "\n", + "$$\n", + "C = \\frac{|u|\\,\\Delta t}{\\Delta x},\n", + "$$\n", + "\n", + "the number of cells of width $\\Delta x$ that a particle moving at speed $|u|$ crosses in one timestep\n", + "$\\Delta t$. Keeping $C \\lesssim 1$ ensures that particles do not skip over cells. See\n", + "[a priori estimation of `dt`](./tutorial_dt_integrators.ipynb#a-priori-estimation-of-dt) for the same\n", + "reasoning applied to a structured grid.\n", + "\n", + "To use the local cell width in a kernel, we add a `cell_width` field to the `FieldSet`. While there are a number of valid measures of the cell width of a triangle, here we use the shortest distance from a corner to the opposite edge. This is equivalent to twice the triangle's area divided by its longest edge. The cell width is defined on the faces and does not change in time or depth, so we broadcast it over the `time` and `zc` dimensions, build a `FieldSet` from it, and add that to the velocity `FieldSet`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "16", + "metadata": {}, + "outputs": [], + "source": [ + "# corner coordinates of each triangle, shape (n_face, 3, 2)\n", + "corners = np.stack([node_x[face_nodes], node_y[face_nodes]], axis=-1)\n", + "edges = np.roll(corners, -1, axis=1) - corners # edge vectors\n", + "edge_lengths = np.hypot(edges[..., 0], edges[..., 1])\n", + "cell_area = 0.5 * np.abs(\n", + " edges[:, 0, 0] * edges[:, 1, 1] - edges[:, 0, 1] * edges[:, 1, 0]\n", + ")\n", + "cell_width = (\n", + " 2.0 * cell_area / edge_lengths.max(axis=1)\n", + ") # smallest height of each triangle\n", + "\n", + "cell_width_da = xr.DataArray(\n", + " np.broadcast_to(cell_width, (U.sizes[\"time\"], zc.size, cell_width.size)),\n", + " dims=(\"time\", \"zc\", \"n_face\"),\n", + " coords={\"time\": U[\"time\"]},\n", + ")\n", + "uxds_cell_width = ux.UxDataset(\n", + " xr.Dataset(\n", + " {\"cell_width\": cell_width_da}, coords={\"zf\": (\"zf\", zf), \"zc\": (\"zc\", zc)}\n", + " ),\n", + " uxgrid=uxgrid,\n", + ")\n", + "fieldset = fieldset + parcels.FieldSet.from_ugrid_conventions(uxds_cell_width)\n", + "fieldset.describe()" + ] + }, + { + "cell_type": "markdown", + "id": "17", + "metadata": {}, + "source": [ + "The `CFLLimitedDt` kernel below shrinks each particle's `dt` so that it moves at most `CFL_target`\n", + "local cell widths per step: $\\Delta t \\le C\\,\\Delta x/|u|$, with $C$ = `CFL_target` and\n", + "$\\Delta x$ = `cell_width`. To expose the `CFL_target` as a value in the kernel, we use the `fieldset.add_context(name,value)` method to store a scalar value under the name `CFL_target`. The `dt` passed to `pset.execute()` then acts as the *maximum* timestep, and\n", + "Parcels sub-steps each particle until it reaches the next output time." ] }, { @@ -333,9 +358,11 @@ "source": [ "def CFLLimitedDt(particles, fieldset):\n", " \"\"\"Shrink each particle's dt so it moves at most CFL_target cell widths per step.\"\"\"\n", - " h = fieldset.cell_size[particles]\n", + " cell_width = fieldset.cell_width[particles]\n", " u, v = fieldset.UV[particles]\n", - " dt_cfl = fieldset.CFL_target * h / np.maximum(np.sqrt(u * u + v * v), 1e-12)\n", + " dt_cfl = (\n", + " fieldset.CFL_target * cell_width / np.maximum(np.sqrt(u * u + v * v), 1e-12)\n", + " )\n", " particles.dt = np.sign(particles.dt) * np.minimum(np.abs(particles.dt), dt_cfl)\n", "\n", "\n", @@ -347,7 +374,8 @@ "id": "19", "metadata": {}, "source": [ - "## Release particles and advect" + "## Release particles and advect\n", + "Here, the initial particle positions are selected at the face centroids in the deep basin and in areas where the cells are expected to be small." ] }, { @@ -371,7 +399,9 @@ "\n", "# release 500 more on faces where the CFL limit at dt = 5 min is below 1 (small cells, fast flow), at 1 m depth\n", "surf_speed = np.hypot(U.isel(time=0, zf=0).values, V.isel(time=0, zf=0).values)\n", - "dt_cfl = h / np.maximum(np.nan_to_num(surf_speed[face_nodes].mean(axis=1)), 1e-12)\n", + "dt_cfl = cell_width / np.maximum(\n", + " np.nan_to_num(surf_speed[face_nodes].mean(axis=1)), 1e-12\n", + ")\n", "fine = np.where(dt_cfl < 300)[0]\n", "idx_fine = np.random.default_rng(0).choice(fine, 500, replace=False)\n", "\n", @@ -380,8 +410,24 @@ "z = np.concatenate([np.full(idx.size, 2.0), np.full(idx_fine.size, 1.0)])\n", "print(\n", " f\"releasing {idx.size} particles in the deep basin and {idx_fine.size} in fine nearshore cells\"\n", - ")\n", - "\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "21", + "metadata": {}, + "source": [ + "When calling `pset.execute` we call the `CFLLimitedDt` kernel before the `parcels.kernels.AdvectionRK4`. With each execution loop, each particle's time step size is adjusted so that its local CFL estimate is at most `CFL_target` before being advected." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "22", + "metadata": {}, + "outputs": [], + "source": [ "pset = parcels.ParticleSet(fieldset=fieldset, pclass=SchismParticle, x=x, y=y, z=z)\n", "output_file = parcels.ParticleFile(\n", " \"output-schism.parquet\", outputdt=np.timedelta64(30, \"m\")\n", @@ -399,7 +445,7 @@ }, { "cell_type": "markdown", - "id": "21", + "id": "23", "metadata": {}, "source": [ "## Plot the velocity field and trajectories\n", @@ -413,7 +459,7 @@ { "cell_type": "code", "execution_count": null, - "id": "22", + "id": "24", "metadata": {}, "outputs": [], "source": [ @@ -476,7 +522,7 @@ }, { "cell_type": "markdown", - "id": "23", + "id": "25", "metadata": {}, "source": [ "The particles move with the SCHISM surface currents, and any that wander over shallow water where\n", @@ -494,7 +540,7 @@ }, { "cell_type": "markdown", - "id": "24", + "id": "26", "metadata": {}, "source": [ "## Adapting this tutorial to your own SCHISM setup\n",