diff --git a/.DS_Store b/.DS_Store new file mode 100644 index 0000000..b82fcc8 Binary files /dev/null and b/.DS_Store differ diff --git a/README.md b/README.md new file mode 100644 index 0000000..721ed15 --- /dev/null +++ b/README.md @@ -0,0 +1,92 @@ +# Requesting City Services via AI-Driven App + +This Flutter application allows users to submit municipal-related complaints by capturing images using the camera or selecting images from the gallery. The backend API, built with FastAPI, classifies the complaints and directs them to the appropriate department using a Vision Transformer model trained on a custom dataset. + +## About Dataset ## +- The model is trained on self made dataset consisting over 125 images with 25 images for each category, featuring images both self-captured and sourced from the internet, across five categories:. + + - Road and Transport Department + - Electricity Department + - Waste Management Department + - Nature and Recreation Department + - Water Supply and Management + +## Features + +- Capture images using the device camera or form gallery +- allows user to share location of the compliant to be registered +- Submit complaints with images and descriptions +- Automatic classification of complaints to the relevant department + +## Technology Stack + +### Frontend + +- **Flutter 3.19.0** + - Dart programming language + - BLoC (Business Logic Component) state management + +### Backend + +- **FastAPI** +- **Vision Transformer model for image classification** + +## Installation + +### Prerequisites + +- Flutter SDK: [Install Flutter](https://flutter.dev/docs/get-started/install) +- Dart SDK: Included with Flutter SDK +- Python 3.7+: [Install Python](https://www.python.org/downloads/) +- FastAPI: [FastAPI Documentation](https://fastapi.tiangolo.com/) + +### Steps + +1. **Clone the repository:** + ```sh + git clone https://github.com/AMANREVANKAR/summerofcode.git + cd summerofcode + ``` + +2. **Install Flutter dependencies:** + ```sh + cd app + flutter pub get + ``` + +3. **Run the Flutter app:** + ```sh + cd summerofcode/app/lib/features/complaint_form/domain/usecase.dart + add the url for the api server + flutter run + ``` + + +4. **Setup and run the backend API:** + + - Navigate to the backend directory: + ```sh + cd backend + ``` + + - Setting up the server: + ```sh + add the server ip address and port number + ``` + + - Start the FastAPI server: + ```sh + uvicorn APIserver:app --host ip_address --port port_no + ``` +## Working + below is the demo video of a working app + https://drive.google.com/file/d/1QOL003BB6ShAkGesp5ocMF6mtkS2mJcM/view?usp=drive_link + +## Directory Structure +- **summerofcode** + - App + - contains whole flutter app + - backend + - contains all the server and model files + + diff --git a/_config.yml b/_config.yml deleted file mode 100644 index fff4ab9..0000000 --- a/_config.yml +++ /dev/null @@ -1 +0,0 @@ -theme: jekyll-theme-minimal diff --git a/app/.DS_Store b/app/.DS_Store new file mode 100644 index 0000000..2f9d7de Binary files /dev/null and b/app/.DS_Store differ diff --git a/app/.dart_tool/extension_discovery/README.md b/app/.dart_tool/extension_discovery/README.md new file mode 100644 index 0000000..9dc6757 --- /dev/null +++ b/app/.dart_tool/extension_discovery/README.md @@ -0,0 +1,31 @@ +Extension Discovery Cache +========================= + +This folder is used by `package:extension_discovery` to cache lists of +packages that contains extensions for other packages. + +DO NOT USE THIS FOLDER +---------------------- + + * Do not read (or rely) the contents of this folder. + * Do write to this folder. + +If you're interested in the lists of extensions stored in this folder use the +API offered by package `extension_discovery` to get this information. + +If this package doesn't work for your use-case, then don't try to read the +contents of this folder. It may change, and will not remain stable. + +Use package `extension_discovery` +--------------------------------- + +If you want to access information from this folder. + +Feel free to delete this folder +------------------------------- + +Files in this folder act as a cache, and the cache is discarded if the files +are older than the modification time of `.dart_tool/package_config.json`. + +Hence, it should never be necessary to clear this cache manually, if you find a +need to do please file a bug. diff --git a/app/.dart_tool/extension_discovery/vs_code.json b/app/.dart_tool/extension_discovery/vs_code.json new file mode 100644 index 0000000..c0e215c --- /dev/null +++ b/app/.dart_tool/extension_discovery/vs_code.json @@ -0,0 +1 @@ +{"version":2,"entries":[{"package":"sanpresolve","rootUri":"../","packageUri":"lib/"}]} \ No newline at end of file diff --git a/app/.dart_tool/package_config.json b/app/.dart_tool/package_config.json new file mode 100644 index 0000000..a212c60 --- 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+file:///Users/amanrev/Documents/flutter/packages/flutter_test/ +file:///Users/amanrev/Documents/flutter/packages/flutter_test/lib/ +flutter_web_plugins +3.2 +file:///Users/amanrev/Documents/flutter/packages/flutter_web_plugins/ +file:///Users/amanrev/Documents/flutter/packages/flutter_web_plugins/lib/ +2 diff --git a/app/.dart_tool/version b/app/.dart_tool/version new file mode 100644 index 0000000..209f579 --- /dev/null +++ b/app/.dart_tool/version @@ -0,0 +1 @@ +3.19.0 \ No newline at end of file diff --git a/app/.flutter-plugins b/app/.flutter-plugins new file mode 100644 index 0000000..2805acb --- /dev/null +++ b/app/.flutter-plugins @@ -0,0 +1,25 @@ +# This is a generated file; do not edit or check into version control. +file_selector_linux=/Users/amanrev/.pub-cache/hosted/pub.dev/file_selector_linux-0.9.2+1/ +file_selector_macos=/Users/amanrev/.pub-cache/hosted/pub.dev/file_selector_macos-0.9.4/ +file_selector_windows=/Users/amanrev/.pub-cache/hosted/pub.dev/file_selector_windows-0.9.3+1/ +flutter_plugin_android_lifecycle=/Users/amanrev/.pub-cache/hosted/pub.dev/flutter_plugin_android_lifecycle-2.0.19/ +geocoding=/Users/amanrev/.pub-cache/hosted/pub.dev/geocoding-3.0.0/ +geocoding_android=/Users/amanrev/.pub-cache/hosted/pub.dev/geocoding_android-3.3.1/ +geocoding_ios=/Users/amanrev/.pub-cache/hosted/pub.dev/geocoding_ios-3.0.1/ +geolocator=/Users/amanrev/.pub-cache/hosted/pub.dev/geolocator-12.0.0/ +geolocator_android=/Users/amanrev/.pub-cache/hosted/pub.dev/geolocator_android-4.6.0/ +geolocator_apple=/Users/amanrev/.pub-cache/hosted/pub.dev/geolocator_apple-2.3.7/ +geolocator_web=/Users/amanrev/.pub-cache/hosted/pub.dev/geolocator_web-4.0.0/ +geolocator_windows=/Users/amanrev/.pub-cache/hosted/pub.dev/geolocator_windows-0.2.3/ +image_picker=/Users/amanrev/.pub-cache/hosted/pub.dev/image_picker-1.1.2/ +image_picker_android=/Users/amanrev/.pub-cache/hosted/pub.dev/image_picker_android-0.8.12+1/ +image_picker_for_web=/Users/amanrev/.pub-cache/hosted/pub.dev/image_picker_for_web-3.0.4/ +image_picker_ios=/Users/amanrev/.pub-cache/hosted/pub.dev/image_picker_ios-0.8.12/ +image_picker_linux=/Users/amanrev/.pub-cache/hosted/pub.dev/image_picker_linux-0.2.1+1/ +image_picker_macos=/Users/amanrev/.pub-cache/hosted/pub.dev/image_picker_macos-0.2.1+1/ +image_picker_windows=/Users/amanrev/.pub-cache/hosted/pub.dev/image_picker_windows-0.2.1+1/ +permission_handler=/Users/amanrev/.pub-cache/hosted/pub.dev/permission_handler-11.3.1/ +permission_handler_android=/Users/amanrev/.pub-cache/hosted/pub.dev/permission_handler_android-12.0.7/ +permission_handler_apple=/Users/amanrev/.pub-cache/hosted/pub.dev/permission_handler_apple-9.4.5/ +permission_handler_html=/Users/amanrev/.pub-cache/hosted/pub.dev/permission_handler_html-0.1.1/ +permission_handler_windows=/Users/amanrev/.pub-cache/hosted/pub.dev/permission_handler_windows-0.2.1/ diff --git a/app/.flutter-plugins-dependencies b/app/.flutter-plugins-dependencies new file mode 100644 index 0000000..a35af01 --- /dev/null +++ b/app/.flutter-plugins-dependencies @@ -0,0 +1 @@ +{"info":"This is a generated file; do not edit or check into version control.","plugins":{"ios":[{"name":"geocoding_ios","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/geocoding_ios-3.0.1/","native_build":true,"dependencies":[]},{"name":"geolocator_apple","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/geolocator_apple-2.3.7/","native_build":true,"dependencies":[]},{"name":"image_picker_ios","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/image_picker_ios-0.8.12/","native_build":true,"dependencies":[]},{"name":"permission_handler_apple","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/permission_handler_apple-9.4.5/","native_build":true,"dependencies":[]}],"android":[{"name":"flutter_plugin_android_lifecycle","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/flutter_plugin_android_lifecycle-2.0.19/","native_build":true,"dependencies":[]},{"name":"geocoding_android","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/geocoding_android-3.3.1/","native_build":true,"dependencies":[]},{"name":"geolocator_android","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/geolocator_android-4.6.0/","native_build":true,"dependencies":[]},{"name":"image_picker_android","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/image_picker_android-0.8.12+1/","native_build":true,"dependencies":["flutter_plugin_android_lifecycle"]},{"name":"permission_handler_android","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/permission_handler_android-12.0.7/","native_build":true,"dependencies":[]}],"macos":[{"name":"file_selector_macos","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/file_selector_macos-0.9.4/","native_build":true,"dependencies":[]},{"name":"geolocator_apple","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/geolocator_apple-2.3.7/","native_build":true,"dependencies":[]},{"name":"image_picker_macos","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/image_picker_macos-0.2.1+1/","native_build":false,"dependencies":["file_selector_macos"]}],"linux":[{"name":"file_selector_linux","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/file_selector_linux-0.9.2+1/","native_build":true,"dependencies":[]},{"name":"image_picker_linux","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/image_picker_linux-0.2.1+1/","native_build":false,"dependencies":["file_selector_linux"]}],"windows":[{"name":"file_selector_windows","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/file_selector_windows-0.9.3+1/","native_build":true,"dependencies":[]},{"name":"geolocator_windows","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/geolocator_windows-0.2.3/","native_build":true,"dependencies":[]},{"name":"image_picker_windows","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/image_picker_windows-0.2.1+1/","native_build":false,"dependencies":["file_selector_windows"]},{"name":"permission_handler_windows","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/permission_handler_windows-0.2.1/","native_build":true,"dependencies":[]}],"web":[{"name":"geolocator_web","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/geolocator_web-4.0.0/","dependencies":[]},{"name":"image_picker_for_web","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/image_picker_for_web-3.0.4/","dependencies":[]},{"name":"permission_handler_html","path":"/Users/amanrev/.pub-cache/hosted/pub.dev/permission_handler_html-0.1.1/","dependencies":[]}]},"dependencyGraph":[{"name":"file_selector_linux","dependencies":[]},{"name":"file_selector_macos","dependencies":[]},{"name":"file_selector_windows","dependencies":[]},{"name":"flutter_plugin_android_lifecycle","dependencies":[]},{"name":"geocoding","dependencies":["geocoding_android","geocoding_ios"]},{"name":"geocoding_android","dependencies":[]},{"name":"geocoding_ios","dependencies":[]},{"name":"geolocator","dependencies":["geolocator_android","geolocator_apple","geolocator_web","geolocator_windows"]},{"name":"geolocator_android","dependencies":[]},{"name":"geolocator_apple","dependencies":[]},{"name":"geolocator_web","dependencies":[]},{"name":"geolocator_windows","dependencies":[]},{"name":"image_picker","dependencies":["image_picker_android","image_picker_for_web","image_picker_ios","image_picker_linux","image_picker_macos","image_picker_windows"]},{"name":"image_picker_android","dependencies":["flutter_plugin_android_lifecycle"]},{"name":"image_picker_for_web","dependencies":[]},{"name":"image_picker_ios","dependencies":[]},{"name":"image_picker_linux","dependencies":["file_selector_linux"]},{"name":"image_picker_macos","dependencies":["file_selector_macos"]},{"name":"image_picker_windows","dependencies":["file_selector_windows"]},{"name":"permission_handler","dependencies":["permission_handler_android","permission_handler_apple","permission_handler_html","permission_handler_windows"]},{"name":"permission_handler_android","dependencies":[]},{"name":"permission_handler_apple","dependencies":[]},{"name":"permission_handler_html","dependencies":[]},{"name":"permission_handler_windows","dependencies":[]}],"date_created":"2024-06-26 18:40:50.845908","version":"3.19.0"} \ No newline at end of file diff --git a/app/analysis_options.yaml b/app/analysis_options.yaml new file mode 100644 index 0000000..0d29021 --- /dev/null +++ b/app/analysis_options.yaml @@ -0,0 +1,28 @@ +# This file configures the analyzer, which statically analyzes Dart code to +# check for errors, warnings, and lints. +# +# The issues identified by the analyzer are surfaced in the UI of Dart-enabled +# IDEs (https://dart.dev/tools#ides-and-editors). The analyzer can also be +# invoked from the command line by running `flutter analyze`. + +# The following line activates a set of recommended lints for Flutter apps, +# packages, and plugins designed to encourage good coding practices. +include: package:flutter_lints/flutter.yaml + +linter: + # The lint rules applied to this project can be customized in the + # section below to disable rules from the `package:flutter_lints/flutter.yaml` + # included above or to enable additional rules. A list of all available lints + # and their documentation is published at https://dart.dev/lints. + # + # Instead of disabling a lint rule for the entire project in the + # section below, it can also be suppressed for a single line of code + # or a specific dart file by using the `// ignore: name_of_lint` and + # `// ignore_for_file: name_of_lint` syntax on the line or in the file + # producing the lint. + rules: + # avoid_print: false # Uncomment to disable the `avoid_print` rule + # prefer_single_quotes: true # Uncomment to enable the `prefer_single_quotes` rule + +# Additional information about this file can be found at +# https://dart.dev/guides/language/analysis-options diff --git a/app/android/.gitignore b/app/android/.gitignore new file mode 100644 index 0000000..6f56801 --- /dev/null +++ b/app/android/.gitignore @@ -0,0 +1,13 @@ +gradle-wrapper.jar +/.gradle +/captures/ +/gradlew +/gradlew.bat +/local.properties +GeneratedPluginRegistrant.java + +# Remember to never publicly share your keystore. +# See https://flutter.dev/docs/deployment/android#reference-the-keystore-from-the-app +key.properties +**/*.keystore +**/*.jks diff --git a/app/android/app/build.gradle b/app/android/app/build.gradle new file mode 100644 index 0000000..373ec12 --- /dev/null +++ b/app/android/app/build.gradle @@ -0,0 +1,67 @@ +plugins { + id "com.android.application" + id "kotlin-android" + id "dev.flutter.flutter-gradle-plugin" +} + +def localProperties = new Properties() +def localPropertiesFile = rootProject.file('local.properties') +if (localPropertiesFile.exists()) { + localPropertiesFile.withReader('UTF-8') { reader -> + localProperties.load(reader) + } +} + +def flutterVersionCode = localProperties.getProperty('flutter.versionCode') +if (flutterVersionCode == null) { + flutterVersionCode = '1' +} + +def flutterVersionName = localProperties.getProperty('flutter.versionName') +if (flutterVersionName == null) { + flutterVersionName = '1.0' +} + +android { + namespace "com.example.sanpresolve" + compileSdk 34 + ndkVersion flutter.ndkVersion + + compileOptions { + sourceCompatibility JavaVersion.VERSION_1_8 + targetCompatibility JavaVersion.VERSION_1_8 + } + + kotlinOptions { + jvmTarget = '1.8' + } + + sourceSets { + main.java.srcDirs += 'src/main/kotlin' + } + + defaultConfig { + // TODO: Specify your own unique Application ID (https://developer.android.com/studio/build/application-id.html). + applicationId "com.example.sanpresolve" + // You can update the following values to match your application needs. + // For more information, see: https://docs.flutter.dev/deployment/android#reviewing-the-gradle-build-configuration. + minSdkVersion flutter.minSdkVersion + targetSdkVersion flutter.targetSdkVersion + versionCode flutterVersionCode.toInteger() + versionName flutterVersionName + } + + buildTypes { + release { + // TODO: Add your own signing config for the release build. + // Signing with the debug keys for now, so `flutter run --release` works. + signingConfig signingConfigs.debug + } + } +} + +flutter { + source '../..' +} + +dependencies {} diff --git a/app/android/app/src/debug/AndroidManifest.xml b/app/android/app/src/debug/AndroidManifest.xml new file mode 100644 index 0000000..399f698 --- /dev/null +++ b/app/android/app/src/debug/AndroidManifest.xml @@ -0,0 +1,7 @@ + + + + diff --git a/app/android/app/src/main/AndroidManifest.xml b/app/android/app/src/main/AndroidManifest.xml new file mode 100644 index 0000000..37a864d --- /dev/null +++ b/app/android/app/src/main/AndroidManifest.xml @@ -0,0 +1,55 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/app/android/app/src/main/kotlin/com/example/sanpresolve/MainActivity.kt b/app/android/app/src/main/kotlin/com/example/sanpresolve/MainActivity.kt new file mode 100644 index 0000000..92d46bd --- /dev/null +++ b/app/android/app/src/main/kotlin/com/example/sanpresolve/MainActivity.kt @@ -0,0 +1,5 @@ +package com.example.sanpresolve + +import io.flutter.embedding.android.FlutterActivity + +class MainActivity: FlutterActivity() diff --git a/app/android/app/src/main/res/drawable-v21/launch_background.xml b/app/android/app/src/main/res/drawable-v21/launch_background.xml new file mode 100644 index 0000000..f74085f --- /dev/null +++ b/app/android/app/src/main/res/drawable-v21/launch_background.xml @@ -0,0 +1,12 @@ + + + + + + + + diff --git a/app/android/app/src/main/res/drawable/launch_background.xml b/app/android/app/src/main/res/drawable/launch_background.xml new file mode 100644 index 0000000..304732f --- /dev/null +++ b/app/android/app/src/main/res/drawable/launch_background.xml @@ -0,0 +1,12 @@ + + + + + + + + diff --git a/app/android/app/src/main/res/mipmap-hdpi/ic_launcher.png b/app/android/app/src/main/res/mipmap-hdpi/ic_launcher.png new file mode 100644 index 0000000..db77bb4 Binary files /dev/null and b/app/android/app/src/main/res/mipmap-hdpi/ic_launcher.png differ diff --git a/app/android/app/src/main/res/mipmap-mdpi/ic_launcher.png b/app/android/app/src/main/res/mipmap-mdpi/ic_launcher.png new file mode 100644 index 0000000..17987b7 Binary files /dev/null and b/app/android/app/src/main/res/mipmap-mdpi/ic_launcher.png differ diff --git a/app/android/app/src/main/res/mipmap-xhdpi/ic_launcher.png b/app/android/app/src/main/res/mipmap-xhdpi/ic_launcher.png new file mode 100644 index 0000000..09d4391 Binary files /dev/null and b/app/android/app/src/main/res/mipmap-xhdpi/ic_launcher.png differ diff --git a/app/android/app/src/main/res/mipmap-xxhdpi/ic_launcher.png b/app/android/app/src/main/res/mipmap-xxhdpi/ic_launcher.png new file mode 100644 index 0000000..d5f1c8d Binary files /dev/null and b/app/android/app/src/main/res/mipmap-xxhdpi/ic_launcher.png differ diff --git a/app/android/app/src/main/res/mipmap-xxxhdpi/ic_launcher.png b/app/android/app/src/main/res/mipmap-xxxhdpi/ic_launcher.png new file mode 100644 index 0000000..4d6372e Binary files /dev/null and b/app/android/app/src/main/res/mipmap-xxxhdpi/ic_launcher.png differ diff --git a/app/android/app/src/main/res/values-night/styles.xml b/app/android/app/src/main/res/values-night/styles.xml new file mode 100644 index 0000000..06952be --- /dev/null +++ b/app/android/app/src/main/res/values-night/styles.xml @@ -0,0 +1,18 @@ + + + + + + + diff --git a/app/android/app/src/main/res/values/styles.xml b/app/android/app/src/main/res/values/styles.xml new file mode 100644 index 0000000..cb1ef88 --- /dev/null +++ b/app/android/app/src/main/res/values/styles.xml @@ -0,0 +1,18 @@ + + + + + + + diff --git a/app/android/app/src/profile/AndroidManifest.xml b/app/android/app/src/profile/AndroidManifest.xml new file mode 100644 index 0000000..399f698 --- /dev/null +++ b/app/android/app/src/profile/AndroidManifest.xml @@ -0,0 +1,7 @@ + + + + diff --git a/app/android/build.gradle b/app/android/build.gradle new file mode 100644 index 0000000..6f5b2a5 --- /dev/null +++ b/app/android/build.gradle @@ -0,0 +1,21 @@ +allprojects { + repositories { + google() + mavenCentral() + } +} + + + + +rootProject.buildDir = '../build' +subprojects { + project.buildDir = "${rootProject.buildDir}/${project.name}" +} +subprojects { + project.evaluationDependsOn(':app') +} + +tasks.register("clean", Delete) { + delete rootProject.buildDir +} diff --git a/app/android/gradle.properties b/app/android/gradle.properties new file mode 100644 index 0000000..598d13f --- /dev/null +++ b/app/android/gradle.properties @@ -0,0 +1,3 @@ +org.gradle.jvmargs=-Xmx4G +android.useAndroidX=true +android.enableJetifier=true diff --git a/app/android/gradle/wrapper/gradle-wrapper.properties b/app/android/gradle/wrapper/gradle-wrapper.properties new file mode 100644 index 0000000..e1ca574 --- /dev/null +++ b/app/android/gradle/wrapper/gradle-wrapper.properties @@ -0,0 +1,5 @@ +distributionBase=GRADLE_USER_HOME +distributionPath=wrapper/dists +zipStoreBase=GRADLE_USER_HOME +zipStorePath=wrapper/dists +distributionUrl=https\://services.gradle.org/distributions/gradle-7.6.3-all.zip diff --git a/app/android/settings.gradle b/app/android/settings.gradle new file mode 100644 index 0000000..985a6e2 --- /dev/null +++ b/app/android/settings.gradle @@ -0,0 +1,26 @@ +pluginManagement { + def flutterSdkPath = { + def properties = new Properties() + file("local.properties").withInputStream { properties.load(it) } + def flutterSdkPath = properties.getProperty("flutter.sdk") + assert flutterSdkPath != null, "flutter.sdk not set in local.properties" + return flutterSdkPath + } + settings.ext.flutterSdkPath = flutterSdkPath() + + includeBuild("${settings.ext.flutterSdkPath}/packages/flutter_tools/gradle") + + repositories { + google() + mavenCentral() + gradlePluginPortal() + } +} + +plugins { + id "dev.flutter.flutter-plugin-loader" version "1.0.0" + id "com.android.application" version "7.3.0" apply false + id "org.jetbrains.kotlin.android" version "1.9.22" apply false +} + +include ":app" diff --git a/app/ios/.gitignore b/app/ios/.gitignore new file mode 100644 index 0000000..7a7f987 --- /dev/null +++ b/app/ios/.gitignore @@ -0,0 +1,34 @@ +**/dgph +*.mode1v3 +*.mode2v3 +*.moved-aside +*.pbxuser +*.perspectivev3 +**/*sync/ +.sconsign.dblite +.tags* +**/.vagrant/ +**/DerivedData/ +Icon? +**/Pods/ +**/.symlinks/ +profile +xcuserdata +**/.generated/ +Flutter/App.framework +Flutter/Flutter.framework +Flutter/Flutter.podspec +Flutter/Generated.xcconfig +Flutter/ephemeral/ +Flutter/app.flx +Flutter/app.zip +Flutter/flutter_assets/ +Flutter/flutter_export_environment.sh +ServiceDefinitions.json +Runner/GeneratedPluginRegistrant.* + +# Exceptions to above rules. +!default.mode1v3 +!default.mode2v3 +!default.pbxuser +!default.perspectivev3 diff --git a/app/ios/Flutter/AppFrameworkInfo.plist b/app/ios/Flutter/AppFrameworkInfo.plist new file mode 100644 index 0000000..7c56964 --- /dev/null +++ b/app/ios/Flutter/AppFrameworkInfo.plist @@ -0,0 +1,26 @@ + + + + + CFBundleDevelopmentRegion + en + CFBundleExecutable + App + CFBundleIdentifier + io.flutter.flutter.app + CFBundleInfoDictionaryVersion + 6.0 + CFBundleName + App + CFBundlePackageType + FMWK + CFBundleShortVersionString + 1.0 + CFBundleSignature + ???? + CFBundleVersion + 1.0 + MinimumOSVersion + 12.0 + + diff --git a/app/ios/Flutter/Debug.xcconfig b/app/ios/Flutter/Debug.xcconfig new file mode 100644 index 0000000..ec97fc6 --- /dev/null +++ b/app/ios/Flutter/Debug.xcconfig @@ -0,0 +1,2 @@ +#include? "Pods/Target Support Files/Pods-Runner/Pods-Runner.debug.xcconfig" +#include "Generated.xcconfig" diff --git a/app/ios/Flutter/Release.xcconfig b/app/ios/Flutter/Release.xcconfig new file mode 100644 index 0000000..c4855bf --- /dev/null +++ b/app/ios/Flutter/Release.xcconfig @@ -0,0 +1,2 @@ +#include? "Pods/Target Support Files/Pods-Runner/Pods-Runner.release.xcconfig" +#include "Generated.xcconfig" diff --git a/app/ios/Podfile b/app/ios/Podfile new file mode 100644 index 0000000..d97f17e --- /dev/null +++ b/app/ios/Podfile @@ -0,0 +1,44 @@ +# Uncomment this line to define a global platform for your project +# platform :ios, '12.0' + +# CocoaPods analytics sends network stats synchronously affecting flutter build latency. +ENV['COCOAPODS_DISABLE_STATS'] = 'true' + +project 'Runner', { + 'Debug' => :debug, + 'Profile' => :release, + 'Release' => :release, +} + +def flutter_root + generated_xcode_build_settings_path = File.expand_path(File.join('..', 'Flutter', 'Generated.xcconfig'), __FILE__) + unless File.exist?(generated_xcode_build_settings_path) + raise "#{generated_xcode_build_settings_path} must exist. If you're running pod install manually, make sure flutter pub get is executed first" + end + + File.foreach(generated_xcode_build_settings_path) do |line| + matches = line.match(/FLUTTER_ROOT\=(.*)/) + return matches[1].strip if matches + end + raise "FLUTTER_ROOT not found in #{generated_xcode_build_settings_path}. Try deleting Generated.xcconfig, then run flutter pub get" +end + +require File.expand_path(File.join('packages', 'flutter_tools', 'bin', 'podhelper'), flutter_root) + +flutter_ios_podfile_setup + +target 'Runner' do + use_frameworks! + use_modular_headers! + + flutter_install_all_ios_pods File.dirname(File.realpath(__FILE__)) + target 'RunnerTests' do + inherit! :search_paths + end +end + +post_install do |installer| + installer.pods_project.targets.each do |target| + flutter_additional_ios_build_settings(target) + end +end diff --git a/app/ios/Runner.xcodeproj/project.pbxproj b/app/ios/Runner.xcodeproj/project.pbxproj new file mode 100644 index 0000000..26a972a --- /dev/null +++ b/app/ios/Runner.xcodeproj/project.pbxproj @@ -0,0 +1,619 @@ +// !$*UTF8*$! +{ + archiveVersion = 1; + classes = { + }; + objectVersion = 54; + objects = { + +/* Begin PBXBuildFile section */ + 1498D2341E8E89220040F4C2 /* GeneratedPluginRegistrant.m in Sources */ = {isa = PBXBuildFile; fileRef = 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b/app/ios/Runner.xcodeproj/project.xcworkspace/contents.xcworkspacedata new file mode 100644 index 0000000..919434a --- /dev/null +++ b/app/ios/Runner.xcodeproj/project.xcworkspace/contents.xcworkspacedata @@ -0,0 +1,7 @@ + + + + + diff --git a/app/ios/Runner.xcodeproj/project.xcworkspace/xcshareddata/IDEWorkspaceChecks.plist b/app/ios/Runner.xcodeproj/project.xcworkspace/xcshareddata/IDEWorkspaceChecks.plist new file mode 100644 index 0000000..18d9810 --- /dev/null +++ b/app/ios/Runner.xcodeproj/project.xcworkspace/xcshareddata/IDEWorkspaceChecks.plist @@ -0,0 +1,8 @@ + + + + + IDEDidComputeMac32BitWarning + + + diff --git a/app/ios/Runner.xcodeproj/project.xcworkspace/xcshareddata/WorkspaceSettings.xcsettings b/app/ios/Runner.xcodeproj/project.xcworkspace/xcshareddata/WorkspaceSettings.xcsettings new file mode 100644 index 0000000..f9b0d7c --- /dev/null +++ b/app/ios/Runner.xcodeproj/project.xcworkspace/xcshareddata/WorkspaceSettings.xcsettings @@ -0,0 +1,8 @@ + + + + + PreviewsEnabled + + + diff --git a/app/ios/Runner.xcodeproj/xcshareddata/xcschemes/Runner.xcscheme b/app/ios/Runner.xcodeproj/xcshareddata/xcschemes/Runner.xcscheme new file mode 100644 index 0000000..8e3ca5d --- /dev/null +++ b/app/ios/Runner.xcodeproj/xcshareddata/xcschemes/Runner.xcscheme @@ -0,0 +1,98 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/app/ios/Runner.xcworkspace/contents.xcworkspacedata b/app/ios/Runner.xcworkspace/contents.xcworkspacedata new file mode 100644 index 0000000..1d526a1 --- /dev/null +++ b/app/ios/Runner.xcworkspace/contents.xcworkspacedata @@ -0,0 +1,7 @@ + + + + + diff --git a/app/ios/Runner.xcworkspace/xcshareddata/IDEWorkspaceChecks.plist b/app/ios/Runner.xcworkspace/xcshareddata/IDEWorkspaceChecks.plist new file mode 100644 index 0000000..18d9810 --- /dev/null +++ b/app/ios/Runner.xcworkspace/xcshareddata/IDEWorkspaceChecks.plist @@ -0,0 +1,8 @@ + + + + + IDEDidComputeMac32BitWarning + + + diff --git a/app/ios/Runner.xcworkspace/xcshareddata/WorkspaceSettings.xcsettings b/app/ios/Runner.xcworkspace/xcshareddata/WorkspaceSettings.xcsettings new file mode 100644 index 0000000..f9b0d7c --- /dev/null +++ b/app/ios/Runner.xcworkspace/xcshareddata/WorkspaceSettings.xcsettings @@ -0,0 +1,8 @@ + + + + + PreviewsEnabled + + + diff --git a/app/ios/Runner/AppDelegate.swift b/app/ios/Runner/AppDelegate.swift new file mode 100644 index 0000000..70693e4 --- /dev/null +++ b/app/ios/Runner/AppDelegate.swift @@ -0,0 +1,13 @@ +import UIKit +import Flutter + +@UIApplicationMain +@objc class AppDelegate: FlutterAppDelegate { + override func application( + _ application: UIApplication, + didFinishLaunchingWithOptions launchOptions: [UIApplication.LaunchOptionsKey: Any]? + ) -> Bool { + GeneratedPluginRegistrant.register(with: self) + return super.application(application, didFinishLaunchingWithOptions: launchOptions) + } +} diff --git a/app/ios/Runner/Assets.xcassets/AppIcon.appiconset/Contents.json 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"60x60", + "idiom" : "iphone", + "filename" : "Icon-App-60x60@2x.png", + "scale" : "2x" + }, + { + "size" : "60x60", + "idiom" : "iphone", + "filename" : "Icon-App-60x60@3x.png", + "scale" : "3x" + }, + { + "size" : "20x20", + "idiom" : "ipad", + "filename" : "Icon-App-20x20@1x.png", + "scale" : "1x" + }, + { + "size" : "20x20", + "idiom" : "ipad", + "filename" : "Icon-App-20x20@2x.png", + "scale" : "2x" + }, + { + "size" : "29x29", + "idiom" : "ipad", + "filename" : "Icon-App-29x29@1x.png", + "scale" : "1x" + }, + { + "size" : "29x29", + "idiom" : "ipad", + "filename" : "Icon-App-29x29@2x.png", + "scale" : "2x" + }, + { + "size" : "40x40", + "idiom" : "ipad", + "filename" : "Icon-App-40x40@1x.png", + "scale" : "1x" + }, + { + "size" : "40x40", + "idiom" : "ipad", + "filename" : "Icon-App-40x40@2x.png", + "scale" : "2x" + }, + { + "size" : "76x76", + "idiom" : "ipad", + "filename" : "Icon-App-76x76@1x.png", + "scale" : "1x" + }, + { + "size" : "76x76", + "idiom" : "ipad", + "filename" : "Icon-App-76x76@2x.png", + "scale" : "2x" + }, + { + "size" : "83.5x83.5", + "idiom" : "ipad", + "filename" : "Icon-App-83.5x83.5@2x.png", + "scale" : "2x" + }, + { + "size" : "1024x1024", + "idiom" : "ios-marketing", + "filename" : "Icon-App-1024x1024@1x.png", + "scale" : "1x" + } + ], + "info" : { + "version" : 1, + "author" : "xcode" + } +} diff --git a/app/ios/Runner/Assets.xcassets/AppIcon.appiconset/Icon-App-1024x1024@1x.png b/app/ios/Runner/Assets.xcassets/AppIcon.appiconset/Icon-App-1024x1024@1x.png new file mode 100644 index 0000000..dc9ada4 Binary files /dev/null and b/app/ios/Runner/Assets.xcassets/AppIcon.appiconset/Icon-App-1024x1024@1x.png differ diff --git a/app/ios/Runner/Assets.xcassets/AppIcon.appiconset/Icon-App-20x20@1x.png b/app/ios/Runner/Assets.xcassets/AppIcon.appiconset/Icon-App-20x20@1x.png new file mode 100644 index 0000000..7353c41 Binary files /dev/null and b/app/ios/Runner/Assets.xcassets/AppIcon.appiconset/Icon-App-20x20@1x.png differ diff --git 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a/app/ios/Runner/Assets.xcassets/AppIcon.appiconset/Icon-App-83.5x83.5@2x.png b/app/ios/Runner/Assets.xcassets/AppIcon.appiconset/Icon-App-83.5x83.5@2x.png new file mode 100644 index 0000000..0467bf1 Binary files /dev/null and b/app/ios/Runner/Assets.xcassets/AppIcon.appiconset/Icon-App-83.5x83.5@2x.png differ diff --git a/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/Contents.json b/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/Contents.json new file mode 100644 index 0000000..0bedcf2 --- /dev/null +++ b/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/Contents.json @@ -0,0 +1,23 @@ +{ + "images" : [ + { + "idiom" : "universal", + "filename" : "LaunchImage.png", + "scale" : "1x" + }, + { + "idiom" : "universal", + "filename" : "LaunchImage@2x.png", + "scale" : "2x" + }, + { + "idiom" : "universal", + "filename" : "LaunchImage@3x.png", + "scale" : "3x" + } + ], + "info" : { + "version" : 1, + "author" : "xcode" + } +} diff --git a/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/LaunchImage.png b/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/LaunchImage.png new file mode 100644 index 0000000..9da19ea Binary files /dev/null and b/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/LaunchImage.png differ diff --git a/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/LaunchImage@2x.png b/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/LaunchImage@2x.png new file mode 100644 index 0000000..9da19ea Binary files /dev/null and b/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/LaunchImage@2x.png differ diff --git a/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/LaunchImage@3x.png b/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/LaunchImage@3x.png new file mode 100644 index 0000000..9da19ea Binary files /dev/null and b/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/LaunchImage@3x.png differ diff --git a/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/README.md b/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/README.md new file mode 100644 index 0000000..89c2725 --- /dev/null +++ b/app/ios/Runner/Assets.xcassets/LaunchImage.imageset/README.md @@ -0,0 +1,5 @@ +# Launch Screen Assets + +You can customize the launch screen with your own desired assets by replacing the image files in this directory. + +You can also do it by opening your Flutter project's Xcode project with `open ios/Runner.xcworkspace`, selecting `Runner/Assets.xcassets` in the Project Navigator and dropping in the desired images. \ No newline at end of file diff --git a/app/ios/Runner/Base.lproj/LaunchScreen.storyboard b/app/ios/Runner/Base.lproj/LaunchScreen.storyboard new file mode 100644 index 0000000..f2e259c --- /dev/null +++ b/app/ios/Runner/Base.lproj/LaunchScreen.storyboard @@ -0,0 +1,37 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/app/ios/Runner/Base.lproj/Main.storyboard b/app/ios/Runner/Base.lproj/Main.storyboard new file mode 100644 index 0000000..f3c2851 --- /dev/null +++ b/app/ios/Runner/Base.lproj/Main.storyboard @@ -0,0 +1,26 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/app/ios/Runner/Info.plist b/app/ios/Runner/Info.plist new file mode 100644 index 0000000..02d286f --- /dev/null +++ b/app/ios/Runner/Info.plist @@ -0,0 +1,49 @@ + + + + + CFBundleDevelopmentRegion + $(DEVELOPMENT_LANGUAGE) + CFBundleDisplayName + Sanpresolve + CFBundleExecutable + $(EXECUTABLE_NAME) + CFBundleIdentifier + $(PRODUCT_BUNDLE_IDENTIFIER) + CFBundleInfoDictionaryVersion + 6.0 + CFBundleName + sanpresolve + CFBundlePackageType + APPL + CFBundleShortVersionString + $(FLUTTER_BUILD_NAME) + CFBundleSignature + ???? + CFBundleVersion + $(FLUTTER_BUILD_NUMBER) + LSRequiresIPhoneOS + + UILaunchStoryboardName + LaunchScreen + UIMainStoryboardFile + Main + UISupportedInterfaceOrientations + + UIInterfaceOrientationPortrait + UIInterfaceOrientationLandscapeLeft + UIInterfaceOrientationLandscapeRight + + UISupportedInterfaceOrientations~ipad + + UIInterfaceOrientationPortrait + UIInterfaceOrientationPortraitUpsideDown + UIInterfaceOrientationLandscapeLeft + UIInterfaceOrientationLandscapeRight + + CADisableMinimumFrameDurationOnPhone + + UIApplicationSupportsIndirectInputEvents + + + diff --git a/app/ios/Runner/Runner-Bridging-Header.h b/app/ios/Runner/Runner-Bridging-Header.h new file mode 100644 index 0000000..308a2a5 --- /dev/null +++ b/app/ios/Runner/Runner-Bridging-Header.h @@ -0,0 +1 @@ +#import "GeneratedPluginRegistrant.h" diff --git a/app/ios/RunnerTests/RunnerTests.swift b/app/ios/RunnerTests/RunnerTests.swift new file mode 100644 index 0000000..86a7c3b --- /dev/null +++ b/app/ios/RunnerTests/RunnerTests.swift @@ -0,0 +1,12 @@ +import Flutter +import UIKit +import XCTest + +class RunnerTests: XCTestCase { + + func testExample() { + // If you add code to the Runner application, consider adding tests here. + // See https://developer.apple.com/documentation/xctest for more information about using XCTest. + } + +} diff --git a/app/lib/.DS_Store b/app/lib/.DS_Store new file mode 100644 index 0000000..d21ac74 Binary files /dev/null and b/app/lib/.DS_Store differ diff --git a/app/lib/features/.DS_Store b/app/lib/features/.DS_Store new file mode 100644 index 0000000..3420563 Binary files /dev/null and b/app/lib/features/.DS_Store differ diff --git a/app/lib/features/complaint_form/.DS_Store b/app/lib/features/complaint_form/.DS_Store new file mode 100644 index 0000000..3da2229 Binary files /dev/null and b/app/lib/features/complaint_form/.DS_Store differ diff --git a/app/lib/features/complaint_form/data/models/userimage.dart b/app/lib/features/complaint_form/data/models/userimage.dart new file mode 100644 index 0000000..9e39d97 --- /dev/null +++ b/app/lib/features/complaint_form/data/models/userimage.dart @@ -0,0 +1,6 @@ +import 'dart:io'; +class UserImage { + String? userimagepath; + + set userimage(String userimage) {} +} \ No newline at end of file diff --git a/app/lib/features/complaint_form/data/remotedatasources/dataresource.dart b/app/lib/features/complaint_form/data/remotedatasources/dataresource.dart new file mode 100644 index 0000000..759ccd9 --- /dev/null +++ b/app/lib/features/complaint_form/data/remotedatasources/dataresource.dart @@ -0,0 +1,37 @@ + +import 'package:dio/dio.dart'; +import 'package:sanpresolve/features/complaint_form/data/models/userimage.dart'; + +class DataSources { +Future uploadFileDio(String url, String imagePath) async { + var formData = FormData.fromMap({ + 'file': await MultipartFile.fromFile(imagePath), + }); + + Dio dio = Dio(); + try { + var response = await dio.post( + url, + data: formData, + options: Options( + headers: { + 'accept': 'application/json', + 'Content-Type': 'multipart/form-data', + }, + ), + ); + + if (response.statusCode == 200) { + + return response.data["predicted_label"]; + } else { + // Handle error + // print('Error: ${response.statusCode}'); + return null; + } + } catch (e) { + print('Exception: $e'); + } +} + +} \ No newline at end of file diff --git a/app/lib/features/complaint_form/domain/usecase.dart b/app/lib/features/complaint_form/domain/usecase.dart new file mode 100644 index 0000000..ced854d --- /dev/null +++ b/app/lib/features/complaint_form/domain/usecase.dart @@ -0,0 +1,16 @@ + +import 'dart:io'; + +import 'package:sanpresolve/features/complaint_form/data/models/userimage.dart'; +import 'package:sanpresolve/features/complaint_form/data/remotedatasources/dataresource.dart'; + +class UseCases{ + Future UserImagePicked (String? userimagepath)async + { + DataSources apicall =DataSources(); + UserImage user=UserImage(); + user.userimage=userimagepath!; + String url = ''; + return await apicall.uploadFileDio(url, userimagepath); + } +} diff --git a/app/lib/features/complaint_form/presentation/bloc/complaintform_bloc.dart b/app/lib/features/complaint_form/presentation/bloc/complaintform_bloc.dart new file mode 100644 index 0000000..244da9b --- /dev/null +++ b/app/lib/features/complaint_form/presentation/bloc/complaintform_bloc.dart @@ -0,0 +1,52 @@ +import 'dart:async'; + +import 'package:bloc/bloc.dart'; +import 'package:meta/meta.dart'; + +part 'complaintform_event.dart'; +part 'complaintform_state.dart'; + +class ComplaintformBloc extends Bloc { + ComplaintformBloc() : super(ComplaintformInitialState()) { + + on(_UploadImageButtonClickedEvent); + + on(_GalleryNavigationButtonClickedEvent); + + on(_CameraNavigationButtonClickedEvent); + + on(_ImageLoadedSuccessFullyEvent); + + on(_complaintformInitialEvent); + + } + +} + + +// ignore: non_constant_identifier_names +FutureOr _UploadImageButtonClickedEvent(UploadImageButtonClickedEvent event,Emitter emit ) +{ + emit(UploadImageButtonClickedState()); +} + +FutureOr _GalleryNavigationButtonClickedEvent(GalleryNavigationButtonClickedEvent event,Emitter emit ) +{ + emit(GalleryNavigationButtonClickedState()); +} + +FutureOr _CameraNavigationButtonClickedEvent(CameraNavigationButtonClickedEventevent,Emitter emit ) +{ + emit(CameraNavigationButtonClickedState()); +} + +FutureOr _ImageLoadedSuccessFullyEvent(ImageLoadedSuccessFullyEvent event,Emitter emit ) +{ + emit(ImageLoadedSuccessFullyState()); +} + + FutureOr _complaintformInitialEvent(ComplaintformInitialEvent event, Emitter emit) { + emit(ComplaintformInitialState()); + } + + diff --git a/app/lib/features/complaint_form/presentation/bloc/complaintform_event.dart b/app/lib/features/complaint_form/presentation/bloc/complaintform_event.dart new file mode 100644 index 0000000..366ce80 --- /dev/null +++ b/app/lib/features/complaint_form/presentation/bloc/complaintform_event.dart @@ -0,0 +1,16 @@ +part of 'complaintform_bloc.dart'; + +@immutable +sealed class ComplaintformEvent {} + +class ComplaintformInitialEvent extends ComplaintformEvent {} + +class UploadImageButtonClickedEvent extends ComplaintformEvent{ } + +class GalleryNavigationButtonClickedEvent extends ComplaintformEvent{} + +class CameraNavigationButtonClickedEvent extends ComplaintformEvent{} + +class ImageLoadedSuccessFullyEvent extends ComplaintformEvent{} + + diff --git a/app/lib/features/complaint_form/presentation/bloc/complaintform_state.dart b/app/lib/features/complaint_form/presentation/bloc/complaintform_state.dart new file mode 100644 index 0000000..d636caa --- /dev/null +++ b/app/lib/features/complaint_form/presentation/bloc/complaintform_state.dart @@ -0,0 +1,15 @@ +part of 'complaintform_bloc.dart'; + +@immutable +sealed class ComplaintformState {} + +final class ComplaintformInitialState extends ComplaintformState {} + +class UploadImageButtonClickedState extends ComplaintformState{} + +class GalleryNavigationButtonClickedState extends ComplaintformState{} + +class CameraNavigationButtonClickedState extends ComplaintformState{} + +class ImageLoadedSuccessFullyState extends ComplaintformState{} + diff --git a/app/lib/features/complaint_form/presentation/pages/complaint_form.dart b/app/lib/features/complaint_form/presentation/pages/complaint_form.dart new file mode 100644 index 0000000..b429bfc --- /dev/null +++ b/app/lib/features/complaint_form/presentation/pages/complaint_form.dart @@ -0,0 +1,97 @@ +import 'package:flutter/cupertino.dart'; +import 'package:flutter/material.dart'; +import 'package:sanpresolve/features/complaint_form/presentation/widgets/image_picker.dart'; +import 'package:sanpresolve/features/complaint_form/presentation/widgets/location.dart'; + +class ComplaintForm extends StatefulWidget { + const ComplaintForm({super.key}); + + @override + State createState() => _ComplaintForm(); +} + +class _ComplaintForm extends State { + // XFile? _selectedImage=null; + String? _Prediction; + + // ignore: non_constant_identifier_names + void PredictionImageCallBack(String? Prediction) { + setState(() { + if (Prediction != null) { + _Prediction = Prediction; + } else { + _Prediction = null; + } + }); + } + + @override + Widget build(BuildContext context) { + return Scaffold( + appBar: AppBar( + title: const Text('Complaint Form'), + centerTitle: true, + backgroundColor: Colors.lime, + ), + body: SafeArea( + child: Column( + children: [ + imagepicker(ImagePrediction: PredictionImageCallBack), + Expanded( + child: Column( + children: [ + _Prediction != null + ? Container( + margin: const EdgeInsets.only(left:40,right:40,top:40), + alignment: Alignment.centerLeft, + child: Column( + children: [ + Container( + alignment: Alignment.centerLeft, + padding: EdgeInsets.only(left: 10, right: 10), + child: const Text( + "Department", + style: TextStyle(fontSize: 20), + )), + Container( + padding: EdgeInsets.only(left: 10, right: 10), + height: 55, + alignment: Alignment.centerLeft, + decoration: BoxDecoration( + color: Colors.lime, + borderRadius: BorderRadius.circular(10), + border: + Border.all(color: Colors.black, width: 1), + ), + child: Text( + _Prediction.toString(), + style: const TextStyle( + fontSize: 20, + fontWeight: FontWeight.bold, + ), + )), + ], + ), + ) + : Container(), + LocationWidget(), + TextButton( + onPressed: () {}, + child: Container( + height: 40, + decoration: BoxDecoration( + color: Colors.lime, + borderRadius: BorderRadius.circular(10)), + alignment: Alignment.center, + width: MediaQuery.of(context).size.width * 0.3, + child: Text('Submit'), + ), + ), + ], + )), + ], + ), + ), + ); + } +} diff --git a/app/lib/features/complaint_form/presentation/widgets/image_picker.dart b/app/lib/features/complaint_form/presentation/widgets/image_picker.dart new file mode 100644 index 0000000..07f797f --- /dev/null +++ b/app/lib/features/complaint_form/presentation/widgets/image_picker.dart @@ -0,0 +1,197 @@ +import 'dart:io'; +import 'package:dotted_border/dotted_border.dart'; +import 'package:flutter/cupertino.dart'; +import 'package:flutter/material.dart'; +import 'package:flutter/widgets.dart'; +import 'package:flutter_bloc/flutter_bloc.dart'; +import 'package:image_picker/image_picker.dart'; +import 'package:permission_handler/permission_handler.dart'; +import 'package:sanpresolve/features/complaint_form/domain/usecase.dart'; +import 'package:sanpresolve/features/complaint_form/presentation/bloc/complaintform_bloc.dart'; +import 'package:sanpresolve/features/validation/permissions.dart'; + +// ignore: camel_case_types +class imagepicker extends StatefulWidget { + // final Function(String?) onImagePicked; + final Function(String?) ImagePrediction; + // final BuildContext passedcontext; +const imagepicker({super.key,required this.ImagePrediction}) ; + + @override + State createState() => _imagepicker(); +} + +// ignore: camel_case_types +class _imagepicker extends State { + final Permissions ImageAccessingPermission = Permissions(); + final ImagePicker _picker = ImagePicker(); + XFile? _image=null; + void showimagepicker(BuildContext context) { + showModalBottomSheet( + context: context, + builder: (builder) { + return Container( + decoration: const BoxDecoration( + borderRadius: BorderRadius.only( + topLeft: Radius.circular(20.0), + topRight: Radius.circular(20.0), + ), + ), + height: 150, + width: MediaQuery.of(context).size.width, + child: Center( + child: Row( + mainAxisAlignment: MainAxisAlignment.center, + children: [ + Container( + margin: EdgeInsets.all(22), + child:Column(children: [ + IconButton( + icon: Icon(Icons.photo_library, color: Colors.black), + iconSize: 60.0, + onPressed: () { + Navigator.of(context).pop(); + uploadimage.add(GalleryNavigationButtonClickedEvent()); + }, + ), + Text("Gallery")]),), + SizedBox(width: 70), // Add spacing between the icons + Container( + margin: EdgeInsets.all(22), + child:Column(children: [ + IconButton( + icon: Icon(Icons.camera_alt, color: Colors.black), + iconSize: 60.0, + onPressed: () { + Navigator.of(context).pop(); + uploadimage.add(CameraNavigationButtonClickedEvent()); + }, + ), + Text("Camera") + ], + ), + ), + ] + ), + ), + ); + }); +} + + final ComplaintformBloc uploadimage = ComplaintformBloc(); + @override + Widget build(BuildContext context) { + return BlocConsumer( + bloc: uploadimage, + buildWhen: (previous, current) => current==ImageLoadedSuccessFullyState, + listener: (context, state) { + + // ignore: unrelated_type_equality_checks + if (state is UploadImageButtonClickedState) + showimagepicker(context); + else if (state is GalleryNavigationButtonClickedState) + openGallery(); + else if (state is CameraNavigationButtonClickedState) + openCamera(); + }, + builder: (context, state) { + if(_image!=null) + { + File uploadedImage=File(_image!.path); + return Center(child:Container( + height: MediaQuery.of(context).size.height * 0.3, + width: MediaQuery.of(context).size.width * 0.75, + margin: const EdgeInsets.all(30), + decoration: BoxDecoration( + color: Colors.white, + borderRadius: BorderRadius.circular(20), + border: Border.all(color: Colors.black,width: 3) + ), + child: Stack( + children: [ + Center( + child:Container( + height: MediaQuery.of(context).size.height * 0.25, + width: MediaQuery.of(context).size.width * 0.60, + child: Image.file( + uploadedImage, + fit: BoxFit.cover, + ), + ),), + Positioned( + bottom: 0.0, + right: 05.0, + child: IconButton( + icon: Icon(Icons.cancel_rounded, color: Colors.red, size: 50.0), + onPressed: () { + setState(() { + _image=null; + widget.ImagePrediction(null); + }); + } + ), + ), + ], + ), + ),); + }else { + return Center(child:Container( + margin: const EdgeInsets.all(30), + height: MediaQuery.of(context).size.height * 0.3, + width: MediaQuery.of(context).size.width * 0.75, + color: Colors.white, + child: DottedBorder( + strokeWidth: 3, + color: Colors.black38, + borderType: BorderType.RRect, + radius: const Radius.circular(20), + dashPattern: const [5, 5], + child: TextButton( + onPressed: () { + _image=null; + uploadimage.add(UploadImageButtonClickedEvent()); + }, + child: const Center( + child: Text('Upload an Image'), + )), + ), + ),); + } + }, + ); + } + + Future openGallery() async { + final XFile? pickedFile = await _picker.pickImage(source: ImageSource.gallery); + if (pickedFile != null) { + setState(() { + _image = pickedFile; + }); + // widget.onImagePicked((pickedFile.path)); + UseCases imagepickedusecase=UseCases(); + imagepickedusecase.UserImagePicked(pickedFile.path.toString()); + UseCases imagepickedusecasegallery=UseCases(); + String? result=await imagepickedusecase.UserImagePicked(pickedFile.path.toString()); + widget.ImagePrediction(result); + } + + } + + Future openCamera() async { + await ImageAccessingPermission.checkPermissions(Permission.camera, context); + final XFile? pickedFile = await _picker.pickImage(source: ImageSource.camera); + if (pickedFile != null) { + setState(() { + _image = pickedFile; + }); + // widget.onImagePicked((pickedFile.path)); + UseCases imagepickedusecasecamera=UseCases(); + String? result=await imagepickedusecasecamera.UserImagePicked(pickedFile.path.toString()); + widget.ImagePrediction(result); + } + } +} + + + + diff --git a/app/lib/features/complaint_form/presentation/widgets/location.dart b/app/lib/features/complaint_form/presentation/widgets/location.dart new file mode 100644 index 0000000..72ec26d --- /dev/null +++ b/app/lib/features/complaint_form/presentation/widgets/location.dart @@ -0,0 +1,99 @@ +import 'package:flutter/cupertino.dart'; +import 'package:flutter/material.dart'; +import 'package:geocoding/geocoding.dart'; +import 'package:geolocator/geolocator.dart'; +import 'package:permission_handler/permission_handler.dart'; +import 'package:sanpresolve/features/validation/permissions.dart'; + +class LocationWidget extends StatefulWidget{ + const LocationWidget({super.key}); + + @override + State createState() => _LocationWidget(); + +} + +class _LocationWidget extends State{ + String? _currentAddress; + Position? _currentPosition; + +Future _getCurrentPosition() async { + // ignore: non_constant_identifier_names + Permissions AskUserLocationPermission=Permissions(); + final hasPermission = await AskUserLocationPermission.handleLocationPermission(context); + if (!hasPermission) return; + + await Geolocator.getCurrentPosition( + desiredAccuracy: LocationAccuracy.high) + .then((Position position) { + + setState(() { + _currentPosition=position; + if(position!=null) + _getAddressFromLatLng(_currentPosition!); + + }); + + }).catchError((e) { + debugPrint(e); + }); +} + +Future _getAddressFromLatLng(Position position) async { + await placemarkFromCoordinates( + _currentPosition!.latitude, _currentPosition!.longitude) + .then((List placemarks) { + Placemark place = placemarks[0]; + setState(() { + print("working"); + _currentAddress = + '${place.street}, ${place.subLocality}, ${place.subAdministrativeArea}, ${place.postalCode}'; + print(_currentAddress); + }); + }).catchError((e) { + debugPrint(e); + }); + } + + + @override + Widget build(BuildContext context) { + + return Container( + margin: const EdgeInsets.all(30), + alignment: Alignment.centerLeft, + child: Column( + children: [ + Container( + alignment: Alignment.centerLeft, + padding: EdgeInsets.only(left: 10, right: 10), + child: const Text( + "Location", + style: TextStyle(fontSize: 20), + )), + TextButton( + onPressed: _getCurrentPosition , + + child:Container( + padding: EdgeInsets.only(left: 10, right: 10), + height: 55, + alignment: Alignment.centerLeft, + decoration: BoxDecoration( + color: Colors.lime, + borderRadius: BorderRadius.circular(10), + border: + Border.all(color: Colors.black, width: 1), + ), + child: Text( + _currentAddress==null?"Click to find the current location":_currentAddress!, + style: const TextStyle( + fontSize: 20, + fontWeight: FontWeight.bold, + ), + )),), + ], + ), + ); + } + +} \ No newline at end of file diff --git a/app/lib/features/validation/permissions.dart b/app/lib/features/validation/permissions.dart new file mode 100644 index 0000000..5f92ef5 --- /dev/null +++ b/app/lib/features/validation/permissions.dart @@ -0,0 +1,64 @@ +import 'package:flutter/material.dart'; +import 'package:geolocator/geolocator.dart'; +import 'package:permission_handler/permission_handler.dart'; + +class Permissions { + + Future checkPermissions(Permission permission, BuildContext context) async { + final status = await permission.status; + if (status.isDenied || status.isPermanentlyDenied) { + final result = await permission.request(); + if (!result.isGranted) { + // Handle the case when the permission is not granted + showDialog( + context: context, + builder: (BuildContext context) { + return AlertDialog( + title: const Text('Permission Required'), + content: Text('This app requires access to ${permission.toString().split('.')[1]} to function properly.'), + actions: [ + TextButton( + child: const Text('Cancel'), + onPressed: () { + Navigator.of(context).pop(); + }, + ), + TextButton( + child: const Text('Open Settings'), + onPressed: () { + openAppSettings(); + Navigator.of(context).pop(); + }, + ), + ], + ); + }, + ); + } + } + } + + + + + Future handleLocationPermission(BuildContext context) async { + var status = await Permission.location.status; + if (status.isGranted) { + return true; + } else if (status.isDenied) { + if (await Permission.location.request().isGranted) { + return true; + } else if (await Permission.location.request().isPermanentlyDenied) { + // The user has previously denied the permission and selected "Never ask again" + openAppSettings(); + return false; + } + return false; + } else { + // If the status is not determined, request the permission + return await Permission.location.request().isGranted; + } + } + + +} diff --git a/app/lib/main.dart b/app/lib/main.dart new file mode 100644 index 0000000..4d857cc --- /dev/null +++ b/app/lib/main.dart @@ -0,0 +1,113 @@ +import 'package:flutter/material.dart'; +import 'package:sanpresolve/features/complaint_form/presentation/pages/complaint_form.dart'; + +void main() { + runApp(const MyApp()); +} + + + +class MyApp extends StatelessWidget { + const MyApp({super.key}); + + // This widget is the root of your application. + @override + Widget build(BuildContext context) { + return MaterialApp( + title: 'Flutter Demo', + theme: ThemeData( + colorScheme: ColorScheme.fromSeed(seedColor: Colors.lime), + useMaterial3: true, + ), + home: const ComplaintForm(), + ); + } +} + +class MyHomePage extends StatefulWidget { + const MyHomePage({super.key, required this.title}); + + // This widget is the home page of your application. It is stateful, meaning + // that it has a State object (defined below) that contains fields that affect + // how it looks. + + // This class is the configuration for the state. It holds the values (in this + // case the title) provided by the parent (in this case the App widget) and + // used by the build method of the State. Fields in a Widget subclass are + // always marked "final". + + final String title; + + @override + State createState() => _MyHomePageState(); +} + +class _MyHomePageState extends State { + int _counter = 0; + + void _incrementCounter() { + setState(() { + // This call to setState tells the Flutter framework that something has + // changed in this State, which causes it to rerun the build method below + // so that the display can reflect the updated values. If we changed + // _counter without calling setState(), then the build method would not be + // called again, and so nothing would appear to happen. + _counter++; + }); + } + + @override + Widget build(BuildContext context) { + // This method is rerun every time setState is called, for instance as done + // by the _incrementCounter method above. + // + // The Flutter framework has been optimized to make rerunning build methods + // fast, so that you can just rebuild anything that needs updating rather + // than having to individually change instances of widgets. + return Scaffold( + appBar: AppBar( + // TRY THIS: Try changing the color here to a specific color (to + // Colors.amber, perhaps?) and trigger a hot reload to see the AppBar + // change color while the other colors stay the same. + backgroundColor: Theme.of(context).colorScheme.inversePrimary, + // Here we take the value from the MyHomePage object that was created by + // the App.build method, and use it to set our appbar title. + title: Text(widget.title), + ), + body: Center( + // Center is a layout widget. It takes a single child and positions it + // in the middle of the parent. + child: Column( + // Column is also a layout widget. It takes a list of children and + // arranges them vertically. By default, it sizes itself to fit its + // children horizontally, and tries to be as tall as its parent. + // + // Column has various properties to control how it sizes itself and + // how it positions its children. Here we use mainAxisAlignment to + // center the children vertically; the main axis here is the vertical + // axis because Columns are vertical (the cross axis would be + // horizontal). + // + // TRY THIS: Invoke "debug painting" (choose the "Toggle Debug Paint" + // action in the IDE, or press "p" in the console), to see the + // wireframe for each widget. + mainAxisAlignment: MainAxisAlignment.center, + children: [ + const Text( + 'You have pushed the button this many times:', + ), + Text( + '$_counter', + style: Theme.of(context).textTheme.headlineMedium, + ), + ], + ), + ), + floatingActionButton: FloatingActionButton( + onPressed: _incrementCounter, + tooltip: 'Increment', + child: const Icon(Icons.add), + ), // This trailing comma makes auto-formatting nicer for build methods. + ); + } +} diff --git a/app/pubspec.lock b/app/pubspec.lock new file mode 100644 index 0000000..db6cd42 --- /dev/null +++ b/app/pubspec.lock @@ -0,0 +1,602 @@ +# Generated by pub +# See https://dart.dev/tools/pub/glossary#lockfile +packages: + async: + dependency: transitive + description: + name: async + sha256: "947bfcf187f74dbc5e146c9eb9c0f10c9f8b30743e341481c1e2ed3ecc18c20c" + url: "https://pub.dev" + source: hosted + version: "2.11.0" + bloc: + dependency: "direct main" + description: + name: bloc + sha256: "106842ad6569f0b60297619e9e0b1885c2fb9bf84812935490e6c5275777804e" + url: "https://pub.dev" + source: hosted + version: "8.1.4" + boolean_selector: + dependency: transitive + description: + name: boolean_selector + sha256: "6cfb5af12253eaf2b368f07bacc5a80d1301a071c73360d746b7f2e32d762c66" + url: "https://pub.dev" + source: hosted + version: "2.1.1" + characters: + dependency: transitive + description: + name: characters + sha256: "04a925763edad70e8443c99234dc3328f442e811f1d8fd1a72f1c8ad0f69a605" + url: "https://pub.dev" + source: hosted + version: "1.3.0" + clock: + dependency: transitive + description: + name: clock + sha256: cb6d7f03e1de671e34607e909a7213e31d7752be4fb66a86d29fe1eb14bfb5cf + url: "https://pub.dev" + source: hosted + version: "1.1.1" + collection: + dependency: transitive + description: + name: collection + sha256: ee67cb0715911d28db6bf4af1026078bd6f0128b07a5f66fb2ed94ec6783c09a + url: "https://pub.dev" + source: hosted + version: "1.18.0" + cross_file: + dependency: transitive + description: + name: cross_file + sha256: "55d7b444feb71301ef6b8838dbc1ae02e63dd48c8773f3810ff53bb1e2945b32" + url: "https://pub.dev" + source: hosted + version: "0.3.4+1" + crypto: + dependency: transitive + description: + name: crypto + sha256: ff625774173754681d66daaf4a448684fb04b78f902da9cb3d308c19cc5e8bab + url: "https://pub.dev" + source: hosted + version: "3.0.3" + cupertino_icons: + dependency: "direct main" + description: + name: cupertino_icons + sha256: ba631d1c7f7bef6b729a622b7b752645a2d076dba9976925b8f25725a30e1ee6 + url: "https://pub.dev" + source: hosted + version: "1.0.8" + dio: + dependency: "direct main" + description: + name: dio + sha256: "11e40df547d418cc0c4900a9318b26304e665da6fa4755399a9ff9efd09034b5" + url: "https://pub.dev" + source: hosted + version: "5.4.3+1" + dotted_border: + dependency: "direct main" + description: + name: dotted_border + sha256: "108837e11848ca776c53b30bc870086f84b62ed6e01c503ed976e8f8c7df9c04" + url: "https://pub.dev" + source: hosted + version: "2.1.0" + fake_async: + dependency: transitive + description: + name: fake_async + sha256: "511392330127add0b769b75a987850d136345d9227c6b94c96a04cf4a391bf78" + url: "https://pub.dev" + source: hosted + version: "1.3.1" + file_selector_linux: + dependency: transitive + description: + name: file_selector_linux + sha256: "045d372bf19b02aeb69cacf8b4009555fb5f6f0b7ad8016e5f46dd1387ddd492" + url: "https://pub.dev" + source: hosted + version: "0.9.2+1" + file_selector_macos: + dependency: transitive + description: + name: file_selector_macos + sha256: f42eacb83b318e183b1ae24eead1373ab1334084404c8c16e0354f9a3e55d385 + url: "https://pub.dev" + source: hosted + version: "0.9.4" + file_selector_platform_interface: + dependency: transitive + description: + name: file_selector_platform_interface + sha256: a3994c26f10378a039faa11de174d7b78eb8f79e4dd0af2a451410c1a5c3f66b + url: "https://pub.dev" + source: hosted + version: "2.6.2" + file_selector_windows: + dependency: transitive + description: + name: file_selector_windows + sha256: d3547240c20cabf205c7c7f01a50ecdbc413755814d6677f3cb366f04abcead0 + url: "https://pub.dev" + source: hosted + version: "0.9.3+1" + fixnum: + dependency: transitive + description: + name: fixnum + sha256: "25517a4deb0c03aa0f32fd12db525856438902d9c16536311e76cdc57b31d7d1" + url: "https://pub.dev" + source: hosted + version: "1.1.0" + flutter: + dependency: "direct main" + description: flutter + source: sdk + version: "0.0.0" + flutter_bloc: + dependency: "direct main" + description: + name: flutter_bloc + sha256: b594505eac31a0518bdcb4b5b79573b8d9117b193cc80cc12e17d639b10aa27a + url: "https://pub.dev" + source: hosted + version: "8.1.6" + flutter_lints: + dependency: "direct dev" + description: + name: flutter_lints + sha256: "9e8c3858111da373efc5aa341de011d9bd23e2c5c5e0c62bccf32438e192d7b1" + url: "https://pub.dev" + source: hosted + version: "3.0.2" + flutter_plugin_android_lifecycle: + dependency: transitive + description: + name: flutter_plugin_android_lifecycle + sha256: "8cf40eebf5dec866a6d1956ad7b4f7016e6c0cc69847ab946833b7d43743809f" + url: "https://pub.dev" + source: hosted + version: "2.0.19" + flutter_test: + dependency: "direct dev" + description: flutter + source: sdk + version: "0.0.0" + flutter_web_plugins: + dependency: transitive + description: flutter + source: sdk + version: "0.0.0" + geocoding: + dependency: "direct main" + description: + name: geocoding + sha256: d580c801cba9386b4fac5047c4c785a4e19554f46be42f4f5e5b7deacd088a66 + url: "https://pub.dev" + source: hosted + version: "3.0.0" + geocoding_android: + dependency: transitive + description: + name: geocoding_android + sha256: "1b13eca79b11c497c434678fed109c2be020b158cec7512c848c102bc7232603" + url: "https://pub.dev" + source: hosted + version: "3.3.1" + geocoding_ios: + dependency: transitive + description: + name: geocoding_ios + sha256: "94ddba60387501bd1c11e18dca7c5a9e8c645d6e3da9c38b9762434941870c24" + url: "https://pub.dev" + source: hosted + version: "3.0.1" + geocoding_platform_interface: + dependency: transitive + description: + name: geocoding_platform_interface + sha256: "8c2c8226e5c276594c2e18bfe88b19110ed770aeb7c1ab50ede570be8b92229b" + url: "https://pub.dev" + source: hosted + version: "3.2.0" + geolocator: + dependency: "direct main" + description: + name: geolocator + sha256: "149876cc5207a0f5daf4fdd3bfcf0a0f27258b3fe95108fa084f527ad0568f1b" + url: "https://pub.dev" + source: hosted + version: "12.0.0" + geolocator_android: + dependency: transitive + description: + name: geolocator_android + sha256: "00c7177a95823dd3ee35ef42fd8666cd27d219ae14cea472ac76a21dff43000b" + url: "https://pub.dev" + source: hosted + version: "4.6.0" + geolocator_apple: + dependency: transitive + description: + name: geolocator_apple + sha256: bc2aca02423ad429cb0556121f56e60360a2b7d694c8570301d06ea0c00732fd + url: "https://pub.dev" + source: hosted + version: "2.3.7" + geolocator_platform_interface: + dependency: transitive + description: + name: geolocator_platform_interface + sha256: c6005787efe9e27cb0f6b50230c217e6f0ef8e1e7a8b854efb4f46489e502603 + url: "https://pub.dev" + source: hosted + version: "4.2.3" + geolocator_web: + dependency: transitive + description: + name: geolocator_web + sha256: "7a22f400d831f924a89d931ba126a10e6b8b437f31e6b9311320435f3e1571bd" + url: "https://pub.dev" + source: hosted + version: "4.0.0" + geolocator_windows: + dependency: transitive + description: + name: geolocator_windows + sha256: "53da08937d07c24b0d9952eb57a3b474e29aae2abf9dd717f7e1230995f13f0e" + url: "https://pub.dev" + source: hosted + version: "0.2.3" + http: + dependency: transitive + description: + name: http + sha256: "761a297c042deedc1ffbb156d6e2af13886bb305c2a343a4d972504cd67dd938" + url: "https://pub.dev" + source: hosted + version: "1.2.1" + http_parser: + dependency: transitive + description: + name: http_parser + sha256: "2aa08ce0341cc9b354a498388e30986515406668dbcc4f7c950c3e715496693b" + url: "https://pub.dev" + source: hosted + version: "4.0.2" + image_picker: + dependency: "direct main" + description: + name: image_picker + sha256: "021834d9c0c3de46bf0fe40341fa07168407f694d9b2bb18d532dc1261867f7a" + url: "https://pub.dev" + source: hosted + version: "1.1.2" + image_picker_android: + dependency: transitive + description: + name: image_picker_android + sha256: "0f57fee1e8bfadf8cc41818bbcd7f72e53bb768a54d9496355d5e8a5681a19f1" + url: "https://pub.dev" + source: hosted + version: "0.8.12+1" + image_picker_for_web: + dependency: transitive + description: + name: image_picker_for_web + sha256: "5d6eb13048cd47b60dbf1a5495424dea226c5faf3950e20bf8120a58efb5b5f3" + url: "https://pub.dev" + source: hosted + version: "3.0.4" + image_picker_ios: + dependency: transitive + description: + name: image_picker_ios + sha256: "6703696ad49f5c3c8356d576d7ace84d1faf459afb07accbb0fae780753ff447" + url: "https://pub.dev" + source: hosted + version: "0.8.12" + image_picker_linux: + dependency: transitive + description: + name: image_picker_linux + sha256: "4ed1d9bb36f7cd60aa6e6cd479779cc56a4cb4e4de8f49d487b1aaad831300fa" + url: "https://pub.dev" + source: hosted + version: "0.2.1+1" + image_picker_macos: + dependency: transitive + description: + name: image_picker_macos + sha256: "3f5ad1e8112a9a6111c46d0b57a7be2286a9a07fc6e1976fdf5be2bd31d4ff62" + url: "https://pub.dev" + source: hosted + version: "0.2.1+1" + image_picker_platform_interface: + dependency: transitive + description: + name: image_picker_platform_interface + sha256: "9ec26d410ff46f483c5519c29c02ef0e02e13a543f882b152d4bfd2f06802f80" + url: "https://pub.dev" + source: hosted + version: "2.10.0" + image_picker_windows: + dependency: transitive + description: + name: image_picker_windows + sha256: "6ad07afc4eb1bc25f3a01084d28520496c4a3bb0cb13685435838167c9dcedeb" + url: "https://pub.dev" + source: hosted + version: "0.2.1+1" + leak_tracker: + dependency: transitive + description: + name: leak_tracker + sha256: "78eb209deea09858f5269f5a5b02be4049535f568c07b275096836f01ea323fa" + url: "https://pub.dev" + source: hosted + version: "10.0.0" + leak_tracker_flutter_testing: + dependency: transitive + description: + name: leak_tracker_flutter_testing + sha256: b46c5e37c19120a8a01918cfaf293547f47269f7cb4b0058f21531c2465d6ef0 + url: "https://pub.dev" + source: hosted + version: "2.0.1" + leak_tracker_testing: + dependency: transitive + description: + name: leak_tracker_testing + sha256: a597f72a664dbd293f3bfc51f9ba69816f84dcd403cdac7066cb3f6003f3ab47 + url: "https://pub.dev" + source: hosted + version: "2.0.1" + lints: + dependency: transitive + description: + name: lints + sha256: cbf8d4b858bb0134ef3ef87841abdf8d63bfc255c266b7bf6b39daa1085c4290 + url: "https://pub.dev" + source: hosted + version: "3.0.0" + matcher: + dependency: transitive + description: + name: matcher + sha256: d2323aa2060500f906aa31a895b4030b6da3ebdcc5619d14ce1aada65cd161cb + url: "https://pub.dev" + source: hosted + version: "0.12.16+1" + material_color_utilities: + dependency: transitive + description: + name: material_color_utilities + sha256: "0e0a020085b65b6083975e499759762399b4475f766c21668c4ecca34ea74e5a" + url: "https://pub.dev" + source: hosted + version: "0.8.0" + meta: + dependency: transitive + description: + name: meta + sha256: d584fa6707a52763a52446f02cc621b077888fb63b93bbcb1143a7be5a0c0c04 + url: "https://pub.dev" + source: hosted + version: "1.11.0" + mime: + dependency: transitive + description: + name: mime + sha256: "2e123074287cc9fd6c09de8336dae606d1ddb88d9ac47358826db698c176a1f2" + url: "https://pub.dev" + source: hosted + version: "1.0.5" + nested: + dependency: transitive + description: + name: nested + sha256: "03bac4c528c64c95c722ec99280375a6f2fc708eec17c7b3f07253b626cd2a20" + url: "https://pub.dev" + source: hosted + version: "1.0.0" + path: + dependency: transitive + description: + name: path + sha256: "087ce49c3f0dc39180befefc60fdb4acd8f8620e5682fe2476afd0b3688bb4af" + url: "https://pub.dev" + source: hosted + version: "1.9.0" + path_drawing: + dependency: transitive + description: + name: path_drawing + sha256: bbb1934c0cbb03091af082a6389ca2080345291ef07a5fa6d6e078ba8682f977 + url: "https://pub.dev" + source: hosted + version: "1.0.1" + path_parsing: + dependency: transitive + description: + name: path_parsing + sha256: e3e67b1629e6f7e8100b367d3db6ba6af4b1f0bb80f64db18ef1fbabd2fa9ccf + url: "https://pub.dev" + source: hosted + version: "1.0.1" + permission_handler: + dependency: "direct main" + description: + name: permission_handler + sha256: "18bf33f7fefbd812f37e72091a15575e72d5318854877e0e4035a24ac1113ecb" + url: "https://pub.dev" + source: hosted + version: "11.3.1" + permission_handler_android: + dependency: transitive + description: + name: permission_handler_android + sha256: b29a799ca03be9f999aa6c39f7de5209482d638e6f857f6b93b0875c618b7e54 + url: "https://pub.dev" + source: hosted + version: "12.0.7" + permission_handler_apple: + dependency: transitive + description: + name: permission_handler_apple + sha256: e6f6d73b12438ef13e648c4ae56bd106ec60d17e90a59c4545db6781229082a0 + url: "https://pub.dev" + source: hosted + version: "9.4.5" + permission_handler_html: + dependency: transitive + description: + name: permission_handler_html + sha256: "54bf176b90f6eddd4ece307e2c06cf977fb3973719c35a93b85cc7093eb6070d" + url: "https://pub.dev" + source: hosted + version: "0.1.1" + permission_handler_platform_interface: + dependency: transitive + description: + name: permission_handler_platform_interface + sha256: "48d4fcf201a1dad93ee869ab0d4101d084f49136ec82a8a06ed9cfeacab9fd20" + url: "https://pub.dev" + source: hosted + version: "4.2.1" + permission_handler_windows: + dependency: transitive + description: + name: permission_handler_windows + sha256: "1a790728016f79a41216d88672dbc5df30e686e811ad4e698bfc51f76ad91f1e" + url: "https://pub.dev" + source: hosted + version: "0.2.1" + plugin_platform_interface: + dependency: transitive + description: + name: plugin_platform_interface + sha256: "4820fbfdb9478b1ebae27888254d445073732dae3d6ea81f0b7e06d5dedc3f02" + url: "https://pub.dev" + source: hosted + version: "2.1.8" + provider: + dependency: transitive + description: + name: provider + sha256: c8a055ee5ce3fd98d6fc872478b03823ffdb448699c6ebdbbc71d59b596fd48c + url: "https://pub.dev" + source: hosted + version: "6.1.2" + sky_engine: + dependency: transitive + description: flutter + source: sdk + version: "0.0.99" + source_span: + dependency: transitive + description: + name: source_span + sha256: "53e943d4206a5e30df338fd4c6e7a077e02254531b138a15aec3bd143c1a8b3c" + url: "https://pub.dev" + source: hosted + version: "1.10.0" + sprintf: + dependency: transitive + description: + name: sprintf + sha256: "1fc9ffe69d4df602376b52949af107d8f5703b77cda567c4d7d86a0693120f23" + url: "https://pub.dev" + source: hosted + version: "7.0.0" + stack_trace: + dependency: transitive + description: + name: stack_trace + sha256: "73713990125a6d93122541237550ee3352a2d84baad52d375a4cad2eb9b7ce0b" + url: "https://pub.dev" + source: hosted + version: "1.11.1" + stream_channel: + dependency: transitive + description: + name: stream_channel + sha256: ba2aa5d8cc609d96bbb2899c28934f9e1af5cddbd60a827822ea467161eb54e7 + url: "https://pub.dev" + source: hosted + version: "2.1.2" + string_scanner: + dependency: transitive + description: + name: string_scanner + sha256: "556692adab6cfa87322a115640c11f13cb77b3f076ddcc5d6ae3c20242bedcde" + url: "https://pub.dev" + source: hosted + version: "1.2.0" + term_glyph: + dependency: transitive + description: + name: term_glyph + sha256: a29248a84fbb7c79282b40b8c72a1209db169a2e0542bce341da992fe1bc7e84 + url: "https://pub.dev" + source: hosted + version: "1.2.1" + test_api: + dependency: transitive + description: + name: test_api + sha256: "5c2f730018264d276c20e4f1503fd1308dfbbae39ec8ee63c5236311ac06954b" + url: "https://pub.dev" + source: hosted + version: "0.6.1" + typed_data: + dependency: transitive + description: + name: typed_data + sha256: facc8d6582f16042dd49f2463ff1bd6e2c9ef9f3d5da3d9b087e244a7b564b3c + url: "https://pub.dev" + source: hosted + version: "1.3.2" + uuid: + dependency: transitive + description: + name: uuid + sha256: "814e9e88f21a176ae1359149021870e87f7cddaf633ab678a5d2b0bff7fd1ba8" + url: "https://pub.dev" + source: hosted + version: "4.4.0" + vector_math: + dependency: transitive + description: + name: vector_math + sha256: "80b3257d1492ce4d091729e3a67a60407d227c27241d6927be0130c98e741803" + url: "https://pub.dev" + source: hosted + version: "2.1.4" + vm_service: + dependency: transitive + description: + name: vm_service + sha256: b3d56ff4341b8f182b96aceb2fa20e3dcb336b9f867bc0eafc0de10f1048e957 + url: "https://pub.dev" + source: hosted + version: "13.0.0" + web: + dependency: transitive + description: + name: web + sha256: "97da13628db363c635202ad97068d47c5b8aa555808e7a9411963c533b449b27" + url: "https://pub.dev" + source: hosted + version: "0.5.1" +sdks: + dart: ">=3.3.0 <4.0.0" + flutter: ">=3.19.0" diff --git a/app/pubspec.yaml b/app/pubspec.yaml new file mode 100644 index 0000000..b24571f --- /dev/null +++ b/app/pubspec.yaml @@ -0,0 +1,99 @@ +name: sanpresolve +description: "A new Flutter project." +# The following line prevents the package from being accidentally published to +# pub.dev using `flutter pub publish`. This is preferred for private packages. +publish_to: 'none' # Remove this line if you wish to publish to pub.dev + +# The following defines the version and build number for your application. +# A version number is three numbers separated by dots, like 1.2.43 +# followed by an optional build number separated by a +. +# Both the version and the builder number may be overridden in flutter +# build by specifying --build-name and --build-number, respectively. +# In Android, build-name is used as versionName while build-number used as versionCode. +# Read more about Android versioning at https://developer.android.com/studio/publish/versioning +# In iOS, build-name is used as CFBundleShortVersionString while build-number is used as CFBundleVersion. +# Read more about iOS versioning at +# https://developer.apple.com/library/archive/documentation/General/Reference/InfoPlistKeyReference/Articles/CoreFoundationKeys.html +# In Windows, build-name is used as the major, minor, and patch parts +# of the product and file versions while build-number is used as the build suffix. +version: 1.0.0+1 + +environment: + sdk: '>=3.3.0 <4.0.0' + +# Dependencies specify other packages that your package needs in order to work. +# To automatically upgrade your package dependencies to the latest versions +# consider running `flutter pub upgrade --major-versions`. Alternatively, +# dependencies can be manually updated by changing the version numbers below to +# the latest version available on pub.dev. To see which dependencies have newer +# versions available, run `flutter pub outdated`. +dependencies: + flutter: + sdk: flutter + bloc: + flutter_bloc: + + + # The following adds the Cupertino Icons font to your application. + # Use with the CupertinoIcons class for iOS style icons. + cupertino_icons: ^1.0.6 + image_picker: ^1.1.2 + dotted_border: ^2.0.0 + permission_handler: ^11.3.1 + dio: ^5.4.3+1 + geolocator: ^12.0.0 + geocoding: ^3.0.0 + +dev_dependencies: + flutter_test: + sdk: flutter + + + # The "flutter_lints" package below contains a set of recommended lints to + # encourage good coding practices. The lint set provided by the package is + # activated in the `analysis_options.yaml` file located at the root of your + # package. See that file for information about deactivating specific lint + # rules and activating additional ones. + flutter_lints: ^3.0.0 + +# For information on the generic Dart part of this file, see the +# following page: https://dart.dev/tools/pub/pubspec + +# The following section is specific to Flutter packages. +flutter: + + # The following line ensures that the Material Icons font is + # included with your application, so that you can use the icons in + # the material Icons class. + uses-material-design: true + + # To add assets to your application, add an assets section, like this: + # assets: + # - images/a_dot_burr.jpeg + # - images/a_dot_ham.jpeg + + # An image asset can refer to one or more resolution-specific "variants", see + # https://flutter.dev/assets-and-images/#resolution-aware + + # For details regarding adding assets from package dependencies, see + # https://flutter.dev/assets-and-images/#from-packages + + # To add custom fonts to your application, add a fonts section here, + # in this "flutter" section. Each entry in this list should have a + # "family" key with the font family name, and a "fonts" key with a + # list giving the asset and other descriptors for the font. For + # example: + # fonts: + # - family: Schyler + # fonts: + # - asset: fonts/Schyler-Regular.ttf + # - asset: fonts/Schyler-Italic.ttf + # style: italic + # - family: Trajan Pro + # fonts: + # - asset: fonts/TrajanPro.ttf + # - asset: fonts/TrajanPro_Bold.ttf + # weight: 700 + # + # For details regarding fonts from package dependencies, + # see https://flutter.dev/custom-fonts/#from-packages diff --git a/app/test/widget_test.dart b/app/test/widget_test.dart new file mode 100644 index 0000000..12871fb --- /dev/null +++ b/app/test/widget_test.dart @@ -0,0 +1,30 @@ +// This is a basic Flutter widget test. +// +// To perform an interaction with a widget in your test, use the WidgetTester +// utility in the flutter_test package. For example, you can send tap and scroll +// gestures. You can also use WidgetTester to find child widgets in the widget +// tree, read text, and verify that the values of widget properties are correct. + +import 'package:flutter/material.dart'; +import 'package:flutter_test/flutter_test.dart'; + +import 'package:sanpresolve/main.dart'; + +void main() { + testWidgets('Counter increments smoke test', (WidgetTester tester) async { + // Build our app and trigger a frame. + await tester.pumpWidget(const MyApp()); + + // Verify that our counter starts at 0. + expect(find.text('0'), findsOneWidget); + expect(find.text('1'), findsNothing); + + // Tap the '+' icon and trigger a frame. + await tester.tap(find.byIcon(Icons.add)); + await tester.pump(); + + // Verify that our counter has incremented. + expect(find.text('0'), findsNothing); + expect(find.text('1'), findsOneWidget); + }); +} diff --git a/backend/.DS_Store b/backend/.DS_Store new file mode 100644 index 0000000..1abbe48 Binary files /dev/null and b/backend/.DS_Store differ diff --git a/backend/APIserver.py b/backend/APIserver.py new file mode 100644 index 0000000..e3cbf00 --- /dev/null +++ b/backend/APIserver.py @@ -0,0 +1,28 @@ +from fastapi import FastAPI, HTTPException +from fastapi import UploadFile,File +from fastapi.responses import JSONResponse +from fastapi.encoders import jsonable_encoder +from image_classification import * +import uvicorn +import io + +app = FastAPI() +model=torch.load('final_model.pth') +@app.get('/active') +def active(): + return "API is running successfully" + +@app.post('/api/imageClassifier') +async def imageClassifer(file :UploadFile= File(...)): + try: + image_bytes = await file.read() + image = Image.open(io.BytesIO(image_bytes)).convert("RGB") + predicted_label =pred_and_plot_image(model=model,image=image) + return JSONResponse(content={"predicted_label": predicted_label}, status_code=200) + + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + +if __name__ == '__main__': + uvicorn.run(app, host='', port=) diff --git a/backend/going_modular/going_modular/engine.py b/backend/going_modular/going_modular/engine.py new file mode 100644 index 0000000..e26376b --- /dev/null +++ b/backend/going_modular/going_modular/engine.py @@ -0,0 +1,195 @@ +""" +Contains functions for training and testing a PyTorch model. +""" +import torch + +from tqdm.auto import tqdm +from typing import Dict, List, Tuple + +def train_step(model: torch.nn.Module, + dataloader: torch.utils.data.DataLoader, + loss_fn: torch.nn.Module, + optimizer: torch.optim.Optimizer, + device: torch.device) -> Tuple[float, float]: + """Trains a PyTorch model for a single epoch. + + Turns a target PyTorch model to training mode and then + runs through all of the required training steps (forward + pass, loss calculation, optimizer step). + + Args: + model: A PyTorch model to be trained. + dataloader: A DataLoader instance for the model to be trained on. + loss_fn: A PyTorch loss function to minimize. + optimizer: A PyTorch optimizer to help minimize the loss function. + device: A target device to compute on (e.g. "cuda" or "cpu"). + + Returns: + A tuple of training loss and training accuracy metrics. + In the form (train_loss, train_accuracy). For example: + + (0.1112, 0.8743) + """ + # Put model in train mode + model.train() + + # Setup train loss and train accuracy values + train_loss, train_acc = 0, 0 + + # Loop through data loader data batches + for batch, (X, y) in enumerate(dataloader): + # Send data to target device + X, y = X.to(device), y.to(device) + + # 1. Forward pass + y_pred = model(X) + + # 2. Calculate and accumulate loss + loss = loss_fn(y_pred, y) + train_loss += loss.item() + + # 3. Optimizer zero grad + optimizer.zero_grad() + + # 4. Loss backward + loss.backward() + + # 5. Optimizer step + optimizer.step() + + # Calculate and accumulate accuracy metric across all batches + y_pred_class = torch.argmax(torch.softmax(y_pred, dim=1), dim=1) + train_acc += (y_pred_class == y).sum().item()/len(y_pred) + + # Adjust metrics to get average loss and accuracy per batch + train_loss = train_loss / len(dataloader) + train_acc = train_acc / len(dataloader) + return train_loss, train_acc + +def test_step(model: torch.nn.Module, + dataloader: torch.utils.data.DataLoader, + loss_fn: torch.nn.Module, + device: torch.device) -> Tuple[float, float]: + """Tests a PyTorch model for a single epoch. + + Turns a target PyTorch model to "eval" mode and then performs + a forward pass on a testing dataset. + + Args: + model: A PyTorch model to be tested. + dataloader: A DataLoader instance for the model to be tested on. + loss_fn: A PyTorch loss function to calculate loss on the test data. + device: A target device to compute on (e.g. "cuda" or "cpu"). + + Returns: + A tuple of testing loss and testing accuracy metrics. + In the form (test_loss, test_accuracy). For example: + + (0.0223, 0.8985) + """ + # Put model in eval mode + model.eval() + + # Setup test loss and test accuracy values + test_loss, test_acc = 0, 0 + + # Turn on inference context manager + with torch.inference_mode(): + # Loop through DataLoader batches + for batch, (X, y) in enumerate(dataloader): + # Send data to target device + X, y = X.to(device), y.to(device) + + # 1. Forward pass + test_pred_logits = model(X) + + # 2. Calculate and accumulate loss + loss = loss_fn(test_pred_logits, y) + test_loss += loss.item() + + # Calculate and accumulate accuracy + test_pred_labels = test_pred_logits.argmax(dim=1) + test_acc += ((test_pred_labels == y).sum().item()/len(test_pred_labels)) + + # Adjust metrics to get average loss and accuracy per batch + test_loss = test_loss / len(dataloader) + test_acc = test_acc / len(dataloader) + return test_loss, test_acc + +def train(model: torch.nn.Module, + train_dataloader: torch.utils.data.DataLoader, + test_dataloader: torch.utils.data.DataLoader, + optimizer: torch.optim.Optimizer, + loss_fn: torch.nn.Module, + epochs: int, + device: torch.device) -> Dict[str, List]: + """Trains and tests a PyTorch model. + + Passes a target PyTorch models through train_step() and test_step() + functions for a number of epochs, training and testing the model + in the same epoch loop. + + Calculates, prints and stores evaluation metrics throughout. + + Args: + model: A PyTorch model to be trained and tested. + train_dataloader: A DataLoader instance for the model to be trained on. + test_dataloader: A DataLoader instance for the model to be tested on. + optimizer: A PyTorch optimizer to help minimize the loss function. + loss_fn: A PyTorch loss function to calculate loss on both datasets. + epochs: An integer indicating how many epochs to train for. + device: A target device to compute on (e.g. "cuda" or "cpu"). + + Returns: + A dictionary of training and testing loss as well as training and + testing accuracy metrics. Each metric has a value in a list for + each epoch. + In the form: {train_loss: [...], + train_acc: [...], + test_loss: [...], + test_acc: [...]} + For example if training for epochs=2: + {train_loss: [2.0616, 1.0537], + train_acc: [0.3945, 0.3945], + test_loss: [1.2641, 1.5706], + test_acc: [0.3400, 0.2973]} + """ + # Create empty results dictionary + results = {"train_loss": [], + "train_acc": [], + "test_loss": [], + "test_acc": [] + } + + # Make sure model on target device + model.to(device) + + # Loop through training and testing steps for a number of epochs + for epoch in tqdm(range(epochs)): + train_loss, train_acc = train_step(model=model, + dataloader=train_dataloader, + loss_fn=loss_fn, + optimizer=optimizer, + device=device) + test_loss, test_acc = test_step(model=model, + dataloader=test_dataloader, + loss_fn=loss_fn, + device=device) + + # Print out what's happening + print( + f"Epoch: {epoch+1} | " + f"train_loss: {train_loss:.4f} | " + f"train_acc: {train_acc:.4f} | " + f"test_loss: {test_loss:.4f} | " + f"test_acc: {test_acc:.4f}" + ) + + # Update results dictionary + results["train_loss"].append(train_loss) + results["train_acc"].append(train_acc) + results["test_loss"].append(test_loss) + results["test_acc"].append(test_acc) + + # Return the filled results at the end of the epochs + return results diff --git a/backend/going_modular/going_modular/model_builder.py b/backend/going_modular/going_modular/model_builder.py new file mode 100644 index 0000000..e51f422 --- /dev/null +++ b/backend/going_modular/going_modular/model_builder.py @@ -0,0 +1,56 @@ +""" +Contains PyTorch model code to instantiate a TinyVGG model. +""" +import torch +from torch import nn + +class TinyVGG(nn.Module): + """Creates the TinyVGG architecture. + + Replicates the TinyVGG architecture from the CNN explainer website in PyTorch. + See the original architecture here: https://poloclub.github.io/cnn-explainer/ + + Args: + input_shape: An integer indicating number of input channels. + hidden_units: An integer indicating number of hidden units between layers. + output_shape: An integer indicating number of output units. + """ + def __init__(self, input_shape: int, hidden_units: int, output_shape: int) -> None: + super().__init__() + self.conv_block_1 = nn.Sequential( + nn.Conv2d(in_channels=input_shape, + out_channels=hidden_units, + kernel_size=3, + stride=1, + padding=0), + nn.ReLU(), + nn.Conv2d(in_channels=hidden_units, + out_channels=hidden_units, + kernel_size=3, + stride=1, + padding=0), + nn.ReLU(), + nn.MaxPool2d(kernel_size=2, + stride=2) + ) + self.conv_block_2 = nn.Sequential( + nn.Conv2d(hidden_units, hidden_units, kernel_size=3, padding=0), + nn.ReLU(), + nn.Conv2d(hidden_units, hidden_units, kernel_size=3, padding=0), + nn.ReLU(), + nn.MaxPool2d(2) + ) + self.classifier = nn.Sequential( + nn.Flatten(), + # Where did this in_features shape come from? + # It's because each layer of our network compresses and changes the shape of our inputs data. + nn.Linear(in_features=hidden_units*13*13, + out_features=output_shape) + ) + + def forward(self, x: torch.Tensor): + x = self.conv_block_1(x) + x = self.conv_block_2(x) + x = self.classifier(x) + return x + # return self.classifier(self.block_2(self.block_1(x))) # <- leverage the benefits of operator fusion diff --git a/backend/going_modular/going_modular/predictions.py b/backend/going_modular/going_modular/predictions.py new file mode 100644 index 0000000..8c4077a --- /dev/null +++ b/backend/going_modular/going_modular/predictions.py @@ -0,0 +1,86 @@ +""" +Utility functions to make predictions. + +Main reference for code creation: https://www.learnpytorch.io/06_pytorch_transfer_learning/#6-make-predictions-on-images-from-the-test-set +""" +import torch +import torchvision +from torchvision import transforms +import matplotlib.pyplot as plt + +from typing import List, Tuple + +from PIL import Image + +# Set device +device = "cuda" if torch.cuda.is_available() else "cpu" + +# Predict on a target image with a target model +# Function created in: https://www.learnpytorch.io/06_pytorch_transfer_learning/#6-make-predictions-on-images-from-the-test-set +def pred_and_plot_image( + model: torch.nn.Module, + class_names: List[str], + image_path: str, + image_size: Tuple[int, int] = (224, 224), + transform: torchvision.transforms = None, + device: torch.device = device, +): + """Predicts on a target image with a target model. + + Args: + model (torch.nn.Module): A trained (or untrained) PyTorch model to predict on an image. + class_names (List[str]): A list of target classes to map predictions to. + image_path (str): Filepath to target image to predict on. + image_size (Tuple[int, int], optional): Size to transform target image to. Defaults to (224, 224). + transform (torchvision.transforms, optional): Transform to perform on image. Defaults to None which uses ImageNet normalization. + device (torch.device, optional): Target device to perform prediction on. Defaults to device. + """ + + # Open image + img = Image.open(image_path) + + + # Create transformation for image (if one doesn't exist) + if transform is not None: + image_transform = transform + else: + image_transform = transforms.Compose( + [ + transforms.Resize(image_size), + transforms.ToTensor(), + transforms.Normalize( + mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225] + ), + ] + ) + + ### Predict on image ### + + # Make sure the model is on the target device + model.to(device) + + # Turn on model evaluation mode and inference mode + model.eval() + with torch.inference_mode(): + # Transform and add an extra dimension to image (model requires samples in [batch_size, color_channels, height, width]) + transformed_image = image_transform(img).unsqueeze(dim=0) + + # Make a prediction on image with an extra dimension and send it to the target device + target_image_pred = model(transformed_image.to(device)) + + + + # Convert logits -> prediction probabilities (using torch.softmax() for multi-class classification) + target_image_pred_probs = torch.softmax(target_image_pred, dim=1) + + # Convert prediction probabilities -> prediction labels + target_image_pred_label = torch.argmax(target_image_pred_probs, dim=1) + + # Plot image with predicted label and probability + plt.figure() + plt.imshow(img) + plt.title( + f"Pred: {class_names[target_image_pred_label]} | Prob: {target_image_pred_probs.max():.3f}" + ) + plt.axis(False) + diff --git a/backend/going_modular/going_modular/train.py b/backend/going_modular/going_modular/train.py new file mode 100644 index 0000000..6040b30 --- /dev/null +++ b/backend/going_modular/going_modular/train.py @@ -0,0 +1,62 @@ +""" +Trains a PyTorch image classification model using device-agnostic code. +""" + +import os +import torch +import data_setup, engine, model_builder, utils + +from torchvision import transforms + +# Setup hyperparameters +NUM_EPOCHS = 5 +BATCH_SIZE = 32 +HIDDEN_UNITS = 10 +LEARNING_RATE = 0.001 + +# Setup directories +train_dir = "data/pizza_steak_sushi/train" +test_dir = "data/pizza_steak_sushi/test" + +# Setup target device +device = "cuda" if torch.cuda.is_available() else "cpu" + +# Create transforms +data_transform = transforms.Compose([ + transforms.Resize((64, 64)), + transforms.ToTensor() +]) + +# Create DataLoaders with help from data_setup.py +train_dataloader, test_dataloader, class_names = data_setup.create_dataloaders( + train_dir=train_dir, + test_dir=test_dir, + transform=data_transform, + batch_size=BATCH_SIZE +) + +# Create model with help from model_builder.py +model = model_builder.TinyVGG( + input_shape=3, + hidden_units=HIDDEN_UNITS, + output_shape=len(class_names) +).to(device) + +# Set loss and optimizer +loss_fn = torch.nn.CrossEntropyLoss() +optimizer = torch.optim.Adam(model.parameters(), + lr=LEARNING_RATE) + +# Start training with help from engine.py +engine.train(model=model, + train_dataloader=train_dataloader, + test_dataloader=test_dataloader, + loss_fn=loss_fn, + optimizer=optimizer, + epochs=NUM_EPOCHS, + device=device) + +# Save the model with help from utils.py +utils.save_model(model=model, + target_dir="models", + model_name="05_going_modular_script_mode_tinyvgg_model.pth") diff --git a/backend/going_modular/going_modular/utils.py b/backend/going_modular/going_modular/utils.py new file mode 100644 index 0000000..da1ce20 --- /dev/null +++ b/backend/going_modular/going_modular/utils.py @@ -0,0 +1,35 @@ +""" +Contains various utility functions for PyTorch model training and saving. +""" +import torch +from pathlib import Path + +def save_model(model: torch.nn.Module, + target_dir: str, + model_name: str): + """Saves a PyTorch model to a target directory. + + Args: + model: A target PyTorch model to save. + target_dir: A directory for saving the model to. + model_name: A filename for the saved model. Should include + either ".pth" or ".pt" as the file extension. + + Example usage: + save_model(model=model_0, + target_dir="models", + model_name="05_going_modular_tingvgg_model.pth") + """ + # Create target directory + target_dir_path = Path(target_dir) + target_dir_path.mkdir(parents=True, + exist_ok=True) + + # Create model save path + assert model_name.endswith(".pth") or model_name.endswith(".pt"), "model_name should end with '.pt' or '.pth'" + model_save_path = target_dir_path / model_name + + # Save the model state_dict() + print(f"[INFO] Saving model to: {model_save_path}") + torch.save(obj=model.state_dict(), + f=model_save_path) diff --git a/backend/helper_functions.py b/backend/helper_functions.py new file mode 100644 index 0000000..cb4576e --- /dev/null +++ b/backend/helper_functions.py @@ -0,0 +1,194 @@ +""" +A series of helper functions used throughout the course. + +If a function gets defined once and could be used over and over, it'll go in here. +""" +import torch +import matplotlib.pyplot as plt +import numpy as np + +from torch import nn +import os +import zipfile +from pathlib import Path +import requests +import os + + + +# Plot linear data or training and test and predictions (optional) +def plot_predictions( + train_data, train_labels, test_data, test_labels, predictions=None +): + """ + Plots linear training data and test data and compares predictions. + """ + plt.figure(figsize=(10, 7)) + + # Plot training data in blue + plt.scatter(train_data, train_labels, c="b", s=4, label="Training data") + + # Plot test data in green + plt.scatter(test_data, test_labels, c="g", s=4, label="Testing data") + + if predictions is not None: + # Plot the predictions in red (predictions were made on the test data) + plt.scatter(test_data, predictions, c="r", s=4, label="Predictions") + + # Show the legend + plt.legend(prop={"size": 14}) + + +# Calculate accuracy (a classification metric) +def accuracy_fn(y_true, y_pred): + """Calculates accuracy between truth labels and predictions. + + Args: + y_true (torch.Tensor): Truth labels for predictions. + y_pred (torch.Tensor): Predictions to be compared to predictions. + + Returns: + [torch.float]: Accuracy value between y_true and y_pred, e.g. 78.45 + """ + correct = torch.eq(y_true, y_pred).sum().item() + acc = (correct / len(y_pred)) * 100 + return acc + + +def print_train_time(start, end, device=None): + """Prints difference between start and end time. + + Args: + start (float): Start time of computation (preferred in timeit format). + end (float): End time of computation. + device ([type], optional): Device that compute is running on. Defaults to None. + + Returns: + float: time between start and end in seconds (higher is longer). + """ + total_time = end - start + print(f"\nTrain time on {device}: {total_time:.3f} seconds") + return total_time + + +# Plot loss curves of a model +def plot_loss_curves(results): + """Plots training curves of a results dictionary. + + Args: + results (dict): dictionary containing list of values, e.g. + {"train_loss": [...], + "train_acc": [...], + "test_loss": [...], + "test_acc": [...]} + """ + loss = results["train_loss"] + test_loss = results["test_loss"] + + accuracy = results["train_acc"] + test_accuracy = results["test_acc"] + + epochs = range(len(results["train_loss"])) + + plt.figure(figsize=(15, 7)) + + # Plot loss + plt.subplot(1, 2, 1) + plt.plot(epochs, loss, label="train_loss") + plt.plot(epochs, test_loss, label="test_loss") + plt.title("Loss") + plt.xlabel("Epochs") + plt.legend() + + # Plot accuracy + plt.subplot(1, 2, 2) + plt.plot(epochs, accuracy, label="train_accuracy") + plt.plot(epochs, test_accuracy, label="test_accuracy") + plt.title("Accuracy") + plt.xlabel("Epochs") + plt.legend() + + +# Pred and plot image function from notebook 04 +# See creation: https://www.learnpytorch.io/04_pytorch_custom_datasets/#113-putting-custom-image-prediction-together-building-a-function +from typing import List +import torchvision + + +def pred_and_plot_image( + model: torch.nn.Module, + image_path: str, + class_names: List[str] = None, + transform=None, + device: torch.device = "cuda" if torch.cuda.is_available() else "cpu", +): + """Makes a prediction on a target image with a trained model and plots the image. + + Args: + model (torch.nn.Module): trained PyTorch image classification model. + image_path (str): filepath to target image. + class_names (List[str], optional): different class names for target image. Defaults to None. + transform (_type_, optional): transform of target image. Defaults to None. + device (torch.device, optional): target device to compute on. Defaults to "cuda" if torch.cuda.is_available() else "cpu". + + Returns: + Matplotlib plot of target image and model prediction as title. + + Example usage: + pred_and_plot_image(model=model, + image="some_image.jpeg", + class_names=["class_1", "class_2", "class_3"], + transform=torchvision.transforms.ToTensor(), + device=device) + """ + + # 1. Load in image and convert the tensor values to float32 + target_image = torchvision.io.read_image(str(image_path)).type(torch.float32) + print('aman') + # 2. Divide the image pixel values by 255 to get them between [0, 1] + target_image = target_image / 255.0 + + # 3. Transform if necessary + if transform: + target_image = transform(target_image) + + # 4. Make sure the model is on the target device + model.to(device) + + # 5. Turn on model evaluation mode and inference mode + model.eval() + with torch.inference_mode(): + # Add an extra dimension to the image + target_image = target_image.unsqueeze(dim=0) + + # Make a prediction on image with an extra dimension and send it to the target device + target_image_pred = model(target_image.to(device)) + + # 6. Convert logits -> prediction probabilities (using torch.softmax() for multi-class classification) + target_image_pred_probs = torch.softmax(target_image_pred, dim=1) + + # 7. Convert prediction probabilities -> prediction labels + target_image_pred_label = torch.argmax(target_image_pred_probs, dim=1) + + # 8. Plot the image alongside the prediction and prediction probability + plt.imshow( + target_image.squeeze().permute(1, 2, 0) + ) # make sure it's the right size for matplotlib + if class_names: + title = f"Pred: {class_names[target_image_pred_label.cpu()]} | Prob: {target_image_pred_probs.max().cpu():.3f}" + else: + title = f"Pred: {target_image_pred_label} | Prob: {target_image_pred_probs.max().cpu():.3f}" + plt.title(title) + plt.axis(False) + +def set_seeds(seed: int=42): + """Sets random sets for torch operations. + + Args: + seed (int, optional): Random seed to set. Defaults to 42. + """ + # Set the seed for general torch operations + torch.manual_seed(seed) + # Set the seed for CUDA torch operations (ones that happen on the GPU) + torch.cuda.manual_seed(seed) + diff --git a/backend/image_classification.py b/backend/image_classification.py new file mode 100644 index 0000000..183cdb5 --- /dev/null +++ b/backend/image_classification.py @@ -0,0 +1,65 @@ +import torch +from torch import nn +import torchvision +from torchvision import transforms +import matplotlib.pyplot as plt +from typing import List, Tuple +from PIL import Image + +# Set device +device = "cuda" if torch.cuda.is_available() else "cpu" +custom_image_path = "complaint_dataset/test/Electricity Department/download.jpeg" +class_names = ['Electricity Department','Nature and Recreation Department','Road Construction and Management','Waste Management','Water Supply and Management'] + + +def pred_and_plot_image( + model:torch.nn.Module, + image: Image.Image, + class_names: List[str] = class_names, + image_size: Tuple[int, int] = (224, 224), + transform: torchvision.transforms = None, + device: torch.device = device, +): + + img = image + model.eval() + + # Create transformation for image (if one doesn't exist) + if transform is not None: + image_transform = transform + else: + image_transform = transforms.Compose( + [ + transforms.Resize(image_size), + transforms.ToTensor(), + transforms.Normalize( + mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225] + ), + ] + ) + + ### Predict on image ### + + # Make sure the model is on the target device + model.to(device) + + # Turn on model evaluation mode and inference mode + model.eval() + with torch.inference_mode(): + # Transform and add an extra dimension to image (model requires samples in [batch_size, color_channels, height, width]) + transformed_image = image_transform(img).unsqueeze(dim=0) + + # Make a prediction on image with an extra dimension and send it to the target device + target_image_pred = model(transformed_image.to(device)) + + # Convert logits -> prediction probabilities (using torch.softmax() for multi-class classification) + target_image_pred_probs = torch.softmax(target_image_pred, dim=1) + + # Convert prediction probabilities -> prediction labels + target_image_pred_label = torch.argmax(target_image_pred_probs, dim=1) + predicted_class = class_names[target_image_pred_label] + return predicted_class + + + + diff --git a/backend/model.ipynb b/backend/model.ipynb new file mode 100644 index 0000000..fd29b52 --- /dev/null +++ b/backend/model.ipynb @@ -0,0 +1,684 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import torch\n", + "import torchvision\n", + "from torch import nn\n", + "from torchvision import transforms\n", + "from helper_functions import set_seeds" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "device='cpu'" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "# 1. Get pretrained weights for ViT-Base\n", + "pretrained_vit_weights = torchvision.models.ViT_B_16_Weights.DEFAULT \n", + "\n", + "# 2. Setup a ViT model instance with pretrained weights\n", + "pretrained_vit = torchvision.models.vit_b_16(weights=pretrained_vit_weights).to(device)\n", + "\n", + "# 3. Freeze the base parameters\n", + "for parameter in pretrained_vit.parameters():\n", + " parameter.requires_grad = False\n", + " \n", + "# 4. Change the classifier head \n", + "class_names = ['Electricity Department','Nature and Recreation Department','Road Construction and Management','Waste Management','Water Supply and Management']\n", + "\n", + "set_seeds()\n", + "pretrained_vit.heads = nn.Linear(in_features=768, out_features=len(class_names)).to(device)\n", + "# pretrained_vit # uncomment for model output " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "============================================================================================================================================\n", + "Layer (type (var_name)) Input Shape Output Shape Param # Trainable\n", + "============================================================================================================================================\n", + "VisionTransformer (VisionTransformer) [32, 3, 224, 224] [32, 5] 768 Partial\n", + "├─Conv2d (conv_proj) [32, 3, 224, 224] [32, 768, 14, 14] (590,592) False\n", + "├─Encoder (encoder) [32, 197, 768] [32, 197, 768] 151,296 False\n", + "│ └─Dropout (dropout) [32, 197, 768] [32, 197, 768] -- --\n", + "│ └─Sequential (layers) [32, 197, 768] [32, 197, 768] -- False\n", + "│ │ └─EncoderBlock (encoder_layer_0) [32, 197, 768] [32, 197, 768] (7,087,872) False\n", + "│ │ └─EncoderBlock (encoder_layer_1) [32, 197, 768] [32, 197, 768] (7,087,872) False\n", + "│ │ └─EncoderBlock (encoder_layer_2) [32, 197, 768] [32, 197, 768] (7,087,872) False\n", + "│ │ └─EncoderBlock (encoder_layer_3) [32, 197, 768] [32, 197, 768] (7,087,872) False\n", + "│ │ └─EncoderBlock (encoder_layer_4) [32, 197, 768] [32, 197, 768] (7,087,872) False\n", + "│ │ └─EncoderBlock (encoder_layer_5) [32, 197, 768] [32, 197, 768] (7,087,872) False\n", + "│ │ └─EncoderBlock (encoder_layer_6) [32, 197, 768] [32, 197, 768] (7,087,872) False\n", + "│ │ └─EncoderBlock (encoder_layer_7) [32, 197, 768] [32, 197, 768] (7,087,872) False\n", + "│ │ └─EncoderBlock (encoder_layer_8) [32, 197, 768] [32, 197, 768] (7,087,872) False\n", + "│ │ └─EncoderBlock (encoder_layer_9) [32, 197, 768] [32, 197, 768] (7,087,872) False\n", + "│ │ └─EncoderBlock (encoder_layer_10) [32, 197, 768] [32, 197, 768] (7,087,872) False\n", + "│ │ └─EncoderBlock (encoder_layer_11) [32, 197, 768] [32, 197, 768] (7,087,872) False\n", + "│ └─LayerNorm (ln) [32, 197, 768] [32, 197, 768] (1,536) False\n", + "├─Linear (heads) [32, 768] [32, 5] 3,845 True\n", + "============================================================================================================================================\n", + "Total params: 85,802,501\n", + "Trainable params: 3,845\n", + "Non-trainable params: 85,798,656\n", + "Total mult-adds (Units.GIGABYTES): 5.52\n", + "============================================================================================================================================\n", + "Input size (MB): 19.27\n", + "Forward/backward pass size (MB): 3330.74\n", + "Params size (MB): 229.21\n", + "Estimated Total Size (MB): 3579.21\n", + "============================================================================================================================================" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from torchinfo import summary\n", + "\n", + "# Print a summary using torchinfo (uncomment for actual output)\n", + "summary(model=pretrained_vit, \n", + " input_size=(32, 3, 224, 224), # (batch_size, color_channels, height, width)\n", + " # col_names=[\"input_size\"], # uncomment for smaller output\n", + " col_names=[\"input_size\", \"output_size\", \"num_params\", \"trainable\"],\n", + " col_width=20,\n", + " row_settings=[\"var_names\"]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ImageClassification(\n", + " crop_size=[224]\n", + " resize_size=[256]\n", + " mean=[0.485, 0.456, 0.406]\n", + " std=[0.229, 0.224, 0.225]\n", + " interpolation=InterpolationMode.BILINEAR\n", + ")\n" + ] + } + ], + "source": [ + "pretrained_vit_transforms = pretrained_vit_weights.transforms()\n", + "print(pretrained_vit_transforms)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "train_dir = 'complaint_dataset/train'\n", + "test_dir = 'complaint_dataset/test'" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "from torchvision import datasets, transforms\n", + "from torch.utils.data import DataLoader\n", + "\n", + "NUM_WORKERS = os.cpu_count()\n", + "\n", + "def create_dataloaders(\n", + " train_dir: str, \n", + " test_dir: str, \n", + " transform: transforms.Compose, \n", + " batch_size: int, \n", + " num_workers: int=NUM_WORKERS\n", + "):\n", + "\n", + " # Use ImageFolder to create dataset(s)\n", + " train_data = datasets.ImageFolder(train_dir, transform=transform)\n", + " test_data = datasets.ImageFolder(test_dir, transform=transform)\n", + "\n", + " # Get class names\n", + " class_names = train_data.classes\n", + "\n", + " # Turn images into data loaders\n", + " train_dataloader = DataLoader(\n", + " train_data,\n", + " batch_size=batch_size,\n", + " shuffle=True,\n", + " num_workers=num_workers,\n", + " pin_memory=True,\n", + " )\n", + " test_dataloader = DataLoader(\n", + " test_data,\n", + " batch_size=batch_size,\n", + " shuffle=False,\n", + " num_workers=num_workers,\n", + " pin_memory=True,\n", + " )\n", + "\n", + " return train_dataloader, test_dataloader, class_names\n" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "# Setup dataloaders\n", + "train_dataloader_pretrained, test_dataloader_pretrained, class_names = create_dataloaders(train_dir=train_dir,\n", + " test_dir=test_dir,\n", + " transform=pretrained_vit_transforms,\n", + " batch_size=32) # Coul" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 10%|█ | 1/10 [00:39<05:54, 39.36s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 1 | train_loss: 1.5883 | train_acc: 0.2598 | test_loss: 1.2689 | test_acc: 0.6000\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 20%|██ | 2/10 [01:18<05:12, 39.03s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 2 | train_loss: 1.1868 | train_acc: 0.5990 | test_loss: 1.0282 | test_acc: 0.8000\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 30%|███ | 3/10 [01:56<04:31, 38.82s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 3 | train_loss: 0.9060 | train_acc: 0.7964 | test_loss: 0.8714 | test_acc: 0.8000\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 40%|████ | 4/10 [02:36<03:54, 39.15s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 4 | train_loss: 0.7098 | train_acc: 0.9216 | test_loss: 0.7383 | test_acc: 0.8000\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 50%|█████ | 5/10 [03:15<03:16, 39.23s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 5 | train_loss: 0.5608 | train_acc: 0.9688 | test_loss: 0.6267 | test_acc: 1.0000\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 60%|██████ | 6/10 [03:54<02:36, 39.12s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 6 | train_loss: 0.4494 | train_acc: 0.9688 | test_loss: 0.5343 | test_acc: 1.0000\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 70%|███████ | 7/10 [04:34<01:57, 39.23s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 7 | train_loss: 0.3616 | train_acc: 0.9841 | test_loss: 0.4688 | test_acc: 1.0000\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 80%|████████ | 8/10 [05:13<01:18, 39.12s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 8 | train_loss: 0.2975 | train_acc: 0.9841 | test_loss: 0.4167 | test_acc: 0.8000\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 90%|█████████ | 9/10 [05:51<00:39, 39.02s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 9 | train_loss: 0.2494 | train_acc: 0.9922 | test_loss: 0.3768 | test_acc: 0.8000\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 10/10 [06:30<00:00, 39.06s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 10 | train_loss: 0.2128 | train_acc: 1.0000 | test_loss: 0.3465 | test_acc: 0.8000\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "from going_modular.going_modular import engine\n", + "\n", + "# Create optimizer and loss function\n", + "optimizer = torch.optim.Adam(params=pretrained_vit.parameters(), \n", + " lr=1e-3)\n", + "loss_fn = torch.nn.CrossEntropyLoss()\n", + "\n", + "# Train the classifier head of the pretrained ViT feature extractor model\n", + "set_seeds()\n", + "pretrained_vit_results = engine.train(model=pretrained_vit,\n", + " train_dataloader=train_dataloader_pretrained,\n", + " test_dataloader=test_dataloader_pretrained,\n", + " optimizer=optimizer,\n", + " loss_fn=loss_fn,\n", + " epochs=10,\n", + " device=device)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from going_modular.going_modular.predictions import pred_and_plot_image\n", + "\n", + "class_names = ['Electricity Department','Nature and Recreation Department','Road Construction and Management','Waste Management','Water Supply and Management']\n", + "# Setup custom image path\n", + "custom_image_path = \"complaint_dataset/train/Road Construction and Management/2.jpeg\"\n", + "\n", + "# Predict on custom image\n", + "pred_and_plot_image(model=pretrained_vit,\n", + " image_path=custom_image_path,\n", + " class_names=class_names)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "torch.save(pretrained_vit, 'test_model.pth') " + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "VisionTransformer(\n", + " (conv_proj): Conv2d(3, 768, kernel_size=(16, 16), stride=(16, 16))\n", + " (encoder): Encoder(\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " (layers): Sequential(\n", + " (encoder_layer_0): EncoderBlock(\n", + " (ln_1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (self_attention): MultiheadAttention(\n", + " (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n", + " )\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " (ln_2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (mlp): MLPBlock(\n", + " (0): Linear(in_features=768, out_features=3072, bias=True)\n", + " (1): GELU(approximate='none')\n", + " (2): Dropout(p=0.0, inplace=False)\n", + " (3): Linear(in_features=3072, out_features=768, bias=True)\n", + " (4): Dropout(p=0.0, inplace=False)\n", + " )\n", + " )\n", + " (encoder_layer_1): EncoderBlock(\n", + " (ln_1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (self_attention): MultiheadAttention(\n", + " (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n", + " )\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " (ln_2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (mlp): MLPBlock(\n", + " (0): Linear(in_features=768, out_features=3072, bias=True)\n", + " (1): GELU(approximate='none')\n", + " (2): Dropout(p=0.0, inplace=False)\n", + " (3): Linear(in_features=3072, out_features=768, bias=True)\n", + " (4): Dropout(p=0.0, inplace=False)\n", + " )\n", + " )\n", + " (encoder_layer_2): EncoderBlock(\n", + " (ln_1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (self_attention): MultiheadAttention(\n", + " (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n", + " )\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " (ln_2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (mlp): MLPBlock(\n", + " (0): Linear(in_features=768, out_features=3072, bias=True)\n", + " (1): GELU(approximate='none')\n", + " (2): Dropout(p=0.0, inplace=False)\n", + " (3): Linear(in_features=3072, out_features=768, bias=True)\n", + " (4): Dropout(p=0.0, inplace=False)\n", + " )\n", + " )\n", + " (encoder_layer_3): EncoderBlock(\n", + " (ln_1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (self_attention): MultiheadAttention(\n", + " (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n", + " )\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " (ln_2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (mlp): MLPBlock(\n", + " (0): Linear(in_features=768, out_features=3072, bias=True)\n", + " (1): GELU(approximate='none')\n", + " (2): Dropout(p=0.0, inplace=False)\n", + " (3): Linear(in_features=3072, out_features=768, bias=True)\n", + " (4): Dropout(p=0.0, inplace=False)\n", + " )\n", + " )\n", + " (encoder_layer_4): EncoderBlock(\n", + " (ln_1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (self_attention): MultiheadAttention(\n", + " (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n", + " )\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " (ln_2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (mlp): MLPBlock(\n", + " (0): Linear(in_features=768, out_features=3072, bias=True)\n", + " (1): GELU(approximate='none')\n", + " (2): Dropout(p=0.0, inplace=False)\n", + " (3): Linear(in_features=3072, out_features=768, bias=True)\n", + " (4): Dropout(p=0.0, inplace=False)\n", + " )\n", + " )\n", + " (encoder_layer_5): EncoderBlock(\n", + " (ln_1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (self_attention): MultiheadAttention(\n", + " (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n", + " )\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " (ln_2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (mlp): MLPBlock(\n", + " (0): Linear(in_features=768, out_features=3072, bias=True)\n", + " (1): GELU(approximate='none')\n", + " (2): Dropout(p=0.0, inplace=False)\n", + " (3): Linear(in_features=3072, out_features=768, bias=True)\n", + " (4): Dropout(p=0.0, inplace=False)\n", + " )\n", + " )\n", + " (encoder_layer_6): EncoderBlock(\n", + " (ln_1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (self_attention): MultiheadAttention(\n", + " (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n", + " )\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " (ln_2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (mlp): MLPBlock(\n", + " (0): Linear(in_features=768, out_features=3072, bias=True)\n", + " (1): GELU(approximate='none')\n", + " (2): Dropout(p=0.0, inplace=False)\n", + " (3): Linear(in_features=3072, out_features=768, bias=True)\n", + " (4): Dropout(p=0.0, inplace=False)\n", + " )\n", + " )\n", + " (encoder_layer_7): EncoderBlock(\n", + " (ln_1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (self_attention): MultiheadAttention(\n", + " (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n", + " )\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " (ln_2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (mlp): MLPBlock(\n", + " (0): Linear(in_features=768, out_features=3072, bias=True)\n", + " (1): GELU(approximate='none')\n", + " (2): Dropout(p=0.0, inplace=False)\n", + " (3): Linear(in_features=3072, out_features=768, bias=True)\n", + " (4): Dropout(p=0.0, inplace=False)\n", + " )\n", + " )\n", + " (encoder_layer_8): EncoderBlock(\n", + " (ln_1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (self_attention): MultiheadAttention(\n", + " (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n", + " )\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " (ln_2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (mlp): MLPBlock(\n", + " (0): Linear(in_features=768, out_features=3072, bias=True)\n", + " (1): GELU(approximate='none')\n", + " (2): Dropout(p=0.0, inplace=False)\n", + " (3): Linear(in_features=3072, out_features=768, bias=True)\n", + " (4): Dropout(p=0.0, inplace=False)\n", + " )\n", + " )\n", + " (encoder_layer_9): EncoderBlock(\n", + " (ln_1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (self_attention): MultiheadAttention(\n", + " (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n", + " )\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " (ln_2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (mlp): MLPBlock(\n", + " (0): Linear(in_features=768, out_features=3072, bias=True)\n", + " (1): GELU(approximate='none')\n", + " (2): Dropout(p=0.0, inplace=False)\n", + " (3): Linear(in_features=3072, out_features=768, bias=True)\n", + " (4): Dropout(p=0.0, inplace=False)\n", + " )\n", + " )\n", + " (encoder_layer_10): EncoderBlock(\n", + " (ln_1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (self_attention): MultiheadAttention(\n", + " (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n", + " )\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " (ln_2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (mlp): MLPBlock(\n", + " (0): Linear(in_features=768, out_features=3072, bias=True)\n", + " (1): GELU(approximate='none')\n", + " (2): Dropout(p=0.0, inplace=False)\n", + " (3): Linear(in_features=3072, out_features=768, bias=True)\n", + " (4): Dropout(p=0.0, inplace=False)\n", + " )\n", + " )\n", + " (encoder_layer_11): EncoderBlock(\n", + " (ln_1): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (self_attention): MultiheadAttention(\n", + " (out_proj): NonDynamicallyQuantizableLinear(in_features=768, out_features=768, bias=True)\n", + " )\n", + " (dropout): Dropout(p=0.0, inplace=False)\n", + " (ln_2): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " (mlp): MLPBlock(\n", + " (0): Linear(in_features=768, out_features=3072, bias=True)\n", + " (1): GELU(approximate='none')\n", + " (2): Dropout(p=0.0, inplace=False)\n", + " (3): Linear(in_features=3072, out_features=768, bias=True)\n", + " (4): Dropout(p=0.0, inplace=False)\n", + " )\n", + " )\n", + " )\n", + " (ln): LayerNorm((768,), eps=1e-06, elementwise_affine=True)\n", + " )\n", + " (heads): Linear(in_features=768, out_features=5, bias=True)\n", + ")" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model1 = torch.load('test_model.pth')\n", + "model1.eval()" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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87/uR7PQ7v/M7XLhwgWc+85kHjmOM4frrrx/n6ee7Hh/72Mcuet2f5/hi1+V/+A//AWMML3jBCw48/g//4T8kxshb3vKWA49/7dd+LQ972MPGv+9xj3vwrd/6rbz1rW89kH6KMV4WCXCxWFBV1UWPZ/LmYrG4y/ceO3aMpz/96fzqr/4qr3zlK/nYxz7GH/zBH/Ad3/EdIxK1+v7jx4/z0Ic+lP/r//q/eNOb3sRLX/pS/uAP/oDv+q7vGl+T4fWzZ8/yS7/0S7zwhS/k6U9/Ov/+3/977n//+3PTTTd93u90OP5s4xBy/wsc//yf/3Ouu+46rLVcccUV3O9+90Prgz6VtZa73/3uBx778Ic/zPb2NidOnLjk595xxx0AfPKTnwTgvve974Hnjx8/ztbW1p/p3B/1qEfx8z//85w5c4ZbbrkFY8xouG644QZ+8Rd/ka7rLsqfA7z//e/nH//jf8w73vGOA4YLGA3Uve51L37wB3+QV73qVbzuda/j0Y9+NE95ylP4zu/8zgPG5VLj9OnTXLhwgde85jW85jWvueRr8jW6nPGsZz2Ln/u5n+NP/uRP+LVf+zWe8YxnXASd53Hu3Dle9rKX8frXv/6iY+TvtjrucY97HPg735fz58+P0OnNN9/MS17yEt71rndd5Nxsb2+zsbEx3uucAsnjyJEjF93rD3/4w/z3//7fx3z0ncedz/vO55iv/53h2/x45nF8+MMfBpY56DuPO0PDuVRqdWxtbV3EC/nzHl/suvzkJz/JVVddxdra2oHHv+IrvmJ8fnXceV0CXHfddcznc06fPs3Jkye/oPNummaEzldHTrlcCk5fHf/yX/5LFosFL3zhC3nhC18IiNN27bXX8hu/8RvMZjMAPvaxj/G4xz2O/+f/+X/4tm/7NkBKVjNX4y1veQvf9E3fNB6vKAqe9rSnjcfRWvMd3/EdvOQlL+HWW2+9aH4dji/dODTof4Hj4Q9/OF/91V/9OV9TVdVFm0kIgRMnTvC6173uku+5q436SzmyQb/55pu55ZZbeNCDHjQu+BtuuIGu63j3u9/NH/7hH2KtHY39hQsXeOxjH8v6+jo/9mM/xrXXXktd17znPe/hh3/4hw+Qsl75ylfynOc8hze/+c287W1v4wUveAE//uM/zn/+z//5os10deTP+M7v/E6e/exnX/I1X0je9frrr+faa6/lB37gB/j4xz/Os571rLt87dOf/nRuueUWfuiHfoiHPOQhzGYzQgh84zd+44Hvlocx5pKfExOJ6qMf/ShPeMIT+Gt/7a/xqle9iquvvpqyLPkP/+E/8NM//dOX/MzPN3LZ0Yte9KJLPn/ddddd1jl+vnPP5/ba1772ksZpNbr/XJ/3Fz2+2HX55R5XXnnlJUvBPvvZzwJw1VVXfc73b2xs8OY3v5lbb72VT3ziE1xzzTVcc8013HDDDRw/fpzNzU1AODBt2/It3/ItB96/ypn5pm/6Jo4cOUJd12xubl50b3Mwcv78+UOD/uc4Dg36X4Jx7bXX8va3v51HPvKRn9PrvuaaawCJlO5973uPj58+ffrPHPWsEuPe9a53Hagxv+qqq7jmmmu4+eabufnmm3noQx86kvl+7/d+j7Nnz/Ibv/EbPOYxjxnfkxnEdx4PetCDeNCDHsQ//sf/mFtuuYVHPvKR/It/8S9GuO5SkfLx48dZW1vDe3+XwjBf6HjmM5/JTTfdxFd8xVfwkIc85JKvOX/+PL/7u7/Ly172Mn70R390fDxHql/M+K3f+i26ruM3f/M3D2x8d4ar873+yEc+wr3uda/x8bNnz150r6+99lr29va+ZNfmrkYmEZ44ceJLdqy7Qkb+VxjXXHMNb3/729nd3T0Qpec0Ur5HeVxqXnzoQx9iMpl8UU75Qx7yEN75zneys7NzAP34L//lv4zPX864xz3uMc61Cxcu8Md//MdjJA5COI0xXlSVMgwDIIRBkEj8IQ95CO9+97vp+56yLMfXfuYznwH+YoKP/53H/1ou5+G45Hj605+O956Xv/zlFz3nnOPChQuA5AKLouDnf/7nD5TN3JnFnMfllq2BGO173ete/O7v/i5/9Ed/NObP87jhhht405vexAc/+MEDcHv21FfPp+97fvEXf/HA+3d2dsaNIY8HPehBaK0PwIrT6XT8vqvH+LZv+zb+3b/7d7zvfe+76NxPnz59Wd9xdfztv/23eclLXsIrX/nKu3zNpb4b3PX1vpxxqc/c3t6+SI3vCU94Atbai8rZfuEXfuGiz3z605/Ou971Lt761rde9NyFCxcuuu5f7LjxxhtZX1/nn/7Tfzpu9qvji7kP2TG88z3/X2E86UlPwnt/0TX/6Z/+aZRSfNM3fdOBx9/1rncd4FXcdtttvPnNb+aJT3zigYj2csvWnva0p+G9P5Bm6rqOX/7lX+b6668/kCK59dZbR0fjc40Xv/jFOOf4B//gH4yPXXfddcQY+Tf/5t8ceG3mmTz0oQ8dH/uO7/gOvPf86q/+6vhY27a87nWv4/73v//nRQ0Ox59tHEbofwnGYx/7WJ7//Ofz4z/+4/y3//bfeOITn0hRFHz4wx/mjW98Iz/7sz/L0572tLGO98d//Mf5lm/5Fp70pCfx3ve+l7e85S0cO3bsos+93LK1PB71qEfx2te+FuAiFbgbbrhhXOCrBv2GG25ga2uLZz/72bzgBS9AKcVrX/vai4zgO97xDr7v+76Pb//2b+e6667DOcdrX/va0Vjn8bCHPYy3v/3tvOpVrxqdjOuvv55/9s/+Ge985zu5/vrr+e7v/m7uf//7c+7cOd7znvfw9re//ZL10p9rXHPNNZ+33nl9fZ3HPOYx/ORP/iTDMHC3u92Nt73tbXeJPlzOeOITn0hZljz5yU/m+c9/Pnt7e/yrf/WvOHHixAilgtQE//2///d55StfyVOe8hS+8Ru/kT/5kz8Z7/VqZPtDP/RD/OZv/ibf8i3fwnOe8xwe9rCHsb+/z//4H/+Df/tv/y2f+MQnLjk/vtCxvr7Oq1/9av6P/+P/4Ku+6qt4xjOewfHjx7n11lv59//+3/PIRz7ykg7H5xpN03D/+9+fN7zhDVx33XUcOXKEBz7wgQfKvL5c48lPfjKPe9zj+JEf+RE+8YlP8JVf+ZW87W1v481vfjM/8AM/MCIWeTzwgQ/kxhtvPFC2BlJjvzout2zt+uuv59u//dt58YtfzB133MF97nMffvVXf5VPfOIT/N//9/994LV/62/9LX7/93//wLr7Z//sn/G+972P66+/Hmstb3rTm3jb297GTTfdxNd8zdeMr3vOc57DK17xCp7//Ofz3ve+lwc84AFjyeUDHvAAnvrUp46vff7zn88v/dIv8b3f+7186EMf4h73uAevfe1r+eQnP8lv/dZvfUHX93B8EePLQa3/323clSLVncezn/3sOJ1O7/L517zmNfFhD3tYbJomrq2txQc96EHxRS96UfzMZz4zvsZ7H1/2spfFK6+8MjZNE7/u674uvu9977ukUtzllq3l8S//5b+MQLzb3e520XPvec97xnKWU6dOHXju5ptvjo94xCNi0zTxqquuii960YviW9/61gjEd77znTHGGD/2sY/F5z73ufHaa6+NdV3HI0eOxMc97nHx7W9/+4HP+sAHPhAf85jHxKZpLirPOnXqVPze7/3eePXVV8eiKOLJkyfjE57whPia17zm8363XLb2ucal7uOnPvWp+NSnPjVubm7GjY2N+O3f/u3xM5/5zEWlVrls7fTp05f8zI9//OPjY7/5m78ZH/zgB8e6ruM973nP+BM/8ROjKtfq65xz8Z/8k38ST548GZumiY9//OPjn/7pn8ajR4/Gv/t3/+6B4+zu7sYXv/jF8T73uU8syzIeO3Ys3nDDDfEVr3hF7Ps+xrgsW1tVHosxxne+852XLCm8q3n9zne+M954441xY2Mj1nUdr7322vic5zznQMnWXc31fJ1Wxy233BIf9rCHxbIsL6uE7c+qFHfn8bnW5e7ubvwH/+AfxKuuuioWRRHve9/7xp/6qZ86UDYa41Ip7v/9f//feN/73jdWVRUf+tCHjvP/zq+9nLK1GEUZ7oUvfGE8efJkrKoqfs3XfE38j//xP170usc+9rEXXdff/u3fjg9/+MPj2tpanEwm8RGPeET8N//m31zyOJ/61Kfic5/73Hive90rlmUZr7zyyvjd3/3dF83nGGUdPvvZz45HjhyJVVXF66+//pLndDi+9EPFeBeSRofjcByOv3TjwoULbG1tcdNNN/EjP/IjX+7T+bKMr/u6r+Oe97wnv/Irv/LlPpXDcTj+QsdhDv1wHI6/pONSdcY5f/91X/d1f7EnczgOx+H4so/DHPrhOBx/Sccb3vAGfuVXfoUnPelJzGYz/vAP/5Bf//Vf54lPfOKfS6e7w3E4Dsf/2uPQoB+Ow/GXdDz4wQ/GWstP/uRPsrOzMxLlDhW5Dsfh+N9zHObQD8fhOByH43Acjr8C4zCHfjgOx+E4HIfjcPwVGIcG/XAcjsNxOA7H4fgrMC47h/4Df+tZOOfY2dlBKSisQWuFVumHyLlzp9nb3aGyBdYYptMJ1lqUUhhjmE6nlGXJ2toaxlqKskChiVERYsQTAQUolDJ45/nUJz/F0A9UZU0Ika7rGIaBruswxmCtxVqL1poLO9vsz+ecOXOGtm2xhaWsKu52t7vRNA1ra2s455jP5+zN99je2R6FFowxKKWY7+3hnWdtNmEymfDX7nvd2NEohIBzjrquWV9fZ2dnh+3tbTY3N5lOp9x6661sb28zn88JIVAUBVVVccUVV+CcOyDJWRQFRVFQliVFUdB1Hd576klDiIFPfOITLBYLuq6jKAo2NjbG73v27Fk++9nPcu2113LNNddw++23s7e3x73vfW/W1tYoigKlFM45FosFt912G/P5nAsXLtD3PV3XUdc1dV1jrMFYy93vcQ9m62sUVTneq77vRzGTqii5cOECn/nMZ5hOp8xmMzY3N1lLeu6QmkHEyJnTZ4ghjFrv3nustWMXqBgji8WCtm3xMeCTBniM8aKfEMIlH4elLOgwDMQYx3mQVbe892itx2tcliXBR0KAyXSdup6glUUpg9YapRRKyQyUEwqE6AghyE90hOBo5wv6rgUiSimuvPIkk6ZhMmkwRnxkrRVlVRBDIDiPDwEfA5PpGk0zRRmD0oq+7/Hey7kqxaSuMMbIfNQKraEsC6qqlM/yAe8dPnhc3xG8p+97Qgh4v1RnUwpMWp9KQXSO4DzEIJ9zJ014Y+QaFEWBMYayLMfzcM6N1zgmCdAQAsMwEEIY527btvh0Pi4E+hg4c/4Cp86ew9Y1RVWxtXGEpp7Q9z3D4LhwYZdhGGjbluADwUFZlsxmM7TSaDRVVVFVFcbInfnMZz5Du1hw5OgRyjTX5bwGqrpm68hRbFFRlA3WWoy1rM1mVFXFRz7yQc6fP8cwDLKf7V6gH3r25/tsbKzzFV/x17jj9Bk+9KEPY4sSW5bcfvspzp87z7ErrmQ6W6MoSkKE02fO0bYd29u7KKWoq4KmMKw3lq2NdY5ubbKxscF0OsU5R4yREydOsLa2xgMe8ADquh73stOnTzOZTDh58uR43ff395nP56yvr9M0DWfPnmV7e5u3ve1tnDp1ijNnzuC9H/cupRTW2nHfKcuSpmmoqoojR47QNA1HjhyhLEvKsiTGyDAMWGtZW1tLc8hz5swZ7rjjjnGdXXXVVcxmM3Z3d+n7nvl8TlGW3Os+92UynbF55Di98+wtFpw+fZrbb7+djY2NA3K0WQb27NmzgOjQa63x3tN1HXt7e+M6yHtj0zTj2gWRoN3Z2eUDH/wg80XLftsTI4TI+N6u6+i6Ls2vYfwOMn/M+HnT6XRlzcu82tjYYGNjY1zveT/Jqof1pMEWBfWkwViLKQtCDPjgKOuSuqmZra8xmUwY+hbnBkI/QIhMmxqjNUasm3xe3bCxvsXgHa0bKCdTismEncWcRd+x13f4GNk6dpSiLPmG6z5/P4rLNuhlWWCMZjqZoLWiqkoxvSpCjKgQaOoaN/Q0ZUVhLWtrM4wxhBDQWlEUFmO0bCbOEYnECDEofAyEGFFKg1JobfFONo3BOZQaIEIkoo2mKGXjKYpivDEHN8LljfLeM7iBru9xzsnvweFDSBueQmmN1hprZYMoihJrLV3fy4ZnLcRIBHyQiRNiwBYFwzCwt7eHMYZmMsE5h3MOpTUqbZJKa8qqlE0rBIw1FGVJURYUtsCHML4mxkiRPndwA0VZsLW1hXOO/f19tNbM1mZMJhPKqqSZNMQYRkMWYkBFhdKKSKTrWpxzGGvQXo8LbDaboYycY1XXVFVFUp+g7zqGwRFDANS4MHKDihACwXv53GQMsvENIcicUDJ1Y7q2CjkfYLxfwcvriFGsUBSnLsrNlr9jJIYo8yUE+YQY5frmY7BiiEkPkN3D5d+k98YghikqjVIsz1cv3yMGLDkUIRz4kDy3tFIyL2PEe0cICh88WitCdMQQCd7L8zGiTUsIoO2qQQ+jQSd4tNFYY1FaHAM3FHgv9yKGiPODXPu+Gw1oCF5eMzo72aCny+oD0XliDJA2rJE+o8BoI/MvGfR+GGQDspah72UdpPmf3+udODv9IOeTDXvf97gY6YMfDVnwYVwXLr0PIlorjNbSuMWAKmQurq+vY7TBaktVlWk9GpSSFrxKqdGpKMsSrRVgIDmLVVTYol6uP6WT01dQllXa7NM9TXPWOc+iXeDcMO4jIE1lqqqmsAXamLRnRbQWB7ssS5SSPdEa8QizypIxZjSuSinquh6NW0SO69NPNiRKa3SMB6ZsiAevn09zapyLK8qAatVQpcezsXbOodN6BMSZTs7YqrqgTnuXXtlDZV/Wo9NcWIsxRs4/fTYsnUPSGsr3Kj+3ehyVPnO5NJcO+6pDn19rraGuK0IEF5Wse6XlnhBxgxsdUO/duC9UVS33oq6w1jKdTNP1YbQrs+l07AnhfTboEhhFoG4atDHYokBbjS0rQvS4oEfjr+LyvGV+OmLwaCJaKUxkdJyDD3I9MZgYlg5Gvjbp5HwIqMuUZ75sg37ixHFZ+EoinvX1dbwfGPqOoesYupbppGJ/d5f1tRl1XXPkiHTd2d7eHhexeFFiYLquxznP4BwhRgKy4LQ2WFMSQuT89nnc4LBWIoamaSiqgo3NDWwh3ujonbmeQKCqS0L0aVLC7nyfedeys7uLSxuP8w7nB1lsyaO1xlIkw72xNsMawx1n7sBay5GtIxLNGsP+Ys65C+dZX1vnyLEj3HrrrZw9c4b7XncdV979Km679Tb25/sMfU9RFWwe3ZLNpDC0bcfu3i7TtRlbm1toIwukSpvh1pEtUIrz2+ewpcWfDxw7doxHP/bR3HrrrbzjHe9kY2OdB13zQI4ek7ao09mUvu/IGZR+6FBKMWmmxBj5zO2fwRrLkaPHUFqxaBecOHmCa6+9D/0w4IPnxMmT1HXNmTNn6LqO7fOi8d33w7jpymc24rX2Pfv7+3jv2VxfxxrL0KYNvZPjGyULv8xOE+T9k8JYTKWha1HREZNRDUoWFwFCcr/FkAVCFIM2OhdWnBYVQYXsWEa0ls1UR1ARCBGVXfkgjoIbemIArQZQGqMT4qTFwBu1YtAJybCLATBaEa0YDzEkEeccu7vy/ffnu2nzku+sUShtUMYQwllCFIOO0gyDROjRe5TSNHWNMVoifSWOaVkU1FU5eizBDQTvxui+61rCivEkeiA5tSSnO8i1ke8T8S45KshGq5VOBt2ijaGwpWzcVrO/t8/u7l6aq0qMv9LoFDHHINdqcIIUDL3DBc8QPJ0Tw9O1LaFtMcrQ9704ziiqoqC0lqZusLZgNltjfX2Du9/t7lRlSV1WlGV1wKCvr69z+vRpPvrRjzD0PcePH09IXUXbdtx6661sbh3lpK2YzdY4cuQYQ9/h3MDGxgZVVfLxj++nuQ8+iAZ6JHLrbbcRQpSo2gdcCKytrTOZzKinM6wt2Ntf4Jwfo9+iqrHGsDad4IeWYb5NIOKCZzqbcfLkSaZrM8qqotCCiKE1g/d0fUfXtszbBdoYQT3SXhhiEKQtBNTg2N3d5fz58+zs7bK3EBQQpdDWyr3MRteK0SnLEm00Qcn3CyGMzzVlhdJ6dCrOnjlD3TSsb26AUlRVRTOdUFW1OEltKwGBMYQYBaXc2MDYgrZtWXT92A99fX39QJ/2GCN9Cowmkwla63ENl2U5GvtVYw7iRGTjr5QaHaGrrryKtuvZ3ttDW0szmY5ohDWCyIgvswzymkbQmqZpUqRejevWO08/9KOzkh0mcTRUckrAlmKTtnd3QGnKpiYEz+AHQgyEtJZcPySUoGP3wjZD1xOGXoIC56nKkuPHjqOPGuq6piBSBA+2ILJ0whSyf7WLBeoyO/1dtkGPMaBQmEJjraEoLFpFghvwWmA9YzS2MBJ1ljZF5Am+0xrnHUbrFE2q0XPzPhIVRAXGFGilMcYSAmwd2ZQNwsmGJ5NKg5ZIOQwSGXnnccHJRZVdNHnKstE4r8fjOS/eTobrs3eFVmhjgIgpLEZrBgdKK8q6pLAWWxSEEKjrirW1NdbW19jc2pRzCV4MuRcjOW8XBCJdLwYOrVLUJZH4ZDYZJ/HgBgJyHUjvaftWPit6tJXv7ILDFpbZxoxmUlNUJVV0aKvkOkYolNzWoGJCPgK9H9jd32Xoe5RREtlPGyZqClpRJ6i3LGSBGW0IOqAiBBeYD3OGoU8pFo1WGkLEO493gWDC6B07J/fZey9zZrWVYoyQYfQQ0YjhjzESlQKVUJs0sWOKlyMKHRUh+9wxiiEnGfSIoBIqGfF8rFWjngy7Cgj8HBxRBZTSKBPk+EaPkXqe9+IehIQeBIxWKGslAjaa6VQ2dmLEB4c24lxoo1CklJQxaGvxPhJixBiL0nqMroOTCL1pGjGcaX0opSgLS11mgx7xbkhQu8U7T1HoES2R+STXHSWYiFKyHHRU4hTFiPc5lRHShinRmC1kLYhBV2irR1jTZINuLFqZ0aCHEFM0Ig5Gbwdc8BjvKCJUMeKCIBSTSUNd1RhjAYXTThwCFNYW1FVFU1c0TU1d1jR1LbC5kf1EKcX6+jp93wuSgKzxCCl6ktSOTtd2SPOx6zuGvk9rr6KqSgZX0vWdIH4J6ev7IU3RiPOObnBobbHJmDjvmc8XDMOANgIFh5Vo2miDKiU4ELBJnLlsYLNDOjiHiVqClwQBF2VB2/XYELAxEIKgULIOYHCOPiGWzrmUqlIMzokz7L3M4U482hACZQjYIlCVFQZAaYloEZTBBT+iBBHQWpDDppnQNBOqumboOrwP4oigKBMsrpSkSvthoB/60WiXqdXsnVNnQHIyzPi31locd5bRev7J6R3vJRmbYXSUwljDdDbFWMtkOqWsKibJaOc2vRFGBLZMiK4xydHVaY1qwCoKrMykGNNrlmm48be1eB8obAHJ0Q7RoLzCe4cLTo4HgjoZI/uglutEjMu55RwupT8D4EioqlUYpSispYgRldf1ZdrpyzboXdsm42zRGqxRBBeJwRG8wBtKRazVFIWmLAxGK4xWNHWJ9wbvC2IM1HXanJRKG4lsdjp5/gpFVJoQ4Yorr6Drek7fcSZNZI9SEKJEj22C0XNkODiHJxA18kNk0S5GKFkpiTCKshjhL8nRKGIEbRO0k1IMRXTUVcWRo1uSmyqr8b05tzdbm7K/v89HPvIRPnvqswzDQN/3nD5zB2VZcvzEsQQLaqKKGKuZTiccO36Utm0l7+M6YnQMweG84/T5s+zsbDMMjv1ujXZo6X2Pi55yUnHsiuM09YSqrlAWSl/inCdGmE4bQoicPn2GPgyoQjOfLzhz/hx1XTGdTqimNWub62xubjKZTLhwfpuu7ZhOppRFSfTCV+jbnrZrOX/+PFYbyqKg0GnRBHDdwNAPaBRtK8hL36bNtu2INqCrKm1MkehjypWmvDGSXhkXvlJEnYxuMtAh54GVwidIKyYDpYP8Jv8btYTQPRKZ6ygGOgBerFPoegIuzTlFTIacxPmIJjkHWtwJMTkpH2cN2ljquqIsC+525RVMJhOsNYTo2d/fG+da3hCMtZjCCkAQl0hUzn8HN6CyQdc5+pVzKK2lKmXtCLQ+jLlzidAXeB9wblhJDxwchbUUxi7hcp83WpeyHTltlc7XFLI5aei6nrbtRoNuTZFSVPLZw+BTDn2Oc5627QQJc4M4SEai0SF4Js0Ea8sRtu4WfTJy4ihMmgmzyYRp09DUDdPpbDQI2fE+ceIEZVXywQ9+gK7vRoNqrGFiJ9TNBOcj+/v71PUuVVWzt7dL17UcPbrFtJmytrGBspp26IgK1tbXhQ/Q9sl9U8wXLfP5nLX1TSbNhG4YGAbH6dN30LYds9k62ki0HUNgKAsqq1nf2ELrNGvEg8fYEltUzPf3BVbfn1MUBWuzGUXd0MzW6NqWC9vbYvwrgYYLY1IaUrPoB/bmCxZtT9sNDAn96BP8HkNAdT1qvhDDZsTo1XUjKYOywhaSPycFN23Xr6SbDEVZYWxBM5lSNw1VVbKzvUPXdVR1LU6flRx3iBE/DOzv77NoO/b295lMJqzNZpJ2STDxaoS+kXqlLxaLMSWQDbY2ggCUZUlRlrKPdoJguBWuyOAHtNEc2zxCURYJSajG6D/zPnJKxnuPDx0+wOAWI9cgj7xOczBSFIXMtWT8q6qUVHEE54Ubo7SmqWoCgTIU9ENP2y3EoUNRFSWFMbimwyrNIqNwOmK0Yeg65vM558+dI2pFUFA2E8paeGfTskAPA713nLlwgd5d3L3wz2TQd3YuSMQ6tCzKEtcLpLDY38M7h3cDXbvADR3zucG7ATck4poR72cYnEAUwzBukVobjLboBOco2ZLxShEitJ3k7/bbueRxYhw3yIAnEFBaUgE2WjAKYzXa6/GmOZeiEPLmWlCUJWVVSqSgNd55QoJrjUai2LJga3MtEe7OUxQCCVaxRBvF4Hv2F/v0XYcLjtn6DGUUt3/2s3RDSzd0+Og5d/4sZVWOubu2XTDdm3Jh5wIukXNCDGij2N3foW1b9uZ7LLoWow390HP7Hac4e/4c/dDRdi37i326vsfsm0TY8nStTPhFJ5H/9s42+/M9fAyCMlSSs7elRZsMt4kH6IYBN4inb5SmKktUjJRFwdD1+MGBiRilsMaMZEilFNF7eT4ECPIaFWHoBwhgjUFZm+A6iCHgktMjhk2PkXSG5XNkG5Ue89qBkCJPicnE+cuvX8mVx4P5d7KRSz8xRPkO2qwY3QRP4yGqjFoTQ86G5jgw4l3yl6MnhJK+7ygLizHlcnNMiJUYZSG3KSAGyc8pFEGHZJyFj6AUOD+gg8aEJTtPxYBWcYTiFUZSE1FyfDGWhOCFNLYSda+yChQ57ZGvdUYcjDg95NyvrDu14jSlLIUYzggEL+/xMeUtxaD3gzijwyAR+jAMhEHIgGiN0gqjoLCa6CEooCyIEawpMCblqgsr89I7+qEnA5DZKAhqUVLVFWVbMiQ+jtaKqq7Z2NjE+UDXS15ysViMG7tzHp24LpHIqdOnExRtic7jhyGhQyliTDnToihxCZ63RUERArYs0MaiU6rOWAsq0rsBayQSdl5Sit77tMYNZE5JMvpaKYqyxKUIO5B4CiDOgsq5YjmfuqmZTCe4qhodYQWjoSrKgrIQoyj5ezF6RVXJMdPrNNCkOR5iFMcrRfsgEbHzjjYTzNIxnHf0zvHZU6dAaVyAfnAj+hNjHA1wjm4z8TUTKduuHclhg5PPNskYGyv7E0PKR6fVZ62VSDchY0VpMdaglKBSzvWJy2OS85vXwmouXuZ6SDyX7AAIIqxQKvE6TOLWEAGxDf3g8SEmovcybZAdzkwWBQhBbF3f9fRdj+uFs1EZQX6NNlhjqMpS7rFR6MTfErRF7JxF5taXPEI/c/rUmMcorOVcXdL3PYv5PlZrrNEE7+RCukE8Gi/EmuPHj2OMGVmwbduO6UwhlhTolJ/OWLkHfIy0fU/XD5zfOQcxUtgCWxRUFjyeiMDRShtMITCvLQuMd5SVwGRBCRtSbp7AZ1VVUdXNuFW73jMMjqoSONEYTdVUXHvdvWnblvf88R9ji4Lj4ThN0xDwdAkyKYqCwlqOnjjCkbjFZ099mnm7z6Kfo3rFp2//lHiQie3atS2m0BS1HRdiURRoozl75jQ7Ozuc3zlP3/VsrG3Q9i0f/cRHOXf2HPPFnN39Xc4lbkFwAVMIgWd3exfvPM2sQaGY783Zn+/jokNZxbSciEGvCpRRRAL90AGRvm0ZugGjDEYppnVDoQ2L/Tm9aWWj87KRl7bAZOhda+LgcT5FCCFiktHoFi2h8BTGSCRelGMuu287FouFeNVFMZLQMlxulCIikWoIYtijXkJ3q1CehmSEUjSd8ukkYxx9AC2/s2EvyoqikOk/OgNAIEU7MeXwWW4KktmMY2Q8DDVVVTLf38PolNNXsinkaFdGTInmgBt6MXxuGBm0IxlKCRSolMKsnJGzFu9KJk1NUVdopRG0NWCCOAsxsdzvnIfM3845MWZRCVARlVqmOfIpJphWoFSX+AkSXQtLHwgqOT3I1YiRoRfEoO1SJNV2eO8Y/EDbt7RdSz2ZCBROpDRaziGCrUqU0kyaWariEAKc9y7xQsAYK1FNMsqZaDaZTOm6jv12gerFgTxSFBw7cRznIm070KXcrk97UzcMoDVra+tynPBRBh+EjMrAMM/3QaOMwZYlZVVR1jUupYLqRsh2ZV1jjcUWNdZoyrIg+J5511Jai1IF/TBIZO8dzksOW6MSKVKugzGauqnxwcvmDvgYsIAyRnKqCnEErGVtfV1g+Jgrb4ZEtCqp65pZispz6kGcSzsS3Uj5YK01zaRJlQo92mjarpUgyxgW8znODTgn6cS275ZrIwQ+e8cd2KJkY+uoOCExjuS+fuhZdC2FLcb0mxB0Jf24t7c/pkBjFI88R+ejQSc7NhGUoihtyqlXKKOxda5w8AgYEEa4PufelwZ9yeECRkMuVR2KojDj51irJI0Vlu8FmC9aYlTU9QwQGH2ZwvIjUizrWchwi/25IMdtiwKaaYnVQiisipJpM0FZA9bgUfioGILDx4ApxC7WiaF/OeOyDfpVV16RIg0xdmUhcGFdWeqykIgu5evKFMG17RyF4siRLYzRI6O373spNYhxzPWFtBH1vZPF7AacDywSjI4S9m/VFFhbUNVlKrnS2KLAWCs53MFhC43qJcrOOdyIMCxRepx4zvsRrusT3NJMKqq6YjJraCYV/dARouPIsSPkTT1ETyRQ1QV1U8lN9CG9NnDV3a5kY3Odqqlo2wX7e3u0fYuPHmsNVV1iC5M+K0HAiVCxs7vNzu4uVS3nceLECWazGRubGywWC5x3aKOZTCd0i46OjmbSSPRtizHa7/ues+fPClRWVRLRRkUzaVjbWMMHz6nTpyhtiTWWUpVoFBd2dpbM5BRxF8ayPp0xOCeMZ92i80ZrDHayzHlJDsqM7w/eExPELijAwJA8VtcP9LojOj+aHrFFcfwNOSe+zJmTXh2iR0XwyTvUYZkvjhGCFw6AEtac5M2ChFn9Ys7QtjkwXcay6hK/VRy99Zh5I97RLjxu6Dh/7gxdN2dvfwcQUmLOR0ukEBK8KCWaMTIiE4MbJIeeXtPVwobWAg9IJYW1lEVBO2lomjox/aVcJuZrHCRKgWVqSWUOglIpz02KWuTaxJhzp5E0/YjZdox0f0VI0eWBUsIQhbMSAkMnnJGu7wnei4GPwrp3bsC7AYJDEyiMorQSkRCT06YN00kteUslkW4uuZP0hKEqK7Qxo2FwwY+55dVNuuuHRM4yxCgRcj8M1HVJUUhqp+t7tIZukBy7Dx5bTASOrmtBBPf3MUpRGYvSwuTOZLWyqkBrQgwM3jH4BQpF20YKo2mqgqqpmU4nFHVN1JrOefTQUVeS59VFAVrTDgNDCChrcUDZiIH1MdB7T+g6huBRWoIcZQu2jh2jmQlBDwTVMdpQFBXGaoqUvpS9Woij+bhNU4uxjMJlWnQtWmsma2uCoGid0i+aQmu0t9g0ZyTdmgIuH9jb30NrS9k0gnZZiSZHVMN7SVFaK6QvECJejOLYaE2RuAk2ReClLcb9efCewWfulKaphV+CEl6TrWxi/w/44BjaPjljSshxqVJBpU1Bocbqlm7egYIipQ8WrZTRLhYL2UsL2UtjkKqqGGFvb0GIUBUTQlQMzqOtoawKfPD4KAiy8BPEoPddR991BOcxShGcYwiRPS8Q4B2nTqELiylLgtIEpWmDYyDQrK1J1I7cl8sZX4BBPzn+O+cWh6Fn0pRM6pppU1NYMy5EYmR3Z4cYI0cT233wsgG4QTYqP0IVYoD6VGrgnGfoW3o3SD4uBKIS77ZuSik9qUqsD9jCSL6pLBhSPtdYgWklD6mFUTwadnEeXAiymSaDMCTI2Vj5vOlswqSp6IYOYuDo0S0G51I+3hOiZ1JPmEyn7O3u0S4WdH2PD5673f0q2aANnDt/nlN33J54AYHpdMra2gxbGtCR4LxA0EE2lu2dnaVBrypOXnmS6XTK5tYmF7YvjPmj2dosQVuOSaqZb5oG7zwXdi7Q9i1nz53FeTfWgwYfaKYNW0e2cMFxx+k7UFGh0dzt+FU0VcP5c+fpUgmL1jqx/w3rszXJle3t00WIPoz1onVVYc2SjW7Sog3p72x0XD8w9L2kKPoe3w/0EYIR+G+V0Xrn32plLo7liCnc1IHxt6zdBEP6RIJTAaWEYapSmY6wfsXzzgZ9JC4qNW4MpNIxpZcv9G7AO8fgxAifO1eyv19RlCWRyDB0ApdZMegu5alByiELW2ITi9zd2aA3pcDjMObMhYRa0rYNk6ZJUYesIWIYkYjRAUrXR2stBl1rotDixKDD6AT4DL3HZVIBhIsQ88VJKQ0hfkZcipT7oZeNt5N53w+DIAWpPC7EkAh8g5TjEbFaUVpB4sTJEcLbdFKjlIEoudx8zTOMXNUV2toEYQ9o58ikSZdyyFpruqFnZ3ePoqgoi1qQAjewVk6ZTqfsLxa4QQx6P/QMbsCHIPelLKknDds7O+zN56KVYSzK6LGsNgJlXaOtZdF2Y7oqxkDwPbNpw2y2RT2ZMNvcSAbd0HlH7HqqyQxdlOiUaljMW7TxqaY5UjYT+qEXXoRzdM5jE7/CxYguCraOH8P7wKSZjmiK1oayqFYcKSGr5jzwdLpGWVZMJrVUusw7+qFn3ndUVc2RtbWVnJWkZpQ3mODTbFDMZhNsYVGIY2UulIBCFzL3q6aR4CQEClfiY6SuG+EoKflk14nTZ1LJm80lh4lEZrWhG3pcL+kb55wQlK2lTjyV0aCX4hC7IGnL1dK7KnEQMncpl/BGouyzu9sAo7ZHWZYsFgv29/dHLYaMxGWdg93dOSFAYWt8gLYdqOqK9Y01bGEllamFZ0KQNdB3PUPXo1LFgneegKd1HucCRhfYssDWFRhL1IY2elwMYCxlLekUo7/EEXqXhDRQkvMxWuOGnqHv6DVYDcMgxtymcp2+F5LUpz61WLIFtUTUQvxZkqGcGxiGnjZ5SvP9fVwIzNZmoDW9c2ilsYUGPG27z+AkT9cPHbYoxah2Pds7F9jd2xMmqjZEzHjjUjJQyqFijlhigiQdRNnA67pmMmmYTKsx0tzZ2eZ/vP9/cNVVd+PBD3zgSDDru5a+U/iQa2zFG63rKrHH9ci03NzY4J73vIbNrU22jhyRSNU59ub7LBYLvHepDClitWFtbY3pdEpd1VSFlO7VdcX62hpVUdLN1qgbyTtOm+mSOJVgXVBsbW3inWd3d5fNzU2uvfe1zJNoxWwyoylrSlVCEC+cUI4GoSpLSmspU75H0D8J43K9qR8GOu/l/EOQnHmKnvCBzrZ0HSM82/UdrhejGJxj0DrZyjRHYKyl1SvGVQy7GiHIGFY58AnWRkOKJkl5yBiXUHsMXnLfrsd7h9CfVoY6aNClTl82xRS6EoNDEbAaQUsmDdPphPWNdYxNYkeFZTqdpo0sjpC2VgK1FilCz4hKDLJxVFU5biBiJLxoFhR25AUotTTgajTBy7p/lWBW2dwSwTSRDEdqQYI6R4Z2SPnA/Hn5l0qMXW1wQaB31/d45+kSq30YyUo+5f9SiiIGhr6l6xaS7y5LtjbWmTSTlBeWdIpCyT2JkeAV2oJRksaqKxEjattWDG5RY72wrau6whSWthNoviwK2q7j1B2n2No6yvqVW1IaNkjON87nAmsrxdaRIxhjWN/alLRN1q8whu2dHaaz9ZGk1UymiRAm984YiZrarhfkw8sc837AWk1TWSaTmrVpM7KlF+2CthfiWDf0mNYQvOfC9g5aq6TZYaX80w30fTeWA5ok4hW1oqhLNswRQIyWSvngEKVyodCC/uUoW6U929oCow1lXaKVpqhqQghMU3nuZDrDGtmbxUlxgkopxXx/n8E5yqYZ66dVyNcuMnhhrzeTiSB4bSfpigQZK6MTQ17y8kEJD8GHwJmzZ2Wdp5RrYSxt19L1PXu7u3Rth03VUov5Am10yrkHIuJU7uwJ72h/by8hveKgWSPk5yxgE4OgM4KutSPUr5TGaEk3tIn8bbTBB58QR0mNdp2QjhUWH6DvPevra1x196uYrc1YK9eW2ihK1ma/6LBai0GPUongBsfe7i7qwg7nzp6XtE5TUU/XqKYzghUi13Sjl2uYUInLGZdt0CXXKvClVoporHjqbsANin4UsVCERCgYhp4hqTAREeEFW9AkxZ2yrMcNRUrPHMPQ0Q+dGLUY2ay2MEVB4ZY6cs75USRGIHqPHUQBrm1b5nMxViTmrLFlOne1slNF2a1WYMQM5yklZQOi0FURvGduNF3Xcuutt9LUNVnkIAvuKBXJ4h4hQWRFUYhQR/IQrTVMJg3Hjh0dDXrfdSNEmaO1YZCNwvuappGfLOJgUolNUzcUtqBp/GiAcu3n7u7uWJ9vjGE6EdW3/f19ppMJV5w4IezKGNna3GA2mdHutgztgDWWYD2QhTMMCjsqcsm5hQM1osE5ArCYC3Ex5+5AyFVjRJfINX0SKVExEvCIfod8B5PY1io5QUbJtRORiyR0kQx6QsPHkXPocbRaYuRjkPB91ajH4AhuYFmOlqbFSnQrG41KJCaVw38yTUcrg0lKbnVds7G+loR+hHW7trGeIk1F5uPk08plUsv0hlyHqqxQigO5Obnnlq7tUo1/cqxJDk1C41bLbJbzXUhQPkS8X3EBkiM7RuUpSg95fYQ4RlWFtZLO8W4Zkacaap8h9gQT58/JDkffL+jaedokNdNJTV2VhHQebojyLfL3DQoVNCAkQCkvk5r7sqqlXMpoiapLEX8acrkeMPQ954eBZjITtnJKx62S0ozWTGdrTCcTrr7nPYjAfDEfc6LNdJb4G1LNsLa+TjOZyJorSqazNYy29P0gAUEQg+68g+iJcRDVuLocFRHbvqNvHW3f4ZLz5pzjwvaFRDTzlGXJdDpNa2TJrbA+Qd1Kyb6Z2OZZQS0rWC4WC3F6mkZKbO0yYBo3/DTvjBUjNZ3NxjlTFDKPu64Tpc2057RdR3QOk8p2+9ij0FRNg3cB13YSqFk7EiLzPirxU8RmVC1Ibb9Wwm6/sLMt3ysR04rCjpU/e3t7tF037n1dL5B62y1EKTH0dH3H9s42i8VcOETB44OX72/kfJVWBCcoWDdIVcUogiU1kxBjYqr3GJ33GSR3b4uRtxKjInhBugYn5cabRzZHvtaYl5cqaHHQowivxRDwrSidzvf2cT4wuCClx03N+pGBWYjoqkCXhaC3Pjmb6vIs+mUb9LPnz6YdTwx6YY0QfNoFVVmO0pQxBEorG0vXyoVXKacnYi9SXy0nKHkoFwJuENJOPww47ylKSwiRO06dkk0n5XasMeMmRZSyuBg8Qwhj1Nm3Hb7v8YWo2RkjMKZWcrzgpawtQxlGWVrVkovhg4+cPn2anR1L01icc5w9fYb5Ys59rr03Riv++I/fzfr6Ohubm6NB8EHykqdPn0qbU8BaxZVXXkHXdcz39zh1+2dQMTCdzVhbX0tOkeezt59id3eX3e0dVIh0ixarLe18jh8ct88/y+lTpyBE5nv7nPrs7SNU69JkzXKOn/rUp9jd3WVS13gf+OTHP56MvubMHad5//943yiRON/Zo6kqfOuILuWitUTSjp6hXwjJJTlQzqVSkhQVgYjEKKBNm2JVWYiy6So8rtcCfeYSQzckIROVtvXMME9/RyBmjFsLHTrnn3N0nox9plCq0TAreW8MqOjSv1PwHiS6JvjxJ4SU8kiRsqRhkopcEosYwWwlOXRbSFVGVUm1xNrGGs71RETiVmmNNkkZMCl85Vpfa8tRntMYg095upgguSrlFENGWpwTfQdrJF0xDIl0dzBVoBRLdCP5HjJyDK+TMZcfFXNEnkDWZIRDWuMHIPi4Uk8cl6mVnFceyYcZIchHVqAIKIKUvBlNaY04VEkEKUSJJovSYMg125ayKijLgrJKxLKuo26cGKQEw584eQWByJ9+6IP0fT8qwimtuf3UHQwu0jQNdSrvtAm61cawP1/QDQ5v5Pr1g6OsKo4fO0LZTBhClLK1RUtZN6xvblIWlVTFKIHgXSILDoNP1SIDMTi87+h6S9sl0asQ0EVJ2UhpUlFYrBVZ4Jgi+Nl0mpCYkjoxtPP6zle0SBoBSmmIMc1ZifpMGbBVNRpnFyND34sxj6QyLC1loRHaRYv3EgQ5JymosiyYTCYsUrleNiJ33HGK/f05s9kUrQ3z/X1ijBRlSdv1nLrjDNaIwMswDGNAkh1VUb4UaL1tu5EX4b1nb28/zRU1yjNnDk3XdaOynZBMJZW3aBcorZhMG2GSD10ipUk1hTYGY6VqIjsw2dJVqQLEGpvg9zCmicbJmxaFzkGFNmnOlQn1KAg+0g2Oza1N7nGPewhKN5uSK2aE0ycp1WEYGNoFYXC0exLcTiYTIXIbKwFrWTLd2GS6to43CoyoNpZlSTVpRpLg5xtfQITep41RvKvg9Vh6lBevbE4eb8XD6bpW4A9rZctOG6hPEJFEoUGgPB9Hwk5EYD5UpN3fFaWkVGZUFkL4MLZAKZOkZfNnJc3pxITO0duoN58m81jCRBYeMGJg8n9RMZ/PGXqFG0xSAdshAke2tpjP59xx+ykWiwWLdsF0MqEua1SCRrrE5releHZryQve3tlmf3+PM2dOs2jntN1irMe+4w7RKZY8ouSoo0/5yNCxs73NfH+ORuGdY55U2lbLJbq2JYTAhfPnRW/ZFhAGti9sS23jdEq7WHDu7FnRBA8eHSND1xE7DwGmdZOukx8jhOz9y94u0qN9l5wyBdFLdOlSrWQmR8pnLEs4YvohldGNEHFy+FI+ZPnvBIkJzS1tbJEUl+Z9bmUFjvBzWP4dQyKiCUQnf6dzSMfIkfASHUk65WP+O/PbhRRZlCWmsPhQUQZhdxdlwWKxEHgvSDI/V130fT/Ke4rqmSxgo/XIochEtjIJyOTN3A/90qA74XmotFmkor2x5G5p0FdgizSi0uQKkkRFveTI6YG8qS7FPdzyuidnIAuCZISF5FhIiZzsCUZLCi5Gg0WPSNwyWcKYK5fNMgmLpI1Rp9xnnuMCkwpis7YmvI6ICL4MwyD5d2OZLxao8+c4oo4ymWQGfSE5W6OFl5N1LYzGhUipNfVkSj946smUbvC4MEencjpblGgtUHnIJLmwnDvjb+c4yEhYlr8Za9GpUifGKHKiWlPWDUulQkkpiDOQjHqMmKIcFRtDjIKMRRHsEfKjsOa9E73/zC0gGV+jtRBIkRTGMAzs7OxIxDifU5Ylk8kkoZzz0Yk7dccd7O/vU52XdNDenugs1HXNou349GduT5UHzQEmea4/z/rsGfomIaA5UMjHyRr0JqU6XKoAGYdSxBCYt3OM0Ti/LmslprRZ6skgaS/pJ2KS3kMWfInJ8S0LKTH1Uc7XD0sEIkssG7siLqMUVdWIZgqSLuj6no3NTTY3N8d+CwcqVka0S8p0XT/Qt8KvadbWEiIh3BBbChepqiqcEj0Oa0z6kfK8yxmXbdCvvsc1stH1HSpGjBKY3A09TV3T1FXSdvYkTQyJ0H3ePLNimECYmebfDwOxG4g4QnRjaKG0CNmvb2ymv1XKoYv2eV1PksBBmWrVB4KPmKQB3/c9VTVJTE/x3A2iVrfYWxCqiFY2bbCGyhZQBqb1RORN6SAIC7IqK9avWRPN9vkeVhvC4JlNpkwnE45sHmE2nSVI0jOtJwQf2F/soyJM6ylDN9AtWgptKW3JFcev4J73vpdAnz5idMGpO06xs7OPd4GTV1zJbDajLitCiJLftgUb6+tMmwlGG7pFy3y+4Nixo0ymU3a2t1nMF1KmFZDzVJKz0em/pqo5snlkJKxNJxPJxc8XBOdo6lrIOu0+qEgzraV0JQxjfrbvW1wYxuYJQzJYZS0R0PrWGlopdnd3ZYGVGhM1RWVTpCrs9JHPMBr0bKPVktilloZiZV2nfyR1NxVAeQnqkZwYBIJapgWkvlelaoJIWRaoskwRRGBwEk03rhEjFnMdcEyfqRJoIFrhXd9TlhVlVVFXjbCIc6MQ70auSFEpJtNZUoozI1mpLCWnKbk9qZzQSgmDGggpdeOsHg16oydjGRIqs/45eO3k3YzZ8JhJcOI8w0Gjm420ZtUlks+ORKGbBIH+YjLcOtt1ks8VM9loqXu/VKxLJClb0jSVOL91Q5vg6hAl8qrrGqVEmTESmS8WDC7Q9gM+RExhiEn5sFuIcM2VV11F3TQcO3ZsnGtFUdBMZ1RlzaSZMJ1OqepKSLBty2YjlQLrmxuJyFXjQ2B3dw+lDfO2px0cISp25wtO3XGa4yeuwBTlWCfcpZSDSflhQQsjJaWkJPVa2tj9yDMxZcGQ6/S7nkUnjmMmcrUJqRmGYYzy2laQsP39/RGByNUkIXh2d5OAUdIbX8wXY/otOxd94uj44JOmAuSGOqu9IbJefpNY9vknO3Srqm/Sp0JRJ47SFVdeNR5XyIUVWYxpZ2ePruuwSeFzmpwrbVSSZJ3ghoH9/T1ETtikMmCDS30vQkLLUIK2DU6IdV3fpXMXOyB67bJWluF21iDRS4czITwZ2RK/VDGbTVlfXxsDRJsMuuhGQNNMQCmGzqUmXy2ztRnHjx8XR9W7UdmuLCsKo6UsVxY0zli0CykNOiFEROvdSyqmmkyFr1JYVGEE6kfRt+3oGn6+cdkGfWvrCN575vM9gd0RqMe7gaoqqMsKNwjhwJocO8hriIyQoGw3CuW91GBGKGPOiy5FLLLkYVFWKV+qUqMFS1GUTJopRSFiLdZ2WNOxW1X0bS9kESVemNIGrdINjoz5k1x6E30g6oBGGmKURUFVCPnLmCh5GGuoiore9mOUJOUYBUaZpAFfYKwRZm8vN3VIpLSmccwX8zGXZbShrmrW19ZQUc5rNpuxs7vLfL8jekfTNExS5J+larWS8h1hShcJVYCqrJk2U3a3dwg+JEdH6oHlfSJkkHOhWd41BpGErKsKvMcnUkyM0jwmxjiW14mASRxh6Cyxq1NZjIokqGtFtjQTyVg6ZCpqdNDLXGvIeddcqpaGkjgyZnhZJwRFqeXmsvJaOU6aaGQIOOeB03mPuuxJlCafY1SplEeNuT6rEss6yRqj5FyiJpUvSS1vUZQjQ1rYvKL6lMvUdJLTtYUQ5bpuYFADNkVb2phkAANKMeZFvdGCfKRSImN1Uv+yYw49B+I5Ilc5uE59C7MxJxGmvAvJGVJjVUHay8bPGmPK7AgQIdjxekeWWgFLQl26prmqgZwykA01a2GPZMOMlilGLYPlc9lwIPO+70UHP7F8x+qJGKmaRnLbk8kYCeZa5rIsxppmpXViHYvx06kxUllVFGWFDgFtWkhCMKLhLpKmi6R6F1Vm08N8Lg1crJZGLUsxliRKYhkZ2jYJpXRdj0td5Xwul01RngLsYjEiQ7kpSptU0vb290XvIinl5XTefoqUjTEMCbUj3ddlc5AkqJMdx4QsdF2HT8xwbYzIphaS0snk5eyY5fx9vt+ZsBoCSYJ1bTSOZVlRVXVCegI+gCkKrJG67/X1jVROJmmA2WwdNwwpBy0ojS0shTV4H0bkNa9ZcTBcShcsEoFZCJd1PRHpcWtHrkrWH9A61bCrmNCs3AU0zzvD2tqMjY31FYMuaUE3iFNQ1zUKRV9Kp0CtLZNJCmoGcXxX53jmFYwk8CSIY5LjOTiPc13K9Mq+ZpROnRhFiUJSW/FLb9Af9tUPp20X3Hbbp6R7TIYFvZMGLalJS9cNbG6sU5ZJaD5GNjY2JK/jJV+8SJ5nPzhmG5tMJlPatktlJG4FytPMZmtoJQIc4sk3qVRqIgSRomK+aGnbjqETZaqdnT2G6MYNzBQCy2cWdl02yfvRtIuOvZ25NCOoGjbWNzl6dIsjWw3GKNp2ZyT+WG3ZXN+kLmoqU0mpTtcz35ujguaKK69gMmm449Rphjhw5RVXSn6uG5g2Uz760Y9SFzWlrShMgcFQ1w1lUXJ06yh927N7fg+vAmvTNY5uHeXe97o3+/tzPv2pz2KNZW26xtbGFsePnWDaTGnnC06cuILpdMZtn7yN+f6ce11zL/p+4I//6N243nN06xjT6YQTx47TTCdk54YgJCxh0WcjL+ShE+UV8v36nrAQQzhfzNne2ZY0AAJHD05jSoNVdoyut3e3UagEhSkWQztCYUZpbLnS7lFpNEoavSQlwZHIk1LiRVFQN1PJiVnLfD5nsVik6Eel0hwzRpchRdfG6vyI8DT6YQknJz8iVyWExJi3pcg+TiYTge6qAlLu2AXRay6qmg2iMHmt5cjxE2xsrDNdmxIV7M/n9EPP3v4+dVHQrK2ljd1QVMIC11ltbzRmydnLiEJm36tENtUKM7Z5zVEH6fuEZLzHKwAr0Lk44IwQvbwoewPp77A02Kt/oyTfaI10YBu8o0/lWlJDH4WbAJhEQAxOOs45H1KuXOQ64yKi9A5t31M3U4qqwOgKlE6cDAVKlNeqUjpqee9lkyM5UiFIG16lhFUPHD12FG0058+dF7Z0UVBUFVUtAjC9GyirWhCTskRpzd5iQeE9x2ZrWKUoG5F8XfQDe4uWCzu77M4XzPuetnd0veP0HafZ3dvjU5/6tKTkkoBO2y1WiKKgjBpTi1mCNQuu5FSZSRGiTo7CfurWWKU8uMo5C5a3SQyhTulIteRPZOOrkzJd3yfZXs10fV3ysAnKznofWXUTILcdVUlsZdI0TKZTWV9KCTM85bLzOXnn2dnZpSwrrrji5ChqoxL033UL+q6jma7jfaAsc1+PakTQBPGT3Pux48cFGjcWn6TEszyxHtNzekQIJNpPVSSJO6OUSGpPpxNpkxzj2LhoNl1LzW+65Ojk1sriJJdljS2EBCyVoMmRCEHmcQpiFVDXE7zzgghYUeoUNE9RTRoarQmuZ/BuLIlzgzQj885jSimNdsOcnQvb2LKgahqMlkqioAX16RatOA5VMaJwn29ctkHPcENVSYcZrRUhuJTnkLIvpUWEQRoAiMQhMSaddi1RfSSH6+jUGccUhYgXKE1UIj4TiWilKQuRKwwhjhNCRAMsRsskKWyBL4SVnW9sbqkHWfFT8tEheZzyYyAuc3MxMub1iWNGXbzGJOIgYZA0QmnbFtct6HuH0S1d20lTkyCRYl1L2UppPZPJlNJWUj5iDFrbsUzFrOrYp1y+tcX4o7XBDVLLXFVNQgdKCjvgS5860UneLUaVFo0gE9bC2to60+mEWcrbuEHgXZE7lEYROV8ltdlR4NW8qShhnUdNgqLl+0VSHTNJCCXNORf8GE1Deo847BLlxhXhk7RZizzm0qCHsGJelMhNZgMzeGkrG1XEsMwtZWnH8b0x54RX/p2G9CGIyw5lyOZYaC0CGbXkuqumSp/NaNBtIrRJOY5EKFUzwSY0qQoy530kaf7X5K5PPshxlc6NToS/ocfObOm7jAZ9uQZN3syJI+SeDXr+nvJenz+EgwY9Lj8uOUzxUgY9Yen5eutU1qODx8SVvvFKVOrkk0mIisajUEEdQE5y1JdFQ5bOBwlBEKENZczIqdAoEQRRSyKYOInJUUuOWyZT5e6LZWK/q3GOirOzyrp23qO8H8+bFPlGRPDKhTDuVSrtFQHwPtAmHe793b3E2+mWCMZIpEzlU7YY9QhCjJIaDB5Luq4m8Sycw+S9Mh3T5H0qw/aJEJc7NOZWpKOoU4rI264bSadZoa+upSPcuAKyEdRSG5211bXWIzqYiXR9t6zHlrAxXb/keG1sbo3XPdMii7KgrzrcIPtrVUvJbVmIw+L8kEReArawTJoanRz2TL4Naa2YVDpKlCh2GKRl82w2S/t7yAAJTT2haaZjlJ3bdzeTKUtRHE+M0kBK0LOCum5EWlnrlArKWJcXieMYRelPKaqyAKvGdMoqYjjej5wyTMhE5gyNSzbNZeccKglxCXIg9Pgs/0sQ9U1lvsQG3aEJymLrBqLAEX3f48IcVQRshDoKcUNZi4swpD2mHSSnKA0kAt3gCRiqyRraWoYAmAKjLfhlCZtSIh6ivaJdDFgbmTQaDywWHcYI7d/7CGjcEOk7j1YWa8txMg1R9LO7LuWnrDgDVVkjiVEj3aDajjNnzkl+qd+nKg3aCFnjyJGjCe4NDBPHdNpx5swZ9vcX7O7us7s758L2LtZaNjc3aZoJs+nm2PJv0XasrW1Ju8Wypq4nNM2aQPXG4B10rScEhVYFZdFgbcWiHdjdW3Du/DZlWXH8+Ammsw20LtCmRGsRfghBYUyJLWpA2gc2UzHg97nPtTTNhI2NDbYvXOD2U6fY2tpkbX2Tvfk+5y5sM1/s4VwvkLkWKcq8iQSjsJOaMgaqvhf9gWHA6yiiFk4We446rbbJZ1MpixWJXtATSXP4MeVBmsgxecEZMPcpVRMRBalFEmvRxqTWhL3k8BNEHZF0SiSOv7NRimnBLzXOYeh9ctzEOSmKQiLRRiQzN44eXWkRaZLqm5Djto4cYba2LvW+eik64oJDoTiytrksDVLJKUyEJ4kcwrIPfZHqg0s7KnVllEFSWpL/9N5hrbBiVf4eY9phSQIV2p7UvBIZc5nRDeAduX/diFSQHaHl74OfLWxjyWlnPXQpXxvh80QGzSm1OBLGghgfm8ioMYr2uTZiMHPzDqToAGWw0RCVwcSIscI3kdhIixDVMEDqPiV5ez825ujcQF3XHDsqwivD4MB7cE5gca2xg9RBG6WJ2jN46QXhSbAnhqAMQWt0UVA2E+rZGpP1DTa6DmMtnz11O4vFnHm7wDlHWYpC2nQ6TcjMbko/SYqsLIpRcpXk4xRVak+rtHRmTAbVZgNuLWVKkemUfzYcLOksbZFSCDY5g4q2a9nd3x+5KVVTC1fASnltDq4krahEVyFCTM7Nqu6AkPgyoUyJ7kAIouyoFCb1lt9Y2yASGbwf3+sTVyaXOE7XZmO5LTGyvbdL33Xs7eymjmmTxFcqZT2t7g/52iXmfN+lFGRqhJINfQiBuqkpizr5tjGJ7YhkeAiBdrEzcgoknSrlxEbLOrTWij6FD3jX0/eB+Tw1nepbrDGcOHFMgsHRQRQn0IeAjhEDqdQMVFWhtRlz6a7rCVHIgn0nHep0Iryp5MChVWaaHlyTlzEu26APToxnJioMIQhcvbsvylmDwDIiKSnG2CXB5nnbo5UmKvFwPRlOUsIkbftUAyrlFLkMRCvNtOlRKPbnCyHDNQLNhSALvugl9wKKrh9SkwBkE8iRYXpeZQ83oQhZRUtpLQ1FtBrLHRZtR9+DsWBtT4yJqWotPtXFOh+xtho1fLteNM3bdkDpnr39BeXgk+ytRylDROM8LBY9O9t7I4y2uzdn0fY4F6WjGCK60bYDbdvTtj3GlFRVQ4zSPW13d5/9/X1QhrpuUdpS1xP29xf0fY9Ssnl2nUOpHmvn7O3P2dubUxQlxpR0XSskk7RwohIBi2z6tFJELRuBKQuKqhQPcgXyE6lOfSDPPdaop0mZI6NcX52hv5gIN7neHKVG4xtTiBgUOKKIM/iIi8ICHYInODlOdgSWWWCW+XSt06OZKAM6aqLOxwBlLBiLFNophhDRPkj7zBAwIUP5kWLeEpQZlaG6Qcrxdvb2sNZwt7vfncIYSHm6LHfpUtSQSrxRUUoEQxQvXJOue4KanXOiqpf0GXJrSCnRW0bTUcnfOl/nBLmrkL+1qOOp4FK52iUM951/p2sZI2NdcnYupMnSsn4/18lmecpliVtAB4OOOfUBRgXRMidFxgqkHDHxDjKsm/aHqDKvJkIQ3f6YnpcoOEf/kt6LqdwrwlK/QOdSJpsEZMwoGrP8LJX0ppYoYkBUJEWdzksTlrJitjYb26h6L90Yi0LSNIMbqJpKGNNlQWlFICeXW+oUw5pSxGlUMgRFri1PjGZjRcOisKlxlTZLNcUU7Vkj0by2Vr67D8Lit3bUbKhqSTVk5EelpjFVbn+qklCYWrnuKQGtU4ReJr6OGTpJHQx+jP6tkdr1YUitZhOyZ6zFaiEjB+dF6CW3kI1QFB0hxPE+ZLTW2kKQXCKptaIYNwUx9YsIIfFokq6CSvZElrvKBUwyw5TBKMb7Ozhx5MuiTOupSDr3maeRq0ESzyalAXSU1t4mOdUxhtTGO5Flczn7yg+s8EYyLyEhN4MTgmRGhzNX51LQ+up++vnGZRv0vXag6wZ2F33aYHp2dnY4fccdSPclT1EIzV5FqXY1yXPf3d8WuD4Jsqgo7QC1MpzfPc/pM2dHskbfD3gfUj9ZC1HIAedOnxEiQRBj3vfDWM9bJKLYhd09dvbnOCelSiEKBK2VQRlDUS1vMrrAo4jKoKyoLhVFwfrWFtNpw9k7PsMwtAhL19O2C8qyYmtrayzlqqqKyWyT/f09Bt/inTg+F3bm7C96BqdGsYZz53YIWJxXLFrHqdPn6cXRJMbIbZ++nfPnt5l3AwqN95phiFy4sMf587tsb88pyymz2SbORT796Ts4e/YsFy5cGNnmV1xxgq2tKX/6p3/K/v4+ShWEoPjsZ0+T+9Lv7e1x/vx59vYWnD+/h7ZCbNvYmkmDCiWiMqTNLhjxRG1VUSpFEyOm71FdN5JmptPpSLTL8OlqOV2u9UwKrQLzailL7IaB4ByT6VTmTkrTxGFFHEUpXIJrRSRGEcuCuXP4lC8kQV1j7/EUOWb4Mv/OZDjrIQbRpI7L1UcfNcFFzu8tsO3AbjvIZqJSXjR6ilNnhNSWmuKIEEjHRz/+cWazGU958pOZTA0GLz2+y4q+62jbbiT6JG+IwjrJnfW5+5MhBE/Xt/RtJ2pZnYglFWUhPcFjTilkbyRF6CEX1oWEymcZmYglYImQFKvyOBidHyQm5uf6vhuZ3aKIFpYtWpUaod/VBhLCkI8juqFS5FFXtWyiRYInjZS06qBAGfGgjSFqjVeMncCSBiA6OZ4qRzAwMs37oScS2Z+L9GtR1okxXVDVNWVdUTYNtigpUk5dGelk5ZVKJUwC0aMFtWuHgd39BRd2dkRRbW3GVXe/mq2jR9lYXyeGwGw6GdeXT/ruksMXJTeNpKFCjKmmOa2DEEXnOwTp0GYtTVVLoFIWI4lVDJ4e1fyy+E8WYdJWUnKL+XyUxm0qgdnLSoiBi/251EN7IfAVKYU4OEdRWNbX1sUxMpqhk6ZTmZUxm04prOgB+KRCaYxhY2sThWLoHUPYH4Ouqow0k0b2ewzeOrTNnenkuMYWGB/GNO1oOG2B0auOBeN5SIlnJCojaYKuk+s7yqJKsKSGMELfxohTLc2UAvO5NIfZ2jo2pgmEdZ8QC7FcRECbEhs1da1l7VcN1iiKqpIKBidSz0IT0WmfYGxalNG/7FiSSX1BUhxt1zF4R0UcDT5anNvVuFw0HL7EZWuy0DzalhhlUKagcZHZep8AsSAGXWv6Tgr9q6oQ6DVdrLIqR8Z19sCrtqeo5qMAQ2XEgzNKcg/SoQuqibDam+kaRKi8RyeIJOfYtClRpiA62dR0EgKwRSVzI9V3olKrOmPRaNAGW4oesfyu2TxyFO8EXvbBU1YTYTwG8dSaqpENTBtMUVNGw6JdiEBB53BBMYsKgyYqgREjhhA1g4s4DyGmEpQIzsPgIyE1q6gmE+rpFG0L0IYhRPoUMeYNcwgS9Z3f3hFugJUJujufs2i7UYCjnorD09S11Nu2LWsbWxw9egwfRaWumjQUpUl11+JcKRCCSFD49B2ULSSa9HEshRkCxMGPZUs5H581Adyo7b0sfcmQb5das0ZbYm2C5GMc2b9FiiQy8Wc1l+dSpJg92KVhCWkxZ75E/g0iyiItSJXSZMK9RCuaYARuzY0SgjKj8Y0pjxeUwSUZdZXuXe8ie/stAc3O/oLOic5+LqXa399nd28vBz8iWqE1TSW8ivV1gSSn00napEtspah9XM7VrCmf7002wslojy1Px3Ahy8gECiWLXeX6e7n8KWJIMyr9Xn0OQJkCZfoD5UyZp0BMkXBKK8ASkdExEFUUWDuCigoXYmqok1IE6XBSuh8Fe/ca7T06SkfAVLVJSuiT04l508s55uxEOjdIZGbD6FBmeVTnPCiHLuScfMolS3iUFOqspW4a6aZmRYDEeYcxQiybTuVexdTgZto0gKAqVkFlGilnbGq5RDGLwATKpOGfuSR920t6JcqcLa3UyZskhWq1TXNFjaFfRorybc5roKpqbPBYL5K5dVWP7x2ckLIGL1oRJqFHI6NdZpA4x8LCJHcoc86LW6KSprghpY8CWcgnO8ooQTnyehRnTqUctE/CSEoIokH6vougzlLVb6yOGXVJ0p5hIOqIVcKrKIqEEKkVkm0K8lb/zqz/1bx7VsEbeT5pX/Hp32PknNJxMUoLcJPK7VCCLkQiSieGe0qFSIlsqqxJabN+6KX3gReHOqO6qy1cxxLbKHN+GRibUTr3843LN+hFJY08qgk6Ig0j6glF3VAYnVqoSv3k+bPnaNuW2UzqZjsR8h7JRFXq4xtCoAuw20qLPuclotEJFtdKUaUWl2u6oKpqto6dHHN1KnXMyI1dTDXBVhMWfcBFR1XVI0wGCutDSi0FgViMFT8lSFOEqqoomynVZMrRY0dQKrK7vT3WYbZty7lz56iaKUeOHEl5kI6yLiiqyH7rWPQD7dBTFJGj0YKuUKYGXeGTBjB9YAiaqAoCAk0OUTMEhcegTcHa1hHWNjcp6inK7tKFwGJw7M47tJUF34fIEBSfPX2G3b1dFr3UkZ/d3pUGFkgd5PG1dZq6YWNtA13VtCFw5dXXcM09rmFnf4dFN6coNcpA20sLTJf0ucMYwRq8LlA2oqJBRSO5TO9ZDJEYJb8afBgduj59RiaeXSof1M4XIlCEOGdDKj9qO8mZT5pmNOg+LY4Mo2bHIZfRZA15k/KEucwnC1Xk55VSFFZjjJC4JPOSjIK1BFsQTUGw8jPCZoj/HpVKilsyD4eo6b1ie7+ldZE7zm6j9S7nz58fN4bzFy5w5uzZkfxYlLJ5bazNqOuaK6+8kul0yskrZX3MZjOKKlI3M3zqC56llJc58BVy2Qilr1znsDTopdGUWgkx7k45888VnQMpuhnGNTvKZo5k0jv95NI1Al3f0nZzlJauVdpH0MkJDGCUGFThwQR0dJgAUWlZm5iRoDRqk+dzBNAqKa+ZlXXaEaMWyeeUWhucw6SN1cWIKiowiX+j5XhocTbKqmZtc5Pp7i5lXRMVdMOQGn4UbG5tEWNkMp1ADNRJi+HChQtCsJo01E1NM5mM5YKD6wnB09STpCYo17hrk4G1aXaNwnDJWCKOqDwmddg+d7nrEwvbDRhjmUxngqAER1XWlGWFc9LTfL5o2d/bx/sBpRVFItIaK5LK3kdQMVFMVbon8tlt2+GsENukJFVOqOukDr1I5cFZWCsivdVNMubBBxZtix96QFCKohSRnunMSalh6haZSz9J6Iwge8vUSozicAUbIJrk0SybrOQfmS+p73uyF6uo4UEDGkc1x9V5nT8jN3iRunRQOoBHct/JDwwEtF9eg3ysoZdGVPPFgrZdMPhBZDMiSQVv2WdEKakM8iHgiZgg3zGXvl3OuGyD7qPGBU3v0u02Gl3UzNalZrAw0mieGCjmHR5DM10TGNtIGDQkyc8iSZSGEDiiLLaaJhKFkBiySlCMkUlZoWCs6ZxMpuNFyIpAMXnBa0eOs7+/T9f1S+9RaYHVknceU94uK0eJYppMMmO0lNxVBfgeCBw9cYV8/5Q/7Lte6gsTaznXgDrnuCo1hCnLMjU8mFIUBZOm4fhVd6NZ35DFa4w0f2lSP/YYOXn1PQSCSQTCu11999SQpWK6ucUTNazN1rjm7tfQDR3zds4V85Zu0fGAKKV+k0pUpxapjCa4SN1UXHW3q6TTUtWwvbvNHWdOc8WJKzhx7Djbu9vM2zlVbdFG0fulUto4qZE8WwgSlbthkBKmvsc5f6A+lpg6yK1A7zlC9ymiGRdMZDT+TVLMyrBhbpKwNpuNBDPv5djLOliBfiUyXG3kstQ0V8mbH/9O87kopBtTNj65+1dhU+14WQtJprAJTWJEGJwXrkhRChzapTJMrORSt45eIZHc+lYqV+loZhusbR5NlQt2hI2buqYsCraOHBEjMN2gLAuKqkmSlANBOXTUlEYeB1IteD73bMTvZNBzhB4DBki9Bg/Ivuac+fI96fNW1r4OAVOtGu2suy6ISkZqlhUKWS43QFFA2viiYkScXJScqFRJRGLITXCk+kW6cKUKkCiweyYSZlwipPr9DJ1mOd2mqanqhul0KpC+NmNLTPTB5j+BuIRtY4oItWhkKGMp64aqmVA1E7S1RCWqdFKy68frDCub+OAwxmFt6nrmpT948B5jSmJUqcmUSpAw2EKMk5RqJVQhrZec3paoWi8j9XS8rhsoC4VujPAR0vfIJGSJsNOxUjdMrZOhiyzPA9JaldbIRTK+4oSqEV3NrGxRUwRjham+sblFJucVqTzNWg0GKTH0qYd7jJikyV+UCeoea8zD6KaGVDufqyJy+2SVeDbG6GXHQIW0y04dEr33BCeltTqhvQBVU42BCtwpZ63FiRBeR1wiBYKWJ6a52LHBSwAzEllTii9Xr6BTa98gTYv6tGd651GAT4GETciETcTJMKaY4sjr0n8eEboLhsEruiTmpqNQ/utZSVkIyzMmic9yvxWDvrZJU1esrUurz+3tbUBhjcge+hioZ5scPcEoKCMlPpa9vT288ytSpMsGKlkAv6oqKccoCmxRcl0uI1ipMY5RGKzZo80XPntyMumXzeltYhnvnD9LjJ6trS20FhQgowtt27K7u8va2hpra2tjM4G8KU6nUiKxn4QemkbUx+7zFfcfoz3hIQzjpGoaUb7LsHWXDWpavPd54AOoq5qtjS3OXzjPqdOnEG0XxbETx5jOpuzv7ks/+FJgwqET5+L4FceTZr1hd2+XM+fOMJ1MmTZTzm+fZ76Y00ykl7KPfjS6+dyM1ivKSpIzHpyja4X9OZ1MRMQnQ9+skOJSRJcVlPJ1Xs2zxxhHr3p3dzcJcIi61PrGhgj3lMUYoacTOzhBV43U6t9xaZyWMDXj5p83v5jZaImYkmG8VbZpdkQWiwXDMIylPfv7wna+6pp7o5QaHy+Kgq7r2N3dlaYVTvTCi1zzj5ABtdZMk/M3XRMlrSKp2KF7ghK0xRgRmMlNaFaNd6bDrRpzWIHYnUsiPlkW984R+sGo/M5jtTwnvzbfu+z8LRvN5POIaFdhq1IkTEVSCtC4TF4KWepXYaKi0AZljcicptLUnP45AA/HOMqiZoOey9WappEqk9lMSJ5KjyIymc2u0ma5TCuY5XV1Gh9BW0vViEFvptMUvUZpA53m8ZJDlr63c9BL5GrsIOpwzjMkvXFrK2IArVPf+xRIlEkKVqmQNOEZnQGlpGKEwqB1mq/J+Dvn6RLpWOuDBj3va8PgADFqBjOWS+Z6cHnOEoKoSpIcnFJrol0iNzqVCVtb4H1gsWhROmIL6W62dUTap8aEmpECH600nXPSJGhwqEgSsLIUxZB9CgJi+HOjn+DEaXJ5raR9pShSj3ArsL/zUQSokjFHibDPMAwwkNIR1Vi9E0IYpaxXNpClurSK4+conZ0ENaYOeidls877UYETpZI8eU49SC7cBS975dCPfUokQJIDFEmcKgcOLnhxaFTasBLCuMpP+Vzjsg26KkqUC7jUoUwPHmNLbDVJpSmGGCyEQD1ZQ+mCyWxDemUXQiKwRSe5NV0cIFdYa2WviZGiatDGUvrkZSVMoyyTgpb3adEm4Y8ilSM4n/phJxWkEKireqx9DVoTrQUlBBjJWy+VkzwIjKokH1ivb8j1THDLpJrgvGevnRODopys4TDsLlqUMth6KhBwDPRBCSuylOPrshbGcpAWtFopTFExaaajh6yMISiFiwOBSDGZkkueJM/uUUqz1/dQlmwdvyLVqRrqphYxDY/kHpMRMqWIMuy1ordPIk3NNo8QQ2Sv71FlRVNIf3ltNCYZdO8SnEpA6dzsQNp4VimHKhH6IPrGycCOETGk6BB0ENERHzxFWEZWWQs7jJBvoPcG7RzRSrencrJOUVjquj4AmeVmNHb0XJcbz2q0GVeMXn4M4kpecgk35zzwMrrP8CJpdYmDlZ2SqhLYMLO+00eLRr7WQpLynmPDMDoVRcoT5s5ludVohgbrJCyS65Oll+gAxqYOWoaRDpadlZxTzT/pezMa/kAYHGHIZWtxfP7Ov9OVXPGMGCPnsQQv50qD3DOXZEuzgV9qa0eGYU7X74vGQEz6BCh0kmOOIUVtIRnsxEvJUHk2vpplu97sMGSnWOZFajscpTubTagZ2oAGayRlF5RUbUxmU2xZUZYVETX2NB9coE/55n5wUnusDbYoUcGLA4JOaZNSmOlVhTJajH4SKSnKUtq7Gjc2GJGcaYZ/QSdZYe8DfT8kWNeuzGGNSvLFOnVvNKkcSiBom8oZ7ehwZ2O8VFiTdNLGxhIdlKWajFPfjQ6RdENcjOmnMoks+SysMmL/y3JF7wM7u7vUdcPm1tbodHddz7BYopUhlVpmrtRiscBo6diW0Rayw6gVBDXOb4VUL5BQLW2lvWmhhRwnTp2mHAWrpJzW+X4FgfNJq10jKnVqJNn6lBb0ac6MDXVSai+L8kREHnq+WOC8oxsk6FBGjd9PAkYzli0uf6RaIatq5r0lI82jpHNkbJeb5/uBPe3zjMs36KYA44QZHiJqCFSNxpTVKIAQlEfrIAQyZaiaqRgKa8F7tK0EOtEWnEq5lhJbVQIvBTBFYnn6iPZi9KNS2KqRi+U9RVnSTKcjK9B1HZ3z6BSN7LUtLgRMVUu9Kam5hlUrEVuENFGFeS0LPZdj1ZMpJtVRK60pq5rQtsx3dihMQVVPcK5n3g00tSjWCYzocCHlb4oq1X5WEKQunyjwtTUl1WSS92Vcioodnqii5P+ztwdjLnqRNJ3XJtOR2DHezDqiMmkMkS8NIbDoly1P67pmNlsTtbXUkKEqRMBGIpbU0EEl2DykbkdWulVV1bJM0LlBfoasEz0Wuy0NOgjWSlwhawnZCSI+kPTCBcIqBoVyg+gSGEtRz6TxQUI5RMRIlKQmkxllWa0cNwemy5I3WQjLv0ejl6Lx1feuGvKDcqSykeWSozyH7CgsIe+XKCckXWo1knNIBCGdZIS1FvUyn6C4kAwhCBlUZmdEGZn7YpRMku214zkvo+WD0O8B2D0ZcKcHvBqWBv1zROfxwGcxchZGoZNcWpZTEGNKxae3xcRLiHR9iWkN3g+IaFE2OrkBSUwCPylSXzXmyR0RxEQlQ6PGc3WrG3DK9yqtxhaazjm0Te9PqF7QGoyRcq6qwthCjuGkuiPD1Lm8SSoSpOImVeEeIFxprUe4tKobrLFUSdffFnbctIEDBl2iaDXeqyXSYFaez/NSYNy83jOypJQ4N9kAy7qX14bgyE1SQDGdToTxn3KxWctdEE9Bk+TvrPevknNSjchLdhjyWlFaStL254tRFAbSXuWloVOMEb8CF/soaZquE0diNqvHe5lRH51TGFpLesgnaFynuZgMZpH4LWYQ/YxRGTJGYvT4BIvLuUds9MRYpbSOgiACQjF6nFu2dl5el2xQJaWgjRASu74TBMANghwEIcxFxchW10ZLyWYuy0vrZiQ3QoLrzUo+X66t7LdmrNbJCNDljMs26PuLnrYdGLxEXdYYbFHRTNfkoocAKbqzVU1EsegGeueZ1I3kCydraSvVaO/ADGlzMAQEZvG9Qw0ekFyNVqnsQFYmURmcMsydMAuUEsZs0DZ595pSr1OESB+R+tsUUShtRm8whDj2JVZ6aXxzZ7jQ9wwx9X4Pkb1daRlYzTZQKJzS2ElFncg4Cx/ofCQEmNQ1WhsWQwfeU8SBGMFOZst8nTH06NEbtNaiikKgWR/wXYbRUtvJoiQiBJMh/fZDmxa0LGaXGPCbmxsopdje2REIeH0jpRx6ArCzaCmqms3ZGov5gkXfU5sqqa5ZAgGHpE/63oGKmMFRFuCCqACqRKTxQWF0neCopcpbzHMibShKLSM9ycmlaD7kjlUDBM8UaZbhfS9RkJX6VZtKgEDT9x2D64m6xMWkbS5LQbxcHcfXSgVMinZQJLo1IQi7fxnVjnEvITkaMXtbOdMal7X3Sil671FKmMtKKRZzSbsoI6TPtg+pnElKJEPIutDC2xBBCpMETZbXaoTElRG2uzFoK+VXhbWjM0Q645hzTMmYxhUnJVsFbQOxXH1ffvquDXtGLkQL3KVKF50Y95IDVBGMF7lgkkHP91briKlLmmlF7rg3nlpMbTxbkcP0oSUEqW4QjeuwJAwlZciiDOSWs1muNLfxlePJJt80UoHS9z06BJQJksN0TioVQkhwf0JwUOgk8GMD1Okq7ac2oSpt1DqKloYtS4gWndT8skHORm4ZhUdRg0y1zjHm6gBphZrRn9x1TOuQjDcUxbKEMRv3JWkrs8gtxkBRlOka5FpmnbhEcn1Ed1yOlaF2yW9b1tbWADU2ccmpyiFB7875A4EFpIYiMY7RMVEY7PPFQmB75yUtEWVP1ym6zw2KYjL4gQjz/YTuuGS4gsDXZPXIRK71YdRBjzFIYyMtvUMWi31KX4JO/UW8Z3++T5vK2pSC0Dn0oEUIS0sZYK7AGdxA17b0/SDGOqdfjVQYRBUofEFWPlQaVGrlnKHx7ORLSa4aHY/CFsRCet0H56HyECI6yn0ac+1Rmh9po6W6oi6lZFiLzkWf+nl8vnH5OXQfJVdByg+gUNpQlFVq4+cSZCAlYTqIcpAQ3QIGQ1FU6eQlErH5aiSDixL4KYL0ntUapVMv9cwM0QKZ92F542NEJESTp2pLk+AkgVyUkc3cZFUkpfCIQEluq0qxhJVzjjt62ch9jCz6QSCiuhobvOikGe0WLcPQIe3EFdEYojYMXSIR6VQXaZd5MzkHxRBFvCLregeU6Ck4MRaS9wJbyjWI2uCT19YPEqFkT9I5J5PECOnKBYHcbVmlvBTjAikbSz2ZsugGXOzxUWJQ2cb1aBZckIUsLUEjxkW0klIN76WkLQtfxNSHfFVKV4ZailfoJLhiRKNcp/qlAGhlKeoSGyM+VBLoKZ0EQUrJa2tDiHLt0HY8V9lvklyJWN0EjapEKkoVwUrylHhShJRV11YFbbIAzsFIidVcrloaLhMleh+cQN9lIT2dfSLsichR+ojk7ARySU7aIZaHWP5bSeWBjjK3jbGpHjWXqsFowLNBj3cy6Ok4RkWiOfDw+O6LoPfx+ZSZ73vhpWhL1AZsVj5T6R75VKLmE9Su0EpEc0yC2KNfMeiREe4c9xRyaVNAByA6tBJj4ouIjaRrycjBGFL704gY3Nz+Mtc/E026tkvJzRAyYhOXlyxH/0iFRBEjoYrJCK/ckBRFGWsgJGnayGh0V1nTMQRpgblSHrXKM8hEM1iS25aRtxoNsFJK2rWSU1XiKOUqDpXY19ngZ9heomPJo/eJvGptSM5A5jjkkqyYmriEdD5x3CdijCPUn8dYuujDgQ5u/bBEApcpqDRXFeP3QalEdGM8hvSHSM5njv7vxL8RMSiNS2RWlCgoDm5I8L8bURvJcQ+iZcIStaFjTIdlgqu0mnXSayRF9cKPkMy9925EPUgBoIrLfQal0l6yOlWWqTttVkjchZVumH4FVSSlHZPjaAtLUZY4JfPWeScpiMsYl23Q15PI/97e7tj3PABukBZ9fd9TFgK7TKZrhGbZn7v3ER0DupBe0Yu2SxOxJAvyV+nC7CcBhBwFSGN3EX3QStrzhRjoUoejXMZgjLTbwwfJeWghtvjkFafMjxiIwmIKRamWkycG6cs+n88J3kvURerxHqXmMMTIfpJoNFqz37bMOxEqwGhslSMzKS3SCXItigLnk14yctOapqFuGqLuCF3H3mKxJPyVJVkpzaUI3qdGJ0rppP2dhAhQY75GG7md2zs7gog0wm/I+tmDE9W62doatijE2SpLUIquc7S9lLvk3saRSFFUQN5kDIVNDR6C1NILg9YTDCkCTsxwcptNxYGpmIyG87LFCmNY2mhGFGVdps1PFnPX9XglJCqTSDZBG0Iqc5PvvGqEuEiYIcuviRsnoZkiMWNTvh+tk3RqMr4hwcdL3JMsEpKhWOlQVdC3HYMPFBlFUCKfOVmfMfTSa3rptC6hfNI1XV6fOB5PWL1LYZgcIPnMwl39vnFpSLKDPELfZORh6TTkqzEeUwn8m/PwceVVEAmmhEI07pW1IjVqlucdpNVUur5pZGJROp8QejxurBDwib/SDhHvwOsCFJSlGOa6qlnMF+zu7mGGgLGOYpD1kSOotov4YChnR5gVU668p2JjfZP73Pc66mbCZLZG1w90fZ+UEQ3ntrfp+4HBRdAeZSPaKqqyogLqCuaLeeqO5lgsulFQJd+HXNceXSoby+TWxKeY758fI/Xc4zqnKdou7Yn90sj3/ZAEouqENEhJZV4rfSdwcO7UJkRCzWQi86+ZNDgfaNuOyUQknotCkIq+75NBH+g6lci78tpMxoSYInIoy0IaXQ1DamwSWVtbG4W3lEKqiOKyPLEoS7x3nD19Zpw11lrKhEwYpZfSzhlISvyLmJ2LHFyZZVdBb5JiKCIMoxFjWhVFypZJF8iyspRVQd2UDINC9wA1ZWVHgmrmWjiXZWNlLUqQWTFbm8g+lO5tthkoKYvMmicAXT/gvFsy0HUBOLJIlYAWqax1xbAbY1BlRfQiiSuBgxvTIwph7td1Qz2dshikp/2iv1Nf+M8xLtugL+v8EjnNCawZRsg0EK0sYNFrBme9wHBJijFvTz5IP/VRIShJMQpM0aN8OLDhRZB8N0lxJ3XSSfgoq/nScTtKhloFELmAtAtqxSiCoHOpk8bliCFtFoUpVkpkUnSQvqc0mkllFSxzqaP3mSdNroHMnniK8FQuw8hlEUqNEYdJQjnj5pqhX+/HZg4ZzcjHG73BtAlIraNKxlmPwhXZ+5fPUCNMKJHBMpcrsLEYMFvY0XBona9paj4xnmUyJuogJD1GGTlXCCu66un9MS1sGD1UyZNqwI/XKESkBcglvnuOwFb6hxLH/9/JPCUIXSmk1fmqt6GEsLI09HFsspAJYVqpZFTjuGnn75Ejd5HRVYn85qWsJsr30PrgPTtwXPJJkSZ1hJhVr9S4ga7G5vLdV6L9bMRH5F7+nb/H8lqk9aAysS7BhSPfIL89INpLCpVKwCQxrUeoMf87t6Yk3wtAiuVsSqnJuvUxsZm9BCqCtiw1BKwthFDaD7Iuk58TfUBFRfAJCbMVGoGcTeXYCpr19Q02jl7BZDZjtr5BmxT6VLoe+70j6k5IeakMTKMTd0EIVWN3t2SsQ4hp60jrmLTnjWVqAwpFYS0+wefkqZWNVYrS+16U4XLEm0tE+77FGHneGE3IikcgnSyHgb6TqhJSJF5YQcR8aROxTvLSkjvPDZAySJGQNp/FYgYkbTaMaZVsdEzSbBhiYIlmCJE1L5hs7IDU0ERg9OzQCk/IjGp2KzNT1lEmn6pMRCalG/TYVRAdUFG04WUmqdQrQoRdQgxjikGN812GaN/bkTegUpSenaTkZy65MlqNe18MmdiZnPOVHLggJB4dsqBO3hcEPVVJKyCOCzUTSfX4XaNiJNFlZDY3wtEraUmjJdAhuosQgLsal23QF4t9hn5Aq0hpDbaUCzUk5Z+qqsZuQjYp5hRVRZGgIACHAiXt8nK+SaJvEuQiTMT6ThR9BRQp+oypjq8sChG6gaVOcoIunXOo9DqLIqb3ygJjCXcock8riCKqMKlqgVbTZC0K0UnOjQGKZOBUzJlMuXvRuREVKTLJIUptrutlUVRlMU7o4By7OzuMTRTS9YwxEIMnE8oEoYDcA5sYCC4QfFxeByLRe4wtUneftPF4Rwhpy49gjWwAfdeS667zJC4LI1GY8oAseNng5JopIHrwK9BPWUBpJYctLT0TWSt9y/EyrxoTlb4L2eYElM6CFhB9Kypi6b5UhUo2aZBWvaFHESkL0MpDvLTnmuPSu3w8Wy2fX+PzyYqnPEbTq2+W56w1hKBFtCMRY5QBF4ZxEwgu4ObC/i7KYnQcTMoHZ8awbNLiSGklQjqQKjy85DKtTRKWicnscx14JnUmo5ydKi4i9omcrU8GcfSKYNx5YvYBEkM9pvkLEWsVGkl/kR6WvjaJmZyuDcakpjDZ0QDnDd6DdwrvrRh6E5nvX2AYAsZUKKuoyhTRptaoaCUHmXps6li3ty8tl5vJOmVRceLIccqypk7aFDqlmoyx6MIQSkuloNYKE2TNrh2/Gu8GokvnnuDhrpeeBvN2LnKoKFzbsbN9geBF5pnkuLVtK70s+p6hH9jZ2UErxayqUCGAd7TtPvP9vaSAZlfgfZZONKS2pSpVcXTs7Z4XdCr6sWwrZKndFBAUVlovmzigQ0Q5C14QqLbd544z/RhkBXKN+DpNPaHtRH8+l9LqlI6Stq0yJdZmM+qqTshNZG9vP6UvpSnLetKGyIIvg/OUZcFkOk3zX6oGcmviGHMpr+Ls2XOEEFhfXx8Do9GBzMRg53D9gO+lblsTKZWhToz5opayz/1hNzV7iizmLYv9VgKXsNT37xY9fpBrUFppyOW9T73kwatxF8c7URnM+goiJGRRlThXwvXwLPbnuCT2pI0lRtGT2FjbFA7IMBBchxsiROEcWWMZtKHttnFdz3xvl7oSKfEjRze56u53p57Mkk11hP2WerZObQuiFm2OyxmXbdBjKjXKntmSgZc9wVwrHgmS6xcDu+KdxbTuR48qb69xuSEd2PzTWH0sb1qaHOXI5j+ijWKlxwh4ZevKH7Dy7/F/42tMzokceFzJ5M7nEVaeS58xlvqo/B0ZH1vNDS3fJwSOfFylRNLSp3KN/IRa/mPleyS1rxXvN8OBSq1er4PHV8k6yyXwS68v5nNLd2oFZj5oE5cM43ys8fTUgReyfOPyPfl9+Rpk+3PwIBIq5ry4+GhxfDyk9xx4HA7e48818oHh4FxYOf7IOL3zPVj5Dlong5Zfkb5HjpohksnnaoSeGdfKKqs1G4qoljCfVomnki/JytpQLNnfAs3LZ8fVi7ucDGNUICSsLK6TNdfkGuY1qsbHYezPqnJ6J658xzhCpflT7rx2ZU0LGTAghLJcUhmVJeLH5ijCrdD4zOMIEBCpYVtPqCZTnK7Qg6eZrlGWNc3GFmVRU1SipV6koGJwHq8l8jdGY40eZXpNCdoURDUkxMPhkdpoFSC6QPSSHw7eCz8opQeW+1hGhAxKS297k7geKkiljU0lhsbkyCxdk/HeyNrUWsqU6rpKYlUiLpJ1EcRpSqWNRtJtdVViraEqUytmpRI5riCiRtIvCISrVGo3bQ3GJQ6Gybl7CciKYnSpE6PeJERO0Xd94jsMyTHJVEL5LllzPuvDg6CXSqmRbxS8F+MGiU8jUW02A8IVSJ/tA653DP0gfdgTemuSsI3J6o5KE1IfgyzglPk7WWjIGZfWrCLq1G45I1dppgu6sWS552g88wu880RhsY1zIaQ5QvR47dP11rIWQ15J4kzH3FIcUifCMPbBkGoJQ1UtW/6S7JkI+YgWQ1al/Hzjsg26BnIvmnw57nooSArvQPqdNzrSY+n3pfbUzzPU6u/RkDPCpePr8u7/BY+0ZNXy75iEp2UCJlh63BKXm6Ks10sbmYv+Xs6p8TmbN/+87aqVb5uNd14I4+fIdRZ0+k7G8U7f63P/fSfDFe98/eJdvDZ+jr/v6j13dQ5fyLjzcb/At66MOxttsZArL8wR60HvcPnay/o7M5XdSJRSycjlfHn0Ljl3SpqOJFZ7RsLGVMPKeUsJGCgdxigQGBuAJEYbKovl5Hx5JM3r1VMcVyYjlUzlWZUdhshF/tslRkRwDwdisI3BFAVaKcq+A1tIOVuC4aML7Hbz0U2LSqGaGWvHTnLsxBXYciLE1SKnw6Rt8LxLblTU+BAZCBJt9Y5CG6zRmBClscvg0D5gQ2p1GUXX3yorOuHG0vc9i719XNdDhK5txzafWZXQmILZTPpOrM02hDNRWmkT3C6ALYgS0eaIfCxXDIFF1wJQlVIO2kwnadUvBbSGrmPoOulZ4KVaqCgs67O1sWQuJlS0NpbNuqEbBuaLNuX5A1WVmqEYIXVlmDlGQZcuXLhA1jgfSXrJwNW15M3rpqKqpbHTMAzs7FwQxM+K7Ov6xiagxo58WTArxshivmDoe/Z3l6WcxkgLZK00OjJCzt45iV7399jf36fvpISsmTRS5VOJNr6KYJVog3SDMPn39vY4derUKOB05MgR1tbWRsGmLPJVFMV4vIxiXbhwgc985jMsFgvm8znHjx9na2trnMcHBMLSGvYhSFWR8lK5EmR9BO+JPkjaoFAoo/BquX0YBVEryqoQueKQ9Bk0S/5AUaCLAtCCsCqLvpwFxxdSh77675Uo41IRdYZxL/UJ46Px4Ou/4LGyCR04t0se9c827mySDjp4yZjf6UCX7Udc9Lo7R4Pqon/f+ZovI7cv7vsu78lqJH/wsfTEysOrUfel58DFz8UUlV/K2F/yMJf1+Bc/UiTN0qCPf8UURR147fJ7rZLK1Mr/811YOlYH74oY0pA0u1ffKYbVp7bB1ubIy6TywLDMN6rswWZInTECV/z/7P1ZkyxZlqWHfWdSVZt8uGOMGVFZlZVdVd1oQgRosAnyCU+gCPlIUIQU/kaC+AMUCgRjT+ihqlHVmZGZkTHdyQcbdDgTH/Y5auYe90bciIzMrELlCfHw6+42qJmpnr332muvdVR4n5ncKc+2lhR2rozdHKv7enT1PVE1K1DwtXPyLd7ZmlgoI9MNM79FJ47SNuJslnPGGZkHN3UioQR/17a0yxURU4xBZLNTWnMYPT5E9lMAJeM+SWemJCJGUwhEnXGp+KvnjIkJnZKMDVE4IUjvvvpmm9LPt9aJwUmZ91YxSg+/TnGU1pBGhKRSlHZYjAlrFNYVzQaFeFRoLZMwhALy5eJ1bjnKqyICNgW2zihCUbO0QVjWVWxL6aJ0KCnTbPU6nejuV5Z9nfE+3bPruFwNsLV/nkq//PQaVkrNcHgdFdS6IyPwdkpiylTVIGuwrDC6D5JM1Dn44EviyjHZqSJfKZaErLDNK5N+bg+Vc+bULKiOMfoZ6j+aNtXHPn0tp6N4dfrgVKjoji7DyfPJ6y6aDEYXisQxCZtbI6VnDpGsq8ri0QWu9sxjjNQWb0UGKpchl9csev4/dEC/9ya8zTo9Ie4H7e8VxP8erG8K4G8K5D/Iqj2Lvy+rtBPqWZg4GUOh/r60i1SVlJnvDCcBO88w9il+JaH1TkAv8GlG5vfl6dRJeyYxTcLkbtwSZUULexwj0+hPJEuLYlbhqihzRGhyeZ4Ku6biWKVEiVMCe60UTj7ympse6/PT13pv5Ts3+NqfqK+HjGuFlVylMlORa53SyBhFjU1rzbI7l963FdfDbrni7HzDg8cXfPXilhdXW5posE1m3YgF6Rc31xyGkX3f4xrHk/W70uMO4irWDyNOWZy2NFkQxiZnLEJkNUWsRZHRRmHcRFYy7dIcGjabDY8ePRZ+UNl4UWqefJlhbZT01H0gRk8II4vlko1bzRieNQ5lDGEcmUJidxjIQLNYQ1aMPmGtaBagDOSATwODT9zsDgzDQNeONK7BNAsWHXSd9OZ9Er5MGHf0w8B2t50DV2Wo11GspmqnIzyNw+GAUmq2g16v10dr3LIquXUYBg6Hg3AGyuiXIEQiHDQUKegQwmxokpEEc7ffFatZQQKq9KrTR2OSWPQMQpI59jr+dqd4zMwBexxHMdspSUbf9/PzA3ckgWu8qXapNSadKk/WgH0/kam/q4lKfYzEUYho/nsB8SSR0hASpKPcdW2RWKPn+6ScZtK52IE3mKYhQCFhqyPs9i3rOwX0+9/vv+DTNbOl793vtHp/U1D/QQPV3+FV37/73+///bfxvKfr/mf8TRX529znu37u3/Qaf5DE8E2IAFI/H8P3aRV/vMXX7jUHytdgJorZz/wI9SBjoLWvVmpYraRyjMEcjWdKdX7nUcvzqfrvk85AJWcqCk+iVOhfO3fm9srxleY7z3J6zG+M53dWVvlEXtMTUpiTDDQYq3E4tLY0XYsxTuSkXUvTLcA4Rl9Y8MYwBE8OgUP2KKMYUyRZjeocOMuIKOslqwgBQn0fEVlnSWZK/7U68TVGfNYLkz9lEZ9RVuNTxKfIo4ePWK/WVMlinymz4VH68gi3Mvog4lipzHJnZsg9lVnKVHggVXugsuXle+EgpUrWFdGtqpwXCvFtnAJKB4wrbT5tSEEq1Kp0Vj/7OrVTg1WtkOvfT4PdafV66lB234XstJLk3nOcthcE5ZBZfufcsa9eHqsmy6eBtT5+0zSCyOR8MjInyE6K6U58cc6xXC65uLiYA+dqtZpJbbXihWNyclpVGyPSuHXMb71e37lflZ2euV5l2qQSW1UZoTXFD4CcjwEdS452NrkRvRRQWs0ICVDQEX2HUS9aGafV/rev30qF/jaB5nWw/B8C+esTo9cF89et39f7930Ti98nSnN8bnU3LNdNuPxt/tV8T3VyQzhW5fVv9yv5uz+qOW6WHnV5mBiOVrPkBsUKawxd68jRM5ijEIlg5ieYQS21K4yLBITZ1AiBvXWJ+nfbHvfPMaiUd3lf8vEp5tL864pzX19y25jFYneMUjUXOXS0E5Mmi8Uax3KzLuz/Ftu0dMs1CbjejYwRVNOw3W7ZDwP75yNRZR6+8xTbNTRrB1qxQ0axdKPxQTGWj0MD1ihMCY5KKXTTiDJkK2qCpIYUAtppNvaC97uGi4cPePTkMWdnG1arJf0wiHEQB3EcLEx5qzSkJKxsxBciRPCRsknrohRYVC2zkpE5iq5ASGhdVfYqOU0VASYH2oHy+CBV9fYw4qPC2GWRFG6IYWC73xc55qMVaNd1J6NsHGfikSCyWq3mYDqPrZ1IStexvFM4uvbBa2U9FsfEOo5X+9QAXdfRtu1cOd8P6Jjj6F49F2vw1iWQ1YpYaxkJ8+HoBGmMoTPdHbGYlBKbzUaMu8oxniYAp4nONE00TcN77703n7n1/avEuuVySc6Z29vbMoZa9E+0oDxYkf+1jZPrOkPTCiMfI9JXzonKI0XkzBozawvU11HHwm2Z1sixjMMaNyOH37a+U0A/rchPfz6tuF/37/sC8/O832s29NdV9L/J+t73v18Ffde7f88Ad19A4PT9/bZ++ps4DW/13HIAX3vMelynv/+2/vl3vc93rcxf18L5LuvYBy8/o2ba5umFU+PkKdye56+TY3vN6/n60dUxRAmuKco8sfRicxkxjOQYyVGkcSvb2FlL2zR3jgEorPZSBeda1eWTVEPLDLm6d57ceZxjD//OvYt2gKoE0Hxyj3wa7OvY2klekTky7hHpTBE3iviQSbFMWpSqOavMMPUY42gaBUkTcsCnxBgjN/sDt4cDh+CZUmTIkUjmqt+jw0BQoJ1hebbBGEVjDaNS9CFC8bB22pCMJZeqMltNNmq21FaoWdbWOkPXGs7O1sQkJjyuKHx5IBVLV0yADK11RG1Ii0ggE8jYtgFthQfg7HxCiXe4ZlP0C6q2vzaWrNQ8niSnqIhvLVdr6ccXjwjXLtDW4VMWH240OYsgSc4tq+VCHBG9n6Ws5z24zFjXfaYGq5wrM18SjZQz0XvIorgZSiXbdh0LXSpGpeZgPF/vWtj+3ntC8ZAXS9uFJBXltKhB27mq2FYq9HJc9Viq1rkuz1X1NGrym8nEMnK6XC7n6+9UV76iBqdV+eFwmNGH6txZC9bT29VCFo6mTHX+3BSFTKPFcMk2TlCacjtyJhXRtclP+FCIrdwtjqvef/UqSDmVvUEuLFW0U95mvT3LfZ5pvRvQ67/vkwi+bdM9Deq/1d7w91q/38rxlMBxur6pp15P2u//xHeP4f5z1t9/UwB/ExT/pgThTeu7nA+/ccJ3UoV/Y3Vd1lyb3j+m0/eJ1x1zLheyMI5VFge941jPJFVOyGRjUGSMVjhriI1j0XV3rpmcC1R7cr6cJhq1wlFKStSca8Q9PaSTz5ka1I9pTk3yjsKpdbqjBvUy/VEfag7qFfPQBZKQfqMQtgIxpHkWX+lMVpHDcMBY8U7PSWFyyxACh2ni5e0Vz29uwDmyMYxkQob+cEtSijEnXNvwaLmg0QasZVSKQ4ygE8YqmlI5ojVZK7JVJK2KwmEBPdAo57CNZtEZUBuatmMWVYkJoxTJTZicRRcA6FxLspIWRgVBQTaaVDwi2raZoWDXdNic6VYrcha3M6XAFGjaF7g8lxaIdQ0b62YuBIDWUnX6CCFlTBIHuMViiTWaxhmGYaDve4GOldgB1w9qrpCVmtnt9xPvSm6r/ekYI4vFAmvF+RCkpy5BcToiH6XK7/ueQ99ji7DLqr7eYZyrcPE5aPDe049DGROMc2VcK+x6voch3Ol3++JuGbL07KsqXNXxPyXHnZrSTNPEzc2NVNml8p8TiKJEeKosdz+gVwSjVtRNMRTT1jDmLNa6IRIJxHFgGoeZsNciojqnbYn6nsn1UNxBg4z5wbEN8jbrN6rQX7dOq/A3Vdv1+ykJod7mVMP49LZ/l9b3TUhOoaHvs34b79W39e1Pf/4uQf03Xb9xlT5/SSQS+topuH4XaP9NVyXMK04UUbUI0KgsYj5aZYzTuMJwr/bOzsicqpS+zIE8BJEFhjBX6RUQPwX/K+f+de0cKuxf/z074tUHOKY6orBVbn+iyveGV1ySn9pndKLNDiTivKFrIypnV9cvsK6hXTZYbdAuYXTGGc36ckHqFNtxop8Cz69ecZg8i4sLsta83O1AG77cHdisz3j/vQ/pdwdudjvCIqOUBHOrIBjpX07lJQ9ReuCmvAeRzBgT20FMRmLOc0BsiqR09h6vRHgmxcTUDzIu5z1Yi24bwkyYCgRtmIpDV1Up7FxDJjOlWKrMgmYiRKgYjnwDXfqvtqhIqqKemWPVXQ8iVZxGuraha91cAddecN27a2JRNdRBqmERzjleq9UborLHQwhfG/mSUcpEiDUpOlbswzCw3+8FZs55roDr/lZ/dsX+Wu4X8LPZzrGqro5poSABVdVtGMdZDKht2xk+d87NAfQUrq/tgWEYGIZhfv5asdfeda3a631qcK/vYb1vzAnnElqJcZi2Zr6cUlHkiyEQfJg9HHK5plI+tgxqcqCLnbP3npAD2ol099dHat+8vndAr787XfeD+esqvftB/U1w8m8aAH6Tzf6HiD0/RE/5dbD1aT/9fjD9Xa1vC+qnx3x6m9f9/pvep98G5J5Pvn/d3wypSFUVbpl/dfJzuXU+ufPpA9//+fS4ocybF0a6qmEvUrXlrRZmew3mmozVivakP+djKoEcVDxCdKoe/8nzz2/haxLFnDNUp7b5vjXI55PHqGz/MnBWS/RvWMc0QJoZCovCIf7eWXqFxSIyEbndXdO0LQ/zQ7JyKJMwBc1Ymg61sAxXt+zDxNXuhpv9gYu2IWvLs6trQspws+Xhg4Hl+SOGQ89tf8AYS+MaVjlJ9aylQip1MGMJ6G4+6MwUIY2SZElKoucqz2pNGkdUCfQpJfwoiVWISUYOtYEYSmBOBB0KG9sXhEbGnkAEolKKxByLu6KVfnworosp4WyLUsWcp7pOAlMsrmc+kFMghQlbLESdc3PFOeuIK8XhcJgr7xqkQGasgbkPfkqKq4IrFZ4/fcyMEpemsmpwngNnd+xvz6NYMB/bqc56jFIZ1yBXyX31WFOQ57HFNGf0E+M4sN1umSZBuGrPfhiGuRVQ2e41oE/TxDiOMywfq89GeS9OSXjA/NiqtBmmaZI9oiBSzrZoU0cIC3oW5fWkShgs3hzz9lGu3/paT+H+ECJTzLRuIeeJevv9/Teu0N+0ub5pA69/u98v/m1Ucd93FbTr97behIK8CWr/w/puqxag8u9al5f39uTn07P67s8n7/lp5H/dz9RqWSG62KIwpbIoilWJ36boTYt4SEPjNFplYvCgFM7o+cCV0qJtrzTRCCs4poSKpXIvJhFkyLE6uxXVsXqYJXip04DO8TZ3k3FpxIvQEHPSEHndJnMqQiPSm4dxKJLEC843a6w1PHx4QdNapjBwc3vNv/yXX6GtZn3R0PkVQ96Bc+AcvY/0IdIsLefdmuXLjj569sNIUgHlFpisCbrhxdXI/++/+5e0WrHUmoxYz67WKzojFboxMAVhpmcShlxY8LkEHZFeNUoSCrQRre6C5yQEJRnHiWkYGLYihqOdw2olojUK+cxSwI+BOI2kGNBWQdYkP6IVtJrSjiiEPjI6Rwzi051SIvlR5riReXbXyGx80zQyTpciU5jYbm+Zxp5p6Gnbdq5WxRREAloovW0JHOJZXqvkOfBpma7P88eoQMEwjaSccDsxXYGqKmfnc6YS6JRSLBYLec4KYdfzB4UPYngza+Gr4nTXNmKxqsQ+dYbW5wkQyXRjSTxMGfWq6ENljdckoCYF1Qp3v9/T9z1XV1ci9DNNM9xeK/Su6+6Mt9WWQwhBTK68yD0P00jjWoJPIntbRtFMbZkV61WjRPrWKGDsyTnNrnuniReoORnqp0C7klHOt6Gg1vW9Avo3Bev769syi7+LkPpvc70pWH9bkH/d395+nfRBX/M4r/u8v+0c+KZK/duO85sq89905dd8nYbzO8H85P2Yg37OfG0m9C2Cen0sEdqImJPuvUIMLozWQsCyDqMFck8xFvvFUtKjEKW2TM4WpYrRT0pEIiqJ13cmE6OEoDRH93R6KFK1cxrQKa8v3/ld1oVgV/9O+Ry5e9e7S6rzEDJDH2i7DmsaFm1Ht2i4vHhA2zkOww3jdGC3vwENu8M1gQlcQjctlgXjFOl9QHVnNE2LbS3GWYYYCRlQlqwMKVsOh4Fnz55ztuh4erFhtRzZBC/qcRqSFifKWD5KlRMJmcs3UHyyhaiIKtbK5a2vbQupxiOTnxjHib4/oLSm1ZqcIzlLQLdaAnrMiRQDOYZi85XFqU2DVVmOJ0VQ4omtUhKv9SwiOEkyM6KRpK9xQpispEilRMBlGiVpyOlu9Q1H85UKuVfEpgarKnNavx//kxaFKvedgGEcsTbOpifGmK/1trXWRR9elSQzlsRAjjlEOVejSneEaMQq2UBBP3I62qfWa1FHMSpS5fOp1W0lstVgWWNVhexrwuG9p+/7OYBba+cAfjqjXhOF09bDPMIHpBDICYyR2fEkF155LeVxkiGXpCM6h5/E1jZFab0YY0Skpszs10SrJibSAvgtVOh3LtXvCIm/rpf+Ovjv/u/+PlafryM/fFuQv//vP6zvvua2cdm4346C8s3rdZ9IDpGER1upVnTB360VA4f1cimMWSMe1yEELApr6gMKsU5lhXalUo+6OMCFYks6le+xyFQWtq5g/hxbBhVyP3kXahWfajV1RBHq+1T/XR1S08nf7r56hVGO1ixYt2sWyyVnmyWLRcPCLrAZtj5w2O/42c/+mqwy7cayXK/YTJco56Bp+NXnz/j1Vy84e/Q+3eaSkB2bzYqFOaP3iV/97Nf0Y2AI4gbXNktQim1/YDOtGKInkMlGCbZujnlZSmUuv7gYalPeEp8IORJ8ZO8FOu23O/wwcP38OeP+wPWz52IiMnq6rmW1WaPI+KEXM5DWilXrNIixSTEOSRrGOGCMyMXGHPG+ZxhHbrc74RK0HSiDU4bJJ2KS3v6kDTmlUrlJv7fvD5AiFxcX+GlkGES0pQb12ivWWktQyhnr3DFBKcEKBArPRUq3Vttd19F13TyaVoVlZCSuYbXcAMeqOMbI2dkZ6/Wavu/vEMyMkTe/7/uiqsadYzxKIitikbyt68i5knNaSHlxZtLXkbnTVkPdF+uxbzYbmqaZCX2VGPjo0SMWi8U8i16FdurjpZR49uwZKUk1HlNkt98jKm5Hz/vaDgkhEIPHD3umsWd7u2XsDzikPRZjmFsOpkw6xCyfR20J5CzoG/cmn75pfaeAflqhv6lSPA3Mb4Lo7//t/vqmbORNlerb3Pe7rSOr9JvWD93D/rYe8zdV6t8U1H+I43tdwvU6vsTp8b3pPm9a34QA/RCvocREZvT4zh+YIeVTGL6GsePz5zvR684xyy/ulK5q/irCGEmMcWrBUlmv1po7JKac82yKJLKR5uR9kcpMZYhZ4GCjDTmrYlpxUmGnfLTQzIJDpHz0I1D1McuGQq4VqgT/rArRrijUfe1jOKnaBbw4KuYZbWhsS9u0LNqORdPRNQ6rDLqgAzFGdvsdich2eytIQ2fBWrJzPHv+jF//+jMuJlieD7SbR2i3JOssTlv7nv3gOUyGxjnc2hByZiQKtJulyi1moMTqKJfz7DiRCuyey+tLKs86+CEGmT8fB8ah5+bmhn63Z7fbEX1ABVHzqp8XMYBVaIyQ1UIgJQ9ZKtIEqKRF59a0EANhHAjjgB8O5OCFUW8dxoirpEGRcxTOYgxFOtzK+RETWkPjGkRtcJAqslTFtUJVJ/92ZWb7NIDWr6pVDsf5aKUUkxeL5bFYwNYRstProAbnpmnoFt38fHXpEvBiOe6ck5wjpUI+7V1Xh8vTL7n6jqNl9RjvB/N6HR1PUbmvtXZGJGrV3zQN6/WaxWLBcrlkv98zDMMc0Nu2nefSU0osl8vZ7joX7/N6vdb3JJc9RBKchA8eHzzOFsTnNTFS9oZ0vA6PGwpvC7p/5wp9hmROgnr9EGu/ohIITskV9fZzJsPd4H/6oVfYoT7uN63fVmX6bUHnbWDp77pe97jf9vPb/u27PvfbBM/XkR5P//Ym/sQ3Pc/p+/hNj/+9V3kYXUw2akV+5/EViInTUbM7F9g6A1mkwGZYrfqgyz2OcLRGFc90MxOhklezXjUJmqLxXTXETxW3BOdVxMkz+ICxDdoeRSbkmNTxmGfY0oCWUH0kOYnzmPcTMSTGfpBRpLbBWMNq2ZGTBNQQAtMgtp5Gm7nXeXZ2xmK1FLJWeX2JY/Uz+YA2lrYTDfOU4Gy5pjlbcn7esVq1IuRiFNWUqnUdy2bFql1zGPd89eVzuu2O7TCinCU3DT//+Sf85V//HPWzX4Nd4FYPMc2K5fm7oBsOg8LHzDhkhmnidrfDbToWjzacb5ZknuBTYPCeMHh0SrQxYYGVMzitiEbTGI3WDSFMjENPYw2NszijaboWaw1jf+Bf/fN/wYsvv8JlhUqZOEys+iXr1Zp22bHcrCBk8AkVBlQcONxcMw4HchhRZC7ONzKSeAvjOPDFF5+xXK547713efb8BT/7m39Pu1zRdUs+/PiPefjoMcpI1Z61QymDbReknDl0LSkFUvacrZa88+QxMcroVHXFjBwh9pwzizKzvVyKOE3tuS8WC8ZppB+GI8FsrAx9VVClI1ErxsTQix78qtuwLn7epsz7L1ereT4cjqNfy3Jtm5PRrVSmAtq2pW1berkCOYwD4zCyXMrY3GKxIKZISKXdpPI85lZXJb/dD/DjKGYur169wjnHw4cPWa/XnJ+fi63qfn+HBKe1Zr/f34HxYxQSpC5aylpJknB7eyt7Q86sVyvW6yWDBWePMa9pGnGuK7yBqoM/jiMhaUJSdIsOt1hK1R7kujdvyXR/e/vUewHrNBCfZnent3/TJlzHF+Yq5DVB/XXP+X3W97lvfkM29NsKpt/2WN8nqH/nalapuSL9tqD7tuvb+uXf9LivO4bXPdZ3fd/n9natRu49zp0qfO4ilp/r3+ZzNp9A2UfFuZRPpttz/To+j/TuirSrEfGMat5xp1oqCUE9ppQT+UTYQsQmpCInZ7JV0kPPYuOZsypVSL2+ar88y0YKOGeLcI0jZ4P3LcFrcgxzfzFGTQiq2HeqGcVQWheTk/K6U0bpIg2qDMpqOteyaDoWXUPX2Kp4SkjC/KUgCo1rGfzEOHqSUiS7RzcO1Ub2u579vicOmaxH7KAwzcDoHdp2RL0kJk2eMnEciYcDpjNYrckxMoziotVZRws4BU7pwlIWqdZIIihDKNU8qlRMOWG1xmhIiMnIoe/Z7Q+YmFApo0LCaC0wbsEC2taRY8PhsGPoD9y8ekF/2GOJGA0O8bnXRIFfyTRGsXAWpzLRj0wH6dMO+y3jcsli3WCNI+QMJKn+y/kl+uB2tlX13jMxzedUDMcZbqB8RkeZ10qgs9bO5i7lhBVCo7LzeVmLsjpqBtNcnRrMSdEmEwUzzpWPI3FzRXsyDlbP09eikEqqepWk2j0aqMgYW30dp4TrCv/Psq0loanBXik1B/zKqq9tAzgy9qu1ag3y9T0/vZ7TXF0f/djl2tZlHK3e5S4acloMyDFWwRpblB45Imhvsb5TQD99s97U874Ps+uTDekP69vXbwtx+MO6u4Qha4ipEMdmeK9AXql21WVJ4K5cddEGd04uWGcLM7gg7ckXk4kYBLL1Mr6kVWLRarpuhTECPza2EUJcEVpxxjJf9ChUOgL2h2HgsN/jmrYIfMh3VYr2lOVr9BnvI/vDUBjGI/3hQN8fBOXVmsePHgikWFC0thEU4b13n+Knie3tLa48R20/7Q4HkT+NYihhmxaUFinMEIl5lLn5tmG1XPHg4hyrNE4pIflpGMaEj4kxjcQcGKMneFifPcRj6IeR7WGgf77FLha06zXX1wPTCNkAOhPDAaU8w01AmQa1uECZBmMWQqJqDZcPL/gHP/ljgh/55D/8DdtnzzhfLvmTH33Eg/Nzzh5c0FpLPOwhRWJIqBQZyTgrKnFjsdNcLTqsc3zxxRc8+/JLrm9u2O63fPqzTyBm3nv0mGkYWC8XTNPAzfaKi/M1Dx6ec/XiBTfXr/jis0/Z397wwXuPWS06fp0mcorEMPL48SP+i//ivyijVZpps2D/6IyXr265/vIF26trbLPgP/5P/jMePnrKGDIhZvopkJKIyyyXC95553EhsB3361oRb29vGMcJXxK1KtoCx75tTImYE9fX11xdXWGcxVjLer2maY5+3acIrIKZLX59fT1D1Mvlkq7rpCWQ7saMymyfponbmxuMMSyXS9qmZblYzEzvColXC9TdbsdutytyqRI0XSN8itPgfaoJXw1j9vv9TIabpmkW3al9+0qmq1wCOFb5V1dXTNM0o11dsVGVBOXoviYs1pJgGSE/VoZ/TGJMFGNEzIDMPP/fNG0RPZLrPVtH1nZG1mKMpWH07et7BfT7X/d7MKeb4P3HeNNjnt7+73sC8F2QgLdNAP7w3t5dOVdTjColWZPVQsJJIBU4c3AF5gtYK2bDlJxz0WORcbFq4iECMhptdRmJSljLXJ1rXT+X+lV6+6VYOeWqAcdjjIlAJBRNa5Up7LrS/03Sq5cqQZOzxTqL9QajqqSsPVERg2rpmmJk6Hu++PwzrDG0XTtXJL70Vo1tZnvXuR+ooG1l3EfGflyRxVTYOvKWC/p12l5Dg7asVucMPtHvbvBh5HY3Yb2miYZxzCganF2gbYsyLSjDFDI5RnSYyly4kecxmWVrudysuLmWzXs0liFnDttbOq0IqwU2JaZhQOeEdUJ88tOIxpGdntGVGiz6vhdI1k+EEAWRIIvQi1JzoNjeXJPCQPA9t9ev2N3eMOy3+KmntYZV1+C0I+dIf0gsW8dmWTb1rFh3DWerJbfXt/ixx4eEHidur69xtiFgiAn2vSi0td1SeBGx9NjVXTvQGCNDPzCMA6EEpVCsWLXWqEq6ihEV1MyyViGAPmqp1wtAQWkl6RnHiqW3XgNp7Z2nEtBPq1p5qmMAnV3Git98Tnlu89Q+fx2tCyHMpL8KsZ+2duu1fdquzTnPCURlzNfrvt73dfGsVur1faxJzJ2LkhNDG2tEsjVV9PnYQ5fHFkRIwWyNfErg05liZ6xQ2sxInMj1/sA99HpSnzr3HGEPWbPYwEmAfhMJ6n5/9HW3eV1P+e/z+sN78cMsucAn0pSRMaM8E0lrQBcxEQl+us5hF2jdFY1pSuAOfirXh5eAnCisXdmIFt2S1mna1uCnA96LIYOQg4SARY5CyiokGCHA5YqQI25bMvntg4cQGEeBDVM5Lq2tBHatUar6KrsyCmfo2oYYPCkGgdyzzD+TM9EfX8svfvEJ/81/8/8h5zyTh2KMfPjhj3j89Ck//Qd/zoPHT/BRxFS896A1T548oe06zi/OyCkzeY+x4mNeVc8UEaWzkOKyYsgZ69a8+95P0O1LXg2f0G+v+fKrF2TtwQ1MEZx9wMX5QxarNa5dkNE8e/EC7wMmjqgcMASU0WjneLJ2fPT4Ab/c33K12xGAMXi++jSyf7FgnROrrmPc3uKMZvnkMTlHdv2e0LUYNhAj1miiDwyT5+b6hlcvX9EfDoTgOTs7w2rD2dk5rbMM48hue8vLZ1/xPE7EMJLiRIqe1sC6tfz4w3d57+lj3nn8AEXmyy8+Zb1e8nDV4FyDdQ1ORVTyvHr2jHF3izItyjT86md/w4tnz+hWF2RluN0NdMslf/KTP8Vqze52K9BvPsq2Tl7IWK9evRJmuQLr3Gyr6sp8utYaXQRQZljae3w8sUIt2eapVGl1i5uC53A4EFuB0KtDma9yqQWGt8VbvqrJHUqlbKylaUWgZfAilVpbVbWn/vLlS7z3bLdbtNYsFguctSyXyzuxJud8JPIVxvqpOcxpy7c6stV94VRYp8a6qjrXdd3X5LVrgm+dxTXNsULXipyL+t08Ry8xlJJQVzSjaQpKkEGlLDP+TvYYpeX8q1a937a+MynudRW6vLA3V+hvqgrfFNS/bxX6t2X9kD3/79s3ftN7//e9Uq/vnOic5xk60/r4HSRTluq8VuLyb0UWqDRloYSVTadm3ceenhIoXSmpiudrQ3rftVKt/fagEgolNhMZQHrfc2GTkQ3We6hz8vW7rgda+pxWArpSlbQnanJaa7SzKFtcopAKN+cEqmw4wTONAzfX18Qk6mUVxmyaBh8Dj5++Q9N1dKs1rnEiqlE32AIbZ3VM+kMoe0WpXIwtsrBZkSZFVobV2SWbAOvNLWM0rDY9UwwMIZIxQCJGRQiZpimuYChizqgk0qcpeoE6s2Pabdm+fIE/7DEpkceRkBLJOZLSHG6uYehoAKMVcRqPjmlaE6epMNYT4zQRJs9+t6PfH5jGieBF6CWnzGG/Z0CxTYHge6zRjD4yDgOaiFZJUJQE169eYolYPFYrpuHAoDNXL17QdR2L1Zpp6MkhYLVi0TZEBAG4vbnh0E88eGIxrp3RkWHoyWQJDEpRxUKVEgJmJtMVadeU86xqNou11L1by3f5TJfocUR7j6lQe5kLV1pRp9TrtEQ1bqnkutNW65E3IkdWe+i2BOMKPbsTcZfXxZHq675er2enuMViQdO0pd0lr+n0MZpiarRer2fS9jRN7Ha7O/3zep/T+9bXcGowU8l1c++fe8epC6E2M/sspJSKCmBFAtQJD6Yia3lOeslJzH+oqo9vLwf+vQP6aa+ivpj7PfNvqtDfZv1dC+S/6fpNEpnfDM34e/Y+o7C2jGCJjhoVrp7FV1J5V07U1SrRLfiJFDNGM+t8a9RMNNMIEcYajTUaGSEvDe5yiwpxVyvGXBIDCqM+n/Qcs1zjMzmncGuKuxqoEtCzNqCPMp9i4gFKixJd4xyd67DGzO5uMXrxYi8qdmGaGA4HXr18fsdbG2C727L4/DM25xeknPnxT37Karlisd6gjaVbyvx3OkFXQ/D0PhbgQKHaDmus9PtTZoojSTkePf0Q3V1wNWrs6oaBJVe3t4wvX0IOkD3jkElpZNGsMErhEkUEpvSjx5FkDHQN269+za/+/RLvA22K5P2eCcBaVM68/OwzDm3LR++9R6ssfreThGaaCDkxWUOOkRQTN1dX7G63vPjqGdcvX3HY7xmHER0hpsCzL5/hx4GbVy85P1vy4XuPCMOBqT/QNQbrDCpHog/8h3//V/zaWZ6/+5BF27BaNPRdx8+iZ7Ve8+jJE4ZxYtqPtFrx4GxD72EMmS8//4wpZJRxLDfntKtLtNZcXV+z2Ww4Pz/HWo21hpAiIcZZWtVoLWI4VcM9i7iLLQFwHpfUmtVqTdN18/hW17aYQpaLKWEaR1aSTNUxLeccl5eXNK6hLf12OJp6zZaq5eSoFXStep1ztCURqEE2l9vWva1aoi4Wcp86U75eL++owp0SaJfL5TyOVhOPw+HAdrtluVzORMBTgZn7HLD1ej0/VlVlTPU5asupLC0VgBjNxEiIgRhDUUo8otfmBOWgtCxCkOTX2AgmUVk8r+OrvWn9xhV6XacVev39/e9vWq9lNfKbBqnf7/q+x/22Qf3bfv9tvIQ79/97VKyrEr5D9OQIStX3qWTMVHnJck4K3Rly0Y/LiJJVtSUF6d0CKcdK9yYnRYpSZwelIWvIEVUY3alU99XzWIgvuQRWSqZeq6hCtsuFc182kjo2p4xU5BSFLSHkFBZ8Kd7r/LvSwmbORtTFUpiYouf5sy9FEjRF9vsdl+fnM/QqdpsZ50rPvYzAdW3LYtESspYNPqQyjiaJTeMMOoFOhReAvI6YMr2PjDGyHz29T+h2SbNWnD16ilqsCW7B6vaW9uyCq6trbm5uiGPPcBjYG8fUOJL36BhFvjZlrHQbaLXCTJ7h6prgAz4ERh8gJoZnz7FKsV60NNbyi9WK1jnOz1ZCAmwbce5aLRiLicd+u2c4HPj1L37F7fUNYZhIPtLvDuSYsBFiCGgUYfJCoip93hgjPieMlcQqp0QInmdffYXViq4xLBcdpMDDRw959Pghh/2eL798zn5/KEklBXruUCbx4sVL7O2e1aUvtquaBw8uWSykQl4sWqkOi02qUopVcVWr5K4phrkPXvfsEAIpZLQ1s1lL0zRiSlNkVlVOWCNQ8DiKOU2F1JfLJdbIxAalgj/tR6cyriXjdBptzBzE61dVtKse6inGmXVvC0lvsewkSbAObY4I0nyNK3XHn73C86fx5OzsbCYGnk6XVILcrN3O0UO+OrbVyZHTvbW2pHNBSFJOZYpD9gxJUiw6hzus/5kTE4JouE+i3Z91UfvLtQj4LQX00wOpL+T0jbzfy6i3v7/ehvj1h2D+9sH87+p79btfsjt6PwmkXIhpxpR5cF3hdV0uvBMN9UJYU0oLZE+ls0nQD1FGlmbnsxxFISxlkjWkZOgWHU3bHDfcUAg6yOZ19HvOd77XgF6xf6U1uoy6VUhUWTMH+xpBT+lndbNsGodWoicRpp5xSPzql79kHAQu3m5vefr48UwCC1GCoi4bqLMGZw2rRcd6uWSIEFKiHzyppEyN0yxaA0mRQoH3cyYg79N+HOl94LYfGWPCLDZ0dsFDGlZTYP3kfW5ub7l49ZJf/vKXTOlTbm5uGa6uUBlc16CTR5FoEClcdMZpWFqDm0b6Z88LwcsTxpE4eZ5//jnDfs+qa9FKMe73NNby/vvvsF6vefLkSVF5c2y3W25ubgRinwK7m1vC5Hl88RCrLTdX1+SYWLtOqk5t8NPE8+dbjBJzmRgiKUcaJSp25EwMgV9/9YwYJiyRzXqFSgFF5o//+Mfsbm/41S9/AbpBqWb+FJfLJTZkPv38S0LKXDwZySi2uwNP33nC5eUFq9WK8/PNMXiVivH87Jy2E0cyHwIvr15JkCzBOcY4y9mu1utZz1zOTdnDQ0kQbNEi2e12UkWnozhLfd7aszYlUa5s+1mhzYgI0PnmbI4X3nv8NM0Ve0Wk+t2OEAJnZ2c451ivV5Az4yDJZiwmNaerSrxWmLzC9PUaePDgwT0d9SMHrN63Jhnr9foO1D5Ok3BlCuQu9sfHgJ5RpCi/q8dlrSU7iwrxzl6dUpqRk2mSgJ7thFXlWE0ql/zb7e9vHdArXPCmqvk0CL+JDX96u/v3e9t/v+36ffeIf99B/U2Vel133p+3TwD/N7PUXPqUF59F6CWVi7SG81qVV9Y7VKcwO7Ogc71wS48xp8JkNdJDd0UBzjnxTzbGQRK/46zqxlAv3FLOFpU2+dwkm2iLc1WtyE0J6Lqwg1WpzGfdccox58w09EzjyMuXL7h6BZvVksY52uKzbo1lSJl9v4Oc+dGHH8ws5JevXvLs+XMeP32HiwcP+ZM//hM+/OhjYRlnmKaRmAS5MAUhMKZKwipQZlYf60NgSpn94BlCZEowJThETx8CB+/xKRI10Fia1ZLFes3qfIPfX4JWXD58QNc12BwgRsJ+CylikHn689UGlBG1tVj00LMM/vi2xaP44OlTGmu5uboipQDDyG6c2L58xXqz5tHjR4zTiPIRfxgY+oE0eQiJYX/AaoPJQl5USTgXRtvSN52wzrHoLH444KfA4dAzqkhqDc6IcUnbbPj4g3d49Ogh//h/949xznE4HBj6QUxUUiJkj8eRlaVpWrQzaHtL9pFh8Chj6JZLQkj8zd/8B5bLBefnm5lB3TQNtqivCddBiSiLD8JOT6Jt4L1nGEf2h70owlEY4MbIbcrZVKto770IqaSM1Y6cj6zzijjFGHFGks3dbof3nv1+D0hPO6fMwRzm+4QQmMZxJsHVwFrFXuZeu3MoyqhdDPgwzXGp3mcYhll7vc6c1/G6EILwPUobIOc8Jw/e+xmZqgH+1Fq2yuTmwk1AFaOiFMkecdp7zaj2aUv6dG+u7Q+Jm0fyOSUB0gVhMeYH9kOvAvzfBIOf/v60en9TD+DbHufvatX5m7YKflPY/XW3+SbI/fec+/ze1mlQF2hLxFjmfnq93b37GaPF57kyV1MuTPUqLFGuk1wFP7Qojs39umLNkhJJSSCviitHlytxbFIqkwrLpikbnTIFojR3A3ptE1R3ppTLv3Ii+BHvRUVtGgfio4esl0seP30i/cOisX3Y7+m6hvfefQcoREGjuL655unTp3z4o4/4+OOPeff9D0EZYs5MkycBTVdQDkEmZzU5hSKmTIgwTJE+BPrRM8SEzxmfs/zOe4bgCTkTFGAtrutoVwuW6zXD+RlJw/nlBauupckiq7r1EzkGGmDRNFwu1oQQGaYJHRMmFYQDyE1LNpaPnr7Domt54RxDf+DFi+cc+gMvXr3i8uED2tIDVkAYRob9AZKMCE79QERjEXEWlSgcChmt8iisEQZz9FLNDeNAjhM6NXTO8OB8yeX5hr/48z/nvffe4z/7z/8p11dX/OW/+7cygx0iY4iMPqOaFVgJ6EY5jHXkAMPkcU6xWW8IMfKLX/yCxaJls1nP5LQ6D75YLsg503QtmVyU344B5HA4cOgPXN/ckHJCGU23WNA0zazIVvvedaytVuitEwh8GIav8auSTegS0Pu+Z7fbcUpW6/vj/hTKaFmFvuu4WN/3jOMoc+05F20E4ZSEGJim4Wv3GcdRWP2l8q/Q++FwQCn1NYJbDfR1vO00oFd2fEUZ/DSRlSSwBXsi1766Yaasnm4gdwI6d7lombofn7Tf6nRASihlpX32FuutA/ppn+MUZn/dOmVQ1p/hWL3/bxlu/03X39fX/btcSim6tkXrlqqTnmLpWVf54sJy11qqdaOq5jXCBE9pVk5rmlIBtc3cE8sgFqlFdCJX0o4ypHwk1oiJSkkKcpZAr0QeFaRQN6USsNYVuN/MYhbqJOOPQUhLg5d522EaSTGKSlgI5Bg59AcOux3JexZdy2rV4azl3ffeYdE17LbXxBC4ublmsVhycXHOX/z5n/MP/uzPuHz4iM3ZOYuuZRp7tOtAabquJWVFUpoEjBFCSExjgJDJQXrwKWdup4khBPYhMKXEmAJ77/n1l19w2/d8cXUlo1dasz/subm9ZXe75TDsMI1ic77i/OKMddfRxkQcJw7PXpKC9NCN16ghk8aJabfl4YNLHj55h363w48DyyfvoJXm1YvnHELk8nxDsIbh9oZOa84WS5quxcTIer1hvTnDYWiUxVbcJmS00jw+f4BRmmErY2xDfyChSGimENn1A08eP+by4o9579EFZ+slD886Fq3j8cMzFl3D44s11hhePnvGNHkePXrCxYMn/Omf/yNeXu+4ujnwcjuw7Sde7TyDH7h48JBFSNzuPSnDdnfAGkXrbBGRuWUqjHPvZZxMGc3i5UvOLy+w1hKSyMKe+qJrLVV9RiDr2soRVb9jQPchEKpDW1FFq1Xu/TVrLWo1i6nAsSLv49FAJiW5XkKB5qcyQ19Z8yAz4bvdDoWafQ4k2OXZPrUG5/ocOec5kFcovWrG19uM43hndv8UZTgcDvK+lNtudzu00SKfa2RvmJFoLQWCVkos/JTAZTNicaKcV5MQV5AUHxUhaVKd7y9QvnZvXyB+54D+TdXnm2D2evA1mL8JjvhaMFfqa9XR35X1Q1bo3/T7b/osXne733cr4ruseqQKQH0t7/3G9Q0po/Q7jcFaTYxBiLcxlgBb+nFZLspsBDI2xhQimioJgPDclDbzuI0tT5qK/WZMoSLeJ8SZRFaRmIXhXm+bZhdTNScO0gqv10QuJDg9f9V+uiQlMp8eYqTvD/jgOfQ9MQSmcaKxFmcM0yRwZPITQ+8Y+h69XHBxfk5OsVQkEgSapqHtOi4vL7l8+Ahb4VtrCd5jtEOZYniRpQovk174KdIfPDkksk91AIdhCvQxMKbAlDOexOgnXt5ccbPf8dXLlyQFyhm22y1XV1fiaOY9ndE0rqHrWhZdRxshotFZy+eVNTpp8Jk8BlI/stCWx2fnbFNmVIrHlw9x1vL8V58y9Ac+ePyI7ByvXEtyDbZtBN2IidY6LtZn9LsDfphwSsR0wugxyvDg4hKjNDdRMQ49Q1/hYyV8iimw3pzx4Ycf8mc/+THvPH7Io/MFy87x+PEFjVUwDfSHPV989muUUmw2ZyxWG9YXD/ji2SuevbxGf/ESdb3j6vCSEAPL1ZomwX68wYfINE7QGJZdR4yBaRzma6VWn2hNu9+TFbRdR9OKyt+pqpoxhe2u9J1KO8aqmX5CcMupBDnQucjLFiLZ/f08U/rTthDrOE5yhFwhZTN/zznL/HpJNmaGfHk94zjKbQvpU2tVRr7S3A441UoB5sq/7n+1l14D9zAMX7NercI2VZCm3m8cR1GM6xZkybjlOufYJlNaCeeGypMtxL0S0Os2rJQkOs45bMjYkPF1jC2LcuUJJeZb19v7oRstDkFaz9Dem9ZpQBc0saguvUWFjqriGuXHtz3Arz3M9x+X+8P627OEYP7dEjs1///0XrWrLL/76ouv2O9vi6exEFNqP0trYXA717BaLenajuWqldGvxtG4Rnrhuvgxl8dMs/SkCEGI9WM5mqpaxXFETSEjbhmwGjKGskfNlbcxx83RWkksRCwkcLu9YfKe7X43V2IhBsZpEg/qVPzFci565JrGWs4uHnDz6gX7/Z5//7/+ezarFR//6AOaxvHBBx+w2255+eI5bbfknfc+ZH12ztnFBT5J0L7eHxinHreMaGPRriGmzM1uT4iRcZrwU6Df9TS6pbULjLEobdmPI0PwbOPEmCPbFLje7/jFz3/J9X7Ls9trtLN06xV9f2AcDoRxIk6eFDMTimtliN2Cx4s1OiYW1kKGlbFYpdAxsbSO7vwCv9vzyV//Ncl7UZWbPG3T8sE772CN4aOPf4Qxhg/e/4BhHHh1e8P1zQ2ff/Ul+9stWmmmfkBnJNlTiqdPntI1LVYZUpCA4UPg1dVLUvYk41EqolRgtV7x0R/9EX/6D/8R77//Dk4FjMrY1gIJbE/TrnhnuYGUUDGCEg+4s/NzbLdicf6IDwbP5dOX3OwOfPH8hn0/MYwBHyIxRZwzrFct+/2O3fZAdfCTUS7F7e2u+AIYNmdnvPeeeMu3rsNYi2scMSUeR2HOW2fRRkY7x3EkpkTXLdDa4H2gcQ2X55fymQxjkSLuMNoIR6Ta9Ja1Wok86zSMxz5xrmOfR9U05xzD0DMMA66V3s3lw0vheAwDqbicUVJEawxN24hK3+EwJwOVlV9RrAq5V8Gb/W43m9FM0ySiOKWKrqY0dSKgohjVRvVwOOCsZbXeoHSWeFiuaZnPFBve0rxDpSjnXwhgmhLfsuxr1mKahma5pMHimUghz9OyEsPy12H8N6y3l34tRJuvGUW/caeVA8lZoMeaod8lbr2mwryfjtwt075xYz+SgE5/d/+NeNvQcGSKzY/wuvdU3fk2//L7phKn/DR157cn1fVJgPt60qLufb/3DtT3Np/8/j4pTqm7jfXvS5p7TVV956EKHHX3JeT5T0ihfBqH7z/8nZXrHlJuX8+tlGp1cXyY7c0tz198JeVkTT4VuKZBK0W/kwo1x4jeKMzmTDadMipGpmxeItlYIbLjay7T7Sf9M0EGi31qHYcDgdHrmFzmhDwj/foq+CGbkiFnT4qJoR8ZxoGb61umaWK/3x9tHet1VFC/UAK62zisa0pFH7i9vSXFgFYf0jjHarUihCDwq2tZLNe0ixW2XRJ8IoXEGA4cpojVHm0yOkKIkdvtDh+CSIxOnmE/smxWqNZgDBijSEHaGzEKIasfBg77A/vtjv1+z2G3x7YN2tpSmYfy5dExo7Ji6gfGlMlNh84ZV4iCnbPoDDpHCRKNYxpHDv0gfIacGfsBUma9XEmlv1jgrGOxWHAYBqYYild3JkxeXOl8QGXm6YW2bVh0CxlfK4IFmYQPE5kAKqBUBCLGGgkQiwXNYokloEkoK1oEuIyxiWXbCVHST9Ku8IGmNWgHybQ0i0gfoF0sOQwRrXtGH/E+MHqPKaOESh3d73JK5NJ7FRMVxXAYadyIohquyDnVNIX4pTpBgLSWvV5JBatixBorsLlxZJNZLpekKKI51tgCjRtM0T9AFaEUjkVc4xwpprm/bdVRxMU6S9u0hOBRRhVxJzUT2HIqxiwlKdbIiJ0trYYysgKAttUYpSTGRbGwitNs73G8TuVgq2nNfWtZow1JF5Gg41ZFbSyI0I6QP60R4SpVgrEqxQKqej5kUBplDMpY+bIJZVMhzJ5Mj+Vy/7dYbx3QD/2eFBPGaIKGwQ9oq4ClzPSO6RhKVEYr8DGKWYKIWwmJQCsh4CiN0kYK/qp0NX8d37AUywZP2ZC1+VoikAvcUdnGtW9zP5irez98EyxbZ3irSUfOR1Wx+VaqHFfZNVU9fn2/Onz7dVqNzq/hJEfJ+Zgu5NM/KOYgcP+1vOk13llf41zcTyd+mHX/tCw8suPPigLv5XopnLze4t5dsv+2cVhjZkJKf+iJxZbUGcf52QXBB/b7Lc45louudDgzf/mv/pJ/8c/+Jy7O1yzalgcPH7Ber/mzf/Bn3N7e8l//1/9vUk6cbc74T//Jf8p/9X/7r5imkfEw8Mtf/ornz57zZ3/+Zzx+/IhF16G09E1zzmAMSsvcaWXmVghztzvQ9z2NbaW6aFqMNVhjjwkOp+OgStj3wND3Uon3wli/vr0V8s9hIMaEpcFZxbIrwjJGz4iX7Vps2xB8zz5MrM7PWW9W2ELK+8UnnyDnuWK5XPP+h3/E+YPHeFr61JCDY+8zQ8js9BmD9ez3Az707LZfiCnJzStSDKgkYzeNdugu09KSNSSd2GzWXLQNqxjYDQP/5i//e15cX7PUC5KDgx7JQZF3gTR4ch/QIaEitGgapQj7HcPQk9oOqzVLJ3Kmj1YrUvAcdttSHSlW6yUX9my2vFVKkZUiAL0P/OLTXwusGry821qjtOXi4gJQhElsSGPhViSl2G5vBaL15fNuFHbVcPH4kpRHIj2tM3StZRgO/M1/+Gu++vILlosFf/HTn/LwwQPef/cd2q6FlUjMsrsBnWG5xOREV6rYFCJX26/YbW955/EF7737hA/ff5fJR253I7v9gU9++Uuubq759LNP8SHQtSIi1FjHcnVG1y25fPCIxnV8+tmXvHi+44P3FUYp0a43E4f9JBakixZUJKuMa51U6sLiQKMxaBatiLSoJEIxOSm0M7RNx2Hf8+r2msVSCJxijuJrLGO1Ws5z5lIxt2IGtN0x+olD36M0dIuOfpDzfZgGYg4Mk1TR2pqyPwu6dZhGfAzEcp6vrFTijWuKkE7i8vwC55z0yX2B8q1lUWRja2/dGFM08TPn6015TxbSciuBf71YCwdGib3rMI1UfH3Y7YjB8+D8nGXToHPEKuisxaRMW+yPYwbXLunOLtHdkiHDpBTBGmLMpCxCVU5rLK/Znt+w3jqgx0JAoMAFp/Z1OYuQRq0c5wBQspIjOU6hsp6h+LrqRXYnmJe97Gt5yVx53INTS1VWkY/Xwe21Yrr78xvC1dzH5xtK9PJqT5IRebz7x/cd151+d5VCOVayp8H99MXk/A2v52vP8b3+9IOunL9ewc+qbXd+d/xbljveOTfync+oSC6WVKDevC4/ecI0cn11zcsXL9EpElcLNqs1uUt0bcfUCJnM+0CvD4TJY41hP07cXN3w1Rdf8tlnn/HkyROB5q3DOX1sLRVWcAY5JwopTq4P+aAkay8InSq+0Pr4ucfyPSXmmfXK3p3GiWny0mOMCVXY1tqUSqdxaFWUqZQkiaZt0K0YgqSccAp0toRxjw+R3W53tHM1DteuWK43aNeQ0PQhM0QYoyIoRzKKMY6MPrHtR6ZpZJg8pIBVUfqxRs+thgqrNk4QAq8tU0jEKRKmQGtbost0tiXmRAwZFUFH8VUnyj6TcgZXKqccMSi6xmGBxmpCFQAqyYkq1WGmsNxLL9SEgMmJNBUv9yBqaqInrlku12V8aZqrtzqznBDzkCl6yOCsQ1mDay0xRVTSLFcLLs5WGKvp+wE/TNway5PLh+QIm+WaRUhy35TQEVSWwCjZuRKzDlP9BJBJidbhmpaUYL3J7PYH+n6HUpHPPk9oJTritVhtnEDh52cXdN2SL758IQhOghgFAtdG4ZKDDE3bUObwynlalmLml0ifGYzOc59ZBirUDFHH6Ob+vUDXIqrUde0JL+RYBCWOrmxyHiumaWSaPJ3vBClI4vKn1Yxnk1IZdwuecRpn2LxW/DFFctZY5zDWFmIqc1++zt+HEO7MpOd8NIVpizlNiqKqt1wshaviR1FbTFG2fyPjayEGci7iM0gwNlqT9ZH7UotTbR256Lin+cwte/4JqviDV+gZJCNRzD3uim6efObzH1Sez4njB3j/DiePfX+9iUf/prnq39b6u0gm+7u01L0kTitzAsmXE+YkeKuTn4UEFjBKUJJlGc2ZxgmtFD72oGCzackZMR755Of84uc/56vPP4eYZBPFsFys2KzPeHT5iMcPH/P/+L//PxmGnu12xx99/BFpCvzsb/4D/+yf/3N+9vOf8dWXXzFNEx99/DH/9J/+73n46BHr9ZoYI1fX17OTm49BLCvLMbZty6LtyoVUNOUL6qKRPjkoopZe4DgOEsiniWEOMIEYE842GO1YtLXHXsfGnAjPGCu6OAomIlNOtBcNWmf8/hY/9Dz76nOmoWfdOFaLJR999BHdYslyc0mzXLI63/BiO/HsxQ3ZtGTTkIxDaUegZ0qGiEXZlssHj7FGsWo1XdNw1q1IoyINivPzCzabM4LWJBRNiLSh5Xx9TsyatUr0fkKbhn1/4NXNFWAxtmUKkcknttdXhGHg8qMPOF8s6Kxh6SxP3n2KihG/uyVmj1FVRjMy9AdiygyDvI8KqcLPNme4xtG17THgJ2HHL5ZLnr7zHp9++iueP//FjJY8ePCA1WqF0ZqUM/v+ADnTLloMGt0YctSkqHjvg3f5j/7hnzMeRvzo8aNnnAb+5b/+S7qm5Ve//oLNZsOPPniPrm04WzW4xrLMLSkHYvTSztGKi4sNbdfQDxPTYWK9uaRpF6wuH5Ny5k/+6AN+9otPuN6+4PrmluevrkAFUp6wTrNYtFxcnrFabXjy9CHDOIFKDMOBL778HOMMFw/OSXnNct1IQDVK+sBaPO5zSly9eoUPgetbYZmfby4EFcygsqY3AznJPLo1Elr2+z23t7d4L6S0tm1o26aw0xUhePFRN4opBsZpYLfbcjjs6fse7wMpvc9qtaLuArFAvlkpQogchpHbm1tePn8+J18ffvghD60VxKV+VsBw6CFnnLGisfDyJbe3tzx/9ozFYsFqtWK9XLHoOkkOQsRPnqRjsUOWa1iHQD8Nktj5CeMMVhnarmHRObquoXGFAJgyjbXoLC2jmiZlJYz2pBQeyginVP1JUQrlJO2bH3ps7bRSfV319LbhVQrs19/6PoT8TY99GmBfx6r/IdabGPlvuu2bju+7PufflzXX4fNrFnj4TtNBpVLpVmJIOp4QhdiRMmJPquV0joYCj41oJTPWMYjz083NNV98/hn7/U56jPV5S3UQQsA1jsvLC8ZpSdO2rDdrtJLqY/ITzjWsN2sy1TPZE7ynaYtzVUGclJH2UCrVuVbVBc0U1OB43vqTWdecKS5mQfzHy9xvJeeAKopvpiTMBkXtocr4UUXLagsqBM8YPZ1yWGNxrsGQWS5XOGNYtQ2rxZLFakXTLDBOTFZ8GTlTShXRlFgQAyEB5pSktWA0q85gjWLRaFrb0HYLfEpMo7D6pxAZ44TPmSEpgg9YK/DwOA2lVWJpXcOy7ehTYvIRnRWNsQTr0DbSNaIXnkMkQFHVLa5WM9OaeewnnNpllirMFl2ACqeesrKXy6Vs7OsNm83mDhP81Kt7GIaiB6CxONquLSz/RNstcE3LNPjikqdAacZpIobEdrsj58zVy46ua0h+wWLRIshuJCVPtgZjTRnPilxfvWIYRryPdIslumkBjZ8Gcgq0jcE1Gm0yxmQkpgZSmhjHPVrD5PviZ19aDCajVCLEiRAnEh6yJmeFTgqVihyxyvjombxUwkppqZapNqXHCZHayxezn0AIHu8lyRZ3Q1F3O73O5a1PgoxNE31/YBhGEY7xEzE0d2Rq1ck+IVMnkvzOqm2VrY7sqULCy9ISQmEaMwvZTOM4f5bOWWLbltcT8cFjvCZpI5U4Suxys3BAjpwVSXy0qSY0ogNRR+Fy4V+8ZhOcC+OKLB8B4YJ+598CKe43XV8fTbv79wq1yr/52os/nWm/z5S/P+/+Qx3v637+JoGcv0/B+IdaShcYp3SJNIZcIaDSl1IqFXGV+iVnilYWRRF8yJlF18hYWcrE4BmHA41zIkoSxHTk01/8Df/sn/0P+GEgxUAuMiyHcY/dGb58/gWr1YrVasVyveTiwTmXF5fYtmG5WnF+ccG7771H27azs9N+v8M1Dm1FWauKZhhr7yhLRYoTFLNHxVxRTNO+3HYSUZFpJBaN59p/d43YXTrnZgUrrYXUBMwBXwJOYpoCMQVCCtz2e7bDnocPL6WPvV7TugsuzzaonFl14na1XC0JMbPbDxymiN8O6KbjYr1mN4wcph4fEOvUfk8OnnW3pHGWRw8vxMUtiT2rM47oR5I+cLU98PL6wM1+z+A9brUkKTHnWITAZ8+eMcWANZrNYsl6teSLzz/jq1//ms1qwfnmjMu2Q6XI00ePWXcth6uXHELAWzE/CYcDRisaZwv3hVnPXDTOF7Nt6Pn5OW3bcnl5OdtYVjjZlM+waRoePXokM9HTxOeff86LFy94/vz5PDq1Wq14//33MWaBazRKRYyeWG/OOIwT20PPbrdnvdjQtg2+uL7tDwe8n9jdXOOs5mzdcXF5zkcfvV94RYnGCdt8t7tlf9jzz/7H/56vvnrOk3ffZbVa8/77H6O0YT8MbPs9i07RjeCaRLtULJeGwJ7twfOLX+5R2vDFl89Bad55/5K263j4dE2MgdHf4lPCx0ZaYVFhcZgkoiZZK6Y0MsaJKYwy3dCIbntjxPAm+kmCotGzI2H0E3Ga8OMg7Zck+uR+HIGMjdUYRUOMRD8xDgf2261U74UZPzWNjIcaI+2pkrhmXUiRWbzsK+Qeo4ccy/Um8L0QBSPGWlbrBZCY/Mg0DXg/Mk2acTSk1QqAYTgwDOB9tU2VYN2hmYrgzeAnDuMB22hcsKyXCxprCTFCjOx2W/a3wrmQmX1JtmsUOR3Hq1MyFFS7nrtJnRQx37J+6wH96/2S+rvTZvbdXjEcYX3FXdj+tb3x11Trv6v1psD/+1q/yWv/fR378Xlna5T64xzU705Kyms0xas8hFiqmqncSRjGOXnp7SVPDCPe75mmPdMo8pPGiI1pSJGrmxuGceTnn3wy61ivViveeeedeb57uVrx3nvvzSMwVUHKOSc9slxc0lKpONLRNa2S3WIWFqsE6Vz6jamQhyJ9P8yztPd1HFI6umXVHp8xRwKdwJNxrlRjOLqoda3DNBs2qxWrhaiHNVYqa5UzrpHX4BP4kBhDmMVipqEnjRM3uwP7YSRgSFmR/YjO0FknM+tNgwK8l2o041A247rCBUiZLmfwHp+FGW9sQQu0weUM1sr7lIIw1lPGonDa4NoOq6Q1kYP0zyn9ZYXCuiNxqerPn/a/T79qkiSMfj2/p6e/B+bb16RguVxyfn7OMAxcXV2x3+959uwZzlmMhcXCst6cEWLiq6+eCwO8aWm7BV3Tiu5AiEy+VJBO3Ni6+pk0DUZntM7YxmEbS5eXoKHrWppGDFJyDIRxQBlDToEUq4qZZ+h7jLY40xJ9ZlKeYfDkrDgcdmhj8NOAdRprBNmxTUvXWbSBRCrVZSblgDYOkDl15xzL5RJjLG3b0JSAnmMiTB7hV8XylbDWsFh0wvguPuBaK6opUrUmrnwsoHicL0iplb5+IyOitZesVCXgC/naFZOXzWpNiEVDXutCkpbuVr2G7rqrGbq2Ja1XhPCgtAO6YnLTCDIQj1rqIqxz1GKx1uJINDRz37+K81TnRaGRZYH+SXN7px6POnn99bacopT1vPzbVKHfFRuoEpd3190KvcATcwv1roPbm2bMf9fB/A/rN1zlxFVyeQIifJpnQmIuxO/SdTo5aZSCphE4fRgmYpzwPkqFmCMqB1IS0koKGj/t6PcvGYZrvN/Stisa1xFJ9H7gy19+RYyRn/3854AIUfzoRz/iv/wv/0ucc/TTyKMnj7m4vODq6mqWsKzmDW3bCmckplltTsRl4hzkcwaPVOo10IyjJ4TAfr+fdatrUKmVonNO5nPHiXHqRZ+7EHwqXJxzngU1ajJQNweU4uHlBZuLs8L+dVhrZpGcesmklNgeDkx+YtcLBGmc4+Z2x/XNlqvrG7b7A65bYqxjsVzjmpZNCUbLtiOmzOgNZI3KFts2NG4980ZXPjGFyK+++IJxHGmajkWCZdtJgG8d3k8cDhMmSjBvlKbThrNFR9dY1CQVc2sNVmkajYwwOY2fJna3W8bR049D2SS5814aY2axkEp8gkJGLJB9JUzBUVTr4kLMT548ecIwDPy3/+1/y/X1NdfX1ywWHe+++4R33n3Mo8cf89mvP+XnP/sb/ujjH/P+ex9wfn7Bou3ISTEOI30/MhlNc76maTveefc9zjYrLs4v0DqjdUJ3Dt05VmFF9BPvvfcEUsDZRiraMKGyoTEaTWLsR3a3O14+f4EfIzloScoy+CAJ5OgnmqbhcLjB2MT6bEXTOJabM6wzuFYxhUDwXirenHHNAmMcTedouo7V+hxjLOdnZ1hjaLUVmLxCzN7jgyemyGLRseg6hlH4LIuuxRjNUIo75wp8nQM5J7QSnfduITa/RhuaVkyBchTamJ2h94QBFo2DszMMCu8nvJ9YNI1oTJTzriJZXdtgjIgspablwYMLLi7OePr0nfK5Q9d2tK7l9vaalEZMGckTxzZNDGBzFvnY1GBzS0qBkDxt29B1nZBOU5onuKwRjfe5wIUiC10QkHzijkexVc11VPJvc0DnSIQ6VRKqFUxdtZ9+Onn+24DWv+24vymB+H1X4//bWLoE9HIeqHhM66pByUzeqHOmVTN9IiqPYkQrXzZvJeQTIs7oIqiiIHm836LVRNeBUoGYJiChtJohdOukerNZ4Od33n2H9WbD5CcO+wOH/Y5d8Yl+ePlg9ltumqa4K9WLsryeov8dQsBPQdoJWZXqMc0s6gqTq5LZ28LCtYXYk+FO5V57c7V/eWQf5xnRMlZmz43V5BiYDnsZnynVuNKKyYsilRyqImsr8pXaEFJi7A9AYr1s0OqMzWrBYrXBNS3adMLUVYo4eV6+uGHyievdWCqVBmc0rake1wq0FQMcwZWJRRFMK5Hy3N3cELxnGA6oEDlbLFm6hkYZWmNotSGkDDHSdBarFZbAbK6TItM0kqF8phLIThOfWWe8qqghUqeU97j6cdfqvK6+72flMuccXSFOdV3Har3kwcOHrDcbQBNiYpgmfEyUiWkyhrZbYowj+RGjNYvFUjTTi0Vp8J6chdBmvMWMBoNAxau24XyzZOwncpgY+y3GOuxihVOGVbPC0eD7jLeJyUZxeFN67lbpLMp60QdSiLS2iiXJSHGKYZ6DDt4z+cDYe1CatltjbSNoj9JMw0AylqaT6Y76GQbvCYWwuiwz5MYKAmsKB9Y5CwqsNQVZiOUxoG0cnW5onLDLqxhTViLUNCew0zT3Zw2wXi6JsZH+vNKEacJYIRaKKZLFWUkgbq5viFHOG+csq1VXAmosY9WIqptRhVhaybiSOMfSbmusxtqGyY8yuj3bMNd1N8ZVVn8lZ5rScz+NbVLp67mAyfdi4zet32lALz/It9c0BeYXVQ9fdviv//130Mc+fbw39ezr3+/zA/6w3nYpRDdRgpKc8YHTXjkn1Tsw92KUyqQ4kpNHqx6jA+RAzmIHYpSis0bU1TTkPDKNVxgzsF5p+sEz+UhWEtCX62VBC+TzdY3jwcMH/MlP/kSEKLZbXl695MXz53Pg/NGHH/Lk8ePZa3m/3UnlXSo70XWW8eI4efr9QdjXMTNOHh+kZ14hc2EBt3M1WeE4yrsjRhRislJ7b/cD1AwFOsvCdiIa4gzJS/97vehwaiGbiNYCUaY82z5m10niZAYmf2C/27LsWi7PVjy6PMdow/n5A9q2Y/QwhcxXL7fsh5EvX2zZD56X1weUsbi2ZbFoWC8bCRqNCNdYa0HLrL6fPH6cMEqTQ+Dq2XMJBtOIypFHZ2e01tBozUJbFtaxS2I72zVLnC1Sr6kiH4G+PwgLfCUmLTEeR85qFV6r7wq/t4XtfmpAVQN3rdBvb2/nAF6NT4wxnJ2dcXa24f0PPmCxaEhZ4UOiHz0+JJHFzZqEZrHaoFJmHHYYrVifnbFer1l0C4xRjOOE9z3juMMacFbRNBajFWfLjnx5zhe9TFjsw4RrOs6ajkZbLpYPaNUV0zYzkhhUxDUWY4vRT86YnDBZE8ZJ9PwL67x1jpgDU5C5bUXEjwOHQ88wBGLMXDx4TNetWC02GIWorVnHwjkJqkbEcvw0MfqREDyX52dsNhtG7+aRNEWmbUVLvbGOKWcOQZAsXUbbukUnla61hW/gSfGI7uaUmAYRCQJoXMNqs0GiR+L2Zsvh0KOyRVtDYwzOWRpnmSbPi2dfglIslx2tW3D54BLvJ8ZJmPopZVFtrBmIKhzclBlGSRiNs9jW4VYd+8OOEI/X5f1dLhdt53puaShSu0dZ2wqVVZW/Yzw5otfftn5npDhg3qDujypxkn0cg+UxJ7lPiLt7u9cH3d9mcP22x/599bH/zvXPM4h/ONQRtSO8VF+LsLqp/8+gVCQTmaaelEY0CWcUjSv91JhRRioGZzPLVuF0IIUDpBHFhDUtKKlKKJVFTJHDfo8xhouLSxbLBd2iI3gxbwBhtV9eXrLZbDi/OKdbdGLTWKpncsZZKxvO5EkpEkJkHGR+3PskhLIkhiy1Hz8rWpULWQLO3WBdK3JVJGfrZ5Zkp0HUNDM5y9hW3yemUTEOBpUTOmf2XYfJ4JUhALf7gZAyqQjbaCsz8zFMeC8oQIqGHD3OahprwPf4MHF1fWDfT/zy81fses+zq4EpKobUoF3GRUM/ebaHLY0zOGdYrVY0TvTSBdWIkBIX6w1OKbbNFTQtbrOhP+zZ3lzN/VIVIsooGq1JxjDs94w54YedsKHHnuCl3VETmwq5n+4RFWavUqBVIrW2K5QSd7BT9bCcM33fz3rf1XkrF+h1WYiUw9jzxc8/wYfIjz76MRcPHuOaTgxbYoIpkmOk3/cYrbnYeMZm4jAMtE6jlQYloklk6Y3vbneE4MU/3cBq2dA4MekxtsEpiAppPaSAPxwYlcaiCI3DODtPXGSViEzcvvoKlXoOj1bEyRGCK39LGGtpG4tVAZM9YeyZpsDYLtApw9kDss5Mh56oR25KtWq0IoSJGD0p1r6+sNxTJWxW3kkjoWfyk8ybV4Z6SsRo5hHDYAzjMIgZTEFLwjSJBoP3ZaxsInULQaOMLvB8JAWPbi2miJFR2lLTNDJOY5lacHPPPyY53hnVsYZGNYhaniSKMSR22x0ZhW0dLUvazbLwAqQNEGMUfYl0ROzq61ksFGhTZtNl2mIO3uV6rgI3Gn3n92+zfg899CMBal651mcngfsNj/W6oH6XPf+HKvnv1MqSUcuu+7qAfhS3qHlqJkIO+GnA+57VwolFqS3nQRbYXmxLYdGCM5EUenIcUDlgTCtyi1o8yVOBrG9ub2mahnfefZfFcknbidBIMwhzffKezdkZ77/3Hmfn57Rdy267YxpG6mjTwlhiDoQyaibiGmUW2UdRlCvKH8aYWXTl9Dyuetch+LuylFqMH2ZYjuINkVV5/yiksIwPk1QFJBxglWLXLVAZdhGmmLnaH/Axk12D0kYsUBVYk0neE0IkRQ9JY7Wjs5CnHh8yV8+fc7M98Oknz9gePC+2iaRb9OoRtlG4FICRlA84p3BWsTqsaduORw8e4ppmfl3nmzVOKV42Lc4aztZLXuVM/+olmizOdSHcCejj/oboJ/b7W0IQdrTo1R+raqnK7yJuNZBXv/CaQIkpzTFo933P4XCYPbjr/Y9MagnoXdeV1suS290tP//FL3j69Ck/+ujHbFYbbNORkao9ThPRB/aHAasV4+QZJ0/fD+RkcdbijEDSVdVsu72h3+9K/xiWi4bYWDQarSxGZ4LKNFqhY8D3B0YlLn3BOawz2KbBWI0ykLKeA3q/vSD5hhBNUThSdMslTq+wKqKzJ44HpmFiapeYDNkHsgY/HJgyxGmkaRyLRScBPfniZyDv6fEcjnNS2nUyVTBOY7k+xnlLiDESSnKslJoTZmctWsFQAnos/uX9/gBF+a1pRZshR3EY1KjZFRGOAd37sViCL4gnwVwSu8phkQQhFaMlGU8Vt7eMwsUW5UxJxo8jdamoyJGOLoMhhFKMiNiShiKja+YxN3VyfhptUPN/bx/Xfg899GMv/e66G6Tn76oy3fPXvl73PPcr9R/q+P/QQ/8h10lrRcXT2E3OhmpfpEigIjJ7fgLFC3VddKBNi1MOpxQmCzkoqyCM0uwxOBoLRg3kMBL9JNWAasjaYZTCGU0/CoHu7GzN2dk5//Af/gUff/yREHW0YrHsePT4ITEFzjYblBIJ0N1OM/bDvOGoDLvtjnEYePHixRwctLHSw3MNptUY61C6XNBlpjeXOfdU1KZSSqJ4V3TYUyrKcHMmf2TWKgU5N6WSl0Ds/VRmcid5r7QiDD290fQBxiRyNhhNUJYYE1evbiDLRq7ihA49m+4Rl2drLBnlR55/8RXb2x2ffv6S293I1fOR3kNIS2y34mzzCOMadNew71+x211x3ixxXSt98xTZbm/JKXNzfU1OkYfn79EaywdPnzIOPf32Fr8/kMaJECb66Il7R2sNbWMwSvyzc4o0zqJVYuqldSGMY3l/hLmsSl9cFx9sx3K5KHoAUn0dDvvZ4Obo5x1pGiHp9f2BV69eMY4jf/qnf8pyueSnP/0JSikePHhIzpmff/IJu/0WrS3Wtdi2Y3sYuLre47Qwn9syRqW1RRnNvh8I0eP9ntZqVgvDauE427SQJogTL188Y7e9oXVOgozWIhjTLNDaoo0lhj39zeek/jlLvWWhE0sDfpqYhkhztqExLWebM6xTpOkFw+0NX/zKs1h2nD/YoIxBO0salqRxxf7VLfvbA+NtzzRGSQKbHS/tAqMtt7cHlNa0i050AaL4AOQY0IW8Ng0Du1RMgpDPTGvN1DaEEHj54gXjNLI/7Gmco+06glKonDkUlKRyFxRCbtxut6QQ0Tnjx4nDYcc0jvSHHtc4XGPZbfcMw1j8Azz7ncz9+yjJhS6h0vuRQw/5FXOwV0oMyNZrQZMkocikLIHfh4kYM4dpQBUOQE0Su6ahaxyODCmxWHT4vmMsVrPGGJlMQPgDzjl0FcBRR5TOWCM6ALl6qP8tCuhwEvxeW6Df1Un/Nlbf/aB+2k/8bQfzNz3+H4L7d10Vk0nHCYdceurzzKLIe2aVgIgikIkS6BFPaq0dRolTtWisZVAJcoDco4gY3aIJEAMpeMLkySaCEclGEY0RwYvFYsH5+RkffvgBjx8/mnuqrnGsNzKzu+g6lFL0JZAT05xJkwSa7fcHbm9u5+q67RYsFgbTGpxrJeAZgzPFczpIhTAFLwS4WVqZUpFrcijGDdRMXs0zvDVhnkU3lKhwUcaIss6opIh+wg+GKSimrMntEqUtSRl8TtzuB1L0qDhgs8dlQR6WXUcee5KfuH31gpcvXvLyyyt2h4nD1jAlR3ILUd3rNijnoHXsh1tGH0gotBMd65RSee8CQ39AI6YdjTZcnp1xmxI3h544DhACYRjw0wCTxhuNWnU4a0hJkjxrTEkEZ1L/3N6rfcpKdKtM96olLoI9uciMTozjMO8tVWhkHAf6/sDz58/Y7/d89NGPWK9lpFFsNDt2ux3PfvUMH4RAprRBG8sw9Oy2NaAb1l1HYwyLVjbxYZrwPnPYjzRGsW41Z5sFKa0xOaAJbG9v2d7esFxIT3m9WmK1EXKatqAVVgX84QrClqWdWLiGpZ3YTeIDryPYHDnrNtgWbvc70gi7q0ScFnTthLEW7Rw6j2gmpv2WaX8gDp40ZcakSc6zv36F1o5+P6KNIedIjgFrzZwMKSVjpcFPpBiEEKmYNdNj8EzjyHYrxkJ935OLUU5UUlEPfc84jnOSdbbZYK1lOPTklERsqDzOxMRw6LHOYp2hH0a8DyyXLYpMX8inU5xQqGJGI2YvMYuqoC9ogi4mNOv1UgilIzNhLqUo16mPjCHQrZd3uCtNI+eWyeKc59xxsiKrVFpmpUIvfg/VWbGet1qVCj2fVO0/uFLc72i9qQ98P4jfnz0/nVP/IYlxr+vVv+52p9//MDr39ks+0yRELPlF/YtU4kqCtzj2neaDmc1yRWMb/NjLLG6I6GK+klMkThMBSNNEnjyEgKiiBMgelQM6C/94e3NNSpmf/Omf8uGHH/LTn/6U9XrNfr+fj6txjqdPn6KLMltKCZ8yTSs62NvbrchJPn85B3KlFFYbKIIvrWukcpk8KU9zFS1Eu+KXwJE8Y4qEplKwXC4welWkX2P5HihTcmJ3Sf23EvOPaMhOk8eBaRjougWkBqUajLbYxQpsg3MdUwj4rMjRY9KASRM2HugaBykwHnaMu1tefvU5z758xrCLJK/o9FnxRnc0tqVr19A4krN0izXL9UYY9dNI1hqjBKHQWnF5fkaOkd3VFaQEweMPe1599RUpeJbO4lJDING2FmeLVUgMWKNQqlQzChaLTl57CdSvXr0SFnm3OOqwl3HAGrCrAl+dO1+tVjOqUsVlDocD0zQxDAPjOLJer7m8vJzlZK+vrzn0YrozTCPbfi/691NgsxLJ1a5pcUbkPwVqjkzZ0+8nyAGdBpadRV2uSFkqdmcyzohOgmsa/DQyjT272yuM0pytz0Qk52IN6Zazdc9P/mjBxeZPubi45Pzikn/3V/+OT3/9KSlfo9Oepw8vObtosO1j2q7lnfffFcLishVMLENWcs4Zn3EpcbFYkKIhpAYwrLRH64zppO6OcSL4zKE/JpaujEZ6P5UZ/mYeBawWpIfDgefPn88eBRcX5yyXy5KImRkxub6+JoTA2dkZzjl2+z2kRLQi3zocDkyjZxiGMj0lSosxJ6ZpoGlbrq6uZEJEyfnhWmmhxVwd146FpWsaXNMwjh9wdnbGMIxFgdAQfGS32zOMI1e3WyKJh+88FrKfzuTcHPe10jabp1OK4mIVlzJFZVDpqu9+7KFro2VaJ323YvHttdzfMkipe+DA14lqr2GD33voKjIgJPdvZ/i97gW/LrC/6XZv83ivC+anPc/fBjpwul7HG/htPcfvbr1mcmC2Xisja6r8U83dpPl8sdrQWEccB2Iq1b6KZb5aMYWIHyb22z3TOMq4jNZ0zuERKVOSsNKnYSAD69WK87MzLs/PaZpmHmuqDPTFoitTPdX0IwtER5ZNvx/Y7XaAVJ1aiWsSMKtAQRlBi5GpyIgeme7yuG7uqTN/udLzHccBEAtSId1U6UwR7zBayFXWgszyO/w0EWuVESNKUwwsGpTr0K4DE2kXA0SHSRq8QpWKNQVP8CN+HBn2e/rdljBqUpJRIKUsXsncsNaWrAwZGU+zzqFUlbFUgrgUZKRxlgiMhwPESJpG/DAw7A8YnWmskvldU5jKVkOScaPad6zyvtY66hscYyQWWVpjjkIy9XOokwKnkrq1yqrXeq3q60jgqQSsMXreqHe7nUj0es80efphxOz2GNfQuAXrlZmrvhSEBBimQE6B7HtUDqjUk6Jj0WpiUMSo6ZyitUII1EYTfJLKduiFI6IFpVivDeSB1k1cnmuWiw2Xl2dcXJ5z9aqj3xuGKYOOXJzBxblmuVmwXC344P1zkZfVgnuFlIlREQL0HcRJo1QDOPpBk5KmNTI+lowi5ETMkZw0MYb5vVGKWecgRk/O7s4e5kv/u77/cg0c0aXTfvQpZ0FrPUsOR0Uh30mbaRj6ueiruN+hMOS3t7dM3s/SrNY3iIBRmp+jXmhtJ4qMfd/Ttm1JSjJGK2JMRY5WEoia5LnGzES/euy5PHb9oqJn5Taq8DxQZTC3BPuKyCnSt0S+r6+3DuinbNtv6mHXDOT0PvWrXizKiLlBTMeNjMo2zjJgP04TKWdMq2e4ofYX6sVWf3f6/G86nvp9/sDTUdzjPrnuTWNor/vd/ffoN12nJzN8HZk4XVrrO8f0Ns//puM/fR++66rH8d1WyUZpyAp8GonRE8MOSMdeoekwxmHMAmKRR4wTOU5cDVeQPa1TGA0pTjhrePz0KX4c+dXzLZ9+/hn/6l/8zzy4POOD95/wn/zjf8xP//hP+Wf/y8/55FfPuH3xksQV427HYrnkw3ff5b0nTwjTSC4MdWuFVJRioN8f6PuhjBeJTGsfduQoBiAxRvGJLhewwGcabaVXpkv/bAqeKXhW6zVN47i4uEDY1bcSNFCM48DN7Y0EKyf3RSlCDIWlq3DGzWNzQ39AK8VyuSy9x4N4RGdDs1iim4bDMLLb95jzJ9hlw+XlOaZb8WpIkDKXzglpMPV88cv/wF/+i3/F9OMP2PAxbQ4yU56iqL3tAzE7Lt5fkewKvzMQhQU8xMD1cCCzJak9m8Was80CXfiOnTHkGNleXzEcDsRDz3A48Oyzz/DDQBz3oGBSoEk0ChqlcCgiMlY09j2oTKdaVKnQh3Hk6uqKxXLN+fkl4zjx6tULrJWK8ezsjKZpGQY5/25ubgBYrdbkUtEZY1guO3a7PS9ePOP6+ophOLBYdDSN5bPPPuXm5koIg4XBPE4j+/2e3num0ZNWGWMs+90eP0biJAnBsu0wSnHY3pBzZNVorIbOJV6+OvDXf/2Ch5cb3nvnIZdnC843C5atpiluftqYMuKm2WzWGAOHw0tivGG9ek7OPTFuUfoZ+63hL/6s4T/6Rz9lc3aBa9rjPLWZaFt458GOmDO7/oA2DtMsyNmQs+V81eHDgra9RKuOr77a0vcRP414P/BqG8nK0rhzbGNol8sSMM2sByDVeiNKemW6oCZIxhh+9KMfzTLGFbIOIeB9YL3esFwu+eCDD0QUpusgZ5bdQpKnXqSdjdJ47zk/P5/3sFid+cq+9PTpU4C5Mp+iuKutNut5D528aNU3rVTo77zzDpvNpkg5K8ZhYhgmwpjoFiO2bdlciEFN23asN0vaokI3TBO+74smfdH8L+0mZbgjcuRTYph6jG3YbDraRsxtQpGrNejfAeQ+tznV8YfX/u1eIJxvehc+VxyDk6q2mmXk5PTh7wfVtwkk9wP0/cBVq+tvqrK/a8D6vhX0d7nf/df1ppbAtz3X77NFoJQ+Vt5AztIXzVkDJQEsbN6sEjpr6dllTQqJmHzRcgZ8wGRQUUHSJK/Ybyc++9VXZB95fHmGUZrNas3F5ozLs5HRa3zMrBYLlsslm9VK+sUxFm/6wtNQihSCXHx9zzCOIjARI9kXuVfAWDMH9CqYopWW/qR1aGdQRnqzFLJd27ZszmRjSTmWi1jeEnvYl0onV6CiJL25gFdq3izMHWa3VAU6y/ie0gqdhbEbQsDpckyFZZvLeGDTtOQkEP04eq6urrm5XnNzc8NFa8t4oGXRNez2kRQzZBkRGodITg1stxyC57bf4dqJppPqxhkjvuS1JeI9++2Ww27HtN8x7A9cv3pJjhFdLClFF0VhTr4qDjgFQWUq4lALgso/MMYgZONU0AE9/7tqCVT5Xnlf7yJg4zjMqoDDMKCUzK3v9/sZoq/FwTSJI1593HJ2iyxxGhn7kRgiKgnUuj/0kBMWsaI1Gvph5MXLV2iV2Gw6GqdoG0NjG6xRs2oYCA6RckalREoDMOKchzyB86TsSTlzfvaQ1XrBxeWKtu3YHXqxCyVinUflvSAAecCoSGMMIFwHZxtSsnStuOsdthpDZFKZycAYNB7DaC26zLvX88/7QlDUd9uRdY+qEwJVvKfqAOQstq7Bh4KYOBaL5Sy7mnOiadoiZjSCdXMyYEuykLOMhNaisaIqqkDtOWfUNOKahvV6PU9EVEdD1zisc7Mio3MyCRF8FI8C50gp04Yo13G5LqsYTM6ZFOOsgVDbPLq8Puo1ebL/is878xirUqrEv++2N791QD/tP1Va/bHyfX1FWw+mflgxxrIJi5hH3UyccyL3qdUR1rIybmLy1zOTt4HS6+9Pg9z9avy0cv+2x/p9rTdV5/Vvf9uO97uuejGl7DBGYU2RgNTCBBYDFgNRF1FmjUag1UWzQdPhxx1TmEijZ8qeX+5+LWzvfYZRY1PLZ598ya/+/d9g2w7XtPzkz/4T/sl//H/iZi8+3re7PcZY3n/0mLNuQZomrFIsl6uSVMB2v+fm+ppDPzJOE7e3t0WCtKFpWj768Eeslksuzy/JKdEfehlbG0RzWxlLspZsLE+XK2zjcFajjaJrTPk8z1FK0bWWYRhZrTqur695/vw5Z5s1XefEoMIYUeoqKJdzjvVyNQf/afJst1taa1l1rRCH9juUdiwXCx48fES7ecD+MOL3np1XKGvYXKw57A589qtf88UXX3JzdcMvf5Gw/Q0/+eBd3nv0gI8+/JD3Hz/lr/7mU15dH/j5z3/O9T7yN18M0J6zeveGqDWTzrz3/hmPH13SWoVKE2kKxBC5vblhv93yb/+Xf8HN1RXjbo9KCZsTRiFyr63D2RZnNc5qFp0T4xXlZHTxIL3uYRyEtJRFS6CK80zTRNd1rNebWcP7dKYcYLFYAKIvUJnKKYm2/qeffsq//rf/WoxestinLhYLrq6u7qB9IQQm77nZ7rBNQ7teo5Qu88hGkrOyJh/EfyAVjUTToAyEFOinwKvbHUqDaxQxjKQ0kfOasGgJw0gKnuhHyJmb2y3OweVFpmtGNqvalulEpc+2xSHvwP420BtDtxATmcmP+DHwy0++wDrH2fklxrS4nDGmxdgObTVaW1I8EOPA0u2wi8zywQO0XaAXTzh4y2c3liEo9t7Me1UV5bk/319HwqrUcZVQvqvHIBWptEsM4zAVAlmdJ0+FxKow1rE6c8UtMZcJjyDJDzVAKnJpi/kUhG1uG1wjuvSqiByhe0mStBhEDcNIzrDfH0gps73ZEkMqSEODs74kfiNKCQu+dY7GGnxJ+HMJ3qvVqgT0Mqd+AvXfR73nf6vvHo/eOqB/DYq+V4XXAznNLO73e1NKs16tRlPP9JzzrMIDSN+tOEhlf+w73j+eb/r5/rofGE+D4d+moPimIP06ct59VOGbgv/9avx1hL/f9Li/1yqCMpJTKciWSgrTRUWuVk65WpQhNRpJkbNG56ZU8QpFwo8Fmg8Zpx2X5w8Y+4YBRcwQhky/G9jf7Oi6JV0jYzhGGxZNQ+ccjTEYFNH7GeqMXhi1fprw0yQzz03Dcrmma1sWywVt12GKsIxt3JHBqsWJLRpL0pqmE1gPUqlEFWRh00O5BpzAjG3b0jTS8xOJ2GLsoRUaPVeJsiHWc0IU9kRedhSpz5TEp7lblNlqS5oSIQnhD6NJUTTBX754yX67QytFf+h59tXERetoFWwamcs+Ozsj4WivrtGHnsN+RxwhLl7RrFYsL89YLlpWXUtrNUYJW5gYmYae4bBne3PN9vqaYbfDasX5clEQmzz3Za1MMUqVfaJRIFMO4g9hSlBolLjide2C5XItY3tl1O/03D9VilNKzZtv/Xff90x+Ou5lJRDdDU5p7geHGAWN0dLPV6oUECnPioEgrYJMlHNaqaKFgPxOGAGElOjHie3+IGpxRsn57EdyClKZljGuttWsVg1GJbwvlaH3tK2BNkvPNwuLX6rnBmPlXFNZ1wlQEe7JgrbkHMjJQ5ZkWkYfFVqJsE3TJIzN6BayNazjAj0ppkMuCUTp/SrBt1SMQvwCUV+LSYq5InVM+UTrdS7xRQI7SiGdREGQlKpVf+lBK8qUQ+G1aCkMcwkbpnoWUNq5IZNUpjVORtxcU47zXusyZ4Kv0sri4DhNImSTgxhCiX1q6ZHn6gIqCEwovfDKBatxMyWZwrnbYy/7dt2/j6f4d15vHdBrNVuJCXIx3a2e60GdEgEqnACcZE53g5AYycuJV/sKi4X0Yw63h1lK87vC4fcD3et65af93/vEs9/X+qa+ef37/UTqh1i/28SmEB/zJFoDWmBto1aQhdSmykUq55UXIlRKqCQjWMMuE6fExeYRXWcxbSBHz+7mOXkaiEPgcn3B//Gf/B/QWSDnX/zyU37xy1/xL/+7f83zl/9f/s//1/8LH//4x+imxVjHxWrF2XrF47Nzhmnis2fPcK5hsVoxHoZZ8S34wPvvv8/m7IynT5/SNh0pxCITu5MLPUacdaw2Z5gCCXqlCCgwmpilEsw50TZLjNG0nSWEyGEYRFlqvUIbTdc1PPvqGV9++WVByDTL5QJbKtGa6Ghd7FuzYtktOey2vHz2imVjWTnDoyePefDwCZNb4hVEH0Br3n/3kpDh159v+eKzL/gX//M/x6WJi/U5ty8+54v/9ddcffZrfnF5xl/89Kc8ffSIP/roY2K25MUzfvX5S/7nf/tL9vuBfe74+Cd/wj/5j/+CiwvHw4eOzEBmZN9HYhjpt9dsr15y9fxLrl++ZNjtWS06np7/CKMUOidiGNlPB/KiQy1atM7E5FFaYHuUwOpLu8A4w+Z8w2K55OGjx6xXay4vHvCzn/2cn//s5xwOhztM6Wpk03XCjD91sdvtdrx8+ZKcMh9//DG77Y6+778W+KtynJCiGh4+fIAqo19WF7105cim9g11uT/EhEiSdkuMzkSfMK6jW52RSdxuD+x2Wz77PPLO4wvONitaWwRS4iTBwHuWi4b18jF+jPQ7z9Bv2W+fsdms2Ww2ZZrAkElopXj4dEnbGRbLBdooLs/OUaa2cSRJCXEg5RHnJqztOfQR7zNKmdILv0WpiaFXZHfB03feZzco0nXEe0Er6jIFWp8ldJURKd6mxXtPt1x9bf8SXYWjJvr93a2Ks1iXMErRNI6a5ofocSGI+mTOxTNAzYEzlvn4itp0XUuIkWGayBmxHI6lZaN0CerFntiLVPPLr66kkreGrGEdz4RwW5zo1sslBzJDLkJPIZCdkxZAlPl5E6O0PkIgZuakACTpVamMwr5l77yu79dDz3eDTq4HUTKy+wH9lF16OnN+t2Ku3+vjJplaugc7fJegfppxvS5Avon8Vo/jb8N6XZLxut53rUBe9xpPb/umvvlvEsy/+3uV569UPuecC4s9S0asyix61UBOaS7mISlUNljdoY2j33kmPKtOZjfDBGHMTL0oxrVuCVGhgmLVnvHg7DHvPBppbIvJinF/KJu0QWoSJRrRSUwfUvAc9nvImdVyibWOEJNYXRojG0WMM0RmmwaTEikmaU0ZM4+maKOxSpHLXK5zmpylQkiJ0lusLQeBmnNyxLjg7PyMTOaw3zNNE9W8pVaZwCzEUf+uSqWzWq14eLZmuVxhncWXRHa5aohaep6HYeLLz7/k+bNn9Psen0ZgxI9T+ZzlGG9ublEZFocMusFaw/n5hn/w058wZEdavcsHH3/IB+9fsFkZNmcarRxKdYzLBj9OLG3i9nLD1Zd/zvWrV9y+fEXjLO8+fkwKgeGwJ3ghIK03Kx48uKDtGow19P2eEAMLJ2TBy4eXdIuOy4eXtG3H5uyMRbdgvdqglWa5WHJ7e3tHNKaOUNUAXc1Z6nV0ZCaXiYTghf1c+rR1T9Nas1wu50KkMpcVUi0L3+Oo1R9ztddVc7tR60yKRggDWpPIovTnJ6IfWC5F1U6vFjS2DGbmzOgjSnludwOGnuwPTOPI2ItfgHyNxPJvhaL3WxbLkeValONsK1KzWXu6RcvmfCNwctOgmw7TLdC+R0VPDImcPZPvQWe8XpLVRPYTMUkPPeaMLoz0O0VdCVjRi2mLqK1JEJQ9+DRwlcqeEwS1BHfZNsSRrHVWKmIjzmQZMNmWNpQE01z+S0lQFmVEiGm5XGGNwTUOFQIhJnRpI9fbVsRgJvBqjTWWbrEgZ1DO0HYdzgoSV5MGSYpiIfd5fAi0cw89zZbK9Tw6Pk+Nf8zkxddy1L5hfaeAfhrET/F/eZ+PT1rHEOpFUoknEtDl+GaruHJin8q+VpLJfULF/fVNQfx1x316Eb6OsHcfNfh9rK/1Ufh6wHwdLP+2QfVvU999zl5zFOUsZYTUlqWaIWdyLNB6Kcp0Bp0NOmuW3QbdGn7+V/8r++2WD997TGM1w23Cj5Hbq5HWGRbnG/wYGfYTZ90T1j96xB9/9BNSDry8fsXV51+xWK9wCZoMLkHsR0iRpXPsDgdePX/BxYMHvPfOu8SciRl8kYq8urrCGMtms8Fax/nFBYDoV8dM9BG0IpDQRuOcpppgta1UiDFCCIlhHFBKRmesUbSN3N46YcJrpfi3/+bf8MUXX2CtZbFYsCnKdbfX14zjyPX1NQqF1Q7nWhaLJe+//wF/+uOP6CfP5FNBRRTvvXNGVIaffbrny69e8j/9D/8jt1ev6Hc7Qr/l2e0Lzhu4WKxZLNZ03ZpPP/2CT/wv8clg3YKf/Ef/lA/ef5f/11/8E7JbEttHrC8anry/wFmFM7DoMm0DVgomwpQZB89/9o//ETdXN/zqF5/gp5HkPTfX13z6yScc9jtub2740ccf8NOf/oSmkdn1T375Cbv9nosH55yfn/NP//P/nMsHl7z3/rtkxBde0sPj5vyLX/yCr776ir/6q7/i2bNn3NzcEIIEllQ0ArTWc0+9Bvy+79ntd2x3Wy4vRMN/u93Oe1rTNDx9+pRMpi9cCVt6BNFPJOvINlIVMit0b4sb3WK5RqlMTBOqiKpkBI69uum5ub7Gti0Yw2K9RjddqaQ9+2nH4CP681eEac/21VdoIlbBZgObNXz5/Jbr6z39QTT/f/yTHauNY7VusE7RLTQpB3zac/nwgg8/ep/HTx7y9Okl9vwJ3eUDAl+Sb7fs+h1+CgxTANOi247oLYN/RTJrjHuABVJMTGWsCyQc+dJLv70WrYYXr16y6Bb88Y9/jHUO14j3uSqfnw/H/de5Rqr2EvjGacBZzeX5BnLGe+l1p1yQPq1IUQLjOA3SoioDQMZKErxebUryBcM4ERM0bsRaRy7eCDUZNlpaf02TcbZltTgrLDiF7Rra1RJtKDLPI4NW4sy427Pf7zns97SlFRNCwqBmuD3GSCyk4ON+n8hJlxaOIJVvu77T2Nr9yvs0SHKvB/G6MShTRnbq7G5lH869v5PgOvlJWMOYe5Ptbx/I4fUB8jjzq+Zs/W1QgN/luh/MX1eNn67XVejfdLv763f/mmsFPhsmoVUGFUGdpIdKgZILSlF7fRqVNRrRs768eMiyWTAePEP0jNuBMHmm7zf65AABAABJREFUgyGqTDzshYw5BcZpwE89i5XFNZrOOpwuvA/v2V5dE33AWItxjmXXQZZg2zUt5Mz2dsuu78Xi1IryW3U4s1bmx4WgVcRwjJbKwGo8Ce8jcQykHEUpSmmZKU+JUGZ5haWu8D7PEODopRf+4uVLvvjiC/rDga5t2Ww2aK3o9wdiCAzjSOMaztbn80gNSjGME/04MfrAIUeCtsRrg8+KLz7/iq++esHVyxcctreEyeMHmavf2I6m6UTush8lQcmKd995j/X5JR//yR/RrS8wi4ck0zK5jm5lOVuKiYzO0GpFozJVtl9nRWMs7zx+yPl6ybqzYmeZAvvtjvfffcLYS1/+gw/f5733350T/GbZMYwDZ+cy1nR2cU63XAgCokTuNYZE8PH/z9x/PcmWZWd+4G+Lo1yFujpvZmVlAVWoAqrQYppNdjd7JGkcIzm0eZyXMZu/bp74F4w1h2Q30Y0WIIDuAlAys1JcGcrVkVvMw9rnuEfkzURmEbCeYxY3bnh4uB8/Yq+1vvWt75PWYGa4uDgnLyzOD1xcnDO4gZubG968fs3gHEpLO/Hm5pqmbanrPV3XMgyCTgihTs6P944QA0VZiNaAkdlo7x1GgVZ5WhtlXpogwkmKhERGgY11smhFRZS2RKVxXvTasRYXdXK0E0OfqAyYDEyAqMjLOSoGOq8JoSSaB3R9y66p2bWKy9uO9dqzbzTz+Snzcsbi9ILZzNK5Ha1zbJqG+XzBe+9/yHxVkVcrPHP2bUbR51QuR5sFptDYXBGUWAArU2DyCnSJUhnaWDCGum7YbLZcXV9zu75NjXGmCYT9rk5Exo6+H/jihZDyRia5VgrvoxgXJbJ1npeJJS5J/uD6pLEuBNph5DqgJv31iUMSRpKtFb2CLEMrTdcLD8IYhfMyVy/tqgKjLMFGyrwkyy3WyNgaYwswpL56qva1OlgY35mbT+qThyLqaI0di8cQZLT0XpSL0tVn7Dl804LtWwf0cUfvGBTc29nj34+BYgzcsrMJUkBNYw4mF/buWN23TUOIgUU5TxnSt9veFciPfzchC/Eg83i/cv+PAbvfJ+7df2z8+ZtU6F/1vK9CMX6boP7bHaOxM6YIQb4UEFRM1cxIqtGoaIhoCAYVtGgbByVazBGMUrz/3vsE5/jpn/wZ2/WGYbeX8SiX4bqOZnuNUWANbDaXbDZXPH16ytnZnOXpHFvM2Oz3xK7j8ouXlLMK7xzLs1Oen3+XqijJi5KohTT29s0bvnj1ivOHD5gvFpycnpEXYvkogiMQXKT3bmLr2tyQFZqubtg1Lft6Tz8MkwXnhB6hsMamYKDw7jB2tdtt2W12/OaTT/jFL35BlljAi8VC4N4QUwAvWC5XzKslWhuq2QwfIuvdjn3T0Q6OOhgcBmpH03t+8Vc/483bS159/jmu79Cup28a6l1NnJWUxYy+96z7PZmGIsv44Y9+n6fP3+fDv/v3yKo5Qw8OaACdQVaIBozvoVCy2HQ9OBdFKQvNB+89kpztd78jBCcLQ+/Y76SyckM/zQXLmKDjd933CVH63zr1SHVS3xPUoqANPX3fy+iRsTx59oj3zBMeP3nCdrOl7Vo+/fRTPvvsU7quE4vPruWLF19MoifDMKRKHMqiIMQgErGD9Nvn81PyPEdrCULDMIASCWIfoow++nG0T4KwLM4qCc1YbF6ACmibEdG0vacsNEUK6E0PbR9ph0DQFpUV4CUBqJaW4D1t3UEs0OUpXbvh7c2bJHpSS1KpDH/w5AMePX7Ek+ffJS8sH//mr9g3G27Xr3j/gwf84A/+C7QNeFqC8tzsHPO6gEWJsedk1ZJsXhD7Huc8SufksxOcWmJDKaY8JqPret68veTjTz7mixcviCkZFeKZoFVKaap03V9fC7qV5cUkEETqkWc2wxpDWVbCQbE2JUUC111pYZZL0iWwfZbJLLu1eVIHlGJxnA6xKSnf7ZM4T2YmeN4YS1lUkAtKWBQyPy89dFF8lJG61DbWpHZaCrwcXBGdd+IIF+K0tk5FFySzGBKZLi2J03OYjtk31XAft28d0O/0zqfGN1M8V+rIgCXt9NinKstSjCasmSqYqWflw0R+UEolXeCDRvvx9nUB7auIcOPv7rcMxiA+SkPe9aH9j7f9bVXof5v7+ttsY5I3kmDkh/QtKlCW5B4sv/AqKbVBkQv5aOgGXB9YVGfYUNCrBUPXs7/ZgoM45HSuY983dJ0Hp9mva2Lf0jZbTKbZ7PfYPOM73/2I5cmK5ekZNs/Z3N5i8pzFbM71Zs31es3Q91RlwWI+Z7FcUpWVjOgkdbIQJWHJyzyx8TW9G6i7AacgyzPqq5rNdkPT1OnaS+YdRUEMgZqE6pE0orMc7z11XVNWFecXF/Rti3ee3U7Y6IvZAmM0WZbjnefNmzdiYel6Xr8UcZKgJF3aD4ouwLaNtL3ni7c3bDY76u2Wtt5T315TWsXJYkXwkaurG2ZWURrN00cPOD895eHTZ1w8fkwcAn0QgxaspljIHHN00iKxRqB2AxQG7MhRAHFRS6fc+0BdiwVq1/aMUrg2GqKK01c/9PjghY9gMxbVfFIAU0pmv7VSVFU5mbJ4FxgGR5Fn6NMVP/nJT3j06BEvXryY4HdrLbPZTCRc23Zyyhtd2UYC3LhWjA5s19fXKKVYzOdp9v3AEREISnQTYkw91HhYTwfniIQkauIZfMAGTVQGkxmKyoBRuCje8+3gGZzAHGVREnzEDRqsQWUF2WApThQUPZS9OJ2FwG2tGN7UXO1+QSTw6vIznO/QuqVnzR//ya84OZ3z8PEJ1XzGfJ4zxCV1X+KcxkdH0BGsw5iI0hnYFTAjBAPKYKylms04Oz+jHwbK1L4gIgxx72WeH8ViuZL58zyX1lsKfDHEVL3KNRJjZLvdSeAbkVWdzHesAkKSQD60gMdWLhyc1gS2TwkDUZKSVNGP2gx930mbIAAxpvl2M8kvi8YAKKxce2XBbDnn7PEDijKnrHKslfn1Is/xeUFmLcbaifk/tpi1MZOCpFJMWhLTlFiq0Kc1/G+6Qr8fyO8EGimnvtSXHndmFGEwCWLKywIfkjB+quRJQhLj3xsrusfENOpytH1VQJv2J23HymmHsYFwB224D7f/dqpnf7Pb1wXz45//Oqb7V0Hr3yQZ+Lbbtz9mkpkqJRDZ+BoT8WV6XWG8omQ2NHhFdFGqlCzD6ox92zN0EtArs6TXLc2+Zn85EIdIHAq6umO3aVDKAYbd7Z5m07PfKbSJ3O73zBYLHp6dcf7gAeVqResGrm5uWJyccnJ+wZvLt7x5/YqgNVVRsFgIk7isSvI8Z3B+YtsaqynLjBjAD1DvHdv9jnJRkVcl+2bP9c0VZV4m8QxJCozWBO0ZRlEaFPPZnGyW4b1nv99TliUPLh5wfXlJE5pJ7WxWzlFKgpxLAb3vWtqmpu9r3NCSVxU2z9l2kbYPfPHmhrb3YEu63rHfbtht1rz5/FOeXJzz/oPvENsdV5fXDFWOL6Xve/HwEQ+fPuX80RO6LjD4ltpBVloWZxkuQDdApiJF6psrwEj3BO9UIh4dyeEOQzK0cbLgJsKTjxki5imk2n4YGNyQlPMQslxSjhT+jUtTAOV0bTeNyLLO5yJ5+od/+Ie8//77/Omf/ikvX77k8vKSLMsmLfdRz30YBlmgi2Kq2heLxaT05Zzj8vJSzsmDBwLLu4E0KAUhTFVqiON9NtrjBvphDOhOtPRdEA4HWgL6zIgbXlR0LpANgaEXv+3FvCIG6HqFihlazclCQeEKVDugOkEpBue4rTU3+5rLq09ou4bb+hZjIw8vZmy7Nar8Jc/ff8KPyxMusorF2Rl9XLDvSiIZMXqCNmBDEirKUHYFsSAMVubtjYgqnV2INe75xfm07m43QuQc585Xq1OyTK77YXCSyKXjPbYlRq387W5H23Z0XQdEqZqNxhYjchuSsU4nxkhNM00x2DSRNZFGj2KRiDGZ6VyPr0EiQ47CMuO15b0UkkVeYvOc+WrJ2YNz7KxA6SXzRZUQAtGlcEWPzQRlOAR0Pdkla3PwOx+Fb6QVndZuLUB85JureH4rUtwhUOsJojbGiNnCuFNpQT6Wfx2/t22LsQaX1Ht8PKr4PZCg74koFyPRxzsLPHwzKPmY2GatfMxxn8ZMbjgarxj3YxQ4+P+X7etO5N8Uwe2rEodvun3745XeR40a5OPMLgx+pDPFpGAlbmZxCPgu4tqA7zyh81x+8QbfO1bVgtxYaDXBadomsN/2vH7xhug9VimKbEl1seDq7WdcXV6S53uMafnsizdEPfCP/tE/5cnTpxgfuXr9lr/64z8mak2+mvP4vfdYnZ1DFOh1dXHBfLnEliXaWpq2pRsG6ZUrJZChFylJgVklms3mM4bg2e235HnG6mQlCauPvH79ahpzM9ZQlXPpj88X1Puam+trXr18xdXVFdfX12w2G/Z70aleLlcyHrdYolCs1xvqfc3bN28xSdkNJb266/Waru/xuiBEQwwBRWC33dL1A77ryJTm4fkF52enrBZLvFV4A+enS04Xc54+e87TZ8/IF0tUWZKpgIky86uszAZr5C29d7TOIe53YYIVvRMRmH0tuveL5SJpbt9O+trVrKScLfDRU7fCD/AhoI3CaovSAk8K1B6TapdKSeAIgwIK8txO/dXxWi+Kgn/yT/4JbdtgjOi6r9dbXrx4wV/+5V/yF3/xF/z5n//5FCCWyyVlWSaYXSdNAD/Jgx7MdZK2wDiHHD3OgY+ikR6jCNnEGNlstsQYWK+37OsGHyPd4NjuW2xecvHoMfPljLwq0XkBJqP3Msrrrtd457i93VA3A1fXrRDqYoTkP9g0HX0vfW+iImhFLCtWlcyjF8sCVZRs+5yOJaZ6gi5PIDtl3yvaoJnNVjKuVjpRpvMBHxRtbXHR0Dnhn9BvGQYHKMpqRpYXEqSA+eKE4KWIixEym09OdYNzNHUzJTkSRLOp8t5td1OFj4KyLEBFnB8YLcm897heJHhH//QQoxjiaD1B3H70JZczQwxi6Trqste1XGfB+Qmt1Uo+g08s9rbtJ32Jkcw2Qu1N0xCco65r2qb9UmvXWpP4Nhk27RtaE4+4ZCNaIZfutyu2vpWwzHEvYIIO0kysUUeBOMSktyzQxyjz1w892mvc2Fs/YrHH42o6iUUIuchPgjP39yXdqweCwb0PPQkccBc1GH93LN84BvL/rZXqN92O32Hcx69635hS1vHXx+fiS4nMl6c23/ke9xOB31bLfToX3yKxSGdrBHYOY4whgpeFR8sgFyYEolcigNJ7+tbhGodrHVcvLqk3NR88e5/lbEHmIXrF0EfaZuD2ZoNRipP5gqwoWVQzrt+8ZrfpKIsWa2tevX2BVx1PHj3iux98BxUi2/WaP//TP8MUOY/ff4+sKOnahug9WZZxdnrK+cOH1H1PHwJd3wEyrqaSP3lEMnqRfjXYTAg3fbOj6RpMZpjNK4bO0cee29sbWeRDwNqM1fKExXwuBhze453n+vqa9WbNdrtlu93KDHuIrFYnFEVBkec4J25Q6/Wa169fU1UlJycrbAY20+z2O9bbLbZYonROjEI0autaHOCGAQOcLFcs5wuqssTjcdGxWJ5werri/OIB5xcPsGUFNsN4j1GQzSxxvB6SUV4YAq7rCUNP9IekxyfP9/XNNSjIrGHwA21TS6JPpKhEzWtwThjwI5xqFBlJChSEEa00NpMLaoQq5SqTa9pYqSDHGyEis9E/+tGPMEZzfnGGc471essnH3/CfD5nu93y05/+dKrgzs/Pmc1mUwI7BmVBV5IK3YjRKI5MeTxe9HQSZyTBt0TquiFEz76uabuegGLwAdqO5SJnPptTlhkmtyiTgTIMPuIGT9Ps6IeB69sbbtZ7Pv70LVlhqOYFuS3JspK67ei6QdqXUTGbLbBZxqwssFZjqwwySzMYhlCg81OUPSGaE9phIPSOrFxgVIWyIiXsg8MTaPsBFxRDVPjoGUI9JbR5UR6hnSrNlh/WaTeESZlPnO3Kaf3J8yLZm8pz630jErpRhGNms5IYA3WzJ6qI0kmwx3tBJFKLN8Y4oV7Tuu+cQPnh0Hbt+556v6eua/b1nqHrRZ/heL2Kh5hxc7uRFoBWKVYdFOD6PhKco+vEjvcwBZauQ6On1q4e27tKc7BQHflF6Z2Prtdvsn0rYZnxu9YabU3qYdkpoGtzyIS0NxOz0RiDcwPX11f0w0DTtAK3zCuWywWr1QlZkWOsFfcd72gamRktspzjGUUV1WFGDyGYMP2c+g/jwHIIKWxI0DNKJ/giEIMnpIw/xCD+ytpMycN/DEKcbGPwHhOLQ4Z350QLjQwSuAdqchji6FnHr/p1IXd6P3X0B0zF5d2fj3Yjxiiqf7/NFqXHqIjEYZA+2KBkzjyImqCJgejAd5G+Hmh3HX09yP+3NUPT8/blWzb2lixqdATlA9HDkyfPMEpR5RlDN7De7JgvV/zOD75P23yG66/4g4e/TzXP+eiHP+D84QN+9ctfcrtZc3KyoHWOz198ztvba3728a+YrVbMTlYsT05ZnZ5htKHQhn3bMSR4PoQIWti08/kKm1mK3NJ7R+/FEarvGjKtsEWBs/L7iwdnNE3LZr3FOc/rN2/oTk9YrFZyf+WWbb3li5ef8+bVa7abLS7Bk027QwG3N+ukctaK69euZj6f0XY1WkeMgm7owUVuNpf0zoMW28yhcQz9QL3ekGeW5WqFRdTJ2qam3m753ocf8Oz9D3jy/H0ePnkCvaO9WdN2g1yl24y273lzfUNRlJycnFIYQ2UNt+s9m3Wqvol45xi84+3lG2xmOT09xVjDyekpSis5bmUpFXEy2jBGCEpCUZA+KEqRFYX0QgHnHft9jbGGPBmCWGMYEtk2zzOUEulT7zx5+lvvpaqtZjM++PA7LFZLPvzou/zn//t/yk9/+lM+/vhjrq9vpJpH5p8DYDPLw4eP8N6xuV2jtRJIOAUylUbQvPM4F/BeIFXnhNuw2dwSomO7WaN05OmTp7TNnv3uFqNzynKB9z1107Ove4JX7JuBvu0EVek6bm5v8THy8MmZcJOiR2cGk1sezFdYm+OHKGNdUWDd3BhpX/QdbdtxdXVFnlV8+OFrhkGR53OZ9LA5Mc6IseTVqzcTt0Bpw2yxBG2xxhK9aPNnmZn61SOK4Zyf9NhBMfQDr169Issynj17hlKaosgnqNkYPXENxqpW1N7GpSkQVSQrMwmkQRLKqA2zrAKqaT0LqZgc13WbzFmiP3A3QqhYLufi/jYMadz0SLskiHZA76Tqf2+QOfOma5mvFjx89IgsFz5A8D3eDbjBSVKgxIxMaQ1GXAN1+hJ0W/gHUaUYmtqOIjKjEGuiMQr89ds3h9yPKtxDJnEEB+ij52kRBtFGT5lwRGZsm6bh9nYjoyXRkeeiy60TEW4Y0s06DATnya1YL8r6LxB8RIK2Hl1oxvcexUlU5ED1lxsqpguBMBo1JPGAEAjBJRevu2IIdwhmfAn5/9abGktS2dXD6x5H28mf9ziQH34+fq1x92KamZzaF1Mn9+5eq3hAKt7Vlx8ZmONzYaL2TC62idYwHmJALj497d9R2pDeftqLdx3EGJi0mX3AD8jV62KSflWEITI0nr4Z6JuOru7p6x7XD0Tnafc1gzJoFzFKMcsLYoBqVmGUEsbw4Oj6HptnlLMztL6mMzsePj7n9HzByYMzysWcXb1j3+zJi4yBQL1es9nveXF5ydP3n/NeWYjiofcoa1GILOfQD+y2O0GftPBE8mImghMxXYMxTYV4L6M1k6OcFqa6NlM10rQNRVvQ9ULCykykaRs2uw3b9OWdhxhlEfGezz/7gr4fGAY/nbioAnmRyTgVBySlrWvabsDmUt363uP7gaGrMTFHM4fgcYO4yg2D9AMXyyWz+YJyNsP3A64bqLseHwGbsW9a3r66YrFYCD8gz0Dn9G1HvduLwyIyiue8o97Xk2GG0YayqNBWkxdZGmfKJnXJLC8mglKMIoMbER94lJiXuDQDbZM4j1KKYA59UmutCLlMiXwaO0sXqEnJzGyxYLaY8/jJE1zwtF3HPlVw6DDdD9qI6trYqzbGkOey/k2MZSIx+PSlk4CQ9M6HoSMEQSDyImM5X4jaoRiTo5SR54eYdOAN/eDpesd219B1HXXbyYjlqhLi3jBgs5wsExncqqjoe58IdNIftkoTgqdzwnGqm4btZs/t9YblfEV7PlBUYvsaoyV4w2bbsNvtGIZ0HPMZ2sj4Vp+qUgBjM0jraNcJ7yDLZPRLK41zjs1mQ57nOJfGNI/WjMP6O66NUpkfo4xRiaVsSAJQKKbetElIK1H4Ft57WfthMuwZR6RHFGVs0fpkzToqVMYoyWf0gT5xZJQSNcftfkc5r9KkirRzhiTLfJxEoGQke4qN+uB/ohMWeVgPjxdH+bugxHf+m2zfTlgGWbx9DAzBc7vbcLvdUBY5ZdJ3ltECqYhHBatuaOm6lrZv2Nd7rm6u0Bour9+yXt+w3a45OztjuVzJmIFSlJkmWs28lAq963v2dc0Xn72gH3raruHk5JQH58IwzIpMgn2E+UJGIrZdyzA4NtubFFjkoGd5BiFSFBld79OYXE3fdvgwJHGBdDKDsCFtZkXnuuvQSWFoGITEYROcN9opdkOX2g3JF1jp5Bhlpu9o0SI2R+xGEQNRB/Q6Ho58PH7oKDEAuTjjyI5MrY3gw0HOkohRZhoDsaMM41HvOybFovHCGV89jP8fE4v0+HFsPryPbCNKMyaBOu2j/J18PuFaR6LvicFBn1orXcS7SLPpMcoyz1fU24Y3X1ySqZxSVwybhnbXYrzGophbAxH+6hd/SfSBH//B7xO8583ly4nt7IYBZwY6t8P1W6qV5fzxA/7hP/47PHv+CJN5tvtLVKUw3hL7SGFz3jt9j4DCKcPv/+Ef8pO/9/cJaPpuoK87huB5+eaSumm4WW+IwPL0FB8URdnQ945hCOSZJs8NpbXkKk8iKp7Ts3OyPOfhxUPqpiXqX7Df1+hCvNj/9D/8mWT8fc92s6but3RuR+/3NPsdQ9/z+W5P3w2s1+L5XNcdZTXj4cMneDyDH5gvlpzOF2w3G9q6oUQYv2cnKyLw81/+Snp++5qu1VwOG7r5nNCeU+QZ80WFJ7Cp97y5ucErkT51ztN2jgDoLCeEyNAO9NpQ327YdC1DU7Pf72jbhgcPH7JKsqQ2y/je934XbTSnp6civhN8moSxUmVaO7VkiGrSzhYOjhBm+7qVxCaJVXklBhpYlej16bvSDHhUDJjCoqKh7weUV0TDZOE8BNFyv91vuNre8vmrl/zy00+43q6pXU90osK3XC5Q1vL69hqFYnaymsbxNDJr3w9O+sZeOCF+aAk+Jh1xw6KyhKBwXUaWWTKt0SHiesft1Zp6V3N2dsJstmS/8zSqpu8iXRd59eaWGCLL1bm0FILl9GTFw4cPEW8DQ1d39N3A7s0V9X6PSnoOJrUEZrOS2XLJ4+9/hNaKX/zZn9Pe3uDqHU+ePeHiwQU7FI01/ObXv+Tt5SUvX70iAuePHoM2dEF81AcXKauS2Wx+B/oGqMoyoVZzgg+8ePmCIi8YXC/kRg4jWiOMPU5+ZHmG0UbU67RKPIhIYJQET61grVMpG6c1t8gziHYqfkhrmUukU4lRJF6HJH1ZnpHZbLrObm9vGYaBqsyFn2EFTahOFgD4wRMGj1OR3BqqakFoOkLX44KncwMmE84H1kKWofMMZSS5IQiHLPqWofdYW5CZTMj2IeBi/Juv0MfAEI8W9lENbgxaKIFF0n2RIHgtVXAUwpso9Yxe5qkvMQwyXuEGFAmuivEokIwwtGS0wkZs5fmJWKWVwkXJQhVHLd0oNpaSLSlitNhMLiCj1cSAjFG05F26CMeTOSpCxZinsYtGxhCikOrGsRZr7TRD33Tt0ejEgTl/ENHRh4CujgM6iZX5FeeAQ2U//gwpoI+Vf4z0fT/1hsYejtGGLM1m5imgj+xNGGV5R6jnHvJ+dDe8K6DHEdYaf5c+C2ObZupnMgV4pSSg4wdU8GgnlUMcxKZwv92hoyHmkf2mZntzQ64LvO3p9j1DM1CYAqsyrIYYIk29FeKU71EKslxGVAKOwIBjwMUeFzpmuSKf5awuVpw+PKVuOwbX4fEEHYRhqiSR01mGyUtOTk84Ozvler2j2Td0ztF7z363o25a2qZFaSOELy8wq1JaDB3swf8gRk1Q0iyxSU5SW41zYeqnZXlO23Xcbta0dc1+uyEGRwxOEuS+pe1qurZlvV7Tdb2Qt5yj7Xq00Tg/MHjxXY9JQEknjfzSZgRjKayR8VE/gOvROIwy5FZhjcIY6b1nuUUZRVCR3jmarmOzlR5u14swR15WcmVERXCevu3o25Zu3zD0A8ELbJ7nBfP5grwopqrFZlbSVmUmJ8ZRHOR4DRKdFlkLwmSReZCYjiSDjkSKm67KhK9GBFpSRqNCTBM0IsmqggKtZQLHO9q+Y9/U8lXX9KlFJ5C/QluLMobeid5AabPp+CrUdB/HxJpWSIspxoBRGUZQWLnvjRYhlQkqjjgXUMpBFFMV54S5HQYJnv0get95Xk2E5MwUzMr5CHwxxB5cIAxO+uHWJLEfEW4pjWFe5JwtlrRtw+36hu3NLTeXV5yslrjVkpBY+0PX0bUN2+1GWidGpk+6qInIqJ2ItGhpLaVEH6Cua4wxtG1LCKKX3+c9V9dXaR36snqnTd7i4/hYnhdp/SS1WINU5voen0vrqWd//JrjChYjk0ZKJEzEN++F12GjldfXSdkvjVjrzKbAJslHpvPUhxc+BOk5mbGpeNPT9emSQU1AyfWTru1pJG1Cnz3KMPmfj03Xv/GAPjLSR+epoigIyTO2LEuq5DKltSaKGsYENWoNeZnz3gfvQ4x8//vfnwKKtSbNBiYYre1wwyBMxRBo6i6ZtVSUecF3vvMBIEFysZD+ewieEIUN2bYdTV0nHWxDZiuqWSUZ/PGNH0Xft8iTJeMI8RBxQ0/dNAILHkk8jnOoxtpJ6EIqdOnVTex57+681/i4mNMEhgTvuyOIn+QkFl1iA09gt2zhTpCfhmLuBPjRjGy6iKdnJyWiIzLjHWRAKYYRarp33r+SS/CuAH5nj9/93PH1dJRPMM8tuTUUSrLwZbVi6AZ++Ze/oq8H3N6ho8GSU28adjdbzk/OOV2d8vD0IeVsSWYdMQTy3NHFju3uNQ8eXvDf/N//T+z3Wz7++Fe8fvOat5++xNgBUzhUFYiV4nJ3CZeBLCvpXM/l+oqm7VCZYegd129uePTkKR99+AGZNbx88YJPv3jBm8trfFSECM0gZhDKCgFnFL2JPqAzJSYQRcliXjLUjsG1zLIcbEa92dG7Da+urtns9vzi1x8TiMwXizRK43j5+jW/+sXPWc5LFrOS1y++YHN7Q73dMXQ9u10jyUAMGGM5OTkhonj19g2zsqLe1/TbmuZ2R24smcl478Nn5EXOx7/5hN1ux7zMyQ1UheLBw4f8vb//95nP56xWK66vr3h7ecnJ+SnnDy+wRY4jcrXZCKs3QJbnPDk5FfQpCpv4zatXnKxWPHn2jGGQmejVyQlVVWHyApMJb0YplQxCIOi0wBqNC56h7kHHo+s8Hryu48EbQimkCkp/K9XwgQA1jsjmWSYBP0rwHHulw/giSgxUwhC4vV7zm998yma7A1SC7b1ot+c5eZanXqhAtMPg0sSPFXc9bdA6orUsyyGEhOZprAGjImEYCDLig/fCkh76ASLMZwtOTlYsFkvyvOT29mYa5XLOUc1PyaxleXIBEVk3W8/nv3klroBtT24sVhtO5kvO5ktOT1bk1gpKoRVlUaA0tNudWM9mBbv1jo9//itm1YzFfMGDB49Ynax4/t5zZvM5WVHQtC03ux3aaB6ePqCcLVidnnOyOuH87IK2b+n7jtvbNft9zdXVW9q25ebmdpow6vuen//8l6kaT17hqMRuH6VfR3g6rXsRvBdZ8Fk1klBBJFoPkwzWZiJYk41crzyJPEmyWBYVMQa6vpW/TYmk0lDkBdbmoCS5qvc1wUdmiwVKG0KUZDNPiHSR52gl5zNLinRGGzJjiSicD1zf3ibt+BKd2RQTRl90YborbVDKpmREBHZkjdd31vmv2771HPqYuYys8KDFYMCO5gRKpSz2iHqfqtHCFmn279itTaLQ2L8Y+9jj34bg77C5i6KYsjExNkj2eilijL0JOGR6xzOqxxrzSsUpkzt2hvNRIJuo71bXwMRQHNW9hLRhp+fFGFHmYGl5LAV4ODYKn3oqk5qeCBVPCmH3N3UvoKcU9e6WFI/GMY3xfCiOBHpS8D0eQRwRjjCOHd477++6FjgK4vdn9++PwU1Z6P3PFMHoDGsyjLZYZQFDjJ6hD7Rtz369xypLaWc0CbotbE5mLPO8xCioSotRinJm0NaC7tHWsVjlmLzifL/Aq5q6X6LNgDYDg5MAumv3zLsKjMXHIO0k7+jalrYfaJqaGIP4GWtFm+Zc66bGJVVPn3pdeZaJAUPqmXrncIPovbu+p+80wXkII6IV6buOph/YbrZsd3up8s14f1iszSBKW2MfPa5r2W637Pd7XD8QfEjezKQFRtzdBhfY7kWbWimd+stekg2EPKa9TtafjrIqKcqcpZrz8OEDHj16SFmVzOdzuqFju99SzkqqWUU1n1GWJcuTVep/KzKbsVjMhbSWRoEAirKkms3JfC7VT5GDMdIbBEyqpiNJKTCOlTV3qu84yQEfkT/TNZgE2PBRYO0QowjWhNTGCWIKMupmRy3EtBAiwY0jtNMtJK2zwdPsam4ur+nqNmXLAlhnNiO3koCmhpK8/9ifMukeHeef1UjoGsdxGftYsualBD5GpiQfZNy2LKupRSYmQEGsO30gy0V61mY50QeGfsANHtc7hk5cAckLlBVFxbHdZ62lsCJTvFjMpKe9XU92oH0nwj3bzZbb2zW73Z4sF0+AUyJt39N0Hbas0DZnfnpBWc1Znp4zn81lEsAIEtt1QtxsmznG2PTaIX2eMOkNjJygw0BTTAgMKJ/Q4SBrifNDQleF4U5q8Sr0FOCNFpc5a7WMOZpE1DOyLs5ni6TrsIUUgLWRgJ/ZIhH4IpFA24gTW+ccxtgpoGepoF3O5xSZJcsPrczjompsGR336UO6TscnqbG/rkZDpVTJj9eK+nJMeNf2rZTi5B5S2FShjz9XiY2q0lnpYsANY1COaC0fdJTuM0pPWdow9PRpntN7n1h+Kr2eJsS7AVrmPeVAjLOD48HSWqehfjl5o29xnidmY4LQj9WERrGbMTh3XYcKgZMT0b8eEwnRchZ5x9EKc9znMcAfE8vutCfGx+NRZXH0WIwxOYlFvBNrxDuC/Oo+5JIqdHW3Im7aTlCHopiMO0bHrfFiCiFM4goCC6o0z3uXBPj1I3R3t9Ea8ZCEHbnrxbtue+NrqCBKSMtyRWkLTNREH9ne7Nlvd6xWN+A33LiaIXpc3+CDJ69ydvWG3faWzfoNs7LkRz/8AScnS97/6IwQHFnRo6s1e/cF89OSf/DhRwzuOU37A9p2R9tu+e//+/83f/In/5oHT1cUc3GWihGKomCz2/Hn//7P8Cjy2Zyn7z/n7MEZ/eDZ7jb0XUv0jq7tGJxHZbnIu+oKoyPRdbjo2SPjYE1dszGKzChWs5xFmYGR63y72bPd1Vy9vWFfN7huIC9KZuUCozOCC2yub5mXC968esHVm1f0bYN3A+fLFfNqwaNHj5jN5jx88Jg8LyiqBXXd8vL1W4IX+LaylsJkNHXNer/jcnMDRAbv0Ebz5PkzFos5z5+/x3K55Mmzx4wzsGfulKgCj5884tGTR3zwwYecnpzyg9//oSw2jlShhun68s7Td0MK6BWjPWTbddJXTOxkpTKUJmlTJA5HBBWENNcFIRkFDuOZJlVdmRVodHS2apJFatc0WKUpEJQuTyz34D29lZZeSMGhExYuWptUIbcpgTe8+s3n/PTf/RnXl5fQevKg0TrjtFxQlAU6jokBE8qmUPgIOlMIe1ng5EgQnoHNpdVIwAH7JJYi6rABPzgZW1Oacjbn5OxcKkWitASDkP4isDo5EYS0qmSGumnTiKOT7CJEnBHxrLrtEiFYxuy+8/w5q+WK737nA25vb3jzZ5e0fSeBOrnY/fyXv+b19Q3rfcOjx4/5nd/7HZ6+9z6Pn70PSlEtV4JoRJOqSE3biKiTHzxD54RbZTIuzs5ljWrahHS2U1IWgpw/5zy9c2nMT6xYvfMMTlqHwSfUMiUAmUFapWlCRkxdenHpc/sDHB5ToogUccYYlssT2q7lzetX6XxLgnPQMlBpvZLEQinNYrnC2AxrCyIyqbBaLnn29CmPHz3k+dMnZHlGkVlh5afYYYzBlCVaidaBsZZhGChSsaoTZ0RpQXamgpHE91PHDc6v375VhS4HRE0f+A6EmwIaR78fYexxO8yFf9mtDcbK8m51GZ28wOTDfjQrPjJXx220szyujoGjPvgBbr/fWzmu5mVG/mhU7qgXMyITx4SyYzEaqSbuHrPp8RTsA18OnmNAd4MhxnsBnfu9cznGx5D7mN16HyiKIrFtizvHbNLfNwnfjMeV+rvP+/E+vuvn417XuxKY42N+J2kIpP5fiVY5t5c3tHXL5esrmn3Dft/SDzIeE5ynHTpybVgs5wxtK7PNOAbfst5dE1SHUuKV3bmB9b7jV7/5S2bzgvOLJXmRUVY5JnfMsown7z3iu+vvsDoRr/LbzRrnPC5I9tx7h1IHAqFzjq4fklBHl/qZYvxgUh9P+routXwMtu+xWU7hPYMGqxXaZ4TOTqIj65s127qhb8VjXXqnnqYWYxCXnMOKvKDIcvKsICQouapmLOdzLs4vxId5vsCYDKWNmLMsT+j7QTzc+542mbcE72X/Y5JPVRbnHVHBcrVivkgjRilhLGYlC7dksVyyWC4oqwJbiDENQHTS/1PapzabwQ2eqDQ2z9CZTaY6gdC3DN7BoHEhYHKLjlren7RsKaTSRpJ0nxx8woj0+OTWmBa5MaB3fX9o16FQGKIxYE3SgfdJ6EQx6nf7cVE18px6u59+3tyuuX57SVM3RB+wKsG32sq4UbqH8NIjN2qcO092nRz1QKMIk9hEAJPkHhFkSfwgay2zeQko2rZDa0EBfWopGmspilKIgWmUbxgGbtdrXApqggYNEAIqRGFxp0KGVBF756f2XIgRYy2rk1P0fk+f5E0H59lsdvTeU80/p24aHjx+BErIv8Zailz020uTC7IRkXuVgxaA0QatDMvlAmstdSkiPdutkAfyophamc57Uc5LPAPnREp5SFK/MsUk+uuyAvqEhA24JO07TmQIiuEn3sEBJAypuMwww5DW7aPZcG2m545TCiOSGaMkri5xKfq+p5g8BvydtS+MUrRTwZaSMi9JyjEKPcbQEcmeWqFxXOUP8eev2347P3R1gFnHi/840KqjgHb8/2EYUvP/uHKLU0IwzoofRquQk5lu2GMSV4yRtpUxuON9UUpNkPpIyrjvdTx9DHUgko3biAB0g7sToEZofOwXT73ge3DzsaDFO0kZqdr+UkIhiSd9Zwjhq6xbD+Q3OECNRDlWbvA4HEYfNOmP9+EOq/2ocgbSjO9XXzRfFdCBKaCPj9+H3I8r8/G7ihrxPs8YHPzbP/kPvPz8JZ/++hOCc1ycXmCVxmQ5zjVst2seP3zAe8+fsd+sqXcbousJoeOTL36GtYonT8/Ick3f72ne7PkX/+Y3GKuYrwo+/PB9fvyTH/HgwQUPHjzg//B/+Uf8Z//476OUxjnPv/tf/4zdbsdidYInijVinnN6dorNMzbbNfu6Zbev2W53NE0j8C2aPBPhmBhEg3yzrdMxNRRFyWK1mqwQ1zFgCJN94uvrG5p+AJPhgiBbbuh49cVLQvD0fUdwgZPlCfQDpc64vbmkqfc8e/KUs9NTPvreR5RFRduIZOxu16CN5fGjJ+x2e66urnnx6g0vP/+M09NT5vMZTVvjvWM+nxFU5HpziyksJ+cnlFVJ1Apj5XPZ3LJYLnn63lOevveUajlH5+leDBIUI2ByjdUKY3P6zuFiROcWMiM9bgXdxrNrG3QvdqUx9TS9G0TjICm5oaWVlRc5OCeaESO65vuJ7CYQrKwPdV3jh4G+brFR0UeEM6AN/dBPFp7yJX8/jq3ZLKNtW95eXkIErQ2ff/wpv/qrX1BWM/KipEyuernJsBhJQkKYDEeszSZCnQoBHcKkejeMbbdEenU+JmJtm/bDMF8s+e5HH3F1dUVE5K/rpkmz3I7ZYsF8scLmW4ahZ7cTcaHLt2/JbcbJ6hTX97T7hpF8NwwDmZGeuUZY95kVbkbT9ay3O4wxfP8HP+Lt5Vv6X/+Stuuou5bbF28Y/MBvPvuC2XxOUS149vw9sjKjrCoWy3PKWclyeUoIQUiD3cBOGay2ZNoKgUxp3nv6HrP5jF1d0zQtn3/+KcYYHjx8xOAc+/2WwTm63k2GKmNVLVNDPhmuGBaLuSDBzX4aB5RWqgRw+fLpa5CK34eUxEkwbdueuhY5Wq1ldl5U3LS4IfqQevOpvYnCJu3+bgiTiE3f99MYKyDIVAyTYt2YQMeUOHadxpgsEagPhDw99tD1kchMemet1DQl9Ndtv11AT8FgDBZjpX2/Cpt2KvVp72/HAXIKePEQQMeKf/QmHivr8bkjGe24zz3uz7ug3vtZznFAv/+7MUG5Hwyn91fqy4+lzR/pUx8O2ajsxrQYjY/DIaB/vZb83YA+VlAjWaQsS2kBWDP1YcaLUdAHnUg6Zpo8iClVN/ZgFnB/++ug+GNDm3cF/jERu5NMRXFSy3VFdIr5fMF8saCazxi6XuY504VuM81iNScrLIPvaPod2/oWq0RNbnN7iQ89AxcUpcUYjzbw9P0HDL6nbjZcb97w84/hizcL5rMZOlo0hlm1QCmZH3UxcH17Q900knQZuYll3jXQdS273ZYQAnlu6b1UYsPQ4f2Aj8KRaBsZa6qqiphmucfRM0vETMhFZLfZ0TlHMVtIJTd4XAji0ewGscPc7OjbXkblup55NWdRzajKGZnJpELOIqvFksF5+s7T9QNvXr/BZjkPHjzkwfk5P/nxHzBfzCjynKvrS+p6z/X1Fd57Tk5PODk9YbFaUpSj2IrAnYv5ktViycnpiYx8xoB3QzqnUnkCaCWBGw3aKLLCSoBOj0m1KsInznt0Mq3R0ROCSIZqhAAUgwTqNpFjffQEn65Z/NS+ijFOojFD3ychkUCM4uLX+54hCNQ/HKF5ITXNnRXkz+ZiHNK10nuum5ab61vatiPLpWo2Rkx0pMKKKQE+3NPj3RNCkPE7N0iykdBIN6KMUck+B6lM5d7JaLuO9XZD1/dkeUZeFORlST84QnQTZ6brOrqupesEwcmMkAH7Tsx6IgcjkJjW08yIAExZlhSJwKyUousHqspwcnJK27WUZUXb97Rth8mE/Nt1PZthw89//kuubm4oqxKb5XzyyResTs/43g9+T+beC1EqnFVz0Rnxc+o02hiDVK1GpR5+LrB12/ZCag4RqZSTQ1qyQFUoTCaoq81yEXMqCkl2O3FMU1pIb3nOVN3L2obYp4aA92PLU1oS+31D3czT+iVchZFQNyIDImgjF+647voQ2GxlFr+qKlbLJSep9eGc+K57hyA2qZ1rrKVteogRre2dgm08T1qyhyke3tnU30KFfvyCIR500pVSuGFgsIeXGi3jSAd71E++DzMIJKOnyjBGYaaOxLUQInkhjj3H7zf248ee+LGu/Ng7P4bijxOB+9X0u4I5qGTjd/f5x1B7uPfz8TGKCeYZ3/t4P0ZCz/3fjwF9vDnv7Y48d8rZ7m4j432cn5961yMmHw9jHeNrHxP2YozkmT36LF9djb8roL8Lobj/85cSJiSglnaJipaHjx8RItT1nv12z+bmFo84k+WV5ezsAkOk7rfcbC+5unnFvMrJrOKXn/0F290tb9cXzGYF5xcLHj2+4D/9T/4zbtfX/Puf/q+8vP6UX734qQivdI6Lsyes5mc8f+87zOdLuuAICj794gvatpUxJmPIywxrNTF66mbP5dVbFssT5rMZtD394GjrHc4H2rbDx4iPSkazZiUEx9A27LZb1usbbJSbboT1NnUrI522ED/sXryib7c7hl5U2tq2pt7X7DY79ts97z97wtnpCVkSpumbjkxnPHzyEOcCTT2w3b7hZ3/1c7770Uf83u/9kJ/8+A/4gz/4kQTWGPjlL3/Omzdv+B/+h3/Ger3m6XvPePjwAecPH1AUwvDd7XZsrzY8f/85P/zBD5nPZaGWfqdYVsaokkS7MIQjMsqkM01e5UTUyCcjKnB4+uCm6z/rcow1kMaHDGYixI1mG0ICPty/ozDUyIfp3TD9TIhpHE0RoqZrWvpGkLx+GMiyRBIMh3VIa02W5v73+5qbm1u++PwFL168pN43VLNFIliJ0E3XCUJQVTKmJz3Ww/0Rosh/+hhT20RGB11aw7RStIPwhuo0kRMBtjt48ULaZWVJNZ+zWCxou562F2JWCIFNmi7o+x6FyLl659jvdqmikzVVqwMZuJglb4Dlklk5E7hcG5qmpSjKqVJeLlest1t2uz2PHj/i9OyMTz77lM12y//yL/4lRVlQzWZEYL3b8+TpM/6r//q/5uzsnEdPHnN6dsb5xUOyTHrSL1++YrPZ4gdP3/YobchMRjWb0w8Dm802rTdRyGnGJplehUnEQ20EjrY2T+u8Yhh6IgqlDTax2g9VtplUBcfXHu+3EEQ75OZmTde1PHjwgCzLmc8XjDPuYzVflkVy/ZTkezRv+eLly0TmU8yqiovzc7LkBUBwENOamucUZUnf92zXt4lvlR2KVUgVeYoz+l7gVgee0994hX4cCMYKfdzue58fk9QgJsH+VHWPPsHjc+73b4/8Y41RSUlOTYjA+L7H/ffjXv5xcD8mtI3PGYPYuJ/3g/L0utqkjOoulDwmAf4etByPnvsupbk7x1F9OcAlrkeqduIhph6AC/hSQD+C35FjpZWWEZ0oDF6majBM+6enQc7ELg4+6TGMqcHRbv01wfxdjx8H8fG43OctRARy7F0LQfPg0Tk203zx+Sfs95522IP3+F4zKwuKcikQpxvofIOLPdEYdJ7x3gfv4f0DHj8+oygyykpzfnFCMa9YqBVP33+Putmx28/oekffDcyKFTYrcDHSOccQAgNR5sOtYb5aUs4qAoG271hvbmnbBohst2s22w1tPzA4T9P2DM7Tth0oRVHOYRaIfhB2eQx0bU2z38PgwHtZbJSmbntJDjdbolLU+z19L9V827Rs1mvq/Z7d5pbMaB5dPCD4wPrmlqrMyW1GkxcEH/n888/Ispyzs1MhbQbF93/wA/7hP/yHPH36OI2zCXP3ux99xMNHD+n7jv1+x9nZyVT51M2evu/QSvHg/ILlXGxZ27ZJ9peCnFWzhch+pntWvBrk3I4iTpPDWLpOtBHP6q7viDHQ9y3ayTox3sMxRlwQw47tbkeMY9V93C5j6ocbI/eFnvqOqfcYRZ1yt93QtC29G1jMF2RZNrHnnRN5zsz3Ikvdt9ysb/jk00/Y7DYHroBWeKT8avqGGCNFVabFVir0wfVCYtIq9bdFxnqcYxbyl+z/2Hf1biBqjfcZfRfZbWJiWxsZn93t2Gw2tF3LcjEjzzLms0rGpLSCGLHaCBHZDeRZRlnmWG3k8aYV/kRrIYg9rYry/jI+J14Bb9++5fb2lq7rqKoZz58954MPP+Dho0cEFG8v3+JiILjA0EkylxlDs6/5k3/z71ienPDoyWMePX7M8+fvc3JywnK5pN7XuKSiaBor7ZUojPy+61jfrtFGU1SiAmiNkeo6zWQHDZmRUdDBSRt06Du8F3lWpRRiRzCuxQk18qNNrU/n2U8kuRHqtjajLKtp9HrkEhkjCUCeWOt9PxDTOYxAVc3TGh/I8/wQE7z4Oqt44HCN+5XlOWaaaBpR6RHFPkKnR35VlN65fPtb7qHfJz0dB/T7fWrSxUMiwsUgdoITaS3G6WaWfsJB7GVkrYNKXrR3Z8kPs4rcqUCPA4hSMuo2HpAxqz8O0MdBewzoY6tg/CwjKS/Gg1DA8Tjc3YDuuR/6DsGMOyfo/onq247ov05G4F5QnwK/wpZlktmNEgxlCZpERcZ9lGpKiTxljGg1wlFheofxeLxr+6rH73/e4yTqy2iIBJZuaIgeHj25YHUy50//NCNqT9Pv8ENP4z0+zlmd5HjX07c1ratTQM/RecaHH31AVWVcPFhhM43zDYvljGJRoUvDc/MB+3rHZnND1w4ySuOskLeAdnD4CEOMeAUqsyzmYpHpY6DtG65vrmnbDqUi6/WG7W7PkKC57a6hd56u6zHGcH7+AKMi0Qt5xg3Q1aKHPrQdrhNIVRtDOyR4WBkimn3T4pKUbFs33N7csttu2Nxc8/57T3jy6BFv37zkervhZLmkLHIya+najvV6y2p1yk/+3t/n/OKC84tH/P6Pf8w//af/+cTxHDGii4cXQOTi/Jy2bclyQ9s2fPbpxzRNzWaz5uz0jKfvvcdyKQF9v9/Lc5OQ0ny5EggeEowp1piEgMkysqKEKIgdqcUgSo2WfmgJwdN2Yuihj4g/IQWn3W6XVLqSr3e6N8druKoqMmuZz8T3PLPFtIaoRPhqu5bbzZqmE719m8uEwdjbrpta0K1BmMd1W3N5fcUvP/4V2+2WvMwxuUFZMSDx3lO3EtBXnKC0kYASghAYlU6cgIOwU0jBPHhP7yXJljaBw7lBLHPdQOcGuuT8prVmv90y6qF773n65BFFnrGYz0SEJi3+Rmm8H3Cup8gyqqIktxmZMQxNS991tEqLC1hRQBSi2ThH7Z3n1YuXrDdr2rZlPpvx4OIh3//BD3jv+XOarifLcl69eU3XdQxxQGlNXhY0+z3/8o/+iNliwYNHj/nggw+4+d0bnj9/zqPHj6f1dnBORsps0pAfBtqm5eb6mrwoUNaQK41VibAoFDIRwIkZIzfKDY71zQ3ESJlLm1AqaBJSEhGb0zCRBEOQezMkgh2oJAaWUVUzsiynLKu0th0krIUbpOi6kXAoZML5fJHOqbujoeK9OBeqeD++ITrvQeYaVVqvD+3b43V1HLu8m7weF51ft3076dfpTe4Ruo572GkHxmdKptpJ9ZdutpFRqJS6E9CBaWxt/LCjP+6har+rAHS8H9PFk9Te7o9THRPZjv/2OEBNr68Fcj9mzR/3/I8r3ik7S6+nv66nzF3i2P3njNXM9GSOw/dfk6VF6T0qtEg7GhFwiTGdk0jqJY3a9uOx08CX+/7fdLt/Po4fP/5cd/6vEtISPd47fv7L33D59i1/8ud/xHaz4Xy1wqgS4z1Ex8u3n4lpQt+hCcxWJaYwRBPpg4MhcnW7xmaGap5zu2v543/75wyuZ99sJKBvb3GDkGcKOyOzBc/fK1guiuSepClmlczjEglaUVQlHrjdbFiv19zcrhnJOovlHGtzTk7lZl5vthK0NPS9jMSkDI62afGuRxGwVhSqvJc+XyBd50oREtFK7GM9wQ1oAnlm0ESp6LyH4GXxIOCG1IeMRnqrTU1ZzXny5DEnqyVCBJLLp25qGZ0xcs5m84qqKvBJqbHvRHP9+vKS5WzO+fkZKkau375lHD2r8pzcWrp6z9A2qW8LWWp55akd1jdNkiUW1GhwHvyAIRCGjqFvJ+UwnZjfLgW6rpd+sBsGIbQNA90oqjIMosOeZWTWcrJcUBQlZ6dnZEXObDYjqjTXbiOqEGa68pp8VpCXhSj5hUChD4m9izIhsWm2vLx6LVVcleFVoHEtJqbJGyOIWOt6dNT0ISm4edmnWVHggyP4NBKHWGwEJaqY0jMOk3WtAsQ/WgKKR0HUOIKgHGEgRs9uu8b7npubK/oUoIxS2LJgOSsp3nvKcrHgwfkDmSoIkdwo5lXO4wcPmc9nnJ+cUhalSGYXBavlMiUQhvmsYLmoKMqSopyxqCq6pqbZ7qg3G7r9XgK6c6A11WJOQKGjwneO7e2W19lrNJqhd7Rtz9OnT1mtTkGLfkBd1ylhFc7E2dk5Ns+Yz0UKOC/yicGvxr6y1pL0JuBSW0FPRyKvmgqpCHHkc5GuJ0kE+24Qhz8nzPYsy4WRlCYTnBM9NrkWJI61riXGwPp2LahZDIkbMyPGQNP46ZrNUt/faoPRsN+u2e/33K7X7He7lICpKVl7F1dK4oxHa5EbH2OQrPvfbHH+1mNr43ZccR0T0sbfjb+P8cBut9YmpbmjDyWvfvg7phwmHWh/GMCHL73Xu5CC48r9eD/G7Zgtfz+gT6+dpGyPE4Lx+bzjRBzD2ubIKvD+cwROOUArXw7u8PUh/CuCeozJbGbsu4iU5PQeHDJA71OEV0efKX7zi+ZLe3SEcnzdduezJkc8HweG0PHJpz/n008/5Zcf/xTXDzx9+ncp8xzjI81+z/XbS4JzxMGxWsyoZmLiEVRkCI44BDonM7SmPGfoOr54+RmD6+mGlqbZs9mtJ1nWxWzFrJxz/vAppewdQYEtCpQXtniuwBQ5IUa2+x3Xt7e8efOW+XxOWZaUZcFsNseYTIKSEXiubTvcIJao8rnFHjh4J17hRqoQWbhkSfd+kPCcFnpJsPwku2lt0q/2LjF7BdojirKh9oagDMPQ07Ud1WzBxcW5sNhDSOtCpGtb6qYRfr5WnJ2fYI2mqWtsq/GDo287tusNbhhYLhbsdzvW6+3k1aCVwmrD0LZTAq21YXlyKl4BRjMkkhpagza4XsaJCE6Cm+sZupbdZi08GMTkpu1kJLDtGtHx1oY+qYo1+5q+76ib/cSdscbgTk+ZzWZU1qDiDFUJ4SqKsDoq0xiVoWPElhlZmaO8RwcJsnLvgnI9Q3Ds24ar9TXz+ZzlaonXgeA6LDZBvAKHDmFARcWQWgIheqwymMyguih2sRNxVtpZ3vd4n3D3CGpSmBjFZQIEkaIdnRRCShjqeodzPbvthmEYxLjKGowSL4vTecXJSrTcg/OEwRH9QG4Vz5495nR1wslyRZHnzKs5mc2YzaqDFse8EiW5ohQynhtEurep6eoa13UMXUfdNod7XhuUliq/2e250XoSO9La8PjxE+bzOVFJO3G3308MdFDi35FZirJK+h42tePiYYpnVExLAV1pk65fw0FITLgcXgVUSN7lPuKcjLyJn3rAuV5Iw4iw00h6886nEzJKiRuGfmBwA7udJMEqTUOcnOSCLrViPua9l+kOI71/q0UXvm1b9vs9+/2eRTrOx8jlcYF4iCFAENR0rO7Hiv6bbL9VQFf6LsN71DIfN8/dIFmkUbDxq+/76cMYM2rv3g3S6Z3Ewo+7fXI4kLqOyWVjkjD2zMfsqe/7O/s6QvBKjXKO7g48r7VOzNK7fd/p/e+p2R1X8CEKi5mjROF+r/1YdOb+Jm5ARwH96Gnj49Nvj19CgR+kr5SaM1gjs5MjvDix/1P2e3D9Gf9EH5pQfHWFfT9ZGacNvvLz3kcgYkwfLLCv12x3G/7Nv/6f+OTXv+b8wYLz83P+j//nf8JiPqfUlnq35+3r13zx6Wf86uc/p25qbrfXlEVBZu1UoY6SkKvTE1BRRrOix/khQXhzhtCLWUbjaV3Dx5+/5M31RirfKNrqgMxoa82rt5fkWUZVVGx3Wza7LVdXVzjnODt/PUF2SmkRFNGG+XyZRjlF379tO4KXsStrpLe5229pu47ey+RCMV8SUWz2Df3Qs9lu2W43vHr5gtxayiKj3m/QYcCHgaLIAI93PbteDIMWq1Oc7/nks4/5Xm75znffZ75Y0vctXdfRdi3GaMoixyaiUbPboxXMqhKzOuF3v/cRb1+/YX19Rb3Z8if/+t+K1XAS//A+8PjxYxaLJavVSog/RUlmbbImVZPiI+OMcAg0TUPbdcQobYp2v6He7bh69YohjZf6NHrW9zJSFJNm+2qxYDGfc7aYkWUn7Pc7+q7jzds3NLuOz6+uKIqcdr1msVry+OkzZqsly4sLVicLbGEZBRvmC+mhu3QvjNft0Htubm949fYV6HE0riDqQJc+d1mWZJmlqCqU1lMvPaZ7UiuFMoq8sHSNglR9a63xSbed4IneTe5hJk0EaCUJlsksw+BkXFGT9MQFUau3azpjaHYbmbSYzUUpzQ/46Oldj5+VWB3RhUEXFuIZq8WM3/noQ87PzsmNiHsNgySK3vVYk7OcL0UZcLHkxYuX/ObXv2Rf1zRtg+saThczHpyfoa2hLCsG7/ji9Wu6wbHvvUjdWkuzr9nvpDXz6uVL5nNhkhdlAVrR1g0hRjmWec5ytcInZETGydpkL6onNbWuae5MOc3nc0F6o9CEJT6M3BzJArQCdBRdBmUgl0kVm9mklie9eryX6j8VY1onE6skNiZtIkl4Zov55OMRgbIsEu8o9fm1qOPl5kjgLEGjxy3pY67XtHgj6My4L6gwtZ6/RYH+7XvoYxP/uCIbB+HH7c57J2gEYqL1S2AZYXWiQdnjSvn+nPdB8GV8/3cKlXAIusJkVXfm0O/0j4+q/GPGobyfJASD86l98GWr0a/dRsj8XlCb/s/dn8f9Pm4HjML8U0o6fj5AHSnMjC2M0V5S1KqCQP7pdaI6YtQnyNSPkC4HmUF1dNW8C134OlLGsXgN3FOE+4rWAzEQCVJBdzWXb19y+fYlP/zJT3j63iM++t53WC2XVDan3u85PV0QwsDLl59TN3s2uy3OOzKb0TS1QLN9h9KKfTegjdwIoz+0sZasyAmI2hY+4vBcr7fsm46h71HArCxE65uY+qIDZVGyWiyS7kHNdrOjbVr63lGUZVImNORFRV6IROb4GmKSM5J4PMQMZREIeujpnFDIorUTy7/tOtbrG3a7Hbv9lnlVURWSuLQqYo3CZqliT4paOljRw8Zzc3tN0zUsV0uyXCRXu76lrsUfPcustKMU7JoaYmQ5n2HynIfnF/h+YF7NcP3Ai88+k4Q9MzR1Tdf3aBRd20n/MEbKorxjMCTVkU+z9kkCt+8YOiEVhhjo24a23rPfrEUIJiXW+50E6/0+Wa16j/YPKK0hW8xZlAXKD7REGQtrG3abrfT1laJvWxmJUjA7PcFYTTkrMcqglfR9jbWYRIYrioIYI23TsdtbBj/gJ6ay8A2cl7nmLFhMFIMpUV8bUiCQWWutDUqDScmSMPeFcW60IqbHRDgqSS7r0cRFVOasUXgXiWFIsqfTzc7QtzgUru9kLQklBE3wDoLCgcD83gmHwRrms5Iiyzg9PeH87BSDTAnsd/uEBnmUipSFZT6bcX52xpvXr9ht12y2WzFVUbBczDk9vxCf+9MT2r5n19Ts65YhtFKpG0vbtezrmkikaRouLy+5uLhgsVpOBlYgRUCeC0LQe0e/l9jgnMOqkVgo69U46z2SnbMsBUrvhQN0vG7FCEpQMdQBPRynokwwU+AmhKlImtZiDkJp42z4+HNRlknBLU6fYQzoo4SHTi3X0e98bBscc7aO489dpDmh3keFH98m9vAtAvpxRR71gXEeQpgq4PGgDF1HDH6C1EdVLLmA4sROlE2y8KlHzaFHDaC0k6wpBenjqnp8/1HY5L5i23jQFovFnczoGHIfT/b4fk3TAGNuffhM49+MTmbj5xdhAj2p1Gl9ENIfk4VxX733E4x0P1Mb4RirxQ1ptIlsG6kCRtKQUTaRaRynJ2ecLFfcrm9pmo7FXDLItpfjbzOxAGz7TvrCk+RsIM9LyqpinNscK9R3bccX3rsC+zGZcEQrjv/2+OIdfx+QPtfqZEm1yPl//L/+n2y3a05WZ8xnM1bnJ2TG4r2IkyxPT/j+D3/AxYML/s2/+mP+9E922LzA2IyZzeRziGIP2ogrUlAKzQExCUpjCk+ZeZQOoCL7zrHvRGs9xAC3G0QtJU0IJEEIowRG897JOdKa2/UtemuEUQvoNCqT578mRhicEGlGA588z6jKnLLI+b0f/pAHDx9ys9mzb1p+8cuPqduWPhEil8s5i+WMx48vKPOMWZHT7La09Z5qVogtpBdpm9l8QZbnnJ2f4ELgzdUNby5f8fNf/hUXDx7y5OkzdLKSVCHg+wGU+LHn2hKDZ3e7wVrDxdk5ZZajXeDTT3/Dn//Zn/L48WPee/aU/e2a7fUNn/eeqppR5QUmKnw1Z4hw+fK19DwxopltDZnRlFVJGFpcF7m5vma33fLrn/2M25sbrq8u6bqWzXojCMDg0vjYnrIsWMxnvOka1m9f86qakWe5sNojtPsdoe+JbUMbIp9vNmhr+dUvf46ZleTLBY+ePePxs2dcnF+wmC+pm91UmSut6fKMpmn5+c9+wWeffcb/9M//Z25ubpkvF2ijaOs9MYp4q+tboh+IzslCnQL1OK9stSYzCqsjRkt/PM8VeW5ZLqWxE1xDU/uE/pHmtT3bzTVGa6pS+Bwyvi8KklIgBHwnsLDBE4nUuw0Nis2toswzzk/m3Fy+pl5fc3FxzsXZuSQUSrO5eQu+44P332c+W/LRd54zDAOff/6FrFsq4oeG7fqak+WMP/zxj+iSBepisaAoCs4fPMRmGU3TsK9rFosZN5sdH794IypxaLb7PevNmmo2o6xKXrx4QdM0/PgnP+bk7BStNIHIbrulaeqD2VVVShLoA53vCLTkZYnN7CTxPZvN7haOab3xIWCsIR/HdqOMkLZd0qzTmvl8hh1HghWpoAwo46eCcXBijqOS/G+WdPJPzy8E35svgMhuvyNESQZUCujBCxKnYg4xiBdEIpBWVZW059U0VXFyckI1m0t7WBlBGbQIq9ksQxmL8wEfHQeFg79++9Zja/d7yPfnmcfFPYYDSUxg46/oGYdIVEdjVUf93giQxg+mYHn8HkevddyTuF+1jxD8fSLC/b+dPgepT6MODO3jzztmWvcr+zEoH0u7jgFs+o6gf8cV7bt4CKNS0mRY430ivaUxQefIrYwttU1L1zSUubQSovcHFlyCMiPJVpLxYk78gCCSGD7tq0r9/ePPfD+Yf1VQvx/Q7ycCd/4fBerP8gyL5oPvfkjfd2K8YjOyvBDbi+SPneUZy9VKTECWq8m6UhuLnvKz1EtjTKpGt6JUBaffGhsAD8rjXE/0nsGnijxp6eNdOn6CeoTgJzu7sijIs1zmipPvvDBzEwNEmVRZSCLnnKcoCsqyoO9zujIDFSmqAtu0qA7qtqauGzAyQ5uXFZk1FEVOkVnKwpIZsDqyWMwo8gzXiY/BbD4jywvmixn94DF2TQie7W5LNZ/jnIzdGK2maynTGqKVyhGNd4NwCIyhKkseXFxwe32NUZrMCAypArjeUe/2uMHR7GuqskqCLkE0yJGEyhhNXmSoaDDaEpzDDT377Yb1zS1Xb15zfX3NZi2jUre3twQf0IhrWNM06Ohx1hCHgb5p6OuGzFrKQuaR/TBIEHByP/R9T1AQdhtinhHLHE9EZxZNSsiSZnxRiFNa3xp2uz2vXr7gxYvP+eKLzxn6AWvTPPwRVErwBCLDeL/bDLQiRp1sNmOyuPWJB5H6sRqsHYnDqcWFGEBl1kAUYmM0Bu/N0T2SoORpTZQkU6eiwPthukQNATfk+KGnrQNZZiiynLIoU8tT3PiKImM2Kzk9WzH0jpubGwleuaikKR2Zz2fpWpXpguVyRVmWnJ6fY2zG7e0t1hoenJ+jtOX17ZbBRxzikNcP/VTg1Ps9MUY2m60YeI1TEXEc66rJixx75NEhSOJBTdE5N2mL6HFNnlpjqd0Z5F6Xn2WKoO+HI2hbAvtY8E2yrOOx1qO/iJviirEyRpcn35Kxyh8r5xHmF4DlMKp2/DUVmhxihkJG4qw1d1DbcT/G/RwVVaW3/zfcQ/86iH0MhOOC7twwuaYppfAJUjqeQz/uh48Zknzw44AL/XC38nsX5D4euPvJwhhY3hU85fXv6ozfeeP/Ldu9RGN8f2sT4ePo8fsJhnNiKFOVBcFoGq2ptzt+/etfc3tzw4vPX1AWBbNqztD3uH7g8ePHrFYrVqsTirLkwaOHoueuxdK1bfbkec5qcTYJfLRdx9XlW8qiwGY2JQzpYj3ajhOX40TmXQH/220S/Kwt0AbKaoE2GbnJRNUqKyTzxYn5a+7QPmCsw+Q5Ni+wRSluZFMgPwroJEEGpFJPwBgiIh9BO1Ae5aT/rqwEcj30Uu27YcyeGM2lVYLDpMcmeulaG9AaNzj2dYMPcUoGlRHSjjEicdoHR+gcvVP86b//M37x61/w5npD3fast3uU1pw/eEhe5Zyer5jP5zw8P6cqCxbzijIzFFaTWY0G3r6WMaLV6SlZkZPP5gwu8ODZU5YnZ0QN+3bPq7evmBUVVV6xvr2lTiSdosh58ughRVUmMSTP+uoaIiyqih/93u/x0Xe+w3q95vb2ljwvyG0ubnP7Pb/5zW+4uRF0KC9KTJanCJSClwKtIkZH3rx+xfXVJb/61a948+YNf/qn/yvX11fSU033aZHnXJyfS6Va5BAC+81mEkpxuSR7PnkVBC/9+L5rD6xxrTAg5MS+52c//Ut+9pc/o6xk3vj8/JzZbMb5+QXWWvZNw3a74y//4i+4vLri+s0VxmgxX1EyTjcaGI1z7zEl1H1Cz5xL6mRehFlwXmxQ/YDuBeJu25oQAvtmRzd0SQddT66NJlX7OrGhNUzTQxK+IzHIvWeUvKbXqV0YAsSB65v1ZOO53TZ8/PELPvruc54+ecj7H77Ph9/5Do8ePKIsC6o0Urg6WY4vT1GWLJfL6V6/vb1hu92x39c07Z72ZU2MSaluGESqQwW2mzUuKqIVO9yLiwu2uy03NzfSAx8G/vk//58pypJ/8A/+ASenpyxPVzjvJTnIMtq+x+YZWVHISKe1bHdbmtuGPrVkrq+uRI7YavIsp0wVuUtKgSN6GkJgt9vRdd2E3o6EznH9GnlcY5BWStG2Lev1eooRs9nsTjtxhP6buiESD33z4/gyOpGO8WwsRH1CV4y0Z8Y1Sw72FAG+Yqn85uvrb6UUd/8Npor6KMDeGfPSh+B5HOziOwLICIeMr3y/38y993rX1/Hz7n8fofj7j935gqme+6bbcY/k/mk5VN16+rzHiMJ0bBNcRIjUtcMNA9eXl2w2G26urliv13LzlBUqQNe29J3Mkw59z9APlGWJtdLvmfX9UaWeICqVzGHSuRA+Axz83L46mTkO5veP828V1KNUs5LFFsIQnXpPydBDRZSyKGWS1rGQzbS1qToXNyt5OblRxoAex0B+9PgU0JUGJVa2KnhUHMlHSiospUjUZ0aREoFAI9YICdCksUjTG+kbp/OnYhI8UWmfVEzHHTkfWol4y9Cz3mxpe1EVs0pPPTcfRQRjcAN6UJgOCBaiwXu5Q5pOZowrN4DRKOfwIaKtIcTArt6lfp+iK1u6XERWuroRpnny347eQxqXG/oWrTRFllFkOUWeT0S1sbUwDAODc1xf39C2PWgrRkBZxqgMRzpWWgU0gevrS9a3N1xeXnJ7ezspnd3RcFAipCFkpaR1njyjtVJEH3BGuAg6BfSQCHcjgUlpjcqMGBAZw9B1tAlN0MYQfaCZzQguYIxhs9ux2+24vrpis96Ih3o0RCcoV9Dp3ActlwxH93dCbNRYRJGY+q0QGyfCLaJ3L8RCPyF1iaQjyY+RnrrwW+6uDZL4H9ZFRRL3SgicQhjdPglJKUZdc8eurllvd2x2W7a7HWenZ+QhIwLGamb5jOCFjKa0SvwAme/u+1kSxfFTqzNEkUSNCmbzGfOuZzaf0blAFw5tRJdY3rbei7gO4mS43+8oq5JTe4Y2hqoq0cZOxOosOVmazNAY4T2UuWjoC+qhEqEPMqWFkxXSGpb2Ub4cLk0TaKNFWS4Kp2FMApQW+F1HWZfHxEClBM4dvQZA8OIAKCiuICXEyOjefdxCVel3U3E4LY8jCXlEag5raPrfOwvKb7q+fuOAfqzH/aUZunvw8ggJT4QRe/jbePQhhdhxP6CSSA0pOUgQuD+q6o8hjWOiwf1q9371PX4/7vEeJyHHzzn+PXw9Oe5LScRRcL9/7EbIfdwmGFqyoiT63/GLv/orrq+u+Omf/1T69CiyzLJazCmygjLPOF0syLOMTz/9lN/8+lesTk7FPvNnBVmWcXZxwcnZKT/68R+giGxur2UG1DvmyyWnJ0uR96z3lGWe9lOlHOAuQe6rgvlvV53DGISVKtHaUmQBoway0ahAZRLM9YDWFmMgWI3NIC9mVKX0jUdLXlSa6FWKgMxvRsb2kD4K8qnaSYCTiR4IhGEgBk829BLQB1Eyww/y12NAVzJvbdPsLkA3eHSU6Q4fR2EkfYQYmJQuRYrZjMW8ouka6mZP5wY8sDo9xeY5WZnjCLx48woV4eNPPiH4gTD0DF2N61uKzGKNpkvWwY+fPmE2m3Hy4CHG5iibkxUlX1xdUxUVi/kCHUCHyOliybysaGsZX7q9ukJryFK1sprPZJa6qmSx8oE3r9/w8cefsN1uRdd7W1M3DV+8fCuzv8YSgLYXedOmlfnd6ANKBQxees06OSJqw/nFA87OzkVpC+gTfN53HX3bsdmu02y3T+N5SCKl9QRfj8YXTdskmFaqWpNnnJxf8OjZeyg6ousYuoHB97xpX6GN5nP9GSFENrstXdtyeXUp5EIfwTu6Xghx8WghFrKp8HlkWqDEZJayEJtik4kJzM3NOgUDT5s4Nt7LPHTX9wLPJzEUFwIBRV5VuMGx29VJylQ0y3NtBF3IcmazSsRQ0r06sqiNVtLOSGYtu52cp77rePHmkt988Yar61sePTjnv/1v/lueP3/O+8+fU5Yli3lB2+/57MXnVFXFvj1jPp+zmC8o5xXVYsbZxcUdFHZM7vad52azw8xWvL2+5ePPX9A0LXW9Z7dbc319ydurt6Dg4sEDlsultDTcwHe+9yHL5ZLf/cHvSPXrPCF6nA9oa6Qnnmci15vUQi8v306jYL1qiZVUvT54IRdqLdoF3tG7XqxU3TD2LbDGTiPTgoxEMbKRVU8+VxR3QxUU292Wrm+ndS6zmYgepeQ3JFEgb4Qrkid/dLmmD+JFo16AINE6jdsl8vNxVE/bWCCP6du32b5VhT4Fz6PH0n/uP/sowI5fcdrb48AatLojGzvyDsfgHu4F4/uV+FdV6PcRg+N++FcF7a8K2F96f3hncJuee++43TmGSEC/ExTTX4mIwS273ZZPP/0Ntze37Pc7qUhQBGdRIeKzgTA41DwJS2gtSkTO0QeB7Y0dBXE8282GvMjRNpOAZEe/3tFK0Byd32/ecfi6JOcb/DVERQyK4DVgp96+vG7iU0SprIWNL/aGxlpMJvDeWNmhSMYeKk0JqKlilznWFGBTy2GskBQmVTVa+vUo6YMSIXjRV44Bg6AFGsitBNQQESEfbQRet5aoAjbLiRF8OGA9WkkzNSotLYDkH62MCFGYLBMjGGuJEZT2kwxyiNJzdD5M9pJGq8nXfl/X+BAx1RxtBoJqMVnLrnPkecGsqFA+okNgO18yrypmZZVUruQzFZklzyyrlCRWVTUyAnj16jXb7Q6UZr5YoqxYRu7qRsxgvCgnxqZFO8cw3uNRqnOjApnRZEZTFFJtlUEq17IoUErLFEAQWdG+a6mWc9wgKNVkIKRHa2WpgFzyfbBtKQlElLFBm2fMlyuKskLbnLyoRH/+qC3onU8Kigab5SwXJ/gQmPuDWqLkEXH6PmpTGC3Xo538D4TvEkLE+UDXD8mMxR1N0yRibPosgw8EPLoXWWylLTZLr2v0RKLMs4y8rOR7UUoVm/rTYu0rhE2lNTOgnM1Ynp6w3+3Y7/csgyZGzXvvP+PBxRnVYo7OMjrnUc5RxsAQA733qKFnW9f4tO7a1FpSSlj7Rlt0jKDELa7QnpkPnJ2d41Dc7mtCuOb29galhQzZJJW7cexxs92S5RkvXnzB+fkFq5MT0Wk3GheivH4q5LQSxG5cH6uqwho7FUxZJha/ucqmIH2sWpolUrBSijIx1Mfx6hjv8rBCqvTHbWx/SlV/n40ep979yElRmcXqA1F8SDa+Y+9f9AJGxDq93r0idEKk7xRMfKuY/lvap97dEX3UJwYh1ngSk1SNBK+7Oz0FghinUTat9TR3fajWzZ3Xvl+dvytwj39/v+r+OnLXt6o6j4L7O59777XuXBAwjT0cIxZygTn+4qf/gRdffM4f/6t/Sd/1PH/6HkbJOE697XldN0KasjkPLx5wcXrG6XLJo4tz3rx9K5rVvXz2yzdvWV4tmc0rzs4veP/DDwWKn89lVKRtKQvJ/Ed5yW8ToI+Tmm9dqUcFGNygpE3t8xT65LyLY1EAr4lBo7BoHTDWk5cV5Xwu4gtwmBlRRoJ2csEKMg95gNyVkuek6lnCeBL0SERObzticASbSUD3PZqIVdK7NEqRZ5bMirGF3KwZOkBRzQiRFEA8270wpAOIFayxDBFa58BYMmMplE0VWonNCvJyBiiyrEQp8VAP3okQS9swtC0xCJowjju1/UDnA6rcE1Dc7mRRdonhbJTB+IDxgcIYrNa4tpdxsqEDYLWYk2cZi/kca4RQNWpcZ1bYvr/zu7/Ls+fvcfHwMWU1Z9+0dMPA9WZL2/dc367p+p7tvpH73iiMkmMn0PuhpTWqR5aFCG6MRDerk8vb0NE0LbvtnpgCwnhf6SR72qfA2SUp1lF2Nc9zXAgMLiTVs5Jxnby9uaFpWzYbYdUvTs/T4l98KZkdyUrey/3UDYJAdK3A6W0rTmJ93+PDIOOBw8CubZPuwDC+0GFLQ9N9YlI3/YAxlqoqqYqC09WSUZzKJvcvQQQMuZEEQpvUloHkQy5OZCerFefnZzx79oTXb97w+vVr3n/vOY8ePOT3f/QjLlKlHbxnu69pvENXBa0fcFrRdx3brsNqEeyZzeYUZcFqsaTIC+EVGI0mw5pIZgxzY3mmM+bnpxSLJf/hpz/lZ7/4OdW8YnW64vLqOhnQKAbX89kXn/P67Rs+f/F50nxfUVYVRZmnxA0GJzK9Kk2r7LYbgg9cXDzAWkvfn0rPPKm+jUmieBEkSd+6nmxnQwgTSS/LxBxl1K0f171xUut4a5pmWtvGpGCMRSHI6GVMqOq8KtHMyIxM1my3W25vb9mmMczFrEJl2dTOOFaLO44N4/e76/DfQg/9Dtt7bAvc6/OMj4WU+R+0zg867MGHyTtWXmtcxMfgJrs/BuPRqe2b9NDvP+9dP4+PfVUgup+NfRXU/K7tGwW21At712spYDGfcXKy4uL8nKauhWGdkh4VxZAhN5Yyz/HDwHazlsUwz6nKAqMU+7aVm1wrgnO8efWKYRgoZzMuHlxwenbK0Awye61Vcv/66nbC/WPw28Ps914bkVyMeCH8AFHgi8mkRiX1uxjTSKOWRdtmWZqkECEdgUYPmS9qnMOXynj8nfS0TUooJKmQv3SSPIYgz/GeEVkyRMwY0LWIHSkj1TUhYGwmLmpZTgSpDJ3DdEPqcwoUHJUoa6HNpJo4RI2LJARBo02WkAqTFNkUKstQscDZDJflDF0jY4apl6qnyrQkKk0ZNC4EokutpaiwmSHPFSpVqd3Q4QYh/mktrQgfA7u6lvdVRsbNAO9rvA8sz87IZzOCySmrjtvNlqbveXuzpu07bjZbhmFg33SJHKTRSJUuDZHDCOeQzFkyKxB8WRUp+VCEKLatY184+oMRE0ilrpBZ/pBaVNIKFIevwkcxy+kH8m4ga7qp971vOlGeC+ATQ1Sh09SFRpvUx5/0xEVBMOooqnMYdKaI2mMCYDxBG1QQAmWwPXmaJhih2RgO95ax+sBrUQqb+sdFNaMoCrJyjtE6tRYkqI8BPUsth3GaxoxTK0pUCm2Ro7KCoDPK+Yrzh4rFyRn5fEHrA+t9ze3tmrZteP3qFXmW8bvf/x28c9zsdrI2h5DIjIqyrsnznPVWVAIF4tcTeuHRDAG2A+z2e/bNnizPePrsqdw6miSUM8j8v9GH0c4iJ0TPq1ev5HWtmpLswQ04PzBfLCmKkhClR+6TaqIw9uOkqzEkvsKIgtytrg9j0+OILpC4RjKNMQyOLhErxbhFVoTRHneMCRKLUmwIgdyalBQP0zkayXAm8QGK1BbJU3tQH7HY77eJGZGgezymsaX4TbZvpRT3rqCp72UbWmsIgWgOjmd1fRCOkN7DIaAHrYhJI3mU4WN6L4XS2R2h+m8Cix/v7/3H7gdr+HIVPcKkx8/7ppXrWIH8NpvSmqfPnrKYz2jSeM/Lz15MtpBGKaq8YFbNWC6W7Lc73t7csJyJ7vLZcklYRMLbS3oGgbGc45c//xmr01O6vkepH/DR73zEvt7TNjUQiLlPRKa/mUD9DT6pfIvQD+ILbYwsFrIfIYl7CBysJnxcZqdtnpOXBW7oDnFXHW4+gUb1FETjCMujEBUjkyD99DwUSjtIs6UxOCHEBQtBYwCrEEtHDcYKe11bh46QFRFlLbkPgGa2XNH3jroTFrYbWz0KMBkqKyhmM6zNGNiB83gMKmq0lSpAJ/5JpmW0qcgsYegIQ89+u6Zrm2Qx7MmUlXn8+QnaWoqFoADruhGjHx9YlgXLsqDZbeiaGk9gCI6qyMkySzmbyb262xN8wA+e5XKJzQuurm94c3mJM4ZdP3BydUtWlrx884Zd3fDy8oq2E7jWeU/vfBrrspMyGmkxHWHIvm9F1TCK3WdVCSIREXMjHxzzasZqeUKM/k5BYY2eWmghjRoKqpFhjWVWVkmCtxW4mKMF1BzId6CSumrERI8xJJg2MddBEsLUJwsqJ5oIuUDPmS0wMaATWcyHQOYdqmukRRJEmEhMW4SbUiSYfCpYlCazVma984yiqlJAN+TJCjTPc2yqLk1KBrVWk6qhGi3mNJCVNA6q1QUnD56K8mWW8fJ6TXh7zccff8zN9TX//t//ObNZxX85/Bdk1tI37UTikyTEk9nEWTCSaI0eFTYhBTYrUTZD5TO2+5pXby4pqoKf/J2fsN1tqZs9eZ7aBEUGCm5vNoTgKUq57v7yL/+CGAODHxjFeVyQNeH58w84Pz/n5GRJnud0Tc2QxHtCTEkh0PWHSatxnR7HnO+2PKTNaIzh5GQ5revDMEzEz67rpr8ZK/+xWO26Q+IYYyQ4KYrq/Z7cGvLMkuc5WZZRFmIzexgxTkI16rhCv7veTpHjfgD524Dcj2eLQ7wHed9/f3V3n6TX5SbHtOj8URA9uIBB6jUeVYL3E5Ovqw7v96vftd0nuX1VUPdfE5Xf1UO/2xNX08m5//t39dDlbwClKPOCOJvz8MEFVmnevnwlyG8UqRujFH4Y2G23+F5G3G5vb+j7nmVSYzJKrA1VlCwz6oIYAm9evSTPM8pZRVbk4jwVZU5djAAg8uVj+K4WxbuO2bffDn9nTLrQE31MWpnSh42JjCYjSTpVmxkhiOHC1AKavos1adSp/5fIfihNVIaorCACQU0jZjpqgdiNONQpncbhxizfJBGRpEAXAW0ybOrVK+dRuiUqjclyMmUo5zNCELTBe48LHheg7R3oHmMDTSeObLN8TlZUzOZLlBJWLlG020NQ+ADeRfwQCEmkvB8aUdbKhR/RDQ4dFWSFxKoovdistITgqNuGEEWEo5iVmMyQGyM9aSOVl82zZLaiCAq6YQBjqBYLeh+42WzYtD1RaV6+fcu+abnZ1zgfJravJ7XOnLQxxjFVhabH4HWErEJZ6XujNbqayXH1omEf/UCHZt1000zyiG6ZUQUwVZSDE7jUGhHwqZOgT98JIUqR+t5ao8eesDqyRQZQAwphm4+znaJlKAQ2IbLda/NJSXW4p5USYqS2RIWosmlLNCLJHGKUNghadBRI65/RdB5c5+iG/SQwYlJveQxOdlR1VCPrPaGb6XtAJFXni/mU7BR5js0yOaYhcHNzQ9s2rOuGuu/5F3/0L2XN0GkmetQPAWxCCkZRlPFez8aAnhcok6HzGYP31K0kVgrFvtnTtA1ZJlC387L2Gy1977E3bfPR41xMTxbLJU3b0HYtGsV+u2X2e99nMZ8lRGlApfM/9szbrktywfV0bmYzQTxGqP24ZXsc+Edp8Lqup9+NI9Sjxe047jbxL7y0Ukxa90II9IOQ5MRQKZMRt2GYZum73qfEdXanOp94ZlN8OMTTOxHlb7pCP2aGf2l2+14lDIfFPsaQiAHDNIdOyrZ1Irkk1FM+KHdJd/e/jh+//17v2r6SuPaOYH7M3g8+fClR+arX+NLrC8IzPefO9/FX6u7ThdSlqMoKoxRPHj0mN4Zf/sww9EzVo1FKDBK2OxnxMJary0su41vee+890TlGkVuTEgtDpmTO84vPPqNuajb7Lb/zu7/Dd7/3kVQWPmBVCm5H6MTXBfSvCvK/7SamHhaFI0ZwA3JdJSCOsfBWhiyz5EVGP2iUlyREJWhdvktAV8okcxA7Ve1RWw6scwU6iQ4RRT1uJMbpQZKbGBlRep16mqJK5zFGemLa5GjjwOxQKGxeoLNIlUapYpS5f982DCHiO4cLHdo46rYnRsXypCQv5yxWp4Cirmv8MDC4gA/gnFSNQ+/xQRGVpe0c/TBwOluibU7TOXRQlMWcoEW5S2cF1XxGt71lu99TWkWWGarlLI2ryVjYOImSFTnaBqIaCEpR9z3KWhYnJ/Tec3l7y67t6XrHi7dvabqeHlDGMFssBVK1dpIYFtJQmIKS1xkxwdaTXKbW2MUCSBrjwYu86zCwa9ppvRmvt1ESQwqEQD/0h9exlrJzkki5A8FtCorWptlgSfJG9cRje2atDdZkEoCDF2e2I0LduE0Va2qfKCMNBq/tFBSMzYnO4dOMNMh9XtqCUUkzAK2PhH7AHflOaA4aYQoOJMm0HyEFyYCfjneWZ5RVIaYgu900fz22PbOUwJWltOz+4i/+AmMti5PTNHfP5JM+tpjG5tS4H/k4rpnnMkKaVdg8p6hmSeZXkseu75Ijmma9viWEwNOnz7DWstttJdENgTzPWCwWnJ9f8ITIZruRGfTdntl8xkcffYc8y2jrrRzDlOQU8xk+eLquk9HD6+spLp2dnbFcLr8kSDaev3Fkcuyj7/f76frIsoyRNDdW6jpxOwS9SQhUfpiDj97RBS9clzyjbVv64WD5O3Qt4vOwmGbTp7Xz/hI67ed4zX+LdfSbPvEO4SwcZs1HY5NxnCzGOCk4jZmRFE/HM+mHecWR8TdB9upOSP9SsB5PzlcFl2Pp1/vB5j7x7V1fk4COD3/ta3zVNlbb7xLAGbP5O/ubbiRZeDRaQ13v6LqWBxcXbO2GF59/DiEyRHEGGnrPkDLocd9vr6/ompr33v+ALM/ZJa9nU+SU3lOUJS4Gvvj8M2azUuZBz8+YzRfT8Y93jv83q9K//TaSMKJImCrLYlmISEwYkqNYQwwRnWwl1XjgggSkPJd+qXMSqEEnlEGjTJaCd5Z+tkgD1CamucHHmIK1FahPRVQMRJsTvJLHEYa7tL3VJGoRoicGA160vFHJelbJuJzNckKErBiTYI2yGdFYqiKnyC29c7gQyIJYQxbVnKKcTciANgUKi8GKOAsRgkIh8/d+GDB2j4mavJyTZTkuZR5OBOzwUT6rthnFbEZuIsr1coydSAGLUhy4pKDWp7lbU2QUZcVyeSJMdueJRtOHQNQalWUsTs/Ig8cr6R0W8zkoTcDQu0FcubIMG5O3tLGoVLVMo2dJItouloIW9Z34EbgBkwco/R3IXUFSCYuQ2jWqE3JSUAqvDS7PZeHVgTzLRI3wyEAoAi4eFtMYQYUkDuMcPircmNgqOR/JnytdunEit8YI/Vimg/Tx8zL1ujU6RGyImFzQJJUQnzwrJob6GDx0jNisRNY9ku1qHFcUaWVGaUkcB3QfZXwrqMSVKHJUXlLMl1OVOSsKkahVyHH2A0pnPPnweyglvJBRQGmsKgfv6N0orBQnqHh0A7NBzF3arcz4Z4XwILQyqQ/u6IeeCGS5BRSb7QalwI/JSEDIeNsN9X5P17ZJw130OPqu4+ryklkpIlJaK/b1XnrVRWKxwxRjxm1U5JO1NxzQ4Xj4/TAM7NKo33a7oyzL5D6nCUEnDxBRiTTmcP1IYRoYlIxbDsOAUakoScYuwCEJDOFO31zfizlHTeG7iPdRqPkbr9APDXvuBKiRne7UQafbDSJ/GOK40Kk7WZJIGo4V+t3++/0KfbyYv65CP37sfqD/Eqnr7h/dCeQHmcC/7lgcn4J721huHz3nWOkuRIHG7sAuqHRFJuclraRH2necnqym2fTghIjjXZB5S0jz6ULI2K7X9G3HR9/7Har5nD7NYBazighU8xmXN9e8efGKk5MVy9WSajZjuVwlbeq7CkaH4334cEqN3//69sa7Ds3R8iSwXiY3wWwmvafgFd4p+l6kD9UobZeCOVphrSbLpL9oRmEZJVC7UkcVuc6OKnSLUtlETFPOgwoolSx9lQh0RG+nQC/7aOUlkt+xyYzITEZPmOp8hdIx7YfGZBkqKqxP5hzGyqy2MiyXc+azks1OTFjsIMckLyuyvEIpeV+tM5SyaJMntr3DZml0SGmc6jE2R/tIlldkeU7wkag0qW1OQAI6WhZbkylcs8V1IvQRkOo8KpmHjjEyBC+kpTwjq0pmywVtPxC7gcF7qWgTfD1bZZQoos1QxogeN4rBQ+xaohcfBqst1mYildpLsm/zZDGcBD7sbJ5abyYFdOFQKOK0liju3vuh7yeZ45gStKC1BHQf8DpAVZHNZtM90rtBfuclgZlMn0AIg8Mg1b0/QhETkcuMXIy0jg2pdz6aP0XnyRPbWhZtjRnbBKP3hIxvJHvR0eI4EJM50KiVeb9CB5J2ucjR3g3oog+urJmu0ayaQYTNZkPTtlTLFWWZJxtfz3a7wVrNxcMHALi+k0TBe4ahZ+g7Bu9lTt4LpyTLMumlx4iRjIZ+cNxs1lNSkOcFVVElRzKRUg0hslwtsMaw2ewIwWNtaoMF6PtO3Aebhr7rmc0rIWQ6sfK9ub5mMZ/x4MFDtDZ0yZFtlkhwqDGeCDcixuPrJE6F57HYWQiCBjVNI9r0+x1KiSRwSMndMIiWPQi3oijKw3oODEThSDiHtiZd44fRuGm9j3GaBNP6yBBrXF8RE90pZLwD8f6m27cbW4tx6n9IhS5iAN6PMLWMlwx9h/dBMlQlDL9RiSeGSHD+EBjMYY546iKkhFfFiLGIoo8+9NxJEOy4jb8nKf/Ig2oKBsJsvAeNp/dMqd309yoxG8cbVz52lEUDpj7hncOiRihdwpX8nGRHo8wjj4vElBbFmNjFws0aL0prDGQ5Dx48IvrIH/8vf8zt7S3X19eUecHFybkQLYaDxntRiV6zyXKMsfzms0+pqhnPnr+HMpqm6xi8ox0GjFI8urhg6Dp+8/EnbLd7licrfvf3fsjp2fkRenB0qKZ/DoftbssgpmAtycqYNumUnB2nCerob3SMUrGWFatFQZZZvDMMg8E1mVxXXiwFR81/QiAzRmbBp0VWahmB2mUmHGUgVeroLAX7DLSMrWmNiK0Yk2Q3kevFGhQBb8bXTdW5SSpaRkQvlILBOXxw9N6LjvnI4s3FVjF0vQSoLCMzBl2Uom9uM6JqCVFjcrHi1HkFJmdbdxAFTs60psozBu9FEdBqsqKgaWrqtmXXiC3qsu3BiJhKVJrOB7QLeF1ircajpdLUCvKIMTmZLtDOEYYhTRTIgljN8ymQ9d7z9uZGxgSXC7QT4Y/M5ERtyFD4CLt2wKU2ifSpLRbNDJ103S3GSEClbRnSXK5SCoZO4OpyDkiPVYUI3jO4AT/0RG2BMPEdRt0EVUiFHnMJVGMPPM/ydEPpBH1bsAavNWTJR957YkAQhxQEMBEyMUIy6OliHXvj7h15qwaKmISFQ5RKDdHWGJwTEpvSZIUkm971KdjJIq6s6C1YW0lQVGNAj0l2lkOJM1aYY4U+fo+eLM+YLxc0bcNmt5Z2nM04reacJOa6UjD0A8pGHp+cAtD2QlgODqzNKcqMYnpuj+8HhqGb5sK1VgK5K401lsx7VCHXcGbzdH9kCXkdRcDGuBEpok3ku57MWs5WJ+x2W7b7fVorPWfn5zx//pw3r9+wWW/4Z/+ff0ZZlfx3/7f/jkePH3F6ckogsl5vZem2hjwvODk5nYrGqhIRHtGBd+LoFwJZJojcmODNZnOUUvRpfHBsr4zBN8vyxAPQaZpC1nbvQzKXEaEbu1pSVRXzsqAqRCzJ9T1DJ5LSVVUeGYwdOBdjkfN1213M9Ou3by4sM/0vha4JSh5lXlOADx7nkwlCYvTlNj/cHCHgj183we6kSmEa8Yjygc0YcI+q2CkIIzdiVHf37vDixzXhO/rc4+sdsw3fBbEfvxeHr+MIJcGMJLwwJihCjgtREoFwlFAIdBYZ0cPDbokW8GKxYLNe8+btW9Y3NzR1I2iGMSnZSPsWQrIGLUQlTClubm9p2pbvfPdDjDXs2ybN9op+8Xw2wznH7fU13TBwu17z3vsfsFqdpBlXUp2QUpT76MjdC2L6AN4NkzoSID3mlJ3e/dtDp94kVazMKjIDBEVMI08qCc+MMq5oqVmM1lhlMErLfqb++Lu/JLhrbVHaEJWR3rIW28iDTrcE9DvmCOjJwW1coKZxrKTtHZGEzYeQkgeNspYkWyYMeyNKdyZPpCutScNwaCtBT5mMqA1d7+TchoDO5LkBGLwnyyQ4hShjWc6nL+fxIVKUFWiD7waiChTRgI4JRzCpiosoIzagmNTaUH4sa8iScluMIkPatS2mKLFFQdDihqWyMqEeChcBtyf6iA8qLfoZJtPkSk8LvNbSuzYRghmm/rMiJeSZvK8K6R4KAae0BIOY0midbIFzQVWs9egQ8EpBSEE1oQvCJrZTghq1kXMx3r1OIF3vkriI5DSTyp9W5uCamKhKgq7J9a4QlvlxELbImKXyAfoB7wWCj8Zgckm2cRaVquQIaJsCuIkHtJLjgK6m+2eC+0Ma2/Ih7ZenKAsWp6eE7ZpY7yErMEVBaeR+6btOhIiSb9Pi5JwQPNeXl2KUgqA/tqhkXC6zuE60y/uuFeIsSSnRSlC0WqNjYDax7/OEkKXE1mhZMwM0yULYRo3yHtdETF6wPDsjKiXeDVpMjapqxsXFA7abHbvtjk8++QTvPf/4H/1jFosFj5ZLfAhcbTZoo6nMDJtczWI6RiMCIpMgdyt0Y8aWrLhkOufukOek+JLfG3Ng97tkcqW1eKJ3fTfpuyukis/Tl4JpRHskfZu0th5zqKalX91/4Dgm3Ftuv2b7xgE9z8TTPCq5uWxmBGZUAjVkNiNgiTGQldLbGNmBPvUvdJ4BEX00lzlWcWMFrO4h3kPwuChjQRqBWdGgsywtZA4/DHTDIJCH0elkjjPH6SgdFfXqKCJFLZlyCNJDVSljd8EfkguVAgojr/RucuFSD24YhHU++bEPAxGweS43oJVqJcsy+q6ja9uJTh+jQKD9viW4gdPVOXjF3/k7f5/PP/uMf/XH/4quG+g74SbYpHOstabwHhMilZUFb+hlvOmL168oq4r5YgHa0LRyU/XJAEahuH17yVv/GqMNFxcX/MFPfsxytSJP0p/DMKCtYT6fpWogTGYZPvWH+n6g7Vr+x//v/8jbt28ZekeW5zx//j7LxYqnz55RFiJoU+TiANV7xxAcb794KQ5HpD5gqgSqIpN0yPcUecZiXpFZS56XzGxJpqyMe3UDs0WJsRl159MEhpPIEMU9SiGV7XyxFEGN/R5lLEWVCaYQA23XoYjMC4PKMwpb0XcN23WPyLhm4uRFFHZ8VBSzEltmuM1O4DelUBHawYE2mGomfX2bTddM7z3dENDlnDKrBDnQGhcVwQVs6t2b3KK0YiBg8ozF6QpDIKrIbDHDZhptRa4yoGi7js16i85yyApxBXMRk1lMVkhVERUiR+LR2YCJnnLeo6PHRo/o9R2RXyP4GMkLCeBBKRwe7yU5NUWF0ZbT8xU+wjD4KehpBaZQ6ecgqInWVMsllVLTLLVP8KXApRGljASs4CmKinJ5Qt/L7DhBQquyuUjvFqJ3kRcFo/e6QiefdiWCRFpc+VRRoDJLPQxEH4m5JM9zW0CEvhVFupiQtHbwZFVJUZXYZK5Tp/n/4AX+z4ocozSFkjZB7HpUDKA9RaGo0n2i01z6ECNO2WmBly6Rmg52VBB0GvsdIX+lyKxJ5DR5bki9XZWS5cxooopctz3RFpw+eW/SRR/74sHkKOcgFwVApzJ0lnPx5P0kudtgtCYzFlSavc8s6IA1ZZI+PiygMcIQR9JYQltGnQVl8FoQERdSQZOldqtz6OAwRc3q7JS/85/+J/ih58d/93/H29ev+OyTj3EB1usNP/nJH3J2esqvf/Urbq9v+KN//kf823/97/gv/6//FXlZcrVdiwVwWbJcLri4uJg04bfbLft9M3G0lssTUIq63ksy7NoJEc6LkkePq6mFLMUjCXGQpMRHJtc1F4IUHsg8+2q+YDmfUZUlru9Z7/cQIlVRkBux5m7qmq6VRKcbemnXKEfUaWqnzImJTxPGdTdpUagQv3FE/+Za7noc/Ge6SA/kNpUyzYQlJHhlIgcEnwKqpCf/P9r+7Fm27TrvA3+zW03m7k93W1yQBAiIpChREhVhy1FR/YPrxfVSf5xfqvQX+MF2hBXhqJBLqrDsKFtsTAkAARDA7U+zu+xWM5t6GGOuzHMAkvfSVgL77rPP2Xtn5lpzzjHGN77xfW+1qf+m16pVrKEsJKaCVuTWgdFRGbUuxEjW63zhLcF0zLvR/OQpzJLVvdX3foucUFXr9Mv6OzSg1x+XKkf6S0YrnPqNtX9vrSX4oCMYaHUgvcuSEpv7DWkeWfc9ORXWqzV9vxK4rggJwxep/rxMmon4B0XMSKxdzFd2+z3FGM4uLlRKssFEJeFpFRp1nHC/2YjCXxR3s4qMZJ13DU44EClzvOcUEoZ5HNhtNvzyr37O559/QSnQdysaFxivBlZdz9j1xHmm63pSL9Btypnt44ZxGBmnQSDEnHDWcnV1LjaRyhr1pVDaBtdBiVkEZ1KBlLWSsZiiFqemQnx6T/Qwsk4qtJRnJWlZ8Z2vBhRkYaAaiyuOnJTRXgyLyEjJWjEpBM/RUKUiN0l5ItaHE5RAJGyz/g6p2g1G/y3rOnRUxMCClQTCOSOEoBwhR1zwNDSs1ytCE4QJXoqsDXQ+uDY6jAMTBG2wTgN6wVoZsQkuYMn4ErEl48rRjKIgB4R1QgwTeRhJPko2WOOxNtD4VvQDjCA0c0qYqq1dssz1W0ErKsu8tkrkjhRt1xWBva0oBMoMtCjppSKKeRQxZjEq3lGBNrG+nQUut46SpN1lcMpFkFaHyUawNCPX2LdrKIacRxWyyZQSSUx420DoscFRFDHCTjKOBxBa0Y7HiahMNKJfQBTULIjUsrHCqi4pKdZaZGzNGozTo0fXbUUpi5HENhsR6rLu1D/DLGvaGGlb5pyY5oNqoMvcurNO+Ac5YXzGIKqBANnIOhd1tQQL1K9cKDJFFfmM9bjafqznIYWSo4zX+bo+EBTFeIp1ZGPJRm1l62t3EZMSJhVCf8bFzTO8KdxcXWKt5c3r12CM9P1XPc+ePWMeR9b9ih//+C9J+YHN44YuZcZxAmuIOauKmxSXTdMAO2JKOEQzwmuRJZbUSgo0RgssR9d1qo+gVsilqGmMW8bcJLGHXGriWghOkIG2EXfLKWfmaRLdEOsw3pBz4nBIqq9wHPmuZ4Ez6BliJVFI2kM3RWNm+cag+7fooWeF4orAW8p8PD6OYvLvAtyno13mnX989+vjQz2tLUuFvPCjKvStWESxArkVK9+nXHI5IN59siWBMAsS/7ddqnd+y1/7yPqL5iiwaVUJO+xFtGEaR0IIrLvqMmWIc2LOka+//IKHu1v+h3/133H7+hVnfU9MkS+++IKcM7/7/R+oQcNK2KbOiZHFNEni5NziaV70ej9ut+RSuHnyhPPzc7773e8uik/ee+kF10kDJS19+NFHtH0n+uXO0a+fLmMXBUPwlW5gyN6RcuL/+yd/wk9+/BP+zb/6V9zf3fOD3/sD+qbj8fGB3WbLZ7/4jJgiwzhKwZAK73/wAU+ePePq6pqu6xmGvYg/xBlK4e71S3KcOew2xHlmGgfW6xWX52e8fv2KzWYj41DWMx1GzBjBaF+97cA6sg2kYphzZn/YM8yRWUWNShFSVEzKPiYufcZaOTlv6fqAO/l++VmrS6lQivyA0fVpFkhNAnjBkutCNpZsTkbmAKsBvRJlko5B19cip6xsbh8c3ojATCx5MQkxzokHgrVgjRxswdOtHNk4YrIU1yCM7ZqWTzgS0TosgvDUFtHxe+QFpGJkbK6S7awhG6t9ZgkSxhisM0pMkGAgXuEJk6x8bYQ9bhTxXnqJGApedH6Cx1GWVo0xVn5lMXgjGJmrwU2remyhICRFgUkb5hgZhwkXLA4vUsIGEk5JfTrxYBshMAZHtgVDJJcZTCEmwzBGDMIF8t0Kx2qZ1XZq3EeWiju04m1eRVmCisgYYzB+Ei0ORSSCBnSnFXrJRVjh44j1Mn9eKcIpJ9E51+PQds3y55ILU5okcHoRb5kyxJKxpsLzUIwXRz7j5N4a0e8bo95nJ4Svo0aGJlZFPOp/XTejqPywEp6NTgFYD67BaMJQjXWWCShmQeNCZsLx+u6Rq4s177//IU3bcnlxwVeff8YXX3zB/e0dXdvy937wA66vrvm//J//r9q2tIzjRNt2xJwZhpHNZsvr17es12vW67VW2lZ74oVhmAQpyYV5jtze3tI0gZubG6wV5C/GxDzLQjFG7FP7vmcYRIr2cbNhjjOH4aCTLmmZMjoGAbnmMr43aZ1XpJhy2jK19hjL0HPkrRgjgWnRC/qmeDvfpode5Infio+wBERTTv9WX9BJqFzedHm7SDYnle+vP6eqa9Ue9snHkpobjfAnVfPx+95mC9anqblmfX2/KVifPO03epwCAlFtDMuymE8mArQXU59VlIQSj4+PvHnzhlevXnP76hWbthE26uOGtm15/uz5MiPZNA1t27LdblUnWRn66iR0eXmpakiXnJ0JFHV+fs6LFy+OEo66EH2Qiqlof7LKO1KqV9hxXMcapD9mZJzmMAwcDge++uorPvvs08VMpqQ6J5uIaWb7uOdwOHC/ecTicMbRdT1t18ncvfPM06wBXWwOKYkUZw77A+N4YPP4yLDfMykjNc4z8yQjI7mAtdLSqTBl3Ujl5EDJ+r2V/VoJRTmnKoWwrA2MIFHeu2PyWuraKMfdSFlW/HHhHP9iIVwta1NbQfrIvE15+bW1eJJkWBUaEUCgLL38plbPi1Sl9na9VCQ5ywI1Wg7K8eF0j1ituKw60dU+c7VJUjJoqWRV8847PmYexhpRuzMoWmSwNWGu98QY3XlGzxTdgwvPAk0lpFUio67CMRCBk5NkB6SKsQoHv9W/Bed03Mg6FZ6VJzD6fLX6QREerEwJOHVUW+aF9cM7AxZK1qppztXyB4OovhUgG2VTL2O5ooBW2c4FnWG3IjULkK0y2m2Sg9+740kaRRmtHp7WHnk0kMlJxY2swOWVt1NJujWAY4/9+Hpvc93j6hyIOZ71Rh0GSzmSXo+PwiJwo+0AyVtloqN6JlhdN5kk+9pYii2KsIjIVb9as1qvIUVMjOw3j9y/ec1ms+Xu7o73X7xH8IHQCNlxnCZsdvSrC0iJcRb3t2maCCEQtB1bR6tBVN6MMYzjSd/bGGJMOCcoZYzCRzmOYZfl7M4pHwl2KjXs7GmiU07O/LL4k9S4txRPmvz/WkxbEGij+90s91++8ZuUlN9ybE10jwsmm+XDluNHrZptEXjK6THpcO8shuPDmNNk4N1/1M1tTmb23s0Ul4uf3/o+OGaF9evf9LO/+TUtYexbPYw+x34nqkNt21LHKRyGtg3qBJbVNjYzHvYMh4Ff/tXP+ezTTzHA2dkZ4+FA1F732dkZP/zhDxnHkdevX/P06VO+853v8PXXX/PmzZuFsbnf73HO8c/+2T/j+fPnfO9736Pve1YrIY1UWEksFsWNyTodQTq/wHnP7d3dImVYKDw8POC9Y9X3OO/xdcqgFH70F/+OH//kJ/x//rv/jp/99GfsDgesE2ZpmiNON8zdm1ve3N7y6eef8eH7H/LdT36LVd/ThYY4R/a7nVboCUqSKkyTx67rl4252W7FqEGlQV+9esn9wyM3T57R9yvOV+dY7xnnmZQL+1lgs9B2wo2w4JwX0RAkSGWVZhSJbSO9WKMVorWs+hV5nojTKH3hkwBcN+PpjOlpdlrnIlLOEpSKQusnAb2uyDqilEk6y4swpq1UpsFAFxyd9wzOYE2h7UTYJhZRkttNyrT3Mo/feEeeRTXNOlmDCyRmnBb+TuOEW4KsYAs1mEtVI0pnx2Ratk4NwppEBaeHt846WCvJFEUcvOr7LdKWkD9WhMPp7z2Z08VIYlXE3KZrGoL3omOfBcoXx0CPSQmbxWK16VZ0reFyjVx36xhMYdKqci6ZqK2YPE9YrHAyTCEZ6LqWm4szihMVtxwMxRlyDZZJ929MmJwJOYsEsFbTaZ7kvLNGoHpr1cubpeqqj7ysJXHta7tOvAqEuSXQL5ZijzayWK8oXFaI3mNwBCeckFy0oMhFxylFQ14ScbmzVGKdep0H53VB52MLslZs1BQvL+mgKbpHAG+OZy82gGvIqspo671WYZ1sE46CD55nT2/43//v/3cEZ0nDnnx1SXr+jKvzM95//oz/4d/89/z851/w3/+P/4au7Xn29AVt29Guey6uLvn9jz8UDoaR8cNxFKOhGKMIu0zTQoqr8+Pb7RaAvu9JKXF7e7v03CvkXsVoQOx+p2kS2+k4M8WZx8dHrDWcn62P91E5VKIpL+N68zwv50K/lvPTqR5CXeNylP56ADQn/z2tV/+2x7fQcteD4CQhAQ3GusuPFfvpyzGyIKvH2DsvzPwtL9aU8u6P6OspbwX53zSb/nd5vP07vvnvO/3OUzWnetOMQe0fdRTKGgzS76LImEXf9wyrXqCyJKN9tZquNnwgC3a/3+O95/Lyclk0Z2dndF3HRx99xLNnz3j6VNyJKgmnLpxqNei9x1aNYVA7SXsym2t08dkFRgLYbTfstht+8Ve/4Gc//Sl3t7cMwwCl4Lyja1qaIBKiUT2rvXOcrdesFcaqalOCXMRj38oYma2vZCEcOSfOzs6Ik1hrFopOCLhF1SmmKLOk7ti/M/ilss36/oTUmRR+tEsJXVFG6SciinGliDOZtdS68lSnYGkjwTEAwfEsVPRIyJUVnz1Wo6ePU8itUKTyNMeKVA4AtXDVr52iMiVr4LOgcnqA0T178lzGnMBUJ5W14jDyPmRsT5Az/fdSwGStxGT9lErqWn6NpMByTJilIjbWYBUNqMeHtAcrhiavqZJO5XXrqzJydmA8xmacF8vcUiArM99o7xeTsDHJHHBocMXgk04dGMuchSNgjSQ2tamgRTeNc5hcyMUcFQGdBW9JFvmogidFpvilw2FosWKQI38tugFZ9kxtK1CyCsPIXc6lYLQIkX60HBLOa6+3HvayYfVsVbSJ47lbitFxvoJ1UKjaDQWsogemLBMhS4We67pXEyC1Jc0no7VVI74G+KKJgt6gRfjGlMqrUu+EWmRxRMuOmhuak+jaPd1L1lpsEzg/PyM+ebIUItM4k2KmbTa03cy5FU2NJgSKMcSclvOsVuhZz7L652qrWjUDQghAVRuUvVaFYOrrOXViSylJOzfVe3hMOk81WY5iYkftkQU9dW+bssjP5neCunnr0+n1+SaPbx7Q8+kXcIQc5dmPQVzgncIxG3RUu8p3XjSqPlfMcYViK+ZGAbx9+438dRX6uwG+/tu7j98kSPNr3/MtAvlveixVhrzg5bU1ulkN0kNrfODiTEwCdpsNV5eX/NVPApuHezZtqwpKG6y1/PznP18W7MuXL3n58iXf+973+MEPfrBkl3/wB3/A8+fP+eEPf7j0kYZh4MsvvxSI6GTRV0vB0Ai0uNsdmFNitVphrGEc9jhrObu4IM4zm82jLFoKf/Hnf86f/cm/5d/8j/8DP/rxj4WcVlAUoOXF8+f0/Yrtbsc4TFhjePbkCd/97nc5W59zeX7J+dk5TQjEFIVzgGzoNog05bptF3vQi/Mznj655vHhgds3r9k8PjKNM5eXl6zPzjgME8PhwKdffE3GcPP0OW2/4uLmGVaVm+aYmRVWS2WgW63xzcJIUulMmCehrpk04y2smiAz0YhuwHG0JS/RSXS3jy5UBlnO1kh1klNUNy9HqsFkqdIrZFt3h4LwRkaovDF4C8GCNZlSZoKTaj0ojCe/RhT0ivEYhC07pyxDFOrwhk59mAqXloI1ghyYktTiVFA4W9KSACQl5zgrDf5kZcRuEcnQKntJdrQUT4CxDu8aKr+eUiF8TfBVGjehlaH+bEHMcLxzYAPWWUK7om0aMAdJAtXL3gencK6j9Z7Vao3H0ORKZpT7GmPGY6BYxd9k5CxYx2XbLclkSpFpEs1w62C20qE/xIE5RbwmnusuEIxhVay8jzmzPyTGOMkCcII1gRV73lLFpeo9MEt7KhbZj32/EiVINUmhKCnNmUX6dZpnSknKM2Dp1QvJUpOvUhRpOZ7OhuO5ZJczUs7pxjkd7xIHw8LxPE1F4PKi1W4qdURQRWbyvBQCxQhvo1SRJyU+ztYqKVDWkohIZb744gv6NtDaQrDQGsP19RVX52f85U8+5O7ulsd72e+vX7/ChwYsrM/PZWqma7l5+mQ5295FZ+uaFEg98vDwsHiVT9PE4+PjYkpzivaWIhaoNbCXUujWKwBl0te2jBUi6FwwKVHifBLUj2e/c47gg2g0KDH0CLu/G9NQNLwmuRoQv8HjW1Top1/Uz+akIn87DC65vy6YQj7JAWqfzh5f9JJyyuFQTPm13/ebHm/NR/+GYP13DerkX/+rb/IoRQR0UoosWvVFMnkbeGtjJWN1HlUMUmoVPM8zh/3+LcimVujDMCyM9cPhwN3dHW3b0vc9Nzc3XF9fL4uwugfV97jIu54stqSa9WUhOeqGc2KiMAyDzJfPkbv7O7746kt+/KMf8dOf/pTHh8dj77GwWEVO44g1lsN+T4oyvtj1PVdXV/RtT9eJNGZOWTULsijkGSGFgXALphTZ7zYCPzvLOIyqzCS9LmtEMS40HSlnHnbDot5VUQzrPG6aqLapRisKSpGARt1Ach2E7yRQLM5SghDJKspy2t5BqxyzVNC6npZ1BVAWZMCWrOYwVnvJUqlqGlvrouVnjSlYK706Eb5JlCSym8EL7E5Fg7LBmkZnrYW3EWPWmXuvkLZdXpMkGLU2F+SoVnMWsWSlVt4l45yhFCuVvKnEstrvO77hY78VZa1Lf7Z60C87QK93DWhCYiqkqleu4isVdTAWal8WK9W0sRL9nfNadWVhd/sgo7Hl+OGsjndZg6Oo+Y9cf1cyJU5L1Z5jJE8TJlvIXqxTbcHGGa8tIVvAJbnv0k8o5DlDmqVN4nROu0LuTmbUc73Dp0iKHuBCBBYuQ9ZwXBRVMIqQllKX3fHMqsmhjAvK9a667EsNXCvyeqtUpEfEvyzeCsG1EKmjnEuBlMWQC6NneK3ulrNXZ/e1Kl/eju6Jd7lKBgjBUyjc392Rz1b0V+eyntH7n9NCKu77FU1ITNNMofDwuKFbP7Ddbskl0/b9W5UvHBUA66Oef3Xe3Dm3mLcsyUhN1PVRk4HD4SBnlFcpc8fiU2+tnOHJGCF6nqAwp3FFJF3LwncymixXjk8pR0Gu5SLpRVtaIN/g8XcK6JI4Hjcn1VNYX4HVo8lq9m5N1Q+rC+pYoUM9ETSgn1QRNUvUq7NcmOU9V+iiHiTvBPDfJOP6jYI5vOVh/G0f4zgwT5POVFs9UCzVYMWAZKvad4nzzH63ZdiLocLm8ZFXr16Rc+by8pIqajCOI4+Pj9zc3PD8+XPevHnD4+Mj/+Af/APef/99PvzwQ25ubtjtdjw+Pi7uQ6cL+BQeqh+yaZWwk6RSatuWGGdu37yRAFYKP/vpz/hv/sV/w69++Qt+8Yu/YrVec3VxwXgQkslhHEhz5OH+nkNzYLPd4pznfH3J5fk5H7z3nohXWDW+mGfGQSQmQxt05lOYozZn9vsdv/zFzwjec3F+xjgODPs9h8PANM00XUfTBJ69eIHznsf9gd3+AKYwzSPbVy+FiOIb+tWa88vLI3O0ZGHyG5lOKEkNLor0QefhQPGO3Ah0apH1LPdR17GertXEwlI0EZWgWwN2rhRr6yjOkc0R8q1r/1ivC/3bmjoemFHkF+JETjPeZFyopJ0obobF4JqOYp3MO6fMYZixocW2jarmqawsBWPEY9qi/teIUI9olgtKUSt0bwrZZKzxZCzZeOmRWt2rprYIjnmwkIIKNgiMzKKZr6YoenAT1RMii6vanOMiBNIEEQExxmK8XUSBhHhlNCkpClNLYA/W4YOo4JEmRcgyQXxvCUbqz5jURW0WWd243wiqogn5NI4Yb7HeUrz00J2R9WL1vfppkh7xJLPtcZIZ5t7LbLFvvCjiWYuN4lFvVFirGE8FJOSCCWqTcSQjLQVJcQo263hfkXMuVUjdGEFDjfxMVcexqo4XKtGtFOIsY3NFBXiMFzGYKlMbnJiPYEXZLOV4LACynFVlrgp3UZOSWoi5ZUyxVGhVH1aJjRWpFMU/Q9eKmuJnn/6K95495YOn19iSIUfmODMPIgM7z4mr62tCCLx+/YbDYeDzL75kiJEvvvySy6tLbp48WfzNT2OCMUc/jfq564TNX4N427Yq69oyjiOHw2Epdurv3Gw2TNPE7rAnpsg4S5HkncGcihNRcDkt/BunqAdUkZmsSII7XitYnk/iHpwi3vVU+N++Qn8nQzhS7WtANvp/IzfNsPS3jnKtx9E2+Q01i6oBnePXejCeqqv9psdfV6H/dX31bxzQTfmmSdGvPdq2xTtH3/ea1BScUQUrZASnyihuHh54eHjk9atX3L55Q9M2XFxc8NWXIjDR9z0gLE3vPev1+q2+kLWWvu+5vr5eKvlxHH9Nu7hW7afMz9OHzKQnfvbTnzKOI02jm8NaNptHfvFXf8UvfvELvvj8czabzfJcOWetnBMxybjedrdjlQvr9Zq2abm6vGGl6nQ2qOuWohhCNInMWQiAFkl+Ytey3215eHjAWcs4HkhRmO/TNDHHmd6v6bqORt2Q6ntvrJcpMWV7V/jRAGRx/4phBp2zddaQIvp9cq3iPOOQhCufMGbfddw6XWfLWixojxipoDWxKznJnLUxy2FeCaFl2VHHHWKNJgsGnFVGfjoqdomtaNFkRBMKreLK0peTWduio0V1HE0ScH3tWCSUy6iTrFfdF9aQyfqyLcZItW8wotBmKnnthIy6/FnlWCvcb4WPgTkmRVmhfePc0ff+iHFQtS6qiUx1r4PTay6vwXvZVzmLyQrTqPrnCdsG2hBIVq/7LAIx0xBJ08z+fgM5Y2qPtAiJEmswjcMGh+9Eq9tZqbbncYSYyPuDKOXNGRNafL/GlkitV6UFVzQZ0PdhTs7NImdjwQhCARjnsTKIJ3s9Hyd2rJP5+6qaXRG2rOqctt7/5ZyVAr1O8RogK6Qr57cy5LOOvGqiUJX55ExPC3pQKm/B6prh2I4Sq9l6dBbdh5WngYxUWkPXtfS6d401HA57TE6StM4TKcoEyxxnmTAIgbPzC3xoedjJZE+cNZlVyLzC5qck6MPhsBCB6/hY7a2fep1Xu9R6ptXe92lvHEU/Wk1GcpZWoRjEaDzU/XzaCgbEEXBJ0gUdeQv0rhW6Od7Tyi/7hu1z4FsF9OOjslVlX1mWfbjAhadQjMG4vGgtLw9zJEjoX7zzjLUyT2/97Slr/e3n+vXA/DcR5b4JFP93eRhjWK16KLBerXDWSXVnBdaq26PkREqR7XbLl198wWeffc793S3Pb65Zta1AQDmzXotpRR3JqFnjqd7w+fk5z549wxizZJm18q4LK6W0BPRKChEBBpbAXWLkT//0T3n9+pX28zo+/vhjPv30U/7r//q/4vHxkbu7OzC6AaaJQ4wMw6QjeZaSC48PD5RcePbsGev1Gc+evgdAnGaCDdhWoMTKKh2nmZijBKgYscYynvXsd1vevHkDFDFiscL+zaoY5r2nX62WrHscR4HZQ4v1OhpUlxGC+uSUSPNMnNyyebxVTEk3VSmZOI2Y7JhaT0nVWONtC83THpm1whg5SoPqR8ny89YKtKubtu4fScxVTY16/FpM7VsbObi9EWWukmbpXRqIpag3QlRcTC1XytuvzXlPxsmBvhzj+hza47RYMd4wgi7Y40XDFYMrBms92XrxO9c6vpLa5LCWN2VyhVprsqOHmPXL1wsmVyyYjHVJe8uKZlRhHE0IvBcGfYppCUoSUFiCpg8OoxV2mSfyOEgSVTJ9FwhtQ1b/BEshMjPHkXjYc/v15+Q5wizGIW0TyIgjne8bfBu4uL6ksa0cmjnx+HhHHEeG+wdKFOewbn3BRdtgs8fkqGN7ch/R5ExPdq12jws0F6OiPOLOZ42MeQnL+jjq2jWSwHojay2nSTl3EnRchuQUM9W1kIpq3iTZ76kG9Bq4nQZ0Jp3E0PulAd2YipCUpWWE9RgyzkhSbK3V3nxeKlZTzxcN6t4K92Pdr1mvZALHatFQ4kyZx4VsN0wj4zSBsfjQcnXdMY0Tr+/v8cFLMVDNUaxlHMflTKyB+PXr1+z3+wWtvL6+pmma5Ryt7Z56dp4WQ1UcrZLiQM69rm2Fn3TYyTinInjF6g5+J8lf+vAckYHKpWLZByfBvJilBfZti8pvHNDjMrGISmAeFcq8/rku2mPWuexJ0Ws+eSwJAbwt6vbON/0mgtpv6lH8pmD8NzED300M/rq/+7s8girkFfUan2NaDp5KvMkxEuPMw/0dt7dvMKbQ950iG4ZPPvmE/W7Hp59+inOOm5sbSilvyct+9NFHvP/++zx//lwMcE4WZ11I1fO3HvAVfq9w1DiOzPPMw8Mju/1BzBswbDcbtptHXr+SDfHs6VO6tsVZy26/Y7fbYBCjhpwKyYpEYtM0fPKdT7i8vOTq6ooQWjm8tVd0f3/Pl19+vUgyZj0cYhSjjWl/0Gsgrn0XF1fEeWIYDxiyWGTmE8nZYeD2zRtiSmw3W6ZplEQqNKQMwzhx9/CGdrdjv9+zPjtjfXbGmBLDfkvfdzinkKWFxnsSyjzNiXmaKDlRYmR2M6MTDoOzbqF9GFPZIMqEL/Ugk0q9pISxSYOLVC2lLA2n0xWoBDUJlc7IhzcCuVexlkUCtWjlp/OwOUriQJDqom1bnIoIxSzV7nGK3CwHtQRfSUeszhRLMDEYa4hZCVrm5ICWl7scQovGvSYNBbApLZoFSS4oLIlHfctZbENrUhkCKVvtQ3sZQ1N97DiLOEul2NakI6cExWK8o8TEuN9LdT6O5BRJaSasO5rSyf0oRTzXs4xQ2ZyY9ztKjBIMJzgMkHIk5kgYGnwXaFzGxB4TJHMx0wE7TYQUtUXncGli3m/IOeEp2NziciBlo23smgRVrXjJhqpXgRAY5bOIGRmKVWSnriu18nRWR2CtIedInrMqRYq/gFG0ReB8J20KnZLACR8hF4i5YGI+2uQWFeWyRdadqSJfOjVQRBTH+4An47IoiXrnSOV41i1tV21ViaYDNI3nbN1zeX7O05sb2uBovKztrBM+Oc4LV6i2G7t+hQsBH2RccxhG2nZ8q1BB12c9+6qb2uFwAFiCf84yt344HBYd+FqZ13G3x8fHt87U80sZ7a2IwDRNolRZZK4+eAexUM1z6kcumThG2S418THmiKLVAkG3xBKCjiDfyb/+zY9vHNDTsk21QjfyUQN7fcrlgKqQkn78dS+nVve/+d8rPKhf/YYA/W6F/i4c+tcF9VM2/G/8+W+NuB8Xk/NOf5fMIMdpkt+r/SuHEUhpmnh8fOD+/g5Doe9aCQ7G8NGHH/Lw8MCf/umf0rYtH3zwwTJCUSGjDz74gN/7vd/j6dOnS7VdM8kasN+FiCsxpMJIh8OB/X7PZ599xuPjhnmaMBh22x2Hw56XL1/Stg1Pn8lz1DGzh/u7hWDShCLazSnRhIaPPvyIq6urpRo7LUcfHx748suvl8q6Xa9xIag7lagwUVhGgs7PL8Rd7LCXStZILyovAX3kMIxM88R+JzrNfb8ihIZhjhyGgYf7O7wP7HY7Qgg8efqUcfPIOBzoWxmFskZWWuMdsTit5ovIOJYsfdbZMhlwvRWN9gqvUStSlsp8YRGjGzxnLZF082qJKg5yx5ZWDVS1/q3z6RLQAQtRTR+qgpmzhZxl5j+7hPEiO9k0HhtEBlSmqcrJaz0J6JzAoqZayRrlbcm+yDlj3SlR1VD7BUbzDKe618aIWqNLMvtsSlHyX5FgfpLB13aI0zFOPORiSRqwvHME5wUunydKitI6MEpCLCzWqraIic04DDBP2FmcwuI8cVbFnPQemJyxOQssXiJpOEhARxLGlGZiEk/vOAX8GFi1Dl9mfCc+A2YahCinrSaDgTQzH3Yi62mMSBZnIScmYSxIgKw98OVC2AXmFtRTAn6WCK6sySphrPK5Tqc0rCUlS8pREhzEBU98y3XJGavBRJMCDc6pIMlIEcfAOZUlGNosBNJcEYXKm9C+uKuqfklaNELGQxMJxVkqeuUsrlgc0IbAqu85W6+5vr7CUyBOkuiaIlauUcRYQgg6dTDSr89w3ghb3DjGcVoKktM++WlhdjgcGIZBxmqRgF572zFGNpsN3vslsIcQlkp9s9ksgjQ+eFbnZziDqs9JQK/6A9YYvPfkFDVxO8aeirCyiAxVzYpjIH87Tp320L9dFPpWkHv91clIxi3wC0cJO8OvfX0arN+txN8N5qdf1zlYk49v/K97/HXV+bcJ5r82Drccz9/2IVUIqH6zskstskBLzpSYOOz3bB8fuX39mjevX/HsyQ3r1YppGASKHkaGYeDFixcAvHnzRkYfQuDFixd8//vf53d/93f56KOPVI85L9DQ6WxlHZmokPvt7S0PDw/c3t5yd3fH/f09u92OL7/8mt1up9dOCGnjOPLy5Usw0P7ir5ZNs9ttl7G31WrFarUmhIbz83PWqzUvXjzH+8CbN2+Yppn9blyuTkqZq6srfAgSSLWH1YSAs5bB7khxZrPZijTj5SXTNDEcRrE+bBo5cHNis90yzTNn5+cYI0SgOSZeff21ELGcI+XCi2dPGaeZwzDyxeef8erVK9pVT9M2lPNzuTe6DpoQtI8vIjNpjqoUl5bgXmddQYh1YqKgAf1tYEp+NidR3Vqy8XIUGCkVeK0wvSaote+vwdKAqMR5R5wGYpxwrpWxKy/a5ft5phRwrbz+VduJ5Ku1cjhzDMgLYlSTBqNzxcvnY2+88gBwCWOiyrjW36IHuD0yi1PK+KLiKDWiFKF4VVMLBWwW8qk3gkD4RlzolvULtMHRBsdIZkoR46ooqtSBcZbDsgRHnifG/ZY+eC4vz9nvHYcDhCYQvGOYlLsxDMR5Jk8TeZqIwwGTEi4EuQbBkVxBi38ha20f2E97StfImGKMuJRltLYAJRHzzDQeVAWuchcA62Wd6GFurQrvWNFBdxlcaHRiQ0iNuSg07gPe+drgAKOGUka0LZq2I0UHRhn4plBboTIpYJa+uzdGRYuOQki5lGVUb5xmanrpc8GpWqfkBNqfBxEq8kE8A03GGYt3YsZSCZdS1EsAq0I5wRbapqHve0ITGIeBqSTKdBAhJSPJqOs63n//A1IqPDw8Eucoa9t73nv/fXzw0j47UWOrc+bzPC/98Vr8NM3RFvi0gq8Ve/2+rusWsvA0Tez3InjlvV/+XIz4BgzDQLCOthExoBAC8zyRyjEpyjr5M8+zrluNV8YceTZvl+L/qx7fOKBnFOPXIPdW8D4J3NmYpWKvkGId0XmLWFdLGv2eWvXDMbAbhe1P3+e3gcW/6TD+b3qYk0xjqZ5OsJAFO3jrNZYl6a5QTclZ1MV0wedSiKUsM+bb7Yb9doN5ckPTNkzDQM6ZYZTAfnl5yTzP7Pd72ralbVsuLy/55JNPePHiBdfX1zomlxZJw/q+F4GYE3j9/v6ezz//nM8//1z0ku/v2W63fP3yFcNhEK1454hxYpomXr9+LdV8SYQQ6PueGOelv9R1HdfX19Irf/aM1WrN2fm5EI6mif3+wP39BpDN3XU96/XZsTrRzzLHrTQezWitETtP69wiyRh8XkRopN+VBIpzDmMdpRg2jxtRtWtbIdOcrWG3Y7vbsbvfMQwTz957wcXVpZCnsh5AKqdakl1eR04iJGJKIumSXUiFpWjVZE/mfTVol7IE8eXjrdWlVevJuOCC8ugaq0G9PqxB3LlKJqco890GOQAL0how0ke2ViqobC3JnELtRxRtSUCUAGo0mJv6/UbXfIHFJtkVqCJRx6Got/ZHNW+yi0arksNK5njp9J2Vk4qxIjock+xSCt7JGJjRCruOy9WQRammJ0IajPOECbI2Ra5zknaAGgzllGUUM84yNhoF4rU5Y72MmzXeiy2uzURTRE99GChxwuUZ7xyNMapip8hlJabFiRIDpAhphlxnjmWULOt1rQIsRZEWqbwDqahroFbHzorBiK3IT53hlxJYjEcspBTk34riqVoUFQzGuuM0hrb9jLxoSimLWVI8RfhKeWtVSnumckb09ZKxyJiccx5j05KIGVjWkCA/omVQCxNnHdM8Y3IkTSONNVgvOhTeBi4uL3k2TewPg2isG7DOcnF5ucx/pyrOo2ulEuCqX4XRyrk6YFYVuLcCbjmy0k/JcrVIqoS7WdHRTCZGgeWdV1TWyc9HXb+nkHspsn5yOlHUO9nppw+Jb0f+wenff5PHNw7os0y0iiezNYSSVQBhxngnyls6m1pykuxplIXlnRCQFvcxXRDO16cXRxohdcjfWCdksqIZo8gt5sX55rRfUjOserPenUn82x6/qZeeUzlWEXqgydcVJjklPiAJSIUnLdrjHSUrbTtCcKxWPfMoMqJfffUFf/Jv/4RxGOi7jsN+T8mJdb+iaxrGYYQCL168YJ7nRWCm9tO///3v0zTNkjXWgF4rZ2D5t3meubu746c//enCBP/888/51a9+xWazkT703R3jOLHb7xAG+whG7AFF1nAil8x2tyUET9u2XF1d8fTpU6wVhuirV69o2w0X55eA4XA4ME3T0vPve9FtN0ZUmVLOzNNIypnNVsRxUhTpxSdPnkh/Pssc+9XNNYfdntdvbjm/OOPsbE2MMhr16tUbUk7L7H7tPeYUmVRcxxjL9cUZb25nttOB1y+/4v7uDZv7O/q+5/mzG9q24c00kOaZYbejqKWoGG7M9F2H7xzTIG5KMUVyKYRG7vvZqmeeI4/3d1KhhYaUCq23NH1De7Zi9g2zE/JQKrDf7wQF8BKsbWgoOYuxSOOh7ai9rXmeieOAwdAG6S3mkmj6czyOgUIy4gEe48zh8QF8i20SRTX0XV2n00TKM8lEKJE4bXGmcN6LZrpz4Kz0r+cQGYOTyrwe/hRxUjOW4iIOiFHMKGJOzFGqGGcdDlmPFqsVu6kn/bL/WWZzzVKFCjtcnrPMA55E66Br5NC3mnS0Zz1QSPOEbRzuyTXkzON2Q8oJ2wTxdp8mrDM0xmP6juSlD1uawNOrK/I4YuaJ1hjWbcM8i4iLuPglfAZfHIGCJxOQ++iSVI85g3WFxjraYOm6AF4oj1OcySSME7g4lUzKhqlEinX4pidj2O4PiyxxUca7zJmbmn0RvATmUJMmJEV0zpGiaEskRQa9k2QgK4+nJEGDvEK/rQa6WqFCv6B81grqNUWRNA2hIQSWkTbvAy4nyjyCq+qTgRBUFU+r01wi8zAyzxPFFSyJYb/Dkdi6hDeFYEUEaS6JecyUlLBW1C/fe+99sX5W9nzOEnvG7Qbr7KLNUcnC8zyz2+1IKfH8+XMuLy+FT6JtiloMhBC41pG41UrsoeuZ6Zzj6uqKrus4HA5KPr7ABcdm+ygCVSlh247z83Na7wnBM2gxsijEWUsumSY0NI2Mx1WinbFOXeIUqdT9MM+inBnU4Ka8C23/DY9vB7kblPWIjpkUatlSNFus/fJ64QEJ6LAw+TDmLdOVWgUsv0f3uEICWsAcYYz6+d1AfDp3Xhfp3+VRA04dAQIWc4pcjoyB0+cwxx8+kiGWyk+zOGuJRn7Hbr8TNnkQL/l5FvLVWb9aoGjvvc6Dx0X2VarcjrOzs2XjnSY5p32bStyoxi9ffvnl8v52ShKrPaZJR0RqQTinUeZUz2SsJBcn4hYJgg8LWiCkleNM+wIvmaPiUs2MJUu2y/XMOWufMi3B3yl02/f9sm6E4CUbaxwnzop4Fec0kYq42FXhnZp1G/3IuTDHSNM0NKGTUR8K03BgHAYMMBz2nK9bGWkbEXGfaQLyAr2XHElJMCc5NCRwlVKwLlKQ+5usYT4MgMDcYJb59eCsbhcdCysFUl76wgUjiSNi75i9rDNZSyxMe2PkmpQ5koshWOnpey/s9UgRQt+csMWAbeCEjGN1DZaUKFaSgjRNImjS6ECbsSJ2Zs3CYC62iqAUFiACZdqb6iUNR5vItMz7W2PU/GUpVnX7a+JdZ9o5BnVj5bpJJR1xphCczEx7V8fsDH0nSdAQJ6y3uL5jGkeGcVyqOiGKKenPVYJWlj69dXRNQ8yZNAnL2htDVsTCliKysYqa2Jz1PRQlESnKkvU1o4RGK9cnlyzCMxxd5I6jfXJBrPMqBpSoo8C1mDheNLluQog7ygLXYsLU87dIK6MsZ+QRl8kxyllqZfwu1CJIz7Ia8N4axSxHQq2MWxXluNgF3annRv09Rn9HURQqZz0jKCdjoOKjYJxqHWiSm9ULAoR4169WWOfZHURTvZgqipVEmEph99obr8XNNE2AKOmt1+ul9Xjakqxs9zq2VoMxsCQBtUAUVU27xKN6NoUQNHESsuQpjwk5CVT61eF0Bj2nLOeC90e1Rzi5XoWsqOVy47/B4xsHdOu9bAZROCDnpF7aAo06FYTxzqpmOdJ8KlJZALjgls1bKMxxBD08xLPWLS5Bs9po+qIw4NJ7OkIaR4jv+G+nDO96Yb/dQ7KKVA0Y9MalctT4hZPi4vQn9blTnCkls151shlSZM6JrVaRD7d3jIeDXqNMjjP3m430aoyj7zrpdyn7sgb0WhX3fc/r168lSOlcJcgCrAYE9b0/PDzwL//lv1yU44ZhWKr99957j9vbW7bbLd43zFGEXkrJrFwn0Pc4LZrxNzc3fPjhh7o5I/f39/zqV78SRyvnefbsGf2qp2nElEY2hKcJZQnk8xy1gjiS9ay1i8Z72/ill2WNyEV6F2ialuAbnPO0Tc9qtVZIcqJpheT35ddfi8DN4SAwpdOKsWSmcWC322IxPH/6hN3hwDgJzJrGkZ//5U9xarjgrIE003jH+fmalDPTMNM1+a17PyrfYbvdk0thfxhFN8FYnBeCXc5S5Y3brYzn+ZbkG5p+TeMDfXAk4yGO5FzYb2aCNbgAyUvFNRWx9BTWuKeYRLFSAVAMdYDEaV5cZ56DAWMyjgg6amaL2g7lCGXG5oTV3w+FEkURLhdDsoUY5VDpvCdZkfXMar6UVfms0v3rQViDec5S2Vo0OcZicFoZyF4zyBkh/cQaQJS4VzKmWJzJWFs4W3XQtzpaB94Ghd4TmMKqa5DJEi/3MAuSkEvBeK+EM3m9znlMKYTgycHhvVWpVojTxGYe1YlP0JPgRGHOlMx0OGCAQ4rYUuiy9olDA1naIXEYOJgHsvUU60m+pfiG4CyuCazPLii+YbQNCctsHOMcOcRRoG3nSPOkJK4GnGWeBkzJ9K1U3SXJrLzV8TLnWiYDKY5EdQczFHCWpmllbLZp5D4nSTKqGUnXtkvyYI2Mlxmkt25QJzlFKY2uplyTNYWnD4eBbCzeN2QkUawsb2Oq4qElNIHnz55wtuo4ax1pGjlsH5jiTIkShE2BaRqZY5Q59Kaht46YMsM0Yq1hvbqmbdu3ZserQUoVjXl8fGQYBu7v7zHGLLPqXdfRti3r9ZoYI7vdju12y2azWWD38/PzJagbYyhWRKeaJigykpeEQMCrY/FSnfrq+N4R9j+qxJ30dL9pvP5bH9/cPtUeoWWoFav2jBaZvrxsRrCLNOWswdCgc8EnmVv1mELdluQNaqWSK8HMHPt5776uk0zyXcb7bxJQ+Vsf7/AU3vnjrz338TUcP8vCzzq+VkhxIhdhTE+jBNV5kv5dBowpTNNInCPDcNCq/piYVMi6bdvFsKCyNeviXRbPyUeVir27u1tkZCurvWmaxaVN2OvgYrUxPaIPzjvWqxXvvf8eV1dXvHjxgu12s2i7T/NM0IZerQZqZizmBhkQ0pgw648HvyQ/kZhFXMTq+6z9rlqdltN7uiSs2kEtx9dal4ewilncwXKFh3OmaTuatpMRG5uoo4U5ziQDc/AU5wjCkluqnHqt3iLUzFGuV5agMU0iH+pCs/SG0aq6FMn8S6P94zBLb7NWftaoII0GtyIHdooJUMiXIo5pdU0qslUPYmPQueejIqEaq2IQLoDIiIJd5D3zQtwT38ykUrWWnO0iZGNtraLN4q4ov//tPSnz/MdKAyoPoPINJBxUVbMKr9fvM8Xq65C/QxnYkIUUaAzVkS94QQtzloJBOCryesTZKix70ViV261naWUcqxFLrVKNrp+YIhgZ1RN542Mrr2jwyPMsSnGLB5/RtEnve5zJtlBsodigIjfKybBWg7CTd55Pzpl6RsJR8x6W85alv3o8bxdg01QkxiqMe/yV0ufW0eMChawSuKf92rJ8b+VO1N9b9LUcxxaPpXkp0n83zmO918BVRXqOyVodb+z7jtWqZ9V6ZmuIw05Fa45jlbmA0b58yoUmizeCHyWgn63apU9eC7hKiqvFwulcedXjqEHXa8u39spPq/rTs91rFT1M4/LzIqTj3yowK4q7XJ+Th6veB2/tlZNrWM+L/5WB/RsH9GovKYesVGii8T2RjJU5ZNvIaITOtjrVvq0qPaZYTLFir0rVNa7pSQ3eZYHxyGWZV3Yn1fe7AXy5QCdwc/38rYlxyvA7BtSTVsHJowZw6ZOYBQaFqmZV6LoWCuyGiRQj4zyzfXzk7vYN97dveLi7Fdg6CNtznmZefv2Sruv45JNPcM5xe3u79HPatqXruiW7rGS59XpN0zTc398TY+Tp06eklPj3//7f8/XXX4s2/OGwuAeVUvjqq694eHhYekxdLyINj5tHxnlkd5i5uLjgj//JH/P9732P//T/9p9y++YNP/v5z/mf/uf/H3/2v/w56/WaftVjrXpOl8IwDvy7H/17pmniiy++wFnP5eXNkg0H3+B9I6x253j56a+4f3xY3sOq7wG7zI3mWUhNMUbGSXr8u8OB9WHgcBj1PSkkaByNtgNKEZUo9B6NhwP77Zb1+QWcZYI1+FXHdrMhpsSH772gbRohm3nHk+tLYpzZbh64vLzkg9/6LeZpFHh/nElZsnoZm1H9+JQwxtJ0GVIgGcucEvM4MheYC3Tn0DrPtHkQeFEroJvrKxrvaIySnuaBNMtsfWOhcUgQskgvsXo1o/KWJmGLJNrEEbLBVovj7BXlKrgs6FkqkVISPgspKcYZTCZPQjpL1mBKZDaZYj3BBxHHsZ6SRUQnxUwqoiWw7DdqUK/7TgZbzXLQ1TOkHpgiBVsD/Ok+yykTc9IxOmjUpS9OI6Uk2kaY28Ne1koIgYIhWig0pGKwOTOnjAkelJQqRavDeGiaDppI8J6iTPCso6Y+OFywhKbFtQHXWLAwjaM4CSYZ7crWUZyhaVqKc/jgSaYQ44Rxmqokacsc9lvMHGlciwkdsSnEYtiMiSrGW73LsyblNajGOFNSXIiBqCmKN15IqPOEIdO3Ddl7ctJkqBQtNJIoAhqDCw6KtICssYvKoKGKYMlZnOMsDHlrxTCmFG0JmqVPThH503kcaLqernEkm8nGMul4rLMG4x1NEATyyc01V5fnPLnoSdPE/uYch0w71N7z/jCqcIy8Mus7MDJWmEsizgPTNLJ5fGAcBvb7Pff399zf3y/EtnpGP3nyZGkRgvCLYox47xmGYTFpOX1sNht2ux1932OsYbvbUYBu1QIyplmr/pQT5gTOX8KJrreg/XPr7Ftxq5wE9KN/iVmKum/7+OZ+6MsmNfo5a0VeK/Mjo1fGK4yGZ3Dad2GxkczHPqKml5Kt5OUCWEkTl0PgNwXzdy/M3+UC/HUPCc4nAf03XI8jxH+szuu/HXsfJwQ+dK9ayXbneV5culKM5JwYR5mXrJng6bx4ZZXXzLL+3jp+AfI6avD++uuvefnyJY+Pj8u/Ly0E7TPV9xo1uxXoMNA0gcvLSz7++GOun4g+/N39PS9fvmS32x2z4pyXyqs+xzjGZYTOGPcW2pAreqDqa85ZVaXrl89SCUtSVxmy3h03aCksHIoK951+bfR9VvU669xSeVXzm6ZrCd7Ttg0+Colz1jlna4KO2ggpzNd2k97gGGemeSIqvFfq/GsuYKUijxjsNElfNkYZTCsQrKVvAnF/IM0z0yj3IK56XAlkZ3RMTldMMRgrZFRT5CCrwbwiFFJRy/fKNq2sb6uEroj4nztVgTPHylVH7+Tgz3XwWdoZ0ZCjk2xeZ9DraNsxQNfHr2e8x/5tPbRkP7wdt9/dW2X5K0FPoii7GRTGd1IKLJXfKSNYIOHKc7HOIyNURnXSj69lGXzTSlmU7Orrfbt9J+Q8qyx0acdhpEKTw0qteBf4MrMAj15n7K2RiQPtbZcsZ6V3Mpnhvdy7lH79IK/32CxHirx3GTc8mYbIyq9wovpXbEGE8vJxrFKvpTWGkgVGrsMI8s6lx2+MUWlhmWyQto6c33XOfEED87E6/Y3npa4VmdV2x35zKYJUxrjgTnVvnxZjouthcU0j+g+6FkY152mbZllPtWCpffH6O1ar1cJ8P0X1Fga7VvUV2azXvX6u34ueyQpgLD17UoQTPtNbGvJIsVFFdpb7u1yrclzPC9RSt5Hh3cv5Nz2+eUBPsxwaWOmL5YgpMl9rczr5EFKIMTJbSSn03pIzpDgrjJmw3tGEZhl7m5XgUHsOIh5gcNkeZ3v/moqcd/7tFC751hW6JhCLk46Kfiz9oAXGLyfPc3ofpH9ZCkKsytWcA7q+oeQV0+UlIXjGYaCkxOz80gea58g4jWw2j4TQLHDQV199xXe/+13+/t//+6xWq4U93jTN4qpW1Y5+9rOf8fLlS/7lv/yXvHnzhs8//5z1es1HH320XJNTxbhSCm/evGa73dH1PWfn57x4/pQPP/qQ/8P/6f/I119/zX/+n//nvHz5kl/86pdcX13x/vvv87jZSM/JNUvfyHnHNMj7vbi8pG07bq5v5HmM3DORe5X+2OXFJS9evMf5xQVN2ywyrpvNRgLjNGr/ybPdbmmbbiHL1Q263W61F2gBr1B1ZDoMhKZhvVqRfMA5T4wzu92G1arj4mzN1cU5OWc+/+xTxnGgazyr1Yon11e0TeDF8xdYa9httlSP491+z3a7ObYOOB6gpRSmYQQzMQwHDboGlDF8te55/vSGn//yl2we73n9+g1xjphppOtaVn1H4x3rrsU4TxM61quWq/M1h+0jw34jiETWyQ+kbVFMoWQh7AjEb7DFYZI8t4wMGVxRNTftobsiLHebZwnsURy1RNktYYw4i4kee4XQ1UfcHEWlMJoLAMaJgIj3R/tKxSIpix9X/cgnf64f8gvrrO8pASzFmSq+E+N8PFhLhnki5cIYI9iAbTpMSmBEQa9gRHylBnwjIlDWe6wPWCuGKUI66yVrWZBD6Q37xuN8o4Q/4XjYWMA6RVwSMU0UJ0Y8je0JbUNppIe+k44/3gojvD+/IFtPlw37ceLuUURpTvuxReF7Z9ApolnGYY3ObZMoJWJyVM6K1yJI5JZTjEISRXwSnLXSE7fCOF8COeKuIcRUw6j+DD7I+hE9hRPCn7aTpmkW1AARyj/1FV8SIivrsO9b2q4hTjPbzYa7rx+xyHw6qsi4kIDVITC0Pc4HGmQPtW2rRRELU72eZzXAnhLdFgOqcrRCrSTed10pQR0mdTompcTFxQVt23J2cS7n2zRpPCrMSAFVVG44jQNZCbqVsAzIutFJgNMqffHb0ETJUpMu+2vx7ps8vjnLvUqKYmRxFLUQLJx8Lm8LWGgw9YVFs7gUhdL1Y0GZlAlandqqkUEl/ByzmWNm+HYP++2P0yzsWz3KOxl61ad+p/tx+hqk54zKXmoCYdAZ5iK9MmNogoeuI1+cs+pXIpRijtVShdZkZnxast1qBVr13GtVumgC6/utLM1f/epXfPXVV9zd3bHb7ZYFvN/vF+JIznmB7be7rcxIWqlmm7bhgw8/5PLyih//+Me8efOGzXZDLuL+dnl1ydX1NXOMMtajKf44T5homAZhuffOLa+9lgGNb2ibntCIQlvXdXRtSwheqhWttuM8ixmLJnmidOWEDQxLtmys1QO9tm44IcbI7H9wjslpa6QoSXEcGQ57+q7HOct6vaJrG85WPU0TpLdvDNl7iiJGdeOPw0Cc4wmkp0eiOQm0Oeu6EAjVGKm84zhw2GyYD3vSOGBSFAa1SqCaXLBYurajDV7ESTBMMYn6l3HygYi51PYQta+XZT5b9MphsUMlY0vSqk4Cq6xfJTaJvthJgVykgste5ttTpFivNrT1+D9ec+qftBLLRUZPjT3OQ7+1zZafOS1JTn9XWb6vGjTNUfT+gwrWpKxnkrVa3UaizlIbPMYJmzybo2d70mrXSaa1oIS1UkerKG+lCoxZOBYlRuGKGEdovKAHUxId/ST653NMYMH6oxhLRTTEXS6rnKwQvpJxmGEgW88hIT9fr08WvkPwXtqTOeGdwSFkNUrCqeWwGKTINJF11es9q6iVBnInbZImeJ2wkNZgHSW2DlCyYdUQqGe4qdyoim7UAqZWoFEkfoMXy2WBnY93cokbWqh55xiGAzk6yjwLauSQPbnfqbLbSNv1hNCyMk587KcZ54syzZV4qTKxy7O9g9weVdnkLK0S2Utlrd9Tq/l63p4S7OqoWdM0GGc1KZVrfHyuilYcTZxq0lDP9FyO/AD9CTnjyaovUKeqzIJi/Yer0Gc9QDPYlHFZDi+PIRQIBXwqogGtgSwrJNdYJ4u7CPSecsGmjI1JRmytwSQ51OpNCboEFhSrHGHU00r52Me2b1WdNbv99sQ4BeM0i7JZD5QaWKg98lNJ1VqpiShArWLmGBdYLXjP2XoF3YrrswuePnnCer1insQ+FbUoxEhPdLfbLYpH8zxze3u7kNnq+6pkOJBF+fj4yMPDA//6X/9rPv/8c3a7HTlnlU9MfPXVVwvUvl6vubi4YLffcXt3h/NhUW9anZ3xj/7xP2a33/H//Of/nJIzN9dXnF9e8t3v/Q5917LqOlIR5a6iFeNOZzjH/SiHuRfhiM1mvyQLT26ecn5+yTqsl7E856T3bTAMe3FH2jw8ChPecBx5cx6vSnG7w0DXyUar0HNNbLbbLQBd1yjvoCHGSUhTOZNjYvNwz7DfCTO/7/n4gw9pQuDJExHq+eLzz0jzrF7gYof5qAp7Fbatrnp1zbliVZxjEA1/Dfo+KBvbWrZvXjM+PrK7fyAOA03J4Cy9s7TWEoyh84Hry2u1ZJUA9bCRuV3rwwLJmyUYyfM31hFzYcpx2TuST4jwqMlRDViAEilEHAlD1Eo9YXLVgshyX5MjzVb75AIrV4OTE3Qc3YwaYJ1arhpx8UICq24SrarN8sWSmOt/5VeXZYRVLW3YjwOUzNlqJeshRZxVP4GcOEwDc0wMs0wDeAPRGJKV3ncxYmiTFb72RXwosFbIV87La3eOvgkchgNxnpnGSEmJcL7GG0u/WuskTyCOM/vpgZgS02GkaQVdqe52ThOrmCIpwzjPTMUyugdsM7IrjmQcm5gxLuDbTjy1cxISYGhJ04GcZtouEJzFlEhJENpGxjBLwluwXUtFxnOMggyq1ngbpMW07jusEeJqnBPjPKmoTcDYQrFaoS9CNll07ysSYFC2v3qWqyxr6wNN1xFVUMqoJr21kvxJ4mHFYa0J3N3f0QbHyhu8FWnxh8d7vv7yS+4fHnh8fOTZs/e5uLjiifV0BcYk8rJzktdTVD57t90sPfTKM6q2qGdnZzpfL/uv7/ullVlKkfFYLSxOLaXr+QrHfnssWbkyMsVUToqqegbVQH5aoRcKbnLEedb2TkWtONFeyRRb6jY6bpRv+fjmLPeclTmp/ZysWsj6Z4G2JPMrerFqxo5T+Ag9AJRMEWNcDodijUJK+mazzBtajjPsp8o+p5J/9XHK9D6t3r/VQ0+oCoWIn8ZR0EY+VwvSU9JdWXpL3krG33gvkojWLLrUqRRiThgrcqfo6EcTxFp1UE/l0wyyFLEirXD0cc79aKEK8Ktf/Yovv/yS7VakWVd68J2dnam865fLz1Y46aCKdFZHz56crXDe8dXXEvw/+OADQhP44L0XtF3Har1W+Baub27IFMbDyDxH3DCIIIURkYeLy0sMhjimJaB3fScHkXNY65aFX693zYpDCPhSFsGK2l9frVZAYZpmRSuOSEwux81kDOTsFRIUUqIx0DYCva/Wa9qu4/rqiq6XETljjaAJJXN+tpbEUvWyK9ll0c+mvJVQyfoTuMm7gEFmsUWVS+DEPGXGGJnNgcPmUSp9ZAY5DiMmwziMpCmyu7ggBE/wFu8MjfM4nCTMWWRBl8kTRHXMWAe54GLUSktnux3ao5N+8pGSWnAL1Kea6rqWczky40tJ5DRjXMCoGl2dm0crjIqgFVMDMktfOdcDz9Q6TQ8rU8Heuk8r0lEvqMOFsFzvWPuqC0qgKmjOLUmCMNkVXi+ob3uFK1hEW5L2sKtVqBQDHq8zxaFtmVPETm6xUfW+ITTtokyYU8GaiTEMgE6tZOkL6w3AzBPFjuRGImXX9gQX8Odn2KbHrFZELPNU7UmPRYy1UqETLSYjpElfq9qjRoApOves94OiiGHlBMg20tGqTClHlNXZypLXfrXT9katxOvP5JP4Us+8oqO9uf6sJ2UhWxpYkJrlzhqzGBvN04wtSaSJMXqmOJlO0CS5VtcVSSjzLMmp0/n3JKYt282Gw+HAZrPh/Px8KfCMJi6nffHTMV8ZOd0uI271bKzPXcVqGlWrdBrQXdLCIM14K2dTomBSEnOkkzP6tOoX5OgYk8oSP449d05Qr+P3fvMS/ZvPoReB7ZwGY5cyJWVsStqvsdpuUsGKfJSaLE1RkpGaN+TCnCLjPJE1mPumwTdhWUQpZYE2nB41J0GsfnBycU4v4t/9cTxkckoC99WArkp2NaCfjuXos+sNgOBEN/pMR8y6JghiMUfpscUJYwptGzBkHND3K5wL3N0/Mse0BKca1EVedf1WUlMDYdd1GGP4i7/4C/7yL/+Sx8fH5WfOzs74+OOP+fzzz/nJT36yBMftdruwM3UYBec87330AT4E/vKnP6XrOv7e7/8eV5eXfPLJdwTWj5FxHBgOe96ncHZxzv3dA4f9ge12yzxH5i7iQ8Pz588pBfbbQaYfnGN9dkariQnAeBhIyjatmbMxMsNurBUDCK3Qz8/POT8/Z7fbcTgcFrTCarJQyYHzLPyCrm20D7tnjhMW6FWU5+rmhrOzcy4vz2maZkFEHu7v8M7x/OlTaiCf5lH64qCvU+7zqURkKUVn36FtjFZkVWBC2OwpJsY5kmNk+7hhHCdMaHChYdzviNPE7jCyX62WBG617ln1Db7rxAgDgeWzajdgaivKiOVmzoR5ksAgGbKgYFkOZYuMrbki43BeWfXeSAD3pkLpZSHLlRzJyWBSBOcpNiMaE8JWzyRQ1ErG7qQNYmxNE1jU6tGUYqnM9eMY1GuNbgSRaU8IfElgSxQez/oz1nsRuLL1DBIQOut1Ks5iloAuhiQpC2xajUecD/ggAbsJnrbTgD4O4ARFDE1H161ZnV0qucpi/chhM1CwMIvr13iYMU4SjWQ8rghSYa3nbLXCdCu6J08xTUduL5gKlDEypcwwV/tYgdDb4GG2xGRom0AXHFPaS9/ZycRCiUnh/SM8a0xR3RAhiXonJj4lC0ETFf1ZppdKUVEYvfolU538KJV0yqKdUQoqqCPIoiCiXv3k9S5WqF1blsawzHjP44jNDrqjUp3T4Nk0zQJzS5Em45tRk7lSqvdA5LA/cHt3x2675f7+fikG6lqy1i5TPqWURdo6hMB+v+fLL7+UxP1EGnalxlGVgNy2LT5rPKAQkxQd8ySJdtu0svxyJh7cr8WqUgrTPInx1TstgWWsz9bgX+/ff+AKvdGbI5rRko0QI2kcyV76hc4nGeGoLM764qMIYZAl25qjqJLN0yh2mAaKilD4ELDuWAFko6SZUuGIt/viC7P5pE9Sq71vH+DL0kOvuVIlxZWT5wfNEDky2+W9ykKTGW/x6vZOR0B0MaZ5JqdM27RcX19zf3vHPE6aEWoPLBcxI8hlySjrwjo/P18g+crc3GiG+vj4yH6/X2a5rbXL+Njj4yOXl5fLol1GCZ0c4KHpaNqWq+sbrq+v+OD997i4uOC3v/c7rFY915eX4lz2+Mh2K4Slfr0CZ0kxi5WiWh3utgcRhdFgU4O5bwK5ZOnla7/JGqk0hX5QlnnREMJyaOdUmPLMPMcFXXh4eODi4oyu6xjHAWPg7OyMvutYr1fEeWa32xKjEIHa0HDx7IzziwsuLs6FsWzMcp0p4J3nyc0TSs48Pj5qrDFM07gkQCVnnJcKorJ1p3xUxJPDU+BpZyspU4iR8zjhKARTCEZiYtt1tF3Ps+trrA94v6fte/p+RaNogndi2lHSTIlRA5KO+FD1FgyuVtQ6U25srdygZAtJqvjaQzdaoYMQOaWqOu4GY6QCrPdmsU/lpNtdpJovRs4Ek4v0rhEY9W31SOV7aFA//W0VtkSvoQR8txzoOWdcA8Z6ipFGgcjyCnmrlLRYhNpihVEOJ37fUrEa5yD5o2iUFREXHxpKG2m6Hqd5AcbiQpARr+Do+hVtv8KHRs8otbZRP/HQ9FBmTD4I8Sz4pXW3tAmL8IymcaSkwmHMTBkepyRmLa62Z456+ME7HIrWeEvxTpXrtJd7UgnWO2N1xt7qGrYFKJk06wSFIo5N8AtXx5qyXO+iCY8zwiUoiDCYtXoWVyQUFti5FlmnFXY58RavkwXOWrq+xVsYp5E4F+ZBtDhCCFxcXND3PV13JmOFoCpz8vbE5wGClQTPa4V9fn6+QOg1RlS3tCpuVuH0KrD19ddfL8jB+fn5ckZWzY6qQFlKwXrR5C9G+vfzPAsXozmiD8a8XViKVn859tBr0qRJVD0fSj7qDZw2n/6DVeiNzpraospLKVHiTFYhkuRUKF9hP6lWrWbgcTkpZMZTpDrnaRQlpwrxFDUf8OJShLGSCNTNzjGLr/2NetF+k7DKu9ahf9PDnPxXmPYLevUWKeFIvOPkQ8kp+vUS0DtlZJcsB531TMNIyZm2abi6umK/21EeJZv23uKsI5q8LCJhdKructsu8Plms1kyyM1mw+3tLY+Pj0vlWn9mnuclc728vHwrc5xjxEkzln69pl+tuL655snTJ3znu5/w9OkT/uE/+kcycUDh/uGBbCCmmf1+JwlL0xCnJOzTviemKKFFF2iGBW73QTS194fDgi6sNSmB48gKoH9nGOeodpZJHZfKMjcKH9J1HY+PUn6dnZ1RbQz3+x2bn28oMRPNzNlqxfNnz7i8vuLy6pLddi+iE7OwgK22RK6vLpnGkb96/RIQLfthOLBXJ7o6whS8eHXLepzf2sCyROWeVk2ChbHvHN4agpF+5VnX0q9XPLm6woWGbByhaRWxqT7SAR9aadcUDehFLbIRTgdG+p2FvLSrTI7UERGTpYksY6U6U0Ve9NCdRmhniu41s9inVjZ7RaBszWK1okhZ4GKjvU3Ji40ewPpsSyV+DOoLDq4H/ZKUn1RXInAiAjgOg3PyfrIKqmQMk8qZYpysNV/IONm7RoK4dQbrtKdvE8WIP3Xtn7umocRE03UqGSyucsY5XNvi2oZ2taLte7wqIVZoH+uxXmmCEfI8YJ2lCZ7sRAO/JrBGE6A0Sg/7MR4YM2xiwTcN3dmF3A97lOkNwVFsWNovRn3FqxRt1tHDkqtYjxVfADWEstbI9IIiWOQ6XiyQfiXUSrCVNmNUwSNrFK0sBdtUbXGtwkuF2t2CroHsP6veHjVJB1mKFVoXNczEtN9AjuyTBOlTXo10653QNXPSFLSOoxaZ8dc+dv2ZruuWYqa+r1Mp1vrn7XbL3d2duEmexJMLDejGCHt9iSEGgs6ROy/SrfM8C6K1BGptMb3D8AdIMb01hlsfR5i9LK2SJSItxaLu8W/w+OYB3YXlJsYSibkwx8w4z9LjKIVkDN6h7mIiPelshd4K4yjw6ng4EJVQUfd1OmSmOEDXSR+r7yULTpOSS9zyPrXpA9ozq/03yXqOQeHdgL7McS5A4OljSRn0cHEnERtKOUIgkkEra9oavK1KU2CsMkmtpaQsJJHxQBsabq6uRYO6JHb7HfvDgfu7e351+JXIkFrLHOU19BdC3ri7v6NtW9577z3avmN/2INBRih0LOPly5d89tlnWGO40AoeZP5/TokHDehVPz0XIWwV5KDJpeBiwsbM+vySJ09f8L3v/4Cr62tWq3PmaeLV61fsD3tiTAzDxHa7Z5pE+OH2jRD2Li4vaXxD37dHedcsizR4z9lqrdWeQm/OLz24pBuvzrhXNup2v9dzozBORxOGELyupYHddkucJ/7eP/xDnj55wg9++APubm/5r/7L/5JhOBDniZvraz54/31BA1Lm4vwce3nJ3d0d4zCoscXMl18IkbDvV4skZFRb0irfePT9Vn1m5xGntqDtokTJkGI+Joc1sOvBZJRsNO7FROKLzz8D63h1v2V9fs7N02fiNGct4yR2suLcJTaXKU4YL2tORGGOB9Y8jVJdapCTWtlBOfpVFxIGCcB19lgmCaTDXnT+3Vrx06pJqzUCYtUtqIg9S/qm/prCmTc4ZTCbY/Go+1C/39jacJe/e6sikc91C3svAjkpTmI24kTPfRiPSnGmUHngC6vYIlKm1hlmK0WGM1aY/9aBy9gmYHPE9R3zsGe724vjYEn0VvywZeTLkOaRnBPDdiNn2bgTHow1RGRv+bbFtz00Kwgdk++IrgHfUFxgBOYMQypExMgHFxR5qPwISRi8D1h/VBrz3ktbw6gWiBHmd+O9kDEn0bSIEQhSXIRqvYsEwTzPUDIxJr3AYgPsLcQkULqlyNdF2OQOIeHFeNQgMRjwHoxlijKOHEJTO5dAouRJRpyxmDLjbcP1xRpTEts0sN8N3L15hfeWJgTOLy5YdStysUKGFuci8A25iMd5SpHN4QBk+pWQefu2l2vkLNW2+jAMzHGmbTRJ0MKyaRq6vmd9ds4cZ+IkPuYpF4ZxImeEFJkSF2fnipYdSXLzNMnoahdZh0ZMet6C2eUc91rVC2/qbb2CpVg0J9yS04fRXVK+eY3+jQO6s/4k2zoSFWY1E8jGgEtka8TJB9U+RklvWXyL4zyLRWiRLBgnizcTKUkPgJJwbcBaSHmWw0mkro79h5rxn2Y7nJAReDugm/oNmg2Vd4J6BdqrgpV1xwrCLN+g/SWd5RTZSHGTc+aoGOe9ZLKozOk0THgrWaQ1kNMlT548ZfPehq7v1ZxEZFJD6AihWcYodrstUFitheA2zTM+eLq+wxSzVOCvXr3CGMOq798yGCg5s1e2u7Qxio7uLEeqKFJlIQo1rSzyZy8Ecveh4TCM3N0/MM2TeCYPI4f9wKiEuu1my26/5/z8Ah+qCUskqiuZXBNL2zTLOM+6X9G1HYfdQQKUjtK9JRubE9vddrndKWWVbJSPnLLI6Q4DKSdevHiP7373O/yz//g/4uXXL/m3/9P/pG2ILZdXV1xfX+tIzIFee2Q12QHhSgjUbhTNkNeRtfJwzhNCs6yh2ss11mlwqGtRBU5OvABqUKoEo2qbOk8TMRfubt+Qsdw+7IgpESdxKqMJok+fk2iac+RWJCNM8Kg6B0LUEhVHo+NXGKnaq/65qetZofZlKuM0UtcdsSSwp4qIR8EocxJ3pRrW96pdeBldW3bQciqZBQU4DfT1D4XaYav7uF7vOkOdZqnSvB7OtTfpbVPrU/koOlqLmK04a9V0pVqIahVpHcZbqXwbTxrhoEE7lSziK84iHMNCSkKynMY98ziQ51FIai6QKMQs+gDWN5jQYpqO6FqMDcpB8EQMsYh6YDIG4wJYlYFVFEi4QyKQE5yMGIKapBRAbHhAURPrPKXEE3g/E6wDJ4p3zlpwKotMWaD15TitiA1FZs6loQBFWhrWSJGQVEhsOTjlcCbmTMCrQqg+i3IwbGVRFPnzqmugJEYvuia7zSNNEyh9w3k+o/GemFWLzHphzIcgapSDcAGG4aAjpx3r1Zrrq2tiTExpJk069ppF36QzFf6W9VilX9uug9GS5rQgwTEmSh7Z7Q/McWa9WgNyT3LJOrs+isubwvle19SRMK1YiXVaAGpMOKnaZWmfxDM4tu5OUOmy7Ki//fHNx9a0J4pzMsdrLfuSuY0jfePo+4bRGCDhsmR3bhbWbD8eCM5y1jfEPHN//5r721u++OJTPvjwfT757seqslUoZiQlByFhQoAs0Lvzrb4GgdJi5u1xE+8F+tcMK6bqmyw9KEohxZl5nhgOO61KCn3b0LXNouc8jxM5F5zvMUY8to01i9CNOAkJQccJ71iEN0xZdJeLk03UrdcYb+jENJe7u3tZTL7l2XsfsDq7YJgTN8/f48/+7M/46ssv2T1u2e92TIOQOB53W6y3XN1cc355jgmSgWJgs92w22z51a9+yS9++Vc8vbphdXnFp7/6lOFwYJpnpmnGGQ8mMedEv15zeX3F7cMD9w+PGnRgfXnN2cUlX726ZU6Gq5sf0bUN4zCweXzkV7/4Bdvthru7N8RpYp5HGYGyRli9IDPQqbB/3IgFIDJ3enVxSfABSDQh0LQt0zhxf9hz2A2qmOcoFM2ELefnZxhrOFuvOQwHHh7vxQvcWhrvCN4xDgceDQTvWLc9n3z8Md/5+Dt0bUffd7z33nv0fc/9faBr2yWYHw4DxhiGYSCnjDOWNMvheHlxSc6Z7eOWYTiwedjStA1n52fq2CakHR8cu/2ewzAzDJJApaIQMUYkUYslzjPjNIoEGJZ5HohxUlctGa1zXgg6MWcdkzpwf3/HxdUl55fnlCzMfR8cTQikyYhXdxQVtU7H4nISHkpjVU5V0ZhcIsZmcEVMObA03mCNl1EkNVlJObHf7KSC9Q5fDF1ojwdLyhQTsa7FWEejINacC9k4XLdW+Loj5sw0R0LwNKHRBF409bPyKgwW62W6QIxRinqBa7tMpwaql3xJMzmBN1nMUpRN7XVCxGvCLkS9QsRAnCElbJT+76X10K+gbSk5MR8OxDSxSRNzGtmngdKAf3LGYb/jsBvoXcKEzH53Rxw3BAslJdjd4qaJFQJX+xSZ0sg0JfZjhoNInjrvmEJD9g2mWWGaFX59jTGOMCbynHjcHmg6z2V7Tk6RMc7kORPnhO2kYDDeyZSRJjvS2sw6GiYf1nraVloqdWQWWPr3dS5d8jdx9bPG0HhPKYlxnEhRpxoUaV13AUyj91vIG6VYohF/+zlLwhN8wxgj+/sDOU3kEhn2G+I04Ig03jLtOgYz8vIL0YO4f/010zTS+EJwhWBhv71nGnY0KiiTiqUYS9OtMMbicmScR169+hofHHO6YBgHhmGg7SVRH6aRcRxw3tEFGXctwJs34mux227JpbA6O+fqOrDqelbrNevzNWlOwgsKDcVYxilRyixtGYSgZ0qh7xqCF2QvhEDrg7YkijpSdsQ4L/apXdfLlENoycWq9nwmNJ6m7cBa5pTxizJf5ZV84yj97exTQYJoMZZsIQJDTuLsFJzAiVmgB1MKNoobUbGRNnsu+hYMTNPAYb/l8e4NN5dr8nRQBYaC8QVrPcQBTMIUJxvfyOZOxgrEpz1pal+iSNAuuSyCJCJsoSxklVWdxoHN44P0a0zB5hWNzZTiwTnyLHrntkjmjvOUrC5xxkCuJCEo3kNx8n22yDheEVlOozwCb6xk/TlxGMalR9Sv1rRdz0ff+YQ5Zb56+ZLDYaDEzDSOWqsIlBYaGT3r+n5xnQOBWodxYD8cxLP3RiCrkjNpjoz7gajyp5IIilf62cUFu3HCbHeyyXOh7Xq61RnDGHnY7Pjiy69w1vF4f89288jnn37K5vGBN69f4azBOyvOaF4EYbyTijlrdRnnWWBCY+iaRnpqCu16Zxn1fkiVHxeugFfCmXOS3dpWCHjHSsIsfdwYZ6ZRGKpn6xXn5+ecrc+0knMLYa5pmoUYM89RbWWlVVTNV5befRDntsf5kWkSo4fQBPF+dl6YuKoJvR9GUpbkUUYaM8Ue5WkphpQRG1MV/8hZpkCyVp/eO4FCh4EpVptJUQuMccY5K5BnFiWuKhV8JH8KeiYjluJQKM5Yeujr/cVYSY5V4cs6pyNPGgyMwo3TLEkwYLxCh+b0d2Xt30qfV/JqEdDxLmB9Q2h6XEqUMhKcw1tLTmURV5Fg46QvXqFZRd5LKsIDIKo0qV2QgFLkX2pLzxYhblVmtj2+WG0HaBWqPWZjLU0j4kTFiflMHISgOZfMVDKjBkjXNZT5QCSTTaaQmKeBErUvnxNlHiDOmlgIPwE9A2MqjDGrh7ohGUe2AesajG8wbS/MdyIwM5cBVyxYaUOlPElfnExSBcDTvmq9HksLUqt5Y8Rsxqg8bhWBKdpaq2iHqVWfzqNZI2p7deys/r3BLCQzGYMT5nvO6JmIWsFKcZVjlX0eyXkmziM5TViicA7iRI6Ow+6RHGf2uw051QpeoP5pPDAO0r8OTUfMUJB+vLEy65F1esUnTz+1y9mPFd30mGTv+qYRpEtR4sNwYBxGHh4fhQh3cclqteL66hqvZOKSJ1ISPpizhZQK0Yh2vwj2yFkRvFMCbDmuQ1OrbItznnmWAtE3bjk/rHMct5OsWfk7SypFxYjMCWZVvnFQ/8YBfRhHgdGsYZxnirUkZ5gNRG/IjWMYJqY4i+VpAZ9mgb1mKM4zjp6SZy7WHc9+97f443/4Q7788nN+9L/8GeeXZ6zPen77+7/N1c0V94+PTIfCzc0LrA9McyTlwjxFUpEKyAU5qD0NwXma4CjW0vW9wH06m7zdPHI4DHz5xefsthvevPqaYA1tsDy5uWK8vmLdybhKnGbp+64MzgU8LTlP3D3cykJ4eFh6R+v1mvV6zWolI0aVHDKMk8CdpdC0DavVmmJYXHtSFoOD0Hm+98Mf8OEn3+EHf++H7DdbmR7ImVH12L/4+it80/D8vfeFEa0WqaOyzLuu4/d+T0bLXn/xNbev33CxPqP1gc1GFODO1tK7nhHSx8X5Ja5puXpyw6s3t2x3O548e87NzbNl1Oy//W//3xz2e6bDgRxFWQ2dTXZWxTpiIPvEWISt/rX7Ug0yJCM9Oz8Th7h1RwElt83s91HscdVebOmigMhCxsiPfvyjk9n0yOGwV0KNXURhyJnUtfzxH/8xH3zwASUnHh/uGcfnHA4HXr58ye3tLa9evWK96rm6vDiKPWQhBdVRtwq71891FLCq88WYVLsbkaHsetbrKHKgzmvFLc0uMY8QpTRpD8hBl1Ki0Z7m4SAz+1X6OCOfrQ8yhkU9ezXoOSglMU+JOE/kOGEVcs9RE14lXXnLMo9tS8EkOT1SilgjiYEckjLDXLK4WaUiftQyP2xUzEkUD0XiPUKxECMCvHsUuFaei0LzLuCwBK9z7Ulm542OStWeLRhKljEtIe0hDH0dl8u5kOa8NL5q97HGsVIEWq8HqlmMlUT7W+B7aT3Izxb1m5A2WTGW3K1wxnJYrcEYkeuNM2mOxFKYi2g1OFNI3hCMYSoRkxPTsBN/8VmSIOsDc7b4tiUbyzAlwpyOrbTVGazOKKFjKNKrjhKBOLt5CsawG0ZxaZsS2WSCyaToiM6QsyEbddyz6qhmxCSEbMiRY/tDY7fR/ZXJC8GwFBmLXdQpi049GJlLd0YIn9KSAWectm9kSVq1rLM6AWGswQVPs+pwwdI0lpJayBMmNZgS6YOhCZbnz67pGk/jZL31rcSNh8cHtXxN9KsVXbcipoz3B8Ypq2KfhDjXNKSccKbgdW5+nie1Wx05HHYL6bYgc+uHndwH+R75XsWlhLEeJ+Y4cRiMIhRZWjRNkKTbGnbbDQURlnEW+q6lb1ou1ueqPMhC3q36GsZIsSPiT+60ISSh2hxR99PH0rz6ps1zfXzjgC7ZiWwiGVOpYhHHrnSupB99c1mrklpxVbgneMfl+Rkff/CC4bDl80+F6DIOCNSjDMui2eDSx0lC5tC8XN2RMkuSb620BIwq01lLSrW3eZRGPewPzBZmB23wItYQZ9rGk+aoq9bjfZTKImU2j48c9nve3N4KP8BZco7UIRxKWTLZOCeMNYvZSc75OA9UpEqz2uvvup6mbWlDQ5wmGQ/Mhf1OJBC7M/H9DtV31zqd8Tc0bUdwnufPn2MKHB62xGnWtsFRTSx4lUvVXjBIctH1HW3fMeesfufX2oeS1sR+t+Ph9lbgxZwJ3snsfFHI19pF2rIYw363F+JYG/AnPaHKfi3UHrLMd6f4Nvs063MId2D3lkHNPItut4UT3fsJaw0XFxc8efIEH+QQGkfpb1UrxWmaaIJfnqOS007VnE6fq472ee9pVATnON1wFI44jkyKVeQiPnSikyABRtmvpQACMVep0WrWsPTJ6uZeqqm6tlEmc+1pnmgg1PVViUpLW67Od5/0pBVBEi9rq1VsWdTYah9RRGPqXLNW1rlIT772ULX3vZBS62vV9WCNsunVOVFeBMeIU9DfJXyTchqN9PtKyUgKUqikoYXoWtzxGtRrZvRAMirQqS+q2qaWeu+U6OedJzshaHrnpU9qjqI5cHJIq0tMThMmJ+YUKfkIT1sgFk8xDRUpEI6KonvLXL4kknIHZQ24YMhJdB6KmgU5W8hG2w9ZfSXscU1UYSEpXOqSKcvnuoaWL2FZI0vkX66r/F5bkciaKBk4pkOcXO+TSR9dz9Y5yA68VNEyuumxGFadp20cXdvQBicVu5IN/azjcEmSzqLIU07iQJeStGvmScmpuu68Vsj1e+d5lvbUPC2v1CDxRzhKiTQnVdGbyckIWpbkvENRDCHqSqVvrUwp5VyIUZMAk0QEx0rCHoKHmMiznCUxRdGhOGHXH01Z6l55O4ovPfNyvML19b+15v+WxzcO6POcwEqPpi5IiooZxMi0P2BSJFAwacbkTGPFWeq3X3xAYy15t2VOhhgsN1cXfP97v82zp1f8vd/9bf7kz/6Ev/z5T/nFz/+KN2/e8L0f/ID12TmH/cwwHjgME3NMjFOSMZGmW4J5KYkUJ7kEWbWujQTzKu9ngGfPntEEz2G7YdjveHh44LDf8/Ll1/RtIKhRvcHSdmcLCWqeI7ev3yyzi6u+5+bqmqjQ6WEYCL5ZRBOePHlG23VU8ZdxHDHOYoMn50iOcBgHOeCNkAKdQltpEpnJnAvWOC4vRDN9P44YMsFDCA1N2/LsyROur655/733Oez2fPfDT/jis8/55//8/8Wrly+5OLuga1r6vme72/H6668Yhj2ZhAh/Fs5WPU9ubvhn/9Ef891PfgvvpUJ+//kTPv/sM/7L/+K/YLc9cNjtMV3Hug1S0ZVMJEOyXF1d0TQNr169Yp5n+rM1IQQ2252IODSB1XrN9ZMnS5b/cL9hu91xcXZB07R89dXXTNPEzfUVBmGh1mtXNFkax4FBZRhDCIu3+3q95r333uOT73yM955PP/2Uly9fEoLI2Z6dndG1zRKojTE8Pm6YVZv9dONVycema+m8GGtUQaFqvziOI3tFUGKMbPc7oprqnEoNn0oUy9cwxUwyGVwQASLtO89pyzTNFDRpTVF0GbTXKQQlIcW5kvCk4xGbZ6moU9bAbGBJPI7xNIPEV4BUcJo4y9kuB3A9eE6FLepRIvPIIjBjrcO4jDNORt1MxuqHU7a7dzICJRMWqrBYR56MvqAkAjY1oVgklRWyMDiqT/lxjlkOOo+T5NpIgqsK9zqnDqOa4uCchheZx7apLI5kTWixxbDyPZiImw0uOQwNs2mYaGAqTHHCtlIpz8Mg2vZZWkyHw0HOQhswVtZZEzrappGRQ+/lsD8MzDyQw0DqxZQFWsiQonAixmGQBC0nlWAVI6/kCjnp5LmOE7qFcCWs7pxluqIsyZMy4CngrLYKJBmTlo8kmBR5fmuFWCcELqdxvUgbpBydzHI50QxwhsZ6aUkZsadNk/BA4jzQ+ULjoGlXrPtOLZQtJQ5kZ3HmnPWq5+LynGmaORwG2rajaTumKRJjoulbjHGM40Qu4Jugba2MsdK22g4Htnd3StydFnOWs/U53ofFHrVfrSmlMA97SBP7jWMeAtN+txDanPOLwAzBM2ch5G62DxhruLo5x7hW0bcgZ8K8Y7/bsd1ueHx8ZLvZMhwO9H0nExJOVPCqk53RscR3hWb+1z6+RQ9dNpOw9mqPTvqBcZqZ3LBoAFdoK1gdXTNyGOUc8RbOz9b0XQM50zaBq8sLLi8vuLy4EJUenSk8jsrohtbP0kOtBUImRTnQyFlEHmxYZkRPD1XvPa1KiFIyUdmpmCLqbLn6+0JU3WBr/cIkj9ofWvU9TdssB7yzx5l4IRTJaFXtXaWUFuEOjAAudS61mKyEUUlPTM7Kji9LICuAi3GpGo/a9bJQ+q7HGbu0ANarFfuVaLVb1dGXxb0Wm1I1fDCm8P577/Hk2TPef/GCm5srKFoRP39GiTMffPAem4ee+9s7rBEDjDpgUbPGaZpI+aiBnKIQzMpenrdJLQWz6LCnnNjvD4zDRBNaITmqfWxOWQU17NL3rkpO3omSVHU/2u/3lFJUr1lGdmIc+OKLL7i9vV2qaOfEq/3UUek0mFcxG6jGEoVQtJ3j/VvytHW2ddZkI8bINE7McV6Sj+NSMMsYS7WXzLKZBCqWOUf0yAVj8C7gfFj6wovGf85YKwIwirDqPtCDG3MkZVLrMlTmNEvFZAQar6ptSyVeX4t9O6BLTNc9V6RGq9MhR923shz8khnUkaZ6cGSOyorlWIHU8kMviiB9+r/6vdTnN5pbaGVj6p+O8+u21jw1ESknwjbWLM+btUeZcsFYJCUwVuwtEYnVyn8wRURqKNWuVtKKXEQHQISPHFGvZTWq8k6FlPTDOUkwagKQjOisV6066UCowmaSloPRa1XRPxHrMoujn7yht2CH5botfId63Y0E+WKPVXm9QXUNZNVotXVE0YqFMYbFIlnOUo5WqRWZMTU4sRCHZcTO6O+oY1lS4BjskrSmKH0CKZ7k5TVNS2gaSpHfHdpugaxLKbjgdQ0URQhE0rlT5U1y0qkEfX6yTFilSDMHORdKoiSIkyZnKWpiW0T7PXjS7DAkYhQi3HDYYyyMY4PVsyn6oLwX4b6klHTSRKD8usNqHKugUY0Vp2eFSDgcd2b9zm8jkPbNWe7WY7yj7VdEUAgkaq93D5vCs5srVmdrUaQCzr2jcYb9/RtcyTAeuFit+O0ffp+SIl999it84wmN53e//z0+/OgDVudrfAjcPT6y22zo+zMhehVLTBlnVfPYewqFNE1Mh4EpF4oRFSnfdiK7eDISUFIiOM96tea9994nzhPT9FxnWmcOuy3zMPCwe5S+qZsAI8SoaeLu9o4QxCP8+vqa73//+5ydnXF2diYH+hS1Qg+crdeEpiHqASu9lDoL63A+MCfx4D2MA9M0McwzJWV632CRIJmTZItWhS+8D3RdT4XCcs5sNhuRW0xyIHjr+Kf/+J+y20l1vN1u+fc//hHn6zO+9/3vY4PHBMeQImOK/N//s/+Mf/LH/4SsBivTIGNaZ23g+fUF593/g7vbN/zsZz/lV7/8JX/+p39G27R0OoJnreXTzz9lGAdePHtBv+opyGJ/fNzgg2i6P242/PLzTxdRnOubJ1xcXrHd7nHG0vcr+n4ljGdkTn2aJu7v72nblidPnrDqe7r2GX/0R3/EH/zBHyzQu/S7LZ999hmPjw/8i3/xL5imiYuLi6XiHg573mw3yxz7NMroUUVVqoFDDfKnkrNJq7AKzQ/jyDhNC6y/Hw5L0H83oB83o4bZArlI8mCKYaoukcjruLy6YX22ZtV3BG+J06Ce5jO+cXRe/MldttTRIcPR3yAX8d0WJCQxxcwwJ7xvcT4sQf2oG17AZIxvsVic19aGau0b7Y0bjIxX2Sr+pkZMxmCTuImJroQhz5McY1n+LidN8DgFyDUoqAdEKactvAora6DWnEPmmFUFDRBc6yhXaouhWENSIZeYiozFqhAIuVBUWMUhOv29d4IC4LDFQbaUCGmO5Cg4QK7tDddgg4d5BuPwrWiX53FSopTDuoZWpyzW6x636nB9y8FaZgo5ziIMNE9SVVsjmgVz0tcozH2HeEI4w+LCl1UtLXs1JzGSOOVidf9HLRRQPkVeuBl1JNcq+72ei+i1mlPC4/BOrmvliwAk5mW0Nau+BAXRuNcq3VhpiwTv8KuOYDPRGzwRZ6W9NQyZ29sZSybOe0pKpDgSvGfVr6jmKaFpaZqWpukkwHdrrBWeSnXeE2lbbbfawuVZz9Pri2ObTQWj6vjv412WwvOwlbPYFMiZ/eau7tZlJLbrOkpqOeQRax3DIFbPm+0GjCGWia7rJIacn9M6SxxGhfyPKqUpqdCPFYEf73X00cprNlZbym9V6JKASJYL5Tc12P+Gx7cI6O8Mxeci2tOPj1hvcN6Qz1bYpJrTVi6aL4k8iYZ53m8ZKcRpkLE2CyVFxmHGIFmW16rTWouzheDErSl4UYsSYogcLqkUco4iYqJjalizCLzkKOSkKp/nqoRq12nvw5FiS04zzlrmpqUYqwFaJFqB4xhNKcshX7V++77HWU/wcfHndlpFO71WR5MBZY6q4ArI4eSc0x5i0vdSmOe0jO4Yawn6u70PmthJBh/nSLBSBaz6FRcXF3zyne+w3+953DwSgue7n3xC23c8e/FclN4MdOsV3dma9997Qd+1TMNIKjIOlApCuqLw3vNnnK06vIHWe3YPYioyDCK3WnJejGeqItqcksy61yqgSJZfr2uM0u8ax5FEFEUrL5lznMalIrfWLtrLKSWKVzWniws++OCDo4SitoC++vKLBR6v8OC7MozTNMlEgDlCXlZHiwyGOc5LdVqDZO2J+aKVgamWqXIfasA+lR+uP1uJcrV6KcYdv88YZYU3XN/cYKzj6bPnrFY9lxcX4gGQZQZYDDgUJTMycrlUWrUXWg87FU9B1w62iFqaD0vFrUPV8m9FKrJis4q1HNesVEA6r40mIgs6IFdACvSC2KwKt6QUCVRLlaivtlbaRd/NEshzeadiqW+tLPw21UQ7amEose5UBrYU+ToVFbspS+d9QQsoQsiypShyYbE+4EKDbxrmnJhjFtNInVW3Dnzo8I3Hx4jNkaYLpBwJ3UBJwv5vfEvbCt9luTaIsJJ1Dck3WOsZEeTEGDG9aptAnKUP64zBG0Nw8uFUffCUA2HsccrBnLZ29JqZinScXMcFNNFXVvk/p62OBa0/KQir+FQVEFvQioxA+kanW2IUARlFxuxJ2yelRCQzGVV5ywr4W0fOhf1+v/Sam3aiaSYRarKOdDhgjBUUdlmbBWu07aRjEE0IBOfIbatju5OIV1E4P1vTaDIvqpxBCsJ4NNuyeo52XasCUrJXZ+UyWCNckzqFNAwDbQjMkyR01fFT4P46bSAXoI5Qv418HTdQlQ5/S9uBCmL9B6jQjXPgVFu7yAbcb7d89dln9H3DatUQ1x2mb+i8pTGGjoTLmbjfk8aR3e0tab3idee5ODvj2ZMbHrYb7h7u8W2DC0EICznTeOkxdm0L6IhJylg3i59wyuQ5CRs1ZWIqhNbhjZihuBDYpVGrmCpu4o+HcVGij47RRHXkmoaReZ748vMvOBwOxHR0NKvBvO06VqsVZ2dnXFxcyEZMedERTkkWq/PaNjiRRowpqRUtArF6j/WOEgTu37zZMI8T+730Y421Mgd9udJKstX3ANMwCGy9WtOEwIv33uf66ppPPvqY/W7Hv/23/zO5ZP7RP/4jnHdY7xnmmd144O//w3/A7//h3+fh8YH9YS8OTiXTOphTYnP3Bmstv/PJx6Ln/fu/x6effsZvffwR/+7f/Tv+/M//XJOPmXXfs+o6Sk4chshufwBjOLs4F21+6yhlFh4Glia0zHNks9kQjNeWhUBSb968xlnLJ598QgiBDz74gGmaRPAFMay4urrid37nd7i5uWK97klJNte//lc7NpvHxSIR3Qy1Su/7nlevXvH69Wue3NxwfnamG08Ma4w1izhKlY6U0bqRcZ4IrfghhzZgvWWaJ1JWi8iinsoUEYY56f8D0msLAWOCQIeauffrC1arNR9+57foVyu+852PRV0qR+I8Mu4eoUQgYpMw1l2JFDLF1J7mCRGqJojWUXzAWZF6dW2Lb/paAi9mJbb6oYcE1uKSJNfOVr4BOC+iHrO0ZEUsxkpOkLRhkEshRTnYltGiYk7EnTQLQILTCVK8HPo1+smMutHfKU9qjFSiNQAJiq4IwgKGC/qQkmU2OolRe8natsjKuJ9zlgLFOLmn3Yo2F84urnjMsH9zR4qFgsc1gbb1dOtzurbBuoZcEt26EXJlsSKPGhNdaLlcncvv1TdoKKz6DtuvaXzPbCxvBk3UlAi6Xp0xTTMmJbwxtE7QzeAMwWa8LVIIkEloQWAixhSF898+ryvsnkvlSwrkXoymZdZAsTptq20hI8hryuKiWW9MUvb5rIVT1r6RMOPBFnWam2eRNXZyd60FUiGXxDhGoimUKMqaq1YCX3DSOvv65avFKVHGQlsuLi7pup5hlAmn0LRLwLWmQK42pom+77m4uKDpe9q25fHxgcNhfxyHNYKUVl+My8tLEak5DMQ4i1GSQSD+IJV6bccZZqYxM82WOSWGvahHOivcjN16Tauxqu87VquOfdeQ46yJaVnihz1xkVs+jiD8OzfxeB/53zqgo32Wqn9tilbomw3BnuFXDSZFyjThjOgOmyi9iXgQacRnN5c03jPutuzJbLxlniecEegtUhjmSfqMVqrceZok/86S+TkjM7PeCLTmFBJ0FJkBTTJilVJiHkcVsbBLFhpTYhpHqboUInmL+WlkXC1ov3eVEt45xmEkBMnwSs6LZnrbttoYPfZLk1bfrig7VJMHgR7rqIdk/kvvMGVyqtKB0lOytr4eLzO+5m29+nmWnn4MLd44tVN0TPEgsPl6TSmiGx+ahm7V86RraNc9z549IWex2QzeYqzHFJFgtd7y9OZSe3hS/3jveXJzxQ9+9/tM48B288jd3T3b7Y5ZkzDrNDA7TzFGJSAtB1Vy67pO+t+dwL/Oew7bPfMoGzNmaJtKNpHka1Jo+3A4cHF+zocffsiTJ0+EXBMCxlgZRZkjL957b4HgT5nuwqiPpDjTNA3X19dL8nUkpMjsaLVRNMacwOh5OQhCCEcUIB+Z7cDSh5eWaF42bEV2nA+kKH3Ey+sbVqszPvz4u5xfXHB5dUnXt7x49gxrIc8jh/2G+2kvh3cSv/IcZY2XrEG9QtewsI29F6ElEzpwmWgyPrRY3xzPBu2PFhKozCtFVO8MlcGuO9/IzHkqWV0XhSNTj5jqwyAe60iljvbt6wXRPnct74s5PaBO/1x5MtoOsMfCvfYZq+LdWz9djp3ho9xuRs0HdFJDiGNo0Eomk4qOZjWBkFv68zOmeSL0HS44cuNZrVq6TvZPCAKzJ/UskB5p1cCQxH4eZ0E+RKcWk6SwoWRtUxmCzBZS5XadEYi9DYFgLa33NA6CFdjaItX8MQs65RsICcHyDuv/BCFbrq0WEov8ri0yhlb1EzjyjurPpXys3JfzTK+zc9CG5liJagBD+UhV7Ch7vR5FkkSpgMULvSKe9fz0ejaE0OBDg4sI6VLV1kouJDJpUjW/OC/7rW1b4jyxUaOqrm/FtjpFKFn7/QLZOyAEi7Ui3Vz5GcGL2h2E5VrPrahczikzFYkR4ojYLpLIVpOGcRyZVcOingl1Tdvl80mlbng7pNd7s9y//wAVekHmUQeVvTOlMA0D929es24s7c0Fdpophz3Br2isp4x70jwxbm5ZNQ2/84MfME8zL7/4kvmwJQ4Hmq4hdC1TmpmmxOYwMMXE2cUFPrSQT6F+kZUVBT0JbsnJMH62QtiKOVN28u/DNIsQRQh6eMnI005Hwna7nWTWOauhSmDddziF5Y0VudLTGxOcJ+Us8+h6c4IPeBfUUrGQVHRBKqUivaKcmeZ5uU1WWY/1deUk/amobYImtMt1D6HB+xYoYoShVc8wjIyHA71vVG5XhEeGw55xOHB9dUUVp+n6jusnN7z/8Qd87+/9Lm9ub7m9v8eQ6VtPYwO2FA47ccy7+Ph94hy5u3ugFEfwng9ePOO3P/mYVdfgrOEnP/lLPv/sCw7jSEyJpu2xznKBwHTDHJnmiYfNoxjLnJ/z4v33+PCjj7CasP3y57/g/vaOzWZDSpHzi3PappEeVYxst1v2+z0PDw/89m99l9///d/no48+WlyRUoLdbsc0TXz/+9/nRm1mNxthm1YiY4ozcZ5Yr9c8ffpUKgrNwOvhZYxZPOcrCW6eRenJn7RaKhkuKjnutB1jjBHxIc3K68P5gG9axmlgOIx857ef894HH/L7f/iH3NzccHV1QdN41l1DKYl52HF/95pxdydSp9MEeWaOk/A+0iwHupGQIr1Mj/WWtpPgbbsVLhZKSOA6sK2MlObap1PIuWRwTsVXnIrN5GNigsFbmYMuCCvdkKT3jri8CboudLucZoUAKre8Bmkd3bFGZUSOh1YNCBjpnItbGGRTHcVY5tBhyUeUSCR/mzkW5EW5ASVKJBLCWV6MRmKKWAxzkZaR61sabzlHpj/67aMy2SOXZ2vWfUtovLQJEUU/UZnJgOz7HGfmlNjHg8zih4YyTZRmxsYZ4oxpMs542iCz+haRfDVAYx1ODZ3aIAHdGyDJvTc5KuVBYOZq6ImKR1lFVH7jQ4MHlW9gFKU0CPtd1z9Fq/SUluQvZUl8SjEnsPyRtLvqe0rJpFnEcNBRuxgjZZ4pOeJBlB4bqVC7rlsI1BRIFxfHBFhfcL9a07QdKYON6sRpZA3mGIXXMs+M40DYHxj2B7qupetabm9v2W63rNei814Nq5wKwZQsvKYmOLLTBEtP3MqrqQTk1UrOom7VEXMhGmkFNKGl9UErb0Gepmlc3C8rQheaRgoz1Q5wul+tOWlrLaWevAZT2bPfLI4vj28c0DMyuxrnKLrbcSZYw8Wq56LvOe86ztuGs+DxaZYFOI24FLnoW1rvmQ9bUkx4m7EkcpqgiOmBSWIS0LUtTSsLJs4zFisjFIrzGe2ROyA4Sw5eE5rCbpyYYmZ63JAxdGsZPSOJeEUtTLq2xTtP17bKbC/LhbVObmzXrwg+EGcRFinaT/fO0bSNkm4S4zShAzEy/mSMGB5oJiv9N6v9Is3GVS3IKbGvgAjmkCQJKNC1ImyScsaqbrlx0vupWaNdr+mbwLpf04aGAOQmsD77LVKMbG5viVF6wE3XcH51QeMcm/t70jzTBKfdx0yeBuYYmQfRfTelpeRCGxwpJjabe9FJnoRs8lvf/S7jMGGN40c/+Ql39/dcXBS8D8waJMco3sQff/Qx/WrN1fWVqN1VtzIfePrkKX0rgjmSKAqS8sUXXyiRZmC9XvOHf/iH/JN/8k/4j//j/4gXL14wqKHKaSW934mgxO/+7u/y3nvvMc8zr1694s///M9pmkZgT61EvPcYZcYXrSyOlUlhnIT4NqtOOooWPD4+SpJxODBO00KEk4MuL/cdjg5OxtQ+qMUYBy5wcXXD8xfv8/T5C0lCznr5njxTsrSHvKrreZ3XLZpciNGFrAGDsrk5jsO44LEhiACHFb+qbALFBIFegVwSKEHKUMQIA+GlVB/0lArJomxdFnjTKHwtvdIj473iE5asVbhR2PDYdxcUQQ5lW4z2sWtwP8KQ9bBztorslCWA19LR5uNpVwND7Vm7Ag3ozL0gNCVlchThqCFnZjuBKXjr8OITSvYGukA4X4nITUq052d0q07ke3Na2glxjKJbMWfMXCCKdO1AwjWFYKy016YZM44k5yl+pgSLdUJ+lTZAIc47rHW0vqEJnq5pCFYCep6zjo7Ncs+tGMtINSBWtXWdlaW6q1fiJGGi9m51ysJoq8ZUoZPj91RJ6PrTxgihCyy2aKtHk6ThMMgoa1RNe1MYD3vm6UCeB0GTgkxnjHvxYN9vHvDOyhmkGVsIga5pF32GGlCbpsX7DDpdlaNwNJqmpXgv8+LGKoomvvZt1xGTTJeM08RhkAkXa7W1d+vfQn6OKpWepnK5VFDmiIpW33eLD4H1akWwnuD8QhydpontdqtKj0LKcykdZcPNcSS0ooN1UsNQA7u+sCW+/weA3IsG9HkWWc8cRZD+crXictVzueo5bxvOQ8DGQQP6gCNz0bcE55j3W4FUbCVSTEC3yFlSMl3bY71nszswpwlbLNZmXECJENWq1KqxixrK58wuzszDwN39hpQzH3TfXXohpQjCZY2laztsb1URS25WDQp1fKrvV5QmMU3iEKevELEx7ZaAPk0zzkofOCbJmafpaJCwHLBWFoFXLXOn5DmRWxTIzBRZLBToVxL45ij99pgS3h5JcYZCF6Sqbn3AW/GQN8DNe88wBh6++IppHNnt92LoctZTDDze3mEbR9uIMA/FsNtPzMPANOyE6IbAU12w7OPEw8Mtm8ctr1/f8vTZc377t77LOE5Y6/h3P/oRd7e3eB8ITcs4z6LqlzJXVy0ff/wJF5cXPHn6lMMwsDvs8T7QNi1Pnz7l6vJSxB/2e9Fa3+/5/PPPhW3uHDc3N/zRH/0R//Sf/lP+k//kn7Hfix57Ja6klEgxst0JzPXDH/5wmVX/8Y9/zF/8xV/QhMDZul8g+DobegqZ13uWcmYYJ6Z5Yj7pu43jyKjXs8L5dYYdWEiPx775cXvVdkT15r68vuH5ex/w/MV7XF1d0bWeUjL7xwcyGR+ckmqkF+mdZ06Qs0KHVYPh2I2WhNSKh7dtBBGIGtBLCeQSlChVg7pRGLcsQUoCukCmhsJsCk1uOI6fZe39Wn0NUmVZBdirwYe8aUUrlt64HKhGx8iyBvXMEe5ciIqmjo26k0Pt5HBbDrljVVO/NkXsYFtElCQWDeQximJfkQrbWEsqSe03wyJLTBsIF2tIGZMz3cUZ3apn3gkXqOjo2jzMpHmCuWCifKSUmEtIJ5cAAQAASURBVFIiFEOxXgL6HCnjJBK9zQw4jJfRJ5QEexgmuqaluehpm0Cv4kzOFIROViVgswaP2s5botLCrSlF0Eu0NWFO/t1QGel6zRBxIatWpIvwUK5BDFUyM1pYnYivIIn7sN9ru0EtUJ0RlPCwI6dRWjBBAv007CglEYwYNp2tetq24fz8TINxwLla9QaF0aVVFKPszaiJXNN2EhMwKhQlVXxoGtpO1EL3+x3zNLPf77UnLi20lOMxCHoJ4pXoHFQCtvrR18TCN614FXjxVFiv12LpW44ji9M4Cdo4z4LMJkdS6fB3A7rcliPeXhOt02ZS0TVv/rcO6Eb3p7do/2Ji1TR854P3eXp5xkXb8ORszc35isdXO6bDns5kgrNcrFY4A9N+L4Ybq14cqpzMQ4/DQeZDreWw3zGnog5Wlmn8/9P2Z02WZFeWHvidUVXvZIObjxFAAAFkJjKRWaxiV7FJlpD1yn/aDy3SfOqnbunHbmFxqMpKVuUEZCGACA+fbbj36nSmfthH1RxJshkUQVuKpcPdw83sXlU95+y91/rWCCjULP53CUsxqyq1801N8ZLIzfMwohH86sOnD1INth3WOdrtTuL9vK+wDZkZh8+IYVBnodaSkKg8ocv1a45viLJxiNJbVcW0XjeYRZQlFbkS5bAScRxFVJJ5nFgEVCknYkVE9qeBnAqCCVQcz2dCDPTDQNs1XF5f4ZyRh957OucI80QsBa8kDOT//t/+twx9z5PDgbZpuLg4oKzm2N9z93DPmw/v2F9dsL88YLUsArrCgBa0q4QgJR6OJ+7vj3z3299WIJlco3fv3qGU4vr6ml/+8pdcXT/h229fM40TP//jX3BxeclXP/0JTdex2+/Zbrdc3zxZN8xUxYZ3nz4x9ANPnz5FkukGQgj88pe/xHvP8+fPef78OX/2Z3/GyxfPmaZQ7SCsavZhkH/z9Oaa2Xv6vud8Pq8e9n/1r/4V796+4bff/Ia2bdnv9xyPUmkvVf5SmY+j8O/Pg3jcl4e7bVvO5zOn00m6JlrXzHZWKw2fVfnrwwqPB8YE+4trnm4v6HZ7EvDh0x1jCDy/uZYsamQxDeMkToWHBzpv8Bsvcz3nJGVtUYezQGNkxyyIC0ShK4uhtkiVoah6gKSgU02Xlu5tDXGpvO9cW9RFAbkecmUzlNhSsY7KTFhXsIx0zVA1Mll8V5QogUlK1T7WchhHqvtU0sqGh0fuxBIV+kiQkw4B60ZTBClbD/MUKOlxczdW0zhLpKDqnDXFQJrFjxwqhGcYHNqYquuQyniaR8YU105EBIrWhCzpkjGXRWMHRdP6hmwcSdvq8ogUbQhJfsYSE95ZfNti2pbiGs4pE3JimrJ42suyvmr5NGat0GPUJKMhaUqWjiUqo7FVGCnXQWlTO4mpjvIWCeHjxq4/n9/W90prjdNmZUgs4JnlAKWrV1FTxxlF/AZUbvyu62SWHRSLyHhR5re+wWjF0+s9jbOkKNW8RkaHKc2kEHj79p0kOU6jILeNZfF4NU1baaO+cjdanLPs9h3OmEr4TPTDiDYG5xuaGoJirWMOE9q4Km6mPrOy3k/jKGAvI/uRNlYYE/PM+Xxirkl+2mj2hwuUtowJtpsdCkPnPbtG9DitdXjvcNbg6v27CKnN4otfD9/VQ18+U7bLDb881XLVfu/Q+r//8X9gQ18M8tKSKzHSOsvT62suOs/WO/Ztw75rOeVEHid0Y3BWs209qhTGh4Cxhq7x9WIZiRsMM0XLbGUaJ4YpsNluMUat1e4i2hCLicXljLUGbw3Wy8yQomicZ55mrFa8ef+RlDLbwyWlbdlstzitKga0KjdLWTeGz4VM2mhyloPBNAqRzFm35nDHGNfZunfC814EbV3nHn2cy9yqLu4S3FADQmIQRXQlw+VcGIaJkgpGSzV1d3fHMI58urtluxMmfNt6tpsOpxTFOfE/xoh1nnkc+e//3/8f7j594s9/+WdcXV3i3VdgFKFEXr95zd/9+lc8ffGcm+dP8U7wiRtn8Eaz6RoB1ihFLpG+P3E83vHh/Tu8b9nuLpjGgWkKKAyHw4Gf/OQn7PYH3rx9zxwiX375I7748kv+z//lf442hn4Y6DYdV9fX9cG0nM9nERZay+l4Wu1pYZpk4Qb2+z0///nPubi44OXLl5Rlpp3z723Ci/e07TqMMczzvG6+XdfxF3/xF/wHrfnV3/8d2+2W3W7Hw8MDwzCsDP7l6y4Hu3Eaq6JWTuxN03A6nRhqq/9zHOwyNvm8/Q6s2N/CkkMfebLbcfP85VpBPJxOhBS5POzwdXyUS15BNefzGaM6tJZxQdGCN17nmNSZ6tJiXYBKa91cLUdK189Hu5dCVf4569fLaxWcURn5N/kRlJFzqi1XXeEnhSWadYWL6MfWeqrtVFUfhc83ls8bw8sqs7Qf9TrPfVRbL524VTlfxyUlLXAWams+Y7TFLyrrnFCVuZ5rK3SKsyB6tcw/p9SJ4JENc5yYc0RlEfslilhlS1k5/fI2SU3lrAddSMrIYS9F5pyZcxZnQs4oLSwJ5zzFOvIkASAxCBRLaQFRaa2quLV+KsSrXt+TvLZnF20RKJWk2PlsZLFOZNVSofNYpSuxSMmGQbWN2ipgqyPI31v7P7u3TCFVjkJRwtZovBfkqhJ4WEmxQsAUzlkaZ7m6vGazaShplrFFlk7v8XjHOQTuH47c3d7y7t07gSsZu0K9l6TDrt3inOfp0xt5Lr0Fr/BOEVJmGCacb2hjqjRNAUoZa8lZCgDrKvALQUfnZZSjRMy7rAXzPPPp9pbz+Vz1MIY5JJQxHPvA/nDB05vn6FLYeVHSy+zdiCbD6nVsZE39M/XYTXvcU/9Rl0lR15PHqlyO1X/gCn3uRbQ0nE4QA4eupfQP3J1PKLOj6Rxvv/mG7+eB+3dviNPAn/zsxzStJ08zxmguDnt5quuJdBG3ZW0J9XTorUUrQTqqXHDWytxkeRPUIrUBUiLNYk3TMWBUpnWap1cHDrsO7yzjNPPx/sg0nDk+3OHbjsPlFc63+LajcY7G+yr2EyLcPE8YU9GCVUwyjiOTEoX/0DRM47Ta1lJIHLWIsJqm4fnzl7StLMAoJTPwRSRSOwNzmBmnaZ2nH48nxmFiHiI5Fj58vKPve/7qP/x7AK6fXHMVAxeXh1Vtr+uM9tPHjxzvbvm7//nfc/vxI2EeOey3kCNhHLj79JFEYgiiTncaTvefGIYjbetkZmcU3hp+8uMf48ymjkQC958+8nB7zzCcuX848t3rNzTtlrbbcv3kKbv9Bb/4kz+lKMVf/Cf/DJTmx1/9hO1ux9Nnz1FaMcdYtQNLahTsdjvBsm53MtJYZttGhH1t2+K9Z7/fr5u0CBjT2v1YPp48eVI1F7Kh/tN/+k85Ho988803NI209b/55jfc3d2tFKtcsniOU2SOc1WtJ/pzj3OOr776MaVkqfRj4MPH90zThLWSfmeN4VS7AIs9saybrFR/mSzt7VLoth2b7YGnz2548vQJxtv6vQMmGuYYBUdqDUp5mqZDG8swSQiL1ZkSR0qccFYW90WMOEbZcFRrsDphUqWVFUMoiSkLOCSUWTYObQVcY6CMZ9I8cnv7HtJM5zwqK3IJtd2oyDkyDr1YOEtBJ3EXxDhTVCYHmYMb7UWVjtw7MWYyS9tcRJ+F8NiGr4vawn6X31fWf5BRkJzl62G+3jxrN62K8W0tBrSrUaslykFfK+6P93z48J6P97ec+jMYKy0Ea0ErqaK1xlWLkyIzDSPH4wNt7QCO08RDKezaln234TZGZgV0UWiXtTKfx0n4Ggqc0nRaM6KYYuHYj8ymx+sW3SSadovxMKVesmvQGCMjkBRnhj4y5iTdhTCS40yO0r42OqM1OC9zbdd4FiHh4neOpZCTaIKsNuy2G7xzVUOQGPseqiAwa1WRsHJgatuGw6GhPw+M1aECcHlxjbWO8yBdy4dxJIXMOJywVZkfgxxkjJI0Mld5HxeXFxz2W+bpLIS4eaSUwuEgz/8XX/yoop0XgFNmmgT3nXKqFkY5hIzTxPF84m//7u9ACXNdhG6FbiNQn67rqtB58YTLPZJriopU3rDZX64tdOeFJNoE0cZMOaN9yzCMAGjfYoxlZ+TrpyTj2SXRc55n5kkIlK3zaCOF4eeH03EcKVrjlJIR7TLmizWkSKnqvoLGNRitiYIT+sNu6EJUi6R5xpBpjMaCkJdSRKfMw/0957uPDHefKGlGpS+xKAkaUIjFC7FBoJb5gVpJOSUX4RMvP34pGGUqHOGxjblYBOQGTEJ0KkWwi1rRNZJTG2PC2ZGPt7eEeWYMkWaesM7S5apmdOJ/TzGStID9x2HA2KUtKG/y0o6fpK8qrfyqgI8lonhM7grhkSWslCxejxu6tCCXaM6CWPCmcaLvB+KUyTEzzoGH45Hvv3+Dc5bD5UFOk4p1riNvS+Z0OvHxwwf+9m/+hg/v3vHqxVPazQZVsbjDIG3ifh4I04hWEOaJceqJwYvS01uyd6zWmooUDfNMCDMpRcZh5O7+zGYbiKlwdS0n5YvLJ7SbDd12h/WO3f5CLF5esrRT1QnEFFdV+bIh77bb9b1TQNsIQGe3262b7xLOsmzon1fHwKpMD2Gi5Mzz58/Zbrfc39/jvefi4oK2aVaYzTiO1Wana4xqWq1oIQah2x32xKqkLSUzTo//xhgROqYkKn6H+70Dxgp3WjYtrfDeCQFut2Wz3aw42gWFG2uXSFu5xxf/fsqFOUaGaaoZCVFGVdqsmeNzlArc+iKi5ywq2YwkpsUMIUs8qFXUFCmPt5qYglhLY4RKyAOzVoSL7S7GsKrIF7xrTqne2yKFU+ax8iilpmPpqnMBQMBQS7933cQfR4rSOudxfluXgbVNvxLxZBeU+8BUsayuiv2s1oN/mCf60wMPd5+4Px6xbSsdvs0GpTWzWFKka1EyYeqYZ9FKWKXBN5JpXwqHVjYJAUdZIe+VgjVOKG5Z1ABaKQkosY4wBaYQCCnDHCjVv9xujWTVab1qCRZtTCkyDy4xQIrkOIpVMQYoiaIL2qia/67r6FJuPIWM0Jbzj1Jyr3rvxbFTCrF8FoJiDRRFLKxobWssXdOI9WqWebwCNpuOxntANuwjMgYRQqDFaCepfCVXPYJ0P5bvL0THJG4AZJ3x3q3jlJIzOSbZGOeZYZik2zb0zCEyjbWrkUW79P7DhyoafmSE+KGnafy6oW+3G7yXTAdjDELyLYzTjLWGbdUz2aaRzd87vLGYlGi6LXPMhCTdU10jlLVdxm2PFXTJmURaQ1mKXaHKj7RDqhYqRnTtCC83eE55jcbOdSTZ1DTR5b7/IR8/eENvjeAi7caRppHp7gGbAje7HWqa+PD6gfl0TxoGHCI00ClRgsytNJ7tbiPWCmPrQpUkCjVJnrCpcxzqG55LFiuU1uspfAGxuMpQ1wYKSxJb5ehWRODGGZxqeHl9wTDN3B0l1P50e8t07hnOJ9rNlqbbCDAhyfzYOVNPpQXrHEornjx9KocGlkpCYCa3ObPttrRNy+XlJfv9ns1mu3LeCzAMA9YY9td7+r7n44dPQokq0J/PhBA5n3rmOZKCPKRXl9dcXz3h5atXbHdbvv7ZT9ntOq6u94JfnCOnh3s+3N3y7/7y3/APf//33H56D0QuL/bsNxsoiTD13H0aMdZgWy+zqzSzP2zZ7LcMQ0+KgT//5V/w4tlTGuvq7N9ijOWnP/2K7fuPfPh0R8oK11ckbgi8fPmKP/vln0u+s7b4tsMYS9N1q6JfsJJ1w6BUJTWseE+1LEL69+63f+y9fMSnsv75Yi1bsKyNl1nVQpp7+vTpio199eoVX3/9Ncfjkbdv3+Aah7Gm5rGH9fDw6tUrjDG8f/+eGCPn/oytX2s5DMzzzDCKKyCltNoVF1X7spF/To66uHzC9c0zIVY5Q9eJElepQggzHz5+wDtD60T5e7nt6HZ7rp4+JU4D5+FMY8GbBmUdyhq0i2isCNtQJCylaOYIWRdUzMwJUlakItEuqYqpYgGThUle9e7yNWr3bHmfcy6i1+haYpZNSxsFSuxpuSTmIAcKUGgLTimsqiCqoit+tHy2a0NZLOpLP1ivUjoRFiolaNSS1wNXXPIWipTm1tpalUrHpT+fiPNEf75nv+m4udyRcsA4wW46o4jTQBgLMc4icPKtwD5SocyR/k7Qz6GfCEUzY0mM9ChKyDTOcTqLXcp6J63UphM6ZtgI5TEmtPfYpqHEiIkJs9uhfSv3f0wC2yqKYRyku2E9Bam81xAZa1BGkXWmJE2xqlbV4un2Xq+t3lJR3DKKKLXqX6AxaoW2pBQqx6DaX+sBcA4DXdNw2O8hJ/rTCacVVxd79vsDXdfx9OZpDScKHE9HpvMJKFxfXsjhdhyRLPVE0zhab0WZnwvD0GONpvESL+tr61tXofNCVdM8Ji9O00yMSX6tI9KlUzvHyFc/+VoyJCrpbeGpxxgkHS9Fjqd+fe2i34nr4cFay2YrG/9ms2G73bDfbyUB03uadotSFuclaGu/l6CXpmno2o6b6yc4Y+R9zZlQ8dveStDXsh4UYLfZst/tab0XX3ycRR/gvUCgkES/lAtGWzkMLVyL8v+HDd2K+BplFDOFNE+olGisIU6Jue9J80xJSdjDwDxOjNYKKCNnUpJTsTGmNiVTFeLAYu3JGhYFq+BRSxXa6HVDN8bUZDQ5+aQsraKSAjkKsakUeWPQik0r3PFpcswxMcyBUB43hjqxoBS1ClNSlq+hjUZT+b5VbViW71ekzdJ6qRCdW/yOsnAtC/2yjC2tw883J/GeL3QujWtF5bnf70Wt2TXsdlu++OIL2tax3XnGYaTPoiyd55GHh3s+3X4kxVkyqWXcBTX4IYUIWHTSgKQ4WaNxVpO9JRm4OOzFt54ksSkXSTHabDZsNr3Q8WJh3meMbTCuYX/Yc3l1VTcLhfMN2gh8Ra3qk4zK/9tEpGXu9/g+qd+7if+3bubP/2xRrnv3maq8tu2bpqFtJeXp6uqKcZQ2orbS3l4edsk81jgnsJm+H9Y0PaVYW3bLz5pzWq+jtNnLqixeWmdSNdhKFuzWamGZj+rFElYy4ziQoqFkA3iK2qCdo91smEjEeZBNTivQtpIbnfhVc0YVVTdVLRyEvMaQP4axlMdYlTXRlAXLukikPnuPF9FcfS0rSkbIHOu/WBww6rNrtVTdYierKNLPvrqqfyLq9rLO039PH1T/LVDdKDU8qf69tDOlOifLGhOSCJpaXw/lSgRy1hqsM6Qpr+uLpuAr8GfpiOgiamXZVGuQ0mLDnKUVGrMcTK2r18G7+vNYWX+IKOfR1R7rXEb5RgI/1ELAS3KYqh2CJbzpc3X66ujR1UOgpJrWWkRV4gIQUW5WedGw/eOp7OMoaP3M63+g6ggwrxVjWSvmtlLXDrsdbdfRdS3eOakcS6FrpYI87PfEMHMumZIjoQrCFAXR2Im1zWgFRQ7dtm7gJWchFBrpJizr/NJdSElAM6ky5KUpIX/um06s1ClVnPS8dlfGcRDoVrXWhSCbfYgzC+bW1MLPuZl5jus6st0muq6mveUsz02RfUZXi/OCu9ZKOoiqFpKlLGuFuFRSFW6uvnYj1yzVtUNbwwLzSTmRYkY7s2ZarOCrP/SG3qgg8zKdyWliPt6iUqRVMKTANPboENA5E8aJOc78u7/8K4xRXF1fstvv+NFPZbZ6/ewZMWemEAUPWRRtt5EFOKuqpFTVMiSq9oUg1nTNWvUsApmcZnKYiaPYjEIMlRAn0IYnhy0xd2zahnM/8u7TPdM8cjw9cLy/A2NoGlHC+7bDdS3zcar54XIBlwhWlo2nwDSOTOP0e7naOWeGfiC6yH6/Z/E8hxh48+YNCsV2u2WaJ4ZxFM+jsxwOHmscP//ZH7Hd7olJ+ma+0Wt7MpXCw0PPPA4M5xNzmGtlqCUUwTtUyXx4/47+1PLly6fVSibf//bTHa7x3NxcME4jH9898NOf/ZTnL57hvaXvT+w2W4wz9GOo80tL22159eoLfLNhf7iSOazx/PgnP2Vz2BOTbBaqhnmgHsMJxKs/rW3zRYBI3Sy8FxTq55xjeFyAHtGhjx/L3y1Yx3GUGddmu6lUKNlsJYVNVOo3Nzf82Z/9GfM88/r167VFl3OsmomWnCMfP34AZEzgnefy8sA0zXz8+IFxGhnGAVdhEsZKBZqKvKZQc7FVZUU717DZbri6vuLm5hnPXrwkF2k/pzAy5cg0h/rgXtTEOFHjbjYdRRuun75gGvZMux1hHGRjty1Yi24U2kSMEm1GUo5UDIRCUhkVCzErxLgmhy5dN/WYRTxGKaSSHzfU8plFpgi2M2VRuS8LjLUWZRxFexKaSWVigVSFbjElMplQAGURkNqyzdSlPqv18COrdN3u9WLFqqLH2saWfb+spC0UGLdkUldBasloCznP2M6RLJiNp2PHBQnXNYyDiOG6biMM/csbnGsk9Kj6nM/nnk8fb9lst+z2O7EozjNKOxIa1Yprp9lt0UYTdUXMxkwYZ4a5p7UNrtliG3kesnVkLfjqUAQUlAtkzeqMcdZJJ2sR5tZDka1tceln5yqCkwONsPqltl14FRIr+hlq1DxuGvUiimMi10ASrfFaoUrm4fYjF/sDl5eXfPHqFU+ePOH4cGKaZu7ev0MrzfX1NZ3TfPH8GW3b8vXXX5OT6Czevvme3/7uN5yOD/TnM3MYyTnw61//uuqDRcx88+RK5ut1vt00Dd452rapHnCLKgqlDM5prP2sw1PFge1298iYT0nW/jBLaErdnGVcKNVvrnY1ccb0Eqx0PtMPPe/ef1//Lqz6nc9He7IHyIHm6vKCq8sLdpstTmscWoSPSTRXbdvSVp3N0A+Ukqr1VA4yxhhiFtSyNmJ3FupnJIaENQ5lHwubVYX5Az5+OPo1BWE+F8EQ6uo3tRq8NZSmkRNzcgwxECicTjJ/tM6SC5zPA9o6Ypbgg1xPPXmxptRTaVb8nn1lgeYbKyb+Jcs4LbP1aqkpdR5IErFKVmJ/s5XT3XpHionWW1HrThDjTJil6rah+iDX09Fy/6h6g5U1TUejCFqv1Rksp2GZh8jBR6JAVW0fztNcb14R+pU6xzfW0vgN3ovFbLPdMYxSXVsv4rwpCh6V/Fg1LTNO7xxd2zDMIzkmpnnEmqqYNVINpipWWhTJ3hmUaTgcdlxeXKwtsJSXdtfIOAWOpxMhRvYXF3TdjovLJzWkQlwDUo0uyup639VNOMbHoJTHwBSZVX5+f66Ahc/m4j+kQv/8z5dT8+ItV+u9I1X1ZrPh2bNnPH36lJubG4wzdR4uJ+l/fHgoCmKqGMcQ5HRf1a9a6wogWqrHzyoepTCYtaq31spi1Xga7wgJYoJSIjkVksxYaltZMQeZuffjIAl88oVQxoEJZGXEgqYNaCeGa6Oq6MQAprbNFemz3GqKZiHKwSLgWzzorGOC5T6uk7vHa7BsrPU1aq0pRjoCWoPOsqFX/c9nM/B/fL2X2q1+rSo4WHQHpc7YH/31S7Vf5+56CWeh/uzSflc1YMcVyVqwToArpdpGjXOiG6i58eJe8LSN/Nq4Rn6uDEGHCpuxWOMxJhG1oGxzUWBlDKebFmW0VI6lQElEY0jakLWhGAdV6Vy0EaU8YlOLSbwGmdrwqLCdBU6lahdnwYyoOoZguYa1q8H/yjPy+/Kpz56nvOTRV/qeeoSZLF0L4R6oFWpEliGNVeozhoCAjbaddMDMZ1ooAcvU75kz8zQxh4kcZwS9mjFGk9O8EvGWLAVf3STLIdwZh9GPjpJVHFntbNq52uF7XDtEX2SwTnQNMbWr6Ey6wRIU1viGqQZBgWIYRuZZrLoswUJGDhTLOptzWemV3lkR1lVl/OKI+Pz5WDrIlAXS83iNFsH0KopLjwTQ3/v8oTt5/fjBG/p0/CSCCaWwJXCx9RACakpcXV/hn1xjS8bkzP3tR4b+zG9/+xv6oef+vmcMhcPdiWw816nelNqRq9LXhYQxEm1YchGyUy74RryEzYJE9H5dbHJK5GkijSNpGsnzXOMRhdc8zWeUMnirsMaydQ63aVBccB5GvDXc3R8Z+hPzuaeo6p3cdNICs4ZillasqzeotLWtc5gg83xtDcqaCjeIOCOWs/P5vCqqc87CmK/pcbHG+93c3HD95Jr94YqmkZOhArFU5ExIsqHPKWC0ovEW03oar8hxZB4tN0+vmceX/P2//8jpdI9VEWsybWNpGkcpibYx+PZASIFxeOCLH33Bqy9f8fT5cw4XB4jyvt/dPTCOEx8+3HM6nfmHb37H5dUT/sk//RcY12Cs5+L6hqubpxyPA0M/U5RAUxbe87Jxh3oqDimsbcvFF6vXBUWtN7g8lI/CkP/lhv7ZDLaIZ3wRSclzKX+/dEs+//dPnz7jP/vP/jOur6/4yU++4q//9q/57vV3EujgPaeTeE6ttWt10/c93377LV3XcXF1SUxCrlt+1oXnHqMwzJeZ+YIRllmbBPm0jcdZTSlpnV9mZCbKSuEqnIae89hzPD0Qw8R47mXuGSFmTVQepyTkJRsFKgsSNJeqHq8giyJZ3UXJ/DgkyFH+Hm2qhiNjyzK5rBtmZYYrLW17oatVIpp+XLitMRRrVnV2UUh3QP2+FiJXqMsCZX/M0F4GLHVOqOvWsmzmy0xesUa5ZiML4zyHOved0EnsW0v0Jl3LdtcR4sg0n0TtDWjrcC2Cky6KrtlWZLNHYyhyrpI2eCyI/kwDVmKZdWauU17bNmhv0YcLUIq+P8pcvBSysiTf4lxHsh3ZaIpWxCyV+YwmkJljFIuglkjYDIQUSWGWkZ8xUEN2jF7S9ZJEopYF2ysVYc51nJIrSCfWOOUMJheyFmtnSUpiW6s9TbHEskbCONI2nkOlT1oKH998z6c33/PkWrITrq+eYK3l9tMdKUaeXV2ScuLt69+J8vx4FB1DrIVVSXz6+IG7u1viLHbUpjHkkvmr208oBduuq4+t+OFtrdabpuFif0HXSuhK0zSrsM1UQNfh6qpySRb6o67hVe1jq3q5D5f1hLzaX2OM9H3PMAzcP9wT5lDXALMexkWUG6vdeGaaRl6//p3w4n/0I3Lb4TYbTKmHo1KgXpcVBa0gVnZJDAFtbNWkZM6ToM7HKaz3sRQPgjkXoMMP//jBG7pTUplaBdoqcuPEmhOEGOeVgpirOEPSa0ptmYg9zaxABpSWU3ON6lR19pCzDP7EBymVpDN2nZvrZe5SamxqDd3IUTKXJcAl15NSRhfByZYg6sisqhhCFRpr2HUt8zwzzRPjXL3h0wCqkJ2TlojWj5VfnTfp/0UrWNWbpqxqeKVU5UbnFTzSNA0p5aqcLnXxd3XW62kaD0WTKwmpFHkvc8nEHClW4/JCD6sboIbDYU94esM/WCPt0SRBJOM4oFSm8ZaMLKzeW3b7DVeXF1xeHGSOnqJsAKUwDAPnfuDT7S3TNLPZbtnu9my2OyE3acnUHqdZ5lI1ylFapDV1K+WVgJfLo6918aauFRf8o1jBx79b3tulGnuczX7WOqy/XxSn5h8J65aT78JUbpqGq6srXr16xcPxgULhH/6jMAZyWeIjRSkWa0X+CMKpmoqqul947qmKbaitaGst3aajbVt2+z37w57D4cBut6XrOrSe0TpKPGdKxDCRCpzPArkJtQNE46WLpTSpKEIupKJWYVsqmiQ8v1VgJnPpugioikpWkvOtqrNkGW6vc3+WP16q9/LZ72sLfnnflze2dpdyFhubzDflZ1XFVAynpJVTO3BrC6NIdbl+4388Pa+d1UIFb9RDtvw4yyS+rM9VKZXLXvT69RaQzzhNxDkQU2XRKS2K+KJr+JGFyriTjmEh5kxGY5sW41uMb9BVo0CpnW9j0cZRjKeoQiiaWDKx+sl1o1GuoRhL0cuGHqTVjrSLY31W5OUn5jCjUZj6fi8R0VkteFzWQJxSN/R628kVK7KxS/JkXDftnBU5QVRRfvZQ18mau14BsrTeV8uwJO1Zo+R0U2Q0o0pem0GmdkpQipgKE+CMYdt1CDI4EKaJeRrZdhtyjMyzjLcW3cjiTNFGCqGwuE0qLtpZy9RPdF0nMaVVC7OMEYy13B8fREdQnzvnfLX0umpXW6p7vd4/una8jNYka6GUlVT6ex04reo9olchZowzk/ecDxfsdts6E19YAKArI3FNr1v0HuqRGZCiCLel7Z5rJoR0L221rUqRIkWJqgf9f3xA+d/6+MEb+r6p6mGtKdqxjRtmreinCZuFPDWdB6Zh5N2b9zw83IslRDvarsW3TV2ENNq1IkJxFtUPLHGjMcZ6w8lmLlSgrlrLFpuWvNg4j4RpZB7EipXCtG7orq4bCYkoDP2JgmLKCMDGOLbestte0jhD1zjef7zl4XTmdP+JcrRsn9xg25a2Ilqd91AkYlUUuLky26kXTa1t2aUCEWW3zGONMTx58oTb2zu++/579vs9FxcXVV25FbuW00yjIKMlfCbx8HAU7rYpeGexplS627L5FX784x/x6vkN//P/9N/zLs7EYJgGePf2Nfvdli++fE4ME8eHW3701Y/45V/8kv3lgf3FnofTmfu7W9pmQyma958+cXt7z9//+je07YZ//i/+cy4ur7l+8gSUJSvDw2ng7ftv8ZXGpGuLOdbFO1Q1cspx1RyousgvLGWlP2utru3xzwE8v09bE8Xn40EHWA962+22triWjGjZsB7tL4N0l6zl5ctX0hW5ueb9h/e8e/+W714LZrZAxTUmTqcTgp2UuNq+79dDwTCOTDUDuQoN1jlo13U8ff6M7XbLs2fPOBwOq41ut9txPp3p+57j8cQQA+fjp3W0oa3FNxt802KbFowkpsWYOYeCzJiM5LJn8yjsNL5W1JUQpx3oBqWbynSw6JxQKgplUWtRN5csoRlK/LKShCWQElMMpcgsXGmJUJVtuXZPKjwlZujHLO19K04VZy3KWJx1wrsfJ1GasZCyZFNfFym1bEysHRxV0cOPuFgg1Y08i8Ap5UxRQtfTWmNixUCXxLk/cXd39zgIylJUKFU5F6YRHYDyJBRTKtX7HFHGsX/yjG67pdntCbYl1XjlXDLROYq1BC+irHM5S2hHzjTWsd90kmznPAmJmJ1CYkqJgCYCYyUl5lKwQYJ2vDFsvJdNBqHEpTrOUNVuJeOL6kteyHhVRJYSqzVT9AYVApYNOSTZbmrr25aK6FWFzntubq4gJWIIOAWds5hGNj6vFCoGShihODqjSErcC0kBbYP1ezbbDff393z69BGroKRI9+OvyDkxjGdCEPpazpEXL5+Ts3j3h6Hn7tMnjg9Hbm8/CS43Rvxmg/V+1cJ4KyjYXERSHXPCWEPTtnRtx35/YLfbsdvvOez3dF3HZrtdW/lLB80YU5MoBZ8dY+Kw3Ym4rh7il4Lr87FdzoGYIk+eXNB4x+Gwx37WaTJ1BBtCYNYGFgGdMavodhxHlLVcWMtUg8JilPhvuxFBsQRKRQzCaFkr/R/w8cPDWYKEukfklBenAVUSm9ajY0aHTNQyb8hJcox904CRGzikwnmYaMZJ1KJKiypZqbVlInNQA6rUWblZF+1lIU+1+pR4ulij86SFKdV5Xl+8kQkbqlSMZaq+9ZRRdsFWQusdXeOlBRMSscjsJ5Yip7loJd41VKCF0RTM6n1d/Mq3t3f05544R9q248WLF2ijCZNU/0JHG2m8+CR3u50Q5pKo5SVIReZ0zou/tJ0b6QrYKqqwtp6CRbEZQqiUt44f/+hHqBT58P13nM9H5umS2Dogs+ladvtXPHt6U61Tto4IAjFMnGOprTtw3vP02TOMsdw/PIC2XN3MKJ0FH5rLyiaXqlziMmOUFnQIoS68UkkYJYsyRoJnVG2vqnWmy+8lDwG/tzH/vgqe9V6YJglcWAQsC298qaY/Z6lLx0egMEptmVPAecfXX39NiIFf/epXDH2/tvtDCGvbTanl3hNhn1haWto679vt97Rty4sXL+g2HddPnlQPrNgXt9utqMRzwjuD3rZYo9iGDtd45pjANBSlScpI5aikY5JQGN+y3RvmsWeeRjKGiFAWMwUWVkOlhRVla6tOsY4plFoDLCQqFSq9U7CeC95TyTjEVFLi4j0vudRkLuoG/Nn1K9JhS0Vk9SktaWy6djWWVvvjtaglE3JDsM5zP/uPqh6lWrGUrjGeZb0nrLMopbHeyT1Tu3whzDIiyIjH2NSAJ6mBAU3TbDDG0XZbQBOiHESDGrHe03QbXNuimxZJMTagJhnzYUhZE7IiFy3XovJri3bSdkcTiiJQSAVCLoRcyFoyKKiMelUPhMs44vOJ6SoMhZq+ldd7vKwXsDY8yuO1LmX5X4/PV64HnQXvvDZrgJwi59MRby2dl9CYME1gRcU/psg0wIf3b0R0l8TydXl9TVGaKRXUNNL3Z6YaaSotcIPoBcWmiYKcn0j3LskBaeh7yS3/7HnJQfz6tnrEl824pLzyPHLJFJVJITPX7mMMM/35yP3dLZ+qD71rW6yzNL4VyI6xWGe5uLgUWmHtuplq17W60hipavVK0ZODhCGXhHGs9ticJflNmwKVz6+rSHJlbpSCNUYEu/Xnn8NjC742Qn7vvi85k2ICzVrs/JCPH7yhx/EoNrKYyHMkngY613C53ZDnRNaJOEwEbSQ9KBb213u0s3w8PQgA4+GI8g0P54EtCts28qBXL6lWSoJMULTtpgpZGtCaWMVa8yzs33kciWEihlmC5LOchXVduEsBU1W8ZEEclhpNGsqEsg6TMxbFtvHMu43YDB5O5DnSn08wGsE3GvEFUoq0hHBYW9O0nGOaJoZ+4O7TJxSK/fbAfr/n5cuXwpevbPHXr1/Tti2Xl1dcXV5yc3OD954YAvMkWenKivXrcNGAMmR9IRfKVZFKiYRpkDSwcWQcey66C3ZNx//pP/1n/Pjlc/5v/9f/C8eHO4bn13SdzNAvLi74+R99zXa/5XB1EErZPBLmgWka6IcTIRSKUmy2O37x9CXjOPH3v/6Gh37k+ukrabmbhoLB+7a2KnOlOZXfixz93L7kKoxlgYDU+/bxs1bvSj8u6p+PNB496o+t2ZwFqDNN04qNzSmiFOvsa7Ea5iwQC0VZ4S7b/Zbnz5/x7v1/wdNnT/nNb36zVuXLa1gY7stPtaS/3Tx9ysXlJS9evOBwOPDVV19xeXnJz372MzbbLfvDnpzzypMfhoFx6On7M13raHyLUpcopcnGUZRmTpqQCrfHnmmO3J9HeU+Lpuk6Lp9suP34gTl+JCkHxRAq19xU8ZWu7eNCFdEpU38vF0LX6sQYI1zwZZatVb2/DVonDBqHkZk9Im7KKVH7sVX8JHbO5cosYUVZR3SsuQDl0ZK6VuBrZb5s6LDU5uueX//bWAM3PrfaLfW71grfNpXd7cm50I8zKQvbP84BXRSNkcOzcw1GWzm0ovDtFus828MFShnmWBinQHAnmq5jf3VVWfg1Gc1OFC1x0HNKkBQ+1vY5lqw1yjmKMkRl66Yvo5JYCmOCOYm3vCgFzqKSlsOT1rLBKzlsfK5DWDZ0WfGl41jKIqerO3cR0NV6sKvv0aIrKara47LksmsKyi7Hm0KYJ97f33J9ecmzal3tT0c678FZztXq+Zf/9t/ycP/Apm3Z7w/8J//pf4rzDUlJtXnszzSNZ7PpUKrgnCVn6d49f37DZtux3+8AOJ0fmOeJU0Uw397e0p9P3N/dEWbZ6EzdExb30PFeGAHj2FNKxjjpIs3jxJAStzFWnshj92cpCL1v0PpRpPrs2bNV57Ld7ri5ecput1vJlFqb6gU3NahFk1UCXbBuXznwg2zO/YBuWzrr5NBg7WPHOefVUeOsAMzmaaI/nxkmSXQUDY2p1zTXojMSiiJrqdp/6McP3tA1UvWkOEtOcAqivqVImzIExmGgP/VSwWnDOM2omEAJ/S2mLAjKmJhjIsQl7CBjS1UyIgp2Y8SSstzUKzQgSMJRDAsgQW7sR91sWQUfS0upPhI4yTQQhWkMhJhX1bBVooLfdh3GRVKQUIZ5nikqUJLQj5yxtWL0a6UQwsw0zhKMUEpVLyc+fvyI954PHz9wPJ54/fo1z54950c/+vGKhl0ACrmesI1opMkLZWutDqNc8PzIkbfWsN1u1hn8s2c3NFbxR3/0c24/vieEiRhnbp5c8+TJNfv9DmUU5/OJmCOxiH1Dwk00pRiePXuOUobvvn/L+/cf+Td/+Zd03Y4PH49cXj3h6Ysv2O0u2R0uiTKmox/mGnCT1gqZulAZo6HxgKjJlw5oXXMePz6br/+vqdulS1Me579FHAJLS0vaYmad9y5//nsn+pzQg5C5pkmsdC9evEBpxV/8xV9wdXXFmzdvGMdRWuDGgBKxUpziekj7+mc/48XLlzx58oTNZsPhQkQ72hhCmHn//j0hBI7H43pKj2EmhIlpOEKOzLNw/LWX9mx3uMb6lufPn5NQXI6Rh4cjr79/y5wy4XRiToKilMVf1QNqrilYGqVkJqyq0C1lSEU2FFBVXCbXZBWnaYUqtaqo1bsCjNLkpNeFsdRNQy0HA2swSLdmmb3HlFBEyjQJLGMONT74sfJ8dDSI6E3uAcUiglP1SS5KbKtz7eYtzXg5nJgVWqTWOfQjQ14rjTMO56FxLa1pMErgR4FCKYqEdKOGJFXulGEshV7BlCLj+Uys0JUpRkJKTCmTimaMYrtswnI/WhY6WgHmCNoUTCkkBVlrEvI9tTYoI9036UTKc9FaW8NPqv6kyAhLkyiijKCUIGOQLJAm0a6wxo0qJdCaUDfDosTfrlGkKlSzOaIpOCX3ti6psieE+BbCzHIMHIcz/Snx8cN7zqcT8zhgNVzsd7Rtw5vXr9HWoVwr7XekstRKcXd7y4ePH1YL2OIVv729lZHW+UE2wxrGpJSiaVuur69Z+nfeifVreYbOx1ONJz1Wi9kkQJtZbIXjODLNgXkKj8LYJG1ykoySojGkeeK+dncEddtx++Ej2+2W7Xa7rh+2pr5ttzucs2hv0FbhO1sBZFb0W59lHSgkYlvVkWHKMiKSGb/sHTElPn36RKjvlar2tVIKcQ6rkyon8fWXnOsz8L//8YM3dIPM01KcIUZIAbJD5UKJiTBN9Oee44NU8sZYCRrRGtW1oGBOgTkm5pCwITGFWNu0iUJVF6OxSq8t9/RZuzPFSJinmpw0VyVlqbnMyE1eFnDCogyVlrBsxtLO10noXGNISP/EY7XGeEdWGh8z56PMNqYKJxj7AWct++1OYAI+rUStJQwkV2X+NM5M4yRBA9by5s0bjscj377+ThTTFxc0dUNP9UZfoB9eOwqKKIfBWpMuqMYERXCjIQSctbj9js1GfI8vXz7n+mLLn//5n/H2+9f83V//O2KQWe71kysOFwfOw5n70514p0vm3J/p+5FCg7WaV6++QGnLv//rv+eb3/2O/+5f/2uUsvz13/4DP/7qa/7JP/vnvPriR9imYw6ZEDMPD2fGaV5b3cvC3TgrxCQFCkkhQi+svd//UMtcHdZ2FXUjWnjowGNqc2FVky9/oLDrfbBAiFZC1JK2VTJTmFmCRr744guun1zzL/7Fv+D58+f863/9r7m/v68n51op1lnXF69e8ad/+qf803/2z/j5H/0R2+0W5xxzFH/9OI6M08SHDx8YhoG7u7tV9S654Znzwy3D+UG+xzThNgdc0/HqJ3/E5fUNX3zxCuMahgjfv3nHmw+3DIMI94zSGL9Z74msEgkwysphxkr6m0pUtTsivMmFYsQeuVQfuVZui7JWrHtmrb6NtqTPRmHLNfqcfpeLISvZREsleZUMQU1UlzvWCwfhH19reDwsoB439PVT6XUeXNRnVasSNoKqC73WmpU6WDUaEo7hcdrjrcebBoytI41CVhCQw2WKiawKQ4a5ZM4KUfU/HJmirFHCV6iHiqIYgqwrXagThyziKq2rPTUmdMkYq8hGDidJyYbuTN3QrcBZfONxWtN5T4mRNPa12yEoa51lrCKz8GWUJYd7ERsvI0u5diFEQozkKv5KqqCKIs7SycxFMNxJAaqgEJuv5JlH5mmksQZnDMfzifPpxDf/8Gvu7m5pvajPn1xeoLSWBEalcdsKwdpsKTXF7+PHj7z+7juePHnCbr+vrI7A7e0t8zxx7uWwS35MuOzaDr/f07UtbdNKqlodm5WcZZwZQ+18jZxOt4KwHiTo6XQ6cT73nM8SwTzV4ienwszMUkFYa1FVwHw6nWp8qkSnbjabtTvorMdax/X1tXjLdx3WG9pDS9c2PHlyLQLsupYsdllrzKrHKTlRkpa12jmK1swxcHf7Ce0cTR3HaWNEfT/Pj4ezCp2SDuMfmOVulATT+41HJY/tNpgiYfeqajfJkVISX331Y3zbcjf0jDHw8XxiThFTZ6+qSiVLnd8tqM62bWm0gA66tkFry7ni9HKoC3JVtK+n1LqgKGTGUtBVrKRo3IZc4DQMpFxTk1A4LZafkORhyTlW8pbGlCLIw8sDc4bTFJjmmTCcZRafZ8KcOOd59cpTIq03bK8u8M7jbQNK8Xd/97dM88Tbt2/x3vPs+XO22w3H41HYxHOsClUlMxxjCDGQKPTjgDbV310Wmlx159YDjlEKoy3H05ljikzHO+ZxoN1suX76lB8PP8NZw1//zd+y3+94+u6mzkwz4zwxhYk37z5ydzxi7QHfbNjunxFj4f/5//h/8ebtO5z2WNegiuLjh4/8m//hf+T1t9/z3e9eryyBtttirV/V/IszQHUtCg/Fo7DYSuxy3q66CVHCP6Z1LZv4YzkmXHJTlk0FAU6UanXTihAFE9w0Ig4LIUispIkUIsVFlCkYr0Anks41OCWL4NDCs5dPURbGMHB/f89vf/c7zqcT7z98oOkaLi72fP2zn/LLX/4pX375kssLEQEZa3k4HtdkunN/5u377+mHgYf7exmxXF3ReIv3FtdoYtRsdg2u0cxk5jTyH7/5Ne37d2Tb0m73bA5PahJbFvW4a1iig5cDTzQSP6q1qwAmV1vVklNeqlBriglTA490pXHJqEs9xm5qsUkVZSmqCEfBOJKyKN9gN1t5RrQhG0/EMCWYYqafIuOcGaM8z7Y+1xIhCnH+Xy5GWj0e/ORXvfbYlg1eunfL862kAiyCbc0FTrOkX/kqXMwo0boUyaguWRGmxHkcRHGuNMVJLGdRlfhYZrJSzMrI4ch3xBAZppkpRqYQaJqqoK5z1lRkjVHa1PdZbtuYRQtinEFbAb0YK8r6McYaIyv/JicRuJGXTpyu1rVMVghzPENURdbYkuVQXzd2ObRShabSei4pSDu3H2oEq66bs2Lue3IM2Lqh51YO2rZEDNAA/TDw5u33bJuGXdvw5vvXfPrwgW9/9w2n45Ef/+jHWNMRU4AE8zxKsE1sSCUzpkSeRuLoefvb3/Kbv/87PlxesNntOOxa1M0TrFEUVwE4WTzpnxNAjbVVL5EZKwOiVCFHiJmcwTqHRB8ptHV0uz3tdsfF9RNhgFTbc6rAliVZc3EhpZQYeiHKJZBkPt/Qdi1tt5HZdkqElAnzxN3DEdsPmP6INgp3Z7i6uuT5i+c4o3FSShBSIMSJkOaagCgdYqWhaTxt2xCKYpxnPnz8SLfdsr24xBjJBRC4zLQmPMaaTZFzpug/9IZORmmFMw6rNJ3ypDkS+0k28woMgcTLl8+5vH7Cm7tPHIeB0+uZNBdMzGhrqiikCmy0nDCtc/imwRvJkm0aj1JaqseUKJ/Z03KK9XsV0KXmKSuZj1XcJUXR+E5gAlGU9KkUMDKnNwq0knZWyRFlZb6njQS87LsNsWiyHtb2vSoJciDlwBhGmbNoXdtDmquLPZvNDms98xz4y3/7b7l/eOD9+3fc3DzlT37xJ7RtKzO+VJiDzOeVsrTKySKY5HA0zmadvSzKXiXnIPhMGKS14XQcmYYz59tPxGnENR2HSzmVz9PIN9/8lrZruTve021atvtOKvOh57evv+fj7T3d5gltt+fm2VumKfA//g//E/f3R569+AJvxRv/cHfHu7cfuf10x+3HW/Hta83LV1+y2+3Xmay1TlpMttpfeAyVMRW5ugbXhFDbdJ8JedZOS23CFoXKi4hHNnOFwtTZ+1xtJcaKnzukLAuiSRQSxYrbQAO5JPlUMvdNWhwEVzeXGKeJOXB/fw+68P79e95/fEfbdTx98oQvvnjJT3/6FU9vnrDbdrQb4YCf+yOliJL3dD7y6fYj/TBwPD6wy3u2Fxu8UlgnTgbrFG3nME4RxkgIE+/e32Jci9tesru44sWXhvPQVxuVQhlXPyXzuqhM0omkNUm7Gj8swKKk4uOGngox5QXYtlbcyxxbaY3KMsMtZZnDingrLxu9bTDdBmrGetaWosRiFxJMc2YKiTkoCWjxcsBWSvQ0q/XwM+GbiOYexyxysT9vwdfgGpb8br3a5IYQBE5VvbtuXtL8BMFK0RJckiEFERcVLRnutlNC4ar0upACWWmiLuIqaDwllVqdy6drNNo4XM3ldtNSjYnIs1QQSQaUUShr0c6uG7oAjCza1FdT1CMgavm/eqCJOUvnBOnCGIBSK7UolWApNWfCKHQWeFROmTgniZ/uR0E7G0NyQmObhokUZlwNVtElYeuG7o3Geyf23eFI6DpK3PDhwzvefP+ad+/eMpx7fvTqlUCqFl92nFDKomKs33+WeNrJ8entW97+9rfc3u5othv+9Bd/xH63xXorwrP6zGrtVl3HUqmiVE2kjKJ9quKJpUtnrK1YX4UyFu8kH903zWpzVvVgGOaaez5JF01m8BOvX7/B9D1TiJUz4mnajqbr6rhoJsRRDgJ9L6LRQRYRbcVnro0EdHXGkkMgTpOM51LA1HVq2eOckwpdLL2Fh/uH6o4RF5W1jnmWEVPTtKurJxe53vlRHPGH2dDffv9bjDZsmw2N9eh2K5J3MlpFrE08f3nFzbNLDpcbbKM4XG4wnaa5sxRf2HYHtvs9WEhk5jjjrGbTbLGNJStJGZszeCuUIEKgzDNzf5JZSJzRKqPtMkvN4kXUGqUc2sA4Dmv8IhjIB2lZJfFulgwhJ3JSzDkwZ7EgFV3IxlO0JU6aVAy+SIuu1YkQZx5uP9F4x27ToYtFF0PX7WhcxzydGfsT3/7uNedzz939PaB48fIpT58+Zb/fsD/sOFxdMk2Zcx/qgy5YThMhlhPozIWW7N5ShA3vrJGIxmlCodhudszDQD+MjGMizIUnz77AGcXp7pZp6AkzjEPPFApDmPn1P7xmDiKk64czw9BzPA9MMfFf/Muf8fz5l/z673/Lp093xDFDVJzvTgQ3kyYZDYxTwKRIGYaqeFa8//a3WOu4efaMrttw/eRJJUjNNPaSq8sd1lms05R63b1y9RBX070qpzsFOUmrArpUTUFR6PjYkLVZYwrkkEmIX6eUyDgcUVZhOgWmMJkTQ+z5MHxgnAZO/XHNop/OM3FOfPHyC7abLd2Vh3bLfuwwXcG0X/Py+Iwnzy7YdhueXF7z7OkzQuh58+Z3vH37rYi2UuTb19/RD32tKBNjPLPZt3z9iz+vqXOeMA/cj584T7eM0wPjILPD4xCZQ2EMkTQP/Lu/+jds9pd8dR5JRTPFwjAFTv1M223wzYaUICdF1h14SG1L0Vo24ZyZ8lSVsjUt0HuKhpQiKltRaVhDUY6QRsiJYh1FFYYQMRqKViTXkTcwNxt63aKNEwW+FsFdcpqiC+3eU6bA8bbH6Zb9/hkhZc7jhGk8rmtkcy7SIldAqLY/XznoIQg211knfukiNVjMaUWBxpgIJaNth1O6Lv4aZSV9TnlfN5bIMAbCPGKwaCuuBGsdcxGCfOs2mAp5KlrRWEfKhWGM6KjY2padl+5Fu9nS+Ibj+cwwj5gMGsM4TFV0Kd0i5x1oyFpVb3ViPk2CI41SXTfaYJ3l6eEKYw273VZGFiUzW0vMEr6y8v7VoiqowsSykvlxVTTmjRGv9zBg7EBOSlrETVutrprt/gpyxhtx3ps4SWqmEi6HQ2Ja0zDz8faWd9+/5rvffcOHd28hF5quJStFSInb+3sKyLqLIg8j1hpa55j7E6dposwjXWMpaSYNmfsP72idotl0cn1TQBtN2zbiuqhdmVzA+ZZNtxGdyRx5//4tfT9Iwh5I0pw3bK+fy3oSZoq1lKahWAvWrYdD4wsqFaIZICWatqCamd2Q2V/Dj3/eEarY9XAQ5G0/jEzzxMePHxn6QbrKSqGtXItcZpRt+O23r2mtpXOGxhpaa6Vj5q1oI5RCB4O1jk/3d8ylEJFO0s/+5Bd0my37/eUKU+owWNfgvXSCNptORspaCHd/0A29Px9F8l9AuUS0Dp0lFUjpjDGIMt16XOdRVtEoR1IZ54Xy1O63dNtOZqVa2oXeWHzjpb2sqKB7iZTUSkt1niIxTNWeFsWbahV5qcZrlU9VUKc8EVLBBqkSjN5AbdJAJpZYrTayAMYUyQSyTiglR/ucRKltlMFphTOKHBPn8YRVLVrZ1eNpVMFZxfk0MAwTr7/7HcfjCaUtbduw32/Z7Tb4xgkCtG0JcZLvW4q8j0YWsSnNoCNddKAyRoPB4Iy0tGOIEuJiLGMuNVQgEWOh63a0rXROFIa225OLxvozU0jcPZw5Ptzz8dN7hlqhh5QBgzMtu+0l//E3f8O7t+9JIVMSzMNEiRlTW6DzPDMYIzdO7YxPcxDqVY4CUekk1S3HBkWi65o6PqB2G0plmgvXWSkky5zaXspl1Q+YWqGLxFlOqbrILDNTAzuSpI+HGAVG5BqKLiRm5jJwCvcchwc+HT8Sg7D++/uRMEZ2FxvEtq1wWFxn6HSD89dsdy1GF7bdhuuLa7zzxCitunmeOfdnxnnit9/+jnEccZ1YY7SzNBvPyy+eg4IYEw/HibmfiGUmqUgsgZBnQgzMNWd8DoEP99/Tnc80+2us77B+zxwS4xzAZrClihGVzJK1ptiGXAWHmURUQd6b2tJ0Zpn/plVzIrNnTQ4V/GIMpdjqE4GotYBTPGTbELTDGI82ri4bmmKtdO1aQyCAjijT0DQ7SgUiGdWg3VaEklla5FpBCVTVsEQq1wYqyogOgCpiLAqKthTjJDUuZ4zzdUQm4JaFqIb3lJRJZWaeYcgTzhhc5erTNMQ5kHOh1V7CVJBRj7UNIUZKnNEZnDLSZvcNTdNined4fySOM9bKITvU5xfkYCsK9iWsRkiWwzgyDtICN1rWS4tmW9uq2+0OKIzzSC4Z631tpVexm9arQ0PV67cYEq0W263XRmh8GWLIWOdxvsV3WxpnhQWfxarWGIWmkIcjuiS8LhgSOk2kJBCevu853X7i9vaW+/t7DrudvH9KrInDND52egrkeYYiB4dpmhhPD5QYsEYTc4YQGE5HTg8tMUeU0WL1Uo7F8AB1lFhklOF8Q0yFojL9MPFwPJGiIJa11bTblssXT8lk5iKwn6ytuEasq1odJSpoVSgmAtIdtMrSbHZ477mpKYr3Dw9cXl5wdX1NN46SxY7GNKfVh66N3Jcx9GhrOB5PTEYTnGHbNtjtRgSMRkn4UxVuamPkPevlZ7RNw/WTZ/imxTetdApzobgqOFUVYVurdBF+/4Fb7i+fv5JWbyrSdjdih4o50rQt++0BwThqdNtStOHhXqqQ7XZHp2F/c0Oz6bi8uqxtBkvjHJ3zGORmR4vIYJ4TSRXJ455mwjiRSqJo2Vy0cWRViCTmShgiW8ia2TQkD9F0NL7jx8+/wDcd7W7HPI/cPXzi9uEDbz99RxkLYQxkZlF5xp5cDNru0cZzubumdIlWO07nB4hINKDdcjqfOJ/uef/9R3KCcz8Q5sAwTDirefnFC5z3pDgzzeMKOpmmSXyclw3nc2QYzyhTcMrKKdBowScWUZ5qpZnUIK2nlOjHSTbkU8/Y92IRyoV372+x1pDDTEmwPVzTbHY0Xcc49BwuLrm7u6Xb7rn99IHbT594OPVMIZGzISfF+TRxf9/zcBSrSttk+fQN5IwBUY7Owzr/vH3/nmEYGc4P7A8HDoctXef56ssvuLy6YrPppHIdJxF8aM04jZzHM1cXF7St8KBLLliVKKkQJ/k1zBK/mFOldVHbtqqgnVTi8zwR8oyiYJTCJeGWRjUxpZ7TcMvDcMfd+b3Q3LzFtiKl+uu//ytKgovdBUYb5nGo81FNKTPjeMQbAAlpGQYR54zjyHffv+Z0OmG8dFm0Tmw2LT/7xR+z2++4uN7XrG5N82BxG81h8yW71vNw98AwjHzzuzc8HHu+e3vHuZ85Dmf6/sTf/s1/YHe45sUXX6OMEO5SMYRYxJlhjCiMjSHqhQkgPPiorBx6vcxRvbPkmsXNqsOgahQEtqKMcLE1G4xVuM5TcsKkCNowY7DKY40HXF0cOzSGrQHXJaLaY6yn6S7ARjY04JwIT7W0DqvaBnxB5UyS/GMq4YZYUZdFg9aFxhWUeESJYWCKma5rMM4yxoS46cTupWJ9Pe2Oxm7w3YW80FLI2jIrTXTSwg1KiZ1sHFFK0yGLr+TUp0f7JYU5Sms/xoDSYL3BGMum3ZFyrhqKzJTmas1UqyMn167Efr+ja1sOmy2upjCSYToP5JIZwkwmY4xF8tpyTXVMWCuHAe9a0TzUkVQIkZAyQz+icsZk0UCI0Fc+s7YkJfGclJoWBqDEcijwLVA5c39/5Lv/+BvKPFLmkXkOaKUFirTdsaRLbvc7FIowj4Q5cj4NOGMYvef+eOTT7S3n+1tUmNltN9jG8/Ht95yPt3SHA9pasa8qhfpO2t2brYwqnW+Ic2Qap+oWKljr2Gx2YsMvhTkHCor7hzPaKjCO8zjx/tM9+51AZdpWkOFv3r3mfDyJo0RpDocDRhuubm7wTcP+6ppNjHT7g6QvojlcSYfx8slTQgh0mw3aaOZ5YJ4GPrz9DkVm13kZW5AkGMvUIK2qeUoKUpSjalrsh9rIqKZ+PPqzCkrnGkizaEnqardIi/6QG/pmsxUf+DhjqggnK4CEMSIqWGZJSmtBF6Ykb6QWYUjjm5qa5tYN3VYE41KRqeqlTLFQkDg5ETXEdUMv2mJQ9fQuLYyEQisL2mC7BpM1zmxxfsPu8ppus2V3ccU4DWA1kcj9cMeYR0wwlZleg1WKEKqKUoJqKgqjGoxqUMVhaLC6gTwQpsQwjEzjTD+MwnJ3khy03XYYazmP49r+LKWIx9IK9nWaEloXCjULV8l8Rlj2uZ6sZY6oURilCCFwPveMw8A0jjhtMEozjrOIZMSUI8EBQNNuAMVmnphDZLs9MQ4jQzcyzoVCEFGV0ljr8L6h20jwiqn+8FyVPyKOlYVmMQ6HeWIah9rFkQXHOcvFYc+uJlJRoSzGWIySeNrFX/qYAsUazrOI/3ISEFCK9WavM1dV28LwiFqUg01Vh+ZMVFGQm3EmxJmY5jrD1iSnyTFzez4yDROqZNEK1AVPZS1trmWGleL6fUKcmcPIMJw59ycu2yt86/Gtp9s0XF4e6LYbXONWIl7TerrQcXl14Gq3pWla+n7g9mEgFYX7dJYsA8SBcepvQVnCPOM7j3NequmUKUaATGhxDYhwkoomZhW8qcXfvIBLPrMDPoY/1C2+HrTUEn7kvIyzkhwWCgp05ZoXDRhZB5TEkhaVaTdKrHN1Do+W5zGrqvqtjRbZsOusFMFyYmxdAOpCr+Q+U0UClqQ8kteqK+2xxOU1yEEv50clvrYGa2r0aZIZZAaKMTJa0/KqYk4oVTGyVKGlSvV+l3spJwmXyUVQnDIn17jWY3KGM1WAGGWuquv1WVwBWuOso3EO7/xjIiBywfICQ+LRAphh/ZmWebBw+Cu0BNEXSO5FwhTpapXFx77cG6p+1m5WKtQejKwqmRq9myU/4vhwQueAqYp6pR9JZ+LICeuzmitZbTificagqt3vfDoSZ6HVWa3x1lbP9kwsZQ3KQUEsGe8bFArrpENgqtiQWiAqpSQuW9ftKmg5NOUM2cgor8A0zXRtqh1AeSbGYeJ07ilFrK/bLG4E793qL8c5WrVAlArWSXZIygUXE9v9DmsM8+yYJkd/ukOVROMtumR5v2oVv3QbljjhXBAlvKoC0OWzvonrPr3qSdT638p/tYhHf9g+/cM39O4JOWesHrHK4GxL0QWrIkZZCsKmzbkQh5lUCufzxHkYub87opzl8CSTQiGMiWI1uqkBEhhyUegMOisomXkSb+Q4R8Y5cHc+E1MglIDvGrZWCFF20+F8g3GezeYS32xomwusbrBIa9y7Dq0dNB3NruPpRYe73KC3DvumIeRE7GVG3PktSnmOvWWeA7/51W+Y58gwnJnnib5PPHvW8uL6S4LbEBpPmj8S1QNtm1HK8aMffUnbdeS6uRilaJuGZzdP0dbz8eMH9ocLLi8tN08bntsN7z584NyfaZS0bR/O8uA4J4ums47GN+w3W0o+MfQjcY7kJNYgb61QxFJClSghDtWrP01nwjzRjxO5QNdtuXmm2R0OvAjykF/dPGWzO/Cf/8t/yTTN/OLP/pS721v++m/+A6fjkQ/v30lr0rlqRfKrYrRpOzDiYb9+csMf/fEf8+rLL/nyqx8Lj+Dcczyfef/xI5uNsOHbVuZk0zgxDkOtPBS6CJY0jJEcM/MkDICUSiX7iW9Xo+mHMyEFxJVkQUsVMgwjWUWG9MD5fGI+j6hU2DYdl4dLLg4H7rjnXHryxY7ZO0qYmOdJZrgpM5wkue76sEcpzfF4x3635/LqgCSlBZ5cX7Lbb/jyxz9mu9+xv9zLe9Pauv8khmni4fgglsf9FqMNISS6bof3G7bbW/ohSv7BODJPM/Mwc74940theinvYeM70pyY54xpCsZ6KLYKpSs6ecHXatlAQy7ELC4NnSI6JqZYedo1xEhIbFLZUzRGe6w1eL/EBee6uCrxTmvLMIoFKRHFY64d2hnanWWaI+9uPzGEwMMw4ncbGrsnq+ooqapVa4XClZNsx65tqwq/fhrNMI4M5zPtxtI2ntYLfW7bCRQmRPGJO9dSgDGILXEmiDCqEeBM0qwHMt/JhmoqXS6FanntFFoZvHLEvhDmM1pLDG1ImZgzegnr8AXlCnZrRUl9KwfHFBOtadm1DZtOyyG775mHEY3YW4MLaAWbTSewJWuYQ2C6C8wpMs4jGC1akPr9xGpYqWQpMcdQ9SYLl13a/KoUYb87L2ChGh+N0sRSLaUpocm4/OjrXyJI5zlyPvc4lfFKvNObzYacEuMwkFOqCXWd+MNjou/P/Pa337DtWp7dPOH+eMf9/S3KKNrWi3CvZHKYyUmKEW0t+8sLaX/Xg0AYBsI40h+PnO/vKpdddA9t09E0nuvra5zzVXOUGeJU7ZsZUy1+u03H1vsVY5vnGULAGodTmq5GH8/zRJgnhnNfbWvydbUxjOcTcRr5/s1bTqezWAut5erqAmc115eXQiUlibMr1HQ6pVfiZakgNKUsphazvmkqCVIOKoVF6KfWg6haxiusZwMBOv2hK/ScJbe8IGrYlEEVoShREAtTbafFCmJYYCM5FxE4aYHFaATFKIu4flR+roWaqv9OPLQpCz4xFfkeRRmUtRjf4DedBCk0Dc12j/cb2vaANQ26NCgMqkilUKxUG9a0NJstu/0Fu/MFu/ORmCexMokOlJI0McD5JCEkigajDY3XOLtH02F0h7MbtpsZazWpjKAL+8OOpmk4n8ca7CE+zyXyNFOgJHIOGKPx3mJMQmvJzdUgApACWWXQkIomEBjVSH8eOJ/6RyCE9xQrs9oUA2RxAciGHphD/ZwrACYL89P5BuOrzsBa0EoEYlv4MgR2+z13D3dCb4qztOzqIcM5B0oOHbv9nk0pPH32jOsnT7i4vKhYW6FirVXS5zGqtfMQ5kCMYZ1TmWIhK2KQyiimVO1FsNoUkf8t91jAtg3GahLCxi4hkYiiUQiptvINrWtpXUPrGjZNC10hj4FZafpjLxXILKrooT+hi8Ibj8QpJpwTbvz9/f0asNAoz/X1FYeLC7qDtOaSlhlaqSrVEIO0Ta1d1cymtt4ekaTUe1MTtKq6kcA8DRjb4JtJulZZRlJLahtQ+zGyMEux/VlQSVUTl0qVS1Upnmv3J+caq7kIEZWotpXSLAOOUpGri31skSeW2hHIpdRnU0A24yw0NfF8K6kqtWwfpeS1s1aUvM61AuXxcCJriuBYmyJtdWMMrpT18KeKDPmslsXRKMH/hpRIKqFSlMpUQVaFograVYuUN5BlHouSinsl2FVLbdHl8dci/75o+VXgq/WQorLEoiI2yJQixjrMGs9b1fC55rvnsv7dYt+MaelYLcAYocgtgrHCUpHKsyQgmFxn6mq9DtJJWarzRU5HPUxJg7eUgoV6/YocmOe5xgQnNPL+adTqA1+e36wjcZ4pxqxhJuM0CtJYS+Ld1dXVZ9A7QQrnqi2Yghwu49RSkrgBSs6M9WCacpGDjLF432GtI24DjW/puo6c5VCRlWCBUxWmllJovaexDld/thwjzhha76vzxlX6m8DLxN4WpBtoDariWRc/+DgM9P2ZcawMkt0Gqx3OyTMr7bBHC6jcxrI5LxZMXaEx0pGWvfPx+fxHrXWtK833MYxaHmP12e7+//vjB2/o7z8dHx/lAmdmNk3LxXbPPEzM4yjZ3sZyPp8YxpHz2DPFIHnQm47Ly0t829F0W4yxIt7QDl/n8YUst7EqTLPM36coEaLatzjV4BtLt99w9eIp3X7H5vKA9h7tPEU3oB1Rt0QMJRlUMXjl0UqiJFURelKzu+SZ87S7HU+fv+D1699w++kd337/ieE8k6OlJM00arzf8ss//XOMNqQcyDlQ0ogzif1W8dOffsX+oiGmkwjywlg9hYF5Djzc3dP4Dce7I4fLS26e3YiieLhH6YaiHJuNkqpIN3JginJqtsZBgXmaOd4f+c3dPbe3n3j39i1t09L6hpIym82G/niqsayhioqEcx8r3vXh/p5x7DmfpDVutGGzO9B2G1JRDHNAN+Cs48c//ZpXIfD85QtOpyPff/+a/nzi4faWvu/pz2emWUYMf/TqCy4uLvn65z/n8uqSr37yE9qN+O0X5aoEIuxQWjONIyAVpfxMNZIUhcbWX6uoBaErGa3IesFZSktySoE5zBzaA03nuesnYfxPA5lAKjNpTjhl2fiGtnO0nWzo+5sWruFhJ6/nd998y+l44uP7j4zDyO37Wzbthi9efoE2FqMNT59c8fVPv+LDu7fc33+iKOHe/+JP/5hnL17QT70s7Eoxx5n78wM5pyqSEXWzMR5jPKp6mVNSpAzet2w3cHPlOfqRh+PElBLvX79ms+sZhxnrNxjXQpwA8ZiXygwvtTIz1uBa8WWjtfhxq82rhBmfEjpqgYzkBEEOmyXKdLvoIpVp1JXrXjifB87nnt3hQLeVpDGrxb6Ws+I49JK6lRBs7dBjvGd3dYHdbHD7DVnLiGwaelIIVYRXGKZRNilVbWST8B2MNoJUHme6LWjraVuNreMXydgWK5ozriI6FeM8MTzcM6XAeeqxjce1TipeLO2uk8xtLRHHbepkIWzl93OMFJNRVaCkjVRYZBFsRQTulDOc54GYIlOaSTUjfJgG5nFgt9lysd0JnVBrgcbkLFG4uR6W6kY+TRN3d3cUBaZx6/hx+f9poY5NQQ7FQcZxusjhX2ayuca3arCWrE0dRcrGHVKpBwGp0E2FNekUmM9nHt58x/3HTzVWdGKKI1f7HbvNZk3A9EZsuvd3twLQGUeGvifEGesvuHl+w7Nnz3j16hX3D3ccT0c+fvwowJfhxDhNvHn3jilFSpgrk8QKzbAWgXPIiyIQ46Sa9o1U6oeLK5yXbATvHdv9lhADp9ORp0+f8fXXP8U5j/eeu/OZ8Xzm2fUTzNNnjz3rmiPRtS0xJs59v6atdW3L4XDg4eFB4DXDwFyx3cZovnjxDKNES1TIkoZTrw01zVAridpOqpCTovENbdex2W3oNhvKJMLQlcCYswhFa9Uuc5P0aAMvyNjuD12hh1oxUjKqQCxgjavD/sfghqJkLhVSYI4Tc4pY72gaj2883rsaOydzX728sOo3FEyxnNRircyzUviuA6Owm4Z2t6HZbnGbDbbtwEr60Ron+aj4kYpDITcwFaFYT7HaNTTtlpwTu+0FYZ7ZbSIpjhzPhRQLT5++YLvZ8/LFl4QQeP/hneRUDyNzHJnDyDR6uo2t4omW9+8HWYyGkXEYGWsrNdeq1FpLykEqiST2OYVYVcSDKZutVkh4SxbL3dAPvHv3jvu7e25v7znsEmoLc4j4GkFblvey+rhL7WpIfnRkGCeO57O0HbVBuQZdbR5KmzVC0pYCWtN0G4qCJ+GG7WZD17YMvXDJ53kmpciTm6fsdgdubm64uLyk7TqcdcS0ZE2JAlted1n9oCkl5loVpJSgKEQRobB6aTfaKjSSGb+k6BW52bUoyrWRoByhUUWKfrz7SyqkSeAZxRniGJhSwWuDQTMNA+P5LLSuxtN6J3Suw4FNK+xp7zxN03J9eclhv1s/Y8kY6yqxzmKSkWdQI8lnywl44dQreT3WOsZ+ZhoD4zAxjzONbwFJ03Nu5P5hAOVINatAl4RBoEdL+lhSSJ2Ys6j+c4IsHt4lWx5tUCavupal2ltrgPL4qVgqbtbqWyrxpeJYWoWPX6PSIMRjbjTKFLS1GO/kYOGs/Jz1U0gVy0aEYGmLOGBLEUytriV6RqFqUM0651es2NwYa/cqZpQ1uMaTC3jnmVKQShnpLJjaDtUVZLLQB7V5RNCWpYpGPMbyXtU3RkMOQlc0RSx+aWmralF7U6piHhGxLewFtEY5K2Q4J+ufWv5e6ZUmKD72ivUtgqhe1IulUDtyKxfv91rm6/VD1bm5bObUNSFVe51aRYKgchErYAiM47QiWJdisG0bDvs9tmp0utajlOLcj8Qi0cElJRkdaBkv7g97vv76p3z8+IHb+zus0RKQcqfxduChuWMOmtY6uSe1RiWhhaokm2ROqXb2ElFrYhKdVgEZtcwj1jnG8UyIkfPphDeW05MnuEqPPJ+O9P0gmgXva3fsEbpkjMMoTfRu7ZyWui6FWdDi1lo2XStV/NJOh0qxrPqmkteOYcnLvFs6WcvoaE1tMxqtP8syqNdvmZ2vnaqc5e9X7/lnQrn/nY8fvKHPdX4zjVXsUCTIo9l00lppnVhnVGFipk8j9+cHYkrcfPGK/cWOw2GLdQ3a+fUJl5ZCIUdJziHKSjKHxBwzM4B1HK5eYFtHd7nHdZ72YotuPLQtAYgIkjHkRMwzpWi8FRyiR06zTRHimC9glcG7lqYTxF+cI53fobnkbtfzm9/+ijla/qt/9d9wff2UL158ybfffsvf/M3fcT7d8/DwgWl+YJruOJ/3XF1v+Sf/9I+4ut7z61//mg8f3vPuwyeGYeLu05Hd5hKJhRVG8TQnaXWFQDA1NQuk5VKgcQ2gKjEo0seBTx9v+cu//CuGfqA/n3nx/DnlBrabLa5uysZa8atmEe8UrcVCNmr6KfDp/sjr79/UebTiyRS4uJj56Z+I33ZOiRwjwzStD3bTbXj15YZFXStZvXEVs/X9QM6FL3/8FYfDgXazJZfC8XSUTUHJfKlpGsZpYpwCfd+vqESAGKUKEGGTlk3SOjZNhzZuFWlJbK34em3jaGyD8ZaiJOJ0jiPbna/QD0WZE+fbE8Fb8ijK7Vwiu7bFW8M3v/p7Hu4f+PLll1xeXdHWw0fTbvCuYb/Zsd8feHrzlP3+wOFwwc9/9lO01dwfH8RGZXStvKqSO0sz1jiDzaYueLqOOTraZsu7t9/y8f0t79584OHhyNXhCmvlgHnuR7pmy8NDz/dvP2F3e7Ze41uDawzaC2RmRrLS5xSIpTDPBZUSxdXIXyPqcF1b+DmERwV0PUBllaSFXCrApyhM0sSo1nleURbrOrRp5JBRJDZVoksVOIdGy3iiSWyUxrYN7WHPSGbIQkQsSjGVTCwSt6oozHWD0fUQIbS1uoxZT7P1aNfIOK8ITe3+4SRdHd+KyFKPNJ3i6cUN3gn29L4/cnroxVbnnXjZdc2bVgKUKblgK5ZW2uh51SFY51gigJcle5xHQS63DUYVUgqknLHOoLTY8BrruGg3eGNxRq8H6q7p8NayabsqBpZNUBvLRsHz58+ZY2QIE3OOTAujvEYwUwsorUV0p7SCKCLNKcWaW4FgcrUlIgLlJa5nTmWF/BgyFvnfYZgY+4HT6UyYZpyWcaYqlmc3T/nJl1/w5OqaTdeRo5Do/u5X/8DpdKaPolnpNi1awcPxnpuba/7r//q/4vXr73j/XsA093d3fPvttzw8PAhTZJppNx0FmKKMA3sFs0l4Lcr9UHPdc42ELSj680kcI41YHRcc+DRN3H/6SJxGgZN5v44PGmvxxrCrAuV5FieCd2IXa7wVKtw8M/Znjg8PNfkycnlx4Mn1FQ8PR0rJtN7KeznPlJLQRd53q+oetgiH6zwcEORr1UJIchuwODmo4y3UOnIUSWRZiLj12Kz4oSX6D97Qp8rEnmLAagECYDVzjlhtcM5KbGGMYMC2Ft85dDa4zmEbizKgtHgLRRG/BBE8zlZJYo1LCNAla4O2Br/d4tqGbr9He4tyjaAlM8ylEEohoklKob1HKYuzHQpDmKtFJiRsrc4LVVFdFDmB0Z7Gb7m8NDg/8+rVQD8W5nnk/v6WkjJv3r3h3B+Z5p5cAm3r2GyvuLjYsd93jOPM7ad7+vPENEZiyJRMnf9s2O/3tG1HSQWjLW2zwXtRkE7zJBWHOGMpq9RbKi3vPG3Tst1s8dbRtR2XF5fsdjuaRhY2bQULKhujePblsGfWNtaa6qTUuiCnAsfzGf/wgKmpRNouN53UAUvVJ7ALWVAWlbqx4lLQdeOy1pIRtWgIkaFag4y1MttKMv+LMa4VeK5zXNnQRR2aa9dAVNdGdBwZmVvl+vMrmENApaVKEcFczpnhPHC6P3H7/hbnDN3Go1WRr9+OeGtw2nCx3fHs5oa2adk0GyjI/M4YvG1wzosdsR8AUf1eXVw8LkjzxPncg5WDS6ooWmsszmWatqHrNmx3e/a7Cw7tgfvDmTjD1fUTnGvY76+wztPWDf18HNF84v27W3KYGU5HeWYKWBTaFZTxskgYJZjTDKWI3SqVQtbS2jOy3tRwFnk/WcJujK00K+EqSBFfB6BI1ayUqU4MifbNWTQzVCfIGqVrxUPru0aeQWtIc2KcJ2m5a71GEC9uhaKMzIx1TbhqVH1NtmovJP17jolU6vOK6GjEh2+YQgQjVXsuRf5c6aoPkI1sgSClmKoyXDqOZhUzGdAK7z2FIGyFLNawdQ49R4hJAqS0xRiH0hlrPYoo/PUqilqilbMqa0xnrk6PRc8gs9w6/zcGvWoaSv1VOrqPHccktjMta5fEuqqKoBXdO0WuiegexPKqlVqjZ5d2fs4yO4/zzDTPEhc9S0vfFKSTVGfKjfc03nPfnxn6gWmcCNO0gl6MMYQU+XT7iffv3/P6+9fknLi6uiSMA05rcorsNxvefPdaPOh1TSElVEprfrtRgvhVNX8DVNU5LJ+fkQWzWJi3XUfJmU8fPrLZbthst6uLSsZ5Dxgn4Sghpipaq+9ort5+Y5jmmWEYqjtBYF7WOXa7LZRSVfEr22+N3zZaQYq125pXsp1U1rImPl5zs27ojx9qHTkqVRkTdX2Wv+UPX6Gfa4t0nAa2XUt7sUcrRZ8CWy+L5fH2xKk/YlpN23Xsyo6UMptDR7v1YHM1+IsvL6Qi/besSHMWW06QhziUQtKabDW68Wwur2m3LbvrC7JRRA1TyUxJWNVzzmQnIQyb3Q7rWlqzp2S4/Xgvud/9SKMtxbc0tQ2aYiGFjDYbuo1nf+iE0FWuuL0f+Pb1O8bxW/p+4HR64Pbue0qJaCLXTy559uyKy6sNm63n48fv+e7bB+4+nen7SJwKFMvFxY4n1ze8ePES5xpyzYpv2guMU2ijGPtbpmEEUh33SJumGBEEbbdbri6vePXy1XoC3G23bLsNTeOxzuKspI3p2n4OYYIUUTmKz9g6tPVY19Z5jwJjSUrz5v0HTmPk2ctXdF2Hb9saXRirdSehFWSj6/cwhFlEMVpL+MCiWLONtOZSzpxOZ+7vH1h4/XKvK2J9AEBOrjHlx+hDrbENWCUtdeMdthVVfYlKZkw51uCezLE/s2RyG20lWGSa+fTulnfv3vLNr77BWk3bOrrW0TaOBwvOKJ7eXLO/2fGLn/0x2+2W87EXoJCRJLEwJ7GX3d5zfDiJhcd7Xr58hfEN53HgeDwxTCM3L15gtGbuTxSNvIfWgbFcHK64vnrC04tnXG6vKdGy31yRQuF8PnNxuMRZj3diZ3PK01rP7/7j70hjz+27N2z2A5vdQLMP2HaD3Rww1ksnKsMchMY2jqNU5knEV94YTCliEbVSvasiwIsCojWpgiuNbIhaiQq8kOuowACGKHsaKRdhyWrhaSulKVpS2LaNoGizNcxD5P54IuuaM10DlbIFoxRYJ5uTbyR8plEVqSzBOtM0EYviPIXH9rtyUjQ0HaA49z0hQz8FsZTVONlcN+4U6sxYwTSKkDPNsrAvvmTQGKNwrgUGzueRECoytI4D8zBBSlgMzjYrFKQNmahniFkQoTy20lUqoquIUcYNIclm4T3WWlpjKciGoqqIeHELpSSbeqqbQUSQvsnIxueNwygRUlKBTaUOQXKSVDZTO3E5SUewaqulExEiQz8wnntO5zNl7GEcMU5Q3KZqR7xzNM5zf3vH3d0tD7e3TFMt3ihY7xnngY8f3/If/ubf89/96y/55Z/+KT/76U9ptOZ8ceDF06ecjkd+9bd/Sxx76SSlRB4E7a1ilBwNINXnWxupbH3TYKyhpndIdyIXVNT4xnNxcSE6mN/8hqsnT7iun5uu4/hwz8ODrP/eeykSardwFawZYfWHELh/uGO73bLZbPC+xqt22/pzWDkwTwqKhIgZBU4LK34O4nQoSQq55T7Q+tGmq61/3NDraFQOKWYd01DERrmMW/QP3Mz/D23oUxZIQlKZYjVu21KytCqCiswq0ueRUxy43B3wjefSySlss9/QNA1KeBQiaiqZWIKcQFOt0KoKN+ciivTqKXetR3ctqmkp1i+jPFmESiTmyDhF4lzIKlBUg3OF7IwMNLWShcx5ShZ7S1aCY7LK4podmZESAnMohBjY7ndENOdf/5q7+3vevnkNZHYHzWaz4/Jyx9XlgeurAynPpBz4dHvP3d0tzm24utzw7OkXFCDExPX1DTEmvFdst7t6szrmMUhbLW/wtpH3g8c5S4ppHYw3vuHli5d1zldwxq5K2cVXvMZbAqiMFsMtKWcur5+gjLSnY5QZmPMdKEO33bE7XKC0IabM6XhGG03T1KxtY0kpMo3jSr1KBdBCg8pV9BNz3VCUYhzHNRt98eALA3rxtOvqn65I3lLHRmqZDWZijjJgDVpmajEyx5mQAilUYVe16WkjM9B3b95yPj3wzT98w/n0gC0GWzQmG3SU+bPkLg/cXF7SupZ5mFBZMfaC81TI3MwauUa3H+/oNh3ddktWCZVkxlkyayrT0I+gZT43zhPvPnyP8Y5u2zH0A5/yLa3a0eodXbtFXRnGV2Lb27QbrHU0Tcs0zqhi6JqWcZgqUzwSiyIWBSWSwkieLMRA0g0FLQpe1Or/xsjIiVoFxtoRW5XkdS6NqrALrVACkqBQQ2AKjNNMP/R0WeFb8apbaypSVjOkQkyBcxzQ1tJudyJ6cw43iro4K1VnxK6Ka6WZKP5dTcoy31e12o/Ia60SLhFJKtFR6KbBGgtWIoznIizz0zQJhQxhy8cE85zQw4xRFquorVBVHQKyMIsINaONobENmkAKBZJCFSOaigJoD2RKMZA1uphaKSrIGlU0ORbGLNZe2xp0a1C+kdk1UsAsy3POAmqJOXHqe8Z5ZhinCsxaNi85pJcqbiilCAxGaayqzgMj46W8jDYKa1yp1Ua6I1lEe4vSPddNf5om6XAt38t7msaybbwwQ4yhP/dM/cDtp0/c39+TYkIDbdMIRKXM5CyI47v7e/76b/6GVy9eoH/2M7q2RZVM6zxWKTbec680Dw93VdGvxT45B5knK4UqQsMTbYb0R0oR51MBtJX7oWnlZ2zbZoX+dF3L5eUlz58/4+Lyktu7W6ZpAkXVdsl1n2NYg22WDX2YROSYsjhkxmkgpoCzTeXMS6tffPIaX6l7BkESL7P3GKX40VrVTAs5GC0RxShJ3/vM2LWq4/Xi/ljn7Mts/Q+8oY9ZvI9ZF4rXuP2GMI2EODCpiCZwSgMP4cRld0V3saHTm7rBeGmtetnMRUCQCGUWu1tk3chjrdJ8s0E7g99vcV2L2Wyg8RTna+wjKBK6KGKcGMbIFCdiLmQczidmD1pbnPEiivGKHCJ9PxJrRbFvWpqmISlHMjP35zumMXC42IM1HM/veff+NX/793/FxcWOv/iLX/D8xQU/+9lP2G42bLsN33//hg8fet69/8T7d+/56U9/ysXFBV988QVKK27vbzkcDkJZ2u45HC4l2jLC2EeOx0i33dF6zzz3AjRRctKOQTZ0BXRNx1c/+ooYA6FGqC40qyqPkoa9ESSotgqztMRrWES33bHZ7USp3veyKRXYHS65vL4mJbEKHfsT1hqe3FxjtEZbLQKUYcQZg3eVdqWNYFtjTSeKiX4YKEUoXNM0r4cNqDCKOUgrXesqwsqPJKXaGs0UYskyHyYTlcwLRUgnfOxx7JnDBCmgKTy52lNy4dvffcftpw/86m/+FqVg03ocBpcNJhlUgI/ff+T29j2//JNfsHEdw3Fg7gPzHGt7tOCc53DwTMPE+7cfuHpyjWs34j1VqbaPM77pcM5xPPWgFZvLHfE88B//4Rv2Fwd+9JMfcZp7Hu57NvaCrb9gs9lx2MlhIoQg3Yhq+4khcbm/5MWzZ1zsD9w/HPl4e8fbj7d8uHsglCC2vlwo2kEr8ajOW7KqqWvakLV8zcVpQErSBRFhQ93QjYhrjWUNOlCWUky9bop+mPl4+8AFhq22dLsO1zTgPRlFPJ8Zw8z96YhvW7ZXlyjrwDlc4/G+qSEzVDa5YJSl1Vm7OfWQoavoLmXqAcZUh4pZN3TbbFBewEkpJeYCIWbux1FEaMAwBVJCeBZlxpsWbwSIo5SipIpXqZvzPM14p/GbFl1G0lwoSaOyWQE3AjwoUAwkcWTIJq3k98WQUqAPE63zGK1pfYO3VjbjnIlTqHbMqnofR6YYeXg4MoZAP02CsLYyFlny6RWSOimCYYl8TTrXcYgVp8JnQrmYEnOYydrI84sI4gQkU8jU1LFxJNa5srYG00o06GEr8aXWWo73D8zTxLu3bzmfTghUyLBpOzKJISRKcfjU8PH2E//m3/4b/uKXv6w88g2NlXurtZZt2+K14uHTJ0Cxv7hEpUyZ5yrM1ehcZBSx6MKKpKyFeRJjcfFo69hstnUM2UmOu9HsdluePXvKl19+wZOnN/ANPDw81KImMU4jS8gPsApvnfOM0ySskxhwKRB7EQm2jdjnJJCzWhGVorFaDsC1gzNPM2EOpBDRro6QnIhmja3BMxW5vDx/n8dNay1hU3kZ29TR+Q+vz/+PoF9/9GMBDIw9202H9h5KIjvDWDJhGjnNM+cQuBt6kllmHwCDPIh9j1YWYxppZZ4nyIqSDarSp1LJFBSu8ZiuY3/zBNs0RK0JIXL8cEs1DVTFbOF0kjzcOQokpfUzplisr+3c5SEapS0mbT8FRMqcmNRUiT8F326xTSFqxUZ5/uTPf8azVxccnih225avv/4RzhnG+Zb7h7eMw8T7d7fc3T1w7s8Y5/jJT3/G06fPaNsWVGG73+GbBpDXcD4NjFNiHAMhGBQtcZYqYZxncg44L+foaZAq93w61lQgxzSN9H1fKWuZ/X5H08pJ1RhDrJakaRqkok2xikk6lDZY3+JPR5w/8XA8MU0zd/dHirJsd/vK+VbElDmezrIIKyHchRDl5suFoT8zTiNvvv+eaZp5+eol2+22VuNCbppnwY0uCvRxnBiHieubGw4Xl5zHkTkIXlS8snJzZ+REfR76VfCZKiwiRPGupzhTUiQFEWq2jWEae/7nf/dX3H78wPfffsOL58/4J7/4M6xRWAXjeGYczoJ6VUDUDKeJxiaUM7RO2ripzuTv707c3564uz0yTZH7hzMJYSJMVRT14dM9aMUQJ/HyX+wZppHzqWe3O3DYXogKPcmMvz8P+K1HeVHzo+URN0rjlKaoBCmw71r++OufcOp77o9nfnweOA4j7z49cH8eeHt3op8j8zSQdZSF3YA2S4a2zBmLKqQ4k+aR2WlsVTirUlZssIBllKjklSJlVX3r0G52PPUtrqqFY5KkM1u7AF3XYbyjjwHrHZRMfz7y6XgiZIUpmlLLkcUHHKr82hmZd6ckiFRjm7U7lUtEGTDOY+q4Jlf192L3iikRECHdtOKBIaExRmKMc1IY7XC2wfkGrTQp1NeXpB19f3eS16cbhn5mnhNKG7zz9agM1tejc9GEUAizdBrHoeoCahiUVoYUM/0wkGMkWoez0h6fQyCGwP39gyiujSUBoc5fQSr3EksVKixOAhkDKbMwAqRNW7J0UKo8cVW95yxtflVT5axS1eEjH3JrZKkop5ncn+VdU3m1xinEmXJ3PnN6OKJQeOcx2q1K7pxyRTrDZrOhlMLd3R2//e1v+Q9/89fcXFyy6zpyCCgF/+Kf/3O+/slPePniOaUUDocLjqcTv/v2O/pp4jgMmHmCeWauo4pYbY05y5jocNjV1E8RuX3//ff0g9jL+r5nGHumSSysh8OBbiOWMaU14zxJJ7Hqf2ISJPXxeJKDUilMsziSmqbBWsvpfEKhmMYe7xw3FxeSGqm1PGMJSsqEKRCDrHPeO4y2QkdtO5qmw/uGUKpjo/DZ1agzciVwo0cvO8ih+4dv6j94Q3/24iUxRk6nB0mDcRaSoVjLnAJ5jvQhMKbIcRzIRmGcBG+ktIjze6mYXUecM8Mwo7GyyWsJJUjLa3Qe03Zsri4w3nOeJqY58PDwQM7V9qelTTT0o1C2kmwIcROwOmL2guyYqlhvniZUljCUUudTMQWGrGiMxWtL2wnBaUgjrXH89Odf8uy8Z3+VaVvHyxdPOJ+OVcX+gbdvPnD78cjpOBICONvw8tWXvHr1RVVDZpSuUX9KEWOm70fhdh9HvLvA2o4QZB48ToFcZlAWSmbsR4Zh4P2Hdzjn2O/3nM9nHh4eastIsd1t8d7TVgVtSKGmigV5uEthAclY52m6rQiH0AxjkDSvU0/B0LQbnJfZas6Fvh/qBVkAJQmdDMYWzsPAw/GBb2p2+L/s/8tVPAeFea4dhMJjdOEgec1Pnz/ncDiImDEXAToUsSmKk0nsbTELhjOkUHUB8mtKUXKiKcRpgFIYB8/pdOTXf/crPn58z/3tRy72B3706kuZT+XExw/vCMPErtvhjKEkxdjPxE3CqIJvRCGfFIzzzPF45vjQc3o4cz4PqNt75jpaUFbEhXNJpFKY8ow2mu3FQRb6aaJk2G72orjPItmbxonc5spEMEgEcK7zTo1BQU5sWs/T62uGeeY0TAwhMcbEr7/5jrcfPnEcZ6YQxNqmEviOBQijl35NWfCgS1fHEY1BFwHJmNo9ydLfhCzC0lREnJNSoWm37Bov8JOcqqc5oBqPMYa2bTEp0Yy9VCElM/Q9b7//Ht/t6XaX6yJmK1BKDu4FuwrYUhVOOqhtY/Hvg/Ee6xtClLlrUoqAop9ngQsh8/g5L0q9SrQwHlXtaUpbrG0qNVIz2VhhKYoQMsfjGe8jbbNjHGdiyKKOt+3azLDVPldyIYZMjIWUMtMkSWrWaDQSLpJyYhgHmRPbhG5FaxBjZJpn7u4fCDGiKo9fe0+qg9dSrZ3rMm6kVavqTHvxTassI6Z5DjUgihUWk7PErab6NUoFzcg2Uq95rkjtMFPGUaA5rvIRqrpea80wDBwfHlAFsd0Zjxy4pGs2TwHXWLbdhrHvOR1PvH7zml/9+tc0f/THbJpGDhcofvlnv2Toz2zahpwzh8Ph/0vbnz5bmmXnfdhvT+90pjvmVPPQ3UADBAgSJEVRIZJBmZQUpvnJ/50d4T/EQYc/MCRQFAGQRIPNnqq6Kqsy845neqc9+cPa52ZD4bBaEe2LuMjqyqyqzHPOu9deaz3P7+GudOsPux357k6S/nIi+BlSwgcvFjwtXe5yscAaS5jkTLm9vWX2c3HQDEzT+ATRWiyXaGvZbDYYJ1S+mBKzl7H6MI48Pjzy8Lh98vv7cumyRZ0+DAMpJcbB0NY1V+s1RokVUoqy7PRjeI+zFvGsRKZWlXjjXVURfBHMnVbkv1nUS+d+wjfl3/j/v+3Xb13QMS1GJ5abipQij4dZoA7dBqWEbqTaBWdlHDrkhMvy8LpGYg13+56+P/Duzc+xpqJtllxcXvPs+pLlYkPTLhh6UXu3F1e4uuZxnMizF5VmSljXUFlH1y4Yx4m+7zlr1mzqNd+/fcvucKDnkdTNrOuOqq7pjMUnTT+PolA1lbx46v3tlyhCEV1nrMkMcSAwc/FswTpYFptA3x/4/t2vef36W/76J3/N3d0j93eP9PvANEY0NVpX/N/+H/93Li4u+e//+X/P1dUVH3z4HK01IWXAMMfEw3bPd9/dsVlnFov3XkXnKkAzzz0xzBwHuW2GlPHDyKHvC6FpeuIRD+OAMpqxhL50S1l1CKgh4IPYO052jDl4UogobWm7JdpUrNcb2nZR8qNH9vuDHFJWtlkpSdRl1zXElDj2PTHLWPrTTz8nk1mdnWHLGDamxFxiCR/uH54ETk3dslmvcdYRY6Tve3aHI/MpYzkL2z2VQydGKebjPHI8HNjutgQvu6rry3NWiwVX5+c0VcU4DIz9wMXFBV1T89mHH3J5fs6333wvyXjB8/Bwx+PDPa42OFcTvWIaEnc3W2DH8fg11lW8ePFB6e4MCoezLY+7HQ/bR3ySAm5LSEi7XGIrx2qxwThL03Z0Xcf1y2dszjY0rn0iwrV2QW0Ecxq9jOdSjCzKdMVqAYOcr9d47znst2QUdRGwKa354pOP+fCDD7l8/orHQ89Pv3rNrh95GESv4KpGPOFVVXzGM7WVy2pX19TWErwvFj7KyaKKH13ojOMshLtxnKh9pIlRPkcp4dpa7JFZELLTNDIHT3/YY52j6Sp0DnS2xEoai09iV1M+o1SkRkaqYZSxpjVONBVRLoL74xHrKqqmYZgDfpjlWS0CuqoW9X4K8s9nrQlWP3WeqYgsm7qmqSsylnGOaJtLDoSVbHckKGS5vpTJQQDjOq6eVcwFDmWck+COIlibZllzicsdsipBVTHIpCXD7CPkUYRr1jGMM32acMbSNJq6adHei08/C10vIor+9KRqfzr1Iclq6kSuUyjxbedMDh6soipi0OGwI5af00pSuxZthzWaw90NaZ7IKhCHnnQ8kr1HdQsUAZ1F09NHzze//jX7+1vCMJFTwhZh5Gltc9KySACRaJ6Mq6jblm+++ZboA5erFZdnZ9RVhcqZXXG8vHr5AVpLWMqnn37On/79f8BUVg5fv/6WX3//HX/5V3/Fr1+/5t3DPaOfOVtvqJuG2jmCj9zc3orGyGgMjkorQoo87nYcx4HJz+ToQSlhRhiZAqIUxlnQmqqpObu8oGrap9XgKT+iKR36KV+93x/RCpbdAmcNrbVYDc4uCNPE/uEBozJeQfSBYzzw+PhITMUhZAzT8SjEVV1RV5bVavN0iTBal4bXYbQmMpHLVDKfVHa/q4KeMShtcbbCe2G0W2eomlrSC7Vi2TSkHLm/v8OPI0pZsaAoRyTSz4HHfc+vX7+hbRZcXmhW5wrXLek256yWa1TVM88B1y3QznL0og5VSvZAAvJoWHZLiIopjVSuxlnHu/SOOMwEN+ATxGEkK03VVQUzKZ5bSX8sgpiifg1QCopsokL2JDztsgIMrj0n38zc//yG79++5ue//BmPj3seH/b4URG9onZLtHK8fvOG9WbDP/yH/zXnF+d0iyXaGKbZE6L4hYdxZrs7YMwabSYZZRlNWwkkZZzDE7LVh0DOYs8axv5pl6yN+Gpn79HjWGxghrqtBbRSGNQxCQ5zHCc5pKdJonCNoa5btBE+c1VVxTqW8HMA0lO3nVIEZB/q/czsA1obqqqme7bAOdlpmeKHP12UZKQlN+ZxlPeqbVr5wBawzDiNDMU3GsrYK+bTzjyUP/fAdvvI3d0tfpZLo5YWhavzc6y1HPs9fvYSCtO1bLoFlbPsdwdS8IR5YrvdstvuOTtbU7uaHDUxwPEwEkLk7dsbSWFaXWKsLfdjI2siH9ntjlLQU6KOCVdXtN0SowxN1QpX3zWslms+/uhT6qbG2UrU90pEV7WpZfxZOk7KYWmteUKZtk0t3dc4CFGxdgXxmujO1yhXQ9XyuO9593ggoXg4PkpnS0YrsRNRpglWiR+7sgZnJDY1nrQNp+6cU4eHXCBDYpzm0h0aASGliG0aVLF+5pyYppHJe/w8y7seAzonKi0rhKp0MoJ3LoEjRQ3uvUBErHboQp6JITIcB+qFpmoNPniGaSaXTrVtO9GF+Fk86z5AgZTk8gyfcsqVkozpjMKHRIiUwBzxgUu6uKFuFmXFIJ1V3Xbk45FxChglRLMcZdrlC5ZamSD2z9M8JJ3CVPITFCYVe9rkJ4KPVEt5Rmy5ECljSCniw1TCY/T7In4q7CmDzk9gKlXOKLlRiTshF/pcjhE/DJwsqiXeBGctlbVsQ8DPE05F0jSTp1mYBJUT2Y4PpBTwKfL48Mi437GoGyorPn4QtPepuw/p/fRRxLMGVzkeHh8Y+56Hh0emacI1DUa9R3qv1huctazXa1abNS8/ePWUSvaff/Ezzn75S24fHuQSvd8xe0/bNNRti1GaOXkOh4MUsVosklaLPW+YRlltxCgaIUS3eAoJ01pTmVMkqqFuyjlYNCdh9iIYLtz35VLWiA/2jhyjdNtaOCfOapraPBX/FC0YyxxmUkgMgzy/lM98irIWVlosbHXdPDU7KZ2AUKZkQZjSyBZU8++yoH/3+hZjDG3Xoo2haS9IZOYYmIeJyU+0XY2rW9YXH7IG5nliGAb+/X/8T/THnnmKIutXC0y1oVpc0W2ec3b1Acv1Oe1iiXc9ap45zDPBj/gcUeWGqZRGR8U8Bu6Od5L7PUNlDK2qaJKhjpoqQ5Uy8/4Ahedrtebq8gxfRHExKXQqedAhs2nXNFVL0JGYArZxJAWHaUuMM9N45Jvvvuf//W/+jIf7ex73Pf0UiCi61ZLatXz22Y+4vLjms0+/5Pz8gt//g99js9nQrZZ4H+n3PUpbqrbj8tk1yjbsdiNvb1/TNC3OWc5Ug3WqfBAlDAWgbiSPePbTE/DC+xmlYJpnlFaF0hf4+S9+Ts6ZzWbDaQFttKXtFljvUUpy2pu6IUah8nkfGQfP+dk5dV3x8Ycf0bQ118+vn8Ihqkr+uWEcGIZeuAMxPPGqXzx7Rl3X4rcNsmufxpHVYlnIeQOVFWVqiJHD8UgioyvL9uGOYRjLBcbzuHtEKUXbNuVwlhCR9WpBf8yQPL/6xS/4mff85C//gq5t+Fu//3ucbdb8i3/+L+jqhsvNhrEfuH37ltfffsvPfvpTyIbV8pzlYsViueDi4gXr1Yrb+3u8HwlBVNbbbQ8oxklGeYvFmk8/W/HRp18wTnIx6tZLqqbm/OoKbQ3v7t4RUsQaJ6PlCI2tuTq/FkFpSNjsMBmin8W3nJP44r0npog2hhQD89CTg5ec5aqmahpyL1aq/rDDx8zd21se90fG/SNhGHBECedIHh1AzQM6RlwOGJUxZKzOWANRuK6i5i66BaU1ddVhjKWtW0xhdtd1Td002CiJh3XXiK3JGVmNJI8zoJWcDVVOJA3rpiJGz3h/J5wHLamM2ljBlKbMsURhulJ4rJY13qJtCDHyeHePrirqumZOQmrzcRYEq8o8tcQGbG3F76uSCLzqmjjPPDzcs+iW8meo5LJbNw0xRm7e3YoqWUv++Wq1JmdxuqScpQAYLWpom8lKU9PI4WsNOSfSKFoO4kQi4PNMKLyD2g0oZRmPQ5mKiFd9txfKma4EYBPGCWUN2rWF/FZoYci6DN7TxJ5+PI3TUeIpHwbi0MNwxLSdXGSiTOS2YcZqxXoh4uLHN98QjgdpcHImzxO5IEe1VjgnF0xjRDwYT/5q3vP2lTEoMnGGlCXSOifRcIxTYOwn/p//+v/FX/3VT7jcnNFWNcumoakqnl1f03Yd3WLJ4dDz7TevnzRR4zCyaDtevnjJOM1MIXD/+CiOKh/Y7vb4EEpTU3IoEK2ANoaUiigweOJJMlzYAKGQAPN+XxqX+emMbJqGruuKCBImNZYAoSQNiPfC20hlJB7lvB2DZzwODMcjZGmC6lq0IJWr0drKSlNZusWSjCYq4XWcVpHH40DwkWmcZW1TJoo5yerhd17Q++OEMZKMVlUVxhXLQkqMc+bYC4Uqa1XEWZp+CIxT5u3NI/2hx2gRClTNirpdU3dr6nZF1SzQriGbimw9OWbGMOCDl3GKKpuE4mnKMTGPnuwTyQdJPqoUlbLU2mISqBglnMQIt1pbS1258oCkp+CCmGU0l4u1LSa5fSrJCMFHETlMPnAcJ+7utxwOIyEptHHUjWaxWLFolrz84CUvnr/iD/7wx5yfX3B+eU5TN9I9EJlmj7UKW0mh7hYdh+OIjxM6QFaWccq4pEvgQHpSPxprMTHILVMLklJsfjLqC9GiS7ThdrsFYLlcllunKYADQ0ZRpUxV0n9ABEv9cSDGTNu2dG3L1dUlXdfx8uWLYo0Thad1hmHoGZqGEGZJkyvrgrppJBqyCDratpXPTBS6knMVp1CNmEogRBTRy+w9o5+YJlHvD8NQbB8lXpOMNRprGnIKqBzp93vGoZfs5rEmp0jtHB+8eiWj+M05h/2eOM883j+g0AWuIuCYumpo6o666VBqR866CH4M0yhRjodjL1GI2tI1NVXbiOAmBNplh6srzs8vUFrIcTp64Um7SoBLxtJUdRH3BEwSIIjAdcLJgSlWRIVMjpL8HDnjjByq1mgJ9NDi1PBzYOx7ia6cRqKfJHkL0QoopVEpoFMUwSdi/xF4h/xnTlG1772w6umANM5hc8a6qgSNWEHaZvk8nRS5AFYrMJrGFXdFTligNprJy461BLVhs2RIqyyHt8mSF61SQikRphoUzhiSD4TZU1cOaw3Bx2JxjCfGCEYrgcOUaVVKCQrlzihNmBLez4QYhANfnhVbeNoCdIoyRTGCBz2F2GTy+yANlZ9cfvI8lOCWhFjgyncuWhOK3coHWXvNxSY6e49GHCM+CDY1JSEgkg0nuMh7GdTJ0qOe/vpUzH8jfJNTGFMOAVKxcSpk0hXFrpW0YrVcCLSksCXKP1yY5EX5XexTWpfOO0u4zek/9+RaOf2+CglSKYPSJw2BJ/rIt999z/Zxy7OLS7qm4dn5OctObMwhRuqmQWvN43YnpL6cOE6T5NSjnoiRzlrmKOE3c5SJ41PsMu9tX+VP85QgdwrREYCMKh7/hC879HEcnyZUqUS3GlXikrKsNpyRTj2HJK9/BlW0KaL1kfc2hIBRp8+leVK2a6WYZ0/lPU29ED1Dkt+vTCFl2qHLa23KzIdUQnhS+ht/1v9fX7/9yH10jDHw5vX31G3NxfMrIYMZw93jwO3jA207UNU1rnZkMn/9V3/Fw8MD797c4Kzli88/4uriih/96MdCzlqtWa434M6420+MdzfsB/FjPu4eyTnxxeefUDnL0PeYrOh0Q60sXbfm4d0tN998h372jOZC8+L8gvPFgtfvvmcYetZnCwyG/vggI5m2IyvN6mxZvKOK/eORfpro56GM36QT3O/vSMxUjSIlw3FwKHPBR5/9CbvHR+5vb7m4OOfq8pLVYkHbNvzgyy+5vLzk2fVz2rZjvbkgRcX3Nzf0/cjd7RZjHXU7Ms8Sa9muDYvNBeM04v3M6zdv8fNcRjiGrpMPfLvosE722cPYiz9TyVjbh5k8JR62o6AQ5wljNPvjga7tePbiuTgE9gequqFbLJ+66qZqcbZi9cmGumq4ODsXgV2JdzRKM/Q9t3fv8MEzzdNTt1w3wuY/YQvv7+8BaOsGYyQDuqpq7LnschcrSTAajj3DPDN6zzfff8fDfgfOYuoKFQO1a/jByx9ijS6wnOJFLQS8ZdeyaJsn6lVXVbLTKj8apYhexlhk2GzO+PjjTzDGcn9/z8PDPevNOcvVClMvyLqmatZgWrrlBbP33Nzds9vt+ebb1zRtw+bsjOVqyQpDs1iyrisO/ZHDoUdZi3WWzWqDdZZnL5+xWC54/uKaqqqwqXDAxwlnamqtCF60IbaWOE+nM1plaqsJaKwCYw0Udfc0jCyahvV6w5u7R1I64Icjx90j27sbdseBwYvwyhmLchVGiYpdXB3F+19ZtNPUVlNpxVT0DiGkpwOVnPA5EVUGq4kafC5Jdlk857kQ2ZUCnRNOQdPJmiDMI3XKWGc4joE8j+RpJmVNaAewTjzyKOw0S5Ki9yRjyW0LSrFylkqD0ZmmddRdzcNhJgaPjhqNZdWKin2xqEGLVmecJoZ9TwyRaY4YpWkWJZinNuJymI5MdYMC6sZQZXGPKBL7w71cSowVCpwDCE8FOCZht2ulBIBCgDwDkYJuA+1K/ZewlJBkhRFSZgqiJJc8iaJYNxrlQJXEL/Gsn9K83hfOk+XvFFv0vuTLmmOajuQYsE0DKTIf9pJQpzXOKLSCMA/olFi0DT4F9gqU0bjFApsDLk1YElp8Ek9dM1mJKDYLPU80MhG0YrVaY51Q+1CpNH0d2mVubh/4bn7L/cUjbVPzVUlDWy7+I9ZYmbzMM/v9ninMDNOErWts5dgd5Gx+2MrIvVl2aGPF027ej9PnOTzVqTYknrZIiBg3FUus0hrrKiKR7XHPNE8ytk+lQIeM07aw65Xkb8RIHAPOWKGMWoOqZfqiy/qDMn1LIYsrw0gGh3UW6xzKWvpxAGtRdYfSRtTuyqBnoRIK4lcK+mktcHqnlT79aX6HBX08SlfS7we8T7jmKAZ/6xiHgPcA4hFWoyelxHY7cNjPgMOYhrpa0jRrum5D3bS4qkNpJ2Q2n+gnTz95Ru8ZZw+qeFOL+peUJVvYVFA5iBmVIIwzw6HH1gbXtegsqt5c2NopgUqJHCe0dTLGToocxVqnjSYi4itKBKJsqTQhZmIEHzXWLXj24mOaZo3WNednG84vztislywXLZuLMxbrJcrqp4jFSIn5jImQIjEocrHbxByxVuOcfgLdZCUj/9krYjKi9DVlPFMOE2MM1ooK/qQGz+S/oQDPWZcut8SSGjm0TvYxU0apy8VSMLLrc5q6Zb1cScygk0tZCGLF6PuBaR7ph750BunpAdclwWicRhnfxST7pFpuuCkWxXoIzNNM3/fsh4F+mrh/uOd+v+f61YvCaJY90nq9fO+flUeTU1725fkZZ2drXMFaLupaCG1DLw9giHjCk+JUIYz7umlElT6HwoqWtDK0JWXZv4UQGaeZx8cd292Ox+2OLkRc3eDqmrZ4uWVNIWlvIQS0KZ7bumLZLWibpnxmE2GaiHOAKF2o0rmozNN7dGTO0mXF8NSdn4Q0Icrr7cqfoWtbfEyslkuGybNZCaiomkFZR9s1gjfWYoea5wml5EDI0QsZrohCtUYsZaU6yORHcMwSulRe/ad9+2mflzG6WKViQJGxGFKWJDSy2NUciUrJRSylVKZIGZUKfjkWXOlpvBxMSZ+SHG2dIyoFCB5i+Q6aTEIlUxK7pDhqldE5QpqfdsvaWiHkafkMyZlAGYkr0WEAKotOJQaxq8mvk9FrLiNm6cRzKfYUwYFkmuVTCEOZ9J3GturE7S5FWbpHSlcrEwCNqPnfp3BJ953L7+19J3zi6/MbBf0UsZmlCJcCLZS5IJMMZFphtSLOMlUTmyTl9y+RyDpmAfiUrlDisEVwKMOBMiV9shWeOOOq2DJPgCh53pzWHI+HEn+dCTHThwkNDOOI0YK0nuaJx+2WcZrox4GqaaiamrEIeudpFmFZFtyqIKnENiZujPz+sxtTwYinJ7aJIGbFf5+NMCZikHMinSBXWSa/ROEFJKWIs5DfovEyXbIGlXQBe6nikT8JF99r0+U9O711Muo/uQpOIVSpdOenz9YpRve0+tK6aClUKnqT33FB//lPflrUgY6kFTc3d0I7qyq61ZL15pJjP3A8TOyOe+bZ0zVXLNtnWOOoq4rrwsu+vzui7YhxR9YXZ5xhGWNgzoohJcYYiEajVWYaRqqseH5+Tb/d87Of/ITGVozLcxpb8fmHH/Hu3Tt++utv+fL3vuDy+kIw1QRG35NCpF4uSSpxGHpc07JeOHKSD2u1cKzMitAnhmmQODsNVy9fknXiq2+/Yp48MdacP/uM//OXf5fd9pF333/P/f077u7ecXb5nKvrM3Rt6P3M9uYtCsX6cMDZhq47J+sKN4iPez/0aKMwThH0RGZkcd5xZhZUlWXsJ25vHhinkXd374CMcxZXWdq2QVnNar0sqvWZaR6JMWJt4cJP4tHd7b5msRDBWtt2rNcbbm9vef36NZ9//gUfvPqQjz98weXFGQQth3ApoZNHLnDHo3wfxN95OO7Lw53xIVCP0xPxaL/fklNis14XQZb4z/vDQCwc693jlof7e+73O3Z9zze3b+nDzP/1j3/Mhx9/xHF/EJ60zqLwnGSUnDOcrzc8u7jk1auXPH/2jPGwx08zbVOjgHfffU9/7Hn7/RucdSzqjnme2R6O3D488vrNW7766td8/dWvefZyz9nFOefPX9Gta+53Bx4eHvj5z3/B4XDk7v5OMJwx0k2T7N60pll0bI9vC9BH9o3rsxV15fji008kGCJNEDy7+3sRPPmJrmlZdgt0lG6i0nJAtE7ERrP3+Dly3E6ySokRV3bHJiVUiLRty2K5pFudkdC8+vATjsPEn3z/luMwsesnfEgMPrE7HPn2+zfcvLvhzZvXNG1N2zbMOkOYsVZ2exoFBnThxIcUiWTCVEqGlh2qEPmke0/TjFKZOIuXPfkRraHuapKfONy9E5GgremwrFY13ieCj2TtydkzjgLGcUK1wdWarCHEsdjlNHma8cOA77dgDGOMRBJ5ciijYW4wzlC1rdASo0KPI3rciwDROaxJWBNh3hMmqIvVbj7uZZ9tDDllxlloaSc3ig8JY2X9EIutT2sh2y3cCmOsgJRIzNqX0a7COkPdtkWgrrCuEuSyiZI/oC2gMFWFThnXyJTBlS4yKumEU0kTfFqHgFxYODH2yhYgg0oZo4WcloMorGcCPmW5AKVA1zY4a3n77g1+HFg5TZ5HGAesVaw2a9KsCL1wL6axJxiN0wq7XKKcpXKyF9Y2iP9/kHPncByKBkEwvkZpmtWS9XJB03aE2XN9dUHlHP1+h59nDvstBnk/nDUstMaMI/ROPoexYHtjkgZDaWrbopWmnyZiTjjlZDSd5bMUU2IcRvbbHcfDnuF4RBsHWshwmcw4zlL054AqGheFrL0a7XC5eKdzJg0SaJS1h0qEmyYq5n6WIDIn62Crpems6xqJAY+SFUB8upSbwlsYhwlMRLnqKXPAuUp+NAZnDHUJ7wnjKKFK4aSp+B0W9DhNclPIcrBFrUhWUszmasYME34OQtgyFbq2dHVbDnYZQZA1fg48PmwlUrVrqRctMcUislBl7BfRVmFLh5NCIIwTcz8y7A+oqiXVS2ICn0RM0zQ10zTyuH3EOE27aNFOkXVmTjM+R7bDkSZ76uVC/O9GYhBRIroKQTpLY414bVMm4ySKMCuUrukWZ4QATXdkHWVfdHZxyXqzIkRBBe6PPTlD3S5RqkIZg3FQtw1Zz0xRSE85RiE25YT1puxqEf/+KUr1tMuLARUlotCoggZ82uvJXmcuQIRYEKl3t3fs97uSyduwXKwIIVJXFctFx9nZmq7tqFxViH1SgFPM9KNkuR/2e/qhJ/hAitLt6nLrVKgnD3M6saSfFMaJ6APei+/2tAtKJ1ta8dpa52T829RUdcU82cIo6AUnO474eaI/7Ki0pnr+nNpZaueYgZwC8yi37FiiIG9ubnDWsepWxBAYp5HD8cjjdsswzaRi6Rtnz/3jloji7vGR7XbL/thzHHqOhXantSm+VVHjH4dedvvOUteOqnJcXl6w3qxZr1cYo9ntJ5lexERKpeNOUYQuUaZXKovvnRhIWTNPI8F79ocDlN2hLVGbOpf9s5PH1VmLMo7NKsvIMkSGybMeRWg3+sD+0Atq01mIvrzucgEhRclD14mszBPfWtTn6smlcOoWTkIs6UbK7e20d82JHIPsE4MizRNpGoXulkGpREkixTlF1tKlBh9IKSIb84RT8jkPXhCgIYl9yKRi7fPgnCj0c6EopqknBi02LmPQVmPiTKMyViUqJRMQW6ZYKSW0Sehk0F4IhrURsanRssKyVih1sVDatIHJR3yU5wKlULORIh0jOgZsEgFdVgaD7Ewzp45cPYnIEtJNKoTAl5925SXMpfyakxP5BOjl9MsyZTcvj758yaVKK0n9CoiYyiiFdgbv5fOnUsRkg1WU3b/sZ3VJfZPnU+ytMfgiAJNgkZhS4QIIVQ1lMCkREfGuDv5p4ndKcazrFm2dTDNM2XkDU7kk+6Ij6QtJMgJZaZS2hXdxgvhQ9vNapiUpiwo9p5LuKWyDZMrEBem0c8yQMraSTPu5iE797IlRIsCtMvLzpbd22qKi0CxTSMRpJsyeYCd0FJsiJUQnGEX0GqPBGVH+QxmknGYnxeHwRJcrnynUiQp3ykEvWhRjfuPXStzxiSNwWq/873391gW9KbGTkxdec9sty6gMjg9b7m7vqbsO1zS8ev4h3WJBVzeQ4ebtrQidDiPTNHJ3f8tiveT6xXNsW3GeL9BOUxlL3HumMLJsaxprsCmRhpG37+45POx4ePOOvNqglhfshyM3h54Xr17yyccf8ZNf/IS3P3/H53/4JZcX1/RuZiZwN9xxHHu+efeG5XpDaBTLZs1mcUkcZsZ5khCGKfJ885K6afnu9pYpekx1htPiu3axIaoFPk+M0fHy4x/yR9fntK3COfj2m1/w8HjP67e3hBBYba6xtSYbS9VVXFSNEN7uH+mHA4f+gFIBVORxv0MBi2qDVkaiN6OjKgAGSg/ggydAGaFK8lLVVORs+fVXX3E8Hjk7O2McR/7yL/8cP3v+ovsLcs7Mc+Dv/b2/x7/8l/+SL7/8jB/+4GOy14QZpmMkTJHdbsc0Tdw/3DHNE7v9ToqBkv/Wom4xlcU4K8FtGuYQIIOVhWO5ccoFIxYwjLWWrq5kVKYs2Vp05Vi9vEY1FYvVCrQm5sAw9/zql7/AzxPZz9zdvOW//PVf8d/+o/+G3/v8M5KfidPAYfvA/vGR/W5P8J7K1ex2e/7n/+l/QivDYX8UEIYTK+FPf/4LjLFsLi/RVc0YIv/uL/6CmBK77VZQuiGUGEsJnemamqRhijP323smP/LFl5/zwQevePHyGev1is8//4TlckFVG6Zp4ri/JaaAMTLSNRacjmhm4ig53rWrsNrixwMxJh4eH+mHge/fvMW5mlcffIirapqmwVUNrmkZZ8/kPY2rcVqxWbSsuoambuVChhzOts7MPnPYR7b7PTd3t/zs57/g57/4JdvDgX6c6McDIWWUrUFbdNOV8bXjlKqG0ehCONNaoYoKWgUkPKNcVPI8lGyGiTiN5MNOhD/zSDaWrB1d24nlyAlnPk1b1DwVcallqSt8yvSHnnme2Q09pmpYdJ38uUPg/PqSbtkyRykKNw93+BSpxqXoGFpHB3S1FEebfRlHwzSP+NljvVhpdQlJOWvF8mi6Cm0EviQJf8JJCDFyd3/PdtgLJjUE4rQgGyPFNyU6HyS21NYyek7looTGp0zOUdLiYiJFDxl8US2bmAtOv4y1EfytLiKo0/JPxKTpqVgIBEiEU+SAzgGrI2EeGfePLFdrlqsN9/f3HIYjuW1QKnOxWhBqy/7+hhhm3HqJjp6hPxKmnvl4IE0DcRxIzpKspgsdLiWMc8L1cA1KaTaxsCISVFXNarV8stqN48A0TUwRhjmwf/OOnMRTTZYwmpQit7u3T5cBciZrWwSiiYS4KHSBEclIP3LY7SWXvq6xztEul3LxPN0cI5iksNmwXqyp64btXs617f6RFDNN3VBXFavlUi5HKQs9cY74fmAaRvr9AT/PqMHjrGNujpJdX9uydUhYq6grQ9/v5QJqhA//VGCtLdAvcYrgGslCcC2uakpXLw3OCc9rncUZg1fqac31W07cf/uCrpM8HA6hRI3HPdkYcuUIyA7YGk1TVYR5ok+Z/cOjIFenUG4roqBsm5rlomOzWdF1FUpn5jAyzZ7DsOUw7GnrDZlaWLkhM+6PzMdeYjJ9ZB4njNIsl0uUUgzjQLdccO2uaRYNujaYyqJS4ng8sh323O7u6OOM61quzgJdvSSmACpjjey+UkzM08zN7T3HaURXtfgCqRkmzzfffQ85sd6c0y3X1O0CY4UGZ6zoAlarC7nATIE57Hj7ZkvbLnj+4hWurrh+fsX9g2LyQ6E3aUljSplhHCV9LiVQxa5WJB6qXM1zjtL1lcJuys7lhF3dbrccj8fSAYmIyWhL17WsVkvOz8/pChFvnjJhTuy3e6ZhZh5lv2+UwRlHZZ3AGLQoOrOKEhEJJSxBhDFGS4a5dDnygTbGkG2mqqonj+fJmz5NE/0wULUrrLXc3t1yGA7sHu4Yehl5x3ki+Ynt9pFxGIghyChqnthvH7m7ueHx7o6cpGuxWrLg53lGIZ+JTJY9qnMs12ucqySmtOuwVfW011xt1rLjn2emaaJq66cdl3OWtql59vwZL18+5+XLF1xenrNaLem6hspZjFEEPxPDTO0sySq0zrxHvib8OJDnSPYRHSNZG8aiexiHHj/N5XXTNE3z9LqhBJZyGt+dJiOn7s5qXfo5qQgmKxyK1kFua/JmTf/8muhn3t7d8bjfo3YHxskzZ5kikEo2/UnlnXMhkUlKmkU/Mc1PwRMmnxTQchCZslvvnJOIZWdKBz+hs8Vgaasa6yzjsqVxmslnUBpTNA9xOkKMOCKVTtSis0LlTKuh1RmTMz5lWkGqszAKaxWVM08jX0PGlBYv58QUNR5NCDLFMspgtWFpMpVVEq1bSGTaSDSqDzDPiUknfA6QPT4H6jCisnnahwuuxBCQlYAvxTgpRcolfOi0Zy76ptP5LJGmp46uvKW/eXqXv5mf/u9UM08HfYIUidkzzwM5BiorToPkJ1KYycEzjyKGOwkkc5kcJe8FvhLmcqa8126c8KMhBmYvVEKURttagDVORsYKK4W+XZbfewnaiom2W6CNZRqPomsqkx6tJZQFb8hKduGn10X206cwHtmYg0yRBJTjiopfMLsqFWW+KpNNrYVn4CPDQZ6r7cOjTOq2B/kvJNAJVFs0OjET50CaPdNxYBpH/DARfSCoGWUTU5CJRgi2THXFtTTXlnkeChZbOnH0e068Na5MGcpkUwqhPNe5iPgKs0A97eRPfyb1fvXyW3z91gXdxBGlBFAwzDN32x1Ra6KzVIs19WLNonKsVwvu7h45HHu+ff2a6CMff/ARbdOyXHY0ztI9u+Ly+pJPv/gIt6iwLvGwfeD+sOXt7bfshj3LVlGbJTq2MEf27+6YjgM2ZpgCh+2W68trXr54ycP+kTfvvufl5x+wutqwzQdm5XELzRwit6/vuNne88s3X+Fcze3uni8++pKz1ZkkKmlNU4ta208Th33PT3/2S+53e6J2dIslP/ry99kd9vz6P/wVn37yMX/6d/8OVWVwzkCWtDVXb1isLB9+vGCeJ25ubnl4eMP/+u/+nBcvXvKv/tW/4ur6ko8+fsVXX33FYTyQkQ52GkbCLIltcY4449DasD5bP1lIQpCx7zwNzGEuezUwVhjbL1+9ZBxG/vW//tfc39+LSr2Mb5bLBa9efsCnn37KRx99xNlmLapXHxh6z5vvvmf/uKdtOqy1LNsFiYQ5WeRUIkTP5MeS1CSag9nPrNfCqq/rBqVVCW5JMjY2VixPBY4QUqQfB+4fH3l3e8OzVYszmr/6zz9h8hP7hzvCPBOGnhQ8cRgY+555HCW1qbL0+y2H+1t+9td/zbu3b3n54gXLxYLaVuSCvM05czzuyUpY5Iv1ho8++wznKlxVs95saBfig3XOiWc1RvblJn9zc8PxeODt2zc4Z1l0LX/n7/wJf//v/SmQng5FpXJJeQsc9g+k5FkvW56SBlISL3Y/cDwcyXOEkIhW4kK3xyOzF1tkSpnaiQf7/OyMplvIpSiL7U9biXNEyYUvlb23QVS3sQCI4iwHvkuZVWXpLjas2oZPP/qQn331Fd+9e8evvv6Wh92e2/2RGAMpSAqaqUTMORebj8oRayxZOVSK6JyxWmGVwSkjIr8i1rIpUmlFt1xiNFRGEvf6ucdEsClz1q7olg2L+oI5RI7HmTkEHvsB7wfC4Q6UltAkB10Fo4JRKzYm06rEpCJBB6hEILVeyIWt7RqJyXWuFPRMCoEUPJPN+Nlwc/OOcRxZr9bUVnFuE02juL5ccgJ/6FP61pjp8WQd0UzUeWLOARuiiKPKhUpbQ1CJPmmmJJ191JqkBViVM8QsItuUhFudcsm+Loe5FgqOFO98quX56UdVxu2cCp8smmVCEgPBj+wPD9RWsW4aYgqMh0fCcCRPI8fHxGQtXS1NUpgnwjTgj3uIHpVmsTlSstkrcUmg8hP/XBtHXXuUrakqTd0tsMbRVguqqma5lIIunyBNStC0HZDZbu+Z5omxgLEUIhDzpYBFKACVXLIjNNpkTCoj56wwyoJRdPVClOumFLwQ0cpgS2iMtgZCYh4m+mNPiJE3726eAFfGGOLGk5dLzruVAHVCZOp7hkPPeOzx40QYZ3JITFMmGsNklLD0G0PMkXkeMFbRNLZchBJaN1SVfYJ+NVVNU9VF2CbduxR0jXB8BIkrUgCBTEVnhcugymVdV3/zkve7KOh/+MNPmeaZ729vGPqBu3evwTlM14l9Q2c0z+gqzdBYcnIsGkcwmkVbUdcGskdjaOtW8Ie1AiVjznHaMY6PoCeciyg1kbMlzgP4TGcdxkWCFTHJcXdgs1w/wW5wCl1ZAU5UkjC1nR45zEeCySJq6CpiTNxub+naBRevv+asOeesPsc5jcHw1Vffcf+45/HxwDAF6lWH0lYK0TRwc/eWqjF8/c05y+WC5aJjOB6Yx4Hb23cMY8+yWL7Wm2tcteSHPxpp25Z3tzeM88joxWe5ObtkLtQ1ZxfkmDCpxk8zfppJKXLs+/JhKerjIJxh2QmKanf2kxR9JDUqRtm8SIcnNKKzszNePH/Os+tLzs9XOFcxT5nd9sDu8YCfZmF7U4RxWQrEcX8oQimJxIkEbO1wlaNRLdZZcgY/z7i6QmVNCGUiUyw51rgnDvtpl+SqiqqpcbVQ0DrVYoMl+RE/W8boiSqjguXy4pxPXr3g4w8/oK0rHg97dvcPWKM5W6+52GzoFgucrci542//8R+htOHjTz4VfGjdcvnsGR9++qnkULuKqpZOse264iCQHeswDiUM58g8TxwOe4zR1M7y/PkzXO3w80gIM/1xTwwzRkcqZ/B+kJG0kq7XT0NxAkjYheyaIxRaVFYGUkSrTFuL1qJqOknEWywwzhXGAPiYqTtFbZ3c6lN+yjQ4RQ+XsPkirVAFhqjEHqNr6sby/PoSpRWTDzRdx5TfchxnhiipZMlWxCyRv0JTO6nbk0BwcqZyqpAWSzeRIjl4QvJYBQtnipdWOmxqTe2gsommUixqjTU1IWXqyjF7Sa8zRFaN4EO71YoQE1O/k2Qvo0n9nn7qhSZIZmHF67spWoaulYSzqnD7VQiMU8809JhpJs+BLky4FOj8iM2B6WYmWos97oojRIRwrqoFmzwH3HhgmQPLrgbVCO9fa+Kps9YwRridRbg2UFptpZ+6TsmLL+9RUYz/jb2o0u+78Pz++2Rdy/CUPpbLxOLkf88xUmnN8mzNsqm4WHZiqex7VMpFZGWl40Pey6Zy+OhE7Fm+dRY1vCmshtOKRWKCPf0w4GNE2xpXeSKKtu5YNGuU0oQQS0HPIvKqaqraCZxGwzRPsNP4eabvD6Kv8aFcWMqfMyWxiJlyWdSIEl+pQlw0qJVMDrSzQvrMSTQUrqxJJs/2YUtOCDrbzzw8PJbzp/DVMaiQOTZ7EXbOgXmcmIeRNAd0zFTKogzCNtHmaXoVvGifQN5H2YOnctmSi4oyMkVT5XJyin5O3kueSBFH6hjLZ6Go5wt2NsWE91HEe/x2grj/QwX9H/7pH/K43XL8t7fc3ux5880vsW1De35GlybQEcsnLFtD8DXOZA7LlhACm7UAR4bhiFaORbukazVNnZmYmeeZYbzn0N+i9ETVJLSS0fM8WypvWNU1dVLEamKePLv7By7PL9Bas1yt6OyKUGfGHKAW5ezd7QO76UCsMnSWetNy2B148+YtKWVMNPzoox9x9cEFlbJYZfjVr37JV19/x320ZFvRnjcY1+CT5zDsef3m18zhiHGJ66trri6vuXt3x/Zhy9u3bxnHkR988Tlnmw0ff/wB2iour645HPZ8+903mHeWr1+/5uXLV3zwwYccDgP9MFEb2VU2pmMaBu5v3zKOge1uK1AEoowTtXqyAPl5ws8TsaSrOe2eCr02mroSJO5yueL66oqPP/6YDz54yfNnZ0xDZjwm7m4euHt3i5qkmFtlRIwYJerx8f6ROXp8ChLHWhlWdk1VCW8gkTgeD0zTJPtRpYiTrANMwZlWzj0J9qyVB6ppG7rFgqarqdoK0zlSilidmceB7TwRjLCZX1xf87d//GN+8NmndE3F26Hn3ds3dFXD+tk1z59d07Ut4+Spm5p/8k/+Ma6qODu/IqbMcZzplks25xfYSvZucwjEFKnLgXP68vF9XO1J1VxMOux2jzxs75nmwOwH7h9uGPoj87SnrhyVU2WtlPF+Yr99ABJaZZxx1LaSrqpY5k57UaOgXbRy8Xj+grrpWK1WhJzpZ880B4YpoKylbloJ70jy7zh1Nac928nOpEsc64mz3XU1WBGdLldLsJbN45btMJG3e/bbA4GAMZaIYg5FAKYM0WhxnRRATWeqUqzKpCJ4sp+Zxh7tLItujSqFxlpFZQ11rXAusWhg2RmWWnCsoxdth8qeSieOy4qq7bi4uuD27oHX9ze0yyVtt2C3f2CYJjnMjeb5i2e0Tc15K+EXy66RdUBO5DmQ0gzDjvn+AT17TIisQyDlRO0VzJIMllKmrwQsU9VCwXN1A2V7XaXEOZnN6pymbWnaFm1kP55yJqTIfg7EhwEUPJa1BCfQSc6CzwUk01zGxb9RzTlFcJysoE/FPKX3zZmSIpITpe2P5BTI0VM3hpcXV1yul7y8OuftzS1vb25orGOaBDhFzgzHPTFH2rrGpkBf3iexSfIEVjFockRoaD7gM/icMaMlZIVzNbNPxGXm+vIFoIof/LQeNNRNy3K9FCV72wjEh0zfHxl2W6ZZgqFkJCH2OYMqIkr53J54Oho5zypXsegWQiRsaolEnUdO/4Zj3+OHgbu3N2wfttze3dIPA33fA3C2OaOuarRPpGFma1uZmMxebGqzxymD0wanLMZqGiOrr6wykSRTSpVQpkC/jJHVU4xPYl+dtIgKy5g9hAjag5pQJmG0kymNDkUcJxfzXM6GEJO4mMYJ/v9R0FddhdFLfvyjL1itO/bDgfXlBS8//ZTlxSWri0sWZ5fU7ZKH27ccHu45X9do3aERjvbhuKOjw1mR52utZc8x9fT9kb7fo1pD5TQpzISksHmNiZnjdk+aE5V1kJVwtfc7fvrzn/Hykw+4/vAFe3p8mtjujgx54thPDLPneJzxc6R1HdWmZl2f4aLjsD3yzr7DTZZFXmCj5fH+gWkY+PCTH2DbBUFrdPQct/dMhx1GRcI8sL2/YTzuuXnzPaT35J+6rnnx6gOury65uN4Qwszd4w1TDGSrSVrhc+J2+8gYE4+PRw6HgbZuhI41yaj5MAwEPzOXtzNlgUekKCpUP89FMS1jMjIc91v8PGOUpjKOOAXCFBgPE+vFhufXz+maFf0hME+RaRLPbd22LNYNzlgqI8K2cZ6IKjCEQbKbDSXTXjPpiEoz/SS335M4jyykr7Hv4Tdu2l3dyK38ODwJUi7PL6jahnePj7y+ecNxltGYKiPS/vGRpnJ8+OwZlxcXLLoFztWkBM+fv+RsfYZ1MtKXsARbstdBlcmEMcJidwv1lDSnyqjr5BAo0y58UZ+HEFAKKuuYfWQYjtRVxaLrsLXs4ava4VdLfPCl05dRXNVUKBLzsCeFCaNP79dMbVoq50hJk9BY22CMo7OnzrzFVjWLzQXKGI7FezvFKLjRtiEDwzhJMVASDax0LlnYFC2Fwhr75J+OMTJPE2FIBDIqJJZVxYuLC7qq5ptv3xB94OZxCzEXm4552icbW6Eoe/MIOouHXiMj3+w9c38kjD1+94ivHWsHKXr81KN0wuhU0sA0YZqY+yOHQUKYspL3qKstOdasulrcLvOIJbKoLC+uzrl+/pxff/Mt9/eByU+QZJ/eqoQaj6jkS1wyqBhI8wxjz0XtuHxxRQzShYaiVTn1xx8/v5aV1ziJxXKcsCZTWbHqxZjKbCrTqkirI7UKaGVorCrOvorGarajJ4SMnofyGikRGDwJ2ES5n5M4Dk4FXvzV5skOqnJCxxOj/dT5nbo9JSPiLBM7yeOORfuT2D6OpPGRYZrROTAcdxwOB7pOEsqIQS5fxwNhHNBW4m7TOAg3Q3xwcqCIqZwTQIgSgzvPQeJ16QkBtH4tn8VielcaYpwFoe0MRit8mIgxcDjsmaeRfrstjp2iTtf2vRVPFdW9lxTPylgqa3i+3rAowUdZwexnMArtrDD2U+a777/nsN0y5wk/BSrbYJc16/Ul2louLiSjQWt55lSzJHrPNL9/n03BGqaCFphniZL1aRZHRatxlaVeOOrasVp1zPPINA2ghPWfi0o9JEmQjCKmEAaFyiVORP3GWrQEGJVo6DEntvsdY98T/Py7t60tWktdL/jhl5+y2nQcxh3PP/yQH/7h32JzdcX66or7fc/2MPCf5gP99oZXH31K3bSSL+wn+uMeaxXOmoL0VMQYmaaRcegZ+iOLdkFlDSnMRIS6o2Om3x4gKdp2Sc4KVwX2xwMPvzqwen7Ox8sF+2HC+8Rjf+QQjvTzzBgCwzATYqKpWqq2Ynm9Zn+z4+7bW27CDWkfWKolLlXsto/M48irZ89o12u+u7klRM9x+8jU77EqEf3A9uGWGGQscn5+zXKxAQWuqnj+4gUvXjynWRr64cgUPXMKooxVQt162O+4edxxf39gt+tZtC21c9RaRpV+Hkkx4FUmKZ6gJ/M44OeJaRzQBeVZFSXybr9n6iVRzlnHsT+WHfmAf/URVxfXtPWC4RhKklTJSW9azs7PaKpK4ilDZNyORB2ZwkjIEeVsUT0rJp2IaeZhOLAfjnRdS+UqIKES7IcjhEStrVisoozkx2Ekx0ztas42lsV6xS//46/56s233G0f8MGzbBo04IeBy7MzLi8uOT87p207GaknxfX1c1bLBRhTxtZyWIZxIiuFWyxEYNj3KG0wVSOnjNIl8lsCecpEVAp6wdh679FaY61h9hMP2weWywVN12AqR2fFEplTZBgkLjTOAyjRDJAj/X4ixgmjApmZFHoUlrrK+GQI2eDqFutqFss11jm0rTBVRbveEGPi8LgrdDGoKgHKpKQYx4mqErSyYEIVqoz/BA0rwlSJTA0EL4Ko0QsT2zYLFlXNs7Mzlk3LxWrFMAzidY8yOsfIOFNWI/apG5TuFwyCT1dFVOWHnrk/cHi4IzQVw7Ii+Jmh32GNonKKpnaotiZOI5PWPNw9Ms2eqm6xzrHaXKCaimVbLJR+xBBZ1JbnF2d89tEr+u0j02FH9pGcE61OtDrD1EPymNaWi4aHeSaPA5vVirPV6omFfbKvzbNkDZydnRFj5O7ujuOx5+27dxgDlRUfdEhB1k050+pIpxKVKq+FLcjj2lFZxd1gOA4Z3Q+C9FWGnI3M5KWFLJjX96PpFBNaAzEWwZQAdSgQmxzT+4mROtmXZBqTCzwn5zKinSZ2vWd/N4gzwtVMw57d9p7Kapk6RE8KnvF4IHrZJ6uoSSE8bb+loKcyni9WrLIDzkmS5FSEEEbGMTAORVAJhR6qiGkmRk+Ks2hNypOWQyBGz3DYAYKHFsSzEWdeUXvnKFjv5D3WWBpjuV6t2azWXFxckFLkbnuPrRyLs410tCFweNxCSPgwk1C0qxWurmmWa1xdc3n9DKU1x2EUN069IOcJr+YCD81U2ok7I4ulOHlZbU5+AAvNosU5w3K1oG1q1usFw2DISEJhiJ4cIklpCVfJxa5Y3i9Zu6gn4Jcxct5Er943F9GzP+457vdMQ/+7Z7n7KMkx337zNf008Or5OVcXHWddRsct4+PIzevveXd7T+zf0JmepZM3427/QMqKTz76mLPzCz748DN0Zej7REqOplpR2RarKvr9wDAMXF19yEI3/Pq/fEV4nHn41R2LbsGXv38uO20ytmtwywW7eeAv/8tfExtNshCSIkdL/xDwWfHp9Q+Fq6s0la1YtisOmx333R2/+s+/4H/+9/8Lr85fctadseiExHXzzS9Aa4ZZMq43Z0uUSXx0fkZIgTAeCfPMNM28Gw7cWsezF69YLM/YHW9Qd55w5wkp0qwX2GVDc77i2IsgzMfMHBO5rWisYRgnDuNEY2TPFYN0vrqqim/V4aeR4zwwA2NKOMChUElUocHDNAa+/fo14zCQQqRrOj778HOebZ4xHWZ2dwfeVrd0yyXtsgOlqTuPahTBBHkA68xqscSOlo/Nx4zR00fP0c/cjj3TeGAaI/u+p59H8lF2hperMxZNw+cfvKLShnwQdsB3370VwlYWv2acZ7rNiuVyyfOzK6ZpZPdwz3AcuH/YUlcVP/riSz589Yo/+aO/w8XZGR+8fMGyXdAsltimBds8iYhCEo98NhVKCbE8qUy2EuWaUkabjDZFYFMOxpwyES8/r0/8bYBEjAPoxGIl6Vj9ND157k0RqrTrS3Atw+GB6Cf2/YEYRob+AGlCpyNWB9rO01QzRo3QnmPbFdquwdSMxqHRkCw2GswsY9w5a+YYpIAn6IwrjHgJwPDBk4ptCNSTkOgktslABLGxWYsNRU3/eI8PmSmCD4lPr67YNC27xyOPx56bfmSOM3NMmChJWqci3tiKxhjqFLE+0WpBzNJ2zDmi2hprFcPcM489u+09XdOgu5YwB+IYGA8jOSi6qqGtWrSryUpx2B+IBUq0Pxx5/eYdbdtyfX1BihNvvvuG4/6e5Hsu1jLtOF82GK14uL8jW4taWFIMDIcDYRqZjz0Xy5bryzMJ80iR3X6P94nFUsSFY5A44uN8YIwj2WZUBa4xNEYgNK5EaF5dSr6B6C6E058B72fc7oB921PHxAaYgApDSJqQ5OKZlaFbtkXUKNObYdoJqyAUQdpJKRezjHz16UKgf0N1Lmu1MPUYlXCtIsWZu4cb4vaO+e23PP/0c559+hkXZw11dc5wOLDdP+K0pSaTrCEExXEcUcHTaCdOhxSehJy5+LqT0nJhbSXnYOg9qEjT1eAj++O2pC22BD8xhxljEsYkOmdw2qH8hMoJa2X9sFy0hV0Ry97Yl81CyRHXFmsQEVz0LJPj73z6Kc+vrtEKhmlA99Ll5/2WSst08fc/+YyPXnzIEDNTApqWpC13hx6fYa5W1F3HF3/wEXXTsFqsOR723L19x8O7d9y9ecMYE84HltZSG4fNAZIh5Rl0IsSZrqr56KOXmJI1MYaRMciULyIMFa01pmpwTUe3XIsmJoubqnZWLj5lXZqix1jNct3JAiZnzp9dsNwsni5Lv9OCHmNimmfu729BZTbLllXraGzEh54p7Nndveb+7RvSvMWpQKUDGs/UH1Cm5uL8gvPLKxGDpcB+7kEbGYvoGqMc4ziS8NhrQ6Udd7cPDLdHHt89Es8SErCBvChdx/LijEOYuHv3hvpsiW0rgsmkpPFDJmnN5fI5dV1TWUflKpbNkoPe04UFP/uLn/Grn3+N+kARzxPPrp9RVw3v3t0we4/SmqqpcKsKrTIXi5Z+6HkY9qRpwo8jU5Bu6vL6HGvX9OMO9pH92KO0Znm2wWpNpTqC1oTtjpnAmCKqMtjKcZgGxjARs8EoiCmiFNTGUVgEpBSYlWJScmCI9EmRspbCFSH4xMPDI8PxiEHjVMX1+TXrbkMYI0M/sdseJRXPVqQGtDNgJoIOROVBQdt26E5xySX9PJP7I8f9jm0/sJ8ndn6inydJGhonUkyMZM7zih9tlixsQ+BImCPb7QGrFK2rCV5EfVYbFk3Huluw6RbYrMB7xsMR08GziytePX/Fxx9+wvnZGc+fXWO1pOYZV5O1e//ZTJGYZWyHktcjUzytWdLkThbVp2fj1KHnUEQ8JcDEnCwkARRUdQUoJi+pYDkL4MRgcM2SrB0hiN3s2D8Q5gnvJ1SesHnE6URTJSrrUcpjrSGbTr51w2nrqLImJsUc5dIQEAb4OEvokQ0RV0lx9nMoKF3Z2Vljn4AVoJ6U0wI0KRALQKWE73v6YSQkQ8qai+WSxtVcbzYoNPfHAVVGzQDJ2gKdUbjK0FQVdhjQIVEbCQ0KrsJWNVPlUCrhw8Q4j/TDEaMVXV2TQyIHsbBqPE0R/WErYkrsD1uyUjRNy/HY0x/2NE3NerUgxsD28YFpPJLixKJZ0rUti1rcFHE4oKwBv5Hx6XGHnyamY49WieWiZfIzPgSOR/AkXG1RSrHvj0x+Yg4TIQeUA1MpXG2o6oqmbmiLZ/ny8ozFomXRLcRfbMUzfTgcGP2Ew1OTWGjQzJBnpqxRyZB0RdaKurICOgkQQmIYvez6wyxjdYpNL4ExNRXibZddEqWgi3gq+4lskJjfFOj7LdP9W4Zvf8nmYoXmA7rWYk3H8eGR4dBTLVaykivBK8p7iBGrJCciJ0mfTEEAYgklwSwKFAalLLOfyGRcJTHHx36iaTKuaRi9p5966gqqDIuqwTmDihkVE7US+3JbO0KMDJMo6L3wcOUSoTW2ZFWgFTWZTsHHV5d8+Pw509izP8Ct1uX88RhXY41jdXFJtVizD5khZWbb4NFM37/lOHmia1DtmquPv6BpO1nlbbeM2bIdPMO7O6YwY3zCGV3YDKBUJEctdrUsjInzizUZEfsprfAxPDkfktJivbMO4ypc02KtI4eALtoiUMUyqkqoWUNduyeRYrdakLrmKbntd1rQt/sHjv1BBAE5MOcDPh0ZwpY5euY4881333Nz98Dd3ZFxSriqBd3w5rt32Krj+QdfYN3A7e0O29TU3QZsJLvE2frAHBLp8Tv6cc+bb284mJbf+70/IPeJvw5/RUqZn3/1S3xOHP3E5cvnvGod3mSihq+++pr92NNsFri65uXlKxm3hBoVFSEHMDBWR2LvcdHQ6JrOdUK304owz+icWTSGrhJriasMnQUfMkPyEISG5UdR0I7e42PiuL9l2yh+/ouEdo5dL1ziz370Q7S1EtKQE5tn1zw8btlOD2KzMBoah1aJbrnCGc1++yhvrDWgZSzjcmaxWNG1HXm1wcaETYn+ccfxKGO29VrzwcuP8dNEY2suzy/57PMvuX72jLZb0NQttauZR8/du0duH2849DvOrxuqRvGwuyXmyGK5wjU1m5eXmHHk9s3A2+/u+LO//Hdsx5HHaQBbyEnFD3rYHeiqmnCYeHV5zT//r/5bhvNzHm/vaa3jcrmmdo7GVRynnmEaUSGhQ+bZ5pxNt+DTTz7m2fU1/90//WdcXlzwwasPcdbijCQuVZUUmATEKCPLJ6qfKgAOvOAjQ9mLZTlMdIhPPl/nVImGLLPQ37AKpSeqnWjYchZSYCrJdFGJeGcMEsWdsGBq6m6FqywmH8lBEYedoHnHiZw0UJGzL8Q2C7kiZfk9NY2IsZSu0DljbKJSlpU2whbPmWmaS6Et400rlCujZPw+zSIYS/H9vjhH6YDiPELypGkkjj0xCjxmxpIT/P7nn3G7O3B3OLAbRo7jgDYKpxCWesr4PjKOQlnTKWG7ikop7GKBdwoTzwjJM6WRmCLHaWTRLWjrtlzaK2KIzHnm8uoZ3WKJLUXg7c0dwzhyfHtLIvPyxQtWJdd+v9/RH/fMwxE/9uSwRGVDmgfRPcwDfkx8981XwiEYes7Pzvj0B59zfrbGB3ErHPuBw3Ev1LAs66bJzyQym/MNSmuME4Rp0zRUTsKHmqrCWUvbNDhn0Qh5TSxFcLZsQK358RcfcHGY4O7A/RB51z9wmCDPYNsNWreEMchK5c1rwtQTxwe0szRXZ1K05xmnDbV2sjYIB8bBE3yiXYo7xVlF1ImjmXFOcdaIC+cYjnjtoXPc3L1l+Iv/leViQ113aD/icqDfPoibJSRUDLR1JeP+4PHJM84jbV2zWp0zDCPTPJfkOUU/zyiToKohQ3/spWhVDbiaZBwpeZLW+BwhSjZ5DqDGAR1DcdK8TxiM3qOMpm1q0AZK+EptHegR5QM/fPEhz88vOGs7akTH4XOiDh6VE5U1Iv4EdEqYkKgwYDTrswuoW/TynCFEdhmyNrx72GMOI3U70h/23O2OPI4zYwKbFRbDlEU3kkNGp0xOYKxmsaxoGsccBkIIHA49x/7A7D22qjDOoYyFInwTlHAoJDz9HjxTJoXvGw1ZSySEqBlJYhfOoaw8focF3ReRg4hbJZM4D4FwPzKHmSlMHPaPTNOB4CdiyAz9kayD0Ha0RHWmrJiniLLQmBpMIptEUy3o2jX18QE/z0xDwFnP2atL7Erz3cV3jOPEME/MKXL0E90s/zs5TbJa8J67LWutaBLUpqZ2LXkWNbD3Aas1uICfPPMwo5KiqRshilkrL2eKVPZETS7QmZJRS7GK5RQL1tMTw0wIkWkaGIcDeSuFbt8P1G1HP/Ro5wRTayyubtCVA6PFVqQV2Wgp3tYIWhcRwtmTdktrjDZY61BZ4Bc2inhm0j1Kaaq6AeM4P78kek9XtVycXXB5dcl6c1aEYRKFGX2kDwPbh0ce9/co29F0ht1hS8yBkCNtXrBx12QPQ5h43G95/f1r6dDnGds02LrC2RqrLWqOTGbga6/JPqKcoeoaFuslratZrzYsmpZVu+Dm/oYQA21ds2hari4uySR+9IMf8uLFC374gx+U4JhO7CzxfZRszrLLE35zftqDS0ZDhiiwhpRPEbOn2MPyK1XGGFf20CVoQYbwRWFcPLFPPypiEvNIQljPWWV8kO+Y5UaubYVSkaquScrDZIodJReBVRQkpRZfrUKL2CXD6ZiLZYwuDYuwwCkdd4jxqeNWxfGglCoC9xLSk0743kQMJWUtnvCsEv6SQyCFgqwmY7Tl6uwcZSzLpmGOAT2UYJQcizVNnouAEm93zqhoMEaCOAwVbdMwB8VclOixMPj1af+aBfaRk8yWTkAkDcQg58TxeKSqa1ZnG9qmwSpFLgEzMXhyjCLSQ3DNp3FtjJHjoai1U6SuHJdXF7St8LV98MzzRIihWIg8aFUmYTIZsM7SLgRX7ZwTe5NzNJVcJp0V7r6o/QUXq4s2o60t58uOGcXVNBNiz+44MIaEniWGVmtF8PL6+ccbwnCEeSurivO2OAYmnHU0GsmbiDDPI0wBXVmMkojPpDKT8lgUtaqwOhGtgsoSu5YwzzzcvBMh4xIIAZ0T0zRDzDRaAmSsERobST7/MQkoylYONfsS0CL7fp8iWmtct5BqNHihDHYrqrqialqCiug0ojJick3iNVfeo2MglHAX+dyK/VIVCAslvdOUCF/txKZ2fXXFy6tnNFWFUfL7MVmKV0bWFKdHX2cwOeO0ImtDW9XopuXMNTRi/GaKiV0/ooxnipnhOHCcJiYfiBR8rJJnPipK0I3oCQxCf9NGEaJ/SqD0wReRn+gIUKfA4vfIX0EP2ydx42lc+P5/F2VFfo8ROuka1O9aFHd2vWEZFtRrRz8euHt8w/3DHV//6leyU06BdrXm2YvnrC8sPmj6yZGy44//5O+y3Fzx4z/+U4zriLrGNQ11vWJOgoNdNBcY29A0HeN8xPpIrSx6uaIxNf/1//DPCCE8xavuhyPHceB+eyfF0Gg23ZKz9Zr1xTnGGl7/4iu899RtwzTNfP/99yiU2KjGif4wQEz86Msvuby4YLkQxWNOidrZAic5MEfP3faeefZs97syigdnZQQ5zTMpeh4fHwgp8rxpqZpWVPwx8Pq770BrQlbUbcfy/IK6bfj400/YHo4c+oEpeo5Dz9u3b8SOduwxSvH8/JxF3bA438AcMMPM1PeM+z3LtmXRNHzx0ccsmg4/TcQY+eIHP4AMzjrW6w0//oM/KtnfLc44UIr+2NMfer7/9Tfc3L3hP/3774l54sd/+/fo1gtuh1vUwyNvdzve3N3xb/78z/nqZz/jV//zn2EuznGXVyxdR6dq5l7sM826RofIf/jZn/P16udcn214efWMH//4B1RoqgjLqmFTdXRdzavn13zyxYdMaWZKMuo/22yo65qz9QalFNMwFF9mZB4tU+WeCsFJpn5KnwslKtHHUOAc6skClKIcLqW5lXhDo8nZkLMW/nOGGLRgTIMq/65iTYqnhzPLAauk+MzzRBil+22MxuqGs7MX6Dyhz1ck3xPHe7xXjCNUuuxks0FnIaWlFJliz5ATb6bvReQE1HXNZrN+QkPaSuhzseRYex/KIZyKP/bEyZcjmCwCI4M4JHIIeD8zzyPHw0SIcPXqI+puSXv1nMvxnO3Y8/rmhuEnPxEE7uMNtatoq5o0TkyzxxTl90BHtobaRFRWtE2H9pohjoKtbZdkpdn3A7OP7PcHsW9pzZQSrq459qOQA6NkuJ+tN9RNw3qzwfuZ+9s7bm9vuHu4L/7pmtVyxWq1JMUgSNVycUtkzs7O+OLzz3h+dc0nH30oIriYaFvRQNRNJeLHWNTuMaCtYblelRCj5ilIKIVMQNZilTNPueyVkdVPU9XEGHm83zEcj4z7W1qj+f0PFjS6Z9pvmYc9h/sjfr9G2YaII4VIfvtLGI7gD+S2ItajcOdTZNEtuVieiV3PdezrzDjCHLakKZMDJBI5HbBGYbcVV13DZ3/yx4RhYNw98p//y8/5zz/9BX3Q5MNICJBiZjqOkBXdeoMyco8UhbjHk8Ba+nlkuh9JxpIaSzYWlCYZg2tb/ugf/ANWm3PWyzOsrqhtV0KIZu7u3/Hm3Tf0hweG4xY19Xg/ESOokKUgKqiMJmPAKnzO9MdREgLNTG09tZ15dX7B5XLN3/rTv8dnrz5kY2tMTPT7PRnNxeaCcZ7Y9gfhc0yZru5YVBanK7y28rmfJ1Z1R6sNtnbs+pFvvvmamDPG1SUrYk8ceioUldJUKqOjZMbHaSaniCaKnCHLCnoYhie6ZAgln/3UEMQggrjiFDg1I8aK2FSXgp5PzoXCJfhNBsHpO8b4ux+5V02DiZGlTmin6Ocd1XAskX8CPqnqtozRakLUpF0mZku3WLJYLGm7JcY2+OywTjyFyUfmOONsjbKKkCecs5gQcUqjnEVZx2LRyY2/d1TeY8aavN1ymEcZTURRvpI0afaQEsftjnGasAfZzd+8eQsZKufws2caJlaLJctuQVPX1HXFjBz+J3BGTFGgI3GWDPNpksIApUsSfjZA8PLzx8MRHyKh8DfmaQJtCBkwFjtNVE1DXdWlk0mSjWw1c7nxRe8xQH84kmdPpyB7CalJ00z2AWwEK/uvyjlISfZPzqJQWFvTrVc0y65AGezT1OG0pyElVMr4cSbEkXmcsM5yiJ6gwB8PfHdzwze//jV3NzeEacbFTKUMFRqXpctNGZhDSTwaqK1lLKlI7bLDZYWZo4wxncNZRUoVre0IOpGNXFirEoVqT3Q5Ik9hFVk8sbkUdLHJKGwJ/HhfvEtBE53u3wR1nEbr6X3Uo3BTCpozKemMnqAtv/EjBeHJKba2wF1OLh9KWIRrscpS1RAny5RmQvQigCmhZaJ0ldeeBGEOhBjYbR9JOUsWes6k5fLpGXw/ochPITw5iQ9aHvzTZCI9dfWqrByS96RpEiiRDwU1DNZoKmewGiqrOV8tOA5Hlk3FcUzimjAag5WOOMxPjj+ZVCHeHvJ7q5s2WFsJOVBp0R8U1T3aoJTm4fERbS273YGUs4yTq5q6kjG31YY5ymfJl0t2U8vPtU1LXdUMQwQUVV2TU6SylsVyweXVFeuzM5q2ZRwGybVO8u5pI3HJaFWwqwZtLU1TPwFVyEooZFr4A6rsc09ipRP6VhtVhhdyodUIKa9qNKsaFjZSM2F8L58TPYKqUSnj0owioIiYHHFxwmpFRaYh0OrIulKsmooqeEad2B89cxFeyZXPC7PeJ1a25dMXL4jTyLBacvPmhlprVAiEcRS7ZKao2SHliC6/91TAUUnJ9Cil9P4M1BrtLMo5FssV3WrF9auXbM4vOT+7xpmKWrUFuTzRLBpso9k/LjjuF0y7e8LQM4RZ1mQhQoJT9EwEQoI5phKDq9EpyYrMVTSLBYv1muVmg/UZZo8qk8q2aQCBx+QkxB2DojKmRL6KsDT5GWUr0cikhIqeMA6ElJ40PXGeUClKdrzW2JzFOlimgzklwV8nniKoQ/DEmP8GJEjOm0RMJ+VtUbSfplEn9Kt6P6l46tD/t2fV6d/5G3/9v/f12xf0xbkUNluh6w7dNGyuX/Hio09lhx58GTFoJm8I0XBxVTN7xbdve0LesdttWSw1Z5eX1F1Lu15xGC3qGInakFSNrSJzrKhLag/ZMabE8XgvY/OYMFbTXWyoN0uuXr3g4fGBx+2WP/uzP+PrX3/Ni1ev6BYdGU3wgXc3N0zTxOF4lLGM1lSVo64bjjHip5HVaslyuaRpa3JKbLePJYL0UcZ13hNiYBhHeXOKzaKyjto5YgyonJjHgX//7/4tIcPHX37J+uyci2fPUdbJdtd73r17h61rbFOz70f6aWJ1tub86pJFUzP1A/N+z3Ts+ebnv8QPA3++3bHuOj68umbVdVwuVxAT/jDw7eFrKMUGrXCNoGDbdoEncX/c0lQNXdVhlMZhqZqKrmmwNvHixSWu/iE5e372659yc3vLzTSwn0a+eveG27s7fvrXP6FZrfjoj/6Ytl2waFfkmMl95HK1xhjLr371K8Zx4tWzZ3z88cf803/8jzlbrgTUgKKtazpT0ZkKrWu0godhRwgBV0k4hk7I6JEorO3NukAbMtMkhL3J+2LjkELvTuSuAtwR5rTCWPf04JySq07JTSEAOXKCa+fTqLsU8BBLdnVSElSCeir+sk8H62qMdXgFOXlyPLHjNZWDdXuOH/do7G+QEEFlD3GUCF2t0WgOw5Hj0PPNL35FBpabNeHMs16unqh6TS0CmXGe8FlWSDJCTiKs05LgdcpdnuaJ7ANxnJgPe+bDAV8Qw1pZautwOqHizLtvv2JOmWWleLZp+fLDZ9zePxDHPVWeqQKkNAGeVVXTWVs6IYWKcykMGYXBNR0r46jqhuN2y939A00le1FjHEopvn93y+w9u/0B52r+4A//kK5ZcL7ekIF5GDjsdtzf3FLVFS+fPefVq5dszjZUtRxbNzcereEHP/hBwSNrLi4u+PSLLzCIT/nu4YHbmxuGYcDPntVmJermzRrnHItlV/jtmnEcub27pW0aLi/OJOUxeIzK5Dgx+AHIxKYIbA3lEh2oHVyedbLztDPP28xwVuHvM97N3O+ODGPCdmdUtqK9PkdxjlYzxmi6RUVtLYvK0diKzlmerRdcnl0wrTr87Pn2u9ccjp6oIlklsjOyPmLmy8s1/5d//N8wDSPb+0fMFBjut9w+7NgdB3wU62uOGZRmHI/kGDje38nVt7ZCP1NZgtKNkefDR9rLSxYXl/x3/+P/yMtXH9BuLqiqhvXqEqscLoveYNF2oANKBQ77e4bjI9/8/Kfcv/2en/7lv+fx5h1333wj78UkoBftLDHDnBNNV7FYrCBDyFCtN3SX13jrOMZIrR2u0pxfXRPmEWc0h8OBMAemEOlnz9I5VlWDU4YJxXDY0cfEXO/wSnM/jhynGYY9xIhHLvc2ZCoFuquxwWJiguNInj05iC1QmYzPgZu3O6a54+LZEusquhIg5JwI2uZ5LmAmKdzOWpq6xlV1mVCVUTs8deqqZDb8fyvov61l7f9QQR9GUSGiG4w11A1kXYkM388oLx5gyQSuiNngY83sYdUbTLXAGo1zWhCNlUHrSE6eGEayjaAjSkkWdl0LuS1NoqQMRSgwRY9TwmoWZoN0M3VdsV6tuDg7R+WMHyeMceQQyUHGjdlHjNFU1kLKTOP4FOu5fXyEDNZJoT4cDxLU4SdCkB1cjKIuVrl0aIXYJbd2JYQlramrCptzESZ5pnFC2ciM7HWwjnGaCNPIrh/ox5EYA3VVEWMouccC8JCoyyCRgVZ2iAaorSOr+PQBCiGQtRR0HaXd9cEzzhO7/Z658oQ6YNBYDMu6Y9G0uMrS5BZbBRKWxXpNtIp3tyOTD9zdP/C43TH5QJUVtqpFkT15AWKgRNhG4my5guWKH/zgB3z44Ydslku5NCTJva7QOCWgCRlNvd+LB+/JHqyWAAZVKXnQp7lcdOWfMaVDle5TlaLO018ppd4/JE/F/H13K5AM4UyHLAlLou7lfaf+G8Ub3o/2KY+h7OV5H39Y1eRkyHNEqSSd/mlXqBuMXeBcpKoCWlliyBLmkzymqsV7rCQCN8VUpg6FS62KdsLIdEUEe2WU93RJKR2CKq9rSsQYZO88zfh+II6jhMdEGRFUlfDKDfkpytXpTKMUrTOs2oqDVeCncsHK6OhROeI0onBXMtKfp4kQPYMf8TkwZinwGUWImWn2AlnJChPlHOl7yQGIUexN0zhhbc9+J/7kkCIpRBZti6sctqro2o5l12ErSybTNA0hGJq2AYUw/JVMKOZpYjgceNxu2R8OT6/XqRs6aSty0VUYo3HO0tQVTVPR1E5gSjpjrUbrk1UwMqtECjO1M+X1lme2axw+BUgTtcosnWbhDAurOWbxtNuUMDlTVbWku9kGYxSLRlTzq7oSUZxxdNbRlX1+QHHWtlQkfNKyn9YzqITGsHSWZeVgnMB7nNYs6pqdkeQ2UypIPtk9iGQSJypVzmXCSRKxpbWsViu6ruPsw49ZXV7zyaef8uzlS2zTYV3FcrHBYDHRyei96iSe1iSaxuI3C3ScON8sUH5ke/uMN92Cse9lbJ7FwjbHSD9PuKalWS6k0KE4u7zi/OoaW9dkbQhBJlq5XB6N1iJWrGqUCiSU2N2UjPUTEpxjUiTPEzFn+u2OwXscYlNNJ5+/EsGbK/G3hkhQBbqa1WkIJQ3D0OMahfdCVjzlZZxshU+jd/JTHOqpO89K8ZvQ39MZpdX7KWR5q57OsXRK9Pktvn7rgv71r49UdcXVs0u0hbbyRPYwOFLqibGnbhtcXVO3a7StGCcRFly/bFCmoltvWCyXPH+xYQozu+GB4/EdDw/fY2uFdpDUgNaR9fqFBKm8ORJSgsrg58jjdk/lHEEnxn6g3x+p64rVesV/98/+KSrD//Jv/xdubm6IUcQrl8sVk63Ik6frFrx49ZK3797xq6+/om5qqrrm7Zs3pJxZrpa4ymFsSbspb5QuPN6cAjFm4pQk1zfK6NMBbVXRdh0fffIpylq+v7snDCNvv3tN0poxw+r8gucff8Lrt2/5+vVr7h637I5HqhJu/8mzZyyqirQ/kKaZddsSjSFpS1fVtK5mUbWs2g6j5fe13W8Zx4GAAFOs1YXXPRH3j/yXX/yMylQ0VVNShjIfvfyAD168BJ2xTcV+OBCZ+fHf/bsEEg//5t+wnQNvb+44jiNufY5pFiSf2fdb7o8DF+tzlt2S8X6Hc5Z/8vf/IR988Ip//n/6pyyXSw7jhNOaTRm5V0nhYsaEzDD0zOOAaSpaV/Htu+8Zp5GubXHOsVmtmVLicOjRSuGMcNdXyyU+BkmEM/Y3Ru8QCzbTVpV8/JV+f3CXcamcYOLZTyGWB/XkPz9dAPST0O6kQpWHT6PQBC/JgIvFoiiiWxQJ31tIgTnNEGCYNTorXGtZ5TOcGzjuI/1RlNlKB6ozJwEXribXia7uMNby/Oo53XJJ13RUTU3dtkzzJB1JksvtqRDpJ3FcIcMFzzQObB8eJHBit6NWikYV+5oxXJ2f0bUdEFFx5uXZmqgUD2OPTo4X65bDbWR+fIdyFcbV1BgqpVmajpXTOBLZBx7ubuiHnnePDwQS3oKxEjO53x/ZHXp8HaltfLLTHY89KWUuLi5wruLdu3eodzf86he/wjpH07V8+OEH/OHv/T7DNDJOE6vFgq5pWawW5bnMeD8TcpBY5ttHQoxs1ivub2759a++Kre0zOXlBauVhAhZaznsd2Qy49jTNBVX11d0bc3Z5uMi9NOSRhbC06h9O+6Yx57hIMmTU78tqWFS9K8v1vTDgbu7RxYqct06douGsOpI+4ibMhaFwXC+2FDVNculBMp0taO2hlVdSapdzCzcgi4qsq6gcqxevCTGwDAf8GHi8XhDJlJXiqvKkvZ7Hr//np/9p7/meHvLqqp4NIZGgascSWuSls92EGUi9dmC6GemwwFSgOSpuzO6iwv+4T/6R/z4D/8Wrz7+nM35Bc8/+Ih2saBetvL+VlI186wYetjeK2L2eB9Zr85YtFf8/pcfUtlE2P8P+HHizS+/oj8cuHnzlnmeOYw9+8OB12/eMkXPED11VVG7ir/15Y/48PkLzl2FQnG428E4kx4eUTHgYsApw9X6jDkmhhCwTY2NkcbKpXhlNSYn5qlnGEfefvVLfIb185ckDMdZwlG0MtSmkoCncSKPgaGf8KpczpNCaVn5PWzvSHlmGAask8Aka0sp/Y3zxGhNU9d0TYstl/NTc5DKepRSuP9Go3IS4Cm5SIYUiuD3d1jQ+8Ezh4x+FNqbdaLEbbs1tqppYlfCA8ouMsoBqJWWG1X29Ic9SinmqWf2E9NwlO/+QMoGlzVzOpJUEKqcmxmnEe8zORqil11PSBLnl3JCF+KcUhSbTpKUGmNkV6MRu0nBgFbFglJXospVWj3Ro1LO0tWkSFUXq5i2vN/FPrVxRfH+fgedycJWjklGi5UUKp/zU+ykvKnqbwQRaKOx1lI7Jzf0rmPhKh7vH0nTjNOapm5puyWNsayqmrqp0fq0c0lM48jxeMRUTm7XSg75GBNh9uwetxhtcLZCy+qW9XrNhT/HGIXS4DX4lHn3+MDgJ75795aH/Y7zy0sujWV1fi7oypB4CHf0j3tyyhilub66YrNe89knn0jyWbugdhXzJHGED4cbLIpWWbQPqMkXBGbEqAhJUKVG66doVu+9WJymSTrVSgn1bJ6ZvaxATmlusXRZ2spkwhpDVqeoSikgoNAql85bPe3QVZlmPfXfJ8XsUxU/FfrTgF8ALjLiF7oaRZmAsjJly7JkLlZujFYSUqGaQs7yRXQnK5iUTzt/RF1dVeJJLfGpOWW89/T9kWN/FJoX8tlGUVj0ohqOUWiCYRqF+paEambLhdFVJ0FXJahhOV6Q6W1ChZk0DUyHLXE4YNOMiaeXQ4RMYeiZYxSRYIwMxyP90NMfjyQNtJWM/9HSWa9W6FxU9eX9MNaKQruuMcYyjQWkpMozkpL4pauKYRyYp4njfg9Zxs3W2fJZmOnHA8M4stttISe2ux37w55+GIRbUA5OYwxV5aQ7tvI+N03Z2VuNtZq6Ku+hzqKe1qYgUBPOaqIzaERNn5KXz1KM8roETU4BZxVWi9reiKmRRV1BsjTLM1y94OzsnKqqWSxbKmdYdjWNc6y7pgQkKXQy6KSZJ1H4u0ZS/IwOzB6mWWJeLy/WXJ+f0VQOlRL9YUf0M84IR7+qLPLqZpnS5CTxuFrRdQ05OWqnifOMnwaev3zBR198weeff85HH33E5uyMtusE140SRnlSxFlJd5tUMVOk8nk3T52pCFYzpjM4W3Nxfc1iuaSuG5l4Zs+hH7h4/oIxeI5+Khoby8vnLzlbrVHDJGui8j4YoyEVPnpxdogAVMlZHAPGWbl0GEVIoEpELEGilWstCW8TwjYxCpwGZ5TE3pYpqSrC0lNn/ZSMltPTxFa+ZdJLORtMYTQ4W9xTRfciljVRzef/rcq9/P3T39NakU88+N9yj/5bF/T7naR+vbm9wzrNYlFxcXnGBx+/wlqNsZrbuxt2+x3TJEIy5zpRiu92zCEx+MRqs6FdtvjgOfQHdo837O9vaVcVqXPs+jvmMOCnEWNrxtEQo8LPcmgZJTfiw3DEGUu3WEDZGd7e3HE8HAghUNcN5AkyrJY12hg+cJVQofqeZbfg5fMXbA979scDrhIqVIieEGeUrsjZYK0qwqIijEBG7AbeW6KSPOBhmJgxVFlSsc4WS3xOzMqQjQRr1M6RgkeTcdayXi5puo6zrqOraz5//opaKe5/9kvmw4GFrVgtlnz56SeSsDTNGMT2FAvX/fbulru7O66ur+m6jqpkOs/TwOQnbg/vCpeiRPihqRctm6tz6rbCVobRia/6z//DX3Jzf8u/+bd/hjaGP/zjv82HH37Ef/UP/iHfffua//gf/gP/Of6Ed99+X5T0lj/9k7/Dl198zh/8/u+zXq/QWRMHT6cM2/2Wv/5P/5FKG1Zth+975sORzWbDYrGgnpfYphK+v+sEnwoMx57gA2M/4Jwo26dpIiXJtx+GgcViWXbKs0xXlktcXbHctCilyvQkIcNf+SphZ8SYCSEX+9ipWEuVVL/BeS9P19NIW6EENpESc4zMMWLLuqUyFq0sGok79CmUHZqiqQ2VcTR1z7AY2T4eGMeJY38U9XXbknOm6zrqpmGz2Yh1SCkhvPmZt2/fcnN7gy1K2aqyaKvl8qqkuMYYmedRolTDjCWjK8eiqllUFZvFiq5pMFEiOUVBm6l1RIdI6ndMjzfcfP1z+ttbmjRiQ8DmGRWkth3HAV9CfGKM3N/c0I8jj/st2lna6hyDRruK1abi7OyM3cOWfr9HoKfQLZc4a1kuVuSU2T5sUSBcfq2pjaWxsuefh5GH2xuO+y22slw9v6JuG0Y/MvuZtzdv6Yee2/tbiUWtHOOxZxgHalfRlIuRtZau61gsOppOukzrFEpJZ+Sspm1O1tWAtnLBJAquNXY1zkIMhhzF+pZiZBpHtFakOKB1YtEajsdEDgM6emzOXG3WXGxqLp59RtttWG4uca6i6xrquuJss6RrGy42axrr6Kqax9sHdg9b7t7dcDzsWa8WWKfZ7iLTpEmhZbFo+KM//D2uLq+4XK/4RmUe728Jc0/tNIuuYo4Nu3Em+sDhsGUuueZN2/Dq1XOssxij6PsjDw/3/Mnf+7v8i3/x3/Pi5QdcXl5z6GdJ35sDkYk5GTIGH+X1qSrLOCamOVA5Te0qmRwpmMtnxmaDtoqz6+eonPjwk0+onGazqQkRDhP088xhnERbYjRpGEnTzO2vvmYYR3QMmBTZtA1Za46Pj+QYUMXdojLk4EkztF2Dqx1jnEV4GEbUfMTGEa01CyOXmhmPUgajNLXONBq8yoSCvtVk0Cdbq+hdtCkrTS+ZGvNvfLtKRL3Oyc5cYDHihkg54ypdBLRlZehOR8z72Nxy1KAK7EfyJX7HKveE2Iq0QJyZ/MCh19zdaaraUlWOGL3A+O3/h7Y/7bU0S9PzsGtN77inM8ecU1VldVU1u0nJtNgSJUgeZAOGJcCwDP8AfzD8LwwY8N/w3zAtySZF0uyZLHYNWVmVmTGfcU/vvCZ/WG9EdgM2QALlBA4iMjMicGLv/a5nPc9z39edERF4L/GBOWs8CZ0UIom+pomubdnd77h5d8OyL6kWOft2x2A72uOEVBofC7QuOD9/kqxGUqVDFUF0Ae98UkUbw/nlBaenZ0QEx8OBcbI455Ef4BpDjxASk2dkLkvj9mlAj/qjsb+qq3mMmYhGiTEsEjmJdFuTSqab6vw12aQ09uPEFCL3NzcUVYWpU6BIVZSoPCdbb8Bo4pxLvF4u8SLdCNdVRWWyZJWwjlJKpDJoBNE59vsdIqR858IYqrzAz6zhcUrjn77r0vc6OYSGME4pbMM6rHP040QIERcCZ/fnrO9OKVclpsjYjwd62/Mw9kxK8pM//iMyk/H82QuuLq84OzklOk/ftHSHloe7B378oy958ew5n33xOVePHyeiEeCHpNI/brfstzuOd/doKbFZjrMjdhg5tkekktSbDVlVfowxFTLFCHZtm26xEfKiQCDwLqmzP8SzXl+nsV03DMQYuXx0RV3XqMygtMb79NBa7+YdlpzTkGLai/Hh9ptUt6mC+4+f+Zh+2ewL5eOX1opCyYQTne1wgTQiEymgPt3g50Nm+rCbDxGpM4pKz2EQgv1dAp2sjSaKRP0SSibrnUvipNFO9OPAfrdn+/DwcSentUIqgZ6hGnPrkNTn84/ElAvuxpF2GimUJlMSO7m5UKXP9aHdMVnL9rCj3e+QbmBVGr54/mSW+cPUDLhhIvQdgw1kOiPGlHseMsOyrlF5RrVZo7IMUxT4aWSaR+bdMCSXQoxzRC8c9vu0lxx6jDbks5JdKUnXtrx59YqmOcxTrXR5Pux2yEYyeZssb8OIdy7F4HrH7e0tfduyv99yeX7OarVgc7Lh8vKCk5MNZVmQFckXHmLypY9Tn6I5RZ40LIK5y0xAKu8dSoExEqMyYkxhKMFBDHrewabxqZCJZx5lgv+YPKPINiiz4OnzFyxWZ6xPLjEmAUpMplgvC4xOz7VRikJrxtEzjoGotow+sDs2CBHo+gbnxtnRYijKEqUlbd9i3YQ2CXgTCGnSoEQSu4mAMamw1osly+WSTz99PjsLNM2x4W5RU2UZu7s7TpZr4nLNIssgV8mYYT3rRYIdtUMiycWQ+AJD3xOsBJeSxvCCLKE1yJVIHu25GZJSERF0vWOcHNtjz+AczZRCXFxwaZrnUgiX7VpyO6Gdox0mpHNoYxLDI35IHJxRsjYt1nKtyLXE+rQTVwSqXOOFILohnQ9jjxAKoZL90QPejjg7JWZDCImhLwRBJKZCVVUURU4anafpmXM2fQZN9neK7wdNz8fzY67aIYY0xfqwM/9bKvePXHwJabIovp8Y/v4KesrczsoUczlMA27f0487ijJPN80iZQXnWYWUhv2hAxuoy4IiAyXTwdrvj/TjwOFw4ObNe7773becnq1Yrmt2zT39lCwFUUiycs1qfcKPPv8xZVHObGMgQNu07HcHdF6Q5TmPnj+irmpsCMj319xvD9hg8fMLvj/sqOuaJ0+f4kkq4NEmTGXavwZONivKsqAfWkLwCdUZInZyyHlMpaUiUxonPVZIpA8M1jN1PWPseDNa8qrkR3/4h5RVRbE5pVgs2Dx+TGctd23Dqq7xEVRRoLKMdVlSSE3/6g3T4chCGvIsfGSfX7979/HNXy2XqEyngh487dDTNA15lhOcx5+cIrOI63uctYQx7VTvd1sGZ+mmiWxVQZ1Rn6/IFyXXhzvasccGR1kW/Bf/2X9JXVQIG9ks11xdXLCsFqwXa6KLdE3Hf/yP/zE/+9lPeXx+yaKqkc4Rncc1HV3T8N2vfk1z2LN99xYhUiEMs+Vru9txbBtOzi6oFkseP348i5xSbvr24QEpFcvFisVikdT5xpBlWfoTYuSbb77h7du3NHM04o9+/CWnp6fUqxVZMVsCY7rAfICFOOexNkDMkEJ935l/fOTmOXn8fgT2IYc6hbokh0RhNMemxQefOh4iSmYgFMgUaOLcrDgPESciTgbKvGRRZVhP8mi//I6macjqKo0JjUEoxTBN6BjxQtC2LbvDjpvbG66vr/+WADA951qmQmJkGtNlOhXEzKS0OykV4zDQjAOlUmQSbNcTbIK0OGd58+5Nuji4gX4aUa7ncrXg9LPn2GFi7Ecebu44bvfcPWzpji2hqJFzJ220RpcFuipZXF4lOJKEo3N0/UDTduyPDW5KFjQjNMEF9v02TRasZVEvqKukoTBasd9t2T7cU1QFZVnMItHA/e0Nk5uS//xviWPzLMc5y6tXr2iPDfv7B+q64tNFzaNHl3z6ySdUdZlssSq9v13fME2eZuqQIkOparaoSYySaCXpbcCGCa0jWkm0MhChkx7vXGpySA1A2mklCypSoApDXsP65JJ6cc6Pf/IzTk+vOD1/gskydCbQGhYVM7qZj17tyQpGK/Fv39PZQL/f4+xACC1SeupFwtNWiwqpJLv9lmHqyXKDUOBD4mWkAh9AeIoyoWefPn/C2dkZf/T3fkpVFtRFwX63593bt2hlePPNN5wvVlwu15xfPKEsFzxsj0TnuKoUUhu2EUYHBwt2dDTHhkyDMxI/KeygyHRAK6hLg1Eqza6EIJMK6wPNw0DTtry/vWEMjj46js2RpmuSIFBK3MOW2A+sR4+xjnHfkAEXRZnYCiHFjnpS5oj1DiUiZaaoXEIcGxEweDZVjo2ROLbprOlapNRElSO9wwbH1E/YPtnZQvAoIeYVUtKGrIsV+cIgRIInjePINE4468jy8BH8lIpyuuDF+Yj5AI354C3//2VJk1LO4Ciw837991rQD+0ukZLMgqQWTQIkawMhWIahJZtJZJv1KXleokSKttNK40PyRYcIbuxx/YDtO9rdjofrazIVybQEG9BeEHxC4CEd0gYqnVGaPL1Ys1LZSE2RFeh5TzFay7Db0g49o08CidIoqrrGeY8sMozRBAGmyFmerLEEXEzh8+nNSWpgIdNNySid0qfCfLh7n4qLVGlCED/AO9JD6KNg6jq88xy3W0IIFIsl0SbvIzGSK0WcUoLbSX7JqirZVDW5kFzf3XG8vkONI8onWEOIMfGnjaGoqrmjOtLsUxrP/nBgdJah79MEZEyrhmAdCsF6vUIZxWHssEPAT57BTxynDkON0YL11TlLmcQzZVFycfWIOi8pYtqbPdw90Hc9x/2Bp8+e8b/4X55yslljnZu/LHEYwPmUFhVDei2dI8/zNN3RgnboaIaWUQQoDJbAYEfevns7+5fTvmkYBrx1XL+/Tp7TsqQsS5bLZSp8SnF/f0ff97RtCyQOQIhx3pNmH5nXIaR8diEE05TYz7lRaGU+jty/f+K+v02nwj6r4GMq7F547OiIE4x2woU0soZ06/ZBMDmHjAkhKdAfU7SElGkNMAx4IlEnFnXvpoRCLvKkQpYCO+szjEiZ8H0/MI0TdrIfO4foHcSIngt5adLuMmiNFILpw6U+MncQKRntJstZFiW51pSZQQq4PN0QoseSdCrP4+N57peieDNleJ1n3GhNf/vAdPCo4FNHqtMl204TY+tpr6G3I7umYRr6lBbl0gHm/DxhERGhJXmecLCjT5fT42FPURQsl8t0sImYXFSClDmfZ5R1AUQ8kck53t9dY61NqYbjyPF4pD007Hc7gg/Udc1yuWK1WibXyTjMSWCWpj3QDx03128xmaZrd8mNo2UqdFXJ9OFMIPnRP2hu+r5Nfv44d3FKJRRtnEBFimXOYtSJulinETByHreq5GNP/57WXWI+kX26t1BtCrJK4Pmck4tTrt+9pO8OCDEgpWdRC6oqox86vFPkSlHmhk8/eY5QitFaJp8cOpKQ9vtzgt6qLlmUORKPCOlrVZeUL56zfdhyf3vPzZu35ChKXVJIw7ooEVLBqPAThCFgbaBtLe2xoW0OBKPQhU7seqXxMflAJ+nxSuJinO3IyTI6DQN939E2DdEodGGSSO7dGzZ1RZVliL5DW89isaSKAik0JkKdJUyyWC2ZrE1TrLaha4/zM5+aSZVpVnWBD5b9oOitpekbRmsZ54KujQXvwHum0c5ciGSP1dJ8v31TgqKqyIv0rAnEPEmcgU7xAzrapoydOS5XmSwJbuPf/bUfDpt0Afh+pw7Jhir42w6d32NBPzZ7siyjrLNkO5oLuvOCYUxReUnCr9Ey3WAzUyGEBgwRSYlmnCzb3THlJ/cd3X7P9uaWZZVTFzmCiCb5hJOtySGtTxYOk82igwSwKIuS9eqDMllw//BA0zS0w5CiIsscI3I2Z+eEGFBFNvtlAzrPWBX5rJh2WJvykPsu7eDr+SZvlE7jt0jaobtka5MxjZBECB/HSJE02mq6HsaJ43aHQHB6aYluwg09UWkyqQh2ojvsOb84TwW9rjAIjnf33L55w9VimawXM1LQhmS5K8q0jzk0Dbe3N9zf3NIfG6y1DMOAQjANY0pJch5lNOvVEqEFebOn9xNBBMYw0tiOGk+pJZvLE7K6ZLVaUeUFF5ePqLKMlc7pji1vvn3NMAx0bcvzTz7h088/5+3r19zf3X0s6m7owXsqBMTANCY7XlEURBGJKuLGwH5oEUojigxHADvycHdP8CF14yq9xn3f8+rVG7xLF67VasX5edqf5nnOMIxJLNa2xA+iyBiTbzvLiJPFz7ZESP9/nCaGYcSoCmlEKuizeC7OfnMxj97+TjEnpE5QRsZpYgp+Rqfy/Uguxrljn8fvJG6zkCr5TJVisgPejUnYpiSjdwzOoouMvCpBqxRW4R0ypt249z7578cJOznsNODdhB9HYghoKRJXPE+dedRpQhBnj7qbUa2ByPb2FmLk08ePWS+WZMuKPDNcnK4TcEWTeOZ1Qdf3bPc7Nss1p6sTMucwzvE+0xyjRwY32zWT4MpOI+MYaPqG3fHIq3fvPopI18sldVnifJpoREFaF2Q5QTqmYSB4z/FwIAZPXZWzt1zMBV1QZInkVi5rtNGJVjcO3N5dMzjH2PcMw8Bxf6A5HDnsD8SQCvpiuWC5XPKwvWcYBoYhIar3hy1d1/D2zWu0lrTNKhEgc81msyL4dRK9BZ/sa0LgSZqdvm/wzqedr1YoBD46Rj+mgl7nLCxEKVAmhXN8X9DTMAeZJj+DA6UEmUn6Dh9gsSmoioKsLLk8TOg8st/fo9WEloG6Bik8/djhbHrfi9zw6YvnDNPE7nCg6XuGUadLtncfUbbLumRR5QnvGxKbflmVbK6u+Krrebnbcfv2LcJ6nlw84aRes1ydoXVOnCTegx9S2E5z6GiOLV1zQOYZBTkhRUHiYypoIxIlwcb4UfRIiNh+oO9a2rbF1CXloqRpG96+e4s9PWFVVeSjpYyCxaJmpQ1KanSMVEonvYVUyQHSNXRuxO1TZy0IVGVOLnKWdYH1I2Wj8MEyNS3jNDH2qaB7l4q5iJFpsrgpEQZjnEOe5rG5VJKyKskKNXfizJCu+VI/20pdSKS4dPmLM/c/xan+XdDV/3dL2odR/b9PMf/3Kuj/5J/899R1xY9+9Cmb9Ypnzx6nTsikG74XAmcd49Rz/e49D+aB1fIEY3LKcpkCJlDECHWhcVaAH1lVGc8fXVBqhW0biirDZIbnjx6hjWG36yhNDs2Id4n3mxUFy80i7TsiBDH7+4whaIVZ1BQCRFUk77pMFC2vZCosMY3OlNZUi5oQI9uHe8ZhwOikNq+KMoWBzJ5160YEoOUH72nAT5apH2a19zylBao8aQiOux3OOorFElOVZMcGJwWTEPTDQG0Myjls03C72xNHy/HhgaltUXWNUenW7QDnHePQc3P9fk7rSftCIZN6F6PZnGxYLZasNiuKouTs8hyTZSxO1xyHHhYF2+ZAub3n+Ref8fSLT9hcnFGtV9QXG7KyoC4qjNK0h4bDMPLzV2/JteFyc44qJEZItFSMfU+RF5yfnRMFdGNPYTQqMxiRusynX3zCNI4M44DONcWy5MqNvJh69ocjbdtyuHlgOHZM3uGtR/QdWZZxdnKaku6yDFWqJPbLUxcbQqDruo+4xc8++4x6seD5ixcsV6u0Z9bmezHLXBSttWitWW+KtBO2Pcsqvc/jEHAuTRUgJtqekKkri+Gjo0IZhRea6MGkSp6cHDEydgMOMFmZVjMmI1OKymTzdCegshydG0J06JDzo5/+hGEcKBYLmC8yzPGYh67j+u6O7cMDN9fvebi/Z7d9wI0DwVkWRY5RChUieEvTNqlrKAu8cwxtQ1EWLJZLlicbFps1+awgPilLCjN36ET6/oidFeRBRMJ+3vOFQE5gkSlOFgX9ZsG6LjgWhq7riEg2i2W60LoEXxpmdkJVlQljPFqsnRilRGlFqVKHPVlLf2jwzjH1PWbeeea5JssUdppo2o66KlgsKsa+o20PdK/72YmS42NgaI5Mw0h72NE0Hdfvb3FuwjvH2zev+au/+HPaw57fPLri+uZdSoETyYccSROPoW8xWjINR7JMUxYZx/0dN+/NR9V1VeZoo9M0zzm22we893NuvGGxrokqEpVnCB37vuE4CNpJUmdLtK7YHe8ZnWd1dkpQ8SNoR+m0c48CogQvIz2C6MFlElEp6vMF3ky8+u5XONvzSNQoEfBDk7ztQXKyOeHx1ROKouTFi0/5xVdf8/LNG45txzT2aAmaQBh7plbR7XZk6zXnV5cYpTHRc7Fe8eVnnyGQDM2RoWkYmwYjcrSeCFFjfeR47Nn3A++u75IwdexwcWJiwutAVBGZRYSeKZre8ublS8ZxRPrUBGXoRJe0llWeOACr5YLT0xM2JxsWdcXCBcooMJlOYUQ6CRXH4AgopFGMeHo3USwqHpnHnJ6fslwvEUbjBVxdnJEVhn3XIGTkMBiEiPhQzLx6qOqM1WqJtxAdlFmFFpr93QE7TSiTIXRAmQGhEp/dOQeMBO8xSs+Jnho/JjriB2x13/d8YFhoYzg5Ofle3T5Pt+TMMGFep324MPz/paD//Oe/YLmqybLI1dUV5+dnSCkpPtwgpMKGKdmk+h0giV5Q5GWyoigNQiGEIjc5RkZEsJS55vxkTYieMI2oylBoxePzc4qihPF92ln1EyHOAH+dkSuTdibEj/5KaTRCa1SRY2JAFCmasev7lJqlVZr0hEBUCqkVWZ5T+cBhHs+ZGRKQmwytVYLb8IEolj5McVZPB+9x1n68TX142XOtCUDftqmb3m7RfY8aRrwUTCIStaE0Buk9ru9pD4kMN8xZzpKAFCphTeexsLOWpu/I85yqrOZbaNrToBT1oma1XlFUJVVZslyvyYqcarMin0ZsJsmONbEwXD654urxFfXJmryuqFcrTFFQmBwZYDx0NLsDX3/1NafrDU/PHmGkwgiJEpJpnNIEwyzo+57R2o/4TCEkWuScXF0wTiNt15BXBcuzNRsZmVTk+t177u/uaI8t7tjOPO6AneMF8zxP8AijKfKCk9PTj7up1K2OQPrsXVxecnZ2xunJKVme0TQNQkp0ls+ipHQJsNZSlhllWdK3KeZU6RyTgZ0AItZZhEirBz4oUQFiSHZAJdFRpjCWeTwuZrFd1zpESPtcZNq3Ka0xhcFPHusjyiTGQUCjoufx82c459JnNHiIadYThKAfRq5vbtltH7i9u+Ow23E8HPHjAM5SaTXT9ZJlcmi7FFcqwE0T/eFAJgXFyQknqxWXjx+xqCuKLMfEiCaFWARnaZuH2dJk8dEzuDF973mGwpMpQZlpFmVGVWhKozjaBh/miw2C6B1+jimNwZPnGdE7bIwE57HSYnR6vkJM2M22axNUyDli0ExTOhy1kkwxrcCEgCLP6PuGpm24vr1OzIJFjZSSyTnclOJSu2PDfntAiojW8HB/z2+//ho7Drx7+4Z371/TdQ1VmaG1pCjTPj3TEqMVznbkmcFVOc0sJKurirLIscsFWWY+gpz2hyTo01onW2IhkJlEapj8SDc2DFYxOkWJA+lp+yM2wGAHpDNok5TTyV2RMlIiqWuf0k/wSiAKSbEusZQchyNDd2C1AS0itj8iXUBbWC+WnKxWrNYnPBMK6xKo6Ne/+Q37rQYBmkiY0oRn6jqoK9Z1hQCi86wXFfLqkt3uQNN02KFn6nsm1RG0x0fN5ANd06ZArIe7xHoQcyALHl9oop1T0GQKMhmngTdv39AcjvhhRAnFKq+Sl7tK+FijNWVZsFwuqJc1VVWyCFBGgQoKEWJaVcTZtkbSjjhSeIwpMvK6YLFaUNUVKJnS9FZLkFBXRdIJZUnI6Im4EJl8pCwMy2UFQRGDZLPckKmcaZiIbSArBEJ6vBhm5oObRbbJYfJ92NAMiSLOIUk+iUFJ+gGlFIu6nm3SCUscXEBlCSAFf1scFz/inn+vBT11RpHffP0dv/v2HX/+17/m/HTNi6cXvHj2jE9ePEPrEqMLpskSwuzp9o5xHJMnfR7JZ0VO1/UQBupCcXm+Sv5pJSnLPO3JMkOmFOeLFUTJ9t01ZV1z9vgRru15/c235Isl5WZNVheYsuTp85wzZzlME733dG3iRFfrNVor6rxkGgb22weGtuNwPODGCe8dWZ6xXC7TXjIEgvVY5+ltm/aUH4D6pNHtR8a0iHMudaCfksczLxNOUkSHnXrevX1FVlasL8+ReY6uak42a06vrng4HNi+f8/1q1cctzumqUcbye6wQwroxyl9CLIMQ+r6tNToCDqIGZWa3qNqUbNYL/ECWjdx3N5RViVPTxdUJ0t+8uljjkPLs8OO5emGxWbF06cvOD09xanUHUiffLWD9ixOz/j0f/4/wyjDIqtmmhFMLuWWhxlwYmfxyLvDLu19Z+gHBKywNMrjxyMv3+2IWhKNBBkoztb8wR/9IXIMtHc7bJ/2nzFETJnjYmCxTIhOnWezUCS5FBYxcnFxyXKxBCnphp5/9Wf/CqU1f/j3/h5ZUTDaGSkrFcpoyrLEuUDbNrRNxzhOTFOH0Ya6XKC05uR0TZwftOSLluQqp8hK7Iw4zrQmLzL6aUh7Npvc3JvNakbrGgiRrusYoqDdt+g5lAWtEVJ9FHTZ+WsIabc8jFOyVjYtx7Zl37Qc2nRwJvHdfL8Axj6hKQuV+NMXJxvKzHC+WWOUJFMqwXg2a4r1kmK1SDp+n9jVeE8hBRAock1mBM6nGNauH5n6lt3DxHg4sLu+5u3Lt9zf3IEdWC0Kdg872mHkt7/5FRbBMAuThIxkWpNlBZlKCGc5TzI+7Afv7+8I3qe4SyGoFgVVUXL16IpMa+7ublivV/zBj384O08Cl+enXJyfEPzEbrfjuN/PU6pkn9POUUnBo039AbXF1Pe8/PY73r15i1aaYeqJMfDk0QlVmbFclSiVfOPaSMrSUBQZdqrITHLvjEoAafooBHRdP69vRoQQ1HWNJycbMsZ25DgdGCbPMDqczwGFc4mhkAuPl577uwfabmR5ekIg0g4NZV1y+egMLyKOiLOR3kGuBdqY2cNd8/zTzxn6I1cXNZkC468QkyUee5ZlRbvbE5UmKsUPP33Bi2dPWS4WvHrzhn/2L/45+8MR7R21UXz5+Sc8urrix1989pGRcXf7wE1+y+lmjbUBpWG7v6fpRyKS/aFnsoGj9XSTo28blNYUVUWmICdi24b92JItNCqTTCEV9KZtaPsWP0yoKIi9ZbFcsjk5xSgzUxCTriDLC+p6QdgfGaaR49Djo+QyL9HFBy66SO4nEcmDS2vBoeditaR69pTQNvhpYFknGNFnL17Q24knn7xgco7jMGFDYAiB5WrDenOGcxFvI+/e3XC7vebXv/sFu+0WpSMBR+/Sz+vazPkFGVlRUJQVb96/p+t7Xnz2OadnF/zud7/l5vaWi0ePKauKi6sryipdnggBb5O+B8GcAig+XhiV/h4Y9e/6z79zQZdSEULkYXfAuUjbOy7P17ixIzcFZ2fnFHmCtkiZ/Nof9tXTaGfgh0ZpTcTh7IjAYQzUVYbODNoYjNHJZyvSqLMwhuAEQ9MlH7VL+bDHcUje7uUyCeSyjLrIyGIgL0tUluGb1FirLEs0ueWawRi6tqXvOvphJCYpMlrrpLIeBgLf70+mcfwojvuA3vQh7XTjfHuy8YMwbMKFgCkLlFBpLO/SSDD3jmxRkgvI65qqyDnfrDkeDwxtw+7hnv39A6V3aAnDmAR0wzgilabUeg6+SAekiklQK7/vIdPrl2UEmcalg7XgFF5EdJlxdnlOOS3IVxW6yFB5xqqu2SzW2OiSHGr0hCDwCLIs59mjx4gAbpg+Zm/vmwY7tGk/FhMxLwRP13X44JI6UwpMofF4BhmZvKObeqIXxCApdEZmNKuTFbXI6EzJ1A1orbEufciN85RVidY6cQL+DkZRcnJyymq14v7hgbZt+e67lyit+NGPf4zSJtnGZh/3B8iFmxPHEm/A0vUeJRXZLLjMsnwWe058IMd9SHPz0RNd2ocprRns94AJIQR5Vifrk0uQl8l7vI9MjhkSowizBe5jrKKIeALW+9laOGInSzsM9EPKo56s+5gk97ftK9659HdUGVpJ1sslVZGxWS0psox1NVPmFjWiyBBaJzFYSJGjOIeVIuFipESKJAp0EkT0BDcx9R2N87h+4P72mvvb+4/QEi1TrPBhv8VGgS9SR6SUSAhio/DOYLPs+z3j/O2P44B3lkIni2GWGfIyo66rj4JKrU84OztFfDgLygKtFIUxGCUJNimLtU7wFxkCmRDUuZlH1ynv/Nh3WOv+zr77ZJ2jZKCcFFEJgnAEL1PWefRkWiDIUUqmJC/1vRiu6zqcT0FESilynyO9ZJom+qlnd9zho8KjZztVSudy1mF0mux1bYePgmyxwIVEwPRETvzmI5aYmCBFWiu0kuRlhVKK9eaUoshYLHMyCUW0MFli1BipmfoBoTWYlLaYFSVffvEFq8WCX/3yl0TnyJQk14rNouZkueBktUzPiJB46xjaDl/PzIYgGO2QkLNRsN3tGa2j8zD4hJ7OZrufIiIJBGuZbEBkOVEoXEzrmEgSlyLS+jj4ZK00JnFAEgMqwZuU0ihtcB8mPC7gSP9da40ycv61JKtqniOcxY8g8wK9WODdBMElW3UMbNYrSu+p5uez7kemEBiCp16sWa43WBtx1vP+/TX92LFvtinVM6YJVjvt0DqyqLI5ByBjuVqzRrB9eOBht+PRk2copdjt9nTDSLlIa2c1NyVxFll/CMER4kPMcvhb1txZTPsRPPN7LOjbdgIgEjBSs6rXdH3gr375Hd+8vOVf/Mu/4sdf/pBnT59yfrahqgqqWiOloB8TlCbLMwwK5RI5TuqJTMY0ajAaZRTOTVjXc3fbI6MmF0tE1B9HF6+/e4nMM1RdY0fHOFqKmAIxDseG4zByevmIbLniOP2Stus49gPdODEME+3xyNuXLznudmxvrllWFcuyoixLTFXRty12nNjep/1YVRXJd5wXTNPE/rBHCIHOUwRsBdzc3tL1SZgltMIGh7Wedpw5RHnO6EYemh1Xj59wfnHBIs9Y1yW5iIipY2z2tPsHpMmS6rVPnPnoQgo+KAp0jEmkFz0qSPIIlUw7dogEGXE6Eg2oTLPZnFKUBbE2hEIRckFV1SwuVjRdCgN5/fIbbt+85ovnn7Kpl3THlmmYcLsjDsF7G6nLkqvzU8a79uBlAAEAAElEQVTR0h5amoct+/sH8iLHZIZp7JOIK08CsKPtmYKjOQyoTFOeLMnLNVerimN7ZH/Y8+rtDYe7B16Up2x0SS1ztJKcXF0kQERIB+B6c5IgKnlOZgx5ln7UxvDq1Wt+9dWv+eu//muur6/59Ve/pl4u+cnPfsbVo0dsTk5xzvHmzZs09amqOec64+QkhZ4cdgfGcWK7u0cKyXKxJNOGqqhhFrq54OnagUBAiaTo/jAWBp1EaiHhJaWQRBvRQrNc1kQfCaOfU/mSSGh0EWQy8E3eM1jL3cMDTdPy7l0aJzfHw7x/S4z+zdk5zW5H6wNRjnggyzLqIueHn77gdLXiy08/wUiB7Vq0FFR5lkRXUtDakWZoPiruSyHQRuGnFF8afRp1j1NPFIHlcsFyseD87JSu6WiPLd99+w2/+dVvKFWJkYbNsmZZ1/Q+JJV6meG1Ii8yBu85jh2EQK4V05QuLcxCt7OTkzTytBNSCuplRV2V5KWZY4nXnJ+fsFzVNMcDbdMwdA0iRrY372kPBx5t0hpm6DumcUJ2I1OKfydIQQq8FEmDEpMV+/HlGat1zQ++eMqiLqmqDAiMfUOInhgdchb4aS2IQeFcErs6ly5DyIiWmjJPgUJCKibruL65ox97tsc9Jl9SFBViymDKGF3AygmcwxmLd1uycsLkSyZveffuloeHA8duoqprlusVMvHi8DZiVKAyCikKnjz5AcENFHokTgPt7VtMiCyzKkF47m/Jq4q8qnh/v2f0nmfPnvLDTz/lh59/xm6/50//7E8Zx5GbV6/R3jF+/iKlmp2dE0Si4gUUAcH9vqcfHXm1JiA5BMvU9mzf39GPln07UeRFEthpjTYm0USVYL04Y3W6BCNxMZAXOeMwEq1PMWuNw5iMerkkLyqkVOR5SbVY4mKk6XuwDh1gtTphJZMoTkiBUyJpoohQGGq9olovOA+B5SqFvCiTULqqaciU53x9wuAsb+/vCdPE0LWpQ/fpwjeMQ6K5CUmUE1kJF49P0Hnk5etvmWyPlgkpPk0TMQp8HGm7gbuHB7pxYrQJ1aq1xlvL4APv3rzlsD+Q5zn1YpEokyI1iB8KtipylNAs6hohxcckvLbtPkYm/94Kup3xj1Iq4rwLd87RjCNutLT7huVqjVRZ8s65xSwMUmlkIJJS2Md55BccMQbS+l2jM/WxoPvgGLsRvMApiRJZSjMVyZKlEJgsdS3eh++7npAAA2VVIY2mKEsmN1u/gqfzA13f081q2MnaBLlQijzLybVC+IgVmi7vcNZ+5IV/4Gx+sKn97ci8hKP1acw+24wiMPlECstEUtd3w8A0DinDWAq0YA5fsXg7pR2mSvQl620SUc3pYyKGpMj2848EVAQ9p9I5EsvcxUCWG0yRU6+XZGWOLvOUpiRiCiDIDe7gOB4O9B5UFFyUS1Rv2d/vmMaJvh+QWjFlOTJEdlrirWfsLXacCJPFS4kkpgCcEFDSEBRYFxm95zANKGEQ1AgFZW4Io8JKGLylG0cOoUEohypEImSVZeLmO49UOlGcZJrA5CajKPI06VGKYRi4v7/n5ib5s+/v75msZbfdUtU1681JcmK4NJbVs/BEmzB/lsFHly6RQ4ppzWdudEI0iqTtCBGbpOugZ+tJiPOvkx8/CzF4AgFnffIxzjYnpWa1tvyetx68IxAYxoG+Hzg2LcdjChMZx5G2bWaPedIsaJMmNB8EMn87kanIc+q64vRkg5aCfoZ4FEbPnwkPPoULzXE6CWlKEltG55IifraUCUUSIM0TkWA9Uz9itMZo9TGuxmiFjAIt0/ngY9ppSlLuYvB2jsr8Xq37YcqSFwYpBH1wyTufG7IiIysy8sxQFzlZkYGI89quJ7qUT+2mERHCLGg0NDEyIXBKg3SoEEiMr5CQwkqlQ1hBVeYs64qyKCiKnCI3xBiI3uC9wHk/jz9njYyzqZh7x2TTpSfthSU6NzPrIJ1DwzAyTCPT6JEiELQgOEF0YmanO/IshTsJ5RHSJdeCc4yDxUeQ+4aAJC/r9BkFoo84KVIugIA8rxEmw4gOFyD4FPsrlfwosDJZBiGhXqdpwkhFXZZ88uwZ56envH39iv1hT9c1H8+eODtpssxQVgU+CnwU6N6iYkTlCUorcw2jpJ8G+tlJ4r3FTVOyYyqJiEkbkBmdbKtGoomsVium0iJcBBsgc0gh0SZPaGqpZz56gZAzzEYkjVZaNxrcZAlRIIssebqjS5hXY9J6R6bn108W4QNx/gxKIcl0ipE1SjEJOaNik4jTyylNrLRJ3bSCLFMsVxXOjSACITrk326WRQJUhZgmFTHEGWAVcM4jZJqkDn2fGuOHB6yzlPWH5sLMf4z4+FwDM4xmDmwJHyilv8eCbkyBUprVaslkRx72W4zWbOoNmVFkRvGrb1/xb77+HU/PN2yWFT/84Recnm740Zc/IM8zQpjwIbBv2vlD4MjLgnLGXZrMMPS3jOPEq9fXqSvqJHlW8vkXf8DSaM6WKwbvubl/4NQYypMThtGhO0ddVVTLKiUFO8/uk8/Y7Y+8ffeasR847PdJqOYCRV6SX1xxtt5wul5TZxm50nCePL5f/OAHjOPIr3/9a8ZxxA8jCFhsNnRdx/1uRz90dH2PdRaHJzcGpRRN1yYbVwzoLGO9LFNUZH9ECE9mBCJapr5lbPb0+wds3+BtzyhCipINFikEVZGTaZ0Khk+jfq01SkeMlFR5Tjt0jM5ybBpkmfHpz37M5uyU9dXZLIpbzCP4NL4d/cjf/OLn/NVf/RVn1YplXvLVP/8LxBi4fv0OIQR/+B/+A84uLzhZrHj55lv+b//df8eTx4/5w5/9PXKlWRYVx+bIfuypNiuqogBjsDIyDZHWO+7aI3GAW99ickNxV6SHxzvyuubJi5Lu1Q3Hux1uMVLn5UeP+WSn+Yadkp9MlmFMsqM1bUvXdfz6N1/x1VdfcWiOCCV59PgxJsv40z/7M569e8d6lRjUj6+uEjvcGEIMhOh5d/2WYew57I5MkyVXBbnOqYoapQzBQ4jpEjaMI8e+JS8ziipPo3cZEDoV3KpIbgoRIThH3zQMUTIdOzKVUZqSuqpY1BVt39C3PbtmTzd0vHt/TdO0vH3/PhX2Y/PRo6rmqMUoXKILA2ou0qOd2O4n+k5zvz1FK5i8JcsLLh5foOYLhLUT4zhgjcAOYL1NdDvnCD5wPBzwbsLIZC9z3mJkEsNppTGZoS5rHl895sXjZwxtz2/+5tfcvr/l229f0x4b7NAxjJbbw4GgJGJhcGJO+/ZpL18UFVldkxez2FQLYvAcjg+oKNicrjjZrHn6yRMyrSkyTXSO27vrtI7abtne3tIfW67OznlyfsYXT59QZDndoaHve26k5mG7ZX97i3WBo/eUq4qT1YJQJ+jsyXrJsirp2wY39bgp+7hDTxk/SYgUnaVrLV3XMIwDkx0/PuvZfFadnV8ki2ReEEJkHG3KB4g53irGNjB2lnGA4PtkewpD+hwVGZqcafDYEFGmwIXA/cMeFyQyq2fwkUp40xDIRSSTcLmuKUxGnhXIYAgix8fUGdoQE6Eu0+RVzlldEoCbm/e8fvuaerUkyzP+i//8P6XvO/7Nz/91Ehw2RzItcYsS4RxZJtm3Pe0wEqVAFworEplSlpowwLuHG0IUnGwu0UJi7UBUAkNOMSfXqZn82PcjNqQO3iiF9IKs0pyeLQiBxG4oC1RVs95YJqnm9yNC0GjrELJgcp53r96Q5xmf/ewLAoG+m1jVCy5OzhBKgVQ0Nzccr29SeiOkjI8g8cFhUDy5uOLYtQzjhJxGJmeRIdEZrbdEIVitcurFGVkG2+2G3/zuF/RDSN23VCwWJXlRslhuEl8lJA1JiJFh6Hn16iVXj55QVhXDmJrJV2/esFyt+ON/8Pc5Ozvj088+SytFY5imcXbvJAKlnMEy/z7//DsX9CgjUc6I0xiIMoISSJ0k/5MP9ONIP/bsDoLgUhaxJ7C+uaUoCkw2R2N+tBMZYtT4oLAuWc+c1/hgiGSE6OmnER8to7Nk3jEFj/We0TmObYu6v6cLgUM/kC/KZAki4nxAoci0QQvFFAVucvjJE1xAhu/DUj4SfGLEmNQ5OBdwPpDlReo3ok8K58yAUtgY8CLS25EQU9SnF5EoAl7OYmXSFTsR3ZLffRh79vstRZlTL2qaw47mcMBOA8E7ICPONLXIDBcQzH7ev/ueyA+WhtkjmRU5RVmmG7+dkDqJwaSSieUeJNZOtGPP/njgcDhAP9EpQ9FG5BjYP2xRSnPYpdXC17/5Dbd3t7x//45FvfheySnSEizMgTRx7mg+8O0/hN04H5iGgdFNDNOIkgItBIUpqPOMWByZcp8eRCEQ6ntWcrLzzGwDYxBK4mOkaRru7u+5u7vj4eEhJa9pzXK1QitF27Y0TYv3DkjvKSKF8ByOew7Ngd3+gbZrOOyPOOs431yxqJacnlq0cgzjmCAzQSCEItMfsMOSD0zYBH1IwSchJDTtx0I8//8Y09h8HAZECBzaA23fsjvu6Yeew25P1/WM/YCdpnQTj3H+vTOAgpisZPFD7rlEapXCauzE7rDHaMn99p7gVyyuzubdnkDikU7M3HJNnO1awocZopOEjSHEj3oI4VOwD8IjvETFlFBXFAWFzjg7OwMfaZseYzIO/YDsR45Nh9cSlRummLrcDxMBOe869RxTKkQCR5nMJPpaptEzOEbPqNJk1ezo+/TlpokYHOvVgrPNKVWWLruyLMmEwC1X+MlSmQwXJ4Rz6NkxIWL6e+fGoJXCW0v0FqPneNRMArPvOAbiDD6Jgo8hHB/BITG5XJybI5+VI8aUN54+K8mEHTw4F3E2EPwsEp08WnmUTIKqvhuwweOsx8aAxaG6Hr0/olTKj0/xULNoSgiGMrlbSiNBaLRJEC98RBiNLnJQEhs8WZmRmYxj3ycL7zQQRSTLToGC5aJOkxaZPqtuGtN7T+q6rR2JIoXtuDBhgyCI8LEeEFO4E3PRFKSJiNEJ7pQsnXOxixFlspRF4UELjdFFOptUIBpD/GDQFyqx9KUgmhER0pksJkc/TElQ6tNEbHIOLwS6LOZvRKQgKWuxH57T+bLmrScIQV7lTMaRmwzrfZqEzc4nT5zFnRIZE+5X65mzRPoMf4hL/TDF0jJZjK1PCNnwgR0xJHa80AYfAofjER8DNzc3xBjZnJxQVRXL5TKtcrWevezhY036d92f/3sVdKt7xgDbhyNGS1arLAkopOPQjTTdSK5BG0E7jVjvCN9+i36t+X//2V9SVSU/+YMfszk94dPPPp+7rYLJRbpDGmWE6PC+IsSS1WlNvhh571/jiTxMPUOrCA/3BCGZIrz/9jvu/vW/AZMhtOHq6VOWm03al0nJ5dXjNGYJBuslrrdM3ch07FEyFcvu2BEnR681RkmuLi/RecbN9VvGceLs0WNCiAxjjzaaer1IB6USvH77ipevX/Lu+j399gEbJ6IDs8jJZIGfhXX3h4c5KvDI63cv6caWZ0+f8+mnn/KrX/2Kb7/9lmGYkuq3LtEm8eE/FPDIHKIhPxRojVAq4ZkjH4Umn3/xOZdPn/Drb75BvNHUlyd4BVPj0ZmhrCvevnng17/6Je9vrgnR87tvf0e32/NYb1jqgquTC4os5/rta7769S/5l3/+FxRVyWeff0ZmNJ988mLmuR8/2vuctelQcgInItYOBG/RJPVxu2/nbPaBRVWyqmsePznh6fklTi0J7QjdiIxQLZfpVi/TuKnIvmdcT8NI03X88jdf8W9//nP+7c//Le/evefZs2esVivOzpKV8ng80vf97FNPu6ymadhut/zFX/45f/nXf8n28EDbtXNCF/zjP/mf8PTxM9bLM2wZ6A6WvCjZnF6wXlZcVRuGydOPHikmgnAJCSkExqRo3eMwQoicbDYoJCpI3OQYmp7rt+94uLtnd9jRNIdZQOnTYTRfhlSMFCabL0KzoNROMGOJvXN4IllVojNFu72nHQf+za/+hirP6Jotz58+5r/8n/7nlFmJKgxgCVNEl5q6qLDWJJGgdeA8fZt2yMEnEEY/jozepdXPnNMercdPjkIZMql4+vQpnzx7wc/+4Gd0fc+f/et/w+12y1evX+G0Qp+s2fc9b+8ecEHivWYYEzxGVBlGi7TuIvDo8VWyP+YZ0siUqucsh8MR2w8MTZs69IcHVkXB2fqC/9Hf/2MeX15y//oaN1nWVY0oa54uNlwv10zHhvfHA+P2jvWiYrNZI2WC0yyqEmMkx2ZPCI7gMoxRsEze+ET48h9zKbRR5HlGURYsV8tkPZIKpEQoTYgkaxgSoQxFXrFanNK1nuZgsYNg7CJSpPXL0IzgpzQJ0hnffPua0VusTnjgSQZuDw3+7XsW9ZKqqrk4OWVZ1oyjT0AWv6fMNep8iREZp+dPiLYj9LeUi5z6dEHT9Vy3e56crFifnuAzzdAPXN+859g16CytP66uLtBasVqUKAVde8DFiIuRfmjohh6RLwjKcGgbBhcYgsQrz/J0ibMRP9t6ZUwX8LquWS0XLBYVwhhsCNgIQUiWmxOk0oTBoYIk2hQfvFiVtMGzD5beRpresSzSytD3nuh7Hu6PyHbg2CRw2M12SxCBtm/IlgtYLYnHltg0qRDrnGZ3wE2W1WqFlIJm1yKk4KxcEFTBab1MeFk/kdcF+aJimlny7dAzTJ6u3dIc7yE4tJKsFsXcJH1IQexYrzecnp3T9B39ODJZxzQ53r9/nwTbq3Vy48zTxX95+JdsTk54/eYNz58/58svv+T09IST05OUNOk9x+OeaZoSbe73bVv7yR/+DOs8+12b9jJ9Q/BJSe1iTAtJmdB4WVFSZBlZWaOkZBgmJh9oxwnVDtzvDhiTkWfJW57UfAYhNFImlrXKwAhNtV4nBGxmmAjc7XeYvKCoF1jvabsOF3scApSh7UbyqsJkOe2hSR2sC8goyKTByUR/UzKNS6X4Pp4yOMEwjvP0INnspDZIwMgk6quWy4+Up+XpCad2gFyzON3Qjx3Wzd5a7wkykYBCTGMwZBp5Hpsjh+OO3X5LjMnnWpUlMYpkbQLGEAiBpLYOkVyatP/NZquEVKn7C3z0cE82ATyM0aAU+92OyU1Uqxo5KoYx+beLqkzhFJlCz/v205MzTvIFGSkk5EM0ZQgeJQXLxYI8NzhncS7pF6RKwRODd/jg0sVKCXKdgZSsosNGT1GkIBnrLYUxlHmOEQo/uY+7ock5RIiMzqJloqUJEipUiBRV6mNyGNg5RvXZ8+dcPXrEs6fPWC6XrNdrhBAcDgc2mw3L5ZJi9qB/AMscj0dub2/Z7u5o2hSxKaViHEesdVjrmJTFBghBUpUWEZPK3dmYugSd9nrep7AQIVPB/dBZKymJLtC2Pd2xY3uz4/bmhrdv3jAMPeM0INUMjzAmdQLzLt7PneGHbh9I7gZl8CLiBahcIwkYEbFDz9jsiBK2xz3lruB2e089JpGZn9MDB+foXcKrxvghIEOQ5UmfEpzFOYl2CcgT+H5q9aHrct7hJ4vJU/dvMkMJnJ2eIIyiDZaRyFRmmDJHlwX9EGi7wPHY0fYDUnzIghYgEpDFGEWcY5GHcUhBSsExuYlxGrBuIkbHer3iYnNCVeRoIVO3HRPFUQlJnhvsYsWTy0dYKXnX7JEkfoNWKTCFmCYTWibRV9qHRryzqUN1E2pG0n5EEMwgqShmGmT6jx8TvuSspdA6m10883RhGpmsxnmFViGpv70jBJsuEVqw29/TuwmfSZwI9FhcTES15dCxGFcIIuM4IG3CKodJUeWGTa0pjKCcJ0RjDIjoEdHTR0fnHZ0dyad0SZsICKORktlKHJnGDq0UinTpL2JKMkPKOaBGJDurIGGzZWCyCcxV1SUxSBbFCRqFCYrz5YqTkxMWi4qqKvGVIhiBDRpPRM4aldGO6BCpRJqAWhtmDHfEhRmh7QJMHhFIYS9SI5TBZAUIeNjuiTJgw5jWfw8PxLaHpiNMFqJESU2Uc6piEGTKpAAlHzFCsV6sUFrjREAXBl3mFAR89CgjySbNallh7YJPXjxhGEdON2uIiVIopcZkJXlRzHkRGT5GTK6JIqlJnPe0bfvxOY8iWdM+xF5/+CrLgrIqgVmjNds8P0zqfq8F/f/wf/o/0vc9333zLa9evuZ/+Kf/A13bcWySjzcv8zT2EZKTi8esV8v5ZiwQ5h0QaUbHsN2z7Qa0MmRZSZ6X5EVNXa0pigWLRYnOCrTKEcFzuaoI0TOFiXYYeP/yW07Pzvnh2VkKrhhGmm6gH0Z2u4YsK/niBz9ktVpx071FSpmCI4JgUyzIAvi6RwJazAKeOVPce4vUOr05eYEqJJ5ktanqgrIuObu6wEXH6CcuK8Pq8TnSKKQUvH3/lu1uy5/++Z/SbrcpBx2ByTVCRuSosN6x3d9jMonWgjIv+cHnn1AWFUpp3r15R9O0NN7hJkczTBhtUEImxfhqkbqEGInRMdmQIlrnlKmoJOdXpwit+Pbr35GVGY9ePMEFT9M3rDYrPvn8E5r+yPXDDafxHE7W/Ac//R9ztTrll3/1c477Q9INRM+TJ484OT3l888+ZbVcst0+YMdUULMipzIVzd0t3dCzKHMylXFaFHgRWcYlQklMlaGMxhQZzk7YcWTqBg53Oxgm4uRoDrskhDNpXIdPBX2yjswk2Iub0iTAz6Pn/+q//q/4gz/4CacnpxR5/vHwHYYBIdLe1lpL0zTYKX3P2+2WN2/ecHfzluNh+zHW1k4W7wNdPxF8j+t78twhKMmLnGGokvUmWrJSojOVWPXBok1MvvsQP9oI+2Hg1XcvuXl3y9e//JqX337Lb7/6mrLIKPKMzcmaqio5u7wiL0vysiIIGGfm+tCnUV2WJ9xpvaix44CzI+tFRVkYpq7BTgM3r79l7Fve7+4Zw8i/+dW/ZVnXnK3XZLmhKHP2bcu+7ebgE43OS5TSqesMadRqnQUt5rzsNF3yMVJkKUdhd/tAtz/gs5FcGVaLFVorXrx4xqW1nD97zHHsebW/x1Q19ekFt3cH3r7d8u76lruHHS443DhR1Mk9oubLgYtpHfWwvfu4lhmmnn2zY7IdEc/nn37Cjz//glJobN+zqUtinjNsG4wUnC8WLPPEgS9++xtebm/xIdDsD5hMY4ykLjRGZZR5ASKidRov26HHeUs/dCzXKy5PzlN40zQwOptgOfNhLHSCZBkkSoEuFMpk1NWKGAW9HWn7lv3xiB1y3GQoihJjMmwYUCGjWKQC992b33AcOigNQ7DsbZdsVC6w2ZyyXJ1wvT5lUdYUQmCkZJ1rFkVOkXtWdc7lJse6wM71hDAR/EhvR4YwIZo9x5gojDFEsmWFiDElmI0D++0tWgoWRcFiUXN6fobJc7KyJFOSMjM4LfFSsF4tcAjcvsWHyMXFGXle88mzH5DJnIKck6zgvCgT7c9oOh0YZcAEiyXipWKaLPf7hlwkYprzkeOhY1QwaBhdxEbJoZ0Qg6UcPXmQqLymEAX6xNEPR776+ncIDeXS4CZHbCekC0jrOa1WKYsiq4gqoKJERDitNwkTbT15Zvj0yQs623PSbXAy4mVIcCAjacaWYRoQWC4vNlxebhBCcn72hHGaePv2HcFHYpQc25bt/kAlJVmRs1htMFnB+5tb2q7j5uYGoRTPX7xASEnbp11527bsdjvev39PCOnCvVgsyLLs40j/wwj+91rQ68U5Jpt49Fgg1YLDwXFzfcN3336Hsyk67vT8gs1mzYunT1gtFwiRoCOm2CWqmdagFUEkWwlK4AVYAu3YMzpPbx1SGbox4R1lCYiIjYnDfZwGpod7pt98RdcNWOeYJpusEEHhxsDd+xv6Y0td12lcWyYudCYNUecs8nIO7fAwdyzTNM0HdEAZTV4tEVLS2zGNtCXUi5poVHrDM8XgE24w5eqBqQrW+pQvfvwjmqahb9s5ScrRtS1t1xL8iB0m2mPDvbnjxbPnnJxsyOabKyHgpwlc4kc7n97IfhrJfInXs4kTCFoSlEi+c5hTf0bONieUdcVZcKhMs1yvObRHbm4bdKYZxxFTZJxcnjHmOX6YsDrShgmzrMgJHG/v6IaOh/s7FnXFk8ePOTnZpH1OurrjYtqzoSTKmDQamuxHwl0175nUFJEhoPHoKMhkRpEJvDSMvsH6mPbm8/5dBD/HZYJ3YUb1Jo9sVuRcPXrENE0slsuPtg+pJHmWinqWZfOtNnWWRVFgraWuKi4uLvjkk0/o2z2H/UN6/4PHOZ928UqhdZpeKGkY+gnnUgiFKRQmNx8BOx9YnXreVxulCN6xe9hxf3vPL/7mFzzc3PPym9c0hwPFrNTPlCZax9QPHHd7xn6gWCQlfph7wNxkKK3Iy5yiyMnzpMgm1iyqnCxTGC1w1uDGc6ahpN+nXfTt7oF+6gnRURQ5ta/YHxv2TZsgPUrjsyFljs/ApBgiEYFSOl0oxgnnLHYckSEiPdhuwI8TtunQUbJ/2BFj5PrhIdnoNss5BGYiDhKaA95acmPYrNconXE47pPIbBwZRo9rPNoorh6dpshRkRQkPiRXjJCwXC7I1ivW6yVFkWOPaZ1SlQuUVASlUAFcPyCkZFVVnJ1sePrkMYex5zD2iDgzIYaeGCzaCNQccSokc3QqxDxHS8E0DlibID/OfxApzfoRleBAQiStR/IMA6L9GOd6bHqOfUuwJcHlCF8mcZnSGGHQefJkj+FI7xqCVUx4rLCIXFMtc0wtkEVgP97TjA+clDWlyaiLmqAEXo04CZMQWOWxuUCqnEwXPLy75v3+gZ7AYhpYL5bkuWHyaWwvtER4mXbQ1nO0qWNfLuu0Hw4ZxFmR7z0iCpRKz+fh4YF903F3s6NerHl0aTGzfscokzpLOVPiZodHDGm11I0D02SxLqBkJETJMI7c3W/xucFXGT5IlC5xIgk3s5jsh3xYdUg9f6kUoiUl4zTxsH2gEJpCKEY1oaPCIJBIlEgOEZNX+ODojzu88wijiDJSFyVOBKz0CCMQCiaviEGzWS/I8+TMAMmiXmGtT+p7JFJo3r6/5th2MyyJOT9hTLqXGJP4dMa+ItMkuPpbtDhrLW3b0PUdjx8/ZrPZwMy9d9bOiNnfa0F/RBUj9eIRj54MPHv+U371y19j/T/j4f6O7cM9zz/7MT/64Q95/vQxi7ri3fuXHI97brb3eGeRRZYOLSHAKESuiVLgoqftDjgbcF4QAmzbAy54qrMKZVT6dT7Q9SPDwwN/+Te/YLM+4fLsKtlFugE7eKTomdqRPMt4dPWIqixhvSEvctbrBVkGsl4zjgNd3yWRn/N0XU/bHhnuUixjfXqKkIrdcY/zHhsdy/WKLlrq9ZKTy1OaoU+K9pBwmRdXF6yqMy5fPMV7x/u3b+i7jv39A/d399ze32KHIXk4vaPrGz598ZzHjy8hgHcpP9F2HViL8J606gwE2WHqEqsTalQKibcKNwl8ih5OZLKu58WjJ1xcXqLrgiDACserd6/5+W4PSlCuavK65OlnL2h2B8aupwkOOxwpLtbIuuD1+7fsDnteffcN5ycbfvTDH1JWdRKOmCQcGrzD2UDUCqMKnHUwWUpnUFqxKDLwECcL0oFxCQBRZKiqRCrBvYu0PmLyDCclNnqC46My1U8pLSqEwLJesFzW/ODLH/L8kxeIAG3bslqtMJlhmWcYnVYTzjkOh+ajNeSD5/OLz79gtCN3N2959/ZVirVyLq0YJofWOXleoUyJd4G2GWZkY8Pp+YbzaoESCZ4hYgpgyUyBMYrcKLqu5as3X/Htb7/h//nf/ncc90d2t3tOVmvOT07JtEqoSmcZp46xn5BaU61aTJ5TrpYorVlUVRqB1iVZnlGUOWWZUxQZxqTOcOoM3o7UtcaOPbtbgxtHXl2/pcwz2rGhrirW45LdoeFwbBLaWCoOKrk6ztcnZMaQZRpIaNroHMdjUo4fj3v6Q0N3OLLKqyQ4awfCnGMwDiO/ffkdOs/54z/5hzgJY9fihh7fdUDqkh5dXnAlNd+9/I6H7QPX9+/pho7tcU9WZFw+PklY5RmKFKMjkEAwF+fnXJ2cc35xRlkW3F7f4fqBJ8sNhTKgO/zkGA4Hsqri7PKS548e8ZMw8t31W8b3b7FuxFtHczgwaEG9SO+Z0hlaCDJjQGjyQoOIdG3D5GzSOMwCVZVl81g1RyjNh1iNYbREJhg6hnF+zbqJth0RYYGgImiFE5bCCDIp0ZUFAkN4oHV7xhGCFvhMUq3XrM5rtDEoFbh5+57j4cinl485qRecGkHIJU73TDrQyYAzE2OtqOqSxcmK4907fn3zmnV3oK5qfvqjH5HVNcPhSIyOujAo4QkiYu3I/rAnRsdmVaO1hLJAeJe+gkSIgFIGrOf65Stut3tevr9nfXLJ0yc/pNAlVV2jU9BiUpApgVDpvPLjyGQ9u33DOFlGG1Ba4KOiaSe+ffkOvazJL05wUmKKBdPUMrqRDJUsvlIhpAdpQCV6pFCJQdKPA932wKZccFqt6EIHU2CZp1AcIw1KG7LNCdM0cvPufVLITwPVqmJ9dYITnglLUIEgAtYrRFRcXZzgwwo7U+y8NUQEl48ef5w0q7/5BW/evSMI8DaktMgwfASUPdzd0fU9dw8PSaAbA2VVsd1uWSwWvHz5kucvnvPs2VOEEGRZloibCMZhnMmVv8eC/ujqSRIBOMs0Wpb1CXW15OL8kuAmvJ94/uwpZ2enHPcH2ubIty9fc3t7ze3tLd5b7rYyRYG6gDGaokjCuCwviVFClGhTIKWmG/pkz9k5goh044AQ6fAkwmq1ZrlYUZUVdblEIhEhOWSVSKrDi/Mz8rkr0irZJ+w0cjgc2O933N3dJJ9xDOmB9zalYYsUs4nwyQuoknI1AO9vb1lMPZP0VMuKyyePkUYitEgQGqOxNqXPXT66wk4Tp5sNT58+5bNPPqHZ7rl99Y6iLKiqip/95Kd8/umn3Ly9ZvuwpesTkhYAxZxk5RjskcEaJrtPnmRjkKrF6B6jOzLT8eUPrvjii8/5wScXbE7WjMwRk0Li3Jovf/AJzdDx5tXveDju2LYH+qbDDpar8pRaFeRO4YaJQ9uQVyX/q//1f81nn31GkZcIIZkmSzcMNEP/QTo6j6s9/XxDPYbUZX5Qzlo3oYwhK3PK1YJqsyIrTPp7BEFucgqTY5FokWxrhUmJfcGEj37/4D12smnFs8rZ3W05th273R4BrJarZOmbeQAfuPIfPOtN03J6esaf/Ef/iLrO+Qf/4d/nn/+Lf8ntzR27/Z7q9pa2bdAiKYvt5GkOHcM00nYd798bssJQ1pqsVNSrHFMo2qOA6Nk+3LHbbfnrv/hLHu7uaduEx60XVcqoFikTPs80cfAEm3bF3iYymo8BmRtMzFC5QZIKTVkU1HX9saDH6IjRzdnuniwvybOcMjeMQ8fN21cEIrum43a7Y/y6Q+kkPqrLpG8xJrkUjn2LGgRd2+CdpR+Tovz2/jZ1qOOAjMlW/+jJOc8ePeabX33N7u4emUmMNKzPNug8R+cZwzRyc39PkBryEiknlHRzYpUmBIfWKetZS8npZoPJTCrI3YCMkeAdduzJtWG9PuH5s0/4/MUnGBs5th2bs3N0gGM30IaBqqxATDxs95gY4XhECcnz8yumYaBtjnSTYnAjw9QxDZYQJ7QWTO7DDr9EKYkyScfggp0T6pg7TpnGqzic75OzZHaYKDPrW7QmSEUmNMFALBTBZ8SgCMIxhZ7oW4Q3NK7BEmhcw2E80I4TxbLm9PSKy8eXvPj8C/K8IstKXq8X7O63/PiTTzldrblYLqkyQ1VnKB0ZXE8UDlUayCROBi6fP+HvG5WwxCEiioyBiCwKVIzImPLbZVGSKU1VJmslOinNE+AukRJNZtBScxwHmqbn+t1bbu633N4e6HvH119/zfB45HR5ip+75xgUMSraydJHx/X9Pce+Z3dsiVGwrjfUWYnMJEFFejfiW4/zPVaBlcznqsS5wOQj+8Yz2cgyzylM4ESfEIUDZSkqw/KiZFMtOSmXFDLDCI09NPTDgKk0eMHhLmlnvv7Nb2j6hodux+PnT/jpP/gZi9MVi/M1Lo64YNkdJ4a+RRiBFODsCCjKeomQGkTi+u8OW6wbKcsCpqQ/GG1ikZycLFmHyM2jO9quSxoGpciKktVqyZNnT8myjCLPWdYLgg90bct+t2O1XGCMYb1e/f5H7o8fPf0IxXDW0Z+OfP75D/iTf/QnLBclq0WZDnAi//x/+Bd8/fVv+d233/Hy5bdY1xOCx9oB6zxtZ9EaskxS1wsWixXa5GiTsVysybKCwadd6TgmbOjd7oHMZFydP6IqK042G5b1krpesFmfsFqsiS4lWnmbbB0nJydopXBT2sFG75jGkd1ux/XNe7777puZ+QxlmZFlBp3ns0gqMdSjkGmcWua44Hh/c001NPRYvth8waMXTynrJDILwRKC49gc8c5S1zWEQJwcRZZzfnLK7v6el7/9hkW1YLVY8eTRYy7Ozvhr95d0XUfXd+yP+zlGVKI0uOAZ+pZhUox2ByonUzlKtWjdYVRDbnp+8uVj/ujv/ZAvP0+84G17TPt1oTFmjRWf8suvv+Lnv/qa17fveXN3gx0dwUb68+esiyVlyAiTY980XJ1f8r/53/43bNYbiqLEOs84TXRdx7FpMFmO1oZxSPCKw/0uQWf6MXnmpxHnHf3Qz3ulFZuLU04fOYpFSV4VCCMpTMGYJVyuFhIlFVVRpxVEHvHWzRqHwDRZlssli7rm7vqO3W7Py5cvaduWekZjap1gFhcXFyk4I8uw1jEMIz/+gx/x5Y9/xB/87Mc87B+43x9p+r/kYbtDyZymOWJURi5hHCz7/Z7D8cjt3S392DOMPatNRb0o+eyHz9mcLPF+ZBh7fvGLn3N7c81f/tmf4qxLOeI6Y7GoyE1GFAFtJFmeYd1IGsi4VDTmgq6GBMvIfYEQkJm0713WNUVZkOcZ09QlEZHzTNaxqGryzLCoL+nbI/vDjrHv2DZHbm6u+e7bb3h0ccmjy6uPwj0jkv3u2DUE73n3+hVD33Fs9vR9x/32NmlAYmCzXHKyXvH0+RV/+NOf8HD9jt32Nk1rguTk8jSlyJUFbhy4vr0nSo2ulmg9obUlCk1E4WcrmZIikQHXS7Qx2MmmNdhksdNI2xy4Or/g5PIJL158zs9++lO++dVXPFzf8vj5ZyyKkt/861/ghonPHz1LjPGuR1sHeYauSl5cXNG3Dcf9lu0oaK2kG/b0Q8s0pYJWWpOee5NEX7kyWG/pp+GjhVJLjRSa4BPkZvJTMqCoFONckMSNRkqiVGQyhUTpAqzXWKfxWHwAGwzRaY4uPZuH6cB+3LMbG84qwfp0ydMXj/jpz35EXa0oy5pNXfBwc8cfffkHXJycUCmFjAHX7gl+YrAdwoCuDBjFJDyPPn3Kix9+zv3NHcfdEeEiQwwsyhIjBDIkn7MqK3QJ6zm5LypFkApPOvsQEpMZpDbcHR5oDjvevXnF+9sHbnY9h0OHyU8JNvDps88IeYHICggGAhytpbEDb2/v2B8bmq4nMzmPL59SFxUql0QV6P1Ec2w47ixWJpDO+nRDVZdYFxAusDt0jAHWp0uMUpwuTvF+ZJyOnK7WPL14xKZasimXCC/BR94eW/q+p8oLIpH9w46H+3u++upX3Nzd8KtvvuLHf+8nnD0+5VmdcbV8ymQl1gmcm+i7hmpVJcS3nRBSU9UlSmdImbPd7XjY3TPZkbL6XlDow0QkcH56hjIZdw9bmrbFBY8xGZvTM07PTvj8B5+nZiUkYW0Mga5t2G0fKPIMrTWbk/XvPw+doUWKtC/UKkXipS67wHvLfvvAn//5n/PVb77iF7/8JTc3NxwOR5Q2jC4JrKY551dqQVEVnJysyfOcPE85ydZNTG5IAjKhEUIk6pKL1KIilzkLXbGu1jy5eMKiXrBebRjHiYeHe8qiJDOGxaaemeBJ5HJ/d5cOqft7rJ0Yhp5pGqhWdVITSlgsavI8J5JUhe0wpQz1zMze47S7/sASj0A/9Ox2WyY/UrgCY9KObTVbr1ZlnVS944SWmmVRc1KvudhcJsh8gMViiVA5Lz7/ISfnVwSpub254bvvfsvhuOfNq98inGdTCJZLS24eWJcVp+sF5gS0LGmenOGs5cnJgYKX9HuDH0usj0w+8NCN3Gy3/Oa3v+PXX/2GX/7rP6edBoZpwHeeMAWum8BeV2hnEEEQB4v3oLOCvKioqxXWOZQcCU6AU2nvaiMrVUNZU5/kuMnSN22KvjwckDiCURiVoWWJHyX9bmLsPNL0rDYLijKjFAVGabqmZQoj4yEpojNtEilOGzKZkemcoR3ojz3r5Yb1YsNquaZrW47HI9Y6xnlP9/bNO7LMsFwsWa83fPriU1aLNc56ptExjY6z0wuePX1OexjY7x+4u33HNPTgk0f49vqecRzp2m6WLkS644QdDtyUgm5Xsd3d0bZHfvmrv0nhMi6gRaJkSSKTHQjR4aJG2jR1sCoQC0VemtngqkCnZ0NIECISnWNsO+q8IFcZthsZji1aJ4X6+fqSGD3j0NJ3jr5LfPTVyRPGqgO95ZSMKApKo0HoecPg8VnExsDd9VuGruX1y28SwtaPTOPEfn/ATRE7wPrLBc+erEE03D18Rzs94FTHT3/2x1T1ije3DwSh2Fw9pR4f8x+vT2Y9TExriajScxUEv/vmd7THPZvFCl/VPGwfiEQ2J2sscJgmMqNZVmuuTp7wxYsvyVTN7fWBtg1Yp7nd9zS9RyzXqNLzfhwhRlaff5qChaaJcrKUh5ZPF2suvvwDfnn7ktf7W6xckw2G/X6fULSTxUaP2EeMURS2QCgJOsV6BmfTeoW5sCmFkSm1LMykx6k9YIXENgaCIncZOihM1AwhpSU2g2UIE6ebC7L1gtHA4DydiGTrFf/wR/8BF1dXfPmTH7NZbyhlAb1laHdc1isuntVUCHzT4rN0NhbaEJQAJoL0BDfQjZbtbqQsasqyRhrN5vyUqZsILlKUi8RTGCey0vEkXxCsxfdputZ7D2hElDipiVrihcT5wM3tLW/evuerX33F3cOOaCr6bmKyv8Qow+4Pj0zeMUTPXliMNxzGnsFZiuUSXVWsRkemNZvNAnzgm9cvubt/oPUNqsw5W55w+3DPdveAUg5cxWaxpsgUt/tbch/44sUZyzrj8aJOhvY4YIeR/X6HcB6cTyQ6H5G5IF8VvLl/SwyRy8tLrupH/In5T2jahp89/BHlskx79fbI7u6GKQy4MLFcLigXBf3UYb2jXlQIqUAG2v7I++tv2R+OvH9/Qz+MmEyRkyFmvrv/kJHuPZcXl6yWI4djk6aHIk1P2kOL0unimGXpcnk4HBmGgXyOWXY+ZQr8Xgu669oEVinLJFhSkdwIqsJwOA40xyN/9Zd/yT/9p/+U71695HA8UFRJSRsR+CBShGmMCCUwec5yvUHrBNr3XYe3DucnVBBonfCB2Ij0glLk5KqgVAWLvOZ0dcpisWC1WnF9c8PxeEBrhck05aLEGMN2+0A3dtxub9nvd/zum98lvGeegkHKqpwRoIJ6saAsS6YpjTLppgRKyJIfOondRRLPyDRqnuzEsTkSVfJi1nVBlhmqckGRZVyenqOlxM/BJrnMYCl4dPGEvuvp2g6tEmbw4uoxF1ePqNdrdvst/+yf/be8f/ea2/tv8RZyrVguAmXWsawkZ6ucVZWxKA1uSnjAs2VPJm8ZO4V3BV4VSfCyO3J/c8frb3/B629+y+tvvgKdxlm+9cQxsmsEUhQoa1BoluUC70EojdKJhqWkBy/xWcSbFFzjraMoCrTSlOS43HH0ilGOjO0E0eKVwCiDEhnRCobGEuVEFJHS5OTSkKkE/GjG/bzPnlBSJURnXlAsCrQ0aGlou4a+7Xjy5Anr9ZqiKOm7jlevXqWAGO8Zx5Hjbkee50gkpyenXF5cUpYFfh5VuymwWq45P7vg8PANbXtkf9jivcMNga7tuL6+wbsU1mNMeuCm3jP2ke2tZmhy3r57xeGw5+Vvv2WcRvI8BY5olQJ6rBtT4I/waK/Ap90iSiQxpJAz5zxtMeaPFzF47DASnccIxTh2dG1DtSjJc8NykW7u74eRabL0fT9z0U/RWcXoIlFkKFUQpp44DXPco0/CVCLbw5bDfsv13XucHdFynsB1A2MP3TF9LxfnNUIMHI43jP5IVBNPP3/C2fkVvFwwBUG5vqRGkF89oesntvuG4FIewYds6DdvXuLdxHK5BODdmzdJsJiX6SJ9bFguFlysa06Wpzy5eoaIsN91jFPER82hmximQF4tECGw3e5RSnHx6ArX9xzfX5M5j3IjV8uK4vKMvT9y9C2dXEAh2DdNwtz6iI8BgUtsezw6z8mzOsFerEMEjwzpEFak+FdkGs2HGJiGLiFXgyYTBZXaoESGJksi2xgZp57GWk4zg6oLrILBRyYpyKoFX/70D7m6uuKLL75IBPcItk+F6nS5ol6XuL4j9AMhGKKWaSqIwAeDm0Eww9Cyb/ZMVYqx3WzOqcsl0OOsJ1ss0VLhxIACFpsL7DCwv7nGTRNuGJAiiQwRClQSpPkY2e333N7d8u7NGx62B5bnjxCDY3fwnJ9fcey6xKHQoLBIr2nHAesdy+WSUmuEDRitWNQ5XdNzfX/L7rBnYqIuSjanSx4O9wz9kcEIdLSo5QKjFft2h3YBmUvKZcnlZYFWEa0cN++vuXt3jQIUAuECuEBmkgj34eUDzjqefvqUolyyPF9hnaUZjhy7I7fbG8ax57jf4rB4HMuzFaYwvL8bscEmK6NUhOjoh5bX717RNB3b7R4hErgpQ4DQSJUsxQAxRE5WG6bKEX1CdEshIUTGfkjWzRyUzMmznLZr2e8nLi5OMZkixiTW/b0W9P/r/+X/jNaa1WbN02dP+U/+8X+ClKlYR5In89NPn+PDP6L5vzccjoePWbjJuO3x84dEmwyEYhwd42QT3o8403cSEWl7f4/3kTI/odA5eb2gKApOV6eUpmLsRmRMubNKSE42G87OTqnrikCgGzp2hx3H45F3N+/m/OQKYzTLevGR4JVlCSe6WC4pi4JxtDN6DyZracYhKY+DJa8Lnjx5SrmqWJ6vUJlMqUnB0bcG3JJQFGgfCXkOqxOkEgQXmSbL7rjFu8A0Jvazd56iKMmyHGR6HZ1SZMslf/wP/0P65of8+IvHRNeT03F5uuAPvnhEWRuqRYZxPdoNBAUIQVGUKGWw9Hg3Ym1P1w68ffmar3/3hn/1//pTjl3HeZnCIsbRE6eIt2Bkyqn/4Q9/Qm4K3r9+xziM/MVf/BVnJ6c8f/ycuqw4WW4Y2p6x7bCjxVuP690cLZsuFulSFNGmQGcly41GSIkwybJyPHSMU491E0VuEiI9S8z/qU+KTyUVuc44XZ9ijKHIc5RUeOuRQpFlBYf9gbbpyLKMsqj46U9+li6f3jONI/e3d8kfDiyXqwS5adJao2/TASeFnFGkSUUPjhgtiIDUgbLUTFNg7KakzO4DeZ5jtObu+j0hBt69e03bNUzDiCCmqYKSie0e0p488dgloxuZ2olhGLDWzTQwnbqysmKxrCnyIk1uRBLdDf3A9ftrYkjpdkooMl0g0UghWC7WFEVFvVgiZOKwj9MIOqc97olRMh5hHCcOx47jwfPs2QvOL844uzhhGnoevvyCoW/Y3b8nOEt0E0YpcmN4/uSMs/MVZWEwBi4fn1EuSw7dAfcgWJ5tkKak2FzhoiQbwGQFZb1iaFu643FGcAqWqwXv3r3n+v179rs93sHQObp9eh9PVmecn53zw89+xKOLp2S6Qs8pVevlaeK/t8nyw8yen2YITqckQUrsTPSqEGSTRTeBF6sNRW2oHwwP3R4dbFLb+xHnPF03EqSgkJp+cuzvdrM9lHT+aIOQOVJlM/s9MI2J0xCJKKETLCbkKJchVYnUJdtux0N7hFxTlQWT9Bxdx/XxDpFl/MP/7E8wecHVJ0+oy4rBjeA8WE8uJFWRoUVE+IlMJVvw0LdMAoxcJmCOVIhoEBjq5RnPLh+xP3TsDj0H3zDknrJYUpY1oxNMMaJUmkb2SERWUl8+Bu/ApsCSXXNM53KM1DOl0YlI1JJnnz1lcbpMWe9TpD8ceLi95ne//YqsLskXJcWiJi+L5NUXkCmBzHK0jwincMcOxpFVaThZXvGTH3+OyDQiz7D9jsP9W3To8d3I7TvPNsI3b35LHEb++3/pePronP/0P/pDciOQfuL1y5f827/5OS+ePEM8e45BolEsNyfkxvC0f56is9sd7WRYLGrQUC5Kog5Y1uR5lpoBNzKFEY4SNSrevH3PsT3STUnY97BrGUbL7tAmXokwaDVPbz1ImSilUgqkygCJlR6lDZ9+8hlSpQCjOF+qyzJnsaoTYvp45PrmHYfDnqbds16v+JM/+UdJ9f77LOh/8Wf/CpMZTk5P6buGv//3/wjvA23fp3QdYyjLnEePH5EX+fy70iGfivr8cyHQ2sydOzN4PoUCpLFCJATPMPR4F6myU7TUVFlJWVTURbKieeuwyjIOQ/I45wlkUFYlTZcAL/3Y0w0dTdfinKMoMvIso6orrJ2YxpBuVXk2Ay5SHu8HlSEIYp/EecKBFJLVek21rFiuVoxuYLQDgoB3lipPEJpcKjQiIVFFJPq0B26bFjt5+t5+fH2iSIGDUc7XGilRWcblo8cEu+GsFGA71LTj8fmSP/ryKaZU6Eoh+wNibCBLN+mUoxvYNhMhJAjKNHYc91t2d7e8f/UWoQRlYQhTwNqIcIBPBb0wOY8uH1HkJbu7LSFG3r19x9iP5Dpns9xQqJSW5CaLt8nfar2FmcgGzBhRUHPka14WiXYnIj6M9H1P17dMU0/f9Yx1iRDZrHOYRTxSoKSmyPIkdJOKNOFM/nSlFOMwEULPZnNCZjJOT8/SWFRIpnGkzJNdbRzHZGUjBbX4KXWhcR6JCZG45+lSkjzlQsbkMc4kKejI451NSniZwnWatmUcR3bbLX3fEZxLUyyVONTxA76RxAlPfuuE+Wz7lmmakDI9C8vlKkWw5hl5kaduIIrElPeevus+IielUCiVxq5EQWYKlDKYPE8TJyUQyuBiIgxmTYMfeqzUjENHsCMmy1mu1iyXJcFbNuuKvjvyLoPgJ1QYKQvNepElulqmkSqlLVbLEmE0k7fEsWezucIUNUVd4dB4I6kWK84vHtEdjxx3W7SU82vWUJYlQ9fRdz3BJ2uidwG0oCrqNDU5v2S52KBVimQ2Ss9wo4w7cZdIgNOY7IlKgRRY0hg8ijRV0xGk98jBsalzVJaxm3ZELM2ipDPQTZFxsrSdJSIJItENh3FKO2QkWgmMkAlLyhxzGZOXOQSPVCD0DJZxBhF1Kicyw7tAP4yIMkPnGV4Gpmhpxo7cSJ5+8hyT59TrGi01k5uIk8UPU2IFZApBOiP1HLM5+iTY884R1Qz0igIVFaUp2SxXjF0kTC2jmPBOUuYbtMoZxxRWgkprEAsoqclLlSBJPmOwE2NIbH9BoCDBkoRW6Dzj4tE5WZlzvx2QvadrkqD4eNyh3YC2HZWbKFyFEmkN6eoKD5ggEDIQhhGcJVeCuq54+uwJU/T0wVIZiYqOaD02BBpnET5yaHf4fuDV+1dEBvbNC0qjMCFpXW5vbxJ/4fQEg0ILxenpBpUbFqsFo9EcmwPKjRR1nqYtRqKDoSgLlEnnlw9Jn9IPA8LCdrdjd9jTDD3DOPLm/T3ORUIUZFlBVa8+QqDijBFPUBg5C3PnkBmpWNRrtNEUZY51NuHLlSbPcoZhYBgGjodD4n24kf1+wT/4B39MCMvfb0H/3/3v/xu0SrzssirZ77b8/Be/4J/8P/7bFETiPGdXVyxXK47NEZNn6ZCLEa0MqtBIqVKHvFqxXC24uDifD1LY7bYcm0MqenaiLldonWOkTgc9gTzPePHJC6yzHI7HjwSw88sLzi8uEk7TO+w0MQ0Dx+ORpmlmq4nh4vQkMa1V+jO9sx9H/tM4Jdb7bDPQRiO15syoxNHWgtXJikfnlxSLgmpd0XRHjq1H+IgIgYd3tygpqD79FClz2vs9g1RMw5T81AGU0tR1PofTRKJQTOHD3UfghcLHSLtrEXZkJWq6puPrv/oF70zk/b/KODmpuLxYcfXknIurDW4CLwNeFzgi+3ZgmAJCFNheEztNHkqers44tD3b65ahj4wDaayO4JMvnnP56CmfvHhOluVMff//Ye0/em3N8vRO7Lfs67Y77tqwaSurWFX0RbHZJBr9CRpQa67+RJpoqIkAoRuayIADQSDRFBtSt+hRzGSli8yMiGuP2/a1y2mw3rMjqVEN8iYOIvLGNeecvd+1/uZ5fg/eebruRF0VGKN4eLzlq1/9gsvNJVcXV/joCDGw3e0Yx5Gbm2cURUG9KvP+sY1M3vGwz+CZ/fFA12Wr31MSWfXeMk4tP/zB91k0NfrFc5zLD2iKnsNhn1cpxswPyFMmevZ+IyRtd6QfWsZpyJQ2MuHsaUx+dXOF0hlYM/kJ5ycGPxBTwAef7XYwg1wsdV1TFXXGNLYdQxc5nU7z+y2STp6uUzw+3tN1LfvDnhA8VWVzZ06cM7A9CObwhTwJktEjk6RpGsqyoixqClvw+uVLmrrJ7ISZN25NQVPlmNeisDlONQaauqEqq+ymiCGTFoXCKj2P7UVek5QlSkimYWBZlnB5xePte9rjjkM78vFux/X1krIuubzcEPzI5eWa9rjj9u3vCG7g9v7APTskkaooKKxlc/GMzcUGU66QumAcHaPvOLkt0lQUiytOp5bb259jlMAoydj3uGEgpqwbOc48/ikEpNG8ev2aRdNwcXHF69ev+eGPfkxTNywXeTJX2CL7oeY5ZiJP0EKMXF5dZo/zMKCCp1416GFibAf8NOG8Y2EWrGzBIVi0tzwM4MfEJA1YzeVNDjHxSVDUDZubJcM40Y+OFKEN4NoRLT1WMNPb8ueiK4tIFoclCoOWEhc8oTsxeEcgoSXZ36wBnXDkJMJqs0AZjRMD/ejoDy1j1zMcTlyvNlwt19ysNiyrmnq5wmqDUHm617uJOAamoUeTqKSkP474+x3JSy7lNd4popcEK3EuZ5vHmOjDMPMOJIKIDBPBTbihRUuor9b4cSR4D9YijeFHf/zHfPq9L/nBT/6IYZzY70bGIbDfOZbrC1598gWHruXxsCe2e7rTjugcxMSiO5HqGmtrMAbhHcJ5xMM9YhoQi4qP79/wn379C/7Nf/j3/If/+Jc0qwVlVXJzdUVVlty82mCV4vWrl1gJ/+O//Bdcrpb88Zdf0A0DUms+fPjA/nHLx7fvOez2/JN/9I/47JNPaWxBDIE3b7/O++pCgxSMvs955FpgCkuzWhB7QRwE33z7hsfdI//hp3/J/nhgsVlleqjU2ELCnDo6TZ7Oj7hpj/OZodAsspC4qvLU1PhACIHdbpfPkeRpu46Pd7c0i5rNxSrfXSHnSGiteXx8ZLvd8m/+9b9ls97wX/39f/yHu9AvLy+QStHU2Qx/d3/H27dv+PVXv2IYHeM08UnfcXV9g3M+d0pJnw/KmNKMi7QsFgsWzYKmbmbgfUKbE1KqHDvnAtRiBvvnsY+ai4GqLJFOofs+j0nn6NO6rjmeAtFNObRimmacpzsrn21RZIhGerJV/R5yMwRCyqHyQLbRAdYaogAvM9wkx1nmHZdIORrvCTQyDBMuRZLL+5tpGOdu0eWuNWQIglQ6R/FlqG3Gn4qclx2FICJwLiBdRCcFU2T/ccsoPHormLYV8XDACEFZWChN7tJrlTn3XjBMCTcOHI8DQ+vBCVbVAtcntmOLmATSyRm9KqlslVXi8/dktVripgk/+DmQIjC5kVN7oq4yUjTGQCQwTgP9kKcVct4NR7KuwMffm5S0xznApzv/PcPY03WWFANSiHm0LmnnnVHG286vmUgzNlTO0btzTOLMPR/H4fxaPgUdGJEDP5TK75Uk4nzhzvnWIe9Bn6I95Wx3a5oqY29/j9n8hGCMwUOCrmvndCT3e5+PmMM9cqUvlfwu0EbmEbqIMcNopKSYLStVWWUtwhxGo6TEGENdzz7aGdwTQsj/XSnGiVxgzDTD35+CIXIiVM6mtjO1EGxR4lzFMDqOp5blKsc4FlUNqcC7HqUk/WlP3x5xU14NRDeSAngfubjS2KJCqAzaGMeJKBPJW6SFoAaGwbE/tBRGUxWG9nhk6PuMWQ6ecZwYxxxnK61ltVqxWC5Ybdas1mtWq1XWTpRlDkzSkuizjSzOSNo0F4XaGETINiHxZCPzIU+9Qp74SR8xLrIQlkGV2CiQIY+rM9dU4mPCO4+QhqKoSGhimnLw0tx1pXlBSEykKOc8bk3GJs2gEUTml4d4JhvKmcckjULZXHghQdkcQpJkwidPP/X0w4lTu8dIgRaJ0mRU9aIu8/RF59hiN8dQBx9y0h8Cl3LIi9AGY4ocKZ0EcQIv0hySkgNNso3S5uCXlM7ZAtJqhFaIoBAzhTKkRNXUFFVJWdc4F2kvHdMUOR0CRVmzXK8RKjGMbQbyOI/zOQaaacwBTChEDESl8dPIsHtER4c7rGjv77h/8y27D+853t+SfI+vK0otiL7hcrVmUddc3GyQ3vHw+AEjBYfTiXaelk39wCke+Obbb3i4u+OLTz9BkLharxHA4XhAa03btyBgcD26MFSmyoXwfE5IZei6nsftnoeHR/bHA1FKTFGgi2oG2ohs7wuecXQMfXauhAjGjiilM1I8wjg5nPMcj8e8JnITp67l8fGRYexxfgaYCYgpR4sPfU8IgXdzlvpf58df+0L/Z//8n+Vs6ZAznB8eH+nHAa0VNkUSht/97jf88qtf8umnX/LyxUv+9G/+OVVd8/XXX9O2LQ+PDxhjuLy6AhLOBw77Pbvt47zrTBS2REnF4+OO6BPL6pLlYs3N925Yr9e4ccJazevXLynLkqqqMIWh63JnH7zn/v6e3W7H/d0dznvW6zVa64wFHUdOpxNG59CFJ7HBOA64yVHXC5RSPNxv8TGy3KxBQDu1+DAhtcCWhnJRwBy5eHGxplnUPI7Zt8sUCL3j4PZZLOM8CJmTk0yBLfOlHRJ5uhHdHPsnsGUBSZG8IE2QfGLcTXz86gPrQnH9csPXb7/l3z2+5+bLF1x98owv//Qn3HzykmdfXKCriil2bPeP/Mt//j9x3LWc9hNaFfz40z/lrfhAdxdZNpLQyNzNO8/UjRwe9/zl4d9RlBV/8kc/wWjD2Pcopbm7+8hqseRv/a0/YxxG2v7wXWa48HgmPty+y+xhkQu4KeYLaHR5BWDKPKlp1s28Dw4IAeM0zGCLvJ9OKVFVFVprlssl1uau+Sn282k0tV6vqcoy5xCnnGufUuJ4PJ7ftykltP4u21vpkrIq+fbtt3z48IFxGJFA0+Rs7cmNxBR4/vwZhbW8+fYNEBmGbkYwJoa+m616w4xqbNBaUVYFiETfD+QssURRWCpTnlWqOSd5ngiIPOaXZPeIUTnRzWpNXdXUdcPmYp395lOOzS1nZnQI+flxzuNmG5UJmc6ljCKRqV7j6PEBdg87dne3XKwbLm5e8fHugTfvP7I7HlmtFijzA0qrUHbB89cX/Omf/0129x9585tf0p8OdKc9bhjx3tMsL1isLtgeBvqx58P2kZAUxeKaYQq8vft32KJiubpg6Fv605FxyDkCT9bX++2WEBOvXjyjKEq+/8Mfslqtubm54WJ9QTn7olfLJY/bLbvbjzR1jdUmh2YMfeZep8TxlLPjLy8vwU2k3R5Za2xRo4cBNQz0+xOH2yOfvXzJpxef8Itv33N0E6UxBClwRiNCoA8DIQi600RRVjQ3Vyw2G6pmkYunGJkOLW4Yubv7iA8+Q2OkZkgWkQQyeQbv6SbHozuxCz1VqrGy5PmLZ6yeXVNeXmSbn5Yoo7F1jUCQyp6xa9m7ntNty5t3b7hZb1jVNdfLJU1V8vknn1AVBakIGCtY1itC7xnuWqZ+YjgONJsLFhclweWEykCH0BPtlO2RQiXKquDZy2usEmgZCNPINNRMXcfYtSjydOlXv/gFu92e73/5Peq6wU85w/zm8oKEYrpRSKWxtqJZaC7XFVLkhmc4toRpYllUGCkRwwT9wOGQ7WP/+n/5n1lt1hx+8mPuHh8Y3r+hGk+8rA2ndsdhf8fh7ltsVfBf/uN/zLMXz/kv/snfp5Sa3W+/4P79B/7dv//3vPnmW37+05+xbBpWTcO3777h/vaOf/r/+Kc0VUlTlFRlxR/9+Ic0i4YhtLngt5b11QXNxQIXPIfjES9AG8s0Rdp25NSOHI4D3XiLMoZ6vURrg7bVOZFxGB39MOJ8xPvIbp8b1HGKOBd43O5wPkBSxBjoxx6lNUVVst9vefc2PG2oMYVBGZkTBr3jX/yL/xeQ4H/3v//DXeiP28dz1zFOGYYvlWK5WgKZcdyPI1PwfP7Z51xf3/DFF19Q19kb/ET00sawudjk9KjgWTYL6iqPD7137HaPxDbiJodzgWWVO+miyD5xpeTZZ1wUBWVZkkT2hw59T9/nvewwDmczvrU5lzfOCEfvPUrmTibFdD6ogbnLyrv8J89uTBE3TfliP50YJ8XoDdoojFWIzYpCG0pjc1DEkyo+fffPNFfACQfKnat+HyM+PsWqSYTPdb4xBSoJdASFIoyBKCUiKFKQBCdoW4fYtay2J0RzQl8OlFGDKhGq4nScOB1Hxi6r9U1VUtsFF8srhLagDcrsOPYDhSlQQjIM4yw0zN3/arGYFdeCsswYUu8mfPTIjIQiiVzYDGM/h6jkkWgUc+UfPFIqtNUorVBaE4InBo+Q4L2jPZ3OAJmnFYnWap6gML9GYe5SfR41zzvq+Zt3jhl8ujyffj/M/uEpe0Njiuz3e3a7Ld7n3PmiKNBKMw7jHHko5o46zZdQXis9FRT5cnp6f+UOWht9XgPFlPUTMcZscUrfxcqS0rljN3P3bbQ5Q3G0ymsgozVaaWKIZ/QoPHXl/rs4z5jmC1wiRUKm/Pc553E+zBhVMaMyNVIZpCmQCQ7HDh8j+0OLqyxWJopCoW1FtVhzef2cviwpi2LusgcQCh+Y8ZuCcTwwuonjcM+pm3jz/gFjS5rFkaFv6U4H4pwq9wQhGoYRBHn1UFUURUlZVfNKr56tfFny772n7/vsGpi1GrYsMv1vVppLIc/ffyfnfbdWBJ+IeEJUJC/RySCl5WJxQRci79xxJkGCiwE3elIQyDShlMVkJS9CqqyFSWTVN5KAwpMgSXzM8cwiAFNi9J4+OProGQlUhcU0FeVqRbVagbFEqUgyc+FdhCnljyAkwlgEAQi4FBj8xO60Z5xaLi6WhFiiBBihKIwAGUHmtDNjS5AS5+cpQQjzuiLQ9h0u5IAdocjJcklAcDNHY9aKjCMyJURMOWrWefpTiwxQ2AopNSKmswgzo14T2kiq0uQpJqDchBeJQgu0YC5zPSFOiOhQIiDChOtP4EdKCRdNhb/ecBg6ejcxpUyYbGpLXVlsoam0RV1d0R+PtF3H4Xhku9/jnMsBWX3H5Cd2+y3dSXO0GQH+6WevkFqiu5lXEUtq15ydSzFGpM2ajSTErAfKAWLT5MFHgpAorbFFXneRBOPkGUZ3jt0WwgGSfsj32G6/J4SYdRUx0PVtnhyaDFvyfkKbfD7mMKDE0w3fdW3GlP81fvy1L/TtfotSirpuaJqai8tL6qZhtdlw8+w5z5+/4PmrV2wuLqnqJcZYTFEgVR4xhxDYHw9nwZnWCmttjoT0gV/+6hd8883X/PN/9v/kV7/8FX2f1adN0+TxW1VQ1xXrzQqlFdJktm5RGoaZhfv1119ze3tLP/T44M8JOE3TEIJn/3icucvp/DFNIwxpHt3nPaeaBTghBLSSTM5z2h+RWuBcDxKSSpRlQVUXPNtcsHxeUV2/gJSoTYVFs65XCCnPUJP77S4fBrKdyVolEwnPLAZL0A8TSko+u3lJnWDxsGWsd6hUopJFqSVX1wuuX3xCawOdjvzy7ZZfPbTc7CKLi0t+8kd/xpW8pq7/EtftSWJETJr23rMun/MXf/NLmosLms0FP//tV3y4u2V9vcGUhsfdDiEl0zhwdbHhv/zH/xhiYr/d0/c9p8OJyWWfppsZw0Ilispwv7uj7wdcyHx1U9p5TAl107C+XLGYU9HcNOLcxO2797THA7/53VcU1vL555+zWCx58eJ55hC4ga6fL+OUL+6nH6f2yDQNQB611nUewTdNPb9Xa6RUc6G45/b2I23X0nYn/tPP/4q377JlShvD1eUlQgjev3/LNA785Mc/ZpyGOQvb4fyUQ3Nmu1MIgbIssNbQLBcURQHEvOqZU+ryAavwIRDGyOSnfE8JqKu8F16vL6iqmvV6RVVWNHWDNZamqimLAi0lgw8MXUewNlsqh4yjfSLixawjhChQQmCkxo0ju/0xF7dTYLG+5GpzxTC0DG7ksy9/jDWaf/Nv/xX9u1tSUqyWNS9vNhxOA30/cLFZ8oO/8bfxQ4fvW27fv2f3+Mjp1HO63XPz/BOqRvGrbx64f9jxH3/+7zi0A7ePLW03sN3tz8KqzWrJYtFwd7el70e+/+WXrFZLbl7cUJUVSeTL6Nnz52ilmXxAO0c/OU5dz+F4ZJomjDF88slryqLgN7/5Nd3Q52QwrRBaQVA4ZZh0wVQu6UdBPwxs9AV1IxhaAUPkH/zZP+JhOPB/+Kf/Z+5PO4ZCMqVA68esXagb2lOHORzZtz22aTj1szMBDREO/VwsBYGPjm7YZzhOmHK+goIjkd4kXn/6gpdffsnzH/6Y5uKCu6EnREFhV0Tg8TgxtBO7w4RRNRcvv2BpDY3VpOFEmgZuP77Fjx1D2NFUlnVdUhUlLzbPMKmkWK+o7YJldcntdsfdbssQAj5FlioL7N7ev6HtWhbL7KhYb0skEdcdwDviNBD6Ad/1uK7HDxMX1YJnr1a8/eYtDyHx9//O/wpjC94+3IHW2KsLUiIDblIOvJEp5zcoBkgTOgaUEGg1gchFrrlu+Iu/92d55aokpapYFdf8+IvnCCMZUi5mjlNPEImbz17TLGvuP36Nq5d8+fI17WGfJ71ty5v7u7wyE4KCgFHMBNApj8IZ2R4eCEwkE7J+yvXU60V+/ygFWlM3S2xVoU1FRGOLBWUROPU9Yz/yzduPIMCW5Znpn4MXM2clxtwAxZQNCzExe9JzwmKKKWcKkKi8Pzcjq9WK9WadRxskhmnAeYcQAuccf50ff+0L/Yc//EG2ra1W2KKgblaUdUWzXLHebLjYXHJ184zVep1j7oTM3yAhkEoRY2JJmrvtMu+dZeaXB++5uromhMDnn3+Jd4G+n+i7gbrO6vXlckFVl7mCQp4PszArgI/tib7vGMdxTgrLrFw9KxdJnHGgZVmipJj9xfmjqeu5k89dnTWaoHIllmLAaPVEOs1j0xAIWhG8hpQV8Frlsb4UMne1KSdwzTKAOcDh96LxpJyjIiMxpRz0oTUCQXfqmJzj+OEjj9sdtqhR1hCEQSmBKKD3LbtpIABpCvQfHqhOE1JfEF1kHBJKVrx8/gwrC2qzxBQVZbWgvryg3mwYhaBYLNmftvkAU7nQasqSwljCNL+RUpr3sFk8IATnnXJm7mTboTYqw3jmXWaMkWGOYu2HnqIssvVKKaQsWK9XFEYxDn3+tcOA1jlA5ilpCL5T0D+NbJ86YT9rIpgvuCfwz1PsYO7MM3Ti9vaW/WHH/pAVsbvdLqvGpaQ0Od2o7XOIzumUBZWn05G2a5mmEedyEQJ5kiNm0Eze80cQ8z6b72I2Y0qEEJnD2PLuXGee+lMnrpU6v1+eJhExZu/7UwH63deTO9KYEsZahBTzz6W885QZffgUHKGUwRYlhZIUKgdhOD8wjJ4QoawWIBTHNlMcJYllU2C0xBYl4xSRaLStaZZ5xBrSjmEYCTFHa242V4Rk2Gx2+LhnHLbnKcbThd72+pyEN01ZpS2kpG4aFnXDcrWirnOnpLTGmiIHWQBKK2xRwKzFGYaBmBK2KOfCrs0uiqfnSClcgsMw5GmRLYhTfs7C5EEmLJZGlVw1GZh0PB3wIiBVQqaIiHkq50LAIVCTo3cBn2CzXqK1pS6XuUAXMhdxaYt3Ay4EfPSE4ElVhS1KytWGYrnBS8UQEoNPeAFh8sQE/eCYfCSKHF4VhCBpjTSW4DRJKYq6zqE8ZZE7OyGYgudxv8NSskASUw42mdJEEHHG8ypMqef9vURMMEwd6eT5ePseET2+PWCVpDGa4XSk2+2JoyO5wMpUKGVzAI6P7B62GFsQXSAi8GNHUoKoBJZsA1UxIaVAqxx0ImV+BsK8HyZ5kgyUjT2LHUup0bpCGY0yijF5XIyU0RBlYlEajBIM7QnlInvZkGLkiy+/JMTI8XRiHAamoac2glKKPGUgQfJZmzOcQEbqdQ0i5YyQ6DNETGRXjgsB3w/sdnseHra0bX9+XhI5vCmSz/Xg/Rzekwg+/1x8cqekvE8HgZhdKdOUhax5Apltp/nM+C4mNaV8jqSY0zpXq+9U9H+wC/2/++/+t9jCcn1zkzuKy6s8clOacZyYhjFbsITk1HVMzueAjZho+1PecUqDVpa6apimMXdY48jQD1xeXPHyxSuaquHDhw/83/4v/1c+vP/Is5tnXF5c8cVnnyGl5HA6UlKxXC2JKdL3PR8+vOfd+3cZrTfnkaeU+PSTT7BFwf54yN32rGivq4q+azk+jWicY71asVqt8k4kQV1W2V9qNJNWbJYLkkhIm60lfnKkkLIF5IkfK/Llkw9TwTBMgMDHlLvW+QBXRYk0FmksveuYxqwWT8BFsUEJyVe/+orhccvDT39G7FqayxtKqxlUidACqQXvdo98vX1ALBtEUXB68wt8Avsvf4ZOmoWveH7xjH/0D/9rLpYXPLt8ASpnpdv1CrNe8urbH/H+4wf+h//+/8hvvvoNf/xHP+Lq8pJPX7ykrmvefv01c7bYXKzkjOR8oaXzhZZEpFk2lE1FXdd5MhEjbdexfbunn0ZOfYvzE9oomrqmLEp+8IPvY5XiF7/4OafjkcPhcL7Un3bnZZkjMZ+mKsfjkbbNVkRmwdpTMSClpK7r8wMzjiPb7ZY3b97w85//nLv7W+7u7zi2R/phYLlsKMrMUVZScTodiTHw5u23HPYHvv7md2y3W3aHHdOYL/WiqLJiXearexyHLLzSMue3q5wl/cRncD7AE2uhzrtyoyxGW6zO6WfOTQhAIYneo6UhRdDaEELWFjifgTnO+1ywzrqBcZoyd1wIDIBQSGkobIXRlqpqstdfJLbbI20XaLtblJK8+uz7CAG/+PlPmcae333tuL7aoIzFeQFRsl7WbJY1F88+4fqZoKw/cDiceHw84CP8yZ/8TUYfWWxe8auvfsd/+sU3kARV3cxefJ8V430P5DjhrGkw3NzcsNlc8MUX36csS2ISaGO5ubk56w3qZsFlgmHomKaJN+/eIQR8+cUXSCH5zW9+nVdu44BIAl2WtKeOj4/3XOqs4HcPe+LQksYeYqCpJZWK/J3v/5hv7u749f/7XxOVZ/U8MwmMFBy7lkPXEx73BGNJ5QJV1jz/0aesLq8xzZokFb2D0/FI+/Vv8ac97eM7xu5AfzpxdfOaq08/4+KT77F8/prdmPDuxDFEghAIfyKSGKcMnzJVQwiOzk3YCDaRQ0m05cXnX1IZzarUKJHw/Ymh6/j6N7+mkCXX9TPKYsFi8YhUBlFq6uUCW5WUyxqhJJfPVsgi8vbt1/jtyMe3vyR5RxxOvLy+5o++9z0eb9/x7rffUOmCUls2uqKIktqUTGHiP/7b/4C2BZ/95Md44bh9/IiwCt0UbIqGplpgokTHhJo0QWZRYgqBIfR5KuuGbPFdKoiC6BJWlZRmmc8VwVx8Oq6qCqElVJZI5Hj7gWOQPP7uI1ebK/7X/+3/hof7e7753W949+Yb3r75lqbQWC0helIMtKecL/Kv//W/Qu4km2cboogoERnDyOgzntvagt2x5XBq+el/+gV/+R9/yuHU42OkXi6QuuTmWZ3H5mNH34+0pyPOhcxUma2NzkfCLDgWQlE3C0DQdlmUd3Fxmc84nbt7FyLT6GiPbRY6xpw0qLXiy+99SVmVf9gL/fLyAm0Mi+USY0w+3CVoo/E+5PCClLtXpTRm3jsBc0oHSKmRMgefTJPDTbmykULN4oJEWVSsl2u+/OJ7LJs1hcne8mHIIoJ8Kefu3E2Oru8ZxzHvzmZ1exZB5XSt4F1WJZNmC0Hezw5C4n04ewalVMhZzJVSFj7FEDGFxQVPDCF3ok97SxJC5b0dSuYs67nb19oQUmJwee8RkyDEnOEtRVYvIxWJzPIeuz7v11Pi4BMKQXR5rLs9HmAYaAQUpcVeXRJUwCnPowu82e4phURHQTdFUhLcrGrqYsH3r77genXFYnFBUS5AZfuJsAZRllBYeu/Z9y1lXXN9fc2nrz/h4mIzM/E9xWJJjDmNznvPOI4M45gvT6Wo64pxGnHBZ2vVLEJjFv1plYVc+TIGN+XoWBEzd98K8EbDk0pcZJX4Yb9HaZXJaHVG6D4lpxVF9qw/wWyszfjULPQWGJN3u23Xcjoeeff+HR9vP7LdbbMqPQTSPLHxwSOnvGcXInf5MUbu7m7Z7w7c39/Tnk6zWC7mbtFqisKehZwhBgggkPlinycEQubPWWl9HrU3zYLlopkDg1Tuwl3eWRITVs8AHe+ZxER7ajOUR8izhuCpivfez+/xvJlUIc688bz3fRIYAgxdS9v3FPWC62ea/X6P945hygrsqlmjdYEbT0we3n18xJiC5foaa1XeSc+6k4gmRMHoAj4kxsmThOL65hk+Sf7RP/rHnLqO/enIMPT0fUt3OuY9+KziL6oKKRVFUVGWde7AhWC32xNDZLVcnTsWYy3r9ZoQ8vsvxxCHjMe0BYvlkmkaGYYu6yG0QagEwiN0QBUR20g0ht4diH5EjAajBS+bGulX/PHrKybhkGtIImNPJzfBPGFxRIIBGSWdLjFFQ1hconRBVSxR48QnixvwI9KfOO0f2W9vufnySy4/+YTrzz6hXq+5m/I6UIlETJG2H+YQmJjV5kIiY0DNKvnRRXCAF4yTRCaJUxahJIvFkrKYYCqQUWAxuOC53X5AWYM0FuuP6M6iTxleNfkWpQLLhSUFSSVr8J7YG6wS3H94z9R3NGVBYytKUzAOPTsXMKrA1A1W10htkFrhCOzHFpk01kasUozBElxAhUgKjpRyap6QOXY6KRC2IMXIGHLORva5a7Q1iJg7dj1bA9TcMsWQ9TlqnmMrNeugyBdfXddc3VyjFDSlzZO/vsX7iYtxmd+LYxa3rjdrirJksdpw8/wZy/UKNeeJtO09H2/vObUDk4tIZTBSkFDECP04zU6WzFSpm0W+vxCZRSANg3N4H7LDKSVsUeW7IKYshivypLLrOkIMuBDmSd+sv0nZjSOVZL/f52nXH/JCv3l+k8fVVUOIkfZ0oqgqtLGz0CjhQyBGMiKzKObho2BhinPXOk0T2+2WaRrp+wkpJEpZQkgM/UhpKy43V/y9v/sPOJ1OvHvzHu89292Woiy4vLrCzgf6MAw8PNzTdd1sWxrpuo7laoEtLN5PWXAwTSilWK/XZ+GUmBPVckqSQc67EEHOx94/7pimkaquiSTc6ECBlImQcjetTFYpCqPxEtop2+TEHFHZdT0xplwsSI2xBUZpiqIipISLibHvOe0P+XAOgb27Qya4LApSTNxutyQ3cbWsKBc1zfc+p3U9x+HAm3HiL99+5CopGi8JDrS0fO/Tl7y6ecU/+bv/FcuyoYyZATClvBbQZUksLa4wfDzu+e2H92wur1g3DX/7z/8Wi0XN17/7HWNMrD/9lGEcz+lh+8MhK/OD5+b5M9abDbv9HoYBbcwMC8pvXBlj5jav1jjn8ri1G3nw90zLgaau8V2L0WruSuU5Fe/244d5/BxZr9ekGFit11xeXLBsGvR6zegmQghnRfyTSOwJ/Xp/f8/d3R0/+9nP2G63fPz4kZDy5SdnceU0i7Tyw5P1HTEEfvOb37Ddbvn6698SfBbg5fe1payyYtb7iZAiPjh8zJ7zRBZxCinPsCJbZJW7VJLr62tuLi8ZhwHvPME5og9IBN4WVLbGI5nGCTc5+rbHFiV108wiN5+fKwHT6EhkMRdC4FUAmZXvWmuaZnkuLrq24+5hz8sXL9ms1/ziFz9nu9uyO+apxsX1K6J37B5vGaeBn/38dyxXl7z49AeEscN1p+xekOCCZHLQDTkcxh5aiqrhs8+/5LMvfsif/+1/yHa/5+s3b3h8vOfu7iNv377h7vb27LPvTi1KKprFgsVySVlWjOPEm7fv2KzX1M3iLBy8WK9Zr5Z0XcvhsM/cg2Hg+fPnrFZLrm9uGIaOr756RCtJs7Jok9DWoQuDqgKVVJRNQX8cmfoDoosUVvPjzZLXjUHwPU5+4iGNtM7zOAxM08gDEEJiDBFXSFLSbE2DL9fUqxeUiw2vX/8Qow2fIblqSr53veL+9j3v3n3L809fc/niGccw0PuJ0zdfMXZHrE4kN7G9fyASsJXJc76UMEAhBb0LiORhSOAFOsCkBToUNHXFp6++wGrJZ897xuHEbvuOjx/e8dW7X8wanSIXg3JGCyN48fwZpbW8uF5iteLZapVtZG3H7ft3/PpnP+VqueH55SWLsqE0Je+/vaU9Dfzgyx+zXm642DwjScWd65mmEx9OW2ShqU2DEJFKSeTgkJPHhohOYAqbhbHC5jG4yULo7eM9WkgaaxEmw5GYHGlyWC/QMQOCRIAwZvvcNHmQhrKcNSbjiE8RUxa8fP2KTz99RVNZCqvZ3t8y9h3WSEiRH//kR5m8ePuRqq755PMv2Vxc8ezVS3xITD7xsN3zq69+x3bfMnkoyiVSqiyadI5Dd0RIKOsSY0vqOuOn6zrz88ui5tT1jNPE9nE7B33l9aHRBVJmDkXbZttajJEQA31vKYpiznIg3yXzijaDzv6AF7qQCp46WECqTFQ6nU50/UDbDRhboJRlctl3HWKuYpR2swDNMQx5BPq0A1UiZ3uLeS879kMO9jgdOR5P5/3K6XDAu5LlcpXhJVXJ6fSkAM77KqUkZWGpqyrna3uPEILFYoG1lsvLyxx3t9udR+3GmLMKP1PIgJgorcXONqgQPMFNkCSy0POEXc4HXM53D0IgrUFLgSyKLMrS8w5QKNIcihFD5nMzH1Yake0ciWxjmzzRB7bHI+1+x8Nui59GutHQy4h9t+Q49Wz7Iw9tT1KWIC1RFXz2+nMuVhf82R//HZ5tblhdXNGYikbm4ipGEIVGFIbWjfS7nn17oB87ri4vKKUguByuIhMkH7i/vZvhJXlHbgtDIuJD3pEpJecOOaF0zgkeZkGj9AGjDavlkmEYSSG7CcZ+pLQFQXva4JECgp/OroKnoiuldFY4Pz4+4pwj+MyFXiwW56zhJ/b74XA4v67jOPLw8MDd/T3vP36gbVu6Ye4QZ9QrIpFi5vOXNieZGasZOsfHDx/mkIQeJRXW2LP9TSqJ0hIhLSplX29Kaa6ynxgHAmsLbFnQNIv575TYubhVSme617xbSwnGaeLjx4/EGOn7gRgS3gfWmwtubm4oq5qiLNFzLndMgTT77YWUOT9bSsL8vre2yB1mjCwWK16/Vnjvubt/pKgaLqTi2zffMk0TF5slWgqKesX64pLr9Y/45LMvicKQZIEwkWHs8G5E2ZrFWnLpJePk8BGEizmBShmE0SwTvHjuWTQNm82a6+trjofD7GYJ7Hd7JJJnz1+wXCzp+qxPKMsKpQ3DOM5Gk/z9DCFQVBXPnr/g/v4e7zyHQ16lFfNlsV6vCd7R9i1JBKp1hQ+e7bgjIQlaINcFhWrwzsE4ZY6ESvz49SfsxpZw/x5FwkfFgxR5bIxHiwQyInRCq4DAcWy39N6hdIUWBhsFQ12g2yXRTyzKGhETQ9uhrKTShpeX16wWDcepp5sG9vUC57O6XJCyhVEKDBI8uBBYFQ1VY2mUwUpFUTZobTkdJ0QKjO0jIk0oJamaiuubK4Zpop9G6lkbpH3uAPvjASclpRIIa6EucwhQd0QDz2+u0EnSDx0KSYrw7OVztLJs1ldYUzEQcd7z2B85xCFzMApNMln1P7qJ0LakU08ZwCSIVeZLdLPfWpYGSFTLxSyWy334FD1a5GapjCVCG6L3mZcREyJBbSxSF1SLBWX1JKg0ufkKObp6cFPOBbGaStWkmHf3ZVOjCsu1BGMs2hpG5/h4d4c2JcqUHLuO7W7Pqe3o+pEp5OltSJFAIJFpkFVZz4yIIpNPU8YrO5dou45xmphc1kgUhZ3PtLnqTwmt83v2aWqc5lWD93mFeHl5mVMjn92cf/8f9kKX+YuCjPV087j4NH+s1pfUTTEHsjsm9zTSzvCPw+HEMAxst9ts2TE581mk7FCBlGM3nWe323M6HhExh1Qc9jvcVHN5dQ2LhkVTs9tpUowE73FuQiuJLAuapsZYy263AyG4urqinkfKh8OB29tb3JQV2k8+9OPxSHtqc5coFJtmgURwbA+kkLt8gUKnPBqUch61yzm8AJDWIIxClQVKaypjMsMbjZscu8dd7h77AW0zLtcIQTFzrn1MhMnhx4mHxzv220duH+4zAe0g2PqBqTEcx57H7sTtsSOZkqgKkir5/g//hC9ef87f+9O/x0WzZhly8MmmXOCDpxsHkpZEqzh1e+66PbvTjrZv+fL1J1w2C3zXMXUdEkH0no/vPiC1xFQWpSVlWRCCR0x5TKZ15hIrLTOcBDGLQ6asONWaRVPS6Q4/OrquZ+gG6qLEG8voR2L0WJ1DLwTMgJT//EK/v8+4z77P4jljzLkjzlx0x7t37xiGgX5ewzw+PvLw+MCbt2/PyvS6rnK+s9b5PRflOQSmKAqsMXSx5d3bd7Rtjl6sygrb2HPHmK2TCoSeiWUTfo6LffLDaymxZZX91MslRmus0RRFCYgsoBRZgChmu+A0TeweP3I6nXjz5i1ucgzDxIsXL/nyy+/x8tUrnj1/QT1HzD4JEp+86dLk1YOfHFIopFCEGAg+sFptuLl5zi9/+Uvef7zl+fPnLFcb/vJnf8V+vycmQV2X3Fxf8Pzmir/z53/CxXqBTybLQ4ygO7Z0x57SNhTVCmFqhmHkzfs7ovMoXaBNgRIGqS22qLKQ0D8JCp8KpQMP99kG++rVa6wp+PbbN/Pr02CMpe9H4nwWeJ/pWTdXl1xdXvHN17+jbduZUDhwfX057yUvaNsjHz48UJWa1UVDv99y3G+hqInGYjclulT497f4YYR2olxU/MmPfsT9acfD7gGdIiFpaplto1oEFAGlPNJEtPIIMXI43pPaI0MfUCi0F+xLi7tvuL7Y8Pz6kuQC3f5IfbGkqIuc0Z48H3cPHPuWQ7NiGAdO3REhsjZFo+YLPeBDoFktuVxtsCk3AKUt0UKy3w/4qWd7/4G6Erx6WdEsa17KZ3y4veXYHjBqQVOVeJ+/j6f9jhQClBZVlrBeEqeJ/rBHC8Gr58847g4cHveIlB0UX/zkB1xfP2ecwLnI7jDQupG7dk+rAmJZIKwiWYVP0E8j4/GIe9hTRbBJEOq87uziSJRgQoEpLMuL1cxiSKTR0Q8TtcgshkIZdIT+eML7HJYlhWBhSlRZ06xWKFvmotZYmsWSrjsyuhE/TJA8q6bE1gX9bP0qi4YSqJd5p41QDNPE4+EDi9UFq7XmcOq43+7ZH1tO3YAcmS+oTBLTpURpS10v5jVgQQgR7zNky4ccvDWOU3afzLZYKRVKmvME0WjD5eUlVVWxXC4Zxsx16LoO5xyvXr5mvVnz/PnNH75DHyeHkGL2cWZBizICKyRlgkgmanVdd04sc87NGdb5jdn3A8EHrCnm7k4Rfci7hmlgco6+bRnnS38cBkqTK7sXL55TLxpevHhOUVi6rp1jUEekFJRlSdM0WRktwHvP5uICo3WOM1WKw+FwFl0hYLFYnK1qc6YaIoKWgsvVCqM1dVnQTwNeRKKEJBUueQY/UQtQhSUoZkVm3n8IP2JSBCWzeGUeHRtrIKQZ4NDn/ekwUsQMjtLzCx+VQrklcexp2xNTmFgvLwhacXKO/TDweDoxuAiy4Aff/wlffv+H/MlP/owXV89p6hVSWk7HgS4NDP2QL/RpYAwTnR9o40iXJpSKbC4amqakKm3O587VVT4AhhY8DH5+fYY+K4klHE4Hxhm3m5Lgpqiyl1LJOTAid/BVUSICuGpiWS3gSpy55Kexx40jUctZ9xDO7zdIZzQwKTLMdsSua3n79k0O/xFiJgLmtYyb98reOQ6HA13fZ7hLVZ6V8sA8VTCM/UBK6Uyaenh44LA/0A8dKQUWywYpJOM4UFUVZVXkXPKyzOhR72lnfQEikxCvb26wRclisZpJcXlvLJXOeFEfOB6OmWyXmIV8+b17cZlTBI2xeeTeDzTNAiGgbU/c3X3EHvYo8xS7KvJIX2cBlLGWZpl1D95NM2I4k/CsLbi4uCRFuH98oOt7rm9esFpfcjwdSMPES1sRheHx0BEic0iOoFDQj4lTH/jqq1/TtScuLq8oipIXrz5FaZPFPaNj9NOsIcjAEZkCp92O/X7H4dQyjhOr9QatDT7k4k/ILBZc1A2QC7msLZgoyuxAeHzc8pge5k79GWkm7nXDMDMHROaNlwVBR47JQVOgqysO48TJT1ytCqqmgNMpawJaj3Cex3cfcdHx+XrDduyQXWC6rJFixceuZzc6li8KyquKy8WALo9ciorIhCQgyTzuRlsuxYDtT4x39xlzqjV6XENVUTQNhVYYWzApxerV54ze0fYD4zRyOObozK7t8G4iOs9R7ZFTYFXWWK2JQw8x4fscwjT1R1IU7O8Hhv7EYX+P6weKqImdZ/RdbqCE4PPrVznsJnj8NPCzf/uXSBKN0VhjEDPbwz63VNUCW1TE2tDpRDAWHxL7/sRuGvi2e6QTgZPIGQQrUVOkgEuW7e0D+28/MN0+4ucIYK0VqVSowrB6doWpLPUmT0+bpkK4gJwcvdTUUlMmgYkCMwuqiVlwXNZLVFGhTTGHAC1w08jQ+bzuVJoksw04ytxsoVTufmcs85OGKUZAaco6CzIPpxPv3r3nq9/8lmF0GFuSkiYmwRSmLF33gqGfuLvfzus1RQyzQ2V2M8WYYRzKzNO0mEmXT2LdjIM21IvqLADu+g47WC42m9mOGjns9nN89F/vqv5rX+iTyxd6EmK228xhKlJhkyCmPH7LnW8kxAy28D7QtkOGN8zM7MzlzoKGQIZ1dN1A33c56KLrOB5PBO8xUqF1weXVBYvlksvLi0zamS9zH9xshSvOu9T98YgPntVySVEUsw89sN/v6bpuFhiIvM/TBmvM2VeWQkQhWTU5ArWwNnPIxxMuRUaZEa7OO6IAaTVBwBizZzKmhPR512OTzftOH3OhoDQhOtw0Mg5Z3a+kwsw2t4hAW0NSCtHU9Mcih1Akj7CaqCR9DLST49ANTCGBLPjk9Rf8jZ/8Od/7/Adcri4oVY3wcBoPJB9oSfjoGdzAsT+xPW6JFqLJ48bloqIqCwqbx6WBHPEXU8T7rMD3Y2ByE13fo4xBFznG9NS3kHJxdpVuZoFhTtkT5CS8wliwibrIAJGqqufM8jyG9zMeUUiRuQDzj3wJ2RlsE5nGga7PSmfnXA5/kZK2bXMYz5CFa1pn7kHbtsQYz4l6VVWdbY1PhYcbM11wGDI29nA4cDweGMfhvOvyzjMOE1Vd5S5+/nCzpWwcRibn5vefPV90Vd2cxZoZ+ZvBKD5ETm32tAeXk+pevNBUVcV6tSLGRFlWTNN3ynBBBvf44DLadGZKZ5tXnvaEFCjrmmaR1eUZSTsfLmQBz3KxJiXJV7/7mruHBz755FOEFNz/fEsUAqkLIor9aQAEVmsWlUXUltEl+jHym6/fcPfxIz/5yR9zeXXFi09v0NpyOPVMztON2dtfVtUMsgn048jjbsfQZZXz9fUFVVXl91bIolqtDItFRg4fj/uzyDVm7w+Hw55h6DP/oSoZ+36mPw7ooKnrEqkUqrB4JsY4UlQZ43rcbhnbgaquUUIjmgoRI6LvSD5wuH9EWcXz5RKjYQgn0jqL3/RjwBwDL64sixcFdTMhi45eQUgKN/ZIoSl1Q6ktK+FII0x9QhqL0AYfT8iqpuYZpqhYNQuStVwUJT5E2tFzOJ14Owl2faLvDsTJ4aeR3p5QIVJsBMKY7GrwOb87RYcMPSIKWiHp2gOH7Q6SwCZNGjxugsJatDE8X99QWcvUtmzHe373i19jtOLTV69IVUExi1irqsJUNaYoiaVhUAlRaFyEo/bsGfg4HBgIjFpRpxJrNFMClwTH7YG7dx95/PXXdPdb6pk9UmwaTF1yM46YusAeG+q64urqChEDwnmcMjilmaLEJsG6KDFSIcnBRFVRIYsatMEYS1nm6N0k5FxEKtKMHU/i6ULPnuPg4/lsSQl8SplypysmF+jajtv7B968eQ9So7XFBwERfEggIipIQgwM7nC2Iz8FUsGTMNfme9LkdVCKkARnQfcT1vnq5ip/nrM1VQrJYtlQFJY3b97Qtt0ZR/0HvdC/+fYN1lqunt3kVDJkVn/6wDA5xtGz2x9ou462HXDeY2Yv6dXVM6TK0ZkxhHyIzsS2GDKMY7/fsd1u6dvMAV4tl1hruLnMkYnH03GmAPn5sMgV383NNWm2CJVltitdTWPmaM8jUmvtnESWdzFGabRVuSIVuTcPIZBCoFlUFMawXq2xSs27vOwthzh3PPkQGsaRY5vVw/UwziIoNfsLZS5uUoLRQ4jEwWXW8O4IISJColpknGMAogzIGAnOcbvfcdxtSTErqxfNkvXFJS9efoq2D/RjZB9b3NDz4ZsP/Mr+kj96/UeUFzXbhz3TMNFu9zlesykzU9137LstHx/ekXQkqZAziJcFQnh8GMh6Xkc/nRjdxBgHQsiJagkwlQYlSCrve4B5nOf4cPsBrQxxtvPllDRJmDwSybJeUlUVTb0gNtlrncLIQTIz1rOgLbPj49l7/TQuHMaBtu+zbqPraBZPQJfZnz7v+vNkKJxFdWd3uACpFWaeMpFy0pRQczc5i0+stXmkD7O/XJyrainz69rGlv3hyDhNlFXFYrXi2YsXVFXNan2Rd2tFBsEkMsbx4WFLaTRWSZwLaGWoyjpPkVZrqqpkc7GZHRdiHuO5mRyV94pKa8pyXhuYPMZ7GuuJufq3Jn/fZ+o4SggOux2P949M8wi7rhdcJkE/5GelrtcoJXnctTifKKsKJTWLGuq6wFYrdNmhihEXJe3g+A//8WcUZcWxy9YybWtMUbBYbZBKZUEWEZkUwUeGYeJ06vCT5+ULizUlv/vdN8SQeP48g4Q+fryl61ru727PbIf9fo+UgsJojNF87/tfsmga7m4/5hXe4xZjNcY8wxYln376Gft2z8f9B/ox0U4jSZSIxrKbYPCRZ8srlGrYvt+hQ2RhNClFRneiaRR//OVndGqilRMnGehlJDSGVBqaVyWyVBymnohEm4YUPX7aYpSmtm2mRJIDPJAaaQ4IaVD9R+RkUX4BytDYmiQ1oSro5MRFkrSrmv3lM/pxZBgnfEiE6DjdvmcfAnGO/b1Yb6jrBa9uvofrT+w+/I44CQpZzxdMopAlRhuWZUYouzYQu4Gp7WGS/Oh7f4wgUdkM6iqLiqIsMVWFriqkLXAqEXAM05HRBx6mI7vQMcjASGAKCdGP7NwBQ8FClIyHnnAaebW+wdZXpGFEpES9WBOV4OE3H3BERpNYXWzw3/8CoyRWKkapaIVi9/4j/eHIpzfPWdYNizIX1MkuURVIWWEjiLLmdDry8PDAatnw7OVLxqHFu3FehmbLMClimPHNw5Sb08IghCIJzaE9cXv3yOHU4lOkNGV+xrQlIajn5sa5jjSnVTxZabOWKxMbmUlvgYRzgZQcUowopc6AmBACbdey3X+nJ3tiN1xcXNA0NcM8PRzH6Uy//INd6LvdPqMZNxsysCJ335PzTJNncjk9Zr8/sD+cmCafD6m6pqyqedfgshhljih9st045+j7nrZtmcaRFGMeodc1q/WKFCOP28fcXTk3V/65w2+aelZyCooyB1mUoSLEeGZ8P10MTwe9IAM+yuI7OxVABMqioC5KCmtRmTk6+69FRrjOl0SaPbLjODJOjsl5tDXZSjXvgP0c+4fLgIYwjAxtx2m/xyAxQqLqmlJJQlA51xxwQjD2PWPfAwkpNWVRUlc1q+WKUzdQmBIjJmSaOO1PPHy4x48BmSRdO2QM7jBmAlNt8CkwhYnRDXTDkSgcUXhqIzGlIaU8WUkif0xhYgoTPjp88riZN6+0JopEwCOQs40pf0+Ox8x3z9YrjVVFFpP4fKFbYylMQWkKnnzZZVEyWEtMPkfVzA/I7wHhzm/4fk7Qy130kRAjVTV7wmd1fILvLvLfR8POghM5g0uY/448UXjqgTNp7hzk8vRrEN8Ba6ScRZh5DzY5x3q9oaorLq+uc4Jald+TUitSEggZcC5wOrZ4ayiMykEd82TJzmlqRVHkw1Tn8e1TofL0tSidL/S6rudJQSZVOR+IMbsmEGIOg/nOxocQdO3A4djCfM0bY6nKxLFrcd5jbZnV8MOE0ppxDIxlyLATJFJlIZLSliQUPsL93UNmej97zWo1sboQ1FJlMZ4QhLkQTlLNEI4cHet9mPeJisP+QAiRly9fQsqQmOPhwMPDI4W1VGXFNI1M08hmvWTRNBhtqesm6yAEdH2P8RrvPcaWrFdrpugRe83kHaMPWRhmNEPf413gxtYQNRNZWJuCyCLENFI3NRebFb6MuCoSV4pUSbauZUie5lIgi8S+H0hCUtYlIUS6dpgnUgOC3FEmcjxyJAcnRbcHr5GiQSiLlhegC0SxpE4R0wQGK7koK9pR042W/bGj6z0P/YlhmPAuYpRBr6+obMX15hknqXhwsxpeGLJvI6KEQcuCQpcUqsAPOZLU9x6i5Ob6JURHmHqsyamA2liUsUg9T+wEeAKddwzO04WRLk44Of9ZAURwDGNkEIlJStLkkT5x0axYS8u4OxBDYFGtcSnw4cMHOj9ywBEHz3q1ojCGwhpGoTBC8fb9B/b3DwgPm+WKZ5sLqjpRDRNGGFSV1fDFlK20/TCwXi9pFkukErhRMU19RkyLLOqWitxckfM1pDYwv0b9OPG43dENIzGBVAptLNqW+XkOJkNk4kRKgTTDYNLcfj8Bps6jfPK5lc8Vd8Y3fwfHygCiGJ8iw4c5UjkLzjP5+Ak48wcGy7gQkN4zDo4YBDFmZWFZLVAmYorAt28/cHv3wOGQoyY//+J7XMxKPRCEkCsOa+35kDq1J+7ubhnHXMFcX11hraGaleKn03EewWVrl085RrXtT/kArLKlp6qrmV898uFjrtybxQIfAt988zWn44mPHz6ex3fW2FyNFrkjK4sSoy0hRPph4Js330KM7A57XAxoY5A+Mg15ZxxDJPpAdJ7h1HLa7ukOB6QU1NaghaQQGiUEldA527ftaB+3PHz7LVZqCqVZKYkqCzSQZOLx8ZFT23LY3tMfD1RGU9Y1LzdXlLYhHSbcQ0f/YY+Ngmu9pBgVce/49U9/yenuSFXnru/m1TMECec7XJjyLk0HLjYlx2PL6fjAb+++JTjH588/Y7Pc8OrFawpZczc8MoWRw3QgEnOyUEyEKXE4HdkfD2zWFzRNQ1HUSKO4u78l+Mizi+dUZc3FekPwkePugEJhpMGPE8Oxy5qJaaId9lnUGEdCytTAJ+tXVn/mzikEgewhBEffdxyPB7RRQKSsMudfhLx3yqCVMF/iWRk711hnMtw4jHNegCOGyPFwyiO5kPnMxmSfrJDZhaFmFTkp0Q490+io6obVes2Ll69omgUvXr7G2AI5sxmOp5Zx8pzagZgEVbNExIALMUMv5BMeMrI/nuhnnoK1ltVyhTGasrQYlUExYragGS3ReqZwySxcEqQcuiFyQpdWgqLQcyCQIYbAOA7cPWw5HltQ2ZEQZzBS1TSQchHqfGKKcBocd9tD/hx9RCGoV5d8/r0fUy82vHv3luA9VbPClhVFVVKUFbascscyjRidV2Hr5ZqL9QVX6yuEkAQXOeyPvHz+Mhcufmbg+zhPeNK5y/z9DkYAfd/R1BXLZoGWkvvbD7TDwFe/+hUXF5c0VY3xhkt1xe54YNwfKDdL6rph8ieSc+yGRBUsX/zRX0B75P4XP0WlkbqKdPsW/66nuNaUlaEsNWqj0PHIlAaE/4iIiZumQCiJN3nF09MhUkSmiH4qrMgJe37Ggk5TIkRBGAuQBjlsQJdQXmAwqFgSZU1cLHFNjaPisNZ0g+GuNLRd4HSIxKhQQ4mLgg9ph58GlGgyOCrlCOE8QStI0XA6JTpG3NAjYqQpMuDr01fP8G7g8eEDWkvKymAqiyktWA1aMcaIdxOHoaebJg79gXbsCTFrSPrW46IgBsnaRigtz5aXvPy85CcXr3hWLTm8/0gYJy6urhinkbRtmVLAXK/5uL3n//t//x9xKeJIlEUucCutMUrxeP8zjNb86Z/8CZeXV4jVJY003NiSkODj/QNaK569fIUpDKd+omlWrC4u+Y9/+R+4v/uYBdMyMyuU1pRFFvB2g8cWhmax5sPdz/if/j//C2/efcDFhIsRgud0zBz2fhzmyeHMrNBzwJLKAlupcm5F8CFreUKi7YZzUwk5F0QqSVXkacNqtaRZLNis1xyPB47t6RzadHV5RVVXbNZr9OyY+oNd6HGuEkKICBFIwmOQSJ2DH3L0aU5j894TYpol/facMR7Cd6jVc3c7Q0rCDOQw1mBtMSd5JYZ+mLGbOdfYzZWNUHmPIZSkKEu+E9J4DvOuPMzwjbu7O06nEw8PDwjy/sIZN0M4sgpYkEewU0pEKZnGkegDXd+TJHkXhsi6gODOXwchEp3Hj/kSESKhyxKURglPQuCFJjmPazvGU0t/OBCVAWMJ4wDOIeeRSgqe4HOeuxuHTI+SitqWGKlJYyAOntBNWFtnUYgqsMJw2p941FsukyBWBY3IeMMoEpE5HhaPEJ4URrzr6NsD4zAwXFwxhRJpM39cWolwgiAztSjFfGH4FOldTzd2VKGmoKTU2cY4+jFnyqdcXZaVxY3z6yXmt1uMRALTODEM/fyAwFPH/oROfYoi1VqRkjxje8UMnglhDidhVpXPufV5YTZ3+eKp855v9Pn/C5Hl8XG+NOI8zYHsOYYsBptNjHm3Ne+w4vw+9sFjraGua5bLzKhfLpcYU+RDcJxo+wGQefJBLoCThxSePh9BJCNLpzme9UnFXxQ5ua1IBqEy/jR/Lt8VJ/nfM70vSVCZJ5MDWkQetStJjvxVWaCYZi+tmjuWXFhDMR8YGYAkcD4yuUA/Obp+5Gg7FlVBafNI3fkMG3LOZbuqtiht5tdoZiSTYSJKKrQ2uYi2JUrpWSMTqKr6vPLK5D/myYKaX49wPhCfULhPhVjOjM8MCVKG8JRFSXQREQQmGUwy6GhQwSC9QaWCmBQuOHQSVOsmWz+jJkVHjCLzATqHGC3Gh3zRSoVVI4qJ0O8RMbDUS6RWjDLi8UjTQ/QIP6Fltp/lva/Ez/ZGkzI+1ntDkhrh1hBLkrhEioIkFiCXICe89ASRkNFSSI1vFIVUKJ/wPlvK0hRoDydSzJoH8RThOk8wlTJIqQkhn83j4BApUdkSIQxFWc+Fc4UyAmXm8B5lSE+W3BTxPjG5nFMw+RyAkmIuwMdhJASQQeIpSSZSFxWLdcnNxRXPqhW2dfh+5KrZMOiBC9PgRWK5vmZqB8KxZ/COk/f0Nq9W1qslVVHkGGqZ1zy1C0wxUqSUXVdkolytKoqyQsrMTRdKo23B5AJtNwKzQn5RYywYkzvfyWV2gw2Rw7Hlw+0tbd/l3XuKuQB3Hh/C+RnV+ikmOaOPf/+MSUnMGOJ0jjt+mhKm+X8qKqy2Z6iZ0YaqqnOjOHf5OZuipmma8zTqr/Pjr32hewdKZcX2NI70+wPeRybnqaqaqs6KyBcvX2FsxTRObHc7uv678AxrLdM4sn145HjMO480U4GkEGijaE8n2nikLC2QeLj7iJ/52ZAPKT9NPN5nkIkttqw2G5bLJV0/MIwj/+mv/ortdpu7r5RTzoIPdKfuLEioyholNafTKSepxex3fXlzQ11lxeUMaUdZTWNqwhB5uL9nCI4uTFlMt1hCN4EdGdojMXievXpNXUjiOBInx/1uz9T1HO4f6Y4ndnd3VGVBqCpOi4aj0ee1xNXFhqoq+Vf/6sTuccvQ9VRlzco2gKI/DoTjSDw6Nq/XPHv+mh/90d/g+YtXhCQ57lo+fLgDEWnWFc2i4vMvXxBxCO3YHW/56quf4qcTwbdcbNa8aJ7z4pNrVssNeq1QWnIlLym7gqM4sDvs+WZWlWurMauCFzfZP1yVNXVZI4XCbDWMiXJTsFwt+PR7nzL1E8EFjDI0RUNtaxZlzcPjA4fDjsEX+DgxTD0+eqYxv9Z6hrIsFot5Px4RSs5Z2tnitV7ni/Ti4oKyLDm0J8Zpouu6DP6ZswTEHJJyvmTILH0psjAmhHieKrkpFyVi1kx478/Ru1mHETDGslrVXF/n7IIXr16zWq149foTbFFiioqu79HFe7aPW07tgHOSECdMqdESUnQQ8/PzlA+glCQRKaZ8AFVVhVZQVSVlac6roZSe2NG50NBaopEYM3+9mTmGGzomoEuCMHlKrXl2fcVqueJ+d6DrR7quJcTE+vIKbQx1syLGwIcP92zWSwpbsD/1uNEhnl1hi5Ll5gJtLcvlaobyZD99UTZIXdCPY95/24LgHcehxU0BkXKOgzGWu7t7xnFkvVwBgrdv35JipLAFRVFydXFF2514fNxSlyV1WaPmtdfj45YQPFcXG7TWvHjxgr7v+PjxI1JKuq5j6Ef608CiWnGxesbDds/D7ZaL5YZ6VeDDgTFEOlNiGsHN935IGHYMx28IqcO3A/224ygjtTIUQdOswdiE9Q6ZYrabSoGYJpKI1IXIqFvZIWes6JwAnnPTdf7IO9acrR7FnigMk/+IlwWjXOBczRSWDGnJmBrKuELHkmJ1QViU9KuSyQke7juGfuL+ww4pwVZyLjYdVb2grpdYU6GUYf94zPZKmWmVWMMEfPPhFq0F5XKF0jKnsGkIKgOL/BToomeMeeU1TCNj3zH2PUPX0XY9dx8fsSiWsmSz0vR6ySeXz/hseUXjDQSZd9EOmCLawevlNdJqXrz4nB88+4w//+Gf8Nge+bB75H7/yP1+y8e7W7YPJ168eJGhUjevWF9eUi8uMMWCKQQiWUycyOAyKTNjoutG2ranrFZcXAV++tO/xE0Tf/pnfwqy4MP9bi4QA+N0R9v9ip/91S95//GeyQWMtYxuYpg8pshBSs2yySLMoZtJcYng83rySeeTL/F4Bjo9pY0WRYHWmsVike/T+de2bcs0TRyPR4zRGKt5+fIlq9WKxSJHeX/48OEPT4qLMc0dbT5cnct85rbtmVxgnALjNJ33c0JkXGVWAOY9Qow5mvLJ3zsMwzkdJz11aHMspnN5f+imHKv61J3lzyVXTVkh62ZVYzpf6F3XMQw9w5BHmMx7CzGPwfKflat/73LFH0OAlDi1bYbUpFmlbRRaJqp5t/sEOJAx5ajURPaqxoTyEeEjjI4UBb7rcMPA8e6BqetpH7e4cUSGjHaUMY8lpz6P6rwxqLKcpxH+LOJLIeYghBQZ2hERBYtqwWZ1wfXVDevlhqZe0k2ONCuvQ4y0bYeQEedGYsp+4HHqaPsjUowIFZGFQFcKWQhEIYg6ggokk4g6MDIyxIHOd8iUq0mlNbrWmNpkwpXKXbMwIKJAaBAGTKHzCF1EnqRpSkuKsjjH4UZpECHhkwMPQYUMnpgFjU+Rocwd+u9/GGNmEVuOLpUiv2bx90R1Yt5Vn3GsPP1xYgYa5ZFoiHn0zvnS5HzZCxFmEl0Csoq+rKq8hpE54lSpJ+V5zioPYdZmCDlbuiL42cduJGGavyMx6wa8zF+39x4pxZwCp787KGKYd+MzhInvdncijx6YI4FIRIgQZtdFnKcRArA6ByeVRZ6cZaDHUzyrQhn7He7UBcbJ51CeGJl8wMeE1paqSpS2OAOjhJAUZYVSOov0yDGuPoRcCDk/W1gdKX73/XfOz6N+f9Y0aJXRmH3f5bhVY2arUS7EgvfzueBnwEeJAJq6prAZqRlnCIiWCanEXMzNU6YYwBqIkS4GChL1eokwHqaSJCZ8guQCvnPIDkSfuzo8mDFfHq7NmrfJ5QkJdhbCpadpSsr+anKw0VNQSA44ivOF7sjXEih83ronh4ieGEdCbAmph1QihSfqCi0aJiUZixEZJozcIqRCyTypjCmiVECbiNIRpeZnWgWkzd93jCQq6P1IIQ11UWY8q5EkGc/wKJdC7shjyNO3p4/R4caJqR8Z+4GIwigYy4kxOJJW6LokdokpJJKSoNVZDV6aAlMUrMsFCwXVYkFz3COlRgmFRHE6tPTdiNEWoywx5AmalPlZizGRnoBKOttChZIzajx3zEVZU9WOlCTOp3zlCU0OGUpMLrLdHfnm27d8vL2jH0cQ+XzJ0bt5giikOHfY8wzprL96sqrlgjtrcrTOQS9lWWKMmf+paZpcFIzTSPDhfDbl9V52kFkzE+PIAWKn04m+6/+wF/owOGKSeXwhcqj72DseH3eM4y3DOGXPndZcbC5YLJbc3Dw/86T7vufrr79m6HvaNqNal8tlHvd2HU+RcVYrlND0Q0fwmQ9ujJ4vpeypDbMgzY8Zhbnd7c5JTDkbOlDVGeoRfOB4PCKkZH1xibGZJDeNE13bQ8reQFUUCODu8R7vc0671jqPPasSvawJIbKsGpoUCUSuywUXquRCGNbRsFAVMTrGbz/SO0e/O9C3Ld/8+iuidygii+WCVzfXZ+sNY8fjhzf42T/fB8HgHO2QU9QE4MeJj99+wPnE/tizurzmL/7iv+CzL3/Ey0+/IEhFFILleomQipuXLwjRcf/4DkFk93CPCy3H7j2P+1t6f2B5UbLarMAmOtNxkIcMx1HZCnU73vFw3PKztz+l63tOosspd16TJNiqwN4Ylpslh8cDfTsQ64A0MOmRQfR0saWdWu62H5BJslcl6cVrNhcrlBWYwhCkBh9xMV8s05QvuRCyD32aclRottBllC9ElBJUVcFy2eS9mJL44JjcyOTy3srM49gni6VS80gsgtEamQTRR7zQTClbKMWsWI2z7bLrOoqiwBiLUrk4WK/XbC4uiVHQth1d16O0Ybc/EtOR29sHxmmi7XoSgma5RnQdLiSUkWgj55VByAz/GIkioZPEuFzADNMEEtpO5WIjOTbrNU1Vn0fuEg8xAOq7cV9KM6s+EWLKyU8wxzlKtMyZ66+eP8PPo8lT23F/d4eQmsvrZ0glsVWNC4kPH+9Z1iXLpmR56rC2oClqFoslF+v1/Gz687M3ec/xlIviYRgYu5bhdOR0ONEdOx5uH/DB8+rVKzbLDd9+8wY3uXNxVhYl2ERhLW17Yuj7fCmGwGq1zEljQkBMHPcHjNFcXK5Zr1ZcXlzkI1dlm2gsPQe/4/H4gKkq1nXN4/0d0+j48vMvKZTmN7/9LSWRv/HpNWYs0GWHHy1TP+DHE/6+J5YVSRQcb3sEnqtyjZGSu289gUgvCqJKROuxtWV50SClQ4kJS8QSKQhoIlZkmRw6sxykmVdLJgEjKY14oZiE5oTAIjhNgsELol6SpKW2a5LWNM8E4wSrJuJiQR82OG8ZXYG2CakdQRaEpKH0aJXQts4MkSKTzU79RDSK681yDhvKz5nzI+0w0k+5K59CtgoP08TwcKJvWw4f7jl2A6fdHiUUk+pptOFi0fCSgRsbGbsREzx1o9FW0p6yoKyul9RVxbPmkiihDw49CCY1srpZ8NnNp1Sy5l39MavhW8eb373jdOj48gc/RkqN9xFTmjOXvW6a8yp0sVxQFiXW1qzWJ3791Tccj0eSKBCy5PJmRd8PtO8/8vNf/Zb/0//w388XsmC5XFHVFfjcRCmT17/393eEGCmK8my7zgV7LtotnMWzTxf5ssnnU1VVuVD3WahdxSJz4Mv6O2rq/HuVVIz9xN3HDNP67W9/O9tX/4AX+qntUONEIJ27mnGa5gtUnAU7JEGI+VDp+i7bzJT6z3LIs3AgV9nuKTt67tBDStmGNgdfyLmbnqaULW/e4UNGDzrn59jCNBPs8v7Cu5zCZU1B0mlWGmb/u5q79ScrEjx1C2LG8WUeOVJk28E0EkQG5jif93YhMIMdRrrtnmOSiH4CNyFipEigYqSMQJIsdYZL1KVlc7Hm9evXKJ1H25EM4pfzPiia7EPPVacBJGkmNoWYcD6SUBhTIrXN4iaZx3enfiDEhC0kMTq6ts1dRSqQc7wpMuEJBBnxJhFVwIlIGzqSk6RTfqOefMuQeqKJOVUuZLAOMhBU/jiOR+IxF2uTc0QRQAuiDEQZcHHKH8mRXGTqJ1btkrY7MUwDkx/PcaBP6vazDeTJ4z1m+lpIcQbI/P9Z0ub9s4ph9qdP59c7ptwZ5ReZM2I1wfnveerIsxqbmekvZ+zo/FtF5r4XRZGxw3Xea7Vtjw+B4+mED5FATk66u3/A+4iPEW2e9pSzNkTNdf5c2fsQiSHrMvJIORCCx1qNUmROvJd4r/HOZefE/LUIoWenAd/hcs9PQe4E5bzjc7MvXZk8phdKgJQYrWZVvSUJifMeEQSCDPVByXlaFBhHRz8MFLrGaIUPEUSYv5+5Gw+zkFAkhVL5GxhDnIukeMb0Bh+IKp01DU8fWun59RAU1lLY4mwXfAIGPe0mY1T52RHiTJ7MCg2fD1mr6V1HO3RYFdHiKd8h0A8d0RhMU6BSZO96ZHSkuiSKAj/ojLwVgRRLvCuYpkCMEu0sSijaXuBSokUTVSKVBtsHjsGjFRidqESiFJFKBKyIlHi0iEgdkDKhbEQoEJYs4JRZE2K0ppSzzkLnIsDLQJQGJR0JjTTZKePqvIqyocYFweANkSwy9d4Qk85YXq0xhUAqgdT5nWJ1gSkLKGQ2YoXERGSMnsF7RucZXHbxDEO20Q19hlVN/Uh44kEgSBK8SAwpcIoT+zCwUImylFSqRHqQSZKkRBqNNPmZCCkyTR4VQUeBtDlY5dXNc8qi5DgN+BgoyopCFcT5LDm5iXq1ZH11SYKczTGL1J4EnyE+RZjmc/vu/pGiKFlv1vnMSgJtCzabi5lu6ohk7oqfzxkxg7ZSLo3ztHe+86TMGFgxr19+f3qotZ55F0/T5SfUc35eC1uwXKzOqOqnKaJS+jyml1Ly7NmzP3we+tffvsV5x3a3RUlN0yxYby548fIFi2WNsUUeg4fAOE70/cjDQybpbNbr8wPn3cQ4DHRty3b7mA8Uo89Z26N3pBSpyxKrs3fQ+zySG6eJU3vKkBrvmZxjHB3DODC4aS40BEWZ/e/r9QZjLJvNJttKTl2mn51OGG1ZzgS5PF7J4Si2KLJaPmbhx257RLSCKHJXV5YWFyK+n3jcHbgdfsuHoqK2lsYYKm348Wefs2pqqmpNsg0vpKYqC16+es71zTWff/8LuqHjNLRsDzuO3RGnFFFK1OqKwSd+9/6O0+DI82uNMlU+7IXDJcUQBLthQhxP1OsLVFHyi1/9lN1uR1MZBIHxdMdmVfH5pxsKU2DqNbu+YJKOVuWRW1IJFLjxI9Zt6T/mHfZitcALT/OiQfSCftvlYa6IuNIxqJ5fvrulbweaosFqSy0bClMQTcBLRxda+tDhGen6jsPdkRCyKGcaJ7xzZ8VohsvkB8h7j3OORDoH7/iYR0/H/Z5+hgP1/YBtW1zIlLb9fp/5ydN0tms9oVilVhkuQV6ZeB9wo8f7SAzM4qG5qPQBZnWylBprC5bLFavVms1mw8XlFYvlkmH8QNuf+M1vfzfbXCwxQj9MKGNoVisWiyVXxYJihupMQ4tzHSHlgqOf9QBjn3ML6sJQlQUkTwwNVWny5aoEbStI0WNmTG5d1whtMNrOYzuRKX4pp8kpwZnWth2OnPYnmiUUlSLFJx9+pua9fPmSyQfuHvd455nGkboq2ayXTFOgV47d/kjwHgXEWNH1d0iRrZ4J6IcRISVF3WC1QRYJN/T/WQH2JILd7/dU1UTTNOefVzILXHNhA8P6kuc3p/kgjfhp4jSOdKsGpQRlkVd7MUv15+IrFwWmLChFw8Nhz+3jHcIpZJTURYNRhm/ffkthLX/3z/6Y5EZ++m/+Zyoj+N7LC/ze0R5LqrJmUT3L2o1BcuoqxslzFwwhCB6OntHD4yRAK8zKgOrB7CgLaCrJxkqWVrJRnlIGlrRYHLUaMDKwqDxaR2wV8+7ORlSlUUuDtZq11ayLyBQifWzxSRCVzVY4ofFasZAVnhVONHgEExX32y13u5ZxgtFLNs+/oGzWqAKQ4IJHactq/QyjDEkrvPMMfWBII93U0Y15bZnpnxP7w4G+H3i423LqOg67E1HliVUCfMoBNjvpeeuOpNM9ny0uubQNl2aFRVPe98RTz+nUIcqScrVm6gfC457UO9QYqUyFtTWf/Nkn6Lrk/rinGwd2hyNJgDtNtMeO3z5+5NnrF7z4/BOGcWS/O7Ber1mvN4xTpB86Hncnjscj/RA4HEd+9lf/Gq01P/zRj7CFxRYFn3zyBf/Nf/Pf8tVvvuIXv/wFh8OB7W6XUzZToqoyWlkXefUTfUQogTV2ptw15wmTlFmzc7bLziK3rutQKkNjMlSmpiorNuuLHHq135/fv09W3GfPnmGt5S/+4i/+8GCZp72BEOq8G/fe03cDPqQ5rCPHkD4pcrPPPGM1IXdF4zB+pzgWIsNApoCdQzOUzGK4FCMuhCxS8m7GvOZKJsTANHcNwWcVdn6oc+X0hOHsux5n/LnyefL8WmshZYvT047WGIOwFukyPCAnYiaizPvhtusorMFqRfIB4WNOAhKalS1YlRXroqIyhpUyNCgW2iK1ZbEWVFXJ880Fy7pGp0RyjrFtCX5CkKirElWWLF68wiF59uIlo4s0ixVaWY59Tz96Dn2PGkeqyaGGgdh39MZiQiBqja6qvNiPEY1ES4VVGqkBpRBa4GWkSxNjiDlmMsFwmlBRIkIeAY4qA0daf8LhUJXCxzwh2Q97Ot/RHmfxkV1gdUGjewpVosk2qf1ph588tjKMgyIITzecuN/ekXyc43LtGdsJAqOf9A35vfO0P56cm7tvP8NemBP7uvlC5/zfn/6spzhCHzwqqN+bAMTzbj3NalSRIO+Sv1OZPhWh1tqs0rZ25r1btDKIzKSl7wd8iBibqVOLxQJblqw2lxRlhTF25hd4pFLIqOf3pDxPC3zIo/dRJITMQS2lz6mCWuu8ngHGoSeaXIRamydOanYDSKHztGPmArhZ2JliQAkwRs2IZU/SligUAjBagdaZVKjyz2mVi4ZpchAzp17LhEgRd7GatTL569BznDKMWeEbwtmzcAZIzYpeaywpZvdKCJFVsyIp6NqOCcc0ZHqikhIpxBy9m4NFTuOImzJjwWjFovmOxKek/E4AqVTWsLgISaKEzVCq0aO8IqqQdRxS0bUtRIdaVCQReJw6ejfSRbC6RFUNgYgbE6MvGFNi5zSDl9y5RO/g9pQQJqeNJdERhKUqPM3oaQvB2ghG42hUwAlDKSaCEljpwPdo7bHOo0zCNCBERCjPjGzMNjgSNuUo0UQ4TzFDAoTHp4Ep7YkyEJRksh1j0SGlYoyKZeMoFoGoPQGYxjylC2oCmVeIU3S0rqOfevppYAwOlwJ9DIwhcOgH+q7nNE70zpOURhpN2dQkKQgCRFUwmMRBeioxsTYRXZK/9ihYFpAmQScC+JGH3ZbkcjOlpWJRlDTrDc3lBlEYUJKlrVBJ0MYTLgR8NzLGieN+T71qMnhFKmyRg4/cHFvqJs9ud+B4OlE3SzY+8s3bdwyT48OHW2xRUC/ySPx73/8hXT/w/uOHXBQLkTUbT8/W/LySBH6KSKkobDl34uZ84Say5fLpvnuCOz01GFlblqdpk3Nst9uM+u06VqvVOXgqX+rFOc7Zz5TVP9iFLqRCa8GiWZ7tEN4FHh93WZFsLev1hqZZUM8VyzDkbun9uzc4587L/yeUnTGGaezpxx69WmJtQWEzu333+JhzeLdbnJsYhjy+7/oh79BjhmmkOB8gMc2jW0CIHJYRHpBSzar2ihfPX56JX6fjie3j7jzqaxYLyrLMHmPvCU4QJGANfprY7ndZbWsMafKIKVBLTVUVfHbxjJvlmmeLBbWxVEJgkVzaBqMV9uKSqq64fnZFUoLQ9XTbLQ937whGELVgtV6yvLzisz/5EzAlX725xZQLvvrV1wzDxIfHR9rBc3foGMsG+o7TcU9lNJVzWYm5aFg2DfRHhBthrKhtxaKowEwgFcIIJp2r8MEFlM6whe52S+wnbpYbjDbELq8/puBRWlFtKsIQGE89t9uPObfaZQxupRqMtDSmplAFQ9ezaTYsyppCWhYXNd5PoAL70yPd6YhVGY14dXlJo+p5XKXPYsUQc5fup2nGug4MQ59XNMkjJXR9i/MTyuS9v/f5Ta9NfluHFGZBYcoVdcyRtCnl4lNrOQs83axqiWdBohAZlZoDacozDrOua4qywNjZLoXgeDwxTY5mLWiaJa8//ZSmWXJx9YyYwLnANI2MY8hjT1HgXObrZ+taws2j9/y1Z4pUVebOu6pKLi8vOO53nI778zgvX+gCYyRFYShsRYwRrbKoLs1/VvAerQRNXXB7v+VwbFFlBpuooqG0ljhn2FtjkYWkrCuGPkOQjt4R3ISbBqZh4Pmza9ZSUjWLDCPRmuAD7TDM2oMpM+rJlKtxzBZRiaSpFxS25PHxkZQSVz+8RinFx/4jUkwctMkrgKJACMFyuczK8eDZPz5wPBzZNzUpRtbL7EPvu/7MF9Bm9t07GLoAwVCYFcP4SL8f8MJhleL6i8+pbcnt+w9InVi+umEcTvzm/lt8e8LFRGkW6PVLjruevp0YqBkx/G5S7J3kvbMcB/h261Cm4FJfE+OJabqlMp6FdVwXkQubeF6MLLXjmd5Ty4FLVVLIgd48ouWANQNFlVgFiRwTapwQhUcUEhR5IqEUSUikyuLMTFRMVDhcOtF5h7ALpBlQ9YRJjjYWjFgW1xO6mTilnjFIDjGShKUXFjDEZGjdwLY9MHYTQzeSsk6YU8hj94+HE+2pZdv2OB+QRYWpS1bXVwgjiTaP7Y/AnXE42VNUEb8UOD9SB8fzCoQL3IsROwyor7+iUoa1Lim04Xp9wc3rT7n69FMeH+5pT0fWssRqyV3n83Okj7Su5/7jLaYs2B+OrFc5WjnGRD+MHA8tXTfw7dsPnE4nXty85OLihl/8+rdst1v+6he/xhjDxeUlP/7xj/gH/+AfEmLk3Yf3lGXF6XSkaiq0zauumCJyTs2c+jzBe0pKzE1hPleCCzxZb4E5i2IexUt1thPGGOm7I7vt/lz0Xl5e8sknn3B9fc1isWCasmD766+//sPv0EuTU2Kizv5VrTXG2oyI1JkgFryjm21gGUmZckjGdjdf6GK2bIT8TfIeicge2BCZ+oGpy3zm0/GY8837Ducmur6bFbN+rsIzT14IiXAa5d25imoWC7TRxAgpPnU/ifbUZsVhkQlmy8UCawzGPOEyIUZPmBPAINE0Nc5oppTQUmXRhfeEaUJVFXVZUtmCsijwztM5z/5whBA4LpcUhWVzsaTxE8WyxhNo/cCHh3ve395jFiW6Lli5iPNw6gaEESyXG16+dPydv/sXjJMjJMWhHXhzv6W+uGR1c01zc019ecXm6ibnR/sA3jNuJWHsCbGnKov8OYvAJLLdSTKn1LmAtJKkJEVRgci4UikkbdfiY2AKHqkkLrnsUVYJXWrqZU1pyuynHAUpQOwjkx85nPYQEvfbOxZ2wVV9RRSRyU8cTiPDoac0BVYXDGPORS8Km3Gl87iqH8aZVTDzByZ/hgIpqTHKZGxwcuiY883lLCqxpiCSiFOOZH1ap6QYiHNWe1HV6NrQdnn/76ac7pUV2Xncj8g79addft93nE6GGGO+7A47uvZIVVrKsmC1WWGLkmHoAObuvKCqapTKu8vgFSFqJjfiQ0SbAhsSVekI3uGnjuADh/0RLQWPj0uMVmxWS6L3KCEZh4E+BMa+x2hNd2opy0xIkypHPcY4G3lk7rTHqcONI1pKqrJkjAEfBiafSEIjiwhCsVkvZgtayVEkuuMBPwe9tO0JlQK3t3ekGDBKkqoyT8nCzCoInrF3CLIP+4mOZbShKMosFlOam5tnpJjY7feQEuXMkhhnuI6ebYbW2mxbTZGiLKhchbUZ3fv4+Ig2mvU6I4AvLy8Bstjp1HLYHogBmmpBqCeUEwgfkMDQtiQ/5eSsJNHY7LlGgraYaoEqatAVykiUsURf4KOmWqxxQeHanilGIgpSyeRLopB4JejTiB9HohtphWO0koU2uEqw0BOh0JRqZEKjZI+JkoLA1Hrk5NFuQhWgiph1DxqUyR2j0GJ2nOf+L2eoRxQOUg/xgFcgKyijY0gJ4e9IfYcWC2IyNNISMIRREjE4arpu4HA6MA35NdQqawVC8oToGFxPP3WM0ZEkFIsGU1qEyK+XbSpG7+hcji01TUEsJKNJHL3DJVjZAl1r5MUCOUaIBh/gNPb5udaGME4Muz1pcvlrDAF8YF03lMbQhwguEEZHcC6LaseR0+E4758Nv/zFL/jtb76eCaWWcJVFZy+eP8doPVsfI33f8/DwwK9+/Wu6ruPq6oppGumGLp93cxxzjNmORhJoWSJFjlHOUch5bgIxawRIZ0dNnpzlyeOZHz87V9zkCCHHQV9dXfHJJ6+5vr7i9vYjv/rVLzmd8qqja7uzLugPe6ErRfQOpEQZQ1WVLJYNT4ns4zDSTS1PKy1rLcF7Hu/ucVOGLTzZR/J4PCebaVsQfWAYO/q+Y3JTDq33nrbLDPdT3507cmMNdVnN3bZBz4z3/OIZrq+vc3pNl2M19/tj9hrvD3n82WRwx8VmQ1kYrNF4/0SAG/FumEV2ieXy/0fbf/7oll1pnthvm+NfH/6a9MnMJItZRZbt6ump7p4eoUcYQIIEDAQIEPRZ84cN9HUkQD3TQkOt6WmVIbuqWIZk0aS7Lny87tht9GGdeDPZgjSEwAniIpOZee+NG3HOXnut9Ty/Z4LrB/aDxyixEfhhwHUdpqyYFhVlUVBkOcN2S9O2vP7sC4amZT6dUJYFz956wrybkU0nNEPH3X7Nq5tLXly+Zna8ZLKcsWg92RBZb/aoNLBYrsiLCafHT3Eu0nSe2/WGn794DVkGRcHk+JRqdcST58+ZL5YMuz2+63iw0Nc7ulCTZ2OiXRjoGPAOjErBe0LviJlBWUNRTrB5JE0SYvDU9y390NMHJ0jqXjrfJE3JyhSbWU5WJ8wmM7a3O9pdy+3rO9q+4357R992zNIJq+mK1eQIT6AdOq5urnjzxRvKrCBPc9abNVVVMRlHX3meo5WMS733NF17uMFKsILYmmISx0LcExMRTxZlgjUJeV4cxlQ+iMjssaiHIMK4clJSFRPuH9bUbUtfS7BQ30sioIyIZSwfYqBp9qMbJlDXcjG8v7+hrhvmiyOyvGRxvEIpw26/Yeg7rLXMZktWR0fjxTHB+QTnetpOAovStERFjYrghp7tGDN6V9/hh54qT0mN5mg+k9Gr1uzqmv1+TztCaK7mlxR5wcXFBXmeM5stDglO2liUTdjtJJ3QWsvEJnQPW/puoPUNEUNaRbK84OT0XGJ90wwVPfc3mj6KP3+78fRNTZFn1Ps98+nk0dp/sIo559huHhOikkNEcZJmBB/E1uYDs9mMGCN/8zd/gxsGnj9/ToyBzWaND440lYuJhPMEYnDkRU5ExuXGaN5cXRJjoG1XzOczTk+PCVEEvJv1lvubB6bTObPJDD0NZNHS72uCG9itN7RWMV1VJCohkBCUwimDSTLSicXkM7AlOs1IhkBw4KKhWp5DTBlev6B1A1FZgsrofEE0JTGZ0w01vt+z6XckrubeJFTG0S5K5lnETeeUSU9NgVV7rNKkvmOramzSYmtPlnnSTERlaaooMoW1Gj0SyiwC8EkJRB2orMfj8W4gsTmTNKcKPbUf2PYv6TpLksxROmNqFgwxZV03DDGjYc5223K33jL0AddHyrwiS3NccLjQ03Q79t2OLjq0TVjMK2xqAEdiM+bTkm1T0/qOpLDks5JQGLo0MtQtaYgs85zcWOzpHNt62CuGuqdZ76iykizLGZqG3c2NpE5qRRw8DI6j6ZTBOV5t76F3+LYjtAPRebq6YWh7qnJKWRr+6od/xb/9t/+W73//d3n65KkEfeUF77z1NkVW8Dd/8/eEGEjSPa/fvCb+lbzvZ2dnbHYb7tb3EsA1jAFVY1qo1obFrJCkx7GBeBRucxivCy9FVnZmvNDKfzMMA855AUh5OZuWywWffvpdTk5OWK1W/PCHP+Av//Ivubm5pet6VqvVIVviN1bQS6tAGSbZHBcCTdeTqEhiJA+673uhluUTtDKirO0HWieEtL7r0Gk6RpLmQsRxMupU3tPXexG39WPUZ9syjKMeHwMmFbGM1ck3wlkk8i878NXFrrNdb0b6lKiJy1RQlE3TYYwiUUZCUtZrppOCSVWw2d5TN3t29Z7eOfaDH2NPhUddFblAIqLY2JK8YLVYMl8uqYee5vaSbrcj9D2xzFBlhssyuixlYzSDD/iHDUIKmbJ8VjJ58hYkUlD3naa+XPNi/QuwCXk1J0kyzi9OiRH2dcfJ+QXvffgRPdCjSKqKpCgpqgmJUYQiwZlInCS0KkE1CYlV9MGT5BlPlm/jtWLftYRKEUpFHWr60HJz/Yqu2dMkoqKeFUt87mmGRqAYRnzkwcl0ZegHmlry46tK0qPm+ZTQB8IObLCHW2hwARXlezctZ/iVFFs3BMGjDg6MJh93gkopwhDG7YnsUzFakJZBaFapzakKeTbDyBjIiwKlYL+pcV7CXLRR2FS8rY/7cu8Dve8wwXK1vuL69obUpOhEk6clQ9+z3t4zm0756MMPmU0rjlYL+q6n61qurq64uXmD0pqqSlF0xBCxao5NFGaaESJstzeEMGCtUOdCVBLgk5ZUkxU2qVAxoWsbdvEWrSxVMYB3qFCQWUu9aXntXtM8bDleLVgu5jAEMmVRNiV4T7PZ0ax3PFzfjalu427bJigjauKud3SDp5wIprXuHIPzbPctAcXCGPA9168HzNhNhxA4O1nST0u65Yx6t6VrGyEvbtbMZxWr5YKT02O0Vux3e7z3WK1pm4arhze0+5p6s4Nx1bHbbOj7nul6jVKKtuuIMbDdbbHWUFaF7Mv3O/I8Y1JWeK9lZZIlRHI5J9owhvEE7h8e8KPbYBgc17d3KJPw/OlTsjQjTXMS7ykSTZ0ohq6jq3ciNGsULljMGmko7ndM85yjxTGpyehaWfO1dc9+21MP8owak/HR3LFPPa/Dhm3jeP3lz3A2Z6jmBElQJ8OSMhHMdQz0G0duPa+bhNwMLIpIYirKVLOcwzszi4prCNeYbotpd8wGKFKwDw7DwDRLyJKE2XQ6EgwDSgeIDhMCKg5EF1C6J6LIUJQonFLshy0OS2u2DKqgMqfc1ztevrqicRbjCqxOUHlK3/Vsd3t2D7e09Y4QdmjTEjOIVhGSgaA9uEihSy6mUxZZyjLLmBcVU6UJux3b/R7bRvqo2WczlEmYPTtGb1vuf3HN0O1p1rcsJw6bZyS2oipSdn1H1zuyIqMoc0yAtmv5/NVXuKZmUUyY5yWZMphoUEGzubnjqn1Nt9uSG8vPfvxjvvjFL7i5vqKqKvphYF/XpKnG+0jb7okPDu8HeieZATd3NyJiswalBVajtTQ9WhsSI6u7fujQxpCq9EBwfGS0x0dz+ij6LTKJAO67Ts6mphlFiA2ffPIx3//+97i6vuKLLz7j6voN680DidUkNhcxtIv/34vz/z8FvbACq8+LkraXfZpVEaugcz1ds6fIC6qyIEtkpL25XwvmsGkZ2pYsCgqxtCnBO7o4MtGDp68b6t2W3g+4IJ3ZEDxdDKA0SS7IyCx7LOTpYVT+uAfvxvH8brPHDU441saymC3xOtDte3RQWGVo2j33dzdEN0HHgfvbKzY7ydN2IbDtPN5HwWKmGUfn58Lf6nvyJGVaVsznCyaLOTdv3rB+uKPb1QTnOFqsyNKUwYjYaKs1bQjU2z1FVTKfLJnNZ8yWC/ZNK9GSuy377Y775o6oDN/6+Ntki4rj41NAUe4b8qpidXxCMwzs2l4yfo0ZrXweMou30BYJNlpckaB0ZMBTpAWnJ2cEpaibjmyWk81yrtZveNg/sO/vafY1nXFoq5gu56ACtrNiBdISn9r2NX5wYwRsQ2IMy+MF03KKnmoYYH/V4FuP3wqhL/gAQQp6kVeohWb9sGHX7tnXLU3fk09EWBOi2KyCC2ilydIccY2M9j3HOOoS4p8xZrSfSKCPD4HbO1nxDL4n+UbX/yhMc8HThw7tDXfbO64frjlenpBnuawetKJzPUlmee+Ddzk5WvH86QU3N9dcX13y5s0Lbm8vOT09pSyzEYMZsNqRGnE0tN3A5u6B4J0ckCZBmZSpXZAlOWVlSDPZLRub0TW1jFG9RwWPZkAFT7vvaDdbrl+8JLz7DrlJMApSJXx3HzX3mwe6ruP+/kHsRV0PSgSqylqJu01zbJazOj5lMpsTlcFH2G/WhIgIzIae3XaNNpY8r5hMJxwfHx9sYq9eeNpG3Cn3MXJ0tKDvW+aLKdZamroGIokxdG3L5evX1Ls9u/VWBEQ24e7mlrres60qjDF0fYdSin29I89zJtMlfd+x3m1Gf68W4Ikeo4VVYL/ZyJ5eK4iBzWZDjJF9XdO2LTc31xwdn/Ls7HQcTCu0H0itQuPoGmjb7Si2DfhgSHeKvm3o1jUzUzCvlkQf6DpH03bUbUO939J0YpHUac47kxV9Hsh2D7xptnz2+ku6dEYze05MpsR0xpBkpCZn8AoLbIYeg+f13pCagVWlyGzJtNQ8qTKOqgWxv8Y3CfSX0DuGGKiGAPse4x2xjJSZYpKJFQ08aIeKDhXkKqHUCIE1mkIrgha403aAIWpa2+PMhMqWDINj/eoOb+eY8ilJkpMkBd12z379wO7hmrbdEcMebTwYTbSaaB0RDc6TaTipKoYso8tyISaieKj3tL3DYsh0QqO9gFPOFoRkz+3PX9H2NdvdGqxl5hdMDZg8Zehq6r6VSWqaUShDvbe4usG3HbO8ZJIWpFGho1AEb+/XvLm6pN/XZMbw2S9/wW6/p653TKdTsjwnAqnVDCpQtzV937Dfb6Wh2+/ox/M0y7Mxoll24PPFQvzvneCT+7rHRivPKCLidN6NCHIBVbmRp+HGZqNtW1kltgJNqvd78jzl29/+hPWfPvDq9Uvu7+/Y7TYsZjPSJB2R6b9hUdzH77yNc46HMYBkWWQ0fcObL+9wIcqPvuf+NiXPS6y29G1HWzf0XSNqdWvoCTS1oes6druNfAEGR9PVdENHOa0osoplfkzUivW+xUUBYMheQvYVIUZJ2Gmakf3MqPi1rFYrUbv3ErSB6J1QCJnq9vYe7zoZ5wRP17ckqWE6KemGHh88eSnWEIVEUSb66zQvY7Rkh2sll4++Y9fWJKkhyRJaAl0vSVzWWNqRfFWhaZTGpQ2dTnAmF9Vm0ARSlFaym623/Lf/7f8VlObJkyeUZcXx8QlVNWF1csxydczp+TlpmpBmKQ+bjmZoZfdI5J1n58R4Svv8dATjWJLMUk5zqmrKk4unoCNRRa7WZ6zrNW+fP6ce9ry8+ZKma+h9Rze0+EFU12mZ0LmOut2RrkaLhpKHOPSBbb8j8RYTDdPJjGyWcfTOMUVSsSqPGboARrFv91xeX2O0JasK0jLFppa0kA658/IitPsWhSK1jRzISsuIynnMSGRr6kYuC6Nfd7OR52n9cI8ymtliDgrqWsRaxthReQpdK97W45MVWZZye3lHs6spzjJOT074z/7pn/DWsyf84z/6A4o8pyoL2rqmqXf8sz/5E+7u7nj58gUPD2u++OpL6rpmu33AJgmzxYoksZyeHuG9Zl9v0SbDJA6b5ZJiNXbQIzVHgC9pRlFkRN/TbB/wvYRiTMqc5XSFUpGbq8sDcawsBRf85PwchWJ30tC0LZdXV/SDo+vc6D3OcEDXdVxeXnJ1cysuER+o2wGUFtvYmN2dJCnlZEbX1rih5+TkhPPzc1bzGV3b8Mtf/oKH+3tevnrJze01ZtzLRySwqGsa1g8PXL25HFdUnuAjve5pu55+8MTR+dJ3AgFq6h1lVZLnKTFKZLAPnu1+h3c9PghkKs9TZtOJdPG7LYrI0Uq+3l3f44OM89M0oW3qkR6ocUOH9wMRDzpSTnKcM7T7HSEo+tqgYuBoumCaVyM9UJ63tm3Y11s261vqukXvNpgkYbncYLThrOgpVpH4rWNu+oTP2442appe4YeWVhlikmONReUZGE1vS5xy9C5DDw16P/C6Dlw1O2a5YVVdUOmKUh9DU9P0HTNqUtVzc3+PiR37h9dkqWYxMyRJJC8jKgFygaUlWmFMFH6ECUQVsSgchv3wQDd0DK1m1id8dJTz0A68Xr9iN1jawVL3gxBAO4dzirKcUWhNmcoz9fTiKWWWsSomTIqSZV4wDI5BWZp2oN01DN4x+MC26eUcrh1VkrNN50y84fytC/xsxsTkZEFTDx1eIVqeMQK4axp839MH6Lqe5WpJ2Bte3b3hzes3/ODPf8jFxQXvf/ABs8mU4D0nR0ds1mvJaB8GposZxloGN6C0Zrmcj3HMO+qmkWyBkbcfR4Hbfr8XN8eY1Jdk7cgySTBJQlkJYz3LszF7QpP74kB/FMW78DTMqB8rq2IMSqo4Ozvl+7/zPX77tz8lzVI+/vgjVqsFt7c33N3d4vqepqnHCvwb7tBPFwvBqm63RA1laumamu3DPaLYsHSdZMzmWSOAFh8Z2m7cQTic69Eq0nXt+JLsRsHTQO97huCozJQ0z5gu5yhrCHYnCmBk9ymQCtkTydhWbkCKSJnn2EQiF40xtKqX1CcnYBQFhxdUK0m9iTGMaFlNlqegAj5oMlOglEWrBFCoGIhKuMGS06wP0XYueAYvEY3GJgIZCZFd00gwRVHRR1D5QOh7VNtB0mHSlqgeYZAyOnODhF78/d//hK7vefnyFYv5gvff/4BqMmG9WRN94PTkBBsDmVaY4GDopa5pxWw6wRhF5zJQAW0Vj3kZ0zLn9PhENANuwCrNLJ9ynp3Rqx6bWta7B+7X9zR6T93s0UZRFgXtIGlX0+mE6XxK38q+t913DL0AYBIFWZUzyaecn16Q6pw8FKRZijKKzg9s9jumE7ktZ0VGkidCY9KypnGDo+4aVIRBD/L11iLkCz5gbcSYSNe2+MFhEgtKUbc1zg00dUOapWRJiouBtt1jjBZ/+RhJ6FyPi34MgMi5u5SdWWITVssV/+Qf/ye89ewpv/e9744HC0TvCN6x3+9ompq/+PO/4MuvvmRX7zBGs95uGAaZOCVpwiSvaFtH07SoqPAomWz0AqgxjzjaR8hRUFSlwQ+Gfi+eW2IgSxPm8zl+6EablQi70jEffD6djhz2KXVdU9e15Jz7GmNFhf4oxGnqlsEJl9t5j48yojfGYNOUJCtIUvGVS1cQOVotmVQls+kEpWD9cE/ftdzeXsMmcrU6GiNdRRG8fViz3WwkxxyNVmYMQFIHYIcfYVJd2xKDZ78XS2R7ciyKdSPaha7vicFBHCNDraEoRAHvvXDwT89OhUPw8CBY0Twfs6d72WUqjQ/ukMCnNaR5ihkU9S4QXRRAitZMioo8zWEkCgoXQbQVbVvT1Ht0u8dai0tlhTK1lqTSeD3BbiNX/UAMht43hNgTMDgViSojVTnKJAxWo/A0wyAW2TZn0/XsupbThcWdLFimKTGt0GGNVzVFlmFVR9NsYBhw2zVFqkhCSp7LKlF7ISgoA8oqdAigx45GM4rcPN43EAPWJRS+5KIqwQ1cNjV9HVnvwakUr+yY8y02LZ1YplVOXuRcHK2YFCVn8xWJMiQY0qhx0dDXHW5X45XEUjd1I6hTp9nZlDT3+KTi7fkTlE5J6oDfNjT3e4bR9ji6mwXzCwxebKxFkZO5jqHv6dcb3OdfkCYpH3zwIVmaMq0mzCYT5tMpRZGPhVpw2F3fYTQUuSCCFeLKWG8e0Nag7aOlVJ5ViTHVoMRFo5TGZBLXLFoOK2fbiBUHgZ6Kmh3i+Jz7ES0eguC80yzlrbfe4k/+6Z9wenqK1oqzs1OOjpacn58xnU64v72TSdQjGvI3WdBf/vSnaGNYFgUusRRJQgIQHA6FA3ZNR9sPXN+8pu8H8ryUhDbjcMZxu7/HGsPeS843hcFgUGQ02weaZuBh2NG2Dt8aGbFp+QL1dcswOJq6ETC+DweikiDzxKrmh4bddkfwUZTRYbQShIAbRsZzcGSppSgTXAzo4IWepBL0eGEIPhKik0zn0R9NAAPgPX3bkc4WHK2OMMDxYsl+u6Xre5q+YegdXd2glGaf7/BeQj36rqeuW9b3a67yG6xNpIsqcskbN5rJpOL3fu/7oDSLxfxgj1qv7/niyy949fo1X716ibXiR57OZhRlyXvvv0ue5/zlX/yQN1ev+dM//39R1zu6oRFnQKI5OzvhnXffYj6fMp1POHt6xnw1J7MF0UQups+Y2gWLZAU68v3v/B4+Ovbdjs1uzdXdJUmisRjW3Zq2dujeooKhSKvRjpYCil1To3yL292zb/dMT2dU9Zb8PqeYFKPXMsFqTUDGSnWzY+gHdvsdREWiE4wyJCZ5RLyh3XDwKtvUynrGCWo0RI+xRrKytUaNvnLnHE3TkGQJaZrgOwc4fuc73+X46IT/8p/9L7Em4Xh5wnw257uffJs8z9g9tGI9TO14C0+xJiOxkW999AlPn7/FJ7/1qYgh31zysN7wdz/5Cf3g6fd78nzKex88ZbOtuX/Ycnn1ivbF5zx5csFsNuXsdI7VC3brnKFtWN9cMvQ1MXZkmWY+WTGfVkynOUblcmkbD6IkTTHGsO92qEHjPAzRUc0rbJ4QjWbwnnboadqeuu25vV+z3dcMo2p2eXSKNoZ9XaOalqB2wqe/uxefblny8HDPy5cveeeddzg7O+PiyQVHRyvevHlNXe958fIlTb3nxYsvaZuG7cOaxCZUZUme5ZR5Qdf29L3oCbQxTCcV2mjarmO/3/HZZz9nUlXE4Dk6WvHOu2+Nk7UggCClaPsO1Qky1ehHUmXgzdWlAD6KUgS0ux3CNEgxaYJNDKoFCCyWC4ySVUPXtfRNLq6VYaCYlDx78gSIhMduXjHG2GbkWcow9MLC6AYe1nfjNKMCkzIvJrT9wBl7WtXR6EYEhTEw9ArfQ9NmoC0mq9AmIcumGG0pqrexCnofuX3wdHvPxNZMTM1xuWOat7jljmnWkKYRm+7ozSVD9NxeD+Q5HDlFYiGxMMlhmoMtFDpV4EW4PIQ4Ip41udFcVAnLABO7Ye4datLxs13L1V2NmT8nmZySzc/BFLi+J0ss//z3fovFpCDVwm3Yj5ORzjkmRcVsNsN3kWbbc1SVkKZUpqZ3Tt5lZVBJShsCn12+YhoTzpczXl5e8w9/+Zc8XF5z+9Urjo+PmE5KvvzyK+r9ntXRERG4fLjhrhZxXr1r+PL+htYNpGVBWZWUZcnx+RlZVVK3DV3f8+LVS5q2ZTaf4ULg8upyHKvnlN4xmUyEA6c4wMbKSXUYtSdJgnfhoFJPkoTZYiEX/fBIkIN8jON+DG8hyntWVRUAzX6HtYbFYsFHH33ERx99RAiB27s7yrKgyAveeuttvvPt3+LP/uxPubu/l13+r1nUf32W+3ZLkqZMqwqDwo1Uq1lV0XpH4z2mA2Kg71rqriWMn0PQEuHZDi06GOhHH3pqYETmxUbJnjsMRKdIh45ERfwI5BdP8kDfdzzyO/XY3TzuOFwvN6q26XDO44aRUDX4R5sxcUSt+qiIJCL0imEc2wubV6lHPijgA1Ep1GPgAupw0BitDzfCRGuGTkIohEUuubhKi5AsuDFuFUWgH4MqHDZNsUnKJElIjFh1jNGcnJyMtLsZznkeHtaiIN5uRQijZSccY+T8yQXL5YonT87RSvHq5Us+/+Iz/vKH/4HNdk3T7dFakWSWp8+e0DZ7VkdLVkeLcUepKVWFTg2FqVCZRnuFMorJtMKFgUQnKK/p8g6lBVG5jzXam8M0KLOSKf+YYtb1PWGIdPW4k6pysiojqRJsYdHZuB9VEKI/dEOD6xn8AEEmC0GHw9cdxKYTdEAlqXTeI9ZUcMECCUpS2a8H4mgXETa7/HNLcB0xBJazOU/Pzjk7fkqel0yrOWVecLw6hhjp2wYdFVFLwIS8WAatDIvFiulszvLomK4fKMopN7e3fP7VS2hamk5AMmVZ0nQDKOj6lt1uS9tMKXJLNq/I0wTlclrleYhutEyKzaYoMvJcilJqZTJk1OPERVqYfuRDD34Mk9EKbTVJavB9JPQDzjv6XtT1TdPgRqRlGFMlJD5WEdAoPaCdG1G6AyCxwdPpZOzERZTVzGcYrXj11Qvu727FL1s37LdbplXF6emZcCdQ7OuGtmkPFKwQg1zUh56mbbm7u6PvOjbbLdV4kMYgXZXWMl5y4y7fey/qeiQwo25aQoxMJ1P0r2CBPZAc0M5aC10usRbXNcTgsdbImDU46dAnldhk9/sD7UubR5uuTET6XqBLfd8TYiAdUjSGNIHcRKY2kMaBNAZaP9AGR+3G0ClnCcoS4gxjCxKbSxiJrSBovNM0bmBoOnqtaI3GRgOxoJklpJRkxR6tUoLe4IeOzc7R9mD7iHWRVEV0gBxQZsTqaojjexnHSZ5ByTMVINiB1g4s056Cmtht0VEmlzqboNIZxJosSXi2esJqktPv76lDy6bZCe47gCk0k6IktymJMqRJjslyglP0TtDABo3SBucj27YhsRFTzvAjwGt9/8CtTplVJZOyoN3v2W02FGVBNCLqbYYOFwO9d+ybms12w+39HZ6ITVOyPEdbg20yuq4ju7uVZ14rGF1UIUaxXBsrBTtGAvEb+FYZtRcjl72p20MUuJwzo/03SKHnwLcwhKAOBEM9Qs2UguB6sizj9PSU4+NjprMZ9X7PbrejyPMxK2LB+cUFeZGLTfF/jg79dLmQIuL6MQHMUeUZk8WUl9fX3F9e0fYNve8pZhlJSKQTGAYGNdCrga3bg4M6yC6iIBf8XpIRM010hib2tN1Ad+9BaZp1B0GR2RytDXmaPUJ8vpG89XWaVoxqZL0LgjbGOCZKQVRx9NgmKBUZokNHi0ZLNx/dCPDWJDYVQY0RWU1qZIfbhoFEG6q8INGG6BxWG4o0ExuJj3T7jq7rscqIjSrJKLKCaTUlSTPyohx1BwEzMtsvzs6pZlO++os/42G74aPv/Baz+YzT0zMREW23HB2tePrsGbc3t3z1xRfc3Nxwf3/PbDGnLCv+ww//gjzP+OnPf8r9/R131zf0Q0dUHpulVFkBLnJ/88Dly9d0fcu//lf/mqgiH33nO5ycn/OP/skfcTI7R2G4u7nl3/3rf02SJzx964w0T3k2e5uoPJFA0hVUbA5s/MVsgTGG7XpH33le3b8heAh9pCoqjp4e0dHT0NJuW/bNHq8SrNLEXiYj3SB890chlDESc6rMOLsLEtTinaicpXuDNEuZL+bYJGEynZJmKbP5jKZrUVYJjampWR2teHLxhIfrG9r9nm6zZ3+/4em3f5ej5bEcQNpgouQS5EkunwOaoRVPqgsSyzudzjGJ4fWbK4iek7Nz5qtj5sdn3Nzc8lc/+jvqpuPF6xc4F7AJrJYT5vMco3r2m2tuVUeWWEz0eNcSfAuhQ4/e3izTGPs1HQwNs+WCsiwPiNzPPvuM7XbH9e0dMUJWfs2OjzqgrKJuG27u7kAZpvOZZLQH0RJ0XU83DNgk5eT0TIA6SSrdyDDwcH/Hdrth/XDHj37017zz9tssl0uxZRYFfd/Sda0E2EwNi/mMqixZLpaMYbViu4kAEed67u/viTFyczMqio0lSTPSLJW42pEhEWOkqiqqqmS3XdO1DXrMcj87OxtV7ve4XqZqoEb2uwICwQ+4QY3gHcukzLHa0LcZcQQURSMJkdkYmBSDo29bYRHESJYmmGlFCCuqquD+PhHAyeAYvBtXLh2J80xsyqfvLth1A+u6425Xs2726NDQOIfWGUElokYPPXYoUcHhY4b3ln5IcW1PXzdM88A0E7RoYS3ZUcL8SPPe8++TmC2Xr/4dfbumnN4Qg+PGexhqVLumaSLdFmZlpMwiSRHRiSKb5GASem0JaFzfYzBMTMo8iRxlMNWO1LWkfiDxgTBAjIpFtmSSZei9o63XfP6zH/Ow2/CLyzeUkwknF084LucsixkP+YQ63VIVc5KqZFUtcUT2/SC6iq1kZPjMMmhDowMX777FebGgu3mgu9tw/eaK3d0DrpWz9Ks3r+iiZx066uBwCorZhA/efsZsNmOIgV0jY/5HgEtW5qRlznv2A5q25cXLl/gGyoko3uu2Gdc/0ghYYxhlV9T16JZpW9E/aIHJTCeCMt9ut5Iv0vWysrKWGIM0neNHllqi1ux2uwP3fblc8gd/8AccHR3RtS1aa5bLJVopuq7jk08+4fz8nPv7WxaLBdvt9gDN+o0V9CyVWMTOj6hV7+T2N/q1MRBVkP1MDDgC7SCHRd2Lp7kdBPsalDDBlVNgFToagqClCAjtre076fK6ARU1iU4xSm4/cuN+DKSIYlmLEvnox6SsEOJoaxkDXsaCjgZtNTF6iZdE6EaPMZNG29HjadEYLPJz9TjmVzEKnCPL0SiGrh89zoE0EX98kRcYLYeOjB4riqKkLEqyrKCaTOmGgbYfRoTj14EMj8hL8TxH6v2Opm1HVbelKkvqYk+WpqIJGAbaRtYQ11dXJGlCWzcE58nTDGs06CCOAJugAdcPNHVLvd+xb/b0buDs7BllPqXddCQqo910NOuW7e2eJDWsi5KyKjAYIgKqYVAkURL2jDGU+QStNLUSwdkwODlko3zPVaJJipRyJsWoG1rZpyhk5B5FuCN7ThEzySpE9mlxTFKVLBe5EBHlYqeMwSRCLBRxVcFisSRp9uzqHSGKbz1JxsAPbVCBw48iTSnzDP0YeHLQoOjDPvVx5C+BIjI6FsCRlShVpbBp5MSmoAyz2Vc4v6a5uZc/AApjZJqkohcyXd+ANyRKBHBaBYwRTKsxCpR0moMbAEeMWsKNgtD0nHc0bcu+qdnutsRx/ZUkKVEpCYkZ/a7eewG8M0Y/8hiqJEEq9tFXOz6DaJkIeOfpu451kPzm+XSKVuMlNwR22x11XaOUkOaqqiRPs5FDIRHFjJ5+0dJ8k+0uY/P5YsFiMWc+nwujfryoAQfhUd+J4lcGEyMWlki63x92nsQoWpYxUtl7j1LDgWinlBrBH4yTITk7ZH2lRoCIfL3Gp+3wudvEkoaULBM8tQtybozAT4geqwNZrkZvPjhJNCKgMb1Cx4DDQ+hRXqNcMz5rNTEko0aow/teujylKSZz5qsJKnMMKtKrAkyCnbxNTNd4k9J3LfvtXkbrrqdSgV6NU8BR6GU8ZHlA6a8nkMEHohJbFlEmiXhR9JgQMV5gVSjPYloxKwqGfYd3Ddv7Ndvdlna3J00yEqVJtSEzCbkdfxhLamSt5hUEpRmUY0eDJ0qkqlJ0wVOmCdPlkk3d49Z76v2eZrsFI2f0rtnTBEdjIkMM2CzFFjnVZEI2As7sOJ0LB8yzNBuT6ZSsKNjst5jEUHetnL2NZEWEKBHBUUs07oGXEsGP0b5Jmhz85n4Uf4YQ8IMjSSwhpHjv6Puv3yGFMBO6rsMYw/FqQVEUzOdzijxnGIaDjsaHQAyByWRCkiQ8ffqMpmm5v7/7zYezJIllcI5mv6MPnjp66m3PQ9tAnjI/mrGPHUO/5/X1NZv9nvV2R9d13N0/SC52jCRGMmG10+yGPaUrmcSKwXci5Ijyku33W4KL5LoiMakUJyuWoMePx5SaYXjkuocRAcshMSdESW+T/Wckarl4hOgZ4oAOChW0PAw6YVJIsIT1CothVk3xznN/c02Ijth7JlnBO0+fs9/uuHr5emT3Rp6cX1CVFdv1Vvy4STbG4VlsmlJNZ1TTKavjU9abDXf3D1zd3PCwXrN7EF/u2ekps8WM/W7H1dUVP/rRjyjLkk8//R20grbZcn52zLe+9QFffvklr169GhufSF3v8cHz4XvvAZF33nqG80Iga7uGh4dbESv2nsKkFNMF83JORPHxW9/m9Oycn/zgZ3R9x3a3IRC4yJ+wb3b87f/wE4xVJEUCWkAWq5MVs8WUo6crJlPhD0ciO1MTDBjdoVVEWU1IPJt+Qywi8ycLgg2ExJN5iw2SWuWVw2WGYJXsjWC0HUkl1/LNQ3m5sMlqxTEZLVBuzJkvqwlHx0d8+umn3N3f40YxTNf3LOczEp2Ai/jOMcsLjmdzcmMxEbq2RqEpiooYYOjGA330s09mFhfE++6dw7mB+WLJJATWu61MXdICHxXvvvc+fPY5P/3Zz8exrRmP9kA1KUiTVDy47cD9fgsxUJQaXRYYMrwbJMyl37PfjTsjArf3N+RZPk4qPFe31zRNQ922+BjZj5hlaxJ8BOcjbS+izYftjn3diepfWz5++ozJdCpwpxipazmkXNdxdHTE22+/zfX1DZeXb+iahr3b8upFymb9wFdffE7fdfzgBz+g7zsuLi6oJhPeeeu5TLOalr7v2W13AoCyCdv1A00tYRTOOaqyYDab8S/+xT/n5PiYDz94jxA8+/3uwOZPslSiMaPHpgltWxNjpKhKCUwqCpq65sVXL5hNJ7z37rt0XcN2uxb3h3ecn50zm03ZPjzIVKJthAhW71AxslpMUBpu767o2o6uaw4F4fHyIRA5oSSmeUqSZ8Kp0HIxSjJLwOPjPVVhmU4TTjkicMrdrmXfDry+3bFvBu53tYz9Wy8I3nwNGGK0pFYxWWimVcakTPnjf/op3/ud7/CDP/+/87dffcVPvtozmaT80//0f4exgavLz9jcXPLLl39DErYU8Z7KNqyKmsZd44YNagtKRRZhhy0sQ2XwJtKagmgtqlzy0Nzz8y8ueXjwZJSkPdh9A+6BJId/8o/+iMVszt/8j/+Wzf0N93eXoCLHkwWnR6d89OxtTpfHzEzCKi8ZJjNSm6GjJtgUP4rLmthx27XYqLCzJUMXeP1wz3KwpDEhKXIWqyU/+esf8ebFS56/+zb5pOL13S0737FPNLYquHjvbVRiCUnCZDZlcXzMxcU5FxcXvHj5ktvbW27vbun7gY+/8wnVZMJb777DervmBz/4Abd3dweGQd/3hxChLM/lmSvKQ9KfNobpdArAdtuw3+95+fKlrDKTZIzDLuhaeearqiJNU8pS7GqvXr2iKkv+t/+b//UBAAWKzWb79RppXAudnJxwfHLCv/wv/gvu7+65vr5mGPrfbEHf7qVYdEOPyEUCTd9yv35A9RmqzBmix6QWFz2d6/FKIjddlNzn4CQDWncGazQ2CHbVuVSoXo9BKzEIAcxFvM1QQdGpFu8sijDuhBRukJGjRDJKNxhCHMNj4uHX8kEeJFHPgjYI6Qfxssu+RMJhsiwjMQmq82g0iTHocV9vDj8ks/ZREJFaoYAdLVfMZ3Nm5VR2RTYZx5ZeAAR5QZmXTIqKrpUxTd91bNdrLi+v2NZ77ustzdCz6xp2+z1v3rxiMp2y3a4pikIuQ1qRpglHRysSa+g6UazvdhnOO2bzGcCh41AaNpsHdrsNwXl2251MVmIky6WbnZZTZuWMq9fX1HVNDGCNZZIVdPuOh8sHtFUkuZUM50RhMLjWURUVOkjhVRpwcqNSaKKSIBUfAk3fEIgkeUJWphRDTuYs1it0H3EI7MH7QNDSOUU3dkBjJ6QeQxOQ3aaJZnQffB2CYEaxICPood7XpHnG6emCZNzNPoKI0jShLDKZ2Dh5aZQW209AjYEf4zOj1djVCqd8GGTsnyQp2hqhmnmxaSVJwtHREbv9nouLC9qupm1qCIKgjd7JxCFIp6612Omy1ErYilb4XoHvR0eHoJONEpxqP/SSV+CcsBN8IIwU6Tju9EJ0Y0RrpB8c/eDG4BkEmTxS8GIM8m5EoQF6L/YzSU7saNuGpvk6Na1pGpRSo5+2Zb/bjnvEKLqSLBtV9R5r7WGC8/i9sdYeDsfZbMpiMefs7Jzlck5eFPRjZK7RBjUq1mOU5zGm0qXHOOpR4tewIGBkyQuNK476APmQv38M7On6jn5MeNNK3u94iOjtD9O9+Ait+sbzZ0fqV4iPHbo8G8qIX0XFIBoHDQaZ+BWpnBfLqiCzKYqe3kHnA4Ge6Dbi6UYIeUZZZtOM05MJs3lGVhru1mu+en0FvqGqcp58vmYyKcjyZ5AmdPEVvTPi4zeKTQIhlOQ4lO9EVd9GLBJ/HGwgFJYYE5xLaAbLvlOEmJFn+oB+LfKMclKwmuTMyowY5BzPswybGGbLGSeLBUfTCaU10HfY4MmUwhLRMRKVwquRR59YsjTBosnKHKs9phXY1Hq/I3UD1uiDKFMZQwBMlpJETVEmJFXJZDZDpRbShOl0ynQuXbi2o8YIRKNlDWkmmPJklpAVOW+/8w6T6RTnHOvNhiRNqeua3X5/CBd7pC3KL6MPU5/HcKdstNalaXKI4n787x733qKMf5wy5axWK+bz+fhExkNYy+N7GQKH98yOu/0QJR3yN1rQf/LLn6GNwRY5WE3ILHf7NT978Rm9UvRacfTkgslqTrhU9DiyaYkNgbxrRCxzu4EIdVOTJillUWC0Ik9S2hEK4fwgY4zOQ5DYUoVm7R/G25Add4tC44pE2raj7wfcICAYY40EtDix3UQdSR/33qkhLTVJItahx4+iKOVzSkus0uy7DdEH9Ej8SZFT3SepjI+GAR0hMwlPz59wdHTEhx9+yGq5lPzwKFnXfT9wfX03WoSgKidMywm77R48XL+55qc/+Sl//5N/wCtoVE8XHFf3t6KY7xpm0xlVWXF2dsZHH33EMHQ09ZZ33nrOydH3uL69YbffjoeYFHLnHG/evEZpxWq14MWLr7h89Zqbm2tevnoho7YY+da3PuZ4ccrZ8oyL1QU//7tf4PeB87Nzsjylmha0dw1f/fhLtNUUk5yiKigmBTdf3tD7jvs3d6xOVpw+OSMtUrx2xBjQor4R9rlr6XYd5aRkMpui1JxqkpMPCdZpdnZD3/ak+0aKVDciEnftKDIMaGWxWsIq0Iq8zGFUnfbDINGbiR1VppGr62u+evGCv//xj/nup9/l93//D3jz8iWXr17iBrkEzecTjk+WtH0NdWQ6WWATgy0U3oMJssPOchg8tAPYFIyFvunphp5lJeKZuZ3TdQOby2uSNOHb3/6Ep8+e8NY7b/Hjv/9b/uovf0i7b+n7mpZOEreShNRqqtlE7DRZgjWaPLO4fqAtUnbbLQ8PHWUh4KbHAtO1g2Q4e4+LATVONVAjhCdKvvXgI9vdjvv7LVkuWe4oESbttgJpWYRIkojo1TnPrq7Z7db85Kcb7u/vubu5kxSosmS9XrPb7bi/v6dpGnZbobzFkdiXpukB+vOY+SAWU898Pmc2m/L04gmTScVisaCsSt59522sMeKf7yUWuapK5qPwru8HEptJgFOWHbLRm0bsc957URIrxYtXrzBakSZaGBKJIXpP1zaHw/jh/o62bZjNpmNSW8C5nv3QSUhOdOPB6mSXH5AxrFZkuegLkjQdD1tHJOAY0DqibcD5ntY5vDMEr0lMRZqnzJ6eEDHsW4HWXN4+ULctN3c3eKQBMtFglOWDdy74vT/4mKMj2O1e8Rf/4S/4q7/+G7QS3c3/8y9+ybvvvcd//V//nzCzWwkt2XzF+nJHM7PUTcbFJGWZr0jiC3TY0j1EyUJvOkyRMCmmDL7idpdxs8253ZdEM2G1moKZoEzJt956xunpBc+XBUmiqAoDvmDx9IRJVfLW01Nmkwmnx8cSjX13hW72lNFjoxNRaUyJSmOKnDJNGE6OsdpwPD/G9pFk2nH/0y/58Rc/4zSdcpJMeP7ee7z9/G3u6i2tHzhePcPnluRkjily8uWCJM8oZlMmVcViuZQCvdtS9y1ddFRzicguyoqyKjk9O8Nayyff/oTNdssvf/lLbm9F0Pn555/z85//nF29p2lFwJll2YGjLgteCVyZVCWLxQeHkLHHWOBHcfUhUW2087777rucn5/z27/920ynU8k/V5rJbE7fi9bLueEgfO66jsurK25vb/nRj37Edrvl//B//N//5gr64vSYCDgFWE3MEyZ+yWn3hK+uLnn15jV2PiGdT1icHJFOKnSS4LwX69Z2h+97XD+Me2dP3/Z0pqU1Ke2+oWtbxFMOdlRCJjpBKYn91FphkzGi1Wj0+AXOsgxtLIPxOCcecCKUZSniKhOxVkaeSWJIM9mnJal5XJMAj2r6kX4UIoQ4TgpkD6hCHL2gGtf1JMaSzuYcrVacnZyQJykqxJF+J7cqPzgI8XFVLPuyCHYU+GVJSmZTNm1N6wb6RKIM1ah2T6zc8Ov9nv1ux267PYALJmVFlRcyPuw66tHrGZHD7uHuXsaBIbB92OD6AYNmWk7kgB0FfSrAl59/zsPdA5txFJqnKalNGJqOzKZ8/P5H9K6n9z06kc54qAfqZs/1y2u6usM7T1Hl5LMMjMIr6UJjgnw94YBfjYiewSaW1FjSPJV9VZD9lDWWoZfISzd4EYXJQBORWQgZisjYJamvk7aCQIdev37D5ZtLHu7uaJv2kLRnrSUvC6IfBGQ0KbCZRicKlSgwSoA/DtohkGpNagwxKqKK+Ch+eJ0YUpPgowcPIWp49LiOr3+aJiwXM549e0LXbtlvHmh2W9b3N0I27Fu81pRTSeYTHYU6dIJFURzU/8ZINKQa9/EBhR/dBE3bsd3X4t+1Fq0M1sgeXRvDdDYnyycYnaJGfQdKkuSSJDnoUSSJTlHkuVwIYqAsCtxsOorVAtvtBu8cu52MxbUZw5m8xNw+JkNJpyy7aOccXd8LDClJOD07Y76YM5/PyMYIXaL4vpU2TCYTqqpkMpnw2F2nicUYDZTEGKj3O2IDXS+783Jaig9+uyXLEozOx7AOI6ExnWQ7OD8wjGyMbDrBaCUYaiJ6dL2EGMQRczgdxnNiRHmqOE75RsuSj4HeDyPARSaNDkdUCVEZohIPs2JAEUlVAOuZFgKAwVtccHS+I801xSTh4iTn6VlFVUQ0DcHX+KEGWxIdbHc1+31HjAlZOuf09B1etz0v6895HQJdO9AOObtpwtysyFWGjwM6BEJrMFETd9BpWAdD6wtscULQJUpPMKbE2oLFfM5qMcX3e1y7I8YObQKTKmNapUwTTaE8utsTmoZhvyO2ndhLg8VERQw9IUhjpDTMyhyhPz5Ob3uCidgqp20Hrpt7VklJkVr2Dx3btqa2OcrmnM9nZJOKydEKm6VkVSlch8SKUt178rJgFmVaE4nUbYOymuMozIJH3dJ0Oj101dPplNPTU1mB7iVB0XvHZrNhcO6gn5Exuh6tsQozhnb1ahTxajNeur9OFn3+7BkXFxcURYm1Cfv9HqN74TKM8cLOC4EuxCjgqTH/4fHf/Tofv3ZB/9b3fptuGLi8uyFqhSoz8rMTVh+8y8v/7l/xV//wY9RySno05/1PPmI6nxORPOUvTn7J/e09Kip26y03by7xvaPe99B6qB1t3TC0nRww1lKWBdampNkEbSxpJjQeZRnHHl7mokpEPShNve/ouoH1ZkcIgZPTE9IsYQiNYEy1J8sS8fSOCvlHpOjQSwCFjw4dNanzqBBpdnv84Gj3NWmSsJzPyG1Cu9tzfHTEyfEJH77/Pk/OL2jrmr5uaNt+DBYRG53rOjngtYEQCM6R2oTFZMZqtmS1OGL7uqZrGtAJ2ihmk4mANboOrQ3rh3uxCFUVZVkwmUxwXU+93dF2DX3f8+bNJU3d0PUdbuhZ3z+glKIsS7bbDe2mJrcp7zx9i6aRMWppc2Lv+Tf//b+maXuePn3GcrlkUpRorXn1+iWTdMJ/9b/6ryQF6Bc/Y9fs2NZb/Naxudmwe9hhUs3ZszMms4qn7z0lKzOSSYJKNboUcYRRmhj8GIDiJBwhSyh0hm97KWhj9+V7P05eHKieoXciYgwcJiDRixJdKHCGoiopypLeefbNhlevXnF1+YaXX37Jtz78EEIUd0VVcnR6hFtUHF0csThbkmUZ1iSYXKw9+2ag7z27umeiU3JdEYyssTvv8G6gLFKszdk3e9o+oJMEpTSr5YJhcGx2WxID56dLTo+mfO/Tj3m4vWZ7f8e//X/8Gz775S+ot1sgcna0oChykrGwEh3WJkyK4rBqub+7Y71ek+WCP/ZR4SKstzXb3Z6bu3sikBY5eVYwm4lg0dqU8/MTVssT6rqRONMolyIZXzMWeTXyEhJms9nhIJmVFaerI+7u79nstrx5+YLNZg3IiHEynZFmYg/a73bc3t6O4Bd/oPzVTc1ut+Pp06csl0s+/OhbnJ6eMp1MiATub29GXK8Q4Y6PV5RFznRSSTCPdxR5dvCEKwWXb96wXq+pG1EKP53O2WzWXF5eMp9NyNNjslSohn3f0zY1cQzr6boW5wam0wqtFHe3N6gQsFqNIqnx0jk6Cw7XfvW1XfAx7cxHz+B66m6P1w6X9BJoNOp2jMqI9MToiYMnRo0NEaMiySwSsTw9ntJ0DffrHbNlyfH5jE+/teS731qxaz3buiZhi2WPTTJQhrZtaNuO4BNmkym/81v/BNek/On6p7y4cnTdjg+fT7k4yfjwZMpR2bNQa2zo6NcblLXkOFrtuVKGrTuiPDnHkTLEjCLLydOMp8+e8OR0ye31a5nouC3GwtFRzjxLWRqH6QfCzYZhFLL5oDBRkWaKxEb8EAnBYFNFMAnZakbvAg+bGt90DPs9OoHF01Nu/uErPvviJR89fYezxYo3m3uu1/fUfUHu53zr7IzF8RHHF2doK1kYIUiYk4oBFTSrkxOOThV3d3fUdc313S3r7YYnz56BVnKue89kMuHo6IhPPvmEJJFn5fr6mvv7e/76r/+aV69e8bOf/YzNdsvgBrTRnJwcH8bkjxoL7weaRrRmjx37MASs0RR5wR/83u/z9OlTJtWUEAL1vsYNTqKex9VN1/e0bcscDm4d5z3G/tpl+tcv6Nf396JeD4EhRJp1RzapWBwdcfbkCW+99x71ruanf/tjrm8fKKZTZvM5Rhu6fkBrw9HqmDIrSTG0u5rN3RoCdI3sy7WypCYltSkqaiHN9QNah8PukkHAIWmWcHR0zNnFBScnZ6xWRzT1QNc5Pv/yKzabDdvdA8M4QhuGjvv9PXmRosx89KUHsrQkzQrq3UDXeXKVYpVmqhIsis45hrbl/vaWSVVyulpSZBmzyZTVfMHJ6ogyyyUtq3f04/RB+OVjBnRRgdYoY0nzAqstWZoxqSYsl0tOT07Z1Ds8kR0jvH8QUU6SpIdoyPl8zqQqSdMUazRD37HbbmSf6pxkh/cd2/WDADBa8efW+z3D0JOl8mtNJhUE6Nue7XZL07R0Y0hG0+xABf7ub39EUcjt3GjYbTYE71nM5ng/sN9uZQemE8qyJMlTXDOwCzvur+5Iy4xyKDGZJYuZRD4mEAbPoHosRqyBUeh94hYUe1GMipDILTXLM2KAVveysxxjDIOPqKi/lr57uL6+IU1SdtO9hCkUBcdHx3zw4beoqglvXr1mt5dEPJMmpLnF5gmkChLxuz+mjwWTojJFZYXn3A7j4Z4APkIIDLGTsfy4X2/7hhgVKqYHyIRzPV1bo1XEaCizFD2d8sF77zEtCm6ur+i6FmKka1r6GDFGk2fJKAZUhADOBYJYNOg6J6z4XU3X9aAMWV5wdl6gjaWaTrA2Ic2KMS4WsaEpYeWHEEgysYFKNGSQwhAB1ZPnGVVZjGQ+2bszKsHzLGW5XJDnmegLlIRXKC1K3qqqWC6XlGXJdDolsQlpkrLf72mahqOjI6bTKYvlgjRLR2iGZT5fHMaZxmiyMdY4SxPKkVXhhv6w148x0ncD3gdms7mkOj6I+Pb8/AI7rp36vscYNe62I+v1A23bjOsAQ9f3oxZGdqODjwfVM2N/Hsa96aNOQNTLSnzdyHP7mL5ldERZO1oMo0yRQiCGAR+9RIEGdZhY6XF0Z3SALBJmGc+eHvPRtz/mZDnB93vurm65vn3AdztS47FqkN/TGjLj0aEjNSnlPGe5mLFYnfGwNbQY7jtFuI/ooLjN4XxakJsEHcT9k6UZvUnZmYRBF6TFlOhgGKCsJixm03HaEZlNCrRy9O2OGCNlqikTRTI0mBgw3lMqRygMQ1S4qClyg80MDQEPDH4YRcoJxmq63DKEQEwtOk+xVSCdV+SrKYNVbIaOwWjIMmbHx+SrOZ0P7LqWZLclzTJ53hPJbEiz7MBNf7yGVVVFO9rDHsfbKA6x38ZovBfuQwiSxDmbzXjrrbeYTqesVisJBOo6gg8MbmC9XvP3P/7xYc0kF+Mo4tS6PnjVZ5MJs+mM6XRKnufsdrtxCiaj+scJ3CP8yjl534ZhIM/zA5DGj57231hBf/HmDcposrKkcT2XmzXnec7zs3Pe+eBDfuvulr/8sx/w2T/8FXo5xVYl77//PvPpjOP5MYm2nF88wXc9x9WS26sb+m2P7wcZh2qL1Sm5FcuLWG0Ey4fWGC/+okBPXuQUVc7T58/4wz/6I77//e/x7W9/m7aBtvP8+V/8gC+/+op/9d/9X7i5ucT5jrre8OXLz6nKHK1PJDqyaVksjlnMj7i/q6n3PZUtyExCWs6IWhOblma/5+rVS8LREel77zMpS46XK85PTnl2fkGRF5Ln3va0tXgQo1zdMcYwmS4kp9omYxKWpcxKrEk5Pz2n7xzbek9UUK8vhZS23YDWnJ1UTCcTnlycM51OWS7mhx1N33U8jAdyHIE+Q99xf3tL33coDM4NrDcPpEnCfDaXX2O5xPWO7XrL/e0dbddKl5VmbHdrtrs1X3z2c46WR/zLf/kviUEY4tZaTpYrurrm1kVSLIXJOJkdk08KXl+/pN7sCMGRFhmLbklapkyZYnNLNkklHGUYyMoJVZajuniAwiilxu7LAAZrE3abmhgU2jYE5yTK0Xn8EGQVo8yI9gy8+Orlwbc8m8345JNPWCwWXFxckKYJv/zFL4hKrHHL1YTZrMRWKSrTxCTi8XT9DqLB2jmJTZhmBf0Q2TWRNIU0VWACeE8XOqL3TLIJBs3DZo9zAR0liGQ6nbLf9zzshCmd5yllllJay+9891Oa9z/gs89/ycPDPb/8+c+oawm+SdOUIluN+gM1vgcS/aq0FMe2bVmvt3SDQymZaK1OzsiKgsVyKesx72majv2uwSaZwD9GId1klpFlOe2oyn1UnTsfCb5iuVgQveSgh5G2lyYWKEjPz2U0PorVNmOC2mazIYbA2dkZ5+fnvP/++xRFSVVWgu90jqKQ2ONHkZ0dBXPT6XR8RqcIjrk/YJ4nVUlZ5FxdXrLZrGkaUb/XtSRWHR0dU9c1X331FdNJxXvvvUu923J/ewVI95SPY/2r62s26wcuzk7I05S6aaTgxvFQ9Y8o6UdsjYhrHyN8Rbz0uBJJpNGwRuyG3oBRqETEoJ4wWiwlgSv4SBwQCw5yP7RWj2JBSBIoioKPPnjGP/1Pfh8XYdjf8/qLf+Czr17imnsK6zC6BR3IUkuVOEyoyW3OajXh9PSI0/N3GZKKdSy5bjdc13vu7iOTJPL+Wck0h0lisVaTqgJnc3Zpiikr8ukxvumIrmW2WHB+fkKRp2gVWa1m5LmmqddE75nmhqmFdLPBhICN8v0sJgk9GociLxNsanloB/oQUL4jqog2Bc5oQpXToghFjw4a6zXlyQLfD3Sd4rZr6KxBVSVHz59RLGfUzjHsagYl4KtiNiFLE5n2/EfOhGoywY9ecbFJdvR9f3gOsyzDO8fQjYLYUQOSpil5nh/ifwH2+z11XfPFF1/w03/4Kf+3f/Wv5L0Y/9uyLNntxMKZZWLbnF084eTk5HDJvb+/B2QdnOW5EOrGAv6odn+8tBZFIVAl+M370NOsFCWntthEM50qkrSgHzxpVnB8fEq1WGJnEwIK13Rcf/4VmzTlbnaHNZY0aqETBU3fDeLvjZrgNS5GvHds9w1dJ/umiMJF6cy8jtKVn8x4+vQJv/P93+Gjjz7mt3/7tzk6PsH5iJclF+++94zjkxk2cdzd3/LLz/6eul7z8fo5Rku+cPABPwSqck5VzHi4a9nvejbXa1w7SF64D/i+x2rNe++8y/HRMW89fcZ8OuP0+Jg8zejbDt87NJqubsYDOUObEVeqZB8fohfqXejp/U4Ku7UkJmFSTVgtV7gYuO02dF5QikZrlosl89mcxVwKTNcKlCfLEogB7yPWyNohxiBOASc54cE/MoTBaEOWpBI3m6ZMyorVQnJ2m66hHTp2bYv2En0bvOdhe8uf/fm/F9FQhDwvmE1n7LZr3NAJT9wm+H6g30VCN7LOH3Y0dUPT1WSTjN4dMZlX5MkRGIU24OqBpodCZSTKMqkm0vWMh13wiizPOX9yQb2rsTbj4WHNzc0t/TDQtyKSMkZsjgDFiE789NNPWa1WvPfuuxht0KPafRh6Xrx+was3Lzm9WLI6O6bDcV+vyQvZI3eDJ0aDGgJGJWy7BhAlsCiQLZ1v6d2ezEpHiXIoNHmR4H2EQTzNOnryxHK8nImSWoNJU4mSVXpkFuR0XcfZ0Qm73ZZXL16hgMlEuoqH+7txXC3df5IUVJOELHd4ErLBMZ3NSNKUopqhtMa5OBbzVjLkR7sfUTGdzJhN5yPvXMOIkR0rD3mWMp1OuLg4p+ta1psNfTccomOHXvy0xsq+0hjNu++8LQjUsmCxWHB+8YTFYkGW5zJNShLRuWg9ugvC4eA1VkaURVmOMbPfLK4O1w/sFTg/HFCvyaiVmC2EBb/ZbYkRlqsjjIab2zuInqzI0WOX3fXihkFrkiyXyxIKRh/64AbCSBzUjK4WI7tVp4IwKmyCVULji4gLIoTIvmnxwYnS3ntwA8ZqUitWXyc+R9SjsM48UikVUSMhNLuO+XzG2++8y2xxQtN6fBBNiSRUZjw/OyY3mr4P+ABd3zAxD7j9lwxZS18ajo4m/PE//j7/5t/9e/767/+GSZVR5FN6nVLjueoM2xCpklbCGp2GJIUykviBQu8wRrGsEhaTlMUkxVjprN98ISP35WxGnljmacKESB46VN8Ruz1ea1qtiWkGScaAx/UpmoRUG/KsJBpNM3T4EBnaARyUVSaX18bTm8gOh+8HYuswywnTJGVxfkoxnzE5OSLNU6aziixLD26NthPOyTe5atoIL8JaGW17LxeyZLSjGWOEb6LNN9awstaVSag57NxFb2L54MP3yYuMf/HP/xkvXr7kb//2bxn6jrap2W631Ps93/7Od3jy5Anf/973OT87p6qqXyG+PVqu9/XX9kjnwzglE/3Y4DyD8yyWK9GF/WYLeiFQGA1WKSZpRpJmdL0jTXJWy2PKxRw7rRjqFt/23Ny/hAh6co+1CVWSUyQZx9MFXec4QDuixvkgwqe6pVWOJJVvVD8MuOhpQ8t0OuFZec7Fkyf8wR/+Pu+9/wGffPs7eC/gfh+E+fz220/R+oKLJ6c8PNzzZz/IaZo1zq0Zhob9/mGEh2hSW5LagvWyZ78d+Fn9czbtmuhk7OZ7R5pYnr79lOOjI56eXzCdTFjOF4KubDuCC4duIkYwWTH6F43sKUMgeHDB0/YD231DXpQUVUViEyZlxWK+xMVIefeKXbcnRImmXcznLOYL5tOZYG3bVopDnh7sSTox4+EcRaHrBtzQ03WDjITGMWGaJFLUR9iNcx6TGPI+4+XVC+p2TxxkfJyqhGHf8MP/cEWWZiwXS6aTKUN/Iil5fTsWdIvvBsIwEHpH9J5m6Agq4h4c+UTiT1WIHC1XAiOySnQJypMVFpVYqqrEaEvbjnjFAFlqWMxX1PsapSzOea6ubiQitO/kZEQRg4hVZpM5R6sjfvd3f5eT42OeXFzIXswmB1X29a3sx2yasDxe0eO4bzZUJkUbRe8CIWiCG1BYtCpIkow8q9CkWBRtaOncjiTNx65Vghfy3IrtRI10uxjIU0ORzQh+ILgBq8UKlBr58zx/+hyl4OL0jIeHBwyWYRhIkoS7u1u2u5q6btjtWvKiIMty0kxQqIPX9M5z8eQJWT6GfgyO2/s7us6LRgV1yAKIMTKZTsnzAsWYCBXCWMwDikCWpUwnFWenJ+zrmhADjWkOlq+h70nG4hsHhzWGt54/Z7FY8M4775BmQkIsy5I0y7FpikksVVGSZxn7/V5G5shA21hDkiYUZSF7ydHlIj5/8QeH4OmHjn6Qy31i0xHElNAk6VhgFYvFkq5tuL27pixSFrNSVgZ+oB9kFaaUIUkzlB7H5VHGmb0T5K4fBinmWovgST326hymCaEf1z8oXPQ0bUeIXpDRIvLApJpEGfwwEL/hIZZfTkb0j5TDIQxsdltmyyXP3n6P6XxB3boxHCZioqFIUp4cL5mkhs1mM6ZV7pjoNb5+wZAF+smC1bLi9//wt/nLv/sRN1dX2ItnFMWEXs8JSnHTQjJAmfZo7aBusamiipCFAfSO6bxgNqlYVCnzKsFoxxAcX754webhgeVsxrwqmaYppe/IfEsY9gz1Ay5GWgKmmmHLCud6orbofIZNM6pUS8ZA16Ocx9UNyqQUxZR+iAxZTzcW9GaocV3P2dEzpvM5s5MTyvmM6mhJlqcs5tUhBMUH2UHLCkh//WOEJT0Cu+BrZszXRV+hDsJQxmc9opKEOIo9Y4yoEc16fnHGfD5ju93wwx/+kB/+4C8OmNfddktd1yzmM95/712+/73vcX5+IfqQESLz2JH3Xc++bg4THzc+x4+C1WHoDwVdm1+vVP/aBb3ZtdKhpxaMwWQJQ9Nzf33L9ZtLLl++JvaeeTkjnR+jtaHbN6L+G+TlrLc1nWpoNy2+62mbjmk15fRkwXw+o6omTMopWSLjCqXlgddWM11UzOYTPvjwLc4vzvnOb33CfL4cb7ojqWk05sv6WpHlGcvVnN/93nfphx1te81+v+by8gWXry75/Je/5OF2x8Ptjs060NaRbt2jveLp+x8yryYsJxVVUfLW0yeURTGOIgOb+wcByoRAYlOstqMYN/LqxUtCiEznEqziPNRNx+XNDXXdcr/ZsVgdcXxyymK55PnT53zx+iV1XTObzkirnPe+9QFplnK0PCLPM2bTKSEGqrIYM76zUakuXmpjNPOZKHZvrjOGoWe72RxGhNZqur4l7dPxwYIsTeldgo8DaZHQK0vTj7t7Ky/BZNz5R+Vouz23t0IG22621K109gLWUGPgQ0aW5rjgeNhvaIeWy+GS+q6m3bdU04pqPqHIc7Iso4s9JJDbnCSR3ZpWYLUUImsTsRjmBUVVMZ3OhOamDKEPdG3H6ckZVVlxfnbOarliPp2SZ5nkEccBXCBLUp6cnfPO22+za7bMlgshUOmII1C7BlygaYXQFX0p9iA9kIQMhyeaFJVmBNOhc0/UHY4BQ0Ah4hwTNCaxqKgxSgMBFT0qyhjXaPH3qiKRPVuQy2BRVFiT8vu/94cynh33cR9//G3+/u9/zJ/+6Z+RpiXT2VxEMlpj0wmD8yIkjNDWLTFEymKKtQMx2sPo0ftAPTSEEGmalpPjI4o8O3hej4+P6bqepm1GYh1Yo8jShOg90QemkwqlIpPJhDTNUOP3pyoFwFHXtYwGlT5Y1x7ta0rM3tgkAWA6FXFQWZajCl0+j0drWfDiz3/0BHsvmgqTJIcxZN/3DM5RlBVmHKXGqMiLElRkt2/I04QsL9lsLtluNhRFTp7nQqwbBryXHXqWF8KuSIbDhAstSWVt7+j6Dl/XwrnQYtFr2lbU7F448FUu2NjQg44G5TSxj2LBHS0uLo6BL5kkxg3eoY3l6fNnPHn6lNXqRAh7Q5A8CufRUZMnGZmxZMawmlb0WcJQr1Gupl5fUpYFZenpvIgen59X/Kd/+G1u7ht26ztCtcQmOb2Ty//CztF4/PBA4j3BCCTJRMfRrOB8PqFUnths0Vki8hFtyNOUi5MTJnmKq2ucb5koT9Qeqz2BIIFXqkdhhdYcPbgGRcDvN3ht6WuP8xHjI9FHPAneDwQV0IUlnVcMLhKMobdQR8/e9cShJ4uBBCQd7ZEaijqkF/5KQf/mP3u0k0VxIj1+jMzEw977kV3wWOAf/edCVRS9xXQy4fd//3dJ04QXL17w5Zdf8vOf/5xvffQRFxcX/Mmf/Anf+vBbHB+fHESZ3vsDw2EymWAT+ysWN2PMwXL76BAJIXB6espsNvvNFnTXDSijJUiAiIkaN3ja7Z56u2O32aKjYlJUVNMZNk3ZFzVDN7Df7OhDR90PDCEy4FAeQFFUE47Pz7k4O+doecRisSTPhaKljUZZRZqlXFycMFtMeO/9Z0xnFSenRxiTCGKRKGspuUwzZqCMOMect956inc1+9qyXqf4YcPd1RvW91d8+flrvvr8kt0G2hbmyZxJVlFmOavFgufnF8ymFW8/e4Y1BhWh2desa7GPxRAoMzDpaCUKkYe7B8FQItGUg4tsdju++vJLdvuGu4cdJ3UrXcVqxXJ5hDUC9CjLktJWvPW+dDvOOREj5bnshtJ0tN8l0gWqYfxzaoqigBhJUos2ajywPNroA9Xs0esIHDz91htsarBBE3pRn0edimaiSNBRsuB71+GGQeI5m5qmq2ldh0iENNPpRHK9jaFHwxAZes/Qbhm6AY9nsVqgosLMNFYlOO0xQaxpWhm0SUfoiRrtiVbwqklCluYURYl34q+uh1r8x2XFcrkSOMlcxsnWWikKIRLxFEXBbDIRi+HpKUVZghbOQVCRPogKWXLlhR6olBfAC3HUcXiSEEAPKBUIasCPsagag1LZuJaS6Y96tNaFcUqCMBW0MuhEOrS+kSKbJjlZmnP0GArTy/fq6ZNnPDxsQf2QNM0oy8moxTDYpMD7QDeqw/u+kXeqKFHKMmTxsPvtXUvfD4Qgv/b56YlYfcZx5GQywdqW/X4nWGdkqmNHJHFIEoosIwRPVZakmezghYEuX+++74lAMuo6zDdQsijpcs0jhplIDJIYp0dRkWAzu6/H8ePvH7xgl1EChnpUPA2jiChLM+J4UQmIkNQ7mVAlY1ZCPzh2+z1VVZHlBfV2K0xxJ1S9sshH0If4911oUSGiQmTwnn4QxK5zjjTNAdjsdvgYBSmb6G90URYdNHhNdBCGKBGmasRRqyj7d6UYBk9mE1ZHR+IumUxHJGvEO4lTVih5r5RcErMsI9EKqwKEnq7d4t2eNBPCX/ANR4ucjz94xl//7WfcXd9jkpn8ftGgjSWLM3Tw9K4jjT1Z59B4ButJgGWZk4liebQMa6zSpMaynM2p0oTQ7/G+Q+PRKoCWZLlMeVAOGCSeF/BephShawjK4GtHiAqjEwEgjSuPqEAlFltm6LpHhYjTio5AFzzW+2/QP0UsKe+V+tXi/R8X9LFwPlo+4euQlUe1xK98xK///6HgfqODz/Ocd5Zvs9/v+fjjj+m6jl/84hc8ffKE7376KR9//DHvvPMOWVYcLguPnfnjykrrX01RO+SRwOjskMnAdDqlLMtfq07/2gX96epMDtksJSjoVCAYhTeK77z7Ld5+8jYvri+5ebjnyxcvuF9vuN9cs9/XbB42GG14/vxtjo+O+e53vsu0mrKarzg5Oefi4gmzWUVVFthUDivCWCZGilOaJiSJppoYElleEkcaUFQKtLzgwxAZhpbgB4b+AWJPkrR0/YbLy5/ghgYTGxLVkxuPCZHQgvaQKc13P/qYZ2dP+d53v8tqvmA1m5Gnwmj33tPua4Z+gBBIjSXJLKlNsdqwr5tx1yjdwtWbK1wI3D9sqZuWm7s7XABGO99mIzGveZbzx//oP+E7n37K//hXf8rDbs3p8SlJKgKoEOXF/hrALH/RyA5XbqgwncpOqapK2rYZufpiQ9JWE1XEBUfbt2ijSfMUO1i017LzNeCDkMc6rQlWYmYJ4DqPikpgMSjKSU4XWqKT7hSg63r6waFaKZJFWhBVFBFM1HQPHftYY0OG30f6aiC7OMWkCX074IeANXH0eCZApO9qurEQ5XnB6ckZi7ljGIQ5rSKcHJ9SlRWr1RFVWUp0bjfQYxj6nv12R1kUNPMZu4cNvnej9U0420pr8jwVXkFuiUETQil/9eK9btwet99RD5EkabC2Z4/HEMl0RaJSqmSJVRm5qaRD8+pwTBgltsXgHG0vmgCtDRo7qqO/XrB676kbCTD5/PPPaRrHt7/9KdVkQllVuHHVIg1+ZL3bSgzprh3PIT0SqCStLctyHu5u6btuhA8FSZEak89ijMymU7Ikod7tSBPRavRdR9+1aKUoy5x9vYMoXYZzIkabTKasjo8l0MWY8RJmBPjUd+KtdY7eDdjOoOLXO06l1ej5hr7rDj52rcaAlTEX/dGfq0eofzdeVB9GMd7jZWG92YrHO7WAQhvLZrvn/v4eF2A6X9H0jq7fygQoSbGpaFG2dTPqLDq6rmW/25GOrhCxIMnlLSjLrmnlcA6IXzgriMDDtkb7gHUebxXBgu8tyqXYTP48KnZEIgkZRBhCzySd8OFbH8jzm2Y45+nCIO6ZwrC5X7Pb7bm+XfPw8EA2ssq9mqGTJVmxIMtLUtszDD1J3PHeE83cPKW++Zzt5R3bnaPeFujqFJuW1H6JMSnYKS7W1LsdpbYss4qTvOIsy/H9Ht+0ZEaTZBmrLKdXmuVkRmY0sdkQBgd+gOjASBS1DR5wEAa0kvmVDoP0wX0LGGh7UptxOl8RdMKgc2oGtFfUZUY9yWk7h9MaXaToNEVnFpMKSySxBmuE0aHHi5ikED5mYch7/VgkzehMkGflm/Q/KdD/HzvqGA8XR/Wr/4ZhkJ9vrWG1WPGP/uiPmJQlVmu+++mnfPStjzharjBanEhSyDuJ7S5yjLUUZSFT7HEtGmMkyzPyPJOLZvAMg8d5R1lNfqXw///6+LULepXlMtJOE7xshvEavFYkVcZsLreO6WTCdr2lrVsRlg0DiTFkac7pySlPnzzlO9/+Dov5ktOTc46PTzk9v6AsM/Lcjmt1RXBAkE9QMY5IlEfpDm3UGM0q0pSIjLpdEBFB27b4oWfo90CP9y1tu2XzcAMMpCaQmEiRWYo0IU9StIdgDRenp7z19Cmnx8fMJxOmRYE1kr0dx7Ego1XBGkNmE0FUKhGSDcMg3fAwMAyBYfCs12varheLkTZoa0V4FsIoAlOcxoeW3QABAABJREFUnZ6xisf8+PN/YAiOPCuwqT1YGbrejxCccb8zHogGPaI8OQBCkkRQhLKGiGN4iUBRQhTbRWpkAvI4Ln98ag8WHe+kcwqeGEQ0pFDoKEl0SZJiaoNSo+AK2UVq8fmAkZUHCokeVUg08CDpa77zOOvln0WF6z1eR8IIZhi5qIQIwyCCI20MRVGSZfK+6ajQSNxgkReUY/72Y4cz9ANd28nqYXCHiFsZfdtxFys3ZWMV2sgtKQSN95oYNF6JyjzEwBAcvnf4uMf4Dh17dAx440lMRqbLb9y65cfhNTzsyaRrNioQRw3Ar/z3yuCDY79v2Wx2Qhl0gaOjE9I8I80yhhGRTJT407rtGMaI4DCCeSTbwB/G3to87tEDIfArnYzRGp0kxBDE+jP+fQhis9LGHMSFatRpOCWRkGVZHpjXPP45xoCLA5866jHsRFgE6nDgjhee0e/+2JHwjc9Ndt2PEcfiaBBok6PvB4bBCT1QiU1NK0AJjErrSNd3NE0nQJssoW0bBu8wWTaOUIUuOTixDTVNNwbACNsiKrGbahTJiPSs97JaSIykuiVpRvCepu4E2uLlHdIRvFfEYFAkGKXRCLRGBS3Z2xhSk7GYzpmUE4ySyF8VEGJhkuF9oGk62lZy7cOjVVOlKJNhRk2BwqHpMNQsKkVxVnE8N8xyz+ZhR9d3pOkUZS2981iQ3y8avIsYDFWaU9iUQhka7wldh3GOJEkpbCLecpNgtRCeD4JKooj9kHjjR13GKB0cxYceFURvgndok1DYhKATjLJ4G+msI0ktNk2wWULiIzbPsFlKkibyz0dctx47bw2H7vubnfjjW6W/8SYqedwORVTwwIj2Yawj3/w4/DrfKKiCF1d4J/kITy4uWD88cH19zdMnTzk5kekXUcS4PvjDBMAmVnINkmR8Rx6jfgNZlEu+V3Jh9+OqLMvsQaz3P/Xx6+eh1w1KK6x3mDRlMZ+w71vu91tqN1APPVlV8OzklOHdluPZnIfra6Z5zr/45/8L8VEvjphNZ7z97F0iImQLCom804peaUyqUUaeD6Ugy2Ra1XWiZHTeyfgySienMfR9oB889W6gbx19WxP8gDUDip7d9pb97obryy8oc8vifMm7z45YFd/j4+drrr69odlaXJ/wve/8IadH5+RmjFXterxS4CQzvcwLMptQptmojtSHqMfEJjjrDvaGLBPE5nKxZHCesprJ460Nx6dnnF08JUZ48eIVy7Mj0iLj3XfeY3l8xKbZ0vcDi9mCEDz7ekffd+zrHTqxpNaitBUFdxQRkTGaGKXbzPOMLLPEaJnOZOdpE0uInn2zBx2xicGP/+uHga4fZK0wXhoG59hst2MhVxhtMSahmlbMZwtQgtDdbfcMg1iSkiQlKyTcYHV8dEhCc8Ez+IFqOmG2WFCUGWmRogz0e0c7dPgYsEZ2pFlWQBR8rveBrvdShJOcLBUEaLtvcYOjqiom1YTnT59R5jlWGdwwcHdzS73fcXN1RVnImJVEcX58xkfvfsiz954zmAavezwPeNfTN3sGF6ibLVqn5MWMPMspl1MiPaiey8uXPNx/RXAtRM80XVIkFZxYytST5keYqA6OARCalNEaY+V7ghec6HDgq0s3avOc7cM9/8O/+3fiFGhbsjynnEzQ1o4xoxLssNvXDL0oZXe7HXd39xKFOk6JNtuNOCiOVsQQhGylJKio63r2Y+a30hINnGUZH374IVkmQRMAXd7RNi27Zk/fdUJsG9PPjlZLVqsVWSHkrEEkumhtDx37o4XwMc5y7JO+hnI8XpIRfYHJMrkoZxkKobIZa1HWiShNG4ahJ6KxNh2nOcLzn8/F0lnkGUlqyDOJOe1HBbJ0S8jP15bee26v36CU4mi1pO0dL99c8t677/KP//iPRXsQ5FKitOb5hx8yXcx5+cvPqbdb1lthGlxeXrJ+uOf27kEEos1AliTkiUMp+bMpr4na0PVyoet6yWKfLxbMqyVVOiNROUMT6HpH2ziMKsjSjNubDV98+ZrBKZK0wo0jYp0VmCxHW4X3HfvNawiRSerJY2Awmk++9QSi47//9z/lYXOFrSp83/Nw02OMZZYbksQzzTUn8wnvvfUW8yKh3ba43hFcgB5UopiXUwbv6XYNQcOsqshcFJtpSCCUmMGR9YNkvnsphHGcoEQiakxys8gqSrc9yiryNCNog08z2rLAzTxlVuIcrFbHFGXFyflT8rygqkohXMJBmyK/w+jvH9ewSiHdOGqEA42fzzeKufD6o+hEvmF5eyzsSn7SeB2QRMLpdEIInru7O4zWXFxcHGyyj5eFYSQWplmKNkI+DDGStiKYrqpKdC1jGFLXdWhjDuN2uVy2sjLV/zMU9BBk5Dr00pBZl+KHYfSX9rhhIC1SrErI04RJkXO8XOKc5/133ma5PCIvJEZ0WlX0zuHqdlSw9ug+IWqDVQYdNSooDIrDJORxfTFSm0IMh+mzG2Ejjx4+58U+ZbXcCvu+pW33NPstOli6xqJiZFqm+OWExBv6aUkcck5XK5bTKa4bRv+t5LILDEBwfxIFKBGbGiFFPXYachFRh12IVkriOpMIeky/AspCwBt2VFGGINKM+XyBTi37N83o/U2I0TK4/rATfvw9jBYRoESUjgeH4gDNeBRzGCs7dRCLjNz60q8DKKKE2sQQMcrIhcrL7yNdj0ZruVGKCPNrRneaZti0JyrZ3aZZRl6WZHnKbDqTDtjaEUokZKbpfI7NDDYx9L7Dh0GCdaJ4d4lqZM2rMfc8QpSdepqkZFlOnuUjjEiTpZkU3VwOwKFt6bue3XZL24h/3Y8vyaScUM0q5pMZk6Ki9p4hBh43cVYJUlWFIDAYpbBGk1iDDwoXPF3XsNtvBMMZPTqzhExUtomW9YAMkB7VBY/dtx7H/P/xh3xvnPPs7++5vr7h5atXDP0gYAzv0YnFhkiwsnp4nMA8JkV1XcfQ92OCWE3bCrVNISESWZaJxWc86B5/3tfRwwLWKMtizC4fi+nI4u9HsloYUadai/XHJonYGlHjhHI8+sZ9oUSTCiJTq2/0Sd7LFMA5OYrHDujrcelj6R8v7lomNzJClS7fjgI5CSES69vjn/cR9SwuIH1QGWtjMSEcEMPdqNTPctEjpFlOXpRMpjO6fuRza7lsLVYrjs7OUEOg3u2Y7rbiY9cSvLRe7xiajmHXHKxQ3vd4P+CB6KXxcE5y2EFTlVOqckqaFFiVEp0iOk3wiug10Wuapmezqel6j/PQ+15WFXh6NxCiJ4QB39VorUnGvINgFIvFlLOLEyaTz0hT0LTgFb51whHQYicsEkOZWao8R6tI1znJDYpGRKIB0Swhk8oIJJnFqISgZb2jTCIXfw/yCWjRqTxqSeLjhU6N/HwFIaBCkIkEilSLor/Pc/JU3pflckFZVcymFUmakSYyMRHh1DcLxNebcBUCUenDvwpBGrI4FvRvKtq/+av8x8X+G6VnfBYPk3iC9xgzCkDHwCFp5hoeY3gfPyQrPeKScMARx/j13jyMlwAJPfIHgJYfg6QOv+n/xMevXdAjMsbb7xt8jAw3HkekjwFbZFR5TrNds767Yf/wQOx7/sv//D9nMplwfnqBMZaudxg30OzW9IOgPZ0bGFzPrtmjbUpalpgkoSwKrDYMreyJi9yirSFPSmJ0uNBLapb3aKNIUkuayYM09PW4I3UE37F9uGH9cMnd9QvuQsfVVwO5yajSipQpi2rK4ugpVXpCmU4wSrEPAYJ40bVRI/EqYVKWkkQ1+lr7Mb6173qaVohrJ8fHDM6x3bUopZlMl0Sl6V2k7Xu2dSO7x9WKshSRjkqlYL79/B0cXqx6XUueZMA4Nkdxf38nxTdGHr/PXSd58xIaEUnzhLzISPNERrM64KOj7Rvc4Om7Qe6tRgm7PoAKBh0SylT8mv0wHFYI2lqKfEIYBULd4Kj7HowmrQpWeY5SmufPn1GWFTaVFCJjEyEipTlpmlFVFUVZUk0qts2Wuq2JKHQ02IkIytJk3C1be+hgZScsxTzPCnEV2IQirQg+cHwku/M0yQne88Xnn7Ndb7l89YqyKHh6cU5VlsynM9565y2ev/UcnSe49YAbOgI91TLDZAlHVYXzkftsICqDTUpB9g49m80N9w+XXF59xf3DK9zQQPSECQy5o142WF0xCJYe5b4+wFJE4NfWDV3bk+dSOLMiAxTDMHB/c81/89/8n7m8uuLzL76Q711ADrP5nMl0ymQy4e133mFZrej6jt1uy/397chV7/Cux7ue4HuInr5v2GzvOS8vODo6GmlrjqHv2cVwEN/sNhvSNGG1nOOHgW3XjgwDT9fUrB/uaLqeYXCCk00ShkMK3MiG5+uDqes7NruNwGSqSi6YVux6WquRx4+wt0dIjRrdDSDRx0ZLUUySVBwPWoSGSSK+/2SZEkOk71u55OXlOL501PWeh4c1KElA29cd9b4ZL6AZ11eX9F1LkpXMphM++OgTFJEPP/qIvu/4ux//lJvbG66urmRnHzzNEPjoo494cvGE8ydPCUlCAFnD+CDx0tsd92+uuL+/4+b6ii8//4w3r15ye3PJfrthv3nADQNFmrFcZHz80Xc5OT7jZPWMEBRd69DBkZDhu4w6KK7e7Hnx5Q197Bn8wNXDG/qhw2vP8/0Ff9z9DmUb6LdRVk+TCVul6LFcvP8+k6fv8A+Xa2yZ8ebqjq67Jg8BqxS5s8zMnLeP3udkKkK7thuo64GiSsnzkiakhF6BSjE2EEMr1MMqRw2epkmEfmlLjHVoBpwD78AFWX8I0z5B6wylLVUBAYsfRDBqVEBjyJKEapFxOlui0xxtU6r5kiSVvI4YoWtbfATJcoOIuKEed+QKCI8TITWuJHlcK8rF0xo556LSBB0I6jHxTJ6/x4vuoWMHYpSUP8FxK6bTijjqP5I0pSrLQ9pgmib0fT/qXeKhwfvmhzGavCiEStg0bLe7MfdcPkczrsqGEWn7Gy3ou2YvDNpelKROR1wM9NGTqEBQ8gc2ClJrIP6/afuvJ9muLM0T+21xpMsQVwAJJIBEyq6p6Wk5fOEDjWa0+XNnHsaGRhppJI3srpqpFlM6KxXkVSFdHbUVH9Y+HpE1Tetss2TAAhcXN65HuPs5e631rU9YKivdogQYBJIXYgT5B9QpkYLHjSN+cgSlqb2nqMRpSxUKHxUpgY9RmJQxR6KGkFmqQVjPHsYp4V3e/aVI8FmC4kZS9DR1gYqRQkXasmRV1ZSqpqRh07YsygUqmDPDVli16ryvUWT2oZOfecrkN/nVnX8/57OP44hSmrJyGFtkwxmLLqpzHq7K5gbzgTjvdNerDUVR4qaBlCLq2T9Psos8dWdUokz2zO6f90xyQebXI8qhMzoJp3DeZVMWhVEWq4WIlojolIlX0QsZThmJRgkxu43JISwe+1Kslus1TdtSFJmprnT24ZeJerlcU9UVVdUwTCNajbLHVmIPqa2mLCpUNv1IMWF0yK9RSWFLqrKSfa4W4x6V5DWLQUJD/OS4vbnldDzRdz1VWdLW4kltjaG0ma2tNCkoTMjcc58kwlSJWslmLahROu+mYzYbEvQnBE9K4bw/TKJZnEEaQf6eOYKFkGS3CnlC9jK9FjIxvP/wnrdv3vDVV7/j7v6e/WF/li11Q88wjRL56Sa2lxfYomC3e2S329N1HeMoaNeTD3lEzUlA+UAxRuOcMK3HSRAfl1UPfd9LsMl+LxPDOT405VzyQAyBkBUSs/2pPK6VHX1WaqTkMhHIM4yCGBSFFd/qssQamw/JPAkxo1qcD9OQPXV1tlfVWTeeUjrHlsohnc6SN63NefeYIiil8UHUAjGB0kJAzFgAc6SyLTInxAih6u5+4v3NLff3d9zdP9APA5N3fPPNt9RVzcXlFfViSVWLN0ewIqvRxjC0CwptqRYtZduQjKJaNNTLhsPukdv3hcTohoStStrVmma5RJkCNQPE2mIKOX/mImOMAQ/iCDkyTAMuys5fATqjKTrzGJLSJKUoyoLWKF6+uGJ/OHI67DAx0mooNLRFYl0nUeoozzAcIYfSlJQkYwVVzLnvWsnrZQ1CEoyRw+SojMLYEo05k3Q1CYNFYUGXJF2giwptCmpriGg8FWjJQDBoAgZbaIIysk4oSpnIrc7vayQGJ/a5WszHZsnyeU8LAuUq4RClM7udp2v3mVpCo8+QPDzt0c+/KsVsvBSjDDvWaIrCnq9zpRTTs6bgzAHJzcCcmSA8lpzQlzkvz61fx3E6G9zYjEwJ5+KPPKH/6pvfCGyWCQv1sqUbBh4OO7QRDe7rjz7i6uqCtq2YJse7778VY4QvfyZQqAvUVUvRrjDIY/XO03Uj9/s9h65jcXFBvVhQ2Z9gliu0ymkz/YBSHm0GEp4UR8ZBtOx9PzH0DryFqCl1QhMYxz3eHRhOB4yO/OJnX1AViXWtWJQtm2aNOxrcSdPqF5RccHiITGOisoZoZWesc7KO957T/kB/6tjvduLKFgLJR1JI7I8nxnFi93hgHCcej0dQmvWqY7ne8MlnX3C5WnNx/UICRE4dRVFRlklS5JQR0pbRfPn5j+mGjr/8y//A5EaMgeDEhjDFxDQKOVAbxeRGscqkxGhN3da0rqGoCgKBbuhy7dd4HxjGiXIosX2+kYxhUa7QoTgzmJVPEBTJOVAGTUH0ka4bsXaiqEYWyyV1ti+sqooXL1+K8UkxE44Emm/qBVVVs1iscrFT2H7A6Il20WJLzfZyTVmWGFPIIXHq8sUuEp+6adHKYLQlZq/87WZLXdW8e/eW+4cH/uHd33M6HPnqN7+GGNksVlxut7y4fiFdexI9dRwDVSkNgk4jLkLcn3B6JJiJCKhYoGyJ1XJ2JPJEU1gKozAqYbJtZ1UJZ0H2xhKaEpMi+dm8JWd2R+EItIsqe4qLveM4Tvz3/8N/z1dff82f/y9/zjg5yqpiGEZ2ux3GWMqyYntxweZiy6nruLi84JtvvuV4ODIMwxN0Hj0hTKTkBVkqDFVZZEe9QNd1nLoTY9ejtabvT3jv6PZHIHF7815WS1plR8IqJ01B9A7vJ6zJ0qkcRLFei21wmc2KDkfxbd/v9+z3B8I331BlUtN2LZyEKuuwZ6nYnPYWo6BCXSdhSHVVnw9H7z3BB4ahx09OLH9D4OFhJyzhqjhb0FprWaw23Nx+4PbmjqZtWKy3YlwTAlXdYmyB0eKCKf2xAl1w+7DjL/7Df5BmfZrY7w/0fc//9H/+v/AX//4/sthe8hNTctW0KAWnwwmlNFUjDfv65UsuPv6ILwvLvwiOED0fvvuO3f09//Hf/wUf3r/jd7/6DU3dsHr1inq9YdTSpPhCoO2FaRmnkXEaWG8XvP7oJXePNxy7PAg5T3fwTJeJxtYs6iWL5QXaWHyyRAxoi9EFldH88z/9Ez776BWcHni8T3x6uaIsNJWWNL2LJaTwyNffPVC3C5rFilrVqMrgCEQfsVZWT9vNC7RK3He3dMeB79/ds25LPjUX1N7QpAKdJLzGainYqVxAUaLX11BULMuGlDQhGkKAcUzEpAhRYcsaXVaoqgZrGVIkjIOEToWIG0XiWhQykc8kQfEkIU/p4Tyxyy/PCrrWYlwGZ7Kq1vr3JvJZYjYXWuGgRkKK7Hc7rLWsVnK9D8N49mivKiGuzk2m8DBizh8AbfP5dhB3w5hgyMjuHME6ezNUlYQrjeN45pn80Qp6F0estqzaVnZXlRWtrlWYwmDLgqI0GKuxVjyo21ogMUOE4ImTwyuD6zoiChdFa5l8QoeASQmbP3X+TMwSHQ8qoPGk5EnRM7qJU99z3Hecjj14+ZnaymJ1JIwnvDsxjh3WTFRLS10k6lJRFYZCK2Euj5ExnvDR0p/ATYoJQGlULSQ92VcKlHc8HLi/v88TWZK9vzLnSWi+uNqmlSkgp+UMw0BZN+cLSMyidL7IhDg1eZn61pslSiG74hSzxhjqus6TF9l4RXbIJu8M5wJT1RVVXRKiJ+bdjOj2FUVKKK0IKWDmKUsXFDrRhxGCxiqBxrwKaFVIx5uEhCiscDnMi6qUPVlKTN6jrKesG9kTZRa5MpaEwoeQO2phBi9XazAepRPWFFhbyOuoNEZblBJb25mhHULE58kyhsDxeGIaJ/a7PafDgf1uT9+diCFSZH/wtmnQWYHgp4mh68QzoTWYSrT3JMOpG/GpZ0wdyWhMvZGmPbNQJ++JzmOUSGDMeac753/n56oNMSkymJSztPOzVsIN0EqhraWsYbd7ZL/f87h75Hg8PJF5koShLJdLyqqiaVrqtsEYQz/06J2mO50Yhv7Z35mZxTMQmW1dFdn7fcfj7pGu65iKCqM149SLyco05YIqJimFNcIfQTT/ITwR1+bAitVqJbruqszNjKAdVWaQoxTGmvNhKRyXzPLWOhMwZ5JSlBXaWbVCDuP5fRhUUIiUs979uVFKKTI5Mrkz6+Fz+p2xhaTJZQTMaMN6syV4zzicsGXJcrXBOcf7+3seH/ciKY0pE3Fll/nh9o5+crx794HtxRWLzQZbFGco9dwUKJmQI4qkLUpr2vUWjOWTH33JYrsFaylsQXO1QVc1JydytlhEogpEHRjpGGNP2cBmW1FUl4xji2HidOq4udnzarul1jWFrlFFtt3OwSgJTXRiXLRpF9iLyOuLC6oYWC9LCqMobaQoLS4NBC/EVVUmSgxB9URVE5WVc8oYkjEEXeJj4GY/cjz0fDgOeBSXDnTU1BRnngOqyqqDEnSFMiXYEl3WslN3SpQTKogunfyZp/8YIiojjDqKTFQV5omZMl8seYf+/Nff05bPX5P36d65czGfz+vnH2em/Pz/1XxrzUS6iJsE4Zz36vP1IqsqQQvmBmF+jPleEP5KEntX557ur7ya0sY8vYb/BR9/cEE/MNCUDR+9vhDWqVY4G7GhEJbxckm7qikqhXdAVHz86hqNpjGaGD2hl9SvA4oYFS5EkrZgCqoUUIVlVVhqa6kUmCRStJQSLjqUcugwIt5eE4fuxMPjI3cf7nm425GcQUXNxbqlLBRpuiGGE8PpnrYOVC8r6iJRmYhJjuQGhn3H401P6h1pWuLGmhAsPu9xN5eaVBQYrRjHgbu7Wx7uH3jz3Rth5RrDZrmmrVuU1lLkyhJtLC/WFyitGaZATHBzc0MEtlfXaFueDVDEyc1iCsux60kalm1LU5dcXlyy22ne7HYoo7i4uGRyI8PQSShAU1IvKhIxx4sGVqslqMRyswSj8IejTMpNI85ik8NYg49eJmk0pWnAlqSpJzpoFrU0Uz4TWIJM6dbWVFUjBWYhRWaaJsbBoQ6W2k20yxWqtJTNQg7sqBh9YDyeMpxUsFituaxfsNvfME0dRhUYVZzJhcYUGKUorMSpuikw9gPdqTvfJLc398QQeby7Zeh7Dg8PEvxSFKwWCz7/9IdsNxtI4MaJ0+HAvblFOwWXoBeKstaUuuD+7sBpfGQ3PWDLilefrtFlAsTs5PG4RxWOolCURlPm9YC1huViQVsLIdDagpAUBIVzUtCjj3iT8BGiG4lh4vrVS9Z1xV//9V/y7TffcHf/gX440baNyPRSol00/GC9ZrXecHl1Td/3DMPAMHQcj3t2+weccyyXS0mSGicUQYw+CCgCEIDI4+MDt3cSv9r3PU1ZYbUhEURNooUBn8aINZKq5oPHBydnYZJ9ZF3XfPrJp/zws8/45JNPWCxX2VBFvqO1mvVaPOW1NYzjQNeJl0JKUq4jUFQSgJF8eJqGZsa7Mlm6KCuuuQEWf/eQyZOJaRoFJcurhsnJ2qvrB0J2dFPaslyJUiRkWV5hLa9ff0yKga+/+i1Nu+AHP/yMmw8f+PW/+Td89c133Nw9nuM0Y9IkZfndN28I8Xv+8q/+hpgU64tLlqul/KxaC490XrmMnjBIJkOIkapds11v+W9evcb5iS/ffktMnsvrC8Zh4M03v0WrRNMaxCfaM8Qj43Si3UY+Vms29Q8otKV7/Cndqee3v/oNm+2Wrd1Qmy1UL5lC5DQ5QpSi408nxmHko/UWu7rgw+dfcr9akVKH0hFbJUJy7Kd7fJgYfAdNT6M9XhV4DcYs0KYilS3JVvSqpZ8G/uabB/aHez7c7PlogvWFEH/XagHaSBqiqUBb0A2oEooWqhrVLiEqTPKoFGQDkj0uVFSoEJlGR9KeWcNcaE1hNKaRZsD3Myw+w+zzv9SZ7Caw+xPLnvzrfF3N5kcmn8PP2eRncnMmz4vELatCohAjjbWUdZUbT8lM93OmObL+kXWQFOeiKDK0Lmvarh/ywApoTZkT48pSVpnSuOj5yf3xCnq7aqnrGm0loD6RUFrcxiS8QwhqXk4xMYTJOsXgM2Pce1yIdBwZs6e5sgXKVqiyRNkCHSNWltVEPxGSERJedCQ8KjiUTmIzWi24vqqo7ILN6or9/YmhGzkd9+zdwHH3NSl2LKoTVhkUrQTAjD1FcoyEHIKgznKD+QZ0UfCQ4+EoU5ExjMNwNrhYrZbnVJ6qKClMIcYyzuXwBc0UJ7SyVG1NSipHMwYeH+5ZrDas1hV+GDlNDue9dPtWoQrD0E2gEtv1BdFH3PgVthASms+cg1QVzC5SaJFBocBWFaX31M0CH2HyEmixWq3wLpxDLsS6dr4PRNOtk8Yqy3qxISmZ/FAi1xDJRxRrXlOQfGTqR0LwxJQy/Cu8AVsUZ9c3q8WtqywqQT2UxKIWVUFhZ7mdIiXZQxqjKCoxXqjKkmEYeXjcM3nH4Xhk1oamHHVpssxpqiqMUoQEZSGWpG1dUxgDZQlNg0YxdQMHdqRT5OKipShg2k+Mw0g/9FQtFFGjgjgkjscTu7s7bJMoWghjhGBRpUFri9YVWlegLAmdp/JAikriMkPes6t8IKB4uL8npsD7Dx+4ub3l9vaOw+EgUHZZklC5YWswRjNlgwqtNW6aZDLPB513Ml2fDgdiimhNRn8SIUz0/YEQBM4M3pGiBNVELWiaIAYGazRlaTPkrklIoSUftD7KBSa7fMcwDFmWKITOyc/TtXiV68Lms0BIf5ObKMuClCKLxUIOueeM4ucHanZGJEXmEI1Z656AIqsvYggCcUZh7bupRltxQCwLuT+9d+cd/floj5EYE9uLC5aLBTEpnBdf9nF0OCfGHl03iiGMtlRlTSTR9SO7/ZHTacDYMvNIEOKSmr0ERG7pQsCHgM52vcZWaFuwvrgkJI+tKqKC1cWGGD0qOaKTKW8Mjt4NPO53PNzdwTrRFDUJYU1fbC9ZrTdoVRKjoZ8SLoIPOk+3ZMKraMONUmxWS9zY8d137/BhxNYQVcCrEWWhKIusiMmRr36CokFrKLKXfdf3HA4n7h8e6U4HghNlitFW0BBbo5zO/haSZxFDJCpPGkZZdWuJBzbZE8FUdd5tmTM3Q6UzzIWaD6oIKThBDMmeD7mQq2f/5vz//9GHkiZ7HCUVc/bnL6L4XDzfn4vpUTwjQ7MqSGXGvFEZXYgJn4NUjBYbBmsFDX3Y7RnGkbKQqOAi79FnDsdM2ktp9gMR7pCffT8ykmX/2LK17eU22ygKRBxDQGuoy1ISp5IcLC6BiplUhhRF7yVwIzjRgY7dyO5w5N2HG0xZUVQN68srlusNJnpKEsmNhFGYmoHEkPeCKQ1Ya6jqguVyzerViuRlCvrtr37Hzfsb/uFvvub+5h3ff/NXKAZ+9uWG0i5AXUpX9LBHR0MRChgrVKxyQZF5JqTI5CIxOYZejEgUTxIhay0vXl6LqUbb5oSzwO64pxtPAikpRTedsEXJq+srQDONQqZ69/YNH6G42lzknOgRU1WYomD96iWVqTg+dpjC8vr6Y1RUjN2AaioaUzJEGLuepi6loNtMGvGQoqayloBmsb4gmZKAFLyri0u880zDQNd1dKcOgsjedNToZDAI3HN98QKlc/hK9Pg0EaKlMJZF2VLbCjc5pmE8G9Mcj0dCitzd3ZFSYhhFJlS3S5q2ZbPZ5gSpvGIwmh99/ilXl1tivnfLsqAoC9abi3PG8ePjjse9uKHdPz5QGEthbQ4WgaaqhOg2TjhjmWKiLiu26xXLxUICaYyhsRYcjMee+90tR/bU4SPUoqS76Tl1J079kbSGOhiSUkx+pL9/5MM339JsStqLmqkP4At0KjG6xJoWY1sSlph0NmRJJI9QfUOQJxcTSokM68133/G4e+B3X/2Od+/e8e233zFNEy9fvhQpmCmk+6+k+z+djhnd0Exjz+m4Px9f0yhGJw/3d2ituLjcglEYnfBuYOhPJCyoQhruGHFhwANm0aCUOB5WZcnFZg0JgveSAT30+WDU9MOI857T8UjfdRz2wiPRtsy7wJEQxCRGaY0uJdZ1uVxmD4UT5Ml6tVrlxiFbweaDdDbCKcsS7xzTMKCNfUKy8pQtqWuio59/fzgcCCGwmaYZs8+8J9ltWms5HSXYZPfwQAyBjz76mKZt8D7SD47TaaDvJ6YpZjRkYLPdslguWCxXKK05HHtubh/Z7U4oXbJUhcjQtBObYiN7YR8SoxPnRV2UoKGsa4zVbF9oYvKEOKJKywv7EePYcdzfE5LHTYHeD+yHE29v3vHuu7e468CqWbKuVxhjefnyIxbLNVrX+Gg5dIGoFB4jvB4vTbuKCYIMWVfbC5Kf+Hf/7gOn7oCpwRSKYqFZrBsuN2uKwgCBGCaCG1DNCmMUdVWiVMHdhwN39w+8ffsONx2orJC2SlthywZTtWAUOGaASFAnH/DHE0wOE6QB0LpE2RLTtqCsfHoPzoOb5L+ZJblC9gxTgmy1PJPfzoJINS+cOA/u/KP/nq+V59fbfH0URXEmy4VcxIWXIo6HKSXwXuyMi0LQPy/N3zQ5rE1YC3W7oChKuv4bdvs9m80FJZoyzcXboFRCa5t/bnXOKIghEnwgFTl+e7n84+vQV0UjkaBRdhth8qTJk0aJDrUWmDzeJ0pboJXieDpJopcypAhTEI1u8EIwWKxa9seOm/s7ejeKjEklDvtH7vePmKpCrzaowqKrksxsoijA6IJgC6KvsDpRVnB9+YJClzx++A7CyPffyJ7N2IoQDR8+nLA6YlnjfKIfEkwanKLWNbZZEIISB6SgUTERXcjwiRwOTdbztouGdtGyWCw4dSf6oUc9yETXjT0JaNolptJEGzBa0xQ1ZVGzqFeQNLdv3wnDGwN4oof97Q5TD1yZgqY1NNuS1aLlanUBRKZjj/aJVdVSmUK6byWsSD8qppDEgKRsefnxD7H393z7/XuWwfD6RYsfTwyniUpXrNYtKsnW6mL9CmtKfvXL3+ScafE2VzFRW4HIu+7I/cMdJYqlrQhYYt56JpBwCgUuRlwM+BTFDUwHpjCw63eSyZ2naqsNd7sFCU9RiURjuV5TVlUOIFGEFGmWLV/+5EvWmzV1W/N4/8B+t2PsB4JzxGYhboR1yaKpufjkB6yXSy4vLgQ90ZKwVa8KkZJ5xXA34E8eXCINie9//ZbD6YHPfvYD1qs1dlAcxyNff/81TkVerS8o1yXVsqIfD5zCQFVe0rYty+VHNNWawizQqSD5CRU0BQqiI00iJev8QNQQVOK3v/mKN+/eMgwOo0umURjLu/2RqqrZbEpSSEyDBKacTsdzYIPPyWF1XWKNkMVSlM+QFEPfoRAJWAyJGFx2BNQYE8+48MyO1nmaTynQD7349o8ua9p7ZhvZ5WpF07YYbehOHe/evKUoC4wtRb4z+Rzb2ksoh0qstxsur65EV35GGsQ9cZomFk0rTPaZiV/IwaV1RnmyQ122Xzgz3ROIi1wInLqT2DKPfZ5Mw7mgz4zr00EQjv1+J+SjrgPIA4o6M+SP3YAylpevP+Z4PLDfH1isNiyWC+LpRIiBu/sddXsnHG5bEqNMVgZDigqfpzrhD2mBnEMkjI4BJFsBDyqhlRXttlnLKmvbclCPPPQKoxxaeV68+hF1dc2yWlCYgoQlaU27bmmWK4rNmiJLpnxK0kRGkRyWpQUrzVVUinLZ0votH//wCw6HR/ane8rKcvXygs12xeuPr1kua1ZLcf+z1lBQooNiOp2AntCdiN096XhPrR2fvdjwqqkpxhFDCWZC6QIqC0EqrIkzXyinIzovRb+SaGbcXP3dGTW3pRWuFin/iZw1ISCFPOvQU5pTyhRoQflk3SIFMpG5LJnHoZSiLEopgNrIexRE1++lukrqdfbY1tZkxEkIyT5npycla5boY/YiaM8a84AmhcR6e0VRtUyTuH0msm2wS9k/RJwQUySndebnkxLBBbRS+NGdi/0fraAvrLBNbRQJDpOHUT61tphCJGgeT9lKAIDIaaYsYxLILoaI85GkFYvVgtvHB968+54xOIaxJwRH0y7g5j26LFl9/DFF27C8uJRuJmlSVJTGEoqS6EtspahKuL68ZlEvuHnzAj+dQEl2sbElMVne35xoqoKr1ZrJO7puACepSGpZYaoFYXSEGFFaYCrvnZCNSBTW0NYVy9WCy+sLFqsF7XLB/aNBH0DX4K3ncNgRIrSXS3StSTairMBlm+WWj198wrvv3vHdV9+xXW5ZtSt8DESV2A07KAqWqwtKW9HWFa6Vgj70HcPxgFGwrhciF0pCptOmENMJL12nLiteffxDoirYHQa0qihsQx8HhuPIanPB9frizBz/yU//CYvlGqLi9vaO77/7FudGiQC1Fa8urrhP8HhzQ4VmYUtZveQEqUiiWjagFfuhY/ATYxhzaE5gipG+n/Ax4DPb2xpLu6sIwbHZbqnrhuVqTV3XjNNIUuBTpFm0/ODTT84F/Ve//AceHu7o+hND36NilIl8sWLZtvz8yy9ZNC3b5RKdFCokFk3LxXqDCRoTNO9279hPA0yJqCLf/eodx+6Rf/XP/gUX6w12VAx3R77+239g8/KST3/+I4p1hV1W3D3uwHfUxQsWzZbV4mPqaoFNDSpo8BM6aAo0KUp8putO9KcjkwGnEr/59e/43Tdfc3FxgTalOB32I3p3pG0jm/VWiF9u4rg/cHP74exAuFxIFGldF1mKNks1BRkY+pME+pQlHrkvlc4SPB1RJp3hSJHqyWdMgaHvCCEyDCLBHIbhLEt8vVrx6tUrWUGdThxPJyCTz1B4L3vs/WGPz5Dx1Ytruu7I9vKS5XolngmTZrd7ZBpHVEIkqhluT8U8TCkhSZY6I2AiPYsZXp3Z8QnouhM++AyjSggO2f3LaI1Riu54pO97Hh8fGYaB2ShKyKkWo8Vk+tQPoC2vPvqY4v6BpCzLtTQyg4/EceT2foctG1AGYytiUrIPzmYhZw1zFKtbrRX4SAiOceYEWIGki8KilcWYClWAbkG7iuPDhFEOoz0vXi24vo74yRF9ZBqzkdPlNe1yRbmWMCxtNMnLWjJFGY2LqhDLWi0ErWqxYEHiB599zuPjA8PXjratef3yU66uL/j0049ZLRtWy5a+l6hbi0V7jfNybfjTjni6J53uqBvL5xevWNcV5TBiVAnFSCoNyko0NlFho8p4ktgyJ+clwKiRde3sWBYTKGPBipoKa7G55g9ezubJyToLZKUQU8wyPVBG1kemKGTNkQt6mMKZcY5SUpPSk/ySKNe/OCeSO11IOjeZ8z49pqcGIWbiZoiyes2OiUobAoLQbC6uaJeeN2/eME2O0QniJetCAAm+EllblFXdvIYKMUdkP5nc/NEKehg9GIkvNEZjW0NT1jRVJd3E5OkH2SF758/xiVobpklYfKLXE8lAWdUslyuaRcvL16943O05Hk98/btf40OkWq0p2oarOLHcXNCuN1hTUpgWjWHshdim40iqLam2lKakWmn+5Be/4NOPXxCmWx7u3/H4+B3HQ+Jq21BdLXnx8gvev73h7v5rdAKTNNp4Sf1BFpDSE0rIvUKiJGUP3dC2DXVZUdqC0hqJ66xLPus+Y7Va0zTv8THyxY++FPJYtZQ0rmi5WF3y8uVLxuPAQ3OPHyce+3tM1YpMarFC6xI3OIbTSL/zTKeE1RkWKpKYtSpP0CKpON7dM6WIaVuqssEH8M5zPHaMvWe12KJVwYe3NzRlxY+/+Bk/+ewLfvzZZ7TNgrKsGX1imjyfff457XLJmzffZcciT9d1vH/7nhAc282GuqhIPqILjdGGxXJBURaUixqMZuFHpuBoji0uRsYUCCRcinl6j+I+p4RJPYwDDw8PQnB7eJBJcNGKFWohsLPSUDcV24sNn33xGYtly/fffMvu8ZGPrl6yWiz45NVHNFXFsqwxKFmPKENt5mQ6xbt3b7n57h0vFy/4+KMXvHv3LWPX8eXnP8SWn/Hy6gpbGu5vP3B/+4HD7p7t9ZqXV1tGExmCSC+3mxcs2muaeoO2K9A13ikJZAmyozV5laeNmKNUVcOH23e8u7/l/fsbHh4eswe77HONKSgKYYzLfTNxOOw5nTqmyVPYgvVqJe6AMTJ0PW4cz2xvyfAWa1ZjNEYruW6N/GqNOk/m3meP/mkgeoMivydaE4IUDeeEEFjXLVVVUpbFeWqzhUFnVrc1ovAIJFQKRC+ubMPYc9gVmMJiSysBOFkd4KYBReIxinNW28jk7ybHfAo/P8QUuVBGWe2FGHCTmORMbjybIAmPZ5KD0PvzuqzrOsZhjlhNZ61vUckO3JYlq/WGL778kof7B96//yChGNrgQ+DUj0yjF/8FZTCmpK4XlGVD13egZp0xmeH0lLkgT0CJJvrM4UpSMBD7a7Lro7aaplrz6sWnbJZXjK/7pwM+T/2S6w5tDtdZb7bYoqCsa5ybGPqeaRiYhlF4MikhGduw3G6pl0tsWTCOAz/56Y/FgnazoqosbVNRWg3RSpqbFU6L1orlcoFzE3/1H/8Ddzc3KDeIxGyQfW/SmqBLpmIUDTUAhpQ0Mc6acQM6yRClFMKgFv5MUpqkdc5+kL25imHWapyvXaPEgQ5l82Qr6/eAykiTF3c7T9aQg4sSyBSyamKxWIi/Rr7YUoqSN4EMKSDXc4pRyI4z7y57TSgtiZdk1Y61wh94eseFZT9O0mg+POyYJscyB62EnCAYgpdr1ovHRYrhHJsqfJeYvR3+yAU9Oo9OFpWQibAoCMZSWCO7JjecSUXzfnP2c5bdmuySjBHDmbqpWG/XtMsl1y9e8Mt/+BX73SN3tzecTifaiwvKxQK1XskaJoq5SmEE4nJTZMRj0oRNGpOgWhjqUvPJD37AeL3l8f4XvHu74M//zW9J0bGoKxIl680L7m46jl3AEDEqUE8BYwKWQliMWccoMaWZ2VwVNE0jxCVjKXL339Q1ZVXy4vKKsigYJoePgdevX9HUC4ypSQH8EFguFqyWS9q2pSpL+r5j7EbqoLGVwrYaoyx+8ky9Yzx63BCZs8GtRnZsSRGTI0bP4Xiim0aumpayqMSoxwWGfsK7QFMvUSFy2B1Zvljw8asf8OMf/Zj/6mc/Z7OWyfg3X3/H/eOO6xcvBPFSKhs5BKYpsPeeqipYLcQXHrLJhDGs2gV121AsapTRNDgm71CFYQyeoxtwMTIFj00RO+fbJknbcs5xOp3QSnM8nTDWslgus71s5m0oCTZYLBe8SNe0bcM0DCgF1y+v2a42fP75Z9RFxXg84UfHcDjIOWbLs/zj4eGe3/72N1z9ky3b7ZKvf/33PNze8sWPPma9XbJeLvFx4rB75Lh/ZOhPQGC9WrBzPd3kZG3Saup6RVku0boGSpF55QNUZStfpeTm17agKCOnU8e7d+/Z7XacstZ+PiSe7E1FshJjpO97xnHEO09VSja891Pmc4zZSETIgZJMqM/SuoxAYrTCKCHKGSUHlsqs8+ATUcmecrZYjSEyTT5HrzqU4lzM5z2+0VqCUJDvNQuFSInoRSrpxpG+O6H3lu3FFu/FVS5pYQIrwE+ydzZ5bSTOgPIxWznPxZdc0IZxkPPEjXkaDme9sPeyd4/eE71nDgnp+z5LhXItnYl2RW44CrGOff36NTEm3r+/EVc5W/C4PzD2pxwgk0jIFGaLEmMLvEQoolWYZ9Dzc3iSRZ1Xs+QuQ5qWzMIWcr8UtdI2bNclcSmqFWZy6nwWZxmUyeFKcxhTXTe4caS0ll5rdCJLogJk57SmEjnsarWUYuF/KEXSKDFM8gNazeuKQlLpdMIYxbJtmUbD3c17bj+8R0WPSRHtBAFKhSM6RwgOHWz2Jk+klA2uUKQUIIJSERWCrAdULvZKCnDSiZzylMnK2cI3pWxyJS+mRhPV03o8zf+kPNkyy2Sz5DE3RTpH0Oo8mcv9IyijmBbliNaUBOJP8riRGdmSs68oSmmUMtKjjZH7GWYnbny+l445pbOqmrN/grz+ITehGYUK/vyezY2pn3f3f8DHH1zQT/0AwO54OO8iqkbgZ6U0TbtAGUPrFlln5+i6nhAjQ5ZveO8z5V/2bLvdLlPyDdv1is2f/Al/8if/hJSgD5ExRL7b7Xm4ueNwvyM0kVgJ5B6cIlUJ2xr2w0hvFV2VqApYtGB05E9+/l/x6cevGQ93eDdwuW1Zr1ZMY2Cx2PDjH/+c23cP3H7YsVkkQNjWCkW7XGAQEo5CmI1Ftq60SZHGwOB6puMgzEQF432HP018evEx2lrWeoGNJSoZptFzejgxPo7cf//I+zcfePPtG6wqsMoQ8+lblgW6MBz3e7ruyOQOjFPPw3GHNomiNXgCU/J4FQlW9KHKiBbeKkNbNNhk2bsDra746Sc/orCW9WLJ6xcv+OKzz1gtlzweTuw6sad92J/op4nBeaYQKeqGYhrpO8dqs+HnP/8ZpdUUhWazXbPdbigr8R5YrBYUVUHZVnITF+CC5/6w49T3vH+4YxhHDv2JyXsG52TacR6TjHTcMeGmibvbWyFcHQ8Ya7C5ibq4vMQYI8jIZcnF9oLoPNvNhm5/5HH3CFpjqwI3Fqgg9rnRCxytrKKl4bt33/Hv/+rfsW0LrDryN7/8t9x+eM9nP/3vaNY1Ew88nh74i7/+f+NV4NVnF6xftng7sT/seHt/R7necrm+ot2sRZpnC6IyTBlmJUYsmmRE7lgYRSw9qnYcXODd3T0+CkwnzoLuDAfujwdcDKzHDX02mpg918WAQlzmYgxUpc16eFEfjONIipHuJMXdGp3Z1tkYI0+Hch7mfWY+DqdBdso5IoE0jyRKUVWW7WYp01sp3gfaqPPeUmnx+k4KAuLZP/qJYRqg12A1p+OB03HB2UEQ8WIPPvMplBAdrS0pbEFdN4x+ZBgHookEnbPtU8KNEz74bFuc5XApSmJfRgLdNDH1fUYvPOMwSspgWYntp9YoayjKUkxGtGK5XvGLX/yCECL/63/8y+yXDilJVOZqtQJg6DseHu54fHxgsWhZr1fZK2LK09Z0ljxJKA15B6rPU/y8y511zHOBjtGc1w+i67eZMyCF5+mxchFL6Zys54Yx72MTVS12y3Mh0MxpZLmfyChBQtz/xtORYewYxlPO5pjQStwGi0K8FY6ngb4/8bA7MIyen3z+I7ZtxaJd0pTiwFiWrTD5TSHStawXT0nSEZWW0ig2ioEwdWKtbMSlUunMbk+iEEkqMudcQB7MjTyuUYVouec0t8i5EIckufMz7yL4uTnIWnEfCPICnmWwwmoXeWPMLqiRiM877ZgSWinqohHGejZHQj29H1rJc7WFsPVD5SFGysISvGMaekCcGIX8JhkTbhIb5eDFUjxkxdgTHP+H1ek/uKBPkwQt+Ch7DO8cixTPZhc2d7tKK4kvDSKPmkNTZgmACgmHO9vcCenFyo5ttaZtGoy13J96Dv3Am51EXwbn8cbjmHJBB4vB6ZKgIpOKhCExWNCpoK4VF9tLmsry0euPcVPPshU/duciRhds1lsebk+5uEjsocodm7bShekorP2UsgVjjgtNXqDjGCPayATpTo7Qe5bVkqKoJCo0RrROhCng+onBDTxOBx7uHzmdOtqqxZT2fHgqWd2IgYqLBDUw+ZHRjdnaUYgvLkXCHEuqsmcxCpXkdYnIa11guFhtaKqai4sLXl5fc311jUrQTw4fBnEychEXRN+LVqIv9xPOjzTLBR/94AcCZ8WJy6tLrq+vaNuKshIdvC0sZSPJQrrSuBCoFy2H0wkfI93YY4xmzGlMgx6Z9CRM8ARkKLE/nfKh6EVKVRU4584JYFVZUlmRVl1cXqCA7nBkHEe5Eee7Sqt8Y0qn76LHx8CxP3H7eMvucMeh23L38Ibb+7dM8UTQI910YNfd8+bmW8pFzZc/+hn1siQozxhGTsORcrulXjQC1RZiWpKSyOVi7uATCqclXEJrK4ebMQwhsD8e8V4OdOeebuAQAi7vu6dMgJsdp2YXONFqC0xvFGKCY56MW8SeVabqwszuV5HgRcNtjZFVRn4NZehIEmiUMlFnvp6UIAaFtdR1RVEKlH+2aVXqadrMuffwJPfx+X30OcRpGudCp8/Qt5sEtXPTlNGN2bQng6FBzGaIcDafCeLMGDMUOUPxwcccRynXkpAI81kzTXjvxflRZ0Vyfn5zylVZllxfX7NcLs+vx8yWNs9es2Gc6PuerjsxjgPLpQwx4ziejUVm3bEQ7uZAkDPengttOk9y8pHtVbU+NwRiWDJDrjH/LOb8GBJ1nJ3NfLZJ1lpQj0KMj+aYG0WOElWiMpn/h59GcQEMDrTE0zrnMSZl0qR84anr6U7deUDbbLZsmoqyspSFxRYS5apNIUOGzmfl/BPMq4Z8raQUcuaARSkjU3uOXBWymAQ0RZUfQ7Jxn5olNGixbI5Bnf3O5TgJPLVBuVE9yyOfUA75s/n+yrbi+VwPBEKKOc0yX3/6yZVO53thbn6fT9FzyNB5RWUlbdE7WSnNpjnB+3NwkJumHLud733v5XqP/3+A3N/f3soF//KawlrKskRbjSks+91OrFBjIKZwfsHruqaupdtOCbou23kmaNuWi4sL+m7gdBQJVlsXkCLBTagofuv/7b/4VxRVy9XrTyAZhlNgcp7pMBBOA4M+Ev1E9A6jHUZHLrYlTW15+bKmLBR/+if/nKE/8v23v2UaHLeHB8bOcdqN3Ly95+2bD1hWuMHQlg1GGb6/v4MQ2LQNpbEs64bYtKwXK4FFBiEMDf2AUkKauL1/5Nj1/M3f/Y7JeWzVUNUNrz76gZBulCX4iBs8CcVqs6UuJQ5UGYUPE/vHe3RRUm9X6LJEVRC1R1cWCnG3HSfP0Q+5mAPGYMuK6AJTHBl6hxsdnAI2QqlK1tWKT64/pmlbwgQuOEKYcPkA1KZEact2e0nbLvk//p/+O7ruyPfffc32Yss/+a//lN/+9lf823/77/nkkx/wWZj4/LNP2ayXolvVYhSkYkInhQuOoesZjie63Z7JOdQUWNiC9aLBlR7nA7v9kWEU1jZMHA/Hpz2ntZRJYiaHYTgnFoEcai9evGC9WrN/fOTx4ZHffvU7mrrh9fUVPjoejjvqsuLl1TVBwc3ugWa74Kd/+lOWr9f4OhBXieng+LO//3OWbxaYVnEcjvzu8Tt+ePk5P/1Xf4KpKx7cgWPoGJnQhUTUWit7amGY60xikZ8vKQmIiEoTjRgeqWh4f3/H3/7930mAyqyddo67uzsx6AliFHN5eYlWsF6v6TqRpXWngb7vzlC6RqBQPR+UKWK0om5qQTMqWRfJzyiFtsj79bIqM5lSyGDe56nEPfn+J4SkdH215WK7oq1LrFUolWHurA1WSnLZUUFieUtDES1laamqgqoqCN7RHY9UZSVrLJLYy1a18AWGURr2yZFioq4a4WcsljJNnaeUiLUlxkhxDN7TDSM+SECSXB9GKpVCJnGjsxWxzoe9NDA6CCQ8ox/WWq6vr8UFb7M5W782TXM2IAH4cHOLc45f//rXjOOYo2YT+8MuKwfUmXQ3IyH/KUeylIvEXAxEyinFWvaogbM/f5ynWrn2z5nyuUGKMdJPk4TZWDH6EXsQQVFSXkLPih2TdL6OFKYoWV1fs/AbtlcXnA47DvtHxrHHTRPODXR9xy9/+bfc39/R9RNVUVG3KxbLBRfbJY3VLErJbzdVjTJGdjxZbTB/RpzsyxEiWwwS/qRVQusSgzpvLGLSOU1drkVjZGDUVuVG4fnkmiH62UUwNxKJnOqWm5o5GTDrJMhvCuf0SsHWSIBRWcGTnTmlBxN3U+cFZZZG+hnXIw9d8/tTVRJUdXVxQWktNx9uhL+S+P0J3blM/nxq4iULg7yr/8M+/vA89GnKexgJ3LBFyRyMMMPryuSUGGPOF6d0KAVzjGIIQlYxWlNXFcFHRjuJlp1sQjOzQ42hXq4o6gVtWYs8pAiooPDWk6ISs5phlBCTOEByRGeoK41RC9rGcn21oLAVWhm58QfP0E10p4Hj4cRud2C7OlEXPXFKaBT39/ck78BvqEvRMZdFIfal2YK0O/WcTh1aizViNziG0fHweKAfRopqpKpHinqZPdsbYhA5AihsWZ7ZmFqL0UAMnniGRclpdPKptVivBpVy5zhbDUpRHroBrSb6o+zQ8RGdeQCltlhtSSHRdyMhCQnQZxjKKjLrVixMy6pkGFb4MLFaLlkslyQUt/f3NIuGxXrB9csrtt6L9S1z9yyGC2IkJBNj8gEVIgYolKGyJYUyeB0Zi4kYorioBQmeAPCNl046WIKXw9pVLk9ZspOzmV1dliXWWrqhx4fAZiWZz6Nz8rVKYk+ddxR1yeXLa8plQ6o0xaah6hd0TAQH4eToXY8vINUG3ZZ4Bd1wovejwG8qQ4Mzlhgl/lFFSY6aXwdxqeI8CQkvQeKC/TMi15x/7L1nctO5kJRZIythKU8mF1rLikeKnELnHavVGms0bVNTFJa2rtFaiUlMNseYJ4WyLLKJjxB7ZFMg9r0xiiFKTIkQE01Ti8++1RlSfCYV4pksCGEIz/aVRfFEzkspnl38znt9rcVPX2WNbYxElRG9IIiYNRZi5tDkaUgkZrILjUomyni2p533zQKFKh3RaZ7EZcJN8640PsGw866+LMtstdswZ2fPBF/5EWMm+2r2+z273SPjOMh7e2aw2/8kM/n5Pn1+3Z6T/+Yvf+4n/vxznm7/sS3pzPafvTTmz5ie9svPHlzY4EnOOSF4aXnPtKbQskufJ0mAkN0Cd/sDD497yrKibWqaZkFdt5RVI8TLYrbZFbvbc6iJOrMF8z+yS5/lhzGCSh6SQap5hBRmhlp+pWQazy+BnA0ZZj+jHecnLgZI0szkx1BPiAk8NTj/6A3Kk7+Q7AQRTWdC3PzepOiF95CechogR6HO71H+eqMNyYgPwjini7pnwSzZw2RG6GbkQBoMaQ7mBu4P+fjDIXfnUdpw6keGyXPs+jPD1LmJSOL19Qu2F9vz35mX+8PQC0RolEQ1HkXUv1gsIMFy0RC9l73xscP7wKdf/JiqXXB7PDH1E6tmw6Jd89kXPyQGxTQGTocTu4c9j/d37Ieem5tbDocHDrsPxDDy4kVLuyj5wUcXtE3F5WZBRLEfTuweO969ueVXv/kdf/nXf0twJdMAw6nHjRMPN29QKfDFJz9gvVphrcETsfuSvhvYP+45Hk4c9ieqZklZ1viUxDilbEGXULdMSvO7dzcIechQFRWLeklbNSybVuBaBe1yQVVVdEPe7QTH2A18e/c9x+HI+8N7FtsFr9uPcAQoLafDXrT+vSNMnuPDCdc7xkNPoQt+9OmPaZoF2+YSHTUfvv3A6B3dOLC93LK53GKrEm0LJicyF60t1kKpxZp2vVkC0I8Td4+P/O7bb/lwf8s//O433O0e+PHdj/j4k49ZrZYysRolMa4xYtAUytKaiqAKopa9cV1W4qBlI4UpGb3n/e0d4zhyfNxTVCVt24oHewwM/cDtzQeGocc5Jx7tbYvK8G6zalknz3jqGVzP3/7ql6QQUc7jU6Q8PGQDRcX61RUXry8pq0QyiZ/9H/5bPp86Nlcrkk58f/s9lRsofvqKqq3589/+HT5GRidwrTElPnpimEjjADqiY0IlQxNkl4zWaBUplJdiSzr/+vLlBT/56Ze8/e47DvsdRleEopBABmtxRznIuq4jNQ1ltaKfJj7c3lCVBe1iIYdhjIxjTwweRaIoLJ+8fsl6veJHX3zOom3ZbtaYPIUN3Ymx7zKTNmapD3naFYQHLeSkECJjdi8cJkfdtDSLGmMNqEiMLktPQZoBIfUlpdCFoV0tsHWBKe25eAU/MY4d282a5WLBom2o65YXVy/R2nA6ZUmUi6iUGPqeqqypmxqVeS3+vFMV3+9ZwhqDIgYIfgZZxWrZFAUmH3HaWFnbRWmEfUjokPAx4UJkmHJcbqlo2wWffvopx+PxHLqRkjDlnXN89PoVVVVxf3cDKfLpJz+gbhpxU9TPi/YM+D77mKvRmcz1BNeG4IUcmlcO87583qnPELwxYrKj9NP+V2sj2RH58UKCOHmRZWXOhKAH8riSUw7a58l2DOeJvSgXbC4KmsUKN4103YG+O9Eutqxc5Kc/+wXr1ZIvP/+UWkMxDegzni9cAWEyC2o0F8FIvk5QzwhrChWLTFNPEIwUc2UhikxZYfLrFc8mVilzNcTTX1AXefB4Js9lJh0g8LisPwSlcZM/r13m6WnuA8+/NzLkpPwHgoopFk0um1Hl9YrLg6s9J97N65mU/96ybXDjwOkoBllKmXO/n/LKSAAlfUaDZmvwqqoysvCf//iDC7rzAW3ExlBeXSPJN87nKE+R58zTeMrTxMyUBXKalhXtpVayJ1UqH9ySy+29y9Gojuh9lp5IDJ0hURcF0Sh01HhrKa2hqUpi29A1DcENjCfL6EceHx7oO8Oi1kS/4GK1RClDYSu8jzw+7BiGCZC9/36/ZzgNMn13JxSRY3dEa8WpP5FIWFMyDBOHvmcMgWAMpm4o2iV1UZC0xpcNzkfKuiEBwzBJJxzBZALc/Jl7y3xjprxvg3Ho6d3I/f0dp/HEvtsRbWTdb5iCY/Aju92e/X6PktwaMfsJER3FgaspKhZVwyannE3Byy559IzDRH8aKGLCllEgzrxLnFmfSinKqiYEzzD2OB8IMdGPI3EfuLm7ZbFaoEtDN3SUpcUaTdPWkGDsOmEXn6FQSD6QTMhTbaLIgSaFMXitxWUsR9EmkjieWYGirC0Ym/HsGlZkE5J5Vz6H4MTUy89PIiC8AG10Ti0zlKUmMuBxFNsWFS0sS2LyuBKc1pimIRjNfX+YzwmqvJ+UJ5LE8i7NBT2Jd/WMVMgxRObYnsempq7Zbra8f/O97M5zolzM5K65E58ndvlW6fwcZz/qWRMbgpA2rUn55i9ZLZcsFwu2m7VAqgqGwjAW5pw2Nh+GUhw0OjtkJRTBpDwdy8FSVAXW6N8jUskPJl9/ZvbmYmFLCyplhrYclGVZnJPfqqpgTlczVuc4XMl3UBke9iFgZ6tNJaY4OokPPM/2nygxEtH5uYiWOJ6h6PlnNllaF72s/Gbk5CwJmwlTMWKsZbVaEaMQDefpaX7dZ1Z513UyeY1yTVZl8ex7nn/C35vU5x3u7Gz2j//M+/CseD99zfl1UApzBjTknJUMbUEhZk7E/O2TFjKaznbUc7GKJFSG/OdCIvd9QmmLLUUapnNIT0qJ1WZLUrC9vGLVthRlJWEpzp+n8DRPxudGRsk9oNVsq/50/TLvsoP4uacAyecVujRs8rA6Iwsz7yDI3w0hkxbTs++WgbGU8t99QibUs9dlzjh/XsDPFf3579NTQUfJNW7N02M8/5wJd0/PS94j70X622fppJsmuWaZz5PniYPqrCaZkceqqv74TnGHU48LYudZN+KjnkDMHHJX5nxkGIUhGYLncDhkyn2kKOQmaZqG9XpF8IGx7zMLdNbuSkKU0XB38x5TPFC2l2IpGEXuZIIjuYjvBphGCiKvry6wr6759KMrprHj9vZj9vt7/u2f/d+5HzuWTQEhMl1eUhYFr68/5tvfvuXv/ubviVHxxSdf0p9Gfvv4laR7kfB+RKvIzf0HTv0RjKYqa5rmDmndLOvNJS8+ueLjTz/n8sVrtlfXlHXN/eMB5wNlXZMS9F1PdAHfjzze3vHd774mJUUfvKQxKSWsbn1isd5ileJ333/Dw/6Rv/nt3zKEkbFwLPsVqYzsuwP3uwfu7+55fNjx8vIlm8WKjy5esyhbylRT25ofvv6U1WLFxx9/ItacbuLu8QGT3tOdRt7s3lG1NWVd8otf/ILt9oL94ZFxGnnc70HDUrfZQ/1ASJH1ZsPoBk5Dz69+91ve3b5n8+s1dVOzaBvKsmCzWmG1RichfkzDiDWGqihkOi8ljxylqNYrqqpi1Yq39+Nux+g9tx9u0NZQ1BJ20yxaQiZ19f0JWxRcXGyp65rdfs/hcOD1i5cUxlA3FdM4srt/RBWGclHRNi2r5ZqkHFE5DmPP4AamIuGBm+mOwQ18P9wQCLSrlpgc0+lAUzVsFht0VYnu1lhxEgyyxy6SdO46iT/1nG1PnDO8MySdIpfbC370+ef8zV/+r7x79074A890pioT2U6nk8C4IaCUpixrYgj03UBhZ2Z7ngATqKQorby+y0XLaimKDmsUhVb4piAsa8gFzzsJNRkmh88TecgeAVJzNIVVIs0qLNZqcUBLQlRSSIgKcN63K6NF6VKVxFhQtyVlIdGypZVEusvLCxaLpZjW9IFpHLE2COqRBC6PmbGvUGhjmdP9ZFcvZLuQJz2lDe1iSQiBoizw3jFOHSEg5iX5bKaUKMo4DKgorHWTQ6Pm5lWUAj1VVfLZZ5/x3Xff5ZhLKfRzIwnScN3c3Jwll0LalPtdGjHpGuZifM5sN09w+T+GUUOITNNwPsjnj5lnMX990zTZL0BIh8djDl9aLP83xb8wFozGaiGsGiVNpmTEy7BVFAXLxZrgJqb+JGY0dUnBgkSkqCrqoeVP/vS/YRj6zNtIDF4kXVZVaOS/Y74ntEoYnYTBrqVpQ4E9r6Fyvvk4ogjiqBgU0WtQBUpLo5EkD1JeT+9lMg9CfvWEMylYrth5in3aO6QzQ17ngpxjar2XNdPcNKlnn/lR4rnIy4dOgmC4qsq79HB+D2bb2HnNOA4j3rmz7PTbbyXq+OHujhjj2Wq2qoTvMicDijzZnsO0iqI4v99/yMcfXND7fiDGxG6/Z/IN1oovdAjpaW8EWasppBph+ZkzrAeciQnKJKLVmcUXzsxVlVmeWuV9ZAwk7xi7EzrBY3GLd4HTYcDnAAVb12hbSXa10bR1RQwtF5sN01iyWixZNC1VWQOcD4vFYom1FdZUdEfHNAaqwgqXw8vhV+hEWZQkDVMKhFECGWxVoNqG+nJLud1QbNeYzQpdN9RlQRGihGxEMEMrvsrDxBQ88RuBYhRCTmqKkugFRt3vd7jgeXi449AdheRkC9pVw2K1pK1rkVZ4h/KJypR8+voHXKwvuGovqExFGWusshDAj57h2KONxDVWpqIpaznAB080nqQMrhuZip6pH/DOya2RJIPdOyFtKMgpazVocW0rq4KkND5GXPAkB8fTUfpyJ/vxMLlc0EvGomQsKyHNaM0QE7osGEfRzHsfJDWu62S3NxnKukJpiYXt+540pHMj3TQN+1zQF01DWRQoEpNzvHn3ls1mzeX1hRxmQ0/UjqgmhjgwqQlnPV55puBw0UOjSSnSI6iCV4FCRaIGlQ1irCkwymKTxST5VSeLSQUgNqkyuQqsKXCgyuulNS9fvmK5kkbGOYkDPX/kCXWe+vq+Px/mISWiD2f990zs0ZqzPIqUnljlQ080IhuzGqqmYo5U9TnlzI6jsKPne3eazlKtefmv8nSj8iGp5z2unmeefHgiB73oo2XSq5uKRbuQKVwJc9n7iePxQIiJohCb376XvGiVpIDbopTClBnb2jztpX2QZmR+vczshEYpjQ4e7xIpGoFWELkRWlCHoJRI5Iw5I4nzDtY7hzGa7WbD/d0d1mjGIeRJXfgFp9MxF2lZIfV9xzA05ymep1fl9x5bZQTk9wlt5zc+Nx9PhT5m7/+QjUfmJsFa4dOI9v7JAW3+/jE+QwHS/DiCYiQt5TGkZ/B3yqTJKD78JklxOb++tqAoajabC+qmJQQHMaDcJFryKNdiTBFNJt6pmHf4OVJ6bqyeQKy8AkB2zimiUiBFYeqnKOsdnSlqcmmL5C2m2Ywn/d7rln/cLKOc5WtZAkcg6STGT+n81DJ8/1TI47N3T+5bcoObERyl0M4J2pMVXGfZaQjnnfg0zgVdpvLT8cjpdGAYRP49o1/CJ8kKiuwyN0Puz6+D/83q5v/Hxx9c0O8eHrDGcOo7lsslbvJ51wNVVVDXOaBhctlHWLK7tdZsNqLfnLOqDRarDWVbMAwDXTdkYX2kbVthx5YlRhc4P4qm+UNA64KbN+9wk6c79lRFTV0vYLPGpCV+7IhhpK1LSrvmT3/xTwhx4sX1lratubi45LA/8P23b1DK8NOf/oy2WdI0S7rTxDR52qqkMAbDQAwTd7cf8CGSTIELiX1/ojSaRV1iX1yy/vJzihevYXPBuNrgq4ry1UaGtHyVVC5hIlQJBp1wf/f3Zwna+nLL1WrN8WFHf+r41S//nofdAzf7B5JOXLzc0CwbXn7yirKtqLcNzksWfMw6qZ/86Ge8vHrFsBuIY0RNiql3fPe77+l3Pd1Dz2q15qNPPqU1DdftBeNhZHf0zFKRxze3DA8HBj+ATjTLFpRiPIppUH/s0EpzfX3N9mrLxYsLJj/hg8MFR4yBohD4aHc44KaJw+OO6AN4cTGrTEFpLVVRngmBQRuiNthKdrjD0Mvzm6Yz5N4s2qdoTQ2nruPUdVxfS0DO119/JcEq3ZG2aXj98gV3u3v+H/+f/yeffPwxrz56waE/YfaPJOPAetJigNrhy5FoPAMjrnTUVcvoJm7u7lDI1FuYiCdiioK2XdFUC+qioXQNNhYUoZHCToPCENWc/47wKsi2rDhev/qUy+2W//nP/4wP79/x/v0NfU7xS7koxhjZ7Q+Mk9idumlCay2ue24ELEUU7b6GHOUqh0MMnsP+ETf2hLGjLCxNaXl5teXqciNGIWo+gBNdNzA5z+Nuzzg51FEYvIMLxAiRkE9dISwpxITEFDKNJ5D3akYLlESookQ+uV4vub66YpqEDDS6nmHs+P77N/T9wPdvvkcpzeSy4Uchu/XNxQV13bIYeqwtzzvJGbWQ7ye/t4VomIvSEqOnmAzjYEjJE4OTPActXuuqlJVgk5UA0XtR1RBJQQJpqsLy+Wefctg/8s3XBff3PQ8P92di3Pv37xnHkbZtidFzc/MBpeD6+upsgnOWRxFQcS42Ch1+fydufm9in9eSGfkIPtvwPnkVzAf8/FpIIUmgUkZDkejU3PzM1qZl6TDZ3ey5NG5OCJwmL+Tm0aFsQR0RpCklrK0xuuD1xy0hBo7HPW4acYeDFDcmUhRXyUQuzElhlBR44aorwcLngq6lMSzsXKjFcAavxElOS2odGZKeZZspgY/SmFDps+PkjMTMRTlXYIKfG4AIaDDCrjfanFeeUc1rTynkM6oW5zXheT8vjcXvEQa9OBbOX+fdRMhE1+gD3enEOAw83N9yOBw57Hcy6Ga56TydN1X9e/7zSgkvxKcIafrjk+I22+0ZOpqmiVPXiTbTCBEqpVLSaBA5itGKqq5zOpREgRZFkaPhRHs6QwvivFac9aTjMFJVLUolkndyqKDRypOMQB1EB1g0nu60Y+yPPD7e0Q8nCitv636/I0WPwmVXNvH+Puz3hOhZLBbZDUpTVjZPOYmQPCk6vJ+YnOw50RoXJfUt+AncxGEa2Y0Dw+6Re+fQxyPKFpgqR1AaSwqRYXfCJsXSWt7dfOAwdMSsFBimga639EPHMPaUdUEbF1TTiYBMYyl4jrsdla9QNtK0LVfXL4X5PXm63YE3R4cNVuRRk8ZPAZ255zNpNLoAPqGjojEl62qBxqBdwp16cI4pOYnFtTL1RGRq67uO6ANtI+lZm82GU39kGIXPkIi0rZA3wqIl+sByuRSvbqXFpCcbihgE0dHWoKsGZS2qKIhAfayZnKMbenGRi+4ZOaSkbVq0lv2Sc47HxweRIGVVhfOOv/yrv+T25ob7mw+URvOr3/ya5XLJerWhXBjKVksO9+S5ebihcyeOowRvBCPTTj97JBQFyWq0Llm0G15evWZVbahMTRFKKeTRorGYlOVSqAwJzw5TkgKekEPJuQmlyPLP4lygYoz47IY2Z4SfTqdcHBS2sCjVYOZd4nzYIFB1UdjMLDc5ATEv/1PEu5GhO2U4lPOe0GhNXRZcX13gQ2CxbBkmx+54YnSObhjzmRrypP7kPqeNzPtaPz3XWUc8646HoeP2NjAMoxT+KAXp/YcbxmHE2BLQhJAw2tI0S7FPXi7yhJvO7nnWmvzfIgebyWHRx/O0BeIoGIO8Fi6bC6lcwGx2L5PH0lI0vRAFAxHnJqwVdcGsPT8eDrx7+1YGFGM4nU7EGFmv12itBR1aLDKqIQiP1Ianqer5Pnz+7/l56KyAmN9zpZRo2vNudi7m81rG57Sv+XGMlebA+cD8bc9NQmZKn9kcUVYmKfMIZo8/GxIoLXtxW5CUkSKdoqyRtBKpZVKUdSsGQBHiOBJHyQFXUZ/31DomvIqYGNE6oo2Y1KgQ5yW3fF2GuWNWTUgksEERUCZm1cg8mStRPARBj3RGhOaAIa0EEVNJKHcasSJWIV+dSox9olK45IgoQv47UWVl3Xxf8ayQ5xd13smnzKLXWpQNs6GQcL98JqrK5WiNIWY0yGglbomzU1x6kirKvS1ryNk90gePCuoZ8vOf//iDC/pHH3/MOI7nvd9ut5PM4bLAWEPTNDm0Hdq6QhcFq9UCYwzv3r5FAS9eXBO8Z3c6UZZQ1xV1JZ7o88V+d3NH38lEqRXEHLkqUKMhaCGxSeiCxyjP/uGO/X7PV1//loeHezbrlrI0xOSAyIcP8sKV5VNUY2Erttu1sGQjVJWlKAx9d5KA+umIdyPH/kgESmsYY+Dohmxne6Q+7Sn3j4yHI14ZJjQBha7kxl+2C/zkeP/VNxRoXi6WdPcP3B4e8FVDoRbsjgfiONIfDrhpZLldUq0butAxeXFrckPP++8faZctyY9cffEFP//sc3aPBw77I7/5h6+4u3ng1eVHNGUL3kDUmGxjq5KBAGHw4ALGKda2xa4U/dQxjRPjw4HRQDQRZbTs2qwmFTD1PYeHR6LzrFdrLi8uuL6+Rj0qokoUSpy2Lq82VBnh0Chx1zOWZdOgE6ggSUXTMAq0rDSLzZairvFJdrG3dzcM08ihOzG5iVN/wpayR1oul1xst8y3+K9+82tubm/QWopZXZecTif+x//pf+Tx7o5pt6M/HVCl5fWr1/zoiy/YXq+5KFeE0eOD4x9++Tve373j6E5EIvWixhQFzXJBVVbYpiEWFqMbrrav+NFnP8EOBjuaXMgNOpaoKE59ZGLcXMJD/iflHMlhGjieDqgUqQpLU1fne8yHgB/HJ1g5N89lWVBXlezbWo2fBkKOKo5xJjYl6lr2uFVZUNh5opZ999h37MOYs6Qj2hYYY7m4uKRqKjYXl2JoEwKnrufN+w/sD0c+3N1nS0w/byKxJlFYCa2ICYyeJ8IggRtyrKJQ7Hb3vDmdckxwj3cCVe/3RybnJagDIMlqbr3ecv3iJdurK4Zx4MDMMoeikL1ju1hQFAV1WeeJRqZhMbjSQk5LJdGVpDDheTJIMVqKX1XKmTMOPdMkZMGUEsPQU9cJpSrR65cFt7c3/PLv/47VZkNVzdGtEu1bliV3d3fUdf3UwD3Tlv9j6drvQ6niCz8bkzjn6LruvJd97rnwXAfv8oRoskmQ5MFHxmzc8/T1Jjd3mpmE57NDHeEpWtZEMCagtaFulhRlAUpik4MXqaPSEiUcY2K52oi0q2wYj0ceH0+Z0B4zR4N87XmMDmgVMMaL8xwBMdgJaGOomlYKZcqe6QmETpqNZoxM+Im54qZs6aspMFm/Hs/2xhHhqgqjPqJDyC5x0nwGLSqHk/fytUpLQdd6FsydP34vSyDD7uS1lyBD5rwnd+MkRN5s+tTWDUVGIzWyLiwKg5vGjDI5Ugp5QjeSikdm4DtBZnw2lvlDTWXgv4Tlni+ii4sLqrJku1nnC0/cbR4fHylK6aI3q6VMv1WF1oq2bbMOVrpMgZQSLuuEZyhLodhsNrRNK45xxtLRIzuwAClKeIO4qZDiRHDCaG4aw+XFisImtIpoDWXVZpJNTkxLzyYhPzHMB2IUz90YEuM4EIPH6oQuNGVTiazFTYxepBLOTQynI+ndWw4+4E2J1wXeWKLSBCXuU+vlCpXAHU/UxnDUinEaiER2xx3d/R2HqmFdlhRK2KC3+0eGaeQ0dvjgGA8dZVXy8tU1L1+94Oc//wmLxRI9etZFRbspKT43HK96uoO46H308ScUtiaMSfgGu44UErfvPlAVJW1V8/DwgXdvvudw2jGMPe1FS1EX6EphSktdGYq6pGpaugTH3Q6XPFZr3DRy2EtDd3GxpZ8GQgoYK/7N2lppnIKYq/iUsuGFwWoN1pzzkWMmtVgrO75mscCUBRjpYptFI0xpKzvDw+FA3dSiFa5qFk1LP/YMw8C//4u/YL/bcXp4IDpH0bb4GHn37beMpxPD0PP5j35IWf2QzcsVF4sr/tUv/vcMfmBKI4EIhQRkVItG9Nq6oCkatvWKi+ULCmoqW1Bi55WmaP5TQBfZSyBlrS8x63NLDodHHh/v+Ku//gt+/Xd/w/sP7wWhKixlFL7F5DzdIFyVszY79/oJKDLBzFtN8JbSWvEtcD2gWS4WLBctZWEw81SNwpo8Uc/aopgPpxjpe2mcfPDnlCjnA8Yo2rbmhboU+VdR0o+jyNmSwrtJPNVjpDudcM4zZOg9ptzQ5D38zGg2RuUUNw9KyK/T5PKO12KsETvhwqIyoleVNd6Lusa5iXEaOPWnXJSr7N9A3tEqrNHUhaG0mrYwNFVBoRtZ2STRlOtseOKD53jYEdxEfzpJWlmSUIxxHFitlnz55Y/4i7/4X4DEOAzEEGhaOVe+/e5b7u5vSQhb/7lDnJiFTGcJms2kPonGhJSy0U2C2bbXe3/escqe/YntLntUeT1nuH72KFDMUqmMBGhBX2YdfYiyR1bz5YTiqXQlzKxSUnKNjJOjsLKyIEVCTGIelc+1mA3UlSko6gXLyxcwTdD3hDDgXZ/PaI1C4OgQHIGIUgGFuGcKRh6ZNeJGZfwun4UpesiFOKmEUYW4s1kjDHyjiClD3kVFUZWCyMaAih4dA6WRVUt3OOFCJBUlIcHgnEznxoDSJGPPk/pcROdfZzpatggSJCBFfP+0Bpm5X2JUlETB4h2FsaQUZUUxjoScZzBP5lVZivdBWWaYX94frQ1VJZkORVGcofj/3Md/UUE3xnB1dUXT1Fxut/R9x36/YxoHTqcjbVtTN8JsXS4XcvNoSbaJwWd5zlzQhfjT1A22etqPFVZC44uiYLZLVASMEih0GkZEomFxY6KLibZtaZqaq6s1i0XJ8fBI8J71aoHWislJmMMwdMySOucnnJ8kqScKSch7Yf8SI6bJ3W9bkZznsO+loOc3Z/KJ3TiRbm8JRU20FdGWJK0ZM3y13WypbMm2qvG2oFYQxoFI4rDfcbq5ZVdVbKqKq4stdVny7bvvOHYn2mVDipH72w9sN2te/PxLvvzkE/53//SfcTyeuL97YNEsqBYtr1cvCR7+8q9+yfE48Nmnn7FoV3SHib4beOvecjwcuXn3gavtBVev1wz3e978w+942N1y6o+8+OQFzbqhWJaUTcV2u6Q0mtYW7FPiuNsJuWpR4qaR3e6RixeXLNdL1HEn1rQ5N1hZQUJiSgQFU4woI5C5LiwmlPij6I5jhtxEw6loF0tK77FFwZy07oKnnwZiiOx2O7Q1NG1LU9csFwuGsafve/7nP/szHu/uYBrRhaW+uMBPE2+/+ZqH+zs+3N9SlIYX19e8fvUxLxev+fmP/jn1oiZZMTXp4ggayrYQGHZyqJDQAa4WFxQ01LaitoVYsaaAS93ZhQ0twT5JJbQFUxUUi5LdOHJ3esdf/Mc/4//1f/2/8fLimrZq8nWuqJuGcXK8//BB2NDPJEZzxSqKkrZd4AtN8AVUJSl4Hu8mUlKsVktWywVlkclgwaMwOXVNSzOlhG08T9Td6QhZZaG0lvWHlvjJRVuzWC6p25a6bXncHzicTtze75j6gVPfM3nPqZPgk91hzzQ59sfT2ca2XSxYrdcsV6szoWqaJD/AWPBBWP5aRcqyoKxLisqeuTnLZSuxk5PLufAdp77Dh0BdSHrbEzlPGpem1FxvN6xevaDQBbo09KPwFNpa4PTTqSc4CeFx40h3OspgoUQ6O/Qd69WS5fLHbLcbIDGNA26aWCwXKK345tuvz/vytm3OpkcA0zQyDP2Z/TwHqcwFQI5ewZpCCJxOJzEWmiZsduKcp+wZng1hXq3kpLic6Q2CPpRaP2NpPzHsZ+ZXSrKn//2BL+GVOlsRqxnJMOq8Tg0xPrMLVnOeiXAblGV1VZCGgWD3TOOJpCFFDXHKK5+EAEPCTVcqYWcZXX4NtDagDEZZUsqNTvR5daVBJawtUUZQYXQi6IALETd2si41S5RL4MVpVKdIZQqB2IeOfnLoqiEA/TQRlSYVBRgrpM4Zfs8EtxQSxGdr//l1Lktmd8Gzw1w2gJmRAedGxhBYtgtSlJoxjgPBOVSRMAoKY6jKiqqsKMuSMMtQlRYvkKrBFgVtu/jjy9b+23/1r2jals8//5yqEtOR3eMj79+94ZtvvuLrr7+iKCX+cX844NzE7a14IK+WS+mk0xwV+eSGE4I4eM2cmpBZm2UpCVlloRmj5+3bb6XoToGyrFgs16Jpt5aH+w+cuhNTDm0osiRlGDoJkciTeVHYs9PWrP0lszC1sZSlAspMphhFzmI0Jlmx04wJPPikGZPFKYNcP5Oko6WeoBSmECjwcHtDh2YwhlJr9rbAukAxjMSxR+uEKRS6UMIN0JHRj3RTx3gYhSGaD7aL9RpC4Kt/+BWzV7UNChs1p5NjHANXmwsuN4a6rNFoYVCHRNu0qKCIK0eaAt//7msOt/eowbEqalpjMSHgTieU8Wg8p8cHhu7I7eMHbh7vuHn7hmJRs9IbpmBgMrgwsdvXXL264uJqe/b1n1mmbhwRXpu8vhgDxqBNolqALksx9uh7yizPmg1PUGLSMnkn7NmZFJISx/2evuu4uf3AYb/n9uYDx+OB5WopB2cSJOWUO2KSXIdNXXE6HPn2q29oygXJaU77gaIq8dqDUZTLUjKVCyFbLduWuqxZr5aUWIaTE0/yKZ31/3EKkBTaB9CRIU4ERAo2Hhyntz2//vWv+Nu/+Wvu7m5o2wbnJo7OczocmSbH6SRFyhhLlS1ZdXZalF2uZCXMhJ35ME5Jph2JE8gmNue9Y8qkpAQpZEcuQbrO68F5Ysv7SfkiJeqS/Mf96cDpdBSJkobriw1xu6YbJybn+HB7R9d1dMcDgYTN0lOrC6xC5FBDBynQn/Z0/YDWooqJwUEEWxbI4BVQyRPjhFYNdV6F1U2J9yPgGcajeF97UdJUtYRkyKpIYUwiRcfUn9DIwT72PdM04sYepRTHY8cwDuwf73Fty/HwSNu2IoGLgf40UtYNdd3w8Uev+fnPfsr3b95yPEpGeJESr16+YrVe8S//5b/k888/fyY1k6GlqqqzZn0u0HNxnhHP57tyeILXZ4hda31GFZ9L4M67+DyFc+ZFzNfG7OCe9+lklZF67hM/KyN41mhkNneEcDbBma8pMXYRBEmuGZUQsqEt0c1SuDeFwU0H/ARuHCUgyWfvCZUh9CgM8ugFTU0qolTer6c5DTD7O6gMhp8lb3LdezcQU8BqMCmAG4jjSBgGWSlERVlZsJq2sKQY6KcBBzIKa0hnoP0f7c6ff+Tfzq/VnE2SSLlRIrs4Zg+ENJtJkRPUAuMw4MYxIw+RYeg5HQ883t/RLBbZ/0DWYDP/xHmPz06sf3RS3M9+9jNWqxX/9J/+1zmQQnN3e8N6taDrjnz33TfnfU3XnRj6juAnrDU0dSNmHjE+K6RycfkQcD7v0mI6E0BiSkLnNxqv4eHxTuD2KNKpsi4wpsbaguPxkffv358L9HZ7gTYlzo2o8MQknbtkpbNtpktoLfsWa8Su0BqBNg4HudGUEUJXVSlMghQUPipMNAwhe1zkncfkEj5BsxR9bDcMkBJDEjXlMSlqpVhrjQ2RQkvBVkYiA4MKTHFidCPRywXRGk1RGFZtCyHw7rvvRX5WVpSqpFQF/b6j6x2bi5dU9ULia/OhEUKkLCqoE6FZcHzccffhA/3uiHKBtizRVUUXjvjREyfwOtEfjyQNj+ORu/0Dj/f3QtZblaIXdZrRj5jO8vqT11xcbCnqSiQnKRFDEAlRnCU7hqQFGlRGCVGuCBxOPdPoCBm50fYJak4p53YzE4nkGulOHT54do+PHI8Hdo8PdN2JuqklbtUIqejw9i0xiDmL0ZqysAx9z4d377ncvKQ0Df1hwFjLpDzKai5fbdFWE3WkaRoWpqUoSzbNFj843OCY9gOhnyiwGDQm5dCcIIXSBY9Lni4NHLoD7+4/8Jvf/pq//bu/4bDfUVUloc+s775nnBxT1tZK8pgYvcyE0fmaNdacSXApE94ST6SguaDnMy8X5Fn+OdtkSkGfYXwyxCe7//l0enKuSsA4OYZpoqhqbFmyXrVi8uM8oxN4WhNF767AIiRSjMm9gcNNGlJkGnumoZcAD6XE0U9pjM7PIZuLxOBQKlJYTSGsMbquxPsiNy8+3+8arYp87WQ3LyUF3Y29FHQS09BJGl2GNY9HCfTpTkcg0fcnisJgzYoYIuMw5Gx6w9XVJT/84ac8PD6evTWMtVxdXXF9fc1Pf/pTXr16dXZ3k7WiECmfwjnsGSr/x1Kn50S55wX9efHlWaGZz8+zTC0XdPVsVz43aiqz3GcC3vyYMyKqZ1vgMNPBZJKXNUi+QLIsjZALe4bBdVKZ5KpBF+haoazCWIl2DsHhE3ifJckxolWmh4Yg1rMhnw96LthRrsV5wpuvZ+Zwm/wzkmQPTZT1aIrgJ5IbidMASaPRWAQOr6zGe81pHESyl/M35saXvKeXz+d76/n756YXda5P558kr00kPll2uOc+OQrp0k3iqCr3WGQaBwZjOR73xJSwtqCqW3Ql6wSF1MYYEyEMf/Ae/Q+Xrd3c5AN0n5PVLO/evuVXv/x73rz5nrdvvichbNMffvIJ6/XqbEz/5s3358cJ3gtjOsPvbdOyWLS0zYK6qqmqhqKwLFcLrDF4N1I2FT/7+U9kFxRV3tNBVVY0dc2nn3/M9avLp++RJU7jOPDcfUtYxqK19MHjMhEmxoTBo6MiKWHO2qpAF5YiJVJStFHIKy5ofIBpShwHx7F3KHeCfmTqxEO9f9gBspdXWlHWQqQ5DoMkcBUWHQLae1TYQFqClR30Y7fjsd9jrabQhkpXTH7icDiA9/S7vTgMoVkutyzaFXW7wdia3/zq10wuUtUbUlTc3x0gKZZlS21LtvWSWJb0xrJpF5jtJcd+xzB0qCqgtRjqJBeYxhMuBm7u37M77pm6I0k5kolEIw6N7XZFvWq5vfmAj14sPwtLVTfn6QEFKSQcQexCY3qWA5wP86rAh4j3UhSUAm0NKk/aKWuJQwyE4Ngf9hxOR/b7HX3f8Xh/zzD0kFLOAtcSzxEj2hiKzZK6qdHAh7dv+ebXv+W0P/Ld69d8/sUXrNdrkpU9/eT24lleGIyx3L/7wMvLF6gfBhb1kmW9wlQWHz2lKjEYzOwQl1P4xILUUChD6Doe3hx5//Ud3/zyO/TkUD5SWNlLrzeXpARvb26EJIYUHB9inuwqYgyigdaJpNOZBSuqkIC1ijIHxYgzprjkPU3nOYEszD7ZZ7+5J1vLWa8dATQ6AFGjdDpzAaIbGaYRNw5obSiqmkJrPn31gulyy+V6zTgO7HY7nA+M3nPqO/ano5iRaMTXwUBZZTjZCphpC4vVieG0Z58ChVHgRxaVZbXesFitKF9f4a7XrJYlfT/kQkiGQBP90OOnkeF4YN/tme4/UBglqXPZHq5uGqy1XK5fkZDgmaIo2SxbmqqkNHI9GrOkKC0qeq6vLvniiy/41a9/gzaan/7sp7x+/RH/+l//a7bbLZdXVzRNw+SckLPMc220yMpiFIfNWYo2T+YqQ7V1XecmXBQ9syTv9yaz3G+dA0jIjmlJkIpCm/nLIJ51B5kvoc8DvKxzpGHQaLHC9TI9ozjbxYaQ0998bihnO1ojjzklUa40ppD7TltUIUFTRfIorXBeVELO9UQPBinq2hpSJr/Nz/dsmp5ifq5i4StNSESHEZIX7TsBldw5x0DHkdA70uRQwaFVgVYWFZyQc7XKPvVioJSMJapEjEYkcMj5LlK2maiZC3PuI1RWjoQAc6gOcL4XY4zorAQxWnwi3Tgx9D3H44HueJQBI2qGvj+vLbwPKG1YxCQ787LCFOKrn1CiHvtjF/TT6QjAfv8gJv5lybs3b/j6q6943D1wOh2ZppEYPdeXFzRNRVWVQOJwODKHK0hq1CkfMBLTl5AnVpWzPKmmrhuM0aAiyigur+XgI8o+/9T1El5RWTblmvVmff5ZD8eDSAnSk2UjmawgZMlMeiCdoRPpchUx5dhUazIZQroynQpSkrxi7xKjiiQPQXlOIWInh+4H1ORw+YabJ64EpOCZuiPKGFxVyUUZPJOrcL5g9AUmWQY3MriRSlkgEpLFB08/dIRx4rh7lCCQoBg7R9f0XL8saBeWh7t7jt1IUXbEqHi4P2KUwS03bNoVV+1KiC8oKluQ6pp+2BG9IxUhX6wSpuLcyOgdx8OOrj+JVG+E/nQk6EQwYGqDrTSn4xFTWJJKlFWJNpLTPcOBMc32puRpQJinMTw5Jnk/EVOU6Q6Vd6P62Q0TRPPuJrrTSchvpyPj2DONI24SxyuFOts+6nwTllUp+/2UOB0O3H+4o6lrJjew3ixROqEL4Uz40KNtNrNRihOaImmO22sKSlSlUdicYlZhlD0X9BjEHIgodsXGGpI3jEdH99izv9tTa01lFKYuqIqCzfYSrQ37rscMAwHRETM5jLGYbKgyF/HnE/qMfphsSTvPZ/M0I8VdqsAMo86nUzrP33KIxnwQxSRBM1E95XSrNMOHPmdv+xzTKWuAZVOTmpqysIzjRFOVWdM8Yo0SpCwjYJW1RGuoywJtLNFmqpG2KC1RnqNSHPePLJuGcehYLltKoygXNYma4EeGRnaOQA598pAcY3QMyROcfP/KapKVEBqtDVZDWRjWqyXaGMpCVhulNVgtZCyjlaztMmmrqWu22y1VLTHBL1++5Ic//CG/+MUvWK1WYoudndtm0ppMx5zfs3/sGOe9DBNa2zO0LsS35xKl/zTMmtKz84xcXGYSHOmMzsz/Sgmijmhkt51yyMmMzsiE+ezamuH4fM3MpkVR5+Ipjr6EpIjaUGghNUtUq2Sbm6KCGDBFiXYlMWlCzAt+DU9F/Nmnyk8u85xmvhO5cVFRHPhUQOoCYohkFBAi0ScIYiOrsaLUCZnPguytU5R7NGl9XsXK94oklU12znfI/Drl1UWaX/+5IX7+psy/5BWuApLO8agT0zgwTaOcf0q07E4bxnHAFgXVMOQALyfQe0Y1Z9XCH72gv3v7vewtvEcrTVHIQfPJpz+gXVRUpeF4OjAOPff3dxwOe9brNWVZ0rYNs3e7c46uHzOJwNK0C66vX3J9dc1msz1n+364vSMGT1EatFEUVg53nzzKGlabde44peuuqxo3SQSdtpoQIi9evCIlzqEep9MB7x12HHJST/YFUuQ9TWI+xUYXMvlDjkkTjUxgQckUo8GphCOyIOc/p4CNnn3fScIYgFaMrhdyXwq07YrXry5IwZO84+piy8V6zTiNnKYjUQewic4NaAf4EaUiv/rqN6zqhqv1GpNkQk/JMAbH4XRkykzVqixZrVcChKWCkGHd3eRRw0R/OHK4v4dpFDgoekJ0HLsDo5qYBo8qFKOSgn5z+44peopC3P1IXqDi0WFPBdooHm5vGccB5yaqpiZ4CYt4clqS1KyyrGRHXIpFZkK02CqbpiTvCciUXdUNRVWCTgzDwOGwozt17PaPPNzfs9s9ZhMax8Vmi7Xi1e294+bDe8a+IwWPwVAoRZomTrsdbpC9/vu373i4f2CxWNB1HXXbgEo87B8oy5IvfvQjgdwXK1w3cffhnof3B77iO2qzoDQ163ZNVdQ0pZBWrNZgNI1t0QbKxtAf9pTJYD2oKeLiSEiB6+2Wq6tLfvTlj3OwD+wOB3Y5K72sJLxCac3kHaObBMXW6pzXHINAfGVRSCMlcuFsUZm1ucDMVE5Pp/z5OldaQiK0kkNKZygfJAhF4NZ8VAUPIeCdsNlTcGdpVIIzRFhrRV2XrNuaF9s1X3z6iRyWCva7A8M4UVUNWhuckxzz0zAwjhMP9ztC59mNA7VSbNqaUkUqnXLim6EiCLxuxVVOLFcT22WFnyaGyxblHHocBaXIhLIYE6awGKuoTEKbRCgNMSZ2DzeyRhg6nPd048hqvWWzkXvVKPjyi8/Zbjb883/+z/j444/RRnLrTV4tSHJeYhqjQO5GU9gCa4vztD0PGDNHSGs5godhyNav7kwInqH3f5zC9TywBUAlUYkU5dz8zV4GuREkZf/zbOub2fWigddn6H/+UHnqndUQz0zjnniacgTijMUoIfipECgMlBZ02VDUFUsdqeuG6EbGXhPHPMnmCfpczOO8/095H53lZ1HJdag0IYmfgEkWDBSlNJ1KQ/KBMOX7vTSSNBsDw2mP93KNJR8p5VVgCOKZEsNEUpZo5IESeubxzZ1T9sPJze+5y33GUkhP95NW4m1ntTREu2mgOx3pjif6rjvnFlgt54VWEsrT9ydiSgzjRJ198pt2SVFI+t8fP20tw9duciit8F5MMeqmpqpKYahOkns8ew9ba/DeU1UFAmmkfCGpHNlnn0wccoyo8yPeixGF945WVwJrGn2eqCVkozxfvLawIlnIb0CZoamyrMnfEK1HhnGQQ8t7McDQ8RwONFtiCoSVoceUSEmjUvYJTup84UWtKI3sZhprCIXBlRadIsFbnJ4bYIVWcmdoo6lKS9tWhEnhVRSpX6E59Y5x6vHBEaJn8g6VEjZ6it5w+3BHWK1ZNS2lKcQgI0jalI8C30sAhmXZtqAMflK40dG5IyRhZY5D3uU4B0FY2omEjw7HyOQl6GGYBkY/0Q8nolbYRSVTrDVoJ0Yc3k2Mw8A0DNiyIDhHsBbvPFpLrKvUEAXFnOwl733uo86GH88JPgmEu6ChqipC9tqOMeZpfMLn5i2FQFWWVFWF98Kq9W7CTxN5vEAl2dn5ID7LSsE4Tjjn2T3uKauaVV7NHPcnqtqL/7wyhMIz9iOH3ZEUFMEr1m1kUSUKU0MyaO2xCZIRkxCthTRUGI1VCh2C7A+jaFhjdIJyFZIqV9UNdV0zjOO5OCptstEFZxb3GVl6Pq2fuSYmu4LNu/Qn6HT+unieK/J0rtTsninwNfOeVjFnb56zoPP0pJLsQklJkB3lCU54E+FcdExmRRuUFiLk7JNtIoyVo65btBG0y/tA1RV0XU9/OJ2behU90U9ENxGmkagSOllBQGJAJzEpMgiRsswOdrrKxEYlu1UVE84L1I1KqBhI0efJTZpxN8m15LJ8cOwHqrJmakTbXVcl11dXlFXN5cUFy6Xs2h2z7E44OqLKicSkMSnbWMc5/vIJmp1Jb8ZY5hAY78PvacznjxmdeU5ym6d6kIIuvxci6fxay0eaq5P8/zS7zT0hMM8Jcee/lb/fDN/PlSs9zTy5jonyh3xtJ0T6VhYWVSiKqkGniC0rvJuIU5+beTXTNSClbE5EJrwlUlSkEAQVVZ5EzpZPhmiyRXh+LZQSWRtJ1CHa5Os3iSmWc56YZmfFpzWUGOzE8+f8nGbjnXlCV/k1PlfvuaYr9fTnqPN7/PR7zvJFn/POTSlrC5MdG+UxBLlx05Sfr6IIEW0KUgKT+Rd/yMcfXNBXbStv6CLDdxkSmcaOcegZ806rKIozI7PPzFKQ7nq93rBY1Gy3l9IdZtp+143041vevH2X1yeSpGWslpxsn/BhmK80alPStAs5VJKkbIUYJbo0Kcp6IW+sNnLh6gl0IKLxUeFmB4MkeeFaz4lPnDWcycwEPiAqlFd5ksm+2MbSWMO6qblctYyjdPViEyt7GWWE2PB42ItmPzrauma7bXi879k9PlCXCaUm3rx/y+Nux7vbO7phwCWBlw4YHo73PDzcs24XfHV5zaurl3zy+hM2q0vW6zW2qLG24ssf/pTlckNhWmKA/f0JN06c9ifGU8/+7oEwDqChm3q6w54xjYQKyBaKpkpgwKmRMQycpiNVU3N5/Ypq0dBsljwcdtzvHjmejuwe77m43NJYy6KsqauGthSzlNM0cPabDqKt9s4zaWFH++BpFguKssCRiEbho0eniPHi/75crzDWMI0jfd/J3slY6rKitLKWaMsaawzDfs9wOnG4l4zq5MTkIoxTfi8DKibqqiAoS8Lw1TdveffhgZ/+5MesVitev/gBhbVMR4fvDpwee27tA9+XH6iqlqpc8PFrg7msKPxIUNC5Ea0kj1ygPU9VWjauod/dMh1uUeOemokpOXwUIlnXnfjw4YMoQ/Y7TqcTwzCitWG52hBTYspe7957MfPIpNIQhIegUqBatNRVJQ6Naj7kEs/8wZgT0eb4SZX/mYMrzmrbOMOGTxNhyvedVRpbaHSeLueGuut7vHN0fQ/wFDZRt8LS9UGkjFoRfRLXxKUQ/sp1LZNrhGEYuV4schqaZrlasd2uWVSGIk6EbsDHSHcSlvs5fU7NzlrCHbBElPeocaLQGmvEPGrOd08Jxn4vzUa26Q0JTNNSZVcva8QE5N2b71ktW7Y//xkvX39EPwo5sOtOHE8igx2dTNXr9Vqkdm2dB5vss1748zAz9GIctNlshIdQFEyTcGScE/vVqqoIIVAWEmjzlLL2pGk3Rox4lEKuayXmW2d3s9lg4zlSm+S9JUUieWeei/Xz4JnzF+df5936rF1//nVJKcaQI229IygD2bffFgV6uUHVDauhpyobdiEQ3MDpNDCaAMnk/Xv2uFf6XFRjJt9JwIshJfPUsCZZ36ENqqwk877IkH6KJDeRxsB4ONKPjljUoLQ4x6V0jhAOVpNUklWE0nnczx3RTICP4ripYhT9u85Z75mRT+YaWGMQ2/MnRUJ/OnI87BmHHj/JOqowgnCXZZGT1KygHW5idI7T0IMyHA4niqKkaRboP3ZBP8sbMh6h0pONZYpC4EGl804MxItYupSAUp5xGvPUlicKI3DXHCxwnuBRaFOjkia77GW2JlkWpXMAgMrGEtnKUOucZiRvzJnRaUQGJHnWsztT3i3l6U0rJbnLWf+rdAZU0lN3mk9CtFE59lUmZWsNdR2onDg2+TxtmqqUQ8YiJDw/URYFttCAJCuN08A4Woax//+295/NlmxJdiC2tgpx1BUpnqrqQgMNcAYcAeMXDufX02g00oxmBAU+YIDukl1PZuYVR4TYkh/cfUec+/JVZw0Bs7G2jGf33ZtXHBGxY7v78uVrYZonso/NiY0HgFQSfCo4pQtSSVBGkXtS2yJkIGaFw1YByqLpWjKcUS1yBGKfEI2FLRqjMvCXAcl32Gw3CH6Emgz1miAGCwAMUExBLKRwBl2grUbTOTSto5FF36BrG4xhhgqkNT6PI8JMrmq5o5sHmXvZ0ERU06K9rGq7LOVMFRPfi6RklUkmlNXfaASIRiW7rkNJqbpG0ZpgoQc2JUmso1xyQUkZMaRqAiQCFlQYFEzDiBgiLucLGmvx5ds3aNsWXes42yfDlZILnHXY7Xbotxu0fQ/XNTBsUhQzMfsVMlSakbKBMxnjNCD4CSVH7icXnkv11bLXWPI0EL1zY5aeZs6k9qa1YY1sYdVyf7EUMp4x15abSu5ZLD2/sl7OSsmNtb7L670rzOv1eJQqC82q/qYCrFIkDsR3iZYqPkfCTSMJlBSjgcjJRIyAsVCGxVig4RRolhqAthaNVlApIvsZUSskliKN80ToTCkgX2xCjEJKlJYYUED3ga1VjRSp9SMFT0msIXZzzArGeLpWStgIhdXP6F7su46uVYiIIWD2xLQPaZFsjbGFNQo0JrgIWcn1JPlbEh4RNGSeZ1wuF3bdoz0uxgijDYzJtRJf9mJV4XKAEKFSlj0UEM6FCPtg6bRg2UuXK08BVfa35eCTJRA8n5N1QFeKSHUFpLZG+EStl6ilYx1s26HESKY7KcJHgtU9e7ZbTcWSkWAJCuhLP1/V1yNs9xQDS782dTnLhEaJHsmTTn+OEcXYKmcrxFxBLK74A7VvzvfKuk0lP7u6X5afC4chy4RIztw/n5FTRCnp6i+VxDVOEiB8Br7/RJsfyvxsDfzS8enCMuOIlBLOw4lmP9sW4zzhdD6ibVt8+eVbFs/P2G63MMbi8fEB0+xxuZAv9sPTIy20XLDZbHF39wo3h1vc3TU8CaiYiVvQFOJy+wxYBbRND2cNNpseOUU8nc5oG9rkicim0HBfjkQjIvquAYxC221hTIOcFaZpRMnA7EdMU0QOJMGXnGZmeVPhziSQUC5ATryRUSLiGg7m2lLwUprVsQp+enhASAn72xtAKexe9cTQDpE28nGCTyOez49QOiHECZfxDB9naFPQNBbdZgNAIfoZOSUM3uMye/z07hH/8OEf4X77/8Wr/jXu+lf4d//tv8NvfvW3+NcpQFsNW4j40hqDrrN4vbvDdBjQWQP/+h7zV2/w44/f491PHU7+hDEOeHx+hg8RwQQiv5SIoCM2N1tsdltsb3q4poG1wGbTopgbNJsWk/d4/vAeTx/eYzgP2O72ePvVV2jaFk2zgbMW202Ptm2x3e3ISEEbTGGGjxFzCfAx8riawsCb9fPzMzoe2bJa4/7+Hl3bYLfdIPqZst2ugdEKf/+f/xMePnzAcDrhcj6xqARQQkHwCXEaGYIGXGPROIM4exqnARC1xve/+y38q1f4n/77/w6vX7/G27dv0bYdtrsbnIYR7x+f8Jt/+Xf423/9b2BcD2WJIAUF/PDDe8zThOhpRGU4P8OUjMcn4N2PP+DpdETMCf12g8nPmOcZHx4+4DKOeP/hEUprnIcZIUachomcC7Umtnsgln8dL2JoW5yeNDKZGfFEiZJEp8J6dP9KsYFlFVMirFiYRQlQuDo4kJE3s2VLyAgfqQohow+Nm80GBQVh0xEMzboSJSU0IJ4EJc6F5V4zxsdHzMbgzMQfpQ28Dzg9PMJYi36zIRez5yfSt2hcFZHRbB9bxzPnsY4GaUWStConag05CwULxWNKzjZQSiNkCri5JKRccBkChssZl/GCtttgu79D0/fY7Hb44acPeHw6ot/uYVyDyzBg9gEPj8/IALa7PXJK+O6777Dd9nj75p6DaK7ysBIEYyDiXAjimFYwDCO+/fZbdF2H+/vXxFh3NJNsuLf9T0GuKSWM0wAJLmJLrYTNblhRjmDIGkDAcL3M0AtUfx20y/L5Kv9TZEXKyoa2cxAxwpgK/BTgLKC1RXe4h2s38OMFEwye3j8AOSLNkTQLDHECHJMnlVZQYmADDn46s3yvQirk4WHbBruehGGgMzAHYIyYjyPmwSNOnFRaC6iEFGakXDjeWJRkUbRCziRsQzAYn4iaBUur4/qcU9JCQWI9UphiJOnmGPD8/IznpyfyBElx0XxPPOWTSUWz73soY6GtI1S6KIRI3JdhuMit+E8enxzQ+75DjBFzoF56DIFvasu9I1RlOIFvjLUwK3u/5UVp7qHw+AXP4EqfUAF1g4EiKCTlApULYiK4MaQMk+gNKyb9GGY5a20BU6qiETXJDbRxMCaR9StLXSKRS1DKGSVllKCgdUJMRBxJkRIQpMQQJfWiNDMvi1KL/TV77arOQCegOIa4GgWVuGeSgaK48jUKMQVM00D+xJksEpXYUzLbXhkN05BKk7EaOSakkBA1MOeIOUdM0eOHH3+EnxJ2dgck4PxwhioafdNjvAz48acfEIOH9zM+PH7A0/mI5/CMIQ54HI84RyINZpX5Zs1ISIgl0oIEuY5lVdC2DsZZbEvBZRgQUyaXOqWg+FoZpWCVgWPCmObES0PBaQtYRZVtSVj3z5f7iDYl6yw2XQtraJY8ejbIyWS3uN/uSN/5b36N4D1+/fXXRL68jAg+YGB9fj/PcI56u7c3BONtt1u0TYP7u1vcHA54e3vAzbbH1lk4a9AahVkTaQygXtscA0qmERwohbOfMc4zTAFSTjjNM0oMeA4z3j894f3zEU+XAcPsMbNmQQgRWnukzFWOTEbkjJISxmkCoJBZHYyMr1aMaSyfqRcrwXy9ES/VNpSqtXWBVD6LGp3MKwOrPZtv2FIyM/jZ5jjTREROPBnBv1vY5ARcoWi+f5WiwEUQORli6FrFJBTF92ykESNTClrNg+kA9cFTpL6qAjRI0wCSvCTigyCGygokYhJg2JqzWthqDcAQilMKYBxVkqCea/A0ZjWHjLbfoN3OOD4/43g8YfIR2lpcJo8QyZmNWNEk6eq9B5DxXmVS5rMGIQSGVU0NogqKTXeozTBNE87nM/1MffxDLoegM2siW84cQMQURIO4P+xCpvlD2iwVHuO1QTGJGXDSKy7rhQDUZnG5rtABmYNXMNzLpu0yI+TCI6QKMA66KWiaDqmZiTtQCms3cLe+KCgkQnhYqlYpBZgEnRSZnigh+wVEPxMq7GeoWICYUHxAnj3xaIKnPT1Tcll04b483w+FHRekh64keCuuzBdUoAZ4Jfchatu58H1A90SmwM3PP08TpnmqojOl0P2RJaHke0kBsJYUGg3IftkEipuib/EpxycH9K+//AIhBLhGYxgGvH//Hm3b4M2re3jvMc8zttsD+k2PYSARB6VIoYsEThJrLxsY64jx7BpkKEyBbCJLQd2cWEkDSjeAUhinQIGWs6GUEqAyjM3ImWRlsbFoG4O22wJQGIaJmcAKpRgY08I5oGl3yFBcSRTSTPcBBRF6ngEoaN2gFGLLl0wXiqo8DZMM5hKgi4GGAXiWUaAndeNglcMle4LkrEfWZNXhTYDHBN0A/a5DnDyeL2eC72JicX9ObDSgOwfbONzcHrDdbPHq/jXOxzOePjyjKQ0aOESncQ4T/s//1/8LVFD45u5r2GLx9NMTkApa2+B0PuHP3/25ekn77BFywGN4wCWf8KH8hAkDMiIkyzeGAl40Ce8e30EZSjBubm9xe3ePm9sbbLZbHE8DfIiwjvpBnbZwymBjGxpHtA0UDEqIpF9iDBrboGk0SrLQJWKKMzkkGQ3wWFjTNnAtEcde39/BKgWrFHIMyDHg++++xfPzE3719df4+ssv8M3XX2G72eD1/T1SjPjw4R0ePnzAP/z9f8aH9+/x/bffQiDEv/nmK7x+fY9/+9/8N3j96hUOux2MNvDTzCJBAQgZZShI44g4XXB8/IDvvvsWk7LwMHDbHWAd/vzTT5i9x2G3Q44B756PmC5nnN6/w4cff8AffvsHvP/xe/z00wOKpzl/O86UKM6eBI26TYW4gw8Y/SOUMjDawjqSuxQ3wlKE30EQv2VFOa10rSJeFBMLaKiWniTbptXgfvU3K6JUChHZe8QQ+X5aRhyzUvD8uqKfAcg9bNA4RxWzMlUjO1oKHgVATgl+DnTP2AY6JbSloDcGd5vNwmcBJcYhSeKtaFYpk22q8jNUilB+opaUInOaXesoUCAhehq5a0BkvHmckHJB022hFNnPpkLto8fHJ/zw4RFttyEvgzliDgmXibzjiyZ53HazAwD89P4DjDHY7TY4n4/4w+8fsNv2OBx26PsNIT3bLU/8bKC1xuPjE6Zpwo8/vmN2PAkgOeeWD+6VC6tdxhdDIM0IguhJYCVngpe1XtAXBfIt08qwxahU5ahtgARSVCt5gY3l80JWpWCuylKlShsmlYJYMpMTybcBrIevc4IFmZKgaaGsw2Z3CwuNp80eYR4RpwElF+iiUDSz8DWJUoGNZAwKtI2ALjDRIMEgpYBxOKEJFl5l6KSgg4IfZoTLDD9ExDlR5Q2NFDwiFBF3S0E2hqRec+R+vSVWv+HWa1FA0SjSS2cMnmgJJErtEyew3GrTKASxTxP8NCDME56fH3F8fqLkIudahMTgEYzhIoPGuxvn0G230LaB0haRJzPmEKuV6z91fHJAH0ZS5yqs6HU47GFY0rCSNhgWFGMBYeN2XYtSgLbtOTMiqGa4XOB9xDhOVfauaQjKJI/ZUr1mNYs1jJP0FhMGazE0DRrWwvXeE5yoUXtMWmmURFBNKY4SdJXRNAZNY+DDiBB6hDghZU8VSAEFdCgkVjIqSQBLkCUhw0FQCgnUDwo5kQqSp9n6EGmzMlpYwNRHn3lsrmkdbbDW4v71FsY4PFxG+JiR2Bu33XTUs7cGrmmhtYU1JLF76A7YNTukGPH48Ih8TNBJ46h76KLx4cMHGKVxe7hDQoRtLXLM5KWuSTDHx4Ahz4jMgVaWpglCjEgZMH5G0cD5coZ1Dg27gzlnq3OVYRis5ERrP1OW3TUOriFDEYBaGKpkIAWSgoUiaVAAKiWolNA5C91obPsNuq7F3X5Plq19D6tJNSz6GTFQAEoh0JrLBckHREumCEZrvH51j75tYBTw/PYt3rx6RdfdWdwetthtenzx5h43+x1u9zfQWuN8PBPhLNPrnbPCfrOBci02hwNaa6GMg9UOrusAa9GyrGTbOiSteG3oCplBGzjXod/s4AsFJi6Z6KyXAp0JpdJGwyhaT+T21bAoC43TCNNd+nlF8XokmTXURbranCtzvTYal0OqtnXv/WflQO0D5/pYSoH6+lLQKTa6AJt8KGEl07rnO4d4FKwHrnNBkKoPmbuvRNYyzOxPq75j4c2Q5B2JgAhFZEQUUpRUoDWWE+C5VWG0VGNM5s0KwzggxAQXEpS2gG0J5sxEMmucQ0oRl/MZPhYEhla1AnwkzV8XAqA1rFZAyRjOZ6QkXtl0PsmMJtRxtJwLrLWVAOnZ6/7+/hUOh1uWinWwxtaxtdVlAPXHE/fMUQM6WB5ZPoySc63rHLlUt+AKWto3SpFrIqSnK2tHArqcV8PrRZaQUlU0NQOImpCXUhJMyTAgEmIqxKOBVtBNC9N26Ld7Ii3HQHitLksCAe7/M5ETsSAXmiCgQGwoEKeMVALmywCdKaDHOTLamSvHohTiMEVGWJfWN1eR0o9awe3Cwgf9sxL9CUVGRZbBiJqWvn7ObCQUMHtfP6rMOLcT5D2mTNLnwc/wvoVxHhYaxhLvSBtGs/HinvyF45MD+rsP7+rXzjnc3X1FlV4INfOMMSD6wHPqS0Wx3x9gLSk+pZRxuYw4nU54/+49VeZQ2O322GzIyKFtW4zOws8ap9MZBcB2vwVQqvpbLgxVFODt27dk51kUYogw2kNri91uR4lFpJNHs/MttrsNSFc+8JjcjGE8wfsJI3MFtCZpysSStJkhhMydyAzKciOrePkUMcdAbmzMoJznGUYb3N7coJRUDRtOpyNyTug3PdxGwymNf/Ev/w43t/f4/uGI8zjj3fMR0BpvvniNGCPev39PlU5R0IZcqN6++QJfv/4S3/79n/D+3Q/Y5A6NcvgQChCB77/7Ho1rsd31MI3C3dsDTtOA+RRINEMZ+JRwDgMFVeXgWsqUh3NEyRFhjHBhhs8Bm80GN/oGCgV929JGmRJUydAl0XiI0shdD900OGx7tF2H7XaHEChxI6WsAGVaGKvQ8EYyBA/EiMO2R991+Pqrr9G3LQ7bDa2vvqOAbkhlaZ6oT+qHAYkFG54fHjBdWhgF7Pdb/M2vfgXz1Vf43/2bf4NxuOB8OuL25oCbmz3G0yP8eIHVBVZrvL69hdYGjaJqxbkOkw/4cLzgbrPD5v41Alfmud0gNy3sdo9iLB4fHmC1ws1uhxgCHrsOYZxo7cDAtRtsD7dQueAJpManDblFpcq+jyi1/0uEQucabHe07imYKRoRYphQ2lOGZ8FpI8ayIa8O2Q4qEYfjO8Gx171zJQ8E0JovMm5VViQ5TUn4agOWKhIl02akDFKKleBltaUWkpKRpcJiVAR3y4dChjHUvihcuRYASNxmUYSMGUV99eIstCIuhAIouYszLinCOcfGF7kSlkopeHp6wjjO0KaBtg6b3Q2K0ojQgDa4Oezx9HzC49MDoCygLWzTwmqLeR6JyGsc9fvbDrP3+PD+A6w12PQNkxRNtY3VipTxgo/oug5PT89kOjMH7Pd7/Kt/+a+x3W7RtT2ahtjtJD27zJbL+Q+Bw2gpdXyUvApcTWBMTQjs4odegFJo4oSkZwsjA1yAASw7qnh/oAVSv9R6FcxB7VDG8xOPAiJn6JxhFWA1kQ1TZvhfA6rbwELhcP8G83BCnEegEBeEAJlc20kk21zA9ufIcab2Y2DzoRgRS8F5nEjiOykUcikmFAeqJi1zLgigPU9BVfEplQqgC82tS9LL48kygJYBcD5CSSYTuYlsm4BMOgXKqGqwM04TpnHAeRxwmQaEkijBcvRRVCHCc5ihZwMzXmjvLAp9X9C0Ba7pSfSoWUx4/qnj08fWDvs6L1lKwfF0rgF98fgty81XVBUSMUx0EKnGrm2AskMpGdNEb76kiHm8wFnNns2JZs8T4TzzcOH9hRazUWA2ckdjRtMElUmBp3EtjUyoHVk0Zl+fW3MFRa2MDK2bOiKX4gaNGxBCwPkyMCGpcC89c0ZFN0BZ74CJF0QgSKVhS75qZ+hpVMLBoNEWXdPhOHiczxcgJiAXNNs9TrPHwxAwx4zAldMweigAh80BRhm0ysIHA2sLzJwwP57QZODQdGgzqYvnOAMZ2N+T5rbXE1LJuOQRwSbYG4ecKIsNJmKGh2JlsJgo89WrnFBmnym51QyVTjT/7yyk7iuJoKHT8RHzdIHRBW3X4XBzw3AfZ7e5AN6gnBUeL0eMfq6ohzUaugDh6QmmaxFLgmlbZBSMMeDkZzw+PuL5+Ql//x//I7779s/44ou32G63uLk5oGkb5Jwwzx6XcSALzrZlj/MdtLMIKaEoDW0dwZUx4zSO0EpjmKjlYlzHzk4tFID5coFyHdqmR/AzUkxotIV2Dq+tw+gy/OMjkfVSxpwS4uWCPM3QuaDEhBiIdd31HWA0YmEPaAAxR+o3a8MqdNQamGeyB84pIfiJSJLRoyTSvyeAhyYtSqGpgaS4f82CJ4KeSYUuBi6K5VALMrJeIPcCkP47/0M0rhWva9nUae+Uxi6QNYn7lCJoAFXuRStSxwJVXcIPKRrQjYEqbEISCzABWSXy3sZ6dh7gwWPa3AtNQkDxe+ZxmIKCVAqUODJmIPpAbGtlMMWIXADrGjRFYQ6ZmeoR4NaAAkneNs5iu9mQyEmhvaekgkYDWWmYkogT42foFLFxFsZqOGOAXOBnDw2NrulhGYGMPmFME5A1Gtvh9otX2O322G8PRKBzHawmEavgI6JP0IYmQ1IiZj/ZyypOokD6E5YmQiokrmn8quSCwgpvMhYGTWNWxNcBSBp46SFrJdKzuu6ZhLouwZ32QLZnjcyBuUoM6bF8JO5Ro4ikaTPpvreHW8AY2McPSGFGDCO0KjAq16SOy2XEQGTraSZp1M2GVERbY2mKxUcgE9/JaBIbypYkQ8LoMceEIWuEouBdh8DM/FSAbBpoq9CYFqkoxEgjjqUQWU1rTSTQDJZiJcJfAY3PZkXJTMzkSTIHDx8Dnk7POB2fcTyfcB4JfjdGY/ATmpLRtgrIGjEn+OihxpGTDQ1nLJwx0E0LK4qPLxL0Xzo+OaDf3N4ixoj8/IxpIr1mMVYRi0DnyNNY7vGu7VEKzaAXFIwT2Sb2LEaz3fZ4enpCeQjkr+wnGFWQQws/D9zDJae26UIuSeI+ZYzBtutxf39PWdE0IUcyjC99QiktjCabvjF7oJQ6v9k0BjkDMZK8HhTQ9z2AgrYlN6XjcUTwXB0UYqemTP7vAkXV/laiTK8Ekk3temIcgxWfEgf0RhkU0yC0PZ7TE56fjphFKMVYbE8njLpFVha26aGLwvk8onMNXt/cwRYNm4AQLHqnoMeE8fKENgF928NlA1UU6QRD4e7tnpTG9IA5BpzSAN1YuL5F8BlpDphNxASPVmuqciKNV4g6pBxknkPhIIaIaRzRti3QNjw6ApQcWNr3CKUULqdHdD1dI6rUidsAACHQ2vnuu+9xOp/xxRdf0HSEs9ApYioZ6Fr4kqC7DhkFl/MZz8+P+Pbbb/HDDz/gP/y//1/47rtvsf+f/2fc3hxwd3+Htm3w9ERz6KfLGV3XkTqYs9i0DZATZh+oJeMazDGQrvyZZtwvwwBrLPrdAcoYdG0HHxPG4wn9FsQH8BEhA62mNsiXTYOpFPzu++8R5hnbAkwhIRxPSMMInYESE/zsYQxZv6YUEHKs0x05kZyqdnRTW1CgGqcLS64GRE8iK6oEICeyWjQkv+qcYzJSQSoZ2moU8ZbmgH7lqcxQa8mRNmPuVwK0eSwVPZf8mhEAvZCpElB7rwWK+vKlgOiC3J+tMp+gziMnh5a9vE3LML3WyKEAlkyKpjhyEGb5XxTAKKiiGfak8TWq5vjnXPkL/AztEGNEChFNS97zs/eIMcF2HWAdxqczSsoIMdJ70yQEpXJC6yzUbkvTHyHCh4SUCloZ8SoJiKRwqAHq2RsNZTSQM6aBxGnarkfbdjDGYpomTMnD2gZd2+FvfvUvsN1ucdjfUfLpWgqYLIZDwlxkEhODZ5teDraga0iubhabTV/5RZnn7QvzFUTASQRNsiFab1LShqCArvg6CidRG1I2k6LtY4S4HKnFKO0fpTQlf1DwgYqgnDKspp8b06K7fUXjbN33lJxNJxYIytBI0CpxC6kghQkxRQzTBAUFizuacNrukRARWX0OucA4Dds4RFVQVMGcJ5oQCkCARoJCUhYRxCQvJkNnjda0mGOGj4kJqoBu6X3MPlDiYOj8xEgCNo1z9Hia7k3vJ4x+xhw8Hp6e8OHDOzyennAaTkgxwmqNfhrQ5gTtLJA1TA4oge5bwfO7pkXrHAwSnLaU3H/i8ckB/en5GSklDONYRR3kRpQPxfObqzodADCy4ERdFKAZwuFyIRN4a3BzOKBrO+x2O7jGYRwnhBhwOj4j53Ild2itRde1GIcRZ3denh8EHzprSVd6GuCVwjRSdW+t40rGVZao4gXOzUOkSOL7QiDxnvrq3ofau5S5wZQTkiJ4XReF3nUolti/OcYVRBYqPDZPM43/ROoNimpeKkBIGREJSZEuuE4ZcZrh9QzlE2xWcFEBPqKw9WnrSGDFKg2TFHLKOJ6eECKNnTVdi8OrO1jlYEqLOUWM0WNMA47zmYRcYABFm6/VNOKz3tyXMRpi7RIjt2AYBrRdW3u73k91JINkLj38PCInX8VGRP53mj28D0iRFvLZGoTzGWmgqrrnUbf5cqoJ4/sP7/Hdd9/h93/8I/7xz39GjB7Oki737c0N/Dxjnia8f/8eSitMfkLf97i9u6s9wa516BqHRhOvavas5GRIhGOcPZSKKA+PiCHi+Hxhn2Lg9i7AsH+Xgsb48IBBKZzHmZKEaYIOAePk4S8XlBDqR2Z2bYyRSUyB+3tc/RYSvUlk7kibTc6IPOpC2t+ZZS4J1hZ2rFRPxmiuxLlnDkrA6gwrzyVXpjKzfetnyN8ViN7nz3SrlfRyZeKDvlF/h6u2WqtJRc1/Qd4JEoBpMoR+jTZgrD/zXwHSpy11b5HHkGC+zBJLW5R6uYURhmGakDnRLQW4DBNCStzCUJh9gNYZ2iokHxDiBcY5WNeibcjdcJxmah3NkUi5SXFlSucqAdDKwipXe6n7XYP9/gZt2xEh2DjklLHb7dE0HZxrUbLC+XSuyIWQIBfnNULCrCPEpetaGMPXVytGyVRV2KN7cLFkXR9kT10wzXSveu9htEbbdcw5okAMpTmQs+gLV/Qoq0kL/hAuQ1E0wSIJodTYqgAx04SDITwIllsIyhhkAOM0QZcIU2jUzVlSm7NWw5oOBQXWWZQCNM4COePh3XtETz10Wett26JpW8RM/fthHDD6CJ8MoiLhl6wVcjHIKiMnIjxnlofNKdO9xx+QRJURKkooNMcZA6UyctKICvV8juOIyzjweKPntgat5pn1B4wxcDEiZxAnyoaKdM49jWi3zgGpsMbLf+EK/Xy5VMid/GBpE1h791YorSwLqZRSjeD7vmcf3YIUI+aJWOjWUM/q7u4O2+0Wzjl8+EAey+9+eo8QqO8kGWLTNDBaw9sZw+WCruvQtm09IaL05D21B+aZVOZoTIDkL6QvpbWmERg+iIhIkJ2CRgyJxvXmuSYUMo6ZV+9TKYXOkebu+XxGiouoRPSLVSJV5JGdxpagKSpWUWVkRb0ZVYAyBUQoqCnCJsBFBZsKbAagGzStQd80aIwFUkEKCT6xK5aOyHaLV5s3UM6isQbH4YLzccCcZ1z8BSlnZsBSRmyt5dFDc5WVS9KUUmKeQcTAwZf+RleDFTmvOUd4axDCWM/TPM8YxxHjSEIqt7s7bLoNBgDeOsRhgHU0h9y0DcI8AopG6L7//nv8/ve/x3/+3e/w+z/+Ef/iN7/G27dvsN1usdttEbyH9x7Pz88ohfqz/bbnAUNai4f9FmW/AxqLxhj4GMkDgAP67CmgxlQwTzM+/PTAN7aG1RbbbgNtyehj8gNiTLgME0GLPkCFiDAMiONIY1wsT1vElCOJvGfksMQM5qwoiBEohMSwX4oR4rYmTk6yrgDply+JF1XhZdkAKlxXOAEQdo/6eVDnYC7GLR9TDqttGMVQ/FUyIA+jluDKkG0V8FAcgKukLH3ONZCDX4NQgdage7kK6YWf9TqYL/d2TKmu4XGeMXuPpum4tTIixAQoC6WIwKp1gVVUkV2GCZvtlvvYDsa6Km07zYGnDfhlcf85o/D5V7VSdq7BbreHaxpy4CrEmzgcbtE0DaxxABSGYax7RNs26Dc9NpsNQ/Vk9GMtjQW3rauqcTTWSdM48zQjJ1JmlMT6pbCNTByRdjztR03TwDU8MaAAyAgkw+QCtUvytBbMAeFAvNDW643WTmbP9FQIzYl85aonOmt+zPMMlT1UmtF3FgoGbaNZIrkl9MDQPum0Rpwjnh8eSUxqnOv6jzEgxIBUgFQKxnnCHBICGmSR/eWGYmFNlJyobVCYLyVJIK0zRVAFnQzI4KdRPI0Fjagpfc05c7EyY5wmjNPE5GLqnxcU+BiQUWA8qZuiKFgTkV2ix1SaLIadQ2g6auk07r885L6uxEsp2Gw29WdVT/dF5rb+25wzzudzXbQxxhroSWGJ/l0KVeOXywXee/T9Bl1HkrLrhSiayALpE5xLh+ghtyxqL0xRUdNaHy9hJBFZ6Pu+vtcY42KEoNTV+xUXOWkHyPO9VNoiCdRYH69tW3RdV8/F5XLG5D2wOcA0HW5u79HYBr22MAWwsSDPAek0QscCHTPaTYPNzQY32x061+LDuw8YpwlzmjGnGSkBrnRwXQPXtTB9i7kEpCci6I3jCGs09tsNbu426DoL58gM5/rcLQFEuAhyLgDuu8eMaRoRY8Q4ct+Xz421piIr8je8F+Dx6QHP5Qk3N7do2hYbv6Xz/vCe+qE5cbKTMI40r+uMwldfvMUXb9/g9evX6PsOxmicThfM3qNlXf/EqlBWk7a4NgZdR5V/Ch4XVmrz80QGGuC5b8J6MHuPEyeyKRVi5nOVRb3wHYx10NbAAID3yCCSUkqRjGeUIg39mQRlvJ8RwgzNPgIi/CF3S8y8RlihjCBtnl/VpHnAqHIltWue6KDkmuBe6XsDy1qlg7kQqnBQh2ClC+GtSH0l0LKoRNSbhv9ZagpQfwRJCQqWbXFZK+t9gdA61iMXU4X1PfniXq3IAPNa6jzwam1WgY9CFXpi8aDn52eczme0DVXKcyDxG9f0BO2D2PizT8hQ7C3hoIwFWL0sQyPD0DhtIX5PyhnDMJF86/kM2zbYHA549eY1fvPNNzgcbrHd7vm8AsoYlBzw4fEB1jp8+UWLtm2x3x1qQSQJ3OQ9KSdqQjasI2LZZTjRfsZe67ttT3vIaah7kuyN63P9co8T5MYYU+/V9fHzOfiygvRZ2EgrWOc4q9RX16wG/ULaFBqAR6RgDvZbADHuh2GCyh4me0aryBcjsvOh1mSEk3PGHCakQMzwHHmMkhlrKUYEDfiQ4CM97hQiZtWgGAdjGsB1aDY7FNsiN6T2aLSGKQUmc7wCuwlqA1g6l5Y5AkSgo/s8+BnTOGAcLpguJwwXErcaL2eMwxnD5YxxuKBwG8hPI9qmgS0Fquthuh6G0cKcIuZpxNPjA4ZhwMDSrzTd9F9YKU4usCgKvXwCudBr1x45JDB67yssIRd7PZohs5iUaZEAhzD8yGKTgsXLxMEwE1ACprwGUbJ6KdLwMuGQ9yaflVJwztXXJAH65Q0iG8nP3I9WVa2cG7nBrLUVQm6aplb+MQTElGFsR2NORqNrHPZtTzagPiFCYRomctMqxIh2rUPTt2iaFgkJc6L58lACSjaIJZEAktVwjSNhGqS6aThLQfzmsEe/bdE0xFFo27YGCXr9sV7flwlVTAQHVzh9IglbQUZkAxGrVLou9DzzQDdl07Z0LVnze/ZkznO+XIi7sFpXzlnc3R6w3++x223JaQ2FAmYgGD6DEg2A2jCGe82SXIxDgJ9GDOMAP01wjpXWIPK0JL9JCk9U9QzjgNP5BM1WnMZ1tPFrDW1KZQgXrm4JIqVkldZz4n54hLEUvjRX1IWh6BTZuU/eby61l2iUqQhXkWK2rjddK3QptqWCFRS9lCXQUqCvX9ZK/TqoA0vQ5ufCEsDX9bz8fsGSaKxulgrzr++z5REBSTxeHvVVrOD064+lMr8K7DKVkjNyAXtSn+Ed2dIWUKvLuAxdKEvKOWP2Cdo62BWhV7PctDIGMJTY6ZK490zqd+PscTyd0cQOuiWW+83tLfp+i6Zt6Loy0z7ljHGcWOCK1fSapt4b0zThcgkovFaa1kIZhVQIcp/mAYWV+pxj5cMQK2F5vVe93PvkHEtxIwXU+hyv/+7qWrzYd0niVMiUH0vAqBon73b6OpZEnexCSIGc9xACmfHkCGeApAEPFi/ifSiyKFOcZ+RAbU3iCGSoooFCokcpAsGToqGfZ+JAaKCYghwCjHJEXDQGxVooY7hVQIhEZkKgmKfI2LHmm0op6tfnlFmhkAJ78DO1/eaJTKSYH0VtW5IGVjzm5rueSHWZCLol02MhA+NISoI5JILjm/aa//IXjk8O6I+PjwvcLeYLHLRkc19/AIvAxHa7rUFWAiT1wbsqonC9EIDtdg+A9jNA1f7tzzcE/CzQxBhXFctSlctrk9ciwX+dnHieGdzv6fk3mw1CIAm/eZ5xOp3qc6wfX86DvDZ5fjkPknhIQDfGoOs6nM9nDMMAzyYW//juAVOImIYRjWuwMQ2sIZEWpzQ6ZdFYi6ZtEFXE83jC8/kZJSb88P33uFwueJ5O1KNPE6Yyw/yuQbftsb29wWUakRGxPfT4un2D7X6Lrm9hXQEZY2ms1f6EDfvyZhY+QUHBYh/pGcZb+nMS9CXhkXOgtYHRmuRXM7DpN3DOUWtFaxRQH3CeCcZPzAKHZk14o7DZbtF2LY7PT5hGkq9VWuNXv/4VAOB4OhKMPs/otUbTO4zDgNPxGe++/w7Pjw8YLmekGNC3PYxhYw7rcNjdEnnKWdhGY6PJ0S/lhMfnI4ZxgrIOt5ocpZzWMA15dN++vsfT8xGeJwm+/ZZnyp1B9IWFWRRQVDVQSdIGSon6r5FQJgVmGiuQbztIzrWsgvF6rZO9Kq93rAIilg2W4uuy4aMw3F1whSq9THrlkaovNMry4NdffORY0oKr5LkmF+pnP/tYMJd/r5Nkue/WAR0A7xkTpplac5fTGc/xiAKF12/foDEdQiTt/M51yCVh8h4b12J/uMV2f8D+cIO228A2Lc7DhHkOeHh8wjTPOJ1HIERssobrNmi6Le5e3+Nv/+5fIpWMD4+P2PuEvo94fj5iGEa8f/8BwUfcv3qFvtNkAzxP8DFgu9nizevXAIgQOc8j5plGaq2z8J5alCESu3/Tk7dB8F8Q6RHLuVt03q8LGjk/UpXLPi4V+zKxhFq1y+c1hL/MecsYoySPDD9XpIRahylHqJyRcoAqCSHPyJ4sc+fZY/YBDjT+hUKg0DjMKCXDDhO0Voh8b/hporHOXHj8bGnLpBQQc8Q0e0w+YBwnzDEhmgKYhNzOKMZhaw2Us8iWpF8pKZCVygl2TjQGV8j0JyV6PkT6WZyJCDcPZ0yXM8bLGcPpGefnRwznI8bhTCO1MSCzjokvE4L3GE4TK1/+CdvNFof9AXe397i9uUNjLQwsLmzqdT4PHy2UP3Z8un0qCyBorgCMEQbqx4N5Kctikkq56gUXkont+74G9FrBsPqRZtESzT1GCTBt214tKAmuEjzWi1DIWS91kNeBV46Xm5csdIDe6zSRGMwaaq+JgELdJNcZr8xtCixIPRci5XVdV1+Dcw6jJwcy/e49cvDw44DsPRJIOrW0PTrr4NoOWStAO4QUMAWFeRgRZo/nyxHTOJJIjAGgCxIShnlANoANLVKJsM6g1y1sY3FzS+p+GTOAVF9zPf8fTQwLV4GsGc4cChqryQhhU7Pu5TrQiaKEYeFdkJzAkiiSfLBmb5eCvuckjdnYYLEFYwRxsJQRe49pGrnnyK9dUfUbI5loaEWqhOMw4Hw543w5Y55GljBV7LinYa1DY8mznURbOIHlTWUYBxxPZ1yGC9quw77raR5ZxrqYxNJvevYp13Uyo44LQQQ8CEGQmXIaoiWInbdG1P7kCsZWtW2pKrFzDVMXSM9TwignYlyNXwds6aGUVcV+fcXrrVJ/pdTP8n95X+t1ouRDXusaBbj63etgvn4M4GWF/rHk8rpal4cQHkKMpLM/TZ7IWrzB5pQJQ1WLmIgxFpvtFpvNBl3fo+l6ONfR9ImLmEKEtg4hK4QQAWXR5AzXdjjc3OLu/h7nywXPx2eaAgpkKe054S0l18o/pgjFRCqtNKZpwjiNGKcRw3AhKHd2MNZgvFxINAW09wTfw3uP3W6HxjXouU0m57nyKhjBWZ9W+VlhOIemIJbfl/OceRxQVVvTF0jli2u4umIVXCooUIlGepEiVElACkgh1n5/TokIkqZUNEnakWKqFLmNN09kk1ygoAtbomreW0HJboi+ElBTyiS3rUw125H7pYh4Xs6rm0XG+Qrfh4z2FGrhqUxSyGLTHMOM6EkkyM8T/DxS241NiRTAexGfl5TgfYJWwKyBHCOMUui7HmGzQYodsjFU+YeI4XKq6PU/dfwVkLtefawveGH4NtUgK4x3zezA8/mCUgratkPTAOICVAqNL6VUas9VYHkJ7NYRTLvb7VjQ5q6Ozc3zjJwzkefevUPfkyiDVP6y8CRYCHwsVbmwt0W8obYNciIXuZJ43EVD6VtsfY+2cQgxMLzFF4gZmzESWWZ/2EIck4gh7xFTRogMD2mg33ToNx1u7w4oLO8XYkSz2WAYZ2hNqlKX45GJLiPmNANxxqQtJmOrTvLpeMQ0TnR1jMarN2/QtC367QbWOWx2e3SbHrf3dzR/mRMu04SRZyO1JsnGsuqVKoWrDUGCESn2XW8Qcs3allQDD4cDb8o/77nJuZKjcQ0TGGkqgBjgCk1HRD+33TDBKWAOJNE7zyNiDNjtd2jQYpoGqmozkZDO5yMngOT4dzo9Ayjo+xbjZcDpdMThcIO7u1ue607sEx/x8PAAzB4lq0W50Gi4psE0eTxOZ7x7/w5Pz8+YQsBut8N/9z/+H/Dq9Wt89fWvaISo7bD98Uf8/e9/i91ug9u7PYwtABJSvCB4rqi5sqZzRdBw5PLbSHArEvQ5bJYMowFtAUTAaSKB1rZQ5kqCZ2ZLQZVVBiTovaykpdtOF55I8stGrVb/l9+n70hQp6+lc79kBOtO/vJoy/qh0St6WsU/W+8z18/38wpdUI1ck2YKJBmS20hVqVcBbNHSD8gqQacC1yVAG+wPN/jqm2/w3/8P/w5zjJh8RMzA5CPabovNzuH+7TeAUpX1fjyeEELAZRxRUPD4+Iyu7/DNr/6GRZBmfPHVl+j6Hq/uXsM5h6enI7wnv4GYEh6fH/H9D9/j3//7/yc5M6bI/dcBTUsB/XI+IaeIm7tbtG2Dw/6AzWYDHxJuDwf8+ptfkWua0le8iqohr7D6vD4USy7jKqFLMYO1H1dXAQCjRtYSglfrYxb7gjIsGCbjroUEgnKCCh4qR+gwIocJfpzhJw8/eygD5KKRLNlW55hRYiY+iQJ8oKJvHAZE7zEcn6EBNIaKxcaJgY/GHCJiynVm3GgFZTWsszBGwc8T+2o4JF0QY0FijoRiUSB5PzWX5f1dBQrmw+mJhMKOzzidnvH0/Iin9+/w9PgB0+WMHDy2XYdNy/K3CkSQFSlx9rawxkGjYDwd8T4EnLsjGteicS20Mdhtu4+2oz52fHJAF0hmgZlXYy0v+lov+2KJs2Gp0Je/WyoF+dvMqmwLLL6QO6RSX/q6S99WDqnQpWcPLOQ4+b489ktYsWa1iqrNyoIvpcLQbddCB12fa7Es5GCoUGF1eWxtNPn1shWRJD1reMuGiBAT7m5u0HceSlmaABBbxJDI1ERpGGWYsEGsSNc1KIrIX8YY7G53aNoObdeSQU5jYJwmlyoFWFiSq4VUzgUo5kW3dAnompWntKEK+7q/VpDS0lJYCDfX5/s6oC+bBAV0zTPUiSsmetzKY66ylNdrUtZJ5qybXhdB7DklFtdgZm8MPJ1Bz02TEQ5htkjcm5NRn8wzwLKOxbxinCY8P59wvpwxjiOUfqq+7tSOIlewApJ0jIG4BU1D5CVtFjlOkUCtlQK/Oa1IiIXkSuU6yClhBEgRcgBTYI2w2xk54ntLjIkk8Za/Xdfs6+ssqMsKyV//wrKpySqRe5K/i6u/KVd/f/W1Ui/2iKunwcte+s+r8OV74ARGEkSBgJe/WdaaWpEGC9g8JEZAWxRFI0vGGXR9j36zwWa7RZlm+DSybSzIgtk1aLueNnxj4UJESiDovmngI5ktKb2MnBmXKcHue1KHtA7H0wVQxMgOgQqE2c+YPE1/TPOE8/mE4XzGZrtB07rKEVqdrI+c8SVh0trwx7LPvOQKvfz6l9CP9fWr10fWrlwYAOIRXhGiVfKFnEn3XKY+eFqqZPbL4NZTjApRA5HHyMCJm2gITCP1q8dhhEZBchbO0H6peQ+KKXORIudCMdpGCAapM7J3eSZ/+KIJiZB7Uu5PwzBrYig+p4joPUYmw52Pzzifj7icj5iGAX6egEwWz5anBxyPHBYZLYyRMx72C8o0muonBWQguoDcUg9dTM8+5fjkgH5/f39VsUnPWGBtudgSUNeLSH4mzHHpx8gCLWWBRWXBEBlOoWm7Gihe9nfkb8lLmvyl11D+MAxo2xZ3d3eVcCJQsGUd+rZtfyatl3PG4+MTQvD1vUhCs9lskFJC0zQEjzFJTwh+66p/Tc6Tn0kCss6e6fEDmpTwN998BRTFkLzi0T7acEpKiD7UGLfbbrHpe1Dqp7h3nUnwBcDpfCHIZr4gwKNYJuW5BqUEiHV9UWwrqa+vl1Lk7mb4/SsO0ku7g8h19FqXyh5Yw3V0vHy/9VpKkOKeXogE28dIC3wYL/WxZFNumg2zXuma39zcoGkaBFaqe//uHZqmwZs3b1BAhht+JucjZy1ub2/IOKNrcT4+YxpHHI8nvjYyu0xKU6kUJD9jnGb845//jD/+6R/ZoAF4Pp/QdT2AjLZ1gCoYxwG//+Of8P333+NPf/wdLsPA1qZACBO0BrqmhfgPiXYDDKByhrMGJivokpeNULrVfN7bhvT8dclonaPNQmv2A5eElUlUJbNoRWb1t6WH/st98uX4S5WBxgrmxpJ0XP39Lzxm/cA60FwHmZev7TpALMnXuv1WeNOV+0xxS6htaV/QxiKmzAE0wHU9TC44XwYcbm7x5Vff4Ob2niW9SdVMOwVrNXTTQtkGPhXkEnEZyIoTrkXXbXDbvYEPM87nI+aZUMTD4Qb3r16hFAU/R/yn//QPdVY5hICnpyMASjA3mw3+23/7b/Hjjz/iD3/4A/w843Q54+buFnd397i9vUHXtdjtN3X/6vseX3/5JVpBIbWB44JCip+XojAvkbeXnIQ1H2kd1K8TAJBbJSgRlz5QKavPBVSdJ57wSRHFB6gUqFJPkQpDpXl0LZDXxagxOr24+mWKDU/HE7z3GBipKHEmxVBLznZkaU3iZkVpFNA1M4ZczJRzNDqogBgDtDIwOYOsMROMIp8HmXDQlqp9w54ECBNiChjGM87HI779xz/g+ekJP3z3LaZpwDieEcKMGDycVmg2PRpHxU1V9eO4cD6fEULEPBLKHEqkXruxmMcLtDI4sWyvMfYv3ofr469iuV/fXD9nfb8M5C9vyjVBSj7Lh1TD0itfeqmGjR6W3nXhfuhLskeKER7LmJwgAmT1uixaYh2mq/fCXwD8WuZ5QvChkj6ssdAM7eREuuWznxE8Ex5KoWpYU2CK7KC0TnCcdfV9kIiDrj3lwpKYln+nbSgoG644kJkXENmGLxf0fc/BmwK6sjSvba0lPfLoAKMQQWp+xiqusoFSNH0wHqrt0u+v13RRC/3ZziwV0LoyF/0BqQRzXiDZCvXVx+JNQhNPogBQhWVIs+LqStOISwEANjVQqJs2AMjMvLUWRZH+N41DshZ4ITENqYKIUKcRPJlCjOOEaZoQAjl5OTYb6vqekkDrKnJknYWxlsU5Mns2E5rj/YyHhw+YZ48///lP+PGnd3h6eoL3nnth0lMrXJ0z6kBnrPaZjdwPfD4FvVJFghV4LVkYRTKgIqqUMnGJaWRL198nxHKpossKVl0q5tWxLtM/XhC+XAyrCh4vFtE1xHv1XFeA0PJ7df+4+oXV16vb9WMV5XWVvsieUsVcUJDIFnm1J0hx0XYdrQFtAJVQoAgJypRkFtCIlNjJFH6PhS2hwRtw07bQWqFxNH9OEHRB0yx7gDEWux0ZR9F4bsd6G6Dqb5rqmK5SCvv9joW36JqT3oblM3WtF7FOmq8RtdV+Vy8Ro0O8by699eX3F97Dy0tfUMCjaVpSz7IE9JfXhvdvlclQSWxKqWqmexXMVAdX0IknbC6XAcEHzDP10B1zbfgCc8Fbqmxx5ZaszoOYvsgoprSLUEjuWqxmtQIR7jLNh5ackXhM7XI+4XI64vz8jMvxGcP5ROJUIZBandZwzsBaXQM6GegQ9I+i0TY0Kmd5DpXOgKa9kG4iaq1phbax/+VZ7jJeta7QXwb09fz1y4uec8blcqn/ljEmIcXJCZeA/urVKzjncD5fEOPCXpfMds3KLJmIBzFGhJFITtaS6X2KEfNuR31zDrLTNJFTHFf00m9fk2qOT88IIVRi1xo9qFA7qJSTx+ga6vcP41CJekoR2cFZC9fRLP1s5/q3tWrlxda1JJqDQn0WJHqPXdsTZGTN0mZgLNazcpXZWFhNvfVSCjaW+s+bSNrHTdOyH7nmLNxU9S2pA6WFIIEks8CJjFcptUwLSMLSdR2ahjTUJcOngJzq5krnFQBYh4CfY7PZkGRwJs9sY+j8migBqamvJ6QEH4jfEEJA23VoG1lDFspo5jeQCczEPc3Ze3qXijQLmqbB5fyMnBOOR5LfTYE0p+/v79C0Le5uXwEAK/oRbOdTQobGh4cHnE5n7PYHbLdbjH7Auw8/4j/+p/+I5+cj/j//4T/geDrj3fsPAGijPB2fMI0X6JLRWIsCQadYmhM0p2u1KI8ZTmwKw3ScnBTSkO76Do1RaBvH88kKPgRKDHKEUpZMLSjqwSjAaICodgWLsAwn41xZ1Q1WATKn/k9vJat9oJTVvyQoL4+g1CLIcv0z+vqqGAC9BtngMisSFt6PXwaLhXm9tOmo0qRr6JxDzIX02nMCqfQBiWVkU87Y7LboNxtY10H7jIIJkw+YfISNGcZ6tO2OR9gIlUmRRKHCMAElQSmNu9t7HA57XIYLpnHiKtHg7dsvYK0j8amUeM0T8keS00dM04jvvvsWx+MRp9MJb9++hfceb968xZs3r+vfUsIH2ldLwc1+X61019U5sBCB159fFlJy3tf73Pq8yt4on4kgl6sjni6sUsjrClArJIWuQ8kJSJlIcomMXHJRUNoh5Rnz6DEkD6TAFTol4zFFPDGKZlRG4yz2twdYA1gtRZOqgU9rGjO01hJJVc5DjAACpMGoOQmh7nmBoTsPqiQajSvkDZBTwvn4hOFyxrd/osr8uz/9EcNwxunpkdqSVsM1Fta26PuWWnAMtc/zQJD6OMEo4LDdENroWk7GNPzs4Wcag4sxY7Mhy927uzua9f+E45MDusC4L+Gbj95QLy7+S6GVdUB4mRy8zCjnmYgnAK7Y7MJcr31qvYhSyIJOrMq1ZgiGEDCOI5HWnIP3vorWLBBxqa5r8vrW429SlcohkLr8zBqSYhQmrdxYMiqyPl8L9EhHjglKLWN1kjUao2qFCvAYF1dmYK3fBJrrVJrgcddxosLmCYorYwm0SoO9k1EXfFCLCI78LmXuCUtvTq/OhcB0kXgHnETRxpuurqfWAqtiteEuLFa6tTgjVrI502vmJBxay2dVmeNCytOW1lnDM731mjRsYCGQG1AhfUlgGlby2u52ldDoQ8Dz85GTzw6lZFLwmjZIOaPviXz58OEDLpcL6dKfznh8fMA4TiwwQ5r1YZ7JZjPTdcxZARJ4OGABZKqSQUITUIAumTaUhaJBqITRcJbgVWHQZobVVSms5IgasJSSiWFKH1YDY7XKlEOq+IrY/IXq/OWPfunXl/Wi+HpKFc5/84sQAK8LyRIKfra/XPd7GdHgfYD2jFDv7citPmsdyA90TfLlVktBbfE416IrFtpmKMv6CZb80GGoUreNqtel5IicZrQtrY3GNchJUmZViXyUAC+qilprzPOM7777rqpkAuQxIcVL3/fYbndXe6cgLDFEnC8XOEPksLWC48s5c9nT1tdFfv7yZy/37eV8872/StgFtQIXK1IkFGBVsfOZ4BNNPvWLvS4hpLSHEIGM7p+YErHmtUHbdWisYec+1MKGKnSqu2W/gNj4ShXPF1qSkcKW17kUJGVYuS5DGeLApJyQE01InJ6fcDmd8OH9O1xOJwQ/QauC/W4L5wyaxspbIN6MMVyJKzhLffvYtPVcauY5KNa9sNqgdQkxtJRc9htSGtxurvhnf+n45IB+OBx+tgCWi1tq1Sq98XWAlB61VG/rcab1jOPLx00p4/n5CO89Qd0512Dctm19LmBRsiulXPXQCT6fazUpWfC6pysz7uvXQIFMYb/fk7Z439eFLR8vkxu50YSEJ4eM7cnvr8/V8oZpXCmMM0KhrB1cHRmlYR2bUiAhZI8pjEQAsbSxKKMw+Rm5FGhLm0Df9LRhMwFFdOlTzlVzWUhatnGA1pimmeY9kxg8UCWglBAjhaEs4juFZ8/J6z3nVLXra6uBEx5rl3Mu5+d0on5j0zaV0ELXP/K6Aq87Da1R2wVKWSahWZxPJ9LNvrkhUiBPREjbpgP1KHfbHc+0E3w6Tx7iE3DYH9A0DQ6HA1JKePjwiMenZ/z297/DZrPBq1ev4WyDm5s9iirEwmfVsd/97neY5gm/+93vK1s+UxGMYRjw+PhIPdy2QWHtaBSWd11VP5ScGbJipAWFBHq9YgteABhNUF7XOLRNA22El0KOzwoZhit/3nKr/MciaYmroC7//9hRiry6l9j8X3/8LHCvktlP7RPSa/o4eUsCh9GGRr3GEZdhhPTopXd+92oPaxtMPvEao8CYUkGM4iJpsNnu0G41sa8ho20GBRqNJWjeuRbaaLTOIkaPebrAGg1jCEp3rq3IotwbImUtxN1SCh4fH/Hv//2/xw8//ICnpyfc3Nzg9vaWJWAt9vsD7u/vYQwhbM61SDHi+fmRvNWZI9IyCiUI6Jq7st7zXu5Ja3RkXaCse+vr9kQWngcW3ZGSC5QuNUfNhTX4OclMIvCeqXiZh4HH0OgaQCmkUhBiqqNfJJ+aAUX98dv7OzijoAohUmQThAX6B6es3BJTxtRKgCD/RC6XJlKwzoBPgE4FNhUiqCqNcRwQIovGhIB3P3yP0/Mzfv/bv0f0M1RJ6LsOr958gbZrsdl0zOei+XmgYLftqC0mcrqFksrhciGtjhBpf2eXONLSp6NtaR/fbDY/G73+pePTzVmenl9UWz9331kTVShL1vzCqLqnijfCmFiDMi0qA+coWEbWQPc+QOuETd+jsY424pSQLM0DK4BY3Y2uN7TR5L+c2JKUiCLU8y48PlYA7He7ChlN04TzfKoVneU+uOMMa7vbrAK6zGiTjCjNtyY0DWXDkhTIedhtSR5X8UKPwVdZUGoTlBrIZavVxlCVJSPuWkZKOAsmyzNydNKKtLJ5BMqChBcSMhFQ5pE6M3x3Ka0qQ16V+pAorCWAF0G4cC8WkOuNq82zuiFV9jgFfmOWDF9Y8mt0oIYTxTeh4veVl0JRG+olER9l3R/lc6VQWfeW7SRj8CjZYr+nKjvFAGUtur5HKRmnE5Fq5uCl40mEF6VJvnamTTXGhMfnZwzjwC0gzWJFBqZkmk/uOljjUAD8+OMPeD4+I8XIiY9BShmTn6BQyMudr1FMBSUnan2wTGtGqQiQEl3wROYPXdciRfJe9qxVoECPYS1tFn6eaQ0lhtyREEQwxGg0luxAocjwwhhNFXzBCo6mXqwwwxd0SsGxshpfVF4nWCEoS7CnpbYO/DITvkIAlFRjrO7F11YU+bQiD4WlzKKHzOwwt7SFcPWZRl0X3QMVVeXSyO+0bUsSvgwHLy5kFj4GfPvtn/E2Zdy//oI5FA2NMxWNouk8hEhIg206QCmEVFBSwlQSUqSZczjiX0jlKUFU0MM1FC7n+3w+48OHDxVSP5/PmOcZr169qrC4cw3atuPRW8stE+LCyAAZPd5Sxcv5o+AsUtSUyApBd/FdX7gxyyGoGl3P5bFQA7sQaumSUbkslW9OCTEvjm7giaF5Bh4fn3B+fsC7779HmifE+YIwj4h+omJDcctbKWhLAT0XhVgUKyfyylSAyDRRta6QMhBihkKC0hEwCsk2dM7YkphMkxRQFFLwiCEhJPp4enrENA64XM4I3mMeLgh+xn7To3QNNDKZ5hgNEp4JcFbD2Y4VKSnxVpqSbQBoLO2rRtGkRYoJWhMXwvBUwsvk1M/j1f3zl45PDujvuR94PZp0nfFdH6r+ft9voJRispJGCFTF7vf7WmVrLWSRic1QSMhmzxDTOI7MlJTFtmiEy6J1ZpGHjaXg/v6emO0sXnC5XND3Pe5fvaqGK8fnZzy8/1Az4cY6rtT2aBqHftPWLGkd7LquwziOGIYB2+0WXdcxuSrgdKJez5btDKvp/UA/z6wCRmSmQn03vhmcMbw9UtZpLEtPQuAr2piNJe/mogHjDIy1cLpAJ5YXTRHTPEMBcIrMahrnKKCzwEJJC0qS8gLLG6NgjPSulw33+t+5viLp58kNLX7N64RPKenbof4u+BEIgl4Ik0opQh74oBl/lnksS0An9r1B2zpEQ6Ic1lpsN2+glMLlcoHRCl3XYhhGPD8fqzLf7c0B201f108MET4L+zjieL7UaQZjZOMzMNZht9vyxIZBCBFPTw/46aefiHmuqI8mIhNa65rYIRN8XnIi33dt2LRFVXKb1mQelDMlja5taKwmRhxPR5zPAVrRxINzhFJM0wjvJyAGOje80aQUSWyk71BURlaK1oB1gFRb3BYSMmBOmVngvhIOtTawEoQLcRGuG+UviXVrZvT1nrCsB2b3r+BaEutIUNDwPtDa52AshNC40jKoMHmRiSjxifAVDk4515ZaShl9v0GTiYsQc4bSdM1gHOZ5xj/8w28BZfF3//q/JZSn3yAV0vaGbQBlME6EwHQ9eaXPxxP1iAtVlWGaoNChbVxFN7Q2sHbh2wgBTWSB53nG8/MzfvzxR/ZCyHh+fob3Hr/5zW/qvkPM9g3ftwyT81y4nOqUMrROiJHhZihoLTwY2leE3yN7uQh2LQJfy2ivFDvrPb4UVJEZEl/RNKkhBGbG3HOiaxYTQegGIHjZNRgL8NO793h8/yP+/Ps/UEKaPFLwKCliu+3RtW2dLW9YjjeCEioiLi7jqnWtKXZTz0SUVhnQKtLYipEFQ6x7HSOK0tAwNDY4BwzjhHGemcfwjMeH94jBo28bNNbi/mbHNrRY7YWk7d53HfquxXa3QdMsrp6XyxkAsO17AEDXOh65xBXBUQI6cc5GYvUPl58h2L90/FU99DV8KnDmS2hm/SE3qpiwSP9bfl8Wj8Dm8r11n9kHXxeOwLzyM4GK5G/le9KfGoYBMmom7HbpocuY2ziO1XHocDjgcDiw2xFVVa6x9f0ScuBri0Bgd3lsSW5klO36BqDqoFZiL5AOscO0SsaB6ENsGMM8IZUMnyLNauYMbS2UJTjJFFFmSyy0wQ8AhcSZtVaKdNxFMYkFDjKjG9Rruu6h5rzMk9cKuYC0k7m6pg11cWiT9ygkuVitZHP9uTE8lx01clEIkaDImD2U0mgUjS2WQtntNHkilbAbGkHWEfpMojTSapG+qYgQQZE/vJ9JQCb6gHmckLYbup4z+QqEuG4DFbSuARrw7KomExZtKLs2Gs5ZjCMZ3Eys6nU+ErR7e7sHFNA4g02/wf2r14CY1eQIZJJ2zSnhdD4jxoi+72Cdw3a7JejN8NysMfDzzCp4VNE2TLSJIcArwGpCRQxXR7KJ51Jo7cRE8pZKY/SBqqVVdasUOYBJP1IZSlwUV2PiBCjVtID2Wl33Y+s+kOIinkF9BHxqhbE+rur8igYA6175x6B3Ah+klyvIlgjsSItQVO1LtWuFomTo+XjE7//wB9zev8bdqzcIZHuOORbEVDDMpD4GZZFzwTCSL3vlvpeEtKdN3xoLayyxpJVC8AExREKlMjmk0ZQE7R+vX72uqnLSjvm7v/s7/Kt/9a/QuIYmb4oERQ1nLOwX5JU+jxekEKrLJHEFbA3YVexqRfIVQvI6oX7Zc1/3z9eoGxVhgDaUDBL7n8bFhD8krTKtLVXCiUxzQkpIpaDte7i2A7QlxEwzopkitG1Ib10RGhkykBTh41onslvVQGNp76G+tSAgvG9pSwicItJtmGb4NOHdn3+Edh22d2+RoBGKxjCOOF0ooQ+JeudOK7y5uwNQ0BjSh2iYxEyVOd8zeumdN9YS1ZNH9lTOMIzukuUqKXAKqiSiR4rNl1ShBHC76dC1DfquwVqM6y8df3VAF4ONTvxz9TKPLtnmmkghQRDAz3627qWv5x7rDVwKYqDKTBaTzJKv+/brPs/6dy6Xy1WAl166OF+N43hVde92O9ze3qDvW1h3PTPdNE0l2CmlahJijKmvQc6JkN/WyU4lXn1kLhQgpx2UDFv7p2CYPiCkiPM4IOaEOUUyATGGWJkKQCTyxjoZ4t0KMsyBpBEKka4SIo12rKwCDQgBpWC+QGzCS6BrxlpgdW2pGhAUW68uOv+opLMQFljRGGJkW8Xn12jorGg0JScgcUvDcmAqoBHBmdANWkt07sZ5QilEcFNKYbvdwFrpLzocDoeqwx89sWZjCPBsAUxr0CPFhGme6KbhlkrjOmhjYMW6UC2tHalcYyS52Xmm8aKffvqJ1x/QOIembbHfbfH1l18gJ+rXNZakfMlNcIZz1KrZbonRen9/D+scXCvaCOQ7fzodEcMMP4+1OojBUzVuDUox0M5C8EeCHEllK8RI5AOjMPkAH1Ld8IwhoDLlQm1GZgoLZ4Ug+MJWjzxyVBPSxfiGb9AahJQ0/T8lkP/SXvXRYL3sDz//dfkeLd6FkCWJyQI9U++XX6/i4K8yUAjq/sdv/4yQC1zbY44FIWacLhNmHzHMHiFleE8qlz4SwmaNgjMarSMTnbZtsd1s0DiNbKiVEkJgIRPaswITOgX6vr+7Q0xEArPsLfCb3/wGv/71r+Fcg+Dj1V5otMF+v4efRjyVjLEUpHG46omvfTOE7LuG2td7FICrgL4kQMseLAm7YQnmpjUoDK/HRB8KTECrbUqzug6FRWUA13WwTYsCQ4Gf9+NiDKEz2tC6UpSgImUi+SIDyZN3QWvQKg0DGg22TcvFhUIqNF4YIvXmZz/jPM744x++hXYtbi4eGRqhKDyfznh6PtV1c3d7i77vsNsdSB+CZZmj9+SHbnQ9h9ICFLKu5ntBCjXD7StJNjSjkkYvaKW0K6Sl7EzLP+k/ut4/dnxyQF8T22IkL+yXDMl1db5eBMsLVqsTcN1TE9KFQPnyO3MiQ4KXz3XVy109jnw2xlQiX0o0m/zu3bsalCXw9H1fx65SSvjppx8BAPvDjuebDRNS9nwjzJxdtdAaFdpMKQBoYYzGdrvh4KU54ERuK1C1GcIiS7tAXMSkLJqUiYwmnWGlNXS+7knbxsG1LWzbwjZEJoMiERpR5UPhGc9CWSIKSDuZdzbFP+cingIXDPXiGEqSfa5+KOo1yfWiMaNSzXWaRjT7JZFZWP4As7A1AOraQ0EhpoCQAprWAYozfU5qKGAYbJzFdrdBjDT/L73kygHI3IbQMpJFxJd5HCvUV3JCyRnbTY+msdAFuBzPmCdO8gLxK1zTkDBHT0JE3XZTq4+cCwc0YPZzJU7+5m9+jdubA756+wWM0fj666/Qtg02XY/94YAvv/wKOUbu8Wc+6XSPXC7kqW5YUldaGNM80cZfCqwGutbisN8ixTuqgNmOEaCkJCeFlHikVHGiiZYDcUFpWmht4GMm0pz0jrPmBNXT31najIw21Vu9QHHvXyp0Vn40rJevWVpVKUAJumCg1DLl8MuHevF1xU1rMF4QO0GDlv7tet9ZfkYSy4Qs5Cp3nFh+OeaMlLhqVwVFEXRLlWDCh/fv8fh8xjh6aO24d67xdLyQF7qmNsA0ezYhIcJqyACyhdPkivisKZH0nefdmng0OTMPBqQuCDi0fYOHDw7jeCHyXIzY7/Zo+p74P9OM9z+9I5+BtoGxFvsNkT/t1qBxDV69eo1pGtA2NL0jKKQUMTIiLKilFCqyn6/30PU+K3DvWoxm4QOQ6RARvAJyTAieUKGYSNQo54LsPQljzWxW4i+kqKYMYi44DRda54xCIWfEEqD8Mp4bWdBJRsT22xZFa8xZIYaEOc9Q5wlAQQqBkI9IvKIpEakxwiIrg7brAdNgnkZo28A1Pe5viYRI+3lmxAvQJUHlAmc170db5sCAtUTI1lZLqwFl2SsKJTddQ7oEVi9TRVqJQqSSAMYFFa13nxJLOaefxbpfOv4q6df1DbSGyZfxievqev3vNcS8EDAW0RX5PVk4L0kj62D9TwVz+RCYXHrbZ4Y3U0o1kLdti+12Wyvt8/lI702VOkdIPfN2BclS5SLQU0pLf1hruklLsfW1SkZGC2Vh48vjyOhWSpFnOQlykUp0uceEmW7qzWm591kARG2oqgYzh4khg1TIhCIzMYV0hBfXrOXaLeKvEtSlX10qLernm/Nyo+t6TuT7dTRPK+iiXqwP6t2nTDrwaz4EyfkWaKPq2Fi1MR1GYFzeo5CsxPgEXAGI+5vMwOZMfee2bTANE+aRkJrImxG4kjDa1I1LTFmUXlwFC1i3n6/t/f0dNn2H28Me1lh89dVXaJsG280G2+0Or5mzEb2vJiGusTBaY57JnpXc5VKt3GOYKeXhjSQ5i03fIYYtV3VkNUnriFm+cXXeS4EOBiioAdoax7A5YE3hDYjQFTEesmDHPYYTNZtyJDHlkA8UQlA0q9mxpCZx3TRQaMPjVuov1+nlZUBffS7XipDroP5LULss+yXQc1DPgujxlEMqKEUhAShqYTZDA2HyGKYn7PY3ePX6LWzTQVuHYaCAblsiyKYYUAAYQwltyQVFk3tg8IFafkoBGbDMdI6BkjHwvtc4lvXUCtaQIYcPnqWHd3CspxFDxCVeoLVG12/gGoeGnzfnDGs02s2GCoGc6oSPIKeCKq7VLCUor4svSb4XMt31OPJ6pE38CKzWld8iNqAxUFDPmWSIMyfWPgaUGJCYOV6URioFo/cEaSsLxUThKPrF7EtAXhgUMonfRAZKZJhSoAOPogaPaRyJyMY+Gh6G/Ox1A9f2uP/yBtAWMUVoY+GMhms7uK6romBhnpBihOFGguX33LqG97SlRVGr7pTZVjdWwyWFRTpd1zhFOhtZXSdRALVZ5TzmnOtkxKccnxzQBcb2vCkJjC6kCZFWlZlzAFeN/PWCkBnx9Rz6OiADsqGvoPe4eJ2vk4OX9qjrjPKlY5qYhggxRdj33ns8Pj7ifD5jmkaUkmk8ydma8Ysla9/3NfjLDKncGHJ+1idfXqv04YV1u2a3UuCjfmfyHgpAk5ZAnUqB5lGVHDLGNGGcZpanBLN7yerVsq6xUgqOkwKtLLLOyEbRzLqh62BY1UprgyLENIARy49Bm0vvcl26izPbWsqXep70upQmNjkZznD26WfkOSOlAKUynKPKXgLnPNNinuYRxljMfkJKBSnmqu7WNi2xQw1VHdL/nuaRxk34xrxcLphnj2EY0TYtEW2KglEaHc+Fdh0p7mluCVB7JsAHXwV9lKI+FzFSidDYOIuvvvgCANB3JNxDPTBFM+Ja4XJ8XpJZrWCcRSetq6YFSoG2pAznDweE6HF7s+ckivgFwc/46d07fPjwgRMVUqfLeWlzyfWQtXW5XGjsJwRYQ+ti22/Qti122w2NvnU9y2YS+Y/UDpmQx31JP3tS2TPUSrEC1wuMAqp2Y6DxIwJmaFMymqSD/1f10Eth4tDPHR3XQWb9vZQyciIxkJgzB3OWEmY+QcpUqecCJO75FpWpraISic/khMv5hPc//Yibu1fY7g+kXJYjSY26Bvd3tzDWoesWPga1uRT8NGE4XhCngIu7YLvboG0aSBZtDCkOlJRqQTAPAy6nE9271uLV7R3+5td/g91mB1WoUDDaUhWcCs75jNEOGM4XNM5iu+2YBEqKc/f391dcH9n71m3SYRhQyoKyvSzMZB8tpdSgJDPu1lpoVRBCREwcBGNi4Sv5ms5/DpG9ygNKikBhKSVtEIvCMHtES4gf9RtXZl/cd07cIkwoGIYRj6cjtAKco1FPoxRyDMiJeAo5JhhHpOLdzQ2atkN/cw/bdOj2d4AySMrCNS267Z4JyA7BUwFo9htopbDpSNWtiKWx0jXQUtaZoJSBBnPKlKHXkpeiT0aZ17od68J0XYguiptpdZ9fo92/dHxyQF9X4euMbp2xrSvr9U0pn5dKexEqWAfkdS/tWrGsXAVAxdXYy6r8Y1C8TLlqpdC1HbShoGyNZY9hkuacQeIMIXooxWNUXEVKQCeSHFX94s0uC3x9k8jrenku1smLsHqNMSxjS+8/JdIvlplsEZPRxsAUQGveoEJEzDymxsQ2YrHTjULMUH7/DFlBlwrFG0NCBpbJXj7RrGf12X5x/ZYLtL7Zl38rJWgKJ1+QKm498qbqta3MenDvlqt4pWqM4JvGI4poTSInMRIbCiSla7FaC/SckQluKKrqZs8zfVaFbnxnXDXQAACr+K/5XKUYGcbO1Oe3VGFpQ4TCrNktTCkSmDEWd3c3UEphuhDsZ4wmf/MQYI2hMTWloCCsVib8oMBYgm01CMpOedFXoFncht7HNCElag/N3lVCVVnB+Ik3G4JuEy7jCMXZXzxkbCLJjcbUAErDZVZrLAqG++8iY6qNpZEfrmA1j1EaLXfWek6Z2wllhabxYy3ozqdVGrLefrka/9gHt/p+Vslz3zYv93POFNCzrBrFyaxOYDNIhOhxuVyw3R+40qJ3oxVgjeb2TYvNdo+cC+ZxpOdIBSUmjGlkDlBB17bIhtcSw+3C8i+FuTKePpwjTfK+63E4HNA4R3uCouQoRjIToTFZro6TpZEpZ9Gtqu914gNI/3u5B6mo0jWg0zkvLEWtK3kLQIXajbFY22fLBIEggHIt5B6nJCutfgZuz1BfO/I8NoqGM4AE9MS/b1CIKLdS9iPXtRFaA42zsEqRymKKKJmnoXKGbgy0dej6Dbp+g/3tDVzTodkciCwHwwF9C83FjbcKMRC5zRiNXd/CaIXgJ0JhMs2So4jTKEk6KywFqWZCkkhNSwuZkG1aYFftDazwqVVwp32x5oH/5PHJAf34fJLLDQBoGxonMOJtbTQU9JUkoxhLGGNRFFVXuRRauMFjGieCjhtSUyqFgmqKieQ4uY8BgOcFX+B3TF0VCEtOKg+DIXjKmBMjAfv9Ds4SkzgxpDFGWhiuaWCtwWbTU18r8+v0lLicjkdmwt+QQf04kMa8Vnj79i1ub25xPp8rcgGgwrViCECJCFXFMAAcvWfRf7fGVcg/5AyjFFpL9qK7wy25EWViZHsfKPPN4su+VMhWkf69gSFyimwedTMt0EXGhlARkJgTVSq0rOSU1uPnrdAloNPlELEJgsbW6Ij8XpZZc/ahbtsOmgPYNIX6N9YR0SaOAeNpxNPTkftSYsPbwux2FWUBgP1+i1KA45F0Bbb3u9pqAYiBqjRtZkbOkThScd8/JCLniUhPzrQJW0fJjySBiaVnG+fw+v41msYS5G4tfE9rwGpN6/wyLPAmxzytNVQBxoE8rkOiVpCfqO9P1rak1YBCG3hjNe5u9mwasVRSkkTaZpmgGMcJH95/wNPTE3788Se8f/eI9++eME4Jm82A738kmRRqKzT41ddfoe87HA43NNtvFLUN+p5aSdbR9zlpL0BNnMI8gdpqBUZb9G0L6xy6vkGYPfw4LTdtXYJStf9y5VGKjKOxvGpaCLS0v6DuMym9+Lla2ny0dvlrJmkpVdjEj9sEILZ74XWycS1KSnh4/x7396/QOIO+baCVQgozQslo3Sv0XYPDbotSCiZjYLRF61qczxfs+l1NUGVfqQIjCiighDV4j8fHB5yOTwh+wnazwRdv3uLN6zd4ff8KpQB+9mhMQ0YxbNqhtYWzFvvdDkqRhkdKEdM8skGLW4nLSCFB425a0STDpt/Wa0NjjJHnxokfgrKMJkvhIsGJ2oXkLica7SgS+DNMJsc0lAIe9YZ1DbQrcKrBuWT8+P49fvzwAR+enuEMcG7JtrSUBMkPXeugjUHTdDTTzXtef/sKVpOhirMKnTU0WaBp/Rqj0XcdXOOwP9xT4N4f0G+2+Po3/xIFGpcxkIMeq7K1bUMtrRBgFJGOd9sOzogaY8E8B+JkvX+PYRjw9PRUeVov286Wk4L1iDdxjzQr0q1QTVBiqS2vI773pND5lOOTA7pUpAvD8YUDWkG1pvxY71ytMhKp5GSWVPqgS/W+zJQK40/+XvoWH+vbA0vQpG9iSQI4cK7nKbNaqWNJVsr/iTWn4h5iYBKWQJjTONXqk/pipbKw5X0DXKXbpecECOGL3pXRywxisomEcGjHZ0aGrqzjAkAL+ceQdGDWlAgorTFjRk4ZVtMNJ5Kg0sfk5iJbFWZ+7wmKq7qccw3odG4/thLWK2uBeEut1K7lIOV602PK95dEgBS9NFIgln8pSz+8jnbkhHme2GqRZvMdFo335XxT0kIiDqq+ngX6quyCBfXhUaWSKaMunDRUS0dGEbICEqMIVE15EpAhFwfW4qey0FrD0CslnDlG5BhrgkkztBRIzpczMe95IsBPxEKeA83UUwZUuG9PXAujzGpzWM6vBHRp4bRdj7abWIaURJaUJkkdHyIbFBU4FzDNHsY6LF0/RTB6oo29FM1a8NfrV+7XpfIqtW0j43PXwfzToff6uDLvnMvVNZcl9rEqXpbq9RJ+8dxKPqmr9r18GUNASgPSyh5XKYU5MIoGer/EMyBDD6NJQa5rE+KG/cFRajtSaUHqaB0k3oMKj3gqReI/m76vDmoxUnWbUqpyoQUFYSblx7b1dG9BWi8Z0Vo4l+r+vLQfJbFf3vBVpcj78jXEq64+SJxGOAm0rus+nBcZXbrkpXIaAOJXKIgSpsbMBNdUCnQBj1RSD10CusoFRhcU3gsLFGAMbENOnIZFXIzTaKxFYw3axsI5Qz4azmGz28FaKh5t08C5BrkAWqdK6HSOpwGMRnYWSAEoGZallmn/Jv9yY0wlEs48NbO2t12roJaCOoHUMOdJa5rgKcrWParqcyhuZTsqNlxjrq7RXzr+KnOWtdJR13X15pFAJpmzjC/J7ONLH3TpG68Vk6Svve5NZyFw8c/XYxbrcTfZnOV5ZXxMfj7Pcz3JADCOY93g179bSmGRjhld3wBomOBGMO86gZHnXMvciqMXsMDrks3+0gWRzE2mCJS5JTa99FgUEXcmHneJPsCHQHKJiq6+aqnntuvIwIVmxEHBpGTEHElyNFKAipE3GmaHFwUoJ/B+udr3XpIR5W2sSTPDcKnJ3NXmwJvZNI0QKK/+XFGg0sZxNW5JjatI0idkQj4/LMRQCk0WWKsx+xE5RQpUyiDRwD05p6WEx6cPSDGzvSuWgF4oQQ0lwIB0BWoCpRYUSisFxSMpil4UUghQwBUhyCig5Ih3P/0EZwwOuz1yijifThjOFzx8+IDT8Yin52c466gXbTVX0uIZAFBylFDYT71xDpsNqw2qUkVxdoc9ur5H0zaUyM0zjS0mmm+WgB5CBJTG/nCAa3u8fvsFzchqjYeHDzRDP46ANrBtj267w9svvyTBJqVqz3Oe6Pe6lgwn+q4j5znXkMRsYTWwQATDyzjAzBrjMNK4zot18anHy/54zosK47pCry2ctPo5r+OcC1IBjS8tuX2Fm/TKJU2sPIMPOJ8H+psM/O3f/i00Ct68uoOxFj+9e6T73nsEpTHaE3IqGIcZbdOjMy1a69Dc3C57ZJyQQqCqDEDXk8Z31zTQCtjv9rjZ7XG7P+D+9hZv3rxC6xz8NEMC6TQMmJXGdrNFzgXfffcTck5oGro/tocttKalLH3u7XaLtm0Jum+aq/0uxojz+VzZ7jLOttYGkWRAZtilXVhKRo7E5ZhnGg/WRgGKWOQhZma5LyPJKAXZ8FpglcvZexSlcLi9gVIFVheUkkCdcjqMa2Csw+HuDtpYhBiglEHfstgXiGMEq+G6BpuuwX6/w6brsGG/BSi6ziEDl2HC3//2twgh4fl4QdO22O4PePXqFd68eQuSEco4PjxgHgcybtHAbr9H27a4vX+Drmnw+vVr3KWEL7/8shZscr1PpxPGccT79+8xjiOOz0eUUnC4OYCsb+n6NNZW2D7GUFGvnDObLi2x71OOTw7o69npdYB6SQCT311/rB9DbtJ1QH/5uBKcFcgdR2ZdhXW87uGv5yPl+aR6Wff516SOj73uJUhThktzmpS1yaax1qlf9/alTyuEwTV6sSbuvSQArp9bMxGp8FiL9I9KAZSiPjlZ+EXyRi9CNFPUC69ELd6gpILhJqGCWvV1QBWoLjV4fcohfeqr168ZtSnX66L24up5fsFt0NQYIiQkVs3xXBYSpHij0+RAU6sHzSNkIZB1beNozFo2HJExTWz60HcdMs9Tl8QtmrKgSgpqkaWU6M0QIVbrIpcCpdjYhhYREfdGYsMiZ7oOUMgpYeAAPHPgnMYR0UYYQ6M4BcA4iTsgzc0aS+tTc78jRoZAmXS0rJ+FdS7BzM8zj1GBERNwy8DA2oLSkoyrMKXJFIJmiV3Tomk7bLY7gjCNgfcThssZwzjj/U/v0fct2ob0GpqmQdc4yEQDoUhCrOLq/JNi+LoV9PPjZUX+l/69/n1q/xDBLdbEm9TmUr2/BPDXq+tO5zJ4j1wUiR55Dz/POBxu0PU9+u6C2StK8GJECh450UiahmZ9C0oQCFnImP2MmAIKB3SlEvfTSRa6cQ7bzQavX7/Gzc0NKfyB24Z091aRIwkeVFRltK3llpCtAR1YRL1kT5L1syblCvK6LlBkPck9L3uy3F+iDJmjR06L77y2dE8XXeq4WkVV6vVEvc9pjJCep+17KGQYRcIzopSpOKnWxsK1LYy1KJ7OrW1aRn+pPUnjkjS7Xpg3EXMG2Pa2FMAnSvD8eURMBbOPhHzaEZfzGW3TwBnqxxPSVwg5zKL7QEk4AEK5eC3JOVofmu8J52IlldfJg0SppFELUW59nhSkaI1VM+BTjr9KWGYNuUuWLC98zZJcq8kppWrVKsEYwBVpI+dcx7AkcGpNhCI/TVD8/BLQXy7G9WOsVezk51L9Amu9+Vyz0XUlACbinE9nzLOrFbooxC3WhUuQ/8BuWzJecHd3h7Ztq3KZGDF8bPORYG6chUXB+YF8kPNqw+K7gM5vKdT/Ugada9Fy1m2tXVASvpFS4uDDusemWUYPU8l108ulIIHtYNXSr1mqc/ng5sfq+1Ak6LKebhBy1tJaWRMcF1geqsDHCVNI0BSDEUKC6FjnlJECrYW7uzta4DHDe1LDGuMIFODm5g5to5DSDGst7u7uUHLB6fmIruvw+vVrTNOM0+lMFoUhEs8AmgP1omxYhIRoDRMEZX2xwlYpaBuyayU52oLvv/sOOSVM4wBnLb754ksAgJ9G8m8eJxKjACVSCakmf6fTCTlnHA7EB9jfHLjfibpGh8sFj8+PuL+/x+vXr2Eb6suBe9laA0iFDDpCwMAbDnFbLKxr6ugPNI1Evnr1GlCkf6+Vwu3dHW5vbvDlV1+j7zps+hbPT4/49s9/xnff/4T/+//t/4HtxqHvLF6/eoXdbosv3rzGZtPj7u6uogmVJMsbYY4RJSxuh3/5uM4A1vflkkDjqnf+syp+hRoOfqpKi9RfzjxKxRK8RfEMOkvuKqow5zlguAzQmgLJ+XjEw7t3+Pqrr3B/e4MYIqZpxjR7BB8xD9Tnn4cJUxlwfDzDaEvtM97AQ5yRUoD4GlhHiZQYSe22W3zz9Tf4P/0f/6e6z4aQ8Pz0BBlEdY6g4vZNi77f4M2rL2CdxW7fI6aI83gCUKA1jepO01T14I/MAfryyy9XdscktrXey9dJtxyyfy/IiIy/elDAizSWqgEoi6IsMlfEEuNkz0iZRHVKjBinGcM0oSiFu9evUXIEckBhUpzmWJNApLj9zYHEZi4jtDbYbG6kQQpVCgwyilbwCTgNE6Z5hj5JS5ih7wKElPB4vMC5Fnf3r6idygn3j99/h/22x6ZrcX9zwH67gdO0nr33mMIFx+OJDGSymI0t6ntCrJPiUfg+fd8jxIin4zNCivBpIVXL/rpmvhUUTPMMoNT7+VOOv9oPfZ3lravPNbQswWue53pz1b7BatHI74lE4fr71lpkrYDsKtGiVgNqGQVblOMyj2AtFYy8JoLqyvWCLGuWfgH5Ty8nN6YIhMXwQbLTcXVyq4SpXlzepCpfv5d1Vb5GFwQ1UEpVElnNwNnmUzLcFGPd7jTPrL7UsjcMKSfk6nBEWZ/wDpbzr9h1jCr4hFI0uSapNVuTg/sqoEsQZ7QfVEhmEHmJTFoSV9bUW0d9TvFIT4lmz3NJSAj0vJrA0BB4w400zUD6zeQbTC0Y8jf3PuByusDPAWH2zH/QCJpmPXMuGM4XxBix2Wzo8ZQi9b0YAZUJbmUyZm3vFukL806UGZWQa1m4bRFK9a2/nM/cbw1I1uJ0oo1VyDV+mpFzgbOONKYLTTFYBbSsb+CaBtY5Ri5UTa5EtnOz2WC325EbXGYvbEYRNpstupzRuBY+BJwuZ6rqI0Hu2ligKGiYSgKU+eexEFdgGAY45xBCRN8r7HZ7xBCx3W5xf/8Kv/rV10CJQEmY2NI4+IymafH0fEbbNrg97GsfUshJNBSGupYkXkivvihV2yzCiC/yfYg8q2L+q7idydeoP68f3EkKKWGePYvIZHYQpPG1lPMKfs+EVLB5DRi1IjMmA6UNQvA4HZ9pwoDvQ6XACBCQHfW4CVYGVZiSaPA9oRTgmCBFrYCAWDL87LmFs8N2u8VXX35Zk3khT8mapP3BVMXJtm1geKTLOYsbt+d7klQrvfdo27a2Sw1PaIQQCFlICfM00e4nSOkKMV3vV/X9MMNcEEClwGOJoO8tXXPeoxU0tBAdUBJ/5j1YKcBah+1uR/rq2dek31girvpEUxZd38MYCx9zXTO0FzawGnCa8EkDQJVIiToLbWlFrHxjySJ102W4pkXfdeTIphRyivAxYLbURhvHASVFGND7JWXTginSvlaq7vqCkulSoLVIHhvZVCDtR6M1JZbMO0jMURE5advYOjqaMz1vzP8VhGWenp7qBZZALqIsfd9fyZqKkMuFLeLWffU1kQ2gICD2qFLBK6XgGgvAojG2EkvkUArcX7XcU5efC5GLfrfrOpCdp0cpYutJQYVuEFE108hZZi1pcT4+PbD2u6/JiVTgbdtW2HGNTLx58wZ93+P5+bkyjyXxWCczy/ge6vea3CLGiOand5jngKZjC1bOAiuDMmdYxxaJrmFHJ8qenSXii2dJXcWPTVXctY955D69SiT7WWR+B+VF8F4q8WWsbFWhYxFZGacJMQWMLD0pa8U5RzAbaCGH2WPyE3zwcA0RWvxKS10pVUV/Djvq/W36LW0UhXrkIUR8G79FmJ4wXM4QWLIU4Ifvf+ANtmC73SLnzPPnPY95TQgZ1Cbg6kduaoC5BHKNhBUNrkA0Oa+FlGor6MOHd5inCZu2Q7AWPzFcmXliI3iP7XaL3W4P72mUrO1oSqTpWgCLzj+0YlnQBMMcD9c4bPdbvH79Gvf393h6eiIDj5IBrXD36lW1y4wx4vHpqdq2hhjhQ0TnFAtw0UYslozBB0xhwo8//IBxGHA6nQj6ffUGzjrM04T//b8teH1/ix9//BGPj4/44x9/j6fHdzg+f4eUCrZboO8bfP31W+y2W3z1xRfoOpp179sG265DnbPgZZ955I8xMf6eWT5IaJO7mYUmPJARM3+viB699MdJ5jOBPqYQ8Xy6sKBModHHnBEjJTCpJnGaAzqPYWmDrt/g1at73k8U5nHE9999i+PTv8bN4QYlkXKYH0eUAnRMsCos8KOQeVZ8CU673RZt17AyHPDw8J4mepgMKmz1X//qV2zfGrHfH7DfH+pkxDiK+dOF96EFAe03Hb58+yWtXb3sM2v/CiLzjpiGoULx3nsYa7FjcS0p1tb9YEH+oiTi0spUYiwiyF/kpIpHUY0ivggndigFwRdqT8QIIDFK0eHm0KPkgFzPGbdIjaG2VCm4vb2j/n9RiCxaozSp3rXOYts1MhaBeRzg/cR7U0bbOhhr0W920Fpjv1ewzmGz2yKljGn2mCMZrMwTgBSR/ASrNdI8QsSbMoA5FWhr0ffbK3EegKaxaH/HUhQAVebcWYOSE8bLgHmecb6cyDiraXBzc8CNPaBvGjRdgxzJDe7CRNlPOT45oG82ff26wsQcTGMMmCZS2VJa8ZsqcI7s7hTYKpIDwLpvq7Q4TalqDSrPAVDgpjgjkJB8udzQ4sAlwkIF0qfiOUajALXIkea8Zt8S9FuyPN9SOZeSqxkIsYRldMOwXCex0ong4DCOE7z3OJ3OtRK11mGa5iozS0YjMxNU2krgkir95uaGxD7YsUwWSO3he1qgJS/ZsOL+X8w0D5lRmBSU6zkmaUsW2kipVqRKsXOZUdBFr5ALIfUZGjVMy1w0kTci9X2Nrprt0zwi5QTL0H5MkYlltOkcz8clU1cZxpKJQ4qJNw26/tYYtLZFY1oYZWGVI+Zw12O329Zr19oWHw4PeHp8xjxTr7EUmlQQgg8KqWxpSL+SJXlBDVS5UXUmCFuv9O1fHjSHzh7ySsHP01W/kcYKM0F9jLJkFKoWY4QLHtY1aPoe1tEI02JYVKqjFOVxGSVlzD5UNT0i/Sl0HTm9ee+RS4YfZ5L19Vx1jRPC7DlYFFgOVsooJJFwjaQX3joHqxQaQz4NP37/PabLgBLJEc4ai81mi9vbe5xOF1wuI25u7mFNg+2Gkqauo0rM+4RjuiDGH9C1Dfb7LXabDQ67HdnHmkWhzCS282U7ZAAoOqFoIlUlKIJttRXHDiBT4pWSR8rA7MngZuaAI+eS5pozbNNXcy0n1WOm3UdmPAQpUOKuAeITLHPWlDzM84zT6YTj8xGb7Q7ONTidLgg+4HQ6c1LgkBK1g7TSUEpQNIe2caTvz/f17c0NmyLReReRJEocDZylFCiGUKtRuk8NurZd7WuAoWYOoahaUy9b9kue3HGWdN+dJmvfxjXVmVLx+KZiU5VYIsQMRCnFgisWWvhEeZEv1kqhtZYh+ECcBZGfToSGAIoCdc5Ike5JA5IgTiwEo6BgNFXrRBCL1WRKCpUcyBmt1RZNY6CU5b3CoHUWrXOkSAfA7rbYlg1CpOdt254Z8WRpGxOP+xbCdpzRUI2DVWSg4uxShMFa6LzSidAiprUUNcsHxZiUCOXTrKAoug1TJE+J1llK/FLLSZEhB0ZFvLEwF8SZ1rUgnp9yfHJAP9wcrqpKeuGcwQWP2c+1IpUMr2l/7sgm0MPSS9cwpmWYepGCVQzrKqMXKKfQJkw92FzHmMi6kMeMijDBAK3IrMJaw8L9LHNYEsS6Dlw7AkI6IGi4aRxXxjOz4fuKSlAbgf2xTYa1Ta3MyeCeNpanpyPIPrZH3/d4+/ZttUk8HA41CZjnuZrevHn9GtUpaNWuoJ5awHgZcD6fcTweuealham0Img3ZXJgAyU20IDiOfCCgpB8tRkldCPXTBsAJBEkC1VTez9hoJtOKUX9yeGCru/QtI6U2YLHZRxQANy9uoXSCtPEvuVOYx4n/PD+e7J/5Plt5yymy4QwB0wjj9w5C9MY9G6DxrWwcHC6QWs7vLl/g2+++QZdR4Ied4d7vHv3Dv/L//Kf8Pj4VNdXtLRZXfIFCkRqojG0xBuEQSLfOerv54ysDFRmUR6lKNiXUtn7ALHrW93UudLHx0diqQv0WgpKTgiDrwzjBJChjp+hrMH9dovb27sa2NayxAIryrWYxhHH47nO9seYUYpG32+x2Wyrv/twJkRETIGkGotTgDa07sna1SDpVMlSKSVs+h52s6nmQ3/47e+htcZv//4f8De//jX+3f/4P2C/O8Aah6enI47HM968+RJ3d1RZKpCs5TzP+NOf/oTjPOAf//wD2rbB/rDD7c0Br+/u0LY047tnpjAQuFLqYLm9BFNQjEPWBqFoCuiGVdyygcoaQEIsET5GnMYZ3pP4i+iVyzisaxp0mz3EplWba1KZHIIQUBWslqodUrUb+BARwoTHhwf0bY/7+1fo+h7HpxMuKePduw+w1uHu7h4peJyfj9w33aCxG2w2Hfqe0DxJ5Pa77RXfp7beEgnIaGuRU67jsYIeGa2x3fagfJTWOylCZpzPZxhLgllaceuJfRxaR4if3dK5FsRROEF1UiDSfVFUrDC9aMdrS54RieHyzAl7ZxsqYALpx8sYl3hc5JQwzRcyoAIRwXabFhoJMVAbI0Wg6xp0bVd79JIYbLdbWGsRJnKa6xkNJm4SBdW2IUGdpGkUcLPZMGJFe3Hb0n0le7P3JNsLfg+N1WhdB/RdTfUoRhcY3dYitJRSpzaED7G2ji4Mp6TokVforOXrGT0hrX3XoHEkpCOxsOHpkhQ8os+YBtpblP2vMLYmQXnNthNYdQ2jryHmKxW4v3Cs+zXXkDzN8BJsvBDWUMrq+cjlRhVN3uBFIDzuf+eyJARCohG4DuvkgpX/eVZaXvtaTGE991urAd7MRWI0hFAJfrLJrkkoAGp7QtzHRPyB4Gl7lQR1LZlq9H1PQjjbsY6ehBA5yx7osTSrzgmECWJzGyznk7J8qrwFGSmlsBGHQtJx1VbRVZ3KrPyr14TAlIjY0296+ETjix8+fEApGYGJH8ZZXC4XFGT4QOQgqynpO/QH7Po9HvMTgvfQygBFYbgMSCHDmQbz5PGcj9htd0gx8SZFlq/OugrnCklK4ELNCMdwuVxNPyjusZdSED23J/j7JJC0rMfEFTyUQoxkxCPqfjMnb5FlitemQzVf5x2nKFK4AvcpLQf0y8MD5nnG4XBA13V48+Y15mnCH/7wBwDA/rCnMUV2dHt4eKi699M0c3JF/tmNcxRgtQFMRuscvQaeJEgggiHNSlPgdMbCaEMqg1rjsNtDaVJVdNYihoQUKQHWrCxobaKAkhKggLbr4VyLt2+/ZP/mAYZ96rU2OF9G+Bgx+YCYgaYhso/SGiGi9gx9CBimGdZYQBvMnrypxfEt8rWXgBFSRlYatu1gXIZrOylMQRa0FqLmRyjVms9S+Han+z5LmxfgvgAFdK0NwKSnaZzoHveeELa2RU4ZXdvx+ohAAXpuF7Vtg65tWPiEqj5rdb0GVLRc/yfmRzRvzsJHnIzIXH/l1eTE3ILCBEoP6xyKYv1+pav8sQhz1T2ZkU1Cm3Tdr2JK9fHYH5ddzhKVSQo1oJNAk0bSBWEOGFhTQdqUQEbwE1IMmKYLUgwIYUbJGe9/9Difj3StjAjBLKYvJTcEngJoXENFoiJEWIRyGiu682CJYYWSFfIqnhDbfuFAvWTxg9tpSjKDFUdI1f9RNY5CL0imhSoBVAnDvdRYRbtwgVIGLNUPZTQ2PY3Qtm3DqFJT99LGGpqcYGXM6An5dLxnfMrxVwf0NWFCgu/LgP5y81wzuz92yGNcf01BOPKIxBrSkKP2ePHzN0tku+mKgPbyQ75Pn7kSKwtPYK2O9FIzXm4UIQuKLrIYvxDBKMBaW9nuAq2LFa0E/CrcrzXPKesqBCFJxeFwqLCi3Hyn0wnnM/Ws53nGbrer1qWSuEhmL4dYf74M6GIGE1fXVDaekvmzJEUyfpEpoO92WzhncTw9w/sZD48fyOWM1bq0MeR3DpK4nFKiCkhpvDq8xu3hDsN5REmlbnLDZUSOBdvNHjl5zNOM4XZEDAm5oUSNkg2qRlAIXqS1qkmEQq2gdz4EPZJDeluydtc/WxMYASBFR2YNvLZFNrhC7plhPNqX64cwzHMpNaAbfh3DOGIcR3z9zTe4ORzwxdsv8Pj4iKenZ3Rdhy+/fItxHHmteTw9PWHDFbUE9HHkdZ7Iq71pGsBYNK6po5Y5ReTMyaQ1AKNVVqow61AM9XEBVPlRGffKfL4Xf28hRSm0bQ+lFF5zABHiqNLAPE24jBTQrSNIVrQklFKIiZTPnHOUnE4e1mYoY3EZBjzy/G4p1Htd2OyZ0TgF6xaxDvlcqJW67FeKdtWlwGCORymyT6/2BgBlNXLK13aaJwzDQJ7kKaPlUcq27arcrlbUE26cQ9c1aBuB2y3dd8Kn0RK4FSfhtSNJiIKisVRrSMVQ1xaAjI0VlLgQzQonOqQ+pmG1QVG5uq6JZTAlo5pU63hsURuassmZrHarSArPii/3ASVBMlKbUkLRBTll+BBwPl/YmMXDGAWladJDvNpDDBiHM7yfcXx+QGAWd9Wb4PNtjSUxLgnolgI66e2TdrvA1HI57erarwsvmbRZB3R6P0tPek3mFmKgJOLrWCcxx76omK/iihSJYJEyJZwkQPHa0Eqh73vmdzVVphmM8CX+d6x9d4vV0/3F4/+vOfSXYyXyxl8y4NfObB8LpuvE4OooPKOcMpRefnd9ktcf6xMPLGo9Pw/ey+eX33v5fQm+wlynRGHxHS9lMTaQMTip3ueZxqhubm6q6IzAbHJD9H1fRwKvYZyyupFQR/moD0/vq2mamjyIatEyfrcI6axRFUkQmqapqEEpQorj6U++kbBKXKIPpKGcE4bLgMuZXMGso6y5aYgYZKxF3xLfYnvYogBE0isJudzQ2Ng8w1ki9GmlMTBkmnOu72e73aLretze3iAEEsAQoYbj8QjnHL7//kc8PT3h4eEBz8/PfM0oYZJA/nKmVpIouaZrURLguspek/TWGgqCsKzP7RrNkceRJG5pZyQcT0cS9gEhCo+PDwgh4B/+4R/QdR0eHx4wDAOOxyML8uQKYzbch00poWmaSlYSsmZ2FgbLfSdrFQCUox7pZgWvS2WwvlfkQ8aZ1sJJx+OxXqPNZlOJmnLOpG0k5znlCLPp0bVN9YqWvUE21nmeETXN2kpQFCKW9+HKwMlaDaX4HEvVfbVdLPdwzuSlUvcqrr6WwmEZPaUgtdqUeTTuSlUyZ5xPZ1jjMI5DdWvUxmCz3cDPAdM4QBmF1jXEWGbxIQVAlUr4WT7YnGXpV2sKhGskjfu+S0GhkBStHcjkjhYJX3dVeBljsNlsiLFfzwvroF8G8gZnWeRKClVLpWwMSR3Lumbphkq6Lfw+5mlEjhFt02Dk9TgMM0L0yGFGigGPj+8xTiMeH9+zjXCkfjQbGDVuEVuhHJjoquQrz+RjlikUzYblWuar+/BlQJcESNb5el+V++Ql8nzV+l3FFlnD6z1CEnkiIlPy/jJGifx1Xj2mZtfMukZzXhUli+ZK13VXhcZfOv6qgC6f1wF9/fX6hL5kVb+s0OXm+XgwL/X/BJsTxKcUfnaiP5ZoyLGuqj/2/OvX8TKgrzf4dUCXDR5Ybo4QQoXQZROUTWm9eKZpqoFUHktr/UIJ6NpFSsYEZdGQlWuHHVdSawWncRyvEAn5es2qX4vdrEfuchRb1dW5AYi0lpZRsxBpTCzMHuT0ZZhvwPKj2qJx5At/f3uPVDLOlwtdO0Mw9TiO6JqOKsiJNnMyg1iSjb7v0Xc9uq4HMNXzeTqd6nt4fHzA8/OxBntgWXtXs8mrKlvO7aJHXa6u93oNraG69Q21Rp/W62/dlvmZNDIWoY8UM6ZpBvm7E6v3hx9+IORFpIUnYuhS60gEjRpkXjO18l7Dh3zd1siYvGetLYy2dXpA1qusmXViLlMVa1dF4XOUUup0h6wxOTcvTYoQiQ1MyG25Cqj1PosRWQnisxLeWCUS8vgylirPIy5c6/tl+awq0ZUCOoTBBKAg54WzU0qprbZSCrK6Lh7K6tqJc1+MCZtNC6WI1FZywXApUAYcyE3tY6vlDVckSamFtEZiNiSOJE4UJCurqhrhuvJEod/JmlsDJaNIAfUiea+CXCtzEOHipER2vbnkyi8w1tY9yiq3Cu7kyEhQP3EnstYoiddwyjRqy+tkHEdM84gcPUoKeH5+xmW44P27d4gxoG0sGmdx2O15BNfWj2qCg0WS1VkSqlBQsO5aXCnn63W1Lr5e7gHrAm99yB65TghkjV7Hl2u10JcjyutD0MZlT6HqX9fHoust3BdoXQO6tHkB/NcJ6C+Pl4F8vWmuj49Vvi8r4/VNSV/XP6BqVQl08fMAvn4tL9GDdda2ft0vX9/HXpNkTiIKsw6UaxGcGGOtKmUTksppnondfj6fUQpJd0p1ZPnGqTaE9X3Ra5AKahgGWEvQp8wjS3CnKrZj+HXChw8f6gigtAXWG/VaQ2B5nbzgI814ez+jFNQ+rWssrLbYb8nOM5VURXOMNdBW00hQzNhv9jBW483r12iaBm++eAMfA95/eM8JQcTgRlhNVXzrWmxfb2CNxfPjM4u/kNDK5XLBOE5ECltVbuvz//T0XKUriVewmEiUsvQL12tGrpmc86YhAp1Um2vLXTnPa9KS1sxKbtuKcEiSt9vt6g0ur2HBW5oAAAkFSURBVANAfWx6PDJDOR7PmKYJb968grUW3333Hfw84x2/pl//+tdENLyc64SEtVT1oVy3CgQx6PqeYcgleTPGQoRJsOIGrAPgS3QNQOUhLASnBakQ62GymI1XCWyt6nm8qelabLquBnQ5RDraGlc3yQJgkzf1fLumhbtCr9hQRxKqajiyOCIuvBYNhaVaLUCFjwVylTZbLoWG4+QaKcXicby/8LmbpglKaW5xTej7DdnpMq/AWcskTILks6g7MmPbGoPkErQ2dX68UOSGShrKFRjXLBC8tLc4YatqhkVc3zSgCzLI/ElnEkry3mOKpEBY1wnvrXXdWxIC+s1vfkOPDR4hjgT1hhgxPT3TuWHGd7thoSweUz4cDpjHEe+++w7n8xkP799hmqgtMU0D/Dzh+ekDpvGCaRqQcoIzpLVeCpPRGgrWTePQWGJ6K1gO5tx+qMmz4QC53r+X4uUlSvuxvX0dL14e61i2fqx1UKd1k64e4yoRUAZ65Tao9HWclL+REeqUFtElzb4WayE0uRc/9no/dnxyQP8oJP4Jf7P+/EuP+fOgvvxOpYuon8PtL49fen0vT/zL1/CxgL7eyNfvQTZsmfk1q+xSnkOYy9K7lZtKYEwJJAu06CHCOSKeI4FHkoOXQUpuzjWse7lcalYuz7NepBLQ1/+OrMyWE/XHpSKjv10EfZx11BtekQsNj61dxgExRThLynpt11ZGs5CkSMrVI4UEbx2cJXhts92iazqgKLTjhGkc4RnmR4kY01SvlVRIEtDneSIinXAPrKWqhq+F5mzYMllMKZrRFyRgHfAlGLyE014GZ2BROZSgJ1X8mhsh10eShwp9gzYmOf/i8ETuS7G2ZbbbLabJ4HJZtLaNph5sXnlFy/NQ79G8uPlXGw0x9D663tf3h7yn9RyyJC0vxaPWG+fP4E3urxstPgVUBa/PIQAYvRDXACDDLq9DMVRe3801KqKNqVW/rPW6n0BDqWV7E0LXUqEtHABZG3IOSu15KnliKEViU7UFFTkhKGIkJBU0ETEjn9vIVRrxPMiSFIb7qpo80RVlGijcr1eMbRP8z0jbi2JFeu2q3qschPhaCJIme1FOhHK2HbVFDrt95fdcBRkshFcfAummS+KkUN0x14jB7D2G4YKnpydMjMDN0wjvJzw9kU5EKRFKAc22u0IcZc2KSJaINcEszpn1+tc1t44r5WqPW1fYL4vJ9WOsf+djv/exe2PZF5bkdo3eKkUiOmV5yVcEW6VQTZxoHS7Iwfp1rVG99Wv4lOOTA/oaevxYUJTPHwviLzeRX6rQlw1i9QLZCxgrF7CXn+WxXg7fSyD9GDy6/tuX1Yps0gBq1TEMQ9085TGkOpHRsnVvvW7CxlxV7NM04Xg8YrPZ0FgTV+ESYIRgJq9PMmp5TdM01fMm10JGUA6HQ/0+9bGGKiwh8JpcQ3nt0zgj+ACjiBTnZ5K4PdzcoHEO/VZ62hvwigTZNhKsrozCrt/R8yqNkgA/BaSY8f7HB+SckGZS6Jp9QPAJOQJDGDFhgoVF6hKctjD9BjeHm9ozpjFEWhClkAHI6fmZleI8Nv0WrWugd+QJLbPEZnW+6lIqPHiSqW/Z7/foN5sqwSrrZ81nEJh1LXokVfzHOCIyfSAbiwQteT9rpER6ZJfLgBACvvnmV1AA5nmE5etXSmHxCnqurm3r/DCNatImIWtHa0lGNBZmOJHp2qZF07Q1iZR7Q16jvG+5F+Tfa+6ABAdZ50LWE4nndZJDAUvVeV7693Lf0vMqkCTnuqe5kE7pftgtBNTJ1+cGAOOuIfh1ZZNiRghr1JCu//J+rveK633puu2ilKpEQOLCeJIeHkcAuqIXm80GwXtMFzJ/slojOYdoLXKSCh5AXiFyzIhW0NClwICDe8qIhRTdyHJVxujW+xgpmhGMa5GQYUqGzqay3AEKIsPlAu+JVJlTQuEWmWICrqBL2poKv1trYJ1l5nvG0+MjYs74wx//SAlpCEghYD6fMQ4DHh8f8OH9e/z4ww+cbE/Y7zfo2gaOdf9TTFBW44b3F2rfWEIE1VK4aa1J8g+4SpBkfay/XrfLZM/9pYr8ZQt1nYyu/y37wTr4y54wz2N9LpH2Xoo/XRNXSixXaB8n/fLYFJuuY5BPS/V/lcB94vFXVej1Rb4IwPL9jwXxv/Z4+bhaKYbqfm728Jcyl5cX6GV1vg7mLxOS9UVd98nlb2Qzl9+VBSWbzcuJgJcVjFQ7bdteWa5SX7ODzDmvb155fS+TlvXCXPdt5Wcv/1ZejzzvPE0U0DXBhfPMyUlgy8iY+L0uLUilFAtncE/LmDqnicKEnZQRfKj6AB/7yKWQWUZKRPzRrBXAm0VGqT399bmeWae6azqohp4ftcekrs5J/aCTABmWkBuwBocVyW193tYjmAuCdM3fWJ/v9c2/zuBr321VUSileD2YpbWTwhWyIggJ3QtLv62UAq0W+WK6TxZYfbkPOFl9sVbW6/7le15/Xlcya2Oil4TT9Xqnr8H63ut7AS/Oneb57+UaSbVceMFJr59eQ75+XgWUFSpxvQkqqChcENpYr1/rdeGwPhT/rxTZlOkPFvtWuZfz8jiK+SxKV4g7lQXpyylRzzlnFC0TNasXsH5t/G+B2DPKihS8vk70xBqkUKw1nU+tf26QVQrxYfw8I4bF8rQA5NqnCNlyDaFfmpM0pTVUptG+GCOz2c9LmypGFO8JWZvnqjY4TSNCmNF1Dh0/vlYKhQXBrluNsv5W60hOxNX9T6y4Zb/+eRH5Mga9jBEvW7br2PDyvpBDfkf28XVxu0YbAFwRNVfsCXpcJfdDqcGcVEq5nbviT62T6b/mUOV/TdT9fHw+Ph+fj8/H5+Pz8b+p49Om1T8fn4/Px+fj8/H5+Hz8b/r4HNA/H5+Pz8fn4/Px+fhncHwO6J+Pz8fn4/Px+fh8/DM4Pgf0z8fn4/Px+fh8fD7+GRyfA/rn4/Px+fh8fD4+H/8Mjs8B/fPx+fh8fD4+H5+PfwbH54D++fh8fD4+H5+Pz8c/g+NzQP98fD4+H5+Pz8fn45/B8Tmgfz4+H5+Pz8fn4/Pxz+D4/wG5zobvebAeUgAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import torch\n", + "\n", + "# Load the pretrained model\n", + "from going_modular.going_modular.predictions import pred_and_plot_image\n", + "class_names = ['Electricity Department','Nature and Recreation Department','Road Construction and Management','Waste Management','Water Supply and Management']\n", + "# Setup custom image path\n", + "custom_image_path = \"complaint_dataset/train/Waste Management/2.jpeg\"\n", + "\n", + "# Predict on custom image\n", + "pred_and_plot_image(model=model1,\n", + " image_path=custom_image_path,\n", + " class_names=class_names)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/guidance.md b/guidance.md deleted file mode 100644 index 951fa2b..0000000 --- a/guidance.md +++ /dev/null @@ -1,43 +0,0 @@ -# Guidelines for Applications and Project Proposals - -## We are seeking mission-oriented technologists to help us address urban issues in Boston. - -The Department of Innovation and Technology engages, empowers, and improves life for residents in the City through technology. Our team makes sure the networks, computers, and systems that support the City are secure and effective. We also manage the City’s websites and technologies focused on service delivery. - -### A Quick Note on Working with Us - -As an office in local government, we are open 9 - 5 PM EST. Selected students will be expected to attend frequent check-in meetings during those hours. If you have any questions, you can reach out to us at **opensource@boston.gov**. - -## Templates for Proposals - -Below, you will find a a template for proposals: - -### Section 1: Information about You - - - Name - - Contact Information - - Resume/CV - - List of Skills/Experience Level - - Link to GitHub/Equivalent Site with details on your open source code contributions - -### Section 2: Your Civic Commitment - -Please answer these questions: - - - What civic issues are you most passionate about? - - - How do you think civic technology could be used to improve life in your community? - -### Section 3: Your Project Skills - -Take a look at our ideas list is [here](https://cityofboston.github.io/summerofcode/) and answer the following questions. - - - Which ideas are you interested in? You can list one or multiple ideas. - - - Why do these particular ideas interest you? - - - Note the list of skills/technologies associated with your chosen ideas. - - - How many months/years of experience do you have for each skill? - - - Note and describe any relevant projects, open source contributions, or jobs where you have applied these skills and experience. If you have any links to this work, we would love to see them. diff --git a/index.md b/index.md deleted file mode 100644 index 202258c..0000000 --- a/index.md +++ /dev/null @@ -1,51 +0,0 @@ -# Google Summer of Code with the City of Boston - -Below, you will find a list of ideas we have for a Google Summer of Code contributors for the **summer of 2024**. Thank you for your consideration! - -## Guidance for Applications and Project Proposals - -You can find guidance for applications and your project proposals **[here](https://cityofboston.github.io/summerofcode/guidance)**. - -## Ideas List for 2024 - -### 1. Requesting City Services via AI-Driven Apps - -Residents of Boston can request a variety of non-emergency services through the City’s 311 system. Annually, more than 300,000 requests flow into 311. These include requests for street sweeping, litter pickup, pothole repair, parking enforcement, and dozens of other services. Residents request services by calling our 311 contact center, going to our website, or using the 311 app. - -The City believes that we can greatly improve the 311 experience by including AI-based image-recognition in our 311 apps. We envision a future where all a resident has to do is snap a photo of a problem they want to remedy. The AI will analyze the photo, determine the problem, and allow the user to submit a request in seconds. City staff would also benefit from this AI, as miscategorized 311 submissions can lead to mistaken deployment of resources. - -To help bring this to life, a Google Summer of Code contributor will build and train an AI model based on the hundreds of thousands photos submitted to Boston’s 311 system over the last several years. The AI will be capable of analyzing images users submit and determining the type of services they are most likely to be requesting. - -We give this project a **medium** level difficulty. The project can be completed in **175 hours**. - -This project requires knowledge of AI-based image processing and associated libraries and tools. The trained model must be turned into a performant API that can be accessed through a Web or App-based UI. Advanced app-building experience is not necessary, but we will a basic app to test the model on a variety of devices in varying conditions. - -The mentors of this project will include the City of Boston/s Senior Director of Products and Services (Basic City Services); the Chief Digital Officer; with guidance and input from the Chief Information Officer. - -### 2. Expanded Translation for the City's 311 App with Machine Learning - -In 2010, our office launched the City of Boston's [311 app](https://311.boston.gov/) (one of the first in the nation). The app allows residents to report an array on non-emergency issues (such as potholes) with their smartphones. Historically, the app has only been offered in English, and we have done some of the preliminary work to provide it in other languages. This is a very important issue to address, since up to 33% of the city does not speak English. - -[Inspired by the City of San José](https://medium.com/swlh/better-language-translation-through-machine-learning-everything-i-wish-i-knew-6-months-ago-8fa212fb1731), our Google Summer of Code contributor for 2022 created a machine learning model that improves the translation of text from residents reporting issues through the 311 app. The model was based on a custom, trained model using vocabulary frequently associated with City services. Their progress can be found here: - -[github.com/monum/311-translation](https://github.com/monum/311-translation) - -The machine learning model works well, but still needs improvement for the languages initially tested, namely Spanish and Vietnamese. We also want to make the translation model accessible via a web-service API. Finally, the translation service does not address the following languages used by Boston's residents: - -- Simplified Chinese -- Haitian Creole -- Cabo Verdean Creole -- Portuguese -- Russian -- Arabic -- French -- Somali - -This summer, we would like to add two more languages to the machine learning model and make it API-accessible, in order to create a translation service. The translation service should accept text from a 311 request and return translated text that could be easily understood by our City operations teams. We will also continue to benchmark the progress of this translation service against more general translation services. - -We give this project a **medium** level of difficulty. The project can be completed in **175 hours**. - -This project requires intermediate experience with machine learning, building and training models with text classification, natural language processing, and Python. It will also require intermediate experience with building web service APIs with with a web framework like Flask, Django etc. - -The mentors for the project will include key staff from the City of Boston, including one who served as a Google Summer of Code mentor at Code for America in 2011 and the City of Boston between 2021 and 2023. -