diff --git a/.gitignore b/.gitignore index 21fc4d1..b39c4c9 100644 --- a/.gitignore +++ b/.gitignore @@ -1 +1,2 @@ /PATSTAT/EU_CH_scope/cpc_defs.csv +/misc_code/ diff --git a/WOS/ai_scope_keywords.txt b/WOS/ai_scope_keywords.txt index ababf68..9f72e92 100644 --- a/WOS/ai_scope_keywords.txt +++ b/WOS/ai_scope_keywords.txt @@ -153,11 +153,10 @@ markov chain, markov process, markov decision process, monte carlo method, -bayesian interference, +bayesian inference, kernel method, eigendecomposition, eigen decomposition, -kernel method, radial basis function, QR decomposition, LU decomposition, @@ -169,4 +168,39 @@ convex optimization, nonlinear optimization, L? regulari*, ridge regression, -gaussian process \ No newline at end of file +gaussian process, +manifold learning, +locally linear embedding*, +vector database*, +vector embedding*, +text mining, +human-robot interact*, +semantic web*, +fuzzy set*, +face recognition &! brain, +object detection &! brain, +multi agent system*, +speech recognition &! brain, +brain computer interface, +intelligent robot*, +remote sensing, +image reconstruction, +representation learning, +data augmentation, +adversarial robustness, +meta learning, +learning system, +adversarial training, +adversarial example*, +generative model*, +large language model*, +few shot learning, +image representation, +optimization algorithm, +swarm optimization, +variational inference, +kalman network*, +knowledge distillation, +kernel learning, +classifier, +lasso regression \ No newline at end of file diff --git a/WOS/wos_extract/geckodriver.log b/WOS/wos_extract/geckodriver.log index 6e1cd7e..2c19b09 100644 --- a/WOS/wos_extract/geckodriver.log +++ b/WOS/wos_extract/geckodriver.log @@ -10248,3 +10248,1961 @@ JavaScript warning: https://www.webofscience.com/OCCqHqkkkVdS3/1spykg8tf6TTG/4/5 JavaScript warning: https://www.webofscience.com/OCCqHqkkkVdS3/1spykg8tf6TTG/4/5aucJpSSYS/fgMKIwUl/HzhK/FzhwTiE, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. 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Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392165840 Marionette INFO Stopped listening on port 59933 +Dynamically enable window occlusion 1 +1681392166744 geckodriver INFO Listening on 127.0.0.1:60003 +1681392169792 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "600 ... 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(new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilebykyrK\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:60083/devtools/browser/a8258367-a9a2-4803-a296-0e026e033b24 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392204448 Marionette INFO Stopped listening on port 60094 +Dynamically enable window occlusion 1 +1681392205230 geckodriver INFO Listening on 127.0.0.1:60165 +1681392208254 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "601 ... 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Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392223284 Marionette INFO Stopped listening on port 60173 +Dynamically enable window occlusion 1 +1681392224202 geckodriver INFO Listening on 127.0.0.1:60243 +1681392227207 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "602 ... 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(new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileDd5yhL\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:60244/devtools/browser/8f83ecb0-038d-4ed4-85fe-3e7fe7d5c418 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392242396 Marionette INFO Stopped listening on port 60251 +Dynamically enable window occlusion 1 +1681392243113 geckodriver INFO Listening on 127.0.0.1:60321 +1681392246172 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "603 ... 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Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392354123 Marionette INFO Stopped listening on port 60599 +Dynamically enable window occlusion 1 +1681392354866 geckodriver INFO Listening on 127.0.0.1:60667 +1681392357893 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "606 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilelsb5NM" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392358164 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392358168 Marionette INFO Listening on port 60675 +Read port: 60675 +WebDriver BiDi listening on ws://127.0.0.1:60668 +1681392358297 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilelsb5NM\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:60668/devtools/browser/2c642319-3ae2-44c5-bb59-fdd99a456834 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392373669 Marionette INFO Stopped listening on port 60675 +Dynamically enable window occlusion 1 +1681392374389 geckodriver INFO Listening on 127.0.0.1:60750 +1681392377426 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "607 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilecXst9d" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392377743 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392377747 Marionette INFO Listening on port 60762 +Read port: 60762 +WebDriver BiDi listening on ws://127.0.0.1:60751 +1681392377876 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilecXst9d\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:60751/devtools/browser/5036b3e4-c972-426f-a7ed-c63ffbbadd3e +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392396653 Marionette INFO Stopped listening on port 60762 +Dynamically enable window occlusion 1 +1681392397387 geckodriver INFO Listening on 127.0.0.1:60844 +1681392400415 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "608 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileSJuruj" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392400738 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392400742 Marionette INFO Listening on port 60852 +Read port: 60852 +WebDriver BiDi listening on ws://127.0.0.1:60845 +1681392400876 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileSJuruj\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:60845/devtools/browser/7769341a-f0ab-49c6-abdd-1b6007bb53a4 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392416905 Marionette INFO Stopped listening on port 60852 +Dynamically enable window occlusion 1 +1681392417738 geckodriver INFO Listening on 127.0.0.1:60924 +1681392420773 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "609 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileENITLI" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392421098 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392421104 Marionette INFO Listening on port 60932 +Read port: 60932 +WebDriver BiDi listening on ws://127.0.0.1:60925 +1681392421231 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileENITLI\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:60925/devtools/browser/e80e098c-91db-4a60-a835-6b31d757dbdd +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392435777 Marionette INFO Stopped listening on port 60932 +Dynamically enable window occlusion 1 +1681392436497 geckodriver INFO Listening on 127.0.0.1:61005 +1681392439529 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "610 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilecmcY7n" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392439801 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392439806 Marionette INFO Listening on port 61013 +Read port: 61013 +WebDriver BiDi listening on ws://127.0.0.1:61006 +1681392439942 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilecmcY7n\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:61006/devtools/browser/206cd646-f8d2-4753-b29d-a32b1b742689 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392453260 Marionette INFO Stopped listening on port 61013 +Dynamically enable window occlusion 1 +1681392453990 geckodriver INFO Listening on 127.0.0.1:61080 +1681392457022 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "610 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilec81uBi" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392457290 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392457294 Marionette INFO Listening on port 61088 +Read port: 61088 +WebDriver BiDi listening on ws://127.0.0.1:61081 +1681392457425 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilec81uBi\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:61081/devtools/browser/40bb5636-267e-40f4-996e-90df62dfa66f +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392470516 Marionette INFO Stopped listening on port 61088 +Dynamically enable window occlusion 1 +1681392471222 geckodriver INFO Listening on 127.0.0.1:61160 +1681392474240 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "611 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofiledsoIut" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392474547 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392474552 Marionette INFO Listening on port 53767 +Read port: 53767 +WebDriver BiDi listening on ws://127.0.0.1:61161 +1681392474689 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofiledsoIut\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:61161/devtools/browser/257c5405-f283-4c8c-b120-921bac8253ab +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392490025 Marionette INFO Stopped listening on port 53767 +Dynamically enable window occlusion 1 +1681392500888 geckodriver INFO Listening on 127.0.0.1:53846 +1681392503913 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "538 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileXoP3KI" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392504194 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392504198 Marionette INFO Listening on port 53855 +Read port: 53855 +WebDriver BiDi listening on ws://127.0.0.1:53847 +1681392504349 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileXoP3KI\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:53847/devtools/browser/b349591d-74ef-4a9a-9284-cb5d56642024 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392516469 Marionette INFO Stopped listening on port 53855 +Dynamically enable window occlusion 1 +1681392517176 geckodriver INFO Listening on 127.0.0.1:53922 +1681392520208 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "539 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileG53xj5" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392520472 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392520476 Marionette INFO Listening on port 53930 +Read port: 53930 +WebDriver BiDi listening on ws://127.0.0.1:53923 +1681392520607 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileG53xj5\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:53923/devtools/browser/0f1a33b3-12b6-4a8f-b7fa-109ceaaecc20 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392535544 Marionette INFO Stopped listening on port 53930 +Dynamically enable window occlusion 1 +1681392536335 geckodriver INFO Listening on 127.0.0.1:53998 +1681392539340 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "539 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilepzGFbA" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392539611 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392539615 Marionette INFO Listening on port 54006 +Read port: 54006 +WebDriver BiDi listening on ws://127.0.0.1:53999 +1681392539772 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilepzGFbA\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:53999/devtools/browser/91a61d6d-c9a6-414b-8043-fdbbd42c1978 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392553111 Marionette INFO Stopped listening on port 54006 +Dynamically enable window occlusion 1 +1681392553871 geckodriver INFO Listening on 127.0.0.1:54077 +1681392556908 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "540 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileg0GjBn" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392557181 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392557185 Marionette INFO Listening on port 54085 +Read port: 54085 +WebDriver BiDi listening on ws://127.0.0.1:54078 +1681392557338 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileg0GjBn\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54078/devtools/browser/d755a191-32db-4cd2-a96e-63db71c157f5 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392572435 Marionette INFO Stopped listening on port 54085 +Dynamically enable window occlusion 1 +1681392581167 geckodriver INFO Listening on 127.0.0.1:54155 +1681392584192 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "541 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileDZRnfs" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392584457 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392584461 Marionette INFO Listening on port 54172 +Read port: 54172 +WebDriver BiDi listening on ws://127.0.0.1:54156 +1681392584622 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileDZRnfs\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54156/devtools/browser/c9037ac2-c1cb-4d90-8d8a-b2b94803e332 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392597253 Marionette INFO Stopped listening on port 54172 +Dynamically enable window occlusion 1 +1681392597973 geckodriver INFO Listening on 127.0.0.1:54242 +1681392601026 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "542 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileKJAb3k" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392601299 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392601303 Marionette INFO Listening on port 54250 +Read port: 54250 +WebDriver BiDi listening on ws://127.0.0.1:54243 +1681392601470 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileKJAb3k\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54243/devtools/browser/1c9d94df-d3d0-45a8-8fc1-a33f4d5a24e6 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392618051 Marionette INFO Stopped listening on port 54250 +Dynamically enable window occlusion 1 +1681392618795 geckodriver INFO Listening on 127.0.0.1:54318 +1681392621803 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "543 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilezXN04T" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392622073 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392622078 Marionette INFO Listening on port 54326 +Read port: 54326 +WebDriver BiDi listening on ws://127.0.0.1:54319 +1681392622247 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilezXN04T\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54319/devtools/browser/b2d768d4-0369-4eeb-9cec-d01b0a74d240 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392636687 Marionette INFO Stopped listening on port 54326 +Dynamically enable window occlusion 1 +1681392637615 geckodriver INFO Listening on 127.0.0.1:54399 +1681392640641 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "544 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile6UOIMA" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392641204 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392641211 Marionette INFO Listening on port 54418 +Read port: 54418 +WebDriver BiDi listening on ws://127.0.0.1:54400 +1681392641480 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile6UOIMA\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54400/devtools/browser/d148fa4e-2860-4535-b852-d74ea9567981 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392655646 Marionette INFO Stopped listening on port 54418 +Dynamically enable window occlusion 1 +1681392656426 geckodriver INFO Listening on 127.0.0.1:54499 +1681392659680 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "545 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileSELfDW" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392659953 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392659958 Marionette INFO Listening on port 54507 +Read port: 54507 +WebDriver BiDi listening on ws://127.0.0.1:54500 +1681392660125 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileSELfDW\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54500/devtools/browser/9f94b039-45ed-453d-b4a9-6997de893a88 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392679791 Marionette INFO Stopped listening on port 54507 +Dynamically enable window occlusion 1 +1681392680553 geckodriver INFO Listening on 127.0.0.1:54587 +1681392683598 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "545 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilevWKmyT" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392683923 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392683927 Marionette INFO Listening on port 54596 +Read port: 54596 +WebDriver BiDi listening on ws://127.0.0.1:54588 +1681392684069 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilevWKmyT\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54588/devtools/browser/28c79e02-0ba4-4199-b754-e60172541a4d +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392699283 Marionette INFO Stopped listening on port 54596 +Dynamically enable window occlusion 1 +1681392700046 geckodriver INFO Listening on 127.0.0.1:54671 +1681392703090 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "546 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilelKFyGm" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392703355 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392703359 Marionette INFO Listening on port 54679 +Read port: 54679 +WebDriver BiDi listening on ws://127.0.0.1:54672 +1681392703596 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilelKFyGm\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54672/devtools/browser/736ad3d2-5a99-4e09-912e-dffdd650b6fe +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392716100 Marionette INFO Stopped listening on port 54679 +Dynamically enable window occlusion 1 +1681392716844 geckodriver INFO Listening on 127.0.0.1:54747 +1681392719870 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "547 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileN41bnw" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392720141 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392720145 Marionette INFO Listening on port 54755 +Read port: 54755 +WebDriver BiDi listening on ws://127.0.0.1:54748 +1681392720305 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileN41bnw\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54748/devtools/browser/b72f1bd0-5413-473c-b4f9-16b28a3c4e3a +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392733903 Marionette INFO Stopped listening on port 54755 +Dynamically enable window occlusion 1 +1681392734690 geckodriver INFO Listening on 127.0.0.1:54828 +1681392737717 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "548 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofiletdrdrm" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392737980 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392737984 Marionette INFO Listening on port 54836 +Read port: 54836 +WebDriver BiDi listening on ws://127.0.0.1:54829 +1681392738133 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofiletdrdrm\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54829/devtools/browser/68608115-d60a-4814-a972-24766cbe5c12 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392751207 Marionette INFO Stopped listening on port 54836 +Dynamically enable window occlusion 1 +1681392751920 geckodriver INFO Listening on 127.0.0.1:54904 +1681392754954 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "549 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileAYtRiC" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392755222 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392755226 Marionette INFO Listening on port 54912 +Read port: 54912 +WebDriver BiDi listening on ws://127.0.0.1:54905 +1681392755404 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileAYtRiC\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54905/devtools/browser/a4f7d20b-19ab-443c-b5c6-64cd60c8ee5a +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392779842 Marionette INFO Stopped listening on port 54912 +Dynamically enable window occlusion 1 +1681392782741 geckodriver INFO Listening on 127.0.0.1:54994 +1681392785754 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "549 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileNWzHDl" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392786026 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392786031 Marionette INFO Listening on port 55002 +Read port: 55002 +WebDriver BiDi listening on ws://127.0.0.1:54995 +1681392786179 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileNWzHDl\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54995/devtools/browser/a037246b-8e1f-4830-b32b-815e772ef321 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392798566 Marionette INFO Stopped listening on port 55002 +Dynamically enable window occlusion 1 +1681392799280 geckodriver INFO Listening on 127.0.0.1:55068 +1681392802331 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "550 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile0ftwVS" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392802595 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392802600 Marionette INFO Listening on port 55076 +Read port: 55076 +WebDriver BiDi listening on ws://127.0.0.1:55069 +1681392802750 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile0ftwVS\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55069/devtools/browser/c0eed5cb-7147-4ce7-ba4c-d61668d90896 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392816627 Marionette INFO Stopped listening on port 55076 +Dynamically enable window occlusion 1 +1681392817351 geckodriver INFO Listening on 127.0.0.1:55142 +1681392820369 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "551 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilevAIgCo" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392820637 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392820641 Marionette INFO Listening on port 55150 +Read port: 55150 +WebDriver BiDi listening on ws://127.0.0.1:55143 +1681392820798 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilevAIgCo\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55143/devtools/browser/e6de6c4a-6c4e-4733-93d7-36edf22bedc5 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392833372 Marionette INFO Stopped listening on port 55150 +Dynamically enable window occlusion 1 +1681392834098 geckodriver INFO Listening on 127.0.0.1:55215 +1681392837162 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "552 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilealpNDd" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392837502 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392837506 Marionette INFO Listening on port 55223 +Read port: 55223 +WebDriver BiDi listening on ws://127.0.0.1:55216 +1681392837672 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilealpNDd\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55216/devtools/browser/e48c0287-c9a2-4384-9d49-e7c780233631 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392853616 Marionette INFO Stopped listening on port 55223 +Dynamically enable window occlusion 1 +1681392862374 geckodriver INFO Listening on 127.0.0.1:55291 +1681392865399 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "552 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofiledoZmRo" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392865737 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392865742 Marionette INFO Listening on port 55307 +Read port: 55307 +WebDriver BiDi listening on ws://127.0.0.1:55292 +1681392865911 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofiledoZmRo\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55292/devtools/browser/93204a42-ae71-412c-add9-092411c83acc +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392877983 Marionette INFO Stopped listening on port 55307 +Dynamically enable window occlusion 1 +1681392878681 geckodriver INFO Listening on 127.0.0.1:55377 +1681392881724 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "553 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileNsWaaR" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392881992 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392881997 Marionette INFO Listening on port 55385 +Read port: 55385 +WebDriver BiDi listening on ws://127.0.0.1:55378 +1681392882153 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileNsWaaR\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55378/devtools/browser/7a96b26c-9531-486b-8bc6-1f9e925e48d6 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392896358 Marionette INFO Stopped listening on port 55385 +Dynamically enable window occlusion 1 +1681392897125 geckodriver INFO Listening on 127.0.0.1:55457 +1681392900170 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "554 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofiletrfXpu" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392900440 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392900445 Marionette INFO Listening on port 55465 +Read port: 55465 +WebDriver BiDi listening on ws://127.0.0.1:55458 +1681392900600 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofiletrfXpu\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55458/devtools/browser/1a829146-b658-478f-9a21-eb4ec7e9ea8a +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392912964 Marionette INFO Stopped listening on port 55465 +Dynamically enable window occlusion 1 +1681392913680 geckodriver INFO Listening on 127.0.0.1:55536 +1681392916731 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "555 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileMTWVWP" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392917005 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392917009 Marionette INFO Listening on port 55549 +Read port: 55549 +WebDriver BiDi listening on ws://127.0.0.1:55537 +1681392917164 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileMTWVWP\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55537/devtools/browser/b4a1010e-2241-4b01-9bb3-a3ba8ca5fcff +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392933343 Marionette INFO Stopped listening on port 55549 +Dynamically enable window occlusion 1 +1681392934198 geckodriver INFO Listening on 127.0.0.1:55622 +1681392937222 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "556 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile6SQHhs" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392937518 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392937524 Marionette INFO Listening on port 55630 +Read port: 55630 +WebDriver BiDi listening on ws://127.0.0.1:55623 +1681392937707 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile6SQHhs\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55623/devtools/browser/f4b7637f-8934-413e-a800-2385854d8ef1 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392952304 Marionette INFO Stopped listening on port 55630 +Dynamically enable window occlusion 1 +1681392953244 geckodriver INFO Listening on 127.0.0.1:55711 +1681392956508 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "557 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilerICd8u" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392956888 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392956893 Marionette INFO Listening on port 55719 +Read port: 55719 +WebDriver BiDi listening on ws://127.0.0.1:55712 +1681392957057 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilerICd8u\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55712/devtools/browser/1c74cc49-cac7-4757-bba8-926393aa9c7f +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392972972 Marionette INFO Stopped listening on port 55719 +Dynamically enable window occlusion 1 +1681392973724 geckodriver INFO Listening on 127.0.0.1:55792 +1681392976759 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "557 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilerGt3wa" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392977033 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392977037 Marionette INFO Listening on port 55800 +Read port: 55800 +WebDriver BiDi listening on ws://127.0.0.1:55793 +1681392977203 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilerGt3wa\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55793/devtools/browser/9c31eff6-684c-435d-b6d7-62254b8be290 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681392991146 Marionette INFO Stopped listening on port 55800 +Dynamically enable window occlusion 1 +1681392992053 geckodriver INFO Listening on 127.0.0.1:55870 +1681392995075 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "558 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileXz3rHV" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681392995403 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681392995408 Marionette INFO Listening on port 55880 +Read port: 55880 +WebDriver BiDi listening on ws://127.0.0.1:55871 +1681392995577 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileXz3rHV\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55871/devtools/browser/243e8e3d-a79a-4db6-b685-d7eba1e8ee93 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393010156 Marionette INFO Stopped listening on port 55880 +Dynamically enable window occlusion 1 +1681393010858 geckodriver INFO Listening on 127.0.0.1:55951 +1681393013896 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "559 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileU8ezIo" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393014166 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393014170 Marionette INFO Listening on port 55959 +Read port: 55959 +WebDriver BiDi listening on ws://127.0.0.1:55952 +1681393014329 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileU8ezIo\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55952/devtools/browser/cb906d50-7eec-4b70-acb7-c4d6d76aa8c9 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393026322 Marionette INFO Stopped listening on port 55959 +Dynamically enable window occlusion 1 +1681393027041 geckodriver INFO Listening on 127.0.0.1:56029 +1681393030070 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "560 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileZA0KhN" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393030345 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393030350 Marionette INFO Listening on port 56037 +Read port: 56037 +WebDriver BiDi listening on ws://127.0.0.1:56030 +1681393030509 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileZA0KhN\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:56030/devtools/browser/a27242d7-56ca-44f4-acc1-aa1cfd425706 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393044564 Marionette INFO Stopped listening on port 56037 +Dynamically enable window occlusion 1 +1681393055463 geckodriver INFO Listening on 127.0.0.1:56132 +1681393058493 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "561 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileO34KWL" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393058782 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393058787 Marionette INFO Listening on port 56140 +Read port: 56140 +WebDriver BiDi listening on ws://127.0.0.1:56133 +1681393058930 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileO34KWL\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:56133/devtools/browser/e14751d1-ff9e-4288-8444-6cea18871a34 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393071874 Marionette INFO Stopped listening on port 56140 +Dynamically enable window occlusion 1 +1681393072978 geckodriver INFO Listening on 127.0.0.1:61064 +1681393076249 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "610 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile28VHaI" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393076570 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393076574 Marionette INFO Listening on port 61072 +Read port: 61072 +WebDriver BiDi listening on ws://127.0.0.1:61065 +1681393076726 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile28VHaI\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:61065/devtools/browser/e25c59f6-a23a-46ad-8aa2-6e7c13493bed +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393090864 Marionette INFO Stopped listening on port 61072 +Dynamically enable window occlusion 1 +1681393091627 geckodriver INFO Listening on 127.0.0.1:61145 +1681393094646 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "611 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile0Sy3Um" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393094953 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393094957 Marionette INFO Listening on port 61154 +Read port: 61154 +WebDriver BiDi listening on ws://127.0.0.1:61146 +1681393095110 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile0Sy3Um\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:61146/devtools/browser/e5cef9e7-cbc0-46d0-8145-7886ba612e8b +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393108310 Marionette INFO Stopped listening on port 61154 +Dynamically enable window occlusion 1 +1681393109031 geckodriver INFO Listening on 127.0.0.1:61220 +1681393112063 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "612 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileEYmGYa" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393112340 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393112344 Marionette INFO Listening on port 61228 +Read port: 61228 +WebDriver BiDi listening on ws://127.0.0.1:61221 +1681393112506 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileEYmGYa\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:61221/devtools/browser/c3b00041-cc14-476d-b00d-e466c6eb954d +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393125851 Marionette INFO Stopped listening on port 61228 +Dynamically enable window occlusion 1 +1681393126555 geckodriver INFO Listening on 127.0.0.1:61298 +1681393129596 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "612 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileI5OY31" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393129912 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393129916 Marionette INFO Listening on port 61306 +Read port: 61306 +WebDriver BiDi listening on ws://127.0.0.1:61299 +1681393130069 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileI5OY31\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:61299/devtools/browser/3ca32d2f-1ca3-4b37-a237-cf2e0f7d8937 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393182111 geckodriver INFO Listening on 127.0.0.1:54221 +1681393185163 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "542 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilexQpo19" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393185509 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393185513 Marionette INFO Listening on port 54229 +Read port: 54229 +WebDriver BiDi listening on ws://127.0.0.1:54222 +1681393185690 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilexQpo19\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54222/devtools/browser/e461b963-9711-4741-9273-623756d46c3a +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393199381 Marionette INFO Stopped listening on port 54229 +Dynamically enable window occlusion 1 +1681393200309 geckodriver INFO Listening on 127.0.0.1:54299 +1681393203365 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "543 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilep1kRyt" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393203770 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393203775 Marionette INFO Listening on port 54307 +Read port: 54307 +WebDriver BiDi listening on ws://127.0.0.1:54300 +1681393203950 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilep1kRyt\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54300/devtools/browser/653c043b-2e0d-454b-bd53-4fbdd10808f8 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393218311 Marionette INFO Stopped listening on port 54307 +Dynamically enable window occlusion 1 +1681393219247 geckodriver INFO Listening on 127.0.0.1:54380 +1681393222293 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "543 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile2AS1JC" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393222592 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393222598 Marionette INFO Listening on port 54388 +Read port: 54388 +WebDriver BiDi listening on ws://127.0.0.1:54381 +1681393222778 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile2AS1JC\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54381/devtools/browser/b98657c3-899f-4f08-be98-d15f3b4e2cdb +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393236323 Marionette INFO Stopped listening on port 54388 +Dynamically enable window occlusion 1 +1681393237159 geckodriver INFO Listening on 127.0.0.1:54462 +1681393240304 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "544 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileITj6jW" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393240588 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393240592 Marionette INFO Listening on port 54470 +Read port: 54470 +WebDriver BiDi listening on ws://127.0.0.1:54463 +1681393240761 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileITj6jW\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54463/devtools/browser/44586bb5-1b1c-4acf-b5d7-17b953a9fdd9 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393255275 Marionette INFO Stopped listening on port 54470 +Dynamically enable window occlusion 1 +1681393264142 geckodriver INFO Listening on 127.0.0.1:54548 +1681393267170 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "545 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilegzIttI" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393267498 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393267503 Marionette INFO Listening on port 54564 +Read port: 54564 +WebDriver BiDi listening on ws://127.0.0.1:54549 +1681393267682 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilegzIttI\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54549/devtools/browser/53210cad-e92c-4078-84e3-e34f1332c350 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393281260 Marionette INFO Stopped listening on port 54564 +Dynamically enable window occlusion 1 +1681393282346 geckodriver INFO Listening on 127.0.0.1:54630 +1681393285378 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "546 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileGVC9t3" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393285656 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393285663 Marionette INFO Listening on port 54638 +Read port: 54638 +WebDriver BiDi listening on ws://127.0.0.1:54631 +1681393285831 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileGVC9t3\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54631/devtools/browser/14ebf452-0a3c-4824-b7be-2e661e40aafe +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393301530 Marionette INFO Stopped listening on port 54638 +Dynamically enable window occlusion 1 +1681393302452 geckodriver INFO Listening on 127.0.0.1:54713 +1681393305485 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "547 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileEm2iuX" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393305778 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393305783 Marionette INFO Listening on port 54721 +Read port: 54721 +WebDriver BiDi listening on ws://127.0.0.1:54714 +1681393305946 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileEm2iuX\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54714/devtools/browser/69f5395f-7857-4270-93cb-1b5065ee94db +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393318604 Marionette INFO Stopped listening on port 54721 +Dynamically enable window occlusion 1 +1681393319467 geckodriver INFO Listening on 127.0.0.1:54788 +1681393322497 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "547 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileYgJPCP" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393322799 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393322804 Marionette INFO Listening on port 54797 +Read port: 54797 +WebDriver BiDi listening on ws://127.0.0.1:54789 +1681393322962 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileYgJPCP\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54789/devtools/browser/da32fa5b-b32d-4a2f-85dc-08746f6bd28c +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393338685 Marionette INFO Stopped listening on port 54797 +Dynamically enable window occlusion 1 +1681393339552 geckodriver INFO Listening on 127.0.0.1:54868 +1681393342602 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "548 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile4sngjt" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393342886 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393342890 Marionette INFO Listening on port 54876 +Read port: 54876 +WebDriver BiDi listening on ws://127.0.0.1:54869 +1681393343055 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile4sngjt\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54869/devtools/browser/b1abc35e-a9aa-43d1-826d-5aa888f97dde +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393356294 Marionette INFO Stopped listening on port 54876 +Dynamically enable window occlusion 1 +1681393357149 geckodriver INFO Listening on 127.0.0.1:54951 +1681393360195 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "549 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilethaueD" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393360496 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393360500 Marionette INFO Listening on port 54960 +Read port: 54960 +WebDriver BiDi listening on ws://127.0.0.1:54952 +1681393360672 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilethaueD\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:54952/devtools/browser/3cfa80f6-15a3-461d-8613-d110d8ad18b6 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393377021 Marionette INFO Stopped listening on port 54960 +Dynamically enable window occlusion 1 +!!! error running onStopped callback: TypeError: callback is not a function +1681393377975 geckodriver INFO Listening on 127.0.0.1:55034 +1681393381028 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "550 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileLdgQiJ" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393381322 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393381327 Marionette INFO Listening on port 55042 +Read port: 55042 +WebDriver BiDi listening on ws://127.0.0.1:55035 +1681393381494 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileLdgQiJ\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55035/devtools/browser/6d21aaf3-a9d0-4762-813e-c948e04c0710 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393398113 Marionette INFO Stopped listening on port 55042 +Dynamically enable window occlusion 1 +1681393399362 geckodriver INFO Listening on 127.0.0.1:55110 +1681393402366 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "551 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileSmLqZr" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393402646 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393402650 Marionette INFO Listening on port 55118 +Read port: 55118 +WebDriver BiDi listening on ws://127.0.0.1:55111 +1681393402823 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileSmLqZr\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55111/devtools/browser/6585a507-4793-49c7-be1f-6307e0fd02c2 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393415826 Marionette WARN TimedPromise timed out after 500 ms: stacktrace: +TimedPromise/<@chrome://remote/content/marionette/sync.sys.mjs:219:24 +TimedPromise@chrome://remote/content/marionette/sync.sys.mjs:204:10 +interaction.flushEventLoop@chrome://remote/content/marionette/interaction.sys.mjs:425:10 +webdriverClickElement@chrome://remote/content/marionette/interaction.sys.mjs:173:31 +1681393446603 geckodriver INFO Listening on 127.0.0.1:55191 +1681393449643 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "551 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileogb8IZ" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393450075 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393450080 Marionette INFO Listening on port 55201 +Read port: 55201 +WebDriver BiDi listening on ws://127.0.0.1:55192 +1681393450269 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileogb8IZ\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55192/devtools/browser/32e828ad-a24e-4189-9e46-3a2c4820103c +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393468831 Marionette INFO Stopped listening on port 55201 +Dynamically enable window occlusion 1 +!!! error running onStopped callback: TypeError: callback is not a function +1681393469729 geckodriver INFO Listening on 127.0.0.1:55272 +1681393472762 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "552 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileHEuUjP" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393473155 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393473160 Marionette INFO Listening on port 55280 +Read port: 55280 +WebDriver BiDi listening on ws://127.0.0.1:55273 +1681393473342 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileHEuUjP\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55273/devtools/browser/250eeabe-6d74-4bea-816b-6ec48cddcf0f +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393481266 Marionette WARN TimedPromise timed out after 500 ms: stacktrace: +TimedPromise/<@chrome://remote/content/marionette/sync.sys.mjs:219:24 +TimedPromise@chrome://remote/content/marionette/sync.sys.mjs:204:10 +interaction.flushEventLoop@chrome://remote/content/marionette/interaction.sys.mjs:425:10 +webdriverClickElement@chrome://remote/content/marionette/interaction.sys.mjs:173:31 +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393490250 Marionette INFO Stopped listening on port 55280 +Dynamically enable window occlusion 1 +!!! error running onStopped callback: TypeError: callback is not a function +1681393501793 geckodriver INFO Listening on 127.0.0.1:55359 +1681393504825 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "553 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileqYdz4C" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393505164 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393505169 Marionette INFO Listening on port 55367 +Read port: 55367 +WebDriver BiDi listening on ws://127.0.0.1:55360 +1681393505359 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileqYdz4C\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55360/devtools/browser/9e7b5995-6a48-462f-ae01-025ef885b70b +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393512184 Marionette WARN TimedPromise timed out after 500 ms: stacktrace: +TimedPromise/<@chrome://remote/content/marionette/sync.sys.mjs:219:24 +TimedPromise@chrome://remote/content/marionette/sync.sys.mjs:204:10 +interaction.flushEventLoop@chrome://remote/content/marionette/interaction.sys.mjs:425:10 +webdriverClickElement@chrome://remote/content/marionette/interaction.sys.mjs:173:31 +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393519545 Marionette INFO Stopped listening on port 55367 +Dynamically enable window occlusion 1 +1681393522399 geckodriver INFO Listening on 127.0.0.1:55441 +1681393525417 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "554 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileDorjEB" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393525729 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393525734 Marionette INFO Listening on port 55452 +Read port: 55452 +WebDriver BiDi listening on ws://127.0.0.1:55442 +1681393525888 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileDorjEB\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55442/devtools/browser/26daf50f-a842-44ab-8143-a8728f0cd5fb +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393534065 Marionette WARN TimedPromise timed out after 500 ms: stacktrace: +TimedPromise/<@chrome://remote/content/marionette/sync.sys.mjs:219:24 +TimedPromise@chrome://remote/content/marionette/sync.sys.mjs:204:10 +interaction.flushEventLoop@chrome://remote/content/marionette/interaction.sys.mjs:425:10 +webdriverClickElement@chrome://remote/content/marionette/interaction.sys.mjs:173:31 +1681393539184 Marionette WARN TimedPromise timed out after 500 ms: stacktrace: +TimedPromise/<@chrome://remote/content/marionette/sync.sys.mjs:219:24 +TimedPromise@chrome://remote/content/marionette/sync.sys.mjs:204:10 +interaction.flushEventLoop@chrome://remote/content/marionette/interaction.sys.mjs:425:10 +webdriverClickElement@chrome://remote/content/marionette/interaction.sys.mjs:173:31 +1681393540351 Marionette WARN TimedPromise timed out after 500 ms: stacktrace: +TimedPromise/<@chrome://remote/content/marionette/sync.sys.mjs:219:24 +TimedPromise@chrome://remote/content/marionette/sync.sys.mjs:204:10 +interaction.flushEventLoop@chrome://remote/content/marionette/interaction.sys.mjs:425:10 +webdriverClickElement@chrome://remote/content/marionette/interaction.sys.mjs:173:31 +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393543836 Marionette INFO Stopped listening on port 55452 +Dynamically enable window occlusion 1 +1681393545202 geckodriver INFO Listening on 127.0.0.1:55520 +1681393548315 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "555 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileUA5n5A" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393548680 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393548684 Marionette INFO Listening on port 55535 +Read port: 55535 +WebDriver BiDi listening on ws://127.0.0.1:55521 +1681393548904 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileUA5n5A\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55521/devtools/browser/7b69528d-a624-404f-ab58-1d41be63658e +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393565913 Marionette INFO Stopped listening on port 55535 +Dynamically enable window occlusion 1 +1681393567248 geckodriver INFO Listening on 127.0.0.1:55606 +1681393570290 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "556 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileSker6Y" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393570568 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393570572 Marionette INFO Listening on port 55614 +Read port: 55614 +WebDriver BiDi listening on ws://127.0.0.1:55607 +1681393570720 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileSker6Y\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55607/devtools/browser/43e2189f-0173-43b5-acbe-1b5740bdf466 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393577656 Marionette WARN TimedPromise timed out after 500 ms: stacktrace: +TimedPromise/<@chrome://remote/content/marionette/sync.sys.mjs:219:24 +TimedPromise@chrome://remote/content/marionette/sync.sys.mjs:204:10 +interaction.flushEventLoop@chrome://remote/content/marionette/interaction.sys.mjs:425:10 +webdriverClickElement@chrome://remote/content/marionette/interaction.sys.mjs:173:31 +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393585801 Marionette INFO Stopped listening on port 55614 +Dynamically enable window occlusion 1 +1681393586528 geckodriver INFO Listening on 127.0.0.1:55682 +1681393589564 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "556 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilesTwhFE" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393589857 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393589862 Marionette INFO Listening on port 55691 +Read port: 55691 +WebDriver BiDi listening on ws://127.0.0.1:55683 +1681393590004 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilesTwhFE\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55683/devtools/browser/4d10d870-ca0c-4422-9630-7034cf47e94d +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393613918 Marionette INFO Stopped listening on port 55691 +Dynamically enable window occlusion 1 +1681393614676 geckodriver INFO Listening on 127.0.0.1:55766 +1681393617703 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "557 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileJy91rY" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393618345 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393618361 Marionette INFO Listening on port 55774 +Read port: 55774 +WebDriver BiDi listening on ws://127.0.0.1:55767 +1681393618589 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileJy91rY\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55767/devtools/browser/95e97174-a9ea-4f02-b590-7c59c2831c37 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393633022 Marionette WARN TimedPromise timed out after 500 ms: stacktrace: +TimedPromise/<@chrome://remote/content/marionette/sync.sys.mjs:219:24 +TimedPromise@chrome://remote/content/marionette/sync.sys.mjs:204:10 +interaction.flushEventLoop@chrome://remote/content/marionette/interaction.sys.mjs:425:10 +webdriverClickElement@chrome://remote/content/marionette/interaction.sys.mjs:173:31 +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393637983 Marionette INFO Stopped listening on port 55774 +Dynamically enable window occlusion 1 +1681393734155 geckodriver INFO Listening on 127.0.0.1:55855 +1681393737191 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "558 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile72W06I" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393737498 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393737503 Marionette INFO Listening on port 55863 +Read port: 55863 +WebDriver BiDi listening on ws://127.0.0.1:55856 +1681393737645 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofile72W06I\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55856/devtools/browser/72fb755a-9d23-412d-938e-ca2a5c7a3c69 +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393772429 Marionette INFO Stopped listening on port 55863 +Dynamically enable window occlusion 1 +1681393773155 geckodriver INFO Listening on 127.0.0.1:55930 +1681393776188 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "559 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilexhiciK" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681393776526 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681393776530 Marionette INFO Listening on port 55938 +Read port: 55938 +WebDriver BiDi listening on ws://127.0.0.1:55931 +1681393776678 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofilexhiciK\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:55931/devtools/browser/52851fe2-6727-415c-aa65-c805afbd4cfb +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +1681393804925 Marionette INFO Stopped listening on port 55938 +Dynamically enable window occlusion 1 +1681394503924 geckodriver INFO Listening on 127.0.0.1:63086 +1681394507081 mozrunner::runner INFO Running command: "C:\\Program Files\\Mozilla Firefox\\firefox.exe" "--marionette" "--headless" "--remote-debugging-port" "630 ... "--remote-allow-hosts" "localhost" "-no-remote" "-profile" "C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileoBpe6C" +*** You are running in headless mode. +console.warn: services.settings: Ignoring preference override of remote settings server +console.warn: services.settings: Allow by setting MOZ_REMOTE_SETTINGS_DEVTOOLS=1 in the environment +1681394507428 Marionette INFO Marionette enabled +Dynamically enable window occlusion 0 +1681394507433 Marionette INFO Listening on port 63095 +Read port: 63095 +WebDriver BiDi listening on ws://127.0.0.1:63087 +1681394507595 RemoteAgent WARN TLS certificate errors will be ignored for this session +[GFX1-]: RenderCompositorSWGL failed mapping default framebuffer, no dt +console.warn: SearchSettings: "get: No settings file exists, new profile?" (new NotFoundError("Could not open the file at C:\\Users\\radvanyi\\AppData\\Local\\Temp\\rust_mozprofileoBpe6C\\search.json.mozlz4", (void 0))) +console.error: ({}) +DevTools listening on ws://127.0.0.1:63087/devtools/browser/d296b3eb-b837-4a50-88f3-61f132ec5fbc +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://access.clarivate.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: unreachable code after return statement +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +JavaScript warning: https://www.webofscience.com/3Z5dUt/R5N/j9C/AEQjeg/iufOzhhLawh7h7/IlZ7JyI/Ext/3RTRhdEU, line 1: WEBGL_debug_renderer_info is deprecated in Firefox and will be removed. Please use RENDERER. +console.warn: LoginRecipes: "Falling back to a synchronous message for: https://www.webofscience.com." +1681395725426 Marionette INFO Stopped listening on port 63095 +Dynamically enable window occlusion 1 diff --git a/WOS/wos_extract/wos_query_generator_simplesyntax.ipynb b/WOS/wos_extract/wos_query_generator_simplesyntax.ipynb index c1fcf0d..9bbd50f 100644 --- a/WOS/wos_extract/wos_query_generator_simplesyntax.ipynb +++ b/WOS/wos_extract/wos_query_generator_simplesyntax.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 47, + "execution_count": 29, "metadata": { "collapsed": true }, @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 30, "outputs": [], "source": [ "country_mode = \"CU\" #CU-country-region AU-address" @@ -27,7 +27,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 31, "outputs": [], "source": [ "# (TS=(\"artificial intelligence\") OR TS=(\"machine learning\") OR TS=(\"neural network\") OR TS=(\"big data\") OR TS=(\"deep learning\") OR TS=(\"computer vision\") OR TS=(\"pattern recognition\")) AND" @@ -38,7 +38,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 32, "outputs": [], "source": [ "keywords_source = r'..\\ai_scope_keywords.txt'\n", @@ -51,13 +51,13 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 33, "outputs": [ { "data": { - "text/plain": "'artificial intelligence*,machine* learn*,neural network*,big data*,deep learn*,pattern recognition,computer vision,image classification,reinforcement learning,support vector machine*,recommender system*,random forest,ensemble model*,image processing,generative network*,ai ethic*,natural language processing,clustering algorithm*,feature extraction,time series forecast*,anomaly detection,identity fraud detection,dimensionality reduction,feature elicitation,chatbot*,clustering,*supervised learning,convolutional network*,convolutional neural,adversarial network*,adversarial neural,adversarial machine,autoencoder*,gated recurrent unit*,perceptron*,feature learning,feature engineering,long short-term memor*,word embedding*,word vector*,gradient descent,k-nearest neighbor*,naive bayes,transfer learning,fuzzy logic,backpropagation,computational modeling,computational statistic*,intelligent agent*,expert system*,decision tree*,Bayesian network*,genetic algorithm*,swarm intelligence,cognitive computing,artificial neural network*,convolutional neural network*,recurrent neural network*,ensemble learning,data mining,artificial general intelligence,artificial consciousness,evolutionary algorithm*,self-organizing map*,deep reinforcement learning,adversarial machine learning,machine vision,neural-symbolic integration,probabilistic graphical model*,hybrid intelligent system*,machine creativity,explainable AI,interactive machine learning,artificial emotional intelligence,evolutionary computation*,human-in-the-loop,unsupervised deep learning,deep belief network*,quantum machine learning,artificial immune system*,swarm robotics,autonomous agents,machine ethics,collaborative filtering,content based filtering,pervasive computing,ubiquitous computing,human-computer interaction,cloud computing,Internet of Things,artificial cognition,computational creativity,sentiment analy*,robotics,boltzmann machine*,kernel machine*,Hopfield network*,Hebbian learning,latent factor model*,non-negative matrix factorization,independent component analysis,principal component analysis,data augmentation,image segmentation,autoregressive language model*,generative pre-trained transformer*,smart city,smart home,smart grid,smart health,smart manufacturing,smart agriculture,smart environment,smart energy,smart mobility,smart buildings,smart tourism,smart logistics,smart supply chain,smart retail,smart waste management,smart parking,smart governance,smart education,smart technolog*,smart diagnostic*,data* analytic*,hadoop*,mapreduce,map$reduce,large$ dataset*,data warehouse*,predictive analytic*,no$sql,nosql,no sql,unstructured data*,data science*,facial recognition,t$SNE,KNN,singular value decomposition,regularization,turing test,computational learning theory,backward chaining,forward chaining,entity annotation,entity extraction,scalable computing,expectation maximization algorithm*,markov chain,markov process,markov decision process,monte carlo method,bayesian interference,kernel method,eigendecomposition,eigen decomposition,kernel method,radial basis function,QR decomposition,LU decomposition,Cholesky decomposition,spectral theorem,model selection,lagrange multiplier,convex optimization,nonlinear optimization,L? regulari*,ridge regression,gaussian process'" + "text/plain": "'artificial intelligence*,machine* learn*,neural network*,big data*,deep learn*,pattern recognition,computer vision,image classification,reinforcement learning,support vector machine*,recommender system*,random forest*,ensemble model*,image processing,generative network*,ai ethic*,natural language processing,clustering algorithm*,feature extraction,time series forecast*,anomaly detection,identity fraud detection,dimensionality reduction,feature elicitation,chatbot*,clustering,*supervised learning,convolutional network*,convolutional neural,adversarial network*,adversarial neural,adversarial machine*,autoencoder*,gated recurrent unit*,perceptron*,feature learning,feature engineering,long short-term memor*,word embedding*,word vector*,gradient descent,k-nearest neighbor*,naive bayes,transfer learning,fuzzy logic*,backpropagation,computational modeling,computational statistic*,intelligent agent*,expert system*,decision tree*,Bayesian network*,genetic algorithm*,swarm intelligence,cognitive computing,artificial neural network*,convolutional neural network*,recurrent neural network*,ensemble learning,data mining,artificial general intelligence,artificial consciousness,evolutionary algorithm*,self-organizing map*,deep reinforcement learning,adversarial machine learning,machine vision,neural-symbolic integration,probabilistic graphical model*,hybrid intelligent system*,machine creativity,explainable AI,interactive machine learning,artificial emotional intelligence,evolutionary computation*,human-in-the-loop,unsupervised deep learning,deep belief network*,quantum machine learning,artificial immune system*,swarm robotics,autonomous agent*,machine ethic*,collaborative filtering,content based filtering,pervasive computing,ubiquitous computing,human-computer interaction,cloud computing,Internet of Things,artificial cognition,computational creativity,sentiment analy*,robotics,boltzmann machine*,kernel machine*,Hopfield network*,Hebbian learning,latent factor model*,non-negative matrix factorization,independent component analysis,principal component analysis,data augmentation,image segmentation,autoregressive language model*,generative pre-trained transformer*,smart city,smart home,smart grid,smart health,smart manufacturing,smart agriculture,smart environment,smart energy,smart mobility,smart buildings,smart tourism,smart logistics,smart supply chain,smart retail,smart waste management,smart parking,smart governance,smart education,smart technolog*,smart diagnostic*,data* analytic*,hadoop*,mapreduce,map$reduce,large$ dataset*,data warehouse*,predictive analytic*,no$sql,nosql,no sql,unstructured data*,data science*,facial recognition,t$SNE,KNN,singular value decomposition,regularization,turing test,computational learning theory,backward chaining,forward chaining,entity annotation,entity extraction,scalable computing,expectation maximization algorithm*,markov chain,markov process,markov decision process,monte carlo method,bayesian inference,kernel method,eigendecomposition,eigen decomposition,radial basis function,QR decomposition,LU decomposition,Cholesky decomposition,spectral theorem,model selection,lagrange multiplier,convex optimization,nonlinear optimization,L? regulari*,ridge regression,gaussian process,manifold learning,locally linear embedding*,vector database*,vector embedding*,text mining,human-robot interact*,semantic web*,fuzzy set*,face recognition &! brain,object detection &! brain,multi agent system*,speech recognition &! brain,brain computer interface,intelligent robot*,remote sensing,image reconstruction,representation learning,data augmentation,adversarial robustness,meta learning,learning system,adversarial training,adversarial example*,generative model*,large langauge model*,few shot learning,image representation,optimization algorithm,swarm optimization,variational inference,kalman network*,knowledge distillation,kernel learning,classifier,lasso regression'" }, - "execution_count": 51, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -71,21 +71,45 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 34, + "outputs": [], + "source": [ + "keywords = [c.strip() for c in keywords.split(\",\")]" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 35, + "outputs": [], + "source": [ + "def wos_kw_formatter(text):\n", + " if \"&!\" in text:\n", + " return('('+' NOT '.join('\\\"'+sub_text.strip()+'\\\"' for sub_text in text.split('&!'))+')')\n", + " else:\n", + " return '\\\"'+text+'\\\"'\n" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 36, "outputs": [ { "data": { - "text/plain": "'\"artificial intelligence*\" OR \"machine* learn*\" OR \"neural network*\" OR \"big data*\" OR \"deep learn*\" OR \"pattern recognition\" OR \"computer vision\" OR \"image classification\" OR \"reinforcement learning\" OR \"support vector machine*\" OR \"recommender system*\" OR \"random forest\" OR \"ensemble model*\" OR \"image processing\" OR \"generative network*\" OR \"ai ethic*\" OR \"natural language processing\" OR \"clustering algorithm*\" OR \"feature extraction\" OR \"time series forecast*\" OR \"anomaly detection\" OR \"identity fraud detection\" OR \"dimensionality reduction\" OR \"feature elicitation\" OR \"chatbot*\" OR \"clustering\" OR \"*supervised learning\" OR \"convolutional network*\" OR \"convolutional neural\" OR \"adversarial network*\" OR \"adversarial neural\" OR \"adversarial machine\" OR \"autoencoder*\" OR \"gated recurrent unit*\" OR \"perceptron*\" OR \"feature learning\" OR \"feature engineering\" OR \"long short-term memor*\" OR \"word embedding*\" OR \"word vector*\" OR \"gradient descent\" OR \"k-nearest neighbor*\" OR \"naive bayes\" OR \"transfer learning\" OR \"fuzzy logic\" OR \"backpropagation\" OR \"computational modeling\" OR \"computational statistic*\" OR \"intelligent agent*\" OR \"expert system*\" OR \"decision tree*\" OR \"Bayesian network*\" OR \"genetic algorithm*\" OR \"swarm intelligence\" OR \"cognitive computing\" OR \"artificial neural network*\" OR \"convolutional neural network*\" OR \"recurrent neural network*\" OR \"ensemble learning\" OR \"data mining\" OR \"artificial general intelligence\" OR \"artificial consciousness\" OR \"evolutionary algorithm*\" OR \"self-organizing map*\" OR \"deep reinforcement learning\" OR \"adversarial machine learning\" OR \"machine vision\" OR \"neural-symbolic integration\" OR \"probabilistic graphical model*\" OR \"hybrid intelligent system*\" OR \"machine creativity\" OR \"explainable AI\" OR \"interactive machine learning\" OR \"artificial emotional intelligence\" OR \"evolutionary computation*\" OR \"human-in-the-loop\" OR \"unsupervised deep learning\" OR \"deep belief network*\" OR \"quantum machine learning\" OR \"artificial immune system*\" OR \"swarm robotics\" OR \"autonomous agents\" OR \"machine ethics\" OR \"collaborative filtering\" OR \"content based filtering\" OR \"pervasive computing\" OR \"ubiquitous computing\" OR \"human-computer interaction\" OR \"cloud computing\" OR \"Internet of Things\" OR \"artificial cognition\" OR \"computational creativity\" OR \"sentiment analy*\" OR \"robotics\" OR \"boltzmann machine*\" OR \"kernel machine*\" OR \"Hopfield network*\" OR \"Hebbian learning\" OR \"latent factor model*\" OR \"non-negative matrix factorization\" OR \"independent component analysis\" OR \"principal component analysis\" OR \"data augmentation\" OR \"image segmentation\" OR \"autoregressive language model*\" OR \"generative pre-trained transformer*\" OR \"smart city\" OR \"smart home\" OR \"smart grid\" OR \"smart health\" OR \"smart manufacturing\" OR \"smart agriculture\" OR \"smart environment\" OR \"smart energy\" OR \"smart mobility\" OR \"smart buildings\" OR \"smart tourism\" OR \"smart logistics\" OR \"smart supply chain\" OR \"smart retail\" OR \"smart waste management\" OR \"smart parking\" OR \"smart governance\" OR \"smart education\" OR \"smart technolog*\" OR \"smart diagnostic*\" OR \"data* analytic*\" OR \"hadoop*\" OR \"mapreduce\" OR \"map$reduce\" OR \"large$ dataset*\" OR \"data warehouse*\" OR \"predictive analytic*\" OR \"no$sql\" OR \"nosql\" OR \"no sql\" OR \"unstructured data*\" OR \"data science*\" OR \"facial recognition\" OR \"t$SNE\" OR \"KNN\" OR \"singular value decomposition\" OR \"regularization\" OR \"turing test\" OR \"computational learning theory\" OR \"backward chaining\" OR \"forward chaining\" OR \"entity annotation\" OR \"entity extraction\" OR \"scalable computing\" OR \"expectation maximization algorithm*\" OR \"markov chain\" OR \"markov process\" OR \"markov decision process\" OR \"monte carlo method\" OR \"bayesian interference\" OR \"kernel method\" OR \"eigendecomposition\" OR \"eigen decomposition\" OR \"kernel method\" OR \"radial basis function\" OR \"QR decomposition\" OR \"LU decomposition\" OR \"Cholesky decomposition\" OR \"spectral theorem\" OR \"model selection\" OR \"lagrange multiplier\" OR \"convex optimization\" OR \"nonlinear optimization\" OR \"L? regulari*\" OR \"ridge regression\" OR \"gaussian process\"'" + "text/plain": "'\"artificial intelligence*\" OR \"machine* learn*\" OR \"neural network*\" OR \"big data*\" OR \"deep learn*\" OR \"pattern recognition\" OR \"computer vision\" OR \"image classification\" OR \"reinforcement learning\" OR \"support vector machine*\" OR \"recommender system*\" OR \"random forest*\" OR \"ensemble model*\" OR \"image processing\" OR \"generative network*\" OR \"ai ethic*\" OR \"natural language processing\" OR \"clustering algorithm*\" OR \"feature extraction\" OR \"time series forecast*\" OR \"anomaly detection\" OR \"identity fraud detection\" OR \"dimensionality reduction\" OR \"feature elicitation\" OR \"chatbot*\" OR \"clustering\" OR \"*supervised learning\" OR \"convolutional network*\" OR \"convolutional neural\" OR \"adversarial network*\" OR \"adversarial neural\" OR \"adversarial machine*\" OR \"autoencoder*\" OR \"gated recurrent unit*\" OR \"perceptron*\" OR \"feature learning\" OR \"feature engineering\" OR \"long short-term memor*\" OR \"word embedding*\" OR \"word vector*\" OR \"gradient descent\" OR \"k-nearest neighbor*\" OR \"naive bayes\" OR \"transfer learning\" OR \"fuzzy logic*\" OR \"backpropagation\" OR \"computational modeling\" OR \"computational statistic*\" OR \"intelligent agent*\" OR \"expert system*\" OR \"decision tree*\" OR \"Bayesian network*\" OR \"genetic algorithm*\" OR \"swarm intelligence\" OR \"cognitive computing\" OR \"artificial neural network*\" OR \"convolutional neural network*\" OR \"recurrent neural network*\" OR \"ensemble learning\" OR \"data mining\" OR \"artificial general intelligence\" OR \"artificial consciousness\" OR \"evolutionary algorithm*\" OR \"self-organizing map*\" OR \"deep reinforcement learning\" OR \"adversarial machine learning\" OR \"machine vision\" OR \"neural-symbolic integration\" OR \"probabilistic graphical model*\" OR \"hybrid intelligent system*\" OR \"machine creativity\" OR \"explainable AI\" OR \"interactive machine learning\" OR \"artificial emotional intelligence\" OR \"evolutionary computation*\" OR \"human-in-the-loop\" OR \"unsupervised deep learning\" OR \"deep belief network*\" OR \"quantum machine learning\" OR \"artificial immune system*\" OR \"swarm robotics\" OR \"autonomous agent*\" OR \"machine ethic*\" OR \"collaborative filtering\" OR \"content based filtering\" OR \"pervasive computing\" OR \"ubiquitous computing\" OR \"human-computer interaction\" OR \"cloud computing\" OR \"Internet of Things\" OR \"artificial cognition\" OR \"computational creativity\" OR \"sentiment analy*\" OR \"robotics\" OR \"boltzmann machine*\" OR \"kernel machine*\" OR \"Hopfield network*\" OR \"Hebbian learning\" OR \"latent factor model*\" OR \"non-negative matrix factorization\" OR \"independent component analysis\" OR \"principal component analysis\" OR \"data augmentation\" OR \"image segmentation\" OR \"autoregressive language model*\" OR \"generative pre-trained transformer*\" OR \"smart city\" OR \"smart home\" OR \"smart grid\" OR \"smart health\" OR \"smart manufacturing\" OR \"smart agriculture\" OR \"smart environment\" OR \"smart energy\" OR \"smart mobility\" OR \"smart buildings\" OR \"smart tourism\" OR \"smart logistics\" OR \"smart supply chain\" OR \"smart retail\" OR \"smart waste management\" OR \"smart parking\" OR \"smart governance\" OR \"smart education\" OR \"smart technolog*\" OR \"smart diagnostic*\" OR \"data* analytic*\" OR \"hadoop*\" OR \"mapreduce\" OR \"map$reduce\" OR \"large$ dataset*\" OR \"data warehouse*\" OR \"predictive analytic*\" OR \"no$sql\" OR \"nosql\" OR \"no sql\" OR \"unstructured data*\" OR \"data science*\" OR \"facial recognition\" OR \"t$SNE\" OR \"KNN\" OR \"singular value decomposition\" OR \"regularization\" OR \"turing test\" OR \"computational learning theory\" OR \"backward chaining\" OR \"forward chaining\" OR \"entity annotation\" OR \"entity extraction\" OR \"scalable computing\" OR \"expectation maximization algorithm*\" OR \"markov chain\" OR \"markov process\" OR \"markov decision process\" OR \"monte carlo method\" OR \"bayesian inference\" OR \"kernel method\" OR \"eigendecomposition\" OR \"eigen decomposition\" OR \"radial basis function\" OR \"QR decomposition\" OR \"LU decomposition\" OR \"Cholesky decomposition\" OR \"spectral theorem\" OR \"model selection\" OR \"lagrange multiplier\" OR \"convex optimization\" OR \"nonlinear optimization\" OR \"L? regulari*\" OR \"ridge regression\" OR \"gaussian process\" OR \"manifold learning\" OR \"locally linear embedding*\" OR \"vector database*\" OR \"vector embedding*\" OR \"text mining\" OR \"human-robot interact*\" OR \"semantic web*\" OR \"fuzzy set*\" OR (\"face recognition\" NOT \"brain\") OR (\"object detection\" NOT \"brain\") OR \"multi agent system*\" OR (\"speech recognition\" NOT \"brain\") OR \"brain computer interface\" OR \"intelligent robot*\" OR \"remote sensing\" OR \"image reconstruction\" OR \"representation learning\" OR \"data augmentation\" OR \"adversarial robustness\" OR \"meta learning\" OR \"learning system\" OR \"adversarial training\" OR \"adversarial example*\" OR \"generative model*\" OR \"large langauge model*\" OR \"few shot learning\" OR \"image representation\" OR \"optimization algorithm\" OR \"swarm optimization\" OR \"variational inference\" OR \"kalman network*\" OR \"knowledge distillation\" OR \"kernel learning\" OR \"classifier\" OR \"lasso regression\"'" }, - "execution_count": 52, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "keywords = [c.strip() for c in keywords.split(\",\")]\n", - "\n", - "keywords_str = ' OR '.join('\\\"'+k+'\\\"' for k in keywords)\n", + "keywords_str = ' OR '.join(wos_kw_formatter(k) for k in keywords)\n", "keywords_str" ], "metadata": { @@ -94,13 +118,13 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 37, "outputs": [ { "data": { - "text/plain": "172" + "text/plain": "206" }, - "execution_count": 53, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" } @@ -114,7 +138,16 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": 37, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 38, "outputs": [], "source": [ "scope_country_source = r'..\\eu_scope_countries.txt'\n", @@ -147,13 +180,13 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 39, "outputs": [ { "data": { "text/plain": "'AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND'" }, - "execution_count": 55, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } @@ -168,13 +201,13 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 40, "outputs": [ { "data": { "text/plain": "'PEOPLES R CHINA OR HONG KONG'" }, - "execution_count": 56, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } @@ -188,7 +221,7 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 40, "outputs": [], "source": [], "metadata": { @@ -197,7 +230,7 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 40, "outputs": [], "source": [], "metadata": { @@ -206,13 +239,13 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 41, "outputs": [ { "data": { - "text/plain": "'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"artificial intelligence*\" OR \"machine* learn*\" OR \"neural network*\" OR \"big data*\" OR \"deep learn*\" OR \"pattern recognition\" OR \"computer vision\" OR \"image classification\" OR \"reinforcement learning\" OR \"support vector machine*\" OR \"recommender system*\" OR \"random forest\" OR \"ensemble model*\" OR \"image processing\" OR \"generative network*\" OR \"ai ethic*\" OR \"natural language processing\" OR \"clustering algorithm*\" OR \"feature extraction\" OR \"time series forecast*\" OR \"anomaly detection\" OR \"identity fraud detection\" OR \"dimensionality reduction\" OR \"feature elicitation\" OR \"chatbot*\" OR \"clustering\" OR \"*supervised learning\" OR \"convolutional network*\" OR \"convolutional neural\" OR \"adversarial network*\" OR \"adversarial neural\" OR \"adversarial machine\" OR \"autoencoder*\" OR \"gated recurrent unit*\" OR \"perceptron*\" OR \"feature learning\" OR \"feature engineering\" OR \"long short-term memor*\" OR \"word embedding*\" OR \"word vector*\" OR \"gradient descent\" OR \"k-nearest neighbor*\" OR \"naive bayes\" OR \"transfer learning\" OR \"fuzzy logic\" OR \"backpropagation\" OR \"computational modeling\" OR \"computational statistic*\" OR \"intelligent agent*\" OR \"expert system*\" OR \"decision tree*\" OR \"Bayesian network*\" OR \"genetic algorithm*\" OR \"swarm intelligence\" OR \"cognitive computing\" OR \"artificial neural network*\" OR \"convolutional neural network*\" OR \"recurrent neural network*\" OR \"ensemble learning\" OR \"data mining\" OR \"artificial general intelligence\" OR \"artificial consciousness\" OR \"evolutionary algorithm*\" OR \"self-organizing map*\" OR \"deep reinforcement learning\" OR \"adversarial machine learning\" OR \"machine vision\" OR \"neural-symbolic integration\" OR \"probabilistic graphical model*\" OR \"hybrid intelligent system*\" OR \"machine creativity\" OR \"explainable AI\" OR \"interactive machine learning\" OR \"artificial emotional intelligence\" OR \"evolutionary computation*\" OR \"human-in-the-loop\" OR \"unsupervised deep learning\" OR \"deep belief network*\" OR \"quantum machine learning\" OR \"artificial immune system*\" OR \"swarm robotics\" OR \"autonomous agents\" OR \"machine ethics\" OR \"collaborative filtering\" OR \"content based filtering\" OR \"pervasive computing\" OR \"ubiquitous computing\" OR \"human-computer interaction\" OR \"cloud computing\" OR \"Internet of Things\" OR \"artificial cognition\" OR \"computational creativity\" OR \"sentiment analy*\" OR \"robotics\" OR \"boltzmann machine*\" OR \"kernel machine*\" OR \"Hopfield network*\" OR \"Hebbian learning\" OR \"latent factor model*\" OR \"non-negative matrix factorization\" OR \"independent component analysis\" OR \"principal component analysis\" OR \"data augmentation\" OR \"image segmentation\" OR \"autoregressive language model*\" OR \"generative pre-trained transformer*\" OR \"smart city\" OR \"smart home\" OR \"smart grid\" OR \"smart health\" OR \"smart manufacturing\" OR \"smart agriculture\" OR \"smart environment\" OR \"smart energy\" OR \"smart mobility\" OR \"smart buildings\" OR \"smart tourism\" OR \"smart logistics\" OR \"smart supply chain\" OR \"smart retail\" OR \"smart waste management\" OR \"smart parking\" OR \"smart governance\" OR \"smart education\" OR \"smart technolog*\" OR \"smart diagnostic*\" OR \"data* analytic*\" OR \"hadoop*\" OR \"mapreduce\" OR \"map$reduce\" OR \"large$ dataset*\" OR \"data warehouse*\" OR \"predictive analytic*\" OR \"no$sql\" OR \"nosql\" OR \"no sql\" OR \"unstructured data*\" OR \"data science*\" OR \"facial recognition\" OR \"t$SNE\" OR \"KNN\" OR \"singular value decomposition\" OR \"regularization\" OR \"turing test\" OR \"computational learning theory\" OR \"backward chaining\" OR \"forward chaining\" OR \"entity annotation\" OR \"entity extraction\" OR \"scalable computing\" OR \"expectation maximization algorithm*\" OR \"markov chain\" OR \"markov process\" OR \"markov decision process\" OR \"monte carlo method\" OR \"bayesian interference\" OR \"kernel method\" OR \"eigendecomposition\" OR \"eigen decomposition\" OR \"kernel method\" OR \"radial basis function\" OR \"QR decomposition\" OR \"LU decomposition\" OR \"Cholesky decomposition\" OR \"spectral theorem\" OR \"model selection\" OR \"lagrange multiplier\" OR \"convex optimization\" OR \"nonlinear optimization\" OR \"L? regulari*\" OR \"ridge regression\" OR \"gaussian process\") AND PY=(2011-2022)'" + "text/plain": "'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"artificial intelligence*\" OR \"machine* learn*\" OR \"neural network*\" OR \"big data*\" OR \"deep learn*\" OR \"pattern recognition\" OR \"computer vision\" OR \"image classification\" OR \"reinforcement learning\" OR \"support vector machine*\" OR \"recommender system*\" OR \"random forest*\" OR \"ensemble model*\" OR \"image processing\" OR \"generative network*\" OR \"ai ethic*\" OR \"natural language processing\" OR \"clustering algorithm*\" OR \"feature extraction\" OR \"time series forecast*\" OR \"anomaly detection\" OR \"identity fraud detection\" OR \"dimensionality reduction\" OR \"feature elicitation\" OR \"chatbot*\" OR \"clustering\" OR \"*supervised learning\" OR \"convolutional network*\" OR \"convolutional neural\" OR \"adversarial network*\" OR \"adversarial neural\" OR \"adversarial machine*\" OR \"autoencoder*\" OR \"gated recurrent unit*\" OR \"perceptron*\" OR \"feature learning\" OR \"feature engineering\" OR \"long short-term memor*\" OR \"word embedding*\" OR \"word vector*\" OR \"gradient descent\" OR \"k-nearest neighbor*\" OR \"naive bayes\" OR \"transfer learning\" OR \"fuzzy logic*\" OR \"backpropagation\" OR \"computational modeling\" OR \"computational statistic*\" OR \"intelligent agent*\" OR \"expert system*\" OR \"decision tree*\" OR \"Bayesian network*\" OR \"genetic algorithm*\" OR \"swarm intelligence\" OR \"cognitive computing\" OR \"artificial neural network*\" OR \"convolutional neural network*\" OR \"recurrent neural network*\" OR \"ensemble learning\" OR \"data mining\" OR \"artificial general intelligence\" OR \"artificial consciousness\" OR \"evolutionary algorithm*\" OR \"self-organizing map*\" OR \"deep reinforcement learning\" OR \"adversarial machine learning\" OR \"machine vision\" OR \"neural-symbolic integration\" OR \"probabilistic graphical model*\" OR \"hybrid intelligent system*\" OR \"machine creativity\" OR \"explainable AI\" OR \"interactive machine learning\" OR \"artificial emotional intelligence\" OR \"evolutionary computation*\" OR \"human-in-the-loop\" OR \"unsupervised deep learning\" OR \"deep belief network*\" OR \"quantum machine learning\" OR \"artificial immune system*\" OR \"swarm robotics\" OR \"autonomous agent*\" OR \"machine ethic*\" OR \"collaborative filtering\" OR \"content based filtering\" OR \"pervasive computing\" OR \"ubiquitous computing\" OR \"human-computer interaction\" OR \"cloud computing\" OR \"Internet of Things\" OR \"artificial cognition\" OR \"computational creativity\" OR \"sentiment analy*\" OR \"robotics\" OR \"boltzmann machine*\" OR \"kernel machine*\" OR \"Hopfield network*\" OR \"Hebbian learning\" OR \"latent factor model*\" OR \"non-negative matrix factorization\" OR \"independent component analysis\" OR \"principal component analysis\" OR \"data augmentation\" OR \"image segmentation\" OR \"autoregressive language model*\" OR \"generative pre-trained transformer*\" OR \"smart city\" OR \"smart home\" OR \"smart grid\" OR \"smart health\" OR \"smart manufacturing\" OR \"smart agriculture\" OR \"smart environment\" OR \"smart energy\" OR \"smart mobility\" OR \"smart buildings\" OR \"smart tourism\" OR \"smart logistics\" OR \"smart supply chain\" OR \"smart retail\" OR \"smart waste management\" OR \"smart parking\" OR \"smart governance\" OR \"smart education\" OR \"smart technolog*\" OR \"smart diagnostic*\" OR \"data* analytic*\" OR \"hadoop*\" OR \"mapreduce\" OR \"map$reduce\" OR \"large$ dataset*\" OR \"data warehouse*\" OR \"predictive analytic*\" OR \"no$sql\" OR \"nosql\" OR \"no sql\" OR \"unstructured data*\" OR \"data science*\" OR \"facial recognition\" OR \"t$SNE\" OR \"KNN\" OR \"singular value decomposition\" OR \"regularization\" OR \"turing test\" OR \"computational learning theory\" OR \"backward chaining\" OR \"forward chaining\" OR \"entity annotation\" OR \"entity extraction\" OR \"scalable computing\" OR \"expectation maximization algorithm*\" OR \"markov chain\" OR \"markov process\" OR \"markov decision process\" OR \"monte carlo method\" OR \"bayesian inference\" OR \"kernel method\" OR \"eigendecomposition\" OR \"eigen decomposition\" OR \"radial basis function\" OR \"QR decomposition\" OR \"LU decomposition\" OR \"Cholesky decomposition\" OR \"spectral theorem\" OR \"model selection\" OR \"lagrange multiplier\" OR \"convex optimization\" OR \"nonlinear optimization\" OR \"L? regulari*\" OR \"ridge regression\" OR \"gaussian process\" OR \"manifold learning\" OR \"locally linear embedding*\" OR \"vector database*\" OR \"vector embedding*\" OR \"text mining\" OR \"human-robot interact*\" OR \"semantic web*\" OR \"fuzzy set*\" OR (\"face recognition\" NOT \"brain\") OR (\"object detection\" NOT \"brain\") OR \"multi agent system*\" OR (\"speech recognition\" NOT \"brain\") OR \"brain computer interface\" OR \"intelligent robot*\" OR \"remote sensing\" OR \"image reconstruction\" OR \"representation learning\" OR \"data augmentation\" OR \"adversarial robustness\" OR \"meta learning\" OR \"learning system\" OR \"adversarial training\" OR \"adversarial example*\" OR \"generative model*\" OR \"large langauge model*\" OR \"few shot learning\" OR \"image representation\" OR \"optimization algorithm\" OR \"swarm optimization\" OR \"variational inference\" OR \"kalman network*\" OR \"knowledge distillation\" OR \"kernel learning\" OR \"classifier\" OR \"lasso regression\") AND PY=(2011-2022)'" }, - "execution_count": 57, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" } @@ -227,7 +260,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 42, "outputs": [], "source": [ "from wossel_miners import wos_fetch_entries,wos_fetch_yearly_output" @@ -238,7 +271,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 43, "outputs": [], "source": [ "keywords_sub_str = keywords_str.split(' OR ')" @@ -249,13 +282,13 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 44, "outputs": [ { "data": { - "text/plain": "['\"identity fraud detection\"',\n '\"dimensionality reduction\"',\n '\"feature elicitation\"',\n '\"chatbot*\"',\n '\"clustering\"',\n '\"*supervised learning\"',\n '\"convolutional network*\"',\n '\"convolutional neural\"',\n '\"adversarial network*\"',\n '\"adversarial neural\"',\n '\"adversarial machine\"',\n '\"autoencoder*\"',\n '\"gated recurrent unit*\"',\n '\"perceptron*\"',\n '\"feature learning\"',\n '\"feature engineering\"',\n '\"long short-term memor*\"',\n '\"word embedding*\"',\n '\"word vector*\"',\n '\"gradient descent\"',\n '\"k-nearest neighbor*\"',\n '\"naive bayes\"',\n '\"transfer learning\"',\n '\"fuzzy logic\"',\n '\"backpropagation\"',\n '\"computational modeling\"',\n '\"computational statistic*\"',\n '\"intelligent agent*\"',\n '\"expert system*\"',\n '\"decision tree*\"',\n '\"Bayesian network*\"',\n '\"genetic algorithm*\"',\n '\"swarm intelligence\"',\n '\"cognitive computing\"',\n '\"artificial neural network*\"',\n '\"convolutional neural network*\"',\n '\"recurrent neural network*\"',\n '\"ensemble learning\"',\n '\"data mining\"',\n '\"artificial general intelligence\"',\n '\"artificial consciousness\"',\n '\"evolutionary algorithm*\"',\n '\"self-organizing map*\"',\n '\"deep reinforcement learning\"',\n '\"adversarial machine learning\"',\n '\"machine vision\"',\n '\"neural-symbolic integration\"',\n '\"probabilistic graphical model*\"',\n '\"hybrid intelligent system*\"',\n '\"machine creativity\"',\n '\"explainable AI\"',\n '\"interactive machine learning\"',\n '\"artificial emotional intelligence\"',\n '\"evolutionary computation*\"',\n '\"human-in-the-loop\"',\n '\"unsupervised deep learning\"',\n '\"deep belief network*\"',\n '\"quantum machine learning\"',\n '\"artificial immune system*\"',\n '\"swarm robotics\"',\n '\"autonomous agents\"',\n '\"machine ethics\"',\n '\"collaborative filtering\"',\n '\"content based filtering\"',\n '\"pervasive computing\"',\n '\"ubiquitous computing\"',\n '\"human-computer interaction\"',\n '\"cloud computing\"',\n '\"Internet of Things\"',\n '\"artificial cognition\"',\n '\"computational creativity\"',\n '\"sentiment analy*\"',\n '\"robotics\"',\n '\"boltzmann machine*\"',\n '\"kernel machine*\"',\n '\"Hopfield network*\"',\n '\"Hebbian learning\"',\n '\"latent factor model*\"',\n '\"non-negative matrix factorization\"',\n '\"independent component analysis\"',\n '\"principal component analysis\"',\n '\"data augmentation\"',\n '\"image segmentation\"',\n '\"autoregressive language model*\"',\n '\"generative pre-trained transformer*\"',\n '\"smart city\"',\n '\"smart home\"',\n '\"smart grid\"',\n '\"smart health\"',\n '\"smart manufacturing\"',\n '\"smart agriculture\"',\n '\"smart environment\"',\n '\"smart energy\"',\n '\"smart mobility\"',\n '\"smart buildings\"',\n '\"smart tourism\"',\n '\"smart logistics\"',\n '\"smart supply chain\"',\n '\"smart retail\"',\n '\"smart waste management\"',\n '\"smart parking\"',\n '\"smart governance\"',\n '\"smart education\"',\n '\"smart technolog*\"',\n '\"smart diagnostic*\"',\n '\"data* analytic*\"',\n '\"hadoop*\"',\n '\"mapreduce\"',\n '\"map$reduce\"',\n '\"large$ dataset*\"',\n '\"data warehouse*\"',\n '\"predictive analytic*\"',\n '\"no$sql\"',\n '\"nosql\"',\n '\"no sql\"',\n '\"unstructured data*\"',\n '\"data science*\"',\n '\"facial recognition\"',\n '\"t$SNE\"',\n '\"KNN\"',\n '\"singular value decomposition\"',\n '\"regularization\"',\n '\"turing test\"',\n '\"computational learning theory\"',\n '\"backward chaining\"',\n '\"forward chaining\"',\n '\"entity annotation\"',\n '\"entity extraction\"',\n '\"scalable computing\"',\n '\"expectation maximization algorithm*\"',\n '\"markov chain\"',\n '\"markov process\"',\n '\"markov decision process\"',\n '\"monte carlo method\"',\n '\"bayesian interference\"',\n '\"kernel method\"',\n '\"eigendecomposition\"',\n '\"eigen decomposition\"',\n '\"kernel method\"',\n '\"radial basis function\"',\n '\"QR decomposition\"',\n '\"LU decomposition\"',\n '\"Cholesky decomposition\"',\n '\"spectral theorem\"',\n '\"model selection\"',\n '\"lagrange multiplier\"',\n '\"convex optimization\"',\n '\"nonlinear optimization\"',\n '\"L? regulari*\"',\n '\"ridge regression\"',\n '\"gaussian process\"']" + "text/plain": "['\"identity fraud detection\"',\n '\"dimensionality reduction\"',\n '\"feature elicitation\"',\n '\"chatbot*\"',\n '\"clustering\"',\n '\"*supervised learning\"',\n '\"convolutional network*\"',\n '\"convolutional neural\"',\n '\"adversarial network*\"',\n '\"adversarial neural\"',\n '\"adversarial machine*\"',\n '\"autoencoder*\"',\n '\"gated recurrent unit*\"',\n '\"perceptron*\"',\n '\"feature learning\"',\n '\"feature engineering\"',\n '\"long short-term memor*\"',\n '\"word embedding*\"',\n '\"word vector*\"',\n '\"gradient descent\"',\n '\"k-nearest neighbor*\"',\n '\"naive bayes\"',\n '\"transfer learning\"',\n '\"fuzzy logic*\"',\n '\"backpropagation\"',\n '\"computational modeling\"',\n '\"computational statistic*\"',\n '\"intelligent agent*\"',\n '\"expert system*\"',\n '\"decision tree*\"',\n '\"Bayesian network*\"',\n '\"genetic algorithm*\"',\n '\"swarm intelligence\"',\n '\"cognitive computing\"',\n '\"artificial neural network*\"',\n '\"convolutional neural network*\"',\n '\"recurrent neural network*\"',\n '\"ensemble learning\"',\n '\"data mining\"',\n '\"artificial general intelligence\"',\n '\"artificial consciousness\"',\n '\"evolutionary algorithm*\"',\n '\"self-organizing map*\"',\n '\"deep reinforcement learning\"',\n '\"adversarial machine learning\"',\n '\"machine vision\"',\n '\"neural-symbolic integration\"',\n '\"probabilistic graphical model*\"',\n '\"hybrid intelligent system*\"',\n '\"machine creativity\"',\n '\"explainable AI\"',\n '\"interactive machine learning\"',\n '\"artificial emotional intelligence\"',\n '\"evolutionary computation*\"',\n '\"human-in-the-loop\"',\n '\"unsupervised deep learning\"',\n '\"deep belief network*\"',\n '\"quantum machine learning\"',\n '\"artificial immune system*\"',\n '\"swarm robotics\"',\n '\"autonomous agent*\"',\n '\"machine ethic*\"',\n '\"collaborative filtering\"',\n '\"content based filtering\"',\n '\"pervasive computing\"',\n '\"ubiquitous computing\"',\n '\"human-computer interaction\"',\n '\"cloud computing\"',\n '\"Internet of Things\"',\n '\"artificial cognition\"',\n '\"computational creativity\"',\n '\"sentiment analy*\"',\n '\"robotics\"',\n '\"boltzmann machine*\"',\n '\"kernel machine*\"',\n '\"Hopfield network*\"',\n '\"Hebbian learning\"',\n '\"latent factor model*\"',\n '\"non-negative matrix factorization\"',\n '\"independent component analysis\"',\n '\"principal component analysis\"',\n '\"data augmentation\"',\n '\"image segmentation\"',\n '\"autoregressive language model*\"',\n '\"generative pre-trained transformer*\"',\n '\"smart city\"',\n '\"smart home\"',\n '\"smart grid\"',\n '\"smart health\"',\n '\"smart manufacturing\"',\n '\"smart agriculture\"',\n '\"smart environment\"',\n '\"smart energy\"',\n '\"smart mobility\"',\n '\"smart buildings\"',\n '\"smart tourism\"',\n '\"smart logistics\"',\n '\"smart supply chain\"',\n '\"smart retail\"',\n '\"smart waste management\"',\n '\"smart parking\"',\n '\"smart governance\"',\n '\"smart education\"',\n '\"smart technolog*\"',\n '\"smart diagnostic*\"',\n '\"data* analytic*\"',\n '\"hadoop*\"',\n '\"mapreduce\"',\n '\"map$reduce\"',\n '\"large$ dataset*\"',\n '\"data warehouse*\"',\n '\"predictive analytic*\"',\n '\"no$sql\"',\n '\"nosql\"',\n '\"no sql\"',\n '\"unstructured data*\"',\n '\"data science*\"',\n '\"facial recognition\"',\n '\"t$SNE\"',\n '\"KNN\"',\n '\"singular value decomposition\"',\n '\"regularization\"',\n '\"turing test\"',\n '\"computational learning theory\"',\n '\"backward chaining\"',\n '\"forward chaining\"',\n '\"entity annotation\"',\n '\"entity extraction\"',\n '\"scalable computing\"',\n '\"expectation maximization algorithm*\"',\n '\"markov chain\"',\n '\"markov process\"',\n '\"markov decision process\"',\n '\"monte carlo method\"',\n '\"bayesian inference\"',\n '\"kernel method\"',\n '\"eigendecomposition\"',\n '\"eigen decomposition\"',\n '\"radial basis function\"',\n '\"QR decomposition\"',\n '\"LU decomposition\"',\n '\"Cholesky decomposition\"',\n '\"spectral theorem\"',\n '\"model selection\"',\n '\"lagrange multiplier\"',\n '\"convex optimization\"',\n '\"nonlinear optimization\"',\n '\"L? regulari*\"',\n '\"ridge regression\"',\n '\"gaussian process\"',\n '\"manifold learning\"',\n '\"locally linear embedding*\"',\n '\"vector database*\"',\n '\"vector embedding*\"',\n '\"text mining\"',\n '\"human-robot interact*\"',\n '\"semantic web*\"',\n '\"fuzzy set*\"',\n '(\"face recognition\" NOT \"brain\")',\n '(\"object detection\" NOT \"brain\")',\n '\"multi agent system*\"',\n '(\"speech recognition\" NOT \"brain\")',\n '\"brain computer interface\"',\n '\"intelligent robot*\"',\n '\"remote sensing\"',\n '\"image reconstruction\"',\n '\"representation learning\"',\n '\"data augmentation\"',\n '\"adversarial robustness\"',\n '\"meta learning\"',\n '\"learning system\"',\n '\"adversarial training\"',\n '\"adversarial example*\"',\n '\"generative model*\"',\n '\"large langauge model*\"',\n '\"few shot learning\"',\n '\"image representation\"',\n '\"optimization algorithm\"',\n '\"swarm optimization\"',\n '\"variational inference\"',\n '\"kalman network*\"',\n '\"knowledge distillation\"',\n '\"kernel learning\"',\n '\"classifier\"',\n '\"lasso regression\"']" }, - "execution_count": 60, + "execution_count": 44, "metadata": {}, "output_type": "execute_result" } @@ -269,19 +302,19 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 45, "outputs": [ { "data": { - "text/plain": "['\"entity extraction\"',\n '\"scalable computing\"',\n '\"expectation maximization algorithm*\"',\n '\"markov chain\"',\n '\"markov process\"',\n '\"markov decision process\"',\n '\"monte carlo method\"',\n '\"bayesian interference\"',\n '\"kernel method\"',\n '\"eigendecomposition\"',\n '\"eigen decomposition\"',\n '\"kernel method\"',\n '\"radial basis function\"',\n '\"QR decomposition\"',\n '\"LU decomposition\"',\n '\"Cholesky decomposition\"',\n '\"spectral theorem\"',\n '\"model selection\"',\n '\"lagrange multiplier\"',\n '\"convex optimization\"',\n '\"nonlinear optimization\"',\n '\"L? regulari*\"',\n '\"ridge regression\"',\n '\"gaussian process\"']" + "text/plain": "['\"manifold learning\"',\n '\"locally linear embedding*\"',\n '\"vector database*\"',\n '\"vector embedding*\"',\n '\"text mining\"',\n '\"human-robot interact*\"',\n '\"semantic web*\"',\n '\"fuzzy set*\"',\n '(\"face recognition\" NOT \"brain\")',\n '(\"object detection\" NOT \"brain\")',\n '\"multi agent system*\"',\n '(\"speech recognition\" NOT \"brain\")',\n '\"brain computer interface\"',\n '\"intelligent robot*\"',\n '\"remote sensing\"',\n '\"image reconstruction\"',\n '\"representation learning\"',\n '\"data augmentation\"',\n '\"adversarial robustness\"',\n '\"meta learning\"',\n '\"learning system\"',\n '\"adversarial training\"',\n '\"adversarial example*\"',\n '\"generative model*\"',\n '\"large langauge model*\"',\n '\"few shot learning\"',\n '\"image representation\"',\n '\"optimization algorithm\"',\n '\"swarm optimization\"',\n '\"variational inference\"',\n '\"kalman network*\"',\n '\"knowledge distillation\"',\n '\"kernel learning\"',\n '\"classifier\"',\n '\"lasso regression\"']" }, - "execution_count": 63, + "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "keywords_sub_str[148:]" + "keywords_sub_str[171:]" ], "metadata": { "collapsed": false @@ -298,345 +331,515 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 46, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"scalable computing\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"scalable computing\") AND PY=(2011-2022)')\n" + "('TS=(\"manifold learning\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"manifold learning\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:37<00:00, 18.67s/it]\n" + "100%|██████████| 2/2 [00:36<00:00, 18.40s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"expectation maximization algorithm*\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"expectation maximization algorithm*\") AND PY=(2011-2022)')\n" + "('TS=(\"locally linear embedding*\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"locally linear embedding*\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:45<00:00, 22.96s/it]\n" + "100%|██████████| 2/2 [00:39<00:00, 19.66s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"markov chain\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"markov chain\") AND PY=(2011-2022)')\n" + "('TS=(\"vector database*\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"vector database*\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:33<00:00, 16.91s/it]\n" + " 50%|█████ | 1/2 [01:05<01:05, 65.81s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"markov process\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"markov process\") AND PY=(2011-2022)')\n" + "No results\n", + "('TS=(\"vector embedding*\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"vector embedding*\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:49<00:00, 24.60s/it]\n" + "100%|██████████| 2/2 [00:47<00:00, 23.81s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"markov decision process\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"markov decision process\") AND PY=(2011-2022)')\n" + "('TS=(\"text mining\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"text mining\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:35<00:00, 17.87s/it]\n" + "100%|██████████| 2/2 [00:36<00:00, 18.40s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"monte carlo method\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"monte carlo method\") AND PY=(2011-2022)')\n" + "('TS=(\"human-robot interact*\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"human-robot interact*\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:45<00:00, 22.82s/it]\n" + "100%|██████████| 2/2 [00:43<00:00, 21.64s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"bayesian interference\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"bayesian interference\") AND PY=(2011-2022)')\n" + "('TS=(\"semantic web*\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"semantic web*\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - " 50%|█████ | 1/2 [01:03<01:03, 63.26s/it]\n" + "100%|██████████| 2/2 [00:36<00:00, 18.15s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "No results\n", - "('TS=(\"kernel method\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"kernel method\") AND PY=(2011-2022)')\n" + "('TS=(\"fuzzy set*\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"fuzzy set*\") AND PY=(2011-2022)')\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2/2 [00:44<00:00, 22.43s/it]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('TS=((\"face recognition\" NOT \"brain\")) AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=((\"face recognition\" NOT \"brain\")) AND PY=(2011-2022)')\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2/2 [00:35<00:00, 17.71s/it]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('TS=((\"object detection\" NOT \"brain\")) AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=((\"object detection\" NOT \"brain\")) AND PY=(2011-2022)')\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2/2 [00:36<00:00, 18.43s/it]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('TS=(\"multi agent system*\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"multi agent system*\") AND PY=(2011-2022)')\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2/2 [00:45<00:00, 22.80s/it]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('TS=((\"speech recognition\" NOT \"brain\")) AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=((\"speech recognition\" NOT \"brain\")) AND PY=(2011-2022)')\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2/2 [00:37<00:00, 18.81s/it]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('TS=(\"brain computer interface\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"brain computer interface\") AND PY=(2011-2022)')\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2/2 [00:43<00:00, 21.82s/it]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('TS=(\"intelligent robot*\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"intelligent robot*\") AND PY=(2011-2022)')\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2/2 [00:34<00:00, 17.30s/it]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('TS=(\"remote sensing\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"remote sensing\") AND PY=(2011-2022)')\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2/2 [00:46<00:00, 23.03s/it]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('TS=(\"image reconstruction\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"image reconstruction\") AND PY=(2011-2022)')\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2/2 [00:34<00:00, 17.31s/it]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('TS=(\"representation learning\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"representation learning\") AND PY=(2011-2022)')\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 2/2 [00:37<00:00, 18.52s/it]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('TS=(\"data augmentation\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"data augmentation\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:40<00:00, 20.06s/it]\n" + "100%|██████████| 2/2 [00:42<00:00, 21.36s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"eigendecomposition\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"eigendecomposition\") AND PY=(2011-2022)')\n" + "('TS=(\"adversarial robustness\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"adversarial robustness\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:35<00:00, 17.75s/it]\n" + "100%|██████████| 2/2 [00:37<00:00, 18.51s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"eigen decomposition\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"eigen decomposition\") AND PY=(2011-2022)')\n" + "('TS=(\"meta learning\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"meta learning\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:37<00:00, 18.63s/it]\n" + "100%|██████████| 2/2 [00:39<00:00, 19.80s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"kernel method\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"kernel method\") AND PY=(2011-2022)')\n" + "('TS=(\"learning system\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"learning system\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:46<00:00, 23.32s/it]\n" + "100%|██████████| 2/2 [00:37<00:00, 18.57s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"radial basis function\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"radial basis function\") AND PY=(2011-2022)')\n" + "('TS=(\"adversarial training\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"adversarial training\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:38<00:00, 19.34s/it]\n" + "100%|██████████| 2/2 [00:34<00:00, 17.21s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"QR decomposition\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"QR decomposition\") AND PY=(2011-2022)')\n" + "('TS=(\"adversarial example*\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"adversarial example*\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:49<00:00, 24.57s/it]\n" + "100%|██████████| 2/2 [00:36<00:00, 18.07s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"LU decomposition\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"LU decomposition\") AND PY=(2011-2022)')\n" + "('TS=(\"generative model*\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"generative model*\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:39<00:00, 19.85s/it]\n" + "100%|██████████| 2/2 [00:34<00:00, 17.48s/it]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "('TS=(\"Cholesky decomposition\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"Cholesky decomposition\") AND PY=(2011-2022)')\n" + "('TS=(\"large langauge model*\") AND PY=(2011-2022)', 'CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUSTRIA OR BELGIUM OR BULGARIA OR CROATIA OR CYPRUS OR CZECH REPUBLIC OR DENMARK OR ESTONIA OR FINLAND OR FRANCE OR GERMANY OR GREECE OR HUNGARY OR IRELAND OR ITALY OR LATVIA OR LITHUANIA OR LUXEMBOURG OR MALTA OR NETHERLANDS OR POLAND OR PORTUGAL OR ROMANIA OR SLOVAKIA OR SLOVENIA OR SPAIN OR SWEDEN OR NORWAY OR SWITZERLAND OR UNITED KINGDOM OR ENGLAND OR WALES OR SCOTLAND OR N IRELAND) AND TS=(\"large langauge model*\") AND PY=(2011-2022)')\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 2/2 [00:35<00:00, 17.96s/it]\n" + " 0%| | 0/2 [00:53\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
queryRecord Count
0CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST...972.0
1CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST...451.0
2CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST...12.0
3CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST...5.0
4CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST...2631.0
.........
275TS=(\"ubiquitous computing\") AND PY=(2011-2022)3655.0
276TS=(\"unstructured data*\") AND PY=(2011-2022)3386.0
277TS=(\"unsupervised deep learning\") AND PY=(2011...728.0
278TS=(\"word embedding*\") AND PY=(2011-2022)7068.0
279TS=(\"word vector*\") AND PY=(2011-2022)1747.0
\n

280 rows × 2 columns

\n" + "text/plain": " query Record Count\n0 CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST... 972.0\n1 CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST... 451.0\n2 CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST... 30.0\n3 CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST... 12.0\n4 CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST... 5.0\n.. ... ...\n384 TS=(\"word embedding*\") AND PY=(2011-2022) 7068.0\n385 TS=(\"word vector*\") AND PY=(2011-2022) 1747.0\n386 TS=((\"face recognition\" NOT \"brain\")) AND PY=(... 19690.0\n387 TS=((\"object detection\" NOT \"brain\")) AND PY=(... 28989.0\n388 TS=((\"speech recognition\" NOT \"brain\")) AND PY... 19912.0\n\n[389 rows x 2 columns]", + "text/html": "
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queryRecord Count
0CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST...972.0
1CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST...451.0
2CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST...30.0
3CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST...12.0
4CU=(PEOPLES R CHINA OR HONG KONG) AND CU=(AUST...5.0
.........
384TS=(\"word embedding*\") AND PY=(2011-2022)7068.0
385TS=(\"word vector*\") AND PY=(2011-2022)1747.0
386TS=((\"face recognition\" NOT \"brain\")) AND PY=(...19690.0
387TS=((\"object detection\" NOT \"brain\")) AND PY=(...28989.0
388TS=((\"speech recognition\" NOT \"brain\")) AND PY...19912.0
\n

389 rows × 2 columns

\n
" }, - "execution_count": 62, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -84,7 +84,7 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 6, "outputs": [], "source": [ "# agg_df = agg_df[agg_df[\"Publication Years\"].str.startswith(\"20\", na=False)].copy()\n", @@ -97,19 +97,10 @@ }, { "cell_type": "code", - "execution_count": 84, - "outputs": [ - { - "data": { - "text/plain": "Publication Years\n2022 314\n2019 305\n2021 305\n2020 302\n2018 296\n2017 287\n2016 281\n2015 271\n2014 258\n2013 251\n2012 233\n2011 224\n2023 52\n2017 4\n2014 4\n2019 4\n2021 4\n2018 4\n2020 4\n2022 4\n2016 3\n2015 3\n2013 3\n2012 3\n2011 3\n2023 2\nName: count, dtype: int64" - }, - "execution_count": 84, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": 7, + "outputs": [], "source": [ - "agg_df[\"Publication Years\"].value_counts()" + "# agg_df[\"Publication Years\"].value_counts()" ], "metadata": { "collapsed": false @@ -117,20 +108,20 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 8, "outputs": [], - "source": [], + "source": [ + "agg_df.to_excel(r'C:\\Users\\radvanyi\\PycharmProjects\\ZSI_analytics\\WOS\\wos_processed_data\\query_yearly_agg.xlsx', index=False)" + ], "metadata": { "collapsed": false } }, { "cell_type": "code", - "execution_count": 85, + "execution_count": 64, "outputs": [], - "source": [ - "agg_df.to_excel(r'C:\\Users\\radvanyi\\PycharmProjects\\ZSI_analytics\\WOS\\wos_processed_data\\query_yearly_agg.xlsx', index=False)" - ], + "source": [], "metadata": { "collapsed": false } diff --git a/WOS/wos_processing_pipeline.ipynb b/WOS/wos_processing_pipeline.ipynb index 2678862..adde38e 100644 --- a/WOS/wos_processing_pipeline.ipynb +++ b/WOS/wos_processing_pipeline.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "outputs": [], "source": [ "import numpy as np\n", @@ -18,7 +18,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "outputs": [], "source": [ "import hashlib\n", @@ -32,7 +32,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -42,7 +42,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "outputs": [], "source": [], "metadata": { @@ -51,21 +51,15 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of initial records: 41511\n", - "Number of filtered records: 35663\n" - ] - } - ], + "outputs": [], "source": [ "wos = pd.read_csv(outfile, sep=\"\\t\",low_memory=False)\n", - "print(f'Number of initial records: {len(wos)}')\n", + "\n", + "wos = wos[((wos[\"Publication Year\"]<2023)&(wos[\"Publication Year\"]>2010))].copy()\n", + "print(f'Number of initial (valid interval) records: {len(wos)}')\n", + "\n", "metrix = pd.read_excel(\"sm_journal_classification.xlsx\", sheet_name=\"Journal_Classification\")\n", "\n", "\n", @@ -79,30 +73,95 @@ "wos = wos.rename(columns={'level_71':\"issn_var\", 0:\"issn\"})\n", "\n", "wos_merge = wos.merge(metrix, on=\"issn\", how=\"left\")\n", - "wos = wos_merge.sort_values(by=\"issn_var\",ascending=False).drop_duplicates(subset=record_col)\n", + "\n", + "\n", + "\n", + "wos_indexed = wos_merge[~wos_merge[\"Domain_English\"].isna()]\n", + "wos_unindexed = wos_merge[~wos_merge[record_col].isin(wos_indexed[record_col])]\n", + "\n", + "\n", + "wos_unindexed = wos_unindexed.sort_values(by=[\"issn_var\"],ascending=False).drop_duplicates(subset=record_col)\n", + "wos = wos_indexed.sort_values(by=[\"issn_var\"],ascending=False).drop_duplicates(subset=record_col)\n", + "\n", + "wos_postmerge = wos.copy()\n", + "print(f'Number of METRIX filtered records: {len(wos)}')\n", + "print(f'Number of unindexed records: {len(wos_unindexed)}')\n", "\n", "# drop entries not indexed by metrix\n", - "wos = wos[~wos[\"Domain_English\"].isna()]\n", "# drop duplicates (based on doi)\n", "wos = wos[~((~wos[\"DOI\"].isna())&(wos[\"DOI\"].duplicated(False)))]\n", "wos = wos.drop_duplicates(subset=[\"Publication Type\",\"Document Type\",\"Authors\",\"Article Title\",\"Source Title\",\"Publication Year\"])\n", - "wos = wos[((wos[\"Publication Year\"]<2023) & (~wos['Domain_English'].isna()))]\n", - "print(f'Number of filtered records: {len(wos)}')" + "print(f'Number of filtered records (dropping duplicates): {len(wos)}')" ] }, { "cell_type": "code", - "execution_count": 7, - "outputs": [ - { - "data": { - "text/plain": "WoS Categories\nEngineering, Electrical & Electronic 9344\nComputer Science, Artificial Intelligence 6045\nComputer Science, Information Systems 5162\nTelecommunications 3929\nComputer Science, Theory & Methods 2706\n ... \nLiterature 1\nEducation, Special 1\nDemography 1\nSocial Work 1\nWomen's Studies 1\nName: count, Length: 234, dtype: int64" - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } + "execution_count": null, + "outputs": [], + "source": [ + "wos[\"Domain_English\"].value_counts()" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "wos_classifier = wos[[\"WoS Categories\",\"Research Areas\"]+list(metrix.columns)].copy().drop_duplicates()\n", + "wos_classifier = wos_classifier.groupby([\"WoS Categories\",\"Research Areas\"], as_index=False)[[\"Domain_English\",\"Field_English\",\"SubField_English\"]].agg(\n", + " lambda x: pd.Series.mode(x)[0])" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "wos_to_reindex = wos_unindexed.drop(columns=list(metrix.columns))\n", + "wos_found = wos_to_reindex.merge(wos_classifier, on=[\"WoS Categories\",\"Research Areas\"], how=\"inner\")\n", + "# wos_found = wos_to_reindex.merge(wos_classifier, on=\"Research Areas\", how=\"inner\")\n", + "# # wos_found = wos_to_reindex.merge(wos_classifier, on=\"WoS Categories\", how=\"inner\")\n", + "wos_stillost = wos_unindexed[~wos_unindexed[record_col].isin(wos_found[record_col])]\n", + "\n", + "print(\"Found:\", wos_found[record_col].nunique(),\"\\nLost forever:\", wos_stillost[record_col].nunique())" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "wos = pd.concat([wos,wos_found], ignore_index=True)\n", + "print(f'Number of records (after remerge): {len(wos)}')" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "wos[\"Domain_English\"].value_counts()" ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], "source": [ "wos_cat = wos.groupby(record_col)[\"WoS Categories\"].apply(lambda x: x.str.split(';')).explode().reset_index().drop(columns=\"level_1\")\n", "wos_cat[\"WoS Categories\"] = wos_cat[\"WoS Categories\"].str.strip()\n", @@ -114,17 +173,8 @@ }, { "cell_type": "code", - "execution_count": 16, - "outputs": [ - { - "data": { - "text/plain": "WoS Category\nEngineering 14168\nComputer Science 13807\nTelecommunications 3929\nImaging Science & Photographic Technology 2155\nAutomation & Control Systems 1964\n ... \nLiterature 1\nDemography 1\nWomen's Studies 1\nSocial Work 1\nMusic 1\nName: count, Length: 176, dtype: int64" - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "wos_subcat = wos_cat.copy()\n", "wos_subcat[['WoS Category', 'WoS SubCategory']] = wos_subcat[\"WoS Categories\"].str.split(\",\", expand = True, n=1)\n", @@ -138,17 +188,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "outputs": [ - { - "data": { - "text/plain": "Research Areas\nEngineering 14204\nComputer Science 13807\nTelecommunications 3929\nEnvironmental Sciences & Ecology 2156\nImaging Science & Photographic Technology 2155\n ... \nCultural Studies 1\nAsian Studies 1\nMusic 1\nDemography 1\nSocial Work 1\nName: count, Length: 147, dtype: int64" - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "wos_areas = wos.groupby(record_col)[\"Research Areas\"].apply(lambda x: x.str.split(';')).explode().reset_index().drop(columns=\"level_1\")\n", "wos_areas[\"Research Areas\"] = wos_areas[\"Research Areas\"].str.strip()\n", @@ -169,18 +210,8 @@ }, { "cell_type": "code", - "execution_count": 101, - "outputs": [ - { - "data": { - "text/plain": " Article Title \n28929 Superpixel Nonlocal Weighting Joint Sparse Rep... \\\n8360 Graph topology enhancement for text classifica... \n42582 Application of machine learning and rough set ... \n32203 BUILDING ROBUST SPOKEN LANGUAGE UNDERSTANDING ... \n37519 Mining of High-Utility Patterns in Big IoT-bas... \n... ... \n21487 Long-range precipitation forecast based on mul... \n37473 Big data fusion in Internet of Things \n27468 An Effective Approach for Selection of Terrain... \n8955 BlockHammer: Improving Flash Reliability by Ex... \n67744 Deeply Supervised Salient Object Detection wit... \n\n Keywords Plus \n28929 DIMENSIONALITY REDUCTION; FEATURE-EXTRACTION; ... \\\n8360 NaN \n42582 PREDICTIVE MAINTENANCE; FRAMEWORK; SELECTION; ... \n32203 NETWORKS \n37519 FREQUENT ITEMSETS; UNCERTAIN; DISCOVERY \n... ... \n21487 YANGTZE-RIVER BASIN; INTERDECADAL VARIABILITY;... \n37473 NaN \n27468 ERROR ANALYSIS \n8955 MEMORY; PERFORMANCE; RETENTION; ENDURANCE; OPT... \n67744 IMAGE; ATTENTION; MODEL \n\n Author Keywords \n28929 spatial-spectral fusion; joint sparse represen... \n8360 Text classification; Graph neural networks; To... \n42582 maintenance; availability; machine learning; d... \n32203 Spoken Language Understanding; NLU Robustness;... \n37519 IoT data analytics; Utility patterns; Data min... \n... ... \n21487 long range; multipole SSTA; preceding fluctuat... \n37473 NaN \n27468 Support vector machine (SVM); terrain classifi... \n8955 Reliability; Three-dimensional displays; Error... \n67744 Salient object detection; short connection; de... \n\n[100 rows x 3 columns]", - 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Article TitleKeywords PlusAuthor Keywords
28929Superpixel Nonlocal Weighting Joint Sparse Rep...DIMENSIONALITY REDUCTION; FEATURE-EXTRACTION; ...spatial-spectral fusion; joint sparse represen...
8360Graph topology enhancement for text classifica...NaNText classification; Graph neural networks; To...
42582Application of machine learning and rough set ...PREDICTIVE MAINTENANCE; FRAMEWORK; SELECTION; ...maintenance; availability; machine learning; d...
32203BUILDING ROBUST SPOKEN LANGUAGE UNDERSTANDING ...NETWORKSSpoken Language Understanding; NLU Robustness;...
37519Mining of High-Utility Patterns in Big IoT-bas...FREQUENT ITEMSETS; UNCERTAIN; DISCOVERYIoT data analytics; Utility patterns; Data min...
............
21487Long-range precipitation forecast based on mul...YANGTZE-RIVER BASIN; INTERDECADAL VARIABILITY;...long range; multipole SSTA; preceding fluctuat...
37473Big data fusion in Internet of ThingsNaNNaN
27468An Effective Approach for Selection of Terrain...ERROR ANALYSISSupport vector machine (SVM); terrain classifi...
8955BlockHammer: Improving Flash Reliability by Ex...MEMORY; PERFORMANCE; RETENTION; ENDURANCE; OPT...Reliability; Three-dimensional displays; Error...
67744Deeply Supervised Salient Object Detection wit...IMAGE; ATTENTION; MODELSalient object detection; short connection; de...
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" - }, - "execution_count": 101, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "wos[[\"Article Title\",\"Keywords Plus\",\"Author Keywords\"]].sample(100)" ], @@ -190,18 +221,8 @@ }, { "cell_type": "code", - "execution_count": 102, - "outputs": [ - { - "data": { - "text/plain": " UT (Unique WOS ID) keyword_all\n0 WOS:000208863600013 COMPARATIVE GENOMICS\n1 WOS:000208863600013 ANAMMOX\n2 WOS:000208863600013 KUENENIA STUTTGARTIENSIS\n3 WOS:000208863600013 METAGENOMICS\n4 WOS:000208863600013 ENRICHMENT CULTURE\n.. ... ...\n97 WOS:000209724300006 VIRTUAL DISKS\n98 WOS:000209724300006 HETEROGENEOUS SERVICES\n99 WOS:000209810700046 CORROSION CHARACTERIZATION\n100 WOS:000209810700046 FEATURE EXTRACTION\n101 WOS:000209810700046 PULSED EDDY CURRENT\n\n[100 rows x 2 columns]", - "text/html": "
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UT (Unique WOS ID)keyword_all
0WOS:000208863600013COMPARATIVE GENOMICS
1WOS:000208863600013ANAMMOX
2WOS:000208863600013KUENENIA STUTTGARTIENSIS
3WOS:000208863600013METAGENOMICS
4WOS:000208863600013ENRICHMENT CULTURE
.........
97WOS:000209724300006VIRTUAL DISKS
98WOS:000209724300006HETEROGENEOUS SERVICES
99WOS:000209810700046CORROSION CHARACTERIZATION
100WOS:000209810700046FEATURE EXTRACTION
101WOS:000209810700046PULSED EDDY CURRENT
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" - }, - "execution_count": 102, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "kw_df = pd.DataFrame()\n", "for c in [\"Keywords Plus\",\"Author Keywords\"]:\n", @@ -218,18 +239,8 @@ }, { "cell_type": "code", - "execution_count": 103, - "outputs": [ - { - "data": { - "text/plain": " UT (Unique WOS ID) keyword_all\n0 WOS:000208863600013 COMPARATIVE GENOMICS; ANAMMOX; KUENENIA STUTTG...\n1 WOS:000208863600266 ANME; PYROSEQUENCING; AOM; COMMUNITY STRUCTURE...\n2 WOS:000208863900217 DEFAULT MODE NETWORK; EFFECTIVE CONNECTIVITY; ...\n3 WOS:000208972600008 BRAIN-MACHINE INTERFACE ; FIELD-PROGRAMMABLE G...\n4 WOS:000209043200014 CYANOBACTERIA BLOOM; DRINKING WATER TREATMENT;...", - "text/html": "
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UT (Unique WOS ID)keyword_all
0WOS:000208863600013COMPARATIVE GENOMICS; ANAMMOX; KUENENIA STUTTG...
1WOS:000208863600266ANME; PYROSEQUENCING; AOM; COMMUNITY STRUCTURE...
2WOS:000208863900217DEFAULT MODE NETWORK; EFFECTIVE CONNECTIVITY; ...
3WOS:000208972600008BRAIN-MACHINE INTERFACE ; FIELD-PROGRAMMABLE G...
4WOS:000209043200014CYANOBACTERIA BLOOM; DRINKING WATER TREATMENT;...
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" - }, - "execution_count": 103, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "wos_kwd_concat = kw_df.groupby(record_col, as_index=False).agg({'keyword_all': '; '.join})\n", "wos_kwd_concat.head()" @@ -240,7 +251,7 @@ }, { "cell_type": "code", - "execution_count": 103, + "execution_count": null, "outputs": [], "source": [], "metadata": { @@ -249,17 +260,8 @@ }, { "cell_type": "code", - "execution_count": 104, - "outputs": [ - { - "data": { - "text/plain": "Index(['Publication Type', 'Authors', 'Book Authors', 'Book Editors',\n 'Book Group Authors', 'Author Full Names', 'Book Author Full Names',\n 'Group Authors', 'Article Title', 'Source Title', 'Book Series Title',\n 'Book Series Subtitle', 'Language', 'Document Type', 'Conference Title',\n 'Conference Date', 'Conference Location', 'Conference Sponsor',\n 'Conference Host', 'Author Keywords', 'Keywords Plus', 'Abstract',\n 'Addresses', 'Affiliations', 'Reprint Addresses', 'Email Addresses',\n 'Researcher Ids', 'ORCIDs', 'Funding Orgs', 'Funding Name Preferred',\n 'Funding Text', 'Cited References', 'Cited Reference Count',\n 'Times Cited, WoS Core', 'Times Cited, All Databases',\n '180 Day Usage Count', 'Since 2013 Usage Count', 'Publisher',\n 'Publisher City', 'Publisher Address', 'ISSN', 'eISSN', 'ISBN',\n 'Journal Abbreviation', 'Journal ISO Abbreviation', 'Publication Date',\n 'Publication Year', 'Volume', 'Issue', 'Part Number', 'Supplement',\n 'Special Issue', 'Meeting Abstract', 'Start Page', 'End Page',\n 'Article Number', 'DOI', 'DOI Link', 'Book DOI', 'Early Access Date',\n 'Number of Pages', 'WoS Categories', 'Web of Science Index',\n 'Research Areas', 'IDS Number', 'Pubmed Id', 'Open Access Designations',\n 'Highly Cited Status', 'Hot Paper Status', 'Date of Export',\n 'UT (Unique WOS ID)', 'issn_var', 'issn', 'Domain_English',\n 'Field_English', 'SubField_English', '2.00 SEQ', 'Source_title',\n 'srcid', 'issn_type'],\n dtype='object')" - }, - "execution_count": 104, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "wos.columns" ], @@ -269,7 +271,7 @@ }, { "cell_type": "code", - "execution_count": 105, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -355,7 +357,7 @@ }, { "cell_type": "code", - "execution_count": 106, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -369,17 +371,8 @@ }, { "cell_type": "code", - "execution_count": 107, - "outputs": [ - { - "data": { - "text/plain": "212138" - }, - "execution_count": 107, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "len(locations)" ], @@ -389,18 +382,8 @@ }, { "cell_type": "code", - "execution_count": 108, - "outputs": [ - { - "data": { - "text/plain": " UT (Unique WOS ID) Authors_of_address \n0 WOS:000208863600013 Hu, Baolan \\\n1 WOS:000208863600013 Jetten, Mike S. M. \n2 WOS:000208863600013 Speth, Daan R.; Bosch, Niek; Keltjens, Jan T.;... \n3 WOS:000208863600013 Stunnenberg, Henk G. \n4 WOS:000208863600266 Chen, Yifeng \n.. ... ... \n95 WOS:000209843500045 Blautzik, Janusch; Meindl, Thomas \n96 WOS:000209843500045 Breitner, John C. S. \n97 WOS:000209843500045 Buckner, Randy L. \n98 WOS:000209843500045 Calhoun, Vince D.; Courtney, William; King, Ma... \n99 WOS:000209843500045 Castellanos, F. Xavier; Colcombe, Stanley J.; ... \n\n Address \n0 Zhejiang Univ, Dept Environm Engn, Hangzhou 31... \n1 Delft Univ Technol, Dept Biotechnol, Delft, Ne... \n2 Radboud Univ Nijmegen, Dept Microbiol, Inst Wa... \n3 Radboud Univ Nijmegen, Dept Mol Biol, Nijmegen... \n4 Chinese Acad Sci, Guangzhou Inst Geochem, Guan... \n.. ... \n95 Ludwig Maximilians Univ Munchen, Inst Clin Rad... \n96 McGill Univ, Douglas Inst, Dept Psychiat, Ctr ... \n97 Harvard Univ, Dept Psychol, Cambridge, MA 0213... \n98 Mind Res Network, Albuquerque, NM 87106 USA \n99 Nathan S Kline Inst Psychiat Res, Orangeburg, ... \n\n[100 rows x 3 columns]", - "text/html": "
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UT (Unique WOS ID)Authors_of_addressAddress
0WOS:000208863600013Hu, BaolanZhejiang Univ, Dept Environm Engn, Hangzhou 31...
1WOS:000208863600013Jetten, Mike S. M.Delft Univ Technol, Dept Biotechnol, Delft, Ne...
2WOS:000208863600013Speth, Daan R.; Bosch, Niek; Keltjens, Jan T.;...Radboud Univ Nijmegen, Dept Microbiol, Inst Wa...
3WOS:000208863600013Stunnenberg, Henk G.Radboud Univ Nijmegen, Dept Mol Biol, Nijmegen...
4WOS:000208863600266Chen, YifengChinese Acad Sci, Guangzhou Inst Geochem, Guan...
............
95WOS:000209843500045Blautzik, Janusch; Meindl, ThomasLudwig Maximilians Univ Munchen, Inst Clin Rad...
96WOS:000209843500045Breitner, John C. S.McGill Univ, Douglas Inst, Dept Psychiat, Ctr ...
97WOS:000209843500045Buckner, Randy L.Harvard Univ, Dept Psychol, Cambridge, MA 0213...
98WOS:000209843500045Calhoun, Vince D.; Courtney, William; King, Ma...Mind Res Network, Albuquerque, NM 87106 USA
99WOS:000209843500045Castellanos, F. Xavier; Colcombe, Stanley J.; ...Nathan S Kline Inst Psychiat Res, Orangeburg, ...
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" - }, - "execution_count": 108, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "locations[\"Address\"] = locations[\"Address\"].str.strip().str.strip(\";\")\n", "locations = locations.groupby([record_col,\"Authors_of_address\"])[\"Address\"].apply(lambda x: x.str.split(';')).explode().reset_index().drop(columns=\"level_2\")\n", @@ -412,7 +395,7 @@ }, { "cell_type": "code", - "execution_count": 109, + "execution_count": null, "outputs": [], "source": [ "# import dask.dataframe as dd\n", @@ -426,7 +409,7 @@ }, { "cell_type": "code", - "execution_count": 110, + "execution_count": null, "outputs": [], "source": [ "# locations_test = locations.head(1000)\n", @@ -439,7 +422,7 @@ }, { "cell_type": "code", - "execution_count": 111, + "execution_count": null, "outputs": [], "source": [ "\n", @@ -455,7 +438,7 @@ }, { "cell_type": "code", - "execution_count": 111, + "execution_count": null, "outputs": [], "source": [], "metadata": { @@ -464,7 +447,7 @@ }, { "cell_type": "code", - "execution_count": 112, + "execution_count": null, "outputs": [], "source": [ "scope_types = [\"EU\",\"China\",\"Non-EU associate\"]\n", @@ -476,19 +459,9 @@ }, { "cell_type": "code", - "execution_count": 113, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": " UT (Unique WOS ID) Address \n0 WOS:000208863600013 Zhejiang Univ, Dept Environm Engn, Hangzhou 31... \\\n1 WOS:000208863600013 Delft Univ Technol, Dept Biotechnol, Delft, Ne... \n2 WOS:000208863600013 Radboud Univ Nijmegen, Dept Microbiol, Inst Wa... \n3 WOS:000208863600013 Radboud Univ Nijmegen, Dept Mol Biol, Nijmegen... \n4 WOS:000208863600266 Chinese Acad Sci, Guangzhou Inst Geochem, Guan... \n\n Country City Country_Type Institution \n0 China Hangzhou China Zhejiang Univ \n1 Netherlands Delft EU Delft Univ Technol \n2 Netherlands Nijmegen EU Radboud Univ Nijmegen \n3 Netherlands Mol EU Radboud Univ Nijmegen \n4 China Guangzhou China Chinese Acad Sci ", - "text/html": "
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UT (Unique WOS ID)AddressCountryCityCountry_TypeInstitution
0WOS:000208863600013Zhejiang Univ, Dept Environm Engn, Hangzhou 31...ChinaHangzhouChinaZhejiang Univ
1WOS:000208863600013Delft Univ Technol, Dept Biotechnol, Delft, Ne...NetherlandsDelftEUDelft Univ Technol
2WOS:000208863600013Radboud Univ Nijmegen, Dept Microbiol, Inst Wa...NetherlandsNijmegenEURadboud Univ Nijmegen
3WOS:000208863600013Radboud Univ Nijmegen, Dept Mol Biol, Nijmegen...NetherlandsMolEURadboud Univ Nijmegen
4WOS:000208863600266Chinese Acad Sci, Guangzhou Inst Geochem, Guan...ChinaGuangzhouChinaChinese Acad Sci
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" - }, - "execution_count": 113, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "univ_locations = locations[[record_col,\"Address\",\"Country\",\"City\",\"Country_Type\"]].copy()\n", "univ_locations[\"Institution\"] = univ_locations[\"Address\"].apply(lambda x: x.split(\",\")[0])\n", @@ -498,19 +471,9 @@ }, { "cell_type": "code", - "execution_count": 114, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": " UT (Unique WOS ID) Country Country_Type \n0 WOS:000208863600013 China China \\\n1 WOS:000208863600013 Netherlands EU \n2 WOS:000208863600013 Netherlands EU \n3 WOS:000208863600013 Netherlands EU \n4 WOS:000208863600013 Netherlands EU \n\n author_str_id \n0 54c7bc6fe9b77434ca1bf04d763d843b \n1 df81f9da6c8f5c968c16ef0aab1bb8f9 \n2 6a775fcd8d11fcb084671b8cae4d6305 \n3 aa6accfdf7626441fe9191636dab4c35 \n4 b707b51d1ca3b5aa76de6ce6df20e6e4 ", - "text/html": "
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UT (Unique WOS ID)CountryCountry_Typeauthor_str_id
0WOS:000208863600013ChinaChina54c7bc6fe9b77434ca1bf04d763d843b
1WOS:000208863600013NetherlandsEUdf81f9da6c8f5c968c16ef0aab1bb8f9
2WOS:000208863600013NetherlandsEU6a775fcd8d11fcb084671b8cae4d6305
3WOS:000208863600013NetherlandsEUaa6accfdf7626441fe9191636dab4c35
4WOS:000208863600013NetherlandsEUb707b51d1ca3b5aa76de6ce6df20e6e4
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" - }, - "execution_count": 114, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "author_locations = locations.groupby([record_col,\"Country\",\"Country_Type\"])[\"Authors_of_address\"].apply(lambda x: x.str.split(';')).explode().reset_index().drop(columns=\"level_3\")\n", "author_locations[\"Author_name\"] = author_locations[\"Authors_of_address\"].str.strip()\n", @@ -523,18 +486,8 @@ }, { "cell_type": "code", - "execution_count": 115, - "outputs": [ - { - "data": { - "text/plain": " UT (Unique WOS ID) Country Country_Type \n0 WOS:000208863600013 China China \\\n1 WOS:000208863600013 Netherlands EU \n5 WOS:000208863600013 Netherlands EU \n7 WOS:000208863600266 China China \n13 WOS:000208863900217 China China \n... ... ... ... \n438826 WOS:000951829800021 China China \n438827 WOS:000951829800021 Netherlands EU \n438828 WOS:000952055000007 China China \n438829 WOS:000952055000007 China China \n438831 WOS:000952055000007 United Kingdom Non-EU associate \n\n author_str_id \n0 54c7bc6fe9b77434ca1bf04d763d843b \n1 df81f9da6c8f5c968c16ef0aab1bb8f9 \n5 df81f9da6c8f5c968c16ef0aab1bb8f9 \n7 5dfb4f0408a2cc8b7f36f5516938b62c \n13 00e44aa0a23a3fc9571b1053a4453a54 \n... ... \n438826 fc15bf7c800877e1c33f4a7397840faa \n438827 6b8763361150d7c3ceecf9eca9efd83b \n438828 80231479c1502ce8649717236023b6c9 \n438829 0af23824e538b0816c19239079d58c77 \n438831 b77dd6bc0ae30a2f96d43eebb1b3d89a \n\n[384417 rows x 4 columns]", - "text/html": "
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UT (Unique WOS ID)CountryCountry_Typeauthor_str_id
0WOS:000208863600013ChinaChina54c7bc6fe9b77434ca1bf04d763d843b
1WOS:000208863600013NetherlandsEUdf81f9da6c8f5c968c16ef0aab1bb8f9
5WOS:000208863600013NetherlandsEUdf81f9da6c8f5c968c16ef0aab1bb8f9
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13WOS:000208863900217ChinaChina00e44aa0a23a3fc9571b1053a4453a54
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438826WOS:000951829800021ChinaChinafc15bf7c800877e1c33f4a7397840faa
438827WOS:000951829800021NetherlandsEU6b8763361150d7c3ceecf9eca9efd83b
438828WOS:000952055000007ChinaChina80231479c1502ce8649717236023b6c9
438829WOS:000952055000007ChinaChina0af23824e538b0816c19239079d58c77
438831WOS:000952055000007United KingdomNon-EU associateb77dd6bc0ae30a2f96d43eebb1b3d89a
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384417 rows × 4 columns

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" - }, - "execution_count": 115, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "author_locations[author_locations['author_str_id'].duplicated(False)]" ], @@ -544,7 +497,7 @@ }, { "cell_type": "code", - "execution_count": 116, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -566,18 +519,8 @@ }, { "cell_type": "code", - "execution_count": 117, - "outputs": [ - { - "data": { - "text/plain": " UT (Unique WOS ID) Country Country_Type \n0 WOS:000208863600013 China China \\\n114146 WOS:000404623900013 China China \n114147 WOS:000404623900013 China China \n330506 WOS:000704130600006 China China \n114149 WOS:000404623900039 China China \n\n author_str_id \n0 54c7bc6fe9b77434ca1bf04d763d843b \n114146 e0d590d171727e520f187ff576a3608c \n114147 773953f1e94a1293cc8417da7b6e435d \n330506 d5296d1bbee9f1c6d4f33e6ae493410a \n114149 88907be51c34b8883aed738d51844b9e ", - "text/html": "
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UT (Unique WOS ID)CountryCountry_Typeauthor_str_id
0WOS:000208863600013ChinaChina54c7bc6fe9b77434ca1bf04d763d843b
114146WOS:000404623900013ChinaChinae0d590d171727e520f187ff576a3608c
114147WOS:000404623900013ChinaChina773953f1e94a1293cc8417da7b6e435d
330506WOS:000704130600006ChinaChinad5296d1bbee9f1c6d4f33e6ae493410a
114149WOS:000404623900039ChinaChina88907be51c34b8883aed738d51844b9e
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" - }, - "execution_count": 117, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "author_primary_region.head()" ], @@ -587,18 +530,9 @@ }, { "cell_type": "code", - "execution_count": 118, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of records: 35663\n", - "Number of valid cooperation records: 31574\n" - ] - } - ], + "outputs": [], "source": [ "print(f'Number of records: {len(wos)}')\n", "print(f'Number of valid cooperation records: {len(valid_scope)}')" @@ -606,7 +540,7 @@ }, { "cell_type": "code", - "execution_count": 119, + "execution_count": null, "outputs": [], "source": [ "wos = wos[wos[record_col].isin(valid_scope)]\n", @@ -621,7 +555,7 @@ }, { "cell_type": "code", - "execution_count": 120, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -632,17 +566,8 @@ }, { "cell_type": "code", - "execution_count": 121, - "outputs": [ - { - "data": { - "text/plain": "Affiliations\nCHINESE ACADEMY OF SCIENCES 3606\nUNIVERSITY OF LONDON 1725\nUDICE-FRENCH RESEARCH UNIVERSITIES 1421\nCENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE (CNRS) 1330\nTSINGHUA UNIVERSITY 1330\n ... \nUNIVERSITY OF NATIONAL & WORLD ECONOMICS - BULGARIA 1\nCENTRE HOSPITALIER RENE DUBOS, PONTOISE 1\nUNIVERSITY OF PRINCE MUGRIN 1\nMINDANAO STATE UNIVERSITY-IIT 1\nTANGSHAN UNIVERSITY 1\nName: count, Length: 6772, dtype: int64" - }, - "execution_count": 121, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "affiliations[\"Affiliations\"].value_counts()" ], @@ -652,17 +577,8 @@ }, { "cell_type": "code", - "execution_count": 122, - "outputs": [ - { - "data": { - "text/plain": "Institution\nChinese Acad Sci 3600\nTsinghua Univ 1611\nShanghai Jiao Tong Univ 1359\nZhejiang Univ 1274\nUniv Elect Sci & Technol China 965\n ... \nStatSol 1\nJan Kochanowski Univ Humanities & Sci 1\nTomTom 1\nLUMC 1\nInt Digital Econ Acad 1\nName: count, Length: 14564, dtype: int64" - }, - "execution_count": 122, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "univ_locations[\"Institution\"].value_counts()" ], @@ -672,17 +588,8 @@ }, { "cell_type": "code", - "execution_count": 123, - "outputs": [ - { - "data": { - "text/plain": "31574" - }, - "execution_count": 123, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "univ_locations[record_col].nunique()" ], @@ -692,18 +599,9 @@ }, { "cell_type": "code", - "execution_count": 124, - "outputs": [ - { - "data": { - "text/plain": "31574" - }, - "execution_count": 124, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ + "execution_count": null, + "outputs": [], + "source": [ "affiliations[record_col].nunique()" ], "metadata": { @@ -712,17 +610,8 @@ }, { "cell_type": "code", - "execution_count": 125, - "outputs": [ - { - "data": { - "text/plain": "137536" - }, - "execution_count": 125, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "univ_locations[\"Institution\"].value_counts().sum()" ], @@ -732,17 +621,8 @@ }, { "cell_type": "code", - "execution_count": 126, - "outputs": [ - { - "data": { - "text/plain": "181023" - }, - "execution_count": 126, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "affiliations[\"Affiliations\"].value_counts().sum()" ], @@ -752,18 +632,9 @@ }, { "cell_type": "code", - "execution_count": 127, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": "WoS Categories\n Engineering, Electrical & Electronic 6006\nComputer Science, Artificial Intelligence 4769\nComputer Science, Information Systems 3698\n Telecommunications 3271\nEngineering, Electrical & Electronic 2423\n ... \nAndrology 1\n Criminology & Penology 1\nArea Studies 1\nArt 1\n Geology 1\nName: count, Length: 415, dtype: int64" - }, - "execution_count": 127, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "wos_cat = wos.groupby(record_col)[\"WoS Categories\"].apply(lambda x: x.str.split(';')).explode().reset_index().drop(columns=\"level_1\")\n", "wos_cat[\"WoS Categories\"].value_counts()" @@ -771,18 +642,9 @@ }, { "cell_type": "code", - "execution_count": 128, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": "Research Areas\nEngineering 12704\nComputer Science 12221\nTelecommunications 3544\nImaging Science & Photographic Technology 1936\nEnvironmental Sciences & Ecology 1876\n ... \nMusic 1\nAsian Studies 1\nCultural Studies 1\nArea Studies 1\nEmergency Medicine 1\nName: count, Length: 145, dtype: int64" - }, - "execution_count": 128, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "wos_areas = wos.groupby(record_col)[\"Research Areas\"].apply(lambda x: x.str.split(';')).explode().reset_index().drop(columns=\"level_1\")\n", "wos_areas[\"Research Areas\"] = wos_areas[\"Research Areas\"].str.strip()\n", @@ -791,36 +653,27 @@ }, { "cell_type": "code", - "execution_count": 129, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": "['Domain_English', 'Field_English', 'SubField_English']" - }, - "execution_count": 129, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "[c for c in wos.columns if \"_English\" in c]" ] }, { "cell_type": "code", - "execution_count": 130, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ "metrix_levels = [c for c in wos.columns if \"_English\" in c]\n", "for m in metrix_levels:\n", - " wos[m] = wos[m].replace({\"article-level classification\":\"Miscellaneous\"})\n" + " wos[m] = wos[m].replace({\"article-level classification\":\"Multidisciplinary\"})\n" ] }, { "cell_type": "code", - "execution_count": 130, + "execution_count": null, "outputs": [], "source": [], "metadata": { @@ -829,44 +682,25 @@ }, { "cell_type": "code", - "execution_count": 131, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": " Publication Type Authors \n0 J Maurya, S; Srivastava, PK; Yaduvanshi, A; Anan... \\\n38775 J Huang, BS; Zheng, GY; Xu, ZY; Rao, SX; Wang, SL \n38758 J Wen, SH; Hu, XH; Li, Z; Lam, HK; Sun, FC; Fang, B \n38760 J Yu, WR; McCann, J; Zhang, CY \n38762 J Zhang, AZ; Sun, GY; Liu, SH; Wang, ZJ; Wang, P... \n... ... ... \n41597 J Liu, H; Long, SX; Pinson, SRM; Tang, Z; Guerin... \n41666 J Komarizadehasl, S; Mobaraki, B; Ma, HY; Lozano... \n41621 J Xie, QH; Wang, JF; Liao, CH; Shang, JL; Lopez-... \n14505 J Li, RYM; Li, HCY \n41622 J Shen, YF; Wang, TZ; Amirat, Y; Chen, GD \n\n Book Authors Book Editors Book Group Authors \n0 NaN NaN NaN \\\n38775 NaN NaN NaN \n38758 NaN NaN NaN \n38760 NaN NaN NaN \n38762 NaN NaN NaN \n... ... ... ... \n41597 NaN NaN NaN \n41666 NaN NaN NaN \n41621 NaN NaN NaN \n14505 NaN NaN NaN \n41622 NaN NaN NaN \n\n Author Full Names \n0 Maurya, Swati; Srivastava, Prashant K.; Yaduva... \\\n38775 Huang, Bingsheng; Zheng, Guoyan; Xu, Ziyue; Ra... \n38758 Wen, Shuhuan; Hu, Xueheng; Li, Zhen; Lam, Hak ... \n38760 Yu, Weiren; McCann, Julie; Zhang, Chengyuan \n38762 Zhang, Ai Zhu; Sun, Gen Yun; Liu, Si Han; Wang... \n... ... \n41597 Liu, Huan; Long, Su-Xian; Pinson, Shannon R. M... \n41666 Komarizadehasl, Seyedmilad; Mobaraki, Behnam; ... \n41621 Xie, Qinghua; Wang, Jinfei; Liao, Chunhua; Sha... \n14505 Li, Rita Yi Man; Li, Herru Ching Yu \n41622 Shen, Yifei; Wang, Tianzhen; Amirat, Yassine; ... \n\n Book Author Full Names Group Authors \n0 NaN NaN \\\n38775 NaN NaN \n38758 NaN NaN \n38760 NaN NaN \n38762 NaN NaN \n... ... ... \n41597 NaN NaN \n41666 NaN NaN \n41621 NaN NaN \n14505 NaN NaN \n41622 NaN NaN \n\n Article Title \n0 Soil erosion in future scenario using CMIP5 mo... \\\n38775 Application of Image Processing Techniques in ... \n38758 NAO robot obstacle avoidance based on fuzzy Q-... \n38760 Efficient Pairwise Penetrating-rank Similarity... \n38762 Multi-scale segmentation of very high resoluti... \n... ... \n41597 Univariate and Multivariate QTL Analyses Revea... \n41666 Development of a Low-Cost System for the Accur... \n41621 On the Use of Neumann Decomposition for Crop C... \n14505 Have Housing Prices Gone with the Smelly Wind?... \n41622 IGBT Open-Circuit Fault Diagnosis for MMC Subm... \n\n Source Title ... \n0 JOURNAL OF HYDROLOGY ... \\\n38775 CONTRAST MEDIA & MOLECULAR IMAGING ... \n38758 INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ... ... \n38760 ACM TRANSACTIONS ON THE WEB ... \n38762 MULTIMEDIA TOOLS AND APPLICATIONS ... \n... ... ... \n41597 FRONTIERS IN GENETICS ... \n41666 SENSORS ... \n41621 REMOTE SENSING ... \n14505 SUSTAINABILITY ... \n41622 MACHINES ... \n\n UT (Unique WOS ID) issn_var issn Domain_English \n0 WOS:000641589600020 issn 00221694 Applied Sciences \\\n38775 WOS:000416383700001 issn 15554309 Health Sciences \n38758 WOS:000590197400003 issn 0143991x Applied Sciences \n38760 WOS:000510863400004 issn 15591131 Applied Sciences \n38762 WOS:000403039400031 issn 13807501 Applied Sciences \n... ... ... ... ... \n41597 WOS:000615818700001 eissn 16648021 Health Sciences \n41666 WOS:000701119200001 eissn 14248220 Natural Sciences \n41621 WOS:000465549300041 eissn 20724292 Applied Sciences \n14505 WOS:000425943100064 eissn 20711050 Applied Sciences \n41622 WOS:000737607200001 eissn 20751702 Applied Sciences \n\n Field_English \n0 Engineering \\\n38775 Clinical Medicine \n38758 Engineering \n38760 Information & Communication Technologies \n38762 Information & Communication Technologies \n... ... \n41597 Biomedical Research \n41666 Chemistry \n41621 Engineering \n14505 Enabling & Strategic Technologies \n41622 Engineering \n\n SubField_English 2.00 SEQ \n0 Environmental Engineering 25 \\\n38775 Nuclear Medicine & Medical Imaging 111 \n38758 Industrial Engineering & Automation 27 \n38760 Information Systems 35 \n38762 Software Engineering 38 \n... ... ... \n41597 Developmental Biology 85 \n41666 Analytical Chemistry 149 \n41621 Geological & Geomatics Engineering 26 \n14505 Energy 14 \n41622 Industrial Engineering & Automation 27 \n\n Source_title srcid issn_type \n0 Journal of Hydrology 5.008900e+04 issn1 \n38775 Contrast Media and Molecular Imaging 5.400153e+09 issn1 \n38758 Industrial Robot 1.804700e+04 issn1 \n38760 ACM Transactions on the Web 5.800207e+09 issn1 \n38762 Multimedia Tools and Applications 2.562700e+04 issn1 \n... ... ... ... \n41597 Frontiers in Genetics 2.110024e+10 issn1 \n41666 Sensors (Switzerland) 1.301240e+05 issn1 \n41621 Remote Sensing 8.643000e+04 issn1 \n14505 Sustainability (Switzerland) 2.110024e+10 issn1 \n41622 Machines 2.110084e+10 issn1 \n\n[31574 rows x 80 columns]", - "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Publication TypeAuthorsBook AuthorsBook EditorsBook Group AuthorsAuthor Full NamesBook Author Full NamesGroup AuthorsArticle TitleSource Title...UT (Unique WOS ID)issn_varissnDomain_EnglishField_EnglishSubField_English2.00 SEQSource_titlesrcidissn_type
0JMaurya, S; Srivastava, PK; Yaduvanshi, A; Anan...NaNNaNNaNMaurya, Swati; Srivastava, Prashant K.; Yaduva...NaNNaNSoil erosion in future scenario using CMIP5 mo...JOURNAL OF HYDROLOGY...WOS:000641589600020issn00221694Applied SciencesEngineeringEnvironmental Engineering25Journal of Hydrology5.008900e+04issn1
38775JHuang, BS; Zheng, GY; Xu, ZY; Rao, SX; Wang, SLNaNNaNNaNHuang, Bingsheng; Zheng, Guoyan; Xu, Ziyue; Ra...NaNNaNApplication of Image Processing Techniques in ...CONTRAST MEDIA & MOLECULAR IMAGING...WOS:000416383700001issn15554309Health SciencesClinical MedicineNuclear Medicine & Medical Imaging111Contrast Media and Molecular Imaging5.400153e+09issn1
38758JWen, SH; Hu, XH; Li, Z; Lam, HK; Sun, FC; Fang, BNaNNaNNaNWen, Shuhuan; Hu, Xueheng; Li, Zhen; Lam, Hak ...NaNNaNNAO robot obstacle avoidance based on fuzzy Q-...INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ......WOS:000590197400003issn0143991xApplied SciencesEngineeringIndustrial Engineering & Automation27Industrial Robot1.804700e+04issn1
38760JYu, WR; McCann, J; Zhang, CYNaNNaNNaNYu, Weiren; McCann, Julie; Zhang, ChengyuanNaNNaNEfficient Pairwise Penetrating-rank Similarity...ACM TRANSACTIONS ON THE WEB...WOS:000510863400004issn15591131Applied SciencesInformation & Communication TechnologiesInformation Systems35ACM Transactions on the Web5.800207e+09issn1
38762JZhang, AZ; Sun, GY; Liu, SH; Wang, ZJ; Wang, P...NaNNaNNaNZhang, Ai Zhu; Sun, Gen Yun; Liu, Si Han; Wang...NaNNaNMulti-scale segmentation of very high resoluti...MULTIMEDIA TOOLS AND APPLICATIONS...WOS:000403039400031issn13807501Applied SciencesInformation & Communication TechnologiesSoftware Engineering38Multimedia Tools and Applications2.562700e+04issn1
..................................................................
41597JLiu, H; Long, SX; Pinson, SRM; Tang, Z; Guerin...NaNNaNNaNLiu, Huan; Long, Su-Xian; Pinson, Shannon R. M...NaNNaNUnivariate and Multivariate QTL Analyses Revea...FRONTIERS IN GENETICS...WOS:000615818700001eissn16648021Health SciencesBiomedical ResearchDevelopmental Biology85Frontiers in Genetics2.110024e+10issn1
41666JKomarizadehasl, S; Mobaraki, B; Ma, HY; Lozano...NaNNaNNaNKomarizadehasl, Seyedmilad; Mobaraki, Behnam; ...NaNNaNDevelopment of a Low-Cost System for the Accur...SENSORS...WOS:000701119200001eissn14248220Natural SciencesChemistryAnalytical Chemistry149Sensors (Switzerland)1.301240e+05issn1
41621JXie, QH; Wang, JF; Liao, CH; Shang, JL; Lopez-...NaNNaNNaNXie, Qinghua; Wang, Jinfei; Liao, Chunhua; Sha...NaNNaNOn the Use of Neumann Decomposition for Crop C...REMOTE SENSING...WOS:000465549300041eissn20724292Applied SciencesEngineeringGeological & Geomatics Engineering26Remote Sensing8.643000e+04issn1
14505JLi, RYM; Li, HCYNaNNaNNaNLi, Rita Yi Man; Li, Herru Ching YuNaNNaNHave Housing Prices Gone with the Smelly Wind?...SUSTAINABILITY...WOS:000425943100064eissn20711050Applied SciencesEnabling & Strategic TechnologiesEnergy14Sustainability (Switzerland)2.110024e+10issn1
41622JShen, YF; Wang, TZ; Amirat, Y; Chen, GDNaNNaNNaNShen, Yifei; Wang, Tianzhen; Amirat, Yassine; ...NaNNaNIGBT Open-Circuit Fault Diagnosis for MMC Subm...MACHINES...WOS:000737607200001eissn20751702Applied SciencesEngineeringIndustrial Engineering & Automation27Machines2.110084e+10issn1
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31574 rows × 80 columns

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" - }, - "execution_count": 131, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "wos" ] }, { "cell_type": "code", - "execution_count": 132, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": "['Domain_English', 'Field_English', 'SubField_English']" - }, - "execution_count": 132, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "metrix_levels" ] }, { "cell_type": "code", - "execution_count": 134, + "execution_count": null, "outputs": [], "source": [ "record_countries = locations[[record_col,\"Country\"]].drop_duplicates()\n", @@ -880,7 +714,7 @@ }, { "cell_type": "code", - "execution_count": 135, + "execution_count": null, "outputs": [], "source": [ "# Basic network layout" @@ -891,7 +725,7 @@ }, { "cell_type": "code", - "execution_count": 136, + "execution_count": null, "outputs": [], "source": [ "country_collabs = record_countries.merge(record_countries, on=record_col)\n", @@ -904,7 +738,7 @@ }, { "cell_type": "code", - "execution_count": 137, + "execution_count": null, "outputs": [], "source": [ "inst_collabs = record_institution.merge(record_institution, on=record_col)\n", @@ -917,17 +751,8 @@ }, { "cell_type": "code", - "execution_count": 138, - "outputs": [ - { - "data": { - "text/plain": "Index(['Publication Type', 'Authors', 'Book Authors', 'Book Editors',\n 'Book Group Authors', 'Author Full Names', 'Book Author Full Names',\n 'Group Authors', 'Article Title', 'Source Title', 'Book Series Title',\n 'Book Series Subtitle', 'Language', 'Document Type', 'Conference Title',\n 'Conference Date', 'Conference Location', 'Conference Sponsor',\n 'Conference Host', 'Author Keywords', 'Keywords Plus', 'Abstract',\n 'Addresses', 'Affiliations', 'Reprint Addresses', 'Email Addresses',\n 'Researcher Ids', 'ORCIDs', 'Funding Orgs', 'Funding Name Preferred',\n 'Funding Text', 'Cited References', 'Cited Reference Count',\n 'Times Cited, WoS Core', 'Times Cited, All Databases',\n '180 Day Usage Count', 'Since 2013 Usage Count', 'Publisher',\n 'Publisher City', 'Publisher Address', 'ISSN', 'eISSN', 'ISBN',\n 'Journal Abbreviation', 'Journal ISO Abbreviation', 'Publication Date',\n 'Publication Year', 'Volume', 'Issue', 'Part Number', 'Supplement',\n 'Special Issue', 'Meeting Abstract', 'Start Page', 'End Page',\n 'Article Number', 'DOI', 'DOI Link', 'Book DOI', 'Early Access Date',\n 'Number of Pages', 'WoS Categories', 'Web of Science Index',\n 'Research Areas', 'IDS Number', 'Pubmed Id', 'Open Access Designations',\n 'Highly Cited Status', 'Hot Paper Status', 'Date of Export',\n 'UT (Unique WOS ID)', 'issn_var', 'issn', 'Domain_English',\n 'Field_English', 'SubField_English', '2.00 SEQ', 'Source_title',\n 'srcid', 'issn_type'],\n dtype='object')" - }, - "execution_count": 138, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "wos.columns" ], @@ -937,17 +762,8 @@ }, { "cell_type": "code", - "execution_count": 139, - "outputs": [ - { - "data": { - "text/plain": "['Authors',\n 'Book Authors',\n 'Book Editors',\n 'Book Group Authors',\n 'Author Full Names',\n 'Book Author Full Names',\n 'Group Authors',\n 'Addresses',\n 'Reprint Addresses',\n 'Email Addresses',\n 'Researcher Ids',\n 'ORCIDs',\n 'Publisher Address',\n '2.00 SEQ']" - }, - "execution_count": 139, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "drop_cols = [ws for ws in wos.columns if ((\"uthor\" in ws or \"ddress\" in ws or \"ORCID\" in\n", " ws or \"esearcher\" in ws or \"ditor\" in ws or \"name\" in ws or 'SEQ' in ws) and \"eyword\" not in ws)]\n", @@ -959,7 +775,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "outputs": [], "source": [ "outdir=\"wos_processed_data\"" @@ -970,7 +786,7 @@ }, { "cell_type": "code", - "execution_count": 140, + "execution_count": null, "outputs": [], "source": [ "os.makedirs(outdir, exist_ok=True)\n", @@ -993,7 +809,7 @@ }, { "cell_type": "code", - "execution_count": 141, + "execution_count": null, "outputs": [], "source": [ "wos.drop(columns=drop_cols).to_csv(f\"{outdir}/wos_processed.csv\", index=False, sep='\\t')\n", @@ -1018,7 +834,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "outputs": [], "source": [ "wos_areas.to_csv(f\"{outdir}/wos_research_areas.csv\", index=False, sep='\\t')\n", @@ -1029,22 +845,39 @@ "collapsed": false } }, + { + "cell_type": "markdown", + "source": [ + "# Simple NLP part" + ], + "metadata": { + "collapsed": false + } + }, { "cell_type": "code", - "execution_count": 151, - "outputs": [ - { - "data": { - "text/plain": " UT (Unique WOS ID) \n697 WOS:000290510900023 \\\n871 WOS:000291698400013 \n1127 WOS:000291752600003 \n1470 WOS:000294492600001 \n1772 WOS:000295615800053 \n... ... \n211125 WOS:000926330000001 \n211658 WOS:000929537500051 \n211686 WOS:000929537500051 \n211719 WOS:000929537500051 \n212266 WOS:000929737300001 \n\n Authors_of_address \n697 Liu, Jian-Guo \\\n871 Abdesselam, A.; Barr, A. J.; Beauchemin, P. H.... \n1127 Hill, Jamie R.; Kelm, Sebastian; Deane, Charlo... \n1470 Barr, A. J.; Heinemann, F. E. W.; de Renstrom,... \n1772 Huang, Xiaolei \n... ... \n211125 Wang, Tingyan \n211658 Lewycka, Sonia \n211686 Maude, Richard James \n211719 Moore, Catrin E. \n212266 Matthews, Philippa C. \n\n Address Country \n697 Univ Oxford, CABDyN Complex Ctr, Said Business... United Kingdom \\\n871 Univ Oxford, Dept Phys, Oxford OX1 3RH, England United Kingdom \n1127 Univ Oxford, Dept Stat, Oxford OX1 3TG, England United Kingdom \n1470 Univ Oxford, Dept Phys, Oxford OX1 3RH, England United Kingdom \n1772 Univ Oxford, Oxford OX1 2JD, England United Kingdom \n... ... ... \n211125 Univ Oxford, Nuffield Dept Med, Oxford, England United Kingdom \n211658 Univ Oxford, Ctr Trop Med & Global Hlth, Oxfor... United Kingdom \n211686 Univ Oxford, Nuffield Dept Med, Oxford, England United Kingdom \n211719 Univ Oxford, Big Data Inst, Oxford, England United Kingdom \n212266 Univ Oxford, Nuffield Dept Expt Med, Oxford, E... United Kingdom \n\n City Country_Type \n697 Oxford Non-EU associate \n871 Oxford Non-EU associate \n1127 Oxford Non-EU associate \n1470 Oxford Non-EU associate \n1772 Oxford Non-EU associate \n... ... ... \n211125 Meda Non-EU associate \n211658 Meda Non-EU associate \n211686 Meda Non-EU associate \n211719 Biga Non-EU associate \n212266 Meda Non-EU associate \n\n[789 rows x 6 columns]", - "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
UT (Unique WOS ID)Authors_of_addressAddressCountryCityCountry_Type
697WOS:000290510900023Liu, Jian-GuoUniv Oxford, CABDyN Complex Ctr, Said Business...United KingdomOxfordNon-EU associate
871WOS:000291698400013Abdesselam, A.; Barr, A. J.; Beauchemin, P. H....Univ Oxford, Dept Phys, Oxford OX1 3RH, EnglandUnited KingdomOxfordNon-EU associate
1127WOS:000291752600003Hill, Jamie R.; Kelm, Sebastian; Deane, Charlo...Univ Oxford, Dept Stat, Oxford OX1 3TG, EnglandUnited KingdomOxfordNon-EU associate
1470WOS:000294492600001Barr, A. J.; Heinemann, F. E. W.; de Renstrom,...Univ Oxford, Dept Phys, Oxford OX1 3RH, EnglandUnited KingdomOxfordNon-EU associate
1772WOS:000295615800053Huang, XiaoleiUniv Oxford, Oxford OX1 2JD, EnglandUnited KingdomOxfordNon-EU associate
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211125WOS:000926330000001Wang, TingyanUniv Oxford, Nuffield Dept Med, Oxford, EnglandUnited KingdomMedaNon-EU associate
211658WOS:000929537500051Lewycka, SoniaUniv Oxford, Ctr Trop Med & Global Hlth, Oxfor...United KingdomMedaNon-EU associate
211686WOS:000929537500051Maude, Richard JamesUniv Oxford, Nuffield Dept Med, Oxford, EnglandUnited KingdomMedaNon-EU associate
211719WOS:000929537500051Moore, Catrin E.Univ Oxford, Big Data Inst, Oxford, EnglandUnited KingdomBigaNon-EU associate
212266WOS:000929737300001Matthews, Philippa C.Univ Oxford, Nuffield Dept Expt Med, Oxford, E...United KingdomMedaNon-EU associate
\n

789 rows × 6 columns

\n
" - }, - "execution_count": 151, - "metadata": {}, - "output_type": "execute_result" - } + "execution_count": 1, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import os\n", + "import shutil\n", + "from flashgeotext.geotext import GeoText\n", + "import re" ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 2, + "outputs": [], "source": [ - "locations[locations[\"Address\"].str.contains(\"Univ Oxford\")]" + "import spacy\n", + "\n", + "nlp = spacy.load('en_core_web_trf')" ], "metadata": { "collapsed": false @@ -1052,10 +885,11 @@ }, { "cell_type": "code", - "execution_count": 142, + "execution_count": 4, "outputs": [], "source": [ - "inv = record_institution.groupby(\"Institution\")[\"Country\"].value_counts().reset_index(level=[0,1])" + "outdir=\"wos_processed_data\"\n", + "record_col=\"UT (Unique WOS ID)\"" ], "metadata": { "collapsed": false @@ -1063,20 +897,20 @@ }, { "cell_type": "code", - "execution_count": 147, + "execution_count": 8, "outputs": [ { "data": { - "text/plain": "Empty DataFrame\nColumns: [UT (Unique WOS ID), Address, Country, City, Country_Type, Institution]\nIndex: []", - "text/html": "
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UT (Unique WOS ID)AddressCountryCityCountry_TypeInstitution
\n
" + "text/plain": " UT (Unique WOS ID) keyword_all\n0 WOS:000208863600013 COMPARATIVE GENOMICS\n1 WOS:000208863600013 ANAMMOX\n2 WOS:000208863600013 KUENENIA STUTTGARTIENSIS\n3 WOS:000208863600013 METAGENOMICS\n4 WOS:000208863600013 ENRICHMENT CULTURE\n.. ... ...\n95 WOS:000209672000007 SECURITY\n96 WOS:000209672000007 TRUST EVALUATION\n97 WOS:000209672000007 WIRELESS SENSOR NETWORK \n98 WOS:000209673200006 FORMAL VERIFICATION\n99 WOS:000209673200006 STOCHASTIC MODEL CHECKING\n\n[100 rows x 2 columns]", + "text/html": "
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UT (Unique WOS ID)keyword_all
0WOS:000208863600013COMPARATIVE GENOMICS
1WOS:000208863600013ANAMMOX
2WOS:000208863600013KUENENIA STUTTGARTIENSIS
3WOS:000208863600013METAGENOMICS
4WOS:000208863600013ENRICHMENT CULTURE
.........
95WOS:000209672000007SECURITY
96WOS:000209672000007TRUST EVALUATION
97WOS:000209672000007WIRELESS SENSOR NETWORK
98WOS:000209673200006FORMAL VERIFICATION
99WOS:000209673200006STOCHASTIC MODEL CHECKING
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100 rows × 2 columns

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" }, - "execution_count": 147, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "univ_locations[univ_locations[\"Address\"].str.strip().str.strip(\";\").str.contains(\";\")]" + "kw_df.head(100)" ], "metadata": { "collapsed": false @@ -1084,20 +918,58 @@ }, { "cell_type": "code", - "execution_count": 146, + "execution_count": 44, + "outputs": [], + "source": [ + "kw_df = pd.read_excel(f\"{outdir}/wos_keywords.xlsx\")\n", + "wos = pd.read_excel(f\"{outdir}/wos_processed.xlsx\")\n", + "kw_df = kw_df[~kw_df[\"keyword_all\"].isna()].copy()\n", + "wos_kwd_concat = kw_df.groupby(record_col,as_index=False).agg({'keyword_all': '; '.join})" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 43, "outputs": [ { "data": { - "text/plain": " Institution Country count\n95 Univ Oxford United Kingdom 1\n3125 Dept Engn Univ Oxford United Kingdom 1\n13397 Univ Oxford United Kingdom 629\n13398 Univ Oxford China 2", - "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
InstitutionCountrycount
95Univ OxfordUnited Kingdom1
3125Dept Engn Univ OxfordUnited Kingdom1
13397Univ OxfordUnited Kingdom629
13398Univ OxfordChina2
\n
" + "text/plain": " UT (Unique WOS ID) keyword_all\n0 WOS:000208863600013 COMPARATIVE GENOMICS\n1 WOS:000208863600013 ANAMMOX\n2 WOS:000208863600013 KUENENIA STUTTGARTIENSIS\n3 WOS:000208863600013 METAGENOMICS\n4 WOS:000208863600013 ENRICHMENT CULTURE", + "text/html": "
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UT (Unique WOS ID)keyword_all
0WOS:000208863600013COMPARATIVE GENOMICS
1WOS:000208863600013ANAMMOX
2WOS:000208863600013KUENENIA STUTTGARTIENSIS
3WOS:000208863600013METAGENOMICS
4WOS:000208863600013ENRICHMENT CULTURE
\n
" }, - "execution_count": 146, + "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "inv[inv[\"Institution\"].str.contains(\"Univ Oxford\")]" + "kw_df.head()" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": 45, + "outputs": [], + "source": [ + "kwd_nlp = pd.DataFrame(kw_df[\"keyword_all\"].drop_duplicates())\n", + "kwd_nlp = kwd_nlp.rename(columns={\"keyword_all\":\"Document\"})\n", + "kwd_nlp[\"Type\"] = \"kw\"\n", + "kwd_nlp[record_col] = \"kw_\"+(kwd_nlp.index).astype(str)\n", + "wos_nlp = wos.merge(wos_kwd_concat, on=record_col)\n", + "wos_nlp[\"Document\"] = wos_nlp[\"keyword_all\"].fillna(\"\").str.upper()\n", + "# wos_nlp[\"Document\"] = wos_nlp[\"Article Title\"].str.cat(wos_nlp[[\"Abstract\", \"keyword_all\"]].fillna(\"\"), sep=' - ').str.upper()\n", + "# wos_nlp[\"Document\"] = wos_nlp[\"Article Title\"].str.cat(wos_nlp[[\"Abstract\"]].fillna(\"\"), sep=' - ').str.upper()\n", + "wos_nlp[[record_col, \"Document\"]].drop_duplicates()\n", + "wos_nlp[\"Type\"] = \"doc\"\n", + "\n", + "tnse_nlp = pd.concat([kwd_nlp,wos_nlp], ignore_index=True)\n", + "tnse_nlp = tnse_nlp[[record_col,\"Type\",\"Document\",\"keyword_all\"]]\n", + "# tnse_nlp = tnse_nlp.sample(1000)" ], "metadata": { "collapsed": false @@ -1105,19 +977,20 @@ }, { "cell_type": "code", - "execution_count": 143, + "execution_count": 47, "outputs": [ { "data": { - "text/plain": "Institution\n Aalto Univ 1\n Aix Marseille Univ 1\n Alexandru Ioan Cuza Univ 1\n Av Rovisco Pais 1 1\n Brandenburg Tech Univ Cottbus 1\n ..\niMinds 1\niOLAP Inc 1\nneuroCare Grp 1\nsen Univ Guangzhou 1\nvon Hoerner & Sulger GmbH 1\nName: Country, Length: 14564, dtype: int64" + "text/plain": " UT (Unique WOS ID) Type Document keyword_all\n66311 kw_132167 kw VERTICAL PROGRAMMABILITY NaN\n121641 kw_354170 kw NONLINEAR CLUSTER INVERSION NaN\n35468 kw_59369 kw TIME-VARIANT PARAMETER NaN\n117421 kw_324755 kw MULTI-INCIDENCE NaN\n87947 kw_199369 kw EVERGREEN BROADLEAVED TREES NaN\n... ... ... ... ...\n56273 kw_105016 kw DOUBLE ARC COORDINATE PLOT NaN\n26548 kw_42376 kw MODAL SHIFT NaN\n70903 kw_144947 kw PRIVACY-PERSEVERANCE NaN\n49655 kw_88641 kw IRAP NaN\n104544 kw_254913 kw COGNITIVE-PROCESSES NaN\n\n[100 rows x 4 columns]", + "text/html": "
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UT (Unique WOS ID)TypeDocumentkeyword_all
66311kw_132167kwVERTICAL PROGRAMMABILITYNaN
121641kw_354170kwNONLINEAR CLUSTER INVERSIONNaN
35468kw_59369kwTIME-VARIANT PARAMETERNaN
117421kw_324755kwMULTI-INCIDENCENaN
87947kw_199369kwEVERGREEN BROADLEAVED TREESNaN
...............
56273kw_105016kwDOUBLE ARC COORDINATE PLOTNaN
26548kw_42376kwMODAL SHIFTNaN
70903kw_144947kwPRIVACY-PERSEVERANCENaN
49655kw_88641kwIRAPNaN
104544kw_254913kwCOGNITIVE-PROCESSESNaN
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100 rows × 4 columns

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" }, - "execution_count": 143, + "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "record_institution.groupby(\"Institution\")[\"Country\"].nunique()" + "tnse_nlp.sample(100)" ], "metadata": { "collapsed": false @@ -1127,15 +1000,81 @@ "cell_type": "code", "execution_count": null, "outputs": [], - "source": [], + "source": [ + "vectors = list()\n", + "vector_norms = list()\n", + "\n", + "for doc in nlp.pipe(tnse_nlp['Document'].astype('unicode').values, batch_size=300,\n", + " n_process=4):\n", + " trf_vector = doc._.trf_data.tensors[-1].mean(axis=0)\n", + " trf_norm = np.linalg.norm(doc._.trf_data.tensors[-1].mean(axis=0))\n", + " norm_vector = trf_vector/trf_norm\n", + " vectors.append(norm_vector)\n", + " vector_norms.append(np.linalg.norm(norm_vector))\n", + "\n", + "tnse_nlp['vector'] = vectors\n", + "tnse_nlp['vector_norm'] = vector_norms\n", + "tnse_nlp['vector_norm'].plot(kind=\"hist\")" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "is_executing": true + } + } + }, + { + "cell_type": "code", + "execution_count": 32, + "outputs": [ + { + "data": { + "text/plain": " UT (Unique WOS ID) Type \n159915 WOS:000493345400001 doc \\\n62232 kw_120676 kw \n18729 kw_28349 kw \n146728 WOS:000337736000001 doc \n157327 WOS:000793790600002 doc \n... ... ... \n64501 kw_126785 kw \n114208 kw_304857 kw \n90681 kw_207619 kw \n117081 kw_322648 kw \n146051 WOS:000660876800002 doc \n\n Document \n159915 A COOPERATIVE EFFECT-BASED DECISION SUPPORT MO... \\\n62232 URBAN STREET VITALITY \n18729 CONTINUOUS ATTRIBUTE DISCRETISATION \n146728 VENTRICULAR FIBRILLATION AND TACHYCARDIA CLASS... \n157327 MAPPING AND MODELLING DEFECT DATA FROM UAV CAP... \n... ... \n64501 LITTER PRODUCTION \n114208 MIXING-STATE \n90681 SAR-OPTICAL \n117081 INNATE IMMUNE-RESPONSE \n146051 LOW-CYCLE FATIGUE LIFETIME ESTIMATION AND PRED... \n\n keyword_all \n159915 TEAM FORMATION; COOPERATIVE EFFECT; COVERING; ... \\\n62232 NaN \n18729 NaN \n146728 MACHINE LEARNING; PUBLIC DOMAIN ELECTROCARDIOG... \n157327 UNMANNED AERIAL VEHICLE ; BUILDING INFORMATION... \n... ... \n64501 NaN \n114208 NaN \n90681 NaN \n117081 NaN \n146051 GAS TURBINE; LCF; COMPRESSOR; PREDICTIVE MAINT... \n\n vector vector_norm \n159915 [0.037737507, 0.03163352, -0.023620829, -0.019... 1.0 \n62232 [0.05269539, -0.00761333, -0.043163303, -0.023... 1.0 \n18729 [0.048983343, -0.012124105, -0.0497743, -0.024... 1.0 \n146728 [0.041310925, 0.03034619, -0.020368228, -0.021... 1.0 \n157327 [0.04185079, 0.03162047, -0.022166232, -0.0242... 1.0 \n... ... ... \n64501 [0.04933314, 0.0028764526, -0.053359915, -0.03... 1.0 \n114208 [0.04587132, -0.014809725, -0.037412226, -0.02... 1.0 \n90681 [0.049859583, 0.00093559147, -0.040774263, -0.... 1.0 \n117081 [0.04046586, -0.009001592, -0.043696642, -0.02... 1.0 \n146051 [0.038426127, 0.032835256, -0.015592382, -0.02... 1.0 \n\n[100 rows x 6 columns]", + "text/html": "
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UT (Unique WOS ID)TypeDocumentkeyword_allvectorvector_norm
159915WOS:000493345400001docA COOPERATIVE EFFECT-BASED DECISION SUPPORT MO...TEAM FORMATION; COOPERATIVE EFFECT; COVERING; ...[0.037737507, 0.03163352, -0.023620829, -0.019...1.0
62232kw_120676kwURBAN STREET VITALITYNaN[0.05269539, -0.00761333, -0.043163303, -0.023...1.0
18729kw_28349kwCONTINUOUS ATTRIBUTE DISCRETISATIONNaN[0.048983343, -0.012124105, -0.0497743, -0.024...1.0
146728WOS:000337736000001docVENTRICULAR FIBRILLATION AND TACHYCARDIA CLASS...MACHINE LEARNING; PUBLIC DOMAIN ELECTROCARDIOG...[0.041310925, 0.03034619, -0.020368228, -0.021...1.0
157327WOS:000793790600002docMAPPING AND MODELLING DEFECT DATA FROM UAV CAP...UNMANNED AERIAL VEHICLE ; BUILDING INFORMATION...[0.04185079, 0.03162047, -0.022166232, -0.0242...1.0
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64501kw_126785kwLITTER PRODUCTIONNaN[0.04933314, 0.0028764526, -0.053359915, -0.03...1.0
114208kw_304857kwMIXING-STATENaN[0.04587132, -0.014809725, -0.037412226, -0.02...1.0
90681kw_207619kwSAR-OPTICALNaN[0.049859583, 0.00093559147, -0.040774263, -0....1.0
117081kw_322648kwINNATE IMMUNE-RESPONSENaN[0.04046586, -0.009001592, -0.043696642, -0.02...1.0
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" + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tnse_nlp.head(100)" + ], "metadata": { "collapsed": false } }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 41, + "outputs": [ + { + "data": { + "text/plain": " UT (Unique WOS ID) TNSE-X TNSE-Y\n0 kw_0 127.197891 114.109520\n1 kw_1 -21.558281 -202.681183\n2 kw_2 15.277477 -37.555573\n3 kw_3 54.094421 -164.205536\n4 kw_4 -165.029221 -96.129143", + "text/html": "
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UT (Unique WOS ID)TNSE-XTNSE-Y
0kw_0127.197891114.109520
1kw_1-21.558281-202.681183
2kw_215.277477-37.555573
3kw_354.094421-164.205536
4kw_4-165.029221-96.129143
\n
" + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Simple NLP part" + "from sklearn.manifold import TSNE\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "# % matplotlib inline\n", + "\n", + "vector_data = pd.DataFrame(tnse_nlp[\"vector\"].to_list(), index=tnse_nlp[record_col]).reset_index()\n", + "vector_data.head()\n", + "\n", + "labels = vector_data.values[:, 0]\n", + "record_vectors = vector_data.values[:, 1:]\n", + "\n", + "tsne_model = TSNE(perplexity=30, n_components=2, init='pca', n_iter=5000, random_state=42, metric='cosine')\n", + "tnse_2d = tsne_model.fit_transform(record_vectors)\n", + "tnse_data = pd.DataFrame(tnse_2d, index=labels).reset_index()\n", + "tnse_data.columns = [record_col, \"TNSE-X\", \"TNSE-Y\"]\n", + "tnse_data.head()" ], "metadata": { "collapsed": false @@ -1143,29 +1082,43 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 42, "outputs": [ { "data": { - "text/plain": "" + "text/plain": "" }, - "execution_count": 32, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": "
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\n" + "image/png": 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\n" }, "metadata": {}, "output_type": "display_data" } ], "source": [ - "import spacy\n", + "wos_plot = tnse_nlp.merge(tnse_data, on=record_col)\n", "\n", - "nlp = spacy.load(\"en_core_web_lg\")\n", + "g = sns.scatterplot(wos_plot, x=\"TNSE-X\", y=\"TNSE-Y\",\n", + " hue='Type', s=1)\n", + "g.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n", + "# wos_plot.head()\n", + "# wos_nlp = wos_plot[[record_col, \"Document\", \"keyword_all\", \"TNSE-X\", \"TNSE-Y\"]]\n" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ "wos_nlp = wos.merge(wos_kwd_concat, on=record_col)\n", "wos_nlp[\"Document\"] = wos_nlp[\"Article Title\"].str.cat(wos_nlp[[\"Abstract\", \"keyword_all\"]].fillna(\"\"), sep=' - ')\n", "# wos_kwd_test[\"BERT_KWDS\"] = wos_kwd_test[\"Document\"].map(kwd_extract)\n", @@ -1188,18 +1141,8 @@ }, { "cell_type": "code", - "execution_count": 35, - "outputs": [ - { - "data": { - "text/plain": " UT (Unique WOS ID) TNSE-X TNSE-Y\n0 WOS:000641589600020 131.783783 -4.202979\n1 WOS:000590197400003 74.897812 89.280334\n2 WOS:000510863400004 84.939049 23.416033\n3 WOS:000403039400031 -39.527546 54.230900\n4 WOS:000439363600016 -59.109379 72.877693", - "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
UT (Unique WOS ID)TNSE-XTNSE-Y
0WOS:000641589600020131.783783-4.202979
1WOS:00059019740000374.89781289.280334
2WOS:00051086340000484.93904923.416033
3WOS:000403039400031-39.52754654.230900
4WOS:000439363600016-59.10937972.877693
\n
" - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "from sklearn.manifold import TSNE\n", "import matplotlib.pyplot as plt\n", @@ -1224,17 +1167,8 @@ }, { "cell_type": "code", - "execution_count": 36, - "outputs": [ - { - "data": { - "text/plain": "
", - "image/png": 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\n" - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "outputs": [], "source": [ "wos_plot = wos_nlp.merge(tnse_data, on=record_col)\n", "\n", @@ -1250,7 +1184,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": null, "outputs": [], "source": [ "\n", @@ -1262,7 +1196,7 @@ }, { "cell_type": "code", - "execution_count": 93, + "execution_count": null, "outputs": [], "source": [ "wos_nlp.to_csv(f\"{outdir}/wos_nlp.csv\", index=False, sep='\\t')" @@ -1273,17 +1207,8 @@ }, { "cell_type": "code", - "execution_count": 37, - "outputs": [ - { - "data": { - "text/plain": "Index(['UT (Unique WOS ID)', 'Document', 'keyword_all', 'TNSE-X', 'TNSE-Y'], dtype='object')" - }, - "execution_count": 37, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "wos_nlp.columns" ], @@ -1293,25 +1218,8 @@ }, { "cell_type": "code", - "execution_count": 94, - "outputs": [ - { - "data": { - "text/plain": "" - }, - "execution_count": 94, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": "
", - "image/png": 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\n" - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "outputs": [], "source": [ "import spacy\n", "\n", @@ -1337,18 +1245,8 @@ }, { "cell_type": "code", - "execution_count": 95, - "outputs": [ - { - "data": { - "text/plain": " UT (Unique WOS ID) TNSE-X TNSE-Y\n0 COMPARATIVE GENOMICS -114.811630 -43.915569\n1 ANAMMOX 8.044455 100.761032\n2 KUENENIA STUTTGARTIENSIS 8.044455 100.761032\n3 METAGENOMICS 8.044455 100.761032\n4 ENRICHMENT CULTURE -99.356590 -78.270439", - "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
UT (Unique WOS ID)TNSE-XTNSE-Y
0COMPARATIVE GENOMICS-114.811630-43.915569
1ANAMMOX8.044455100.761032
2KUENENIA STUTTGARTIENSIS8.044455100.761032
3METAGENOMICS8.044455100.761032
4ENRICHMENT CULTURE-99.356590-78.270439
\n
" - }, - "execution_count": 95, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "outputs": [], "source": [ "from sklearn.manifold import TSNE\n", "import matplotlib.pyplot as plt\n", @@ -1373,32 +1271,8 @@ }, { "cell_type": "code", - "execution_count": 96, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" - ] - }, - { - "data": { - "text/plain": "" - }, - "execution_count": 96, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": "
", - "image/png": 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0s7W4hkcWGjhS40ITFECcNpCHvzPlujUvbMi3iLSwQDCOEWlQwbhDCLXrj9nmYunvCvmsrJadpTb+ftxOkcV5yd8byQQ3zaBl4+q5lFSdo6ndy26zAwCH28PqdIMici4m1jOTonk2O+m6CTWzzcX7X55ma3ENOZlG8k86aWr3cqaxHU9PL6s2HbhmqVl5MP1Ij+UWWi+6jUAguLERkTWBQHBZ2F2dFJTV8sr9M7Gdk4r5d3xt5ztG3SV/92Jia3laHKGB/mwuqgRgXWYiDy1IYHla3JDnGCt2ltRQ7eoak6iTtd5NWV0r2SlR7LM243B7WJGmp6v7PLvNDlak6Qekc8cKWYzB0KYKu6uTnaU2HlwwGX2oakxfVyAQfHsIsSYQCC6L7SU2couqyck08qnZwer5BuK0gYpv2aW4mFiR05kv7jpOeJBqVKnV/mzMt6AdZRp0Z0kN3zjcbC2uAa6+e3SRKYqMRB0nat0APLhgMh8fPsuqeXHoNWq6us9f9nOabS5KzjTi7+c34jHJ+z14/802F2kGLdsfW8y+8noeWjTlsl9fIBDcGAixJriuiNFS4w9ZFOwrrwdgzijr1UZLZlI07z08X/m/LDouxcZ8C+8USqOigEsKtmpXl1Jbpp5wVbsMwGlnKyHqiUSEqGhq9/Lx4bNkJOqICgkgIkTF99Muz3DXbHPx+30V1Lm6KKtrBWBqdOiw7/Wz2Um8nW/hx+kGGls9FJ5yUlrdzC/vSQYQQk0gGOcIsSa4bojOzvHFzpIaTDEaWjq9eL3dlNW1kpNlGlOhJlN7roNth2u4c3okeysa+eGcOKI0gZxxtuHq6uG2YQTiep+IHG1kTRad6glc1WipnSU1rExPIDMpmrPNHRyrdbHf2sSKNGkw/KaiajaunjsknTsaIkPVBAZMBKCpq4fNu46Ts3TaEPH1dr6FdwuteLq78Z7vo6ndC0DBKSc7S2289/B8MZlBIBjHCLEmuG6Izs7xw86SGp7fdYLU2DCyk2PYfdzBmowE5bHRpkAvRZHFSXiQitfyTuJwe3B3dhOrDeTIWRd7TzVwuymCHV/b0WvUrLt96hBRtv4yU5lXm/rcvLeCN76oAKQ0aO6+0zjcHl64NwltsApPTy8/XZx4RUIpzaCl9lwH7395mqXJMewsteFwe/hndTOTdcEDxOqP0w20dnk5YW+luLKZBxdMpqTqHIum6HC4PbR0eq/qOAUCwfVFiDXBdUUItfGBLMbsri7yy+uVVN/W4hol7Xilgm1jvoUfpRs47Wxl7dYSnltmIn3KJBLC1eQWVaMJCgA8zIrX0NLZTUaiju8YdbyaV06UJvCyIlZXknbPLbDww/mGAb+37WAV2mAVb3xRwSMLDbR19Shp4d8+MIuV6QkUWZys3VrCljXpl/V6/VmeFkf8pGDSDFqWzYjmQIWT1MlDo4px2iC+P2cyqzYdYNW8OD4+fBa9Ro2njwHWJwKBYHwybqw7Xn/9dRYsWEBYWBjR0dH88Ic/5NSpUwO26erq4sknnyQiIoLQ0FBWrVpFfX39gG1qamq47777CA4OJjo6ml/96lf09PR8m4ciEIxb8svryTRJXZ+7zQ4eXDCZ200RLDJFXdHzyXVmfz5YybToMJ7OMvFmgdTZeKS2lVXz4iiubKbO1YUpMlhJCfpNgOyUKOYkTBrV6xRZnJhtLv58sJKdJTWj3r/cAgsb9ljZ/KUVu6uTLV9a2Xawipc//YYzDW08stCANljNzqO1vPzpN+QsnaaI1sykaLasSb/qNLEclUszaHn8rqQhz5dntiuPv3L/THZ8bWdNRgIr5+hZNiOa5+6ZQWZStLKdQCAYf4wbsbZv3z6efPJJDh48yBdffEF3dzf33HMP7e3tyjbPPvssn376KX/5y1/Yt28fdrudlStXKo+fP3+e++67D6/Xy4EDB9i6dSt/+tOfePnll6/HIQkE4wq7qwuQarCSY8NYkaaXIjjhwVccIZ2sDUSvURPsH0D+iTreKbTys9uN7DY7FH+y7JQomtq9nG3xsNvsYJ5Rxw/nG5gTF872EtslX0OOcBWU1fKfRdUUnW4clXAx21xMjQplTUYCdyXH8PejZ3n9MwtNbV5SY8OoaGzjSI2LdwutaIICyMk0khqvBaT0KHBN6vn6k2e2s377Ud7Ot0gWHvtO83SWCUt9G5bGDmUf5O029vNaE+JNIBg/jJs06D/+8Y8B///Tn/5EdHQ0paWl3HHHHbS0tPC///f/5qOPPuKuu+4C4I9//CMpKSkcPHiQRYsW8fnnn/PNN9+Qn59PTEwMc+fO5dVXX+X555/n//l//h9UKuFDNFpEF+etx7ToULw9Ug3Zjq/trEjTkxobRlNbF0UW5xUJk5XpCThautiwx8qv756OXqPG0erhZ7cbKa5sZrdvgoHD7SE6VI1eoyZBG8jS3xWSkaijuLIZuHjtWWZSNL/IMvFWoZXslCh2mx2X9IQz21w8+VEpIBnzLk2K5pv6Vn52u5F/VkuvGaqWvj5TY8OU4fGhgQ0cOt2g1LGtu3P6Zb8noyHPbGdOwiSWp8XxlLON0upmiiubeWShgT3l9ZTVtZKRqKOsVuqknZMwiZ9nGnnH58c2WRvI87tOsBGuqPFBMBDxfSi41owbsTaYlpYWAHQ66Uu3tLSU7u5usrOzlW2Sk5NJSEiguLiYRYsWUVxczOzZs4mJiVG2uffee3niiScoKyvjtttuG/I6Ho8Hj8ej/N/tdl+rQxo3iC7OWxN5UV+QGMXdyTF4enoxRYSSdpXWHTnLkpgUosLR5iU7JZoPD9lIjQ1DExTAmowEzvf2EasN5KSjlZ9mGFmZnkCQyp9th2vIyTJdsknA7uqkq6eb1NgwAgMm8twy0yWtLNIMWl57YDbHfdG10hoXJVXncLg9pMaGUVbXysKp0ndPWV0rOZlGcouqidMGMmVSMOuzTGMq1OTGizSDli1fWjlcc47PTzr41b0pGLSBNLYFA6CaKCVLUmPDyJwWwfYSGy0dXsKDVfxnUTU5WSb2lNfT1O7lmSwT8ZOC2fKllbV3mMZsX281xPeh4NtgXIq13t5efvGLX3D77bcza9YsABwOByqVCq1WO2DbmJgYHA6Hsk1/oSY/Lj82HK+//jr/7//7/47xEYxvRBfnrcu1isI0tnnJLbSSGhtGTqaRncccZCfH8E9fxOixTCOJkWFKPZg87WC080jvTo3H1XWe2yZrR9UIYXd1cqiygfeLqtFr1ESEqMhOieZIjYtYbSCzJ4dz0tFKrDaQ2xK0kklwlkk5hqZ2L+FXOaNU9peTU5hyY8XbvghhSdU5PvnaxpsF0v/vnB7J+d4+AFanG8grc9DU7uXNAt/7mmXiSHWzMmXh7UIrZ1s62PG1lA4Vgm0oo4mYie9DwbfBuBRrTz75JCdOnOCrr7665q/1wgsv8O///u/K/91uNwaD4Zq/7o2O+GISjCVP+6JjPUBuoZVnskzcMSOatwutStQqJ2ugmLicaF6aQUtkmHrU1+1BawMtXefRa9RSZ2pEKDtLbdxuigCgsc3DmcZ2IkKk0omMRB2h/hPIToni4e8YOeNs49W8cuYadVdk22G2uVi16QC/fWAWRacbWTUvjvK6Vt4utCqTEZ7xNWNsXD2XOQmTiNMGUWRx0tjuVSxEHlloIP+kU7I/8QnfjEQdSZHBkBLFfmsTOVkmIdSG4XIiZuL7UHCtGXdi7amnnmL37t18+eWXTJ48Wfm5Xq/H6/XicrkGRNfq6+vR6/XKNv/85z8HPJ/cLSpvMxi1Wo1arR7joxAIbh3ezbfQjRTtudiiJgu2UP8JSgpxx+OLiQxTg3/AVXuiXWpB7R9FCVL5c/xsC9+bpcfZ5qG5rQuH20N5XStlda08uGAyDreHO2dEsfdUAw/ON/DGFxVkJOpo6+rh0SWJilB7J9+iHNtI9J/SIA9c37h6LtsO1xARqlK85bJTopTJCHHaQHY8vniAGCypcbHlQDVrMhKIDFbxZoGVdUuMHDjdTFO7l4xEHe7Obtp7+jhR68bh9rCz1IbxMsaF3SqIiJngRmLcdIP29fXx1FNPsWvXLvbs2cPUqVMHPD5//nwCAgIoKChQfnbq1ClqamrIyMgAICMjg+PHj+N0OpVtvvjiCzQaDTNnzvx2DkQguIV4N9/C24VWdpbaWP3+Aeyuzkv+Tv9arzSDljht0JgMWr8YchRF3r/laXE8ushIzbkOSqrO8fHhszyVZaKp3cuKND3Hz7bwyEIDe081kD5Fsg95aXkyxZXNhAb6K/v+Tr6FjYVW3unXhTkYOYpmtrmUoewWRwvlzjbcnd1MjQglI1HHD+boyT/ZQGpsGCn6MBaZooZE7SIC/clOiUIXJAm19VkmPjX7ykDcHkLUE1lq0tHU7iUiREVOlompkSEsMkWJ7tBhEEJNcKMwoa+vr+9678RoyMnJ4aOPPuJvf/sbM2bMUH4eHh5OUJD0gXriiSf47//+b/70pz+h0Wh4+umnAThw4AAgWXfMnTuXuLg43njjDRwOB//6r//Kz372M1577bVR7Yfb7SY8PJyWlhY0Gs0YH6VAcHPxbr6F7aU2SRBM0V3VWKfRYra5aOn0Mi1aMoMd7YI7XH2S3dXJvvJ6unt6eTWvnOyUKJIig8ktquaJTCOBAQEcrJLSi8/eZWK2YWizxeVE1nILLBysamZWXBibv7owpmpnSQ1BKkkEdnp7WGSKIk4bpBxrZlI0ZpuL//i8nOwZ0YQG+nPkrIuPD59lTUYCn5XVs3K+QZmCINfhrZwbT/asWI7VnJOsPa5wLJZAMB4Yz+v3uBFrEyYMP2n5j3/8I//jf/wPQDLFfe6559i2bRsej4d7772X3NzcASnO6upqnnjiCfbu3UtISAhr1qzhN7/5Df7+o8sIj+eTLRBcD97Nt+DvB4/fNVSwjLXlgWy5MTUyhDON7aRPmcS0iFBWXiIFeyk25FvYWWpj5XwDuYVWpZngtw/4GpxausZMiOYWWNCHBxKlCbxoXZ58rA63hy1r0pU6uV/fPV1JyQKcaWxXBNoP5uj52zEHjy5MoMbVyd5TDcrYrjyzXQg1wU3NeF6/x41Yu1EYzydbILiRuFaWBxvyLezzeY09stBAZ/d5dnxtv+LXkacYyDYhcnfmK/fP5KFFU751jy15PFecNohNeyz8+bCNn2YY+W5aPNsOVvKdxCj+ftxOeZ3UrVrn6iLZN3JK9sfbbXaQkahT/OFeXJ4ihJrgpmc8r9/jrsFAIBBcOf0L2a83Y1XALdeZ/bXUxpKkaCXVt2peHEdqXJTVtfJEppHTztYrei05Yib/vTwtjn0Jk2hs9WB3dbL6/QM8u2w61a6uUdfWyQLvcs+HPJ7rL6U2tj+2mMfvSkLl78d0vYZ/mGvZVFRNoH8A+61NRISoaPecp6yuFU1QALPiwshOieJMQzsPLphMZGggEaEqdpuHty0SCAQ3DkKsCQS3CGabi4KyWkAqfr/SqQNjydUKNTnKtW6Jkc1fVQPw6MIE/n7CoXRuPpFpZEpk2FUb9/ansdXDqk0H2LImnamRIfyzulnxKxuNSe+2g5X4+QdQ39JBWa1WMem9VH3bet9jP+qX1p2u1ygD45+9y8SSpGj6gO2lNmWSAcCnZgez4qVowvGzLTS1N/DTDCOZ0yJFVE0guMERYk0guEUoOOUkt6ga/AM4UOHkzQLrVQ8a37y3gnV3TmdDvuWad2wOpsjiZP32ozyeaWSTz4dNFlVq/4lEaQIpd7axr7yeBxdduTntcKQZtIptxrToMI7VnCMmPHhU78H2EhtFVsmcNjU2jP3WJrTBKqzONjb6xkGNRrDJyAPjAT4/Wc/BKmkclmzk++EhG49nGn2judxEhKhYatIRpArg9c8s6DVqpWFBIBDcmAixJhDcAmzeW0FzWxc/u90IPd28WVTN+iyT0jF5pc/5xhcVtPX0kesTGd+mYMtMiuaV+2fy8qffDBk7JU8OWM6l/d2uFDl9GacNIk4bxPJR/l6QH8yeHM7CqTrO9/WRoA0eENkaTqhdrC5u28GqAeOzvq5x8X9LbdybGsPW4hrWLjbS2dNHqq9urayulaZ2L7ebItBr1PxkwbV5fwQCwdgxbnzWBALBlfHBV5W88UUFjW0e/P2QpgFkGtlYaOV/7jg2Ku+zwZhtLtT+E1mTkUBydOioZnReCXZXJztLarC7Oofdz4cWTZHSfxd57RtNiKRO1nL8bAtTIkJYmhQ9YCTVYKEmH7fsATf4Pdh2sIqXP/2GbQerAEnATgr0lzzVAlWsmhfHlgPVlFSd47YELbMnh7MiTU/6lEnEhQcTEaLiwJlmiixOxoqxfC6BQCAhukEvk/HcTSK4NdmQb6G5rYs2Tw+7zQ7WLjby3ycc/Gi+gR9fZtRp28EqJuuCeXHXcRxuDyvS9ISq/Uc9c/NyKLI4+ftxO5OCAujtgy0Hqoc49o8VcqF/f9+ya8lo6gVls9wdjy8GIDJMzdLfFQ55DwZH1gClS1SuUcs/2UBGoo4Q9UTyTzag10hTWR5dmEByXPiYHW+e2c6+CidLp0eLOjjBDcd4Xr9FZE0guImRHfF1oYHsNjvIToni0JlmHG4P/7fUxkFrw6ifa9vBKnL3nebFXceZFa9RLCD2nmpgQ0EFZptrzPbbbHPx4q7j7Pjazu7jDk46Wvl5ppH/+Lz8iiKBl3qtVZsOsO1gFR/9s4oXdx1n0x7LmB7PYEYr1LasSWfVpgM8+VEpgPL//u/BYKEGsHh6NA63hztMUbR7zvNYppE4bSD5JxvIToni0YUJvPfwfNbdOf2qhZrd1cmWL63YXZ2U289JNikVzjE/TwLBrYyoWRMIbmLk9KBRG0hqbBhJ+nBO1Lp59i4T+vDLmwep9vdj5XwD+8rryT/ZwNrFRtZkJBDgN4HFw4w+Gon+zQgjNSYcqHByf5qeE3apCL+rp5f/LKrmqSzTJSOBG/ItpCcMnSQAQyNasiDbuHou7395Wvn5nw/baOnqBrjkcdldnZx2thIepLqsYfEXez45ohYZplYia42tHqXrM04bdNE6tjSDdsA0grwyB8WVzaxbYiQoIIAPDtWwcFrUVe2nvK85H5ZQVtcKQGigikcWGnC4uwDYWVIjZo4KBGOAEGsCwU3Os9lJ2F2d/PWYndXpBiIC/QfUSY2GnSU1PL/rBKvmxVFW18qKND3/fcKBw+0hNTaMf1186ecz21wUnHKys9Sm/GykxgRjZCifmGs509hOcWUzjyw08FSWiWcuURcnTxrILZQ6XcODVKQZtLydbyEpOpT3vzxN2VkX359nUOw3UmPDWJ1uYPE0HZu/qlZsQMrqWtEFN1xUrJltLv54oBK1/4UkxcPfmTIqgfdfJTZ+MczxxGmDFIG29HeFpMaGUVbXil6jZsuadEWwrd1aMmJa2GxzsX77UXZMCuahRVPo7ulldnwY/1lUTUaiDofbc9H9Gy1x2iByH0nnH+Za1t5hAqSJFfknnfy11MaGPdL5FYJNILg6hFgTCG5gRjNXcjTEaYP4zao5xGmDLluowYXFNkjlT6jan5Kqc/zLfAPhgf5kz4q9ZDRpZ0kNGwoqyE6RoloWRwvhQQGkxoYR6j90lJwcEZoTF86BM808cJthVJE7WfTpQ1WEB6l4+W/HWZocQ26hlZ9nGgE4Zm/hmL2FjCkRrEjTMztWw8uffsNvH5hFTqaR9p4+MhJ1pOjDLhp9kiNgDy6YzN5TUjrZ4fbQ0tnNSytmjfieyNGoqVEhw0YW7a5OXv7bccrqWtmyJp22rh7e//I0z90zg/AgFXqNmhd3HWfj6rms2nRgWGPh/tYidlcnR2pd7DY7eDLLxNfVzbxy/8wxq/2L0wYpQg1gWnQoDreHGlcHL9ybJISaQDAGiJo1geAG5Z18C5VNbWzMt4zJ811tem5legJzEibxWVk9t5t0rEo38OiSxEs+b5HFyfO7TjArXsORGhcRISryTzZQ7rOQKDrdRJ7ZPuT3lqfF8fhdSfxm1ZzLEhbpCVpe/vQbjlZLXmYWRwtrMhL45JhDSde1e87zTb1bqrmraCQjUUeQyp/comqmRYaSOS2C+9LiL/q6B60NiuFsRIgKgHVLjOSfbKCx9eKRq6UmHbvNDmqa2oY99rK6Vn77wCze/PwU67cfJVYbyIu7jvPy347z4vIU3nt4Pq/lnVRSosPR31pk5W2TeXDBZEL8J/j81saebQerFO+7NRkJ7Pjazifmumta+ycQ3CoIsSYQ3KD0ALvNDjw93QOKtXeW1GC2ua5bAbfD7eGTYw62l9guvTEX/NDyTzZwW4KW5NgwUmPDWGrS8ZMFhkuKh8sVmZlJ0eRkmcg/5SQ7JYo6Vxdbi2v43iw9qbFhtHvO4+7sZr+1idTYMIwRwWROi5DGSP0qi4cWTWHdndMvKtTsrk4+OFhNiHoiHx8+C8D3Zulp7ui+ZNTqH+ZacouqeSzTyG6zgzkJk4Zsk5Go46/H7DS1e8lOkaJ7UyNDKKtr5bW8k9Se68Dh9vDm56cueR2YbS7Wbi1B7e/HG19U8FSWCbW/35hcP0UWJ1u+tCoWIkdqXGSnRKH2n8DaxUZitYGUnGkUgk0guEqEWBMIblCezU4iJ8vETxZdiF7tLKnhr8fsrNp0gM1fWnkn38K7+ZZvzdtKnue5cr7hsnzVHlo0hZeWJ/PhIRuenl7Sp0wit6iaxdOjyU6JGlawXCkbfR2wafFhnKh109TuZd0Sya6krK6VEPVEmtq9ONwe0qdMorHNwxtfVFBkcY5aGMZpg3junhmcqHXz67unE6sNZFJQAEunRw/bndmftXeYeOHeJBYmRo04G1UWsA63B70mkBO1bkLUE3ks08iseA3rtx9l4+q5SqRwJOSU6qp5cWwtruFntxtpbOtiQ0EFv997dR28RRYna7eW8Mfias61e3kmy8RfSm0EBkzkk2MOthyopt1znjPNHazadEAINoHgKhA+a5fJePBpuViXmGB8Ixf6ZyTqcHd2K4XnESEqnrtnxnWf9Xkp8sx2XB1eAJYmx1yyq/FykaNF20ukJoOcLBO5hVb0GjXZKdEcqXGRPkVK5c6K15CiD2dPeT2r0w2XFFnD0d+f7WprwOT3oX+HZUaijtviw8gtqkavUTMrXsOJWjcvLk+RGggu4Tsn+56V9xN1mqAA3J3dTI0Koav7/EXr6y5FkcXJcZuLz0/Wc98sPW98UUF2ShSRoWqCAyay5UA1qbFhPHbHNDq9PaJ+TXBdGQ/r90iIBoObDNntfKQ7dsH4JyNRR3FlMzmZRpravaycbxjRquJGYzij1JGuU7PNRe25DkID/Wlwd11yobe7Oln9/gEcbg/7fpWldL1OBPaU1wMokag7Z0Tx8eGzJEUGU1bXijZYdUXHIwulsRBq/T+3r/xgNk9+VIq7s5t91mYyEnXEaQNJigqlztWlCLXIMPWIz2m2udh2uIYzje1EhKgoq2tl1bw4ZcD97Mnh7DY7eGKp57K/K/LMds42t7PuzukcrXFRVtfKbQlaUmPDqHN1UefqQhMUwGOZRv52zMHZ5nbe+KICEJ2hAsGVINKgNxlymkoItZuTlekJ/HBOHK/cP5NlqfHkLJ3Gs9lJYy7UNoxRU8PmvRVX9HsffFXJHw9Usn77UV7cdZzj9hZ2ltQM2W7THsuA2qvvz9Gj16jZXmIjShNIkcXJX0ptaIIC0ASrpVq55Bg+PnyWdUuM0uitLNN1d9sf/LmVRdhjd0xTBOZ+axN/LK7m0UVGZQKBPIZqOOTnmBWvoandS06mkR1f25WRUx8fPsuKNP1l72ue2c5reSd544sKNu+t4Glfuj7/pJOmdi+x2kDK6lqZFhXC+0XVrJyjJzkunNTYMEwx4yuaIRDcKIjI2k2IEGo3N/0jE9di9JI89QCubDC7nBrzmwBvFkjPs+7O6aP+/W0Hq3g1r5wHF0xGr1GzYraeP+yv5pksSXxs3luBp6ePCcBbhVbOdXaz5napru8nixLx9w9QUp8vLk8hZ+k0unt6eTWvnPVZJjYWWvntA7MwxWj41Oxgdbrhso/xWtD/cxunDWL7Y5LXWmpsGO7ObhxuD1vWpJOZFM0iU9Qlb8zitEH88p5kfr+vgogQlTITdp9VqofTa9Tck6K/7GtIFrZyZG3bwaoBKeeVc4I5oVGTf9JJTqaRnccc6LUhvPKD2dfkehUIbgVEzdplMp5z3oJvlw++qqSpq+eaDDi/1ozk/5V/ou6ivmpFFif7LE62FteQkagjIlTFr+5NGfUNhN3VyYfFlXxqdjA1MoQQ9UTaPeeZFhXCA7cZOHS6Abu7iw8P2Vg1Lw5DeDAPDDPfdGdJjeQJF+ivmMgCHKlx8ZdSGz+eb2C9zyz4Rr+56R8567+vo913s83FR/+sUtKfqbFhxGoDefg7xjGJyJptLvaecvJOoZWf3W7kD/urlXNfUnUOgPceni+EmuC6M57XbxFZEwiuAR98VUlFY5ti6yALn/EgDmBoRM3u6mT7wUqau87zTcEp1i+bMexxHKtxUevqJDU2TJk+MC0ilKdGKVjjtEEYJoWQnRKNJljNkepmiiubmRMfRmSYmuS4cN74ooIVaXrsri7umx037H6sTE/gg68qWZ6WqESj4MJMzvW+/RkP52K4fbyc2tQ0g5bIsBk0tnpo6fQyLTpsxOe9XMw2l2Lgm5NlYmepjeyUKE7UujFGBONwe/jtA7OEUBMIrhIRWbtMxrMyF3y79I+sbd5bQVdPH7UtHcyM0VzRFIGx5GLdi9sOVg3pjJTHODncHjISdXzHqBtRgG3Mt+Du8uLp6SUiNHDYkUqXQp4pmWe2Y3G28eN+0bMiixNzjYu0izRVfPBVJa/mlfPS8uTr/l5fK24U4f9OvoWJE2DDHitPZpnYUWrjh3P0BPoHXPQcCQTfNuN5/RaRNYHgGiGLhNwCC23ebg6cbua2BC2v5pXT09s7YETPWJBnttPg7sLTc56IUPWIXXdmm0sZFC6PI9rn65ZsavOSX15PW1e3Umdmd3X6IiaS9UVxZTM/nDNyQf767CSlk/NKC/flfV+eFsfyQY9lJkVfUgDI7/3NKtTgxogKvpdvYWOhlV9kmRRhHBOqInffaQAyZwihJhCMBSKydpmMZ2Uu+PaRB32faWhX6oVA8rr65T3Jl5UeGq6OTEY2y70tPox91mY0QQFkz4geUazIkbWdJTV8cLBa8fQqrpRsIowRwczUa5QIm93VybGac5xytpGgDRT2CzcwuQUWliRFf2upx/fyLTw5TNr8WM056lwdTNdrRHRNcEMwntdvEVkTCK4haQYtP12cyNHqZmZPbiNeE8j5XinicLlCbaQOzTyznQ0FFTjcHsUoNyfTyM6jtcw16oZ9nTSDljyzned3nSA1NkwxXwWUWrMVaXom64LJTIomThtEnDZoSJTreiI74ot6qAvkFljYVmKjorGNlbdN/lZE0mChBtDY6uG1vJM43B7FHkQINoHgyhFiTSC4xqQZtEq68UpTV8tmRNPc1sWyQWkleXD2c8tMHDhzwZJhn7WZ76fFXlTILE+LYyPQ6e3B2tBKTYuHEPVEpkaGsHKOntyiahIiQi+6yL6Tb+HpYRbr/scqdzP+w1yrpH4/+KpySNSvyOKkrauH0EDpa+liryunch9ZKNluCMEm4emTRlQ1tXlZu7WEnCzTRbuRzTYXBaecY96xnGbQsnK+gSPVzew2Oy55HQkEgosjxJpA8C1xNTVGIznlZyZFs2VNOtOiw/jHN/XMnhwOcNEUKEgC6rSzldBAf7YdlsxmiyubWZORQFO7Vxk0nltoxThC2vMdX70SMECw9e9UBMm4Ve4Q7OruJVTtz6t55cCFmrIii5M3Pz9FrDaQKbpgdh938NoDsy+6wD+4YDIfHrKhCVYLseZDFl07S22K79kEGLbJw2xz8ZfSmiEdy2O5LxvyLdxm1I1L+xqB4EZCiDWB4AZG7syUo1NFFucQASP/P/eRdBpbPUSGqS8qDPvPnkyNDaOp3cuzy6azwKjjcHUzZxrb0WvUfGVt5td3Tx+xPm1VuoHKpjZWDTKVlc1a9/kaFbJTosg/2UBOppGKxjbuSdHzVJaJqdGhgCQazjZ3AJB/soE1GQk43B7KzrpGFGuyONOFBgohMIhns5MUgT2SUINv5z28lufG7upkZ4mNlcP47AkENxuiweAyuVEKFG+Utn3B2CMPO29s87Kx0Mqv755Oc4cXfz84VtvKQwsSrno80oZ8i+Jh9mSWlJp8r9DKC/cmkT41kpIzjbz+mYWNq+de9LVGug63fGnlE3MdZXWtPJZpZKJ/gGL98VimkfeLJOPU7BnRvJpXznPLTFSd62C/tQlAmVpwqUHlgpuHy/lOs7s62VhwiklBAXT39rF2yTTxfSi4JDfK+n0liNmg4xA5zTTSTEDB1TPcbMwPvqq85q+bZ7azfvtRvnG42egb4VPj6qS4spm/HnNQXNlMuf0cH3xVOSDadjnYXZ3kFlq5zajjaZ8v1nu+13r9M+m4195huqRQg+FTu2abiz8WVwPSqKSJQG6hleyUaPQaNX875iAjUcdCo45X88rZuHouqZO1lNe1EhGi4s4ZUew+7uCV+2cKoXYLsHlvBRvyLfzPHcfYkG8Z1fV8rOYcMSEB/GF/NSGBqlEJtdwCC++O0cxbgeDbRqRBxyFiWPu1pX/n5TJf12ZugYUNe6SfXUvvruVpcTzb0MaGPVbFEf52UwRN7V4iQlRMjQyhues8O4+d4Uiti3tS9KzffpSNq+cSPyl4VOKm//Wz7WAVESEqvj9Hr8x3lJ9jOKF2MfsQmYJTThxuDwBTI0PY6RNnHx6ysSYjgc/K6vmOUceT2UkkRocO2O8GdxdNbR5eXJ5y3YerC649m/dW8MGhGhxuDzm+GslV86TzfrF6RVeHl53HHJdsoJCRu2QjQlQAo56oIRDcKAixNk4RQu3asTrdAD3dpCdo+f2+Cu4wRbFhj7SINHX1UGRxUlLjuib1OGabi+4+eGShgYhAfxxuDzEhAUyNDKG4splV8+LYe6oBh9vDjKhQ6lwd/CLLxGt5J8lOiabolHPYWZmDidMGUWRx8vKn3/DK/TNR+/uRk2m86FDz0Q547/+YxdFC+pRJAGQk6ggJVHFvagxvF1qZk6Bl/faj6DVq3nt4vugWvAVZOC2KotNS6rumxUNOlon0UUw90AarcLg9WBwtw9ZxDqbX1yWbnRLNnATtWO2+QPCtIcSaQDCIOG0QqxclcqzmHPknG1iQMIkVaXp2fG0nNTaM+pYOdnxtB8a2gNpsc/HkR6U43B70GjUvLk9ROvoyEnWkxoYRGRJARIiKlfMN/PmwDeBCVKKomkcWGti6v5I1tydeUrDJnaTyQnexmqFNeyShtiYjgXDVpasnVMBbvkhdrs/h3hgBO3x1a799YBZnnG3oNWqmRoZQcqZxxKjgu/kWEQm5DsjGybLNit3VSWOrZ0xT02kGLb+8J5mj1c18U+9m9SibBWTbmdBA/1GJfPn6mXOF46+2fGmlxdsrmlkE1w0h1gSCYZBNYDciLQy5BRalq3FpcgyPXSIKdaXMitcAblbONxA/KZhth2vQa9RMiwqhp7eP94uqB6RHWzq7mRUPbm8v2SlRnG6QDG0D1QGjWlj6L1wXWyQfv0t6LpW/36jGZMlGqU9mJxGu8uP1zyzs+1UWAUBidOiAFOfFRm/1twcZSbCJZpuxQxZk1no3z+86wbN3mdiwx4qn5zxvfFGh3ETIXnjTosOu+r2/Uh/Cy02TX67gl8Xqli+t2FydfHhIujkSgk1wPRDdoJfJeO4mEVwduQUW6lq7lDTkK/fPHDLw/GrJM9t5Le8k7z08X5ky8Im5lgUJk7C5Osk/KRVfr5xvYGepVINzT0oMP5xvoLFVqhMbzuR0NKmia8mVCCo57bo+yzSs8a78vKvfPyBq3MYAeTQawG6zg1Xz4ghV+9PU7qWk6hxTI0Nwd3aTPmUSJVXnKKtrZdW8OO6bHXfTpbAHz88VkbWbg/G8fotuUIFglPhNgI8Pn+VH8w2XLdQ25FtG1b27PC1OEWoA8ZOCyT/ZQPrUSO5KjgHgoXQDFkcLDreHe1Ji+PxkPcdqzikRiuGE2ou7jvPORTrhzDYX7+Rb2JBvUcY4jQa7q3PYztnB28Rpg9i0Z+TtdpbUKP/OM9sVofZ4phGTz49tOP5hrsXh9rDtcM1ld8UKLkyXsLs6+f2+CnabHXR1n+exTCP7rU1sLZbOy+2mCM40tivCLVYbyKp5cez42s7fj9sx21yjum7GSwd7mkGrCLUii5PvpsXT5em+rM+GQDCWjCux9uWXX3L//fcTFxfHhAkT+Otf/zrg8b6+Pl5++WViY2MJCgoiOzubioqKAds0Nzfzk5/8BI1Gg1ar5d/+7d9oa2v7Fo9CMF55/K4knltm4pnspMsWarmFVrYfrBzVl33/mqD+i0ZmUjTvPTyfnGVJvLRiFq/cPxO/CVBW10p148jX8Nc10mtuLLSSWzBUMJltLj4rq2VjoRWLo4W/m2svuZ95Zjvv5FvY/KWV3ELriIJtQ76F1e8fILfAwpsFVjbtGWrNsLOkhi/K69lZUqNYl+hDVWQk6ojThowYMdt2sIq9FY2sSNNzprGdcnvLRfdZMJD+FkAHrQ0EBkxk1bw4AgMm8rdjDlbM1rN2sZHdZgctnd1kp0TjcHuI1QbS7jlPS2c3qbFheHp6KTnTyKpNBy563Yw3yyFZqK3dWsL2EhuHzjRTUFY7bvZfcHMxrsRae3s7c+bM4b333hv28TfeeIONGzeyadMmDh06REhICPfeey9dXV3KNj/5yU8oKyvjiy++YPfu3Xz55Zf8/Oc//7YOQTDOkWu3LsbmvQNvEIzaQLJTojhS28oXV/BlP1i8gVRf9tCiKYqAvNh+PZOdxI/mG3j2LhM5y4ZuV1br4pNjUtorXhvEf59w0NLpHfH5NuZbeP/L02wstHKkxkVqbNiw28ki9f40PQETJ6DXqAFYu7VkgGBzdXjJP9mAq8MrFY6vnstDi6bwy3uSWeqLJg7HuXYvZxrbKak6B0BLl1cspJeBbOEC8EV5PQA7vrajDQrA4fbgaPWw5UA1K9L05J9soKe3TxkbVlwpzaGVI22Ha86xcfXcizYfXGvLofeugYfatOgw1mQk0NzWRVldK/uszfzDXDvmryMQXIpx1WCwfPlyli9fPuxjfX19vPXWW/yv//W/+MEPfgDABx98QExMDH/961958MEHOXnyJP/4xz84fPgw6enpALzzzjt873vf4z/+4z+IixM1L4KrY/PeCt74QhJr6+6cTm6BBY+vKrS4shl3Zzdx2pAxrXUbjYB85iK1NpN1wTjcHkLV/mwt9jU0RA8vwN7Lt3CuQ6qNe2ShgfyTTiJCVFgcLUM82OR/y151av+JPLokkdTJAzvy5OYC+W85ktbS6eXlvx3nlR/MHlYE5CxLorsP3i208uCCySxMjLqujQbv5VsIC/SnzdMzrCi+EZHfr4e/Y+Sjf1aj16gJVvmRnRJFSdU5MhJ16MPUPLhgslKruWpeHOV1rUSGSp28qbFh/GF/NS+tmDXq1xtr3su38JavEeXJK6wrezvfQtKg5pfGVg+1rk5O1LrJSNRRXNnMwqk6pflAIPi2GFeRtYtx5swZHA4H2dnZys/Cw8NZuHAhxcXFABQXF6PVahWhBpCdnY2fnx+HDh0a9nk9Hg9ut3vAH4FgJNbdOZ1f3z1dEWoHq5rJLbSSpA8nOyWKqVEhqP2/nY/dpWrJZGQLjwRtMBmJOlbNN5B/om5IlMru6uRcl5cPD9m43aQjKTqMlXP0aIICqHN1ETDMcz+bnaQsarKZcHiQash2g7tBzTYXxacb0AQF8I8TI0cjn8lO4rcPzOLH8xOua5H7e/kWDlU309TWKZ3zYdLNNzL9xXllYwf5JxsACFFP5A/7q9l7qoH0KZN4ZKGB/dYmYrWBfHz4LBGhKoorm9m4eu6YCrFtB6uGRKhl3hrmuvYCOVkmHrjCDu238y28W2jl/S9Pk2e2Kz+PDFMT7os0GiOC0WvUHDrTfEWvIRBcDTeNWHM4HADExAxMm8TExCiPORwOoqMHfqH7+/uj0+mUbQbz+uuvEx4ervwxGMberkEwtmz50npdi83X3TkdkCI/3zHqWJORwLIZ0dydHMNus4Mg1ZUHtEeb5pNTkKMRbHZXJ5lJ0TR19TAnPoy95fXsPFrL6vcPDHi9OG0Qa5dMIyfLxCfHHDS2SS7y7s5uyupaaerwDFuz1H/Ej9xld6mauDSDlpCAAIormwlVBVxUCKxMT7juUY4e4Lb4MHKLqrktPozucdZjH6cN4oml00mfMokTtW70GjXfm6Wn3XOedUuMrJxv4ExDOx8esjE1MoR2z3kyEnXsNjt47I5prN9+FLPNRZ7Zzs6SmqtKR7+bb2F7iY03vqgYItjeyrfwXqF1gGCTr/WdpTa2H6y8otd+JjuJp7JMPHbHtAGRtThtEOuXzeCl5cnsPdWg/DwyTH0FRyYQXDnjKg16PXjhhRf493//d+X/brdbCLYbGHmA+BJfqu56Wwo8lZ2kpEzSDFqCVP5XbDFhd3Wy/WAlqxdd3PDW7upkZ6kNvUYt2XsE+o84Iksu+pbNa9cuNlJW18q6JUb0YUFDXidOG8Sz2UnoQ1W8/Ok3PJNlog9YOFXHXMOkIaLp3XwLbxda6QPFfkOvUVN7roOWTi/l9hbaevp4NjtpiL3Ik9lJTPQbXZr3ehMdqsLilMyJLY0d3GGKut67dNmkGbT86t6UAT5rz2SZeLvQyq/vns49KTE8d88MAN78/BSP3TGN36yaw2lnKxmJOqz1bjYUVOBwe1iRpmflbZMHnM/NeyuUG5mR+OCrSt4utPJMlon7ZumHbK8L9OeRhQZ0Pp+3IouTnaU2JTWb3i8Vnltguax09EilAnHaIB5dkkiAvx//rG7mnhS98PUTfOvcNGJNr9cDUF9fT2xsrPLz+vp65s6dq2zjdA6MuPT09NDc3Kz8/mDUajVqtbiLGi90eHspq2sFIMA/YMzFmt3VyfYSm1KHNRr6bycLtQ35llGN1enP9hIbuUXV4B9AkB+EB6uGrX2L0wax/bHFfPK1jWDVyEJN3nbfr7L4S4mN7JQoTjpa+dntRjZ/Va0Unw/HQ4umoPb3Y2V6AsCINTxx2kDWZCRQ2dSG3dWJtd7Ni8tTWL/9KKmxYcRqA6lzSQ1AuYXWARMVYHwINZDej20Hq6hv83KHKWrM/fe+LWQz6DSDlkUmSfio/ScMEE15Zjtlda28lneSF5en8FreSWmU04xoIkJUPJRuYLZBy9qtJex4fDEAh043DKjl3HawSnmP+ot0+Vod6Zp9dEmiMlEBpJsxeR+mRoYoKfb+s3zHqn7woUVTmKwLvu43gIJbk3FrijthwgR27drFD3/4Q0BqMIiLi+OXv/wlzz33HCBFwaKjo/nTn/6kNBjMnDmTkpIS5s+fD8Dnn3/Od7/7Xc6ePTuqBoPxbKp3q/BuvoXzSHfK7+RbFJ+uKx1MLiNHoVak6enqPs+cuPArEhMb8i3sK68nOTaMpdOjh+yXbMA5ePTOzpIaql1dWBwt5J9sYEWantmxmlFNFBjNsf2fA5Usnx1PZJia/BN1TI0OHZOFaWdJDYtMUfy11MaGPdLoqY9Lbaycoye3SCpqXznfMGrxKoq7Lw95KkFkmHrMxkXJdV2uDi/bS2w0tXuJCFFxV3IM7xRaeWl5Mt/Uu5kTr+XlT79h4+q5nG1u53xvH+HBqgEzaZ/fdWKISB+JkaJzw43CGimylme2CwPlW5TxvH6Pq8haW1sbVqtV+f+ZM2c4evQoOp2OhIQEfvGLX/D//X//H9OnT2fq1Km89NJLxMXFKYIuJSWF7373u6xbt45NmzbR3d3NU089xYMPPig6QW8i5LEyb+dbKCyv579KbaRPmYSrw0tqvFb5Qh/tYHKZOG2Qki7MTonizQLrqMcvyeSZ7ewrr6esrhVNUAD/rGpiTsIkRZRt+dKKq8PD74uq6enp5ie+lOfOkho+OFhNWV0rj2UaqYsNo6TqHCVV50ifGjnqcT0jbROnDeJfF0uvte1gFa/mlSuWHIMX0dGKJbl2yNXhZUeJjY2FVh5ZaOCEo4XslGhyi6r52e1GVH6QPEphKBfyZ8+IZq5RJ0TbJZB961ak6ZWpBLXnht4gXC7xk4IVh//ve3s4XCPZp7zj+2zUuKT5uREhAWQk6ngt76QydePB+QZeuDcJbbCK9duPkp0SNaDBYWdJzYCI7YEKJ4/flTSk07o/ckSwPyMJtdfyTtLp7cEUo6HglBM/YJ7vRuFqhZwYfSa4VowrsVZSUkJW1oXUjFxLtmbNGv70pz/x61//mvb2dn7+85/jcrlYsmQJ//jHPwgMDFR+589//jNPPfUUy5Ytw8/Pj1WrVrFx48Zv/VgE1xazzUVpdTOx2kDK6lrp6j5P7r7TAMqEAFmgXc4IGXlbfaiKBQmTLjuqJS8Elc42+oCIUNWAL/fvpsWz9HeFrFtiZL+1mUW+GhxTjHQX+MhCA19Zm1maHMPOUhvPLpuuCLWcD0tYmhxD8iD7AZm38y2UVjcrdUYAFQ4353v7uG/uZGU/5PRU/5SPLNDyzHYOVDbS0ukd8lh/5ChkRqIOAHdnN3qNGldnN/knG8hI1LFuiZRuXTUvDou5lvhJwcM+j7xfcv1bamwY+aec5J9y8tCCBBElGYFtB6t4+dNvWLvYqPil7bc2UV7XOux7fTnIZs2RYWrONHco5zQ1NozIUDUqn6/eJ8ccyvQDi0MyLXa0SSPbIkJUyhSEO0z1Spf087tOAGCK0bBq0wHFn0+OYg8XWdu0x0K0Rkqpx2oDFbHXnw35FiYADreHL8rrlZuf1NgwvD3dnHG28WpeuTIP+HIZbU3paLmcqL/g5mfcpkGvF+M5jHorYba5ePlvx5X0TFO7F4fbwy+yTDyZnTTg7v1a078+pz87S2p4ftcJfvvArAH7Io+HenbZ9AE/N9tclJxp5PXPLGxcPZfQQH9FMOWZ7ZTbz5FbVM26JUZmx09SFpyNvs65dwqtZCTqWDxVx58PS3NFl5p0dJ2H/z7h4LUHZg8b3ZJd3Deunqu8xqp5ccyM0RClCWT99qPKlIX+yN5XGYk6bosPY5+1mdsStGiC1TS3dfHx4bPK/MmtxTVDnkOe+7n9scX8/ehZPjhUQ0SISplJueNrO6mxYSP6sN3KyOfssUwj7xdVsyYjga3FNWQk6jBGBHPbZC2mGM1Vv2+ygM5I1OHu7CbTpGNTUTWpsWGkT5mEp6eXjw+fVbpLtxyoJiNRxzyjjr3l9SxNjsHiaCE8KIDyulYeXWTE6e7i8buS+OCrSuYadUpkDaQ0aFtP34Ca0U17pOkYsg+aXqMe8tmRo+gPLphMRGgg/5Ju4LSzlYOVDfgDxsgwXB1e/lhczU8zjFdUWiC/Rk6WiXDV5UXch3uunaU2Vs43CME2hozn9XtcRdYEgtFSe65DuWuePTmcvaca+HmmkUPVzdDPQHMsBduGfMuQqJYc3QCGCDb5tQfvgzxWavBCKneUxmqDWZ4WN8D+Qn7NnKwAcgutvLRcurPfmG/hHd8CkhobRnFlMw8tSMDh9gyoGZsaGcKLu44PeV27q5MXdx1Hr1ETGuhPeLCanEwjzV3nOVLromT/OZ5bZiIyTD0ghVRkcfKxr0tvx9d2ZSEvsjZTVtfKIwsNvLQ8maauHpbNiOb7cyYPOd5PvrbhcHvYXmJjX3m9IrrliNzaxUaC1AFKxE9E2C4QHqQiNTaMvx1zkJGoY2txjXIuIkJVeHp6BwwqvxI2763g7UIrq+bFERkSwPtF1UyNkkxy5Saf2ZPDSY0NY6lJR25RNdkpUeSfbJB+lhyjlBSEqv0pq2vlrKuLdwqtdPbiu46TBwi1Dw7V4HB78Hq7AekzIT8erQnkO0Yd20ttLOrXjbvtYJUionILrcoUhThtEOYaFx+X2vjeLFhzu9S0MJLIyjPbqW5so7v3Qmdzf1anG6Cnm1D/Cbz+meWiz3UxtnxpZV95PQ63h3DVTeOuJbhKhFgT3LT8+u7pfHCohuCAidw5I4pPjjlwuD1MiwrhhXuTxlyo7SyVxEX/NIos0OS/N+Zb+FG/xgF5H97LtwxwXu+/gG7ItwyIJMhCTV5sy2pdPLRoCsvT4lgORAT682peOXONOu6cEU13TzfLZlyImH1+0sHG1XPZV+HkwQWTOX62hRR9GOsyE4cs3HJn6WlnKw3uLv5YXA1IqaTU2DCmRobwZoGVY3ap6eEldxePLkkkMyma1x6YTYO7C09PLxEhKjYVVfPru6ezNDmG1ekGPvnaRm6hlaAR7DkWT4+mqxc83m6a2r3cboogYKIfARMgI1HHf59wEBGiYgLSFIMrTV/djKQZtKycG8+reeVMjQxhTUYCQf4TyE6JYrfZQea0yKsSanZXJx8cquGRhQY+PGRjRZqe1NgwQtX+NLV7WZEmddfrQgOJ1XqoafEo6czslCh2H3ewco5eEW8ZiTpysky8U2hlTUaCIq6m+pqDNu2xKNdIW08fuYVWokLVyv4/flcS7+ZbeCo7iZXpBv5hrlWEUv/P4OCmHV2oCofbQ3y4JN4uJtTWbz+qHAMMFWxx2iAlBTrRb8IVR9a+mxaPpaGN+2bpx6R5SHBzIMSa4KZD/mJ94d4kVs838M/qZs40tvO9WXo6us/znSkRY76oy6mKfeX11Lk6Bjy2NDmG3AILPX1SKtLe0sGceK2yiLyTb2HjoFE5sniTUyv7yusHpPvkmqGyWhe5+07T0OZlve93PT3neSrLhLXezcr0BIpOOWnp9JKeoCW30Mqji4zETwpmx9d2nltm4rZFF2wahiuQlqMQRRYnP5yjx3seDp2RImR6jZpV8+KICQ/mRK2bisY2xYpBTqmaYjREhqlZu2SaZD8yqKljOKFmtrl48qNSZsVrlEjMjq/trEjTs/dUA1MjQ3C4JS+96FAVG1fPFUJtELK9RXFVE5+V1fOTBQZmx4Zzd3IMz+86cclZnhfjH+ZaHG4PkcFqXrg3idc/s5AaG8beUw38aL5BGQEm38CkxoYREaIiYVIwh84043B7OFLbijEiWKlr3Fkq2cdsLa5hTUYCO0ula0X2egNQ+fuRW1hBTqaR1z+zKFFmOR0LEKzyGxDZsrs6cbR5h722B99MjUSDu4vU2DDuTI5hIsNH1uDCOK2Liay38i2EDLJDGfwc65fNEI0KggEIsSa46VieFsdTzjZe/8xCdkoUZxrbcbg9TIkIYWlyzDX7Enw2O2lIrYpcdNzcdZ7YsEByskzsLLWx42s7an8/TDEa/qvURk6WiUxf9Kv/nMP+DQ0lZxoByT1d9sLad0qazflOoZWJwHmgpLqZ4spmUmPDOOvqYk95PW/5UkoZiTqqXV0sMkWh16j5/rwLkQazzUXe8VqWz44fdhFvcHexqaianCwTS0w6bkvQ0tl9nvtmx7F2awk5mUaMkWED6t5k4SY3IQxu6pCF2jv5lgELYJpBy6MLE/imXkplN7V7WTUvjv3WJhxuDw/ON5A9I5ojta5rek7HO48uSWSuUUdZrYt/Vjez2+zgpeXJw4pbu6uTXSW2Uc3WXHuHiU5vL7HaQJ7fdYJn7zJxsKqZ786M4c+Hbfz67um88UUFGYk6pkaGUFzZzBOZRpzt3Up5AsDHh88q0V2H28PtJql7tKTqHBEhKiJCJN+0BxdM5vvzDByrOcf6LBMbC608t8ykHEMv8EyWiaeyk9h2sIrslCi+mxavfP5yi6rp7u4mJCBgyPE52ryjeh/7/32lyBH4qZEhwPDNEnDtZqgKxi9CrAluOrZ8aaXc0SJ1DZ5s4KXlyURpAsck8vJuvoWVg1Ip/Rl8R729xMaR2laKK5vJyTKxr7yeH8030IsUcWrplNJ7uYVWpQ6nF0iNDaPX9xzJ0aG8/+VpyupayUhs5ExjO9sfW0ycNoi5CVoOVzfztM+7zOH2kJGo45GFBo7UuLgtQcs7vg5KGTmylbN0GgetDaxMT8Du6uTJj0pxuD2o/C4IQhm7q5OV6Qm0dfVwplkaO/Tggsk8/J0pkmj8VZbicyULM7nI/bcPzOL5XSeUtNvggun+kcX+gq29p4/dZgc5WSaSfemwOfFatpfYeKtQ8mvbbXbwHaNu3JrQfhvItY7aYBW3xWt5dEnigHFsssXK/zlQyR/2S2nuSwm2PLOdtwqtbFw9V6o9bOukuFKyVJEjnnIzQ3VThyLe5Ehsi68reO1iIycdrcRqA9EEBRAeGEB5Z6sStb1zRhSnm9oA+PvRsxSdbsLd2c0vsky8WWAldbKWIzUu3im08nSWiQ++quTVvHJeuX8mx2rOsTwtjvTEKFKtzTR3dLP562p6kKKxzW1evDCsfc+WL61DPssXE2qjsezYdrCKfeX1ABRXNvPDOSISLBg9QqwJbjq+mxbP4ZpzLDXp+H5a7FXfDcvIxfqdPd1EBKsVf7ORKLI4ldqb24w6jL4FqdQX+apv6SBBG8x3jDpiQgJIT4wizaCl9lwHGwut3JMizbmNnxTMbQlamtq9uDu7eSjdwL7yeh5aNEWJYmUmRXNbgpazzR00tHm5c0Y0mmA1Z5s70GvUPLrIiKenVxGNFkcLO2vdysK6Mj2B7Y8tZnuJTanrMdtctHRKUYfi0w08kpHIo0sS2VlSw4ML+jh+toWZekmYKQXb/Wrp5AHxx22ui9ZHyQKtv1D74KtKfpGdRB9gcbQQALztEweZJp3U3dvWxeOZxqs7qbcIRRanUusoN728cG8S0/UaXtx1nO2PLSZWE4Reo0YXqrrk8y1Pi2MjMCdhkiLycrJMbN5/hlfun0ljm5fiymaWp+o5fraFiFA1T2WZ+L+lNgIm+nGi1k1qbBhbDkgNLulTJpF/sgF3ZzcZiTo0QQG4O7vRhQay95SNFbP1fH3WRXFlM+uWGHnLF1krO+tifXYS54HbEqSpCb++ezpNbV7JjNe3rw3uLp7fdYKcTCPvFl7oHM3JMvHIQoNyMwCSUHv9Mwst3t4hk0o27bGQOnmgebNsm7NybvxFv2uWJsdwrNZFbHgwhhHsRQSCkRBiTXDTEacN4qUVs8bMrR2kFKFc/PyfRZJn1SfmumFtI+TIkixW+ttryAtEij6MUHUAn5+sZ2pUCLvNDl4IVlNS4yK30Mr6LBMb9ljxm3AhVagJlmZ9BkycMKDDtKTGRYXDzdo7TGw7WMU7hVbOI0UMUmPDyFk6bcDC8NCiKdhdnfy11MbnJ+vx9PQq75scXZBFl9zZp9eoCQgI4NlsqTEjShPITL1mSERLrqWT35PjNhcb9ljx9HHRczFYqL2aVw5IUcXcQit1ri6evctEpbONv/q8uz4+fJZHFhp4+dNvUPv7Ue3qIgC44zJGgd3syIJbFjF/P+EgfcokHllo4HDNOV7/zIJeo+a/SmzcNSOaHH8/UuO1F31O2fZmeVocRRYnf9gvmRsbtYE43B6a2rxs9F3Dk3XBAHxRXk/+yQYeWWhgdlw4UaGBhKr80AQFAFBSdU5qWIkKUYRfbqFVsd6RGxLaE3V8anbwZJaJA2ekm57OXpT6tt8+MIsPDlbT1O7lmSwT5c425viiwlGaQKZFh2GMDMPp7iLdqMPe0kF5XStxmgtenOlTI8nJ9AypFd20x8IxewtvFgwci7a9xEasNpCKxrYRbXpA1KIJrg4h1gQ3JcM5ml8NkWFqUmPDCAlUKW7wP7vdSGTYwLmx/SNLaQYtx2pcype6HI1YnhZHboGFisY2ZZLBijQ9h2vOkX+ygZwsEyEqP55bZlKE2r5TTp7NTlJGMk30m8DS5BilAUFOcw7ugDMOuoOXfx6nDSJnWRKTQi7MFzXbXAPq4XY8vpiWTi/hQSoKfK8PUiThYtMG+gulnGVJePok4Riu8uO7afH8tdTG1KhQyp1tw/pRDa4P2gicbW5n3Z3TMdtcvFVoRR8ezIo0PVEhan5993SqXV3sLLUxK17D24XWq+p0HC9cKvUmXxu/fWAWGYk6PjhUw9TIELYW1yh2LdkpUSRFBrOj1MYpRwvfT4u/qKWH7A0IUjRWviEBFC++5Wlx+E2Qzn2RxUlZnZTmzMkycaS6WUmh+4cFKvWkctp+t9mhdIOuyUig1tVJYMBEmtq9WBo7lNq39wqtrFti5ExjO/pQFT9ZYMAYKdnm1Lm6eKvQSjfSddfb081Di6Rr6ZOvbRgjQ3mzQBKTLZ1SDd3UqBBFhCrH7R8wILLW1Yvy+ZSv/017LNQ0tSk/v1Q6fjQTRkazneDWQ5jiXibj2VRPcHXIi+NIsztl5Mia3KEmFz7LyIvoc8tMqPz9aPP28k6hlV/fPZ22Lq9iOpsUFUr61Ej2nnIqNTnrs5PIM9t5/8vTZCTqiApV0+LtZV95PbmPpBOnDVJsDoosTsKDVCOKlv4O6Wabi0+OnaWp3cuv7k0ZcbHYWVJDZWMrD/dzad92sEqZdvCOby7r/EFzPrd8aUUbrKK6sZWdPgsVOWr3wr1Jw3bPjTTWSu72zUjUsTxVr6T0Xv/MwpNZJu66BSJr8oQI2TNsMG/lW3jPl4I3agP56zE7s+PD+OSYZHcSqw1UasZqzl2YQLA8VT9gJNtwDDaUli0zBp8vuWkkz2xn2+EafnlPMqs2HeAXWSbe8n0uAPJ9dVyyH2JEiApNUAARoSrONLQrhtZ6jVrxBnw806hEWFs6u6lzddHU7uVf5hvY6KtnfKvQSk6mkYn+AdyWoGXnkbPsNjt4bpmJYJW/UnuZnRJFxpSIISnM/gPm+7+vv+j3Wba7Otm6v5JgdQDPDIoOX275hdwBPTUyhHWZiUyLDhOibYwZz+u3iKwJBAz1MhuO0bTlw4XIkizQhhNqP880EqzyV2rAMhJ1qP0nkpwYxYoWD7rgAKbrNUrR/yMLDbxTaOW2BC3vf3mapnapJqisrpWXlifz6CIjp52t7Cyxsb3URk8virP8usxEvq5xDVhM+s9FXTYjmoJTTrYW15AaG8auEhtpwwxVzzPbeX7XCfQaNRP9pZSoXP+0Ik1PaY2L9wqtkr2GbwGWn8Pfz4/j9hYlqlLd1EGcNpB7UmJGFGojRXiWp8WxY5KUXmvp9CrRHNnG4VYgThs0olADFEERE6oiSiNFsM40tnN/mp4zTRfE2UmH1PzyyEIDmmA1L3/6DTseXwxIJrShgQEjmjnDBVEIF67znSU11Lq6lKYRP6SC+kOnGxRh3o10fa5I00u+bLP1/GF/NQ8umMzHh88qxsfyJARZtFkaO1iRpmeTz8xZHx5MeGA3J2rdAGwstPJYppGwQH/0GjUT/AP4S6lN2u/bJjMjKlSJVhdZnBi0QUNqT+2uTg5aG4adLvKLQY0Xja0e1tw+cLyUnMZv6eoZ0eJjMP0bfLJTotlcVIm7s1u5ARMIhD2y4JZHFi4FZbXkme0UWZxs3ltBkcVJntl+Rc+ZZ7bzwVeVA4Ta5r0VSsOBv38Ac406RQAtmqLj1bxyKhxuSqrOsfmras42d/Dew/N5KsvEh4ekaQDToiXnd8nmQIdeo6a1q4cNBRVSobivI9TfD3KyTBRXNlNS2cC7hVbe9o2dMttc1Ld0KHVBecdrlf26OzmGL8rrefPzU+wsqRlwTMvT4ti4eu6AETgPLZrCK/fPZOVtk0nQBrJqXhy7zQ5Wzo1XhFqRxcmreeVogtXoNWraPD0UVzbT0tmN34Th3z9rvZs1GQkUnHIq+92fNINWqcUKDZTuOU8725Q00q3A4EV8y5fWAf+PCVXx8qff8NE/q5kaGcLUyBDO+1J5Dy6YjLuzmzhtIBmJOo74aiV/+8As0gxaZWh67r7TbDtYNezr55nt7PB5o8nnUU6TxmsDeTLLxNwErdK5q/afyOufWcgtsCiifnpkqNSBrAogOyWKjw+f5YlMI3W+SNpSk2TjEasNJH3KJOpcXUoJAkBTWxeHzjSzco6eqZEhrEjT87djDioapQ7SQD/JwPkvpTbONnfw+F1JyvGEB6no9PZirZeE3raDVcqIsyNnXeg1aqwNrQMmhfRHvqFobPUM+PmjSxIVe5EPvqoc8Njg/8scqzkHQE6mkQ8P2TjT2A4w5LkFty4isia45ZGFx85SGw7fSBz5Tn1WvBQqv5yITZ7Zzmt5J5VOSzkdInsqyQ7s7g4PD9xmUCJDfX3w+mcWcjKNhAZeqCWz1rvRa9TMidey02cqm5NpJNc3g7EPeHRhAh8cquHB+QYm+kHqZC3hQSro6Sa3SBrNlOTreCs85fT5ldnJTokiVhPES8uTeTWvnJwsk+KD9cHB6gHzI+WRTssHHW//mrcNBRW8cv/MAdGYzKRoZZrEj+cbmACKc/0d/cYC9X//nt91ghVpej4rq1fex2cGRSn6N3DIKeftpTYeXZgwbEToZuDtfMuQ9wEudDDChchvd08vqbFh1Lm6yE6OIb+8npOOVlak6ZW5rPJ81exkqfM4SCUtCfK1erH3Uf5MnGloI2eZtE+uDi+/fWAWAO/5une3rEmnrauHTm8Pz95lImdZEoEBfooP4vosE//li349uGAyv/dFze5NjSG3qFoxzZXr2RZO1fGH/VKTT5unh7K6VqURIcI3kaCxzcOP5xske4/YMDRBAbz86Tc0tXl5u9BKp7eHvRWNyixRR0sXG/ZYeQXY/thi8k/UERwwkYxpUcr1v3lvBffNnTxAJO94fDH7TjmHRH+fzk4iPNCf7FmxSvlE/8aZwSnS5WlxVDjb2FNez4MLJtPY5uH7acP7HQpuTYRYE4xb+tdcXS3PZicREehP/iknJ3yWFqmxYZyodTNLHz6qfZHTqPGTgpkaGcKjCxPInhU7YLv+Jpj90647S2qkGhtftOvxTCOb9kiL7+N3JeHp6UUbrELt74deoyYiNIins0ycaWpje6mN200R3Jsaw8elNn6ywMCbn59iiUmHLlhqjIgMUbHtcA2d3h5Kq5uZGhnCD+foKbI2s/NoLY8uMpIaG8bOUhs/u93I9OiwIUJt/fajbATqXB24vb30MdCbKs2g5b2H5wMDxwMBTNZJEwemR4dS6WxjTlw4d5iihhUClc42ZSxSTpaJmqY2fpxuGLLdtoNVLPWJjDkJWh7PNOLnH8AbX1Swal4cXKQzbzzSP3U9WLDJAq1/SvnRJYk0dfWQW2glKzmGJSYd7/uEUGpsGOV1rTyZZWJHqY23fTM6G9xdSiRpJMPW/ixPi1MiVbJf3vosEwXl9bxy/0z+WdXE7Lhwjpx1sfdUAw63h6lRobR6e9Fr1CRFBrOx0MqTWSbeK7SiCw0kOyWKhEnBbDlwIS2ak2nkhEZNeKCK5g4P2SlRqP39aOnsJjslisCAiew2O5gaFUJGoo46VxeRoVIkVxai6b65oTlZJqbrNfyxuJqns0yE+ppcvH3SjUee2c6reeX89oFZnG2WppHIkcZv6ltJiJBuenILrTyVZeLdYTwCiyxO5hp1LP1dITmZRlYvShzRWHfbwSocbV5yC608e5eJ2QbtRWtNBbcmQqwJxiWDa67kL7aRitJHw6NLEonSBNLg7uJIrYuEiFBUXNogVNmXnm6s9W6qXV2sy0wkPEg1YhF4fy+zVZsOkJNlIiNRR3J0qOKDdqLWTUSIivO9cML3/+yUaB5dmMCRWhdNbV4WGHXsNjsor2tldboBh7uGc74Ot1htIO+flGwQZEPSvx6zsy4zkbPNHSxNjuE7iVG8uOs4R866yDTp8PMPYF95PYtNUYrBrTy26gVXB2eb2/n6rIv8kw1kp0QNEcy15zr4/KSDru7zbMi3KMcpd8JWOtuUtJgspAYXcqclaPm41KZEYYbrepRr5bKtDby0YhYVDjfHfObD8gIfEx58yXO+Id9CRKD/mHnxXSs2+pzv9Ro16hGKVwbX/m3aY1HS21VNbTS1eRXxe6ahneTYMN4rtPLCvUmkT43kaHUzr+aVsyYjgQBfXvNSnyX5PDT77DoyEnX8ly8V72jzcqTGhTZYrdSh6cOCBkRn/UHxX3twwWRyfWOqQIq+7j3VoEz9WDnfQIGvFlK2/JBHkcVqA9Fr1JxpkNKHZXWtZCfHsHK+gbcLrdINjm8agtzc8+jCBJLjwlm7tYR2by/vFVpR+bpYNyJFCWWLnIXTonimp4/tpTZ2mx3oNWpyMo38ON2AH0OF2tqtJcq809xCK/hqPIcTat843FQ3SX6IfhO4aKe14NZFiDXBuKS/QFi16QCv3D+ThjYv9pYOymovzN2Ui4WrXV2ofV/EF0NO7WSPwpF88L4YtYFKEf0TmUbOdZ1Hr1Hzf0tsytxOeZ9yPiwh95F00gxa5Qs9J8vEtsM1PLQgARXSQgRwqLoZkGpv8k86mRoZQoh6IsWVzdxmlOrWspJj2F5iU7oi5TTj2sVG5bmTo0OZkzCJT762sXh6NAetDZhiNEra6PjZLmK1gZTVtXK2uUOJpmWnRCnWGNkp0YQHBSjTIeCCQDbbXGw7XENxZTMZiTpyC63Ut3Qo3lJ1rg5F+D6ZnaS46K/dWkJOlkkRdvIQeHnRGu48yOdXHjUlC5X5Rh2F5fWsyUhg9TDRuP7IIntNRsIVde99m8jXj2qEofcb8i2KrYuMvF1vn+RjBii1UA63h++nxfLsXSZe/8zCljUaHl2SSE9vL3Z3F3/YX41KFXBJsSafh9R4rWKmqw1WUe5sI7fQyqp5cZRWNyvdmSvS9My1ufjK4iRgAmwrkYSd8hnINCrdwrK9iGxNc6S6WUnRy/V28nXe1O7le7P0HDrTzOzJ4WiCAnB1edlaXENOppF91maykmMIU/nxibkOgA8O1bBqvkGKPIeqePYuEwETJ5BnthM/6UKziqPNy8u+ZpeIUBU1ze0UVzazLDWeOG3QkCaCBncXW9akD+jmvFgG4PjZFklcpkRRda7jsm44r+bmVDC+ENYdl8l4bv29mdh2sIpaVzvv+2ZV7iuvp6yuVfFAe2l5MtmzYln6u0Il0pIaG8Y9KTGXFGxXitnm4uW/Haep3cvK+QaOVDfj9kW5+tdxDbb0sLs6+bC4kgOnpcXowQWTmanXsL3ExsKpOkLUFzra+nfzyT5USfpwdpbauDc1RunoTI4Nw9PTy26zQ0kTzYgKpbcPNuyxKu/Tbx+YRZQmkEOVDdJ7mWmkvr2b/dYm7pwhRTa+N0tPS1c35XWtynucEBFKd3c3GdOiBggEs28h7uuDiX4os0flmiq5G1COPmxZk64YAcvposHibNMeC+HBKpxt3iHpv8E2EiBFNkZrezBeImsXo7/X3nP3zBgSmbG7Onl19wkCAyYqXZURISrum6XnjS8qlEkG/c2by51toy4xkKPD8lixV+6fycuffqP4qqUbpTmyZWddLJ4ezVcWJxv2SCnEgAng6ZPqRftbdjS1eUnRSxMOHss0EqoKoKsX9pbXs9SkU0a46TVqZsVriAyVonfyZALZFiY7RaqJzD/ZoNTo/TzTSFP7hes5NTaMx+6Yxtnmdv5+wqGYQL/38HwKTjmpaWojISJ0gM1N/3Fs/VP+O0tqOFXfyoyYsItOKCiyOKlwuNlb0ci0qBA0Kj9yfSlqeZTcxdi0x8Li6dEX9cQTDGU8r98isiYYlzy0aArbDlYpEZl95fXKoG+9Rs2RWhehgf78PNNIRLCanCzTqCJrF+NS0ZeCU06lPma7T1x9b5YeTVAAzf2GRQ+29DhobeBTs0OZ63n8bAvHz7aQPmXSgHE80aFqZbtHFhqodXVyotZNeD8XeFm4zozR0NLVI0UnIoLZ/FU1XSlRhPsMeKdEhKLXqKl1dSmLyvle0GtD2HnsNBEhKvaeaiA7JVrZB5BSUz9dnEiaQYvd1anMOpSR51DKqUu5O7N/TVWRxUnZWZfSHHCsxuU7Z61QYhsgEjbtsfCPb+pJnzKJrcU19NKvIcTXeVjr6hoQ3RgsVmRBJ0fy5MHy9HuuTXss9PaBPvzajAF6N9+iGMWONfIxDI6sycRpg7g7OYYNBRWsnG9gZ6mNZckxrLtzOhGhaqI0gYpwzkyKHraJpD8b8i34I6X+7K5OxUD5QIWT1NgwcvedVoSb3BUpR8nCg1UsSYqmuw/e9dW37Suv5/tz9Oy3NnOmsV25wUmLD2PdEiPv+xpp7kyOUZoJHko38B2jjn9WNyspeTnK9shCAw53F5qgANo95znT2M66JUY+NTuGRO7kiN7Z5nbae/oUgXd3cgy15zpo7/Ky2zcxAS402RRZnBy0NuB0d/FmgVSO8fhdSVS7uthyoJpn7xrZ3ke+UZE/UxGhKj485FA84UYj1N4ssNLZK3V8H61u5kCFU7kxEtycCLEmGLf0Lx5/5Qez+f2+C4vR7FgNGwoqcLg9rF1s5L6r6Kwy21wUnHKys9RGh7dnxDTUTl+tzoo0PS8uTwHgQKXUcbZ4qm7A9v0tPaI0gUoKp7iymR2PL6bglFOJNh2pbWW32cEjCw38YI6e2hYPDnfXgOia3DG5r7yepckxvJpXjl6j5sH5BhKjQ8lIbCX/ZIPyMzkl9V+lNnqQFny5qLmlw8ubBdIC6+rsRq9R88M5ev56zMHdyTGkGbTkme0Danr6d4QeOt3AG19USMdRVqtEy2Sh9ubnpyira+W5ZZITvPxedDM0XdTTC1OjQpSI4c5SG8nRklN9lEaqU/rG0TJis4ks6BwtXXx+UhKWZWddSpfgo4uMON1dnGpoY7fZITUmwJgKNjmSKk+Z6C/YZDF72tmqCK3hUltFFqcy9zV0mKkPl4qCrUxPIEjlz/K0OIL84M0CK4H+E5Qmgv7jky6GHMXTa9T0Ae8UWtn3qyzSDFoiw9S8WWBVJl+kxoYR7vM7+5f5Bv6r1MaX1gbFyy3YfwIRoWrK6lq5b5ae9CmTCAlUKU0u5tpWzjS281imEbV/AN84Wngmy0QvUnRYrkP72e1G/rBfuqFYkaans/u8coOSkahj5Rw9R2pbpZRqkdS0sPdUAyvn6NlZaiMjUUd9m0dKmfpq+praPESEwtbiGh7LNHLXjGi2Haxie4mNBneX8vl6dtl0crKkSSMffFWplBz0DpOvsrs6+fvRs8r7fcbZxpFaaWpDamwYbm8vHxZZmcjF62S/P89AZ680M1e2Yfn48Fk6vd3DRqYFNwdCrAluCtIMWl5aMYs4bZCymKdPjaSgrFYZkH4lFFmcfP6NQ+lkO9XQRm6BZUiEZNmMaM73dBPoH8DKfpMN5iRMIl4TqAg8s81FWa1rgLgpqXGx5UA1azISeHSRURnmvnaxZM+RnRLFU1kmyn1fznqNmjtnRLFqXpxSk3PClw46Uesm11c03untxYs0CD57xoWFeKIf6DVqZsdqSIgI5Uh1s+LMbrZJQkbuNJXtEjb5pio8v+sEnp5eaUj26rkDGgVkB3Y5QlhwykluUTX4BwyoRwNJMMnvid3VqQjG/nzwVaWSLpZr7uBCXWFmUjQPzjdwwtGiNJsMfo6V6QnUubqocXXQ1O7lB3P0vFlg5We3GwlUBfD8rhNsWZPO+V549i7TsJG1S3Udy079I7Ey3UB+eT13Jw9MwX/wVSX1bZ30nIdDZ6S6xPAg1ZDUlhyJWZGmp6v7PIEBE9nypfWS5syDkd+3x+9KYqLfBaEGoy9qX51ugJ5uJvoHsD47iR/1u9bjtEHkZJmUEWxlda3ck9LD1MgQNvquyT8WV7NlTTq15zr44FANLy5P4bcPzKLO1cXW4hoezzRyf5oeQBlFFRwQwLYSG1MjQ+hBsgSR69AAJe0pp3dLqs6hCQpAr1ETop7IPqtUXrB2sRF3Z7fSXZpbVK10cy406kiNDaO5TfJxK9Gc4/40vTTYPlg6nu0lUrTc3dXDljXpNLi7cLq7lFFqQSp/HlloINfXaCFPdgDpGv/93go+PnwWvUbNowsTWHfndKZanKy8bTLmGhex2kB+kaW+qFCT6101QQEsNOqUEgi9Rs3OYw6lkUFw8yHEmuCmQV405EXpQIUkFp5TBSiLUW6BhZ4+BhT8D+atfAsTgIAJUNHYRknVOdKnTAKkVGNJ1TkCAwZGN+SFdbAojNMGDXBM75/+SI3X8uRHpUSEqMjJMhER6M/zu05gitFQ3dimCDhdkIqDVVKKSJ6hKPtkpcaGkVtUzSMLDXx4yMaKND23xWuJ0gTy+UkHJVXnaG7rYu+pBh5KN7Bhj5UFRh33p+klTzefcW6IeqKS4pE91164N4nZsRql1my6XsN+axONbV5euX8mrg4vbxVa0YVKnnBpBi2PLkyg6HST4pifkyk1OFgcLYqYzkyKJjMpmtwCC0uSonnyo1JmxWuGjPIZyeqgP7pQFfknG1iRpie30DpkCkWe2c5bvjmSAH875lAW6hVpep5bZiI8SMVbvnmikWHqAZGt/l3Hwy2Csl0FMKJgi9MGDXGi33awivxTTtyd3TS1exU/v4JTziE1SJlJ0eRkmRTPvJws07BCbSTROFwN331zJw+ovbrUnNH+x9I/etP/d+T3amepje2PLebXd0/njS8q+PXd03logSSAHW4PbV09WJxtONweTjvbmBYdyluFVp7INGJr8bDb7OCZLJPSventQ4kcuzu7BzTk1PhuKORJCBMnTKCsrpWf3W4kKSZU8enLToliywHpxidWG8jOYw7lBujZu0xs2GNVIlRPZZnwA8VS5PXPLGxcHcyy5Bg2Flq5b5ZeSaU/v+sEzy2TzscHX1WSf9LJc8tM9PQOjJ7HaYN44s7pxGsCOWZv4b65k5Vz2//vSyGb5xZXNnNbfBg7jzl4KN2g1P3JNzSCmw8h1gQ3LbJIkv/OLbAo3WcwvGB7K9/CDl+92e2mCHabHfz67ul8U9+KPkyNw+3hF8MsloPtJwZHY+yuTtZuLSE1NozZk8Pp7uklMkxK48g2G+FBAby0PJmj1c0YI0N5bpmJiX4T+OBQDQ+lGzjT2E6cJpAQk46mdi+enl6mRoVwu0nHfxZVK+mgMw3tPHbHNKJDpf3VhQbicHsIDPBTuvJSY8Ok4uueblak6fmOUcf67UfZMSmYR5ckEuDvx0OLprDlS6ti2mt3dZKdEq0YmL738PwBjRN2Vyd/P+Ggqd3L1MgQiiubqW+X0qjtnvM0tnqUxT23wMKGPVY+P1lPRIgkuGbHDvSzM9tcBPj7DWki6B/ZfGjRFNq6uvn6rEtx3+9PaKC/NMorIECJ+FkaO3xmwGr+fNhGsMqf1NgwWjq9/Mfn5bg7u3nlB7OJDFOTHB1KdkqUsggO3hdZHF1qrNBgIfTQoik0tnkVm4tZ8VBS2SBFIhko+t/ziaAnfRHGi4lGOUJZZHFy3FeXd7yuBYC7k2MwxWiIDFOz+v0DSt3Wi8tTWL/96BCLmeFmYw4+lv4ib3W6gZqmNn66WBJz6+6cjqenb0AE7ylnG6GB/rzr8yibFh3K+u1HeSbLpFhsrM8yKZHIzp5u3vNtG+w/gTe+qACkWq2enm5Kqs6RnRJFSdU5pkaGUHNOOrfFlc00tUt1ok9lmWhs61Kaan6eaSQ8KIBepMaDJH04K9L0HD/bQo4v0paRqOPpLBPv+GxmPj/poKnNy5qMBNT+EwHJpkYW1rL4Xnf7VOXmQr5W7K5OJc39+F3DW9GMBrurk/e/PI0mKIBV8+IUU2w5vf/ssum3zLi1WxEh1gQ3Nf3ry3KWJXG+D/6r1MZtCdpht5+foFVG4bR0ditiRK5b02vUqPwHzkjq39mYmRQ9bDRme4mUqliaHENEoL8yO1DuRgsMmMiOr+3s1zRxuymCHb7I1uufWchI1PH5SSlC0NbTx/tF1TyZZUIX6I+zrZP3femcgAlSA0B4UACuDi/3pcUTqA5g2Yxo/AG7u4uZeo3SFdfU7lXMRH+6OJFX7p+Jtd5NWa2L3H2nFaNOuaNueVocdyXHMClYzTuFVlo6vQPqBhtbPUq36JmGdrJTotjxtV3xyZLTY/K5APjhfAP5J+q4J6VnSIpw59FaAGK1gbR19fDokkRF5MnPYXd1su7O6SMKi8ykaCocbv5YXK10CuZkGqlp8RCqkgTcmeZ2vp8WS1tXD+7ObjISdRytlsyCH7tjGt9Pi2d5Whw7S2rYUCCJheEE23BsyLcQ6rte+rvf212dHK5uZla8hpXzpVTWHaYo1i42DrEc6W93MhJPZyfRg+QhFgCcbelgx9d2HlwwmRO1bu5NjeGvx+wkxbhJ0Abz2gOzeXHXcdKnTOK1vJPKOZaR/dMGz8YcfGxyFC1OG0ScNohf3ZuiHOO2g1WUOVrY5jMnfi/fwrs+8bNlTbqS8pWF2trFRv77hIPalg7lBib/ZIMy4WD1fAOv3D8TR5vX9xmyKtMN5AHucl2gJiiAxdN0nLC38m7hhe7nZ7JMSvPP6vnBrPClXHebHYo4kyN37s5u5eYmI1GnND/Uajvx9JznjS8q2Lh6rlLn2b82Va6VlEsGVqTpOeNs49ElV15TFqcN4pUfzGbVpgOsmhenfK7kGz7BzY0Qa4Jbiqezk5g7QtccXBhhFB6kGtCerxT8Z5mGOLv3H3sEUlee7Asl30XLok3+W45chaj86Orupa61iwcXTEYXGsjO0oF+aSn6cN7xuZuHqv15JsuExif4UmPDyMkyMSnQn837z5A+ZRJ2Vxf7radZOV+qn/F6u9l9/EK3aXFls1LT5mjrQq9R8+UpJ/k++5PslCgcbg8WRwsZiTpO1Lo5Ueum09vD87tOsOPxxYrYlcXIQt9YHrkLUI7yrV1sxOJo4cXlKQOEyvZ+XZ/Zs2IHLGA7S2rYvP+M0ixSVtfKFF0wZptLEXQ5y6T6uoKyWvz9Ay4qmNKnRnK45hztnvNSutSXAgVYkaYnKkTN659ZWLfESFldK5qgACUys377UV65f6byXHJUdjRsyLcoljIZiTrOdXp5JCNRETa/WTVHibjIdZYjRV0uZcwMUt2ku8PD9lIb35ulJyNRp9hZ9B/b1dTupbiqiYgQySJD+rlbeZ4iixO7q13qTLa3YBqm4aG/XUh/ZO++NIMWR5tXiVzJx9Db71g++KqSjEQdp5vaBqQpd3xtV2oms1OiCFH5MStew9u+CFtuoZVf3z1duSkormwmSR9ORqKOiFCpZm1qVAibv5LqLH+eaaSysYOMRB1ljhYcbg/rlhhxdXlJiAhVar5O+q73XJ9w3HKgmlhtIKmxYUSEqpQu1aZ2LzN9r+fqkKJ3qZO1UlnCZOl9kiJqXUrk940vKujqPk+UJlDpJr0S89s0g5Z9v8oCfCnpdAN/P3qWWG0gi4YZ3Sa4eRj1IPd/+Zd/4dy5c9dyXwQCgFENT7e7Oskz24cMGx8Nl/qSzEyS6p76L5rPZieNmIIa/JyZSdE8d88MfrNqzgCB0v93ZeuRWG0wU6NC+fjwWfaealCsMF7/zMKKND35JxuYAIpQyz8l2U/kn3IqczxrmtrYvP8MINXUxWkD+ZFPqOVkmfjD/mpW+8w/p0WFsHH1XADeKrTSfb6XnywwsL3Uxt3JMaTGhpGqD5dGAfkW2amRIfx4vhTt0WvUSoSspLKB3EIrp5vaefKjUsw2FyvTE9iyJp3Fpigey5QWvAUJk5T0jN3VyZavTpNbaGVDvoUN+RaW/q5wwAD2tq4ebjdFkFto5d7UGFbNi+MP+6tp6ZQWRjmilne8ltyiar5xtPDuMMPeZaz1kr1JcWUzoWqpO7Gk6hzbSmwkRITy+cl69Bo1B043syJNT5w2kKlRIXxvlp7slChy953m7XwLphgNL9ybdNFIU3+M2kBitYH8PFOql9v8VbVSpA4MaLiQ35/LiboMHgpecqaRDw/ZeCjdwFzDJKXwflqUNMRdTg+WVJ0jMlRNU7uXM43tyixPmQZ3F5uKqpkdH4bD3TXkdTfvrVCEWv9JHJv2WCg63ciqTQcw21zKZ0aOFJptLjYWWjHbXOQWWAgN9OdMY7uSBv/Z7UaSIoNZkyG9v7vNDpL04bz+mYUUnziKDlXxjG8iR1f3ee5KjiEjUUdNUxvFlc1og6RoqTFCSl/HhAfzn0XVJEUG4+7sJkUfTnZKFJu/qqbW1UmQn3R9/zTDSP7JBuYZdWSnRBGqlhoUwoMC0AQFsNsspfdXpOlZ6YviZU6LUCLLmUnRxIQHK+dzy5dW3i60suVLK+vunM4L9yYpEVo5Er8h36LYyfRnuJ/1Rxb78r/X3TldqQcV3LyMOrJ29uxZUlNT2bx5M/fdd9+13CfBLcy7+Ra6e7opd7YpC8Fg7K5OVr9/QAn/e3p6B6TjzDYX+045L1lHdLmMJNTkwnyzzUXJmUbW3mFSvrRl/64Ne6zKHfGOEpuSspJrhn77wCyKTjcCsHCqjvjwIDbvP0N2StSFIdfzDRRXNmOMCKa4UuqEy+kXafD29PFWoRW7S1pg9Ro19S0drMlIUFI/Hx6yoQlWs2xGNDmZHtQBAaRO1uIosDJhghR18feDiBCVUie1t7yed3z7+uyy6cRpg/j70bPsPCZZDuz42s5Ly5OV6It87NOiw0iMHGgOGqcNYqZew4o0vWI98LPbjcrjRRanYosgm6oWVzazal4c06LDBjxPVKiaJzKNTPAPGFDMPZiV6Qm4OrzkZBpp7jqv2JA8MEevWJ3sK69nalSI4vT/vVn6Af5y5Y4W3vW9B/0NZOXh3ttLbENS3yvTEwZYhlxM7F+KzXsrmKwLodPbwyJTFPkn6jhS64J+3n+D54PumBTMl6ecdHRLbv/yeQoN9GdDQQVTI0Nwd3YrHbHyZ00+X56eXu5NHWp5I0eW1f4TlRKBl/92HJCun6eyTMrvrE438OeDlfxkUaLixyab4ub4mghky4wuTzc7jzmYFa9h68ka5dqW05NPZpmob/Oyt7xeSZm2e87j7uxWhGn+SSer5sXhaOkgMlSt3LDIEU5NUABnGttZNS+O8jrJzkZOpeo1ak75rsl2z3lmxWvw9PQSEaoiI1GHu7ObMw3tlFSd48ksEwunXYhkDS59kM+Bv5/fgHMCFxpG5OkZ8s9Auv43F1UO+NloEELt5mfUYm3//v38x3/8Bz/+8Y95+OGHeeuttwgNFZ0ngrFj894KxY9q9uRwfr+3gifunD7ki2i7r0ngB3OkDrDtJTZl7JDZ5uKTY2fZWixF3C4l2N7Ot+AHxGsvWDZcTopCHsmU4xuvIy/ua+8wsWmPhT8flvZVNsn888FK/tNXGJyRqCNEPZFKZxuJ0aEYI0J5r9DKzzON5J9yEhGiUobKr11sxAukxoahC5yopDPx/azodBPFlc387Haj8nOA8MAA/vuEg+/P0fPJMalrLjk6lIKyWsUc9Nd3T2fj6rlsO1xDRIiKf3xTz6OLjLg6vKy9w8S/pBs4aG1QfLpAmpV4uqmdpdOj6fT2EKQa+lUSpw1ikenC/FC5y1L2/IqfFEySPnyAKA8PUrFlTTrHfSnPt33RqqXTo4dcB3IH3mimD3R6e/H3D6C6qZWPK5vJToniS6uU6qxv6WDhVB1bDlQrtU1+E1AsUrrP97LjazvZKVF8Py1+gFCTh3vv9hmuDq43y1mWxKQQFd09vcPu58XGBX3wVSVzjToKTzkp7JdOLTrdyIyoUHabHcyMGZiGHNz48nahlS1r0gF4+DtTBjQXTI0MoayudViPtUv5zC2cFsWqTQeYa9SRZtCyOt3ANw43x89KojbJl9bdWWLjP4uqCfIJ6n2nnMxN0CpzX4P8pJsT2aMwOyWKE7Vupbt37WIjfym1KXVrgGIWLfulgXSuMhJ17D7uwO7qkmoTs0xKN/KDCyZzW4KWIzUuHG4PdlcXZXWtrMlIYGtxDbcZJcFW55IaEbRBAXx4yEZqbJgyh3SpSUdukdShvbe8nh2lNt57eD6RYWpqmtrQa9QYtYHKe3S+t48/Fp+hqatniEg3agPJyTQSHqwe8N6X1rgormxmnlEnZoQKBjBqsTZhwgR+9atfcf/99/PTn/6U2bNn8/TTT+PvP/Ap1q9fP+Y7Kbg1WHfndLrP91HX2sXHh8+ycfXcIQt0keVC7Vi4yo+V8w0DFnt54QsPVF1SqMl3wyvS9Ir9wmA398HbD/7StTrbSI0NY195PY8sNBARrFYWzP7NDfK/f7IoEZV/AL093Ryple7sw4MCeKtQ6rqUu96KK5t5aXkyUZpAXss7iUYdwMelNsnI85iDlXP0uDu7uc2oUxzpp0WF8If9khA809jO7aYI/vuEJMg+Oebge7P0xIcHUelsU/zbVs4P5765k2ls9RCinsiZxnZmxWt4ftcJnvG5tsdpg5SuNvk9qD3XwcPfmaIY5K7ffpRXOrw42rzK+bC7Otl+sFLpcMz12WOkGbTETwpWph3ImG0ufr+vgieWTldq036cblAW/sHYXZ24unoAqc7N7uoaNsL2Xr5FKRKX55bGa4OYogvmD/urCZjox3+fkMZyyca4u487uDc1Rqn1kiMhTyy9UK8oX69To0JpavNypLaVZb6O1w35FsVGpH/UV0YWYgVltRw63TCkDvKDryqVCOPUyBBifSIgzvf3eZ97vfx7w4k+OZLV/+d2V6diifHLe5IH1GXKj48mShMZph7w3Ofavew91cCP5xtYOTee+EnB2F2dzEnQ8kyWiTtmRPNOvoX/KrWxsZ+A7O2DLQeqFRuNSF8Hc1f3edYtMXLgdDMOt4e5CVr8kFL3TW1exX5FHvoOkp3F1MgQAEWkrclIYE1GwoXzmGnkuzNj+Mc39eRkmbA4WqTpGdXN3Dkjio8Pn2XxNB2bv6oeMKrq13dP5+uzriFNCHIk/Vf3pvDXUpsics02Fx8cqlEi1BMZ2H2+Mj1h2FFpsnXNL8Y4KyAY/1x2g0FycjL/9m//xuOPP86GDRsGiLUJEyYIsSa4KuTC8Xtm6kfs7ruU23qaQUvBKedFF55tB6sU0ecPSteb2eZifZaJNp8IkBnJbysyVEVTu1cp3i6ra2VaP3Hx+F1JbNpjUeYHxmmDeMYXZVqWCkerm4nSBLJ0ejRnGtqIDlWRu+80zy0z8WpeueSvBdhaOnC4PRypbcXh9lDT4lE65iJCVDR3SFMNZHPQ9CmT2PG1nUcWGsg/6eQnCwz8+bBkLPrDOXFkp0SRpA8nt9AqjftJiyVFH07+yQYeXaglVR/O24VW/CZIHZsAv/vsJLvNDkDydHp22XTSDFqWp8Xx6+Z28socUlSvp5v0RGlm6OpFiYpRpyxezDYXfymtoeCUc8CIpK8sTsXCQx5Z9T93HCMpZqAZrjxX8VyHhyJrM+d9+zMrXjOsoJYL2lX+E/jlPcnsO+VURiCtmhdH9/leAAIDJpKdEkVLZzcOt4eSqnN8b5bUiJBbaOW5ZaYh4nJbiY07Z0QpA9ILTzmVZpT2Lq9yPfZHFmI5WSbFfkHtP3FA5M3Tc36Aj9gTmUYSJgXjPd+Lw93FfqvUBRgA3DFj4IxI2SpiWnTYsL5/uY+kK/8ebr9eWp580WilbPA6Uy81EhRZnEwKUeFwe9hTXk9ybBiv5pUr3n+v3D+TVZsOsHH1XOWGQT7nOcuS8PRBdKiKQleXMi5K7jjOSNTxyv0zWbu1hOeWmXhpeTKtXT285RsSv/dUA1MjQxQD3dTYMCUC9limNKoqOyWKqZEh3JsaQ26R1BUcqw1UUqOr5sVhd3UpZrn17d1kp0QRrw1iWmQoc+LCeeOLCvQaNXcnxyjdqxmJOjq9vcp0iQ17rEwKUdHp7WHtHSbee3g+tec6qHC2DRBq2w5WKdsMx9UINblrvf8NrBj2fnNwWWKtvr6en/3sZ3z11Vf87//9v1mzZs212i/BLcylvlgulR6QhVV/I9bByNGOwbVuqzYdICNRR3OHJL5kgTC4m3Pw8zS3eQlS+fHYHdMGRIHkOX5yelSOsKUZtOwsqeHVvHK2rEnnSI2Ld3yzEh1uD6mTtYq7umyYm3RvKK9/ZuG5ZSbFhf8P+6XowhGfA3qyr4bsTEM7K9L0fHjIRnZKFJ29UiejZFrbyN2+GabPLTOh8vfjj8XVONwenukXrZGF2kcHKwnyD5Bmj2Ya2VcuRSm+cbhZ5BMGb3xRwZqMBCJCVVLUrrFDGV8V5DdwrmrhKSfHz7ZQVndW6SbMTIpWFm45qnasRmqW2FpcQ62rk9BA6evqo39Wc6L2Qvdibr9IR52vXu/Z7KQBkQtZsO0sqeG/Sm08mWXilKMFu6tLWehLqs7x4vIUGtxdnKh1E6sNZFJQAG8WSFMUhhsztmK2nj/sv5A+Nfi68o5UN7M0KXrYa1l+H7JnxVLT1MbsWM0AcSSnV9cuNiqGr63eXjq7z7Pf2sTK+QbyTzaQPmUSwSo/JYIWGaYmt8CCp7ub+vZuWjq7h73+h/s8bDtYxc6jtWQk6th5tJY2T8+Ic0y3l9j4+LB07jq9Pbz+mYUta9J55f6ZNLZ5KfBFmU83SLVhFqdkT1NmP0eYOoBX88oJDfRnZXqCMqLppeXJrE43kBovTe+InxTMnn5zZ+VrXq9R89MMI6vmxREbHozDbWdqZAi3myKICQ9WbqjWZCRwurFDMbrNSNSxtbiGFWl6QtX+fHz4LNkpUTS1e5WB7v1r5CaHo/i+RYSoeOX+mbT4Oj/fLrTyyv0zaW7zkpagVSLxr9w/U3k/QEpJpxm0A+asbjtYdeGmhqFp6/5s2mOhu/fSpRwyRRYnJZUN7DzmoL6lg/XLZnDa2crfj9upPRctPNjGOaMWax9//DFPPfUUc+fO5dixYyQkjP2wY4FgLJAF1UgNCjKD01MlZxqVGpZpUSGKOBj8vJd6nv53so/flURvH9S1dvH9eRfqmTbkW6hv6eC3D8yirauHv5TaWJORQLxWmndZbm/hx+kGJgBRoSpe/vQbXlqezC+yTJxqaOOZLBNljhZyMo1YGjsUA1A5MnGkxsWZhnYezzTi6jrPzlIbT2VJJru7zQ70YWr+sF9yw+/2Sh2h4cHSJILNeytYd6eUityQb+Fvvto22ddJjmB8VlbP2iXTyEyKViw7VqTpFRF5d3IMByqcvFkgRSGau3r4RXYSwf4TiNUGSua5USGEB0lpuXd9IjsAyf19eVocDe4ughZOJCk6bIBIP25zcbyuhSm6YBJ0Ibz86TdKFFIWas/vOgEMrL9ytHThcHv4urqZ5al6Gtu8GCOCiQkNJL+8njkJkzhobSAiRMW8yVre+KJixEhTZJiac51SFCbB131oitEothyDr73+kV75+fr7ksksnBZFxukmTjpalbFKZXWtinBwd0jvf2JEKH8srkYbrCJKE8jv91WQf7KBVfPi2G9twuH2MDvWNqrh8dpg1QBz5W0lthGH2i+bEU1PTzcxoUE8uiSR8719NLi76O7pZaPPl6+nt48zje0sMOr4r1KbYsPicHt4KsukTOrInhVLm0fy0CuyOAekhJclx9Dj27elyTFM9JvA6aZ2PjHXMXtyOO/6atGOn5VMf/dbmwZEjB9cMJnqpg5lsPszWSZON7URGRp4YYh6iErp8kyODmXVvDje8YnHRxYa0AarebfQirPNy7s++xy9Rs1kXTAPLZrChnzJB7GkxjXg+2HtHSa2HawiNX5gql82Q3Z3dl/0fMg3eRmJukuOM4MLptur5sXhcHtI0AYDsPPIWUqqzhGq9ldKD/rzXr5lVLYwguvPqMXav/3bv/Gb3/yGp59+WvlZTk4Or7zyCpGRkddk5wSCK+VKuu7W3mFi894KcjKNJMdNumgEb6QUqxzVk1O1eWY7U6NC2bDHyuLESKWeSZ4f6InvxdPjVb5gV6Yn4HR3UePqZOnvCtFr1Lz2wGyeyjKxef8ZRSglhKvJP9kAKVHUubrITonG4e6iqd2Lq7ObWG0gdS7JguHZu6Ro3SSfN5s8Xqd/mi01Nozn7pmhRHXO9/bR3SsVQt85Iwp9aCBPZicR6j+Br8+6CA8K4OHvTBnQQSi74wNMj5a6QHMLLPwiy8THpTaKK5sJ9JMGUX9wqEYy//3azm2+Be2p7CT6YMA8RXkRz0yKVv6W/+SZ7cxJmEScNojJuuAB50sWGYPFhixcZCGSZ7ZTUF7P4jsilZmu/X9X9o8bjjhtEOuXzWBniY2n+jVQyI9tO1gFQHdPLz29vbR0eIYM2h7uGqo910FxZfMAs9hYbaBiYCzPwKxsaiMiRKV0dhZXNiupR1mgjJblaXGcbW5n7WIjumAVzy6bPmKTgXyM1no32w5WKSnCdbdPVYSiPD7rcLVUc5YcHcqP5xvwQ4pM/faBWUSGqXl19wlO1LoJVUvXptyZ6e3pU6Y7/Ox2I8drz6FRBzBlUjA7vrazNDlGsthQTeS2BC35J5043B7+ZX44G32RVrmTOCkmVPqsIDUQlFSd43ZThE/cRaNR+bHP2sxrVSeJCFHx3DITnp7zHKlxUVbXqtSpPbfMJNW6LZ2GucZFm69xYEO+BRUXbtKU0VOnnMrQ+v7X0NPZSYSo/C4aVZOjuKONrDW2StMoYkICSI0No6u7m8ZWycJkt9lBm6dH+WzK+7kx38I7hVbOc/Hxe4Ibg1GLtaNHjzJ9+sAi2A8//JBf/vKXQqwJLsqGfAsRgf6j6tq7HLYdrMLR5h3TwcXr7pw+ohCTzVzlCQSDx/PIImztYiNrt5bw2wdm8ddjdhYadeg1auYkSPNF5f3NLbQOiMA8tGgKdlcnB85Ii0x2ShQLEibx9+N2aRJAppH2nj62FteQPmUSeo2awICJlNW1MntyuGJDUFJ1jh/OkTzacrKk4eSpsWF4es7zyEIDARMnoNeolRFK67NMBPpPoK2rh4XToljT5qHW3cXxsy3clRzD9MhQHl2SyLaDVcr70/j/s/f24U3Vef73qyVN0jZNQx/TljS0TUuhpSAUoUiFQpFhB50BdhZ1/ck9XMOoqCjjjP6c69brHv2trs76Q1EYZtibvfXnjDKz4KwPy6iFikUetCBUCiUtLW1om6ZPaZo+JA3l/uOc77dJKQ86zu7o9HNdXkhJk3NOzjnf9/l83g+9yphYBIrv+KgWf+ASK4MAj0gb2LRY4e/sO+uSi9Cue+ZTdqqVactHRoAt7gG2lNexutDCyaZuPjjjZHqKEVOUllfK7Fzo6aeyyS25b8FjHQHUXiqz84NCCx29viuCjeBOk3iP0SMi8bvBi+yOj2rxBi6FnG/Kvloue+3Oj+ukqXFsZAQTIyN494vrC9peXpDKE55Bnt5bI7uUZqOOlTPMcmx8Q7qJ1486JJiPjdTS3N3PgVoXG4qt7Dnp5B9mW66rqyYW79zUWA7YXeSmxspu55Wqrs3DY2+d4rmV+Tx16zR0mnASjXr2nGhm0ZREPjqrdCcP13fxyBIbz+w9Ix80glMRbrYlYjYqoglhBP3TW3Jp7u4HkJYeOz9plErR0qmJUhhU3dqLZ2CIZXnJxOi1+AJKpzPY8uXVw008UGLDYtLz2FunQjrE51RTXdGVFWNUY2QExWqsGyjmyYFhhZPa7vXzcpAhsBZF+NChUicSYnR0eAfk59e1eeS5EQzoAMllHauCf34thXrPgBLx1tTjwxgZwQRNhBTwhKEIdcTnr95+iCeW59LnU6LgBoeGvrJJ73j919V1g7XRQA3g0qVLX+vGjNe3rwSAWT0rVXpSfR2eQCIOR9wwrxewidEEKDfVcy4lpiX4RnUloPZ/DtXzr58oruhFmXG8fdwRckMV22A16TnwsxJ2VTpkSPoPi6wh72vQhIWAvYW5yVJBOCMthhuscVhNemzJRv7tcKNUv+WlxEiPqR8WWZUwdvXfhJ/UqhnmkL8vzk2murWX70xLlh2I1bNSaXX3c6CmjdLcZN475ZRk65TYKGYnKUa9ws0/MDwsuTgLc5NZvf2QwkNq7cXjH2aryu/x+IZYe5PSPQpOGxgt0Ojo9WHQa2h0j3R/Uk2RHPhZCedcvXxwxinFDGJkW5QZx+7jLQwNKSOk0R2vl9Q4oxpnD6eaPayabSECQgQfY9X1cHl2fFTLa0ebpJBkU2mOBK33/+4Yu+6ZL/ehyuGmxTNI6dRE+nwXaXUPShFKvP7Kt9xgccTdCzIx6DUSXHze2MWvVPXj0MVhMuKieerWadKyRhwPg15DbKRWCjyuVcIj7ZapyfQMKlmb9jYvDR19/Hz51Csem+Du4ytldh4ozWHnx3VUt/ZSkptM4eSJvFvlpCgzjhf2KV2pZo9C4hfinSqHW/K3hA3HE8sVoLZx1wm2rJlJu2eQmVOS0OsiMGjCWJqbzOZ9tdw+ZxIdXp8Udrx6uEmej7fPmUSCAeZa44gzaPmkrpNy1U/PbNRxoKaNv1dFM+c7vWwosWFQc0cFb+2uuRa2q7Fu+1Uhgtmo44nluQSGhzEbdczNiGNG+kQudPVx+5xJJEbr5Dk5JzORMCDeMNKpfe1gPYfPd5JjjmXJlCRJEQDGBGwvltl5WM15vZJCXVRxThInmtw09yhdWc/AEDlJBtImRlEyJYm3Kh04vYOkGRXLkKf31qhqcEuIyGe8/nprPG7qr7C+atDvX2PF6zUh3YHXjjbJLMGvWlUONzpNuBxPCHXblarFPcDJpm4udPXx/Ie18gl95QwzQ8Pwr580XlNhmmqKJEYXEZJ3+cK+OqK0oR1DsdgKcCL2/YkVIy7xwaNGEews/NcIDLFdVbBNQFkMRdC26AjE6iN4ZuV01r1ayY9uUoDaXXMt6FRT2z0nFRuKWG04nX1+WnqUcOs/nW7jH2Zb+P0xBzWtveQkGqhu7WVNoYXq1l7Z2TAbdfzDbIuM3fr4rIt1N9uI1GqYFBdFR6/CXytMN1Hr9LDuZhvhQGVjFzsPNaLXKb5UawpHOjsGTZg0ha1yuLn/d8fk6C74uIHitbbqhkmkxxvkuLgoM44b0mLwDAyhj4gI6VaIekiNM9o2agwm7B2uBsqEsbEAYD0DfrKSYuR5KnhUorMWbMwMcM7Vy7pXKznwsxK5XUIVel+xFX1EBAbdlbvLY6mNxWhZ2KOUTkmSoPnGlXH4AsOXXUfXs+iKbk6F3UW7ZxBjZASb9490qlYUmLnBGscze8+MyXMSJYDaS+p2P1Caw+DQMJv3K+Cs0qgjWjeB2+dMkt3iTYsVlbPwZ/vpLbnsO+uCgKLALTvr4nB9F8+tzKfW5Q2xyXi4xIbLM0hGQjSNnf2y+5xmiqTZPUD6xChKcpNlSPyLqpFufLTCedtWrghFhoBj6rkR3GVbPStVRqy9ftTB6lmp8iFE8ECf3lvD7nvn4/UP8/dqt2owcIl0NUlAnEtpE6PYVtHI7nsVEP/GkfMcPt9J2Zl2TjV7OFDTxlPfmw5cGahtVY/rw6U517w/7a1qob7TK0VAsVE6DHoNT/7HFzJjtXRqojxuG4qt1w3ox+uvo/4ssNbbOx4e+3VXi8pVGj1i+ybWy2V2LoLsingGhnjklil/NlD73afnJYF6RYGZc67eK76nsH8Qir8VBWbpUv+rikZp33CtsQ8oHaLt++1MMceyVR2DlOanjLmNYsHNTTJw4GehPKXcVCXO6Wy7VwLzf5yXiUajhK5fAt466eRUs4dFU5Iw6DU8viyHSK1GdtMeXZqtuOknxfBgiQ1tOBxq6JImt3OzEvnVgVqcHh/JsVHsPl7HhmIrM9NNpJn0+ALDLMxNprPfJzuU2WYjZqOOZXnJxOo1ZCXFsPPgOV493ER4mOKJtavSIcPnCQyxZl4mVQ5FyfrUrdO4wRrHpcAQv1KB55p5mbx34gLPf1jLo0uVxazAYmL9TRk0dPXR0NGH2aAce6FmE4ucsPsoP+siSs0fjdBESONkCOWk7fy4ji4167TLO2KMmhvUWRPiieAK9ok72exm9/EWGdwd/GAhjGCXTEmiZ0DplBVOnkh1ay87KupljJfYxwKLSY7Mg201Onp9IfYKe6ta8PQrhrCDviEZfC7eB0KBpilKKwPCvywNQBDXA8MKd+yJ5bmkmvSKnYVRJ1WteSkx0rNMHKOxwO6MdBMrCszMSDfJmDizUcfQMGxaki15jCeburljjvJdifBzUeJ82VBsBU0Ed8xJ51B9B29+doEHS2yY9BoeLLFxvyocESBNjJi9vgA5CVEcUE2O75prUVTUxVa2ql39CJSRqk4Txq6jTdw+20K0bgJ2Z48UP1hio/AFvJxq9kjLG/EZrx9VBDoA+8+62Fpeh0EbTme/j9+oXWwYsT/ZsmYmO9cWyu98V6WDhbY4YmelkhwdwZ6TTuraPFccgUYAt8+ZJBfoa4GqGekTeeOzJkqnJskUiI9qO7gh3YR7YIi8lBj0ERMUaoTaid+dl3YdZ8x4/bXUdYO13//+93z/+99Hq1VurBcuXCA1NZVwNU6jv7+fV155hUcfffQvs6Vfc23dupVf/vKXOJ1OZsyYwcsvv8yNN974371ZchT0bQBqvz/mkNmONeoY7s99kqtudhOrj6Bw8kQqz3czLTnmqu/Z0euTnJb3q9sw6JRTPj5ay60FZiIiIiQHaqwa3eUUN9fZ6aaQzgso3RGzQctpp2IrcaVFNCsphvhoLe9WOcmKN/BAaU5I2DuAo8fHqhsm0TPgZ92rldLQ9YnluTy6NJvTbb2svymDinMdVJ7vxulRCMYrCsyKglEzgVPNHhlCLlSFAgidaOzivRMX+KRO6XYsyEmirs3D38+2MFHlF24ts5OVYGDTYhvhYfBG5YjLfNmZdm6ZmixzCh9fliMBxrZ9dn6sijREduHQxUvkpsbK43n3gkz2VDaRkxTDHfMms32/nV7/EL9RHeJFDuihWhevBHmcFVhMZCUZGPAHLuOkFWYk8Oz7h3ioxMaMdBOJBn0IcVp0NIEQwObu9/PcynxJ1Bf7t6HYKoPJE2J03P+7Y+xcW8iT//EFnX1+1s23cvHSJZka8cxehaD+1Pemy0X67gWZsovU4h5gw+uVLLTFseekU4LZtIlRnPusCc/AEDNSYy+zkxl9bgrLCzHSC0fpKl6r3jhyXp6/1gQDZqOO2g4vERPClYxONQS9dGoiOQlR7Dnp5ERjF5UNHTz7vp3nxjjm4trzDgbk6PIf1OxMs1HH1jtn8/ZxB/Ozk6g46+LNY4rX32hT5DBNBOHAKyqAvG9RNhlxUWjCw6WwZhjYqj4UfNrYJUGlGDELEFJ2xiU7ziKQ3WzUcZMtnqbAME6PDz+Kctps1HGq2UPh5Ik4vYOKUtqow6gNJyMhWr5mQ4mNf1cTFLaq3b4UUxTPvm/nHtWAN1arWOA8sTyXGekT5UN3R6/iiZiRGC3f/+9nW66aEuEH6ft2tUmL4JqVnWrlcH0Xs9UkBmFtI2K4ABra++S1vmSMGLHx+uuu6wZrd9xxB62trSQlKRfntGnTOHHiBJmZSlu/t7eXxx9//BsB1nbt2sVPfvITtm/fzty5c3nxxRdZtmwZZ8+elfv331nfdKBW5XAzIUzx9YqL1HLbjEnyhj96bHg9tbXMzspCC2WnWjnd5pFxMisKzFSc67wqDy4hRkdJbjI1zh4yEqLRhIdJpdo7VU6eWTl9zJuWCOW2O3u4b2H2Za8ZK91AOKa/+dkFMuIuHx9tLrNTqIK8bXcVShXhWE7mP5yfqRCVe30yfql0ShI7PmmQJqDpsTrpwzU4dJE56RN59n07D5XYpLKuu89P14CfrAQDi3MjeOp70/n4rIuXVBuC6tZe7p5npa7Nw4c1bZSdaefBEpt0/Rd5oKsK0xkaht8fc5Bg0FE6NZGJ6gjwjSPnefZ9O5FaDXlpJjYsyZGLiOAIvlHp4A01xHz9TRkkGkdsIV4ps/NpYxc3qEKMzj4/tU4PDS4vt82ycLKlh7xJJjaX2VlTaAnp8IjPEbmswcq74pwkyacCpTP2KISMq9z9SlzZqplprJptUUaoxVYyi63oIiKkHcmqGybh9PjISorh7nlWHnvrFC6vD50mnN3HW1g9K5Xdx1uIj9ayevshdq4tlGNRUammSJbmJsvjatBrJdgVpPrgfXvjyHl2VTok+AsucQ11DwZ4SB3LXu2+Id4ruBNX6/Kyv6aNzj4/pVOTZLxSsIfd03trWFFg5tGl2Tz21inm2RLH/JzlBalsYaQDODPdRGykVvKyBvxDHKhTOr+rZltC9qdnQNmmvVUt0ialwu7CHxjGZNRyR6GFi5dgi0orGPAHpFHwiWZlunOb4Gmq+a9Dw5fYUGylqUfpNA8ELhGGok69a64FT79Pxr1lxEfxTpWT0qlJsqN6oK4LY2SE/LtHFQ/kpxlZNTuWAzVtHKhp44nluWQkGYiL0hGp1eD0+IjQhJNqiuS5lfl09PqkD97Rc+1QALZ4w1XtMqocbnkeFmaOfbyBEC4bKLFz5TVtlE5V7k2fN7n53gwzzT3Ktt9ojRszTWO8vhkVfr0vHC0m+CaLC/73//7frF+/nh/+8IdMmzaN7du3ExUVxc6dO/+7N+0bWS+V2amwu9hb1cLmMjv3/+4YH5xpk/l/R8+1s+5m2zWd0ceqzWV23jzmYM2vD1F21sXu4y141Lb+u1VOGjr6pDJxdAku2CvldUwzx3LHnHTW32zjzhut5JtjeWbl9DG7cgJ47TnmwGzU82+H6mlxD4T8e3BVOdwcqGnDbNTxfnUbD5bYLpPli/c8WNvOhtcrVYd5g/QDe+1gvXyv1dsPsfeLZn53pJ5fHailweVl8/46DHoNu+6ZL3MMxeLU6fUzJ30ipigtTyzP5SXV6+pwfRe1HV7er26j3etnY2kO1c1uXlIXvQVB/mjOnkGW5ibzYImNG9JNrCy0cH9J6D4snJLEhoVZxBn0FE2O5455k3ntYD2mKMU0NC/NxL8dqueNI+clUHvyndPsO+viezPMykI9w8zTe2t447Mm9la1sKeyiWpnD4fru4jXK2Pe6SmKqGLHJw3srnRw541W9nx+gW3ldbx5ZOS7qLC7+PlbX8hz7qPaDoX/pJbgU71SZpfHVYRv761q4Zm9Z2jz+qlu7aW5Z0AukGgi8AxeZPN+heP0bpWTBjVW7EhdO5v31bJ+gWJYW6OOhHcfb+H2OZMwRkawZc1M1r1aye5750sBwmZ1G1YWWshLieHuuekh3T2hbn1FPbd2fFTLtgPnqG7tlV3G0XX3gkxmpZvYWmZnza8P0eIeYMdHtWO+tqdf2c+mTi+vlNnZ8VEtL5fXSRsQYZ5sjIzgJls86RMVn671C6xUnu9mIHAJs1HHn6qaQ95XAIYKu0sCtW377BSrhsD3Ls6RSQ2C4L/nmENu5xtHzrPu1UpeO1jPxl0nSDTqqbC7OFTXzgv76viwpo3N++tIM+lZN99KokHHs+/bWT0rlV9VNHJDmiIq+KSuS3bWvrjQQ7N7gG0VjXR6/bR5fbxcXkcYSqcp2aDj9aMObkhTRoM7DjayaEoiTs8gN6QpXahbpibL+LUV082UnXFxky2eKaqHW0aikqu645MGfv7WF/zb4UYmxUXxUIkNU5SW1w7W89hbp3i/upkqh5vm7n7WL8rmZ8umjgnUKuwuafUiwN2SvLSrTg1EmktspJY9J5pJMempbu1FOyFc2o78x0knN1rjuGWqeRyofcPrb05g4Pf7OXbsGI8//rj8WXh4OKWlpRw+fPiy1/t8Pny+ETDg8Xgue83fcgkFXl5KDIWTJ0pVljEyAt8lpH3D0MVL12UjEFyby+yS/HvXXAsWUyTfn5FKQ0cvF3p8ZCRG09DeJ/2DRpfggokQ6eCfX+0maFU5PKkmPa8fdfDcyhEX+LGI4AUWE099bzrN3f20ewbHBKTBdh15KTEcsLt49XATz63M54nluSGka6HiFOOdOekTeW5lPolGPammSArTTfJ9l0xJwprgodPr48OaNpbmJsvQ68eX5ZBtNvJulZNFU5JocQ9gitKyelYqh+u7iNRGsLE0h2b3IJv3K6TsWaoj+z3FVu6cl0m6qkitcrj5lw9qsMZH8eZnF7hrroWdH9fJ5IMta2ZS2aCMZN+tcmJSDXbbvH45Nlo9KxWDXgF2pihtSBepaHI8EZpwDBoNF9yD5KcZOdXsYYvaAfzh/EzS4w0hRse1Tg/x0Vp5jsRHa2nq9EoCvfjOxZ+CK1VhdzEjfSJOj4/dxxz86CarJNZvU3mMAD+6ycouNUR8z4lmqlt7+VBNbzjVoqgDxUizdKqSK/ncynw27johO3yCx2V39kBgiCV5aWy7q1DuQ3BHTIDLIYDAEBkJ0ayYbiYrKTSsXVSF3cUHp53SoX9XpUOem8FAsMU9wPnufmnrMj3FyBetHooy44g3aOn0+jEbdfT5LlKQFsNB1YRXkO+/P8PMyypZP9tsDNmG0fFv4noHheO546Natqnf4YKcJPoG/Rj1WtYvyqbCrviQPXXrNO6YN5lEo560iVEkxOhY92ol96tRcLcVpLG8IFUCQyGEebjERke/Txrj2jv6yUuJIcWkl93fU80ePANDPKh61uWlxHBxWOlCmU3RId+d2ahjclwUhZMnsnm/8sDj9PjoVuPHalp76VEfFDPjDfKe9FlTN0WT46l1emQMVVZiNOsXWPlNRSMaTQSfNypCGnHOB4+391a18MZnTVJsc8e8ydc9ohRd5c4+BYyXTk2UecCrZymfpdOEK+fkVcQi4/XXX39zYK2jo4OLFy+SnJwc8vPk5GRqamoue/2zzz7LL37xi/+qzfvG1TDKjW9hbjK5SQYMei0DviH0E5CdCrNRR5O7/0tn1AmAE4bCERMLQpXDzYGzLlaraqyrjX9STZFjhntfrcR4rtU9yJY1M0NARTDoigwPjY8SuZdbyuxXNJncUGKDgDIS+nGxMk478LMSCdS27Rvxamvq7mfV7Fj+7XAj62/K4LG3Knnq1mk8+c5puUC2uAd48j8apeIrzxwrXeQLMxL46KyL3ffO56OzLv5wzMEzK6fTolpJvFxeR3aSgX01Sqj1KyofSKjvJqiCh387VE9xluKlKHg0QkmmCVf8tepdXoaBHxZZSTFFyWP2cGkO2jC4dAl2H2/h4RKb5KgFH2/RhRPmqukTo8gxx+L3D7F5fx0ZiYYQTl+Vwy2BonhQ6PT6ebfKSUZQR1B891UON7/++BwN7V7eqHTwwyLlvPzeDDP/cXIktH21SgC3d/Rzvkvx+jrt7KGzzy9BdVFmHDnJBqzxUTJM3OsL8NzKfObZEllRYJYPEK1u5T1ONXsUY1ZNhPS3KzvVGuLXpwlHAkWRWuAZGOJ/zB+7Gx0bqSVOP0HyGT0DQyHh7qKEee8fVCuZHv8w71Y5pSmyUMy++dkFPANDzM9SOrcCBP9RBTRbVUsLCKUBBP//xUvKOS4ezMS2iD+rm91sO3CObNVWIhjopU2M4nefnic5NgqzUYezp5/dx1t4fFmO/JyHS2x4/cOUTk2U4+RVsy2kmHy0ugel6lOAtttmmPmkrouX1USDeIOeSG041a297K1WQM3f5UdJtefheuW4/+gmK+9+4ZR8L/HwJpTgW9TPiI9SzKlvK0hj464TrCgwEx+tcP8E4B30DXG4vos5akdcdHmfW5lPo3tQ5toqWaOhmcTXUwUWE3fPTee1o03kmGO5b2E2B+0uNu9XFLTBquLx+ubWlwJr77//PrGxsQAMDw+zb98+Tp1SIl3cbvfXvnF/DfX444/zk5/8RP7d4/FgsViu8ht/WzU6M3M5jIwMNREh3IuvcrMYi6QfTEz+S9XVyL+bSnNCgJoocRMWN/hgwLa5zC6Do4sy46hu7cUYGaGq8SL5U1Uzzd390kJh5yHVW034lw0GZAdiUlwU3sGAHCVtu6uQP1U1szQ3mVWF6URpwyVQEw7lYuHNSoqRdglrVPPZ6laF9/NAiQ1XEKdpyZQkKhs6eLfKyZREAw0dfaxfMALU9lQ2cfeCTNkREpYfwYHro2N47i9VFLW//czBgJKfTmG6SY5odJpwbMlGOqub5TY/ssQW0pEA5RzYeudsPj7rYpdK/P5uvplCa1zIca+wu8hKiuHouXZSTHqOnFd4U581dUsifOnURCnSqGntpUcFvmajTnb4/mG2RXpT5ZtjeVHtFm1ZM5ONu05QlBnHY2+d4qlbp/FulZPirARWFabznYI0vmj1kBqrQwPSiuTtqmbKzrTL7x+UZIc/nW5jTaGFyHDFmPWnt+Re8WHkoN0lwSKAZ2AIT79vTIPTPZUOLCY9D5XY2HVMMdNt6vTS0N6H2ajD6wtIQLLjoELMP9rQxaIpSkqAQRshY5wSonRjdqZfLrOzTz3Hg02wRRetOCeJIZXg3+4ZZOOuE2wssdHg8nL3gkwO1So0h0eW2Fg124LZoCUn0UBhhvKgsH2/Qolwenw8WKLQGQ7YXfI8EdfL6iDFpTCNLp2qGPWK2DSzUccN1jjyU2N4p8rJTbZ4Ovv8FE6eSIpJz7tfKIrK2MgIYvUR7K5XxtwrCszyYUo/AT5tVEQ/Br2GR5dmMykumsYOL8bICFYUmJkA/OcpRVQwU+2IF1hMPLcyX3JE81JiyDHH0tbTL/f1y9b6Rdn0By7xSnmdYpOzJIeICWESJI8DtW9+fSmwNjq4/Z577gn5e1hY2J+/RX/hSkhIYMKECbS1tYX8vK2tDbPZfNnrdTodOt3YY7bxUmo0oBKLy6bSHMwGbYhx57elxpLcF1hMPKz6O31nWmjnVhyjhbnJGDTKdbIoO4G7F2RKt/vHl+XIrta6+Qr/pigzjhuscRIMmaIUUv+vPz4nLTR8gUu8VF4nrSP6/MP0DPjRhsODJTY2luagAfSaMM65euVCe87VS73LyxPLc+n3BzjbrkRPDaMAtdXbD3FvsZVNixVPuUeXZksxh+Da+QLDvKT6V11CicbZW9XCOZdXgihQAJng6lgTlM6SAKIXA4rJ7WWcGk0EZoNW/rzC7uLwuXZaPT4JhgosJm6ekiSPf3BV2F0y9D0+WiuNTdfNt2LURfChyjNMMOhkpubu4yP2E/lpRsxGBbjZkgzkpcQoAGtFPmFqyP3CX5az+9751LV5ZBqFThMuwX6qKZKfLZs6wqtUO2tpE6Po810MsX5JNUWyJDeZjl4fQ8NI0cFBu2vMnE7RvdJHhPPFhR4W5iZzoKaN9VfgS+alxHBbQYrCSTNFceR8F7dMTebI+S4MOg2V57uxxitdrf885eTWAjM7DjZKdewjS2w8rFpojFUiFmnVzDQJ1KocbqloFmNVwV3tGQywRQWvMHJNBV9b4gHooRIbD5TmSJFLokErz+N0UxSHz3dKI2gBiEWH655iK+c6+lVLGq2MoxIPT+J3hCfi7XMmqebHHjISovmko1OCs4/OtsvXm406Sqcm0e8PyHH0o0uzsSYYONTQhSkygkhNGOtvyiAjyXBZHFqiUU+OWREr2J09Yx7TL1MPqbm7o7uZ4/XtqOsGa8PDw3/J7fgvK61Wy+zZs9m3bx/f//73gZEu4QMPPPDfu3HfwvprJLXuqWySY4EdH9USb9BxwT34pfLxdn5cR4opirSJUVQ2dFCYkUCBRQEkE8boukEoqA3OnCzMSODxZaAJD+dATatcLDeU2DCrIe7CL+yZvWfYdc98SnOT6ezzk5sSQ6pJL8e1YmEWY61HligLd7Q2XBreblqSzeZ9tTLE2unx8dzKfA41dCkgsbwOq0nPj26ysr1CSWx4dGk2z39Yi0EfwR3zJnPBPcgTy3MV9ae6kMII/8aj8nw2FFsBQhzYlxco6QlvV7XKsVVmQigvq7m7Hw1IcNriHqCyvp13qpTRVUN7H4lGPcU5SVQ3u+V5JhSjqaZIqi+4ZeTWHrWbVDpVccOPM2hJMenl529abKNrQAn0To/VYe/op+xMO/cWW3luZT7LC1Jp7PCyNFcB4Zv31/H92RYeXZotFY9b1syUUVt7q1podfez7mabVHxCKKAcHfb+SpmdLeV1BAJDbKto5PfHHNxki6dnQBkFO3sGL+N9ir+L0XMwpw8U3y+x7wtzk1l3s40tZXZqO5SUAtEFFl2nDq+P0qlJlJ1x8Y6aQADwcImNi8Og1YRddcz/YOnlQGv3vfMlwFk9K5WZ6jhwZrrycBOj1+D1BahyuMmbpByfLWV2JpkUgCoyUsPDRnI1m919ki+7Zc1MCSYHhpGg+5ElNn77mYNfVzSyUR1drl9g5a65FgnURDTVigIz/6pGWmnCw2S8169Ug+qdhxrlsdpWXsfGEhte3xBnnL0yFeSRJTae/7BWKoAvdPXx2tEm1t+UISkLR+raJeguzkmiweWVfLOizDiau/uv2gXbts9+Ve7v1wXQqhxu9p11fa1RfuP159XfHGcN4Cc/+Qlr166lsLCQG2+8kRdffJG+vj5++MMf/ndv2nj9herFMjv6cIiNUsDP2qJ06TBvNurISIi+6iIkQsM7en18dNZFd7+Pt6taZXbg21Wt0mIhGKhtLrOHmLKKSojRyXipYKuHR5dm0+Qe4KOz7dKB//FlOfzb4UY2LcmWcUdGvYaMhGha3IP80d3C92ek8saR89K9HxQu4cCwsu2FGQncNXeA6amxrCpMJ1Kr4YMzTnJTYvikrpNIrYbleWaefOc0TyzPZVVhOlUON1ptBLHacLLNRh5ZovDNRAD0XXMtfN7slrFQawotzEifyKH6Dho7+1lblC5Bz4ZiawhRft3NNgkwrKbQrpEwqb19ziR+r3bnlhekskSYeGoiZESO4LoBOL1+tpXXYXf2kGeO5YHSHHzDUKN2LYQ1h+BYlp1pZ9YkE1vWzKTV3U9z6wBlZ9p5fFkOZuMw95fY2H3MwaYlMez4qJY/nW6TI+MDPyvhT1XNMqbr4ZKRUe3eqhaqLnQrnDc1OzW4XjtYz90LMjnZ1B0CrLKSDKwoMHOgrguzUUfh5In4AsNyVFbb4Q2JpAou8dmjO9iiw9UzGOBBNRLqZbXz5PT4GAwMSxuc9FidjDTLSIjGMzAk0wRa3YN8GDTGv9q1AkhOohBaCAAiPA2DbSe+cLjZvL+O9j4frx91hKQKwAjvcMMSJf2is9/H2ycV0L5RPe67J0ZRrl7PRZlx5KXEcF7NF81LieEzFZD1+i7y0dl2+fMccyx7jilcvrvmWjBow9le0SgBoui2Ca/I/DQji6bouAjsPKT8PFo3gZ8vT5Oj0I5eH8sLUqlyuHn+w1pmWuNocQ/wxpF6tlc0Kueier7PtMbBJw2sKDAzPcV41ZQNId7wXeIyUP51VpXDzb7qZrap2zoO2P466rrBmt1ux+12hxjH7tu3j//1v/4XfX19fP/73+fnP//5X2Qjv+5as2YN7e3tPPnkkzidTmbOnMmf/vSny0QH4/XtqBfL7HykLjR5KTEUZcZhb1OI1SLGKFwTcVWgtnHXCenbJDIPRVdq3Xwrk+Ojx/RV23PMwYrpynhd3IiFOapY+MWCJojUb352gQdUwv9zK/NxeQZxenw0ugclGT0jycAN3gHsHf3ERkZQca6DG61xirAgSIyRm2Rg464TPFhi4/WjDjYt1kmbBeExJnhmLe4BzAfOYdBrpD+aADedhxuJj9aSZNSzSB07TgBMUTo2FFv5vLGLbapAQXT0zrYrnag+30WW5KXJxUV0nb5TkCY7YaJE5+Ahl5eX1HFwmmojUWAxcajWxW2zlIVKdDcFl09UW08/nzZ2sbXMzkOlObxx5Dw32xK5Y95kYtUOY2ef0kWbm5VI+VkX5er58cgSG8++b2dFgRm32h30DgZkx0L4pK0stPCdgjQ+a+qms89P96BfCmhqXF7e/UIBEznm2JBzQmSMdg4G2FZeF+JNtrwglQZ1FC3AwoZiKysKlPOnob1PAuMvs4AGq5M14eE8ujSb4xfcEog8XGLjw5o2piUr18bMtBhqO/qxxkfx3XyzBO4D6ri6oaOPn96SO+ZnCZ5il1fJARXfm9jmV8rs9Az4Q1Sk4lxdkJPEYrVzOQFkZ63KodjN3BxkXq3RRLDnmIOZ6Qrwq77glmHl4SiebPfcnIUlNgpHTz8RE8LJiIvis6ZuVkw3SyFBiknPoimJeH0BJoSHsb2ikRUFZjr7fVLsYTbqSI6OoAbQR0yQIfVmo46s+GgqznVypqWbX6lA971TTvngJq7tl8rsbK9o5L5iK7bkEUWt4F6O9tgbq/QR4WwotrLnmIPPG7uYNznuSyvsr6cqzrqkLVDwtTle/7113WDtscceY/r06RKsNTQ0cOutt1JcXExBQQHPPvssUVFRPPzww3+pbf1a64EHHhgfe36DSxDHO3p9JMTo2F3pYOFVkgiqW3tZN9/KGWevjKtZN9+KXhchQcZYJaJ/Nri8UiyRlxJDfmoMDR1KgPPOQ40h5qfB5fT4cPb6+B/pE+XPBH8pLyWGvkE/dW0ejp5r5/kPa3m4xMaGEhs/KFSSBB576xS7753PwLAyftGg+J2te7WSHxdbKTvTztqidGakGaT44EJXPy3uAbSMmJW6+/1sWmzDHKuXHY12r9IV3FJeR4LKDbt9toU/nmyRHb1HltgY8CtjufhoLRXnOnjsrVM8XGLD0dMvY79Wz0qVC9NQYJhO7wDvVjlJjzeEjPsEP89s1NHT72NbRSPDgSHumJfJnkoHL5UrnYNNpTno1Iip6ma3HFn/9jOH5M89/2EteSkxrJqZJgns8XoNnzcqpsmlKqgMBnLCi67srIviLEWEUa7apNxTbOWFfUpnRpjdbiyxseOTBgx6jQRsWk2Y3J8nVuSzq9IhO0Yt7oGQ7qYAVS3uAd47cYEWFXgfqGmjdGoihqBg9x0f1eK7pICDTxu7VGuNSHJTJzIjfSL/XunAGBmB1aQPOceE/ce1RlciCumJ5blSJLGhxEZYmHJ93GxTVKXzJsfJSLWN6n4ctLv4tcoJu1LiR4Xdxf6aNl4/6pCu/8ElhChinChAWot7AN8lpdss+G3Baud9Z12KgbN6HhRYTPQM+KWFzc/f+gKnx0evf4j4KMWH7albp3GsqYtXDzfJFINNi23oIybwr580SgBcdqZdRmzdPmcSa4vSqTzfLTvm737hJCMhOoQPJ/zcHiyxUXGuk8P1XaSa9DKMPiMhWnrjiXNCJEyUjHHsrkcwJYyn1y+wyo5jQ0cf4WFjUy7+nBKcxJV/we7deH35um6wVllZGZJO8Nvf/pacnBzef/99AAoKCnj55Ze/MWBtvL65JYjjZqOez5vcLLTFsa2iEZd3ELicaP5waQ6XQHJmRE7ezkNK9FIwiT24gkdsS6YkYXf2EG+IJMWkpygrEVtiDJFaDfctyh7zpiYWzdEjC+HLdvRcO/EGHa8daaS6tZeNJTb6A0My0H1bRSPPrcynwGLiwFkXD5bYJCdIqBA3FFvZc9LJ1jsVRWCDy0vZWRct7j62VzQyDCSovLfHl+WweV8tjyyxUZyThHcwwMtBi+fOj+t4UV2grfFKlI6whSidmog+YgKrbpjED+dnUtfm4UU1saGzz8/u4y1kxStZkiJKqigzLsSTbm9VC8++b5e+WIMXkdufaormXKeX2+dMUmxDgL8vVLhF4jsw6CNYMd1MijGS0vwUJoQrQo3D5zt5em8NO9cWcveCTALDw9xojZMdJeG79trBevacaObueVbWF2ey7tVKnlieS3VrLz8utvJrtTOSlRgt3fyFkYLLMyiP0fMf1jIhPEzy0YK/37Hi4lrcA/zy/TM0tPdRkpsswUFnn5+alh6Kc5JkFNajS7NZNdvCmkJLCL8JFHVxcNqFMFvduOsEmxbb8A0NXXN0FWxMHabmvW5YksPQJSXqqXRqoowVy0uJweUd5LWD9bKDc7VOjgBf8VE6en1D6MLghX3K9x/sexceFgrUtuw7qwg71PitYKD2q49qpY+c8CGbFBfFjop6SqckcfeCTJ5ZOZ3KJrccnT66NJuhwDCvHm7iwRIbL5fX8aBqJ7J9vx3TXAuvH1X89Tr7/KTH6qQi9s3PlK753Iw4/BeHKTvj4garkmJgd/ZI4c8G9X2LMuMkeMtLicHp8fHDIivtnkGZWPLzt75g1z3zrysS7Erl8vopnZrIjoOKACIqYgKx+oivHaiJulrCwnj999R1g7WOjg4mTZok/15eXs6tt94q/75o0SIeeeSRr3frxmu8xqjKJjet7kEZiyNUk9PMV/YSEqHgPQN+Pqn7grvnWfnh/MyrPtUKACf+vG9hNpUNHaSZIslKunomafDnjq6X1PFcXZuHebZEIrUaOer7t0P13DXXwraKRmXhLkznZZV4npcSw9+rwEDwdBJidNIWZW9ViwxHBwUIbSmvY/e983nq1ml0eZWx7W8/c5BkVMxut6yZSbtnEFOUlm0HzvH4shzW3azETT116zS8g0P89JZcTjR20eYdwDsYwDsY4LG3Tkku3TMrpzMtOYbc1FhJKBdqtxuscWwqzZGWG8EWCktyk1ldaCE3dSLLC1LJSzNR1+Yh0aAnO8nAwl+W83CJTY45N5fZ+ddPlIVy4S/LQ2wzSqcm0u4ZpMU9IDt38QYt3X1+xZR5GJp7+qlu7aXRPciqwnR23zuf5u5+VhSYefukUyoEXz/qGAGUviFussXz288cWBMMkn+27mYbVQ43Jxq76PQOEBulk/8mulzivEo1RTItWUncuK0ghRvSTKTHG/i8sYtJcQrAHa3g21pmJ86gvSxAPRiord5+iHuKrawtSueDM8oYd21ROgdq2i7rfgV31UQNX1LC3GEkW/TfjzlksPnC3GSaOr0kGpVOngBq2/bZWZCTJMeZwSXGmqLbN7rzE6WOofUR4VKUc+eNk4mMmMCek84Q1/5UUyT3LcomzqDHoAljfoYSl7Tz4zoJ3BKNempF1ztIkLP73vk8ujSb3NRYSqcm8rL6APDmMQfx0Vp+XGyls2+I+Ggt21QRze7jLdJfraGjj/hoLatmmDlQ00bh5Ik0tPfR6h6UKQyrZ6WSbopiusXEBk0E8XoNq2ZC2VkXnoEhSbtwenz8vtLBw+oxfu1gPe7BwJcSND1UmsNLZXZuK0hjwB+4YuzXlWpcMPDNr+sGa3FxcbS2tmKxWBgeHqaysjLEf8zv93+jI6j+WupaGX/jNQKArCY9je5BzAbtZY74V6tVM8y0uAcld+RqCqvgjtuJxi7ZbXrvxIWvpLwSCrZh4EBNG4+9dUp2zwBuSDNx+HwnZqNORiM9WJpDQH19R69PgoHqZjd5aUrigAAuT906jdePKq7zgneSEKMoAX97pF6aztqSjfzLBzWsL87kjc9cpJr0OD0+Lg5fYsdHtdLPqnRqIpPionF5B/hNRSMbSiLYVJrDc34FsBVlxhEbqUWnmSAD5w/aXRRYTHgHAxKoCRB3W0Ead95o5VCdQvIWSskKu4vjTW4eKs2R5PMHVRuUDSU2mZd4X7GVJVOSKEw38cIHZ9myZiY1Ld1sq2gkxxzLKrWzdaCmjYW5yWzZdxazUUdzTz/ppig2lNhCkicqzrroVEFsl3cQY2QEZqMOnSachbnJ2J09UlEqXOCzzUb2VDbxYU0bsZERfFLXSX6aEY0qHAjeX/G9zs1K5HG1GydqNBAT59OWMjuVjV00dPSxLE/hcF3o6gs535q7Fbf+/1CJ9qVTE+ns86OdEMZtBSlXzBIN5q+NTngomZJEOIo1hvhckUjxhJrMIUju7X0+ys64uKPQgj4i/DIRhThHb5sVynkSr/P4h0OOUUKMjpU3WGju7qeyoYN1N9vkvVB0ZTfuOhECmFNMUTR2eCXo2ahmpK7v7pPioedW5qOPmMADKi/P6fGRkRDNb9SHoeTYKFJUs1uhCBWGuqeaPWyraJQADpAj/xb3oKLSPV6nCFIMWvLSTKzefoiNJTbCgPlZcRw6p8RgTVGNkINpAGKbr7e+SmeuxT3AW5UO/IEhPm/uvaJAZbz++uu6wdqiRYt4+umn2bZtG3/4wx8YHh5m0aJF8t9Pnz7N5MmT/wKb+LdTLe4BFv6y/LIxynhdXl/2hlPlcHP/745xky2eT+o6Aejs98lQc7j6iAeUhc4XuMjzH9aOSbC+VkLDi2V2LqE4vNudPfLJ+8OaNkWNWZDK3QsyMeg1LM1NprKhg+buflrd/SHquCqHm999ep6a1l6q3znNAyU2DHqNDHQWodHBYeFbyuz8RjVQzUgycNDu4nC9Ep4uxpybFivu968drGfNbAtDwNDQEBe6+rhzXiYTNApQe+1gPRGacPJSYjhc3yXd0kUM0D+vnsGOj2o5fsFNjctLYbpCtD5U6+LexYoiURDww4AZ6SbJdQJlURIdvouMpEXsvnc+APf/7hg/Xz6V6tZeDHoNa+Zlgrptbxw5z4A/wLqbbbxx5Dyf1HUSH61l9/EWGcotuk7b9yth9Q+X2Jg3OY6MRANvfnZCeuWtnpVK2Zl2SqcmogtTPl9wqsxGHT+YbaGh06sCgIt4BpWhaTCxXBDuD9S08dT3poecD8JqJQxk16XCriRN3GSLB+DVw01E67WXxUgZ9BpSTHqMkRGSIL9iuhmDNuIy4BR8/o6u4ISH1dsP8UCJTRFV+ALcNkOZpMTrNTy9t4YITTjfn22ha8BPs3uA+Ggtg0NDbN6vjF6DP1e839qidNYtyCLVFCnBl9c/zFZ1hFjX5qHAYiLVFMnJpm6ONXXxfnUbF4cv8fyHtTyxPBf3YIC/L7SEpIlowsNp7PDKMasAPW9VOthxsFFy5nyBYSkIWjUzje/mX8Sgj6B0ShIeVeSxocRGn++ikuqgjjQBFk1J5IsLPfzrJwpgO1zfJRXFwpImv8RGpFYjY7OERYjwtPtuvplJcdFSwPN2VauivI03XAbUgu8fLe4BTjZ1X/cD6Fj1Ypkdn39IWpIcru8iWjeBHR/VjnuwfQPrusHaP/3TP7F06VKsVisTJkxgy5YtREdHy3//P//n/7B48eK/yEb+rdRYfJe/xRI39WB+zp9bwaqr3cdb+HGxlXmqE3942OVA7eUyO/ogg0lR6xdlh3ikiRJgcM1sC6vGiMF6sczObhVwCf5NUWaczNqcEyRASDTqJWlaPIH//WyLJCdX2F0kRkewWzX0fEVd+IT1xs61hcQbdPywyCo7FBdBhrQHK/DEfgsAI3hdwqJBADmDfgSoiXHaotxk7p5nZVVhOr5LymL9nYI0/njMQZNbsew41ewhEBgiUhMhQbEYi/X7h3lAfc/FucmYonQ8VJojFZP+wLBMi7htloVdlQ4K0004PT7SJkbxQImN2Egt51y9EqiJyCp/YJgX9il+c0MXhzFGRnC4vouHSmzSy+rexTkMDENcEGdxp16jhJCnm8hKiuG701OltcR0i0mqGL2DATbuOsEjS2ykl9iIgJBYM/E97fn8Au9WKQ72+866QkaHwhPPbNRxCeUBxDsYwOnxkRwbJQHmmkILhlHnovDo2nOiWYkAK7HxeWMX/7x6xpjn/2sH6+kaDBAOLLoCyV0AzHCQYh3xughNuDxG6xZk8ftKB7GREfxK7d6Ozgw9VOvi0aXZvHa0iXRTFKX5KWzZd5aNS6ZIkDJplGVLjcsrs4X9gUsy3ksYJ6+Zlyn3RZyDjyyxkWTUs7XMTmaSgftLcxgGxatO9WB76tZpdKpiGl/gEuvnTWZPZROfN7tZPStVWuQI+oFQiPuHkZ3WwcAw1a29zM+K48cqz9Lp8bF+gZXitCSZdys8Efccc+APDIeMgFNNkWy7qzDEmFqUALdSlKF2woCvBNheKrOztbyOH6tq4vhoLbfPmUSSQT8O1L6hdd1gbfLkyZw5c4bq6moSExNJTQ09gX7xi1+EcNrG66vVOFBTSMWJBj1/OOag0+u77pvL6LHS6BKLj+B6iWM9FlDboi6icLnRZPBCJ55S951VjDF3HXPQ2T8yIhLvLTonl1DGt9b4KDThYZxr7+PRpdkhXYninCSeWTmdz5vcnHH20Oe7yCvldcRowznR2CU7JOGaCCagqAezEqMxRWl5dGk27Z5BHnvrFJsWK0Bt15F6SYq+0NUv/d02LMmR3mxmg5YCi4nA8LD0DQsAN6TFyBEjgNcX4InluXh9AXYfc/D3sy28rIKOCCDeoOWDM4q68q65FvSacOo7+nliRT4a1Sz4lTI7q1TunSDWP7E8l4dUAn3FOaXzKbh1t82y8OaRen5V0cj6BVZ2ri3k47MuZZysCjF2ri2UYMI7OMT6RdloNQo/amOJjRb3IA+X2MhUrUy2AGdd3pCO5R3zJpOVFEOVwx3CmyrOSZJATXw/AAfSJ455vYpzIisphsrz3Yqvmy0Ou7OHbeV1kkAf3B3eVl7HkilJUr27vCCVMOAf1OM01jUgurB17b2sKbRcJmTZW9VC2sQoTjR2ST88s1HHfrXLNxZgg1BjW1HBdIBUUyQPl+bwcpmdDSW2EKsYUAQdL+xTjIYzEqJJNOrZU+lg9/EWJsVG8UBpDhvVcXdwFaab2FBsJUyjpEvcPc/KE8tzcfYOsK2iEWtCDKsK0zHoNWxabJNCFjGOP+Xswd3v50F19C64kAIUBydUhIchO27zJscx2xrHK+VK1Fuq6jd3f4mNVJMez8AQnze5MRt1nGpR8lrjo7Wsmm2RDzk9A35e+OCs5FdGhkOUVsOeyiYSjXqykmLkyH+sc+bouXbWL1AMqUViRF5KDBe6+i577fWUGJn+oNBCR69Pipm+roff8fqvry9liqvRaJgxY+wntyv9fLzG68vUrkoHb352gdKpiTg9Pt475byum4zoqmwBScD9Q6WDnDEMaa8lkxeL1VidteASHSBRRZlxROsmkGrUc0ehhc3760II1gKwtbgHeOytU2xZMxOnZ5DvzlQecoLHIO2eQV5WR3SnnD08VGJDEx7O03trAKX7FrzYZycZcPf7ef7DWp66dRqbFtvYvL+OidFaaSYbr9dwstnN7uMt7DnmYOudszFFKWTrbtWqIJhAD8qCf/uci+w55kALMhNzQU4Sm/fXUV7TxvysOO6aa5E+WN7BISXtQDUYLcqMo6PXx72LcyRnr9c3xILsRN5TcxN7BwO0uAd47Uij9K9bW6SIFFJNkUxOiGFFgRlb4oiw4z51ZLV+wYjhbpfXz4vldXx35iTW3ayMqO6YN5kW9wB/qmpmRvpEOU5brh67ZLWzJlSbOk04PQOpIQAkKynmsoeBsRZdYU8BCsjfdc98TjZ1q+PaGO68sZespBipUA3OYRXfvfiMh0eBpgq7i6omd4hSb1Vh+pg8V8HxykuJYUluMu9WOSVotCbEfKWsyNGZo2OBOhg53weG4XB9F9PTYpiXmSgjo4K3b+faQmIjlQeF4pwk2j2DfNqoeKA1uQd5WOWh2RIVoLansonN+2rJSIgmo6qFVYXpuPv9PPu+nbyUGE42u8lzjFh8vKQCtQ3FVmKjdHIbKuyKHYhBN5JhOsxIhu5DJTZmpJtY96piE3O6TelyTTXH4L84TFyUji3ldYShWI58cFoxR/64rp28NBNRWg07PmkY+Z5mmFkzL3PMc+a1g/U8/2Etd821KA9eCVHklNgu66Z+2RKALdUUOZ4N+i2o6wZrTz311HW97sknn/zKGzNef7v1xpHzLMxNZk2hhbaefkn4bWjvY/O+2quqn6ocbp585zQbS2zUuLx83tjF5n1KyLng/lzPKCF4MbrSQhRcc7MSpY3DtvJaSqcqgoDnP6xl973zr+iBJMbdZadaKTvTzjSzg1iVFySezIPBaUqQOagIjRbdoRnpE7mEAu7EonPHvMm8ceQ8T906jUlxShzWnpNO7p6bTs/AkAxcB2X09JsKheMjFq51N9ukWe3yglRmpE9kfmYCF7r6WD0rlQVqxNPue+dTrna48lJimJ6qdN/iDTpWz0qVBqPFWQlyLFhe08aGEltIJNTFYcUqQChGV84wo4+IYLpFEU/svnc+3sEAg0MXmWdLZOfHdRRmJCgjuKD32rZvhIN2ztVLqilSHosOr58t5XU43AMyO3PHR7UhgOhAjZIXvPt4C5ERE2Q3pMU9wJpfH1JsIbr6mBQXzVmX9zIwtbeqhV3HFMuPwcAl+V2PHnst/GW57NqCAmoiw2HfWZfcl9HAcHOZHU+/j3PtfVBmDwFs4rrYovLf9Jow4g066UV3W0EKeSkxFKsWN4L7J0oAx6uV8FCrbHJfky+6t6pFGhcDsvMWbNfxdlWz2jnqZ907lXIEK1TE8dER/EMQnSBSqyxV7n4FyC/LSyZtYhR7q1pYd7ONbLORmpYeSVGQ5spBHSaxPW8cOc+uSgffmZaM16fwDEV3WIwwU016dlQoghxf4BLmGB1JBh07Dyn8NZEvurW8jmhNmFStCtBd3exm/U0ZdA8GqHH2KDw4lVc5usR1O9MaR0ac0on8c7hq4/XtrOsGa2+99dYV/y0sLIyzZ88yODg4DtbG60vXG0fOs+3AOZ585zQHflbCnTdOBmBGmokfzs8MGVleqe4rtvJ79anYbNQRH62V/mtpsVHX3AahQLy/xMbiq5jrQui4dcuamaRNjKJ0areMVTpl1HGiseuKC+DeKmUU8/TeGjYEEZLXL7BKT7GFucn4AsM8+c5pnluZH8Jp2fFJA8+tzGdG+kQZYVOUGYcvcJH1i7Jll/HRpdmSDP/DIiumKC1z0ieSY45loRpzJRZuu7NHZjaKsZHwvTrn6uWZvWeIj9by3Xwz1c1udlU6WIPy9K5BAZSiK7b1ztl4BwP0TB2SAAsUD7jq1l46+/yEAzHacF7YVyeTGwosJpnVuW6+ldhILc+tzOejsy5eLq/jieW5/KmqWQ29h+dW5oeAWjFyNug07Kio50STW2aiFmXGsbHExupR41cAb+ASm0pzWJibLKPIFuYkyXOu7FQrK6abefcLJ03uAZrcA7z52QUuQQhXbXlBKhe6+hgMXGJmuok3jpxnUlwUL3xwFlDGpwKov31cEVMcalD4UvcWKzmsfYN+ppmNSudVfc8X1e9DPAwEuLxEBNj6BVbqO30MXlDsbcQxitRqWJibzNK8tJBzW6g7/cOQaNBKccboqmxyS7NbuLLAZ29VC29XNfPrj8+x7a7CMV+3q9JB2Zl2flxsZVJcVIhqVoygBVAW7ykeTsS2FWYkSI85cZwEGBT7JM4JAdg2lykRWCKV47efOchPM7Jtn10+nD1YmoNBE4Z3MMDh+i42lNgw6jV8qvLa1hal8+4XSpcyXq9hbVE63505iZNN3WiAngG/vP6eunUaPyi0sOH1NsxG3VXTAARg+yodsL1VLdS5vFzk8m7seH176rrB2ueffz7mz0+cOMH//J//k1OnTrF+/fqvbcPG62+nnCr5d0PJSOh1QsyU6+LvtbgH+JcPapQba7EVNBH4/UMUTJpIu2eQjUFGsmPVawfrMeg1+ALDbCi2srW8jqHAkFQuji6xcDzk8tLmHaSxs595k+NInxhFUWYcbX1DrJptGVN5F/z7G0ps5KXEsE3lyQwOXWTHQQV0Od19bHi9EoCnbp3GqsJ0tpbZFaWamskpxoM3Ziai0UQQpQnjvVNO5mYpsUpOr5+5WYncM+jnP0466fEP8+z7p3hIdWGP1YbzYIlNjouEZ1hCjA67s0cxtK1oZM28TC509fOD2RZeLq9jaW4yPf1K8LR3cIgqh5u6Ti9hYcjxpfBzSjTqmRHE6xJq2hbPoBRL9PmHJTl958dKgLxwye8Z8PNhTRtlZ9p5sEThKO2tUlIFss1G1r1aKcPchSVBRqISdg/KCE6oAg/UtIWAHDFe8gYuhRj3HvhZCR29PiobOijOSWJPZRNlZxXl7OpZqXx0tp38NKN0sxfg5QGVb/fa0SZ+MNvCns8vUHm+m1WzLRgjI6hqCuXB3btY6SQealAyK7er49zv5CtgSqiDYcTUWRgl32CNu6zztrE0RypnxTatmm2RYFZwzs65lHGe6GS39g5y+5xJtPT0U6kCEuAywKYLU7iRpVOVlIgrVY3LK61OrnT9CgA3musmRDqblmTj7BmUnelgHh8oth/VzW4lp1b9uQAssXrNmAa+4gGkKDOOosw4PANDLMtLxt7mJSNRsdWICFeOi0jG2LTYJg2CH12ajWdgiGSDjvw0I2Vn2jFGuvj+jFRONnVzoNbF7uMtmI06nlk5PSQCbdtdhfJ7H12vlNlDhClfpsRY/MUgnhuMALaXy+zXNSEYr29GfeUg94aGBp544gl27drFqlWrqK6uJjt7XGUyXl++xM170xijnWtVqimSf149QyoFi3OSrmmhIeq1g/XUdnhp7OyXqsfVs1L5pE7hzGg1l/tHLS9IZVO7l/Y+H29+doEfF1vZvL+OB0psHK7vIi8lht3HW64YyZM2MYq1RelsU0OiCydP5NXDTZiNOiX+aoJi8nv7nEm8+dkF8tKU97i/NIfNZXZKpyZyrr2PxbnK4ibGhAftLqpbezlod8lA63Dglrw0JmiUiKLnVubj7vdz+5xJ9PmHeVl9zQOlOZxo7JJ8uNsK0ni7qpmdawtlgsCGEhulUxNlB21jiY3vzpzEL98/I7MshYlooZrXKDhJuyod8rtdvyibl8rsFFiUztPvjznkSEkAjU1LsmVMT9mZdskzEkDXbNSRYNBKqxKRwSrOoQF/gC9aeoiL0lHfqRimCvK26BYK0n6Le4ADNW2y65FqipTdO1A6OIfrT0nuoNPjIz8N+frgzlqiUU9+mpH9anwVjHCgblC7loBUORdYTPz0llyau/uZkmgIGR0uL0hla9C4UxoLayJk3mswgBE+dBtKbPj9Q7z7hRNPvy9ktC+6x2I8usHrl/zQsjPt3FNsJdWkJ9tslGHzooK7lld6EAEwG7Ssm2/FbNCG/FyoNcX2ju64tbgHqGzoICMhmg9r2ujzXZTAUQA2UFTVW9VrR0TBifNi9axUtpS3hGwvKABszzGlK9jQ0cea2RY+bexidnocs9PjWF6QKkURjyxRTJh1mnBWFaaTkWigod3L3KxEOWLdvt8ut0+YPgOkxUYxMwiAvnHkPDpN+BUpHC+X2dmnjt6vF7C9drCe0vwUzrl6eeGDs+SmxJCXEiNjsxarEWvB7z0O2L4d9aXBWkdHB7/4xS/4zW9+w4IFCzh06BBz5sz5S2zbePG3Y5L75xg1CuNMUdc7SugcDCiAKCVGUXo1eyicPJHOPj95KTEUZiSM+XsRE8J4/ahDdoDiVff6iXoNiUY9aROjrrgNBRbFpX/1rFTpxm826vi7fCWrcM9JJ2uL0ml2D/DUrdNC3qcw3cSeYw42LMyiOCeJbfvsPL4sh31nXRSmm9i0WInU2fmxAh4fKs1ha5mdA2pIuQBEjy7Nxhu4hNmoY0h972DezOrth9iyZqaMYxK/V5QZxx9PKovhlvI6orXhrLphEoNDF8lKMrDrmIO2viHWvVpJXkqMfI/g0dnLqsAgHEgz6YmP1irZi+r7A5KflGqKZEOJjV3HHMxIN4XknIpEA7/qI2U26ojVhlPlcLOqMJ156nVTYXdhjtGx46BiMSEC5Xd8VMvF4UvcuziHbXcVhlxj3ylI4+LwJQnUxZjulTI7S3OT5eIbfM61uAckQb7ZPcg+1ZQ3AhhiRO1Z1+bhsbdO0eQe5JL6nY7FT9paZufNYw78jFwbwVYawUBN/NsjS2y8sE/57m+fbaFgVOcqODwd4L1TTrnQr56VytBFha9niY3iRbXbOBZgE/ubaopkc5kdDSOAQHAEg9WjW8sULuG6+Yo32ej9FcIOoVaNj1aAXl5KDEPDocdFdI2Sg+xWFBpCIruPt/CQ2oEN3oa8NBMbFmaRl2aSDyXiO33tYD1vHDkvu+j3LlYeCoQKs7HDy+b9dXzR2sN9C7Opcrj57WfKg0FRZhx7jjnIHUPEJEahpVMTOdfRyz+OEhe0uAfo9yspB6VqeP21SliW1HZ4mWY20tnnl56Rgmt3y1TFliaAkve68Drfe7z++uu6wVpfXx//8i//wv/+3/8bm83GO++8wy233PKX3La/+Ro3yf3LllgEI8MV7tBUcwwur4/bZpj5TUUjH511jQm6gqOBdn5cJxf1uxdkUmF3ceCsi+bu/stu4C+X2Vk4JUlyiGpaewlX/+0/TzlZf1MGGxZmMRQYZnZ6HBt3ncAUpZXu9cLSQwA1YZHh9Pi4r9jK1NSJ0iH98WU5bNtn56iqrFs33yo7L++dUpRr9xZb0aBwfDISDXLMaDbqqHF5pc/VigIzt8+ZRIfXR9HkeAx6jVTgbVkzk6LJ8Vzo6uOHRVaefd/OI0ts3DbLwsmmbnauLeRQXTt7jilh52JRF5y5H91klaadADfbEkf4gGV2Pm/sonDyRCqb3GQlxYT8m+BxrS1Kl0aqo5MDvnC4+R/zM4mL0mLQR8hAeHEMADmSLD/rIkoThnvQT2ffkAQkBRYTW1WV58NjjPeEAGHVbIsExsEZnG8cOS+3qcBiosk9yO5jDv4u38yezy8AhIAqULzfROB78Lkqqtbl5WyZPYSjdO/inDG7wcElPmduViIV5zq5IS0GY2QEu4+3sHpWKnfNtVDX6eXRpdlX7KAJIDJ6FBwM2ILr/tIc/KCefxFShStqV6WDd6uclE5NZHJclDwfcsyxY3aFRvOyCiwmbrYlcrMtUYJFwf0UqQK7751PQoyOPSeaQ4Da03trZDauAGrP7D0j7VwEiJufPdIp33rnbHoG/JxocnPHnHSWF6ReloJiitIqdiLNHsrOtKMZJS5INUWSYozk9jmTiB/VhbxSCRpBvEFHoqo4f6PSQUZCNAZNGD9fPvWyzuV4WsG3p64brGVlZdHb28uDDz7IHXfcQVhYGFVVVZe9rqCg4GvdwL/lGjfJvXp9HdEp4vdjVQ6PKJ0m4jKH8WB/MAHUxLhs3c02KuwuPjjt5IsLPWwprwvpfgjvts8au/jpLbksL0jFoNew7tVK7iu28nFdFxlJBmm2umXNTLasmUnVhW7+9RPFUV0ANoAFOUn0Dw0RF6Wjp9+n5hsOkRYbxePLcijMSOCtzx0cru+SYdarZ6Vid/bQ2edn3XwrdR39TDPHsnn/yILr7vdTOjWJPWpG5FO3TsPp9Uv7gx2fNJCREM28yXFsWTOTWpeX/SpAyUuJkd0d4XG2Zc1MorURbL1ztuTGBVAW2J1rC1n3aqUMiX+3yskTK/Ll8b4EcrTcqW6DuB5uSDexfoGVhs5+Xj3cxKbFNp7/sJbHl+VQftZFQoyOPx5zSKK5OVbP5n21OL1++Z1/Z1oyw5eUEeIfjjXJLqvYl7JTrRKwiHHkykILr5TZyRrVTVk1wyxHnmuLFC8wGBHPrJptkYv94ilJbC2v42iDAqR/tmwqoIA+8ZkC8Di9fnLVqCJRQkwgvrNg8CKA2pYy+5hRRi3uAUkZEGPGrMRoGjr6qGntpXDyRN6tcpK92MCeyqbLRnh7Kpt48p3TEshvKLGFdNbE+4/2fBsNHoLHs8EctthILelx0XIMeT21t6pFse1ZMxMYAYsD/kCI2e/mMjvVrb00d/fTM+CX322w4e/yglQG/AFOOz3SUidvUmh+sPj/KwkaxPu0uvspSFMiwfYccxCrDQXSozuA16oKu4v3TimxV9WtvTx16zR+WGTlo9oO3jvlvEzAMA7Uvl113WDN5VIMDJ9//nl++ctfhuSAhoWFcenSJcLCwrh48eLXv5V/wzUO1MYuqVhk7JvSlx0fj75hjl7oXi6z8/tjDtq8g9y3KJtUU+RlnmSxkVq54G8osYUs5sEdpeCbvXjin6OmKVTYXdIHTASXry1KJ1e1xRD79n51s5rVaWPNvEw0mgjqO71sKa/jIVU4cPRcO48uzaYvcInSqYlSZfsvH9SQHKNjQbbymRPCICPRwIA/wJPvnObxZTk4PT4i1ONS5XArjvCqFQfA5v0jPLO1Rekszk2WzvgDw5BtVkLiG9q97DrmIDxM2fYPqpv5tRrnYzXp2X3vfFZvP8TOtYX8bNlU+Z3t+KhWmpQODl2kz3dRdkBAsSqJjIigz3dRkrknRmslsCxXjV+b3P18f7ZiDLpoSiLbyuskuAheZKeZjZROTcRs1DN9UiwZcVFyMW9xD/D2cQeZSQaefvcUZWfaubfYSr3Ly/2lOaSaIslNnUhhj4/0eAPWIGf+vDQT8dFa7M4e+XAhAETFWZccwe6tauFQfQcfnW3H6wuwYUlOCB8rGPiLc3OYUKBW5XBz9Fw7/YFLHGvsugywtbgH+N2Ren6tnjdP3TqNbQfOSfHE7uMtdPb5WVuUzub9ylj6tNMj46JgJEh+VWE6pfkpIdfYjo9q6Rn0K9+vyg08UNNGXpoCdoKB2rpXK0NGstdLY6hyuOkZ8BMbqaXirIviUUbC4jUD/kDIg9RLKq+xKDOOY01d2Nu8QOiYV3w/82yJPPbWKdYtyJLbGiwYGF1jCRrE5+6taiHJEElgeHjMjuf1ArUW9wC/+1RRW+enGVmYm8yuSgeP3DJFxl2Zoq6vQzde38y6brDW0NBw7ReN13j9F9WaQgt+/9CYcvgKu4uDte0SjPy51eIekLYgH51tJyMu6jKgBiORPUINObrGGukkxCjdkaykmJBFbOfHdZep5oKVY2+fdEqwVJhuYuGUJBKatWTFG2SE0/Mf1kolZHVrL7MmmchNjeWfV8+Q/mGgdOkE4f+5lfnYko38uNjHS+V1MorrRGOX5Ojd/7tjsoO2abGNiAlhzM1KJCFGx8sqR25beR1P3ToNc6wSEG+O1VNgMVHZ0MG9xQoBXaQs5KXEUNPSQ01LD+sXKbyg5z+slRmKoqsn+GbCtV6oEyfFKdYsIu6nKDOOVJOehBgdG5dM4UhduwQZSQa9/B42LMkhcEnZ//t/d4y756Zzuq2Xd6ucbFpsk9+9AGhmo45FUxKlzcY9xVY5BhedlB7/sLQqEefEd/PNPP9hLaeaPQASsAlQ8nKZnc8au7DGR+H0+JTRVqLSuRsNRET9/ajOVXB38J5iqyS/B4ttUk2RMuM1DAUoTIqL4kJXP+1eP6VTE5lqjuXlIHVhfmoMJ5u6Qz5rVWE6Oz+uI8UUJX++8+M6XjvaJDuLTT0+3j7u4LefKddN8Gh6NHcuuF4qs49pZD16H++aa+Fcex8d/T6au/sx6JW0AIDH3jrFzrWFbFpsk7zTMJSszzc/u8ANaUqm7fdnhPrYjVYFC2X6o0uzOe30sPPjOgb8w6wcdezFuQSXp6h8XX5pR+raaXUPkpEQTat7kASDjs4+P7VOD+tutmGK0o57s33L67rB2quvvspPf/pToqKu7Vk1XuP1dVfwCBKUhed/zL/cEbzK4eaFD85S3dqLZgLSHX10VdhdnGxyXzbOGqtSTZFsvXM2//JBDcVZ8VflBAUvwqACvUpHSAdEdP1a3AO8+kk9/ovDuAeGWHXDJJ5bmU9NS4/0AItXsyqDnfGzkgzsumc+B2ra2LRYyccUvJyeAX9IUHO/P0B1ay/rF1g5fsHNa0ebeGbldHZVOiAwhNkUzZPvnOahEhsvqQDr6Ll2luWlER0RwYYlOSH2FbowcHp8WBMM0nR33auVmI82kZ9mJMccS0ZiNN/NH8kpferWabS4B9lT2cSz7ysRRQtzk3l0cEiOdcRCD8q496lbp8nRljC+PVDTJo1TARrdg2wrr2NilI7inJEOy1mXV8Y0iZQJd7+fdTfbqG52y+9hx0e1vFxeh5gFvHa0iVsLzGwoscnFN9UUyc22RPp8F1mUncB3CtJ4q9LBPcVWYvVaeS7sqWzC3e/jV0FdJXFurl+UjU4zgc7BwGUgfts+RbVX3arEGJmNOgonTyRt4sh9Vpyfe6taOOdSOkKDgSHuDPqMngFF2flwiQ0/I+T3pk4vP5yfGQLYwoCt6rkUfF4Kc9xEg5ZtB85RlBnHO1VOirJGwCcgx/9iDLu8IFUeh4vDl6g410m8QcsL+5TOqDXecNk1eCWg9krQeHf0dbnvrIs3P7tAUWYcnze5qW7tJT81hjc+ayLeoKWhvY/q1l42Lbbxu08bKTvTzpHzXRRa43i5vI77S2wy9WJjiS1kzDp6TJtqiuS1g/VkJBk419lHz8AQH51tp3DyRH71US0/mJ1+2T69drCeNu/AmNv+59aqwnSa3YPyoTE3JYabbPE8+76dHv8whemma77HeH2z67rB2i9+8QvuvffecbA2Xv/lJawZen1DrL0pMwSwja4Ci4mnvjedfWddIfYZwaHwwQHb6+ZbJYH/alVgMcmO1Fi1tczOykJLiFu9AGM7DyljPxGds/CX5Ty3Mp9G9yBHG7qkSACgob0PY2QEjy7NDomXmpFu4qESG1mqbcMjS2z89jMH8dFa9BHhEqiJAHhf4BIPlOawfb+yqEZHRLA0N5myM+1UNrklv+r2OZPYoAK1FQVmuvv8bN5fx6Mo3QKhrgQotMZhjlV80ISFxvqbMtiyZiZvVzWTkxAlfeB8gUvsXFtIVlKM3Kb7S2z8uHjEQqMwM5EJ4WHStBaUxV6ABlOUYtIaHNIOSkcoUqvB7x/igRIbvsCQ/H7d/X62lteRbNBiitJy/IIbp8fH21WtXBy+JEEwIDuPonO3raKRUy29ksslFu475k2WHKo9lU28qILa4LHTqsJ03jhyPqQDWGF38XmTm78vHPHdG20r8/3ZFtr7fHw330xf4BKXAkPsOelk1Q3+kPMrOD5KhNJPCCKtB3erRBLEDda4MS1kBEAbTdQXZHrRcctKihkzdFwAsxRTFMsLUiXvat3NNrbvt3O4vouHS2w8ssRGr3+IreroedUYHangEua1V+qsiX0NA3Yfc1A6NZFWj4+Gjj7yUmLQacLJTYlh837lXBaj3eKseH5cbMWoDadwShoxem3I9S4enoKBtBAfPL4sh93HWyjKjCM+Wkvl+W7io7U0dtaE3A8q7C6a3P28X92GRnO5iOLrqNWFFnyBIcKBX1U0kpcSw49usspO9pW6leP17ajrBmvBHLXxGq//qhJAzenxsSD7ypFTwRXc3WpxD/DvlQ7+oPpwrSpMlze09HiDfO/R+aNVDrccUZ5s6mZ5Qepl/BxxwxfWBB1qgLtQbKaaIll7UyaRugi5MKaaIhWg1tGrhKsXWxm8qKhBK893s/6mDJ7eW8NPb8kF4PFlOXQOBtjx1hfyfbegmI86PT5WzbaE5HiKgOmXyutINenlqHLDEgUoPlxi42hjFzfZ4onVR+C/OCx5ZxeHLzHdYuLRpdmsX5TNtn12BoYUcw/vYICXVUD3bpUygo1XI7IeWWKj7Ew7rSkxrJ6VijFKx0vlSjJBcU4SP18+lTqXlwdLFVsRs1FHvCFSesRtWRNFQ7uX+RkKYHthn9L1STLq+ePJFryDgZAorQq7i2NNXbx6uIkNJTbePukkI6EXW7KRvDTFwmRSXBTHm9yUnWlnbVE608xGNQQ8Qok1+/UhSqcmckCNv8pNMnBvMWxXv5Nt5XUhJPlG96A8f0CxFwnmkolxaEuQZch7X7Sw+3gL+2vaWJSbzOKg1IiEGB17Kh1kJRlYf/OIwrTFPUBhZiLrXq3kwRIbG1WAL7qGdS4v+2raWDffii4s9LwX5sDbyutCxo5j1bWc7oMNfMcqcc6NBtHWBANFmXGK+nOfYhOzQQ1E33nwXAj/bXTtrWqRgO1KFRmunB/CAFuoUd/9wsmyPCU+qigzjnernNw+ZxJ5KTH4A5eI0UbIbQ6+NwBjbpdQXhZmJLBuvg+X14dnYEj12TOyNDc55PXCtuXVw00smXJ9gOmlMrs0h76e2lXp4NeqB+Ndcy183uTmcH2XtOUZB2rf7vpSPmthYWHXftF4jdfXWGMFXV9vtbgH2PFxHa8fdYSQ0wGZVRgGpAcRwmHESR0Uld+2isYQ3lBwVNH6Rdkh1gQ/uskaEtSdaoq8bGFcVZjO3qoWNpQoZrXCu2zDwqwQVdvq7YdUk95OnB6fDCtvdffL5AOxMFTYXdS5vJIf9dSt0+j0KtFbH5xpY0GOAhTMRh2rZ1s46+whPjqCnYcU0rUw5nV6BrlvYTY7PqqVKtFwdVEsnZpIVrxBctcKLCZmWuPoGfDz+LIc2QnMS4nh0aXZFGYkUGF38euPzwGKuKLfP8zPl08lTU18ACXfNDjpAJQuz5Yyu+xyJRr19PT7pVlrg8tL6dRE+gaVruRNtnh6BvzSCmPzfqXT8ECJTS6Ie6tauGPeZLbvt6tAN5bbCtJYXpDKnsomtlc08viyHL5TkBYyxhzNZxLnijgngs8HAQiKc5KodXrkSG+rGvotgNqvPqqVhrQD/oB8T5EluqHYysvldQwDZ509PLEiX55/M9NN7Pn8AjsPNTKsPkM/oJomC3uW0dfKljI7k0x6GY4efI0cqWtnni0xxLx4rBIdu54BvwQGgiAf7Hl2gzVObsfptl4Ghy5K3mS0XjvmZ2xWuY5w+QjxxSCLkttmWegZVLqPTo+P1bNSqWntJcWk59XDTRRlxtHQ0ceGYit7TjopnZrEKWcPZWfaQ+w3RId7Q4mNyvPdTNQ7QvJWBW9yS1w0PYNDVJ7vll6Ifb6LJBr1l+3DqsJ0bMlGaeh8tQdLMfJ19/uoa/PI3wt+CBxd4rgJU+R1863sPKR02AgMfSll6Xh98+pLgbWcnJxrAraurq4/a4PGa7xG11eRoIscwLIzLvJSYliam8xjb53CFxgOuaGN1WEosJhYNdvCtvI6Pm/upSgzjnbPoPz3YJ+10du4ptDC28cdsjt0pXzQ5QWpclQyz5Yox015aSYOnHWxvCCV3ffO50RjF77AMAadRhLl191swx8YlpYCFXaX5OmZjTqZB7m3qoWMhGi+PyOVAotJZlK+sG9Eybl6VioJ0RHEG7TckGbi6b013HmjlfWLFOPcPcccGDRhPHXrNKmwK52aKLs3PQN+1r1ayePLcrh7QSaJRj0GvUby6HauLeSGdBOvH3Xw1ucOXj/q4KESGwa9hsP1Xew/65Kjv133zJdRTC+W2WWQd3aSgQ/OKJ1HMS4uzU8h0ajH3e+XMU37zrqoPN8NIDsNxTlJ7K1qYZ+a6rAl6DsRf7a4B0JUjsG1p7JJjkk/b+wKEXksL0ilwu7i+AU3a4vSGfCHOrgK4rezZ5CFuckhXaMfzE4nTj+BPSedlJ1plxYZVQ43B2vb+U/VsNbZ00/ZmXaW5irfvcjOjI1UxCTVKhAJPgdHXy9byuz84ZiDm2zx7D6uPBiIkbwQT6wtSufVw00hvy+6y3885lDyVj9pUDzvzneHeHqJ60k85Dg9PjaU2LA7ezjV7JF/X5ibfEWgJvI6B/yhyacisUBss+CqxkVpiTfo2LyvllsLzOw42MjqWam0uAfltRvsA7dzbWEIgE01RXJ/iY3dame9ZJR5bLDlR43LS37aEDsPNfJQiY0Zo8yGR/+eoD8EUzZGV8mUJPyBITr7hjjt9PBhTRvTU2KlOvlagG2nXkNWUgwzLROpcXnl/o7Xt7e+FFj7xS9+QWxs7LVfOF7jdR21ucz+lTpm1/O+n6s5h2Jcd/eCTOIMWvZWO0O8tq5U4t89/T5SjfrLDELHupmK3xkNBq6V0Se6KYAMLR9G4fAUWExwsJ49J5q5T/3M1w7W88K+kS6eWDhONLmxJRmYkT6RKodbLqbiTwGEBoaRN3ezQcvC3GT+eMzB3QsyyUgycFLNsdxUmkMYEG/Q8dhbp3jq1mlKtuLkeO5bmE1zdz81Li9FmXE8+76dSK2GbQfOER+t5Z6bs2Q3s+yMS4oE4qJ0PKBGJ62elYqzp5/dx1tCsiTFAv1RTZu0tkibGMWURBfDlxSgFmwW3eIe4GRTt1yYxWIt/Mk+Pd8pEyfEsbh3sQJW/lDpYFgVBAigtqeySWaOripMxzsY4PNmZeQUrZsgu3uC13TXXAvvV7eRkRBN2ChzVF9gmEuXlNgpXZjCURNGuwkxOtBEhIxbCywmmrv7OdrQhTEygqz4aAm+qxxuVm8/xMMlNu5Xz429VS3kmWMlgBzrvL6IIgqpUcdl4gHlZFM3ZWfaebjExspCS0jXq8rh5sn/+AIAY2QE0boJOD0+Gtr7WDQlkUP1HZd1QwssJrbeOZvqZjcur5+yM+2sm2/ljLP3qte5+Mx4veYysDwWv074HO6tapFd2ulpE/n1x+cUMU1xJnfNtbCm0EJhuikkFF7U3qoWtqoA8e/yzcwag6AvtlcDMu/0emKhdlU62HmoEb0uYszvo8U9wJP/8QXTJ8Wy+3gLKwrMimVMEAXhWhU8pp7hHlBELVcJih+vb359KbB2++23k5Q0Phcfrz+/5GgpoHCivk7AtkkdCQXn9gHS4uFq/myj3+daOaNVDveYVh3BQG1LeR0BuMwoVFSF3cXP3/pipCNQbOWV8jpmqU/wM61xPL23ho5eH0fq2nl6bw2lUxP5108aiYsaIUtPCINTLd3Sr2vrnbNZXpCqhK23eZhnSxzJwVRv7h29Pt47cYHN++uImBDGYOASW9TjE6UNZ2u5wnl7YnkupigtDR19PF1fI607xMj2RmucDJDfVl7HsaYunvredKqb3dLxvaPXR79fSQZQjulkPj6rADlx/N44cl4uzELRKfyvmrv7eeOzJgw6DWajLiQPNtUUySMdXs539xMZDs+tzJfkdwHURsdD/fZIPS09PqUbp5L1hS3I2qJ0GlxeZlrjuHtBJjMdbmkjcueNVqmQVSwuXJI/GAzUdn5cx9tVraSYlJGZ/xJseL1SAtDRpHZA5oGmTYySYeWimrv7+XGxlRfL65gQHpqZGbxfo88x8RnbyutYHNRBWl6QyhOeQXZ80kBBuumybRFCBjGKF4bBnX1+Fk1J5I/HHJd5i41WQ0dpwvjpLblXvYZeUXmpq2aYx7zexup+S/+5NTPlZwoFbYFlBKBdqbPl7lci5Rba4vi8uZe1N10571Q8aF1vxua10gNSTZEsyU1mS3mdtIEpnZrIFw73ZcfzeirVFBkyth+vb2ddN1gb56uN19dVAqitKDCTmzrxa++swdg3yuKcJBpcXlJN+stc4a9UV9q2FvcA51y9VNa3s+ek84qfubrQQgAkMF2Sl3bZe55schMfrZW8MGE++8IHZ8lKiqHAYpJGt4BUuT1cYmP9omyZnCBsDRo6lFzDngE/eyqbqO/o5T9OOnGq3mTewSEitRGcbOrmmb1n2HrnbB5FiSBavf0QD6odhDeOnGfTYhtvVCrijA0Ls9iwMIuTzW461MVuRvpEWt39PPu+HU04kkO355iDVKOeZ9+3y+BwsdhrtRGXeY1t328nVvVJg5EFOpgvFqsNp6Gjj0D2MKtmW9hzzCFVcN7BAIcaumjo6GO3p4W8lBhp1wEjozoRC9TR65NAzenxya5Ep9cn46sA8s93ct/CbLmthUEjMF9gmO4+odr0EK8fuZ1WOdxS5drqHsTp8XFcjf7aXemQC78AJ9v22fGpHThAds7E9lY53Pz643Myt9Y3KjNT2Ez87tNG8syxRAW55YuQ99KpiUwyhXKtPIMBnB6f7KYGV0NHH/cUW/l1RaPkhuWlxJCbEkNjZ7/s9F6priUWENu965iD/DQj2yoa0Woirut+MJb/3Ogx59VqYW4yF9x9ishnjAix0fVlw9Cv9iC4bZ/yALexxMYW9T6YGqtj8/46JkZrvxLvbByofftrXA06Xv/lFfykv+qGSV/690cbT36ZEvmXwd5VNS4vurDLHcjHKhGnIzoBnzf34vT42HPs8ogdQWLOU1WSe0466QtcIiFGJ1+3bZ/in7axxMb8rDh2HGxk/QIrlonR0tFfvCZcbuNkvjs9VS6uxTlJfOFwU5QZJ20TCtJNrHu1UoK3VbMtkk8njF9vnzMJp8fHvrMu4vUayTFb92olJlXp+dSt09i0JJvXjjTy5DuneerWafgCw+w+3sSDJTbePu7g4jCYjTravD5Wbz/EpsU2nB4fpiitBJQ6zQT2nGjmRzdZL+tsbt9v54V9dTyyxCa5cXurWkibGEVTp5f1C6xSsQrw7Pt28lJiiI/W8vezLSEg45zLS5Q2HK9/mLerWtGEh8sR9ktldv79mAPfJeWzb5lqpqG9j2dWTpcpAsLOw+nxUZQZR445NgQEVF9wS6HHk++c5uESG7nmWE41e+gcHOFbCc7T0XPteAOXWJibjBaYY41jgvrcK8aaD5TYeEXtqDo9PuLUrMjRMUaP3DKFHRX1zLLGhQAhMY5dW5SO2ajnpfI6Kd5Yd7NNbktdm+eyMeMDpTkMqX8GV3N3P06Pj3Md/eSlxMjA8L/LN0tS+zlX75cGCUKkII5pML0g3xwbQvIPrq1ldiKDAGiw6OCrVKopknmZiUo2bnkdkeFX5pd+3SXuMwtykuj3D/GvnyhgeEOxlW0HzsnEh/Ear+C6brA2PDx87ReN13hdZ20qzQnpUlyrXiyzcwnQguJz1e//ysqnYKAmLCCEau9qgK3FPcCuI/Vsq1AioEQHzGzUyQU/uN4+7uDAz0oA6Oj1MSk2ilWFFt6qHFGeic+LmBDG6sJMbIkxUhkmKvjmLjoxe6taQrJRNyzJ4VKZne/PSB1RK66ZKb25RMdLgKLsxTYZKSTsS55Yniv9uiqbVE6Zyu/zBYbZVelApwmn8nw395fYqFR5gY8ssXH7bAsTwpERRo8uzcYXGObF8jr8KN93olHPWZcXs1FHBCMju7xJJjYUW5mfnURlQ4fsSN0xJ30kwaDEhtWkJ0oTRm1Hv+QQTdRr5OgQFNCx8+M6/qDu06qZyjHcU9lEeU0bTo8PT79PWm2kTYySxzq4WzMBhesV3CERFi0nW3q4b2E2KwrMvKiOicUIm6DfKbCYpLBhg8ozCwZg0y0mnluZz+Z9tYr/nNrB2nbgHDpNeEiMkdheMd4TauMqh5sITTilUxN59XATeSkxMn3gn1fPkNteYDHRMxDq3QZXjm1bXpDKo119PP9hLfcUW6lqVvznEqK1PL4sh2yz8UtbRVQ53PzLBzVMT4sJUZSOFRj/2sF6Eo16BvwBWt2DvKl+nwAe//CYpr5j7ZvZcOVOVWWTW3bWvipQ+7KxdqJEt/TdL5zcNddC2RkXq2ZbcHqURIZxsDZeo+tLcdbGa7y+zvoyQG33McUAtrq1l9WzUnnyndN/9hPo8oJUalxeNpTY0IWBQXf55SDMbgX/Zc28TNBEcKCmjQdLbFxEMbKtdXpC9kd0iwBp4VFgMckFH0bCwSMmhIVYgQS/h1hEFuQkSTXlo0uz8Qz62a5mbG4qzWFvVQsvlo9wyISdxO575wPIBeCJ5bns+KSBVbMtmI06bkiLYX1xJpVNbkrzU6hyuFn3aiW3z5nEJ3WdbFhokmHkTo+PZnWkpw2D789IZa41DmuCQY5CH1QVaQZ9RAiHLQKFA/dwaY40SF34y3J2ri3kSH07v6lo5CIwNzORR5bY+NNpZQwpgM4a9fWPL8shIx4eLrERo1cUik6PjwDwSnkdz6mKVdFZ6lW7XZFaDUtyk1mYmxwSqF1gMV2m8ITQbNgKu5KL/GJ5nSTjp5oiWXXDJIU/F6vnsbdOXcaLE99N8J8CgE23KJ3PLWtm4vT4+KSua8Sgt8RGxbkObMlGvj/bIhMDAPr9w2hUr7GLw8o27b53Pt7BIVpVL7gccyxPrMgPeSgYK49zrO0LrvWLsvEHLvGmeu09XGLj+Q9reW5l/hWv3W377Bh0mstyQwEq1BQMz8AQnkElN2Ks93mlzM6n6oOA2ahj05Jsbp9tCemswbWBmqBawNgZnMEK7tFcuauBsBb3AG9VOvCjjK2FivnLlhBk7DurcB61IHOBx2u8Rtc4WBuvv/oSN+VLwG0FKQDXNP28nnpJvaE/UGLDoNPItADxpC+A1SnV50rJpXRI1aHIZ4wdtYjA5YpQUWLxDB73rF+UzcXhS5cBtWCwt++si9ePOrhrroX3TjmlEaZYcAx6jVRfCqB2+xxlxNzc3S8NXEvzU3h6bw17jjkonZpEbupEpcOgcurWzMuUAMrp8bGr0kFnn58NC7Po8vqJMyiL9huVSqfj3mIrz+w9w8+XT+WhEhtu1fdsb7WTSXFRLJmSJIGaABzCE0yoOWMjtWhUL7eOviHSTVE89b3pADxYYuNlFeyJTuFTt07j47p27luYzT/6A1wcVo6nRfXLE55hc61x3K8C2bermik7owTbr7vZJj2phPJ0iLEBiyCyrygw88gSG7fNUkbJA8NgNmh587MLTDMbLwNBW8rsaNXRWvD7BndDn7p1GssLUjmQPhEY4R3F6zVsq3IyPcXIZ03d3Lcwm8eXKUDtpfI6HlLTAeZnJ1GsqiyPnmvnnpuzONbUJTtl24IeCopzknh0afaY4OhK/KoqhxuPTxEALcxN5kXV6Dg4+zS4xJjZ6fFR2+HlvkXZISDmfnXk+lFNGx1enzRFDr6O3zhynpfU62tDsRWzKfqy0S1c29R3yZQk7M4epqcYr9hZCxY5batolNvS4h4IEYIEHw+AfztUL7mO9xVbr7od1yrBhdTCFUfA4zVeMA7WxusbUtfDT/myIwnB+wnm/wSPZMTNMzi4WXRggqNzrpQVOhqoie0bfVNucQ8woKokxXuOBntiQTUbtLgHhnjklily4X3tYD3dgwHuuTmLX398jozEaFbPSuWWaWYqzroIC4O8lBga2r0sL0iVUVfC1mDjrhOyq5ObOpF6l5ffVCjcuR0HG6VH1oGaNtlh+9FNVqpbe9leIfhLXs51enm3ysnqWan0DAzhHQzIbs6Frn6KMuOI1GouG72JBStWG87g0LAcEwpj29Kpidw8JYnysy52ri3kpJpMkGuO5RVVYNDiHqCho5cW9wAdvT4K0018oS6uolMxa5KJ9Yuypet+jxpNJXzjQHHIj41SRmct7gGqW7opnZrIu1VOKDDz5pF63lIFJatmmFlRoGSginE3jHSCnR4fw5eUju3dCzJD9rsw3cS5Du9lJqijgdOpZg+rtx+SwFacg9v22Vm9/RDPrczn6Ll2nv+wlkeXZhMXqWXdfCvxeo20+AAFBD3/YS0GfQTewSHWL8qmxT3AgZo2Or3+K1pS6Ccoth8EhtiyZiYz0ieG2KaI2lPZxLFGxWNzRYFZCUyfZBrTiiPdpPjjCeFGcE2Ki5I8y6FLkJcW+u/XWwUW05jvL6rFPcA2ldu356QzxEj4vRMXqG7t5b0TF5iblciJxi46BwMySq2hvY/CyRNJMeqYk3n1VJXg7vjV6ssAtS1ldm74EhSS8fp21DhYG69vRbW4B1jz60Osmm0h9zrC2UVdCaiJGusmei2vpbEEEEJs8NSt0+ju88sFHBRfpm0VjdI+QrzemmDgjSPn5bhXC5iitLxb5ZTCDEEuz0uJYRjo7PNT3drLljUz+bzJzcvq6O6Wqcn4LimL9q5KB/fcnEVxThJbgzpc4SgO9Bt3neCBEhs1zh6KMpV8SeH2vmFhlrRAGQwM4xkYYm5GHPEGLS+VO9m02MbEaC06TTigCA8+q2/n9nnKvg74A1hNelbPSsUapEwcTRgfujRibBsbqaWsuplfVTTyQImNh0pzGAYmgOxobS6zs72ikXBNBJ83KqpQwXHasCQHg15Df0ARSY123RfxRbow5f8Ff3FhbjJ5qRM5WNclAdv6BVby04yUnWlHo4nAFh8RAlyqHG62BsV3fdE6Ylq7ZEoSXd5BlkxJYt9ZF+9XKxw6MTKGkQii4HOxND9FdvPWFFp4pWxElPLYW6d4Ynku9xZbpUlsfLT2sq6QeP8ur58Xy+voC1yisdMbYjQ8+ryWQGeUF9xooAZgSzZyuP4UKwoU0caKAjPeIMFFcI3VKRMV7Bm48Et6MAZ3LUO2f4xKNUVy4GcldPT62FfdHOJR5g9cUrNGJ/AvH9RI+5KizDgmRulYmptMpDacwoyEq37G6O7411Fbyuwy9g2un0oyXt/8Ggdr4/WtqHOuXjISoqVFAVweW/N1lVCEXmls9szeM7S6+0kxRdHuGeTuBZmcbOrmqVuncdrpwesLKJ0aFIA4mjfU4h5gy76zMmYqLyVG+jKtnpXKljUz5U1akMtzzLFsKs0hHJiVbuJCVz8vq/ynSygeX9vK67h9ziSqW3tJmxgVwp8DhfOlQfEo+7CmjdsK0rC7vBRYTCF8qiffOc0Ty3NZeYMFY5SObeV1PLE8l02qaOHRpdlsO9rEpiXZ3DbDzK9USwYxCn18WQ43WuNYVZjOy2X2EWsTYPGUJD440xYSbr+pNIeEGB1hmggeUr3QhLjhYRXQ5SYZ5DZuWTMTg14jfav2VrVwqL6DNz9ToqgeKs2R4OXexTnERinGwKmmSMLDkH8XHaQlucmkmfS0ugf5Tn4aR8+1k2eOJTxM6f6FqSpdAdIFT/DouXbW32yjaHIrbhW4/GB2eohlidmghNVX2F0cb3JTXtPGvx9zsPXO2RRYTNy9IJPt++386bQS1yRGdg+V2MhKMnDXXAsu7wD/cdLJqtkR/OMcCy/sq+O9Exe4OHyJgWGkkGdSXBRPvnOaosw4jjd2YY1XQPf9VzF7He2bBmPbRBRYTDx16zSa3X1Unu+murWXzPjrs8cZXSJ54mr12sF6DHoNvsAwOk04je5BaXtyNduM4AcpwUMNVmfv+KiWF1Ug3O4dwDMwRF5KDLuPt2A26shKjA7Jcr1a5U0ysTFIvHAtz8brqUkmvUybSI83jIO1v6EaB2vjJeurKpv+GkoEKd+QFsO2ikbmqDyg0VVhd1HZ5B7ToLbC7uJEk/uqnkot7gH+z6F6/vWTEXJ/cLn7/aycYZaxTGVn2vH6Amzer6gwqCdekgAAlxBJREFUGzv7OVzfRVFmHDOtcfL3NpUqWZiLpiTRM+Bn9/EWijLj+N4MM2mmaBbmJvP7Yw7uvHGyvOEHqyAF+HioNIcKu4sn3zktA8nNRh0ZCdH8uNiKXhNBXkoMB+0uiqckcbSxi+IpSSTE6PADmar/XNmZdnLMsWxTMy3FfmqAJ5bnygD3bWrnLiPJIK1CvCpvzdkzyLK8NHSaCC4xMi4Wf4qxoNmoIy8lhgkoi/7d86ycbevlaEOXVLEeqGmTQoWXyut4bmU+c61xZCYZpPHwljUzpcCiOCeJE01uWtwDvPFZk0yzeChoLOj0+lkyJSmE0xTcATnwsxL+eMzBFlXxKbpVIuJLLJQCqAle4Iz0iWzZd5bdx1vQaSbgHgzwh2MOXlbFAKLWFFr4U1Uzz75vZ918KwuyExlGAa7N3f0y6ikj0cDcjCFyU2KkEjkrycAze8/g9PikpcmBmjae+t50JoSH0eQe4M3PLpCXEsOeYw7ZERXqUwHqnlieS4TaBa1yuDlod30lY1ZRwpMtOTqC1ddw1K+wu2hwecfsaF+p3jhynqHAME/vreFHN1lDgswFuL9SBX9HwQ9ywfcBMZIWnoMbiq3YO/q5rSCFAb+ibl5/BdpDcG3fb8fjG2LHwUYSVCuWJ985/WdzbVcVpkNl05hilvH6dtc4WBsvYGRMN9aI45tSIpInNko3Jo9MKOLMRh2DviGZ3Scc/j+saZMjq6sBturW3pAQdVFVDjcf17VTdqZdOpOvX2BlQU4SGYnKaDbqYD3W+ChumWYOuWmL8Ua7d5AfzE6XgChaN4G8VCXWJ1h1NpaqVFRxThIPl9h4UfXu2nPSKY1yZ1njuGVqMhuWKHFLU82KKOHVT+o52tAlO1MioWD1rFRuSDexp7JJhnE/UGLjuZX5uDyDmI06JoRDVZOb51bm82ljl7RDeKPSgTlWL200Aihdns1ldgyaMPYcc5CXEsM9N2dR4/LyoJoY8dhbp9iyZiYzLRMlMHryndOUTk3kpXIF9IrsUwHENpYoNhwiIknkJQL88+oZvHfiglyId35ch73dy+7jLQTUBA2AhBgdZada6RwMUJhuIjZSG2KfsW2fne/PtnCyqZtTLd3y5+LzzEYdNS6FF/jd6alMSzZKIDIM7FY7PyI8/Y8nW/jpLbn86CYfh+u7mBwfjdWkl9ywHR/XUXbGRUZCNIfru5RjpZrUxkVqWTQlkS8u9OALDMsw+4QYHZPioqXAZOjiMDWtvZx2enjyndM8VGIjPlpLbJRWKoOdHh9Or59Bn5J/GbxfY5W4XkaPM4X6d88xB4WTJ3Kgpu2K5H7RgRYA63oAm+AaPro0m0eXZuMdVEb+pVMT5bm055iDyHClqzW66yRsY866vDKXd6wSRtNmo47c1IkhRtYrr5BCElyvHaznUIPS+b19ziScqvnuU7dO+1osOa42Rh6vb2+Ng7XxAkY4HN9UoCZqrLGNqGAPMdFZE8akP7rJStmZdlbPSiVWP/ZlIaKlirPimZuVeNnnFFhM3HmjlZyEKDmqulnl3QSbgAZ3MAUBWVhFLAp6vUGvIVKrCRnbiIDzYFWpSFMAxbR1+JJi6fDo0mxyU2PZc9LJ+psy6BoMsLW8jgdLbFQ53FQ2dPCfp5wkx+hYkJ3IzkONbFpsY8AfkF2Xz5sVE9jYSC0ZidFMnxRLa08/OUkG2YUSFhIPldjoGRjirrkW6d2WaNRLe4Jt5XX8uNjKbyoa+dFNVkqnJrE4N5malh62lddh0IThD1zCbNTx6flOys64SJsYhXcwIFMFVs9KRat2gto9gxyu7+L+EhsPqh3F6ZNiefOzC5TmJrNR/XmLewCdZoL8DoW1x4oCM2+fdJKVEMPmfbXye3R6fKybb2XnIUUhKIDa5v11NLn78QWGebfKiUYTIQFB8Chb2J/svnc+rx2sp3cwwOx0E4tVcP/0u6fQR0zgcH0X+866ePcLZSS+t9rJ4founluZz3snLpCTFMPrRx384xwLN1jjaOr0crCuixUFZumRJ+KfVhSYqWnt5U9Vzay72cYW9ficbvNQ3drL0txkJaLrmIOMhGip8v3eDDMTUCwoVs22UJQZx4KcJCk+GA229lQ20dDRK21jRgOHMPX4VZ7vZnqKcczrqMU9wK8/PidTKERn72rV4h5gUlwUD5TYeO+Uk1xV+VyUGYfZqKfsTDuFkycqPMNJii2K+P5FzU43cdbZw+wxckBHV3FOEs+snH4Z4Lue++NMaxyn2zzyQQng9jmTLgupH6/x+jI1DtbGS9Z/NVDbXGa/Yl7mX6pG82GEu3t1s5vSqYlMnhg15lO+AHXCHmNCeNiYoLA4J4mspBgKMxOvyCcJBmrBBOSNKuAAZXH648mWEGNTYTNxSbXYEEBt4S/L+dFNVsLCYMdBRZ25tihdAspVsy3cvSCTCruLDcVWXi5XTGN/oJpw9vuHyUqK4Ynluew5oZCtN5TY6BlUuHWZ8QYeVB3/RceqRuW9DV8a6ewVpJv4tLGL1486WFFgptPrJysphj9VNbOpNAeDJozc1Fg0mggiw+F/zFK++6ykGC4OXyI3NZYPTiuLmzFKJ7suA/6ANC7+pK6TT+o6yTYbmWmN44nluQRUw+6spBjefLWSDUEgWdgwpJj0eAYDPFCaI938AVbdMImspBhu6+ilpcfH4NBFSqfq2XmokedW5lNgMVHlcLMgJ4kvWnv47vRUspJiSI83SIAmiO3i7wkxOp66dRonGrtkjqvwwHtm7xnio5Wx2OpZqawptBCOwhcEZcTc6fXx2tEm/nGOhXuKrVL0sGq2hXernEyfFCtB78YSG809/QASuKWYonD3+ylTfc1KpyZyytlDfpqRPHMsu9T0jW0VjRys6yIjMRqA3CQDS9SR+NPvnpJdZgHYdnxUS6/q77d6Viru/stNdoVIxDiGnY2ojl4fxkjFquU+1bV/UlzUFa8XweFscQ8Sb9AyNyOO/zzlxOnxcfucSbx+1MF9xVZ+VdEo+ZwiymlCUDJJcOLHlSr4Qeqr8sEqGzroGRiiplV5gMpIiGbo4jDPvm/HFKUd74yN11eqbwxY+6d/+ifee+89Tpw4gVarxe12X/aapqYm7rvvPsrLyzEYDKxdu5Znn30WjWZkNz/66CN+8pOfUF1djcVi4f/+v/9v/q//6//6r9uR8QJG+EoHatouU679V1fPgB+nu0/ytMYqAer2nXWN6asWXFcLkA6u0fYcFXYXB2vb8Q4GZNeo7FSrBI8Pl+ZwCTUeRxshzXY3lNhkJ2ttUTqRmjBuzFSAWrBdhBhjCv+qbQfOYTbquNDTz8JflvPo0myqW3tpdvfxa3WUubHExsx0BbAIr7INJTYiw+Gg3SVtNgqCrARusMYRDvxs2Qgnq8c/LM1796gmq1pNOCmmKGpauukLXJI2HwkGPa+o484Ci4mPzrp4bmU+82yJdPT66BnwExup5a3PHSQbdBLwrrvZJnNI96gk/UO1LlJMSuclfWIUbxw5j04TzqrCdPZUNlGck8SOj2p5+6STjIRopqfFEKWJkCrTKoeb+393jNtnW6QVRJXDTaw2XApNgm1IWtwDEuhsWTOTJ5bn0jsY4M4brRTnJDFD5VKebOpmRroy3p6VbmL1rFRutMZJdafT42NoWOGA3V9iY8A3RGG6idvnTCLdFMlrR5t4dGk2E8LD+KSuk4yEaPJSYrh7nlUqeu+aa6F0ShKdgwF0qhhCHzGB9Tdl8PTeGh4qsTEE8twRaQ47Pqql7Ey7kiWqKn/fOHKe1442ER+tZUWBmYgJ4ZiitGPyXK9ls1NgMfHTW3LZd9ZFW08/P18+9TJT6eA65+pl9/EWbp8ziTc/u8B9xVb+Lt+MXqcAvh/dpAC1h0tssgv9YGlOCFATdTUAtrXMrnA4s+JD7FS+TO2pbOLtqlaqW3spyoyjs88vAfOGEts4UBuvr1zfGLDm9/v5wQ9+QFFREf/v//v/XvbvFy9e5Lvf/S5ms5lDhw7R2trK3XffTUREBM888wwADQ0NfPe73+Xee+/lt7/9Lfv27eNHP/oRKSkpLFu27L96l/6mK9g9/OsAaiLj88uSbsXIqnRqIqVTE9GFXfm1VxuxXs/2DfgDIVFSLe6BEEL7sSY3Ow81cm8x3KFaXQigJgjtZoOWTYsVc9Yqh5uEGJ3c5z3HHETrlUD4pXlpvHawXio4RWdrbkYcB+q6MEb2cvfcdF472sS0ZCM3rlSAwsYSG/tq2qSy8onluax7tVL5zII08s2xOL2DvPnZBR5ZYmPTYhvTLSZe+OAsoHS3XvjgLMbICMJRFs0e/7AUB9w8JQmnx8c/zrGQYoqiuqWbX6tj0U2LFWVnTUsPD6gqOsHle1AN295V6SA3yUBlk5vXjzrYUGLj8WU5rLvZxp7KJr47U7E0mZuVSEKMjvPd/Zxq9khAK4j1Ls+gBHm5qbGyizc/Iw7/cJCFhOod9mJ5HRPUad2T//EF1a29vF3Vyt3zrCFk71RTJEWT47mtII3lBansrWqhNH+iPMd3VTrQAFtUf7hUUyTVF9wy61WMvT2DAXYdc8gOUV5KDBMjI3jzswusKDDj9PjQaSZI25ZF2Ql81tSNs2eQVYXpbFkzkzc+a8I9MMS7VU517KzYj0xLjgkx8RXcS9GJ9AcuyRG6eI3org0FlC6mQa/hsbdOKaPVIC7l9YqUxDWwevshkmOVDFgRWj+6spJi2FBspanHR+nURD6uUwQ6wietYNJEHl+m44tWz2XCj2spMEV6hRCp3D5nEq8dbWJCeNhVH8iuVMFgLNGo53iTm95BP68ebqLPd/GK+zhe43Wt+saAtV/84hcA/H//3/835r9/8MEHnD59mrKyMpKTk5k5cyZPP/00jz32GP/P//P/oNVq2b59OxkZGbzwwgsATJ06lYMHD7J58+YrgjWfz4fPN6Iy8ng8X++O/Q3X16Vm2lvVwqmWbn5TMbZC82qVEKPjuZX5nHZ6eL+6jVPNHqZbrm442eIeCPn7tRYnoULLS4mhurWXnWsLqWnp4fgFt1zUYaQj8Q+FlhBCvBBGCAC1osDMwl+WYzbqiI/Wcs/NWWxT3eUjtRqpOBsdlp2bGsvP3/pC5oAa9Bo2LMxiYW4yT7+rxCV19fuobu1l1cw0nlieS0aSgRUFZt6oVEZnS/LSSIjRkWbU88I+Rd348VkX1a29nGhyU5yTxKqZaTy9t4bleYoXVLxew/oFVlYVWvj3Soei/lR5Rc+tzGdDiU2OSHd8VMtrR5sAiNGGSy7fRjX1QCzQQt0pulni9/5OVZF+d+YkUk2RbFwyhZxEhcdlNenxDgZ4bmU+qwrTidJqaHQPYks2smXNTFrd/Xj9w7xcXidzQTOSDKy/KYN+f4C8ScrxfOp706ls6MAUpWXzvlqcHh9L1LHrS2V2znd6SR80QND3vu2uQnZVOmR3c6NqORIcYt/uGWTzvlraPYOUqTmmsXoNjy7N5nRbLy/sU/a9ob2P9QusfN7sJi8lhsW5yaSYomitaqXVPUh4GERpNTR09FGcFY+1xMDW8jqeunWaNAbeUmaX53jww4NQsQqPu+AaSyyweV8tJ5u6STVFfmmRkrCEEZ291bNSQ8CWqHOuXila2aZ2XOdnJ7F8eprMGN1SZufdKicZQXYWoiv68+VTx7TxEedTACVVQXTuVs9KRRN+bR7dlcqWbGT19kM8sTyXcvX7Xj1L+fzvz766Qna8xutK9Y0Ba9eqw4cPM336dJKTk+XPli1bxn333Ud1dTU33HADhw8fprS0NOT3li1bxsMPP3zF93322WclUByvv86qUR33NxRbQ8wtr1XCILYoM24kBDs3+ZpAbcPrlXT2+clPM3Kq2SM9sa62fWajjoU2ZSxyqK6d8139tLoH2bjrBDv1GvmZD5fmyLgoUJRporMgfNJumGTiZ8um0tHro67Nw/KCVHbqNTS4vDz5zmmpOttT2URpfgpvHDkvXeufWTmdz5vcGPQaXjvSyJpCJT7pVLOHsjPtrC1KJy8lBl/gIs9/WMvjy3KoPN9NfLRWIUurxr33Ls4hb5ICCJu7+2UHKBxFMRehCeeOeZN548h5nt5bo/DhKh2yS1ack8QG1dT1wM9K+PdKhxyDiu7XdwrSAIjUhIUYntqdPTJDUXwfQqG781AjRZlxdPT6JGB49n073ylIwzsYkNtS5XBz+HwnZWfa+bxRyau8e56VdTenc5ER37c9xxw8s1KJvvr5W18QH61l1cw01t1sk/FDTyzPpcBiYvt+JW4J4N0qxRX/ieW5lOancLKpmwM1bSzMTaY0N5kHSnN448h5rAkGCT4EJ9Kg11Dd2sumxTae3luD2aijcPJEBZwbtNxojWPXMQe3zTCTZNDxh2MOfr58Kt+ZlswL++q4rSCFw+c7AXj+w1ryUmJ4qMQmwZboVkJoBmpHr08CtbHC3cX5L47rqsL0ywQwo4GaiPW6UsdNvL8ujCs+JAlhkPDTGwt4BYN6URVnXeSnGTnW1CVHvKJ2flwnu85bVXFMWU2b5KQariAyup4SlAkhEhIcxFWzLVf0Zxyv8bpWfWvAmtPpDAFqgPy70+m86ms8Hg8DAwNERl5+M3n88cf5yU9+Iv/u8XiwWMafjv6a6quMVPdUNnHaqSjlMhKj+dFNVt79wsnQNX6vo1fpshZOnkiSQUfZmXbu/90xOQqqsLvwDgZCFofg7Ys3RFKan8KfqprpMQ+HxEaJWr8oG2/gEt7AJTnGMei1bCixkav6oKWaIjnZ1M1jb50iUqthRvpEXvjgLI8vUwxf91Q28dhbp7h9ziS+uNBDdWsvQxcvER6GNMutbu3l08YupiXHKCBktoVtqqeYAGqRWuUWMTqLtMLuorK+nQtd/Tz5zmm2rJkp7ULeVMOtYaQbM+APMAQ8pBqwilzW+0tsvKWCuNvnTCI2Usu9i3MIDCv7KDpmwQa5eyqbGPAHeKXMzqpCC9vuKuRkUze1Li/3FFuZoImQ21jT0oPZqOO9ExeYFBfN48typCJX8O+WTEmirs3D5n21RGo1ch8PqN0tUACDOD7QjEGvYVVhOhsWZvHkO6fJCFLHJhn1NLoHyU0ysHHXCXyBi0yKiyYjMVry9cKAbnU89viyHHoG/JiNOr4zLZlGt2KJ8kalQ3ZkegaUM7PyfDfpsYr44u2TTpblJeP0+HjjsyZKpyTx+LIcUkxRlL1vlyPqn7/1BS+V15GqZqeOBWwgFGQEn7eiWtwD7Pi4jsVBDzSjgZO4BgC+cLhp7R2UStorddyuB7xc6fOCa/T++EFy70ZXsOefeMB7STXUtsRG/dncMnEMxfv0BS6xVR1nw9c3Vfg21zfZ9/MvUV+91/s11P/8n/+TsLCwq/5XU1Pz37mJ6HQ6jEZjyH/j9ddXm0pzvvSF/eZnF1hblM67VU502ghWzjCzrbyOF8vsY76+xT3A/b87Rm5KDJXnFZ8t0fX44zEHeyqb+N2njRyodbF6+yHZeQnevrsXKN5u625WgE8wUBPj1RdVILPnmIOy6ma277fz2tEmtpXX0djhZeOuE9KJXXSY/l21Yuju99HiHmBVYTrPrcwnzqCXQGvz/jrmZysebKKrUHm+m+c/rOWWqcmsKbTwyBIl1H5FgWLs26Mq/sQiA8pY91BdO9sqGnG6+2Qg+cpCC3fNtRAfrWVXpUO+vtPr598ON7JNDUwH+EGhhbyUGP5BXSjFCAoUovdL5XVsLbMzNyuR+Git7JpWOdz88WQLn19wU1bTxquf1APQ6lYSGwYDl9hWXscH1c2se7WS3NRY1sy2MCkumo27Tsjj896JC5iNOiLDlaSBRKNekuyrHIq1y9LcZNnRaXEP0NTppXRqImsKLawqTKfFPSCBartnUHIQfQGFo3eg1kVRZhzPf1jLp+c7lZiw2RaqW3vxB4Z49bBibvrs+3YudPWTn2bkUEOXdOK/o9DCJ3Wd9AwMUXamnYyEaJblJbPnpBOzUUfp1CRePdzE6lmpFFrjeHpvDV+0emh19/PIEsXn7guHm/hoxVPNp/LNAAzacKocbjaX2dkcdL6PBdT2VCpj6V2VDl4/6uCA3RVybgdXhd3Fjop6fv7WF9R2eHnzswu09g7y3Mr8L319CtD3VWtTaQ4bSmxXzAgVgE0IgjaU2Cg7087lGtc/v2anm1hRYKa6tfe/d9H9hpQYqY+mnPwt139rZ+2RRx65phIzM/P63K3NZjOffvppyM/a2trkv4k/xc+CX2M0Gsfsqo3Xf39dLdrpz6lVhen4AsPYXb3cPmeSBA3hmogrqtlSTZE8s3K65H1dvHSJwskT6fT6WXWDQrIXMUmiI3K99VKZMkLbdc98ZqebyEuJYWFusuRCaTXhRGo1PPnOaR5flsPyglRJjgZl8XV6fBj1WrkoJhr18sl+U2mOfK8Ci4niKUmcaOxi9WwL2jB4o9JBz+CQtER4Ynkuq26YxLpXKxUD0sAlqeb89cfnWKOCrUhtBE++c5qFuUrHuuyMS9mOyAipvHxJ7ZpN1E9QwuKTDMxIn8ii3GSO1LWTmWTgRZVTJdSfD6oh5C3uAVJMegrVwOxUU6T0HKtu7WV+ljLyFAuvJjycHxdbyUxQSPTewQAvqR08Md6L0ESwsTQHf+ASHf1+mdG5c20hAP92qJ5Or59/Xj1DHsuyU628W+Xk8WU5kmT/e5V/J+xMijLj+OfVM+ju85OXEoMlNooZaSYaOvooO+MKiezShSkAuG/Qz3Mr80lUvcKKMuP4YZGVt6taeaPSoXb2PKyelcru4y2kmvTSDNcYpWPdfCtHG7r4pK6TFQVm0uMN/NvhRn5YZCU+WsuR813cPc+KLzDMk++cBpQu57Pv21m/wCetXkSNvs5EhxYUaw+zUUdWguGKY/8LXf00dPSRn6Y81BZlxtHY2c8PZn+5TlWF3cXP3/riS2f9jq4vc98YHfv2dZZ4KJscbwjJIx6vsevb4vv5ddZ/K1hLTEwkMfHyFvVXqaKiIv7pn/4Jl8tFUpJyYXz44YcYjUamTZsmX/Of//mfIb/34YcfUlRU9LVsw3h9vdXiHuDVT+qlq/rXfRMVXBoYEQlcy3agOCeJrXfOpmdg5Pk7KymGVFMk3sEANS3d7DnpJDk26qo8tuCMwi1ldl5RAY34jOA/YaQLYIrSSqD2ksoreqA057IoJyFK2Lm2UJLwD5xVOhUFFpP0AHtI7biZjTqONnTxg9kWEg1aGR4vcjbXvVpJrhpxJGphbjK//czB48ty+OMxBxuW5LDrnvnsqXTwaWMXT75zmp1rC3luZT62ZCPN3f3kpSjqyoW/LJeCi+dW5vOwyqkSfKq75lpkZ6XsTDv6iAlkJcXw+0qHNHAVI0xxnDXh4fgCF/mkrguTfsTPaoPLy+5jDlbPtvBAiU362XX0+5ieGktcpJYFOSMCgXernGwotiqjatVyJNh77+m9Srf/Hwot7D7mIFYbjtmo4/szUpUOjar2m25RRBQCRAmgZjXp8QWGuWVqMpv310lvsKduncauSgf/driR/DQj87PiaPX4aGjvk/Fjn9R1smhKItWtvaSoeaXVrb2YjToqz3fT0K4E2Hv8w3T2KedoolHP501unrp1GgP+gDxHCjMSiIiIkPs1Fk9NHMPgsWAwcHrtYD0zrXEyaWLbgXM4PT4yEi6GbFtzd3/I9VDlcLP/rItLjH1dVza5///2zjysqTtt/zcISYAQwh6WEIWAWBSt0ipUtFGqdbqqnbF2s2PHarHaOr5dbF+dmXbe6V6rtmqXnx07nVbbajdb2gpSRUUrVkVQiAhCBMJqCGFJQM7vj5PzNYGwKSrL87kuLoWcnHO+2c6dZ7kfdk49nfX7Tqq20/fv+lQtaxrpiquZnuzJzFPiEiTU7BkwNWslJSWora1FSUkJLl68iOPHjwMA1Go1pFIpZsyYgRtuuAEPP/wwXn/9dej1evzv//4vli5dCrFYDABYsmQJ3n33XTz77LNYuHAh9uzZgy+++AI//PDDdVwZ0RnBcjfcERsCyTD0qnGgt8doj1AU3RmdibBZscEI8XZnRfidsTZVi5IaE5osrXY1RPfZ1Nw5+lAXph0AvAUGALsB3CbLpTTXSZ0BCpkYJ3X8BIJNv57BtiPncaS4Fv8zIxqPTA5HnTXqJHTkCWnUyAAp1nx7Eo9MUuG34lrs+L0Mq2dFY2yYN/RG3j5Bb7KwhofaRjPez7AfU/Tq3LE4W1mPiABP/F5iwJy4MPh5iiFzc8XYMG/sWJKAn3N5A15DowXvpBfATeSMyAAp/nKLCiKRK0zNrZgVG8xGb80YpUCYnE9Xqqz1V1v2FSBWKccn+wvZvFLBsf+dVC2mjQxgtWfCuKeoACn2nqnEgQJ+SsLoEBk+z+KL9J9KimLzOW1Ts4JgS8kuY00Dhwqq8MKsUVi+/TgfiYwLY0bPgm2EMHR75XQ1/nKLChV1jawjdNXMKJbGXp+qxWl9HaKtQ8PvHeuOjAJe2MrcXHH/TaGoNvH1c8LMzzBvd+SUGpkB8fybwpBXaQIA5OvroDea4eshQlaJgQlFQZAJgq39a7n96/bzQ+dYKlx4jQt8sr+QH1eVkocdSxJwvrYRI/w8cM9YBb49oWe+fzcoZFi+/Tj2Wn3lsnUGbNrLe7kpZGKHxxV+L6kxYaR/15G19n537QWb8AWgs2MRxEBgwIi1NWvWYOvWrez3G2+8EQCQnp6OW2+9FcOGDcOuXbvwxBNPID4+Hh4eHliwYAFeeukldp8RI0bghx9+wIoVK7Bu3TqEhobio48+Io+1a0R3nkeOiFXK4ecpvmbfsj4/dA4b954F4NiqAOBTQ50VIHflxSYMDxfsN34rrsUkNZ/eEwSbbcRNQBhzJVyMhM5B26Hg7Tv8Wjm+5il5ehQ279Fi25HzbFi4EAVZb/VRSxodBLS2wE3kioRIXgTmltejuJo3I10QH4aXU/Lg6sJHkKaoebGWrFHDV+KCl1PysEyjhsJLYhfxC5ZL8GFGITILedHxVFIUbrQOr8/Ir8QHGcV4UqOGZmQAVkxrQ6RCxvusVZpY3RbAW4+YWy/C0GjB/EnDcd7QzITaKz/z9Va3x4bA0NyKJdOicLEN2HZUx5oDXrpnDI4X12Ln8VLcHRuE5duPY9XMKBwoqMEjE8Pw+u4zWD0rmnXmrkiKgtgJkLg6s6YKoXFk75lK3Kzywbz3D0JvNOO12aNZXZtgBdHW2oL5k8KRVVSNrZkleEqjhspPiu+ySxEid0NueT0eT1RBW2VC3Ag/vJOqRXGNiYmX+28KxeaMYjYHNCbIk1lK+HqIMMLPAx5ifnyW3miG3M0VN6t88Nu5Gnx6mO9ubjBftBObwjraGzrbvt4cCbXtWTrkWp34bT0BhecFAIuslV7gJynst4rMmCBPRPhJ+cfNJqUVq5TjiamRGKnw6jSyJpxPd1+cygxNeOPn06z71lFkTXhv9SSy1hMc2YsQxNXGieM47nqfxEDCaDTCy8sLdXV11GzQQ9amajF95CWB0RfDjK+EnVklTCS1R7jg2nY+2rJlXwEzQ+2qY6y9oLMVgQDwh9G8zcTK6Wp2ERT82IRoC3DJK2qEnwdGKTzhJXHtYPYpzPk0WdoQGSBlNVTLrCm/T/YXotHSirvHK3G2sh5ZJQZ2IRTSnWWGJjYtoczQhC37z+LnXL6+8xa1L8aGyDF/0nA74SikIUsvNMLQaMGa709h5XQ1mtrAOiFfmz0aOkMznkqKYuOyFDIxkqdGsKHfeqMZd8YqkHXuAh68SYn/HuH/Fh/ug0WJ4agyNrPOVtvpBkumRbFIluAPJnRD5lWa0GxuwYJbeEGxI0uH9em8L1xdkwV7tZXYmlnCvOS83ETMswuAnWfY2cp6O5+7ZI0aJTUmZJ27gDkTlHap2LWpWsRZZ08K9X6Cee3c8cHIK6/HjFGBKDE0YsfvZVgxTY1D52rZoPapah9stAq1uuaL8JFKmOWH8Fgt06jhYq0zFDpU547nh8dnFVbBy12MV37WImmUP6IUXtiYXsAmUdiKjJTsMtZFam69yHz93k3Vwgn88PkvrKOp5k0KZ15qXX1xEsyfiw3NzNdOEPP3xSlxouRCBxuNK+VK61p7c3/h8+Glu27oUkQS/ZOBfP0eMJE1YmBiO+6oPwi1zw+dQ0quHrvzKrD6zo4dal0VGWdoK1FlMqOmwYJiQ3Onx1ibqmWRIUGwCR/soT7uqDLyRqzebq52Qg2AnVADgDRrnVlmYS2Kqhvw53gVANgJNcGf67boQPwr5TRGh8igkIlxX5ySpQdXz4rGoYIqfHOijEW6NlqtBFbOGImiShOrxXpkcjgWTo6Ah0QEhbV+DeBnQy669VJnnSDAX5s9Gmu+P4UV09R2cyxXzYzCnLgwvGftNhTGZSmkIqz5/hRigjzx53gVIhUyfPZbMfRGM9xFLhgdIsOcCV5QSEVMXJQYmvGeVaStnK5GTCjva7YxvQBuzkCQlzsTar+c1qOoqgF3jOYbi57fcQKZhbVYrlHDz1OMtHxeqCWN8seHB4qwYnokE2OCkLUtcP4puxQv3XUDYkLkqKhrhEougdY6a3NjegFKakyYMUqBQqtIfmiiEjcP98X6eeOwfPtxKGRiJtRyy+sRN9wbd4wJxnBvd6j8pBjhL4XK1x2/5ldBW92Iv9yiwtnqRqSersLc8cHQRAfiXavpcZmxGRus/9cbzdh5VIf7bwrFjBv4tW7MKMZLd90AhUyMnFLewFshE6O0rhFffK1D8tQIOzuVzMJajFJ4srpQcyuHdVZBff8EJf40QYm51vR8maEJ894/iBXTI1FsaHb4HmkfFf7w1zNQyHgvuAuNfKRTn13aaYfm5RAsd7sioSa8PoDOI29b9hWgztKGvXkVbJ5pk6UVcSP8rvtnGjE0ILFGXFXmxSlhsbRc84HtjigzNEFvaEBmYS3+covKbkqALZ19YCdGBcDU3IqPDhR3WkMniFOFTMw8ygTafxMXPuRTssvw27kaNLVcRISvh8Nz8ZW4oLWtzS6FJaRjXrrrBtaRKXQPJo0KwKEC3pJC6Ez95FAxNNGBKKpuwLHiWhb1Wbg1C3uf0cBkbmVD0YPlbpgXp0RqTjkAYOlnR1lacZizEzamF8BL5MyGkytkYkyOCoDCi/cYE+qy6i1tbEh54sgANrPztdmjUWMyI1Ihw0mdAamnq7Bco77UFTncF2u+P4WW1jb4yyRoMrdAIRMjITIAdU0WLNyaxYSbpY0fhL5Mo8bYMG9oK03Yla1HUnQgguVuSBoZgIkqH8yOU2LL/rPMMkOIgCVGBdids/C4B8vdWKo1JsgTi91FCPJyx3Nf52DLgjjknjcgSuHFoog7liTAAt6f7dPDOqyfNw6rZkbh1zPVGO7tjgMFNcx8NevcBUQHeeKtNL7BYMYNCgR5SqDwkmBtGm+IrJCJkVfOp6KfvS0Sr/yshUImxqLJKtweG4ImSxt251UgIdwPVcZmmFvbWF3WC7NGwdBoQUquHn8YrWBdvr8V17Kh6cIXCX+ZBH4eIvZeuAigvK7Rbt4rwHsM6o1mO8HfnUhi+2zj0GRp4ScRJKo6bCdEt3wlLkgaHdTpZ0WGthIndQZMjgrAwTOVHVKzvSVY7oZX547tMrImvAYEb8IxoV7w9RDhlZ+1iA+vxv/MiCbBRlx1SKwRV5VguRseTgi/7kJNOJd5k8IBF1dIXZwua1jzrNhgVijtCOEDvzd2A3mVJnx6WMe714tdOqRQO4vyCdGgeXFKrHcX8eOjNGq0trbguxN6nK3ixw3t+L0MB2Q1SBoVwLpOFVIJc7d/bfZonCi5gLV7Lpl23h4bwpoSVs+KxnsPTMDhs1WwtHJYmsQ/bgunqLFlXwEevEkJd5EL6posdue9eEoE33ABftB7Rj5v65GRzw9XF46/eEoE4sN9WARnRZWJ1UO9nJKH5EQVthwsZl2BwvSDt9L4CNMSq4C9L07Jphks06ixLr0AYhcnvL77DF666wYEy90Q4Sdl6WGAF8qf7C/EseJa5JbX282HLTM0od7SxiJ2wkizZRp+NNRbaQV4bfZozIoNxg5vdz69ahV8MUGe+FfKafh6iHDHaAWig72AIzpEBEixzhohfCuNrxk0NFrwXXYpUk9X4WkNv5Y5E5QwNpoxzNkJc8aF4MMDRbgzVoEIX/7+3m4ivGNNyTZZWvHc1zl49rZIJE+NQEyIHHM3H8TeZzQQuzjjua9z8NBEJbzdxdiQXoA5N4ayZhXh+bIVZU9Za/Ta12XVNVnY6yMmyJPNFBWwrX+ztZUR3mfZOgPg4mqXNhYe5+2HCnGstB6ZhbU4VmrAMzNHdXiPrU3VotY6l7a2iTcUBjrW0gkIaxTMkRfdGokt+wo6zPzsLjJ3e2wIfj1Tjb15FXzTjtVkOibIE2NCPFFQYSSxRlx1SKwRV53+INQEriRlYruPrujt/qMDpExk+bqLMScurMPFsszQhOp6M7somJpbcWesghW0+0vd8K+UIuiNZrx01w14YdYonCq7gE8Ol+DZ2yJRZmzGp4d1+MstKpyrbcS2I+eRNMofqaerAAAh3u5YPSuaRe8+tAq1ZI0a41Q+yC01wNLK4R1rlGxpUpRd1KmmwQJfDxFMza04U2nCiqQoVm/n6yHCu9Zmhqet/mlb9vF1PzUmC85Wmpin2Sf7C3GyvA6f7C/EI5PD4erijDXfn2L1YmODvbBfe6lmThglJcwOFVK6j0wOx41hcni5iZDcyrGpDmu+PwWFTIzIACmKqkzMOuPWSD8kjPBBG8d3tAp1e1szS/CkRo0gAA9OCofExRXr0wvw7G2RiA/3gbm1zW4UFsDbTuy0joAqqjLh9/MG/JCjx7wJSsyKDcZL1vq+ueOD2UD0l+66AaMVXth2VIdHJobhhxw98+xbNFnFGglSrYJB7DIMD01UslmZK6ap8UOOHo9MUmHpZ0exelY0guVuzE9QsFERIoLCEHtB6Ai1aMLj7qiAPiKAT5kDgJebyE6gsHpLAGcrTVhnNUC2fVw6a76prjdDW93I5r06isKvT9VCq69Dg/kiYoI84SkR2dV7tkeYudrUBlTU8fWBJqthMoBeDWkPlrthVoyCpe7jw30QJJfAy80VEhfXK552QBA9gcQaQVwlhCYAR0XZQtPFwTOVeCuNH/G0MaMY6+eNs/NIE9zz571/EDNjeONZ4YIndMAJabiX7roBcncRAN7R/xurfYJU4opjOXrcGavARweKcWesgqXLnr0tEupAGdZ8e5INmQf4VOdT1uhUSQ2fVnzprhvwtEYNJ2vkSbjg1Vl4x/67xyrw+ZESliJbnhSFf80eg4VbsxAT5InMczW4OzaEibzFiSpkW6MpHIBlSVGoaW5F6ukqRCm8AAB6k4UVc7s5XxIXZg6siSJY7sbqBIUUdE1zK6aPDMCbv+Qhs7AWTuB90QSvsfO1DVi7h3/cx4Z54/MjJXYmuMFyNyycHAFPiQhR1sd3/bxxWJYUBQ+RMyvgP6U32tl7eLmJsDG9gE01EDzsACA1rwIu1jWIXZwxSe2P1JxyKGRimJpbWAdrqI8HahosWDE9EmvTzqDcaMZDE5XMcDg+3Id1tq6YxneaCrVxOkMz9EYzPjxQxEZiTY0ORHyuHkcKq3D/pEtCzFaoTX0jHSum8Z57Nc2tHQRTmaEJnx0qxAOTHEfJq4zNdvWWLXDs2+YIoTt0TJAXs35pz/KkKOaV5mJ9rXSFyk+KmCBPVpepkInR0GxxWJ7QE+ZPGg6xizP0dfxzKnx5sO3IFtiYpu10HQRxuZBYI4huWJuqZYX2jiIDGdpKVphu+zehruqtNPu5iEJdm5DSSdaoUV7fjAXxYUwUCEINAH7KLgUAbM0sgYeEj2iMDfNGTJAnu6iuNjbD1NwCubsIy7cfxzKNGvPjlPjldAXk7iLEDffGz7kVWJigQsmFRvh6iBA/3Bcvp+RhR4Q/ZowKZHNKBTG1amYUEzcAb4K7I0uH9Xv4i3DydN6MNyW7DMs0atw6MgC+7tWIU/mwNOPxEgP2PqPBjiwd1NZOVeFxCpK7o675IgC+6zBELoFKLoFCJoZKLmGPU9Iof8jdRVD5SfFeqhZLk6LgCt6OYrk1gmdrOFtsaMbG9AI4AfifGdFIy6/En+KUzG7jzlgFxC68LcfkqADsyNIhs7AWO7J0TARsSNViWVIUc5tPrjQxIbJwihoX2zhknK1BuaEOMUGeOFZcy8T5jiUJyMivxFLrfY3NrUjNq8AIfw8kRAYgW2fAc1/nIFmjhjOAP8erEDfCDz/k6JE8NQKGRgsevEkJdaAM8+OUOHSuFruy9XhoohJNLRex4/cyPDRRyQTj2j18dO2nUxUor2uEQibGvAlKTFJfMhyPCpRiU0YxXKzTGwShJqQKhWYI5sXW2sI6QAHgqywd3s8ohsh6f1s+2V+I1PxK3KjywSzr37qbBtC+A7MryxuB9sftiiZLK4LkEgDAmFAv/JpfhaxzF3D/BOVld3EKETSFF+/x1z6dC/BC7dC5WpjbRVuJjtDsz95BYo0gusC2YSBuuDf+nBBu9wEtzEK0LbguMzThrV/yER/uwxz+DxVU2Y1+AvhuyjC5G0zNFpaWXDldzYrVBWwjWMJ9g+VueOmeMQiWuyEluww7j5cit7weK6erMXd8MLKKa3Gjyge55fUoqjKxgeEfZxbjwZuUeOBmFc7XNmLHkgQcPluFtXv4KFViVICdw73QaTrVOhrqi6M6XmQ48fYkgjBaP28cjhfX4pWftVg9Kxqf7C9EXXMr1lujK8usaUrbaMvOrBJsO3IeL911Ay40WPDc1zlYP28cVkyPZKng+HAf3BTmDQB4f99Zfq4mLnWySl2cMDHCHzFBnvC1phQVMjGSNWq8l14AzrptXJgcf5qgxJHiWmSduwC90czXX7W2YHpMCDtHgBdqaXkV4ACWXm0fJVp0ayQmRvgjI7+ST11OUrHXRUZ+pV26GABaAUyzXtyzdQYsSVQxK46YIE9EKmRYOWMkXvj6JADeP81obsHBs3wt3UMTlfj0sA5Jo/i1NrVcRNIofzxwswpPTI3EcWvNXU2DBbeO9IezEz8lQoiUBsskiAnyxEVc6jwurjbZpUNfs9a+OUpFLk+KwkU4Fkx1za3wEA/r8Bh1JdQ+3FeATw/r7LZrP03kSpgTF4Yakxmvnz6D6CBP3DdBiaPFtQgPkPbJvgHH5tiuw5xQVM03MflKXOwmXxCXsLXGIcHWM0isEUMewZLCEcKFpLPImhD9ulHlw7atruftPYQB6nJ3EZuv2F6wCQa1yS6u0OrroPKTOrQ4aV9jU2ZoYkXks2KD0WRpxSeHiqHyk+JiG7Dj9zLcqPKBQiaGVOyC12aPxnNf52DHkgQUVBhxvrYRa74/hZfuugGLbo1EUyuHDekFkEtccKG5lRWZ71iSwHzVFsSHwddDxIrokxNVfHefRo1ZscH4ZH8hVs+K5h/TA0VYdMsILNeomQgS1ix0ki6cooapmY/aCdGhWbHBWGe1+sgrq8P8m/ho495nNJgXp0StyYLwAD7FNcLfA3eMC8UOZtxaiqRR/hit8EKQXIJlGjU2pBfgSY0auecNWG+d3zkzJhAmcyvcXIdhY0YxpseE2KXVWsGbAt8YxqewHYkPobaLn9vqxJ7XMkMTE2hLrbNUi6tNeC+9AK6wjyA5u/CjnlRyCRZuzcJTGjW2L07A3rwK1DVa8FYa/5jI3FxxrMSApFH+kLgOwwh/D5hb29BgvoiIAE+crazHyyl5eGiiEr7uYrg4gzUvCOOublb5IG64N3Ye1SFpVABST1fihVmjsHK6mhkhz4kLgzpQ5lCEbNlXgI3pBQ5TkMuSorAhVYsohVePoknBcjfcPNwXZ6sasPOoDvPilDhUUIXi6no0tHJYODmiTy7gi26NRKiPB5osrag0NiOzsBYJI3yueL9A595swueI2GUYCbUuoNmfvYfEGjGkWWedywmgW8HWGe1n/sUq5XjvgQlIy690OGexs/s7ml5gS4a2ElXGZmboa/thpw6UYYS/B46W1MLPXcRGSCWNCsDLKXl46a4bsPcZDb77Xce6GFfPimbzUW8dGQAXJ6DG1ISNGcVs5NKWBXGYPjIAzeYWbDlYjNWzorHzeCme1qgRJJcw82BbPzd/mYR32g+QIiLAE2tTtVDJJXATuWDnUR3ujFUgboQfsnUGpOZXYv5NYXjprhswNTqQPR/C8Z+9LRJ7n9HwReiV9Zh9oxKxSjmaLK2YpPbH11az24cmKiFz59On35woQ2Z6LV6bPRpPatR41yrS4sN9cO/YYLiJXNiM05ggT3z22zkAwy/Nt0wvQHKiig2P37KvoINQ23mcT027ujjj9d1nIJW4Ymp0ILYfKsT0mBAm1IS09tMaNd5JL0CQdUxWrFKOggojnvs6B3fGKnBnrALr0gtYTVbiyABWi/aURo3tR3UIkktYOlQpd8MrP2tRXW+2s28R0ufDnJ0wTuXDInLhvlKUGpqgN5ohcxfjhVmjMCs2mPn0CV8Q2gs1wSzZxdkZyzVqfHFUBz+pqEMqsbsasvbMiuWbKyICPPlO5LQzLMook+g6TXkKpsw9TTG2fz9dqdUHcKl7dWOG45nFl9NlPhQhodY7SKwRQxKhzmyjNfIyMcK/+zv1gtILjdiYXsAsPHrSMWZ7YWk/lDpDW4m3fslHbnk9FsSHdYg+pOVXYle2nnVmzrf6wH16WIcnrUPSd2aVoNTYDIVMDEOjBa/8rMWIACl+OFmGuqYW5JQaMcLPg695ilMizuqztTZViy0Hi1mh/ziVDw6frWIpUCHdU9vciqTRQfhwXwFyy+uRV1aHrMIqbLSOTJoxiveByzp3Ac/MFGO7tVbsxhBPeLmLMfWNdLw2ezTujFUgOkDKe6i1cgiWu2F7lg6fHtZB7i6Gn6cYz32dgyc1alZTJqRGl2nUuEnFi7Iakxl5+jqsnhWNRksrS/ktSuQjHv+aPQa/lxjwbnoBDhTUYPtifr7llgVx8HITYe7mgw7nadY1tyK3vB7To1uZSJk/aTifLrVewP08xZBKXPjIpsQFS5OiECSX4Lmvc+Amcunwmig2NGPRZBXKrZ2LBTUm/DkhHFsWxOF8bSP0RjP+MNod8eE+zMPNNlU+f9JwhPq4I6+sDlXGZry++wxWOTthhI8H7r8pFF8c1WF0iMzhZA4hegoA+/IrmeVGmaGJTYYQjI71RjP0Jgt6Q5mhCSdKLnQQTsIXnGC5Gz/1oLoeGzOKkRDh49A6JFtnwO7cUmzuRCR1R18INeF8BQsgqksjrhUk1ohBh1CE3hkZ2kp89lsxUk9XIdk6m7KvR2HNig3GamNzj7zW3kvVItGmWFkYywRcGkodEcCPIqppsMBkbrWrgfvw1zOshis+3AeZhbUYo5RD4SXBJ4eKMcx6HH+ZhNXG1Vl4A9W92krs+L0MT2nUbDTR/TeFsour7fitNd+fQkyIHIfPVuGTwyXQG81IthrZbt7Dn7PICUg9XYlnb4vEHeNCMfWNdCRr1BCBT3UKdXOHCqowL06JnUd1Vn8tXgyamlsxY5QCY8O8cbSkFlszS5gQe2iiEpqRAUjNKWcRMyfwdVRb9vFCbRjA/MeEx+TllDxsWRDH5pDGKuXYvjgBX2fpkJ5Xgac1asyOU2JvXgVLDcMHSE5UYW9eBZITVTBa2tjzJQg0W6EGXBIP86z7CvVxx79mj2Gio9LYjDtjFXZDzf1lEvxwsgx55fWID/eB6zB+/mpzy0W78VctrW1IGh2EEyUXcGukH2bFBrPI3Y4lCTheXIu65lZ8cVSHB29S4qGJSpws5ycYjPCVQm80Y8X0QDuBKETVbJsKBLH5pNUUePn0kbghkB/LI6T1eiJQBD+zMkMTth0qxKaMYqxHx0gXwNeFSl2cWEp9b14FHorvmEKMVcpR12SBydLWqSn1taIvLIAIojeQWCMGDWtTtXAF2CDxzgSbcAG0rbHpjVDbsq8AQXJ3hxceYfD02lQtKuoauxz6LpzzxvQCbLM6+8cq5Uyg2UbWbL/Nq6ypNIGJEf6439AEk7kVu07ydh1FlSaMU/F+UOusomZpUhSb3bkxvQB/uUUFkTPvlC90KypkYlSbzJBK+I+GeXFK/iJubSIAgJaLHB68SQmjuYU1Xwj1T0umRWGMUo6sEgMAYO8zGvxw/Dwblt7a1oYRfh5sCsB9E5QYHybHvWODUWZoxjqrH9t3v+swNSoA5tY2TB8ZAKmLE8Quw5BVVM06VZdp1PCXilj3qtB5u1Sjxu/Ftbj/plBE+kmxeIoEeWV1eDe9AN4SF5ReaESTpRW7rbV3K2eMRLDcDXoTb+2gN1kQ6uMOo6UNueX1mBodiPfSCxAoFUFvsmBFUhSWtRsyLkSChJmrgieX4Ev24a9n2MzTZKvdiCBoskoMOFBQg48O8NYtkX5SjAiQIjEqABnaSni5ifBySh7GqXxYk4WbyAVrvj/FGjteTslDTJAn9EYzVH5SnLvQiF3ZesSH+6CoqgIxQZ6YpPa3S7XHKuWX5p1a075PubiyyJrwurOtvRL887p6rwjPB8A3xejqzKyusbPXf7JGjWdvi8SiWyO7nHaSGBWAiADPTo8t0N05EsRAg8QaMShgH/qJKsSH+yDWOkqoMxzVmfWE9alaZBXXwtjUAsA+UiBcpIUB5b4evOdZ+6LtMkMTvs7SoRWXRJPJchF+nmK2ja1QEy48nX2bj1XK7S7Yo0NkLJr0wM0qhHm7Y7Z1TqggGBbEhzHPNQC4Re2DAwW1eGRiGKQSV1ZDJ5W4YGNGMe6/KRSGRgve33cWNQ0WzJughNKbF3f8fVywZBp/If+tsAqG5ov47FAhwv088fruM7j/plA2RqjJ0oZFieE4Zk1BLtOoIRU5IzWvAk9p1CxlmaxRY9uR8xjh447Xd59hHbkrp6thaDRD7i5mkbAnNXyh/MGiWnCtLXx6VeWDpNFBSP40CzUNFtwZq4DJ3IqXrXVkj0xSwV8mwYkSAxNaAC9I3kvV4tPDOpY2VFiFmpASFeab6k0WxIXJsXBrFl666waE+rgj1Med/V9g0a2RMLVy2HlUB6mLk52gWZEUBScAE9qNdxLsX+6/KZR5tW18KI5FPeXuIowN82bO+kFyCaZGB+JgYTV2/F6GmCBPFFU3IG64N3Zl65GaU46XU/JYhKvM0ISdR/k0+R+tAsmRGa4ttjVuwmuvPUK6eOEUNdamarErW4+/3KJyWJPpqHmjJ7VMb/x8GjNGKTArNpiJ3mydAb/mV8IJQFpeBbOiIYjBAIk1YlBgm4KKq6y/Kh/Sn+wvxJ68CkQHeSI2xBOGRvvaHdsB2XqjGXMmKB2O1tn06xn8ml8FvdXs9KMDxVgxTe3wItW+ALwzHpkcDqnEBeWGZmw7qsNrs0ezxyAiwJOfkTk6CIbmVri5OPHjjwA2J1Mll+BAAW8/IszkfDkljxno/prPTzoQXPVz9XV44GYVFt0yAiMCpMzENyLAE20Ath05D4VMjO2Lw7FyOn/xPltZjxMlF/BOOj+94L44JZpbWnBjmBz7z1Qht7wec8aFwNDceinio1HjZLkRK6erESCTwNTcihpTEzZZ6+BWz4rGhQYL3k0vgKsTX4/2wtcneWEXxgvcxVMi8K+U02huuYhfTldg1cwohHi7I1Ypx7upWhaJ9ZXyhrYKqciuo1NgY3oBFieqWAruL7UN7BxXzYzCmu9P4c5YBYqqGjA9OhBydxH+lXKaFfOvSIrqMOZMEDZPWxsSbL2nTuoMiA/3wbYj57Fyupo9/8FyN2RoK/GvlNPQG81IGuWPe8cqcNFqFJycqEJyogo7T+hx/wQlfKQizLkxFIlRAfCXSVjn7jiVD24d6Q9PkXOnAumT/YUYESBF7nkDlkyLwvHiWsQEebIO4c5el8K6ejJ+rbfpxB+On8eubD0AoKjKhM+zdGiwtKGu2YKfcysAADNjArFwa5bdaDGCGMiQWCMGDbYeZFeDGmtheU2DBUmjAjA1OrDDNrZdco5G2gTL3fDErZFQSCWYHafEjixdl2NzYpVyLNOosTe/ku8yTdXC04F/0zvWFPDSpCi7+jeAHyw+NToQ/z1UiA8yivHsbZFIjAqAl5sIwTIJ80YT1rZ6VjQemRwOfxlvKlpjsqCougE+kmEYHSIDYEROqZH5y62crkZMkCeyrRGq0cHeWJwIfHuCj+a8lcanSn1P8eeRNMof+wqq0GRpxYf7iyEVuWLLwWI8pVGjtrkV76UXYEmiitW6ZZ27gF3ZeizXqJn9RrJGDa2+jh/8foQXnIL9x/bFCThbWY+IAE98+OsZ+ErFbMD9nAlK5h+3Y0kCS/k9aRVLQhMFAMyOU2Jtqhbz4pTQmyyswzZAyqcGY0O9kazhZ11+fLCQj2RVNaCmwYL16QV4PJEfE/VddinGWmvUFt0aySJMwuvjk/2FuNDcinetBsCr7xyN6nozfjldgZoGfh6nTckcygxNWLg1C8/eFomMszVoMF9ERkEtZG6uUMjEqGhowYGCGtw7VoHZVmEpvCcEofZySh6LXAqu/u07PIWu19zyehbZiwnlX1eCSO1JRLqva7taLnJ4SqPG2DA53228pwCldY3IK69H0qgAfHpYh59zK7BosgobrCUAvelW3bKvALfHhlC3ItGvILFGED1EuOiInYB7J3ReVwN0PXswWO7GIjbdXUTeTdVij7W2SkibChdOQbC9k6rF78W1zJjXNhokpGaTTRZ8kFGMxYkqfHK4BBMj/JlVg9xdhDlxYRin8kHphUZm6QDwF/cQb3ek5VfapXZH+Hngf2ZE4+CZSiyZFoWLbXxh/zCrx9f6eeNQWmeGydyKl+66AbUmC5ycgDFKOTam89Yh5tY2vHTXDahrtCBplD/W2QgxoUtXaBYQO/ENCsLYJWNTC3LL6zFS4cXWLQx3b27jR0tNfSOdpWlfmz0axYZmVg+VrFHj8NkqxCrlTKgJUTCAF0TCUHi0tmDnCT18PUSYM0GJl1PyYG69iNd3n8GWBXGIVcrx54Rw5JYaUGuywAJg51EdQuUeWD0rmqV/M7SVMDW3shmagnD68EARANilI4WI4PLtxzF3gtIuOiTYthwqqEJRdQMAwNdDBF+pCB7iYQj0cIXeaMY3J/Twl7rh5ZQ8O5sX4XUj/KtwYMVhe/uccfwXFQDMtNdRV2l7OnOoF3wN16ZqER0gZUK2J6xL1eKrozrcovZFRLMUJ0ouYEF8GLZmliAmyBOGphYoZGKM8POAt5vIzuevJwiR1rpGM1R+nig1NPfaloQgrgYk1giiF/QmStCV2W5PGRsmx7p0vmj+6aQoiIAOkbU/xSnxe3EtnrIOSbdl/qThrNZKMLF9IpEf9r19cQIb9i3Up9l6b8UE8YXcs2KDUVBhhN5oxi1qX9Q1teCJqZHYl1+JdekFELk4Y2lSFNxEzvgum5912WRpxa5sPRt99JtVTD6tUUMhE7NmAiFatkyjRk6pEcFyCYvavGvT1Zk0yt86eL4Sc8YqsDGjGI8nqjAyQIqnNWpsO6pDUXUDm1wgcb7U3CCkfJ/7OgcVdY0I9HLHMRtxu+jWSGgrTdAbzdBWmjALfMq2poGPpsWFybExoxh/nKDErSMDoJCKUFLLH0sodheEr9BQIjSBZOsMTKi99Us+5owLsZuh6erijBF+HsgsrEUbLkXAygxNmBUbjB3WdG17quvN8JdJ+IaFRBVqmy9i25HzWDSZf47jw31QVN2AcSofh+ajPe3s9JdJ8Nu5Gnx6mPfHmzdBiXXWiRC2bEzT2n2B6cyh/sNfz+D13WfYUPX4cB98l12K1XeO7law7cwqwVfWqQ+BXu5M7Aqp/L15FVD7SpEY4Qegc1/Drvb/mzXNK7xPNlm7Y0mwEdcbEmsEcRUQLkpA700y19rMFUyMCrCbE+qowzVY7mY3hNyWzXv4xgvBngIurszsVth+Z1YJTumN2JpZwsYTxYfzTu9jraOeyg3NeG32aJiaW/FySh7Gh/Ii8imNGgunqPHJ/kIEyd1R02DBv2aPwRm9EevnjcPZShPmxClRYWpGYoQvhjk7YdEtI7DzeClWTONnoq6aGYW4EX6oMjUj0k+KsvBmJths/10QH4YQuRv2FtQiaZQ/Psgoxp2xZoRZrSmSNWpMHxmAttYWJEQG4LvfdYgJ5Yv/188bB4VMjLzyeuYbtkyjZs+N4Nf2lLXbMTEqwM52Qyion7v5IJZp1Mgt5wfQN5tbsOAWfobmzqwSu0kVtvWGRZUm1DRY+AJ/a1ctcCltbjsBw1boxCrlrIBeQNjv+nnj2EzP9fPGwcXZCR/uL0bSKH+MCeIFam6pAfMnDWepV6FZpafdkkVVJnx6WMdeDxxg93oE+PFc69ML8MvpCmx8KI5FBh2JxDvGheKTwyWoNTUjJsgTEf4euHm4b48ia4L4so12jQiQImmUP+LC5B26pHuKMHi92MBPOYgP90FyogoKuUevI3MEcbUgsUYQVwFBBLQXainZZRgb5o3tWTqHFgWO5lA6apZoH8no7GIn1MIJ/65IirJreigzNCG/oh5bM0swd/ylAvBFieGsMeG9VC3esQq+pUlRrEjdVyrGnLgwVgMVH+7Dm95azYaf1qixLr0Azk58w8FTGjXWpZ/Bimm82LktOhDbjpzH6ln8sPVtR85jqUaNYLkECxNULPKy0Vr/9d0Jvqhcb+THeQnDy7POXUDSKH9o9XUsTewMYGNGMVZOV2PLgjjknjfA10OEmgYL4sN94CsV4T4br673UrVMqAkCS3jchZSwMKTdz5Pff5zKBzdamxgAvutXIROj2NCMMkMT2952MoDw2NkSEyLHfBvhZCt0bLtGBcGWW8o3HizffhxbFsSxlOinh3VYrlEjLa8CflIxixwK3clFVSas3VPABF53TSsp2WX4PEuHxxNVqGloYSKXA+DlJmITH1pb+dTjZLX9KCdHr8nqejO2L+aF7/YsHTNe7ox11udFoL0YE+57uQ1FG9O0WLunAGaOr+2MCfJEVKAU0cHePfJIJIhrBYk1grhKOBJq/0o5jdljFXx6pbUF8yaF213UHFkZ2EZBbCcv1Jtb8HBCeLdRCUGolRma8GWWDuPD5Ni8R4sl03jj0+G+vAVHoBdvNSF0dgr7bd8ZKVzEakxmNiMTAMapfPBrfiXui1PiWHEt3rF6pr2ckoeV09VobeM93do44LXZo5Fxthpzxwej0dLKImg+Ehe8l17Ghtr/94iOjWp6SqPG+bpG1DW1QOI6DCIXZ8jcXHFbdCDesRrg2vrIPaVRw13kgjN6I5uzmRB5yQD5u991WDLNflD70qQovHTXDezx/vzQOegNDdh5Qo/3HpgAgB+Qvn7eOIR4u9t16tY1WfgUbXoBak3NeOLWSDsx1L4pRKjZen/fWUyPDsTcuI7i+/bYENRZ2lBnaUOZoQmHCqqw5vtTiA/3wcIEFRZuzcLeZzRMxMyJC8PUkQFY+tlRxAR5YmyIJ3Ye5Qemf56lY35nnaVX28ML4xbklddjcaIK+wtqsSG9AKf1dXhiauQlkeTi2qU/GsBHeU+U8V3EtlYpnSGMHuNgb2XTnivp/E6eHsX+dQIwbSS/L/JoI/obJNYI4hoR4u2OW0f6Y5O10L/5Ih9paH+Bay/U5m4+iCc1aowPk7MOzGSN2uHFsczQBAD4KbvULnVWZmjCvPcPshonwal+ybQo6E0WjA6RMcHUPs0FAEFyCT7ZX8iK5T/89Qx+yNFbB6jzQi1WKcd+bSVLy373uw5Jo4NwqsLI5pHOm6DEk0lR2LyH99969rZIiF2GISbIE3FhcvxeYuCjGwov/HSqAreofbHtqI7NJJ0zLoR1KALApOE+WLuHn7rgI5XAXeSCn6wpVqnYBS+n5LE6OS93EeqaLHYzUgVhl2yNGqZklzHrkkZLK/57RMceg7omCxZuzcJrs0dj+fbjeOmuG7B+3jjUNVmQrTNg4dYsxAR5IibIEyfP13X5WhAE4l9uUWGq2gdfHOVnnNqmDssMTXh5Vw4azBdRVN2AY8W1uHdsMOLDfXCjio84LtdcsnwRBJswoeG733XMV2+pRg0O6BC17YpZscFYUWVCVYOZPd7TogMRJJdgfOilaGF7z0JHvJeqxTZrvVmUnzuL2nbFH+OUaAPwXnoB/tSNELwSBMHWlSAkiOsNiTWC6CM6634TEC5uflIJnAHMiAno9ht8XZMFD01UsmL7RYnhdvVN7Y8vDJjmi/zbWDQsWO6Gf80eg19O6aHy82R2Idk6A0sdCrVhtjMnAT66dLbahK2ZJThVYcTy6SNZ1HDOuBDUNLdi7uaD1jQnLwZchznhrbQCmNuAHb+X4dnbIrE27Qz+NXsMPvz1DIt0NbZyeH03byMhRPTaWlugkkuQW16PpOhA6I1lzDZlTKgJY0K9cFt0IHbn8SnQ1bOicabaxDpIZW6uOFNtQoSvFPHhPmgFcIvaF3pDA9Z8fwqrZ0WzaKO7yAVPadR40poCbbK0YvWsaHx4oAh6oxnLNWrWhZtdYmCduC/ddQM27j0LXw8RcsvrsWVBHBv7JAyw/zpLh9kORIbwmCdr1GzEE99AIenwnKaersIyjRqZhbVYMT0Sz32dwyKNyRo1jhTX2tU4CgTL3bBkWhS83EU4V9OA96ypZKH2rKckT4/CO6lafsC6myvui1MiNaejdUxXpGSXYdtRHUb4eWDOBCU/Mze46w5Q27mkyRrHHoTCvmfFBvdJMw/RM7r7nCOuDiTWCKIP2JlVguLqevhK3ViUyRG29UudYZv2TIwKQO55Ptq0N68C0QHSTqMi27N0rBMQALYd1SHcxoxU8FazPX6sUo4tC+LwYUYhdh7V4f6bQu0mKbybqkVNoxmfHtbhoYlKyN3F7INasF8QOk1lEhfcGasAx/G3WVo5lgp1dXGG3mjGiRIDth/VISbIE61tsOv4XKbhRy8JMyJXTOO90xYLMzo1ajZOTCET4xa1L3b8XoYRAVIAwJ2xCnhLXJBZWIuFCSqMDZOjBfwxFiao2H5fTsmDv4yPwr2ckofVs6KRrTNg094zSD1dhVUzo5if3BdHdXhh1ijmPRdkU8Qe6uOOokoTHpnkwiJLsUo5Pj90DtklBryTXoALzRZMCPNBQaWJFarb1r49v+MEFsSH4efcCsQovOwugra1a7da6wzVgTKUXmjk6+6sI8G6ipbpTRZMjvRHiJcbpBIXuFzG8PE/xSlhaWnB99l6VNebeyXUAD5C12RpRbmhGUuTojoY5Nqm0m3XHuHrgbnjg+Elcna4X2E26rJKE7KKa9FykevWUoe4Mjrr8iWuPiTWCOIKSckuY92UMUGeOFVhBDD8supebIdrr0iKQpmhCUumRcFd5OKwON0W4SK886gOSaMCkFlYixBvd7tt9lnNdW3JK6vjU6uJKuwtqMXZynrWWLDOKsQUMjHcXJ2hlEuYPUVKdhmLEB0rrsWrc8NR39yKd9IL4CPl/di2LIiDqbkV2ecv4P6bQrEuvQArpqkxRimHyTqpQBBiXx69NDtTGPy+VKOGvq4RueX1uP2GQPz3CC/0guQSBHq4IibIE2f0RpwsN6LGZEGjpZXZgTS2XMSv+VVIGuUPD7Er4sN9YGw0IybIEyHe7nb2GbFKOZ6YGonbovlh55HWmZyC71yZoQnrU7V2fmdVxmacqjBix+9lbKSY4Gu3TKPG09bU4+dHSlixv61gA4BX547FoYIqeEtEnXb62m5vK/ZnxQZjRICUpUTb+6XZzt1cYU3xbkwv6HKagCOC5W5wdeW929IcvH66o8zQhOe+zsHeZzTsvAFepAHAyyl5qGtu7dB1uejWSKxL1XbqWXim0oT4cB/2urkxxBPz3j/ILGmIvqezLl/i6kNijSCukFmxwcivNCEmyBNTowM7jJjqDX6eYr6mzBot2WitY3JUnN5+dBHACzYvq99Ze4d529FKgnN/maEJi26NRMtFDp9n8Rc9LzdeaC1NimIGr0L6SoiCAXyN1HoAhkYLMgtrsTevAkuTouAjFaHWZGEdpOEBUoic+Y7QZI0arsOcmDlsTJAnxoR6sfqtXSf1aGi2YKPVO2uHtTheqDkTzmNqdCA2WoWfi7Mzakz8ORRVN2CEnweLysUEeeKmMG/cHhsCNxcnNlD+44OFeGbmKLi6OGPN96cA8DYax4trka0zwNTcCi83ERNqL+/KQeppfuSWINiKDc3Y8XsZ4sN9WDSyydLKhKdwrg9NVGKCyoeJESGNJAx/vxy7CdtoaWJUgENj2/bNKrNig5kZb29x1PjSU7Zn6fjRY1k6dn+hg3j1rGgs16jxhfV5XmYVlQBQbmjEu+kF8BQ5dxBs76ZqscH6evSVipB17gK01Y29Pjei95BQuz6QWCOIPuDppCi44JII6g22A66D5W6YHhOCi+DnnHZm77HTGk0AOnad1llnE7VPjz3Z7t8MbSVe+Pok5k1QIjWvAu89MAGlFxrtBJ4wxFwQAiuSouz8rGbFBiNDW4k7YxVs/FaojztqTRZm9SGQrHGF1CqYnr0tEqtmRsHQaMamjGLMHR+MzMJa+HqI4OcuYmJLEHD3T1Bi496zbAi9YJSr8JJgbdoZ+HqIkJyoQoXVYsJDPAzx4T7ILKzFmFAvNo1g1cwoSCUu2JWtx80qH8yfNBxNllbMnzScTRPQW2ei7srW46W7bsDU6ECsvnM0ohU6hFobLR6ZHG43j1aw2fguuxw1DfzM2GPFtUzcrpzOe9HVNLeipMaEGaMUzHrDUXH+2tRLQ957gqMJBI7u336ebW+43LFRjoSe8OXD1cUZrda/rU8vwDAn4JfT/MSO9fPGYdXMKIeRNdvX8if7CyF2ccbYEHmPzHUJYiBCYo1wCBWR9p7LEWpCqso24hGrlMPPU9zp4y9c9BxF1gBePAh1ZPNsvMRszzFbZ8Bbv+TD10OE7dbi7z35lXgvvaCDrYOtUAPsva6ydQZ89lsxUk9X4c8J4ThbWc86Vpdq1HYjhYT1NbVyVgf7M0ga5c8c+HPL65Gs4b3TZoziZ4juOqlH3HBv5Ojr4OshwugQGYJlEpbqjFF4QW80Y84EJROwD01U4mxVAzILa7EgPgzDnJyQW16P+28KxclyI56ZOYo1CFSaLDhXY0K2zoBxKh/4Hi/F3WMVOFnKz8PcZ7XK2LEkAedqTHjXWi9nbr2I6GA+Iih24gvxIxUyILscI/w8AABF1fw5xAR5Ir/KhKKqBjZn84ZATz5aaI1iOnpNCM0MPRFJghVLVwgp2rpGS4dtd2aVoNjQ3OdzPAVs9yt0LLe2teHl7/OwamYU5oxVYOcJPUb4S7HYn69B7C4CKLyWH5kcTp9XxKCHxBrRgaFaRLo2VQtfB0PSr+bx9uZVIDlR1aG2rLvHvauLqlBX0tV+YpVyLJ4SgaMltdiaWcL+/uxtkZ2mcNenaiFv9/ik5Vci9XQVkjVqFFQYMScuDEWVJvhKRXjP6n0mRMFW3zkaP2WXYoNN96mbdZboco0a998Uio3W+xw6V4sbQzyReroKYb5SbEwvwNzxwQjxckdNoxnfndDjzlgFnADEBHnCV+KCP01QIi2vAp8e1vFRN5kY5tY2/JpfxexKFk1W4UTJBUyNDsRvxbVsfNHNKh/EhMjx0j1jUHqhEc4AbgzxhELuwaI1z8wchQhfKVoAvL77DJ62aYIAADMHLJ4SgX+lnGaPz4L4MHhKRBgfJsfOY+cxNToQJTUmXGzj8N4DExw+1vPilLBYWnChqQXTR3bvIbZ5j5bZkHT1uogJkSNZw3vXuYsuPY/CmKUdv5exbRVSESpMFjydFOWw27Q3CBMCgEufLQ9NVOLTwzoWOcvWGa7IiHYofU4RQxMSa0QHhmIRqRDNSBrlD6CjgenVwBlAbnk9pkYH9rkJZ0+eO+HC6OHiBIXcAy2tbZ2ue721RujOWAVgTQNmaCtZHZtKLmGjlh6ZHI76VC0UMjFuDJMjOsgTd4wJRnW9Ga/8rMWzt0Xik8MlUMn5FObc8cH44qgOo0NkeDxRhQMFtfCVilj35t68CswdH4wdv5dh7vhgHCioAQAUVTWw+aPHSg3Yla3HUxo+ZZZ6+pJAY2OrElXYeUIPtb8nquvNmHNjKMQuzhju7Y6YEDkzuDU0WiB2ccU6ax2d0HDxU3Yp1qXznm7JVvuMFdPUiA/3YfV+yRo1ti9OwE/ZpdBWmeDnLsKSaVHYsq8Au7L1eFKjRlFVA4qqGiCyNjY4eu4eTghHdb25R6+Lu8crUdfc0mVXaLbOgJ9zS3GylPdLezklDyMCpHY1c7YzU4U0cG+92WxZm6qFC/j0JsBHH4PlblimUbN6s7gR/BzPnnRJE8RQhsQa4ZChJNSASxeiaxlZs51HeSXszCqBztAM5WXMRpwVG4yQTtzsywxNTDDcF6eEubUFvu5i9vhEBHh2qCmaExfGGhmSRvljhI8HpBLe2iJbx1uQTIzwh1Tiiklqf+itAg/gBdbK6fy+dmXrkTTKH1IXJwDAgYIaxIf7wEviyrzNfD1EmDs+GIFe7my81TtWC5CaBgt2ntAjWaNGSY0JCpkYLi78fZ/7OgcKmRjvPTABUyMD8K+U00iIDMCOJQnILTVgzfen8NJdN+BpjRqxYXK88PVJrJgeCTerJ5swEzVZo8bkqADcO0GJs5X1yCoxsNfRwilqlprL1hnYY9RoaUNueT1igjz5tGknCPM1e4Ig7kSizm05YpVypOVXMkPl9mOehNdNmaGJbwiQiqDylTKj2I3W4e09nRZgW1e5XKNmkTWAb9C4CL5xRfD1I6FGEF1DYo3ot1zrOpSrVa/TFZcr1IR5lRn5ldh2VMcEDNBxfmJ3OLpQrk3VoqTGhBqTBYsSw5EYFYAHbUZjlRma8GlmIT7cXwy5uwhz4sIwJy6MjQh6SqPGRfCDthduzYK/TILEqADMi1OioMKINd+fwipLK+LDfXCgoAYzYwLhJRHhv0d0uEXti5oGC8YGe+GTwyXQG81QyMTwlYpQaTJD5ubK6tKEeZXP3haJYc5OWDldjbfS+IiXsxOYg3+ydSC3OkCKf6Wcxorpkaw2MG64N6sRLKgwIibIE2IXZyxNisLGNC30RjO+OVGGouoGLLplBGKCPJGr5ycUVNQ14oGbhyMiwBMnrc+JwNnKepwouYDl249j1Uy+pi0xKgAtABM+ts0lXSGIqM5eo8Fyt25fvz3p6HS0nxVJUb0SagCfyr3Y2oJvT+ihtvrgtb+da23BTeH+HV5/61O1iAyQIq/S1KPO6nWpWmiuoAObIAYCjt0GCeI6I9S2CMXIxCWydQZ8d+I8ln52FNus6UNhQLm/rKMLvoBgidAdtrMyMwtrsfPYeSachefjiywdPtzPpxgFcbh5Dy/UntSo4QTejDa7xMA6HrfsK8Ca70/BTeSC12aPxu2xIYgKlEJvNOPn3Ap8YW10uGNMMOZMUOKttAI8eJOSF2oeIkT6SbErW4/xKh8cKzGgqLoB8eE+uEXtizJjM175WYuLbcBDE5VYu6cAJ8rqEDfcG8usadB3U7WYFRuM5KkR7Jx/OH4eWecuIDWnHAAvdB+ZpGID6tfu4SN2oxSe0BvN8JdJUNNgQZi3O1JPV8F1mDMKKozY9OsZrN3DHyMluwyfHzqHDzMKsXz7caycrsYrP2vxwtcnsXkP/9ie0RuxNlWL5duP45P9hVhn7f50RJmhCf85WIiN6QWsS9TRa6InXO4XEkdCbUOqFjuzLtU7fn7oHFtHsNwNM2JC4Oshwtgw7w73DZa74f5J4R32K6Tb88ouYGN6AVJOlna5trWpWhwtrsXczQfx4a9nerWmbJ2h08eTsIc+h68/FFkj+iUDoW7uciJ/fTEWJy2/ElutPmQb0wswwu8i64aMCPB0eJ6HCqrw3Nc5eMlq3WBqbsEd40Idnv8Km9TXco2aDRgXRMPDCeEsPWY7T1HoMIwJlcPLTQQOl4a/p2SX4ePMYjxpHSQusHByBDwkIuw8qsOfJiixPr2Ambwma/go2dMaNXbnVWDtHj5i9svpCgTJedF071h+X9+c4CNsOfo6pJ6uYgXsQtfok9b0pa9UhDXfn0Kojzu83ET4/bwBeqMZ9c2tbHKEIOQemRwOc+tFSCWueCe9AKtmRrFzL642sZo4H6kECqkET2nUyNXXYZ1Q2wdgcaIKKj8p5o4PRpmhGW+l8bf9eqYamYW1iA/3QY2pic1qdRRp7SrNma0zIC2/8orSiYLfW2/YkKpl3mgAYG5tQ0ltAz46cGkdsUo5Nj4U1+l7xNHfBQ+7yAApkjWuXUbWMrSVqKhrZDV2r+8+A7HLsB6VMWTrDEjLLWWP+/WIqg8UhmrDWX+DxBrRb+nPHwyX8wG2eY8WFSbzFQs223TW9JEBzGW/s8Hu894/iBF+HkhOVGHN96cQE+SJmgYLTM0WzLNJbdoSHSCFQiaGOkDKbv86S4ePDhTDQ+SKJ5OimFCztY2ICeVrvEaHyFBuaMYc6znlVZoAoIPJ6YmSC1iRFMVqBdU27vpuzrwZrsjFCY9MUsHc2oYLDRa+KUPtg9TTVcg4W42scxcQN9wbvlIRdmXrsSA+DFnnLmCpVag9e1skXt99BiunqzF/0nCE+rgjMSoAnx86B4kr78dWUGOC7rdG2E6eSMkuQ4mhCWFysBqzbJ0By7cfh0Imxp/jVUwwK2Ri3q/udBVWz4pGqrU+DACkIlfcMSYYpuZW/M+MaMzdfBDr543D6GBPfJ+tR5zKB09q1B2Emu2XAUfpyWydAW/+ksfq0Hoq1NamauHmDIhcnBGpkLHh9L1Jn7cC0BvNmDuef67mTxqOzw+d67COy3kPC4JtVjfbJUYF4Jh1XusIXykbCdYT2GN1GeO3hhoD4YvzUGBAiLVz587h5Zdfxp49e6DX6xEcHIyHHnoIL774IkSiSz5F2dnZWLp0KY4cOQJ/f38sW7YMzz77rN2+vvzyS6xevRrnzp1DZGQkXnvtNfzhD3+41ksiBji9/QArMzThQlMLPj2s4wd4XyHCBca2i87RuQTL3bB9cQI/N9RmAsESa1Sos4uVIJhso2BLk6LAgZ/NKYgwwTYC4CNrJ0oMSBoVgE8P67BlwaWoinAML6tQ25lVAjeRC5ZvP44VVSas3VMAqcQFk9T++GR/IbPqmDNBiYkR/ii90Ijnvj6O+HAf1tWpkIkhts4cFSYYPJ6owgfW+ai/5lUgaZQ/LrZxWD0rGi+n5CFAdqkJQzDEPVluxJggGeJG+LHHMltnQF7ZBWw7ch53xiowZ1wIEqMCUGZoQny4D25U+WDhFDUytJVQyMT44wQl3EXOiAnyhL9MgkWJ4Yjw94DMXYyYUPt6L+F1MzbMGx6urg7HTGXrDPgltxQBUrdOBUisUo7/mRGNtPzKHgsO267n1NNVeFqjxnKNGmvTzrCRWd1RZmjCRmv0cGyI3O7xvFJ6G61enhSFYYDDx7A7qAO155BQu/44cRzHXe+T6I6ffvoJ27dvx/z586FWq5GTk4NFixbh4YcfxptvvgkAMBqNiIqKQlJSElatWoWTJ09i4cKFeOedd/D4448DAA4ePIgpU6bglVdewZ133onPPvsMr732Gn7//XeMHj26R+diNBrh5eWFuro6yGSdd3MRRHu6KxK/2gh+WTuzSrA27VJ9T2d+X7aUGZqwI0uHZdZ5pbYf3raRNcE7LiHCB2p/T4fRGsGcdblGjbS8CsjcXDFpuA9OlvMpzC0L4lBUaYK59SJe332GdW5m5FfiHasPW9xwb4TJ3ZE0OgiHCqqwNu0M7hyjwEcHirEkUYXNGcUsFRoT5IlHJqkA2DdflBma8FWWjg1Jb4+QYrSdpVlmaMKH+wpYilUYj/T+vrNsQoIg4rJKDNhoHSI/OdK/x6nGMkMTth8qxMaMYixOVCFE7nFFQihDW4kTJQa0AEywiwActtp0CDWBi6dEAADO1zZ0G/kVapj68iL+yf5C1JiaOo32EsSVMpCv3wNCrDnijTfewKZNm1BYyA8D3rRpE1588UXo9XoWbXv++efxzTffIC8vDwAwb948NDQ0YNeuXWw/kyZNwrhx47B58+YeHXcgP9l9DbmGD1xSssswNsy7R15eGdpKZBVWMc+yrsRm++Hhjva1cGsWFiaocLioFjUNFuiNZixOVOHbE3r8OV6FV37WYseSBGQVVQMA4kb44XhxLV5O4d3uXZyd+bFQRjN2LEkAAMzdfBAKmZjN40wa5Y9yQzPuGK2Ar1TcQTQKaWxhnmt3AvrzQ+eYYLIVrgJCJOyBSfwUh4Vbs5CsUaO1tQUfZBRj5XR1txMG2p+fYKFxpULtw4xCGJtakFtez0ZwrZjG246UXmjE+doGhPp44HxtAxPHj0wMw8QI/w5itTfnvzNL1+OpHp8fOgdtZT2LPFNqkrgaDOTr94BIgzqirq4OPj4+7PfMzExMmTLFLi06c+ZMvPbaa7hw4QK8vb2RmZmJv/71r3b7mTlzJr755ptOj2M2m2E2m9nvRqOx7xYxgKGi04GN7SzSrsjWGfDLKT0/hN06YL6zMVdC+rKzi222zoAXvj6J1bOicazUAADw9RDhFrUv3s8ohkImhrbKhPXzxiGrqBqv/KzFMmstliAohZSgVOJil7bbsSQBx4tr8eGBIqyaGQWjpQ2pp6sgc3PF/8yI7nAuwXI31nxQ02Dp0ppCiAQCfKovWO6GZUlRdhHFg2cq8X5GMaQiV3i5i7BlQRwAYOex85g7PhgJkY733Vlxf0+sOAR2ZpUwa5T2mJpbESyXwNjUguREFbTVjVgQH4bJUQF2j+vOrBKUGJqgkIkxOkQGUyuHuZsPIibIE3vzKgB0P/4pQ1uJvLI6TIzwxw/ZpdhykC/e74lgE2reSKhdfehL9sBkQFp3FBQUYMOGDVi8eDH7m16vR2BgoN12wu96vb7LbYTbHfHKK6/Ay8uL/SiVyk63HUpQ0Wn/ZGdWSY9tHNrfzxGxSjnf7SgTY+cJPeaOD0bG2RqHrfyPTA7H6lnRDi+2W/YV4PDZKuiNZpQb+fvmltdjTKgXDhTUQCETY2ZMIG5W+aDJ0oqFU9TM6f6T/YVs/2tTtSgzNGFt2hn4eYrtzrPR0gq90QxLaxueTorC0xo15t8UhlilnD0mtuucG6fEQxOVeGHWKDuhsyFViwxtJbM6mT9pOF666wa7CJdQq7d5D2/9sGQafzxzG7Dm+1M4X9vITwe4MRQP3DzcLnq5ZV8Bv4ZULd76JR+fHzrXxTPDi9zOrBN2ZpWgoKoen/1WjAxtZYfbpRIX1FmjasNcXPHAzSq78WIC5w3N2HbkPOZMUCKn1AiLpQUv3XUDm7Ahlbhgyz6+NtHRcTK0lfjst2J8crgEXx4tgbebK5I1avhKO84+7Yz5k4aTULvKkCXSwOW6Rtaef/55vPbaa11uc/r0aURHX/pmXFpaittvvx1//OMfsWjRoqt9ili1apVdNM5oNJJgs0JC7epxOd9+N+/R4r9HdLhzjALHi2t73Bm3M6uEjYpyVGNmOzg+OtgLEQGe7NzWpWrtuv+EY35iHUkF8OJEGDM1d3wwEtT+rIvPVyrBiumRqDQ2IyZUjipjMzuX5UlRdrNIbf3fALAxUMKxhCiX8G/iyAAs/ewo8ipN2JhewJoMhHUGy92waIra7nHekKrFepsh6k2WVsyJC+uQimx/rGydATn6OuSUGvGkRs22bx/tEh6LukYzdp7QQ280Y3uWjnWotidbZ2ARrnlxyg7nUWxo5v3uElUObVsSowJwvrYREtdhuNEaPXRk8bE8KQptALjWFuiNZmQW1kIkcsVfblGxUV0bM4rR3NKGtXsKmHee8LxEB0hRbmiG3mhGcU0jimsuWWoAfdN8QFw5vfmSTRG4/sV1FWsrV67Eo48+2uU24eGXLjhlZWXQaDRISEjABx98YLedQqFARUWF3d+E3xUKRZfbCLc7QiwWQywWd3o7MfC5HJ+pq4lQYD49JqTH3Wo7s0rw3yO8Qe6uk3rEDfeGNKukR3YMxYZmvDa76wYbRxEPYVoBYO8P9sn+QiaKHpkczmw6bEcwJUYFQOTMi50Pfz2Dt9J4iw0hvWrrdSYwfWQAPzpKKoLeaHZ4LJWfvVu+3mjGzqM6LJqsQtLoIEglLnaPSfuLkVCHNi6MF47fnCjDJLW/w9o+2xo0YaD9E4kqaLoYvr5wihoX2ziUGZvh6yGCr4cIM0YFdvr6yy3lR3QBwNlqE3a2e05tn5fOLqy2diWA44kVADAyQIrl24+zjuGaBgtmxgRimUaNG8PkWOUuxsIpaoxRyu2EmpD6zi2vR7JGDWOjGamnKzF3fDDqmloQE+L4eO0R6gKvdHA80TU9FWpU5tK/uK5izd/fH/7+/j3atrS0FBqNBhMmTMDHH38MZ2f7DG58fDxefPFFtLS0wNXVFQCwe/dujBw5Et7e3mybtLQ0PP300+x+u3fvRnx8fN8siBhwZGgr8dYv+QAcu7RfD7Zn6bAxoxi1zRfZGKTumBMXhkpjM0yWFuSUGrErW48I345jftpje7EVolY99dtyNNs0JbuMCSxboRWpkGHLvgK7OaKC2BEEmvBvpbG5w7HKDE2Yu/kgkhNVKKltgEImRlaJAb4SF+avlZJdhuXbj2M9+PqqWKUcO5YkIC2/knnQ2a6tM1EgCLYNqVpkFtbiyywdvjqqw/0TlJjtwMsOuCSapo8MwH5tZZciO9THA6cq6pm4uXdC55H6+ZOGQ2+yYGN6AaZGB3b63HQ3bL0nr+1ZscHssVPJJSg2NNvV8rX/1/Z4K5Ki2GOcrTNg9o1K1DVZ4OUm6tEXDqEuUFhrV2shrj5U5tIP4QYA58+f59RqNTd9+nTu/PnzXHl5OfsRMBgMXGBgIPfwww9zOTk53LZt2zh3d3fu/fffZ9scOHCAc3Fx4d58803u9OnT3N/+9jfO1dWVO3nyZI/Ppa6ujgPA1dXV9ekaievD27vzOfULP3Bv786/3qdix9u787nSC429vt/WjLPc27vzuQ3Wdb3bg3UJa99xpLjXxyu90MidKLnAjq1+4QfuxxOldtvsy6/g1C/8wN2zYR/3//ae4TiOY/+2Z1Maf96b0jqet+1z9fbufHa8rRln2TbCsbt7Prt73rdmnOX25Vdw663HUr/wA7fkP79xr/2Y0+Xz8l4qv+17qZ0fX3g8hOdY/cIP3T7X7/RgPQOd/vpeJAYPA/n6PSDE2scff8wBcPhjy4kTJ7jJkydzYrGYCwkJ4V599dUO+/riiy+4qKgoTiQScTExMdwPP/zQq3MZyE824ZjBcnE4UXKBU7/wAxNPPRFqV0LphUZu8qupnPqFH7gdR4q7vNDuy69gAu291HxuyX9+4zal5XP78is6bOtIqAm8vTvfTlTaCjXbbXpy0e9KqD38USYTu+oXfmC/T3411eExbelKqAnYrvtyRHlvOVFyoYOI7m+cKLnAvZ2Sw16/3XEtHjdicDGQr98D1mftejGQfVqIwY8w3/JK6apuSKjxW5uqRUVdI/LK63FrdCBqTHxHYbJG7XD0lXDfPXkVOFZiQKLaB5sziu2K1btDaIboajySUPM3b1I4quvNPXL4T8kuw5lKE5YnRWFjmhZr9xQgPtwHr84dix+On4eplYMLAC+bhoeBwif7C5GaXwmVrztCZBIkRHY+b/Ny6Msas56+fgVz4vYNIgTRFQP5+j1gfdYIguhIXwm1zuqGBFNbocYtOVEF6XBvBEpFGBkghY9Ugo3pBdh5VIftixM6XEjP1zbiWIkBueX1AIBVM6O6FGrtmz8EgWYr1Npf4IPlbkyofX1Mh08P6xyuRSAluwy/nNZjVzZv4SPMprx3Ai84r2SOa08RpiUopCJUmSzsHDrD1uOtK3ZmleDllDx+/FZ+Fe4co8DczQcve+h7e7p6rVwOPT2n7Vn88ypzF1NtGzEkILFGEEOUDalaOxd+Adui8fYkRgXYRcLmxSmxN68Ca74/hddmj2YD4FdMj0R1vbmDWBMsHKpMFoTKJV02M3TW/NFeqG3aewYP3Kyy2yZY7saO3f6CnpJdZmfwOis2GEVVJihkYsglLlifqmX76AxBLO3MKkGxofmKBEO2zoDU3FJsyihGTJAnahosANCpYBM83praAFU3j6FwW5mhGZmFtfCSuPaZUAO6fq10xuY9Wtw9Xomvs3SI7cKMuK+PSxADGRJrBDEEEfzEAHQp2BwhXFyFbeZPGg6xizMTBnmVJvjLJJ1GcHrquZVljcBllRg6XNAFm4f92kqUG5qRVVhl5/8m0H5Yd/uOUYHk6VGQil1gaG7FBhufNUeCSRBLljbYbXu5wqGgwogLzRdx/02hKK5pxNTowC4jayo/KeLDfdgwdaDrDl7htogejo3amVWCGpO5xxHF3gq1t9IKUG/hx3D95RYVqozNPe5AvtzjEp1DfmoDAxJrBDEIaB8tcoSQaluRFMUEmiOhdjkIF1tmBZKowpYFcd1GcIQoS1d2GO0vyoLNQ0trG6oazKhpsGBjRjFcXVy7HW00KzYYyZUmjA3z7nCbUIvGAWg0t+C+OMeWGraGuP5SEfSGBszrZFug65quMkMTiqvrse3IecQEeWLGqEAkT+9+DYZGC3ylIuzK1iOsBxYtwv26Y2dWCdamncGtI/07jbxeCUumReFiG2BubUFMkCc+OlCMpFH+dqPDiGsH+akNHKjBoJcM5ALFaw19Y7s2pGSX4bjuAjzErsylvj3ZOgO+O3EeWzNLejV/8XKew7WpWpYedRRFE1KIQpTlzlgFnpk5qlfHESJrwsBzV3Q+g/K9VC2WWm8TxOTCBBUW3BLe6TF7s+6utu1usL1w/8sZ2m4rvvuKd1O1WJdegJggT8jcXJEY4YuJEf59LqSEc3cFMGVk3zY8EDw9fQ0Ppc/pgXz9psgacVWgb2zXjrxKE37M4UcXCWmx9oLNz1MMbYUJyYmqLqNAtgjPYW+Ha69IisLnh84hJZcv2Hc0UxMAmtoAhUyMoqoGh/VtXSHss7uB5++lavGONd27NCmKbdtZt6pAb86lq21to4NXOrS9/UW1fYq3L3gyKQotALT6OqSerkKEvwc+PliIPyeE9+mxrsa5E5fozecvfT4PDEisEVcFcsC+dggXerET7EYB2RIsd8Orc8ey//eEYLmb3WSD3gi2KpMFmYW1iFP52P29/UxNgHfftx3K3hd8+OsZLLo1EhYAT2vULLIGXPtaJ0GoHS6sAtDzSRm24uxKvvxs2VeAOktbj9e9IikKG1K1GOHrjg/3800PBRVGElcDCPr8HXxQGrSXDOQwKkH0hgxtJXLPG3CwqBYxQZ6YNSYEQM/tFdanaru1oAA6T8NkaCsREeCJ7Vk6+Fr9zXoyx/XDX8/g9d1nLtmL9DIy2N25bs/SYV6cEidKLqDK2Nwj37WepEPbH6e9OLucdJUwOF4hE2POBGWvHocPfz2D5lYOId10nBLEQGEgX78pskYQRAcytJX4MKMQwXIJiqobUFTdgNzyehRVN+C9Byb0SLD1RKgBjiN9QtdmcqIKGzP4IvT65la8k16A12aPxiS1P7Zn6RyKj/azRh1tcznF82WGJnyaWYjvs/XYeVQHvdHMhqx3J9h6azXhKDJyOVESN5HLZQk1ANfEX44giJ7h3P0mBEEMNRKjApA0MgA7fi/DnLEK6I1mFFU34M/xqqueDiszNOH9fWcRE+SJ5otATJAnvNxccbi4FqtnRWNt2hmsT8vHxvQCrLV6orWnO6G2Pr0AGxzc19H+ygxN2LKvAMFyN/h5iDHCzwOjQ2SID/dBbnk9XF2cka0zdLuu7sTShlQtMrSV7Pe+SGHNnzQcyVMjyOaCIAY4FFkjCAIp2WUYG+ZtJxDGqXwwd3wwNmYUI1mjxt68CrzysxZxI/y6FGzvpmoxp5sC/q6orjdD5uaKzMJa1DRYcOcYBT46UAyFTIxxM3zwnk0dXE+bJWzpzLbEkRt/maEJz+84gczCWjS3tOFkeR2C5RJmMhsf7oMak6VTT7mejmLakKrFF0d1SMurANCxrk3ooH03VQtnJ0Aq7tnYq41pWpivcqFLSnYZQrzdqaaNIK4iJNYIYggjWChstNo1bHwojoks/uI7HAovdzydFAU3Z+Cle8Z0K9RS8yqwLr3gsgucY5VyLEoMh4d4GBQyCT46UIz4cF6g+XmK2T79PEd2uf8yQxMOFVQ5rLfq6eQGoTHjp+xSLJyiZl2umYW1WBAfBm2FCWdrTHj2tkiHQq2nzRnOAPRGMwCgqNJkJ9ZsJxYI6dekUf5otLR2OXJKmHF6Z6yiT+d32pKSXYZ/pZyG3mjG+nnjeuTlRhBE7yGxRhBDDKFQPVtnwJdHS7ocvm5rsdCTWZQtAHLL65Gs6XrAdncDuxOjAhAR4InqejNuHu6LEG93O6EGdJ0mLDM04Y2fT0MqdoGpubXHw9cdCZpguRsWTlEDAOTuIhRVNyBZo7arW5sxStHpvnoikoRuVU8Hg+IFI9ltR3Xw9RDhFrUv6ppa+MaPLhoukqdHgeOAd6zC+WpQUGnCrSP98Wt+FfLKLlCEjSCuEtQN2ksGcjcJQbTvMrSNrPVVq393UZxsnQFpuaWYHhNyRRf27gSfENl6IlGFpCs8li0p2WWQSlzwYUYhjE0tiBvujbvHhl5VkbIzqwTHzhtw8nwdcsvr8ZRGjbE9nKvZVwa/nbEhVYtWANPJ3LZfMJRMbnvLQL5+k1jrJQP5ySYIwPGH+bX8gO+tjYUjsnUGLP3sKObHKbscz7Q2VdupiNiZVXJFlhQZ2kpklxiQODIAdU0WZJUYrlohf7bOgJ9zS3GytB4AcO/Y4D630xCeF/LnGriQGXnXDOTrN6VBCWKI4ehD/Fp+sPfWxsIRafmV8PUQYe2eAjg7dZ6i7ewYtvVklyt6EqMCkBgVwGxOMgtrOz3mJ/sLUdPcCmcAT13GugWx6eJSCdVV8D0THo8F8WGd1vkR/R8ywx28kFgjCOKacyVCrczQBGOjGbnl9YgJ8oTJ0tKryKDtsHl14JV/uxZSkTeqfDoVai+n5CE+3IcJussVbL1NM3aXKhZwc+YtUi62cXAT0WVhIENCbXBC70qCGGAMhJoUYdzT1SBY7oZFU9SQu4vRhu7nfNqyLlWLvXkVSNao+7TGSoiyOWKcygcxQZ6I8PeAr1QEb0nHj92dWSUoNjT3aRo1W2fAdyfOI6uoGrfHhnT5GAmRSZWflDo6+ykD4X1PXD3IFJcgBhBCTUqZoel6n0qnCOOePvz1zFU7RrDcDU9ZB7P39AK2MU2Ld9MLECSXQCEVXZZQKzM09fqxj1XK8dI9YxAV4IkbQ+Qduj13ZpXgua9zcKy4tlOT38shLb8SWzNL8HFmMZ7fcaLb814yLYqEWj9lILzviasLRdYIYgCxPUsHhUzc6ailvuJKImPRwV5I1qgv6/49Tdv1hjJDE3Zm6fCk9fHy9hBh/qThPbpvhrYSZ/RGuIlcoDdZoNXXIfV0Va/rgrpKYQr1YX0dWRP2pZCKMDU6kKIyAxiqRSNIrBHEAKIvivO7Q4iMAfzYppTssh5HXDK0lcgqrMLGjOJen2e2ztDpJIDLpczQhORPs5BbzndRPtmL80nJLsPnR0pQVN3A/NRqGixIGuWPs5X1fXrhvFoF/TRmavBAQm1oQ2KNIAYYV/sCbDsIXSjGXw/0SLAJdVvJLq69Ps+6JgvuvykUdU2WXp9zZwTL3TBjVCAAwKUXRR9lhibsPVMJD/EwjPDzwJwJSmxM56cBjPCV9sjfjCAIoq8gsUYQRAdshVqyRm0n1DK0lfByE8HPUwyAn+VpO12gq2L7rsgqMWDbkfPwkUr6VAwlT4/q0t6jM7zdXLHj9zIka9RQySV4aKISx0oM2JWtx61kAEsQxDWExBpBEA5xlHLN0FZi4dYsxIf7wEM8DA3miyiqbsAIPw+8OnfsFaVqrlaK951ULf7Uy4HvwXI3PJwQDpHIJkKYVQKZuxg1DRb8ml/ZJ2Lt80PnAABTowNxtrKeInYEQTiEukEJguiU9sIpIsATSaP8EafyQerpKtwY4gm90QxjU8tVOd6V8k6qFjuO6i6rky5Y7mZ3PsWGZmxML8CcCUos74Pz/PzQOWzcexbbs3TYfqgQC7dmIUNbecX7JQhi8EGRNYIgekx1vRmpp6twd2wI/nKLCjtP6DF3fDDq+kis9TVPJ0WBA9BsbsF3v+uQEHn56cu+jvyF+rhjhJ8HM8pNTlQhq8RA0TWCIDpAkTWCIHqMn6cYCpkYId7u2HVSD73RjLzyeqSerurR/demapGtM1zdk3TAloPFaGoD5m4+eEXHvxrNHcmJKsjcXKGtbsTG9II+9VojCGJwQJE1giB6TLDcDdsXJ7B/29/WFULDQmsrH4W7VgX6thGxvpxacKUIEbSIAE8gSwexExDl5455vayvIwhi8OPEcRx3vU9iIGE0GuHl5YW6ujrIZFc+V5C49tDYluvH2lRtrwTT1TDJ7YpP9hciaXTQdXt90GuTIK4eA/n6TWlQYkhBY1uuLyuSonosvnZmlVxx2rI3fLK/EB8eKML2Q4XX7fVBQm1oQJ8/RG8hsUYMKWhsy8AgQ1uJ577OwROJqmt2TH+ZBEmjArAxoxjbs3S9uu/mPVqsS9UiQ1t5XWryiIEDfWEkLgeqWSOGHCTU+j8RAZ54PFGFTRnFcHJxvSapUMH4V+Yu7lUjweY9Wvx0qgK55fW4/6ZQVJvMeGJqZL+pjSP6F/SFkbgcSKwRBNHvCJa74cFJ4XC5jLFVV8Ks2GDM6uV9lkyLQlMb//9qkxnlhmZkFVWTWCM6hYQa0VsoDUoQRL+kvSltfyVDW4ljxbxXWk6pEUFyCeJG+F3nsyIIYjBBYo0gCOIKSIwKwPybwjBF7QO90Yz44b4UVSMIok8ZMGLt7rvvRlhYGCQSCYKCgvDwww+jrKzMbpvs7GwkJiZCIpFAqVTi9ddf77CfL7/8EtHR0ZBIJBgzZgx+/PHHa7UEgiAGKbNig3H/pHC8Nns0Hpkcfr1Ph7jKUHMAca0ZMGJNo9Hgiy++QH5+Pnbs2IGzZ8/ivvvuY7cbjUbMmDEDKpUKR48exRtvvIG///3v+OCDD9g2Bw8exPz58/HYY4/h2LFjuPfee3HvvfciJyfneiyJIIhBRLDcDXPiwq73aRBXGermJK4HA9YU97vvvsO9994Ls9kMV1dXbNq0CS+++CL0ej1EIhEA4Pnnn8c333yDvLw8AMC8efPQ0NCAXbt2sf1MmjQJ48aNw+bNmx0ex2w2w2w2s9+NRiOUSuWANNUjCIIgrhwyLx6YkCnuNaa2thb//e9/kZCQAFdXVwBAZmYmpkyZwoQaAMycORP5+fm4cOEC2yYpKcluXzNnzkRmZmanx3rllVfg5eXFfpRKGgVDEAQxlCGhRlxrBpRYe+655+Dh4QFfX1+UlJTg22+/Zbfp9XoEBgbabS/8rtfru9xGuN0Rq1atQl1dHfvR6XpnlkkQBEEQBHElXFex9vzzz8PJyanLHyGFCQDPPPMMjh07hl9++QXDhg3DI488gqudxRWLxZDJZHY/BHE5UI0LQRAEcTlcV1PclStX4tFHH+1ym/DwS51Vfn5+8PPzQ1RUFEaNGgWlUolDhw4hPj4eCoUCFRUVdvcVflcoFOxfR9sItxPE1UIoSibncoIY3FA9G3E1uK5izd/fH/7+/pd137Y23jJcKP6Pj4/Hiy++iJaWFlbHtnv3bowcORLe3t5sm7S0NDz99NNsP7t370Z8fPwVrIIguodGzBDEwOFyBRd9KSOuFgOiZu3w4cN49913cfz4cRQXF2PPnj2YP38+IiIimNB64IEHIBKJ8NhjjyE3Nxfbt2/HunXr8Ne//pXt56mnnsJPP/2Et956C3l5efj73/+OrKwsPPnkk9dracQQgj68e8baVO31PgViCHMl1hz0pYy4WgwIsebu7o6dO3di+vTpGDlyJB577DHExsZi7969EIvFAAAvLy/88ssvKCoqwoQJE7By5UqsWbMGjz/+ONtPQkICPvvsM3zwwQcYO3YsvvrqK3zzzTcYPXr09VoaQRA2rE3VYmN6AQk24rpxpYKLhBpxNRiwPmvXi4Hs00IQA4G1qdoBMROUIIiBxUC+fg+IyBpBEEMHEmoEQRD2kFgjiGsMWXgQxPWB3nvEQIXEGkFcQwbyXMGBeM5DAXpeesZAfu8RBIk1griGDNRuMbrQ9U/oeek5A/W9RxAANRj0moFcoEgQVwKZffZP6HkhiJ4xkK/fFFkjCKJHkCDon9DzQhCDHxJrBEEQBEEQ/RgSawQxyKD6JYIgiMEFiTWCGERQwTlBEMTgg8QaQfRjeiu6qOONIAhi8EFijSD6KZcbJSOhRgwGKDpMEJcgsUYQ/RSKkhFDFUrnE4Q9JNYIoh9DQo0YitAXFYKwh8QaQRAE0e8goUYQlyCxRhAEQRAE0Y8hsUYQBEEQBNGPIbFGEARBEATRjyGxRhAE0c8YDF2Qg2ENBNFfILFGEESfca0u0H11nJ7u51oKj8FgWzEY1kAQ/QkSawRB9AnX6gLdV8fp6X768ng9YTDYVgyGNRBEf8KJ4zjuep/EQMJoNMLLywt1dXWQyWTX+3QIol9RZmi6JhfovjpOT/dzpccTBB8JGIK4fgzk6zeJtV4ykJ9sguiPXCuBd70ZKuskiP7KQL5+UxqUIIjrxtVMnV7rOrPuGChCjerMCKL/QWKNIIjrxtWqbbqWBe6DqZh+MK2FIAYTlAbtJQM5jEoQQ4nLSTtebqpyMKU4B9NaCMKWgXz9psgaQRCDkssRapcbVRpM4mYwrYUgBgsk1giCIEB2EwRB9F9IrBEEQVgZ6EKNas0IYnBCYo0gCGIQQM0BBDF4IbFGEMSAgERI11AalyAGLyTWCILo91DUqGeQUCOIwQmJNYIg+j0UNSIIYihDYo0giAEBCTWCIIYqJNYIgiAIgiD6MQNOrJnNZowbNw5OTk44fvy43W3Z2dlITEyERCKBUqnE66+/3uH+X375JaKjoyGRSDBmzBj8+OOP1+jMCYIgCIIges+AE2vPPvssgoODO/zdaDRixowZUKlUOHr0KN544w38/e9/xwcffMC2OXjwIObPn4/HHnsMx44dw7333ot7770XOTk513IJBEEQBEEQPWZAzQZNSUnBX//6V+zYsQMxMTE4duwYxo0bBwDYtGkTXnzxRej1eohEIgDA888/j2+++QZ5eXkAgHnz5qGhoQG7du1i+5w0aRLGjRuHzZs39+gcBvJsMYIgCIIYqgzk6/eAiaxVVFRg0aJF+M9//gN3d/cOt2dmZmLKlClMqAHAzJkzkZ+fjwsXLrBtkpKS7O43c+ZMZGZmdnpcs9kMo9Fo90MQBEEQBHGtGBBijeM4PProo1iyZAni4uIcbqPX6xEYGGj3N+F3vV7f5TbC7Y545ZVX4OXlxX6USuWVLIUgCIIgCKJXXFex9vzzz8PJyanLn7y8PGzYsAH19fVYtWrVNT/HVatWoa6ujv3odLprfg4EQRAEQQxdXK7nwVeuXIlHH320y23Cw8OxZ88eZGZmQiwW290WFxeHBx98EFu3boVCoUBFRYXd7cLvCoWC/etoG+F2R4jF4g7HJQiCIAiCuFZcV7Hm7+8Pf3//brdbv349/vnPf7Lfy8rKMHPmTGzfvh0TJ04EAMTHx+PFF19ES0sLXF1dAQC7d+/GyJEj4e3tzbZJS0vD008/zfa1e/duxMfH9+GqCIIgCIIg+o7rKtZ6SlhYmN3vUqkUABAREYHQ0FAAwAMPPIB//OMfeOyxx/Dcc88hJycH69atw9q1a9n9nnrqKUydOhVvvfUW7rjjDmzbtg1ZWVl29h4EQRAEQRD9iQHRYNATvLy88Msvv6CoqAgTJkzAypUrsWbNGjz++ONsm4SEBHz22Wf44IMPMHbsWHz11Vf45ptvMHr06Ot45gRBEARBEJ0zoHzW+gMD2aeFIAiCIIYqA/n6PWgiawRBEARBEIORAVGz1p8QApFkjksQBEEQAwfhuj0QE4ok1npJfX09AJA5LkEQBEEMQOrr6+Hl5XW9T6NXUM1aL2lra0NZWRk8PT3h5OQEgFfrSqUSOp1uwOXBrxRa+9BcOzC0109rH5prB4b2+gf62jmOQ319PYKDg+HsPLCqwCiy1kucnZ2ZXUh7ZDLZgHwB9wW09qG5dmBor5/WPjTXDgzt9Q/ktQ+0iJrAwJKWBEEQBEEQQwwSawRBEARBEP0YEmt9gFgsxt/+9rchOUOU1j401w4M7fXT2ofm2oGhvf6hvPbrDTUYEARBEARB9GMoskYQBEEQBNGPIbFGEARBEATRjyGxRhAEQRAE0Y8hsUYQBEEQBNGPIbF2GZjNZowbNw5OTk44fvy43W3Z2dlITEyERCKBUqnE66+/3uH+X375JaKjoyGRSDBmzBj8+OOP1+jML5+7774bYWFhkEgkCAoKwsMPP4yysjK7bQbr2s+dO4fHHnsMI0aMgJubGyIiIvC3v/0NFovFbrvBuv7/+7//Q0JCAtzd3SGXyx1uU1JSgjvuuAPu7u4ICAjAM888g9bWVrttfv31V4wfPx5isRhqtRr//ve/r/7JXwXee+89DB8+HBKJBBMnTsRvv/12vU+pT9i3bx/uuusuBAcHw8nJCd98843d7RzHYc2aNQgKCoKbmxuSkpJw5swZu21qa2vx4IMPQiaTQS6X47HHHoPJZLqGq+g9r7zyCm666SZ4enoiICAA9957L/Lz8+22aW5uxtKlS+Hr6wupVIq5c+eioqLCbpuevAf6I5s2bUJsbCwzuo2Pj0dKSgq7fTCvfUDBEb1m+fLl3KxZszgA3LFjx9jf6+rquMDAQO7BBx/kcnJyuM8//5xzc3Pj3n//fbbNgQMHuGHDhnGvv/46d+rUKe5///d/OVdXV+7kyZPXYSU95+233+YyMzO5c+fOcQcOHODi4+O5+Ph4dvtgXntKSgr36KOPcj///DN39uxZ7ttvv+UCAgK4lStXsm0G8/rXrFnDvf3229xf//pXzsvLq8Ptra2t3OjRo7mkpCTu2LFj3I8//sj5+flxq1atYtsUFhZy7u7u3F//+lfu1KlT3IYNG7hhw4ZxP/300zVcyZWzbds2TiQScVu2bOFyc3O5RYsWcXK5nKuoqLjep3bF/Pjjj9yLL77I7dy5kwPAff3113a3v/rqq5yXlxf3zTffcCdOnODuvvtubsSIEVxTUxPb5vbbb+fGjh3LHTp0iMvIyODUajU3f/78a7yS3jFz5kzu448/5nJycrjjx49zf/jDH7iwsDDOZDKxbZYsWcIplUouLS2Ny8rK4iZNmsQlJCSw23vyHuivfPfdd9wPP/zAabVaLj8/n3vhhRc4V1dXLicnh+O4wb32gQSJtV7y448/ctHR0Vxubm4HsbZx40bO29ubM5vN7G/PPfccN3LkSPb7n/70J+6OO+6w2+fEiRO5xYsXX/Vz70u+/fZbzsnJibNYLBzHDa21cxzHvf7669yIESPY70Nh/R9//LFDsfbjjz9yzs7OnF6vZ3/btGkTJ5PJ2OPx7LPPcjExMXb3mzdvHjdz5syres59zc0338wtXbqU/X7x4kUuODiYe+WVV67jWfU97cVaW1sbp1AouDfeeIP9zWAwcGKxmPv88885juO4U6dOcQC4I0eOsG1SUlI4JycnrrS09Jqd+5VSWVnJAeD27t3LcRy/TldXV+7LL79k25w+fZoDwGVmZnIc17P3wEDC29ub++ijj4bk2vsrlAbtBRUVFVi0aBH+85//wN3dvcPtmZmZmDJlCkQiEfvbzJkzkZ+fjwsXLrBtkpKS7O43c+ZMZGZmXt2T70Nqa2vx3//+FwkJCXB1dQUwdNYuUFdXBx8fH/b7UFu/LZmZmRgzZgwCAwPZ32bOnAmj0Yjc3Fy2zUBfu8ViwdGjR+3W4ezsjKSkpAG1jsuhqKgIer3ebu1eXl6YOHEiW3tmZibkcjni4uLYNklJSXB2dsbhw4ev+TlfLnV1dQDA3t9Hjx5FS0uL3dqjo6MRFhZmt/bu3gMDgYsXL2Lbtm1oaGhAfHz8kFp7f4fEWg/hOA6PPvoolixZYvdhZIter7d7wQJgv+v1+i63EW7vzzz33HPw8PCAr68vSkpK8O2337LbBvvabSkoKMCGDRuwePFi9rehtP72XMnajUYjmpqars2JXiHV1dW4ePHioHwOu0NYX1dr1+v1CAgIsLvdxcUFPj4+A+bxaWtrw9NPP41bbrkFo0ePBsCvSyQSdajXbL/27t4D/ZmTJ09CKpVCLBZjyZIl+Prrr3HDDTcMibUPFIa8WHv++efh5OTU5U9eXh42bNiA+vp6rFq16nqfcp/R07ULPPPMMzh27Bh++eUXDBs2DI888gi4ATwAo7frB4DS0lLcfvvt+OMf/4hFixZdpzO/ci5n7QQx2Fm6dClycnKwbdu2630q15SRI0fi+PHjOHz4MJ544gksWLAAp06dut6nRdjgcr1P4HqzcuVKPProo11uEx4ejj179iAzM7PDTLS4uDg8+OCD2Lp1KxQKRYcuGeF3hULB/nW0jXD7taSnaxfw8/ODn58foqKiMGrUKCiVShw6dAjx8fEDbu1A79dfVlYGjUaDhIQEfPDBB3bbDbT193btXaFQKDp0RPZ07TKZDG5ubj086+uLn58fhg0b1m+ew2uJsL6KigoEBQWxv1dUVGDcuHFsm8rKSrv7tba2ora2dkA8Pk8++SR27dqFffv2ITQ0lP1doVDAYrHAYDDYRZhsn/eevAf6MyKRCGq1GgAwYcIEHDlyBOvWrcO8efMG/doHDNe7aG6gUFxczJ08eZL9/PzzzxwA7quvvuJ0Oh3HcZeKzIWie47juFWrVnUoMr/zzjvt9h0fHz9giswFiouLOQBceno6x3GDf+3nz5/nIiMjufvvv59rbW3tcPtgXz/Hdd9gYNsR+f7773MymYxrbm7mOI5vMBg9erTd/ebPnz8gGwyefPJJ9vvFixe5kJCQIdNg8Oabb7K/1dXVOWwwyMrKYtv8/PPP/b7BoK2tjVu6dCkXHBzMabXaDrcLRfZfffUV+1teXp7DIvuu3gMDCY1Gwy1YsGBIrr2/QmLtMikqKurQDWowGLjAwEDu4Ycf5nJycrht27Zx7u7uHewbXFxcuDfffJM7ffo097e//a3f2zccOnSI27BhA3fs2DHu3LlzXFpaGpeQkMBFRESwN+NgXTvH8UJNrVZz06dP586fP8+Vl5ezH4HBvP7i4mLu2LFj3D/+8Q9OKpVyx44d444dO8bV19dzHHepdX/GjBnc8ePHuZ9++onz9/d3aN3xzDPPcKdPn+bee++9AWvdIRaLuX//+9/cqVOnuMcff5yTy+V2nXADlfr6evbcAuDefvtt7tixY1xxcTHHcbx1h1wu57799lsuOzubu+eeexxad9x4443c4cOHuf3793ORkZH93rrjiSee4Ly8vLhff/3V7r3d2NjItlmyZAkXFhbG7dmzh8vKyupgXdST90B/5fnnn+f27t3LFRUVcdnZ2dzzzz/POTk5cb/88gvHcYN77QMJEmuXiSOxxnEcd+LECW7y5MmcWCzmQkJCuFdffbXDfb/44gsuKiqKE4lEXExMDPfDDz9co7O+PLKzszmNRsP5+PhwYrGYGz58OLdkyRLu/PnzdtsNxrVzHB9RAuDwx5bBuv4FCxY4XLsQVeU4jjt37hw3a9Yszs3NjfPz8+NWrlzJtbS02O0nPT2dGzduHCcSibjw8HDu448/vrYL6SM2bNjAhYWFcSKRiLv55pu5Q4cOXe9T6hPS09MdPs8LFizgOI6PQK1evZoLDAzkxGIxN336dC4/P99uHzU1Ndz8+fM5qVTKyWQy7s9//jMT9f2Vzt7btq/PpqYmLjk5mfP29ubc3d252bNn231Z47ievQf6IwsXLuRUKhUnEok4f39/bvr06UyocdzgXvtAwonjBnCFOEEQBEEQxCBnyHeDEgRBEARB9GdIrBEEQRAEQfRjSKwRBEEQBEH0Y0isEQRBEARB9GNIrBEEQRAEQfRjSKwRBEEQBEH0Y0isEQRBEARB9GNIrBEEQRAEQfRjSKwRBEEQBEH0Y0isEQQxYHBycury5+9//zvOnTsHJycnBAQEoL6+3u7+48aNw9///nf2e1FRER544AEEBwdDIpEgNDQU99xzD/Ly8ro95rZt2xye448//giRSITff//d7u9vvfUW/Pz8oNfr++4BIQhiSOByvU+AIAiip5SXl7P/b9++HWvWrEF+fj77m1QqRXV1NQCgvr4eb775Jv7xj3843FdLSwtuu+02jBw5Ejt37kRQUBDOnz+PlJQUGAwGu20//vhj3H777XZ/k8vlDvf7hz/8AY888ggeeeQRHD16FGKxGKdOncL//u//4t///jcUCsVlrJwgiKEMiTWCIAYMtkLHy8sLTk5OHcSPINaWLVuGt99+G0uXLkVAQECHfeXm5uLs2bNIS0uDSqUCAKhUKtxyyy0dtpXL5b0SWWvXrsWYMWPwt7/9Df/85z+xYMEC3HXXXZg3b16P90EQBCFAaVCCIAYl8+fPh1qtxksvveTwdn9/fzg7O+Orr77CxYsX+/TYnp6e2LJlC9566y08+OCD0Ol02LRpU58egyCIoQOJNYIgBiVOTk549dVX8cEHH+Ds2bMdbg8JCcH69euxZs0aeHt7Y9q0aXj55ZdRWFjYYdv58+dDKpXa/ZSUlHR5/GnTpuG+++7DF198gfXr18PX17fP1kYQxNCCxBpBEIOWmTNnYvLkyVi9erXD25cuXQq9Xo///ve/iI+Px5dffomYmBjs3r3bbru1a9fi+PHjdj/BwcEAYCfglixZwu5TWlqKn376Ce7u7sjIyLh6iyQIYtBDNWsEQQxqXn31VcTHx+OZZ55xeLunpyfuuusu3HXXXfjnP/+JmTNn4p///Cduu+02to1CoYBarXZ4/+PHj7P/y2Qy9v9FixZhwoQJePHFF3Hbbbfhvvvuw9SpU/tmUQRBDClIrBEEMai5+eabMWfOHDz//PPdbuvk5ITo6GgcPHiwx/t3JOI++ugj7N+/HydPnoRKpcITTzyBhQsXIjs7Gx4eHr06f4IgCEqDEgQx6Pm///s/7Nmzx87m4/jx47jnnnvw1Vdf4dSpUygoKMD/+3//D1u2bME999xjd3+DwQC9Xm/309DQ4PBYxcXF+Otf/4o333yTdZm+9tprcHJy6pFgJAiCaA+JNYIgBj1RUVFYuHAhmpub2d9CQ0MxfPhw/OMf/8DEiRMxfvx4rFu3Dv/4xz/w4osv2t3/z3/+M4KCgux+NmzY0OE4HMfhscceQ3x8PB5//HH2d3d3d/z73//Gpk2bsHfv3qu3UIIgBiVOHMdx1/skCIIgCIIgCMdQZI0gCIIgCKIfQ2KNIAiCIAiiH0NijSAIgiAIoh9DYo0gCIIgCKIfQ2KNIAiCIAiiH0NijSAIgiAIoh9DYo0gCIIgCKIfQ2KNIAiCIAiiH0NijSAIgiAIoh9DYo0gCIIgCKIfQ2KNIAiCIAiiH/P/ARKkUATmK3JlAAAAAElFTkSuQmCC\n" - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "outputs": [], "source": [ "g = sns.scatterplot(tnse_data, x=\"TNSE-X\", y=\"TNSE-Y\", s=1)\n", "g.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)" @@ -1409,7 +1283,7 @@ }, { "cell_type": "code", - "execution_count": 99, + "execution_count": null, "outputs": [], "source": [ "wos_nlp.to_csv(f\"{outdir}/wos_nlp.csv\", index=False, sep='\\t')\n",