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class="social-profile-avatar-container"><img class="profile-avatar u-positionAbsolute" alt="Michael Gastner" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/51216508/19848670/19671702/s200_michael.gastner.jpg" /></div><div class="title-container"><h1 class="ds2-5-heading-sans-serif-sm">Michael Gastner</h1><div class="affiliations-container fake-truncate js-profile-affiliations"></div></div></div><div class="sidebar-cta-container"><button class="ds2-5-button hidden profile-cta-button grow js-profile-follow-button" data-broccoli-component="user-info.follow-button" data-click-track="profile-user-info-follow-button" data-follow-user-fname="Michael" data-follow-user-id="51216508" data-follow-user-source="profile_button" data-has-google="false"><span class="material-symbols-outlined" style="font-size: 20px" 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</a></div></div></div></div><div class="right-panel-container"><div class="user-content-wrapper"><div class="uploads-container" id="social-redesign-work-container"><div class="upload-header"><h2 class="ds2-5-heading-sans-serif-xs">Uploads</h2></div><div class="documents-container backbone-social-profile-documents" style="width: 100%;"><div class="u-taCenter"></div><div class="profile--tab_content_container js-tab-pane tab-pane active" id="all"><div class="profile--tab_heading_container js-section-heading" data-section="Papers" id="Papers"><h3 class="profile--tab_heading_container">Papers by Michael Gastner</h3></div><div class="js-work-strip profile--work_container" data-work-id="75363637"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75363637/DOI_10_1140_epjb_e2006_00046_8_THE_EUROPEAN_PHYSICAL_JOURNAL_B"><img alt="Research paper thumbnail of DOI: 10.1140/epjb/e2006-00046-8 THE EUROPEAN PHYSICAL JOURNAL B" class="work-thumbnail" src="https://attachments.academia-assets.com/83161584/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75363637/DOI_10_1140_epjb_e2006_00046_8_THE_EUROPEAN_PHYSICAL_JOURNAL_B">DOI: 10.1140/epjb/e2006-00046-8 THE EUROPEAN PHYSICAL JOURNAL B</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Abstract. We study networks that connect points in geographic space, such as transportation netwo...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Abstract. We study networks that connect points in geographic space, such as transportation networks and the Internet. We find that there are strong signatures in these networks of topography and use patterns, giving the networks shapes that are quite distinct from one another and from non-geographic networks. We offer an explanation of these differences in terms of the costs and benefits of transportation and communication, and give a simple model based on the Monte Carlo optimization of these costs and benefits that reproduces well the qualitative features of the networks studied. PACS. 89.75.Hc Networks and genealogical trees – 87.23.Ge Dynamics of social systems – 05.90.+m Other topics in statistical physics, thermodynamics, and nonlinear dynamical systems – 64.60.Ak Renormalization-group, fractal, and percolation studies of phase transitions 1</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="800b0720ff993fdabb65718740a87c6e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":83161584,"asset_id":75363637,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/83161584/download_file?st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75363637"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75363637"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75363637; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75363637]").text(description); $(".js-view-count[data-work-id=75363637]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75363637; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75363637']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75363637, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "800b0720ff993fdabb65718740a87c6e" } } $('.js-work-strip[data-work-id=75363637]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75363637,"title":"DOI: 10.1140/epjb/e2006-00046-8 THE EUROPEAN PHYSICAL JOURNAL B","translated_title":"","metadata":{"abstract":"Abstract. 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A cartogram is called contiguous if it conforms to this area principle while also keeping neighboring regions connected. Because of their distorted appearance, contiguous cartograms have been criticized as difficult to read. Some authors have suggested that cartograms may be more legible if they are accompanied by interactive features (e.g., animations, linked brushing, or infotips). We conducted an experiment to evaluate this claim. Participants had to perform visual analysis tasks with interactive and noninteractive contiguous cartograms. The task types covered various aspects of cartogram readability, ranging from elementary lookup tasks to synoptic tasks (i.e., tasks in which participants had to summarize high-level differences between two cartograms). Elementary tasks were carried out equally well wit...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="7c0ce60a28b9deff50bb4eeb55287839" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":79554497,"asset_id":69466588,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/79554497/download_file?st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="69466588"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="69466588"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 69466588; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=69466588]").text(description); $(".js-view-count[data-work-id=69466588]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 69466588; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='69466588']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 69466588, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "7c0ce60a28b9deff50bb4eeb55287839" } } $('.js-work-strip[data-work-id=69466588]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":69466588,"title":"Task-Based Effectiveness of Interactive Contiguous Area Cartograms","translated_title":"","metadata":{"abstract":"Cartograms are map-based data visualizations in which the area of each map region is proportional to an associated numeric data value (e.g., population or gross domestic product). A cartogram is called contiguous if it conforms to this area principle while also keeping neighboring regions connected. Because of their distorted appearance, contiguous cartograms have been criticized as difficult to read. Some authors have suggested that cartograms may be more legible if they are accompanied by interactive features (e.g., animations, linked brushing, or infotips). We conducted an experiment to evaluate this claim. Participants had to perform visual analysis tasks with interactive and noninteractive contiguous cartograms. The task types covered various aspects of cartogram readability, ranging from elementary lookup tasks to synoptic tasks (i.e., tasks in which participants had to summarize high-level differences between two cartograms). Elementary tasks were carried out equally well wit...","publisher":"IEEE Transactions on Visualization and Computer Graphics","publication_date":{"day":null,"month":null,"year":2021,"errors":{}}},"translated_abstract":"Cartograms are map-based data visualizations in which the area of each map region is proportional to an associated numeric data value (e.g., population or gross domestic product). A cartogram is called contiguous if it conforms to this area principle while also keeping neighboring regions connected. Because of their distorted appearance, contiguous cartograms have been criticized as difficult to read. Some authors have suggested that cartograms may be more legible if they are accompanied by interactive features (e.g., animations, linked brushing, or infotips). We conducted an experiment to evaluate this claim. Participants had to perform visual analysis tasks with interactive and noninteractive contiguous cartograms. The task types covered various aspects of cartogram readability, ranging from elementary lookup tasks to synoptic tasks (i.e., tasks in which participants had to summarize high-level differences between two cartograms). 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="52402134"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/52402134/Mapping_the_inequality_of_the_global_distribution_of_seasonal_influenza_vaccine"><img alt="Research paper thumbnail of Mapping the inequality of the global distribution of seasonal influenza vaccine" class="work-thumbnail" src="https://attachments.academia-assets.com/69681936/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/52402134/Mapping_the_inequality_of_the_global_distribution_of_seasonal_influenza_vaccine">Mapping the inequality of the global distribution of seasonal influenza vaccine</a></div><div class="wp-workCard_item"><span>Environment and Planning A: Economy and Space</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">With an estimated annual worldwide death toll of between 290 000 and 650 000, seasonal influenza ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">With an estimated annual worldwide death toll of between 290 000 and 650 000, seasonal influenza remains one of the deadliest respiratory diseases. Influenza vaccines provide moderate to high protection and have been on the World Health Organization’s Model List of Essential Medicines since 1979. Approximately 490 million doses of influenza vaccine are produced per year, but an investigation of geographic allocation reveals enormous disparities. Here, we present two maps that visualise the inequality of the distribution across 195 countries: a conventional choropleth map and a cartogram. In combination, these two maps highlight the widespread lack of coverage in Africa and many parts of Asia. As COVID-19 vaccines are now being distributed in developed countries, data for seasonal influenza vaccine distribution emphasises the need for policymakers to ensure equitable access to COVID-19 vaccines.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="33e3a48cbff725548fd92bc98d75f229" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":69681936,"asset_id":52402134,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/69681936/download_file?st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="52402134"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="52402134"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52402134; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=52402134]").text(description); $(".js-view-count[data-work-id=52402134]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 52402134; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='52402134']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 52402134, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "33e3a48cbff725548fd92bc98d75f229" } } $('.js-work-strip[data-work-id=52402134]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":52402134,"title":"Mapping the inequality of the global distribution of seasonal influenza vaccine","translated_title":"","metadata":{"abstract":"With an estimated annual worldwide death toll of between 290 000 and 650 000, seasonal influenza remains one of the deadliest respiratory diseases. Influenza vaccines provide moderate to high protection and have been on the World Health Organization’s Model List of Essential Medicines since 1979. Approximately 490 million doses of influenza vaccine are produced per year, but an investigation of geographic allocation reveals enormous disparities. Here, we present two maps that visualise the inequality of the distribution across 195 countries: a conventional choropleth map and a cartogram. In combination, these two maps highlight the widespread lack of coverage in Africa and many parts of Asia. As COVID-19 vaccines are now being distributed in developed countries, data for seasonal influenza vaccine distribution emphasises the need for policymakers to ensure equitable access to COVID-19 vaccines.","publisher":"SAGE Publications","publication_name":"Environment and Planning A: Economy and Space"},"translated_abstract":"With an estimated annual worldwide death toll of between 290 000 and 650 000, seasonal influenza remains one of the deadliest respiratory diseases. Influenza vaccines provide moderate to high protection and have been on the World Health Organization’s Model List of Essential Medicines since 1979. Approximately 490 million doses of influenza vaccine are produced per year, but an investigation of geographic allocation reveals enormous disparities. Here, we present two maps that visualise the inequality of the distribution across 195 countries: a conventional choropleth map and a cartogram. In combination, these two maps highlight the widespread lack of coverage in Africa and many parts of Asia. As COVID-19 vaccines are now being distributed in developed countries, data for seasonal influenza vaccine distribution emphasises the need for policymakers to ensure equitable access to COVID-19 vaccines.","internal_url":"https://www.academia.edu/52402134/Mapping_the_inequality_of_the_global_distribution_of_seasonal_influenza_vaccine","translated_internal_url":"","created_at":"2021-09-15T00:39:18.927-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":51216508,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":69681936,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/69681936/thumbnails/1.jpg","file_name":"0308518X21998356.pdf","download_url":"https://www.academia.edu/attachments/69681936/download_file?st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Mapping_the_inequality_of_the_global_dis.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/69681936/0308518X21998356-libre.pdf?1631692900=\u0026response-content-disposition=attachment%3B+filename%3DMapping_the_inequality_of_the_global_dis.pdf\u0026Expires=1732457002\u0026Signature=fq-UX7VKHim-cHGjs~Zl0oFmxb1MYibjpVqaBj7JCP7Z9uc3P068MyveQSPnYuhyuQlgriZLRYPdXe93mEgY4-Cz0IIPtvtO42UEnDAyCnGl5a2se1B4CmrRky6fuELr1KbiVVDt4hZ-ptlBN0lnzkF39WyXTzDd2djSv2l4cHzAWfYpaB-yzbd6My5~fJZ05xfatmfEiJ9wcDvzVhEwmpONqoL4cFc9844AiMov8EJdMZURwj7LgaMrVuAQwst9MfS-47yGvlsBlMg9Rq9GILyFbRs2oMl7zZQ9~n8HLlEhw8-B8GSrRWI06HirZ57N0~viVgsE2SGl-PCX2yZKyQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Mapping_the_inequality_of_the_global_distribution_of_seasonal_influenza_vaccine","translated_slug":"","page_count":4,"language":"en","content_type":"Work","owner":{"id":51216508,"first_name":"Michael","middle_initials":null,"last_name":"Gastner","page_name":"MGastner","domain_name":"independent","created_at":"2016-07-21T04:30:27.273-07:00","display_name":"Michael Gastner","url":"https://independent.academia.edu/MGastner"},"attachments":[{"id":69681936,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/69681936/thumbnails/1.jpg","file_name":"0308518X21998356.pdf","download_url":"https://www.academia.edu/attachments/69681936/download_file?st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Mapping_the_inequality_of_the_global_dis.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/69681936/0308518X21998356-libre.pdf?1631692900=\u0026response-content-disposition=attachment%3B+filename%3DMapping_the_inequality_of_the_global_dis.pdf\u0026Expires=1732457002\u0026Signature=fq-UX7VKHim-cHGjs~Zl0oFmxb1MYibjpVqaBj7JCP7Z9uc3P068MyveQSPnYuhyuQlgriZLRYPdXe93mEgY4-Cz0IIPtvtO42UEnDAyCnGl5a2se1B4CmrRky6fuELr1KbiVVDt4hZ-ptlBN0lnzkF39WyXTzDd2djSv2l4cHzAWfYpaB-yzbd6My5~fJZ05xfatmfEiJ9wcDvzVhEwmpONqoL4cFc9844AiMov8EJdMZURwj7LgaMrVuAQwst9MfS-47yGvlsBlMg9Rq9GILyFbRs2oMl7zZQ9~n8HLlEhw8-B8GSrRWI06HirZ57N0~viVgsE2SGl-PCX2yZKyQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":69681935,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/69681935/thumbnails/1.jpg","file_name":"0308518X21998356.pdf","download_url":"https://www.academia.edu/attachments/69681935/download_file","bulk_download_file_name":"Mapping_the_inequality_of_the_global_dis.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/69681935/0308518X21998356-libre.pdf?1631692900=\u0026response-content-disposition=attachment%3B+filename%3DMapping_the_inequality_of_the_global_dis.pdf\u0026Expires=1732457002\u0026Signature=TGASL4qcmjjJHZahBFFWJYqCwDx3dCgRPaqduBbC5gL8ULMQ6xeIwwzE9E3cnWdOSahDoVf7Te6mbMn5wu~E9-L4fCpRT9-QYn5nZeAu733sapfyAOozUoxQFXA92V95UmfE0lENars9WOoo9ex2s6PWzZSsFAOugm-tBexJWM-rrPjF2exGWmDvOZwrAwq4C7~aVJ8xsHJUjqyafVK0pB0g1nnJapSE-ZEIDrhb~9yDKqCDMpse-KVssgBN8sRVCTyKzaWAxrx4D0NDA37h2dsnTpk~8RndsHkGr8fRgrqQjgIpWk5l7KEE~QO-blYlrOSTSQ4KE~ZWOeg2IjUzQg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":262,"name":"Human Geography","url":"https://www.academia.edu/Documents/in/Human_Geography"},{"id":20436,"name":"Urban And Regional Planning","url":"https://www.academia.edu/Documents/in/Urban_And_Regional_Planning"},{"id":27659,"name":"Applied Economics","url":"https://www.academia.edu/Documents/in/Applied_Economics"}],"urls":[{"id":11192389,"url":"http://journals.sagepub.com/doi/pdf/10.1177/0308518X21998356"}]}, dispatcherData: dispatcherData }); 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Social networking plays a crucial role in the appointment to a board so that an informed debate requires knowing where women are located in the network of directors. One way to quantify the network is by studying the links created by serving on the same board and by joint appointments on multiple boards. We analyse a network of ≈ 320 000 board members of 36 000 companies traded on stock exchanges all over the world, focusing specifically on the position of women in the network. Women only have ≈ 9 − 13% of all seats, but they are not marginalised. Applying metrics from social network analysis, we find that their influence is close to that of men. 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In each update, one agent is chosen uniformly at random. The selected agent then copies the current opinion of a randomly selected neighbour. We investigate the voter model on a network with an exogenous community structure: two cliques (i.e. complete subgraphs) randomly linked by X interclique edges. We show that, counterintuitively, the mean consensus time is typically not a monotonically decreasing function of X. Cliques of fixed proportions with opposite initial opinions reach a consensus, on average, most quickly if X scales as N 3/2 , where N is the number of agents in the network. Hence, to accelerate a consensus between cliques, agents should connect to more members in the other clique as N increases but not to the extent that cliques lose their identity as distinct communities. We support our numerical results with an equation-based analysis. 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Cartograms are called \"contiguous\" if they maintain the topology of the conventional map (i.e. regions are displayed as neighbours on the cartogram if and only if they are geographic neighbours) [1]. An example of a contiguous cartogram, showing the 48 conterminous states of the USA with an area proportional to their population, is shown on the right of . Such maps are an invaluable addition to a professional geographer's toolbox. However, producing contiguous cartograms should not be the privilege of only a handful of experts in cartography. Journalists or bloggers, for example, may also benefit from a cartogram as an intriguing illustration of their own data. Similarly, high school students may enrich a term paper with a cartogram that can summarize data more effectively than raw numeric tables.","publication_name":"Abstracts of the ICA","grobid_abstract_attachment_id":66770109},"translated_abstract":null,"internal_url":"https://www.academia.edu/47865639/GO_CART_IO_A_Web_Application_for_Generating_Contiguous_Cartograms","translated_internal_url":"","created_at":"2021-05-02T02:09:24.235-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":51216508,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":66770109,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770109/thumbnails/1.jpg","file_name":"ica-abs-1-333-2019.pdf","download_url":"https://www.academia.edu/attachments/66770109/download_file?st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"GO_CART_IO_A_Web_Application_for_Generat.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770109/ica-abs-1-333-2019-libre.pdf?1619949320=\u0026response-content-disposition=attachment%3B+filename%3DGO_CART_IO_A_Web_Application_for_Generat.pdf\u0026Expires=1732457002\u0026Signature=FsiC0pVl~PirIZZ4gOxy-wmsFAHxlWClEpZm6KlKmcD8mCoX-d-X7d2MALlu6NkE~bW1Xy~zOyBQi3GEQpneZILb2V1S5CAusvedj6xFeEqousNav6noU29qePTkITA16GXDlpftVH4-pQiBjtZSnogEK2nOxXUROR9wph4HXRTfelMxjNI3txCfKMaAks5WxGXAApDcd4vcscDI6fTQUbXgnMNqeU7zPWXr1cPt8Q82aAJEx~phpubfG7Ffw6XRdNVTd5Az5FN3sTjiiXrH4Uq3TUAAvodtER5hiVasZXR7B5SaeC~~X6Vdqepn8mNa6rCVTcGKnTZ-GZU5Q3UMbg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"GO_CART_IO_A_Web_Application_for_Generating_Contiguous_Cartograms","translated_slug":"","page_count":2,"language":"en","content_type":"Work","owner":{"id":51216508,"first_name":"Michael","middle_initials":null,"last_name":"Gastner","page_name":"MGastner","domain_name":"independent","created_at":"2016-07-21T04:30:27.273-07:00","display_name":"Michael Gastner","url":"https://independent.academia.edu/MGastner"},"attachments":[{"id":66770109,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770109/thumbnails/1.jpg","file_name":"ica-abs-1-333-2019.pdf","download_url":"https://www.academia.edu/attachments/66770109/download_file?st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"GO_CART_IO_A_Web_Application_for_Generat.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770109/ica-abs-1-333-2019-libre.pdf?1619949320=\u0026response-content-disposition=attachment%3B+filename%3DGO_CART_IO_A_Web_Application_for_Generat.pdf\u0026Expires=1732457002\u0026Signature=FsiC0pVl~PirIZZ4gOxy-wmsFAHxlWClEpZm6KlKmcD8mCoX-d-X7d2MALlu6NkE~bW1Xy~zOyBQi3GEQpneZILb2V1S5CAusvedj6xFeEqousNav6noU29qePTkITA16GXDlpftVH4-pQiBjtZSnogEK2nOxXUROR9wph4HXRTfelMxjNI3txCfKMaAks5WxGXAApDcd4vcscDI6fTQUbXgnMNqeU7zPWXr1cPt8Q82aAJEx~phpubfG7Ffw6XRdNVTd5Az5FN3sTjiiXrH4Uq3TUAAvodtER5hiVasZXR7B5SaeC~~X6Vdqepn8mNa6rCVTcGKnTZ-GZU5Q3UMbg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":66770110,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770110/thumbnails/1.jpg","file_name":"ica-abs-1-333-2019.pdf","download_url":"https://www.academia.edu/attachments/66770110/download_file","bulk_download_file_name":"GO_CART_IO_A_Web_Application_for_Generat.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770110/ica-abs-1-333-2019-libre.pdf?1619949320=\u0026response-content-disposition=attachment%3B+filename%3DGO_CART_IO_A_Web_Application_for_Generat.pdf\u0026Expires=1732457002\u0026Signature=hINIPGJ0GHWoBhbH7KWSrhI26f9Fiy6f4DTKBAgGl1FbJPf-8oi-I8NKqPCALA0J~awz-EIXcHrV3hQi2ZudHmkvy8KWUR9VhGE6h8Js295WpqLCGs3OAHqN2np92rkA6K~nc-M38snKWXYcVJrI-yYTDAqWw0Ck7g8LYBsb1t16H5~W~AEyLoyxD91FIOmC~Zp6AP6rCiJnBrm3uQYWc3r1jJh5pkhL~TzKkXE~rABH2K32kyDZy5vuQGIr9xIOCr6AqnvJj~ca3D-ZmmjzsNFOhhbRJ9FvVFKYSRypK5pZoLzY6Nn3IxcwQKFGcE4f~k5Vx-DDVPkIDHqLIVjeOw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[],"urls":[{"id":9908480,"url":"https://www.abstr-int-cartogr-assoc.net/1/333/2019/ica-abs-1-333-2019.pdf"}]}, dispatcherData: dispatcherData }); 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In plenty of empirical contexts, publicly revealed opinions are not necessarily in line with internal opinions, causing complex social influence dynamics. We study to what extent hypocrisy is sustained during opinion formation and how hidden opinions change the convergence to consensus in a group. We build and analyze a modified version of the voter model with hypocrisy in a complete graph with a neutral competition between two alternatives. We compare the process from various initial conditions, varying the proportions between the two opinions in the external (revealed) and internal (hidden) layer. According to our results, hypocrisy always prolongs the time needed for reaching a consensus. In a complete graph, this time span increases linearly with group size. We find that the group-level opinion emerges in two steps: (1) a fast and directional process, during which the number of the two kinds of hypocrites equalizes; and (2) a slower, random drift of opinions. During stage (2), the ratio of opinions in the external layer is approximately equal to the ratio in the internal layer; that is, the hidden opinions do not differ significantly from the revealed ones at the group level. We furthermore find that the initial abundances of opinions, but not the initial prevalence of hypocrisy, predicts the mean consensus time and determines the opinions' probabilities of winning. These insights highlight the unimportance of hypocrisy in consensus formation under neutral conditions. Our results have important societal implications in relation to hidden voter preferences in polls and improve our understanding of opinion formation in a more realistic setting than that of conventional voter models. program (GINOP-2.3.2-15-and behavior of others. The dynamics resulting from these interactions have been studied in various models . One of the most appealing and widely studied representations is the voter model due to its simplicity . The paradigmatic voter model (which we will call the Basic Voter Model, BVM) represents the opinions of individuals as a binary variable in a single opinion dimension. At each update, an individual adopts the opinion of one of his acquaintances. 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Unlike conventional bar or pie charts, cartograms can represent correctly which regions share common borders, resulting in insightful visualizations that can be the basis for further spatial statistical analysis. Computer programs can assist data scientists in preparing cartograms, but developing an algorithm that can quickly transform every coordinate on the map (including points that are not exactly on a border) while generating recognizable images has remained a challenge. Methods that translate the cartographic deformations into physics-inspired equations of motion have become popular, but solving these equations with sufficient accuracy can still take several minutes on current hardware. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="47865635"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/47865635/The_topology_of_large_Open_Connectome_networks_for_the_human_brain"><img alt="Research paper thumbnail of The topology of large Open Connectome networks for the human brain" class="work-thumbnail" src="https://attachments.academia-assets.com/66770119/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/47865635/The_topology_of_large_Open_Connectome_networks_for_the_human_brain">The topology of large Open Connectome networks for the human brain</a></div><div class="wp-workCard_item"><span>Scientific Reports</span><span>, 2016</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c793f175b201c9ba2f6d5d565d46b0ab" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":66770119,"asset_id":47865635,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/66770119/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="47865635"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="47865635"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 47865635; 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Here we analyze several large data sets for the human brain network made available by the Open Connectome Project. We apply statistical model selection to characterize the degree distributions of graphs containing up to  0 1 6 nodes and  0 1 8 edges. A three-parameter generalized Weibull (also known as a stretched exponential) distribution is a good fit to most of the observed degree distributions. For almost all networks, simple power laws cannot fit the data, but in some cases there is statistical support for power laws with an exponential cutoff. We also calculate the topological (graph) dimension D and the small-world coefficient σ of these networks. While σ suggests a small-world topology, we found that D \u003c 4 showing that long-distance connections provide only a small correction to the topology of the embedding three-dimensional space.","publication_date":{"day":null,"month":null,"year":2016,"errors":{}},"publication_name":"Scientific Reports","grobid_abstract_attachment_id":66770119},"translated_abstract":null,"internal_url":"https://www.academia.edu/47865635/The_topology_of_large_Open_Connectome_networks_for_the_human_brain","translated_internal_url":"","created_at":"2021-05-02T02:09:23.931-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":51216508,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":66770119,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770119/thumbnails/1.jpg","file_name":"Odor_The_topology_srep27249_u.pdf","download_url":"https://www.academia.edu/attachments/66770119/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_topology_of_large_Open_Connectome_ne.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770119/Odor_The_topology_srep27249_u-libre.pdf?1619949323=\u0026response-content-disposition=attachment%3B+filename%3DThe_topology_of_large_Open_Connectome_ne.pdf\u0026Expires=1732457003\u0026Signature=VDfcAAldSOIK~mTirMMX3jgipkA8k~AM8kXy0SwiKUYpnfkBisY1~0tocU0kIPEMY72IVhVVljCspIIJ~ZvAi9jtYSnWwSw5R8SCdu306c6RCs~gstQWS70rOw61oi4elJxB3uJDkVTdbCLjAGthGGG7OlEbZCKMisdoCMrXCuf0jZuvGr986aq5qarCg4g3qhqSsoIY8oqhm9HGMFLDXzmkXtQbyEvaIBvrgpabftOmuuqbR~fJdqZYC4XY9mISwPiin6sk866QFquroK4U0QT3NFx7bT4ZFMkrZeHu6mQDnoSJ-1CN8YJBxoc3dhWAlb4mUb2p0nZ1m95pMV0gtQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"The_topology_of_large_Open_Connectome_networks_for_the_human_brain","translated_slug":"","page_count":11,"language":"en","content_type":"Work","owner":{"id":51216508,"first_name":"Michael","middle_initials":null,"last_name":"Gastner","page_name":"MGastner","domain_name":"independent","created_at":"2016-07-21T04:30:27.273-07:00","display_name":"Michael Gastner","url":"https://independent.academia.edu/MGastner"},"attachments":[{"id":66770119,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770119/thumbnails/1.jpg","file_name":"Odor_The_topology_srep27249_u.pdf","download_url":"https://www.academia.edu/attachments/66770119/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_topology_of_large_Open_Connectome_ne.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770119/Odor_The_topology_srep27249_u-libre.pdf?1619949323=\u0026response-content-disposition=attachment%3B+filename%3DThe_topology_of_large_Open_Connectome_ne.pdf\u0026Expires=1732457003\u0026Signature=VDfcAAldSOIK~mTirMMX3jgipkA8k~AM8kXy0SwiKUYpnfkBisY1~0tocU0kIPEMY72IVhVVljCspIIJ~ZvAi9jtYSnWwSw5R8SCdu306c6RCs~gstQWS70rOw61oi4elJxB3uJDkVTdbCLjAGthGGG7OlEbZCKMisdoCMrXCuf0jZuvGr986aq5qarCg4g3qhqSsoIY8oqhm9HGMFLDXzmkXtQbyEvaIBvrgpabftOmuuqbR~fJdqZYC4XY9mISwPiin6sk866QFquroK4U0QT3NFx7bT4ZFMkrZeHu6mQDnoSJ-1CN8YJBxoc3dhWAlb4mUb2p0nZ1m95pMV0gtQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="47865634"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/47865634/Scaling_in_the_gradient_contact_process"><img alt="Research paper thumbnail of Scaling in the gradient contact process" class="work-thumbnail" src="https://attachments.academia-assets.com/66770138/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/47865634/Scaling_in_the_gradient_contact_process">Scaling in the gradient contact process</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The gradient contact process displays a rich variety of scaling features which are relevant for b...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The gradient contact process displays a rich variety of scaling features which are relevant for biological processes and very interesting from a more theoretical point of view. We have investigated the finite size scaling of fluctuations as well as the geometrical features. On the one hand, the aim is to identify biologically relevant observables that would allow us to identify the contact process as the uni-versality class of the underlying microscopic mechanism in the generation of species patterns. Is it possible to infer the universality class of the reproduction mechanism in a biological system by looking at, say, areal photographs? On the other hand, the gradient contact process can be studied as a form of correlated gradient percolation.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="32023600cc3bd8cfd83c0f3fb7a174c8" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":66770138,"asset_id":47865634,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/66770138/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="47865634"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="47865634"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 47865634; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=47865634]").text(description); $(".js-view-count[data-work-id=47865634]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 47865634; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='47865634']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 47865634, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "32023600cc3bd8cfd83c0f3fb7a174c8" } } $('.js-work-strip[data-work-id=47865634]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":47865634,"title":"Scaling in the gradient contact process","translated_title":"","metadata":{"abstract":"The gradient contact process displays a rich variety of scaling features which are relevant for biological processes and very interesting from a more theoretical point of view. We have investigated the finite size scaling of fluctuations as well as the geometrical features. On the one hand, the aim is to identify biologically relevant observables that would allow us to identify the contact process as the uni-versality class of the underlying microscopic mechanism in the generation of species patterns. Is it possible to infer the universality class of the reproduction mechanism in a biological system by looking at, say, areal photographs? On the other hand, the gradient contact process can be studied as a form of correlated gradient percolation."},"translated_abstract":"The gradient contact process displays a rich variety of scaling features which are relevant for biological processes and very interesting from a more theoretical point of view. We have investigated the finite size scaling of fluctuations as well as the geometrical features. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="47865632"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/47865632/Shape_and_efficiency_in_growing_spatial_distribution_networks"><img alt="Research paper thumbnail of Shape and efficiency in growing spatial distribution networks" class="work-thumbnail" src="https://attachments.academia-assets.com/66770139/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/47865632/Shape_and_efficiency_in_growing_spatial_distribution_networks">Shape and efficiency in growing spatial distribution networks</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We study spatial distribution networks, such as gas pipelines or train tracks, which grow from an...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We study spatial distribution networks, such as gas pipelines or train tracks, which grow from an initial source or sink of the commodity transported by the network. 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Traffic patterns primarily depend on the users' preference for short paths through the network and spatial constraints for building the necessary connections. Here we study the traffic distribution in a spatial network model which takes both of these considerations into account. Assuming users always travel along the shortest path available, the appropriate measure for traffic flow along the links is a generalization of the usual concept of \"edge betweenness\". We find that for networks with a minimal total maintenance cost, a small number of connections must handle a disproportionate amount of traffic. However, if users can travel more directly between different points in the network, the maximum traffic can be greatly reduced.","publication_date":{"day":null,"month":null,"year":2008,"errors":{}},"publication_name":"Unifying Themes in Complex Systems","grobid_abstract_attachment_id":66770128},"translated_abstract":null,"internal_url":"https://www.academia.edu/47865628/Traffic_flow_in_a_spatial_network_model","translated_internal_url":"","created_at":"2021-05-02T02:09:23.535-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":51216508,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":66770128,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770128/thumbnails/1.jpg","file_name":"Traffic_flow_in_a_spatial_network_model20210502-4444-14whg2p.pdf","download_url":"https://www.academia.edu/attachments/66770128/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Traffic_flow_in_a_spatial_network_model.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770128/Traffic_flow_in_a_spatial_network_model20210502-4444-14whg2p.pdf?1619946628=\u0026response-content-disposition=attachment%3B+filename%3DTraffic_flow_in_a_spatial_network_model.pdf\u0026Expires=1732457003\u0026Signature=CEFOmlg1XJiU6gFCeUPUQ5x6OacgWwYEBxHxOQGhXbts4vxuQm2yP9QexR2OZ9lQMFzNH5D7JI3caHIK14P6ls0Qtj~OO8R1U2MRaDGpC6fc1cVkLrtv7EQDqtew8Vg-XdZ3OgMBitz3zt4gQ6ZJ-45M74Opx26-yJPG1XnjJNWV69FdqP9pxnZ4lOthsTCAMGmc3P0-N017ezB8NjCk19DAg-ldhJ7ZPMwQniA~aZRszG8M-FUxpEtjRKF42-XmZGFVeniQWiea7HkzWA4vghj-YGOQ19mNBE9AtmkKiAvGFt9chVefMiFmGc7a24lco3S445vlr8AnDTA6LgfTfg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Traffic_flow_in_a_spatial_network_model","translated_slug":"","page_count":8,"language":"en","content_type":"Work","owner":{"id":51216508,"first_name":"Michael","middle_initials":null,"last_name":"Gastner","page_name":"MGastner","domain_name":"independent","created_at":"2016-07-21T04:30:27.273-07:00","display_name":"Michael Gastner","url":"https://independent.academia.edu/MGastner"},"attachments":[{"id":66770128,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770128/thumbnails/1.jpg","file_name":"Traffic_flow_in_a_spatial_network_model20210502-4444-14whg2p.pdf","download_url":"https://www.academia.edu/attachments/66770128/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Traffic_flow_in_a_spatial_network_model.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770128/Traffic_flow_in_a_spatial_network_model20210502-4444-14whg2p.pdf?1619946628=\u0026response-content-disposition=attachment%3B+filename%3DTraffic_flow_in_a_spatial_network_model.pdf\u0026Expires=1732457003\u0026Signature=CEFOmlg1XJiU6gFCeUPUQ5x6OacgWwYEBxHxOQGhXbts4vxuQm2yP9QexR2OZ9lQMFzNH5D7JI3caHIK14P6ls0Qtj~OO8R1U2MRaDGpC6fc1cVkLrtv7EQDqtew8Vg-XdZ3OgMBitz3zt4gQ6ZJ-45M74Opx26-yJPG1XnjJNWV69FdqP9pxnZ4lOthsTCAMGmc3P0-N017ezB8NjCk19DAg-ldhJ7ZPMwQniA~aZRszG8M-FUxpEtjRKF42-XmZGFVeniQWiea7HkzWA4vghj-YGOQ19mNBE9AtmkKiAvGFt9chVefMiFmGc7a24lco3S445vlr8AnDTA6LgfTfg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":210359,"name":"Spatial Networks","url":"https://www.academia.edu/Documents/in/Spatial_Networks"},{"id":220371,"name":"Traffic Flow","url":"https://www.academia.edu/Documents/in/Traffic_Flow"},{"id":496530,"name":"Community Networks","url":"https://www.academia.edu/Documents/in/Community_Networks"},{"id":771878,"name":"Spatial structure","url":"https://www.academia.edu/Documents/in/Spatial_structure"},{"id":871148,"name":"Network Model","url":"https://www.academia.edu/Documents/in/Network_Model"},{"id":937133,"name":"Shortest Path","url":"https://www.academia.edu/Documents/in/Shortest_Path"},{"id":958863,"name":"Network Traffic","url":"https://www.academia.edu/Documents/in/Network_Traffic"},{"id":1232975,"name":"Wireless Communication","url":"https://www.academia.edu/Documents/in/Wireless_Communication-1"},{"id":2698374,"name":"Maintenance cost","url":"https://www.academia.edu/Documents/in/Maintenance_cost"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="47865627"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/47865627/Inefficiency_in_Networks_with_Multiple_Sources_and_Sinks"><img alt="Research paper thumbnail of Inefficiency in Networks with Multiple Sources and Sinks" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/47865627/Inefficiency_in_Networks_with_Multiple_Sources_and_Sinks">Inefficiency in Networks with Multiple Sources and Sinks</a></div><div class="wp-workCard_item"><span>Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering</span><span>, 2009</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We study the problem of optimizing traffic in decentralized transportation networks, where the co...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We study the problem of optimizing traffic in decentralized transportation networks, where the cost of a link depends on its congestion. If users of a transportation network are permitted to choose their own routes, they generally try to minimize their personal travel time. In the absence of centralized coordination, such a behavior can be inefficient for society and even for</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="47865627"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="47865627"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 47865627; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=47865627]").text(description); $(".js-view-count[data-work-id=47865627]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 47865627; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='47865627']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 47865627, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=47865627]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":47865627,"title":"Inefficiency in Networks with Multiple Sources and Sinks","translated_title":"","metadata":{"abstract":"We study the problem of optimizing traffic in decentralized transportation networks, where the cost of a link depends on its congestion. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="47865626"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/47865626/The_geography_and_carbon_footprint_of_mobile_phone_use_in_Cote_d_Ivoire"><img alt="Research paper thumbnail of The geography and carbon footprint of mobile phone use in Cote d’Ivoire" class="work-thumbnail" src="https://attachments.academia-assets.com/66770133/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/47865626/The_geography_and_carbon_footprint_of_mobile_phone_use_in_Cote_d_Ivoire">The geography and carbon footprint of mobile phone use in Cote d’Ivoire</a></div><div class="wp-workCard_item"><span>EPJ Data Science</span><span>, 2014</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ffa9e8b1505c86323cc374a134197642" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":66770133,"asset_id":47865626,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/66770133/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="47865626"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="47865626"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 47865626; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=47865626]").text(description); $(".js-view-count[data-work-id=47865626]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 47865626; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='47865626']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 47865626, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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Here we perform a series of spatial data analyses that reveal important geographic aspects of mobile phone use in Cote d'Ivoire. We first map the locations of base stations with respect to the population distribution and the number and duration of calls at each base station. On this basis, we estimate the energy consumed by the mobile phone network. Finally, we perform an analysis of inter-city mobility, and identify high-traffic roads in the country.","publication_date":{"day":null,"month":null,"year":2014,"errors":{}},"publication_name":"EPJ Data Science","grobid_abstract_attachment_id":66770133},"translated_abstract":null,"internal_url":"https://www.academia.edu/47865626/The_geography_and_carbon_footprint_of_mobile_phone_use_in_Cote_d_Ivoire","translated_internal_url":"","created_at":"2021-05-02T02:09:23.421-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":51216508,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":66770133,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770133/thumbnails/1.jpg","file_name":"The_geography_and_carbon_footprint_of_mo20210502-2462-1koyj4l.pdf","download_url":"https://www.academia.edu/attachments/66770133/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_geography_and_carbon_footprint_of_mo.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770133/The_geography_and_carbon_footprint_of_mo20210502-2462-1koyj4l.pdf?1619946631=\u0026response-content-disposition=attachment%3B+filename%3DThe_geography_and_carbon_footprint_of_mo.pdf\u0026Expires=1732457003\u0026Signature=Sk2WLR3y7Xm~MvRtwYYXrhlSBoVUcnypAdJgzIhOj6UoKQdjZvBdGKGkCW~XqVIb683L6~HemPXiEMXtBFY7glCEZjPYkaQNyOhvOJO9zVb4aJtOZY2Wz9wEMEf6QJFu~tw9jmQPFn3ABL1NZZYijyHu6Su4o8eZsDvgjIIxB6a5svxsboBy-OyJKg2DJma8xDdOgrd2tzVyO8CvQ-pTzGbtZgDlKWvKrDEknFqedLpMVnvB0eHooRCplWEmeKbnPd0BIrCrKdijNi714HmnGU~KlvnEy67sP0iv9K-~pCBK3TgWTdfuBbgZcrrMsUitiOmiCCtWOwPzVQeAB8BjDg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"The_geography_and_carbon_footprint_of_mobile_phone_use_in_Cote_d_Ivoire","translated_slug":"","page_count":15,"language":"en","content_type":"Work","owner":{"id":51216508,"first_name":"Michael","middle_initials":null,"last_name":"Gastner","page_name":"MGastner","domain_name":"independent","created_at":"2016-07-21T04:30:27.273-07:00","display_name":"Michael Gastner","url":"https://independent.academia.edu/MGastner"},"attachments":[{"id":66770133,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770133/thumbnails/1.jpg","file_name":"The_geography_and_carbon_footprint_of_mo20210502-2462-1koyj4l.pdf","download_url":"https://www.academia.edu/attachments/66770133/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_geography_and_carbon_footprint_of_mo.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770133/The_geography_and_carbon_footprint_of_mo20210502-2462-1koyj4l.pdf?1619946631=\u0026response-content-disposition=attachment%3B+filename%3DThe_geography_and_carbon_footprint_of_mo.pdf\u0026Expires=1732457003\u0026Signature=Sk2WLR3y7Xm~MvRtwYYXrhlSBoVUcnypAdJgzIhOj6UoKQdjZvBdGKGkCW~XqVIb683L6~HemPXiEMXtBFY7glCEZjPYkaQNyOhvOJO9zVb4aJtOZY2Wz9wEMEf6QJFu~tw9jmQPFn3ABL1NZZYijyHu6Su4o8eZsDvgjIIxB6a5svxsboBy-OyJKg2DJma8xDdOgrd2tzVyO8CvQ-pTzGbtZgDlKWvKrDEknFqedLpMVnvB0eHooRCplWEmeKbnPd0BIrCrKdijNi714HmnGU~KlvnEy67sP0iv9K-~pCBK3TgWTdfuBbgZcrrMsUitiOmiCCtWOwPzVQeAB8BjDg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="11163527" id="papers"><div class="js-work-strip profile--work_container" data-work-id="75363637"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75363637/DOI_10_1140_epjb_e2006_00046_8_THE_EUROPEAN_PHYSICAL_JOURNAL_B"><img alt="Research paper thumbnail of DOI: 10.1140/epjb/e2006-00046-8 THE EUROPEAN PHYSICAL JOURNAL B" class="work-thumbnail" src="https://attachments.academia-assets.com/83161584/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75363637/DOI_10_1140_epjb_e2006_00046_8_THE_EUROPEAN_PHYSICAL_JOURNAL_B">DOI: 10.1140/epjb/e2006-00046-8 THE EUROPEAN PHYSICAL JOURNAL B</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Abstract. We study networks that connect points in geographic space, such as transportation netwo...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Abstract. We study networks that connect points in geographic space, such as transportation networks and the Internet. We find that there are strong signatures in these networks of topography and use patterns, giving the networks shapes that are quite distinct from one another and from non-geographic networks. We offer an explanation of these differences in terms of the costs and benefits of transportation and communication, and give a simple model based on the Monte Carlo optimization of these costs and benefits that reproduces well the qualitative features of the networks studied. PACS. 89.75.Hc Networks and genealogical trees – 87.23.Ge Dynamics of social systems – 05.90.+m Other topics in statistical physics, thermodynamics, and nonlinear dynamical systems – 64.60.Ak Renormalization-group, fractal, and percolation studies of phase transitions 1</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="800b0720ff993fdabb65718740a87c6e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":83161584,"asset_id":75363637,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/83161584/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75363637"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75363637"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75363637; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75363637]").text(description); $(".js-view-count[data-work-id=75363637]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75363637; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75363637']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75363637, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "800b0720ff993fdabb65718740a87c6e" } } $('.js-work-strip[data-work-id=75363637]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75363637,"title":"DOI: 10.1140/epjb/e2006-00046-8 THE EUROPEAN PHYSICAL JOURNAL B","translated_title":"","metadata":{"abstract":"Abstract. 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We study networks that connect points in geographic space, such as transportation networks and the Internet. We find that there are strong signatures in these networks of topography and use patterns, giving the networks shapes that are quite distinct from one another and from non-geographic networks. We offer an explanation of these differences in terms of the costs and benefits of transportation and communication, and give a simple model based on the Monte Carlo optimization of these costs and benefits that reproduces well the qualitative features of the networks studied. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="69466588"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/69466588/Task_Based_Effectiveness_of_Interactive_Contiguous_Area_Cartograms"><img alt="Research paper thumbnail of Task-Based Effectiveness of Interactive Contiguous Area Cartograms" class="work-thumbnail" src="https://attachments.academia-assets.com/79554497/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/69466588/Task_Based_Effectiveness_of_Interactive_Contiguous_Area_Cartograms">Task-Based Effectiveness of Interactive Contiguous Area Cartograms</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Cartograms are map-based data visualizations in which the area of each map region is proportional...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Cartograms are map-based data visualizations in which the area of each map region is proportional to an associated numeric data value (e.g., population or gross domestic product). A cartogram is called contiguous if it conforms to this area principle while also keeping neighboring regions connected. Because of their distorted appearance, contiguous cartograms have been criticized as difficult to read. Some authors have suggested that cartograms may be more legible if they are accompanied by interactive features (e.g., animations, linked brushing, or infotips). We conducted an experiment to evaluate this claim. Participants had to perform visual analysis tasks with interactive and noninteractive contiguous cartograms. The task types covered various aspects of cartogram readability, ranging from elementary lookup tasks to synoptic tasks (i.e., tasks in which participants had to summarize high-level differences between two cartograms). Elementary tasks were carried out equally well wit...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="7c0ce60a28b9deff50bb4eeb55287839" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":79554497,"asset_id":69466588,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/79554497/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="69466588"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="69466588"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 69466588; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=69466588]").text(description); $(".js-view-count[data-work-id=69466588]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 69466588; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='69466588']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 69466588, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "7c0ce60a28b9deff50bb4eeb55287839" } } $('.js-work-strip[data-work-id=69466588]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":69466588,"title":"Task-Based Effectiveness of Interactive Contiguous Area Cartograms","translated_title":"","metadata":{"abstract":"Cartograms are map-based data visualizations in which the area of each map region is proportional to an associated numeric data value (e.g., population or gross domestic product). A cartogram is called contiguous if it conforms to this area principle while also keeping neighboring regions connected. Because of their distorted appearance, contiguous cartograms have been criticized as difficult to read. Some authors have suggested that cartograms may be more legible if they are accompanied by interactive features (e.g., animations, linked brushing, or infotips). We conducted an experiment to evaluate this claim. Participants had to perform visual analysis tasks with interactive and noninteractive contiguous cartograms. The task types covered various aspects of cartogram readability, ranging from elementary lookup tasks to synoptic tasks (i.e., tasks in which participants had to summarize high-level differences between two cartograms). Elementary tasks were carried out equally well wit...","publisher":"IEEE Transactions on Visualization and Computer Graphics","publication_date":{"day":null,"month":null,"year":2021,"errors":{}}},"translated_abstract":"Cartograms are map-based data visualizations in which the area of each map region is proportional to an associated numeric data value (e.g., population or gross domestic product). A cartogram is called contiguous if it conforms to this area principle while also keeping neighboring regions connected. Because of their distorted appearance, contiguous cartograms have been criticized as difficult to read. Some authors have suggested that cartograms may be more legible if they are accompanied by interactive features (e.g., animations, linked brushing, or infotips). We conducted an experiment to evaluate this claim. Participants had to perform visual analysis tasks with interactive and noninteractive contiguous cartograms. The task types covered various aspects of cartogram readability, ranging from elementary lookup tasks to synoptic tasks (i.e., tasks in which participants had to summarize high-level differences between two cartograms). 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="52402134"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/52402134/Mapping_the_inequality_of_the_global_distribution_of_seasonal_influenza_vaccine"><img alt="Research paper thumbnail of Mapping the inequality of the global distribution of seasonal influenza vaccine" class="work-thumbnail" src="https://attachments.academia-assets.com/69681936/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/52402134/Mapping_the_inequality_of_the_global_distribution_of_seasonal_influenza_vaccine">Mapping the inequality of the global distribution of seasonal influenza vaccine</a></div><div class="wp-workCard_item"><span>Environment and Planning A: Economy and Space</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">With an estimated annual worldwide death toll of between 290 000 and 650 000, seasonal influenza ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">With an estimated annual worldwide death toll of between 290 000 and 650 000, seasonal influenza remains one of the deadliest respiratory diseases. Influenza vaccines provide moderate to high protection and have been on the World Health Organization’s Model List of Essential Medicines since 1979. Approximately 490 million doses of influenza vaccine are produced per year, but an investigation of geographic allocation reveals enormous disparities. Here, we present two maps that visualise the inequality of the distribution across 195 countries: a conventional choropleth map and a cartogram. In combination, these two maps highlight the widespread lack of coverage in Africa and many parts of Asia. As COVID-19 vaccines are now being distributed in developed countries, data for seasonal influenza vaccine distribution emphasises the need for policymakers to ensure equitable access to COVID-19 vaccines.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="33e3a48cbff725548fd92bc98d75f229" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":69681936,"asset_id":52402134,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/69681936/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="52402134"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="52402134"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 52402134; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=52402134]").text(description); $(".js-view-count[data-work-id=52402134]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 52402134; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='52402134']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 52402134, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "33e3a48cbff725548fd92bc98d75f229" } } $('.js-work-strip[data-work-id=52402134]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":52402134,"title":"Mapping the inequality of the global distribution of seasonal influenza vaccine","translated_title":"","metadata":{"abstract":"With an estimated annual worldwide death toll of between 290 000 and 650 000, seasonal influenza remains one of the deadliest respiratory diseases. Influenza vaccines provide moderate to high protection and have been on the World Health Organization’s Model List of Essential Medicines since 1979. Approximately 490 million doses of influenza vaccine are produced per year, but an investigation of geographic allocation reveals enormous disparities. Here, we present two maps that visualise the inequality of the distribution across 195 countries: a conventional choropleth map and a cartogram. In combination, these two maps highlight the widespread lack of coverage in Africa and many parts of Asia. As COVID-19 vaccines are now being distributed in developed countries, data for seasonal influenza vaccine distribution emphasises the need for policymakers to ensure equitable access to COVID-19 vaccines.","publisher":"SAGE Publications","publication_name":"Environment and Planning A: Economy and Space"},"translated_abstract":"With an estimated annual worldwide death toll of between 290 000 and 650 000, seasonal influenza remains one of the deadliest respiratory diseases. Influenza vaccines provide moderate to high protection and have been on the World Health Organization’s Model List of Essential Medicines since 1979. Approximately 490 million doses of influenza vaccine are produced per year, but an investigation of geographic allocation reveals enormous disparities. Here, we present two maps that visualise the inequality of the distribution across 195 countries: a conventional choropleth map and a cartogram. In combination, these two maps highlight the widespread lack of coverage in Africa and many parts of Asia. As COVID-19 vaccines are now being distributed in developed countries, data for seasonal influenza vaccine distribution emphasises the need for policymakers to ensure equitable access to COVID-19 vaccines.","internal_url":"https://www.academia.edu/52402134/Mapping_the_inequality_of_the_global_distribution_of_seasonal_influenza_vaccine","translated_internal_url":"","created_at":"2021-09-15T00:39:18.927-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":51216508,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":69681936,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/69681936/thumbnails/1.jpg","file_name":"0308518X21998356.pdf","download_url":"https://www.academia.edu/attachments/69681936/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Mapping_the_inequality_of_the_global_dis.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/69681936/0308518X21998356-libre.pdf?1631692900=\u0026response-content-disposition=attachment%3B+filename%3DMapping_the_inequality_of_the_global_dis.pdf\u0026Expires=1732457002\u0026Signature=fq-UX7VKHim-cHGjs~Zl0oFmxb1MYibjpVqaBj7JCP7Z9uc3P068MyveQSPnYuhyuQlgriZLRYPdXe93mEgY4-Cz0IIPtvtO42UEnDAyCnGl5a2se1B4CmrRky6fuELr1KbiVVDt4hZ-ptlBN0lnzkF39WyXTzDd2djSv2l4cHzAWfYpaB-yzbd6My5~fJZ05xfatmfEiJ9wcDvzVhEwmpONqoL4cFc9844AiMov8EJdMZURwj7LgaMrVuAQwst9MfS-47yGvlsBlMg9Rq9GILyFbRs2oMl7zZQ9~n8HLlEhw8-B8GSrRWI06HirZ57N0~viVgsE2SGl-PCX2yZKyQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Mapping_the_inequality_of_the_global_distribution_of_seasonal_influenza_vaccine","translated_slug":"","page_count":4,"language":"en","content_type":"Work","owner":{"id":51216508,"first_name":"Michael","middle_initials":null,"last_name":"Gastner","page_name":"MGastner","domain_name":"independent","created_at":"2016-07-21T04:30:27.273-07:00","display_name":"Michael Gastner","url":"https://independent.academia.edu/MGastner"},"attachments":[{"id":69681936,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/69681936/thumbnails/1.jpg","file_name":"0308518X21998356.pdf","download_url":"https://www.academia.edu/attachments/69681936/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Mapping_the_inequality_of_the_global_dis.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/69681936/0308518X21998356-libre.pdf?1631692900=\u0026response-content-disposition=attachment%3B+filename%3DMapping_the_inequality_of_the_global_dis.pdf\u0026Expires=1732457002\u0026Signature=fq-UX7VKHim-cHGjs~Zl0oFmxb1MYibjpVqaBj7JCP7Z9uc3P068MyveQSPnYuhyuQlgriZLRYPdXe93mEgY4-Cz0IIPtvtO42UEnDAyCnGl5a2se1B4CmrRky6fuELr1KbiVVDt4hZ-ptlBN0lnzkF39WyXTzDd2djSv2l4cHzAWfYpaB-yzbd6My5~fJZ05xfatmfEiJ9wcDvzVhEwmpONqoL4cFc9844AiMov8EJdMZURwj7LgaMrVuAQwst9MfS-47yGvlsBlMg9Rq9GILyFbRs2oMl7zZQ9~n8HLlEhw8-B8GSrRWI06HirZ57N0~viVgsE2SGl-PCX2yZKyQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":69681935,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/69681935/thumbnails/1.jpg","file_name":"0308518X21998356.pdf","download_url":"https://www.academia.edu/attachments/69681935/download_file","bulk_download_file_name":"Mapping_the_inequality_of_the_global_dis.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/69681935/0308518X21998356-libre.pdf?1631692900=\u0026response-content-disposition=attachment%3B+filename%3DMapping_the_inequality_of_the_global_dis.pdf\u0026Expires=1732457002\u0026Signature=TGASL4qcmjjJHZahBFFWJYqCwDx3dCgRPaqduBbC5gL8ULMQ6xeIwwzE9E3cnWdOSahDoVf7Te6mbMn5wu~E9-L4fCpRT9-QYn5nZeAu733sapfyAOozUoxQFXA92V95UmfE0lENars9WOoo9ex2s6PWzZSsFAOugm-tBexJWM-rrPjF2exGWmDvOZwrAwq4C7~aVJ8xsHJUjqyafVK0pB0g1nnJapSE-ZEIDrhb~9yDKqCDMpse-KVssgBN8sRVCTyKzaWAxrx4D0NDA37h2dsnTpk~8RndsHkGr8fRgrqQjgIpWk5l7KEE~QO-blYlrOSTSQ4KE~ZWOeg2IjUzQg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":262,"name":"Human Geography","url":"https://www.academia.edu/Documents/in/Human_Geography"},{"id":20436,"name":"Urban And Regional Planning","url":"https://www.academia.edu/Documents/in/Urban_And_Regional_Planning"},{"id":27659,"name":"Applied Economics","url":"https://www.academia.edu/Documents/in/Applied_Economics"}],"urls":[{"id":11192389,"url":"http://journals.sagepub.com/doi/pdf/10.1177/0308518X21998356"}]}, dispatcherData: dispatcherData }); 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Social networking plays a crucial role in the appointment to a board so that an informed debate requires knowing where women are located in the network of directors. One way to quantify the network is by studying the links created by serving on the same board and by joint appointments on multiple boards. We analyse a network of ≈ 320 000 board members of 36 000 companies traded on stock exchanges all over the world, focusing specifically on the position of women in the network. Women only have ≈ 9 − 13% of all seats, but they are not marginalised. Applying metrics from social network analysis, we find that their influence is close to that of men. We do not find evidence to support previous claims that women play the role of \"queen bees\" that exclude other women from similar positions.","publication_name":"Complex Networks and Their Applications VIII","grobid_abstract_attachment_id":66770125},"translated_abstract":null,"internal_url":"https://www.academia.edu/47865641/Beyond_Fortune_500_Women_in_a_Global_Network_of_Directors","translated_internal_url":"","created_at":"2021-05-02T02:09:24.432-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":51216508,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":66770125,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770125/thumbnails/1.jpg","file_name":"1910.pdf","download_url":"https://www.academia.edu/attachments/66770125/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Beyond_Fortune_500_Women_in_a_Global_Net.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770125/1910-libre.pdf?1619949320=\u0026response-content-disposition=attachment%3B+filename%3DBeyond_Fortune_500_Women_in_a_Global_Net.pdf\u0026Expires=1732457002\u0026Signature=S3BVQHcqOniJYjxjPgGXR4vDF3RtxQeitZCWNg5bkDNUD5MgjxQGJwIgmuw6wObTcUGrehK9xE3DdnoHqQMsXgabxvmoM2AQa0Xd66ZdJP7F4~BV28-HP52HCVH5kt3nlGKTUvVxXDkqMuluBjGiRQagivNJAn7F0adXcmg1XqZTvQBnrIfdEhpUMfmO9lVxmRMhnCCmFhmpGqoypyRIRd1WdLTJd3wCwmjO0ths77daCGEyD-K8rkOTFjyNrZDd-z4NxPrEBtQemrsLREOUwnW8h4vAjoqpA~o3M5Jl5FbzSSdr5XxJzRUti-OMJ79mZTnDXhqmYdd3~sewof2-Wg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Beyond_Fortune_500_Women_in_a_Global_Network_of_Directors","translated_slug":"","page_count":14,"language":"en","content_type":"Work","owner":{"id":51216508,"first_name":"Michael","middle_initials":null,"last_name":"Gastner","page_name":"MGastner","domain_name":"independent","created_at":"2016-07-21T04:30:27.273-07:00","display_name":"Michael Gastner","url":"https://independent.academia.edu/MGastner"},"attachments":[{"id":66770125,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770125/thumbnails/1.jpg","file_name":"1910.pdf","download_url":"https://www.academia.edu/attachments/66770125/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Beyond_Fortune_500_Women_in_a_Global_Net.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770125/1910-libre.pdf?1619949320=\u0026response-content-disposition=attachment%3B+filename%3DBeyond_Fortune_500_Women_in_a_Global_Net.pdf\u0026Expires=1732457002\u0026Signature=S3BVQHcqOniJYjxjPgGXR4vDF3RtxQeitZCWNg5bkDNUD5MgjxQGJwIgmuw6wObTcUGrehK9xE3DdnoHqQMsXgabxvmoM2AQa0Xd66ZdJP7F4~BV28-HP52HCVH5kt3nlGKTUvVxXDkqMuluBjGiRQagivNJAn7F0adXcmg1XqZTvQBnrIfdEhpUMfmO9lVxmRMhnCCmFhmpGqoypyRIRd1WdLTJd3wCwmjO0ths77daCGEyD-K8rkOTFjyNrZDd-z4NxPrEBtQemrsLREOUwnW8h4vAjoqpA~o3M5Jl5FbzSSdr5XxJzRUti-OMJ79mZTnDXhqmYdd3~sewof2-Wg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[],"urls":[{"id":9908482,"url":"http://link.springer.com/content/pdf/10.1007/978-3-030-36683-4_47"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="47865640"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/47865640/Voter_model_on_networks_partitioned_into_two_cliques_of_arbitrary_sizes"><img alt="Research paper thumbnail of Voter model on networks partitioned into two cliques of arbitrary sizes" class="work-thumbnail" src="https://attachments.academia-assets.com/66770120/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/47865640/Voter_model_on_networks_partitioned_into_two_cliques_of_arbitrary_sizes">Voter model on networks partitioned into two cliques of arbitrary sizes</a></div><div class="wp-workCard_item"><span>Journal of Physics A: Mathematical and Theoretical</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="e8bf2ed2df330bad07b6efce4aa1a84b" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":66770120,"asset_id":47865640,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/66770120/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="47865640"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="47865640"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 47865640; 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In each update, one agent is chosen uniformly at random. The selected agent then copies the current opinion of a randomly selected neighbour. We investigate the voter model on a network with an exogenous community structure: two cliques (i.e. complete subgraphs) randomly linked by X interclique edges. We show that, counterintuitively, the mean consensus time is typically not a monotonically decreasing function of X. Cliques of fixed proportions with opposite initial opinions reach a consensus, on average, most quickly if X scales as N 3/2 , where N is the number of agents in the network. Hence, to accelerate a consensus between cliques, agents should connect to more members in the other clique as N increases but not to the extent that cliques lose their identity as distinct communities. We support our numerical results with an equation-based analysis. By interpolating between two asymptotic heterogeneous mean-field approximations, we obtain an equation for the mean consensus time that is in excellent agreement with simulations for all values of X.","publication_name":"Journal of Physics A: Mathematical and Theoretical","grobid_abstract_attachment_id":66770120},"translated_abstract":null,"internal_url":"https://www.academia.edu/47865640/Voter_model_on_networks_partitioned_into_two_cliques_of_arbitrary_sizes","translated_internal_url":"","created_at":"2021-05-02T02:09:24.316-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":51216508,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":66770120,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770120/thumbnails/1.jpg","file_name":"pdf.pdf","download_url":"https://www.academia.edu/attachments/66770120/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Voter_model_on_networks_partitioned_into.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770120/pdf-libre.pdf?1619949323=\u0026response-content-disposition=attachment%3B+filename%3DVoter_model_on_networks_partitioned_into.pdf\u0026Expires=1732457002\u0026Signature=RRLO9znFe1s5RVoXaatRqvm2u4H4lXkxEqic2fUkFiOnc7gGnBqKD25WKWR6~bzZMjBN3RUd4B368Lz75vNQZVkKRFBQ5VzdWBGfkfN0VJ8wWAj~rwCkYeJAfQK3oavaKEGWekL067nZkklpu-M85P4JQtXKadGdeyIAfRWdZdNrBJGvDWxbXbqujqh4QcKHGK4yK0KC0U4IEgELgqg6KVSD9zjqkJyImfAjWA-uoq~hg4sKMjzU6Lk5n4CO-tIEv26MB276VKBCE2agAMSY3SbVULIQ1rrgKS3rbl1TYjo9aV55FdYhkIG~t0P9d4jaguKYwAkTAyA96r0zAkS-tA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Voter_model_on_networks_partitioned_into_two_cliques_of_arbitrary_sizes","translated_slug":"","page_count":19,"language":"en","content_type":"Work","owner":{"id":51216508,"first_name":"Michael","middle_initials":null,"last_name":"Gastner","page_name":"MGastner","domain_name":"independent","created_at":"2016-07-21T04:30:27.273-07:00","display_name":"Michael Gastner","url":"https://independent.academia.edu/MGastner"},"attachments":[{"id":66770120,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770120/thumbnails/1.jpg","file_name":"pdf.pdf","download_url":"https://www.academia.edu/attachments/66770120/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Voter_model_on_networks_partitioned_into.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770120/pdf-libre.pdf?1619949323=\u0026response-content-disposition=attachment%3B+filename%3DVoter_model_on_networks_partitioned_into.pdf\u0026Expires=1732457002\u0026Signature=RRLO9znFe1s5RVoXaatRqvm2u4H4lXkxEqic2fUkFiOnc7gGnBqKD25WKWR6~bzZMjBN3RUd4B368Lz75vNQZVkKRFBQ5VzdWBGfkfN0VJ8wWAj~rwCkYeJAfQK3oavaKEGWekL067nZkklpu-M85P4JQtXKadGdeyIAfRWdZdNrBJGvDWxbXbqujqh4QcKHGK4yK0KC0U4IEgELgqg6KVSD9zjqkJyImfAjWA-uoq~hg4sKMjzU6Lk5n4CO-tIEv26MB276VKBCE2agAMSY3SbVULIQ1rrgKS3rbl1TYjo9aV55FdYhkIG~t0P9d4jaguKYwAkTAyA96r0zAkS-tA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":80414,"name":"Mathematical Sciences","url":"https://www.academia.edu/Documents/in/Mathematical_Sciences"},{"id":118582,"name":"Physical sciences","url":"https://www.academia.edu/Documents/in/Physical_sciences"}],"urls":[{"id":9908481,"url":"http://iopscience.iop.org/article/10.1088/1751-8121/ab542f"}]}, dispatcherData: dispatcherData }); 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Cartograms are called \"contiguous\" if they maintain the topology of the conventional map (i.e. regions are displayed as neighbours on the cartogram if and only if they are geographic neighbours) [1]. An example of a contiguous cartogram, showing the 48 conterminous states of the USA with an area proportional to their population, is shown on the right of . Such maps are an invaluable addition to a professional geographer's toolbox. However, producing contiguous cartograms should not be the privilege of only a handful of experts in cartography. Journalists or bloggers, for example, may also benefit from a cartogram as an intriguing illustration of their own data. Similarly, high school students may enrich a term paper with a cartogram that can summarize data more effectively than raw numeric tables.","publication_name":"Abstracts of the ICA","grobid_abstract_attachment_id":66770109},"translated_abstract":null,"internal_url":"https://www.academia.edu/47865639/GO_CART_IO_A_Web_Application_for_Generating_Contiguous_Cartograms","translated_internal_url":"","created_at":"2021-05-02T02:09:24.235-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":51216508,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":66770109,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770109/thumbnails/1.jpg","file_name":"ica-abs-1-333-2019.pdf","download_url":"https://www.academia.edu/attachments/66770109/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"GO_CART_IO_A_Web_Application_for_Generat.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770109/ica-abs-1-333-2019-libre.pdf?1619949320=\u0026response-content-disposition=attachment%3B+filename%3DGO_CART_IO_A_Web_Application_for_Generat.pdf\u0026Expires=1732457002\u0026Signature=FsiC0pVl~PirIZZ4gOxy-wmsFAHxlWClEpZm6KlKmcD8mCoX-d-X7d2MALlu6NkE~bW1Xy~zOyBQi3GEQpneZILb2V1S5CAusvedj6xFeEqousNav6noU29qePTkITA16GXDlpftVH4-pQiBjtZSnogEK2nOxXUROR9wph4HXRTfelMxjNI3txCfKMaAks5WxGXAApDcd4vcscDI6fTQUbXgnMNqeU7zPWXr1cPt8Q82aAJEx~phpubfG7Ffw6XRdNVTd5Az5FN3sTjiiXrH4Uq3TUAAvodtER5hiVasZXR7B5SaeC~~X6Vdqepn8mNa6rCVTcGKnTZ-GZU5Q3UMbg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"GO_CART_IO_A_Web_Application_for_Generating_Contiguous_Cartograms","translated_slug":"","page_count":2,"language":"en","content_type":"Work","owner":{"id":51216508,"first_name":"Michael","middle_initials":null,"last_name":"Gastner","page_name":"MGastner","domain_name":"independent","created_at":"2016-07-21T04:30:27.273-07:00","display_name":"Michael Gastner","url":"https://independent.academia.edu/MGastner"},"attachments":[{"id":66770109,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770109/thumbnails/1.jpg","file_name":"ica-abs-1-333-2019.pdf","download_url":"https://www.academia.edu/attachments/66770109/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMiw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"GO_CART_IO_A_Web_Application_for_Generat.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770109/ica-abs-1-333-2019-libre.pdf?1619949320=\u0026response-content-disposition=attachment%3B+filename%3DGO_CART_IO_A_Web_Application_for_Generat.pdf\u0026Expires=1732457002\u0026Signature=FsiC0pVl~PirIZZ4gOxy-wmsFAHxlWClEpZm6KlKmcD8mCoX-d-X7d2MALlu6NkE~bW1Xy~zOyBQi3GEQpneZILb2V1S5CAusvedj6xFeEqousNav6noU29qePTkITA16GXDlpftVH4-pQiBjtZSnogEK2nOxXUROR9wph4HXRTfelMxjNI3txCfKMaAks5WxGXAApDcd4vcscDI6fTQUbXgnMNqeU7zPWXr1cPt8Q82aAJEx~phpubfG7Ffw6XRdNVTd5Az5FN3sTjiiXrH4Uq3TUAAvodtER5hiVasZXR7B5SaeC~~X6Vdqepn8mNa6rCVTcGKnTZ-GZU5Q3UMbg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":66770110,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770110/thumbnails/1.jpg","file_name":"ica-abs-1-333-2019.pdf","download_url":"https://www.academia.edu/attachments/66770110/download_file","bulk_download_file_name":"GO_CART_IO_A_Web_Application_for_Generat.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770110/ica-abs-1-333-2019-libre.pdf?1619949320=\u0026response-content-disposition=attachment%3B+filename%3DGO_CART_IO_A_Web_Application_for_Generat.pdf\u0026Expires=1732457002\u0026Signature=hINIPGJ0GHWoBhbH7KWSrhI26f9Fiy6f4DTKBAgGl1FbJPf-8oi-I8NKqPCALA0J~awz-EIXcHrV3hQi2ZudHmkvy8KWUR9VhGE6h8Js295WpqLCGs3OAHqN2np92rkA6K~nc-M38snKWXYcVJrI-yYTDAqWw0Ck7g8LYBsb1t16H5~W~AEyLoyxD91FIOmC~Zp6AP6rCiJnBrm3uQYWc3r1jJh5pkhL~TzKkXE~rABH2K32kyDZy5vuQGIr9xIOCr6AqnvJj~ca3D-ZmmjzsNFOhhbRJ9FvVFKYSRypK5pZoLzY6Nn3IxcwQKFGcE4f~k5Vx-DDVPkIDHqLIVjeOw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[],"urls":[{"id":9908480,"url":"https://www.abstr-int-cartogr-assoc.net/1/333/2019/ica-abs-1-333-2019.pdf"}]}, dispatcherData: dispatcherData }); 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In plenty of empirical contexts, publicly revealed opinions are not necessarily in line with internal opinions, causing complex social influence dynamics. We study to what extent hypocrisy is sustained during opinion formation and how hidden opinions change the convergence to consensus in a group. We build and analyze a modified version of the voter model with hypocrisy in a complete graph with a neutral competition between two alternatives. We compare the process from various initial conditions, varying the proportions between the two opinions in the external (revealed) and internal (hidden) layer. According to our results, hypocrisy always prolongs the time needed for reaching a consensus. In a complete graph, this time span increases linearly with group size. We find that the group-level opinion emerges in two steps: (1) a fast and directional process, during which the number of the two kinds of hypocrites equalizes; and (2) a slower, random drift of opinions. During stage (2), the ratio of opinions in the external layer is approximately equal to the ratio in the internal layer; that is, the hidden opinions do not differ significantly from the revealed ones at the group level. We furthermore find that the initial abundances of opinions, but not the initial prevalence of hypocrisy, predicts the mean consensus time and determines the opinions' probabilities of winning. These insights highlight the unimportance of hypocrisy in consensus formation under neutral conditions. Our results have important societal implications in relation to hidden voter preferences in polls and improve our understanding of opinion formation in a more realistic setting than that of conventional voter models. program (GINOP-2.3.2-15-and behavior of others. The dynamics resulting from these interactions have been studied in various models . One of the most appealing and widely studied representations is the voter model due to its simplicity . The paradigmatic voter model (which we will call the Basic Voter Model, BVM) represents the opinions of individuals as a binary variable in a single opinion dimension. At each update, an individual adopts the opinion of one of his acquaintances. 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Unlike conventional bar or pie charts, cartograms can represent correctly which regions share common borders, resulting in insightful visualizations that can be the basis for further spatial statistical analysis. Computer programs can assist data scientists in preparing cartograms, but developing an algorithm that can quickly transform every coordinate on the map (including points that are not exactly on a border) while generating recognizable images has remained a challenge. Methods that translate the cartographic deformations into physics-inspired equations of motion have become popular, but solving these equations with sufficient accuracy can still take several minutes on current hardware. 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Here we analyze several large data sets for the human brain network made available by the Open Connectome Project. We apply statistical model selection to characterize the degree distributions of graphs containing up to  0 1 6 nodes and  0 1 8 edges. A three-parameter generalized Weibull (also known as a stretched exponential) distribution is a good fit to most of the observed degree distributions. For almost all networks, simple power laws cannot fit the data, but in some cases there is statistical support for power laws with an exponential cutoff. We also calculate the topological (graph) dimension D and the small-world coefficient σ of these networks. While σ suggests a small-world topology, we found that D \u003c 4 showing that long-distance connections provide only a small correction to the topology of the embedding three-dimensional space.","publication_date":{"day":null,"month":null,"year":2016,"errors":{}},"publication_name":"Scientific Reports","grobid_abstract_attachment_id":66770119},"translated_abstract":null,"internal_url":"https://www.academia.edu/47865635/The_topology_of_large_Open_Connectome_networks_for_the_human_brain","translated_internal_url":"","created_at":"2021-05-02T02:09:23.931-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":51216508,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":66770119,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770119/thumbnails/1.jpg","file_name":"Odor_The_topology_srep27249_u.pdf","download_url":"https://www.academia.edu/attachments/66770119/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_topology_of_large_Open_Connectome_ne.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770119/Odor_The_topology_srep27249_u-libre.pdf?1619949323=\u0026response-content-disposition=attachment%3B+filename%3DThe_topology_of_large_Open_Connectome_ne.pdf\u0026Expires=1732457003\u0026Signature=VDfcAAldSOIK~mTirMMX3jgipkA8k~AM8kXy0SwiKUYpnfkBisY1~0tocU0kIPEMY72IVhVVljCspIIJ~ZvAi9jtYSnWwSw5R8SCdu306c6RCs~gstQWS70rOw61oi4elJxB3uJDkVTdbCLjAGthGGG7OlEbZCKMisdoCMrXCuf0jZuvGr986aq5qarCg4g3qhqSsoIY8oqhm9HGMFLDXzmkXtQbyEvaIBvrgpabftOmuuqbR~fJdqZYC4XY9mISwPiin6sk866QFquroK4U0QT3NFx7bT4ZFMkrZeHu6mQDnoSJ-1CN8YJBxoc3dhWAlb4mUb2p0nZ1m95pMV0gtQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"The_topology_of_large_Open_Connectome_networks_for_the_human_brain","translated_slug":"","page_count":11,"language":"en","content_type":"Work","owner":{"id":51216508,"first_name":"Michael","middle_initials":null,"last_name":"Gastner","page_name":"MGastner","domain_name":"independent","created_at":"2016-07-21T04:30:27.273-07:00","display_name":"Michael Gastner","url":"https://independent.academia.edu/MGastner"},"attachments":[{"id":66770119,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/66770119/thumbnails/1.jpg","file_name":"Odor_The_topology_srep27249_u.pdf","download_url":"https://www.academia.edu/attachments/66770119/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_topology_of_large_Open_Connectome_ne.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/66770119/Odor_The_topology_srep27249_u-libre.pdf?1619949323=\u0026response-content-disposition=attachment%3B+filename%3DThe_topology_of_large_Open_Connectome_ne.pdf\u0026Expires=1732457003\u0026Signature=VDfcAAldSOIK~mTirMMX3jgipkA8k~AM8kXy0SwiKUYpnfkBisY1~0tocU0kIPEMY72IVhVVljCspIIJ~ZvAi9jtYSnWwSw5R8SCdu306c6RCs~gstQWS70rOw61oi4elJxB3uJDkVTdbCLjAGthGGG7OlEbZCKMisdoCMrXCuf0jZuvGr986aq5qarCg4g3qhqSsoIY8oqhm9HGMFLDXzmkXtQbyEvaIBvrgpabftOmuuqbR~fJdqZYC4XY9mISwPiin6sk866QFquroK4U0QT3NFx7bT4ZFMkrZeHu6mQDnoSJ-1CN8YJBxoc3dhWAlb4mUb2p0nZ1m95pMV0gtQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="47865634"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/47865634/Scaling_in_the_gradient_contact_process"><img alt="Research paper thumbnail of Scaling in the gradient contact process" class="work-thumbnail" src="https://attachments.academia-assets.com/66770138/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/47865634/Scaling_in_the_gradient_contact_process">Scaling in the gradient contact process</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The gradient contact process displays a rich variety of scaling features which are relevant for b...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The gradient contact process displays a rich variety of scaling features which are relevant for biological processes and very interesting from a more theoretical point of view. We have investigated the finite size scaling of fluctuations as well as the geometrical features. On the one hand, the aim is to identify biologically relevant observables that would allow us to identify the contact process as the uni-versality class of the underlying microscopic mechanism in the generation of species patterns. Is it possible to infer the universality class of the reproduction mechanism in a biological system by looking at, say, areal photographs? On the other hand, the gradient contact process can be studied as a form of correlated gradient percolation.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="32023600cc3bd8cfd83c0f3fb7a174c8" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":66770138,"asset_id":47865634,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/66770138/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="47865634"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="47865634"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 47865634; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=47865634]").text(description); $(".js-view-count[data-work-id=47865634]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 47865634; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='47865634']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 47865634, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "32023600cc3bd8cfd83c0f3fb7a174c8" } } $('.js-work-strip[data-work-id=47865634]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":47865634,"title":"Scaling in the gradient contact process","translated_title":"","metadata":{"abstract":"The gradient contact process displays a rich variety of scaling features which are relevant for biological processes and very interesting from a more theoretical point of view. We have investigated the finite size scaling of fluctuations as well as the geometrical features. On the one hand, the aim is to identify biologically relevant observables that would allow us to identify the contact process as the uni-versality class of the underlying microscopic mechanism in the generation of species patterns. Is it possible to infer the universality class of the reproduction mechanism in a biological system by looking at, say, areal photographs? On the other hand, the gradient contact process can be studied as a form of correlated gradient percolation."},"translated_abstract":"The gradient contact process displays a rich variety of scaling features which are relevant for biological processes and very interesting from a more theoretical point of view. We have investigated the finite size scaling of fluctuations as well as the geometrical features. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="47865632"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/47865632/Shape_and_efficiency_in_growing_spatial_distribution_networks"><img alt="Research paper thumbnail of Shape and efficiency in growing spatial distribution networks" class="work-thumbnail" src="https://attachments.academia-assets.com/66770139/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/47865632/Shape_and_efficiency_in_growing_spatial_distribution_networks">Shape and efficiency in growing spatial distribution networks</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We study spatial distribution networks, such as gas pipelines or train tracks, which grow from an...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We study spatial distribution networks, such as gas pipelines or train tracks, which grow from an initial source or sink of the commodity transported by the network. The efficiency depends on two properties. First, the paths to t he root are ideally not much longer than the &quot;crow flies&quot; distance. 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Traffic patterns primarily depend on the users' preference for short paths through the network and spatial constraints for building the necessary connections. Here we study the traffic distribution in a spatial network model which takes both of these considerations into account. Assuming users always travel along the shortest path available, the appropriate measure for traffic flow along the links is a generalization of the usual concept of \"edge betweenness\". We find that for networks with a minimal total maintenance cost, a small number of connections must handle a disproportionate amount of traffic. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="47865627"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/47865627/Inefficiency_in_Networks_with_Multiple_Sources_and_Sinks"><img alt="Research paper thumbnail of Inefficiency in Networks with Multiple Sources and Sinks" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/47865627/Inefficiency_in_Networks_with_Multiple_Sources_and_Sinks">Inefficiency in Networks with Multiple Sources and Sinks</a></div><div class="wp-workCard_item"><span>Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering</span><span>, 2009</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We study the problem of optimizing traffic in decentralized transportation networks, where the co...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We study the problem of optimizing traffic in decentralized transportation networks, where the cost of a link depends on its congestion. If users of a transportation network are permitted to choose their own routes, they generally try to minimize their personal travel time. In the absence of centralized coordination, such a behavior can be inefficient for society and even for</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="47865627"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="47865627"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 47865627; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=47865627]").text(description); $(".js-view-count[data-work-id=47865627]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 47865627; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='47865627']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 47865627, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=47865627]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":47865627,"title":"Inefficiency in Networks with Multiple Sources and Sinks","translated_title":"","metadata":{"abstract":"We study the problem of optimizing traffic in decentralized transportation networks, where the cost of a link depends on its congestion. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="47865626"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/47865626/The_geography_and_carbon_footprint_of_mobile_phone_use_in_Cote_d_Ivoire"><img alt="Research paper thumbnail of The geography and carbon footprint of mobile phone use in Cote d’Ivoire" class="work-thumbnail" src="https://attachments.academia-assets.com/66770133/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/47865626/The_geography_and_carbon_footprint_of_mobile_phone_use_in_Cote_d_Ivoire">The geography and carbon footprint of mobile phone use in Cote d’Ivoire</a></div><div class="wp-workCard_item"><span>EPJ Data Science</span><span>, 2014</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ffa9e8b1505c86323cc374a134197642" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":66770133,"asset_id":47865626,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/66770133/download_file?st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&st=MTczMjQ1MzQwMyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="47865626"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="47865626"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 47865626; 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