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Lili Shang - Academia.edu

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href="https://www.academia.edu/103477130/Compressive_Strength_Parallel_to_the_Grain_in_Relation_to_Moisture_Content_inCalamus_simplicifoliusCane"><img alt="Research paper thumbnail of Compressive Strength Parallel to the Grain in Relation to Moisture Content inCalamus simplicifoliusCane" class="work-thumbnail" src="https://attachments.academia-assets.com/103474508/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/103477130/Compressive_Strength_Parallel_to_the_Grain_in_Relation_to_Moisture_Content_inCalamus_simplicifoliusCane">Compressive Strength Parallel to the Grain in Relation to Moisture Content inCalamus simplicifoliusCane</a></div><div class="wp-workCard_item"><span>Forest Products Journal</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This research aimed to investigate the compressive fracture behavior and the compressive strength...</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">This research aimed to investigate the compressive fracture behavior and the compressive strength parallel to the grain in relation to moisture contents (MC) below and above the fiber saturation point (FSP) in Calamus simplicifolius cane. FSP of the rattan was investigated using a dynamic vapor sorption (DVS) apparatus, and the fracture behaviors of compression parallel to grain were analyzed by three-dimensional X-ray microcomputed tomography. The study indicated that the value of FSP derived from the DVS method was 25 percent. The average compressive strength parallel to the grain was found to be 39 MPa at 3 percent MC, 30 MPa at 10 percent MC, 17 MPa at 12 percent MC, 12 MPa at 27 percent MC, and 10 MPa at 45 percent MC. The strains of the yield and densification stage were prolonged with increasing MC, whereas the stress in the linear elastic stage decreased with increasing MC. The cracks of the rattan core and the deflection angle at higher MC were larger than that of low MC. B...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="eb746d982088e9fa0717d143d47a8cc2" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474508,&quot;asset_id&quot;:103477130,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474508/download_file?st=MTczMjM4NTcwMiw4LjIyMi4yMDguMTQ2&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="103477130"><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="103477130"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477130; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477130]").text(description); $(".js-view-count[data-work-id=103477130]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477130; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477130']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477130, 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: "eb746d982088e9fa0717d143d47a8cc2" } } $('.js-work-strip[data-work-id=103477130]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477130,"title":"Compressive Strength Parallel to the Grain in Relation to Moisture Content inCalamus simplicifoliusCane","translated_title":"","metadata":{"abstract":"This research aimed to investigate the compressive fracture behavior and the compressive strength parallel to the grain in relation to moisture contents (MC) below and above the fiber saturation point (FSP) in Calamus simplicifolius cane. 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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="103477125"><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/103477125/3D_Visualization_of_Bamboo_Node_s_Vascular_Bundle"><img alt="Research paper thumbnail of 3D Visualization of Bamboo Node’s Vascular Bundle" 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/103477125/3D_Visualization_of_Bamboo_Node_s_Vascular_Bundle">3D Visualization of Bamboo Node’s Vascular Bundle</a></div><div class="wp-workCard_item"><span>Forests</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The vascular bundle is an important structural unit that determines the growth and properties of ...</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 vascular bundle is an important structural unit that determines the growth and properties of bamboo. A high-resolution X-ray microtomography (μCT) was used to observe and reconstruct a three-dimensional (3D) morphometry model of the vascular bundle of the Qiongzhuea tumidinoda node due to its advantages of quick, nondestructive, and accurate testing of plant internal structure. The results showed that the morphology of vascular bundles varied significantly in the axial direction. In the cross-section, the number of axial vascular bundles reached a maximum at the lower end of the sheath scar, and the minimum of it was at the middle of the diaphragm. The frequency of axial vascular bundles decreased from the lower end of the node to the nodal ridge, and subsequently increased until the upper end of the bamboo node. The proportion of parenchyma, fibers, and conducting tissue was 65.7%, 30.5%, and 3.8%, respectively. The conducting tissues were intertwined to form a complex 3D netwo...</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="103477125"><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="103477125"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477125; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477125]").text(description); $(".js-view-count[data-work-id=103477125]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477125; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477125']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477125, 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" } } $('.js-work-strip[data-work-id=103477125]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477125,"title":"3D Visualization of Bamboo Node’s Vascular Bundle","translated_title":"","metadata":{"abstract":"The vascular bundle is an important structural unit that determines the growth and properties of bamboo. A high-resolution X-ray microtomography (μCT) was used to observe and reconstruct a three-dimensional (3D) morphometry model of the vascular bundle of the Qiongzhuea tumidinoda node due to its advantages of quick, nondestructive, and accurate testing of plant internal structure. The results showed that the morphology of vascular bundles varied significantly in the axial direction. In the cross-section, the number of axial vascular bundles reached a maximum at the lower end of the sheath scar, and the minimum of it was at the middle of the diaphragm. The frequency of axial vascular bundles decreased from the lower end of the node to the nodal ridge, and subsequently increased until the upper end of the bamboo node. The proportion of parenchyma, fibers, and conducting tissue was 65.7%, 30.5%, and 3.8%, respectively. The conducting tissues were intertwined to form a complex 3D netwo...","publisher":"MDPI AG","publication_name":"Forests"},"translated_abstract":"The vascular bundle is an important structural unit that determines the growth and properties of bamboo. A high-resolution X-ray microtomography (μCT) was used to observe and reconstruct a three-dimensional (3D) morphometry model of the vascular bundle of the Qiongzhuea tumidinoda node due to its advantages of quick, nondestructive, and accurate testing of plant internal structure. The results showed that the morphology of vascular bundles varied significantly in the axial direction. In the cross-section, the number of axial vascular bundles reached a maximum at the lower end of the sheath scar, and the minimum of it was at the middle of the diaphragm. The frequency of axial vascular bundles decreased from the lower end of the node to the nodal ridge, and subsequently increased until the upper end of the bamboo node. The proportion of parenchyma, fibers, and conducting tissue was 65.7%, 30.5%, and 3.8%, respectively. The conducting tissues were intertwined to form a complex 3D netwo...","internal_url":"https://www.academia.edu/103477125/3D_Visualization_of_Bamboo_Node_s_Vascular_Bundle","translated_internal_url":"","created_at":"2023-06-17T07:31:39.403-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":274044901,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"3D_Visualization_of_Bamboo_Node_s_Vascular_Bundle","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":274044901,"first_name":"Lili","middle_initials":null,"last_name":"Shang","page_name":"LiliShang2","domain_name":"independent","created_at":"2023-06-17T07:30:42.428-07:00","display_name":"Lili Shang","url":"https://independent.academia.edu/LiliShang2"},"attachments":[],"research_interests":[{"id":511,"name":"Materials Science","url":"https://www.academia.edu/Documents/in/Materials_Science"},{"id":39890,"name":"Bamboo","url":"https://www.academia.edu/Documents/in/Bamboo"},{"id":54589,"name":"Anatomy","url":"https://www.academia.edu/Documents/in/Anatomy"},{"id":117033,"name":"Forests","url":"https://www.academia.edu/Documents/in/Forests"},{"id":178994,"name":"Vascular tissue engineering","url":"https://www.academia.edu/Documents/in/Vascular_tissue_engineering"}],"urls":[{"id":32327746,"url":"https://www.mdpi.com/1999-4907/12/12/1799/pdf"}]}, 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="103477121"><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/103477121/Quantitative_characterization_of_bamboo_cortex_structure_based_on_X_ray_microtomography"><img alt="Research paper thumbnail of Quantitative characterization of bamboo cortex structure based on X-ray microtomography" class="work-thumbnail" src="https://attachments.academia-assets.com/103474541/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/103477121/Quantitative_characterization_of_bamboo_cortex_structure_based_on_X_ray_microtomography">Quantitative characterization of bamboo cortex structure based on X-ray microtomography</a></div><div class="wp-workCard_item"><span>Cellulose</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="e84688e9d20de3cb4727a5a13798cd99" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474541,&quot;asset_id&quot;:103477121,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474541/download_file?st=MTczMjM4NTcwMiw4LjIyMi4yMDguMTQ2&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="103477121"><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="103477121"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477121; 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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="103477119"><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/103477119/Distinguish_the_Wild_from_Cultivated_Agarwood_by_Using_HPLC_Combined_with_PCA"><img alt="Research paper thumbnail of Distinguish the Wild from Cultivated Agarwood by Using HPLC Combined with PCA" class="work-thumbnail" src="https://attachments.academia-assets.com/103474505/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/103477119/Distinguish_the_Wild_from_Cultivated_Agarwood_by_Using_HPLC_Combined_with_PCA">Distinguish the Wild from Cultivated Agarwood by Using HPLC Combined with PCA</a></div><div class="wp-workCard_item"><span>Asian Journal of Plant Science &amp; Research</span><span>, 2017</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Agarwood is the dark resinous and aromatic wood harvested from Aquilaria trees belong to Thymelae...</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">Agarwood is the dark resinous and aromatic wood harvested from Aquilaria trees belong to Thymelaeaceae. It has great value as a raw material for perfume and traditional Chinese medicine. Agarwood is wildly accepted from natural forests and plantations. The former has more highly valued. This paper focused on distinguishing the wild agarwood from sustainably produced cultivated agarwood using high performance liquid chromatography (HPLC) combined with statistical analysis. 10 cultivated and 30 wild agarwood samples were used to respectively establish agarwood HPLC characteristic chromatograms by multivariate analysis. By the retention time and peak area analyses of two types of agarwood, characteristic chromatograms and characteristic peaks (i.e., 10 characteristic peaks of cultivated agarwood (CPC1-10) and 9 characteristic peaks of wild ones (CPW1-9)) were established. The principal component analysis (PCA) and sample validation further verified the accuracy and feasibility of the c...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0fadb5d6bd4a87400216d9bc1043df26" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474505,&quot;asset_id&quot;:103477119,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474505/download_file?st=MTczMjM4NTcwMiw4LjIyMi4yMDguMTQ2&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="103477119"><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="103477119"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477119; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477119]").text(description); $(".js-view-count[data-work-id=103477119]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477119; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477119']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477119, 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: "0fadb5d6bd4a87400216d9bc1043df26" } } $('.js-work-strip[data-work-id=103477119]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477119,"title":"Distinguish the Wild from Cultivated Agarwood by Using HPLC Combined with PCA","translated_title":"","metadata":{"abstract":"Agarwood is the dark resinous and aromatic wood harvested from Aquilaria trees belong to Thymelaeaceae. 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The principal component analysis (PCA) and sample validation further verified the accuracy and feasibility of the c...","publication_date":{"day":null,"month":null,"year":2017,"errors":{}},"publication_name":"Asian Journal of Plant Science \u0026 Research"},"translated_abstract":"Agarwood is the dark resinous and aromatic wood harvested from Aquilaria trees belong to Thymelaeaceae. It has great value as a raw material for perfume and traditional Chinese medicine. Agarwood is wildly accepted from natural forests and plantations. The former has more highly valued. This paper focused on distinguishing the wild agarwood from sustainably produced cultivated agarwood using high performance liquid chromatography (HPLC) combined with statistical analysis. 10 cultivated and 30 wild agarwood samples were used to respectively establish agarwood HPLC characteristic chromatograms by multivariate analysis. By the retention time and peak area analyses of two types of agarwood, characteristic chromatograms and characteristic peaks (i.e., 10 characteristic peaks of cultivated agarwood (CPC1-10) and 9 characteristic peaks of wild ones (CPW1-9)) were established. 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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="103477110"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/103477110/Design_and_implementation_of_bridge_structure_health_monitoring_data_analysis_platform"><img alt="Research paper thumbnail of Design and implementation of bridge structure health monitoring data analysis platform" 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" rel="nofollow" href="https://www.academia.edu/103477110/Design_and_implementation_of_bridge_structure_health_monitoring_data_analysis_platform">Design and implementation of bridge structure health monitoring data analysis platform</a></div><div class="wp-workCard_item"><span>World Automation Congress 2012</span><span>, 2012</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">to evaluate, predict and alarm the bridge structure health state, the bridge structure health mon...</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">to evaluate, predict and alarm the bridge structure health state, the bridge structure health monitoring data analysis platform is set up. System deployment, system structure and system function design are introduced from the aspect of platform design. Based on multiple parameters data format collected by hardware in actual monitoring, a unified multi-data format conversion method is put forward combining with multi-threading technology. Online and offline evaluation platforms are integrated, with which the bridge structure health status is feedback using kinds of prediction and evaluation methods. According to the applied practice of the platform, the design of platform and methods are proved to be feasible and effective.</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="103477110"><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="103477110"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477110; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477110]").text(description); $(".js-view-count[data-work-id=103477110]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477110; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477110']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477110, 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" } } $('.js-work-strip[data-work-id=103477110]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477110,"title":"Design and implementation of bridge structure health monitoring data analysis platform","translated_title":"","metadata":{"abstract":"to evaluate, predict and alarm the bridge structure health state, the bridge structure health monitoring data analysis platform is set up. System deployment, system structure and system function design are introduced from the aspect of platform design. Based on multiple parameters data format collected by hardware in actual monitoring, a unified multi-data format conversion method is put forward combining with multi-threading technology. Online and offline evaluation platforms are integrated, with which the bridge structure health status is feedback using kinds of prediction and evaluation methods. According to the applied practice of the platform, the design of platform and methods are proved to be feasible and effective.","publisher":"World Automation Congress 2012","publication_date":{"day":null,"month":null,"year":2012,"errors":{}},"publication_name":"World Automation Congress 2012"},"translated_abstract":"to evaluate, predict and alarm the bridge structure health state, the bridge structure health monitoring data analysis platform is set up. System deployment, system structure and system function design are introduced from the aspect of platform design. Based on multiple parameters data format collected by hardware in actual monitoring, a unified multi-data format conversion method is put forward combining with multi-threading technology. Online and offline evaluation platforms are integrated, with which the bridge structure health status is feedback using kinds of prediction and evaluation methods. According to the applied practice of the platform, the design of platform and methods are proved to be feasible and effective.","internal_url":"https://www.academia.edu/103477110/Design_and_implementation_of_bridge_structure_health_monitoring_data_analysis_platform","translated_internal_url":"","created_at":"2023-06-17T07:31:29.377-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":274044901,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Design_and_implementation_of_bridge_structure_health_monitoring_data_analysis_platform","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":274044901,"first_name":"Lili","middle_initials":null,"last_name":"Shang","page_name":"LiliShang2","domain_name":"independent","created_at":"2023-06-17T07:30:42.428-07:00","display_name":"Lili Shang","url":"https://independent.academia.edu/LiliShang2"},"attachments":[],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering"},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":564622,"name":"Alarm","url":"https://www.academia.edu/Documents/in/Alarm"},{"id":1268642,"name":"Software Deployment","url":"https://www.academia.edu/Documents/in/Software_Deployment"}],"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="103477105"><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/103477105/The_one_step_pyrolysis_process_of_rattan_based_silicon_carbide_multiphase_ceramics_prepared_by_sol_gel_method"><img alt="Research paper thumbnail of The one-step pyrolysis process of rattan-based silicon carbide multiphase ceramics prepared by sol–gel method" class="work-thumbnail" src="https://attachments.academia-assets.com/103474501/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/103477105/The_one_step_pyrolysis_process_of_rattan_based_silicon_carbide_multiphase_ceramics_prepared_by_sol_gel_method">The one-step pyrolysis process of rattan-based silicon carbide multiphase ceramics prepared by sol–gel method</a></div><div class="wp-workCard_item"><span>Journal of Wood Science</span><span>, 2021</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The sol–gel method was used to prepare rattan-based silicon carbide (R–SiC) composite ceramics un...</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 sol–gel method was used to prepare rattan-based silicon carbide (R–SiC) composite ceramics under different pyrolysis parameters through adjustment of the temperature and retention time of the one-step pyrolysis process. The crystalline phases, microscopic morphology, element distribution and specific surface area of the silicon carbide (SiC) were characterized by X-ray diffraction (XRD), Fourier transform-infrared spectroscopy (FT-IR), X-ray fluorescence spectrometer (XRF), field-emission scanning electron microscope (FESEM), transmission electron microscopy (TEM), energy dispersive X-ray analysis (EDX), and N2 physisorption. The results showed that the R–SiC prepared at different pyrolysis parameters was able to retain the porous structure of pristine rattan stem. The R–SiC prepared at 1500 ℃ for 120 min possessed the lowest density (0.25 g/cm3), the largest specific surface area (43.38 m2/g) and the highest SiC yield (44.24%). The SiC whisker was the major SiC morphology on th...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="e8973f2aaffa2036929496d51ec0a35d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474501,&quot;asset_id&quot;:103477105,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474501/download_file?st=MTczMjM4NTcwMyw4LjIyMi4yMDguMTQ2&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="103477105"><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="103477105"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477105; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477105]").text(description); $(".js-view-count[data-work-id=103477105]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477105; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477105']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477105, 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: "e8973f2aaffa2036929496d51ec0a35d" } } $('.js-work-strip[data-work-id=103477105]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477105,"title":"The one-step pyrolysis process of rattan-based silicon carbide multiphase ceramics prepared by sol–gel method","translated_title":"","metadata":{"abstract":"The sol–gel method was used to prepare rattan-based silicon carbide (R–SiC) composite ceramics under different pyrolysis parameters through adjustment of the temperature and retention time of the one-step pyrolysis process. The crystalline phases, microscopic morphology, element distribution and specific surface area of the silicon carbide (SiC) were characterized by X-ray diffraction (XRD), Fourier transform-infrared spectroscopy (FT-IR), X-ray fluorescence spectrometer (XRF), field-emission scanning electron microscope (FESEM), transmission electron microscopy (TEM), energy dispersive X-ray analysis (EDX), and N2 physisorption. The results showed that the R–SiC prepared at different pyrolysis parameters was able to retain the porous structure of pristine rattan stem. The R–SiC prepared at 1500 ℃ for 120 min possessed the lowest density (0.25 g/cm3), the largest specific surface area (43.38 m2/g) and the highest SiC yield (44.24%). The SiC whisker was the major SiC morphology on th...","publisher":"Springer Science and Business Media LLC","publication_date":{"day":null,"month":null,"year":2021,"errors":{}},"publication_name":"Journal of Wood Science"},"translated_abstract":"The sol–gel method was used to prepare rattan-based silicon carbide (R–SiC) composite ceramics under different pyrolysis parameters through adjustment of the temperature and retention time of the one-step pyrolysis process. The crystalline phases, microscopic morphology, element distribution and specific surface area of the silicon carbide (SiC) were characterized by X-ray diffraction (XRD), Fourier transform-infrared spectroscopy (FT-IR), X-ray fluorescence spectrometer (XRF), field-emission scanning electron microscope (FESEM), transmission electron microscopy (TEM), energy dispersive X-ray analysis (EDX), and N2 physisorption. The results showed that the R–SiC prepared at different pyrolysis parameters was able to retain the porous structure of pristine rattan stem. The R–SiC prepared at 1500 ℃ for 120 min possessed the lowest density (0.25 g/cm3), the largest specific surface area (43.38 m2/g) and the highest SiC yield (44.24%). The SiC whisker was the major SiC morphology on th...","internal_url":"https://www.academia.edu/103477105/The_one_step_pyrolysis_process_of_rattan_based_silicon_carbide_multiphase_ceramics_prepared_by_sol_gel_method","translated_internal_url":"","created_at":"2023-06-17T07:31:21.213-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":274044901,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":103474501,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/103474501/thumbnails/1.jpg","file_name":"s10086-021-01991-7.pdf","download_url":"https://www.academia.edu/attachments/103474501/download_file?st=MTczMjM4NTcwMyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_one_step_pyrolysis_process_of_rattan.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/103474501/s10086-021-01991-7-libre.pdf?1687012895=\u0026response-content-disposition=attachment%3B+filename%3DThe_one_step_pyrolysis_process_of_rattan.pdf\u0026Expires=1732389302\u0026Signature=XZW2Jia1ZUVNPFQ-UK4Ifg9LlAMP653WGFsHYXos2CE-NMENkoY57fkc7WuNIdwEDc9XYXUvHWfpH1~p3CxKidJhkxdOUKhqx0YP2MiGNBzlK7n7O0PDV93HEJMjDtLccrvRMZI4BL9XW19qGfll1OdElbjgKIEavqQzcOoz8uqd6~PIjyPHk~k20R9N1Nxbh-ASdlsx-~OZ1PKgLgYhXVzu8lUGsoqro~tPtUVExYJaadV0ri3hPBO3JXkdk1a2Za~eTpAZIG-EtuX-oRU1xjhHRpO3-fZLUJF8S-2o0zat4YJumO4BRhusyAF2EeSNm4fDbiM5PEL6pZ5kdjVYIQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"The_one_step_pyrolysis_process_of_rattan_based_silicon_carbide_multiphase_ceramics_prepared_by_sol_gel_method","translated_slug":"","page_count":11,"language":"en","content_type":"Work","owner":{"id":274044901,"first_name":"Lili","middle_initials":null,"last_name":"Shang","page_name":"LiliShang2","domain_name":"independent","created_at":"2023-06-17T07:30:42.428-07:00","display_name":"Lili Shang","url":"https://independent.academia.edu/LiliShang2"},"attachments":[{"id":103474501,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/103474501/thumbnails/1.jpg","file_name":"s10086-021-01991-7.pdf","download_url":"https://www.academia.edu/attachments/103474501/download_file?st=MTczMjM4NTcwMyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_one_step_pyrolysis_process_of_rattan.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/103474501/s10086-021-01991-7-libre.pdf?1687012895=\u0026response-content-disposition=attachment%3B+filename%3DThe_one_step_pyrolysis_process_of_rattan.pdf\u0026Expires=1732389302\u0026Signature=XZW2Jia1ZUVNPFQ-UK4Ifg9LlAMP653WGFsHYXos2CE-NMENkoY57fkc7WuNIdwEDc9XYXUvHWfpH1~p3CxKidJhkxdOUKhqx0YP2MiGNBzlK7n7O0PDV93HEJMjDtLccrvRMZI4BL9XW19qGfll1OdElbjgKIEavqQzcOoz8uqd6~PIjyPHk~k20R9N1Nxbh-ASdlsx-~OZ1PKgLgYhXVzu8lUGsoqro~tPtUVExYJaadV0ri3hPBO3JXkdk1a2Za~eTpAZIG-EtuX-oRU1xjhHRpO3-fZLUJF8S-2o0zat4YJumO4BRhusyAF2EeSNm4fDbiM5PEL6pZ5kdjVYIQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":72,"name":"Chemical Engineering","url":"https://www.academia.edu/Documents/in/Chemical_Engineering"},{"id":511,"name":"Materials Science","url":"https://www.academia.edu/Documents/in/Materials_Science"},{"id":10997,"name":"Wood Science","url":"https://www.academia.edu/Documents/in/Wood_Science"},{"id":14136,"name":"Pyrolysis","url":"https://www.academia.edu/Documents/in/Pyrolysis"},{"id":86555,"name":"Silicon Carbide","url":"https://www.academia.edu/Documents/in/Silicon_Carbide"},{"id":189405,"name":"Ceramic","url":"https://www.academia.edu/Documents/in/Ceramic"},{"id":317638,"name":"Forestry Sciences","url":"https://www.academia.edu/Documents/in/Forestry_Sciences"},{"id":390995,"name":"Scanning Electron Microscope","url":"https://www.academia.edu/Documents/in/Scanning_Electron_Microscope"},{"id":398650,"name":"Fourier transform infrared spectroscopy","url":"https://www.academia.edu/Documents/in/Fourier_transform_infrared_spectroscopy"}],"urls":[{"id":32327732,"url":"https://link.springer.com/content/pdf/10.1186/s10086-021-01991-7.pdf"}]}, 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="103477104"><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/103477104/Investigating_older_adults_intention_to_learn_health_knowledge_on_social_media"><img alt="Research paper thumbnail of Investigating older adults’ intention to learn health knowledge on social media" 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/103477104/Investigating_older_adults_intention_to_learn_health_knowledge_on_social_media">Investigating older adults’ intention to learn health knowledge on social media</a></div><div class="wp-workCard_item"><span>Educational Gerontology</span><span>, 2020</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT Abundant health knowledge resources are available on social media to facilitate technolo...</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 Abundant health knowledge resources are available on social media to facilitate technology-enhanced knowledge learning among older adults. The objective of this study is to investigate the predictors and the underlying formation mechanism of older adults’ intention to learn health knowledge on social media. We propose a novel model to examine how older adults’ emotional state (i.e., health anxiety) and cognitive state (i.e., e-health literacy) during knowledge acquisition influence threat appraisal (i.e. perceived severity and perceived susceptibility) and coping appraisal (i.e. self-efficacy and perceived benefits), thereby shaping older adults’ intention to learn health knowledge. Survey data from 337 Chinese older adult users of social media was collected to test the research model. Results reveal that perceived susceptibility, self-efficacy and perceived benefits exert positive effects on older adults’ health knowledge learning intention, while the impact of perceived severity on health knowledge learning intention is not statistically significant; health anxiety is positively correlated with perceived severity and perceived susceptibility, and e-health literacy is a powerful predictor of self-efficacy and perceived benefits. This paper enriches the literature related to technology-enhanced knowledge learning and online health behavior among older adults. Effective strategies are proposed based on the findings for practitioners dedicated to promoting health knowledge via social media and older adults who apply health knowledge to address health-related needs.</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="103477104"><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="103477104"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477104; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477104]").text(description); $(".js-view-count[data-work-id=103477104]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477104; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477104']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477104, 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" } } $('.js-work-strip[data-work-id=103477104]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477104,"title":"Investigating older adults’ intention to learn health knowledge on social media","translated_title":"","metadata":{"abstract":"ABSTRACT Abundant health knowledge resources are available on social media to facilitate technology-enhanced knowledge learning among older adults. The objective of this study is to investigate the predictors and the underlying formation mechanism of older adults’ intention to learn health knowledge on social media. We propose a novel model to examine how older adults’ emotional state (i.e., health anxiety) and cognitive state (i.e., e-health literacy) during knowledge acquisition influence threat appraisal (i.e. perceived severity and perceived susceptibility) and coping appraisal (i.e. self-efficacy and perceived benefits), thereby shaping older adults’ intention to learn health knowledge. Survey data from 337 Chinese older adult users of social media was collected to test the research model. Results reveal that perceived susceptibility, self-efficacy and perceived benefits exert positive effects on older adults’ health knowledge learning intention, while the impact of perceived severity on health knowledge learning intention is not statistically significant; health anxiety is positively correlated with perceived severity and perceived susceptibility, and e-health literacy is a powerful predictor of self-efficacy and perceived benefits. This paper enriches the literature related to technology-enhanced knowledge learning and online health behavior among older adults. Effective strategies are proposed based on the findings for practitioners dedicated to promoting health knowledge via social media and older adults who apply health knowledge to address health-related needs.","publisher":"Informa UK Limited","publication_date":{"day":null,"month":null,"year":2020,"errors":{}},"publication_name":"Educational Gerontology"},"translated_abstract":"ABSTRACT Abundant health knowledge resources are available on social media to facilitate technology-enhanced knowledge learning among older adults. The objective of this study is to investigate the predictors and the underlying formation mechanism of older adults’ intention to learn health knowledge on social media. We propose a novel model to examine how older adults’ emotional state (i.e., health anxiety) and cognitive state (i.e., e-health literacy) during knowledge acquisition influence threat appraisal (i.e. perceived severity and perceived susceptibility) and coping appraisal (i.e. self-efficacy and perceived benefits), thereby shaping older adults’ intention to learn health knowledge. Survey data from 337 Chinese older adult users of social media was collected to test the research model. Results reveal that perceived susceptibility, self-efficacy and perceived benefits exert positive effects on older adults’ health knowledge learning intention, while the impact of perceived severity on health knowledge learning intention is not statistically significant; health anxiety is positively correlated with perceived severity and perceived susceptibility, and e-health literacy is a powerful predictor of self-efficacy and perceived benefits. This paper enriches the literature related to technology-enhanced knowledge learning and online health behavior among older adults. Effective strategies are proposed based on the findings for practitioners dedicated to promoting health knowledge via social media and older adults who apply health knowledge to address health-related needs.","internal_url":"https://www.academia.edu/103477104/Investigating_older_adults_intention_to_learn_health_knowledge_on_social_media","translated_internal_url":"","created_at":"2023-06-17T07:31:21.030-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":274044901,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Investigating_older_adults_intention_to_learn_health_knowledge_on_social_media","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":274044901,"first_name":"Lili","middle_initials":null,"last_name":"Shang","page_name":"LiliShang2","domain_name":"independent","created_at":"2023-06-17T07:30:42.428-07:00","display_name":"Lili Shang","url":"https://independent.academia.edu/LiliShang2"},"attachments":[],"research_interests":[{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology"},{"id":124971,"name":"Education Systems","url":"https://www.academia.edu/Documents/in/Education_Systems"},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences"},{"id":318095,"name":"Educational Gerontology","url":"https://www.academia.edu/Documents/in/Educational_Gerontology"}],"urls":[{"id":32327731,"url":"https://www.tandfonline.com/doi/pdf/10.1080/03601277.2020.1759188"}]}, 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="103477102"><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/103477102/MicroRNA_148a_3p_promotes_survival_and_migration_of_endothelial_cells_isolated_from_Apoe_deficient_mice_through_restricting_circular_RNA_0003575"><img alt="Research paper thumbnail of MicroRNA-148a-3p promotes survival and migration of endothelial cells isolated from Apoe deficient mice through restricting circular RNA 0003575" class="work-thumbnail" src="https://attachments.academia-assets.com/103474529/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/103477102/MicroRNA_148a_3p_promotes_survival_and_migration_of_endothelial_cells_isolated_from_Apoe_deficient_mice_through_restricting_circular_RNA_0003575">MicroRNA-148a-3p promotes survival and migration of endothelial cells isolated from Apoe deficient mice through restricting circular RNA 0003575</a></div><div class="wp-workCard_item"><span>Gene</span><span>, 2019</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="77cf315c863bac3a3dd7904d85473b1d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474529,&quot;asset_id&quot;:103477102,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474529/download_file?st=MTczMjM4NTcwMyw4LjIyMi4yMDguMTQ2&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="103477102"><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="103477102"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477102; 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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="103477100"><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/103477100/Imaging_the_dynamic_deposition_of_cell_wall_polymer_in_xylem_and_phloem_in_Populus_euramericana"><img alt="Research paper thumbnail of Imaging the dynamic deposition of cell wall polymer in xylem and phloem in Populus × euramericana" class="work-thumbnail" src="https://attachments.academia-assets.com/103474532/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/103477100/Imaging_the_dynamic_deposition_of_cell_wall_polymer_in_xylem_and_phloem_in_Populus_euramericana">Imaging the dynamic deposition of cell wall polymer in xylem and phloem in Populus × euramericana</a></div><div class="wp-workCard_item"><span>Planta</span><span>, Jan 25, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Both G units and S units deposited in the whole lignification process of xylem fiber. The topoche...</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">Both G units and S units deposited in the whole lignification process of xylem fiber. The topochemical variations in newly formed xylem and phloem of Populus × euramericana were investigated by combined microscopic techniques. During xylem formation, earlier cell wall deposition in vessel and afterwards in the neighboring fiber was observed in situ. Raman images in xylem fiber emphasized that cell wall deposition was an ordered process which lignification started in cell corner following carbohydrates deposition. Higher deposition speed of carbohydrates was revealed at the beginning of the cell wall differentiation, and the syringyl (S) units deposition was more pronounced compared with guaiacyl (G) units at the earlier stage of lignification. The comparative analysis of cell wall composition in phloem fiber indicated that phloem formed earlier than xylem and the distribution of lignin monomers varied significantly with phloem fiber location. Furthermore, an interesting phenomenon w...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="572c8cb1b7b99b55c6df73e374b21533" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474532,&quot;asset_id&quot;:103477100,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474532/download_file?st=MTczMjM4NTcwMyw4LjIyMi4yMDguMTQ2&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="103477100"><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="103477100"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477100; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477100]").text(description); $(".js-view-count[data-work-id=103477100]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477100; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477100']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477100, 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: "572c8cb1b7b99b55c6df73e374b21533" } } $('.js-work-strip[data-work-id=103477100]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477100,"title":"Imaging the dynamic deposition of cell wall polymer in xylem and phloem in Populus × euramericana","translated_title":"","metadata":{"abstract":"Both G units and S units deposited in the whole lignification process of xylem fiber. 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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="103477099"><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/103477099/_Comparative_study_on_promoting_blood_effects_of_Danshen_Honghua_herb_pair_with_different_preparations_based_on_chemometrics_and_multi_attribute_comprehensive_index_methods_"><img alt="Research paper thumbnail of [Comparative study on promoting blood effects of Danshen-Honghua herb pair with different preparations based on chemometrics and multi-attribute comprehensive index methods]" 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/103477099/_Comparative_study_on_promoting_blood_effects_of_Danshen_Honghua_herb_pair_with_different_preparations_based_on_chemometrics_and_multi_attribute_comprehensive_index_methods_">[Comparative study on promoting blood effects of Danshen-Honghua herb pair with different preparations based on chemometrics and multi-attribute comprehensive index methods]</a></div><div class="wp-workCard_item"><span>Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica</span><span>, 2017</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">To evaluate the promoting blood circulation and removing blood stasis effects of Danshen-Honghua(...</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">To evaluate the promoting blood circulation and removing blood stasis effects of Danshen-Honghua(DH) herb pair with different preparations (alcohol, 50% alcohol and water) on blood rheology and coagulation functions in acute blood stasis rats, and optimize the best preparation method of DH based on principal component analysis(PCA), hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods. Ice water bath and subcutaneous injection of adrenaline were both used to establish the acute blood stasis rat model. Then the blood stasis rats were administrated intragastrically with DH (alcohol, 50% alcohol and water) extracts. The whole blood viscosity(WBV), plasma viscosity(PV), erythrocyte sedimentation rate(ESR) and haematocrit(HCT) were tested to observe the effects of DH herb pair with different preparations and doses on hemorheology of blood stasis rats; the activated partial thromboplastin time(APTT), thrombin time(TT), prothrombin time(PT), and plasma fibr...</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="103477099"><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="103477099"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477099; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477099]").text(description); $(".js-view-count[data-work-id=103477099]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477099; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477099']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477099, 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" } } $('.js-work-strip[data-work-id=103477099]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477099,"title":"[Comparative study on promoting blood effects of Danshen-Honghua herb pair with different preparations based on chemometrics and multi-attribute comprehensive index methods]","translated_title":"","metadata":{"abstract":"To evaluate the promoting blood circulation and removing blood stasis effects of Danshen-Honghua(DH) herb pair with different preparations (alcohol, 50% alcohol and water) on blood rheology and coagulation functions in acute blood stasis rats, and optimize the best preparation method of DH based on principal component analysis(PCA), hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods. Ice water bath and subcutaneous injection of adrenaline were both used to establish the acute blood stasis rat model. Then the blood stasis rats were administrated intragastrically with DH (alcohol, 50% alcohol and water) extracts. The whole blood viscosity(WBV), plasma viscosity(PV), erythrocyte sedimentation rate(ESR) and haematocrit(HCT) were tested to observe the effects of DH herb pair with different preparations and doses on hemorheology of blood stasis rats; the activated partial thromboplastin time(APTT), thrombin time(TT), prothrombin time(PT), and plasma fibr...","publication_date":{"day":null,"month":null,"year":2017,"errors":{}},"publication_name":"Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica"},"translated_abstract":"To evaluate the promoting blood circulation and removing blood stasis effects of Danshen-Honghua(DH) herb pair with different preparations (alcohol, 50% alcohol and water) on blood rheology and coagulation functions in acute blood stasis rats, and optimize the best preparation method of DH based on principal component analysis(PCA), hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods. Ice water bath and subcutaneous injection of adrenaline were both used to establish the acute blood stasis rat model. Then the blood stasis rats were administrated intragastrically with DH (alcohol, 50% alcohol and water) extracts. The whole blood viscosity(WBV), plasma viscosity(PV), erythrocyte sedimentation rate(ESR) and haematocrit(HCT) were tested to observe the effects of DH herb pair with different preparations and doses on hemorheology of blood stasis rats; the activated partial thromboplastin time(APTT), thrombin time(TT), prothrombin time(PT), and plasma fibr...","internal_url":"https://www.academia.edu/103477099/_Comparative_study_on_promoting_blood_effects_of_Danshen_Honghua_herb_pair_with_different_preparations_based_on_chemometrics_and_multi_attribute_comprehensive_index_methods_","translated_internal_url":"","created_at":"2023-06-17T07:31:19.726-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":274044901,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"_Comparative_study_on_promoting_blood_effects_of_Danshen_Honghua_herb_pair_with_different_preparations_based_on_chemometrics_and_multi_attribute_comprehensive_index_methods_","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":274044901,"first_name":"Lili","middle_initials":null,"last_name":"Shang","page_name":"LiliShang2","domain_name":"independent","created_at":"2023-06-17T07:30:42.428-07:00","display_name":"Lili Shang","url":"https://independent.academia.edu/LiliShang2"},"attachments":[],"research_interests":[{"id":4083,"name":"Complementary and Alternative Medicine","url":"https://www.academia.edu/Documents/in/Complementary_and_Alternative_Medicine"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":48732,"name":"Hemorheology","url":"https://www.academia.edu/Documents/in/Hemorheology"},{"id":53044,"name":"Fibrinogen","url":"https://www.academia.edu/Documents/in/Fibrinogen"},{"id":271683,"name":"Herb","url":"https://www.academia.edu/Documents/in/Herb"},{"id":389277,"name":"Blood Viscosity","url":"https://www.academia.edu/Documents/in/Blood_Viscosity"}],"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="103477098"><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/103477098/Multi_view_collaborative_semi_supervised_classification_algorithm_based_on_diversity_measurers_of_classifier_with_the_combination_of_agreement_and_disagreement_label_rules"><img alt="Research paper thumbnail of Multi-view collaborative semi-supervised classification algorithm based on diversity measurers of classifier with the combination of agreement and disagreement label rules" 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/103477098/Multi_view_collaborative_semi_supervised_classification_algorithm_based_on_diversity_measurers_of_classifier_with_the_combination_of_agreement_and_disagreement_label_rules">Multi-view collaborative semi-supervised classification algorithm based on diversity measurers of classifier with the combination of agreement and disagreement label rules</a></div><div class="wp-workCard_item"><span>Transactions of the Institute of Measurement and Control</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Considering the deficiencies of the Co-training algorithm including redundancy and sufficient con...</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">Considering the deficiencies of the Co-training algorithm including redundancy and sufficient conditions, diversity measurers of classifier, combined label rules, unoptimizable classifier during model updating process etc., a multi-view collaborative semi-supervised classification algorithm based on diversity measurers of the classifier with the combination of agreement and disagreement label rules (Co-AgDiag) is proposed. This algorithm uses a combination of agreement and disagreement label rules during the labelling unlabelled data process by judging whether the two classifiers are consistent and considering the diversity threshold in order to improve the performance of the classifier. During the process of generating classifier and model updating, we employed the diversity rule of classifier to update the model in order to judge the performance of the two classifiers. The experimental results on UCI datasets demonstrate the effectively and feasibility of the proposed algorithm fo...</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="103477098"><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="103477098"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477098; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477098]").text(description); $(".js-view-count[data-work-id=103477098]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477098; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477098']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477098, 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" } } $('.js-work-strip[data-work-id=103477098]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477098,"title":"Multi-view collaborative semi-supervised classification algorithm based on diversity measurers of classifier with the combination of agreement and disagreement label rules","translated_title":"","metadata":{"abstract":"Considering the deficiencies of the Co-training algorithm including redundancy and sufficient conditions, diversity measurers of classifier, combined label rules, unoptimizable classifier during model updating process etc., a multi-view collaborative semi-supervised classification algorithm based on diversity measurers of the classifier with the combination of agreement and disagreement label rules (Co-AgDiag) is proposed. This algorithm uses a combination of agreement and disagreement label rules during the labelling unlabelled data process by judging whether the two classifiers are consistent and considering the diversity threshold in order to improve the performance of the classifier. During the process of generating classifier and model updating, we employed the diversity rule of classifier to update the model in order to judge the performance of the two classifiers. The experimental results on UCI datasets demonstrate the effectively and feasibility of the proposed algorithm fo...","publisher":"SAGE Publications","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"Transactions of the Institute of Measurement and Control"},"translated_abstract":"Considering the deficiencies of the Co-training algorithm including redundancy and sufficient conditions, diversity measurers of classifier, combined label rules, unoptimizable classifier during model updating process etc., a multi-view collaborative semi-supervised classification algorithm based on diversity measurers of the classifier with the combination of agreement and disagreement label rules (Co-AgDiag) is proposed. This algorithm uses a combination of agreement and disagreement label rules during the labelling unlabelled data process by judging whether the two classifiers are consistent and considering the diversity threshold in order to improve the performance of the classifier. During the process of generating classifier and model updating, we employed the diversity rule of classifier to update the model in order to judge the performance of the two classifiers. The experimental results on UCI datasets demonstrate the effectively and feasibility of the proposed algorithm fo...","internal_url":"https://www.academia.edu/103477098/Multi_view_collaborative_semi_supervised_classification_algorithm_based_on_diversity_measurers_of_classifier_with_the_combination_of_agreement_and_disagreement_label_rules","translated_internal_url":"","created_at":"2023-06-17T07:31:19.515-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":274044901,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Multi_view_collaborative_semi_supervised_classification_algorithm_based_on_diversity_measurers_of_classifier_with_the_combination_of_agreement_and_disagreement_label_rules","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":274044901,"first_name":"Lili","middle_initials":null,"last_name":"Shang","page_name":"LiliShang2","domain_name":"independent","created_at":"2023-06-17T07:30:42.428-07:00","display_name":"Lili Shang","url":"https://independent.academia.edu/LiliShang2"},"attachments":[],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence"}],"urls":[{"id":32327728,"url":"http://journals.sagepub.com/doi/pdf/10.1177/0142331215617235"}]}, 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="103477097"><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/103477097/Comparative_Analysis_of_the_Effects_of_Hydroxysafflor_Yellow_A_and_Anhydrosafflor_Yellow_B_in_Safflower_Series_of_Herb_Pairs_Using_Prep_HPLC_and_a_Selective_Knock_Out_Approach"><img alt="Research paper thumbnail of Comparative Analysis of the Effects of Hydroxysafflor Yellow A and Anhydrosafflor Yellow B in Safflower Series of Herb Pairs Using Prep-HPLC and a Selective Knock-Out Approach" class="work-thumbnail" src="https://attachments.academia-assets.com/103474528/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/103477097/Comparative_Analysis_of_the_Effects_of_Hydroxysafflor_Yellow_A_and_Anhydrosafflor_Yellow_B_in_Safflower_Series_of_Herb_Pairs_Using_Prep_HPLC_and_a_Selective_Knock_Out_Approach">Comparative Analysis of the Effects of Hydroxysafflor Yellow A and Anhydrosafflor Yellow B in Safflower Series of Herb Pairs Using Prep-HPLC and a Selective Knock-Out Approach</a></div><div class="wp-workCard_item"><span>Molecules (Basel, Switzerland)</span><span>, Jan 6, 2016</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The flower of Carthamus tinctorius L. (Carthami Flos, safflower), important in traditional Chines...</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 flower of Carthamus tinctorius L. (Carthami Flos, safflower), important in traditional Chinese medicine (TCM), is known for treating blood stasis, coronary heart disease, hypertension, and cerebrovascular disease in clinical and experimental studies. It is widely accepted that hydroxysafflor yellow A (HSYA) and anhydrosafflor yellow B (ASYB) are the major bioactive components of many formulae comprised of safflower. In this study, selective knock-out of target components such as HSYA and ASYB by using preparative high performance liquid chromatography (prep-HPLC) followed by antiplatelet and anticoagulation activities evaluation was used to investigate the roles of bioactive ingredients in safflower series of herb pairs. The results showed that both HSYA and ASYB not only played a direct role in activating blood circulation, but also indirectly made a contribution to the total bioactivity of safflower series of herb pairs. The degree of contribution of HSYA in the safflower and ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="fb5b6120cad07c3b680febfa3e141084" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474528,&quot;asset_id&quot;:103477097,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474528/download_file?st=MTczMjM4NTcwMyw4LjIyMi4yMDguMTQ2&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="103477097"><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="103477097"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477097; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477097]").text(description); $(".js-view-count[data-work-id=103477097]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477097; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477097']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477097, 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: "fb5b6120cad07c3b680febfa3e141084" } } $('.js-work-strip[data-work-id=103477097]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477097,"title":"Comparative Analysis of the Effects of Hydroxysafflor Yellow A and Anhydrosafflor Yellow B in Safflower Series of Herb Pairs Using Prep-HPLC and a Selective Knock-Out Approach","translated_title":"","metadata":{"abstract":"The flower of Carthamus tinctorius L. (Carthami Flos, safflower), important in traditional Chinese medicine (TCM), is known for treating blood stasis, coronary heart disease, hypertension, and cerebrovascular disease in clinical and experimental studies. It is widely accepted that hydroxysafflor yellow A (HSYA) and anhydrosafflor yellow B (ASYB) are the major bioactive components of many formulae comprised of safflower. In this study, selective knock-out of target components such as HSYA and ASYB by using preparative high performance liquid chromatography (prep-HPLC) followed by antiplatelet and anticoagulation activities evaluation was used to investigate the roles of bioactive ingredients in safflower series of herb pairs. The results showed that both HSYA and ASYB not only played a direct role in activating blood circulation, but also indirectly made a contribution to the total bioactivity of safflower series of herb pairs. The degree of contribution of HSYA in the safflower and ...","publication_date":{"day":6,"month":1,"year":2016,"errors":{}},"publication_name":"Molecules (Basel, Switzerland)"},"translated_abstract":"The flower of Carthamus tinctorius L. (Carthami Flos, safflower), important in traditional Chinese medicine (TCM), is known for treating blood stasis, coronary heart disease, hypertension, and cerebrovascular disease in clinical and experimental studies. It is widely accepted that hydroxysafflor yellow A (HSYA) and anhydrosafflor yellow B (ASYB) are the major bioactive components of many formulae comprised of safflower. In this study, selective knock-out of target components such as HSYA and ASYB by using preparative high performance liquid chromatography (prep-HPLC) followed by antiplatelet and anticoagulation activities evaluation was used to investigate the roles of bioactive ingredients in safflower series of herb pairs. The results showed that both HSYA and ASYB not only played a direct role in activating blood circulation, but also indirectly made a contribution to the total bioactivity of safflower series of herb pairs. The degree of contribution of HSYA in the safflower and 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$a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="103477096"><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/103477096/A_novel_method_for_measuring_mechanical_properties_of_vascular_bundles_in_moso_bamboo"><img alt="Research paper thumbnail of A novel method for measuring mechanical properties of vascular bundles in moso bamboo" class="work-thumbnail" src="https://attachments.academia-assets.com/103474499/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/103477096/A_novel_method_for_measuring_mechanical_properties_of_vascular_bundles_in_moso_bamboo">A novel method for measuring mechanical properties of vascular bundles in moso bamboo</a></div><div class="wp-workCard_item"><span>Journal of Wood Science</span><span>, 2015</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="b38fbe566424f9c5fcd59614e11a4c3d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474499,&quot;asset_id&quot;:103477096,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474499/download_file?st=MTczMjM4NTcwMyw4LjIyMi4yMDguMTQ2&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="103477096"><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="103477096"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477096; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477096]").text(description); $(".js-view-count[data-work-id=103477096]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477096; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = 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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 present preliminary results of the VSOP imaging of the nearby southern blazar J1924-29 at 18 cm. The high resolution image shows that the source possesses a core-jet structure along the northeast direction. 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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="103477092"><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/103477092/Multi_view_semi_supervised_collaboration_classification_algorithm_with_combination_of_agreement_and_disagreement_label_rules"><img alt="Research paper thumbnail of Multi-view semi-supervised collaboration classification algorithm with combination of agreement and disagreement label rules" 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/103477092/Multi_view_semi_supervised_collaboration_classification_algorithm_with_combination_of_agreement_and_disagreement_label_rules">Multi-view semi-supervised collaboration classification algorithm with combination of agreement and disagreement label rules</a></div><div class="wp-workCard_item"><span>Journal of Computer Applications</span><span>, 2013</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">To improve the performance of the co-training algorithm and expand the range of applications, a m...</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">To improve the performance of the co-training algorithm and expand the range of applications, a multi-view semi-supervised collaboration classification algorithm with the combination of consistent and inconsistent label rules was proposed, which aimed at providing a more effective method for the classification of the bridge structured health data. The proposed algorithm used combination of agreement and disagreement label rules for the unlabeled data by judging whether the two classifiers were consistent. Put the sample to the label set, if the label results were consistent. If the label results were inconsistent and the confidence was beyond the threshold, it put the label result of the high confidence to the label set, took full use of the unlabeled data to improve the performance of the classifier, and updated the classification model by the difference of the classifiers. The experimental results of the proposed algorithm on the bridge structured health datasets and standard UCI datasets verify the effectiveness and feasibility of the proposed model on the multi-view classification problems.</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="103477092"><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="103477092"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477092; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477092]").text(description); $(".js-view-count[data-work-id=103477092]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477092; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477092']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477092, 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" } } $('.js-work-strip[data-work-id=103477092]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477092,"title":"Multi-view semi-supervised collaboration classification algorithm with combination of agreement and disagreement label rules","translated_title":"","metadata":{"abstract":"To improve the performance of the co-training algorithm and expand the range of applications, a multi-view semi-supervised collaboration classification algorithm with the combination of consistent and inconsistent label rules was proposed, which aimed at providing a more effective method for the classification of the bridge structured health data. 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The experimental results of the proposed algorithm on the bridge structured health datasets and standard UCI datasets verify the effectiveness and feasibility of the proposed model on the multi-view classification problems.","publisher":"China Science Publishing \u0026 Media Ltd.","publication_date":{"day":null,"month":null,"year":2013,"errors":{}},"publication_name":"Journal of Computer Applications"},"translated_abstract":"To improve the performance of the co-training algorithm and expand the range of applications, a multi-view semi-supervised collaboration classification algorithm with the combination of consistent and inconsistent label rules was proposed, which aimed at providing a more effective method for the classification of the bridge structured health data. The proposed algorithm used combination of agreement and disagreement label rules for the unlabeled data by judging whether the two classifiers were consistent. 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The experimental results of the proposed algorithm on the bridge structured health datasets and standard UCI datasets verify the effectiveness and feasibility of the proposed model on the multi-view classification problems.","internal_url":"https://www.academia.edu/103477092/Multi_view_semi_supervised_collaboration_classification_algorithm_with_combination_of_agreement_and_disagreement_label_rules","translated_internal_url":"","created_at":"2023-06-17T07:31:18.481-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":274044901,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Multi_view_semi_supervised_collaboration_classification_algorithm_with_combination_of_agreement_and_disagreement_label_rules","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":274044901,"first_name":"Lili","middle_initials":null,"last_name":"Shang","page_name":"LiliShang2","domain_name":"independent","created_at":"2023-06-17T07:30:42.428-07:00","display_name":"Lili Shang","url":"https://independent.academia.edu/LiliShang2"},"attachments":[],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence"},{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning"},{"id":26817,"name":"Algorithm","url":"https://www.academia.edu/Documents/in/Algorithm"},{"id":144892,"name":"Agreement","url":"https://www.academia.edu/Documents/in/Agreement"},{"id":308710,"name":"Computer Applications","url":"https://www.academia.edu/Documents/in/Computer_Applications"},{"id":601808,"name":"Multi-Label Classification","url":"https://www.academia.edu/Documents/in/Multi-Label_Classification"}],"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="103477091"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/103477091/An_Online_Recursive_Identification_Method_over_Networks_with_Random_Packet_Losses"><img alt="Research paper thumbnail of An Online Recursive Identification Method over Networks with Random Packet Losses" 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" rel="nofollow" href="https://www.academia.edu/103477091/An_Online_Recursive_Identification_Method_over_Networks_with_Random_Packet_Losses">An Online Recursive Identification Method over Networks with Random Packet Losses</a></div><div class="wp-workCard_item"><span>Communications in Computer and Information Science</span><span>, 2014</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Under the network environment, data packet losses bring an undesirable effect on parameter identi...</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">Under the network environment, data packet losses bring an undesirable effect on parameter identification. To solve this problem, an online recursive identification method over networks with random packet losses is proposed. In this algorithm, the Bernoulli processes is firstly employed to describe the character of data packet losses. Considering random packet losses, an improved recursive least squares (RLS) algorithm is then presented by using Givens transformation, where the intermediate matrix can be updated recursively. Simulation results show that the proposed algorithm is able to significantly enhance the accuracy of parameter estimation, and the estimated variance becomes smaller as the number of iterations increases.</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="103477091"><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="103477091"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477091; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477091]").text(description); $(".js-view-count[data-work-id=103477091]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477091; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477091']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477091, 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" } } $('.js-work-strip[data-work-id=103477091]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477091,"title":"An Online Recursive Identification Method over Networks with Random Packet Losses","translated_title":"","metadata":{"abstract":"Under the network environment, data packet losses bring an undesirable effect on parameter identification. To solve this problem, an online recursive identification method over networks with random packet losses is proposed. In this algorithm, the Bernoulli processes is firstly employed to describe the character of data packet losses. Considering random packet losses, an improved recursive least squares (RLS) algorithm is then presented by using Givens transformation, where the intermediate matrix can be updated recursively. Simulation results show that the proposed algorithm is able to significantly enhance the accuracy of parameter estimation, and the estimated variance becomes smaller as the number of iterations increases.","publication_date":{"day":null,"month":null,"year":2014,"errors":{}},"publication_name":"Communications in Computer and Information Science"},"translated_abstract":"Under the network environment, data packet losses bring an undesirable effect on parameter identification. To solve this problem, an online recursive identification method over networks with random packet losses is proposed. In this algorithm, the Bernoulli processes is firstly employed to describe the character of data packet losses. Considering random packet losses, an improved recursive least squares (RLS) algorithm is then presented by using Givens transformation, where the intermediate matrix can be updated recursively. Simulation results show that the proposed algorithm is able to significantly enhance the accuracy of parameter estimation, and the estimated variance becomes smaller as the number of iterations increases.","internal_url":"https://www.academia.edu/103477091/An_Online_Recursive_Identification_Method_over_Networks_with_Random_Packet_Losses","translated_internal_url":"","created_at":"2023-06-17T07:31:18.342-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":274044901,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"An_Online_Recursive_Identification_Method_over_Networks_with_Random_Packet_Losses","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":274044901,"first_name":"Lili","middle_initials":null,"last_name":"Shang","page_name":"LiliShang2","domain_name":"independent","created_at":"2023-06-17T07:30:42.428-07:00","display_name":"Lili Shang","url":"https://independent.academia.edu/LiliShang2"},"attachments":[],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":26817,"name":"Algorithm","url":"https://www.academia.edu/Documents/in/Algorithm"},{"id":128839,"name":"Qa","url":"https://www.academia.edu/Documents/in/Qa"},{"id":244232,"name":"Ta","url":"https://www.academia.edu/Documents/in/Ta"}],"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="18126400" id="papers"><div class="js-work-strip profile--work_container" data-work-id="103477130"><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/103477130/Compressive_Strength_Parallel_to_the_Grain_in_Relation_to_Moisture_Content_inCalamus_simplicifoliusCane"><img alt="Research paper thumbnail of Compressive Strength Parallel to the Grain in Relation to Moisture Content inCalamus simplicifoliusCane" class="work-thumbnail" src="https://attachments.academia-assets.com/103474508/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/103477130/Compressive_Strength_Parallel_to_the_Grain_in_Relation_to_Moisture_Content_inCalamus_simplicifoliusCane">Compressive Strength Parallel to the Grain in Relation to Moisture Content inCalamus simplicifoliusCane</a></div><div class="wp-workCard_item"><span>Forest Products Journal</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This research aimed to investigate the compressive fracture behavior and the compressive strength...</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">This research aimed to investigate the compressive fracture behavior and the compressive strength parallel to the grain in relation to moisture contents (MC) below and above the fiber saturation point (FSP) in Calamus simplicifolius cane. FSP of the rattan was investigated using a dynamic vapor sorption (DVS) apparatus, and the fracture behaviors of compression parallel to grain were analyzed by three-dimensional X-ray microcomputed tomography. The study indicated that the value of FSP derived from the DVS method was 25 percent. The average compressive strength parallel to the grain was found to be 39 MPa at 3 percent MC, 30 MPa at 10 percent MC, 17 MPa at 12 percent MC, 12 MPa at 27 percent MC, and 10 MPa at 45 percent MC. The strains of the yield and densification stage were prolonged with increasing MC, whereas the stress in the linear elastic stage decreased with increasing MC. The cracks of the rattan core and the deflection angle at higher MC were larger than that of low MC. B...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="eb746d982088e9fa0717d143d47a8cc2" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474508,&quot;asset_id&quot;:103477130,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474508/download_file?st=MTczMjM4NTcwNCw4LjIyMi4yMDguMTQ2&st=MTczMjM4NTcwMiw4LjIyMi4yMDguMTQ2&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="103477130"><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="103477130"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477130; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477130]").text(description); $(".js-view-count[data-work-id=103477130]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477130; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477130']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477130, 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: "eb746d982088e9fa0717d143d47a8cc2" } } $('.js-work-strip[data-work-id=103477130]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477130,"title":"Compressive Strength Parallel to the Grain in Relation to Moisture Content inCalamus simplicifoliusCane","translated_title":"","metadata":{"abstract":"This research aimed to investigate the compressive fracture behavior and the compressive strength parallel to the grain in relation to moisture contents (MC) below and above the fiber saturation point (FSP) in Calamus simplicifolius cane. 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A high-resolution X-ray microtomography (μCT) was used to observe and reconstruct a three-dimensional (3D) morphometry model of the vascular bundle of the Qiongzhuea tumidinoda node due to its advantages of quick, nondestructive, and accurate testing of plant internal structure. The results showed that the morphology of vascular bundles varied significantly in the axial direction. In the cross-section, the number of axial vascular bundles reached a maximum at the lower end of the sheath scar, and the minimum of it was at the middle of the diaphragm. The frequency of axial vascular bundles decreased from the lower end of the node to the nodal ridge, and subsequently increased until the upper end of the bamboo node. The proportion of parenchyma, fibers, and conducting tissue was 65.7%, 30.5%, and 3.8%, respectively. 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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="103477119"><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/103477119/Distinguish_the_Wild_from_Cultivated_Agarwood_by_Using_HPLC_Combined_with_PCA"><img alt="Research paper thumbnail of Distinguish the Wild from Cultivated Agarwood by Using HPLC Combined with PCA" class="work-thumbnail" src="https://attachments.academia-assets.com/103474505/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/103477119/Distinguish_the_Wild_from_Cultivated_Agarwood_by_Using_HPLC_Combined_with_PCA">Distinguish the Wild from Cultivated Agarwood by Using HPLC Combined with PCA</a></div><div class="wp-workCard_item"><span>Asian Journal of Plant Science &amp; Research</span><span>, 2017</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Agarwood is the dark resinous and aromatic wood harvested from Aquilaria trees belong to Thymelae...</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">Agarwood is the dark resinous and aromatic wood harvested from Aquilaria trees belong to Thymelaeaceae. It has great value as a raw material for perfume and traditional Chinese medicine. Agarwood is wildly accepted from natural forests and plantations. The former has more highly valued. This paper focused on distinguishing the wild agarwood from sustainably produced cultivated agarwood using high performance liquid chromatography (HPLC) combined with statistical analysis. 10 cultivated and 30 wild agarwood samples were used to respectively establish agarwood HPLC characteristic chromatograms by multivariate analysis. By the retention time and peak area analyses of two types of agarwood, characteristic chromatograms and characteristic peaks (i.e., 10 characteristic peaks of cultivated agarwood (CPC1-10) and 9 characteristic peaks of wild ones (CPW1-9)) were established. The principal component analysis (PCA) and sample validation further verified the accuracy and feasibility of the c...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0fadb5d6bd4a87400216d9bc1043df26" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474505,&quot;asset_id&quot;:103477119,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474505/download_file?st=MTczMjM4NTcwNCw4LjIyMi4yMDguMTQ2&st=MTczMjM4NTcwMiw4LjIyMi4yMDguMTQ2&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="103477119"><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="103477119"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477119; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477119]").text(description); $(".js-view-count[data-work-id=103477119]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477119; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477119']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477119, 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: "0fadb5d6bd4a87400216d9bc1043df26" } } $('.js-work-strip[data-work-id=103477119]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477119,"title":"Distinguish the Wild from Cultivated Agarwood by Using HPLC Combined with PCA","translated_title":"","metadata":{"abstract":"Agarwood is the dark resinous and aromatic wood harvested from Aquilaria trees belong to Thymelaeaceae. 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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="103477110"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/103477110/Design_and_implementation_of_bridge_structure_health_monitoring_data_analysis_platform"><img alt="Research paper thumbnail of Design and implementation of bridge structure health monitoring data analysis platform" 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" rel="nofollow" href="https://www.academia.edu/103477110/Design_and_implementation_of_bridge_structure_health_monitoring_data_analysis_platform">Design and implementation of bridge structure health monitoring data analysis platform</a></div><div class="wp-workCard_item"><span>World Automation Congress 2012</span><span>, 2012</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">to evaluate, predict and alarm the bridge structure health state, the bridge structure health mon...</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">to evaluate, predict and alarm the bridge structure health state, the bridge structure health monitoring data analysis platform is set up. System deployment, system structure and system function design are introduced from the aspect of platform design. Based on multiple parameters data format collected by hardware in actual monitoring, a unified multi-data format conversion method is put forward combining with multi-threading technology. Online and offline evaluation platforms are integrated, with which the bridge structure health status is feedback using kinds of prediction and evaluation methods. According to the applied practice of the platform, the design of platform and methods are proved to be feasible and effective.</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="103477110"><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="103477110"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477110; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477110]").text(description); $(".js-view-count[data-work-id=103477110]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477110; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477110']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477110, 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" } } $('.js-work-strip[data-work-id=103477110]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477110,"title":"Design and implementation of bridge structure health monitoring data analysis platform","translated_title":"","metadata":{"abstract":"to evaluate, predict and alarm the bridge structure health state, the bridge structure health monitoring data analysis platform is set up. System deployment, system structure and system function design are introduced from the aspect of platform design. Based on multiple parameters data format collected by hardware in actual monitoring, a unified multi-data format conversion method is put forward combining with multi-threading technology. Online and offline evaluation platforms are integrated, with which the bridge structure health status is feedback using kinds of prediction and evaluation methods. According to the applied practice of the platform, the design of platform and methods are proved to be feasible and effective.","publisher":"World Automation Congress 2012","publication_date":{"day":null,"month":null,"year":2012,"errors":{}},"publication_name":"World Automation Congress 2012"},"translated_abstract":"to evaluate, predict and alarm the bridge structure health state, the bridge structure health monitoring data analysis platform is set up. System deployment, system structure and system function design are introduced from the aspect of platform design. Based on multiple parameters data format collected by hardware in actual monitoring, a unified multi-data format conversion method is put forward combining with multi-threading technology. Online and offline evaluation platforms are integrated, with which the bridge structure health status is feedback using kinds of prediction and evaluation methods. According to the applied practice of the platform, the design of platform and methods are proved to be feasible and effective.","internal_url":"https://www.academia.edu/103477110/Design_and_implementation_of_bridge_structure_health_monitoring_data_analysis_platform","translated_internal_url":"","created_at":"2023-06-17T07:31:29.377-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":274044901,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Design_and_implementation_of_bridge_structure_health_monitoring_data_analysis_platform","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":274044901,"first_name":"Lili","middle_initials":null,"last_name":"Shang","page_name":"LiliShang2","domain_name":"independent","created_at":"2023-06-17T07:30:42.428-07:00","display_name":"Lili Shang","url":"https://independent.academia.edu/LiliShang2"},"attachments":[],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering"},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":564622,"name":"Alarm","url":"https://www.academia.edu/Documents/in/Alarm"},{"id":1268642,"name":"Software Deployment","url":"https://www.academia.edu/Documents/in/Software_Deployment"}],"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="103477105"><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/103477105/The_one_step_pyrolysis_process_of_rattan_based_silicon_carbide_multiphase_ceramics_prepared_by_sol_gel_method"><img alt="Research paper thumbnail of The one-step pyrolysis process of rattan-based silicon carbide multiphase ceramics prepared by sol–gel method" class="work-thumbnail" src="https://attachments.academia-assets.com/103474501/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/103477105/The_one_step_pyrolysis_process_of_rattan_based_silicon_carbide_multiphase_ceramics_prepared_by_sol_gel_method">The one-step pyrolysis process of rattan-based silicon carbide multiphase ceramics prepared by sol–gel method</a></div><div class="wp-workCard_item"><span>Journal of Wood Science</span><span>, 2021</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The sol–gel method was used to prepare rattan-based silicon carbide (R–SiC) composite ceramics un...</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 sol–gel method was used to prepare rattan-based silicon carbide (R–SiC) composite ceramics under different pyrolysis parameters through adjustment of the temperature and retention time of the one-step pyrolysis process. The crystalline phases, microscopic morphology, element distribution and specific surface area of the silicon carbide (SiC) were characterized by X-ray diffraction (XRD), Fourier transform-infrared spectroscopy (FT-IR), X-ray fluorescence spectrometer (XRF), field-emission scanning electron microscope (FESEM), transmission electron microscopy (TEM), energy dispersive X-ray analysis (EDX), and N2 physisorption. The results showed that the R–SiC prepared at different pyrolysis parameters was able to retain the porous structure of pristine rattan stem. The R–SiC prepared at 1500 ℃ for 120 min possessed the lowest density (0.25 g/cm3), the largest specific surface area (43.38 m2/g) and the highest SiC yield (44.24%). The SiC whisker was the major SiC morphology on th...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="e8973f2aaffa2036929496d51ec0a35d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474501,&quot;asset_id&quot;:103477105,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474501/download_file?st=MTczMjM4NTcwNCw4LjIyMi4yMDguMTQ2&st=MTczMjM4NTcwMyw4LjIyMi4yMDguMTQ2&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="103477105"><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="103477105"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477105; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477105]").text(description); $(".js-view-count[data-work-id=103477105]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477105; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477105']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477105, 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: "e8973f2aaffa2036929496d51ec0a35d" } } $('.js-work-strip[data-work-id=103477105]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477105,"title":"The one-step pyrolysis process of rattan-based silicon carbide multiphase ceramics prepared by sol–gel method","translated_title":"","metadata":{"abstract":"The sol–gel method was used to prepare rattan-based silicon carbide (R–SiC) composite ceramics under different pyrolysis parameters through adjustment of the temperature and retention time of the one-step pyrolysis process. The crystalline phases, microscopic morphology, element distribution and specific surface area of the silicon carbide (SiC) were characterized by X-ray diffraction (XRD), Fourier transform-infrared spectroscopy (FT-IR), X-ray fluorescence spectrometer (XRF), field-emission scanning electron microscope (FESEM), transmission electron microscopy (TEM), energy dispersive X-ray analysis (EDX), and N2 physisorption. The results showed that the R–SiC prepared at different pyrolysis parameters was able to retain the porous structure of pristine rattan stem. The R–SiC prepared at 1500 ℃ for 120 min possessed the lowest density (0.25 g/cm3), the largest specific surface area (43.38 m2/g) and the highest SiC yield (44.24%). The SiC whisker was the major SiC morphology on th...","publisher":"Springer Science and Business Media LLC","publication_date":{"day":null,"month":null,"year":2021,"errors":{}},"publication_name":"Journal of Wood Science"},"translated_abstract":"The sol–gel method was used to prepare rattan-based silicon carbide (R–SiC) composite ceramics under different pyrolysis parameters through adjustment of the temperature and retention time of the one-step pyrolysis process. The crystalline phases, microscopic morphology, element distribution and specific surface area of the silicon carbide (SiC) were characterized by X-ray diffraction (XRD), Fourier transform-infrared spectroscopy (FT-IR), X-ray fluorescence spectrometer (XRF), field-emission scanning electron microscope (FESEM), transmission electron microscopy (TEM), energy dispersive X-ray analysis (EDX), and N2 physisorption. The results showed that the R–SiC prepared at different pyrolysis parameters was able to retain the porous structure of pristine rattan stem. The R–SiC prepared at 1500 ℃ for 120 min possessed the lowest density (0.25 g/cm3), the largest specific surface area (43.38 m2/g) and the highest SiC yield (44.24%). 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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="103477104"><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/103477104/Investigating_older_adults_intention_to_learn_health_knowledge_on_social_media"><img alt="Research paper thumbnail of Investigating older adults’ intention to learn health knowledge on social media" 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/103477104/Investigating_older_adults_intention_to_learn_health_knowledge_on_social_media">Investigating older adults’ intention to learn health knowledge on social media</a></div><div class="wp-workCard_item"><span>Educational Gerontology</span><span>, 2020</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT Abundant health knowledge resources are available on social media to facilitate technolo...</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 Abundant health knowledge resources are available on social media to facilitate technology-enhanced knowledge learning among older adults. The objective of this study is to investigate the predictors and the underlying formation mechanism of older adults’ intention to learn health knowledge on social media. We propose a novel model to examine how older adults’ emotional state (i.e., health anxiety) and cognitive state (i.e., e-health literacy) during knowledge acquisition influence threat appraisal (i.e. perceived severity and perceived susceptibility) and coping appraisal (i.e. self-efficacy and perceived benefits), thereby shaping older adults’ intention to learn health knowledge. Survey data from 337 Chinese older adult users of social media was collected to test the research model. Results reveal that perceived susceptibility, self-efficacy and perceived benefits exert positive effects on older adults’ health knowledge learning intention, while the impact of perceived severity on health knowledge learning intention is not statistically significant; health anxiety is positively correlated with perceived severity and perceived susceptibility, and e-health literacy is a powerful predictor of self-efficacy and perceived benefits. This paper enriches the literature related to technology-enhanced knowledge learning and online health behavior among older adults. Effective strategies are proposed based on the findings for practitioners dedicated to promoting health knowledge via social media and older adults who apply health knowledge to address health-related needs.</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="103477104"><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="103477104"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477104; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477104]").text(description); $(".js-view-count[data-work-id=103477104]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477104; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477104']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477104, 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" } } $('.js-work-strip[data-work-id=103477104]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477104,"title":"Investigating older adults’ intention to learn health knowledge on social media","translated_title":"","metadata":{"abstract":"ABSTRACT Abundant health knowledge resources are available on social media to facilitate technology-enhanced knowledge learning among older adults. The objective of this study is to investigate the predictors and the underlying formation mechanism of older adults’ intention to learn health knowledge on social media. We propose a novel model to examine how older adults’ emotional state (i.e., health anxiety) and cognitive state (i.e., e-health literacy) during knowledge acquisition influence threat appraisal (i.e. perceived severity and perceived susceptibility) and coping appraisal (i.e. self-efficacy and perceived benefits), thereby shaping older adults’ intention to learn health knowledge. Survey data from 337 Chinese older adult users of social media was collected to test the research model. Results reveal that perceived susceptibility, self-efficacy and perceived benefits exert positive effects on older adults’ health knowledge learning intention, while the impact of perceived severity on health knowledge learning intention is not statistically significant; health anxiety is positively correlated with perceived severity and perceived susceptibility, and e-health literacy is a powerful predictor of self-efficacy and perceived benefits. This paper enriches the literature related to technology-enhanced knowledge learning and online health behavior among older adults. Effective strategies are proposed based on the findings for practitioners dedicated to promoting health knowledge via social media and older adults who apply health knowledge to address health-related needs.","publisher":"Informa UK Limited","publication_date":{"day":null,"month":null,"year":2020,"errors":{}},"publication_name":"Educational Gerontology"},"translated_abstract":"ABSTRACT Abundant health knowledge resources are available on social media to facilitate technology-enhanced knowledge learning among older adults. The objective of this study is to investigate the predictors and the underlying formation mechanism of older adults’ intention to learn health knowledge on social media. We propose a novel model to examine how older adults’ emotional state (i.e., health anxiety) and cognitive state (i.e., e-health literacy) during knowledge acquisition influence threat appraisal (i.e. perceived severity and perceived susceptibility) and coping appraisal (i.e. self-efficacy and perceived benefits), thereby shaping older adults’ intention to learn health knowledge. Survey data from 337 Chinese older adult users of social media was collected to test the research model. Results reveal that perceived susceptibility, self-efficacy and perceived benefits exert positive effects on older adults’ health knowledge learning intention, while the impact of perceived severity on health knowledge learning intention is not statistically significant; health anxiety is positively correlated with perceived severity and perceived susceptibility, and e-health literacy is a powerful predictor of self-efficacy and perceived benefits. 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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="103477102"><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/103477102/MicroRNA_148a_3p_promotes_survival_and_migration_of_endothelial_cells_isolated_from_Apoe_deficient_mice_through_restricting_circular_RNA_0003575"><img alt="Research paper thumbnail of MicroRNA-148a-3p promotes survival and migration of endothelial cells isolated from Apoe deficient mice through restricting circular RNA 0003575" class="work-thumbnail" src="https://attachments.academia-assets.com/103474529/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/103477102/MicroRNA_148a_3p_promotes_survival_and_migration_of_endothelial_cells_isolated_from_Apoe_deficient_mice_through_restricting_circular_RNA_0003575">MicroRNA-148a-3p promotes survival and migration of endothelial cells isolated from Apoe deficient mice through restricting circular RNA 0003575</a></div><div class="wp-workCard_item"><span>Gene</span><span>, 2019</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="77cf315c863bac3a3dd7904d85473b1d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474529,&quot;asset_id&quot;:103477102,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474529/download_file?st=MTczMjM4NTcwNCw4LjIyMi4yMDguMTQ2&st=MTczMjM4NTcwMyw4LjIyMi4yMDguMTQ2&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="103477102"><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="103477102"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477102; 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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="103477100"><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/103477100/Imaging_the_dynamic_deposition_of_cell_wall_polymer_in_xylem_and_phloem_in_Populus_euramericana"><img alt="Research paper thumbnail of Imaging the dynamic deposition of cell wall polymer in xylem and phloem in Populus × euramericana" class="work-thumbnail" src="https://attachments.academia-assets.com/103474532/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/103477100/Imaging_the_dynamic_deposition_of_cell_wall_polymer_in_xylem_and_phloem_in_Populus_euramericana">Imaging the dynamic deposition of cell wall polymer in xylem and phloem in Populus × euramericana</a></div><div class="wp-workCard_item"><span>Planta</span><span>, Jan 25, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Both G units and S units deposited in the whole lignification process of xylem fiber. The topoche...</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">Both G units and S units deposited in the whole lignification process of xylem fiber. The topochemical variations in newly formed xylem and phloem of Populus × euramericana were investigated by combined microscopic techniques. During xylem formation, earlier cell wall deposition in vessel and afterwards in the neighboring fiber was observed in situ. Raman images in xylem fiber emphasized that cell wall deposition was an ordered process which lignification started in cell corner following carbohydrates deposition. Higher deposition speed of carbohydrates was revealed at the beginning of the cell wall differentiation, and the syringyl (S) units deposition was more pronounced compared with guaiacyl (G) units at the earlier stage of lignification. The comparative analysis of cell wall composition in phloem fiber indicated that phloem formed earlier than xylem and the distribution of lignin monomers varied significantly with phloem fiber location. Furthermore, an interesting phenomenon w...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="572c8cb1b7b99b55c6df73e374b21533" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474532,&quot;asset_id&quot;:103477100,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474532/download_file?st=MTczMjM4NTcwNCw4LjIyMi4yMDguMTQ2&st=MTczMjM4NTcwMyw4LjIyMi4yMDguMTQ2&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="103477100"><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="103477100"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477100; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477100]").text(description); $(".js-view-count[data-work-id=103477100]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477100; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477100']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477100, 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: "572c8cb1b7b99b55c6df73e374b21533" } } $('.js-work-strip[data-work-id=103477100]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477100,"title":"Imaging the dynamic deposition of cell wall polymer in xylem and phloem in Populus × euramericana","translated_title":"","metadata":{"abstract":"Both G units and S units deposited in the whole lignification process of xylem fiber. 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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="103477099"><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/103477099/_Comparative_study_on_promoting_blood_effects_of_Danshen_Honghua_herb_pair_with_different_preparations_based_on_chemometrics_and_multi_attribute_comprehensive_index_methods_"><img alt="Research paper thumbnail of [Comparative study on promoting blood effects of Danshen-Honghua herb pair with different preparations based on chemometrics and multi-attribute comprehensive index methods]" 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/103477099/_Comparative_study_on_promoting_blood_effects_of_Danshen_Honghua_herb_pair_with_different_preparations_based_on_chemometrics_and_multi_attribute_comprehensive_index_methods_">[Comparative study on promoting blood effects of Danshen-Honghua herb pair with different preparations based on chemometrics and multi-attribute comprehensive index methods]</a></div><div class="wp-workCard_item"><span>Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica</span><span>, 2017</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">To evaluate the promoting blood circulation and removing blood stasis effects of Danshen-Honghua(...</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">To evaluate the promoting blood circulation and removing blood stasis effects of Danshen-Honghua(DH) herb pair with different preparations (alcohol, 50% alcohol and water) on blood rheology and coagulation functions in acute blood stasis rats, and optimize the best preparation method of DH based on principal component analysis(PCA), hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods. Ice water bath and subcutaneous injection of adrenaline were both used to establish the acute blood stasis rat model. Then the blood stasis rats were administrated intragastrically with DH (alcohol, 50% alcohol and water) extracts. The whole blood viscosity(WBV), plasma viscosity(PV), erythrocyte sedimentation rate(ESR) and haematocrit(HCT) were tested to observe the effects of DH herb pair with different preparations and doses on hemorheology of blood stasis rats; the activated partial thromboplastin time(APTT), thrombin time(TT), prothrombin time(PT), and plasma fibr...</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="103477099"><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="103477099"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477099; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477099]").text(description); $(".js-view-count[data-work-id=103477099]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477099; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477099']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477099, 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" } } $('.js-work-strip[data-work-id=103477099]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477099,"title":"[Comparative study on promoting blood effects of Danshen-Honghua herb pair with different preparations based on chemometrics and multi-attribute comprehensive index methods]","translated_title":"","metadata":{"abstract":"To evaluate the promoting blood circulation and removing blood stasis effects of Danshen-Honghua(DH) herb pair with different preparations (alcohol, 50% alcohol and water) on blood rheology and coagulation functions in acute blood stasis rats, and optimize the best preparation method of DH based on principal component analysis(PCA), hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods. Ice water bath and subcutaneous injection of adrenaline were both used to establish the acute blood stasis rat model. Then the blood stasis rats were administrated intragastrically with DH (alcohol, 50% alcohol and water) extracts. The whole blood viscosity(WBV), plasma viscosity(PV), erythrocyte sedimentation rate(ESR) and haematocrit(HCT) were tested to observe the effects of DH herb pair with different preparations and doses on hemorheology of blood stasis rats; the activated partial thromboplastin time(APTT), thrombin time(TT), prothrombin time(PT), and plasma fibr...","publication_date":{"day":null,"month":null,"year":2017,"errors":{}},"publication_name":"Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica"},"translated_abstract":"To evaluate the promoting blood circulation and removing blood stasis effects of Danshen-Honghua(DH) herb pair with different preparations (alcohol, 50% alcohol and water) on blood rheology and coagulation functions in acute blood stasis rats, and optimize the best preparation method of DH based on principal component analysis(PCA), hierarchical cluster heatmap analysis and multi-attribute comprehensive index methods. Ice water bath and subcutaneous injection of adrenaline were both used to establish the acute blood stasis rat model. Then the blood stasis rats were administrated intragastrically with DH (alcohol, 50% alcohol and water) extracts. The whole blood viscosity(WBV), plasma viscosity(PV), erythrocyte sedimentation rate(ESR) and haematocrit(HCT) were tested to observe the effects of DH herb pair with different preparations and doses on hemorheology of blood stasis rats; the activated partial thromboplastin time(APTT), thrombin time(TT), prothrombin time(PT), and plasma fibr...","internal_url":"https://www.academia.edu/103477099/_Comparative_study_on_promoting_blood_effects_of_Danshen_Honghua_herb_pair_with_different_preparations_based_on_chemometrics_and_multi_attribute_comprehensive_index_methods_","translated_internal_url":"","created_at":"2023-06-17T07:31:19.726-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":274044901,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"_Comparative_study_on_promoting_blood_effects_of_Danshen_Honghua_herb_pair_with_different_preparations_based_on_chemometrics_and_multi_attribute_comprehensive_index_methods_","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":274044901,"first_name":"Lili","middle_initials":null,"last_name":"Shang","page_name":"LiliShang2","domain_name":"independent","created_at":"2023-06-17T07:30:42.428-07:00","display_name":"Lili Shang","url":"https://independent.academia.edu/LiliShang2"},"attachments":[],"research_interests":[{"id":4083,"name":"Complementary and Alternative Medicine","url":"https://www.academia.edu/Documents/in/Complementary_and_Alternative_Medicine"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":48732,"name":"Hemorheology","url":"https://www.academia.edu/Documents/in/Hemorheology"},{"id":53044,"name":"Fibrinogen","url":"https://www.academia.edu/Documents/in/Fibrinogen"},{"id":271683,"name":"Herb","url":"https://www.academia.edu/Documents/in/Herb"},{"id":389277,"name":"Blood Viscosity","url":"https://www.academia.edu/Documents/in/Blood_Viscosity"}],"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="103477098"><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/103477098/Multi_view_collaborative_semi_supervised_classification_algorithm_based_on_diversity_measurers_of_classifier_with_the_combination_of_agreement_and_disagreement_label_rules"><img alt="Research paper thumbnail of Multi-view collaborative semi-supervised classification algorithm based on diversity measurers of classifier with the combination of agreement and disagreement label rules" 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/103477098/Multi_view_collaborative_semi_supervised_classification_algorithm_based_on_diversity_measurers_of_classifier_with_the_combination_of_agreement_and_disagreement_label_rules">Multi-view collaborative semi-supervised classification algorithm based on diversity measurers of classifier with the combination of agreement and disagreement label rules</a></div><div class="wp-workCard_item"><span>Transactions of the Institute of Measurement and Control</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Considering the deficiencies of the Co-training algorithm including redundancy and sufficient con...</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">Considering the deficiencies of the Co-training algorithm including redundancy and sufficient conditions, diversity measurers of classifier, combined label rules, unoptimizable classifier during model updating process etc., a multi-view collaborative semi-supervised classification algorithm based on diversity measurers of the classifier with the combination of agreement and disagreement label rules (Co-AgDiag) is proposed. This algorithm uses a combination of agreement and disagreement label rules during the labelling unlabelled data process by judging whether the two classifiers are consistent and considering the diversity threshold in order to improve the performance of the classifier. During the process of generating classifier and model updating, we employed the diversity rule of classifier to update the model in order to judge the performance of the two classifiers. The experimental results on UCI datasets demonstrate the effectively and feasibility of the proposed algorithm fo...</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="103477098"><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="103477098"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477098; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477098]").text(description); $(".js-view-count[data-work-id=103477098]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477098; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477098']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477098, 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" } } $('.js-work-strip[data-work-id=103477098]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477098,"title":"Multi-view collaborative semi-supervised classification algorithm based on diversity measurers of classifier with the combination of agreement and disagreement label rules","translated_title":"","metadata":{"abstract":"Considering the deficiencies of the Co-training algorithm including redundancy and sufficient conditions, diversity measurers of classifier, combined label rules, unoptimizable classifier during model updating process etc., a multi-view collaborative semi-supervised classification algorithm based on diversity measurers of the classifier with the combination of agreement and disagreement label rules (Co-AgDiag) is proposed. This algorithm uses a combination of agreement and disagreement label rules during the labelling unlabelled data process by judging whether the two classifiers are consistent and considering the diversity threshold in order to improve the performance of the classifier. During the process of generating classifier and model updating, we employed the diversity rule of classifier to update the model in order to judge the performance of the two classifiers. The experimental results on UCI datasets demonstrate the effectively and feasibility of the proposed algorithm fo...","publisher":"SAGE Publications","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"Transactions of the Institute of Measurement and Control"},"translated_abstract":"Considering the deficiencies of the Co-training algorithm including redundancy and sufficient conditions, diversity measurers of classifier, combined label rules, unoptimizable classifier during model updating process etc., a multi-view collaborative semi-supervised classification algorithm based on diversity measurers of the classifier with the combination of agreement and disagreement label rules (Co-AgDiag) is proposed. This algorithm uses a combination of agreement and disagreement label rules during the labelling unlabelled data process by judging whether the two classifiers are consistent and considering the diversity threshold in order to improve the performance of the classifier. During the process of generating classifier and model updating, we employed the diversity rule of classifier to update the model in order to judge the performance of the two classifiers. The experimental results on UCI datasets demonstrate the effectively and feasibility of the proposed algorithm fo...","internal_url":"https://www.academia.edu/103477098/Multi_view_collaborative_semi_supervised_classification_algorithm_based_on_diversity_measurers_of_classifier_with_the_combination_of_agreement_and_disagreement_label_rules","translated_internal_url":"","created_at":"2023-06-17T07:31:19.515-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":274044901,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Multi_view_collaborative_semi_supervised_classification_algorithm_based_on_diversity_measurers_of_classifier_with_the_combination_of_agreement_and_disagreement_label_rules","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":274044901,"first_name":"Lili","middle_initials":null,"last_name":"Shang","page_name":"LiliShang2","domain_name":"independent","created_at":"2023-06-17T07:30:42.428-07:00","display_name":"Lili Shang","url":"https://independent.academia.edu/LiliShang2"},"attachments":[],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence"}],"urls":[{"id":32327728,"url":"http://journals.sagepub.com/doi/pdf/10.1177/0142331215617235"}]}, 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="103477097"><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/103477097/Comparative_Analysis_of_the_Effects_of_Hydroxysafflor_Yellow_A_and_Anhydrosafflor_Yellow_B_in_Safflower_Series_of_Herb_Pairs_Using_Prep_HPLC_and_a_Selective_Knock_Out_Approach"><img alt="Research paper thumbnail of Comparative Analysis of the Effects of Hydroxysafflor Yellow A and Anhydrosafflor Yellow B in Safflower Series of Herb Pairs Using Prep-HPLC and a Selective Knock-Out Approach" class="work-thumbnail" src="https://attachments.academia-assets.com/103474528/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/103477097/Comparative_Analysis_of_the_Effects_of_Hydroxysafflor_Yellow_A_and_Anhydrosafflor_Yellow_B_in_Safflower_Series_of_Herb_Pairs_Using_Prep_HPLC_and_a_Selective_Knock_Out_Approach">Comparative Analysis of the Effects of Hydroxysafflor Yellow A and Anhydrosafflor Yellow B in Safflower Series of Herb Pairs Using Prep-HPLC and a Selective Knock-Out Approach</a></div><div class="wp-workCard_item"><span>Molecules (Basel, Switzerland)</span><span>, Jan 6, 2016</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The flower of Carthamus tinctorius L. (Carthami Flos, safflower), important in traditional Chines...</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 flower of Carthamus tinctorius L. (Carthami Flos, safflower), important in traditional Chinese medicine (TCM), is known for treating blood stasis, coronary heart disease, hypertension, and cerebrovascular disease in clinical and experimental studies. It is widely accepted that hydroxysafflor yellow A (HSYA) and anhydrosafflor yellow B (ASYB) are the major bioactive components of many formulae comprised of safflower. In this study, selective knock-out of target components such as HSYA and ASYB by using preparative high performance liquid chromatography (prep-HPLC) followed by antiplatelet and anticoagulation activities evaluation was used to investigate the roles of bioactive ingredients in safflower series of herb pairs. The results showed that both HSYA and ASYB not only played a direct role in activating blood circulation, but also indirectly made a contribution to the total bioactivity of safflower series of herb pairs. The degree of contribution of HSYA in the safflower and ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="fb5b6120cad07c3b680febfa3e141084" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474528,&quot;asset_id&quot;:103477097,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474528/download_file?st=MTczMjM4NTcwNCw4LjIyMi4yMDguMTQ2&st=MTczMjM4NTcwMyw4LjIyMi4yMDguMTQ2&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="103477097"><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="103477097"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477097; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477097]").text(description); $(".js-view-count[data-work-id=103477097]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477097; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477097']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477097, 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: "fb5b6120cad07c3b680febfa3e141084" } } $('.js-work-strip[data-work-id=103477097]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477097,"title":"Comparative Analysis of the Effects of Hydroxysafflor Yellow A and Anhydrosafflor Yellow B in Safflower Series of Herb Pairs Using Prep-HPLC and a Selective Knock-Out Approach","translated_title":"","metadata":{"abstract":"The flower of Carthamus tinctorius L. (Carthami Flos, safflower), important in traditional Chinese medicine (TCM), is known for treating blood stasis, coronary heart disease, hypertension, and cerebrovascular disease in clinical and experimental studies. It is widely accepted that hydroxysafflor yellow A (HSYA) and anhydrosafflor yellow B (ASYB) are the major bioactive components of many formulae comprised of safflower. In this study, selective knock-out of target components such as HSYA and ASYB by using preparative high performance liquid chromatography (prep-HPLC) followed by antiplatelet and anticoagulation activities evaluation was used to investigate the roles of bioactive ingredients in safflower series of herb pairs. The results showed that both HSYA and ASYB not only played a direct role in activating blood circulation, but also indirectly made a contribution to the total bioactivity of safflower series of herb pairs. The degree of contribution of HSYA in the safflower and ...","publication_date":{"day":6,"month":1,"year":2016,"errors":{}},"publication_name":"Molecules (Basel, Switzerland)"},"translated_abstract":"The flower of Carthamus tinctorius L. (Carthami Flos, safflower), important in traditional Chinese medicine (TCM), is known for treating blood stasis, coronary heart disease, hypertension, and cerebrovascular disease in clinical and experimental studies. It is widely accepted that hydroxysafflor yellow A (HSYA) and anhydrosafflor yellow B (ASYB) are the major bioactive components of many formulae comprised of safflower. In this study, selective knock-out of target components such as HSYA and ASYB by using preparative high performance liquid chromatography (prep-HPLC) followed by antiplatelet and anticoagulation activities evaluation was used to investigate the roles of bioactive ingredients in safflower series of herb pairs. The results showed that both HSYA and ASYB not only played a direct role in activating blood circulation, but also indirectly made a contribution to the total bioactivity of safflower series of herb pairs. 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data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/103477093/VSOP_Imaging_of_the_Southern_Blazar_J1924_29_at_18_cm"><img alt="Research paper thumbnail of VSOP Imaging of the Southern Blazar J1924-29 at 18 cm" class="work-thumbnail" src="https://attachments.academia-assets.com/103474522/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/103477093/VSOP_Imaging_of_the_Southern_Blazar_J1924_29_at_18_cm">VSOP Imaging of the Southern Blazar J1924-29 at 18 cm</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We present preliminary results of the VSOP imaging of the nearby southern blazar J1924-29 at 18 c...</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 present preliminary results of the VSOP imaging of the nearby southern blazar J1924-29 at 18 cm. The high resolution image shows that the source possesses a core-jet structure along the northeast direction. The brightness temperature of the core in the rest frame of the quasar is 1.18×1012 K.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c1f53521f6884a5316b737704c60c35d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{&quot;attachment_id&quot;:103474522,&quot;asset_id&quot;:103477093,&quot;asset_type&quot;:&quot;Work&quot;,&quot;button_location&quot;:&quot;profile&quot;}" href="https://www.academia.edu/attachments/103474522/download_file?st=MTczMjM4NTcwNCw4LjIyMi4yMDguMTQ2&st=MTczMjM4NTcwNCw4LjIyMi4yMDguMTQ2&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="103477093"><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="103477093"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477093; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477093]").text(description); $(".js-view-count[data-work-id=103477093]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477093; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477093']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477093, 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: "c1f53521f6884a5316b737704c60c35d" } } $('.js-work-strip[data-work-id=103477093]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477093,"title":"VSOP Imaging of the Southern Blazar J1924-29 at 18 cm","translated_title":"","metadata":{"abstract":"We present preliminary results of the VSOP imaging of the nearby southern blazar J1924-29 at 18 cm. 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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="103477092"><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/103477092/Multi_view_semi_supervised_collaboration_classification_algorithm_with_combination_of_agreement_and_disagreement_label_rules"><img alt="Research paper thumbnail of Multi-view semi-supervised collaboration classification algorithm with combination of agreement and disagreement label rules" 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/103477092/Multi_view_semi_supervised_collaboration_classification_algorithm_with_combination_of_agreement_and_disagreement_label_rules">Multi-view semi-supervised collaboration classification algorithm with combination of agreement and disagreement label rules</a></div><div class="wp-workCard_item"><span>Journal of Computer Applications</span><span>, 2013</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">To improve the performance of the co-training algorithm and expand the range of applications, a m...</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">To improve the performance of the co-training algorithm and expand the range of applications, a multi-view semi-supervised collaboration classification algorithm with the combination of consistent and inconsistent label rules was proposed, which aimed at providing a more effective method for the classification of the bridge structured health data. The proposed algorithm used combination of agreement and disagreement label rules for the unlabeled data by judging whether the two classifiers were consistent. Put the sample to the label set, if the label results were consistent. If the label results were inconsistent and the confidence was beyond the threshold, it put the label result of the high confidence to the label set, took full use of the unlabeled data to improve the performance of the classifier, and updated the classification model by the difference of the classifiers. The experimental results of the proposed algorithm on the bridge structured health datasets and standard UCI datasets verify the effectiveness and feasibility of the proposed model on the multi-view classification problems.</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="103477092"><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="103477092"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477092; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477092]").text(description); $(".js-view-count[data-work-id=103477092]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477092; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477092']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477092, 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" } } $('.js-work-strip[data-work-id=103477092]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477092,"title":"Multi-view semi-supervised collaboration classification algorithm with combination of agreement and disagreement label rules","translated_title":"","metadata":{"abstract":"To improve the performance of the co-training algorithm and expand the range of applications, a multi-view semi-supervised collaboration classification algorithm with the combination of consistent and inconsistent label rules was proposed, which aimed at providing a more effective method for the classification of the bridge structured health data. 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The experimental results of the proposed algorithm on the bridge structured health datasets and standard UCI datasets verify the effectiveness and feasibility of the proposed model on the multi-view classification problems.","publisher":"China Science Publishing \u0026 Media Ltd.","publication_date":{"day":null,"month":null,"year":2013,"errors":{}},"publication_name":"Journal of Computer Applications"},"translated_abstract":"To improve the performance of the co-training algorithm and expand the range of applications, a multi-view semi-supervised collaboration classification algorithm with the combination of consistent and inconsistent label rules was proposed, which aimed at providing a more effective method for the classification of the bridge structured health data. The proposed algorithm used combination of agreement and disagreement label rules for the unlabeled data by judging whether the two classifiers were consistent. 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To solve this problem, an online recursive identification method over networks with random packet losses is proposed. In this algorithm, the Bernoulli processes is firstly employed to describe the character of data packet losses. Considering random packet losses, an improved recursive least squares (RLS) algorithm is then presented by using Givens transformation, where the intermediate matrix can be updated recursively. Simulation results show that the proposed algorithm is able to significantly enhance the accuracy of parameter estimation, and the estimated variance becomes smaller as the number of iterations increases.</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="103477091"><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="103477091"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 103477091; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=103477091]").text(description); $(".js-view-count[data-work-id=103477091]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 103477091; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='103477091']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 103477091, 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" } } $('.js-work-strip[data-work-id=103477091]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":103477091,"title":"An Online Recursive Identification Method over Networks with Random Packet Losses","translated_title":"","metadata":{"abstract":"Under the network environment, data packet losses bring an undesirable effect on parameter identification. 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