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| http://dx.doi.org/10.4049/jimmunol.178.8.4707 | DOI Listing |
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Aspect category sentiment analysis based on pre-trained BiLSTM and syntax-aware graph attention network.
Sci Rep
January 2025
Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing, 100081, China.
Aspect Category Sentiment Analysis (ACSA) is a fine-grained sentiment analysis task aimed at predicting the sentiment polarity associated with aspect categories within a sentence.Most existing ACSA methods are based on a given aspect category to locate sentiment words related to it. When irrelevant sentiment words have semantic meaning for the given aspect category, it may cause the problem that sentiment words cannot be matched with aspect categories.
View Article and Find Full Text PDFExpert Comment Generation Considering Sports Skill Level Using a Large Multimodal Model with Video and Spatial-Temporal Motion Features.
Sensors (Basel)
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Faculty of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-ku, Sapporo 060-0814, Hokkaido, Japan.
In sports training, personalized skill assessment and feedback are crucial for athletes to master complex movements and improve performance. However, existing research on skill transfer predominantly focuses on skill evaluation through video analysis, addressing only a single facet of the multifaceted process required for skill acquisition. Furthermore, in the limited studies that generate expert comments, the learner's skill level is predetermined, and the spatial-temporal information of human movement is often overlooked.
View Article and Find Full Text PDFCommentary: The ME-BYO index: A development and validation project of a novel comprehensive health index.
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Antony- Xavier Interdisciplinary Scholastics (AXIS), GN Corporation Co. Ltd., Kofu, Japan.
Going to extremes: progress in exploring new environments for novel antibiotics.
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Institute of Life Sciences, Medical School, Swansea University, Singleton Park, Swansea, SA2 8PP, Wales, UK.
The discoveries of penicillin and streptomycin were pivotal for infection control with the knowledge subsequently being used to enable the discovery of many other antibiotics currently used in clinical practice. These valuable compounds are generally derived from mesophilic soil microorganisms, predominantly Streptomyces species. Unfortunately, problems with the replication of results suggested that this discovery strategy was no longer viable, motivating a switch to combinatorial chemistry in conjunction with existing screening programmes to derive new antimicrobials.
View Article and Find Full Text PDFEducation Research: Making a Tweetorial Fly: Features of Educational Social Media Posts Associated With High Sharing and Engagement.
Neurol Educ
December 2024
From the Departments of Neurology and Neurosurgery (C.S.W.A., E.C.L.), Emory University School of Medicine, Atlanta, GA; Division of Biostatistics (T.M.), Rollins School of Public Health, Emory University, Atlanta, GA; Department of Neurology (G.F.P.), University of Pittsburgh, PA; Department of Neurology (A.S.Z.), Weill Cornell Medical College, New York, NY; Emory University School of Medicine (N.D.), Atlanta, GA; Consulting Web Developer (S.M.), Scotland; Department of Neurology (A.S.), Wake Forest University, Winston-Salem, NC; Departments of Neurology and Neurosurgery (N.S.D), Icahn School of Medicine at Mount Sinai, New York, NY; Department of Neurology (A.L.B.), University of California, San Francisco; Department of Neurology (N.A.M.), University of Maryland School of Medicine, Baltimore, MD; and Department of Neurology (L.K.J.), Mayo Clinic, Rochester, MN.
Background And Objectives: Social media platforms such as X (formerly Twitter) are increasingly used in medical education. Characteristics of tweetorials (threaded teaching posts) associated with higher degrees of engagement are unknown. We sought to understand features of neurology-themed tweetorials associated with high sharing and engagement.
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