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Topological screen identifies hundreds of Cp190- and CTCF-dependent Drosophila chromatin insulator elements

science Advances 2023年第5期9卷

作者： Kahn, Tatyana G. Savitsky, Mikhail Kuong, Chikuan Jacquier, Caroline Cavalli, Giacomo Chang, Jia-Ming Schwartz, Yuri B. Department of Molecular Biology Umeå University Umeå Sweden Department of Computer Science National Chengchi University Taipei City Taiwan Institute of Human Genetics UMR9002 CNRS Montpellier France

Drosophila insulators were the first DNA elements found to regulate gene expression by delimiting chromatin contacts. We still do not know how many of them exist and what impact they have on the Drosophila genome folding. Contrary to vertebrates, there is no evidence that fly insulators block cohesin-mediated chromatin loop extrusion. Therefore, their mechanism of action remains uncertain. To bridge these gaps, we mapped chromatin contacts in Drosophila cells lacking the key insulator proteins CTCF and Cp190. With this approach, we found hundreds of insulator elements. Their study indicates that Drosophila insulators play a minor role in the overall genome folding but affect chromatin contacts locally at many loci. Our observations argue that Cp190 promotes cobinding of other insulator proteins and that the model, where Drosophila insulators block chromatin contacts by forming loops, needs revision. Our insulator catalog provides an important resource to study mechanisms of genome folding. Copyright © 2023 The Authors.

关键词： Proteins

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A User-Centered Extended Reality Authoring Tool Development Framework for General Aviation Weather Training

A User-Centered Extended Reality Authoring Tool Development ...

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Conference on Digital Avionics Systems (DASC)

作者： Jiwon Kim Kexin Wang Jack Miller Michael Dorneich Eliot Winer Lori Brown Industrial and Manufacturing Systems Engineering Iowa State University Ames IA USA Human Computer Interaction Iowa State University Ames IA USA Mechanical Engineering Iowa State University Ames IA USA Aviation Flight Science Western Michigan University Kalamazoo MI USA

This paper describes a comprehensive framework for the development of an extended reality (XR) authoring toolkit for general aviation weather training. Conventional weather training methods often rely on static, text-based materials, which might result in limited engagement and failure to provide an immersive experience tailored to the unique learning needs of students. Conversely, XR-enhanced lessons offer promising alternatives to enhance weather-related knowledge and decision-making. However, existing XR toolkits typically require advanced programming skills, posing challenges for non-technologist instructors. To address this gap, a content-centered approach that shifts the focus from the technicalities of developing augmented reality visualizations to enabling non-technologist instructors to readily interact with weather objects and scenario elements is proposed. The development framework, rooted in the user-centered design approach, encompasses understanding the user's context, specifying requirements, and developing a prototype. This study provides a description of the framework, accompanied by a case study specifically tailored to developing an XR authoring toolkit for general aviation weather training. Emphasis is placed on the significance of conducting comprehensive user studies and adhering to evidence-based software design guidance throughout the development process. The proposed framework is expected to contribute to the development of user-friendly 3D authoring environments, empowering instructors to create engaging and interactive aviation weather lessons. By enabling non-technologist instructors to create XR-enhanced lessons without requiring extensive computer skills, the framework aims to broaden access to XR-based training, catering to a wider audience.

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Isometric Vector Neuroanalyzer 2

Isometric Vector Neuroanalyzer

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2nd International Conference on Neural Networks and Neurotechnologies, NeuroNT 2021

作者： Safyannikov, Nikolay M. Bureneva, Olga I. Aleksanyan, Zoya A. Chepasov, Aleksandr E. Saint-Petersburg Electrotechnical University LETI Department of Computer Science and Engineering Saint Petersburg Russia Institute of the Human Brain Russian Academy of Sciences Saint Petersburg Russia

ISBN: (纸本)9781665445344

In the sphere of neurotechnology, hardware systems for obtaining and analyzing data on the features of central nervous system (CNS) functioning are of great importance. One of the directions is related to the development of methods and hardware for CNS state assessment by motor activity. The proposed report is about the isometric vector neuroanalyzer that allows estimating the functional state of the human central nervous system based on the analysis of involuntary movements of limbs occurring against the background of isometric efforts. The analyzer can be used for scientific research, in neurology, sports medicine, and in other areas where evaluation of the CNS condition is required. © 2021 IEEE.

关键词： Neurophysiology

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Pre-training Multi-party Dialogue Models with Latent Discourse Inference

arXiv

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arXiv 2023年

作者： Li, Yiyang Huang, Xinting Bi, Wei Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China NLP Center Tencent AI-Lab Hong Kong

Multi-party dialogues are more difficult for models to understand than one-to-one two-party dialogues, since they involve multiple interlocutors, resulting in interweaving reply-to relations and information flows. To step over these obstacles, an effective way is to pre-train a model that understands the discourse structure of multi-party dialogues, namely, to whom each utterance is replying. However, due to the lack of explicitly annotated discourse labels in multi-party dialogue corpora, previous works fail to scale up the pre-training process by putting aside the unlabeled multi-party conversational data for nothing. To fully utilize the unlabeled data, we propose to treat the discourse structures as latent variables, then jointly infer them and pre-train the discourse-aware model by unsupervised latent variable inference methods. Experiments on multiple downstream tasks show that our pre-trained model outperforms strong baselines by large margins and achieves state-of-the-art (SOTA) results, justifying the effectiveness of our method. The official implementation of this paper is available at https://***/EricLee8/MPD_EMVI. © 2023, CC BY.

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Developing Digital Therapeutics: The University Health Network Experience

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Journal of Commercial Biotechnology 2022年第1期27卷 7-11页

作者： Pham, Quynh Cafazzo, Joseph The Centre for Global eHealth Innovation Techna Institute University Health Network Canada Healthcare Human Factors Techna Institute University of Toronto Institute of Health Policy Canada Dalla Lana School of Public Health University of Toronto Canada Telfer School of Management University of Ottawa Canada Institute of Biomedical Engineering University of Toronto Department of Computer Science Canada

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PaCaNet: A Study on CycleGAN with Transfer Learning for Diversifying Fused Chinese Painting and Calligraphy

arXiv

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arXiv 2023年

作者： Yang, Zuhao Xu, Yang Yuan, Yisheng Bai, Huajun Pang, Wei Hu, Yeqi Luo, Zhang Wang, Yue Yuan, Yingfang School of Computer Science and Engineering Nanyang Technological University Singapore Department of Computer Science San Diego State University United States Graphic Design Department Rhode Island School of Design United States Seafog AI China School of Mathematical and Computer Sciences Heriot-Watt University United Kingdom College of Information Science and Engineering Ocean University of China China Graduate School of Advanced Integrated Studies in Human Survivability Kyoto University Japan

AI-Generated Content (AIGC) has recently gained a surge in popularity, powered by its high efficiency and consistency in production, and its capability of being customized and diversified. The cross-modality nature of the representation learning mechanism in most AIGC technology allows for more freedom and flexibility in exploring new types of art that would be impossible in the past. Inspired by the pictogram subset of Chinese characters, we proposed PaCaNet, a CycleGAN-based pipeline for producing novel artworks that fuse two different art types, traditional Chinese painting and calligraphy. In an effort to produce stable and diversified output, we adopted three main technical innovations: (1) Using one-shot learning to increase the creativity of pre-trained models and diversify the content of the fused images. (2) Controlling the preference over generated Chinese calligraphy by freezing randomly sampled parameters in pre-trained models. (3) Using a regularization method to encourage the models to produce images similar to Chinese paintings. Furthermore, we conducted a systematic study to explore the performance of PaCaNet in diversifying fused Chinese painting and calligraphy, which showed satisfying results. In conclusion, we provide a new direction of creating arts by fusing the visual information in paintings and the stroke features in Chinese calligraphy. Our approach creates a unique aesthetic experience rooted in the origination of Chinese hieroglyph characters. It is also a unique opportunity to delve deeper into traditional artwork and, in doing so, to create a meaningful impact on preserving and revitalizing traditional heritage. © 2023, CC BY-NC-SA.

关键词： Transfer learning

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Coach, Data Analyst, and Protector: Exploring Data Practices of Collegiate Coaching Staff 25

Coach, Data Analyst, and Protector: Exploring Data Practices...

引用

2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Brewer, Mollie Childs, Kevin Thomas, Spencer Wilkins, Celeste Boyer, Kristy Elizabeth Nichols, Jennifer A. Butler, Kevin R.B. Beatty, Garrett F. Ferris, Daniel P. Department of Computer & Information Science & Engineering University of Florida Gainesville United States University Athletic Association GainesvilleFL United States J. Crayton Pruitt Family Dept. of Biomedical Engineering University of Florida GainesvilleFL United States College of Health & Human Performance University of Florida GainesvilleFL United States

ISBN: (纸本)9798400713941

A rapidly emerging research community at the intersection of sport and human-computer interaction (SportsHCI) explores how technology can support physically active humans, such as athletes. At highly competitive levels, coaching staff play a central role in the athlete experience by using data to enhance performance, reduce injuries, and foster team success. However, little is known about the practices and needs of these coaching staff. We conducted five focus groups with 17 collegiate coaching staff across three women's teams and two men's teams at an elite U.S. university. Our findings show that coaching staff selectively use data with the goal of balancing performance goals, athlete emotional well-being, and privacy. This paper contributes design recommendations to support coaching staff in operating across the data life cycle through gathering, sharing, deciding, acting, and assessing data as they aim to support team success and foster the well-being of student-athletes. © 2025 Copyright held by the owner/author(s).

关键词： SportsHCI

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The effect of distance and angle of virtual keyboard on user experience of bare hand interaction in VR

引用

Displays 2025年 90卷

作者： Haiqing Tang Chi Zhang Fan Yang Human-Computer Interaction Laboratory Department of Product Design School of Art and Design Dalian Polytechnic University Dalian China

Along with the popularization of natural computer interaction, bare hand interaction has become an important tool for text input in virtual spatial. However, there is still a lack of sufficient research on how to choose the placement of the virtual keyboard to enhance text input efficiency and user experience in using bare hand interaction techniques. This study examines how the interaction between the placement distance and angle of the virtual keyboard affects the text input efficiency and user experience, which provides suitable parameters for the use of bare hand interaction techniques in virtual reality. Text entry efficiency was obtained by evaluating words per minute (WPM) and error rates, and user experience was gathered by measuring user preference level, fatigue, and workload. We asked 33 participants to perform text input tasks of different difficulties at 3 angles (tilted, medium tilted, vertical) in 3 distances (near, medium near, far). The results showed that while WPM was generally higher in the near distance situation, it also caused greater stress and fatigue for the participants. Medium tilted and vertical in the medium near distance generally performs better in terms of text input efficiency and user experience, and were considered to be a suitable parameter for text input in bare hand interaction. In addition, the far distance showed higher WPM only at vertical angles, but performed poorly at all other angles.

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Dietary carbohydrate intake and risk of type 2 diabetes:a 16-year prospective cohort study

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science China(Life sciences) 2025年第4期68卷 1149-1157页

作者： Lu Gan Yi Yang Bin Zhao Kai Yu Kehua Guo Fang Fang Zhiguang Zhou Demetrius Albanes Jiaqi Huang National Clinical Research Center for Metabolic Diseases Metabolic Syndrome Research CenterKey Laboratory of Diabetes ImmunologyMinistry of Educationand Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityCSU-Sinocare Research Center for Nutrition and Metabolic HealthXiangya School of Public HealthCentral South UniversityFurong LaboratoryChangsha410011China Division of Cancer Epidemiology and Genetics National Cancer InstituteNIHDepartment of Health and Human ServicesBethesdaMD20892USA School of Computer Science and Engineering Central South UniversityChangsha410083China Institute of Environmental Medicine Karolinska InstituteStockholm17177Sweden National Clinical Research Center for Metabolic Diseases Key Laboratory of Diabetes ImmunologyMinistry of Educationand Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangsha410011China

Despite considerable research underscoring the importance of carbohydrate intake in relation to the risk of type 2 diabetes(T2D),a comprehensive assessment of this relationship is currently *** aimed to examine the associations of various types and food sources of dietary carbohydrate intake with the risk of T2D,to evaluate potential effect modification by other factors,including genetic susceptibility,and to explore the potential mediators for such *** present study included 161,872 participants of the UK Biobank who were free of prevalent cancer,cardiovascular disease,or diabetes,and had at least one validated 24-h dietary recall *** age-stratified Cox proportional hazard regression models were applied to estimate hazard ratios(HRs)and 95%confidence intervals(CI)for the associations of various types and food sources of dietary carbohydrate intake with risk of *** a median follow-up of 13.6 years,4,176 incident cases of T2D were *** the multivariable-adjusted models,a greater intake of fiber,carbohydrates from whole grains,and carbohydrates from non-starchy vegetables was significantly associated with a lower risk of T2D(highest *** quantile,HR[95%CI]=0.70[0.62–0.79],0.74[0.67–0.82],and 0.83[0.75–0.92],respectively,all P for trend<0.005).In contrast,a higher intake of starch and carbohydrate from starchy vegetables was associated with an increased risk of T2D(highest *** quantile,HR[95%CI]=1.31[1.16–1.48]and 1.19[1.09–1.31],respectively,both P for trend<0.005).Replacing one serving of refined grains or starchy vegetables with an equal amount of whole grains or non-starchy vegetables was associated with 4%to 10%lower risk of T2D(all P values<0.001).The observed associations were generally similar across population subgroups,including individuals with different genetic susceptibility to *** analyses of the inverse association between T2D risk and isocaloric substitution of carbohy

关键词： dietary carbohydrate type 2 diabetes prospective cohort study UK Biobank

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The ToMCAT dataset 23

The ToMCAT dataset

引用

Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Adarsh Pyarelal Eric Duong Caleb Jones Shibu Paulo Soares Savannah Boyd Payal Khosla Valeria Pfeifer Diheng Zhang Eric Andrews Rick Champlin Vincent Raymond Meghavarshini Krishnaswamy Clayton Morrison Emily Butler Kobus Barnard School of Information University of Arizona Department of Computer Science University of Arizona Department of Psychology University of Arizona Norton School of Human Ecology University of Arizona Lum AI University of Arizona Department of Linguistics University of Arizona

We present a rich, multimodal dataset consisting of data from 40 teams of three humans conducting simulated urban search-and-rescue (SAR) missions in a Minecraft-based testbed, collected for the Theory of Mind-based Cognitive Architecture for Teams (ToMCAT) project. Modalities include two kinds of brain scan data— functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), as well as skin conductance, heart rate, eye tracking, face images, spoken dialog audio data with automatic speech recognition (ASR) transcriptions, game screenshots, gameplay data, game performance data, demographic data, and self-report questionnaires. Each team undergoes up to six consecutive phases: three behavioral tasks, one mission training session, and two collaborative SAR missions. This dataset will support studying a large variety of research questions on topics including teamwork, coordination, plan recognition, affective computing, physiological linkage, entrainment, and dialog understanding. We provide an initial public release of the de-identified data, along with analyses illustrating the utility of this dataset to both computer scientists and social scientists.

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