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Transdisciplinary reflections on social robotics in academia and beyond 3

Transdisciplinary reflections on social robotics in academia...

3rd International Conference on Robophilosophy 2018 / Transor 2018: Envisioning Robots in Society - Politics, Power, and Public Space

作者： Hannibal, Glenda Lindner, Felix Vienna University of Technology Institute of Visual Computing and Human-Centered Technology Research Division of Human Computer Interaction Argentinierstraße 8 Vienna1040 Austria Department of Computer Science University of Freiburg Germany

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Combined effects of host genetics and diet on human gut microbiota and incident disease in a single population cohort (vol 54, pg 134, 2022)

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NATURE GENETICS 2024年第3期56卷 554-554页

作者： Qin, Youwen Havulinna, Aki S. Liu, Yang Jousilahti, Pekka Ritchie, Scott C. Tokolyi, Alex Sanders, Jon G. Valsta, Liisa Brozynska, Marta Zhu, Qiyun Tripathi, Anupriya Vazquez-Baeza, Yoshiki Loomba, Rohit Cheng, Susan Jain, Mohit Niiranen, Teemu Lahti, Leo Knight, Rob Salomaa, Veikko Inouye, Michael Meric, Guillaume Cambridge Baker Systems Genomics Initiative Baker Heart and Diabetes Institute Melbourne Victoria Australia School of BioSciences The University of Melbourne Melbourne Victoria Australia Department of Clinical Pathology Melbourne Medical School The University of Melbourne Melbourne Victoria Australia Cambridge Baker Systems Genomics Initiative Department of Public Health and Primary Care University of Cambridge Cambridge UK British Heart Foundation Centre of Research Excellence University of Cambridge Cambridge UK British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge UK Health Data Research UK Cambridge Wellcome Genome Campus & University of Cambridge Cambridge UK The Alan Turing Institute London UK Department of Infectious Diseases Central Clinical School Monash University Melbourne Victoria Australia Department of Public Health and Welfare Finnish Institute for Health and Welfare Helsinki Finland Institute for Molecular Medicine Finland FIMM-HiLIFE Helsinki Finland Department of Medicine Turku University Hospital and University of Turku Turku Finland Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Ecology and Evolutionary Biology Cornell University Ithaca NY USA Cornell Institute for Host-Microbe Interaction and Disease Cornell University Ithaca NY USA Department of Pediatrics School of Medicine University of California San Diego La Jolla CA USA Division of Biological Sciences University of California San Diego La Jolla CA USA Center for Microbiome Innovation University of California San Diego La Jolla CA USA Department of Computer Science & Engineering Jacobs School of Engineering University of California San Diego La Jolla CA USA NAFLD Research Center Department of Medicine University of California San Diego La Jolla CA USA Smidt Heart Institute Cedars-Sinai Medical Center Los Angeles CA USA Department of Computing Univer

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Skeleton-Based Intake Gesture Detection With Spatial-Temporal Graph Convolutional Networks

arXiv

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arXiv 2025年

作者： Wang, Chunzhuo Xue, Zhewen Kumar, T. Sunil Camps, Guido Hallez, Hans Vanrumste, Bart e-Media Research Lab the ESAT-STADIUS Division KU Leuven Leuven3000 Belgium University of Gävle Gävle801 76 Sweden Division of Human Nutrition and Health Department of Agrotechnology and Food Sciences Wageningen University and Research OnePlanet Research Center 6700EA Wageningen Wageningen6708WE Netherlands M-Group DistriNet Department of Computer Science KU Leuven Sint-Michiels8200 Belgium

Overweight and obesity have emerged as widespread societal challenges, frequently linked to unhealthy eating patterns. A promising approach to enhance dietary monitoring in everyday life involves automated detection of food intake gestures. This study introduces a skeleton based approach using a model that combines a dilated spatial-temporal graph convolutional network (ST-GCN) with a bidirectional long-short-term memory (BiLSTM) framework, as called ST-GCN-BiLSTM, to detect intake gestures. The skeleton-based method provides key benefits, including environmental robustness, reduced data dependency, and enhanced privacy preservation. Two datasets were employed for model validation. The OREBA dataset, which consists of laboratory-recorded videos, achieved segmental F1-scores of 86.18% and 74.84% for identifying eating and drinking gestures. Additionally, a self-collected dataset using smartphone recordings in more adaptable experimental conditions was evaluated with the model trained on OREBA, yielding F1-scores of 85.40% and 67.80% for detecting eating and drinking gestures. The results not only confirm the feasibility of utilizing skeleton data for intake gesture detection but also highlight the robustness of the proposed approach in cross-dataset validation. Copyright © 2025, The Authors. All rights reserved.

关键词： Musculoskeletal system

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The micro-randomized trial for developing digital interventions: Experimental design considerations

arXiv

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arXiv 2020年

作者： Walton, Ashley E. Collins, Linda M. Klasnja, Predrag Nahum-Shani, Inbal Rabbi, Mashfiqui Walton, Maureen A. Murphy, Susan A. Department of Philosophy Dartmouth College Methodology Center Department of Human Development & Family Studies Pennsylvania State University School of Information University of Michigan Institute for Social Research University of Michigan Department of Statistics Harvard University Department of Psychiatry and Injury Prevention Center University of Michigan Departments of Statistics and Computer Science Harvard University

Just-in-time adaptive interventions (JITAIs) are time-varying adaptive interventions that can deploy a high intensity of adaptation;in other words, use frequent opportunities for the intervention to be adapted-weekly, daily, or even many times a day. This high intensity of adaptation is facilitated by the ability of digital technology to continuously collect information about an individual's current context and make treatment decisions adapted to this information. The micro-randomized trial (MRT) has emerged for use in informing the construction of JITAIs. MRTs operate in, and take advantage of, the rapidly time-varying digital intervention environment. MRTs can be used to address research questions about whether and under what circumstances particular components of a JITAI are effective, with the ultimate objective of developing effective and efficient components. The purpose of this article is to clarify why, when, and how to use MRTs;to highlight elements that must be considered when designing and implementing an MRT;and to discuss the possibilities this emerging optimization trial design offers for future research in the behavioral sciences, education, and other fields. We briefly review key elements of JITAIs, and then describe three case studies of MRTs, each of which highlights research questions that can be addressed using the MRT and experimental design considerations that might arise. We also discuss a variety of considerations that go into planning and designing an MRT, using the case studies as *** Codes 62P15 Copyright © 2020, The Authors. All rights reserved.

关键词： Just in time production

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Effects and Issues of the Disaster Information Tweeting and Mapping System for Residents

Effects and Issues of the Disaster Information Tweeting and ...

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International Conference on computers, Communications, and Systems (ICCCS)

作者： Hiroya Yamada Yoshitaka Kajita Sachi Tajima Keisuke Utsu Osamu Uchida Yuji Murakami Department of Civil Engineering Tokai University Hiratsuka Japan Center of Liberal Arts Tokai University Hiratsuka Japan Department of Communication and Network Eng. Tokai University Hiratsuka Japan Department of Human and Information Science Tokai University Hiratsuka Japan Department of Electrical Eng. and Computer Science Tokai University Kumamoto Japan

ISBN: (数字)9781728161365

ISBN: (纸本)9781728161372

Using social media for information sharing during and after disasters has been gaining attention. To facilitate information sharing during disasters, we developed a web system called Disaster Information Tweeting and Mapping System (DITS/DIMS). We organized a disaster evacuation drill in July 2019 and participated in a disaster prevention fair in August 2019 using DITS/DIMS in Hiratsuka City, Kanagawa prefecture, Japan. In this paper, we describe the results from the questionnaire surveys at the two events. The results showed that participants recognized that DITS/DIMS could be useful during disasters. Therefore, the use of this system has the potential to make an important contribution to disaster prevention and mitigation. However, some issues exist with the system when it is actually used by individuals; therefore, future improvements are required.

关键词： Twitter Urban areas Tagging Mobile handsets Browsers

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Identifying Clinical Terms in Free-Text Notes Using Ontology-Guided Machine Learning 1

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23rd International Conference on Research in Computational Molecular Biology, RECOMB 2019

作者： Arbabi, Aryan Adams, David R. Fidler, Sanja Brudno, Michael Department of Computer Science University of Toronto TorontoON Canada Center for Computational Medicine Hospital for Sick Children TorontoON Canada Vector Institute TorontoON Canada Section on Human Biochemical Genetics National Human Genome Research Institute National Institutes of Health BethesdaMD United States

ISBN: (数字)9783030170837

ISBN: (纸本)9783030170820

Objective: Automatic recognition of medical concepts in unstructured text is an important component of many clinical and research applications and its accuracy has a large impact on electronic health record analysis. The mining of such terms is complicated by the broad use of synonyms and non-standard terms in medical documents. Here we presented a machine learning model for concept recognition in large unstructured text which optimizes the use of ontological structures and can identify previously unobserved synonyms for concepts in the ontology. Materials and Methods: We present a neural dictionary model which can be used to predict if a phrase is synonymous to a concept in a reference ontology. Our model, called Neural Concept Recognizer (NCR), uses a convolutional neural network and utilizes the taxonomy structure to encode input phrases, then rank medical concepts based on the similarity in that space. It also utilizes the biomedical ontology structure to optimize the embedding of various terms and has fewer training constraints than previous methods. We train our model on two biomedical ontologies, the human Phenotype Ontology (HPO) and SNOMED-CT. Results: We tested our model trained on HPO on two different data sets: 288 annotated PubMed abstracts and 39 clinical reports. We also tested our model trained on the SNOMED-CT on 2000 MIMIC-III ICU discharge summaries. The results of our experiments show the high accuracy of our model, as well as the value of utilizing the taxonomy structure of the ontology in concept recognition. Conclusion: Most popular medical concept recognizers rely on rule-based models, which cannot generalize well to unseen synonyms. Also, most machine learning methods typically require large corpora of annotated text that cover all classes of concepts, which can be extremely difficult to get for biomedical ontologies. Without relying on a large-scale labeled training data or requiring any custom training, our model can efficiently generalize

关键词： Ontology

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Identifying and validating subtypes within major psychiatric disorders based on frontal-posterior functional imbalance via deep learning (October, 10.1038/s41380-020-00892-3, 2020)

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MOLECULAR PSYCHIATRY 2021年第7期26卷 3003-3003页

作者： Chang, Miao Womer, Fay Y. Gong, Xiaohong Chen, Xi Tang, Lili Feng, Ruiqi Dong, Shuai Duan, Jia Chen, Yifan Zhang, Ran Wang, Yang Ren, Sihua Wang, Yi Kang, Jujiao Yin, Zhiyang Wei, Yange Wei, Shengnan Jiang, Xiaowei Xu, Ke Cao, Bo Zhang, Yanbo Zhang, Weixiong Tang, Yanqing Zhang, Xizhe Wang, Fei Department of Radiology The First Affiliated Hospital of China Medical University Shenyang China Department of Psychiatry Washington University School of Medicine St. Louis MO USA State Key Laboratory of Genetic Engineering and Human Phenome Institute School of Life Sciences Fudan University Shanghai China School of Computer Science and Engineering Northeastern University Shenyang Liaoning China Department of Psychiatry The First Affiliated Hospital of China Medical University Shenyang China Shanghai Center for Mathematical Science Fudan University Shanghai China Department of Psychiatry University of Alberta Edmonton AB Canada Department of Psychiatry College of Medicine University of Saskatchewan Ellis Hall Royal University Hospital Saskatoon SK Canada Department of Computer Science and Engineering Washington University St. Louis MO USA Department of Genetics Washington University School of Medicine St. Louis MO USA School of Biomedical Engineering and Informatics Nanjing Medical University Nanjing Jiangsu China Nanjing Brain Hospital Nanjing Medical University Nanjing Jiangsu China

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

关键词： Neuroscience Prognostic markers Psychology Medicine/Public Health general Psychiatry Neurosciences Behavioral sciences Pharmacotherapy Biological Psychology

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Minimum information and guidelines for reporting a Multiplexed Assay of Variant Effect

arXiv

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arXiv 2023年

作者： Claussnitzer, Melina Parikh, Victoria N. Wagner, Alex H. Arbesfeld, Jeremy A. Bult, Carol J. Firth, Helen V. Muffley, Lara A. Ba, Alex N. Nguyen Riehle, Kevin Roth, Frederick P. Tabet, Daniel Bolognesi, Benedetta Glazer, Andrew M. Rubin, Alan F. The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease Broad Institute of MIT and Harvard CambridgeMA02142 United States Center for Genomic Medicine Massachusetts General Hospital Harvard Medical School CambridgeMA02142 United States Stanford Center for Inherited Cardiovascular Disease Stanford University School of Medicine StanfordCA94305 United States The Steve and Cindy Rasmussen Institute for Genomic Medicine Nationwide Children's Hospital ColumbusOH43215 United States Department of Pediatrics The Ohio State University College of Medicine ColumbusOH43210 United States Department of Biomedical Informatics The Ohio State University ColumbusOH43210 United States The Jackson Laboratory Bar HarborME04609 United States Wellcome Sanger Institute Hinxton Cambridge United Kingdom Dept of Medical Genetics Cambridge University Hospitals NHS Trust Cambridge United Kingdom Department of Genome Sciences University of Washington SeattleWA98105 United States Department of Biology University of Toronto at Mississauga MississaugaON Canada Department of Molecular and Human Genetics Baylor College of Medicine HoustonTX77030 United States Donnelly Centre University of Toronto TorontoON Canada Department of Molecular Genetics University of Toronto TorontoON Canada Department of Computer Science University of Toronto TorontoON Canada Lunenfeld-Tanenbaum Research Institute Sinai Health TorontoON Canada The Barcelona Institute of Science and Technology Barcelona Spain Vanderbilt University Medical Center NashvilleTN37232 United States Bioinformatics Division WEHI ParkvilleVIC Australia Department of Medical Biology University of Melbourne ParkvilleVIC Australia

Multiplexed Assays of Variant Effect (MAVEs) have emerged as a powerful approach for interrogating thousands of genetic variants in a single experiment. The flexibility and widespread adoption of these techniques across diverse disciplines has led to a heterogeneous mix of data formats and descriptions, which complicates the downstream use of the resulting datasets. To address these issues and promote reproducibility and reuse of MAVE data, we define a set of minimum information standards for MAVE data and metadata and outline a controlled vocabulary aligned with established biomedical ontologies for describing these experimental designs. © 2023, CC BY.

关键词： Genome

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Experiencing an Invisible World War i Battlefield Through Narrative-Driven Redirected Walking in Virtual Reality 25

Experiencing an Invisible World War i Battlefield Through Na...

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25th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2018

作者： Yu, Run Duer, Zachary Ogle, Todd Bowman, Doug A. Tucker, Thomas Hicks, David Choi, Dongsoo Bush, Zach Ngo, Huy Nguyen, Phat Liu, Xindi Virginia Tech Center for Human-Computer Interaction BlacksburgVA United States Department of Computer Science United States School of Visual Arts United States University Libraries United States School of Education United States

ISBN: (纸本)9781538633656

Redirected walking techniques have the potential to provide natural locomotion while users experience large virtual environments. However, when using redirected walking in small physical workspaces, disruptive overt resets are often required. We describe the design of an educational virtual reality experience in which users physically walk through virtual tunnels representative of the World War I battle of Vauquois. Walking in only a 15-by 5-foot tracked space, users are redirected through subtle, narrative-driven resets to walk through a tunnel nearly 50 feet in length. This work contributes approaches and lessons that can be used to provide a seamless and natural virtual reality walking experience in highly constrained physical spaces. © 2018 IEEE.

关键词： Virtual reality

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Ambient heat and human sleep

arXiv

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arXiv 2020年

作者： Minor, Kelton Bjerre-Nielsen, Andreas Jónasdóttir, Sigrídur Svala Lehmann, Sune Obradovich, Nick Copenhagen Center for Social Data Science University of Copenhagen Denmark Department of the Built Environment University of Aalborg Denmark Global Policy Laboratory University of California Berkeley United States Department of Economics University of Copenhagen Denmark Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Center for Humans and Machines Max Planck Institute for Human Development Germany

Ambient temperatures are rising globally, with the greatest increases recorded at night. Concurrently, the prevalence of insufficient sleep is increasing in many populations, with substantial costs to human health and well-being. Even though nearly a third of the human lifespan is spent asleep, it remains unknown whether temperature and weather impact objective measures of sleep in real-world settings, globally. Here we link billions of sleep measurements from wearable devices comprising over 7 million nighttime sleep records across 68 countries to local daily meteorological data from 2015 to 2017. Rising nighttime temperatures shorten within-person sleep duration primarily through delayed onset, increasing the probability of insufficient sleep. The effect of temperature on sleep loss is substantially larger for residents from lower income countries and older adults, and females are affected more than are males. Nighttime temperature increases inflict the greatest sleep loss during summer and fall months, and we do not find evidence of short-term acclimatization. Coupling historical behavioral measurements with output from climate models, we project that climate change will further erode human sleep, producing substantial geographic inequalities. Our findings have significant implications for adaptation planning and illuminate a pathway through which rising temperatures may globally impact public health. © 2020, CC-BY-NC-ND.

关键词： Sleep research

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