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EEG Source Localization of μ-Rhythm Event-Related Desynchronization during Tactile Imagery

Moscow University Biological sciences Bulletin 2024年第Suppl 1期79卷 S100-S106页

作者： Yakovlev, L. Syrov, N. Miroshnikov, A. Morozova, M. Berkmush-Antipova, A. Petrova, D. Kaplan, A. Laboratory for Neurophysiology and Neuro-Computer Interfaces Department of Human and Animal Physiology Faculty of Biology Lomonosov Moscow State University Moscow 119234 Russian Federation Vladimir Zelman Center for Neurobiology and Brain Rehabilitation Skolkovo Institute of Science and Technology Moscow 121205 Russian Federation Baltic Center for Neurotechnology and Artificial Intelligence Immanuel Kant Baltic Federal University Kaliningrad 236041 Russian Federation

Abstract: Tactile imagery remains a relatively understudied phenomenon of mental imagery research. However, this technique holds promise as an effective tool for sensorimotor rehabilitation following stroke and spinal cord injuries alongside motor imagery. In this study, conducted with 22 healthy volunteers, the authors investigated the source localization of μ-rhythm event-related desynchronization (ERD) using multichannel electroencephalogram recordings and subsequent inverse problem solution with the sLORETA. All participants exhibited ERD during tactile imagery task and under vibrotactile stimulation. It was demonstrated that μ-rhythm ERD during both vibrotactile stimulation and tactile imagery was localized in the sensorimotor areas of the contralateral hemisphere. Within the source space, ERD in the postcentral gyrus was significantly stronger compared to the precentral gyrus. These findings indicate that tactile imagery, akin to the perception of real tactile stimuli, leads to prominent activation of sensorimotor cortical areas, consistent with the general understanding of the shared neural substrate during mental imagery and perception. © Allerton Press, Inc. 2024. ISSN 0096-3925, Moscow University Biological sciences Bulletin, 2024, Vol. 79, Suppl. 1, pp. S100–S106. Allerton Press, Inc., 2024. Russian Text The Author(s), 2024, published in Vestnik Moskovskogo Universiteta, Seriya 16: Biologiya, 2024, Vol. 79, No. 2 (Suppl.), pp. 105–112.

关键词： event-related desynchronization inverse task sensorimotor rhythm source localization tactile imagery μ-rhythm

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6D Movable Antenna Enhanced Interference Mitigation for Cellular-Connected UAV Communications

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IEEE Wireless Communications Letters 2025年

作者： Ren, Tianshi Zhang, Xianchao Zhu, Lipeng Ma, Wenyan Gao, Xiaozheng Zhang, Rui The School of Information and Electronics Beijing Institute of Technology Beijing100081 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore The Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems China The Engineering Research Center of Intelligent Human Health Situation Awareness of Zhejiang Province Jiaxing University Jiaxing314001 China School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of HongKong Guangdong Shenzhen518172 China

Cellular-connected unmanned aerial vehicle (UAV) communications is an enabling technology to transmit control signaling or payload data for UAVs through cellular networks. Due to the line-of-sight dominant air-to-ground channels, efficient interference mitigation is crucial to UAV communications, while the conventional fixed-position antenna (FPA) arrays have limited degrees of freedom to suppress the interference between the UAV and its non-associated co-channel base stations (BSs). To address this challenge, we propose in this letter a new approach by utilizing the six-dimensional movable antenna (6DMA) arrays to enhance the interference mitigation for the UAV. Specifically, we propose an efficient block coordinate descent algorithm to iteratively optimize the antenna position vector, array rotation vector, receive beamforming vector, and associated BS of the UAV to maximize its signal-to-interference-plus-noise ratio. Numerical results show that the proposed 6DMA enhanced cellular-connected UAV communication can significantly outperform that with the traditional FPA arrays and other benchmark schemes in terms of interference mitigation. © 2025 IEEE. All rights reserved.

关键词： Aircraft communication

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DEMONSTRATING DATA-TO-KNOWLEDGE PIPELINES FOR CONNECTING PRODUCTION SITES IN THE WORLD WIDE LAB A PREPRINT

arXiv

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arXiv 2024年

作者： Gorisen, Leon Schneider, Jan-Niklas Behery, Mohamed Brauner, Philipp Lennartz, Moritz Kotter, David Kaster, Thomas Petrovic, Oliver Hinke, Christian Gries, Thomas Lakemeyer, Gerhard Ziefle, Martina Brecher, Christian Hafner, Constantin Chair for Laser Technology RWTH Aachen University Aachen52074 Germany Knowledge Based Systems Group RWTH Aachen University Aachen52074 Germany Communication Science RWTH Aachen University Aachen52074 Germany Chair of Textile Technology RWTH Aachen University Aachen52074 Germany Laboratory for Machine Tools and Production Engineering RWTH Aachen University Aachen52074 Germany Human Computer Interaction Center RWTH Aachen University Aachen52074 Germany Fraunhofer Institute for Laser Technology Aachen52074 Germany

The digital transformation of production requires new methods of data integration and storage, as well as decision making and support systems that work vertically and horizontally throughout the development, production, and use cycle. In this paper, we propose Data-to-Knowledge (and Knowledge-to-Data) pipelines for production as a universal concept building on a network of Digital Shadows (a concept augmenting Digital Twins). We show a proof of concept that builds on and bridges existing infrastructure to 1) capture and semantically annotates trajectory data from multiple similar but independent robots in different organisations and use cases in a data lakehouse and 2) an independent process that dynamically queries matching data for training an inverse dynamics foundation model for robotic control. The article discusses the challenges and benefits of this approach and how Data-to-Knowledge pipelines contribute efficiency gains and industrial scalability in a World Wide Lab as a research outlook. Copyright © 2024, The Authors. All rights reserved.

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Adapting to the Long Tail: A Meta-Analysis of Transfer Learning Research for Language Understanding Tasks

arXiv

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arXiv 2021年

作者： Naik, Aakanksha Lehman, Jill Rosé, Carolyn Language Technologies Institute Carnegie Mellon University United States Human-Computer Interaction Institute Carnegie Mellon University United States Rehabilitation Medicine Department Clinical Center National Institutes of Health United States

Natural language understanding (NLU) has made massive progress driven by large benchmarks, but benchmarks often leave a long tail of infrequent phenomena underrepresented. We reflect on the question: have transfer learning methods sufficiently addressed the poor performance of benchmark-trained models on the long tail? We conceptualize the long tail using macro-level dimensions (e.g., underrepresented genres, topics, etc.), and perform a qualitative meta-analysis of 100 representative papers on transfer learning research for NLU. Our analysis asks three questions: (i) Which long tail dimensions do transfer learning studies target? (ii) Which properties of adaptation methods help improve performance on the long tail? (iii) Which methodological gaps have greatest negative impact on long tail performance? Our answers highlight major avenues for future research in transfer learning for the long tail. Lastly, using our meta-analysis framework, we perform a case study comparing the performance of various adaptation methods on clinical narratives, which provides interesting insights that may enable us to make progress along these future avenues. © 2021, CC BY-NC-SA.

关键词： Benchmarking

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Fully implantable and battery-free wireless optoelectronic system for modulable cancer therapy and real-time monitoring

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npj Flexible Electronics 2023年第1期7卷 119-130页

作者： Kiho Kim In Sik Min Tae Hee Kim Do Hyeon Kim Seungwon Hwang Kyowon Kang Kyubeen Kim Sangun Park Jongmin Lee Young Uk Cho Jung Woo Lee Woon-Hong Yeo Young Min Song Youngmee Jung Ki Jun Yu Functional Bio-integrated Electronics and Energy Management Lab School of Electrical and Electronic EngineeringYonsei University50 Yonsei-roSeodaemun-guSeoul 03722Republic of Korea Center for Biomaterials Biomedical Research InstituteKorea Institute of Science and Technology(KIST)Seoul 02792Republic of Korea Department of Fusion Research and Collaboration Biomedical Research InstituteSeoul National University HospitalSeoul 03080Republic of Korea School of Electrical Engineering and Computer Science(EECS) Gwangju Institute of Science and Technology(GIST)Gwangju 61005Republic of Korea PA1 Foundry BusinessSamsung Electronics1 Samsungjeonja-roHwaseong-siGyeonggi-doRepublic of Korea R&D Center DNA Lab PharmaresearchSeongnam 13486Republic of Korea KU-KIST Graduate School of Converging Science and Technology Korea UniversitySeoul 136-705Republic of Korea School of Materials Science and Engineering Energy Materials for Soft Electronics LaboratoryPusan National UniversityBusan 46241Republic of Korea IEN Center for Human-Centric Interfaces and Engineering and George W.Woodruff School of Mechanical Engineering Georgia Institute of TechnologyAtlantaGA 30332USA Wallace H.Coulter Department of Biomedical Engineering Georgia Institute of Technology and Emory University School of MedicineAtlantaGA 30332USA Institute for Robotics and Intelligent Machines Parker H.Petit Institute for Bioengineering and BiosciencesInstitute for MaterialsNeural Engineering CenterGeorgia Institute of TechnologyAtlantaGA 30332USA School of Electrical and Electronic Engineering YU-Korea Institute of Science and Technology(KIST)InstituteYonsei University50Yonsei-roSeodaemun-guSeoul 03722Republic of Korea

Photodynamic therapy(PDT)is attracting attention as a next-generation cancer treatment that can selectively destroy malignant tissues,exhibit fewer side effects,and lack pain during *** PDT systems have recently been developed to resolve the issues of bulky and expensive conventional PDT systems and to implement continuous and repetitive *** implantable PDT systems,however,are not able to perform multiple functions simultaneously,such as modulating light intensity,measuring,and transmitting tumor-related data,resulting in the complexity of cancer ***,we introduce a flexible and fully implantable wireless optoelectronic system capable of continuous and effective cancer treatment by fusing PDT and hyperthermia and enabling tumor size monitoring in *** system exploits micro inorganic light-emitting diodes(μ-LED)that emit light with a wavelength of 624 nm,designed not to affect surrounding normal tissues by utilizing a fully programmable light intensity ofμ-LED and precisely monitoring the tumor size by Si phototransistor during a long-term implantation(2–3 weeks).The superiority of simultaneous cancer treatment and tumor size monitoring capabilities of our system operated by wireless power and data transmissions with a cell phone was confirmed through in vitro experiments,ray-tracing simulation results,and a tumor xenograft mouse model in *** all-in-one single system for cancer treatment offers opportunities to not only enable effective treatment of tumors located deep in the tissue but also enable precise and continuous monitoring of tumor size in real-time.

关键词： optoelectronic enable battery

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CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis

arXiv

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arXiv 2023年

作者： Zheng, Kaizhong Yu, Shujian Chen, Badong National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi’an China Department of Computer Science Vrije Universiteit Amsterdam Amsterdam Netherlands Machine Learning Group UiT - Arctic University of Norway Tromsø Norway

There is a recent trend to leverage the power of graph neural networks (GNNs) for brain-network based psychiatric diagnosis, which, in turn, also motivates an urgent need for psychiatrists to fully understand the decision behavior of the used GNNs. However, most of the existing GNN explainers are either post-hoc in which another interpretive model needs to be created to explain a well-trained GNN, or do not consider the causal relationship between the extracted explanation and the decision, such that the explanation itself contains spurious correlations and suffers from weak faithfulness. In this work, we propose a granger causality-inspired graph neural network (CI-GNN), a built-in interpretable model that is able to identify the most influential subgraph (i.e., functional connectivity within brain regions) that is causally related to the decision (e.g., major depressive disorder patients or healthy controls), without the training of an auxillary interpretive network. CI-GNN learns disentangled subgraph-level representations α and β that encode, respectively, the causal and non-causal aspects of original graph under a graph variational autoencoder framework, regularized by a conditional mutual information (CMI) constraint. We theoretically justify the validity of the CMI regulation in capturing the causal relationship. We also empirically evaluate the performance of CI-GNN against three baseline GNNs and four state-of-the-art GNN explainers on synthetic data and three large-scale brain disease datasets. We observe that CI-GNN achieves the best performance in a wide range of metrics and provides more reliable and concise explanations which have clinical evidence. The source code and implementation details of CI-GNN are freely available at GitHub repository (https://***/ZKZ-Brain/CI-GNN/). Copyright © 2023, The Authors. All rights reserved.

关键词： Diagnosis

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Bodily expressed emotion understanding through integrating Laban movement analysis

arXiv

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arXiv 2023年

作者： Wu, Chenyan Davaasuren, Dolzodmaa Shafir, Tal Tsachor, Rachelle Wang, James Z. Data Science and Artificial Intelligence Area College of Information Sciences and Technology The Pennsylvania State University University ParkPA16802 United States The Emili Sagol Creative Arts Therapies Research Center University of Haifa Haifa Israel School of Theatre and Music University of Illinois ChicagoIL60607 United States Human-Computer Interaction Area College of Information Sciences and Technology The Pennsylvania State University University ParkPA16802 United States

Body movements carry important information about a person’s emotions or mental state and are essential in daily communication. Enhancing the ability of machines to understand emotions expressed through body language can improve the communication of assistive robots with children and elderly users, provide psychiatric professionals with quantitative diagnostic and prognostic assistance, and aid law enforcement in identifying deception. This study develops a high-quality human motor element dataset based on the Laban Movement Analysis movement coding system and utilizes that to jointly learn about motor elements and emotions. Our long-term ambition is to integrate knowledge from computing, psychology, and performing arts to enable automated understanding and analysis of emotion and mental state through body language. This work serves as a launchpad for further research into recognizing emotions through analysis of human movement. Copyright © 2023, The Authors. All rights reserved.

关键词： computer vision

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Active learning: "Hands-on" meets "minds-on"

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science 2021年第6563期374卷 26-26页

作者： Wible, Brad Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh PA USA Department of Psychology Temple University Philadelphia PA USA Brookings Institution Washington DC USA School of Education University of Delaware Newark DE USA Department of Psychology and Center for Mind and Brain University of California Davis Davis CA USA Department of Psychology George Mason University Fairfax VA USA Graduate School of Education Stanford University Stanford CA USA Department of Physics Harvard University Cambridge MA USA Department of Chemistry and Chemical Biology Harvard University Cambridge MA USA Department of Physics University of California Merced Merced CA USA Department of Biology University of Washington Seattle WA USA Research for Inclusive STEM Education Center School of Life Sciences Arizona State University Tempe AZ USA.

Widespread disruptions to schooling spurred by COVID-19 have amplified long-standing discussions about what high-quality teaching and learning can be. Growing bodies of research and practice, from early childhood to university classrooms and beyond, demonstrate the benefits of moving beyond traditional lecture-driven approaches in favor of "active learning." Such approaches put students more in the driver's seat through discussions, in-class questions, and feedback;interactive technologies;and other strategies to engage learners and deepen understanding. Beyond cognitive and academic benefits, active-learning approaches can also provide socioemotional support, particularly for students who may not feel at home in or supported by traditional passive learning. But there is no single active-learning approach. Instead, as the experts below describe, we see a rich and developing portfolio of methods and ideas supporting different ways to produce more effective learning. © 2021 American Association for the Advancement of science. All rights reserved.

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Prioritizing Strategies for Building the Resilience of Public Health Systems to Disasters Across Multiple Communities and Countries

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International Journal of Disaster Risk science 2024年第1期15卷 1-17页

作者： Benjamin J.Ryan Mayumi Kako Shelby Garner Rok Fink Ismail Tayfur Jonathan Abrahams Sanjaya Bhatia Adriana Campelo Matthew Fendt Alicia Fontenot Nahuel Arenas Garcia Tim Hatch Ryoma Kayano LaShonda Malrey‑Horne Makiko MacDermot Md Moshiur Rahman Chaverle Noel Shuhei Nomura Jeremy P.Novak Maria Opazo Kendell Oliver Luciana Peters Sohel Rahman PerihanŞimşek Andrew Stricklin Raymond Swienton Bryan W.Brooks Frist College of Medicine Belmont UniversityNashvilleTN 37212USA Department of Environmental Science Environmental Health Science ProgramCollege of Arts and SciencesBaylor UniversityWacoTX 76798USA Division of Nursing Science School of Biomedical and Health SciencesHiroshima UniversityHiroshima 734-8553Japan Gordon E.Inman College of Health Sciences and Nursing Belmont UniversityNashvilleTN 37212USA Faculty of Health Sciences University of Ljubljana1000 LjubljanaSlovenia Department of Emergency Medicine University of Health Sciences34668 IstanbulTurkey Monash University Accident Research Center MelbourneVIC 3800Australia Global Education and Training Institute United Nations Ofce for Disaster Risk ReductionIncheon 22004Republic of Korea Regional Ofce for the Americas and Caribbean United Nations Ofce for Disaster Risk ReductionPanama City 0843-03441Panama Engineering and Computer Science Baylor UniversityWacoTX 76798USA Department of Public Health Robbins College of Health and Human SciencesBaylor UniversityWacoTX 76798USA Alabama Department of Public Health MontgomeryAL 36092USA World Health Organization Centre for Health Development(WHO Kobe Centre) Kobe 651-0073Japan Waco-McLennan County Public Health District WacoTX 76707USA Department of Health Policy and Management School of MedicineKeio UniversityTokyo 160-8582Japan Department of Global Health Policy Graduate School of MedicineThe University of TokyoTokyo 113-0033Japan Tokyo Foundation for Policy Research Tokyo 106-6234Japan Global Development College BrisbaneQLD 4000Australia Municipality of Pudahuel 13124 PudahuelChile City Hall of Porto Alegre Porto Alegre 90010-170Brazil Ministry of Health and Family Welfare Government of the People’s Republic of BangladeshDhaka 1000Bangladesh Department of Emergency Aid and Disaster Management Trabzon University61335 TrabzonTurkey Department of Emergency Medicine UT SouthwesternDallasTX 75390USA

The COVID-19 pandemic highlighted the urgent need to strengthen public health *** response,the United Nations Disaster Risk Reduction(UNDRR) Public Health System Resilience Scorecard(Scorecard) was applied in workshops across multiple *** aim of our research was to explore the workshop findings to develop priority strategies for strengthening public health system *** conducted a workshop from 14 to 16 March 2023,at the UNDRR Global Education and Training Institute in Incheon,Republic of Korea.A sequential modified Delphi method was utilized to develop a set of prioritized resilience *** were drawn from 70 strategies identified from 13 distinct workshops in eight *** two surveys,23 strategies were *** received ratings of "High" or Very High" from89% of *** related to the inclusion of public health risks in emergency plans,integrating multidisciplinary teams into public health,enabling local transport mechanisms,and improving the ability to manage an influx of *** Scorecard provides an adaptable framework to identify and prioritize strategies for strengthening public health system *** leveraging this methodology,our study demonstrated how resilience strategies could inform disaster risk reduction funding,policies,and actions.

关键词： Health system resilience Public policy Resilience scorecard Workshops

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Providing Security Assurance & Hardening for Open Source Software/Hardware: The SecOPERA approach

Providing Security Assurance & Hardening for Open Source Sof...

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IEEE International Workshop on computer-Aided Modeling, Analysis, and Design of Communication Links and Networks, CAMAD

作者： Apostolos P. Fournaris Christos Tselios Evangelos Haleplidis Elias Athanasopoulos Antreas Dionysiou Dimitrios Mitropoulos Panos Louridas Georgios Christou Manos Athanatos George Hatzivasilis Konstantinos Georgopoulos Costas Kalogeros Christos Kotselidis Simon Vogl Francois Hamon Sotiris Ioannidis Research Center ATHENA Industrial Systems Institute Patras Greece University of Cyprus Nicosia Cyprus Department of Management Science and Technology Athens University of Economics and Business Athens Greece Department of Business Administration University of Athens Greece School of Electrical and Computer Engineering Technical University of Crete Greece AEGIS IT RESEARCH LTD Germany Pierer Innovation Austria University of Manchester UK VoXel Interaction Design Linz Austria GreenCitizen Marseille France

Rapid open-source software and hardware prototyping fueled by the significant expansion of the development community, led to the deployment of highly sophisticated frameworks, solutions and products. However, as the provided open-source solutions are managed in all aspects by their designers/engineers, they lack professional evaluation of their security level. The absence of comprehensive security assessment as well as a consolidated and ubiquitous roadmap for vulnerability patching and security hardening, makes open-source solution a risk for widespread enterprise use. This paper introduces a security assurance approach which addresses open-source hardware and software shortcoming in an end-to-end manner, by providing a logical decomposition of any such module into four distinct component layers: device, network, application and cognitive. This allows highly focused security assessment, taking into consideration the specific characteristics of each layer. In addition, the paper provides an approach on how open-source solution security can be improved, through decomposition, layered vulnerability mitigation and specialized security hardening techniques. The proposed framework which is the main research and innovation focus of the SecOPERA Project intends to transform an open source solution to a protected one, as well as provide security guarantees of its overall security status.

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