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arXiv 2023年

作者： Zhang Zhou, Ruixiang Wu, Hanlin Oh, Ji Seop Li, Sheng Huang, Jianwei Denlinger, Jonathan D. Hashimoto, Makoto Lu, Donghui Mo, Sung-Kwan Kelly, Kevin F. McCandless, Gregory T. Chan, Julia Y. Birgeneau, Robert J. Lv, Bing Li, Gang Yi, Ming Department of Physics and Astronomy Rice University HoustonTX77005 United States School of Physical Science and Technology Shanghai Tech University Shanghai200031 China Department of Physics The University of Texas at Dallas RichardsonTX75080 United States Department of Physics University of California BerkeleyCA94720 United States Advanced Light Source Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Stanford Synchrotron Radiation Lightsource SLAC National Accelerator Laboratory Menlo ParkCA94025 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Department of Chemistry and Biochemistry Baylor University WacoTX76798 United States Materials Science Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

The interplay between charge order (CO) and nontrivial band topology has spurred tremendous interest in understanding topological excitations beyond the single-particle description. In a quasi-one-dimensional nonsymmorphic crystal TaTe4, the (2a×2b×3c) charge ordered ground state drives the system into a space group where the symmetry indicators feature the emergence of Dirac fermions and unconventional double Dirac fermions. Using angle-resolved photoemission spectroscopy and first-principles calculations, we provide evidence of the CO induced Dirac fermion-related bands near the Fermi level. Furthermore, the band folding at the Fermi level is compatible with the new periodicity dictated by the CO, indicating that the electrons near the Fermi level follow the crystalline symmetries needed to host double Dirac fermions in this system. © 2023, CC BY-NC-ND.

关键词： Ground state

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Correction: NaCMC-decorated ZnO nanocomposite polymer membranes for the separation of reactive dyes from textile water

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New Journal of Chemistry 2023年第3期48卷 1443-1443页

作者： R. Robin Vinoth Kumar Raja R. Sathish Kumar G. Arthanareeswaran Wirach Taweepreda Membrane Research Laboratory Department of Chemical Engineering National Institute of Technology Tiruchirappalli 620015 India Department of Chemical Engineering National Institute of Technology Andhra Pradesh Tadepalligudem Andhra Pradesh 534101 India Polymers & Composites Lab Department of Biomaterials Saveetha Dental College and Hospitals Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai 600077 India Polymer Science Program Division of Physical Science Faculty of Science Prince of Songkla University Hat-Yai Songkhla 90110 Thailand

Correction for ‘NaCMC-decorated ZnO nanocomposite polymer membranes for the separation of reactive dyes from textile water’ by R. Robin et al., New J. Chem., 2023, 47, 20517–20526, https://***/10.1039/D3NJ03783E.

Correction for ‘NaCMC-decorated ZnO nanocomposite polymer membranes for the separation of reactive dyes from textile water’ by R. Robin et al., New J. Chem., 2023, 47, 20517–20526, https://***/10.1039/D3NJ03783E.

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Localization transition in three-dimensional stealthy hyperuniform disordered systems

arXiv

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arXiv 2021年

作者： Sgrignuoli, F. Torquato, S. Dal Negro, L. Department of Electrical and Computer Engineering & Photonics Center Boston University 8 Saint Mary’s Street BostonMA02215 United States Department of Chemistry Department of Physics Princeton Institute for the Science and Technology of Materials Program in Applied and Computational Mathematics Princeton University PrincetonNJ08540 United States Division of Material Science and Engineering Boston University 15 Saint Mary’s Street BrooklineMA02446 United States Department of Physics Boston University 590 Commonwealth Avenue BostonMA02215 United States

The purpose of this work is to understand the fundamental connection between structural correlations and light localization in three-dimensional (3D) open scattering systems of finite size. We numerically investigate the transport of vector electromagnetic waves scattered by resonant electric dipoles spatially arranged in 3D space by stealthy hyperuniform disordered point patterns. Three-dimensional stealthy hyperuniform disordered systems (3D-SHDS) are engineered with different structural correlation properties determined by their degree of stealthiness χ. Such fine control of exotic states of amorphous matter enables the systematic design of optical media that interpolate in a tunable fashion between uncorrelated random structures and crystalline materials. By solving the electromagnetic multiple scattering problem using Green’s matrix spectral method, we establish a transport phase diagram that demonstrates a clear delocalization-localization transition beyond a critical scattering density that depends on χ. The transition is characterized by studying the Thouless number and the spectral statistics of the scattering resonances. In particular, by tuning the χ parameter, we demonstrate large spectral gaps and suppressed sub-radiant proximity resonances, facilitating light localization. Moreover, consistently with previous studies, our results show a region of the transport phase diagram where the investigated scattering systems become transparent. Our work provides a systematic description of the transport and localization properties of light in stealthy hyperuniform structures and motivates the engineering of novel photonic systems with enhanced light-matter interactions for applications to both classical and quantum devices. Copyright © 2021, The Authors. All rights reserved.

关键词： Phase diagrams

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Tracking and Failure Analysis of Explanted Neuromodulation Devices

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Neuromodulation : journal of the International Neuromodulation Society 2025年第4期28卷 700-702页

作者： Tess L Veuthey Deborah Duricka Dario J Englot David A Provenzano David M Dickerson Sanket Dhruva Christopher Miranda Loftus Nina Meizu-Nwaba David Prescott McMullen Richard B North Pierre D'Haese Peter E Konrad Lawrence Poree Department of Neurology and Neurological Sciences Stanford Medicine Stanford CA USA. Washington Wyoming Alaska Montana and Idaho School of Medical Education Anchorage AK USA. Departments of Neurological Surgery & Electrical Engineering Neurology Radiology & Radiological Sciences Computer Science and Biomedical Engineering Vanderbilt Health Nashville TN USA. Pain Diagnostics and Interventional Care Pittsburgh PA USA. Anesthesia Pain Management Services NorthShore University Health System Chicago IL USA. Department of Internal Medicine University for California San Francisco San Francisco CA USA. Office of Neurological and Physical Medicine Devices OHT5 OPEQ CDRH FDA Silver Springs MD USA. Department of Neurosurgery Anesthesiology and Critical Care Medicine (ret.) Johns Hopkins University School of Medicine Baltimore MD USA. Rockefeller Neuroscience Institute West Virginia University Morgantown WV USA. Dept of Neurosurgery West Virginia University Morgantown WV USA. Department of Anesthesia and Perioperative Care Division of Pain Medicine University of California San Francisco CA USA. Electronic address: Lawrence.Poree@UCSF.edu.

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Precise Measurement of the Cosmic-Ray Electron and Positron Spectrum with CALET on the International Space Station 37

Precise Measurement of the Cosmic-Ray Electron and Positron ...

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37th International Cosmic Ray Conference, ICRC 2021

作者： Torii, Shoji Akaike, Yosui Adriani, O. Akaike, Y. Asano, K. Asaoka, Y. Berti, E. Bigongiari, G. Binns, W.R. Bongi, M. Brogi, P. Bruno, A. Buckley, J.H. Cannady, N. Castellini, G. Checchia, C. Cherry, M.L. Collazuol, G. Ebisawa, K. Ficklin, A.W. Fuke, H. Gonzi, S. Guzik, T.G. Hams, T. Hibino, K. Ichimura, M. Ioka, K. Ishizaki, W. Israel, M.H. Kasahara, K. Kataoka, J. Kataoka, R. Katayose, Y. Kato, C. Kawanaka, N. Kawakubo, Y. Kobayashi, K. Kohri, K. Krawczynski, H.S. Krizmanic, J.F. Maestro, P. Marrocchesi, P.S. Messineo, A.M. Mitchell, J.W. Miyake, S. Moiseev, A.A. Mori, M. Mori, N. Motz, H.M. Munakata, K. Nakahira, S. Nishimura, J. de Nolfo, G.A. Okuno, S. Ormes, J.F. Ospina, N. Ozawa, S. Pacini, L. Papini, P. Rauch, B.F. Ricciarini, S.B. Sakai, K. Sakamoto, T. Sasaki, M. Shimizu, Y. Shiomi, A. Spillantini, P. Stolzi, F. Sugita, S. Sulaj, A. Takita, M. Tamura, T. Terasawa, T. Torii, S. Tsunesada, Y. Uchihori, Y. Vannuccini, E. Wefel, J.P. Yamaoka, K. Yanagita, S. Yoshida, A. Yoshida, K. Zober, W.V. Waseda Research Institute for Science and Engineering Waseda University 17 Kikuicho Shinjuku Tokyo Japan Department of Physics University of Florence Via Sansone 1 Sesto Fiorentino50019 Italy INFN Sezione di Florence Via Sansone 1 Sesto Fiorentino50019 Italy Waseda Research Institute for Science and Engineering Waseda University 17 Kikuicho Shinjuku Tokyo162-0044 Japan JEM Utilization Center Human Spaceflight Technology Directorate Japan Aerospace Exploration Agency 2-1-1 Sengen Ibaraki Tsukuba305-8505 Japan Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwa-no-Ha Chiba Kashiwa277-8582 Japan Department of Physical Sciences Earth and Environment University of Siena via Roma 56 Siena53100 Italy INFN Sezione di Pisa Polo Fibonacci Largo B. Pontecorvo 3 Pisa56127 Italy Department of Physics McDonnell Center for the Space Sciences Washington University One Brookings Drive St. LouisMO63130-4899 United States Heliospheric Physics Laboratory NASA/GSFC GreenbeltMD20771 United States Department of Physics Catholic University of America WashingtonDC20064 United States Center for Space Sciences and Technology University of Maryland Baltimore County 1000 Hilltop Circle BaltimoreMD21250 United States Astroparticle Physics Laboratory NASA/GSFC GreenbeltMD20771 United States Center for Research and Exploration in Space Sciences and Technology NASA/GSFC GreenbeltMD20771 United States Via Madonna del Piano 10 Sesto Fiorentino50019 Italy Department of Physics and Astronomy Louisiana State University 202 Nicholson Hall Baton RougeLA70803 United States Department of Physics and Astronomy University of Padova Via Marzolo 8 Padova35131 Italy INFN Sezione di Padova Via Marzolo 8 Padova35131 Italy Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo Kanagawa Sagamihara252-5210 Japan Kanagawa University 3-27-1 Rokkakubashi Kanagawa Kanagawa Yokohama221-

Primary objectives of the CALET (CALorimetric Electron Telescope) mission are to search for possible nearby cosmic-ray sources and dark matter signatures with the precise measurement of the electron and positron (all-electron) spectrum. The instrument, consisting of a charge detector, an imaging calorimeter and a total absorption calorimeter, is optimized to measure the all-electron spectrum well into the TeV region with a thick calorimeter of 30 radiation length with fine shower-imaging capability. Due to the excellent energy resolution (a few % above 10 GeV) and the outstanding e/p separation (∼ 105), CALET achieves optimal performance for a detailed search for structures in the energy spectrum. CALET has been accumulating scientific data for more than five years without any major interruption, and the statistics of observed electron events has increased more than double since the latest publication in 2018. In this paper we will present precise measurements of the all-electron spectrum up to several TeV, as obtained with the high statistics data, and we will briefly discuss about its interpretation. © Copyright owned by the author(s).

关键词： Electrons

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Magnetotransport in graphene/Pb0.24Sn0.76Te heterostructures: Finding a way to avoid catastrophe

arXiv

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arXiv 2022年

作者： Stephen, Gregory M. Naumov, Ivan Blumenschein, Nicholas A. Leo Sun, Y.-J. DeMell, Jennifer E. Shirodkar, Sharmila N. Dev, Pratibha Taylor, Patrick J. Robinson, Jeremy T. Campbell, Paul M. Hanbicki, Aubrey T. Friedman, Adam L. Laboratory for Physical Sciences 8050 Greenmead Dr. College ParkMD20740 United States Howard University Department of Physics and Astronomy WashingtonDC20059 United States University of Maryland Department of Electrical and Computer Engineering College ParkMD20742 United States US Army Research Laboratory 2800 Powder Mill Rd. AdelphiMD20783 United States US Naval Research Laboratory Electronics Science and Technology Division 4555 Overlook Ave. S.W. WashingtonDC20375 United States

While heterostructures are ubiquitous tools enabling new physics and device functionalities, the palette of available materials has never been richer. Combinations of two emerging material classes, two-dimensional materials and topological materials, are particularly promising because of the wide range of possible permutations that are easily accessible. Individually, both graphene and Pb0.24Sn0.76Te (PST) are widely investigated for spintronic applications because graphene's high carrier mobility and PST's topologically protected surface states are attractive platforms for spin transport. Here, we combine monolayer graphene with PST and demonstrate a hybrid system with properties enhanced relative to the constituent parts. Using magnetotransport measurements, we find carrier mobilities up to 20, 000 cm2/Vs and a magnetoresistance approaching 100%, greater than either material prior to stacking. We also establish that there are two distinct transport channels and determine a lower bound on the spin relaxation time of 4.5 ps. The results can be explained using the polar catastrophe model, whereby a high mobility interface state results from a reconfiguration of charge due to a polar/non-polar interface interaction. Our results suggest that proximity induced interface states with hybrid properties can be added to the still growing list of behaviors in these materials. Copyright © 2022, The Authors. All rights reserved.

关键词： Graphene

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Blueshift: Rebalancing engineering engagement, integrity, and learning outcomes across an electronically-enabled remediation hierarchy

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Computers in Education Journal 2019年第1期10卷 1-12页

作者： DeMara, Ronald F. Sheikhfaal, Shadi Wilder, Paul J. Chen, Baiyun Hartshorne, Richard Department of Electrical Engineering and Computer Science University of Central Florida OrlandoFL32816 United States Department of Engineering Computer Program and Technology Valencia College OrlandoFL32811 United States Center for Distributed Learning University of Central Florida OrlandoFL32816 United States Division Dean for Learning Sciences Educational Research University of Central Florida OrlandoFL32816 United States

With a growing number of enrollments in engineering programs, more time and energy for tutoring and grading exams/quizzes is necessary. The BLUESHIFT framework utilizes a synergistic combination of faculty, Graduate Teaching Assistants, and educational technologies to provide reliable approaches to not only meet the increased time, cost, and energy efficiency needed for increasing numbers of engineering students, but also to focus on improving the quality of education, skills, and employability of our graduates in computing-related fields. An Evaluation and Proficiency Center (EPC) has been piloted at a large state university, where key elements of the BLUESHIFT learning flow have been integrated into selected undergraduate engineering courses. The EPC integrates computer-based evaluation with a close-knit review and learning cycle based on directed and open tutoring. This approach has received overwhelmingly positive responses from students regarding the effectiveness of pedagogical approaches (i.e., Exemplar Vignettes, content tutoring), assessment models (i.e., electronically delivered quizzes, flexible scheduling, use of testing center), and tutoring strategies (i.e., self-paced, exam results review). Survey results have been positive with respect to student perceptions across a variety of perspectives compared to paper-based delivery. In this manuscript, the BLUESHIFT framework and process, as well as results collected from student performance and perceptions of the initial implementation, will be addressed. © 2019 American Society for engineering Education. All rights reserved.

关键词： Students

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Quantum materials for energy-efficient neuromorphic computing: Opportunities and challenges

arXiv

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arXiv 2022年

作者： Hoffmann, Axel Ramanathan, Shriram Grollier, Julie Kent, Andrew D. Rozenberg, Marcelo Schuller, Ivan K. Shpyrko, Oleg Dynes, Robert Fainman, Yeshaiahu Frano, Alex Fullerton, Eric E. Galli, Giulia Lomakin, Vitaliy Ong, Shyue Ping Petford-Long, Amanda K. Schuller, Jonathan A. Stiles, Mark D. Takamura, Yayoi Zhu, Yimei Materials Research Laboratory Department of Materials Science and Engineering University of Illinois Urbana-Champaign UrbanaIL61801 United States School of Materials Engineering Purdue University West LafayetteIN47907 United States Unité Mixte de Physique CNRS/Thales Université Paris-Saclay Palaiseau91767 France Center for Quantum Phenomena Department of Physics New York University New York10003 United States Université Paris-Saclay CNRS Laboratoire de Physique des Solides Orsay91405 France Department of Physics University of California–San Diego La Jolla CA92093 United States Center for Advanced Nanoscience University of California–San Diego La Jolla CA92093 United States Department of Electrical and Computer Engineering University of California–San Diego La Jolla CA92093 United States Center for Memory and Recording Research University of California–San Diego La Jolla CA92093 United States Pritzker School of Molecular Engineering Department of Chemistry The University of Chicago ChicagoIL60637 United States Materials Science Division Argonne National Laboratory LemontIL60439 United States Department of NanoEngineering University of California–San Diego La Jolla CA92093 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Electrical and Computer Engineering University of California Santa Barbara Santa BarbaraCA93106 United States Physical Measurement Laboratory National Institute of Standards and Technology GaithersburgMD20899-6202 United States Department of Materials Science and Engineering University of California Davis DavisCA95616 United States Department of Consdensed Matter Physics and Materials Science Brookhaven National Laboratory UptonNY11973 United States

Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new energy-efficient device concepts that implement neuromorphic ideas at the hardware level. In particular, strong correlations give rise to highly non-linear responses, such as conductive phase transitions that can be harnessed for short and long-term plasticity. Similarly, magnetization dynamics are strongly non-linear and can be utilized for data classification. This paper discusses select examples of these approaches, and provides a perspective for the current opportunities and challenges for assembling quantum-material-based devices for neuromorphic functionalities into larger emergent complex network systems. Copyright © 2022, The Authors. All rights reserved.

关键词： Energy efficiency

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Artificial intelligence for modelling infectious disease epidemics

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Nature 2025年第8051期638卷 623-635页

作者： Kraemer, Moritz U. G. Tsui, Joseph L.-H. Chang, Serina Y. Lytras, Spyros Khurana, Mark P. Vanderslott, Samantha Bajaj, Sumali Scheidwasser, Neil Curran-Sebastian, Jacob Liam Semenova, Elizaveta Zhang, Mengyan Unwin, H. Juliette T. Watson, Oliver J. Mills, Cathal Dasgupta, Abhishek Ferretti, Luca Scarpino, Samuel V. Koua, Etien Morgan, Oliver Tegally, Houriiyah Paquet, Ulrich Moutsianas, Loukas Fraser, Christophe Ferguson, Neil M. Topol, Eric J. Duchêne, David A. Stadler, Tanja Kingori, Patricia Parker, Michael J. Dominici, Francesca Shadbolt, Nigel Suchard, Marc A. Ratmann, Oliver Flaxman, Seth Holmes, Edward C. Gomez-Rodriguez, Manuel Schölkopf, Bernhard Donnelly, Christl A. Pybus, Oliver G. Cauchemez, Simon Bhatt, Samir Pandemic Sciences Institute University of Oxford Oxford United Kingdom Department of Biology University of Oxford Oxford United Kingdom Department of Electrical Engineering and Computer Science University of California Berkeley Berkeley CA United States UCSF UC Berkeley Joint Program in Computational Precision Health Berkeley CA United States Division of Systems Virology Department of Microbiology and Immunology The Institute of Medical Science The University of Tokyo Tokyo Japan Section of Epidemiology Department of Public Health University of Copenhagen Copenhagen Denmark Oxford Vaccine Group University of Oxford and NIHR Oxford Biomedical Research Centre Oxford United Kingdom Department of Epidemiology and Biostatistics Imperial College London London United Kingdom Department of Computer Science University of Oxford Oxford United Kingdom School of Mathematics University of Bristol Bristol United Kingdom MRC Centre for Global Infectious Disease Analysis School of Public Health Imperial College London London United Kingdom Department of Statistics University of Oxford Oxford United Kingdom Doctoral Training Centre University of Oxford Oxford United Kingdom Institute for Experiential AI Northeastern University MA Boston Thailand Santa Fe Institute Santa Fe NM United States World Health Organization Regional Office for Africa Brazzaville Congo WHO Hub for Pandemic and Epidemic Intelligence Health Emergencies Programme World Health Organization Berlin Germany Centre for Epidemic Response and Innovation (CERI) School for Data Science and Computational Thinking Stellenbosch University Stellenbosch South Africa African Institute for Mathematical Sciences (AIMS) South Africa Muizenberg Cape Town South Africa Genomics England London United Kingdom Scripps Research La Jolla CA United States Department of Biosystems Science and Engineering ETH Zürich Basel Switzerland Swiss Institute of Bioinformatics Lausanne Switzerland The Ethox Centre Nuffield

Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social science, have the potential to transform the scope and power of infectious disease epidemiology. Here we consider the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science. We first outline how recent advances in AI can accelerate breakthroughs in answering key epidemiological questions and we discuss specific AI methods that can be applied to routinely collected infectious disease surveillance data. Second, we elaborate on the social context of AI for infectious disease epidemiology, including issues such as explainability, safety, accountability and ethics. Finally, we summarize some limitations of AI applications in this field and provide recommendations for how infectious disease epidemiology can harness most effectively current and future developments in AI. © Springer Nature Limited 2025.

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Time synchronization between parietal–frontocentral connectivity with MRCP and gait in post-stroke bipedal tasks

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Journal of Neuroengineering and Rehabilitation 2024年第1期21卷 101页

作者： Phang, Chun-Ren Su, Kai-Hsiang Cheng, Yuan-Yang Chen, Chia-Hsin Ko, Li-Wei International Ph.D. Program in Interdisciplinary Neuroscience (UST) College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B) College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biological Science and Technology College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Physical Medicine and Rehabilitation Taichung Veterans General Hospital Taichung Taiwan Department of Post-Baccalaureate Medicine College of Medicine National Chung Hsing University Taichung Taiwan School of Medicine National Yang Ming Chiao Tung University Taipei Taiwan Department of Physical Medicine and Rehabilitation Kaohsiung Medical University Hospital Kaohsiung Taiwan School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Regenerative Medicine and Cell Therapy Research Center Kaohsiung Medical University Kaohsiung Taiwan Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Science and Environment Biology Kaohsiung Medical University Kaohsiung Taiwan Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung Taiwan

Background: In post-stroke rehabilitation, functional connectivity (FC), motor-related cortical potential (MRCP), and gait activities are common measures related to recovery outcomes. However, the interrelationship between FC, MRCP, gait activities, and bipedal distinguishability have yet to be investigated. Methods: Ten participants were equipped with EEG devices and inertial measurement units (IMUs) while performing lower limb motor preparation (MP) and motor execution (ME) tasks. MRCP, FCs, and bipedal distinguishability were extracted from the EEG signals, while the change in knee degree during the ME phase was calculated from the gait data. FCs were analyzed with pairwise Pearson’s correlation, and the brain-wide FC was fed into support vector machine (SVM) for bipedal classification. Results: Parietal–frontocentral connectivity (PFCC) dysconnection and MRCP desynchronization were related to the MP and ME phases, respectively. Hemiplegic limb movement exhibited higher PFCC strength than nonhemiplegic limb movement. Bipedal classification had a short-lived peak of 75.1% in the pre-movement phase. These results contribute to a better understanding of the neurophysiological functions during motor tasks, with respect to localized MRCP and nonlocalized FC activities. The difference in PFCCs between both limbs could be a marker to understand the motor function of the brain of post-stroke patients. Conclusions: In this study, we discovered that PFCCs are temporally dependent on lower limb gait movement and MRCP. The PFCCs are also related to the lower limb motor performance of post-stroke patients. The detection of motor intentions allows the development of bipedal brain-controlled exoskeletons for lower limb active rehabilitation. © The Author(s) 2024.

关键词： Brain–computer interface Functional connectivity Motor execution Motor preparation Post-stroke

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