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Real-time Lightning 3D Imaging and Forecasting Project in Malaysia for Sustainable and Reliable Supply of Energy and Storm Disaster Early Warning 12

Real-time Lightning 3D Imaging and Forecasting Project in Ma...

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12th Asia-Pacific International Conference on Lightning, APL 2023

作者： Morimoto, Takeshi Ahmad, Mohd Riduan Baharuddin, Mohd Zafri Wang, Daohong Yamamoto, Kazuo Kudo, Takeshi Kahtani, Ammar Nasser Al Aziz, Mohamad Zoinol Abidin Abd Akita, Manabu Takayanagi, Yuji Kawasaki, Zen-Ichiro Torii, Tatsuo Kindai University Depertment of Electrical Electronic and Communication Engineering Osaka Japan Melaka Malaysia Universiti Tenaga Nasional Department of Electrical and Electronic Engineering Kajang Malaysia Gifu University Department of Electrical Electronic and Computer Engineering Gifu Japan Chubu University Deptment. of Electrical and Electronic Engineering Aichi Japan Fundamental and Advanced Research Group Otowa Electric Co. Ltd Hyogo Japan Universiti Tenaga Nasional Department of Electrical and Electronics Engineering Kajang Malaysia The University of Electro-Communications Department of Mechanical and Intelligent Systems Engineering Tokyo Japan Osaka University Osaka Japan Research Institute of Nuclear Engineering University of Fukui Fukui Japan

ISBN: (纸本)9781665456852

A joint research project 'real-time lightning 3D imaging and forecasting project for sustainable and reliable supply of energy and storm disaster early warning' has been selected for Science and Technology Research Partnership for Sustainable Development (SATREPS) program. Held in the coastal area of the Straits of Malacca in Malaysia, which suffers from serious lightning disasters with more than 200 lightning days per year, this research aims to contribute to disaster prevention by forecasting lightning strikes by constructing the world's highest lightning observation network. This research project is to conduct the field campaigns associated with artificial rocket-triggered lightning in the coastal area of the Straits of Malacca, where the thunderstorm activity is very high and there are many positive cloud-to-ground flashes that may damage electric, communication and other equipments. Measurements of radio waves in various frequency bands and high-energy radiations, and several Rogowski coils are set up surrounding the strike points. It is planned to realize an electromagnetic field observation network in VHF and LF bands to observe the entire progression of each lightning in detail in a wide area. 3D charge distribution in the thundercloud and the amounts of neutralized charges estimated from the information where the lightning discharge begins, how it progresses, and where it terminates. Then, it is examined by the lightning current waveform measured directly with the high structure and rocket-triggered lightning. By comprehensively grasping the charge behavior in the air related to lightning discharge, it is possible to estimate the charge distribution in the cloud and to predict lightning strike. In addition, promoting the control of electric power equipment using IoT, and the early warning system of severe weather disasters to be implemented in the society. This project further researches on active and adaptive lightning resistance and protection as well as

关键词： Imaging systems

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Mid-infrared Photons Released by NAD^(+)Reduction in the Tricarboxylic Acid Cycle of Myelinated Neuron

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Neuroscience Bulletin 2023年第7期39卷 1146-1150页

作者： Daoling Peng Wenpeng Qi Feng Zhang Bo Song Key Laboratory of Theoretical Chemistry of Environment Ministry of EducationSchool of EnvironmentSouth China Normal UniversityGuangzhou 510006China Shanghai Institute of Applied Physics Chinese Academy of SciencesShanghai 201800China Key Laboratory of Optical Technology and Instruments for Medicine Ministry of EducationShanghai Key Lab of Modern Optical SystemsSchool of Optical-Electrical Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China

Dear Editor,Life can utilize energy with high efficiency,especially with the help of aerobic respiration,where the tricarboxylic acid(TCA)cycle acts as an important metabolic engine for mitochondria to produce the cell energy currency of adenosine triphosphate(ATP),and nicotinamide adenine dinucleotide(NAD)plays a particular role of energy management molecule in the TCA cycle[1].

关键词： carboxylic utilize cycle

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NeuroSparse: An Unsupervised Framework for Inferring Brain Connectivity in Autism Diagnosis

NeuroSparse: An Unsupervised Framework for Inferring Brain C...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Yang, Shuqi Zhang, Lijuan Lan, Qing Ma, Qiujie Huang, Huan Miao, Jiaqing Mou, Shiyu Luo, Cheng Yao, Dezhong Tan, Ying Southwest Minzu University Key Laboratory for Computer Systems of State Ethnic Affairs Commission Chengdu China Moe Key Lab for Neuroinformation University of Electronic Science and Technology of China Clinical Hospital Chengdu Brain Science Institute Chengdu China University of Malaya Faculty of Engineering Department of Biomedical Engineering Kuala Lumpur Malaysia

ISBN: (纸本)9798350386226

Autism spectrum disorder (ASD) is a mental disorder that severely affects social interaction and communication skills. A timely and accurate diagnosis is crucial for effective intervention. However, as an objective diagnostic tool, the existence of spurious connections and noise within the functional connectivity (FC) matrix in the brain contribute to the complexity of ASD diagnosis. In this study, we propose an unsupervised sparse graph structure learning framework, called NeuroSparse, for reasoning regarding the topological connectivity relationships between brain regions. First, the framework fuses spatiotemporal information from static and dynamic FC to provide a comprehensive representation of complex brain networks. Next, the context and neighborhood information of nodes are captured as their local and global embeddings, and the latent representations of node embeddings are learned, which are then decoded to infer the connectivity relationships among the regions of interest. Finally, we introduce three innovative loss functions to regularize and optimize the sparse representation generation process. The experimental results showed that, after learning using NeuroSparse, the FC matrix achieved state-of-the-art performance in ASD diagnosis using only a simple multilayer perceptron, indicating its wide-ranging application potential. The code is available at https://***/yangshuqigit/NeuroSparse. © 2024 IEEE.

关键词： Unsupervised learning

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Live Demonstration: A fully embedded adaptive real-time hand gesture classifier leveraging HD-sEMG and deep learning

Live Demonstration: A fully embedded adaptive real-time hand...

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IEEE Biomedical Circuits and systems (BIOCAS)

作者： Xavier Isabel Thomas Labbé Félix Chamberland Étienne Buteau Evan Campbell Ulysse Côté-Allard Simon Tam Paul Fortier Alexandre Campeau-Lecours Mounir Boukadoum Erik Scheme Benoit Gosselin Electrical Engineering and Computer Engineering Department Laval University Institute of Biomedical Engineering University of New-Brunswick Department off Technology Systems University of Oslo Mechanical Engineering Department Laval University Computer Science Department University of Quebec at Montreal

In a fully immersive virtual reality setting, visitors will actively participate in our demonstration, engaging in an interactive videogame utilizing our cutting-edge HD-sEMG Bracelet. Prior to this, they will undergo state-of-the-art training to personalize their machine learning gesture recognition model. The gameplay will be broadcast on a computer monitor, allowing onlookers to observe while the demonstrator explains the core concept of our work. By wearing the bracelet, the player gains control over their limb in a game inspired by Simon Says. Throughout the demonstration, visitors will gain firsthand experience and knowledge about the forthcoming advantages of HD-sEMG for control applications, such as prosthesis control. They will also discover how the EMaGer HD-sEMG Bracelet capitalizes on its uniform and high electrode density to enhance the reliability of hand gesture recognition models utilized in myoelectric prosthesis control.

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Generalized Haldane map from the matrix product state path integral to the critical theory of the J1−J2 chain

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Physical Review Research 2025年第1期7卷 L012037-L012037页

作者： F. Azad Adam J. McRoberts Chris Hooley A. G. Green Electrical Engineering and Computer Science Department Technische Universität Berlin 10587 Berlin Germany London Centre for Nanotechnology University College London Gordon Street London WC1H 0AH United Kingdom International Centre for Theoretical Physics Strada Costiera 11 34151 Trieste Italy Max Planck Institute for the Physics of Complex Systems Nöthnitzer Straße 38 01187 Dresden Germany

We study the J1−J2 spin-1/2 chain using a path integral constructed over matrix product states (MPS). By virtue of its nontrivial entanglement structure, the MPS ansatz captures the key phases of the model even at a semiclassical, saddle-point level, and, as a variational state, is in good agreement with the field theory obtained by Abelian bosonization. Going beyond the semiclassical level, we show that the MPS ansatz facilitates a physically motivated derivation of the field theory of the critical phase: By carefully taking the continuum limit—a generalization of the Haldane map—we recover from the MPS path integral a field theory with the correct topological term and emergent SO(4) symmetry, constructively linking the microscopic states and topological field-theoretic structures. Moreover, the dimerization transition is particularly clear in the MPS formulation—an explicit dimerization potential becomes relevant, gapping out the magnetic fluctuations.

关键词： Topology

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AUGFL: Augmenting Federated Learning with Pretrained Models

arXiv

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arXiv 2025年

作者： Yue, Sheng Qin, Zerui Deng, Yongheng Ren, Ju Zhang, Yaoxue Zhang, Junshan School of Cyber Science and Technology Sun Yatsen University China Department of Computer Science and Technology Tsinghua University China Zhong-guancun Laboratory China Department of Electrical and Computer Engineering University of California Davis United States

Federated Learning (FL) has garnered widespread interest in recent years. However, owing to strict privacy policies or limited storage capacities of training participants such as IoT devices, its effective deployment is often impeded by the scarcity of training data in practical decentralized learning environments. In this paper, we study enhancing FL with the aid of (large) pretrained models (PMs), that encapsulate wealthy general/domain-agnostic knowledge, to alleviate the data requirement in conducting FL from scratch. Specifically, we consider a networked FL system formed by a central server and distributed clients. First, we formulate the PM-aided personalized FL as a regularization-based federated meta-learning problem, where clients join forces to learn a meta-model with knowledge transferred from a private PM stored at the server. Then, we develop an inexact-ADMM-based algorithm, AUGFL, to optimize the problem with no need to expose the PM or incur additional computational costs to local clients. Further, we establish theoretical guarantees for AUGFL in terms of communication complexity, adaptation performance, and the benefit of knowledge transfer in general non-convex cases. Extensive experiments corroborate the efficacy and superiority of AUGFL over existing baselines. Copyright © 2025, The Authors. All rights reserved.

关键词： Federated learning

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Optimizing Bidding Curves for Renewable Energy in Two-Settlement Electricity Markets

arXiv

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arXiv 2025年

作者： Zhao, Dongwei Delikaraoglou, Stefanos Dvorkin, Vladimir Lamadrid, Alberto J.L. Botterud, Audun Argonne National Laboratory LemontIL United States Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA United States Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI United States Department of Economics Department of Industrial and Systems Engineering Lehigh University BethlehemPA United States

Coordination of day-ahead and real-time electricity markets is imperative for cost-effective electricity supply and also to provide efficient incentives for the energy transition. Although stochastic market designs feature the least-cost coordination, they are incompatible with current deterministic markets. This paper proposes a new approach for compatible coordination in two-settlement markets based on benchmark bidding curves for variable renewable energy. These curves are optimized based on a bilevel optimization problem, anticipating per-scenario responses of deterministic market-clearing problems and ultimately minimizing the expected cost across day-ahead and real-time markets. Although the general bilevel model is challenging to solve, we theoretically prove that a single-segment bidding curve with a zero bidding price is sufficient to achieve system optimality if the marginal cost of variable renewable energy is zero, thus addressing the computational challenge. In practice, variable renewable energy producers can be allowed to bid multi-segment curves with non-zero prices. We test the bilevel framework for both single- and multiple-segment bidding curves under the assumption of fixed bidding prices. We leverage duality theory and McCormick envelopes to derive the linear programming approximation of the bilevel problem, which scales to practical systems such as a 1576-bus NYISO system. We benchmark the proposed coordination and find absolute dominance over the baseline solution, which assumes that renewables agnostically bid their expected forecasts. We also demonstrate that our proposed scheme provides a good approximation of the least-cost, yet unattainable in practice, stochastic market outcome. © 2025, CC BY.

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A Novel Ku-Band Reflectarray Antenna Design Enabled by Stereolithography

A Novel Ku-Band Reflectarray Antenna Design Enabled by Stere...

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European Conference on Antennas and Propagation, EuCAP

作者： Irsat Gulen Evangelos Vassos Panagiotis Ioannis Theoharis Thomas Whittake Will Whittow Alexandros Feresidis Department of Electrical Electronic and Systems Engineering University of Birmingham Birmingham UK Department of Engineering and Technology University of Huddersfield Huddersfield UK School of Electrical Computer and Telecommunication Engineering University of Wollongong Wollongong WSW Australia Wolfson School of Mechanical Electrical and Manufacturing Engineering Loughborough University Loughborough UK

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

A novel reflectarray antenna design enabled by stereolithography operating at Ku-band is presented. The demon-strated fully metallised 3-D unit cells feature multiple-layer cuboid elements attached to a ground plane through metallic vias. By varying the number of layers, the sizes of the elements of each layer, and the diameter of the vias, the required phase response is achieved, along with low reflection losses. Another benefit of the variable layer design is the engineered phase response over the frequency range of 14 to 17 GHz, which can lead to broad bandwidth reflectarray designs. At 15 GHz, simulations in CST Microwave Studio demonstrate that the reflectarray antenna achieves a directivity of approximately 33 dBi.

关键词： Microwave antennas Design methodology Bandwidth Reflector antennas Three-dimensional printing Microwave theory and techniques Ku-band Reflection Stereolithography Resins

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Towards AI-driven Next Generation Personalized Healthcare and Well-being

Towards AI-driven Next Generation Personalized Healthcare an...

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2024 Ital-IA Intelligenza Artificiale - Thematic Workshops, Ital-IA 2024

作者： Aksu, Fatih Bria, Alessandro Caragliano, Alice Natalina Caruso, Camillo Maria Chen, Wenting Cordelli, Ermanno Coser, Omar Francesconi, Arianna Furia, Leonardo Guarrasi, Valerio Iannello, Giulio Lauretti, Clemente Manni, Guido Marino, Giustino Paolo, Domenico Ruffini, Filippo Shen, Linlin Sicilia, Rosa Soda, Paolo Tamantini, Christian Tortora, Matteo Wu, Zhuoru Zollo, Loredana Department of Biomedical Sciences Humanitas University Milan Italy Department of Electrical and Information Engineering University of Cassino and Southern Latium Cassino Italy Unit of Computer Systems and Bioinformatics Department of Engineering University Campus Bio-Medico of Rome Italy City University of Hong Kong Hong Kong Unit of Advanced Robotics and Human-Centered Technologies Department of Engineering University Campus Bio-Medico of Rome Italy Shenzhen University China Department of Diagnostics and Intervention Radiation Physics Biomedical Engineering Umeå University Sweden

In the last few years Artificial Intelligence (AI) is emerging as a game changer in many areas of society and, in particular, its integration in medicine heralds a transformative approach towards personalized healthcare and well-being, promising significant improvements in diagnostic precision, therapeutic outcomes, and patient care. Our research explores the cutting-edge realms of multimodal AI, resilient AI, and healthcare robotics, aiming to harness the synergy of diverse data modalities and advanced computational models to redefine healthcare paradigms. This multidisciplinary effort seeks to bridge technology and clinical practice, advancing AI-driven next generation personalized healthcare and well-being. © 2024 Copyright for this paper by its authors.

关键词： Personalized medicine

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Control of Magnetic Skyrmions in an Exchange Biased van der Waals Ferromagnet

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Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2023年第1期29卷 1710-1711页

作者： McCray, Arthur R C Lebedev, Dmitry Arpaci, Sevdenur Te Velthuis, Suzanne G E Lopez-Dominguez, Victor Amiri, Pedram Khalili Hersam, Mark C. Petford-Long, Amanda K. Phatak, Charudatta Materials Science Division Argonne National Laboratory Lemont IL United States Applied Physics Program Northwestern University Evanston IL United States Department of Materials Science and Engineering Northwestern University Evanston IL United States Department of Electrical and Computer Engineering Northwestern University Evanston IL United States

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