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Natural Human Skin‑Inspired Wearable and Breathable Nanofiber‑based Sensors with Excellent Thermal Management Functionality

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Advanced Fiber Materials 2024年第6期6卷 1955-1968页

作者： Peng Wang Xiaodan Li Guifen Sun Guoqing Wang Qing Han Chuizhou Meng Zhonghe Wei Yang Li School of Mechanical Engineering University of JinanJinan 250022China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Engineering Research Center of Ministry of Education for Intelligent Rehabilitation Device and Detection TechnologyHebei Key Laboratory of Smart Sensing and Human‑Robot InteractionSchool of Mechanical EngineeringHebei University of TechnologyTianjin 300401China Shandong Provincial Key Laboratory of Network‑Based Intelligent Computing School of Information Science and EngineeringUniversity of JinanJinan 250022China Network Information Center Department of Computer ScienceQilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Integrated Circuits Shandong UniversityJinan 250101China

Wearable sensors have been rapidly developed for application in various human monitoring ***,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics urgently need to be ***,we develop a wearable and breathable nanofiber-based sensor with excellent thermal management functionality based on passive heat preservation and active Joule heating *** multifunctional device consists of a micropatterned carbon nanotube(CNT)/thermoplastic polyurethane(TPU)nanofiber electrode,a microporous ionic aerogel electrolyte and a microstructured Ag/TPU nanofiber *** to the presence of a supercapacitive sensing mechanism and the appli-cation of microstructuration,the sensor shows excellent sensing performance,with a sensitivity of 24.62 ***,due to the overall porous structure and hydrophobicity of TPU,the sensor shows good breathability(62 mm/s)and water repellency,with a water contact angle of 151.2°.In addition,effective passive heat preservation is achieved by combining CNTs with high solar absorption rates(85%)as the top layer facing the outside,aerogel with a low thermal conductivity(0.063 W m-1 k-1)as the middle layer for thermal insulation,and Ag with a high infrared reflectance rate as the bottom layer facing the *** warming,this material yields a higher temperature than ***,the active Joule heat-ing effect is realized by applying current through the bottom resistive electrode,which can quickly increase the temperature to supply controlled warming on *** proposed wearable and breathable sensor with tunable thermal properties is promising for monitoring and heat therapy applications in cold environments.

关键词： Wearable sensor Breathable Personal thermal management Electrospun nanofibers Joule heating

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Cooperative Relaying for Connected Construction Equipment Networks with Hybrid Hierarchical Proximal Policy Optimization

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IEEE Transactions on Communications 2024年

作者： Ning, Pengfei Wang, Hongwei Tang, Tao Zhang, Jie Chen, Changji Niyato, Dusit Richard Yu, F. Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation Beijing China Beijing Jiaotong University Collaborative Innovation Center of Railway Traffic Safety Beijing China Nanyang Technological University School of Computer Science and Engineering Singapore Beijing Jiaotong University School of Automation and Intelligence Beijing China Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

The communication network in a tunnel construction site facilitates real-time data exchange, and serves as a backbone for successfully executing construction projects. However, the long and closed spaces, irregular surfaces, and variable topology as tunnel excavation impose rigorous limitations on signal propagation, communication quality and coverage. To alleviate the realistic issues, we introduce a holistic three-phase cooperative relay scheme based on 5G New Radio (NR) vehicle-to-everything (V2X) architecture, which can extend the communication range and enhance network throughput. We theoretically derive the outage probability of the entire cooperative relaying process from source to destination, and quantify the impact of relaying on construction workflow with relay cost. To minimize the outage probability and relay cost, we formulate a cooperative relay strategies optimization problem and transform the solving procedure into a Markov decision process (MDP). We design a hybrid hierarchical proximal policy optimization (HH-PPO) reinforcement learning method to solve the MDP, which consists of two discrete actor networks, two continuous actor networks, and two critic networks. The hybrid structure enables HH-PPO to tackle the mixed action space, and the hierarchical structure enables adaptive and contextual actions generation by integrating the discrete network outputs into the continuous actor network. Simulation results validate the effectiveness of the HH-PPO algorithm with faster convergence speed, and show superior performance in terms of lower, stable outage probability and relay cost satisfaction compared with another benchmark. © 1972-2012 IEEE.

关键词： Markov processes

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Integration of ANN for Accurate Estimation and control in Wastewater Treatment

Integration of ANN for Accurate Estimation and Control in Wa...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Andreea Elena Țîru Iulian Vasiliev Larisa Diaconu Ramon Vilanova Daniel Voipan Harsha Ratnaweera Department of Automatic Control and Electrical Engineering "Dunărea de Jos" University of Galaţi Galaţi Romania Department of Automation Systems and Advanced Control Research Autonomous University of Barcelona Barcelona Spain Department of Computer Science and Information Technology "Dunărea de Jos" University of Galaţi Galaţi Romania Faculty of Science and Technology (Realtek) Norwegian University of Life Sciences Ås Norway

The management of wastewater is a significant global concern that calls for innovative solutions to lessen its negative effects on the environment. Conventional techniques of treating wastewater need improvement in order to deal with newly discovered contaminants, which highlights the importance of providing precise estimates of process performance and resource requirements. The worsening water shortage situation requires a paradigm shift in which wastewater is viewed as a useful resource. It is possible to create an economy that is both sustainable and circular by treating and recycling wastewater, putting less pressure on freshwater supplies, and leaving as little of an environmental footprint as possible. This study investigates the use of Artificial Neural Networks (ANNs) as software estimators in the treatment of wastewater, with a particular emphasis on predicting ammonium concentrations in effluent. In order to deal with imbalanced time-series data, the research introduces innovative data pretreatment strategies. These techniques include a Sliding Window protocol, Data Normalization, and a K-Fold training scheme. This illustrates the potential of ANNs to revolutionize wastewater treatment procedures and drive developments in this field. The suggested method demonstrates higher performance when estimating pollutant concentrations, showing the ability of ANNs to do so.

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Global prescribed-time control of a class of uncertain nonholonomic systems by smooth time-varying feedback

arXiv

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arXiv 2024年

作者： Zhang, Kang-Kang Zhou, Bin Fan, Chenchen Lam, James Department of Mechanical Engineering University of Hong Kong Hong Kong Department of Computer Science KU Leuven HeverleeB-3001 Belgium Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin150001 China Department of Rehabilitation Sciences The Hong Kong Polytechnic University Hong Kong

This paper investigates the prescribed-time smooth control problem for a class of uncertain nonholonomic systems. With a novel smooth time-varying state transformation, the uncertain chained nonholonomic system is reformulated as an uncertain linear time-varying system. By fully utilizing the properties of a class of parametric Lyapunov equations and constructing time-varying Lyapunov-like functions, smooth timevarying high-gain state and output feedback controllers are designed. The states and controllers are proven to converge to zero at any prescribed time. The proposed smooth time-varying method combines the advantage of a time-varying high-gain function, which enhances control performance, and a smooth time-varying function that can drive the states to zero at the prescribed time. The effectiveness of the proposed methods is verified by a numerical example. Copyright © 2024, The Authors. All rights reserved.

关键词： Lyapunov functions

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Recurrent Attentional Reinforcement Learning for Fault Diagnosis of Hydraulic System

Recurrent Attentional Reinforcement Learning for Fault Diagn...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Zhenhui Tang Ru Liu Kang Lou Chaojian Gao Jingcheng Wang SJTU Sanya Yazhou Bay Institute of Deepsea Science and Technology Sanya China Department of Automation Shanghai Jiao Tong University Shanghai China Shanghai Marine Equipment Research Institute Shanghai China Department of Automation the Key Laboratory of System Control and Information Processing Ministry of Education of China and the Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China Autonomous Systems and Intelligent Control International Joint Research Center Xi'an Technological University Xi'an China

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

Recognizing fault types of machinery system is a fundamental but challenging task in industrial application. Although data-driven fault diagnosis method attains remarkable progress by learning fault features automatically, the existing data-driven fault diagnosis pipelines learn non-discriminative feature. To deal with these problems, a new data-driven fault diagnosis method with recurrent attentional module is proposed to find a sequence of informative features by localizing distinguishing time fragments about each individual faults iteratively. The contextual sequence dependency between the localized time fragments is enhanced. Then, the fault types are further predicted on localized time fragments. The proposed framework also explicitly models long-term dependencies among these attentional time fragments to capture historical fault information. Experiments on hydraulic system show that the proposed framework achieves superior diagnosis performance and computation efficiency.

关键词： Fault diagnosis Location awareness Accuracy Computational modeling Pipelines Reinforcement learning Hydraulic systems Computational efficiency Information technology

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Switching Multiplicative Watermark Design Against Covert Attacks

arXiv

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arXiv 2025年

作者： Gallo, Alexander J. Anand, Sribalaji C. Teixeira, Andre M.H. Ferrari, Riccardo M.G. Department of Electronics Information and Bioengineering Politecnico di Milano Milano Italy School of Electrical Engineering and Computer Science and Digital Futures KTH Royal Institute of Technology Sweden Department of Information Technology Uppsala University PO Box 337 UppsalaSE-75105 Sweden Delft Center for Systems and Control Mechanical Engineering TU Delft Delft Netherlands

Active techniques have been introduced to give better detectability performance for cyber-attack diagnosis in cyber-physical systems (CPS). In this paper, switching multiplicative watermarking is considered, whereby we propose an optimal design strategy to define switching filter parameters. Optimality is evaluated exploiting the so-called output-to-output gain of the closed loop system, including some supposed attack dynamics. A worst-case scenario of a matched covert attack is assumed, presuming that an attacker with full knowledge of the closed-loop system injects a stealthy attack of bounded energy. Our algorithm, given watermark filter parameters at some time instant, provides optimal next-step parameters. Analysis of the algorithm is given, demonstrating its features, and demonstrating that through initialization of certain parameters outside of the algorithm, the parameters of the multiplicative watermarking can be randomized. Simulation shows how, by adopting our method for parameter design, the attacker’s impact on performance diminishes. © 2025, CC BY-NC-ND.

关键词： Networked control systems

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Design and Deployment of a Simulation Platform: Case Study of an Agent-Based Model for Youth Suicide Prevention

Design and Deployment of a Simulation Platform: Case Study o...

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Simulation Winter Conference

作者： Joshua Huddleston Michael C. Galgoczy Kareem A. Ghumrawi Philippe J. Giabbanelli Ketra L. Rice Nisha Nataraj Margaret M. Brown Christopher R. Harper Curtis S. Florence Department of Computer Science & Software Engineering Miami University Oxford OH USA National Center for Injury Prevention and Control Centers for Disease Control and Prevention (CDC) Atlanta GA USA

ISBN: (纸本)9781665476621

Research has examined the process of engaging end-users in co-designing a simulation model and using it within workplace settings. In contrast, few studies document the software development aspect of creating, packaging, and deploying a simulation platform that satisfies end-users' needs. In this case study, we detail these aspects regarding a platform involving Agent-Based Modeling for youth suicide prevention. Goals and constraints are detailed in three categories of needs, each showing how competing demands are addressed via software solutions: 1) data, encompassing data security (e.g., no direct access to individual-level data) and data updates (e.g., changing a model's initialization without coding expertise); 2) deployment, to satisfy security protocols (e.g., secure intranet communications) and the end-users' experience (e.g., ease of installation); 3) accessibility, ensuring that individuals with impairments are not excluded from using simulations. By presenting practical solutions to each category, our case study supports modelers in addressing their own deployment needs.

关键词： Protocols Filtering Employment Ecosystems Packaging Software Data models

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D2NT: A High-Performing Depth-to-Normal Translator

D2NT: A High-Performing Depth-to-Normal Translator

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yi Feng Bohuan Xue Ming Liu Qijun Chen Rui Fan Robotics & Artificial Intelligence Laboratory (RAIL) the State Key Laboratory of Intelligent Autonomous Systems and Frontiers Science Center for Intelligent Autonomous Systems the College of Electronic & Information Engineering Tongji University Shanghai P. R. China Department of Computer Science & Engineering the Hong Kong University of Science and Technology (Guangzhou) Hong Kong SAR P. R. China Robotics & Autonomous Systems Thrust of the Systems Hub the Hong Kong University of Science and Technol-ogy (Guangzhou) Nansha Guangzhou P. R. China

Surface normal holds significant importance in visual environmental perception, serving as a source of rich geometric information. However, the state-of-the-art (SoTA) surface normal estimators (SNEs) generally suffer from an unsatisfactory trade-off between efficiency and accuracy. To resolve this dilemma, this paper first presents a superfast depth-to-normal translator (D2NT), which can directly translate depth images into surface normal maps without calculating 3D coordinates. We then propose a discontinuity-aware gradient (DAG) filter, which adaptively generates gradient convolution kernels to improve depth gradient estimation. Finally, we propose a surface normal refinement module that can easily be integrated into any depth-to-normal SNEs, substantially improving the surface normal estimation accuracy. Our proposed algorithm demonstrates the best accuracy among all other existing real-time SNEs and achieves the SoTA trade-off between efficiency and accuracy.

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Bis-benzylisoquinoline alkaloids inhibit flavivirus entry and replication by compromising endolysosomal trafficking and autophagy

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Virologica Sinica 2024年第6期39卷 892-908页

作者： Lihong Huang Lele Liu Junhai Zhu Nanjun Chen Jie Chen Chuen-Fuk Chan Fei Gao Youqin Yin Jiufeng Sun Rongxin Zhang Kehui Zhang Wenbao Qi Jianbo Yue State Key Laboratory for Animal Disease Control and Prevention South China Agricultural UniversityGuangzhou510642China Key Laboratory of Zoonoses Ministry of Agriculture and Rural AffairsSouth China Agricultural UniversityGuangzhou510642China National and Regional Joint Engineering Laboratory for Medicament of Zoonoses Prevention and Control Guangzhou510642China Key Laboratory of Zoonoses Prevention and Control of Guangdong Province GuangzhouChina Department of Computer Science City University of Hong KongHong Kong999077China Department of Biomedical Sciences City University of Hong KongHong Kong999077China Guangdong Workstation for Emerging Infectious Disease Control and Prevention Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease ResponseGuangdong Provincial Center for Disease Control and PreventionGuangzhou511430China Laboratory of Immunology and Inflammation Institute of Basic Medical Sciences and Department of BiotechnologySchool of Life Sciences and BiopharmaceuticsGuangdong Pharmaceutical UniversityGuangzhou510006China State Key Laboratory of Bioactive Substance and Function of Natural Medicines Institute of Materia MedicaChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing100730China Beijing Key Laboratory of Active Substances Discovery and Druggability Evaluation Institute of Materia MedicaChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing100730China City University of Hong Kong Shenzhen Research Institute Shenzhen518057China Division of Natural and Applied Sciences Synear Molecular Biology LabGlobal Health Research CenterDuke Kunshan UniversityKunshan215316China College of Life Sciences Wuhan UniversityWuhan430072China

Flaviviruses,such as dengue virus(DENV),Zika virus(ZIKV),and Japanese encephalitis virus(JEV),represent a substantial public health challenge as there are currently no approved treatments ***,we investigated the antiviral effects of bis-benzylisoquinoline alkaloids(BBAs)on flavivirus *** evaluated five specific BBAs—berbamine,tetrandrine,iso-tetrandrine,fangchinoline,and cepharanthine—and found that they effectively inhibited infections by ZIKV,DENV,or JEV by blocking virus entry and genome replication stages in the flavivirus life ***,we synthesized a fluorophore-conjugated BBA and showed that BBAs targeted endolysosomes,causing lysosomal pH *** studies on inhibiting ZIKV infection by BBAs revealed that these compounds blocked TRPML channels,leading to lysosomal dysfunction and reducing the expression of NCAM1,a key receptor for the entry of ZIKV into cells,thereby decreasing cells susceptibility to ZIKV ***,BBAs inhibited the fusion of autophagosomes and lysosomes,significantly reducing viral RNA ***,our results suggest that BBAs inhibit flavivirus entry and replication by compromising endolysosomal trafficking and autophagy,respectively,underscoring the potential of BBAs as therapeutic agents against flavivirus infections.

关键词： Bis-benzylisoquinoline alkaloids(BBAs) Flavivirus Zika virus(ZIKV) Endolysosomes TRPML channels Autophagy

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A Time-Series Higher-Order Network Hierarchical Evolution Model for Dynamic Interaction of Nodes

SSRN

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SSRN 2022年

作者： Yang, Xiaoteng Wu, Zhenqiang Zhang, WenBo Javaid, Shumaila School of Computer Science Shaanxi Normal University Xi’an710119 China Key Laboratory of Modern Teaching Technology Ministry of Education Xi’an710062 China Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China Frontiers Science Center for Intelligent Autonomous Systems Shanghai201210 China

The evolution of hierarchies in complex systems is an exciting phenomenon since hierarchies exist in many social and biological networks. So far, many approaches have been proposed, however, they are either based on the locality of the nodes or the cluster relationships between networks. These approaches often use traditional time-series network modeling methods that focus only on local static relationships between different nodes but ignore the dynamic interactions between real network nodes. Local static and dynamic global relationships should be considered to understand better the generation and maintenance of hierarchical phenomena in networks. To address this problem, we propose a long-term, flexible hierarchical evolution model for explaining the hierarchical phenomena arising in networks. Our model can integrate both local static and dynamic global information in the network and use time and higher-order inter-node interactions to integrate static and dynamic relationships. New interactions in the network are formed based on preference information between nodes, while old links fade out over time. In addition, we derive critical points for the hierarchical evolution of the system over long periods. Importantly, our model allows the comparison of network rank formation across different data as a way to perform rank evolution studies. © 2022, The Authors. All rights reserved.

关键词： Time series

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