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A Multi-Objective Particle Swarm Optimization Algorithm Based on Decomposition and Multi-Selection Strategy

Computers, Materials & Continua 2025年第1期82卷 997-1026页

作者： Li Ma Cai Dai Xingsi Xue Cheng Peng School of Computer Science Shaanxi Normal UniversityXi’an710119China Fujian Provincial key laboratory of Big Data Mining and Applications Fujian University of TechnologyFuzhou350118China Information Construction and Management Center and Institute of artificial intelligence and educational New Productivity Ningxia Normal UniversityGuyuan756099China

The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization *** the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search ***,two update strategies based on decomposition are used to update the evolving population and external archive,***,a multiselection strategy is *** first strategy is for the subspace without a non-dominated *** the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global *** second strategy is for the subspace with a non-dominated *** the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local *** third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated *** the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to ***,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search ***,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test *** results show that the proposed algorithm has better performance.

关键词： Multi-objective optimization multi-objective particle swarm optimization decomposition multi-selection strategy

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The interaction between KIF21A and KANK1 regulates dendritic morphology and synapse plasticity in neurons

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Neural Regeneration Research 2025年第1期20卷 209-223页

作者： Shi-Yan Sun Lingyun Nie Jing Zhang Xue Fang Hongmei Luo Chuanhai Fu Zhiyi Wei Ai-Hui Tang Hefei National Research Center for Physical Sciences at the Microscale CAS Key Laboratory of Brain Function and DiseaseMinistry of Education Key Laboratory for Membrane-less Organelles and Cellular DynamicsDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiAnhui ProvinceChina Institute of artificial intelligence Hefei Comprehensive National Science CenterHefeiAnhui ProvinceChina CAS Center for Excellence in Molecular Cell Sciences Division of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiAnhui ProvinceChina Department of Neurobiology School of Life SciencesSouthern University of Science and TechnologyShenzhenGuangdong ProvinceChina Brain Research Center Southern University of Science and TechnologyShenzhenGuangdong ProvinceChina

Morphological alterations in dendritic spines have been linked to changes in functional communication between neurons that affect learning and ***-4 KIF21A helps organize the microtubule-actin network at the cell cortex by interacting with KANK1;however,whether KIF21A modulates dendritic structure and function in neurons remains *** this study,we found that KIF21A was distributed in a subset of dendritic spines,and that these KIF21A-positive spines were larger and more structurally plastic than KIF21A-negative ***,the interaction between KIF21A and KANK1 was found to be critical for dendritic spine morphogenesis and synaptic *** of either KIF21A or KANK1 inhibited dendritic spine morphogenesis and dendritic branching,and these deficits were fully rescued by coexpressing full-length KIF21A or KANK1,but not by proteins with mutations disrupting direct binding between KIF21A and KANK1 or binding between KANK1 and *** down KIF21A in the hippocampus of rats inhibited the amplitudes of long-term potentiation induced by high-frequency stimulation and negatively impacted the animals’cognitive *** together,our findings demonstrate the function of KIF21A in modulating spine morphology and provide insight into its role in synaptic function.

关键词： actin cytoskeleton dendrite KANK1 KIF21A microtubule spine morphology spine synaptic plasticity talin1

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LiDAR-Visual SLAM with Integrated Semantic and Texture Information for Enhanced Ecological Monitoring Vehicle Localization

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Computers, Materials & Continua 2025年第1期82卷 1401-1416页

作者： Yiqing Lu Liutao Zhao Qiankun Zhao Foreign Environmental Cooperation Center Ministry of Ecology and Environment of PRCBeijing100035China Beijing Computing Center Co. Ltd.Beijing Academy of Science and TechnologyBeijing100083China Beijing Guyu Interactive artificial intelligence Application Co. Ltd.Beijing100024China

Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental *** vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant *** address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data ***,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less ***,visual texture information complements LiDAR-Visual localization by providing additional contextual *** incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of *** approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.

关键词： LiDAR-Visual simultaneous localization and mapping integrated semantic texture information

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An Efficient Boron Source Activation Strategy for the Low‑Temperature Synthesis of Boron Nitride Nanotubes

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Nano-Micro Letters 2025年第1期17卷 548-558页

作者： Ying Wang Kai Zhang Liping Ding Liyun Wu Songfeng E Qian He Nanyang Wang Hui Zuo Zhengyang Zhou Feng Ding Yue Hu Jin Zhang Yagang Yao National laboratory of Solid State Microstructures College of Engineering and Applied SciencesJiangsu Key Laboratory of Artificial Functional Materialsand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093People’s Republic of China School of Electronic Information and artificial intelligence Shaanxi University of Science&TechnologyXian 710000People’s Republic of China College of Bioresources Chemical and Materials Engineering Shaanxi University of Science&TechnologyXian 710000People’s Republic of China key laboratory of Carbon Materials of Zhejiang Province College of Chemistry and Materials EngineeringWenzhou UniversityWenzhou 325000People’s Republic of China Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen 518000People’s Republic of China College of Chemical and Molecular Engineering Peking UniversityBeijing 100871People’s Republic of China

Lowering the synthesis temperature of boron nitride nanotubes(BNNTs)is crucial for their *** primary reason for adopting a high temperature is to enable the effective activation of highmelting-point solid *** this study,we developed a novel approach for efficiently activating boron by introducing alkali metal compounds into the conventional MgO–B *** approach can be adopted to form various low-melting-point AM–Mg–B–O growth *** growth systems have improved catalytic capability and reactivity even under low-temperature conditions,facilitating the synthesis of BNNTs at temperatures as low as 850℃.In addition,molecular dynamics simulations based on density functional theory theoretically demonstrate that the systems maintain a liquid state at low temperatures and interact with N atoms to form BN *** findings offer novel insights into the design of boron activation and are expected to facilitate research on the low-temperature synthesis of BNNTs.

关键词： Boron nitride nanotubes Low-temperature Boron activation Density functional theory

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Preface: Water-related vision

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Science China Technological Sciences 2025年第1期68卷 5页

作者： Zhe SUN Xuelong LI School of artificial intelligence Optics and Electronics (iOPEN)Northwestern Polytechnical University key laboratory of Intelligent Interaction and Applications (Northwestern Polytechnical University) Ministry of Industry and Information Technology The Institute of artificial intelligence (TeleAI) China Telecom

Water-related optical imaging serves as a crucial tool and method for human beings to understand aquatic environments,develop and utilize water resources, and protect aquatic ecosystems. It offers distinct advantages such as intuitive target detection, high imaging resolution, and rich information content. However, due to the absorption and scattering properties of water, water-related optical imaging is often plagued by noise, making the acquisition of clear images a challenging task.

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Science China Technological Sciences 2025年第1期 6-53页

Water-related optical imaging constitutes a pivotal domain within the field of water-related optics and vision,furnishing essential tools for comprehending the water-related environment, harnessing water resources, and safeguarding water ecology. Its merits encompass facile target detection, elevated imaging resolution, and copious information ***, the formidable challenge of attaining clear images in water-related environments is challenging due to the water's absorption and scattering properties. Substantial strides have been achieved in recent years through advancements in software and hardware optical imaging and processing techniques. This review offers a comprehensive exploration of the present state of water-related optical imaging, spanning historical, theoretical, and methodological dimensions. A retrospective analysis of the historical evolution of water-related optical imaging is presented, accompanied by a detailed exposition of the operational principles and the latest noteworthy advancements in various categories of water-related optical imaging. Furthermore, a meticulous comparative analysis of these methodologies is undertaken. These approaches not only enhance water-related optical imaging efficacy but also furnish robust support for scientific inquiry and resource exploitation in water-related environments. This review enhances the comprehension of advancements in water-related optical imaging research, acting as a crucial touchpoint for future explorations and innovations. Water-related optical imaging is critical for comprehending marine ecosystems, supporting environmental conservation, and improving industry efficiency.

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Flexible Graphene Field‑Effect Transistors and Their Application in Flexible Biomedical Sensing

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Nano-Micro Letters 2025年第2期17卷 252-313页

作者： Mingyuan Sun Shuai Wang Yanbo Liang Chao Wang Yunhong Zhang Hong Liu Yu Zhang Lin Han Institute of Marine Science and Technology Shandong UniversityQingdao 266237ShandongPeople’s Republic of China State key laboratory of Crystal Materials Shandong UniversityJinan 250100ShandongPeople’s Republic of China School of Integrated Circuits Shandong UniversityJinan 250100ShandongPeople’s Republic of China Shandong Engineering Research Center of Biomarker and artificial intelligence Application Jinan250100ShandongPeople’s Republic of China

Flexible electronics are transforming our lives by making daily activities more *** to this innovation are field-effect transistors(FETs),valued for their efficient signal processing,nanoscale fabrication,low-power consumption,fast response times,and ***,known for its exceptional mechanical properties,high electron mobility,and biocompatibility,is an ideal material for FET channels and *** combination of graphene and FETs has given rise to flexible graphene field-effect transistors(FGFETs),driving significant advances in flexible electronics and sparked a strong interest in flexible biomedical ***,we first provide a brief overview of the basic structure,operating mechanism,and evaluation parameters of FGFETs,and delve into their material selection and patterning *** ability of FGFETs to sense strains and biomolecular charges opens up diverse application *** specifically analyze the latest strategies for integrating FGFETs into wearable and implantable flexible biomedical sensors,focusing on the key aspects of constructing high-quality flexible biomedical ***,we discuss the current challenges and prospects of FGFETs and their applications in biomedical *** review will provide valuable insights and inspiration for ongoing research to improve the quality of FGFETs and broaden their application prospects in flexible biomedical sensing.

关键词： Flexible Graphene Field-effect transistor Wearable Implantable Biosensor

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Personalized federated few-shot node classification

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Science China(Information Sciences) 2025年第1期68卷 204-218页

作者： Yunfeng ZHAO Xintong HE Guoxian YU Jun WANG Yongqing ZHENG Carlotta DOMENICONI School of Software Shandong University Joint SDU-NTU Centre for artificial intelligence Research Shandong University Department of Mathematics National University of Singapore Department of Computer Science George Mason University

Personalized federated learning(PFL) aims to train customized models for individual clients in a decentralized setting, with the account of non-independent and identically distributed data across clients. However, most PFL methods adopt uniform classification layers for diverse clients and give rise to error-prone predictions, due to the task heterogeneity notably prominent in decentralized graph data scenarios. Although some PFL solutions setup client-specific classification layers for each client and optimize them only locally, they are corrupted with limited local training data. We propose an innovative solution called federated parameter decoupling and node augmentation(Fed PANo) to address these problems and to achieve personalized federated few-shot node classification, which is a prevalent and challenging but unexplored topic. Specifically, Fed PANo first separates the local model into the GNN and classifier to handle unique client-specific task variations. The GNN is trained through federated learning to capture shared knowledge of graph nodes across clients, while the classifier is custom-designed and trained individually for each client. Additionally, a generic classifier shared among clients is adopted to encourage the GNN's grasp of shared information. Then Fed PANo further proposes the node generator along with its local and collaborative training strategies to deal with the node scarcity of clients. Extensive experimental results on benchmark datasets confirm that Fed PANo outperforms eight competitive baselines across different settings.

关键词： personalized federated learning few-shot learning node classification task heterogeneity parameter decoupling node augmentation

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Smaller, faster, lower-power analog RRAM matrix computing circuits without performance compromise

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Science China(Information Sciences) 2025年

作者： Yubiao LUO Pushen ZUO Shiqing WANG Zhong SUN Ru HUANG School of Integrated Circuits Peking University Institute for artificial intelligence Peking University Beijing Advanced Innovation Center for Integrated Circuits

Recently, the analog matrix computing (AMC) concept has been proposed for fast, efficient matrix operations, by configuring global feedback loops with crosspoint resistive memory arrays and operational amplifiers (OAs). The implementation of a general real-valued matrix (containing both positive and negative elements) is enabled by using a set of analog inverters,which, however, is considered inefficient regarding circuit compactness, power consumption, and temporal response. Here, with the assistance of the conductance compensation (CC) strategy to take full advantage of the inherent differential inputs of OAs,new AMC circuits without analog inverters are designed. Such a design saves the area occupation and power dissipation of analog inverters, and thus turns to be smaller and lower-power. Simulation results reveal that the new circuit also shows a faster response towards the steady state, thanks to the reduction of poles in the circuit, which, again, is contributed by the elimination of analog inverters. Along with all of these benefits, extensive simulations demonstrate that the CC-AMC circuits do not compromise the computing performance in terms of relative error caused by various non-ideal factors in the circuit.

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Event-Triggered Robust Parallel Optimal Consensus Control for Multiagent Systems

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IEEE/CAA Journal of Automatica Sinica 2025年第1期 40-53页

作者： Qinglai Wei Shanshan Jiao Qi Dong Fei-Yue Wang IEEE the Institute of Systems Engineering Macau University of Science and Technology the State key laboratory of Multimodal artificial intelligence Systems Institute of Automation Chinese Academy of Sciences the School of artificial intelligence University of Chinese Academy of Sciences China Academy of Electronics and Information Technology the State key laboratory of Multimodal artificial intelligence Systems the School of artificial intelligence University of Chinese Academy of Sciences

This paper highlights the utilization of parallel control and adaptive dynamic programming(ADP) for event-triggered robust parallel optimal consensus control(ETRPOC) of uncertain nonlinear continuous-time multiagent systems(MASs).First, the parallel control system, which consists of a virtual control variable and a specific auxiliary variable obtained from the coupled Hamiltonian, allows general systems to be transformed into affine systems. Of interest is the fact that the parallel control technique's introduction provides an unprecedented perspective on eliminating the negative effects of disturbance. Then, an eventtriggered mechanism is adopted to save communication resources while ensuring the system's stability. The coupled HamiltonJacobi(HJ) equation's solution is approximated using a critic neural network(NN), whose weights are updated in response to events. Furthermore, theoretical analysis reveals that the weight estimation error is uniformly ultimately bounded(UUB). Finally,numerical simulations demonstrate the effectiveness of the developed ETRPOC method.

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