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MixerKT:A Knowledge Tracing Model Based on Pure MLP Architecture

Computers, Materials & Continua 2025年第1期82卷 485-498页

作者： Jun Wang Mingjie Wang Zijie Li Ken Chen Jiatian Mei Shu Zhang key laboratory of education Informatization for Nationalities Ministry of EducationYunnan Normal UniversityKunming650000China Yunnan key laboratory of Smart education Yunnan Normal UniversityKunming650000China

In the field of intelligent education,the integration of artificial intelligence,especially deep learning technologies,has garnered significant *** tracing(KT)plays a pivotal role in this field by predicting students’future performance through the analysis of historical interaction data,thereby assisting educators in evaluating knowledgemastery and tailoring instructional *** knowledge tracingmethods,largely based on Recurrent Neural Networks(RNNs)and Transformer models,primarily focus on capturing long-term interaction patterns in sequential ***,these models may neglect crucial short-term dynamics and other relevant *** paper introduces a novel approach to knowledge tracing by leveraging a pure Multilayer Perceptron(MLP)*** proposeMixerKT,a knowledge tracing model based on theHyperMixer framework,which uniquely integrates global and localMixer feature *** architecture enables more effective extraction of both long-terminteraction trends and recent learning behaviors,addressing limitations in currentmodels thatmay overlook these key *** evaluations on twowidely-used datasets,ASSIS Tments2009 and Algebra2005,demonstrate that MixerKT consistently outperforms several state-of-the-art models,including DKT,SAKT,and Separated Self-Attentive Neural Knowledge Tracing(SAINT).Specifically,MixerKT achieves higher prediction accuracy,highlighting its effectiveness in capturing the nuances of learners’knowledge *** results indicate that our model provides a more comprehensive representation of student learning patterns,enhancing the ability to predict future performance with greater precision.

关键词： Knowledge tracing multilayer perceptron channel mixer sequence mixer

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Physarum polycephalum-inspired adaptive optimization design of artificial microtubular networks

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Science China Chemistry 2025年

作者： Si-Min Zeng Di-Wei Zheng Ting Pan Xing-Lan Ding Yun Zhang Chi-Hui Yang Si-Xue Cheng Xian-Zheng Zhang key laboratory of Biomedical Polymers of ministry of education&Department of Chemistry Wuhan University

Natural biological microtubular networks have undergone adaptive evolutionary selection and may offer viable solutions to design challenges in artificial microtubular networks. The plasmodium of the slime mold Physarum polycephalum(P. polycephalum) extends continuously to form a protoplasmic microtubular network structure, directly connecting food *** simulations revealed that the formation of this adaptive P. polycephalum microtubular network could be captured by a mathematical algorithm. Inspired by the P. polycephalum microtubular networks, we propose an adaptive optimization design method for artificial microtubular networks. Specifically, we utilized hydrogels with biodegradable and tissue-adhesive properties to replicate the P. polycephalum microtubular networks via photomask. In Rhodamine B diffusion and glucosecatalyzed reaction experiments, we found that the P. polycephalum microtubular networks exhibited significantly enhanced efficiency compared to vascular and artificial networks. Furthermore, we demonstrated the potential for uric acid(UA) degradation of the hydrogels with a real P. polycephalum microtubular network loaded with urate oxidase(UOx) in a rodent model of hyperuricemia. And this network achieved more than double the effect of the artificial network. This underscores the potential of natural microtubular networks to replace artificial microtubular networks.

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DKP-SLAM:A Visual SLAM for Dynamic Indoor Scenes Based on Object Detection and Region Probability

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Computers, Materials & Continua 2025年第1期82卷 1329-1347页

作者： Menglin Yin Yong Qin Jiansheng Peng College of Automation Guangxi University of Science and TechnologyLiuzhou545000China Department of artificial intelligence and Manufacturing Hechi UniversityHechi546300China key laboratory of AI and Information Processing Education Department of Guangxi Zhuang Autonomous RegionHechi546300China Guangxi key laboratory of Sericulture Ecology and Applied Intelligent Technology School of Chemistry and BioengineeringHechi UniversityHechi546300China

In dynamic scenarios,visual simultaneous localization and mapping(SLAM)algorithms often incorrectly incorporate dynamic points during camera pose computation,leading to reduced accuracy and *** paper presents a dynamic SLAM algorithm that leverages object detection and regional dynamic ***,a parallel thread employs the YOLOX object detectionmodel to gather 2D semantic information and compensate for missed ***,an improved K-means++clustering algorithm clusters bounding box regions,adaptively determining the threshold for extracting dynamic object contours as dynamic points *** process divides the image into low dynamic,suspicious dynamic,and high dynamic *** the tracking thread,the dynamic point removal module assigns dynamic probability weights to the feature points in these *** with geometric methods,it detects and removes the dynamic *** final evaluation on the public TUM RGB-D dataset shows that the proposed dynamic SLAM algorithm surpasses most existing SLAM algorithms,providing better pose estimation accuracy and robustness in dynamic environments.

关键词： Visual SLAM dynamic scene YOLOX K-means++clustering dynamic probability

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Structural Modal Parameter Recognition and Related Damage Identification Methods under Environmental Excitations: A Review

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Structural Durability & Health Monitoring 2025年第1期19卷 25-54页

作者： Chao Zhang Shang-Xi Lai Hua-Ping Wang School of Civil Engineering and Mechanics Lanzhou UniversityLanzhou730000China key laboratory of Special Functional Materials and Structural Design Ministry of EducationLanzhou UniversityLanzhou730000China

Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the ***,it is particularly signiﬁcant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientiﬁc basis for structural damage identiﬁcation and dynamic model modiﬁ*** view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and brieﬂy describes how to identify structural damages based on the derived modal *** paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),brieﬂy describes damage identiﬁcation methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artiﬁcial intelligence(AI)methods in the direction of modal parameter recognition and damage identiﬁcation is further *** on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identiﬁcation methods are given to provide scientiﬁc references for the optimized design and functional upgrading of SHM systems.

关键词： Structural health monitoring data information modal parameters damage identiﬁcation AI method

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A Support Vector Machine(SVM)Model for Privacy Recommending Data Processing Model(PRDPM)in Internet of Vehicles

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Computers, Materials & Continua 2025年第1期82卷 389-406页

作者： Ali Alqarni Department of Computer Science and artificial intelligence College of Computing and Information TechnologyUniversity of BishaBisha61922Saudi Arabia

Open networks and heterogeneous services in the Internet of Vehicles(IoV)can lead to security and privacy *** key requirement for such systems is the preservation of user privacy,ensuring a seamless experience in driving,navigation,and *** privacy needs are influenced by various factors,such as data collected at different intervals,trip durations,and user *** address this,the paper proposes a Support Vector Machine(SVM)model designed to process large amounts of aggregated data and recommend privacy preserving *** model analyzes data based on user demands and interactions with service providers or neighboring *** aims to minimize privacy risks while ensuring service continuity and *** SVMmodel helps validate the system’s reliability by creating a hyperplane that distinguishes between maximum and minimum privacy *** results demonstrate the effectiveness of the proposed SVM model in enhancing both privacy and service performance.

关键词： Support vector machine big data IoV privacy-preserving

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Resting-state brain network remodeling after different nerve reconstruction surgeries:a functional magnetic resonance imaging study in brachial plexus injury rats

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Neural Regeneration Research 2025年第5期20卷 1495-1504页

作者： Yunting Xiang Xiangxin Xing Xuyun Hua Yuwen Zhang Xin Xue Jiajia Wu Mouxiong Zheng He Wang Jianguang Xu School of Rehabilitation Science Shanghai University of Traditional Chinese MedicineShanghaiChina Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation Ministry of EducationShanghaiChina Department of Rehabilitation Medicine Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina Department of Traumatology and Orthopedics Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghaiChina Institute of Science and Technology for Brain-Inspired intelligence Fudan UniversityShanghaiChina key laboratory of Computational Neuroscience and Brain-Inspired intelligence(Fudan University) Ministry of EducationShanghaiChina Human Phenome Institute Fudan UniversityShanghaiChina

Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected ***,differences among reconstruction strategies at the brain network level have not been *** study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve ***–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper ***-state brain functional magnetic resonance imaging was obtained 7 months after *** independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the *** in intra-network resting-state functional connectivity were compared among the *** muscle reinnervation was assessed by behavioral observation(elbow flexion)and *** results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural *** repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor *** thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve *** areas related to cognition and emotion were enhanced after end-to-side nerve *** study revealed important brain networks related to different nerve *** networks may be potential targets for enhancing motor recovery.

关键词： brain functional networks end-to-end nerve transfer end-to-side nerve transfer independent component analysis nerve repair peripheral plexus injury resting-state functional connectivity

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

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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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Characterization of ultraviolet communication in a mixed aerosol environment

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Optoelectronics Letters 2025年第2期 77-84页

作者： ZHAO Taifei SUN Yuxin WANG Wuxin ZHANG Haijun PAN Feixiang WU Hao artificial intelligence key laboratory of Sichuan Province Sichuan University of Science & Engineering Faculty of Automation and Information Engineering Xi'an University of Technology

Wireless ultraviolet (UV) has strong scattering characteristics and can communicate through non-direct *** UV signals are transmitted in the atmosphere,they are affected by the absorption and scattering effects of atmospheric particles and atmospheric turbulence,resulting in attenuation of UV signal energy and reduced reliability of the communication *** paper focuses on the channel model of UV non-direct-view single scattering communication,and simulates and analyzes the communication characteristics of UV light in atmospheric turbulence and mixed aerosol environment under horizontal,vertical and oblique range communication *** results show that at equal relative humidity,the wireless UV non-directive scattering communication performance for vertical communication scenarios is more affected by the mixed aerosol environment and the communication performance is worse.

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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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