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Adaptive-basis decomposition-based low-rank network for efficient non-uniform motion deblurring

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Optoelectronics Letters 2025年第1期21卷 43-50页

作者： chen Lei XIONG qingbo ZHANG Wei LI Runde School of Software Henan University School of Applied Technology China University of Labor Relations

In this study, we present a unified sparsity-driven framework that significantly enhances motion deblurring performance by integrating two key components: a custom-designed dataset and a low-rank module(LRM). This framework leverages the inherent sparsity of per-pixel blur kernels to bolster both deblurring accuracy and model interpretability. Firstly, we propose an adaptive-basis decomposition-based deblurring(ADD) approach, which constructs a tailored training dataset to enhance the generalization capacity of the deblurring network. The ADD framework adaptively decomposes motion blur into sparse basis elements, effectively addressing the intricacies associated with non-uniform blurs. Secondly, an LRM is proposed to improve the interpretability of deblurring models as a plug-and-play module, primarily designed to identify and harness the intrinsic sparse features in sharp images. A series of ablation studies have been conducted to substantiate the synergistic advantages of combining the proposed ADD with the LRM for overall improvement in deblurring efficacy. Subsequently, we empirically demonstrate through rigorous experimentation that incorporating the LRM into an existing Uformer network leads to substantial enhancement in reconstruction performance. This integration yields a sparsity-guided low-rank network(SGLRN). Operating under the overarching principle of sparsity, SGLRN consistently outperforms state-of-the-art methods across multiple standard deblurring benchmarks. Comprehensive experimental results, assessed through quantitative metrics and qualitative visual evaluations, provide compelling evidence of its effectiveness. The overall deblurring results are available at Google Drive.

关键词： Image enhancement

Mutual-structure weighted guided image filtering for depth map restoration

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Optoelectronics Letters 2025年第1期21卷 51-56页

作者： LIU Zijian SONG Jian chen Quanmin XU Jiangtao Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology School of Microelectronics Tianjin University Spikesee Technology Co. Ltd.

Although guided image filtering(GIF) is known for preserving edges and fast computation, it may produce inaccurate outputs in depth map restoration. In this paper, a novel confidence-weighted GIF called mutual-structure weighted GIF(MSWGIF) is proposed, which replaces the mean filtering strategy in GIF during handling overlapping windows. The confidence value is composed of a depth term and a mutual-structure term, where the depth term is utilized to protect the edges of the output, and the mutual-structure term helps to select accurate windows during the structure characteristics of the guidance image are transferred to the output. Experimental results show that MSWGIF reduces the root mean square error(RMSE) by an average of 12.37%, and the average growth rate of correlation(CORR) is 0.07% on average. Additionally, the average growth rate of structure similarity index measure(SSIM) is 0.34%.

关键词： Wiener filtering

Netrin-1 signaling pathway mechanisms in neurodegenerative diseases

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Neural Regeneration Research 2025年第4期20卷 960-972页

作者： Kedong Zhu Hualong Wang Keqiang Ye Guiqin chen Zhaohui Zhang Department of Neurology Renmin Hospital of Wuhan UniversityWuhanHubei ProvinceChina Department of Neurology The First Hospital of Hebei Medical UniversityBrain Aging and Cognitive Neuroscience Laboratory of Heibei ProvinceShijiazhuangHebei ProvinceChina Faculty of Life and Health Sciences Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhenGuangdong ProvinceChina

Netrin-1 and its receptors play crucial roles in inducing axonal growth and neuronal migration during neuronal *** profound impacts then extend into adulthood to encompass the maintenance of neuronal survival and synaptic *** amounts of evidence highlight several key points:(1)Diminished Netrin-1 levels exacerbate pathological progression in animal models of Alzheimer’s disease and Parkinson’s disease,and potentially,similar alterations occur in humans.(2)Genetic mutations of Netrin-1 receptors increase an individuals’susceptibility to neurodegenerative disorders.(3)Therapeutic approaches targeting Netrin-1 and its receptors offer the benefits of enhancing memory and motor function.(4)Netrin-1 and its receptors show genetic and epigenetic alterations in a variety of *** findings provide compelling evidence that Netrin-1 and its receptors are crucial targets in neurodegenerative *** a comprehensive review of Netrin-1 signaling pathways,our objective is to uncover potential therapeutic avenues for neurodegenerative disorders.

关键词： Alzheimer’s disease axon guidance colorectal cancer Netrin-1 receptors Netrin-1 signaling pathways Netrin-1 neurodegenerative diseases neuron survival Parkinson’s disease UNC5C

A Novel Self-Supervised Learning Network for Binocular Disparity Estimation

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 209-229页

作者： Jiawei Tian Yu Zhou Xiaobing chen Salman A.AlQahtani Hongrong chen Bo Yang Siyu Lu Wenfeng Zheng Department of Computer Science and Engineering Major in Bio Artificial IntelligenceHanyang UniversityAnsan-si15577Republic of Korea School of Electrical and Computer Engineering Louisiana State UniversityBaton RougeLA 70803USA Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11574Saudi Arabia School of Automation University of Electronic Science and Technology of ChinaChengdu610054China

Two-dimensional endoscopic images are susceptible to interferences such as specular reflections and monotonous texture illumination,hindering accurate three-dimensional lesion reconstruction by surgical *** study proposes a novel end-to-end disparity estimation model to address these *** approach combines a Pseudo-Siamese neural network architecture with pyramid dilated convolutions,integrating multi-scale image information to enhance robustness against lighting *** study introduces a Pseudo-Siamese structure-based disparity regression model that simplifies left-right image comparison,improving accuracy and *** model was evaluated using a dataset of stereo endoscopic videos captured by the Da Vinci surgical robot,comprising simulated silicone heart sequences and real heart video *** results demonstrate significant improvement in the network’s resistance to lighting interference without substantially increasing ***,the model exhibited faster convergence during training,contributing to overall performance *** study advances endoscopic image processing accuracy and has potential implications for surgical robot applications in complex environments.

关键词： Parallax estimation parallax regression model self-supervised learning Pseudo-Siamese neural network pyramid dilated convolution binocular disparity estimation

Bioinspired Passive Tactile Sensors Enabled by Reversible Polarization of Conjugated Polymers

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Nano-Micro Letters 2025年第1期17卷 361-377页

作者： Feng He Sitong chen ruili Zhou Hanyu Diao Yangyang Han Xiaodong Wu School of Mechanical Engineering Sichuan UniversityChengdu 610065People’s Republic of China School of Software Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065People’s Republic of China State Key Laboratory of Polymer Materials Engineering Sichuan UniversityChengdu 610065People’s Republic of China

Tactile perception plays a vital role for the human body and is also highly desired for smart prosthesis and advanced *** to active sensing devices,passive piezoelectric and triboelectric tactile sensors consume less power,but lack the capability to resolve static ***,we address this issue by utilizing the unique polarization chemistry of conjugated polymers for the first time and propose a new type of bioinspired,passive,and bio-friendly tactile sensors for resolving both static and dynamic ***,to emulate the polarization process of natural sensory cells,conjugated polymers(including poly(3,4-ethylenedioxythiophen e):poly(styrenesulfonate),polyaniline,or polypyrrole)are controllably polarized into two opposite states to create artificial potential *** controllable and reversible polarization process of the conjugated polymers is fully in situ ***,a micro-structured ionic electrolyte is employed to imitate the natural ion channels and to encode external touch stimulations into the variation in potential difference *** with the currently existing tactile sensing devices,the developed tactile sensors feature distinct characteristics including fully organic composition,high sensitivity(up to 773 mV N^(−1)),ultralow power consumption(nW),as well as superior *** demonstrations,both single point tactile perception(surface texture perception and material property perception)and two-dimensional tactile recognitions(shape or profile perception)with high accuracy are successfully realized using self-defined machine learning *** tactile sensing concept innovation based on the polarization chemistry of conjugated polymers opens up a new path to create robotic tactile sensors and prosthetic electronic skins.

关键词： Passive tactile sensors Reversible polarization of conjugated polymers Tactile perception Machine learning algorithm Object recognition

Potassium and calcium channels in different nerve cells act as therapeutic targets in neurological disorders

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Neural Regeneration Research 2025年第5期20卷 1258-1276页

作者： qing qiu Mengting Yang Danfeng Gong Haiying Liang Tingting chen Department of Pharmacology School of PharmacyNantong UniversityNantongJiangsu ProvinceChina Jiangsu Province Key Laboratory of Inflammation and Molecular Drug Target NantongJiangsu ProvinceChina Department of Pharmacy Longyan First Affiliated Hospital of Fujian Medical UniversityLongyanFujian ProvinceChina

The central nervous system, information integration center of the body, is mainly composed of neurons and glial cells. The neuron is one of the most basic and important structural and functional units of the central nervous system, with sensory stimulation and excitation conduction functions. Astrocytes and microglia belong to the glial cell family, which is the main source of cytokines and represents the main defense system of the central nervous system. Nerve cells undergo neurotransmission or gliotransmission, which regulates neuronal activity via the ion channels, receptors, or transporters expressed on nerve cell membranes. Ion channels, composed of large transmembrane proteins, play crucial roles in maintaining nerve cell homeostasis. These channels are also important for control of the membrane potential and in the secretion of neurotransmitters. A variety of cellular functions and life activities, including functional regulation of the central nervous system, the generation and conduction of nerve excitation, the occurrence of receptor potential, heart pulsation, smooth muscle peristalsis, skeletal muscle contraction, and hormone secretion, are closely related to ion channels associated with passive transmembrane transport. Two types of ion channels in the central nervous system, potassium channels and calcium channels, are closely related to various neurological disorders, including Alzheimer's disease, Parkinson's disease, and epilepsy. Accordingly, various drugs that can affect these ion channels have been explored deeply to provide new directions for the treatment of these neurological disorders. In this review, we focus on the functions of potassium and calcium ion channels in different nerve cells and their involvement in neurological disorders such as Parkinson's disease, Alzheimer's disease, depression, epilepsy, autism, and rare disorders. We also describe several clinical drugs that target potassium or calcium channels in nerve cells and could be u

关键词： astrocytes calcium channels central nervous system extracellular ion concentration microglia neurological disorders neurons potassium channels

Computational screening of doping schemes for LiTi2(PO4)3 as cathode coating materials

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Chinese Physics B 2020年第3期29卷 7-12页

作者： Yu-qi Wang Xiao-rui Sun rui-Juan Xiao Li-Quan chen Beijing Advanced Innovation Center for Materials Genome Engineering Institute of PhysicsChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100190China

In all-solid-state lithium batteries,the impedance at the cathode/electrolyte interface shows close relationship with the cycle *** coatings are helpful to reduce the impedance and increase the stability at the interface ***2(PO4)3(LTP),a fast ion conductor with high ionic conductivity approaching 10^(-3)S·cm^(-1),is adopted as the coating materials in this *** crystal and electronic structures,as well as the Li^+ion migration properties are evaluated for LTP and its doped derivatives based on density functional theory(DFT)and bond valence(BV)*** part of Ti sites with element Mn,Fe,or Mg in LTP can improve the electronic conductivity of LTP while does not decrease its high ionic *** this way,the coating materials with both high ionic conductivities and electronic conductivities can be prepared for all-solid-state lithium batteries to improve the ion and electron transport properties at the interface.

关键词： lithium battery materials high-throughput calculations density functional theory virtual screening

Machine learning and neural network supported state of health simulation and forecasting model for lithium-ion battery

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Frontiers in Energy 2024年第2期18卷 223-240页

作者： Nan qi Kang YAN Yajuan YU rui LI Rong HUANG Lai chen Yuefeng SU Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China Department of Energy and Environmental Materials School of Materials Science and EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing Electric Vehicle Co. Ltd.Beijing 100176China

As the intersection of disciplines deepens,the field of battery modeling is increasingly employing various artificial intelligence(AI)approaches to improve the efficiency of battery management and enhance the stability and reliability of battery *** paper reviews the value of AI methods in lithium-ion battery health management and in particular analyses the application of machine learning(ML),one of the many branches of AI,to lithium-ion battery state of health(SOH),focusing on the advantages and strengths of neural network(NN)methods in ML for lithium-ion battery SOH simulation and *** is one of the important branches of ML,in which the application of NNs such as backpropagation NN,convolutional NN,and long short-term memory NN in SOH estimation of lithium-ion batteries has received wide *** so far have shown that the utilization of NN to model the SOH of lithium-ion batteries has the advantages of high efficiency,low energy consumption,high robustness,and scalable *** the future,NN can make a greater contribution to lithium-ion battery management by,first,utilizing more field data to play a more practical role in health feature screening and model building,and second,by enhancing the intelligent screening and combination of battery parameters to characterize the actual lithium-ion battery SOH to a greater *** in-depth application of NN in lithium-ion battery SOH will certainly further enhance the science,reliability,stability,and robustness of lithium-ion battery management.

关键词： machine learning lithium-ion battery state of health neural network artificial intelligence

一元溶剂体系TKX-50结晶形貌的分子动力学模拟

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原子与分子物理学报 2025年第4期42卷 163-167页

作者：董羚陈芳李天浩郭国琦贾翔宇米方琦宁瑞星中北大学化学与化工学院太原030051

本文应用分子动力学方法(MD)和修正的Dreiding-TKX-50力场计算了三种单溶剂作用下TKX-50重要晶面层与溶剂层的相互作用能,采用修正的附着能模型预测了TKX-50在不同溶剂中的结晶形貌并与实验结果进行了对比.计算结果表明,TKX-50晶体真空... 详细信息

本文应用分子动力学方法(MD)和修正的Dreiding-TKX-50力场计算了三种单溶剂作用下TKX-50重要晶面层与溶剂层的相互作用能,采用修正的附着能模型预测了TKX-50在不同溶剂中的结晶形貌并与实验结果进行了对比.计算结果表明,TKX-50晶体真空形貌中的重要晶面为(020)、(011)、(11-1)和(100).水(H_(2)O)溶剂和N,N-二甲基甲酰胺(DMF)溶剂作用后所预测的TKX-50晶体形貌近似梭形,纵横比为1.857和2.073.乙二醇(EG)溶剂作用后所预测的TKX-50晶体形貌为块体,纵横比为2.320.

关键词：附着能结晶形貌分子动力学 TKX-50 溶剂