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Steel Surface Defect Detection Using Learnable Memory Vision Transformer

Computers, Materials & Continua 2025年第1期82卷 499-520页

作者： Syed Tasnimul Karim Ayon Farhan Md.Siraj Jia Uddin Department of Computer science and engineering BRAC UniversityDhaka1212Bangladesh Department of AI and Big Data Endicott CollegeWoosong UniversityDaejeon34606Republic of Korea

This study investigates the application of Learnable Memory Vision Transformers(LMViT)for detecting metal surface flaws,comparing their performance with traditional CNNs,specifically ResNet18 and ResNet50,as well as other transformer-based models including Token to Token ViT,ViT withoutmemory,and Parallel *** awidely-used steel surface defect dataset,the research applies data augmentation and t-distributed stochastic neighbor embedding(t-SNE)to enhance feature extraction and *** techniques mitigated overfitting,stabilized training,and improved generalization *** LMViT model achieved a test accuracy of 97.22%,significantly outperforming ResNet18(88.89%)and ResNet50(88.90%),aswell as the Token to TokenViT(88.46%),ViT without memory(87.18),and Parallel ViT(91.03%).Furthermore,LMViT exhibited superior training and validation performance,attaining a validation accuracy of 98.2%compared to 91.0%for ResNet 18,96.0%for ResNet50,and 89.12%,87.51%,and 91.21%for Token to Token ViT,ViT without memory,and Parallel ViT,*** findings highlight the LMViT’s ability to capture long-range dependencies in images,an areawhere CNNs struggle due to their reliance on local receptive fields and hierarchical feature *** additional transformer-based models also demonstrate improved performance in capturing complex features over CNNs,with LMViT excelling particularly at detecting subtle and complex defects,which is critical for maintaining product quality and operational efficiency in industrial *** instance,the LMViT model successfully identified fine scratches and minor surface irregularities that CNNs often *** study not only demonstrates LMViT’s potential for real-world defect detection but also underscores the promise of other transformer-based architectures like Token to Token ViT,ViT without memory,and Parallel ViT in industrial scenarios where complex spatial relationships are *** research m

关键词： Learnable Memory Vision Transformer(LMViT) Convolutional Neural Networks(CNN) metal surface defect detection deep learning,computer vision image classification learnable memory gradient clipping label smoothing t-SNE visualization

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Semantic Segmentation of Lumbar Vertebrae Using Meijering U-Net(MU-Net)on Spine Magnetic Resonance Images

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Computer Modeling in engineering & sciences 2025年第1期142卷 733-757页

作者： Lakshmi S V V Shiloah Elizabeth Darmanayagam Sunil Retmin Raj Cyril Department of Computer science and engineering College of Engineering GuindyAnna UniversityChennai600025India Department of Information Technology Madras Institute of TechnologyAnna UniversityChrompetChennai600044India

Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people *** to its ability to produce a detailed view of the soft tissues,including the spinal cord,nerves,intervertebral discs,and vertebrae,Magnetic Resonance Imaging is thought to be the most effective method for imaging the *** semantic segmentation of vertebrae plays a major role in the diagnostic process of lumbar *** is difficult to semantically partition the vertebrae in Magnetic Resonance Images from the surrounding variety of tissues,including muscles,ligaments,and intervertebral discs.U-Net is a powerful deep-learning architecture to handle the challenges of medical image analysis tasks and achieves high segmentation *** work proposes a modified U-Net architecture namely MU-Net,consisting of the Meijering convolutional layer that incorporates the Meijering filter to perform the semantic segmentation of lumbar vertebrae L1 to L5 and sacral vertebra ***-colour mask images were generated and used as ground truth for training the *** work has been carried out on 1312 images expanded from T1-weighted mid-sagittal MRI images of 515 patients in the Lumbar Spine MRI Dataset publicly available from Mendeley *** proposed MU-Net model for the semantic segmentation of the lumbar vertebrae gives better performance with 98.79%of pixel accuracy(PA),98.66%of dice similarity coefficient(DSC),97.36%of Jaccard coefficient,and 92.55%mean Intersection over Union(mean IoU)metrics using the mentioned dataset.

关键词： Computer aided diagnosis(CAD) magnetic resonance imaging(MRI) semantic segmentation lumbar vertebrae deep learning U-Net model

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Role of copper chelating agents: between old applications and new perspectives in neuroscience

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Neural Regeneration Research 2025年第3期20卷 751-762页

作者： Rosalba Leuci Leonardo Brunetti Vincenzo Tufarelli Marco Cerini Marco Paparella Nikola Puvača Luca Piemontese Department of pharmacy-Pharmaceutical science University of Bari Aldo MoroBariItaly Department of Precision and Regenerative Medicine and Jonian Area(DiMePRe-J) Section of Veterinary Science and Animal ProductionUniversity of Bari Aldo MoroBariItaly Department of engineering Management in Biotechnology Faculty of Economics and Engineering Management in Novi SadUniversity Business Academy in Novi SadNovi SadSerbia

The role of copper element has been an increasingly relevant topic in recent years in the fields of human and animal health, for both the study of new drugs and innovative food and feed supplements. This metal plays an important role in the central nervous system, where it is associated with glutamatergic signaling, and it is widely involved in inflammatory processes. Thus, diseases involving copper(Ⅱ) dyshomeostasis often have neurological symptoms, as exemplified by Alzheimer's and other diseases(such as Parkinson's and Wilson's diseases). Moreover, imbalanced copper ion concentrations have also been associated with diabetes and certain types of cancer, including glioma. In this paper, we propose a comprehensive overview of recent results that show the importance of these metal ions in several pathologies, mainly Alzheimer's disease, through the lens of the development and use of copper chelators as research compounds and potential therapeutics if included in multi-target hybrid drugs. Seeing how copper homeostasis is important for the well-being of animals as well as humans, we shortly describe the state of the art regarding the effects of copper and its chelators in agriculture, livestock rearing, and aquaculture, as ingredients for the formulation of feed supplements as well as to prevent the effects of pollution on animal productions.

关键词： agriculture Alzheimer's disease chelators copper feed supplements multi-target

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Plasmonic tandem heterojunctions enable high-efficiency charge transfer for broad spectrum photocatalytic hydrogen production

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Journal of Energy Chemistry 2025年第1期100卷 710-720页

作者： Wenxuan Chen Xiu-Qing Qiao Guo Hui Bojing Sun Dongfang Hou Meidi Wang Xueqian Wu Tao Wu Dong-Sheng Li college of Materials and Chemical engineering Key Laboratory of Inorganic Nonmetallic Crystalline and Energy Conversion Materials China Three Gorges University Hubei Three Gorges Laboratory college of Chemistry and Materials science and Guangdong Provincial Key Laboratory of Supramolecular Coordination Chemistry Jinan University

Rational engineering of semiconductor photocatalysts for efficient hydrogen production is of great significance but still challenging,primarily due to the limitations in charge transfer ***,a fascinating plasmonic tandem heterojunction with the hc-CdS/Mo2C@C heterostructure is aimfully prepared for effectively promoting the charge separation kinetics of the CdS photocatalyst via the synergistic strategy of phase junction,Schottky junction,and photothermal *** difference in atomic configuration between cubic-CdS （c-CdS） and hexagonal-CdS （h-CdS） leads to effective charge separation through a typical Ⅱ charge transfer mechanism,and plasmonic Schottky junction further extracts the electrons in the hc-CdS phase junction to realize gradient charge ***,the photothermal effect of Mo2C@C helps to expand the light absorption,accelerate charge transfer kinetics,and reduce the hydrogen evolution energy *** carbon layer provides a fast channel for charge transfer and protects the photocatalyst from *** a result,the optimized hc-CMC photocatalyst exhibits a significantly high photocatalytic H2production activity of 28.63 mmol/g/h and apparent quantum efficiency of 61.8%,surpassing most of the reported *** study provides a feasible strategy to enhance the charge transfer kinetics and photocatalytic activity of CdS by constructing plasmonic tandem heterogeneous junctions.

关键词： Cadmium sulfide

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2D CaWO4 nanosheets derived from scheelite minerals for enhanced electrocatalysis in oxygen evolution reaction

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science China Chemistry 2025年

作者： Qing Sun Yongxiang Sun Yan Dong Hong Zhong Hongbo Zeng National&Local United engineering Laboratory for New Petrochemical Materials&Fine Utilization of Resources College of Chemistry and Chemical EngineeringHunan Normal University Department of Chemical and Materials engineering University of Alberta college of Chemistry and Materials engineering Hunan University of Arts and Science college of Chemistry and Chemical engineering Central South University

Scheelite （CaWO4） mineral holds promise as a cost-effective and efficient catalyst for the oxygen evolution reaction （OER）crucial in renewable energy ***,challenges such as limited active site exposure and low electrocatalytic performance need *** this work,we have fabricated two-dimensional （2D） CaWO4nanosheets from scheelite minerals via a straightforward ultrasonic exfoliation method and evaluated their efficacy as OER *** to scheelite powders,these 2D nanosheets exhibited superior crystallinity and a 1.26-fold increase in electrochemical surface area,promoting active site *** 2D CaWO4nanosheet electrode demonstrated outstanding OER catalytic performance,achieving a current density of 20 mA/cm2at an overpotential of 290 m V in alkaline conditions,which was lower than that of bulk CaWO4electrodes （～340 mV）.Density functional theory calculations attributed this enhanced catalytic performance to moderate adsorption of oxygenated intermediates （*OH,*O,and*OOH） on the W sites of 2D *** situ electrochemical atomic force microscopy tests also confirmed the catalytic enhancement by 2D CaWO4nanosheets during *** findings demonstrate the potential of affordable and abundant mineral resources in advancing electrochemical catalysts for oxygen evolution,highlighting their broader application in sustainable energy technologies.

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Data-Driven Healthcare:The Role of Computational Methods in Medical Innovation

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Computer Modeling in engineering & sciences 2025年第1期142卷 1-48页

作者： Hariharasakthisudhan Ponnarengan Sivakumar Rajendran Vikas Khalkar Gunapriya Devarajan Logesh Kamaraj Department of Mechanical engineering Dr.Mahalingam College of Engineering and TechnologyPollachiCoimbatoreTamil Nadu642003India Department of Mechanical engineering JKKN College of Engineering and TechnologyKumarapalayamNamakkalTamil Nadu637209India Department of Mechanical engineering Gharda Institute of TechnologyLavelMaharashtra415708India Department of Electrical and Electronics engineering Sri Eshwar College of EngineeringCoimbatoreTamilnadu641202India Department of Mechanical engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai600062India

The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical *** review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health *** findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and *** synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment ***,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease *** review emphasizes the need for interdisciplinary collaboration to further advance this *** research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and *** fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.

关键词： Computational models biomedical engineering bioinformatics machine learning wearable technology

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All-optical neuromorphic devices: materials, working mechanism,and applications

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science China Chemistry 2025年

作者： Song Wang Hao Chen Hui Huang college of Materials science and Opto-Electronic Technology Center of Materials Science and Optoelectronics Engineering CAS Center for Excellence in Topological Quantum Computation CAS Key Laboratory of Vacuum Physics University of Chinese Academy of Sciences college of Chemistry and Molecular engineering Peking University

Traditional von Neumann computing, with physical separation of memory and processing units, cannot satisfy the development of artificial intelligence and cloud computing. Neuromorphic computing, inspired by the human brain, has drawn much ***-optical neuromorphic (AON) devices employ optical signals as information carriers and leverage the neuromorphic functions to implement fast operation speed, low energy consumption, and high bandwidth of neuromorphic computing. Here, we discuss the recent progress in AON devices, including materials, device performance, working mechanisms, and applications. Moreover,the advantages and limitations of AON are presented and discussed. Finally, the perspective of AON devices points out the future research direction of neuromorphic computing.

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Multivariate synergy for heightening ionic HOF robustness and proton conductivity

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science China Chemistry 2025年

作者： Xiang-Tian Bai Li-Hui Cao Xu-Yong Chen Jia-Yu Wang Zi-Ye Zhou Shaanxi Key Laboratory of Chemical Additives for Industry College of Chemistry and Chemical EngineeringShaanxi University of Science and Technology

Multicomponent crystalline materials construct more complex and diversified structures with different combinations and modes,which expands the material structure space and application *** this work,we have successfully synthesized two twocomponent ionic hydrogen-bonded organic frameworks （iHOF-32 and iHOF-33） and a three-component iHOF （iHOF-34）.Guanidine hydrochloride which is rich in N and H and has a short chain length strengthens the hydrogen bonding network of iHOF,thereby aiding in the efficient migration of *** rigid architecture of 1,1'-diamino-4,4'-bipyridine diiodide furnishes additional scaffolding for the iHOFs and enhances its robustness under harsh ***-34 accomplishes the combination of the ultra-high proton conductivity of iHOF-32 and the robustness of iHOF-33 by the synergistic interaction among the three components of *** addition,iHOF-34 was fabricated as a composite membrane with a peak proton conductivity of 1.55×10-1S cm-1,which is 3.8 times higher than that of recast Nafion,and has extensive potential in fuel *** self-assembly strategy of multicomponent HOFs opens up new avenues for constructing diverse structures while promising new opportunities for applications in the fields of proton conduction and energy storage.

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High-performance transparent graphene-based antennas

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science China Technological sciences 2025年

作者： Chaoye HONG Lusong WEI Weijia WANG Youmei TANG Qinghai ZHU Jiangtao HUANGFU Mingsheng XU college of Integrated Circuits State Key Laboratory of Silicon and Advanced Semiconductor Materials Zhejiang University college of Information science and Electronic engineering Zhejiang University

With the continuous development of wireless communication technology, applications in the military, aerospace,and vehicle wireless communication sectors have demanded miniaturized and aesthetically pleasing antennas. Transparent antennas, which combine the advantages of optical and radio-frequency(RF) technologies, have become a popular research topic. However, existing transparent antennas often suffer from complex preparation processes, fragile materials, poor conductivity, and low optical transmittance. Here, we develop hybrid conductive thin films using graphene and silver nanowires,achieving a transmittance of 86% and a sheet resistance of 7.8 Ω/sq with high environmental stability. We demonstrate the suitability of this nanocomposite in two applications: a transparent ultrahigh-frequency RF-identification tag folded dipole antenna and a transparent X-band microwave half-wave dipole antenna. These antennas offer high gain, high radiation efficiency, and small size, indicating that transparent graphene-based antennas have remarkable potential for intelligent information sensor systems.

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Self-assembled carbon monoxide nanoprodrug for chemiexcitationtriggered synergistic chemotherapy against breast cancer

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science China Chemistry 2025年

作者： Shunfei Cui Yiyao Pan Chenzhe Ma Bin Qi Qingqiang Min Ming Li Huabing Chen Hengte Ke Xingyue Ji Jiangsu Province engineering Research Center of Precision Diagnostics and Therapeutics Development College of Pharmaceutical ScienceSoochow University

Carbon monoxide（CO） has recently been well-established as a promising therapeutic modality against cancer. The development of transition-metal-free and tumor-targeted delivery platforms for CO is highly demanded but remains very sporadic. Herein, we developed a polyprodrug system for the co-delivery of CO and a chemotherapeutic agent combretastin A-4（CA-4） to the tumor site based on a chemiexcitation mechanism. Such a poly-prodrug successfully achieved the co-activation of CO and CA-4 in response to H2O2at the tumor site both in vitro and in vivo. Importantly, a synergist effect between CO and CA-4 was observed in suppressing tumor growth in a mouse tumor model. It is anticipated that such a poly-prodrug system could be potentially adapted for the co-delivery of CO and another drug payload for combinational therapy for other indications.

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