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CableSAM:an efficient automatic segmentation method for aircraft cabin cables

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Optoelectronics Letters 2025年第3期21卷 183-187页

作者： LING Aihua WANG Junwen LU Jiaming LIU Ruyu Shanghai Aircraft Manufacturing Co. Ltd. school of Computer Science and engineering Tianjin University of Technology school of information Science and Technology Hangzhou Normal University

Cabin cables,as critical components of an aircraft's electrical system,significantly impact the operational efficiency and safety of the *** existing cable segmentation methods in civil aviation cabins are limited,especially in automation,heavily dependent on large amounts of data and resources,lacking the flexibility to adapt to different *** address these challenges,this paper introduces a novel image segmentation model,CableSAM,specifically designed for automated segmentation of cabin *** improves segmentation efficiency and accuracy using knowledge distillation and employs a context ensemble *** accurately segments cables in various scenarios with minimal input *** experiments on three cable datasets demonstrate that CableSAM surpasses other advanced cable segmentation methods in performance.

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Advancements in Liver Tumor Detection:A Comprehensive Review of Various Deep Learning Models

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Computer Modeling in engineering & Sciences 2025年第1期142卷 91-122页

作者： Shanmugasundaram Hariharan D.Anandan Murugaperumal Krishnamoorthy Vinay Kukreja Nitin Goyal Shih-Yu Chen Deptartment of Artificial Intelligence and Data Science Vardhaman College of EngineeringHyderabad501218India Deptartment of CSE V.S.B College of EngineeringKarur639111India Deptartment of Electrical and Electronics engineering Vardhaman College of EngineeringHyderabad501218India Centre for Research Impact&Outcome Chitkara UniversityRajpura140401PunjabIndia Department of Computer Science and engineering School of Engineering and TechnologyCentral University of HaryanaMahendergarh123031HaryanaIndia Department of Computer Science and information engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Intelligence Recognition Industry Service Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan

Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment *** Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and *** review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and *** metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical *** review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging *** suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular *** paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.

关键词： Liver tumor detection liver tumor segmentation image processing liver tumor diagnosis feature extraction tumor classification deep learning machine learning

Exit options sustain altruistic punishment and decrease the second-order free-riders, but it is not a panacea

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Science China(information Sciences) 2025年第1期68卷 278-291页

作者： Chen SHEN Zhao SONG Lei SHI Jun TANIMOTO Zhen WANG Faculty of engineering Sciences Kyushu University school of Statistics and Mathematics Yunnan University of Finance and Economics school of Computing Engineering and Digital Technologies Teesside University school of Artificial Intelligence OPtics and Electro Nics (iOPEN) Northwestern Polytechnical University

Why do humans punish free riders at their own expense? This behavior represents an evolutionary puzzle in human societies. This study explores the role of exit strategies in fostering altruistic punishment within evolutionary game theory. We extend the traditional prisoner's dilemma model by incorporating exiters, players who opt out for a small payoff while nullifying their opponent's payoff, and altruistic punishers who cooperate and punish non-cooperators. Our findings indicate that in well-mixed populations, exiters destabilize defection but do not promote altruistic punishment. In social networks, however,exiters enable altruistic punishment via cyclic dominance among altruistic punishers, defectors, and exiters. Notably, this cyclic dominance is sensitive to exit payoffs; adjustments can lead to cyclic dominance of non-punishing cooperators, defectors, and exiters, or to a bi-stable state between these two types of cyclic dominance. These results highlight the nuanced impact of exiters on altruistic punishment, emphasizing the need for careful incentivization of exit behavior. While exiters can support altruistic punishment in networked populations, their effectiveness is not a panacea and is highly sensitive to exit payoffs, indicating limits to the voluntary participation mechanism.

关键词： evolutionary game theory altruistic punishment coexistence cyclic dominance bi-stable

Deliberate design of MOF-based pre-catalyst rationalizing the structural reconstruction toward efficient oxygen evolution reaction

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Science China Chemistry 2025年

作者： Yunhui Chen Meng Tian Zhongqi Zhang Guangzhao Wang Yan Guo Jing Wu Dawei Qi Zhenhua Yan Xiangyu Liu Xi Liu State Key Laboratory of High-efficiency Coal Utilization and Green Chemical engineering College of Chemistry and Chemical EngineeringNingxia University Key Laboratory of Extraordinary Bond engineering and Advanced Materials Technology of Chongqing School of Electronic Information Engineering Yangtze Normal University Frontiers Science Center for New Organic Matter Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education) State Key Laboratory of Advanced Chemical Power Sources College of Chemistry Nankai University school of Chemistry and Chemical engineering In-situ Center for Physical Sciences Frontiers Science Center for Transformative Molecules Shanghai Jiao Tong University

Metal-organic frameworks （MOFs）,that have emerged as promising electrocatalysts in oxygen evolution reaction （OER）,usually undergo structural reconstruction to form metal hydroxides as active ***,it remains a great challenge to design and synthesize ideal MOF-based pre-catalysts for properly cognizing and utilizing the reconstruction process toward efficient OER ***,the well-defined MOF-808 is post-modified by 2-hydroxyphosphonoacetic acid （HPAA） to form a micro-adsorber that enables to capture of metal ions ***3+and Ni2+ions are synergistically anchored into the microadsorber,developing a Fe/Ni-containing pre-catalyst that can be dynamically electrooxidized to be an active and stable dual-site electrocatalyst denoted by R-MOF-HPAA@FeNi with abundant metal *** a result,R-MOF-HPAA@FeNi exhibits an excellent OER performance with a low overpotential of 272 mV and Tafel slope of 35.9 m V dec-1,as well as long-term stability over 300 h at 10 m A *** and theoretical calculations suggest the resulting catalyst mainly follows a lattice oxygen mechanism （LOM） of dual-metal-site mechanism （DMSM）.Owing to the chelating role of HPAA,the post-synthesized MOF-HPAA behaves as a trap to uniformly and firmly adhere Fe3+and Ni2+ions,leading to a functionalized MOF-based pre-catalyst which can be structurally evolved into atomic level-distributed OER electrocatalysts.

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Design high-performance narrowband emitters for blue light-emitting diodes through manipulating resonance structure of aromatic heterocycles

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Science China Chemistry 2025年

作者： Yue Yu Lei Xu Wenle Tan Yuyu Pan Jiyin Xiao Bohan Wang Guangjun Tian Yuguang Ma Lei Ying Institute of Polymer Optoelectronic Materials and Devices Guangdong Basic Research Center of Excellence for Energy and Information Polymer Materials State Key Laboratory of Luminescent Materials and Devices South China University of Technology school of Petrochemical engineering Shenyang University of Technology Key Laboratory for Microstructural Material Physics of Hebei Province School of Science Yanshan University

Narrowband light-emitting materials play critical roles in improving the color gamut and energy consumption of electroluminescence. Herein we demonstrated that by regulating the ground state resonance structure form of emitters with polycyclic aromatic heterocycles, the high-energy vibration of the C–C bond can be effectively suppressed, resulting in narrow emission like classical cyanine dyes. The designed compounds consist of twist and planar conformation, while having differences in the orientation of the positioning electron-donating(nitrogen) and electron-accepting(carbonyl) groups in the polycyclic aromatic hydrocarbon skeleton. The resulting compound Ac-Ph-Ac with a dominated zwitterionic resonance structure exhibits a relatively wide electroluminescent profile with the full width at half maximum(FWHM) of 42 nm and moderate device performance. In contrast, the “soliton transition” of 2AcPh based on the cyanine limit character effectively suppresses C–C stretching vibration in the polycyclic aromatic heterocycle skeleton, leading to a narrow electroluminescent profile with FWHM of 30 nm(0.16 eV)associated with an impressively high external quantum efficiency of 28.52%, which is among the highest efficiencies of so far reported non-sensitized organic light-emitting diodes.

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Mitigating methodology of hardware non-ideal characteristics for non-volatile memory based neural networks

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Science China(information Sciences) 2025年

作者： Lixia HAN Peng HUANG Yijiao WANG Zheng ZHOU Haozhang YANG Yiyang CHEN Xiaoyan LIU Jinfeng KANG school of Integrated Circuits Peking University Beijing Advanced Innovation Center for Integrated Circuits school of Integrated Circuit Science and engineering Beihang University

Non-volatile memory-based computing-in-memory (nvCIM) paradigm has been extensively studied to boost the energy efficiency of neural network accelerators in edge ***,the degradation of inference accuracy induced by the non-ideal characteristics across circuits,arrays,and devices is becoming a crucial *** this work,we establish a hardware characteristic behavior model to analyze the impact of nvCIM non-ideal characteristics on neural network *** we propose a hardware aware training and weight mapping correction methods to mitigate inference accuracy *** simulation verification,about 95%inference accuracy degradation is recovered by adopting the proposed mitigation method for various non-ideal characteristics and various neural network *** feasibility of the proposed method is further proved in an experimental example with a flash-based LeNet recognition system.

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Boosting aqueous nickel-zinc battery stability with bimetallic ion-integrated 1D metal-organic nanowires

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Science China Chemistry 2025年

作者： Yihao Chen Jin Liang Yichun Su Guoyin Zhu Hengyue Xu Hongye Ding Guangxun Zhang Dianheng Yu Zizhou Shen Yizhou Zhang Wei Huang Huan Pang school of Chemistry and Chemical engineering Yangzhou University Key Laboratory of Flexible Electronics (KLoFE) & Institute of Advanced Materials (IAM) School of Flexible Electronics (Future Technologies) Nanjing Tech University (NanjingTech) Institute of Advanced Materials and Flexible Electronics (IAMFE) School of Chemistry and Materials Science Nanjing University of Information Science & Technology Department of Chemistry Tsinghua University State Key Laboratory of Coordination Chemistry Nanjing University

Limited by low conductivity,designing cathode materials with excellent electron transfer efficiency for high-performance nickel-zinc batteries （NZBs） remains *** this study,a series of bimetallic metal-organic nanowires were fabricated by doping M ions in NiNTA,resulting in NiMNTA (M=Mg2+,Mn2+,Co2+,Zn2+,Ag+),and NixCo6-xNTA （x=1,2,3,4,5）.The proportions and types of metal ions can be modified without altering the initial coordination structure.X-ray absorption fine structure spectroscopy （XAFS） revealed that only M–O bonds,not metal bonds,were present in the *** performance of Ni2Co4NTA as the cathode for aqueous NZBs was significantly improved,achieving the maximum energy density of 279.17Wh kg-1with the high cycle stability （retention rate of 72.0%after 1,000 cycles）.The flexible Ni2Co4NTA//Zn@carbon cloth battery employing gel electrolyte also exhibits the excellent Coulombic efficiency of 96%after 350 *** approach shows considerable potential for designing one-dimensional materials with bimetallic modifications,providing new strategies for developing cathode materials for NZBs with high specific capacity and cycle stability.

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Poly(lactic acid)/Poly(butylene adipate-co-terephthalate)films with simultaneous high oxygen barrier and fast degradation properties

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Green Energy & Environment 2025年第1期10卷 1-10页

作者： Mengjing Yang Yuxi Mao Penghui Zhang Jie Li Zeming Tong Zhenguo Liu Yanhui Chen Institute of Flexible Electronics Northwestern Polytechnical UniversityXi'an710072China Key Laboratory of Flexible Electronics of Zhejiang Province Ningbo Institute of Northwestern Polytechnical University218 Qingyi RoadNingbo315103China school of Chemistry and Chemical engineering Shaanxi Key Laboratory of Macromolecular Science and TechnologyKey Laboratory of Special Functional and Smart Polymer Materials of Ministry of Industry and Information TechnologyNorthwestern Polytechnical UniversityXi'an 710072China

Although poly(lactic acid)(PLA)is a good environmentally-friendly bio-degradable polymer which is used to substitute traditional petrochemical-based polymer packaging films,the barrier properties of PLA films are still insufficient for high-barrier packaging *** this study,oxygen scavenger hydroxyl-terminated polybutadiene(HTPB)and cobalt salt catalyst were incorporated into the PLA/poly(butylene adipate-co-terephthalate)(PLA/PBAT),followed by melting extrusion and three-layer co-extrusion blown film process to prepare the composite *** oxygen permeability coefficient of the composite film combined with 6 wt%oxygen scavenger and 0.4 wt%catalyst was decreased significantly from 377.00 cc·mil·m^(-2)·day^(-1)·0.1 MPa^(-1) to 0.98 cc·mil·m^(-2)·day^(-1)·0.1 MPa^(-1),showing a remarkable enhancement of 384.69 times compared with the PLA/PBAT composite ***,the degradation behavior of the composite film was also accelerated,exhibiting a mass loss of nearly 60%of the original mass after seven days of degradation in an alkaline environment,whereas PLA/PBAT composite film only showed a mass loss of 32%.This work has successfully prepared PLA/PBAT composite films with simultaneously improved oxygen barrier property and degradation behavior,which has great potential for high-demanding green chemistry packaging industries,including food,agricultural,and military packaging.

关键词： Barrier property Oxygen scavenging Blow molding Eco-packaging Degradable composite film

Stochastic Augmented-Based Dual-Teaching for Semi-Supervised Medical Image Segmentation

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Computers, Materials & Continua 2025年第1期82卷 543-560页

作者： Hengyang Liu Yang Yuan Pengcheng Ren Chengyun Song Fen Luo school of Computer Science and engineering Chongqing University of TechnologyChongqing400054China College of Artificial Intelligence Chongqing Technology and Business UniversityChongqing400067China

Existing semi-supervisedmedical image segmentation algorithms use copy-paste data augmentation to correct the labeled-unlabeled data distribution ***,current copy-paste methods have three limitations:(1)training the model solely with copy-paste mixed pictures from labeled and unlabeled input loses a lot of labeled information;(2)low-quality pseudo-labels can cause confirmation bias in pseudo-supervised learning on unlabeled data;(3)the segmentation performance in low-contrast and local regions is less than *** design a Stochastic Augmentation-Based Dual-Teaching Auxiliary Training Strategy(SADT),which enhances feature diversity and learns high-quality features to overcome these *** be more precise,SADT trains the Student Network by using pseudo-label-based training from Teacher Network 1 and supervised learning with labeled data,which prevents the loss of rare labeled *** introduce a bi-directional copy-pastemask with progressive high-entropy filtering to reduce data distribution disparities and mitigate confirmation bias in *** the mixed images,Deep-Shallow Spatial Contrastive Learning(DSSCL)is proposed in the feature spaces of Teacher Network 2 and the Student Network to improve the segmentation capabilities in low-contrast and local *** this procedure,the features retrieved by the Student Network are subjected to a random feature perturbation *** two openly available datasets,extensive trials show that our proposed SADT performs much better than the state-ofthe-art semi-supervised medical segmentation *** only 10%of the labeled data for training,SADT was able to acquire a Dice score of 90.10%on the ACDC(Automatic Cardiac Diagnosis Challenge)dataset.

关键词： Semi-supervised medical image segmentation contrastive learning stochastic augmented