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Domain generalization with semi-supervised learning for people-centric activity recognition

science China(Information sciences) 2025年第1期68卷 171-188页

作者： Jing LIU Wei ZHU Di LI Xing HU Liang SONG Academy for Engineering & technology Fudan University shanghai East-bund Research institute on Networking Systems of ai school of Optoelectronic Information and computer Engineering University of Shanghai for Science & Technology

People-centric activity recognition is one of the most critical technologies in a wide range of real-world applications,including intelligent transportation systems, healthcare services, and brain-computer interfaces. Large-scale data collection and annotation make the application of machine learning algorithms prohibitively expensive when adapting to new tasks. One way of circumventing this limitation is to train the model in a semi-supervised learning manner that utilizes a percentage of unlabeled data to reduce the labeling burden in prediction tasks. Despite their appeal, these models often assume that labeled and unlabeled data come from similar distributions, which leads to the domain shift problem caused by the presence of distribution gaps. To address these limitations, we propose herein a novel method for people-centric activity recognition,called domain generalization with semi-supervised learning(DGSSL), that effectively enhances the representation learning and domain alignment capabilities of a model. We first design a new autoregressive discriminator for adversarial training between unlabeled and labeled source domains, extracting domain-specific features to reduce the distribution gaps. Second, we introduce two reconstruction tasks to capture the task-specific features to avoid losing information related to representation learning while maintaining task-specific consistency. Finally, benefiting from the collaborative optimization of these two tasks, the model can accurately predict both the domain and category labels of the source domains for the classification task. We conduct extensive experiments on three real-world sensing datasets. The experimental results show that DGSSL surpasses the three state-of-the-art methods with better performance and generalization.

关键词： activity recognition deep learning domain generalization semi-supervised learning adversarial training

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Deep learning-based software engineering: progress,challenges, and opportunities

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science China(Information sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU Hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG school of Journalism and Communication Sun Yat-sen University school of Software technology Zhejiang University school of Software Engineering Sun Yat-sen University school of Software Dalian University of Technology school of computer science and technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software technology Nanjing University school of computer science and Engineering Beihang University institute of Information Engineering Chinese Academy of Sciences school of computer science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University school of computer and Information technology Beijing Jiaotong University school of computer science and technology Harbin Institute of Technology school of computer science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

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Mainchain conformation ordering self-assembly tailored room temperature phosphorescence emission

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science China Chemistry 2025年第1期68卷 329-336页

作者： Yuzhu Li Yumeng Gao Feng Tian Yu Wang Yuan Yao Shaoliang Lin Xiang Ma Binbin Xu shanghai Key Laboratory of Advanced Polymeric Materials Key Laboratory for Ultrafine Materials of Ministry of Education School of Materials Science and Engineering East China University of Science and Technology shanghai Synchrotron Radiation Facility Shanghai Advanced Research Institute Chinese Academy of Sciences Key Laboratory for Advance Materials and Feringa Noble Prize Scientist Joint Research Centre Frontiers Science for Materiobiology and Dynamic Chemistry School of Chemistry and Molecular Engineering East China University of Science & Technology

Developing organic room-temperature phosphorescence （RTP） materials with a wide range of tunable-emission is significant in expanding the applications of RTP ***,we rationally designed amphiphilic alternating copolymers poly(1,2-bis（4-alkoxyphenyl）ethane-1,2-dione-alt-（ethylene glycol）x)(P（Bz-alt-EGx）) that combined the advantage of alternating benzil and EGxskeleton,and tunable mainchain *** a mainchain conformation ordering assembly （COA） process,P（Bz-alt-EGx） self-assembled into well-defined platelets,and such assemblies emitted blue RTP at ca.425 nm due to the ordered folded-chain conformation and confined *** contrast,traditional self-assembly （TA） of P（Bz-alt-EGx） obtained less ordered aggregates,such as asymmetric worms,vesicles,and rod-like *** resultant less ordered aggregates exhibited yellow-green RTP at ca.550 *** wide-tuning RTP emission in solution （between blue and yellow-green,over125 nm） is realized using the P（Bz-alt-EGx） alternating copolymers under the treatment of different self-assembly *** study uncovers a new strategy to tailor the RTP emission through different self-assembly pathways and holds great promise for the fabrication of advanced optical materials.

关键词： self-assembly conformation ordering alternating copolymer phosphorescence emission

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A functional cathode sodium compensation agent for stable sodium-ion batteries

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Green Energy & Environment 2025年第1期10卷 173-182页

作者： Wei Wu Zhenglin Hu Zhengfei Zhao Aoxuan Wang Jiayan Luo Key Laboratory for Green Chemical technology of Ministry of education School of Chemical Engineering and TechnologyTianjin UniversityTianjin300072China State Key Laboratory of Metal Matrix Composites School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghai200240China shanghai Jiao Tong University Shaoxing Research institute of Renewable Energy and Molecular Engineering Shaoxing312000China

Hard carbon(HC)is widely used in sodium-ion batteries(SIBs),but its performance has always been limited by lowinitial Coulombic efficiency(ICE)and cycling *** compensation agent is a favorable strategy to make up for the loss of active sodium ions consumed *** it lacks agent that effectively decomposes to increase the active sodium ions as well as regulate carbon defects for decreasing the irreversible sodium ions ***,we propose 1,2-dihydroxybenzene Na salt(NaDB)as a cathode compensation agent with high specific capacity(347.9 mAh g^(-1)),lower desodiation potential(2.4–2.8 V)and high utilization(99%).Meanwhile,its byproduct could functionalize HC with more C]O groups and promote its reversible ***,the presodiation hard carbon(pHC)anode exhibits highly reversible capacity of 204.7 mAh g^(-1) with 98%retention at 5 C rate over 1000 ***,with 5 wt%NaDB initially coated on the Na3V2(PO4)3(NVP)cathode,the capacity retention of NVP t NaDBjHC cell could increase from 22%to 89%after 1000 cycles at 1 C *** work provides a new avenue to improve reversible capacity and cycling performance of SIBs through designing functional cathode compensation agent.

关键词： Hard carbon ICE Cathode compensation agent Reversible capacity Stability

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Role of iron ore in enhancing gasification of iron coke:Structural evolution,influence mechanism and kinetic analysis

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 58-69页

作者： Jie Wang Wei Wang Xuheng Chen Junfang Bao Qiuyue Hao Heng Zheng Runsheng Xu school of Chemistry and Materials science Hubei Engineering UniversityXiaogan 432000China Key Laboratory for Ferrous Metallurgy and Resources Utilization of Ministry of education Wuhan University of Science and TechnologyWuhan 430081China Institue of Ironmaking technology Baosteel Central Research InstituteShanghai 201999China State Key Laboratory of Advanced Metallurgy University of Science and Technology BeijingBeijing 100083China

The utilization of iron coke provides a green pathway for low-carbon *** uncover the influence mechanism of iron ore on the behavior and kinetics of iron coke gasification,the effect of iron ore on the microstructure of iron coke was ***,a comparative study of the gasification reactions between iron coke and coke was conducted through non-isothermal thermogravimetric *** findings indicate that compared to coke,iron coke exhibits an augmentation in micropores and specific surface area,and the micropores further extend and *** provides more adsorption sites for CO_(2) molecules during the gasification process,resulting in a reduction in the initial gasification temperature of iron *** the heating rate in non-isothermal gasification can enhance the reactivity of iron *** metallic iron reduced from iron ore is embedded in the carbon matrix,reducing the orderliness of the carbon structure,which is primarily responsible for the heightened reactivity of the carbon *** kinetic study indicates that the random pore model can effectively represent the gasification process of iron coke due to its rich pore ***,as the proportion of iron ore increases,the activation energy for the carbon gasification gradually decreases,from 246.2 kJ/mol for coke to 192.5 kJ/mol for iron coke 15wt%.

关键词： low-carbon ironmaking iron coke gasification structural evolution kinetic model

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Sequence-activated chemiluminescence probes: programmable illumination for high-contrast in vivo sensing and imaging

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science China Chemistry 2025年第1期68卷 26-34页

作者： Yutao Zhang Juan Li Wei-Hong Zhu Zhiqian Guo shanghai Key Laboratory of Functional Materials Chemistry Joint International Research Laboratory of Precision Chemistry and Molecular Engineering Institute of Fine Chemicals School of Chemistry and Molecular Engineering East China University of Science and Technology State Key Laboratory of Bioreactor Engineering Shanghai Frontier Science Research Base of Optogenetic Techniques for Cell MetabolismEast China University of Science & Technology

Sequence-activated chemiluminescence(CL) technique offers a unique approach to detecting specific biomolecules or cellular events with high sensitivity and spatial resolution. The fundamental principle behind sequence-activated CL probes involves tailoring highly-controllable CL signals in response to specific sequences or events of interest, thus enabling high-contrast signals under complex physiological conditions. This sequential activation could be triggered by enzymes, reactive oxygen species(ROS), biothiols or changes in the microenvironment. These unique sequence-activated CL probes bestow several advantages, including minimal background, deep-tissue penetration, and the ability of non-invasive or minimally invasive detection. The sequence-activated CL techniques represent a significant advancement in molecular imaging and diagnostics. In this mini-review, we focus on the latest developments in sequential CL probes, addressing the technical challenges and discussing the future trajectory by harnessing CL signaling and molecular recognition.

关键词： chemiluminescnece sequence-activation in-vivo bioimaging cyclic peroxide

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Evolutionary Particle Swarm Optimization Algorithm Based on Collective Prediction for Deployment of Base Stations

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computers, Materials & Continua 2025年第1期82卷 345-369页

作者： Jiaying Shen Donglin Zhu Yujia Liu Leyi Wang Jialing Hu Zhaolong Ouyang Changjun Zhou Taiyong Li school of computer science and technology Zhejiang Normal UniversityJinhua321004China school of Future Technologies Jiangxi Institute of Applied Science and TechnologyNanchang330000China school of Computing and Artificial Intelligence Southwestern University of Finance and EconomicsChengdu611130China

The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real *** development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of *** a specific area,achieving higher signal coverage with fewer base stations has become an urgent ***,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as *** a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by *** also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization *** better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base *** experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches *** results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and *** ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.

关键词： Particle swarm optimization effective coverage area global optimization base station deployment

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Industrial Control Anomaly Detection Based on Distributed Linear Deep Learning

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computers, Materials & Continua 2025年第1期82卷 1129-1150页

作者： Shijie Tang Yong Ding Huiyong Wang school of computer science and Information Security Guilin University of Electronic TechnologyGuilin541004China school of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin541004China Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic TechnologyGuilin541004China institute of Cyberspace technology HKCT Institute for Higher EducationHong Kong999077China school of Mathematics&Computing science Guilin University of Electronic TechnologyGuilin541004China

As more and more devices in Cyber-Physical Systems(CPS)are connected to the Internet,physical components such as programmable logic controller(PLC),sensors,and actuators are facing greater risks of network attacks,and fast and accurate attack detection techniques are *** key problem in distinguishing between normal and abnormal sequences is to model sequential changes in a large and diverse field of time *** address this issue,we propose an anomaly detection method based on distributed deep *** method uses a bilateral filtering algorithm for sequential sequences to remove noise in the time series,which can maintain the edge of discrete *** use a distributed linear deep learning model to establish a sequential prediction model and adjust the threshold for anomaly detection based on the prediction error of the validation *** method can not only detect abnormal attacks but also locate the sensors that cause *** conducted experiments on the Secure Water Treatment(SWAT)and Water Distribution(WADI)public *** experimental results show that our method is superior to the baseline method in identifying the types of attacks and detecting efficiency.

关键词： Anomaly detection CPS deep learning MLP(multi-layer perceptron)

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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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Establishment of human cerebral organoid systems to model early neural development and assess the central neurotoxicity of environmental toxins

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Neural Regeneration Research 2025年第1期20卷 242-252页

作者： Daiyu Hu Yuanqing Cao Chenglin Cai Guangming Wang Min Zhou Luying Peng Yantao Fan Qiong Lai Zhengliang Gao Fundamental Research Center Shanghai Yangzhi Rehabilitation Hospital(Shanghai Sunshine Rehabilitation Center)School of MedicineTongji UniversityShanghaiChina institute of Geriatrics(shanghai University) Affiliated Nantong Hospital of Shanghai University(The Sixth People’s Hospital of Nantong)Shanghai University School of MedicineNantongJiangsu ProvinceChina shanghai Engineering Research Center of Organ Repair Shanghai University School of MedicineShanghaiChina Key Laboratory of Arrhythmias Ministry of EducationShanghai East HospitalSchool of MedicineTongji UniversityShanghaiChina

Human brain development is a complex process,and animal models often have significant *** address this,researchers have developed pluripotent stem cell-derived three-dimensional structures,known as brain-like organoids,to more accurately model early human brain development and *** enable more consistent and intuitive reproduction of early brain development,in this study,we incorporated forebrain organoid culture technology into the traditional unguided method of brain organoid *** involved embedding organoids in matrigel for only 7 days during the rapid expansion phase of the neural epithelium and then removing them from the matrigel for further cultivation,resulting in a new type of human brain organoid *** cerebral organoid system replicated the temporospatial characteristics of early human brain development,including neuroepithelium derivation,neural progenitor cell production and maintenance,neuron differentiation and migration,and cortical layer patterning and formation,providing more consistent and reproducible organoids for developmental modeling and toxicology *** a proof of concept,we applied the heavy metal cadmium to this newly improved organoid system to test whether it could be used to evaluate the neurotoxicity of environmental *** organoids exposed to cadmium for 7 or 14 days manifested severe damage and abnormalities in their neurodevelopmental patterns,including bursts of cortical cell death and premature *** exposure caused progressive depletion of neural progenitor cells and loss of organoid integrity,accompanied by compensatory cell proliferation at ectopic *** convenience,flexibility,and controllability of this newly developed organoid platform make it a powerful and affordable alternative to animal models for use in neurodevelopmental,neurological,and neurotoxicological studies.

关键词： cadmium cell death cell proliferation cortical development environmental toxins neural progenitor cells neurogenesis neurotoxicology organoids stem cells

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