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Personalized federated few-shot node classification

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Science China(Information Sciences) 2025年第1期68卷 204-218页

作者： Yunfeng zhao Xintong HE Guoxian YU Jun wang Yongqing zheng Carlotta DOMENICONI School of Software Shandong University Joint SDU-Ntu Centre for Artificial Intelligence Research Shandong University Department of Mathematics National University of Singapore Department of Computer Science George Mason University

Personalized federated learning(PFL) aims to train customized models for individual clients in a decentralized setting, with the account of non-independent and identically distributed data across clients. However, most PFL methods adopt uniform classification layers for diverse clients and give rise to error-prone predictions, due to the task heterogeneity notably prominent in decentralized graph data scenarios. Although some PFL solutions setup client-specific classification layers for each client and optimize them only locally, they are corrupted with limited local training data. We propose an innovative solution called federated parameter decoupling and node augmentation(Fed PANo) to address these problems and to achieve personalized federated few-shot node classification, which is a prevalent and challenging but unexplored topic. Specifically, Fed PANo first separates the local model into the GNN and classifier to handle unique client-specific task variations. The GNN is trained through federated learning to capture shared knowledge of graph nodes across clients, while the classifier is custom-designed and trained individually for each client. Additionally, a generic classifier shared among clients is adopted to encourage the GNN's grasp of shared information. Then Fed PANo further proposes the node generator along with its local and collaborative training strategies to deal with the node scarcity of clients. Extensive experimental results on benchmark datasets confirm that Fed PANo outperforms eight competitive baselines across different settings.

关键词： personalized federated learning few-shot learning node classification task heterogeneity parameter decoupling node augmentation

The complex roles of m^(6)A modifications in neural stem cell proliferation, differentiation, and self-renewal and implications for memory and neurodegenerative diseases

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Neural Regeneration Research 2025年第6期20卷 1582-1598页

作者： Yanxi Li Jing Xue Yuejia Ma Ke Ye Xue zhao Fangliang Ge Feifei zheng Lulu liu Xu Gao Dayong wang qing Xia Department of Biochemistry and Molecular Biology College of Basic Medical SciencesHarbin Medical UniversityHarbinHeilongjiang ProvinceChina College of Basic Medical Sciences Harbin Medical UniversityHarbinHeilongjiang ProvinceChina Basic Medical Institute Heilongjiang Academy of Medical SciencesHarbinHeilongjiang ProvinceChina Key Laboratory of Heilongjiang Province for Genetically Modified Animals Harbin Medical UniversityHarbinHeilongjiang ProvinceChina Translational Medicine Research and Cooperation Center of Northern China Heilongjiang Academy of Medical SciencesHarbinHeilongjiang ProvinceChina Dongzhimen Hospital Beijing University of Chinese MedicineBeijingChina

N6-methyladenosine(m^(6)A), the most prevalent and conserved RNA modification in eukaryotic cells, profoundly influences virtually all aspects of mRNA metabolism. mRNA plays crucial roles in neural stem cell genesis and neural regeneration, where it is highly concentrated and actively involved in these processes. Changes in m^(6)A modification levels and the expression levels of related enzymatic proteins can lead to neurological dysfunction and contribute to the development of neurological diseases. Furthermore, the proliferation and differentiation of neural stem cells, as well as nerve regeneration, are intimately linked to memory function and neurodegenerative diseases. This paper presents a comprehensive review of the roles of m^(6)A in neural stem cell proliferation, differentiation, and self-renewal, as well as its implications in memory and neurodegenerative diseases. m^(6)A has demonstrated divergent effects on the proliferation and differentiation of neural stem cells. These observed contradictions may arise from the time-specific nature of m^(6)A and its differential impact on neural stem cells across various stages of development. Similarly, the diverse effects of m^(6)A on distinct types of memory could be attributed to the involvement of specific brain regions in memory formation and recall. Inconsistencies in m^(6)A levels across different models of neurodegenerative disease, particularly Alzheimer's disease and Parkinson's disease, suggest that these disparities are linked to variations in the affected brain regions. Notably, the opposing changes in m^(6)A levels observed in Parkinson's disease models exposed to manganese compared to normal Parkinson's disease models further underscore the complexity of m^(6)A's role in neurodegenerative processes. The roles of m^(6)A in neural stem cell proliferation, differentiation, and self-renewal, and its implications in memory and neurodegenerative diseases, appear contradictory. These inconsistencies may be a

关键词： Alzheimer's disease cell self-renewal central nervous system memory microglia nerve regeneration neurodegenerative diseases neurogenesis RNA methylation

High-precision magnetic field measurement system based on a coherent population trapping magnetometer onboard the SATech-01 satellite

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Science China Technological Sciences 2025年

作者： Hongbo XUE Wei SONG Haoran zhao Yiteng ZHANG Shanzhi YE Jindong wang Ran TAO Peng SANG Keli CHEN Xingzi BI Bingjun CHENG Bin ZHOU Yongliang XUE Yingying TANG liu liu Jinsong LI Xiaocheng ZHU baoquan LI Jinguo liu Wen CHEN Xiaofeng ZHANG Yonghe ZHANG Lei LI State Key Laboratory of Space Weather National Space Science Center Chinese Academy of Sciences Key Laboratory of Solar Activity and Space Weather National Space Science Center Chinese Academy of Sciences Key Laboratory of Electronics and Information Technology for Space Systems National Space Science Center Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Innovation Academy for Microsatellites Chinese Academy of Sciences

On July 27, 2022, a high-precision system for measuring the magnetic field based on a coherent population trapping magnetometer（referred to as the CPT system） was launched onboard the Space Advanced Technology demonstration satellite（SATech-01） by a ZK-1A rocket. The payload comprises a scalar coherent population trapping magnetometer（CPTM）, triaxial anisotropic magnetoresistance magnetometer（AMRM）, and nano star tracker mounted on a non-magnetic telescopic tubular mast. This configuration enables synchronized measurement of scalar and vector geomagnetic fields, as well as the attitude,making the payload with its compact sensors suitable for applications on miniature satellite platforms. On November 7, 2022,the novel telescopic tubular mast was deployed in orbit, extending to a length of 5.28 m. The CPTM, an absolute scalar magnetometer with an omnidirectional sensor, is the first China-developed quantum/atomic magnetometer successfully operating in space. In orbit, the CPTM has sensitivity of ～10 pT/Hz1/2and can automatically operate under complex magnetic field variations. The difference between the scalar fields obtained using the CPTM and CHAOS model has a mean deviation of–3.73 n T and a standard deviation of 26.11 nT（1σ）, without on-orbit calibration or correction. The miniaturized AMRM has a sensitivity of ～0.3 n T/Hz1/2and maintains stable and reliable operation in orbit. The low-power and miniaturized nano star tracker has a measurement uncertainty of 14.23″（1σ） in orbit. The mission has realized the on-orbit technical verification of the integrated and synchronized detection of the vector magnetic field and attitude and fully validated the system's performance,automation level, and reliability.

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Precise gradient separation of nanoparticles using reduced graphene oxide-polyoxomolybdate membranes

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Science China Chemistry 2025年第1期68卷 209-216页

作者： Yixin Yang Wanlei zhao Ruoxuan zheng Hongqiang Li Wei Chen Yu-Fei Song State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical Technology Quzhou Institute for Innovation in Resource Chemical Engineering

The purification and size sieving of nanoparticles （NPs） represents a significant scientific ***,the r GO-polyoxometalates (POMs=PMo12,Mo132and Mo368) membranes were fabricated successfully via a simple and scalable POMsassisted in-situ photoreduction *** the mass ratio of r GO to PMo12was 1:30,the resultant r GO-PMo12membranes with highly ordered and uniform nanochannels of 1.0 nm can be obtained,which showed an accurate carbon quantum dots（CQDs） separation with a cut-off size approximately 1.0 *** increase of the size of the interlayered POMs from PMo12（1.0 nm）,{Mo132}（2.9 nm） to{Mo368}（3.8 nm）,the resultant r GO-PMo12,r GO-Mo132and r GO-Mo368exhibited precise gradient separation of CQDs and Au nanoparticles by size exclusion *** results pave a promising way to construct new twodimensional （2D） membranes for highly efficient size-selective separation.

关键词： reduced graphene oxide polyoxometalates membranes gradient separation nanoparticles

Short-term Photovoltaic Power Prediction Based on Feature Optimization and Hybrid Improved Grey Wolf Algorithm-optimized BiLSTM Network

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Dianwang Jishu/Power System Technology 2025年第1期49卷 209-222页

作者： zhao, Ruyi wang, Xiaohui zheng, Bihuang Li, Daoxing Gao, Yi Guo, Pengtian China Electric Power Research Institute Haidian District Beijing 100192 China Economic and Technological Research Institute State Grid Tianjin Electric Power Company Hedong District Tianjin 300171 China

To address the challenges posed by strong noise interference in photovoltaic (PV) sequences and the issues of low accuracy and poor generalization of a single model in PV power prediction, we propose a short-term PV power prediction method. This method uses feature optimization and a hybrid improved Grey Wolf algorithm to optimize the BiLSTM network. Firstly, the mutual information algorithm is employed for variable selection in input data to eliminate redundant variables. Subsequently, the Complementary Ensemble Empirical Mode Decomposition and an improved wavelet threshold algorithm are applied to the selected data for feature reconstruction to reduce noise interference in the data and optimize input variable features. Finally, the standard Grey Wolf Optimizer algorithm underwent hybrid optimization by integrating improved Tent chaotic mapping, nonlinear decreasing factors, dynamic weight strategies, and the differential evolution algorithm. This process aimed to ascertain the optimal hyperparameter combination for the BiLSTM network. The attention mechanism was also employed to extract key temporal information from the data, developing a novel short-term photovoltaic power prediction model. Simulation experiments demonstrate that, compared to the least squares support vector machine, long short-term memory network, and bidirectional long short-term memory neural network, the proposed model achieves an average reduction of 12.45%, 7.95%, and 5.37% in root mean square error under various weather conditions such as sunny, cloudy, overcast, and rainy, showcasing excellent predictive performance, good generalization ability, and promising engineering application value. © 2025 Power System Technology Press. All rights reserved.

关键词： Mean square error

Study of thermal decoherence of harmonic oscillators

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原子与分子物理学报 2025年第5期42卷 108-114页

作者： LI Jian ZHOU Gao-Liang YAN zheng-Xin liu Wei wang zhao-Qi College of Science Xi’an University of Science and TechnologyXi’an 710054China

The thermal decoherence of harmonic oscillators is investigated *** quantum system presented here is a one-dimensional oscillator with angular frequency,which is surrounded by a thermal bath of environmental *** are various environmental oscillators with different angular frequency(below an ultraviolet cutoff).At the beginning,the quantum system is a pure state and the environmental oscillators are in thermodynamic equilibrium with *** a period,the system-environment interactions inspire significant decoherence of the quantum *** decoherence is displayed by explicit calculations of the purity and von Neumann entropy of the quantum *** is worth noting that the decoherence could be significant even in the weak coupling and low temperature case due to the large amount of environmental degrees of *** the decoherence process is inspired between the quantum system and an ordinary thermal environment here,the thermal decoherence result is quite general.

关键词： Quantum decoherence Grand canonical ensemble Oscillators

A stretchable, ionic conductive, and adhesive patch electrode with ultra-low on-skin impedance for electrophysiological signal recording

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Science China(Information Sciences) 2025年

作者： Yang LI Yuzhe GU Sheng QIAN Yuncong PANG Aoxi YU Shuwen zheng Wenjie XIA Yuan LIAO Baoguang liu Shujuan liu Qiang zhao College of Electronic and Optical Engineering & College of Flexible Electronics (Future Technology) Nanjing University of Posts & Telecommunications (NJUPT) State Key Laboratory of Organic Electronics and Information Displays & Jiangsu Key Laboratory for Biosensors Institute of Advanced Materials (IAM) Nanjing University of Posts & Telecommunications (NJUPT)

Flexible electrodes have significant potential in fields such as healthcare and neuroscience, as they enable comprehensive recording and analysis of human electrical signals, providing deeper insights into physiological conditions and the state of internal organs and tissues [1, 2]. However, commercial Ag/AgCl wet electrodes face issues such as dehydration,poor comfort, and insufficient mechanical strength, while other types of electrodes, like dry and semi-dry electrodes,also have their own limitations, including the higher contact impedance. In contrast, ionically conductive electrodes offer potential advantages such as transparency, stability, and low impedance, making them a promising alternative to existing electrically conductive electrodes [3]. Acrylic acid (AA)and 2-acrylamido-2-methylpropanesulfonic acid (AMPS) are commonly used in the synthesis of ionic gels, as they ionize in water to produce a large number of ions, helping to maintain moisture balance and reduce impedance caused by dehydration [4]. However, the presence of freely moving ions in the gel network can interfere with conductivity, highlighting the need to introduce new conductive networks to enhance performance [5].

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Multifunctional nucleic acid nanostructures for gene therapies

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Nano Research 2018年第10期11卷 5017-5027页

作者： Jianbing liu zhengang wang Shuai zhao baoquan Ding CAS Key Laboratory of Nanosystem and Hierarchical Fabrication CAS Center for Excellence in Nanoscience National Center for Nanoscience and Technology Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China

Nucleic acid nanotechnology has been developed to be a promising strategy to construct various nano-biomaterials with structural programmability, spatial addressability, and excellent biocompatibility. Self-assembled nucleic acid nanostructures have been employed in a variety of biomedical applications, such as bio-imaging, diagnosis, and therapeutics. In this manuscript, we will review recent progress in the development of multifunctional nucleic acid nanostructures as gene drug delivery vehicles. Therapeutic systems based on RNA interference （RNAi）, clustered regularly interspaced short palindromic repeat associated proteins 9 system （CRISPR/Cas9） genome editing, gene expression, and CpG-based immunostimulation will be highlighted. We will also discuss the challenges and future directions of nucleic acid nanotechnology in biomedical research.

关键词： nucleic acid nanostructure nucleic acid drug gene therapy drug delivery multifunctional nanomaterials

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风筛组合式花生秧粉碎除膜机设计与试验

农机化研究 2025年第2期47卷 159-164页

作者：刘勇郑孟坤赵福勇王家胜青岛农业大学机电工程学院山东青岛266109 日照市勇杰农业装备有限公司山东日照263318

针对覆膜种植的花生收获后的地膜残留于饲料用花生秧严重影响牲畜健康的问题,结合粉碎后的花生秧与地膜的物理特性,设计了一种花生秧粉碎除膜机,可一次完成喂料粉碎、筛分输送、负压除膜、回料输送、出料收集等功能。对整机的关键部件... 详细信息

针对覆膜种植的花生收获后的地膜残留于饲料用花生秧严重影响牲畜健康的问题,结合粉碎后的花生秧与地膜的物理特性,设计了一种花生秧粉碎除膜机,可一次完成喂料粉碎、筛分输送、负压除膜、回料输送、出料收集等功能。对整机的关键部件进行了设计与分析,重点确定了粉碎装置、风筛式清选装置等部件的结构与工作参数。利用Design-Expert进行了试验设计,研究了振动筛频率、风机转速对花生秧残膜清选质量的影响,并对花生秧粉碎除膜机的工作参数进行了优化。试验结果表明:振动筛频率、风机转速对除膜率和损失率影响显著;当最优参数振动筛频率3.4 Hz、1号风机转速1000 r/min、2号风机转速1350 r/min、3号风机转速1500 r/min时,花生秧粉碎除膜机除膜率为96.8%,损失率为11.2%,实现花生秧中残膜的清选。

关键词：花生秧除膜风筛式