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First observation results of Macao Science Satellite-1 on lightning-induced electron precipitation

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Science China Earth Sciences 2025年第1期68卷 1-10页

作者： Yongping wang Yixin SUN Qiugang ZONG Gaopeng LU Xudong GU ze-Jun HU Bin LI Key Laboratory for Polar Science Ministry of Natural Resources Polar Research Institute of China Institute of Space Physics and Applied Technology Peking University State Key Laboratory of Lunar and Planetary Science Macau University of Science and Technology School of Earth and Space Sciences University of Science and Technology of China School of Electronic Information Wuhan University

The Medium-energy Electron Spectrometers(MES) is a space-borne instrument onboard Macao Science Satellite-1(MSS-1) dedicated to monitoring the typical charged particle radiation characteristics in the satellite orbit and the process of their occurrence and development, including short bursts of lightning-induced electron precipitation(LEP).This paper presents the first results of the LEP measurements by the MSS-1.47 LEP events are identified with the routine operation for 3 months since satellite launch, all within the range of 1.5

关键词： Lightning-induced electron precipitation Inner radiation belts Energetic electrons Macao Science Satellite-1

MXene Hybridized Polymer with Enhanced Electromagnetic Energy Harvest for Sensitized Microwave Actuation and Self‑Powered Motion Sensing

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Nano-Micro Letters 2025年第3期17卷 265-279页

作者： Yu‑ze wang Yu‑Chang wang Ting‑Ting Liu Quan‑liang Zhao Chen‑Sha Li Mao‑Sheng Cao School of Materials Science and Engineering Beijing Institute of TechnologyBeijing 100081People’s Republic of China School of Materials Science and Engineering Peking UniversityBeijing 100871People’s Republic of China School of Mechanical and Material Engineering North China University of TechnologyBeijing 100144People’s Republic of China Key Laboratory of Functional Inorganic Material Chemistry Ministry of Education of the People’s Republic of ChinaHeilongjiang UniversityHarbin 150080People’s Republic of China

Polymeric microwave actuators combining tissue-like softness with programmablemicrowave-responsive deformation hold great promise for mobile intelligentdevices and bionic soft robots. However, their application is challenged by restricted electromagneticsensitivity and intricate sensing coupling. In this study, a sensitized polymericmicrowave actuator is fabricated by hybridizing a liquid crystal polymer with Ti3C2Tx(MXene). Compared to the initial counterpart, the hybrid polymer exhibits unique spacechargepolarization and interfacial polarization, resulting in significant improvements of230% in the dielectric loss factor and 830% in the apparent efficiency of electromagneticenergy harvest. The sensitized microwave actuation demonstrates as the shortenedresponse time of nearly 10 s, which is merely 13% of that for the initial shape memory polymer. Moreover, the ultra-low content of MXene (upto 0.15 wt%) benefits for maintaining the actuation potential of the hybrid polymer. An innovative self-powered sensing prototype that combinesdriving and piezoelectric polymers is developed, which generates real-time electric potential feedback (open-circuit potential of ~ 3 mV) duringactuation. The polarization-dominant energy conversion mechanism observed in the MXene-polymer hybrid structure furnishes a new approachfor developing efficient electromagnetic dissipative structures and shows potential for advancing polymeric electromagnetic intelligent devices.

关键词： Microwave absorption Electromagnetic response Energy harvest Self-sensing Soft actuator

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Multi-party quantum private comparison of size relationship based on one-direction quantum walks on a circle

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Science China(Information Sciences) 2025年

作者： Jintao wang Jiangyuan lian Tianyu YE College of Information & Electronic Engineering Zhejiang Gongshang University

Quantum walks (QW) are the quantum counterpart of classical random walks, and portray a natural stochastic process when the walker randomly wanders around. In a discretetime QW system on a circle, when the walker particle generally steps towards two directions, i.e., clockwise and anticlockwise, this kind of QW is called two-direction quantum walks on a circle (TDQWC); and the walker particle always steps towards one direction or stays stationary, this kind of QW is called as one-direction quantum walks on a circle (ODQWC).

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Identification of a dual functional betulinic acid analog for the treatment of osteoarthritis by phenotypic screening

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Science China Life Sciences 2025年第1期68卷 300-302页

作者： ze-Min Lin Mai Xiang Wen-Hui Wei Shu-Hui Fan Li Chen Jie wang Xiao-Qian Yang Chun-Hao Yang Shi-Jun He Jian-Ping Zuo Laboratory of Immunopharmacology State Key Laboratory of Drug ResearchShanghai Institute of Materia MedicaChinese Academy of Sciences School of Pharmacy University of Chinese Academy of Sciences School of Pharmacy Nanjing University of Chinese Medicine State Key Laboratory of Drug Research Department of Medicinal ChemistryShanghai Institute of Materia MedicaChinese Academy of Sciences Innovation Research Institute of Traditional Chinese Medicine Shanghai University of Traditional Chinese Medicine Experiment Center for Science and Technology Shanghai University of Traditional Chinese Medicine

Dear Editor, Phenotypic drug discovery, which observes compound effects on physiology,has given way to targeting specific molecules, but has revived by using modern methods to find drugs based on therapeutic outcomes in disease models(Vincent et al., 2022). Osteoarthritis(OA) is a prevalent chronic joint disorder, primarily affecting knee joints, with osteoclast activation due to low-grade inflammation resulting in increased bone resorption and structural changes in the joint(Katz et al.,2021).

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A dry-electrode enabled ECG-on-Chip with arrhythmia-aware data transmission

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Science China(Information Sciences) 2025年

作者： Xinzi XU Yanxing SUO Yang ZHAO Peiyi ZHOU Xiao HAN Qiao CAI Min wang Jiajun YUAN Liebin ZHAO Yongfu LI Guoxing wang Yong lian Department of Micro-Nano Electronics and MoE Key Lab of Artificial Intelligence Shanghai Jiao Tong University Pediatric AI Clinical Application and Research Center Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP) Child Health Advocacy Institute Shanghai Children's Medical Center School of MedicineShanghai Jiao Tong University Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP) Xin Hua Hospital Affiliate to Shanghai Jiao Tong University School of Medicine

Early detection and treatment of cardiovascular diseases (CVDs) can be significantly enhanced through the use of flexible wearable electrocardiogram (ECG) sensors, potentially reducing CVD-related mortality. This paper introduces an ECG-on-Chip (EoC) solution tailored for flexible ECG sensors, incorporating novel features to address common challenges in wearable ECG technology. The EoC integrates a chopper-stabilized capacitively-coupled instrumentation amplifier (CS-CCIA),ensuring a high common-mode rejection ratio (CMRR) and low noise performance. Performance is further boosted via a positive feedback loop (PFL) and a programmable gain amplifier (PGA) with shared on-chip calibration logic, which enhances input impedance and minimizes gain variability to ensure consistent algorithm performance. Additionally, a secondary chopping technique is employed to further reduce noise, achieving an input-referred noise level of 454 nVrms. The embedded algorithm within the EoC is designed to extract clinically meaningful features, facilitating robust real-time arrhythmia analysis. Fabricated using a 0.18μm CMOS process, the EoC consumes 14.9μW with a supply voltage of 1.2 V. The algorithm’s efficacy has been validated over 0.4 million heartbeats, demonstrating a sensitivity of over 99.7%for R-peak detection and 98.3%for arrhythmia analysis. To demonstrate practical application, the EoC has been integrated with a commercial Bluetooth low energy (BLE)transceiver, forming a wireless arrhythmia monitoring sensor equipped with dry electrodes. This system consumes 292.04μW in arrhythmia-aware transmission mode, supporting 13 days of operation with a 30 mAh thin-film battery.

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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

Dual modulation of homogeneous nanomaterialization and electrochemical activation enhancing zinc ion storage

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Science China Chemistry 2025年第1期68卷 385-393页

作者： Jianwei wang Huan wang Kangning wang Wenhui wang Wenlin Zhang Yanzhong Zhen School of Chemistry & Chemical Engineering Yan'an University

Vanadium-based electrode materials are widely investigated,but the low specific capacity and slow electrochemical kinetics in aqueous zinc-ion batteries still limit their commercial ***,the VS2/Ca V4O9material with the morphology of nanoflower was synthesized by a one-step hydrothermal *** to the blocky structure of pure VS2material,the VS2/Ca V4O9material is composed of thinner homogeneous *** open structures could provide abundant electrochemical active sites and ion transport channels,and then promote the electrochemical reaction *** addition,they can also buffer the bulk strain during the reaction *** improve the utilization of vanadium elements,an in-situ electrochemical activation strategy is used to explore the storage performance of the VS2/Ca V4O9material,the different activation voltage range of 0.4–1.6 and 0.4–1.4 V are selected,*** with the longer activation plateau of activated-VS2,the VS2/Ca V4O9cathode could quickly reach the activation state in the range of 1.4–1.6 V and cause the release of additional Zn storage sites *** VS2/Ca V4O9cathode delivers a higher power density of 37,000 W kg-1and a significant energy density of 423 Wh *** the high current density of 15 A g-1,the VS2/Ca V4O9cathode still has a discharge capacity of 183.9m Ah g-1after 5,000 cycles,and the capacity decay rate per cycle is only 0.0042%.Continuous cyclic voltammetry （CV） curves,electrochemical impedance spectroscopy （EIS） measurements,density functional theory （DFT） calculation and galvanostatic intermittent titration technique （GITT） measurements demonstrate that the VS2/Ca V4O9cathode has a faster ion diffusion/charge transfer ***,the assembled flexible device has an excellent mechanical stability.

关键词： dual modulation homogeneous nanomaterialization electrochemical activation zinc ion storage

An Iterated Greedy Algorithm with Memory and Learning Mechanisms for the Distributed Permutation Flow Shop Scheduling Problem

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Computers, Materials & Continua 2025年第1期82卷 371-388页

作者： Binhui wang Hongfeng wang College of Information Science and Engineering Northeastern UniversityShenyang110819China

The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent *** iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because of its straightforward,single-solution evolution ***,a potential draw-back of IGA is the lack of utilization of historical information,which could lead to an imbalance between exploration and exploitation,especially in large-scale *** a consequence,this paper develops an IGA with memory and learning mechanisms(MLIGA)to efficiently solve the DPFSP targeted at the ***,we incorporate a memory mechanism to make a more informed selection of the initial solution at each stage of the search,by extending,reconstructing,and reinforcing the information from previous *** addition,we design a twolayer cooperative reinforcement learning approach to intelligently determine the key parameters of IGA and the operations of the memory ***,to ensure that the experience generated by each perturbation operator is fully learned and to reduce the prior parameters of MLIGA,a probability curve-based acceptance criterion is proposed by combining a cube root function with custom *** last,a discrete adaptive learning rate is employed to enhance the stability of the memory and *** ablation experiments are utilized to verify the effectiveness of the memory mechanism,and the results show that this mechanism is capable of improving the performance of IGA to a large ***,through comparative experiments involving MLIGA and five state-of-the-art algorithms on 720 benchmarks,we have discovered that MLI-GA demonstrates significant potential for solving large-scale *** indicates that MLIGA is well-suited for real-world distributed flow shop scheduling.

关键词： Distributed permutation flow shop scheduling makespan iterated greedy algorithm memory mechanism cooperative reinforcement learning

Controlled cationic ring-opening polymerization of L-lactide by organic ion pair: novel approach to isotactic-rich and crystalline polylactide

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Science China Chemistry 2025年第1期68卷 394-402页

作者： Zhiqiang Ding Mingqian wang Zijing Zhou Bin wang Yuesheng Li Tianjin Key Laboratory of Composite & Functional Materials School of Materials Science and Engineering Tianjin University

Living/controlled cationic ring-opening polymerization （ROP） of L-lactide is a promising approach to isotactic-rich and crystalline poly（L-lactide）.In contrast with the unsubstituted lactones,L-LA can not be polymerized by organic Lewis acids or carbenium ions,and the state of the art in this field is the cationic ROP of L-LA catalyzed by Br?nsted acid/alcohol system via activated monomer ***,we reported the first example of controlled cationic ROP of L-LA by using Meerweintype ion pair[Me3O]+[B（C6F5）4]-as the catalyst.[Me3O]+[B（C6F5）4]-promoted rapid L-LA cationic polymerization in the absence of alcohol,producing isotactic-rich and crystalline PLLA without transesterification and epimerization side *** activated chain end mechanism,involving twice SN2 substitution and configuration-inversion （S→R→S） with the assistance of released Me2O,was proposed and further verified by density functional theory and control *** work expands the catalytic toolbox of isotactic-rich and crystalline polylactide *** represents a unique example of cationic-controlled polymerization of L-LA catalyzed by an organic ion pair.

关键词： organic ion pair controlled cationic ring-opening polymerization activated chain end mechanism isotactic-rich polylactide