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SSRN 2025年

作者： Yang, Zhen Xian, Jiawei Xu, Yuanji Lin, De-Ye Wang, Qingchun Gao, Xingyu Tian, Fuyang Song, Haifeng Institute for Applied Physics University of Science and Technology Beijing Beijing100083 China National Key Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing100094 China CAEP Software Center for High Performance Numerical Simulation Institute of Applied Physics and Computational Mathematics Beijing100094 China

The elasticity under varying temperatures and pressures is particularly significant for understanding mechanical properties and structural phase transitions. Consequently, there is an increasing demand for tools capable of determining elasticity across wide temperature and pressure ranges, either numerically or analytically. We propose HTEM, a comprehensive toolkit that automates the workflow for input generation, elastic calculations, modeling, and visualization within an integrated framework. HTEM performs simulations with four computational modes, allowing users to balance accuracy and efficiency. It incorporates a semi-analytic model for robust, high-precision elastic modeling with finite data combinations, even using sparse elasticity at high temperatures. To validate the workflows of calculation and modeling, we perform HTEM to study the elasticity of Si across wide temperature and pressure ranges. Results show the high precision and high efficiency of HTEM. And modeling mitigates noise from constant pressure ensemble simulations. Furthermore, HTEM provides detailed visualizations of elasticity and its anisotropy as functions of temperature and pressure, providing comprehensive insights into how the intrinsic properties of materials evolve under varying conditions. © 2025, The Authors. All rights reserved.

关键词： Elasticity

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A modeling framework for assessing the future changes in the occurrence of extreme rain-induced landslides

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Gondwana Research 2025年 143卷 52-63页

作者： Zhang, Xinlong Lin, Qigen Lok, Manhoi Huang, Taosheng Yu, Xuan Wang, Weiping Shen, Ping State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering University of Macau Macao SAR China Institute for Disaster Risk Management School of Geographical Sciences Nanjing University of Information Science & Technology Nanjing China Department of Civil and Environmental Engineering University of Macau Macao SAR China Center for Water Resources and Environment School of Civil Engineering Sun Yat-sen University Guangzhou China School of National Safety and Emergency Management Beijing Normal University Zhuhai China Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance Beijing Normal University Zhuhai China

Landslides triggered by extreme rainfall pose a serious threat to lives and livelihoods under climate change. However, the influence of climate change on the frequency and intensity of extreme rainfall and the resulting landslide hazard remains insufficiently investigated. Here we develop a novel framework to assess how future changes in extreme rainfall affect landslide occurrence, using a comprehensive dataset of landslide events in Guangdong province, China. We apply the XGBoost machine learning algorithm with a correction by feature interaction constraints to model landslide hazards based on various predisposing and triggering factors. We use a new extreme rainfall correction method to account for the global climate model-projected changes in rainfall patterns under different emission scenarios, based on which we perform a multi-model ensemble analysis to reduce the uncertainty of climate projections. We find that regions with high landslide probability are strongly associated with intense rainfall events, especially in steep and erodible river valleys. Our projections show that under a high-emission scenario, extreme rainfall events and landslide hazards will increase substantially in Guangdong, highlighting the urgency of adaptation of climate change and risk management. Our framework provides a valuable tool for understanding the interactions between climate change, extreme rainfall, and landslide occurrence, and for developing effective mitigation strategies. © 2025 International Association for Gondwana Research

关键词： Climate change Extreme rainfall Machine Learning Rain-induced landslides

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Single-cell omics: experimental workflow, data analyses and applications

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science China(Life sciences) 2025年第1期68卷 5-102页

作者： Fengying Sun Haoyan Li Dongqing Sun Shaliu Fu Lei Gu Xin Shao Qinqin Wang Xin Dong Bin Duan Feiyang Xing Jun Wu Minmin Xiao Fangqing Zhao Jing-Dong J.Han Qi Liu Xiaohui Fan Chen Li Chenfei Wang Tieliu Shi Department of Clinical Laboratory the Affiliated Wuhu Hospital of East China Normal University(The Second People’s Hospital of Wuhu City)Wuhu 241000China Pharmaceutical Informatics Institute College of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058China Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration(Tongji University) Ministry of EducationOrthopaedic DepartmentTongji HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji UniversityShanghai 200082China Frontier Science Center for Stem Cells School of Life Sciences and TechnologyTongji UniversityShanghai 200092China Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji UniversityShanghai 200082China Research Institute of Intelligent Computing Zhejiang LabHangzhou 311121China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai 201210China Center for Single-cell Omics School of Public HealthShanghai Jiao Tong University School of MedicineShanghai 200025China National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River DeltaZhejiang UniversityJiaxing 314103China Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghai 200241China Beijing Institutes of Life Science Chinese Academy of SciencesBeijing 100101China Peking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary StudiesCenter for Quantitative Biology(CQB)Peking UniversityBeijing 100871China Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases Women’s HospitalZhejiang University School of MedicineHangzhou 310006China Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of StatisticsEast China Normal U

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular *** exploration of how the genomes orchestrate the formation and maintenance of each cell,and control the cellular phenotypes of various organismsis,is both captivating and *** the inception of the first single-cell RNA technology,technologies related to single-cell sequencing have experienced rapid advancements in recent *** technologies have expanded horizontally to include single-cell genome,epigenome,proteome,and metabolome,while vertically,they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR ***-cell omics represent a groundbreaking advancement in the biomedical field,offering profound insights into the understanding of complex diseases,including ***,we comprehensively summarize recent advances in single-cell omics technologies,with a specific focus on the methodology *** overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

关键词： single-cell sequencing genome epigenome proteomics metabolomics multimodal spatial transcriptomics CRISPR screening

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Mission-oriented capability evaluation for combat network based on operation loops

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Defence technology（防务技术） 2024年第12期42卷 156-175页

作者： Yang Wang Junyong Tao Xiaoke Zhang Guanghan Bai Yunan Zhang Laboratory of Science and Technology on Integrated Logistics Support College of Intelligence Science and TechnologyNational University of Defense TechnologyChangsha 410073China National Key Laboratory for Complex Systems Simulation Beijing 100101China

With continuous growth in scale,topology complexity,mission phases,and mission diversity,challenges have been placed for efficient capability evaluation of modern combat *** at the problems of insufficient mission consideration and single evaluation dimension in the existing evaluation approaches,this study proposes a mission-oriented capability evaluation method for combat systems based on operation ***,a combat network model is given that takes into account the capability properties of combat ***,based on the transition matrix between combat nodes,an efficient algorithm for operation loop identification is proposed based on the Breadth-First *** the mission-capability satisfaction of nodes,the effectiveness evaluation indexes for operation loops and combat network are proposed,followed by node importance *** a case study of the combat scenario involving space-based support against surface ships under different strategies,the effectiveness of the proposed method is *** results indicated that the ROI-priority attack method has a notable impact on reducing the overall efficiency of the network,whereas the O-L betweenness-priority attack is more effective in obstructing the successful execution of enemy attack missions.

关键词： Combat network Operation loop identification Mission-oriented Network reliability Network effectiveness evaluation Strike strategies

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A bio-inspired PDA@MoS2 electrode with high conductivity and excellent antibacterial properties for selective and efficient uranium recovery via capacitive deionization

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Chemical Engineering Journal 2025年 514卷

作者： Zhang, Shuang Deng, Sheng Bo, Tao Li, Yuanli Zhao, Jiayin Wang, Yingcai Jiang, Hao Li, Xiaoyan Liu, Yuhui National Key Laboratory of Uranium Resources Exploration-Mining and Nuclear Remote Sensing East China University of Technology Nanchang330013 China Zhejiang Key Laboratory of Data-Driven High-Safety Energy Materials and Applications Ningbo Key Laboratory of Special Energy Materials and Chemistry Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution Chinese Research Academy of Environmental Sciences Beijing100012 China Innovation Center of Nuclear Environmental Safety Technology Southwest University of Science and Technology Mianyang621010 China

Capacitive deionization (CDI) has been identified as a promising method for uranium recovery due to its efficiency and rapidity. Nevertheless, challenges with electrode materials, including low conductivity, poor selectivity and antibacterial properties, remain to be addressed. This study presents a novel biomimetic electrode material, PDA@MoS2, designed for efficient uranium recovery through CDI. Inspired by natural adhesion mechanisms, the integration of PDA with MoS2 significantly enhances charge transportation, improves uranium selectivity, and imparts intrinsic antibacterial properties. CDI experiments revealed that PDA@MoS2-4 achieved an impressive 81.0 % uranium removal rate at 1.20 V and pH 5.0, significantly outperforming standalone MoS2 Density functional theory (DFT) calculations provided insights into the enhanced electrosorption and reduction mechanisms driving this performance. Beyond efficiency, PDA@MoS2 exhibited nearly 99.99 % antibacterial activity against Escherichia coli and Staphylococcus aureus, ensuring operational stability over an extended period. Remarkably, the material maintained consistent uranium extraction from radioactive ore leachates across 145.0 days. These findings position PDA@MoS2 as a sustainable, efficient, and environmentally friendly solution for uranium recovery, offering a transformative technology for environmental remediation and a reliable nuclear fuel supply. © 2025 Elsevier B.V.

关键词： Layered semiconductors

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Data-Driven Learning and Control with Event-Triggered Measurements

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IEEE Transactions on Automatic Control 2025年

作者： Feng, Shilun Shi, Dawei Chen, Tongwen Shi, Ling Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Kowloon Hong Kong

Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively learn unknown system dynamics from event-triggered measurements and consequently, develop a learning-based event-triggered controller. Existing works learn system dynamics based on periodic time-triggered measurements, and it is yet to know how to learn a controller with performance guarantee based on event-triggered measurements. To address this issue, we consider the problem of learning an event-triggered state feedback controller for an unknown linear system based on event-triggered state measurements in this work. In particular, we first analyze the event-triggered measurements within a set-membership framework. We prove that the estimation error belongs to a bounded ellipsoid determined by the historical measurements and the event-triggering condition. Subsequently, we demonstrate that all admissible systems compatible with the collected data samples can be explicitly represented in the form of quadratic matrix inequalities using the state estimates. With the acquired set of admissible systems, a co-design problem for the data-driven controller and event-triggering condition is solved using the linear matrix inequality technique, with guaranteed closed-loop stability and L2-gain performance. Finally, numerical examples and comparisons are provided to illustrate the effectiveness of the proposed event-triggered learning and control approach. © 1963-2012 IEEE.

关键词： Networked control systems

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A coevolutionary framework of business-IT alignment via the lens of enterprise architecture

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Journal of systems Engineering and Electronics 2020年第5期31卷 983-995页

作者： LIN Menglong YI Shuanghui ZHANG Mengmeng CHEN Tao CHEN Honghui ZHANG Xiaoxue Science and Technology on Information Systems Engineering Laboratory National University of Defense TechnologyChangsha 410072China National Key Laboratory for Complex System Simulation Academy of Military SciencesBeijing 100000China

Due to the turbulent external business environment, the complexity of internal relations of the organization and the emergence of subversive IT roles, the business-IT alignment(BITA)has become increasingly difficult. The unsuccessful realization of BITA will lead to the waste of organizational resources, the reduction of return on investment and eventually the loss of competitive advantage. In recent years, coevolution has received widespread attention due to its ability to describe the dynamic relationship between IT and business. Multiple principles such as quickening learning action loops and adopt suitable organizing principles for achieving business and IT coevolution(BITC) are obtained. However, the continuous BITC is still hard to be achieved because of the lack of complete BITC management. This paper focuses on the management process of the BITC and how to perform it gradually. A coevolution framework combines the enterprise architecture(EA) approach with the coevolution analysis is proposed, which contains the design of EA, the sensing and governance of the misalignment and the procedure of the EA misalignment *** steps for the governance and prevention of misalignment are discussed in particular. Through comparison with the principles,characteristics and methods of coevolution in the literature, the proposed framework is evaluated. The results show that the proposed framework is effective for BITC implementation.

关键词： business-IT alignment(BITA) coevolution misalignment governance misalignment prevention enterprise architecture

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Modeling the dynamic alignment of business and information systems via the lens of human-centered architecture evolution

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Journal of systems Engineering and Electronics 2021年第4期32卷 881-888页

作者： ZHANG Mengmeng YI Shuanghui CHEN Honghui LUO Aimin LIU Junxian ZHANG Xiaoxue Science and Technology on Information Systems Engineering Laboratory National University of Defense TechnologyChangsha 410072China National Key Laboratory for Complex System Simulation Military Academy of SciencesBeijing 100080China

The complexity of business and information systems(IS)alignment is a growing concern for researchers and practitioners *** extant research on alignment architecture fails to consider the human viewpoint,which makes it difficult to embrace emergent *** paper contributes to the extant literature in the following ***,we combine an enterprise architecture(EA)framework with a human viewpoint to address alignment issues in the architecture design phase;second,we describe a dynamic alignment model by developing a humancentered meta-model that explains first-and second-order changes and their effects on alignment *** paper provides better support for the theoretical research and the practical application of dynamic alignment.

关键词： business and information systems(IS)alignment human viewpoint enterprise architecture(EA) meta-model dynamic alignment

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Pre-Equalization Aided Grant-Free Massive Access in Massive MIMO System

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IEEE Transactions on Vehicular technology 2025年

作者： Wang, Yueqing Mei, Yikun Gao, Zhen Wan, Ziwei Ning, Boyu Mi, De Muhaidat, Sami School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology MIIT Key Laboratory of Complex-Field Intelligent Sensing Beijing100081 China Yangtze Delta Region Academy Jiaxing314019 China Beijing Institute of Technology Advanced Technology Research Institute Jinan250307 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Birmingham City University School of Computing and Digital Technology BirminghamB55JU United Kingdom Khalifa University KU 6 G Research Center Department of Computer and Information Engineering Abu Dhabi United Arab Emirates

The spatial diversity and multiplexing advantages of massive multi-input-multi-output (mMIMO) can significantly improve the capacity of massive non-orthogonal multiple access (NOMA) in machine type communications. However, state-of-the-art grant-free massive NOMA schemes for mMIMO systems require accurate estimation of random access channels to perform activity detection and the following coherent data demodulation, which suffers from excessive pilot overhead and access latency. To address this, we propose a pre-equalization aided grant-free massive access scheme for mMIMO systems, where an iterative detection scheme is conceived. Specifically, the base station (BS) firstly activates one of its antennas (i.e., beacon antenna) to broadcast a beacon signal, which facilitates the user equipment (UEs) to perform downlink channel estimation and pre-equalize the uplink random access signal with respect to the channels associated with the beacon antenna. During the uplink transmission stage, the BS detects UEs' activity and data by using the proposed iterative detection algorithm, which consists of three modules: coarse data detection (DD), data-aided channel estimation (CE), and fine DD. In the proposed algorithm, the joint activity and DD is firstly performed based on the signals received by the beacon antenna. Subsequently, the DD is further refined by iteratively performing data-aided CE module and fine DD module using signals received by all BS antennas. Our simulation results demonstrate that the proposed scheme outperforms state-of-the-art mMIMO-based grant-free massive NOMA schemes with the same access latency. © 1967-2012 IEEE.

关键词： Channel estimation

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A review on characteristics and synergistic behaviour of coal-biomass blends in co-pyrolysis process for bioenergy generation

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Carbon Letters 2025年 1-40页

作者： Khoja, Asif Hussain Hussain, Muzzamail Tauseef, Maham Naeem, Nida Khan, Arslan Akram, Ramza Khan, Tahreem Assad Ansari, Abeera Ayaz Zeng, Xi U.S.-Pakistan Centre for Advanced Studies in Energy (USPCAS-E) National University of Sciences and Technology (NUST) Sector H-12 Islamabad 44000 Pakistan Department of Chemical and Environmental Engineering (ChEE) University of Cincinnati Cincinnati 45221-0012 OH United States State Key Laboratory of Multi-Phase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing 100190 China Laboratory of Alternative Fuels and Sustainability School of Chemical and Materials Engineering National University of Sciences and Technology Islamabad 44000 H-12 Pakistan School of Interdisciplinary Engineering and Science (SINES) National University of Sciences and Technology (NUST) Sector H-12 Islamabad 44000 Pakistan School of Ecology and Environment Beijing Technology and Business University Beijing 100048 China

The environmental, social, and economic concerns regarding fossil fuels necessitate the demand for an efficient energy mix utilising renewable resources like biomass for sustainable development. Recent interest in the thermochemical conversion of coal and biomass into bioenergy via co-pyrolysis processes is gaining importance. This review critically assesses the behaviour of different types of coal and biomass blends during co-pyrolysis from various perspectives, including the effects of temperature, blending ratios, heating rate, synergistic and inhibitive behaviours, heat transfer mechanisms, nature of products, and their future applications. The possible synergies arising due to differences in the compositions of coal and biomass are discussed. In addition, the synergistic effect on co-pyrolysis yield is critically presented. Moreover, it is analysed that the co-pyrolysis offers higher yields of liquid and gaseous fuels compared to individual feedstock coal and biomass. Co-pyrolysis of coal and biomass can be promoted from a scientific standpoint;however, further research is still required for the integration of new technologies to enhance the effectiveness of co-pyrolysis. © The Author(s), under exclusive licence to Korean Carbon Society 2025.

关键词： Bio-oil Blending ratios Char Co-pyrolysis Gases Synergy Temperature

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