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Ecological health analysis of wetlands in the middle reaches of Yangtze River under changing environment

International Journal of Digital Earth 2023年第1期16卷 3125-3144页

作者： Shengqing Zhang Xiaoyan Zhai Peng Yang Jun Xia Sheng Hu Libo Zhou Cai Fu Hubei Key Laboratory of Regional Ecology and Environmental Change School of Geography and Information EngineeringChina University of GeosciencesWuhanPeople’s Republic of China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin Research Center on Flood and Drought Disaster ReductionChina Institute of Water Resources and Hydropower ResearchBeijingPeople’s Republic of China State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan UniversityWuhanPeople’s Republic of China Yangtze Valley Water Environment Monitoring Center WuhanPeople’s Republic of China Wuhan CGeo Clouds Science&Tech Co.Ltd WuhanPeople’s Republic of China

Changes in wetland ecosystems have a critical impact on the local ecology and species *** development scenarios and policies are key factors influencing their ***,we studied changes of wetlands in the middle Yangtze River basin(MYRB)in 2001-2020,and a patch-generated land use simulation(PLUS)model and random forest(RF)method were applied to predict and analyze the changes under different scenarios in the MYRB in the future(i.e.2035-2095).The results indicated that:(1)The regions with high wetland proportions were concentrated in the central and eastern MYRB in 2001-2020,with a 1.5%decrease in overall wetland area;(2)The RF could simulate the future ecological quality with training and testing accuracies of 0.98 and 0.92,respectively;(3)Remote Sensing Ecological Index(RSEI)less than 0.5 in the central and eastern regions and 13.3%reduction in the northwest in the SSP245 *** general,the study provides a basis for future regional studies of ecosystem quality and provides data to support wetland conservation and management.

关键词： Remote sensing machine learning ecological prediction ecological change Yangtze River basin

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Evolving Generalizable Parallel Algorithm Portfolios via Domain-Agnostic Instance Generation

arXiv

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arXiv 2025年

作者： Wang, Zhiyuan Liu, Shengcai Yang, Peng Tang, Ke Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

Generalization is the core objective when training optimizers from data. However, limited training instances often constrain the generalization capability of the trained optimizers. Co-evolutionary approaches address this challenge by simultaneously evolving a parallel algorithm portfolio (PAP) and an instance population to eventually obtain PAPs with good generalization. Yet, when applied to a specific problem class, these approaches have a major limitation. They require practitioners to provide instance generators specially tailored to the problem class, which is often non-trivial to design. This work proposes a general-purpose, off-the-shelf PAP construction approach, named domain-agnostic co-evolution of parameterized search (DACE), for binary optimization problems where decision variables take values of 0 or 1. The key novelty of DACE lies in its neural network-based domain-agnostic instance representation and generation mechanism that eliminates the need for domain-specific instance generators. The strong generality of DACE is validated across three real-world binary optimization problems: the complementary influence maximization problem (CIMP), the compiler arguments optimization problem (CAOP), and the contamination control problem (CCP). Given only a small set of training instances from these problem classes, DACE, without requiring domain knowledge, constructs PAPs with even better generalization performance than existing approaches on all three classes, despite their use of domain-specific instance generators. Copyright © 2025, The Authors. All rights reserved.

关键词： Cellular automata

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Direct visualisation of metal-defect cooperative catalysis in Ru-doped defective MOF-808

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Journal of Materials Chemistry A 2024年第30期12卷 19018-19028页

作者： Xu, Chirui Orbell, William Wang, Guilian Li, Boye Ng, Bryan K. Y. Wu, Tai-Sing Soo, Yun-Liang Luan, Zhao-Xue Tang, Kangjian Wu, Xin-Ping Tsang, S. C. Edman Zhao, Pu Innovation Center for Chemical Science College of Chemistry Chemical Engineering and Materials Science Soochow University Suzhou215123 China Department of Chemistry University of Oxford OxfordOX1 3QR United Kingdom State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China National Synchrotron Radiation Research Center Hsinchu30076 Taiwan Department of Physics National Tsing Hua University Hsin-chu30013 Taiwan State Key Laboratory of Green Chemical Engineering and Industrial Catalysis Centre for Computational Chemistry Research Institute of Industrial Catalysis School of Chemistry and Molecular Engineering East China University of Science and Technology Shanghai200237 China

Improving the efficiency of catalytic materials is vital to the chemical and energy industries. Constructing neighbouring active sites in metal-organic framework (MOF) materials for cooperative catalysis is a promising way to achieve the above goal. However, it is difficult to fine-tune active sites at the atomic level due to the challenge of visualising their local structures and their interaction with substrates. In this article, we report the direct visualisation of metal and defect active sites and binding of the phenol substrate in Ru-doped defective MOF-808. X-ray absorption spectroscopy, X-ray pair distribution function analysis, X-ray powder diffraction, and infrared spectroscopy reveal that the enhanced selective hydrogenation originates from the specific adsorption geometry of phenol over 7-centred Ru clusters and hydroxyl or water of defect sites. This mechanism also well explains the high catalytic activity in CO2 reduction. This work represents the first example of structural elucidation of metal-defect cooperative catalysis in MOFs and will lead to the rational design of new superactive MOF catalysts. © 2024 The Royal Society of Chemistry.

关键词： Substrates

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Pomelo Peel-Inspired 3D-Printed Porous Structure for Efficient Absorption of Compressive Strain Energy

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Journal of Bionic engineering 2022年第2期19卷 448-457页

作者： Baisong Yang Wenhui Chen Renlong Xin Xiaohong Zhou Di Tan Chuan Ding You Wu Liang Yin Chuyang Chen Shan Wang Zhenglei Yu Jonathan TPham Sheng Liu Yifeng Lei Longjian Xue School of Power and Mechanical Engineering The Institute of Technological SciencesWuhan UniversitySouth Donghu Road 8Wuhan 430072HubeiChina State Key Laboratory of Automotive Simulation and Control and Key Lab of Bionic Engineering Ministry of EducationJilin UniversityChangchun 130022China School of Materials Science and Engineering Wuhan University of TechnologyWuhan 430070China Department of Chemical and Materials Engineering University of KentuckyLexingtonKY 40506USA

The porous structure in pomelo peel is believed to be responsible for the protection of its fruit from damage during the free falling from a *** quantitative understanding of the relationship between the deformation behavior and the porous structure could pave the way for the design of porous structures for efficient energy ***,a universal feature of pore distribution in pomelo peels along the radial direction is extracted from three varieties of pomelos,which shows strong correlation to the deformation behavior of the peels under *** by the porous design found in pomelo peels,porous polyether-ether-ketone(PEEK)cube is additively manufactured and possesses the highest ability to absorb energy during compression as compared to the non-pomelo-inspired geometries,which is further confirmed by the finite element *** nature-optimized porous structure revealed here could guide the design of lightweight and high-energy-dissipating materials/devices.

关键词： Bionic design Pomelo peel Porous structure 3D printing Energy absorption

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Single event transient characterization of SiGe HBT by SPA experiment and 3-D process simulation

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science China(Technological sciences) 2022年第5期65卷 1193-1205页

作者： PAN XiaoYu GUO HongXia FENG YaHui LIU YiNong ZHANG JinXin LI Zhuang LUO YinHong ZHANG FengQi WANG Tan ZHAO Wen DING LiLi XU JingYan The Key Laboratory of Particle and Radiation Imaging Ministry of EducationDepartment of Engineering PhysicsTsinghua UniversityBeijing100084China State Key Laboratory of Intense Pulsed Radiation Simulation and Effect Northwest Institute of Nuclear TechnologyXi’an710024China School of Materials Science and Engineering Xiangtan UniversityXiangtan411105China School of Aerospace Science and Technology Xidian UniversityXi’an710126China The 38th Research Institute of China Electronics Technology Group Corporation Hefei230088China

The single-photon absorption induced single event transient in the silicon-germanium heterojunction bipolar transistor is *** laser wavelength and bias condition have been proven to have significant impacts on the characterization of the single event transient(SET) response of the device by two-dimensional(2-D) raster *** optical analytical calculation,the laser-induced charge distribution is well-embedded in the 3-D TCAD process simulation conducted to explore the underlying physical *** addition to the ion shunt effect,the excess electron injection from the emitter to the base could play a vital role in the SET peak amplitude and charge *** impact of the metal layer on the SPA experimental results is also determined by establishing a figure of merit that will help researchers estimate the laser-induced transient sensitivity of devices with metal layer blocking.

关键词： silicon-germanium HBT single-photon absorption TCAD simulation single event transient

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Numerical study of effects of hydrogen addition on methane combustion behaviors

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Journal of Iron and Steel Research International 2023年第11期30卷 2173-2185页

作者： Dian-yu E Ling-yi Weng Guang-wu Tang Jing Li Guang-chao Wei Jia-xin Cui Jiangxi Provincial Key Laboratory for Simulation and Modelling of Particulate Systems Jiangxi University of Science and TechnologyNanchang330013JiangxiChina International Institute for Innovation Jiangxi University of Science and TechnologyNanchang330013JiangxiChina Shenzhen Smoore Technology Limited Shenzhen518102GuangdongChina ARC Research Hub for Computational Particle Technology Department of Chemical and Biological EngineeringMonash UniversityClaytonVIC3800Australia School of Transportation and Vehicle Engineering Shandong University of TechnologyZibo255000ShandongChina

The methane combustion with hydrogen addition can effectively reduce carbon emissions in the iron and steel making industry,while the combustion mechanism is still poorly *** oxy-fuel combustion of methane with hydrogen addition in a 0.8 MW oxy-natural gas combustion experimental furnace was numerically studied to investigate six different combustion *** results show that the 28-step chemical reaction mechanism is the optimal recommendation for the simulation balancing the numerical accuracy and computational *** the hydrogen enrichment increases in fuel,the highest flame temperature ***,the chemical reaction accelerates with enlarging the peak of the highest flame temperature and intermediate OH *** the hydrogen enrichment reaches 75 vol.%,the flame front is the farthest,and the flame high-temperature zone occupies the largest proportion corresponding to the most vigorous chemical reactions in the same oxygen supply.

关键词： Oxy-fuel combustion Hydrogen Combustion mechanism Flame temperature simulation Modeling

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Large Language Model-Based Benchmarking Experiment Settings for Evolutionary Multi-Objective Optimization

arXiv

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arXiv 2025年

作者： Pang, Lie Meng Ishibuchi, Hisao Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

When we manually design an evolutionary optimization algorithm, we implicitly or explicitly assume a set of target optimization problems. In the case of automated algorithm design, target optimization problems are usually explicitly shown. Recently, the use of large language models (LLMs) for the design of evolutionary multi-objective optimization (EMO) algorithms have been examined in some studies. In those studies, target multi-objective problems are not always explicitly shown. It is well known in the EMO community that the performance evaluation results of EMO algorithms depend on not only test problems but also many other factors such as performance indicators, reference point, termination condition, and population size. Thus, it is likely that the designed EMO algorithms by LLMs depends on those factors. In this paper, we try to examine the implicit assumption about the performance comparison of EMO algorithms in LLMs. For this purpose, we ask LLMs to design a benchmarking experiment of EMO algorithms. Our experiments show that LLMs often suggest classical benchmark settings: Performance examination of NSGA-II, MOEA/D and NSGA-III on ZDT, DTLZ and WFG by HV and IGD under the standard parameter specifications. Copyright © 2025, The Authors. All rights reserved.

关键词： Population statistics

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User-level failure detection and auto-recovery of parallel programs in HPC systems

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Frontiers of Computer science 2021年第6期15卷 31-42页

作者： Guozhen ZHANG Yi LIU Hailong YANG Jun XU Depei QIAN State Key Laboratory of Software Development Environment Beijing 100191China Sino-German Joint Software Institute Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing 100854China

As the mean-time-between-failures(MTBF)continues to decline with the increasing number of components on large-scale high performance computing(HPC)systems,program failures might occur during the execution period with high *** successful execution of the HPC programs has become an issue that the unprivileged users should be *** the user perspective,if the program failure cannot be detected and handled in time,it would waste resources and delay the progress of program ***,the unprivileged users are unable to perform program state checking due to execution control by the job management system as well as the limited ***,automated tools for supporting user-level failure detection and autorecovery of parallel programs in HPC systems are *** paper proposes an innovative method for the unprivileged user to achieve failure detection of job execution and automatic resubmission of failed *** state checker in our method is encapsulated as an independent job to reduce interference with the user *** addition,we propose a dual-checker mechanism to improve the robustness of our *** implement the proposed method as a tool named automatic re-launcher(ARL)and evaluate it on the Tianhe-2 *** results show that ARL can detect the execution failures effectively on Tianhe-2 *** addition,the communication and performance overhead caused by ARL is *** good scalability of ARL makes it applicable for large-scale HPC systems.

关键词： high performance computing parallel program failure detection failure auto-recovery

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PNESR-DDI: An Effective Drug-Drug Interaction Prediction Model Based on Pretraining Method and Enhanced Subgraph Reconstruction

PNESR-DDI: An Effective Drug-Drug Interaction Prediction Mod...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Ke Chen Xiaosong Han Xiaoran Li Yanchun Liang Dong Xu Renchu Guan Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Software Jilin University Changchun China Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Computer Science and Technology Jilin University Changchun China Zhuhai Laboratory of Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education School of Computer Science Zhuhai College of Science and Technology Zhuhai China Department of Electrical Engineering and Computer Science Christopher S. Bond Life Sciences Center University of Missouri Columbia USA

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Drug-Drug Interaction (DDI) task plays a crucial role in clinical treatment and drug development. Recently, deep learning methods have been successfully applied for DDI prediction. However, training deep learning models always need large amount of data, while known DDIs are scarce. To address this challenge, a graph neural network-based DDI prediction model named PNESR-DDI is proposed, which compensates for the lack of DDIs by enriching drug representations. First, to obtain initial node representations that incorporate rich semantic information from the biomedical knowledge graph (KG), a link prediction pre-training method on external KG is proposed in the node embedding pre-training module. Then, considering the large scale of the KG, subgraph extraction for the target drug pairs is introduced to reduce noise and decrease computational complexity in the subgraph anchoring module. After that, the subgraph is updated, and node similarities are propagated in the subgraph reconstruction module. Based on the node similarity scores, the subgraph is pruned and reconstructed, which adjusts node representations to be more conducive to DDI prediction. Finally, the drug embeddings, subgraph representations, and drug fingerprint features are concatenated to predict DDIs. PNESRDDI is evaluated on two benchmark DDI datasets: DrugBank and TWOSIDES. Experiment results show that PNESR-DDI achieves better performance than baselines. Ablation results validate the effectiveness of the pre-training method and the adaptive subgraph reconstruction strategy.

关键词： Drugs Deep learning Adaptation models Visualization Biological system modeling Noise Knowledge graphs Predictive models Fingerprint recognition Transformers

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A Resilient Control Strategy in Connected Vehicles under Actuator Attacks 7

A Resilient Control Strategy in Connected Vehicles under Act...

引用

7th CAA International Conference on Vehicular Control and Intelligence, CVCI 2023

作者： Li, Kai Wang, Yulei Chen, Hong Gao, Jinwu State Key Laboratory of Automotive Simulation and Control The Department of Control Science Jilin University Changchun China School of Electronics and Information Engineering Tongji University Shanghai China The Department of Control Science Jilin University School of Electronics and Information Engineering Tongji University Shanghai China

ISBN: (纸本)9798350340488

With the promotion of advanced communication technology, autonomous vehicle platoons (AVPs) develop rapidly due to their advantages in enhancing traffic efficiency, road safety and reducing fuel consumption. However, as cyber physical systems, AVPs are very vulnerable to malicious attacks. In this paper, we propose a novel resilient control scheme to detect and tolerate a malicious directional actuator attack in a distributed manner which destroys the feedback control system by reversing the direction of actuator. The scheme consists of a distributed trigger mechanism with a logic-based switching criterion to detect the directional actuator attacks, and a resilient and distributed triple-step control scheme to defend against the attacks. The proposed control scheme is applied on bidirectional (BD) topology. Both global asymptotic stability and string stability of the platoon system are strictly proved via Lyapunov's stability theory. Finally, simulation results are provided to show the effectiveness of the proposed approach. © 2023 IEEE.

关键词： Autonomous vehicle platoons Directional Actuator attacks Distributed control String stability

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