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5th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2021

作者： Liu, Jiajun Ru, Xinfeng Xia, Weiguo Wang, Chen China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration Shanghai China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology Dalian China National Engineering Research Center of Software Engineering and the State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

ISBN: (纸本)9789811939976

A distributed fault-tolerant formation control law is designed in this paper for multi-agent systems under external disturbances and actuator faults including time-varying loss of effectiveness faults. The initial position of each agent is already on a circle and the control purpose is to form a desired formation on this circle. Based on this local information, a distributed adaptive formation control law is designed by employing the congelation of variables method to deal with time-varying actuator faults. Finally, a simulation example is given to verify the effectiveness of the adaptive fault-tolerant control design method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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General theory for designing phonon transport in alloyed/doped materials

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science China(Physics,Mechanics & Astronomy) 2024年第12期67卷 133-140页

作者： Chenhan Liu Chao Wu Wei Liu Yunshan Zhao Gang Zhang Hongmin Yang Yunfei Chen Micro-and Nano-scale Thermal Measurement and Thermal Management Laboratory Key Laboratory of Numerical Simulation for Large Complex SystemsMinistry of EducationSchool of Energy and Mechanical EngineeringNanjing Normal UniversityNanjing210023China School of Electrical and Automation Engineering Nanjing Normal UniversityNanjing210023China Phonon Engineering Research Center of Jiangsu Province Center for Quantum Transport and Thermal Energy ScienceInstitute of Physics Frontiers and Interdisciplinary SciencesSchool of Physics and TechnologyNanjing Normal UniversityNanjing210023China Agency for Science Technology and ResearchInstitute of High-Performance ComputingSingapore138632Singapore Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments School of Mechanical EngineeringSoutheast UniversityNanjing211100China

Alloying/doping is a widely used technique for improving the electrical,mechanical,and optical properties of ***,this technology induces significant distortions in the lattice structure,mass distribution,and potential field,greatly enhancing phonon ***,we introduce the concept of alloying/doping path and employ crystal symmetry,lattice deformation,and electron distribution to characterize *** on this new concept,the phonon thermal transport behavior in alloyed/doped materials can be well designed,and along different alloying/doping paths,the difference in thermal conductivity can be up to 45 *** one hand,strategic alloying/doping that combines high crystal symmetry,large lattice contraction,and the same electron distribution suppresses phonon-phonon scattering phase space,induces phonon stiffening,and bolsters electronic structure symmetry,*** synergistic effects significantly improve thermal *** the other hand,random alloying/doping has a low symmetry,leading to the typical“U”shape of alloying/doping level-dependent thermal *** theory is corroborated in three-dimensional(3D)Si,2D MoS_(2),and quasi-1D TiS_(3),affirming its efficacy and broad applicability in controlling phonon transport.

关键词： phonon transport alloyed/doped materials crystal symmetry lattice contraction electronic structure

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Investigation of Allopurinol binding mechanism to allele HLA-A∗33:03 by using Molecular Dynamics simulation 46

Investigation of Allopurinol binding mechanism to allele HLA...

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46th Vietnam Conference on Theoretical Physics, VCTP 2021

作者： Pham, Oanh P. Lai, Hien T.T. Tran, Duong B. Le, Linh T. P. Nguyen, Anh Thi Van Nguyen, Hang Thi Thu Nguyen, Toan T. Key Laboratory for Multiscale Simulation of Complex Systems VNU University of Science Vietnam National University 334 Nguyen Trai Street Thanh Xuan Dist Hanoi120000 Viet Nam Key Laboratory of Enzyme and Protein Technology VNU University of Science Vietnam National University 334 Nguyen Trai Street Thanh Xuan Dist Hanoi120000 Viet Nam Department of Theoretical Physics VNU University of Science 334 Nguyen Trai Street Thanh Xuan Dist Hanoi120000 Viet Nam

Allopurinol (ALP), a xanthine oxidase inhibitor, is an FDA-approved urate-lowering medication used to treat Gout, prevent tumor lysis syndrome, and prevent recurrent calcium nephrolithiasis in hyperuricosuria patients. However, it has been known as a common cause of severe cutaneous adverse drug reactions (SCAR) including Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN), hypersensitivity syndrome/drug reaction with eosinophilia and systemic symptoms (HSS/DRESS), especially in patients carrying the Human Leukocyte Antigens allele HLA-B∗58:01, which is more prevalent in Asian population. However, although patients do not carry the HLA-B∗58:01 allele, they still exhibit allopurinol-induced SCAR. Surprisingly, a large number of these patients have the HLA-A∗33:03 allele. In this research, we investigated the binding of ALP to the HLA-A∗33:03 structure using Molecular Dynamics (MD) simulation. Our results showed that the complex of HLA-A∗33:03 and ALP was stable after 100000 ps simulation time. ALP had strong interactions with three important residues locating in the active site of HLA-A∗33:03, which include the seven amino acid residues Val 76, Asp 77, Leu 81, Ile 95, Gln 96, Asp 116, and Tyr 123. This data suggests that ALP has strong binding affinity for this allele. Thus, in addition to HLA-B∗58:01, HLA-A∗33:03 may be a potential screening marker before prescribing Allopurinol for Gout treatment. © Published under licence by IOP Publishing Ltd.

关键词： Genes

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Characterization and prediction of tailpipe ammonia emissions from in-use China 5/6 light-duty gasoline vehicles

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Frontiers of Environmental science & Engineering 2024年第1期18卷 71-81页

作者： Lewei Zeng Fengbin Wang Shupei Xiao Xuan Zheng Xintong Li Qiyuan Xie Xiaoyang Yu Cheng Huang Qingyao Hu Yan You Ye Wu College of Chemistry and Environmental Engineering Shenzhen UniversityShenzhen 518060China State Key Laboratory of Engines Tianjin UniversityTianjin 300072China China Automotive Technology and Research Center Co.Ltd. Tianjin 300300China CATARC Automotive Test Center(Guangzhou)Co.Ltd. Guangzhou 511300China State Environmental Protection Key Laboratory of Cause and Prevention of Urban Air Pollution Complex Shanghai Academy of Environmental SciencesShanghai 200233China National Observation and Research Station of Coastal Ecological Environments in Macao Macao Environmental Research InstituteMacao University of Science and TechnologyMacao SAR 999078China School of Environment State Key Joint Laboratory of Environment Simulation and Pollution ControlTsinghua UniversityBeijing 100084China

On-road tailpipe ammonia (NH3) emissions contribute to urban secondary organic aerosol formation and have direct or indirect adverse impacts on the environment and human health. To understand the tailpipe NH3 emission characteristics, we performed comprehensive chassis dynamometer measurements of NH3 emission from two China 5 and two China 6 light-duty gasoline vehicles (LDGVs) equipped with three-way catalytic converters (TWCs). The results showed that the distance-based emission factors (EFs) were 12.72 ± 2.68 and 3.18 ± 1.37 mg/km for China 5 and China 6 LDGVs, respectively. Upgrades in emission standards were associated with a reduction in tailpipe NH3 emission. In addition, high NH3 EFs were observed during the engine warm-up period in cold-start cases owing to the intensive emissions of incomplete combustion products and suitable catalytic temperature in the TWCs. Notably, based on the instantaneous NH3 emission rate, distinct NH3–emitting events were detected under high/extra high velocity or rapid acceleration. Furthermore, NH3 emission rates correlated well with engine speed, vehicle specific power, and modified combustion efficiency, which were more easily accessible. These strong correlations were applied to reproduce NH3 emissions from China 5/6 LDGVs. The predicted NH3 EFs under different dynamometer and real-world cycles agreed well with existing measurement and prediction results, revealing that the NH3 EFs of LDGVs in urban routes were within 8.55–11.62 mg/km. The results presented here substantially contribute to improving the NH3 emission inventory for LDGVs and predicting on-road NH3 emissions in China.

关键词： NH3 instantaneous emissions Catalytic temperature Vehicle specific power Combustion efficiency Emission prediction

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DeepDir: a deep learning approach for API directive detection

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science China(Information sciences) 2021年第9期64卷 238-240页

作者： Jingxuan ZHANG He JIANG Shuai LU Ge LI Xin CHEN College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics State Key Laboratory for Novel Software Technology Nanjing University Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education School of Software Dalian University of Technology School of Electronic Engineering and Computer Science Peking University School of Computer Science and Technology Hangzhou Dianzi University

Dear editor,Software developers tend to reuse existing libraries to facilitate their development process and implement certain functionalities by invoking application programming interfaces(APIs) [1]. However, it remains a challenging task for developers to correctly use APIs [2], so they often consult API learning resources [3, 4]. As one of the most important API learning resources,

关键词： Information systems and Communication Service

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A Synchronous Parallel Method with Parameters Communication Prediction for Distributed Machine Learning 19th

A Synchronous Parallel Method with Parameters Communication...

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19th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2023

作者： Zeng, Yanguo Xue, Meiting Xu, Peiran Shi, Yukun Zeng, Kaisheng Zhang, Jilin Yue, Lupeng School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Key Laboratory for Modeling and Simulation of Complex Systems Ministry of Education Hangzhou310018 China Data Security Governance Zhejiang Engineering Research Center Hangzhou310018 China National University of Defense Technology Changsha China School of Cyberspace HangZhou Dianzi University Hangzhou China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9783031545306

With the development of machine learning technology in various fields, such as medical care, smart manufacturing, etc., the data has exploded. It is a challenge to train a deep learning model for different application domains with large-scale data and limited resources of a single device. The distributed machine-learning technology, which uses a parameter server and multiple clients to train a model collaboratively, is an excellent method to solve this problem. However, it needs much communication between different devices with limited communication resources. The stale synchronous parallel method is a mainstream communication method to solve this problem, but it always leads to high synchronization delay and low computing efficiency as the inappropriate delay threshold value set by the user based on experience. This paper proposes a synchronous parallel method with parameters communication prediction for distributed machine learning. It predicts the optimal timing for synchronization, which can solve the problem of long synchronization waiting time caused by the inappropriate threshold settings in the stale synchronous parallel method. Moreover, it allows fast nodes to continue local training while performing global synchronization, which can improve the resource utilization of work nodes. Experimental results show that compared with the delayed synchronous parallel method, the training time and quality, and resource usage of our method are both significantly improved. © ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Forecasting

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Enhanced carbon capture with motif-rich amino acid loaded defective robust metal-organic frameworks

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Nano Research 2024年第3期17卷 2004-2010页

作者： Qi-Ye Ju Jia-Jia Zheng Li Xu Hai-Yan Jiang Zi-Qian Xue Lu Bai Yang-Yang Guo Ming-Shui Yao Ting-Yu Zhu State Key Laboratory of Multi-phase Complex Systems CAS Key Laboratory of Green Process and EngineeringBeijing Key Laboratory of Ionic Liquids Clean ProcessInstitute of Process EngineeringChinese Academy of SciencesBeijing 100190China Laboratory of Theoretical and Computational Nanoscience National Center for Nanoscience and TechnologyChinese Academy of SciencesBeijing 100190China School of Rare Earths University of Science and Technology of ChinaHefei 230026China Ganjiang Innovation Academy Chinese Academy of SciencesGanzhou 341000China University of Chinese Academy of Sciences Chinese Academy of SciencesBeijing 100049China Institute for Integrated Cell-Material Sciences Kyoto UniversityInstitute for Advanced StudyKyoto UniversityYoshidaUshinomiya-choSakyokuKyoto 606-8501Japan

The use of metal-organic frameworks(MOFs)as solid adsorption materials for carbon capture is promising,but achieving efficient and reversible adsorption with a balance of capacity and selectivity for carbon dioxide(CO_(2))over N_(2) remains a *** take full advantage of the strong channel traffic and robustness of MOFs with relatively small pores,it is highly necessary to employ a defect-engineering strategy to construct a broader channel structure that can facilitate the loading of functional motif-rich amino acids(AAs).This strategy can greatly enhance the CO_(2) adsorption performance of *** this study,motif-rich amino acids are loaded into the defective and robust porous frameworks via combined defect-engineering and post-synthetic *** defective Zr/Hf-MOF-808s modified with AAs,especially for the 18 mol%4-nitroisophthalic acid,generated defective products allowing for the loading of L-serine(L-Ser).This modification resulted in a significant improvement in both the adsorption capacity(248%improvement at 298 K,100 kPa)and the selectivity of CO_(2)/N_(2) using the ideal adsorbed solution theory(IAST),with the selectivity increasing to 120.55 and 38.27 at 15 and 100 kPa,respectively,while maintaining good cycling *** functional theory(DFT)simulation,CO_(2) temperature-programmed desorption(CO_(2)-TPD),and in situ Fourier transform infrared spectroscopy(FTIR)were further employed to have a better understanding of the enhanced CO_(2) adsorption ***,unlike the AAs loaded pristine MOF-808s that showed the best CO_(2) adsorption capacity with the loading of short and small glycine(Gly),the broadened channel size in our work enables the loading of functional motif-rich L-serine,which brings more active binding sites,improving CO_(2) adsorption.

关键词： carbon capture and storage metal-organic framework(MOF) amino acids(AAs) defect-engineering motif-rich

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Exploring the Physical World Adversarial Robustness of Vehicle Detection

arXiv

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arXiv 2023年

作者： Jiang, Wei Zhang, Tianyuan Liu, Shuangcheng Ji, Weiyu Zhang, Zichao Xiao, Gang Information Science Academy China Eletronics Technology Group Corporation Beijing100846 China Beihang University Beijing China National Key Laboratory for Complex Systems Simulation Beijing China

Adversarial attacks can compromise the robustness of real-world detection models. However, evaluating these models under real-world conditions poses challenges due to resource-intensive experiments. Virtual simulations offer an alternative, but the absence of standardized benchmarks hampers progress. Addressing this, we propose an innovative instant-level data generation pipeline using the CARLA simulator. Through this pipeline, we establish the Discrete and Continuous Instant-level (DCI) dataset, enabling comprehensive experiments involving three detection models and three physical adversarial attacks. Our findings highlight diverse model performances under adversarial conditions. Yolo v6 demonstrates remarkable resilience, experiencing just a marginal 6.59% average drop in average precision (AP). In contrast, the ASA attack yields a substantial 14.51% average AP reduction, twice the effect of other algorithms. We also note that static scenes yield higher recognition AP values, and outcomes remain relatively consistent across varying weather conditions. Intriguingly, our study suggests that advancements in adversarial attack algorithms may be approaching its "limitation".In summary, our work underscores the significance of adversarial attacks in real-world contexts and introduces the DCI dataset as a versatile benchmark. Our findings provide valuable insights for enhancing the robustness of detection models and offer guidance for future research endeavors in the realm of adversarial attacks. Copyright © 2023, The Authors. All rights reserved.

关键词： Pipelines

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Thermal convection driven by a heat-releasing scalar component

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Acta Mechanica Sinica 2022年第10期38卷 56-65页

作者： Yuhang Du Mengqi Zhang Yantao Yang State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceCollege of Engineeringand Beijing Innovation Center for Engineering Science and Advanced TechnologyPeking UniversityBeijing100871China Department of Mechanical Engineering National University of SingaporeSingapore117575Singapore

In this paper,we investigate the thermal convection flow which is driven by a heat-releasing concentration *** from our previous work on the internally heated double diffusive convection(IHDDC),in the current internally heated Rayleigh-Bénard convection(IHRBC),the fluid density depends solely on the temperature field and the concentration field only serves as the internal heat *** stability analyses reveal that the most unstable mode is always the stationary *** critical Rayleigh number,which measures the strength of the unstable driving force,decreases with the Schmidt number(the ratio between the viscosity and the molecular diffusivity of concentration field),but increases with the Prandtl number(the ratio between the viscosity and the thermal molecular diffusivity).Fully developed flows are then studied by three-dimensional direct numerical *** unifying model developed for IHDDC can also be used to describe the transport properties for the current *** characteristic widths are smaller for the plumes descending from the top plate than those ascending from the bottom one.

关键词： Internally heated convection Direct numerical simulation

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FedAG:A Federated Learning Method Based on Data Importance Weighted Aggregation

FedAG:A Federated Learning Method Based on Data Importance W...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Xu, Mengchu Zeng, Yan Xue, Meiting Zhang, Ji-Lin Wan, Jian Zhou, Mingyao Wen, Yilin Shi, Yukun Hangzhou Dianzi University School of Computer Science and Technology Hangzhou China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou China Zhejiang Engineering Research Center of Data Security Governance Hangzhou China Hangzhou Dianzi University School of Cyberspace Hangzhou China Huawei Enterprise Communication Technology Co Hangzhou China

ISBN: (纸本)9798350345384

Federated learning is a distributed machine learning approach that trains models with multiple clients and data locally. However, the existing methods ignore the differences between local models caused by the data heterogeneity, and give a high aggregation weight for the low-quality local model, which leads to low accuracy of the global model. For this problem, we propose a federated learning method based on data importance weighted aggregation, FedAG. It constructs an evaluation model of data importance based on the data distribution skewness, data volume, and data quality of clients, and aggregates local models with different weights computed by the evaluation model of data importance into a global model. We make experiments on five datasets including EMNIST, MNIST, and CIFAR-10. The results show that the accuracy of FedAG is respectively improved by 6.5%, 1.8%, 1.3% and 2.1%, compared with FedAvg, FedProx, FedVar, and Scaffold algorithms. © 2023 IEEE.

关键词： Scaffolds

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