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arXiv 2024年

作者： Feng, Fang Hu, Yuming Yu, Yue Zhao, Jikun School of Mathematics and Statistics Nanjing University of Science and Technology Nanjing China Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education National Center for Applied Mathematics in Hunan School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China School of Mathematics and Statistics Zhengzhou University Zhengzhou450001 China

In this paper, we develop a residual-type a posteriori error estimation for an interior penalty virtual element method (IPVEM) for the Kirchhoff plate bending problem. Building on the work in [18], we adopt a modified discrete variational formulation that incorporates the H1-elliptic projector in the jump and average terms. This allows us to simplify the numerical implementation by including the H1-elliptic projector in the computable error estimators. We derive the reliability and efficiency of the a posteriori error bound by constructing an enriching operator and establishing some related error estimates that align with C0-continuous interior penalty finite element methods. As observed in the a priori analysis, the interior penalty virtual elements exhibit similar behaviors to C0continuous elements despite its discontinuity. This observation extends to the a posteriori estimate since we do not need to account for the jumps of the function itself in the discrete scheme and the error estimators. As an outcome of the error estimator, an adaptive VEM is introduced by means of the mesh refinement strategy with the one-hanging-node rule. Numerical results from several benchmark tests confirm the robustness of the proposed error estimators and show the efficiency of the resulting adaptive VEM. Copyright © 2024, The Authors. All rights reserved.

关键词： Discrete element methods

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General room-temperature Suzuki-Miyaura polymerization for organic electronics (Jan, 10.1038/s41563-023-01794-9, 2024)

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NATURE MATERIALS 2024年第3期23卷 439-439页

作者： Xiong, Haigen Lin, Qijie Lu, Yu Zheng, Ding Li, Yawen Wang, Song Xie, Wenbin Li, Congqi Zhang, Xin Lin, Yuze Wang, Zhi-Xiang Shi, Qinqin Marks, Tobin J. Huang, Hui College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing People’s Republic of China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing People’s Republic of China School of Chemical Sciences University of Chinese Academy of Sciences Beijing People’s Republic of China Department of Chemistry and the Materials Research Center Northwestern University Evanston IL USA Beijing National Laboratory for Molecular Sciences CAS Key Laboratory of Organic Solids Institute of Chemistry Chinese Academy of Sciences Beijing People’s Republic of China CAS Center for Excellence in Topological Quantum Computation University of Chinese Academy of Sciences Beijing People’s Republic of China CAS Key Laboratory of Vacuum Physics University of Chinese Academy of Sciences Beijing People’s Republic of China

π-Conjugated polymers (CPs) have broad applications in high-performance optoelectronics, energy storage, sensors and biomedicine. However, developing green and efficient methods to precisely synthesize alternating CP structures on a large scale remains challenging and critical for their industrialization. Here a room-temperature, scalable and homogeneous Suzuki–Miyaura-type polymerization reaction is developed with broad generality validated for 24 CPs including donor–donor, donor–acceptor and acceptor–acceptor connectivities, yielding device-quality polymers with high molecular masses. Furthermore, the polymerization protocol significantly reduces homocoupling structural defects, yielding more structurally regular and higher-performance electronic materials and optoelectronic devices than conventional thermally activated polymerizations. Experimental and theoretical studies reveal that a borate transmetalation process plays a key role in suppressing protodeboronation, which is critical for large-scale structural regularity. Thus, these results provide a general polymerization tool for the scalable production of device-quality CPs with alternating structural regularity.

关键词： Electronic devices Materials for optics

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Fully-Connected LEO Hybrid Constellation Design with Global Uniform Coverage

Fully-Connected LEO Hybrid Constellation Design with Global ...

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Asian Aerospace and Astronautics Conference (AAAC)

作者： Yao Xiao Shuai Guo Yazhong Luo Hunan Key Laboratory of Intelligent Planning and Simulation for Aerospace Missions College of Aerospace Science and Engineering (of National University of Defense Technology) Changsha China

ISBN: (数字)9798350355833

ISBN: (纸本)9798350355840

Low Earth orbit mega-constellations have been deployed with the development of small satellite technology, and the decrease in satellite manufacturing and launch costs. The network connectivity and coverage performance are important factors in evaluating the low Earth orbit mega-constellation system. This study considers the problem of designing a low Earth orbit hybrid mega-constellation to achieve global uniform coverage considering the constraint of constellation connectivity. First, the precondition of establishing inter-satellite links is analyzed and characterized by inter-satellite angular distance. The constraint of the satellite phase and the topology design method among sub-constellations are derived. Then, the coverage longitude width model is established and the coverage ratio of latitudes is proposed. Finally, the coverage uniformity and connectivity models are proposed as the objective and constraint respectively in the hybrid constellation optimization model. A hybrid constellation design example is provided, which achieves a uniformity metric of 0.0186 and a maximum transmission hop of 6.

关键词： Measurement simulation Optimization models Design methodology Low earth orbit satellites Small satellites Orbits Topology Manufacturing Optimization

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Enabling Surrogate-Assisted Evolutionary Reinforcement Learning via Policy Embedding 1

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17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Tang, Lan Li, Xiaxi Zhang, Jinyuan Li, Guiying 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 Faculty of Engineering Shenzhen MSU-BIT University Shenzhen518172 China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen518055 China Department of Statistics and Data Science Southern University of Science and Technology Shenzhen518055 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Evolutionary Reinforcement Learning (ERL) that applying Evolutionary Algorithms (EAs) to optimize the weight parameters of Deep Neural Network (DNN) based policies has been widely regarded as an alternative to traditional reinforcement learning methods. However, the evaluation of the iteratively generated population usually requires a large amount of computational time and can be prohibitively expensive, which may potentially restrict the applicability of ERL. Surrogate is often used to reduce the computational burden of evaluation in EAs. Unfortunately, in ERL, each individual of policy usually represents millions of weights parameters of DNN. This high-dimensional representation of policy has introduced a great challenge to the application of surrogates into ERL to speed up training. This paper proposes a PE-SAERL Framework to at the first time enable surrogate-assisted evolutionary reinforcement learning via policy embedding (PE). Empirical results on 5 Atari games show that the proposed method can perform more efficiently than the four state-of-the-art algorithms. The training process is accelerated up to 7x on tested games, comparing to its counterpart without the surrogate and PE. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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The Impact of Wind on Rainfall Distribution in Urban High-Rise Residential Areas 6th

The Impact of Wind on Rainfall Distribution in Urban High-Ri...

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6th International Symposium on Water Resource and Environmental Management, WREM 2023

作者： Gao, Xichao Song, Xinyi Yang, Zhiyong Wang, Pengfei Gao, Kai State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin Institute of Water Resources and Hydropower Research Beijing100038 China School of Hydraulic and Environmental Engineering Changsha University of Science and Technology Changsha410114 China Ministry of Emergency Management Big Data Center Beijing100013 China

ISBN: (纸本)9783031559884

The spatial distribution of rainfall in urban areas has a significant impact on urban rainfall-runoff processes. Wind can affect raindrop trajectories and thus affect the spatial distribution of rainfall. Due to the obstructive effect of building facades, the influence of wind on the distribution of rainfall is more pronounced in urban areas. In this study, we proposed a method to detect the spatial distribution of rainfall in urban high-rise residential areas based on computational fluid dynamics modeling. The variation of rainfall distribution and the ratio of rainfall on builds to that on the ground with changes in wind speed was analyzed using the proposed method. The results show that: (1) the spatial distribution of rainfall intensity on the ground in the high-rise residential area becomes increasingly uneven with the increase in the wind speed. (2) wind can lead to an increase in the total rainfall in the high-rise residential area by more than twice. (3) the ratio of rainfall on buildings to that on the ground increases significantly with the increasing wind speed. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Rain

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A study on the prediction model of dam seepage volume based on isolated forest-multiple stepwise linear regression 4

A study on the prediction model of dam seepage volume based ...

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4th International Conference on Computer engineering and Application, ICCEA 2023

作者： Chen, Guanyu Zhang, Suli Zhang, Chenlin Qian, XiaoChun Changchun University of Technology School of Computer Science & Engineering Jilin Provincial Key Laboratory of Changbai Historical Culture and Vr Reconstruction Technology Jilin Prov. Changbai Mt. Ecol. Culture and Virtual Reality Simulation Engineering Research Center Changchun China Jilin Institute of Chemical Technology School of Information and Control Engineering Jilin Provincial Key Laboratory of Changbai Historical Culture and Vr Reconstruction Technology Jilin Prov. Changbai Mt. Ecol. Culture and Virtual Reality Simulation Engineering Research Center Changchun China

ISBN: (纸本)9798350347548

In the study of hydraulic seepage prediction, it is often necessary to target multiple feature dimensions. In this paper, a variety of traditional machine learning algorithms based on stepwise regression filtering features are used to train a dam seepage prediction model based on isolated forest processing of data outliers. The results show that the algorithm can be applied to predict the seepage data of a reservoir more accurately, and further suggest improvements to the dam's seepage control function and observation facilities. The experimental results show that the correlation coefficient of the linear regression model is significantly improved when the training sample ratio is 0.8 after the isolated forest treatment of outliers and stepwise regression screening features. © 2023 IEEE.

关键词： Forecasting

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Control and Stability of Large-scale Power System with Highly Distributed Renewable Energy Generation:Viewpoints from Six Aspects

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CSEE Journal of Power and Energy Systems 2023年第1期9卷 8-14页

作者： Qing-Hua Wu Anjan Bose Chanan Singh Joe H.Chow Gang Mu Yuanzhang Sun Zhaoxi Liu Zhigang Li Yang Liu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China School of Electrical Engineering&Computer Science Washington State UniversityPullmanWA 99164USA Department of Electrical and Computer Engineering Texas A&M UniversityCollege StationTX 77843USA Department of Electrical Computer and Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNYUSA Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

Power systems are moving toward a low-carbon or carbon-neutral future where high penetration of renewables is *** conventional fossil-fueled synchronous generators in the transmission network being replaced by renewable energy generation which is highly distributed across the entire grid,new challenges are emerging to the control and stability of large-scale power *** analysis and control methods are needed for power systems to cope with the ongoing *** the CSEE JPES forum,six leading experts were invited to deliver keynote speeches,and the participating researchers and professionals had extensive exchanges and discussions on the control and stability of power ***,potential changes and challenges of power systems with high penetration of renewable energy generation were introduced and explained,and advanced control methods were proposed and analyzed for the transient stability enhancement of power grids.

关键词： Distributed energy resources high converter penetration power system control renewable energy generation stability control transient stability

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Antibiotic resistance genes in manure-amended paddy soils across eastern China:Occurrence and influencing factors

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Frontiers of Environmental science & engineering 2022年第7期16卷 101-111页

作者： Yuwei Guo Xian Xiao Yuan Zhao Jianguo Liu Jizhong Zhou Bo Sun Yuting Liang School of Environmental and Safety Engineering Changzhou UniversityChangzhou213164China State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing210008China Institute for Environmental Genomics Department of Microbiology and Plant Biologyand School of Civil Engineering and Environmental SciencesUniversity of OklahomaNormanOK73019USA State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Earth and Environmental Sciences Lawrence Berkeley National LaboratoryBerkeleyCA94270USA

Pig manure,rich in antibiotics and metals,is widely applied in paddy fields as a soil conditioner,triggering the proliferation of antibiotic resistance genes(ARGs)in ***,comprehensive studies on the effects of manure fertilization on the abundance of ARGs and their influencing factors are still ***,pig manure and manure-amended and inorganic-amended soils were collected from 11 rice-cropping regions in eastern China,and the accumulation of antibiotics,metals,and ARGs was assessed *** results showed that manure fertilization led to antibiotic residues and increased the metal content(i.e.,Zn,Cu,Ni,and Cr).Tetracycline and sulfonamide resistance genes(tetM,tetO,sul1,and sul2)were also significantly enhanced with manure *** to variance partitioning analysis,the most important factors that individually influenced ARGs were soil physicochemical properties,accounting for 12%of the *** correlations between soil nutrients and ARGs indicated that manure application enhanced the growth of resistant microorganisms by supplying more *** and antibiotics contributed 9%and 5%to the variations in ARGs,*** co-occurrence also increased the enrichment of ARGs,as their interactions accounted for 2%of the variation in ***,Cu was significantly related to most ARGs in the soil(r=0.26–0.52,p<0.05).Sulfapyridine was significantly related to sul2,and tetracycline resistance genes were positively related to *** study highlighted the risks of antibiotic and ARG accumulation with manure fertilization and shed light on the essential influencing factors of ARGs in paddy soils.

关键词： Pig manure Antibiotics Metals Antibiotic resistance genes Paddy fields

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Game Generation via Large Language Models

Game Generation via Large Language Models

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IEEE Symposium on computational Intelligence and Games, CIG

作者： Chengpeng Hu Yunlong Zhao Jialin Liu Department of Computer Science and Engineering Guangdong Key Laboratory of Brain-inspired Intelligent Computation Southern University of Science and Technology Shenzhen China LightSpeed Studios Tencent Shenzhen China

ISBN: (数字)9798350350678

ISBN: (纸本)9798350350685

Recently, the emergence of large language models (LLMs) has unlocked new opportunities for procedural content generation. However, recent attempts mainly focus on level generation for specific games with defined game rules such as Super Mario Bros. and Zelda. This paper investigates the game generation via LLMs. Based on video game description language, this paper proposes an LLM-based framework to generate game rules and levels simultaneously. Experiments demonstrate how the framework works with prompts considering different combinations of context. Our findings extend the current applications of LLMs and offer new insights for generating new games in the area of procedural content generation.

关键词： Video games Solid modeling Procedural generation Three-dimensional displays Large language models Prototypes Games

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A public data-set for synchronous motor electrical faults diagnosis with CNN and LSTM reference classifiers

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Energy and AI 2023年第4期14卷 221-237页

作者： Zhenglong Sun Ram Machlev Qianchao Wang Juri Belikov Yoash Levron Dmitry Baimel Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)JilinChina The Andrew and Erna Viterbi Faculty of Electrical&Computer Engineering Technion-Israel Institute of TechnologyHaifa 3200003Israel Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast UniversityNanjing210096China Department of Software Science Tallinn University of TechnologyAkadeemia tee 15a12618 TallinnEstonia Department of Electrical and Electronics Engineering Sami Shamoon College of EngineeringBeer-Sheva84100Israel

In the last two decades,motor operation monitoring tools have become a necessity,and many studies focus on the detection and diagnosis of motor electrical ***,at present,a core obstacle that prevents the direct comparison of such classification techniques is the lack of a standard database that can be used as a *** view of this,we offer here a public experimental data-set that has beendesigned specifically for the comparison of synchronous motor electrical fault *** data-set comprises five types of motor electrical faults:open phase between inverter and motor;short circuit/leakage current between two phases;short circuit/leakage current in phase-to-neutral;rotor excitation voltage disconnection;and variation of rotor excitation *** addition,each fault has been recorded as a four-dimensional signal:three phase voltages;three phase currents;motor speed;and motor *** package includes two deep-learning reference classifiers that are based on a convolutional neural network(CNN)and long short term memory(LSTM).Due to the good performance of these classifiers,we suggest that they can be used by the community as benchmarks for the development of new and better motor electrical fault classification *** database and the reference classifiers are examined and insights regarding different combinations of features and lengths of recording points are *** developed code is available online,and is free to use.

关键词： Motor faults Synchronous motors Public data-set Classification Deep-learning CNN LSTM

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