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2nd International Conference on Electronic information and Mechanical Manufacturing, EIMM 2022

作者： Chen, Mengqiang Yang, Jiazhi Yu, Guangwang Shen, Jie College of Information Science and Engineering Guilin University of Technology Guangxi Guilin541006 China Guangxi Key Laboratory of Embedded Technology and Intelligent System Guangxi Guilin541006 China

Working distance and background radiation greatly affect the signal-to-noise ratio of avalanche photodiode (APD) in the lidar detection system. The traditional method cannot adapt to a complex environment by offline compensation or pre-compensation according to the influence factors of the external environment. In this paper, an avalanche photodiode voltage compensation method based on the improved random forest is designed. Firstly, the distance image data is de-noised. Then the weight of each decision tree in the random forest was changed to improve the classification performance. The particle swarm optimization (PSO) algorithm was used to search for the optimal combination of parameters affecting classification accuracy and performance. Finally, the improved random forest algorithm is used to judge the current working state of APD at different distances, compensate for the bias voltage, and make APD work in the optimal state. The proposed method is compared with the k-nearest neighbor, support vector machine, and other commonly used classification algorithms, and the results verify the effectiveness of the proposed method. © Published under licence by IOP Publishing Ltd.

关键词： Particle swarm optimization (PSO)

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China's greenhouse gas budget during 2000-2023

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National science Review 2025年第4期12卷 24-36页

作者： Wenping Yuan Minqi Liang Yuanyi Gao Ling Huang Li Dan Hongtao Duan Songbai Hong Fei Jiang Weimin Ju Tingting Li Ziyang Lou Shilong Luan Xiao Lu Zhangcai Qin Lishan Ran Lulu Shen Fei Teng Xiangjun Tian Yilong Wang Jing Wei Jiangzhou Xia Xiaosheng Xia Lijun Yu Xu Yue Haicheng Zhang Wen Zhang Yuzhong Zhang Xu Zhao Qiuan Zhu Shilong Piao Xuhui Wang Institute of Carbon Neutrality Sino-French Institute for Earth System Science College of Urban and Environmental Sciences Peking University School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Key Laboratory of Regional Climate-Environment for Temperate East Asia Institute of Atmospheric PhysicsChinese Academy of Sciences Key Laboratory of Lake and Watershed Science for Water Security Nanjing Institute of Geography and LimnologyChinese Academy of Sciences State Key Laboratory of Lake Science and Environment Nanjing Institute of Geography and LimnologyChinese Academy of Sciences School of Urban Planning and Design Shenzhen Graduate School Peking University Frontiers Science Center for Critical Earth Material Cycling Nanjing University Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System Science Nanjing University Key Laboratory of Atmospheric Environment and Extreme Meteorology Institute of Atmospheric PhysicsChinese Academy of Sciences Shanghai Engineering Research Center of Solid Waste Treatment and Resource Recovery School of Environmental Science & Engineering Shanghai Jiao Tong University Department of Geography The University of Hong Kong Department of Atmospheric and Oceanic Sciences School of PhysicsPeking University Institute of Energy Environment and Economy Tsinghua University State Key Laboratory of Tibetan Plateau Earth System Resources and Environment (TPESRE)Institute of Tibetan Plateau ResearchChinese Academy of Sciences Tianjin Key Laboratory of Water Resources and Environment Tianjin Normal University State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC) Institute of Atmospheric PhysicsChinese Academy of Sciences Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of

National greenhouse gas（GHG） budget,including CO2,CH4and N2O has increasingly become a topic of concern in international climate *** is paying increasing attention to reducing GHG emissions and increasing land sinks to effectively mitigate climate *** estimates of GHG fluxes are crucial for monitoring progress toward mitigating GHG emissions in *** study used comprehensive methods,including emission factor methods,process-based models,atmospheric inversions,and data-driven models,to estimate the long-term trends of GHG sources and sinks from all anthropogenic and natural sectors in China's mainland during 2000-2023,and produced an up-to-date China GHG Budget dataset（CNGHG）.The total gross emissions of the three GHGs show a 3-fold increase from 5.0（95% CI:4.9-5.1） Gt CO2-eq yr-1（in 2000） to 14.3（95% CI:13.8-14.8） Gt CO2-eqyr-1（in2023）.CO2emissions represented 81.8% of the GHG emissions in 2023,while 12.7% and 5.5% were for CH4and N2O,*** the largest CO2source,the energy sector contributed 87.4% *** contrast,the agriculture,forestry and other land use sector was the largest sector of CH4and N2O,representing 50.1% and 6 6.3% emissions,***,China's terrestrial ecosystems serve as a net CO2sink(1.0 Gt CO2yr-1,9596 CI:0.2-1.9 Gt CO2yr-1) during 2012 to 2021,equivalent to an average of 14.3% of fossil *** GHG emission estimates showed a general consistency with national GHG inventories,with gridded and sector-specific estimates of GHG fluxes over China,providing the basis for curtailing GHG emissions for each region and sector.

关键词： greenhouse gas budget China carbon dioxide methane nitrous oxide

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Joint Optimization of Compression, Transmission and Computation for Cooperative Perception Aided Intelligent Vehicular Networks

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IEEE Transactions on Vehicular technology 2025年第5期74卷 8201-8214页

作者： Lu, Binbin Huang, Xumin Wu, Yuan Qian, Liping Zhou, Sheng Niyato, Dusit University of Macau State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science 999078 China Guangdong University of Technology School of Automation Guangzhou510006 China University of Macau State Key Lab of Internet of Things for Smart City 999078 China University of Macau State Key Laboratory of Internet of Things for Smart City Department of Computer Information Science 999078 China Zhuhai UM Science and Technology AQ2 Research Institute Zhuhai519301 China Zhejiang University of Technology Institute of Cyberspace Security Hangzhou310023 China Tsinghua University Beijing National Research Center for Information Science and Technology Department of Electronic Engineering Beijing100084 China Nanyang Technological University School of Computer Science and Engineering 639815 Singapore

Cooperative perception is a promising paradigm to tackle the perception limitations of a single intelligent vehicle (IV) to enhance the driving safety and efficiency in intelligent vehicular networks. However, the real-time transmission and computation-intensive fusion of raw sensing data raise new challenges for satisfying the stringent delay requirement of delay-sensitive applications. In this paper, we formulate a joint optimization problem of the cooperative IV selection, compression ratio selection, transmit power control, task offloading decision and computation allocation to minimize the end-to-end delay consisting of compression, transmission and computation. In particular, to meet the perception probability requirement, the quality and quantity-aware matching algorithm is proposed to optimize the cooperative IV selection. To guarantee the queue stability of offloading tasks, we develop the Lyapunov optimization algorithm to determine the upper bound of the offloading tasks and the corresponding optimal computation allocation. The Lyapunov aided deep reinforcement learning algorithm is further proposed to dynamically adjust the task offloading decision and compression ratio selection to minimize the end-to-end delay with the transmit power control being optimized by the successive convex approximation algorithm. Simulation results demonstrate that, compared to several benchmark algorithms, our proposed algorithm achieves the lowest end-to-end delay while guaranteeing the requirements on perception probability and queue stability effectively. © 1967-2012 IEEE.

关键词： Deep reinforcement learning

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Low-loading gold in situ doped with sulfur by biomolecule-assisted approach for promoted electrochemical carbon dioxide reduction

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Nano Research 2023年第2期16卷 2059-2064页

作者： Meijie Tan Xiaoqian Han Sen Ru Chao Zhang Zhouru Ji Zhaolin Shi Guomeng Qiao Yunying Wang Ruixue Cui Qiquan Luo Jiqing Jiao Yaguang Li Tongbu Lu MOE International Joint Laboratory of Materials Microstructure Institute for New Energy Materials and Low Carbon TechnologiesSchool of Materials Science and EngineeringTianjin University of TechnologyTianjin 300384China Institutes of Physical Science and Information Technology Anhui UniversityHefei 230601China Haihe Laboratory of Sustainable Chemical Transformations Tianjin 300192China College of Materials Science and Engineering State Key Laboratory of Bio-Fibers and Eco-TextilesQingdao UniversityQingdao 266071China Hebei Key Lab of Optic-electronic Information and Materials College of Physics Science and TechnologyInstitute of Life Science and Green DevelopmentHebei UniversityBaoding 071002China

For electrochemical carbon dioxide reduction(CO_(2)RR),CO_(2)-to-CO conversion is considered an ideal route towards carbon neutrality for practical ***(Au)is known as a promising catalyst with high selectivity for CO;however,it suffers from high cost and low mass-specific *** this study,we design and prepare a catalyst featuring uniform S-doped Au nanoparticles on N-doped carbon support(denoted as S-Au/NC)by an in situ synthesis strategy using *** S-Au/NC displays high activity and selectivity for CO in CO_(2)RR with a Au loading as low as 0.4 wt.%.The Faradaic efficiency of CO(FECO)for S-Au/NC is above 95%at−0.75 V(***);by contrast,the FECO of Au/NC(without S)is only 58%.The Tafel slope is 77.4 mV·dec−1,revealing a favorable kinetics ***,S-Au/NC exhibits an excellent long-term stability for CO_(2)*** functional theory(DFT)calculations reveal that the S dopant can boost the activity by reducing the free energy change of the potential-limiting step(formation of the*COOH intermediate).This work not only demonstrates a model catalyst featuring significantly reduced use of noble metals,but also establishes an in situ synthesis strategy for preparing high-performance catalysts.

关键词： electrochemical CO_(2)reduction nanocomposites heterogeneous catalyst in situ sulfured heteroatoms

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Over 18.2% efficiency of layer–by–layer all–polymer solar cells enabled by homoleptic iridium(Ⅲ)carbene complex as solid additive

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science Bulletin 2024年第18期69卷 2862-2869页

作者： Hang Zhou Yingjie Sun Miao Zhang Yuheng Ni Fenghua Zhang Sang Young Jeong Tianhuan Huang Xiong Li Han Young Woo Jian Zhang Wai-Yeung Wong Xiaoling Ma Fujun Zhang Key Laboratory of Luminescence and Optical Information(Ministry of Education) Beijing Jiaotong UniversityBeijing 100044China Department of Applied Biology and Chemical Technology and Research Institute for Smart Energy The Hong Kong Polytechnic UniversityHong Kong 999077China Department of Physics Beijing Technology and Business UniversityBeijing 100048China Organic Optoelectronic Materials Laboratory Department of ChemistryCollege of ScienceKorea UniversitySeoul 02841Republic of Korea School of Materials Science and Engineering Engineering Research Center of Electronic Information Materials and DevicesMinistry of EducationGuangxi Key Laboratory of Information MaterialsGuilin University of Electronic TechnologyGuilin 541004China Tangshan Research Institute of Beijing Jiaotong University Tangshan 063000China

The vertical phase distribution of active layers plays a vital role in balancing exciton dissociation and cha rge transport for achieving efficient polymer solar cells(PSCs).The layer-by-layer(LbL)PSCs are commonly prepared by using sequential spin-coating method from donor and acceptor solutions with distinct solvents and solvent *** enhanced exciton dissociation is expected in the LbL PSCs with efficient charge transport in the relatively neat donor or acceptor *** this work,a series of LbL all-polymer solar cells(APSCs)were fabricated with PM6 as donor and PY-DT as acceptor,and triplet material m-Ir(CPmPB)_(3)is deliberately incorporated into PY-DT layer to prolong exciton lifetimes of active *** power conversion efficiency(PCE)of LbL APSCs is improved to 18.24%from 17.32%by incorporating 0.3 wt%m-Ir(CPMPB)_(3)in PY-DT layer,benefiting from the simultaneously enhanced short-circuit current density(Isc)of 25.17 mA cm^(-2)and fill factor(FF)of 74.70%.The enhancement of PCE is attributed to the efficient energy transfer of m-Ir(CPmPB)_(3)to PM6 and PY-DT,resulting in the prolonged exciton lifetime in the active layer and the increased exciton diffusion *** efficient energy transfer from m-Ir(CPmPB)_(3)to PM6 and PY-DT layer can be confirmed by the increased photoluminescence(PL)intensity and the prolonged PL lifetime of PM6 and PY-DT in PM6+m-Ir(CPmPB)_(3)and PY-DT+m-Ir(CPmPB)_(3)*** study indicates that the triplet material as solid additive has great potential in fabricating efficient LbL APSCs by prolonging exciton lifetimes in active layers.

关键词： Layer-by-layer All-polymer solar cells Additive strategy Triplet material Energy transfer

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Metal-organic nanosheet assembly ions sieving membrane for precise lithium ion and anion/solvent separation toward robust lithium metal battery

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science China Chemistry 2024年第10期67卷 3320-3327页

作者： Jian-Qiang Shen Tian-Tian Zhao Ying-Li Song Lingjuan Zhang Ya-Nan Gao Xiao-Nan Cui Peng Zhao Xian-Ming Zhang Key Laboratory of Magnetic Molecules&Magnetic Information Materials Ministry of EducationSchool of Chemistry&Material ScienceShanxi Normal UniversityTaiyuan 030031China College of Chemistry and Chemical Engineering Taiyuan University of TechnologyTaiyuan 030024China

Metal-organic nanosheets(MONs)as a novel material with tunable pore structures and low mass transfer resistance,have emerged as molecular sieves for the separation of gases and *** theory,they can also serve as ion sieves for lithium metal batteries(LMBs),realizing the high-energy and dendritic free ***,there are rarely relevant reports,because it is difficult to simultaneously balance efficient ion sieving ability,high ion passing rate and high electrochemical ***,we synthesized a stable ultrathin MON[Zn_(2)(Bim)_(4)]([Zn_(2)(Bim)_(4)]Nanosheet,HBim=benzimidazolate),which can achieve both efficient lithium ion sieving ability,high lithium ion passing rate and high electrochemical stability at the same *** separator assembled by this MON exhibits high Li^(+)transfer number of 0.81 due to the accurate lithium ion and anion/solvent *** battery containing such separator shows high lithium ionic conductivity of 0.74 m S cm^(-1)and low activation energy of 0.099 eV,which can be attributed to the nanometer level thickness and the ion sieving *** is more,we realized the application of MONs-based ion sieves in LMBs with intercalation cathodes for the first *** the LiFePO_(4)|Li battery with as-assembled separator demonstrates improved Coulombic efficiency(>99%)and significantly extended cycling life(>1600 cycles)with 80%capacity retention.

关键词： lithium sieving membrane metal-organic nanosheets lithium metal battery lithium ion and anion separation lithium ion and solvent separation

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Temperature control method and verification for spaceborne atomic clock based on phase change technology 2

Temperature control method and verification for spaceborne a...

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2023 2nd International Conference on Mechanical, Aerospace technology and Materials Application, MATMA 2023

作者： Yang, Changpeng Ren, Hongyan Song, Yunfei Xu, Feng Yang, Huning Beijing Key Laboratory of Space Thermal Control Technology Beijing Institute of Spacecraft System Engineering Beijing100094 China School of Engineering Science University of Science and Technology of China Hefei230027 China

The spaceborne atomic clock, as the time reference for navigation signal generation and system ranging, is the core component of the satellite system payload, and temperature stability is one of the main factors affecting the output frequency stability of the atomic clock. To ensure its continuous and stable operation in orbit, the temperature control system needs to provide a good working temperature environment for it. This article takes the high stability temperature control of the rubidium atomic clock in low-Earth inclined orbit as the research background, and conducts research on temperature control methods and phase change devices based on phase change technology. Simulation analysis and in-orbit telemetry data show that, by utilizing the temperature stability characteristic during the phase change process, the phase change temperature control system effectively suppresses the temperature fluctuations of the rubidium atomic clock caused by drastic changes in the space thermal environment. © Published under licence by IOP Publishing Ltd.

关键词： Atomic clocks

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Swarming magnetic photonic-crystal microrobots withon-the-fly visual pH detection and self-regulated drug delivery

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InfoMat 2023年第10期5卷 64-79页

作者： Zheng Yu Luolin Li Fangzhi Mou Shimin Yu Di Zhang Manyi Yang Qing Zhao Huiru Ma Wei Luo Tianlong Li Jianguo Guan State Key Laboratory of Advanced Technology for Materials Synthesis and Processing International School of Materials Science and Engineering Wuhan University of TechnologyWuhanthe People's Republic of China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbinthe People's Republic of China Wuhan Institute of Photochemistry and Technology Wuhanthe People's Republic of China

Swarming magnetic micro/nanorobots hold great promise for biomedical applications,but at present suffer from inferior capabilities to perceive and respond to chemical signals in local *** we demonstrate swarming magnetic photonic crystal microrobots(PC-bots)capable of sponta-neously performing on-the-fly visual pH detection and self regulated drug delivery by perceiving local pH *** magnetic PC-bots consist of pH-responsive hydrogel microspheres with encapsulated one-dimensional periodic assemblies of Fe3O4 *** programming extemnal rotating magnetic fields,they can self-organize into large swarms with much-enhanced collective velocity to actively find targets while shining bright“blinking”structural *** approaching the target with abnormal pH conditions(*** ulcerated superficial tumor lesion),the PC-bots can visualize local pH changes on the fly via pH-responsive structural colors,and realize self-regulated release of the loaded drugs by recognizing local *** work facilita tes the develop-ment of intelligent micro/nanorobots for active“motile-targeting”tumor diag-nosis and treatment.

关键词： collective behaviors drug delivery micro/nanorobots on-the-fly sensing responsivephotonic crystals

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Prediction of NO_(x)concentration using modular long short-term memory neural network for municipal solid waste incineration

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Chinese Journal of Chemical engineering 2023年第4期56卷 46-57页

作者： Haoshan Duan Xi Meng Jian Tang Junfei Qiao Faculty of Information Technology Beijing University of TechnologyBeijing 100124China Beijing Laboratory of Smart Environmental Protection Beijing 100124China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing 100124China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Beijing 100124China

Air pollution control poses a major problem in the implementation of municipal solid waste incineration(MSWI).Accurate prediction of nitrogen oxides(NO_(x))concentration plays an important role in efficient NO_(x)emission *** this study,a modular long short-term memory(M-LSTM)network is developed to design an efficient prediction model for NO_(x)***,the fuzzy C means(FCM)algorithm is utilized to divide the task into several sub-tasks,aiming to realize the divide-and-conquer ability for complex ***,long short-term memory(LSTM)neural networks are applied to tackle corresponding sub-tasks,which can improve the prediction accuracy of the ***,a cooperative decision strategy is designed to guarantee the generalization performance during the testing or application ***,after being evaluated by a benchmark simulation,the proposed method is applied to a real MSWI *** the experimental results demonstrate the considerable prediction ability of the M-LSTM network.

关键词： Municipal solid waste incineration NO_(x)concentration prediction Modular neural network Model

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Retrieval of high spatial resolution mountainous land surface temperature considering topographic and adjacency effects

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science China Earth sciences 2024年第11期67卷 3610-3625页

作者： Zhiwei HE Bohui TANG Zhaoliang LI Faculty of Land Resources Engineering Kunming University of Science and TechnologyKunming 650093China Key Laboratory of Plateau Remote Sensing Department of Education of Yunnan ProvinceKunming 650093China State Key Lab of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Key Laboratory of Agricultural Remote Sensing Ministry of Agriculture and Rural AffairsInstitute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijing 100081China

Land surface temperature(LST) is a key parameter reflecting the interaction between land and atmosphere. Currently,thermal infrared(TIR) quantitative remote sensing technology is the only means to obtain large-scale, high spatial resolution LST. Accurately retrieving high spatial resolution mountainous LST(MLST) plays an important role in the study of mountain climate change. The complex terrain and strong spatial heterogeneity in mountainous areas change the geometric relationship between the surface and satellite sensors, affecting the radiation received by the sensors, and rendering the assumption of planar parallelism invalid. In this study, considering the influence of complex terrain in mountainous areas on atmospheric downward radiation and the thermal radiation contribution of adjacent pixels, a mountainous TIR radiative transfer model based on the sky view factor was developed. Combining with the atmospheric radiative transfer model MODTRAN 5.2, a nonlinear generalized split-window algorithm suitable for high spatial resolution MLST retrieval was constructed and applied to Landsat-9 TIRS-2satellite TIR remote sensing data. The analysis results indicate that neglecting the topographic and adjacency effects would lead to significant discrepancies in LST retrieval, with simulated data showing LST differences of up to 2.5 K. Furthermore, due to the lack of measured MLST in the field, the MLST accuracy obtained by this retrieval method was indirectly validated using the currently recognized highest-accuracy forward 3D radiative transfer model DART. The MLST and emissivity were input into the DART model to simulate the brightness temperature at the top of the atmosphere(TOA) of Landsat-9 band 10, and compared with the brightness temperature at TOA of Landsat-9 band 10. The RMSE(Root Mean Square Error) for the two subregions was0.50 and 0.61 K, respectively, indicating that the method proposed can retrieve high-precision MLST.

关键词： Mountainous land surface temperature Topographic and adjacency effects Nonlinear generalized split-window algorithm Landsat-9 data DART model

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