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2020 International Conference on Wireless Communication and Sensor Networks, icWCSN 2020

作者： Luo, Aimin Yi, Shuanghui Liu, Junxian Kou, Yuxiao Gao, Lanlan Zhang, Mengmeng Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha Hunan410073 China National Key Laboratory for Complex System Simulation Beijing China Academy of Military Science of the PLA Beijing100000 China

ISBN: (纸本)9781450377638

To address the limitations of the FDNA approach, in this paper, we analyze the dependency of the receiver node on the feeder nodes as well as the impact of the node's operability level on the system effectiveness, and improve the FDNA approach. We also propose a computing method for system effectiveness based on an improved FDNA model, and conduct relevant case verification. © 2020 ACM.

关键词： Information systems

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Enhancing through-plane thermal conductivity of fluoropolymer composite by developing in situ nano-urethane linkage at graphene–graphene interface

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Nano Research 2020年第10期13卷 2741-2748页

作者： Muhammad Maqbool Haichang Guo Akbar Bashir Ali Usman Adeel YAbid Guansong He Yanjuan Ren Zeeshan Ali Shulin Bai Department of Materials Science and Engineering Key Laboratory of High Eenergy Density Physics Simulation(HEDPS)Center of Applied Physics and Technology(CAPT)/Laboratory of Turbulence and Complex System(LTCS)Key Laboratory of Polymer Chemistry and Physics of Ministry of EducationCollege of EngineeringPeking UniversityBejing 100871China Institute of Chemical Materials Chinese Academy of Engineering Physics(CA EP)Mianyang 621900China School of Chemical and Materials Engineering(SCME) National University of Sciences and Technology(NUST)Islamabad 4000Pakistan

Attributed to the intense development and complexity in electronic devices,energy dissipation is becoming more essential *** carbonaceous materials particularly graphene(Gr)-based thermal interface materials(TIMs)are exceptional in heat ***,because of the anisotropic behavior of Gr in composites,the TIMs having outstanding through-plane thermal conductivity(┴TC)are needed to fulfill the upcoming innovation in numerous *** order to achieve this,herein,nano-urethane linkage-based modified Gr and carbon fibers architecture termed as nanourethane linkage(NUL)-Gr/carbon fibers(CFs)is ***,toluene diisocyanate is utilized to develop a novel but simple NUL to shape a new interface between graphene ***,the prepared composite of NUL-Gr/CFs with polyvinylidene fluoride matrix shows outstanding performance in heat *** to the unique structure of NUL-Gr/CFs,an unprecedented value of┴TC(~7.96 W·m^–1·K^–1)is achieved at a low filler fraction of 13.8 wt.%which translates into an improvement of^3,980%of pristine *** achieved outcomes elucidate the significance of the covalent interaction between graphene sheets as well as strong bonding among graphene and matrix in the composites and manifest the potential of proposed NUL-Gr/CFs architecture for practical applications.

关键词： graphene thermal interface materials polymer composites

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Mapping anthropogenic emissions in China at 1 km spatial resolution and its application in air quality modeling

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Science Bulletin 2021年第6期66卷 612-620,M0004页

作者： Bo Zheng Jing Cheng Guannan Geng Xin Wang Meng Li Qinren Shi Ji Qi Yu Lei Qiang Zhang Kebin He Institute of Environment and Ecology Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China China National Environmental Monitoring Center Beijing 100012China Center for Environmental Risk and Damage Assessment Chinese Academy of Environmental PlanningBeijing 100012China Center for Regional Air Quality Simulation and Control Chinese Academy of Environmental PlanningBeijing 100012China

New challenges are emerging in fine-scale air quality modeling in China due to a lack of high-resolution emission ***,only a few emission sources have accurate geographic locations(point sources),while a large part of sources,including industrial plants,are estimated as provincial totals(area sources)and spatially disaggregated onto grid cells based on proxies;this approach is reasonable to some extent but is highly questionable at fine spatial ***,we compile a new comprehensive point source database that includes nearly 100,000 industrial facilities in *** couple it with the frame of Multi-resolution Emission Inventory for China(MEIC),estimate point source emissions,combine point and area sources,and finally map China’s anthropogenic emissions of 2013 at the spatial resolution of 30’’*30’’(~1 km).Consequently,the percentages of point source emissions in the total emissions increase from less than 30%in the MEIC up to a maximum of 84%for SO_(2)in *** new point source-based emission maps show the uncoupled distribution of emissions and populations in space at fine spatial scales,however,such a pattern cannot be reproduced by any spatial proxy used in the conventional emissions *** new accurate high-resolution emission mapping approach reduces the modeled biases of air pollutant concentrations in the densely populated areas compared to the raw MEIC inventory,thus improving the assessment of population exposure.

关键词： Anthropogenic emission inventory High-resolution mapping Air quality modeling

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气候变化情景下中国因高温造成的劳动生产力损失预估

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Science Bulletin 2023年第22期68卷 2827-2837,M0006页

作者：程亮亮谷魁英赵亮王会滨纪思翰刘钊黄建斌陈艺丹高学杰徐影王灿罗勇蔡闻佳宫鹏梁万年黄存瑞 School of Public Health Sun Yat-sen UniversityGuangzhou 510080China Vanke School of Public Health Tsinghua UniversityBeijing 100084China State Key Laboratory of Numerical Modelling for Atmosphere Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China School of Linkong Economics and Management Beijing Institute of Economics and ManagementBeijing 100102China Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100190China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100084China Climate Change Research Centre Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China National Climate Centre China Meteorological AdministrationBeijing 100081China Department of Earth System Science Ministry of Education Key Laboratory for Earth System ModelingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China Department of Earth Sciences and Department of Geography University of Hong KongHong Kong 999077China Institute of Healthy Chin1 Tsinghua UniversityBeijing 100084China

气候变化背景下,高温会影响职业人群的工作效率并造成劳动生产力损失.本研究基于区域气候模式并采用本土化的暴露-反应函数,预估了未来气候变化情景下中国因高温造成的劳动时间损失.研究发现,与基线期的213亿小时高温相关劳动时间损失相... 详细信息

气候变化背景下,高温会影响职业人群的工作效率并造成劳动生产力损失.本研究基于区域气候模式并采用本土化的暴露-反应函数,预估了未来气候变化情景下中国因高温造成的劳动时间损失.研究发现,与基线期的213亿小时高温相关劳动时间损失相比,到21世纪末在RCP2.6、RCP4.5和RCP8.5情景下,损失将分别增加-17.8%、10.8%及121.1%.损失主要集中在华南、华中和华东地区,其中广东与河南将占到全国总损失的四分之一.因为这些区域的温度将更高、人口更密集、户外工作者在总人群中的比例较大.与RCP2.6、RCP4.5和RCP8.5情景相比,若能实现1.5℃温控目标,将分别能够避免11.8%、33.7%和53.9%的劳动时间损失,相当于避免了全中国21世纪中叶的0.1%、0.6%及1.4%的年均GDP损失.本研究显示未来气候变化会给中国造成严重的热相关劳动生产力损失,并强调亟需采取因地制宜的气候减缓及适应策略以保护职业人群健康.本研究对其他与中国相似的发展中国家同样具有重要意义.

关键词： Climate change Heat stress Labor Work hours lost Occupational health

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Air pollution characteristics and their relationship with emissions and meteorology in the Yangtze River Delta region during 2014–2016

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Journal of Environmental Sciences 2019年第9期31卷 8-20页

作者： Tao Ma Fengkui Duan Kebin He Yu Qin Dan Tong Guannan Geng Xuyan Liu Hui Li Shuo Yang Siqi Ye Beiyao Xu Qiang Zhang Yongliang Ma State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing Key Laboratory of Indoor Air Quality Evaluation and Control Tsinghua University Beijing 100084 China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System Science Tsinghua University Beijing 100084 China National Satellite Meteorological Center Beijing 100081 China College of Resources and Environmental Sciences China Agricultural University Beijing 100094 China

With rapid economic growth and urbanization, the Yangtze River Delta(YRD) region in China has experienced serious air pollution challenges. In this study, we analyzed the air pollution characteristics and their relationship with emissions and meteorology in the YRD region during 2014–2016. In recent years, the concentrations of all air pollutants, except O3,decreased. Spatially, the PM2.5, PM10, SO2, and CO concentrations were higher in the northern YRD region, and NO2 and O3 were higher in the central YRD region. Based on the number of non-attainment days(i.e., days with air quality index greater than 100), PM2.5 was the largest contributor to air pollution in the YRD region, followed by O3, PM10, and ***, particulate matter pollution has declined gradually, while O3 pollution *** conditions mainly influenced day-to-day variations in pollutant concentrations. PM2.5 concentration was inversely related to wind speed, while O3 concentration was positively correlated with temperature and negatively correlated with relative *** air quality improvement in recent years was mainly attributed to emission *** 2014–2016, PM2.5, PM10, SO2, NOx, CO, NH3, and volatile organic compound(VOC)emissions in the YRD region were reduced by 26.3%, 29.2%, 32.4%, 8.1%, 15.9%, 4.5%, and0.3%, respectively. Regional transport also contributed to the air pollution. During regional haze periods, pollutants from North China and East China aggravated the pollution in the YRD region. Our findings suggest that emission reduction and regional joint prevention and control helped to improve the air quality in the YRD region.

关键词： Air pollution Spatiotemporal variation Meteorological condition Emission inventory Regional transport Yangtze River Delta

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A Comprehensive Evaluation Framework for Deep Model Robustness

arXiv

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arXiv 2021年

作者： Guo, Jun Bao, Wei Wang, Jiakai Ma, Yuqing Gao, Xinghai Xiao, Gang Liu, Aishan Dong, Jian Liu, Xianglong Wu, Wenjun State Key Lab of Software Development Environment Beihang University Beijing China China Electronics Standardization Institute Beijing China Zhongguancun Laboratory Beijing China Institute of Unmanned System Beihang University Beijing China National Key Laboratory for Complex Systems Simulation Beijing China

Deep neural networks (DNNs) have achieved remarkable performance across a wide range of applications, while they are vulnerable to adversarial examples, which motivates the evaluation and benchmark of model robustness. However, current evaluations usually use simple metrics to study the performance of defenses, which are far from understanding the limitation and weaknesses of these defense methods. Thus, most proposed defenses are quickly shown to be attacked successfully, which results in the "arm race" phenomenon between attack and defense. To mitigate this problem, we establish a model robustness evaluation framework containing 23 comprehensive and rigorous metrics, which consider two key perspectives of adversarial learning (i.e., data and model). Through neuron coverage and data imperceptibility, we use data-oriented metrics to measure the integrity of test examples;by delving into model structure and behavior, we exploit model-oriented metrics to further evaluate robustness in the adversarial setting. To fully demonstrate the effectiveness of our framework, we conduct large-scale experiments on multiple datasets including CIFAR-10, SVHN, and Im-ageNet using different models and defenses with our open-source platform. Overall, our paper provides a comprehensive evaluation framework, where re-searchers could conduct comprehensive and fast evaluations using the open-source toolkit, and the analytical results could inspire deeper understanding and further improvement to the model robustness. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

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A Solution Analysis of U.S. Weapon Equipment systems-of-systems Development and Application

A Solution Analysis of U.S. Weapon Equipment Systems-of-Syst...

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International Conference on Information Science and Control Engineering (ICISCE)

作者： Menglong Lin Shuanghui Yi Mengmeng Zhang Zhen Shu Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha China National Key Laboratory for Complex System Simulation Beijing China

In recent years, the development and deployment of the U.S. weapon equipment systems-of-systems (SoS) have yielded rich research results. However, there are still large gaps in the SoS development, joint testing, and design and acquisition of our own equipment SoS. The barriers of these steps have not yet been opened up. This article mainly analyzes the solutions of the U.S. weapon equipment SoS from three aspects, such as capability-based requirement generation and architecture design technology, interconnected-oriented integration test technology, and weapon equipment design and acquisition technology based on complex adaptive systems. We explore key technologies involved in order to form an overall understanding and explore related research approaches.

关键词： Technological innovation Adaptive systems Weapons Agent-based modeling Planning Sustainable development system analysis and design

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Logarithm Radon-Fourier transform for high speed small target detection with atmospheric resistance effect

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Digital Signal Processing: A Review Journal 2025年 165卷

作者： Sun, Difeng Xu, He Wu, Zutang Li, Jin Wu, Youcao Li, Jianbing State Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System College of Electronic Science and Technology National University of Defense Technology Changsha410073 China National Key Laboratory of Intense Pulsed Radiation Simulation and Effect Northwest Institute of Nuclear Technology Xi'an710024 China Academy of Military Science of the People's Liberation Army Beijing100071 China

Detecting high-speed, small targets in air is challenging due to their complex non-linear motion model and range migration effects. Traditional finite order polynomial models often fail to account for atmospheric drag accurately. This paper introduces a logarithmic relationship between range and time to model this motion, employing the Logarithmic Radon-Fourier Transform (LRFT) for accurately compensating the envelope and phase migration over extended accumulation periods. It offers both the ergodic search method and the fast implementation method for solving LRFT, along with a theoretical analysis of lobe location and amplitude. simulation results indicate that compared with traditional RFT-based methods, LRFT improves accumulation gain, enhances the main lobe's relative amplitude over sidelobes, and offers better detection performance in noisy environments. It provides more accurate recovery of target motion and improved target distinction capabilities. These benefits over traditional methods are especially evident when the product of the attenuation coefficient α, the initial velocity v0, and the total coherent accumulation time TM exceeds a specific threshold. © 2025 Elsevier Inc.

关键词： Fast Fourier transforms

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食品系统与气候变化、空气污染之间的相互作用综述（英文）

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Engineering 2025年第1期 215-233页

作者： Chaopeng Hong Rui Zhong Mengyao Xu Peidong He Huibin Mo Yue Qin Danna Shi Xinlei Chen Kebin He Qiang Zhang Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration Institute of Environment and Ecology Shenzhen International Graduate School Tsinghua University State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex College of Environmental Sciences and Engineering Peking University Institute of Data and Information Shenzhen International Graduate School Tsinghua University State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System Science Tsinghua University

Food systems are deeply affected by climate change and air pollution, while being key contributors to these environmental challenges. Understanding the complex interactions among food systems, climate change, and air pollution is crucial for mitigating climate change, improving air quality, and promoting the sustainable development of food systems. However, the literature lacks a comprehensive review of these interactions, particularly in the current phase of rapid development in the field. To address this gap, this study systematically reviews recent research on the impacts of climate change and air pollution on food systems, as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution. In addition, this study summarizes various strategies for mitigation and adaptation, including adjustments in agricultural practices and food supply chains. Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions. This review offers a critical overview of current research on the interactions among food systems, climate change, and air pollution and highlights future research directions to support the transition to sustainable food systems.

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Continuous and comprehensive atmospheric observations in Beijing:a station to understand the complex urban atmospheric environment

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Big Earth Data 2020年第3期4卷 295-321页

作者： Yongchun Liu Chao Yan Zemin Feng Feixue Zheng Xiaolong Fan Yusheng Zhang Chang Li Ying Zhou Zhuohui Lin Yishou Guo Ying Zhang Li Ma Wenshuo Zhou Zhikun Liu Lubna Dada Kaspar Dallenbach Jenni Kontkanen Runlong Cai Tommy Chan Biwu Chu Wei Du Lei Yao Yonghong Wang Jing Cai Juha Kangasluoma Tom Kokkonen Joni Kujansuu Anton Rusanen Chenjuan Deng Yueyun Fu Rujing Yin Xiaoxiao Li Yiqun Lu Yiliang Liu Chaofan Lian Dongsen Yang Weigang Wang Maofa Ge Yuesi Wang Douglas R.Worsnop Heikki Junninen Hong He Veli-Matti Kerminen Jun Zheng Lin Wang Jingkun Jiang Tuukka Petaja Federico Bianchi Markku Kulmala Aerosol and Haze Laboratory Beijing Advanced Innovation Center for Soft Matter Science and EngineeringBeijing University of Chemical TechnologyBeijingChina Institute for Atmospheric and Earth System Research/Physics Faculty of ScienceUniversity of HelsinkiHelsinkiFinland State Key Joint Laboratory of Environment Simulation and Pollution Control State Environmental Protection Key Laboratory of Sources and Control of Air Pollution ComplexSchool of EnvironmentTsinghua UniversityBeijingChina State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijingChina Department of Environmental Science&Engineering Fudan UniversityShanghaiChina State Key Laboratory for Structural Chemistry of Unstable and Stable Species Beijing National Laboratory for Molecular SciencesInstitute of ChemistryChinese Academy of SciencesBeijingChina Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Nanjing University of Information Science&TechnologyNanjingChina State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina Aerodyne Research Inc. BillericaMassachusettsUSA Institute of Physics University of TartuTartuEstonia Joint International Research Laboratory of Atmospheric and Earth System Sciences School of Atmospheric SciencesNanjing UniversityNanjingChina

Due to profound impact on climate and human health,air quality has attracted attention from all levels of the civil *** key step in the provision of required tools for the society to tackle the complex air quality problem is to characterize it in a comprehensive manner with a long-term ***,we describe a continuous and comprehensive observation station and its accompanying state-ofthe-art instrumentation that was established to investigate the complex urban atmospheric environment in a rapidly developing Chinese *** station,located in downtown Beijing,aims to study air quality by identifying the major atmospheric pollutants and key processes determining their formation and loss mechanisms.A few hundreds of parameters are continuously measured with the state-of-the-art instruments,including trace gas concentrations,aerosol particle size distributions,and mass concentrations,covering aerosol particle chemical composition from molecules to micrometer-sized aerosol *** produced long-term,comprehensive big data with around 1�10^(11)bytes per *** this paper,we provide an overview on the facilities of the station,the instrumentation used,the workflow of continuous observations and examples of results from 2018 to 2019 and a basis for establishing a modern long-term,comprehensive atmospheric urban observation station in other megacities.

关键词： Continuous and comprehensive atmospheric observation air pollution complex photochemical smog haze new particle formation

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