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Bulletin of the American Meteorological Society 2024年第8期105卷 S1-S11页

作者： Boyer, T. Blunden, J. Dunn, R.J.H. NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Met Office Hadley Centre Exeter United Kingdom European Centre for Medium-Range Weather Forecasts Reading United Kingdom University of Maryland College Park Maryland Scripps Institution of Oceanography University of California San Diego La Jolla California NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland Brandenburg University of Technology (BTU) Cottbus-Senftenberg Germany Servicio Meteorológico Nacional Buenos Aires Argentina NOAA/OAR Physical Sciences Laboratory Boulder Colorado European Centre for Medium-Range Weather Forecasts Bonn Germany Center for Geophysical Research and School of Physics University of Costa Rica San José Costa Rica Department of Meteorology and National Centre for Earth Observation University of Reading Reading United Kingdom Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Université Grenoble Alpes Institut des Géosciences de l’Environnement IRD CNRS Grenoble INP Grenoble France Hampton University Hampton Virginia Seychelles Meteorological Authority Mahe Seychelles Section for Glaciers Ice and Snow Norwegian Water Resources and Energy Directorate Oslo Norway National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Agriculture Osaka Metropolitan University Sakai Japan Science Faculty Universidad Nacional de Colombia Bogotá Colombia University of Bremen Bremen Germany NOAA Global Monitoring Laboratory Boulder Colorado Servicio Nacional de Meteorología e Hidrología del Perú Lima Perú Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CSIC-UV-GVA) Valencia Spain Hydro-Climate Extremes Lab (H-CEL) Ghent University Ghent Belgium Department o

In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. A

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Cellular automaton modeling of pedestrian movement behavior on an escalator

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Chinese Physics B 2018年第12期27卷 328-333页

作者： Fu-Rong Yue Juan Chen Jian Ma Wei-Guo Song Siu-Ming Lo School of Transportation and Logistics National Engineering Laboratory of Integrated Transportation Big Data Application TechnologySouthwest Jiaotong University Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention State Key Laboratory of Fire Science University of Science and Technology of China Department of Architectural and Civil Engineering City University of Hong Kong

As a convenient passenger transit facility between floors with different heights, escalators have been extensively used in shopping malls, metro stations, airport terminals, etc. Compared with other vertical transit facilities including stairs and elevators, escalators usually have large transit capacity. It is expected to reduce pedestrian traveling time and thus improve the quality of pedestrian’s experiences especially in jamming conditions. However, it is noticed that pedestrians may present different movement patterns, e.g., queuing on each step of the escalator, walking on the left-side and meanwhile standing on the right-side of the escalator. These different patterns affect the actual escalator traffic volume and finally the passenger spatiotemporal distribution in different built environments. Thus, in the present study, a microscopic cellular automaton(CA) simulation model considering pedestrian movement behavior on escalators is built. Simulations are performed considering different pedestrian movement speeds, queuing modes, and segregation on escalators with different escalator *** actual escalator capacities under different pedestrian movement patterns are investigated. It is found that walking on escalators will not always benefit escalator transit volume improvement, especially in jamming conditions.

关键词： cellular automaton pedestrian movement escalator capacity

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Correlation analysis of strongly fluctuating atomic volumes, charges, and stresses in body-centered cubic refractory high-entropy alloys

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Physical Review Materials 2020年第2期4卷 023608-023608页

作者： Shoji Ishibashi Yuji Ikeda Fritz Körmann Blazej Grabowski Jörg Neugebauer Computational Materials Design Max-Planck-Institut für Eisenforschung GmbH D-40237 Düsseldorf Germany Research Center for Computational Design of Advanced Functional Materials (CD-FMat) National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Ibaraki 305-8568 Japan Center for Materials Research by Information Integration (CMI2) Research and Services Division of Materials Data and Integrated System (MaDIS) National Institute for Materials Science (NIMS) Tsukuba Ibaraki 305-0047 Japan Institute of Materials Science University of Stuttgart Pfaffenwaldring 55 D-70569 Stuttgart Germany Materials Science and Engineering Delft University of Technology 2628 CD Delft The Netherlands

Local lattice distortions in a series of body-centered cubic alloys, including refractory high-entropy alloys, are investigated by means of atomic volumes, atomic charges, and atomic stresses defined by the Bader charge analysis based on first-principles calculations. Analyzing the extensive data sets, we find large distributions of these atomic properties for each element in each alloy, indicating a large impact of the varying local chemical environments. We show that these local-environment effects can be well understood and captured already by the first and the second nearest neighbor shells. Based on this insight, we employ linear regression models up to the second nearest neighbor shell to accurately predict these atomic properties. Finally, we find that the elementwise-averaged values of the atomic properties correlate linearly with the averaged valence-electron concentration of the considered alloys.

关键词： Body-centered cubic Disordered alloys Density functional theory First-principles calculations

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A survey on graph processing accelerators: Challenges and opportunities

arXiv

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arXiv 2019年

作者： Gui, Chuang-Yi Zheng, Long He, Bing-Sheng Liu, Cheng Chen, Xin-Yu Liao, Xiao-Fei Jin, Hai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China School of Computing National University of Singapore 117418 Singapore

Graph is a well known data structure to represent the associated relationships in a variety of applications, e.g., data science and machine learning. Despite a wealth of existing efforts on developing graph processing systems for improving the performance and/or energy efficiency on traditional architectures, dedicated hardware solutions, also referred to as graph processing accelerators, are essential and emerging to provide the benefits significantly beyond those pure software solutions can offer. In this paper, we conduct a systematical survey regarding the design and implementation of graph processing accelerator. Specifically, we review the relevant techniques in three core components toward a graph processing accelerator: preprocessing, parallel graph computation and runtime scheduling. We also examine the benchmarks and results in existing studies for evaluating a graph processing accelerator. Interestingly, we find that there is not an absolute winner for all three aspects in graph acceleration due to the diverse characteristics of graph processing and complexity of hardware configurations. We finially present to discuss several challenges in details, and to further explore the opportunities for the future research. Copyright © 2019, The Authors. All rights reserved.

关键词： Energy efficiency

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Fault-tolerant coherent H∞ control for linear quantum systems

arXiv

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arXiv 2020年

作者： Liu, Yanan Dong, Daoyi Petersen, Ian R. Gao, Qing Ding, Steven X. Yokoyama, Shota Yonezawa, Hidehiro School of Engineering and Information Technology University of New South Wales CanberraACT2600 Australia Center for Quantum Computation and Communication Technology Australian Research Council CanberraACT2600 Australia University of Duisburg-Essen Duisburg47057 Germany Research School of Electrical Energy and Materials Engineering Australian National University CanberraACT2601 Australia School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

Robustness and reliability are two key requirements for developing practical quantum control systems. The purpose of this paper is to design a coherent feedback controller for a class of linear quantum systems suffering from Markovian jumping faults so that the closed-loop quantum system has both fault tolerance and H∞ disturbance attenuation performance. This paper first extends the physical realization conditions from the time-invariant case to the time-varying case for linear stochastic quantum systems. By relating the fault tolerant H∞ control problem to the dissipation properties and the solutions of Riccati differential equations, an H∞ controller for the quantum system is then designed by solving a set of linear matrix inequalities (LMIs). In particular, an algorithm is employed to introduce additional noises and to construct the corresponding input matrices to ensure the physical realizability of the quantum controller. For real applications of the developed fault-tolerant control strategy, we present a linear quantum system example from quantum optics, where the amplitude of the pumping field randomly jumps among different values. It is demonstrated that a quantum H∞ controller can be designed and implemented using some basic optical components to achieve the desired control goal. Copyright © 2020, The Authors. All rights reserved.

关键词： Controllers

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Analyses of geographical observations in the Heihe River Basin: Perspectives from complexity theory

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Journal of Geographical Sciences 2019年第9期29卷 1441-1461页

作者： Gao Jianbo FANG Peng YUAN Lihua State Key Laboratory of Earth Surface Processes and Resource Ecology Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Institute of Complexity Science and Big Data Technology Guangxi UniversityNanning 530004China Wuhan National Laboratory for Optoelectronics Key Laboratory of In formation Storage SystemEngineering Research Center of Data Storage Systems and TechnologyMinistry of Education of ChinaSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Center for GeoData and Analysis Faculty of Geographical ScieneeBeijing Normal UniversityBeijing 100875China

Since 2005,dozens of geographical observational stations have been established in the Heihe River Basin(HRB),and by now a large amount of meteorological,hydrological,and ecological observations as well as data pertaining to water resources,soil and vegetation have been *** adequately analyze these available data and data to be further collected in future,we present a perspective from complexity *** concrete materials covered include a presentation of adaptive multiscale filter,which can readily determine arbitrary trends,maximally reduce noise,and reliably perform fractal and multifractal analysis,and a presentation of scale-dependent Lyapunov exponent(SDLE),which can reliably distinguish deterministic chaos from random processes,determine the error doubling time for prediction,and obtain the defining parameters of the process *** adaptive filter is illustrated by applying it to obtain the global warming trend and the Atlantic multidecadal oscillation from sea surface temperature data,and by applying it to some variables collected at the HRB to determine diurnal cycle and fractal *** SDLE is illustrated to determine intermittent chaos from river flow data.

关键词： Heihe River basin geographical observation complexity theory adaptive multiscale filter fractal analysis scale-dependent Lyapunov exponent

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Spatial optimization of rice systems with ratoon rice increases production and reduces methane emissions

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European Journal of Agronomy 2025年 170卷

作者： Qian Ding Yuechen Li Ruyin Cao Jin Chen Xiong Yao Wujun Zhang Chongqing Engineering Research Center for Remote Sensing Big Data Application Chongqing Jinfo Mountain National Field Scientific Observation and Research Station for Karst Ecosystem School of Geographical Sciences Southwest University Chongqing 400715 China Key Laboratory of Remote Sensing Application and Innovation Chongqing 401147 China Key Laboratory of Monitoring Evaluation and Early Warning of Territorial Spatial Planning Implementation Ministry of Natural Resources Chongqing 401147 China School of Resources and Environment University of Electronic Science and Technology of China Chengdu Sichuan 611731 China State Key Laboratory of Remote Sensing Science Faculty of Geographical Science Beijing Normal University Beijing 100875 China Chongqing Rice Ratooning Research Center Chongqing Academy of Agricultural Sciences Chongqing 401329 China

The ratoon rice system (RR) has potential for increasing rice production and reducing environmental impacts. However, research on the spatial optimization of rice systems with RR to balance rice production and environmental protection is limited. We explored the trade-offs in production and methane emissions between RR, the single-season rice system (SR), and the double-season rice system (DR) by employing spatial optimization as a research paradigm. On the basis of 70 field sites, we analyzed the yield and methane emission differences among RR, SR and DR. A random forest model was employed to assess the suitability of RR in China's rice fields. The potential of RR to increase production and reduce methane emissions in medium- and high-suitability areas under different spatial cultivation strategies was quantified through scenario simulations. We found that the annual yield of RR (12.40 ± 1.98 t ha −1 ) was significantly higher than that of SR (73.53 %) but less than that of DR (1.35 %). However, its methane emissions (0.42 ± 0.19 t ha −1 ) were lower than those of DR (38.25 %) but higher than those of SR (27.43 %). Suitability analysis revealed that 73.82 % of rice fields nationwide are suitable for RR, with 99.21 % suitability in DR areas. Scenario simulations indicated that, with the optimal spatial layout of rice systems, RR could increase rice production by 14.55 % without increasing methane emissions or reduce methane emissions by 5.31 % while maintaining rice production. This study demonstrated the significant potential of RR to increase rice production while reducing environmental impacts through spatial optimization and offered an innovative approach for sustainable rice production planning in China.

关键词： China Methane emission Production Ratoon rice Suitability

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硝酸盐通过上调神经元sialin减轻TPPP磷酸化进而缓解阿尔茨海默病髓鞘丢失并改善认知障碍（英文）

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Science Bulletin 2025年第8期 1224-1229页

作者：陈欣月胡耿常丽荣李晓钰唐毅武艳张然张春梅王劲松王雪王松灵 Department of Biochemistry and Molecular Biology School of Basic Medical Sciences Beijing Laboratory of Oral Health Capital Medical University Key Laboratory of Big Data-Based Precision Medicine School of Engineering Medicine Beihang University Beijing Key Laboratory of Neural Regeneration and Repair Department of Anatomy School of Basic Medical Sciences Beijing Institute of Brain Disorders Capital Medical University Innovation Center for Neurological Disorders Department of Neurology Xuanwu Hospital Capital Medical University Beijing Key Laboratory of Traditional Chinese Veterinary Medicine Department of Veterinary Medicine Animal Science and Technology College Beijing University of Agriculture Department of Oral Pathology Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices National Human Brain Bank for Development and Function Institute of Basic Medical Sciences Chinese Academy of Medical Sciences School of Basic Medicine Peking Union Medical College Laboratory of Homeostatic Medicine School of Medicine Southern University of Science and Technology Research Units of Tooth Development and Regeneration Chinese Academy of Medical Sciences

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline. The pathological hallmarks of AD include the deposition of β-amyloid (Aβ) plaques,hyperphosphorylation of tau protein, synaptic loss, and reactive astrogliosis in the brain [1]. As there is still no effective therapy for AD, the development of novel treatment strategies is imperative.

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PHD: A Deep Learning Based Human Detection Framework for Panoramic Videos

PHD: A Deep Learning Based Human Detection Framework for Pan...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Jinting Tang Zhenhui Chen Yongkai Huo Peichang Zhang National Engineering Laboratory for Big Data System Computing Technology Research Institute for Future Media Computing School of Computer Science and Software Engineering Shenzhen University Shenzhen China The College of Information Engineering Shenzhen University Shenzhen China

Panoramic video has attracted substantial research attention as the coming video format. It is capable of providing 360 degree immersive experience of omnidirectional visual information. State-of-the-art detection networks may fail to detect humans on spherical images, which are normally represented in deformed rectangular shapes. In this paper, we propose a socalled Panoramic Human Detection (PHD) scheme to address the task of human detection in panoramic videos. Moreover, the PHD method is designed to detect humans by extracting multiple overlapping sub-images from each integral spherical image, where three-dimensional rotation of spherical images is employed to ensure consistency of sub-images. Two detection box filters are designed for removing redundant boxes. Our PHD method is capable of accomplishing the task of human detection in various panoramic video types. Experiments prove that our PHD method outperforms the baseline by 35% and 48.6% in terms of precision and recall, respectively.

关键词： Videos Task analysis Feature extraction Matrices Visualization Strain Transmission line matrix methods

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The roles of urban buildings and vegetation in adjusting seasonal and daily air temperature 4

The roles of urban buildings and vegetation in adjusting sea...

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4th ISPRS Geospatial Week 2019

作者： Lan, Y. Huang, Z. Guo, R. Zhan, Q. Research Institute for Smart Cities School of Architecture and Urban Planning Shenzhen University Shenzhen China Shenzhen Key Laboratory of Spatial Information Smart Sensing and Services Shenzhen University China Guangdong Key Laboratory of Urban Informatics Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China School of Urban Design Wuhan University Wuhan China

Exploring the spatiotemporal patterns of the relationships between urban indicators and urban temperature is essential to improve the mitigation effectiveness when we intend to adjust built environment for moderating urban thermal environment. In this study, RS, GIS technology and statistical methods were involved to investigate the spatiotemporal patterns of the impacts of urban buildings and vegetation on Air Temperature (AT). Building Density (BD) and Normalized Difference Vegetation Index (NDVI) are the indicators for urban buildings and vegetation respectively. The objectives of this study are: 1) to determine an appropriate scale for examining the building-AT relationships and vegetation-AT relationships;2) to explore the seasonal and daily characteristics of these relationships;and 3) to compare the effects of urban buildings and vegetation. The results show that, for both summer and winter, a scale of 200–250 m is optimal for examining building-AT relationships, and 960–1020 m is the desirable scale for studying vegetation-AT relationships. Based on the optimal scales, we find that for both buildings and vegetation, they only significantly impact night-time temperature in both summer and winter. For seasonal comparison, the building-AT relationships and vegetation-AT relationships are relatively stronger in summer than in winter, which are indicated by R-square of the regression results. When comparing the effects of urban building and vegetation, we find that increasing vegetation is more effective than reduce buildings to achieve the same air temperature reduction. Our findings are conducive to generating space-time targeted Urban Heat Island (UHI) mitigation strategies. © Authors 2019.

关键词： Vegetation

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