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SSRN 2023年

作者： Sun, Qiyang Hou, Songrui Wei, Bin Su, Yaokun Ortiz, Victor Sun, Bo Lin, Jiao Y.Y. Smith, Hillary Danilkin, Sergey Abernathy, Douglas L. Wilson, Richard Li, Chen Mechanical Engineering University of California Riverside RiversideCA92521 United States Materials Science and Engineering University of California Riverside RiversideCA92521 United States Henan Key Laboratory of Materials on Deep-Earth Engineering School of Materials Science and Engineering Henan Polytechnic University Jiaozuo454000 China Tsinghua-Berkeley Shenzhen Institute Guangdong Provincial Key Laboratory of Thermal Management Engineering and Materials TSIGS Tsinghua University Shenzhen518055 China Neutron Data Analysis and Visualization Division Oak Ridge National Laboratory Oak RidgeTN37830 United States Department of Physics and Astronomy Swarthmore College SwarthmorePA19081 United States Australian Centre for Neutron Scattering Australian Nuclear Science and Technology Organization Lucas HeightsNSW2234 Australia Neutron Scattering Division Oak Ridge National Laboratory Oak RidgeTN37830 United States

Nickel (II) oxide is a prominent candidate for spintronic and spin-caloritronic applications operating at room temperature. Although there are extensive studies on nickel oxide, the roles of magnon- and spin-phonon interactions on thermal transport are not well understood. In the present work, the relationship between spin-phonon interactions and thermal transport is investigated by performing inelastic neutron scattering, time-domain thermoreflectance thermal conductivity measurements, and atomistic thermal transport calculations. Inelastic neutron scattering measurements of the magnon lifetime imply that magnon thermal conductivity is trivial, and so heat is conducted only by phonons. Time-domain thermoreflectance measurements of the thermal conductivity vs. temperature follow T-1.47 in the antiferromagnetic phase. This temperature dependence cannot be explained by phonon-isotope and phonon-defect scattering or phonon softening. Instead, we attribute this to magnon-phonon scattering and spin-induced dynamic symmetry breaking. The spin-phonon interactions are saturated in the paramagnetic phase and lead to a weaker temperature dependence of T-1.00 at 550-700 K. These results reveal the importance of spin-phonon interactions on lattice thermal transport, shedding light on the engineering of functional antiferromagnetic spintronic and spin-caloritronic materials through these interactions. © 2023, The Authors. All rights reserved.

关键词： Nickel oxide

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Spatiotemporal Characteristics of Urbanization in the Taiwan Strait Based on Nighttime Light data from 1992 to 2020

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Remote Sensing 2023年第13期15卷 3226页

作者： Ye, Yuqing Yun, Guoliang He, Yuanrong Lin, Ruijin He, Tingting Qian, Zhiheng College of Computer and Information Engineering Xiamen University of Technology Xiamen361024 China Big Data Institute of Digital Natural Disaster Monitoring in Fujian Xiamen University of Technology Xiamen361024 China College of Urban and Environmental Sciences Key Laboratory for Earth Surface Processes of the Ministry of Education Peking University Beijing100871 China

Urbanization is a crucial indicator which reflects the socio-economic development of a country or region. The regions across the Taiwan Strait (TSR) have garnered attention worldwide as being representative of typical urbanization development along the southeastern coast. Currently, research in the TSR predominantly focuses on individual regions, with limited academic achievements comparing urbanization paths across the strait. In particular, the domain of comparative analysis of the spatiotemporal characteristics of urbanization dynamics in TSR by using long time series of nighttime light data remains largely underexplored. Therefore, this study focused on comparing the urbanization paths in the TSR and analyzing the spatiotemporal characteristics of urbanization by using the long-term nighttime light data from 1992 to 2020. Additionally, some methods such as Theil–Sen median trend analysis, Mann–Kendall significance test, Hurst exponent, spatial statistics, and time series were used to quantitatively analyze the spatial distribution patterns and temporal trends of nighttime lights in the TSR since 1992. The results were as follows: (1) From 1992 to 2020, the spatial distribution of nighttime light data in TSR exhibited significant spatial heterogeneity, with high-value areas mainly located in southeastern Fujian and northwestern Taiwan, while low-value areas were concentrated in Fujian’s inland regions;(2) During this period, nighttime lighting data increased from 729,863 in 1992 to 2,729,052 in 2020, and the percentage of its high-value (40–063) increased from 2.59% in 1992 to 12.22% in 2020;(3) Comparison of nighttime light data across representative cities from Taiwan (Taipei, Hsinchu) and Fujian (Xiamen, Fuzhou) uncovered distinct growth patterns—while Taiwanese cities had a high initial brightness value (the lowest value in the last 30 years was 518,379.4), their growth was relatively slow (average growth rate of 17%);Fujian cities, on the other hand, started

关键词： Time series

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First-Principles Calculation of Ferromagnetic Elements (Fe, Co)-Doped Znv2o4

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SSRN 2022年

作者： Luo, Jiaolian Liu, Xingwang Yang, Anqi Xie, Zhenyu School of materials science and engineering Guizhou Minzu University Guiyang550025 China Special and Key Laboratory of Guizhou Provincial Higher Education for GreenEnergySaving Materials Guiyang550025 China College of Big Data and Information Engineering Guizhou University Guiyang550025 China Architectural Engineering College Guizhou Minzu University Guiyang50025 China

ZnV 2 O 4 with spinel structure has been proved to emit light mainly in the ultraviolet region, expanding the response range of ZnV 2 O 4 in the visible region is of great significance to explore its wider application. Therefore, the electronic structure, optical properties and magnetic changes of ferromagnetic elements Fe, Co doped ZnV 2 O 4 are calculated by using the first-principles under density functional theory. The results show that the doping of Fe and Co leads to the increase of energy band gap, the energy band changes from indirect band gap to direct band gap after doping Co, which is closely related to the direct electron transition of Co itself. The introduced orbital electrons of Fe-3d and Co-3d contribute greatly to the composition of valence band and conduction band near Fermi level. In addition, in the visible region, profit from the doping of Co element, the photoelectric characteristics of ZnV 2 O 4 have been greatly improved and there is a red shift phenomenon, which provides important guiding significance for the potential application of ZnV 2 O 4 in photoelectric devices. © 2022, The Authors. All rights reserved.

关键词： Binary alloys

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Anomaly detection mechanism based on hierarchical weights through large-scale log data

Anomaly detection mechanism based on hierarchical weights th...

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2021 International Conference on Computer Communication and Artificial Intelligence, CCAI 2021

作者： Xi, Lanlan Xin, Yang Luo, Shoushan Shang, Yanlei Tang, Qifeng University of Posts and Telecommunications School of Beijing Institute of Cyberspace Security Beijing China University of Postsand Telecommunications School of Beijing Institute of Cyberspace Security Beijing China Guizhou Provincial Key Laboratory of Public Big Data Guizhou University Beijing China National Engineering Laboratory for Big Data Distribution and Exchange Technologies Shanghai China China-Europe Digital Economy Expert Group Shanghai China

ISBN: (纸本)9781728194011

In order to realize Intelligent Disaster Recovery and break the traditional reactive backup mode, it is necessary to forecast the potential system anomalies, and proactively backup the real-time datas and configurations. System logs record the running status as well as the critical events (including errors and warnings), which can help to detect system performance, debug system faults and analyze the causes of anomalies. What's more, with the features of real-time, hierarchies and easy-access, log data can be an ideal source for monitoring system status. To reduce the complexity and improve the robustness and practicability of existing log-based anomaly detection methods, we propose a new anomaly detection mechanism based on hierarchical weights, which can deal with unstable log data. We firstly extract semantic information of log strings, and get the word-level weights by SIF algorithm to embed log strings into vectors, which are then feed into attention-based Long Short-Term Memory(LSTM) deep learning network model. In addition to get sentence-level weight which can be used to explore the interdependence between different log sequences and improve the accuracy, we utilize attention weights to help with building workflow to diagnose the abnormal points in the execution of a specific task. Our experimental results show that the hierarchical weights mechanism can effectively improve accuracy of perdition task and reduce complexity of the model, which provides the feasibility foundation support for Intelligent Disaster Recovery. © 2021 IEEE.

关键词： Anomaly detection

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An Efficient Implementation for Bayesian Manifold Regularization Method

An Efficient Implementation for Bayesian Manifold Regulariza...

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IEEE Conference on Decision and Control

作者： Junpeng Zhang Yue Ju Bo Wahlberg Biqiang Mu Tianshi Chen School of Data Science and Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Instituite of Technology Stockholm Sweden Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and System Science Chinese Academy of Sciences Beijing China

When applying the Bayesian manifold regularization method to function estimation problem with manifold constraints, the direct implementation has computational complexity $\mathcal{O}(N^{3})$ , where $N$ is the number of input-output data measurements. This becomes particularly costly when $N$ is large. In this paper, we propose a more efficient implementation based on the Kalman filter and smoother using a state-space model realization of the underlying Gaussian process. Moreover, we explore the sequentially semi-separable structure of the Laplacian matrix and the posterior covariance matrix. Our proposed implementation has computational complexity $\mathcal{O}(N)$ and thus can be applied to large data problems. We exemplify the effectiveness of our proposed implementation through numerical simulations.

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A Recommendation Method for Highly Sparse dataset Based on Teaching Recommendation Factorization Machines

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Computers, Materials & Continua 2020年第9期64卷 1959-1975页

作者： Dunhong Yao Shijun Li Ang Li Yu Chen School of Computer Science and Engineering Huaihua UniversityHuaihua418000China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua418000China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua418000China School of Computer Wuhan UniversityWuhan430072China Department of Electrical and Computer Engineering Duke UniversityDurhamNC 27708USA School of Computer Science and Engineering Yulin Normal UniversityYulin537000China

There is no reasonable scientific basis for selecting the excellent teachers of the school’s *** solve the practical problem,we firstly give a series of normalization models for defining the key attributes of teachers’professional foundation,course difficulty coefficient,and comprehensive evaluation of ***,we define a partial weight function to calculate the key attributes,and obtain the partial recommendation ***,we construct a highly sparse Teaching Recommendation Factorization Machines(TRFMs)model,which takes the 5-tuples relation including teacher,course,teachers’professional foundation,course difficulty,teaching evaluation as the feature vector,and take partial recommendation value as the recommendation ***,we design a novel Top-N excellent teacher recommendation algorithm based on TRFMs by course classification on the highly sparse *** results show that the proposed TRFMs and recommendation algorithm can accurately realize the recommendation of excellent teachers on a highly sparse historical teaching *** recommendation accuracy is superior to that of the three-dimensional tensor decomposition model algorithm which also solves sparse *** proposed method can be used as a new recommendation method applied to the teaching arrangements in all kinds of schools,which can effectively improve the teaching quality.

关键词： Highly sparse dataset normalized models teaching recommendation factorization machines excellent teacher recommendation

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Hydrological characteristics and changes in the Nu-Salween River basin revealed with model-based reconstructed data

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Journal of Mountain Science 2021年第11期18卷 2982-3002页

作者： YANG Fan LU Hui YANG Kun HUANG Guang-wei LI Yi-shan WANG Wei LU Ping TIAN Fu-qiang HUANG Yu-gang Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China Ministry of Education Ecological Field Station for East Asian Migratory Birds Beijing 100084China Center for Excellence in Tibetan Plateau Earth Sciences and National Tibetan Plateau Data Center Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China Graduate School of Global Environmental Studies Sophia UniversityTokyo 102-8554Japan Changjiang Institute of Survey PlanningDesign and ResearchWuhan 430010China Department of Hydraulic Engineering State Key Laboratory of Hydroscience and EngineeringTsinghua UniversityBeijing 100084China The International Economic&Technical Cooperation and Exchange Center Ministry of Water ResourcesBeijing 100053China

The Nu-Salween River(NSR),the longest free-flow river in Southeast Asia,plays an irreplaceable role in social development and ecological *** lower NSR region is particularly valuable as it is inhabited by approximately 6.7 million *** basin has limited hydraulic conservancy infrastructure and insufficient ability to cope with climate change *** the hydrological characteristics and changes in the basin provides the scientific basis for rational protection and development of the ***,owing to the limitation of observation data,previous studies have focused on the local area and neglected the study of the lower reaches,which is not enough to reflect the spatial characteristics of the entire *** this study,the ECMWF 5th generation reanalysis data(ERA5)and Multi-Source Weighted-Ensemble Precipitation(MSWEP)were applied to develop a geomorphology-based hydrological model(GBHM)for reconstructing hydrological datasets(***-ERA5 and GBHM-MSWEP).The reconstructed datasets covering the complete basin were verified against the gauge observation and compared with other commonly used streamflow products,including Global Flood Awareness System v2.1,GloFAS-Reanalysis dataset v3.0,and linear optimal runoff aggregate(LORA).The comparison results revealed that GBHM-ERA5 is significantly better than the other four datasets and provides a good reproduction of the hydrological characteristics and trends of the *** analysis of GBHM-ERA5 revealed that:(1)A multi-year mean surface runoff represented 39%of precipitation over the basin during 1980–2018,which had low surface runoff in the upstream,while areas around the Three Parallel Rivers Area and the estuary had abundant surface runoff.(2)The surface runoff and discharge coefficient of variations in spring were larger than those in other seasons,and the inter-annual variation in the downstream was smaller than that in the upstream and midstream regions.(3)More than 70%of the basin are

关键词： Nu-Salween River Distributed hydrologic model ERA5 Surface runoff Discharge Climate Change

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Antarctic krill habitat suitability changes: Historical trends and future projections under climate scenarios

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Marine Pollution Bulletin 2025年 217卷 118142页

作者： Cui, Meng Yu, Yong Shen, Kewei Kong, Jing Wu, Lizong Qi, Xin National Arctic and Antarctic Data Center Polar Research Institute of China Shanghai201209 China Ministry of Natural Resources Key Laboratory of Polar Science Polar Research Institute of China Shanghai201209 China Ministry of Education Shanghai200030 China Shanghai Key Laboratory of Polar Life and Environment Sciences Shanghai Jiao Tong University Shanghai200030 China School of marine technology and geomatics Jiangsu Ocean University Jiangsu Province Lianyungang222005 China School of Environmental and Chemical Engineering Jiangsu Ocean University Jiangsu Province Lianyungang222005 China

Antarctic krill plays a crucial role in the Southern Ocean ecosystem. However, data limitations leave a significant gap in understanding the changes in krill habitat suitability. This study integrated data from Chinese Antarctic research expeditions and KRILLBASE database, using Maxent model to assess spatiotemporal shifts in krill suitable habitat from 1991 to 2100 across the eastern and western Antarctic under SSP-RCP scenarios. The results reveal regional differences in climate and environmental impacts on krill habitats. Sea temperature and pH are dominant environmental factors affecting habitat suitability. With climate changes, the suitable habitats are shifting toward higher latitudes, and the latitudinal shift of habitats in CCAMLR Areas 48 and 58 is in the opposite direction. Under high-emission scenarios, krill habitats face severe contraction and loss, whereas low-emission scenarios suggest partial recovery by 2100. Coordinated global action to protect krill habitats is essential to address the biodiversity crisis in the Southern Ocean. © 2025 Elsevier Ltd

关键词： Global warming

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Resource Allocation in UAV-NOMA Communication Systems Based on Proportional Fairness

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Journal of Communications and Information Networks 2020年第2期5卷 111-120页

作者： Hui Zhang Baoji Wang Chen Chen Xiang Cheng Hang Li State Key Laboratory of Advanced Optical Communication Systems and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China Shanghai Institute of Microsystem and Information Tech-nology Chinese Academy of SciencesShanghai 200050China Data-Driven Information System Laboratory Shenzhen Re-search Institute of Big DataShenzhen 518172China

This paper investigates the power allocation problem in non-orthogonal multiple access(NOMA)integrated unmanned aerial vehicle(UAV)communication *** particular,we propose a novel resource allocation scheme to increase the transmission rate of the users that have relatively worse channel state information,while reducing the sum rate *** solve this problem efficiently,we decouple the optimization problem into three ***,we solve the problem of user pairing and subchannel ***,the optimum power proportional factor is derived to allocate transmit power among different users on the same *** last,different subchannels are allocated with appropriate power to improve the performance of the *** results show that the proposed scheme can enjoy a better performance than the benchmark methods since it can achieve a proper trade-off between the system sum rate and the proportional fairness.

关键词： UAV communications NOMA power allo-cation proportional fairness

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Rankings never really quantify contributions: A quantitative and qualitative study on universities and their libraries

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Journal of Library Science in China 2020年 117-126页

作者： Shelia X.WEI Ronda J.ZHANG Howell Y.WANG CAO Cong Fred Y.YE International Joint Informatics Laboratory & Jiangsu Key Laboratory of Data Engineering and Knowledge Services School of Information Management Nanjing University Nottingham University Business School University of Nottingham

By comparing quantitative ranking with qualitative contributions, we reveal that academic assessment has to put real contributions ahead of quantitative indicators and that rankings have nothing to do with universities’ and their libraries’ true values. The greatness of a university lies in its impacts on the progress for human knowledge and the promotion for social development. Although ranking of universities by way of quantitative indicators can reflect some information, we should pay more attention to qualitative contributions.

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