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Finite Element Method for Transient Electric Field by Using Indirect Laplace Transform with High Accuracy

CSEE Journal of Power and Energy Systems 2024年第1期10卷 401-411页

作者： Teng Wen xiang cui Xuebao Li Sijia Liu Zhibin Zhao State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China China Electric Power Planning&Engineering Institute Beijing 100120China

This paper focuses on the finite element method in the complex frequency domain(CFD-FEM)for the transient electric field.First,the initial value and boundary value problem of the transient electric field under the electroquasistatic field in the complex frequency domain is given.In addition,the finite element equation and the constrained electric field equation on the boundary are derived.Secondly,the indirect algorithm of the numerical inverse Laplace transform is introduced.Based on it,the calculation procedures of the CFD-FEM are illustrated in detail.Thirdly,the step response,zero-state response under the positive periodic square waveform(PPSW)voltage,and the zero-input response by the CFD-FEM with direct algorithm and indirect algorithm are compared.Finally,the reason for the numerical oscillations of the zero-state response under the PPSW voltage is analyzed,and the method to reduce oscillations is proposed.The results show that the numerical accuracy of the indirect algorithm of the CFD-FEM is more than an order of magnitude higher than that of the direct algorithm when calculating the step response of the transient electric field.The proposed method can significantly reduce the numerical oscillations of the zero-state response under the PPSW voltage.The proposed method is helpful for the calculation of the transient electric field,especially in the case of frequency-dependent parameters.

关键词： Electroquasistatic field transient electric field finite element method complex frequency domain numerical Laplace transform

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A new scheme of climate-vegetation regionalization in the Hengduan Mountains Region

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Science China Earth Sciences 2024年第3期67卷 751-768页

作者： Xueqin ZHANG Xiaoming XU xiang LI Peng cui Du ZHENG Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China China-Pakistan Joint Research Center on Earth Sciences Chinese Academy of Sciences-Higher Education Commission of PakistanIslamabad 45320Pakistan

The Hengduan Mountains Region(HMR) is essential for the future ecological protection, clean energy production,Sichuan-Xizang and Yunnan-Xizang railways, and other major infrastructure projects in China. The distributions of climate and vegetation exhibit significant regional differentiation and vertical zonality due to the rugged longitudinal ranges and gorges and the complex disaster-prone environments in HMR. Therefore, it is urgent to develop the climate-vegetation regionalization in HMR to effectively satisfy the national requirements such as agricultural production and ecological protection, mountain disaster risk prevention, and major project construction. We here develop a new scheme of climate-vegetation regionalization with the latest demarcation outcome of HMR, the ground observation from 122 meteorological stations in HMR and its surrounding areas during 1990–2019, and the high-precision remote sensing data of land cover types. The new scheme first constructs the regionalization index system, fully considering the extraordinarily complicated geomorphic pattern of mountains and valleys, the scarcity of meteorological observations, and the remarkable differentiation of climate and vegetation in HMR. The system consists of three primary regionalization indices(i.e., days with daily average temperature steady above 10°C, aridity index, and main vegetation types, dividing the temperature zones, moisture regions, and vegetation subregions, respectively) and three auxiliary indices of the accumulated temperature above 10°C, and the temperatures in January and July. Then, the HMR is divided into five temperature zones, 20 moisture regions, and 55 vegetation subregions. Compared with previous regionalization schemes, the new scheme optimizes the climate spatial interpolation model of thin plate smoothing spline suitable for the unique terrain in HMR. Moreover, the disputed division index threshold between different climatic zones(regions) is scientifically clarified using geographical detectors. Specifically, t

关键词： Climate-vegetation regionalization Thin plate smoothing spline(TPSS) GeoDetector Stepwise downscaling pane division method Hengduan Mountains Region

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Factors and Their Impact on Treatment Effect of Acupuncture in Different Outcomes:A Meta-Regression of Acupuncture Randomized Controlled Trials

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Chinese Journal of Integrative Medicine 2024年第3期30卷 260-266页

作者： XIU Wen-cui GANG Wei-juan ZHOU Qi SHI Lan-jun HU xiang-yu MING Tian-yu LUO Zhen ZHANG Yu-qing JING xiang-hong Institute of Acupuncture and Moxibustion China Academy of Chinese Medical SciencesBeijing100700China China Center for Evidence-Based Traditional Chinese Medicine China Academy of Chinese Medical SciencesBeijing100700China Department of Health Research Methods Evidenceand ImpactMcMaster UniversityHamiltonOntarioL8S 4L8Canada Center for Evidence-Based Integrative Medicine-Clarity Collaboration Guang’anmen HospitalChina Academy of Chinese Medical SciencesBeijing100053China

Background:The effects of acupuncture have varied in different randomized controlled trials(RCTs),and there are many factors that influence treatment effect of acupuncture in different outcomes,with conflicting results.Objective:To identify factors and their impact on the treatment effect of acupuncture in different outcomes.Methods:Acupuncture RCTs were searched from 7 databases including Medline(Pub Med),Embase,Cochrane Central Register of Controlled Trials,China National Knowledge Infrastructure,Wanfang Database,VIP Database,and China Biology Medicine disc between January 1st,2015 and December 31st,2019.Eligible studies must compare acupuncture to no acupuncture,sham acupuncture,or waiting lists,and report at least 1patient-important outcome.A multi-level meta-regression was conducted using a 3-level robust mixed model and univariate analyses were performed for all independent variables,even those excluded from the multivariable model due to collinearities.We used thresholds of 0.2 and 0.4 for the difference of standardized mean differences(SMDs),categorising them as small(0.4) effects.Results:The pain construct analysis involved 211 effect estimates from 153 studies and 14 independent variables.High-frequency acupuncture treatment sessions produced larger effects compared to low-frequency sessions [large magnitude,the difference of adjusted SMDs 0.46,95% confidence interval(CI) 0.07 to 0.84;P=0.02].The non-pain symptoms construct analysis comprised 323 effect estimates from 231 studies and 15 independent variables.Penetrating acupuncture showed moderately larger effects when compared to non-penetrating acupuncture(0.30,95% CI 0.06 to 0.53;P=0.01).The function construct analysis included 495 effect estimates from 274 studies and 14 independent variables.Penetrating acupuncture and the flexible acupuncture regimen showed moderately larger effects,compared to non-penetrating acupuncture and fixed regimen,respectively(0.40,95% CI 0 to 0.80;P=0.05;0.29,95% CI 0.06 to 0.53;P=0.01).

关键词： acupuncture randomized controlled trial patient-important outcome meta-regression

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NFT Security Matrix:Towards Modeling NFT Ecosystem Threat

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3255-3285页

作者： Peng Liao Chaoge Liu Jie Yin Zhi Wang xiang cui Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and TelecommunicationsBeijing100876China Zhongguancun Laboratory Beijing100094China Institute of Information Engineering Chinese Academy of SciencesBeijing100085China

Digital assets have boomed over the past few years with the emergence of Non-fungible Tokens(NFTs).To be specific,the total trading volume of digital assets reached an astounding$55.5 billion in 2022.Nevertheless,numerous security concerns have been raised by the rapid expansion of the NFT ecosystem.NFT holders are exposed to a plethora of scams and traps,putting their digital assets at risk of being lost.However,academic research on NFT security is scarce,and the security issues have aroused rare attention.In this study,the NFT ecological process is comprehensively explored.This process falls into five different stages encompassing the entire lifecycle of NFTs.Subsequently,the security issues regarding the respective stage are elaborated and analyzed in depth.A matrix model is proposed as a novel contribution to the categorization of NFT security issues.Diverse data are collected from social networks,the Ethereum blockchain,and NFT markets to substantiate our claims regarding the severity of security concerns in the NFT ecosystem.From this comprehensive dataset,nine key NFT security issues are identified from the matrix model and then subjected to qualitative and quantitative analysis.This study aims to shed light on the severity of NFT ecosystem security issues.The findings stress the need for increased attention and proactive measures to safeguard the NFT ecosystem.

关键词： Non-fungible token blockchain cyber security

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Spark plasma sintering of tungsten-based WTaVCr refractory high entropy alloys for nuclear fusion applications

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International Journal of Minerals,Metallurgy and Materials 2024年第1期31卷 146-154页

作者： Yongchul Yoo xiang Zhang Fei Wang Xin Chen Xing-Zhong Li Michael Nastasi Bai cui Department of Mechanical&Materials Engineering University of Nebraska-LincolnLincolnNE 68588USA Nebraska Center for Materials and Nanoscience University of Nebraska-LincolnLincolnNE 68588USA Department of Nuclear Engineering Texas A&M UniversityCollege StationTX 77843USA

W-based WTaVCr refractory high entropy alloys (RHEA) may be novel and promising candidate materials for plasma facing components in the first wall and diverter in fusion reactors. This alloy has been developed by a powder metallurgy process combining mechanical alloying and spark plasma sintering (SPS). The SPSed samples contained two phases, in which the matrix is RHEA with a body-centered cubic structure, while the oxide phase was most likely Ta2VO6through a combined analysis of X-ray diffraction (XRD),energy-dispersive spectroscopy (EDS), and selected area electron diffraction (SAED). The higher oxygen affinity of Ta and V may explain the preferential formation of their oxide phases based on thermodynamic calculations. Electron backscatter diffraction (EBSD) revealed an average grain size of 6.2μm. WTaVCr RHEA showed a peak compressive strength of 2997 MPa at room temperature and much higher micro-and nano-hardness than W and other W-based RHEAs in the literature. Their high Rockwell hardness can be retained to at least 1000°C.

关键词： refractory high entropy alloy plasma-facing material fusion reactor spark plasma sintering

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A data-driven approach to RUL prediction of tools

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Advances in Manufacturing 2024年第1期12卷 6-18页

作者： Wei Li Liang-Chi Zhang Chu-Han Wu Yan Wang Zhen-xiang cui Chao Niu Department of Mechanical Engineering University College LondonLondonWC1E 7JEUK Shenzhen Key Laboratory of Cross-Scale Manufacturing Mechanics Southern University of Science and TechnologyShenzhen518055GuangdongPeople’s Republic of China SUSTech Institute for Manufacturing Innovation Southern University of Science and TechnologyShenzhen518055GuangdongPeople’s Republic of China Department of Mechanics and Aerospace Engineering Southern University of Science and TechnologyShenzhen518055GuangdongPeople’s Republic of China School of Mechanical and Manufacturing Engineering The University of New South WalesKensingtonNSW2052Australia Baoshan Iron&Steel Co. Ltd.Shanghai200941People’s Republic of China

An effective and reliable prediction of the remaining useful life(RUL)of a tool is important to a metal forming process because it can significantly reduce unexpected maintenance,avoid machine shutdowns and increase system stability.This study proposes a new data-driven approach to the RUL prediction for metal forming processes under multiple contact sliding conditions.The data-driven approach took advantage of bidirectional long short-term memory(BLSTM)and convolutional neural networks(CNN).A pre-trained lightweight CNN-based network,WearNet,was re-trained to classify the wear states of workpiece surfaces with a high accuracy,then the classification results were passed into a BLSTM-based regression model as inputs for RUL estimation.The experimental results demonstrated that this approach was able to predict the RUL values with a small error(below 5%)and a low root mean square error(RMSE)(around 1.5),which was more superior and robust than the other state-of-the-art methods.

关键词： Remaining useful life(RUL) Bidirectional long short-term memory(BLSTM) Data-driven approach Metal forming

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Detecting compromised email accounts via login behavior characterization

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Cybersecurity 2024年第1期7卷 16-36页

作者： Jianjun Zhao Can Yang Di Wu Yaqin Cao Yuling Liu xiang cui Qixu Liu Institute of Information Engineering Chinese Academy of SciencesBeijing100085China School of Cyber Security University of Chinese Academy of SciencesBeijing100049China China Cybersecurity Review Technology and Certification Center Beijing100013China Zhongguancun Laboratory Beijing100089China

The illegal use of compromised email accounts by adversaries can have severe consequences for enterprises and society.Detecting compromised email accounts is more challenging than in the social network field,where email accounts have only a few interaction events(sending and receiving).To address the issue of insufficient features,we propose a novel approach to detecting compromised accounts by combining time zone differences and alternate logins to identify abnormal behavior.Based on this approach,we propose a compromised email account detection framework that relies on widely available and less sensitive login logs and does not require labels.Our framework characterizes login behaviors to identify logins that do not belong to the account owner and outputs a list of account-subnet pairs ranked by their likelihood of having abnormal login relationships.This approach reduces the number of account-subnet pairs that need to be investigated and provides a reference for investigation priority.Our evaluation demonstrates that our method can detect most email accounts that have been accessed by disclosed malicious IP addresses and outperforms similar research.Additionally,our framework has the capability to uncover undisclosed malicious IP addresses.

关键词： Compromised account detection Mixture model Login log analysis Attribution and forensic

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Clinical evolution of antisynthetase syndrome-associated interstitial lung disease after COVID-19 in a man with Klinefelter syndrome:A case report

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World Journal of Clinical Cases 2024年第6期12卷 1144-1149页

作者： xiang-xiang Wu Jian cui Shi-Yao Wang Tian-Tian Zhao Ya-Fei Yuan Long Yang Wei Zuo Wen-Jian Liao Department of Respiratory and Critical Care The First Affiliated HospitalJiangxi Medical CollegeNanchang UniversityNanchang 330006Jiangxi ProvinceChina China-Japan Friendship Jiangxi Hospital Nanchang 330006Jiangxi ProvinceChina Department of Pulmonary and Critical Care Medicine Center of Respiratory MedicineChina-Japan Friendship HospitalBeijing 100029China

BACKGROUND This study presents a case of rapidly developing respiratory failure due to antisynthetase syndrome(AS)following coronavirus disease 2019(COVID-19)in a 33-year-old man diagnosed with Klinefelter syndrome(KS).CASE SUMMARY A 33-year-old man with a diagnosis of KS was admitted to the Department of Pulmonary and Critical Care Medicine of a tertiary hospital in China for fever and shortness of breath 2 wk after the onset of COVID-19.Computed tomography of both lungs revealed diffuse multiple patchy heightened shadows in both lungs,accompanied by signs of partial bronchial inflation.Metagenomic next-generation sequencing of the bronchoalveolar lavage fluid suggested absence of pathogen.A biopsy specimen revealed organizing pneumonia with alveolar septal thickening.Additionally,extensive auto-antibody tests showed strong positivity for anti-SSA,anti-SSB,anti-Jo-1,and anti-Ro-52.Following multidisciplinary discussions,the patient received a final diagnosis of AS,leading to rapidly progressing respiratory failure.CONCLUSION This study underscores the clinical progression of AS-associated interstitial lung disease subsequent to viral infections such as COVID-19 in patients diagnosed with KS.

关键词： Antisynthetase syndrome COVID-19 Klinefelter syndrome Interstitial lung disease Anti-Jo-1 Case report

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Transcription factor OsSPL10 interacts with OsJAmyb to regulate blast resistance in rice

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The Crop Journal 2024年第1期12卷 301-307页

作者： Zaofa Zhong Lijing Zhong xiang Zhu Yimin Jiang Yihong Zheng Tao Lan Haitao cui College of Life Science Fujian Agriculture and Forestry UniversityFuzhou 350002FujianChina Key Laboratory of Genetics Breeding and Multiple Utilization of CropsMinistry of EducationCollege of AgricultureFujian Agriculture and Forestry UniversityFuzhou 350002FujianChina Fujian Provincial Key Laboratory of Crop Breeding by Design Fujian Agriculture and Forestry UniversityFuzhou 350002FujianChina College of Plant Protection Shandong Agricultural UniversityTai’an 271018ShandongChina

Transcription factors(TFs)play essential roles in transcriptional reprogramming during activation of plant immune responses to pathogens.OsSPL10(SQUAMOSA promoter binding protein-like10)is an important TF regulating trichome development and salt tolerance in rice.Here we report that knockout of OsSPL10 reduces whereas its overexpression enhances rice resistance to blast disease.OsSPL10 positively regulates chitin-induced immune responses including reactive oxygen species(ROS)burst and callose deposition.We show that OsSPL10 physically associates with OsJAmyb,an important TF involved in jasmonic acid(JA)signaling,and positively regulates its protein stability.We then prove that OsJAmyb positively regulates resistance to blast.Our results reveal a molecular module consisting of OsSPL10 and OsJAmyb that positively regulates blast resistance.

关键词： Immunity Jasmonate Oryza sativa OsSPL10 Transcription factor

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Morphological Classification of Infrared Galaxies Based on WISE

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Research in Astronomy and Astrophysics 2024年第4期24卷 222-236页

作者： Zhi-Ren Pan Bo Qiu cui-xiang Liu A-Li Luo Xia Jiang Xiao-Yu Guo School of Electronic and Information Engineering Hebei University of TechnologyTianjin 300401China Key Laboratory of Optical Astronomy National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China

This study introduces a novel convolutional neural network,the WISE Galaxy Classification Network(WGC),for classifying spiral and elliptical galaxies using Wide-field Infrared Survey Explorer(WISE)images.WGC attains an accuracy of 89.03%,surpassing the combined use of K-means or SVM with the Color-Color method in more accurately identifying galaxy morphologies.The enhanced variant,WGC_mag,integrates magnitude parameters with image features,further boosting the accuracy to 89.89%.The research also delves into the criteria for galaxy classification,discovering that WGC primarily categorizes dust-rich images as elliptical galaxies,corresponding to their lower star formation rates,and classifies less dusty images as spiral galaxies.The paper explores the consistency and complementarity of WISE infrared images with SDSS optical images in galaxy morphology classification.The SDSS Galaxy Classification Network(SGC),trained on SDSS images,achieved an accuracy of 94.64%.The accuracy reached 99.30% when predictions from SGC and WGC were consistent.Leveraging the complementarity of features in WISE and SDSS images,a novel variant of a classifier,namely the Multi-band Galaxy Morphology Integrated Classifier,has been developed.This classifier elevates the overall prediction accuracy to 95.39%.Lastly,the versatility of WGC was validated in other data sets.On the HyperLEDA data set,the distinction between elliptical galaxies and Sc,Scd and Sd spiral galaxies was most pronounced,achieving an accuracy of 90%,surpassing the classification results of the Galaxy Zoo 2 labeled WISE data set.This research not only demonstrates the effectiveness of WISE images in galaxy morphology classification but also represents an attempt to integrate multi-band astronomical data to enhance understanding of galaxy structures and evolution.

关键词： methods:data analysis infrared:galaxies galaxies:spiral galaxies:elliptical and lenticular cD

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