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Efficiently Improving Ensemble Forecasts of Warm-Sector Heavy Rainfall over Coastal Southern China: Targeted Assimilation to Reduce the Critical Initial Field Errors

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气象学报:英文版 2023年第4期37卷 486-507页

作者： Xinghua BAO Rudi XIA Yali LUO Jian YUE State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences(CAMS)China Meteorological Administration(CMA)Beijing 100081 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD) Nanjing University of Information Science&TechnologyNanjing 210044 CMA Earth System Modeling and Prediction Centre China Meteorological AdministrationBeijing 100081

Warm-sector heavy rainfall events over southern China are difficult to accurately forecast, due in part to inaccurate initial fields in numerical weather prediction models. In order to determine an efficient way of reducing the critical initial field errors, this study conducts and compares two sets of 60-member ensemble forecast experiments of a warm-sector heavy rainfall event over coastal southern China without data assimilation(NODA) and with radar radial velocity data assimilation(RadarDA). Yangjiang radar data, which can provide offshore high-resolution wind field information, were assimilated by using a Weather Research and Forecasting(WRF)-based ensemble Kalman filter(EnKF) system. The results show that the speed and direction errors of the southeasterly airflow in the marine boundary layer over the northern South China Sea may primarily be responsible for the forecast errors in rainfall and convection evolution. Targeted assimilation of radial velocity data from the Yangjiang radar can reduce the critical initial field errors of most members, resulting in improvements to the ensemble forecast. Specifically, RadarDA simulations indicate that radial-velocity data assimilation(VrDA) can directly reduce the initial field errors in wind speed and direction, and indirectly and slightly adjust the initial moisture fields in most members, thereby improving the evolution features of moisture transport during the subsequent forecast period. Therefore, these RadarDA members can better capture the initiation and development of convection and have higher forecast skill for the convection evolution and rainfall. The improvement in the deterministic forecasts of most members results in an improved overall ensemble forecast performance. However, VrDA sometimes results in inappropriate adjustment of the initial wind field,so the forecast skill of a few members decreases rather than increases after VrDA. This suggests that a degree of uncertainty remains about the effect of the WRF-based EnKF system. Moreover, the results

关键词： ensemble forecast targeted assimilation warm-sector heavy rainfall

n-exact Categories Arising from n-exangulated Categories

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数学学报:英文版 2023年第9期39卷 1781-1794页

作者： jian He Pan yue Zhou Department of Applied Mathematics Lanzhou University of TechnologyLanzhou730050P.R.China School of Mathematics and Statistics Changsha University of Science and TechnologyChangsha410114P.R.China

Let l be a Krull-Schmidt n-exangulated category and A be an n-extension closed subcategory of l.Then A inherits the n-exangulated structure from the given n-exangulated category in a natural way.This construction gives n-exangulated categories which are neither n-exact categories in the sense of Jasso nor(n+2)-angulated categories in the sense of Geiss-Keller-Oppermann in general.Furthermore,we also give a sufficient condition on when an n-exangulated category A is an n-exact category.These results generalize work by Klapproth and Zhou.

关键词： (n+2)-angulated categories n-exact categories n-extension closed subcategories n-exangulated categories

The Maximum Lagrangian of 5-uniform Hypergraphs without Containing Two Edges Intersecting at a Vertex

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Acta Mathematica Sinica,English Series 2022年第5期38卷 877-889页

作者： Biao WU yue jian PENG MOE-LCSM School of Mathematics and StatisticsHu’nan Normal UniversityChangsha 410081P.R.China School of Mathematics Hu’nan UniversityChangsha 410082P.R.China

Obtaining Turán densities of hypergraph through determining Lagrangian densities have been studied actively.Sidorenko showed that the Lagrangian density of an r-uniform hypergraph equals the Turán density of the extension of this hypergraph.Indeed,Lagrangian density and Turán density are the same for a large class of hypergraphs such as hypergraphs covering pairs.Let Pr,sbe the r-uniform hypergraph with two edges intersecting at s vertices.Sidorenko determined the Lagrangian densities of Pr,sfor r=3 and s=1 or 2,or r=4 and s=2 or 3.Hefetz and Keevash determined for r=3 and s=0,and Bene Watts,Norin and Yepremyan determined for r≥4 and s=0.The cases r=5 and s=4 or r=6 and s=5 were determined by Norin and Yepremyan.Jenssen showed for r=5,6 or 7,and s=3,4 or 5 respectively.The cases r=4 and s=1 or r=5 and s=2 were determined by jiang,Peng and Wu,and Hu,Peng and Wu respectively.For r=5,the only remaining case is s=1.In this paper,we determine for this case.

关键词： Hypergraph Lagrangian Turán number

Local Dependence Test Between Random Vectors Based on the Robust Conditional Spearman's ρ and Kendall's τ

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Acta Mathematicae Applicatae Sinica 2023年第3期39卷 491-510页

作者： Ling-yue ZHANG Heng-jian CUI School of Mathematical Sciences Capital Normal UniversityBeijing 100048China

This paper introduces two local conditional dependence matrices based on Spearman'sρand Kendall'sτgiven the condition that the underlying random variables belong to the intervals determined by their quantiles.The robustness is studied by means of the influence functions of conditional Spearman'sρand Kendall'sτ.Using the two matrices,we construct the corresponding test statistics of local conditional dependence and derive their limit behavior including consistency,null and alternative asymptotic distributions.Simulation studies illustrate a superior power performance of the proposed Kendall-based test.Real data analysis with proposed methods provides a precise description and explanation of some financial phenomena in terms of mathematical statistics.

关键词： local dependence influence function rank correlation U-statistic

Frontier studies on natural products:moving toward paradigm shifts

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Science China Chemistry 2023年第4期66卷 928-942页

作者： Jin-Xin Zhao jian-Min yue State Key Laboratory of Drug Research Shanghai Institute of Materia MedicaChinese Academy of SciencesShanghai 201203China Shandong Laboratory of Yantai Drug Discovery Bohai Rim Advanced Research Institute for Drug DiscoveryYantai 264117China

1 Introduction Natural products(NPs)historically serve as a valuable and productive source of bioactive compounds for drug development.The discovery of a range of alkaloids in the early1800s,including strychnine,morph... 详细信息

关键词： alkaloids moving compounds

Aggregated context network for crowd counting

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Frontiers of Information Technology & Electronic Engineering 2020年第11期21卷 1626-1638页

作者： Si-yue YU jian PU School of Computer Science and Technology East China Normal UniversityShanghai 200062China Institute of Science and Technology for Brain-Inspired Intelligence Fudan UniversityShanghai 200433China

Crowd counting has been applied to a variety of applications such as video surveillance,traffic monitoring,assembly control,and other public safety applications.Context information,such as perspective distortion and background interference,is a crucial factor in achieving high performance for crowd counting.While traditional methods focus merely on solving one specific factor,we aggregate sufficient context information into the crowd counting network to tackle these problems simultaneously in this study.We build a fully convolutional network with two tasks,i.e.,main density map estimation and auxiliary semantic segmentation.The main task is to extract the multi-scale and spatial context information to learn the density map.The auxiliary semantic segmentation task gives a comprehensive view of the background and foreground information,and the extracted information is finally incorporated into the main task by late fusion.We demonstrate that our network has better accuracy of estimation and higher robustness on three challenging datasets compared with state-of-the-art methods.

关键词： Crowd counting Convolutional neural network Density estimation Semantic segmentation Multi-task learning

Click chemistry-based enrichment strategy for tracing cellular fatty acid metabolism by LC-MS/MS

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Journal of Pharmaceutical Analysis 2023年第10期13卷 1221-1231页

作者： Ru-Jie Yang jian Zou Jia-yue Liu jiang-Kun Dai jian-Bo Wan State Key Laboratory of Quality Research in Chinese Medicine Institute of Chinese Medical SciencesUniversity of MacaoMacao SAR999078China

Fatty acids(FAs),which were initially recognized as energy sources and essential building blocks of biomembranes,serve as the precursors of important signaling molecules.Tracing FA metabolism is essential to understanding the biochemical activity and role of FAs in physiological and pathological events.Inspired by the advances in click chemistry for protein enrichment,we herein established a click chemistry-based enrichment(CCBE)strategy for tracing the cellular metabolism of eicosapentaenoic acid(EPA,20:5 n-3)in neural cells.Terminal alkyne-labeled EPA(EPAA)used as a surrogate was incubated with N2a,mouse neuroblastoma cells,and alkyne-labeled metabolites(ALMs)were selectively captured by an azide-modified resin via a Cu(I)-catalyzed azide-alkyne cycloaddition reaction for enrichment.After removing unlabeled metabolites,ALMs containing a triazole moiety were cleaved from solid-phase resins and subjected to liquid chromatography mass spectrometry(LC-MS)analysis.The proposed CCBE strategy is highly selective for capturing and enriching alkyne-labeled metabolites from the complicated matrices.In addition,this method can overcome current detection limits by enhancing MS sensitivity of targets,improving the chromatographic separation of sn-position glycerophospholipid regioisomers,facilitating structural characterization of ALMs by a specific MS/MS fragmentation signature,and providing versatile fluorescence detection of ALMs for cellular distribution.This CCBE strategy might be expanded to trace the metabolism of other FAs,small molecules,or drugs.

关键词： Click chemistry-based enrichment EPA metabolism Terminal alkyne-labeled EPA Azide-modified resin LC-MS/MS

Spectrum Usage Anomaly Detection from Sub-Sampled Data Stream via Deep Neural Network

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Journal of Communications and Information Networks 2023年第1期8卷 13-23页

作者： Han Zhang jian Yang Junting Chen yue Gao Institute for Communication Systems the University of SurreyGuildford GU27XHUK Mobile Communications Innovation Center China Academy of Information and Communications TechnologyBeijing 100191China Future Network Intelligence Institute(FNii)and School of Science and Engineering the Chinese University of Hong KongShenzhen 518172China School of Computer Science Fudan UniversityShanghai 200433China.Institute for Communication Systemsthe University of SurreyGuildford GU27XHUK

Anomaly detection is an essential part of any practical system in order to remedy any malfunction and accident early to create a secure and robust system.Malicious users and malfunctioning cognitive radio(CR)devices may cause severe interference to legitimate users.However,there are no effective methods to detect spontaneous and irregular anomaly behaviors in sub-sampling data stream from wideband compressive spectrum sensing as an important function of a CR device.In this article,to detect anomaly utilization of spectrum from sub-sampled data stream,a multiple layer perceptron/feed-forward neural network(FFNN)based solution is proposed.The proposed solution would learn the pattern of legitimate and anomalous usages autonomously without expert's knowledge.The proposed neural network(NN)framework has also shown benefits such as more than 80%faster detection speed and lower detection error rate.

关键词： compressive sensing(CS) machine learning(ML) multicoset sampling anomaly detection

CFCS:A Robust and Efficient Collaboration Framework for Automatic Modulation Recognition

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Journal of Communications and Information Networks 2023年第3期8卷 283-294页

作者： jian Shi Xiaohui Yang Jia Ma Guangxue yue Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province Jiaxing 314001China School of Computer Engineering and Science Shanghai UniversityShanghai 200444China Research Center of Cyber Science and Technology Hangzhou Innovation InstituteBeihang UniversityHangzhou 311228China College of Information Science and Engineering Jiaxing UniversityJiaxing 314001China

Most of the existing automatic modulation recognition(AMR)studies focus on optimizing the network structure to improve performance,without fully considering cooperation among the basic networks to play their respective advantages.In this paper,we propose a robust and efficient collaboration framework based on the combination scheme(CFCS).This scheme effectively explores the spatial and temporal characteristics of complex signals by associating the advantages of convolutional neural network(CNN)and long and short-term memory(LSTM)network.In addition,the robustness of the CFCS is verified by transfer learning.Experiments demonstrate that the recognition rate of CFCS for highorder modulation signals such as 64QAM,128QAM,and 256QAM is more than 90%at high signal-to-noise ratios(SNRs),and 24 modulation types are effectively identified.Moreover,CFCS was transferred from RML2018.01a to RML2016.10b using transfer learning,which can still be deployed efficiently while reducing the training time by 20%.The CFCS has strong generalization ability and excellent recognition performance.

关键词： AMR CNN LSTM combination scheme transfer learning