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Spatiotemporal evolution and driving factors of China's flash flood disasters since 1949

Science China Earth Sciences 2018年第12期61卷 1804-1817页

作者： Yesen LIU Zhenshan YANG Yaohuan HUANG Changjun LIU China Institute of Water Resources and Hydropower Research Research Center on Flood & Drought Disaster Reduction of the Ministry of Water Resources Key Lab of Regional Sustainable Development and modelling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of Sciences

This study examines the spatiotemporal evolution of China's flash flood disasters(FFDs) since 1949 and explores driving factors affecting the spatial distribution of historical FFDs. Records of more than 60000 FFDs are examined, and the centroid comparison method is used to reveal the spatiotemporal evolution of FFDs from 1951 to 2015. In particular, the geographical locations of the centroids, degrees of aggregation, and associated movement tendencies are examined to conduct a preliminary analysis of correlations between rainfall, population, and the spatiotemporal evolution of FFDs. Subsequently, using relevant data from 2000 to 2015, three factors relating to FFDs in natural watershed units include namely rainfall, human activity,and the environment of the Earth's surface. The geographical detector method is then employed to explore the effect of these driving factors on the spatial distribution of FFDs. Analysis results show that displacement of the spatial distribution of FFDs since 1949 is correlated with variations in rainfall and population distribution. In addition, it is determined that the distribution of FFDs occurring between 2000 and 2015 have regional differentiation characteristics. However, the effect of rainfall on the distribution of FFDs is more significant than that of human activity or the environment of the Earth's surface, but interactions occur between these latter two factors in disaster-formative environments. Furthermore, results also show that the driving factors of FFDs have significant spatiotemporal heterogeneity. In China, regions at high risk of FFDs include the Sichuan-Chongqing ecological zone, the South China ecological zone, the Yunnan-Guizhou Plateau, and the middle and lower reaches of the Yangtze River, while regions with a low risk of FFDs include the Northwest China arid zone, Qinghai-Tibet Plateau, Inner Mongolian Plateau, and the Northeast China ecological zone. These findings support further studies investigating disaste

关键词： Flash flood disaster Centroid Driving factor Human activity Rainfall

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CaAl_(2)Si_(2)O_(8) polymorphs:Sensitive geothermometers and geospeedometers

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Geoscience Frontiers 2023年第1期14卷 33-45页

作者： Liudmila A.Gorelova Oleg S.Vereshchagin Vladimir N.Bocharov Sergey V.Krivovichev Andrey A.Zolotarev Mikhail A.Rassomakhin Institute of Earth Sciences Saint Petersburg State UniversitySt.PetersburgRussia Centrefor Geo-Environmental Research and modelling(Geomodel).Saint Petersburg State University St.PetersburgRussia Kola Science Centre ApatityMurmansk RegionRussia South Urals Federal Research center of Mineralogy and Geoecology of UB RAS MiassRussia

Plagioclase is the major rock-forming mineral constituting the Earth's crust,whereas anorthite(CaAl_(2)Si_(2)O_(8))is a common minerals in lunar highlands crust,meteorites,possibly in some comets and on *** anorthite,two high-temperature polymorphs of CaAl_(2)Si_(2)O_(8)are known:dmisteinbergite and svyatoslavite,which are found in burnt coal dumps,meteorites and *** we present the results of detailed studies(quenching experiments,elemental analysis,Raman spectroscopy and in situ high temperature single crystal X-ray diffraction(up to 1000℃))on naturally co-occurring CaAl_(2)Si_(2)O_(8)polymorphs(anorthite,dmisteinbergite and svyatoslavite)from a burnt coal dump in Kopeisk,*** polymorphs were found in all natural samples and obtained upon heating of dmisteinbergite(unquenchableβ-dmisteinbergite and quenchable y-dmisteinbergite).It was shown that Ca coordination differs significantly in CaAl_(2)Si_(2)O_(8)polymorphs,resulting in a different capacity to host Ba and possibly other large ion lithophile *** our data on natural samples with the previously published data on natural and synthetic compounds,we propose a new scheme of CaAl_(2)Si_(2)O_(8)polymorphs *** results indicate that CaAl_(2)Si_(2)O_(8)polymorphs could be used for temperature estimations for both Earth and planetary sciences.

关键词： Feldspar Polymorphism Anorthite Dmisteinbergite Svyatoslavite CaAl_(2)Si_(2)O_(8)

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An open compute and data federation as an alternative to monolithic infrastructures for big Earth data analytics

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Big Earth data 2023年第3期7卷 812-830页

作者： Björn Backeberg ZdeněkŠustr Enol Fernández Gennadii Donchyts Arjen Haag J.B.Raymond Oonk Gerben Venekamp Benjamin Schumacher Stefan Reimond Charis Chatzikyriakou Deltares DelftThe Netherlands Nansen Environmental and Remote Sensing center BergenNorway CESNET PragueCzech Republic EGI Foundation AmsterdamThe Netherlands SURF/SURFsara AmsterdamThe Netherlands Earth Observation data Centre for Water Resources Monitoring GmbH ViennaAustria

An adequate compute and storage infrastructure supporting the full exploitation of Copernicus and Earth Observation datasets is currently not available in *** paper presents the cross-disciplinary open-source technologies being leveraged in the C-SCALE project to develop an open federation of compute and data providers as an alternative to monolithic infrastructures for processing and analysing Copernicus and Earth Observation *** critical aspects of the federation and the chosen technologies are elaborated upon:(1)federated data discovery,(2)federated access and(3)software *** these technologies the open federation aims to provide homogenous access to resources,thereby enabling its users to generate meaningful results quickly and *** will be achieved by abstracting the complexity of infrastructure resource access provisioning and orchestration,including discovery of data across distributed archives,away from the *** is needed because end-users wish to focus on analysing ready-to-use data products and models rather than spending their time on the setup and maintenance of complex and heterogeneous IT *** open federation will support processing and analysing the vast amounts of Copernicus and Earth Observation data that are critical for the implementation of the Destination Earth *** Twins vision for a high precision digital model of the Earth to model,monitor and simulate natural phenomena and related human activities.

关键词： Open compute and data federation big Earth data analytics federated data discovery federated access software distribution

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Physics-based fuid simulation in computer graphics: Survey, research trends, and challenges

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Computational Visual Media 2024年第5期10卷 803-858页

作者： Xiaokun Wang Yanrui Xu Sinuo Liu Bo Ren Jiri Kosinka Alexandru C.Telea Jiamin Wang Chongming Song Jian Chang Chenfeng Li Jian Jun Zhang Xiaojuan Ban Beijing Advanced Innovation center for Materials Genome Engineering and School of Intelligence Science and Technologyand Shunde Innovation School University of Science and Technology BeijingBeijing 100083China National center for Computer Animation Faculty of Media and CommunicationBournemouth UniversityPoole BH125BBUK. Bernoulli Institute University of GroningenGroningen 9700 AKthe Netherlands School of Computer Science Peking UniversityBeijing 100871China. TMCC College of Computer ScienceNankai UniversityTianjin 300350China Department of Information and Computing Sciences Utrecht UniversityUtrecht 3584 CCthe Netherlands. Zienkiewicz Institute for modelling Data and AISwansea UniversitySwansea SA18ENUK. Institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang 110004China.

Physics-based fluid simulation has played an increasingly important role in the computer graphics *** methods in this area have greatly improved the generation of complex visual effects and its computational *** techniques have emerged to deal with complex boundaries,multiphase fluids,gas-liquid interfaces,and fine *** parallel use of machine learning,image processing,and fluid control technologies has brought many interesting and novel research *** this survey,we provide an introduction to theoretical concepts underpinning physics-based fuid simulation and their practical implementation,with the aim for it to serve as a guide for both newcomers and seasoned researchers to explore the field of physics-based fuid simulation,with a focus on developments in the last *** by the distribution of recent publications in the field,we structure our survey to cover physical background;discretization approaches;computational methods that address scalability;fuid interactions with other materials and interfaces;and methods for expressive aspects of surface detail and *** a practical perspective,we give an overview of existing implementations available for the above methods.

关键词： computer graphics physical simulation fluid simulation fluid coupling

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Assessing effects of reopening policies on COVID-19 pandemic in Texas with a data-driven transmission model

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Infectious Disease modelling 2021年第1期6卷 461-473页

作者： Duo Yu Gen Zhu Xueying Wang Chenguang Zhang Babak Soltanalizadeh Xia Wang Sanyi Tang Hulin Wu Department of Biostatistics and data Science The University of Texas Health Science Center at HoustonHoustonUSA School of Mathematics and Information Science Shaanxi Normal UniversityXi’anPR China

While the Coronavirus Disease 2019(COVID-19)pandemic continues to threaten public health and safety,every state has strategically reopened the business in the United *** is urgent to evaluate the effect of reopening policies on the COVID-19 pandemic to help with the decision-making on the control measures and medical resource *** this study,a novel SEIR model was developed to evaluate the effect of reopening policies based on the real-world reported COVID-19 data in *** earlier reported data before the reopening were used to develop the SEIR model;data after the reopening were used for *** simulation results show that if continuing the“stay-at-home order”without reopening the business,the COVID-19 pandemic could end in December 2020 in *** the other hand,the pandemic could be controlled similarly as the case of noreopening only if the contact rate was low and additional high magnitude of control measures could be *** the control measures are only slightly enhanced after reopening,it could flatten the curve of the COVID-19 epidemic with reduced numbers of infections and deaths,but it might make the epidemic last *** on the reported data up to July 2020 in Texas,the real-world epidemic pattern is between the cases of the low and high magnitude of control measures with a medium risk of contact rate after *** this case,the pandemic might last until summer 2021 to February 2022 with a total of 4-10 million infected cases and 20,080e58,604 deaths.

关键词： COVID-19 pandemic SEIR model Texas state Reopening business Infectious disease transmission

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Explainable, Domain-Adaptive, and Federated Artificial Intelligence in Medicine

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 859-876页

作者： Ahmad Chaddad Qizong Lu Jiali Li Yousef Katib Reem Kateb Camel Tanougast Ahmed Bouridane Ahmed Abdulkadir School of Artificial intelligence Guilin Universiy of Electronic TechnologyGuilin 541004China Laboratory for Imagery Vision and Artificial IntelligenceEcole de Technologie SuperieureMontrealQuebec H3C 1K3Canada College of Medicine Taibah UniversityMadinah 42353Saudi Arabia College of Computer Science and Engineering Taibah UniversityMadinah 42353Saudi Arabia Laboratory of Design Optimization and Modeling SystemsUniversity of LorraineMetz 57070France center for data analytics and Cybersecurity(CDAC) University of SharjahSharjah 27272United Arab Emirates Laboratoire de recherche en neuroimagerie Centre Hospitalier Universitaire VaudoisMont Paisible 161011LausanneSwitzerland

Artificial intelligence(AI)continues to transform data analysis in many *** in each domain is driven by a growing body of annotated data,increased computational resources,and technological *** medicine,the sensitivity of the data,the complexity of the tasks,the potentially high stakes,and a requirement of accountability give rise to a particular set of *** this review,we focus on three key methodological approaches that address some of the particular challenges in AI-driven medical decision making.1)Explainable AI aims to produce a human-interpretable justification for each *** models increase confidence if the results appear plausible and match the clinicians ***,the absence of a plausible explanation does not imply an inaccurate *** in highly non-linear,complex models that are tuned to maximize accuracy,such interpretable representations only reflect a small portion of the justification.2)Domain adaptation and transfer learning enable AI models to be trained and applied across multiple *** example,a classification task based on images acquired on different acquisition hardware.3)Federated learning enables learning large-scale models without exposing sensitive personal health *** centralized AI learning,where the centralized learning machine has access to the entire training data,the federated learning process iteratively updates models across multiple sites by exchanging only parameter updates,not personal health *** narrative review covers the basic concepts,highlights relevant corner-stone and stateof-the-art research in the field,and discusses perspectives.

关键词： Domain adaptation explainable artificial intelligence federated learning

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RF-CLASS： A remote-sensing-based flood crop loss assessment cyber-service system for supporting crop statistics and insurance decision-making

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Journal of Integrative Agriculture 2017年第2期16卷 408-423页

作者： Liping Di Eugene G. Yu Lingjun Kang Ranjay Shrestha BAI Yu-qi center for Spatial Information Science and Systems (CSISS) George Mason University VA 22030 USA Department of Geography and Geoinformation Science George Mason University VA 22030 USA Key Laboratory for Earth System modelling Ministry of Education/Department of Earth System Science (DESS) Tsinghua University Beijing 100084 P.R. China

Floods often cause significant crop loss in the United States. Timely and objective information on flood-related crop loss, such as flooded acreage and degree of crop damage, is very important for crop monitoring and risk management in ag- ricultural and disaster-related decision-making at many concerned agencies. Currently concerned agencies mostly rely on field surveys to obtain crop loss information and compensate farmers＇ loss claim. Such methods are expensive, labor intensive, and time consumptive, especially for a large flood that affects a large geographic area. The results from such methods suffer from inaccuracy, subjectiveness, untimeliness, and lack of reproducibility. Recent studies have demonstrated that Earth observation （EO） data could be used in post-flood crop loss assessment for a large geographic area objectively, timely, accurately, and cost effectively. However, there is no operational decision support system, which employs such EO-based data and algorithms for operational flood-related crop decision-making. This paper describes the development of an EO-based flood crop loss assessment cyber-service system, RF-CLASS, for supporting flood-related crop statistics and insurance decision-making. Based on the service-orientated architecture, RF-CLASS has been implemented with open interoperability specifications to facilitate the interoperability with EO data systems, particularly the National Aeronautics and Space Administration （NASA） Earth Observing System data and Information System （EOSDIS）, for automatically fetching the input data from the data systems. Validated EO algorithms have been implemented as web services in the system to operationally produce a set of flood-related products from EO data, such as flood frequency, flooded acreage, and degree of crop damage, for supporting decision-making in flood statistics and flood crop insurance policy. The system leverages recent advances in the remote sensing-based flood monitoring and assessment,

关键词： crop condition flooding crop damage time series MODIS web service remote sensing decision-making

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Machine Learning With data Assimilation and Uncertainty Quantification for Dynamical Systems:A Review

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IEEE/CAA Journal of Automatica Sinica 2023年第6期10卷 1361-1387页

作者： Sibo Cheng César Quilodrán-Casas Said Ouala Alban Farchi Che Liu Pierre Tandeo Ronan Fablet Didier Lucor Bertrand Iooss Julien Brajard Dunhui Xiao Tijana Janjic Weiping Ding Yike Guo Alberto Carrassi Marc Bocquet Rossella Arcucci data Science Institute Department of ComputingImperial College LondonSW72AZ London Department of Earth Science and Engineering Imperial College LondonSW72AZ London Department of Computer Science and Engineering Hong Kong University of Science and TechnologyHong Kong 999077China the IMT Atlantique Lab-STICCUMR CNRS 6285France and OdysseyInria/IMTFrance.P.Tandeo is also with RIKEN Center for Computational ScienceKobeJapan the CEREA École des Ponts and EDF R&Dîle-de-FranceFrance the Laboratoire Interdisciplinaire des Sciences du Numérique CNRSParis-Saclay UniversityF-91403OrsayFrance the Electricitéde France(EDF) 78401 ChatouFranceInstitut de Mathématiques de Toulouse31062 ToulouseFrance and SINCLAIR AI LabSaclayFrance the Sorbonne University ParisFranceand also with Nansen Environmental and Remote Sensing Center(NERSC)BergenNorway the School of mathematical Sciences Tongji UniversityShanghai 200092China the mathematical Institute for Machine Learning and data Science KU Eichstaett-IngolstadtBavariaGermany the School of Information Science and Technology Nantong UniversityNantong 226019China the Department of Physics and Astronomy“Augusto Righi” University of Bologna40124 BolognaItaly

data assimilation(DA)and uncertainty quantification(UQ)are extensively used in analysing and reducing error propagation in high-dimensional spatial-temporal *** applications span from computational fluid dynamics(CFD)to geoscience and climate ***,much effort has been given in combining DA,UQ and machine learning(ML)*** research efforts seek to address some critical challenges in high-dimensional dynamical systems,including but not limited to dynamical system identification,reduced order surrogate modelling,error covariance specification and model error correction.A large number of developed techniques and methodologies exhibit a broad applicability across numerous domains,resulting in the necessity for a comprehensive *** paper provides the first overview of state-of-the-art researches in this interdisciplinary field,covering a wide range of *** review is aimed at ML scientists who attempt to apply DA and UQ techniques to improve the accuracy and the interpretability of their models,but also at DA and UQ experts who intend to integrate cutting-edge ML approaches to their ***,this article has a special focus on how ML methods can overcome the existing limits of DA and UQ,and vice *** exciting perspectives of this rapidly developing research field are also *** Terms-data assimilation(DA),deep learning,machine learning(ML),reduced-order-modelling,uncertainty quantification(UQ).

关键词： assimilation overcome apply

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Integrated medical resource consumption stratification in hospitalized patients:an Auto Triage Management model based on accurate risk,cost and length of stay prediction

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Science China(Life Sciences) 2022年第5期65卷 988-999页

作者： Qin Zhong Zongren Li Wenjun Wang Lei Zhang Kunlun He Medical Big data Research center Chinese PLA General HospitalBeijing 100853China Medical Artificial Intelligence Research center Chinese PLA General HospitalBeijing 100853China Bio-engineering Research center Chinese PLA General HospitalBeijing 100039China Department of Cardiology Fourth Medical Center of Chinese PLA General HospitalBeijing 100048China Key Laboratory of Ministry of Industry and Information Technology of Biomedical Engineering and Translational Medicine Chinese PLA General HospitalBeijing 100048China China-Australia Joint Research center for Infectious Diseases School of Public HealthXi’an Jiaotong University Health Science CenterXi’an 710061China

Triage management plays important roles in hospitalized patients for disease severity stratification and medical burden *** progression risks have been extensively researched for numbers of diseases,other crucial indicators that reflect patients’economic and time costs have not been systematically *** address the problems,we developed an automatic deep learning based Auto Triage Management(ATM)Framework capable of accurately modelling patients’disease progression risk and health economic *** on them,we can first discover the relationship between disease progression and medical system cost,find potential features that can more precisely aid patient triage in resource allocation,and allow treatment plan searching that has cured *** ATM in COVID-19,we built a joint model to predict patients’risk,the total length of stay(Lo S)and cost when at-admission,and remaining Lo S and cost at a given hospitalized time point,with C-index0.930 and 0.869 for risk prediction,mean absolute error(MAE)of 5.61 and 5.90 days for total Lo S prediction in internal and external validation data.

关键词： patient triage AutoML electronic medical records

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A model for the transportation and distribution of jellyfish Rhopilema esculentum for stock enhancement in the Liaodong Bay, China

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Acta Oceanologica Sinica 2019年第1期38卷 90-101页

作者： Liping Yin Xiujuan Shan Chang Zhao Xianshi Jin Guansuo Wang Fangli Qiao First Institute of Oceanography Ministry of Natural Resources Laboratory for Regional Oceanography and Numerical Modeling Pilot National Laboratory for Marine Science and Technology (Qingdao) Key Laboratory of Marine Science and Numerical modelling Ministry of Natural Resources Yellow Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Laboratory for Marine Fisheries Science and Food Production Processes Pilot Qingdao National Laboratory for Marine Science and Technology (Qingdao) Key Laboratory of data Analysis and Applications Ministry of Natural Resources

A numerical model for jellyfish Rhopilema esculentum stock enhancement is developed for the first time. The model is based on an operational ocean circulation-surface wave coupled forecasting system for the seas off China and adjacent areas and uses a Lagrangian particle-tracking scheme to track the trajectories of released jellyfish. The Jellyfish are modeled as particles with diel vertical migration and are passively drifted by the current and dispersion due to the sub-grid processes. A comparison between the simulation and survey results demonstrate that the model can capture the primary distribution patterns of the released jellyfish. The model results show that the ocean current and indirect wind impact are the main drivers controlling the jellyfish transport. A connectivity matrix between the release sites and fishing grounds indicates the top of the bay is better than the eastern and western coasts for jellyfish fishing. The matrix also shows that only 45% and 27% of the jellyfish released from Wafangdian(WFD) can enter the fishing ground in 2008 and 2010; thus, the site near WFD is not an advisable location for jellyfish release. A Lagrangian probability density function based on a nine-year tracing experiment validates the results and further provides a "climatology" distribution of the released *** experiments are conducted to examine the sensitivity of the model to random walk schemes and to release conditions. The model requires a random walk but is insensitive to the random walk scheme. The experiments with different habitat depths show that if the jellyfish are fixed on the bottom of the water, most of them will be transported to the center, or even out of the bay, by the bottom circulation.

关键词： Liaodong Bay Jellyfish Rhopilema esculentum distribution and connectivity Lagrangian particle tracking current

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