In this work,the size-dependent buckling of functionally graded(FG)Bernoulli-Euler beams under non-uniform temperature is analyzed based on the stressdriven nonlocal elasticity and nonlocal heat conduction.By utilizin...In this work,the size-dependent buckling of functionally graded(FG)Bernoulli-Euler beams under non-uniform temperature is analyzed based on the stressdriven nonlocal elasticity and nonlocal heat conduction.By utilizing the variational principle of virtual work,the governing equations and the associated standard boundary conditions are systematically extracted,and the thermal effect,equivalent to the induced thermal load,is explicitly assessed by using the nonlocal heat conduction law.The stressdriven constitutive integral equation is equivalently transformed into a differential form with two non-standard constitutive boundary conditions.By employing the eigenvalue method,the critical buckling loads of the beams with different boundary conditions are obtained.The numerically predicted results reveal that the growth of the nonlocal parameter leads to a consistently strengthening effect on the dimensionless critical buckling loads for all boundary cases.Additionally,the effects of the influential factors pertinent to the nonlocal heat conduction on the buckling behavior are carefully examined.展开更多
The sudden outbreak of the Coronavirus disease(COVID-19)swept across the world in early 2020,triggering the lockdowns of several billion people across many countries,including China,Spain,India,the U.K.,Italy,France,G...The sudden outbreak of the Coronavirus disease(COVID-19)swept across the world in early 2020,triggering the lockdowns of several billion people across many countries,including China,Spain,India,the U.K.,Italy,France,Germany,Brazil,Russia,and the U.S.The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S.,India,Russia,and Brazil.In response to this national and global emergency,the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implementation strategies to rapidly respond to this crisis,for supporting research,saving lives,and protecting the health of global citizens.This perspective paper presents our collective view on the global health emergency and our effort in collecting,analyzing,and sharing relevant data on global policy and government responses,human mobility,environmental impact,socioeconomical impact;in developing research capabilities and mitigation measures with global scientists,promoting collaborative research on outbreak dynamics,and reflecting on the dynamic responses from human societies.展开更多
The sparse and uneven placement of rain gauges across the Tibetan Plateau(TP)impedes the acquisition of precise,high-resolution precipitation measurements,thus challenging the reliability of forecast data.To address s...The sparse and uneven placement of rain gauges across the Tibetan Plateau(TP)impedes the acquisition of precise,high-resolution precipitation measurements,thus challenging the reliability of forecast data.To address such a challenge,we introduce a model called Multisource Generative Adversarial Network-Convolutional Long Short-Term Memory(GAN-ConvLSTM)for Precipitation Nowcasting(MGCPN),which utilizes data products from the Integrated Multi-satellite Retrievals for global precipitation measurement(IMERG)data,offering high spatiotemporal resolution precipitation forecasts for upcoming periods ranging from 30 to 300 min.The results of our study confirm that the implementation of the MGCPN model successfully addresses the problem of underestimating and blurring precipitation results that often arise with increasing forecast time.This issue is a common challenge in precipitation forecasting models.Furthermore,we have used multisource spatiotemporal datasets with integrated geographic elements for training and prediction to improve model accuracy.The model demonstrates its competence in generating precise precipitation nowcasting with IMERG data,offering valuable support for precipitation research and forecasting in the TP region.The metrics results obtained from our study further emphasize the notable advantages of the MGCPN model;it outperforms the other considered models in the probability of detection(POD),critical success index,Heidke Skill Score,and mean absolute error,especially showing improvements in POD by approximately 33%,19%,and 8%compared to Convolutional Gated Recurrent Unit(ConvGRU),ConvLSTM,and small Attention-UNet(SmaAt-UNet)models.展开更多
Real-time 3D weather radar data processing makes it possible to efficiently simulate meteorological processes in digital Earth and support the assessment of meteorological disasters.The current real-time meteorologica...Real-time 3D weather radar data processing makes it possible to efficiently simulate meteorological processes in digital Earth and support the assessment of meteorological disasters.The current real-time meteorological operation system can only deal with radar data within 2D space as a flat map and lacks supporting 3D characteristics.Thus,valuable 3D information imbedded in radar data cannot be completely presented to meteorological experts.Due to the large amount of data and high complexity of radar data 3D operation,regular methods are not competent for supporting real-time 3D radar data processing and representation.This study aims to perform radar data 3D operations with high efficiency and instant speed to provide real-time 3D support for the meteorological field.In this paper,a topological framework composed of basic inner topological objects is proposed along with the quadtree structure and LOD architecture,based on which 3D operations on radar data can be conducted in a split second and 3D information can be presented in real time.As the applications of the proposed topological framework,two widely used 3D algorithms in the meteorological field are also implemented in this paper.Finally,a case study verifies the applicability and validity of the proposed topological framework.展开更多
A Chinese Compilation of Physical Activities was compiled to estimate the energy costs of physical activities(PAs)using data on adults aged 18–64.Data were obtained from published articles and laboratory measurements...A Chinese Compilation of Physical Activities was compiled to estimate the energy costs of physical activities(PAs)using data on adults aged 18–64.Data were obtained from published articles and laboratory measurements.Databases,including PubMed,Embase,Scopus,Ebsco,Web of Science,Chinese National Knowledge Infrastructure,Wan Fang Data,National Science and Technology Report Service,Public Health Scientific Data were searched to collect data from inception to January 2022,on energy expenditure associated with PA in the healthy Chinese population.Two reviewers independently screened the literature and extracted,classified,and summarized data.Data were measured for 36 PAs using indirect calorimetry.Detailed descriptions of specific activities and metabolic equivalent values were provided by summarizing 241 physical activities in 13 categories.The first edition of the Chinese Compilation of PAs in Healthy Adults Aged 18–64(CCPA)was created.It provides valuable resources for people who regularly engage in physical exercise,researchers,educators,fitness professionals,and health or commercial sectors to quickly obtain various PA MET intensities.In the future,the energy expenditure of various PAs of different ages within the Chinese population can be measured based on the CCPA.展开更多
基金Project supported by the National Natural Science Foundation of China(Nos.51435008 and 51705247)the China Postdoctoral Science Foundation(No.2020M671474)
文摘In this work,the size-dependent buckling of functionally graded(FG)Bernoulli-Euler beams under non-uniform temperature is analyzed based on the stressdriven nonlocal elasticity and nonlocal heat conduction.By utilizing the variational principle of virtual work,the governing equations and the associated standard boundary conditions are systematically extracted,and the thermal effect,equivalent to the induced thermal load,is explicitly assessed by using the nonlocal heat conduction law.The stressdriven constitutive integral equation is equivalently transformed into a differential form with two non-standard constitutive boundary conditions.By employing the eigenvalue method,the critical buckling loads of the beams with different boundary conditions are obtained.The numerically predicted results reveal that the growth of the nonlocal parameter leads to a consistently strengthening effect on the dimensionless critical buckling loads for all boundary cases.Additionally,the effects of the influential factors pertinent to the nonlocal heat conduction on the buckling behavior are carefully examined.
基金NSF(1841520,1835507,1832465,2028791 and 2025783)the NSF Spatiotemporal Innovation Center members.
文摘The sudden outbreak of the Coronavirus disease(COVID-19)swept across the world in early 2020,triggering the lockdowns of several billion people across many countries,including China,Spain,India,the U.K.,Italy,France,Germany,Brazil,Russia,and the U.S.The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S.,India,Russia,and Brazil.In response to this national and global emergency,the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implementation strategies to rapidly respond to this crisis,for supporting research,saving lives,and protecting the health of global citizens.This perspective paper presents our collective view on the global health emergency and our effort in collecting,analyzing,and sharing relevant data on global policy and government responses,human mobility,environmental impact,socioeconomical impact;in developing research capabilities and mitigation measures with global scientists,promoting collaborative research on outbreak dynamics,and reflecting on the dynamic responses from human societies.
基金Supported by the National Natural Science Foundation of China(41871285 and 52104158)。
文摘The sparse and uneven placement of rain gauges across the Tibetan Plateau(TP)impedes the acquisition of precise,high-resolution precipitation measurements,thus challenging the reliability of forecast data.To address such a challenge,we introduce a model called Multisource Generative Adversarial Network-Convolutional Long Short-Term Memory(GAN-ConvLSTM)for Precipitation Nowcasting(MGCPN),which utilizes data products from the Integrated Multi-satellite Retrievals for global precipitation measurement(IMERG)data,offering high spatiotemporal resolution precipitation forecasts for upcoming periods ranging from 30 to 300 min.The results of our study confirm that the implementation of the MGCPN model successfully addresses the problem of underestimating and blurring precipitation results that often arise with increasing forecast time.This issue is a common challenge in precipitation forecasting models.Furthermore,we have used multisource spatiotemporal datasets with integrated geographic elements for training and prediction to improve model accuracy.The model demonstrates its competence in generating precise precipitation nowcasting with IMERG data,offering valuable support for precipitation research and forecasting in the TP region.The metrics results obtained from our study further emphasize the notable advantages of the MGCPN model;it outperforms the other considered models in the probability of detection(POD),critical success index,Heidke Skill Score,and mean absolute error,especially showing improvements in POD by approximately 33%,19%,and 8%compared to Convolutional Gated Recurrent Unit(ConvGRU),ConvLSTM,and small Attention-UNet(SmaAt-UNet)models.
基金supported by National Natural Science Foundation of China:[Grant Number 41871285].
文摘Real-time 3D weather radar data processing makes it possible to efficiently simulate meteorological processes in digital Earth and support the assessment of meteorological disasters.The current real-time meteorological operation system can only deal with radar data within 2D space as a flat map and lacks supporting 3D characteristics.Thus,valuable 3D information imbedded in radar data cannot be completely presented to meteorological experts.Due to the large amount of data and high complexity of radar data 3D operation,regular methods are not competent for supporting real-time 3D radar data processing and representation.This study aims to perform radar data 3D operations with high efficiency and instant speed to provide real-time 3D support for the meteorological field.In this paper,a topological framework composed of basic inner topological objects is proposed along with the quadtree structure and LOD architecture,based on which 3D operations on radar data can be conducted in a split second and 3D information can be presented in real time.As the applications of the proposed topological framework,two widely used 3D algorithms in the meteorological field are also implemented in this paper.Finally,a case study verifies the applicability and validity of the proposed topological framework.
基金Funding was provided by the National Key R&D Program of China(2018YFC2000600).
文摘A Chinese Compilation of Physical Activities was compiled to estimate the energy costs of physical activities(PAs)using data on adults aged 18–64.Data were obtained from published articles and laboratory measurements.Databases,including PubMed,Embase,Scopus,Ebsco,Web of Science,Chinese National Knowledge Infrastructure,Wan Fang Data,National Science and Technology Report Service,Public Health Scientific Data were searched to collect data from inception to January 2022,on energy expenditure associated with PA in the healthy Chinese population.Two reviewers independently screened the literature and extracted,classified,and summarized data.Data were measured for 36 PAs using indirect calorimetry.Detailed descriptions of specific activities and metabolic equivalent values were provided by summarizing 241 physical activities in 13 categories.The first edition of the Chinese Compilation of PAs in Healthy Adults Aged 18–64(CCPA)was created.It provides valuable resources for people who regularly engage in physical exercise,researchers,educators,fitness professionals,and health or commercial sectors to quickly obtain various PA MET intensities.In the future,the energy expenditure of various PAs of different ages within the Chinese population can be measured based on the CCPA.
