Based on rain gauge data during 2008-2021 from national meteorological observation stations,this study investigated the performance of the precipitation field from the 1-km-resolution version of the China Atmospheric ...Based on rain gauge data during 2008-2021 from national meteorological observation stations,this study investigated the performance of the precipitation field from the 1-km-resolution version of the China Atmospheric Realtime Analysis(CARAS)over Hubei from the perspective of climatology,multiple-time scale variations,as well as fusion accuracy and detection capability at multiple temporal scales.The results show that CARAS precipitation can reproduce the spatial distribution patterns of climatological seasonal precipitation and rainy days well over the whole of Hubei compared with observational(OBS)precipitation,albeit deviations exist between CARAS and OBS in terms of magnitude.Moreover,high correlation and consistency between CARAS and OBS can be found in multiple-time scale variations over Hubei,with correlation coefficients of interannual,seasonal,and diurnal variation generally exceeding 0.85,0.98,and 0.95,respectively.Furthermore,CARAS has a relatively higher fusion accuracy in summer and winter,and stronger/weaker detection capability in spring/winter at a daily scale.However,the detection capability of CARAS at an hourly scale is weaker than that at a daily scale.With different precipitation intensity levels considered,CARAS daily precipitation shows relatively higher fusion accuracy in estimating moderate and heavy rain,and better detection capability in capturing no rain events.The variations of accuracy metrics and detection metrics under different precipitation intensities at an hourly scale generally resemble those at a daily scale.However,CARAS precipitation at an hourly scale shows a relatively lower fusion accuracy and weaker detection capability compared with that at a daily scale.This paper provides an insight into the characteristics of systematic deviations in CARAS precipitation over Hubei,which will benefit relevant applications of CARAS in meteorological operations over Hubei and the improvement of CARAS in the future.展开更多
This study assesses the predictive capabilities of the CMA-GD model for wind speed prediction in two wind farms located in Hubei Province,China.The observed wind speeds at the height of 70m in wind turbines of two win...This study assesses the predictive capabilities of the CMA-GD model for wind speed prediction in two wind farms located in Hubei Province,China.The observed wind speeds at the height of 70m in wind turbines of two wind farms in Suizhou serve as the actual observation data for comparison and testing.At the same time,the wind speed predicted by the EC model is also included for comparative analysis.The results indicate that the CMA-GD model performs better than the EC model in Wind Farm A.The CMA-GD model exhibits a monthly average correlation coefficient of 0.56,root mean square error of 2.72 m s^(-1),and average absolute error of 2.11 m s^(-1).In contrast,the EC model shows a monthly average correlation coefficient of 0.51,root mean square error of 2.83 m s^(-1),and average absolute error of 2.21 m s^(-1).Conversely,in Wind Farm B,the EC model outperforms the CMA-GD model.The CMA-GD model achieves a monthly average correlation coefficient of 0.55,root mean square error of 2.61 m s^(-1),and average absolute error of 2.13 m s^(-1).By contrast,the EC model displays a monthly average correlation coefficient of 0.63,root mean square error of 2.04 m s^(-1),and average absolute error of 1.67 m s^(-1).展开更多
Green and low-carbon is a new development model that seeks balance between environmental sustainability and high economic growth.If explainable and available carbon emission data can be accurately obtained,it will hel...Green and low-carbon is a new development model that seeks balance between environmental sustainability and high economic growth.If explainable and available carbon emission data can be accurately obtained,it will help policy regulators and enterprise managers to more accurately implement this development strategy.A lot of research has been carried out,but it is still a difficult problem that how to accommodate and adapt the complex carbon emission data computing models and factor libraries developed by different regions,different industries and different enterprises.Meanwhile,with the rapid development of the Industrial Internet,it has not only been used for the supply chain optimization and intelligent scheduling of the manufacturing industry,but also been used by more and more industries as an important way of digital transformation.Especially in China,the Industrial Internet identification and resolution system is becoming an important digital infrastructure to uniquely identify objects and share data.Hence,a compatible carbon efficiency information service framework based on the Industrial Internet Identification is proposed in this paper to address the problem of computing and querying multi-source heterogeneous carbon emission data.We have defined a multi cooperation carbon emission data interaction model consisting of three roles and three basic operations.Further,the implementation of the framework includes carbon emission data identification,modeling,calculation,query and sharing.The practice results show that its capability and effectiveness in improving the responsiveness,accuracy,and credibility of compatible carbon efficiency data query and sharing services.展开更多
BACKGROUND:To investigate the prognostic value of the peripheral perfusion index(PPI)in patients with septic shock.METHODS:This prospective cohort study,conducted at the emergency intensive care unit of Peking Univers...BACKGROUND:To investigate the prognostic value of the peripheral perfusion index(PPI)in patients with septic shock.METHODS:This prospective cohort study,conducted at the emergency intensive care unit of Peking University People's Hospital,recruited 200 patients with septic shock between January 2023 and August 2023.These patients were divided into survival(n=84)and death(n=116)groups based on 28-day outcomes.Clinical evaluations included laboratory tests and clinical scores,with lactate and PPI values assessed upon admission to the emergency room and at 6 h and 12 h after admission.Risk factors associated with mortality were analyzed using univariate and multivariate Cox regression analyses.Receiver operator characteristic(ROC)curve was used to assess predictive performance.Mortality rates were compared,and Kaplan-Meier survival plots were created.RESULTS:Compared to the survival group,patients in the death group were older and had more severe liver damage and coagulation dysfunction,necessitating higher norepinephrine doses and increased fl uid replacement.Higher lactate levels and lower PPI levels at 0 h,6 h,and 12 h were observed in the death group.Multivariate Cox regression identifi ed prolonged prothrombin time(PT),decreased 6-h PPI and 12-h PPI as independent risk factors for death.The area under the curves for 6-h PPI and 12-h PPI were 0.802(95%CI 0.742-0.863,P<0.001)and 0.945(95%CI 0.915-0.974,P<0.001),respectively,which were superior to Glasgow Coma Scale(GCS),Sequential Organ Failure Assessment(SOFA)scores(0.864 and 0.928).Cumulative mortality in the low PPI groups at 6 h and 12 h was signifi cantly higher than in the high PPI groups(6-h PPI:77.52%vs.22.54%;12-h PPI:92.04%vs.13.79%,P<0.001).CONCLUSION:PPI may have value in predicting 28-day mortality in patients with septic shock.展开更多
基金Key Research Project of Hubei Provincial Tobacco Company(027Y2022-006)Hubei Provincial Natural Science Foundation and Meteorological Innovation and Development Joint Foundation of China(2023AFD104,2022CFD132)+4 种基金Open Project Fund of China Meteorological Administration Basin Heavy Rainfall Key Laboratory(2023BHR-Y03)Open Re-search Fund of China Meteorological Administration/Ministry of Rural Agriculture Tobacco Meteorological Service Center(KYZX2023-08)National Natural Science Foundation of China(42105039)Basic Research Fund of WHIHR(202314)Open Research Topics of Key Open Laboratory of Hydro-Meteorology,China Meteorological Administration(23SWQXM018)。
文摘Based on rain gauge data during 2008-2021 from national meteorological observation stations,this study investigated the performance of the precipitation field from the 1-km-resolution version of the China Atmospheric Realtime Analysis(CARAS)over Hubei from the perspective of climatology,multiple-time scale variations,as well as fusion accuracy and detection capability at multiple temporal scales.The results show that CARAS precipitation can reproduce the spatial distribution patterns of climatological seasonal precipitation and rainy days well over the whole of Hubei compared with observational(OBS)precipitation,albeit deviations exist between CARAS and OBS in terms of magnitude.Moreover,high correlation and consistency between CARAS and OBS can be found in multiple-time scale variations over Hubei,with correlation coefficients of interannual,seasonal,and diurnal variation generally exceeding 0.85,0.98,and 0.95,respectively.Furthermore,CARAS has a relatively higher fusion accuracy in summer and winter,and stronger/weaker detection capability in spring/winter at a daily scale.However,the detection capability of CARAS at an hourly scale is weaker than that at a daily scale.With different precipitation intensity levels considered,CARAS daily precipitation shows relatively higher fusion accuracy in estimating moderate and heavy rain,and better detection capability in capturing no rain events.The variations of accuracy metrics and detection metrics under different precipitation intensities at an hourly scale generally resemble those at a daily scale.However,CARAS precipitation at an hourly scale shows a relatively lower fusion accuracy and weaker detection capability compared with that at a daily scale.This paper provides an insight into the characteristics of systematic deviations in CARAS precipitation over Hubei,which will benefit relevant applications of CARAS in meteorological operations over Hubei and the improvement of CARAS in the future.
基金National Key Research and Development Program of the Ministry of Science(2018YFB1502801)Hubei Provincial Natural Science Foundation(2022CFD017)Innovation and Development Project of China Meteorological Administration(CXFZ2023J044)。
文摘This study assesses the predictive capabilities of the CMA-GD model for wind speed prediction in two wind farms located in Hubei Province,China.The observed wind speeds at the height of 70m in wind turbines of two wind farms in Suizhou serve as the actual observation data for comparison and testing.At the same time,the wind speed predicted by the EC model is also included for comparative analysis.The results indicate that the CMA-GD model performs better than the EC model in Wind Farm A.The CMA-GD model exhibits a monthly average correlation coefficient of 0.56,root mean square error of 2.72 m s^(-1),and average absolute error of 2.11 m s^(-1).In contrast,the EC model shows a monthly average correlation coefficient of 0.51,root mean square error of 2.83 m s^(-1),and average absolute error of 2.21 m s^(-1).Conversely,in Wind Farm B,the EC model outperforms the CMA-GD model.The CMA-GD model achieves a monthly average correlation coefficient of 0.55,root mean square error of 2.61 m s^(-1),and average absolute error of 2.13 m s^(-1).By contrast,the EC model displays a monthly average correlation coefficient of 0.63,root mean square error of 2.04 m s^(-1),and average absolute error of 1.67 m s^(-1).
基金supported by the 2018 Industrial Internet Innovation and Development Project——Industrial Internet Identification Resolution Sys⁃tem:National Top-Level Node Construction Project(Phase I).
文摘Green and low-carbon is a new development model that seeks balance between environmental sustainability and high economic growth.If explainable and available carbon emission data can be accurately obtained,it will help policy regulators and enterprise managers to more accurately implement this development strategy.A lot of research has been carried out,but it is still a difficult problem that how to accommodate and adapt the complex carbon emission data computing models and factor libraries developed by different regions,different industries and different enterprises.Meanwhile,with the rapid development of the Industrial Internet,it has not only been used for the supply chain optimization and intelligent scheduling of the manufacturing industry,but also been used by more and more industries as an important way of digital transformation.Especially in China,the Industrial Internet identification and resolution system is becoming an important digital infrastructure to uniquely identify objects and share data.Hence,a compatible carbon efficiency information service framework based on the Industrial Internet Identification is proposed in this paper to address the problem of computing and querying multi-source heterogeneous carbon emission data.We have defined a multi cooperation carbon emission data interaction model consisting of three roles and three basic operations.Further,the implementation of the framework includes carbon emission data identification,modeling,calculation,query and sharing.The practice results show that its capability and effectiveness in improving the responsiveness,accuracy,and credibility of compatible carbon efficiency data query and sharing services.
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2020D01C236)
文摘BACKGROUND:To investigate the prognostic value of the peripheral perfusion index(PPI)in patients with septic shock.METHODS:This prospective cohort study,conducted at the emergency intensive care unit of Peking University People's Hospital,recruited 200 patients with septic shock between January 2023 and August 2023.These patients were divided into survival(n=84)and death(n=116)groups based on 28-day outcomes.Clinical evaluations included laboratory tests and clinical scores,with lactate and PPI values assessed upon admission to the emergency room and at 6 h and 12 h after admission.Risk factors associated with mortality were analyzed using univariate and multivariate Cox regression analyses.Receiver operator characteristic(ROC)curve was used to assess predictive performance.Mortality rates were compared,and Kaplan-Meier survival plots were created.RESULTS:Compared to the survival group,patients in the death group were older and had more severe liver damage and coagulation dysfunction,necessitating higher norepinephrine doses and increased fl uid replacement.Higher lactate levels and lower PPI levels at 0 h,6 h,and 12 h were observed in the death group.Multivariate Cox regression identifi ed prolonged prothrombin time(PT),decreased 6-h PPI and 12-h PPI as independent risk factors for death.The area under the curves for 6-h PPI and 12-h PPI were 0.802(95%CI 0.742-0.863,P<0.001)and 0.945(95%CI 0.915-0.974,P<0.001),respectively,which were superior to Glasgow Coma Scale(GCS),Sequential Organ Failure Assessment(SOFA)scores(0.864 and 0.928).Cumulative mortality in the low PPI groups at 6 h and 12 h was signifi cantly higher than in the high PPI groups(6-h PPI:77.52%vs.22.54%;12-h PPI:92.04%vs.13.79%,P<0.001).CONCLUSION:PPI may have value in predicting 28-day mortality in patients with septic shock.
