Objective:This study mainly analyzed the clinical characteristics of patients with COVID-19 in Suining,one of China’s fourth-tier cities,and Wuhan and compared data between the 2 cities.Methods:A retrospective analys...Objective:This study mainly analyzed the clinical characteristics of patients with COVID-19 in Suining,one of China’s fourth-tier cities,and Wuhan and compared data between the 2 cities.Methods:A retrospective analysis of the clinical data of 68 patients with COVID-19 diagnosed at Wuhan Red Cross Hospital and 17 patients diagnosed at Suining Central Hospital,was conducted.Results:Among the 68 patients with COVID-19 in Wuhan,30(44.1%)had hypertension,and 25(36.8%)had diabetes.Three out of the 17 patients in Suining(17.6%)had hypertension,and 2 patients(11.8%)had diabetes.In the clinical classification,there were 1(5.9%)and 23(33.8%)patients with severe COVID-19 in Suining and Wuhan,respectively.Chest CT showed that lung consolidation occurred in 2(11.8%)and 26(38.2%)patients with COVID-19 in Suining and Wuhan,respectively.The proportion of patients with diabetes or hypertension,severe COVID-19,lung consolidation in Wuhan was significantly higher than that in Suining.The laboratory tests suggested that percentage of elevated C-reactive protein(CRP)(58.8%),ALT(33.8%),blood glucose(45.6%),creatine kinase(CK)(33.8%)or D-dimer(47.1%)of patients in Wuhan were significantly increased than those in Suining(29.4%,5.9%,17.6%,5.9%,and 17.7%,respectively).Conclusion:The incidence of COVID-19 in fourth-tier city and the disease severity were significantly lower than that in Wuhan.展开更多
Due to the constraints of manufacturing and materials,high-power plants cannot rely on only one solid oxide fuel cell stack.A multi-stack system is a solution for a highpower system,which consists of multiple fuel cel...Due to the constraints of manufacturing and materials,high-power plants cannot rely on only one solid oxide fuel cell stack.A multi-stack system is a solution for a highpower system,which consists of multiple fuel cell stacks.A short lifetime is one of the main challenges for the fuel cell before largescale commercial applications,and prognostic is an important method to improve the reliability of fuel cells.Different from the traditional prognostic approaches applied to single-stack fuel cell systems,the key problem in multi-stack prediction is how to solve the correlation of multi-stack degradation,which can directly affect the accuracy of prediction.In response to this difficulty,a standard Brownian motion is added to the traditional Wiener process to model the degradation of each stack,and then the probability density function of the remaining useful life(RUL)of each stack is calculated.Furthermore,a Copula function is adopted to reflect the dependence between life distributions,so as to obtain the remaining useful life for the whole multi-stack system.1 The simulation results show that compared with the traditional prediction model,the proposed approach has a higher prediction accuracy for multi-stack fuel cell systems.展开更多
基金Coronavirus Prevention and Control Technology Project of Suining City,Sichuan Province(No.2020PTJSGG007).
文摘Objective:This study mainly analyzed the clinical characteristics of patients with COVID-19 in Suining,one of China’s fourth-tier cities,and Wuhan and compared data between the 2 cities.Methods:A retrospective analysis of the clinical data of 68 patients with COVID-19 diagnosed at Wuhan Red Cross Hospital and 17 patients diagnosed at Suining Central Hospital,was conducted.Results:Among the 68 patients with COVID-19 in Wuhan,30(44.1%)had hypertension,and 25(36.8%)had diabetes.Three out of the 17 patients in Suining(17.6%)had hypertension,and 2 patients(11.8%)had diabetes.In the clinical classification,there were 1(5.9%)and 23(33.8%)patients with severe COVID-19 in Suining and Wuhan,respectively.Chest CT showed that lung consolidation occurred in 2(11.8%)and 26(38.2%)patients with COVID-19 in Suining and Wuhan,respectively.The proportion of patients with diabetes or hypertension,severe COVID-19,lung consolidation in Wuhan was significantly higher than that in Suining.The laboratory tests suggested that percentage of elevated C-reactive protein(CRP)(58.8%),ALT(33.8%),blood glucose(45.6%),creatine kinase(CK)(33.8%)or D-dimer(47.1%)of patients in Wuhan were significantly increased than those in Suining(29.4%,5.9%,17.6%,5.9%,and 17.7%,respectively).Conclusion:The incidence of COVID-19 in fourth-tier city and the disease severity were significantly lower than that in Wuhan.
基金supported by the State key R&D sub project(Grant No.2020YFB 1506002-03)the Department of Science and Technology of Sichuan Province(Grant No.2020YJ0109)+2 种基金the Fundamental Research Funds for the Central Universities(Grant No.ZYGX2019J060)the State Key Laboratory of Automotive Safety and Energy(Grant No.KF2022)the National Natural Science Foundation of China(Grant No.U2066202).
文摘Due to the constraints of manufacturing and materials,high-power plants cannot rely on only one solid oxide fuel cell stack.A multi-stack system is a solution for a highpower system,which consists of multiple fuel cell stacks.A short lifetime is one of the main challenges for the fuel cell before largescale commercial applications,and prognostic is an important method to improve the reliability of fuel cells.Different from the traditional prognostic approaches applied to single-stack fuel cell systems,the key problem in multi-stack prediction is how to solve the correlation of multi-stack degradation,which can directly affect the accuracy of prediction.In response to this difficulty,a standard Brownian motion is added to the traditional Wiener process to model the degradation of each stack,and then the probability density function of the remaining useful life(RUL)of each stack is calculated.Furthermore,a Copula function is adopted to reflect the dependence between life distributions,so as to obtain the remaining useful life for the whole multi-stack system.1 The simulation results show that compared with the traditional prediction model,the proposed approach has a higher prediction accuracy for multi-stack fuel cell systems.
