Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting...Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.展开更多
Wetlands play a critical role in the global environment.The Middle Yangtze River Basin(MYRB),known for its abundant wetland resources,has experienced notable changes resulting from the complex interplay of environment...Wetlands play a critical role in the global environment.The Middle Yangtze River Basin(MYRB),known for its abundant wetland resources,has experienced notable changes resulting from the complex interplay of environmental factors.Therefore,we investigated the spatiotemporal characteristics of wetland ecological quality in the MYRB from 2001 to 2020.Utilizing the random forest(RF)regression algorithm and patch-generated land-use simulation(PLUS)model,we forecasted variations in wetland habitat quality and their determinants under the Shared Socioeconomic Pathway-Representative Concentration Pathway(SSPRCP)framework from 2035 to 2095.The main findings are as follows:(1)The RF algorithm was optimal for land-use and land-cover(LULC)classification in the MYRB from 2001 to 2020,when notable changes were observed in water bodies and buildings.However,the forested area exhibited an increase and decrease of 3.9%and 1.2%under the SSP1-2.6 and SSP5-8.5 scenarios,respectively,whereas farmland exhibited a diminishing trend.(2)Wetlands were primarily concentrated in the central and eastern MYRB,with counties in the southwest exhibiting superior ecological-environmental quality from 2001 to 2020.Notably,wetland coverage revealed significantly high level,significant changes,frequent but relatively minor changes under the SSP1-2.6,SSP2-4.5,and SSP 5-8.5 scenarios,respectively.(3)Regions with lower habitat quality were primarily concentrated in urbanized areas characterized by frequent human activities,indicating a clear degradation in habitat quality across different scenarios.In conclusion,we established a foundational framework for future investigations into the eco-hydrological processes and ecosystem quality of watersheds.展开更多
目的探究纤维支气管镜(纤支镜)早期介入治疗儿童塑型性支气管炎的临床疗效。方法选取2022年1月至2023年6月于益阳市中心医院就诊的50例0~14岁塑型性支气管炎患儿作为研究对象,根据病程及纤支镜介入时间分为研究组与对照组,每组25例。研...目的探究纤维支气管镜(纤支镜)早期介入治疗儿童塑型性支气管炎的临床疗效。方法选取2022年1月至2023年6月于益阳市中心医院就诊的50例0~14岁塑型性支气管炎患儿作为研究对象,根据病程及纤支镜介入时间分为研究组与对照组,每组25例。研究组在病程≤10 d时行纤支镜介入治疗,对照组在病程>10 d时行纤支镜介入治疗。比较两组临床指标、临床疗效及治疗前后肺功能指标[第1秒用力呼气容积(forced expiratory volume in the first second,FEV_(1))、呼气峰流速(peak expiratory flow rate,PEF)、潮气量(tidal volume,VT)、达峰时间比(time to peak tidal expiratory flow as a proportion of expiratory time,TPTEF/TE)、达峰容积比(volume to peak tidal expiratory flow as a proportion of exhaled volume,VPEF/VE)]、动脉血气指标、炎症因子[C反应蛋白(C-reactive protein,CRP)、白细胞介素-6(interleukin-6,IL-6)、降钙素原(procalcitonin,PCT)]水平。结果研究组发热消失时间、咳嗽咳痰消失时间、肺部湿啰音消失时间、喘息消失时间均短于对照组,差异有统计学意义(P<0.05)。治疗后,研究组5岁以上患儿FEV_(1)、PEF大于对照组,0~4岁患儿VT大于对照组,TPTEF/TE、VPEF/VE水平高于对照组,差异有统计学意义(P<0.05)。治疗后,研究组血氧饱和度大于对照组,血氧分压高于对照组,差异有统计学意义(P<0.05)。治疗后,研究组PCT、IL-6、CRP水平均低于对照组,差异有统计学意义(P<0.05)。研究组治疗总有效率为92.00%,高于对照组的68.00%,差异有统计学意义(P<0.05)。结论纤支镜早期介入治疗儿童塑型性支气管炎能加快患儿临床恢复,促进肺功能改善,减轻机体炎症反应,具有显著的治疗效果,临床应用价值高。展开更多
基金National Key Research and Development Program of China,No.2023YFC3006704National Natural Science Foundation of China,No.42171047CAS-CSIRO Partnership Joint Project of 2024,No.177GJHZ2023097MI。
文摘Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.
基金National Natural Science Foundation of China,No.42207078CUG Scholar-Scientific Research Funds at China University of Geosciences(Wuhan),No.2022166+1 种基金China Scholarship Council,No.202306410026Opening Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin,China Institute of Water Resources and Hydropower Research,No.IWHR-SKL-KF202217。
文摘Wetlands play a critical role in the global environment.The Middle Yangtze River Basin(MYRB),known for its abundant wetland resources,has experienced notable changes resulting from the complex interplay of environmental factors.Therefore,we investigated the spatiotemporal characteristics of wetland ecological quality in the MYRB from 2001 to 2020.Utilizing the random forest(RF)regression algorithm and patch-generated land-use simulation(PLUS)model,we forecasted variations in wetland habitat quality and their determinants under the Shared Socioeconomic Pathway-Representative Concentration Pathway(SSPRCP)framework from 2035 to 2095.The main findings are as follows:(1)The RF algorithm was optimal for land-use and land-cover(LULC)classification in the MYRB from 2001 to 2020,when notable changes were observed in water bodies and buildings.However,the forested area exhibited an increase and decrease of 3.9%and 1.2%under the SSP1-2.6 and SSP5-8.5 scenarios,respectively,whereas farmland exhibited a diminishing trend.(2)Wetlands were primarily concentrated in the central and eastern MYRB,with counties in the southwest exhibiting superior ecological-environmental quality from 2001 to 2020.Notably,wetland coverage revealed significantly high level,significant changes,frequent but relatively minor changes under the SSP1-2.6,SSP2-4.5,and SSP 5-8.5 scenarios,respectively.(3)Regions with lower habitat quality were primarily concentrated in urbanized areas characterized by frequent human activities,indicating a clear degradation in habitat quality across different scenarios.In conclusion,we established a foundational framework for future investigations into the eco-hydrological processes and ecosystem quality of watersheds.
文摘目的探究纤维支气管镜(纤支镜)早期介入治疗儿童塑型性支气管炎的临床疗效。方法选取2022年1月至2023年6月于益阳市中心医院就诊的50例0~14岁塑型性支气管炎患儿作为研究对象,根据病程及纤支镜介入时间分为研究组与对照组,每组25例。研究组在病程≤10 d时行纤支镜介入治疗,对照组在病程>10 d时行纤支镜介入治疗。比较两组临床指标、临床疗效及治疗前后肺功能指标[第1秒用力呼气容积(forced expiratory volume in the first second,FEV_(1))、呼气峰流速(peak expiratory flow rate,PEF)、潮气量(tidal volume,VT)、达峰时间比(time to peak tidal expiratory flow as a proportion of expiratory time,TPTEF/TE)、达峰容积比(volume to peak tidal expiratory flow as a proportion of exhaled volume,VPEF/VE)]、动脉血气指标、炎症因子[C反应蛋白(C-reactive protein,CRP)、白细胞介素-6(interleukin-6,IL-6)、降钙素原(procalcitonin,PCT)]水平。结果研究组发热消失时间、咳嗽咳痰消失时间、肺部湿啰音消失时间、喘息消失时间均短于对照组,差异有统计学意义(P<0.05)。治疗后,研究组5岁以上患儿FEV_(1)、PEF大于对照组,0~4岁患儿VT大于对照组,TPTEF/TE、VPEF/VE水平高于对照组,差异有统计学意义(P<0.05)。治疗后,研究组血氧饱和度大于对照组,血氧分压高于对照组,差异有统计学意义(P<0.05)。治疗后,研究组PCT、IL-6、CRP水平均低于对照组,差异有统计学意义(P<0.05)。研究组治疗总有效率为92.00%,高于对照组的68.00%,差异有统计学意义(P<0.05)。结论纤支镜早期介入治疗儿童塑型性支气管炎能加快患儿临床恢复,促进肺功能改善,减轻机体炎症反应,具有显著的治疗效果,临床应用价值高。
