Cerium zirconium solid solution is a key washcoat material for automotive three-way catalysts(TWCs).However,improving the redox ability and high temperature thermal stability of cerium zirconium solid solution is stil...Cerium zirconium solid solution is a key washcoat material for automotive three-way catalysts(TWCs).However,improving the redox ability and high temperature thermal stability of cerium zirconium solid solution is still a challenge.In this paper,the cerium zirconium solid solution was prepared by a coprecipitation-hydrothermal method,and the effects of the ammonia concentration on their structures and redox properties were investigated.The results show that when the ammonia concentration is 0.8 mol/L,the aged sample(1100℃/10 h)of cerium zirconium solid solution has the highest specific surface area of 23.01 m^(2)/g.Additionally,the increase of ammonia concentration improves the uniformity of phase compositions and increases the oxygen vacancies.When the ammonia concentration reaches 0.4 mol/L,the cerium zirconium solid solution exhibits the best redox activity,with the lowest reduction temperature of 565℃.Therefore,increasing ammonia concentration in the hydrothermal treatment is beneficial to the thermal stability and redox performance of cerium zirconium solid solution.展开更多
The present study investigated the effect of body weight on body composition, digestive and absorptive capacity, transaminase activities in hepatopancreas and muscle, and plasma ammonia concentration of Jian carp(Cypr...The present study investigated the effect of body weight on body composition, digestive and absorptive capacity, transaminase activities in hepatopancreas and muscle, and plasma ammonia concentration of Jian carp(Cyprinus carpio var.Jian). A total of 750 Jian carps(18.0 ± 0.2 g) were randomly distributed into five groups with three replicates and fed the same diet for 56 days. Tissue and plasma samples were collected on days 14, 28,42, and 56. The results were used to develop a mathematical model for specific growth rate, body moisture and fat content, aspartate transaminase activity and alanine aminotransferase activity in hepatopancreas and muscle, plasma ammonia concentration, and trypsin, chymotrypsin, lipase, and amylase activities in hepatopancreas and intestine, activities of creatine kinase, Na^+/K^+-ATPase, alkaline phosphatase, and γ-glutamyl transpeptidase in intestine in Jian carp. There were linear relationships between natural logarithms of above indexes and body weight. The body moisture and fat content, digestive and absorptive enzymes activities, and transaminase activities showed negative allometry against body weight of Jian carp which were partial reasons to explain fish growth rate decreasing.展开更多
Ammonia concentration(NH3)is a dominant source of environmental pollution in geese housing and profoundly affects the healthy growth of geese.Accurately forecasting NH3 and analyzing its change trends in geese houses ...Ammonia concentration(NH3)is a dominant source of environmental pollution in geese housing and profoundly affects the healthy growth of geese.Accurately forecasting NH3 and analyzing its change trends in geese houses is crucial for the survival of geese.A novel forecasting model was proposed by combining feature selector(CFS)and random forest(RF)to improve the prediction accuracy of NH3 in this study.The developed model integrated two modules.First,combining mutual information(MI)and relief-F,we propose that CFS quantify each feature’s importance values and eliminate the low-relation or unrelated features.Second,a random forest model was built using K-fold cross-validation grid search algorithm(CVGS)to obtain the RF hyperparameters to predict NH_(3).The simulation results show that the prediction accuracy was improved when feature selection after quantification based on the CFS was used.The mean square error(MSE),root mean square error(RMSE),and mean absolute percent error(MAPE)for the proposed model were 0.5072,0.6583,and 2.88%,respectively.The NH_(3) prediction model(CFS-CVGS-RF)based on Combined Feature Selector,cross-validation grid search algorithm(CVGS),and Random Forest(RF)exhibited the best prediction accuracy and generalization performance compared with other parallel forecasting models and is a suitable and useful tool for predicting NH3 in geese houses.The results of the research can provide a reference for the machine learning method to monitor the dynamic changes of ammonia in goose houses.展开更多
基金Project supported by the National Key Research and Development Program(2017YFC0211002).
文摘Cerium zirconium solid solution is a key washcoat material for automotive three-way catalysts(TWCs).However,improving the redox ability and high temperature thermal stability of cerium zirconium solid solution is still a challenge.In this paper,the cerium zirconium solid solution was prepared by a coprecipitation-hydrothermal method,and the effects of the ammonia concentration on their structures and redox properties were investigated.The results show that when the ammonia concentration is 0.8 mol/L,the aged sample(1100℃/10 h)of cerium zirconium solid solution has the highest specific surface area of 23.01 m^(2)/g.Additionally,the increase of ammonia concentration improves the uniformity of phase compositions and increases the oxygen vacancies.When the ammonia concentration reaches 0.4 mol/L,the cerium zirconium solid solution exhibits the best redox activity,with the lowest reduction temperature of 565℃.Therefore,increasing ammonia concentration in the hydrothermal treatment is beneficial to the thermal stability and redox performance of cerium zirconium solid solution.
基金financially supported by the National Department Public Benefit Research Foundation(Agriculture)of China(2010003020)
文摘The present study investigated the effect of body weight on body composition, digestive and absorptive capacity, transaminase activities in hepatopancreas and muscle, and plasma ammonia concentration of Jian carp(Cyprinus carpio var.Jian). A total of 750 Jian carps(18.0 ± 0.2 g) were randomly distributed into five groups with three replicates and fed the same diet for 56 days. Tissue and plasma samples were collected on days 14, 28,42, and 56. The results were used to develop a mathematical model for specific growth rate, body moisture and fat content, aspartate transaminase activity and alanine aminotransferase activity in hepatopancreas and muscle, plasma ammonia concentration, and trypsin, chymotrypsin, lipase, and amylase activities in hepatopancreas and intestine, activities of creatine kinase, Na^+/K^+-ATPase, alkaline phosphatase, and γ-glutamyl transpeptidase in intestine in Jian carp. There were linear relationships between natural logarithms of above indexes and body weight. The body moisture and fat content, digestive and absorptive enzymes activities, and transaminase activities showed negative allometry against body weight of Jian carp which were partial reasons to explain fish growth rate decreasing.
基金supported in part by the National Natural Science Foundation of China(Grants No.61871475,No.61471-131,No.61571444)in part by the special project of laboratory construction of Guangzhou Innovation Platform Construction Plan(Grant No.201905010006)+2 种基金Guangzhou Innovation Platform Construction Plan(Grant No.2017B0101260016)the foundation for High-level Talents in Higher Education of Guangdong Province(Grant No.2017GCZX00014,No.2016KZDXM0013,No.2017KTSCX094,No.2018LM2168)Beijing Natural Science Foundation under Grant 4182023.
文摘Ammonia concentration(NH3)is a dominant source of environmental pollution in geese housing and profoundly affects the healthy growth of geese.Accurately forecasting NH3 and analyzing its change trends in geese houses is crucial for the survival of geese.A novel forecasting model was proposed by combining feature selector(CFS)and random forest(RF)to improve the prediction accuracy of NH3 in this study.The developed model integrated two modules.First,combining mutual information(MI)and relief-F,we propose that CFS quantify each feature’s importance values and eliminate the low-relation or unrelated features.Second,a random forest model was built using K-fold cross-validation grid search algorithm(CVGS)to obtain the RF hyperparameters to predict NH_(3).The simulation results show that the prediction accuracy was improved when feature selection after quantification based on the CFS was used.The mean square error(MSE),root mean square error(RMSE),and mean absolute percent error(MAPE)for the proposed model were 0.5072,0.6583,and 2.88%,respectively.The NH_(3) prediction model(CFS-CVGS-RF)based on Combined Feature Selector,cross-validation grid search algorithm(CVGS),and Random Forest(RF)exhibited the best prediction accuracy and generalization performance compared with other parallel forecasting models and is a suitable and useful tool for predicting NH3 in geese houses.The results of the research can provide a reference for the machine learning method to monitor the dynamic changes of ammonia in goose houses.
