Restoration of mining soils is important to the vegetation and environment.This study aimed to explore the variations in soil nutrient contents,microbial abundance,and biomass under different gradients of substrate am...Restoration of mining soils is important to the vegetation and environment.This study aimed to explore the variations in soil nutrient contents,microbial abundance,and biomass under different gradients of substrate amendments in mining soils to select effective measures.Soil samples were collected from the Bayan Obo mining region in Inner Mongolia Autonomous Region,China.Contents of soil organic matter(SOM),available nitrogen(AN),available phosphorus(AP),available potassium(AK),microbial biomass carbon/microbial biomass nitrogen(MBC/MBN)ratio,biomass,and bacteria,fungi,and actinomycetes abundance were assessed in Agropyron cristatum L.Gaertn.,Elymus dahuricus Turcz.,and Medicago sativa L.soils with artificial zeolite(AZ)and microbial fertilizer(MF)applied at T0(0 g/kg),T1(5 g/kg),T2(10 g/kg),and T3(20 g/kg).Redundancy analysis(RDA)and technique for order preference by similarity to ideal solution(TOPSIS)were used to identify the main factors controlling the variation of biomass.Results showed that chemical indices and microbial content of restored soils were far greater than those of control.The application of AZ significantly increases SOM,AN,and AP by 20.27%,23.61%,and 40.43%,respectively.AZ significantly increased bacteria,fungi,and actinomycetes abundance by 0.63,3.12,and 1.93 times of control,respectively.RDA indicated that AN,MBC/MBN ratio,and SOM were dominant predictors for biomass across samples with AZ application,explaining 87.6%of the biomass variance.SOM,MBC/MBN ratio,and AK were dominant predictors with MF application,explaining 82.9%of the biomass variance.TOPSIS indicated that T2 was the best dosage and the three plant species could all be used to repair mining soils.AZ and MF application at T2 concentration in the mining soils with M.sativa was found to be the most appropriate measure.展开更多
The emergence of power dispatching automation systems has greatly improved the efficiency of power industry operations and promoted the rapid development of the power industry.However,with the convergence and increase...The emergence of power dispatching automation systems has greatly improved the efficiency of power industry operations and promoted the rapid development of the power industry.However,with the convergence and increase in power data flow,the data dispatching network and the main station dispatching automation system have encountered substantial pressure.Therefore,themethod of online data resolution and rapid problemidentification of dispatching automation systems has been widely investigated.In this paper,we performa comprehensive review of automated dispatching of massive dispatching data from the perspective of intelligent identification,discuss unresolved research issues and outline future directions in this area.In particular,we divide intelligent identification over power big data into data acquisition and storage processes,anomaly detection and fault discrimination processes,and fault tracing for dispatching operations during communication.A detailed survey of the solutions to the challenges in intelligent identification over power big data is then presented.Moreover,opportunities and future directions are outlined.展开更多
基金supported by the Beijing Forestry University(BJFU),China。
文摘Restoration of mining soils is important to the vegetation and environment.This study aimed to explore the variations in soil nutrient contents,microbial abundance,and biomass under different gradients of substrate amendments in mining soils to select effective measures.Soil samples were collected from the Bayan Obo mining region in Inner Mongolia Autonomous Region,China.Contents of soil organic matter(SOM),available nitrogen(AN),available phosphorus(AP),available potassium(AK),microbial biomass carbon/microbial biomass nitrogen(MBC/MBN)ratio,biomass,and bacteria,fungi,and actinomycetes abundance were assessed in Agropyron cristatum L.Gaertn.,Elymus dahuricus Turcz.,and Medicago sativa L.soils with artificial zeolite(AZ)and microbial fertilizer(MF)applied at T0(0 g/kg),T1(5 g/kg),T2(10 g/kg),and T3(20 g/kg).Redundancy analysis(RDA)and technique for order preference by similarity to ideal solution(TOPSIS)were used to identify the main factors controlling the variation of biomass.Results showed that chemical indices and microbial content of restored soils were far greater than those of control.The application of AZ significantly increases SOM,AN,and AP by 20.27%,23.61%,and 40.43%,respectively.AZ significantly increased bacteria,fungi,and actinomycetes abundance by 0.63,3.12,and 1.93 times of control,respectively.RDA indicated that AN,MBC/MBN ratio,and SOM were dominant predictors for biomass across samples with AZ application,explaining 87.6%of the biomass variance.SOM,MBC/MBN ratio,and AK were dominant predictors with MF application,explaining 82.9%of the biomass variance.TOPSIS indicated that T2 was the best dosage and the three plant species could all be used to repair mining soils.AZ and MF application at T2 concentration in the mining soils with M.sativa was found to be the most appropriate measure.
基金supported by the Science and technology projects of China National Petroleum Corporation:“Research on key technologies of continuous wave transmission and power supply system based on integrated LWD system” (2021DQ0409)the Science and technology projects of China National Petroleum Corporation:“Development of high temperature and high-pressure imaging logging while drilling tool” (2021DJ3902)the Science and technology projects of CNPC Oilfield Service Company:“Development of intelligent drilling systems” (2022T-005-001).
文摘The emergence of power dispatching automation systems has greatly improved the efficiency of power industry operations and promoted the rapid development of the power industry.However,with the convergence and increase in power data flow,the data dispatching network and the main station dispatching automation system have encountered substantial pressure.Therefore,themethod of online data resolution and rapid problemidentification of dispatching automation systems has been widely investigated.In this paper,we performa comprehensive review of automated dispatching of massive dispatching data from the perspective of intelligent identification,discuss unresolved research issues and outline future directions in this area.In particular,we divide intelligent identification over power big data into data acquisition and storage processes,anomaly detection and fault discrimination processes,and fault tracing for dispatching operations during communication.A detailed survey of the solutions to the challenges in intelligent identification over power big data is then presented.Moreover,opportunities and future directions are outlined.
