Most of the Lycium L. plants are medicinal plants, and L. barbarum in this genus is an important Chinese medicinal material. The United States is one of the largest countries in the world in conservation of plant germ...Most of the Lycium L. plants are medicinal plants, and L. barbarum in this genus is an important Chinese medicinal material. The United States is one of the largest countries in the world in conservation of plant germplasm resources and conservation types. The United States has collected 50 plant resources from 13 species and 1 variety of Lycium L. from all over the world. If we can introduce and utilize these plant resources, it is very important to Chinese wolfberry germplasm resources innovation and genetic improvement.展开更多
Tianjin Beijiang Power Plant, one of the first series of Circular Economy Demonstration Project in the country, successfully put its second unit into operation on November 30, 2009
After a thorough demonstration in Panshan Thermal Power Plant, the 500 MW super critical pressure unit simulator developed by the Simulation & Control Institute under the North China University of Electric Power w...After a thorough demonstration in Panshan Thermal Power Plant, the 500 MW super critical pressure unit simulator developed by the Simulation & Control Institute under the North China University of Electric Power was accepted by experts from the North China Electric Power Group Company on 3rd August 1996.展开更多
Phenological events for desert plants were recorded and rainfall and temperature data were gathered over a three-year time scale at a gravel plain in the eastern region of the United Arab Emirates. Variations of pheno...Phenological events for desert plants were recorded and rainfall and temperature data were gathered over a three-year time scale at a gravel plain in the eastern region of the United Arab Emirates. Variations of phenological periods were analyzed and correlations between phenological periods and climate factors were discussed. The study showed that the growth and flowering of therophytes were significantly correlated with air tem- perature. The timing and abundance of rainfall came to be another factor significantly correlated with the onset and duration of chamaephyte flowering as well as the duration of therophyte growth and flowering. The variation in rainfall did not affect the onset of flowering in phanerophytes. Peak growing seasons were from November to March and flowering from November to December （also February to March depending on the availability of rainfall）. Flowering in phanerophytes and chamaephytes occurs 4-6 weeks and in therophytes 4-8 weeks after rain, The results showed that variations in growth and phenology between species were correlated with environmental factors, such as temperature and rainfall or, maybe, differences in life form and photosynthetic pathways, each being adapted for utilizing a particular phase of the seasonally and yearly variable rainfall. The sequence of flowering for the species under study was more or less constant despite the difference in the amount of rainfall. The fruiting patterns of most of the species were also found parallel to their flowering patterns. Our results emphasized the need to study multiple species at many sites for the understanding and forecast of regional changes in phenology.展开更多
Nowadays, with regard to environmental issues, proper operation of wastewater treatment plants is of particular importance that in the case of inappropriate utilization, they will cause serious problems. Processes tha...Nowadays, with regard to environmental issues, proper operation of wastewater treatment plants is of particular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems and environmental engineers are dealing with them mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant, powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the multilayer perceptron (MLP) feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant located in Mahshahr—Iran that qualitative and quantitative characteristics of its units were used for training, calibration and evaluation of the neural model. Also, Principal Component Analysis technique was applied to modify and improve performance of generated models of neural networks. The results of this model showed good accuracy of the model in estimating qualitative pro- file of wastewater. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of output.展开更多
Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, p...Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. With regard to environmental issues, proper operation of wastewater treatment plants is of par- ticular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant (WWTP), powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the treatment plant was divided into two main subsystems including: Low TDS (Total Dissolved Solids) treatment unit and Biological unit (extended aeration). The multilayer perceptron feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant, located in Mahshahr—Iran that qualita- tive and quantitative characteristics of its units were used for training, calibration and validation of the neural model. Also, Principal Component Analysis (PCA) technique was applied to improve performance of generated models of neural networks. The results of L-TDS unit showed good accuracy of the models in estimating qualitative profile of wastewater but results of biological unit did not have sufficient accuracy to being used. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of outputs.展开更多
Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information syst...Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information system （GIS） technology, provides an efficient way to estimate crop acreage at the regional scale. Traditional sampling methods require that the sampling units should be independent of each other, but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units. In this study, using Dehui County in Jilin Province, China, as the study area, we used a thematic crop map derived from Systeme Probatoire d＇Observation de la Terre （SPOT-5） imagery, cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes, and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units. Moran＇s/, a global spatial autocorrelation index, was used to evaluate the spatial autocorrelation among the two crop acreages in this study. The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size, there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units （Moran＇s / varied from 0.49 to 0.89）, irrespective of the sampling unit size. When the sampling unit size was less than 3000 m, the stratification design that used crop planting intensity （CPI） as the stratification criterion, with a stratum number of 5 and a stratum interval of 20% decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum. Therefore, the traditional sampling methods can be used to estimate the two crop acreages. Compared with CPI, there was still a strong spatial correlation among the two crop acreages included in the sampling units belonging to each stratum when cultivated land fragmentation and ground slope were used as stratification criterion. As far as the selection of stratification criteria and sampling unit size is concerned, this study provides a basis for formulating a reasonable spatial sampling scheme to estimate crop acreage.展开更多
Electric power system is one of the most important and complex engineering in modern society, supplying main and general power for social production and social life. Meanwhile, since it is a productive system with bo...Electric power system is one of the most important and complex engineering in modern society, supplying main and general power for social production and social life. Meanwhile, since it is a productive system with both high input and output, it has an obvious economic significance to improve its operating efficiency. For an example, an unit is 10 GW scale, if its standard coal consumption can be decreased with 1 g/kW·h, it can save about 5 000 tons standard coal per year. It will be discussed mainly that how to establish optimization model and its numerical algorithm for operating management of the electric power system. The idea on establishing optimization model is how to dispatch work state of units or power plants, so that total cost of fuel consumption for generation is reduced to the minimum. Here the dispatch is to decide which unit or plant to operate, which unit or plant to stop running, how much power should be generated for those operating units or plants at each given time interval.展开更多
Combined cycle plants (CCs) are broadly used all over the world. The inclusion of CCs into the optimal resource scheduling causes difficulties because they can be operated in different operating configuration modes ba...Combined cycle plants (CCs) are broadly used all over the world. The inclusion of CCs into the optimal resource scheduling causes difficulties because they can be operated in different operating configuration modes based on the number of combustion and steam turbines. In this paper a model CCs based on a mixed integer linear programming approach to be included into an optimal short term resource optimization problem is presented. The proposed method allows modeling of CCs in different modes of operation taking into account the non convex operating costs for the different combined cycle mode of operation.展开更多
This paper presents the data on operation reliability indices and relevant analyses toward China's conventional power generating units in 2009.The units brought into the statistical analysis include 100-MW or abov...This paper presents the data on operation reliability indices and relevant analyses toward China's conventional power generating units in 2009.The units brought into the statistical analysis include 100-MW or above thermal generating units,40-MW or above hydro generating units,and all nuclear generating units.The reliability indices embodied include utilization hours,times and hours of scheduled outages,times and hours of unscheduled outages,equivalent forced outage rate and equivalent availability factor.展开更多
基金Supported by the Science and Technology Innovation Guide Program of Ningxia Academy of Agriculture and Foresty Sciences(NKYJ-17-11)
文摘Most of the Lycium L. plants are medicinal plants, and L. barbarum in this genus is an important Chinese medicinal material. The United States is one of the largest countries in the world in conservation of plant germplasm resources and conservation types. The United States has collected 50 plant resources from 13 species and 1 variety of Lycium L. from all over the world. If we can introduce and utilize these plant resources, it is very important to Chinese wolfberry germplasm resources innovation and genetic improvement.
文摘Tianjin Beijiang Power Plant, one of the first series of Circular Economy Demonstration Project in the country, successfully put its second unit into operation on November 30, 2009
文摘After a thorough demonstration in Panshan Thermal Power Plant, the 500 MW super critical pressure unit simulator developed by the Simulation & Control Institute under the North China University of Electric Power was accepted by experts from the North China Electric Power Group Company on 3rd August 1996.
文摘Phenological events for desert plants were recorded and rainfall and temperature data were gathered over a three-year time scale at a gravel plain in the eastern region of the United Arab Emirates. Variations of phenological periods were analyzed and correlations between phenological periods and climate factors were discussed. The study showed that the growth and flowering of therophytes were significantly correlated with air tem- perature. The timing and abundance of rainfall came to be another factor significantly correlated with the onset and duration of chamaephyte flowering as well as the duration of therophyte growth and flowering. The variation in rainfall did not affect the onset of flowering in phanerophytes. Peak growing seasons were from November to March and flowering from November to December （also February to March depending on the availability of rainfall）. Flowering in phanerophytes and chamaephytes occurs 4-6 weeks and in therophytes 4-8 weeks after rain, The results showed that variations in growth and phenology between species were correlated with environmental factors, such as temperature and rainfall or, maybe, differences in life form and photosynthetic pathways, each being adapted for utilizing a particular phase of the seasonally and yearly variable rainfall. The sequence of flowering for the species under study was more or less constant despite the difference in the amount of rainfall. The fruiting patterns of most of the species were also found parallel to their flowering patterns. Our results emphasized the need to study multiple species at many sites for the understanding and forecast of regional changes in phenology.
文摘Nowadays, with regard to environmental issues, proper operation of wastewater treatment plants is of particular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems and environmental engineers are dealing with them mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant, powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the multilayer perceptron (MLP) feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant located in Mahshahr—Iran that qualitative and quantitative characteristics of its units were used for training, calibration and evaluation of the neural model. Also, Principal Component Analysis technique was applied to modify and improve performance of generated models of neural networks. The results of this model showed good accuracy of the model in estimating qualitative pro- file of wastewater. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of output.
文摘Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. With regard to environmental issues, proper operation of wastewater treatment plants is of par- ticular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant (WWTP), powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the treatment plant was divided into two main subsystems including: Low TDS (Total Dissolved Solids) treatment unit and Biological unit (extended aeration). The multilayer perceptron feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant, located in Mahshahr—Iran that qualita- tive and quantitative characteristics of its units were used for training, calibration and validation of the neural model. Also, Principal Component Analysis (PCA) technique was applied to improve performance of generated models of neural networks. The results of L-TDS unit showed good accuracy of the models in estimating qualitative profile of wastewater but results of biological unit did not have sufficient accuracy to being used. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the standard amount of outputs.
基金financially supported by the National Natural Science Foundation of China (41471365,41531179)
文摘Information on crop acreage is important for formulating national food polices and economic planning. Spatial sampling, a combination of traditional sampling methods and remote sensing and geographic information system （GIS） technology, provides an efficient way to estimate crop acreage at the regional scale. Traditional sampling methods require that the sampling units should be independent of each other, but in practice there is often spatial autocorrelation among crop acreage contained in the sampling units. In this study, using Dehui County in Jilin Province, China, as the study area, we used a thematic crop map derived from Systeme Probatoire d＇Observation de la Terre （SPOT-5） imagery, cultivated land plots and digital elevation model data to explore the spatial autocorrelation characteristics among maize and rice acreage included in sampling units of different sizes, and analyzed the effects of different stratification criteria on the level of spatial autocorrelation of the two crop acreages within the sampling units. Moran＇s/, a global spatial autocorrelation index, was used to evaluate the spatial autocorrelation among the two crop acreages in this study. The results showed that although the spatial autocorrelation level among maize and rice acreages within the sampling units generally decreased with increasing sampling unit size, there was still a significant spatial autocorrelation among the two crop acreages included in the sampling units （Moran＇s / varied from 0.49 to 0.89）, irrespective of the sampling unit size. When the sampling unit size was less than 3000 m, the stratification design that used crop planting intensity （CPI） as the stratification criterion, with a stratum number of 5 and a stratum interval of 20% decreased the spatial autocorrelation level to almost zero for the maize and rice area included in sampling units within each stratum. Therefore, the traditional sampling methods can be used to estimate the two crop acreages. Compared with CPI, there was still a strong spatial correlation among the two crop acreages included in the sampling units belonging to each stratum when cultivated land fragmentation and ground slope were used as stratification criterion. As far as the selection of stratification criteria and sampling unit size is concerned, this study provides a basis for formulating a reasonable spatial sampling scheme to estimate crop acreage.
文摘Electric power system is one of the most important and complex engineering in modern society, supplying main and general power for social production and social life. Meanwhile, since it is a productive system with both high input and output, it has an obvious economic significance to improve its operating efficiency. For an example, an unit is 10 GW scale, if its standard coal consumption can be decreased with 1 g/kW·h, it can save about 5 000 tons standard coal per year. It will be discussed mainly that how to establish optimization model and its numerical algorithm for operating management of the electric power system. The idea on establishing optimization model is how to dispatch work state of units or power plants, so that total cost of fuel consumption for generation is reduced to the minimum. Here the dispatch is to decide which unit or plant to operate, which unit or plant to stop running, how much power should be generated for those operating units or plants at each given time interval.
文摘Combined cycle plants (CCs) are broadly used all over the world. The inclusion of CCs into the optimal resource scheduling causes difficulties because they can be operated in different operating configuration modes based on the number of combustion and steam turbines. In this paper a model CCs based on a mixed integer linear programming approach to be included into an optimal short term resource optimization problem is presented. The proposed method allows modeling of CCs in different modes of operation taking into account the non convex operating costs for the different combined cycle mode of operation.
文摘This paper presents the data on operation reliability indices and relevant analyses toward China's conventional power generating units in 2009.The units brought into the statistical analysis include 100-MW or above thermal generating units,40-MW or above hydro generating units,and all nuclear generating units.The reliability indices embodied include utilization hours,times and hours of scheduled outages,times and hours of unscheduled outages,equivalent forced outage rate and equivalent availability factor.
