In order to reveal the characteristics and climatic controls on the stable isotopic composition of precipitation over Arid Northwestern China, eight stations have been selected from Chinese Network of Isotopes in Prec...In order to reveal the characteristics and climatic controls on the stable isotopic composition of precipitation over Arid Northwestern China, eight stations have been selected from Chinese Network of Isotopes in Precipitation(CHNIP).During the year 2005 and 2006, monthly precipitation samples have been collected and analyzed for the composition of δD and δ18O.The established local meteoric water line δD=7.42δ18O+1.38, based on the 95 obtained monthly composite samples, could be treated as isotopic input function across the region.The deviations of slope and intercept from the Global Meteoric Water Line indicated the specific regional meteorological conditions.The monthly δ18O values were characterized by a positive correlation with surface air temperature(δ18O(‰) =0.33 T(℃)-13.12).The amount effect visualized during summer period(δ18O(‰) =-0.04P(mm)-3.44) though not appeared at a whole yearly-scale.Spatial distributions of δ18O have properly portrayed the atmospheric circulation background in each month over Arid Northwestern China.The quan-titative simulation of δ18O, which involved a Rayleigh fractionation and a kinetic fractionation, demonstrated that the latter one was the dominating function of condensation of raindrops.Furthermore, the raindrop suffered a re-evaporation during falling processes, and the precipitation vapor might have been mixed with a quantity of local recycled water vapor.Multiple linear regression equations and a δ18O-T relation have been gained by using meteorological parameters and δ18O data to evaluate physical controls on the long-term data.The established δ18O-T relation, which has been based on the present-day precipitation, could be considered as a first step of quantitatively reconstructing the historical environmental climate.展开更多
In this study, Saccharomyces cerevisiae (baker's yeast) was produced in a fed-batch bioreactor at the optimal dissolved oxygen concentration (DOC) and growth medium temperature. However, it is very difficult to co...In this study, Saccharomyces cerevisiae (baker's yeast) was produced in a fed-batch bioreactor at the optimal dissolved oxygen concentration (DOC) and growth medium temperature. However, it is very difficult to control the DOC using conventional controllers because of the poorly understood and constantly changing dynamics of the bioprocess. A generalized predictive controller (GPC) based on a nonlinear autoregressive integrated moving average exogenous (NARIMAX) model is presented to stabilize the DOC by manipulation of air flow rate. The NARIMAX model is built by an improved recursive least-squares support vector machine, which is trained by an in-place computation scheme and avoids the computation of the inverse of a large matrix and memory reallocation. The proposed nonlinear GPC algorithm requires little preliminary knowledge of the fermentation process, and directly obtains the nonlinear model in matrix form by using iterative multiple modeling instead of linearization at each sampling period. By application of an on-line bioreactor control, experimental results demonstrate the robustness, effectiveness and advantages of the new controller.展开更多
基金National Natural Science Foundation of China,No.40830636 No.40671034Foundation of Isotopes in Precipitation of Chinese Ecosystem Research Network
文摘In order to reveal the characteristics and climatic controls on the stable isotopic composition of precipitation over Arid Northwestern China, eight stations have been selected from Chinese Network of Isotopes in Precipitation(CHNIP).During the year 2005 and 2006, monthly precipitation samples have been collected and analyzed for the composition of δD and δ18O.The established local meteoric water line δD=7.42δ18O+1.38, based on the 95 obtained monthly composite samples, could be treated as isotopic input function across the region.The deviations of slope and intercept from the Global Meteoric Water Line indicated the specific regional meteorological conditions.The monthly δ18O values were characterized by a positive correlation with surface air temperature(δ18O(‰) =0.33 T(℃)-13.12).The amount effect visualized during summer period(δ18O(‰) =-0.04P(mm)-3.44) though not appeared at a whole yearly-scale.Spatial distributions of δ18O have properly portrayed the atmospheric circulation background in each month over Arid Northwestern China.The quan-titative simulation of δ18O, which involved a Rayleigh fractionation and a kinetic fractionation, demonstrated that the latter one was the dominating function of condensation of raindrops.Furthermore, the raindrop suffered a re-evaporation during falling processes, and the precipitation vapor might have been mixed with a quantity of local recycled water vapor.Multiple linear regression equations and a δ18O-T relation have been gained by using meteorological parameters and δ18O data to evaluate physical controls on the long-term data.The established δ18O-T relation, which has been based on the present-day precipitation, could be considered as a first step of quantitatively reconstructing the historical environmental climate.
基金Supported by the National Natural Science Foundation of China (20476007, 20676013)
文摘In this study, Saccharomyces cerevisiae (baker's yeast) was produced in a fed-batch bioreactor at the optimal dissolved oxygen concentration (DOC) and growth medium temperature. However, it is very difficult to control the DOC using conventional controllers because of the poorly understood and constantly changing dynamics of the bioprocess. A generalized predictive controller (GPC) based on a nonlinear autoregressive integrated moving average exogenous (NARIMAX) model is presented to stabilize the DOC by manipulation of air flow rate. The NARIMAX model is built by an improved recursive least-squares support vector machine, which is trained by an in-place computation scheme and avoids the computation of the inverse of a large matrix and memory reallocation. The proposed nonlinear GPC algorithm requires little preliminary knowledge of the fermentation process, and directly obtains the nonlinear model in matrix form by using iterative multiple modeling instead of linearization at each sampling period. By application of an on-line bioreactor control, experimental results demonstrate the robustness, effectiveness and advantages of the new controller.
