[ Objective] The aim was to use response surface methodology to determine optimum conditions for extraction of polysaccharides from Tegillarca granosa. [ Method] Response surface methodology with three-factors and thr...[ Objective] The aim was to use response surface methodology to determine optimum conditions for extraction of polysaccharides from Tegillarca granosa. [ Method] Response surface methodology with three-factors and throe-levels was carried out for optimizing the extraction process of polysacchafides from Tegillarca granosa. A central composite des（gn including independent variables, such as extraction temperature （A）, extraction time （B）, and ethanol concentration （C） was obtained through Box-Benhnken central combination design. Selected response which evaluates the extraction process was polysacchadde yield. [ Result] The independent variable with the largest effect on response was ethanol concentration （C）. The optimum extraction conditions were found to be extraction temperature 69.6℃, extraction time 6.2 h, and ethanol concen- tration of 78% （V/V）, respectively. Under these conditions, the extraction efficiency of polysaccharide can increase to 1. 635%. [ Coaclusioa] Study on the extraction of polysaccharides from Tegillarca granosa could provide certain theoretical direction for extracting polysaccharides from Tegillarca granosa on a large scale.展开更多
The scheduling of earth observation satellites(EOSs)data transmission is a complex combinatorial optimization problem. Current researches mainly deal with this problem on the assumption that the data transmission mode...The scheduling of earth observation satellites(EOSs)data transmission is a complex combinatorial optimization problem. Current researches mainly deal with this problem on the assumption that the data transmission mode is fixed, either playback or real-time transmission. Considering the characteristic of the problem, a multi-satellite real-time and playback data transmission scheduling model is established and a novel algorithm based on quantum discrete particle swarm optimization(QDPSO)is proposed. Furthermore, we design the longest compatible transmission chain mutation operator to enhance the performance of the algorithm. Finally, some experiments are implemented to validate correctness and practicability of the proposed algorithm.展开更多
基金Supported by Key Scientific Research Program of Wannan MedicalCollege ( WK2012Z208)
文摘[ Objective] The aim was to use response surface methodology to determine optimum conditions for extraction of polysaccharides from Tegillarca granosa. [ Method] Response surface methodology with three-factors and throe-levels was carried out for optimizing the extraction process of polysacchafides from Tegillarca granosa. A central composite des（gn including independent variables, such as extraction temperature （A）, extraction time （B）, and ethanol concentration （C） was obtained through Box-Benhnken central combination design. Selected response which evaluates the extraction process was polysacchadde yield. [ Result] The independent variable with the largest effect on response was ethanol concentration （C）. The optimum extraction conditions were found to be extraction temperature 69.6℃, extraction time 6.2 h, and ethanol concen- tration of 78% （V/V）, respectively. Under these conditions, the extraction efficiency of polysaccharide can increase to 1. 635%. [ Coaclusioa] Study on the extraction of polysaccharides from Tegillarca granosa could provide certain theoretical direction for extracting polysaccharides from Tegillarca granosa on a large scale.
基金supported by the National Natural Science Foundation of China(6110118461174159)
文摘The scheduling of earth observation satellites(EOSs)data transmission is a complex combinatorial optimization problem. Current researches mainly deal with this problem on the assumption that the data transmission mode is fixed, either playback or real-time transmission. Considering the characteristic of the problem, a multi-satellite real-time and playback data transmission scheduling model is established and a novel algorithm based on quantum discrete particle swarm optimization(QDPSO)is proposed. Furthermore, we design the longest compatible transmission chain mutation operator to enhance the performance of the algorithm. Finally, some experiments are implemented to validate correctness and practicability of the proposed algorithm.
