As the influence of feeding type on microbial community structure and functions in host is poorly understood, this study was conducted to investigate the variation of the gastric microflora in a variety of yellow catt...As the influence of feeding type on microbial community structure and functions in host is poorly understood, this study was conducted to investigate the variation of the gastric microflora in a variety of yellow cattle fed diets.For 2 years,the experimental group was fed with Miscanthus(Miscanthus sinensis,M.sinensis)only and the control group was fed with total mixed diets.Samples were collected from the rumen,reticulum,omasum,and abomasum.Total microbial DNA was extracted using in situ lysis and pulsed field gel electrophoresis (PFGE).The bacterial 16S rDNA and the fun-gal 18S rDNA were amplified using touchdown PCR,and the denaturing gradient gel electrophoresis (DGGE)profiles were analyzed.Common and unique bands between the experimental and control groups from the rumen were sequenced and compared with GenBank sequences.Results revealed a significant difference in bacterial community structure be-tween the experimental and control groups.An unweighted pair-group method with arithmetic mean (UPGMA)revealed that the 2 groups were clustered in 2 separate branches and had a similarity of only 0.35.Moreover,the Shannon diver-sity index and band abundance were significantly lower in the experimental group than in the control group.The fungal DGGE profile bands showed no significant change.The similarity in the four samples between the experimental and con-trol groups ranged from 0.43 to 0.68.The difference in band abundance and density between the experimental and con-trol groups ranged from 0.0027 to 0.5999.In terms of sequencing results,the bacterial sequences were similar to those of uncultured bacteria in the database,and some fungal sequences were similar to those of known species.In conclu-sion,high cellulose M.sinensis has important influence on microorganisms in the stomach of cattle,which influenced the microbial community structure,especially for the bacterial community.展开更多
A newly proposed distributed dynamic state estimation algorithm based on the maximum a posteriori(MAP) technique is generalised and studied for power systems. The system model involves linear time-varying load dynamic...A newly proposed distributed dynamic state estimation algorithm based on the maximum a posteriori(MAP) technique is generalised and studied for power systems. The system model involves linear time-varying load dynamics and nonlinear measurements. The main contribution of this paper is to compare the performance and feasibility of this distributed algorithm with several existing distributed state estimation algorithms in the literature. Simulations are tested on the IEEE 39-bus and 118-bus systems under various operating conditions. The results show that this distributed algorithm performs better than distributed quasi-steady state estimation algorithms which do not use the load dynamic model. The results also show that the performance of this distributed method is very close to that by the centralized state estimation method. The merits of this algorithm over the centralized method lie in its low computational complexity and low communication load. Hence, the analysis supports the efficiency and benefits of the distributed algorithm in applications to large-scale power systems.展开更多
基金Supported by National Natural Science Foundation of China(No.31072141)Hunan Provincial Natural Science Foundation of China(No.13JJ3054)The Construct Program of the Key Discipline of Basic Medicine in Hunan Province
文摘As the influence of feeding type on microbial community structure and functions in host is poorly understood, this study was conducted to investigate the variation of the gastric microflora in a variety of yellow cattle fed diets.For 2 years,the experimental group was fed with Miscanthus(Miscanthus sinensis,M.sinensis)only and the control group was fed with total mixed diets.Samples were collected from the rumen,reticulum,omasum,and abomasum.Total microbial DNA was extracted using in situ lysis and pulsed field gel electrophoresis (PFGE).The bacterial 16S rDNA and the fun-gal 18S rDNA were amplified using touchdown PCR,and the denaturing gradient gel electrophoresis (DGGE)profiles were analyzed.Common and unique bands between the experimental and control groups from the rumen were sequenced and compared with GenBank sequences.Results revealed a significant difference in bacterial community structure be-tween the experimental and control groups.An unweighted pair-group method with arithmetic mean (UPGMA)revealed that the 2 groups were clustered in 2 separate branches and had a similarity of only 0.35.Moreover,the Shannon diver-sity index and band abundance were significantly lower in the experimental group than in the control group.The fungal DGGE profile bands showed no significant change.The similarity in the four samples between the experimental and con-trol groups ranged from 0.43 to 0.68.The difference in band abundance and density between the experimental and con-trol groups ranged from 0.0027 to 0.5999.In terms of sequencing results,the bacterial sequences were similar to those of uncultured bacteria in the database,and some fungal sequences were similar to those of known species.In conclu-sion,high cellulose M.sinensis has important influence on microorganisms in the stomach of cattle,which influenced the microbial community structure,especially for the bacterial community.
基金supported by the National Natural Science Foundation of China under Grant Nos.61120106011,61573221,61633014National Key Technology Support Program of China under Grant No.2014BAF07B03
文摘A newly proposed distributed dynamic state estimation algorithm based on the maximum a posteriori(MAP) technique is generalised and studied for power systems. The system model involves linear time-varying load dynamics and nonlinear measurements. The main contribution of this paper is to compare the performance and feasibility of this distributed algorithm with several existing distributed state estimation algorithms in the literature. Simulations are tested on the IEEE 39-bus and 118-bus systems under various operating conditions. The results show that this distributed algorithm performs better than distributed quasi-steady state estimation algorithms which do not use the load dynamic model. The results also show that the performance of this distributed method is very close to that by the centralized state estimation method. The merits of this algorithm over the centralized method lie in its low computational complexity and low communication load. Hence, the analysis supports the efficiency and benefits of the distributed algorithm in applications to large-scale power systems.
