Genus Pseudoalteromonas belongs to Family Pseudoalteromonadaceae in Gammaproteobacteria. A cold-adapted gram-negative bacterium, hydrocarbon-degrading Pseudoalteromonas sp. NJ289, was isolated from sea-ice of the Anta...Genus Pseudoalteromonas belongs to Family Pseudoalteromonadaceae in Gammaproteobacteria. A cold-adapted gram-negative bacterium, hydrocarbon-degrading Pseudoalteromonas sp. NJ289, was isolated from sea-ice of the Antarctica region, and sequenced the whole genome through the next generation sequencing platform. The assembly yielded three contigs representing two chromosomes and one plasmid with the sizes of 3.2 Mb, 636 kb and 1.8 kb, respectively. The G＋C contents of genome were 40.83% and included 3 589 ORFs. Functional annotation indicated some potential roles in enzymatic activity and environmental adaptability. This study may help for understanding the population diverse, evolutionary ecology and the microbial interaction.展开更多
In this paper, the authors consider an adaptive recursive algorithm by selecting an adaptive sequence for computing M-estimators in multivariate linear regression models. Its asymptotic property is investigated. The r...In this paper, the authors consider an adaptive recursive algorithm by selecting an adaptive sequence for computing M-estimators in multivariate linear regression models. Its asymptotic property is investigated. The recursive algorithm given by Miao and Wu （1996） is modified accordingly. Simu- lation studies of the Mgorithm is also provided. In addition, the Newton-Raphson iterative algorithm is considered for the purpose of comparison.展开更多
The variable-structure multiple-model（VSMM）approach,one of the multiple-model（MM）methods,is a popular and effective approach in handling problems with mode uncertainties.The model sequence set adaptation（MSA）is ...The variable-structure multiple-model（VSMM）approach,one of the multiple-model（MM）methods,is a popular and effective approach in handling problems with mode uncertainties.The model sequence set adaptation（MSA）is the key to design a better VSMM.However,MSA methods in the literature have big room to improve both theoretically and practically.To this end,we propose a feedback structure based entropy approach that could fnd the model sequence sets with the smallest size under certain conditions.The fltered data are fed back in real time and can be used by the minimum entropy（ME）based VSMM algorithms,i.e.,MEVSMM.Firstly,the full Markov chains are used to achieve optimal solutions.Secondly,the myopic method together with particle flter（PF）and the challenge match algorithm are also used to achieve sub-optimal solutions,a trade-off between practicability and optimality.The numerical results show that the proposed algorithm provides not only refned model sets but also a good robustness margin and very high accuracy.展开更多
基金The National Natural Science Foundation of China under contract Nos 31200097,41576187,U1406402-5 and31202024the Basic Scientific Fund for National Public Research Institutes of China under contract Nos 2013G33 and 2015G10
文摘Genus Pseudoalteromonas belongs to Family Pseudoalteromonadaceae in Gammaproteobacteria. A cold-adapted gram-negative bacterium, hydrocarbon-degrading Pseudoalteromonas sp. NJ289, was isolated from sea-ice of the Antarctica region, and sequenced the whole genome through the next generation sequencing platform. The assembly yielded three contigs representing two chromosomes and one plasmid with the sizes of 3.2 Mb, 636 kb and 1.8 kb, respectively. The G＋C contents of genome were 40.83% and included 3 589 ORFs. Functional annotation indicated some potential roles in enzymatic activity and environmental adaptability. This study may help for understanding the population diverse, evolutionary ecology and the microbial interaction.
基金supported by the National Natural Science Foundation for Young Scientists of China under Grant No.11101397the Natural Sciences and Engineering Research Council of Canada
文摘In this paper, the authors consider an adaptive recursive algorithm by selecting an adaptive sequence for computing M-estimators in multivariate linear regression models. Its asymptotic property is investigated. The recursive algorithm given by Miao and Wu （1996） is modified accordingly. Simu- lation studies of the Mgorithm is also provided. In addition, the Newton-Raphson iterative algorithm is considered for the purpose of comparison.
基金supported in part by National Basic Research Program of China(No.2012CB821200)in part by the National Natural Science Foundation of China(No.61174024)
文摘The variable-structure multiple-model（VSMM）approach,one of the multiple-model（MM）methods,is a popular and effective approach in handling problems with mode uncertainties.The model sequence set adaptation（MSA）is the key to design a better VSMM.However,MSA methods in the literature have big room to improve both theoretically and practically.To this end,we propose a feedback structure based entropy approach that could fnd the model sequence sets with the smallest size under certain conditions.The fltered data are fed back in real time and can be used by the minimum entropy（ME）based VSMM algorithms,i.e.,MEVSMM.Firstly,the full Markov chains are used to achieve optimal solutions.Secondly,the myopic method together with particle flter（PF）and the challenge match algorithm are also used to achieve sub-optimal solutions,a trade-off between practicability and optimality.The numerical results show that the proposed algorithm provides not only refned model sets but also a good robustness margin and very high accuracy.
