Sequence analysis and distribution of an IS3-like insertion element isolated from Salmonella enteritidis

The nucleotide sequence of a 3 kb region immediately upstream of the sef operon of Salmonella enteritidis was determined. A 1230 base pair insertion sequence which shared sequence identity (> 75%) with members of the IS3 family was revealed. This element, designated IS1230, had almost identical (90% identity) terminal inverted repeats to Escherichia coli IS3 but unlike other IS3-like sequences lacked the two characteristic open reading frames which encode the putative transposase. S. enteritidis possessed only one copy of this insertion sequence although Southern hybridisation analysis of restriction digests of genomic DNA revealed another fragment located in a region different from the sef operon which hybridised weakly which suggested the presence of an IS1230 homologue. The distribution of IS1230 and IS1230-like elements was shown to be widespread amongst salmonellas and the patterns of restriction fragments which hybridised differed significantly between Salmonella serotypes and it is suggested that IS1230 has potential for development as a differential diagnostic tool.

Weakly supervised joint sentiment-topic detection from text

Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework called joint sentiment-topic (JST) model based on latent Dirichlet allocation (LDA), which detects sentiment and topic simultaneously from text. A reparameterized version of the JST model called Reverse-JST, obtained by reversing the sequence of sentiment and topic generation in the modeling process, is also studied. Although JST is equivalent to Reverse-JST without a hierarchical prior, extensive experiments show that when sentiment priors are added, JST performs consistently better than Reverse-JST. Besides, unlike supervised approaches to sentiment classification which often fail to produce satisfactory performance when shifting to other domains, the weakly supervised nature of JST makes it highly portable to other domains. This is verified by the experimental results on data sets from five different domains where the JST model even outperforms existing semi-supervised approaches in some of the data sets despite using no labeled documents. Moreover, the topics and topic sentiment detected by JST are indeed coherent and informative. We hypothesize that the JST model can readily meet the demand of large-scale sentiment analysis from the web in an open-ended fashion.

Leak identification in saturated unsteady flow via a Cauchy problem

This work is an initial study of a numerical method for identifying multiple leak zones in saturated unsteady flow. Using the conventional saturated groundwater flow equation, the leak identification problem is modelled as a Cauchy problem for the heat equation and the aim is to find the regions on the boundary of the solution domain where the solution vanishes, since leak zones correspond to null pressure values. This problem is ill-posed and to reconstruct the solution in a stable way, we therefore modify and employ an iterative regularizing method proposed in [1] and [2]. In this method, mixed well-posed problems obtained by changing the boundary conditions are solved for the heat operator as well as for its adjoint, to get a sequence of approximations to the original Cauchy problem. The mixed problems are solved using a Finite element method (FEM), and the numerical results indicate that the leak zones can be identified with the proposed method.