Mitogenomes provide new insights into the evolutionary history of Prodiamesinae (Diptera: Chironomidae)

Evolutionary analysis of Prodiamesinae has long been impeded by lack of information, and its phylogenetic relationship with Orthocladiinae remains questionable. Here, ten complete mitochondrial genomes (mitogenomes) of Orthocladiinae sensu lato were newly sequenced, including three Prodiamesinae species and seven Orthocladiinae species. Coupled with published mitogenomes, a total of 12 mitogenomes of Orthocladiinae sensu lato were selected for a comparative mitogenomic analysis and phylogenetic reconstruction. Mitogenomes of Orthocladiinae sensu lato are conserved in structure, and all genes arrange the same gene order as the ancestral insect mitogenome. Nucleotide composition is highly biased, and the control region displayed the highest A + T content. All protein-coding genes are under purifying selection, and the ATP8 evolves at the fastest rate. In addition, the mitogenomes of Orthocladiinae sensu lato are highly conserved, and they are practically useful for phylogenetic inference, suggesting a re-classification of Orthocladiinae by sinking Prodiamesinae as a subgroup of Orthocladiinae.     

Phrasal Paraphrase Based Question Reformulation for Archived Question Retrieval

Lexical gap in cQA search, resulted by the variability of languages, has been recognized as an important and widespread phenomenon. To address the problem, this paper presents a question reformulation scheme to enhance the question retrieval model by fully exploring the intelligence of paraphrase in phrase-level. It compensates for the existing paraphrasing research in a suitable granularity, which either falls into fine-grained lexical-level or coarse-grained sentence-level. Given a question in natural language, our scheme first detects the involved key-phrases by jointly integrating the corpus-dependent knowledge and question-aware cues. Next, it automatically extracts the paraphrases for each identified key-phrase utilizing multiple online translation engines, and then selects the most relevant reformulations from a large group of question rewrites, which is formed by full permutation and combination of the generated paraphrases. Extensive evaluations on a real world data set demonstrate that our model is able to characterize the complex questions and achieves promising performance as compared to the state-of-the-art methods.