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Background As a valuable medicinal plant, Rhodiola has a very long history of folk medicine used as an important adaptogen, tonic, and hemostatic. However, our knowledge of the chloroplast genome level of Rhodiola is limited. This drawback has limited studies on the identification, evolution, genetic diversity and other relevant studies on Rhodiola. Results Six Rhodiola complete chloroplast genomes were determined and compared to another Rhodiola cp genome at the genome scale. The results revealed a cp genome with a typical quadripartite and circular structure that ranged in size from 150,771 to 151,891 base pairs. High similarity of genome organization, gene number, gene order, and GC content were found among the chloroplast genomes of Rhodiola. 186 (R. wallichiana) to 200 (R. gelida) SSRs and 144 pairs of repeats were detected in the 6 Rhodiola cp genomes. Thirteen mutational hotspots for genome divergence were determined and could be used as candidate markers for phylogenetic analyses and Rhodiola species identification. The phylogenetic relationships inferred by members of Rhodiola cluster into two clades: dioecious and hermaphrodite. Our findings are helpful for understanding Rhodiola's taxonomic, phylogenetic, and evolutionary relationships. Conclusions Comparative analysis of chloroplast genomes of Rhodiola facilitates medicinal resource conservation, phylogenetic reconstruction and biogeographical research of Rhodiola.

SUMMARYA text-dependent i-vector extraction scheme and a lexicon-based binary vector (L-vector) representation are proposed to improve the performance of text-dependent speaker verification. I-vector and L-vector are used to represent the utterances for enrollment and test. An improved cosine distance kernel is constructed by combining i-vector and L-vector together and is used to distinguish both speaker identity and lexical (or text) diversity with back-end support vector machine (SVM). Experiments are conducted on RSR 2015 Corpus part 1 and part 2, the results indicate that at most 30% improvement can be obtained compared with traditional i-vector baseline.

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