In this paper we investigate the problem of identifying the perspective from which a document was written. By perspective we mean a point of view, for example, from the perspective of Democrats or Republicans. Can computers learn to identify the perspective of a document? Furthermore, can computers identify which sentences in a document strongly convey a particular perspective? We develop statistical models to capture how perspectives are expressed at the document and sentence levels, and evaluate the proposed models on a collection of articles on the Israeli-Palestinian conflict. The results show that the statistical models can successfully learn how perspectives are reflected in word usage and identify the perspective of a document with very high accuracy.

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Background Canine parvovirus type 2 (CPV-2) was first identified in the late 1970s; it causes intestinal hemorrhage with severe bloody diarrhea in kennels and dog shelters worldwide. Since its emergence, CPV-2 has been replaced with new genetic variants (CPV-2a, CPV-2b, and CPV-2c). Currently, information about the genotype prevalence of CPV-2 in Vietnam is limited. In the present study, we investigated the genotype prevalence and distribution of CPV-2 in the three regions of Vietnam. Methods Rectal swabs were collected from 260 dogs with suspected CPV-2 infection from northern, central, and southern Vietnam from November 2016 to February 2018. All samples were identified as parvovirus positive by real-time PCR, and further genotyping was performed using a SimpleProbe® real-time PCR assay. Results Of the 260 Vietnamese CPV-2 isolates, 6 isolates (2.31%) were identified as CPV-2a, 251 isolates (96.54%) were identified as CPV-2c and 3 isolates (1.15%) were untypable using the SimpleProbe® real-time PCR assay. In northern Vietnam, the percentages of CPV-2a and CPV-2c were 2.97% (3/101) and 97.3% (98/101), respectively. In central Vietnam, the percentages of CPV-2a and CPV-2c were 1.11% (1/90) and 98.89% (89/90), respectively. In southern Vietnam, the percentages of CPV-2a and CPV-2c were 3.03% (2/66) and 96.97% (64/66), respectively. CPV-2b was not observed in this study. The VP2 genes of CPV-2c in Vietnam are more genetically similar to those of CPV-2c strains in China and Taiwan than to those of prototype CPV-2c strains (FJ222821) or the first Vietnamese CPV-2c (AB120727). Conclusion The present study provides evidence that CPV-2c is the most prevalent variant in Vietnam. Phylogenetic analysis demonstrated that the recent Vietnamese CPV-2c isolates share a common evolutionary origin with Asian CPV-2c strains. Electronic supplementary material The online version of this article (10.1186/s12985-019-1159-z) contains supplementary material, which is available to authorized users.

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As personal wearable devices become more powerful and ubiquitous, soon everyone will be capable to continuously record video of everyday life. The archive of continuous recordings need to be segmented into manageable units so that they can be efficiently browsed and indexed by any video retrieval systems. Many researchers approach the problem in two-pass methods: segmenting the continuous recordings into chunks, followed by clustering chunks. In this paper we propose a novel one-pass algorithm to accomplish both tasks at the same time by imposing time constraints on the K-Means clustering algorithm. We evaluate the proposed algorithm on 62.5 hours of continuous recordings, and the experiment results show that time-constrained clustering algorithm substantially outperforms the unconstrained version.