https://www.selleckchem.com/products/ABT-263.html Word2vec introduced by Mikolov et al. is a word embedding method that is widely used in natural language processing. Despite its success and frequent use, a strong theoretical justification is still lacking. The main contribution of our paper is to propose a rigorous analysis of the highly nonlinear functional of word2vec. Our results suggest that word2vec may be primarily driven by an underlying spectral method. This insight may open the door to obtaining provable guarantees for word2vec. We support these findings by numerical simulations. One fascinating open question is whether the nonlinear properties of word2vec that are not captured by the spectral method are beneficial and, if so, by what mechanism.Blastocystis is frequently reported in fecal samples from animals and humans worldwide, and a variety of subtypes (STs) have been observed in wild and domestic animals. In Colombia, few studies have focused on the transmission dynamics and epidemiological importance of Blastocystis in animals. In this study, we characterized the frequency and subtypes of Blastocystis in fecal samples of domestic animals including pigs, minipigs, cows, dogs, horses, goats, sheep, and llama from three departments of Colombia. Of the 118 fecal samples included in this study 81.4% (n = 96) were positive for Blastocystis using a PCR that amplifies a fragment of the small subunit ribosomal RNA (SSU rRNA) gene. PCR positive samples were sequenced by next generation amplicon sequencing (NGS) to determine subtypes. Eleven subtypes were detected, ten previously reported, ST5 (50.7%), ST10 (47.8%), ST25 (34.3%), ST26 (29.8%), ST21 (22.4%), ST23 (22.4%), ST1 (17.9%), ST14 (16.4%), ST24 (14.9%), ST3 (7.5%), and a novel subtype, named ST32 (3.0%). Mixed infection and/or intra -subtype variations were identified in most of the samples. Novel ST32 was observed in two samples from a goat and a cow. To support novel subtype designation, a MinION base