Secretion of extracellular vesicles is a general cellular activity that spans the range from simple unicellular organisms (e.g. archaea; Gram-positive and Gram-negative bacteria) to complex multicellular ones, suggesting that this extracellular vesicle-mediated communication is evolutionarily conserved. Extracellular vesicles are spherical bilayered proteolipids with a mean diameter of 20–1,000 nm, which are known to contain various bioactive molecules including proteins, lipids, and nucleic acids. Here, we present EVpedia, which is an integrated database of high-throughput datasets from prokaryotic and eukaryotic extracellular vesicles. EVpedia provides high-throughput datasets of vesicular components (proteins, mRNAs, miRNAs, and lipids) present on prokaryotic, non-mammalian eukaryotic, and mammalian extracellular vesicles. In addition, EVpedia also provides an array of tools, such as the search and browse of vesicular components, Gene Ontology enrichment analysis, network analysis of vesicular proteins and mRNAs, and a comparison of vesicular datasets by ortholog identification. Moreover, publications on extracellular vesicle studies are listed in the database. This free web-based database of EVpedia (http://evpedia.info) might serve as a fundamental repository to stimulate the advancement of extracellular vesicle studies and to elucidate the novel functions of these complex extracellular organelles.
The cold formability of the drawn non-heat-treated steels, i.e. dual phase (DP) steel, low Si steel and ultra low carbon bainitic (ULCB) steel, was examined in terms of the deformation resistance and the forming limit. The present investigation was aimed at elucidating the effect of drawing on the cold formability of non-heat-treated steels which is directly affected by drawing since no heat treatment are involved during forming processes for them. A special care was taken for the present steels to exhibit the similar strength after drawing, so eliminating the strength effect. The present steels after drawing revealed the elastic-near perfect plastic behavior in compression. After drawing, the low Si steel exhibited the lowest deformation resistance estimated by the absorbed energy during deformation. In case of the forming limit in terms of the critical strain under which no cracking occurs during the upsetting test of the drawn steels, the low Si steel and the ULCB steel were better than the conventional heat-treated steel. Accordingly, among several nonheat-treated steels which can replace the conventional heat-treated steel as forging steels, the low Si steel seems to exhibit the best performance if they have the similar strength. The compressive deformation behavior of the present drawn non-heat-treated steels was discussed in association with the strain hardened state and the Bauschinger effect developed by drawing. In addition, their cold formability was explained by the plastic incompatibility between the constituent phases of each steel.KEY WORDS: cold formability; drawing; non-heat treated steels; dual phase steel; low-Si steels; ultra low carbon bainitic steels; tensile and compression properties.
This study aims to identify the multidimensional variables and sub-variables and study their relative weight in music recommender systems when maximizing the rating function . To undertake the task, a optimization formula and variables for a research model were derived from the review of prior works on recommender systems, which were then used to establish the research model for an empirical test. With the research model and the actual log data of real customers obtained from an on line music provider in Korea, multiple regression analysis was conducted to induce the optimal correlation of variables in the multidimensional model. The results showed that the correlation value against the rating function for Items was highest, followed by Social Relations, Users and Contexts. Among sub-variables, popular music from Social Relations, genre, latest music and favourite artist from Items were high in the correlation with the rating function . Meantime, the derived multidimensional recommender systems revealed that in a comparative analysis, it outperformed two dimensions(Users, Items) and three dimensions(Users, Items and Contexts, or Users, items and Social Relations) based recommender systems in terms of adjusted and the correlation of all variables against the values of the rating function .
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