1,468 research outputs found

    One-step vapour-phase formation of patternable, electrically conductive, superamphiphobic coatings on fibrous materials

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    Patternable, electrically conductive coatings having a superhydrophobic and superoleophobic surface have been prepared by one-step vapour-phase polymerisation of polypyrrole in the presence of a fluorinated alkyl silane directly on fibrous substrates. The coated fabrics showed a surface resistance of 0.5-0.8 k&Omega; □-1 with water and hexadecane contact angles of 165&deg; and 154&deg;, respectively.<br /

    Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creative

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    Accurately predicting conversions in advertisements is generally a challenging task, because such conversions do not occur frequently. In this paper, we propose a new framework to support creating high-performing ad creatives, including the accurate prediction of ad creative text conversions before delivering to the consumer. The proposed framework includes three key ideas: multi-task learning, conditional attention, and attention highlighting. Multi-task learning is an idea for improving the prediction accuracy of conversion, which predicts clicks and conversions simultaneously, to solve the difficulty of data imbalance. Furthermore, conditional attention focuses attention of each ad creative with the consideration of its genre and target gender, thus improving conversion prediction accuracy. Attention highlighting visualizes important words and/or phrases based on conditional attention. We evaluated the proposed framework with actual delivery history data (14,000 creatives displayed more than a certain number of times from Gunosy Inc.), and confirmed that these ideas improve the prediction performance of conversions, and visualize noteworthy words according to the creatives' attributes.Comment: 9 pages, 6 figures. Accepted at The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019) as an applied data science pape

    Three-dimensional tissue scaffolds from interbonded poly(e-caprolactone) fibrous matrices with controlled porosity

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    In this article, we report on the preparation and cell culture performance of a novel fibrous matrix that has an interbonded fiber architecture, excellent pore interconnectivity, and controlled pore size and porosity. The fibrous matrices were prepared by combining melt-bonding of short synthetic fibers with a template leaching technique. The microcomputed tomography and scanning electron microscopy imaging verified that the fibers in the matrix were highly bonded, forming unique isotropic pore architectures. The average pore size and porosity of the fibrous matrices were controlled by the fiber/template ratio. The matrices having the average pore size of 120, 207, 813, and 994 mm, with the respective porosity of 73%, 88%, 96%, and 97%, were investigated. The applicability of the matrix as a three-dimensional (3D) tissue scaffold for cell culture was demonstrated with two cell lines, rat skin fibroblast and Chinese hamster ovary, and the influences of the matrix porosity and surface area on the cell culture performance were examined. Both cell lines grew successfully in the matrices, but they showed different preferences in pore size and porosity. Compared with two-dimensional tissue culture plates, the cell number on 3D fibrous matrices was increased by 97.27% for the Chinese hamster ovary cells and 49.46% for the fibroblasts after 21 days of culture. The fibroblasts in the matrices not only grew along the fiber surface but also bridged among the fibers, which was much different from those on two-dimensional scaffolds. Such an interbonded fibrous matrix may be useful for developing new fiber-based 3D tissue scaffolds for various cell culture applications
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