Personalized Prediction of Offensive News Comments by Considering the Characteristics of Commenters

When reading news articles on social networking services and news sites, readers can view comments marked by other people on these articles. By reading these comments, a reader can understand the public opinion about the news, and it is often helpful to grasp the overall picture of the news. However, these comments often contain offensive language that readers do not prefer to read. This study aims to predict such offensive comments to improve the quality of the experience of the reader while reading comments. By considering the diversity of the readers' values, the proposed method predicts offensive news comments for each reader based on the feedback from a small number of news comments that the reader rated as "offensive" in the past. In addition, we used a machine learning model that considers the characteristics of the commenters to make predictions, independent of the words and topics in news comments. The experimental results of the proposed method show that prediction can be personalized even when the amount of readers' feedback data used in the prediction is limited. In particular, the proposed method, which considers the commenters' characteristics, has a low probability of false detection of offensive comments.Comment: 12 pages, 6 figure

Manufacture of Arbitrary Cross-Section Composite Honeycomb Cores Based on Origami Techniques

In recent years, the use of composite materials has drastically increased in the construction of aerospace components. In the case of sandwich panels, they have been extensively used as face sheets with aluminum honeycomb cores. Currently, space structures are increasing in size and require greater degrees of accuracy; hence, the use of composites as a core material is a natural progression. However, these composite core materials are not regularly used in sandwich construction. Compared to standard aluminum honeycombs, their manufacturing costs are very high and they have limited applications. Another problem is difficulty of machining. In the manufacture of complex-shaped parts, the cores must have some degree of curvature. For aluminum honeycombs, this can be done using a contour cutter, a 3-D tracer, and numerically controlled machines. However, burrs and buckling of cell walls present a difficult problem for surface accuracy. It is clear that the machining of composite cores requires more expensive and sophisticated systems. This study illustrates a new strategy to fabricate arbitrary cross-section honeycomb cores with applications of advanced composite materials. These types of honeycombs are usually manufactured from normal flat honeycombs by curving or carving, but the proposed method enables us to construct objective shaped honeycombs directly. The basic idea originates from the fold-made paper honeycombs proposed by authors, in which they attempted to apply origami and kirigami techniques to the creation of sandwich structures. Origami is the traditional Japanese art of paper folding. Kirigami is a variation of origami. We first introduce the concept of the origami honeycomb, which is made from single flat sheets with periodical slits resembling origami. In previous studies, honeycombs having various shapes were made using this method, and were realized by only changing folding line diagrams (FLDs). In this study, these 3D origami honeycombs are generalized by numerical parameters and fabricated using a newly proposed FLD design method, which enables us to draw the FLD of arbitrary cross-section honeycombs. Next, we describe a method of applying this technique to advanced composite materials. For partially soft composites, folding lines are materialized by silicon rubber hinges on carbon fiber reinforced plastic. Complex FLD patterns are then printed using masks on carbon fabrics. Finally, these foldable composites that are cured in corrugated shapes in autoclaves are folded into honeycomb shapes, and some typical samples are shown with their FLDs

Distribution of a brain-specific extracellular matrix protein in developing and adult zebrafish

A monoclonal antibody (IgG) that recognizes a 53-kDa zebrafishnext brain protein was isolated and used to characterize the distribution of this protein in zebrafish.next (1) The antigen was found only in the brain and not in any other tissues such as muscle, dermis and cartilage. Within the brain, the antibody recognized extracellular matrix (ECM) outside neuronal cells. (2) Digestion by hyaluronidase released the antigen from brain tissue, and the monoclonal antibody staining was also decreased by the digestion by hyaluronidase. (3) The pattern of antigen distribution is not perineuronal, as the density of the antigen at the periphery of the cells was practically identical to that of the empty intercellular spaces. Therefore, this monoclonal antibody does not recognize the perineuronal glycocortex. (4) The antigen is distributed only in limited areas of the brain, namely in the periphery of the forebrain, the hypothalamus, the optic tectum, the interpeduncular nucleus, the cerebellum and the ventricular rim of the medulla. In the optic tectum, the antibody strongly stained the most superficial layer, and in the cerebellum, it stained the molecular but not the granular layer. These patterns of distribution are very different from those of other typical brain ECM proteins and suggest that this protein may play quite distinct roles in brain development and maintenance.</p

DETERMINATION OF ZINC IN VEHICLE EXHAUST PARTICULATES BY INDUCTIVELY COUPLED PLASMA ATOMIC EMISSION SPECTROMETRY WITH ELECTROTHERMAL VAPORIZATION

Joint Research on Environmental Science and Technology for the Eart