Deep Learning Predicts Rapid Over-softening and Shelf Life in Persimmon Fruits

In contrast to the progress in the research on physiological disorders relating to shelf life in fruit crops, it has been difficult to non-destructively predict their occurrence. Recent high-tech instruments have gradually enabled non-destructive predictions for various disorders in some crops, while there are still issues in terms of efficiency and costs. Here, we propose application of a deep neural network (or simply deep learning) to simple RGB images to predict a severe fruit disorder in persimmon, rapid over-softening. With 1,080 RGB images of ‘Soshu’ persimmon fruits, three convolutional neural networks (CNN) were examined to predict rapid over-softened fruits with a binary classification and the date to fruit softening. All of the examined CNN models worked successfully for binary classification of the rapid over-softened fruits and the controls with > 80% accuracy using multiple criteria. Furthermore, the prediction values (or confidence) in the binary classification were correlated to the date to fruit softening. Although the features for classification by deep learning have been thought to be in a black box by conventional standards, recent feature visualization methods (or “explainable” deep learning) has allowed identification of the relevant regions in the original images. We applied Grad-CAM, Guided backpropagation, and layer-wise relevance propagation (LRP), to find early symptoms for CNNs classification of rapid over-softened fruits. The focus on the relevant regions tended to be on color unevenness on the surface of the fruit, especially in the peripheral regions. These results suggest that deep learning frameworks could potentially provide new insights into early physiological symptoms of which researchers are unaware

A Shell-less Tokamak “NOVA”

A description is given of the experimental shell-less Tokamak NOVA. This apparatus is designed to investigate the stabilization of plasmas in a shell-less Tokamak device, first by the programand the feedback-control of the vertical magnetic field, and then by controlling the radial distribution of the longitudinal plasma current, The basic concepts of design and the constructional data of the principal components are shown, together with some results of preliminary experiments

Transcriptional and Epigenetic Consequences of DMSO Treatment on HepaRG Cells

Dimethyl sulfoxide (DMSO) is used to sustain or favor hepatocyte differentiation in vitro. Thus, DMSO is used in the differentiation protocol of the HepaRG cells that present the closest drug-metabolizing enzyme activities to primary human hepatocytes in culture. The aim of our study is to clarify its influence on liver-specific gene expression. For that purpose, we performed a large-scale analysis (gene expression and histone modification) to determine the global role of DMSO exposure during the differentiation process of the HepaRG cells. The addition of DMSO drives the upregulation of genes mainly regulated by PXR and PPARα whereas genes not affected by this addition are regulated by HNF1α, HNF4α, and PPARα. DMSO-differentiated-HepaRG cells show a differential expression for genes regulated by histone acetylation, while differentiated-HepaRG cells without DMSO show gene signatures associated with histone deacetylases. In addition, we observed an interplay between cytoskeleton organization and EMC remodeling with hepatocyte maturation

Development of an atmospheric Cherenkov imaging camera for the CANGAROO-III experiment

A Cherenkov imaging camera for the CANGAROO-III experiment has been developed for observations of gamma-ray induced air-showers at energies from 10$^{11}$ to 10$^{14}$ eV. The camera consists of 427 pixels, arranged in a hexagonal shape at 0.17$^\circ$ intervals, each of which is a 3/4-inch diameter photomultiplier module with a Winston-cone--shaped light guide. The camera was designed to have a large dynamic range of signal linearity, a wider field of view, and an improvement in photon collection efficiency compared with the CANGAROO-II camera. The camera, and a number of the calibration experiments made to test its performance, are described in detail in this paper.Comment: 25 pages, 29 figures, elsart.cls, to appear in NIM-

Pressureless sintering of SiC-coated carbon nanofiber/SiC composites and their properties

In this study, in order to improve interfacial strength between CNFs and SiC matrix and to disperse CNFs uniformly in the SiC matrix, using the SiC-coated CNFs which were prepared using SiO2 powder at 1400-1800 degrees C in argon atmosphere, CNFs/SiC composites were fabricated in argon atmosphere under pressureless condition. The non-coated CNFs/SiC and SiC-coated CNFs/SiC composites reached near the full density at 2150 degrees C. The SiC grains and the carbon agglomerates in the composites tended to be finer with an increase in amount of SiC coating on CNFs. The SiC-coated CNFs/SiC composites showed almost the same fracture toughness (4.5-5.0 MPa.m(0.5)) with the non-coated CNFs/SiC composite. On the other hand, the SiC-coated CNFs/SiC composites showed higher bending strength than the non-coated CNFs/SiC composite, and the bending strength became higher with an increase in amount of SiC coating on CNFs. The maximum bending strength was 551 MPa, which represent a 32% increase compared with that of the non-coated CNFs/SiC composite. (C) 2015 The Ceramic Society of Japan. All rights reserved.ArticleJOURNAL OF THE CERAMIC SOCIETY OF JAPAN. 123(1439):570-575 (2015)journal articl