Characterization of the effect of ion irradiation on industrially produced GdBa₂Cu₃O₇−δ superconducting tapes using a slow positron beam

To investigate the effect of irradiation-induced defects on the superconducting characteristics of industrially produced superconductor—GdBa₂Cu₃O₇−δ (GdBCO)—coated conductors (CCs), we irradiated the GdBCO CCs with Au ions at 2 or 10 MeV and probed them using a slow positron beam. Vacancy clusters were detected in both unirradiated and irradiated GdBCO CCs. However, the effect of ion irradiation on the GdBCO CCs was characterized as a slight reduction in the positron annihilation rate with low-momentum electrons. We also found a correlation between the annihilation rate of low-momentum electrons and the superconducting transition temperature

Slope efficiency characteristics of mode-hop driven tunable single-mode cholesteric liquid crystal laser

SPIE Photonic Devices + Applications, 2011, San Diego, California, United StatesYo Inoue, Hiroyuki Yoshida, Kenta Inoue, Yusuke Shiozaki, Hitoshi Kubo, Akihiko Fujii, and Masanori Ozaki "Slope efficiency characteristics of mode-hop driven tunable single-mode cholesteric liquid crystal laser", Proc. SPIE 8114, Liquid Crystals XV, 811415 (7 September 2011). DOI: https://doi.org/10.1117/12.89320

Global Oxygen Detection in Water Using Luminescent Probe on Anodized Aluminum

We have developed anodized-aluminum pressure-sensitive paint (AA-PSP) as a global oxygen sensor in water. Platinum (II) meso-tetra(pentafluorophenyl)porphine is selected as a luminophore based on a dipping deposition study. The developed AA-PSP is characterized using water calibration setup by controlling dissolved oxygen concentration. It is shown that AA-PSP yields 4.0% change in luminescence per 1 mg/L of oxygen concentration at 23°C. Other characteristics, such as temperature dependency, photo-degradation, and physical stability, are discussed in this paper. This AA-PSP is used to demonstrate its capability of global oxygen detection in water using the impingement of oxygen rich water (20 mg/L). Even though the difference in water is only the concentration of oxygen, we can obtain global oxygen information of the jet impingement using a fast frame rate camera. Oxygen maps as well as cross-sectional distributions are shown every 0.1 s

摂食障害と多発性自己破壊行動という特徴を有した症例における行動の遺伝学的研究について

Among a group of patients (n=65) , the majority of whom had been introduced to us by　eating-disorder specialists elsewhere because of difficulties in their treatment, we defined a　subgroup (n=39) characterized by eating disorders and multiple behavioral problems. In addition　to the disordered eating behavior, problematical behavior relating to the use of alcohol and other substances, shoplifting, promiscuity, and suicidal tendencies were seen in 74%, 36%, 33%, and 15% of the patients, respectively. Further, this subgroup showed an extremely worse outcome, when compared with the subgroup of patients with pure eating disorders (n =26). With regard to the intrafamilial traits examined among the first- and second-degree relatives, 49% of the patients had the trait for alcohol dependence, 28% had the trait for problematical behaviors. The physically or socially self-destructive types of behavior, which seemed to be attributable to vigorous and uncontrollable intrinsic impulses of the patients, tended to emerge in the respective patients in revolving or alternating manners. Therefore, enduring efforts should be taken to support the personality development of such patients rather than to struggle with respective problematical behaviors, which may be considered merely as facets of a single disorder. 多発性問題行動を有する摂食障害(EDMUL)39例を対象とし,標記検討を行った。これら症例は純粋な摂食障害に比べ予後不良であった。家族内形質としてはアルコール依存性を49%,問題行動を28%で認めた。EDMULにおける問題行動は身体的,社会的観点からの自己破壊行動であり,コントロールできない固有の衝動に基づいている可能性を示唆した。よってEDMULではそれぞれの問題行動に取り組むよりも,むしろ人間性の成長を支援する努力をすべきであると考えた

Sclerite formation in the hydrothermal-vent “scaly-foot” gastropod — possible control of iron sulfide biomineralization by the animal

A gastropod from a deep-sea hydrothermal field at the Rodriguez triple junction, Indian Ocean, has scale-shaped structures, called sclerites, mineralized with iron sulfides on its foot. No other organisms are known to produce a skeleton consisting of iron sulfides. To investigate whether iron sulfide mineralization is mediated by the gastropod for the function of the sclerites, we performed a detailed physical and chemical characterization. Nanostructural characterization of the iron sulfide sclerites reveals that the iron sulfide minerals pyrite (FeS2) and greigite (Fe3S4) form with unique crystal habits inside and outside of the organic matrix, respectively. The magnetic properties of the sclerites, which are mostly consistent with those predicted from their nanostructual features, are not optimized for magnetoreception and instead support use of the magnetic minerals as structural elements. The mechanical performance of the sclerites is superior to that of other biominerals used in the vent environment for predation as well as protection from predation. These characteristics, as well as the co-occurrence of brachyuran crabs, support the inference that the mineralization of iron sulfides might be controlled by the gastropod to harden the sclerites for protection from predators. Sulfur and iron isotopic analyses indicate that sulfur and iron in the sclerites originate from hydrothermal fluids rather than from bacterial metabolites, and that iron supply is unlikely to be regulated by the gastropod for iron sulfide mineralization. We propose that the gastropod may control iron sulfide mineralization by modulating the internal concentrations of reduced sulfur compounds

Deep Learning for Osteoporosis Classification Using Hip Radiographs and Patient Clinical Covariates

This study considers the use of deep learning to diagnose osteoporosis from hip radiographs, and whether adding clinical data improves diagnostic performance over the image mode alone. For objective labeling, we collected a dataset containing 1131 images from patients who underwent both skeletal bone mineral density measurement and hip radiography at a single general hospital between 2014 and 2019. Osteoporosis was assessed from the hip radiographs using five convolutional neural network (CNN) models. We also investigated ensemble models with clinical covariates added to each CNN. The accuracy, precision, recall, specificity, negative predictive value (npv), F1 score, and area under the curve (AUC) score were calculated for each network. In the evaluation of the five CNN models using only hip radiographs, GoogleNet and EfficientNet b3 exhibited the best accuracy, precision, and specificity. Among the five ensemble models, EfficientNet b3 exhibited the best accuracy, recall, npv, F1 score, and AUC score when patient variables were included. The CNN models diagnosed osteoporosis from hip radiographs with high accuracy, and their performance improved further with the addition of clinical covariates from patient records