Zero-dimensional chemical kinetic simulation of ROS/RNSin pulsed pulsed-discharge exposed water

The concentration variations of reactive oxygen/nitrogen species in water, such as H2O2, NO2 −, and NO3 − generated by pulsed-discharge plasma exposure, are calculated using reaction rates of chemical reactions and acid-base equilibrium in water. The calculated concentrations and pH values are in good agreement with measured data within the range where the significant changes of the measured data are observed. The rate constant for ONOOH generation is estimated to be 7.8 × 103 M−2 s−1, and this value is in good agreement with previously reported values. The generation rates of H2O2, NO2 −, and NO3 − are estimated to be 7.70 × 10−7, 4.10 × 10−7, and 1.10 × 10−7 M s−1, respectively

Effect of the particle brush on polishing performance of surface magnetic polishing using slurry circulation system

ArticleProceedings of the 6th international conference on progress of machining technology. CHEN D. NARUTAKI N. YAMANE. YCHEN W. OCHI A. ed. Xi’an in China, 2002-09, AVIATION INDUSTRY PRESS， 334-339 (2002)conference pape

Study on particle-brush in magnetic field assisted machining : Finishing characteristics of grooves

ArticleProceedings of International Conference on Leading Edge Manufacturing in 21st Century (LEM21). Niigata in Japan, 2003-11, The Japan Society of Mechanical Engineers，385-390(2003)conference pape

Efficient generation of highly squeezed light and second harmonic wave with periodically poled MgO:LiNbO_3

We report on effective generation of continuous-wave squeezed light and second harmonics with a periodically poled MgO:LiNbO$_{\mathrm{3}}$ (PPMgLN) crystal which enables us to utilize the large nonlinear optical coefficient $d_{\mathrm{33}}$. We achieved the squeezing level of $-7.60 \pm 0.15$dB at 860 nm by utilizing a subthreshol optical parametric oscillator with a PPMgLN crystal. We also generated 400 mW of second harmonics at 430 nm from 570 mW of fundamental waves with 70% of conversion efficiency by using a PPMgLN crystal inside an external cavity.Comment: 4 pages, 3 figure

Different Effects of Palmitoyl-L-carnitine and Palmitoyl-CoA on Mitochondrial Function in Rat Ventricular Myocytes

Although mitochondrial oxidative catabolism of fatty acid (FA) is a major energy source for the adult mammalian heart, cardiac lipotoxity resulting from elevated serum FA and enhanced FA use has been implicated in the pathogenesis of heart failure. To investigate the effects of the intermediates of FA metabolism, palmitoyl-L-carnitine (Pal-car) and palmitoyl-CoA (Pal-CoA), on mitochondrial function, we measured membrane potential(Δψm), opening of the mitochondrial permeability transition pore (mPTP) and the production of reactive oxygen species (ROS) in saponin-treated rat ventricular myocytes with a laser scanning confocal microscope. Our results revealed that: 1) lower concentrations of Pal-car (1 and 5μM) caused a slight hyperpolarization of Δψm (TMRE intensity increased to 115.5 ± 5.4 % and 110.7±1.6 % of the baseline, respectively. p<0.05) but did not open mPTP, 2) a higher concentration of Pal-car (10μM) depolarized Δψm (TMRE intensity decreased to 61.9 ± 12.2 % of the baseline, p<0.01) and opened mPTP (calcein intensity decreased to 70.7 ± 2.8% of the baseline, p<0.01), 3) Pal-CoA depolarized Δψm without opening mPTP, and 4) only the higher concentration of Pal-car (10μM) increased ROS generation (DCF intensity increased to 3.4 ± 0.3 fold of the baseline). We concluded that excessive exogenous intermediates of long chain saturated FA may disturb mitochondrial function in different ways between Pal-car and Pal-CoA. The distinct mechanisms of the deteriorating effects of long chain FA on mitochondrial function are important for our understanding of the development of cardiac diseases in systemic metabolic disorders.浜松医科大学学位論文　医博第517号(平成２０年１０月１７日

MADGAN: unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstruction.

BACKGROUND: Unsupervised learning can discover various unseen abnormalities, relying on large-scale unannotated medical images of healthy subjects. Towards this, unsupervised methods reconstruct a 2D/3D single medical image to detect outliers either in the learned feature space or from high reconstruction loss. However, without considering continuity between multiple adjacent slices, they cannot directly discriminate diseases composed of the accumulation of subtle anatomical anomalies, such as Alzheimer's disease (AD). Moreover, no study has shown how unsupervised anomaly detection is associated with either disease stages, various (i.e., more than two types of) diseases, or multi-sequence magnetic resonance imaging (MRI) scans. RESULTS: We propose unsupervised medical anomaly detection generative adversarial network (MADGAN), a novel two-step method using GAN-based multiple adjacent brain MRI slice reconstruction to detect brain anomalies at different stages on multi-sequence structural MRI: (Reconstruction) Wasserstein loss with Gradient Penalty + 100 [Formula: see text] loss-trained on 3 healthy brain axial MRI slices to reconstruct the next 3 ones-reconstructs unseen healthy/abnormal scans; (Diagnosis) Average [Formula: see text] loss per scan discriminates them, comparing the ground truth/reconstructed slices. For training, we use two different datasets composed of 1133 healthy T1-weighted (T1) and 135 healthy contrast-enhanced T1 (T1c) brain MRI scans for detecting AD and brain metastases/various diseases, respectively. Our self-attention MADGAN can detect AD on T1 scans at a very early stage, mild cognitive impairment (MCI), with area under the curve (AUC) 0.727, and AD at a late stage with AUC 0.894, while detecting brain metastases on T1c scans with AUC 0.921. CONCLUSIONS: Similar to physicians' way of performing a diagnosis, using massive healthy training data, our first multiple MRI slice reconstruction approach, MADGAN, can reliably predict the next 3 slices from the previous 3 ones only for unseen healthy images. As the first unsupervised various disease diagnosis, MADGAN can reliably detect the accumulation of subtle anatomical anomalies and hyper-intense enhancing lesions, such as (especially late-stage) AD and brain metastases on multi-sequence MRI scans