Impact of the flush discharge from a dam on the biotic and abiotic river environment

River engineeringRiver habitat management and restoratio

Influence of residual Ga_2O_3 and Cs on the increase in the maximum quantum efficiency of NEA-GaAs by a two-step thermal cleaning process

We investigated the relationship between the increase in the maximum quantum efficiency of negative electron affinity (NEA)-GaAs depending on the thermal cleaning conditions and residual species, e.g., Ga_2O_3 and Cs atoms, on the GaAs surface using temperature-programmed desorption. We found that the increase in the maximum quantum efficiency occurs during thermal cleaning at 500–600℃ for ～8.5 min. The increase in ratio was maximum when the amount of Ga_2O_3 on the GaAs surface was maximum. In the case that Cs atoms remained, when the thermal cleaning was performed in a temperature range where Ga_2O_3 was not formed, the effect facilitating an NEA surface formation was observed. However, the residual Cs atoms might not be affected at an increased maximum quantum efficiency. From the above results, we considered that the double-dipole structures of Cs-Ga_2O_3 and Cs-O are significant to the high quantum efficiency. The Cs-O dipoles are considered to form easily when Ga_2O_3 is on the GaAs surface before the NEA activation, and the amount of Cs-O dipoles required to reduce the vacuum level below the conduction band minimum increase more than usually NEA surface. As a result, the maximum quantum efficiency increases

Prediction of causative genes in inherited retinal disorder from fundus photography and autofluorescence imaging using deep learning techniques

Background/Aims: To investigate the utility of a data-driven deep learning approach in patients with inherited retinal disorder (IRD) and to predict the causative genes based on fundus photography and fundus autofluorescence (FAF) imaging. / Methods: Clinical and genetic data from 1302 subjects from 729 genetically confirmed families with IRD registered with the Japan Eye Genetics Consortium were reviewed. Three categories of genetic diagnosis were selected, based on the high prevalence of their causative genes: Stargardt disease (ABCA4), retinitis pigmentosa (EYS) and occult macular dystrophy (RP1L1). Fundus photographs and FAF images were cropped in a standardised manner with a macro algorithm. Images for training/testing were selected using a randomised, fourfold cross-validation method. The application program interface was established to reach the learning accuracy of concordance (target: >80%) between the genetic diagnosis and the machine diagnosis (ABCA4, EYS, RP1L1 and normal). / Results: A total of 417 images from 156 Japanese subjects were examined, including 115 genetically confirmed patients caused by the three prevalent causative genes and 41 normal subjects. The mean overall test accuracy for fundus photographs and FAF images was 88.2% and 81.3%, respectively. The mean overall sensitivity/specificity values for fundus photographs and FAF images were 88.3%/97.4% and 81.8%/95.5%, respectively. / Conclusion: A novel application of deep neural networks in the prediction of the causative IRD genes from fundus photographs and FAF, with a high prediction accuracy of over 80%, was highlighted. These achievements will extensively promote the quality of medical care by facilitating early diagnosis, especially by non-specialists, access to care, reducing the cost of referrals, and preventing unnecessary clinical and genetic testing

Use of MMG signals for the control of powered orthotic devices: Development of a rectus femoris measurement protocol

Copyright © 2009 Rehabilitation Engineering and Assistive Technology Society (RESNA). This is an Author's Accepted Manuscript of an article published in Assistive Technology, 21(1), 1 - 12, 2009, copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/10400430902945678.A test protocol is defined for the purpose of measuring rectus femoris mechanomyographic (MMG) signals. The protocol is specified in terms of the following: measurement equipment, signal processing requirements, human postural requirements, test rig, sensor placement, sensor dermal fixation, and test procedure. Preliminary tests of the statistical nature of rectus femoris MMG signals were performed, and Gaussianity was evaluated by means of a two-sided Kolmogorov-Smirnov test. For all 100 MMG data sets obtained from the testing of two volunteers, the null hypothesis of Gaussianity was rejected at the 1%, 5%, and 10% significance levels. Most skewness values were found to be greater than 0.0, while all kurtosis values were found to be greater than 3.0. A statistical convergence analysis also performed on the same 100 MMG data sets suggested that 25 MMG acquisitions should prove sufficient to statistically characterize rectus femoris MMG. This conclusion is supported by the qualitative characteristics of the mean rectus femoris MMG power spectral densities obtained using 25 averages

Prediction of Causative Genes in Inherited Retinal Disorders from Spectral-Domain Optical Coherence Tomography Utilizing Deep Learning Techniques

Purpose. To illustrate a data-driven deep learning approach to predicting the gene responsible for the inherited retinal disorder (IRD) in macular dystrophy caused by ABCA4 and RP1L1 gene aberration in comparison with retinitis pigmentosa caused by EYS gene aberration and normal subjects. Methods. Seventy-five subjects with IRD or no ocular diseases have been ascertained from the database of Japan Eye Genetics Consortium; 10 ABCA4 retinopathy, 20 RP1L1 retinopathy, 28 EYS retinopathy, and 17 normal patients/subjects. Horizontal/vertical cross-sectional scans of optical coherence tomography (SD-OCT) at the central fovea were cropped/adjusted to a resolution of 400 pixels/inch with a size of 750 × 500 pix2 for learning. Subjects were randomly split following a 3 : 1 ratio into training and test sets. The commercially available learning tool, Medic mind was applied to this four-class classification program. The classification accuracy, sensitivity, and specificity were calculated during the learning process. This process was repeated four times with random assignment to training and test sets to control for selection bias. For each training/testing process, the classification accuracy was calculated per gene category. Results. A total of 178 images from 75 subjects were included in this study. The mean training accuracy was 98.5%, ranging from 90.6 to 100.0. The mean overall test accuracy was 90.9% (82.0–97.6). The mean test accuracy per gene category was 100% for ABCA4, 78.0% for RP1L1, 89.8% for EYS, and 93.4% for Normal. Test accuracy of RP1L1 and EYS was not high relative to the training accuracy which suggests overfitting. Conclusion. This study highlighted a novel application of deep neural networks in the prediction of the causative gene in IRD retinopathies from SD-OCT, with a high prediction accuracy. It is anticipated that deep neural networks will be integrated into general screening to support clinical/genetic diagnosis, as well as enrich the clinical education

Clinical and genetic characteristics of 10 Japanese patients with PROM1-associated retinal disorder: A report of the phenotype spectrum and a literature review in the Japanese population

Variants in the PROM1 gene are associated with cone (-rod) dystrophy, macular dystrophy, and other phenotypes. We describe the clinical and genetic characteristics of 10 patients from eight Japanese families with PROM1-associated retinal disorder (PROM1-RD) in a nationwide cohort. A literature review of PROM1-RD in the Japanese population was also performed. The median age at onset/examination of 10 patients was 31.0 (range, 10-45)/44.5 (22-73) years. All 10 patients showed atrophic macular changes. Seven patients (70.0%) had spared fovea to various degrees, approximately half of whom had maintained visual acuity. Generalized cone (-rod) dysfunction was demonstrated in all nine subjects with available electrophysiological data. Three PROM1 variants were identified in this study: one recurrent disease-causing variant (p.Arg373Cys), one novel putative disease-causing variant (p.Cys112Arg), and one novel variant of uncertain significance (VUS; p.Gly53Asp). Characteristic features of macular atrophy with generalized cone-dominated retinal dysfunction were shared among all 10 subjects with PROM1-RD, and the presence of foveal sparing was crucial in maintaining visual acuity. Together with the three previously reported variants [p.R373C, c.1551+1G>A (pathogenic), p.Asn580His (likely benign)] in the literature of Japanese patients, one prevalent missense variant (p.Arg373Cys, 6/9 families, 66.7%) detected in multiple studies was determined in the Japanese population, which was also frequently detected in the European population