Survey of ICT use for students with developmental disabilities by type of disability and class

This study was conducted to investigate whether information and communication technology (ICT) devices are used differently for students with developmental disabilities in elementary schools, depending on the type of disability (learning disabilities, attention deficit hyperactivity disorder, and autism spectrum disorder) and class (regular classes, resource rooms, and classes for special needs education). A questionnaire survey was administered to elementary school teachers to identify the extent of use of different ICT devices for students with developmental disabilities in their schools by type of disability and class. Results did not show differences in the extent of ICT device use by type of disability, although relative ICT scarcity in resource rooms was found. For supporting students with developmental disabilities, a need exists for more effective use of ICT devices depending on different types of developmental disability and class

The Structure of Working Memory and Its Relationship with Intelligence in Japanese Children

There is a host of research on the structure of working memory (WM) and its relationship with intelligence in adults, but only a few studies have involved children. In this paper, several different WM models were tested on 170 Japanese school children (from 7 years and 5 months to 11 years and 6 months). Results showed that a model distinguishing between modalities (i.e., verbal and spatial WM) fitted the data well and was therefore selected. Notably, a bi-factor model distinguishing between modalities, but also including a common WM factor, presented with a very good fit, but was less parsimonious. Subsequently, we tested the predictive power of the verbal and spatial WM factors on fluid and crystallized intelligence. Results indicated that the shared contribution of WM explained the largest portion of variance of fluid intelligence, with verbal and spatial WM independently explaining a residual portion of the variance. Concerning crystallized intelligence, however, verbal WM explained the largest portion of the variance, with the joint contribution of verbal and spatial WM explaining the residual part. The distinction between verbal and spatial WM could be important in clinical settings (e.g., children with atypical development might struggle selectively on some WM components) and in school settings (e.g., verbal and spatial WM might be differently implicated in mathematical achievement)

Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms

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Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms

Tea trees are kept in shaded locations to increase their chlorophyll content, which influences green tea quality. Therefore, monitoring change in chlorophyll content under low light conditions is important for managing tea trees and producing high-quality green tea. Hyperspectral remote sensing is one of the most frequently used methods for estimating chlorophyll content. Numerous studies based on data collected under relatively low-stress conditions and many hyperspectral indices and radiative transfer models show that shade-grown tea performs poorly. The performance of four machine learning algorithms—random forest, support vector machine, deep belief nets, and kernel-based extreme learning machine (KELM)—in evaluating data collected from tea leaves cultivated under different shade treatments was tested. KELM performed best with a root-mean-square error of 8.94 ± 3.05 μg cm−2 and performance to deviation values from 1.70 to 8.04 for the test data. These results suggest that a combination of hyperspectral reflectance and KELM has the potential to trace changes in the chlorophyll content of shaded tea leaves

Quantifying chlorophyll-a and b content in tea leaves using hyperspectral reflectance and deep learning

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発達障害児の認知特性に基づいた教育実践に向けて

本稿では，発達障害児の認知特性に基づいた教育実践に向けて，関連する基礎的な知見を整理することを目的とした。特に，発達障害の中でも学習障害と知的障害を取り上げ，それらを有する児童生徒にしばしば弱さが見られるとともに，学習活動との関連も強い認知機能であるワーキングメモリの特徴を検討した。学習障害児および知的障害児のワーキングメモリに関する知見を概観した結果，学習障害児（本稿では読字障害児に限定した）および知的障害児には特徴的なワーキングメモリのプロフィールが見られること，特に，両者に共通する全体的な傾向として，音韻性ワーキングメモリの機能が低下していること，一方で視空間性ワーキングメモリの機能は保持されていることが示唆された。最後に，発達障害児の認知特性に基づいた教育実践の例や留意点が論じられた

Effects of angiotensin receptor-neprilysin inhibitor on ketone body metabolism in pre-heart failure/heart failure patients

Abstract Recently, a mild elevation of the blood ketone levels was found to exert multifaceted cardioprotective effects. To investigate the effect of angiotensin receptor neprilysin inhibitors (ARNIs) on the blood ketone body levels, 46 stable pre-heart failure (HF)/HF patients were studied, including 23 who switched from angiotensin-converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARBs) to ARNIs (ARNI group) and 23 who continued treatment with ACE inhibitors or ARBs (control group). At baseline, there were no significant differences in the total ketone body (TKB) levels between the two groups. Three months later, the TKB levels in the ARNI group were higher than the baseline values (baseline to 3 months: 71 [51, 122] to 92 [61, 270] μmol/L, P < 0.01). In the control group, no significant change was observed between the baseline and 3 months later. A multiple regression analysis demonstrated that the initiation of ARNI and an increase in the blood non-esterified fatty acid (NEFA) levels at 3 months increased the percentage changes in the TKB levels from baseline to 3 months (%ΔTKB level) (initiation of ARNI: P = 0.017, NEFA level at 3 months: P < 0.001). These results indicate that ARNI administration induces a mild elevation of the blood TKB levels in pre-HF/HF patients