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The genotype evaluation process requires analysis of GxE interactions to ascertain the responsiveness of a genotype to various environments, including the development of early maturing rice. However, the concept of interaction is relatively specific to grain yield. In contrast, grain yield is highly polygenic, so assessment should be carried out with multivariate approaches. Therefore, multivariate assessment in evaluating GxE interactions should be developed, especially for early maturing rice genotypes. The study aimed to develop a comprehensive multivariate approach to improve the comprehensiveness and responsiveness of GxE interaction analysis. The study was conducted in Bone and Soppeng districts, South Sulawesi, Indonesia, in two seasons. The study used a randomized complete block design, where replications were nested across two seasons and locations. Two check varieties and five early maturing varieties were replicated three times in each environment. Based on this study, a new approach to GxE interaction analysis based on multiple regression index analysis, BLUP analysis, factor analysis, and path analysis was considered adequate, especially for evaluating early maturing rice. This approach combined days to harvest, biological yield, and grain yield in multiple linear regression with weighting based on the combination of all analyses. The effectiveness of the GxE interaction assessment was reflected by high coefficient of determination (R2) and gradient (b) values above 0.8 and 0.9, respectively. Inpari 13 (R2 = 0.9; b=1.05), Cakrabuana (R2 = 0.98; b=0.99), and Padjajaran (R2 = 0.95; b=1.07) also have good grain yield with days to harvesting consideration, namely 7.83 ton ha-1, 98.12 days; 7.37 ton ha-1, 95.52 days; and 7.29 ton ha-1, 97.23 days, respectively. Therefore, this index approach can be recommended in GxE interaction analysis to evaluate early maturing rice genotypes. Furthermore, Inpari 13, Cakrabuana, and Padjajaran are recommended as adaptive early maturing varieties. [ABSTRACT FROM AUTHOR]

The internal mechanisms of dental air turbine handpieces (DATHs) have become increasingly intricate over time. To enhance the operational reliability of dental procedures and guarantee patient safety, this study formulated temporal convolution network (TCN) prediction models with the functions of causality in time sequence, transmitting memory, learning, storing, and fast convergence for monitoring the health and diagnosing the rotor and collet failure of DATHs. A handpiece mimicking a dentist's hand load of 100 g was employed to repeatedly mill a glass porcelain block back and forth for cutting. An accelerometer was employed to capture vibration signals during free-running of unrestrained operation of the handpiece, aiming to discern the characteristic features of these vibrations. These data were then utilized to create a diagnostic health classification (DHC) for further developing a TCN, a 1D convolutional neural network (CNN), and long short-term memory (LSTM) prediction models. The three frameworks were used and compared for machine learning to establish DHC prediction models for the DATH. The experimental results indicate that, in terms of DHC predicted for the experimental dataset, the square categorical cross-entropy loss function error of the TCN framework was generally lower than that of the 1D CNN, which did not have a memory framework or the drawback of the vanishing gradient problem. In addition, the TCN framework outperformed the LSTM model, which required a longer history to provide sufficient diagnostic ability. Still, high accuracies were achieved both in the direction of feed-drive milling and in the gravity of the handpiece through vibration signals. In general, the failure classification prediction model could accurately predict the health and failure mode of the dental handpiece before the use of the DATH when an embedded sensor was available. Therefore, this model could prove to be a beneficial tool for predicting the deterioration patterns of real dental handpieces in their remaining useful life. [ABSTRACT FROM AUTHOR]

The study aims to verify whether extensive reading (ER) is able to promote senior high school students' English reading motivation and foster positive attitude towards reading in English. It further explores the teachers' perceptions of and the challenges faced in the implementation of ER activities. An ER activity was held for 12 weeks with 258 participants from 4 senior high schools in Southern Taiwan. Focus group interviews were then carried out with 72 randomly selected participants, after which individual interviews were conducted with 6 English teachers from these participating schools. Findings reveal that despite the challenges encountered in implementing the activity, the English teachers observed its benefits and were willing to encourage students to read extensively. The majority of the student participants also held positive attitudes towards the ER activity. Their positive attitudes, however, did not lead to the enhancement of their motivation in reading extensively due to the heavy workload from tests, homework or cram school. It was generally agreed that ER was time-consuming and not efficient enough to boost their exam scores. Accordingly, the study suggests that coordinated efforts and change of attitudes among the stakeholders are indispensable in the promotion of ER among senior high school students.

We studied the dissociation of water (H2O*, with * denoting adspecies) on atomic oxygen (O*)-covered Rh nanoclusters (RhO*) supported on a graphene film grown on a Ru(0001) surface [G/Ru(0001)] under ultrahigh-vacuum conditions and with varied surface-probe techniques and calculations based on density-functional theory. The graphene had a single rotational domain; its lattice expanded by about 5.7% to match the Ru substrate structurally better. The Rh clusters were grown by depositing Rh vapors onto G/Ru(0001); they had an fcc phase and grew in (111) orientation. Water adsorbed on the Rh clusters was dissociated exclusively in the presence of O*, like that on a Rh(111) single-crystal surface. Contrary to the case on Rh(111)O*, excess O* (even at a saturation level) on small RhO* clusters (diameter of 30–34 Å) continued to promote, instead of inhibiting, the dissociation of water; the produced hydroxyl (OH*) increased generally with the concentration of O* on the clusters. The difference results from more reactive O* on the RhO* clusters. O* on RhO* clusters activated the dissociation via both the formation of hydrogen bonds with H2O* and abstraction of H directly from H2O*, whereas O* on Rh(111)O* assisted the dissociation largely via the formation of hydrogen bonds, which was readily obstructed with an increased O* coverage. As the disproportionation (2 OH* → H2O* + O*) is endothermic on the RhO* clusters but exothermic on Rh(111)O*, OH* produced on RhO* clusters showed a thermal stability superior to that on the Rh(111)O* surface—thermally stable up to 400 K. [ABSTRACT FROM AUTHOR]