Investigation on Variables Contributing to the Synthesis of C-S-H/PCE Nanocomposites by Co-Precipitation Method

The usage of nanoscale calcium silicate hydrate (nano C-S-H) proved to have an excellent promotion effect on the early performance of concrete as nano C-S-H with ultra-fine particle size can act as seeding for cement hydration. Therefore, it is of importance to tune the particle size during the synthesis process of nano C-S-H. In this paper, the influence of several variables of the particle size distribution (PSD) of nano C-S-H synthesized by chemical co-precipitation method with the aid of polycarboxylate (PCE) was studied by orthogonal experimental design. In addition, the composition, microstructure, and morphology of the C-S-H/PCE nanocomposites were analyzed by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and Raman spectrum. The results showed that the concentration of reactants had a significant impact on the PSD of C-S-H/PCE nanocomposites, followed by the dosage of dispersant. Ultrasonic treatment was effective in breaking the C-S-H/PCE aggregates with unstable agglomeration structures. The change in synthetic variables had a negligible effect on the composition of the C-S-H/PCE nanocomposites but had a significant influence on the crystallinity and morphology of the composites.

Using Decision Trees and Random Forest Algorithms to Predict and Determine Factors Contributing to First-Year University Students’ Learning Performance

First-year students’ learning performance has received much attention in educational practice and theory. Previous works used some variables, which should be obtained during the course or in the progress of the semester through questionnaire surveys and interviews, to build prediction models. These models cannot provide enough timely support for the poor performance students, caused by economic factors. Therefore, other variables are needed that allow us to reach prediction results earlier. This study attempts to use family background variables that can be obtained prior to the start of the semester to build learning performance prediction models of freshmen using random forest (RF), C5.0, CART, and multilayer perceptron (MLP) algorithms. The real sample of 2407 freshmen who enrolled in 12 departments of a Taiwan vocational university will be employed. The experimental results showed that CART outperforms C5.0, RF, and MLP algorithms. The most important features were mother’s occupations, department, father’s occupations, main source of living expenses, and admission status. The extracted knowledge rules are expected to be indicators for students’ early performance prediction so that strategic intervention can be planned before students begin the semester.

Early Performance of Several Prunus Interspecific Hybrid Rootstocks for Redhaven Peach in Southern Ontario

A multi-year orchard experiment was established to measure the performance of Rootpac®-R, Rootpac®-20, Rootpac®-40, and Rootpac®-70 rootstocks using ‘Redhaven’ peach (Prunus persica var. persica) as the scion, and compared with the Bailey peach seedling rootstock, the current industry standard. Tree survival after five years was 79% on Rootpac-40, whereas the remaining rootstocks showed no tree mortality. Tree vigour and canopy height and width were influenced by rootstock genotype beginning the year of planting in 2016. For the first five years of production, Rootpac-70 consistently produced the largest trees based on TCSA and by year five, all rootstocks produced trees with similar TCSAs, except for Rootpac-70, which was 38% larger than Bailey. By year five, cumulative yields were greatest on Rootpac-70, which were 10% higher than Bailey; cumulative yields of Rootpac-R, Rootpac-20, and Rootpac-30 were 98%, 89%, and 84% that of Bailey, respectively. Cumulative yield efficiency was significantly influenced by rootstock although the magnitude of the differences was small and likely of insignificant commercial importance. Rootpac-40 consistently produced the largest fruit. These results are only reflective of the orchard establishment years and additional data are required before peach producers can make fully informed decisions concerning the rootstocks evaluated in this study for their orchard systems. However, at this juncture, all the Rootpac rootstocks evaluated in this study are likely to impart excessive vigour to be used in a higher density system and offer little advantage over Bailey.

Physical-physiological quality and early performance of sorghum plants under different boron doses via seed

Boron (B) deficiency is commonly found in tropical crops, among which sorghum stands out for its limited yield under B shortage. However, as a micronutrient, the range between its adequate and toxic levels is narrow, thus fertilization should be cautiously applied. Our goal was to evaluate the physiological and physical quality, as well as early performance, of grain sorghum seedlings under different B doses applied via seeds. Treatments consisted of six doses of boric acid (0.0, 2.5, 5.0, 7.5, 10.0, and 12.5 g Kg-1 seeds) plus a control (uncoated seeds). Boron doses were applied to seeds by coating, in which dolomitic limestone and glue were used for pellet formation. Coated seeds were assessed for physical, physiological, and nutritional characteristics in the laboratory, and early seedling performance was evaluated in a greenhouse. Seed tests were carried out in a fully randomized design, while seedling evaluations were carried out in a randomized block design. Boron application to seeds had no significant effect on seed physical characteristics, despite increases in coated seed sizes. Boron doses had a negative effect on the length and dry mass accumulation of both plant shoot and root. Seed-applied B accumulated mainly in roots and significantly interfered with Ca and Mg accumulations in sorghum seeds, shoots, and roots.

Eccentricity Effects on NVH Performance of Interior Permanent Magnets Machines for Hybrid and Electric Vehicles

For the hybrid electric vehicles (HEVs) and electric vehicles (EVs) applications, the electric machine drive unit system provides the main noise source, especially in the presence of faults. Eccentricity is one of the most common faults, which is mainly caused by the motors' package design and assembling process. There are four main types of eccentricity for motors: static offset, dynamic offset, static tilt and dynamic tilt, which are presented and analyzed. Both two-dimensional (2D) and 3-dimentional (3D) finite element analysis (FEA) are utilized in the electromagnetic field analysis for an Interior Permanent Magnet (IPM) motor. The corresponding methodologies for the mesh and force mapping to the mechanical FEA for the NVH analysis are presented. The NVH test shows that both 2D and 3D FEA can provide reasonable accuracy for the motor eccentricity fault analysis. The 2D FEA is the most common method used in the design optimization and early performance prediction for electrical. For the 3D FEA, due to the high requirement for the computer hardware and computation capability, it is usually used in the final validation for electrical machines' performance. The sensitivity of motor performance versus the airgap heights and eccentricities are studied.

Estimates of genetic parameters of economic traits in murrah buffaloes

Data from 1991 to 2017, pertaining to early performance traits was collected from 659 Murrah buffaloes, sired by 188 bulls, maintained at Directorate of Livestock Farms, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab. Least squares means and effect on non-genetic factors were evaluated for economic traits. Moderate heritability estimates of 0.217 ± 0.00, 0.231 ± 0.00, 0.260 ± 0.046 were calculated for first calving interval (FCI), First 305 day milk yield (F305MY) and first peak yield (FPY) respectively and low heritability values of 0.015± 0.025 and 0.043 ± 0.03 were estimated for age at first calving (AFC) and first lactation length (FLL) respectively. The phenotypic and genetic correlation of AFC was found to be positive with FLL and FCI and negative with F305MY and FPY. Although the production efficiency traits like F305MY, FLL and FPY had high positive genetic and phenotypic correlation among themselves.

Human brain responses associated with subjective evaluation of error significance are sensitive to error inevitability

This study examined whether error-related brain responses are sensitive to the degree of error inevitability, a factor which seriously affects the attribution of moral responsibility for an error. We were especially interested in error-related negativity (ERN), which is an electrophysiological marker of subjective evaluation of error significance and its motivational value. In addition, we focused on post-error slowing, which is a post-error behavioural adjustment. We hypothesized that the more avoidable the error, and consequently the greater its significance and motivational value, the larger the ERN amplitude, the shorter the ERN latency, and the greater the post-error slowing should be. To elicit errors whose inevitability varies, we used the stop-signal task. The inevitability of errors in this task depends on whether the stop signal is presented before or after a point beyond which the completion of the movement cannot be cancelled. Consistent with our hypotheses, we found that the higher motivational value of avoidable errors was indeed reflected in larger and earlier ERNs. Moreover, avoidable errors led to greater adjustments in subsequent behaviour aimed at preventing similar failures in the future. These findings show that early performance monitoring, as reflected by ERN, involves an evaluation of error inevitability. In a broader perspective, these results indicate that the elementary basis for distinguishing between culpable (avoidable) and non-culpable (unavoidable) errors may occur in the brain several dozen milliseconds after error commission.