Development and Validation of Perceived Stigmatization in Sports Scale for Female Athletes

The current study aimed to develop an indigenous, valid and reliable perceived stigmatization in sports scale for female athletes (PSSSFA). Eight in-depth, detailed and semi-structured interviews were conducted with female athletes, whereas, the preliminary item pool of twenty items was administered on 125 female university athletes. The age was 18-24 years (M= 21, SD=1.6). The process of scale development depended upon two phases. The first phase was about construct conceptualization through interviews and the second phase consisted of examining factor structure and reliability of the scale. Perceived Stigmatization in Sports Scale for Female Athletes was developed in Urdu. Total 20 items were developed but the final scale included 18 items with five-point rating scale. On the basis of scree plot and Eigen values, three factors were extracted: Family Stigmatization included 6 items and had .82 reliability, Social Stigmatization included 5 items and had .75 reliability and Effect on Performance included 7 items and had .76 reliability. The overall Cronbach alpha value was .88. The findings of the study tended to investigate factors affecting the perceived stigmatization associated with female athletes and these results would help in providing awareness regarding challenges being faced by female athletes in their respective sports.

Catjects

A general theory of digitization would not only look at electronic media and their impact on society but focus on distinctions trying to order, count, and show analogue realities. Calculus with Newton and Leibniz seems to have been invented to do just that. Distinctions become codes when their results are played back to reality to produce a reality of their own. The paper draws on George Spencer-Brown's calculus of indications to come up with the idea of catjects understood as eigen-values of recursive and reflexive functions producing phenomena of all kinds, including social ones. Catjects allow to model, formalize, or symbolize the synchronization of observations contextualizing each other or of different systems, such as neuronal, mental, social, and artificial which draw their distinctions to reproduce as forms of digitization. Spencer-Brown's idea of the "form" of a distinction is a way to understand distinctions as connections modeling complex phenomena which combine systems references standing orthogonal to each other.

Excitonic States and Related Optical Susceptibility in InN/AlN Quantum Well Under the Effects of the Well Size and Impurity Position

Based on the finite difference method, linear optical susceptibility, photoluminescence peak and binding energies of three first states of an exciton trapped by a positive charge donor-impurity ( ) confined in InN/AlN quantum well are investigated in terms of well size and impurity position. The electron, heavy hole free and bound excitons allowed eigen-values and corresponding eigen-functions are obtained numerically by solving one-dimensional time-independent Schrödinger equation. Within the parabolic band and effective mass approximations, the calculations are made considering the coupling of the electron in the n-th conduction subband and the heavy hole in the m-th valence subband under the impacts of the well size and impurity position. The obtained results show clearly that the energy, binding energy and photoluminescence peak energy show a decreasing behavior according to well size for both free and bound cases. Moreover, the optical susceptibility associated to exciton transition is strongly red-shift (blue-shifted) with enhancing the well size (impurity position).

Rising levels of soil acidity in Meghalaya: Evidences and Imperatives

In order to examine the current status of soil acidity in Meghalaya, representative soil samples (n= 497) were collected (during 2015-2016) from across the state and analyzed for soil acidity and associated parameters. Averaged across the samples, pH of the soils was found to be very strongly acidic (4.94). Nearly 20 % of the soils had pH below 4.50, 59% below pH 5.0 and 80% below pH 5.50. Only 3.4% of the samples recorded pH more than 6.0. East Khasi Hills District had the maximum percentage (95.1%) of strongly acidic soils (pH ≤ 5.50) while Garo Hills had the least (50.2%). All other districts recorded more than 85% of the strongly acidic soils. Average exchangeable acidity, exchangeable Al and effective CEC were found to be 1.60, 1.27 and 3.86 meq/100g soil, respectively. Mean base saturation was recorded below 60%. Aluminium saturation (percentage of effective CEC being occupied by exch. Al) ranged from 1.5 to 79.7% with its mean value being as high as 33%. Principal component analysis provided three PCs with Eigen values >1 and together they explained 83.2 % of the variance in total dataset. The soil acidity in Meghalaya is on rise, with 80.2% of its soils being strongly acidic (pH ≤ 5.50) in contrast to the previous reports of 53% soils being strongly acidic. This calls for widespread adoption of soil acidity ameliorative measures in agriculture of Meghalaya, Northeast India.

Mathematical Modelling for Semiconductor and Piezoelectric Media

In this analysis the importance of mathematical modelling of the physical systems has been outlined. The constitutive relations and basic governing equations of motion for homogeneous isotropic elastic semiconductor (n-type) and homogeneous transversely isotropic ( class) piezoelectric elastic media, in the absence of body forces and electric sources are made non-dimensional in order to reduce the mathematical complexity. All the obtained equations are rewritten in matrix form. Then considering the harmonic wave solution the eigen values and eigen vectors are calculated to obtained the formal solution of the problem.

Evaluation of Eigen Value Extraction and Automatic Computational Classification of Corpus in Scene Scheduling of Sports and Health IoT Platform

This study constructed a corpus by collecting samples of applications in exercise health information. Based on the extracted 8 eigen values, this study used the Fisher score algorithm to score the eigen values and then formed a combination of 8 groups of eigen values according to the score ranking. This study performed computerized automatic classification using cross-checking based on three methods, support vector machines, neural networks, and Naive Bayes model. By analyzing the experimental results, the optimal eigen value combination and the optimal classification algorithm were finally derived in this study.

Development of a Scale to Measure Infant Eating Behaviour Worldwide

In order to create a short, internationally valid scale to assess eating behaviour (EB) in young children at risk of undernutrition, we refined 15 phrases describing avidity or food refusal (avoidance). In study one, 149 parents matched phrases in English, Urdu, Cantonese, Indonesian or Greek to videos showing avidity and avoidance; 82–100% showed perfect agreement for the avidity phrases and 73–91% for the avoidant phrases. In study two, 575 parents in the UK, Cyprus and Indonesia (healthy) and in Kenya, Pakistan and Guatemala (healthy and undernourished) rated their 6–24 months old children using the same phrases. Internal consistency (Cronbach’s α) was high for avidity (0.88) and moderate for avoidance (0.72). The best-performing 11 items were entered into a principal components analysis and the two scales loaded separately onto 2 factors with Eigen values > 1. The avidity score was positively associated with weight (r = 0.15 p = 0.001) and body mass index (BMI) Z scores (r = 0.16 p = 0.001). Both high and low avoidance were associated with lower weight and BMI Z scores. These scales are internationally valid, relate to nutritional status and can be used to inform causes and treatments of undernutrition worldwide.

Principal component analyses in mungbean genotypes under summer season

Yield is a complex trait subjective to several components and environmental factors. Therefore, it becomes necessary to apply such technique which can identify and prioritize the key traits to lessen the number of traits for valuable selection and genetic gain. Principal component analysis is primarily a renowned data reduction technique which identifies the least number of components and explain maximum variability, it also rank genotypes on the basis of PC scores. PCA was calculated using Ingebriston and Lyon (1985) method. In present study, PCA performed for phenological and yield component traits presented that out of thirteen, only five principal components (PCs) exhibited more than 1.00 eigen value, and showed about 80.28 per cent of total variability among the traits. Scree plot explained the percentage of variance associated with each principal component obtained by illustrating a graph between eigen values and principal component numbers. PC1 showed 26.12 per cent variability with eigen value 3.40. Graph depicted that the maximum variation was observed in PC1 in contrast to other four PCs. The PC1 was further associated with the phenological and yield attributing traits viz., number of nodes per plant, number of pod cluster per plant, number of pod per plant. PC2 exhibited positive effect for harvest index. The PC3 was more related to yield related traits i.e., number of seeds per pod, number of seeds per plant and biological yield per plant, whereas PC4 was more loaded with phenological traits. PC5 was further related to yield and yield contributing traits i.e. number of primary branches per plant, seed yield per plant and 100 seed weight. A high value of PC score of a particular genotype in a particular PC denotes high value for those variables falling under that specific principal component. Pusa Vishal found in PC 2, in PC 3, PC 4 and PC 5, can be considered as an ideal breeding material for selection and for further deployment in defined breeding programme.