Exploratory and Confirmatory Factor Analysis for Disposition Levels of Computational Thinking Instrument Among Secondary School Students

<p style="text-align: justify;">Computational thinking (CT) is a method for solving complex problems, but also gives people an inventive inspiration to adapt to our smart and changing society. Globally it has been considered as vital abilities for solving genuine issues successfully and efficiently in the 21st century. Recent studies have revealed that the nurture of CT mainly centered on measuring the technical skill. There is a lack of conceptualization and instruments that cogitate on CT disposition and attitudes. This study attends to these limitations by developing an instrument to measure CT concerning dispositions and attitudes. The instruments' validity and reliability testing were performed with the participation from secondary school students in Malaysia. The internal consistency reliability, standardized residual variance, construct validity and composite reliability were examined. The result revealed that the instrument validity was confirmed after removing items. The reliability and validity of the instrument have been verified. The findings established that all constructs are useful for assessing the disposition of computer science students. The implications for psychometric assessment were evident in terms of giving empirical evidence to corroborate theory-based constructs and also validating items' quality to appropriately represent the measurement.</p>

Psychometric Validation of The Cognitive Abilities Screening Instrument Using Rasch Analysis In People With Dementia

Background: The Cognitive Abilities Screening Instrument (CASI) is one of the most commonly used cognitive screening tools to assess overall cognitive function in people with dementia. However, the unidimensionliaty of the CASI using Rasch analysis has not been evaluated in people with dementia, limiting its utility in clinical and research settings. Unidimensionality verifies whether all items of a measure reflect a single theoretical construct, which is necessary to determine whether clinicians and researchers can appropriately use the sum scores of the CASI to describe overall cognitive function. This study aimed to examine unidimensionality of the CASI using Rasch analysis and estimate Rasch person reliability in people with dementia. Methods: CASI data of people with dementia was collected from medical records of one general hospital in northern Taiwan. A total of 506 people with dementia were recruited from the Department of Neurology. Unidimensionality was confirmed through two assumptions: (1) the infit and outfit mean square (MnSq) were 0.6-1.4, and (2) residual variance of the first principal component in principal component analysis was ≤ 20%. Rasch person reliability was estimated after undimensionality was supported. Results: One item from the list-generating fluency dimension was misfitted (outfit MnSq=1.42) and was deleted. The unidimensionality of the remaining 45 items (referred to as the CASI-45) was supported with an infit and outfit MnSq (0.85-1.24 and 0.84-1.28, respectively) and low residual variance of the first principal component (12.8%). The Rasch person reliability of the CASI-45 was 0.62. Conclusion: The CASI-45 showed a unidimensional construct and had acceptable Rasch person reliability in people with dementia.

Evaluation of the phenotypic and genomic background of variability based on litter size of Large White pigs

Background The genetic background of trait variability has captured the interest of ecologists and animal breeders because the genes that control it could be involved in buffering various environmental effects. Phenotypic variability of a given trait can be assessed by studying the heterogeneity of the residual variance, and the quantitative trait loci (QTL) that are involved in the control of this variability are described as variance QTL (vQTL). This study focuses on litter size (total number born, TNB) and its variability in a Large White pig population. The variability of TNB was evaluated either using a simple method, i.e. analysis of the log-transformed variance of residuals (LnVar), or the more complex double hierarchical generalized linear model (DHGLM). We also performed a single-SNP (single nucleotide polymorphism) genome-wide association study (GWAS). To our knowledge, this is only the second study that reports vQTL for litter size in pigs and the first one that shows GWAS results when using two methods to evaluate variability of TNB: LnVar and DHGLM. Results Based on LnVar, three candidate vQTL regions were detected, on Sus scrofa chromosomes (SSC) 1, 7, and 18, which comprised 18 SNPs. Based on the DHGLM, three candidate vQTL regions were detected, i.e. two on SSC7 and one on SSC11, which comprised 32 SNPs. Only one candidate vQTL region overlapped between the two methods, on SSC7, which also contained the most significant SNP. Within this vQTL region, two candidate genes were identified, ADGRF1, which is involved in neurodevelopment of the brain, and ADGRF5, which is involved in the function of the respiratory system and in vascularization. The correlation between estimated breeding values based on the two methods was 0.86. Three-fold cross-validation indicated that DHGLM yielded EBV that were much more accurate and had better prediction of missing observations than LnVar. Conclusions The results indicated that the LnVar and DHGLM methods resulted in genetically different traits. Based on their validation, we recommend the use of DHGLM over the simpler method of log-transformed variance of residuals. These conclusions can be useful for future studies on the evaluation of the variability of any trait in any species.

The Validity of the Residuals Approach to Measuring Resilience to Adverse Childhood Experiences

Background: Resilience is broadly defined as the ability to maintain or regain functioning in the face of adversity. Recent work to harmonise the quantification and definition of resilience quantifies resilience as the residual variance in psychosocial functioning that remains after accounting for adversity exposure. However, there have been no published studies that have formally investigated the validity of this approach. Considering this, we examine the construct and predictive validity of the residuals approach using participants from ALSPAC. Methods: We regressed exposures of adolescent adversity on adolescent psychopathology scores using the Strength and Difficulties Questionnaire and obtained the residual variance. We investigated construct validity by analysing whether previously identified demographic and resilience factors significantly predicted resilience. Predictive validity of resilience was investigated by comparing the predictive power of resilience with other determinants of psychosocial functioning on two developmental outcomes: depressive symptoms at 18 years, measured by the Short Moods and Feelings Questionnaire, and NEET (Not in Employment, Education or Training) status at 17 and 23 years. The associations between depressive symptoms at 18, resilience, ACEs and covariates were tested using multiple linear regression. NEET status at 17 and 23 were run as separate binary multiple logistic regression models to test associations with resilience and known demographics previously associated with NEET status.Results: Seven previously identified protective factors, including self-esteem, positive sibling relationship, temperament, and positive perception of school, significantly predicted resilience to adolescent psychopathology, thus providing strong construct validity. Resilience significantly predicted a reduction in depressive symptoms at 18 years, and significantly decreased the likelihood of having NEET status at both 17 years and 23 years, even after taking into account early childhood adversity and other risk factors. None of the socioeconomic factors were significantly associated with resilience.Conclusions: Our study demonstrates that the residuals method of operationalising resilience has good construct and predictive validity yet recommend replication studies. It has the potential to advance research into the mechanisms and modifiability of resilience.Trial Registration: Not applicable

Childhood Disadvantage and Later-Life Multimorbidity: Demonstrating Robustness Under Imperfect Identification

This study assesses the relationship between indicators of early childhood disadvantage and later-life multimorbidity within a nationally representative sample of Brazilians aged 50 and over (n = 9,412). Data come from the baseline assessment (2015/2016) of the Brazilian Longitudinal Study of Aging (ELSI). We employed survey-weighted Ordinary Least Squares regression to estimate the effects of individual and combined measures of childhood disadvantage on the total number of chronic conditions in later life. Mediation analysis assessed whether adult socioeconomic status (SES) mediated the relationship between childhood disadvantage and chronic conditions. We found that individual and combined measures of childhood disadvantage were associated with the total number of chronic conditions, even after controlling for potential confounders. Mediation analysis suggested that part of the effect of childhood adversity is mediated by higher SES in adulthood (~10%). A formal strategy of sensitivity analysis showed that omitted variable bias is extremely unlikely. To rule out the observed effect, an unobserved hypothetical confounder would need the explanatory power of the residual variance of both the independent and the dependent variables that is at least 30 times larger than that of BMI or 5 times larger than the explanatory power of age. Results should inform efforts to strengthen interventions targeting early childhood development and to improve other key inputs (such as education) to enhance adult SES and lessen the impact of early life stressors on health in older adulthood.

Дослідження якісних показників поляризаційної селекції об’єктів на фоні пасивних завад в поляризаційно-доплерівській радіолокаційній системі

The optimal algorithm of polarization-Doppler selection of targets against the background of passive interference is considered. The polarimetric properties of scattered electromagnetic radiation of objects. The functionally-determined mathematical model of the useful signal, structure and correlation characteristics of the internal radiation of the receiver is determined. The algorithm of optimal processing, synthesized within the method of maximum likelihood, is considered for two limit cases. Algorithmic actions in the processing of passive interference and methods of their compensation are considered and investigated. Based on the obtained results, the expression for the algorithm of compensation of interferences reflected from the earth's surface is written. The obtained algorithm equalizes the variance of the input signals and compensates the residual variance with the help of weight coefficients. On the basis of the developed algorithm the scheme of the structurally simplified optimum compensator of passive disturbances is formed. Feature processing of useful signals in the compensation scheme is investigated. To ensure the adaptability of the generated algorithm, the coefficient of the variance ratio is based on the results coming from the variance meter. It is proposed to introduce quality indicators of polarization object selection on the background of the underlying surface, which combines indicators of efficiency of passive interference compensation and indicators of efficiency of useful signal-processing against the background of internal noise of receivers. The corresponding dependence of the indicators on the correlation coefficients of passive interference of different polarizations, as well as on the coefficients that separately characterize the level of difference in signal intensities and interference in the reception channels. The information value of each indicator of the efficiency of polarization signal selection from the ratio of the input variances, the correlation coefficient of passive interference and the ratio of the input signals is investigated.The obtained results are proposed to be used to improve the quality of polarization selection of objects in ground-based and aerospace-based radar systems.

Qntifying and Examining Reserve in Symptomatic Former National Football League Players

Background: Repetitive head impacts (RHI) from contact sports have been associated with cognitive and neuropsychiatric disorders. However, not all individuals exposed to RHI develop such disorders. This may be explained by the reserve hypothesis. It remains unclear if the reserve hypothesis accounts for the heterogenous symptom presentation in RHI-exposed individuals. Moreover, optimal measurement of reserve in this population is unclear and likely unique from non-athlete populations. Objective: We examined the association between metrics of reserve and cognitive and neuropsychiatric functioning in 89 symptomatic former National Football League players. Methods: Individual-level proxies (e.g., education) defined reserve. We additionally quantified reserve as remaining residual variance in 1) episodic memory and 2) executive functioning performance, after accounting for demographics and brain pathology. Associations between reserve metrics and cognitive and neuropsychiatric functioning were examined. Results: Higher reading ability was associated with better attention/information processing (β=0.25; 95%CI, –0.13–0.64), episodic memory (β=0.27; 95%CI, 0.16–0.38), semantic fluency (β=0.24; 95%CI, 0.01–0.47; β=0.38; 95%CI, –0.14–0.90), and behavioral regulation (β=–0.26; 95%CI, –0.78–0.27) performance. There were no effects for other individual-level proxies. Residual episodic memory variance was associated with better attention/information processing (β=0.45; 95%CI, –0.34–1.24), executive functioning (β=0.36; 95%CI, –3.14–3.86), and semantic fluency (β=0.38; 95%CI, –0.08–0.84) performance. Residual executive functioning variance was associated with better attention/information processing (β=0.44; 95%CI, 0.39–0.49) and episodic memory (β=0.37; 95%CI, 0.36–0.39) performance. Conclusion: Traditional reserve proxies (e.g., years of education, occupational attainment) have limitations and may be unsuitable for use in elite athlete samples. Alternative approaches of reserve quantification may prove more suitable for this population.

Genotype-environment interaction effects on weight gain in cattle using reaction norms

The existence of genotype-environment interaction (GEI) using reaction norm models and their impact on the genetic evaluation of Nellore sires for body weight at 120, 210, 365 and 450 days of age was verified. Three models were used: animal model (AM) that disregards GEI and the one-step reaction norm model with homogeneous and heterogeneous residual variance (1SRNMH_het). Bayes Inference via Gibbs Sampling was used to estimate the variance components. The AM model better fits to weights at 120 and 210 days of age, while 1SRNMH_het was more adequate for body weights at 365 and 450 days of age, suggesting the existence of GEI. The posterior means of direct heritability were 0.33±0.01 and 0.36±0.01 and maternal heritability of 0.21±0.01 and 0.19±0.01 for body weights at 120 and 210 days of age, respectively. For body weights at 365 and 450 days of age, posterior means of heritability varied along the environmental gradient, but the ranking of sires based on breeding values was not changed by different environmental gradients. All rank correlations were greater than 0.80, strongly suggesting a scale effect of GEI. Despite the evidence of GEI on post-weaning weight gain, it did not change the ranking of sires. Therefore, it did not have a relevant impact on the genetic evaluation of sires because they are robust to environmental changes.

PSXIV-19 Heritability for growth and resistance to gastrointestinal parasitism in meat goats and hair sheep

Genetic selection for resistance to internal parasitism is of great research interest. Heritabilities were determined for average daily gain (ADG), logarithmic transformed fecal egg count (FEC), packed cell volume (PCV), and serum immunoglobin (Ig) levels of growing male meat goats and hair sheep from different farms in the southcentral USA during three consecutive central performance tests (CPT). Tests entailed 7–10 wk of data collection after artificial infection with Haemonchus contortus. In year 1, animals evaluated were selected randomly and in years 2 and 3 progeny of CPT sires classified as highly or moderately resistant, which included 46, 50, and 51 Boer, Kiko, and Spanish and 59, 61, 34, and 46 Dorper, Katahdin-farm A, Katahdin-farm B, and St. Croix, respectively. Females were classified accordingly on-farm based on FEC and FAMACHA. Pedigree records consisted of 32 and 57 known sires, 95 and 152 known dams including 4 and 10 full-sibs and 97 and 149 half-sibs for goats and sheep, respectively. Variance components and heritabilities were estimated by AIREML using WOMBAT with a multivariate animal model. Heritability estimates were 0.48 ± 0.214 and 0.85 ± 0.157 of ADG, 0.31 ± 0.237 and 0.20 ± 0.172 of FEC, 0.60 ± 0.206 and 0.24 ± 0.185 of PCV, 0.26 ± 0.172 and 0.51 ± 0.167 of IgA, 0.335 and 0.543 of IgM, and 0.14 ± 0.192 and 0.31 ± 0.190 of IgG for goats and sheep, respectively. Reasons for relatively high heritabilities for all traits include the low residual variance estimates due primarily to a standardized environment in the performance test. In conclusion, moderate to high heritabilities were found for growth performance and response to parasite infection for growing meat goat and hair sheep males under a standardized environment that suggests considerable for genetic improvement through selection.

New computer technologies to determine postmortem interval by the Henssge method

Background: The Henssge method is still the main thermometric method to determine postmortem interval. However, its existing software implementations are characterized by several disadvantages associated with copying simplified nomographic variants of the original mathematical models without any optimization attempts, as well as procedural imperfection in finding the roots of implicit functions. In this paper, methods are proposed for optimizing solutions to the Henssge mathematical models and determine their errors, as well as software application implementation. Aim: Optimization of the Henssge algorithm and development of a series of applications based on the obtained data, designed to determine postmortem interval. Material and methods: Methods for solving double exponential Henssge models and determining their errors based on computational mathematics and regression modeling using the least-squares method with subsequent implementation in the format of computer programs in C# language optimized. Results: The discrete nature of residual variance changes of the double exponential Henssge models intended to determine the postmortem interval according to rectal and cranioencephalic thermometry data under constant external temperature conditions is eliminated. The interval estimate determination of postmortem interval at any confidence probability is possible. The application program Warm Bodies HR was developed, which implements applied optimization methods. The application program Warm Bodies AHBG, designed to determine postmortem interval by the Henssge method in a single discrete decrease or increase conditions in the constant temperature of the external environment, including a change in the cooling conditions of the corpse, was developed. The search for the roots of implicit functions in programs is carried out using the Newton tangent method, which ensures continuous source data nature and eliminates errors associated with the need to round directly measured physical quantities. Conclusions: The developed programs are recommended for forensic medical expert practice to determine postmortem interval.