A nonparametric regression-based linkage scan of rheumatoid factor-IgM using sib-pair squared sums and differences

Parametric linkage methods for quantitative trait locus mapping require explicit specification of the probability model of the quantitative trait and hence can lead to misleading linkage inferences when the model assumptions are not valid. Ghosh and Majumder developed a nonparametric regression method based on kernel-smoothing for linkage mapping of quantitative trait locus using squared differences in trait values of independent sib pairs, which is relatively more robust than parametric methods with respect to violations in distributional assumptions. In this study, we modify the above mentioned nonparametric regression method by considering local linear polynomials instead of the Nadaraya-Watson estimator and squared sums of sib-pair trait values in addition to squared differences to perform a genome-wide scan of rheumatoid factor-IgM levels on sib pairs in the Genetic Analysis Workshop 15 simulated data set. We obtain significant evidence of linkage very close to the quantitative trait locus controlling for RF-IgM. We find that the simultaneous use of squared differences and squared sums increases the power to detect linkage compared to using only squared differences. However, because of all the sib pairs are selected for rheumatoid arthritis, there is reduced variance of RF-IgM values, and empirical power to detect linkage is not very high. We also compare the performance of our method with two linear regression approaches: the classical Haseman-Elston method using squared sib-pair trait differences and its extension proposed by Elston et al. using mean-corrected sib-pair cross-products. We find that the proposed nonparametric method yields more power than the linear regression approaches

Unsteady Flow of a Dusty Viscous Liquid Through Circular Cylinder

The laminar flow of an unsteady viscous liquid with uniform distribution of dust particles through a circular cylinder under the influence of exponential pressure gradient has been investigated. Two interesting cases have been discussed and analytical expressions for velocities of fluid and dust particles are obtained

Protonation Equilibria of L-Aspartic, Citric and Succinic Acids in Anionic Micellar Media

The impact of sodium lauryl sulphate (SLS) on the protonation equilibria of L-aspartic acid, citric acid and succinic acid has been studied in various concentrations (0.5-2.5% w/v) of SLS solution maintaining an ionic strength of 0.16 mol dm-3 at 303 K. The protonation constants have been calculated with the computer program MINIQUAD75 and the best fit models have been calculated based on statistical parameters. The trend of log values of step-wise protonation constants with mole fraction of the medium has been explained based on electrostatic and non-electrostatic forces operating on the protonation equilibria. The effects of errors on the protonation constants have also been presented

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Not AvailableThe present study was undertaken to assess academic achievement, teaching aptitude and research attitude of Indian agricultural universities faculty, to predict indicators for successful teachers and researchers, and thereby enhancing the quality of higher agricultural education. Methodology: Five hundred faculty members were selected to elicit information on academic, teaching and research achievements. Teaching aptitude and attitude of faculty towards research were measured through standard psychometric tests. Correlation and regression analysis was carried out to establish the relationship among selected variables. Findings: Combination of academic achievement and teaching aptitude was a superior predictor for the teaching achievement compared to either of them alone. Similarly, research achievement of faculty was predicted better by the combination of academic achievement and research attitude. Practical. Implications: The study showed the need for training faculty members in interpersonal relationships for effective teaching, and in research methodology and research processes for improving research attitude of faculty. Theoretical. Implications: The expectancy value model provides a useful framework to understand the role of attitude/aptitude in better prediction of research and teaching behavior. Originality/Value: The present study showed that teaching aptitude and research attitude be considered along with academic achievements for promoting quality teaching and research and hence the educational programmes.Not Availabl

Not Available

Not AvailableThe present study was undertaken to assess academic achievement, teaching aptitude and research attitude of Indian agricultural universities’ faculty, to predict indicators for successful teachers and researchers, and thereby enhancing the quality of higher agricultural education. Methodology: Five hundred faculty members were selected to elicit information on academic, teaching and research achievements. Teaching aptitude and attitude of faculty towards research were measured through standard psychometric tests. Correlation and regression analysis was carried out to establish the relationship among selected variables. Findings: Combination of academic achievement and teaching aptitude was a superior predictor for the teaching achievement compared to either of them alone. Similarly, research achievement of faculty was predicted better by the combination of academic achievement and research attitude. Practical Implications: The study showed the need for training faculty members in interpersonal relationships for effective teaching, and in research methodology and research processes for improving research attitude of faculty. Theoretical Implications: The expectancyvalue model provides a useful framework to understand the role of attitude/aptitude in better prediction of research and teaching behavior. Originality/Value: The present study showed that teaching aptitude and research attitude be considered along with academic achievements for promoting quality teaching and research and hence the educational programmes.Not Availabl