Jamal Ibrahim Daoud

In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.

The phagocytosis of apoptotic cells and associated vesicles (efferocytosis) by DCs is an important mechanism for both self tolerance and host defense. Although some of the engulfment ligands involved in efferocytosis have been identified and studied in vitro, the contributions of these ligands in vivo remain ill defined. Here, we determined that during Mycobacterium tuberculosis (Mtb) infection, the engulfment ligand annexin1 is an important mediator in DC cross-presentation that increases efferocytosis in DCs and intrinsically enhances the capacity of the DC antigen-presenting machinery. Annexin1-deficient mice were highly susceptible to Mtb infection and showed an impaired Mtb antigen-specific CD8+ T cell response. Importantly, annexin1 expression was greatly downregulated in Mtb-infected human blood monocyte-derived DCs, indicating that reduction of annexin1 is a critical mechanism for immune evasion by Mtb. Collectively, these data indicate that annexin1 is essential in immunity to Mtb infection and mediates the power of DC efferocytosis and cross-presentation.

We consider linear and nonlinear stochastic models for transmission of blood types and Rhesus factor from parents to their offspring and investigate long run behavior of these models. In this study we will consider an application of the theory of Markov chains and the theory of nonlinear transformations in medicine. It is well known that the gene which determines blood group in humans has three different alleles, A, B, C and that there are four groups of blood, A, B, AB and O. The aim is to investigate the transmission of blood groups from parents to their offspring. For simplicity, we will consider only positive Rhesus factors, since the portion of the population with negative Rhesus is around 1%. It is well known that the blood groups of parents do not determine unambiguously their offspring’s blood group. To describe this transmission, we have rather extensive statistics for blood groups of parents and their offspring. In connection with these statistics, we construct the following two Markov chains. The first Markov chain describes the transmission from a father to his sons; the second Markov chain describes the transmission from a mother to her daughters. Lastly we construct and study a quadratic stochastic operators that describe the transmission of blood groups from parents to their offspring.

In the view of Cadmium (Cd) toxicity from human health, heavy metal concentrations in water are controlled by strict standards and should be reduced to the standards permitted. This study is concerning an approach of removing a heavy metal, Cd, from its aqueous solution by carbon nanotubes (CNTs) absorption. The synthetic water was prepared with initial Cd concentrations of 1mg/L and shook with CNTs, before the water is separated by filtration. A spectrophotometer procedure was applied to analyze the filtrate for the concentration of Cd. The effects of the varying factors on the Cd removal efficiency, which are the CNT dosage, pH, agitation speed and contact time, were studied. All of the factors used in the adsorption experiment were said to be significant with the adsorption capacity which has been identified from the regression analysis. From the results obtained, the highest percentage removal of Cd using CNT is at pH7, 10 mg of CNTs dosage, contact time of 120 min and agitation speed of 150 rpm which gave 19.14% removal.