Background: Pregnancy is a physiological condition that affects the general and oral health.It is also associated with an increase in oxidative stress, which may presispose to oral diseases including dental caries. Aim of the study: This study aimed to measure salivary protein carbonyl, glutathione peroxidase and selenium levels of women who are pregnant and their association with dental caries in comparison to non-pregnant women, and to find out the mostly affected biomarker of oxidative stress during pregnancy. Subjects, materials and methods: A cross-sectional research was performed for a samples of 30 pregnant and 30 non-pregnant women who were chosen from city of Baghdad's Primary Healthcare Centers. Both groups aged 25-30 years. In

Deep drawing process to produce square cup is very complex process due to a lot of process parameters which control on this process, therefore associated with it many of defects such as earing, wrinkling and fracture. Study of the effect of some process parameters to determine the values of these parameters which give the best result, the distributions for the thickness and depths of the cup were used to estimate the effect of the parameters on the cup numerically, in addition to experimental verification just to the conditions which give the best numerical predictions in order to reduce the time, efforts and costs for producing square cup with less defects experimentally is the aim of this study. The numerical analysis is used to study

The aim of this paper to find Bayes estimator under new loss function assemble between symmetric and asymmetric loss functions, namely, proposed entropy loss function, where this function that merge between entropy loss function and the squared Log error Loss function, which is quite asymmetric in nature. then comparison a the Bayes estimators of exponential distribution under the proposed function, whoever, loss functions ingredient for the proposed function the using a standard mean square error (MSE) and Bias quantity (M_bias), where the generation of the random data using the simulation for estimate exponential distribution parameters different sample sizes (n=10,50,100) and (N=1000), taking initial