The study was conducted to determine the effect of of cumin (Cuminum cyminum) and ginger (Zingiber officinale) powder on performance in Japanese quails. 630 bird (7 birds for each treatment) nine weeks of age were used. Experiment was continued for 12 weeks divided to six periods and the birds distributed randomly on nine combinations of cumin and ginger, three levels of each plant powder namely, 0, 0.5 and 1%. T1 (Control) contain the slandered diet (0% of cumin and 0% of ginger), T2: (0% of cumin and 0.5% of ginger), T3: (0% of cumin and 1% of ginger), T4: (0.5% of cumin and 0% of ginger), T5: (0.5% of cumin and 0.5% of ginger), T6: (0.5% of cumin and 1% of ginger), T7: (1% of cumin and 0% of ginger), T8: (1% of cumin and 0.5% of ginger),

Objectives: Umbilical cord blood can be taken at birth and largely gives indication of fetal and maternal conditions. The aim of the study was to investigate the relation between sex hormones in cord blood and birth weight of newborns and pregnancy complications. Methods: Fifty cord blood samples were collected from newborns at labor room of Baghdad Teaching Hospital between May and October 2018. Blood was withdrawn from their mothers for lead analysis. Five milliliters (ml) of cord blood was taken, 3 ml was used for testosterone and estradiol analysis (using enzyme-linked immunosorbent assay) and 2 ml for lead measurement by lead care analyzer. Newborns weight and head circumference were measured. Delivered women were divided into four gro

Fifty-four Sprague-Dawley albino adult male rats were classified into three main groups each of 18 rats treated for a particular duration (1,2, and 4) weeks respectively. Each group was subdivided into three subgroups each of six rats treated as follows; group (1) serve as normal control, group (2, and 3) intra-peritoneal treated with TiO₂NPs (50,200) mg/kg respectively, body *weight of all rats was measured before and after the experiment, then rats were dissected at the end of each experiment and the weights of the thyroid was measured. The result showed a highly significant decrease (p<0.01) in thyroid gland weight, a highly significant increase (p<0.01) in body weights and TSH, while a highly significant decrease (p&

Objective(s): The aim of the study was to identify the prevalence of overweight and obesity in adolescence and
to estimate the effect of socio- demographic and health behaviors that predicting obesity in adolescents.
Methodology: A cross-sectional descriptive study was being carried out at three public Arabic secondary
schools in Erbil city from October 1
st 2010 to January 30th 2011. A systematic randomly sample size of 461 students
was selected.
Results: In this study, the age of (46.2%, 122) of males students were ranged between (17- 18.9) years old compared
to females students (74.1%, 146) their age ranged between (15 -16.9) years old. About (3.4%, 9) of males
adolescents having overweight while all female ado

In this paper, we propose a new approach of regularization for the left censored data (Tobit). Specifically, we propose a new Bayesian group Bridge for left-censored regression ( BGBRLC). We developed a new Bayesian hierarchical model and we suggest a new Gibbs sampler for posterior sampling. The results show that the new approach performs very well compared to some existing approaches.

Feature extraction provide a quick process for extracting object from remote sensing data (images) saving time to urban planner or GIS user from digitizing hundreds of time by hand. In the present work manual, rule based, and classification methods have been applied. And using an object- based approach to classify imagery. From the result, we obtained that each method is suitable for extraction depending on the properties of the object, for example, manual method is convenient for object, which is clear, and have sufficient area, also choosing scale and merge level have significant effect on the classification process and the accuracy of object extraction. Also from the results the rule-based method is more suitable method for extracting

     The present study investigates the implementation of machine learning models on crop data to predict crop yield in Rajasthan state, India. The key objective of the study is to identify which machine learning model performs are better to provide the most accurate predictions. For this purpose, two machine learning models (decision tree and random forest regression) were implemented, and gradient boosting regression was used as an optimization algorithm. The result clarifies that using gradient boosting regression can reduce the yield prediction mean square error to 6%. Additionally, for the present data set, random forest regression performed better than other models. We reported the machine learning model's performance using Mea

Rate of zinc consumption during the cathodic protection of copper pipeline which carries saline water was measured by weight loss technique in the absence and presence of bacteria. Variables studied were solution flow rate, temperature, time and NaCl concentration. It was found that within the present range of variables; the rate of zinc consumption increases with the increase of all operating conditions. The presence of bacteria increases the zinc consumption. Fourth order multi-term model and one-term model were suggested to represent the consumption data. Nonlinear regression analysis was used to estimate the coefficients of these models, while statistical analysis was used to determine the effect of each coefficient. Both models were re