The technology of subsurface soil water retention (SWRT) uses a polyethylene ‎trough that is fixed under the root zone of the plant. It is a modern technology to increase the values of water ‎use efficiency, plant productivity and saving irrigation water by applying as little irrigation water ‎as possible. This study work aims at improving the crop yield and water use efficiency of a cucumber plant with less applied irrigation water by installing membrane trough below the soil surface. The field experiment was conducted in the Hawr Rajab District of ‎Baghdad Governorate in Winter 2018 for testing various trickle irrigation ‎systems. Two agricultural ‎treatment plots were utilized in a greenhouse for the compa

In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

Breast cancer is a disease in which cells in the breast grow out of control. CD200 is a cell surface glycoprotein expressed on many cells, it belongs to the immunoglobulin family (Ig) and have a great role in the regulation of inflammation in autoimmunity. CD200 is the ligand for CD200R1 receptor. To determine if serum level of CD200 and its receptor CD200R1 can be used as a diagnostic and prognostic marker in patients with breast cancer.This case control study was carried out at Oncology Teaching Hospital – Medical city in Baghdad. Six groups were enrolled, four groups were confirmed with breast cancer stage (I, II, III and IV), fifth group (benign) and sixth group was control (healthy individual). Serum is divided to me

In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

    The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible models of parametric models and these models were nonparametric models.

    In this manuscript were compared to the so-called Nadaraya-Watson estimator in two cases (use of fixed bandwidth and variable) through simulation with different models and samples sizes.  Through simulation experiments and the results showed that for the first and second models preferred NW with fixed bandwidth fo

Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

The haplotype association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease.Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls.It starts with inferring haplotypes from genotypes followed by a haplotype co-classification and marginal screening for disease-associated haplotypes.Unfortunately,phasing uncertainty may have a strong effects on the haplotype co-classification and therefore on the accuracy of predicting risk haplotypes.Here,to address the issue,we propose an alternative approach:In Stage 1,we select potential risk genotypes inste

The current study was conducted to demonstrate the effects of air pollution on different biochemical parameters inCitrus aurantium plant and calculation the Air Pollution Tolerance Index (APTI). Five sites were selected tocollect plant leaves, four of them within the city of Baghdad, namely Al-Jadriya, Al-Andlous, Al-Doura and closeto the private generators to represent the urban areas and Abu Ghraib site to represent the rural area. Seasonalsamples were collected for the period from October 2016 to June 2017. Eleven biochemical parameters totalchlorophyll, ascorbic acid, leaf extract pH, relative water content, total nitrogen, total protein content, total sugarcontent, proline, electrical conductivity, cadmium and lead. The results of Citr

Background: Medical students often face substantial psychological stress, which can increase the risk of substance use, professional detriment, and insufficient patient care. However, substance use in medical students remains understudied in Iraq. This study highlights the prevalence, patterns, risk factors, and negative effects of substance use among medical students at the University of Baghdad. A cross-sectional study involving 414 medical students at the University of Baghdad was conducted. The questionnaire included sociodemographic variables and the Alcohol, Smoking, and Substance Involvement Screening Test to screen for psychoactive substance use. The lifetime prevalence of substance use was 38.9%. Among substance users, 42.8