In the present study, an attempt has been to develop a new water quality index (WQI) method that depends on the Iraqi specifications for drinking water (IQS 417, 2009) to assess the validity of the Euphrates River for drinking by classifying the quality of the river water at different stations along its entire reach inside the Iraqi lands. The proposed classifications by this method are: Excellent, Good, Acceptable, Poor, and Very poor. Eight water quality parameters have been selected to represent the quality of the river water these are: Ion Hydrogen Concentration (pH), Calcium (Ca), Magnesium (Mg), Sodium (Na), Chloride (Cl), Sulphate (SO_4), Nitrate (NO_3), and Total Dissolved Solids (TDS). The variation of the water quality parameters along the river have been represented by graphs using Excel.2013 software. The results revealed that the quality of the Euphrates River ranges from “Good” to “Poor”, it enters the Iraqi borders with “Good” water quality and gradually its quality begins to decrease after it receives pollution from many sources such as domestic sewage and different industrial effluents until its quality becomes “Poor” according to the proposed classification. Finally the proposed WQI can be used as a tool to assess the quality of the river with both place and time.
Abstract
This study aims to find the relationships between social capital (social network, social trust, shared goals) and knowledge sharing (knowledge Donating, knowledge collecting) as independent variables and their impact on improving the quality of educational services (academic staffs quality, Quality of teaching methods and study curriculums). This research is an important, because it attempts to identify the relationship between social capital and the knowledge sharing and their effect on improving the quality of educational service for universities. The study problem was determined in several questions related to the nature of the correlation relationship - the impact between the different independent variables (
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As the process of estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .
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Abstract
The effect of physical and mental health on the feelings of personal welfare are known as health-related quality of life. Infection with hepatitis B virus is a major global health problem. Health-related quality of life was emerged as an important consideration in the care of patients with chronic hepatitis B infection. The aim of the current study was to measure health-related quality of life among a sample of chronic hepatitis B patients in AL-Najaf city/Iraq. The current study was cross-sectional study carried out on (104) already diagnosed chronic viral hepatitis B patients who attended the Gastroenterology and Hepatology Center/Al-Sader Medical City/Najaf during November 2018 to May
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A factorial experiment was applied with four replicates on rosemary plants (Rosmarinus officinalis L.) grown in pots inside the glasshouse of the Department of Biology, College of Science, Salahaddin University, Erbil, Iraq, during April, 2019 to July, 2020, to determine the effects of soil moisture content ( SM1: 100% and SM2: 60% field capacity), nitrogen fertilizer (N1: 100, N2: 200 and N3: 300kg/hectare), and magnesium fertilizer (Mg1: 0.0, Mg2: 30 and Mg3: 60kg/hectare) and their interactions on some growth characteristics and essential oil content of rosemary plants. Two cuttings were taken from rosemary shoots (on March, 2020 and July, 2020) after 12 and 15 months of planting respectively. Results showed that cutting 1:
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