Abstract
Objective: To assess pregnant women Knowledge toward Urinary Tract Infection at Kirkuk City.

Methodology: A descriptive and analytical study was conducted from 1st of November 2013 and up to the 19 th of August 2014 in five typical primary health care centers at Kirkuk City. A Probability (randomly sample) was used to select the sample of 180 women aged (15-44) years. A questionnaire format was used as a tool for data collection , content validity of the questionnaire achieved through reviewing it by (24) experts in numerous scientific fields and reliability of the questionnaire was determined through a pilot study. Descriptive and inferential statistics were used to analyze the data.

Resul

This study was performed on the Tigris River (Baghdad city section) during the period between December 2016 and December 2018 to assess seasonal variation in water quality using the Overall Index of Pollution (OIP). The OIP is one of the reliable tools for the assessment of surface water quality. To calculate OIP-values, eight parameters were measured ( pH, Dissolved Oxygen "DO", Biological Oxygen Demand "BOD", Total Dissolved Solid "TDS", Total Hardness "TH", calcium "Ca", Sulphate "SO4" and Alkalinity). The results showed the anthropogenic activities impact of Baghdad population that directly discharge of "inadequate treated" waste water to the river.  OIP values were acceptable (1˃OIP˃ 1.7) in 2011, 2012, 2013 and 2018. However, in

Using zooplankton as bioindicators, this study evaluates the ecological condition of the Euphrates River in Iraq's Babylon Province. Site 1 (North Hillah, next to the old Babylon ruins), Site 2 (Hillah city center), Site 3 (South Hillah, close to Al-Mahaweel), and Site 4 (near Al-Kifl town) were the four monitoring locations chosen along the river. The highest and lowest averages of the measured physical and chemical factors indicate temperature (25.1°-29.4°), pH (7.2-7.9), electrical conductivity (EC) (940 µS/cm-1241µS/cm), total dissolved solids TDS (591 mg/L-789mg/L), dissolved oxygen (DO) (5.6 mg/ l-7.1 mg/L), biological oxygen demand (BOD5) (2.4mg/L-4.2 mg/L), nitrate (1.3 mg/L–3.2 mg/L), nitrite (0.04 mg/L–0.13 mg/L),

Due to the urgent need to develop technologies for continuous glucose monitoring in diabetes individuals, poten tial research has been applied by invoking the microwave tech niques. Therefore, this work presents a novel technique based on a single port microwave circuit, antenna structure, based on Metamaterial (MTM) transmission line defected patch for sensing the blood glucose level in noninvasive process. For that, the proposed antenna is invoked to measure the blood glu cose through the field leakages penetrated to the human blood through the skin. The proposed sensor is constructed from a closed loop connected to an interdigital capacitor to magnify the electric field fringing at the patch center. The proposed an tenna sensor i

The extraction of Cupressus sempervirens L. or cypress essential oil was studied in this paper. This cypress oil was extracted by using the hydro-distillation method, using a clevenger apparatus. Cupressus sempervirens L. leaves were collected from Hit city in Al-Anbar province – Iraq. The influences of three important parameters on the process of oil extraction; water which used as a solvent to the solid ratio (5:1 and 14:1 (ml solvent/g plant), temperature (30 to 100 °C) and processing time, were examined to obtain the best processing conditions to achieve the maximum yield of the essential oil. Also, the mathematical model was described to calculate the mass transfer coefficient. Therefore, the best conditions, that were obtained in

The research aims to identify the extent to which Iraqi private banks practice profit management motivated by reducing the taxable base by increasing the provision for loan losses by relying on the LLP it model, which consists of a main independent variable (net profit before tax) and independent sub-variables (bank size, total debts to total equity, loans granted to total obligations) under the name of the variables governing the banking business. (Colmgrove-Smirnov) was used to test the normal distribution of data for all banks during the period 2017-2020, and then find the correlation between the main independent variable sub and the dependent variable by means of the correlation coefficient person, and then using the multiple

In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor

Oryza sativa japonica (ofada rice) is largely grown in Aramoko, Abakaliki and Ofada are communities and consumed by both the poor and rich in Nigeria. A total of twenty ofada rice farmlands were identified in each study area and rice samples were randomly collected, thoroughly mixed to make a representative sample from each farmland. Soil samples were collected in each farm to a depth of 5-15cm from at least eight different points and thoroughly mixed together to form a representative sample. The samples were thereafter taken to the laboratory for preparation and spectroscopic analysis. A well-calibrated NaI(Tl) gamma-ray detector was used in spectrometric analysis of the samples and descriptive statistics was used to analyze th

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This