Aim: This study aims to determine both the level  of knowledge, attitude, and practice  in clinical breast examination in women and the relationship between knowledge and practice.Data collection was performed within a three-month period starting from February 2019 on.  Subjects and Method: A cross-sectional analytical study included 657 non-randomly selected women visiting primary health care centers in Baghdad city with an average of age between (20-59) years old.  Results: Only 51.8% ever heard of clinical breast examination. The mean knowledge score for clinical breast examination was (51.2±44). Only 5.5% of women performed regular clinical breast examinations. Participants who adequately practice clinical breast examinatio

Trials were carried out in the middle of Iraq ( 3 different sites ) during 2009 to detecation and determined the seasonal occurrence of Agriotes lineatus L. Three YATOR funnel traps were used in each of these sites which baited with the specific pheromone of A. lineatus from the first of March to the end of October in the College of Agriculture - Abu- Ghraib / Provenance of Baghdad and AL-Nile / Provenance of Babylon , while in AL-Radhwania was used through May- June. Pheromone dispenser were changed every 6 weeks in each of these traps . Males of A. lineatus were found in all of the three sites , and the total number capture were 208 , 897 and 57 male / 3 traps / season in College of Agriculture , AL-Nile and AL-Radhwania respectiv

Artichoke (Cynara scolymus L.) is a nutritious vegetable that grown all over the world. It is a promising herbal plant, rich in bioactive components. It is considered as medicinal plant due to its nutritional and phytochemical composition, especially high proportion of phenolic compounds. The primary aim of this study was to achieve chemical profile analyses of artichoke for different phytochemcials, especially Scolymoside and Cynaroside. Methanolic crude was extracted from Artichoke leaves by rotary evaporator and separated by column chromatography. The fractions monitored by Thin Layer Chromatography (TLC), and identified in High-Pressure Liquid Chroma

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

Theresearch took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide a practical evident that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial andthat includes all of them spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. Spatial analysis had

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

Background: Dental caries is the most common oral problem, although dental caries is not life threating, it has aharmful effect on quality of life. Socioeconomic factors were found to be strong predictors of the prevalence of oral diseases in children, likes family income, occupational prestige, and education. The aim of this study is to assess the effect of socioeconomic factors on occurrence dental caries in their children. Materials and methods: The sample consists of 550 kindergartens children aged between (4-5) years were selected randomly, girls and boys. The kindergartens selection was randomly from different geographical areas in Al-Najaf governorate. Information was taken from children's parents using questionnaire with the help o