Four major factories (Petroleum Refineries Company, Detergents Plant, Thermal Power Plant, and Gaseous Power Plant) are located to the north of Baiji City. They release pollutants in form of gases, liquids and solids; they find their way to the surrounding environment. To assess the environmental pollution of the area, 18 samples of surface soil distributed around the industrial establishments were collected and analyzed to determine the concentration of polycyclic aromatic hydrocarbons (PAH) components which are often targets in the environmental checking. Identification and quantification of the 16 PAHs components was accomplished using High Performance Liquid Chromatography (HPLC) had a model Shimadzu LC-10 AVP. The total concentratio

The aim of this study is interpretation well logs to determine Petrophysical properties of tertiary reservoir in Khabaz oil field using IP software (V.3.5). The study consisted of seven wells which distributed in Khabaz oilfield. Tertiary reservoir composed from mainly several reservoir units. These units are : Jeribe, Unit (A), Unit (A'), Unit (B), Unit (BE), Unit (E),the Unit (B) considers best reservoir unit because it has good Petrophysical properties (low water saturation and high porous media ) with high existence of hydrocarbon in this unit. Several well logging tools such as Neutron, Density, and Sonic log were used to identify total porosity, secondary porosity, and effective porosity in tertiary reservoir. For

AI in teaching English is reshaping language learning. While interest in AI-supported education is growing worldwide, research in this area is still emerging in Iraq. This review synthesizes empirical AI-based intervention studies to enhance English language learning in Iraqi higher education, and the perceptions of stakeholders regarding AI tools in language instruction. The reviewed intervention studies, comprising studies employed different AI platforms to support grammar instruction, speaking fluency, writing feedback, and pragmatic competence. These interventions yielded improvements in learners’ performance, motivation, and communicative confidence. In parallel, perception-focused studies revealed positive attitudes toward A

Background: One of the significant public health problems is the traumatic dental injury to the anterior teeth, it has a great impact on children’s daily. Physical and psychological disturbance, pain and other negative impacts, such as tendency to avoid laughing or smiling may be associated with traumatic dental injuries, that may affect the social relationships. To determine the occurrence of traumatic dental injuries in relation to quality of life, this study was established among children of primary schools. Material and Methods: A cross-sectional study was conducted among private (574) and governmental (1026) primary school children in Baghdad city. Dental trauma was assessed according to Ellis and Davey classification in1970

Background: The incidence of oral cancers is increasing all over the world. Early detection ofthis important public health matter makes them more amenable to treatment and allows the greatest chance of cure.The aim of this study was to investigate the awareness and knowledge on oral cancer among final -year dental students in Iraq. Materials and methods: Questionnaires were delivered to 160 final–year dental students in the College of Dentistry in Baghdad. The questionnaire focused on the awareness/knowledge of oral cancer, earlyand common clinical signs and symptoms andassociated risk factors. Results: It was found that 87% of students were aware of oral cancer. The followings were recognized as signs and symptoms of oral cancer: persis

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