Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

Background: Undergraduate dental students are more susceptible to situations of stress that affected quality of sleep, such profiles of stress may result in sleep bruxism and/or awake bruxism, parafunctions that can affect oral and general health. The aim of the study was to evaluate the association of sleep bruxism, awake bruxism and sleep quality among dental students. Materials and methods: A cross-sectional study was performed including 260 Iraqi dental students from university of Baghdad aged from 20to25years old. Students enrolled in the third and fifth class participated in the study. The Pittsburgh Sleep Questionnaire Index (PSQI) was used for data collection. The PSQI was distributed during lecture classes. Sleep bruxism and awake

BACKGROUND: Preeclampsia (PE) is a possible etiology of obstetrical and neonatal complications which are increased in resource-limited settings and developing countries. AIM: We aimed to find out the prevalence of PE in Iraqi ladies and specific outcomes, including gestational weight gain (GWG), cesarean section (CS), preterm delivery (PD), and low birth weight (LBW). METHODS: All singleton pregnant women visiting our tertiary center for delivery were involved over 3 years. PE women were compared with non-PE ladies. Complete history and examination were done during pregnancy and after delivery by the attending obstetrician and neonatologist with full documentation in medical records. RESULTS: PE prevalence was 4.79

     Two field experiments were performed to study the response of two species , Nigella sativa L. and Nigella arvensis L. within different sowing dates at spring and autumn seasons which included 1^st and 20^th March, 10^th April and 1^st May for spring season, while the sowing dates for the autumn season were, 2^nd November, 21^st November, 11^th December, 31^stDecember and 20^thJanuary. Both experiments conducted according to the Completely Randomized Block Design (CRBD) within three replications at hallabja/Kurdistan Region, located [35^°12'48.7^"N; 45^°57'34.4^"

   Analyzing the size of the interrelationships between the main economic sectors in the Iraqi economy is an important necessity to know the impact of each sector on other economic sectors on the basis of the interrelationships and reciprocity between them, and what these relationships have achieved in terms of enhancing development and increasing the gross domestic product. To achieve the objectives of the study, we relied on mathematical (quantitative) analysis using user-product tables. Issued by the Ministry of Planning / Central Bureau of Statistics and Research (Directorate of National Accounts) for the economic sectors that make up the Iraqi economy. The study conc

In Iraq, because of the dramatic turnovers facing the country for three decades, pharmacists continue to experience significant professional challenges in both the public and private sectors. The present study aimed to explore the professional challenges and obstacles facing Iraqi pharmacists working in public hospitals. This qualitative study included face-to-face semi-structured interviews with open-ended questions with hospital pharmacists. The participants were selected purposefully (with ≥ 3 years of experience) to work at governmental hospitals in Karbala province between December 2022 and April 2023. The audio-recording interviews were scripted. Thematic analyses were used to generate themes and subthemes from the interview

Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy