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

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: Alternative natural therapy by plants extracts had opened  wide  door   for   the    use  of  natural products as an alternative therapy instead of many antibiotics and drugs , which had many harmful side effects.Also, an increased interest has been centered on the industrial wastes, especially plant raw materials which contain phenols (e.g. Pomegranate peel and Bay leaves) which is a sources of natural antioxidants ,which are on the contrary  of  synthetic  antioxidants that  had restrict use  due to  their  health  risks , carcinogenesis and toxicity .

Objectives :This study was done to fi

This paper presents seven modified Adomian Decomposition Method (ADM) techniques for efficiently solving initial value problems, especially those involving non-homogeneous and nonlinear differential equations. While the classical ADM is effective for linear homogeneous cases, it has difficulties solving more complex problems. The proposed modifications—from MADM1 to MLADM—include Maclaurin and Taylor expansions, Laplace transforms, and single-step iterations.• These modifications enhance convergence, reduce complexity, and improve accuracy.• Each method offers specific advantages, such as accelerating convergence (MADM2, RADM4), simplifying computation (TSADM5), and achieving higher accuracy (MLADM).• Numerical examples confirm th

In the present work, Response Surface Methodology (RSM) was utilized to optimize process variables and find the best circumstances for indirect electrochemical oxidation of mimicked wastewater to remove phenol contaminants using prepared ternary composite electrode. The electrodeposition process is used for the synthesis of a ternary composite electrode of Mn, Co, and Ni oxides. The selected concentrations of metal salts of these elements were 0.05, 0.1, and 1.5 M, with constant molar ratio, current density, and electrolysis time of 1:1:1, 25 mA/cm2, and 2 h. Interestedly, the gathered Mn-Co-Ni oxides were deposited at both the anode and cathode. X-ray diffraction (XRD) and scanning electron microscopy (SEM) facilitated the qualitative char

Back ground: Several devices with different physical bases have been developed for the clinical measurement of corneal thickness, they classified into 4 categories: Scheimpflug photography based, Slit –Scanning topography, optical coherence tomography (OCT) based and ultrasound (US) based.Objective:To evaluatethe precision of the new Scheimpflug –Placido disc corneal topography in measurement of corneal thickness and to compare the measured values with that obtained by US pachymetry.Methods: Setting of this study is Lasik center in Eye Specialty Private Hospital. Baghdad. Iraq.Eyes of healthy subjects were examined with the Sirius topography.3 consecutive measurements of central (CCT)and thinnest (TCT) corneal thicknesses were obtain

Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti

Infection with the protozoan parasite Toxoplasma gondii is widely prevalent in humans and animals. Infection with Toxoplasma may associate with miscarriage in many pregnant women due to infection. In this study, the level of lutetropic hormone (LTH), folliclestimulating hormone (FSH) and luteinizing hormone (LH) was measured in pregnant women suffering from toxoplasmosis using mini-VIDAS®technique. Results showed that pregnant women have high concentration of both LTH and FSH hormone(10.80 ± 6.53) ng/ml and (9.51 ± 2.40) μIU/ml respectively, while the concentration of LH hormone was lower than normal(4.49 ± 0.56) μIU/ml. Such finding is to suggest that infection with T. gondii is interfering with these hormones in pregnant women.

The importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h