The present study deals with the effect of teaching speaking Strategies (SS) on EFL Iraqi College students. The use of speaking strategies not only solves learners’ communication problems, but also enhances the learner’s interaction in target language, and improves their oral proficiency .The aim of the study is to find out the effect of teaching SS used by EFL College students .The learner of the first stage is population of the study at the Department of English, College of Education /Ibn-Rushd .The sample consists of (60) students distributed on experimental group(A) as well as control group(B) each group contains (30) students . In order to achieve the aim of the study, questionnaire has been constructed to be taught on the experime

This study was aimed to evaluate the effect of spraying nano chitosan loaded with NPK fertilizer and nettle leaf and green tea extracts on the growth and productivity of potato for the spring and fall seasons of 2021.It was conducted at private farm in Wasit Governorate, Iraq, as a factorial experiment (5 × 5) within randomized complete block design using three replicates. The first factor included spraying with four concentrations of chitosan nanoparticles loaded with NPK fertilizer 0, 10. 15 and 20% in addition to chemical fertilization treatment, the second factor was spraying nettle leaf extract 25 and 35 gL-1 and green tea extract with 2 and 4 g.L-1, in addition to the control treatment, spraying with distilled water only. The

Albizia lebbeck biomass was used as an adsorbent material in the present study to remove methyl red dye from an aqueous solution. A central composite rotatable design model was used to predict the dye removal efficiency. The optimization was accomplished under a temperature and mixing control system (37?C) with different particle size of 300 and 600 ?m. Highest adsorption efficiencies were obtained at lower dye concentrations and lower weight of adsorbent. The adsorption time, more than 48 h, was found to have a negative effect on the removal efficiency due to secondary metabolites compounds. However, the adsorption time was found to have a positive effect at high dye concentrations and high adsorbent weight. The colour removal effi

Albizia lebbeck biomass was used as an adsorbent material in the present study to remove methyl red dye from an aqueous solution. A central composite rotatable design model was used to predict the dye removal efficiency. The optimization was accomplished under a temperature and mixing control system (37?C) with different particle size of 300 and 600 ?m. Highest adsorption efficiencies were obtained at lower dye concentrations and lower weight of adsorbent. The adsorption time, more than 48 h, was found to have a negative effect on the removal efficiency due to secondary metabolites compounds. However, the adsorption time was found to have a positive effect at high dye concentrations and high adsorbent weight. The colour removal effi

Academic chemical laboratories (ACL) are considered public places  the employees come in contact with a variety of pollutants. The aim of the current study was to detect heavy metals levels in the indoor air of ACL in two universities in Baghdad city and assess their levels in the academic employees’ scalp hair as biomarkers. Air samples inside ACL were collected to detect Fe, Cd, Zn, Pb and Cu. Scalp hair samples were collected from 40 adult chemical laboratory employees aged 30-60 years, who worked 5 days/week for 6 hours a day. Personal information relating to employees such as age, duration of exposure, smoking habit and sex, was collected as a questionnaire. The results of this study concluded that academic laboratory employ

In this study, a proposed process for the utilization of hydrogen sulphide separated with other gases from omani natural gas for the production of sulphuric acid by wet sulphuric acid process (WSA) was studied. The processwas simulated at an acid gas feed flow of   5000 m³/hr using Aspen ONE- V7.1-HYSYS software. A sensitivity analysis was conducted to determine the optimum conditions for the operation of plant. This included primarily the threepacked bed reactors connected in series for the production of sulphur trioxidewhich represented the bottleneck of the process. The optimum feed temperature  and catalyst bed volume for each reactor were estimated and then used in the simulation of the whole process for tw

Abstract Objective: To identify correlation of elevated LDH & CRP levels with the outcomes of COVID-19. Methodology: The cross-sectional retrospective study consisted of 200 COVID-19 patients who presented at a private clinical in Baghdad, Iraq. It was carried out from February 2021 to February 2022. Data included age, gender and clinical presentation. Blood samples were taken for high sensitivity CRP and LDH in the serum. Results: Out of 200 patients, 50 were critical and 150 severe according to clinical features. LDH and CRP showed a significant increase (p=0.000) in critical patients. This group involved admission to the respiratory intensive care unit requiring mechanical ventilation than in patients with severe COVID-19 (760.5±6.3 vs.

Objective: The approximate life span of a silicone maxillofacial prosthesis is as short as1.5–2 years of clinical service, then a new prosthesis should be fabricated. The most common reasonfor re-making the prosthesis is silicone mechanical properties degradation. The aim of this studywas to assess some mechanical properties of VST-30 silicone for maxillofacial prostheses after addi-tion of intrinsic pigments.Methods: Two types of intrinsic pigments (rayon flocking and burnt sienna); each of them wasincorporated into silicone. One hundred and twenty samples were prepared and split into 4 groupsaccording to the conducted tests (tear strength, hardness, surface roughness, and tensile strengthand elongation percentage) with 30 samples for ea

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an