Abstract

The aim of this research is to determine how well the Cubing Technique affects the Iraqi EFL students' composition writing, vocabulary, and meta-cognitive awareness of writing strategies. The sample of (64) secondary-school female students in the fifth grade is drawn from two classrooms and split into two equal groups: the experimental group and the control group, each of which consists of (32) students. A quasi-experimental design is applied. The performance test and Meta-cognitive Writing Strategies questionnaire are given as a pre-test for equalizing the two groups after ensuring their validity and reliability. Then, they are administrated as a posttest in both groups. According to the results, the si

The concentration of elements were analyzed of twelve cultivation medium (Peat moss, Perlite and Hermon) selected from Iraqi markets using X-ray fluorescence techniques. The analytical results show that the cultivation medium contained high concentration of (Na, Al, Si, S, K, Ca, Fe) and low concentration of (Mg, P, Cl, Ti, V, Cr, Mn, Co, Ni, Cu, Zn). The samples also contained trace concentration of (Ge, As, Se, Br, Sr, Y, Mo, Cd, I, Hg, Pb, U). The results were compared using atomic absorption spectrophotometric technique for measuring the concentration of (K, Ca, Cu, Mn, Zn, Pb).

The Results showed that there is significant difference in the concentration of each element in most of the samples. The concentrations of elements a

     The study area is encompassed by the 33.59-34.93°N latitudes and 45.44-46.39°E longitudes and divided into four groups with respect to earthquake event locations. We determined fault plane solutions, moment magnitudes, focal depths, and trend of slip with the direction of the moment stress axes (P, N, and T) for 102 earthquakes. These earthquakes had a local magnitude in the range between 4.0 and 6.4 for the time period from January 2018 to the end of August 2019, with focal depths ranged between 6 and 17 km. Waveform moment tensor inversion technique was used to analyze the database constructed from seismic stations on local and neighboring country networks (Iraq, Iran, and Turkey). We separated the studie

This study offers the elastic response of the variable thickness functionally graded (FG) by single walled carbon nanotubes reinforced composite (CNTRC) moderately thick cylindrical panels under rotating and transverse mechanical loadings. It’s considered that, three kinds of distributions of carbon nanotubes which are uniaxial aligned in the longitudinal direction and two functionally graded in the transverse direction of the cylindrical panels. Depending on first order shear deformation theory (FSDT), the governing equations can be derived. The partial differential equations are solved by utilizing the technique of finite element method (FEM) with a program has been built by using FORTRAN 95. The results are calculat

In this work, the effect of different particle size on the nonlinear optical properties of silver nanoparticles in de-ionized water was studied. The experimental observation of the far field diffraction patterns by CCD camera in two and three dimensions. The maximum change of nonlinear refractive index and the relative phase shift were calculated. The self-defocusing technique was used with a continuous-wave radiation from DPSS Blue laser .The wavelength is 473 nm with an output power of 270 mW. All the Ag colloids samples containing the sizes 15, 30, 50, and 70 nm of silver nanoparticles used in the study were chemically prepared. It was found that the nonlinear refractive index is a particle size dependent and of the order of 10-7 cm2/

   Genetic diversity was studied in 31 Iraqi common reed samples , which were collected from Iraqi marshes in Basrah , Messan and Thi-Qar provinces and also from different areas in Baghdad province . Random amplified polymorphic DNA (RAPD) technique was used for evaluation of genetic diversity between collected samples . Seven primers were used for polymorphism detecting between common reed samples . The results revealed 102 bands for the all samples when RAPD-PCR was used . The percentage rate for the monomorphic bands is 6.86% , while the percentage rate for the polymorphic bands is 93.13% , and the numbers of these bands are ranging between 10 to 17 for each used primer .  The UBC1 primer gave the highest number of poly

Background: Penetrating neck injuries are common problem in our country due to increasing violence, terrorist bombing and military operations.
These injuries are potentially life threating and need great attention and proper management.
Objective: The aim of this study is to focus on the importance of anatomical zonal classification of the neck in the management of penetrating injuries of the visceral compartment of the Neck.
Methods :70 patients with various injuries who were managed at causality unit and Otolaryngology department in Al-Kindy Teaching Hospital during aperiod from January 1st 2015 to October 31st 2015.
The study carried on those patient depending on proper clinical examination and their urgent management.

 The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine

    In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne