Escherichia coli has been recognized worldwide as the most common causative agent for severe infections of the urinary tract. Colibactin is a genotoxin produced through a gene cluster called polyketide synthase (pks) island by members of Enterobacteriaceae. Limited information is available about the frequency of colibactin in E. coli isolates in Iraq. Hence, this study aimed to examine the frequency of some colibactin genes (CIbA and CIbQ) in clinical isolates of E. coli obtained from urinary tract infections (UTIs) in Iraq. Between October 2023 and January 2024, 120 urine samples were collected from females diagnosed with UTIs in Iraqi hospitals. 70 E. coli isolates were isolated after identification by biochemical methods and confirmed by

ABSTRACT

Learning vocabulary is a challenging task for female English as a foreign language (EFL) students. Thus, improving students’ knowledge of vocabulary is critical if they are to make progress in learning a new language. The current study aimed at exploring the vocabulary learning strategies used by EFL students at Northern Border University (NBU). It also aimed to identify the mechanisms applied by EFL students at NBU University to learn vocabulary. It also aimed at evaluating the approaches adopted by EFL female students at Northern Border University (NBU) to learn a language. The study adopted the descriptive-analytical method. Two research instruments were developed to collect data namely, a survey qu

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The parliamentary election is one of the features of democratic systems that give individuals the right to participate in government and political election-making. Typically, the process of parliamentary elections received wide attention from media, as well as attention from large segments of the public because they understand the vast importance to assume political positions and associated fates of people and their destinies. Its importance comes from the fact that it allows citizens the right to participate in managing the public affairs by granting their confidence and voices to the elected president or his representatives in the parliamentary.
Media task is to emerge democratic societies, in particular, in the mission of urging p

Before introducing an accurate description of the publication of news about the Iraqi-British war in the press of the Great Iraqi revolution, it is necessary to note the importance of this research as it examines a remarkable phenomenon that lies at the heart of public attention at this particular time, where we live the repercussions of a new war similar, with some of its facts and activities, to the events of the Great Iraqi Revolution that broke out in many Iraqi cities. Therefore, the results of this research can be a starting point for new research characterization of the phenomenon of news coverage of war in the Iraqi press.

The importance of research in the press of the Great Iraqi Revolution, according to the well-known r

The aim of this study was to identify the effectiveness of using generative learning model in learning kinetic series on rings and horizontal bar in artistic gymnastics for men ,Also, the two groups were better in learning the two series of movements on the rings and horizontal bar . The experimental method was used to design two parallel groups with pretested and posttest .The sample included third graders at the College of Physical Education and Sports Sciences - University of Baghdad ,The third class (d) was chosen to represent the control group that applied the curriculum in the college, with (12) students per group. After conducting the tribal tests, the main experiment was carried out for (8) weeks at the rate of two units per week di

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

The purpose of this paper is to identify the statistical indicators of the searched variables and identify the relationship between the cognitive learning outcome and the performance of the two mastering skills by parallel spherical standing and equilibrium on the balance beam. And the identification of the percentage of the cognitive learning outcome contribution to the performance of the two mastering skills by parallel spherical standing and the equilibrium on the balance beam. The two researchers used the descriptive approach in the survey method and the correlational relations, being the most appropriate to the nature of the research problem. The research community for the second stage students in the College of Physical Education and

The effect of short range correlations on the inelastic longitudinal Coulomb form
factors for the lowest four excited 2+ states in 18O is analyzed. This effect (which
depends on the correlation parameter β) is inserted into the ground state charge
density distribution through the Jastrow type correlation function. The single particle
harmonic oscillator wave function is used with an oscillator size parameter b. The
parameters β and b are, considered as free parameters, adjusted for each excited state
separately so as to reproduce the experimental root mean square charge radius of
18O. The model space of 18O does not contribute to the transition charge density. As
a result, the inelastic Coulomb form factor of 18