ER Abbas, AA Jasim, Journal of Physical Education, 2023 - Cited by 1

Antibiotic resistance is a problem of deep scientific concern both in hospital and community settings. Rapid detection in clinical laboratories is essential for the judicious recognition of antimicrobial resistant organisms. So, the growth of Uropathgenic Escherichia coli (UPEC) isolates with Multidrug-resistant (MDR) and Extensively Drug-resistant (XDR) profiles that thwart therapy for (UTIs) has been detected and has straight squeezed costs and extended hospital stays. This study aims to detect MDR- and XDR-UPEC isolates. Out of 42 UPEC clinical isolates were composed from UTI patients. The bacterial strains were recognized by standard laboratory protocols. Susceptibility to antibiotic was measured by the standard disk diffusi

Historically, medicinal herbs have been utilized as an important origin of chemicals with particular therapeutic potentials, and they continue to be a great place to find new medication candidates. Parthenocissus quinquefolia L. is a member of the grape-growing family Vitaceae. It is indigenous to Central and North America. It is widely dispersed in Iraqi gardens and plant houses from north to south. Traditionally, it has many uses, like relieving constipation, treating jaundice, expectorant, emetic, and others. At the same time, its proven activities include antioxidant activity, antimicrobial, anti-diabetic, thrombin inhibitor effect, and medicine for treating eyelid eczema. Parthenocissus quinquefolia contains valuable phytochemicals lik

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

Background: Because of wide use of Functional Endoscopic Sinus Surgery (FESS) technique in the recent years and basic role of coronal computed tomography (CT) scan in demonstrating the normal drainage route of para-nasal sinuses, identifying the major patterns of inflammatory sinonasal disease and accompanied anatomical variations is essential for appropriate preoperative surgical planning. In review of publisthed literature, there is no data on CT patterns of chronic inflammatory sinonasal disease and their accompained anatomical variations of nose and PNS in our local population.Objectives: was to determine the frequency of CT patterns and variations in patients with sinonasal symptoms.Methods: This was a cross sectional descriptive st

AI in teaching English is reshaping language learning. While interest in AI-supported education is growing worldwide, research in this area is still emerging in Iraq. This review synthesizes empirical AI-based intervention studies to enhance English language learning in Iraqi higher education, and the perceptions of stakeholders regarding AI tools in language instruction. The reviewed intervention studies, comprising studies employed different AI platforms to support grammar instruction, speaking fluency, writing feedback, and pragmatic competence. These interventions yielded improvements in learners’ performance, motivation, and communicative confidence. In parallel, perception-focused studies revealed positive attitudes toward A

Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th