In this study, 158 clinical samples were collected from hospitalized burn patients during the period from December 2012 to June 2013 in Karbala province\ Iraq. Bacterial isolates were identified using conventional biochemical tests and then identification was confirmed by using Vitek-2 compact system. Pseudomonas aeruginosa recovery was 60 isolates in this study. These isolates were analyzed for antibiotic susceptibility by the disk diffusion test (DDT) according to Kirby Bauer's method using seven clinically important antipseudomonal agents: carbapenems (Imipenem and Meropenem), pencillins (Piperacillin), cephalosporins (Ceftazidim), monobactam (Aztreonam), quinolones (Ciprofloxacin) and aminoglycosides (Gentamicin). The results of resista

This research aims to reveal the impact of applying a teaching course in
gaining and preserving information by female students comparing with the
traditional method, through testing the two following hypotheses:
1. There is no difference with statistical significance at the level of
significance (0.05) between the average grades achieved by the
experimental group of female students taught using a teaching course,
and the control group of female students taught using the traditional
method.
2. There is no difference with statistical significance at the level of
significance (0.05) between the average grades achieved by the
experimental group of female students taught using a teaching course,
and the contro

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

Diabetic kidney disease (DKD) is caused by a variety of processes. As a result, one biomarker is insufficient to represent the complete process. This study Evaluate the diagnostic value of serum kidney injury molecule-1(KIM-1) and cystatin C (CysC) as early biochemical markers of DKD and predictive their sensitivities and specificities as biomarkers of nephropathy in Iraqi type 2 diabetic (T2DM) patients. This cross-sectional study include 161 T2DM patients from Diabetes and Endocrinology Center at Merjan medical city in Babylon. Patients divided according to urinary albumin creatinine ratio(ACR) (Group1:ACR≤30mg/g,Group2:ACR>30mg/g). Random spot urine and fasting blood samples were taken from each patient and urinary ACR, bloo

In the course of generating a library of open-chain epothilones, we discovered a new class of small molecule anticancer agents that has no effect on tubulin but instead kills selected cancer cell lines by harnessing reactive oxygen species in an iron-dependent manner.