The number of infections caused by microorganisms is increasing significantly over the last few years. A total of 140 patients admitted to the central teaching hospital of pediatrics from the 1st of Jun 2017 to 31 October 2017. The Clinical samples was processed from culture and sensitivity testing. Antibiotic discs used for gram negative isolates. The most prevalent gram negative isolates included Escherichia coli 63 (45.0 %), Pseudomonas spp. 21 (15.0 %), Klebsiella spp. 19 (13.6 %) predominantly. Escherichia coli were the most prevalent isolates from urine 45 (71.4 %), Klebsiella spp. 11 (57.9 %) and Enterobacter spp. 11 (68.8 %) followed by Escherichia coli 10 (15.9 %) predominant from blood. 68 (48.6 %) of specimens were urine, 47 (33.

Background: The emergence and spread of multidrug-resistant Gram-negative bacilliin burn wound infections related to biofilm formation, which lend to challenge in treatment with conventional antibiotics andprompting to search for novel antimicrobial agents to control the infections.Silver nanoparticles (AgNPs) have wide spectrum biological properties with different mechanisms of action and less toxicity towards human cells.

Objective:The goal of this study was to evaluated the anti-bacterial and anti-biofilm activities of AgNPs alone and in combination with aminoglycoside (Amikacin) and β-lactam (Ampicillin) antibiotics against multidrug resistant Gram-negative bacilli (Pseudomonas aeruginos

Mixture experiments are response variables based on the proportions of component for this mixture. In our research we will compare the scheffʼe model with the kronecker model for the mixture experiments, especially when the experimental area is restricted.

     Because of the experience of the mixture of high correlation problem and the problem of multicollinearity between the explanatory variables, which has an effect on the calculation of the Fisher information matrix of the regression model.

     to estimate the parameters of the mixture model, we used the (generalized inverse ) And the Stepwise Regression procedure

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

The aim of the present study is to highlight the role of total cholesterol (TC), triacylglycerol (TG), Glycated hemoglobin A1c and iron in Iraqi women with multiple sclerosis and also to examine the biochemical action of copaxone (which is the most widely used in the 21st century to treat multiple sclerosis) on these biochemical parameters. This is the first study in Iraq which deals copaxone action on TC , TG , HbA1c and iron. Ninety women in their fourth decade suffering from multiple sclerosis were enrolled in this study. They were divided into: the first (group B) composed of (30) women without any treatment related to multiple sclerosis or any treatment linked with chronic or inflammatory diseases. The second (group A1) included (30)

The Manganese doped zinc sulfide nanoparticles of the cubic zinc blende structure with the average crystallite size of about 3.56 nm were synthesized using a coprecipitation method using Thioglycolic Acid as an external capping agent for surface modification. The ZnS:Mn2+ nanoparticles of diameter 3.56 nm were manufactured through using inexpensive precursors in an efficient and eco-friendly way. X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and Fourier Transform Infrared (FTIR) spectroscopy are used to examine the structure, morphology and chemical composition of the nanoparticles. The antimicrobial activity of (ZnS:Mn2+) nanocrystals was investigated by measuring the diameter of inhibition zone using well diffusion mechanism