The aims of study is to detect the inhibitory effect of Saccharomyces boulardii and Lactobacillus acidophilus on Escherichia coli that has been isolated from recurrent urinary tract infection in women. The sensitivity of E.coli isolates to antibiotics had been studied and the most resistant E.coli isolate to antibiotics had been studied .The cup assay was used on nutrient agar and Muller-Hinton agar to detect the inhibitory activity for each S.boulardii yeast grown on YEGP media and L.acidophilus grown on MRS media in which the result showed a high inhibition activity for each of them .Also in this study the adhesion property of E.coli had been evaluated in the presence of S.boulardii at concentration of 1×109 and L.acidophilus at conc

n this work, the effect of gamma rays on blood thinning drugs was studied using the drug (Aspirin), where gamma rays were spread with the drug using a radioactive source (Co60), and 15,000 grams of Aspirin were placed in the device (gamma chamber 900). The drug was subjected to different irradiation doses (5 KGy, 10 KGy, 15 KGy) and the amount of absorption of the drug was observed in the gamma for different doses and the study of x-rays. After confirming the absorption of the drug to radiation, the effect of the drug on blood thinning was calculated using the rat model and compared with the same drug and the same dose but without exposing the drug to radiation and comparing all results with the control group. The way drugs absorbed radiati

Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

After baking the flour, azodicarbonamide, an approved food additive, can be converted into carcinogenic semicarbazide hydrochloride (SEM) and biurea in flour products. Thus, determine SEM in commercial bread products is become mandatory and need to be performed. Therefore, two accurate, precision, simple and economics colorimetric methods have been developed for the visual detection and quantitative determination of SEM in commercial flour products. The 1st method is based on the formation of a blue-coloured product with λmax at 690 nm as a result of a reaction between the SEM and potassium ferrocyanide in an acidic medium (pH 6.0). In the 2nd method, a brownish-green colored product is formed due to the reaction between the SEM and phosph

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob