Forty one isolates of genus Proteus were collected from 140 clinical specimens such as urine, stool, wound, burn, and ear swabs from patients of both sex. These isolates were identified to three Proteus spp. P. mirabilis, P. vulgaris and P. penneri .The ability of these bacteria to produce L-asparaginase II by using semi quantitative and quantitative methods was determined. P. vulgaris Pv.U.92 was distinguished for high level of L-asparaginase II production with specific activity 1.97 U/mg. Optimum conditions for enzyme production were determined; D medium with 0.3% of L-asparagine at pH 7.5 with temperature degree 35°C for incubation. Ultrasonication was used to destroy the P. vulgaris Pv.U.92 cells then ASNase II was extracted and pu

The present study aims to detection optimal conditions of production of amylase enzyme from isolate of B. subtillis A4. Nine carbonic sources were represented by starch, maltose, fructose, sucrose, glucose, arabinose, xylose, sorbitol and mannitol) at concentration of 1% for each source. It was found that the best was represented by starch carbonic, which showed higher activity and qualitative activity of 7.647 Unit/ ml and 461.56 Unit/ mg. Ten nitrogen sources were selected, including yeast extract, peptone, trypton, gelatin, urea and meat extract as organic sources Ammonium sulphate, Sodium nitrate, Potassium nitrate and Ammonium chloride as inorganic sources. These sources were added at aconcentration of 0.5% to the production medium. Th

Abstract
This study aimed to survey fungi associated with the product Indomie and Chips being the trades Iargely by a very important segment of society who are the children, beside consumed by adults, but less so, as the survey results to accompany some fungui samples sterile showed proportions presence included various fungi like. Aspergillus flavus, Aspergillus niger, Penicillium Spp., Fusarium graminearum, F.moniliforme, Alternaria alternate and Rhizopus Spp., and other fungi sterile are not diagnosed. The results showed large dominion fungi A. niger by presence sterile samples of both producers, followed by infection in Fusarium Spp., Penicillium Spp., and A. alternata by infection percentage 55, 20 and 17% respectively for the pr

Urinary tract infection is a bacterial infection that often affects the bladder and thus the urinary system. E. coli is one of the leading uropathogenic bacteria that cause urinary tract infections. Uropathogenic E. coli is highly effective and successful in causing urinary tract infections through biofilm formation and urothelial cell invasion mechanisms. Other organisms that cause urinary tract infections include members of the Enterobacteriaceae family, streptococci and staphylococci species and perch. In addition, K.penumoniae is another important gram-negative bacterium that causes urinary tract infections. With the PCR technique, unseen bacterial species can be detected using standard clinical microbiology methods. In this study, the

In order to take measures in controlling soil erosion it is required to estimate soil loss over area of interest. Soil loss due to soil erosion can be estimated using predictive models such as Universal Soil Loss Equation (USLE). The accuracy of these models depends on parameters that are used in equations. One of the most important parameters in equations used in both of models is (C) factor that represents effects of vegetation and other land covers. Estimating land cover by interpretation of remote sensing imagery involves Normalized Difference Vegetation Index (NDVI), an indicator that shows vegetation cover. The aim of this study is estimate (C) factor values for Part of Baghdad city using NDVI derived from satellite Image of Landsat-7

Abstract  

  In this work, two algorithms of Metaheuristic algorithms were hybridized. The first is Invasive Weed Optimization algorithm (IWO) it is a numerical stochastic optimization algorithm and the second is Whale Optimization Algorithm (WOA) it is an algorithm based on the intelligence of swarms and community intelligence. Invasive Weed Optimization Algorithm (IWO) is an algorithm inspired by nature and specifically from the colonizing weeds behavior of weeds, first proposed in 2006 by Mehrabian and Lucas. Due to their strength and adaptability, weeds pose a serious threat to cultivated plants, making them a threat to the cultivation process. The behavior of these weeds has been simulated and used in Invas