Background: The beneficial gut bacterium E. coli can cause blood poisoning, diarrhoea, and other gastrointestinal and systemic disorders. Objective: This study amid to examines the antibiofilm activity of Laurus nobilis leaves extract on E. coli isolates and compares pre- and post-treatment gene expression of fimA and papC genes. Subjects and Methods: Ten isolates of E. coli were obtained from the Genetic Engineering and Biotechnology Institute, University of Baghdad, which was previously collected from Baghdad city hospitals and diagnosed by chemical tests, the diagnosis was confirmed using VITEK-2 System. The preparation of the aqueous and methanolic Laurus nobilis leaves extracts was done by using the maceration method and Soxhlet appara

There are many problems facing the economic entities  as a result of its mass production &variation of its products  , the matter which had  increased the need & importance of cost accounting which is regarded a main tool for the managerial control.

The actual costing system is unable to meet the contemporary management needs ,so the Standard costing system appear to provide the management  with required information to perform its functions by the best use& way.

This research aims to determine  the standard cost for the  direct material for oil extraction activity by applying it in the north oil company.

     In this research, silver nanoparticles (AgNPs) were manufactured using aqueous extract of mushroom Pleurotus ostreatus. Anticancer potential of AgNPs was investigated versus human breast cancer cell line (MCF-7). Cytotoxic response was assessed by MTT assay. AgNPs showed inhibition effect at the following concentrations 12.5, 25, 50, 100 and 200 µg/ml versus MCF-7 cell line, and all treatments had a positive result. The MCF-7 cells were inhibited up to 85.14 % at the concentration 200 μg/ml of AgNPs which reduced cells viability to 14.86%, while 12.5 μg/ml of AgNPs caused 24.23% cells inhibition with reduction of cells viability to 75.77%.

Synthesis And Studies Of Complexes Of Some Elements With 2-Mercaptohiazole (2-HMBT)

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

Thin films were prepared from poly Berrol way Ketrrukemaaih pole of platinum concentrations both Albaarol and salt in the electrolytic Alastontrel using positive effort of 7 volts on the pole and the electrical wiring of the membrane record

This study involves the synthesis of a new class of silicon polymers, designated as P1-P7, derived from dichlorodimethylsilane (DCDMS) in combination with various organic compounds (Schiff bases prepared from different amines and appropriate aldehydes or ketones) [I-V] through condensation polymerization. The structures of all monomers and polymers were characterization by FTIR and 1HNMR spectroscopy (for some polymers). The results of thermogravimetric analysis (TGA) and differential scanning calorimetry DSC test show stable thermal behaviour. Polymers with a higher concentration of aromatic rings in their repeating structural units exhibited a higher temperature for weight loss, indicating increased thermal stability. Thermal meas

As the process of  estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying  model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .