The effect of subinhibitory concentration of Antibiotics on the Adherence of S.aureus (Coagulase Positive Staphylococci), and S.epidermidis (Coagulase negative Staphylococci) and Pseudomonas aeruginosa, Enterobacter cloacae, Citobacter freundi (Gram negative bacteria) was done and the results revealed that Rifampicin was the best antibiotic inhibiting Staphylococci adherence and Vancomycin has less effect on the adherence of Staphylococci, whereas Tetracyclin was the best antibiotic inhbiting Gram negative bacteria adherence and Amikacin has the lest less effect on inhibiting bacterial adherence.
The research aims to learn spatial disparities tracts of agricultural crops in the
province of Maysan and their relationship (the salinity of the soil and the degree of chemical
interaction (PH)) The research is divided into an introduction and three Investigation eat first
section spatial disparities agricultural crops (cereals, vegetables, legumes and forage). The
comparison between the years of production in the province where the province has seen
varied spatial by hand and taking second section degrees of soil salinity and its impact on
agriculture, as well as the chemical reaction (PH) and its impact on agriculture The third
section has been used three technical techniques first linkage and the second simple an
Resin-modified glass ionomer cement tends to shrink due to polymerization of the resin component. Additionally, they are more prone to syneresis and imbibition during the setting process. This
Abstract:
The research aims to identify the concept of trading securities in Iraq and to propose a new mechanism for the taxation of trading profits and the extent of its impact on tax revenues, as it was observed that there are professional investors in the trading market and some of them achieve huge annual profits. and this profit should be like other taxable profits. The General Commission of Taxes and in cooperation with the Iraq Stock Exchange should identifying those profits, subjecting them to income tax, and adding them to the tax base. The researcher relied on the use of the descriptive and analytical approach bas
... Show MoreIn this work, composite materials were prepared by mixing different concentrations of ferrites with polyacrylonitrile (PAN) polymer. Using the electrospinning technique, these composites were deposited on a p-type silicon wafer. The prepared samples demonstrated nanofibers in both pure PAN polymers and their composites with ferrite. Prior to examining the humidity sensing effectiveness with a percentage of relative humidity at a frequency of 10 kHz, based on ambient temperature and a relative humidity range of 50–100%, the composite nanofibers demonstrated stronger humidity sensing compared to the pure PAN nanofibers, which demonstrated a powerful resistance response. More precisely, the PAN@ferrite nanocomposite showed a broad adsorption
... Show MoreThe solidification process in a multi-tube latent heat energy system is affected by the natural convection and the arrangement of heat exchanger tubes, which changes the buoyancy effect as well. In the current work, the effect of the arrangement of the tubes in a multi-tube heat exchanger was examined during the solidification process with the focus on the natural convection effects inside the phase change material (PCM). The behavior of the system was numerically analyzed using liquid fraction and energy released, as well as temperature, velocity and streamline profiles for different studied cases. The arrangement of the tubes, considering seven pipes in the symmetrical condition, are assumed at different positions in the system, i
... Show MoreWildfire 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
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