Concentrations of uranium were measured in this study for twenty soil samples from four areas with different depths (soil surface-20-40-60-80)cm .The study regions include Missan Governorate (Al-Iskan area,Al-Shibbana area ,Hai-Al Moualimin Al Jadied area ,Sector 30 area). The Uranium concentrations in soil samples measured by using fission tracks registration in (CR-39) track detector that caused by the bombardment of (U-283) with thermal neutrons from (241Am-Be) neutron source that has flux neutron thermal of (5 ×103 n cm-2 s-1). The concentrations values were calculated by a comparison with standard samples. Through out the result, it was found that averages of uranium concentrations in soil samples were as the following : Al - Iskan

     Staphylococcus haemolyticus is one of the most frequently isolated coagulase-negative staphylococci. The ability to form biofilm is considered as one of the most important virulence factors of coagulase negative staphylococci. There is only limited knowledge of the nature of S. haemolyticus biofilms. This study was aimed at evaluating the ability of S. haemolyticus strains to produce biofilm in the presence of copper oxide nanoparticles (CuONPs). The biological synthesis of nanoparticles is an environmentally friendly approach for large-scale production of nanoparticles. Copper oxide nanoparticles were produced in the current study from the S. haemolyticus viable cell filtrate. UV-visible (UV-Vis) spectroscopy, X-ray diffra

The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

Mosquitoes like Culex quinquefasciatus are the primary vector that transmits many causes of diseases such as filariasis, Japanese encephalitis, and West Nile virus, in many countries around the world. The development in the scientific fields, such as nanotechnology, leads to use this technique in control programs of insects including mosquitoes through the use of green synthesis of nanoemulsions based on plant products such as castor oil.  Castor oil nanoemulsion was formulated in various ratios comprising of castor oil, ethanol, tween 80, and deionized water by ultrasonication. Thermodynamic assay improved that the formula of (10 ml) of castor oil, ethanol (5ml), tween 80 (14 ml) and deionized water (71ml)   was mor

In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance