This paper reports the effect of Mg doping on structural and optical properties of ZnO prepared by pulse laser deposition (PLD). The films deposited on glass substrate using Nd:YAG laser (1064 nm) as the light source. The structure and optical properties were characterized by X-ray diffraction (XRD) and transmittance measurements. The films grown have a polycrystalline wurtzite structure and high transmission in the UV-Vis (300-900) nm. The optical energy gap of ZnO:Mg thin films could be controlled between (3.2eV and 3.9eV). The refractive index of ZnO:Mg thin films decreases with Mg doping. The extinction coefficient and the complex dielectric constant were also investigate.

The paper is concerned with, the behavior of the hydrostatic thrust bearings lubricated with liquid-solid lubricants using Einstein viscosity formula, and taking into account the centrifugal force resulting from high speed.  Also studied is the effect of the bearing dimensions on the pressure, flow rate, load capacity, shear stress, power consumption and stiffness.

The theoretical results show an increase in load capacity by (8.3%) in the presence of solid graphite particles with concentration of (16%) by weight as compared with pure oil, with increasing shear stress.  .

In general the performance of hydrostatic thrust bearings improve for load carrying capacity, volume flow rate,

As regional development, as a matter of course, poses a number of systemic, scientific and political problems. While the issue of development is primarily at the national level to the limits of World War II in the industrialized world and to the 1960s borders in most Third World countries, the increasing awareness of regional disparities has led to the regional issue Were taken into consideration in the early 1960s and 1970s in most industrialized and developing countries alike. The local issue was only introduced in the early 1980s. The awareness of regional disparities and the fact that the regions do not have the same potential and that some regions have the resources to enable them to develop, grow and develop, unlike other r

Background: Entamoeba histolytica is the causative agent of amoebic dysentery and hepatic abscesses. Despite the efficacy of metronidazole in alleviating infectious diseases, the global dissemination of drug-resistant parasites raises the possibility that Punica granatum could serve as an effective natural alternative treatment. Objective: To evaluate the effect of P. granatum methanolic and aqueous extracts of various parts against E. histolytica trophozoites in an in vitro setting. Methods: Various concentrations (0.14, 0.7, 1.4, and 2.8 mg/ml) of P. granatum extracts of the flowers, leafs, peels, and seeds were chosen for this purpose. A culture medium containing 0.05x106/ml E. histolytica trophozoites was treated with different

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

Enhancing quality image fusion was proposed using new algorithms in auto-focus image fusion. The first algorithm is based on determining the standard deviation to combine two images. The second algorithm concentrates on the contrast at edge points and correlation method as the criteria parameter for the resulted image quality. This algorithm considers three blocks with different sizes at the homogenous region and moves it 10 pixels within the same homogenous region. These blocks examine the statistical properties of the block and decide automatically the next step. The resulted combined image is better in the contras

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s