The acrylic polymer composites in this study are made up of various weight ratios of cement or silica nanoparticles (1, 3, 5, and 10 wt%) using the casting method. The effects of doping ratio/type on mechanical, dielectric, thermal, and hydrophobic properties were investigated. Acrylic polymer composites containing 5 wt% cement or silica nanoparticles had the lowest abrasion wear rates and the highest shore-D hardness and impact strength. The increase in the inclusion of cement or silica nanoparticles enhanced surface roughness, water contact angle (WCA), and thermal insulation. Acrylic/cement composites demonstrated higher mechanical, electrical, and thermal insulation properties than acrylic/silica composites because of their lowe

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Electronic properties including (bond length, energy gap, HOMO, LUMO and density of state) as well as spectroscopic properties such like infrared, Raman scattering, force constant, reduced mass and longitu- dinal optical mode as a function of frequency are based on size and concentration of the molecular and nanostructures of aluminum nitride ALN, boron nitride BN and AlxB7-XN7 as nanotubes has calculated using Ab –initio approximation method dependent on density functional theory and generalized gradient approximation. The geometrical structure are calculated by using Gauss view 05 as a complementary program. Shows the energy gap of ALN, BN and AlxB7-XN7 as a function of the total number of atoms , start from smallest molecule to reached

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

Self is the main factor of personality and the acceptance of others where each of them are connecting and plays an important role in emotional maturation. The researches affirmed that the leading behavior depending on good human relations between the employers and the employees will enhance their goals and the goals of the institution at the same time . This study aims to measure the emotional maturation among the leactures of the university according to sex variable and identify the correlation between emotional maturation and the level of leading behavior among the lecturers of the university. The sample consists of two samples where the lst is to build the measwe consisting of (200)males and famales lecturers and the 2nd which is the