Sb2S3 thin films have been prepared by chemical bath deposition on a glas sub Absorbance and transmittance spectra were recorded in the wavelength range (30-900) nm. The effects of thickness on absorption coefficient, reflectance, refractive index, extinction coefficient, real and imaginary parts of dielectric constant were estimated. It was found that the reflectivity, absorption coefficient , extinction coefficient, real part of dielectric constant and refractive index, all these parameters decrease as the thickness increased, while the imaginary part of the dielectric constant increase as the thickness incre

S Ali…, Journal of Physical Education, 2019 - Cited by 1

Aim: To evaluate the effect of two bonding systems and two curing systems on sealing ability of class V composite restorative materials. Materials and methods: This study was performed in vitro on 40 caries free upper first premolar teeth. The Standardized class V cavity preparation on buccal and lin- gual surfaces of each tooth was done. Then the teeth were randomly divided into two major groups each of twenty. 40 cavities were performed on these teeth and the first group7th generation bonding agent (i Bond) were applied according to the manufacturer instructions and single increment of univer- sal composite (XRV Herculite) from kerr were applied and twenty of the cavities were cured with con- ventional light cure device (astralis-5) and t

Mixing aluminum nitrate nonahydrate with urea produced room temperatures clear colorless ionic liquid with lowest freezing temperature at (1: 1.2) mole ratio respectively. Freezing point phase diagram was determined and density, viscosity and conductivity were measured at room temperature. It showed physical properties similar to other ionic liquids. FT-IR,UV-Vis, 1H NMR and 13C NMR were used to study the interaction between its species where - CO ??? Al- bond was suggested and basic ion [Al(NO3)4]? and acidic ions [Al(NO3)2. xU]+ were proposed. Water molecule believed to interact with both ions. Redox potential was determined to be about 2 Volt from – 0.6 to + 1.4 Volt with thermal stability up to 326 ?.

t-Self-Compacting Concrete (SCC) reduces environmental noise and has more workability. This research presents an investigation of the behavior of SCC under mechanical loading (impact loading). Two types of cement have been used to produce SCC mixtures, Ordinary Portland Cement (OPC) and Portland Limestone Cement (PLC), which reduces the emission of carbon dioxide during the manufacturing process. The mixes were reinforced with Carbon Fiber Reinforced Polymer (CFRP) which is usually used to improve the seismic performance of masonry walls, to replace lost steel reinforcements, or to increase column strength and ductility. Workability tests were carried out for fresh SCC. Prepared concrete slabs of 500×500×50mm were tested for lo

In this paper, we study the growth of solutions of the second order linear complex differential equations  insuring that any nontrivial solutions are of infinite order. It is assumed that the coefficients satisfy the extremal condition for Yang’s inequality and the extremal condition for Denjoy’s conjecture. The other condition is that one of the coefficients itself is a solution of the differential equation .

Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their performance is evaluated usin

Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing