Tin Selenide (SnSe) Nano crystalline thin films of thickness 400±20 nm were deposited on glass substrate by thermal evaporation technique at R.T under a vacuum of ∼ 2 × 10− 5 mbar to study the effect of annealing temperatures (as-deposited, 100, 150 and 200) °C on its structural, surface morphology and optical properties. The films structure was characterized using X-ray diffraction (XRD) which showed that all the films have polycrystalline in nature and orthorhombic structure, with the preferred orientation along the (111) plane. These films was synthesized of very fine crystallites size of (14.8-24.5) nm, the effect of annealing temperatures on the cell parameters, crystallite size and dislocation density were observed.

This work studies with produce of light fuel fractions of gasoline, kerosene and gas oil from treatment of residual matter that will be obtained from the solvent extraction process as by product from refined lubricate to improve oil viscosity index in any petroleum refinery. The percentage of this byproduct is approximately 10% according to all feed (crude oil) in the petroleum refinery process. The objective of this research is to study the effect of the residence time parameter on the thermal cracking process of the byproduct feed at a constant temperature, (400 °C). The first step of this treatment is the thermal cracking of this byproduct material by a constructed batch reactor occupied with control device at a selective range of re

Utilizing phase change materials in thermal energy storage systems is commonly considered as an alternative solution for the effective use of energy. This study presents numerical simulations of the charging process for a multitube latent heat thermal energy storage system. A thermal energy storage model, consisting of five tubes of heat transfer fluids, was investigated using Rubitherm phase change material (RT35) as the. The locations of the tubes were optimized by applying the Taguchi method. The thermal behavior of the unit was evaluated by considering the liquid fraction graphs, streamlines, and isotherm contours. The numerical model was first verified compared with existed experimental data from the literature. The outcomes re

Background: presence of lingual vascular foramina and canals in the interforaminal region may increase the risk ofsurgical complications during implant placement or any surgical procedure in this area. Aim of this study is the radiological evaluation of the anatomic characteristic of the lingual foramina and their vascular canals in the anterior of the mandible using cone beam computed tomography. Materials and Methods: Prospective study including 72 Iraqi subjects (31 male and 41 female) ranging from 20 to 59 years, all subjects attended Al-Sharaa dental clinic in AL-Najaf AL-Ashraf city, scanned with CBCT from September 2016 to February 2017. Using 3dimentional and sagittal cross section to detect lingual foramina and their vascular canal

Background: presence of lingual vascular foramina and canals in the interforaminal regionmay increase the risk ofsurgical complications during implant placement or any surgical procedure in this area.Aim of this study is the radiological evaluation of the anatomic characteristic of the lingual foramina and their vascular canals in the anterior of the mandible using cone beam computed tomography. Materials and Methods: Prospective study including 72 Iraqi subjects (31 male and 41 female) ranging from 20 to 59 years, all subjects attended AL- Sharaa dental clinic in AL-Najaf AL-Ashraf city, scanned with CBCT from September 2016 to February 2017. Using 3dimentional and sagittal cross section to detect lingual foramina and their vascular canals

The analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.

Because the studying of time series can get by building, analysis the models and then forecasting gives the priority for the practicing in different fields, therefore the identification and selection of the model is of great importance in spite of its difficulties.

The selection of a standard methods has the ability for estimation the errors in the estimated the parameters for the model, and there will be a balance between the suitability and the simplicity of the model.

In the analysis of d

This paper aims at analyzing Terry Bisson’s short story Bears Discover Fire stylistically by following both Gerard Genette’s theory of narratology (1980) and Short and Leech (1981) strategy for analyzing fictional works. Also trying to examine to what extent these models are applicable in analyzing the selected story. Stylistic analysis procedures help the readers/researchers to identify specific linguistic features in order to support literary interpretation and appreciation of literary texts. Style in fiction concentrates not on what is written, but on how a text is written. Each writer has his own style and techniques which distinguish him from other writers

In this research work, a new type of concrete based on sulfur-melamine modification was introduced, and its various properties were studied. This new type of concrete was prepared based on the sulfur-melamine modification and various ingredients. The new sulfur-melamine modifier was fabricated, and its fabrication was confirmed by IR spectroscopy and TG analysis. The surface morphology resulted from this modifier was studied by SEM and EDS analysis. The components ratios in concrete, chemical and physical characteristics resulted from sulfur-melamine modifier, chemical and corrosion resistance of concrete, stability of concrete against water adsorption, stability of concrete against freezing, physical and mechanical properties and durabi

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial