The change in the optical band gap and optical activation energy have been investigated for pure Poly (vinyl alcohol)and Poly (vinyl alcohol) doped with Aluminum sulphate to proper films from their optical absorption spectra. The absorption spectra were measured in the wave range from (200-700) nm at temperature range (25-140) 0C. The optical band gap (Eg) for allowed direct transition decrease with increase the concentration of Aluminum sulphate. The optical activation energy for allowed direct transition band gap was evaluated using Urbach- edges method. It was found that ?E increases with increasing the concentration of Al2 (SO4)3 and decreases when temperature increases.

Spatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati

AlO-doped ZnO nanocrystalline thin films from with nano crystallite size in the range (19-15 nm) were fabricated by pulsed laser deposition technique. The reduction of crystallite size by increasing of doping ratio shift the bandgap to IR region the optical band gap decreases in a consistent manner, from 3.21to 2.1 eV by increasing AlO doping ratio from 0 to 7wt% but then returns to grow up to 3.21 eV by a further increase the doping ratio. The bandgap increment obtained for 9% AlO dopant concentration can be clarified in terms of the Burstein–Moss effect whereas the aluminum donor atom increased the carrier's concentration which in turn shifts the Fermi level and widened the bandgap (blue-shift). The engineering of the bandgap by low

Abstract

The Classical Normal Linear Regression Model Based on Several hypotheses, one of them is Heteroscedasticity as it is known that the wing of least squares method (OLS), under the existence of these two problems make the estimators, lose their desirable properties, in addition the statistical inference becomes unaccepted table. According that we put tow alternative,  the first one is  (Generalized Least Square) Which is denoted by (GLS), and the second alternative is to (Robust covariance matrix estimation) the estimated parameters method(OLS), and that the way (GLS) method neat and certified, if the capabilities (Efficient) and the statistical inference Thread on the basis of an acceptable

Large quantities of contaminated carwash wastewater are produced per day from carwash places. Extensively it contains large quantities of chemicals from detergents, oil, grease, heavy metals, suspended solids, types of hydrocarbons, and biological contents. A novel electrocoagulation treatment by foil electrodes was conducted to remove COD, turbidity, Total Dissolved Solids (TDS) from contaminated carwash wastewater and decrease its Electrical Conductivity (EC). A thin layer of aluminum foil is used as an electrode in this treatment process. The effects of different voltage and treatment times were studied. The best result was found at a voltage of 30 volts and treatment time 90 minute where the removal efficiency of COD

in this paper copper oxide (cuO thin films were prepared by the method of vacum thermal evaporation a pressure.

This work presents the study of the dark current density and the capacitance for porous silicon prepared by photo-electrochemical etching for n-type silicon with laser power density of 10mw/cm2 and wavelength (650nm) under different anodization time (30,40,50,60) minute. The results obtained from this study shows different chara that different characteristic of porous diffecteristics for the different porous Silicon layers.

Collagen triple helix repeat containing-1 (CTHRC1) is an essential marker for Rheumatoid Arthritis (RA), but its relationship with pro-inflammatory, anti-inflammatory, and inflammatory markers has been scantily covered in extant literature. To evaluate the level of CTHRC1 protein in the sera of 100 RA patients and 25 control and compare levels of tumour necrosis factor alpha (TNF-α), interleukin 10 (IL-10), RA disease activity (DAS28), and inflammatory factors. Higher significant serum levels of CTHRC1 (29.367 ng/ml), TNF-α (63.488 pg/ml), and IL-10 (67.1 pg/ml) were found in patient sera as compared to that in control sera (CTHRC1 = 15.732 ng/ml, TNF-α = 33.788 pg/ml, and IL-10 = 25.122 pg/ml). There was no significant correlation be

            In this study, pure SnO₂ Nanoparticles doped with Cu were synthesized by a chemical precipitation method. Using SnCl₂.2H₂O, CuCl₂.2H₂O as raw materials, the materials were annealed at 550°C for 3 hours in order to improve crystallization. The XRD results showed that the samples crystallized in the tetragonal rutile type SnO₂ stage. As the average SnO₂ crystal size is pure 9nm and varies with the change of Cu doping (0.5%, 1%, 1.5%, 2%, 2.5%, 3%),( 8.35, 8.36, 8.67, 9 ,7, 8.86)nm respectively an increase in crystal size to 2.5% decreases at this rate and that the crystal of SnO₂ does not change with the introduction of Cu, and S

The current research aimed to investigate the psychometric characteristics of the Arabic version of the Nomophobia scale for the Omani youth. The scale was administered to a random sample of students from public and private universities and colleges in Oman. The research sample consisted of 2507 students, of whom 868 males and 1639 females. The validity of the measure was first checked by presenting the scale to a group of experts in this field. Then the exploratory and confirmatory factor analysis was carried out. The exploratory factor analysis revealed the existence of three main factors: the fear of connectivity loss, the fear of communication loss with others, and the fear of network outages. These factors accounted for 65.6% of the