Zinc Oxide (ZnO) is probably the most typical II-VI
semiconductor, which exhibits a wide range of nanostructures. In
this paper, polycrystalline ZnO thin films were prepared by chemical
spray pyrolysis technique, the films were deposited onto glass
substrate at 400 °C by using aqueous zinc chloride as a spray
solution of molar concentration of 0.1 M/L.
The crystallographic structure of the prepared film was analyzed
using X-ray diffraction; the result shows that the film was
polycrystalline, the grain size which was calculated at (002) was
27.9 nm. The Hall measurement of the film studied from the
electrical measurements show that the film was n-type. The optical
properties of the film were studied using

This study investigated the bioethanol production from green algae Chlorella vulgaris depending on its carbohydrate-enriched biomass. Four different phosphorous concentrations were employed to stimulate bioethanol production from Chlorella vulgaris. The impact of various phosphorous values on Chlorella vulgaris growth rate as well as primary product (carbohydrate) were evaluated. High performance liquid chromatography was utilized in this work. The stationary phase was identified as day 14, 12, 10 and 6 in treatments 6, 4, 2 and g/L, respectively. The findings suggest that the treatment without phosphorous addition had the highest record of carbohydrate content (22.64% dry weight) as well as the highest bioethanol yield (20.66% dry weight).

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

Background: Beta thalassemia is a typically autosomal recessive form of severe anemia which is caused by an imbalance of two types of protein (alpha and beta) subunits of hemoglobin. Oxidative stress imbalance is the equilibrium between pro-oxidant\antioxidant statuses in cellular system, which results in damaging the cells. Antioxidant is a chemical that delays the start or slows the rate of lipid oxidation reaction and it play a very important role in the body defense system against reactive oxygen species. The aims of this study were to recorded the oro-facial manifestations in beta thalassemic patients and assess the oxidative stress marker malondialdehyde in serum and salivs and their role in the pathogenesis of beta thalassemia and ev

study the effect of radiation microwave (MW) in inhibition the growth of some types of bacteria in a minced meat and barker were exposed to MW for different times included (0, 10, 20, 30 and 40) sec.The results showed a high inhibition rate for 40 sec, reached to 100%. It is the other side studied the effect of microwave radiation against four types of bacteria included (Staphylococcus aureus, Escherichia coli, Proteus mirabilis and Klebsiella spp), when were exposed to for (0, 5, 10, 20, 30 and 40) sec the inhibition ratio reached to 100% in each of the Proteus mirabilis and Klebsiella spp at 30 sec and Staphylococcus aureus and Escherichia coli at 40sec. using MW in the sterilization media, such as Nutrient agar, Macconkey agar and Man

The aim of this study is to formulate and evaluate ezetimibe nanoparticles using solvent antisolvent technology. Ezetimibe is a practically water-insoluble drug which acts as a lipid lowering drug that selectively inhibits the intestinal absorption of cholesterol and related phytosterols. Ezetimibe prepared as nano particles in order to improve its solubility and dissolution rate.

Thirty formulas were prepared and different stabilizing agents were used with different concentrations such as poly vinyl pyrrolidone (PVPK-30), poly vinyl alcohol (PVA), hydroxy propyl methyl cellulose E5 (HPMC), and poloxamer. The ratios of drug to stabilizers used to prepare the nanoparticles were 1: 2, 1:3 and 1:4.

The prepared nanoparticles

In this study, an efficient photocatalyst for dissociation of water was prepared and studied. The chromium oxide (Cr₂O₃) with Titanium dioxide (TiO₂) nanofibers (Cr₂O₃-TNFs) nanocomposite with (chitosan extract) were synthesized using ecologically friendly methods such as ultrasonic and hydrothermal techniques; such TiO₂ exhibits nanofibers (TNFs) shape struct