Today, the world is living in a time of epidemic diseases that spread unnaturally and infect and kill millions of people worldwide. The COVID-19 virus, which is one of the most well-known epidemic diseases currently spreading, has killed more than six million people as of May 2022. The World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) after an outbreak of SARS-CoV-2 infection. COVID-19 is a severe and potentially fatal respiratory disease caused by the SARS-CoV-2 virus, which was first noticed at the end of 2019 in Wuhan city. Artificial intelligence plays a meaningful role in analyzing medical images and giving accurate results that serve healthcare workers, especially X-ray images, which are co

COVID-19 (Coronavirus disease-2019), commonly called Coronavirus or CoV, is a dangerous disease caused by the SARS-CoV-2 virus. It is one of the most widespread zoonotic diseases around the world, which started from one of the wet markets in Wuhan city. Its symptoms are similar to those of the common flu, including cough, fever, muscle pain, shortness of breath, and fatigue. This article suggests implementing machine learning techniques (Random Forest, Logistic Regression, Naïve Bayes, Support Vector Machine) by Python to classify a series of chest X-ray images that include viral pneumonia, COVID-19, and healthy (Not infected) cases in humans. The study includes more than 1400 images that are collected from the Kaggle platform. The expe

In this study, the results of x-ray diffraction methods were used to determine the Crystallite size and Lattice strain of Cu2O nanoparticles then to compare the results obtained by using variance analysis method, Scherrer method and Williamson-Hall method. The results of these methods of the same powder which is cuprous oxide, using equations during the determination the crystallite size and lattice strain, It was found that the results obtained the values of the crystallite size (28.302nm) and the lattice strain (0.03541) of the variance analysis method respectively and for the Williamson-Hall method were the results of the crystallite size (21.678nm) and lattice strain (0.00317) respectively, and Scherrer method which gives the value of c

In this work Different weight of pure Zinc powder suspended particles in 4ml base engine Oil were used.
Intensity of Kα Line was measured for the suspended particles ,also for mixture which consist from Zinc particle blended with Engine base Oil. Calibration Curve was drawn between Ikα line Intensity and Zinc concentration at different operation condition. The Lower Limit detection (LLD) and Sensitivity (m) of Spectrometer were determined for different Zinc Concentration (Wt%). The results of LLD and m for Samples were analyzed at Operation Condition of 30KV,17mA is best from Samples were analyzed at Operation Condition of 25KV,15mA

Samples of tea leaves (Green tea, Gugarate tea and Black tea used commonly in Iraq) are dried, grinded, pressed and submitted for the elemental analysis by x-ray fluorescence technique (XRF). The concentrations of major, minor and trace elements are determined. The major elements were Na, Mg, Al, K, Si, Ca, Mn, Fe, S and P. Of these elements, Ca, concentration in Gugarate tea leaves is three times, it's level in the other types of tea. Titanium, Cl, Rb and Sr are found as minor elements, while other elements such as Cu, Zn, V, Cr, Co, ...etc are found as trace elements. Of these trace elements considerable concentration values are found for some toxic elements Hg, Cd, Pb and As. Green tea contains 1.1 ppm Hg and 4.4 ppm Pb. Gugarate tea

The study area is located at AL Jabal AL-Akhdar region North Eastern part of Libya. The study includes (23) fresh samples that are taken from Darnah limestone Formation, these samples were distributed on and covered about (210) km2. The porosities and permeabilities of these samples were determined. This study is important because this formation is considered as a good reservoir for hydrocarbon accumulation in other places in Libya.
The porosity was measured by three different methods namely by porosimeter (using core samples), thin sections and binocular microscope. The permeability are also measured by two methods, the first method was by Nitrogen method and the other is by Klinkenberg method. The instrument that used for measuring

In this work, we give an identity that leads to establishing the operator . Also, we introduce the polynomials . In addition, we provide Operator proof for the generating function with its extension and the Rogers formula for . The generating function with its extension and the Rogers formula for the bivariate Rogers-Szegö polynomials  are deduced. The Rogers formula for  allows to obtain the inverse linearization formula for , which allows to deduce the inverse linearization formula for . A solution to a q-difference equation is introduced and the solution is expressed in terms of the operators . The q-difference method is used to recover an identity of the operator  and the generating function for the polynomials

Background: Although expression of the HER-
2/neuoncogene may be of some prognostic importance
in advanced ovarian cancer, its role in early-stage
disease has not been established. The current study
examined the prevalence and significance of HER-
2/neu expression in different grades of different types
of surface epithelial ovarian carcinoma.
Methods: Thirty eight female patients with surface
epithelial ovarian cancer were included in this study.
The blocks of corresponding formalin fixed, paraffinembedded
ovarian biopsies were retrieved from the
archives and hematoxylin-eosin slides of each ovarian
biopsy were reviewed and marked their grades of
differentiation , then a new sections from each sampl

      The goal of this research is to better understand the physical features of starburst galaxies. Radio and X-ray observations are good for exploring the stuff within the central regions of galaxies.  A galaxy that is undergoing a strong star formation, usually in its central area, is known as a starburst galaxy. This paper provides the results of a statistical analysis of a sample of starburst galaxies. The data used in this research have been collected from NASA Extragalactic Database (NED), and HYPERLEDA. Those data have been used to examine possible luminosity correlations of X-ray to a radio of a sample of starburst galaxies. In this research, statistical software, known as statistic-win-program, has been used to investigat