With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

Wellbore instability is one of the most common issues encountered during drilling operations. This problem becomes enormous when drilling deep wells that are passing through many different formations. The purpose of this study is to evaluate wellbore failure criteria by constructing a one-dimensional mechanical earth model (1D-MEM) that will help to predict a safe mud-weight window for deep wells. An integrated log measurement has been used to compute MEM components for nine formations along the studied well. Repeated formation pressure and laboratory core testing are used to validate the calculated results. The prediction of mud weight along the nine studied formations shows that for Ahmadi, Nahr Umr, Shuaiba, and Zubair formations

Background: Radiotherapy, is therapy using ionizing radiation in order to deliver an optimal dose of either particulate or electromagnetic radiation to a particular area of the body with minimal damage to normal tissues. The source of radiation may be outside the body of the patient (external beam irradiation) or it may be an isotope that has been implanted or instilled into abnormal tissue or a body cavity. Called also radiotherapy. The aim of work studies the relationship between the depth dose and the high photon xray energies (6MeV and 10MeV). Patients and methods: in our work, we studied the dose distribution in water phantom given at different depths (zero-18) cm deep at1cm intervals treated with different field size (5×5-,10×1

In recent years, there has been growing interest in using Nanosystems in different biomedical applications. Among all metal nanoparticles, selenium nanoparticles have attracted the attention of many researchers due to its low toxicity and nutritional supplementation value. The purpose of the current study was designed to examine the possible effect of selenium nanoparticles in combination with fenugreek leaves extract (an edible herb with good medicinal properties) in the treatment of oxidative stress status-related to polycystic ovary syndrome in letrozole-induced PCOS (an imbalance of reproductive hormones that causes infertility) in adult female rats. Cold plasma was used in the preparation of selenium nanoparticles subsequently the prod

A novel technique for nanoparticles with a chemical method and impact for resistance bacteria methicillin-resistant Staphylococcus aureus (MRSA), UV-visible analysis confirmed the by Fourier transform infrared spectroscopy (FT-IR) and Energy dispersive X-Ray (EDX), Scanning electron microscope (SEM) and X-ray diffraction pattern estimation antimicrobial excellent antibacterial activity against MRSA (with zone of inhibition of 11 ± 02 mm , 9 ± 01 mm,8 ± 03 mm and 7.5 ± 02 mm and 6.5 ± 02 mm) at different concentrations (0.5 ,0.25, 0.125, 0.0625, 0.03125) mg/ml while good activity was 16 ± 03 mm at 17 ± 02 mm zone at 0.25, 0.125 mg/mL, respectively. The increase in microorganism resistance to antibiotics a couple of have caused

new, simple and fast solid-phase extraction method for separation and preconcentration of trace theophylline in aqueous solutions was developed using magnetite nanoparticles (MIONPs) coated with aluminium oxide (AMIONPs) and modified with palmitate (P) as an extractor (P@AMIONPs). It has shown that the developed method has a fast absorbent rate of the theophylline at room temperature. The parameters that affect the absorbent of theophylline in the aqueous solutions have been investigated such as the amount of magnetite nanoparticle, pH, standing time and the volume, concentration of desorption solution. The linear range, limit of quantification (LOQ) and limit of detection (LOD) for the determination of theophylline were 0.05-2.450 μg mL-

Background: This study was done to assist X-ray diffraction and biocompatability of glass ionomer cement reinforced by different ratios of Hydroxyapatite. Materials and Methods: The powder of glass ionomer cement reinforced by different ratios of Hydroxyapatite were used to get X-ray diffraction pattern by X-ray diffraction machine, While for biocompatibility test, A polyethylene tubes containing glass ionomer cement reinforced by different ratios of Hydroxyapatite were implanted on the dorsal submucosal site of Rabbit's tissues and histological slide were prepared for histopathological study. Results: X-ray diffraction test showed that all elements of glass ionomer cement reinforced by different ratios of Hydroxyapatite were react with eac