This research investigates the adsorption isotherm and adsorption kinetics of nitrogen from air using packed bed of Li-LSX zeolite to get medical oxygen. Experiments were carried out to estimate the produced oxygen purity under different operating conditions: input pressure of 0.5 – 2.5 bar, feed flow rate of air of 2 – 10 L.min^-1 and packing height of 9-16 cm. The adsorption isotherm was studied at the best conditions of input pressure of 2.5 bar, the height of packing 16 cm, and flow rate 6 Lmin^-1 at ambient temperature, at these conditions   the highest purity of oxygen by this system 73.15 vol % of outlet gas was produced. Langmuir isotherm was the best models representing the experimental data., and the m

       Atorvastatin have problem of very slightly aqueous solubility (0.1-1 mg/ml). Nano-suspension is used to enhance it’s of solubility and dissolution profile. The aim of this study is to formulate Atorvastatin as a nano-suspension to enhance its solubility due to increased surface area of exposed for dissolution medium, according to Noyes-Whitney equation.

        Thirty one formulae were prepared to evaluate the effect of ; Type of polymer, polymer: drug ratio, speed of homogenization, temperature of preparation and inclusion of co-stabilizer in addition to the primary one; using solvent-anti-solvent precipitation method under high power of ultra-sonication.

The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

The Coronavirus Disease 2019 (COVID-19) pandemic has caused an unprecedented disruption in medical education and healthcare systems worldwide. The disease can cause life-threatening conditions and it presents challenges for medical education, as instructors must deliver lectures safely, while ensuring the integrity and continuity of the medical education process. It is therefore important to assess the usability of online learning methods, and to determine their feasibility and adequacy for medical students. We aimed to provide an overview of the situation experienced by medical students during the COVID-19 pandemic, and to determine the knowledge, attitudes, and practices of medical students regarding electronic medical education.

A numerical investigation is adopted for two dimensional thermal analysis of rocket thrust chamber wall (RL10), employing finite difference model with iterative scheme (implemented under relaxation factor of 0.9 for convergence) to compute temperature distribution within thrust chamber  wall (which is composed of Nickel and Copper layers). The analysis is conducted for different boundary conditions: only convection boundary conditions then combined radiation, convection boundary conditions also for  different aspect ratio (AR) of cooling channel. The results show that Utilizing cooling channels of high aspect ratio leads to decrease in temperature variation across thrust chamber wall, while no effects on heat transferred to the