In this study, the stress-strength model R = P(Y < X < Z)  is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used    to estimate the parameters  namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.  

Complexes of Au (III), Pd (II), Pt (IV ) and Rh(III) with S–propynyle-2- thiobenzimidazole (BENZA) have been prepared and characterized by IR and UV- Visible spectral methods in addition to magnetic and conductivity measurements and micro–elemental analysis (CHN).The probable structures of the new complexes have been suggested.

The aim of this study was to evaluate the effects of local application of bisphosphonate gel and recombinant human bone morphogenic protein 2 gel, on titanium dental implant stability and marginal bone level. Twenty-seven patients with upper and lower missing posterior tooth/teeth were included in the study with a total of 71 implants that were used for rehabilitation. The implants were randomly divided into 4 groups: 3 study groups and 1 control. Group1; local application of bisphosphonate gel, group 2; local application of recombinant human bone morphogenic protein 2 gel, group 3; local application of a mixed formula of both gels. The gel application was immediately preimplant insertion, group 4; implant insertion without application of a

Transition metal complexes of Co(II) and Ni(II) with azo dye 3,5-dimethyl-2-(4-nitrophenylazo)-phenol derived from 4-nitoaniline and3,5-dimethylphenol were synthesized. Characterization of these compounds has been done on the basis of elemental analysis,electronic data, FT-IR,UV-Vis and 1 HNMR, as well as magnetic susceptibility and conductivity measurements. The nature of thecomplexes formed were studies following the mole ratio and continuous variation methods, Beer ' s law obeyed over a concentrationrange (1x10 -4 - 3x10 -4 M). High molar absorbtivity of the complex solutions were observed. From the analytical data, thestoichiomerty of the complexes has been found to be 1:2 (Metal:ligand). On the basis of physicochemical data tetrahedral

Abstract Diabetic nephropathy (DN) is a prevalent chronic microvascular diabetic complication. As inflammation plays a vital role in the development and progress of DN the macrophages migration inhibitory factor (MIF), a proinflammatory multifunctional cytokine approved to play a critical function in inflammatory responses in various pathologic situations like DN. This study aimed To assess serum levels of MIF in a sample of Iraqi diabetic patients with nephropathy supporting its validity as a marker for predicting nephropathy in T2DM patients. In addition, to evaluate the nephroprotective effect of angiotensin-converting enzyme (ACE) inhibitors in terms of their influence on MIF levels. This is a case-control study involving ninety

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

Steady conjugate natural convection heat transfers in a two-dimensional enclosure filled with fluid saturated porous medium is studied numerically. The two vertical boundaries of the enclosure are kept isothermally at same temperature, the horizontal upper wall is adiabatic, and the horizontal lower wall is partially heated. The Darcy extended Brinkman Forcheimer model is used as the momentum equation and Ansys Fluent software is utilized to solve the governing equations. Rayleigh number (1.38 ≤ Ra ≤ 2.32), Darcy number (3.9 * 10-8), the ratio of conjugate wall thickness to its height (0.025 ≤ W ≤ 0.1), heater length to the bottom wall ratio (1/4 ≤  ≤ 3/4) and inclination angle (0°, 30° and 60°) are the main consid