This study is planned to find relationship between interleukin-33 (IL-33) with its receptor interleukin-1 receptor 4 (IL-1R4), and assurance IL-33/IL-1R4 proportion as biomarker to atherosclerosisin rheumatoid arthritis (RA) Iraqi female’s patients with and without dyslipidemia. This study was attempted at Baghdad Teaching Hospital included 60 female’s patients with RA that were isolated into: 30 patients with dyslipidemia(G2), 30 patients without dyslipidemia(G3) and 30 individuals as control group (G1). Patients were experiencing treatment by methortexiene medication, analyzed by rheumatoid factor (RF) and erythrocyte sedimentation rate (ESR) tests. All patients and control groups age ranged from (30-55) years. The results show an inc

The corrosion inhibiting properties of the new furan derivative 5-(furan-2-ylmethylsulfonyl-4-phenyl-2,4- dihydro [1,2,4] triazole-3-thione in acidic solution (1.0 M HCl) were explored utilizing electrochemical, surface morphology (AFM), and quantum chemical calculations approaches. The novel furan derivative 5-(furan-2-ylmethylsulfonyl-4-phenyl-2,4- dihydro [1,2,4] triazole-3-thione shows with an inhibitory efficiency value of 99.4 percent at 150 ppm, carbon steel corrosion in acidic medium is effectively inhibited, according to the results. The influence of temperature on corrosion prevention was studied using adsorption parameters and activation thermodynamics. The novel furan derivative creates a protective layer over the metallic surfa

Natural Bauxite (BXT) mineral clay was modified with a cationic surfactant (hexadecy ltrimethy lammonium bromide (BXT-HDTMA)) and characterized with different techniques: FTIR spectroscopy, X-ray powder diffraction (XRD) and scanning electron microscopy (SEM). The modified and natural bauxite (BXT) were used as adsorbents for the adsorption of 4- Chlorophenol (4-CP) from aqueous solutions. The adsorption study was carried out at different conditions and parameters: contact time, pH value, adsorbent dosage and ionic strength. The adsorption kinetic (described by a pseudo-first order and a pseudo-second order), equilibrium experimental data (analyzed by Langmuir, Freundlich and Temkin isotherm models) and thermodynamic parameters (change in s

Numerical study is adapted to combine between piezoelectric fan as a turbulent air flow generator and perforated finned heat sinks. A single piezoelectric fan with different tip amplitudes placed eccentrically at the duct entrance. The problem of solid and perforated finned heat sinks is solved and analyzed numerically by using Ansys 17.2 fluent, and solving three dimensional energy and Navier–Stokes equations that set with RNG based k−ε scalable wall function turbulent model. Finite volume algorithm is used to solve both phases of solid and fluid. Calculations are done for three values of piezoelectric fan amplitudes 25 mm, 30 mm, and 40 mm, respectively. Results of this numerical study are compared with previous b

Background: During the COVID-19 outbreak, the number of patients who have developed acute coronary syndromes (ACS) has soared rapidly, cardiovascular disease and mortality are influenced by the elevated inflammatory biomarkers. The aim of this study is to compare inflammatory markers between patients with ACS who hadn’t previously had COVID-19 and those who’d be infected within the preceding three months; as well as, evaluating the effect of statins on inflammatory biomarkers.

Methods: This is a comparative cross-sectional study of 42 patients who presented with ACS and had previously had COVID-19 and 48 patient who had never had CO

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F