Type 2 daibetes mellitus (T2DM) is a global concern boosted by both population growth and ageing, the majority of affected people are aged between (40- 59 year). The objective of this research was to estimate the impact of age and gender on glycaemic control parameters: Fasting blood glucose (FBC), glycated hemoglobin (HbA1C), insulin, insulin resistance (IR) and insulin sensitivity (IS), renal function parameters: urea, creatinine and oxidative stress parameters: total antioxidant capacity (TAC) and reactive oxygen species (ROS). Eighty-one random samples of T2DM patients (35 men and 46 women) were included in this study, their average age was 52.75±9.63 year. Current study found that FBG, HbA1C and IR were highly significant (P<0.01) inc

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 seed propagation is the predominant method of Echinacea propagation, which has been criticized for its time-consuming control over the separation factor and the uncertainty of pathogen-free plants produced by this method. The technology of tissue culture has provided multiple opportunities for the production of secondary metabolites continuously without being restricted to a specific season, due to the possibility of controlling the environmental conditions and the components of the nutrient medium needed by the plant. This study was conducted to investigate the effects of salicylic acid as elicitor and tyrosine as precursor on propagation and some secondary compounds production in coneflower in vitro. The result showed the superiori

Two field experiments were conducted during the spring season 2020 in Karbala governorate to study the effect of irrigation systems, irrigation intervals, biofertilizers and polymers on some characteristics of vegetative growth and potato production. The results showed that there were significant differences in the values of the average plant height due to the effect of the double interference between the irrigation system and the improvers, The height of potato plant under any irrigation system was superior when adding conditioners compared to the control treatment, as it reached 48.56, 58.00 and 64.33cm when adding polymer, biofertilizer, and polymers+ biofertilizers, respectively compared with the control treatment of 44.64cm in the surf

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

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