Background This study aimed to evaluate the efficacy of once-daily liraglutide as an add-on to oral antidiabetics (OADs) on glycemic control and body weight in obese patients with inadequately controlled type 2 diabetes (T2D). Methods A total of 27 obese T2D patients who received 7 months (0.6 mg/day for the first month, 1.2 mg/day for 3 months, and 1.8 mg/day for 3 months) of liraglutide treatment as an add-on to OADs were included. Data on body weight (kg), fasting plasma glucose (FPG, mg/dL), postprandial glucose (PPG, mg/dL), and HbA1c (%), were recorded. Results Liraglutide doses of 1.2 mg/day and 1.8 mg/day were associated with significant decreases in body weight (by 8.0% and 11.9%, respectively, p < 0.01 for each) and HbA1c (by 20.0

Tight reservoirs have attracted the interest of the oil industry in recent years according to its significant impact on the global oil product. Several challenges are present when producing from these reservoirs due to its low to extra low permeability and very narrow pore throat radius. Development strategy selection for these reservoirs such as horizontal well placement, hydraulic fracture design, well completion, and smart production program, wellbore stability all need accurate characterizations of geomechanical parameters for these reservoirs. Geomechanical properties, including uniaxial compressive strength (UCS), static Young’s modulus (Es), and Poisson’s ratio (υs), were measured experimentally using both static and dynamic met

     The stress(Y) – strength(X) model reliability Bayesian estimation which defines life of a component with strength X and stress Y (the component fails if and only if at any time the applied stress is greater than its strength) has been studied, then the reliability; R=P(Y<X), can be considered as a measure of the component performance. In this paper, a Bayesian analysis has been considered for R when the two variables X and Y are independent Weibull random variables with common parameter α in order to study the effect of each of the two different scale parameters β and λ; respectively, using three different [weighted, quadratic and entropy] loss functions under two different prior functions [Gamma and extension of Jeffery

In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

The two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival

This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa