The most prevalent chronic complication of diabetes mellitus is diabetic neuropathy. The pathogenesis of diabetic neuropathy is exacerbated by hyperglycemia-induced oxidative stress, which causes nerves to deteriorate in a programmed manner. Many clinical trials depend on supplement in an attempt to improve neuropathy symptoms such as (pain & tingling) and patient quality of life, one of them is Coenzyme Q10 which is reported to have an anti-inflammatory and antioxidant effects, and was totally nontoxic and non-reported side effects. This study aimed to evaluate using a Coenzyme Q10 supplement as an adjuvant therapy to gabapentin to improve the clinical symptoms of diabetic neuropathy in relation to its anti-inflammatory and antioxid

Humanity's relationship with the environment is a delicate balance. Since the industrial revolution, the world's population has grown at an exponential rate, and this has a major environmental effect. Deforestation, pollution, and global climate change are just a few of the negative consequences of population and technological growth. Particulates, Sulphur dioxide (SO2), and nitrogen oxides (NOx) are the primary pollutants that harm our health. These contaminants may be directly emitted into the atmosphere (primary pollutants) or formed in the atmosphere from primary pollutants reacting (secondary pollutants. Tropospheric ozone is created When water reacts with volatile organic compounds (VOC) and nitrogen oxides (NOx) in the presen

This research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro

In this paper, the maximum likelihood estimates for parameter ( ) of two parameter's Weibull are studied, as well as white estimators and (Bain & Antle) estimators, also Bayes estimator for scale parameter ( ), the simulation procedures are used to find the estimators and comparing between them using MSE. Also the application is done on the data for 20 patients suffering from a headache disease.

In this paper  has been one study of autoregressive generalized conditional heteroscedasticity models existence of the seasonal component, for the purpose applied to the daily financial data at high frequency is characterized by Heteroscedasticity seasonal conditional, it has been depending on Multiplicative seasonal Generalized Autoregressive Conditional Heteroscedastic Models Which is symbolized by the Acronym (SGARCH) , which has proven effective expression of seasonal phenomenon as opposed to the usual GARCH models. The summarizing of the research work studying the daily data for the price of the dinar exchange rate against the dollar, has been used autocorrelation function to detect seasonal first, then was diagnosed wi

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