An experiment was conducted to study how SAE 50 engine oil contaminated with diesel fuel affects engine performance. The engine oil was contaminated with diesel fuel at concentrations of 0%, 1%, and 3%. The following performance characteristics were studied: brake-specific fuel consumption, brake thermal efficiency, friction power, and exhaust gas temperature. Each treatment was tested three times. The three treatments (0%, 1%, and 3%) were analyzed statistically with a one-way ANOVA model at the 5% probability level to determine if the three treatments produced significant differences in engine performance. The statistical results showed that there were significant differences in engine performance metrics among the three treatments. The 3

  Many production companies suffers from big losses because of  high production cost and low profits for several reasons, including raw materials high prices and no taxes impose on imported goods also consumer protection law deactivation and national product and customs law, so most of consumers buy imported goods because it is characterized by modern specifications and low prices.

  The production company also suffers from uncertainty in the cost, volume of production, sales, and availability of raw materials and workers number because they vary according to the seasons of the year.

  I had adopted in this research fuzzy linear program model with fuzzy figures

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.

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

Using an environmentally friendly chemical process, a novel nanocomposite consisting of reduced graphene oxide (rGO) and silver(I) oxide (Ag2O) nanoparticles was successfully synthesized in this work, and its optical properties along with photoelectric performance were investigated. Ag2O is a narrow-bandgap p-type semiconductor with strong visible light response but exhibits poor carrier separation and structural instability during exposure to radiation. In order to overcome shortcomings encountered with Ag2O, rGO was used as a conductive support to produce rGO@Ag2O nanocomposites with improved electronic interactions. Various characterization tests, including energy-dispersive X-ray spectroscopy (EDXS), field emission scanning electron mic

Background: The collagen triple helix repeat containing 1 (CTHRC1) protein has been connected to decreased levels of vitamin D and calcium, as well as obesity. This study aimed to investigate the relationship between CTHRC1 and osteoporosis in post-menopausal women and compare with healthy subjects. Subjects and Methods: A cross-sectional study consisted of 86 women were enrolled in this study and divided into three groups based on the results of dual-energy densitometry (DXA): 30 women with osteoporosis, 30 women with osteopenia, and 26 healthy women. Data on demographic and clinical features and laboratory values of Calcium (Ca) and Vitamin D3 (V.D3) were recorded. Results: Women with osteoporosis had significantly increased level

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