The aim of this study is to formulate and evaluate ezetimibe nanoparticles using solvent antisolvent technology. Ezetimibe is a practically water-insoluble drug which acts as a lipid lowering drug that selectively inhibits the intestinal absorption of cholesterol and related phytosterols. Ezetimibe prepared as nano particles in order to improve its solubility and dissolution rate.

Thirty formulas were prepared and different stabilizing agents were used with different concentrations such as poly vinyl pyrrolidone (PVPK-30), poly vinyl alcohol (PVA), hydroxy propyl methyl cellulose E5 (HPMC), and poloxamer. The ratios of drug to stabilizers used to prepare the nanoparticles were 1: 2, 1:3 and 1:4.

The prepared nanoparticles

        This Research deals with estimation the reliability function for two-parameters Exponential distribution, using different estimation methods ; Maximum likelihood, Median-First Order Statistics, Ridge Regression, Modified Thompson-Type Shrinkage and Single Stage Shrinkage methods. Comparisons among the estimators were made using Monte Carlo Simulation based on statistical indicter mean squared error (MSE) conclude that the shrinkage method perform better than the other methods

Abstract—In this study, we present the experimental results of ultra-wideband (UWB) imaging oriented for detecting small malignant breast tumors at an early stage. The technique is based on radar sensing, whereby tissues are differentiated based on the dielectric contrast between the disease and its surrounding healthy tissues. The image reconstruction algorithm referred to herein as the enhanced version of delay and sum (EDAS) algorithm is used to identify the malignant tissue in a cluttered environment and noisy data. The methods and procedures are tested using MRI-derived breast phantoms, and the results are compared with images obtained from classical DAS variant. Incorporating a new filtering technique and multiplication procedure, t

The question of estimation took a great interest in some engineering, statistical applications, various applied, human sciences, the methods provided by it helped to identify and accurately the many random processes.

In this paper, methods were used through which the reliability function, risk function, and estimation of the distribution parameters were used, and the methods are (Moment Method, Maximum Likelihood Method), where an experimental study was conducted using a simulation method for the purpose of comparing the methods to show which of these methods are competent in practical application This is based on the observations generated from the Rayleigh logarithmic distribution (RL) with sample sizes

Background: The present work investigated the profile and biodiversity of the pathogenic streptococci species isolated from local and imported mozzarella soft cheese in Baghdad City from October 2022 to January 2023. The study aimed to examine the molecular characterization of 16Sr RNA gene in some streptococcus species isolates from mozzarella soft cheese in Baghdad city Methods: From 50 samples, 8 isolates in all were found and identified based on the VITEK, molecular, and sequencing of the 16SrRNA gene. The eight isolates represented Lactococcus cremoris. Streptococcus alactolyticus, Streptococcus sanguinis, and Streptococcus thoraltensis. The isolates were subjected to conventional PCR and electrophoresis to detect the 16SrRNA gene usi

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.