Background: Polymethylmethacrylate (PMMA) has relatively unsatisfactory mechanical properties such as low flexural strength and impact strength also dimensional instability. Material and method: Zirconium silicate nanoparticles were coated with a layer of trimethoxysilylpropylmethacrylate (TMSPM) before sonication in monomer (MMA) with the percentages 1% and 1.5% by weight then mixed with powder using conventional procedure, (150) samples were prepared and divided into three groups, each group consisted of (50) samples, the first group prepared from PMMA without addition (control), another group with the addition of 1% wt Zrsio4 nanoparticles (experimental) and the third one with 1.5% wt Zrsio4 nanoparticles (experimental). Each group

Background: Polymethyl methacrylate (PMMA) is the most commonly used material in denture fabrication. The material is far from ideal in fulfilling the mechanical requirements. Midline fracture; poor thermal conductivity and water sorption, are common problem in this material. The purpose of this study was to evaluate the effect of addition of surface treated Aluminum oxide nano fillers on some properties of heat cured (PMMA). Materials and methods: In addition to controlled group of heat cured PMMA the silanized (Al2O3) nanoparticles was added to PMMA powder by weight in three different percentages 1wt%, 2wt% and 3wt%, mixed by probe ultra-sonication machine. 200 specimens were constructed and divided into 5 groups according to the test (e

Discriminant analysis is a technique used to distinguish and classification an individual to a group among a number of  groups based on a linear combination of a set of relevant variables know discriminant function. In this research  discriminant analysis used to analysis data from repeated measurements design. We  will  deal  with the problem of  discrimination  and  classification in the case of  two  groups by assuming the Compound Symmetry covariance structure  under  the  assumption  of  normality for  univariate  repeated measures data.

 In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.

 In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.

A simple analytical method was used in the present work for the simultaneous quantification of Ciprofloxacin and Isoniazid in pharmaceutical preparations. UV-Visible spectrophotometry has been applied to quantify these compounds in pure and mixture solutions using the first-order derivative method. The method depends on the first derivative spectrophotometry using zero-cross, peak to baseline, peak to peak and peak area measurements. Good linearity was shown in the concentration range of 2 to 24 μg∙mL-1 for Ciprofloxacin and 2 to 22 μg∙mL-1 for Isoniazid in the mixture, and the correlation coefficients were 0.9990 and 0.9989 respectively using peak area mode. The limits of detection (LOD) and limits of quantification (LOQ) wer