Background: Dental implants provide a unique treatment modality for the replacement of lost dentition .This is accomplished by the insertion of relatively inert material (a biomaterial) into the soft and hard tissue of the jaws, there by providing support and retention for dental prostheses. Low level laser therapy (LLLT) is an effective tool used to prompt bone repair and modeling post surgery; this has referred to the biostimulation effect of LLLT. The aims of this study were to evaluate the immmunohistochemical expression of vascular endothelial growth factor (VEGF) and transforming growth factor -beta (TGF-β) in experimental and control groups with mechanical test. Materials and Methods: Thirty two adult New Zealand white rabbits use

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

This work is devoted to the modeling of streamer discharge, propagation in liquid dielectrics (water) gap using the bubble theory. This of the electrical discharge (streamer) propagating within a dielectric liquid subjected to a divergent electric field, using finite element method (in two dimensions). Solution of Laplace's equation governs the voltage and electric field distributions within the configuration, the electrode configuration a point (pin) - plane configuration, the plasma channels were followed, step to step. The results show that, the electrical discharge (streamer) indicates the breakdown voltage required for a 3mm atmospheric pressure dielectric liquid gap as 13 kV. Also, the electric potential and field distributions sho

The research aims to determine the required rate of return according to the Fama and French five-factor model, after strengthening it by adding the indebtedness factor to build the Fama and French six-factor model FF6M-DLE. The effect of the indebtedness factor on the company's profitability and the real value of the ordinary shares calculated according to the (equivalent ascertainment) model and its suitability with the company's situation, and an analysis of the fluctuation between the market value and the real value of the ordinary stocks.

Insulin like growth factor-1 has metabolic and growth-related roles all over the body and is strongly associated and regulated by growth hormone. It is produced by almost any type of tissue, especially the liver. The study aimed to measure insulin like growth factor in growth hormone deficient patients and find its relation with other studied parameters. The Subjects in the study were 180 studied in the National Diabetic Center for Treatment and Research/Al-Mustansiriya University in Baghdad/Iraq for the period from November 2021 to April 2022. Blood was drawn and investigated for the levels of IGF-1, IGFBP-3, LH, and FSH. Also testosterone and statistical analysis was carried out to find the potential correlations. The results relived t

Abstract

The research Compared two methods for estimating fourparametersof the compound exponential Weibull - Poisson distribution which are the maximum likelihood method and the Downhill Simplex algorithm. Depending on two data cases, the first one assumed the original data (Non-polluting), while the second one assumeddata contamination. Simulation experimentswere conducted for different sample sizes and initial values of parameters and under different levels of contamination. Downhill Simplex algorithm was found to be the best method for in the estimation of the parameters, the probability function and the reliability function of the compound distribution in cases of natural and contaminateddata.

In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of Bayes est

In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of B