Background: Several pathologies of the oral cavity have been associated with stress. Dental students need to gain assorted proficiencies as theoretical knowledge, clinical proficiencies, and interpersonal dexterity which is accompanied with high level of stress. Uric acid is the major antioxidant in saliva. The aim of this study is to assess the dental caries experience among dental students with different levels of dental environment stress in relation to physicochemical characteristics of whole unstimulated saliva.

Materials and Methods: the total sample is composed of 300 dental students (73 males, 227 female) aged 22-23 years old, from collage of dentistry / university of Baghdad, from the 4t

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.

Objectives: Successful endodontic treatment outcome requires effective shaping and cleaning of root canals. This study aims to evaluate the smear layer removal after continuous chelation (CC) ) NaOCL\HEDP( and sequential chelation (SC) )NaOCL\EDTA( and their influence on the push-out bond strength (POBS) of Bio-C sealer. Materials and Methods: Palatal roots of the maxillary first molar (n=72) were divided into four groups (n=18) as follows: 3% NaOCL, SC: 3% NaOCL followed by 17% EDTA, CC: 3% NaOCL \9% HEDP and Distilled water. Thirty-two roots (n=8/group) were split longitudinally for smear layer evaluation using SEM. Forty roots were obturated with Guttapercha and Bio-C sealer using a single cone technique. Thre

Abstract

    Binary polymer blend was prepared by mechanical mixing method of unsaturated polyester resin with Nitrile Butadiene Rubber (NBR) with different weight ratios (0, 5, 10 and 15) % of (NBR). Tensile characteristics and wear rates of these blends were studied for all mixing ratios. The microstructure of fracture surfaces of the prepared samples were investigated by optical microscope. The results were showed that strain rates of the resin material increase after blending it with rubber while the ultimate tensile strength and Young’s modulus values of it will decrease. It is also noticed that the wear rate of resin decreases with increasing of (NBR) content.

Keywords:<

One of the unique properties of laser heating applications is its powerful ability for precise pouring of energy on the needed regions in heat treatment applications. The rapid rise in temperature at the irradiated region produces a high temperature gradient, which contributes in phase metallurgical changes, inside the volume of the irradiated material. This article presents a comprehensive numerical work for a model based on experimentally laser heated AISI 1110 steel samples. The numerical investigation is based on the finite element method (FEM) taking in consideration the temperature dependent material properties to predict the temperature distribution within the irradiated material volume. The finite element analysis (FEA) was carried

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri