Background: Nickel-titanium (NiTi) archwires have become increasingly popular because of their ability to release constant light forces, which are especially useful during initial alignment and leveling phase. The aim of the present study was to investigate and compare the load–deflection characteristics of four commercially available NiTi archwires. Materials and methods: 200 NiTi 0.014, 0.016, 0.018, 0.016x0.022 and 0.019x0.025-inch nickel–titanium archwires from four different manufacturers (3M, Ortho Technology, Jiscop and Astar) were tested. The load-deflection properties of these archwires were evaluated by a full arch bending test in both palatal and gingival directionsat 37°C temperature using a universal material t

Theoretical and experimental investigations of free convection through a cubic cavity with sinusoidal heat flux at bottom wall, the top wall is exposed to an outside ambient while the other walls are adiabatic saturated in porous medium had been approved in the present work. The range of Rayleigh number was and Darcy number values were . The theoretical part involved a numerical solution while the experimental part included a set of tests carried out to study the free convection heat transfer in a porous media (glass beads) for sinusoidal heat flux boundary condition. The investigation enclosed values of Rayleigh number (5845.6, 8801, 9456, 15034, 19188 and 22148) and angles of inclinations (0, 15, 30, 45 and 60 degree). The numerical an

Background:The technology of nanoparticles has been expanded to many aspects of modern life. Titanium dioxide nanoparticles were of many nanomaterials utilized in biomedical applications. The interactions between nanoparticles and proteins are believed to be the base for the biological effect of the nanoparticles. The oxidation reaction of many substances is catalyzed by oxidizing enzymes called peroxidases. The activity of salivary peroxidase is elevated with periodontal diseases. the aim ofthis study is to examine the action of titanium dioxide nanoparticles on salivary peroxidase activity.Material and method75 participants were enrolled in this study—Periodontitis group with 44 participants and the non-periodontitis group with 31 pa

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

SUMMARY. – Nanocrystalline thin fi lms of CdS are deposited on glass substrate by chemical bath deposited technique using polyvinyl alcohol (PVA) matrix solution. Crystallite size of the nanocrystalline films are determining from broading of X-ray diffraction lines and are found to vary from 0.33-0.52 nm, an increase of molarity the grain size decreases which turns increases the band gap. The band gap of nanocrystalline material is determined from the UV spectrograph. The absorption edge and absorption coefficient increases when the molarity increases and shifted towards the lower wavelength.

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp