Objectives: To assess the performance of a novel resin-modified glass-ionomer cement (pRMGIC) bonded to various tooth tissues after two-time intervals. Methods: 192 sound human molars were randomly assigned to 3 groups (n = 64): sound enamel, demineralised enamel, sound dentine. Sixty-four teeth with natural carious lesions including caries-affected dentine (CAD) were selected. All substrates were prepared, conditioned and restored with pRMGIC (30% ethylene glycol methacrylate phosphate (EGMP, experimental), Fuji II LC (control), Fuji IX, and Filtek™ Supreme with Scotchbond ™ Universal Adhesive. Shear bond strength (SBS) was determined after 24 h and three months storage in SBF at 37C. The debonded surfaces were examined using stereomi

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

The researcher focused on the importance of the physical abilities of the tennis game, as this game is one of the games that are characterized by its specificity in performance as this game is characterized by continuous movement and dealing with different elements, so this game requires the development of muscle strength, which plays an important role in Performance skills in the game of tennis. There are several methods to develop strength, including flat hierarchical technique, which is one of the most common forms of training in the development of muscle strength.     As for the research problem, the researcher found a method that has an effect on the development of force. Therefore, the researcher tried to diversify a

These days, the world is facing a global environmental and sustainability problem due to the increasing generation of large amounts of waste through construction and demolition work, which causes a serious problem for the environment. Therefore, this research was conducted to get rid of the waste disposal problems, including old glass and concrete, which were used as recycled fine aggregates. Seven different mixtures were prepared. The first mixture was with the used sand, which is glass sand, and it was adopted as a reference mixture (ORPC), and three mixtures were prepared for each of the recycled materials (waste concrete and glass) and partially replaced by glass sand in different proportions (25, 50, and 75) %. Some

The aim of this work is to enhance the mechanical properties of the glass ionomer cement GIC (dental materials) by adding Zirconium Oxide ZrO₂ in both micro and nano particles. GIC were mixed with (3, 5 and 7) wt% of both ZrO₂ micro and nanoparticles separately. Compressive strength (CS), biaxial flexural strength (BFS), Vickers Microhardness (VH) and wear rate losses (WR) were investigated. The maximum compression strength was 122.31 MPa with 5 wt. % ZrO₂ micro particle, while 3wt% nanoparticles give highest Microhardness and biaxial flexural strength of 88.8 VHN and 35.79 MPa respectively. The minimum wear rate losses were 3.776µg/m with 7 wt. % ZrO₂ nanoparticle. GIC-contai

High temperature superconductor with nominal composition Bi1.6Pb0.4Sr1.8Ba0.2Ca2 Cu3O10+? was prepared by solid state reaction method. Two sets of samples have been prepared .The first one was quenched in air; the second set was quenched in liquid nitrogen. X-ray diffraction analyses showed an orthorhombic structure with two phases, high –Tc phase (2223) and low-Tc phase (2212) in addition to that impure phase was found. It has been observed that quenched in air samples display a sharp superconducting transition and a higher-Tc phase than that of the quenched in liquid nitrogen samples.

In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho

Fourier Transform-Infrared (FT-IR) spectroscopy was used to analyze gasoline engine oil (SAE 5W20) samples that were exposed to seven different oxidation times (0 h, 24 h, 48 h, 72 h, 96 h, 120 h, and 144 h) to determine the best wavenumbers and wavenumber ranges for the discrimination of the oxidation times. The thermal oxidation process generated oil samples with varying total base number (TBN) levels. Each wavenumber (400–3900 cm−1) and wavenumber ranges identified from the literature and this study were statistically analyzed to determine which wavenumbers and wavenumber ranges could discriminate among all oxidation times. Linear regression was used with the best wavenumbers and wavenumber ranges to predict oxidation time.