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001). The cytotoxicity of Tetric N-Ceram Bulk-fil composite resin was higher than that of the two other composite resins. Conclusion. Pre-heating of bulk-fill composite resin did not affect their cytotoxicity. In addition, the cytotoxicity of different bulk-fill composite resins was not the same.Background. This study evaluated the phase transformation of NiTi orthodontic wires and forces they release on deactivation. Methods. The structural phase transformations of the following five thermo-activated nickel-titanium (NiTi) wires were evaluated using differential scanning calorimetry (DSC) Flexy Thermal Sentalloy® (GAC International), NiTi (35ºC) (Eurodonto), Thermo-Plus® (Morelli), FlexyNiTi® Flexy Thermal (35ºC) (Orthometric) and Damon® CuNiTi (35ºC) (ORMCO Corp.). The wires had a cross-section of 0.40 mm (0.016"). In addition, the forces they released were investigated using the three-point bending test. Five arches of each wire were tested using DSC (-20/80ºC at 10ºC/min), and six arches from each wire were sectioned for bending tests. The data were analyzed with ANOVA and post hoc Tukey tests. Pearson's correlation test was performed between the results yielded by the DSC tests and those by three-point analyses (P=0.05). Results. The DSC analysis showed differences between the NiTi alloys from all the manufacturers, with no differences between the lots of the same brand. ORMCO and Orthometric wires exhibited similar TTR values in cooling (P=0.49), and statistically similar TTR values in heating (P=0.056). The three-point bending test showed different patterns in releasing forces. A correlation was found between the DSC analysis and the three-point bending test results. Conclusion. Y-27632 purchase The higher the temperature transformation was, the larger was the variation of force. All the wires presented higher forces at 3-mm deflection from 155 (±12.3) to 168.1 (±8) cN. The DSC analysis and the three-point bending test showed differences between the NiTi alloys from all the manufacturers.Background. Mineral trioxide aggregate (MTA) and Calcium-enriched Mixture (CEM) cement are used for pulp capping since they induce the formation of a dentinal bridge. Long setting time is a shortcoming of these types of cement. This study aimed to assess the effect of the incorporation of some alkaline salts to MTA and CEM cement on their setting time, ion release profile, pH, and surface morphology. Methods. In this in vitro experimental study, 5% calcium chloride (CaCl2), calcium oxide (CaO), sodium fluoride (NaF), and calcium nitrate [Ca(NO3)2] were separately added to MTA and CEM cement. The primary and final setting times of the cements were measured using a Gillmore needle apparatus. The samples were immersed in simulated body fluid (SBF) for one, seven, and 14 days and subjected to x-ray diffraction (XRD) and scanning electron microscopy (SEM) for phase identification and surface morphology assessment. The change in the pH of solutions was studied, and the calcium ion release profile was determined using inductively coupled plasma atomic emission spectroscopy (ICP-AES). The data were analyzed with ANOVA, followed by post hoc tests. Results. CaCl2 and CaO decreased the setting time of MTA, and Ca(NO3)2 decreased the setting time of CEM cement. The incorporation of the salts increased the pH and calcium ion release from both cements, and hydroxyapatite deposits were noted to cover the surface of the samples (observed by SEM and confirmed by EDXA). Conclusion. The incorporation of CaCl2 and CaO into MTA and Ca(NO3)2 into CEM cement decreased their setting time and increased their pH and calcium ion release.Graphene oxide (GO) is a good nanofiller candidate for waterborne coatings because of its outstanding physical and mechanical properties, good dispersibility in water, and low cost relative to graphene. Here, we report on the performance of a one-part, waterborne polyurethane (WPU) nanocoating formulated with four different GO loadings ([0.4% to 2.0%] by mass). The degree of GO dispersion/adhesion was evaluated using scanning electron microscopy, laser scanning confocal microscopy, and Raman microscopy. Nanocoating performance was evaluated using a dynamic mechanical thermal analyzer for mechanical properties, a customized coulometric permeation apparatus for oxygen barrier properties, a combustion microcalorimeter for flammability, a hot disk analyzer for thermal conductivity, thermogravimetric analysis for thermal stability, and a moisture sorption analyzer for water uptake. The results show that GO sheets were well dispersed in, and have good adhesion to, WPU. At the higher mass loadings ([1.2% or 2%] by mass), GO increased the modulus and yield strength of WPU by 300% and 200%, respectively, increased the thermal conductivity by 38%, reduced the burning heat release rate (flammability) by 43%, and reduced the oxygen permeability by up to sevenfold. The presence of GO, however, increased water vapor uptake at high humidity; the moisture content of 2% mass loading GO/WPU nanocoatings at 90% RH was almost twice that of the moisture content for unfilled WPU. Overall, with the exception of water uptake at very high humidity (> 70% RH), the observed improvements in physical and mechanical properties combined with the ease of processing suggest that GO is a viable nanofiller for WPU coatings.Computerized fluid dynamics models of particle deposition in the human airways are used to characterize deposition patterns that enable the study of lung diseases like asthma and chronic obstructive pulmonary disease (COPD). Despite this fact, the influence of patient-specific geometry on the deposition efficiency and patterns is not well documented nor modeled. In part, this is due to the complexity of simulating the full Computational Fluid Dynamics (CFD) solution in patient-specific airway geometries, a factor that becomes a major hurdle for patient-specific studies given the complexity of the geometry of human lungs and their related airflow. In this paper, we present an approximation method based on neural networks to the Navier-Stokes equations that govern airway flow in a Physiologically Realistic Bifurcation (PRB) model for the conducting region of a single generation human airway branch. The flow distribution and deposition of tobacco particles have been simulated for the inspiratory regime using ANSYS Fluent and a neural network has been trained to regress the mean velocity and mass flow components.