A comparative evaluation of polymerization stress data obtained with four different mechanical testing systems

Objectives. The null hypothesis was that mechanical testing systems used to determine polymerization stress (sigma(pol)) would rank a series of composites similarly. Methods. Two series of composites were tested in the following systems: universal testing machine (UTM) using glass rods as bonding substrate, UTM/acrylic rods, "low compliance device", and single cantilever device ("Bioman"). One series had five experimental composites containing BisGMA:TEGDMA in equimolar concentrations and 60, 65, 70, 75 or 80 wt% of filler. The other series had five commercial composites: Filtek Z250 (3M ESPE), Filtek A110 (3M ESPE), Tetric Ceram (Ivoclar), Heliomolar (Ivoclar) and Point 4 (Kerr). Specimen geometry, dimensions and curing conditions were similar in all systems. sigma(pol) was monitored for 10 min. Volumetric shrinkage (VS) was measured in a mercury dilatometer and elastic modulus (E) was determined by three-point bending. Shrinkage rate was used as a measure of reaction kinetics. ANOVA/Tukey test was performed for each variable, separately for each series. Results. For the experimental composites, sigma(pol) decreased with filler content in all systems, following the variation in VS. For commercial materials, sigma(pol) did not vary in the UTM/acrylic system and showed very few similarities in rankings in the others tests system. Also, no clear relationships were observed between sigma(pol) and VS or E. Significance. The testing systems showed a good agreement for the experimental composites, but very few similarities for the commercial composites. Therefore, comparison of polymerization stress results from different devices must be done carefully. (c) 2012 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

An online data access prediction and optimization approach for distributed systems

Current scientific applications have been producing large amounts of data. The processing, handling and analysis of such data require large-scale computing infrastructures such as clusters and grids. In this area, studies aim at improving the performance of data-intensive applications by optimizing data accesses. In order to achieve this goal, distributed storage systems have been considering techniques of data replication, migration, distribution, and access parallelism. However, the main drawback of those studies is that they do not take into account application behavior to perform data access optimization. This limitation motivated this paper which applies strategies to support the online prediction of application behavior in order to optimize data access operations on distributed systems, without requiring any information on past executions. In order to accomplish such a goal, this approach organizes application behaviors as time series and, then, analyzes and classifies those series according to their properties. By knowing properties, the approach selects modeling techniques to represent series and perform predictions, which are, later on, used to optimize data access operations. This new approach was implemented and evaluated using the OptorSim simulator, sponsored by the LHC-CERN project and widely employed by the scientific community. Experiments confirm this new approach reduces application execution time in about 50 percent, specially when handling large amounts of data.

Gaussian deconvolution: a useful method for a form-free modeling of scattering data from mono- and multilayered planar systems

A new method for analysis of scattering data from lamellar bilayer systems is presented. The method employs a form-free description of the cross-section structure of the bilayer and the fit is performed directly to the scattering data, introducing also a structure factor when required. The cross-section structure (electron density profile in the case of X-ray scattering) is described by a set of Gaussian functions and the technique is termed Gaussian deconvolution. The coefficients of the Gaussians are optimized using a constrained least-squares routine that induces smoothness of the electron density profile. The optimization is coupled with the point-of-inflection method for determining the optimal weight of the smoothness. With the new approach, it is possible to optimize simultaneously the form factor, structure factor and several other parameters in the model. The applicability of this method is demonstrated by using it in a study of a multilamellar system composed of lecithin bilayers, where the form factor and structure factor are obtained simultaneously, and the obtained results provided new insight into this very well known system.