Esthetic rehabilitation with ultra-thin ceramic veneers and direct mock-up in the treatment of dental erosion – Case report

Indexación: Scopus.Dental erosion is a high prevalence condition characterized by the loss of dental substance due to chemical agents. It can also be associated with �physical wear, affecting function and aesthetics. Ceramic veneers can provide effective solutions to patients affected by erosive disorders, by means of an indirect approach and minimal intervention. Recent advances in cementation techniques and ceramic materials have allowed their use in reduced thicknesses, known as "dental contact lenses" or "ultra-thin veneers". They contribute significantly to the preservation of the dental structures, having excellent models or mock ups in order to preview the final outcome. Case: The aim of this report is to communicate the use of this technique for the treatment and successful 12-months follow-up of a patient affected by dental erosion of the maxillary central incisors. Special interest was placed on direct mock-up, which is a simple technique not requiring laboratory steps. Luting of the lithium disilicate veneers was carried out with a light-curing resin cement and try-in pastes, yielding a very satisfactory result. Conclusion: Diagnosis and early treatment of this disorder allows the application of conservative techniques, such as ultra-thin veneers, which are seen as a promising alternative treatment to full coverage restorations and traditional ceramic veneers. © 2018, Universidad de Concepcion. All rights reserved.http://joralres.com/index.php/JOR/article/view/481/45

Structured Prediction of Sequences and Trees using Infinite Contexts

Linguistic structures exhibit a rich array of global phenomena, however commonly used Markov models are unable to adequately describe these phenomena due to their strong locality assumptions. We propose a novel hierarchical model for structured prediction over sequences and trees which exploits global context by conditioning each generation decision on an unbounded context of prior decisions. This builds on the success of Markov models but without imposing a fixed bound in order to better represent global phenomena. To facilitate learning of this large and unbounded model, we use a hierarchical Pitman-Yor process prior which provides a recursive form of smoothing. We propose prediction algorithms based on A* and Markov Chain Monte Carlo sampling. Empirical results demonstrate the potential of our model compared to baseline finite-context Markov models on part-of-speech tagging and syntactic parsing

Initial value representation for the SU(n) semiclassical propagator

The semiclassical propagator in the representation of SU(n) coherent states is characterized by isolated classical trajectories subjected to boundary conditions in a doubled phase space. In this paper we recast this expression in terms of an integral over a set of initial-valued trajectories. These trajectories are monitored by a filter that collects only the appropriate contributions to the semiclassical approximation. This framework is suitable for the study of bosonic dynamics in n modes with fixed total number of particles. We exemplify the method for a Bose-Einstein condensate trapped in a triple-well potential, providing a detailed discussion on the accuracy and efficiency of the procedure.Comment: 24 pages, 6 figure