Avaliação da adaptação marginal de diferentes tipos de restaurações obtidas por CAD/CAM e métodos convencionais

The past few decades have brought many changes to the dental practice and the technology has become ready available. The result of a satisfactory rehabilitation treatment basically depends on the balance between biological and mechanical factors. The marginal adaptation of crowns and prosthetic structures is vital factor for long-term success. The development of CAD / CAM technology in the manufacture of dental prostheses revolutionized dentistry, this technology is capable of generating a virtual model from the direct digital scanning from the mouth, casts or impressions. It allows the planning and design of the structure in a computered software. The virtual projects are obtained with high precision and a significant reduction in clinical and laboratory time. Thus, the present study (Chapters 1, 2 and 3) computed microtomography was used to evaluate, different materials, different CAD/CAM systems, different ways of obtaining virtual model (with direct or indirect scanning), and in addition, also aims to evaluate the influence of cementing agent in the final adaptation of crowns and copings obtained by CAD / CAM. Furthermore, this study (Chapter 4, 5 and 6) also aims to evaluate significant differences in vertical and horizontal misfits in abutment-free frameworks on external hexagon implants (HE) using full castable UCLAs, castable UCLAs with cobalt-chromium pre-machined bases and obtained by CAD / CAM with CoCr or Zirconia by different scanning and milling systems. For this, the scanning electron microscopy and interferometry were used. It was concluded that the CAD / CAM technology is capable to produce restorations, copings and screw-retained implant-supported frameworks in different materials and systems offering satisfactory results of marginal accuracy, with significative reduction in clinical and laboratory time.

Estratificação de solos em camadas horizontais utilizando evolução diferencial

This work's objective is the development of a methodology to represent an unknown soil through a stratified horizontal multilayer soil model, from which the engineer may carry out eletrical grounding projects with high precision. The methodology uses the experimental electrical apparent resistivity curve, obtained through measurements on the ground, using a 4-wire earth ground resistance tester kit, along with calculations involving the measured resistance. This curve is then compared with the theoretical electrical apparent resistivity curve, obtained through calculations over a horizontally strati ed soil, whose parameters are conjectured. This soil model parameters, such as the number of layers, in addition to the resistivity and the thickness of each layer, are optimized by Differential Evolution method, with enhanced performance through parallel computing, in order to both apparent resistivity curves get close enough, and it is possible to represent the unknown soil through the multilayer horizontal soil model fitted with optimized parameters. In order to assist the Differential Evolution method, in case of a stagnation during an arbitrary amount of generations, an optimization process unstuck methodology is proposed, to expand the search space and test new combinations, allowing the algorithm to nd a better solution and/or leave the local minima. It is further proposed an error improvement methodology, in order to smooth the error peaks between the apparent resistivity curves, by giving opportunities for other more uniform solutions to excel, in order to improve the whole algorithm precision, minimizing the maximum error. Methodologies to verify the polynomial approximation of the soil characteristic function and the theoretical apparent resistivity calculations are also proposed by including middle points among the approximated ones in the verification. Finally, a statistical evaluation prodecure is presented, in order to enable the classication of soil samples. The soil stratification methodology is used in a control group, formed by horizontally stratified soils. By using statistical inference, one may calculate the amount of soils that, within an error margin, does not follow the horizontal multilayer model.