Generative Model for Layers of Appearance and Deformation

Abstract

The dimensional alterations of denture bases were verified in function of the acrylic resin post-pressing time. Twenty stone cast/wax base sets were confected for routine flasking procedure. Thermosetting acrylic resin (Clássico) was prepared according to the instructions of the manufacturer. After final pressing, the acrylic resin was submitted to polymerization in water at 74 degrees C during 9 hours, following the immediate, 6-, 12-, and 24-hour post-pressing times. The resin bases were fixed on the casts with instantaneous adhesive and the sets were laterally sectioned in the regions corresponding to the distal aspect of canines (A), mesial aspect of first molars (B), and posterior palatal zone (C). The gap between the stone cast and the resin base was measured with a comparative microscope at five referential positions for each kind of sectioning. Data submitted to ANOVA and Tukey's test showed that there was no statistically significant difference between the immediate and the 6-hour post-pressing times as well as between the 12- and the 24-hour post-pressing times. However, there was statistically significant difference between the immediate/6-hour groups and the 12-/24-hour groups.

Cite

Text

Kannan et al. "Generative Model for Layers of Appearance and Deformation." Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005. doi:10.1590/s1517-74912001000200006

Markdown

[Kannan et al. "Generative Model for Layers of Appearance and Deformation." Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005.](https://mlanthology.org/aistats/2005/kannan2005aistats-generative/) doi:10.1590/s1517-74912001000200006

BibTeX

@inproceedings{kannan2005aistats-generative,
  title     = {{Generative Model for Layers of Appearance and Deformation}},
  author    = {Kannan, Anitha and Jojic, Nebojsa and Frey, Brendan},
  booktitle = {Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics},
  year      = {2005},
  pages     = {166-173},
  doi       = {10.1590/s1517-74912001000200006},
  volume    = {R5},
  url       = {https://mlanthology.org/aistats/2005/kannan2005aistats-generative/}
}