Destructive weighted Poisson cure rate models

In this paper, we develop a flexible cure rate survival model by assuming the number of competing causes of the event of interest to follow a compound weighted Poisson distribution. This model is more flexible in terms of dispersion than the promotion time cure model. Moreover, it gives an interesting and realistic interpretation of the biological mechanism of the occurrence of event of interest as it includes a destructive process of the initial risk factors in a competitive scenario. In other words, what is recorded is only from the undamaged portion of the original number of risk factors.

A flexible model for survival data with a cure rate: a Bayesian approach

In this paper we deal with a Bayesian analysis for right-censored survival data suitable for populations with a cure rate. We consider a cure rate model based on the negative binomial distribution, encompassing as a special case the promotion time cure model. Bayesian analysis is based on Markov chain Monte Carlo (MCMC) methods. We also present some discussion on model selection and an illustration with a real dataset.

Changes on degree of conversion of dual-cure luting light-cured with blue LED

The indirect adhesive procedures constitute recently a substantial portion of contemporary esthetic restorative treatments. The resin cements have been used to bond tooth substrate and restorative materials. Due to recently introduction of the self-bonding resin luting cement based on a new monomer, filler and initiation technology has become important to study the degree of conversion of these new materials. In the present work the polymerization reaction and the filler content of dual-cured dental resin cements were studied by means of infra-red spectroscopy (FT-IR) and thermogravimetry (TG). Twenty specimens were made in a metallic mold (8 mm diameter x 1 mm thick) from each of 2 cements, PanaviaA (R) F2.0 (Kuraray) and RelyX (TM) Unicem Applicap (3M/ESPE). Each specimen was cured with blue LED with power density of 500 mW/cm(2) for 30 s. Immediately after curing, 24 and 48 h, and 7 days DC was determined. For each time interval 5 specimens were pulverized, pressed with KBr and analyzed with FT-IR. The TG measurements were performed in Netzsch TG 209 under oxygen atmosphere and heating rate of 10A degrees C/min from 25 to 700A degrees C. A two-way ANOVA showed DC (%) mean values statistically significance differences between two cements (p < 0.05). The Tukey`s test showed no significant difference only for the 24 and 48 h after light irradiation for both resin cements (p > 0.05). The Relx-Y (TM) Unicem mean values were significantly higher than PanaviaA (R) F 2.0. The degree of conversion means values increasing with the storage time and the filler content showed similar for both resin cements.

Thermoset matrix reinforced with sisal fibers: Effect of the cure cycle on the properties of the biobased composite

Thermoset phenolic composites reinforced with sisal fibers were prepared to optimize the cure step. In the present study, processing parameters such as pressure, temperature, and time interval were varied to control the vaporization of the water generated as a byproduct during the crosslinking reaction. These molecules can vaporize forming voids, which in turn affect the final material properties. The set of results on impact strength revealed that the application of higher pressure before the gel point of the phenolic matrix produced composites with better properties. The SEM images showed that the cure cycle corresponding to the application of higher values of molding pressure at the gel point of the phenolic resin led to the reduction of voids in the matrix. In addition, the increase in the molding pressure during the cure step increased the resin interdiffusion. Better filling of the fiber channels decreased the possibility of water molecules diffusing through the internal spaces of the fibers. These molecules then diffused mainly through the bulk of the thermoset matrix, which led to a decrease in the water diffusion coefficient (D) at all three temperatures (25, 55 and 70 degrees C) considered in the experiments. (C) 2009 Elsevier Ltd. All rights reserved.