Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance

In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model. Copyright (c) 2011 John Wiley & Sons, Ltd.

New Optimization Algorithms for Structural Reliability Analysis

Solution of structural reliability problems by the First Order method require optimization algorithms to find the smallest distance between a limit state function and the origin of standard Gaussian space. The Hassofer-Lind-Rackwitz-Fiessler (HLRF) algorithm, developed specifically for this purpose, has been shown to be efficient but not robust, as it fails to converge for a significant number of problems. On the other hand, recent developments in general (augmented Lagrangian) optimization techniques have not been tested in aplication to structural reliability problems. In the present article, three new optimization algorithms for structural reliability analysis are presented. One algorithm is based on the HLRF, but uses a new differentiable merit function with Wolfe conditions to select step length in linear search. It is shown in the article that, under certain assumptions, the proposed algorithm generates a sequence that converges to the local minimizer of the problem. Two new augmented Lagrangian methods are also presented, which use quadratic penalties to solve nonlinear problems with equality constraints. Performance and robustness of the new algorithms is compared to the classic augmented Lagrangian method, to HLRF and to the improved HLRF (iHLRF) algorithms, in the solution of 25 benchmark problems from the literature. The new proposed HLRF algorithm is shown to be more robust than HLRF or iHLRF, and as efficient as the iHLRF algorithm. The two augmented Lagrangian methods proposed herein are shown to be more robust and more efficient than the classical augmented Lagrangian method.

A Robust Structural PGN Model for Control of Cell-Cycle Progression Stabilized by Negative Feedbacks

The cell division cycle comprises a sequence of phenomena controlled by a stable and robust genetic network. We applied a probabilistic genetic network (PGN) to construct a hypothetical model with a dynamical behavior displaying the degree of robustness typical of the biological cell cycle. The structure of our PGN model was inspired in well-established biological facts such as the existence of integrator subsystems, negative and positive feedback loops, and redundant signaling pathways. Our model represents genes interactions as stochastic processes and presents strong robustness in the presence of moderate noise and parameters fluctuations. A recently published deterministic yeast cell-cycle model does not perform as well as our PGN model, even upon moderate noise conditions. In addition, self stimulatory mechanisms can give our PGN model the possibility of having a pacemaker activity similar to the observed in the oscillatory embryonic cell cycle.

Minimally invasive esthetic therapy: a case report describing the advantages of a multidisciplinary approach

The decision-making process for the treatment of esthetic areas is based on the achievement of a healthy, harmonious, and pleasant smile. These conditions are directly associated with a solid knowledge of tooth anatomy and proportions, as well as the smile line, soft tissue morphology, and osseous architecture. To achieve these objectives, a multidisciplinary approach may be necessary to create long-term harmony between the final restoration and the adjacent teeth, and the health of the surrounding soft and hard tissues. This case report describes the application of a minimally invasive therapy on a 33-year-old woman seeking esthetic treatment. Minimally invasive periodontal plastic surgery associated with porcelain laminate veneers yielded satisfactory esthetics and minimal trauma to dental and periodontal tissues. Such a combined approach may be considered a viable option for the improvement of "white" and "red" esthetics.

Calculation of parameter ranges for robust gain tuning of power system controllers

This work proposes a computational tool to assist power system engineers in the field tuning of power system stabilizers (PSSs) and Automatic Voltage Regulators (AVRs). The outcome of this tool is a range of gain values for theses controllers within which there is a theoretical guarantee of stability for the closed-loop system. This range is given as a set of limit values for the static gains of the controllers of interest, in such a way that the engineer responsible for the field tuning of PSSs and/or AVRs can be confident with respect to system stability when adjusting the corresponding static gains within this range. This feature of the proposed tool is highly desirable from a practical viewpoint, since the PSS and AVR commissioning stage always involve some readjustment of the controller gains to account for the differences between the nominal model and the actual behavior of the system. By capturing these differences as uncertainties in the model, this computational tool is able to guarantee stability for the whole uncertain model using an approach based on linear matrix inequalities. It is also important to remark that the tool proposed in this paper can also be applied to other types of parameters of either PSSs or Power Oscillation Dampers, as well as other types of controllers (such as speed governors, for example). To show its effectiveness, applications of the proposed tool to two benchmarks for small signal stability studies are presented at the end of this paper.

Deltocyathiidae, an early-diverging family of Robust corals (Anthozoa, Scleractinia)

Over the last decade, molecular phylogenetics has called into question some fundamental aspects of coral systematics. Within the Scleractinia, most families composed exclusively by zooxanthellate species are polyphyletic on the basis of molecular data, and the second most speciose coral family, the Caryophylliidae (most members of which are azooxanthellate), is an unnatural grouping. As part of the process of resolving taxonomic affinities of caryophylliids', here a new Robust' scleractinian family (Deltocyathiidae fam. n.) is proposed on the basis of combined molecular (CO1 and 28S rDNA) and morphological data, accommodating the early-diverging clade of traditional caryophylliids (represented today by the genus Deltocyathus). Whereas this family captures the full morphological diversity of the genus Deltocyathus, one species, Deltocyathus magnificus, is an outlier in terms of molecular data, and groups with the Complex coral family Turbinoliidae. Ultrastructural data, however, place D.magnificus within Deltocyathiidae fam. nov. Unfortunately, limited ultrastructural data are as yet available for turbinoliids, but D.magnificus may represent the first documented case of morphological convergence at the microstructural level among scleractinian corals. Marcelo V.Kitahara, Centro de Biologia Marinha, Universidade de SAo Paulo, SAo SebastiAo, S.P. 11600-000, Brazil. E-mail:kitahara@usp.br