Multidisciplinary approach for the aesthetic treatment of maxillary lateral incisors agenesis: thinking about implants?

Missing maxillary lateral incisors create an esthetic problem with specific orthodontic and prosthetic considerations. Implants are commonly used to replace congenitally missing lateral incisors in adolescent orthodontic patients. However, an interdisciplinary approach should be observed during the diagnosis, prognosis, and treatment plan to provide a result with good predictability and meet the esthetic and functional expectations of the patient. The present study describes a case of a young patient with tooth agenesis of maxillary lateral incisors, which was conducted with an integrated planning. After 5-year follow-up of 2 fixed implant-supported prostheses, clinical and radiographic examination showed the treatment to be successful. (Oral Surg Oral Med Oral Pathol Oral Radiol 2012;114:e22-e28)

Efficient robust optimization based on polynomial chaos and tabu search algorithm

The study of robust design methodologies and techniques has become a new topical area in design optimizations in nearly all engineering and applied science disciplines in the last 10 years due to inevitable and unavoidable imprecision or uncertainty which is existed in real word design problems. To develop a fast optimizer for robust designs, a methodology based on polynomial chaos and tabu search algorithm is proposed. In the methodology, the polynomial chaos is employed as a stochastic response surface model of the objective function to efficiently evaluate the robust performance parameter while a mechanism to assign expected fitness only to promising solutions is introduced in tabu search algorithm to minimize the requirement for determining robust metrics of intermediate solutions. The proposed methodology is applied to the robust design of a practical inverse problem with satisfactory results.

Robust CERN LHC Higgs boson search in weak boson fusion

We demonstrate that a CERN LHC Higgs boson search in weak boson fusion production with subsequent decay to weak boson pairs is robust against extensions of the standard model or minimal supersymmetric standard model involving a large number of Higgs doublets. We also show that the transverse mass distribution provides unambiguous discrimination of a continuum Higgs signal from the standard model.

The non-twist standard map with robust tori

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Robust tori in a double-waved Hamiltonian model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Robust tori-like Lagrangian coherent structures

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effect of robust torus on the dynamical transport

In the present work, we quantify the fraction of trajectories that reach a specific region of the phase space when we vary a control parameter using two symplectic maps: one non-twist and another one twist. The two maps were studied with and without a robust torus. We compare the obtained patterns and we identify the effect of the robust torus on the dynamical transport. We show that the effect of meandering-like barriers loses importance in blocking the radial transport when the robust torus is present.

Interference of robust tori on the resonance overlap

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Well-conditioned robust observer for detection of family systems components

A new concept of fault detection and isolation using robust observation for systems with random noises is presented. The method selects the parameters from components that may fault during the process and constructs well conditioned robust observers, considering sensors faults. To isolate component failures via robust observation, a bank of detection observers is constructed, where each observer is only sensitive to one specified component failure while robust to all other component failures.

Multidisciplinary approach to chronic pain from myofascial pain dysfunction syndrome: A four-year experience at a Brazilian center

Chronic pain is the major complaint of myofascial pain dysfunction syndrome (MPDS) and is a complex problem which involves physical, psychological and social aspects, the etiology of MPDS is multifactorial and the multidisciplinary approach is essential for differential diagnosis and for comprehensive treatment planning, In 1993, the Dental School of Piracicaba-UNICAMP, Brazil, opened a Center for Pain Studies (CPS), staffed by health care providers including, dentists, psychologists, physicians, physiotherapists and phonoaudiologists. The major aims of the CPS are to provide clinical care and to develop basic and applied research, Sixty-two MPDS patients had been admitted to the CPS by 1997, There were 60 females and 2 males, mean age -32.5 years, the mean duration of chronic pain was 48 months. Pain intensity and unpleasantness were measured employing the Visual Analogue Scale, the tendency to develop stress-related diseases was assessed by the Social Readjustment de Scale, There was a mean reduction of chronic pain of 69.89% and 71.78% relative to intensity and unpleasantness, respectively, the experience of clinical attendance at a multidisciplinary center showed the relevance of a team consisting of health care providers from different specialties with well-established aims, completely integrated and sensitive enough to understand the painful complaints of MPDS patients.

Robust state-derivative feedback LMI-based designs for multivariable linear systems

In some practical problems, for instance in the control systems for the suppression of vibration in mechanical systems, the state-derivative signals are easier to obtain than the state signals. New necessary and sufficient linear matrix inequalities (LMI) conditions for the design of state-derivative feedback for multi-input (MI) linear systems are proposed. For multi-input/multi-output (MIMO) linear time-invariant or time-varying plants, with or without uncertainties in their parameters, the proposed methods can include in the LMI-based control designs the specifications of the decay rate, bounds on the output peak, and bounds on the state-derivative feedback matrix K. These design procedures allow new specifications and also, they consider a broader class of plants than the related results available in the literature. The LMIs, when feasible, can be efficiently solved using convex programming techniques. Practical applications illustrate the efficiency of the proposed methods.

Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Well-conditioned robust observer for detection of faulty systems components

A new concept of fault detection and isolation using robust observation for systems with random noises is presented. The method selects the parameters from components that may fault during the process and constructs well conditioned robust observers, considering sensors faults. To isolate component failures via robust observation, a bank of detection observers is constructed, where each observer is only sensitive to one specified component failure while robust to all other component failures.

Assessing relationships between genetic evaluations using robust regression with an application to holsteins in Uruguay

Globalization of dairy cattle breeding has created a need for international sire proofs. Some early methods for converting proofs from one population to another are based on simple linear regression. An alternative robust regression method based on the t-distribution is presented, and maximum likelihood and Bayesian techniques for analysis are described, including the situation in which some proofs are missing. Procedures were used to investigate the relationship between Holstein sire proofs obtained by two Uruguayan genetic evaluation programs. The results suggest that conversion equations developed from data including only sires having proofs in both populations can lead to distorted results, relative to estimates obtained using techniques for incomplete data. There was evidence of non-normality of regression residuals, which constitutes an additional source of bias. A robust estimator may not solve all problems, but can provide simple conversion equations that are less sensitive to outlying proofs and to departures from assumptions.