An evolutionary approach to the use of Petri net based models: from parallel controllers to HW/SW co-design

"A workshop within the 19th International Conference on Applications and Theory of Petri Nets - ICATPN’1998"

On the frictional contacts in multibody system dynamics

"Series title: Computational methods in applied sciences, ISSN1871-3033, vol. 42"

Evaluation of inflammatory response induced by different types of daily contact lenses

Dissertação de mestrado em Genética Molecular

Real-Time models to predict the use of vasopressors in monitored patients

The needs of reducing human error has been growing in every field of study, and medicine is one of those. Through the implementation of technologies is possible to help in the decision making process of clinics, therefore to reduce the difficulties that are typically faced. This study focuses on easing some of those difficulties by presenting real-time data mining models capable of predicting if a monitored patient, typically admitted in intensive care, will need to take vasopressors. Data Mining models were induced using clinical variables such as vital signs, laboratory analysis, among others. The best model presented a sensitivity of 94.94%. With this model it is possible reducing the misuse of vasopressors acting as prevention. At same time it is offered a better care to patients by anticipating their treatment with vasopressors.

Modelos Mixtos-Aditivos Generalizados para el Estudio de Fenómenos Biológicos y Sociales Descriptos por Datos Agregados y/o Longitudinales. Generalized Mixed Additive Models for the Study of Biological and Social Phenomenons from Longitudinal and/or Aggregated Data.

Este proyecto propone extender y generalizar los procesos de estimación e inferencia de modelos aditivos generalizados multivariados para variables aleatorias no gaussianas, que describen comportamientos de fenómenos biológicos y sociales y cuyas representaciones originan series longitudinales y datos agregados (clusters). Se genera teniendo como objeto para las aplicaciones inmediatas, el desarrollo de metodología de modelación para la comprensión de procesos biológicos, ambientales y sociales de las áreas de Salud y las Ciencias Sociales, la condicionan la presencia de fenómenos específicos, como el de las enfermedades.Es así que el plan que se propone intenta estrechar la relación entre la Matemática Aplicada, desde un enfoque bajo incertidumbre y las Ciencias Biológicas y Sociales, en general, generando nuevas herramientas para poder analizar y explicar muchos problemas sobre los cuales tienen cada vez mas información experimental y/o observacional.Se propone, en forma secuencial, comenzando por variables aleatorias discretas (Yi, con función de varianza menor que una potencia par del valor esperado E(Y)) generar una clase unificada de modelos aditivos (paramétricos y no paramétricos) generalizados, la cual contenga como casos particulares a los modelos lineales generalizados, no lineales generalizados, los aditivos generalizados, los de media marginales generalizados (enfoques GEE1 -Liang y Zeger, 1986- y GEE2 -Zhao y Prentice, 1990; Zeger y Qaqish, 1992; Yan y Fine, 2004), iniciando una conexión con los modelos lineales mixtos generalizados para variables latentes (GLLAMM, Skrondal y Rabe-Hesketh, 2004), partiendo de estructuras de datos correlacionados. Esto permitirá definir distribuciones condicionales de las respuestas, dadas las covariables y las variables latentes y estimar ecuaciones estructurales para las VL, incluyendo regresiones de VL sobre las covariables y regresiones de VL sobre otras VL y modelos específicos para considerar jerarquías de variación ya reconocidas. Cómo definir modelos que consideren estructuras espaciales o temporales, de manera tal que permitan la presencia de factores jerárquicos, fijos o aleatorios, medidos con error como es el caso de las situaciones que se presentan en las Ciencias Sociales y en Epidemiología, es un desafío a nivel estadístico. Se proyecta esa forma secuencial para la construcción de metodología tanto de estimación como de inferencia, comenzando con variables aleatorias Poisson y Bernoulli, incluyendo los existentes MLG, hasta los actuales modelos generalizados jerárquicos, conextando con los GLLAMM, partiendo de estructuras de datos correlacionados. Esta familia de modelos se generará para estructuras de variables/vectores, covariables y componentes aleatorios jerárquicos que describan fenómenos de las Ciencias Sociales y la Epidemiología.

Optimising the design and manufacture of a customised, prescription fit, Maxillo-facial prosthesis

This thesis is a continuation of the Enterprise-Ireland Research Innovation Fund (RIF) Project entitled’ "Design and Manufacturing of Customised Maxillo-Facial Prostheses" The primary objective of this Internal Research Development Program (IRDP) project was to investigate two fundamental design changes 1 To incorporate the over-denture abutments directly into the implant. 2 To remove the restraining wings by the addition of screws, which affix the. implant to the dense material of the jawbone. The prosthetic was redesigned using the ANSYS Finite Element Analysis software program and analysed to* • Reduce the internal von Mises stress distribution The new prosthetic had a -63.63 % lower von Mises stress distribution when compared with the original prosthetic. • Examine the screw preload effects. A maximum relative displacement of 22 6 * lO^mm between the bone and screw was determined, which is well below the critical threshold of micromotion which prevents osseointegration • Investigate the prosthetic-bone contact interface. Three models of the screw, prosthesis, and bone, were studied. (Axisymmetnc, quarter volume, and full volume), a recommended preload torque of 0 32 Nm was applied to the prosthetic and a maximum von Mises stress of 1.988 MPa was predicted • Study the overdenture removal forces. This analysis could not be completed because the correct plastic multilinear properties of the denture material could not be established The redesigned prosthetic was successfully manufactured on a 3-axis milling machine with an indexing system The prosthetic was examined for dimensional quality and strength The research established the feasibility of the new design and associated manufacturing method.

Data mining with graphical models

Data Mining, Learning from data, graphical models, possibility theory

Data-driven system identification via evolutionary retrieval of Takagi-Sugeno fuzzy models

Systemidentification, evolutionary automatic, data-driven model, fuzzy Takagi-Sugeno grammar, genotype interpretability, toxicity-prediction

Models and methods for supporting lot sizing decisions in product recovery systems

Magdeburg, Univ., Fak. für Wirtschaftswiss., Diss., 2011

Contact processing within walking robots' design

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2011

Approximations of the Fisher information for the construction of efficient experimental designs in nonlinear mixed effects models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2012

Experimental design for mixed models with application to population pharmacokinetic studies

experimental design, mixed model, random coefficient regression model, population pharmacokinetics, approximate design

One-year Mortality after an Acute Coronary Event and its Clinical Predictors: The ERICO Study

Background:Information about post-acute coronary syndrome (ACS) survival have been mostly short-term findings or based on specialized, cardiology referral centers.Objectives:To describe one-year case-fatality rates in the Strategy of Registry of Acute Coronary Syndrome (ERICO) cohort, and to study baseline characteristics as predictors.Methods:We analyzed data from 964 ERICO participants enrolled from February 2009 to December 2012. We assessed vital status by telephone contact and official death certificate searches. The cause of death was determined according to the official death certificates. We used log-rank tests to compare the probabilities of survival across subgroups. We built crude and adjusted (for age, sex and ACS subtype) Cox regression models to study if the ACS subtype or baseline characteristics were independent predictors of all-cause or cardiovascular mortality.Results:We identified 110 deaths in the cohort (case-fatality rate, 12.0%). Age [Hazard ratio (HR) = 2.04 per 10 year increase; 95% confidence interval (95%CI) = 1.75–2.38], non-ST elevation myocardial infarction (HR = 3.82 ; 95%CI = 2.21–6.60) or ST elevation myocardial infarction (HR = 2.59; 95%CI = 1.38–4.89) diagnoses, and diabetes (HR = 1.78; 95%CI = 1.20‑2.63) were significant risk factors for all-cause mortality in the adjusted models. We found similar results for cardiovascular mortality. A previous coronary artery disease diagnosis was also an independent predictor of all-cause mortality (HR = 1.61; 95%CI = 1.04–2.50), but not for cardiovascular mortality.Conclusion:We found an overall one-year mortality rate of 12.0% in a sample of post-ACS patients in a community, non-specialized hospital in São Paulo, Brazil. Age, ACS subtype, and diabetes were independent predictors of poor one‑year survival for overall and cardiovascular-related causes.

Development and Validation of Predictive Models of Cardiac Mortality and Transplantation in Resynchronization Therapy

AbstractBackground:30-40% of cardiac resynchronization therapy cases do not achieve favorable outcomes.Objective:This study aimed to develop predictive models for the combined endpoint of cardiac death and transplantation (Tx) at different stages of cardiac resynchronization therapy (CRT).Methods:Prospective observational study of 116 patients aged 64.8 ± 11.1 years, 68.1% of whom had functional class (FC) III and 31.9% had ambulatory class IV. Clinical, electrocardiographic and echocardiographic variables were assessed by using Cox regression and Kaplan-Meier curves.Results:The cardiac mortality/Tx rate was 16.3% during the follow-up period of 34.0 ± 17.9 months. Prior to implantation, right ventricular dysfunction (RVD), ejection fraction < 25% and use of high doses of diuretics (HDD) increased the risk of cardiac death and Tx by 3.9-, 4.8-, and 5.9-fold, respectively. In the first year after CRT, RVD, HDD and hospitalization due to congestive heart failure increased the risk of death at hazard ratios of 3.5, 5.3, and 12.5, respectively. In the second year after CRT, RVD and FC III/IV were significant risk factors of mortality in the multivariate Cox model. The accuracy rates of the models were 84.6% at preimplantation, 93% in the first year after CRT, and 90.5% in the second year after CRT. The models were validated by bootstrapping.Conclusion:We developed predictive models of cardiac death and Tx at different stages of CRT based on the analysis of simple and easily obtainable clinical and echocardiographic variables. The models showed good accuracy and adjustment, were validated internally, and are useful in the selection, monitoring and counseling of patients indicated for CRT.

Optimal designs for mixed effects poisson regression models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2010