Abstract

Abstract

Abstract
Background and study aims Efficacy and adverse events probabilities influence decisions regarding the best options to manage patients with gastric superficial lesions. We aimed at developing a Bayesian model to individualize the prediction of outcomes after gastric endoscopic submucosal dissection (ESD). Patients and methods Data from 245 gastric ESD were collected, including patient and lesion factors. The two endpoints were curative resection and post-procedural bleeding (PPB). Logistic regression and Bayesian networks were built for each outcome; their predictive value was evaluated in-sample and validated through leave-one-out and cross-validation. Clinical decision support was enhanced by the definition of risk matrices, direct use of Bayesian inference software and by a developed online platform. Results ESD was curative in 85.3% and PPB occurred in 7.7% of patients. In univariate analysis, male sex, ASA status, carcinoma histology, polypoid or depressed morphology, and lesion size >= 20mm were associated with non-curative resection, while ASA status, antithrombotics and lesion size >= 20mm were associated with PPB. Naive Bayesian models presented AUROCs of similar to 80% in the derivation cohort and >= 74% in cross-validation for both outcomes. Risk matrices were computed, showing that lesions with cancer at biopsies, >= 20mm, proximal or in the middle third, and polypoid are more prone to non-curative resection. PPB risk was <5% in lesions <20mm in the absence of antithrombotics. Conclusions The derived Bayesian model presented good discriminative power in the prediction of ESD outcomes and can be used to predict individualized probabilities, improving patient information and supporting clinical and management decisions.

Abstract
O presente artigo problematiza aspectos éticos, epistemológicos e metodológicos relacionados ao campo da pesquisa em educação e cultura digital. A partir da reflexão sobre como a ética pode dialogar com as escolhas ao se fazer pesquisa, apresenta os caminhos adotados no contexto de duas pesquisas conduzidas entre os anos de 2010 e 2015 junto a uma escola pública estadual da região metropolitana de Porto Alegre participante de programas governamentais de inclusão digital. Com base no método cartográfico de pesquisa e intervenção, apresenta alguns dos resultados das discussões realizadas junto a professores e estudantes a partir da experiência de produzir e publicar informações na Internet. Problematiza o dilema ético da pesquisa-intervenção com base na ideia de apropriação tecnológica como um processo que se estabelece a partir das mudanças de significado sobre práticas que se produzem em contextos da cultura escolar analógica e da cultura digital. Discute e propõe, com base nos resultados da pesquisa, a superação do dilema ético relacionado à participação de crianças e jovens estudantes em pesquisas que envolvam a publicação de conteúdo online e os receios com relação à exposição midiática – produção e acesso a conteúdo inadequado – e à desatenção em sala de aula.

Abstract

Abstract
This paper addresses a strategy to improve disturbance rejection for the Sliding Mode Controller designed in a Smith Predictor scheme (SMC-SP), with its parameters tuned through the bio-inspired search algorithm—Particle Swarm Optimization (PSO). Conventional SMC-SP is commonly based on tuning equations derived from step response identification, when First Order Plus Dead Time models (FOPDT) are considered and therefore controller parameters are previously set. Online PSO tuning based on minimization of the Integral of Time Absolute Error (ITAE) can provide faster recovery from external disturbances without significant increase of energy consumption, and the Sliding Mode feature deals with possible model mismatch. Simulation results for time delayed systems corroborating these benefits are presented. © Springer International Publishing Switzerland 2017.