Tecnologias da informação e comunicação na formação continuada de professores: estudode caso em escolas do Brasil e Portugal com recursos e aplicação do Google+

Tese de Doutoramento em Ciências da Educação (área de especialização em Tecnologia Educativa)

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Public service culture collections of microorganisms: are they important for biotechnology?

Microbiology as a scientific discipline recognised the need to preserve microorganisms for scientific studies establishing from its very beginning research culture collections (CC). Later on, to better serve different scientific fields and bioindustries with the increasing number of strains of scientific, medical, ecological and biotechnological importance public service CC were established with the specific aims to support their user communities. Currently, the more developed public service CC are recognised as microBiological Resources Centres (mBRC). mBRC are considered to be one of the key elements for sustainable international scientific infrastructure, which is necessary to underpin successful delivery of the benefits of biotechnology, whether within the health sector, the industrial sector or other sectors, and in turn ensure that these advances help drive economic growth. In more detail, mBRCs are defined by Organisation for Economic Co-operation and Development (OECD) as service providers and repositories of the living cells, genomes of organisms, and information relating to heredity and functions of biological systems. mBRCs contain collections of culturable organisms (e.g., microorganisms, plant, animal cells), replicable parts of these (e.g. genomes, plasmids, virus, cDNAs), viable but not yet culturable organisms, cells and tissues, as well as database containing molecular, physiological and structural information relevant to these collections and related bioinformatics. Thus mBRCs are fundamental to harnessing and preserving the world’s microbial biodiversity and genetic resources and serve as an essential element of the infrastructure for research and development. mBRCs serve a multitude of functions and assume a range of shapes and forms. Some are large national centres performing a comprehensive role providing access to diverse organisms. Other centres play much narrower, yet important, roles supplying limited but crucial specialised resources. In the era of the knowledge-based bio-economy mBRCs are recognised as vital element to underpinning the biotechnology.

A supervisão pedagógica como prática de transformação: o lugar das narrativas profissionais

Este texto tem como objetivo discutir o lugar das narrativas profissionais, de natureza autobiográfica, produzidas por professores em contexto de formação pós-graduada em supervisão pedagógica. Começando pela discussão do conceito de qualidade em educação, e que radica numa concepção de educação para o desenvolvimento sustentável e para a transformação de pessoas e de contextos, a autora passa para uma análise do papel dos professores no desenvolvimento de práticas pedagógicas de qualidade. Embora os contextos de educação e de formação tenham um papel determinante, os professores, principalmente através das expectativas que detêm face aos seus alunos, têm um papel crucial no combate a formas de discriminação e de exclusão nas escolas. O conceito de supervisão que informa este texto também se coloca ao serviço da qualidade em educação enunciada, ao ser tomado enquanto teoria e prática de regulação crítica e colaborativa da pedagogia e do desenvolvimento profissional, numa visão da educação para a transformação e para a sustentabilidade. O texto finaliza com a ilustração do modo como as narrativas profissionais se constituem enquanto estratégias de autossupervisão do trabalho docente num contexto de formação pós-graduada. Desenvolvidas em contextos profissionais, e estabelecendo pontes entre o conhecimento acadêmico e experiencial, elas incidem na análise dos modos como o trabalho docente se coloca (ou não) ao serviço de uma pedagogia e de um desenvolvimento profissional docente assente em valores de sustentabilidade e de transformação, identificando os constrangimentos estruturais e apontando rumos de ação.

All different or all the same? Exploring the diversity of professional practices in Portuguese school psychology

"Published online: 29 March 2016"

Que lugar para o ensino da filosofia na era da tecnologia e globalização?

Relatório de estágio de mestrado em Ensino de Filosofia no Ensino Secundário

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.