A inflação pela imaginação: Estudo dos efeitos interferentes

Tese de Doutoramento em Psicologia (Especialidade de Psicologia Experimental e Ciências Cognitivas)

Real-time monitoring of progression towards renal failure in primary care patients

First published online: December 16, 2014.

Análise técnica - económica da produção de energia em sistemas de abastecimento de água: caso do aproveitamento de fins múltiplos dos socorridos

Dissertação de mestrado integrado em Engenharia Civil

Plataforma de suporte à decisão médica para transplante de órgãos baseada em Business Intelligence

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

Financiamento bancário e o desempenho das empresas em portugal: qual a relação?

Dissertação de mestrado em Economia Monetária, Bancária e Financeira

Relatório de atividade profissional

Relatório de atividade profissional de mestrado em Ciências – Formação Contínua de Professores (área de especialização em Matemática)

Hazard assessment of storm events for the battery, New York

The environmental and socio-economic importance of coastal areas is widely recognized, but at present these areas face severe weaknesses and high-risk situations. The increased demand and growing human occupation of coastal zones have greatly contributed to exacerbating such weaknesses. Today, throughout the world, in all countries with coastal regions, episodes of waves overtopping and coastal flooding are frequent. These episodes are usually responsible for property losses and often put human lives at risk. The floods are caused by coastal storms primarily due to the action of very strong winds. The propagation of these storms towards the coast induces high water levels. It is expected that climate change phenomena will contribute to the intensification of coastal storms. In this context, an estimation of coastal flooding hazards is of paramount importance for the planning and management of coastal zones. Consequently, carrying out a series of storm scenarios and analyzing their impacts through numerical modeling is of prime interest to coastal decision-makers. Firstly, throughout this work, historical storm tracks and intensities are characterized for the northeastern region of United States coast, in terms of probability of occurrence. Secondly, several storm events with high potential of occurrence are generated using a specific tool of DelftDashboard interface for Delft3D software. Hydrodynamic models are then used to generate ensemble simulations to assess storms' effects on coastal water levels. For the United States’ northeastern coast, a highly refined regional domain is considered surrounding the area of The Battery, New York, situated in New York Harbor. Based on statistical data of numerical modeling results, a review of the impact of coastal storms to different locations within the study area is performed.

The alarm distress baby scale in a longitudinal Portuguese study reanalyzed with attachment data

Article first published online: 13 NOV 2013

A avaliação da fluência oral em crianças do 3º ano do ensino básico com e sem necessidades educativas especiais: um estudo exploratório quantitativo

Dissertação de mestrado em Educação Especial (área de especialização em Dificuldades de Aprendizagem Específicas)

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.