Operacionalização do processo de raciocínio no estudo para o desenvolvimento técnico do violino

Relatório de estágio de mestrado em Ensino de Música

The urban morphology of Braga between Late Antiquity and the fourteenth-fifteenth centuries

This paper aims to approach the urban transformation processes occurring in the city of Braga between Late Antiquity and the fourteenth-fifteenth centuries. Our approach is based upon the cross-referencing of documental, iconographic and cartographic data with data emerging from archaeological works conducted across the city throughout the last two decades. Despite the scarcity in sources documenting the historical period under study, a similar circumstance registered in other western European cities, new and emerging archaeological data associated with a regressive analysis of available information for the forthcoming centuries —documents, maps, plans and illustrations, have been contributing towards an advance in the overall knowledge regarding the continuity and changing processes impacting upon the urban area of Braga. Thereby, our goal is to develop a synthesis work describing the major evolutionary stages happening in Braga from the fifth to the fifteenth centuries and based upon anintegrated analysis of the architectonic markers, the morphology present in the urban setting, the existing Christian topography, the defensive system and the main road network.

Ashbya gossypii beyond industrial riboflavin production: a historical perspective and emerging biotechnological applications

The filamentous fungus Ashbya gossypii has been safely and successfully used for more than two decades in the commercial production of riboflavin (vitamin B2). Its industrial relevance combined with its high genetic similarity with Saccharomyces cerevisiae together promoted the accumulation of fundamental knowledge that has been efficiently converted into a significant molecular and in silico toolbox for its genetic engineering. This synergy has enabled a directed and sustained exploitation of A. gossypii as an industrial riboflavin producer. Although there is still room for optimizing riboflavin production, the recent years have seen an abundant advance in the exploration of A. gossypii for other biotechnological applications, such as the production of recombinant proteins, single cell oil and flavour compounds. Here, we will address the biotechnological potential of A. gossypii beyond riboflavin production by presenting (a) a physiological and metabolic perspective over this fungus; (b) the molecular toolbox available for its manipulation; and (c) commercial and emerging biotechnological applications for this industrially important fungus, together with the approaches adopted for its engineering.

As últimas vontades dos paroquianos de Cervães: a análise dos testamentos do século XVIII

Dissertação de mestrado em História

O testamento vital: considerações gerais sobre as diretivas antecipadas de vontade

Dissertação de mestrado em Direito das Crianças, Família e Sucessões

Design of a case-based reasoner for information security in military organizations

Information security is concerned with the protection of information, which can be stored, processed or transmitted within critical information systems of the organizations, against loss of confidentiality, integrity or availability. Protection measures to prevent these problems result through the implementation of controls at several dimensions: technical, administrative or physical. A vital objective for military organizations is to ensure superiority in contexts of information warfare and competitive intelligence. Therefore, the problem of information security in military organizations has been a topic of intensive work at both national and transnational levels, and extensive conceptual and standardization work is being produced. A current effort is therefore to develop automated decision support systems to assist military decision makers, at different levels in the command chain, to provide suitable control measures that can effectively deal with potential attacks and, at the same time, prevent, detect and contain vulnerabilities targeted at their information systems. The concept and processes of the Case-Based Reasoning (CBR) methodology outstandingly resembles classical military processes and doctrine, in particular the analysis of “lessons learned” and definition of “modes of action”. Therefore, the present paper addresses the modeling and design of a CBR system with two key objectives: to support an effective response in context of information security for military organizations; to allow for scenario planning and analysis for training and auditing processes.

Step towards a patient timeline in intensive care units

In Intensive Medicine, the presentation of medical information is done in many ways, depending on the type of data collected and stored. The way in which the information is presented can make it difficult for intensivists to quickly understand the patient's condition. When there is the need to cross between several types of clinical data sources the situation is even worse. This research seeks to explore a new way of presenting information about patients, based on the timeframe in which events occur. By developing an interactive Patient Timeline, intensivists will have access to a new environment in real-time where they can consult the patient clinical history and the data collected until the moment. The medical history will be available from the moment in which patients is admitted in the ICU until discharge, allowing intensivist to examine data regarding vital signs, medication, exams, among others. This timeline also intends to, through the use of information and models produced by the INTCare system, combine several clinical data in order to help diagnose the future patients’ conditions. This platform will help intensivists to make more accurate decision. This paper presents the first approach of the solution designed

Algorithms and tools for in silico design of cell factories

PhD thesis in Bioengineering

Contratação Pública Verde: work in progress

Dissertação de mestrado em Direito Administrativo

Attachment orientation and caretaking memories in fathers during the transition to parenthood

Dissertação de mestrado em Psicologia Aplicada

A hybrid MAC Scheme to improve the transmission performance in body sensor networks

Wireless body sensor networks (WBSNs) constitute a key technology for closing the loop between patients and healthcare providers, as WBSNs provide sensing ability, as well as mobility and portability, essential characteristics for wide acceptance of wireless healthcare technology. However, one important and difficult aspect of WBSNs is to provide data transmissions with quality of service, among other factors due to the antennas being small size and placed close to the body. Such transmissions cannot be fully provided without the assumption of a MAC protocol that solves the problems of the medium sharing. A vast number of MAC protocols conceived for wireless networks are based on random or scheduled schemes. This paper studies firstly the suitability of two MAC protocols, one using CSMA and the other TDMA, to transmit directly to the base station the signals collected continuously from multiple sensor nodes placed on the human body. Tests in a real scenario show that the beaconed TDMA MAC protocol presents an average packet loss ratio lower than CSMA. However, the average packet loss ratio is above 1.0 %. To improve this performance, which is of vital importance in areas such as e-health and ambient assisted living, a hybrid TDMA/CSMA scheme is proposed and tested in a real scenario with two WBSNs and four sensor nodes per WBSN. An average packet loss ratio lower than 0.2 % was obtained with the hybrid scheme. To achieve this significant improvement, the hybrid scheme uses a lightweight algorithm to control dynamically the start of the superframes. Scalability and traffic rate variation tests show that this strategy allows approximately ten WBSNs operating simultaneously without significant performance degradation.

Cognitive functioning and efficacy of cognitive intervention in Multiple Sclerosis

Tese de Doutoramento em Psicologia Clínica / Psicologia

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.

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%.