[An editorial to] Recent Advances on Knowledge Discovery and Business Intelligence

Special issue guest editorial, June, 2015.

Supercritical fluid and pharmaceutical applications. Part I: Process classification

The supercritical fluid technology has been target of many pharmaceuticals investigations in particles production for almost 35 years. This is due to the great advantages it offers over others technologies currently used for the same purpose. A brief history is presented, as well the classification of supercritical technology based on the role that the supercritical fluid (carbon dioxide) performs in the process.

Pervasive business intelligence: a marketing intelligence framework proposal

Doctoral Thesis in Information Systems and Technologies Area of Information Systems and Technology

Advancing tendon regeneration through the development of bio-stimulating tissue engineering approaches

Tendon tissue engineering (TE) requires tailoring scaffolds designs and properties to the anatomical and functional requirements of tendons located in different regions of the body. Cell sourcing is also of utmost importance as tendon cells are scarce. Recently, we have found that it is possible to direct the tenogenic differentiation of Amniotic fluid and Adipose tissue derived stem cells (hAFSCs and hASCs), and also that there are hASCs subpopulations that might be more prone to tenogenic differentiation. Nevertheless, biochemical stimulation may not be enough to develop functional TE substitutes for a tissue that is known to be highly dependent on mechanical loading.

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.

O meu ponto de vista é um ponto de escuta. O poder do som nos filmes de Manoel de Oliveira

Tese de Doutoramento em Ciências da Comunicação - Especialidade em Comunicação Audiovisual

Dispersion of fillers in viscoelastic polymer matrices using Eulerian-Lagrangian approaches

Understanding the behavior of c omplex composite materials using mixing procedures is fundamental in several industrial processes. For instance, polymer composites are usually manufactured using dispersion of fillers in polymer melt matrices. The success of the filler dispersion depends both on the complex flow patterns generated and on the polymer melt rheological behavior. Consequently, the availability of a numerical tool that allow to model both fluid and particle would be very useful to increase the process insight. Nowadays there ar e computational tools that allow modeling the behavior of filled systems, taking into account both the behavior of the fluid (Computational Rheology) and the particles (Discrete Element Method). One example is the DPMFoam solver of the OpenFOAM ® framework where the averaged volume fraction momentum and mass conservation equations are used to describe the fluid (continuous phase) rheology, and the Newton’s second law of motion is used to compute the particles (discrete phase) movement. In this work the refer red solver is extended to take into account the elasticity of the polymer melts for the continuous phase. The solver capabilities will be illustrated by studying the effect of the fluid rheology on the filler dispersion, taking into account different fluid types (generalized Newtonian or viscoelastic) and particles volume fraction and size. The results obtained are used to evaluate the relevance of considering the fluid complex rheology for the prediction of the composites morphology

Understanding the dispersion of fillers in polymer matrices

Understanding the mixing process of complex composite materials is fundamental in several industrial processes. For instance, the dispersion of fillers in polymer melt matrices is commonly employed to manufacture polymer composites, using a twin-screw extruder. The effectiveness of the filler dispersion depends not only on the complex flow patterns generated, but also on the polymer melt rheological behavior. Therefore, the availability of a numerical tool able to predict mixing, taking into account both fluid and particles phases would be very useful to increase the process insight, and thus provide useful guidelines for its optimization. In this work, a new Eulerian-Lagrangian numerical solver is developed OpenFOAM® computational library, and used to better understand the mechanisms determining the dispersion of fillers in polymer matrices. Particular attention will be given to the effect of the rheological model used to represent the fluid behavior, on the level of dispersion obtained. For the Eulerian phase the averaged volume fraction governing equations (conservation of mass and linear momentum) are used to describe the fluid behavior. In the case of the Lagrangian phase, Newton’s second law of motion is used to compute the particles trajectories and velocity. To study the effect of fluid behavior on the filler dispersion, several systems are modeled considering different fluid types (generalized Newtonian or viscoelastic) and particles volume fraction and size. The results obtained are used to correlate the fluid and particle characteristics on the effectiveness of mixing and morphology obtained.

Investigação qualitativa em psicologia da educação: estudo dos perfis de alunos de mérito escolar

A investigação qualitativa tem ocupado progressivamente um espaço no campo da investigação em Psicologia, nomeadamente em Psicologia da Educação. Neste trabalho ilustramos o recurso a esta metodologia no estudo da excelência académica. Os participantes foram dois alunos (um rapaz e uma rapariga) a frequentarem o 1o ciclo do ensino superior português, considerados de mérito académico. Os dados foram recolhidos através de entrevista semiestruturada e de provas psicológicas para avaliar a criatividade (TTCT) e a inteligência geral (D-48). Os resultados apontam para a pertinência de fatores motivacionais e de personalidade na justificação do desempenho académico elevado. Termina-se com algumas reflexões e linhas orientadoras para a continuidade dos estudos na área

Numerical simulation of the reflow soldering process

Dissertação de mestrado integrado em Mechanical Engineering

Modelação, simulação e implementação de agitação acústica para aplicações em microfluídica

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Marine Collagen/Apatite scaffolds envisaging tissue engineering applications

Despite the vast investigation and the large amount of products already available in the market to treat the different bone defects there is still a growing need to develop more advanced and complex therapeutic strategies. In this context, a mixture of Marine Hydroxyapatite-Fluorapatite:Collagen (HA-FP:ASC) seems to be a promising solution to overcome these bone defects, specifically, dental defects. HA-FP particles (20–63 μm) were obtained through pyrolysis (950°C, 12 h) of shark teeth (Isurus oxyrinchus, P. glauca), and Type I collagen was isolated from Prionace glauca skin as previously described (1). After the steps of purification, collagen was solubilized in 0.5 M acetic acid and HA-FP added producing three different formulations: were produced, 30:70, 50:50 and 70:30 of HA-FP:ASC, respectively. EDC/NHS and HMDI binding agents were used to stabilize the produced scaffolds. Mechanical properties were evaluated by compression tests. SEM analysis allowed observing the mineral deposition, after immersion in simulated body fluid and also permitted to evaluate how homogenous was the distribution of HA-FP in the different scaffold formulations, also confirmed by μ-CT assay. It was readily visible by Cytotoxicity and life/dead CLSM assays that cells were able to adhere and proliferate in the produced scaffolds. Scaffolds crosslinked with EDC/NHS showed lower cytotoxicity, being the ones chosen for further cellular evaluation.

Algumas considerações sobre o princípio da culpa enquanto factor de autonomização do Direito das Contra-ordenações

Dissertação de mestrado em Direito Judiciário

Predicting pre-triage waiting time in a maternity emergency room through data mining

An unsuitable patient flow as well as prolonged waiting lists in the emergency room of a maternity unit, regarding gynecology and obstetrics care, can affect the mother and child’s health, leading to adverse events and consequences regarding their safety and satisfaction. Predicting the patients’ waiting time in the emergency room is a means to avoid this problem. This study aims to predict the pre-triage waiting time in the emergency care of gynecology and obstetrics of Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto, situated in the north of Portugal. Data mining techniques were induced using information collected from the information systems and technologies available in CMIN. The models developed presented good results reaching accuracy and specificity values of approximately 74% and 94%, respectively. Additionally, the number of patients and triage professionals working in the emergency room, as well as some temporal variables were identified as direct enhancers to the pre-triage waiting time. The imp lementation of the attained knowledge in the decision support system and business intelligence platform, deployed in CMIN, leads to the optimization of the patient flow through the emergency room and improving the quality of services.