Papel do tutor num currículo médico pré-graduado que utilize a aprendizagem por problemas

Educação Médica, 1993; 4(3): 169-173.

Mathematical modeling and simulation of heat flow through pultrusion die assembly system for thermoset composites

Pultrusion is an industrial process used to produce glass fibers reinforced polymers profiles. These materials are worldwide used when performing characteristics, such as great electrical and magnetic insulation, high strength to weight ratio, corrosion and weather resistance, long service life and minimal maintenance are required. In this study, we present the results of the modelling and simulation of heat flow through a pultrusion die by means of Finite Element Analysis (FEA). The numerical simulation was calibrated based on temperature profiles computed from thermographic measurements carried out during pultrusion manufacturing process. Obtained results have shown a maximum deviation of 7%, which is considered to be acceptable for this type of analysis, and is below to the 10% value, previously specified as maximum deviation. © 2011, Advanced Engineering Solutions.

Aplicação da filosofia Lean management:caso de estudo, aplicado à manutenção de edifícios

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia da Manutenção

Ascaris lumbricoides in neonate: evidence of congenital transmission of intestinal nematodes

Clinical and epidemiological study of a forty-days-old infant with a diarrheic condition and insufficient development led to the coprological diagnosis of ascariasis and possible congenital infection. Specific treatment with levamizole, resulted in clinical and parasitological cure, in addition to gain of weight up to normal levels. Maternal parasitism had been diagnosed two months before labor and proved beyond doubt during the ensuing epidemiological inquiry.

Grupos heterogéneos e a diferenciação pedagógica

Relatório de Prática Profissional Supervisionada, Mestrado em Educação Pré-Escolar

Quanto tempo dura um instante?: da dualidade do efémero e da permanência do serviço educativo

Relatório de Estágio submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro – Especialização em Produção

Biofunctional composite coating architectures based on polycaprolactone and nanohydroxyapatite for controlled corrosion activity and enhanced biocompatibility of magnesium AZ31 alloy

In this work a biofunctional composite coating architecture for controlled corrosion activity and enhanced cellular adhesion of AZ31 Mg alloys is proposed. The composite coating consists of a polycaprolactone (PCL) matrix modified with nanohydroxyapatite (HA) applied over a nanometric layer of polyetherimide (PEI). The protective properties of the coating were studied by electrochemical impedance spectroscopy (EIS), a non-disturbing technique, and the coating morphology was investigated by field emission scanning electron microscopy (FE-SEM). The results show that the composite coating protects the AZ31 substrate. The barrier properties of the coating can be optimized by changing the PCL concentration. The presence of nanohydroxyapatite particles influences the coating morphology and decreases the corrosion resistance. The biocompatibility was assessed by studying the response of osteoblastic cells on coated samples through resazurin assay, confocal laser scanning microscopy (CLSM) and scanning electron microscopy (SEM). The results show that the polycaprolactone to hydroxyapatite ratio affects the cell behavior and that the presence of hydroxyapatite induces high osteoblastic differentiation. (C) 2014 Elsevier B.V. All rights reserved.

Multi-strand narrative structures: a filmic game of multiple players

Session 7: Playing with Roles, images and improvising New States of Awareness, 3rd Global Conference, 1st November – 3rd November, 2014, Prague, Czech Republic.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Seroprevalence of HIV, HTLV-I/II and other perinatally-transmitted pathogens in Salvador, Bahia

Generation of epidemiological data on perinatally-transmitted infections is a fundamental tool for the formulation of health policies. In Brazil, this information is scarce, particularly in Northeast, the poorest region of the country. In order to gain some insights of the problem we studied the seroprevalence of some perinatally-transmitted infections in 1,024 low income pregnant women in Salvador, Bahia. The prevalences were as follow: HIV-1 (0.10%), HTLV-I/II (0.88%), T.cruzi (2.34%). T.pallidum (3.91%), rubella virus (77.44%). T.gondii IgM (2.87%) and IgG (69.34%), HBs Ag (0.6%) and anti-HBs (7.62%). Rubella virus and T.gondii IgG antibodies were present in more than two thirds of pregnant women but antibodies against other pathogens were present at much lower rates. We found that the prevalence of HTLV-I/II was nine times higher than that found for HIV-1. In some cases such as T.cruzi and hepatitis B infection there was a decrease in the prevalence over the years. On the other hand, there was an increase in the seroprevalence of T.gondii infection. Our data strongly recommend mandatory screening tests for HTLV-I/II, T.gondii (IgM), T.pallidum and rubella virus in prenatal routine for pregnant women in Salvador. Screening test for T.cruzi, hepatitis and HIV-1 is recommended whenever risk factors associated with these infections are suspected. However in areas with high prevalence for these infections, the mandatory screening test in prenatal care should be considered.

Análise dinâmica de composições musicais

A composição musical é um tema de muito interesse para a computação evolucionária dentro da área da inteligência artificial. É uma área que tem sofrido vários desenvolvimentos ao longo dos últimos anos pois o interesse em que hajam computadores que façam obras musicais é deveras aliciante. Este trabalho tem por objectivo realizar mais um passo nesse sentido. Assim, foi desenvolvida uma aplicação informática que realiza composições musicais de dois géneros distintos: Músicas Infantis e Músicas Blues. A aplicação foi implementada com recurso aos Algoritmos Genéticos, que são os algoritmos evolucionários mais populares da área da computação evolucionária. O trabalho foi estruturado em duas fases de desenvolvimento. Na primeira fase, realizou-se um levantamento estatístico sobre as características específicas de cada um dos géneros musicais. Analisaram-se quinze músicas de cada género musical, com o intuito de se chegar a uma proporção do uso que cada nota tem em cada um dos casos. Na segunda fase, desenvolveu-se o software que compõe as músicas com implementação de um algoritmo genético. Além disso, foi também desenvolvida uma interface gráfica que permite ao utilizador a escolha do género musical que pretende compor. O algoritmo genético começa por gerar uma população inicial de potenciais soluções de acordo com a escolha do utilizador, realizando, de seguida, o ciclo que caracteriza o algoritmo genético. A população inicial é constituída por soluções que seguem as regras que foram implementadas de acordo com os dados recolhidos ao longo da primeira fase. Foi também implementada uma interface de avaliação, através da qual, o utilizador pode ouvir cada uma das músicas para posterior avaliação em termos de fitness. O estado de evolução do algoritmo é apresentado, numa segunda interface, a qual facilita a clareza e justiça na avaliação ao longo de todo o processo. Esta última apresenta informação sobre a média das fitness da geração anterior e actual, sendo assim possível ter uma noção da evolução do algoritmo, no sentido de se obterem resultados satisfatórios no que diz respeito às composições musicais.

Vitamin D Intake and Cardiometabolic: Risk Factors in Adolescents

Background: A growing body of research suggests that vitamin D might play an important role in overall health. No data exist on vitamin D intake for the Azorean adolescent population. The purpose of this study was to assess vitamin D intake and investigate a possible association between vitamin D intake and cardiometabolic risk factors in Azorean adolescents. Methods: A cross-sectional school-based study was conducted on 496 adolescents (288 girls) aged 15–18 years from the Azorean Islands, Portugal. Anthropometric measurements (waist circumference and height), blood pressure (systolic), and plasma biomarkers [fasting glucose, insulin, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TGs)] were measured to assess metabolic risk. Homeostasis model assessment (HOMA), TC-to-HDL-C ratio, and waist-to-height ratio were calculated. For each of these variables, a Z-score was computed by age and sex. A metabolic risk score was constructed by summing the Zscores of all individual risk factors. High risk was considered when the individual had ‡ 1 standard deviation(SD) of this score. Vitamin D intake was assessed with a semiquantitative food frequency questionnaire. Participants were classified into quartiles of vitamin D intake. Logistic regression was used to determine odds ratios for high cardiometabolic risk scores after adjusting for total energy intake, pubertal stage, fat mass percentage, and cardiorespiratory fitness. Results: Mean (SD) vitamin D intake was 5.8 (6.5) mg/day, and 9.1% of Azorean adolescents achieved the estimated average requirement of vitamin D (10 mg/day or 400 IU). Logistic regression showed that the odds ratio for a high cardiometabolic risk score was 3.35 [95% confidence interval (CI) 1.28–8.75] for adolescents in the lowest vitamin D intake quartile in comparison with those in the highest vitamin D intake quartile, even after adjustment for confounders. Conclusion: A lower level of vitamin D intake was associated with worse metabolic profile among Azorean adolescents.

A process-based control for evolvable production systems

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Development of new methodologies in sample treatment for proteomics workflow based on enzymatic probe sonication technology and mass spectrometry

Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia, for the degree of Doctor of Philosophy in Biochemistry

Cultural Intelligence (CQ) in Erasmus Mundus Students and Alumni: an exploratory study on the levels and antecedents of CQ

Erasmus Mundus Masters (EMM) are programs with a strong component of interculturality. Our study aimed at understanding the level of cultural intelligence (CQ) of EMM students and alumni, as well as some of the characteristics associated with higher levels of CQ. The study included 626 EMM students and alumni from 109 different countries that encompasses 6 continents. Ang and Van Dyne’s (2006) cultural intelligence scale was used; closed and open ended questions were used to describe the sample’s sociodemographic characteristics and experiences regarding interculturality. After validating and assessing the scale’s psychometric properties, relations between different variables were explored using Pearson’s correlation, ANOVA, t Tests, and GLM procedures. We then analysed the open ended responses to gain further insight on our results. Differences among respondents are mainly equated with international experience rather than nationality or training. Respondents’ open ended replies provided us with a deeper insight on why training seems to be so ineffective in developing CQ. This is a transversal study that uses self-reporting measures; also, questionnaires were conducted in English, which was not the mother tongue of most of the respondents. This work is consistent with the CQ literature, however we argue that training mentioned by respondents systematically fails to meet some of literature’s foremost conditions for effective CQ trainings and provide clues for the implementation of more successful initiatives. With an exceptionally diverse sample, this study contributes towards the understanding of mechanisms of developing CQ among EMM and international Students. Results can be useful for selection processes, training/development of CQ and reducing dropout/turnover.