Re-use assessment of thermoset composite wastes as aggregate and filler replacement for concrete-polymer composite materials: a case study regarding GFRP pultrusion wastes

Glass fibre-reinforced plastics (GFRP), nowadays commonly used in the construction, transportation and automobile sectors, have been considered inherently difficult to recycle due to both the cross-linked nature of thermoset resins, which cannot be remoulded, and the complex composition of the composite itself, which includes glass fibres, polymer matrix and different types of inorganic fillers. Hence, to date, most of the thermoset based GFRP waste is being incinerated or landfilled leading to negative environmental impacts and additional costs to producers and suppliers. With an increasing awareness of environmental matters and the subsequent desire to save resources, recycling would convert an expensive waste disposal into a profitable reusable material. In this study, the effect of the incorporation of mechanically recycled GFRP pultrusion wastes on flexural and compressive behaviour of polyester polymer mortars (PM) was assessed. For this purpose, different contents of GFRP recyclates (0%, 4%, 8% and 12%, w/w), with distinct size grades (coarse fibrous mixture and fine powdered mixture), were incorporated into polyester PM as sand aggregates and filler replacements. The effect of the incorporation of a silane coupling agent was also assessed. Experimental results revealed that GFRP waste filled polymer mortars show improved mechanical behaviour over unmodified polyester based mortars, thus indicating the feasibility of GFRP waste reuse as raw material in concrete-polymer composites.

Sustainable waste recycling solution for the glass fibre reinforced polymer composite materials industry

In this paper the adequacy and the benefit of incorporating glass fibre reinforced polymer (GFRP) waste materials into polyester based mortars, as sand aggregates and filler replacements, are assessed. Different weight contents of mechanically recycled GFRP wastes with two particle size grades are included in the formulation of new materials. In all formulations, a polyester resin matrix was modified with a silane coupling agent in order to improve binder-aggregates interfaces. The added value of the recycling solution was assessed by means of both flexural and compressive strengths of GFRP admixed mortars with regard to those of the unmodified polymer mortars. Planning of experiments and data treatment were performed by means of full factorial design and through appropriate statistical tools based on analyses of variance (ANOVA). Results show that the partial replacement of sand aggregates by either type of GFRP recyclates improves the mechanical performance of resultant polymer mortars. In the case of trial formulations modified with the coarser waste mix, the best results are achieved with 8% waste weight content, while for fine waste based polymer mortars, 4% in weight of waste content leads to the higher increases on mechanical strengths. This study clearly identifies a promising waste management solution for GFRP waste materials by developing a cost-effective end-use application for the recyclates, thus contributing to a more sustainable fibre-reinforced polymer composites industry.

A divulgação do risco nas demonstrações financeiras : uma análise ao anexo das sociedades não financeiras portuguesas

Mestrado em Auditoria

Fatty liver automatic diagnosis from ultrasound images

In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis, also known as, fatty liver, from ultrasound images. The features, automatically extracted from the ultrasound images used by the classifier, are basically the ones used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The main novelty of the method is the utilization of the speckle noise that corrupts the ultrasound images to compute textural features of the liver parenchyma relevant for the diagnosis. The algorithm uses the Bayesian framework to compute a noiseless image, containing anatomic and echogenic information of the liver and a second image containing only the speckle noise used to compute the textural features. The classification results, with the Bayes classifier using manually classified data as ground truth show that the automatic classifier reaches an accuracy of 95% and a 100% of sensitivity.

Spatial distribution and socioeconomic context of tuberculosis in Rio de Janeiro, Brazil

OBJECTIVE To analyze the spatial distribution of risk for tuberculosis and its socioeconomic determinants in the city of Rio de Janeiro, Brazil.METHODS An ecological study on the association between the mean incidence rate of tuberculosis from 2004 to 2006 and socioeconomic indicators of the Censo Demográfico (Demographic Census) of 2000. The unit of analysis was the home district registered in the Sistema de Informação de Agravos de Notificação (Notifiable Diseases Information System) of Rio de Janeiro, Southeastern Brazil. The rates were standardized by sex and age group, and smoothed by the empirical Bayes method. Spatial autocorrelation was evaluated by Moran’s I. Multiple linear regression models were studied and the appropriateness of incorporating the spatial component in modeling was evaluated.RESULTS We observed a higher risk of the disease in some neighborhoods of the port and north regions, as well as a high incidence in the slums of Rocinha and Vidigal, in the south region, and Cidade de Deus, in the west. The final model identified a positive association for the variables: percentage of permanent private households in which the head of the house earns three to five minimum wages; percentage of individual residents in the neighborhood; and percentage of people living in homes with more than two people per bedroom.CONCLUSIONS The spatial analysis identified areas of risk of tuberculosis incidence in the neighborhoods of the city of Rio de Janeiro and also found spatial dependence for the incidence of tuberculosis and some socioeconomic variables. However, the inclusion of the space component in the final model was not required during the modeling process.

Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012)

ABSTRACT OBJECTIVE To describe the spatial distribution of avoidable hospitalizations due to tuberculosis in the municipality of Ribeirao Preto, SP, Brazil, and to identify spatial and space-time clusters for the risk of occurrence of these events. METHODS This is a descriptive, ecological study that considered the hospitalizations records of the Hospital Information System of residents of Ribeirao Preto, SP, Southeastern Brazil, from 2006 to 2012. Only the cases with recorded addresses were considered for the spatial analyses, and they were also geocoded. We resorted to Kernel density estimation to identify the densest areas, local empirical Bayes rate as the method for smoothing the incidence rates of hospital admissions, and scan statistic for identifying clusters of risk. Softwares ArcGis 10.2, TerraView 4.2.2, and SaTScanTM were used in the analysis. RESULTS We identified 169 hospitalizations due to tuberculosis. Most were of men (n = 134; 79.2%), averagely aged 48 years (SD = 16.2). The predominant clinical form was the pulmonary one, which was confirmed through a microscopic examination of expectorated sputum (n = 66; 39.0%). We geocoded 159 cases (94.0%). We observed a non-random spatial distribution of avoidable hospitalizations due to tuberculosis concentrated in the northern and western regions of the municipality. Through the scan statistic, three spatial clusters for risk of hospitalizations due to tuberculosis were identified, one of them in the northern region of the municipality (relative risk [RR] = 3.4; 95%CI 2.7–4,4); the second in the central region, where there is a prison unit (RR = 28.6; 95%CI 22.4–36.6); and the last one in the southern region, and area of protection for hospitalizations (RR = 0.2; 95%CI 0.2–0.3). We did not identify any space-time clusters. CONCLUSIONS The investigation showed priority areas for the control and surveillance of tuberculosis, as well as the profile of the affected population, which shows important aspects to be considered in terms of management and organization of health care services targeting effectiveness in primary health care.

An unsupervised approach to feature discretization and selection

Many learning problems require handling high dimensional datasets with a relatively small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. Examples of these types of data include the bag-of-words representation in text classification problems and gene expression data for tumor detection/classification. Usually, among the high number of features characterizing the instances, many may be irrelevant (or even detrimental) for the learning tasks. It is thus clear that there is a need for adequate techniques for feature representation, reduction, and selection, to improve both the classification accuracy and the memory requirements. In this paper, we propose combined unsupervised feature discretization and feature selection techniques, suitable for medium and high-dimensional datasets. The experimental results on several standard datasets, with both sparse and dense features, show the efficiency of the proposed techniques as well as improvements over previous related techniques.

A cultura, os valores contabilísticos e o julgamento profissional dos preparadores e dos revisores/auditores portugueses

Mestrado em Auditoria

Share GFS – Games, Films & Series: sistema de recomendação

Esta dissertação incide sobre o estudo e análise de uma solução para a criação de um sistema de recomendação para uma comunidade de consumidores de media e no consequente desenvolvimento da mesma cujo âmbito inicial engloba consumidores de jogos, filmes e/ou séries, com o intuito de lhes proporcionar a oportunidade de partilharem experiências, bem como manterem um registo das mesmas. Com a informação adquirida, o sistema reúne condições para proceder a sugestões direcionadas a cada membro da comunidade. O sistema atualiza a sua informação mediante as ações e os dados fornecidos pelos membros, bem como pelo seu feedback às sugestões. Esta aprendizagem ao longo do tempo permite que as sugestões do sistema evoluam juntamente com a mudança de preferência dos membros ou se autocorrijam. O sistema toma iniciativa de sugerir mediante determinadas ações, mas também pode ser invocada uma sugestão diretamente pelo utilizador, na medida em que este não precisa de esperar por sugestões, podendo pedir ao sistema que as forneça num determinado momento. Nos testes realizados foi possível apurar que o sistema de recomendação desenvolvido forneceu sugestões adequadas a cada utilizador específico, tomando em linha de conta as suas ações prévias. Para além deste facto, o sistema não forneceu qualquer sugestão quando o histórico destas tinha provado incomodar o utilizador.

Análise probabilistica do desempenho de pontes existentes

Dissertação para Obtenção do Grau de Mestre em Engenharia Civil – Estruturas e Geotecnia pela Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa

Using data mining techniques to support breast cancer diagnosis

More than ever, there is an increase of the number of decision support methods and computer aided diagnostic systems applied to various areas of medicine. In breast cancer research, many works have been done in order to reduce false-positives when used as a double reading method. In this study, we aimed to present a set of data mining techniques that were applied to approach a decision support system in the area of breast cancer diagnosis. This method is geared to assist clinical practice in identifying mammographic findings such as microcalcifications, masses and even normal tissues, in order to avoid misdiagnosis. In this work a reliable database was used, with 410 images from about 115 patients, containing previous reviews performed by radiologists as microcalcifications, masses and also normal tissue findings. Throughout this work, two feature extraction techniques were used: the gray level co-occurrence matrix and the gray level run length matrix. For classification purposes, we considered various scenarios according to different distinct patterns of injuries and several classifiers in order to distinguish the best performance in each case described. The many classifiers used were Naïve Bayes, Support Vector Machines, k-nearest Neighbors and Decision Trees (J48 and Random Forests). The results in distinguishing mammographic findings revealed great percentages of PPV and very good accuracy values. Furthermore, it also presented other related results of classification of breast density and BI-RADS® scale. The best predictive method found for all tested groups was the Random Forest classifier, and the best performance has been achieved through the distinction of microcalcifications. The conclusions based on the several tested scenarios represent a new perspective in breast cancer diagnosis using data mining techniques.

Validação da antropometria e ultrassonografia do braço, para medição dos respectivos compartimentos, em lactentes nascidos pré-termo : contributo para a avaliação corporal do recem-nascido e do lactente

RESUMO: Contexto: Indicadores fidedignos da composição corporal são importantes na orientação das estratégias nutricionais de recém-nascidos e pequenos lactentes submetidos a cuidados intensivos. O braço é uma região acessível para avaliar a composição corporal regional, pela medida dos seus compartimentos. A antropometria e a ultrassonografia (US) são métodos não invasivos, relativamente económicos, que podem ser usados à cabeceira do paciente na medição desses compartimentos, embora esses métodos não tenham ainda sido validados neste subgrupo etário. A ressonância magnética (RM) pode ser usada como método de referência na validação da medição dos compartimentos do braço. Objectivo: Validar em lactentes pré-termo, as medidas do braço por antropometria e por US. Métodos: Foi estudada uma coorte de recém-nascidos admitidos consecutivamente na unidade de cuidados intensivos neonatais, com  33 semanas de idade de gestação e peso adequado para a mesma, sem anomalias congénitas major e não submetidas a diuréticos ou oxigenoterapia no momento da avaliação. Nas vésperas da alta, foram efectuadas medições do braço, com ocultação, pelos métodos antropométrico, ultrassonográfico e RM. As medidas antropométricas directas foram: peso (P), comprimento (C), perímetro cefálico (PC), perímetro braquial (PB) e prega cutânea tricipital (PT). As área braquial total, área muscular (AM) e área adiposa foram calculadas pelos métodos de Jeliffee & Jeliffee e de Rolland-Cachera. Utilizando uma sonda PSH-7DLT de 7 Hz no ecógrafo Toshiba SSH 140A foram medidos os perímetros braquial e muscular e calculadas automaticamente as áreas braquial e muscular, sendo a área adiposa obtida por subtracção. Como método de referência foi utilizada a RM – Philips Gyroscan ACS-NT, Power-Track 1000 ®, 1.5 Tesla com uma antena de quadratura do joelho. Na análise estatística foram utilizados os métodos paramétricos e não paramétricos, conforme adequado. Resultados: Foram incluídas 30 crianças, nascidas com ( ±DP) 30.7 ±1.9 semanas de gestação, pesando 1380 ±325g, as quais foram avaliadas às 35.4 ±1.1 semanas de idade corrigida, quando pesavam 1786 ±93g. Nenhuma das medidas antropométricas, individualmente, constitui um indicador aceitável (r2 <0.5) das medições por RM. A melhor e mais simples equação alternativa encontrada é a que estima a AM (r2 = 0.56), derivada dos resultados da análise de regressão múltipla: AMRM = (P x 0.17) + (PB x 5.2) – (C x 6) – 150, sendo o P expresso em g, o C e o PB em cm. Nenhuma das medidas ultrassonográficas constitui um indicador aceitável (r2 <0.4) das medições por RM. Conclusões: A antropometria e as medidas ultrassonográficas do braço não são indicadores fidedignos da composição corporal regional em lactentes pré-termo, adequados para a idade de gestação.----------ABSTRACT: Background: Accurate predictors for body composition are valuable tools guiding nutritional strategies in infants needing intensive care. The upper-arm is a part of the body that is easily accessible and convenient for assessing the regional body composition, throughout the assessment of their compartments. Anthropometry and by ultrasonography (US) are noninvasive and relatively nonexpensive methods for bedside assessment of the upper-arm compartments. However, these methods have not yet been validated in infants. Magnetic resonance imaging (MRI) may be used as gold standard to validate the measurements of the upper-arm compartments. Objective: To validate the upper-arm measurements by anthropometry and by US in preterm infants. Methods: A cohort of neonates consecutively admitted at the neonatal intensive care unit, appropriate for gestational age, with  33 weeks, without major congenital abnormalities and not subjected to diuretics or oxygen therapy, was assessed. Before the discharge, the upper-arm was blindly measured by anthropometry, US and MRI. The direct anthropometric parameters measured were: weight (W), length (L), head circumference (HC), mid-arm circumference (MAC), and tricipital skinfold thickness. The arm area (AA), arm muscle area (AMA) and arm fat area were calculated applying the methods proposed by Jeliffee & Jeliffee and by Rolland-Cachera. Using the sonolayer Toshiba SSH 140A and the probe PSH-7DLT 7Hz, the arm and muscle perimeters were measured by US, the arm and muscle areas included were automatically calculated, and the fat area was calculated by subtraction. The MR images were acquired on a 1.5-T Philips Gyroscan ACS-NT, Power-Track 1000 scanner, and a knee coil was chosen for the upper-arm measurements. For statistical analysis parametric and nonparametric methods were used as appropriate. Results: Thirty infants born with ( ±SD) 30.7 ±1.9 weeks of gestational age and weighing 1380 ±325g were included in the study; they were assessed at 35.4 ±1.1 weeks of corrected age, weighing 1786 ±93g. None of the anthropometric measurements are individually acceptable (r2 <0.5) for prediction of the measurements obtained by MRI. The best and simple alternative equation found is the equation for prediction of the AMA (r2 = 0.56), derived from the results of multiple regression analysis: AMARM = (W x 0.17) + (MAC x 5.2) – (L x 6) – 150, being the W expressed in g, and L and MAC in cm. None of the ultrasonographic measurements are acceptable (r2 <0.5) predictors for the measurements obtained by MRI. Conclusions: The measurements of the upper-arm by anthropometry and by US are not accurate predictors for the regional body composition in preterm appropriate for gestational age infants.

Desenvolvimento de apoio à decisão operacional – previsão de curto prazo de geração distribuída de tecnologia eólica ligada à RND

No contexto da penetração de energias renováveis no sistema elétrico, Portugal ocupa uma posição de destaque a nível mundial, muito devido à produção de eólica. Com um sistema elétrico com forte presença de fontes de energia renováveis, novos desafios surgem, nomeadamente no caso da energia eólica pela sua imprevisibilidade e volatilidade. O recurso eólico embora seja ilimitado não é armazenável, surgindo assim a necessidade da procura de modelos de previsão de produção de energia elétrica dos parques eólicos de modo a permitir uma boa gestão do sistema. Nesta dissertação apresentam-se as contribuições resultantes de um trabalho de pesquisa e investigação sobre modelos de previsão da potência elétrica com base em valores de previsões meteorológicas, nomeadamente, valores previstos da intensidade e direção do vento. Consideraram-se dois tipos de modelos: paramétricos e não paramétricos. Os primeiros são funções polinomiais de vários graus e a função sigmoide, os segundos são redes neuronais artificiais. Para a estimação dos modelos e respetiva validação, são usados dados recolhidos ao longo de dois anos e três meses no parque eólico do Pico Alto de potência instalada de 6 MW. De forma a otimizar os resultados da previsão, consideram-se diferentes classes de perfis de produção, definidas com base em quatro e oito direções do vento, e ajustam-se os modelos propostos em cada uma das classes. São apresentados e discutidos resultados de uma análise comparativa do desempenho dos diferentes modelos propostos para a previsão da potência.

Hybrid systems biology: application to Escherichia coli

Dissertation presented to obtain a Master degree in Biotechnology

Dor crónica lombar : incapacidada auto-reportada em trabalhadores de saúde e sua relação com variáveis psicossociais e intensidade da dor

RESUMO: A dor crónica lombar, é uma condição de saúde cuja prevalência tem aumentado nas últimas décadas. É uma condição que pode ser bastante incapacitante para o indivíduo e por consequência, ter importante impacto social e económico na sociedade. É um fenómeno complexo, multifactorial e pouco estudado na população portuguesa. Objectivo: Estudar a associação entre a catastrofização da dor, crenças de medo evitamento da dor, intensidade da dor e a incapacidade funcional auto reportada em indivíduos com dor crónica lombar. Metodologia: Estudo observacional analítico de corte transversal, com uma amostra de 38 indivíduos com dor crónica lombar, seleccionados a partir de uma população de 186 trabalhadores de uma unidade local de saúde. A recolha de dados foi realizada através de 4 instrumentos de avaliação: Questionário de caracterização e levantamento de factores de risco e impacto associados à dor crónica lombar; Questionário de incapacidade de Roland e Morris; Escala de catastrofização da dor; e Questionário de crenças de medo evitamento da dor. A análise dos dados foi feita através de estatística descritiva pela distribuição de frequências e medidas de tendência central para análise da prevalência e caracterização da amostra e por estatística inferencial para estudar as relações entre variáveis através do teste de correlação não paramétrico de Spearman. Resultados: A variável catastrofização da dor obteve um valor de correlação com a incapacidade auto-reportada de rs=0,473, para p<0,01; a variável crença de medo evitamento da dor relacionada com o trabalho obteve um valor de correlação com a incapacidade auto-reportada de rs=0,462 para p<0,01, a percepção da intensidade actual de dor e a intensidade percepcionada no ano anterior, obtiveram valores de correlação com a incapacidade auto-reportada de rs=0,327 e rs= 0,359 respectivamente para valor de p<0,05. Conclusão: As variáveis psicossociais catastrofização da dor e crença de medo evitamento da dor relacionada com o trabalho, influenciam de forma moderada a incapacidade em indivíduos com dor crónica lombar. A associação entre a intensidade da dor e a incapacidade parece ter um papel menos importante demonstrando associações baixas.--------------------------ABSTRACT: Chronic low back pain is a health condition whose prevalence has increased in recent decades. It is a condition that can be quite disabling for the individual and therefore have important social and economic impact on society. It is a complex phenomenon, multifactorial and poorly studied in the Portuguese population. Objective: To study the association between pain catastrophizing, fear avoidance beliefs, pain, pain intensity and self-reported functional disability in individuals with chronic low back pain. Methods: Observational analytical cross sectional study of a sample of 38 individuals with chronic low back pain, selected from a population of 186 workers at a local health unit. Data collection was performed through four assessment instruments: questionnaire characterization, evaluation of risk factors and impact associated to chronic low back pain, questionnaire Roland and Morris disability, pain catastrophizing scale and fear avoidance beliefs questionnaire. Data analysis was performed using descriptive statistics for the distribution of frequencies and measures of central tendency to analyze the prevalence and characteristics of the sample and inferential statistics to study the relationships between variables by testing for Spearman nonparametric correlation. Results: The pain catastrophizing variable had a correlation value rs= 0,473, p<0,01 with the self-reported disability, the variable of fear avoidance belief of pain related to the work achived a correlation value with the self-reported disability, rs = 0.462 p <0.01, current pain intensity and in the previous year obtained values of correlation with self-reported disability rs = 0.327 and rs = 0.359 respectively for values of p <0.05 .Conclusion: The psychosocial variables of pain catastrophizing and fear avoidance belief of pain related to the work had a moderate association with disability in individuals with chronic low back pain. The association between pain intensity and disability seems to have a less important role demonstrating low associations.