Planning, operations and data handling of planetary science missions

Dissertação para obtenção do Grau de Mestre em Engenharia Física

Assessment of non-steroidal anti-inflammatory and analgesic pharmaceuticals in seawaters of North of Portugal: Occurrence and environmental risk

The occurrence of seven pharmaceuticals and two metabolites belonging to non-steroidal anti-inflammatory drugs and analgesics therapeutic classes was studied in seawaters. A total of 101 samples covering fourteen beaches and five cities were evaluated in order to assess the spatial distribution of pharmaceuticals among north Portuguese coast. Seawaters were selected in order to embrace different bathing water quality (excellent, good and sufficient). Acetaminophen, ketoprofen and the metabolite hydroxyibuprofen were detected in all the seawater samples at maximum concentrations of 584, 89.7 and 287 ng L− 1, respectively. Carboxyibuprofen had the highest seawater concentration (1227 ng L− 1). The temporal distribution of the selected pharmaceuticals during the bathing season showed that, in general, higher concentrations were detected in August and September. The environmental risk posed by the pharmaceuticals detected in seawaters towards different trophic levels (fish, daphnids and algae) was also assessed. Only diclofenac showed hazard quotients above one for fish, representing a potential risk for aquatic organisms. These results were observed in seawaters classified as excellent bathing water. Additional data is needed in order to support the identification and prioritization of risks posed by pharmaceuticals in marine environment.

Comparing the performance of geostatistical models with additional information from covariates for sewage plume characterization

In this work, kriging with covariates is used to model and map the spatial distribution of salinity measurements gathered by an autonomous underwater vehicle in a sea outfall monitoring campaign aiming to distinguish the effluent plume from the receiving waters and characterize its spatial variability in the vicinity of the discharge. Four different geostatistical linear models for salinity were assumed, where the distance to diffuser, the west-east positioning, and the south-north positioning were used as covariates. Sample variograms were fitted by the Mat`ern models using weighted least squares and maximum likelihood estimation methods as a way to detect eventual discrepancies. Typically, the maximum likelihood method estimated very low ranges which have limited the kriging process. So, at least for these data sets, weighted least squares showed to be the most appropriate estimation method for variogram fitting. The kriged maps show clearly the spatial variation of salinity, and it is possible to identify the effluent plume in the area studied. The results obtained show some guidelines for sewage monitoring if a geostatistical analysis of the data is in mind. It is important to treat properly the existence of anomalous values and to adopt a sampling strategy that includes transects parallel and perpendicular to the effluent dispersion.

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

Ankylosing spondylitis: genomic and functional characterization of candidate genes and their repercussion in clinical practice

RESUMO: Introdução: A espondilite anquilosante (EA) é uma doença inflamatória crónica caracterizada pela inflamação das articulações sacroilíacas e da coluna. A anquilose progressiva motiva uma deterioração gradual da função física e da qualidade de vida. O diagnóstico e o tratamento precoces podem contribuir para um melhor prognóstico. Neste contexto, a identificação de biomarcadores, assume-se como sendo muito útil para a prática clínica e representa hoje um grande desafio para a comunidade científica. Objetivos: Este estudo teve como objetivos: 1 - caracterizar a EA em Portugal; 2 - investigar possíveis associações entre genes, MHC e não-MHC, com a suscetibilidade e as características fenotípicas da EA; 3 - identificar genes candidatos associados a EA através da tecnologia de microarray. Material e Métodos: Foram recrutados doentes com EA, de acordo com os critérios modificados de Nova Iorque, nas consultas de Reumatologia dos diferentes hospitais participantes. Colecionaram-se dados demográficos, clínicos e radiológicos e colhidas amostras de sangue periférico. Selecionaram-se de forma aleatória, doentes HLA-B27 positivos, os quais foram tipados em termos de HLA classe I e II por PCR-rSSOP. Os haplótipos HLA estendidos foram estimados pelo algoritmo Expectation Maximization com recurso ao software Arlequin v3.11. As variantes alélicas dos genes IL23R, ERAP1 e ANKH foram estudadas através de ensaios de discriminação alélica TaqMan. A análise de associação foi realizada utilizando testes da Cochrane-Armitage e de regressão linear, tal como implementado pelo PLINK, para variáveis qualitativas e quantitativas, respetivamente. O estudo de expressão génica foi realizado por Illumina HT-12 Whole-Genome Expression BeadChips. Os genes candidatos foram validados usando qPCR-based TaqMan Low Density Arrays (TLDAs). Resultados: Foram incluídos 369 doentes (62,3% do sexo masculino, com idade média de 45,4 ± 13,2 anos, duração média da doença de 11,4 ± 10,5 anos). No momento da avaliação, 49,9% tinham doença axial, 2,4% periférica, 40,9% mista e 7,1% entesopática. A uveíte anterior aguda (33,6%) foi a manifestação extra-articular mais comum. Foram positivos para o HLA-B27, 80,3% dos doentes. Os haplótipo A*02/B*27/Cw*02/DRB1*01/DQB1*05 parece conferir suscetibilidade para a EA, e o A*02/B*27/Cw*01/DRB1*08/DQB1*04 parece conferir proteção em termos de atividade, repercussão funcional e radiológica da doença. Três variantes (2 para IL23R e 1 para ERAP1) mostraram significativa associação com a doença, confirmando a associação destes genes com a EA na população Portuguesa. O mesmo não se verificou com as variantes estudadas do ANKH. Não se verificou associação entre as variantes génicas não-MHC e as manifestações clínicas da EA. Foi identificado um perfil de expressão génica para a EA, tendo sido validados catorze genes - alguns têm um papel bem documentado em termos de inflamação, outros no metabolismo da cartilagem e do osso. Conclusões: Foi estabelecido um perfil demográfico e clínico dos doentes com EA em Portugal. A identificação de variantes génicas e de um perfil de expressão contribuem para uma melhor compreensão da sua fisiopatologia e podem ser úteis para estabelecer modelos com relevância em termos de diagnóstico, prognóstico e orientação terapêutica dos doentes. -----------ABSTRACT: Background: Ankylosing Spondylitis (AS) is a chronic inflammatory disorder characterized by inflammation in the spine and sacroiliac joints leading to progressive joint ankylosis and in progressive deterioration of physical function and quality of life. An early diagnosis and early therapy may contribute to a better prognosis. The identification of biomarkers would be helpful and represents a great challenge for the scientific community. Objectives: The present study had the following aims: 1- to characterize the pattern of AS in Portuguese patients; 2- to investigate MHC and non-MHC gene associations with susceptibility and phenotypic features of AS and; 3- to identify candidate genes associated with AS by means of whole-genome microarray. Material and Methods: AS was defined in accordance to the modified New York criteria and AS cases were recruited from hospital outcares patient clinics. Demographic and clinical data were recorded and blood samples collected. A random group of HLA-B27 positive patients and controls were selected and typed for HLA class I and II by PCR-rSSOP. The extended HLA haplotypes were estimated by Expectation Maximization Algorithm using Arlequin v3.11 software. Genotyping of IL23R, ERAP1 and ANKH allelic variants was carried out with TaqMan allelic discrimination assays. Association analysis was performed using the Cochrane-Armitage and linear regression tests as implemented in PLINK, for dichotomous and quantitative variables, respectively. Gene expression profile was carried out using Illumina HT-12 Whole-Genome Expression BeadChips and candidate genes were validated using qPCR-based TaqMan Low Density Arrays (TLDAs). Results: A total of 369 patients (62.3% male; mean age 45.4±13.2 years; mean disease duration 11.4±10.5 years), were included. Regarding clinical disease pattern, at the time of assessment, 49.9% had axial disease, 2.4% peripheral disease, 40.9% mixed disease and 7.1% isolated enthesopathic disease. Acute anterior uveitis (33.6%) was the most common extra-articular manifestation. 80.3% of AS patients were HLA-B27 positive. The haplotype A*02/B*27/Cw*02/DRB1*01/DQB1*05 seems to confer susceptibility to AS, whereas A*02/B*27/Cw*01/DRB1*08/DQB1*04 seems to provide protection in terms of disease activity, functional and radiological repercussion. Three markers (two for IL23R and one for ERAP1) showed significant single-locus disease associations. Association of these genes with AS in the Portuguese population was confirmed, whereas ANKH markers studied did not show an association with AS. No association was seen between non-MHC genes and clinical manifestations of AS. A gene expression signature for AS was established; among the fourteen validated genes, a number of them have a well-documented inflammatory role or in modulation of cartilage and bone metabolism. Conclusions: A demographic and clinical profile of patients with AS in Portugal was established. Identification of genetic variants of target genes as well as gene expression signatures could provide a better understanding of AS pathophysiology and could be useful to establish models with relevance in terms of susceptibility, prognosis, and potential therapeutic guidance.

Heterogeneous sensor database framework for the sensor observation service: integrating remote and in-situ sensor observations at the database backend

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Stochastic modeling of the thermal and catalytic degradation of polyethylene using simultaneous DSC/TG analysis

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Assessing the impacts of land use and land cover change on hydrology of watershed: a case study on Gigel-Abbay Watershed, Lake Tana Basin, Ethiopia

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

The integration of online advertising: The effects of source expertise and certainty level of the message on consumer involvement and persuasion in the context of user-generated advertising

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

The new mobility paradigm: transformation of value chain and business models

We would like to thank Philipp Schwarz and Julia Gückel for their dedicated support in preparing this paper and our colleagues and students of the School of Engineering and the Business School for our fruitful discussions.

Structural time series models and the Kalman filter: A concise review

The continued increase in availability of economic data in recent years and, more importantly, the possibility to construct larger frequency time series, have fostered the use (and development) of statistical and econometric techniques to treat them more accurately. This paper presents an exposition of structural time series models by which a time series can be decomposed as the sum of a trend, seasonal and irregular components. In addition to a detailled analysis of univariate speci fications we also address the SUTSE multivariate case and the issue of cointegration. Finally, the recursive estimation and smoothing by means of the Kalman filter algorithm is described taking into account its different stages, from initialisation to parameter s estimation.

Experimental Gravimetric Adsorption Equilibrium of n-Alkanes and Alkenes, Carbon Dioxide and Nitrogen in MIL-53(Al) and Zeolite 5A

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Analysis of the interaction of polycyclic aromatic compounds in a model organism: integration of genotoxic and histopathological effects

Due to their toxicity, especially their carcinogenic potential, polycyclic aromatic hydrocarbons (PAHs) became priority pollutants in biomonitoring programmes and environmental policy, such as the European Water Framework Directive. The model substances tested in this study, namely benzo[b]fluoranthene (B[b]F), considered potentially carcinogenic to humans and an effector carcinogenic PAH to wildlife, and phenanthrene (Phe), deemed a non-carcinogenic PAH, are common PAHs in coastal waters, owning distinct properties reflected in different, albeit overlapping, mechanisms of toxicity. Still, as for similar PAHs, their interaction effects remain largely unknown. In order to study the genotoxic effects of caused by the interaction of carcinogenic and non-carcinogenic PAHs, and their relation to histopathological alterations, juvenile sea basses, Dicentrarchus labrax, a highly ecologically- and economically-relevant marine fish, were injected with different doses (5 and 10 μg.g-1 fish ww) of the two PAHs, isolated or in mixture, and incubated for 48 h. Individuals injected with B[b]F and the PAH mixture exhibited higher clastogenic/aneugenic effects and DNA strand breakage in blood cells, determined through the erythrocytic nuclear abnormalities (ENA) and Comet assays, respectively. Also, hepatic histopathological alterations were found in all animals, especially those injected with B[b]F and the PAH mixture, relating especially to inflammation. Still, Phe also exhibited genotoxic effects in sea bass, especially in higher doses, revealing a very significant acute effect that was accordant with the Microtox test performed undergone in parallel. Overall, sea bass was sensitive to B[b]F (a higher molecular weight PAH), likely due to efficient bioactivation of the pollutant (yielding genotoxic metabolites and reactive oxygen species), when compared to Phe, the latter revealing a more significant acute effect. The results indicate no significant additive effect between the substances, under the current experimental conditions. The present study highlights the importance of understanding PAH interactions in aquatic organisms, since they are usually present in the aquatic environment in complex mixtures.

Complex networks and data mining: toward a new perspective for the understanding of complex systems

Complex systems, i.e. systems composed of a large set of elements interacting in a non-linear way, are constantly found all around us. In the last decades, different approaches have been proposed toward their understanding, one of the most interesting being the Complex Network perspective. This legacy of the 18th century mathematical concepts proposed by Leonhard Euler is still current, and more and more relevant in real-world problems. In recent years, it has been demonstrated that network-based representations can yield relevant knowledge about complex systems. In spite of that, several problems have been detected, mainly related to the degree of subjectivity involved in the creation and evaluation of such network structures. In this Thesis, we propose addressing these problems by means of different data mining techniques, thus obtaining a novel hybrid approximation intermingling complex networks and data mining. Results indicate that such techniques can be effectively used to i) enable the creation of novel network representations, ii) reduce the dimensionality of analyzed systems by pre-selecting the most important elements, iii) describe complex networks, and iv) assist in the analysis of different network topologies. The soundness of such approach is validated through different validation cases drawn from actual biomedical problems, e.g. the diagnosis of cancer from tissue analysis, or the study of the dynamics of the brain under different neurological disorders.