The intersection of people, technology and local space. PPGIS and Web in practice for participatory planning

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

Characterization and surface reconstruction of objects in tomographic images of composite materials

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Pedestrian Priority Zones in the Context of Urban Mobility and Valorization of Public Space

The second half of the XX century was marked by a great increase in the number of people living in cities. Urban agglomerations became poles of attraction for migration flows and these phenomena, coupled with growing car-ownership rates, resulted in the fact that modern transport systems are characterized by large number of users and traffic modes. The necessity to organize these complex systems and to provide space for different traffic modes changed the way cities look. Urban areas had to cope with traffic flows, and as a result nowadays typical street pattern consists of a road for motorized vehicles, a cycle lane (in some cases), pavement for pedestrians, parking and a range of crucial signage to facilitate navigation and make mobility more secure. However, this type of street organization may not be desirable in certain areas, more specifically, in the city centers. Downtown areas have always been places where economic, leisure, social and other types of facilities are concentrated, not surprisingly, they often attract large number of people and this frequently results in traffic jams, air and noise pollution, thus creating unpleasant environment. Besides, excessive traffic signage in central locations can harm the image and perception of a place, this relates in particular to historical centers with architectural heritage.

Genome-scale metabolic network reconstruction of Polaromonas sp. strain JS666: analysis of cDCE degradation rates and design of experiments for bioremediation improvement

Release of chloroethene compounds into the environment often results in groundwater contamination, which puts people at risk of exposure by drinking contaminated water. cDCE (cis-1,2-dichloroethene) accumulation on subsurface environments is a common environmental problem due to stagnation and partial degradation of other precursor chloroethene species. Polaromonas sp. strain JS666 apparently requires no exotic growth factors to be used as a bioaugmentation agent for aerobic cDCE degradation. Although being the only suitable microorganism found capable of such, further studies are needed for improving the intrinsic bioremediation rates and fully comprehend the metabolic processes involved. In order to do so, a metabolic model, iJS666, was reconstructed from genome annotation and available bibliographic data. FVA (Flux Variability Analysis) and FBA (Flux Balance Analysis) techniques were used to satisfactory validate the predictive capabilities of the iJS666 model. The iJS666 model was able to predict biomass growth for different previously tested conditions, allowed to design key experiments which should be done for further model improvement and, also, produced viable predictions for the use of biostimulant metabolites in the cDCE biodegradation.

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Children, space, and the urban street: an ethnomathematics posture

Dissertation presented for the PhD Degree in Education Science – Curricular Theory and Science Teaching, by Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Innovation through virtual communities of practice: motivations and constraints in the knowledge-creation process

This paper appears in International Journal of Projectics. Vol 4(1), pp. 39-49

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

Extracting temporal and spatial distributions information about marine mucilage phenomenon based on Modis satellite images; a case study of the Tyrrhenian and the Adriatic Sea, 2010-2012

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

Sudden sensorineural hearing loss : evaluation of co-morbidities and potential clinical associations

RESUMO: A surdez súbita (SS) caracteriza-se por uma perda abrupta de audição, mais frequentemente unilateral e associada a sensação de preenchimento aural, acufenos e vertigem. Afecta 5-20/100.000pessoas/ano (sobretudo adultos em fase activa na década de 40), com grande impacto na qualidade de vida. Possíveis causas incluem doenças infecciosas, circulatórias, traumáticas, imunológicas, neoplásicas, neurológicas, tóxicas e cocleares. No entanto, a causa da SS permanece desconhecida na maioria dos casos (80%), o que origina tratamentos controversos e frequentemente ineficientes. Os tratamentos disponíveis variam desde corticosteróides a antivirais, vasodilatadores, anti-agregantes, anticoagulantes, vitaminas e oxigénio hiperbárico (OHB). Atendendo a falta de informação relativa à etiologia e fisiopatologia da SS, pretendemos avaliar a evolução clínica dos doentes com SS tratados com OHB no Centro de Medicina Subaquática e Hiperbárica (CMSH) de Lisboa entre 2000 e 2005, durante um período mínimo de 5 anos, na tentativa de identificar eventuais factores de risco ou noxas clínicas com a SS. O estudo retrospectivo proposto baseia-se na revisão de processos clínicos do CMSH e na aplicação telefónica de questionários médicos de “follow-up” confidenciais – tanto a doentes (grupo de estudo), como aos respectivos esposos/companheiros/membros próximos da família (grupo de controlo) –, com particular ênfase nos antecedentes médicos e história clínica actual. Um estudo preliminar de 20 pessoas (10 doentes e 10 controlos) foi efectuado para antecipar dificuldades e estimar as necessidades logísticas. As dificuldades identificadas foram: 1) selecção dos doentes com números de telefone válidos e processos clínicos completos (com audiograma inicial e final); 2) contacto telefónico com os participantes de ambos os grupos (de estudo e controlo); 3) recursos humanos requeridos. Dado que a SS não é uma doença em si, mas um sintoma de uma doença subjacente, acreditamos que este estudo epidemiológico seja importante e útil, capaz de gerar novas luzes sobre a fisiopatologia e mecanismos desta entidade clínica.-------------ABSTRACT:Sudden sensorineural hearing loss (SSHL) is characterized by abrupt, mostly unilateral loss of hearing, frequently associated to aural fullness, tinnitus and vertigo. It affects 5-20/100.000 people/year (particularly working adults in the 40ths), with huge impact on quality of life. Possible causes include infectious, circulatory, traumatic, immunologic, metabolic, neoplastic, neurologic, toxic and unidentified cochlear diseases. Nevertheless, SSHL’s etiology remains unknown in most cases (80%), giving rise to controversial (and frequently ineffective) treatments. Available therapies range from corticosteroids to antivirals, vasodilators, antiaggregants, anticoagulants, vitamins and hyperbaric oxygen (HBO). Given the lack of data concerning SSHL’s etiology and physiopathology, we intend to evaluate clinical evolution of such patients treated with HBO in the Underwater and Hyperbaric Medical Center (UHMC) at Lisbon from 2000 to 2005 during a minimum period of 5 years, in an attempt to identify eventual risk factors or clinical associations to SSHL. The intended retrospective study is based on the review of patients’ medical charts from UHMC and confidential follow-up questionnaires applied telephonically both to patients (study group) and patients’ spouse/partner/close family member (control group), focusing past and present medical history. A preliminary study of 20 subjects (10 of each group) was performed to anticipate difficulties and to estimate the required logistics. The identified difficulties were: 1) selection of subjects with valid phone numbers and complete medical charts (with initial and final audiograms); 2) telephonic contact with subjects from the study and control group; 3) human logistics required. As it is believed that SSHL is not a disease by itself but rather a symptom of an underlying disease, we believe that this epidemiologic study is important and will hopefully generate sound scientific knowledge concerning physiopathology and mechanism of disease of SSHL.

Studying urban space and literary representations using GIS: Lisbon, Portugal, 1852-2009

This article proposes a methodology to address the urban evolutionary process, demonstrating how it is reflected in literature. It focuses on “literary space,” presented as a territory defined by the period setting or as evoked by the characters, which can be georeferenced and drawn on a map. It identifies the different locations of literary space in relation to urban development and the economic, political, and social context of the city. We suggest a new approach for mapping a relatively comprehensive body of literature by combining literary criticism, urban history, and geographic information systems (GIS). The home-range concept, used in animal ecology, has been adapted to reveal the size and location of literary space. This interdisciplinary methodology is applied in a case study to nineteenth- and twentieth-century novels involving the city of Lisbon. The developing concepts of cumulative literary space and common literary space introduce size calculations in addition to location and structure, previously developed by other researchers. Sequential and overlapping analyses of literary space throughout time have the advantage of presenting comparable and repeatable results for other researchers using a different body of literary works or studying another city. Results show how city changes shaped perceptions of the urban space as it was lived and experienced. A small core area, correspondent to a part of the city center, persists as literary space in all the novels analyzed. Furthermore, the literary space does not match the urban evolution. There is a time lag for embedding new urbanized areas in the imagined literary scenario.