Relating the spatial component and users interests to improve applications based on questions, petitions and participatory processes

Nowadays, participatory processes attending the need for real democracy and transparency in governments and collectives are more needed than ever. Immediate participation through channels like social networks enable people to give their opinion and become pro-active citizens, seeking applications to interact with each other. The application described in this dissertation is a hybrid channel of communication of questions, petitions and participatory processes based on Public Participation Geographic Information System (PPGIS), Participation Geographic Information System (PGIS) and ‘soft’ (subjective data) Geographic Information System (SoftGIS) methodologies. To achieve a new approach to an application, its entire design is focused on the spatial component related with user interests. The spatial component is treated as main feature of the system to develop all others depending on it, enabling new features never seen before in social actions (questions, petitions and participatory processes). Results prove that it is possible to develop a working application mainly using open source software, with the possibility of spatial and subject filtering, visualizing and free download of actions within application. The resulting application empowers society by releasing soft data and defines a new breaking approach, unseen so far.

An agent-based simulator to estimate domestic energy use

Throughout recent years, there has been an increase in the population size, as well as a fast economic growth, which has led to an increase of the energy demand that comes mainly from fossil fuels. In order to reduce the ecological footprint, governments have implemented sustainable measures and it is expected that by 2035 the energy produced from renewable energy sources, such as wind and solar would be responsible for one-third of the energy produced globally. However, since the energy produced from renewable sources is governed by the availability of the respective primary energy source there is often a mismatch between production and demand, which could be solved by adding flexibility on the demand side through demand response (DR). DR programs influence the end-user electricity usage by changing its cost along the time. Under this scenario the user needs to estimate the energy demand and on-site production in advance to plan its energy demand according to the energy price. This work focuses on the development of an agent-based electrical simulator, capable of: (a) estimating the energy demand and on-site generation with a 1-min time resolution for a 24-h period, (b) calculating the energy price for a given scenario, (c) making suggestions on how to maximize the usage of renewable energy produced on-site and to lower the electricity costs by rescheduling the use of certain appliances. The results show that this simulator allows reducing the energy bill by 11% and almost doubling the use of renewable energy produced on-site.

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.

A new model for EEZ surveillance and management in Portugal

Management Information Systems 2000, p. 103-111

Location analysis of city sections: socio-demographic segmentation and restaurant potentiality estimation : a case study of Lisbon

One of the objectives of this study is to perform classification of socio-demographic components for the level of city section in City of Lisbon. In order to accomplish suitable platform for the restaurant potentiality map, the socio-demographic components were selected to produce a map of spatial clusters in accordance to restaurant suitability. Consequently, the second objective is to obtain potentiality map in terms of underestimation and overestimation in number of restaurants. To the best of our knowledge there has not been found identical methodology for the estimation of restaurant potentiality. The results were achieved with combination of SOM (Self-Organized Map) which provides a segmentation map and GAM (Generalized Additive Model) with spatial component for restaurant potentiality. Final results indicate that the highest influence in restaurant potentiality is given to tourist sites, spatial autocorrelation in terms of neighboring restaurants (spatial component), and tax value, where lower importance is given to household with 1 or 2 members and employed population, respectively. In addition, an important conclusion is that the most attractive market sites have shown no change or moderate underestimation in terms of restaurants potentiality.

Extensible metadata repository for information systems

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfillment of the requirements for the degree of Master in Computer Science

Pliocene-quaternary upwelling in the SoutheasternAtlantic may reflect changes in water mass production

Proceedings of tile 1" R.C.A.N.S. Congress, Lisboa, October 1992

Sustentabilidade e bem-estar humano : duas faces da mesma moeda? : estudo exploratório do bem estar subjectivo em comunidades intencionais que vivem segundo princípios de sustentabilidade

RESUMO - Nos últimos vinte anos tem-se assistido a uma crescente consciencialização de que os nossos estilos de vida são insustentáveis aos níveis económico, social e ambiental, o que tem repercussões na nossa saúde e bem-estar. Do crescimento populacional à pobreza e inequidade geradas pelo modelo de “crescimento económico” actual, à perda de biodiversidade e disrupção dos ecossistemas naturais, ao desmesurado crescimento urbano, à poluição e acumulação de desperdícios, às alterações climáticas, ao isolamento individual e à diminuição do capital social na sociedade do consumo: a necessidade de desenvolvimento sustentável e gerador de bem-estar nunca foi tão grande e evidente. Ao longo dos últimos anos têm surgido comunidades intencionais que se organizam segundo princípios de sustentabilidade, como um fenómeno de contra-cultura – as Ecoaldeias (Ecovillages). No entanto, os benefícios para a saúde e bem-estar deste tipo de comunidades não são ainda claros, sendo a experiência de investigação nesta área escassa. O estudo aqui proposto visa conhecer, a título exploratório, os níveis de bem-estar subjectivo em comunidades intencionais que vivem segundo princípios de sustentabilidade em Portugal, se estes níveis são melhores que na população em geral, e quais os factores percebidos que o influenciam. Para tal, terá componentes quantitativas e qualitativas e irá basear-se num questionário auto-administrado aos residentes das Ecoaldeias portuguesas, que inclui o Índice de Bem-estar Pessoal - uma escala de medição do Bem-estar subjectivo validada para a população portuguesa. As suas conclusões poderão contribuir para o desenvolvimento de abordagens mais elaboradas, capazes de edificar uma infra-estrutura teórica para o sistema de conceitos em foco, tão necessária quer a investigações com maior potencial explicativo, quer a decisões com melhor fundamento. ------------ ABSTRACT - Over the past twenty years there has been a growing awareness that the way we live is unsustainable at the economic, social and environmental level, which has impact in our health and wellbeing. From the population growth to poverty and inequity generated by the current model of economic growth, to biodiversity loss and disruption of natural ecosystems, to disproportionate urban growth, to pollution and waste accumulation, to climate change and the individual isolation social loss capital in the consumption society: the need for a development that is sustainable and generates wellbeing has never been greater and more evident. Over the last years intentional communities who live according to principles of sustainability have emerged, has a phenomenon of counter-culture - the ecovillages. The health and wellbeing benefits of this type of communities are not clear, as the investigation in this area is little. The aim of this exploratory study is to know the levels of subjective wellbeing of such communities, in Portugal, if these levels are different from the general population and what are the main perceived contributing factors. This study will have a qualitative and quantitative component and will be based in the application of a self-administered questionnaire that includes the Subjective Wellbeing Index, a measurement scale of subjective wellbeing, validated for the Portuguese population. Its findings may contribute to the development of more elaborate approaches that allow to build a theoretical framework for the system of concepts focused, needed both for further investigations with more explanatory potential, as for more grounded decision-making, to tackle the challenges of sustainable development.

Metedologia de avaliação da ingestão nutricional e comportamentos alimentares associados num programa de tratamento de obesidade

Resumo: últimas décadas, sendo já considerada uma doença crónica. Ao longo dos anos, ainvestigação desenvolvida nessa área permitiu definir com maior rigor a sua forma de avaliação. Relativamente à avaliação do processo de ingestão alimentar no tratamento da obesidade, e com o objectivo de se obter uma perspectiva completa e contínua, não será suficiente avaliar apenas variáveis nutricionais, mas devem também constar variáveis relacionadas com o comportamento alimentar. O presente trabalho irá enquadrar as áreas fundamentais a avaliar nas componentes da ingestão nutricional e dos comportamentos alimentares associados, e, mais especificamente, apreciar a metodologia de avaliação usada nesse domínio, num programa de tratamento comportamental da obesidade, randomizado e controlado ‐ o programa PESO (Promoção do Exercício e Saúde na Obesidade). Embora este Programa não tenha sido especificamente concebido para avaliar as componentes acima referidas como variáveis‐alvo principais, os dados são relevantes para avaliar o impacte do Programa. Os principais resultados sugerem melhorias evidentes nas variáveis críticas na gestão do peso, tanto na componente da ingestão nutricional como no comportamento alimentar.-----------ABSTRACT: The prevalence of obesity has increased significantly in the last decades and is now considered a chronic disease. Over the years, the research undertaken in this area allowed to define more rigorous ways to assess it. To evaluate dietary intake process in the treatment of obesity, and to achieve a more complete and continuous measurement, it’s not enough to assess the nutritional variables, it’s also necessary to include eating behavior related variables. This work will focus in key areas to evaluate nutritional intake and eating behavior variables, and also in the methodology assessment used in this domain, in a behavioral treatment program of obesity, a randomized controlled trial, named PESO (Promotion of Exercise and Health in Obesity). Although this program was not specifically designed to assess the above components as variables main target, the data are relevant to assess the Program impact. The main results suggest an obvious improvement in weight management critical variables, both in nutritional intake component and eating behavior.

Neural mechanisms of stimulus generalization in auditory fear conditioning

Dissertation presented to obtain the Ph.D degree in Neuroscience Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa

Creating greater value for biomass residues

Dissertation presented to obtain the Ph.D degree in Engineering Sciences and Technology