An integrated recycling approach for GFRP pultrusion wastes: recycling and reuse assessment into new composite materials using Fuzzy Boolean Nets

In this study, efforts were made in order to put forward an integrated recycling approach for the thermoset based glass fibre reinforced polymer (GPRP) rejects derived from the pultrusion manufacturing industry. Both the recycling process and the development of a new cost-effective end-use application for the recyclates were considered. For this purpose, i) among the several available recycling techniques for thermoset based composite materials, the most suitable one for the envisaged application was selected (mechanical recycling); and ii) an experimental work was carried out in order to assess the added-value of the obtained recyclates as aggregates and reinforcement replacements into concrete-polymer composite materials. Potential recycling solution was assessed by mechanical behaviour of resultant GFRP waste modified concrete-polymer composites with regard to unmodified materials. In the mix design process of the new GFRP waste based composite material, the recyclate content and size grade, and the effect of the incorporation of an adhesion promoter were considered as material factors and systematically tested between reasonable ranges. The optimization process of the modified formulations was supported by the Fuzzy Boolean Nets methodology, which allowed finding the best balance between material parameters that maximizes both flexural and compressive strengths of final composite. Comparing to related end-use applications of GFRP wastes in cementitious based concrete materials, the proposed solution overcome some of the problems found, namely the possible incompatibilities arisen from alkalis-silica reaction and the decrease in the mechanical properties due to high water-cement ratio required to achieve the desirable workability. Obtained results were very promising towards a global cost-effective waste management solution for GFRP industrial wastes and end-of-life products that will lead to a more sustainable composite materials industry.

Equipamento de produção de água gelada para melhorar a eficácia do combate a incêndios florestais

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

O ditado como estratégia de aprendizagem

O ensino da escrita é uma questão que tem estado presente nas preocupações dos decisores políticos e dos investigadores em Portugal. O ensino e aprendizagem da ortografia, não tem sido objecto privilegiado na investigação, observando-se na maioria das salas de aula práticas que apelam exclusivamente à memorização. Neste artigo, propõe-se uma reflexão sobre ensino da ortografia, apresentando alguns dados de um projeto em curso em sala de aula com o propósito de melhorar as práticas de ensino da ortografia.

Multi-agent Simulation of Bilateral Contracting in Competitive Electricity Markets

Traditional vertically integrated power utilities around the world have evolved from monopoly structures to open markets that promote competition among suppliers and provide consumers with a choice of services. Market forces drive the price of electricity and reduce the net cost through increased competition. Electricity can be traded in both organized markets or using forward bilateral contracts. This article focuses on bilateral contracts and describes some important features of an agent-based system for bilateral trading in competitive markets. Special attention is devoted to the negotiation process, demand response in bilateral contracting, and risk management. The article also presents a case study on forward bilateral contracting: a retailer agent and a customer agent negotiate a 24h-rate tariff. © 2014 IEEE.

RiSeG: a ring based secure group communication protocol for resource-constrained wireless sensor networks

Securing group communication in wireless sensor networks has recently been extensively investigated. Many works have addressed this issue, and they have considered the grouping concept differently. In this paper, we consider a group as being a set of nodes sensing the same data type, and we alternatively propose an efficient secure group communication scheme guaranteeing secure group management and secure group key distribution. The proposed scheme (RiSeG) is based on a logical ring architecture, which permits to alleviate the group controller’s task in updating the group key. The proposed scheme also provides backward and forward secrecy, addresses the node compromise attack, and gives a solution to detect and eliminate the compromised nodes. The security analysis and performance evaluation show that the proposed scheme is secure, highly efficient, and lightweight. A comparison with the logical key hierarchy is preformed to prove the rekeying process efficiency of RiSeG. Finally, we present the implementation details of RiSeG on top of TelosB sensor nodes to demonstrate its feasibility.

Server-based scheduling of parallel real-time tasks

Multicore platforms have transformed parallelism into a main concern. Parallel programming models are being put forward to provide a better approach for application programmers to expose the opportunities for parallelism by pointing out potentially parallel regions within tasks, leaving the actual and dynamic scheduling of these regions onto processors to be performed at runtime, exploiting the maximum amount of parallelism. It is in this context that this paper proposes a scheduling approach that combines the constant-bandwidth server abstraction with a priority-aware work-stealing load balancing scheme which, while ensuring isolation among tasks, enables parallel tasks to be executed on more than one processor at a given time instant.

Cluster de volatilidade no mercado de taxas de câmbio USD/GBP

Mestrado em Controlo de Gestão e dos Negócios

O problema da extracção do alumínio a partir dos sienitos nefelínicos

Some countries producers of the aluminium, attempt to use other ores which, in the future, will gradually substitute the bauxite as a raw material. Portugal possesses an nephelinic syenite massif which may be utilized for this purpose because the nepheline offers some advantages above other poor ores which are being essayed now. By laboratorial processes, the author puts forward those advantages and calls the attention for the necessity of to accomplish essays about the nepheline (by the acid's method) and realize petrographic's detailed reconnaissances of the Monchique syenitic massif.

Estudo sobre a memória longa na volatilidade dos preços do ouro : uma abordagem com base nos modelos de tipo ARCH

Mestrado em Contabilidade e Análise Financeira

Contratos de futuros sobre taxas de juro : estudo de caso sobre a Euribor a 3 meses

Mestrado em Contabilidade e Análise Financeira

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.

An efficient scalable RNS architecture for large dynamic ranges

This paper proposes an efficient scalable Residue Number System (RNS) architecture supporting moduli sets with an arbitrary number of channels, allowing to achieve larger dynamic range and a higher level of parallelism. The proposed architecture allows the forward and reverse RNS conversion, by reusing the arithmetic channel units. The arithmetic operations supported at the channel level include addition, subtraction, and multiplication with accumulation capability. For the reverse conversion two algorithms are considered, one based on the Chinese Remainder Theorem and the other one on Mixed-Radix-Conversion, leading to implementations optimized for delay and required circuit area. With the proposed architecture a complete and compact RNS platform is achieved. Experimental results suggest gains of 17 % in the delay in the arithmetic operations, with an area reduction of 23 % regarding the RNS state of the art. When compared with a binary system the proposed architecture allows to perform the same computation 20 times faster alongside with only 10 % of the circuit area resources.

O plano de deslocações urbanas e a resposta estratégica que falta aos PROTs e PDMs: A descentralização do planeamento do território e dos transportes

The sustainable urban mobility plan is the framework of planning and organisation of mobility system. It is a strategic and operational plan with consequences in the planning and organisation of territorial and transport systems. When it’s defining the principles and the objectives of sustainable development and when it’s working in the scenarios of modal shift more favourable to the alternative modes than the car, the planning and the organisation of territory will be integrated on the political of reduction of road circulation volumes, in the reduction of GEE, waste of space and time, in the improvement of quality of urban environment. The Urbanism Agencies and the Urban Transport Authorities will get their selves in the urban mobility plan, in territory scenarios development, mobility and transports, with the objective to understand the sustainable politics in the accessibilities which are available by the transportation bill. In Portugal, although the authorities are not yet working, the law (1/2009) recently approved in last December and published at the beginning of the year, they have the sustainable urban mobility plans forward in this strategy.

Federalism and health policy: the intergovernmental committees in Brazil

OBJECTIVE To analyze the dynamics of operation of the Bipartite Committees in health care in the Brazilian states.METHODS The research included visits to 24 states, direct observation, document analysis, and performance of semi-structured interviews with state and local leaders. The characterization of each committee was performed between 2007 and 2010, and four dimensions were considered: (i) level of institutionality, classified as advanced, intermediate, or incipient; (ii) agenda of intergovernmental negotiations, classified as diversified/restricted, adapted/not adapted to the reality of each state, and shared/unshared between the state and municipalities; (iii) political processes, considering the character and scope of intergovernmental relations; and (iv) capacity of operation, assessed as high, moderate, or low.RESULTS Ten committees had advanced level of institutionality. The agenda of the negotiations was diversified in all states, and most of them were adapted to the state reality. However, one-third of the committees showed power inequalities between the government levels. Cooperative and interactive intergovernmental relations predominated in 54.0% of the states. The level of institutionality, scope of negotiations, and political processes influenced Bipartite Committees’ ability to formulate policies and coordinate health care at the federal level. Bipartite Committees with a high capacity of operation predominated in the South and Southeast regions, while those with a low capacity of operations predominated in the North and Northeast.CONCLUSIONS The regional differences in operation among Bipartite Interagency Committees suggest the influence of historical-structural variables (socioeconomic development, geographic barriers, characteristics of the health care system) in their capacity of intergovernmental health care management. However, structural problems can be overcome in some states through institutional and political changes. The creation of federal investments, varied by regions and states, is critical in overcoming the structural inequalities that affect political institutions. The operation of Bipartite Committees is a step forward; however, strengthening their ability to coordinate health care is crucial in the regional organization of the health care system in the Brazilian states.

On a test-bed application for the ART-WiSe framework

This report describes the development of a Test-bed Application for the ART-WiSe Framework with the aim of providing a means of access, validate and demonstrate that architecture. The chosen application is a kind of pursuit-evasion game where a remote controlled robot, navigating through an area covered by wireless sensor network (WSN), is detected and continuously tracked by the WSN. Then a centralized control station takes the appropriate actions for a pursuit robot to chase and “capture” the intruder one. This kind of application imposes stringent timing requirements to the underlying communication infrastructure. It also involves interesting research problems in WSNs like tracking, localization, cooperation between nodes, energy concerns and mobility. Additionally, it can be easily ported into a real-world application. Surveillance or search and rescue operations are two examples where this kind of functionality can be applied. This is still a first approach on the test-bed application and this development effort will be continuously pushed forward until all the envisaged objectives for the Art-WiSe architecture become accomplished.