Preliminary Overview over Requirements Regarding Tools and Methods Derived from LUDA Cases

LUDA is a research project of Key Action 4 "City of Tomorrow & Cultural Heritage" of the programme "Energy, Environment and Sustainable Development" within the Fifth Framework Programme of the European Commission

Programa de Técnica de Dança Clássica : do pré-primário ao 2ª ciclo de escolaridade do Ensino Não Vocacional

Relatório Final de Projecto Pedagógico apresentado à Escola Superior de Dança, com vista à obtenção do grau de Mestre em Metodologias do Ensino da Dança

Scheduling of head-dependent cascaded reservoirs considering discharge ramping constraints and start/stop of units

This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning head-dependent reservoirs under competitive environment. We propose a novel method, based on mixed-integer nonlinear programming (MINLP), for optimising power generation efficiency. This method considers hydroelectric power generation as a nonlinear function of water discharge and of the head. The main contribution of this paper is that discharge ramping constraints and start/stop of units are also considered, in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve two case studies based on Portuguese cascaded hydro systems, providing a higher profit at an acceptable computation time in comparison with classical optimisation methods based on mixed-integer linear programming (MILP).

Seasonal variation of total particulate matter and children respiratory diseases at Lisbon primary schools using passive methods

In this work, 14 primary schools of Lisbon city, Portugal, followed a questionnaire of the ISAAC - International Study of Asthma and Allergies in Childhood Program, in 2009/2010. The questionnaire contained questions to identify children with respiratory diseases (wheeze, asthma and rhinitis). Total particulate matter (TPM) was passively collected inside two classrooms of each of 14 primary schools. Two types of filter matrices were used to collect TPM: Millipore (IsoporeTM) polycarbonate and quartz. Three campaigns were selected for the measurement of TPM: Spring, Autumn and Winter. The highest difference between the two types of filters is that the mass of collected particles was higher in quartz filters than in polycarbonate filters, even if their correlation is excellent. The highest TPM depositions occurred between October 2009 and March 2010, when related with rhinitis proportion. Rhinitis was found to be related to TPM when the data were grouped seasonally and averaged for all the schools. For the data of 2006/2007, the seasonal variation was found to be related to outdoor particle deposition (below 10 μm).

Dynamic equilibrium through reinforcement learning

Reinforcement Learning is an area of Machine Learning that deals with how an agent should take actions in an environment such as to maximize the notion of accumulated reward. This type of learning is inspired by the way humans learn and has led to the creation of various algorithms for reinforcement learning. These algorithms focus on the way in which an agent’s behaviour can be improved, assuming independence as to their surroundings. The current work studies the application of reinforcement learning methods to solve the inverted pendulum problem. The importance of the variability of the environment (factors that are external to the agent) on the execution of reinforcement learning agents is studied by using a model that seeks to obtain equilibrium (stability) through dynamism – a Cart-Pole system or inverted pendulum. We sought to improve the behaviour of the autonomous agents by changing the information passed to them, while maintaining the agent’s internal parameters constant (learning rate, discount factors, decay rate, etc.), instead of the classical approach of tuning the agent’s internal parameters. The influence of changes on the state set and the action set on an agent’s capability to solve the Cart-pole problem was studied. We have studied typical behaviour of reinforcement learning agents applied to the classic BOXES model and a new form of characterizing the environment was proposed using the notion of convergence towards a reference value. We demonstrate the gain in performance of this new method applied to a Q-Learning agent.

Base molecular da hemocromatose hereditária não-clássica em Portugal

A Hemocromatose Hereditária (HH) é uma doença autossómica recessiva caracterizada pela absorção excessiva de ferro a nível intestinal e sua acumulação em órgãos vitais, podendo originar cardiomiopatia, cirrose e carcinoma hepatocelular. O correspondente diagnóstico molecular é obtido pela associação com genótipos específicos no gene HFE (homozigotia para p.Cys282Tyr ou heterozigotia composta p.Cys282Tyr/p.His63Asp). Contudo, nos países do sul da Europa, cerca de um terço dos doentes com diagnóstico clínico de HH não apresenta os referidos genótipos. Para identificar a base molecular da HH não-clássica em Portugal usaram-se metodologias de pesquisa geral de variantes genéticas (SSCP e dHPLC), Next-Generation Sequencing (NGS) e sequenciação de Sanger, cobrindo seis genes relacionados com o metabolismo do ferro em 303 doentes. Identificaram-se 69 variantes diferentes e de vários tipos, por ex. missense, nonsense, de splicing, que perturbam a transcrição do gene ou a regulação da tradução do mRNA. Seguidamente, realizaram-se estudos in silico e in vitro para esclarecer o significado etiológico de algumas das novas variantes. Concluiu-se que a base molecular desta patologia é bastante heterogénea e que a NGS é uma ferramenta adequada para efetuar a análise simultânea dos vários genes num grande número de amostras. Contudo, o estabelecimento da relevância clínica de algumas variantes requer a realização de estudos funcionais.

Epidemiological methods for research with drug misusers: review of methods for studying prevalence and morbidity

Epidemiological studies of drug misusers have until recently relied on two main forms of sampling: probability and convenience. The former has been used when the aim was simply to estimate the prevalence of the condition and the latter when in depth studies of the characteristics, profiles and behaviour of drug users were required, but each method has its limitations. Probability samples become impracticable when the prevalence of the condition is very low, less than 0.5% for example, or when the condition being studied is a clandestine activity such as illicit drug use. When stratified random samples are used, it may be difficult to obtain a truly representative sample, depending on the quality of the information used to develop the stratification strategy. The main limitation of studies using convenience samples is that the results cannot be generalised to the whole population of drug users due to selection bias and a lack of information concerning the sampling frame. New methods have been developed which aim to overcome some of these difficulties, for example, social network analysis, snowball sampling, capture-recapture techniques, privileged access interviewer method and contact tracing. All these methods have been applied to the study of drug misuse. The various methods are described and examples of their use given, drawn from both the Brazilian and international drug misuse literature.

Some bounds of loss in classical semideterministic immunization

Since Samuelson, Redington and Fisher and Weil, duration and immunization are very important topics in bond portfolio analysis from both a theoretical and a practical point of view. Many results have been established, especially in semi-deterministic framework. As regards, however, the loss may be sustained, we do not think that the subject has been investigated enough, except for the results found in the wake of the theorem of Fong and Vasicek. In this paper we present some results relating to the limitation of the loss in the case of local immunization for multiple liabilities.

Structural and Microanalytical Studies of CrO2 Thin Films on c-Sapphire by High Resolution Electron Microscopy Methods

Chromium dioxide (CrO2) has been extensively used in the magnetic recording industry. However, it is its ferromagnetic half-metallic nature that has more recently attracted much attention, primarily for the development of spintronic devices. CrO2 is the only stoichiometric binary oxide theoretically predicted to be fully spin polarized at the Fermi level. It presents a Curie temperature of ∼ 396 K, i.e. well above room temperature, and a magnetic moment of 2 mB per formula unit. However an antiferromagnetic native insulating layer of Cr2O3 is always present on the CrO2 surface which enhances the CrO2 magnetoresistance and might be used as a barrier in magnetic tunnel junctions.

Positive Solutions of the Dirichlet Problem for the One-dimensional Minkowski-Curvature Equation

We discuss existence and multiplicity of positive solutions of the Dirichlet problem for the quasilinear ordinary differential equation-(u' / root 1 - u'(2))' = f(t, u). Depending on the behaviour of f = f(t, s) near s = 0, we prove the existence of either one, or two, or three, or infinitely many positive solutions. In general, the positivity of f is not required. All results are obtained by reduction to an equivalent non-singular problem to which variational or topological methods apply in a classical fashion.

PHYLOViZ: phylogenetic inference and data visualization for sequence based typing methods

Background: With the decrease of DNA sequencing costs, sequence-based typing methods are rapidly becoming the gold standard for epidemiological surveillance. These methods provide reproducible and comparable results needed for a global scale bacterial population analysis, while retaining their usefulness for local epidemiological surveys. Online databases that collect the generated allelic profiles and associated epidemiological data are available but this wealth of data remains underused and are frequently poorly annotated since no user-friendly tool exists to analyze and explore it. Results: PHYLOViZ is platform independent Java software that allows the integrated analysis of sequence-based typing methods, including SNP data generated from whole genome sequence approaches, and associated epidemiological data. goeBURST and its Minimum Spanning Tree expansion are used for visualizing the possible evolutionary relationships between isolates. The results can be displayed as an annotated graph overlaying the query results of any other epidemiological data available. Conclusions: PHYLOViZ is a user-friendly software that allows the combined analysis of multiple data sources for microbial epidemiological and population studies. It is freely available at http://www.phyloviz.net.

Methods for automatic and assisted image annotation

Personal memories composed of digital pictures are very popular at the moment. To retrieve these media items annotation is required. During the last years, several approaches have been proposed in order to overcome the image annotation problem. This paper presents our proposals to address this problem. Automatic and semi-automatic learning methods for semantic concepts are presented. The automatic method is based on semantic concepts estimated using visual content, context metadata and audio information. The semi-automatic method is based on results provided by a computer game. The paper describes our proposals and presents their evaluations.

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.