Reentrant Phase Diagram of Network Fluids

We introduce a microscopic model for particles with dissimilar patches which displays an unconventional "pinched'' phase diagram, similar to the one predicted by Tlusty and Safran in the context of dipolar fluids [Science 290, 1328 (2000)]. The model-based on two types of patch interactions, which account, respectively, for chaining and branching of the self-assembled networks-is studied both numerically via Monte Carlo simulations and theoretically via first-order perturbation theory. The dense phase is rich in junctions, while the less-dense phase is rich in chain ends. The model provides a reference system for a deep understanding of the competition between condensation and self-assembly into equilibrium-polymer chains.

Re-evaluation of a reported increased micronucleus frequency in lymphocytes of workers occupationally exposed to formaldehyde

A replicate evaluation of increased micronucleus (MN) frequencies in peripheral lymphocytes of workers occupationally exposed to formaldehyde (FA) was undertaken to verify the observed effect and to determine scoring variability. May–Grünwald–Giemsa-stained slides were obtained from a previously performed cytokinesis-block micronucleus test (CBMNT) with 56 workers in anatomy and pathology laboratories and 85 controls. The first evaluation by one scorer (scorer 1) had led to a highly significant difference between workers and controls (3.96 vs 0.81 MN per 1000 cells). The slides were coded before re-evaluation and the code was broken after the complete re-evaluation of the study. A total of 1000 binucleated cells (BNC) were analysed per subject and the frequency of MN (in ‰) was determined. Slides were distributed equally and randomly between two scorers, so that the scorers had no knowledge of the exposure status. Scorer 2 (32 exposed, 36 controls) measured increased MN frequencies in exposed workers (9.88 vs 6.81). Statistical analysis with the two-sample Wilcoxon test indicated that this difference was not significant (p = 0.17). Scorer 3 (20 exposed, 46 controls) obtained a similar result, but slightly higher values for the comparison of exposed and controls (19.0 vs 12.89; p = 0.089). Combining the results of the two scorers (13.38 vs 10.22), a significant difference between exposed and controls (p = 0.028) was obtained when the stratified Wilcoxon test with the scorers as strata was applied. Interestingly, the re-evaluation of the slides led to clearly higher MN frequencies for exposed and controls compared with the first evaluation. Bland–Altman plots indicated that the agreement between the measurements of the different scorers was very poor, as shown by mean differences of 5.9 between scorer 1 and scorer 2 and 13.0 between scorer 1 and scorer 3. Calculation of the intra-class correlation coefficient (ICC) revealed that all scorer comparisons in this study were far from acceptable for the reliability of this assay. Possible implications for the use of the CBMNT in human biomonitoring studies are discussed.

Towards an Academic Social Network for Bologna Process

The Bologna Process aimed to build a European Higher Education Area promoting student's mobility. The adoption of Bologna Declaration directives requires a self management distributed approach to deal with student's mobility, allowing frequent updates in institutions rules or legislation. This paper suggests a computational system architecture, which follows a social network design. A set of structured annotations is proposed in order to organize the user's information. For instance, when the user is a student its annotations are organized into an academic record. The academic record data is used to discover interests, namely mobility interests, among students that belongs the academic network. These ideas have been applied into a demonstrator that includes a mobility simulator to compare and show the student's academic evolution.

Contributos do associativismo na (re)construção da identidade profissional dos professores de matemática do 2º ciclo

Dissertação apresentada na Escola Superior de Educação de Lisboa para obtenção do grau de Mestre em Educação Matemática na Educação Pré-escolar e no 1º e 2º ciclos do Ensino Básico

Academic social network in EHES

This paper presents the foundations of an Academic Social Network (ASN) focusing the Bologna Declaration and the Bologna Process (BP) mobility issues using ontological support. An ASN will permit students to share commons academic interests, preferences and mobility paths in the European Higher Education Space (EHES). The description of the conceptual support is ontology based allowing knowledge sharing and reuse. An approach is presented by merging Academic Ontology to Support the Bologna Mobility Process with Friend of a Friend ontology. The resulting ontology supports the student mobility profile in the ASN. The strategies to make available, in the network, knowledge about mobility issues, are presented including knowledge discovery and simulation approaches to cover student's mobility scenarios for BP.

Structural characterization of Co‐Re superlattices

Co‐Re superlattices were prepared with nominal periodicities of 65–67 Å and varying bilayer composition. The structural characterization was made by x‐ray diffraction and Rutherford backscattering spectrometry (RBS). First, second, and third order satellites are observed in the x‐ray diffractogram at 2θ values and with intensities close to those predicted by simulation. This confirms the coherence of the superlattice. RBS measurements combined with RUMP simulations give information on interface sharpness and the absolute thicknesses of the Co and Re layers. Discrepancies between the experimental and simulated diffractograms are found for Co thicknesses below 18 Å.

Desenvolvimento e estudo de modelos de FACTS para o trânsito de energia: aplicação ao estudo das condições técnicas de ligação de linhas MAT

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Atribuição e encaminhamento de comprimento de onda em redes IP sobre WDM energeticamente eficiente

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Electrónica e Telecomunicações

Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

Influence of network effects on the diffusion of information systems: the case of open source

Doutoramento em Gestão

Planeamento de rede LTE de baixo custo com uso de repetidor

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Neighbour list optimization for real LTE radio network

With the increasing complexity of current networks, it became evident the need for Self-Organizing Networks (SON), which aims to automate most of the associated radio planning and optimization tasks. Within SON, this paper aims to optimize the Neighbour Cell List (NCL) for Long Term Evolution (LTE) evolved NodeBs (eNBs). An algorithm composed by three decisions were were developed: distance-based, Radio Frequency (RF) measurement-based and Handover (HO) stats-based. The distance-based decision, proposes a new NCL taking account the eNB location and interference tiers, based in the quadrants method. The last two algorithms consider signal strength measurements and HO statistics, respectively; they also define a ranking to each eNB and neighbour relation addition/removal based on user defined constraints. The algorithms were developed and implemented over an already existent radio network optimization professional tool. Several case studies were produced using real data from a Portuguese LTE mobile operator. © 2014 IEEE.

On the choice of posittioning and cluster size for fixed relay stations in a LTE network

The long term evolution (LTE) is one of the latest standards in the mobile communications market. To achieve its performance, LTE networks use several techniques, such as multi-carrier technique, multiple-input-multiple-output and cooperative communications. Inside cooperative communications, this paper focuses on the fixed relaying technique, presenting a way for determining the best position to deploy the relay station (RS), from a set of empirical good solutions, and also to quantify the associated performance gain using different cluster size configurations. The best RS position was obtained through realistic simulations, which set it as the middle of the cell's circumference arc. Additionally, it also confirmed that network's performance is improved when the number of RSs is increased. It was possible to conclude that, for each deployed RS, the percentage of area served by an RS increases about 10 %. Furthermore, the mean data rate in the cell has been increased by approximately 60 % through the use of RSs. Finally, a given scenario with a larger number of RSs, can experience the same performance as an equivalent scenario without RSs, but with higher reuse distance. This conduces to a compromise solution between RS installation and cluster size, in order to maximize capacity, as well as performance.

The evolution of user mobility on the Eduroam network

The emergence of smartphones with Wireless LAN (WiFi) network interfaces brought new challenges to application developers. The expected increase of users connectivity will impact their expectations for example on the performance of background applications. Unfortunately, the number and breadth of the studies on the new patterns of user mobility and connectivity that result from the emergence of smartphones is still insufficient to support this claim. This paper contributes with preliminary results on a large scale study of the usage pattern of about 49000 devices and 31000 users who accessed at least one access point of the eduroam WiFi network on the campuses of the Lisbon Polytechnic Institute. Results confirm that the increasing number of smartphones resulted in significant changes to the pattern of use, with impact on the amount of traffic and users connection time.

The daily and hourly energy consumption and load forecasting using artifitial neural network method: a case study using a set of 93 households in Portugal

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.