Investment optimization in distribution network based on fuzzy outage parameters

This paper presents a methodology that aims to increase the probability of delivering power to any load point of the electrical distribution system by identifying new investments in distribution components. The methodology is based on statistical failure and repair data of the distribution power system components and it uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A mixed integer non-linear optimization technique is developed to identify adequate investments in distribution networks components that allow increasing the availability level for any customer in the distribution system at minimum cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a real distribution network.

Re-entrant phase behaviour of network fluids: A patchy particle model with temperature-dependent valence

We study a model consisting of particles with dissimilar bonding sites ("patches"), which exhibits self-assembly into chains connected by Y-junctions, and investigate its phase behaviour by both simulations and theory. We show that, as the energy cost epsilon(j) of forming Y-junctions increases, the extent of the liquid-vapour coexistence region at lower temperatures and densities is reduced. The phase diagram thus acquires a characteristic "pinched" shape in which the liquid branch density decreases as the temperature is lowered. To our knowledge, this is the first model in which the predicted topological phase transition between a fluid composed of short chains and a fluid rich in Y-junctions is actually observed. Above a certain threshold for epsilon(j), condensation ceases to exist because the entropy gain of forming Y-junctions can no longer offset their energy cost. We also show that the properties of these phase diagrams can be understood in terms of a temperature-dependent effective valence of the patchy particles. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3605703]

Cost dependent strategy for electricity markets bidding based on adaptive reinforcement learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM provides several dynamic strategies for agents’ behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents.

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

Doutoramento em Gestão

The influence of inter-domain mobility on message stream response time in wired/wireless PROFIBUS-based networks

In previous works we have proposed a hybrid wired/wireless PROFIBUS solution where the interconnection between the heterogeneous media was accomplished through bridge-like devices with wireless stations being able to move between different wireless cells. Additionally, we had also proposed a worst-case timing analysis assuming that stations were stationary. In this paper we advance these previous works by proposing a worst-case timing analysis for the system’s message streams considering the effect of inter-cell mobility.

Designing real-time systems based on mono-master Profibus-DP networks

Profibus networks are widely used as the communication infrastructure for supporting distributed computer-controlled applications. Most of the times, these applications impose strict real-time requirements. Profibus-DP has gradually become the preferred Profibus application profile. It is usually implemented as a mono-master Profibus network, and is optimised for speed and efficiency. The aim of this paper is to analyse the real-time behaviour of this class of Profibus networks. Importantly, we develop a new methodology for evaluating the worst-case message response time in systems where high-priority and cyclic low-priority Profibus traffic coexist. The proposed analysis constitutes a powerful tool to guarantee prior to runtime the real-time behaviour of a distributed computer-controlled system based on a Profibus network, where the realtime traffic is supported either by high-priority or by cyclic poll Profibus messages.

From task scheduling in single processor environments to message scheduling in a PROFIBUS fieldbus network

In this paper we survey the most relevant results for the prioritybased schedulability analysis of real-time tasks, both for the fixed and dynamic priority assignment schemes. We give emphasis to the worst-case response time analysis in non-preemptive contexts, which is fundamental for the communication schedulability analysis. We define an architecture to support priority-based scheduling of messages at the application process level of a specific fieldbus communication network, the PROFIBUS. The proposed architecture improves the worst-case messages’ response time, overcoming the limitation of the first-come-first-served (FCFS) PROFIBUS queue implementations.

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.

Inhibition of Aspergillus fumigatus and its biofilm by Pseudomonas aeruginosa is dependent on the source, phenotype and growth conditions of the bacterium

Aspergillus fumigatus (Af) and Pseudomonas aeruginosa (Pa) are leading fungal and bacterial pathogens, respectively, in many clinical situations. Relevant to this, their interface and co-existence has been studied. In some experiments in vitro, Pa products have been defined that are inhibitory to Af. In some clinical situations, both can be biofilm producers, and biofilm could alter their physiology and affect their interaction. That may be most relevant to airways in cystic fibrosis (CF), where both are often prominent residents. We have studied clinical Pa isolates from several sources for their effects on Af, including testing involving their biofilms. We show that the described inhibition of Af is related to the source and phenotype of the Pa isolate. Pa cells inhibited the growth and formation of Af biofilm from conidia, with CF isolates more inhibitory than non-CF isolates, and non-mucoid CF isolates most inhibitory. Inhibition did not require live Pa contact, as culture filtrates were also inhibitory, and again non-mucoid>mucoid CF>non-CF. Preformed Af biofilm was more resistant to Pa, and inhibition that occurred could be reproduced with filtrates. Inhibition of Af biofilm appears also dependent on bacterial growth conditions; filtrates from Pa grown as biofilm were more inhibitory than from Pa grown planktonically. The differences in Pa shown from these different sources are consistent with the extensive evolutionary Pa changes that have been described in association with chronic residence in CF airways, and may reflect adaptive changes to life in a polymicrobial environment.

Effect of skin colour and selected physical characteristics on Schistosoma mansoni dependent morbidity

The effect of the colour group on the morbidity due to Schistosoma mansoni was examined in two endemic areas situated in the State of Minas Gerais, Brazil. Of the 2773 eligible inhabitants, 1971 (71.1%) participated in the study: 545 (27.6%) were classified as white, 719 (36.5%) as intermediate and 707 (35.9%) as black. For each colour group, signs and symptoms of individuals who eliminated S.mansoni eggs (cases) were compared to those who did not present eggs in the faeces (controls). The odds ratios were adjusted by age, gender, previous treatment for schistosomiasis, endemic area and quality of the household. There was no evidence of a modifier effect of colour on diarrhea, bloody faeces or abdominal pain. A modifier effect of colour on hepatomegaly was evident among those heaviest infected (> 400 epg): the adjusted odds ratios for palpable liver at the middle clavicular and the middle sternal lines were smaller among blacks (5.4 and 6.5, respectively) and higher among whites (10.6 and 12.9) and intermediates (10.4 and 10.1, respectively). These results point out the existence of some degree of protection against hepatomegaly among blacks heaviest infected in the studied areas.

Metalearner based on Dynamic Neural Network for Strategic Bidding in electricity Markets

The restructuring of electricity markets, conducted to increase the competition in this sector, and decrease the electricity prices, brought with it an enormous increase in the complexity of the considered mechanisms. The electricity market became a complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. Software tools became, therefore, essential to provide simulation and decision support capabilities, in order to potentiate the involved players’ actions. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotiation entities. The proposed metalearner executes a dynamic artificial neural network to create its own output, taking advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that provides decision support to electricity markets’ players. The proposed metalearner considers different weights for each strategy, depending on its individual quality of performance. The results of the proposed method are studied and analyzed in scenarios based on real electricity markets’ data, using MASCEM - a multi-agent electricity market simulator that simulates market players’ operation in the market.

Demand Response Design and Use Based on Network Locational Marginal Prices

Power systems have been experiencing huge changes mainly due to the substantial increase of distributed generation (DG) and the operation in competitive environments. Virtual Power Players (VPP) can aggregate several players, namely a diversity of energy resources, including distributed generation (DG) based on several technologies, electric storage systems (ESS) and demand response (DR). Energy resources management gains an increasing relevance in this competitive context. This makes the DR use more interesting and flexible, giving place to a wide range of new opportunities. This paper proposes a methodology to support VPPs in the DR programs’ management, considering all the existing energy resources (generation and storage units) and the distribution network. The proposed method is based on locational marginal prices (LMP) values. The evaluation of the impact of using DR specific programs in the LMP values supports the manager decision concerning the DR use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 33-bus network with intensive use of DG.

Crystallographic studies on molybdopterin-dependent enzymes

Dissertação para obtenção do Grau de Doutor em Bioquímica, Especialidade Bioquímica Estrutural

Scientific authorships and collaboration network analysis on Chagas disease: papers indexed in PubMed (1940-2009)

Chagas disease is a chronic, tropical, parasitic disease, endemic throughout Latin America. The large-scale migration of populations has increased the geographic distribution of the disease and cases have been observed in many other countries around the world. To strengthen the critical mass of knowledge generated in different countries, it is essential to promote cooperative and translational research initiatives. We analyzed authorship of scientific documents on Chagas disease indexed in the Medline database from 1940 to 2009. Bibliometrics was used to analyze the evolution of collaboration patterns. A Social Network Analysis was carried out to identify the main research groups in the area by applying clustering methods. We then analyzed 13,989 papers produced by 21,350 authors. Collaboration among authors dramatically increased over the study period, reaching an average of 6.2 authors per paper in the last five-year period. Applying a threshold of collaboration of five or more papers signed in co-authorship, we identified 148 consolidated research groups made up of 1,750 authors. The Chagas disease network identified constitutes a "small world," characterized by a high degree of clustering and a notably high number of Brazilian researchers.

Long-Term and Concentration-Dependent Beneficial Effect of Efavirenz on HDL-Cholesterol in HIV-Infected Patients

AIMS: To investigate the long-term effects of efavirenz on cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein (LDL-C) and triglycerides (TG). METHODS: Thirty-four HIV-infected patients who commenced efavirenz therapy were monitored for 36 months. RESULTS: In patients with baseline HDL-C<40 mg.dL-1 an increase in HDL-C from 31+/-1 mg.dL-1 to 44+/-2 mg.dL-1 (95% confidence interval 5.9, 21.9, P<0.01) was observed and remained throughout the follow-up period. Median efavirenz plasma concentration was 1.98 mg.L-1 and a direct correlation between percentage of HDL-C variation or TC/HDL-C ratio and efavirenz plasma concentrations was found. CONCLUSIONS: There is evidence of a long-term and concentration-dependent beneficial effect of efavirenz on HDL-C in HIV-infected patients.