Prevalence of intestinal parasitic infection in five farms in Holambra, São Paulo, Brazil

A parasitological survey was carried out on 222 inhabitants of five farms in Holambra, located 30 km north of Campinas, São Paulo, Brazil, on October 1992. Approximately 70% of the inhabitants were found to be infected with at least one species of intestinal parasite. The positive rates of 6 helminths and 7 protozoan species detected are as follows: 5.4% Ascaris lumbricoides; 8.6% Trichuris trichiura; 19.8% Necator americanus; 10.4% Strongyloides stercoralis; 14% Enterobius vermicularis; 0.9% Hymenolepis nana; 3.2% Entamoeba histolytica; 2.7% E. hartmanni; 9.9% E. coli; 14.0% Endolimax nana; 2.3% Iodamoeba butschlii; 10.4% Giardia lamblia; 37.8% Blastocystis hominis. The positive rates of helminth infection were generaly higher in the younger-group under 16 years-old than those in the elder group aged 16 or more, whereas the infection rates of protozoan species were higher in the elder group. The infection rate of Strongyloides was found to be 10.4% by a newly developed sensitive method (an agarplate culture methods).

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.

Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the whole system. The work presented in this paper comprises a methodology able to define the cost allocation in distribution networks considering large integration of DG and DR resources. The proposed methodology is divided into three phases and it is based on an AC Optimal Power Flow (OPF) including the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity.

Pyogenic abscesses and parasitic diseases

Parasitic diseases which during their course in the host switch the immune system from a T helper 1 to a T helper 2 response may be detrimental to the host, contributing to granuloma formation, eosinophilia, hyper-IgE, and increased susceptibility to bacterial and fungal infections. Patients and animals with acute schistosomiasis and hyper-IgE in their serum develop pyogenic liver abscess in the presence of bacteremia caused by Staphylococcus aureus. The Salmonella-S. mansoni association has also been well documented. The association of tropical pyomyositis (pyogenic muscle abscess) and pyogenic liver abscess with Toxocara infection has recently been described in the same context. In tropical countries that may be an interesting explanation for the great morbidity of bacterial diseases. If the association of parasitic infections and pyogenic abscesses and/or fungal diseases are confirmed, there will be a strong case in favor of universal treatment for parasitic diseases to prevent or decrease the morbidity of superinfection with bacteria and fungi.

A historical perspective and prospects of biomedical research on parasitic diseases

We all hope that biotechnology will answer some social and economical unavoidable requirements of the modern life. It is necessary to improve agriculture production, food abundance and health quality in a sustainable development. It is indeed a hard task to keep the progress on taking into account the rational use of genetic resources and the conservation of biodiversity. In this context, a historical perspective and prospects of the biomedical research on parasitic diseases is described in a view of three generations of investigators. This work begins with a picture of the scientific progress on biomedical research and human health over the last centuries. This black-and-white picture is painted by dissecting current advancements of molecular biology and modern genetics, which are outlined at the meaning of prospecting achievements in health science for this new millenium.

Investigation of trypanothione synthetase of Leishmania infantum as a potential target for new anti-parasitic drugs

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Evaluation of the formalin-Tween concentration technique for parasitic detection

The formalin-Tween sedimentation method was compared with the formalin-ether sedimentation for parasitic detection. Of a total 297 fecal specimens examined, 72.1% were positive. The formalin-tween technique was effective for ascertaining helminths, particularly Ascaris lumbricoides, Trichuris trichiura and hookworm eggs; however it has less capability for protozoa detection. This method is simple, inexpensive, less time consuming and highly sensitive when detecting the parasitic infection, particularly when focusing on helminth eggs.

Distributed Sensing of Fluid Dynamic Phenomena with the XDense Sensor Grid Network

IEEE International Conference on Cyber Physical Systems, Networks and Applications (CPSNA'15), Hong Kong, China.

Partitioning the Network-on-Chip to Enable Virtualization on Many-Core Processors

6th International Real-Time Scheduling Open Problems Seminar (RTSOPS 2015), Lund, Sweden.

XDense: A Dense Grid Sensor Network for Distributed Feature Extraction

XXXIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC 2015). 15 to 19, May, 2015, III Workshop de Comunicação em Sistemas Embarcados Críticos. Vitória, Brasil.

Allocation of Parallel Real-Time Tasks in Distributed Multi-core Architectures supported by an FTT-SE Network

Distributed real-time systems such as automotive applications are becoming larger and more complex, thus, requiring the use of more powerful hardware and software architectures. Furthermore, those distributed applications commonly have stringent real-time constraints. This implies that such applications would gain in flexibility if they were parallelized and distributed over the system. In this paper, we consider the problem of allocating fixed-priority fork-join Parallel/Distributed real-time tasks onto distributed multi-core nodes connected through a Flexible Time Triggered Switched Ethernet network. We analyze the system requirements and present a set of formulations based on a constraint programming approach. Constraint programming allows us to express the relations between variables in the form of constraints. Our approach is guaranteed to find a feasible solution, if one exists, in contrast to other approaches based on heuristics. Furthermore, approaches based on constraint programming have shown to obtain solutions for these type of formulations in reasonable time.

Swordfish: an Autonomous Surface Vehicle for Network Centric Operations

The design and development of the swordfish autonomous surface vehicle (ASV) system is discussed. Swordfish is an ocean capable 4.5 m long catamaran designed for network centric operations (with ocean and air going vehicles and human operators). In the basic configuration, Swordfish is both a survey vehicle and a communications node with gateways for broadband, Wi-Fi and GSM transports and underwater acoustic modems. In another configuration, Swordfish mounts a docking station for the autonomous underwater vehicle Isurus from Porto University. Swordfish has an advanced control architecture for multi-vehicle operations with mixed initiative interactions (human operators are allowed to interact with the control loops).

Towards the Development of XDense, A Sensor Network for Dense Sensing

Poster in 12th European Conference on Wireless Sensor Networks (EWSN 2015). 9 to 11, Feb, 2015, pp 24-25. Porto, Portugal.

XDense: A Dense Grid Sensor Network for Distributed Feature Extraction

XXXIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC 2015), III Workshop de Comunicação em Sistemas Embarcados Críticos. Vitória, Brasil.