1000 resultados para Distribution platforms
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Abdominal angiostrongyliasis is a parasitic disease caused by Angiostrongylus costaricensis, a metastrongylid nematode with wide geographic distribution, occurring from the United States to Argentina. In Brazil, the disease has been reported from the States of Rio Grande do Sul, Santa Catarina, Paraná, São Paulo, Federal District of Brasilia and Minas Gerais. We report here a case of abdominal angiostrongyliasis in a 9-year-old girl, from Itatiba, State of Espirito Santo, Brazil, submitted to exploratory laparotomy for acute abdomen. Extensive inflammatory lesions of terminal ileum and cecum, with perforations of the first, were present, and ileocecal resection was performed. The pathological picture was characterized by transmural inflammatory granulomatous reaction, extensive eosinophilic infiltration, eosinophilic vasculitis and the presence of worms within a mesenteric artery branch, with histological features of metastrongylid nematodes. This case report contributes to a better knowledge of the geographic distribution of this parasite in Brazil, suggesting that abdominal angiostrongyliasis may represent a disease of medical importance, more than a rarity of academic interest.
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Scorpion stings were surveyed in the Montes Municipality of the State of Sucre, Venezuela, aiming to extend the information on these poisonous accidents by characterizing their geographic distribution. From 1980 to 1990, 184 cases of scorpion stings were recorded with an incidence rate of 38.6 cases per 10,000 inhabitants. The locality of San Fernando presented the highest incidence (68.3(0)/000) of poisonous accidents. The highest percentages of severe cases were recorded in the towns of Arenas (27%), San Lorenzo (21%), and Cocollar (19%), which are located at the foot of the Turimiquire Mountains. This region is a dispersion area of scorpions of the Tityus genus. Our results show that this region of the State of Sucre is endemic for scorpion stings which are an important public health problem.
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This paper proposes a PSO based approach to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The statistical failure and repair data of distribution components is the main basis of the proposed methodology that uses a fuzzyprobabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A Modified Discrete PSO optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.
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This paper proposes a methodology to increase the probability of delivering power to any load point through the identification of new investments. The methodology uses a fuzzy set approach to model the uncertainty of outage parameters, load and generation. A DC fuzzy multicriteria optimization model considering the Pareto front and based on mixed integer non-linear optimization programming is developed in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power to all customers in the distribution network at the minimum possible cost for the system operator, while minimizing the non supplied energy cost. To illustrate the application of the proposed methodology, the paper includes a case study which considers an 33 bus distribution network.
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A methodology to increase the probability of delivering power to any load point through the identification of new investments in distribution network components is proposed in this paper. The method minimizes the investment cost as well as the cost of energy not supplied in the network. A DC optimization model based on mixed integer non-linear programming is developed considering the Pareto front technique in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power for any customer in the distribution system at the minimum possible cost for the system operator, while minimizing the energy not supplied cost. Thus, a multi-objective problem is formulated. To illustrate the application of the proposed methodology, the paper includes a case study which considers a 180 bus distribution network
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The high penetration of distributed energy resources (DER) in distribution networks and the competitiveenvironment of electricity markets impose the use of new approaches in several domains. The networkcost allocation, traditionally used in transmission networks, should be adapted and used in the distribu-tion networks considering the specifications of the connected resources. The main goal is to develop afairer methodology trying to distribute the distribution network use costs to all players which are usingthe network in each period. In this paper, a model considering different type of costs (fixed, losses, andcongestion costs) is proposed comprising the use of a large set of DER, namely distributed generation(DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehi-cles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). Theproposed model includes three distinct phases of operation. The first phase of the model consists in aneconomic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen’s andBialek’s tracing algorithms are used and compared to evaluate the impact of each resource in the net-work. Finally, the MW-mile method is used in the third phase of the proposed model. A distributionnetwork of 33 buses with large penetration of DER is used to illustrate the application of the proposedmodel.
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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.
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Thirty six cases of acute disseminated paracoccidioidomycosis in 3 to 12 year-old children, natives of the state of Rio de Janeiro, were seen in the period 1981-1996. All patients were residents in the rural region of 15 counties, scattered on the Southwestern part of this state. The rural region of two neighboring counties, where 16 cases (44.4%) occurred, was visited. It exhibited the environmental conditions that are considered favorable to the survival of P. brasiliensis. The most important of these conditions, abundant watercourses and autochthonous forest, are distributed on well defined and limited areas, in which the dwellings are also localized. Probably, a careful epidemiological study of forthcoming cases of the disease in children may facilitate the search for the micro-niche of the fungus.
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Heterogeneous multicore platforms are becoming an interesting alternative for embedded computing systems with limited power supply as they can execute specific tasks in an efficient manner. Nonetheless, one of the main challenges of such platforms consists of optimising the energy consumption in the presence of temporal constraints. This paper addresses the problem of task-to-core allocation onto heterogeneous multicore platforms such that the overall energy consumption of the system is minimised. To this end, we propose a two-phase approach that considers both dynamic and leakage energy consumption: (i) the first phase allocates tasks to the cores such that the dynamic energy consumption is reduced; (ii) the second phase refines the allocation performed in the first phase in order to achieve better sleep states by trading off the dynamic energy consumption with the reduction in leakage energy consumption. This hybrid approach considers core frequency set-points, tasks energy consumption and sleep states of the cores to reduce the energy consumption of the system. Major value has been placed on a realistic power model which increases the practical relevance of the proposed approach. Finally, extensive simulations have been carried out to demonstrate the effectiveness of the proposed algorithm. In the best-case, savings up to 18% of energy are reached over the first fit algorithm, which has shown, in previous works, to perform better than other bin-packing heuristics for the target heterogeneous multicore platform.
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The last decade has witnessed a major shift towards the deployment of embedded applications on multi-core platforms. However, real-time applications have not been able to fully benefit from this transition, as the computational gains offered by multi-cores are often offset by performance degradation due to shared resources, such as main memory. To efficiently use multi-core platforms for real-time systems, it is hence essential to tightly bound the interference when accessing shared resources. Although there has been much recent work in this area, a remaining key problem is to address the diversity of memory arbiters in the analysis to make it applicable to a wide range of systems. This work handles diverse arbiters by proposing a general framework to compute the maximum interference caused by the shared memory bus and its impact on the execution time of the tasks running on the cores, considering different bus arbiters. Our novel approach clearly demarcates the arbiter-dependent and independent stages in the analysis of these upper bounds. The arbiter-dependent phase takes the arbiter and the task memory-traffic pattern as inputs and produces a model of the availability of the bus to a given task. Then, based on the availability of the bus, the arbiter-independent phase determines the worst-case request-release scenario that maximizes the interference experienced by the tasks due to the contention for the bus. We show that the framework addresses the diversity problem by applying it to a memory bus shared by a fixed-priority arbiter, a time-division multiplexing (TDM) arbiter, and an unspecified work-conserving arbiter using applications from the MediaBench test suite. We also experimentally evaluate the quality of the analysis by comparison with a state-of-the-art TDM analysis approach and consistently showing a considerable reduction in maximum interference.
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There has been several studies worldwide on phylogenetics and genotype distribution of the GB-virus C / Hepatitis G virus (GBV-C/HGV). However, in their great majority, those investigations were based on some epidemiologically linked group, rather than on a representative sampling of the general population. The present is a continuation of the first study in Brazil with such a population; it addresses the GBV-C/HGV phylogenetics and genotype distribution based on samples identified among more than 1,000 individuals of the city of São Paulo. For this purpose, a 728 bp fragment of the 5´non-coding region (5´NCR) of the viral genome, from 24 isolates, was sequenced and subjected to phylogenetic analysis. Genotypes 1, 2a and 2b were found at 8.3% (2/24), 50% (12/24) and 41.7% (10/24), respectively. In conclusion São Paulo displays a genotype distribution similar to the published data for other States and Regions of Brazil, endorsing the notion that types 1 and 2 would have entered the country with African and European people, respectively, since its earliest formation.
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Work in Progress Session, 21st IEEE Real-Time and Embedded Techonology and Applications Symposium (RTAS 2015). 13 to 16, Apr, 2015, pp 27-28. Seattle, U.S.A..
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Recent studies have shown differences in the epidemiology of invasive infections caused by Candida species worldwide. In the period comprising August 2002 to August 2003, we performed a study in Santa Casa Complexo Hospitalar, Brazil, to determine Candida species distribution associated with candidemia and their antifungal susceptibility profiles to amphotericin B, fluconazole and itraconazole. Antifungal susceptibility was tested according to the broth microdilution method described in the NCCLS (M27A-2 method). Only one sample from each patient was analyzed (the first isolate). Most of the episodes had been caused by species other than C. albicans (51.6%), including C. parapsilosis (25.8%), C. tropicalis (13.3%), C. glabrata (3.3%), C. krusei (1.7%), and others (7.5%). Dose-dependent susceptibility to itraconazole was observed in 14.2% of strains, and dose-dependent susceptibility to fluconazole was found in 1.6%. Antifungal resistance was not found, probably related to low use of fluconazole. Further epidemiological surveillance is needed.
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Poster presented in Work in Progress Session, The 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 24 to 27, Mar, 2015. Porto, Portugal.
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Catastrophic events, such as wars and terrorist attacks, big tornadoes and hurricanes, huge earthquakes, tsunamis, floods, and landslides, are always accompanied by a large number of casualties. The size distribution of these casualties have separately been shown to follow approximate power law (PL) distributions. In this paper, we analyze the number of victims of catastrophic phenomena, in particular, terrorism, and find double PL behavior. This means that the data set is better approximated by two PLs instead of one. We have plotted the two PL parameters corresponding to all terrorist events occurred in every year, from 1980 to 2010. We observe an interesting pattern in the chart, where the lines, that connect each pair of points defining the double PLs, are roughly aligned to each other.