952 resultados para transmission culturel


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The visual biology of Hawaiian reef fishes was explored by examining their eyes for spectral sensitivity of their visual pigments and for transmission of light through the ocular media to the retina. The spectral absorption curves for the visual pigments of 38 species of Hawaiian fish were recorded using microspectrophotometry. The peak absorption wavelength (lambda(max)) of the rods varied from 477-502 nm and the lambda(max) of individual species conformed closely to values for the same species previously reported using a whole retina extraction procedure. The visual pigments of single cone photoreceptors were categorized, dependent on their lambda(max)-values, as ultraviolet (347-376 nm), violet (398-431 nm) or blue (439-498 nm) sensitive cones. Eight species possessed ultraviolet-sensitive cones and 14 species violet-sensitive cones. Thus, 47% of the species examined displayed photosensitivity to the short-wavelength region of the spectrum. Both identical and nonidentical paired and double cones were found with blue sensitivity or green absorption peaks (> 500 nm). Spectrophotometry of the lens, cornea, and humors for 195 species from 49 families found that the spectral composition of the light transmitted to the retina was most often limited by the lens (73% of species examined). Except for two unusual species with humor-limited eyes, Acanthocybium solandri (Scombridae) and the priacanthid fish, Heteropriacanthus cruentatus, the remainder had corneal-limited eyes. The wavelength at which 50% of the light was blocked (T50) was classified according to a system modified from Douglas and McGuigan (1989) as Type I, T50 < = 355 nm, (32 species); Type IIa, 355 < T50 < = 380 nm (30 species); Type IIb, 380 < T50 405 nm (84 species). Possession of UV-transmitting ocular media follows both taxonomic and functional lines and, if the ecology of the species is considered, is correlated with the short-wavelength visual pigments found in the species. Three types of short-wavelength vision in fishes are hypothesized: UV-sensitive, UV-specialized, and violet-specialized. UV-sensitive eyes lack UV blockers (Type I and IIa) and can sense UV light with the secondary absorption peak or beta peak of their longer wavelength visual pigments but do not possess specialized UV receptor cells and, therefore, probably lack UV hue discrimination. UV-specialized eyes allow transmission of UV light to the retina (Type I and IIa) and also possess UV-sensitive cone receptors with peak absorption between 300 and 400 nm. Given the appropriate perceptual mechanisms, these species could possess true UV-color vision and hue discrimination. Violet-specialized eyes extend into Type IIb eyes and possess violet-sensitive cone cells. UV-sensitive eyes are found throughout the fishes from at least two species of sharks to modern bony fishes. Eyes with specialized short-wavelength sensitivity are common in tropical reef fishes and must be taken into consideration when performing research involving the visual perception systems of these fishes. Because most glass and plastics are UV-opaque, great care must be taken to ensure that aquarium dividers, specimen holding containers, etc., are UV-transparent or at least to report the types of materials in use.

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OBJECTIVE: To show how a mathematical model can be used to describe and to understand the malaria transmission. METHODS: The effects on malaria transmission due to the impact of the global temperature changes and prevailing social and economic conditions in a community were assessed based on a previously presented compartmental model, which describes the overall transmission of malaria. RESULTS/CONCLUSIONS: The assessments were made from the scenarios produced by the model both in steady state and dynamic analyses. Depending on the risk level of malaria, the effects on malaria transmission can be predicted by the temperature ambient or local social and-economic conditions.

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OBJECTIVE: Describe the overall transmission of malaria through a compartmental model, considering the human host and mosquito vector. METHODS: A mathematical model was developed based on the following parameters: human host immunity, assuming the existence of acquired immunity and immunological memory, which boosts the protective response upon reinfection; mosquito vector, taking into account that the average period of development from egg to adult mosquito and the extrinsic incubation period of parasites (transformation of infected but non-infectious mosquitoes into infectious mosquitoes) are dependent on the ambient temperature. RESULTS: The steady state equilibrium values obtained with the model allowed the calculation of the basic reproduction ratio in terms of the model's parameters. CONCLUSIONS: The model allowed the calculation of the basic reproduction ratio, one of the most important epidemiological variables.

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OBJECTIVE: It is an accepted fact that confinement conditions increase the risk of some infections related to sexual and/or injecting drugs practices. Mathematical techniques were applied to estimate time-dependent incidence densities of HIV infection among inmates. METHODS: A total of 631 prisoners from a Brazilian prison with 4,900 inmates at that time were interviewed and their blood drawn. Risky behavior for HIV infection was analyzed, and serological tests for HIV, hepatitis C and syphilis were performed, intended as surrogates for parenteral and sexual HIV transmission, respectively. Mathematical techniques were used to estimate the incidence density ratio, as related to the time of imprisonment. RESULTS: Prevalence were: HIV -- 16%; HCV -- 34%; and syphilis -- 18%. The main risk behaviors related to HIV infection were HCV prevalence (OR=10.49) and the acknowledged use of injecting drugs (OR=3.36). Incidence density ratio derivation showed that the risk of acquiring HIV infection increases with the time of imprisonment, peaking around three years after incarceration. CONCLUSIONS: The correlation between HIV and HCV seroprevalence and the results of the mathematical analysis suggest that HIV transmission in this population is predominantly due to parenteral exposure by injecting drug, and that it increases with time of imprisonment.

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OBJECTIVE: Sensitivity analysis was applied to a mathematical model describing malaria transmission relating global warming and local socioeconomic conditions. METHODS: A previous compartment model was proposed to describe the overall transmission of malaria. This model was built up on several parameters and the prevalence of malaria in a community was characterized by the values assigned to them. To assess the control efforts, the model parameters can vary on broad intervals. RESULTS: By performing the sensitivity analysis on equilibrium points, which represent the level of malaria infection in a community, the different possible scenarios are obtained when the parameters are changed. CONCLUSIONS: Depending on malaria risk, the efforts to control its transmission can be guided by a subset of parameters used in the mathematical model.

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In a liberalized electricity market, the Transmission System Operator (TSO) plays a crucial role in power system operation. Among many other tasks, TSO detects congestion situations and allocates the payments of electricity transmission. This paper presents a software tool for congestion management and transmission price determination in electricity markets. The congestion management is based on a reformulated Optimal Power Flow (OPF), whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the dispatch proposed by the market operator. The transmission price computation considers the physical impact caused by the market agents in the transmission network. The final tariff includes existing system costs and also costs due to the initial congestion situation and losses costs. The paper includes a case study for the IEEE 30 bus power system.

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Multilevel power converters have been introduced as the solution for high-power high-voltage switching applications where they have well-known advantages. Recently, full back-to-back connected multilevel neutral point diode clamped converters (NPC converter) have been used inhigh-voltage direct current (HVDC) transmission systems. Bipolar-connected back-to-back NPC converters have advantages in long-distance HVDCtransmission systems over the full back-to-back connection, but greater difficulty to balance the dc capacitor voltage divider on both sending and receiving end NPC converters. This study shows that power flow control and dc capacitor voltage balancing are feasible using fast optimum-predictive-based controllers in HVDC systems using bipolar back-to-back-connected five-level NPC multilevel converters. For both converter sides, the control strategytakes in account active and reactive power, which establishes ac grid currents in both ends, and guarantees the balancing of dc bus capacitor voltages inboth NPC converters. Additionally, the semiconductor switching frequency is minimised to reduce switching losses. The performance and robustness of the new fast predictive control strategy, and its capability to solve the DC capacitor voltage balancing problem of bipolar-connected back-to-back NPCconverters are evaluated.

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Voltage source multilevel power converter structures are being considered for high power high voltage applications where they have well known advantages. Recently, full back-to-back connected multilevel neutral diode clamped converters (NPC) have been used in high voltage direct current (HVDC) transmission systems. Bipolar back-to-back connection of NPCs have advantages in long distance HVDC transmission systems, but highly increased difficulties to balance the dc capacitor voltage dividers on both sending and receiving end NPCs. This paper proposes a fast optimum-predictive controller to balance the dc capacitor voltages and to control the power flow in a long distance HVDCsystem using bipolar back-to-back connected NPCs. For both converter sides, the control strategy considers active and reactive power to establish ac grid currents on sending and receiving ends, while guaranteeing the balancing of both NPC dc bus capacitor voltages. Furthermore, the fast predictivecontroller minimizes the semiconductor switching frequency to reduce global switching losses. The performance and robustness of the new fast predictive control strategy and the associated dc capacitors voltage balancing are evaluated. (C) 2011 Elsevier B.V. All rights reserved.

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In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.

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This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

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OBJECTIVE: To study the risk of Trypanosoma cruzi domestic transmission using an entomological index and to explore its relationship with household's characteristics and cultural aspects. METHODS: There were studied 158 households in an endemic area in Argentina. Each household was classified according to an entomological risk indicator (number of risky bites/human). A questionnaire was administered to evaluate risk factors among householders. RESULTS: Infested households showed a wide range of risk values (0 to 5 risky bites/human) with skewed distribution, a high frequency of lower values and few very high risk households. Of all collected Triatoma infestans, 44% had had human blood meals whereas 27% had had dogs or chickens blood meals. Having dogs and birds sharing room with humans increased the risk values. Tidy clean households had contributed significantly to lower risk values as a result of low vector density. The infested households showed a 24.3% correlation between time after insecticide application and the number of vectors. But there was no correlation between the time after insecticide application and T. infestans' infectivity. The statistical analysis showed a high correlation between current values of the entomological risk indicator and Trypanosoma cruzi seroprevalence in children. CONCLUSIONS: The risk of T. cruzi domestic transmission assessed using an entomological index show a correlation with children seroprevalence for Chagas' disease and householders' habits.

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This paper presents a software tool (SIM_CMTP) that solves congestion situations and evaluates the taxes to be paid to the transmission system by market agents. SIM_CMTP provides users with a set of alternative methods for cost allocation and enables the definition of specific rules, according to each market and/or situation needs. With these characteristics, SIM_CMTP can be used as an operation aid for Transmission System Operator (TSO) or Independent System Operator (ISO). Due to its openness, it can also be used as a decision-making support tool for evaluating different options of market rules in competitive market environment, guarantying the economic sustainability of the transmission system.

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Congestion management of transmission power systems has achieve high relevance in competitive environments, which require an adequate approach both in technical and economic terms. This paper proposes a new methodology for congestion management and transmission tariff determination in deregulated electricity markets. The congestion management methodology is based on a reformulated optimal power flow, whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the transactions resulting from market operation. The proposed transmission tariffs consider the physical impact caused by each market agents in the transmission network. The final tariff considers existing system costs and also costs due to the initial congestion situation and losses. This paper includes a case study for the 118 bus IEEE test case.

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This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

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In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.