978 resultados para Oxygen demand


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Phosphine (hydrogen phosphide, PH3) is the fumigant most widely used to protect stored products from pest infestation. Despite the importance of this chemical, little is known about its mode of action. We have created three phosphine-resistant lines (pre-1, pre-7, pre-33) in the model organism C. elegans, with LC50 values 2, 5, and 9 times greater than the fully susceptible parental strain. Molecular oxygen was shown to be an extremely effective synergist with phosphine as, under hyperoxic conditions, 100% mortality was observed in wild-type nematodes exposed to 0.1 mg/l phosphine, a nonlethal concentration in air. All three mutants were resistant to the synergistic effects of oxygen in proportion to their resistance to phosphine with one mutant, pre-33, showing complete resistance to this synergism. We take the proportionality of cross-resistance between phosphine and the synergistic effect of oxygen to imply that all three mutants circumvent a mechanism of phosphine toxicity that is directly coupled to oxygen metabolism. Compared with the wild-type strain, all three mutants have an extended average life expectancy of from 12.5 to 25.3%. This is consistent with the proposed involvement of oxidative stress in both phosphine toxicity and ageing. Because the wild-type and mutant nematodes develop at the same rate, the longevity is unlikely to be caused by a clk-type reduction in oxidative metabolism, a potential alternative mechanism of phosphine resistance.

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Measurement of hepatic oxygen extraction was performed on six healthy Greyhound dogs over a two hour period. The Greyhounds were anaesthetised and a right subcostal surgical incision performed. Ultrasonic flow transducers were used to measure flow rate in the hepatic artery and the portal vein. The blood oxygen tensions in arterial blood and in the portal and hepatic veins were also measured. Hepatic oxygen extraction remained stable throughout the study, despite a steady decline in arterial blood pressure. The methodology described in this study provides a direct measure of oxygen uptake by the liver in the dog and could readily be used to investigate hepatic uptake of drugs. (C) 2003 Elsevier Ltd. All rights reserved.

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The aim of this study was to compare accumulated oxygen deficit data derived using two different exercise protocols with the aim of producing a less time-consuming test specifically for use with athletes. Six road and four track male endurance cyclists performed two series of cycle ergometer tests. The first series involved five 10 min sub-maximal cycle exercise bouts, a (V) over dotO(2peak) test and a 115% (V) over dotO(2peak) test. Data from these tests were used to estimate the accumulated oxygen deficit according to the calculations of Medbo et al. (1988). In the second series of tests, participants performed a 15 min incremental cycle ergometer test followed, 2 min later, by a 2 min variable resistance test in which they completed as much work as possible while pedalling at a constant rate. Analysis revealed that the accumulated oxygen deficit calculated from the first series of tests was higher (P< 0.02) than that calculated from the second series: 52.3 +/- 11.7 and 43.9 +/- 6.4 ml . kg(-1), respectively (mean +/- s). Other significant differences between the two protocols were observed for (V) over dot O-2peak, total work and maximal heart rate; all were higher during the modified protocol (P

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Simultaneous nitrification and denitrification (SND) via the nitrite pathway and anaerobic-anoxic-enhanced biological phosphorus removal (EBPR) are two processes that can significantly reduce the energy and COD demand for nitrogen and phosphorus removal. The combination of these two processes has the potential of achieving simultaneous nitrogen and phosphorus removal with a minimal requirement for COD. A lab-scale sequencing batch reactor (SBR) was operated in alternating anaerobic-aerobic mode with a low dissolved oxygen (DO) concentration (0.5 mg/L) during the aerobic period, and was demonstrated to accomplish nitrification, denitrification, and phosphorus removal. Under anaerobic conditions, COD was taken up and converted to poly-hydroxyalkanoates (PHAs), accompanied by phosphorus release. In the subsequent aerobic stage, PHA was oxidized and phosphorus was taken up to

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This investigation aimed to elucidate the relative roles of putative brevetoxins, reactive oxygen species and free fatty acids as the toxic principle of the raphidophyte Chattonella marina, using damselfish as the bioassay. Our investigations on Australian C. marina demonstrated an absence or only very low concentrations of brevetoxin-like compounds by radio-receptor binding assay and liquid chromatography-mass spectroscopy techniques. Chattonella is unique in its ability to produce levels of reactive oxygen species 100 times higher than most other algal species. However, high levels of superoxide on their own were found not to cause fish mortalities. Lipid analysis revealed this raphidophyte to contain high concentrations of the polyunsaturated fatty acid eicosapentaenoic acid (EPA; 18-23% of fatty acids), which has demonstrated toxic properties to marine organisms. Using damselfish as a model organism, we demonstrated that the free fatty acid (FFA) form of EPA produced a mortality and fish behavioural response similar to fish exposed to C. marina cells. This effect was not apparent when fish were exposed to other lipid fractions including a triglyceride containing fish oil, docosahexaenoate-enriched ethyl ester, or pure brevetoxin standards. The presence of superoxide together with low concentrations of EPA accelerated fish mortality rate threefold. We conclude that the enhancement of ichthyotoxicity of EPA in the presence of superoxide can account for the high C. marina fish killing potential. (C) 2003 Elsevier B.V All rights reserved.

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The increased preference for minimally processed vegetables has been attributed to the health benefits associated with fresh produce and the demand for ready-to-eat salads. In this paper, lettuce (Lactuca sativa L.) was evaluated for the effects of different cropping systems on the respiratory properties. Lettuce was packaged in low density polyethylene bags and stored in a refrigerator at 4 ºC. The concentration of carbon dioxide and oxygen inside the package was monitored during the storage at zero, three, six, eight, ten and twelve days by gas chromatography. Dry matter variation was measured gravimetrically up to day fourteen of storage. Values of respiratory rate for conventional lettuce increased from day 1 to 3 and remained low, while respiratory rate of the organic lettuce increased three-fold up to day 8, stabilizing at a high level. Variation in dry matter during storage also resulted from differences between the two cultivation systems. The highest content of dry matter was achieved by organic lettuce.

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Power systems have been suffering huge changes mainly due to the substantial increase of distributed generation and to the operation in competitive environments. Virtual power players can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Resource management gains an increasing relevance in this competitive context, while demand side active role provides managers with increased demand elasticity. This makes demand response use more interesting and flexible, giving rise to a wide range of new opportunities.This paper proposes a methodology for managing demand response programs in the scope of virtual power players. The proposed method is based on the calculation of locational marginal prices (LMP). The evaluation of the impact of using demand response specific programs on the LMP value supports the manager decision concerning demand response use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus network with intensive use of distributed generation.

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The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

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In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. Grid operators and utilities are taking new initiatives, recognizing the value of demand response for grid reliability and for the enhancement of organized spot markets’ efficiency. This paper proposes a methodology for the selection of the consumers that participate in an event, which is the responsibility of the Portuguese transmission network operator. The proposed method is intended to be applied in the interruptibility service implemented in Portugal, in convergence with Spain, in the context of the Iberian electricity market. This method is based on the calculation of locational marginal prices (LMP) which are used to support the decision concerning the consumers to be schedule for participation. The proposed method has been computationally implemented and its application is illustrated in this paper using a 937 bus distribution network with more than 20,000 consumers.

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The design and development of simulation models and tools for Demand Response (DR) programs are becoming more and more important for adequately taking the maximum advantages of DR programs use. Moreover, a more active consumers’ participation in DR programs can help improving the system reliability and decrease or defer the required investments. DemSi, a DR simulator, designed and implemented by the authors of this paper, allows studying DR actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. DemSi considers the players involved in DR actions, and the results can be analyzed from each specific player point of view.

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Demand response is assumed an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed aims the minimization of the operation costs in a smart grid operated by a virtual power player. It is especially useful when actual and day ahead wind forecast differ significantly. When facing lower wind power generation than expected, RTP is used in order to minimize the impacts of such wind availability change. The proposed model application is here illustrated using the scenario of a special wind availability reduction day in the Portuguese power system (8th February 2012).

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In competitive electricity markets with deep concerns at the efficiency level, demand response programs gain considerable significance. In the same way, distributed generation has gained increasing importance in the operation and planning of power systems. Grid operators and utilities are taking new initiatives, recognizing the value of demand response and of distributed generation for grid reliability and for the enhancement of organized spot market´s efficiency. Grid operators and utilities become able to act in both energy and reserve components of electricity markets. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus distribution network with 32 medium voltage consumers.

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The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.

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Recent changes in power systems mainly due to the substantial increase of distributed generation and to the operation in competitive environments has created new challenges to operation and planning. In this context, Virtual Power Players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Demand response market implementation has been done in recent years. Several implementation models have been considered. An important characteristic of a demand response program is the trigger criterion. A program for which the event trigger depends on the Locational Marginal Price (LMP) used by the New England Independent System operator (ISO-NE) inspired the present paper. This paper proposes a methodology to support VPP demand response programs management. The proposed method has been computationally implemented and its application is illustrated using a 32 bus network with intensive use of distributed generation. Results concerning the evaluation of the impact of using demand response events are also presented.

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The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.