Immunological response mounted by Aboriginal Australians living in the Northern Territory of Australia against Streptococcus pyogenes serum opacity factor

Streptococcus pyogenes (Group A streptococcus) interacts with host fibronectin via a number of distinct surface components. The streptococcal serum opacity factor (SOF) is a cell-surface protein of S. pyogenes which opalescence of human serum and mediates bacterial binding to fibronectin. In this study, hexahistidyl-tagged fusion proteins encompassing full-length SOF, and domains of SOF encompassing opacity factor activity and fibronectin-binding regions, were used in the characterization of the Aboriginal immune response to SOF. Anti-SOF serum IgG responses were found to be significantly higher (P

Crack detection in hollow section structures through coupled response measurements

Detection of a circumferential crack in a hollow section beam is investigated using coupled response measurements. The crack section is represented by a local flexibility matrix connecting two undamaged beam segments. This matrix defines the relationship between the displacements and forces across the crack section and is derived by applying fundamental fracture mechanics theory. The suitability of the mode coupling methodology is first demonstrated analytically. Laboratory test results are then presented for circular hollow section beams with artificially generated cracks of varying severity. It is shown that this method has the potential as a damage detection tool for mechanical structures. (C) 2002 Elsevier Science Ltd. All rights reserved.

Antigen-specific suppression of a primed immune response by dendritic cells mediated by regulatory T cells secreting interleukin-10

Antigen-specific suppression of a previously primed immune response is a major challenge for immunotherapy of autoimmune disease. ReIB activation is required for myeloid DC differentiation. Here, we show that antigen-exposed DCs in which ReIB function is inhibited lack cell surface CD40, prevent priming of immunity, and suppress previously primed immune responses. DCs generated from CD40-deficient mice similarly confer suppression. Regulatory CD4(+) T cells induced by the DCs transfer antigen-specific Infectious tolerance to primed recipients in an interleukin10-dependent fashion. Thus CD40, regulated by ReIB activity, determines the consequences of antigen presentation by myeloid DCs. These observations have significance for autoimmune immunotherapy and suggest a mechanism by which peripheral tolerance might be constitutively maintained by RelB(-) CD40(-) DCs.

An approach to verifying and debugging simulation models governed by ordinary differential equations: Part 1. Methodology for residual generation

For dynamic simulations to be credible, verification of the computer code must be an integral part of the modelling process. This two-part paper describes a novel approach to verification through program testing and debugging. In Part 1, a methodology is presented for detecting and isolating coding errors using back-to-back testing. Residuals are generated by comparing the output of two independent implementations, in response to identical inputs. The key feature of the methodology is that a specially modified observer is created using one of the implementations, so as to impose an error-dependent structure on these residuals. Each error can be associated with a fixed and known subspace, permitting errors to be isolated to specific equations in the code. It is shown that the geometric properties extend to multiple errors in either one of the two implementations. Copyright (C) 2003 John Wiley Sons, Ltd.

Methods to classify maize cultivars in use efficiency and response to nitrogen

n plant breeding programs that aim to obtain cultivars with nitrogen (N) use efficiency, the focus is on methods of selection and experimental procedures that present low cost, fast response, high repeatability, and can be applied to a large number of cultivars. Thus, the objectives of this study were to classify maize cultivars regarding their use efficiency and response to N in a breeding program, and to validate the methodology with contrasting doses of the nutrient. The experimental design was a randomized block with the treatments arranged in a split-plot scheme with three replicates and five N doses (0, 30, 60, 120 and 200 kg ha-1) in the plots, and six cultivars in subplots. We compared a method examining the efficiency and response (ER) with two contrasting doses of N. After that, the analysis of variance, mean comparison and regression analysis were performed. In conclusion, the method of the use efficiency and response based on two N levels classifies the cultivars in the same way as the regression analysis, and it is appropriate in plant breeding routine. Thus, it is necessary to identify the levels of N required to discriminate maize cultivars in conditions of low and high N availability in plant breeding programs that aim to obtain efficient and responsive cultivars. Moreover, the analysis of the interaction genotype x environment at experiments with contrasting doses is always required, even when the interaction is not significant.

Wetting response of KrF laser ablated polyimide surfaces

The wettability of polyimide surfaces microstructured using KrF laser radiation at fluences above the material ablation threshold was studied by static contact angle measurements. The laser-treated surfaces present a morphology consisting of conical features whose dimensions and areal density depend on the fluence. The effect of these parameters on the surface apparent contact angle depends on the wetting regime. When wetting occurs in the homogeneous regime, the apparent contact angle of the treated surfaces increases with the radiation fluence because the cone dimensions increase. In contrast, when wetting occurs in the heterogeneous regime, the apparent contact angle increases with the radiation fluence because the average distance between cones increases. The apparent water contact angle of the laser-treated surfaces can reach values as high as 162 degrees, as compared to 75 degrees for virgin polyimide.

Exposure assessment: the influence of environmental monitoring methodology

Exposure assessment is an important step of risk assessment process and has evolved more quickly than perhaps any aspect of the four-step risk paradigm (hazard identification, exposure assessment, dose-response analysis, and risk characterization). Nevertheless, some epidemiological studies have associated adverse health effects to a chemical exposure with an inadequate or absent exposure quantification. In addition to the metric used, the truly representation of exposure by measurements depends on: the strategy of sampling, random collection of measurements, and similarity between the measured and unmeasured exposure groups. Two environmental monitoring methodologies for formaldehyde occupational exposure were used to assess the influence of metric selection in exposure assessment and, consequently, in risk assessment process.

Virtual power players demand response programs management based on locational marginal prices

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.

Study of distribution network demand response events in the Portuguese system

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.

Using demand response to deal with unexpected low wind power generation in the context of smart grid

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).

Energy and reserve provision dispatch considering distributed generation and demand response

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.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

Particle swarm optimization applied to integrated demand response resources scheduling

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.

LMP triggered real time demand response events

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.

Demand response programs definition supported by clustering and classification techniques

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.