The role of the church in developing the law

The church and other community organisations have a legitimate role to play in influencing public policy. However, intervention by the church and other religious bodies in recent litigation in Australia and the United Kingdom raises questions about the appropriateness of such bodies being permitted to intervene directly in the court process as amici curiae. We argue that there are dangers in such bodies insinuating their doctrine under the guise of legal argument in civil proceedings, but find it difficult to enunciate a principled distinction between doctrine and legal argument. We advise that judges should exercise caution in dealing with amicus submissions.

Complementary and layered expression of Ephs and Ephrins in developing mouse inner ear

The distributions of the Eph-class receptors EphA4 and EphB 1, and their ligands ephrin-A2, ephrin-B1, and ephrin-B2, were analysed by immunostaining in the mouse inner ear. Complementary patterns of EphA4 and its potential ligand ephrin-A2 were found, with ephrin-A2 in many of the structures lining the cochlear duct and within the cochlear nerve cells, and EphA4 in the deeper structures underlying the cochlear duct and in the cells lining the nerve pathway. EphB1 and its potential ligands ephrin-B1 and ephrin-B2 showed a segregated layered expression in the lateral wall of the cochlear duct (the external sulcus), which together with EphA4 expressed in the area, form a four-layered structure with an alternating pattern of receptors and ligands in the different layers. This arrangement gives the potential for different bidirectional Eph-mediated interactions between each of the layers. The results suggest that the Eph system in the cochlea may have a role in maintaining cell segregation during phases of cochlear development. (C) 2002 Wiley-Liss, Inc.

Expression of ephs and ephrins in developing mouse inner ear

Levels of expression of mRNAs encoding the different Ephs and ephrins were measured by semi-quantitative reverse-transcription polymerase chain reaction in developing mouse whole inner ears, and in dissected fractions of the neonatal mouse inner ear. Nineteen of the 24 known Ephs and ephrins were surveyed. The results showed that between embryonic age (E) 11.5 days and E12.5, levels increased 10-300 times per unit of tissue. In neonatal mice, the fraction containing combined organ of Corti and spiral ganglion showed relatively strong expression of EphA4, EphB3, ephrin-A3, ephrin-B2 and ephrin-B3. In the lateral wall, EphA4, ephrin-A3 and ephrin-B2 were strongly expressed, while ephrin-A3 was particularly strongly expressed in utricular and saccular sensory epithelia. The results suggest that the Ephs and ephrins are likely to play a part in the differentiation of the structures of the inner ear, and show which Ephs and ephrins are most likely to play important roles in the different structures. (C) 2003 Elsevier Science B.V. All rights reserved.

The engine or the caboose: health policy in developing countries

A discussion of health policy in developing countries is presented. It argues that developing countries must adopt a progressive approach to health policy which rejects the two-tiered system of public and private health care. However, it also points out that ideology is not sufficient to maintain support. A progressive health system must utilize administrative and social and behavioral sciences to achieve effectiveness and efficiency in health care delivery. It cannot ignore these goals any more than a private health care system can.

Microscopic analysis of "prato", "mussarela" and "mineiro" cheese sold in street markets of the City of S. Paulo, Southeastern Brazil

INTRODUCTION: Cheese should be produced from ingredients of good quality and processed under hygienic conditions. Further, cheese should be transported, stored and sold in an appropriate manner in order to avoid, among other things, the incorporation of extraneous materials (filth) of biological origin or otherwise, in contravention of the relevant food legislation. The aim of the study was to evaluate the hygienic conditions of "prato", "mussarela", and "mineiro" cheeses sold at the street food markets in the city of S. Paulo, Brazil. MATERIALS AND METHOD: Forty-seven samples of each of the three types of cheese were collected during the period from March, 1993 to February, 1994. The Latin square was used as a statistical model for sampling and random selection of the street markets from which to collect the cheese samples. The samples were analysed for the presence of extraneous matters outside for which purpose the samples were washed and filtered and inside, for which the methodology of enzymathic digestion of the sample with pancreatine, followed by filtering,was used. RESULTS AND CONCLUSION: Of the 141 samples analysed, 75.9% exhibited at least one sort of extraneous matters. For the "prato" and "mussarela" cheeses, the high number of contaminated samples was due mainly to extraneous matters present inside the cheese, whereas in the "mineiro" cheese, besides the internal filth, 100% of the samples had external filth.

Intelligent decision making in electricity markets: simulated annealing Q-Learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

A multi-agent system for the support of producer coalition formation in electricity markets

All over the world Distributed Generation is seen as a valuable help to get cleaner and more efficient electricity. To get negotiation power and advantages of scale economy, distributed producers can be aggregated giving place to a new concept: the Virtual Power Producer. Virtual Power Producers are multitechnology and multi-site heterogeneous entities. Virtual Power Producers should adopt organization and management methodologies so that they can make Distributed Generation a really profitable activity, able to participate in the market. In this paper we address the development of a multi-agent market simulator – MASCEM – able to study alternative coalitions of distributed producers in order to identify promising Virtual Power Producers in an electricity market.

A decision-support system based on particle swarm optimization for multiperiod hedging in electricity markets

This paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.

Multiagent system for adaptive strategy formulation in electricity markets

Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal.

Renewable-based generation integration in electricity markets with virtual power producers

The development of renewable energy sources and Distributed Generation (DG) of electricity is of main importance in the way towards a sustainable development. However, the management, in large scale, of these technologies is complicated because of the intermittency of primary resources (wind, sunshine, etc.) and small scale of some plants. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. VPPs can ensure a secure, environmentally friendly generation and optimal management of heat, electricity and cold as well as optimal operation and maintenance of electrical equipment, including the sale of electricity in the energy market. For attaining these goals, there are important issues to deal with, such as reserve management strategies, strategies for bids formulation, the producers’ remuneration, and the producers’ characterization for coalition formation. This chapter presents the most important concepts related with renewable-based generation integration in electricity markets, using VPP paradigm. The presented case studies make use of two main computer applications:ViProd and MASCEM. ViProd simulates VPP operation, including the management of plants in operation. MASCEM is a multi-agent based electricity market simulator that supports the inclusion of VPPs in the players set.

Multi-agent negotiation for coalition formation and management in electricity markets

Negotiation is a fundamental tool for reaching understandings that allow each involved party to gain an advantage for themselves by the end of the process. In recent years, with the increasing of compe-titiveness in most sectors, negotiation procedures become present in practically all of them. One particular environment in which the competitiveness has been increasing exponentially is the electricity markets sector. This work is directed to the study of electricity markets’ partici-pating entities interaction, namely in what concerns the formation, management and operation of aggregating entities – Virtual Power Players (VPPs). VPPs are responsible for managing coalitions of market players with small market negotiating influence, which take strategic advantage in entering such aggregations, to increase their negotiating power. This chapter presents a negotiation methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using MASCEM, taking advantage of its ability to provide the means to model and simulate VPPs. VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself.

Commercial agents portfolio optimization in electricity markets

As it is well known, competitive electricity markets require new computing tools for power companies that operate in retail markets in order to enhance the management of its energy resources. During the last years there has been an increase of the renewable penetration into the micro-generation which begins to co-exist with the other existing power generation, giving rise to a new type of consumers. This paper develops a methodology to be applied to the management of the all the aggregators. The aggregator establishes bilateral contracts with its clients where the energy purchased and selling conditions are negotiated not only in terms of prices but also for other conditions that allow more flexibility in the way generation and consumption is addressed. The aggregator agent needs a tool to support the decision making in order to compose and select its customers' portfolio in an optimal way, for a given level of profitability and risk.

Strategic bidding in electricity markets: an agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Investment focused strategies in electricity markets using the ITEM-game simulator

This paper presents a methodology to establish investment and trading strategies of a power generation company. These strategies are integrated in the ITEM-Game simulator in order to test their results when played against defined strategies used by other players. The developed strategies are focused on investment decisions, although trading strategies are also implemented to obtain base case results. Two cases are studied considering three players with the same trading strategy. In case 1, all players also have the same investment strategy driven by a market target share. In case 2, player 1 has an improved investment strategy with a target share twice of the target of players 2 and 3. Results put in evidence the influence of the CO2 and fuel prices in the company investment decision. It is also observed the influence of the budget constraint which might prevent the player to take the desired investment decision.