Mortality problems in Brazil and in Germany: past-present-future. Learning from each other?

This article was written by a Swiss-German historical demographer after having visited different Brazilian Universities in 1984 as a guest-professor. It aims at promoting a real dialog between developed and developing countries, commencing the discussion with the question: Can we learn from each other? An affirmative answer is given, but not in the superficial manner in which the discussion partners simply want to give each other some "good advice" or in which the one declares his country's own development to be the solely valid standard. Three points are emphasized: 1. Using infant mortality in S. Paulo from 1908 to 1983 as an example, it is shown that Brazil has at its disposal excellent, highly varied research literature that is unjustifiably unknown to us (in Europe) for the most part. Brazil by no means needs our tutoring lessons as regards the causal relationships; rather, we could learn two things from Brazil about this. For one, it becomes clear that our almost exclusively medical-biological view is inappropriate for passing a judgment on the present-day problems in Brazil and that any conclusions so derived are thus only transferable to a limited extent. For another, we need to reinterpret the history of infant mortality in our own countries up to the past few decades in a much more encompassing "Brazilian" sense. 2. A fruitful dialog can only take place if both partners frankly present their problems. For this reason, the article refers with much emprasis to our present problems in dealing with death and dying - problems arising near the end of the demographic and epidemiologic transitions: the superanuation of the population, chronic-incurable illnesses as the main causes of death, the manifold dependencies of more and more elderly and really old people at the end of a long life. Brazil seems to be catching up to us in this and will be confronted with these problems sooner or later. A far-sighted discussion already at this time seems thus to be useful. 3. The article, however, does not want to conclude with the rather depressing state of affairs of problems alternatingly superseding each other. Despite the caution which definitely has a place when prognoses are being made on the basis of extrapolations from historical findings, the foreseeable development especially of the epidemiologic transition in the direction of a rectangular survival curve does nevertheless provide good reason for being rather optimistic towards the future: first in regards to the development in our own countries, but then - assuming that the present similar tendencies of development are stuck to - also in regard to Brazil.

Impacto da integração dos veículos eléctricos nos edifícios multi-habitacionais, nas redes de distribuição de baixa tensão e no diagrama de carga nacional

Associado à escassez dos combustíveis fósseis e ao desejado controlo de emissões nocivas para a atmosfera, assistimos no mundo ao desenvolvimento do um novo paradigma — a mobilidade eléctrica. Apesar das variações de maior ou menor arbítrio político dos governos, do excelente ou débil desenvolvimento tecnológico, relacionados com os veículos eléctricos, estamos perante um caminho, no que diz respeito à mobilidade eléctrica, que já não deve ser encarado como uma moda mas como uma orientação para o futuro da mobilidade. Portugal tendo dado mostras que pretende estar na dianteira deste desafio, necessita equacionar e compreender em que condições existirá uma infra-estrutura nacional capaz de fazer o veículo eléctrico vingar. Assim, neste trabalho, analisa-se o impacto da mobilidade eléctrica em algumas dessas infra-estruturas, nomeadamente nos edifícios multi-habitacionais e redes de distribuição em baixa tensão. São criados neste âmbito, quatro perfis de carregamento dos EVs nomeadamente: nas horas de chegada a casa; nas horas de vazio com início programado pelo condutor; nas horas de vazio controlado por operador de rede (“Smart Grid”); e um cenário que contempla a utilização do V2G. Com a obrigação legal de nos novos edifícios serem instaladas tomadas para veículos eléctricos, é estudado, com os cenários anteriores a possibilidade de continuar a conceber as instalações eléctricas, sem alterar algumas das disposições legais, ao abrigo dos regulamentos existentes. É também estudado, com os cenários criados e com a previsão da venda de veículos eléctricos até 2020, o impacto deste novo consumo no diagrama de carga do Sistema Eléctrico Nacional. Mostra-se assim que a introdução de sistemas inteligentes de distribuição de energia [Smartgrid e vehicle to grid” (V2G)] deverá ser encarada como a solução que por excelência contribuirá para um aproveitamento das infra-estruturas existentes e simultaneamente um uso acessível para os veículos eléctricos.

The US actuarial balance model for the pay-as-you-go system and its application to Spain

The aim of this paper is to formulate an approximation of the US actuarial balance model and apply it to the Spanish public retirement pension system under various scenarios in order to determine a consistent indicator of the system's financial state comparable to those used by the most advanced social security systems. This will enable us to answer the question as to whether there is any justification for reforming the pension system in Spain. This type of actuarial balance uses projections to show future challenges to the financial side of the pension system deriving basically from ageing, the projected increase in longevity and fluctuations in economic activity. If one is compiled periodically it can provide various indicators to help depoliticize the management of the pay-as-you-go system by bringing the planning horizons of politicians and the system itself closer together.

Reabilitação do túnel do Loureiro: criação de condições para a sua eletrificação

Existe uma necessidade de reabilitação das linhas mais antigas para que estas possam dar maior conforto, comodidade e segurança aos utentes e para que o caminho - de- ferro possa ser competitivo com outros meios de transporte. A REFER é a empresa que gere a conservação, manutenção, renovação das linhas de caminho-de-ferro existentes e a construção de novas linhas. No caso em estudo, trata-se de uma linha de caminho-de-ferro antiga a necessitar de renovação/manutenção, sendo por isso a REFER a empresa responsável pelo lançamento de novos projetos neste âmbito. Este relatório de estágio foi desenvolvido no âmbito do estudo de soluções para a reabilitação do túnel do Loureiro, com o objetivo da criação de condições para a sua eletrificação. Foram equacionados três cenários possíveis, todos eles com o propósito da futura eletrificação da via. A primeira solução passa pela conversão de via balastrada em via não balastrada dentro do túnel, a segunda solução cinge-se à intervenção nas bocas do túnel e nas zonas de alvenaria, e a terceira hipótese é uma solução de rebaixamento de via. De entre as três hipóteses, optou-se por estudar a terceira solução de rebaixamento da via, em detrimento das outras duas devido à sua complexidade de trabalhos e ao seu elevado custo de construção.

Contributos para a implementação dum modelo de gestão da qualidade num serviço de tomografia computorizada: uma análise prospectiva

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Administração e Gestão de Serviços de Saúde.

Reabilitação no internamento hospitalar: prospectiva na dinâmica de actores - Implementação da governação clínica num hospital E.P.E.

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Administração e Gestão de Serviços de Saúde.

Contributos para uma prospectiva da implementação de um centro de responsabilidade de radiologia numa Unidade Local de Saúde: o caso da Unidade Local de Saúde do Norte Alentejano

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Administração e Gestão de Serviços de Saúde.

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.

ANN based support for distributed energy resources scheduling in smart grids

The future scenarios for operation of smart grids are likely to include a large diversity of players, of different types and sizes. With control and decision making being decentralized over the network, intelligence should also be decentralized so that every player is able to play in the market environment. In the new context, aggregator players, enabling medium, small, and even micro size players to act in a competitive environment, will be very relevant. Virtual Power Players (VPP) and single players must optimize their energy resource management in order to accomplish their goals. This is relatively easy to larger players, with financial means to have access to adequate decision support tools, to support decision making concerning their optimal resource schedule. However, the smaller players have difficulties in accessing this kind of tools. So, it is required that these smaller players can be offered alternative methods to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), intended to support smaller players’ resource scheduling. The used methodology uses a training set that is built using the energy resource scheduling solutions obtained with a reference optimization methodology, a mixed-integer non-linear programming (MINLP) in this case. The trained network is able to achieve good schedule results requiring modest computational means.

Computational intelligence applications for future power systems

Power system planning, control and operation require an adequate use of existing resources as to increase system efficiency. The use of optimal solutions in power systems allows huge savings stressing the need of adequate optimization and control methods. These must be able to solve the envisaged optimization problems in time scales compatible with operational requirements. Power systems are complex, uncertain and changing environments that make the use of traditional optimization methodologies impracticable in most real situations. Computational intelligence methods present good characteristics to address this kind of problems and have already proved to be efficient for very diverse power system optimization problems. Evolutionary computation, fuzzy systems, swarm intelligence, artificial immune systems, neural networks, and hybrid approaches are presently seen as the most adequate methodologies to address several planning, control and operation problems in power systems. Future power systems, with intensive use of distributed generation and electricity market liberalization increase power systems complexity and bring huge challenges to the forefront of the power industry. Decentralized intelligence and decision making requires more effective optimization and control techniques techniques so that the involved players can make the most adequate use of existing resources in the new context. The application of computational intelligence methods to deal with several problems of future power systems is presented in this chapter. Four different applications are presented to illustrate the promises of computational intelligence, and illustrate their potentials.

Towards a future SCADA

Currently, Power Systems (PS) already accommodate a substantial penetration of DG and operate in competitive environments. In the future PS will have to deal with largescale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. This cannot be done with the traditional PS operation. SCADA (Supervisory Control and Data Acquisition) is a vital infrastructure for PS. Current SCADA adaptation to accommodate the new needs of future PS does not allow to address all the requirements. In this paper we present a new conceptual design of an intelligent SCADA, with a more decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). Once a situation is characterized, data and control options available to each entity are re-defined according to this context, taking into account operation normative and a priori established contracts. The paper includes a case-study of using future SCADA features to use DER to deal with incident situations, preventing blackouts.

The role of demand response in future power systems

Power systems are planed and operated according to the optimization of the available resources. Traditionally these tasks were mostly undertaken in a centralized way which is no longer adequate in a competitive environment. Demand response can play a very relevant role in this context but adequate tools to negotiate this kind of resources are required. This paper presents an approach to deal with these issues, by using a multi-agent simulator able to model demand side players and simulate their strategic behavior. The paper includes an illustrative case study that considers an incident situation. The distribution company is able to reduce load curtailment due to load flexibility contracts previously established with demand side players.

Data mining applications in power systems - case-studies and future trends

Presently power system operation produces huge volumes of data that is still treated in a very limited way. Knowledge discovery and machine learning can make use of these data resulting in relevant knowledge with very positive impact. In the context of competitive electricity markets these data is of even higher value making clear the trend to make data mining techniques application in power systems more relevant. This paper presents two cases based on real data, showing the importance of the use of data mining for supporting demand response and for supporting player strategic behavior.

Distributed energy resources management with cyber-physical SCADA in the context of future smart grids

In the energy management of a small power system, the scheduling of the generation units is a crucial problem for which adequate methodologies can maximize the performance of the energy supply. This paper proposes an innovative methodology for distributed energy resources management. The optimal operation of distributed generation, demand response and storage resources is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The paper deals with a vision for the grids of the future, focusing on conceptual and operational aspects of electrical grids characterized by an intensive penetration of DG, in the scope of competitive environments and using artificial intelligence methodologies to attain the envisaged goals. These concepts are implemented in a computational framework which includes both grid and market simulation.