Contributo das tecnologias de informação na gestão do regime terapêutico no diabético

A diabetes é a doença do seculo XXI, atinge mais de um milhão de portugueses cada vez mais jovens em idades trabalhadoras, e já custa mais de 1% do PIB, além dos enormes danos que pode causar às pessoas e à sociedade. Segundo o Relatório Anual do Observatório Nacional da Diabetes, em 2011, cerca de um quarto da população portuguesa integrada no escalão etário dos 60 aos 79 tem Diabetes. Um estudo realizado pelo Lisbon Internet and Networks Institute (LINI), em 2010, diz-nos que “a internet é um recurso para a informação e educação para a saúde”. Em 2010 49% dos lares portugueses possuem acesso à internet e 44% da população é utilizadora (acréscimo significativo relativamente aos 29% em 2003). Destes, dois terços têm entre os 15 e os 24 anos. Os idosos representam 1,6%, dos quais os reformados e pensionistas representam 5%, as domésticas representam 11% e os trabalhadores manuais 22%, sendo estes os menos utilizadores. Um terço da restante população procura informação sobre saúde semanalmente, cerca de 16%. Face à atual conjuntura económica, com restrições orçamentais, nomeadamente na área da saúde, devem-se encontrar meios para prevenir e lidar com a Diabetes numa perspetiva de custo-benefício, isto porque a Diabetes pode reduzir as oportunidades de emprego e de aprendizagem. O atual diretor da Organização para a Cooperação e Desenvolvimento Económico (OCDE) Yyes Leterme diz que “Prevenir e tratar a Diabetes e as suas complicações custa cerca de 90 mil milhões de euros anualmente na Europa”. Atualmente, não é muito utilizado nem explorado o potencial das tecnologias de informação e as ferramentas web ao serviço da saúde, quer por profissionais de saúde, quer por utentes na gestão ao regime terapêutico na doença crónica, mais precisamente na gestão adequada da Diabetes. Potenciar uma visão integrada dos diferentes recursos de comunicação e a sua utilização conjugada com a promoção da saúde e prevenção da doença poderá enfatizar em termos de eficácia e eficiência a minimização de recursos das organizações de saúde e promover a gestão adequada da Diabetes. Tendo por base esta problemática, este estudo pretende abordar e refletir o possível contributo das tecnologias de informação e das ferramentas web na gestão adequada ao regime terapêutico da Diabetes.

Modified Particle Swarm Optimization Applied to Integrated Demand Response and DG Resources Scheduling

The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

Dispatch of distributed Energy Resources to Provide Energy and Reserve in Smart Grids using a Particle Swarm Optimization Approach

The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. 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 optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.

Integration in MASCEM of the Joint Dispatch of Energy and Reserves Provided by Generation and Demand Resources

The provision of reserves in power systems is of great importance in what concerns keeping an adequate and acceptable level of security and reliability. This need for reserves and the way they are defined and dispatched gain increasing importance in the present and future context of smart grids and electricity markets due to their inherent competitive environment. This paper concerns a methodology proposed by the authors, which aims to jointly and optimally dispatch both generation and demand response resources to provide the amounts of reserve required for the system operation. Virtual Power Players are especially important for the aggregation of small size demand response and generation resources. The proposed methodology has been implemented in MASCEM, a multi agent system also developed at the authors’ research center for the simulation of electricity markets.

Constrained Consumption Shifting Management in the Distributed Energy Resources Scheduling Considering Demand Response

Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods.

Cost Allocation Model for Distribution Networks Considering High Penetration of Distributed Energy Resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitiveenvironment of electricity markets impose the use of new approaches in several domains. The networkcost allocation, traditionally used in transmission networks, should be adapted and used in the distribu-tion networks considering the specifications of the connected resources. The main goal is to develop afairer methodology trying to distribute the distribution network use costs to all players which are usingthe network in each period. In this paper, a model considering different type of costs (fixed, losses, andcongestion costs) is proposed comprising the use of a large set of DER, namely distributed generation(DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehi-cles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). Theproposed model includes three distinct phases of operation. The first phase of the model consists in aneconomic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen’s andBialek’s tracing algorithms are used and compared to evaluate the impact of each resource in the net-work. Finally, the MW-mile method is used in the third phase of the proposed model. A distributionnetwork of 33 buses with large penetration of DER is used to illustrate the application of the proposedmodel.

Distributed energy resources scheduling considering real-time resources forecast

Energy resource scheduling is becoming increasingly important, such as the use of more distributed generators and electric vehicles connected to the distribution network. This paper proposes a methodology to be used by Virtual Power Players (VPPs), regarding the energy resource scheduling in smart grids and considering day-ahead, hour-ahead and realtime time horizons. This method considers that energy resources are managed by a VPP which establishes contracts with their owners. The full AC power flow calculation included in the model takes into account network constraints. In this paper, distribution function errors are used to simulate variations between time horizons, and to measure the performance of the proposed methodology. A 33-bus distribution network with large number of distributed resources is used.

A Communication and Resources Management Scheme to Support the Smart Grid Integration of Multiplayers Access to Resources Information

The increasing and intensive integration of distributed energy resources into distribution systems requires adequate methodologies to ensure a secure operation according to the smart grid paradigm. In this context, SCADA (Supervisory Control and Data Acquisition) systems are an essential infrastructure. This paper presents a conceptual design of a communication and resources management scheme based on an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). The methodology is used to support the energy resource management considering all the involved costs, power flows, and electricity prices leading to the network reconfiguration. The methodology also addresses the definition of the information access permissions of each player to each resource. The paper includes a 33-bus network used in a case study that considers an intensive use of distributed energy resources in five distinct implemented operation contexts.

Scalable and Efficient Configuration of TimeDivision Multiplexed Resources

Consumer-electronics systems are becoming increasingly complex as the number of integrated applications is growing. Some of these applications have real-time requirements, while other non-real-time applications only require good average performance. For cost-efficient design, contemporary platforms feature an increasing number of cores that share resources, such as memories and interconnects. However, resource sharing causes contention that must be resolved by a resource arbiter, such as Time-Division Multiplexing. A key challenge is to configure this arbiter to satisfy the bandwidth and latency requirements of the real-time applications, while maximizing the slack capacity to improve performance of their non-real-time counterparts. As this configuration problem is NP-hard, a sophisticated automated configuration method is required to avoid negatively impacting design time. The main contributions of this article are: 1) An optimal approach that takes an existing integer linear programming (ILP) model addressing the problem and wraps it in a branch-and-price framework to improve scalability. 2) A faster heuristic algorithm that typically provides near-optimal solutions. 3) An experimental evaluation that quantitatively compares the branch-and-price approach to the previously formulated ILP model and the proposed heuristic. 4) A case study of an HD video and graphics processing system that demonstrates the practical applicability of the approach.

Is mental practice an effective adjunct therapeutic strategy for upper limb motor restoration after stroke? A systematic review and meta- analysis

Stroke is one of the most common conditions requiring rehabilitation, and its motor impairments are a major cause of permanent disability. Hemiparesis is observed by 80% of the patients after acute stroke. Neuroimaging studies showed that real and imagined movements have similarities regarding brain activation, supplying evidence that those similarities are based on the same process. Within this context, the combination of mental practice (MP) with physical and occupational therapy appears to be a natural complement based on neurorehabilitation concepts. Our study seeks to investigate if MP for stroke rehabilitation of upper limbs is an effective adjunct therapy. PubMed (Medline), ISI knowledge (Institute for Scientific Information) and SciELO (Scientific Electronic Library) were terminated on 20 February 2015. Data were collected on variables as follows: sample size, type of supervision, configuration of mental practice, setting the physical practice (intensity, number of sets and repetitions, duration of contractions, rest interval between sets, weekly and total duration), measures of sensorimotor deficits used in the main studies and significant results. Random effects models were used that take into account the variance within and between studies. Seven articles were selected. As there was no statistically significant difference between the two groups (MP vs control), showed a - 0.6 (95% CI: -1.27 to 0.04), for upper limb motor restoration after stroke. The present meta-analysis concluded that MP is not effective as adjunct therapeutic strategy for upper limb motor restoration after stroke.

Potential Therapeutic Effects of Physical Exercise for Bipolar Disorder

Cognitive deficits are observed in a variety of domains in patients with bipolar disorder (BD). These deficits are attributed to neurobiological, functional and structural brain factors, particularly in prefrontal cortex. Furthermore, cortical alterations in each phase (mania/hypomania, euthymia and depression) are also present. A growing basis of evidence supports aerobic exercise as an alternative treatment method for BD symptoms. Its benefits for physical health in healthy subjects and some psychiatric disorders are fairly established; however evidence directly addressed to BD is scant. Lack of methodological consistency, mainly related to exercise, makes it difficult accuracy and extrapolation of the results. Nevertheless, mechanisms related to BD physiopathology, such as hormonal and neurotransmitters alterations and mainly related to brain-derived neurotrophic factors (BDNF) can be explored. BDNF, specially, have a large influence on brain ability and its gene expression is highly responsive to aerobic exercise. Moreover, aerobic exercise trough BDNF may induce chronic stress suppression, commonly observed in patients with BD, and reduce deleterious effects caused by allostatic loads. Therefore, it is prudent to propose that aerobic exercise plays an important role in BD physiopathological mechanisms and it is a new way for the treatment for this and others psychiatric disorders.