A mudan??a de pol??tica na crise do Estado de Bem Estar Social: uma an??lise comparada

O artigo faz uma identifica????o das caracter??sticas da policy change que vem sendo assumidas nos ??ltimos anos, nos diversos setores da interven????o p??blica, com base no exame das mudan??as das pol??ticas nas principais democracias contempor??neas integrantes da OCDE. Focaliza a tend??ncia, que parece ser mais real e de longo prazo, expressa na passagem do Estado social para o Estado gerencial.

Diverse effects of renal denervation on ventricular hypertrophy and blood pressure in DOCA-salt hypertensive rats

Cardiac hypertrophy that accompanies hypertension seems to be a phenomenon of multifactorial origin whose development does not seem to depend on an increased pressure load alone, but also on local growth factors and cardioadrenergic activity. The aim of the present study was to determine if sympathetic renal denervation and its effects on arterial pressure level can prevent cardiac hypertrophy and if it can also delay the onset and attenuate the severity of deoxycorticosterone acetate (DOCA)-salt hypertension. DOCA-salt treatment was initiated in rats seven days after uninephrectomy and contralateral renal denervation or sham renal denervation. DOCA (15 mg/kg, sc) or vehicle (soybean oil, 0.25 ml per animal) was administered twice a week for two weeks. Rats treated with DOCA or vehicle (control) were provided drinking water containing 1% NaCl and 0.03% KCl. At the end of the treatment period, mean arterial pressure (MAP) and heart rate measurements were made in conscious animals. Under ether anesthesia, the heart was removed and the right and left ventricles (including the septum) were separated and weighed. DOCA-salt treatment produced a significant increase in left ventricular weight/body weight (LVW/BW) ratio (2.44 ± 0.09 mg/g) and right ventricular weight/body weight (RVW/BW) ratio (0.53 ± 0.01 mg/g) compared to control (1.92 ± 0.04 and 0.48 ± 0.01 mg/g, respectively) rats. MAP was significantly higher (39%) in DOCA-salt rats. Renal denervation prevented (P>0.05) the development of hypertension in DOCA-salt rats but did not prevent the increase in LVW/BW (2.27 ± 0.03 mg/g) and RVW/BW (0.52 ± 0.01 mg/g). We have shown that the increase in arterial pressure level is not responsible for cardiac hypertrophy, which may be more related to other events associated with DOCA-salt hypertension, such as an increase in cardiac sympathetic activity.

Does corruption inhibit foreign direct investment?

Globalization creates new opportunities for firms to invest abroad and many economies are making active efforts to attract Foreign Direct Investment (FDI) in order to promote economic growth. Decisions to invest abroad depend on a complex set of factors, but the least corrupt countries may attract more foreign direct investment because they provide a more favorable climate for investors. In this paper we investigate the impact of corruption on FDI inflows in 73 countries, over the period 1998-2008. Our results suggest that countries where corruption is lower, the FDI inflows are greater, and so controlling corruption may be an important strategy for increase FDI inflows.

Criteria for ERP selection using an AHP approach

Information systems are a foundation key element of modern organizations. Quite often, chief executive officers and managers have to decide about the acquisition of new software solution based in an appropriated set of criteria. Analytic Hierarchy Process (AHP) is one technique used to support that kind of decisions. This paper proposes the application of AHP method to the selection of ERP (Enterprise Resource Planning) systems, identifying the set of criteria to be used. A set of criteria was retrieved from the scientific literature and validated through a survey-based approach.

Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

A model for the evaluation of data quality in health unit website

This article presents a research work, the goal of which was to achieve a model for the evaluation of data quality in institutional websites of health units in a broad and balanced way. We have carried out a literature review of the available approaches for the evaluation of website content quality, in order to identify the most recurrent dimensions and the attributes, and we have also carried out a Delphi method process with experts in order to reach an adequate set of attributes and their respective weights for the measurement of content quality. The results obtained revealed a high level of consensus among the experts who participated in the Delphi process. On the other hand, the different statistical analysis and techniques implemented are robust and attach confidence to our results and consequent model obtained.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Towards a Catalog of Usability Smells

This paper presents a catalog of smells in the context of interactive applications. These so-called usability smells are indicators of poor design on an application’s user interface, with the potential to hinder not only its usability but also its maintenance and evolution. To eliminate such usability smells we discuss a set of program/usability refactorings. In order to validate the presented usability smells catalog, and the associated refactorings, we present a preliminary empirical study with software developers in the context of a real open source hospital management application. Moreover, a tool that computes graphical user interface behavior models, giving the applications’ source code, is used to automatically detect usability smells at the model level.

Simple thermodynamics of jet engines

We use the first and second laws of thermodynamics to analyze the behavior of an ideal jet engine. Simple analytical expressions for the thermal efficiency, the overall efficiency, and the reduced thrust are derived. We show that the thermal efficiency depends only on the compression ratio r and on the velocity of the aircraft. The other two performance measures depend also on the ratio of the temperature at the turbine to the inlet temperature in the engine, T-3/T-i. An analysis of these expressions shows that it is not possible to choose an optimal set of values of r and T-3/T-i that maximize both the overall efficiency and thrust. We study how irreversibilities in the compressor and the turbine decrease the overall efficiency of jet engines and show that this effect is more pronounced for smaller T-3/T-i.

Dynamic equilibrium through reinforcement learning

Reinforcement Learning is an area of Machine Learning that deals with how an agent should take actions in an environment such as to maximize the notion of accumulated reward. This type of learning is inspired by the way humans learn and has led to the creation of various algorithms for reinforcement learning. These algorithms focus on the way in which an agent’s behaviour can be improved, assuming independence as to their surroundings. The current work studies the application of reinforcement learning methods to solve the inverted pendulum problem. The importance of the variability of the environment (factors that are external to the agent) on the execution of reinforcement learning agents is studied by using a model that seeks to obtain equilibrium (stability) through dynamism – a Cart-Pole system or inverted pendulum. We sought to improve the behaviour of the autonomous agents by changing the information passed to them, while maintaining the agent’s internal parameters constant (learning rate, discount factors, decay rate, etc.), instead of the classical approach of tuning the agent’s internal parameters. The influence of changes on the state set and the action set on an agent’s capability to solve the Cart-pole problem was studied. We have studied typical behaviour of reinforcement learning agents applied to the classic BOXES model and a new form of characterizing the environment was proposed using the notion of convergence towards a reference value. We demonstrate the gain in performance of this new method applied to a Q-Learning agent.

Sistema de apoio à decisão para a classificação de risco em projectos de tecnologias de informação

O trabalho que a seguir se apresenta tem como objectivo descrever a criação de um modelo que sirva de suporte a um sistema de apoio à decisão sobre o risco inerente à execução de projectos na área das Tecnologias de Informação (TI) recorrendo a técnicas de mineração de dados. Durante o ciclo de vida de um projecto, existem inúmeros factores que contribuem para o seu sucesso ou insucesso. A responsabilidade de monitorizar, antever e mitigar esses factores recai sobre o Gestor de Projecto. A gestão de projectos é uma tarefa difícil e dispendiosa, consome muitos recursos, depende de numerosas variáveis e, muitas vezes, até da própria experiência do Gestor de Projecto. Ao ser confrontado com as previsões de duração e de esforço para a execução de uma determinada tarefa, o Gestor de Projecto, exceptuando a sua percepção e intuição pessoal, não tem um modo objectivo de medir a plausibilidade dos valores que lhe são apresentados pelo eventual executor da tarefa. As referidas previsões são fundamentais para a organização, pois sobre elas são tomadas as decisões de planeamento global estratégico corporativo, de execução, de adiamento, de cancelamento, de adjudicação, de renegociação de âmbito, de adjudicação externa, entre outros. Esta propensão para o desvio, quando detectada numa fase inicial, pode ajudar a gerir melhor o risco associado à Gestão de Projectos. O sucesso de cada projecto terminado foi qualificado tendo em conta a ponderação de três factores: o desvio ao orçamentado, o desvio ao planeado e o desvio ao especificado. Analisando os projectos decorridos, e correlacionando alguns dos seus atributos com o seu grau de sucesso o modelo classifica, qualitativamente, um novo projecto quanto ao seu risco. Neste contexto o risco representa o grau de afastamento do projecto ao sucesso. Recorrendo a algoritmos de mineração de dados, tais como, árvores de classificação e redes neuronais, descreve-se o desenvolvimento de um modelo que suporta um sistema de apoio à decisão baseado na classificação de novos projectos. Os modelos são o resultado de um extensivo conjunto de testes de validação onde se procuram e refinam os indicadores que melhor caracterizam os atributos de um projecto e que mais influenciam o risco. Como suporte tecnológico para o desenvolvimento e teste foi utilizada a ferramenta Weka 3. Uma boa utilização do modelo proposto possibilitará a criação de planos de contingência mais detalhados e uma gestão mais próxima para projectos que apresentem uma maior propensão para o risco. Assim, o resultado final pretende constituir mais uma ferramenta à disposição do Gestor de Projecto.

Utilização racional de energia eléctrica no município de Vila Franca de Xira: casos de estudo

O objectivo pretendido alcançar é o de obter uma redução nos consumos de energia eléctrica do Município de Vila Franca de Xira, recorrendo à URE. Esta URE consiste num conjunto de acções e/ou medidas e/ou procedimentos e/ou equipamentos cuja aplicação tem como fim, o de potenciar uma utilização e uma gestão mais racional e rentável da energia - daí se podendo dizer, cada vez mais, que a mesma é um factor essencial de economia energética, logo, de redução de custos. A aplicação destas acções e/ou medidas e/ou procedimentos e/ou equipamentos deverá, por isso, ser extensível aos Municípios, com o fim de fazer reduzir uma factura energética de grande peso e significado, a qual, em tempos que são de profunda crise económica, pode tornar problemático ou até mesmo hipotecar, o respectivo futuro. Assim e se por um lado existe no Município um conjunto alargado de situações estabelecidas sem critérios de racionabilidade energética e ás quais, todavia, é já possível fazer aplicar essas acções e/ou medidas e/ou procedimentos e/ou equipamentos de URE, por outro lado, é daí garantido que se poderá alcançar a pretendida redução dos consumos energéticos do Município, sempre assegurando e mantendo o conforto e a produtividade das actividades dependentes dessa energia. Com esse objectivo e partindo da análise de um conjunto de instalações e/ou equipamentos já existentes ou com possibilidades de virem a ser estabelecidas/os pelo Município, é pretendido definir, estudar e classificar, um conjunto de dados que tendam a desenvolver, potenciar e justificar a decisão da sua aplicação. Um conjunto alargado de exemplos práticos ou Casos de Estudo serão desenvolvidos, tentando chegar a conclusões sobre a viabilidade económica das soluções apresentadas e, daí, da decisão da oportunidade da execução do conjunto de trabalhos inerentes à aplicação desse tipo de situação.

Checklist cirúrgica: contributo para uma intervenção na área da segurança do doente

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especuialização: Políticas de administração e gestão de serviços de saúde.

Tilted boxes on inclined planes

We propose the study of a box placed on an inclined plane, with an initial tilt with respect to the plane. This is a paradigmatic example of the role played by friction as a link between translational and rotational motion. This example has two advantages over the usual example of a sphere (or cylinder) rolling down an inclined plane. First, it provides a good model for a much greater variety of "real-life" situations. Second, it exhibits a much richer structure in parameter space, even when the box starts from rest. (C) 2000 American Association of Physics Teachers.