Modelação de governo electrónico para países emergentes: O caso de São Tomé e Príncipe

Tese de Doutoramento em Tecnologias e Sistemas de Informação

Determinação da medida da pena privativa de liberdade: um olhar crítico a partir do direito anglo-saxónico

Tese de Doutoramento em Ciências Jurídicas - Área de Ciências Jurídicas Públicas

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.

Una explicación del conflicto social sobre energía eólica en la comarca de la Terra Alta en Cataluña

El estudio investiga las razones que explican un conflicto sobre la instalación de parques eólicos en Terra Alta, una comarca rural de Cataluña. Identificamos tres razones principales. Primero, y de acuerdo con el marco conceptual de ecología política, el conflicto eólico forma parte de un conflicto más generalizado sobre la ‘macro-concentración’ de instalaciones energéticas en el sur de Cataluña que generan energía y beneficios económicos principalmente para el centro del desarrollo económico catalán. Segundo, el impacto paisajístico de los proyectos eólicos choca con iniciativas locales que impulsan el paisaje como un activo valioso capaz de sustentar la vida en la comarca. Por último, desequilibrios de poder en el sistema formal de toma de decisiones sobre parques eólicos impiden la inclusión de valores locales como criterios en el proceso de toma de decisiones y eso también genera conflicto. Para un desarrollo sostenible de energía eólica, la importancia del potencial eólico como criterio principal de localización debe ser reevaluada, y la negociación de la distribución de beneficios debe hacerse en la forma más abierta posible.

Information systems for water resources management improvement in developing countries

Water resources management, as also water service provision projects in developing countries have difficulties to take adequate decisions due to scarce reliable information, and a lack of proper information managing. Some appropriate tools need to be developed in order to improve decision making to improve water management and access of the poorest, through the design of Decision Support Systems (DSS). On the one side, a DSS for developing co-operation projects on water access improvement has been developed. Such a tool has specific context constrains (structure of the system, software requirements) and needs (Logical Framework Approach monitoring, organizational-learning, accountability and evaluation) that shall be considered for its design. Key aspects for its successful implementation have appeared to be a participatory design of the system and support of the managerial positions at the inception phase. A case study in Tanzania was conducted, together with the Spanish NGO ONGAWA – Ingeniería para el Desarrollo. On the other side, DSS are required also to improve decision making on water management resources in order to achieve a sustainable development that not only improves the living conditions of the population in developing countries, but that also does not hinder opportunities of the poorest on those context. A DSS made to fulfil these requirements shall be using information from water resources modelling, as also on the environment and the social context. Through the research, a case study has been conducted in the Central Rift Valley of Ethiopia, an endhorreic basin 160 km south of Addis Ababa. There, water has been modelled using ArcSWAT, a physically based model which can assess the impact of land management practices on large complex watersheds with varying soils, land use and management conditions over long periods of time. Moreover, governance on water and environment as also the socioeconomic context have been studied.

Cardiopulmonary support and extracorporeal membrane oxygenation for cardiac assist.

BACKGROUND: Use of cardiopulmonary bypass for emergency resuscitation is not new. In fact, John Gibbon proposed this concept for the treatment of severe pulmonary embolism in 1937. Significant progress has been made since, and two main concepts for cardiac assist based on cardiopulmonary bypass have emerged: cardiopulmonary support (CPS) and extracorporeal membrane oxygenation (ECMO). The objective of this review is to summarize the state of the art in these two technologies. METHODS: Configuration of CPS is now fairly standard. A mobile cart with relatively large wheels allowing for easy transportation carries a centrifugal pump, a back-up battery with a charger, an oxygen cylinder, and a small heating system. Percutaneous cannulation, pump-driven venous return, rapid availability, and transportability are the main characteristics of a CPS system. Cardiocirculatory arrest is a major predictor of mortality despite the use of CPS. In contrast, CPS appears to be a powerful tool for patients in cardiogenic shock before cardiocirculatory arrest, requiring some type of therapeutic procedures, especially repair of anatomically correctable problems or bridging to other mechanical circulatory support systems such as ventricular assist devices. CPS is in general not suitable for long-term applications because of the small-bore cannulas, resulting in significant pressure gradients and eventually hemolysis. RESULTS: In contrast, ECMO can be designed for longer-term circulatory support. This requires large-bore cannulas and specifically designed oxygenators. The latter are either plasma leakage resistent (true membranes) or relatively thrombo-resistant (heparin coated). Both technologies require oxygenator changeovers although the main reason for this is different (clotting for the former, plasma leakage for the latter). Likewise, the tubing within a roller pump has to be displaced and centrifugal pump heads have to be replaced over time. ECMO is certainly the first choice for a circulatory support system in the neonatal and pediatric age groups, where the other assist systems are too bulky. ECMO is also indicated for patients improving on CPS. Septic conditions are, in general, considered as contraindications for ECMO. CONCLUSIONS: Ease of availability and moderate cost of cardiopulmonary bypass-based cardiac support technologies have to be balanced against the significant immobilization of human resources, which is required to make them successful.

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Adaptive business intelligence for an open negotiation environment

Engineering of negotiation model allows to develop effective heuristic for business intelligence. Digital ecosystems demand open negotiation models. To define in advance effective heuristics is not compliant with the requirement of openness. The new challenge is to develop business intelligence in advance exploiting an adaptive approach. The idea is to learn business strategy once new negotiation model rise in the e-market arena. In this paper we present how recommendation technology may be deployed in an open negotiation environment where the interaction protocol models are not known in advance. The solution we propose is delivered as part of the ONE Platform, open source software that implements a fully distributed open environment for business negotiation

A Negotiation Style Recommender Based on Computational Ecology in Open Negotiation Environments

The system described herein represents the first example of a recommender system in digital ecosystems where agents negotiate services on behalf of small companies. The small companies compete not only with price or quality, but with a wider service-by-service composition by subcontracting with other companies. The final result of these offerings depends on negotiations at the scale of millions of small companies. This scale requires new platforms for supporting digital business ecosystems, as well as related services like open-id, trust management, monitors and recommenders. This is done in the Open Negotiation Environment (ONE), which is an open-source platform that allows agents, on behalf of small companies, to negotiate and use the ecosystem services, and enables the development of new agent technologies. The methods and tools of cyber engineering are necessary to build up Open Negotiation Environments that are stable, a basic condition for predictable business and reliable business environments. Aiming to build stable digital business ecosystems by means of improved collective intelligence, we introduce a model of negotiation style dynamics from the point of view of computational ecology. This model inspires an ecosystem monitor as well as a novel negotiation style recommender. The ecosystem monitor provides hints to the negotiation style recommender to achieve greater stability of an open negotiation environment in a digital business ecosystem. The greater stability provides the small companies with higher predictability, and therefore better business results. The negotiation style recommender is implemented with a simulated annealing algorithm at a constant temperature, and its impact is shown by applying it to a real case of an open negotiation environment populated by Italian companies

The use of expert systems on the differential diagnosis of urinary incontinence

The differential diagnosis of urinary incontinence classes is sometimes difficult to establish. As a rule, only the results of urodynamic testing allow an accurate diagnosis. However, this exam is not always feasible, because it requires special equipment, and also trained personnel to lead and interpret the exam. Some expert systems have been developed to assist health professionals in this field. Therefore, the aims of this paper are to present the definition of Artificial Intelligence; to explain what Expert System and System for Decision Support are and its application in the field of health and to discuss some expert systems for differential diagnosis of urinary incontinence. It is concluded that expert systems may be useful not only for teaching purposes, but also as decision support in daily clinical practice. Despite this, for several reasons, health professionals usually hesitate to use the computer expert system to support their decision making process.

Computerized advice on drug dosage to improve prescribing practice.

BACKGROUND: Maintaining therapeutic concentrations of drugs with a narrow therapeutic window is a complex task. Several computer systems have been designed to help doctors determine optimum drug dosage. Significant improvements in health care could be achieved if computer advice improved health outcomes and could be implemented in routine practice in a cost effective fashion. This is an updated version of an earlier Cochrane systematic review, by Walton et al, published in 2001. OBJECTIVES: To assess whether computerised advice on drug dosage has beneficial effects on the process or outcome of health care. SEARCH STRATEGY: We searched the Cochrane Effective Practice and Organisation of Care Group specialized register (June 1996 to December 2006), MEDLINE (1966 to December 2006), EMBASE (1980 to December 2006), hand searched the journal Therapeutic Drug Monitoring (1979 to March 2007) and the Journal of the American Medical Informatics Association (1996 to March 2007) as well as reference lists from primary articles. SELECTION CRITERIA: Randomized controlled trials, controlled trials, controlled before and after studies and interrupted time series analyses of computerized advice on drug dosage were included. The participants were health professionals responsible for patient care. The outcomes were: any objectively measured change in the behaviour of the health care provider (such as changes in the dose of drug used); any change in the health of patients resulting from computerized advice (such as adverse reactions to drugs). DATA COLLECTION AND ANALYSIS: Two reviewers independently extracted data and assessed study quality. MAIN RESULTS: Twenty-six comparisons (23 articles) were included (as compared to fifteen comparisons in the original review) including a wide range of drugs in inpatient and outpatient settings. Interventions usually targeted doctors although some studies attempted to influence prescriptions by pharmacists and nurses. Although all studies used reliable outcome measures, their quality was generally low. Computerized advice for drug dosage gave significant benefits by:1.increasing the initial dose (standardised mean difference 1.12, 95% CI 0.33 to 1.92)2.increasing serum concentrations (standradised mean difference 1.12, 95% CI 0.43 to 1.82)3.reducing the time to therapeutic stabilisation (standardised mean difference -0.55, 95%CI -1.03 to -0.08)4.reducing the risk of toxic drug level (rate ratio 0.45, 95% CI 0.30 to 0.70)5.reducing the length of hospital stay (standardised mean difference -0.35, 95% CI -0.52 to -0.17). AUTHORS' CONCLUSIONS: This review suggests that computerized advice for drug dosage has some benefits: it increased the initial dose of drug, increased serum drug concentrations and led to a more rapid therapeutic control. It also reduced the risk of toxic drug levels and the length of time spent in the hospital. However, it had no effect on adverse reactions. In addition, there was no evidence to suggest that some decision support technical features (such as its integration into a computer physician order entry system) or aspects of organization of care (such as the setting) could optimise the effect of computerised advice.

Development and validation of a clinical decision rule for the diagnosis of influenza.

INTRODUCTION: A clinical decision rule to improve the accuracy of a diagnosis of influenza could help clinicians avoid unnecessary use of diagnostic tests and treatments. Our objective was to develop and validate a simple clinical decision rule for diagnosis of influenza. METHODS: We combined data from 2 studies of influenza diagnosis in adult outpatients with suspected influenza: one set in California and one in Switzerland. Patients in both studies underwent a structured history and physical examination and had a reference standard test for influenza (polymerase chain reaction or culture). We randomly divided the dataset into derivation and validation groups and then evaluated simple heuristics and decision rules from previous studies and 3 rules based on our own multivariate analysis. Cutpoints for stratification of risk groups in each model were determined using the derivation group before evaluating them in the validation group. For each decision rule, the positive predictive value and likelihood ratio for influenza in low-, moderate-, and high-risk groups, and the percentage of patients allocated to each risk group, were reported. RESULTS: The simple heuristics (fever and cough; fever, cough, and acute onset) were helpful when positive but not when negative. The most useful and accurate clinical rule assigned 2 points for fever plus cough, 2 points for myalgias, and 1 point each for duration <48 hours and chills or sweats. The risk of influenza was 8% for 0 to 2 points, 30% for 3 points, and 59% for 4 to 6 points; the rule performed similarly in derivation and validation groups. Approximately two-thirds of patients fell into the low- or high-risk group and would not require further diagnostic testing. CONCLUSION: A simple, valid clinical rule can be used to guide point-of-care testing and empiric therapy for patients with suspected influenza.

Diabétologie [Diabetes].

The new recommendations on the pharmacological treatment of type 2 diabetes have introduced two important changes. The first is to have common strategies between European and American diabetes societies. The second, which is certainly the most significant, is to develop a patient centred approach suggesting therapies that take into account the patient's preferences and use of decision support tools. The individual approach integrates six factors: the capacity and motivation of the patient to manage his illness and its treatment, the risks of hypoglycemia, the life expectancy, the presence of co-morbidities and vascular complications, as well as the financial resources of the patient and the healthcare system. Treatment guidelines for cardiovascular risk reduction in diabetic remains the last point to develop.

Patients âgés admis aux urgences suite à une chute: que faire [Older people admitted to the emergency department after a fall: what to do?].

Falls in older people are frequent. Falls may lead to serious injuries and are associated with greater morbidity, mortality, and reduced overall functioning in the older population. Evidences exist regarding the beneficial effects of fall prevention programs. However, these interventions are rarely implemented in our health system. Older people admitted to the emergency department after a fall should get careful attention in order to initiate specific interventions to prevent new falls. This article provides a clinical assessment strategy to evaluate older persons after a fall and proposes an algorithm for discharge planning decision.

Shared decision making development in Switzerland: room for improvement!

In Switzerland there is a strong movement at a national policy level towards strengthening patient rights and patient involvement in health care decisions. Yet, there is no national programme promoting shared decision making. First decision support tools (prenatal diagnosis and screening) for the counselling process have been developed and implemented. Although Swiss doctors acknowledge that shared decision making is important, hierarchical structures and asymmetric physician-patient relationships are still prevailing. The last years have seen some promising activities regarding the training of medical students and the development of patient support programmes. Swiss direct democracy and the habit of consensual decision making and citizen involvement in general may provide a fertile ground for SDM development in the primary care setting.