Analysis of Systems with Backlash and Impacts through the Describing Function

This paper analyses the dynamical properties of systems with backlash and impact phenomena based on the describing function method. The dynamics is illustrated using the Nyquist and Bode plots and the results are compared with those of standard models.

Adrenal function in 23 children with paracoccidioidomycosis

Adrenal involvement by Paracoccidioides brasiliensis was described at necropsies and in many clinical studies, but only in adults. Therefore, the aim of this study was to evaluate adrenal function in children with paracoccidioidomycosis. Twenty-three children with the systemic form of paracoccidioidomycosis were evaluated and divided in two Groups: Group A (n = 8) included children before treatment and Group B (n = 15) children after the end of treatment. Plasma cortisol (basal and after ACTH test), ACTH, renin activity, aldosterone, sodium and potassium were measured. They were within normal range in all cases, except for renin activity and aldosterone, which were elevated in some cases. Group A patients showed basal and post-ACTH cortisol levels significantly greater than Group B patients. The results showed that adrenal function was not compromised in these children with paracoccidioidomycosis.

Decision Support for Energy Contracts Negotiation with Game Theory and Adaptive Learning

This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

Six thinking hats: A novel metalearner for intelligent decision support in electricity markets

The energy sector has suffered a significant restructuring that has increased the complexity in electricity market players' interactions. The complexity that these changes brought requires the creation of decision support tools to facilitate the study and understanding of these markets. The Multiagent Simulator of Competitive Electricity Markets (MASCEM) arose in this context, providing a simulation framework for deregulated electricity markets. The Adaptive Learning strategic Bidding System (ALBidS) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM, ALBidS considers several different strategic methodologies based on highly distinct approaches. Six Thinking Hats (STH) is a powerful technique used to look at decisions from different perspectives, forcing the thinker to move outside its usual way of thinking. This paper aims to complement the ALBidS strategies by combining them and taking advantage of their different perspectives through the use of the STH group decision technique. The combination of ALBidS' strategies is performed through the application of a genetic algorithm, resulting in an evolutionary learning approach.

Municipal solid waste management system: decision support through systems analysis

Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental Engineering

Zero-Time Kidney Histology Predicts Early Graft Function

Our purposes are to determine the impact of histological factors observed in zero-time biopsies on early post transplant kidney allograft function. We specifically want to compare the semi-quantitative Banff Classification of zero time biopsies with quantification of % cortical area fibrosis. Sixty three zero-time deceased donor allograft biopsies were retrospectively semiquantitatively scored using Banff classification. By adding the individual chronic parameters a Banff Chronic Sum (BCS) Score was generated. Percentage of cortical area Picro Sirius Red (%PSR) staining was assessed and calculated with a computer program. A negative linear regression between %PSR/ GFR at 3 year post-transplantation was established (Y=62.08 +-4.6412X; p=0.022). A significant negative correlation between arteriolar hyalinosis (rho=-0.375; p=0.005), chronic interstitial (rho=0.296; p=0.02) , chronic tubular ( rho=0.276; p=0.04) , chronic vascular (rho= -0.360;P=0.007), BCS (rho=-0.413; p=0.002) and GFR at 3 years were found. However, no correlation was found between % PSR, Ci, Ct or BCS. In multivariate linear regression the negative predictive factors of 3 years GFR were: BCS in histological model; donor kidney age, recipient age and black race in clinical model. The BCS seems a good and easy to perform tool, available to every pathologist, with significant predictive short-term value. The %PSR predicts short term kidney function in univariate study and involves extra-routine and expensive-time work. We think that %PSR must be regarded as a research instrument.

De Novo Hypertension and Decline of Renal Function in a Young Woman with Systemic Lupus Erythematosus and Antiphospholipid Syndrome

Antiphospholipid syndrome nephropathy and lupus nephritis have similar clinical and laboratory manifestations and achieving the accuracy of diagnosis required for correct treatment frequently necessitates a kidney biopsy. We report the case of a 29-year-old woman referred to the nephrology service for de novo hypertension, decline of renal function and proteinuria. She had had systemic lupus erythematosus and antiphospholipid syndrome since the age of 21 and was taking oral anticoagulation. Two weeks later, after treatment of hypertension and achievement of adequate coagulation parameters, a percutaneous renal biopsy was performed. The biopsy revealed chronic lesions of focal cortical atrophy, arterial fibrous intimal hyperplasia and arterial thromboses, which are typical features of antiphospholipid syndrome nephropathy. We describe the clinical manifestations and histopathology of antiphospholipid syndrome nephropathy and review the literature on renal biopsy in patients receiving anticoagulation.

Adaptive Penalty and Barrier function based on Fuzzy Logic

Optimization methods have been used in many areas of knowledge, such as Engineering, Statistics, Chemistry, among others, to solve optimization problems. In many cases it is not possible to use derivative methods, due to the characteristics of the problem to be solved and/or its constraints, for example if the involved functions are non-smooth and/or their derivatives are not know. To solve this type of problems a Java based API has been implemented, which includes only derivative-free optimization methods, and that can be used to solve both constrained and unconstrained problems. For solving constrained problems, the classic Penalty and Barrier functions were included in the API. In this paper a new approach to Penalty and Barrier functions, based on Fuzzy Logic, is proposed. Two penalty functions, that impose a progressive penalization to solutions that violate the constraints, are discussed. The implemented functions impose a low penalization when the violation of the constraints is low and a heavy penalty when the violation is high. Numerical results, obtained using twenty-eight test problems, comparing the proposed Fuzzy Logic based functions to six of the classic Penalty and Barrier functions are presented. Considering the achieved results, it can be concluded that the proposed penalty functions besides being very robust also have a very good performance.

A Multiple Criteria Utility-based Approa h for the Unit Commitment with Wind Power and Pumped Storage Hydro

The integration of wind power in eletricity generation brings new challenges to unit commitment due to the random nature of wind speed. For this particular optimisation problem, wind uncertainty has been handled in practice by means of conservative stochastic scenario-based optimisation models, or through additional operating reserve settings. However, generation companies may have different attitudes towards operating costs, load curtailment, or waste of wind energy, when considering the risk caused by wind power variability. Therefore, alternative and possibly more adequate approaches should be explored. This work is divided in two main parts. Firstly we survey the main formulations presented in the literature for the integration of wind power in the unit commitment problem (UCP) and present an alternative model for the wind-thermal unit commitment. We make use of the utility theory concepts to develop a multi-criteria stochastic model. The objectives considered are the minimisation of costs, load curtailment and waste of wind energy. Those are represented by individual utility functions and aggregated in a single additive utility function. This last function is adequately linearised leading to a mixed-integer linear program (MILP) model that can be tackled by general-purpose solvers in order to find the most preferred solution. In the second part we discuss the integration of pumped-storage hydro (PSH) units in the UCP with large wind penetration. Those units can provide extra flexibility by using wind energy to pump and store water in the form of potential energy that can be generated after during peak load periods. PSH units are added to the first model, yielding a MILP model with wind-hydro-thermal coordination. Results showed that the proposed methodology is able to reflect the risk profiles of decision makers for both models. By including PSH units, the results are significantly improved.

Stenosis of the Branches of the Neopulmonary Artery after the Arterial Switch Operation: a Cardiac Magnetic Resonance Imaging Study

Background : The neonatal arterial switch operation (ASO) is now the standard of care for children born with transposition of the great arteries. Stenosis of the neopulmonary artery on long‑term follow up is a known complication. Methods : We performed a retrospective analysis of eleven patients who underwent a cardiac magnetic resonance imaging (MRI) due to echocardiographic evidence suggestive of stenosis of the neopulmonary artery or its branches (mean estimated Doppler gradient 48 mmHg, min 30 mmHg, max 70 mmHg). A comprehensive evaluation of anatomy and perfusion was done by cardiac MRI. Results : The branches of the neopulmonary artery (neo PA) showed decreased caliber in three patients unilaterally and in two patients, bilaterally. Magnetic resonance (MR) perfusion studies showed concomitant decreased flow, with discrepancy between the two lungs of 35/65% or worse, only in the three patients with unilateral obstruction, by two different MR perfusion methods. Conclusions : Cardiac MR can be used as a comprehensive non‑invasive imaging technique to diagnose stenosis of the branches of the neopulmonary after the ASO, allowing evaluation of anatomy and function of the neoPA, its branches, and the differential perfusion to each lung, thus facilitating clinical decision making.

Decision making processes based on innovation indicators: which implications for technology assessment?

Based on the report for “Project IV” unit of the PhD programme on Technology Assessment. This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Manuel Laranja (ISEG-UTL). Other members of the thesis committee are Stefan Kuhlmann (Twente University), Leonhard Hennen (Karlsruhe Institute of Technology-ITAS), Tiago Santos Pereira (Universidade de Coimbra/CES) and Cristina Sousa (FCT-UNL).

Decision-making process in radiology: the magnetic resonance example in the TA context

Based on the report for “Project IV” unit of the PhD programme on Technology Assessment (Doctoral Conference) at Universidade Nova de Lisboa (December 2011). This thesis research has the supervision of António Moniz (FCT-UNL and ITAS-KIT) and Michael Decker (Karlsruhe Institute of Technology-ITAS). Other members of the thesis committee are Carlos Alberto da Silva (University of Évora), José Maria de Albuquerque (Institute of Welding and Quality), Lotte Steuten (University of Twente), Mário Forjaz Secca (FCT-UNL) and Nelson Chibeles Martins (FCT-UNL).

Risk-based decision support system for life cycle management of industrials plants

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores