Establishment of optimal physical assets inspection frequency based on risk principles

Risk Based Inspection (RBI) is a risk methodology used as the basis for prioritizing and managing the efforts for an inspection program allowing the allocation of resources to provide a higher level of coverage on physical assets with higher risk. The main goal of RBI is to increase equipment availability while improving or maintaining the accepted level of risk. This paper presents the concept of risk, risk analysis and RBI methodology and shows an approach to determine the optimal inspection frequency for physical assets based on the potential risk and mainly on the quantification of the probability of failure. It makes use of some assumptions in a structured decision making process. The proposed methodology allows an optimization of inspection intervals deciding when the first inspection must be performed as well as the subsequent intervals of inspection. A demonstrative example is also presented to illustrate the application of the proposed methodology.

Sharing best practices in introducing and teaching ethics principles to public administration employees : research report

O projeto, financiado pelo Programa Aprendizagem ao Longo da Vida, decorreu entre 1 de agosto de 2011 e 31 de julho de 2013 e foi coordenado pelo Instituto de Administração Pública de Praga, tendo como parceiros a Escola de Economia e Direito de Berlim, a Escola Nacional de Administração Pública da Polónia e o INA, de Portugal. A coordenação portuguesa do estudo esteve a cargo da Prof. Doutora Helena Rato e da Dra. Matilde Gago, com a colaboração do Prof. Doutor César Madureira e da Dra. Margarida Quintela, ex investigadores do INA, atualmente na DGAEP.

Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.

Real Time Pricing Approaches to Deal With Unexpected Wind Power Variations

The use of renewables have been increased I several countries around the world, namely in Europe. The wind power is generally the larger renewable resource with very specific characteristics in what concerns its variability and the inherent impacts in the power systems and electricity markets operation. This paper focuses on the Portuguese context of renewables use, including wind power. The work here presented includes the use of a real time pricing methodology developed by the authors aiming the reduction of electricity consumption in the moments of unexpected low wind power. A more specific example of application of real time pricing is demonstrated for the minimization of the operation costs in a distribution network. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs.

Real-Time Simulation of Real-Time Pricing Demand Response to Meet Wind Variations

Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer’ loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.

Improving discovery in the life sciences using semantic Web technologies and linked data: design principles for life sciences knowledge organization systems

Dissertation presented to obtain the Ph.D degree in Bioinformatics

The impact of pharmaceutical policy measures: a structural-break approach

Pharmaceutical spending in many other countries has had a steep increase in the last decade. The Portuguese Government has adopted several measures to reduce pharmaceutical expenditure growth, ranging from increased co-payments to price decreases determined administratively. Promotion of generic consumption has also ranked high in political priorities. We assess the overall impact of the several policy measures on total pharmaceutical spending, using monthly data over the period January 1995 – August 2008. Endogenous structural breaks (time-series) methods were employed. Our findings suggest that policy measures aimed at controlling pharmaceutical expenditure have been, in general, unsuccessful. Two breaks were identified. Both coincide with administratively determined price decreases. Measures aimed at increasing competition in the market had no visible effect on the dynamics of Government spending in pharmaceutical products. In particular, the introduction of reference pricing had only a transitory effect of less than one year, with historical growth resuming quickly. The consequence of it is a transfer of financial burden from the Government to the patients, with no apparent effect on the dynamics of pharmaceutical spending. This strongly suggests that pharmaceutical companies have been able to adjust to policy measures, in order to sustain their sales. It remains a challenge for the future to identify firms’ strategies that supported continued growth of sales, despite the several policy measures adop

Technology market transfer plan launch of DELIVES to E.U. Market©

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Biotecnologia

The role of halouracils in radiotherapy studied by electron transfer in atom-molecule collisions experiments

Dissertação para obtenção do Grau de Doutor em Engenharia Física

Alterations in lipid transfer to High-Density Lipoprotein (HDL) and activity of paraoxonase-1 in HIV+ patients

HIV+ patients often develop alterations of the plasma lipids that may implicate in development of premature coronary artery disease. High-density lipoprotein (HDL) has an important role in preventing atherogenesis and the aim of this study was to investigate aspects of HDL function in HIV+ patients. HIV+ patients (n = 48) and healthy control subjects (n = 45) of both sexes with similar age were studied. Twenty-five were not being treated with antiretroviral agents, 13 were under reverse transcriptase inhibitor nucleosidic and non-nucleosidic (NRTI+NNRTI) and 10 were under NRTI + protease inhibitors (NRTI+PI) treatment. Paraoxonase 1 (PON1) activity and the transfer of free and esterified cholesterol, tryglicerides and phospholipids from a lipidic nanoemulsion to HDL were analyzed. In comparison with healthy controls, HIV+ patients presented low PON-1 activity and diminished transfer of free cholesterol and tryglicerides. In contrast, phospholipid transfer was increased in those patients, whereas the transfer of cholesteryl esters was unchanged. NRTI+NNRTI increases the transfer of cholesteryl esters and triglycerides but in NRTI+PI there was no difference in respect to non-treated HIV+ patients. HDL from HIV+ patients has smaller antioxidant properties, as shown by lower PON-1 activity, and the transfer of lipids to this lipoprotein fraction is also altered, suggesting that HDL function is defective in those patients.

Measuring data transfer in heterogeneous IoT environments

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

Ajudantes de acção directa : percepções sobre formação profissional e impacto da formação na prestação de cuidados a idosos dependentes internados

RESUMO: A transferência de indivíduos dependentes é uma das tarefas mais realizadas pelos ajudantes de acção directa (AAD) na prestação de cuidados a idosos, sendo crucial haver formação nesta área. No entanto, os programas de formação em transferências raramente são avaliados em termos de desempenho na realização deste tipo de tarefas. Objectivo: Este estudo teve como objectivos analisar o impacto da formação de AAD no desempenho da transferência de idosos internados na Residência São João de Ávila (RSJA) e identificar as percepções dos AAD relativamente à importância da formação profissional, formação em transferências e dificuldade sentida na sua realização. Métodos: Realizou-se um estudo com duas etapas: na primeira procedeu-se a um estudo descritivo exploratório (através de um questionário auto-administrado a 25 AAD); na segunda realizou-se um estudo quase experimental de observação com duas fases, entre as quais decorreu uma “Formação em Princípios e Conceitos Básicos em Reabilitação Física” (observação directa de 18 AAD durante a realização da transferência “deitado-sentado-cadeira” de idosos, através de uma grelha de observação). Resultados: O desempenho dos AAD na transferência melhorou após a formação. Os ajudantes manifestaram ter uma percepção positiva sobre a importância da formação profissional e da formação em transferências. Aproximadamente dois terços dos AAD revelaram não sentir dificuldades na realização de transferências. Conclusões: A formação teve um impacto positivo no desempenho dos AAD na transferência de idosos. Concluiu-se que há uma sensibilização generalizada por parte dos AAD para a importância da formação na sua profissão e, especificamente, para a formação em transferências. ---------------ABSTRACT: The transfers of dependent patients by healthcare assistants are tasks commonly used in elderly care. Therefore, it is crucial that healthcare assistants are trained to perform these tasks. However, training programs are rarely evaluated in terms of performance of these tasks. Aim: The aims of this study were 1) to determine the impact of healthcare assistant training in the transfers of the Residência São João de Ávila (RSJA) elderly patients; and 2) to analyze healthcare assistant’s perceptions about their education, their specialized training on the transfer technique, and their difficulty in performing transfers. Methods: The study was divided in two parts: an exploratory and descriptive study (self-report questionnaire applied to 25 healthcare assistants); and a quasi-experimental observation study, which involved a “training session on basic concepts and principles of physical rehabilitation” (direct observation of 18 healthcare assistants during the “bed-sitting-chair” transfer, using an observation table). Results: Healthcare assistant performance of the “bed-sitting-chair” transfer improved after training. The healthcare assistants showed positive perceptions about their education and specialized training on the transfer technique. Approximately two thirds of the assistants felt no difficulties in performing transfer tasks. Conclusions: The training had a positive influence in healthcare assistant performance. The healthcare assistants were aware of the importance of training in their profession and more specifically in transfer tasks.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.