Abstract
Inference in many probabilistic logic systems is based on representing the proofs of a query as a DNF Boolean formula. Assessing the probability of such a formula is known as a #P-hard task. In practice, a large DNF is given to a BDD software package to construct the corresponding BDD. The DNF has to be transformed into the input format of the package. This is the preprocessing step. In this paper we investigate and compare different preprocessing methods, including our new trie based approach. Our experiments within the ProbLog system show that the behaviour of the methods changes according to the amount of sharing in the original DNF. The decomposition method is preferred when there is not much sharing in the DNF, whereas DNFs with sharing benefit from our trie based method. While our methods are motivated and applied in the ProbLog context, our results are interesting for other applications that manipulate DNF Boolean formulae.

Abstract
An important characteristic of the role of foreign trade in the technological catch-up of countries is the complementary nature with technological change, human capital development and local R&D efforts. Using cointegration techniques, evidence based on Portuguese long-run growth suggests that by investing in certain capacity-building activities, namely human capital and local R&D efforts, countries can improve their ability to identify, value, assimilate, and apply (or exploit) knowledge that is developed in other (more developed) countries. Although human capital has a stronger direct impact on total factor productivity than internal R&D efforts, the latter's indirect impact, by means of machinery and equipment imports, is tremendous. Trade also emerges as a powerful direct contributor to long-term total factor productivity, especially in its embodied form, through the acquisition of advanced machinery and equipment from more developed countries. The (smaller) productivity enhancing effect of licenses and FDI seems to be strongly dependent on institutional circumstances, namely those related to human capital investments and incentives.

Abstract
In this research programme, methodologies for structural health monitoring (SHM) of composite overwrapped pressure vessels (COPV) were addressed. This works fit in the development of a COPV laboratorial prototype incorporating non-destructive sensing technologies, in order to detect and identify critical aspects that can occur during operation, aiming to reduce possible unwanted and unpredicted failures. Fibre Bragg grating (FBG) optical sensors and polyvinylidene Fluoride (PVDF) polymeric piezoelectric were the selected sensing technologies. These sensors were embedded in the liner-composite interface during its manufacturing and monitored the prototype while being tested under cyclic internal pressure loading. The data collected from the different sensors type were compared. The Analysis of the data, together with the assessment to the suitability of the two sensing technologies in SHM applications are discussed.

Abstract
This paper proposes a new method to manage the use of ontologies in the context of Virtual Organisations Breeding Environments (VBEs). The research focuses on the dissolution phase of a Virtual Enterprise (VE), where ontology decomposition techniques are used to enrich the ontology library. First, an overview of the process used and the Ontology Library System (OLS) adopted are described. Then, the ontologies' ranking and classification method are described, explaining a set of metrics inspired by social network approaches. Finally, the composition method used to construct a global ontology and the decomposition algorithm implemented to segment an ontology are presented. Copyright © 2010 Inderscience Enterprises Ltd.

Abstract
The increasing levels of wind power penetration motivated a revisitation of methods for setting operating reserve requirements for the next and current day. System Operators (SO) are now moving from deterministic intro probabilistic approaches, and including wind power forecasts in their decision-making problems. In this manuscript, a probabilistic approach that evaluates the consequences of setting each possible reserve level through a set of risk indices is compared with frequently used deterministic rules and a probabilistic rule where wind power uncertainty is described by a Gaussian distribution. The comparison is performed over a period of five months for a realistic power system, using real load and wind power generation data. Results highlight the limitations of deterministic rules, challenge the Gaussian assumption and illustrate the usefulness of risk indices derived from the probabilistic forecast and using a full probabilistic methodology.

Abstract
Silvopastoralism is an activity with multiple benefits from both the ecological and economical points of view. Besides the potential cash flow to landowners, it has multiple environmental advantages and it can even help to reduce fire hazard in woodland. This hazard reduction is due to cattle grazing, and for it to become effective, it is needed to move herds to the correct place at the correct time. Only knowing when and where shrubs and sward are ready for grazing it is possible to make an effective management of herd placement. In loco inspection of the terrain can be time and resource consuming, as large areas must be verified. An automated system to detect the presence of shrubs and sward can help to improve the management of herds. Since Wireless Sensor Networks (WSN) have spread in the last years and, are becoming very popular in agricultural applications, the objective of this work is to analyse the effect of vegetation in radio-frequency (RF) signals propagation, and use it to detect plants growth. Experiments showed that by measuring and analysing the attenuation in wireless links it is possible to detect plants growth. Besides providing the infrastructure to transmit data from field wireless sensors, the network itself can be used as the sensor.