Local closed world reasoning with description logics under the well-founded semantics

An important question for the upcoming Semantic Web is how to best combine open world ontology languages, such as the OWL-based ones, with closed world rule-based languages. One of the most mature proposals for this combination is known as hybrid MKNF knowledge bases (Motik and Rosati, 2010 [52]), and it is based on an adaptation of the Stable Model Semantics to knowledge bases consisting of ontology axioms and rules. In this paper we propose a well-founded semantics for nondisjunctive hybrid MKNF knowledge bases that promises to provide better efficiency of reasoning, and that is compatible with both the OWL-based semantics and the traditional Well-Founded Semantics for logic programs. Moreover, our proposal allows for the detection of inconsistencies, possibly occurring in tightly integrated ontology axioms and rules, with only little additional effort. We also identify tractable fragments of the resulting language.     

Segmentation of ultrasound images of the carotid using RANSAC and cubic splines

A new algorithm is proposed for the semi-automatic segmentation of the near-end and the far-end adventitia boundary of the common carotid artery in ultrasound images. It uses the random sample consensus method to estimate the most significant cubic splines fitting the edge map of a longitudinal section. The consensus of the geometric model (a spline) is evaluated through a new gain function, which integrates the responses to different discriminating features of the carotid boundary: the proximity of the geometric model to any edge or to valley shaped edges; the consistency between the orientation of the normal to the geometric model and the intensity gradient; and the distance to a rough estimate of the lumen boundary.A set of 50 longitudinal B-mode images of the common carotid and their manual segmentations performed by two medical experts were used to assess the performance of the method. The image set was taken from 25 different subjects, most of them having plaques of different classes (class II to class IV), sizes and shapes.The quantitative evaluation showed promising results, having detection errors similar to the ones observed in manual segmentations for 95% of the far-end boundaries and 73% of the near-end boundaries.     

On the elastic modulus degradation in continuum damage mechanics

To measure accurately the elastic modulus of a metal, E, can be a difficult task when a specimen undergoes plastic strains. Moreover, some failure criteria, such as those associated with Continuum Damage Mechanics, require the change of elastic modulus with strain to define a measure of damage, D, in a material or structure. Thus, it is important to assess the possible geometrical influence of a specimen on the measurement of the elastic modulus at different deformation levels. It is shown in this article, with the aid of a numerical simulation, that any plastic strains induce important geometrical effects in the evaluation of E, which have a significant influence on the evaluation of the scalar damage parameter, D.     

Dissimilarity-based classification of chromatographic profiles

This paper proposes a non-parametric method for the classification of thin-layer chromatographic (TLC) images from patterns represented in a dissimilarity space. Each pattern corresponds to a mixture of Gaussian approximation of the intensity profile. The methodology comprises various phases, including image processing and analysis steps to extract the chromatographic profiles and a classification phase to discriminate among two groups, one corresponding to normal cases and the other to three pathological classes. We present an extensive study of several dissimilarity-based approaches analysing the influence of the dissimilarity measure and the prototype selection method on the classification performance. The main conclusions of this paper are that, Match and Profile-difference dissimilarity measures present better results, and a new prototype selection methodology achieves a performance similar or even better than conventional methods. Furthermore, we also concluded that simplest classifiers, such as k-NN and linear discriminant classifiers (LDCs), present good performance being the overall classification error less than 10% for the four-class problem.     

Plant oil bioconversion into increase biological activity through lipases derived from wastes

The aim of this study was to show that abundant and inexpensive plant oils can be biotransformed to increase biological activity (antioxidant, antimicrobial and cytotoxicity) through hydrolysis reaction catalysed by lipases. We tested homemade and commercial lipases through the biotransformation of nine different plant oils in forty different combinations. First, the chemical composition of the samples was investigated. Thereafter, biological tests were conducted to assess the antioxidant and antimicrobial activity of the sampled biotransformation products, as well as analyzed their influence on the viability of healthy and cancer cells. Summarising, sunflower, corn and olive oils modified by orange waste-obtained lipases presented the most promising results, reaching up to 90% of antioxidant activity increase and significant growth inhibition of bacteria colonies belonging to genera Escherichia, Listeria, Staphylococcus, Pseudomonas and Salmonella. In addition, those compounds affected human oral squamous carcinoma cells. The bioconversion of plant oils through lipases improves their biological properties and might be an option for biotechnological application.     

Characterization of a water-based paint for corrosion protection

Corrosion of steel rebars in reinforced concrete is one of the major problems in the construction industry. Carbonation reactions of concrete with carbon dioxide and, mainly, the chloride salts action are the main causes responsible for concrete degradation. Protective coatings help to improve the durability of concrete structures by acting as a physical barrier against the corrosion agents. Waterborne paints are usually used for concrete protection rather than solvent-based paints since they are less pollutant. The aim of this work is to investigate the influence of the pore size and porosity on the permeability of the paints films toward sodium chloride. Three characterization methods from membrane science were implemented to characterize paint coatings. The time-lag method was used to determine the permeability toward the sodium chloride and toward helium and argon, these for approximately 100% relative humidity. From the seven waterborne paints formulated, only one was found to be suitable for surface protection of reinforced concrete, since its permeability toward NaCl was smaller than 10⁻¹⁴ m² s⁻¹, the threshold value required by National Laboratory of Civil Engineering (LNEC) in Portugal. For the formulated paints, it was observed that the average pore size correlates well with the permeability toward sodium chloride. This is an important result since obtaining the permeability toward sodium chloride of corrosion protective paints is very time consuming, while the average pore size can be obtained in a much shorter time.     

Modeling the leadership – project performance relation: radial basis function,Gaussian and Kriging methods as alternatives to linear regression

The purpose of this paper is to analyze alternative forecasting methods that produce results at least similar to or better than linear regression (MLR) that can be used in the modeling of social systems. While organizations may be considered as typically non-linear systems, the common feature of most models found in literature continues to be the use of linear regression techniques. From a case study, advanced statistical methods of Gaussian and Kriging are evaluated, as well as an artificial intelligence (AI) tool, the radial basis function (RBF). The results show the best performance of the suggested methods compared to MLR, especially RBF, because of its uniform prediction behavior throughout all ranges of evaluation. These techniques, although somewhat unconventional in social systems modeling, present a potential contribution in increasing the accuracy and precision of the predictions allowing a more accurate assessment of the impact of certain strategies on the project performance to be made before the allocation of material, human and financial resources.     

Carbonation durability of blended cement pastes used for waste encapsulation

Blended cement pastes are currently used for encapsulation of low level and intermediate level nuclear waste in the UK. However, there is still little information on the long-term durability of those mixes to some chemical attacks. Accelerated testing may predict the long-term durability or at least help the selection of more durable formulations. In this work, blended blastfurnace slag (BFS)/Portland cement (OPC) pastes containing 60, 75 and 90% BFS and pulverised fuel ash (PFA)/OPC pastes with 40, 55 and 75% PFA were cured at 20 and 60°C for 90 days then submitted to natural and accelerated carbonation (5% CO₂). The effects of the curing temperature as well as the OPC replacement level on the carbonation ratio are presented. Results showed a good correlation between natural and accelerated carbonation for the pastes studied. Carbonation was found to be governed by the amount of calcium hydroxide available in the mixes before the process started.     

Detection of the Object Velocity Using Doubly-scattered Dynamic Speckles Under Gaussian Beam Illumination

Abstract

The dynamic properties of doubly-scattered speckles produced at the image plane have been investigated using a scattering model that consists of a coherent Gaussian beam, a cascade of two moving diffusers and a single imaging lens. Dependence of the fluctuation speed of time-varying image speckles on the velocities of the diffusers is found to change with the size of illuminating speckles and the width of the point-spread function of the imaging lens. When the point-spread function and the focal position satisfy certain conditions, three kinds of velocity information—the velocity of each diffuser, the average velocity of the diffusers and the velocity difference between the diffusers—can be obtained by measuring a temporal correlation length of the time-varying speckle intensity. Experimental results confirm the theoretical predictions.