Classifying Candidate Axioms via Dimensionality Reduction Techniques

We assess the role of similarity measures and learning methods in classifying candidate axioms for automated schema induction through kernel-based learning algorithms. The evaluation is based on (i) three different similarity measures between axioms, and (ii) two alternative dimensionality reduction techniques to check the extent to which the considered similarities allow to separate true axioms from false axioms. The result of the dimensionality reduction process is subsequently fed to several learning algorithms, comparing the accuracy of all combinations of similarity, dimensionality reduction technique, and classification method. As a result, it is observed that it is not necessary to use sophisticated semantics-based similarity measures to obtain accurate predictions, and furthermore that classification performance only marginally depends on the choice of the learning method. Our results open the way to implementing efficient surrogate models for axiom scoring to speed up ontology learning and schema induction methods

Utilising biological geotextiles: Introduction to the BORASSUS project and global perspectives

Field and laboratory studies indicate that utilisation of biological geotextiles constructed from palm-leaves and other selected organic materials are an effective, sustainable and economically viable soil conservation technique. The three-year plus (1 July 2005–28 February 2009) EU-funded BORASSUS Project (contract no. INCO-CT-2005-510745) evaluated the long-term effectiveness of biological geotextiles in controlling soil erosion and assessing their sustainability and economic viability. These studies progressed in ten countries, both in the ‘industrial north’ (in Europe) and in the ‘developing south’ (Africa, South America and South East Asia). The studied countries in the ‘developing south’ included Brazil, China, The Gambia, South Africa, Thailand and Vietnam. The ‘industrial north’ countries included Belgium, Hungary, Lithuania and the UK. The main findings of these studies are summarised in this paper and thematic information is presented in the other four papers in this Special Issue. Biological geotextiles offer potentially novel bioengineering solutions to environmental problems, including technologies for soil conservation, sustainable plant production and use of indigenous plants, improved ecosystem management by decreasing deforestation, improving agroforestry and cost-effective biogeotextile applications in diverse environments. Biogeotextiles may provide socio-economic platforms for sustainable development and the benefits for developing countries may include poverty alleviation, engagement of local people as stakeholders, employment for disadvantaged groups, small and medium enterprise (SME) development, earning hard currency, environmental education and local community involvement in land reclamation and environmental education programmes. These benefits are achieved through: (i) promotion of sustainable and environmentally friendly palm-agriculture to discourage deforestation, promoting both reforestation and agroforestry; (ii) construction of biogeotextiles enabling development of a rural labour-intensive industry, particularly encouraging employment of socially disadvantaged groups and (iii) export of biogeotextiles to industrialised countries could earn hard currency for developing economies, based on the principles of fair trade. Research and development activities of the BORASSUS Project have improved our knowledge on the effect of biogeotextile mats on the micro- and macro-soil environments and at larger scales through controlled laboratory and field experiments in diverse environments

Hybrid acquisition of temporal scopes for RDF data

Information on the temporal interval of validity for facts described by RDF triples plays an important role in a large number of applications. Yet, most of the knowledge bases available on the Web of Data do not provide such information in an explicit manner. In this paper, we present a generic approach which addresses this drawback by inserting temporal information into knowledge bases. Our approach combines two types of information to associate RDF triples with time intervals. First, it relies on temporal information gathered from the document Web by an extension of the fact validation framework DeFacto. Second, it harnesses the time information contained in knowledge bases. This knowledge is combined within a three-step approach which comprises the steps matching, selection and merging. We evaluate our approach against a corpus of facts gathered from Yago2 by using DBpedia and Freebase as input and different parameter settings for the underlying algorithms. Our results suggest that we can detect temporal information for facts from DBpedia with an F-measure of up to 70%. © 2014 Springer International Publishing

Active axial stress in mouse aorta

The study verifies the development of active axial stress in the wall of mouse aorta over a range of physiological loads when the smooth muscle cells are stimulated to contract. The results obtained show that the active axial stress is virtually independent of the magnitude of pressure, but depends predominately on the longitudinal stretch ratio. The dependence is non-monotonic and is similar to the active stress-stretch dependence in the circumferential direction reported in the literature. The expression for the active axial stress fitted to the experimental data shows that the maximum active stress is developed at longitudinal stretch ratio 1.81, and 1.56 is the longitudinal stretch ratio below which the stimulation does not generate active stress. The study shows that the magnitude of active axial stress is smaller than the active circumferential stress. There is need for more experimental investigations on the active response of different types of arteries from different species and pathological conditions. The results of these studies can promote building of refined constrictive models in vascular rheology. (C) 2012 Elsevier Ltd. All rights reserved