The study reported here presents a detailed description of what it is like to parent a child with juvenile Huntington's disease in families across four European countries. Its primary aim was to develop and extend findings from a previous UK study. The study recruited parents from four European countries: Holland, Italy, Poland and Sweden,. A secondary aim was to see the extent to which the findings from the UK study were repeated across Europe and the degree of commonality or divergence across the different countries. Fourteen parents who were the primary caregiver took part in a semistructured interview. These were analyzed using an established qualitative methodology, interpretative phenomenological analysis. Five analytic themes were derived from the analysis: the early signs of something wrong; parental understanding of juvenile Huntington's disease; living with the disease; other people's knowledge and understanding; and need for support. These are discussed in light of the considerable convergence between the experiences of families in the United Kingdom and elsewhere in Europe.
Abstract.Ontologies are the backbone of the Semantic Web, a semantic-aware version of the World Wide Web. To the end of making available large-scale, high quality domain ontologies, effective and usable methodologies are needed to facilitate the process of Ontology Building. Many of the methods proposed so far only partly refer to well-known and widely used standards from other areas, like software engineering and knowledge representation. In this paper we present UPON, a methodology for ontology building derived from the Unified Software Development Process. A comparative evaluation with other methodologies, as well as the results of its adoption in the context of the Athena Integrated Project, are also discussed.
We provide a model for diffusion of interests in Social Networks (SNs). We demonstrate that the topology of the SN plays a crucial role in the dynamics of the individual interests. Understanding cultural phenomena on SNs and exploiting the implicit knowledge about their members is attracting the interest of different research communities both from the academic and the business side. The community of complexity science is devoting significant efforts to define laws, models, and theories, which, based on acquired knowledge, are able to predict future observations (e.g. success of a product). In the mean time, the semantic web community aims at engineering a new generation of advanced services by defining constructs, models and methods, adding a semantic layer to SNs. In this context, a leapfrog is expected to come from a hybrid approach merging the disciplines above. Along this line, this work focuses on the propagation of individual interests in social networks. The proposed framework consists of the following main components: a method to gather information about the members of the social networks; methods to perform some semantic analysis of the Domain of Interest; a procedure to infer members’ interests; and an interests evolution theory to predict how the interests propagate in the network. As a result, one achieves an analytic tool to measure individual features, such as members’ susceptibilities and authorities. Although the approach applies to any type of social network, here it is has been tested against the computer science research community. The DBLP (Digital Bibliography and Library Project) database has been elected as test-case since it provides the most comprehensive list of scientific production in this field
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