782 resultados para rappresentazioni lavoro, social network analysis, mobilità professionale, lavoro, istat
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Population pressure in coastal New Hampshire challenges land use decision-making and threatens the ecological health and functioning of Great Bay, an estuary designated as both a NOAA National Estuarine Research Reserve and an EPA National Estuary Program site. Regional population in the seacoast has quadrupled in four decades resulting in sprawl, increased impervious surface cover and larger lot rural development (Zankel, et.al., 2006). All of Great Bay’s contributing watersheds face these challenges, resulting in calls for strategies addressing growth, development and land use planning. The communities within the Lamprey River watershed comprise this case study. Do these towns communicate upstream and downstream when making land use decisions? Are cumulative effects considered while debating development? Do town land use groups consider the Bay or the coasts in their decision-making? This presentation, a follow-up from the TCS 2008 conference and a completed dissertation, will discuss a novel social science approach to analyze and understand the social landscape of land use decision-making in the towns of the Lamprey River watershed. The methods include semi-structured interviews with GIS based maps in a grounded theory analytical strategy. The discussion will include key findings, opportunities and challenges in moving towards a watershed approach for land use planning. This presentation reviews the results of the case study and developed methodology, which can be used in watersheds elsewhere to map out the potential for moving towns towards EBM and watershed-scaled, land use planning. (PDF contains 4 pages)
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468 p.
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Sequence analysis of the mitochondrial genome has become a routine method in the study of mitochondrial diseases. Quite often, the sequencing efforts in the search of pathogenic or disease-associated mutations are affected by technical and interpretive pr
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This thesis presents research theorising the use of social network sites (SNS) for the consumption of cultural goods. SNS are Internet-based applications that enable people to connect, interact, discover, and share user-generated content. They have transformed communication practices and are facilitating users to present their identity online through the disclosure of information on a profile. SNS are especially effective for propagating content far and wide within a network of connections. Cultural goods constitute hedonic experiential goods with cultural, artistic, and entertainment value, such as music, books, films, and fashion. Their consumption is culturally dependant and they have unique characteristics that distinguish them from utilitarian products. The way in which users express their identity on SNS is through the sharing of cultural interests and tastes. This makes cultural good consumption vulnerable to the exchange of content and ideas that occurs across an expansive network of connections within these social systems. This study proposes the lens of affordances to theorise the use of social network sites for the consumption of cultural goods. Qualitative case study research using two phases of data collection is proposed in the application of affordances to the research topic. The interaction between task, technology, and user characteristics is investigated by examining each characteristic in detail, before investigating the actual interaction between the user and the artifact for a particular purpose. The study contributes to knowledge by (i) improving our understanding of the affordances of social network sites for the consumption of cultural goods, (ii) demonstrating the role of task, technology and user characteristics in mediating user behaviour for user-artifact interactions, (iii) explaining the technical features and user activities important to the process of consuming cultural goods using social network sites, and (iv) theorising the consumption of cultural goods using SNS by presenting a theoretical research model which identifies empirical indicators of model constructs and maps out affordance dependencies and hierarchies. The study also provides a systematic research process for applying the concept of affordances to the study of system use.
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The successful design of biomaterial scaffolds for articular cartilage tissue engineering requires an understanding of the impact of combinations of material formulation parameters on diverse and competing functional outcomes of biomaterial performance. This study sought to explore the use of a type of unsupervised artificial network, a self-organizing map, to identify relationships between scaffold formulation parameters (crosslink density, molecular weight, and concentration) and 11 such outcomes (including mechanical properties, matrix accumulation, metabolite usage and production, and histological appearance) for scaffolds formed from crosslinked elastin-like polypeptide (ELP) hydrogels. The artificial neural network recognized patterns in functional outcomes and provided a set of relationships between ELP formulation parameters and measured outcomes. Mapping resulted in the best mean separation amongst neurons for mechanical properties and pointed to crosslink density as the strongest predictor of most outcomes, followed by ELP concentration. The map also grouped formulations together that simultaneously resulted in the highest values for matrix production, greatest changes in metabolite consumption or production, and highest histological scores, indicating that the network was able to recognize patterns amongst diverse measurement outcomes. These results demonstrated the utility of artificial neural network tools for recognizing relationships in systems with competing parameters, toward the goal of optimizing and accelerating the design of biomaterial scaffolds for articular cartilage tissue engineering.
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Interest in animal personalities has generated a burgeoning literature on repeatability in individual traits such as boldness or exploration through time or across different contexts. Yet, repeatability can be influenced by the interactive social strategies of individuals, for example, consistent inter-individual variation in aggression is well documented. Previous work has largely focused on the social aspects of repeatability in animal behaviour by testing individuals in dyadic pairings. Under natural conditions, individuals interact in a heterogeneous polyadic network. However, the extent to which there is repeatability of social traits at this higher order network level remains unknown. Here, we provide the first empirical evidence of consistent and repeatable animal social networks. Using a model species of shark, a taxonomic group in which repeatability in behaviour has yet to be described, we repeatedly quantified the social networks of ten independent shark groups across different habitats, testing repeatability in individual network position under changing environments. To understand better the mechanisms behind repeatable social behaviour, we also explored the coupling between individual preferences for specific group sizes and social network position. We quantify repeatability in sharks by demonstrating that despite changes in aggregation measured at the group level, the social network position of individuals is consistent across treatments. Group size preferences were found to influence the social network position of individuals in small groups but less so for larger groups suggesting network structure, and thus, repeatability was driven by social preference over aggregation tendency.
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Research has shown that people often do not claim labels associated with mental retardation or learning difficulties. We discussed the interpretation that this rejection is an example of a denial process, the purpose of which is to protect self-esteem. Alternative explanations for this lack of identification were offered, based on an understanding of the socially constructed nature of diagnostic labels and on the distinction between diagnostic labels and social categories. Some of the problems in using the label as a descriptive or explanatory resource are illustrated using quotes from a study in which people who have been labeled discussed the label.
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While the incorporation of mathematical and engineering methods has greatly advanced in other areas of the life sciences, they have been under-utilized in the field of animal welfare. Exceptions are beginning to emerge and share a common motivation to quantify 'hidden' aspects in the structure of the behaviour of an individual, or group of animals. Such analyses have the potential to quantify behavioural markers of pain and stress and quantify abnormal behaviour objectively. This review seeks to explore the scope of such analytical methods as behavioural indicators of welfare. We outline four classes of analyses that can be used to quantify aspects of behavioural organization. The underlying principles, possible applications and limitations are described for: fractal analysis, temporal methods, social network analysis, and agent-based modelling and simulation. We hope to encourage further application of analyses of behavioural organization by highlighting potential applications in the assessment of animal welfare, and increasing awareness of the scope for the development of new mathematical methods in this area.