Political Discourse Analysis, Sport and Scottish Independence: Provisional Reflections upon Fairclough and Fairclough's (2012) Analytical Framework.

This paper aims to reflect upon the potential analytical utility of the political discourse analysis framework proposed by Isabela Fairclough and Norman Fairclough (2012). This framework represents the most recent substantive development upon Norman Fairclough's past work situated within the wider school of Critical Discourse Analysis, building upon his influential position this methodological tradition. Central to this development is the additional emphasis placed upon the necessity to conceptualise all political discourse as 'argumentative' in nature, given that political actors are ultimately proposing or refuting particular courses of concrete future action. This paper will therefore apply Fairclough and Fairclough's model to provisional data derived from an ongoing doctoral thesis which considers the nature of political discourse relating to sport, the Glasgow 2014 Commonwealth Games and Scottish independence, with an ultimate aim of critically considering the benefits and limitations of applying this analytical framework as a methodological tool within this ongoing study.

Forecasting Methodologies for Ganoderma Spore Concentration Using Combined Statistical Approaches and Model Evaluations

High concentration levels of Ganoderma spp. spores were observed in Worcester, UK, during 2006–2010.These basidiospores are known to cause sensitization due to the allergen content and their small dimensions. This enables them to penetrate the lower part of the respiratory tract in humans. Establishment of a link between occurring symptoms of sensitization to Ganoderma spp. and other basidiospores is challenging due to lack of information regarding spore concentration in the air. Hence, aerobiological monitoring should be conducted, and if possible extended with the construction of forecast models. Daily mean concentration of allergenic Ganoderma spp. spores in the atmosphere of Worcester was measured using 7-day volumetric spore sampler through five consecutive years. The relationships between the presence of spores in the air and the weather parameters were examined. Forecast models were constructed for Ganoderma spp. spores using advanced statistical techniques, i.e. multivariate regression trees and artificial neural networks. Dew point temperature along with maximumtemperature was the most important factor influencing the presence of spores in the air of Worcester. Based on these two major factors and several others of lesser importance, thresholds for certain levels of fungal spore concentration, i.e. low (0–49 s m−3), moderate(50–99 s m−3), high (100–149 s m−3) and very high (150