Bus Transportation – Córas Iompair Éireann and Michael Scott

The book acts as a companion to the Irish pavilion at the 2014 Venice Biennale for Architecture. This chapter examines the context of roads transport and then analyses how its architectural infrastructure developed in this period, concentrating on the work carried out mainly by one Irish firm: Michael Scott and Partners.

Ecopoetics: The Language of Nature, The Nature of Language by Scott Knickerbocker (review)

Review of Ecopoetics: The Language of Nature, The Nature of Language by Scott Knickerbocker Boston: University of Massachusetts Press, 2012. Pp. x + 203.
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Hui and Walter's latent-class model extended to estimate diagnostic test properties from surveillance data: a latent model for latent data

Diagnostic test sensitivity and specificity are probabilistic estimates with far reaching implications for disease control, management and genetic studies. In the absence of 'gold standard' tests, traditional Bayesian latent class models may be used to assess diagnostic test accuracies through the comparison of two or more tests performed on the same groups of individuals. The aim of this study was to extend such models to estimate diagnostic test parameters and true cohort-specific prevalence, using disease surveillance data. The traditional Hui-Walter latent class methodology was extended to allow for features seen in such data, including (i) unrecorded data (i.e. data for a second test available only on a subset of the sampled population) and (ii) cohort-specific sensitivities and specificities. The model was applied with and without the modelling of conditional dependence between tests. The utility of the extended model was demonstrated through application to bovine tuberculosis surveillance data from Northern and the Republic of Ireland. Simulation coupled with re-sampling techniques, demonstrated that the extended model has good predictive power to estimate the diagnostic parameters and true herd-level prevalence from surveillance data. Our methodology can aid in the interpretation of disease surveillance data, and the results can potentially refine disease control strategies.