Main entry, William St, Neville Bonner Building, Brisbane

William St building-Riverside Expressway building junction.

(FAB12_1_002) 'Would you know the new, you must search the old': William Lethaby's 'Architecture, Mysticism and Myth' (1891) and the 'Hypnerotomachia Poliphili' (1499)

Published in the final months of 1891, Architecture, Mysticism and Myth was the first architectural treatise written by the late nineteenth-century English architect and theorist William Richard Lethaby (1857-1931).' Documenting the characteristic attributes of the architectural myth of the "temple idea", and its presence amongst architectures of multiple ancient cultures, the text was endowed with a distinctly historical tone. In examining the motives behind myth, which Lethaby defined as the interaction and reaction between the natural universe and the built environment, Lethaby also injected a series of theoretical considerations into the text. It is clear that Lethaby's interest in the temple idea was not limited to its curious, prolific presence in past architectures, hut also embraced a consideration of what lessons the temple idea may contribute to the struggle of the late nineteenth-century English architect to define an "art of the future".

Development and implementation of the population Fisher information matrix for the evaluation of population pharmacokinetic designs.

In population pharmacokinetic studies, the precision of parameter estimates is dependent on the population design. Methods based on the Fisher information matrix have been developed and extended to population studies to evaluate and optimize designs. In this paper we propose simple programming tools to evaluate population pharmacokinetic designs. This involved the development of an expression for the Fisher information matrix for nonlinear mixed-effects models, including estimation of the variance of the residual error. We implemented this expression as a generic function for two software applications: S-PLUS and MATLAB. The evaluation of population designs based on two pharmacokinetic examples from the literature is shown to illustrate the efficiency and the simplicity of this theoretic approach. Although no optimization method of the design is provided, these functions can be used to select and compare population designs among a large set of possible designs, avoiding a lot of simulations.