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Advances in Cloud computing technology and the availability of affordable and easy to use Cloud services are enabling a multitude of scientific applications to use these resources as primary or secondary computing infrastructure. The urban and built environment research domain is one area that can benefit greatly from Cloud computing. The global population growth and increase in the size and population of cities raise many challenges for governments, planners and researchers alike. The Australian Urban Research Infrastructure Network (AURIN— http://www.aurin.org.au ) project has been tasked with developing an advanced platform (e-Infrastructure) across Australia to tackle these challenges. The platform leverages large-scale Cloud resources to provide federated data access to, at present over 1100 data sets from major and often definitive government and industry data-rich organisations, and for scalable data processing and visualisation. The original AURIN tools were developed using the object modelling system (OMS) and supported integrated workflows to define and enact/re-enact scientific processes. More recently the work has evolved to focus more on delivery of a workbench offering a rich range of tools delivered through an extensible workflow environment. In this paper, we provide the background to AURIN including the scientific drivers that are shaping the work and the realisation of the Cloud-based AURIN environment. We focus in particular on the workflow environment and show how it seamlessly utilizes the Cloud for urban research processes focused especially on data-intensive spatial analysis. We illustrate the utilisation of this workflow environment across a range of case studies reflecting urban research activities.

OBJECTIVES--The evaluation of the role of polymorphism within the class II encoded antigen processing genes, LMP2 and TAP, in susceptibility to ankylosing spondylitis (AS). METHODS--Eighty five patients with ankylosing spondylitis, 35 B27 positive healthy controls, and 55 unrelated healthy controls were studied. TAP1 and TAP2 alleles were assigned by ARMS PCR, and LMP2 alleles were assigned by restriction enzyme digestion of a PCR product. RESULTS--The TAP1C allele was increased in the AS group (6%) compared with random controls (1%), p = 0.03 and TAP2E was increased in AS (3.5%) compared with random controls (0%), p = 0.05. However, the frequencies of these alleles were also increased in B27 matched controls. There were no differences in LMP2 allele or genotype frequencies between AS and either of the control groups. Partitioning of patients according to presence or absence of uveitis did not reveal any significant associations. CONCLUSIONS--Increases of the minor TAP alleles, 1C and 2E, in AS reflect linkage disequilibrium between these alleles and HLA-B27. Polymorphism of the class I antigen processing pathway does not contribute significantly to AS susceptibility nor to the development of anterior uveitis associated with AS.