Blast atlas: a virtual observatory for genomes

Following the completion of the draft Human Genome in 2001, genomic sequence data is becoming available at an accelerating rate, fueled by advances in sequencing and computational technology. Meanwhile, large collections of astronomical and geospatial data have allowed the creation of virtual observatories, accessible throughout the world and requiring only commodity hardware. Through a combination of advances in data management, data mining and visualization, this infrastructure enables the development of new scientific and educational applications as diverse as galaxy classification and real-time tracking of earthquakes and volcanic plumes. In the present paper, we describe steps taken along a similar path towards a virtual observatory for genomes – an immersive three-dimensional visual navigation and query system for comparative genomic data.

Approximate Bayesian Computation for astronomical model analysis : a case study in galaxy demographics and morphological transformation at high redshift

Approximate Bayesian Computation’ (ABC) represents a powerful methodology for the analysis of complex stochastic systems for which the likelihood of the observed data under an arbitrary set of input parameters may be entirely intractable – the latter condition rendering useless the standard machinery of tractable likelihood-based, Bayesian statistical inference [e.g. conventional Markov chain Monte Carlo (MCMC) simulation]. In this paper, we demonstrate the potential of ABC for astronomical model analysis by application to a case study in the morphological transformation of high-redshift galaxies. To this end, we develop, first, a stochastic model for the competing processes of merging and secular evolution in the early Universe, and secondly, through an ABC-based comparison against the observed demographics of massive (Mgal > 1011 M⊙) galaxies (at 1.5 < z < 3) in the Cosmic Assembly Near-IR Deep Extragalatic Legacy Survey (CANDELS)/Extended Groth Strip (EGS) data set we derive posterior probability densities for the key parameters of this model. The ‘Sequential Monte Carlo’ implementation of ABC exhibited herein, featuring both a self-generating target sequence and self-refining MCMC kernel, is amongst the most efficient of contemporary approaches to this important statistical algorithm. We highlight as well through our chosen case study the value of careful summary statistic selection, and demonstrate two modern strategies for assessment and optimization in this regard. Ultimately, our ABC analysis of the high-redshift morphological mix returns tight constraints on the evolving merger rate in the early Universe and favours major merging (with disc survival or rapid reformation) over secular evolution as the mechanism most responsible for building up the first generation of bulges in early-type discs.

Book review "Moving Innovation: A History of Computer Animation by Tom Sito , The MIT Press: Cambridge, MA, 2013"

As a Lecturer of Animation History and 3D Computer Animator, I received a copy of Moving Innovation: A History of Computer Animation by Tom Sito with an element of anticipation in the hope that this text would clarify the complex evolution of Computer Graphics (CG). Tom Sito did not disappoint, as this text weaves together the multiple development streams and convergent technologies and techniques throughout history that would ultimately result in modern CG. Universities now have students who have never known a world without computer animation and many students are younger than the first 3D CG animated feature film, Toy Story (1996); this text is ideal for teaching computer animation history and, as I would argue, it also provides a model for engaging young students in the study of animation history in general. This is because Sito places the development of computer animation within the context of its pre-digital ancestry and throughout the text he continues to link the discussion to the broader history of animation, its pioneers, technologies and techniques...

Ma Ma Ma Mad

Ma Ma Ma Mad is an autobiographical work, written and performed by Singaporean-Australian theatre maker Merlynn Tong. This production, presented at the Brisbane Powerhouse in December 2015, was a multi-genre work incorporating aspects of Butoh, physical theatre, cabaret and contemporary monologue. More than an experiment in mixed performative forms, however, this particular production was also an exercise in inter-cultural collaboration as well as gender in (and of) performance. Heavily influenced by the creator's experiences growing up in urban Southeast Asia, the director's specialisation in contemporary Australian theatre and experience telling uniquely Australian stories worked to manipulate the form in an endeavour to succinctly speak to local audiences, without pandering to entrenched stereotypes or diluting the underlying Chinese-Singaporean themes. The success of this production was also somewhat of a personal challenge for the creatives, after being told by some of Brisbane's most influential theatre venues and festivals that they would rather not support the work because a) it was a one woman show, and b) it was a one woman show about an Asian woman; and therefore would not sell well. One very influential local producer even said that he already had a one-woman show about an Asian person programmed, so he couldn't possibly program another. Operating in such a biased and out-of-touch artistic environment was seen as an easy challenge for the artists involved, which resulted in a highly successful and critically acclaimed sell-out run of Ma Ma Ma Mad, followed by offers to tour the work nationally and internationally. As such, this production also stands as a practical example of the ingrained and patriarchal structures of the Australian arts scene, and how art can work to break down the very barriers that it has helped to construct through a lack of vision and diversity amongst its leaders.