"Rebirth: Combined art performance"--Shirin Madg & Sweet Sound Ensemble

Vanessa Mafe-Keane was invited to participate as choreographer in Iranian singer Shirin Madg 's project, Rebirth: Combined art performance. This project integrated singing, music, visual-art, film, dance and is based on the dissident poetry of female Iranian poet, Forough Farrokhzad. The choreographic dance movement focused on simple, lyrical, flowing classical dance forms that also incorporated everyday gestures and actions performed by two Queensland dancers, Caitlin MacKenzie and Abby Johnson. The choreographic intention was not to attempt to re-create Iranian dance practices instead, to draw inspiration and reference specific movement qualities. This was achieved through the subtle inclusion of spinning movements and focusing attention on the dancers’ arms and upper torso. This fusion became an underlying theme reflected throughout the choreographic component. Additionally, this project presented an opportunity to draw on past experiences and problem-solve ways to construct choreographic work where the dancers and the musical assemble group could be staged side by side. This experience highlighted differing approaches to rehearsal protocols within disciplines, the practicalities of staging different artists, understanding musical cues and the diversity of audience engagement. Performances: BEMAC Multicultural Centre, Brisbane 06 February 2015 and Helensvale Cultural Centre, Gold Coast 07 February 2015

Fresh Cuttings: A Celebration of Fiction and Poetry from UQP's Black Writing Series

As the first anthology of UQP's indigenous-authored books, Fresh Cuttings represents the very best of fiction and poetry publishing from UQP's Black Australian Writing series. An introduction by the editors and a biography of each author is included.

Serum levels of soluble receptor for advanced glycation end products and of S100 proteins are associated with inflammatory, autoantibody, and classical risk markers of joint and vascular damage in rheumatoid arthritis

Introduction: The receptor for advanced glycation end products (RAGE) is a member of the immunoglobulin superfamily of cell surface receptor molecules. High concentrations of three of its putative proinflammatory ligands, S100A8/A9 complex (calprotectin), S100A8, and S100A12, are found in rheumatoid arthritis (RA) serum and synovial fluid. In contrast, soluble RAGE (sRAGE) may prevent proinflammatory effects by acting as a decoy. This study evaluated the serum levels of S100A9, S100A8, S100A12 and sRAGE in RA patients, to determine their relationship to inflammation and joint and vascular damage. Methods: Serum sRAGE, S100A9, S100A8 and S100A12 levels from 138 patients with established RA and 44 healthy controls were measured by ELISA and compared by unpaired t test. In RA patients, associations with disease activity and severity variables were analyzed by simple and multiple linear regressions. Results: Serum S100A9, S100A8 and S100A12 levels were correlated in RA patients. S100A9 levels were associated with body mass index (BMI), and with serum levels of S100A8 and S100A12. S100A8 levels were associated with serum levels of S100A9, presence of anti-citrullinated peptide antibodies (ACPA), and rheumatoid factor (RF). S100A12 levels were associated with presence of ACPA, history of diabetes, and serum S100A9 levels. sRAGE levels were negatively associated with serum levels of C-reactive protein (CRP) and high-density lipoprotein (HDL), history of vasculitis, and the presence of the RAGE 82Ser polymorphism. Conclusions: sRAGE and S100 proteins were associated not just with RA inflammation and autoantibody production, but also with classical vascular risk factors for end-organ damage. Consistent with its role as a RAGE decoy molecule, sRAGE had the opposite effects to S100 proteins in that S100 proteins were associated with autoantibodies and vascular risk, whereas sRAGE was associated with protection against joint and vascular damage. These data suggest that RAGE activity influences co-development of joint and vascular disease in rheumatoid arthritis patients.

From the genius of man to the man of genius, part two: Inheriting (ideas about) genius

In Part One of ʻFrom the Genius of the Man to the Man of Geniusʼ I argued that classical and medieval inscriptions of genius figures suggest a coevalence between characters in their respective cosmologies, making it relatively more difficult to delineate Man from “spirits” and “other organisms”. The labour that genii performed flowed around two significant tropes of production and reproduction whose specificities were inflected in and across sources. In medieval poetry, for instance, genius figures took up a new role in regard to the reproduction trope, as promoter of virtue (in the form of censuring the seven deadly sins) and condemner of vice (in the form of prohibition against same sex intercourse). The sedimentation (complex processes of character-formation), directionality (patterns of descent) and sexual ecology (emergence of a field of ethics) that the medieval literature embodies also indexes an opening disarticulation of Man from universe and the possibility of grounding “morality” in and as His love choices. Through a series of narrative structures, binary concepts and new sources of authority under Christianity the figure now referred to in philosophy as “the subject” is given early grounds upon which to form in the medieval poems.

Eliciting and encoding expert knowledge on variable selection into classical or Bayesian species distribution models

The quality of species distribution models (SDMs) relies to a large degree on the quality of the input data, from bioclimatic indices to environmental and habitat descriptors (Austin, 2002). Recent reviews of SDM techniques, have sought to optimize predictive performance e.g. Elith et al., 2006. In general SDMs employ one of three approaches to variable selection. The simplest approach relies on the expert to select the variables, as in environmental niche models Nix, 1986 or a generalized linear model without variable selection (Miller and Franklin, 2002). A second approach explicitly incorporates variable selection into model fitting, which allows examination of particular combinations of variables. Examples include generalized linear or additive models with variable selection (Hastie et al. 2002); or classification trees with complexity or model based pruning (Breiman et al., 1984, Zeileis, 2008). A third approach uses model averaging, to summarize the overall contribution of a variable, without considering particular combinations. Examples include neural networks, boosted or bagged regression trees and Maximum Entropy as compared in Elith et al. 2006. Typically, users of SDMs will either consider a small number of variable sets, via the first approach, or else supply all of the candidate variables (often numbering more than a hundred) to the second or third approaches. Bayesian SDMs exist, with several methods for eliciting and encoding priors on model parameters (see review in Low Choy et al. 2010). However few methods have been published for informative variable selection; one example is Bayesian trees (O’Leary 2008). Here we report an elicitation protocol that helps makes explicit a priori expert judgements on the quality of candidate variables. This protocol can be flexibly applied to any of the three approaches to variable selection, described above, Bayesian or otherwise. We demonstrate how this information can be obtained then used to guide variable selection in classical or machine learning SDMs, or to define priors within Bayesian SDMs.

Representations of the Natural World in Old English Poetry

Review of Representations of the Natural World in Old English Poetry, by Jennifer Neville (Cambridge UP, 1999).