The double risk of primitivism

This essay examines the possibilities for practices that appeal to the primitive in the contemporary cultural context. The idea of the primitive is driven by a desire to challenge the limitations of Western culture, while at the same time attracting the charge of promoting Eurocentrism. This essay investigates this double risk and how artists have sought to evade it, confound it, or accentuate it.

Road crash risk after whiplash associated disorder

The future on-road safety of drivers affected by Whiplash Associated Disorder (WAD), the most common soft-tissue injury suffered in a traffic crash, has not been extensively explored. We obtained an anonymised file of 4280 insurance claimants with WAD and, as controls, 1116 claimants with comparably severe soft-tissue injuries who are considered to be at no increased risk than the general population. Their demographic information, road user type and traffic crash records both prior and subsequent to the traffic incident in which the injury occurred, the index crash, were obtained. Rates of subsequent crash involvement in these two groups were then compared, adjusting for age, sex, road user type and prior crash experience. The risk of a subsequent crash in the WAD group relative to controls was 1.14 (95% confidence interval, 0.87–1.48). To allow for differentially altered driving exposure after index crash we distributed a brief survey asking about changes in driving habits after a traffic crash involving injury via physiotherapy clinics and online through the electronic newsletter of a local motoring organisation. The survey yielded responses from 113 drivers who had experienced WAD in a traffic crash and 53 with other soft tissue injuries. There were no differences on average between the groups in their prior driving levels or their percentage change therein at one, three or six months after injury. There was thus no evidence that drivers with WAD are at any higher safety risk than drivers with other types of relatively minor post-crash soft tissue injury.

Spatial prediction of N2O emissions in pasture : a Bayesian model averaging analysis

Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.

Forecasting the future risk of Barmah Forest Virus disease under climate change scenarios in Queensland, Australia

BACKGROUND Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. METHODS/PRINCIPAL FINDINGS We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000-2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. CONCLUSIONS/SIGNIFICANCE We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland.