Cortisol shifts financial risk preferences

Risk taking is central to human activity. Consequently, it lies at the focal point of behavioral sciences such as neuroscience, economics, and finance. Many influential models from these sciences assume that financial risk preferences form a stable trait. Is this assumption justified and, if not, what causes the appetite for risk to fluctuate? We have previously found that traders experience a sustained increase in the stress hormone cortisol when the amount of uncertainty, in the form of market volatility, increases. Here we ask whether these elevated cortisol levels shift risk preferences. Using a double-blind, placebo-controlled, cross-over protocol we raised cortisol levels in volunteers over eight days to the same extent previously observed in traders. We then tested for the utility and probability weighting functions underlying their risk taking, and found that participants became more risk averse. We also observed that the weighting of probabilities became more distorted among men relative to women. These results suggest that risk preferences are highly dynamic. Specifically, the stress response calibrates risk taking to our circumstances, reducing it in times of prolonged uncertainty, such as a financial crisis. Physiology-induced shifts in risk preferences may thus be an under-appreciated cause of market instability.

Australian animated feature films

Building on and bringing up to date the material presented in the first installment of Directory of World Cinema : Australia and New Zealand, this volume continues the exploration of the cinema produced in Australia and New Zealand since the beginning of the twentieth century. Among the additions to this volume are in-depth treatments of the locations that feature prominently in the countries' cinema. Essays by leading critics and film scholars consider the significance in films of the outback and the beach, which is evoked as a liminal space in Long Weekend and a symbol of death in Heaven's Burning, among other films. Other contributions turn the spotlight on previously unexplored genres and key filmmakers, including Jane Campion, Rolf de Heer, Charles Chauvel, and Gillian Armstrong.

Is there an app for that? A case study of the potentials and limitations of the participator turn and networked publics for classical music audience engagement

The participatory turn, fuelled by discourses and rhetoric regarding social media, and in the aftermath of the dot.com crash of the early 2000s, enrols to some extent an idea of being able to deploy networks to achieve institutional aims. The arts and cultural sector in the UK, in the face of funding cuts, has been keen to engage with such ideas in order to demonstrate value for money; by improving the efficiency of their operations, improving their respective audience experience and ultimately increasing audience size and engagement. Drawing on a case study compiled via a collaborative research project with a UK-based symphony orchestra (UKSO) we interrogate the potentials of social media engagement for audience development work through participatory media and networked publics. We argue that the literature related to mobile phones and applications (‘apps’) has focused primarily on marketing for engagement where institutional contexts are concerned. In contrast, our analysis elucidates the broader potentials and limitations of social-media-enabled apps for audience development and engagement beyond a marketing paradigm. In the case of UKSO, it appears that the technologically deterministic discourses often associated with institutional enrolment of participatory media and networked publics may not necessarily apply due to classical music culture. More generally, this work raises the contradictory nature of networked publics and argues for increased critical engagement with the concept.

Kelp detection in highly dynamic environments using texture recognition

This paper describes a texture recognition based method for segmenting kelp from images collected in highly dynamic shallow water environments by an Autonomous Underwater Vehicle (AUV). A particular challenge is image quality that is affected by uncontrolled lighting, reduced visibility, significantly varying perspective due to platform egomotion, and kelp sway from wave action. The kelp segmentation approach uses the Mahalanobis distance as a way to classify Haralick texture features from sub-regions within an image. The results illustrate the applicability of the method to classify kelp allowing construction of probability maps of kelp masses across a sequence of images.

Robotics for sustainable broad-acre agriculture

This paper describes the development of small low-cost cooperative robots for sustainable broad-acre agriculture to increase broad-acre crop production and reduce environmental impact. The current focus of the project is to use robotics to deal with resistant weeds, a critical problem for Australian farmers. To keep the overall system affordable our robot uses low-cost cameras and positioning sensors to perform a large scale coverage task while also avoiding obstacles. A multi-robot coordinator assigns parts of a given field to individual robots. The paper describes the modification of an electric vehicle for autonomy and experimental results from one real robot and twelve simulated robots working in coordination for approximately two hours on a 55 hectare field in Emerald Australia. Over this time the real robot 'sprayed' 6 hectares missing 2.6% and overlapping 9.7% within its assigned field partition, and successfully avoided three obstacles.

Novelty-based visual obstacle detection in agriculture

This paper describes a novel obstacle detection system for autonomous robots in agricultural field environments that uses a novelty detector to inform stereo matching. Stereo vision alone erroneously detects obstacles in environments with ambiguous appearance and ground plane such as in broad-acre crop fields with harvested crop residue. The novelty detector estimates the probability density in image descriptor space and incorporates image-space positional understanding to identify potential regions for obstacle detection using dense stereo matching. The results demonstrate that the system is able to detect obstacles typical to a farm at day and night. This system was successfully used as the sole means of obstacle detection for an autonomous robot performing a long term two hour coverage task travelling 8.5 km.

David Williamson's The Club : football politic, a dirty story

Watching David Williamson’s The Club (Bruce Beresford, 1980) now, as a scandal over performance‐enhancing drugs threatens to destroy at least one AFL club and permanently taint the League’s credibility, while in another form of football a player is bought and sold for a world record fee of almost $150 million, the indignant outrage of the film’s coach and players over the $120,000 fee paid for a pot‐smoking raw recruit appears quaint and comic in unintended ways. Were it ever true, it seems harder than ever now to agree with Nick Parson’s assertion that ‘in Australia the only sphere of endeavour that is considered morally pure is sport.

Trade marks for the design and layout of retail premises

In January 2013, Apple Inc obtained United States trademarks for the design and layout of its retail stores. While innovative brand protection strategies of this kind are not without precedent in the United States, traders in Australia have seemingly not adopted them. This article considers the prospects of an applicant seeking to register a similar trade mark in Australia and the protection such a registration would likely provide.

Online self-supervised multi-instance segmentation of dynamic objects

This paper presents a method for the continuous segmentation of dynamic objects using only a vehicle mounted monocular camera without any prior knowledge of the object’s appearance. Prior work in online static/dynamic segmentation is extended to identify multiple instances of dynamic objects by introducing an unsupervised motion clustering step. These clusters are then used to update a multi-class classifier within a self-supervised framework. In contrast to many tracking-by-detection based methods, our system is able to detect dynamic objects without any prior knowledge of their visual appearance shape or location. Furthermore, the classifier is used to propagate labels of the same object in previous frames, which facilitates the continuous tracking of individual objects based on motion. The proposed system is evaluated using recall and false alarm metrics in addition to a new multi-instance labelled dataset to evaluate the performance of segmenting multiple instances of objects.

Sports dietitians Australia position statement : sports nutrition for the adolescent athlete

It is the position of Sports Dietitians Australia (SDA) that adolescent athletes have unique nutritional requirements as a consequence of undertaking daily training and competition in addition to the demands of growth and development. As such, SDA established an expert multidisciplinary panel to undertake an independent review of the relevant scientific evidence and consulted with its professional members to develop sports nutrition recommendations for active and competitive adolescent athletes. The position of SDA is that dietary education and recommendations for these adolescent athletes should reinforce eating for long term health. More specifically, the adolescent athlete should be encouraged to moderate eating patterns to reflect daily exercise demands and provide a regular spread of high quality carbohydrate and protein sources over the day, especially in the period immediately after training. SDA recommends that consideration also be given to the dietary calcium, Vitamin D and iron intake of adolescent athletes due to the elevated risk of deficiency of these nutrients. In order to maintain optimal hydration, adolescent athletes should have access to fluids that are clean, cool and supplied in sufficient quantities before, during and after participation in sport. Finally, it is the position of SDA that use of nutrient needs should be met by core foods rather than supplements, as the recommendation of dietary supplements to developing athletes over-emphasises their ability to manipulate performance in comparison to other training and dietary strategies.

The 10 Australian ecosystems most vulnerable to tipping points

We identify the 10 major terrestrial and marine ecosystems in Australia most vulnerable to tipping points, in which modest environmental changes can cause disproportionately large changes in ecosystem properties. To accomplish this we independently surveyed the coauthors of this paper to produce a list of candidate ecosystems, and then refined this list during a 2-day workshop. The list includes (1) elevationally restricted mountain ecosystems, (2) tropical savannas, (3) coastal floodplains and wetlands, (4) coral reefs, (5) drier rainforests, (6) wetlands and floodplains in the Murray-Darling Basin, (7) the Mediterranean ecosystems of southwestern Australia, (8) offshore islands, (9) temperate eucalypt forests, and (10) salt marshes and mangroves. Some of these ecosystems are vulnerable to widespread phase-changes that could fundamentally alter ecosystem properties such as habitat structure, species composition, fire regimes, or carbon storage. Others appear susceptible to major changes across only part of their geographic range, whereas yet others are susceptible to a large-scale decline of key biotic components, such as small mammals or stream-dwelling amphibians. For each ecosystem we consider the intrinsic features and external drivers that render it susceptible to tipping points, and identify subtypes of the ecosystem that we deem to be especially vulnerable. © 2011 Elsevier Ltd.

Technoeconomic analysis of renewable aviation fuel from microalgae,Pongamia pinnata, and sugarcane

Technoeconomic analysis of renewable aviatin fuels has not been widely considered, despite the increasing global attention that the field has received. We present three process models for production of aviation fuel from microalgae, Pongamia pinnata, and sugarcane molasses. The models and assumptions have been deposited on a wiki (http://qsafi.aibn.uq.edu.au) and are open and accessible to the community. Based on currently available long-term reputable technological data, this analysis indicates that the biorefinieries processing the microalgae, Pongamia seeds, and sugarcane feedstocks would be competitive with crude oil at $1343, $374, and $301/bbl, respectively. Sensitivity analyses of the major economic drivers suggest technological and market developments that would bring the corresponding figures down to $385, $255, and $168/bbl. The dynamic nature of the freely accessible models will allow the community to track progress toward economic competitiveness of aviation fuels from these renewable feedstocks.

A bayesian approach for place recognition

This paper presents a robust place recognition algorithm for mobile robots that can be used for planning and navigation tasks. The proposed framework combines nonlinear dimensionality reduction, nonlinear regression under noise, and Bayesian learning to create consistent probabilistic representations of places from images. These generative models are incrementally learnt from very small training sets and used for multi-class place recognition. Recognition can be performed in near real-time and accounts for complexity such as changes in illumination, occlusions, blurring and moving objects. The algorithm was tested with a mobile robot in indoor and outdoor environments with sequences of 1579 and 3820 images, respectively. This framework has several potential applications such as map building, autonomous navigation, search-rescue tasks and context recognition.

Fast re-parameterisation of Gaussian mixture models for robotics applications

Autonomous navigation and picture compilation tasks require robust feature descriptions or models. Given the non Gaussian nature of sensor observations, it will be shown that Gaussian mixture models provide a general probabilistic representation allowing analytical solutions to the update and prediction operations in the general Bayesian filtering problem. Each operation in the Bayesian filter for Gaussian mixture models multiplicatively increases the number of parameters in the representation leading to the need for a re-parameterisation step. A computationally efficient re-parameterisation step will be demonstrated resulting in a compact and accurate estimate of the true distribution.