The elaborated intrusion theory of desire : a 10-year retrospective and implications for addiction treatments

Introduction: Ten years after the publication of Elaborated Intrusion (EI) Theory, there is now substantial research into its key predictions. The distinction between intrusive thoughts, which are driven by automatic processes, and their elaboration, involving controlled processing, is well established. Desires for both addictive substances and other desired targets are typically marked by imagery, especially when they are intense. Attention training strategies such as body scanning reduce intrusive thoughts, while concurrent tasks that introduce competing sensory information interfere with elaboration, especially if they compete for the same limited-capacity working memory resources. Conclusion: EI Theory has spawned new assessment instruments that are performing strongly and offer the ability to more clearly delineate craving from correlated processes. It has also inspired new approaches to treatment. In particular, training people to use vivid sensory imagery for functional goals holds promise as an intervention for substance misuse, since it is likely to both sustain motivation and moderate craving.

The Craving Experience Questionnaire : a brief, theory-based measure of consummatory desire and craving

Background and Aims Research into craving is hampered by lack of theoretical specification and a plethora of substance-specific measures. This study aimed to develop a generic measure of craving based on elaborated intrusion (EI) theory. Confirmatory factor analysis (CFA) examined whether a generic measure replicated the three-factor structure of the Alcohol Craving Experience (ACE) scale over different consummatory targets and time-frames. Design Twelve studies were pooled for CFA. Targets included alcohol, cigarettes, chocolate and food. Focal periods varied from the present moment to the previous week. Separate analyses were conducted for strength and frequency forms. Setting Nine studies included university students, with single studies drawn from an internet survey, a community sample of smokers and alcohol-dependent out-patients. Participants A heterogeneous sample of 1230 participants. Measurements Adaptations of the ACE questionnaire. Findings Both craving strength [comparative fit indices (CFI = 0.974; root mean square error of approximation (RMSEA) = 0.039, 95% confidence interval (CI) = 0.035–0.044] and frequency (CFI = 0.971, RMSEA = 0.049, 95% CI = 0.044–0.055) gave an acceptable three-factor solution across desired targets that mapped onto the structure of the original ACE (intensity, imagery, intrusiveness), after removing an item, re-allocating another and taking intercorrelated error terms into account. Similar structures were obtained across time-frames and targets. Preliminary validity data on the resulting 10-item Craving Experience Questionnaire (CEQ) for cigarettes and alcohol were strong. Conclusions The Craving Experience Questionnaire (CEQ) is a brief, conceptually grounded and psychometrically sound measure of desires. It demonstrates a consistent factor structure across a range of consummatory targets in both laboratory and clinical contexts.

The OnTrack Diabetes web-based program for type 2 diabetes and dysphoria self-management: A randomized controlled trial protocol

Background: The prevalence of type 2 diabetes is rising with the majority of patients practicing inadequate disease self-management. Depression, anxiety, and diabetes-specific distress present motivational challenges to adequate self-care. Health systems globally struggle to deliver routine services that are accessible to the entire population, in particular in rural areas. Web-based diabetes self-management interventions can provide frequent, accessible support regardless of time and location Objective: This paper describes the protocol of an Australian national randomized controlled trial (RCT) of the OnTrack Diabetes program, an automated, interactive, self-guided Web program aimed to improve glycemic control, diabetes self-care, and dysphoria symptoms in type 2 diabetes patients. Methods: A small pilot trial is conducted that primarily tests program functionality, efficacy, and user acceptability and satisfaction. This is followed by the main RCT, which compares 3 treatments: (1) delayed program access: usual diabetes care for 3 months postbaseline followed by access to the full OnTrack Diabetes program; (2) immediate program: full access to the self-guided program from baseline onward; and (3) immediate program plus therapist support via Functional Imagery Training (FIT). Measures are administered at baseline and at 3, 6, and 12 months postbaseline. Primary outcomes are diabetes self-care behaviors (physical activity participation, diet, medication adherence, and blood glucose monitoring), glycated hemoglobin A1c (HbA1c) level, and diabetes-specific distress. Secondary outcomes are depression, anxiety, self-efficacy and adherence, and quality of life. Exposure data in terms of program uptake, use, time on each page, and program completion, as well as implementation feasibility will be conducted. Results: This trial is currently underway with funding support from the Wesley Research Institute in Brisbane, Australia. Conclusions: This is the first known trial of an automated, self-guided, Web-based support program that uses a holistic approach in targeting both type 2 diabetes self-management and dysphoria. Findings will inform the feasibility of implementing such a program on an ongoing basis, including in rural and regional locations.

Pre-processing for approximate Bayesian computation in image analysis

Most of the existing algorithms for approximate Bayesian computation (ABC) assume that it is feasible to simulate pseudo-data from the model at each iteration. However, the computational cost of these simulations can be prohibitive for high dimensional data. An important example is the Potts model, which is commonly used in image analysis. Images encountered in real world applications can have millions of pixels, therefore scalability is a major concern. We apply ABC with a synthetic likelihood to the hidden Potts model with additive Gaussian noise. Using a pre-processing step, we fit a binding function to model the relationship between the model parameters and the synthetic likelihood parameters. Our numerical experiments demonstrate that the precomputed binding function dramatically improves the scalability of ABC, reducing the average runtime required for model fitting from 71 hours to only 7 minutes. We also illustrate the method by estimating the smoothing parameter for remotely sensed satellite imagery. Without precomputation, Bayesian inference is impractical for datasets of that scale.

Integrating field survey data with satellite image data to improve shallow water seagrass maps : the role of AUV and snorkeller surveys

Repeatable and accurate seagrass mapping is required for understanding seagrass ecology and supporting management decisions. For shallow (< 5 m) seagrass habitats, these maps can be created by integrating high spatial resolution imagery with field survey data. Field survey data for seagrass is often collected via snorkelling or diving. However, these methods are limited by environmental and safety considerations. Autonomous Underwater Vehicles (AUVs) are used increasingly to collect field data for habitat mapping, albeit mostly in deeper waters (>20 m). Here we demonstrate and evaluate the use and potential advantages of AUV field data collection for calibration and validation of seagrass habitat mapping of shallow waters (< 5 m), from multispectral satellite imagery. The study was conducted in the seagrass habitats of the Eastern Banks (142 km2), Moreton Bay, Australia. In the field, georeferenced photos of the seagrass were collected along transects via snorkelling or an AUV. Photos from both collection methods were analysed manually for seagrass species composition and then used as calibration and validation data to map seagrass using an established semi-automated object based mapping routine. A comparison of the relative advantages and disadvantages of AUV and snorkeller collected field data sets and their influence on the mapping routine was conducted. AUV data collection was more consistent, repeatable and safer in comparison to snorkeller transects. Inclusion of deeper water AUV data resulted in mapping of a larger extent of seagrass (~7 km2, 5 % of study area) in the deeper waters of the site. Although overall map accuracies did not differ considerably, inclusion of the AUV data from deeper water transects corrected errors in seagrass mapped at depths to 5 m, but where the bottom is visible on satellite imagery. Our results demonstrate that further development of AUV technology is justified for the monitoring of seagrass habitats in ongoing management programs.

Shifting intimacies

Our world is literally and figuratively turning to ‘dust’. This work acknowledges decay and renewal and the transitional, cyclical natures of interrelated ecologies. It also suggests advanced levels of degradation potentially beyond reparation. Dust exists both on and beneath the border of our unaided vision. Dust particles are predominantly forms of disintegrating solids that often become the substance or catalyst of future forms. Like many tiny forms, dust is an often unnoticed residue with ‘planet-size consequences’. (Hanna Holmes 2001) The image depicts an ethereal, backlit body, continually circling and morphing, apparently floating, suggesting endless cycles of birth, life and death and inviting differing states of meditation, exploration, stillness and play. This never ending video work is taken from a large-scale interactive/media artwork created during a six-month research residency in England at the Institute of Contemporary Art London and at Vincent Dance Theatre Sheffield in 2006. It was originally presented on a raised floor screen made of pure white sand at the ICA in London (see). The project involved developing new interaction, engagement and image making strategies for media arts practice, drawing on the application of both kinetic and proprioceptive dance/performance knowledges. The work was further informed by ecological network theory that assesses the systemic implications of private and public actions within bounded systems. The creative methodology was primarily practice-led which fomented the particular qualities of imagery, generated through cross-fertilising embodied knowledge of Dance and Media Arts. This was achieved through extensive workshopping undertaken in theatres, working ‘on the floor’ live, with dancers, props, sound and projection. And eventually of course, all this dust must settle. (Holmes 2001, from Dust Jacket) Holmes, H. 2001, The Secret Life of Dust: From the Cosmos to the Kitchen Counter, the Big Consequences of Little Things, p.3

Exploiting parallax in panoramic capture to construct light fields

We show that the parallax motion resulting from non-nodal rotation in panorama capture can be exploited for light field construction from commodity hardware. Automated panoramic image capture typically seeks to rotate a camera exactly about its nodal point, for which no parallax motion is observed. This can be difficult or impossible to achieve due to limitations of the mounting or optical systems, and consequently a wide range of captured panoramas suffer from parallax between images. We show that by capturing such imagery over a regular grid of camera poses, then appropriately transforming the captured imagery to a common parameterisation, a light field can be constructed. The resulting four-dimensional image encodes scene geometry as well as texture, allowing an increasingly rich range of light field processing techniques to be applied. Employing an Ocular Robotics REV25 camera pointing system, we demonstrate light field capture,refocusing and low-light image enhancement.

Intimate Transactions Stage 4

A telepresence-based interactive installation allowing people at three sites (The National Art Museum of China, Beijing; The Imperial City Art Museum, Beijing; CalPoly University, California, USA) to interact simultaneously using only their bodies. Each participant used a physical interface called a ‘Bodyshelf’ and wore a sound vibration transmission device called a ‘haptic pendant’ around their necks. By gently moving their bodies and engaging through this ‘smart furniture’, they instigated ‘intimate transactions’, which influenced an evolving computationally-generated ‘world’ created from digital imagery, multichannel sound and tactile feedback. Intimate Transactions (Version 4) was the culmination of a long-term interdisciplinary research project developed in four distinct stages. It was launched in in 2008 and subsequently acquired on invitation by Professor Peter Weibel for the ZKM Media Art History Museum Karlsruhe in 2012.

Representing places never visited: Landscape and the diasporic imagination

While landscape photography’s complicity with the colonial possession of new territory has been substantially discussed and well understood, this paper considers the role of the European landscape as the focus of diasporic desire. The interdisciplinary project, S2Q/Good Blood began as a social history map of Scandinavian and Nordic migration to Queensland in the nineteenth century, incorporating archival material from local collections with visual field trip data gathered in Denmark, Sweden, Norway and Finland. In 2011, some of this material found its way into the installation work, 'my mother is water, my father is wood'. What emerged from this experiment was an imaginary landscape, melding its loci through original photography and video footage in tandem with stock imagery and historical material. This juxtaposition reinforced the represented landscape as a narrative landscape and evidence of the performativity of belonging. This practitioner reflection utilizes Lynette Russell’s research into landscape archaeology to consider the significance of relationships with landscapes that are “not always empirically demonstrable.”

Temporal

An evolving meditation upon the complex, periodic processes that mark Australia’s seasonality, and our increasing ability to disturb them. By amplifying and shining light upon a myriad of mysterious lives lived in blackness, the work presents a sensuous, deep engagement with the rich, irregular spectras of seasonal forms: whilst hinting at a far less comforting background increasingly framed by anthropogenic climate change. ’Temporal’ uses custom interactive systems, illusionary techniques and real time spatial audio processes that draw upon a rich array of media, including seasonal, nocturnal field recordings sourced in the Bundaberg region and detailed observations of foliage & flowering phases from that region. By drawing inspiration from the subtle transitions between what Europeans once named ‘Summer’ and ‘Autumn’ and the multiple seasons recognised by other cultures, whilst also including bodily disturbances within the work, ’Temporal’ creates a compellingly immersive environment that wraps audiences in luscious yet ominous atmospheres beyond sight and hearing. This work completes a two year long project of dynamic mediated installations that have been presented in Sydney, Beijing, Cairns and Bundanon, that have each been somehow choreographed by environmental cycles; alluding to a new framework for making works that we named ‘Seasonal’. These powerful, responsive & experiential works each draw attention to that which will disappear when biodiverse worlds have descended into an era of permanent darkness – an ‘extinction of human experience’. By tapping into the deeply interlocking seasonal cycles of environments that are themselves intimately linked with social, geographical & political concerns, participating audiences are therefore challenged to see the night, their locality & ecologies in new ways through extending their personal limits of perception, imagery & comprehension.

LunaRoo: A Proposal for the Google Lunar XPrize Payload Opportunity with the Part Time Scientists team

This proposal describes the innovative and competitive lunar payload solution developed at the Queensland University of Technology (QUT)–the LunaRoo: a hopping robot designed to exploit the Moon's lower gravity to leap up to 20m above the surface. It is compact enough to fit within a 10cm cube, whilst providing unique observation and mission capabilities by creating imagery during the hop. This first section is deliberately kept short and concise for web submission; additional information can be found in the second chapter.

Brisbane Art Deco: Stories of our Built Heritage

Our built heritage plays an important role in the ongoing story of our city. Modern cities such as Brisbane embraced Art Deco style in its architecture as it swept the world during the interwar period. From inner city landmarks such as the striking McWhirters department store to lesser-known gems further afield like the streamlined Archerfield Airport administration building, Brisbane has a significant range of intriguing and beautiful Art Deco buildings. This publication documents and celebrates a selection of our favourite residential and commercial examples. Written contributions from a range of authors are complemented by stunning modern photography and historic archive imagery, taking readers on a journey through this fascinating era. The articles not only describe the aesthetic and architectural features, but also delve into the associated social history. Brisbane Art Deco: Stories of our Built Heritage is a charming and informative reference, and offers a colourful insight into Brisbane’s built heritage and the life and times of this dynamic city.

Progressive dysgraphia in a case of posterior cortical atrophy

Dysgraphia (agraphia) is a common feature of posterior cortical atrophy (PCA). However, detailed analyses of these spelling and writing impairments are infrequently conducted. LM is a 59-year-old woman with dysgraphia associated with PCA. She presented with a two-year history of decline in her writing and dressmaking skills. A 3D T1-weighted MRI scan confirmed selective bi-parietal atrophy, with relative sparing of the hippocampi and other cortical regions. Analyses of LM's preserved and impaired spelling abilities indicated mild physical letter distortions and a significant spelling deficit characterised by letter substitutions, insertions, omissions, and transpositions that was systematically sensitive to word length while insensitive to real word versus nonword category, word frequency, regularity, imagery, grammatical class and ambiguity. Our findings suggest a primary graphemic buffer disorder underlies LM's spelling errors, possibly originating from disruption to the operation of a fronto-parietal network implicated in verbal working memory.

Yellow Peril

This catalogue essay was written to accompany Eugenia Lim's 2015 exhibition at Metro Arts, Brisbane, 'Yellow Peril'. It discusses Lim's exploration of her identity as a Chinese-Australian, providing contextual information of Chinese immigration during Australia's gold rush years and the work of Hong Kong born American artist, Tseng Kwong Chi. It presents Yellow Peril as an exhibition that speaks critically about art and our cultural history amidst a fine layering of imagery, object and context, with a vitality that is derived from its rich and compelling base in real life moments and connections.

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.