Inter-lamellar shear resistance confers compressive stiffness in the intervertebral disc: An image-based modelling study on the bovine caudal disc

The intervertebral disc withstands large compressive loads (up to nine times bodyweight in humans) while providing flexibility to the spinal column. At a microstructural level, the outer sheath of the disc (the annulus fibrosus) comprises 12–20 annular layers of alternately crisscrossed collagen fibres embedded in a soft ground matrix. The centre of the disc (the nucleus pulposus) consists of a hydrated gel rich in proteoglycans. The disc is the largest avascular structure in the body and is of much interest biomechanically due to the high societal burden of disc degeneration and back pain. Although the disc has been well characterized at the whole joint scale, it is not clear how the disc tissue microstructure confers its overall mechanical properties. In particular, there have been conflicting reports regarding the level of attachment between adjacent lamellae in the annulus, and the importance of these interfaces to the overall integrity of the disc is unknown. We used a polarized light micrograph of the bovine tail disc in transverse cross-section to develop an image-based finite element model incorporating sliding and separation between layers of the annulus, and subjected the model to axial compressive loading. Validation experiments were also performed on four bovine caudal discs. Interlamellar shear resistance had a strong effect on disc compressive stiffness, with a 40% drop in stiffness when the interface shear resistance was changed from fully bonded to freely sliding. By contrast, interlamellar cohesion had no appreciable effect on overall disc mechanics. We conclude that shear resistance between lamellae confers disc mechanical resistance to compression, and degradation of the interlamellar interface structure may be a precursor to macroscopic disc degeneration.

J.W.Lindt’s Colonial man and Aborigine image from the GRAFTON ALBUM : “On chemistry and optics all does not depend, art must with these in triple union blend”

J.W.Lindt’s Colonial man and Aborigine image from the GRAFTON ALBUM: “On chemistry and optics all does not depend, art must with these in triple union blend” (text from J.W. Lindt’s photographic backing card) In this paper, I follow an argument that Lindt held a position in his particular colonial environment where he was simultaneously both an insider and an outsider and that such a position may be considered prerequisite in stimulating exchange. A study of the transition of J.W. Lindt in Grafton, N.S.W. in the 1860s from a traveller to a migrant and subsequently to a professional photographer, as well as Lindt’s photographic career, which evolved through strategic action and technical approaches to photography, bears witness to his cultural relativity. One untitled photograph from this period of work constructs a unique commentary of Australian colonial life that illustrates a non-hegemonic position, particularly as it was included in one of the first albums of photographs of Aborigines that Lindt gifted to an illustrious person (in this case the Mayor of Grafton). As in his other studio constructions, props and backdrops were arranged and sitters were positioned with care, but this photograph is the only one in the album that includes a non-Aborigine in a relationship to an Aborigine. An analysis of the props, technical details of the album and the image suggests a reconciliatory aspect that thwarts the predominant attitudes towards Aborigines in the area at that time.

CBCT image guidance in head and neck irradiation: The impact of daily and weekly imaging protocols

Purpose This study evaluated the impact of a daily and weekly image-guided radiotherapy protocols in reducing setup errors and setting of appropriate margins in head and neck cancer patients. Materials and methods Interfraction and systematic shifts for the hypothetical day 1–3 plus weekly imaging were extrapolated from daily imaging data from 31 patients (964 cone beam computed tomography (CBCT) scans). In addition, residual setup errors were calculated by taking the average shifts in each direction for each patient based on the first three shifts and were presumed to represent systematic setup error. The clinical target volume (CTV) to planning target volume (PTV) margins were calculated using van Herk formula and analysed for each protocol. Results The mean interfraction shifts for daily imaging were 0·8, 0·3 and 0·5 mm in the S-I (superior-inferior), L-R (left-right) and A-P (anterior-posterior) direction, respectively. On the other hand the mean shifts for day 1–3 plus weekly imaging were 0·9, 1·8 and 0·5 mm in the S-I, L-R and A-P direction, respectively. The mean day 1–3 residual shifts were 1·5, 2·1 and 0·7 mm in the S-I, L-R and A-P direction, respectively. No significant difference was found in the mean setup error for the daily and hypothetical day 1–3 plus weekly protocol. However, the calculated CTV to PTV margins for the daily interfraction imaging data were 1·6, 3·8 and 1·4 mm in the S-I, L-R and A-P directions, respectively. Hypothetical day 1–3 plus weekly resulted in CTV–PTV margins of 5, 4·2 and 5 mm in the S-I, L-R and A-P direction. Conclusions The results of this study show that a daily CBCT protocol reduces setup errors and allows setup margin reduction in head and neck radiotherapy compared to a weekly imaging protocol.

Empowering PNG Women through Building Media Arts Production Capacity as Cultural Drivers: Showreel

The creative work comprises six short digital screen stories and emerges from a collaboration between the Discipline of Film Screen and Animation at Queensland University of Technology and the Centre for Social and Creative Media at University of Goroka, funded via the Department of Foreign Affairs and Trade's Australia Awards Fellowship. Six fellows traveled from Papua New Guinea to Brisbane for a two-week intensive course to learn the advanced skills necessary in order to create media that will empower women and girls to make more of their own economies in Papua New Guinea, and increase the representation of women and their well-being through leadership and decision-making. The resulting creative work is evidence of innovative media teaching-making methods designed to build human and cultural assets in PNG and address the increasing demand for media materials driven by the influx of mobile phones and internet services. The creative work provides a platform to directly address and positively impact gender issues in PNG and builds on the success of the Pawa Meri project, which trained six female directors to tell stories of women in leadership roles in PNG. One of the directors was a producer of this creative work. The creative work frames but problematises the complex issues influencing gender equity through the selection of content and narrative structures in ways which address the dynamics of male/female relationships and power in PNG society and will include strategies to illustrate transformed male and female behaviours. The creative work adopts a scaffolded approach, incorporating the findings of the Train the Trainer approach developed by UoG and QUT for the Life Drama research project. The creative work takes into account current developmental themes and approaches in the production of rich media products, and skills the key participants so that they are able to in turn train others in the wider community. The creative work was presented to partners and key stakeholders on 3 July 2015 at the Glasshouse, QUT Creative Industries Precinct and at the Dean’s Research Seminar Poster Exhibition 15 July 2015 at Room 212-213, Level 2, J Block, Gardens Point QUT and subsequent eBook. It has since returned to PNG to be showcased and distributed, and the skills and strategies disseminated.

Destination image: identifying baseline perceptions of Brazil, Argentina and Chile in the nascent Australian long haul travel market

While the popularity of destination image research has increased exponentially in the literature, there has been relatively little published about perceptions held by international consumers of destinations in South America. The purpose of this paper is to report the findings of a research project that aimed to identify the baseline market perceptions of Brazil, Argentina and Chile amongst Australian residents, at the time of the emergence of this long haul market. Of interest was the extent to which Australians differentiate the three distinct countries versus perceiving the continent as a gestalt. These baseline perceptions enable the effectiveness of future marketing communications in Australia by the three national tourism offices to be monitored over time. Importance-Performance Analysis (IPA) is used as a practical analytical tool to guide decision makers. In terms of operationalising destination image, a key research finding was the very high ratio or participants using the ‘Don’t know’ (DK) option for each destination performance scale item. This finding has practical implications for the destination marketers, as well as for researchers engaged in destination image research in long haul and/or emerging markets.

Stopover destination image: Using the repertory test to identify salient attributes

This paper reports a rare investigation of stopover destination image. Although the topic of destination image has been one of the most popular in the tourism literature since the 1970s, there has been a lack of research attention in relation to the context of stopover destinations for long haul international travellers. The purpose of this study was to identify attributes deemed salient to Australian consumers when considering stopover destinations for long haul travel to the United Kingdom and Europe. Underpinned by Personal Construct Theory (PCT), the study used the Repertory Test to identify 21 salient attributes, which could be used in the development of a survey instrument to measure the attractiveness of a competitive set of stopover destinations. While the list of attributes shared some commonality with general studies of destination image reported in the literature, the elicitation of a relatively large number of stopover context specific attributes highlights the potential benefit of engaging with consumers in qualitative research, such as using the Repertory Test, during the questionnaire development stage.

A flexible hierarchical approach for facial age estimation based on multiple features

Age estimation from facial images is increasingly receiving attention to solve age-based access control, age-adaptive targeted marketing, amongst other applications. Since even humans can be induced in error due to the complex biological processes involved, finding a robust method remains a research challenge today. In this paper, we propose a new framework for the integration of Active Appearance Models (AAM), Local Binary Patterns (LBP), Gabor wavelets (GW) and Local Phase Quantization (LPQ) in order to obtain a highly discriminative feature representation which is able to model shape, appearance, wrinkles and skin spots. In addition, this paper proposes a novel flexible hierarchical age estimation approach consisting of a multi-class Support Vector Machine (SVM) to classify a subject into an age group followed by a Support Vector Regression (SVR) to estimate a specific age. The errors that may happen in the classification step, caused by the hard boundaries between age classes, are compensated in the specific age estimation by a flexible overlapping of the age ranges. The performance of the proposed approach was evaluated on FG-NET Aging and MORPH Album 2 datasets and a mean absolute error (MAE) of 4.50 and 5.86 years was achieved respectively. The robustness of the proposed approach was also evaluated on a merge of both datasets and a MAE of 5.20 years was achieved. Furthermore, we have also compared the age estimation made by humans with the proposed approach and it has shown that the machine outperforms humans. The proposed approach is competitive with current state-of-the-art and it provides an additional robustness to blur, lighting and expression variance brought about by the local phase features.

Sepulchre

The work in Sepulchre (2015) came from my research into female ritual practices and my fascination with specific mythological and historical narratives. These themes were explored during a month-long Summer Residency at Boxcopy Contemporary Artspace. Of particular note were the chronicles and rituals from the terrain around the Adriatic Sea, including Greece and Italy. During the residency, I kept referring to specific mythological texts, which had women as the main protagonists. I kept returning to female characters whose representation was framed by aspects of their sexuality. When looking at these women together, they seemed to sit within a greater narrative archetype, a communal dialogue of shared characteristics, repetitious narrative components and mutual landscapes. Sepulchre became my attempt to develop a conversation between these women by drawing from their commonality, and reimagining these collective elements into sculptural objects and moving images. The video explores an apotropaic gesture, a Baubo-style ‘flashing’. A glass star chart rests on white cliffs, speaking to the narrative of Andromeda and her position as both a celestial and terrene landscape. Another object, a wall mounted copper light burst, pays homage to the framing device used by Gian Lorenzo Bernini in The Ecstasy of Saint Teresa. By reconciling these dialogues, I was interested in exploring expanded portrayals of female sexuality and depictions of subversive and authorial femininity, developed through connotations with mysticism, ritual practice and women’s knowledge.

Class-specific sparse codes for representing activities

In this paper we investigate the effectiveness of class specific sparse codes in the context of discriminative action classification. The bag-of-words representation is widely used in activity recognition to encode features, and although it yields state-of-the art performance with several feature descriptors it still suffers from large quantization errors and reduces the overall performance. Recently proposed sparse representation methods have been shown to effectively represent features as a linear combination of an over complete dictionary by minimizing the reconstruction error. In contrast to most of the sparse representation methods which focus on Sparse-Reconstruction based Classification (SRC), this paper focuses on a discriminative classification using a SVM by constructing class-specific sparse codes for motion and appearance separately. Experimental results demonstrates that separate motion and appearance specific sparse coefficients provide the most effective and discriminative representation for each class compared to a single class-specific sparse coefficients.

Multiple instance dictionary learning for activity representation

This paper presents an effective feature representation method in the context of activity recognition. Efficient and effective feature representation plays a crucial role not only in activity recognition, but also in a wide range of applications such as motion analysis, tracking, 3D scene understanding etc. In the context of activity recognition, local features are increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational requirements, their performance is still limited for real world applications due to a lack of contextual information and models not being tailored to specific activities. We propose a new activity representation framework to address the shortcomings of the popular, but simple bag-of-words approach. In our framework, first multiple instance SVM (mi-SVM) is used to identify positive features for each action category and the k-means algorithm is used to generate a codebook. Then locality-constrained linear coding is used to encode the features into the generated codebook, followed by spatio-temporal pyramid pooling to convey the spatio-temporal statistics. Finally, an SVM is used to classify the videos. Experiments carried out on two popular datasets with varying complexity demonstrate significant performance improvement over the base-line bag-of-feature method.

Human action recognition from video sequences

This PhD research has proposed new machine learning techniques to improve human action recognition based on local features. Several novel video representation and classification techniques have been proposed to increase the performance with lower computational complexity. The major contributions are the construction of new feature representation techniques, based on advanced machine learning techniques such as multiple instance dictionary learning, Latent Dirichlet Allocation (LDA) and Sparse coding. A Binary-tree based classification technique was also proposed to deal with large amounts of action categories. These techniques are not only improving the classification accuracy with constrained computational resources but are also robust to challenging environmental conditions. These developed techniques can be easily extended to a wide range of video applications to provide near real-time performance.

Running men: The precarious, paranoid body in screen culture

This paper discusses my video installation Running Men as an example of how an artist’s appropriative engagements with screen images of the perilous body can reflect the technological zeitgeist of the last hundred years but also create a space of meditative and mediated reflection in Slavoj Žižek’s “endlessness” of the present-future. In this artwork, iconic male characters from Hollywood films are recontextualised to create infinitely looping scenes of running; trapping the characters in a kind of Nietchzen eternal recurrence that suspends them between impending violence and uncertain futures. Stemming primarily from my investigation into anxiety as a shared social experience, one perhaps primed by the increasing intensity of visual culture in the 21st century, these digitally reconfigured bodies become avatars or surrogates for myself, and for the viewer. Through selective editing, these emblematic figures are caught in a space of relentless confusion and paranoia – they run with, and from anxiety. They are never caught by any unseen pursuers, but are equally unable to catch up to any unseen goal. These figures map an historical trajectory of violence and masculinity as it has been projected through various iterations of screen culture Simultaneously, as celebrities, they are also fictions of the media sphere, both real and ethereal, they are impossible to grasp but paradoxically are objects of identification and emulation. In this duality, the work also references cinema’s tangled conflation of character and celebrity identity. This discussion will address the two distinct but connected sites and activities of body/image engagement. Firstly, the artistic process and conceptual ramifications of this activity, and secondly in the artwork’s potential as an installation to provide an opportunity for the viewer (like the artist) to reflect on the constructed-ness and complicated power structures at play in the representation of a gendered body.

Image, Political

Political communication scholars, journalists, and political actors alike, argue that the political process, and deliberative democracy (democracy founded on informed discussion inclusive of citizens), have lost their rational authenticity in that image and media spectacle have become more central to public opinion formation and electoral outcomes than policy. This entry examines the validity of that perception, and the extent to which “image” has emerged as a more significant factor in the political process. And if image is so important in political culture, what the impacts might be on the functioning of democratic processes.

Beyond Gauss: Image-set matching on the Riemannian manifold of PDFs

State-of-the-art image-set matching techniques typically implicitly model each image-set with a Gaussian distribution. Here, we propose to go beyond these representations and model image-sets as probability distribution functions (PDFs) using kernel density estimators. To compare and match image-sets, we exploit Csiszar´ f-divergences, which bear strong connections to the geodesic distance defined on the space of PDFs, i.e., the statistical manifold. Furthermore, we introduce valid positive definite kernels on the statistical manifold, which let us make use of more powerful classification schemes to match image-sets. Finally, we introduce a supervised dimensionality reduction technique that learns a latent space where f-divergences reflect the class labels of the data. Our experiments on diverse problems, such as video-based face recognition and dynamic texture classification, evidence the benefits of our approach over the state-of-the-art image-set matching methods.