Social interactions in Chinese parks : a walk in Lu Xun Park

What can we learn from Chinese parks and Chinese people? We took a walk through Lu Xun Park, one of Shanghai’s most popular parks. Here hundreds of people participate in dozens of physical and mental exercises that are considered to be essential for good health and fitness. We found that the most successful spaces for social interaction and inclusiveness were not just coded for ‘doing’ a diverse range of activities but also for ‘showing’ those activities. This dual role of park spaces could be given greater design consideration in encouraging occupants of small households in Australia to make greater use of public parks in the future.

Music, Mime & Metamorphosis: Interdisciplinary intersections, interactions and influences between music, mime and corporate communication

This doctoral thesis comprises three distinct yet related projects which investigate interdisciplinary practice across: music collaboration; mime performance; and corporate communication. Both the processes and underpinning research of these projects explore, expose and exploit areas where disparate and apparently conflicting fields of professional practice successfully and effectively; intersect, interact, and inform each other - rather than conflict - thereby enhancing each, both individually and collectively. Informed by three decades of professional practice across: music; stage performance; television; corporate communication; design; and tertiary education, the three projects have produced innovative, creative, and commercial viable outcomes, manifest in a variety of media including: music; written text; digital, audio/visual; and internet. In exploring new practice and creating new knowledge, these project outcomes clearly demonstrate the value and effectiveness of reconciling disparate fields of practice through the application of inter-disciplinary creativity and innovation to professional practice.

Mineralized human primary osteoblast matrices as a model system to analyse interactions of prostate cancer cells with the bone microenvironment

Prostate cancer metastasis is reliant on the reciprocal interactions between cancer cells and the bone niche/micro-environment. The production of suitable matrices to study metastasis, carcinogenesis and in particular prostate cancer/bone micro-environment interaction has been limited to specific protein matrices or matrix secreted by immortalised cell lines that may have undergone transformation processes altering signaling pathways and modifying gene or receptor expression. We hypothesize that matrices produced by primary human osteoblasts are a suitable means to develop an in vitro model system for bone metastasis research mimicking in vivo conditions. We have used a decellularized matrix secreted from primary human osteoblasts as a model for prostate cancer function in the bone micro-environment. We show that this collagen I rich matrix is of fibrillar appearance, highly mineralized, and contains proteins, such as osteocalcin, osteonectin and osteopontin, and growth factors characteristic of bone extracellular matrix (ECM). LNCaP and PC3 cells grown on this matrix, adhere strongly, proliferate, and express markers consistent with a loss of epithelial phenotype. Moreover, growth of these cells on the matrix is accompanied by the induction of genes associated with attachment, migration, increased invasive potential, Ca2+ signaling and osteolysis. In summary, we show that growth of prostate cancer cells on matrices produced by primary human osteoblasts mimics key features of prostate cancer bone metastases and thus is a suitable model system to study the tumor/bone micro-environment interaction in this disease.

Bioengineered 3D platform to explore cell-ECM interactions and drug resistance of epithelial ovarian cancer cells

The behaviour of cells cultured within three-dimensional (3D) structures rather than onto two-dimensional (2D) culture plastic more closely reflects their in vivo responses. Consequently, 3D culture systems are becoming crucial scientific tools in cancer cell research. We used a novel 3D culture concept to assess cell-matrix interactions implicated in carcinogenesis: a synthetic hydrogel matrix equipped with key biomimetic features, namely incorporated cell integrin-binding motifs (e.g. RGD peptides) and the ability of being degraded by cell-secreted proteases (e.g. matrix metalloproteases). As a cell model, we chose epithelial ovarian cancer, an aggressive disease typically diagnosed at an advanced stage when chemoresistance occurs. Both cell lines used (OV-MZ-6, SKOV-3) proliferated similarly in 2D, but not in 3D. Spheroid formation was observed exclusively in 3D when cells were embedded within hydrogels. By exploiting the design flexibility of the hydrogel characteristics, we showed that proliferation in 3D was dependent on cell-integrin engagement and the ability of cells to proteolytically remodel their extracellular microenvironment. Higher survival rates after exposure to the anti-cancer drug paclitaxel were observed in cell spheroids grown in hydrogels (40-60%) compared to cell monolayers in 2D (20%). Thus, 2D evaluation of chemosensitivity may not reflect pathophysiological events seen in patients. Because of the design flexibility of their characteristics and their stability in long-term cultures (28 days), these biomimetic hydrogels represent alternative culture systems for the increasing demand in cancer research for more versatile, physiologically relevant and reproducible 3D matrices.

Cell interactions of osteoarthritic subchondral bone osteoblasts and articular chondrocytes aggravate MMP-2 and MMP-9 production through the mediation of ERK1/2 and JNK phosphorylation

Matrix Metalloproteinases (MMP) play a key role in osteoarthritis (OA) development. The aim of the present study was to investigate whether, the cross-talk between subchondral bone osteoblasts (SBOs) and articular cartilage chondrocytes (ACCs) in OA alters the expression and regulation of MMPs, and also to test the potential involvement of mitogen activated protein kinase (MAPK) signalling pathway during this process.

The application of profluorescent nitroxides to detect reactive oxygen species derived from combustion-generated particulate matter: Cigarette smoke – a case study

Reactive oxygen species (ROS) and related free radicals are considered to be key factors underpinning the various adverse health effects associated with exposure to ambient particulate matter. Therefore, measurement of ROS is a crucial factor for assessing the potential toxicity of particles. In this work, a novel profluorescent nitroxide, BPEAnit, was investigated as a probe for detecting particle-derived ROS. BPEAnit has a very low fluorescence emission due to inherent quenching by the nitroxide group, but upon radical trapping or redox activity, a strong fluorescence is observed. BPEAnit was tested for detection of ROS present in mainstream and sidestream cigarette smoke. In the case of mainstream cigarette smoke, there was a linear increase in fluorescence intensity with an increasing number of cigarette puffs, equivalent to an average of 101 nmol ROS per cigarette based on the number of moles of the probe reacted. Sidestream cigarette smoke sampled from an environmental chamber exposed BPEAnit to much lower concentrations of particles, but still resulted in a clearly detectible increase in fluorescence intensity with sampling time. It was calculated that the amount of ROS was equivalent to 50 ± 2 nmol per mg of particulate matter; however, this value decreased with ageing of the particles in the chamber. Overall, BPEAnit was shown to provide a sensitive response related to the oxidative capacity of the particulate matter. These findings present a good basis for employing the new BPEAnit probe for the investigation of particle-related ROS generated from cigarette smoke as well as from other combustion sources.

Damaged goods: riskiness and LGBT young peoples’ interactions with police

For some time now, research has suggested lesbian, gay, bisexual and transgender (LGBT) young people are ‘at-risk’ of victimisation and legally ‘risky’. Relatively few studies have examined how ‘risk factor’ research influences the everyday lives of LGBT young people. This paper reports how the experiences of police by 35 LGBT young people in Brisbane, Queensland reflected discourses about LGBT riskiness and how danger informed their interactions with police in public spaces. The participants specifically note how looking at-risk or looking risky affected their experiences of policing. The paper will conclude with recommendations for improved future policing practice.

Visualizing digital media interactions : providing feedback on jam2jam AV performances

Instrumental music performance is a well-established case of real-time interaction with technology and, when extended to ensembles, of interaction with others. However, these interactions are fleeting and the opportunities to reflect on action is limited, even though audio and video recording has recently provided important opportunities in this regard. In this paper we report on research to further extend these reflective opportunities through the capture and visualization of gestural data collected during collaborative virtual performances; specifically using the digital media instrument Jam2jam AV and the specifically-developed visualization software Jam2jam AV Visualize. We discusses how such visualization may assist performance development and understanding. The discussion engages with issues of representation, authenticity of virtual experiences, intersubjectivity and wordless collaboration, and creativity support. Two usage scenarios are described showing that collaborative intent is evident in the data visualizations more clearly than in audio-visual recordings alone, indicating that the visualization of performance gestures can be an efficient way of identifying deliberate and co-operative performance behaviours.

The nature of pedagogic teacher-student interactions : a phenomenographic study

Globally, teaching has become more complex and more challenging over recent years, with new and increased demands being placed on teachers by students, their families, governments and wider society. Teachers work with more diverse communities in times characterised by volatility, uncertainty and moral ambiguity. Societal, political, economic and cultural shifts have transformed the contexts in which teachers work and have redefined the ways in which teachers interact with students. This qualitative study uses phenomenographic methods to explore the nature of pedagogic teacherstudent interactions. The data analysis reveals five qualitatively different ways in which teachers experience pedagogic engagements with students. The resultant categories of description ranged from information providing, with teachers viewed as transmitters of a body of knowledge through to mentoring in which teachers were perceived as significant others in the lives of students with their influence extending beyond the walls of the classroom and beyond the years of schooling. The paper concludes by arguing that if teachers are to prepare students for the challenges and opportunities in changing times, teacher education programs need to consider ways to facilitate the development of mentoring capacities in new teachers.

Nonlinear diffusion and exclusion processes with contact interactions

Exclusion processes on a regular lattice are used to model many biological and physical systems at a discrete level. The average properties of an exclusion process may be described by a continuum model given by a partial differential equation. We combine a general class of contact interactions with an exclusion process. We determine that many different types of contact interactions at the agent-level always give rise to a nonlinear diffusion equation, with a vast variety of diffusion functions D(C). We find that these functions may be dependent on the chosen lattice and the defined neighborhood of the contact interactions. Mild to moderate contact interaction strength generally results in good agreement between discrete and continuum models, while strong interactions often show discrepancies between the two, particularly when D(C) takes on negative values. We present a measure to predict the goodness of fit between the discrete and continuous model, and thus the validity of the continuum description of a motile, contact-interacting population of agents. This work has implications for modeling cell motility and interpreting cell motility assays, giving the ability to incorporate biologically realistic cell-cell interactions and develop global measures of discrete microscopic data.

Molecular characterisation of six badnavirus species associated with leaf streak disease of banana in East Africa

Banana leaf streak disease, caused by several species of Banana streak virus (BSV), is widespread in East Africa. We surveyed for this disease in Uganda and Kenya, and used rolling-circle amplification (RCA) to detect the presence of BSV in banana. Six distinct badnavirus sequences, three from Uganda and three from Kenya, were amplified for which only partial sequences were previously available. The complete genomes were sequenced and characterised. The size and organisation of all six sequences was characteristic of other badnaviruses, including conserved functional domains present in the putative polyprotein encoded by open reading frame (ORF) 3. Based on nucleotide sequence analysis within the reverse transcriptase/ribonuclease H-coding region of open reading frame 3, we propose that these sequences be recognised as six new species and be designated as Banana streak UA virus, Banana streak UI virus, Banana streak UL virus, Banana streak UM virus, Banana streak CA virus and Banana streak IM virus. Using PCR and species-specific primers to test for the presence of integrated sequences, we demonstrated that sequences with high similarity to BSIMV only were present in several banana cultivars which had tested negative for episomal BSV sequences.

User-web interactions : how wholistic/analytic web users search the web?

User-Web interactions have emerged as an important research in the field of information science. In this study, we examine extensively the Web searching performed by general users. Our goal is to investigate the effects of users’ cognitive styles on their Web search behavior in relation to two broad components: Information Searching and Information Processing Approaches. We use questionnaires, a measure of cognitive style, Web session logs and think-aloud as the data collection instruments. Our study findings show wholistic Web users tend to adopt a top-down approach to Web searching, where the users searched for a generic topic, and then reformulate their queries to search for specific information. They tend to prefer reading to process information. Analytic users tend to prefer a bottom-up approach to information searching and they process information by scanning search result pages.

Mechanistic investigations into interactions between IGF-I and IGFBPs and their impact on facilitating cell migration on vitronectin

Numerous studies have reported links between insulin-like growth factors (IGFs) and the extra-cellular matrix protein vitronectin (VN). We ourselves have reported that IGF-I binds to VN via IGF-binding proteins (IGFBPs) to stimulate HaCaT and MCF-7 cell migration. Here, we detail the functional evaluation of IGFBP-1, -2, -3, -4 and -6 in the presence and absence of IGF-I and VN. The data presented here, combined with our prior data on IGFBP-5, suggest that IGFBP-3, -4 and -5 are the most effective at stimulating cell migration in combination with IGF-I and VN. In addition, we demonstrate that different regions within IGFBP-3 and -4 are critical for complex formation. Furthermore, we examine whether multi-protein complexes of IGF-I and IGFBPs associated with fibronectin and collagen IV are also able to enhance functional biological responses.

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

Color and texture feature fusion using kernel PCA with application to object-based vegetation species classification

A good object representation or object descriptor is one of the key issues in object based image analysis. To effectively fuse color and texture as a unified descriptor at object level, this paper presents a novel method for feature fusion. Color histogram and the uniform local binary patterns are extracted from arbitrary-shaped image-objects, and kernel principal component analysis (kernel PCA) is employed to find nonlinear relationships of the extracted color and texture features. The maximum likelihood approach is used to estimate the intrinsic dimensionality, which is then used as a criterion for automatic selection of optimal feature set from the fused feature. The proposed method is evaluated using SVM as the benchmark classifier and is applied to object-based vegetation species classification using high spatial resolution aerial imagery. Experimental results demonstrate that great improvement can be achieved by using proposed feature fusion method.