Choroidal thickness in myopic and non-myopic children assessed with enhanced depth imaging optical coherence tomography

Purpose To examine choroidal thickness (ChT) and its topographical variation across the posterior pole in myopic and non-myopic children. Methods One hundred and four children aged 10-15 years of age (mean age 13.1 ± 1.4 years) had ChT measured using enhanced depth imaging optical coherence tomography (OCT). Forty one children were myopic (mean spherical equivalent -2.4 ± 1.5 D) and 63 non-myopic (mean +0.3 ± 0.3 D). Two series of 6 radial OCT line scans centred on the fovea were assessed for each child. Subfoveal ChT and ChT across a series of parafoveal zones over the central 6mm of the posterior pole were determined through manual image segmentation. Results Subfoveal ChT was significantly thinner in myopes (mean 303 ± 79 µm) compared to non-myopes (mean 359 ± 77 µm) (p<0.0001). Multiple regression analysis revealed both refractive error (r = 0.39, p<0.001) and age (r = 0.21, p = 0.02) were positively associated with subfoveal ChT. ChT also exhibited significant topographical variations, with the choroid being thicker in more central regions. The thinnest choroid was typically observed in nasal (mean 286 ± 77 µm) and inferior-nasal (306 ± 79 µm) locations, and the thickest in superior (346 ± 79 µm) and superior-temporal (341 ± 74 µm) locations. The difference in ChT between myopic and non-myopic children was significantly greater in central foveal regions compared to more peripheral regions (>3 mm diameter) (p<0.001). Conclusions Myopic children have significantly thinner choroids compared to non-myopic children of similar age, particularly in central foveal regions. The magnitude of difference in choroidal thickness associated with myopia appears greater than would be predicted by a simple passive choroidal thinning with axial elongation.

Estimation of vibration amplitude in Fourier domain optical coherence tomography interferometric signals from Doppler spectrum

In presented method combination of Fourier and Time domain detection enables to broaden the effective bandwidth for time dependent Doppler Signal that allows for using higher-order Bessel functions to calculate unambiguously the vibration amplitudes.

Contours in Motion

My practice-led research explores and maps workflows for generating experimental creative work involving inertia based motion capture technology. Motion capture has often been used as a way to bridge animation and dance resulting in abstracted visuals outcomes. In early works this process was largely done by rotoscoping, reference footage and mechanical forms of motion capture. With the evolution of technology, optical and inertial forms of motion capture are now more accessible and able to accurately capture a larger range of complex movements. The creative work titled “Contours in Motion” was the first in a series of studies on captured motion data used to generating experimental visual forms that reverberate in space and time. With the source or ‘seed’ comes from using an Xsens MVN - Inertial Motion Capture system to capture spontaneous dance movements, with the visual generation conducted through a customised dynamics simulation. The aim of the creative work was to diverge way from a standard practice of using particle system and/or a simple re-targeting of the motion data to drive a 3d character as a means to produce abstracted visual forms. To facilitate this divergence a virtual dynamic object was tether to a selection of data points from a captured performance. The proprieties of the dynamic object were then adjusted to balance the influences from the human movement data with the influence of computer based randomization. The resulting outcome was a visual form that surpassed simple data visualization to project the intent of the performer’s movements into a visual shape itself. The reported outcomes from this investigation have contributed to a larger study on the use of motion capture in the generative arts, furthering the understanding of and generating theories on practice.

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.

Tell me what you see : pre-service teachers' recognition of exemplary digital pedagogy

How do you identify "good" teaching practice in the complexity of a real classroom? How do you know that beginning teachers can recognise effective digital pedagogy when they see it? How can teacher educators see through their students’ eyes? The study in this paper has arisen from our interest in what pre-service teachers “see” when observing effective classroom practice and how this might reveal their own technological, pedagogical and content knowledge. We asked 104 pre-service teachers from Early Years, Primary and Secondary cohorts to watch and comment upon selected exemplary videos of teachers using ICT (information and communication technologies) in Science. The pre-service teachers recorded their observations using a simple PMI (plus, minus, interesting) matrix which were then coded using the SOLO Taxonomy to look for evidence of their familiarity with and judgements of digital pedagogies. From this, we determined that the majority of preservice teachers we surveyed were using a descriptive rather than a reflective strategy, that is, not extending beyond what was demonstrated in the teaching exemplar or differentiating between action and purpose. We also determined that this method warrants wider trialling as a means of evaluating students’ understandings of the complexity of the digital classroom.

The relationship between BCOM1 gene variants and macular pigment optical density in persons with and without age-related macular degeneration

Background: Recent evidence indicates that gene variants related to carotenoid metabolism play a role in the uptake of macular pigments lutein (L) and zeaxanthine (Z). Moreover, these pigments are proposed to reduce the risk for advanced age-related macular degeneration (AMD). This study provides the initial examination of the relationship between the gene variants related to carotenoid metabolism, macular pigment optical density (MPOD) and their combined expression in healthy humans and patients with AMD. Participants and Methods: Forty-four participants were enrolled from a general population and a private practice including 20 healthy participants and 24 patients with advanced (neovascular) AMD. Participants were genotyped for the three single nucleotide polymorphisms (SNPs) upstream from BCMO1, rs11645428, rs6420424 and rs6564851 that have been shown to either up or down regulate beta-carotene conversion efficiency in the plasma. MPOD was determined by heterochromatic flicker photometry. Results: Healthy participants with the rs11645428 GG genotype, rs6420424 AA genotype and rs6564851 GG genotype all had on average significantly lower MPOD compared to those with the other genotypes (p < 0.01 for all three comparisons). When combining BCMO1 genotypes reported to have “high” (rs11645428 AA/rs6420424 GG/rs6564851 TT) and “low” (rs11645428 GG/rs6420424 AA/rs6564851 GG) beta-carotene conversion efficiency, we demonstrate clear differences in MPOD values (p<0.01). In patients with AMD there were no significant differences in MPOD for any of the three BCMO1 gene variants. Conclusion: In healthy participants MPOD levels can be related to high and low beta-carotene conversion BCMO1 genotypes. Such relationships were not found in patients with advanced neovascular AMD, indicative of additional processes influencing carotenoid uptake, possibly related to other AMD susceptibility genes. Our findings indicate that specific BCMO1 SNPs should be determined when assessing the effects of carotenoid supplementation on macular pigment and that their expression may be influenced by retinal disease.

Development of optical ray tracing model of a standard parabolic trough collector

Parabolic trough concentrator collector is the most matured, proven and widespread technology for the exploitation of the solar energy on a large scale for middle temperature applications. The assessment of the opportunities and the possibilities of the collector system are relied on its optical performance. A reliable Monte Carlo ray tracing model of a parabolic trough collector is developed by using Zemax software. The optical performance of an ideal collector depends on the solar spectral distribution and the sunshape, and the spectral selectivity of the associated components. Therefore, each step of the model, including the spectral distribution of the solar energy, trough reflectance, glazing anti-reflection coating and the absorber selective coating is explained and verified. Radiation flux distribution around the receiver, and the optical efficiency are two basic aspects of optical simulation are calculated using the model, and verified with widely accepted analytical profile and measured values respectively. Reasonably very good agreement is obtained. Further investigations are carried out to analyse the characteristics of radiation distribution around the receiver tube at different insolation, envelop conditions, and selective coating on the receiver; and the impact of scattered light from the receiver surface on the efficiency. However, the model has the capability to analyse the optical performance at variable sunshape, tracking error, collector imperfections including absorber misalignment with focal line and de-focal effect of the absorber, different rim angles, and geometric concentrations. The current optical model can play a significant role in understanding the optical aspects of a trough collector, and can be employed to extract useful information on the optical performance. In the long run, this optical model will pave the way for the construction of low cost standalone photovoltaic and thermal hybrid collector in Australia for small scale domestic hot water and electricity production.

Optical coupling of Au nanoparticles on vertical graphenes to maximize SERS response

Gold particle interaction with few-layer graphenes is of interest for the development of numerous optical nanodevices. The results of numerical studies of the coupling of gold nanoparticles with few-layer vertical graphene sheets are presented. The field strengths are computed and the optimum nanoparticle configurations for the formation of SERS hotpots are obtained. The nanoparticles are modeled as 8 nm diameter spheres atop 1.5 nm (5 layers) graphene sheet. The vertical orientation is of particular interest as it is possible to use both sides of the graphene structure and potentially double the number of particles in the system. Our results show that with the addition of an opposing particle a much stronger signal can be obtained as well as the particle separation can be controlled by the number of atomic carbon layers. These results provide further insights and contribute to the development of next-generation plasmonic devices based on nanostructures with hybrid dimensionality.

The salt dependence of DNA recognition by NF-kappaB p50 : a detailed kinetic analysis of the effects on affinityand specificity

The binding kinetics of NF-kappaB p50 to the Ig-kappaB site and to a DNA duplex with no specific binding site were determined under varying conditions of potassium chloride concentration using a surface plasmonresonance biosensor. Association and dissociation rate constants were measured enabling calculation of the dissociation constants. Under previously established high affinity buffer conditions, the k a for both sequences was in the order of 10(7) M-1s-1whilst the k d values varied 600-fold in a sequence-dependent manner between 10(-1) and 10(-4 )s-1, suggesting that the selectivity of p50 for different sequences is mediated primarily through sequence-dependent dissociation rates. The calculated K D value for the Ig-kappaB sequence was 16 pM, whilst the K D for the non-specific sequence was 9.9 nM. As the ionic strength increased to levels which are closer to that of the cellular environment, the binding of p50 to the non-specific sequence was abolished whilst the specific affinity dropped to nanomolar levels. From these results, a mechanism is proposed in which p50 binds specific sequences with high affinity whilst binding non-specific sequences weakly enough to allow efficient searching of the DNA.

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.

Random Gabor based templates for facial expression recognition in images with facial occlusion

Robust facial expression recognition (FER) under occluded face conditions is challenging. It requires robust algorithms of feature extraction and investigations into the effects of different types of occlusion on the recognition performance to gain insight. Previous FER studies in this area have been limited. They have spanned recovery strategies for loss of local texture information and testing limited to only a few types of occlusion and predominantly a matched train-test strategy. This paper proposes a robust approach that employs a Monte Carlo algorithm to extract a set of Gabor based part-face templates from gallery images and converts these templates into template match distance features. The resulting feature vectors are robust to occlusion because occluded parts are covered by some but not all of the random templates. The method is evaluated using facial images with occluded regions around the eyes and the mouth, randomly placed occlusion patches of different sizes, and near-realistic occlusion of eyes with clear and solid glasses. Both matched and mis-matched train and test strategies are adopted to analyze the effects of such occlusion. Overall recognition performance and the performance for each facial expression are investigated. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the high robustness and fast processing speed of our approach, and provide useful insight into the effects of occlusion on FER. The results on the parameter sensitivity demonstrate a certain level of robustness of the approach to changes in the orientation and scale of Gabor filters, the size of templates, and occlusions ratios. Performance comparisons with previous approaches show that the proposed method is more robust to occlusion with lower reductions in accuracy from occlusion of eyes or mouth.

Automated species recognition in environmental recordings

Faunal vocalisations are vital indicators for environmental change and faunal vocalisation analysis can provide information for answering ecological questions. Therefore, automated species recognition in environmental recordings has become a critical research area. This thesis presents an automated species recognition approach named Timed and Probabilistic Automata. A small lexicon for describing animal calls is defined, six algorithms for acoustic component detection are developed, and a series of species recognisers are built and evaluated.The presented automated species recognition approach yields significant improvement on the analysis performance over a real world dataset, and may be transferred to commercial software in the future.

Identification of Mendel's white flower character

Background The genetic regulation of flower color has been widely studied, notably as a character used by Mendel and his predecessors in the study of inheritance in pea. Methodology/Principal Findings We used the genome sequence of model legumes, together with their known synteny to the pea genome to identify candidate genes for the A and A2 loci in pea. We then used a combination of genetic mapping, fast neutron mutant analysis, allelic diversity, transcript quantification and transient expression complementation studies to confirm the identity of the candidates. Conclusions/Significance We have identified the pea genes A and A2. A is the factor determining anthocyanin pigmentation in pea that was used by Gregor Mendel 150 years ago in his study of inheritance. The A gene encodes a bHLH transcription factor. The white flowered mutant allele most likely used by Mendel is a simple G to A transition in a splice donor site that leads to a mis-spliced mRNA with a premature stop codon, and we have identified a second rare mutant allele. The A2 gene encodes a WD40 protein that is part of an evolutionarily conserved regulatory complex.

Physical activity recognition from accelerometer data using a multi-scale ensemble method

Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.

All-environment visual place recognition with SMART

This paper presents Sequence Matching Across Route Traversals (SMART); a generally applicable sequence-based place recognition algorithm. SMART provides invariance to changes in illumination and vehicle speed while also providing moderate pose invariance and robustness to environmental aliasing. We evaluate SMART on vehicles travelling at highly variable speeds in two challenging environments; firstly, on an all-terrain vehicle in an off-road, forest track and secondly, using a passenger car traversing an urban environment across day and night. We provide comparative results to the current state-of-the-art SeqSLAM algorithm and investigate the effects of altering SMART’s image matching parameters. Additionally, we conduct an extensive study of the relationship between image sequence length and SMART’s matching performance. Our results show viable place recognition performance in both environments with short 10-metre sequences, and up to 96% recall at 100% precision across extreme day-night cycles when longer image sequences are used.