Nonlinear analysis of plastic ball grid array solder joints

A nonlinear finite element analysis was carried out to investigate the viscoplastic deformation of solder joints in a ball grid array (BGA) package under temperature cycle. The effects of constraint on print circuit board (PCB) and stiffness of substrate on the deformation behaviour of the solder joints were also studied. A relative damage stress was adopted to analyze the potential failure sites in the solder joints. The results indicated that high inelastic strain and strain energy density were developed in the joints close to the package center. On the other hand, high constraint and high relative damage stress were associated with the joint closest to the edge of the silicon chip. The joint closest to the edge of the silicon chip was regarded as the most susceptible failure site if cavitation instability is the dominant failure mechanism. Increase the external constraint on the print circuit board (PCB) causes a slight increase in stress triaxiality (m/eq) and relative damage stress in the joint closest to the edge of silicon die. The relative damage stress is not sensitive to the Young’s modulus of the substrate.

Acacia Light Wall

The Acacia Light Wall is a permanent public artwork within the 3 stage Eden on the Yarra – a residential / commercial development on Victoria Street Abbotsford, Melbourne. The work was commissioned by the Hampton Group for Acacia Place, the first building in the development. The stylised screen was inspired by tangled wattle trees (Australia’s most common Acacia). The work consists of two walls, made from laser cut aluminium screen, acrylic ‘windows” Philips Colour Kinetic controllable LED (1250 nodes), Philips Colour Kinetics control ‘iPlayers”. One wall is 10 m long x 3 to 5 metres and the second is 12m by 3m. The windows are lit by an array of 600+ LED’s in each wall. These lights change colour from week to week marking the progress of the seasons. We worked with the project horticulturalist to develop a palate of colours for each week’s ‘light show’ that was drawn from local flowers and foliage likely to be in bloom that week. The lighting display is not static but rather a very slow moving (morphing) light show. It isn’t fast and flashy. Instead it’s restful and profound.

Residential balconies with road traffic noise : a combined source image and radiosity model

Several significant studies have been made in recent decades toward understanding road traffic noise and its effects on residential balconies. These previous studies have used a variety of techniques such as theoretical models, scale models and measurements on real balconies. The studies have considered either road traffic noise levels within the balcony space or inside an adjacent habitable room or both. Previous theoretical models have used, for example, simplified specular reflection calculations, boundary element methods (BEM), adaptations of CoRTN or the use of Sabine Theory. This paper presents an alternative theoretical model to predict the effects of road traffic noise spatially within the balcony space. The model includes a specular reflection component by calculating up to 10 orders of source images. To account for diffusion effects, a two compartment radiosity component is utilised. The first radiosity compartment is the urban street, represented as a street with building facades on either side. The second radiosity compartment is the balcony space. The model is designed to calculate the predicted road traffic noise levels within the balcony space and is capable of establishing the effect of changing street and balcony geometries. Screening attenuation algorithms are included to determine the effects of solid balcony parapets and balcony ceiling shields.

Dark Cartographies

‘Dark Cartographies’ is a slowly evolving meditation upon seasonal change, life after light and the occluding shadows of human influence. Through creating experiences of the many ‘times of a night’ the work allows participants to experience deep engagement with rich spectras of hidden place and sound. By amplifying and shining light upon a myriad of lives lived in blackness, ‘Dark Cartographies’ tempts us to re-understand seasonal change as actively-embodied temporality, inflected by our climate-changing disturbances. ‘Dark Cartographies’ uses custom interactive systems, illusionary techniques and real time spatial audio that draw upon a rich array of media, including seasonal, nocturnal field recordings sourced in the Far North Queensland region and detailed observations of foliage & flowering phases. By drawing inspiration from the subtle transitions between what Europeans named ‘Summer’ and ‘Autumn’, and by including the body and its temporal disturbances within the work, ‘Dark Cartographies’ creates compellingly immersive environments that wrap us in atmospheres beyond sight and hearing. ‘Dark Cartographies’ is a dynamic new installation directed & choreographed by environmental cycles; alluding to a new framework for making works that we call ‘Seasonal’. This powerful, responsive & experiential work draws 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.

Night Rage/ Night Fall

A new form of media installation combining image, multi-channel sound and internally lit objects into a mysterious, deep image plane. Staged on the very edge of spectrum blackout, and moving into the deep of night, Version 1 (Night Rage) for ISEA 2013 examined the many shades of 'nocturnal', threats to night biodiversity and the myriad myths and stories that have shaped our cultural understandings of life after light. Barely recognisable images float within landscapes of media, noise and sound as the work asserts a profound resistance to today's all consuming media mesh. Version 2 (Night Fall) for the Queensland State Museum examined contemporary ideas around the ‘night’ and the 'nocturnal'. Beginning with the dark myths and stories that have long shaped our cultural understandings of life after light, NIGHT FALL considers how fearful ideas have often underpinned actions that continue to reduce Australia’s extraordinary night biodiversity. Today’s growing hostility towards Australia’s ancient, iconic flying foxes - who have been quietly pollinating our forests for millennia - hints at just how far we have yet to travel in our thinking. Enter the darkened tunnel to experience mysterious, edge-of-perception 3D forms, enhanced by a range of cinematic, illusionary and animatronic techniques, and become immersed in a strangely familiar sound track based upon seasonal field recordings made after dark, sourced from across the eastern coast of Queensland.

Genome-wide SNP detection, validation, and development of an 8K SNP array for apple

As high-throughput genetic marker screening systems are essential for a range of genetics studies and plant breeding applications, the International RosBREED SNP Consortium (IRSC) has utilized the Illumina Infinium® II system to develop a medium- to high-throughput SNP screening tool for genome-wide evaluation of allelic variation in apple (Malus×domestica) breeding germplasm. For genome-wide SNP discovery, 27 apple cultivars were chosen to represent worldwide breeding germplasm and re-sequenced at low coverage with the Illumina Genome Analyzer II. Following alignment of these sequences to the whole genome sequence of 'Golden Delicious', SNPs were identified using SoapSNP. A total of 2,113,120 SNPs were detected, corresponding to one SNP to every 288 bp of the genome. The Illumina GoldenGate® assay was then used to validate a subset of 144 SNPs with a range of characteristics, using a set of 160 apple accessions. This validation assay enabled fine-tuning of the final subset of SNPs for the Illumina Infinium® II system. The set of stringent filtering criteria developed allowed choice of a set of SNPs that not only exhibited an even distribution across the apple genome and a range of minor allele frequencies to ensure utility across germplasm, but also were located in putative exonic regions to maximize genotyping success rate. A total of 7867 apple SNPs was established for the IRSC apple 8K SNP array v1, of which 5554 were polymorphic after evaluation in segregating families and a germplasm collection. This publicly available genomics resource will provide an unprecedented resolution of SNP haplotypes, which will enable marker-locus-trait association discovery, description of the genetic architecture of quantitative traits, investigation of genetic variation (neutral and functional), and genomic selection in apple.

Random projections on manifolds of symmetric positive definite matrices for image classification

Recent advances suggest that encoding images through Symmetric Positive Definite (SPD) matrices and then interpreting such matrices as points on Riemannian manifolds can lead to increased classification performance. Taking into account manifold geometry is typically done via (1) embedding the manifolds in tangent spaces, or (2) embedding into Reproducing Kernel Hilbert Spaces (RKHS). While embedding into tangent spaces allows the use of existing Euclidean-based learning algorithms, manifold shape is only approximated which can cause loss of discriminatory information. The RKHS approach retains more of the manifold structure, but may require non-trivial effort to kernelise Euclidean-based learning algorithms. In contrast to the above approaches, in this paper we offer a novel solution that allows SPD matrices to be used with unmodified Euclidean-based learning algorithms, with the true manifold shape well-preserved. Specifically, we propose to project SPD matrices using a set of random projection hyperplanes over RKHS into a random projection space, which leads to representing each matrix as a vector of projection coefficients. Experiments on face recognition, person re-identification and texture classification show that the proposed approach outperforms several recent methods, such as Tensor Sparse Coding, Histogram Plus Epitome, Riemannian Locality Preserving Projection and Relational Divergence Classification.

Matching image sets via adaptive multi convex hull

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.

Improved image set classification via joint sparse approximated nearest subspaces

Existing multi-model approaches for image set classification extract local models by clustering each image set individually only once, with fixed clusters used for matching with other image sets. However, this may result in the two closest clusters to represent different characteristics of an object, due to different undesirable environmental conditions (such as variations in illumination and pose). To address this problem, we propose to constrain the clustering of each query image set by forcing the clusters to have resemblance to the clusters in the gallery image sets. We first define a Frobenius norm distance between subspaces over Grassmann manifolds based on reconstruction error. We then extract local linear subspaces from a gallery image set via sparse representation. For each local linear subspace, we adaptively construct the corresponding closest subspace from the samples of a probe image set by joint sparse representation. We show that by minimising the sparse representation reconstruction error, we approach the nearest point on a Grassmann manifold. Experiments on Honda, ETH-80 and Cambridge-Gesture datasets show that the proposed method consistently outperforms several other recent techniques, such as Affine Hull based Image Set Distance (AHISD), Sparse Approximated Nearest Points (SANP) and Manifold Discriminant Analysis (MDA).

Staurosporine augments EGF-mediated EMT in PMC42-LA cells through actin depolymerisation, focal contact size reduction and Snail1 induction : a model for cross-modulation

Background A feature of epithelial to mesenchymal transition (EMT) relevant to tumour dissemination is the reorganization of actin cytoskeleton/focal contacts, influencing cellular ECM adherence and motility. This is coupled with the transcriptional repression of E-cadherin, often mediated by Snail1, Snail2 and Zeb1/δEF1. These genes, overexpressed in breast carcinomas, are known targets of growth factor-initiated pathways, however it is less clear how alterations in ECM attachment cross-modulate to regulate these pathways. EGF induces EMT in the breast cancer cell line PMC42-LA and the kinase inhibitor staurosporine (ST) induces EMT in embryonic neural epithelial cells, with F-actin de-bundling and disruption of cell-cell adhesion, via inhibition of aPKC. Methods PMC42-LA cells were treated for 72 h with 10 ng/ml EGF, 40 nM ST, or both, and assessed for expression of E-cadherin repressor genes (Snail1, Snail2, Zeb1/δEF1) and EMT-related genes by QRT-PCR, multiplex tandem PCR (MT-PCR) and immunofluorescence +/- cycloheximide. Actin and focal contacts (paxillin) were visualized by confocal microscopy. A public database of human breast cancers was assessed for expression of Snail1 and Snail2 in relation to outcome. Results When PMC42-LA were treated with EGF, Snail2 was the principal E-cadherin repressor induced. With ST or ST+EGF this shifted to Snail1, with more extreme EMT and Zeb1/δEF1 induction seen with ST+EGF. ST reduced stress fibres and focal contact size rapidly and independently of gene transcription. Gene expression analysis by MT-PCR indicated that ST repressed many genes which were induced by EGF (EGFR, CAV1, CTGF, CYR61, CD44, S100A4) and induced genes which alter the actin cytoskeleton (NLF1, NLF2, EPHB4). Examination of the public database of breast cancers revealed tumours exhibiting higher Snail1 expression have an increased risk of disease-recurrence. This was not seen for Snail2, and Zeb1/δEF1 showed a reverse correlation with lower expression values being predictive of increased risk. Conclusion ST in combination with EGF directed a greater EMT via actin depolymerisation and focal contact size reduction, resulting in a loosening of cell-ECM attachment along with Snail1-Zeb1/δEF1 induction. This appeared fundamentally different to the EGF-induced EMT, highlighting the multiple pathways which can regulate EMT. Our findings add support for a functional role for Snail1 in invasive breast cancer.

Image-guided sampling reveals increased stroma and lower glandular complexity in mammographically dense breast tissue

Mammographic density (MD) adjusted for age and body mass index (BMI) is a strong heritable breast cancer risk factor; however, its biological basis remains elusive. Previous studies assessed MD-associated histology using random sampling approaches, despite evidence that high and low MD areas exist within a breast and are negatively correlated with respect to one another. We have used an image-guided approach to sample high and low MD tissues from within individual breasts to examine the relationship between histology and degree of MD. Image-guided sampling was performed using two different methodologies on mastectomy tissues (n = 12): (1) sampling of high and low MD regions within a slice guided by bright (high MD) and dark (low MD) areas in a slice X-ray film; (2) sampling of high and low MD regions within a whole breast using a stereotactically guided vacuum-assisted core biopsy technique. Pairwise analysis accounting for potential confounders (i.e. age, BMI, menopausal status, etc.) provides appropriate power for analysis despite the small sample size. High MD tissues had higher stromal (P = 0.002) and lower fat (P = 0.002) compositions, but no evidence of difference in glandular areas (P = 0.084) compared to low MD tissues from the same breast. High MD regions had higher relative gland counts (P = 0.023), and a preponderance of Type I lobules in high MD compared to low MD regions was observed in 58% of subjects (n = 7), but did not achieve significance. These findings clarify the histologic nature of high MD tissue and support hypotheses regarding the biophysical impact of dense connective tissue on mammary malignancy. They also provide important terms of reference for ongoing analyses of the underlying genetics of MD.

Joint 2D and 3D cues for image segmentation towards robotic applications

This thesis investigates the fusion of 3D visual information with 2D image cues to provide 3D semantic maps of large-scale environments in which a robot traverses for robotic applications. A major theme of this thesis was to exploit the availability of 3D information acquired from robot sensors to improve upon 2D object classification alone. The proposed methods have been evaluated on several indoor and outdoor datasets collected from mobile robotic platforms including a quadcopter and ground vehicle covering several kilometres of urban roads.

Studies on the in-plane shear response of confined masonry shear walls

The prime aim of this research project is to evaluate the performance of confined masonry walls under in-plane shear with a view to contributing to the national masonry design standard through a set of design clauses. This aim stems from the criticisms of the current provisions of the in-plane shear capacity equations in the Australian Masonry Standard AS3700 (2011) being highly non-conservative. This PhD thesis is an attempt to address this gap in the knowledge through systematic investigation of the key parameters that affects the in-plane shear strength of the masonry walls through laboratory experiments and extensive finite element analyses.

Numerical investigation on stable crack growth in plane stress

Large deformation finite element analysis has been carried out to investigate the stress-strain fields ahead of a growing crack for compact tension .a=W D 0:5/ and three-point bend .a=W D 0:1 and 0:5/ specimens under plane stress condition. The crack growth is controlled by the experimental J -integral resistance curves measured by Sun et al. The results indicate that the distributions of opening stress, equivalent stress and equivalent strain ahead of a growing crack are not sensitive to specimen geometry. For both stationary and growing cracks, similar distributions of opening stress and triaxiality can be found along the ligament. During stable crack growth, the crack-tip opening displacement (CTOD) resistance curve and the cohesive fracture energy in the fracture process zone are independent of specimen geometry and may be suitable criteria for characterizing stable crack growth in plane stress.

Involvement of focal adhesion kinase in inhibition of motility of human breast cancer cells by sphingosine 1-phosphate

Sphingosine 1-phosphate (SPP), a bioactive sphingolipid metabolite, inhibits chemoinvasiveness of the aggressive, estrogen-independent MDA-MB-231 human breast cancer cell line. As in many other cell types, SPP stimulated proliferation of MDA-MB-231 cells, albeit to a lesser extent. Treatment of MDA-MB-231 cells with SPP had no significant effect on their adhesiveness to Matrigel, and only high concentrations of SPP partially inhibited matrix metalloproteinase-2 activation induced by Con A. However, SPP at a concentration that strongly inhibited invasiveness also markedly reduced chemotactic motility. To investigate the molecular mechanisms by which SPP interferes with cell motility, we examined tyrosine phosphorylation of focal adhesion kinase (FAK) and paxillin, which are important for organization of focal adhesions and cell motility. SPP rapidly increased tyrosine phosphorylation of FAK and paxillin and of the paxillin-associated protein Crk. Overexpression of FAK and kinase-defective FAK in MDA-MB-231 cells resulted in a slight increase in motility without affecting the inhibitory effect of SPP, whereas expression of FAK with a mutation of the major autophosphorylation site (F397) abolished the inhibitory effect of SPP on cell motility. In contrast, the phosphoinositide 3'-kinase inhibitor, wortmannin, inhibited chemotactic motility in both vector and FAK-F397- transfected cells. Our results suggest that autophosphorylation of FAK on Y397 may play an important role in SPP signaling leading to decreased cell motility.