Issues in autonomous navigation of underground vehicles

This paper describes current research at the Australian Centre for Field Robotics (ACFR) in collaboration with the Commonwealth Scientific and Industrial Research Organisation (CSIRO) within the Cooperative Research Centre (CRC) for Mining Technology and Equipment (CMTE) towards achieving autonomous navigation of underground vehicles, like a Load-Haul-Dump (LHD) truck. This work is being sponsored by the mining industry through the Australian Mineral Industries Research Association Limited (AMIRA). Robust and reliable autonomous navigation can only be realised by achieving high level tasks such as path-planning and obstacle avoidance. This requires determining the pose (position and orientation) of the vehicle at all times. A minimal infrastructure localisation algorithm that has been developed for this purpose is outlined and the corresponding results are presented. Further research issues that are under investigation are also outlined briefly.

Product stability and sequestration mechanisms in Solanum tuberosum engineered to biosynthesize high value ketocarotenoids

To produce commercially valuable ketocarotenoids in Solanum tuberosum, the 4, 4′ β-oxygenase (crtW) and 3, 3′ β-hydroxylase (crtZ) genes from Brevundimonas spp. have been expressed in the plant host under constitutive transcriptional control. The CRTW and CRTZ enzymes are capable of modifying endogenous plant carotenoids to form a range of hydroxylated and ketolated derivatives. The host (cv. Désirée) produced significant levels of nonendogenous carotenoid products in all tissues, but at the apparent expense of the economically critical metabolite, starch. Carotenoid levels increased in both wild-type and transgenic tubers following cold storage; however, stability during heat processing varied between compounds. Subcellular fractionation of leaf tissues revealed the presence of ketocarotenoids in thylakoid membranes, but not predominantly in the photosynthetic complexes. A dramatic increase in the carotenoid content of plastoglobuli was determined. These findings were corroborated by microscopic analysis of chloroplasts. In tuber tissues, esterified carotenoids, representing 13% of the total pigment found in wild-type extracts, were sequestered in plastoglobuli. In the transgenic tubers, this proportion increased to 45%, with esterified nonendogenous carotenoids in place of endogenous compounds. Conversely, nonesterified carotenoids in both wild-type and transgenic tuber tissues were associated with amyloplast membranes and starch granules.

From ImageNet to mining: Adapting visual object detection with minimal supervision

This paper presents visual detection and classification of light vehicles and personnel on a mine site.We capitalise on the rapid advances of ConvNet based object recognition but highlight that a naive black box approach results in a significant number of false positives. In particular, the lack of domain specific training data and the unique landscape in a mine site causes a high rate of errors. We exploit the abundance of background-only images to train a k-means classifier to complement the ConvNet. Furthermore, localisation of objects of interest and a reduction in computation is enabled through region proposals. Our system is tested on over 10km of real mine site data and we were able to detect both light vehicles and personnel. We show that the introduction of our background model can reduce the false positive rate by an order of magnitude.

Automatic image scaling for place recognition in changing environments

Robustness to variations in environmental conditions and camera viewpoint is essential for long-term place recognition, navigation and SLAM. Existing systems typically solve either of these problems, but invariance to both remains a challenge. This paper presents a training-free approach to lateral viewpoint- and condition-invariant, vision-based place recognition. Our successive frame patch-tracking technique infers average scene depth along traverses and automatically rescales views of the same place at different depths to increase their similarity. We combine our system with the condition-invariant SMART algorithm and demonstrate place recognition between day and night, across entire 4-lane-plus-median-strip roads, where current algorithms fail.

EphB4 localises to the nucleus of prostate cancer cells

The EphB4 receptor tyrosine kinase is over-expressed in a variety of different epithelial cancers including prostate where it has been shown to be involved in survival, migration and angiogenesis. We report here that EphB4 also resides in the nucleus of prostate cancer cell lines. We used in silico methods to identify a bipartite nuclear localisation signal (NLS) in the extracellular domain and a monopartite NLS sequence in the intracellular kinase domain of EphB4. To determine whether both putative NLS sequences were functional, fragments of the EphB4 sequence containing each NLS were cloned to create EphB4NLS-GFP fusion proteins. Localisation of both NLS-GFP proteins to the nuclei of transfected cells was observed, demonstrating that EphB4 contains two functional NLS sequences. Mutation of the key amino residues in both NLS sequences resulted in diminished nuclear accumulation. As nuclear translocation is often dependent on importins we confirmed that EphB4 and importin-α can interact. To assess if nuclear EphB4 could be implicated in gene regulatory functions potential EphB4-binding genomic loci were identified using chromatin immunoprecipitation and Lef1 was confirmed as a potential target of EphB4-mediated gene regulation. These novel findings add further complexity to the biology of this important cancer-associated receptor.

Searching for people using semantic soft biometric descriptions

It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to communicate and easy to understand. However such queries are not easily utilised within intelligent video surveillance systems, as they are difficult to transform into a representation that can be utilised by computer vision algorithms. In this paper we propose a novel approach that transforms such a semantic query into an avatar in the form of a channel representation that is searchable within a video stream. We show how spatial, colour and prior information (person shape) can be incorporated into the channel representation to locate a target using a particle-filter like approach. We demonstrate state-of-the-art performance for locating a subject in video based on a description, achieving a relative performance improvement of 46.7% over the baseline. We also apply this approach to person re-detection, and show that the approach can be used to re-detect a person in a video steam without the use of person detection.

Finding the leverage point in the sustainability crisis: Global, national and regional Australian responses

From an economic perspective, the sustainability crisis is ultimately characterized by a worsening relationship between the resources required to support the global population and the ability of the earth to supply them. Despite the ever-increasing threat of a calamity, modern society appears unable to alter its course. The very systems which underpin global human endeavor seem to actively prevent meaningful change and the one irrepressible goal to which all societies seem to strive is the very thing that makes such endeavor ultimately life threatening: that of global growth. Using the Australian experience as an exemplar, this paper explores how the concept of growth infiltrates societal reactions to the crisis at various scales – global, national and regional. Analysis includes historic studies, a critique of current misconceptions around population demographics, comparative evaluation of various interventions in the Australian context and considerations around potential ways to address the crisis.

Genetic, functional, and histopathological evaluation of two C-terminal BRCA1 missense variants

Background: The vast majority of BRCA1 missense sequence variants remain uncharacterised for their possible effect on protein expression and function, and therefore are unclassified in terms of their pathogenicity. BRCA1 plays diverse cellular roles and it is unlikely that any single functional assay will accurately reflect the total cellular implications of missense mutations in this gene. Objective: To elucidate the effect of two BRCA1 variants, 5236G>C (G1706A) and 5242C>A (A1708E) on BRCA1 function, and to survey the relative usefulness of several assays to direct the characterisation of other unclassified variants in BRCA genes. Methods and Results: Data from a range of bioinformatic, genetic, and histopathological analyses, and in vitro functional assays indicated that the 1708E variant was associated with the disruption of different cellular functions of BRCA1. In transient transfection experiments in T47D and 293T cells, the 1708E product was mislocalised to the cytoplasm and induced centrosome amplification in 293T cells. The 1708E variant also failed to transactivate transcription of reporter constructs in mammalian transcriptional transactivation assays. In contrast, the 1706A variant displayed a phenotype comparable to wildtype BRCA1 in these assays. Consistent with functional data, tumours from 1708E carriers showed typical BRCA1 pathology, while tumour material from 1706A carriers displayed few histopathological features associated with BRCA1 related tumours. Conclusions: A comprehensive range of genetic, bioinformatic, and functional analyses have been combined for the characterisation of BRCA1 unclassified sequence variants. Consistent with the functional analyses, the combined odds of causality calculated for the 1706A variant after multifactorial likelihood analysis (1:142) indicates a definitive classification of this variant as "benign". In contrast, functional assays of the 1708E variant indicate that it is pathogenic, possibly through subcellular mislocalisation. However, the combined odds of 262:1 in favour of causality of this variant does not meet the minimal ratio of 1000:1 for classification as pathogenic, and A1708E remains formally designated as unclassified. Our findings highlight the importance of comprehensive genetic information, together with detailed functional analysis for the definitive categorisation of unclassified sequence variants. This combination of analyses may have direct application to the characterisation of other unclassified variants in BRCA1 and BRCA2.

Comparative proteomics of uropathogenic Escherichia coli during growth in human urine identify UCA-like (UCL) fimbriae as an adherence factor involved in biofilm formation and binding to uroepithelial cells

Uropathogenic Escherichia coli (UPEC) are the primary cause of urinary tract infection (UTI) in humans. For the successful colonisation of the human urinary tract, UPEC employ a diverse collection of secreted or surface-exposed virulence factors including toxins, iron acquisition systems and adhesins. In this study, a comparative proteomic approach was utilised to define the UPEC pan and core surface proteome following growth in pooled human urine. Identified proteins were investigated for subcellular origin, prevalence and homology to characterised virulence factors. Fourteen core surface proteins were identified, as well as eleven iron uptake receptor proteins and four distinct fimbrial types, including type 1, P, F1C/S and a previously uncharacterised fimbrial type, designated UCA-like (UCL) fimbriae in this study. These pathogenicity island (PAI)-associated fimbriae are related to UCA fimbriae of Proteus mirabilis, associated with UPEC and exclusively found in members of the E. coli B2 and D phylogroup. We further demonstrated that UCL fimbriae promote significant biofilm formation on abiotic surfaces and mediate specific attachment to exfoliated human uroepithelial cells. Combined, this study has defined the surface proteomic profiles and core surface proteome of UPEC during growth in human urine and identified a new type of fimbriae that may contribute to UTI.

Comparative analysis of the uropathogenic Escherichia coli surface proteome by tandem mass-spectrometry of artificially induced outer membrane vesicles

Uropathogenic Escherichia coli (UPEC) are the major cause of urinary tract infections. For successful colonisation of the urinary tract, UPEC employ multiple surface-exposed or secreted virulence factors, including adhesins and iron uptake systems. Whilst individual UPEC strains and their virulence factors have been the focus of extensive research, there have been no outer membrane (OM) proteomic studies based on large clinical UPEC collections, primarily due to limitations of traditional methods. In this study, a high-throughput method based on tandem mass-spectrometry of EDTA heat-induced outer membrane vesicles (OMVs) was developed for the characterisation of the UPEC surface-associated proteome. The method was applied to compare the OM proteome of fifty-four UPEC isolates, resulting in the identification of 8789 proteins, consisting of 619 unique proteins, which were subsequently interrogated for their subcellular origin, prevalence and homology to characterised virulence factors. Multiple distinct virulence-associated proteins were identified, including two novel putative iron uptake proteins, an uncharacterised type of chaperone-usher fimbriae and various highly prevalent hypothetical proteins. Our results give fundamental insight into the physiology of UPEC and provide a framework for understanding the composition of the UPEC OM proteome.

Repeatable Condition-Invariant Visual Odometry for Sequence-Based Place Recognition

This paper describes a vision-only system for place recognition in environments that are tra- versed at different times of day, when chang- ing conditions drastically affect visual appear- ance, and at different speeds, where places aren’t visited at a consistent linear rate. The ma- jor contribution is the removal of wheel-based odometry from the previously presented algo- rithm (SMART), allowing the technique to op- erate on any camera-based device; in our case a mobile phone. While we show that the di- rect application of visual odometry to our night- time datasets does not achieve a level of perfor- mance typically needed, the VO requirements of SMART are orthogonal to typical usage: firstly only the magnitude of the velocity is required, and secondly the calculated velocity signal only needs to be repeatable in any one part of the environment over day and night cycles, but not necessarily globally consistent. Our results show that the smoothing effect of motion constraints is highly beneficial for achieving a locally consis- tent, lighting-independent velocity estimate. We also show that the advantage of our patch-based technique used previously for frame recogni- tion, surprisingly, does not transfer to VO, where SIFT demonstrates equally good performance. Nevertheless, we present the SMART system us- ing only vision, which performs sequence-base place recognition in extreme low-light condi- tions where standard 6-DOF VO fails and that improves place recognition performance over odometry-less benchmarks, approaching that of wheel odometry.

Decentralised key management for delay tolerant networks

Public key authentication is the verification of the identity-public key binding, and is foundational to the security of any network. The contribution of this thesis has been to provide public key authentication for a decentralised and resource challenged network such as an autonomous Delay Tolerant Network (DTN). It has resulted in the development and evaluation of a combined co-localisation trust system and key distribution scheme evaluated on a realistic large geographic scale mobility model. The thesis also addresses the problem of unplanned key revocation and replacement without any central authority.