Optimisation of Banana streak virus (BSV) diagnostic assays

Bananas are one of the world�fs most important crops, serving as a staple food and an important source of income for millions of people in the subtropics. Pests and diseases are a major constraint to banana production. To prevent the spread of pests and disease, farmers are encouraged to use disease�] and insect�]free planting material obtained by micropropagation. This option, however, does not always exclude viruses and concern remains on the quality of planting material. Therefore, there is a demand for effective and reliable virus indexing procedures for tissue culture (TC) material. Reliable diagnostic tests are currently available for all of the economically important viruses of bananas with the exception of Banana streak viruses (BSV, Caulimoviridae, Badnavirus). Development of a reliable diagnostic test for BSV is complicated by the significant serological and genetic variation reported for BSV isolates, and the presence of endogenous BSV (eBSV). Current PCR�] and serological�]based diagnostic methods for BSV may not detect all species of BSV, and PCR�]based methods may give false positives because of the presence of eBSV. Rolling circle amplification (RCA) has been reported as a technique to detect BSV which can also discriminate between episomal and endogenous BSV sequences. However, the method is too expensive for large scale screening of samples in developing countries, and little information is available regarding its sensitivity. Therefore the development of reliable PCR�]based assays is still considered the most appropriate option for large scale screening of banana plants for BSV. This MSc project aimed to refine and optimise the protocols for BSV detection, with a particular focus on developing reliable PCR�]based diagnostics Initially, the appropriateness and reliability of PCR and RCA as diagnostic tests for BSV detection were assessed by testing 45 field samples of banana collected from nine districts in the Eastern region of Uganda in February 2010. This research was also aimed at investigating the diversity of BSV in eastern Uganda, identifying the BSV species present and characterising any new BSV species. Out of the 45 samples tested, 38 and 40 samples were considered positive by PCR and RCA, respectively. Six different species of BSV, namely Banana streak IM virus (BSIMV), Banana streak MY virus (BSMYV), Banana streak OL virus (BSOLV), Banana streak UA virus (BSUAV), Banana streak UL virus (BSULV), Banana streak UM virus (BSUMV), were detected by PCR and confirmed by RCA and sequencing. No new species were detected, but this was the first report of BSMYV in Uganda. Although RCA was demonstrated to be suitable for broad�]range detection of BSV, it proved time�]consuming and laborious for identification in field samples. Due to the disadvantages associated with RCA, attempts were made to develop a reliable PCR�]based assay for the specific detection of episomal BSOLV, Banana streak GF virus (BSGFV), BSMYV and BSIMV. For BSOLV and BSGFV, the integrated sequences exist in rearranged, repeated and partially inverted portions at their site of integration. Therefore, for these two viruses, primers sets were designed by mapping previously published sequences of their endogenous counterparts onto published sequences of the episomal genomes. For BSOLV, two primer sets were designed while, for BSGFV, a single primer set was designed. The episomalspecificity of these primer sets was assessed by testing 106 plant samples collected during surveys in Kenya and Uganda, and 33 leaf samples from a wide range of banana cultivars maintained in TC at the Maroochy Research Station of the Department of Employment, Economic Development and Innovation (DEEDI), Queensland. All of these samples had previously been tested for episomal BSV by RCA and for both BSOLV and BSGFV by PCR using published primer sets. The outcome from these analyses was that the newly designed primer sets for BSOLV and BSGFV were able to distinguish between episomal BSV and eBSV in most cultivars with some B�]genome component. In some samples, however, amplification was observed using the putative episomal�]specific primer sets where episomal BSV was not identified using RCA. This may reflect a difference in the sensitivity of PCR compared to RCA, or possibly the presence of an eBSV sequence of different conformation. Since the sequences of the respective eBSV for BSMYV and BSIMV in the M. balbisiana genome are not available, a series of random primer combinations were tested in an attempt to find potential episomal�]specific primer sets for BSMYV and BSIMV. Of an initial 20 primer combinations screened for BSMYV detection on a small number of control samples, 11 primers sets appeared to be episomal�]specific. However, subsequent testing of two of these primer combinations on a larger number of control samples resulted in some inconsistent results which will require further investigation. Testing of the 25 primer combinations for episomal�]specific detection of BSIMV on a number of control samples showed that none were able to discriminate between episomal and endogenous BSIMV. The final component of this research project was the development of an infectious clone of a BSV endemic in Australia, namely BSMYV. This was considered important to enable the generation of large amounts of diseased plant material needed for further research. A terminally redundant fragment (.1.3 �~ BSMYV genome) was cloned and transformed into Agrobacterium tumefaciens strain AGL1, and used to inoculate 12 healthy banana plants of the cultivars Cavendish (Williams) by three different methods. At 12 weeks post�]inoculation, (i) four of the five banana plants inoculated by corm injection showed characteristic BSV symptoms while the remaining plant was wilting/dying, (ii) three of the five banana plants inoculated by needle�]pricking of the stem showed BSV symptoms, one plant was symptomless while the remaining had died and (iii) both banana plants inoculated by leaf infiltration were symptomless. When banana leaf samples were tested for BSMYV by PCR and RCA, BSMYV was confirmed in all banana plants showing symptoms including those were wilting and/or dying. The results from this research have provided several avenues for further research. By completely sequencing all variants of eBSOLV and eBSGFV and fully sequencing the eBSIMV and eBSMYV regions, episomal BSV�]specific primer sets for all eBSVs could potentially be designed that could avoid all integrants of that particular BSV species. Furthermore, the development of an infectious BSV clone will enable large numbers of BSVinfected plants to be generated for the further testing of the sensitivity of RCA compared to other more established assays such as PCR. The development of infectious clones also opens the possibility for virus induced gene silencing studies in banana.

The Cyndi Lauper affect : bodies, girlhood and popular culture [Abstract]

Using a collective biography method informed by a Deleuzian theoretical approach (Davies & Gannon, 2009), this paper analyses embodied memories of girlhood becomings through affective engagements with resonating images in media and popular culture. In this approach to analysis we move beyond an impasse in some feminist cultural studies where studies of popular culture have been understood through theories of representation and reception that retain a sense of discrete subjectivity and linear effects. In these approaches, analysis focuses respectively on decoding and deciphering images in terms of their normative and ideological baggage, and, particularly with moving images, on psychological readings (Coleman, 2011; Driscoll, 2002). Understanding bodies and popular culture through Deleuzian notions of ‘becoming’ and ‘assemblage’ opens possibilities for feminist researchers to consider the ways in which bodies are not separate to images but rather, are known, felt, materialised and mobilised with/through images (Coleman, 2008, 2009, 2011). We tease out the implications of this new approach to media affects through two memories of girls’ engagements with media images, reconceived as moments of embodied being within affective flows of popular culture that might momentarily extend upon the ways of being and doing girlhood.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

Corporate fraud and misconduct : investigative and regulatory priorities

This article investigates the profile of the companies that have been investigated for corporate fraud and misconduct. Our definition of fraud includes financial statement fraud, market misconduct fraud such as insider trading or false disclosures, and managerial fraud. The particular evidence presented relates to those instances of corporate fraud and misconduct investigated by the Australian corporate regulatory, Australian Securities and Investments Commission (ASIC), and relates to sanctions for fraud, misconduct or compliance breaches. Using data compiled from the public announcements in the ASIC reports over the period 2004-2008, we categorise the type of fraud and misconduct breaches ASIC chooses to report and investigate.

Reliability of partial ambiguity fixing with multiple GNSS constellations

Reliable ambiguity resolution (AR) is essential to Real-Time Kinematic (RTK) positioning and its applications, since incorrect ambiguity fixing can lead to largely biased positioning solutions. A partial ambiguity fixing technique is developed to improve the reliability of AR, involving partial ambiguity decorrelation (PAD) and partial ambiguity resolution (PAR). Decorrelation transformation could substantially amplify the biases in the phase measurements. The purpose of PAD is to find the optimum trade-off between decorrelation and worst-case bias amplification. The concept of PAR refers to the case where only a subset of the ambiguities can be fixed correctly to their integers in the integer least-squares (ILS) estimation system at high success rates. As a result, RTK solutions can be derived from these integer-fixed phase measurements. This is meaningful provided that the number of reliably resolved phase measurements is sufficiently large for least-square estimation of RTK solutions as well. Considering the GPS constellation alone, partially fixed measurements are often insufficient for positioning. The AR reliability is usually characterised by the AR success rate. In this contribution an AR validation decision matrix is firstly introduced to understand the impact of success rate. Moreover the AR risk probability is included into a more complete evaluation of the AR reliability. We use 16 ambiguity variance-covariance matrices with different levels of success rate to analyse the relation between success rate and AR risk probability. Next, the paper examines during the PAD process, how a bias in one measurement is propagated and amplified onto many others, leading to more than one wrong integer and to affect the success probability. Furthermore, the paper proposes a partial ambiguity fixing procedure with a predefined success rate criterion and ratio-test in the ambiguity validation process. In this paper, the Galileo constellation data is tested with simulated observations. Numerical results from our experiment clearly demonstrate that only when the computed success rate is very high, the AR validation can provide decisions about the correctness of AR which are close to real world, with both low AR risk and false alarm probabilities. The results also indicate that the PAR procedure can automatically chose adequate number of ambiguities to fix at given high-success rate from the multiple constellations instead of fixing all the ambiguities. This is a benefit that multiple GNSS constellations can offer.

Automatic particle picking of biological molecules imaged by electron microscopy

One of the next great challenges of cell biology is the determination of the enormous number of protein structures encoded in genomes. In recent years, advances in electron cryo-microscopy and high-resolution single particle analysis have developed to the point where they now provide a methodology for high resolution structure determination. Using this approach, images of randomly oriented single particles are aligned computationally to reconstruct 3-D structures of proteins and even whole viruses. One of the limiting factors in obtaining high-resolution reconstructions is obtaining a large enough representative dataset ($>100,000$ particles). Traditionally particles have been manually picked which is an extremely labour intensive process. The problem is made especially difficult by the low signal-to-noise ratio of the images. This paper describes the development of automatic particle picking software, which has been tested with both negatively stained and cryo-electron micrographs. This algorithm has been shown to be capable of selecting most of the particles, with few false positives. Further work will involve extending the software to detect differently shaped and oriented particles.

Quantitative evaluation of matching methods and validity measures for stereo vision

The authors present a qualitative and quantitative comparison of various similarity measures that form the kernel of common area-based stereo-matching systems. The authors compare classical difference and correlation measures as well as nonparametric measures based on the rank and census transforms for a number of outdoor images. For robotic applications, important considerations include robustness to image defects such as intensity variation and noise, the number of false matches, and computational complexity. In the absence of ground truth data, the authors compare the matching techniques based on the percentage of matches that pass the left-right consistency test. The authors also evaluate the discriminatory power of several match validity measures that are reported in the literature for eliminating false matches and for estimating match confidence. For guidance applications, it is essential to have and estimate of confidence in the three-dimensional points generated by stereo vision. Finally, a new validity measure, the rank constraint, is introduced that is capable of resolving ambiguous matches for rank transform-based matching.

Allegations of child sexual abuse in family court cases : a qualitative analysis of psychiatric evidence

Allegations of child sexual abuse in Family Court cases have gained increasing attention. The study investigates factors involved in Family Court cases involving allegations of child sexual abuse. A qualitative methodology was employed to examine Records of Judgement and Psychiatric Reports for 20 cases distilled from the data corpus of 102 cases. A seven-stage methodology was developed utilising a thematic analysis process informed by principles of grounded theory and phenomenology. The explication of eight thematic clusters was undertaken. The findings point to complex issues and dynamics in which child sexual abuse allegations have been raised. The alleging parent’s allegations of sexual abuse against their ex-partner may be: the expression of unconscious deep fears for their children’s welfare, or an action to meet their needs for personal affirmation in the context of the painful upheaval of a relationship break-up. Implications of the findings are discussed.

Characterization of sky-region morphological-temporal airborne collision detection

Automated airborne collision-detection systems are a key enabling technology for facilitat- ing the integration of unmanned aerial vehicles (UAVs) into the national airspace. These safety-critical systems must be sensitive enough to provide timely warnings of genuine air- borne collision threats, but not so sensitive as to cause excessive false-alarms. Hence, an accurate characterisation of detection and false alarm sensitivity is essential for understand- ing performance trade-offs, and system designers can exploit this characterisation to help achieve a desired balance in system performance. In this paper we experimentally evaluate a sky-region, image based, aircraft collision detection system that is based on morphologi- cal and temporal processing techniques. (Note that the examined detection approaches are not suitable for the detection of potential collision threats against a ground clutter back- ground). A novel collection methodology for collecting realistic airborne collision-course target footage in both head-on and tail-chase engagement geometries is described. Under (hazy) blue sky conditions, our proposed system achieved detection ranges greater than 1540m in 3 flight test cases with no false alarm events in 14.14 hours of non-target data (under cloudy conditions, the system achieved detection ranges greater than 1170m in 4 flight test cases with no false alarm events in 6.63 hours of non-target data). Importantly, this paper is the first documented presentation of detection range versus false alarm curves generated from airborne target and non-target image data.

Automatic Audio Segmentation Using the Generalized Likelihood Ratio

This paper presents a novel technique for segmenting an audio stream into homogeneous regions according to speaker identities, background noise, music, environmental and channel conditions. Audio segmentation is useful in audio diarization systems, which aim to annotate an input audio stream with information that attributes temporal regions of the audio into their specific sources. The segmentation method introduced in this paper is performed using the Generalized Likelihood Ratio (GLR), computed between two adjacent sliding windows over preprocessed speech. This approach is inspired by the popular segmentation method proposed by the pioneering work of Chen and Gopalakrishnan, using the Bayesian Information Criterion (BIC) with an expanding search window. This paper will aim to identify and address the shortcomings associated with such an approach. The result obtained by the proposed segmentation strategy is evaluated on the 2002 Rich Transcription (RT-02) Evaluation dataset, and a miss rate of 19.47% and a false alarm rate of 16.94% is achieved at the optimal threshold.

Transforming mobile personal life log into autobiographical multimedia eChronicles

Mobile devices are becoming indispensable personal assistants in people's daily life as these devices support work, study, play and socializing activities. The multi-modal sensors and rich features of smartphones can capture abundant information about users' life experience, such as taking photos or videos on what they see and hear, and organizing their tasks and activities using calendar, to-do lists, and notes. Such vast information can become useful to help users recalling episodic memories and reminisce about meaningful experiences. In this paper, we propose to apply autobiographical memory framework to provide an effective mechanism to structure mobile life-log data. The proposed model is an attempt towards a more complete personal life-log indexing model, which will support long term capture, organization, and retrieval. To demonstrate the benefits of the proposed model, we propose some design solutions for enabling users-driven capture, annotation, and retrieval of autobiographical multimedia chronicles tools.

Efficient real-time face detection for high resolution surveillance applications

This paper presents an efficient face detection method suitable for real-time surveillance applications. Improved efficiency is achieved by constraining the search window of an AdaBoost face detector to pre-selected regions. Firstly, the proposed method takes a sparse grid of sample pixels from the image to reduce whole image scan time. A fusion of foreground segmentation and skin colour segmentation is then used to select candidate face regions. Finally, a classifier-based face detector is applied only to selected regions to verify the presence of a face (the Viola-Jones detector is used in this paper). The proposed system is evaluated using 640 x 480 pixels test images and compared with other relevant methods. Experimental results show that the proposed method reduces the detection time to 42 ms, where the Viola-Jones detector alone requires 565 ms (on a desktop processor). This improvement makes the face detector suitable for real-time applications. Furthermore, the proposed method requires 50% of the computation time of the best competing method, while reducing the false positive rate by 3.2% and maintaining the same hit rate.

The search for individualism : Self-expression through product personalisation

This research paper explores the impact product personalisation has upon product attachment and aims to develop a deeper understanding of why, how and if consumers choose to do so. The current research in this field is mainly based on attachment theories and is predominantly product specific. This paper researches the link between product attachment and personalisation through in-depth, semi-structured interviews, where the data has been thematically analysed and broken down into three themes, and nine sub-themes. It was found that participants did become more attached to products once they were personalised and the reasons why this occurred varied. The most common reasons that led to personalisation were functionality and usability, the expression of personality through a product and the complexity of personalisation. The reasons why participants felt connected to their products included strong emotions/memories, the amount of time and effort invested into the personalisation, a sense of achievement. Reasons behind the desire for personalisation included co-designing, expression of uniqueness/individualism and having choice for personalisation. Through theme and inter-theme relationships, many correlations were formed, which created the basis for design recommendations. These recommendations demonstrate how a designer could implement the emotions and reasoning for personalisation into the design process.

CAT-GRAPH+ : towards odometry-driven place consolidation in changing environments

Changing environments present a number of challenges to mobile robots, one of the most significant being mapping and localisation. This problem is particularly significant in vision-based systems where illumination and weather changes can cause feature-based techniques to fail. In many applications only sections of an environment undergo extreme perceptual change. Some range-based sensor mapping approaches exploit this property by combining occasional place recognition with the assumption that odometry is accurate over short periods of time. In this paper, we develop this idea in the visual domain, by using occasional vision-driven loop closures to infer loop closures in nearby locations where visual recognition is difficult due to extreme change. We demonstrate successful map creation in an environment in which change is significant but constrained to one area, where both the vanilla CAT-Graph and a Sum of Absolute Differences matcher fails, use the described techniques to link dissimilar images from matching locations, and test the robustness of the system against false inferences.

Collaborative intrusion detection framework : characteristics, adversarial opportunities and countermeasures

Complex Internet attacks may come from multiple sources, and target multiple networks and technologies. Nevertheless, Collaborative Intrusion Detection Systems (CIDS) emerges as a promising solution by using information from multiple sources to gain a better understanding of objective and impact of complex Internet attacks. CIDS also help to cope with classical problems of Intrusion Detection Systems (IDS) such as zero-day attacks, high false alarm rates and architectural challenges, e. g., centralized designs exposing the Single-Point-of-Failure. Improved complexity on the other hand gives raise to new exploitation opportunities for adversaries. The contribution of this paper is twofold. We first investigate related research on CIDS to identify the common building blocks and to understand vulnerabilities of the Collaborative Intrusion Detection Framework (CIDF). Second, we focus on the problem of anonymity preservation in a decentralized intrusion detection related message exchange scheme. We use techniques from design theory to provide multi-path peer-to-peer communication scheme where the adversary can not perform better than guessing randomly the originator of an alert message.