Computed tomography analysis of sagittal plane parameters in adolescent idiopathic scoliosis treated by video assisted thoracoscopic spinal fusion and instrumentation

One of the primary treatment goals of adolescent idiopathic scoliosis (AIS) surgery is to achieve maximum coronal plane correction while maintaining coronal balance. However maintaining or restoring sagittal plane spinal curvature has become increasingly important in maintaining the long-term health of the spine. Patients with AIS are characterised by pre-operative thoracic hypokyphosis, and it is generally agreed that operative treatment of thoracic idiopathic scoliosis should aim to restore thoracic kyphosis to normal values while maintaining lumbar lordosis and good overall sagittal balance. The aim of this study was to evaluate CT sagittal plane parameters, with particular emphasis on thoracolumbar junctional alignment, in patients with AIS who underwent Video Assisted Thoracoscopic Spinal Fusion and Instrumentation (VATS). This study concluded that video-assisted thoracoscopic spinal fusion and instrumentation reliably increases thoracic kyphosis while preserving junctional alignment and lumbar lordosis in thoracic AIS.

Case-control study of early childhood caries in Australia

The aim of this case-control study of 617 children was to investigate early childhood caries (ECC) risk indicators in a non-fluoridated region in Australia. ECC cases were recruited from childcare facilities, public hospitals and private specialist clinics to source children from different socioeconomic backgrounds. Non-ECC controls were recruited from the same childcare facilities. A multinomial logistic modelling approach was used for statistical analysis. The results showed that a large percentage of children tested positive for Streptococcus mutans if their mothers also tested positive. A common risk indicator found in ECC children from childcare facilities and public hospitals was visible plaque (OR 4.1, 95% CI 1.0-15.9, and OR 8.7, 95% CI 2.3-32.9, respectively). Compared to ECC-free controls, the risk indicators specific to childcare cases were enamel hypoplasia (OR 4.2, 95% CI 1.0-18.3), difficulty in cleaning child's teeth (OR 6.6, 95% CI 2.2-19.8), presence of S. mutans (OR 4.8, 95% CI 0.7-32.6), sweetened drinks (OR 4.0, 95% CI 1.2-13.6) and maternal anxiety (OR 5.1, 95% CI 1.1-25.0). Risk indicators specific to public hospital cases were S. mutans presence in child (OR 7.7, 95% CI 1.3-44.6) or mother (OR 8.1, 95% CI 0.9-72.4), ethnicity (OR 5.6, 95% CI 1.4-22.1), and access of mother to pension or health care card (OR 20.5, 95% CI 3.5-119.9). By contrast, a history of chronic ear infections was found to be protective for ECC in childcare children (OR 0.28, 95% CI 0.09-0.82). The biological, socioeconomic and maternal risk indicators demonstrated in the present study can be employed in models of ECC that can be usefully applied for future longitudinal studies.

Modeling and exploiting behavior patterns in dynamic environments

This paper presents a new approach to improving the effectiveness of autonomous systems that deal with dynamic environments. The basis of the approach is to find repeating patterns of behavior in the dynamic elements of the system, and then to use predictions of the repeating elements to better plan goal directed behavior. It is a layered approach involving classifying, modeling, predicting and exploiting. Classifying involves using observations to place the moving elements into previously defined classes. Modeling involves recording features of the behavior on a coarse grained grid. Exploitation is achieved by integrating predictions from the model into the behavior selection module to improve the utility of the robot's actions. This is in contrast to typical approaches that use the model to select between different strategies or plays. Three methods of adaptation to the dynamic features of the environment are explored. The effectiveness of each method is determined using statistical tests over a number of repeated experiments. The work is presented in the context of predicting opponent behavior in the highly dynamic and multi-agent robot soccer domain (RoboCup).

Determinants of health costs due to farmers’ exposure to pesticides : an empirical analysis

It is now well known that pesticide spraying by farmers has an adverse impact on their health. This is especially so in developing countries where pesticide spraying is undertaken manually. The estimated health costs are large. Studies to date have examined farmers’ exposure to pesticides, the costs of ill-health and their determinants based on information provided by farmers. Hence, some doubt has been cast on the reliability of such studies. In this study, we rectify this situation by conducting surveys among two groups of farmers. Farmers who perceive that their ill-health is due to exposure to pesticides and obtained treatment and farmers whose ill-health have been diagnosed by doctors and who have been treated in hospital for exposure to pesticides. In the paper, cost comparisons between the two groups of farmers are made. Furthermore, regression analysis of the determinants of health costs show that the quantity of pesticides used per acre per month, frequency of pesticide use and number of pesticides used per hour per day are the most important determinants of medical costs for both samples. The results have important policy implications.

Analysis and detection of cognitive load and frustration in drivers' speech

Non-driving related cognitive load and variations of emotional state may impact a driver’s capability to control a vehicle and introduces driving errors. Availability of reliable cognitive load and emotion detection in drivers would benefit the design of active safety systems and other intelligent in-vehicle interfaces. In this study, speech produced by 68 subjects while driving in urban areas is analyzed. A particular focus is on speech production differences in two secondary cognitive tasks, interactions with a co-driver and calls to automated spoken dialog systems (SDS), and two emotional states during the SDS interactions - neutral/negative. A number of speech parameters are found to vary across the cognitive/emotion classes. Suitability of selected cepstral- and production-based features for automatic cognitive task/emotion classification is investigated. A fusion of GMM/SVM classifiers yields an accuracy of 94.3% in cognitive task and 81.3% in emotion classification.

Development of rapid and highly resolving combinatorial genotyping schemes for Campylobacter jejuni and Campylobacter coli

Campylobacter jejuni followed by Campylobacter coli contribute substantially to the economic and public health burden attributed to food-borne infections in Australia. Genotypic characterisation of isolates has provided new insights into the epidemiology and pathogenesis of C. jejuni and C. coli. However, currently available methods are not conducive to large scale epidemiological investigations that are necessary to elucidate the global epidemiology of these common food-borne pathogens. This research aims to develop high resolution C. jejuni and C. coli genotyping schemes that are convenient for high throughput applications. Real-time PCR and High Resolution Melt (HRM) analysis are fundamental to the genotyping schemes developed in this study and enable rapid, cost effective, interrogation of a range of different polymorphic sites within the Campylobacter genome. While the sources and routes of transmission of campylobacters are unclear, handling and consumption of poultry meat is frequently associated with human campylobacteriosis in Australia. Therefore, chicken derived C. jejuni and C. coli isolates were used to develop and verify the methods described in this study. The first aim of this study describes the application of MLST-SNP (Multi Locus Sequence Typing Single Nucleotide Polymorphisms) + binary typing to 87 chicken C. jejuni isolates using real-time PCR analysis. These typing schemes were developed previously by our research group using isolates from campylobacteriosis patients. This present study showed that SNP + binary typing alone or in combination are effective at detecting epidemiological linkage between chicken derived Campylobacter isolates and enable data comparisons with other MLST based investigations. SNP + binary types obtained from chicken isolates in this study were compared with a previously SNP + binary and MLST typed set of human isolates. Common genotypes between the two collections of isolates were identified and ST-524 represented a clone that could be worth monitoring in the chicken meat industry. In contrast, ST-48, mainly associated with bovine hosts, was abundant in the human isolates. This genotype was, however, absent in the chicken isolates, indicating the role of non-poultry sources in causing human Campylobacter infections. This demonstrates the potential application of SNP + binary typing for epidemiological investigations and source tracing. While MLST SNPs and binary genes comprise the more stable backbone of the Campylobacter genome and are indicative of long term epidemiological linkage of the isolates, the development of a High Resolution Melt (HRM) based curve analysis method to interrogate the hypervariable Campylobacter flagellin encoding gene (flaA) is described in Aim 2 of this study. The flaA gene product appears to be an important pathogenicity determinant of campylobacters and is therefore a popular target for genotyping, especially for short term epidemiological studies such as outbreak investigations. HRM curve analysis based flaA interrogation is a single-step closed-tube method that provides portable data that can be easily shared and accessed. Critical to the development of flaA HRM was the use of flaA specific primers that did not amplify the flaB gene. HRM curve analysis flaA interrogation was successful at discriminating the 47 sequence variants identified within the 87 C. jejuni and 15 C. coli isolates and correlated to the epidemiological background of the isolates. In the combinatorial format, the resolving power of flaA was additive to that of SNP + binary typing and CRISPR (Clustered regularly spaced short Palindromic repeats) HRM and fits the PHRANA (Progressive hierarchical resolving assays using nucleic acids) approach for genotyping. The use of statistical methods to analyse the HRM data enhanced sophistication of the method. Therefore, flaA HRM is a rapid and cost effective alternative to gel- or sequence-based flaA typing schemes. Aim 3 of this study describes the development of a novel bioinformatics driven method to interrogate Campylobacter MLST gene fragments using HRM, and is called ‘SNP Nucleated Minim MLST’ or ‘Minim typing’. The method involves HRM interrogation of MLST fragments that encompass highly informative “Nucleating SNPS” to ensure high resolution. Selection of fragments potentially suited to HRM analysis was conducted in silico using i) “Minimum SNPs” and ii) the new ’HRMtype’ software packages. Species specific sets of six “Nucleating SNPs” and six HRM fragments were identified for both C. jejuni and C. coli to ensure high typeability and resolution relevant to the MLST database. ‘Minim typing’ was tested empirically by typing 15 C. jejuni and five C. coli isolates. The association of clonal complexes (CC) to each isolate by ‘Minim typing’ and SNP + binary typing were used to compare the two MLST interrogation schemes. The CCs linked with each C. jejuni isolate were consistent for both methods. Thus, ‘Minim typing’ is an efficient and cost effective method to interrogate MLST genes. However, it is not expected to be independent, or meet the resolution of, sequence based MLST gene interrogation. ‘Minim typing’ in combination with flaA HRM is envisaged to comprise a highly resolving combinatorial typing scheme developed around the HRM platform and is amenable to automation and multiplexing. The genotyping techniques described in this thesis involve the combinatorial interrogation of differentially evolving genetic markers on the unified real-time PCR and HRM platform. They provide high resolution and are simple, cost effective and ideally suited to rapid and high throughput genotyping for these common food-borne pathogens.

Evolution and change in industrial clusters : an analysis of Hsinchu and Sophia Antipolis

The aim of this paper is to advance understandings of the processes of cluster-building and evolution, or transformative and adaptive change, through the conscious design and reflective activities of private and public actors. A model of transformation is developed which illustrates the importance of actors becoming exposed to new ideas and visions for industrial change by political entrepreneurs and external networks. Further, actors must be guided in their decision-making and action by the new vision, and this requires that they are persuaded of its viability through the provision of test cases and supportive resources and institutions. In order for new ideas to become guiding models, actors must be convinced of their desirability through the portrayal of models as a means of confronting competitive challenges and serving the economic interests of the city/region. Subsequent adaptive change is iterative and reflexive, involving a process of strategic learning amongst key industrial and political actors.

Culture independent analysis of greyback canegrub-associated microflora and microbial community comparison using subtractive hybridisation

Greyback canegrubs cost the Australian sugarcane industry around $13 million per annum in damage and control. A novel and cost effective biocontrol bacterium could play an important role in the integrated pest management program currently in place to reduce damage and control associated costs. During the course of this project, terminal restriction fragment length polymorphism (TRFLP), 16-S rDNA cloning, suppressive subtractive hybridisation (SSH) and entomopathogen-specific PCR screening were used to investigate the little studied canegrub-associated microflora in an attempt to discover novel pathogens from putatively-diseased specimens. Microflora associated with these soil-dwelling insects was found to be both highly diverse and divergent between individual specimens. Dominant members detected in live specimens were predominantly from taxa of known insect symbionts while dominant sequences amplified from dead grubs were homologous to putativelysaprophytic bacteria and bacteria able to grow during refrigeration. A number of entomopathogenic bacteria were identified such as Photorhabdus luminescens and Pseudomonas fluorescens. Dead canegrubs prior to decomposition need to be analysed if these bacteria are to be isolated. Novel strategies to enrich putative pathogen-associated sequences (SSH and PCR screening) were shown to be promising approaches for pathogen discovery and the investigation of canegrubsassociated microflora. However, due to inter- and intra-grub-associated community diversity, dead grub decomposition and PCR-specific methodological limitations (PCR bias, primer specificity, BLAST database restrictions, 16-S gene copy number and heterogeneity), recommendations have been made to improve the efficiency of such techniques. Improved specimen collection procedures and utilisation of emerging high-throughput sequencing technologies may be required to examine these complex communities in more detail. This is the first study to perform a whole-grub analysis and comparison of greyback canegrub-associated microbial communities. This work also describes the development of a novel V3-PCR based SSH technique. This was the first SSH technique to use V3-PCR products as a starting material and specifically compare bacterial species present in a complex community.

Performance analysis of unified enterprise application security framework

Unified Enterprise application security is a new emerging approach for providing protection against application level attacks. Conventional application security approach that consists of embedding security into each critical application leads towards scattered security mechanism that is not only difficult to manage but also creates security loopholes. According to the CSIIFBI computer crime survey report, almost 80% of the security breaches come from authorized users. In this paper, we have worked on the concept of unified security model, which manages all security aspect from a single security window. The basic idea is to keep business functionality separate from security components of the application. Our main focus was on the designing of frame work for unified layer which supports single point of policy control, centralize logging mechanism, granular, context aware access control, and independent from any underlying authentication technology and authorization policy.

Dynamic analysis of on-board mass data to determine tampering in heavy vehicle on-board mass systems

Transport Certification Australia Limited, jointly with the National Transport Commission, has undertaken a project to investigate the feasibility of on-board mass monitoring (OBM) devices for regulatory purposes. OBM increases jurisdictional confidence in operational heavy vehicle compliance. This paper covers technical issues regarding potential use of dynamic data from OBM systems to indicate that tampering has occurred. Tamper-evidence and accuracy of current OBM systems needed to be determined before any regulatory schemes were put in place for its use. Tests performed to determine potential for, and ease of, tampering. An algorithm was developed to detect tamper events. Its results are detailed.

Thermogravimetric analysis-mass spectrometry (TG-MS) of selected Chinese kaolinites

Thermogravimetric analysis-mass spectrometry, X-ray diffraction and scanning electron microscopy (SEM) were used to characterize eight kaolinite samples from China. The results show that the thermal decomposition occurs in three main steps (a) desorption of water below 100 °C, (b) dehydration at about 225 °C, (c) well defined dehydroxylation at around 450 °C. It is also found that decarbonization took place at 710 °C due to the decomposition of calcite impurity in kaolin. The temperature of dehydroxylation of kaolinite is found to be influenced by the degree of disorder of the kaolinite structure and the gases evolved in the decomposition process can be various because of the different amount and kinds of impurities. It is evident by the mass spectra that the interlayer carbonate from impurity of calcite and organic carbon is released as CO2 around 225, 350 and 710 °C in the kaolinite samples.

Thermogravimetric analysis of selected coal-bearing strata kaolinite

Two kinds of coal-bearing kaolinite from China were analysed by X-ray diffraction (XRD), Thermogravimetric analysis-mass spectrometry (TG-MS), infrared emission spectroscopy. Thermal decomposition occurs in a series of steps attributed to (a) desorption of water at 68 °C for Datong coal bearing strata kaolinite and 56 °C for Xiaoxian with mass losses of 0.36 % and 0.51 % (b) decarbonization at 456 °C for Datong coal bearing strata kaolinite and 431 °C for Xiaoxian kaolinite, (c) dehydroxylation takes place in two steps at 589 and 633 °C for Datong coal bearing strata kaolinite and at 507 °C and 579 °C for Xiaoxian kaolinite. This mineral were further characterised by infrared emission spectroscopy (IES). Well defined hydroxyl stretching bands at around 3695, 3679, 3652 and 3625 cm-1 are observed. At 650 °C all intensity in these bands is lost in harmony with the thermal analysis results. Characteristic functional groups from coal are observed at 1918, 1724 and 1459 cm-1. The intensity of these bands decrease by thermal treatment and is lost by 700 °C.

Technical report : acoustic analysis of the natural environment

This technical report is concerned with one aspect of environmental monitoring—the detection and analysis of acoustic events in sound recordings of the environment. Sound recordings offer ecologists the potential advantages of cheaper and increased sampling. An acoustic event detection algorithm is introduced that outputs a compact rectangular marquee description of each event. It can disentangle superimposed events, which are a common occurrence during morning and evening choruses. Next, three uses to which acoustic event detection can be put are illustrated. These tasks have been selected because they illustrate quite different modes of analysis: (1) the detection of diffuse events caused by wind and rain, which are a frequent contaminant of recordings of the terrestrial environment; (2) the detection of bird calls using the spatial distribution of their component events; and (3) the preparation of acoustic maps for whole ecosystem analysis. This last task utilises the temporal distribution of events over a daily, monthly or yearly cycle.

Monitoring and analysis of internet traffic targeting unused address spaces

Today’s evolving networks are experiencing a large number of different attacks ranging from system break-ins, infection from automatic attack tools such as worms, viruses, trojan horses and denial of service (DoS). One important aspect of such attacks is that they are often indiscriminate and target Internet addresses without regard to whether they are bona fide allocated or not. Due to the absence of any advertised host services the traffic observed on unused IP addresses is by definition unsolicited and likely to be either opportunistic or malicious. The analysis of large repositories of such traffic can be used to extract useful information about both ongoing and new attack patterns and unearth unusual attack behaviors. However, such an analysis is difficult due to the size and nature of the collected traffic on unused address spaces. In this dissertation, we present a network traffic analysis technique which uses traffic collected from unused address spaces and relies on the statistical properties of the collected traffic, in order to accurately and quickly detect new and ongoing network anomalies. Detection of network anomalies is based on the concept that an anomalous activity usually transforms the network parameters in such a way that their statistical properties no longer remain constant, resulting in abrupt changes. In this dissertation, we use sequential analysis techniques to identify changes in the behavior of network traffic targeting unused address spaces to unveil both ongoing and new attack patterns. Specifically, we have developed a dynamic sliding window based non-parametric cumulative sum change detection techniques for identification of changes in network traffic. Furthermore we have introduced dynamic thresholds to detect changes in network traffic behavior and also detect when a particular change has ended. Experimental results are presented that demonstrate the operational effectiveness and efficiency of the proposed approach, using both synthetically generated datasets and real network traces collected from a dedicated block of unused IP addresses.