Phoenix activity: Regulatory challenges and the law

Remedying the mischief of phoenix activity is of practical importance. The benefits include continued confidence in our economy, law that inspires best practice among directors, and law that is articulated in a manner such that penalties act as a sufficient deterrent and the regulatory system is able to detect offenders and bring them to account. Any further reforms must accommodate and tolerate legal phoenix activity. Phoenix activity pushes tolerance of entrepreneurial activity to its absolute limits. The wisest approach would be to front end the reforms so as to alleviate the considerable detection and enforcement burden upon regulatory bodies. There is little doubt that breach of the existing law is difficult and expensive to detect; and this is a significant burden when regulators have shrinking budgets and are rapidly losing feet on the ground. This front end approach may need to include restrictions on access to limited liability. The more limited liability is misused, the stronger the argument to limit access to limited liability. This paper proposes that such an approach is a legitimate next step for a robust and mature capitalist economy.

From vision to actions: Towards adaptive and autonomous humanoid robots

Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions.

Comparison of active-set method deconvolution and matched-filtering for derivation of an ultrasound transit time spectrum

The quality of ultrasound computed tomography imaging is primarily determined by the accuracy of ultrasound transit time measurement. A major problem in analysis is the overlap of signals making it difficult to detect the correct transit time. The current standard is to apply a matched-filtering approach to the input and output signals. This study compares the matched-filtering technique with active set deconvolution to derive a transit time spectrum from a coded excitation chirp signal and the measured output signal. The ultrasound wave travels in a direct and a reflected path to the receiver, resulting in an overlap in the recorded output signal. The matched-filtering and deconvolution techniques were applied to determine the transit times associated with the two signal paths. Both techniques were able to detect the two different transit times; while matched-filtering has a better accuracy (0.13 μs vs. 0.18 μs standard deviation), deconvolution has a 3.5 times improved side-lobe to main-lobe ratio. A higher side-lobe suppression is important to further improve image fidelity. These results suggest that a future combination of both techniques would provide improved signal detection and hence improved image fidelity.

A Survey of autonomous vision-based See and Avoid for Unmanned Aircraft Systems

This paper provides a comprehensive review of the vision-based See and Avoid problem for unmanned aircraft. The unique problem environment and associated constraints are detailed, followed by an in-depth analysis of visual sensing limitations. In light of such detection and estimation constraints, relevant human, aircraft and robot collision avoidance concepts are then compared from a decision and control perspective. Remarks on system evaluation and certification are also included to provide a holistic review approach. The intention of this work is to clarify common misconceptions, realistically bound feasible design expectations and offer new research directions. It is hoped that this paper will help us to unify design efforts across the aerospace and robotics communities.

(Z)-11-Hexadecenal and (3Z,6Z,9Z)-Tricosatriene: Sex Pheromone Components of the Red Banded Mango Caterpillar Deanolis sublimbalis

The sex pheromone of the red banded mango caterpillar, Deanolis sublimbalis (Lepidoptera: Crambidae), a serious pest of the mango Mangifera indica (Anacardiaceae) in India and Southeast Asia and a recent invader into northern Australia, has been identified. Three candidate compounds were identified from pheromone gland extracts of female moths, using gas chromatography (GC), GC-electroantennographic detection and GC-mass spectrometric analyses, in conjunction with dimethyldisulfide derivatization. Field bioassays established that both (Z)-11-hexadecenal (Z11-16:Ald) and (3Z,6Z,9Z)-tricosatriene (3Z,6Z,9Z-23:Hy) were required for attraction of male D. sublimbalis moths, and 1,000 μg of a 1:1 mix of Z11-16:Ald and 3Z,6Z,9Z-23:Hy was more attractive to male moths than caged virgin females. However, the binary blend was only attractive when the isomeric purity of the monounsaturated aldehyde was >99%, suggesting that the (E)-isomer was inhibitory. Although (Z)-11-hexadecen-1-ol (Z11-16:OH) was tentatively identified in gland extracts, the addition of this compound to the binary blend did not increase the numbers of moths captured. The pheromone can now be used in integrated pest management strategies.

Neuronal oscillations in gamma- and alpha-frequency bands: from object representations to sensory awareness

The synchronization of neuronal activity, especially in the beta- (14-30 Hz) /gamma- (30 80 Hz) frequency bands, is thought to provide a means for the integration of anatomically distributed processing and for the formation of transient neuronal assemblies. Thus non-stimulus locked (i.e. induced) gamma-band oscillations are believed to underlie feature binding and the formation of neuronal object representations. On the other hand, the functional roles of neuronal oscillations in slower theta- (4 8 Hz) and alpha- (8 14 Hz) frequency bands remain controversial. In addition, early stimulus-locked activity has been largely ignored, as it is believed to reflect merely the physical properties of sensory stimuli. With human neuromagnetic recordings, both the functional roles of gamma- and alpha-band oscillations and the significance of early stimulus-locked activity in neuronal processing were examined in this thesis. Study I of this thesis shows that even the stimulus-locked (evoked) gamma oscillations were sensitive to high-level stimulus features for speech and non-speech sounds, suggesting that they may underlie the formation of early neuronal object representations for stimuli with a behavioural relevance. Study II shows that neuronal processing for consciously perceived and unperceived stimuli differed as early as 30 ms after stimulus onset. This study also showed that the alpha band oscillations selectively correlated with conscious perception. Study III, in turn, shows that prestimulus alpha-band oscillations influence the subsequent detection and processing of sensory stimuli. Further, in Study IV, we asked whether phase synchronization between distinct frequency bands is present in cortical circuits. This study revealed prominent task-sensitive phase synchrony between alpha and beta/gamma oscillations. Finally, the implications of Studies II, III, and IV to the broader scientific context are analysed in the last study of this thesis (V). I suggest, in this thesis that neuronal processing may be extremely fast and that the evoked response is important for cognitive processes. I also propose that alpha oscillations define the global neuronal workspace of perception, action, and consciousness and, further, that cross-frequency synchronization is required for the integration of neuronal object representations into global neuronal workspace.

Developing a best practice pathway to support improvements in Indigenous Australians' mental health and well-being: A qualitative study

Objective: There is a need to adapt pathways to care to promote access to mental health services for Indigenous people in Australia. This study explored Indigenous community and service provider perspectives of well-being and ways to promote access to care for Indigenous people at risk of depressive illness. Design: A participatory action research framework was used to inform the development of an agreed early intervention pathway; thematic analysis Setting: 2 remote communities in the Northern Territory. Participants: Using snowball and purposive sampling, 27 service providers and community members with knowledge of the local context and the diverse needs of those at risk of depression were interviewed. 30% of participants were Indigenous. The proposed pathway to care was adapted in response to participant feedback. Results: The study found that Indigenous mental health and well-being is perceived as multifaceted and strongly linked to cultural identity. It also confirms that there is broad support for promotion of a clear pathway to early intervention. Key identified components of this pathway were the health centre, visiting and community-based services, and local community resources including elders, cultural activities and families. Enablers to early intervention were reported. Significant barriers to the detection and treatment of those at risk of depression were identified, including insufficient resources, negative attitudes and stigma, and limited awareness of support options. Conclusions: Successful early intervention for wellbeing concerns requires improved understanding of Indigenous well-being perspectives and a systematic change in service delivery that promotes integration, flexibility and collaboration between services and the community, and recognises the importance of social determinants in health promotion and the healing process. Such changes require policy support, targeted training and education, and ongoing promotion.

The distribution and spread of citrus canker in Emerald, Australia

Citrus canker is a disease of citrus and closely related species, caused by the bacterium Xanthomonas citri subsp. citri. This disease, previously exotic to Australia, was detected on a single farm [infested premise-1, (IP1). IP is the terminology used in official biosecurity protocols to describe a locality at which an exotic plant pest has been confirmed or is presumed to exist. IP are numbered sequentially as they are detected] in Emerald, Queensland in July 2004. During the following 10 months the disease was subsequently detected on two other farms (IP2 and IP3) within the same area and studies indicated the disease first occurred on IP1 and spread to IP2 and IP3. The oldest, naturally infected plant tissue observed on any of these farms indicated the disease was present on IP1 for several months before detection and established on IP2 and IP3 during the second quarter (i.e. autumn) 2004. Transect studies on some IP1 blocks showed disease incidences ranged between 52 and 100% (trees infected). This contrasted to very low disease incidence, less than 4% of trees within a block, on IP2 and IP3. The mechanisms proposed for disease spread within blocks include weather-assisted dispersal of the bacterium (e.g. wind-driven rain) and movement of contaminated farm equipment, in particular by pivot irrigator towers via mechanical damage in combination with abundant water. Spread between blocks on IP2 was attributed to movement of contaminated farm equipment and/or people. Epidemiology results suggest: (i) successive surveillance rounds increase the likelihood of disease detection; (ii) surveillance sensitivity is affected by tree size; and (iii) individual destruction zones (for the purpose of eradication) could be determined using disease incidence and severity data rather than a predefined set area.

Healthy hardwoods. A field guide to pests, diseases and nutritional disorders in subtropical hardwoods.

Healthy hardwoods: A field guide to pests, diseases and nutritional disorders in subtropical hardwoods can be used to help identify the common damaging insects, fungi and nutritional disorders in young eucalypt (Eucalyptus and Corymbia species) plantations in subtropical eastern Australia. This guide includes photographs of each insect, fungus and nutritional disorder and the damage they cause, along with a brief description to aid identification. A brief host list for insects and fungi, including susceptibility and occurrence, is provided as a guide only. A hand lens will be useful, especially to identify fungi. Although it is possible to identify insects and fungi from these photographs, laboratory examination will sometimes be necessary. For example, microscopes and culturing media might be used to identify fungi. Information about four exotic pests and diseases has also been included in the Biosecurity threats chapter. Potentially, these would have a severe impact on plantation and natural forests if introduced into Australia. To prevent establishment of these pests, early detection and identification is crucial. If an exotic insect or disease is suspected, then an immediate response is required. Usually, the first response will be to contact the nearest Australian Quarantine and Inspection Service office or forestry agency to seek advice.

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

A reanalysis of 409 European-Ancestry and African American schizophrenia pedigrees reveals significant linkage to 8p23.3 with evidence of locus heterogeneity

The detection and replication of schizophrenia risk loci can require substantial sample sizes, which has prompted various collaborative efforts for combining multiple samples. However, pooled samples may comprise sub-samples with substantial population genetic differences, including allele frequency differences. We investigated the impact of population differences via linkage reanalysis of Molecular Genetics of Schizophrenia 1 (MGS1) affected sibling-pair data, comprising two samples of distinct ancestral origin: European (EA: 263 pedigrees) and African-American (AA: 146 pedigrees). To exploit the linkage information contained within these distinct continental samples, we performed separate analyses of the individual samples, allowing for within-sample locus heterogeneity, and the pooled sample, allowing for both within-sample and between-sample heterogeneity. Significance levels, corrected for the multiple tests, were determined empirically. For all suggestive peaks, stronger linkage evidence was obtained in either the EA or AA sample than the combined sample, regardless of how heterogeneity was modeled for the latter. Notably, we report genomewide significant linkage of schizophrenia to 8p23.3 and evidence for a second, independent susceptibility locus, reaching suggestive linkage, 29 cM away on 8p21.3. We also detected suggestive linkage on chromosomes 5p13.3 and 7q36.2. Many regions showed pronounced differences in the extent of linkage between the EA and AA samples. This reanalysis highlights the potential impact of population differences upon linkage evidence in pooled data and demonstrates a useful approach for the analysis of samples drawn from distinct continental groups.

Foodborne Yersinia : Identification and Molecular Epidemiology of Isolates from Human Infections

Yersinia enterocolitica and Yersinia pseudotuberculosis are among the major enteropathogenic bacteria causing infections in humans in many industrialized countries. In Finland, Y. pseudotuberculosis has caused 10 outbreaks among humans during 1997-2008. Some of these outbreaks have been very extensive involving over 400 cases; mainly children attending schools and day-care. Y. enterocolitica, on the contrary, has caused mainly a large number of sporadic human infections in Finland. Y. pseudotuberculosis is widespread in nature, causing infections in a variety of domestic and wild animals. Foodborne transmission of human infections has long been suspected, however, attempts to trace the pathogen have been unsuccessful before this study that epidemiologically linked Y. pseudotuberculosis to a specific food item. Furthermore, due to modern food distribution systems, foodborne outbreaks usually involve many geographically separate infection clusters difficult to identify as part of the same outbreak. Among pathogenic Y. enterocolitica, the global predominance of one genetically homogeneous type (bioserotype 4/O:3) is a challenge to the development of genetic typing methods discriminatory enough for epidemiological purposes, for example, for tracing back to the sources of infections. Furthermore, the diagnostics of Y. enterocolitica infections is hampered because clinical laboratories easily misidentify some other members of the Yersinia species (Y. enterocolitica–like species) as Y. enterocolitica. This results in misleading information on the prevalence and clinical significance of various Yersinia isolates. The aim of this study was to develop and optimize molecular typing methods to be used in epidemiological investigations of Y. enterocolitica and Y. pseudotuberculosis, particularly in active surveillance and outbreak investigations of Y. pseudotuberculosis isolates. The aim was also to develop a simplified set of phenotypic tests that could be used in routine diagnostic laboratories for the correct identification of Y. enterocolitica and Y. enterocolitica –like species. A PFGE method designed here for typing of Y. pseudotuberculosis was efficient in linking the geographically dispersed and apparently unrelated Y. pseudotuberculosis infections as parts of the same outbreak. It proved to be useful in active laboratory-based surveillance of Y. pseudotuberculosis outbreaks. Throughout the study period, information about the diversity of genotypes among outbreak and non-outbreak related strains of human origin was obtained. Also, to our knowledge, this was the first study to epidemiologically link a Y. pseudotuberculosis outbreak of human illnesses to a specific food item, iceberg lettuce. A novel epidemiological typing method based on the use of a repeated genomic region (YeO:3RS) as a probe was developed for the detection and differentiation between strains of Y. enterocolitica subspecies palearctica. This method was able to increase the discrimination in a set of 106 previously PFGE typed Finnish Y. enterocolitica bioserotype 4/O:3 strains among which two main PFGE genotypes had prevailed. The developed simplified method was a more reliable tool than the commercially available biochemical test kits for differentiation between Y. enterocolitica and Y. enterocolitica –like species. In Finland, the methods developed for Y. enterocolitica and Y. pseudotuberculosis have been used to improve the identification protocols and in subsequent outbreak investigations.

Routes of Hendra Virus Excretion in Naturally-Infected Flying-Foxes: Implications for Viral Transmission and Spillover Risk

Pteropid bats or flying-foxes (Chiroptera: Pteropodidae) are the natural host of Hendra virus (HeV) which sporadically causes fatal disease in horses and humans in eastern Australia. While there is strong evidence that urine is an important infectious medium that likely drives bat to bat transmission and bat to horse transmission, there is uncertainty about the relative importance of alternative routes of excretion such as nasal and oral secretions, and faeces. Identifying the potential routes of HeV excretion in flying-foxes is important to effectively mitigate equine exposure risk at the bat-horse interface, and in determining transmission rates in host-pathogen models. The aim of this study was to identify the major routes of HeV excretion in naturally infected flying-foxes, and secondarily, to identify between-species variation in excretion prevalence. A total of 2840 flying-foxes from three of the four Australian mainland species (Pteropus alecto, P. poliocephalus and P. scapulatus) were captured and sampled at multiple roost locations in the eastern states of Queensland and New South Wales between 2012 and 2014. A range of biological samples (urine and serum, and urogenital, nasal, oral and rectal swabs) were collected from anaesthetized bats, and tested for HeV RNA using a qRT-PCR assay targeting the M gene. Forty-two P. alecto (n = 1410) had HeV RNA detected in at least one sample, and yielded a total of 78 positive samples, at an overall detection rate of 1.76% across all samples tested in this species (78/4436). The rate of detection, and the amount of viral RNA, was highest in urine samples (>serum, packed haemocytes >faecal >nasal >oral), identifying urine as the most plausible source of infection for flying-foxes and for horses. Detection in a urine sample was more efficient than detection in urogenital swabs, identifying the former as the preferred diagnostic sample. The detection of HeV RNA in serum is consistent with haematogenous spread, and with hypothesised latency and recrudesence in flying-foxes. There were no detections in P. poliocephalus (n = 1168 animals; n = 2958 samples) or P. scapulatus (n = 262 animals; n = 985 samples), suggesting (consistent with other recent studies) that these species are epidemiologically less important than P. alecto in HeV infection dynamics. The study is unprecedented in terms of the individual animal approach, the large sample size, and the use of a molecular assay to directly determine infection status. These features provide a high level of confidence in the veracity of our findings, and a sound basis from which to more precisely target equine risk mitigation strategies.

Ecological Networks in Stored Grain: Key Postharvest Nodes for Emerging Pests, Pathogens, and Mycotoxins

Wheat is at peak quality soon after harvest. Subsequently, diverse biota use wheat as a resource in storage, including insects and mycotoxin-producing fungi. Transportation networks for stored grain are crucial to food security and provide a model system for an analysis of the population structure, evolution, and dispersal of biota in networks. We evaluated the structure of rail networks for grain transport in the United States and Eastern Australia to identify the shortest paths for the anthropogenic dispersal of pests and mycotoxins, as well as the major sources, sinks, and bridges for movement. We found important differences in the risk profile in these two countries and identified priority control points for sampling, detection, and management. An understanding of these key locations and roles within the network is a new type of basic research result in postharvest science and will provide insights for the integrated pest management of high-risk subpopulations, such as pesticide-resistant insect pests.

Modeling Efficient Classification as a Process of Confidence Assessment and Delegation

In visual object detection and recognition, classifiers have two interesting characteristics: accuracy and speed. Accuracy depends on the complexity of the image features and classifier decision surfaces. Speed depends on the hardware and the computational effort required to use the features and decision surfaces. When attempts to increase accuracy lead to increases in complexity and effort, it is necessary to ask how much are we willing to pay for increased accuracy. For example, if increased computational effort implies quickly diminishing returns in accuracy, then those designing inexpensive surveillance applications cannot aim for maximum accuracy at any cost. It becomes necessary to find trade-offs between accuracy and effort. We study efficient classification of images depicting real-world objects and scenes. Classification is efficient when a classifier can be controlled so that the desired trade-off between accuracy and effort (speed) is achieved and unnecessary computations are avoided on a per input basis. A framework is proposed for understanding and modeling efficient classification of images. Classification is modeled as a tree-like process. In designing the framework, it is important to recognize what is essential and to avoid structures that are narrow in applicability. Earlier frameworks are lacking in this regard. The overall contribution is two-fold. First, the framework is presented, subjected to experiments, and shown to be satisfactory. Second, certain unconventional approaches are experimented with. This allows the separation of the essential from the conventional. To determine if the framework is satisfactory, three categories of questions are identified: trade-off optimization, classifier tree organization, and rules for delegation and confidence modeling. Questions and problems related to each category are addressed and empirical results are presented. For example, related to trade-off optimization, we address the problem of computational bottlenecks that limit the range of trade-offs. We also ask if accuracy versus effort trade-offs can be controlled after training. For another example, regarding classifier tree organization, we first consider the task of organizing a tree in a problem-specific manner. We then ask if problem-specific organization is necessary.