Persistent ocean monitoring with underwater gliders : adapting sampling resolution

Ocean processes are dynamic, complex, and occur on multiple spatial and temporal scales. To obtain a synoptic view of such processes, ocean scientists collect data over long time periods. Historically, measurements were continually provided by fixed sensors, e.g., moorings, or gathered from ships. Recently, an increase in the utilization of autonomous underwater vehicles has enabled a more dynamic data acquisition approach. However, we still do not utilize the full capabilities of these vehicles. Here we present algorithms that produce persistent monitoring missions for underwater vehicles by balancing path following accuracy and sampling resolution for a given region of interest, which addresses a pressing need among ocean scientists to efficiently and effectively collect high-value data. More specifically, this paper proposes a path planning algorithm and a speed control algorithm for underwater gliders, which together give informative trajectories for the glider to persistently monitor a patch of ocean. We optimize a cost function that blends two competing factors: maximize the information value along the path, while minimizing deviation from the planned path due to ocean currents. Speed is controlled along the planned path by adjusting the pitch angle of the underwater glider, so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long-term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California, as well as in Monterey Bay, California. The experimental results show significant improvements in data resolution and path reliability compared to previously executed sampling paths used in the respective regions.

From classroom resistance to school reform

In the project described in this chapter, a group of educationally disengaged high school students investigated their peers' perspectives of factors related to low aspiration for and access to university. On the basis of their findings, they created an informative DVD to address the student needs.

CDKN2A is not the principal target of deletions on the short arm of chromosome 9 in neuroendocrine (Merkel cell) carcinoma of the skin

The majority of small-cell lung cancers (SCLCs) express p16 but not pRb. Given our previous study showing loss of pRb in Merkel cell carcinoma (MCC)/neuroendocrine carcinoma of the skin and the clinicopathological similarities between SCLC and MCC, we wished to determine if this was also the case in MCC. Twenty-nine MCC specimens from 23 patients were examined for deletions at 10 loci on 9p and 1 on 9q. No loss of heterozygosity (LOH) was seen in 9 patients including 2 for which tumour and cell line DNAs were examined. Four patients had LOH for all informative loci on 9p. Ten tumours showed more limited regions of loss on 9p, and from these 2 common regions of deletion were determined. Half of all informative cases had LOH at D9S168, the most telomeric marker examined, and 3 specimens showed loss of only D9S168. A second region (IFNA-D9S126) showed LOH in 10 (44%) cases, and case MCC26 showed LOH for only D9S126, implicating genes centromeric of the CDKN2A locus. No mutations in the coding regions of p16 were seen in 7 cell lines tested, and reactivity to anti-p16 antibody was seen in all 11 tumour specimens examined and in 6 of 7 cell lines from 6 patients. Furthermore, all cell lines examined reacted with anti-p14(ARF) antibody. These results suggest that neither transcript of the CDKN2A locus is the target of deletions on 9p in MCC and imply the existence of tumour-suppressor genes mapping both centromeric and telomeric of this locus.

Change Point Estimation in Monitoring Survival Time

Precise identification of the time when a change in a hospital outcome has occurred enables clinical experts to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for survival time of a clinical procedure in the presence of patient mix in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the mean survival time of patients who underwent cardiac surgery. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time CUSUM control charts for different magnitude scenarios. The proposed estimator shows a better performance where a longer follow-up period, censoring time, is applied. In comparison with the alternative built-in CUSUM estimator, more accurate and precise estimates are obtained by the Bayesian estimator. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.

Wing shape as a potential discriminator of morphologically similar pest taxa within the Bactrocera dorsalis species complex (Diptera: Tephritidae)

Four morphologically cryptic species of the Bactrocera dorsalis fruit fly complex (B. dorsalis s.s., B. papayae, B. carambolae and B. philippinensis) are serious agricultural pests. As they are difficult to diagnose using traditional taxonomic techniques, we examined the potential for geometric morphometric analysis of wing size and shape to discriminate between them. Fifteen wing landmarks generated size and shape data for 245 specimens for subsequent comparisons among three geographically distinct samples of each species. Intraspecific wing size was significantly different within samples of B. carambolae and B. dorsalis s.s. but not within samples of B. papayae or B. philippinensis. Although B. papayae had the smallest wings (average centroid size=6.002 mm±0.061 SE) and B. dorsalis s.s. the largest (6.349 mm±0.066 SE), interspecific wing size comparisons were generally non-informative and incapable of discriminating species. Contrary to the wing size data, canonical variate analysis based on wing shape data discriminated all species with a relatively high degree of accuracy; individuals were correctly reassigned to their respective species on average 93.27% of the time. A single sample group of B. carambolae from locality 'TN Malaysia' was the only sample to be considerably different from its conspecific groups with regards to both wing size and wing shape. This sample was subsequently deemed to have been originally misidentified and likely represents an undescribed species. We demonstrate that geometric morphometric techniques analysing wing shape represent a promising approach for discriminating between morphologically cryptic taxa of the B. dorsalis species complex.

Molecular characterisation of environmental enterococci derived from water samples and assessment of associated public health hazards

Enterococci are versatile Gram-positive bacteria that can survive under extreme conditions. Most enterococci are non-virulent and found in the gastrointestinal tract of humans and animals. Other strains are opportunistic pathogens that contribute to a large number of nosocomial infections globally. Epidemiological studies demonstrated a direct relationship between the density of enterococci in surface waters and the risk of swimmer-associated gastroenteritis. The distribution of infectious enterococcal strains from the hospital environment or other sources to environmental water bodies through sewage discharge or other means, could increase the prevalence of these strains in the human population. Environmental water quality studies may benefit from focusing on a subset of Enterococcus spp. that are consistently associated with sources of faecal pollution such as domestic sewage, rather than testing for the entire genus. E. faecalis and E. faecium are potentially good focal species for such studies, as they have been consistently identified as the dominant Enterococcus spp. in human faeces and sewage. On the other hand enterococcal infections are predominantly caused by E. faecalis and E. faecium. The characterisation of E. faecalis and E. faecium is important in studying their population structures, particularly in environmental samples. In developing and implementing rapid, robust molecular genotyping techniques, it is possible to more accurately establish the relationship between human and environmental enterococci. Of particular importance, is to determine the distribution of high risk enterococcal clonal complexes, such as E. faecium clonal complex 17 and E. faecalis clonal complexes 2 and 9 in recreational waters. These clonal complexes are recognized as particularly pathogenic enterococcal genotypes that cause severe disease in humans globally. The Pimpama-Coomera watershed is located in South East Queensland, Australia and was investigated in this study mainly because it is used intensively for agriculture and recreational purposes and has a strong anthropogenic impact. The primary aim of this study was to develop novel, universally applicable, robust, rapid and cost effective genotyping methods which are likely to yield more definitive results for the routine monitoring of E. faecalis and E. faecium, particularly in environmental water sources. To fullfill this aim, new genotyping methods were developed based on the interrogation of highly informative single nucleotide polymorphisms (SNPs) located in housekeeping genes of both E. faecalis and E. faecium. SNP genotyping was successfully applied in field investigations of the Coomera watershed, South-East Queensland, Australia. E. faecalis and E. faecium isolates were grouped into 29 and 23 SNP profiles respectively. This study showed the high longitudinal diversity of E. faecalis and E. faecium over a period of two years, and both human-related and human-specific SNP profiles were identified. Furthermore, 4.25% of E. faecium strains isolated from water was found to correspond to the important clonal complex-17 (CC17). Strains that belong to CC17 cause the majority of hospital outbreaks and clinical infections globally. Of the six sampling sites of the Coomera River, Paradise Point had the highest number of human-related and human-specific E. faecalis and E. faecium SNP profiles. The secondary aim of this study was to determine the antibiotic-resistance profiles and virulence traits associated with environmental E. faecalis and E. faecium isolates compared to human pathogenic E. faecalis and E. faecium isolates. This was performed to predict the potential health risks associated with coming into contact with these strains in the Coomera watershed. In general, clinical isolates were found to be more resistant to all the antibiotics tested compared to water isolates and they harbored more virulence traits. Multi-drug resistance was more prevalent in clinical isolates (71.18% of E. faecalis and 70.3 % of E. faecium) compared to water isolates (only 5.66 % E. faecium). However, tetracycline, gentamicin, ciprofloxacin and ampicillin resistance was observed in water isolates. The virulence gene esp was the most prevalent virulence determinant observed in clinical isolates (67.79% of E. faecalis and 70.37 % of E. faecium), and this gene has been described as a human-specific marker used for microbial source tracking (MST). The presence of esp in water isolates (16.36% of E. faecalis and 19.14% of E. faecium) could be indicative of human faecal contamination in these waterways. Finally, in order to compare overall gene expression between environmental and clinical strains of E. faecalis, a comparative gene hybridization study was performed. The results of this investigation clearly demonstrated the up-regulation of genes associated with pathogenicity in E. faecalis isolated from water. The expression study was performed at physiological temperatures relative to ambient temperatures. The up-regulation of virulence genes demonstrates that environmental strains of E. faecalis can pose an increased health risk which can lead to serious disease, particularly if these strains belong to the virulent CC17 group. The genotyping techniques developed in this study not only provide a rapid, robust and highly discriminatory tool to characterize E. faecalis and E. faecium, but also enables the efficient identification of virulent enterococci that are distributed in environmental water sources.

Creating value in project management using PRINCE2

This important research is published at a critical time in the history of PRINCE2. The world’s project managers are under incredible scrutiny and pressure to ensure their projects deliver quality on time and on budget – and even more so during a world recession. The research shows that PRINCE2 goes a long way to helping them achieve these goals. Although its origins began in the UK, PRINCE2 now has a truly international reach. We are delighted that the Queensland University of Technology (QUT) has undertaken this global, thorough and informative research project. While it highlights the strengths of the methodology itself, the report also looks at the challenges organisations face when using a project management method such as PRINCE2. We’re sure the challenges will resonate with project managers around the world. Securing executive support to champion the adoption of PRINCE2, creating a robust business case and prioritising project governance are key issues that all project managers will grapple with during their career. The research also shows that to be thoroughly effective, organisations need to properly embed PRINCE2 and tailor it to suit their particular circumstances. Many successful organisations have sought the effective help of accredited consulting organisations to assist them in developing a programme to tailor and inculcate this method into their organisational culture. The latest version incorporates a whole chapter on tailoring PRINCE2. We believe that the publication of PRINCE2 Directing Successful Projects using PRINCE2 and the development of further support in the form of materials, mentoring and training for senior executives will be of significant benefit to contemporary project based organisations. The APM Group has already developed a qualification for sponsors in conjunction with the UK’s Home Office to help with this.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Performance analysis of PTP components for IEC 61850 process bus applications

New substation automation applications, such as sampled value process buses and synchrophasors, require sampling accuracy of 1 µs or better. The Precision Time Protocol (PTP), IEEE Std 1588, achieves this level of performance and integrates well into Ethernet based substation networks. This paper takes a systematic approach to the performance evaluation of commercially available PTP devices (grandmaster, slave, transparent and boundary clocks) from a variety of manufacturers. The ``error budget'' is set by the performance requirements of each application. The ``expenditure'' of this error budget by each component is valuable information for a system designer. The component information is used to design a synchronization system that meets the overall functional requirements. The quantitative performance data presented shows that this testing is effective and informative. Results from testing PTP performance in the presence of sampled value process bus traffic demonstrate the benefit of a ``bottom up'' component testing approach combined with ``top down'' system verification tests. A test method that uses a precision Ethernet capture card, rather than dedicated PTP test sets, to determine the Correction Field Error of transparent clocks is presented. This test is particularly relevant for highly loaded Ethernet networks with stringent timing requirements. The methods presented can be used for development purposes by manufacturers, or by system integrators for acceptance testing. A sampled value process bus was used as the test application for the systematic approach described in this paper. The test approach was applied, components were selected, and the system performance verified to meet the application's requirements. Systematic testing, as presented in this paper, is applicable to a range of industries that use, rather than develop, PTP for time transfer.

Beyond barcoding : a mitochondrial genomics approach to molecular phylogenetics and diagnostics of blowflies (Diptera: Calliphoridae)

Members of the Calliphoridae (blowflies) are significant for medical and veterinary management, due to the ability of some species to consume living flesh as larvae, and for forensic investigations due to the ability of others to develop in corpses. Due to the difficulty of accurately identifying larval blowflies to species there is a need for DNA-based diagnostics for this family, however the widely used DNA-barcoding marker, cox1, has been shown to fail for several groups within this family. Additionally, many phylogenetic relationships within the Calliphoridae are still unresolved, particularly deeper level relationships. Sequencing whole mt genomes has been demonstrated both as an effective method for identifying the most informative diagnostic markers and for resolving phylogenetic relationships. Twenty-seven complete, or nearly so, mt genomes were sequenced representing 13 species, seven genera and four calliphorid subfamilies and a member of the related family Tachinidae. PCR and sequencing primers developed for sequencing one calliphorid species could be reused to sequence related species within the same superfamily with success rates ranging from 61% to 100%, demonstrating the speed and efficiency with which an mt genome dataset can be assembled. Comparison of molecular divergences for each of the 13 protein-coding genes and 2 ribosomal RNA genes, at a range of taxonomic scales identified novel targets for developing as diagnostic markers which were 117–200% more variable than the markers which have been used previously in calliphorids. Phylogenetic analysis of whole mt genome sequences resulted in much stronger support for family and subfamily-level relationships. The Calliphoridae are polyphyletic, with the Polleninae more closely related to the Tachinidae, and the Sarcophagidae are the sister group of the remaining calliphorids. Within the Calliphoridae, there was strong support for the monophyly of the Chrysomyinae and Luciliinae and for the sister-grouping of Luciliinae with Calliphorinae. Relationships within Chrysomya were not well resolved. Whole mt genome data, supported the previously demonstrated paraphyly of Lucilia cuprina with respect to L. sericata and allowed us to conclude that it is due to hybrid introgression prior to the last common ancestor of modern sericata populations, rather than due to recent hybridisation, nuclear pseudogenes or incomplete lineage sorting.

Analysis of Cone-Beam CT using prior information

Treatment plans for conformal radiotherapy are based on an initial CT scan. The aim is to deliver the prescribed dose to the tumour, while minimising exposure to nearby organs. Recent advances make it possible to also obtain a Cone-Beam CT (CBCT) scan, once the patient has been positioned for treatment. A statistical model will be developed to compare these CBCT scans with the initial CT scan. Changes in the size, shape and position of the tumour and organs will be detected and quantified. Some progress has already been made in segmentation of prostate CBCT scans [1],[2],[3]. However, none of the existing approaches have taken full advantage of the prior information that is available. The planning CT scan is expertly annotated with contours of the tumour and nearby sensitive objects. This data is specific to the individual patient and can be viewed as a snapshot of spatial information at a point in time. There is an abundance of studies in the radiotherapy literature that describe the amount of variation in the relevant organs between treatments. The findings from these studies can form a basis for estimating the degree of uncertainty. All of this information can be incorporated as an informative prior into a Bayesian statistical model. This model will be developed using scans of CT phantoms, which are objects with known geometry. Thus, the accuracy of the model can be evaluated objectively. This will also enable comparison between alternative models.

The impact of litigation risk on corporate prospective disclosure : a review of the empirical literature

We review the literature on the impact of litigation risk (a form of external governance) on corporate prospective disclosure decisions as reflected in management earnings forecasts. From this analysis we identify four key areas for future research. First, litigation risk warrants more attention from researchers; currently it tends to be treated as a secondary factor impacting MEF decisions. Second, it would be informative from a governance perspective for researchers to explore why litigation risk has a differential impact on MEF decisions across countries. Third, understanding the interaction between litigation risk and forecast/firm-specific characteristics is important from management, investor and regulatory perspectives but is currently under-explored Last, research on the litigation risk and MEF attributes link is piecemeal and incomplete, requiring more integrated and expanded analysis.

mCOPA: analysis of heterogeneous features in cancer expression data

Background Cancer outlier profile analysis (COPA) has proven to be an effective approach to analyzing cancer expression data, leading to the discovery of the TMPRSS2 and ETS family gene fusion events in prostate cancer. However, the original COPA algorithm did not identify down-regulated outliers, and the currently available R package implementing the method is similarly restricted to the analysis of over-expressed outliers. Here we present a modified outlier detection method, mCOPA, which contains refinements to the outlier-detection algorithm, identifies both over- and under-expressed outliers, is freely available, and can be applied to any expression dataset. Results We compare our method to other feature-selection approaches, and demonstrate that mCOPA frequently selects more-informative features than do differential expression or variance-based feature selection approaches, and is able to recover observed clinical subtypes more consistently. We demonstrate the application of mCOPA to prostate cancer expression data, and explore the use of outliers in clustering, pathway analysis, and the identification of tumour suppressors. We analyse the under-expressed outliers to identify known and novel prostate cancer tumour suppressor genes, validating these against data in Oncomine and the Cancer Gene Index. We also demonstrate how a combination of outlier analysis and pathway analysis can identify molecular mechanisms disrupted in individual tumours. Conclusions We demonstrate that mCOPA offers advantages, compared to differential expression or variance, in selecting outlier features, and that the features so selected are better able to assign samples to clinically annotated subtypes. Further, we show that the biology explored by outlier analysis differs from that uncovered in differential expression or variance analysis. mCOPA is an important new tool for the exploration of cancer datasets and the discovery of new cancer subtypes, and can be combined with pathway and functional analysis approaches to discover mechanisms underpinning heterogeneity in cancers

Active versus passive screen time for young children

In this paper, we report some initial findings from our investigations into the Australian Government’s Longitudinal Study of Australian Children dataset. It is revealed that the majority of Australian children are exceeding the government’s Screen Time recommendations and that most of their screen time is spent as TV viewing, as opposed to video game play or computer use. In light of this finding,we review the body of research surrounding children’s engagement in Screen Time activities and the associated positive and negative effects. Based on existing evidence,we define two categories of Screen Time—Active Screen Time and Passive Screen Time. It is proposed that this distinction provides a more accurate classification of Screen Time and a more informative lens through which to consider the associated benefits and detrimental effects for young children.

Transferring a successful strategy for supporting accelerated nursing students from a small to a large cohort

In 2009 and 2010, withdrawal rates from a Pharmacology unit of accelerated QUT nursing students in the first year of their degree, were higher than for continuing students. The cohort of 216 accelerated students in 2011 had university or non-university qualification or equivalent experience and included domestic and international students. A previously tested intervention was introduced in 2011 to improve retention rates and support all Pharmacology students in their first year of nursing. The intervention involved a community website, on-line tutors and an “O week” workshop comprising information about library resources, effective learning strategies and learning tips from a previous student as well as review anatomy, physiology and microbiology lectures. Withdrawal rates for accelerated students in the Pharmacology unit improved and all students found the workshop and review lectures to be informative and valuable. The intervention was therefore successfully transferred to a large, diverse cohort of accelerated nursing students.