Improving robot vision models for object detection through interaction

We propose a method for learning specific object representations that can be applied (and reused) in visual detection and identification tasks. A machine learning technique called Cartesian Genetic Programming (CGP) is used to create these models based on a series of images. Our research investigates how manipulation actions might allow for the development of better visual models and therefore better robot vision. This paper describes how visual object representations can be learned and improved by performing object manipulation actions, such as, poke, push and pick-up with a humanoid robot. The improvement can be measured and allows for the robot to select and perform the `right' action, i.e. the action with the best possible improvement of the detector.

Building cross-scale models of epigenetic mechanisms

Epigenetic changes correspond to heritable modifications of the chromosome structure, which do not involve alteration of the DNA sequence but do affect gene expression. These mechanisms play an important role in normal cell differentiation, but aberration is associated also with several diseases, including cancer and neural disorders. In consequence, despite intensive studies in recent years, the contribution of modifications remains largely unquantified due to overall system complexity and insufficient data. Computational models can provide powerful auxiliary tools to experimentation, not least as scales from the sub-cellular through cell populations (or to networks of genes) can be spanned. In this paper, the challenges to development, of realistic cross-scale models, are discussed and illustrated with respect to current work.

Multi-parametric hydrogels support 3D in vitro bioengineered microenvironment models of tumour angiogenesis

Tumour microenvironment greatly influences the development and metastasis of cancer progression. The development of three dimensional (3D) culture models which mimic that displayed in vivo can improve cancer biology studies and accelerate novel anticancer drug screening. Inspired by a systems biology approach, we have formed 3D in vitro bioengineered tumour angiogenesis microenvironments within a glycosaminoglycan-based hydrogel culture system. This microenvironment model can routinely recreate breast and prostate tumour vascularisation. The multiple cell types cultured within this model were less sensitive to chemotherapy when compared with two dimensional (2D) cultures, and displayed comparative tumour regression to that displayed in vivo. These features highlight the use of our in vitro culture model as a complementary testing platform in conjunction with animal models, addressing key reduction and replacement goals of the future. We anticipate that this biomimetic model will provide a platform for the in-depth analysis of cancer development and the discovery of novel therapeutic targets.

Environmental conditions are important for establishing and evaluating pre-clinical models of GVHD

GVHD remains the major complication of allo-HSCT. Murine models are the primary system used to understand GVHD, and to develop potential therapies. Several factors are critical for GVHD in these models; including histo- compatibility, conditioning regimen, and T-cell number. We serendipitously found that environmental factors such as the caging system and bedding also significantly impact the kinetics of GVHD in these models. This is important because such factors may influence the experimental conditions required to cause GVHD and how mice respond to various treatments. Consequently, this is likely to alter interpretation of results between research groups, and the perceived effectiveness of experimental therapies.

Emergency department models of care in the context of care quality and cost: A systematic review

To identify current ED models of care and their impact on care quality, care effectiveness, and cost. A systematic search of key health databases (Medline, CINAHL, Cochrane, EMbase) was conducted to identify literature on ED models of care. Additionally, a focused review of the contents of 11 international and national emergency medicine, nursing and health economic journals (published between 2010 and 2013) was undertaken with snowball identification of references of the most recent and relevant papers. Articles published between 1998 and 2013 in the English language were included for initial review by three of the authors. Studies in underdeveloped countries and not addressing the objectives of the present study were excluded. Relevant details were extracted from the retrieved literature, and analysed for relevance and impact. The literature was synthesised around the study's main themes. Models described within the literature mainly focused on addressing issues at the input, throughput or output stages of ED care delivery. Models often varied to account for site specific characteristics (e.g. onsite inpatient units) or to suit staffing profiles (e.g. extended scope physiotherapist), ED geographical location (e.g. metropolitan or rural site), and patient demographic profile (e.g. paediatrics, older persons, ethnicity). Only a few studies conducted cost-effectiveness analysis of service models. Although various models of delivering emergency healthcare exist, further research is required in order to make accurate and reliable assessments of their safety, clinical effectiveness and cost-effectiveness.

BPMN Miner: Automated Discovery of BPMN Process Models with Hierarchical Structure

Existing techniques for automated discovery of process models from event logs gen- erally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of hierarchical BPMN models con- taining interrupting and non-interrupting boundary events and activity markers. The technique employs functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are then discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery tech- niques, it is possible to filter out noise in the event log arising for example from data entry errors or missing events. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.

Alive SMC^2: Bayesian model selection for low-count time series models with intractable likelihoods

In this paper we present a new method for performing Bayesian parameter inference and model choice for low count time series models with intractable likelihoods. The method involves incorporating an alive particle filter within a sequential Monte Carlo (SMC) algorithm to create a novel pseudo-marginal algorithm, which we refer to as alive SMC^2. The advantages of this approach over competing approaches is that it is naturally adaptive, it does not involve between-model proposals required in reversible jump Markov chain Monte Carlo and does not rely on potentially rough approximations. The algorithm is demonstrated on Markov process and integer autoregressive moving average models applied to real biological datasets of hospital-acquired pathogen incidence, animal health time series and the cumulative number of poison disease cases in mule deer.

Applying metaethical and normative claims of moral relativism to (shareholder and stakeholder) models of corporate governance

There has, in recent decades, been considerable scholarship regarding the moral aspects of corporate governance,and differences in corporate governance practices around the world have been widely documented and investigated. In such a context, the claims associated with moral relativism are relevant. The purpose of this paper is to provide a detailed consideration of how the metaethical and normative claims of moral relativism in particular can be applied to corporate governance. This objective is achieved, firstly, by reviewing what is meant by metaethical moral relativism and identifying two ways in which the metaethical claim can be assessed. The possibility of a single, morally superior model of corporate governance is subsequently considered through an analysis of prominent works justifying the shareholder and stakeholder approaches, together with a consideration of academic agreement in this area. The paper then draws on the work of Wong (Moral relativity, University of California Press, Berkeley, CA, 1984, A companion to ethics, Blackwell, Malden, 1993, Natural moralities: A defense of pluralistic relativism,Oxford University Press, Oxford, 2006), firstly in providing an argument supporting metaethical moral relativism and secondly regarding values of tolerance and/or accommodation that can contribute to the normative claim. The paper concludes by proposing an argument that it is morally wrong to impose a model of corporate governance where there are differences in moral judgements relevant to corporate governance, or to interfere with a model in similar circumstances, and closes with consideration of the argument’s implications.

Fractional models in space for diffusive processes in heterogeneous media with applications in cell motility and electrical signal propagation

This work addresses fundamental issues in the mathematical modelling of the diffusive motion of particles in biological and physiological settings. New mathematical results are proved and implemented in computer models for the colonisation of the embryonic gut by neural cells and the propagation of electrical waves in the heart, offering new insights into the relationships between structure and function. In particular, the thesis focuses on the use of non-local differential operators of non-integer order to capture the main features of diffusion processes occurring in complex spatial structures characterised by high levels of heterogeneity.

Remaining useful life prediction of rotating equipment using covariate-based hazard models : industry applications

The ability to estimate the expected Remaining Useful Life (RUL) is critical to reduce maintenance costs, operational downtime and safety hazards. In most industries, reliability analysis is based on the Reliability Centred Maintenance (RCM) and lifetime distribution models. In these models, the lifetime of an asset is estimated using failure time data; however, statistically sufficient failure time data are often difficult to attain in practice due to the fixed time-based replacement and the small population of identical assets. When condition indicator data are available in addition to failure time data, one of the alternate approaches to the traditional reliability models is the Condition-Based Maintenance (CBM). The covariate-based hazard modelling is one of CBM approaches. There are a number of covariate-based hazard models; however, little study has been conducted to evaluate the performance of these models in asset life prediction using various condition indicators and data availability. This paper reviews two covariate-based hazard models, Proportional Hazard Model (PHM) and Proportional Covariate Model (PCM). To assess these models’ performance, the expected RUL is compared to the actual RUL. Outcomes demonstrate that both models achieve convincingly good results in RUL prediction; however, PCM has smaller absolute prediction error. In addition, PHM shows over-smoothing tendency compared to PCM in sudden changes of condition data. Moreover, the case studies show PCM is not being biased in the case of small sample size.

Importance of animal models in schizophrenia research

Objective This review aims to summarize the importance of animal models for research on psychiatric illnesses, particularly schizophrenia. Method and Results Several aspects of animal models are addressed, including animal experimentation ethics and theoretical considerations of different aspects of validity of animal models. A more specific discussion is included on two of the most widely used behavioural models, psychotropic drug-induced locomotor hyperactivity and prepulse inhibition, followed by comments on the difficulty of modelling negative symptoms of schizophrenia. Furthermore, we emphasize the impact of new developments in molecular biology and the generation of genetically modified mice, which have generated the concept of behavioural phenotyping. Conclusions Complex psychiatric illnesses, such as schizophrenia, cannot be exactly reproduced in species such as rats and mice. Nevertheless, by providing new information on the role of neurotransmitter systems and genes in behavioural function, animal 'models' can be an important tool in unravelling mechanisms involved in the symptoms and development of such illnesses, alongside approaches such as post-mortem studies, cognitive and psychophysiological studies, imaging and epidemiology.

Neurodevelopmental animal models of schizophrenia: Effects on prepulse inhibition

Epidemiological studies have shown increased incidence of schizophrenia in patients subjected to different forms of pre- or perinatal stress. However, as the onset of schizophrenic illness does not usually occur until adolescence or early adulthood, it is not yet fully understood how disruption of early brain development may ultimately lead to malfunction years later. In order to elucidate a possible role for neurodevelopmental factors in the pathogenesis of schizophrenia and to highlight potential new treatments, animal models are needed. Prepulse inhibition (PPI) is a model of sensorimotor gating mechanisms in the brain. It is disrupted in schizophrenia patients and the disruption can be reversed with atypical antipsychotics. It has been widely used in animal studies to explore central mechanisms possibly involved in schizophrenia. There has been a recent surge of behavioural and neurochemical animal studies on neurodevelopmental models, particularly on the effects of postweaning isolation, maternal separation and neonatal lesions of the hippocampus. In these models, long lasting alterations in behaviour and/or molecular changes in specific brain regions are observed, comparable to those seen in schizophrenia. The aim of this article is to critically review the available literature on such neurodevelopmental animal models with special focus on the effects on PPI and brain regions that are putatively involved in regulation of PPI.

The development of virtual leaf surface models for interactive agrichemical spray applications

This project constructed virtual plant leaf surfaces from digitised data sets for use in droplet spray models. Digitisation techniques for obtaining data sets for cotton, chenopodium and wheat leaves are discussed and novel algorithms for the reconstruction of the leaves from these three plant species are developed. The reconstructed leaf surfaces are included into agricultural droplet spray models to investigate the effect of the nozzle and spray formulation combination on the proportion of spray retained by the plant. A numerical study of the post-impaction motion of large droplets that have formed on the leaf surface is also considered.

Scoping study into wound management nurse practitioner models of practice

Objectives The primary objective of this research was to investigate wound management nurse practitioner (WMNP) models of service for the purposes of identifying parameters of practice and how patient outcomes are measured. Methods A scoping study was conducted with all authorised WMNPs in Australia from October to December 2012 using survey methodology. A questionnaire was developed to obtain data on the role and practice parameters of authorised WMNPs in Australia. The tool comprised seven sections and included a total of 59 questions. The questionnaire was distributed to all members of the WMNP Online Peer Review Group, to which it was anticipated the majority of WMNPs belonged. Results Twenty-one WMNPs responded (response rate 87%), with the results based on a subset of respondents who stated that, at the time of the questionnaire, they were employed as a WMNP, therefore yielding a response rate of 71% (n≤15). Most respondents (93%; n≤14) were employed in the public sector, with an average of 64 occasions of service per month. The typical length of a new case consultation was 60min, with 32min for follow ups. The most frequently performed activity was wound photography (83%; n≤12), patient, family or carer education (75%; n≤12), Doppler ankle-brachial pressure index assessment (58%; n≤12), conservative sharp wound debridement (58%; n≤12) and counselling (50%; n≤12). The most routinely prescribed medications were local anaesthetics (25%; n≤12) and oral antibiotics (25%; n≤12). Data were routinely collected by 91% of respondents on service-related and wound-related parameters to monitor patient outcomes, to justify and improve health services provided. Conclusion This study yielded important baseline information on this professional group, including data on patient problems managed, the types of interventions implemented, the resources used to accomplish outcomes and how outcomes are measured.

A low-cost attack on branch-based software watermarking schemes

In 2005, Ginger Myles and Hongxia Jin proposed a software watermarking scheme based on converting jump instructions or unconditional branch statements (UBSs) by calls to a fingerprint branch function (FBF) that computes the correct target address of the UBS as a function of the generated fingerprint and integrity check. If the program is tampered with, the fingerprint and integrity checks change and the target address will not be computed correctly. In this paper, we present an attack based on tracking stack pointer modifications to break the scheme and provide implementation details. The key element of the attack is to remove the fingerprint and integrity check generating code from the program after disassociating the target address from the fingerprint and integrity value. Using the debugging tools that give vast control to the attacker to track stack pointer operations, we perform both subtractive and watermark replacement attacks. The major steps in the attack are automated resulting in a fast and low-cost attack.