Radiographer commenting of trauma radiographs : a survey of the benefits, barriers and enablers to participation in an Australian healthcare setting

Introduction Radiographer abnormality detection systems that highlight abnormalities on trauma radiographs (‘red dot’ system) have been operating for more than 30 years. Recently, a number of pitfalls have been identified. These limitations initiated the evolution of a radiographer commenting system, whereby a radiographer provides a brief description of abnormalities identified in emergency healthcare settings. This study investigated radiographers' participation in abnormality detection systems, their perceptions of benefits, barriers and enablers to radiographer commenting, and perceptions of potential radiographer image interpretation services for emergency settings. Methods A cross-sectional survey was implemented. Participants included radiographers from four metropolitan hospitals in Queensland, Australia. Conventional descriptive statistics, histograms and thematic analysis were undertaken. Results Seventy-three surveys were completed and included in the analysis (68% response rate); 30 (41%) of respondents reported participating in abnormality detection in 20% or less of examinations, and 26(36%) reported participating in 80% or more of examinations. Five overarching perceived benefits of radiographer commenting were identified: assisting multidisciplinary teams, patient care, radiographer ability, professional benefits and quality of imaging. Frequently reported perceived barriers included ‘difficulty accessing image interpretation education’, ‘lack of time’ and ‘low confidence in interpreting radiographs’. Perceived enablers included ‘access to image interpretation education’ and ‘support from radiologist colleagues’. Conclusions A range of factors are likely to contribute to the successful implementation of radiographer commenting in addition to abnormality detection in emergency settings. Effective image interpretation education amenable to completion by radiographers would likely prove valuable in preparing radiographers for participation in abnormality detection and commenting systems in emergency settings.

Liability in negligence and the failure to disclose multiple risks in surgery : I would have been willing to run the risk

It has been 21 years since the decision in Rogers v Whitaker and the legal principles concerning informed consent and liability for negligence are still strongly grounded in this landmark High Court decision. This paper considers more recent developments in the law concerning the failure to disclose inherent risks in medical procedures, focusing on the decision in Wallace v Kam [2013] HCA 19. In this case, the appellant underwent a surgical procedure that carried a number of risks. The surgery itself was not performed in a sub-standard way, but the surgeon failed to disclose two risks to the patient, a failure that constituted a breach of the surgeon’s duty of care in negligence. One of the undisclosed risks was considered to be less serious than the other, and this lesser risk eventuated causing injury to the appellant. The more serious risk did not eventuate, but the appellant argued that if the more serious risk had been disclosed, he would have avoided his injuries completely because he would have refused to undergo the procedure. Liability was disputed by the surgeon, with particular reference to causation principles. The High Court of Australia held that the appellant should not be compensated for harm that resulted from a risk he would have been willing to run. We examine the policy reasons underpinning the law of negligence in this specific context and consider some of the issues raised by this unusual case. We question whether some of the judicial reasoning adopted in this case, represents a significant shift in traditional causation principles.

A new distributed control strategy to coordinate multiple dstatcoms in LV network

Voltage rise is the main issue which limits the capacity of Low Voltage (LV) network to accommodate more Renewable Energy (RE) sources. In addition, voltage drop at peak load period is a significant power quality concern. This paper proposes a new robust voltage support strategy based on distributed coordination of multiple distribution static synchronous compensators (DSTATCOMs). The study focuses on LV networks with PV as the RE source for customers. The proposed approach applied to a typical LV network and its advantages are shown comparing with other voltage control strategies.

Enabling safe autonomous driving in real-world city traffic using multiple criteria decision making

This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e., the autonomous vehicles' ability to make appropriate driving decisions in city road traffic situations. The paper explains the overall controls system architecture, the decision making task decomposition, and focuses on how Multiple Criteria Decision Making (MCDM) is used in the process of selecting the most appropriate driving maneuver from the set of feasible ones. Experimental tests show that MCDM is suitable for this new application area.

Multiple map hypotheses for planning and navigating in non-stationary environments

This paper presents a method to enable a mobile robot working in non-stationary environments to plan its path and localize within multiple map hypotheses simultaneously. The maps are generated using a long-term and short-term memory mechanism that ensures only persistent configurations in the environment are selected to create the maps. In order to evaluate the proposed method, experimentation is conducted in an office environment. Compared to navigation systems that use only one map, our system produces superior path planning and navigation in a non-stationary environment where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners.

Effects of wireless sensor network uncertainties on output-only modal analysis employing merged data of multiple tests

The use of Wireless Sensor Networks (WSNs) for vibration-based Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data asynchronicity and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. Based on a brief review, this paper first reveals that Data Synchronization Error (DSE) is the most inherent factor amongst uncertainties of SHM-oriented WSNs. Effects of this factor are then investigated on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when merging data from multiple sensor setups. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as benchmark data after being added with a certain level of noise to account for the higher presence of this factor in SHM-oriented WSNs. From this source, a large number of simulations have been made to generate multiple DSE-corrupted datasets to facilitate statistical analyses. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with DSE at a relaxed level. Finally, the combination of preferred OMA techniques and the use of the channel projection for the time-domain OMA technique to cope with DSE are recommended.

Promoting posttraumatic growth in police recruits : preliminary results of a randomised controlled resilience intervention trial

Recent research has demonstrated that the same experiences that may elicit symptoms of post-traumatic stress disorder (PTSD) in emergency service personnel can also provide a catalyst for positive personal changes such as posttraumatic growth (PTG). In this research newly recruited police officers (N = 412) participated in a randomised control trial of a program specifically designed to promote mental health. On entry to the academy, new recruits were randomly allocated, by classrooms, to either a treatment as usual condition (i.e., existing psychoeducation program) or to the intervention group. The Promoting Resilient Officers (PRO) program is a resilience building intervention adapted from an earlier resilience building program in collaboration with the police service. The PRO program also includes additional components on trauma and PTG. The current research included the participants who had experienced trauma prior to or during the research period (N = 246). It was hypothesised that participation in the PRO program would increase levels of PTG and lower levels of PTSD when compared to recruits in the control condition. Using multilevel modelling and post-hoc analyses, results indicated there were significantly higher levels of PTG across multiple dimensions when compared to the control group. There was no effect on PTSD symptoms with both conditions showing a floor effect. The research indicated the potential value of developing interventions that elicit reflections on the potential for positive as well as negative outcomes of experiencing traumatic and other highly challenging events.

A Combined Renormalization Group-Multiple Scale Method for Singularly Perturbed Problems

This paper introduces a straightforward method to asymptotically solve a variety of initial and boundary value problems for singularly perturbed ordinary differential equations whose solution structure can be anticipated. The approach is simpler than conventional methods, including those based on asymptotic matching or on eliminating secular terms. © 2010 by the Massachusetts Institute of Technology.

Multiple modular additions and crossword puzzle attack on NLSv2

NLS is a stream cipher which was submitted to the eSTREAM project. A linear distinguishing attack against NLS was presented by Cho and Pieprzyk, which was called Crossword Puzzle (CP) attack. NLSv2 is a tweak version of NLS which aims mainly at avoiding the CP attack. In this paper, a new distinguishing attack against NLSv2 is presented. The attack exploits high correlation amongst neighboring bits of the cipher. The paper first shows that the modular addition preserves pairwise correlations as demonstrated by existence of linear approximations with large biases. Next, it shows how to combine these results with the existence of high correlation between bits 29 and 30 of the S-box to obtain a distinguisher whose bias is around 2^−37. Consequently, we claim that NLSv2 is distinguishable from a random cipher after observing around 2^74 keystream words.

Towards a multiple-goal pursuit and multilevel view of continuing information technology usage : a process model integration and a research agenda

The value of information technology (IT) is often realized when continuously being used after users’ initial acceptance. However, previous research on continuing IT usage is limited for dismissing the importance of mental goals in directing users’ behaviors and for inadequately accommodating the group context of users. This in-progress paper offers a synthesis of several literature to conceptualize continuing IT usage as multilevel constructs and to view IT usage behavior as directed and energized by a set of mental goals. Drawing from the self-regulation theory in the social psychology, this paper proposes a process model, positioning continuing IT usage as multiple-goal pursuit. An agent-based modeling approach is suggested to further explore causal and analytical implications of the proposed process model.

Robust multiple-sensing-modality data fusion using Gaussian Process Implicit Surfaces

The ability to build high-fidelity 3D representations of the environment from sensor data is critical for autonomous robots. Multi-sensor data fusion allows for more complete and accurate representations. Furthermore, using distinct sensing modalities (i.e. sensors using a different physical process and/or operating at different electromagnetic frequencies) usually leads to more reliable perception, especially in challenging environments, as modalities may complement each other. However, they may react differently to certain materials or environmental conditions, leading to catastrophic fusion. In this paper, we propose a new method to reliably fuse data from multiple sensing modalities, including in situations where they detect different targets. We first compute distinct continuous surface representations for each sensing modality, with uncertainty, using Gaussian Process Implicit Surfaces (GPIS). Second, we perform a local consistency test between these representations, to separate consistent data (i.e. data corresponding to the detection of the same target by the sensors) from inconsistent data. The consistent data can then be fused together, using another GPIS process, and the rest of the data can be combined as appropriate. The approach is first validated using synthetic data. We then demonstrate its benefit using a mobile robot, equipped with a laser scanner and a radar, which operates in an outdoor environment in the presence of large clouds of airborne dust and smoke.

The child pose : the role of the nonhuman natural world in recovery from psychological trauma

This thesis by creative work explores relationships among human beings, the nonhuman natural world and language. It addresses the central research question: 'How can a novel embody a narrative of recovery from psychological trauma in which recovery is primarily a function of the character's subjective interaction with nature?' The novel, 'The Child Pose', tells the story of a woman's recovery from psychological trauma. The thesis draws on the psychoanalytic theory of Jacques Lacan, who saw the human subject as fundamentally split and alienated, and therefore inherently vulnerable to being destabilised by trauma. Situating the narrative of recovery within the emerging fields of ecocriticism and ecopsychology, the research constructs psychological recovery through interaction with nature as a transformation of subjectivity: the creation of a new, more stable and connected kind of subject, which Jordan (2012) has called 'the ecological subject'.

The effect of cryotherapy on the vascular regeneration following closed soft tissue trauma

INTRODUCTION Icing (cryotherapy) is being widely used for the treatment of closed soft tissue trauma (CSTT), such as those resulting from sport injuries. It is believed that cryotherapy induces vasoconstriction and through this mechanism reduces inflammation [1]. However, the impact of this technique on the healing of impaired vasculature and muscle injuries following trauma remains controversial. Recent evidence suggests that the muscle regeneration is delayed after cryotherapy [2]. Consequently, we aimed to investigate the effect of cryotherapy on the vascular morphology following CSTT using an experimental model in rats by contrast-enhanced micro-CT imaging. METHODS Fifty four rats were divided into three main groups: control (no injury, n=6), sham (CSTT but no icing treatment, n=24) and icing (CSTT, treated with one session of ice block massaged directly on the injured muscle for 20 minutes, n=24). The CSTT was induced to the left thigh (Biceps Femoris) of anaesthetised rats (Male, Wistar) to create a standardized and reproducible vascular and muscle injury using an impact device [3]. Following trauma, animals were euthanized after 1, 3, 7, and 28 days healing time (n=6 for each time point). For a three-dimensional vascular morphological assessment, the blood vessels of euthanised rats were flushed with heparinised saline and then perfused with a radio-opaque contrast agent (Microfil, MV 122, Flowtech, USA) using an infusion pump. Both hind-limbs were dissected, and then the injured and non-injured limbs were imaged using a micro-CT scanner (µCT 40, Scanco Medical, Switzerland) and total volume of the perfused blood vessels (TVV) was calculated. More detailed morphological parameters such as vessel volume (VV), diameter (VD), spacing (VSp), number (VN) and connectivity (VConn) were quantified through high resolution (6 µm), micro-CT-scanned biopsy samples (diameter: 8mm) taken directly from the region of the injured muscles. The biopsies were then analysed histologically to confirm the results derived from contrast-enhanced micro-CT imaging. RESULTS AND DISCUSSION The TVV was significantly higher in the injured legs compared to the non-injured legs at day 1 and 7 in the sham group and at day 28 in both sham and icing groups. The biopsies from the injured legs of the icing group showed a significant reduction in VV, VN, VD, VConn and an increase in VSp compared to those in the sham and control groups at days 1, 3 and 7, post injury. While the injured legs of the sham group exhibited a decrease in VN and VConn 28 days post trauma, indicating a return to the original values prior to trauma, these parameters had increased in the icing group (Figure 1). Also, at day 1 post injury, VV and VD of the injured legs were significantly higher in the sham group compared to the icing group, which may be attributed to the effect of vasoconstriction induced by icing. Further histomorphological evaluation of day 1 post injury, indicated that although cryotherapy significantly reduced the injury size and influx of inflammatory cells, including macrophages and neutrophils, a delay in vascular and muscle fiber regeneration was found at later time points confirming other reports from the literature [2]. CONCLUSIONS We have demonstrated using micro-CT imaging that the vascular morphology changes after CSTT, and that its recovery is affected by therapeutic modalities such as icing. This may be useful for the development of future clinical monitoring, diagnosis and treatment of CSTT. While icing reduces the swelling after trauma, our results suggest that it may delay the recovery of the vasculature in the injured tissue.

Simultaneous localization and planning on multiple map hypotheses

This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.