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© 2018 Australian College of Nursing Ltd Background: There is unprecedented increase in use of simulation-based education in healthcare settings. The key driver is improving quality and safety in healthcare. To date, there is limited understanding of the degree to which this goal has been achieved. Aim: This scoping review aimed to explore the extent to which simulation-based education in healthcare has addressed and impacted contemporary patient safety priorities. Methods: Systematic searches of literature (2007–2016) were based on each of 10 patient safety priorities articulated in Australia's National Safety and Quality Health Service Standards and New Zealand's Health, Quality and Safety Indicators and markers. Included primary studies evaluated transferability to practice and/or behavioural change and improved patient outcomes, based on Kirkpatrick's training evaluation model Level 3 and Level 4. Findings: Fifteen papers met inclusion criteria. Studies aligned with four of ten National Safety and Quality Health Service Standards: (3). Preventing and controlling healthcare associated infections; (4). Medication safety; (6). Clinical handover; (9). Recognising and responding to clinical deterioration. The studies were indicative of potential for simulation-based education to have a significant impact on patient safety. Discussion: Studies that qualify as translational science, demonstrating changes in clinician behaviours and improved patient outcomes, are emerging. Little evidence from Australian and New Zealand contexts suggests that outcomes of simulation-based education in this region are not commensurate with the significant government investments. Conclusion: Translational studies, despite being difficult to design and conduct, should form part of a thematic, sustained and cumulative program of simulation-based research to identify translational science.

© 2018 International Nursing Association for Clinical Simulation and Learning Clinical simulation is an essential component of health professional education. Digital technologies can provide students with near-reality, interactive virtual simulation learning experiences on static and mobile appliances. Clarification is needed, however, regarding the various types of virtual simulation and the different program components. We drew on published literature to define virtual simulation modalities and to offer definitive terminology to clarify the nomenclature and composition of virtual simulation. Reporting should include description of ‘Fidelity’ ‘Immersion’ and ‘Patient’ to add clarity and utility to research in the field.

© 2018 Elsevier B.V. Objective: To identify communication patterns of Registered Nurses regarding patients’ use of complementary therapies. Methods: A cross-sectional online survey conducted in 2017 recruited Australian Registered Nurses working in any area of nursing. Results: Responses of 614 Registered Nurses were analysed. Patient-initiated discussion of complementary therapies were common for 77% of nurses; nurse-initiated discussions were perceived by 73% (sometimes/almost always/always). Nurses’ personal use of complementary therapies predicted discussion with patients and education-based, oncology, or aged care/rehabilitation nurses were most likely to initiate dialogue. Many (55%) did not ‘recommend’ a particular therapy, although 12% ‘almost always/always’ did so. Four out of five nurses (84%) documented patients’ use and communicated with medical/nursing colleagues about this use. Conversely, 61% ‘never’ or ‘almost never’ communicated with a complementary therapy practitioner. Conclusion: Nurses working in Australia often discuss complementary therapies, however they rarely specifically recommend their use. Their workplace environment and clinical context influenced nurses’ willingness to communicate about complementary therapy use. Practice implications evidence: suggests the need for policy development to promote communication between mainstream healthcare providers and complementary therapy practitioners to support the delivery of safe, high quality patient care.

© 2018 John Wiley & Sons Ltd Aim: To explore Registered Nurses’ attitudes and behaviour towards patients’ use of complementary therapies. Background: Despite high rates of use of complementary therapies by the general population, little is known of how nurses respond to patients’ use of these therapies. Design: A two-phase sequential exploratory mixed methods design. Methods: Nineteen Registered Nurses working in Australia participated in a semi-structured interview in 2015–2016 and emerging themes informed the development of a quantitative survey instrument administered online nationwide in 2016. Findings: Emerging key themes “Promoting safe care”; “Seeking complementary therapies knowledge”;” Supporting holistic health care”; and “Integrating complementary therapies in practice” were reflected in survey results. Survey responses (N = 614) revealed >90% agreement that complementary therapies align with a holistic view of health and that patients have the right to use them. Most nurses (77.5%) discussed complementary therapies with patients and 91.8% believed nurses should have some understanding of the area. One-third did not recommend complementary therapies and there was a lack of overall consensus as to whether these therapies should be integrated into nursing practice. Nurses with training in complementary therapies held more positive views than those without. Conclusion: Nurses were generally supportive of patients’ interest in complementary therapies, although their primary concern was safety of the patient. Despite broad acceptance that nurses should have a basic understanding of complementary therapies, there was a lack of consensus about recommendation, integration into nursing practice and referral. Further research should explore how nurses can maintain safe, patient-centred care in the evolving pluralistic healthcare system.

3D Direct Numerical Simulations (DNS) of autoignition in turbulent non-premixed flows between fuel and hotter air have been carried out using both 1-step and complex chemistry consisting of a 22 species n-heptane mechanism to investigate spontaneous ignition timing and location. The simple chemistry results showed that the previous findings from 2D DNS that ignition occurred at the most reactive mixture fraction (ξMR ) and at small values of the conditional scalar dissipation rate (N|ξMR ) are valid also for 3D turbulent mixing fields. Performing the same simulation many times with different realizations of the initial velocity field resulted in a very narrow statistical distribution of ignition delay time, consistent with a previous conjecture that the first appearance of ignition is correlated with the low-N content of the conditional probability density function of N. The simulations with complex chemistry for conditions outside the Negative Temperature Coefficient (NTC) regime show behaviour similar to the single-step chemistry simulations. However, in the NTC regime, the most reactive mixture fraction is very rich and ignition seems to occur at high values of scalar dissipation.Copyright © 2006 by ASME

This paper focuses on changes in the educational preparation of undergraduate nurses in line with contemporary primary and preventative healthcare models. We evaluated a new Australian nursing and community care degree programme using focus groups with 38 students in their first years of study, and quantitative performance data (regarding entry, performance and course attrition). Four main themes were identified related to students' course experience: 'I think community health should be an elective'; 'Focus on relevance to practice'; 'Teaching by non-nursing academics' and 'Access to support during transition to university.' Overall pass rates were 94% (first year) and 97% (second year) with a low 11% attrition rate. We conclude that based on prior experiences and stereotypical views, students may be ambivalent about the inclusion of primary and preventative care models which nevertheless are essential to enhance practice and to prepare the future nursing workforce.

With the fast growth of World Wide Web 2.0, a great number of opinions about a variety of products have been published in blogs, forums, and social networks. Opinion mining tools are needed to enable users to efficiently process a large number of reviews found online, in order to determine the underlying opinions. This paper presents a new methodology for semantic modelling of the domain knowledge for opinion mining. In particular, the new methodology focuses on modelling the domain knowledge in such a way that it can be translated to a formal ontology, which can then be automatically enriched with ground facts obtained from public Linked Open Data resources. The methodology also considers procedures to link between the formal ontology and Natural Language Processing. Our approach successfully enriches the ontology with the relevant ground facts. This ontology can then be used to perform a variety of data mining tasks including sentiment analysis and information retrieval.

16th UKSim-AMSS International Conference on Computer Modelling and Simulation (UKSim) -- MAR 26-28, 2014 -- Cambridge, ENGLAND, WOS: 000411854100049, In this study, a modified neural filtering algorithm is presented for tracking of chaotic signals. A multilayer neural network (MLNN) structure is used in proposed design as a nonlinear adaptive filtering tool. Initially, the MLNN is linearized using Taylor series expansion and then the weight vector update rule is designed by using Lyapunov stability theory (LST) to adaptively update the weights of the MLNN. The tracking capability of the proposed algorithm is improved by using adaptation gain rate parameter "a(k)" which is iteratively adjusted itself depending on sequential tracking errors rate. The tracking ability of the proposed algorithm is tested on two chaotic signals and compared with conventional algorithms. The simulation results have supported that the proposed neural filtering algorithm achieved better performance., UK Simulat Soc, Asia Modelling & Simulat Sect, IEEE Comp Soc, IEEE Reg 8, European Federat Simulat Soc, European Council Modelling & Simulat, Kingston Univ, Imperial Coll,, Norwegian Univ Sci & Technol, Nottingham Trent Univ, Univ Technol Malaysia, Univ Sci Malaysia, Univ Malaysia Pahang, Univ Malaysia Sabah, Univ Technol Mara, Univ Malaysia Perlis, IEEE UK & RI, IEEE Reg 10, Machine Intelligence Res Labs, IEEE