308 resultados para high-level synthesis


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Objective. To assess medical and nursing students’ knowledge, attitudes, and practices (KAP) regarding human immunodeficiency virus (HIV) in Fiji. Methods. A cross-sectional study of 275 medical and 252 nursing students that participated in a questionnaire survey on HIV KAP. Data was analysed according to their gender, program of study, and academic year. Results. The mean HIV knowledge (HK) and attitude scores were 16.0 and 41.3, respectively. Mean HK score was significantly higher in males compared to females. Significant positive correlations were found between HK and academic year for medical () and nursing () students and between HK and attitude scores (). The majority of students indicated fear in contracting HIV through clinical practice and felt that health care workers have the right to know a patients HIV status for their own safety. The majority would wear gloves to touch a patient if suspected of HIV. Conclusions. The study found a high level of HIV knowledge and positive attitude towards HIV patients. However, respondents also displayed negative attitudes and unacceptable practices probably due to fear. Training institutions need to ensure that students gain accurate knowledge on HIV especially on transmission routes to allay the fear of caring for HIV-infected patients.

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Semantic Web offers many possibilities for future Web technologies. Therefore, it is a need to search for ways that can bring the huge amount of unstructured documents from current Web to Semantic Web automatically. One big challenge in searching for such ways is how to understand patterns by both humans and machine. To address this issue, we present an innovative model which interprets patterns to high level concepts. These concepts can explain the patterns' meanings in a human understandable way while improving the information filtering performance. The model is evaluated by comparing it against one state-of-the-art benchmark model using standard Reuters dataset. The results show that the proposed model is successful. The significance of this model is three fold. It gives a way to interpret text mining output, provides a technique to find concepts relevant to the whole set of patterns which is an essential feature to understand the topic, and to some extent overcomes information mismatch and overload problems of existing models. This model will be very useful for knowledge based applications.

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The aim of the study was to assess the feasibility and effectiveness of aquatic‐based exercise in the form of deep water running ( DWR ) as part of a multimodal physiotherapy programme ( MMPP ) for breast cancer survivors. A controlled clinical trial was conducted in 42 primary breast cancer survivors recruited from community‐based P rimary C are C entres. Patients in the experimental group received a MMPP incorporating DWR , 3 times a week, for an 8‐week period. The control group received a leaflet containing instructions to continue with normal activities. Statistically significant improvements and intergroup effect size were found for the experimental group for P iper F atigue S cale‐ R evised total score ( d = 0.7, P = 0.001), as well as behavioural/severity ( d = 0.6, P = 0.05), affective/meaning ( d = 1.0, P = 0.001) and sensory ( d = 0.3, P = 0.03) domains. Statistically significant differences between the experimental and control groups were also found for general health ( d = 0.5, P < 0.05) and quality of life ( d = 1.3, P < 0.05). All participants attended over 80% of sessions, with no major adverse events reported. The results of this study suggest MMPP incorporating DWR decreases cancer‐related fatigue and improves general health and quality of life in breast cancer survivors. Further, the high level of adherence and lack of adverse events indicate such a programme is safe and feasible.

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This study responds to calls for research on work-family aspects in entrepreneurship research. Our study examined the role of work-family conflict and enhancement on small business owners’ (SBOs) wellbeing. We found work-family has negative direct effect on mental health, job and family satisfactions. Furthermore, we found that under high level of work-family conflict condition, SBOs who perceive a greater level of work-family enhancement would feel more satisfy with their life, job as well as family aspects. Interestingly, under high level of conflict, even SBOs perceive greater level of enhancement, it would not lessen the negative impact of the conflict on their mental health. These results suggest that once psychological health is harmed by work-family conflict, its negative consequences remain unchanged.

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For pedagogical change to be sustained over time, and over the span of higher education courses, it needs to be framed widely, rather than ‘tacked on’. The framing includes curriculum reform and resource provision alongside staff pedagogical development. This is especially true for initiatives (such as reflective writing and assessment) that target broad-based, high-level skills and dispositions. For various reasons, such initiatives can easily become lost because of the discipline-specific focus of a syllabus outweighs the initiative, or because lack of resources compromises a desired approach. Course improvement in higher education contexts is typically difficult and episodic. In such circumstances, we argue that a strategic and trustworthy approach is necessary where practitioner-lead pedagogic development is fostered through trust and communication and is purposefully embedded within key dimensions of curriculum integration and resource provision. This chapter describes an approach to pedagogical change where curriculum, pedagogy and resources are simultaneously and collaboratively orchestrated to provide an effective framework for sustainable and effective change. A robust conceptual model is proposed to guide the implementation of such change.

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Coastal resources are coming under increasing pressure from competition between recreational, commercial and conservation uses. This is particularly so in coastal areas adjacent to major population centres. Given high recreational and conservation values in such areas, economic activities need to be highly efficient in order to persist. Management of these industries must therefore also encourage efficient production and full utilisation of the areas available. In order to achieve this, managers must first understand the level and drivers of productivity, and how these can be influenced. In this study, by way of illustration, the focus was on the Sydney rock oyster industry within Queensland's Moreton Bay, a multiple use marine park with high recreational and conservation value adjacent to Australia's third largest city. Productivity of the oyster industry in Moreton Bay is currently low compared to historic levels, and management has an objective of reversing this trend. It is unclear whether this difference is due to oyster farmers' business choices and personal characteristics or whether varying environmental conditions in the Moreton Bay limit the capacity of the oyster industry. These require different management responses in order to enhance productivity. The study examined different productivity measures of the oyster industry using data envelopment analysis (DEA) to determine where productivity gains can be made and by how much. The findings suggest that the industry is operating at a high level of capacity utilisation, but a low level of efficiency. The results also suggest that both demographic and environmental conditions affect technical efficiency in the Bay, with water characteristics improvements and appropriate training potentially providing the greatest benefits to the industry. Methods used in this study are transferable to other industries and provide a means by which coastal aquaculture may be managed to ensure it remains competitive with other uses of coastal resources.

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Most previous work on artificial curiosity (AC) and intrinsic motivation focuses on basic concepts and theory. Experimental results are generally limited to toy scenarios, such as navigation in a simulated maze, or control of a simple mechanical system with one or two degrees of freedom. To study AC in a more realistic setting, we embody a curious agent in the complex iCub humanoid robot. Our novel reinforcement learning (RL) framework consists of a state-of-the-art, low-level, reactive control layer, which controls the iCub while respecting constraints, and a high-level curious agent, which explores the iCub's state-action space through information gain maximization, learning a world model from experience, controlling the actual iCub hardware in real-time. To the best of our knowledge, this is the first ever embodied, curious agent for real-time motion planning on a humanoid. We demonstrate that it can learn compact Markov models to represent large regions of the iCub's configuration space, and that the iCub explores intelligently, showing interest in its physical constraints as well as in objects it finds in its environment.

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This study focuses on trying to understand why the range of experience with respect to HIV infection is so diverse, especially as regards to the latency period. The challenge is to determine what assumptions can be made about the nature of the experience of antigenic invasion and diversity that can be modelled, tested and argued plausibly. To investigate this, an agent-based approach is used to extract high-level behaviour which cannot be described analytically from the set of interaction rules at the cellular level. A prototype model encompasses local variation in baseline properties contributing to the individual disease experience and is included in a network which mimics the chain of lymphatic nodes. Dealing with massively multi-agent systems requires major computational efforts. However, parallelisation methods are a natural consequence and advantage of the multi-agent approach. These are implemented using the MPI library.

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The three phases of the macroscopic evolution of the HIV infection are well known, but it is still difficult to understand how the cellular-level interactions come together to create this characteristic pattern and, in particular, why there are such differences in individual responses. An 'agent-based' approach is chosen as a means of inferring high-level behaviour from a small set of interaction rules at the cellular level. Here the emphasis is on cell mobility and viral mutations.

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This paper describes current research at the Australian Centre for Field Robotics (ACFR) in collaboration with the Commonwealth Scientific and Industrial Research Organisation (CSIRO) within the Cooperative Research Centre (CRC) for Mining Technology and Equipment (CMTE) towards achieving autonomous navigation of underground vehicles, like a Load-Haul-Dump (LHD) truck. This work is being sponsored by the mining industry through the Australian Mineral Industries Research Association Limited (AMIRA). Robust and reliable autonomous navigation can only be realised by achieving high level tasks such as path-planning and obstacle avoidance. This requires determining the pose (position and orientation) of the vehicle at all times. A minimal infrastructure localisation algorithm that has been developed for this purpose is outlined and the corresponding results are presented. Further research issues that are under investigation are also outlined briefly.

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Just over 44,000 registered charities filed their first Annual Information Statement (AIS) return with the Australian Charities and Not-for-profits Commission (ACNC) before the end of October 2014. Of these, 10,918 charities self-identified as Basic Religious Charities (BRCs). These are usually, but not always, unincorporated religious congregations which receive no or little government funding. Having a central agency for reporting, in the form of the ACNC, having access to information supplied in the AIS by registered organisations has allowed access to new measures of charities and their activities. In September 2014 the ACNC, in conjunction with Curtin University Not-for-profit Initiative, released a high-level report on the first AIS, and the data were also made available digitally through the Australian Government Data Repository. This factsheet builds on that report by focusing on BRCs.

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Background Haemodialysis nurses work in a technological environment caring for patients over a prolonged period of time leading to the development of unique nurse-patient relationships. In order to improve retention of nurses in this specialised area of nursing it is important to know the factors that affect job satisfaction, stress and burnout and understand how these experiences are conceptualised by haemodialysis nurses. Aim To explore the factors contributing to satisfaction with the work environment, job satisfaction, job stress and burnout in haemodialysis nurses in Australia and New Zealand. Method A quantitative dominant sequential explanatory mixed method design was used. Quantitative data was collected using an on-line questionnaire containing demographic questions and pre-existing instruments examining job satisfaction, stress, burnout and satisfaction with the work environment. The qualitative phase involved semi-structured interviews. Results 417 nurses completed the questionnaire. Overall, nurses were satisfied with their work environment and the job that they performed but there were stressors in the haemodialysis setting that led to high levels of burnout. Key themes emerged from the qualitative data related to the physical environment, intensity of nurse-patient relationships, workloads, and coping with death and dying. The qualitative findings also provide possible explanations for the high level of burnout identified in the quantitative findings. Conclusion Explanation of areas where specific nurse and patient outcomes were affected will support the development of appropriate interventions to sustain a work environment conducive to job satisfaction that also alleviates stress and burnout in these nurses.

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Background The benefits associated with some cancer treatments do not come without risk. A serious side effect of some common cancer treatments is cardiotoxicity. Increased recognition of the public health implications of cancer treatment-induced cardiotoxicity has resulted in a proliferation of systematic reviews in this field to guide practice. Quality appraisal of these reviews is likely to limit the influence of biased conclusions from systematic reviews that have used poor methodology related to clinical decision-making. The aim of this meta-review is to appraise and synthesise evidence from only high quality systematic reviews focused on the prevention, detection or management of cancer treatment-induced cardiotoxicity. Methods Using Cochrane methodology, we searched databases, citations and hand-searched bibliographies. Two reviewers independently appraised reviews and extracted findings. A total of 18 high quality systematic reviews were subsequently analysed, 67 % (n = 12) of these comprised meta-analyses. Results One systematic review concluded that there is insufficient evidence regarding the utility of cardiac biomarkers for the detection of cardiotoxicity. The following strategies might reduce the risk of cardiotoxicity: 1) The concomitant administration of dexrazoxane with anthracylines; 2) The avoidance of anthracyclines where possible; 3) The continuous administration of anthracyclines (>6 h) rather than bolus dosing; and 4) The administration of anthracycline derivatives such as epirubicin or liposomal-encapsulated doxorubicin instead of doxorubicin. In terms of management, one review focused on medical interventions for treating anthracycline-induced cardiotoxicity during or after treatment of childhood cancer. Neither intervention (enalapril and phosphocreatine) was associated with statistically significant improvement in ejection fraction or mortality. Conclusion This review highlights the lack of high level evidence to guide clinical decision-making with respect to the detection and management of cancer treatment-associated cardiotoxicity. There is more evidence with respect to the prevention of this adverse effect of cancer treatment. This evidence, however, only applies to anthracycline-based chemotherapy in a predominantly adult population. There is no high-level evidence to guide clinical decision-making regarding the prevention, detection or management of radiation-induced cardiotoxicity.

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Affect is an important feature of multimedia content and conveys valuable information for multimedia indexing and retrieval. Most existing studies for affective content analysis are limited to low-level features or mid-level representations, and are generally criticized for their incapacity to address the gap between low-level features and high-level human affective perception. The facial expressions of subjects in images carry important semantic information that can substantially influence human affective perception, but have been seldom investigated for affective classification of facial images towards practical applications. This paper presents an automatic image emotion detector (IED) for affective classification of practical (or non-laboratory) data using facial expressions, where a lot of “real-world” challenges are present, including pose, illumination, and size variations etc. The proposed method is novel, with its framework designed specifically to overcome these challenges using multi-view versions of face and fiducial point detectors, and a combination of point-based texture and geometry. Performance comparisons of several key parameters of relevant algorithms are conducted to explore the optimum parameters for high accuracy and fast computation speed. A comprehensive set of experiments with existing and new datasets, shows that the method is effective despite pose variations, fast, and appropriate for large-scale data, and as accurate as the method with state-of-the-art performance on laboratory-based data. The proposed method was also applied to affective classification of images from the British Broadcast Corporation (BBC) in a task typical for a practical application providing some valuable insights.

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Cloud computing has significantly impacted a broad range of industries, but these technologies and services have been absorbed throughout the marketplace unevenly. Some industries have moved aggressively towards cloud computing, while others have moved much more slowly. For the most part, the energy sector has approached cloud computing in a measured and cautious way, with progress often in the form of private cloud solutions rather than public ones, or hybridized information technology systems that combine cloud and existing non-cloud architectures. By moving towards cloud computing in a very slow and tentative way, however, the energy industry may prevent itself from reaping the full benefit that a more complete migration to the public cloud has brought about in several other industries. This short communication is accordingly intended to offer a high-level overview of cloud computing, and to put forward the argument that the energy sector should make a more complete migration to the public cloud in order to unlock the major system-wide efficiencies that cloud computing can provide. Also, assets within the energy sector should be designed with as much modularity and flexibility as possible so that they are not locked out of cloud-friendly options in the future.