817 resultados para RESPIRATORY MUSCLE TRAINING


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The 2014 federal budget implemented a so-called crackdown on what Minister for Social Services Kevin Andrews calls young people who are content to “sit on the couch at home and pick up a welfare cheque”. The crackdown will change access to income support for people under 30 years of age. From January 1 2015, all young people seeking Newstart Allowance and Youth Allowance for the first time will be required to “demonstrate appropriate job search and participation in employment services support for six months before receiving payments”. Upon qualifying, recipients must then spend 25 hours per week in Work for the Dole in order to receive income support for a six-month period. What happens beyond this six months is unclear. What is clear is that these policy changes, together with the Minister’s accompanying statements, are informed by a deficit view of disadvantaged youth. It is a view that demonstrates how little politicians know or understand about these young peoples’ past circumstances.

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Experts are increasingly being called upon to quantify their knowledge, particularly in situations where data is not yet available or of limited relevance. In many cases this involves asking experts to estimate probabilities. For example experts, in ecology or related fields, might be called upon to estimate probabilities of incidence or abundance of species, and how they relate to environmental factors. Although many ecologists undergo some training in statistics at undergraduate and postgraduate levels, this does not necessarily focus on interpretations of probabilities. More accurate elicitation can be obtained by training experts prior to elicitation, and if necessary tailoring elicitation to address the expert’s strengths and weaknesses. Here we address the first step of diagnosing conceptual understanding of probabilities. We refer to the psychological literature which identifies several common biases or fallacies that arise during elicitation. These form the basis for developing a diagnostic questionnaire, as a tool for supporting accurate elicitation, particularly when several experts or elicitors are involved. We report on a qualitative assessment of results from a pilot of this questionnaire. These results raise several implications for training experts, not only prior to elicitation, but more strategically by targeting them whilst still undergraduate or postgraduate students.

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QUT has enacted a university-wide Peer Program’s Strategy which aims to improve student success and graduate outcomes. A component of this strategy is a training model providing relevant, quality-assured and timely training for all students who take on leadership roles. The training model is designed to meet the needs of the growing scale and variety of peer programs, and to recognise the multiple roles and programs in which students may be involved during their peer leader journey. The model builds peer leader capacity by offering centralised, beginning and ongoing training modules, delivered by in-house providers, covering topics which prepare students to perform their role safely, inclusively, accountably and skilfully. The model also provides efficiencies by differentiating between ‘core competency' and ‘program-specific’ modules, thus avoiding training duplication across multiple programs, and enabling training to be individually and flexibly formatted to suit the specific and unique needs of each program.

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Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant and irrelevant objects in binary classification due to much uncertainty produced in the process of the traditional algorithms. The proposed model CTTC (Centroid Training for Text Classification) aims to build an uncertainty boundary to absorb as many indeterminate objects as possible so as to elevate the certainty of the relevant and irrelevant groups through the centroid clustering and training process. The clustering starts from the two training subsets labelled as relevant or irrelevant respectively to create two principal centroid vectors by which all the training samples are further separated into three groups: POS, NEG and BND, with all the indeterminate objects absorbed into the uncertain decision boundary BND. Two pairs of centroid vectors are proposed to be trained and optimized through the subsequent iterative multi-learning process, all of which are proposed to collaboratively help predict the polarities of the incoming objects thereafter. For the assessment of the proposed model, F1 and Accuracy have been chosen as the key evaluation measures. We stress the F1 measure because it can display the overall performance improvement of the final classifier better than Accuracy. A large number of experiments have been completed using the proposed model on the Reuters Corpus Volume 1 (RCV1) which is important standard dataset in the field. The experiment results show that the proposed model has significantly improved the binary text classification performance in both F1 and Accuracy compared with three other influential baseline models.

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Study/Objective This study examines the current state of disaster response education for Australian paramedics from a national and international perspective and identifies both potential gaps in content and challenges to the sustainability of knowledge acquired through occasional training. Background As demands for domestic and international disaster response increase, experience in the field has begun to challenge traditional assumptions that response to mass casualty events requires little specialist training. The need for a “streamlined process of safe medical team deployment into disaster regions”1 is generally accepted and, in Australia, the emergence of national humanitarian aid training has begun to respond to this gap. However, calls for a national framework for disaster health education2 haven’t received much traction. Methods A critical analysis of the peer reviewed and grey literature on the core components/competencies and training methods required to prepare Australian paramedics to contribute to effective health disaster response has been conducted. Research from the past 10 years has been examined along with federal and state policy with regard to paramedic disaster education. Results The literature shows that education and training for disaster response is variable and that an evidence based study specifically designed to outline sets of core competencies for Australian health care professionals has never been undertaken. While such competencies in disaster response have been developed for the American paradigm it is suggested that disaster response within the Australian context is somewhat different to that of the US, and therefore a gap in the current knowledge base exists. Conclusion Further research is needed to develop core competencies specific to Australian paramedics in order to standardise teaching in the area of health disaster management. Until this occurs the task of evaluating or creating disaster curricula that adequately prepares and maintains paramedics for an effective all hazards disaster response is seen as largely unattainable.

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The effect of 18 months of training on the ovarian hormone concentrations and bone mineral density (BMD) accrual was assessed longitudinally in 14 adolescent rowers and 10 matched controls, aged 14–15 years. Ovarian hormone levels were assessed by urinary estrone glucuronide (E1G) and pregnanediol glucuronide (PdG) excretion rates, classifying the menstrual cycles as ovulatory or anovulatory. Total body (TB), total proximal femur (PF), femoral neck (FN) and lumbar spine (LS) (L2–4) bone mass were measured at baseline and 18 months using dual-energy X-ray densitometry. Results were expressed as bone mineral content (BMC), BMD and bone mineral apparent density (BMAD). Five rowers had anovulatory menstrual cycles compared with zero prevalence for the control subjects. Baseline TB BMD was significantly higher in the ovulatory rowers, with PF BMD, FN BMD and LS BMD similar for all groups. At completion, the LS bone accrual of the ovulatory rowers was significantly greater (BMC 8.1%, BMD 6.2%, BMAD 6.2%) than that of the anovulatory rowers (BMC 1.1%, BMD 3.9%, BMAD 1.6%) and ovulatory controls (BMC 0.5%, BMD 1.1%, BMAD 1.1%). No difference in TB, PF or FN bone accrual was observed among groups. This study demonstrated an osteogenic response to mechanical loading, with the rowers accruing greater bone mass than the controls at the lumbar spine. However, the exercise-induced osteogenic benefits were less when rowing training was associated with low estrogen and progesterone metabolite excretion.

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BACKGROUND High magnitude loads and unusual loading regimes are two important determinants for increasing bone mass. Past research demonstrated that positive Gz-induced loading, providing high loads in an unaccustomed manner, had an osteogenic effect on bone. Another determinant of bone mass is that the bone response to loading is site specific. This study sought to further investigate the site specific bone response to loading, examining the cervical spine response, the site suspected of experiencing the greatest loading, to high performance flight. METHODS Bone mineral density (BMD) and bone mineral content (BMC) was monitored in 9 RAAF trainee fighter pilots completing an 8-mo flight training course on a PC-9 and 10 age-height-weight-matched controls. RESULTS At completion of the course, the pilots had a significant increase in cervical spine BMD and total body BMC. No significant changes were found for the control group. CONCLUSIONS This study demonstrated that the physical environment associated with flight training may have contributed to a significant increase in cervical spine bone mass in the trainee PC-9 pilots. The increase in bone mass was possibly a response to the strain generated by the daily wearing of helmet and mask assembly under the influence of positive sustained accelerative forces.