361 resultados para Motor sports events
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Background: High-resolution magnetic resonance (MR) imaging has been used for MR imaging-based structural stress analysis of atherosclerotic plaques. The biomechanical stress profile of stable plaques has been observed to differ from that of unstable plaques; however, the role that structural stresses play in determining plaque vulnerability remains speculative. Methods: A total of 61 patients with previous history of symptomatic carotid artery disease underwent carotid plaque MR imaging. Plaque components of the index artery such as fibrous tissue, lipid content and plaque haemorrhage (PH) were delineated and used for finite element analysis-based maximum structural stress (M-C Stress) quantification. These patients were followed up for 2 years. The clinical end point was occurrence of an ischaemic cerebrovascular event. The association of the time to the clinical end point with plaque morphology and M-C Stress was analysed. Results: During a median follow-up duration of 514 days, 20% of patients (n=12) experienced an ischaemic event in the territory of the index carotid artery. Cox regression analysis indicated that M-C Stress (hazard ratio (HR): 12.98 (95% confidence interval (CI): 1.32-26.67, pZ0.02), fibrous cap (FC) disruption (HR: 7.39 (95% CI: 1.61e33.82), p Z 0.009) and PH (HR: 5.85 (95% CI: 1.27e26.77), p Z 0.02) are associated with the development of subsequent cerebrovascular events. Plaques associated with future events had higher M-C Stress than those which had remained asymptomatic (median (interquartile range, IQR): 330 kPa (229e494) vs. 254 kPa (166-290), p Z0.04). Conclusions: High biomechanical structural stresses, in addition to FC rupture and PH, are associated with subsequent cerebrovascular events.
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Homelessness is a significant public health problem. It is well-documented that people experiencing homelessness exhibit more serious illnesses and have poorer health than the general population. The provision of services and interventions by health-care professionals, including pharmacists, may make a simple yet important contribution to improved health outcomes in those experiencing homelessness, but evidence of roles and interventions is limited and variable. In Australia, the Queensland University of Technology Health Clinic connects with the homeless community by taking part in community outreach events. This paper provides details of one such event, as well as the roles, interventions and experiences of pharmacists. Participation and inclusion of pharmacists in a multidisciplinary health-care team approach at homeless outreach events should be supported and encouraged.
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With improving survival rates following HSCT in children, QOL and management of short- and long-term effects need to be considered. Exercise may help mitigate fatigue and declines in fitness and strength. The aims of this study were to assess the feasibility of an inpatient exercise intervention for children undergoing HSCT and observe the changes in physical and psychological health. Fourteen patients were recruited, mean age 10 yr. A 6MWT, isometric upper and lower body strength, balance, fatigue, and QOL were assessed prior to Tx and six wk post-Tx. A supervised exercise program was offered five days per week during the inpatient period and feasibility assessed through uptake rate. The study had 100% program completion and 60% uptake rate of exercise sessions. The mean (±s.d.) weekly activity was 117.5 (±79.3) minutes. Younger children performed significantly more minutes of exercise than adolescents. At reassessment, strength and fatigue were stabilized while aerobic fitness and balance decreased. QOL revealed a non-statistical trend towards improvement. No exercise-related adverse events were reported. A supervised inpatient exercise program is safe and feasible, with potential physiological and psychosocial benefits.
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Road traffic emissions are often considered the main source of ultrafine particles (UFP, diameter smaller than 100 nm) in urban environments. However, recent studies worldwide have shown that - in high-insolation urban regions at least - new particle formation events can also contribute to UFP. In order to quantify such events we systematically studied three cities located in predominantly sunny environments: Barcelona (Spain), Madrid (Spain) and Brisbane (Australia). Three long term datasets (1-2 years) of fine and ultrafine particle number size distributions (measured by SMPS, Scanning Mobility Particle Sizer) were analysed. Compared to total particle number concentrations, aerosol size distributions offer far more information on the type, origin and atmospheric evolution of the particles. By applying k-Means clustering analysis, we categorized the collected aerosol size distributions in three main categories: “Traffic” (prevailing 44-63% of the time), “Nucleation” (14-19%) and “Background pollution and Specific cases” (7-22%). Measurements from Rome (Italy) and Los Angeles (California) were also included to complement the study. The daily variation of the average UFP concentrations for a typical nucleation day at each site revealed a similar pattern for all cities, with three distinct particle bursts. A morning and an evening spike reflected traffic rush hours, whereas a third one at midday showed nucleation events. The photochemically nucleated particles burst lasted 1-4 hours, reaching sizes of 30-40 nm. On average, the occurrence of particle size spectra dominated by nucleation events was 16% of the time, showing the importance of this process as a source of UFP in urban environments exposed to high solar radiation. On average, nucleation events lasting for 2 hours or more occurred on 55% of the days, this extending to >4hrs in 28% of the days, demonstrating that atmospheric conditions in urban environments are not favourable to the growth of photochemically nucleated particles. In summary, although traffic remains the main source of UFP in urban areas, in developed countries with high insolation urban nucleation events are also a main source of UFP. If traffic-related particle concentrations are reduced in the future, nucleation events will likely increase in urban areas, due to the reduced urban condensation sinks.
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It is well-known that new particle formation (NPF) in the atmosphere is inhibited by pre-existing particles in the air that act as condensation sinks to decrease the concentration and, thus, the supersaturation of precursor gases. In this study, we investigate the effects of two parameters - atmospheric visibility, expressed as the particle back-scatter coefficient (BSP), and PM10 particulate mass concentration, on the occurrences of NPF events in an urban environment where the majority of precursor gases originate from motor vehicle and industrial sources. This is the first attempt to derive direct relationships between each of these two parameters and the occurrence of NPF. NPF events were identified from data obtained with a neutral cluster and air ion spectrometer over 245 days within a calendar year. Bayesian logistic regression was used to determine the probability of observing NPF as functions of BSP and PM10. We show that the BSP at 08 h on a given day is a reliable indicator of an NPF event later that day. The posterior median probability of observing an NPF event was greater than 0.5 (95%) when the BSP at 08 h was less than 6.8 Mm-1.
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Objective: To examine the association between preoperative quality of life (QoL) and postoperative adverse events in women treated for endometrial cancer. Methods: 760 women with apparent Stage I endometrial cancer were randomised into a clinical trial evaluating laparoscopic versus open surgery. This analysis includes women with preoperative QoL measurements, from the Functional Assessment of Cancer Therapy- General (FACT-G) questionnaire, and who were followed up for at least 6 weeks after surgery (n=684). The outcomes for this study were defined as (1) the occurrence of moderate to severe AEs adverse events within 6 months (Common Toxicology Criteria (CTC) grade ≥3); and (2) any Serious Adverse Event (SAE). The association between preoperative QoL and the occurrence of AE was examined, after controlling for baseline comorbidity and other factors. Results: After adjusting for other factors, odds of occurrence of AE of CTC grade ≥3 were significantly increased with each unit decrease in baseline FACT-G score (OR=1.02, 95% CI 1.00-1.03, p=0.030), which was driven by physical well-being (PWB) (OR=1.09, 95% CI 1.04-1.13, p=0.0002) and functional well-being subscales (FWB) (OR=1.04, 95% CI 1.00-1.07, p=0.035). Similarly, odds of SAE occurrence were significantly increased with each unit decrease in baseline FACT-G score (OR=1.02, 95% CI 1.01-1.04, p=0.011), baseline PWB (OR=1.11, 95% CI 1.06-1.16, p<0.0001) or baseline FWB subscales (OR=1.05, 95% CI 1.01-1.10, p=0.0077). Conclusion: Women with early endometrial cancer presenting with lower QoL prior to surgery are at higher risk of developing a serious adverse event following surgery. Funding: Cancer Council Queensland, Cancer Council New South Wales, Cancer Council Victoria, Cancer Council, Western Australia; NHMRC project grant 456110; Cancer Australia project grant 631523; The Women and Infants Research Foundation, Western Australia; Royal Brisbane and Women’s Hospital Foundation; Wesley Research Institute; Gallipoli Research Foundation; Gynetech; TYCO Healthcare, Australia; Johnson and Johnson Medical, Australia; Hunter New England Centre for Gynaecological Cancer; Genesis Oncology Trust; and Smart Health Research Grant QLD Health.
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Introduction: Extreme heat events (both heat waves and extremely hot days) are increasing in frequency and duration globally and cause more deaths in Australia than any other extreme weather event. Numerous studies have demonstrated a link between extreme heat events and an increased risk of morbidity and death. In this study, the researchers sought to identify if extreme heat events in the Tasmanian population were associated with any changes in emergency department admissions to the Royal Hobart Hospital (RHH) for the period 2003-2010. Methods: Non-identifiable RHH emergency department data and climate data from the Australian Bureau of Meteorology were obtained for the period 2003-2010. Statistical analyses were conducted using the computer statistical computer software ‘R’ with a distributed lag non-linear model (DLNM) package used to fit a quassi-Poisson generalised linear regression model. Results: This study showed that RR of admission to RHH during 2003-2010 was significant over temperatures of 24 C with a lag effect lasting 12 days and main effect noted one day after the extreme heat event. Discussion: This study demonstrated that extreme heat events have a significant impact on public hospital admissions. Two limitations were identified: admissions data rather than presentations data were used and further analysis could be done to compare types of admissions and presentations between heat and non-heat events. Conclusion: With the impacts of climate change already being felt in Australia, public health organisations in Tasmania and the rest of Australia need to implement adaptation strategies to enhance resilience to protect the public from the adverse health effects of heat events and climate change.
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PURPOSE To develop and test decision tree (DT) models to classify physical activity (PA) intensity from accelerometer output and Gross Motor Function Classification System (GMFCS) classification level in ambulatory youth with cerebral palsy (CP); and 2) compare the classification accuracy of the new DT models to that achieved by previously published cut-points for youth with CP. METHODS Youth with CP (GMFCS Levels I - III) (N=51) completed seven activity trials with increasing PA intensity while wearing a portable metabolic system and ActiGraph GT3X accelerometers. DT models were used to identify vertical axis (VA) and vector magnitude (VM) count thresholds corresponding to sedentary (SED) (<1.5 METs), light PA (LPA) (>/=1.5 and <3 METs) and moderate-to-vigorous PA (MVPA) (>/=3 METs). Models were trained and cross-validated using the 'rpart' and 'caret' packages within R. RESULTS For the VA (VA_DT) and VM decision trees (VM_DT), a single threshold differentiated LPA from SED, while the threshold for differentiating MVPA from LPA decreased as the level of impairment increased. The average cross-validation accuracy for the VC_DT was 81.1%, 76.7%, and 82.9% for GMFCS levels I, II, and III, respectively. The corresponding cross-validation accuracy for the VM_DT was 80.5%, 75.6%, and 84.2%, respectively. Within each GMFCS level, the decision tree models achieved better PA intensity recognition than previously published cut-points. The accuracy differential was greatest among GMFCS level III participants, in whom the previously published cut-points misclassified 40% of the MVPA activity trials. CONCLUSION GMFCS-specific cut-points provide more accurate assessments of MVPA levels in youth with CP across the full spectrum of ambulatory ability.
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Relatively few previous studies of individuals receiving a diagnosis of Motor Neurone Disease within the UK health care system have employed qualitative approaches to examine the diagnostic journey from a patient perspective. A qualitative sociological study was undertaken, involving interviews with 42 participants diagnosed with MND, to provide insight into their experiences of undergoing testing and receiving a diagnosis. Adopting a sociological-phenomenological perspective, this article examines key themes that emerged from participant accounts surrounding the lived experience of the diagnostic journey. The key themes that emerged were: The diagnostic quest; living with uncertainty; hearing bad news; communication difficulties; and a reified body of medical interest. In general, doctor-patient communication both at pre and post diagnosis was experienced as highly stressful, distressing and profoundly upsetting. Participants reported such distress as being due to the mode of delivery and communication strategies used by health professionals. We therefore suggest that professional training needs to emphasize the importance to health professionals of fostering greater levels of tact, sensitivity and empathy towards patients diagnosed with devastating, life-limiting illnesses such as MND.
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Video surveillance infrastructure has been widely installed in public places for security purposes. However, live video feeds are typically monitored by human staff, making the detection of important events as they occur difficult. As such, an expert system that can automatically detect events of interest in surveillance footage is highly desirable. Although a number of approaches have been proposed, they have significant limitations: supervised approaches, which can detect a specific event, ideally require a large number of samples with the event spatially and temporally localised; while unsupervised approaches, which do not require this demanding annotation, can only detect whether an event is abnormal and not specific event types. To overcome these problems, we formulate a weakly-supervised approach using Kullback-Leibler (KL) divergence to detect rare events. The proposed approach leverages the sparse nature of the target events to its advantage, and we show that this data imbalance guarantees the existence of a decision boundary to separate samples that contain the target event from those that do not. This trait, combined with the coarse annotation used by weakly supervised learning (that only indicates approximately when an event occurs), greatly reduces the annotation burden while retaining the ability to detect specific events. Furthermore, the proposed classifier requires only a decision threshold, simplifying its use compared to other weakly supervised approaches. We show that the proposed approach outperforms state-of-the-art methods on a popular real-world traffic surveillance dataset, while preserving real time performance.
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The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.
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In competitive combat sporting environments like boxing, the statistics on a boxer's performance, including the amount and type of punches thrown, provide a valuable source of data and feedback which is routinely used for coaching and performance improvement purposes. This paper presents a robust framework for the automatic classification of a boxer's punches. Overhead depth imagery is employed to alleviate challenges associated with occlusions, and robust body-part tracking is developed for the noisy time-of-flight sensors. Punch recognition is addressed through both a multi-class SVM and Random Forest classifiers. A coarse-to-fine hierarchical SVM classifier is presented based on prior knowledge of boxing punches. This framework has been applied to shadow boxing image sequences taken at the Australian Institute of Sport with 8 elite boxers. Results demonstrate the effectiveness of the proposed approach, with the hierarchical SVM classifier yielding a 96% accuracy, signifying its suitability for analysing athletes punches in boxing bouts.
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The Sport Development Project (SDP) was a comprehensive youth strategy for sport in the Northern Territory aimed at diversion from ‘at-risk’ behaviours, improvement of life choices and outcomes, and strengthening youth service infrastructure through engagement in positive (sport) activities. There were five Remote Service Delivery sites that were involved in the trial of this ‘best practice’ model for delivering sport-focused diversion activities. These include: Gapuwiyak, Wadeye, Yuendumu, Gunbalunya and Nguiu.
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The objective of this research project was to consider the social impact of sport and physical activity on the lives of Indigenous Australians and their communities. There has been strong research interest in the links between sport and recreation programs and various health and social outcomes and a well-established body of literature exists on the use of sport to address social issues in mainstream society (A Thomson, Darcy and Pearce 2010). The consensus is that physical activity is an important contributor to health for all people (Nelson, Abbott and Macdonald 2010). While there is strong research interest, what remains unclear is the value and impact of sport and physical activity on Indigenous communities (Cairnduff 2001). Nelson (2009) drawing on the work of Jonas and Langton (1994) indicates that an ‘Aboriginal person is a descendant of an Indigenous inhabitant of Australia, identifi es as an Aboriginal, and is recognised as Aboriginal by members of the community in which he or she lives’ (p. 97). Even this defi nition has the potential to be politically charged. At a general level, the collective terms ‘Indigenous’ (capitalised) and ‘Aboriginal and Torres Strait Islander’ people (title capitalised) appear to be broadly acceptable terms. Indigenous groups cannot be considered to be homogenous as there is much diversity between and within groups (Nelson et al. 2010; Parker et al. 2006). It is therefore important this report is not viewed as taking an essentialist view of who Indigenous people are and how they develop. Rather, this paper attempts to describe and discuss the experiences of some individuals and their communities in site-specifi c surfi ng programs.
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The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a ‘magnitude-based inference’ approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements.