949 resultados para Motor sports events


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Although the "slow" phase of pulmonary oxygen uptake (Vo2) appears to represent energetic processes in contracting muscle, electromyographic evidence tends not to support this. The present study assessed normalized integrated electromyographic (NIEMG) activity in eight muscles that act about the hip, knee and ankle during 8 min of moderate (ventilatory threshold) cycling in six male cyclists. (Vo2) was measured breath by breath during four repeated trials at each of the two intensities. Moderate and very heavy exercise followed a 4-min period of light exercise (50 W). During moderate exercise the slow (Vo2) phase was absent and NIEMG in all muscles did not increase after the first minute of exercise. During very heavy exercise, the slow phase emerged (time delay=58 ± 16 s) and increased progressively (time constant=120 ± 35 s) to an amplitude (0.83 ± 0.16 L/min) that was approximately 21% of the total (Vo2) response. This slow (Vo2) phase coincided with a significant increase in NIEMG in most muscles, and differences in NIEMG activities between the two intensities revealed "slow" muscle activation profiles that differed between muscles in terms of the onset, amplitude and shape of these profiles. This supports the hypothesis that the slow (Vo2) phase is a function of these different slow muscle activation profiles.

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Previous work has shown that amplitude and direction are two independently controlled parameters of aimed arm movements, and performance, therefore, suffers when they must be decomposed into Cartesian coordinates. We now compare decomposition into different coordinate systems. Subjects pointed at visual targets in 2-D with a cursor, using a two-axis joystick or two single-axis joysticks. In the latter case, joystick axes were aligned with the subjects’ body axes, were rotated by –45°, or were oblique (i.e., one axis was in an egocentric frame and the other was rotated by –45°). Cursor direction always corresponded to joystick direction. We found that compared with the two-axis joystick, responses with single-axis joysticks were slower and less accurate when the axes were oriented egocentrically; the deficit was even more pronounced when the axes were rotated and was most pronounced when they were oblique. This confirms that decomposition of motor commands is computationally demanding and documents that this demand is lowest for egocentric, higher for rotated, and highest for oblique coordinates. We conclude that most current vehicles use computationally demanding man–machine interfaces.

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Several brain imaging studies have assumed that response conflict is present in Stroop tasks. However, this has not been demonstrated directly. We examined the time-course of stimulus and response conflict resolution in a numerical Stroop task by combining single-trial electro-myography (EMG) and event-related brain potentials (ERP). EMG enabled the direct tracking of response conflict and the peak latency of the P300 ERP wave was used to index stimulus conflict. In correctly responded trials of the incongruent condition EMG detected robust incorrect response hand activation which appeared consistently in single trials. In 50–80% of the trials correct and incorrect response hand activation coincided temporally, while in 20–50% of the trials incorrect hand activation preceded correct hand activation. EMG data provides robust direct evidence for response conflict. However, congruency effects also appeared in the peak latency of the P300 wave which suggests that stimulus conflict also played a role in the Stroop paradigm. Findings are explained by the continuous flow model of information processing: Partially processed task-irrelevant stimulus information can result in stimulus conflict and can prepare incorrect response activity. A robust congruency effect appeared in the amplitude of incongruent vs. congruent ERPs between 330–400 ms, this effect may be related to the activity of the anterior cingulate cortex.

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There is a notable shortage of empirical research directed at measuring the magnitude and direction of stress effects on performance in a controlled environment. One reason for this is the inherent difficulties in identifying and isolating direct performance measures for individuals. Additionally most traditional work environments contain a multitude of exogenous factors impacting individual performance, but controlling for all such factors is generally unfeasible (omitted variable bias). Moreover, instead of asking individuals about their self-reported stress levels we observe workers' behavior in situations that can be classified as stressful. For this reason we have stepped outside the traditional workplace in an attempt to gain greater controllability of these factors using the sports environment as our experimental space. We empirically investigate the relationship between stress and performance, in an extreme pressure situation (football penalty kicks) in a winner take all sporting environment (FIFA World Cup and UEFA European Cup competitions). Specifically, we examine all the penalty shootouts between 1976 and 2008 covering in total 16 events. The results indicate that extreme stressors can have a positive or negative impact on Individuals' performance. On the other hand, more commonly experienced stressors do not affect professionals' performances.

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BACKGROUND: Western studies have suggested that emotional stress and distress impacted on the morbidity and mortality in people following acute coronary events. Symptoms of anxiety and depression have been associated with re-infarction and death, prolonged recovery and disability and depression may precipitate the client's low self-esteem. This study examined perceived anxiety, depression and self-esteem of Hong Kong Chinese clients diagnosed with acute coronary syndrome (ACS) over a 6-month period following hospital admission. OBJECTIVES: To examine: DESIGN: A prospective, repeated measures design with measures taken on two occasions over a 6-month period; (1) within the 1st week of hospital admission following the onset of ACS and (2) at 6 months follow up. SETTING AND PARTICIPANTS: Convenient sample of 182 voluntary consented clients admitted with ACS to a major public hospital in Hong Kong who could communicate in Chinese, complete questionnaires, cognitive intact, and were haemodynamically stable and free from acute chest pain at the time of interview. METHODS: Baseline data were obtained within 1 week after hospital admission. The follow-up data was collected 6 months after hospital discharge. The Chinese version of the Hospital Anxiety and Depression Scale (HADS), State Self-esteem Scale (SSES), and Rosenberg's Self-Esteem Scale (RSES) were used to assess anxiety and depression, state self-esteem, and trait self-esteem, respectively. RESULTS: Findings suggested gender differences in clients' perception in anxiety, depression and self-esteem. Improvements in clients' perception of these variables were evident over the 6-month period following their acute coronary events. CONCLUSION: The study confirmed the western notion that psychosocial problems are common among coronary clients and this also applies to Hong Kong Chinese diagnosed with ACS. Further studies to explore effective interventions to address these psychosocial issues are recommended.

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Recent claims of equivalence of animal and human reasoning are evaluated and a study of avian cognition serves as an exemplar of weaknesses in these arguments. It is argued that current research into neurobiological cognition lacks theoretical breadth to substantiate comparative analyses of cognitive function. Evaluation of a greater range of theoretical explanations is needed to verify claims of equivalence in animal and human cognition. We conclude by exemplifying how the notion of affordances in multi-scale dynamics can capture behavior attributed to processes of analogical and inferential reasoning in animals and humans.

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Inherent indeterminacy of neurobiological systems has been revealed by research on coordination of multiarticular actions. We consider three important issues that these investigations raise for biomechanical measurement and performance modeling. These issues highlight the role of dynamic systems theory as a platform for integration of motor control and biomechanics in exercise and sports science.

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- Safety psychology and workplace safety - Motivational and attitudinal components of safety - Psychological determinants of safety - Addressing risk-behaviour in safety - Case Study from Construction - Discussion and Questions

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Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites

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Background, aim, and scope Urban motor vehicle fleets are a major source of particulate matter pollution, especially of ultrafine particles (diameters < 0.1 µm), and exposure to particulate matter has known serious health effects. A considerable body of literature is available on vehicle particle emission factors derived using a wide range of different measurement methods for different particle sizes, conducted in different parts of the world. Therefore the choice as to which are the most suitable particle emission factors to use in transport modelling and health impact assessments presented as a very difficult task. The aim of this study was to derive a comprehensive set of tailpipe particle emission factors for different vehicle and road type combinations, covering the full size range of particles emitted, which are suitable for modelling urban fleet emissions. Materials and methods A large body of data available in the international literature on particle emission factors for motor vehicles derived from measurement studies was compiled and subjected to advanced statistical analysis, to determine the most suitable emission factors to use in modelling urban fleet emissions. Results This analysis resulted in the development of five statistical models which explained 86%, 93%, 87%, 65% and 47% of the variation in published emission factors for particle number, particle volume, PM1, PM2.5 and PM10 respectively. A sixth model for total particle mass was proposed but no significant explanatory variables were identified in the analysis. From the outputs of these statistical models, the most suitable particle emission factors were selected. This selection was based on examination of the statistical robustness of the statistical model outputs, including consideration of conservative average particle emission factors with the lowest standard errors, narrowest 95% confidence intervals and largest sample sizes, and the explanatory model variables, which were Vehicle Type (all particle metrics), Instrumentation (particle number and PM2.5), Road Type (PM10) and Size Range Measured and Speed Limit on the Road (particle volume). Discussion A multiplicity of factors need to be considered in determining emission factors that are suitable for modelling motor vehicle emissions, and this study derived a set of average emission factors suitable for quantifying motor vehicle tailpipe particle emissions in developed countries. Conclusions The comprehensive set of tailpipe particle emission factors presented in this study for different vehicle and road type combinations enable the full size range of particles generated by fleets to be quantified, including ultrafine particles (measured in terms of particle number). These emission factors have particular application for regions which may have a lack of funding to undertake measurements, or insufficient measurement data upon which to derive emission factors for their region. Recommendations and perspectives In urban areas motor vehicles continue to be a major source of particulate matter pollution and of ultrafine particles. It is critical that in order to manage this major pollution source methods are available to quantify the full size range of particles emitted for traffic modelling and health impact assessments.

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Measurements in the exhaust plume of a petrol-driven motor car showed that molecular cluster ions of both signs were present in approximately equal amounts. The emission rate increased sharply with engine speed while the charge symmetry remained unchanged. Measurements at the kerbside of nine motorways and five city roads showed that the mean total cluster ion concentration near city roads (603 cm-3) was about one-half of that near motorways (1211 cm-3) and about twice as high as that in the urban background (269 cm-3). Both positive and negative ion concentrations near a motorway showed a significant linear increase with traffic density (R2=0.3 at p<0.05) and correlated well with each other in real time (R2=0.87 at p<0.01). Heavy duty diesel vehicles comprised the main source of ions near busy roads. Measurements were conducted as a function of downwind distance from two motorways carrying around 120-150 vehicles per minute. Total traffic-related cluster ion concentrations decreased rapidly with distance, falling by one-half from the closest approach of 2m to 5m of the kerb. Measured concentrations decreased to background at about 15m from the kerb when the wind speed was 1.3 m s-1, this distance being greater at higher wind speed. The number and net charge concentrations of aerosol particles were also measured. Unlike particles that were carried downwind to distances of a few hundred metres, cluster ions emitted by motor vehicles were not present at more than a few tens of metres from the road.