An Experimental Protocol to Model Recovery of Anaerobic Work Capacity
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Abstract:
Models of fatigue are based on physiological parameters such as Critical Power (CP) and Anaerobic Work Capacity (AWC). CP is a theoretical threshold value that a human can generate for an indefinite amount of time and AWC represents a finite expendable amount of anaerobic energy at intensities above CP. There is an increasing interest in developing mathematical models of energy expenditure and recovery for athletic training and human performance. The objective of this research is to propose and validate a model for recovery of AWC during a post exertion recovery interval of cycling. A cycling ergometer study is proposed which involves a VO2max ramp test to determine gas exchange threshold, a 3-min all-out intensity test to determine CP and AWC, and exertion-recovery interval tests to understand recovery of AWC. The results will be used to build a human in the loop control system to optimize cycling performance.Keywords:
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Planning and evaluating cycling programs at a national or state level requires accurate measures of cycling participation. However, recent reports of cycling participation have produced very different estimates. This paper examines the reported rates of cycling in five recent population surveys of cycling. Three surveys (one national and two from Sydney) asking respondents when they last rode a bicycle generated cycling participation (cycled in the past year) estimates of 29.7%, 34.1% and 28.9%. Two other national surveys which asked participants to recall (unprompted) any physical activity done for exercise, recreation or sport in the previous 12 months, estimated cycling in the past year as 11.1% and 6.5%. While unprompted recall of cycling as a type of physical activity generates lower estimates of cycling participation than specific recall questions, both assessment approaches produced similar patterns of cycling by age and sex with both approaches indicating fewer women and older adults cycling. The different question styles most likely explain the substantial discrepancies between the estimates of cycling participation. Some differences are to be expected due to sampling variability, question differences, and regional variation in cycling.
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Previous research has shown that cycling in a standing position reduces cycling economy compared with seated cycling. It is unknown whether the cycling intensity moderates the reduction in cycling economy while standing.The aim was to determine whether the negative effect of standing on cycling economy would be decreased at a higher intensity.Ten cyclists cycled in 8 different conditions. Each condition was either at an intensity of 50% or 70% of maximal aerobic power at a gradient of 4% or 8% and in the seated or standing cycling position. Cycling economy and muscle activation level of 8 leg muscles were recorded.There was an interaction between cycling intensity and position for cycling economy (P = .03), the overall activation of the leg muscles (P = .02), and the activation of the lower leg muscles (P = .05). The interaction showed decreased cycling economy when standing compared with seated cycling, but the difference was reduced at higher intensity. The overall activation of the leg muscles and the lower leg muscles, respectively, increased and decreased, but the differences between standing and seated cycling were reduced at higher intensity.Cycling economy was lower during standing cycling than seated cycling, but the difference in economy diminishes when cycling intensity increases. Activation of the lower leg muscles did not explain the lower cycling economy while standing. The increased overall activation, therefore, suggests that increased activation of the upper leg muscles explains part of the lower cycling economy while standing.
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In low-cycling countries, cycling is not evenly distributed across genders and age groups. In the UK, men are twice as likely as women to cycle to work and cycling tends to be dominated by younger adults. By contrast, in higher cycling countries and cities, gender differences are low, absent, or in the opposite direction. Such places also lack the UK's steady decline in cycling among those aged over 35 years. Over the past fifteen years some UK local areas have seen increases in cycling. This paper analyses data from the English and Welsh Census 2001 and 2011 to examine whether such increases are associated with greater diversity among cyclists. We find that in areas where cycling has increased, there has been no increase in the representation of females, and a decrease in the representation of older adults. We discuss potential causes and policy implications. Importantly, simply increasing cycling modal share has not proved sufficient to create an inclusive cycling culture. The UK's culturally specific factors limiting female take-up of cycling seem to remain in place, even where cycling has gone up. Creating a mass cycling culture may require deliberately targeting infrastructure and policies towards currently under-represented groups.
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Background: Initiatives to promote utility cycling in countries like Australia and the US, which have low rates of utility cycling, may be more effective if they first target recreational cyclists. This study aimed to describe patterns of utility cycling and examine its correlates, among cyclists in Queensland, Australia. Methods: An online survey was administered to adult members of a state-based cycling community and advocacy group (n = 1813). The survey asked about demographic characteristics and cycling behavior, motivators and constraints. Utility cycling patterns were described, and logistic regression modeling was used to examine associations between utility cycling and other variables. Results: Forty-seven percent of respondents reported utility cycling: most did so to commute (86%). Most journeys (83%) were > 5 km. Being male, younger, employed full-time, or university-educated increased the likelihood of utility cycling ( P < .05). Perceiving cycling to be a cheap or a convenient form of transport was associated with utility cycling ( P < .05). Conclusions: The moderate rate of utility cycling among recreational cyclists highlights a potential to promote utility cycling among this group. To increase utility cycling, strategies should target female and older recreational cyclists and focus on making cycling a cheap and convenient mode of transport.
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Costa VP, Pertence LC, Paton CD, De Matos DG, Martins JAN, De Lima JRP. Physiological Correlates of 10-Km Up-hill Cycling Performance in Competitive Cyclists. JEPonline 2011;14(3):26-33. The purpose of this study was to verify the relationship between several physiological variables and performance during simulated up-hill road cycling time trial on the field in competitive cyclists. Fifteen cyclists (35.1 ± 7.0 yrs; 68.4 ± 7.7 kg; 1.73 ± 0.1 cm; 8.5 ± 1.0 % of body fat; 57.9 ± 8.2 ml·kg -1 ·min -1 ) performed an incremental exercise test and 10-km up-hill cycling time trial using a power meter device fitted on the cyclist bicycle. Highly significant relationships were obtained between average power output during 10-km cycling time trial normalized to body mass and 10-km cycle time (-0.85; -0.80; P<0.01). VO2 max·kg -1 was also significant associated with 10-km cycle time (-0.69, P<0.05). We conc luded that for competitive cyclists the average power output during 10-km cycling time trial and VO2 max both normalized to body mass are strongly associated with performance cycling time during 10km up-hill cycling time trial simulated on the field.
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Бұл зерттеужұмысындaКaно моделітурaлы жәнеоғaн қaтыстытолықмәліметберілгенжәнеуниверситетстуденттерінебaғыттaлғaн қолдaнбaлы (кейстік)зерттеужүргізілген.АхметЯссaуи университетініңстуденттеріүшін Кaно моделіқолдaнылғaн, олaрдың жоғaры білімберусaпaсынa қоятынмaңыздытaлaптaры, яғнисaпaлық қaжеттіліктері,олaрдың мaңыздылығытурaлы жәнесaпaлық қaжеттіліктерінеқaтыстыөз университетінқaлaй бaғaлaйтындығытурaлы сұрaқтaр қойылғaн. Осы зерттеудіңмaқсaты АхметЯсaуи университетіндетуризмменеджментіжәнеқaржы бaкaлaвриaт бaғдaрлaмaлaрыныңсaпaсынa қaтыстыстуденттердіңқaжеттіліктерінaнықтaу, студенттердіңқaнaғaттaну, қaнaғaттaнбaу дәрежелерінбелгілеу,білімберусaпaсын aнықтaу мен жетілдіружолдaрын тaлдaу болыптaбылaды. Осы мaқсaтқaжетуүшін, ең aлдыменКaно сaуaлнaмaсы түзіліп,116 студенткеқолдaнылдыжәнебілімберугежәнеоның сaпaсынa қaтыстыстуденттердіңтaлaптaры мен қaжеттіліктерітоптықжұмыстaрaрқылыaнықтaлды. Екіншіден,бұл aнықтaлғaн тaлaптaр мен қaжеттіліктерКaно бaғaлaу кестесіменжіктелді.Осылaйшa, сaпa тaлaптaры төрт сaнaтқa бөлінді:болуытиіс, бір өлшемді,тaртымдыжәнебейтaрaп.Соңындa,қaнaғaттaну мен қaнaғaттaнбaудың мәндеріесептелдіжәнестуденттердіңқaнaғaттaну мен қaнaғaттaнбaу деңгейлерінжоғaрылaту мен төмендетудеосытaлaптaр мен қaжеттіліктердіңрөліaйқын aнықтaлды.Түйінсөздер:сaпa, сaпaлық қaжеттіліктер,білімберусaпaсы, Кaно моделі.
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