223 research outputs found
All Finite Generalized Tetrahedron Groups
A generalized tetrahedron groups is defined to be a group admitting a
presentation
where l,m,n,p,q,r >= 2, each W_i(a,b) is a cyclically reduced word involving both a and b. These groups appear in many contexts, not least as fundamental groups of certain hyperbolic orbifolds or as subgroups of generalized triangle groups. In this paper, we build on previous work to give a complete classification of all finite generalized tetrahedron groups
The efficiency of the portuguese agricultural credit co-operatives governance model
In recent years the importance of corporate governance (CG) has rising new attention, as the 2008 financial crisis illustrates. Co-operative members, staff, regulators and others stakeholders involved in the co-operative banking business became aware of the need to strengthen co-operatives governance, since this is crucial to safeguarding sound management and, ultimately, to the survival and sustainability of these organizations. With their origins rooted in the 16th century, the Portuguese Agricultural Credit Co-operatives (CCAM) have been considered central players in the economic and social development of rural regions. The goal of this paper is to determine the impact of the different governance mechanisms of co-operative banks on control management, by analysing CCAM governance and assess its efficiency in disciplining management. Hence, using data from 1995-2009 period, and multinomial logit models, the relation between CCAM performance and several control mechanisms operating within the SICAM is analysed. The results show that overall internal governance mechanisms are not related to the CCAM performance, which indicates potential weakness of the CCAM internal control mechanisms. On the other hand, external governance mechanisms are related to CCAM operational and cost efficiency indicators, demonstrating the importance of these mechanisms in disciplining CCAM management. Moreover, the results highlight the value of the supervision task of Central CCAM in the performance of the associates
Relationship between running performance and weather in elite marathoners competing in the New York City Marathon
It is well known that weather and pacing have an influence on elite marathon performance. However, there is limited knowledge about the effect of weather on running speed in elite marathoners. The aim of the present cross-sectional study was to investigate potential associations between running speed and weather variables in elite runners competing in the ‘New York City Marathon’ between 1999 and 2019. Data from all official female and male finishers with name, sex, age, calendar year, split times at 5 km, 10 km, 15 km, 20 km, 25 km, 30 km, 35 km, 40 km and finish and hourly values for temperature (°Celsius), barometric pressure (hPa), humidity (%) and sunshine duration (min) between 09:00 a.m. and 04:00 p.m. were obtained from official websites. A total of 560,731 marathon runners' records were available for analysis (342,799 men and 217,932 women). Pearson and Spearman correlation analyses were performed between the average running speed and the weather variables (temperature, pressure, humidity and sunshine). Ordinary Least Squares (OLS) regressions were also performed. The runner´s records were classified into four performance groups (all runners, top 100, top 10 and top 3) for comparison. Differences in running speed between the four performance groups were statistically significant (p < 0.05) for both men and women. Pearson (linear) correlation indicated a weak and positive association with humidity in the top 10 (r = 0.16) and top 3 (r = 0.13) performance groups that the running speed of the elite runners was positively correlated with humidity. Regarding sunshine duration, there was a weak and positive correlation with the running speed of the elite groups (r = 0.16 in the top 10 and r = 0.2 in the top 3). Spearman correlation (non-linear) identified a weak but negative correlation coefficient with temperature in all runners’ groups. Also, non-linear positive correlation coefficients with humidity and sunshine can be observed in the Spearman matrixes. A Multivariate Ordinary Least Squares (OLS) regression analysis showed no predictive power of weather factors. For elite runners competing in the ‘New York City Marathon’ between 1999 and 2019, the main findings were that elite runners became faster with increasing humidity and sunshine duration while overall runners became slower with increasing temperature, increasing humidity and sunshine duration. Weather factors affected running speed and results but did not provide a significant predictive influence on performance
Editorial: Prevention, assessment and treatment of clinical issues related to endurance exercise and sports
A macro to micro analysis to understand performance in 100-mile ultra-marathons worldwide
The purposes of this study were (i) to describe differences in participation in 100-mile ultra-marathons by continent; (ii) to investigate differences in performance between continents; and (iii) to identify the fastest runners by continent and country. Data from 148,169 athletes (119,408 men), aged 18–81 years, and finishers in a 100-miles ultra-marathon during 1870–2020 were investigated. Information about age, gender, origin, performance level (top three, top 10, top 100) was obtained. Kruskal–Wallis tests and linear regressions were performed. Athletes were mostly from America and Europe. A macro-analysis showed that the fastest men runners were from Africa, while the fastest women runners were from Europe and Africa. Women from Sweden, Hungary and Russia presented the best performances in the top three, top 10 and top 100. Men from Brazil, Russia and Lithuania were the fastest. The lowest performance and participation were observed for runners from Asia. In summary, in 100-miles ultra-marathon running, the majority of athletes were from America, but for both sexes and performance levels, the fastest runners were from Africa. On a country level, the fastest women were from Sweden, Hungary and Russia, while the fastest men were from Brazil, Russia and Lithuania
The Influence of Environmental Conditions on Pacing in Age Group Marathoners Competing in the "New York City Marathon"
Background: The two aspects of the influence of environmental conditions on marathon running performance and pacing during a marathon have been separately and widely investigated. The influence of environmental conditions on the pacing of age group marathoners has, however, not been considered yet.Objective: The aim of the present study was to investigate the association between environmental conditions (i.e., temperature, barometric pressure, humidity, precipitation, sunshine, and cloud cover), gender and pacing of age group marathoners in the “New York City Marathon”.Methodology: Between 1999 and 2019, a total of 830,255 finishes (526,500 males and 303,755 females) were recorded. Time-adjusted averages of weather conditions for temperature, barometric pressure, humidity, and sunshine duration during the race were correlated with running speed in 5 km-intervals for age group runners in 10 years-intervals.Results: The running speed decreased with increasing temperatures in athletes of age groups 20–59 with a pronounced negative effect for men aged 30–64 years and women aged 40–64 years. Higher levels of humidity were associated with faster running speeds for both sexes. Sunshine duration and barometric pressure showed no association with running speed.Conclusion: In summary, temperature and humidity affect pacing in age group marathoners differently. Specifically, increasing temperature slowed down runners of both sexes aged between 20 and 59 years, whereas increasing humidity slowed down runners of <20 and >80 years old
Potential Long-Term Health Problems Associated with Ultra-Endurance Running: A Narrative Review
It is well established that physical activity reduces all-cause mortality and can prolong life. Ultra-endurance running (UER) is an extreme sport that is becoming increasingly popular, and comprises running races above marathon distance, exceeding 6 h, and/or running fixed distances on multiple days. Serious acute adverse events are rare, but there is mounting evidence that UER may lead to long-term health problems. The purpose of this review is to present the current state of knowledge regarding the potential long-term health problems derived from UER, specifically potential maladaptation in key organ systems, including cardiovascular, respiratory, musculoskeletal, renal, immunological, gastrointestinal, neurological, and integumentary systems. Special consideration is given to youth, masters, and female athletes, all of whom may be more susceptible to certain long-term health issues. We present directions for future research into the pathophysiological mechanisms that underpin athlete susceptibility to long-term issues. Although all body systems can be affected by UER, one of the clearest effects of endurance exercise is on the cardiovascular system, including right ventricular dysfunction and potential increased risk of arrhythmias and hypertension. There is also evidence that rare cases of acute renal injury in UER could lead to progressive renal scarring and chronic kidney disease. There are limited data specific to female athletes, who may be at greater risk of certain UER-related health issues due to interactions between energy availability and sex-hormone concentrations. Indeed, failure to consider sex differences in the design of female-specific UER training programs may have a negative impact on athlete longevity. It is hoped that this review will inform risk stratification and stimulate further research about UER and the implications for long-term health
Trends in Participation, Sex Differences and Age of Peak Performance in Time-Limited Ultramarathon Events: A Secular Analysis
Background and Objectives: Increases in the number of participants in time-limited ultra-marathons have been reported. However, no information is available regarding the trends in participation, performance and age in 12 h and 24 h time-limited events. The aim of the study was to describe the trends in runners’ participation, performance and age in 12 h and 24 h ultra-marathons for both sexes and to identify the age of peak performance, taking into account the ranking position and age categories. Materials and Methods: The sample comprised 210,455 runners in time-limited ultra-marathons (female 12 h = 23,706; female 24 h = 28,585; male 12 h = 61,594; male 24 h = 96,570) competing between 1876 and 2020 and aged 18 to 86 years. The age of peak performance was tested according to their ranking position (first–third; fourth–tenth and >tenth position) and taking into account their running speed in different age categories (60 years), using the Kruskal–Wallis test, followed by the Bonferroni adjustment. Results: An increase in the number of participants and a decrease in running speed were observed across the years. For both events, the sex differences in performance decreased over time. The sex differences showed that male runners performed better than female runners, but the lowest differences in recent years were observed in the 24 h ultra-marathons. A positive trend in age across the years was found with an increase in mean age (“before 1989” = 40.33 ± 10.07 years; “1990–1999” = 44.16 ± 10.37 years; “2000–2009” = 45.99 ± 10.33 years; “2010–2020” = 45.62 ± 10.80 years). Male runners in 24 h races were the oldest (46.13 ± 10.83 years), while female runners in 12 h races were the youngest (43.46 ± 10.16 years). Athletes ranked first–third position were the youngest (female 12 h = 41.19 ± 8.87 years; female 24 h = 42.19 ± 8.50 years; male 12 h = 42.03 ± 9.40 years; male 24 h = 43.55 ± 9.03 years). When age categories were considered, the best performance was found for athletes aged between 41 and 50 years (female 12 h 6.48 ± 1.74 km/h; female 24 h 5.64 ± 1.68 km/h; male 12 h 7.19 ± 1.90 km/h; male 24 h 6.03 ± 1.78 km/h). Conclusion: A positive trend in participation in 12 h and 24 h ultra-marathons was shown across the years; however, athletes were becoming slower and older. The fastest athletes were the youngest ones, but when age intervals were considered, the age of peak performance was between 41 and 50 years
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