Participation and performance trends: Polish Nordic marathoners

For the last two decades, the physical activity of the Poles has increased dynamically. Nevertheless, there has been a decline in the number of Polish athletes running marathons compared with an increase in participation in a variety of competitions not directly associated with running. The purpose of this study was to investigate participation and performance trends in Nordic walking marathons in Poland between 2014 and 2019. A total of 490 Polish Nordic walking marathoners, who completed races between 2014 and 2019 were included. Participation and performance were analysed with an emphasis on the demographics of the age and gender of the athletes. The results suggest that overall male participation in Nordic walking marathons was high, yet the number of female finishers increased over the period of the study. Though men also had significantly better finishing times over the same period. In terms of age, middle-aged competitors were the biggest and the fastest age-group between 2014 and 2019.The strength of this study lies in its novelty. It is the first research project to directly examine the participation and performance of Nordic walking marathoners between 2014 and 2019 in terms of gender and age.

Origin of the Fastest 5 km, 10 km and 25 km Open-Water Swimmers—An Analysis from 20 Years and 9819 Swimmers

In elite pool swimmers competing at world class level, mainly athletes from the United States of America and Australia are dominating. Little is known, however, for the nationality of dominating swimmers in elite open-water long-distance swimming races such as the official FINA races over 5 km, 10 km and 25 km—held since 2000. The aim of this study was to investigate the participation and performance trends by nationality of these elite open-water swimmers. Race results from all female and male swimmers competing in 5 km, 10 km and 25 km FINA races between 2000 and 2020 were analyzed. A total of 9819 swimmers competed between 2000 and 2020 in these races. The five countries that figure most times among the top ten in 5 km, 10 km and 25 km races over the years were Italy, Germany, Russia, Brazil and the Netherlands. In 10 km races, considering the all the athletes from each country, male athletes from Germany, Italy, and France presented faster race times than the other countries. In 10 km, female athletes presented no significant difference among the countries. In 5 and 25 km races, there were no differences between countries, for male and female athletes. Moreover, comparing only the 10 best results (top 10) from each country, there were no differences between countries in 5 km, 10 km and 25 km, for male and female athletes. Men were faster than women for all three distances. In summary, male swimmers from Europe (i.e., Germany, Italy, France) are dominating the 10 km FINA races. In the 5 km and 25 km FINA races, there is no dominating nationality, but among the top five countries in the top 10 over the years, three are European countries.

The Case of the Cumulative Redundancy Bias: Understanding the Metacognitive Flexibility in Performance Judgments

The cumulative redundancy bias (CRB) refers to people’s difficulty to ignore the redundancy in cumulatively presented information. For instance, when people consider which of two teams is better, they should focus on the total number of points that each team has at the time. Yet, people are also influenced by the sequence of events that led to that accumulated score, such that if one team was ahead most of the season, people consider it better – even if those teams are currently tied. However, an opposite bias emerges when participants focus on performance trends (performance trend bias; PTB): When the trailing team is catching up to the leading team, people judge it as the better team – even if the other team is still ahead. In three experiments where we manipulated slope magnitude, we obtained both effects: the PTB was observed when the slope was big; the CRB emerged when the slope was small. These studies demonstrate a striking malleability of the cognitive system, flexibly weighing different cues. Results are discussed in terms of metacognitive regulation.

JUMRv1: A Sentiment Analysis Dataset for Movie Recommendation

Nowadays, we can observe the applications of machine learning in every field, ranging from the quality testing of materials to the building of powerful computer vision tools. One such recent application is the recommendation system, which is a method that suggests products to users based on their preferences. In this paper, our focus is on a specific recommendation system called movie recommendation. Here, we make use of user reviews of movies in order to establish a general outlook about the movie and then use that outlook to recommend that movie to other users. However, a huge number of available reviews has baffled sophisticated review systems. Consequently, there is a need to find a method of extracting meaningful information from the available reviews and use that in classifying a movie review and predicting the sentiment in each one. In a typical scenario, a review can either be positive, negative, or indifferent about a movie. However, the available research articles in the field mainly consider this as a two-class classification problem—positive and negative. The most popular work in this field was performed on Stanford and Rotten Tomatoes datasets, which are somewhat outdated. Our work is based on self-scraped reviews from the IMDB website, and we have annotated the reviews into one of the three classes—positive, negative, and neutral. Our dataset is called JUMRv1—Jadavpur University Movie Recommendation dataset version 1. For the evaluation of JUMRv1, we took an exhaustive approach by testing various combinations of word embeddings, feature selection methods, and classifiers. We also analysed the performance trends, if there were any, and attempted to explain them. Our work sets a benchmark for movie recommendation systems that is based on the newly developed dataset using a three-class sentiment classification.

Acceleration of Longitudinal Track and Field Performance Declines in Athletes Who Still Compete at the Age of 100 Years

While physical performance decline rates accelerate after around the age of 70 years, longitudinal athletic performance trends in athletes older than 95 years are unknown. We hypothesized a further accelerated decline in human performance in athletes who still perform at the age of 100 years. To investigate this, longitudinal data of all athletes with results at or over the age of 100 years were collected from the “World Master Rankings” data base spanning 2006–2019 (138 results from 42 athletes; 5 women, 37 men; maximum 105 years) and compared to previously published longitudinal data from 80- to 96-year-old athletes from Sweden (1,134 results from 374 athletes). Regression statistics were used to compare performance decline rates between disciplines and age groups. On average, the individual decline rate of the centenarian group was 2.53 times as steep (100 m: 8.22x; long jump: 0.82x; shot put: 1.61x; discus throw: 1.04x; javelin throw: 0.98x) as that seen in non-centenarians. The steepest increase in decline was found in the 100-m sprint (t-test: p < 0.05, no sign. difference in the other disciplines). The pooled regression statistics of the centenarians are: 100 m: R = 0.57, p = 0.004; long jump: R = 0.90, p < 0.001; shot put: R = 0.65, p < 0.001; discus throw: R = 0.73, p < 0.001; javelin throw: R = 0.68, p < 0.001. This first longitudinal dataset of performance decline rates of athletes who still compete at 100 years and older in five athletics disciplines shows that there is no performance plateau after the age of 90, but rather a further acceleration of the performance decline.

Comparing Alternative Jet Fuel Dependencies Between Combustors of Different Size and Mixing Approaches

Analyses used to reveal fuel dependencies on lean blow out and ignition at specific operating conditions in specific combustors show inconsistent trends with each other. Such variety is however consistent with the occurrence of transitions between the governing physical phenomena as the ratios between evaporation, mixing, or chemical time scales with their respective residence times also vary with specific operating conditions and combustor geometry. It is demonstrated here that the fuel dependencies on LBO in a large, single-cup, swirl-stabilized, rich-quench-lean combustor varies with operating conditions such that a feature importance match is attained to fuel dependencies observed in a much smaller combustor at one end of the tested range, while a qualitative match to fuel dependencies observed in a lean, premixed, swirler-stabilized combustor of comparable size at the other end of the tested range. The same reference combustor, when tested at cold conditions, is shown to exhibit similar fuel dependencies on ignition performance as the much smaller combustor, when tested at both cold and warm conditions. The practical significance of these findings is that a reference rig, such as the Referee Rig, can capture fuel performance trends of proprietary industry combustors by tailoring the inlet air and fuel temperatures of the tests. It is, therefore, a trustworthy surrogate for screening and evaluating sustainable aviation fuel candidates, reducing the dependency on proprietary industrial combustors for this purpose, thereby increasing transparency within the evaluation process while also expediting the process and reducing cost and fuel volume.

Italians Are the Fastest 3000 m Open-Water Master Swimmers in the World

Background: It is well known that athletes originating from a specific region or country can master specific sports disciplines (e.g., East-African runners in long-distance running). In addition, physical and athletic performance are the result of an interaction between genetic, environmental and epigenetic factors. However, little is known about on what determines sports success and performance for long-distance master swimmers such as origin. The aim of the study was to investigate the participation and performance trends of elite master open-water swimmers competing in the World Championships (WC) in 3000 m open-water swimming between 1986 and 2019. Methods: A total of 9247 valid participants were analyzed using generalized linear models (GLMs) with a gamma probability distribution and log link function. Resultsː Most of the starters were from Italy (1646 participations), followed by the United States of America (USA) (1128 participations) and Germany (959 participations). Swimmers from Italy were significantly faster than swimmers from Canada, Germany, USA, Great Britain and also from all other countries grouped (p < 0.005). The age group from 35–39 years old was significantly faster than athletes from age groups of 25–29 years old, 30–34 years old, 40–44 years old, 45–49 years old and 50–54 years old (p < 0.005). The percentage of local athletes in WC was 36% and varied from 36% (Italy, 2004) to 43 % (Germany), 53% (Italy, 2012) and up to 68 % (USA, 1992). Conclusions: Swimmers from Italy were the faster and the most numerous starters during this period of 27 years and 15 editions all over the world in 3000 m master open-water swimming.