… This year, he’s the youngest member of the Red Bulls’ main roster. Though Adams described the team as having a “family atmosphere,” he said he had to prove his worth.
“You have to earn the respect of everybody by showing your character and how you handle yourself on the field, by showing how good you are,” he said. “I think I have proved to them and earned their respect, but at the same time every day, I’m still pushing for a spot against guys who are trying to put food on the table for their families. So, it’s never easy.”
And, before attending afternoon practice each day, Adams attends four class periods at Ketcham, beginning with the school’s “zero period” at 6:40 a.m., in which teachers are available to students as they make up classwork.
… When asked about managing Bell’s workload, offensive coordinator Todd Haley said the Steelers will have “all those discussions.”
“He’s a guy, his injuries have been oddball type of things, even the hamstring,” Haley said. “He’s a guy who gets stronger every game. He does not want to come out of the game. He’s a year older. We’ve got to make sure we cover all of that, which we will and do as a staff.”
… Mariota is nearly fully recovered from the broken leg he sustained during Week 16 of the 2016 season. The quarterback was able to participate in more workouts and practices that the Titans anticipated, giving him a chance to get reps in 7-on-7 drills and a few full-team sessions.
Mariota said the next obstacle for him to overcome is the mental aspect of his injury. The leg is nearly fully healed and he’s able to run full speed. He said he must convince his mind that the leg is sound.
WE WERE promised a surprise, and we sure got one. After the seven former major champions in this year’s French Open women’s field lost in the fourth round or earlier, guaranteeing a first-time winner, the player who emerged victorious on June 10th was the least likely of the final eight. Big-hitting Jelena Ostapenko, an unseeded Latvian who had turned 20 two days earlier, won the title after she bounced back from a one-set deficit to overcome the heavy favourite, the third-seeded Romanian Simona Halep. Ms Ostapenko became the youngest woman to win a major since Maria Sharapova, who secured her second grand-slam title, the 2006 US Open, at age 19. She is now the third-youngest female major victor since 2000, trailing only Ms Sharapova and Svetlana Kuznetsova, who won the 2004 US Open as a 19-year-old.
Ms Ostapenko′s fortnight in Paris represents a huge breakthrough. The list of players who won grand-slam tournaments as teenagers (as she was during her first five matches) is packed with all-time greats, including Serena Williams, Martina Hingis, Monica Seles and Ms Sharapova. However, Ms Ostapenko’s record so far—she was ranked 47th in the world entering the tournament, and still sits outside the top ten—doesn’t compare with what those legends had accomplished by their 20th birthdays. After all, Roland Garros was not just her first major title, but also her first in any tour-level event. So should we evaluate the Latvian as we would any other promising-but-not-elite 20-year-old? Or is winning a grand slam at that age so unusual that we need to re-evaluate her potential?
arXiv, Statistics > Applications; David L. Carey, Kok-Leong Ong, Rod Whiteley, Kay M. Crossley, Justin Crow, Meg E. Morris from
To investigate whether training load monitoring data could be used to predict injuries in elite Australian football players, data were collected from elite athletes over 3 seasons at an Australian football club. Loads were quantified using GPS devices, accelerometers and player perceived exertion ratings. Absolute and relative training load metrics were calculated for each player each day (rolling average, exponentially weighted moving average, acute:chronic workload ratio, monotony and strain). Injury prediction models (regularised logistic regression, generalised estimating equations, random forests and support vector machines) were built for non-contact, non-contact time-loss and hamstring specific injuries using the first two seasons of data. Injury predictions were generated for the third season and evaluated using the area under the receiver operator characteristic (AUC). Predictive performance was only marginally better than chance for models of non-contact and non-contact time-loss injuries (AUC<0.65). The best performing model was a multivariate logistic regression for hamstring injuries (best AUC=0.76). Learning curves suggested logistic regression was underfitting the load-injury relationship and that using a more complex model or increasing the amount of model building data may lead to future improvements. Injury prediction models built using training load data from a single club showed poor ability to predict injuries when tested on previously unseen data, suggesting they are limited as a daily decision tool for practitioners. Focusing the modelling approach on specific injury types and increasing the amount of training data may lead to the development of improved predictive models for injury prevention.
The interview with Russell takes place in the iconic Brasenose College (where the professor is a fellow). Professor Russell Foster is Head of the Nuffield Laboratory of Ophthalmology and Director of the Sleep and Circadian Neuroscience Institute at the University. The interview discusses sleep: what is it? Why do we get disrupted sleep? Do animals? And what can we do to give us the best chance of some decent slumber?
Could you sum up the broader context of research into sleep, and where your research figures in that?
‘Fundamentally, what I’m excited about and trying to understand is how the core mechanisms of sleep and 24-hour circadian rhythms are generated and regulated within the central nervous system, and then use this fundamental knowledge for translational studies – to inform therapeutic approaches that will improve the quality of life for individuals and their family across a broad spectrum of health conditions where sleep is severely disrupted, from eye disease to mental illness.
New York Magazine, Science of Us blog, Melissa Dahl from
Do you want to be working right now? Me neither. Who can concentrate on spreadsheets — I don’t know what it is you do but I imagine it involves spreadsheets — when the country seems to be collapsing around us? And yet you still have things to do, even if it seems sometimes like a patriotic duty to stare in mute horror at the news all day.
Everyone likely has their own ways of bossing themselves around, but here are three things that reliably work for me.
It has been toned down from the draft but Annamarie Phelps’s review of British Cycling shows how UK Sport either missed, or wilfully ignored, numerous attempts to tackle problems
Individuals of the same age may not age at the same rate. Quantitative biomarkers of aging are valuable tools to measure physiological age, assess the extent of ‘healthy aging’, and potentially predict health span and life span for an individual. Given the complex nature of the aging process, the biomarkers of aging are multilayered and multifaceted. Here, we review the phenotypic and molecular biomarkers of aging. Identifying and using biomarkers of aging to improve human health, prevent age-associated diseases, and extend healthy life span are now facilitated by the fast-growing capacity of multilevel cross-sectional and longitudinal data acquisition, storage, and analysis, particularly for data related to general human populations. Combined with artificial intelligence and machine learning techniques, reliable panels of biomarkers of aging will have tremendous potential to improve human health in aging societies.
arXiv, Statistics > Machine Learning; Paul Christiano, Jan Leike, Tom B. Brown, Miljan Martic, Shane Legg, Dario Amodei from
For sophisticated reinforcement learning (RL) systems to interact usefully with real-world environments, we need to communicate complex goals to these systems. In this work, we explore goals defined in terms of (non-expert) human preferences between pairs of trajectory segments. We show that this approach can effectively solve complex RL tasks without access to the reward function, including Atari games and simulated robot locomotion, while providing feedback on less than one percent of our agent’s interactions with the environment. This reduces the cost of human oversight far enough that it can be practically applied to state-of-the-art RL systems. To demonstrate the flexibility of our approach, we show that we can successfully train complex novel behaviors with about an hour of human time. These behaviors and environments are considerably more complex than any that have been previously learned from human feedback.
The NFL will fund a $2.6 million international study on the role of active rehabilitation strategies in concussion management, led by the University of North Carolina at Chapel Hill and the Medical College of Wisconsin.
The project was identified as a priority at the NFL’s International Professional Sports Concussion Research Think Tank, where medical representatives of many of the world’s leading sports leagues convened to share best medical practices and protocols and collaborate on ways to advance science through research.
The study, one of the first of its kind, will examine the efficacy of two clinically supervised management strategies, including both the international concussion return-to-play protocol and early therapeutic interventions on concussions.
It’s no secret that caffeine is very valuable to a runner. There’s dozens of studies out there that will tell you all about its performance enhancement. You may even be drinking some coffee right now as you read it and wait for your next run.
There’s a couple factors that go into coffee intake before a run. Timing is important because you want to get the effect of the caffeine but you also don’t want to stop in the middle of your run and then start looking for a place to go.
We investigated whether caffeine ingestion before submaximal exercise bouts would affect supramaximal oxygen demand and maximal accumulated oxygen deficit (MAOD), and if caffeine-induced improvement on the anaerobic capacity (AC) could be detected by different methods. Nine men took part in several submaximal and supramaximal exercise bouts one hour after ingesting caffeine (5 mg·kg-1) or placebo. The AC was estimated by MAOD, alternative MAOD, critical power, and gross efficiency methods. Caffeine had no effect on exercise endurance during the supramaximal bout (caffeine: 131.3 ± 21.9 and placebo: 130.8 ± 20.8 s, P = 0.80). Caffeine ingestion before submaximal trials did not affect supramaximal oxygen demand and MAOD compared to placebo (7.88 ± 1.56 L and 65.80 ± 16.06 kJ vs. 7.89 ± 1.30 L and 62.85 ± 13.67 kJ, P = 0.99). Additionally, MAOD was similar between caffeine and placebo when supramaximal oxygen demand was estimated without caffeine effects during submaximal bouts (67.02 ± 16.36 and 62.85 ± 13.67 kJ, P = 0.41) or when estimated by alternative MAOD (56.61 ± 8.49 and 56.87 ± 9.76 kJ, P = 0.91). The AC estimated by gross efficiency was also similar between caffeine and placebo (21.80 ± 3.09 and 20.94 ± 2.67 kJ, P = 0.15), but was lower in caffeine when estimated by critical power method (16.2 ± 2.6 vs. 19.3 ± 3.5 kJ, P = 0.03). In conclusion, caffeine ingestion before submaximal bouts did not affect supramaximal oxygen demand and consequently MAOD. Otherwise, caffeine seems to have no clear positive effect on AC.
For this oral history, we spoke with more than a dozen people who were directly, and indirectly, involved in the Oakland A’s 2002 draft, which changed baseball forever.
“The Moneyball draft, for better or worse, is kind of a line of demarcation between the way things had been done and the way things are done now. We were kind of unwilling participants in a science experiment of sorts, I guess, to see if it would work or not.”
— Stephen Obenchain, one of the Oakland Athletics’ seven first-round picks in 2002
SIRC Sport Information Resource Center, Lily Dong from
How do experts differ from novices? In sport, success in both low-strategy sports and high-strategy sports relies on having a solid knowledge base: knowledge may be what determines who is a true expert when athletes have similar skills and experience. As coaches and parents, the importance of knowledge bases give us a clue of how to enhance children’s athletic performances in ways other than improving physical skills.
What are the different types of knowledge?
One way to categorize our knowledge base is to break it down into three types of knowledge. We develop declarative knowledge first, then procedural, and finally, strategic.