At some time in the next 47 days, Alabama QB Tua Tagovailoa will make an official decision on whether to enter the 2020 NFL draft. That’s the deadline for underclassmen to declare, although the junior quarterback has several intriguing options on the table for his next move.
It was clear what Tagovailoa’s recent media junket, speaking to local and national writers on Tuesday, was intended to do: lure a promise.
The general message Tagovailoa gave to multiple outlets was that he doesn’t yet know, amid questions about his health, what his immediate NFL plans are. And that might indeed be true. But Tagovailoa seemed to tip his hand. He certainly knows what he’d like to see happen.
… In this, the latest in the series showcasing how the university’s coaches recruit talent, we examine how Brown has built the Titans into a destination for players who fit his niche and eye. In his 12 years with the Titans, Brown has won five regular-season conference titles and six conference tournament titles, including this year’s regular-season/tournament double. Brown steered the Titans into the NCAA Tournament five of the past seven years.
“I think our investment of time in recruiting not just soccer players, but good people with good mindsets about academics, [is what] keeps us safe from mistakes,” Brown said. “It’s important that we have really strong recruiting classes.
“The first thing that jumps out is athleticism — that’s a factor and one of the first things you can see. The next is decisions they make on the field. You want to see them make good decisions. Then, we look at technical skills and how they perform. If you’re recruiting a defender, is she defending well? If it’s a forward, are they scoring goals at the youth level? Those are the things we’re looking to see.”
When she was in high school, Lyndy Davis realized that instead of writing lengthy descriptions in her training log about how she felt during each training run, she could simply color-code her runs with appropriately chosen highlighters.
“The training journal already stated the facts: distance and pace,” she says, “[but] I was trying to figure out what workouts made me too tired, and what my week looked like before a good race versus a bad race. Color-coding was fun and helpful.”
This study compared injury incidence and training loads between single and multi-match weeks, and seasons with and without congested scheduling. Measures of internal (session-Rating of Perceived Exertion × duration for training/match and % maximal heart rate) and external load (total, low-, high-, and very high-intensity running distances) along with injury incidence rates were determined from 42 players over 3 seasons; including 1 without and 2 (season 2 and 3) with regular multi-match weeks. Within-player analyses compared 1 (n=214) vs. 2-match (n=86) weeks (>75min in matches), whilst team data was compared between seasons. Total injury rates were increased during multi-match weeks (p=0.001), resulting from increased match and training injuries (50.3, 16.9/1000h). Between-season total injury rates were highest when congested scheduling was greatest in season 3 (27.3/1000h) and season 2 (22.7/1000h) vs. season 1 (14.1/1000h; p=0.021). All external load measures were reduced in multi-match weeks (p<0.05). Furthermore, all internal and external training loads were lowest in seasons with congestion (p<0.05). In conclusion, increased injury rates in training and matches exist. Total loads remain comparable between single and multi-match weeks, though reduce in congested seasons. Whether injuries result from reduced recovery, increased match exposure or the discreet match external loads remain to be elucidated.
Imagine if a computer could learn from molecules found in nature and use an algorithm to generate new ones. Then imagine those molecules could get printed and tested in a lab against some of the nastiest, most dangerous bacteria out there—bacteria quickly becoming resistant to our current antibiotic options.
Or consider a bandage that can sense an infection with fewer than 100 bacterial cells present in an open wound. What if that bandage could then send a signal to your phone letting you know an infection had started and asking you to press a button to trigger the release of the treatment therapy it contained?
These ideas aren’t science fiction. They’re projects happening right now, in various stages, in the lab of Penn synthetic biologist César de la Fuente, who joined the University as a Presidential Professor in May 2019. His ultimate goal is to develop the first computer-made antibiotics. But beyond that, his lab—which includes three postdoctoral fellows, a visiting professor, and a handful of graduate students and undergrads—has many other endeavors that sit squarely at the intersection of computer science and microbiology.
Skeletal muscle injury provokes a regenerative response, characterized by the de novo generation of myofibers that are distinguished by central nucleation and re-expression of developmentally restricted genes. In addition to these characteristics, myofiber cross-sectional area (CSA) is widely used to evaluate muscle hypertrophic and regenerative responses. Here, we introduce QuantiMus, a free software program that uses machine learning algorithms to quantify muscle morphology and molecular features with high precision and quick processing-time. The ability of QuantiMus to define and measure myofibers was compared to manual measurement or other automated software programs. QuantiMus rapidly and accurately defined total myofibers and measured CSA with comparable performance but quantified the CSA of centrally-nucleated fibers (CNFs) with greater precision compared to other software. It additionally quantified the fluorescence intensity of individual myofibers of human and mouse muscle, which was used to assess the distribution of myofiber type, based on the myosin heavy chain isoform that was expressed. Furthermore, analysis of entire quadriceps cross-sections of healthy and mdx mice showed that dystrophic muscle had an increased frequency of Evans blue dye+ injured myofibers. QuantiMus also revealed that the proportion of centrally nucleated, regenerating myofibers that express embryonic myosin heavy chain (eMyHC) or neural cell adhesion molecule (NCAM) were increased in dystrophic mice. Our findings reveal that QuantiMus has several advantages over existing software. The unique self-learning capacity of the machine learning algorithms provides superior accuracy and the ability to rapidly interrogate the complete muscle section. These qualities increase rigor and reproducibility by avoiding methods that rely on the sampling of representative areas of a section. This is of particular importance for the analysis of dystrophic muscle given the “patchy” distribution of muscle pathology. QuantiMus is an open source tool, allowing customization to meet investigator-specific needs and provides novel analytical approaches for quantifying muscle morphology. [full text]
It’s been just shy of two months since Skydio announced the Skydio 2 drone, which is virtually entirely dedicated to sports tracking (in the consumer realm anyway). I previously tested the R1 drone about two years ago, which did incredible things in terms of autonomous tracking, but also wasn’t practical from a price standpoint ($2,500) or a size standpoint (roughly like a pizza box).
The Skydio 2 (which I’m going to abbreviate R2, because that’s what’s stuck in my head) – is $999 and roughly the footprint of an iPad. Plus, they dramatically increased the image quality up to 4K60 HDR as well as introduced a new GPS beacon in cases where visual tracking isn’t possible (such as through dense trees), so it can keep following along (kinda like the old AirDog drones). It does all this by using seven (yes, 7), cameras at 4K resolution each.
Karlsruhe Institute of Technology, Press Release from
“Anthrokinemat,” a smart knee bandage, is to support arthrosis patients in determining the right amount of daily exercise. All relevant data on the strains of the joints are collected and transferred to the patient’s mobile phone. Development of the bandage is based on work of sports scientists of Karlsruhe Institute of Technology (KIT), which was funded by the Federal Ministry for Economic Affairs and University Energy (BMWi) in the past three years. Project partners are the of Bremen, the bandage manufacturer Bauerfeind, and the sensor technology company ITP. Within a follow-up research project, a prototype will be developed.
arXiv, Computer Science > Computer Vision and Pattern Recognition; Lucas Caccia, Herke van Hoof, Aaron Courville, Joelle Pineau from
Building models capable of generating structured output is a key challenge for AI and robotics. While generative models have been explored on many types of data, little work has been done on synthesizing lidar scans, which play a key role in robot mapping and localization. In this work, we show that one can adapt deep generative models for this task by unravelling lidar scans into a 2D point map. Our approach can generate high quality samples, while simultaneously learning a meaningful latent representation of the data. We demonstrate significant improvements against state-of-the-art point cloud generation methods. Furthermore, we propose a novel data representation that augments the 2D signal with absolute positional information. We show that this helps robustness to noisy and imputed input; the learned model can recover the underlying lidar scan from seemingly uninformative data
… a team led by Dr. John Rogers at Northwestern University in Chicago described a smart patch that could ostensibly track nearly every vibration your body generates. We’re not just talking about steps or other movement, such as walking or stretching. The soft patch, not much larger than a Band-Aid, uses high-bandwidth accelerometers that also capture delicate, minute internal movements in the body.
In other words, nearly any bodily function that causes your tissue and organs to mechanically shift is hypothetically trackable with the patch: movements, body orientation, swallowing, breathing, heart rhythms, vocal vibrations, and sleep.
That’s not all. “By design, the technologies and methods described here align well with current manufacturing practices and commercial components, thereby offering a high level of technology readiness,” the authors wrote
Injuries in professional sports have a significant impact on performance and also imply an economic cost for the teams that lose a player. One study has estimated that in the first half of the 2018-2019 season, the Premier League spent around £130 million on the salaries of injured players (JLT Specialty Limited, 2019). In an attempt to reduce injury incidence, new research is being conducted to identify the main risk factors.
A recent research study (Rodas et al., 2019) was carried out with the support of Progenika (GRIFOLS) which involved, among others, Gil Rodas and Ricard Pruna, doctors at FC Barcelona, and as well renowned researchers such as Alejandro Lucía. They analysed the association between the risk of tendinopathy and the variations in the genetic sequence (polymorphism) in team sports players. To do this, they extracted blood samples from 363 professional players from different sports areas of the club (football, basketball, handball, roller hockey and futsal) during the 2018-2019 pre-season, and analysed the incidence of tendinopathy in the previous ten years.
The Hockey Writers blog, The Canadian Press, Joshua Clipperton from
… Needless to say, long gone are the days when Martin Brodeur would start 75 games and then be expected to carry his team through four post-season rounds.
But is there a sweet spot for what amounts to a pitch count for goalies in 2019?
“It’s always a challenge,” Capitals head coach Todd Reirden said. “You have a template, you have a blueprint that you want to go with (for) your goaltenders and we’ve already had to adjust it.”
Is a smiling flight attendant performing emotional labor? How about the harried mom baking cupcakes for a kindergarten class, or your friend who’s always ready to listen and dispense advice?
The term “emotional labor” was first coined in 1983 by sociologist Arlie Russell Hochschild to refer to jobs that require people to manage the feelings of others at the expense of their own. Consider, for instance, how child-care workers and teachers must maintain a cheerful, positive tone with their charges and parents, regardless of how they feel.
The concept has been expanded and become a lens to view a variety of paid and unpaid work, including household chores and household management, social organizing at the office, and intimate relationships, with an eye toward the hidden, unacknowledged costs of time, effort, and stress. And in the seminar course “Love’s Labors Found: Uncovering Histories of Emotional Labor,” Caroline Light and her students scrutinize the myriad ways emotion and work intersect, encouraging students to think critically about the connections between labor and identity, and how their experiences fit into larger systems.