A baseball pitcher for the Arizona Diamondbacks’ minor league team spends some of his time off the mound mowing lawns in northern California.
Scott Randall of Rocklin, California, was drafted by the Diamondbacks family of teams in July. He plays for the Visalia Rawhide, a single-A club whose season doesn’t start back until next spring. To keep money coming in for now, Randall told CBSN Sacramento that he offers lawn mowing around his neighborhood.
… “Last camp was obviously a great experience for us all – [for] a lot of us, our first taste of what World Cup qualifying was going to be like,” said the RB Leipzig midfielder.
“The most important thing coming into this camp now is to take each and every game, game by game, not focused on saying, ‘OK, let’s get nine points.’ I mean, I remember, even myself, I previously said, ‘let’s get nine points in the window.’ Let’s focus on each game and what we need to do in order to win each game. And then I think that’s going to set us up for the best success.”
… In one of his interviews, Stockton talked about load management and how players are not doing enough work to be prepared mentally and physically, which are the two critical aspects of being an elite player. Stockton was often the smallest player on the court, but he made up with hard work and tenacity, which he lacked in height and weight. He believes toughness is a necessary trait for any player and his team that wants to be dominant and productive for a more extended period during the season.
Context: The quality of running mechanics is often characterized by limb pattern symmetry and used to support clinical decisions throughout the rehabilitation of lower-extremity injuries. It is valuable to ensure that gait analyses provide stable measures while not asking an individual to complete an excessive number of running strides. The present study aimed to determine the minimum number of strides required to establish a stable mean symmetry index (SMSI) of discrete-level measures of spatiotemporal parameters, joint kinematics, and joint kinetics. Further, the study aimed to determine if differences occurred between random and consecutive strides for directional and absolute symmetry indices.
Design: Descriptive laboratory study.
Methods: A sequential average was used to determine how many strides were required to achieve a SMSI within a 60-second trial. Multiple 2-factor repeated-measure analysis of variances were used to determine if differences between bins of strides and symmetry calculations were significantly different.
Results: A median SMSI was achieved in 15 strides for all biomechanical variables. There were no significant differences (P > .05) found between consecutive and random bins of 15 strides within a 60-second trial. Although there were significant differences between symmetry calculation values for most variables (P < .05), there appeared to be no systematic difference between the numbers of strides required for stable symmetry for either index.
Conclusions: As 15 strides were sufficient to achieve a SMSI during running, a continued emphasis should be placed on the number of strides collected when examining interlimb symmetry.
International Journal of Sports Physical Therapy from
Purpose: To assess the impact of long-haul transmeridian travel on subjective sleep patterns and jet lag symptoms in youth athletes around an international tournament. Methods: An observational descriptive design was used. Subjective sleep diaries and perceived responses to jet lag were collected and analyzed for a national junior netball team competing in an international tournament. Sleep diaries and questionnaires were completed daily prior to and during travel, and throughout the tournament. Results were categorized into pretravel, travel, training, and match nights. Means were compared performing a paired Student t test with significance set at P < .05. Data are presented as mean (SD) and median (minimum, maximum). Results: Athletes reported significantly greater time in bed on match days compared with training (P < .001) and travel (P = .002) days, and on pretravel days compared with travel (P < .001) and training (P = .028) days. Sleep ratings were significantly better on pretravel days compared with match (P = .013) days. Perceived jet lag was worse on match (P = .043) days compared with pretravel days. Significant differences were also observed between a number of conditions for meals, mood, bowel activity, and fatigue. Conclusion: Youth athletes experience significantly less opportunity for sleep during long-haul transmeridian travel and face disruptions to daily routines during travel which impact food intake. Young athletes also experience disturbed sleep prior to and during competition. These results highlight the need for practices to alleviate jet lag symptoms and improve the sleep of young athletes traveling for tournaments in an effort to optimize recovery and performance.
FFollowing a season in which NHL players were encouraged to stay at home as much as they could, the Rangers are looking to make up for lost time on team bonding.
The Blueshirts were scheduled to remain in the New England area for a series of activities coming off of Saturday’s morale-boosting 4-3 preseason win over the Bruins at TD Garden.
“We’re going to go golfing, we’re going to do some things with the guys, like archery and stuff like that, skeet shooting,” Ryan Strome said Saturday after the Rangers improved to 2-2 on the preseason. “I think it’s more just in New York, we have guys who live in the city, some guys live in White Plains, some guys live in Connecticut and this is a great way to have everyone together without the distractions of your families and stuff.
Exercise-related lower leg pain (ERLLP) is one of the most prevalent running-related injuries, however little is known about injured runners’ mechanics during outdoor running. Establishing biomechanical alterations among ERLLP runners would help guide clinical interventions. Therefore, we sought to a) identify defining biomechanical features among ERLLP runners compared to healthy runners during outdoor running, and b) identify biomechanical thresholds to generate objective gait-training recommendations. Thirty-two ERLLP (13 M, age: 21 ± 5 years, BMI: 22.69 ± 2.25 kg/m2) and 32 healthy runners (13 M, age: 23 ± 6 years, BMI: 22.33 ± 3.20 kg/m2) were assessed using wearable sensors during one week of typical outdoor training. Step-by-step data were extracted to assess kinetic, kinematic, and spatiotemporal measures. Preliminary feature extraction analyses were conducted to determine key biomechanical differences between healthy and ERLLP groups. Analyses of covariance (ANCOVA) and variability assessments were used compare groups on the identified features. Participants were split into 3 pace bands, and mean differences across groups were calculated to establish biomechanical thresholds. Contact time was the key differentiating feature for ERRLP runners. ANCOVA assessments reflected that the ERLLP group had increased contact time (Mean Difference [95% Confidence Interval] = 8 ms [6.9,9.1], p < .001), and approximate entropy analyses reflected greater contact time variability. Contact time differences were dependent upon running pace, with larger between-group differences being exhibited at faster paces. In all, ERLLP runners demonstrated longer contact time than healthy runners during outdoor training. Clinicians should consider contact time when assessing and treating these ERLLP runner patients.
Until now, healthcare and biotechnology have been heavily dominated by services — provided by expertly trained scientists and doctors — that algorithms could not replace, let alone add enough value, to make sense for companies to adopt them. But now, we are at the very beginning of a revolution where AI is industrializing biopharma and healthcare, and it is being applied to everything from drug design and diagnostics to healthcare delivery and back-office functions. [As for concerns or challenges that often come up with discussions of applying AI in bio, I address the “black box” of AI in healthcare here; and address what’s needed for us to get smart (vs. “dumb”) AI in bio, here.]
American Chemcal Society, ACS News Service Weekly Press Pac from
… Beelee Chua and Donghyun Lee wanted to repurpose unconventional and widely available materials, including electrically conductive soft candies, into an easily accessible, low-waste sensor that could simply be licked by patients to analyze their saliva.
To make the prototype sensor, the researchers first flattened a Tootsie Roll® and pressed crevices into its surface in a crosshatched pattern to hold the saliva sample. Then, they inserted two thin, reusable aluminum tubes, which acted as electrical contacts, connecting the candy electrode into a circuit with a current source and an output voltage detector. In preliminary tests, the device could measure salt levels that were physiologically relevant for health monitoring in a salt-water solution and artificial saliva
University of Texas at Austin, Aerospace Engineering and Engineering Mechanics from
Medical sensing technology has taken great strides in recent years, with the development of wearable devices that can track pulse, brain function, biomarkers in sweat and more. However, there is one big problem with existing wearable pressure sensors: even the slightest amount of pressure, something as light as a tight long sleeve shirt over a sensor, can throw them off track.
Texas Engineers have solved this problem, which has been vexing the field for years now. And they did it by innovating a first-ever hybrid sensing approach that allows the device to possess properties of the two predominant types of sensors in use today.
“The field of flexible pressure sensors is extremely crowded, and after two decades we hit a bottleneck because no one could solve the tradeoff between pressure and sensitivity,” said Nanshu Lu, an associate professor in the Department of Aerospace Engineering and Engineering Mechanics and the corresponding author of the new research published today in Advanced Materials. “This is the first sensor able to leverage a new hybrid mode to withstand pressure without a significant decay in sensitivity.”
Researchers have made a key advancement in the development of technology to automatically analyze video of hockey games using artificial intelligence.
Engineers at the University of Waterloo combined two existing deep-learning AI techniques to identify players by their sweater numbers with 90-per-cent accuracy.
“That is significant because the only major cue you have to identify a particular player in a hockey video is jersey number,” said Kanav Vats, a PhD student in systems design engineering who led the project. “Players on a team otherwise appear very similar because of their helmets and uniforms.”