![An optimal pacing approach for track distance events](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBb2NNIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--a0dbe5e21beae177167d12809c567c5f6ee6fc4b/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJYW5CbkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--a3b53ba1a0f83efef18f6e75a8d4ce784384bee2/feature%20and%20home%20image.jpg)
In this study, the authors use existing mathematical models to how high school athletes pace 800 m, 1600 m, and 3200 m distance track events compared to elite athletes.
Read More...An optimal pacing approach for track distance events
In this study, the authors use existing mathematical models to how high school athletes pace 800 m, 1600 m, and 3200 m distance track events compared to elite athletes.
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The goal of this study was to determine the if carbohydrates or complex carbohydrates are better for athlete's performance in anaerobic and aerobic exercise. Ultimately, we found that, when one’s schedule only allows for 30 minutes to eat before a workout, the best pre-workout meal for optimal glycogen levels to prompt muscle hypertrophy, strength increases, and better endurance is one that is simple carbohydrate-heavy.
Read More...Risk assessment modeling for childhood stunting using automated machine learning and demographic analysis
Over the last few decades, childhood stunting has persisted as a major global challenge. This study hypothesized that TPTO (Tree-based Pipeline Optimization Tool), an AutoML (automated machine learning) tool, would outperform all pre-existing machine learning models and reveal the positive impact of economic prosperity, strong familial traits, and resource attainability on reducing stunting risk. Feature correlation plots revealed that maternal height, wealth indicators, and parental education were universally important features for determining stunting outcomes approximately two years after birth. These results help inform future research by highlighting how demographic, familial, and socio-economic conditions influence stunting and providing medical professionals with a deployable risk assessment tool for predicting childhood stunting.
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This study applies Taft linear free-energy relationships to study kinetic trends in the enzymatic hydrolysis of sterically hindered substrates.
Read More...An improved video fingerprinting attack on users of the Tor network
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Here, seeking to develop more efficient solar cells, the authors investigated photo-electrochemical (PEC) solar cells, specifically molybdenum diselenide (MoSe2) based on its high resistance to corrosion. They found that the percentage efficiency of these PEC solar cells was proportional to light intensity–0.9 and that performance was positively influenced by increasing the electrolyte volume. They suggest that studies such as these can lead to new insight into reaction-based solar cells.
Read More...Application of arbuscular mycorrhizal fungi to inhibit nitrogen uptake of weeds within crop fields
In this study, the ability of arbuscular mycorrhizal fungi to limit the growth of an agricultural weed Cirsium arvense is tested. This has important implications for developing natural herbicides.
Read More...The knowledge and perception of opioid abuse and its long-term effects among high schoolers
Due to the susceptibility of adolescent age groups to opioid misuse, here the authors sought to determine if there was a difference in the perception and knowledge between 9th and 12th graders regarding the opioid crisis. An educational intervention trial was done with the 9th graders and surveys were used to identify its effects. Although the authors acknowledge a small sample size, their results suggest that their are gaps within the knowledge of adolescents in regards to opioid misuse and its long-term effects that could be addressed with further education.
Read More...DNA-SEnet: A convolutional neural network for classifying DNA-asthma associations
In this study, the authors developed a model named DNA Sequence Embedding Network (DNA-SEnet) to classify DNA-asthma associations using their genomic patterns.
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