Here, the authors sought to develop a new metric to evaluate the efficacy of baseball pitchers using machine learning models. They found that the frequency of balls, was the most predictive feature for their walks/hits allowed per inning (WHIP) metric. While their machine learning models did not identify a defining trait, such as high velocity, spin rate, or types of pitches, they found that consistently pitching within the strike zone resulted in significantly lower WHIPs.
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Surface cleanliness of hydrothermally grown zinc oxide microparticles compared to commercial nanoparticles
The authors test the usefulness of zinc oxide microparticles relative to zinc oxide nanoparticles as antibacterial agents.
Read More...Quantitative NMR spectroscopy reveals solvent effects in the photochemical degradation of thymoquinone
Thymoquinone is a compound of great therapeutic potential and scientific interest. However, its clinical administration and synthetic modifications are greatly limited by its instability in the presence of light. This study employed quantitative 1H nuclear magnetic resonance (NMR) spectroscopy to identify the effect of solvation on the degradation of thymoquinone under ultraviolet light (UV). It found that the rate of degradation is highly solvent dependent occurs maximally in chloroform.
Read More...Understanding investors behaviors during the COVID-19 outbreak using Twitter sentiment analysis
The authors examine a relationship between tweet sentiment and stock market behavior during the early weeks of the COVID-19 pandemic.
Read More...Income mobility and government spending in the United States
Recent research suggests that the "American Dream" of income mobility may be becoming increasingly hard to obtain. Datta and Schmitz explore the role of government spending in socioeconomic opportunity by determining which state government spending components are associated with increased income mobility.
Read More...Analysis of the lung microbiome in cystic fibrosis patients using 16S sequencing
In this article the authors look at the lung microbiome in patients with cystic fibrosis to determine what the major bacterial species present are.
Read More...Implementing machine learning algorithms on criminal databases to develop a criminal activity index
The authors look at using publicly available data and machine learning to see if they can develop a criminal activity index for counties within the state of California.
Read More...Developing novel plant waste-based hydrogels for skin regeneration and infection detection in diabetic wounds
The purpose of this investigation is to develop a hydrogel to aid skin regeneration by creating an extracellular matrix for fibroblast growth with antibacterial and infection-detection properties. Authors developed two natural hydrogels based on pectin and potato peels and characterized the gels for fibroblast compatibility through rheology, scanning electron microscopy, swelling, degradation, and cell cytotoxicity assays. Overall, this experiment fabricated various hydrogels capable of acting as skin substitutes and counteracting infections to facilitate wound healing. Following further testing and validation, these hydrogels could help alleviate the 13-billion-dollar financial burden of foot ulcer treatment.
Read More...From trash to treasure: A sustainable approach to oil spill clean-up
In this study the authors looked at sustainable ways to clean up oil spills that harm marine life. Using water spangle leaves and milk week the authors looked at the ability to recovery oil from both fresh and salt water and the ability to reuse the organic material to clean up spills. Their results show promise to help find a sustainable, eco-friendly way to clean up oil spills and protect marine life and habitats.
Read More...Differences in postoperative satisfaction between orthopedic and cosmetic patients
In this study, the authors investigate differences in psychological outcomes from patients who undergo different surgical procedures.
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