This study examined the relationship between citizenship status, racial background, and the use of marijuana and cigarettes among males in California using data from the 2017–2018 California Health Interview Survey. Findings indicated that non-citizens and naturalized citizens were less likely to use marijuana compared to US-born citizens, while Asian and Latino males were less likely to consume marijuana than White males. Additionally, various racial groups were more likely to smoke cigarettes compared to White males, suggesting that targeted health interventions based on citizenship status and race could be beneficial.
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Ocean, atmosphere, and cloud quantity on the surface conditions of tidally-locked habitable zone planets
The authors assessed the atmospheric and oceanic parameters necessary for tidally-locked exoplanets to be habitable.
Read More...Investigating the inhibition of catabolic enzymes for implications in cardiovascular diseases and diabetes
Enzymes that metabolize carbohydrates and lipids play a key role in our health, including global health challenges like cardiovascular diseases and diabetes. To learn more about these important enzymes, Gandhi and Gandhi test whether various natural substances (ginger, Aloe vera, lemon, and mint leaves) affect the activity of α-amylase and lipase enzymes.
Read More...Vineyard vigilance: Harnessing deep learning for grapevine disease detection
Globally, the cultivation of 77.8 million tons of grapes each year underscores their significance in both diets and agriculture. However, grapevines face mounting threats from diseases such as black rot, Esca, and leaf blight. Traditional detection methods often lag, leading to reduced yields and poor fruit quality. To address this, authors used machine learning, specifically deep learning with Convolutional Neural Networks (CNNs), to enhance disease detection.
Read More...A HOG feature extraction and CNN approach to Parkinson’s spiral drawing diagnosis
Parkinson’s disease (PD) is a prevalent neurodegenerative disorder in the U.S., second only to Alzheimer’s disease. Current diagnostic methods are often inefficient and dependent on clinical exams. This study explored using machine and deep learning to enhance PD diagnosis by analyzing spiral drawings affected by hand tremors, a common PD symptom.
Read More...Cardiovascular Disease Prediction Using Supervised Ensemble Machine Learning and Shapley Values
The authors test the effectiveness of machine learning to predict onset of cardiovascular disease.
Read More...Optical anisotropy of crystallized vanillin thin film: the science behind the art
Microscopic beauty is hiding in common kitchen ingredients - even vanillin flavoring can be turned into mesmerizing artwork by crystallizing the vanillin and examining it under a polarizing microscope. Wang and Pang explore this hidden beauty by determining the optimal conditions to grow crystalline vanillin films and by creating computer simulations of chemical interactions between vanillin molecules.
Read More...Addressing and Resolving Biases in Artificial Intelligence
The authors explore how diversity in data sets contributes to bias in artificial intelligence.
Read More...Computational analysis and drug repositioning: Targeting the TDP-43 RRM using FDA-approved drugs
Molecules which bind to proteins that aggregate abnormally in neurodegenerative diseases could be promising drugs for these diseases. In this study, Zhang, Wu, Zhang, and Dang simulate the binding behavior of various molecules to screen for candidates which could be promising candidates for drug development.
Read More...Battling cultural bias within hate speech detection: An experimental correlation analysis
The authors develop a new method for training machine learning algorithms to differentiate between hate speech and cultural speech in online platforms.
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