Utilization of neural network to analyze Free Word Association to predict accurately age, gender, first language, and current country.
Read More...Investigating the connection between free word association and demographics
Utilization of neural network to analyze Free Word Association to predict accurately age, gender, first language, and current country.
Read More...Maternal mortality rates in the United States correlated with social determinants of health
This article helps in understanding the effect of various social determinants on maternal mortality in the United States. It explains the relationship between maternal mortality rates and factors like race, income, education, and health insurance access.
Read More...Unveiling bias in ChatGPT-3.5: Analyzing constitutional AI principles for politically biased responses
Various methods exist to mitigate bias in AI models, including "Constitutional AI," a technique which guides the AI to behave according to a list of rules and principles. Lo, Poosarla, Singhal, Li, Fu, and Mui investigate whether constitutional AI can reduce bias in AI outputs on political topics.
Read More...Synthesis of sodium alginate composite bioplastic films
The authors looked at the development of biodegradable bioplastic and its features compared to PET packaging films. They were able to develop a biodegradable plastic with sodium alginate that dissolved in water and degrade in microbial conditions while also being transparent and flexible similar to current plastic films.
Read More...Exploring differences in men’s marijuana consumption and cigarette smoking by race and citizenship status
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.
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...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...Effects of noise on information corruption in the quantum teleportation algorithm
In quantum computing, noise disrupts experimental results, particularly affecting the quantum teleportation algorithm used to transfer qubit states. This study explores how noise impacts this algorithm across different platforms—a perfect simulation, a noisy simulation, and real hardware.
Read More...The effects of plasticizers on the mechanical properties and chemical composition of a gelatin biopolymer
Here, in an effort to identify alternatives to oil-based plastic, the authors sought to investigate the effects of plasticizers on the mechanical properties and chemical composition of gelatin bioplastic matrices. Through measurements of their tensile strength and elongation at break, along with FTIR spectroscopy, they identified 3% w/v polyethylene glycol film as having the best performance in their study..
Read More...Studying the effects of different anesthetics on quasi-periodic patterns in rat fMRI
The authors looked at the effects of commonly used anesthetics in rodents on brain activity (specifically quasi-periodic patterns). Understanding effects on brain activity is important for researchers to understand when choosing rodent models for disease.
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