The authors used machine learning to predict the presence of anxiety and burnout in students based on facial expressions and demographic information.
Read More...Identifying anxiety and burnout from students facial expressions and demographics using machine learning
The authors used machine learning to predict the presence of anxiety and burnout in students based on facial expressions and demographic information.
Read More...Groundwater prediction using artificial intelligence: Case study for Texas aquifers
Here, in an effort to develop a model to predict future groundwater levels, the authors tested a tree-based automated artificial intelligence (AI) model against other methods. Through their analysis they found that groundwater levels in Texas aquifers are down significantly, and found that tree-based AI models most accurately predicted future levels.
Read More...Relating socioeconomic position (SEP) and vaccination with Covid-19 rates in select populations
This article describes the relationship between socioeconomic factors and the extent of how the COVID-19 Pandemic affected communities. Factors such as infection rate, vaccination rate, and economic status were all evaluated within the context of this article.
Read More...Analyzing market dynamics and optimizing sales performance with machine learning
This study uses interpretable machine learning models, lasso and ridge regression with Shapley analysis, to identify key sales drivers for Corporación Favorita, Ecuador’s largest grocery chain. The results show that macroeconomic factors, especially labor force size, have the greatest impact on sales, though geographic and seasonal variables like city altitude and holiday proximity also play important roles. These insights can help businesses focus on the most influential market conditions to enhance competitiveness and profitability.
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.
Read More...COVID-19 and air pollution in New York City
Did the COVID-19 pandemic and travel restrictions improve air quality? The authors investigate this question in New York City using existing pollution data and forecasting trends.
Read More...Detergent pollutants decrease nutrient availability in soil
Household detergents have surfactants that can potentially harm the soil and broader ecosystems. In this study, the authors investigate whether eco-friendly and less-eco-friendly detergents affect soil pH, phosphorus, nitrogen, and potassium levels.
Read More...Increased survival of aquatic life through algal pretreatment of nitrate-contaminated runoff
Here the authors investigated the effectiveness of algal pretreatment in reducing nitrate toxicity and extending the survival of fish in contaminated river water. Their findings demonstrate that treating nitrate-polluted water with algae extended fish survival by up to 50%, suggesting that algae could serve as a valuable tool for mitigating the destructive impacts of agricultural and industrial runoff on aquatic ecosystems.
Read More...Who controls U.S. politics? An analysis of major political endorsements in U.S. midterm elections
The authors analyze political endorsement patterns and impacts from the 2018 and 2020 midterm elections and find that such endorsements may be predictable based on the ideological and demographic factors of the endorser.
Read More...Rover engineered to evaluate impacts of microclimatic parameters on pediatric asthma in Dallas schools
Pediatric asthma remains a significant health issue for Dallas students. This study examined the relationship between microclimatic parameters, vegetation, and pediatric asthma vulnerability (PAV) in urban schools.
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