The authors test the effect of insecticide exposure on mouse neurodevelopment.
Read More...Chlorpyrifos exposure in mice leads to altered expression of key neurodevelopmental proteins
How teaching style influences math learning: Comparing discovery and traditional instruction
This study compares traditional and discovery-based instructional methods in online middle school mathematics education. Findings show that discovery-based learning significantly improves students’ academic performance and attitudes, highlighting the value of inquiry-driven instruction for enhancing both understanding and motivation.
Read More...In silico design of an epitope-based vaccine for Rocio virus using phage display and E. coli expression system
The explored the potential of an epitope-based vaccine for Rocio virus using computational methods and M13 bacteriophage technology. Researchers identified 30 promising B- and T-cell epitopes and designed vaccine candidates using both phage display and E. coli expression systems.
Read More...Performance comparison of indoor polyculture utilizing hydroponic and soil-based systems
Hydroponics is often promoted as a highly efficient alternative to traditional soil farming, but its effectiveness in small indoor polyculture systems is not well understood. In this study, students compared plant growth and maturity across hydroponic and soil-based indoor polycultures and found that soil grown plants were generally taller and more mature than those grown hydroponically. These results suggest that soil-based methods may outperform hydroponics in certain household polyculture settings.
Read More...Testing the Impact of a Geometric Curvature Variable on the Accuracy of Econometric Forecasting Models
Classical financial forecasting models often fail to capture the complex, nonlinear dynamics of the stock market. This study demonstrates that incorporating a single variable to represent the 'geometric curvature' of a time series dramatically improves the accuracy of standard econometric forecasts. Our findings highlight that geometric properties are a significant predictive factor, opening new avenues for more powerful financial modeling.
Read More...A model for angle evolution in conical piles formed using the fixed funnel method
When granular materials are poured onto a surface, they form conical piles whose slopes increase before reaching a stable angle of repose. We found that this angle evolution follows a previously unrecognized two-phase exponential growth pattern that is conserved across granular materials with diverse particle properties. The parameters of this model correlate with particle friction and are influenced by deposition conditions, providing a quantitative framework for describing pile formation.
Read More...Early detection of student burnout using data science: a study of behavioral and psychological indicators
This study examined behavioral and psychological predictors of burnout among high school and university students in Pakistan using survey data and machine-learning models. Shorter sleep and greater mental fatigue—especially fatigue—were associated with higher burnout risk, while a Random Forest model successfully identified students at risk of burnout.
Read More...Effect of fuel density and temperature on helium-3 fusion reaction rates in stellar cores
This paper discusses how the conditions at the center of stars affects the nuclear reactions that happen inside these stars. We focused on the effect of temperature and density and found that these two properties interacted to create a greater effect when combined than when separate.
Read More...The influence of economic factors on United States household energy consumption in 2020
This study used machine learning models to examine which factors most influenced U.S. household energy consumption in 2020 using data from 18,496 households.
Read More...Large-scale brain network connectivity under anxiety induced by naturalistic story listening
This study found that anxiety induced by a suspenseful story increased communication between the brain’s salience, default mode, and central executive networks, with the central executive network acting as a bridge during peak tension. These findings suggest that anxiety alters large-scale brain connectivity patterns and may help inform future diagnostic tools and personalized treatments for anxiety disorders.
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