This study used surveys, interviews, and XGBoost analysis to examine how experienced and novice entrepreneurs differ in their thinking and decision-making.
Read More...Examining cognitive differences between experienced and novice entrepreneurs
This study used surveys, interviews, and XGBoost analysis to examine how experienced and novice entrepreneurs differ in their thinking and decision-making.
Read More...Optimizing AI image detection using a Convolutional Neural Network model with Fast Fourier Transform
Recent advances in generative AI have made it increasingly hard to distinguish real images from AI-generated ones. Traditional detection models using CNNs or U-net architectures lack precision because they overlook key spatial and frequency domain details. This study introduced a hybrid model combining Convolutional Neural Networks (CNN) with Fast Fourier Transform (FFT) to better capture subtle edge and texture patterns.
Read More...Increased carmine red exposure periods yields a higher number of vacuoles formed in Tetrahymena pyriformis
T. pyriformis can use phagocytosis to create vacuoles of carmine red, a dye which is made using crushed insects and is full of nutrients. Establishing a relationship between vacuole formation and duration of exposure to food can demonstrate how phagocytosis occurs in T. pyriformis. We hypothesized that if T. pyriformis was incubated in a carmine red solution, then more vacuoles would form over time in each cell.
Read More...Color photometry and light curve modeling of apparent transient 2023jri
Observing transients like supernovae, which have short-lived brightness variations, helps astronomers understand cosmic phenomena. This study analyzed transient 2023jri, hypothesizing it was a Type IIb supernova. By collecting and analyzing data over four weeks, including light and color curves, they confirmed its classification and provided additional insights into this less-studied supernova type.
Read More...Exploration of the density–size correlation of celestial objects on various scales
Building on previous work by earlier astronomers, the authors investigate the correlation between the density and size of celestial objects in the universe, including neutron stars, galaxies, and galaxy clusters.
Read More...Investigating the effects of glucose reintroduction on acutely starved HeLa cells
Cancer cells rely heavily on glycolysis, but how they respond when glucose is reintroduced after acute starvation is not well understood. Using fluorescence lifetime imaging microscopy, students tracked metabolic changes in HeLa cells and found a rapid shift toward glycolysis within 20 minutes of glucose reintroduction, followed by heterogeneous recovery toward oxidative phosphorylation. These results highlight metabolic flexibility and variability in cancer cells, offering insights relevant to treatment resistance and therapeutic design.
Read More...Implication of education levels on gender wage gap across states in the United States and Puerto Rico
Here the authors examined the relationship between education levels and the gender wage gap (GWG) in the US and Puerto Rico from 2010 to 2022, hypothesizing that higher education would correlate with a lower GWG. Their analysis of income data revealed an inverse correlation, where higher education levels were associated with reduced gender wage disparities, suggesting that policies aimed at closing the gender gap in higher education could promote socioeconomic equality.
Read More...Evaluating the impact of prompting styles on LLM accuracy for AIME math questions
Large language models are increasingly used to solve math problems, but their ability to handle multi-step reasoning remains uncertain. In this study, students tested whether different prompting styles could improve LLM accuracy on challenging AIME math questions and found that detailed step-by-step solutions did not significantly outperform simpler prompts. These results suggest that improving LLM mathematical reasoning may require deeper model-level advances rather than changes in prompting style alone.
Read More...Examining the impact of consecutive losses on gambling: When do we decide to quit?
This article explored the question of when do people decide to stop gambling and further tries to extrapolate why people stop gambling at that point. Their study showed that people tend to quit gambling after 4 consecutive losses, significantly more than 1-3 consecutive losses or a win previous to quitting. They also found that participants commonly quit at a point value approximately 5 points greater than or less than their starting balance. The authors concluded that these results may be important in understanding how to cut down on excessive gambling or in creating policies that make it easier for people to disengage from gambling.
Read More...The impact of light pollution on astrophotography and visual astronomy in varying environments