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The authors examined the relationships between S&P 500 Technology and Financials equity sectors and their corresponding investment-grade fixed-income markets from 1995 to 2025.

It can be challenging for the general public to understand data on medical risk. Weseley-Jones and Mordechai tackle this issue by conducting a survey to assess people's skill and comfort with understanding medical risk information in percentage and frequency formats.

Online review platforms often provide different reviews on the same product, potentially confusing consumers. In this study, we found that the number of raters on Amazon is lower for the same book, while ratings on Amazon were higher than those on Goodreads. Furthermore, these differences in ratings and rater counts were larger for fiction books than for non‑fiction books.

Agricultural fertilizer application is a key innovation in providing enough food to feed the world. Fertilizers come in various types and farmers must choose which fertilizer is the best for their applications. To learn more about the effectiveness of various fertilizers, Wilson and Rasmus studied the effects of natural and chemical fertilizers on growth of basil plants.

The authors found that SARIMAX-GARCH is more accurate than SARIMAX for load forecasting with respect to energy consumption.

In this study, the authors created a survey to assess misconceptions and knowledge deficits regarding cardiovascular diseases exist among US adults and minors.

This study investigated perceptions of the emerging workforce toward the use of artificial intelligence in hiring, specifically for assessing subjective "culture fit." Through a mixed-methods survey of 150 high school and early-college students in Nepal, we found a significant disconnect between organizational adoption of AI and the profound skepticism of young job candidates, who express deep concerns about fairness, transparency, and the potential for AI to perpetuate systemic discrimination.

Algorithmic trading has been increasingly used by Americans. In this work, we tested whether including the opening, closing, and highest prices in three supervised learning models affected their performance. Indeed, we found that including all three prices decreased the error of the prediction significantly.

The authors looked at the ability of machine learning algorithms to interpret language given their increasing use in moderating content on social media. Using an explainable model they were able to achieve 81% accuracy in detecting fake vs. real news based on language of posts alone.

This study investigates how bending radius, wavelength, and number of turns affect signal attenuation in single-mode optical fibers.