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The study examined whether high school boys’ water polo teams located near strong programs had similar season performances during the 2024–2025 season.

In this study, we examined the consistency and dependability of Google's Lighthouse tool for measuring website performance, accessibility, SEO, and best practices. Tests conducted on three websites showed that performance scores vary based on the testing mode and website complexity, while other audit categories stay constant. These results provide direction for researchers and developers by highlighting Lighthouse's benefits and drawbacks.

This study examined how prescribed fires affect arthropods in riparian zones surrounding wetlands in north-central Florida. Researchers found that spider abundance remained largely unchanged, while springtail abundance initially decreased but rebounded substantially one month after burning, suggesting early recovery of the riparian food web.

This study used single-cell RNA sequencing to examine whether B cells can predict response to pembrolizumab and radiation therapy in patients with triple-negative breast cancer.

Machine learning systems are often expected to make fair decisions, yet the most widely used fairness criteria—independence, separation, and sufficiency—cannot generally be satisfied at the same time. In this study, students tested these criteria using a logistic regression model on a real-world student performance dataset and found that each criterion was met only at different prediction thresholds, with no threshold satisfying all three simultaneously. These results illustrate the inherent trade-offs in algorithmic fairness and highlight why achieving perfectly fair machine learning models is often impossible in practice.

Physics‑Informed Neural Networks (PINNs) offer a promising way to estimate blood‑flow behavior in arteries, especially near the vessel wall where traditional methods struggle. In this study, students tested how sensor density and placement affect PINN accuracy in modeling carotid artery flow and found that accuracy improves up to a moderate sensor density and depends strongly on how close sensors are placed to the arterial wall. Applying the optimized configuration to a patient‑specific carotid model produced velocity predictions closely matching computational fluid dynamics results, highlighting PINNs’ potential for future personalized cardiovascular assessment.

The authors test the effect of insecticide exposure on mouse neurodevelopment.

We developed new eco-friendly membranes enriched with natural nanomaterials to clean iron and manganese from drinking water. Some nanocomposite membranes achieved over 95% metal removal while maintaining water flux, suggesting improved performance compared to the undoped control group.

The sword is the most important piece of equipment a fencer uses. In this study, we compared the mechanical and physical properties of two of the most common types of swords used in foil fencing.We that found that maraging steel blades had a significantly greater stiffness and were damped more effectively than low carbon steel blades. These properties affect how the blade behaves during particular maneuvers and techniques, and our findings therefore provide useful insights for fencers who want to select the optimal sword configuration to suit their personal style.

The authors studied the accuracy of two commonly used explainable AI techniques for detecting pneumonia in chest x-rays.