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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 looked at whether retinal features, specifically lens clarity, optic nerve cupping, and hyperreflective foci, can serve as biomarkers for neuro-ophthalmological diseases, which share pathological mechanisms with neurodegeneration and may indicate broader neurological risk. Using multimodal clinical data and machine learning, they investigated the potential of retinal imaging as a complementary diagnostic tool for more accurate and accessible detection of neurological disorders.

We observed supernova 2025ngs and created its light curve through aperture photometry. We were then able to determine that 2025ngs was a Type II-P supernova.

Multi-perspective drone imagery (adding oblique views to top-down shots) raised crop classification accuracy from 35.73% to 52.93% across five species. The improvement scaled with canopy complexity, from +4.2% for simple rice to +38.1% for structurally complex sugarcane.

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

The authors monitored water quality over time looking for influences from construction and deforestation.

This project investigated whether previously identified genetic risk factors in non-Korean populations were associated with high gastric cancer incidence rates in Koreans.

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.

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 evaluated the effectiveness of common stress-relief strategies used by high schoolers.