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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 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.

This study aimed to combat widespread hydrocarbon residue persistently polluting global water sources by developing and testing the ability of modified iron(III) oxide-hydroxide (FeO(OH)) nanoparticles to remove small amounts of motor oil from freshwater

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.

Iridescent materials reflect different colored depending on viewing angle. This specific effect can be achieved by biomimetic photonic materials. This project models the quantitative relationship between these material’s coloring and its nanostructure to facilitate personalized design of art materials.

This study investigates the migration intentions of Syrian high school and university students amid ongoing conflict and economic instability. Drawing on survey data, the research examines how academic stage influences migration motivations, preferred destinations, and return intentions. The findings reveal a widespread desire to emigrate, driven by educational, economic, and security concerns, highlighting significant implications for Syria’s future workforce and post-conflict recovery.

The authors used developed a machine learning tool for studying social media discourse surrounding use of tobacco and cannabis.

This manuscript explores the performance of five different machine learning models in classifying brain tumors from a dataset of MRI scans. The authors find that several of the models showed >90% accuracy. Thus, the authors suggest that machine learning models demonstrate potential for effective implementation in clinical settings, including as a diagnostic tool that can be used to complement the expertise of neuroradiologists.

The authors looked at which measurements from the NFL combine were the most predictive of success for defensemen in the NFL.

The authors looked at how injuries sustained during water tubing, that require treatment at an emergency department, differ between males and females.