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An analysis of the mechanical properties of fencing swords, and implications for weapon selection

Redmond et al. | Aug 24, 2026

An analysis of the mechanical properties of fencing swords, and implications for weapon selection
Image credit: Jonathan Falcon

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.

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Comparative study on three machine learning models in novel autonomous drone-based detection of invasive plant Brassica nigra

Ho et al. | Jul 05, 2026

Comparative study on three machine learning models in novel autonomous drone-based detection of invasive plant <em>Brassica nigra</em>

Autonomous drone imaging combined with machine learning offers a promising approach for early detection of invasive species. In this study, students built an autonomous drone and compared three models: CNN, SGDC, and XGBoost, to identify Brassica nigra from aerial footage. Their results show that CNNs most effectively recognize key visual features, demonstrating strong potential for supporting conservation and invasive plant management.

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A study of Syrian students' migration motivations, destinations, and return intentions in a time of crisis

Merjaneh et al. | Apr 16, 2026

A study of Syrian students' migration motivations, destinations, and return intentions in a time of crisis
Image credit: Aaron Burden, 2017

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.

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