Research Topic: artificial neural networks

Artificial Neural Network Prediction of Mechanical Properties in Mycelium-Based Biocomposites

Scientists developed an artificial intelligence model that can predict how strong and durable mushroom-based composite materials will be. These composites are made by growing mushroom mycelium (fungal threads) through wood particles and other plant materials, creating an eco-friendly alternative to synthetic materials. The AI model learns from physical measurements and can accurately predict mechanical properties, potentially reducing the need for extensive testing and helping design better sustainable materials.

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Artificial Neural Network Prediction of Mechanical Properties in Mycelium-Based Biocomposites

Researchers used artificial intelligence to predict how strong mushroom-based materials would be. These eco-friendly composites are made from wood particles held together by fungal networks instead of synthetic glue. The AI model successfully learned to predict the strength of these materials based on which type of fungus was used and what wood particles they were grown on, potentially reducing the need for expensive testing.

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Micro-CT and deep learning: Modern techniques and applications in insect morphology and neuroscience

Modern scanning technology called micro-CT can create detailed 3D pictures of tiny insects and their brains without damaging them. Artificial intelligence using deep learning can automatically analyze these massive image files much faster than humans could. Scientists are combining these two technologies to map insect brains and sensory systems in unprecedented detail, potentially revealing how insects sense and process information from their environment.

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