Risks and Mechanistic Insights Into Arsenic-Enhanced Iodination of Bisphenol F in Brassica Chinensis L.

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Towards the first principles of explaining DNNs: interactions explain the learning dynamics

Published On : 2025-10-17

In the field of explainable artificial intelligence (XAI), deep neural networks (DNNs) face a critical challenge: their superior performance in tasks like image classification and natural language processing is accompanied by opaque decision-making logic, especially in high-risk scenarios such as medical diagnosis and autonomous driving.

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Risks and Mechanistic Insights Into Arsenic-Enhanced Iodination of Bisphenol F in Brassica Chinensis L.

Published On : 2025-10-17

This study highlights the combined risks of arsenic and bisphenol contamination, revealing arsenic’s role in enhancing bisphenol iodination and toxicity in plants.

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