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The evidence supports a compact accuracy–cost compromise for the tested conditions, while field robustness, energy use, repeated training runs, and target-device behavior remain open validation requirements.
By combining a formalized measure of epistemic integrity – via the Epistemic Integrity Index (EII) – with this normative framework, the paper bridges philosophy, ethics, and policy, offering a new model for understanding and regulating AI’s role in the epistemic dimension of modern conflict.
This study introduces an alignment-free computational framework for identifying microbial bioremediation potential, establishing a standardized, multi-domain dataset encompassing Bacteria, Protists, Archaea, and Fungi, and integrating metadata on polymer interactions to fill existing data gaps.
Results indicate that decentralized, interoperable, and energy-aware intrusion detection is feasible for large-scale IoT deployments, particularly in resource-constrained IoT environments.
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