Development and application of an advanced algorithm for environmental risk assessment and safety management of pesticide residues in agricultural soils: Monitoring of currently used pesticide in upland soils.

This study conducted the development of an advanced risk assessment algorithm system and safety management strategies using pesticide residue monitoring data from soils. To understand the status of pesticide residues in agricultural soils, monitoring was performed on 116 types of pesticides currently in use across 300 soil sites. The analysis of the monitoring results, alongside the physicochemical properties of the pesticides, led to the selection of soil half-life as a critical component in residue analysis.

Opportunities and challenges of machine learning in bioprocesses: Categorization from different perspectives and future direction.

Recent advances in machine learning (ML) have revolutionized an extensive range of research and industry fields by successfully addressing intricate problems that cannot be resolved with conventional approaches. However, low interpretability and incompatibility make it challenging to apply ML to complicated bioprocesses, which rely on the delicate metabolic interplay among living cells. This overview attempts to delineate ML applications to bioprocess from different perspectives, and their inherent limitations (i.