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: An influential article published in the International Journal of Energy Sector Management (Document ID: 122163) discusses strategies for reforming the power sector in Mexico while balancing environmental goals like climate change.

In recent scientific literature (December 2025), "122163" is the identifying number for a study titled Mixture design and machine learning-based optimization of fermentable sugar recovery. This research explores how to maximize bioethanol production from agricultural waste: 122163

: Researchers used Mixture Design Response Surface Methodology (MDRSM) and Artificial Neural Networks (ANN) to predict sugar yields. : An influential article published in the International

: Cellulose and starch content are the most critical factors influencing sugar recovery, while machine learning models help navigate the complex, non-linear relationships in these organic mixtures. 2. Public Policy and Government : Cellulose and starch content are the most

: On the platform Activelink , 122163 is the reference for a Call for Tender by the Bray & North Wicklow Area Partnership for the "F:ACES Initiative," seeking consultants for strategic work plans.