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

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: This research explores how to maximize bioethanol production

The number also appears in various governmental and regulatory records: Professional Tenders and Contracts : Cellulose and starch

: A mixture of cassava, potato, and sweet potato peels.

: In administrative law, it is referenced in notices of approval (referencing Sections 122 and 163 of the Business and Professions Code) concerning fees for duplicate licensure certificates and CPA practice privileges. 3. Professional Tenders and Contracts

: 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