AN ARTIFICIAL INTELLIGENCE OPTIMIZATION OF NOX CONVERSION EFFICIENCY UNDER DUAL CATALYTIC MECHANISM REACTION BASED ON MULTI-OBJECTIVE GRAY WOLF ALGORITHM

In the era of industry 4.0, artificial intelligence (AI) offers new perspectives for researching the complex sustainable chemical reactions in selective catalytic reduction (SCR).This aims to further improve the utilization and efficiency of SCR.In this study, a fuzzy gray relational analysis coupled with random forest (RF) and back propagation art

Root hair size determines the surface area/volume ratio of the whole roots exposed to the nutrient and water pools, thereby likely impacting nutrient and water uptake rates.The speed at which they grow is determined both by cell-intrinsic factors like hormones (e.g., auxin) and external environmental signals like nutrient availability in the soil (

Serine(S)/threonine(T)-glutamine(Q) cluster domains (SCDs), polyglutamine (polyQ) tracts and polyglutamine/asparagine (polyQ/N) tracts are Q-rich motifs found in many proteins.SCDs often are intrinsically disordered regions that mediate protein phosphorylation and Mirror Brackets and Accessories (Specific to Truck) protein-protein interactions.Poly