Vol. 9, Special Issue 1, Part K (2025)

AI/ML biochemistry in every digital-health biology

Author(s):

AI/ML biochemistry in every digital-health biology

Abstract:

This article communicates digital health biology that a very low digital CEC below 20 meq per 100 g Soil and low digital TDS below 100 ppm and low digital Turbidity as close as 0 ppm the best environment to every biology since metal ions bind very high-demanding Oxygen bio-molecules and make oxygen unavailable to the biology other than inhibiting every anabolic aquatic and terrestrial biology. Flowing rivers, and the river Ganges here are the major sources in aquatic biodiversity in India. Since river Flows and contents higher Dissolved Oxygen. Present communication dealt how Dissolved oxygen can be retained higher with lowering Turbidity in water or particles in water. In scientific evidence Turbidity can be lowered by our EEM environment editing model namely either lowering digital CEC or lowering total dissolved solids TDS.

This can be applied in any aquatic system where aquatic vegetation and terrestrial cropping system can reduce.

TDS and Turbidity in water environment. To maintain higher dissolved Oxygen. Present communication has been derived 11 statistical AI/ML algorithms to retain higher Dissolved Oxygen by lowering Turbidity i.e. minimising scattering of particulates in aquatic system river-flow, river currents, lowering digital cation exchange capacity CEC of sediments, or lowering TDS or may be with disease percentage zero Environment Editing Modelling DISPER EEM Inland Fisheries in the river banks aquatic environment to avoid not to bind plenty of Oxygen molecules with metals or CEC in aquatic environments so that living biodiversity namely Fisheries can prevail to purifying any aquatic eco-system better medium than any other in this unique water planet where similar principle is bitter applicable in digital Hydroponics etc.

Pages: 843-849  |  76 Views  16 Downloads

How to cite this article:
AI/ML biochemistry in every digital-health biology. AI/ML biochemistry in every digital-health biology. Int. J. Adv. Biochem. Res. 2025;9(1S):843-849. DOI: 10.33545/26174693.2025.v9.i1Sk.3619