Vol. 8, Issue 11, Part F (2024)

Digital Cation Exchange Capacity CEC in any Environment does matter everything in animal biochemistry that relates digitally. Not onlu animals in studies we found in plants as well any low CEC environments results tallness and high CEC results dwarfnes, applicable in both plants and animal science. All in avoiding environmental stresses, physiological needs or to avoid diseases animals are often needs to migrate based on environmental digital CEC values studied with AI/ML. In fisheries science all matured fish often to migrated in lowest digital CEC. All Digital biochemistry applicable among Fishs, Animals & Humans in mandatorily migrated not only to avoid diseases but every individual growth, reproduction, existence and all the best cup aspirants when if not naturally, it is with EEM, the EEM applicable to every animal and mankind. All this to the evolution in animal biology is saying that every non-occurring of diseases i.e. ‘disease percentage’ zero in any terrestrial or aquatic or aerial environments can be minimized to zero, with ‘EEM’ environmental editing model, we proposed. This generated with environmental data with machine Learning Techniques that living species often can migrates to remain disease less. This natural or virtual migrations are mandatory to avoid diseases. With example in fisheries water sediments with a higher digital Cation Excange Capacity, CEC digitally measurable, very much prone to every diseases. In contrast water sediments digitally with low CEC can be very hygienic to all the species, animals and mankind. This same phenomenal model can be universal and as applicable in animal husbandry and EEM mankind. In model we find that ‘Environment Editing’ viz. lowering the value of digital CEC can statistically be correlated with annual occurring of non-diseases, usually in the low CEC environments below 20 meq per 100 gram of sample. The machine learning model we find is Y= 0.182X, R2 =0.85 where Y the dependant variable, the percentage of annual occurring diseases caused by unicellular pathogens, significantly related with X, the independent variable digital CEC of environment. Hence we say lets every animal and mankind can be made disease-less in nature. The EEM i.e. eemodel is to avoid diseases, the rules with machine learning techniques with either human inputs or absolutely machine readable automation AI/ML. Scientific reasons of higher and highest digital CEC disease problems are due the fact that often many pathogens are elementary-chemophillie in nature when remains outside host and secondly, and other-side any animal and EEM mankind excepting earthworms and leaches etc are very highly enzyme inhibitions with higher or highest CEC metals and heavy metals persisting in higher or highest digital CEC environments. DISPER EEM A ZERO DISEASES of zero diseases may also possible with synthetic environment of Isoprene mediated environment in air, water or soil with Digital con 1 pbb or more.