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ZENODO
Doctoral thesis . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Thesis . 2025
License: CC BY
Data sources: Datacite
ZENODO
Thesis . 2025
License: CC BY
Data sources: Datacite
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The Entropy–Decay Framework in Biology: From Senses to Ecosystems and Beyond

Authors: TSANG, LOUIS HIN LOK; ChatGPT;

The Entropy–Decay Framework in Biology: From Senses to Ecosystems and Beyond

Abstract

This paper extends the entropy–decay framework, previously developed in physics and chemistry, into the domain of biology. It proposes that living systems can be understood as structured entropic architectures: senses as tuned receivers of propagating entropy, digestion as resonance-specific extraction of trapped entropy, and ecosystems as networks of irreversible circulation. Building on Schrödinger’s early vision of “negative entropy,” this work reinterprets perception, nutrition, and ecological balance as expressions of the same universal decay processes that govern matter and cosmology. While the framework remains at the stage of hypothesis — τ-resonance and entropic release profiles are not yet measurable — it outlines testable predictions in calorimetry, spectroscopy, and microbiome studies. The aim is not to claim a final theory, but to invite further exploration into whether biology, like physics and chemistry, may be unified under the irreversible propagation of entropy.

Keywords

Animal biology, Biology/methods, Soil biology, Entropy, Developmental biology, Synthetic Biology, Physical cosmology, Structural biology, Biology/standards, Biology, Theoretical physics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green