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The Descent of Ayurveda from Celestial to Earthly Manifestation: A Coherence-Based Research Framework Linking Physiology, Biofield Hypotheses, and Experimental Innovation

Hernandez, Anthony K. · Zenodo (CERN)
Zenodo (CERN) · Papers · License: Open Access
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#AyurvedaResearch #InterdisciplinaryResearchFramework, #AyurvedaScientificResearch

The Descent of Ayurveda from Celestial to Earthly Manifestation: A Coherence-Based Research Framework Linking Physiology, Biofield Hypotheses, and Experimental Innovation | Zenodo Skip to main Communities My dashboard Log in Sign up Published April 13, 2026 | Version v1 Conference paper Open The Descent of Ayurveda from Celestial to Earthly Manifestation: A Coherence-Based Research Framework Linking Physiology, Biofield Hypotheses, and Experimental Innovation Authors/Creators Hernandez, Anthony K. (Rights holder) Description This revised WAVES paper argues that the scientific value of Ayurveda’s descent model lies not in any immediate claim to final verification, but in its capacity to organize a layered research agenda.[1] That agenda begins with the recognition that coherence, regulation, and environmental sensitivity are legitimate scientific themes. It then asks whether candidate biological transduction pathways can help explain how subtle or coherence-oriented influences become measurable in living organisms.[1] The Tesla Bio-Med pilot study provides an initial empirical illustration of this strategy while also making clear that much stronger studies are still required.[3] The broader implication is that Ayurveda and Vedic science need not be presented to modern audiences as either untouchable spiritual truths or prematurely completed scientific theories. They can instead be presented as sources of deep conceptual guidance for disciplined inquiry. Files Consolidated WAVES 2026 Revised Research Paper_Framework for Descent of Ayurveda research.pdf Files (88.3 kB) Name Size Download all Consolidated WAVES 2026 Revised Research Paper_Framework for Descent of Ayurveda research.pdf md5:b068cf7b2426c01e3f1e4dd9c925a949 88.3 kB Preview Download Additional details Software Development Status Active 24 Views 10 Downloads Show more details All versions This version Views Total views 24 24 Downloads Total downloads 10 10 Data volume Total data volume 971.3 kB 971.3 kB More info on how stats are collected.... Versions External resources Indexed in OpenAIRE Communities Keywords and subjects Keywords #AyurvedaResearch #InterdisciplinaryResearchFramework #AyurvedaScientificResearch Details DOI DOI Badge DOI 10.5281/zenodo.19701715 Markdown [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.19701715.svg)](https://doi.org/10.5281/zenodo.19701715) reStructuredText .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.19701715.svg :target: https://doi.org/10.5281/zenodo.19701715 HTML <a href="https://doi.org/10.5281/zenodo.19701715"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.19701715.svg" alt="DOI"></a> Image URL https://zenodo.org/badge/DOI/10.5281/zenodo.19701715.svg Target URL https://doi.org/10.5281/zenodo.19701715 Resource type Conference paper Publisher Zenodo Conference World Association for Vedic Studies Conference-2026 (WAVES) , Maharishi International University, July 28- August 2, 2026 Languages English Rights License Creative Commons Attribution 4.0 International The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited. Read more Copyright ©2026, Inner WHealth Publishing™, Divine Health Institute™, Anthony K. Hernandez™, All Rights Reserved. Citation Export Technical metadata Created April 23, 2026 Modified April 23, 2026 Jump up About About Policies Infrastructure Principles Projects Roadmap Contact Blog Blog Support Help FAQ Developers REST API OAI-PMH Contribute GitHub Donate Funded by Powered by CERN Data Centre & InvenioRDM Status Privacy policy Cookie policy Terms of Use This site uses cookies. Find out more on how we use cookies Accept all cookies Accept only essential cookies

Record · ID 135263 · SHA-256 63d07196ac9cf31c
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