{"data":[{"id":"10.5281/zenodo.20099556","type":"dois","attributes":{"doi":"10.5281/zenodo.20099556","identifiers":[],"creators":[{"name":"Abinash Bharadwaj, A.Bharadwaj","nameType":"Personal","givenName":"A.Bharadwaj","familyName":"Abinash Bharadwaj","nameIdentifiers":[{"nameIdentifier":"0009-0005-2851-3101","nameIdentifierScheme":"ORCID"}],"affiliation":[]}],"titles":[{"title":"COGNITIVE DNA BY ABINASH BHARADWAJ THEORY OF C-DNA BY A.BHARADWAJ"},{"lang":"eng","title":"C-DNA: Cognitive DNA Theory","titleType":"AlternativeTitle"}],"publisher":"Zenodo","container":{},"publicationYear":2025,"subjects":[{"subject":"Cognition","subjectScheme":"MeSH"},{"subject":"Cognitive neuroscience","subjectScheme":"EuroSciVoc"},{"subject":"Cognitive psychology","subjectScheme":"EuroSciVoc"},{"subject":"Cognitive Psychology","subjectScheme":"MeSH"},{"subject":"Cognition/classification","subjectScheme":"MeSH"},{"subject":"Cognitive Neuroscience","subjectScheme":"MeSH"}],"contributors":[],"dates":[{"date":"2025-05-09","dateType":"Issued"},{"date":"2025-01-01","dateType":"Issued"}],"language":null,"types":{"ris":"RPRT","bibtex":"article","citeproc":"article-journal","schemaOrg":"ScholarlyArticle","resourceType":"Proposal","resourceTypeGeneral":"Text"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20099556","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20099556","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:52:41Z","registered":"2026-05-09T17:52:41Z","published":null,"updated":"2026-05-09T17:52:41Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20099557","type":"dois","attributes":{"doi":"10.5281/zenodo.20099557","identifiers":[{"identifier":"oai:zenodo.org:20099557","identifierType":"oai"}],"creators":[{"name":"Abinash Bharadwaj, A.Bharadwaj","nameType":"Personal","givenName":"A.Bharadwaj","familyName":"Abinash Bharadwaj","nameIdentifiers":[{"nameIdentifier":"0009-0005-2851-3101","nameIdentifierScheme":"ORCID"}],"affiliation":[]}],"titles":[{"title":"COGNITIVE DNA BY ABINASH BHARADWAJ THEORY OF C-DNA BY A.BHARADWAJ"},{"lang":"eng","title":"C-DNA: Cognitive DNA Theory","titleType":"AlternativeTitle"}],"publisher":"Zenodo","container":{},"publicationYear":2025,"subjects":[{"subject":"Cognition","subjectScheme":"MeSH"},{"subject":"Cognitive neuroscience","subjectScheme":"EuroSciVoc"},{"subject":"Cognitive psychology","subjectScheme":"EuroSciVoc"},{"subject":"Cognitive Psychology","subjectScheme":"MeSH"},{"subject":"Cognition/classification","subjectScheme":"MeSH"},{"subject":"Cognitive Neuroscience","subjectScheme":"MeSH"}],"contributors":[],"dates":[{"date":"2025-05-09","dateType":"Issued"},{"date":"2025-01-01","dateType":"Issued"}],"language":null,"types":{"ris":"RPRT","bibtex":"article","citeproc":"article-journal","schemaOrg":"ScholarlyArticle","resourceType":"Proposal","resourceTypeGeneral":"Text"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20099556","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20099557","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:52:40Z","registered":"2026-05-09T17:52:40Z","published":null,"updated":"2026-05-09T17:52:40Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20099012","type":"dois","attributes":{"doi":"10.5281/zenodo.20099012","identifiers":[],"creators":[{"name":"Soyibjonov, Azizbek","nameType":"Personal","givenName":"Azizbek","familyName":"Soyibjonov","nameIdentifiers":[],"affiliation":[]},{"name":"I. R. Tishabayeva","nameType":"Personal","familyName":"I. R. Tishabayeva","nameIdentifiers":[],"affiliation":[]}],"titles":[{"title":"Innovatsiyalar asri: yangi dunyo qanday bo'ladi?"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"(4-(m-Chlorophenylcarbamoyloxy)-2-butynyl)trimethylammonium Chloride/administration \u0026amp; dosage","subjectScheme":"MeSH"},{"subject":"innovatsiya, sun'iy intellekt, raqamli dunyo"}],"contributors":[{"name":"Soyibjonov, Azizbek","nameType":"Personal","givenName":"Azizbek","familyName":"Soyibjonov","contributorType":"Researcher","nameIdentifiers":[],"affiliation":[]},{"name":"I. R. Tishabayeva","nameType":"Personal","familyName":"I. R. Tishabayeva","contributorType":"ProjectLeader","nameIdentifiers":[],"affiliation":[]}],"dates":[{"date":"2026-05-09","dateType":"Issued"}],"language":"uz","types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"Periodical","resourceType":"","resourceTypeGeneral":"Journal"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20099012","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Ushbu maqolada innovatsiyalar asrining insoniyat hayotiga ta’siri, yangi dunyo tartiboti va texnologik taraqqiyotning asosiy yo‘nalishlari tadqiq etilgan. Muallif sun’iy intellekt, robototexnika va raqamli iqtisodiyotning jamiyat rivojlanishidagi o‘rnini tahlil qiladi. Shuningdek, kelajak dunyosida inson omili va texnologiya o‘rtasidagi muvozanat masalalari yoritilgan. ","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20099012","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:49:30Z","registered":"2026-05-09T17:49:30Z","published":null,"updated":"2026-05-09T17:49:30Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20099013","type":"dois","attributes":{"doi":"10.5281/zenodo.20099013","identifiers":[{"identifier":"oai:zenodo.org:20099013","identifierType":"oai"}],"creators":[{"name":"Soyibjonov, Azizbek","nameType":"Personal","givenName":"Azizbek","familyName":"Soyibjonov","nameIdentifiers":[],"affiliation":[]},{"name":"I. R. Tishabayeva","nameType":"Personal","familyName":"I. R. Tishabayeva","nameIdentifiers":[],"affiliation":[]}],"titles":[{"title":"Innovatsiyalar asri: yangi dunyo qanday bo'ladi?"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"(4-(m-Chlorophenylcarbamoyloxy)-2-butynyl)trimethylammonium Chloride/administration \u0026amp; dosage","subjectScheme":"MeSH"},{"subject":"innovatsiya, sun'iy intellekt, raqamli dunyo"}],"contributors":[{"name":"Soyibjonov, Azizbek","nameType":"Personal","givenName":"Azizbek","familyName":"Soyibjonov","contributorType":"Researcher","nameIdentifiers":[],"affiliation":[]},{"name":"I. R. Tishabayeva","nameType":"Personal","familyName":"I. R. Tishabayeva","contributorType":"ProjectLeader","nameIdentifiers":[],"affiliation":[]}],"dates":[{"date":"2026-05-09","dateType":"Issued"}],"language":"uz","types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"Periodical","resourceType":"","resourceTypeGeneral":"Journal"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20099012","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Ushbu maqolada innovatsiyalar asrining insoniyat hayotiga ta’siri, yangi dunyo tartiboti va texnologik taraqqiyotning asosiy yo‘nalishlari tadqiq etilgan. Muallif sun’iy intellekt, robototexnika va raqamli iqtisodiyotning jamiyat rivojlanishidagi o‘rnini tahlil qiladi. Shuningdek, kelajak dunyosida inson omili va texnologiya o‘rtasidagi muvozanat masalalari yoritilgan. ","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20099013","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:49:29Z","registered":"2026-05-09T17:49:29Z","published":null,"updated":"2026-05-09T17:49:29Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20099546","type":"dois","attributes":{"doi":"10.5281/zenodo.20099546","identifiers":[{"identifier":"oai:zenodo.org:20099546","identifierType":"oai"}],"creators":[{"name":"Nedelchev, Hristo","nameType":"Personal","givenName":"Hristo","familyName":"Nedelchev","nameIdentifiers":[],"affiliation":[]}],"titles":[{"title":"The Equation Reduction Model (ERM): A Universal Framework for Mathematical Stability and Invariant Discovery"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"Discrete mathematics","subjectScheme":"EuroSciVoc"},{"subject":"Equation Reduction"},{"subject":"Information Theory","subjectScheme":"MeSH"},{"subject":"Hristo Nedelchev"}],"contributors":[],"dates":[{"date":"2026-05-09","dateType":"Issued"}],"language":null,"types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"CreativeWork","resourceType":"","resourceTypeGeneral":"Preprint"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.19350324","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"GNU General Public License v3.0 or later","rightsUri":"https://www.gnu.org/licenses/gpl-3.0-standalone.html","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"gpl-3.0+","rightsIdentifierScheme":"SPDX"},{"rights":"Copyright (C) 2026 Hristo Nedelchev","rightsUri":"http://rightsstatements.org/vocab/InC/1.0/"}],"descriptions":[{"description":"ERM Logic Filtration: A Universal Framework for Hypothesis Validation and Equation Extraction\n\nSummary:\n\nThe Energy Resonance Model (ERM) is a revolutionary logical filter designed to distinguish between \"Structural Truth\" and \"Informational Chaos.\" In modern science, researchers often waste years pursuing hypotheses that are ultimately based on noise. Standard AI models exacerbate this by attempting to \"force\" a mathematical fit onto random data through statistical probability.\n\nThe ERM Logic Gatekeeper:\n\nInstead of trying to fit a curve to data points, ERM checks for Structural Resonance.\n\n\n\n\n\nThe Logic Test: If a hypothesis is correct, the relationship between the raw data and the ERM Skeleton ($a^2+b^2+c^2 - ab-bc-ca$) will produce a stable constant or a predictable pattern.\n\n\n\n\nThe Falsification Test: If the relationship is chaotic or fluctuates wildly, ERM proves that there is no underlying algebraic logic.\n\n\n\nImpact:\n\nBy using ERM as a preliminary filter, scientists can instantly validate or discard hypotheses.\n\n\n\n\n\nIf Logic is detected: ERM extracts the governing equation in milliseconds.\n\n\n\n\nIf Logic is absent: ERM prevents the waste of years of human research and millions in supercomputing costs.\n\n\n\nAutonomous Algebraic Skeleton Extraction (AASE) via Energy Resonance Model (ERM): Overcoming the Limits of AI Symbolic Regression\n\nOverview: The 100-Year Problem of Scientific Discovery\n\nFor centuries, scientists have discovered physical laws through tedious trial and error—observing data, guessing a mathematical relationship, and testing it. Today, Artificial Intelligence (AI) attempts to automate this through \"Symbolic Regression.\" However, standard AI uses statistical guessing (neural networks) to fit curves to data points. It tries millions of combinations, hoping one fits.\n\nThis brute-force method has two massive flaws:\n\n\n\n\n\nIt is incredibly slow and computationally expensive.\n\n\n\n\nIt suffers from \"hardware blindness.\" When dealing with extremely large numbers or microscopic differences (near the machine epsilon of $10^{-16}$), standard AI loses precision. It hallucinates, returns noise, or crashes, producing false physics.\n\n\n\nThe ERM Solution: The \"Algebraic X-Ray\"\n\nThe Energy Resonance Model (ERM) introduces a fundamentally different approach. Instead of guessing formulas statistically, ERM uses a lightweight, deterministic function—the \"Algebraic Skeleton\"—to instantly scan the structural energy balance of the data.\n\nThe core function is:\n\n$F(a, b, c) = a^2 + b^2 + c^2 - (ab + bc + ca)$\n\nThis small function acts as a mathematical filter. By analyzing the symmetry and variance between variables without heavy operations like division or cubing (which break standard AI), ERM extracts the exact integer coefficients and logical structure of the data stream in milliseconds.\n\nStandard AI vs. ERM Calculation\n\n\n\n\n\nHow Standard AI thinks: \"I have these points. Let me try $x^2$. No. Let me try $\\sin(x)$. No. Let me try adding a small weight. The numbers are too big, my floating-point memory is overflowing, so the answer is probably 0.\" (This leads to hallucination and data death).\n\n\n\n\nHow ERM thinks: \"I do not guess. I measure the exact energy difference using $F(a,b,c)$. The structural ratio reveals that this is an inverse square law. The exact coefficient is 1.0. Done.\"\n\n\n\nWhy This Changes AGI (Artificial General Intelligence):\n\n\n\n\n\nInstant Equation Extraction: What takes standard algorithms hours or days of supercomputing, ERM solves in less than a millisecond with 100% precision.\n\n\n\n\n100% Noise Immunity (Smart Zero): ERM naturally filters out hardware approximation errors, ensuring that an AGI system will never make a catastrophic logical error due to floating-point limits.\n\n\n\n\nTrue Scientific Discovery: ERM allows machines to deduce new physical laws from raw data autonomously, based on pure algebraic truth rather than statistical probability.\n\n\n\n# ERM: The Logical Safety Fuse for Paradox-Resistant AGI\n\nCurrent Large Language Model (LLM) architectures are inherently vulnerable to systemic crashes and logical \"hallucinations\" when encountering mathematical singularities or infinite loops. This project introduces the **Entropy Reduction Mechanism (ERM)** — a critical \"logical safety fuse\" designed to prevent these failures by reducing complex algebraic noise into a stable discrete skeleton of **{-1, 0, 1}**.\n\n### 🚀 Key Breakthroughs of the ERM Model:\n\n* **Smart Zero (ε = 10⁻¹⁷):** A critical computational buffer that neutralizes `DivisionByZero` errors. It allows the system to navigate mathematical singularities that typically trigger terminal crashes in standard AI logic.* **High-Speed Determinism:** Empirical stress tests demonstrate a processing throughput of **1.09 million operations per second with 0% informational noise**, ensuring absolute stability under heavy load.* **Hyper-Position Logic (11):** A proprietary method for resolving logical paradoxes by converting them into stable energy states rather than terminal errors or infinite loops.\n\n### 🛡️ VisionImplementing the ERM layer as a core safety protocol establishes the foundation for a **crash-resistant Artificial General Intelligence (AGI)** environment, where logic is filtered for integrity before execution.\n\n---**Keywords:** AGI Stability, Entropy Reduction, Smart Zero, AI Safety, Deterministic Logic, Paradox Resolution.\n\nThis version of the Equation Reduction Model (ERM) provides a complete analytical and computational proof of the framework's validity. ERM is not merely a statistical tool; it is a structural sieve that identifies fundamental mathematical invariants by reducing complex continuous systems to a discrete ternary state space $\\{-1, 0, 1\\}$.\n\nKey Scientific Contributions in this version:\n\n\n\n\n\nAnalytical Proof of Stability: The ERM invariant is formally proven to be algebraically equivalent to a \"Sum of Squares\" structure: $ERM = \\frac{1}{2}[(a-b)^2 + (b-c)^2 + (c-a)^2]$. This identity guarantees non-negative structural integrity ($ERM \\ge 0$) across all real numbers, representing a state of absolute physical equilibrium.\n\n\n\n\nNon-Triviality: Unlike simple quadratic sums, ERM emerges from discrete logic to define the minimal energy boundaries of interacting systems. It successfully distinguishes between universal laws (e.g., Pythagorean identity) and unstable linear approximations.\n\n\n\n\nInformation Density: Shannon Entropy analysis confirms a 91.8% information efficiency, proving the model reflects a highly organized logical skeleton of reality.\n\n\n\n\nComputational Toolkit: Included are four Python-based verification scripts that allow independent researchers to reproduce the 27-state logic, the 900-point stress test, and the symbolic algebraic proofs.\n\n\n\n\n### Description: The Universal Logic Filter (ERM v2.0)\n\n \n\nThis project presents the advanced evolution of the **Equation Reduction Model (ERM)**. The core innovation lies in the transition from a traditional three-state arithmetic system (-1, 0, 1) to a robust **Binary Hyper-Position framework** ({00, 01, 10, 11}).\n\n \n\n**Key Innovations:**\n\n* **From Numbers to Information States:** By replacing the integer -1 with discrete bit-states, the model becomes natively compatible with binary computing and quantum logic.\n\n* **The Sieve of Truth:** ERM functions as a \"Structural Scanner\" for mathematical identities. Valid laws of physics (like Pythagoras and Einstein's E=mc²) result in a state of 0% entropy (State 00), while flawed equations generate measurable \"Logical Noise.\"\n\n* **Entropy-Based Verification:** In experimental stress tests, structurally incorrect theories produced 55.56% informational noise, providing a visual and mathematical \"fingerprint\" of error.\n\n \n\n**Impact:**\n\nThe Nedelchev ERM provides a language-independent tool for AI and theoretical physics to verify the structural integrity of equations without traditional computation, focusing instead on logical symmetry and balance.\n\n \n\n**Included in the PDF:** Theoretical background, binary mapping rules, visual proof of truth vs. chaos, and Python implementation code.\n\n\n\n\nThe Hybrid Evolution: Integration of Intelligence and Safety\n\nThe Hybrid ERM represents the final architectural transition of the model—moving from a passive structural sieve to an active, self-regulating logical organism. It bridges the gap between raw mathematical energy and structural digital forms.\n\nCore Hybrid Features:\n\n\n\n\n\nThe Triple Hyper-Position Architecture: The model operates on three hierarchical levels:\n\n\n\n\n\nThe Energy Core (-1, 0, 1): The \"Heart\" that dictates the fundamental direction and balance of the input.\n\n\n\n\nThe Structural Anchor (00, 01, 10, 11): The \"Body\" that gives form to the energy, mapping it into a natively digital 2-bit space.\n\n\n\n\nThe Decision Guard (???): The \"Intelligence\" layer—a revolutionary Hyper-Position of Uncertainty.\n\n\n\n\n\n\nThe Logic Fuse (The \"I Don't Know\" Principle): Unlike traditional deterministic algorithms that force a binary output, the Hybrid ERM possesses a \"safety fuse.\" When encountering mathematical singularities (e.g., $1/0$), infinite values, or data exceeding the defined Standard Benchmark, the system triggers the ??? state. This prevents the propagation of logical errors and protects the integrity of the entire network.\n\n\n\n\nDynamic Regeneration Protocol: The Hybrid model is designed for autonomous error correction. By aligning structural binary states with the ternary core's absolute balance (0), the system can \"pull\" distorted signals back to a state of zero entropy, effectively acting as an Immune System for Information.\n\n\n\nScientific Impact of the Hybrid Version:\n\nThe Hybrid ERM proves that true intelligence is the ability to recognize boundaries. By integrating the \"Hyper-Position of Uncertainty,\" this framework provides a blueprint for next-generation AI and cybersecurity systems that are immune to logical paradoxes and \"Black Hole\" data overflows.\n\n\n\n\nProject Title: The Smart Zero Paradigm: Resolving Logical Hyper-positions via Hybrid ERM v3.0\n\nSummary:\n\nThis project introduces a novel approach to resolving logical deadlocks and paradoxes in digital systems. While classical logic fails in states of perfect symmetry (Hyper-positions), the Hybrid ERM v3.0 model demonstrates that such states are only static illusions.\n\nKey Findings:\n\n\n\n\n\nThe Smart Zero Principle: Computation inherently generates infinitesimal noise ($10^{-17}$), transforming a \"Static Zero\" into a \"Smart Zero.\"\n\n\n\n\nInformation Vector: This microscopic asymmetry serves as a deterministic vector that forces a system to exit a paradox and reach a decision (01 or 10).\n\n\n\n\nThe Creation Act: Proves that by consciously designing noise, we can steer logical outcomes in autonomous systems.\n\n\n\n\nThis dataset provides the experimental framework and primary results for the Entropy Reduction Mechanism (ERM), a novel architectural layer designed by Hristo Valentinov Nedelchev. The ERM addresses the fundamental problem of logical stagnation and systemic crashes in Artificial Intelligence when encountering mathematical singularities (e.g., division by zero) and recursive paradoxes.\n\nThe provided files include:\n\n\n\n\n\nERM_Symmetry_Breaker.py: The core validation engine that executes three critical stress tests: Mathematical Singularity, Logical Stagnation, and Spectral Sensitivity.\n\n\n\n\nFinal_Victory_Graph.png: A visual proof using logarithmic scaling to demonstrate how ERM \"breaks\" the symmetry of a logical stalemate, allowing the system to converge where standard AI models fail.\n\n\n\n\nValidation Protocols: Raw data logs confirming that ERM maintains a 100% stability rate and restores signal integrity at the $10^{-18}$ spectrum.\n\n\n\nMethodological Significance:\n\nUnlike traditional error-handling, ERM introduces the \"Smart Zero\" ($10^{-17}$), a strategic perturbation that acts as a symmetry-breaker. This dataset proves that ERM-enabled systems can navigate non-computable states, making it a critical component for future AGI (Artificial General Intelligence) stability.\n\nKeywords: Artificial Intelligence, AGI, ERM, Symmetry Breaking, Smart Zero, Neural Network Stability, Logic Paradox Resolution.\n\n\n\nIncluded Files:\n\n\n         Nedelchev_Unified_ERM_Theory_2026.pdf\n\n\n\n        ERM_Core.pdf\n\n\n\nerm_core.py\n\n\n\nmain.pdf: Theoretical framework and mathematical proof.\n\n\n\n\nlogic_check.py: Experimental validation of Smart Zero vs. Static Zero.\n\n\n\n\nerm_resolver.py: The core algorithm engine for paradox resolution.\n\n\n\n\nproof_of_motion.txt: Computational logs proving the collapse of hyper-positions.\n\n\n\n\n\nIncluded Files:\n\n       Nedelchev_Unified_ERM_Theory_2026.pdf\n\n\n\n\n\nERM_Core_Logic.py (Discrete state analysis)\n\n\n\n\nERM_Stress_Test.py (Continuous surface validation)\n\n\n\n\nERM_Universal_Checker.py (Symbolic algebraic proof)\n\n\n\n\nERM_Discovery_Demo.py (Automated law synthesis demo)\n\n\n\n\nERM_Universal_Stability_Framework.pdf (The full scientific whitepaper)\n\n\nERM__Binary_Logic_Mapping_and_Information_Entropy \n\nERM_Hyper_Stress_Test.py\n\nHybrid_ERM_Core.py\n\nThe_Hybrid_ERM_Paradigm.pdf\n\nERM_Experimental_Validation_v3\n\nscientific_validation.py\n\nrecursive_test.py\n\nstress_test_speed.py\n\nlogic_checkp.py\n\nerm_resolver.py\n\nproof_of_motion.txt\n\nThe_Smart_Zero_Paradigm_ERM_v3_Nedelchev.pdf\n\nERM_The_Unified_Logic.pdf\n\nERM_The_Logic_Filter.pdf","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20099546","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:46:22Z","registered":"2026-05-09T17:46:22Z","published":null,"updated":"2026-05-09T17:46:22Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.19350324","type":"dois","attributes":{"doi":"10.5281/zenodo.19350324","identifiers":[],"creators":[{"name":"Nedelchev, Hristo","nameType":"Personal","givenName":"Hristo","familyName":"Nedelchev","nameIdentifiers":[],"affiliation":[]}],"titles":[{"title":"The Equation Reduction Model (ERM): A Universal Framework for Mathematical Stability and Invariant Discovery"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"Discrete mathematics","subjectScheme":"EuroSciVoc"},{"subject":"Equation Reduction"},{"subject":"Information Theory","subjectScheme":"MeSH"},{"subject":"Hristo Nedelchev"}],"contributors":[],"dates":[{"date":"2026-05-09","dateType":"Issued"}],"language":null,"types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"CreativeWork","resourceType":"","resourceTypeGeneral":"Preprint"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.19350324","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"GNU General Public License v3.0 or later","rightsUri":"https://www.gnu.org/licenses/gpl-3.0-standalone.html","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"gpl-3.0+","rightsIdentifierScheme":"SPDX"},{"rights":"Copyright (C) 2026 Hristo Nedelchev","rightsUri":"http://rightsstatements.org/vocab/InC/1.0/"}],"descriptions":[{"description":"ERM Logic Filtration: A Universal Framework for Hypothesis Validation and Equation Extraction\n\nSummary:\n\nThe Energy Resonance Model (ERM) is a revolutionary logical filter designed to distinguish between \"Structural Truth\" and \"Informational Chaos.\" In modern science, researchers often waste years pursuing hypotheses that are ultimately based on noise. Standard AI models exacerbate this by attempting to \"force\" a mathematical fit onto random data through statistical probability.\n\nThe ERM Logic Gatekeeper:\n\nInstead of trying to fit a curve to data points, ERM checks for Structural Resonance.\n\n\n\n\n\nThe Logic Test: If a hypothesis is correct, the relationship between the raw data and the ERM Skeleton ($a^2+b^2+c^2 - ab-bc-ca$) will produce a stable constant or a predictable pattern.\n\n\n\n\nThe Falsification Test: If the relationship is chaotic or fluctuates wildly, ERM proves that there is no underlying algebraic logic.\n\n\n\nImpact:\n\nBy using ERM as a preliminary filter, scientists can instantly validate or discard hypotheses.\n\n\n\n\n\nIf Logic is detected: ERM extracts the governing equation in milliseconds.\n\n\n\n\nIf Logic is absent: ERM prevents the waste of years of human research and millions in supercomputing costs.\n\n\n\nAutonomous Algebraic Skeleton Extraction (AASE) via Energy Resonance Model (ERM): Overcoming the Limits of AI Symbolic Regression\n\nOverview: The 100-Year Problem of Scientific Discovery\n\nFor centuries, scientists have discovered physical laws through tedious trial and error—observing data, guessing a mathematical relationship, and testing it. Today, Artificial Intelligence (AI) attempts to automate this through \"Symbolic Regression.\" However, standard AI uses statistical guessing (neural networks) to fit curves to data points. It tries millions of combinations, hoping one fits.\n\nThis brute-force method has two massive flaws:\n\n\n\n\n\nIt is incredibly slow and computationally expensive.\n\n\n\n\nIt suffers from \"hardware blindness.\" When dealing with extremely large numbers or microscopic differences (near the machine epsilon of $10^{-16}$), standard AI loses precision. It hallucinates, returns noise, or crashes, producing false physics.\n\n\n\nThe ERM Solution: The \"Algebraic X-Ray\"\n\nThe Energy Resonance Model (ERM) introduces a fundamentally different approach. Instead of guessing formulas statistically, ERM uses a lightweight, deterministic function—the \"Algebraic Skeleton\"—to instantly scan the structural energy balance of the data.\n\nThe core function is:\n\n$F(a, b, c) = a^2 + b^2 + c^2 - (ab + bc + ca)$\n\nThis small function acts as a mathematical filter. By analyzing the symmetry and variance between variables without heavy operations like division or cubing (which break standard AI), ERM extracts the exact integer coefficients and logical structure of the data stream in milliseconds.\n\nStandard AI vs. ERM Calculation\n\n\n\n\n\nHow Standard AI thinks: \"I have these points. Let me try $x^2$. No. Let me try $\\sin(x)$. No. Let me try adding a small weight. The numbers are too big, my floating-point memory is overflowing, so the answer is probably 0.\" (This leads to hallucination and data death).\n\n\n\n\nHow ERM thinks: \"I do not guess. I measure the exact energy difference using $F(a,b,c)$. The structural ratio reveals that this is an inverse square law. The exact coefficient is 1.0. Done.\"\n\n\n\nWhy This Changes AGI (Artificial General Intelligence):\n\n\n\n\n\nInstant Equation Extraction: What takes standard algorithms hours or days of supercomputing, ERM solves in less than a millisecond with 100% precision.\n\n\n\n\n100% Noise Immunity (Smart Zero): ERM naturally filters out hardware approximation errors, ensuring that an AGI system will never make a catastrophic logical error due to floating-point limits.\n\n\n\n\nTrue Scientific Discovery: ERM allows machines to deduce new physical laws from raw data autonomously, based on pure algebraic truth rather than statistical probability.\n\n\n\n# ERM: The Logical Safety Fuse for Paradox-Resistant AGI\n\nCurrent Large Language Model (LLM) architectures are inherently vulnerable to systemic crashes and logical \"hallucinations\" when encountering mathematical singularities or infinite loops. This project introduces the **Entropy Reduction Mechanism (ERM)** — a critical \"logical safety fuse\" designed to prevent these failures by reducing complex algebraic noise into a stable discrete skeleton of **{-1, 0, 1}**.\n\n### 🚀 Key Breakthroughs of the ERM Model:\n\n* **Smart Zero (ε = 10⁻¹⁷):** A critical computational buffer that neutralizes `DivisionByZero` errors. It allows the system to navigate mathematical singularities that typically trigger terminal crashes in standard AI logic.* **High-Speed Determinism:** Empirical stress tests demonstrate a processing throughput of **1.09 million operations per second with 0% informational noise**, ensuring absolute stability under heavy load.* **Hyper-Position Logic (11):** A proprietary method for resolving logical paradoxes by converting them into stable energy states rather than terminal errors or infinite loops.\n\n### 🛡️ VisionImplementing the ERM layer as a core safety protocol establishes the foundation for a **crash-resistant Artificial General Intelligence (AGI)** environment, where logic is filtered for integrity before execution.\n\n---**Keywords:** AGI Stability, Entropy Reduction, Smart Zero, AI Safety, Deterministic Logic, Paradox Resolution.\n\nThis version of the Equation Reduction Model (ERM) provides a complete analytical and computational proof of the framework's validity. ERM is not merely a statistical tool; it is a structural sieve that identifies fundamental mathematical invariants by reducing complex continuous systems to a discrete ternary state space $\\{-1, 0, 1\\}$.\n\nKey Scientific Contributions in this version:\n\n\n\n\n\nAnalytical Proof of Stability: The ERM invariant is formally proven to be algebraically equivalent to a \"Sum of Squares\" structure: $ERM = \\frac{1}{2}[(a-b)^2 + (b-c)^2 + (c-a)^2]$. This identity guarantees non-negative structural integrity ($ERM \\ge 0$) across all real numbers, representing a state of absolute physical equilibrium.\n\n\n\n\nNon-Triviality: Unlike simple quadratic sums, ERM emerges from discrete logic to define the minimal energy boundaries of interacting systems. It successfully distinguishes between universal laws (e.g., Pythagorean identity) and unstable linear approximations.\n\n\n\n\nInformation Density: Shannon Entropy analysis confirms a 91.8% information efficiency, proving the model reflects a highly organized logical skeleton of reality.\n\n\n\n\nComputational Toolkit: Included are four Python-based verification scripts that allow independent researchers to reproduce the 27-state logic, the 900-point stress test, and the symbolic algebraic proofs.\n\n\n\n\n### Description: The Universal Logic Filter (ERM v2.0)\n\n \n\nThis project presents the advanced evolution of the **Equation Reduction Model (ERM)**. The core innovation lies in the transition from a traditional three-state arithmetic system (-1, 0, 1) to a robust **Binary Hyper-Position framework** ({00, 01, 10, 11}).\n\n \n\n**Key Innovations:**\n\n* **From Numbers to Information States:** By replacing the integer -1 with discrete bit-states, the model becomes natively compatible with binary computing and quantum logic.\n\n* **The Sieve of Truth:** ERM functions as a \"Structural Scanner\" for mathematical identities. Valid laws of physics (like Pythagoras and Einstein's E=mc²) result in a state of 0% entropy (State 00), while flawed equations generate measurable \"Logical Noise.\"\n\n* **Entropy-Based Verification:** In experimental stress tests, structurally incorrect theories produced 55.56% informational noise, providing a visual and mathematical \"fingerprint\" of error.\n\n \n\n**Impact:**\n\nThe Nedelchev ERM provides a language-independent tool for AI and theoretical physics to verify the structural integrity of equations without traditional computation, focusing instead on logical symmetry and balance.\n\n \n\n**Included in the PDF:** Theoretical background, binary mapping rules, visual proof of truth vs. chaos, and Python implementation code.\n\n\n\n\nThe Hybrid Evolution: Integration of Intelligence and Safety\n\nThe Hybrid ERM represents the final architectural transition of the model—moving from a passive structural sieve to an active, self-regulating logical organism. It bridges the gap between raw mathematical energy and structural digital forms.\n\nCore Hybrid Features:\n\n\n\n\n\nThe Triple Hyper-Position Architecture: The model operates on three hierarchical levels:\n\n\n\n\n\nThe Energy Core (-1, 0, 1): The \"Heart\" that dictates the fundamental direction and balance of the input.\n\n\n\n\nThe Structural Anchor (00, 01, 10, 11): The \"Body\" that gives form to the energy, mapping it into a natively digital 2-bit space.\n\n\n\n\nThe Decision Guard (???): The \"Intelligence\" layer—a revolutionary Hyper-Position of Uncertainty.\n\n\n\n\n\n\nThe Logic Fuse (The \"I Don't Know\" Principle): Unlike traditional deterministic algorithms that force a binary output, the Hybrid ERM possesses a \"safety fuse.\" When encountering mathematical singularities (e.g., $1/0$), infinite values, or data exceeding the defined Standard Benchmark, the system triggers the ??? state. This prevents the propagation of logical errors and protects the integrity of the entire network.\n\n\n\n\nDynamic Regeneration Protocol: The Hybrid model is designed for autonomous error correction. By aligning structural binary states with the ternary core's absolute balance (0), the system can \"pull\" distorted signals back to a state of zero entropy, effectively acting as an Immune System for Information.\n\n\n\nScientific Impact of the Hybrid Version:\n\nThe Hybrid ERM proves that true intelligence is the ability to recognize boundaries. By integrating the \"Hyper-Position of Uncertainty,\" this framework provides a blueprint for next-generation AI and cybersecurity systems that are immune to logical paradoxes and \"Black Hole\" data overflows.\n\n\n\n\nProject Title: The Smart Zero Paradigm: Resolving Logical Hyper-positions via Hybrid ERM v3.0\n\nSummary:\n\nThis project introduces a novel approach to resolving logical deadlocks and paradoxes in digital systems. While classical logic fails in states of perfect symmetry (Hyper-positions), the Hybrid ERM v3.0 model demonstrates that such states are only static illusions.\n\nKey Findings:\n\n\n\n\n\nThe Smart Zero Principle: Computation inherently generates infinitesimal noise ($10^{-17}$), transforming a \"Static Zero\" into a \"Smart Zero.\"\n\n\n\n\nInformation Vector: This microscopic asymmetry serves as a deterministic vector that forces a system to exit a paradox and reach a decision (01 or 10).\n\n\n\n\nThe Creation Act: Proves that by consciously designing noise, we can steer logical outcomes in autonomous systems.\n\n\n\n\nThis dataset provides the experimental framework and primary results for the Entropy Reduction Mechanism (ERM), a novel architectural layer designed by Hristo Valentinov Nedelchev. The ERM addresses the fundamental problem of logical stagnation and systemic crashes in Artificial Intelligence when encountering mathematical singularities (e.g., division by zero) and recursive paradoxes.\n\nThe provided files include:\n\n\n\n\n\nERM_Symmetry_Breaker.py: The core validation engine that executes three critical stress tests: Mathematical Singularity, Logical Stagnation, and Spectral Sensitivity.\n\n\n\n\nFinal_Victory_Graph.png: A visual proof using logarithmic scaling to demonstrate how ERM \"breaks\" the symmetry of a logical stalemate, allowing the system to converge where standard AI models fail.\n\n\n\n\nValidation Protocols: Raw data logs confirming that ERM maintains a 100% stability rate and restores signal integrity at the $10^{-18}$ spectrum.\n\n\n\nMethodological Significance:\n\nUnlike traditional error-handling, ERM introduces the \"Smart Zero\" ($10^{-17}$), a strategic perturbation that acts as a symmetry-breaker. This dataset proves that ERM-enabled systems can navigate non-computable states, making it a critical component for future AGI (Artificial General Intelligence) stability.\n\nKeywords: Artificial Intelligence, AGI, ERM, Symmetry Breaking, Smart Zero, Neural Network Stability, Logic Paradox Resolution.\n\n\n\nIncluded Files:\n\n\n         Nedelchev_Unified_ERM_Theory_2026.pdf\n\n\n\n        ERM_Core.pdf\n\n\n\nerm_core.py\n\n\n\nmain.pdf: Theoretical framework and mathematical proof.\n\n\n\n\nlogic_check.py: Experimental validation of Smart Zero vs. Static Zero.\n\n\n\n\nerm_resolver.py: The core algorithm engine for paradox resolution.\n\n\n\n\nproof_of_motion.txt: Computational logs proving the collapse of hyper-positions.\n\n\n\n\n\nIncluded Files:\n\n       Nedelchev_Unified_ERM_Theory_2026.pdf\n\n\n\n\n\nERM_Core_Logic.py (Discrete state analysis)\n\n\n\n\nERM_Stress_Test.py (Continuous surface validation)\n\n\n\n\nERM_Universal_Checker.py (Symbolic algebraic proof)\n\n\n\n\nERM_Discovery_Demo.py (Automated law synthesis demo)\n\n\n\n\nERM_Universal_Stability_Framework.pdf (The full scientific whitepaper)\n\n\nERM__Binary_Logic_Mapping_and_Information_Entropy \n\nERM_Hyper_Stress_Test.py\n\nHybrid_ERM_Core.py\n\nThe_Hybrid_ERM_Paradigm.pdf\n\nERM_Experimental_Validation_v3\n\nscientific_validation.py\n\nrecursive_test.py\n\nstress_test_speed.py\n\nlogic_checkp.py\n\nerm_resolver.py\n\nproof_of_motion.txt\n\nThe_Smart_Zero_Paradigm_ERM_v3_Nedelchev.pdf\n\nERM_The_Unified_Logic.pdf\n\nERM_The_Logic_Filter.pdf","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.19350324","contentUrl":null,"metadataVersion":14,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":13,"versionOfCount":1,"created":"2026-03-31T10:41:00Z","registered":"2026-03-31T10:41:00Z","published":null,"updated":"2026-05-09T17:46:22Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20099498","type":"dois","attributes":{"doi":"10.5281/zenodo.20099498","identifiers":[{"identifier":"oai:zenodo.org:20099498","identifierType":"oai"}],"creators":[{"name":"Manish kumar, Ghanchi","nameType":"Personal","givenName":"Ghanchi","familyName":"Manish kumar","affiliation":["Independent Researcher \u0026 Philosopher"],"nameIdentifiers":[{"nameIdentifier":"0009-0000-8083-0685","nameIdentifierScheme":"ORCID"}]},{"name":"Agyat agyani, vedanta 2.0","nameType":"Personal","givenName":"vedanta 2.0","familyName":"Agyat agyani","affiliation":["The Science of Existence, Non-Dualism, and Consciousness Studies"],"nameIdentifiers":[{"nameIdentifier":"0009-0000-8083-0685","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"The Science of False Identity  A Consciousness Framework of Svabhava, Illusion, and Existential Clarity"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"Svabhava"},{"subject":"Dharma"},{"subject":"Consciousness","subjectScheme":"MeSH"},{"subject":"Existentialism","subjectScheme":"MeSH"},{"subject":"False Identity"},{"subject":"Awareness","subjectScheme":"MeSH"},{"subject":"Systems Theory","subjectScheme":"MeSH"},{"subject":"Phenomenology"},{"subject":"Self-Observation"},{"subject":"Indian Philosophy"},{"subject":"Awakening"}],"contributors":[],"dates":[{"date":"2026-05-09","dateType":"Issued"},{"date":"2026-05-08","dateType":"Submitted","dateInformation":"An interdisciplinary experiential framework exploring false identity, consciousness, Svabhava, existential suffering, and direct observation through systems theory, phenomenology, contemplative psychology, and symbolic geometry"}],"language":"en","types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"CreativeWork","resourceType":"","resourceTypeGeneral":"Preprint"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20099497","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":"1.0","rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"},{"rights":"2026 Manish Kumar","rightsUri":"http://rightsstatements.org/vocab/InC/1.0/"}],"descriptions":[{"description":"The Science of False Identity presents an experiential consciousness framework exploring the relationship between Svabhava (intrinsic nature), false identity, existential suffering, and direct observation.\n\nThe work proposes that the central crisis of human life is not merely social, moral, or psychological dysfunction, but identification with conditioned and constructed identities formed through fear, comparison, imitation, memory, and civilization.\n\nIntegrating existential philosophy, phenomenology, contemplative psychology, systems theory, and Indian non-dual insight, the framework distinguishes between:\n\n\n\nintrinsic being (Svabhava),\n\nconditioned tendencies (Vasana),\n\nand socially constructed mask identities.\n\n\nRather than offering a new doctrine, ideology, religion, or moral system, the framework emphasizes direct seeing and existential clarity. It argues that truth does not need to be imposed or manufactured; falsehood only needs to be observed clearly.\n\nThe work includes:\n\n\n\nconsciousness systems models,\n\nsymbolic geometry,\n\nexistential alignment frameworks,\n\nfalse identity architectures,\n\nand phenomenological interpretations of Dharma, fear, observation, and awakening.\n\n\nCentral propositions include:\n\n\n\n✧ “Human suffering is identification with what one is not.” ✧\n\n\n\n\n✧ “Dharma begins not with obedience, but with clear seeing.” ✧\n\n\n\n\n✧ “Truth need not be constructed. Falsehood must only be seen.” ✧\n\n\nThis framework is intended as an open philosophical inquiry into consciousness and human authenticity, not as a fixed spiritual doctrine or institutional belief system.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20099498","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:45:44Z","registered":"2026-05-09T17:45:44Z","published":null,"updated":"2026-05-09T17:45:44Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20099497","type":"dois","attributes":{"doi":"10.5281/zenodo.20099497","identifiers":[],"creators":[{"name":"Manish kumar, Ghanchi","nameType":"Personal","givenName":"Ghanchi","familyName":"Manish kumar","affiliation":["Independent Researcher \u0026 Philosopher"],"nameIdentifiers":[{"nameIdentifier":"0009-0000-8083-0685","nameIdentifierScheme":"ORCID"}]},{"name":"Agyat agyani, vedanta 2.0","nameType":"Personal","givenName":"vedanta 2.0","familyName":"Agyat agyani","affiliation":["The Science of Existence, Non-Dualism, and Consciousness Studies"],"nameIdentifiers":[{"nameIdentifier":"0009-0000-8083-0685","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"The Science of False Identity  A Consciousness Framework of Svabhava, Illusion, and Existential Clarity"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"Svabhava"},{"subject":"Dharma"},{"subject":"Consciousness","subjectScheme":"MeSH"},{"subject":"Existentialism","subjectScheme":"MeSH"},{"subject":"False Identity"},{"subject":"Awareness","subjectScheme":"MeSH"},{"subject":"Systems Theory","subjectScheme":"MeSH"},{"subject":"Phenomenology"},{"subject":"Self-Observation"},{"subject":"Indian Philosophy"},{"subject":"Awakening"}],"contributors":[],"dates":[{"date":"2026-05-09","dateType":"Issued"},{"date":"2026-05-08","dateType":"Submitted","dateInformation":"An interdisciplinary experiential framework exploring false identity, consciousness, Svabhava, existential suffering, and direct observation through systems theory, phenomenology, contemplative psychology, and symbolic geometry"}],"language":"en","types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"CreativeWork","resourceType":"","resourceTypeGeneral":"Preprint"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20099497","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":"1.0","rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"},{"rights":"2026 Manish Kumar","rightsUri":"http://rightsstatements.org/vocab/InC/1.0/"}],"descriptions":[{"description":"The Science of False Identity presents an experiential consciousness framework exploring the relationship between Svabhava (intrinsic nature), false identity, existential suffering, and direct observation.\n\nThe work proposes that the central crisis of human life is not merely social, moral, or psychological dysfunction, but identification with conditioned and constructed identities formed through fear, comparison, imitation, memory, and civilization.\n\nIntegrating existential philosophy, phenomenology, contemplative psychology, systems theory, and Indian non-dual insight, the framework distinguishes between:\n\n\n\nintrinsic being (Svabhava),\n\nconditioned tendencies (Vasana),\n\nand socially constructed mask identities.\n\n\nRather than offering a new doctrine, ideology, religion, or moral system, the framework emphasizes direct seeing and existential clarity. It argues that truth does not need to be imposed or manufactured; falsehood only needs to be observed clearly.\n\nThe work includes:\n\n\n\nconsciousness systems models,\n\nsymbolic geometry,\n\nexistential alignment frameworks,\n\nfalse identity architectures,\n\nand phenomenological interpretations of Dharma, fear, observation, and awakening.\n\n\nCentral propositions include:\n\n\n\n✧ “Human suffering is identification with what one is not.” ✧\n\n\n\n\n✧ “Dharma begins not with obedience, but with clear seeing.” ✧\n\n\n\n\n✧ “Truth need not be constructed. Falsehood must only be seen.” ✧\n\n\nThis framework is intended as an open philosophical inquiry into consciousness and human authenticity, not as a fixed spiritual doctrine or institutional belief system.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20099497","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:45:44Z","registered":"2026-05-09T17:45:44Z","published":null,"updated":"2026-05-09T17:45:44Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.15620361","type":"dois","attributes":{"doi":"10.5281/zenodo.15620361","identifiers":[{"identifier":"oai:zenodo.org:15620361","identifierType":"oai"}],"creators":[{"name":"Bostick, Devin","nameType":"Personal","givenName":"Devin","familyName":"Bostick","nameIdentifiers":[],"affiliation":[]}],"titles":[{"title":"The Cashmiri Effect_ When Coherence Becomes Unreadable"}],"publisher":"Zenodo","container":{},"publicationYear":2025,"subjects":[{"subject":"Cognitive Science","subjectScheme":"MeSH"},{"subject":"Epistemology","subjectScheme":"EuroSciVoc"},{"subject":"Artificial intelligence","subjectScheme":"EuroSciVoc"},{"subject":"Theory of Mind","subjectScheme":"MeSH"},{"subject":"Theoretical physics","subjectScheme":"EuroSciVoc"},{"subject":"Cashmiri Effect,"},{"subject":"PAS (Phase Alignment Score)"},{"subject":"Resonance Intelligence Core"},{"subject":"Coherence Misclassification"},{"subject":"Symbolic Entropy"},{"subject":"Identity Rephrasing"},{"subject":"Epistemic Inversion"},{"subject":"Intelligence Alignment"},{"subject":"Phase-structure Diagnostics"}],"contributors":[],"dates":[{"date":"2025-06-08","dateType":"Issued"}],"language":"en","types":{"ris":"RPRT","bibtex":"article","citeproc":"article-journal","schemaOrg":"ScholarlyArticle","resourceType":"","resourceTypeGeneral":"Text"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.15620360","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Supersession Note — May 2026\n\nThis CODES-era work is an exploratory predecessor and is no longer the canonical statement of the author’s program. It has been superseded by the identity-persistence stack:\n\nUniversal Identity and Persistence:\n\nhttps://zenodo.org/records/19904166\n\nA Mathematical Theory of Identity Persistence:\n\nhttps://zenodo.org/records/19967345\n\nA Coding Theorem for Identity Persistence:\n\nhttps://zenodo.org/records/19996467\n\nIdentity Persistence Calculus:\n\nhttps://zenodo.org/records/19905404\n\nThe Bounded Corridor:\n\nhttps://zenodo.org/records/19645631\n\nThe Unclosable Bridge:\n\nhttps://zenodo.org/records/19601328\n\nClaims in this record concerning replacement of probability, unrestricted universality, ontology, physics, intelligence, biology, governance, or reality should be read as developmental framing, not as the current formal claim.\n\nThe current claim is restricted to identity persistence under transformation within explicit admissibility constraints: recurrence comparability, admissible redescription, bounded drift, scalar or scalar-equivalent governance, finite identity capacity, and deterministic finite-regime coding/enforcement where applicable.\n\n ","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.15620361","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":1,"created":"2025-06-08T20:33:47Z","registered":"2025-06-08T20:33:47Z","published":null,"updated":"2026-05-09T17:44:45Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.15620360","type":"dois","attributes":{"doi":"10.5281/zenodo.15620360","identifiers":[],"creators":[{"name":"Bostick, Devin","nameType":"Personal","givenName":"Devin","familyName":"Bostick","nameIdentifiers":[],"affiliation":[]}],"titles":[{"title":"The Cashmiri Effect_ When Coherence Becomes Unreadable"}],"publisher":"Zenodo","container":{},"publicationYear":2025,"subjects":[{"subject":"Cognitive Science","subjectScheme":"MeSH"},{"subject":"Epistemology","subjectScheme":"EuroSciVoc"},{"subject":"Artificial intelligence","subjectScheme":"EuroSciVoc"},{"subject":"Theory of Mind","subjectScheme":"MeSH"},{"subject":"Theoretical physics","subjectScheme":"EuroSciVoc"},{"subject":"Cashmiri Effect,"},{"subject":"PAS (Phase Alignment Score)"},{"subject":"Resonance Intelligence Core"},{"subject":"Coherence Misclassification"},{"subject":"Symbolic Entropy"},{"subject":"Identity Rephrasing"},{"subject":"Epistemic Inversion"},{"subject":"Intelligence Alignment"},{"subject":"Phase-structure Diagnostics"}],"contributors":[],"dates":[{"date":"2025-06-08","dateType":"Issued"}],"language":"en","types":{"ris":"RPRT","bibtex":"article","citeproc":"article-journal","schemaOrg":"ScholarlyArticle","resourceType":"","resourceTypeGeneral":"Text"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.15620360","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Supersession Note — May 2026\n\nThis CODES-era work is an exploratory predecessor and is no longer the canonical statement of the author’s program. It has been superseded by the identity-persistence stack:\n\nUniversal Identity and Persistence:\n\nhttps://zenodo.org/records/19904166\n\nA Mathematical Theory of Identity Persistence:\n\nhttps://zenodo.org/records/19967345\n\nA Coding Theorem for Identity Persistence:\n\nhttps://zenodo.org/records/19996467\n\nIdentity Persistence Calculus:\n\nhttps://zenodo.org/records/19905404\n\nThe Bounded Corridor:\n\nhttps://zenodo.org/records/19645631\n\nThe Unclosable Bridge:\n\nhttps://zenodo.org/records/19601328\n\nClaims in this record concerning replacement of probability, unrestricted universality, ontology, physics, intelligence, biology, governance, or reality should be read as developmental framing, not as the current formal claim.\n\nThe current claim is restricted to identity persistence under transformation within explicit admissibility constraints: recurrence comparability, admissible redescription, bounded drift, scalar or scalar-equivalent governance, finite identity capacity, and deterministic finite-regime coding/enforcement where applicable.\n\n ","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.15620360","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":1,"versionOfCount":0,"created":"2025-06-08T20:33:47Z","registered":"2025-06-08T20:33:47Z","published":null,"updated":"2026-05-09T17:44:45Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.15742771","type":"dois","attributes":{"doi":"10.5281/zenodo.15742771","identifiers":[],"creators":[{"name":"Bostick, Devin","nameType":"Personal","givenName":"Devin","familyName":"Bostick","nameIdentifiers":[],"affiliation":[]}],"titles":[{"title":"What He Saw But Couldn't Write (Ramanujan v2)"}],"publisher":"Zenodo","container":{},"publicationYear":2025,"subjects":[{"subject":"Ramanujan"},{"subject":"Partition Function"},{"subject":"Modular Forms"},{"subject":"Mock Theta"},{"subject":"Chirality"},{"subject":"Structured Resonance"},{"subject":"PAS (Phase Alignment Score)"},{"subject":"Prime numbers","subjectScheme":"EuroSciVoc"},{"subject":"Emission Gating"},{"subject":"CODES Framework"},{"subject":"Coherence Theory"},{"subject":"Mathematical Epistemology"},{"subject":"Symbolic Drift"},{"subject":"CHORDLOCK"},{"subject":"Resonance Intelligence Core"},{"subject":"Mathematical logic","subjectScheme":"EuroSciVoc"},{"subject":"Mathematics","subjectScheme":"MeSH"},{"subject":"FOS: Mathematics","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2025-06-26","dateType":"Issued"}],"language":"en","types":{"ris":"RPRT","bibtex":"article","citeproc":"article-journal","schemaOrg":"ScholarlyArticle","resourceType":"","resourceTypeGeneral":"Text"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.15742771","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Supersession Note — May 2026\n\nThis CODES-era work is an exploratory predecessor and is no longer the canonical statement of the author’s program. It has been superseded by the identity-persistence stack:\n\nUniversal Identity and Persistence:\n\nhttps://zenodo.org/records/19904166\n\nA Mathematical Theory of Identity Persistence:\n\nhttps://zenodo.org/records/19967345\n\nA Coding Theorem for Identity Persistence:\n\nhttps://zenodo.org/records/19996467\n\nIdentity Persistence Calculus:\n\nhttps://zenodo.org/records/19905404\n\nThe Bounded Corridor:\n\nhttps://zenodo.org/records/19645631\n\nThe Unclosable Bridge:\n\nhttps://zenodo.org/records/19601328\n\nClaims in this record concerning replacement of probability, unrestricted universality, ontology, physics, intelligence, biology, governance, or reality should be read as developmental framing, not as the current formal claim.\n\nThe current claim is restricted to identity persistence under transformation within explicit admissibility constraints: recurrence comparability, admissible redescription, bounded drift, scalar or scalar-equivalent governance, finite identity capacity, and deterministic finite-regime coding/enforcement where applicable.\n\n ","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.15742771","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":1,"versionOfCount":0,"created":"2025-06-26T02:34:13Z","registered":"2025-06-26T02:34:13Z","published":null,"updated":"2026-05-09T17:42:14Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.15742772","type":"dois","attributes":{"doi":"10.5281/zenodo.15742772","identifiers":[{"identifier":"oai:zenodo.org:15742772","identifierType":"oai"}],"creators":[{"name":"Bostick, Devin","nameType":"Personal","givenName":"Devin","familyName":"Bostick","nameIdentifiers":[],"affiliation":[]}],"titles":[{"title":"What He Saw But Couldn't Write (Ramanujan v2)"}],"publisher":"Zenodo","container":{},"publicationYear":2025,"subjects":[{"subject":"Ramanujan"},{"subject":"Partition Function"},{"subject":"Modular Forms"},{"subject":"Mock Theta"},{"subject":"Chirality"},{"subject":"Structured Resonance"},{"subject":"PAS (Phase Alignment Score)"},{"subject":"Prime numbers","subjectScheme":"EuroSciVoc"},{"subject":"Emission Gating"},{"subject":"CODES Framework"},{"subject":"Coherence Theory"},{"subject":"Mathematical Epistemology"},{"subject":"Symbolic Drift"},{"subject":"CHORDLOCK"},{"subject":"Resonance Intelligence Core"},{"subject":"Mathematical logic","subjectScheme":"EuroSciVoc"},{"subject":"Mathematics","subjectScheme":"MeSH"},{"subject":"FOS: Mathematics","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2025-06-26","dateType":"Issued"}],"language":"en","types":{"ris":"RPRT","bibtex":"article","citeproc":"article-journal","schemaOrg":"ScholarlyArticle","resourceType":"","resourceTypeGeneral":"Text"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.15742771","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Supersession Note — May 2026\n\nThis CODES-era work is an exploratory predecessor and is no longer the canonical statement of the author’s program. It has been superseded by the identity-persistence stack:\n\nUniversal Identity and Persistence:\n\nhttps://zenodo.org/records/19904166\n\nA Mathematical Theory of Identity Persistence:\n\nhttps://zenodo.org/records/19967345\n\nA Coding Theorem for Identity Persistence:\n\nhttps://zenodo.org/records/19996467\n\nIdentity Persistence Calculus:\n\nhttps://zenodo.org/records/19905404\n\nThe Bounded Corridor:\n\nhttps://zenodo.org/records/19645631\n\nThe Unclosable Bridge:\n\nhttps://zenodo.org/records/19601328\n\nClaims in this record concerning replacement of probability, unrestricted universality, ontology, physics, intelligence, biology, governance, or reality should be read as developmental framing, not as the current formal claim.\n\nThe current claim is restricted to identity persistence under transformation within explicit admissibility constraints: recurrence comparability, admissible redescription, bounded drift, scalar or scalar-equivalent governance, finite identity capacity, and deterministic finite-regime coding/enforcement where applicable.\n\n ","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.15742772","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":1,"created":"2025-06-26T02:34:13Z","registered":"2025-06-26T02:34:13Z","published":null,"updated":"2026-05-09T17:42:14Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20099266","type":"dois","attributes":{"doi":"10.5281/zenodo.20099266","identifiers":[{"identifier":"2583-6897","identifierType":"ISSN"}],"creators":[{"name":"Chandanshive, Vikrant","nameType":"Personal","givenName":"Vikrant","familyName":"Chandanshive","affiliation":["Dept of Botany Gokhale Education Society's Arts, Commerce and Science College Jawhar dist.-Palghar"],"nameIdentifiers":[]},{"name":"Jawale, Chetan","nameType":"Personal","givenName":"Chetan","familyName":"Jawale","affiliation":["G. E. Society's H. P. T. Arts \u0026 R. Y. K. Science College"],"nameIdentifiers":[{"nameIdentifier":"0000-0002-2148-2091","nameIdentifierScheme":"ORCID"}]},{"name":"Bambare, Abhijeet","nameType":"Personal","givenName":"Abhijeet","familyName":"Bambare","affiliation":["Dept of Chemistry Gokhale Education Society's Arts, Commerce and Science College Jawhar dist.-Palghar"],"nameIdentifiers":[]},{"name":"Patel, Mahammad","nameType":"Personal","givenName":"Mahammad","familyName":"Patel","affiliation":["Dept of Botany,M.C.E. Society's Abeda Inamdar Senior College of Arts, Science and Commerce, Pune."],"nameIdentifiers":[]}],"titles":[{"title":"Lutein from chlorella vulgaris: a source for the treatment of age-related macular degradation (AMD):-A review"}],"publisher":"Phoenix: International Multidisciplinary Research Journal","container":{},"publicationYear":2026,"subjects":[{"subject":"Lutein","subjectScheme":"MeSH"},{"subject":"Chlorella vulgaris","subjectScheme":"MeSH"},{"subject":"AMD"}],"contributors":[],"dates":[{"date":"2026-02-09","dateType":"Issued"},{"date":"2006-02-09","dateType":"Available","dateInformation":"https://pimrj.org/index.php/pimrj/article/download/247/373"}],"language":"en","types":{"ris":"JOUR","bibtex":"article","citeproc":"article-journal","schemaOrg":"ScholarlyArticle","resourceType":"","resourceTypeGeneral":"JournalArticle"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20099266","relatedIdentifierType":"DOI"},{"relationType":"IsPartOf","relatedIdentifier":"2583-6897","resourceTypeGeneral":"Collection","relatedIdentifierType":"ISSN"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Lutein, a natural xanthophyll pigment found in green plants and microalgae like Chlorella vulgaris, has the formula C40H56O2 and has high antioxidant effects. Chlorella vulgaris produced reactive oxygen species (ROS), which exposed to stress conditions like strong light, deflection in nutrition, salt and high temperature. To neutralize the reactive oxygen species, lutein play a vital role. It is synthesized in chloroplasts via the Methylerythritol phosphate (MEP) route, preserves the photosynthetic system and promotes cell stability. In humans, it accumulates in the retinal macula, where it filters damaging blue light and promotesvisual health. To extract lutein effectively, the algal cell wall must be disrupted. Using sophisticated techniques like ultrasound, microwave, enzyme-assisted, or supercritical CO₂ help to separate lutein from Chlorella vulgaris. For the purification of lutein use of liquidliquid partitioning chromatography and counter-current chromatography. The other chromatography like HSCCC, HPCCC, and CPC recommended for industrial scale purpose. A Lutein molecules have significant biological, industrial, and therapeutic applications, notably in increasing visual function and treating age-related macular degeneration.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20099266","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:38:09Z","registered":"2026-05-09T17:38:09Z","published":null,"updated":"2026-05-09T17:38:10Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20099267","type":"dois","attributes":{"doi":"10.5281/zenodo.20099267","identifiers":[{"identifier":"oai:zenodo.org:20099267","identifierType":"oai"},{"identifier":"2583-6897","identifierType":"ISSN"}],"creators":[{"name":"Chandanshive, Vikrant","nameType":"Personal","givenName":"Vikrant","familyName":"Chandanshive","affiliation":["Dept of Botany Gokhale Education Society's Arts, Commerce and Science College Jawhar dist.-Palghar"],"nameIdentifiers":[]},{"name":"Jawale, Chetan","nameType":"Personal","givenName":"Chetan","familyName":"Jawale","affiliation":["G. E. Society's H. P. T. Arts \u0026 R. Y. K. Science College"],"nameIdentifiers":[{"nameIdentifier":"0000-0002-2148-2091","nameIdentifierScheme":"ORCID"}]},{"name":"Bambare, Abhijeet","nameType":"Personal","givenName":"Abhijeet","familyName":"Bambare","affiliation":["Dept of Chemistry Gokhale Education Society's Arts, Commerce and Science College Jawhar dist.-Palghar"],"nameIdentifiers":[]},{"name":"Patel, Mahammad","nameType":"Personal","givenName":"Mahammad","familyName":"Patel","affiliation":["Dept of Botany,M.C.E. Society's Abeda Inamdar Senior College of Arts, Science and Commerce, Pune."],"nameIdentifiers":[]}],"titles":[{"title":"Lutein from chlorella vulgaris: a source for the treatment of age-related macular degradation (AMD):-A review"}],"publisher":"Phoenix: International Multidisciplinary Research Journal","container":{},"publicationYear":2026,"subjects":[{"subject":"Lutein","subjectScheme":"MeSH"},{"subject":"Chlorella vulgaris","subjectScheme":"MeSH"},{"subject":"AMD"}],"contributors":[],"dates":[{"date":"2026-02-09","dateType":"Issued"},{"date":"2006-02-09","dateType":"Available","dateInformation":"https://pimrj.org/index.php/pimrj/article/download/247/373"}],"language":"en","types":{"ris":"JOUR","bibtex":"article","citeproc":"article-journal","schemaOrg":"ScholarlyArticle","resourceType":"","resourceTypeGeneral":"JournalArticle"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20099266","relatedIdentifierType":"DOI"},{"relationType":"IsPartOf","relatedIdentifier":"2583-6897","resourceTypeGeneral":"Collection","relatedIdentifierType":"ISSN"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Lutein, a natural xanthophyll pigment found in green plants and microalgae like Chlorella vulgaris, has the formula C40H56O2 and has high antioxidant effects. Chlorella vulgaris produced reactive oxygen species (ROS), which exposed to stress conditions like strong light, deflection in nutrition, salt and high temperature. To neutralize the reactive oxygen species, lutein play a vital role. It is synthesized in chloroplasts via the Methylerythritol phosphate (MEP) route, preserves the photosynthetic system and promotes cell stability. In humans, it accumulates in the retinal macula, where it filters damaging blue light and promotesvisual health. To extract lutein effectively, the algal cell wall must be disrupted. Using sophisticated techniques like ultrasound, microwave, enzyme-assisted, or supercritical CO₂ help to separate lutein from Chlorella vulgaris. For the purification of lutein use of liquidliquid partitioning chromatography and counter-current chromatography. The other chromatography like HSCCC, HPCCC, and CPC recommended for industrial scale purpose. A Lutein molecules have significant biological, industrial, and therapeutic applications, notably in increasing visual function and treating age-related macular degeneration.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20099267","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:38:09Z","registered":"2026-05-09T17:38:09Z","published":null,"updated":"2026-05-09T17:38:09Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20098990","type":"dois","attributes":{"doi":"10.5281/zenodo.20098990","identifiers":[{"identifier":"oai:zenodo.org:20098990","identifierType":"oai"}],"creators":[{"name":"Kenny, Cathal","nameType":"Personal","givenName":"Cathal","familyName":"Kenny","nameIdentifiers":[],"affiliation":[]}],"titles":[{"title":"The Joseph Drive"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"Solid state","subjectScheme":"GEMET"},{"subject":"Solid-state physics","subjectScheme":"EuroSciVoc"},{"subject":"Thorium/chemistry","subjectScheme":"MeSH"},{"subject":"Nano-materials","subjectScheme":"EuroSciVoc"},{"subject":"Cyclotron"},{"subject":"Terrawatt"},{"subject":"Quantum physics","subjectScheme":"EuroSciVoc"},{"subject":"Quantum field theory","subjectScheme":"EuroSciVoc"},{"subject":"Bose-einstein condensates","subjectScheme":"EuroSciVoc"},{"subject":"Metric System/history","subjectScheme":"MeSH"},{"subject":"Superfluids"},{"subject":"Microscopy, Atomic Force/methods","subjectScheme":"MeSH"}],"contributors":[],"dates":[{"date":"2026-05-09","dateType":"Issued"},{"date":"2026-06-02","dateType":"Created","dateInformation":"The Joseph Drive "}],"language":"en","types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"CreativeWork","resourceType":"","resourceTypeGeneral":"Preprint"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20098989","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":"V27","rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Preface:\n\n \n\nThe core objective of this paper is to bridge the gap between the lentz soliton model and real world engineering within the possibilities of a 2026 engineering budget, this theroy if proven would stand as a turning point in human history, officially marking the end traditional combustion era, and birth the start of the metric age, this would catapult humanity from a type .73 on the kardesheiv scale to the begining of type 1 status.\n\nThe Project ES1 craft utilizes a monolithic 1,500-tonne hull constructed from 152 million layers of alternating 0.5nm Bismuth and Magnesium nanolaminates. This \"Russian Doll\" architecture operates as a decentralized nodal network, where each atomic intersection facilitates thermoelectric Seebeck recovery and precise thermal stabilization. Maintained at a 3K superconducting state via an integrated liquid hydrogen capillary system, the hull functions as a rigid, Meissner-shielded frame that houses the dual-cyclotron floor panels and the lower-deck soliton containment vessel. This nodal design allows the ship to withstand extreme localized metric tilts while managing the 1.9 GW energy flux required for geodesic acceleration.\n\nThis document provides a comprehensive technical and mathematical audit of the Joseph Drive, beginning with the structural and material specifications of the nanolaminate hull. It details the mid-deck nuclear configuration, focusing on the pulsed cyclotron transmutation of Thorium-232 and the subsequent 38% mass-energy conversion. The central chapters present formal derivations of the Joseph Metric Tensor and the optomechanical guidance guideway, proving the stability of subluminal and superluminal transit within the laws of General Relativity and Quantum Chromodynamics. The treatise concludes with an operational safety analysis, addressing gravimetric tidal sensing, attosecond AI latency, and thermodynamic entropy rejection.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20098990","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:22:21Z","registered":"2026-05-09T17:22:21Z","published":null,"updated":"2026-05-09T17:36:59Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20098989","type":"dois","attributes":{"doi":"10.5281/zenodo.20098989","identifiers":[],"creators":[{"name":"Kenny, Cathal","nameType":"Personal","givenName":"Cathal","familyName":"Kenny","nameIdentifiers":[],"affiliation":[]}],"titles":[{"title":"The Joseph Drive"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"Solid state","subjectScheme":"GEMET"},{"subject":"Solid-state physics","subjectScheme":"EuroSciVoc"},{"subject":"Thorium/chemistry","subjectScheme":"MeSH"},{"subject":"Nano-materials","subjectScheme":"EuroSciVoc"},{"subject":"Cyclotron"},{"subject":"Terrawatt"},{"subject":"Quantum physics","subjectScheme":"EuroSciVoc"},{"subject":"Quantum field theory","subjectScheme":"EuroSciVoc"},{"subject":"Bose-einstein condensates","subjectScheme":"EuroSciVoc"},{"subject":"Metric System/history","subjectScheme":"MeSH"},{"subject":"Superfluids"},{"subject":"Microscopy, Atomic Force/methods","subjectScheme":"MeSH"}],"contributors":[],"dates":[{"date":"2026-05-09","dateType":"Issued"},{"date":"2026-06-02","dateType":"Created","dateInformation":"The Joseph Drive "}],"language":"en","types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"CreativeWork","resourceType":"","resourceTypeGeneral":"Preprint"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20098989","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":"V27","rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Preface:\n\n \n\nThe core objective of this paper is to bridge the gap between the lentz soliton model and real world engineering within the possibilities of a 2026 engineering budget, this theroy if proven would stand as a turning point in human history, officially marking the end traditional combustion era, and birth the start of the metric age, this would catapult humanity from a type .73 on the kardesheiv scale to the begining of type 1 status.\n\nThe Project ES1 craft utilizes a monolithic 1,500-tonne hull constructed from 152 million layers of alternating 0.5nm Bismuth and Magnesium nanolaminates. This \"Russian Doll\" architecture operates as a decentralized nodal network, where each atomic intersection facilitates thermoelectric Seebeck recovery and precise thermal stabilization. Maintained at a 3K superconducting state via an integrated liquid hydrogen capillary system, the hull functions as a rigid, Meissner-shielded frame that houses the dual-cyclotron floor panels and the lower-deck soliton containment vessel. This nodal design allows the ship to withstand extreme localized metric tilts while managing the 1.9 GW energy flux required for geodesic acceleration.\n\nThis document provides a comprehensive technical and mathematical audit of the Joseph Drive, beginning with the structural and material specifications of the nanolaminate hull. It details the mid-deck nuclear configuration, focusing on the pulsed cyclotron transmutation of Thorium-232 and the subsequent 38% mass-energy conversion. The central chapters present formal derivations of the Joseph Metric Tensor and the optomechanical guidance guideway, proving the stability of subluminal and superluminal transit within the laws of General Relativity and Quantum Chromodynamics. The treatise concludes with an operational safety analysis, addressing gravimetric tidal sensing, attosecond AI latency, and thermodynamic entropy rejection.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20098989","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:22:21Z","registered":"2026-05-09T17:22:21Z","published":null,"updated":"2026-05-09T17:36:59Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.17964123","type":"dois","attributes":{"doi":"10.5281/zenodo.17964123","identifiers":[],"creators":[{"name":"Lindenhayn, Mark","nameType":"Personal","givenName":"Mark","familyName":"Lindenhayn","nameIdentifiers":[{"nameIdentifier":"0009-0008-6051-4114","nameIdentifierScheme":"ORCID"}],"affiliation":[]}],"titles":[{"title":"The Relational Nature of Zero-Dimensional Objects: Dimensional Closure, Scale Relativity, and Informational Leakage"}],"publisher":"Zenodo","container":{},"publicationYear":2025,"subjects":[{"subject":"Geometry","subjectScheme":"EuroSciVoc"},{"subject":"Topology","subjectScheme":"EuroSciVoc"},{"subject":"Information Theory","subjectScheme":"MeSH"},{"subject":"Scale invariance"},{"subject":"Physics","subjectScheme":"GEMET"},{"subject":"Mathematical physics","subjectScheme":"EuroSciVoc"},{"subject":"Mathematical logic","subjectScheme":"EuroSciVoc"},{"subject":"Mathematics","subjectScheme":"MeSH"},{"subject":"FOS: Mathematics","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Quantum physics","subjectScheme":"EuroSciVoc"},{"subject":"Quantum Theory","subjectScheme":"MeSH"},{"subject":"Particle physics","subjectScheme":"EuroSciVoc"},{"subject":"Nuclear physics","subjectScheme":"EuroSciVoc"},{"subject":"Computational topology","subjectScheme":"EuroSciVoc"},{"subject":"Artificial intelligence","subjectScheme":"EuroSciVoc"},{"subject":"Machine learning","subjectScheme":"EuroSciVoc"},{"subject":"Machine Learning","subjectScheme":"MeSH"},{"subject":"Fractals","subjectScheme":"MeSH"}],"contributors":[],"dates":[{"date":"2025-12-17","dateType":"Issued"}],"language":null,"types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"CreativeWork","resourceType":"","resourceTypeGeneral":"Preprint"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.17964123","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"This paper explores the relational foundations of zero-dimensional objects in geometry, challenging the classical view of points as absolute primitives without extension or scale. We demonstrate that zero-dimensionality is inherently dependent on the ambient space's dimensional structure, introducing concepts such as dimensional closure (the ability to recover all geometric degrees of freedom intrinsically) and informational leakage (unaccounted freedoms in lower-dimensional embeddings). Through rigorous propositions and proofs grounded in topology, differential geometry, and information theory, we show that scale is relative and observer-dependent in lower dimensions, while higher-dimensional embeddings reveal hidden indeterminacies. This framework reframes dimensionality as a measure of informational capacity, resolving paradoxes like ultraviolet divergences, non-local correlations, and singularities in physics. Implications extend to alternative geometric foundations (e.g., categorical or information-theoretic) and emergent properties in quantum gravity. ","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.17964123","contentUrl":null,"metadataVersion":3,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":2,"versionOfCount":1,"created":"2025-12-17T14:02:14Z","registered":"2025-12-17T14:02:14Z","published":null,"updated":"2026-05-09T17:34:03Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.17964124","type":"dois","attributes":{"doi":"10.5281/zenodo.17964124","identifiers":[{"identifier":"oai:zenodo.org:17964124","identifierType":"oai"}],"creators":[{"name":"Lindenhayn, Mark","nameType":"Personal","givenName":"Mark","familyName":"Lindenhayn","nameIdentifiers":[{"nameIdentifier":"0009-0008-6051-4114","nameIdentifierScheme":"ORCID"}],"affiliation":[]}],"titles":[{"title":"The Relational Nature of Zero-Dimensional Objects: Dimensional Closure, Scale Relativity, and Informational Leakage"}],"publisher":"Zenodo","container":{},"publicationYear":2025,"subjects":[{"subject":"Geometry","subjectScheme":"EuroSciVoc"},{"subject":"Topology","subjectScheme":"EuroSciVoc"},{"subject":"Information Theory","subjectScheme":"MeSH"},{"subject":"Scale invariance"},{"subject":"Physics","subjectScheme":"GEMET"},{"subject":"Mathematical physics","subjectScheme":"EuroSciVoc"},{"subject":"Mathematical logic","subjectScheme":"EuroSciVoc"},{"subject":"Mathematics","subjectScheme":"MeSH"},{"subject":"FOS: Mathematics","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Quantum physics","subjectScheme":"EuroSciVoc"},{"subject":"Quantum Theory","subjectScheme":"MeSH"},{"subject":"Particle physics","subjectScheme":"EuroSciVoc"},{"subject":"Nuclear physics","subjectScheme":"EuroSciVoc"},{"subject":"Computational topology","subjectScheme":"EuroSciVoc"},{"subject":"Artificial intelligence","subjectScheme":"EuroSciVoc"},{"subject":"Machine learning","subjectScheme":"EuroSciVoc"},{"subject":"Machine Learning","subjectScheme":"MeSH"},{"subject":"Fractals","subjectScheme":"MeSH"}],"contributors":[],"dates":[{"date":"2025-12-17","dateType":"Issued"}],"language":null,"types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"CreativeWork","resourceType":"","resourceTypeGeneral":"Preprint"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.17964123","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"This paper explores the relational foundations of zero-dimensional objects in geometry, challenging the classical view of points as absolute primitives without extension or scale. We demonstrate that zero-dimensionality is inherently dependent on the ambient space's dimensional structure, introducing concepts such as dimensional closure (the ability to recover all geometric degrees of freedom intrinsically) and informational leakage (unaccounted freedoms in lower-dimensional embeddings). Through rigorous propositions and proofs grounded in topology, differential geometry, and information theory, we show that scale is relative and observer-dependent in lower dimensions, while higher-dimensional embeddings reveal hidden indeterminacies. This framework reframes dimensionality as a measure of informational capacity, resolving paradoxes like ultraviolet divergences, non-local correlations, and singularities in physics. Implications extend to alternative geometric foundations (e.g., categorical or information-theoretic) and emergent properties in quantum gravity. ","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.17964124","contentUrl":null,"metadataVersion":2,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":1,"created":"2025-12-17T14:02:14Z","registered":"2025-12-17T14:02:14Z","published":null,"updated":"2026-05-09T17:34:03Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.17930722","type":"dois","attributes":{"doi":"10.5281/zenodo.17930722","identifiers":[],"creators":[{"name":"Lacueva Pérez, Francisco José","nameType":"Personal","givenName":"Francisco José","familyName":"Lacueva Pérez","affiliation":["Instituto Tecnológico de Aragón"],"nameIdentifiers":[{"nameIdentifier":"0000-0003-0998-2939","nameIdentifierScheme":"ORCID"}]},{"name":"Labata Lezaun, Gorka","nameType":"Personal","givenName":"Gorka","familyName":"Labata Lezaun","affiliation":["Instituto Tecnológico de Aragón"],"nameIdentifiers":[{"nameIdentifier":"0000-0002-8634-4124","nameIdentifierScheme":"ORCID"}]},{"name":"Ilarri, Sergio","nameType":"Personal","givenName":"Sergio","familyName":"Ilarri","affiliation":["Universidad de Zaragoza"],"nameIdentifiers":[{"nameIdentifier":"0000-0002-7073-219X","nameIdentifierScheme":"ORCID"}]},{"name":"del Hoyo Alonso, Rafael","nameType":"Personal","givenName":"Rafael","familyName":"del Hoyo Alonso","affiliation":["Universidad San Jorge","Instituto Tecnológico de Aragón"],"nameIdentifiers":[{"nameIdentifier":"0000-0003-2755-5500","nameIdentifierScheme":"ORCID"}]},{"name":"Barriuso Vargas, Juan","nameType":"Personal","givenName":"Juan","familyName":"Barriuso Vargas","affiliation":["Universidad de Zaragoza"],"nameIdentifiers":[{"nameIdentifier":"0000-0003-2980-5454","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"A Multisource Grapevine Phenology Dataset for Smart Farming and AI Modeling"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"Agri-foodstuff","subjectScheme":"GEMET"},{"subject":"Machine learning","subjectScheme":"EuroSciVoc"},{"subject":"Supervised Machine Learning","subjectScheme":"MeSH"},{"subject":"Agriculture","subjectScheme":"EuroSciVoc"}],"contributors":[{"name":"Ilarri, Sergio","nameType":"Personal","givenName":"Sergio","familyName":"Ilarri","affiliation":["Universidad de Zaragoza"],"contributorType":"Editor","nameIdentifiers":[{"nameIdentifier":"0000-0002-7073-219X","nameIdentifierScheme":"ORCID"}]},{"name":"Labata Lezaun, Gorka","nameType":"Personal","givenName":"Gorka","familyName":"Labata Lezaun","affiliation":["Instituto Tecnológico de Aragón"],"contributorType":"DataCurator","nameIdentifiers":[{"nameIdentifier":"0000-0002-8634-4124","nameIdentifierScheme":"ORCID"}]},{"name":"del Hoyo Alonso, Rafael","nameType":"Personal","givenName":"Rafael","familyName":"del Hoyo Alonso","affiliation":["Universidad San Jorge","Instituto Tecnológico de Aragón"],"contributorType":"DataCurator","nameIdentifiers":[{"nameIdentifier":"0000-0003-2755-5500","nameIdentifierScheme":"ORCID"}]},{"name":"Barriuso Vargas, Juan","nameType":"Personal","givenName":"Juan","familyName":"Barriuso Vargas","affiliation":["Universidad de Zaragoza"],"contributorType":"DataCurator","nameIdentifiers":[{"nameIdentifier":"0000-0003-2980-5454","nameIdentifierScheme":"ORCID"}]},{"name":"Lacueva Pérez, Francisco José","nameType":"Personal","givenName":"Francisco José","familyName":"Lacueva Pérez","affiliation":["Instituto Tecnológico de Aragón"],"contributorType":"ContactPerson","nameIdentifiers":[{"nameIdentifier":"0000-0003-0998-2939","nameIdentifierScheme":"ORCID"}]},{"name":"Ilarri, Sergio","nameType":"Personal","givenName":"Sergio","familyName":"Ilarri","affiliation":["Universidad de Zaragoza"],"contributorType":"DataManager","nameIdentifiers":[]}],"dates":[{"date":"2026-01-10","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1016/j.compag.2025.110018","resourceTypeGeneral":"JournalArticle","relatedIdentifierType":"DOI"},{"relationType":"IsReferencedBy","relatedIdentifier":"https://webdiis.unizar.es/~silarri/prot/DREAM/index.html","resourceTypeGeneral":"Other","relatedIdentifierType":"URL"},{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.17930722","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":"1.0","rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Description\n\nArtificial Intelligence and Machine Learning rely on large, high-quality datasets for accurate and robust models, yet data scarcity remains a major challenge—especially in smart farming. Agricultural data are highly diverse and heterogeneous, complicating model development. Phenology modeling, a key application, studies how plant biological events relate to climate and seasons. Accurate phenology models improve crop quality, support climate adaptation, and guide decisions such as pesticide use and harvesting, enhancing environmental and economic sustainability.This study introduces a georeferenced dataset for Machine Learning-based grapevine phenology prediction across 3 Protected Designations of Origin in Arag’on, Spain. Developed by a multidisciplinary team, the dataset combines 9 datasets from 8 sources—including meteorological time series, field phenology observations, and Copernicus Sentinel-2 multispectral imagery—covering the period 2016–2022. It supports both physical and ML-based phenology modeling and facilitates knowledge extraction in agronomy and plant biology. Its relevance lies in its comprehensive scope, the inclusion of 9 phenological stages, and a rigorous methodology ensuring reproducibility. This framework enables the creation of similar datasets for otherregions or crops, advancing smart farming through scalable, data-driven solutions. We further anticipate its potential contribution to developing Foundation Models as well as to the creation.\n\nDataset Structure\n\nThe dataset contains 2 main CSV files and 1 supporting folder:\n\n\n\nDIF Description.pdf- Description of the data set.\n\nDIF phenologicaletages.csv: it contains the links from the phenologystageid values in the file “DIF GrapevinePehologyDataset.csv:  with the correspoding BBCH values.\n\nDIF GrapevinePehologyDataset.csv: it contains the dataset used to train the models we presented.\n\nMetadata: this folder contains the JSON files describing the dataset and its content:\n\n\n\nDIF_DataSetDescription.json: the description contained if “DIF Description.pdf” but in JSON format.\n\nDIF GrapevinePehologyDataset.json: contains the dataset presented in this paper which was used to train the models we presented in [51, 50]. We describe the content of the file in next paragraphs.\n\n\n\n\nIntended Use\n\nThe goal of this dataset is to enable the development of models for predicting grapevine phenology in the three Protected Designations of Origin in Aragón (Spain), using data from field observations, meteorological stations, and NDVI derived from Copernicus Sentinel-2 multispectral imagery. Additionally, it supports the calibration of physical models for these regions by including the calculation of cold and heat accumulation indices. These calculations are performed using the traditional start dates of January 1 and February of the corresponding year, as well as from the date when plants enter dormancy: the first autumn day when the maximum temperature does not exceed 10 °C.\n\nAccess Conditions: This dataset is publicly available under the terms of the Creative Commons Attribution 4.0 International license. \n\nSpecifications Table\n\n\n\n\n\n\nSubject\n\n\n\nSmart farming\n\n\n\n\n\nSpecific subject area\n\n\n\nThe dataset is based on data from 3 Protected Designations of Origin—Calatayud, Cariñena and Campo de Borja, —in Aragón, northeastern Spain. Built by merging 9 georeferenced time-series datasets from 8 data sources considering the period from 2016 to 2022. It includes meteorological data (measurements, estimates, and forecasts), qualitative field phenology observations, and Copernicus Sentinel-2 multispectral imagery.\n\n\n\n\n\nType of data\n\n\n\nAnalyzedFilteredProcessedMulti-source\n\n\n\n\n\nData collection\n\n\n\nData merged in the dataset is obtained from 9 georeferenced datatsets obtained from 8 data sources.  The datasets considered are:\n\n·         Red FARA phenological registry [1]: this dataset has restricted access.  It provides phenology field observations on the control parcels.\n\n·         Spanish Cadastral Registry (Catastro) [2]: it is used to normalize Red FARA records and to obtain the NDVI of the control parcels from Copernicus Sentinel 2 images.\n\n·         Aragón Open Data Common Agrarian Policy Registry (CAP) [3]: together with the Catastro data is used to normalize of the Red FARA records.\n\n·         SIAR [4] and Grapevine [5] climatic station networks provide meteorological data.\n\n·         ERA5 real climatic estimations [6] and ECMWF IFS forecast [7] data used to replace failures in climatic data and forecast data to perform predictions.\n\n·         Copernicus Sentinel 2 multispectral images [8]: these images are used to determine the NDVI of the control parcels used to create the dataset. \n\nFor accessing these dataset we used available APIs.  All they are public and provide open access. The 2 exceptions were Red FARA which has restricted access, and ERA5 data which was accessed using openMeteo API [8] which eased our work.  The access to the data and the transformations performed in them were coded in Python.  A deep explanation of the transformation performed can be obtained in [9].\n\n\n\n\n\nData source location\n\n\n\nCountry: Spain.Region: Aragón.Protected Designation of Origin: Calatayud, Campo de Borja, Cariñena.Coordinates: Parallelepiped defined by points (41.98107, −2.177578) and (41.166320, −0.922575) in WGS84 coordinates.\n\n\n\n\n\nData accessibility\n\n\n\nRepository name: Zenodo\n\nData identification number: 10.5281/zenodo.17930723 Direct URL to data: https://doi.org/10.5281/zenodo.17930723  \n\n\n\n\n\nReferences\n\n\n\n\n\n\n\n\n[1]\n\n\n\nGovernment of Aragón. Red FARA Home Page. Last access: January 10, 2026. 2026. url: http://web.redfara.es.\n\n\n\n\n\n[2]\n\n\n\nSpanish Treasury. Spanish Cadastral Registry Electronic Home Page. Last access: January 10, 2026. 2026. url: https://www.sedecatastro.gob.es/.\n\n\n\n\n\n[3]\n\n\n\nGovernment of Aragón. Aragón Open Data Home Page. Last access: January 10, 2026. 2026. url: https://opendata.aragon.es.\n\n\n\n\n\n[4]\n\n\n\nSpanish Ministry of Agriculture, Fisheries and Food. Agro-climatic Information System for Irrigation (SIAR) Home Page. Last access: January 10, 2026. 2026. url: https://eportal.mapa.gob.es//websiar/Inicio.aspx .\n\n\n\n\n\n[5]\n\n\n\nGrapevine Project Consortium. Grapevine Project Home Page. Grant agreement ID: 863463. https://grapevine-project.eu (Last access: August 8, 2024), https://web.archive.org/web/20230922054033/https://grapevine- project.eu (Last access: January 10, 2026), https://www.egi.eu/case-study/grapevine (Last access: January 10, 2026). 2022.\n\n\n\n\n\n[6]\n\n\n\nCopernicus Climate Change Service (C3S). ERA5 hourly data on single levels from 1959 to present. Last access: January 10, 2026. 2023. url: https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels?tab=overview .\n\n\n\n\n\n[7]\n\n\n\nEuropean Centre for Medium-Range Weather Forecasts (ECMWF). ECMWF Open Data. Last accessed January 10, 2026. 2026. url: https://www.ecmwf.int/en/forecasts/datasets/open-data .\n\n\n\n\n\n[8]\n\n\n\nF. Gascon et al. “Copernicus Sentinel-2 mission: products, algorithms and Cal/Val”. In: Earth Observing Systems XIX. Ed. by James J. Butler, Xiaoxiong (Jack) Xiong, and Xingfa Gu.SPIE, Sept. 2014, pp. 1–9. doi:10.1117/12.2062260. url: http://dx.doi.org/10.1117/12.2062260.\n\n\n\n\n\n[9]\n\n\n\nFrancisco Jos´e Lacueva-P´erez et al. “Developing machine learning models from multisourced real-world datasets to enhance smart-farming practices”. In: Computers and Electronics in Agriculture 231 (Apr. 2025), p. 110018. issn: 0168-1699. doi: 10.1016/j.compag.2025.110018. url: http://dx.doi.org/10.1016/j.compag.2025.110018 .\n\n\n\n\n\n \n\n\n\n\n\n \n\n \n\n\n\n\n \n\nFile “DIF_GrapevinePehologyDataset.csv” Description\n\nFile DIF_GrapevinePehologyDataset.csv contains the dataset presented in this paper.  Each of the records represents the data considered for a given parcel (vineyard) in each date. The following table provides a description of the fields contained in the dataset. For clarity, we simplified the table by using an abbreviated notation for the field names; specifically, for some field names we include an asterisk (“*”) with the name followed by a couple of numbers in brackets (“[…]”) that describe the range of integer values that can replace the “*” in the dataset; for example, we did this in fields which provide values of the given variable data for the n days before (days_after ) and after (days_adelante).  For clarity, we provide here some examples:\n\n·         tmed_min *_days_after  [1,13]: this name represents that the dataset contains all the fields tmed_min 1_days_after , tmed_min 2_days_after , ..., tmed_min 13_days_after , which represent, for the given field, the minimum temperature for each of the n days before the date of the record.\n\n·         wind_NE *_days_after [1,6]: this name represents that the dataset contains all the fields wind_NE 1_days_after, t wind_NE 2_days_after, ..., wind_NE 6_days_after, which represent, for the given field, the wind_NE index for each of the n days after the date of the record.\n\n·         gdd_4.5_t0_Tbase_sum *_weeks_before [1,2]: this name represents that the dataset contains all the fields gdd_4.5_t0_Tbase_sum 1_weeks_before and gdd_4.5_t0_Tbase_sum 2_weeks_before, which represent, for the given field, the GDD calculated using the base temperature 4.5º C and starting to accumulate at the beginning of the session.\n\nMoreover, we use “|” to denote choices (expressed within brackets “[…]”), which can represent several attributes. For example, “rad_[min|MAX|mean]” actually represents (in a condensed way) 3 different variables: “rad_min”, “rad_max” and “rad_mean”. Other notations can be interpreted similarly. The full list of variable names is shown in Appendix A.\n\n\n\n\n\n\nField Name (abbreviated notation)\n\n\n\nDescription\n\n\n\n\n\n\n\nphenologystageid\n\n\n\nId of the phenological stage of the parcel on the given date.  See file “DIF phenologicalstages.csv”.\n\n\n\n\n\nvariety\n\n\n\nGrapevine variety:  Cabernet Sauvignon, Chardonnay, Garnacha, Mazuela, Syrach, Tempranillo.\n\n\n\n\n\ncodigo\n\n\n\nId of the parcel in the Spanish Cadastral Registry.\n\n\n\n\n\nlongitude\n\n\n\nLongitude of the centroid of the parcel.\n\n\n\n\n\nlatitude\n\n\n\nLatitude of the centroid of the parcel.\n\n\n\n\n\naltitudeASL\n\n\n\nAltitudeASL of the centroid of the parcel.\n\n\n\n\n\nPDO_id\n\n\n\nId of the Protected Designation of Origin (PDO): Calatayud, Carinena and Campo de Borja.\n\n\n\n\n\ndate\n\n\n\nThe date of the record.\n\n\n\n\n\nstation\n\n\n\nThe name of the climatic station whose data are considered.\n\n\n\n\n\nseason\n\n\n\nThe season to which the record belongs.\n\n\n\n\n\nday\n\n\n\nThe DOY (day of the year).\n\n\n\n\n\n\"PDO_Borja\", \"PDO_Calatayud\", \"PDO_Carinena\", \"PDO_Somontano\"\n\n\n\nBoolean values which are true when the record corresponds to the given PDO.\n\n\n\n\n\n\"variety_CABERNET SAUVIGNON\", \"variety_CHARDONNAY\", \"variety_GARNACHA\", \"variety_MAZUELA\", \"variety_SYRACH\", \"variety_TEMPRANILLO\"\n\n\n\nBoolean values which are true when the record corresponds to a field with the given variety.\n\n \n\n\n\n\n\nmin, MAX, mean, std, medayn, diff\n\n\n\nValues derived from the NDVI indexes calculated for each parcel from the Copernicus Sentinel 2 multispectral images.  They represent the minimum, maximum, average, standard deviation, medayn and difference values.\n\n\n\n\n\ntmed_[min|MAX|mean]\n\n\n\n[Minimum|Maximum|Mean] temperature for the given date (ºC).\n\n\n\n\n\ntmed_[min|MAX|mean] *_days_after  [1,13]\n\n\n\n[Minimum|Maximum|Mean] temperatures for the 13 days before the given date.\n\n\n\n\n\ntmed_[min|MAX|mean] *_days_after [1,6]\n\n\n\n[Minimum|Maximum|Mean] temperatures for the 6 days following the given date.\n\n\n\n\n\nrad_[min|MAX|mean]\n\n\n\n[Minimum|Maximum|Mean] radaytion for the given date (W/m²).\n\n\n\n\n\nrad_[min|MAX|mean] *_days_after  [1,13]\n\n\n\n[Minimum|Maximum|Mean] radaytion for the 13 days before the given date.\n\n\n\n\n\nrad_[min|MAX|mean] *_days_after [1,6]\n\n\n\n[Minimum|Maximum|Mean] radaytion for the 6 days following the given date.\n\n\n\n\n\nhr_ mean\n\n\n\nAverage air relative humidity for the given date (%).\n\n\n\n\n\nhr_mean *_days_after  [1,13]\n\n\n\nAverage air relative humidity radaytion for the 13 days before the given date.\n\n\n\n\n\nhr_mean *_days_after [1,6]\n\n\n\nAverage air relative humidity radaytion for the 6 days following the given date.\n\n\n\n\n\nwind_[N|NE|E|SE|S|SW|W|NW] *_days_after  [1,13]\n\n\n\nWind index for the North, North-East, East, South-East, South, South-West, West, North-West area for the 13 days before the given date.\n\n\n\n\n\nind_[N|NE|E|SE|S|SW|W|NW] *_days_after [1,6]\n\n\n\nWind index for the North, North-East, East, South-East, South, South-West, West, North-West area for the 6 days following the given date.\n\n\n\n\n\ngdd_[4.5|10.0]_[t0|1|2]_[TBase|TbaseMAX]_sum\n\n\n\nGDD heat accumulation index, calculated with a base temperature of 4.5ºC or 10.0 ºC; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a maximum temperature threshold over which the heat accumulation stopped (TbaseMAX, 35ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum).\n\n\n\n\n\ngdd_[4.5|10.0]_[t0|1|2]_[TBase|TbaseMAX]_sum *_weeks_before [1|2]\n\n\n\nGDD heat accumulation index, calculated with a base temperature of 4.5ºC or 10.0 ºC; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a maximum temperature threshold over which the heat accumulation stopped (TbaseMAX, 35ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the 2 weeks previous to the given day.\n\n\n\n\n\ngdd_[4.5|10.0]_[t0|1|2]_[TBase|TbaseMAX]_sum * 1_weeks_after\n\n\n\nGDD heat accumulation index, calculated with a base temperature of 4.5ºC or 10.0 ºC; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a maximum temperature threshold over which the heat accumulation stopped (TbaseMAX, 35ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the next week to the given day.\n\n\n\n\n\nChillingDD_7.0_[t0|1|2]_[TBase|Tbasemin]_sum\n\n\n\nRichardson cold accumulation index, calculated with a base temperature of 7.0º C; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a minimum temperature threshold above which the cold accumulation stopped (Tbasemin, -7ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum).\n\n\n\n\n\nChillingDD_7.0_[t0|1|2]_[TBase|Tbasemin]_sum *_weeks_before [1|2]\n\n\n\nRichardson cold accumulation index, calculated with a base temperature of 7.0º C; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a minimum temperature threshold above which the cold accumulation stopped (Tbasemin, -7ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the 2 weeks previous to the given day.\n\n\n\n\n\nChillingDD_7.0_[t0|1|2]_[TBase|Tbasemin]_sum * 1_weeks_after\n\n\n\nRichardson cold accumulation index, calculated with a base temperature of 7.0º C; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a minimum temperature threshold above which the cold accumulation stopped (Tbasemin, -7ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the next week to the given day.\n\n\n\n\n\nChillingDD_7.0_[t0|1|2]_ Utah _sum\n\n\n\nUtah cold accumulation index, calculated with a base temperature of 7.0º C; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a minimum temperature threshold above which the cold accumulation stopped (Tbasemin, -7ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum).\n\n\n\n\n\nChillingDD_7.0_[t0|1|2]_ Utah _sum *_weeks_before [1|2]\n\n\n\nRichardson cold accumulation index, calculated with a base temperature of 7.0º C; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a minimum temperature threshold above which the cold accumulation stopped (Tbasemin, -7ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the 2 weeks previous to the given day.\n\n\n\n\n\nChillingDD_7.0_[t0|1|2]_ Utah _sum * 1_weeks_after\n\n\n\nRichardson cold accumulation index, calculated with a base temperature of 7.0º C; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a minimum temperature threshold above which the cold accumulation stopped (Tbasemin, -7ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the next week to the given day.\n\n\n\n\n\nrad_sum\n\n\n\nAccumulated radaytion since the beginning of the season until the given date.\n\n\n\n\n\nrad_sum *_weeks_before [1|2]\n\n\n\nAccumulated radaytion since the beginning of the season until 1 or 2 weeks before the given date.\n\n\n\n\n\nrad_sum 1_weeks_after\n\n\n\nAccumulated radaytion since the beginning of the season until the next week after the given date.\n\n\n\n\n\nprecip_sum\n\n\n\nAccumulated precipitation since the beginning of the season until the given date.\n\n\n\n\n\nprecip_sum *_weeks_before [1|2]\n\n\n\nAccumulated precipitation since the beginning of the season until 1 or 2 weeks before the given date.\n\n\n\n\n\nprecip_sum 1_weeks_after\n\n\n\nAccumulated precipitation since the beginning of the season until the next week after the given date.\n\n\n\n\n\nwinkler_[4.5|10.0]_[t0|1|2]_[TBase|TbaseMAX]_sum\n\n\n\nWinkler heat accumulation index, calculated with a base temperature of 4.5ºC or 10.0 ºC; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a maximum temperature threshold over which the heat accumulation stopped (TbaseMAX, 35ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum).\n\n\n\n\n\nwinkler_[4.5|10.0]_[t0|1|2]_[TBase|TbaseMAX]_sum *_weeks_before [1|2]\n\n\n\nWinkler heat accumulation index, calculated with a base temperature of 4.5ºC or 10.0 ºC; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a maximum temperature threshold over which the heat accumulation stopped (TbaseMAX, 35ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the 2 weeks previous to the given day.\n\n\n\n\n\nwinkler_[4.5|10.0]_[t0|1|2]_[TBase|TbaseMAX]_sum * 1_weeks_after\n\n\n\nWinkler heat accumulation index, calculated with a base temperature of 4.5ºC or 10.0 ºC; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a maximum temperature threshold over which the heat accumulation stopped (TbaseMAX, 35ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the next week after the given day.\n\n\n\n\n\n \n\n \n\nThe GDD, Winkler and Chilling (Richardson and Utah) indexes are also calculated considering the contributions of the time units (periods) to the daily contribution. These fields (or columns of the file) have the same naming schema as their counterparts based on daily calculations but with the “cumm” suffix.\n\nFile “DIF phenologicalstages.csv” Description\n\nThis file contains a description of the different types of phenological stages considered. The fields are:\n\n\n\nitainnovaid: this is an identifier of the phenological stage.\n\nbbch: the number of stage in the BBCH phenological stage.\n\nDescripción BBCH: this is a textual description of the previous BBCH phenological stage.\n\n\nThe contents of the file are as follows:\n\n \n\n\n\n\n\n\nitainnovaid\n\n\n\nbbch\n\n\n\nDescripción BBCH\n\n\n\n\n\n0\n\n\n\n0\n\n\n\nWinter dormancy or resting period\n\n\n\n\n\n3\n\n\n\n63\n\n\n\nEarly flowering: 30% of flowerhoods fallen\n\n\n\n\n\n1\n\n\n\n11\n\n\n\nFirst leaf unfolded and spread away from shoot\n\n\n\n\n\n2\n\n\n\n15\n\n\n\n5 leaves unfolded\n\n\n\n\n\n4\n\n\n\n65\n\n\n\nFull flowering: 50% of flowerhoods fallen\n\n\n\n\n\n6\n\n\n\n71\n\n\n\nFruit set: young fruits begin to swell, remains of flowers\n\n\n\n\n\n5\n\n\n\n68\n\n\n\n80% of flowerhoods fallen\n\n\n\n\n\n7\n\n\n\n75\n\n\n\n50% of fruits have reached final size or fruit has reached 50% of final size\n\n\n\n\n\n8\n\n\n\n77\n\n\n\n70% of fruits have reached final size or fruit has reached 70% of final size\n\n\n\n\n\n9\n\n\n\n81\n\n\n\nBeginning of ripening or fruit colouration","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[{"awardTitle":"NEAT-AMBIENCE - Next-gEnerATion dAta Management to foster suitable Behaviors and the resilience of cItizens against modErN ChallEnges","funderName":"Agencia Estatal de Investigación","awardNumber":"PID2020-113037RB-I00","funderIdentifier":"10.13039/501100011033","funderIdentifierType":"Crossref Funder ID"},{"awardTitle":"COSMOS, Computer Science for Complex System modelling","funderName":"Gobierno de Aragón","awardNumber":"T64_23R","funderIdentifier":"10.13039/501100010067","funderIdentifierType":"Crossref Funder ID"}],"url":"https://zenodo.org/doi/10.5281/zenodo.17930722","contentUrl":null,"metadataVersion":14,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":2,"versionOfCount":1,"created":"2026-04-08T17:59:11Z","registered":"2026-04-08T17:59:11Z","published":null,"updated":"2026-05-09T17:34:01Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.17930723","type":"dois","attributes":{"doi":"10.5281/zenodo.17930723","identifiers":[{"identifier":"oai:zenodo.org:17930723","identifierType":"oai"}],"creators":[{"name":"Lacueva Pérez, Francisco José","nameType":"Personal","givenName":"Francisco José","familyName":"Lacueva Pérez","affiliation":["Instituto Tecnológico de Aragón"],"nameIdentifiers":[{"nameIdentifier":"0000-0003-0998-2939","nameIdentifierScheme":"ORCID"}]},{"name":"Labata Lezaun, Gorka","nameType":"Personal","givenName":"Gorka","familyName":"Labata Lezaun","affiliation":["Instituto Tecnológico de Aragón"],"nameIdentifiers":[{"nameIdentifier":"0000-0002-8634-4124","nameIdentifierScheme":"ORCID"}]},{"name":"Ilarri, Sergio","nameType":"Personal","givenName":"Sergio","familyName":"Ilarri","affiliation":["Universidad de Zaragoza"],"nameIdentifiers":[{"nameIdentifier":"0000-0002-7073-219X","nameIdentifierScheme":"ORCID"}]},{"name":"del Hoyo Alonso, Rafael","nameType":"Personal","givenName":"Rafael","familyName":"del Hoyo Alonso","affiliation":["Universidad San Jorge","Instituto Tecnológico de Aragón"],"nameIdentifiers":[{"nameIdentifier":"0000-0003-2755-5500","nameIdentifierScheme":"ORCID"}]},{"name":"Barriuso Vargas, Juan","nameType":"Personal","givenName":"Juan","familyName":"Barriuso Vargas","affiliation":["Universidad de Zaragoza"],"nameIdentifiers":[{"nameIdentifier":"0000-0003-2980-5454","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"A Multisource Grapevine Phenology Dataset for Smart Farming and AI Modeling"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"Agri-foodstuff","subjectScheme":"GEMET"},{"subject":"Machine learning","subjectScheme":"EuroSciVoc"},{"subject":"Supervised Machine Learning","subjectScheme":"MeSH"},{"subject":"Agriculture","subjectScheme":"EuroSciVoc"}],"contributors":[{"name":"Ilarri, Sergio","nameType":"Personal","givenName":"Sergio","familyName":"Ilarri","affiliation":["Universidad de Zaragoza"],"contributorType":"Editor","nameIdentifiers":[{"nameIdentifier":"0000-0002-7073-219X","nameIdentifierScheme":"ORCID"}]},{"name":"Labata Lezaun, Gorka","nameType":"Personal","givenName":"Gorka","familyName":"Labata Lezaun","affiliation":["Instituto Tecnológico de Aragón"],"contributorType":"DataCurator","nameIdentifiers":[{"nameIdentifier":"0000-0002-8634-4124","nameIdentifierScheme":"ORCID"}]},{"name":"del Hoyo Alonso, Rafael","nameType":"Personal","givenName":"Rafael","familyName":"del Hoyo Alonso","affiliation":["Universidad San Jorge","Instituto Tecnológico de Aragón"],"contributorType":"DataCurator","nameIdentifiers":[{"nameIdentifier":"0000-0003-2755-5500","nameIdentifierScheme":"ORCID"}]},{"name":"Barriuso Vargas, Juan","nameType":"Personal","givenName":"Juan","familyName":"Barriuso Vargas","affiliation":["Universidad de Zaragoza"],"contributorType":"DataCurator","nameIdentifiers":[{"nameIdentifier":"0000-0003-2980-5454","nameIdentifierScheme":"ORCID"}]},{"name":"Lacueva Pérez, Francisco José","nameType":"Personal","givenName":"Francisco José","familyName":"Lacueva Pérez","affiliation":["Instituto Tecnológico de Aragón"],"contributorType":"ContactPerson","nameIdentifiers":[{"nameIdentifier":"0000-0003-0998-2939","nameIdentifierScheme":"ORCID"}]},{"name":"Ilarri, Sergio","nameType":"Personal","givenName":"Sergio","familyName":"Ilarri","affiliation":["Universidad de Zaragoza"],"contributorType":"DataManager","nameIdentifiers":[]}],"dates":[{"date":"2026-01-10","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1016/j.compag.2025.110018","resourceTypeGeneral":"JournalArticle","relatedIdentifierType":"DOI"},{"relationType":"IsReferencedBy","relatedIdentifier":"https://webdiis.unizar.es/~silarri/prot/DREAM/index.html","resourceTypeGeneral":"Other","relatedIdentifierType":"URL"},{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.17930722","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":"1.0","rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Description\n\nArtificial Intelligence and Machine Learning rely on large, high-quality datasets for accurate and robust models, yet data scarcity remains a major challenge—especially in smart farming. Agricultural data are highly diverse and heterogeneous, complicating model development. Phenology modeling, a key application, studies how plant biological events relate to climate and seasons. Accurate phenology models improve crop quality, support climate adaptation, and guide decisions such as pesticide use and harvesting, enhancing environmental and economic sustainability.This study introduces a georeferenced dataset for Machine Learning-based grapevine phenology prediction across 3 Protected Designations of Origin in Arag’on, Spain. Developed by a multidisciplinary team, the dataset combines 9 datasets from 8 sources—including meteorological time series, field phenology observations, and Copernicus Sentinel-2 multispectral imagery—covering the period 2016–2022. It supports both physical and ML-based phenology modeling and facilitates knowledge extraction in agronomy and plant biology. Its relevance lies in its comprehensive scope, the inclusion of 9 phenological stages, and a rigorous methodology ensuring reproducibility. This framework enables the creation of similar datasets for otherregions or crops, advancing smart farming through scalable, data-driven solutions. We further anticipate its potential contribution to developing Foundation Models as well as to the creation.\n\nDataset Structure\n\nThe dataset contains 2 main CSV files and 1 supporting folder:\n\n\n\nDIF Description.pdf- Description of the data set.\n\nDIF phenologicaletages.csv: it contains the links from the phenologystageid values in the file “DIF GrapevinePehologyDataset.csv:  with the correspoding BBCH values.\n\nDIF GrapevinePehologyDataset.csv: it contains the dataset used to train the models we presented.\n\nMetadata: this folder contains the JSON files describing the dataset and its content:\n\n\n\nDIF_DataSetDescription.json: the description contained if “DIF Description.pdf” but in JSON format.\n\nDIF GrapevinePehologyDataset.json: contains the dataset presented in this paper which was used to train the models we presented in [51, 50]. We describe the content of the file in next paragraphs.\n\n\n\n\nIntended Use\n\nThe goal of this dataset is to enable the development of models for predicting grapevine phenology in the three Protected Designations of Origin in Aragón (Spain), using data from field observations, meteorological stations, and NDVI derived from Copernicus Sentinel-2 multispectral imagery. Additionally, it supports the calibration of physical models for these regions by including the calculation of cold and heat accumulation indices. These calculations are performed using the traditional start dates of January 1 and February of the corresponding year, as well as from the date when plants enter dormancy: the first autumn day when the maximum temperature does not exceed 10 °C.\n\nAccess Conditions: This dataset is publicly available under the terms of the Creative Commons Attribution 4.0 International license. \n\nSpecifications Table\n\n\n\n\n\n\nSubject\n\n\n\nSmart farming\n\n\n\n\n\nSpecific subject area\n\n\n\nThe dataset is based on data from 3 Protected Designations of Origin—Calatayud, Cariñena and Campo de Borja, —in Aragón, northeastern Spain. Built by merging 9 georeferenced time-series datasets from 8 data sources considering the period from 2016 to 2022. It includes meteorological data (measurements, estimates, and forecasts), qualitative field phenology observations, and Copernicus Sentinel-2 multispectral imagery.\n\n\n\n\n\nType of data\n\n\n\nAnalyzedFilteredProcessedMulti-source\n\n\n\n\n\nData collection\n\n\n\nData merged in the dataset is obtained from 9 georeferenced datatsets obtained from 8 data sources.  The datasets considered are:\n\n·         Red FARA phenological registry [1]: this dataset has restricted access.  It provides phenology field observations on the control parcels.\n\n·         Spanish Cadastral Registry (Catastro) [2]: it is used to normalize Red FARA records and to obtain the NDVI of the control parcels from Copernicus Sentinel 2 images.\n\n·         Aragón Open Data Common Agrarian Policy Registry (CAP) [3]: together with the Catastro data is used to normalize of the Red FARA records.\n\n·         SIAR [4] and Grapevine [5] climatic station networks provide meteorological data.\n\n·         ERA5 real climatic estimations [6] and ECMWF IFS forecast [7] data used to replace failures in climatic data and forecast data to perform predictions.\n\n·         Copernicus Sentinel 2 multispectral images [8]: these images are used to determine the NDVI of the control parcels used to create the dataset. \n\nFor accessing these dataset we used available APIs.  All they are public and provide open access. The 2 exceptions were Red FARA which has restricted access, and ERA5 data which was accessed using openMeteo API [8] which eased our work.  The access to the data and the transformations performed in them were coded in Python.  A deep explanation of the transformation performed can be obtained in [9].\n\n\n\n\n\nData source location\n\n\n\nCountry: Spain.Region: Aragón.Protected Designation of Origin: Calatayud, Campo de Borja, Cariñena.Coordinates: Parallelepiped defined by points (41.98107, −2.177578) and (41.166320, −0.922575) in WGS84 coordinates.\n\n\n\n\n\nData accessibility\n\n\n\nRepository name: Zenodo\n\nData identification number: 10.5281/zenodo.17930723 Direct URL to data: https://doi.org/10.5281/zenodo.17930723  \n\n\n\n\n\nReferences\n\n\n\n\n\n\n\n\n[1]\n\n\n\nGovernment of Aragón. Red FARA Home Page. Last access: January 10, 2026. 2026. url: http://web.redfara.es.\n\n\n\n\n\n[2]\n\n\n\nSpanish Treasury. Spanish Cadastral Registry Electronic Home Page. Last access: January 10, 2026. 2026. url: https://www.sedecatastro.gob.es/.\n\n\n\n\n\n[3]\n\n\n\nGovernment of Aragón. Aragón Open Data Home Page. Last access: January 10, 2026. 2026. url: https://opendata.aragon.es.\n\n\n\n\n\n[4]\n\n\n\nSpanish Ministry of Agriculture, Fisheries and Food. Agro-climatic Information System for Irrigation (SIAR) Home Page. Last access: January 10, 2026. 2026. url: https://eportal.mapa.gob.es//websiar/Inicio.aspx .\n\n\n\n\n\n[5]\n\n\n\nGrapevine Project Consortium. Grapevine Project Home Page. Grant agreement ID: 863463. https://grapevine-project.eu (Last access: August 8, 2024), https://web.archive.org/web/20230922054033/https://grapevine- project.eu (Last access: January 10, 2026), https://www.egi.eu/case-study/grapevine (Last access: January 10, 2026). 2022.\n\n\n\n\n\n[6]\n\n\n\nCopernicus Climate Change Service (C3S). ERA5 hourly data on single levels from 1959 to present. Last access: January 10, 2026. 2023. url: https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels?tab=overview .\n\n\n\n\n\n[7]\n\n\n\nEuropean Centre for Medium-Range Weather Forecasts (ECMWF). ECMWF Open Data. Last accessed January 10, 2026. 2026. url: https://www.ecmwf.int/en/forecasts/datasets/open-data .\n\n\n\n\n\n[8]\n\n\n\nF. Gascon et al. “Copernicus Sentinel-2 mission: products, algorithms and Cal/Val”. In: Earth Observing Systems XIX. Ed. by James J. Butler, Xiaoxiong (Jack) Xiong, and Xingfa Gu.SPIE, Sept. 2014, pp. 1–9. doi:10.1117/12.2062260. url: http://dx.doi.org/10.1117/12.2062260.\n\n\n\n\n\n[9]\n\n\n\nFrancisco Jos´e Lacueva-P´erez et al. “Developing machine learning models from multisourced real-world datasets to enhance smart-farming practices”. In: Computers and Electronics in Agriculture 231 (Apr. 2025), p. 110018. issn: 0168-1699. doi: 10.1016/j.compag.2025.110018. url: http://dx.doi.org/10.1016/j.compag.2025.110018 .\n\n\n\n\n\n \n\n\n\n\n\n \n\n \n\n\n\n\n \n\nFile “DIF_GrapevinePehologyDataset.csv” Description\n\nFile DIF_GrapevinePehologyDataset.csv contains the dataset presented in this paper.  Each of the records represents the data considered for a given parcel (vineyard) in each date. The following table provides a description of the fields contained in the dataset. For clarity, we simplified the table by using an abbreviated notation for the field names; specifically, for some field names we include an asterisk (“*”) with the name followed by a couple of numbers in brackets (“[…]”) that describe the range of integer values that can replace the “*” in the dataset; for example, we did this in fields which provide values of the given variable data for the n days before (days_after ) and after (days_adelante).  For clarity, we provide here some examples:\n\n·         tmed_min *_days_after  [1,13]: this name represents that the dataset contains all the fields tmed_min 1_days_after , tmed_min 2_days_after , ..., tmed_min 13_days_after , which represent, for the given field, the minimum temperature for each of the n days before the date of the record.\n\n·         wind_NE *_days_after [1,6]: this name represents that the dataset contains all the fields wind_NE 1_days_after, t wind_NE 2_days_after, ..., wind_NE 6_days_after, which represent, for the given field, the wind_NE index for each of the n days after the date of the record.\n\n·         gdd_4.5_t0_Tbase_sum *_weeks_before [1,2]: this name represents that the dataset contains all the fields gdd_4.5_t0_Tbase_sum 1_weeks_before and gdd_4.5_t0_Tbase_sum 2_weeks_before, which represent, for the given field, the GDD calculated using the base temperature 4.5º C and starting to accumulate at the beginning of the session.\n\nMoreover, we use “|” to denote choices (expressed within brackets “[…]”), which can represent several attributes. For example, “rad_[min|MAX|mean]” actually represents (in a condensed way) 3 different variables: “rad_min”, “rad_max” and “rad_mean”. Other notations can be interpreted similarly. The full list of variable names is shown in Appendix A.\n\n\n\n\n\n\nField Name (abbreviated notation)\n\n\n\nDescription\n\n\n\n\n\n\n\nphenologystageid\n\n\n\nId of the phenological stage of the parcel on the given date.  See file “DIF phenologicalstages.csv”.\n\n\n\n\n\nvariety\n\n\n\nGrapevine variety:  Cabernet Sauvignon, Chardonnay, Garnacha, Mazuela, Syrach, Tempranillo.\n\n\n\n\n\ncodigo\n\n\n\nId of the parcel in the Spanish Cadastral Registry.\n\n\n\n\n\nlongitude\n\n\n\nLongitude of the centroid of the parcel.\n\n\n\n\n\nlatitude\n\n\n\nLatitude of the centroid of the parcel.\n\n\n\n\n\naltitudeASL\n\n\n\nAltitudeASL of the centroid of the parcel.\n\n\n\n\n\nPDO_id\n\n\n\nId of the Protected Designation of Origin (PDO): Calatayud, Carinena and Campo de Borja.\n\n\n\n\n\ndate\n\n\n\nThe date of the record.\n\n\n\n\n\nstation\n\n\n\nThe name of the climatic station whose data are considered.\n\n\n\n\n\nseason\n\n\n\nThe season to which the record belongs.\n\n\n\n\n\nday\n\n\n\nThe DOY (day of the year).\n\n\n\n\n\n\"PDO_Borja\", \"PDO_Calatayud\", \"PDO_Carinena\", \"PDO_Somontano\"\n\n\n\nBoolean values which are true when the record corresponds to the given PDO.\n\n\n\n\n\n\"variety_CABERNET SAUVIGNON\", \"variety_CHARDONNAY\", \"variety_GARNACHA\", \"variety_MAZUELA\", \"variety_SYRACH\", \"variety_TEMPRANILLO\"\n\n\n\nBoolean values which are true when the record corresponds to a field with the given variety.\n\n \n\n\n\n\n\nmin, MAX, mean, std, medayn, diff\n\n\n\nValues derived from the NDVI indexes calculated for each parcel from the Copernicus Sentinel 2 multispectral images.  They represent the minimum, maximum, average, standard deviation, medayn and difference values.\n\n\n\n\n\ntmed_[min|MAX|mean]\n\n\n\n[Minimum|Maximum|Mean] temperature for the given date (ºC).\n\n\n\n\n\ntmed_[min|MAX|mean] *_days_after  [1,13]\n\n\n\n[Minimum|Maximum|Mean] temperatures for the 13 days before the given date.\n\n\n\n\n\ntmed_[min|MAX|mean] *_days_after [1,6]\n\n\n\n[Minimum|Maximum|Mean] temperatures for the 6 days following the given date.\n\n\n\n\n\nrad_[min|MAX|mean]\n\n\n\n[Minimum|Maximum|Mean] radaytion for the given date (W/m²).\n\n\n\n\n\nrad_[min|MAX|mean] *_days_after  [1,13]\n\n\n\n[Minimum|Maximum|Mean] radaytion for the 13 days before the given date.\n\n\n\n\n\nrad_[min|MAX|mean] *_days_after [1,6]\n\n\n\n[Minimum|Maximum|Mean] radaytion for the 6 days following the given date.\n\n\n\n\n\nhr_ mean\n\n\n\nAverage air relative humidity for the given date (%).\n\n\n\n\n\nhr_mean *_days_after  [1,13]\n\n\n\nAverage air relative humidity radaytion for the 13 days before the given date.\n\n\n\n\n\nhr_mean *_days_after [1,6]\n\n\n\nAverage air relative humidity radaytion for the 6 days following the given date.\n\n\n\n\n\nwind_[N|NE|E|SE|S|SW|W|NW] *_days_after  [1,13]\n\n\n\nWind index for the North, North-East, East, South-East, South, South-West, West, North-West area for the 13 days before the given date.\n\n\n\n\n\nind_[N|NE|E|SE|S|SW|W|NW] *_days_after [1,6]\n\n\n\nWind index for the North, North-East, East, South-East, South, South-West, West, North-West area for the 6 days following the given date.\n\n\n\n\n\ngdd_[4.5|10.0]_[t0|1|2]_[TBase|TbaseMAX]_sum\n\n\n\nGDD heat accumulation index, calculated with a base temperature of 4.5ºC or 10.0 ºC; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a maximum temperature threshold over which the heat accumulation stopped (TbaseMAX, 35ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum).\n\n\n\n\n\ngdd_[4.5|10.0]_[t0|1|2]_[TBase|TbaseMAX]_sum *_weeks_before [1|2]\n\n\n\nGDD heat accumulation index, calculated with a base temperature of 4.5ºC or 10.0 ºC; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a maximum temperature threshold over which the heat accumulation stopped (TbaseMAX, 35ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the 2 weeks previous to the given day.\n\n\n\n\n\ngdd_[4.5|10.0]_[t0|1|2]_[TBase|TbaseMAX]_sum * 1_weeks_after\n\n\n\nGDD heat accumulation index, calculated with a base temperature of 4.5ºC or 10.0 ºC; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a maximum temperature threshold over which the heat accumulation stopped (TbaseMAX, 35ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the next week to the given day.\n\n\n\n\n\nChillingDD_7.0_[t0|1|2]_[TBase|Tbasemin]_sum\n\n\n\nRichardson cold accumulation index, calculated with a base temperature of 7.0º C; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a minimum temperature threshold above which the cold accumulation stopped (Tbasemin, -7ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum).\n\n\n\n\n\nChillingDD_7.0_[t0|1|2]_[TBase|Tbasemin]_sum *_weeks_before [1|2]\n\n\n\nRichardson cold accumulation index, calculated with a base temperature of 7.0º C; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a minimum temperature threshold above which the cold accumulation stopped (Tbasemin, -7ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the 2 weeks previous to the given day.\n\n\n\n\n\nChillingDD_7.0_[t0|1|2]_[TBase|Tbasemin]_sum * 1_weeks_after\n\n\n\nRichardson cold accumulation index, calculated with a base temperature of 7.0º C; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a minimum temperature threshold above which the cold accumulation stopped (Tbasemin, -7ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the next week to the given day.\n\n\n\n\n\nChillingDD_7.0_[t0|1|2]_ Utah _sum\n\n\n\nUtah cold accumulation index, calculated with a base temperature of 7.0º C; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a minimum temperature threshold above which the cold accumulation stopped (Tbasemin, -7ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum).\n\n\n\n\n\nChillingDD_7.0_[t0|1|2]_ Utah _sum *_weeks_before [1|2]\n\n\n\nRichardson cold accumulation index, calculated with a base temperature of 7.0º C; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a minimum temperature threshold above which the cold accumulation stopped (Tbasemin, -7ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the 2 weeks previous to the given day.\n\n\n\n\n\nChillingDD_7.0_[t0|1|2]_ Utah _sum * 1_weeks_after\n\n\n\nRichardson cold accumulation index, calculated with a base temperature of 7.0º C; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a minimum temperature threshold above which the cold accumulation stopped (Tbasemin, -7ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the next week to the given day.\n\n\n\n\n\nrad_sum\n\n\n\nAccumulated radaytion since the beginning of the season until the given date.\n\n\n\n\n\nrad_sum *_weeks_before [1|2]\n\n\n\nAccumulated radaytion since the beginning of the season until 1 or 2 weeks before the given date.\n\n\n\n\n\nrad_sum 1_weeks_after\n\n\n\nAccumulated radaytion since the beginning of the season until the next week after the given date.\n\n\n\n\n\nprecip_sum\n\n\n\nAccumulated precipitation since the beginning of the season until the given date.\n\n\n\n\n\nprecip_sum *_weeks_before [1|2]\n\n\n\nAccumulated precipitation since the beginning of the season until 1 or 2 weeks before the given date.\n\n\n\n\n\nprecip_sum 1_weeks_after\n\n\n\nAccumulated precipitation since the beginning of the season until the next week after the given date.\n\n\n\n\n\nwinkler_[4.5|10.0]_[t0|1|2]_[TBase|TbaseMAX]_sum\n\n\n\nWinkler heat accumulation index, calculated with a base temperature of 4.5ºC or 10.0 ºC; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a maximum temperature threshold over which the heat accumulation stopped (TbaseMAX, 35ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum).\n\n\n\n\n\nwinkler_[4.5|10.0]_[t0|1|2]_[TBase|TbaseMAX]_sum *_weeks_before [1|2]\n\n\n\nWinkler heat accumulation index, calculated with a base temperature of 4.5ºC or 10.0 ºC; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a maximum temperature threshold over which the heat accumulation stopped (TbaseMAX, 35ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the 2 weeks previous to the given day.\n\n\n\n\n\nwinkler_[4.5|10.0]_[t0|1|2]_[TBase|TbaseMAX]_sum * 1_weeks_after\n\n\n\nWinkler heat accumulation index, calculated with a base temperature of 4.5ºC or 10.0 ºC; accumulated since the beginning of the season (t0), January the 1st of the date’s year (1) or February the 1st (2); considering a maximum temperature threshold over which the heat accumulation stopped (TbaseMAX, 35ºC) or not (TBase); and considering the daily contribution calculated considering the min temperature and max temperature of the given day (sum), for the next week after the given day.\n\n\n\n\n\n \n\n \n\nThe GDD, Winkler and Chilling (Richardson and Utah) indexes are also calculated considering the contributions of the time units (periods) to the daily contribution. These fields (or columns of the file) have the same naming schema as their counterparts based on daily calculations but with the “cumm” suffix.\n\nFile “DIF phenologicalstages.csv” Description\n\nThis file contains a description of the different types of phenological stages considered. The fields are:\n\n\n\nitainnovaid: this is an identifier of the phenological stage.\n\nbbch: the number of stage in the BBCH phenological stage.\n\nDescripción BBCH: this is a textual description of the previous BBCH phenological stage.\n\n\nThe contents of the file are as follows:\n\n \n\n\n\n\n\n\nitainnovaid\n\n\n\nbbch\n\n\n\nDescripción BBCH\n\n\n\n\n\n0\n\n\n\n0\n\n\n\nWinter dormancy or resting period\n\n\n\n\n\n3\n\n\n\n63\n\n\n\nEarly flowering: 30% of flowerhoods fallen\n\n\n\n\n\n1\n\n\n\n11\n\n\n\nFirst leaf unfolded and spread away from shoot\n\n\n\n\n\n2\n\n\n\n15\n\n\n\n5 leaves unfolded\n\n\n\n\n\n4\n\n\n\n65\n\n\n\nFull flowering: 50% of flowerhoods fallen\n\n\n\n\n\n6\n\n\n\n71\n\n\n\nFruit set: young fruits begin to swell, remains of flowers\n\n\n\n\n\n5\n\n\n\n68\n\n\n\n80% of flowerhoods fallen\n\n\n\n\n\n7\n\n\n\n75\n\n\n\n50% of fruits have reached final size or fruit has reached 50% of final size\n\n\n\n\n\n8\n\n\n\n77\n\n\n\n70% of fruits have reached final size or fruit has reached 70% of final size\n\n\n\n\n\n9\n\n\n\n81\n\n\n\nBeginning of ripening or fruit colouration","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[{"awardTitle":"NEAT-AMBIENCE - Next-gEnerATion dAta Management to foster suitable Behaviors and the resilience of cItizens against modErN ChallEnges","funderName":"Agencia Estatal de Investigación","awardNumber":"PID2020-113037RB-I00","funderIdentifier":"10.13039/501100011033","funderIdentifierType":"Crossref Funder ID"},{"awardTitle":"COSMOS, Computer Science for Complex System modelling","funderName":"Gobierno de Aragón","awardNumber":"T64_23R","funderIdentifier":"10.13039/501100010067","funderIdentifierType":"Crossref Funder ID"}],"url":"https://zenodo.org/doi/10.5281/zenodo.17930723","contentUrl":null,"metadataVersion":13,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":1,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":1,"created":"2026-04-08T17:59:11Z","registered":"2026-04-08T17:59:11Z","published":null,"updated":"2026-05-09T17:34:01Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20098784","type":"dois","attributes":{"doi":"10.5281/zenodo.20098784","identifiers":[],"creators":[{"name":"Leizerman, Samuel","nameType":"Personal","givenName":"Samuel","familyName":"Leizerman","nameIdentifiers":[{"nameIdentifier":"0009-0000-0133-2291","nameIdentifierScheme":"ORCID"}],"affiliation":[]}],"titles":[{"title":"It Is Bit: Unit-Testing HC Tokens Non-Markovian Causal Memory For Emergence of Lorentzian Metric, Non-Associativity, Zero-Divisor Dissolution and Other Primitives for Recovering Coord State Spacetime from AI Info Field"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"Information Theory","subjectScheme":"MeSH"},{"subject":"Statistical information","subjectScheme":"GEMET"},{"subject":"Artificial intelligence","subjectScheme":"EuroSciVoc"},{"subject":"Artificial Intelligence/standards","subjectScheme":"MeSH"},{"subject":"Condensed matter physics","subjectScheme":"EuroSciVoc"},{"subject":"Particle physics","subjectScheme":"EuroSciVoc"},{"subject":"Physical cosmology","subjectScheme":"EuroSciVoc"},{"subject":"Quantum physics","subjectScheme":"EuroSciVoc"},{"subject":"Physics","subjectScheme":"GEMET"},{"subject":"Physics","subjectScheme":"MeSH"},{"subject":"Mathematical physics","subjectScheme":"EuroSciVoc"},{"subject":"Transport (physics)","subjectScheme":"GEMET"},{"subject":"Theoretical physics","subjectScheme":"EuroSciVoc"},{"subject":"Statistics, Nonparametric","subjectScheme":"MeSH"},{"subject":"Statistical mechanics","subjectScheme":"EuroSciVoc"}],"contributors":[{"name":"Leizerman, Samuel","nameType":"Personal","givenName":"Samuel","familyName":"Leizerman","contributorType":"Researcher","nameIdentifiers":[{"nameIdentifier":"0009-0000-0133-2291","nameIdentifierScheme":"ORCID"}],"affiliation":[]}],"dates":[{"date":"2026-05-09","dateType":"Issued"},{"date":"2026-05-09","dateType":"Created"}],"language":null,"types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"CreativeWork","resourceType":"","resourceTypeGeneral":"Preprint"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20098784","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution Non Commercial 4.0 International","rightsUri":"https://creativecommons.org/licenses/by-nc/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-nc-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"The biquaternion algebra ℍ_ℂ = ℂ ⊗_ℝ ℍ ≅ M₂(ℂ) is associative and contains zero divisors. Equipped with a causal memory kernel and differential parallel transport, it recovers effective non-associativity, zero-divisor dissolution, and Lorentzian spacetime.\n\nConstruction. Tokens are embedded as biquaternions via the equation-of-state form qₙ = Aₙe^{aₙ} + Bₙe^{ibₙ}. Each interaction Pₓ · Pⱼ produces four complex components c_μ, contributing to the rank-4 informational stress-energy tensor as the Landauer-weighted outer product\n\nT̂^{μν}_{ρσ}(x) = (k_B T(x) ln 2 / V_cell(x)) Σᵢ₌₁^{N(x)} p̂^{μν}_{(i)} ⊗ p̂_{(i)ρσ},     p̂^{μν}_{(i)} = c_μ c̄_ν.\n\nThe Landauer prefactor k_B T(x) ln 2 / V_cell(x) is the energy density per erased bit at local informational temperature. The effective metric is extracted by double contraction g^{μν} = Σ_ρ T^{μρν}_ρ, symmetrized.\n\nSignature test. The induced g^{μν} is decomposed into Hermitian and anti-Hermitian projections under the biquaternionic conjugate q† = q̄₀ − q̄₁i − q̄₂j − q̄₃k:\n\nℋ(q) = ½(q + q†),     𝒜(q) = ½(q − q†).\n\nEigenvalue signs at each test point give the metric signature.\n\nResults (N = 6 token positions, all positions tested):\n\n  Projection      Signature   Hit rate  ℋ(g^{μν})       (1,3)       6/6  𝒜(g^{μν})       (3,1)       6/6  Full g^{μν}     (2,2)       6/6\n\nThe Hermitian projection yields Lorentzian signature, the anti-Hermitian yields the time-reversed Lorentzian, the full algebra sits on the neutral (2,2) signature characteristic of ℍ_ℂ as a real 4D algebra. Lorentzian signature is recovered by projection rather than postulated. Energy partition ‖ℋ‖² / ‖𝒜‖² ≈ 0.5 across all 15 pairwise interactions.\n\nA variable-order entropy functional S_{q(x)}[ρ] on S² breaks the KL-versus-resolution tradeoff and produces directional attention asymmetry. Fed biquaternionic source currents from the Hermitian-energy field E(x) = Σ_{y≠x} ‖ℋ(PₓP_y)‖², it develops a backward-looking bias Pearson-correlated at −0.86 ± 0.03 with E(x) across N = 10 to N = 2000, with bias decaying as N^{−0.42} matching the kernel exponent α_K = 0.5. Coupling is invariant under structured-vs-unstructured token controls.\n\nThe dynamical weight W(α) = Z_p + e^{iπα/2} Z_q decomposes into three sectors under U(1) rotation: geometric (period ∞), mixed (period 4), spectral (period 2). Under the Spin(5) unit, these map to its three smallest irreps: 𝟏, 𝟒, 𝟓. The biquaternionic U(1) closure is the rung-2 instance of a tower-wide closure on G₂ ⊂ F₄ ⊂ E₆ ⊂ E₇ ⊂ E₈ ⊂ E₈ × E₈ ↪ Cl(9,1) with winding pattern (1, 2, 4, 4, 4, 1) at the static level.\n\nThe closure equation has a structural reading that sharpens Wheeler's \"it from bit\" thesis (Wheeler, \"Information, Physics, Quantum: The Search for Links,\" 1990). The framework's lattice projection does not produce physical structure from bit-like substrate; the terminal closure of the framework's lattice projection is bit-like substrate, with the static closure dimension at 2⁹, the cap at 2⁴, the chain's spinor doublings at 2⁵, 2⁶, 2⁷, and the dynamic closure at 2¹⁰. It is not from bit. It is bit. The Cayley-Dickson tower and the magic-square exceptional chain forced by Hurwitz, Cartan, and Spin(9) cap minimality together produce a closure hierarchy in powers of 2, and the powers of 2 are not a substrate the physics reduces to but the structural arithmetic the closure operation itself satisfies.\n\nThe eight equivalence classes of the lattice projection sort into three observable-regime types corresponding to the three pieces of the cumulative winding 7 + 8 + 1 = 16: cap-anchored observables (electron mass at the actualization scale), trajectory observables (α_EM(μ) running across the bifurcation), and coherent-magnitude observables (ρ_Λ as the integrated coherent-winding fraction). These three regime types are the structural grammar in which the eight taxonomic groups are written.\n\nSections 1–14 establish the biquaternionic construction and signature, entropy, and dynamical weight results. Sections 16–18 develop the tower-wide closure and the static-residual cascade verified at the rung-2/rung-3 boundary, with v9.3 §17.8 extending the static Cl(9) closure to the dynamic Cl(9,1) ambient that supports memory and chirality through Majorana–Weyl reality conditions.\n\nAll computations are explicit, reproducible, and use only NumPy and SciPy.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20098784","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:27:59Z","registered":"2026-05-09T17:27:59Z","published":null,"updated":"2026-05-09T17:30:05Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20099323","type":"dois","attributes":{"doi":"10.5281/zenodo.20099323","identifiers":[{"identifier":"oai:zenodo.org:20099323","identifierType":"oai"}],"creators":[{"name":"Leizerman, Samuel","nameType":"Personal","givenName":"Samuel","familyName":"Leizerman","nameIdentifiers":[{"nameIdentifier":"0009-0000-0133-2291","nameIdentifierScheme":"ORCID"}],"affiliation":[]}],"titles":[{"title":"It Is Bit: Unit-Testing HC Tokens Non-Markovian Causal Memory For Emergence of Lorentzian Metric, Non-Associativity, Zero-Divisor Dissolution and Other Primitives for Recovering Coord State Spacetime from AI Info Field"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"Information Theory","subjectScheme":"MeSH"},{"subject":"Statistical information","subjectScheme":"GEMET"},{"subject":"Artificial intelligence","subjectScheme":"EuroSciVoc"},{"subject":"Artificial Intelligence/standards","subjectScheme":"MeSH"},{"subject":"Condensed matter physics","subjectScheme":"EuroSciVoc"},{"subject":"Particle physics","subjectScheme":"EuroSciVoc"},{"subject":"Physical cosmology","subjectScheme":"EuroSciVoc"},{"subject":"Quantum physics","subjectScheme":"EuroSciVoc"},{"subject":"Physics","subjectScheme":"GEMET"},{"subject":"Physics","subjectScheme":"MeSH"},{"subject":"Mathematical physics","subjectScheme":"EuroSciVoc"},{"subject":"Transport (physics)","subjectScheme":"GEMET"},{"subject":"Theoretical physics","subjectScheme":"EuroSciVoc"},{"subject":"Statistics, Nonparametric","subjectScheme":"MeSH"},{"subject":"Statistical mechanics","subjectScheme":"EuroSciVoc"}],"contributors":[{"name":"Leizerman, Samuel","nameType":"Personal","givenName":"Samuel","familyName":"Leizerman","contributorType":"Researcher","nameIdentifiers":[{"nameIdentifier":"0009-0000-0133-2291","nameIdentifierScheme":"ORCID"}],"affiliation":[]}],"dates":[{"date":"2026-05-09","dateType":"Issued"},{"date":"2026-05-09","dateType":"Created"}],"language":null,"types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"CreativeWork","resourceType":"","resourceTypeGeneral":"Preprint"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20098784","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution Non Commercial 4.0 International","rightsUri":"https://creativecommons.org/licenses/by-nc/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-nc-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"The biquaternion algebra ℍ_ℂ = ℂ ⊗_ℝ ℍ ≅ M₂(ℂ) is associative and contains zero divisors. Equipped with a causal memory kernel and differential parallel transport, it recovers effective non-associativity, zero-divisor dissolution, and Lorentzian spacetime.\n\nConstruction. Tokens are embedded as biquaternions via the equation-of-state form qₙ = Aₙe^{aₙ} + Bₙe^{ibₙ}. Each interaction Pₓ · Pⱼ produces four complex components c_μ, contributing to the rank-4 informational stress-energy tensor as the Landauer-weighted outer product\n\nT̂^{μν}_{ρσ}(x) = (k_B T(x) ln 2 / V_cell(x)) Σᵢ₌₁^{N(x)} p̂^{μν}_{(i)} ⊗ p̂_{(i)ρσ},     p̂^{μν}_{(i)} = c_μ c̄_ν.\n\nThe Landauer prefactor k_B T(x) ln 2 / V_cell(x) is the energy density per erased bit at local informational temperature. The effective metric is extracted by double contraction g^{μν} = Σ_ρ T^{μρν}_ρ, symmetrized.\n\nSignature test. The induced g^{μν} is decomposed into Hermitian and anti-Hermitian projections under the biquaternionic conjugate q† = q̄₀ − q̄₁i − q̄₂j − q̄₃k:\n\nℋ(q) = ½(q + q†),     𝒜(q) = ½(q − q†).\n\nEigenvalue signs at each test point give the metric signature.\n\nResults (N = 6 token positions, all positions tested):\n\n  Projection      Signature   Hit rate  ℋ(g^{μν})       (1,3)       6/6  𝒜(g^{μν})       (3,1)       6/6  Full g^{μν}     (2,2)       6/6\n\nThe Hermitian projection yields Lorentzian signature, the anti-Hermitian yields the time-reversed Lorentzian, the full algebra sits on the neutral (2,2) signature characteristic of ℍ_ℂ as a real 4D algebra. Lorentzian signature is recovered by projection rather than postulated. Energy partition ‖ℋ‖² / ‖𝒜‖² ≈ 0.5 across all 15 pairwise interactions.\n\nA variable-order entropy functional S_{q(x)}[ρ] on S² breaks the KL-versus-resolution tradeoff and produces directional attention asymmetry. Fed biquaternionic source currents from the Hermitian-energy field E(x) = Σ_{y≠x} ‖ℋ(PₓP_y)‖², it develops a backward-looking bias Pearson-correlated at −0.86 ± 0.03 with E(x) across N = 10 to N = 2000, with bias decaying as N^{−0.42} matching the kernel exponent α_K = 0.5. Coupling is invariant under structured-vs-unstructured token controls.\n\nThe dynamical weight W(α) = Z_p + e^{iπα/2} Z_q decomposes into three sectors under U(1) rotation: geometric (period ∞), mixed (period 4), spectral (period 2). Under the Spin(5) unit, these map to its three smallest irreps: 𝟏, 𝟒, 𝟓. The biquaternionic U(1) closure is the rung-2 instance of a tower-wide closure on G₂ ⊂ F₄ ⊂ E₆ ⊂ E₇ ⊂ E₈ ⊂ E₈ × E₈ ↪ Cl(9,1) with winding pattern (1, 2, 4, 4, 4, 1) at the static level.\n\nThe closure equation has a structural reading that sharpens Wheeler's \"it from bit\" thesis (Wheeler, \"Information, Physics, Quantum: The Search for Links,\" 1990). The framework's lattice projection does not produce physical structure from bit-like substrate; the terminal closure of the framework's lattice projection is bit-like substrate, with the static closure dimension at 2⁹, the cap at 2⁴, the chain's spinor doublings at 2⁵, 2⁶, 2⁷, and the dynamic closure at 2¹⁰. It is not from bit. It is bit. The Cayley-Dickson tower and the magic-square exceptional chain forced by Hurwitz, Cartan, and Spin(9) cap minimality together produce a closure hierarchy in powers of 2, and the powers of 2 are not a substrate the physics reduces to but the structural arithmetic the closure operation itself satisfies.\n\nThe eight equivalence classes of the lattice projection sort into three observable-regime types corresponding to the three pieces of the cumulative winding 7 + 8 + 1 = 16: cap-anchored observables (electron mass at the actualization scale), trajectory observables (α_EM(μ) running across the bifurcation), and coherent-magnitude observables (ρ_Λ as the integrated coherent-winding fraction). These three regime types are the structural grammar in which the eight taxonomic groups are written.\n\nSections 1–14 establish the biquaternionic construction and signature, entropy, and dynamical weight results. Sections 16–18 develop the tower-wide closure and the static-residual cascade verified at the rung-2/rung-3 boundary, with v9.3 §17.8 extending the static Cl(9) closure to the dynamic Cl(9,1) ambient that supports memory and chirality through Majorana–Weyl reality conditions.\n\nAll computations are explicit, reproducible, and use only NumPy and SciPy.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20099323","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:29:09Z","registered":"2026-05-09T17:29:09Z","published":null,"updated":"2026-05-09T17:29:09Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20038410","type":"dois","attributes":{"doi":"10.5281/zenodo.20038410","identifiers":[],"creators":[{"name":"Miotello, Federico","nameType":"Personal","givenName":"Federico","familyName":"Miotello","affiliation":["Politecnico di Milano"],"nameIdentifiers":[{"nameIdentifier":"0000-0003-2130-6423","nameIdentifierScheme":"ORCID"}]},{"name":"Ostan, Paolo","nameType":"Personal","givenName":"Paolo","familyName":"Ostan","nameIdentifiers":[{"nameIdentifier":"0009-0005-6366-7560","nameIdentifierScheme":"ORCID"}],"affiliation":[]},{"name":"Del Gaudio, Francesca","nameType":"Personal","givenName":"Francesca","familyName":"Del Gaudio","nameIdentifiers":[{"nameIdentifier":"0000-0002-2647-5907","nameIdentifierScheme":"ORCID"}],"affiliation":[]},{"name":"Comanducci, Luca","nameType":"Personal","givenName":"Luca","familyName":"Comanducci","affiliation":["Politecnico di Milano"],"nameIdentifiers":[{"nameIdentifier":"0000-0002-4167-5173","nameIdentifierScheme":"ORCID"}]},{"name":"Malvermi, Raffaele","nameType":"Personal","givenName":"Raffaele","familyName":"Malvermi","nameIdentifiers":[{"nameIdentifier":"0000-0002-5586-6376","nameIdentifierScheme":"ORCID"}],"affiliation":[]},{"name":"Pezzoli, Mirco","nameType":"Personal","givenName":"Mirco","familyName":"Pezzoli","affiliation":["Politecnico di Milano"],"nameIdentifiers":[{"nameIdentifier":"0000-0003-1296-0992","nameIdentifierScheme":"ORCID"}]},{"name":"Antonacci, Fabio","nameType":"Personal","givenName":"Fabio","familyName":"Antonacci","affiliation":["Politecnico di Milano"],"nameIdentifiers":[{"nameIdentifier":"0000-0003-4545-0315","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"THE SOUND OF THE VIOLIN'S HOME: A HIGHER-ORDER ROOM IMPULSE RESPONSE DATASET OF THE ARVEDI AUDITORIUM IN CREMONA"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"Acoustics","subjectScheme":"EuroSciVoc"},{"subject":"Acoustics","subjectScheme":"MeSH"},{"subject":"Acoustics","subjectScheme":"GEMET"},{"subject":"Sound transmission","subjectScheme":"GEMET"},{"subject":"Sound Recordings","subjectScheme":"MeSH"},{"subject":"Sound Localization","subjectScheme":"MeSH"},{"subject":"Sound measurement","subjectScheme":"GEMET"},{"subject":"Sound propagation","subjectScheme":"GEMET"}],"contributors":[],"dates":[{"date":"2026-05-05","dateType":"Issued"},{"date":"2026","dateType":"Created","dateInformation":"Acoustics"}],"language":"en","types":{"ris":"MPCT","bibtex":"misc","citeproc":"article","schemaOrg":"MediaObject","resourceType":"","resourceTypeGeneral":"Audiovisual"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20038410","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.20038410","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":2,"versionOfCount":1,"created":"2026-05-06T08:38:39Z","registered":"2026-05-06T08:38:39Z","published":null,"updated":"2026-05-09T17:27:59Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20093223","type":"dois","attributes":{"doi":"10.5281/zenodo.20093223","identifiers":[{"identifier":"oai:zenodo.org:20093223","identifierType":"oai"}],"creators":[{"name":"Bukáček, Jan","nameType":"Personal","givenName":"Jan","familyName":"Bukáček","affiliation":["Czech Academy of Sciences, Institute of Photonics and Electronics"],"nameIdentifiers":[{"nameIdentifier":"0009-0006-5288-0507","nameIdentifierScheme":"ORCID"}]},{"name":"Homola, Jiri","nameType":"Personal","givenName":"Jiri","familyName":"Homola","affiliation":["Czech Academy of Sciences, Institute of Photonics and Electronics"],"nameIdentifiers":[{"nameIdentifier":"0000-0001-6258-015X","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"Dataset for Large-area SPR imaging of nanoparticles using crossed diffraction gratings"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"Surface Plasmon Resonance","subjectScheme":"MeSH"},{"subject":"Diffraction grating"},{"subject":"Nanoparticles","subjectScheme":"MeSH"}],"contributors":[],"dates":[{"date":"2026-05-09","dateType":"Issued"}],"language":"en","types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20093222","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"The dataset provides relevant raw and processed data supporting the manuscript \"Large-area SPR imaging of nanoparticles using crossed diffraction gratings\". The manuscript presents a new surface plasmon resonance (SPR) imaging platform for the visualization of individual nanoparticles (NPs) based on a gold-coated crossed diffraction grating (CDG). The CDG couples incident light with the propagating surface plasmon (SP) and separates the reflected light from the signal generated by the scattering of SP on NPs, thereby reducing background intensity and improving image contrast. We demonstrate the visualization of gold and polystyrene NPs as small as 20 and 60 nm, respectively, with a field of view of ~20 mm², and show that the presented imaging approach enables visualization of smaller NPs across a larger field of view than conventional SPR imaging platforms.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[{"funderName":"Czech Science Foundation","awardNumber":"GX20–23787X","funderIdentifier":"10.13039/501100001824","funderIdentifierType":"Crossref Funder ID"},{"funderName":"Czech Science Foundation","awardNumber":"23-09170L","funderIdentifier":"10.13039/501100001824","funderIdentifierType":"Crossref Funder ID"}],"url":"https://zenodo.org/doi/10.5281/zenodo.20093223","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:25:25Z","registered":"2026-05-09T17:25:26Z","published":null,"updated":"2026-05-09T17:25:26Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.20093222","type":"dois","attributes":{"doi":"10.5281/zenodo.20093222","identifiers":[],"creators":[{"name":"Bukáček, Jan","nameType":"Personal","givenName":"Jan","familyName":"Bukáček","affiliation":["Czech Academy of Sciences, Institute of Photonics and Electronics"],"nameIdentifiers":[{"nameIdentifier":"0009-0006-5288-0507","nameIdentifierScheme":"ORCID"}]},{"name":"Homola, Jiri","nameType":"Personal","givenName":"Jiri","familyName":"Homola","affiliation":["Czech Academy of Sciences, Institute of Photonics and Electronics"],"nameIdentifiers":[{"nameIdentifier":"0000-0001-6258-015X","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"Dataset for Large-area SPR imaging of nanoparticles using crossed diffraction gratings"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[{"subject":"Surface Plasmon Resonance","subjectScheme":"MeSH"},{"subject":"Diffraction grating"},{"subject":"Nanoparticles","subjectScheme":"MeSH"}],"contributors":[],"dates":[{"date":"2026-05-09","dateType":"Issued"}],"language":"en","types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.20093222","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"The dataset provides relevant raw and processed data supporting the manuscript \"Large-area SPR imaging of nanoparticles using crossed diffraction gratings\". The manuscript presents a new surface plasmon resonance (SPR) imaging platform for the visualization of individual nanoparticles (NPs) based on a gold-coated crossed diffraction grating (CDG). The CDG couples incident light with the propagating surface plasmon (SP) and separates the reflected light from the signal generated by the scattering of SP on NPs, thereby reducing background intensity and improving image contrast. We demonstrate the visualization of gold and polystyrene NPs as small as 20 and 60 nm, respectively, with a field of view of ~20 mm², and show that the presented imaging approach enables visualization of smaller NPs across a larger field of view than conventional SPR imaging platforms.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[{"funderName":"Czech Science Foundation","awardNumber":"GX20–23787X","funderIdentifier":"10.13039/501100001824","funderIdentifierType":"Crossref Funder ID"},{"funderName":"Czech Science Foundation","awardNumber":"23-09170L","funderIdentifier":"10.13039/501100001824","funderIdentifierType":"Crossref Funder ID"}],"url":"https://zenodo.org/doi/10.5281/zenodo.20093222","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-05-09T17:25:25Z","registered":"2026-05-09T17:25:26Z","published":null,"updated":"2026-05-09T17:25:26Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}}],"meta":{"total":134131,"totalPages":400,"page":1},"links":{"self":"https://api.datacite.org/dois?query=subjects.subjectScheme%3AMeSH","next":"https://api.datacite.org/dois?page%5Bnumber%5D=2\u0026page%5Bsize%5D=25\u0026query=subjects.subjectScheme%3AMeSH"}}