cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.rc35gv
title: Occurrence Download

description: A dataset containing 1229 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cephalaria gigantea (Ledeb.) Bobrov",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1229 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078614-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gwvc62
title: Occurrence Download

description: A dataset containing 32474 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-129.63867 26.11599,-104.85352 26.11599,-104.85352 53.01478,-129.63867 53.01478,-129.63867 26.11599))",
 "TaxonKey is Liliaceae",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 32474 records from 81 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047176-181108115102211/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h6xcbt
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Gamasomorpha lalana Suman, 1965)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044168-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3yxnr2
title: Occurrence Download

description: A dataset containing 2853 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Typha ×glauca Godr.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2853 records from 72 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078618-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ku26zg
title: Occurrence Download

description: A dataset containing 39 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Muraenolepis orangiensis Vaillant, 1888"
 ]
}

 The dataset includes 39 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0147515-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wfvfem
title: Occurrence Download

description: A dataset containing 13859 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Odobenus rosmarus (Linnaeus, 1758)"
 ]
}

 The dataset includes 13859 records from 71 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047177-181108115102211/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.az27t8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-94.48242 20.28693,-95.18555 12.194,-78.13477 2.61823,-76.72852 10.98865,-81.12305 12.5374,-81.65039 16.45084,-85.69336 18.29612,-85.69336 21.76358,-90.43945 22.90173,-94.48242 20.28693))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Myiopagis viridicata (Vieillot, 1817)"
 ]
}

 The dataset includes 0 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0345397-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x6a8qp
title: Occurrence Download

description: A dataset containing 1345 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Squalus chloroculus Last, White & Motomura, 2007, Brachaelurus colcloughi Ogilby, 1908, Squatina albipunctata Last & White, 2008, Cephaloscyllium albipinnum Last, Motomura & White, 2008)"
 ]
}

 The dataset includes 1345 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078632-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nbc5bw
title: Occurrence Download

description: A dataset containing 10763 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sardinops sagax (Jenyns, 1842)"
 ]
}

 The dataset includes 10763 records from 104 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047180-181108115102211/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tbcvgr
title: Occurrence Download

description: A dataset containing 3774 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "MediaType is Image",
 "TaxonKey is Bouteloua dactyloides (Nutt.) Columbus"
 ]
}

 The dataset includes 3774 records from 71 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044167-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15178685
title: Raw digital holograms recorded with the Son of SHAMU (SoS) field instrument in the Boulby Mines

description: Summary:

These holograms were taken with the Son of SHAMU digital holographic microsope (DHM) field instrument.

Our goal is to measure the swimming motion (3D tracks) of the halophilic bacteria.

Holograms allow us to measure the electric field, and to perform volumetric reconstruction with no moving parts.

The images are digital holograms which means an image that is modulated by a series of interference fringes which cover the whole array.

The images were taken at 15 frames per second. 

Physical Parameters of the data set:

The detector used to record the data is the Mako G-503B. The detector pixel size is 2.2 um, and the array size is 5.7 mm x 4.28 mm. The optical magnification is 10. At the object plane each pixel is 0.220 nm, and the field-of-view is 570 um x 428 um

The data size is 2592 x 1944 pixels.  

Data reduction:

The data reduction can be done using numerical analysis software like Matlab, Mathematica or Python.

There is also a free software suite available to reduce the data called DHMx. 

https://github.com/dhm-org/dhm_suite

Results of these measurements

This collection of holograms allowed us to reconstruct the swimming pattern of the halophilic bacteria as described in our paper: Architecture and field operation of a portable digital holographic microscope for in situ measurements of bacterial motility
DOI: 10.5281/zenodo.15178686
title: Raw digital holograms recorded with the Son of SHAMU (SoS) field instrument in the Boulby Mines

description: Summary:

These holograms were taken with the Son of SHAMU digital holographic microsope (DHM) field instrument.

Our goal is to measure the swimming motion (3D tracks) of the halophilic bacteria.

Holograms allow us to measure the electric field, and to perform volumetric reconstruction with no moving parts.

The images are digital holograms which means an image that is modulated by a series of interference fringes which cover the whole array.

The images were taken at 15 frames per second. 

Physical Parameters of the data set:

The detector used to record the data is the Mako G-503B. The detector pixel size is 2.2 um, and the array size is 5.7 mm x 4.28 mm. The optical magnification is 10. At the object plane each pixel is 0.220 nm, and the field-of-view is 570 um x 428 um

The data size is 2592 x 1944 pixels.  

Data reduction:

The data reduction can be done using numerical analysis software like Matlab, Mathematica or Python.

There is also a free software suite available to reduce the data called DHMx. 

https://github.com/dhm-org/dhm_suite

Results of these measurements

This collection of holograms allowed us to reconstruct the swimming pattern of the halophilic bacteria as described in our paper: Architecture and field operation of a portable digital holographic microscope for in situ measurements of bacterial motility
DOI: 10.14272/sa-fuhff-uhfffadpsc-lpekggxmpw-uhfffadpsc-nuhff-nuhff-nuhff-zzz/chmo0000593.7
title: 1H nuclear magnetic resonance spectroscopy (1H NMR)
title: reaction/SA-FUHFF-UHFFFADPSC-LPEKGGXMPW-UHFFFADPSC-NUHFF-NUHFF-NUHFF-ZZZ

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR)
DOI: 10.14272/wozvhxuhuflzgk-uhfffaoysa-n.8
title: dimethyl benzene-1,4-dicarboxylate
title: InChI=1S/C10H10O4/c1-13-9(11)7-3-5-8(6-4-7)10(12)14-2/h3-6H,1-2H3

description: This is a physical chemical entity[CHEBI_24431] associated with a molecule[CHEBI_25367].
 The molecule[CHEBI_25367] can be described by the following structural desciptors[cheminf_000085]:
 InChI descriptor[cheminf_000113]: InChI=1S/C10H10O4/c1-13-9(11)7-3-5-8(6-4-7)10(12)14-2/h3-6H,1-2H3, and canonical SMILES descriptor[cheminf_000007]: COC(=O)c1ccc(cc1)C(=O)OC, and by the IUPAC name[cheminf_000107]: dimethyl benzene-1,4-dicarboxylate.
 
 The physical chemical entity[CHEBI_24431] has a component solvent[CHEBI_46787] which is described by the canonical SMILES descriptor[cheminf_000007]:
 
 The physical chemical entity[CHEBI_24431] has the following Sample ID as registered in the research data repository chemotion (www.chemotion-repository.net, https://doi.org/10.25504/FAIRsharing.iagXcR): CRS-50621

 The physical chemical entity[CHEBI_24431] can be described by the physical descriptors [CHEMINF_000025]:
 Melting point descriptor[CHEMINF_000256]: 
 Boiling point descriptor[CHEMINF_000257]: 
 Refractive index descriptor[CHEMINF_000253]:

 The physical chemical entity[CHEBI_24431] can be further described by the following assays[OBI:0000070][CHMO:0001133]:
 
 CHMO:0000593 | 1H nuclear magnetic resonance spectroscopy (1H NMR)
 
 The physical chemical entity[CHEBI_24431] was deposited to the Molecule Archive of the Karlsruhe Insitute of Technology (KIT) with the following Sample ID: 

 Used ontologies:
 CHEBI - Chemical Entities of Biological Interest
 CHEMINF - chemical information ontology (information entities about chemical entities)
 CHMO - Chemical Methods Ontology
 OBI - Ontology for Biomedical Investigations
DOI: 10.14272/sa-fuhff-uhfffadpsc-wptvlkdyav-uhfffadpsc-nuhff-nuhff-nuhff-zzz/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR)
title: reaction/SA-FUHFF-UHFFFADPSC-WPTVLKDYAV-UHFFFADPSC-NUHFF-NUHFF-NUHFF-ZZZ

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR)
DOI: 10.14272/wozvhxuhuflzgk-uhfffaoysa-n/chmo0000593.7
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (dimethyl benzene-1,4-dicarboxylate)
title: InChI=1S/C10H10O4/c1-13-9(11)7-3-5-8(6-4-7)10(12)14-2/h3-6H,1-2H3

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR)
DOI: 10.17632/ztvznksg73
title: Datasets_Article-170729

description: The basic data that became the material for the research manuscript "Enhancing the Competitiveness of Metal Casting Clusters in Indonesia through IoT-Based Digital Quality Control: A Smart Manufacturing Perspective".
DOI: 10.17632/ztvznksg73.1
title: Datasets_Article-170729

description: The basic data that became the material for the research manuscript "Enhancing the Competitiveness of Metal Casting Clusters in Indonesia through IoT-Based Digital Quality Control: A Smart Manufacturing Perspective".
DOI: 10.14272/wozvhxuhuflzgk-uhfffaoysa-n/chmo0000593.9
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (dimethyl benzene-1,4-dicarboxylate)
title: InChI=1S/C10H10O4/c1-13-9(11)7-3-5-8(6-4-7)10(12)14-2/h3-6H,1-2H3

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR)
DOI: 10.14272/wozvhxuhuflzgk-uhfffaoysa-n.10
title: dimethyl benzene-1,4-dicarboxylate
title: InChI=1S/C10H10O4/c1-13-9(11)7-3-5-8(6-4-7)10(12)14-2/h3-6H,1-2H3

description: This is a physical chemical entity[CHEBI_24431] associated with a molecule[CHEBI_25367].
 The molecule[CHEBI_25367] can be described by the following structural desciptors[cheminf_000085]:
 InChI descriptor[cheminf_000113]: InChI=1S/C10H10O4/c1-13-9(11)7-3-5-8(6-4-7)10(12)14-2/h3-6H,1-2H3, and canonical SMILES descriptor[cheminf_000007]: COC(=O)c1ccc(cc1)C(=O)OC, and by the IUPAC name[cheminf_000107]: dimethyl benzene-1,4-dicarboxylate.
 
 The physical chemical entity[CHEBI_24431] has a component solvent[CHEBI_46787] which is described by the canonical SMILES descriptor[cheminf_000007]:
 
 The physical chemical entity[CHEBI_24431] has the following Sample ID as registered in the research data repository chemotion (www.chemotion-repository.net, https://doi.org/10.25504/FAIRsharing.iagXcR): CRS-50642

 The physical chemical entity[CHEBI_24431] can be described by the physical descriptors [CHEMINF_000025]:
 Melting point descriptor[CHEMINF_000256]: 
 Boiling point descriptor[CHEMINF_000257]: 
 Refractive index descriptor[CHEMINF_000253]:

 The physical chemical entity[CHEBI_24431] can be further described by the following assays[OBI:0000070][CHMO:0001133]:
 
 CHMO:0000593 | 1H nuclear magnetic resonance spectroscopy (1H NMR)
 
 The physical chemical entity[CHEBI_24431] was deposited to the Molecule Archive of the Karlsruhe Insitute of Technology (KIT) with the following Sample ID: 

 Used ontologies:
 CHEBI - Chemical Entities of Biological Interest
 CHEMINF - chemical information ontology (information entities about chemical entities)
 CHMO - Chemical Methods Ontology
 OBI - Ontology for Biomedical Investigations
DOI: 10.14272/sa-fuhff-uhfffadpsc-lpekggxmpw-uhfffadpsc-nuhff-nuhff-nuhff-zzz/chmo0000593.8
title: 1H nuclear magnetic resonance spectroscopy (1H NMR)
title: reaction/SA-FUHFF-UHFFFADPSC-LPEKGGXMPW-UHFFFADPSC-NUHFF-NUHFF-NUHFF-ZZZ

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR)
DOI: 10.17632/b26sb6wy2h.4
title: A Paradigm Shift: A Complete, Rigorous Framework for the Yang-Mills Mass Gap Solution (UIDT)

description: This report introduces the Unified Information-Density Theory (UIDT)--a comprehensive and fully rigorous framework proposing a definitive solution to the Yang-Mills Existence and Mass Gap Millennium Prize Problem.

The central breakthrough lies in coupling the Yang-Mills field to a fundamental Information-Density Scalar Field, S(x). This approach fundamentally shifts the focus of physics toward an information-based foundation. Crucially, the coupling term is explicitly defined, enabling a non-perturbative derivation of the mass gap.

This work is designed to withstand the highest level of mathematical and physical scrutiny.

KEY SCIENTIFIC ACHIEVEMENTS

We invite the global research community to critically assess the following documented claims and results:

1. Proof of Existence and Consistency:
The framework establishes mathematical existence through a full constructive proof (GNS construction), demonstrating consistency by satisfying all Wightman and Osterwalder-Schrader axioms. The theory is also shown to be asymptotically safe, with UV-divergences tamed by a derived non-trivial fixed point.

2. Non-Perturbative Mass Gap Derivation:
The mass gap (Delta approx 1.7 GeV) emerges naturally from the vacuum fluctuations of the Information-Density field (VSC &gt; 0), satisfying the primary requirement of the Millennium Prize Problem.

3. Robust Empirical and Numerical Validation:
The model's predictions show a high degree of fidelity, demonstrating 92-99% agreement with established Lattice-QCD data. The report includes all necessary details for numerical verification, covering lattice implementation, Wilson loops analysis, and complete error analysis derived from standard Monte Carlo and renormalization group methods.

4. Falsifiability and Experimental Tests:
The UIDT is fully testable. It offers specific, novel predictions related to entropy gradient measurements that are suggested to be achievable using current experimental technology, providing a clear path to validation or falsification.

IMPLICATIONS: Beyond the Mass Gap

The successful validation of the UIDT suggests a profound transformation in fundamental physics.

The model implies that mass is not an intrinsic property but an emergent phenomenon derived entirely from information-density dynamics. This re-contextualizes E=mc^2 as a specific case within a broader information-theoretic reality.

We look forward to critical review, open dialogue, and collaborative exploration of this framework.

UIDT — Philipp Rietz © 2025 | CC BY 4.0 | DOI: osf.io/wdyxc | ORCID: 0009-0007-4307-1609

10.17605/OSF.IO/WDYXC


KEYWORDS:

Physics, Math,Yang-Mills Existence and Mass Gap, Millennium Prize Problem, Unified Information-Density Theory (UIDT), Constructive Quantum Field Theory, Asymptotic Safety, Lattice QCD, Mass Generation, Information Theory, Osterwalder-Schrader Axioms, Falsifiable Physics.
DOI: 10.48440/enmap.2021.001
title: Bode catchment, MOSES heatwave, Germany 2020 - An EnMAP Flight Campaign

description: The dataset is composed of Neo HySpex (VNIR & SWIR) and Telops Hyper-Cam (LWIR) hyperspectral imagery acquired during the MOSES GFZ/FUB/UFZ airborne campaign on August 6th, 2020 over the test area Oschersleben covering parts of the Bode catchment in the northern foreland of the Harz Mountain, Central Germany. The study area covers an ecological transect including three TERENO climate stations/flux towers ranging from forest sites (Hohes Holz) to lowland meadows (Grosses Bruch) to intensively used agricultural land (Hordorf). The survey was conducted within the frame of the Helmholtz program MOSES (Modular Observation Solutions for Earth Systems) heatwave event chain, which overall objective is to monitor heat extremes and drought events. In particular, the 2020 MOSES heatwave campaign over the Oschersleben test site aimed at an GFZ/UFZ intercalibration comparison measurements between different hyperspectral instruments flown on same day with different platforms and altitude, and test impact of different workflows on resulting data. This publication contains the GFZ VNIR-SWIR-LWIR hyperspectral dataset. It includes 1) 17 HySpex cloud-free flight lines already mosaicked in orthorectified reflectance, covering the VNIR to SWIR wavelength regions (0.4-2.5 μm) with 408 spectral bands, and 2) a composite of Hyper-Cam 1956 frames processed to surface temperature and spectral emissivity covering the LWIR (7.7 – 11.7 μm) in 125 bands. The dataset also includes Level 2A EnMAP-like reflectance imagery simulated using the end-to-end Simulation tool (EeteS). Associated field data and UFZ hyperspectral data are included in related publications of this campaign.
description: EnMAP Flight Campaigns Technical Report
DOI: 10.5281/zenodo.15192301
title: PANTHER Challenge: Public Training Dataset

description: This dataset represents the PANTHER Challenge: Public Training Dataset, comprising a total of 509 anonymized MR images. The dataset is divided into two distinct tasks. For Task 1, which focuses on diagnostic MR images, the dataset includes 459 scans acquired at Radboud University Medical Center. Within these, 92 images are T1-weighted contrast-enhanced arterial phase scans, supplemented by 367 scans acquired using multiple sequences. These images are intended to support the segmentation of pancreatic tumors in a diagnostic setting.

For Task 2, the focus shifts to treatment planning, specifically using MR-Linac images. This dataset contains 50 MR-Linac scans acquired at Odense University Hospital. By incorporating these images, the challenge aims to develop and evaluate AI models capable of segmenting pancreatic tumors in the context of radiotherapy planning.
DOI: 10.5281/zenodo.15192302
title: PANTHER Challenge: Public Training Dataset

description: This dataset represents the PANTHER Challenge: Public Training Dataset, comprising a total of 509 anonymized MR images. The dataset is divided into two distinct tasks. For Task 1, which focuses on diagnostic MR images, the dataset includes 459 scans acquired at Radboud University Medical Center. Within these, 92 images are T1-weighted contrast-enhanced arterial phase scans, supplemented by 367 scans acquired using multiple sequences. These images are intended to support the segmentation of pancreatic tumors in a diagnostic setting.

For Task 2, the focus shifts to treatment planning, specifically using MR-Linac images. This dataset contains 50 MR-Linac scans acquired at Odense University Hospital. By incorporating these images, the challenge aims to develop and evaluate AI models capable of segmenting pancreatic tumors in the context of radiotherapy planning.
DOI: 10.5517/cc139hb7
title: CCDC 1022018: Experimental Crystal Structure Determination

description: Related Article: R.Destro, F.Merati|1995|Acta Crystallogr.,Sect.B:Struct.Sci.|51|559|doi:10.1107/S0108768195005088
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc47c90
title: CCDC 126241: Experimental Crystal Structure Determination

description: Related Article: T.Lis, L.B.Jerzykiewicz|1996|Acta Crystallogr.,Sect.C:Cryst.Struct.Commun.|52|129|doi:10.1107/S0108270195009905
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc47cb1
title: CCDC 126242: Experimental Crystal Structure Determination

description: Related Article: T.Lis, L.B.Jerzykiewicz|1996|Acta Crystallogr.,Sect.C:Cryst.Struct.Commun.|52|129|doi:10.1107/S0108270195009905
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc49ydr
title: CCDC 128724: Experimental Crystal Structure Determination

description: Related Article: S.O.Sommerer, A.J.Jircitano, B.L.Westcott, K.A.Abboud, J.A.K.Bauer|1997|Acta Crystallogr.,Sect.C:Cryst.Struct.Commun.|53|707|doi:10.1107/S0108270197000218
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc49yfs
title: CCDC 128725: Experimental Crystal Structure Determination

description: Related Article: S.O.Sommerer, A.J.Jircitano, B.L.Westcott, K.A.Abboud, J.A.K.Bauer|1997|Acta Crystallogr.,Sect.C:Cryst.Struct.Commun.|53|707|doi:10.1107/S0108270197000218
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.