cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.uxvyy9
title: Occurrence Download

description: A dataset containing 3860 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ficus variegata Blume"
 ]
}

 The dataset includes 3860 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082959-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7nuyn6
title: Occurrence Download

description: A dataset containing 6730 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Camelus dromedarius Linnaeus, 1758",
 "Country is Australia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6730 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082962-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/icpsr200038.v2
title: National Neighborhood Data Archive (NaNDA): Libraries by Census Tract and ZIP Code Tabulation Area, United States, 1992-2021
title: Version 2

description: This dataset contains measures of the number and density of libraries per United States Census Tract or ZIP Code Tabulation Area (ZCTA) from 1992 through 2021. The dataset includes four separate files for four different geographic areas (GIS shapefiles from the United States Census Bureau). The four geographies include:Census Tract 2010Census Tract 2020 ZIP Code Tabulation Area (ZCTA) 2010ZIP Code Tabulation Area (ZCTA) 2020 Information about which dataset to use can be found in the Usage Notes section of this document.
DOI: 10.5281/zenodo.14875094
title: UGC 4325 Rotation Curve Analysis Under Quantum Information Gravity (QIG)
title: QIG Rotation Curve Study for UGC 4325
title: Testing Quantum Information Gravity with UGC 4325
title: UGC 4325: A Case Study in Information-Based Gravity

description: This dataset presents the results of the Quantum Information Gravity (QIG) model applied to the UGC 4325 galaxy's rotation curve. The analysis follows previous studies on NGC 3198, NGC 2403, and UGC 128, demonstrating that QIG correctly predicts galactic rotational structures but exhibits a consistent ~10% offset in velocity magnitudes. This suggests a fundamental missing normalization factor in QIG's formulation, warranting further exploration.

Key files in this dataset include:



ugc_4325_qig_comparison.py – Python script implementing QIG for UGC 4325.

ugc_4325_qig_comparison_results.pdf – Numerical output comparing observed vs. QIG-predicted values.

ugc_4325_qig_vs_observed_comparison.pdf – Absolute and percentage velocity differences.

ugc_4325_qig_comparison.png – Graph of observed vs. predicted rotation curve.

ugc_4325_qig_report.tex – LaTeX documentation detailing methodology, findings, and future directions.

ugc_4325_qig_report.pdf – Formatted research document.


This study further supports the hypothesis that gravitational effects emerge from structured information, aligning with QIG’s previous successes while revealing an unexplained scaling factor.
DOI: 10.5281/zenodo.14875095
title: UGC 4325 Rotation Curve Analysis Under Quantum Information Gravity (QIG)
title: QIG Rotation Curve Study for UGC 4325
title: Testing Quantum Information Gravity with UGC 4325
title: UGC 4325: A Case Study in Information-Based Gravity

description: This dataset presents the results of the Quantum Information Gravity (QIG) model applied to the UGC 4325 galaxy's rotation curve. The analysis follows previous studies on NGC 3198, NGC 2403, and UGC 128, demonstrating that QIG correctly predicts galactic rotational structures but exhibits a consistent ~10% offset in velocity magnitudes. This suggests a fundamental missing normalization factor in QIG's formulation, warranting further exploration.

Key files in this dataset include:



ugc_4325_qig_comparison.py – Python script implementing QIG for UGC 4325.

ugc_4325_qig_comparison_results.pdf – Numerical output comparing observed vs. QIG-predicted values.

ugc_4325_qig_vs_observed_comparison.pdf – Absolute and percentage velocity differences.

ugc_4325_qig_comparison.png – Graph of observed vs. predicted rotation curve.

ugc_4325_qig_report.tex – LaTeX documentation detailing methodology, findings, and future directions.

ugc_4325_qig_report.pdf – Formatted research document.


This study further supports the hypothesis that gravitational effects emerge from structured information, aligning with QIG’s previous successes while revealing an unexplained scaling factor.
DOI: 10.15468/dl.ew7ne3
title: Occurrence Download

description: A dataset containing 883 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Axis porcinus (Zimmermann, 1780)",
 "Country is Australia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 883 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082965-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wsgazw
title: Occurrence Download

description: A dataset containing 9750 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Equisetum fluviatile L.",
 "Geometry POLYGON((-8.00174339329464 54.1998526673513, 0.202120938926891 54.1998526673513, 0.202120938926891 61.2628565887411, -8.00174339329464 61.2628565887411, -8.00174339329464 54.1998526673513))",
 "CoordinateUncertaintyInMeters is 0,101",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 9750 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082964-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28052399
title: <b>Emergence of hybrid </b><b><i>Escherichia coli</i></b><b> with dual disease manifestations in i</b><b>ntestinal and extraintestinal niches</b>-<b>Raw Data</b>

description: <i>Escherichia coli</i>, a significant zoonotic pathogen, continuously evolves to produce hybrid strains with diverse pathogenic characteristics, threatening public health. Hybrid <i>E. coli </i>strains can cause multiple diseases in various tissues within a single individual or among different hosts with diverse genetic backgrounds. These strains have been reported to exhibit higher virulence, enhanced infectiousness, and increased resistance to environmental clearance. Here we identified a hybrid aEPEC/ExPEC isolate, PE164, from the blood and bloody stool of a piglet with severe diarrhea, which exhibited both intestinal and extraintestinal pathogenic traits. Monitoring the emergence of PE164-like hybrids in porcine-derived <i>E. coli </i>is crucial for animal production and public health safety. Phylogenetic and virulence gene analyses of nearly 300 clinical isolates from diseased pigs revealed eight hybrid strains categorized into four types, with significant variations in pathogenicity identified by <i>in vitro</i> and <i>in vivo</i> models. Notably, two O108 isolates, PE150 and PE164, were classified as highly virulent strains. A fused gene cluster of colanic acid and O108 antigen biosynthesis (CAO108) was identified as a key determinant of their extraintestinal pathogenicity, raising concerns about O-antigens linked to other exopolysaccharide components to create new high virulence factors. Additionally, the type III secretion system (T3SS), a classic pathway for pathogenic <i>E. coli</i> to optimally colonize the host gut, enhanced bacterial immune evasion and contributed to the extraintestinal pathogenicity of PE164. These findings underscore the prevalence of hybrid pathogenic <i>E. coli</i> strains in pigs, presenting new challenges for disease control.
DOI: 10.6084/m9.figshare.28052399.v3
title: <b>Emergence of hybrid </b><b><i>Escherichia coli</i></b><b> with dual disease manifestations in i</b><b>ntestinal and extraintestinal niches</b>-<b>Raw Data</b>

description: <i>Escherichia coli</i>, a significant zoonotic pathogen, continuously evolves to produce hybrid strains with diverse pathogenic characteristics, threatening public health. Hybrid <i>E. coli </i>strains can cause multiple diseases in various tissues within a single individual or among different hosts with diverse genetic backgrounds. These strains have been reported to exhibit higher virulence, enhanced infectiousness, and increased resistance to environmental clearance. Here we identified a hybrid aEPEC/ExPEC isolate, PE164, from the blood and bloody stool of a piglet with severe diarrhea, which exhibited both intestinal and extraintestinal pathogenic traits. Monitoring the emergence of PE164-like hybrids in porcine-derived <i>E. coli </i>is crucial for animal production and public health safety. Phylogenetic and virulence gene analyses of nearly 300 clinical isolates from diseased pigs revealed eight hybrid strains categorized into four types, with significant variations in pathogenicity identified by <i>in vitro</i> and <i>in vivo</i> models. Notably, two O108 isolates, PE150 and PE164, were classified as highly virulent strains. A fused gene cluster of colanic acid and O108 antigen biosynthesis (CAO108) was identified as a key determinant of their extraintestinal pathogenicity, raising concerns about O-antigens linked to other exopolysaccharide components to create new high virulence factors. Additionally, the type III secretion system (T3SS), a classic pathway for pathogenic <i>E. coli</i> to optimally colonize the host gut, enhanced bacterial immune evasion and contributed to the extraintestinal pathogenicity of PE164. These findings underscore the prevalence of hybrid pathogenic <i>E. coli</i> strains in pigs, presenting new challenges for disease control.
DOI: 10.6084/m9.figshare.28052399.v4
title: <b>Emergence of hybrid </b><b><i>Escherichia coli</i></b><b> with dual disease manifestations in i</b><b>ntestinal and extraintestinal niches</b>-<b>Raw Data</b>

description: <i>Escherichia coli</i>, a significant zoonotic pathogen, continuously evolves to produce hybrid strains with diverse pathogenic characteristics, threatening public health. Hybrid <i>E. coli </i>strains can cause multiple diseases in various tissues within a single individual or among different hosts with diverse genetic backgrounds. These strains have been reported to exhibit higher virulence, enhanced infectiousness, and increased resistance to environmental clearance. Here we identified a hybrid aEPEC/ExPEC isolate, PE164, from the blood and bloody stool of a piglet with severe diarrhea, which exhibited both intestinal and extraintestinal pathogenic traits. Monitoring the emergence of PE164-like hybrids in porcine-derived <i>E. coli </i>is crucial for animal production and public health safety. Phylogenetic and virulence gene analyses of nearly 300 clinical isolates from diseased pigs revealed eight hybrid strains categorized into four types, with significant variations in pathogenicity identified by <i>in vitro</i> and <i>in vivo</i> models. Notably, two O108 isolates, PE150 and PE164, were classified as highly virulent strains. A fused gene cluster of colanic acid and O108 antigen biosynthesis (CAO108) was identified as a key determinant of their extraintestinal pathogenicity, raising concerns about O-antigens linked to other exopolysaccharide components to create new high virulence factors. Additionally, the type III secretion system (T3SS), a classic pathway for pathogenic <i>E. coli</i> to optimally colonize the host gut, enhanced bacterial immune evasion and contributed to the extraintestinal pathogenicity of PE164. These findings underscore the prevalence of hybrid pathogenic <i>E. coli</i> strains in pigs, presenting new challenges for disease control.
DOI: 10.5281/zenodo.14874927
title: QIG Offset Analysis Across Galaxies: NGC 3198, NGC 2403, UGC 128
title: Systematic Offset in Quantum Information Gravity Across Galactic Rotation Curves
title: QIG vs. Observed Rotation Curve Deviation in SPARC Data
title: Investigating the Discrepancy in QIG Galactic Rotation Predictions

description: This dataset presents an analysis of the offset between observed galactic rotation curves and those predicted by Quantum Information Gravity (QIG). Using publicly available SPARC dataset values for NGC 3198, NGC 2403, and UGC 128, we computed the percentage deviation between observed and QIG-predicted velocities at multiple radii.

Findings show a consistent ~10% offset, suggesting a systematic correction is needed for QIG’s scaling parameter 𝛼(r). The dataset is made publicly available to document the methodology, ensure transparency, and support further refinement in the QIG model.

The provided scripts allow independent verification and modification to test alternative 𝛼(r) structures.

Files:

- qig_offset_analysis.py – Python script performing multi-galaxy offset analysis- qig_offset_analysis_results.txt – Numerical offset comparison for each galaxy- qig_offset_analysis.png – Graphical representation of QIG vs. Observed offset
DOI: 10.5281/zenodo.14874928
title: QIG Offset Analysis Across Galaxies: NGC 3198, NGC 2403, UGC 128
title: Systematic Offset in Quantum Information Gravity Across Galactic Rotation Curves
title: QIG vs. Observed Rotation Curve Deviation in SPARC Data
title: Investigating the Discrepancy in QIG Galactic Rotation Predictions

description: This dataset presents an analysis of the offset between observed galactic rotation curves and those predicted by Quantum Information Gravity (QIG). Using publicly available SPARC dataset values for NGC 3198, NGC 2403, and UGC 128, we computed the percentage deviation between observed and QIG-predicted velocities at multiple radii.

Findings show a consistent ~10% offset, suggesting a systematic correction is needed for QIG’s scaling parameter 𝛼(r). The dataset is made publicly available to document the methodology, ensure transparency, and support further refinement in the QIG model.

The provided scripts allow independent verification and modification to test alternative 𝛼(r) structures.

Files:

- qig_offset_analysis.py – Python script performing multi-galaxy offset analysis- qig_offset_analysis_results.txt – Numerical offset comparison for each galaxy- qig_offset_analysis.png – Graphical representation of QIG vs. Observed offset
DOI: 10.15468/dl.2uwjr7
title: Occurrence Download

description: A dataset containing 406952 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2025-06-05",
 "EventDate is less than or equal to 2025-07-05",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 }
 ]
}

 The dataset includes 406952 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082950-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nhfcj5
title: Occurrence Download

description: A dataset containing 71 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Artocarpus blancoi (Elmer) Merr."
 ]
}

 The dataset includes 71 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082966-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14874409
title: UGC 128: Testing Quantum Information Gravity Against Observed Rotation Curves
title: UGC 128 Galactic Rotation Curve in QIG Framework
title: Quantum Information Gravity & UGC 128 Rotation Data
title: Information-Based Gravity: Application to UGC 128

description: This dataset contains the analysis of the spiral galaxy UGC 128, comparing its observed rotation curve (SPARC dataset) against predictions made by Quantum Information Gravity (QIG). The results show a strong alignment in shape, confirming that QIG accurately models galactic rotation without requiring dark matter. However, a consistent 10% offset at all radii suggests a proportional correction is needed in the scaling factor α(r)\alpha(r)α(r). This dataset includes the full computational analysis, graphical representation, and structured research documentation.

Version 1.0 – Initial Release of UGC 128 Analysis in QIG Framework

Files:

✅ ugc_128_qig_comparison.py – Python script implementing QIG model for UGC 128✅ ugc_128_qig_comparison.png – Graph comparing observed vs. QIG-predicted rotation curve✅ ugc_128_qig_comparison_results.txt – Numerical results for QIG vs. observed rotation✅ ugc_128_qig_vs_observed_comparison.txt – Absolute & percentage differences between observed data and QIG model✅ ugc_128_qig_sparc_data.csv – Source dataset formatted for QIG computations✅ ugc_128_qig_report.tex – LaTeX research documentation detailing methodology & findings✅ ugc_128_qig_report.pdf – Formatted academic research paper for submission
DOI: 10.5281/zenodo.14874410
title: UGC 128: Testing Quantum Information Gravity Against Observed Rotation Curves
title: UGC 128 Galactic Rotation Curve in QIG Framework
title: Quantum Information Gravity & UGC 128 Rotation Data
title: Information-Based Gravity: Application to UGC 128

description: This dataset contains the analysis of the spiral galaxy UGC 128, comparing its observed rotation curve (SPARC dataset) against predictions made by Quantum Information Gravity (QIG). The results show a strong alignment in shape, confirming that QIG accurately models galactic rotation without requiring dark matter. However, a consistent 10% offset at all radii suggests a proportional correction is needed in the scaling factor α(r)\alpha(r)α(r). This dataset includes the full computational analysis, graphical representation, and structured research documentation.

Version 1.0 – Initial Release of UGC 128 Analysis in QIG Framework

Files:

✅ ugc_128_qig_comparison.py – Python script implementing QIG model for UGC 128✅ ugc_128_qig_comparison.png – Graph comparing observed vs. QIG-predicted rotation curve✅ ugc_128_qig_comparison_results.txt – Numerical results for QIG vs. observed rotation✅ ugc_128_qig_vs_observed_comparison.txt – Absolute & percentage differences between observed data and QIG model✅ ugc_128_qig_sparc_data.csv – Source dataset formatted for QIG computations✅ ugc_128_qig_report.tex – LaTeX research documentation detailing methodology & findings✅ ugc_128_qig_report.pdf – Formatted academic research paper for submission
DOI: 10.13145/bacdive14478.20251217.10
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0082128.10fu
title: SH0082128.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive14479.20241212.9.2
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive14479.20251217.10
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0082129.10fu
title: SH0082129.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive14480.20241212.9.2
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0082130.10fu
title: SH0082130.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive14480.20251217.10
title: Staphylococcus aureus Rosenbach 1884

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.