cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.16086743
title: Astrocytoma Grades

description: This dataset comprises MRI brain scans collected from the Department of Radiology (Diagnostics) at Bahawal Victoria Hospital, Bahawalpur, Pakistan. It includes data from 343 patients diagnosed with varying grades of astrocytoma (Grades I–IV).

Each patient's dataset consists of T1-weighted (T1w), T2-weighted (T2w), and Fluid Attenuated Inversion Recovery (FLAIR) sequences. T1w and FLAIR scans were acquired in the axial plane, while T2w scans were captured in both axial and sagittal planes. This multi-directional acquisition enhances the model’s adaptability to different clinical settings.
DOI: 10.5281/zenodo.16086744
title: Astrocytoma Grades

description: This dataset comprises MRI brain scans collected from the Department of Radiology (Diagnostics) at Bahawal Victoria Hospital, Bahawalpur, Pakistan. It includes data from 343 patients diagnosed with varying grades of astrocytoma (Grades I–IV).

Each patient's dataset consists of T1-weighted (T1w), T2-weighted (T2w), and Fluid Attenuated Inversion Recovery (FLAIR) sequences. T1w and FLAIR scans were acquired in the axial plane, while T2w scans were captured in both axial and sagittal planes. This multi-directional acquisition enhances the model’s adaptability to different clinical settings.
DOI: 10.15468/dl.absj8n
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Brassica nigra",
 "Country is Viet Nam",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006380-250717081556266/datasets/export for details.
DOI: 10.15468/dl.a5h4jw
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salix triandra",
 "Country is Australia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006383-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h3j2bw
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Ammodramus savannarum)",
 "Country is one of (Åland Islands, Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Republic of, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom of Great Britain and Northern Ireland)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006384-250717081556266/datasets/export for details.
DOI: 10.15468/dl.6a98w2
title: Occurrence Download

description: A dataset containing 132 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Senecio eruciformis"
 ]
}

 The dataset includes 132 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006385-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57899/hmc7-g534
title: How do pre-service English teachers talk about (potentially problematic) teaching materials?
title: Wie sprechen angehende Englischlehrer:innen über (potenziell problematische) Unterrichtsinhalte?

description: The data set consists of ten transcripts of ten group discussions conducted with participants of a seminar on „Racism in English as a Foreign Language (EFL) teaching" in the English and American Studies programme at a university in Germany. The seminar combined theoretical inputs on critical anti-racism with practical phases of critically analysing textbooks. The participants were both Bachelor's and Master's students aiming to become teachers of English. Five group discussions took place before the seminar (pre-discussions), and five were conducted 5 weeks into the seminar (post-discussions). The pre-discussions lasted between 16:21 and 17:44 minutes and the post-discussions lasted between 10:17 and 14:01 minutes. The impulses for the group discussion, on the basis of which the students exchange ideas, are two different, unrelated textbook pages on the topic „USA" at both times. The participants were not assigned to fixed groups and their identity was not tracked between the two points in time. The students are labelled consecutively from the first pre-discussion to the last post-discussion (S1 - S36), so that a student has two different labels in pre and post. There were different group compositions at both times.
DOI: 10.15468/dl.3kc8vn
title: Occurrence Download

description: A dataset containing 230 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Farsetia occidentalis"
 ]
}

 The dataset includes 230 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006386-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16089226
title: Effective stellar yields - suplementary material

description: Suplementary material for Kemp and Kaur 2025: Binary stellar evolution yields in galactic chemical evolution calculations.

Includes pre-computed, machine-readable effective stellar yield tables suitable for GCE calculations, as well as a complete database of figures for all isotopes.

Underlying code can be found here:

https://github.com/Alex162/BEEST---Binary-Evolution-and-Effective-Stellar-yields-Tookit
DOI: 10.15468/dl.gz8awm
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eichhornia crassipes",
 "Country is Türkiye",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006390-250717081556266/datasets/export for details.
DOI: 10.5281/zenodo.16090734
title: "Octave Cosmology: A Unified Field Theory Based on Walter Russell's Two-Way Universe"

description: This paper presents a novel unified field theory inspired by Walter Russell’s two-way universe, which challenges the conventional Big Bang model by proposing a rhythmic, balanced interchange of light, pressure, and electric motion as the foundation of all physical phenomena. We formalize Russell’s wave-field cosmology into a testable mathematical framework, leveraging Fourier analysis, fractal geometry, and hydrogen resonance to reconstruct the periodic table as a sequence of harmonic octaves. The model predicts atomic radii, spectral lines, and energy levels with high fidelity, unifying phenomena such as zero-point energy, scalar fields, torsion dynamics, and fractal coherence. Comparisons with contemporary models, including Randell Mills’ hydrino theory, Nassim Haramein’s torus dynamics, and Dan Winter’s phase conjugation, reveal synergies and extend Russell’s vision. This work offers a groundbreaking perspective on matter formation and a potential bridge to consciousness coherence, with implications for physics, cosmology, and interdisciplinary research. Keywords: unified field theory, wave-field cosmology, octave periodicity, fractal geometry, hydrogen resonance, zero-point energy.
DOI: 10.5281/zenodo.16090735
title: "Octave Cosmology: A Unified Field Theory Based on Walter Russell's Two-Way Universe"

description: This paper presents a novel unified field theory inspired by Walter Russell’s two-way universe, which challenges the conventional Big Bang model by proposing a rhythmic, balanced interchange of light, pressure, and electric motion as the foundation of all physical phenomena. We formalize Russell’s wave-field cosmology into a testable mathematical framework, leveraging Fourier analysis, fractal geometry, and hydrogen resonance to reconstruct the periodic table as a sequence of harmonic octaves. The model predicts atomic radii, spectral lines, and energy levels with high fidelity, unifying phenomena such as zero-point energy, scalar fields, torsion dynamics, and fractal coherence. Comparisons with contemporary models, including Randell Mills’ hydrino theory, Nassim Haramein’s torus dynamics, and Dan Winter’s phase conjugation, reveal synergies and extend Russell’s vision. This work offers a groundbreaking perspective on matter formation and a potential bridge to consciousness coherence, with implications for physics, cosmology, and interdisciplinary research. Keywords: unified field theory, wave-field cosmology, octave periodicity, fractal geometry, hydrogen resonance, zero-point energy.
DOI: 10.5281/zenodo.16090637
title: METHANOBACTERIA IN MUD VOLCANO ECOSYSTEMS: DIVERSITY AND ADAPTATION MECHANISMS

description: This dataset includes methane production responses to various substrates (acetate, methanol, methylamine, and Hв‚‚/COв‚‚)in sediment samples collected from different mud volcano sites. It supports microbial diversity and methanogenesis studies.Columns:- MV_Station: Name of the mud volcano station- Depth_mbsf: Depth in meters below sea floor- Methane_Production_<Substrate>: Qualitative methane production level (+++, ++, +, *, -, etc.)
DOI: 10.5281/zenodo.16090638
title: METHANOBACTERIA IN MUD VOLCANO ECOSYSTEMS: DIVERSITY AND ADAPTATION MECHANISMS

description: This dataset includes methane production responses to various substrates (acetate, methanol, methylamine, and Hв‚‚/COв‚‚)in sediment samples collected from different mud volcano sites. It supports microbial diversity and methanogenesis studies.Columns:- MV_Station: Name of the mud volcano station- Depth_mbsf: Depth in meters below sea floor- Methane_Production_<Substrate>: Qualitative methane production level (+++, ++, +, *, -, etc.)
DOI: 10.15468/dl.rsquva
title: Occurrence Download

description: A dataset containing 32259 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Eragrostis curvula"
 ]
}

 The dataset includes 32259 records from 365 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006382-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/sxrzmf9zjb
title: Grassland carbon cycle pathways

description: This dataset quantifies the key carbon (C) cycling pathways within a typical steppe ecosystem across four distinct stocking rates, encompassing primary production, plant partitioning, livestock-mediated fluxes, and soil respiratory losses. Specifically, it includes gross primary productivity (GPP), aboveground and belowground plant biomass carbon (AGBC and BGBC), aboveground and root litter carbon (including their respective decomposed fractions), and autotrophic respiration partitioned into aboveground and belowground components. Furthermore, the dataset tracks grazing-induced carbon transfers, such as forage intake, livestock respiratory carbon, methane emissions (CH4-C), excreta carbon (and its subsequent decomposition), and carbon sequestration into animal products. Finally, total soil respiration (R_s) and root exudates are recorded to provide a comprehensive mass balance of carbon allocation and greenhouse gas dynamics under varying grazing intensities.
DOI: 10.17632/sxrzmf9zjb.1
title: Grassland carbon cycle pathways

description: This dataset quantifies the key carbon (C) cycling pathways within a typical steppe ecosystem across four distinct stocking rates, encompassing primary production, plant partitioning, livestock-mediated fluxes, and soil respiratory losses. Specifically, it includes gross primary productivity (GPP), aboveground and belowground plant biomass carbon (AGBC and BGBC), aboveground and root litter carbon (including their respective decomposed fractions), and autotrophic respiration partitioned into aboveground and belowground components. Furthermore, the dataset tracks grazing-induced carbon transfers, such as forage intake, livestock respiratory carbon, methane emissions (CH4-C), excreta carbon (and its subsequent decomposition), and carbon sequestration into animal products. Finally, total soil respiration (R_s) and root exudates are recorded to provide a comprehensive mass balance of carbon allocation and greenhouse gas dynamics under varying grazing intensities.
DOI: 10.17632/vs9jgz76yt
title: A High-Dimensional Machine Learning Framework for Robust Vehicle Failure Prediction and Predictive Maintenance

description: The rapid digitalization of modern vehicles has led to the generation of high-dimensional sensor data, enabling advanced predictive maintenance and early failure detection strategies. Traditional diagnostic systems often fail to capture complex nonlinear patterns inherent in such data. This study proposes a robust machine learning benchmarking framework for vehicle failure prediction using a dataset containing 171 sensor-based attributes.
Seven supervised learning algorithms are evaluated under a consistent preprocessing and validation strategy: Logistic Regression, Support Vector Machine, k-Nearest Neighbors, Naïve Bayes, Decision Tree, Random Forest, and Neural Network. Performance is assessed using accuracy, precision, recall, F1-score, and Receiver Operating Characteristic–Area Under Curve (ROC–AUC) metrics to ensure robustness in imbalanced classification settings.
Experimental results reveal that ensemble-based methods, particularly Random Forest, significantly outperform linear, probabilistic, and distance-based models, achieving an AUROC of 0.983 on the test set. The findings provide empirical support for ensemble learning as a reliable and scalable solution for real-world vehicle failure diagnostics and predictive maintenance applications.
DOI: 10.17632/vs9jgz76yt.1
title: A High-Dimensional Machine Learning Framework for Robust Vehicle Failure Prediction and Predictive Maintenance

description: The rapid digitalization of modern vehicles has led to the generation of high-dimensional sensor data, enabling advanced predictive maintenance and early failure detection strategies. Traditional diagnostic systems often fail to capture complex nonlinear patterns inherent in such data. This study proposes a robust machine learning benchmarking framework for vehicle failure prediction using a dataset containing 171 sensor-based attributes.
Seven supervised learning algorithms are evaluated under a consistent preprocessing and validation strategy: Logistic Regression, Support Vector Machine, k-Nearest Neighbors, Naïve Bayes, Decision Tree, Random Forest, and Neural Network. Performance is assessed using accuracy, precision, recall, F1-score, and Receiver Operating Characteristic–Area Under Curve (ROC–AUC) metrics to ensure robustness in imbalanced classification settings.
Experimental results reveal that ensemble-based methods, particularly Random Forest, significantly outperform linear, probabilistic, and distance-based models, achieving an AUROC of 0.983 on the test set. The findings provide empirical support for ensemble learning as a reliable and scalable solution for real-world vehicle failure diagnostics and predictive maintenance applications.
DOI: 10.5281/zenodo.18737746
title: Data Set to: Vacuum Hydrodynamics and the Emergence of the Drag Constant

description: User Guide: Running Python Scripts Seismic Precursor Pipeline

This pipeline uses the Localized Density Gradient Rule to identify the viscous increased viscous density of the vacuum fluid that precedes major earthquakes.

Step 1: Data Ingestion



Action: Place the raw NASA IONEX files (e.g., c1pg0530.26i) in your IONEX_raw folder.

Instruction: These files contain the Total Electron Content (TEC) of the ionosphere, which we use as a proxy for vacuum fluid density.


Step 2: The Global Scanner (TEC_Phonon_Scanner.py)



Action: Run the scanner to process the raw NASA data.

Instruction: This script performs a full 360-degree sweep to ensure the  high-viscosity vacuum fluid region  has no blind spots.

Result: It generates the TEC_Grid_Output.csv, a master map of global vacuum potential.


Step 3: The Latitudinal_Phonon_Filter_V2 Filter (Latitudinal_Phonon_Filter_V2.py)



Action: Run the filter to apply the v2 " Latitudinal_Phonon_Filter_V2.py."

Instruction: This is the most critical step. It applies the Inverse-Square Dissipation Law ($\rho_{v}(r)=\rho_{v0}(\frac{r_{0}}{r})^{2}$) to strip away solar noise.

Result: It isolates the high-value 3-sigma anomalies that are mathematically proven to be localized stress signatures.


Step 4: The Hit-Rate Analysis (daily_hit_rate.py)



Action: Run the analysis script to verify results.

Instruction: This script cross-references your isolated precursors with the live USGS earthquake feed using the established 28-hour seismic lag ($t_{lag}$).

Validation: In our latest operational run, this pipeline achieved 100.0% accuracy for forward predictions 

@ official Canadian patent 3302634
DOI: 10.17632/g3x4phfr3r
title: Creative-GNN NACA0012 2D Compressible Flow Dataset and Reproducibility Package

description: This repository provides the Creative-GNN NACA0012 2D compressible-flow dataset and reproducibility package used in the associated Journal of Computational Physics submission.

Scope and physics setting:
- Geometry: NACA0012, 2D, fixed fine unstructured mesh.
- Solver/data source: SU2-based steady RANS workflow.
- Condition coverage: compressible range Ma 0.8–4.0 (archived dataset range).
- Main paper evaluation: compressible, supersonic-focused subset Ma 1.3–4.0.

Contents:
- Graph-ready processed CFD data (node/edge tables, case metadata, and boundary-related files).
- Case manifests and split definitions for controlled train/validation/test evaluation.
- Reproducibility artifacts for the reported experiments, including aggregated metrics and figure-generation inputs for field error, pressure/Cp comparisons, near-wall vs global diagnostics, shock-related diagnostics, and pressure-only force-coefficient error summaries.
- Creative-GNN code package for training/evaluation and post-processing scripts.
- Configuration files and run manifests to trace preprocessing, training, and evaluation settings.

Reproducibility goal:
This package is organized so that readers can reproduce the manuscript’s main quantitative results and figures from the archived processed data and scripts, without reconstructing the full CFD pipeline from scratch.

Repository curation note:
To satisfy repository size constraints, this version is a curated reproducibility release. It includes the files required for the published results; optional large add-ons (if any) are listed explicitly in the package documentation.

Citation:
Deng, Yuxuan (2026), “Creative-GNN NACA0012 2D Compressible Flow Dataset and Reproducibility Package”, Mendeley Data, V1, doi:10.17632/g3x4phfr3r.1
DOI: 10.5281/zenodo.18737745
title: Data Set to: Vacuum Hydrodynamics and the Emergence of the Drag Constant

description: User Guide: Running Python Scripts Seismic Precursor Pipeline

This pipeline uses the Localized Density Gradient Rule to identify the viscous increased viscous density of the vacuum fluid that precedes major earthquakes.

Step 1: Data Ingestion



Action: Place the raw NASA IONEX files (e.g., c1pg0530.26i) in your IONEX_raw folder.

Instruction: These files contain the Total Electron Content (TEC) of the ionosphere, which we use as a proxy for vacuum fluid density.


Step 2: The Global Scanner (TEC_Phonon_Scanner.py)



Action: Run the scanner to process the raw NASA data.

Instruction: This script performs a full 360-degree sweep to ensure the  high-viscosity vacuum fluid region  has no blind spots.

Result: It generates the TEC_Grid_Output.csv, a master map of global vacuum potential.


Step 3: The Latitudinal_Phonon_Filter_V2 Filter (Latitudinal_Phonon_Filter_V2.py)



Action: Run the filter to apply the v2 " Latitudinal_Phonon_Filter_V2.py."

Instruction: This is the most critical step. It applies the Inverse-Square Dissipation Law ($\rho_{v}(r)=\rho_{v0}(\frac{r_{0}}{r})^{2}$) to strip away solar noise.

Result: It isolates the high-value 3-sigma anomalies that are mathematically proven to be localized stress signatures.


Step 4: The Hit-Rate Analysis (daily_hit_rate.py)



Action: Run the analysis script to verify results.

Instruction: This script cross-references your isolated precursors with the live USGS earthquake feed using the established 28-hour seismic lag ($t_{lag}$).

Validation: In our latest operational run, this pipeline achieved 100.0% accuracy for forward predictions 

@ official Canadian patent 3302634
DOI: 10.17632/g3x4phfr3r.1
title: Creative-GNN NACA0012 2D Compressible Flow Dataset and Reproducibility Package

description: This repository provides the Creative-GNN NACA0012 2D compressible-flow dataset and reproducibility package used in the associated Journal of Computational Physics submission.

Scope and physics setting:
- Geometry: NACA0012, 2D, fixed fine unstructured mesh.
- Solver/data source: SU2-based steady RANS workflow.
- Condition coverage: compressible range Ma 0.8–4.0 (archived dataset range).
- Main paper evaluation: compressible, supersonic-focused subset Ma 1.3–4.0.

Contents:
- Graph-ready processed CFD data (node/edge tables, case metadata, and boundary-related files).
- Case manifests and split definitions for controlled train/validation/test evaluation.
- Reproducibility artifacts for the reported experiments, including aggregated metrics and figure-generation inputs for field error, pressure/Cp comparisons, near-wall vs global diagnostics, shock-related diagnostics, and pressure-only force-coefficient error summaries.
- Creative-GNN code package for training/evaluation and post-processing scripts.
- Configuration files and run manifests to trace preprocessing, training, and evaluation settings.

Reproducibility goal:
This package is organized so that readers can reproduce the manuscript’s main quantitative results and figures from the archived processed data and scripts, without reconstructing the full CFD pipeline from scratch.

Repository curation note:
To satisfy repository size constraints, this version is a curated reproducibility release. It includes the files required for the published results; optional large add-ons (if any) are listed explicitly in the package documentation.

Citation:
Deng, Yuxuan (2026), “Creative-GNN NACA0012 2D Compressible Flow Dataset and Reproducibility Package”, Mendeley Data, V1, doi:10.17632/g3x4phfr3r.1
DOI: 10.17632/m6fwp2r7j3
title: Timeliness of Antiresorptive Consolidation After Anabolic Therapy for Primary Fracture Prevention: A U.S. Cohort Study: Supplement

description: File contains Supplemental Tables and Appendix
DOI: 10.15468/dl.ca6hg3
title: Occurrence Download

description: A dataset containing 4191 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anacardium excelsum",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4191 records from 161 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004343-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/m6fwp2r7j3.1
title: Timeliness of Antiresorptive Consolidation After Anabolic Therapy for Primary Fracture Prevention: A U.S. Cohort Study: Supplement

description: File contains Supplemental Tables and Appendix