cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48597/4eqr-c9bc
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/vjkn-ubwc
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/a9f7-a9a3
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/kyby-38tv
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/mjpf-7ekx
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/vs8w-uzf2
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/vw5n-bqb2
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/k4c2-t93k
title: PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/8pmb-su3t
title: Measurement of Heavy metals at Diabla Gora

description: Measurement of Heavy metals at Diabla Gora
DOI: 10.48597/97zy-xr8r
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/davy-r7xw
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/kp8g-q8t4
title: Measurement of Heavy metals at Diabla Gora

description: Measurement of Heavy metals at Diabla Gora
DOI: 10.48597/utdv-4fw8
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/bmhg-5ca8
title: Measurement of Nitrogen oxides at Diabla Gora

description: Measurement of Nitrogen oxides at Diabla Gora
DOI: 10.48597/k64t-p2nm
title: Measurement of Heavy metals at Diabla Gora

description: Measurement of Heavy metals at Diabla Gora
DOI: 10.48597/n5sf-rhnq
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/qpqh-7pke
title: Measurement of Heavy metals at Diabla Gora

description: Measurement of Heavy metals at Diabla Gora
DOI: 10.48597/27ta-d9mp
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/y2f4-ppcg
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/b5jc-vz2u
title: Measurement of Nitrogen oxides at Diabla Gora

description: Measurement of Nitrogen oxides at Diabla Gora
DOI: 10.48597/hnwb-bcny
title: Measurement of Inorganics in precipitation at Diabla Gora

description: Measurement of Inorganics in precipitation at Diabla Gora
DOI: 10.48597/qehz-awmq
title: Measurement of Heavy metals at Diabla Gora

description: Measurement of Heavy metals at Diabla Gora
DOI: 10.48597/x86e-uv58
title: Measurement of Nitrogen oxides at Diabla Gora

description: Measurement of Nitrogen oxides at Diabla Gora
DOI: 10.48597/xxt3-m8ym
title: Measurement of Mercury at Diabla Gora

description: Measurement of Mercury at Diabla Gora
DOI: 10.48597/48nx-td7z
title: Measurement of Nitrogen oxides at Diabla Gora

description: Measurement of Nitrogen oxides at Diabla Gora
DOI: 10.48597/8trj-tc2j
title: Measurement of Inorganics in precipitation at Diabla Gora

description: Measurement of Inorganics in precipitation at Diabla Gora
DOI: 10.48597/9a76-6565
title: Measurement of Mercury at Diabla Gora

description: Measurement of Mercury at Diabla Gora
DOI: 10.48597/mu3j-57ch
title: Measurement of Heavy metals at Diabla Gora

description: Measurement of Heavy metals at Diabla Gora
DOI: 10.48597/taft-dgcc
title: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora

description: Measurement of PAHs (polycyclic aromatic hydrocarbons, 16) at Diabla Gora
DOI: 10.48597/xp8m-p8nn
title: Inorganics in air and particle phase at Diabla Gora

description: Measurement of Inorganics in air and particle phase at Diabla Gora
DOI: 10.15468/dl.9vqp9a
title: Occurrence Download

description: A dataset containing 197373 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Cynanthus latirostris)",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1951",
 "Year is less than or equal to 2024",
 "Month is greater than or equal to April",
 "Month is less than or equal to July",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 197373 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050314-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cj44fa
title: Occurrence Download

description: A dataset containing 530 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((15.826192 63.254190, 15.842356 63.300166, 15.772567 63.300166, 15.756475 63.254190, 15.826192 63.254190))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 530 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050331-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ueawat
title: Occurrence Download

description: A dataset containing 621 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erythrina americana",
 "HasCoordinate is true",
 "BasisOfRecord is Human Observation"
 ]
}

 The dataset includes 621 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050332-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23695/9z3r-7e04
title: Fula Ordboken
title: Fula Ordboken

description: Ord från https://www.fulaordboken.se/
description: Words from https://www.fulaordboken.se/
DOI: 10.15468/dl.afk854
title: Occurrence Download

description: A dataset containing 661 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((15.101595 63.175030, 15.114657 63.214114, 15.055383 63.214114, 15.042372 63.175030, 15.101595 63.175030))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 661 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050334-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17894/ucph.62287630-6632-4b1f-9641-ad529d5e8bca
title: Isotopic and elemental compositions of samples from the Iua Supracrustal Belt detrital metasediment rock core DDH-01
DOI: 10.5281/zenodo.17834039
title: Replication files for 'One-minute earthquake, years of patience: Evidence from Mexico on the effect of earthquake exposure on time preference'"

description: This archive contains the Stata do-files and data required to replicate the results in 'One-minute earthquake, years of patience: Evidence from Mexico on the effect of earthquake exposure on time preference'. See the Readme file for instructions.
DOI: 10.5281/zenodo.17834038
title: Replication files for 'One-minute earthquake, years of patience: Evidence from Mexico on the effect of earthquake exposure on time preference'"

description: This archive contains the Stata do-files and data required to replicate the results in 'One-minute earthquake, years of patience: Evidence from Mexico on the effect of earthquake exposure on time preference'. See the Readme file for instructions.
DOI: 10.15468/dl.4r7sbe
title: Occurrence Download

description: A dataset containing 21440 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is NZ National Vegetation Survey occurrence data",
 "OccurrenceStatus is Present",
 "TaxonKey is Dacrydium cupressinum"
 ]
}

 The dataset includes 21440 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050336-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9xh3ee
title: Occurrence Download

description: A dataset containing 1432 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((16.114805 63.122156, 16.130015 63.164903, 16.065215 63.164903, 16.050066 63.122156, 16.114805 63.122156))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 1432 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050337-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25451/flinders.28022267
title: <b>Sex-specific effects of incubation temperature treatment on singing behaviour</b>

description: How incubation temperature affects sexual signals, such as birdsong structure and singing behaviour, has rarely been explored, especially in wild free-living animals. To address this knowledge gap, we exposed wild superb fairy-wren eggs to three incubation temperature treatments 1. Naturally variable (natural nests) 2. Cooler (constant 37 degrees Celsius) and 3. Hotter (37–39 degrees Celsius). We then banded hatched chicks and recorded their song and singing behaviour as fledglings. In doing so, we sought to address two core questions (1) Does incubation treatment affect singing behaviour (singing onset, song rate, and song complexity) in fledglings? and (2) Were there sex specific differences in how incubation treatment affected singing behaviour? Contrary to our predictions, we found no evidence that incubation temperature treatment affected the complexity of song or the age at which singing began. However, we did find sex specific effects of differing incubation temperature treatment on song rate in fledglings.
DOI: 10.25451/flinders.28022267.v1
title: <b>Sex-specific effects of incubation temperature treatment on singing behaviour</b>

description: How incubation temperature affects sexual signals, such as birdsong structure and singing behaviour, has rarely been explored, especially in wild free-living animals. To address this knowledge gap, we exposed wild superb fairy-wren eggs to three incubation temperature treatments 1. Naturally variable (natural nests) 2. Cooler (constant 37 degrees Celsius) and 3. Hotter (37–39 degrees Celsius). We then banded hatched chicks and recorded their song and singing behaviour as fledglings. In doing so, we sought to address two core questions (1) Does incubation treatment affect singing behaviour (singing onset, song rate, and song complexity) in fledglings? and (2) Were there sex specific differences in how incubation treatment affected singing behaviour? Contrary to our predictions, we found no evidence that incubation temperature treatment affected the complexity of song or the age at which singing began. However, we did find sex specific effects of differing incubation temperature treatment on song rate in fledglings.
DOI: 10.25345/c5rx93s8g
title: MassIVE MSV000100207 - Proteomics of conditioned media used in the differentiation of equine umbilical cord derived mesenchymal stem cells
title: This proteomic study aimed to investigate the in vitro transdifferentiation potential of equine umbilical cord-derived mesenchymal stem cells (EqUC-MSCs) using a protocol based on conditioned medium derived from equine facial nerve explant culture. This study contributes to the development of novel cell-based strategies for peripheral nerve repair in equine medicine.
DOI: 10.15468/dl.fn8he8
title: Occurrence Download

description: A dataset containing 578 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((14.675655 62.979206, 14.689194 63.021251, 14.625545 63.021251, 14.612066 62.979206, 14.675655 62.979206))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 578 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050338-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17917805
title: A Rigorous Multidisciplinary Theoretical Framework for Synergistic Bio- and Non-Biochemical Interventions to Reverse Cellular and Tissue Aging: Quantitative Stochastic Modeling, Clinical Applications, and Translational Precision Medicine

description: Aging is characterized by the progressive deterioration of cellular and tissue homeostasis, driven by interconnected hallmarks including mitochondrial dysfunction, reactive oxygen species (ROS) accumulation, telomere attrition, cellular senescence, inflammaging, genomic instability, and epigenetic dysregulation. This theoretical framework integrates biochemistry, bioengineering, applied mathematics, computational biology, and pharmacology to model synergistic bio- and non-biochemical interventions aimed at cellular and tissue rejuvenation.We develop stochastic differential equation (SDE) models to capture the dynamics of these hallmarks, with a focus on the biphasic progression of epigenetic drift: an initial programmed phase (from birth to approximately age 45) marked by linear methylation changes, succeeded by midlife stochastic acceleration at CpG sites, as evidenced by a bifurcation characterized by a positive Lyapunov exponent (\(\mu_L \approx 0.012 \, \mathrm{yr}^{-1}\)). These models employ Itô semimartingales with positivity constraints and are calibrated using multi-omics datasets from NHANES, UK Biobank, GTEx, and TCGA cohorts.Key innovations encompass: (1) biphasic epigenetic SDEs incorporating hierarchical noise structures; (2) hybrid SDE-agent-based multiscale simulations; (3) extended Fourier amplitude sensitivity testing (eFAST) for Sobol indices; (4) No-U-Turn Sampler (NUTS) for Bayesian inference; and (5) physics-informed neural networks (PINNs) as surrogate models. Interventions, such as liposomal nicotinamide mononucleotide (NMN) and fisetin, are simulated using Godunov finite volume methods for partial differential equations (PDEs).Findings reveal pronounced synergies, wherein combined therapies yield hallmark attenuations comparable to a projected 2.5-year reduction in epigenetic age post-bifurcation, corroborated by preclinical and early-phase clinical data. Spatial analyses demonstrate diminished epigenetic clustering (Moran's \(I\) reduced from 0.42 to 0.11). Translational extensions leverage AI-driven digital twins for personalized prognostication and CRISPR-AI-guided gene therapy (with off-target effects \(<0.1\%\)). Insights from ongoing clinical trials (e.g., NCT04910061) and ethical considerations (Gini coefficient \(<0.2\)) are incorporated, supported by replicable code and comprehensive stability analyses.
DOI: 10.5281/zenodo.17604584
title: A Rigorous Multidisciplinary Theoretical Framework for Synergistic Bio- and Non-Biochemical Interventions to Reverse Cellular and Tissue Aging: Quantitative Stochastic Modeling, Clinical Applications, and Translational Precision Medicine

description: Aging is characterized by the progressive deterioration of cellular and tissue homeostasis, driven by interconnected hallmarks including mitochondrial dysfunction, reactive oxygen species (ROS) accumulation, telomere attrition, cellular senescence, inflammaging, genomic instability, and epigenetic dysregulation. This theoretical framework integrates biochemistry, bioengineering, applied mathematics, computational biology, and pharmacology to model synergistic bio- and non-biochemical interventions aimed at cellular and tissue rejuvenation.We develop stochastic differential equation (SDE) models to capture the dynamics of these hallmarks, with a focus on the biphasic progression of epigenetic drift: an initial programmed phase (from birth to approximately age 45) marked by linear methylation changes, succeeded by midlife stochastic acceleration at CpG sites, as evidenced by a bifurcation characterized by a positive Lyapunov exponent (\(\mu_L \approx 0.012 \, \mathrm{yr}^{-1}\)). These models employ Itô semimartingales with positivity constraints and are calibrated using multi-omics datasets from NHANES, UK Biobank, GTEx, and TCGA cohorts.Key innovations encompass: (1) biphasic epigenetic SDEs incorporating hierarchical noise structures; (2) hybrid SDE-agent-based multiscale simulations; (3) extended Fourier amplitude sensitivity testing (eFAST) for Sobol indices; (4) No-U-Turn Sampler (NUTS) for Bayesian inference; and (5) physics-informed neural networks (PINNs) as surrogate models. Interventions, such as liposomal nicotinamide mononucleotide (NMN) and fisetin, are simulated using Godunov finite volume methods for partial differential equations (PDEs).Findings reveal pronounced synergies, wherein combined therapies yield hallmark attenuations comparable to a projected 2.5-year reduction in epigenetic age post-bifurcation, corroborated by preclinical and early-phase clinical data. Spatial analyses demonstrate diminished epigenetic clustering (Moran's \(I\) reduced from 0.42 to 0.11). Translational extensions leverage AI-driven digital twins for personalized prognostication and CRISPR-AI-guided gene therapy (with off-target effects \(<0.1\%\)). Insights from ongoing clinical trials (e.g., NCT04910061) and ethical considerations (Gini coefficient \(<0.2\)) are incorporated, supported by replicable code and comprehensive stability analyses.
DOI: 10.15468/dl.5hw6tn
title: Occurrence Download

description: A dataset containing 1408 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((8.382097 62.849972, 8.391065 62.899006, 8.316923 62.899006, 8.308034 62.849972, 8.382097 62.849972))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 1408 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050340-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tge8te
title: Occurrence Download

description: A dataset containing 2146 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((8.357123 62.741593, 8.365227 62.786255, 8.297769 62.786255, 8.289730 62.741593, 8.357123 62.741593))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 2146 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050341-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15571708
title: Automatic Classification of Thermal Phases During Steel Oxidation via PCA and Infrared Thermography Time Series

description: Automatic Classification of Thermal Phases During Steel Oxidation via PCA and Infrared Thermography Time Series

Gerardo Marx Chávez-Campos ; Héctor Javier Vergara-Hernández ; Jorge Sergio Téllez-Martínez ; Edgar Guevara ; Miguel Ángel Díaz-Ibarra ; Antony Morales-Cervantes (corresponding author)

Contents





Raw Thermograms (/Raw_Thermograms_CSV/):Time-series thermal data (in CSV) from five controlled high-temperature oxidation experiments on AISI 1045 steel.




PCA Results (/PCA_Results_XLSX/):Principal Component Analysis (PCA) outputs (first two components) derived from the flattened thermograms, used as input features for machine learning classification.



A total of 3356 thermographic records were compiled, covering heating, isothermal, and cooling phases.

Methodology

Steel specimens (AISI 1045) were oxidized using a Joule-heating system, with thermal data captured using an Optris PI 450i infrared camera.PCA was applied to the flattened thermal matrices to reduce dimensionality.Five machine learning models (Random Forest, MLP, SVM, KNN, XGBoost) were trained and validated (5-fold CV) for automatic classification of thermal phases.

Purpose

This dataset supports the development of non-invasive phase recognition tools in metallurgical processes using infrared thermography and machine learning, enhancing process monitoring and decision-making.

How to Use



Clone the Repository:

git clone https://github.com/YOUR_USERNAME/Thermal_Phase_Classification_Dataset.git



Explore the Data:


Raw thermograms are organized in /Raw_Thermograms_CSV/.

PCA results for classification are in /PCA_Results_XLSX/.



Note: The scripts used for analysis are available upon request or will be made public after article acceptance.


Data Availability Statement

The dataset will be permanently archived with a DOI via Zenodo upon publication.

Citation

If you use this dataset, please cite:

Chávez-Campos, G. M., Vergara-Hernández, H. J., Téllez-Martínez, J. S., Guevara, E., Díaz-Ibarra, M. A., Morales-Cervantes, A. (2025). Automatic Classification of Thermal Phases During Steel Oxidation via PCA and Infrared Thermography Time Series.

Authors' Contributions

Antony Morales-Cervantes led the data collection. All authors contributed to data analysis and interpretation. All authors approved the final version of the manuscript for publication.

License

This dataset is distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).