cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15858051
title: Hyperspectral Imaging (Vis/NIR) & ROI-Based °Brix Measurements of Multiple Mango Varieties under various Ripening conditions

description: This dataset brings together a rich time series of hyperspectral scans and sugar content (°Brix) measurements for 397 mango samples across four premier Indian cultivars—Banganapalli, Senthura, Kalapadi, and Jowari. Scanned daily over their ripening cycle, each fruit was imaged with a push-broom hyperspectral camera (OCI-FL series Bay Spec) covering 400–1000 nm, providing high-resolution spectral data ideal for chemometric analysis, machine-learning modeling, and quality-control applications.

Key Features





Four Distinct Cultivars:





Banganapalli (golden-yellow flesh, premium export quality)




Senthura (sweet, fibrous texture)




Kalapadi (firm, aromatic meat)




Jowari (unique local variety with high acidity)






Three Ripening Treatments:





Ethylene induction (controlled, accelerated ripening)




Natural ambient ripening (no external treatment)




Straw-based ripening (traditional, biodegradable method)






Daily Scans & Time-Series Metadata:





Unique Scan ID per acquisition




Exact Date & Time stamp for every hyperspectral image




Enables temporal tracking of spectral changes






Regions of Interest (ROIs):





Top, Middle, Bottom, and Full-Fruit ROIs




Independent °Brix measurement for each ROI




Supports spatially resolved analysis of sugar distribution






Spectral Range & Resolution:





400–1000 nm push-broom imaging




Hyperspectral “datacubes” for each Scan ID are stored in the dimension as (Band * Height of the HSI * Width of the HSI)





Dataset Contents





Metadata CSV listing:





Sample ID, variety, ripening method




Scan ID, date & time, ROI label




Corresponding °Brix reading





Why This Dataset Matters





Fruit-Quality Assessment: Build robust predictive models of sweetness and maturity.




Spectral Modeling & Chemometrics: Explore wavelength bands most sensitive to sugar content.




Machine-Learning & AI: Train and benchmark algorithms for non-destructive fruit grading.




Postharvest Research: Compare ripening kinetics across cultivars and treatments.




Precision Agriculture & Industry: Develop inline HSI-based sorting and quality-control systems.
DOI: 10.15468/dl.kpc8g5
title: Occurrence Download

description: A dataset containing 6380 records in GBIF matching the query:
SELECT
 specieskey,
 species,
 phylum,
 COUNT(*)
FROM
 occurrence
WHERE
 occurrence.phylum = 'Bryozoa'
 AND occurrence.basisofrecord = 'FOSSIL_SPECIMEN'
 AND occurrence.specieskey IS NOT NULL
 AND occurrence.occurrencestatus = 'PRESENT'
GROUP BY
 occurrence.specieskey,
 occurrence.species,
 occurrence.phylum

 The dataset's 6380 records were derived from 63 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008088-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/hucgae
title: PASO: Porcine Anterior Segment OCT Dataset
title: PASO
title: PASO-SIS

description: &lt;b&gt; 
If you find this dataset useful, please cite the peer-reviewed paper, presented at the 12th OMIA Workshop at MICCAI 2025:
&lt;/b&gt; 
&lt;br&gt;
&lt;i&gt;
Nienhaus, J, Peter, R.. et al. (2026). PASO: A Multipurpose Porcine Anterior Segment Dataset Featuring Spectral and Reconstructed OCT Volume Scans and Surgical Instrument Segmentation Masks. In: Fang, H., Wang, M., Li, H., Chen, H., Bogunović, H., Lee, C.S. (eds) Ophthalmic Medical Image Analysis. OMIA 2025. Lecture Notes in Computer Science, vol 16209. Springer, Cham. https://doi.org/10.1007/978-3-032-10351-2_13
&lt;/i&gt;
&lt;br&gt;
description: The Porcine Anterior Segment OCT (PASO) dataset contains 141 raw and reconstructed (averaged) volume scans of ex-vivo porcine eyes, imaged with a microscope-integrated SS-OCT prototype, together with Python code for data loading, reconstruction and adjustable averaging.
&lt;br&gt;
For a subset of 1020 scans from 19 porcine eye volumes, the dataset further offers annotations for Surgical Instrument Segmentation (SIS)
description: see PASO_documentation.pdf
description: For more information, see the documentation PDF (PASO_documentation.pdf)
DOI: 10.7910/dvn/og6ppf
title: Replication Data for: Capping oil emissions and the mass politics of Canadian sectoral climate policy

description: Replication materials for: Rowan, Sam S. and Amy Janzwood (2025). "Capping oil emissions and the mass politics of Canadian sectoral climate policy." Environmental Politics, p. 1--22. https://doi.org/10.1080/09644016.2025.2588911
description: R
DOI: 10.15468/dl.nsvcpc
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Iran (Islamic Republic of)",
 "TaxonKey is Lactuca serriola",
 "Year 2024-2025"
 ]
}

 The dataset includes 7 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008095-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15472/mmsvhd
title: Colección Taxonómica Central del Museo Entomológico UNAB, familia Alydidae

description: El Museo Entomológico UNAB contiene cerca de 180.000 especímenes con las siguientes características de conservación: 153.000 montados en alfiler y almacenados en 980 gavetas de madera tipo Cornell, ubicadas en seis paneles de compactadores y 395 cajas misceláneas en estanterías; 10.430 montadas en láminas: Coccomorpha (6.600 láminas), Collembola (1.700), Aphidomorpha (1400), Aleyrodomorpha (500), Thysanoptera (90), Acari (90), Psyllomorpha (50); 18.400 entre larvas y adultos, envasados en 4.600 frascos con alcohol, y 96 especímenes tipo montados en alfiler, que representan 46 especies.Aproximadamente, 20.000 especímenes se encuentran catalogados en la base digital de la Colección Taxonómica Central (CTC) del Museo UNAB, 17.000 de los cuales se encuentran identificados por especialistas, a nivel de género o especie. Dichas identificaciones representan un total de 4.000 especies dentro de 19 órdenes de insectos; así como siete especies de Acari en dos familias.En los recursos del apartado de Hemiptera de la colección UNAB se documentan registros biológicos de las siguientes familias dentro del orden Hemiptera: Aetalionidae, Alydidae, Anthocoridae, Aradidae, Berytidae, Blissidae, Cercopidae, Cicadellidae, Cicadidae, Cixiidae, Clastopteridae, Coreidae, Cydnidae, Derbidae, Fulgoridae, Issidae, Largidae, Lygaeidae, Membracidae, Miridae, Pachygronthidae, Pentatomidae, Pyrrhocoridae, Reduviidae, Rhopalidae, Rhyparochromidae, Scutelleridae.Los especímenes en general de las colecciones del Museo tienen fecha de recolección desde 1950 hasta la actualidad y son parte de permisos de recolección asociados a proyectos dirigidos en los agroecosistemas de Colombia. Todos los especímenes asociados a los registros se encuentran actualmente depositados en el museo entomológico UNAB, de la Facultad de Ciencias Agrarias de la Universidad Nacional de Colombia, sede Bogotá.
DOI: 10.15468/dl.4yyqq6
title: Occurrence Download

description: A dataset containing 3490 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Palaemon adspersus"
 ]
}

 The dataset includes 3490 records from 123 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008096-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17713835
title: James Baldwin's 1965 Debate Speech at Cambridge Union - Prosodic–Musical-Rhetorical Analysis Dataset (v1.0)

description: This dataset contains prosodic, phonetic, musical, and rhetorical analysis of James Baldwin’s 1965 Cambridge Union debate speech on the motion “The American Dream is at the Expense of the American Negro.” Generated using the Rhetoric Analysis Toolkit, the dataset integrates forced phonetic alignment (Montreal Forced Aligner), acoustic feature extraction (Praat via Parselmouth), AI-generated rhetorical scheme detection (OpenAI GPT-4o), and musicological representations (MIDI and MusicXML). This multimodal approach enables researchers to investigate how Baldwin’s vocal performance—pitch, timing, intensity, pacing, phrasing, and prosodic emphasis—interacts with classical rhetorical structures to construct one of the most influential speeches of the civil-rights era.

The dataset includes aligned audio and TextGrid files, detailed acoustic analyses at both word and phoneme levels, rhetorical-scheme annotations across all 38 segments of the speech (including anaphora, assonance, alliteration, homoioteleuton, isocolon, rhyme, and polysyndeton/asyndeton), and cross-segment patterns such as ploce and extended anaphora. Advanced pattern-specific analyses examine the recurring rhetorical force of key lexical anchors such as “dream,” “shock,” and “you,” providing formant trajectories (F1–F4), pitch contours, and spectral information. Musicological analyses translate prosodic movement into notated contours, MIDI sequences, and MusicXML files suitable for computational or artistic use.

This dataset is designed for scholars in digital humanities, rhetoric, African American studies, political communication, linguistics, musicology, and performance studies. It enables close investigation of how Baldwin’s acoustic delivery structures argument, intensifies affect, and produces the moral and political force for which this speech is known.
DOI: 10.6084/m9.figshare.22304293
title: Empirical Evidence for the Rescue Effect

description: These data are from my dissertation research on rainforest frogs in Madagascar. They describe dispersal and extinction patterns in a plant-specialist frog species Guibemantis wattersoni.
DOI: 10.6084/m9.figshare.22304293.v1
title: Empirical Evidence for the Rescue Effect

description: These data are from my dissertation research on rainforest frogs in Madagascar. They describe dispersal and extinction patterns in a plant-specialist frog species Guibemantis wattersoni.
DOI: 10.15468/dl.dhjsz7
title: Occurrence Download

description: A dataset containing 801 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amphiachyris dracunculoides",
 "GadmGid is one of (USA.6_1, USA.17_1, USA.27_1, USA.28_1, USA.32_1, USA.35_1, USA.37_1, USA.42_1, USA.44_1, USA.51_1)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Human Observation, Machine Observation)"
 ]
}

 The dataset includes 801 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008097-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17649859
title: Dataset "Data on synthesis and characterization of calcium phosphate nanoparticles" linked to publication "Cell-Laden 3D Printed GelMA/HAp and THA Hydrogel Bioinks: Development of Osteochondral Tissue-like Bioinks", DOI: 10.3390/ma16227214

description: Dataset contains data on synthesis and characterization of calcium phosphate nanoparticles, which where used in publication "Cell-Laden 3D Printed GelMA/HAp and THA Hydrogel Bioinks: Development of Osteochondral Tissue-like Bioinks", DOI: 10.3390/ma16227214. 

Data included in the dataset are from following measurements: x-ray diffraction analysis (XRD) data, Fourier transform infrared spectometry data in attenuated total reflectance mode (FT-IR ATR), inductively coupled plasma mass spectrometry (ICP-MS) data, nitrogen sorption (specifically, specific surface area analysis when Brunauer–Emmett–Teller (BET) theory is used), scanning electron microscopy (SEM) data, and transmission electron microscopy (TEM) data. 

Additionally, PDF file "Overview Data on synthesis and characterization of calcium phosphate nanoparticles" summarizes materials and methods section of the related publication and the experimental data.

"ReadMe Folder Name Info.TXT" describes titles of the folders included in this data set.
DOI: 10.5281/zenodo.17649858
title: Dataset "Data on synthesis and characterization of calcium phosphate nanoparticles" linked to publication "Cell-Laden 3D Printed GelMA/HAp and THA Hydrogel Bioinks: Development of Osteochondral Tissue-like Bioinks", DOI: 10.3390/ma16227214

description: Dataset contains data on synthesis and characterization of calcium phosphate nanoparticles, which where used in publication "Cell-Laden 3D Printed GelMA/HAp and THA Hydrogel Bioinks: Development of Osteochondral Tissue-like Bioinks", DOI: 10.3390/ma16227214. 

Data included in the dataset are from following measurements: x-ray diffraction analysis (XRD) data, Fourier transform infrared spectometry data in attenuated total reflectance mode (FT-IR ATR), inductively coupled plasma mass spectrometry (ICP-MS) data, nitrogen sorption (specifically, specific surface area analysis when Brunauer–Emmett–Teller (BET) theory is used), scanning electron microscopy (SEM) data, and transmission electron microscopy (TEM) data. 

Additionally, PDF file "Overview Data on synthesis and characterization of calcium phosphate nanoparticles" summarizes materials and methods section of the related publication and the experimental data.

"ReadMe Folder Name Info.TXT" describes titles of the folders included in this data set.
DOI: 10.34740/kaggle/dsv/13867366
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.48670/mds-00366
title: Baltic Sea summer bloom coverage
DOI: 10.15468/dl.4xs9yw
title: Occurrence Download

description: A dataset containing 53262 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Pakistan",
 "OccurrenceStatus is Present",
 "Year 2024-2025"
 ]
}

 The dataset includes 53262 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008075-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/5tzk-e307
title: "LLMParseBench"

description: "The LLMStructExtractBench dataset provides a standardized, open benchmark for evaluating large language models (LLMs) on the task of extracting structured information from natural-language emails into valid JSON objects. The dataset consists of five common administrative scenarios: equipment loan requests, IT support tickets, project extension requests, sick leave requests, and conference or training registrations. These scenarios reflect typical workflows found in academic, corporate, and public institutions and were selected for their diversity in structure, key\/value variety, and semantic complexity.For each scenario, the dataset contains:Natural-language emails written in a realistic business tone with varied linguistic forms, multilingual naming conventions, and diverse phrasing patterns.Ground-truth JSON objects that represent the precise, expected extraction targets. Each JSON object strictly adheres to the corresponding schema.Scenario-specific JSON Schema files, which define the required structure, types, and fields expected in any valid output.Prompt templates that describe extraction instructions, provide examples, or define value constraints, enabling reproducible prompting practices within evaluation pipelines.Validation-ready formatting, meaning each ground-truth pair is automatically verified against its schema.The dataset is fully synthetic but carefully modeled after realistic internal communication patterns. Variations include different date formats, numbered or bulleted equipment lists, implicit or explicit identifiers, and shifting sentence structure.LLMStructExtractBench is intended to support:Benchmarking structured extraction performance in controlled, schema-based settings.Evaluating prompt strategies for enforcing structural and semantic constraints.Developing and testing JSON parsing and validation pipelines in LLM-powered systems.Investigating robustness to paraphrasing, lexical variation, and diverse email styles.This dataset serves as a foundation for reproducible experimentation in JSON-structured information extraction and complements existing research on LLM reliability in constrained output generation."
DOI: 10.6084/m9.figshare.30712841
title: Supplementary Material for: Cardiometabolic-kidney indices and machine learning model for predicting all-cause mortality in patients with cardiovascular-kidney-metabolic syndrome: a longitudinal cohort study.

description: Background: Cardiovascular-kidney-metabolic (CKM) syndrome significantly impacts clinical outcomes, though evidence linking integrated cardiometabolic-kidney biomarkers to prognosis remains sparse. This study evaluated prognostic associations of these biomarkers and developed machine learning (ML)-based mortality prediction models for CKM patients.
Methods: Using NHANES data (1999-2018) and death records from 10,616 stage 0-3 CKM patients, we analyzed cardiometabolic-kidney indices: cardiometabolic index (CMI), atherogenic index of plasma (AIP), estimated glomerular filtration rate (eGFR), and urinary albumin-creatinine ratio (uACR). Survival analysis incorporated Kaplan-Meier curves, Cox regression, and restricted cubic splines to evaluate nonlinear associations. Risk reclassification was quantified via net reclassification index (NRI) and integrated discrimination improvement (IDI). Optimal mortality thresholds were determined using survival cutpoint analysis, and inflammation's mediating role was explored. Seven ML models were trained, with performance assessed by AUC-ROC, brier score and net clinical benefit.
Results: Over a median 96-month follow-up, 847 deaths occurred. Elevated CMI, AIP, and uACR, along with reduced eGFR, independently predicted mortality (all P&lt;0.05), with nonlinear trends for CMI, eGFR, and uACR (P-nonlinearity&lt;0.05). High-risk thresholds for these indices increased mortality risk by 1.19-1.91-fold. Combining all indices improved risk stratification (NRI=15.8%, IDI=3.4%). Inflammation mediated 1.1-5.0% of biomarker-mortality associations. Among ML models, XGBoost achieved optimal performance (AUC=0.852, 95%CI: 0.829-0.877), with brier score of 0.063 (95% CI: 0.056-0.069) and provided clinical net benefits across risk thresholds from 0 to 0.6.
Conclusion: Cardiometabolic-kidney indices significantly associated with prognosis in CKM patients, highlighting the importance of heart-kidney-metabolism crosstalk. Combining easily accessible biomarkers with the XGBoost model may facilitate risk stratification
DOI: 10.6084/m9.figshare.30712841.v1
title: Supplementary Material for: Cardiometabolic-kidney indices and machine learning model for predicting all-cause mortality in patients with cardiovascular-kidney-metabolic syndrome: a longitudinal cohort study.

description: Background: Cardiovascular-kidney-metabolic (CKM) syndrome significantly impacts clinical outcomes, though evidence linking integrated cardiometabolic-kidney biomarkers to prognosis remains sparse. This study evaluated prognostic associations of these biomarkers and developed machine learning (ML)-based mortality prediction models for CKM patients.
Methods: Using NHANES data (1999-2018) and death records from 10,616 stage 0-3 CKM patients, we analyzed cardiometabolic-kidney indices: cardiometabolic index (CMI), atherogenic index of plasma (AIP), estimated glomerular filtration rate (eGFR), and urinary albumin-creatinine ratio (uACR). Survival analysis incorporated Kaplan-Meier curves, Cox regression, and restricted cubic splines to evaluate nonlinear associations. Risk reclassification was quantified via net reclassification index (NRI) and integrated discrimination improvement (IDI). Optimal mortality thresholds were determined using survival cutpoint analysis, and inflammation's mediating role was explored. Seven ML models were trained, with performance assessed by AUC-ROC, brier score and net clinical benefit.
Results: Over a median 96-month follow-up, 847 deaths occurred. Elevated CMI, AIP, and uACR, along with reduced eGFR, independently predicted mortality (all P&lt;0.05), with nonlinear trends for CMI, eGFR, and uACR (P-nonlinearity&lt;0.05). High-risk thresholds for these indices increased mortality risk by 1.19-1.91-fold. Combining all indices improved risk stratification (NRI=15.8%, IDI=3.4%). Inflammation mediated 1.1-5.0% of biomarker-mortality associations. Among ML models, XGBoost achieved optimal performance (AUC=0.852, 95%CI: 0.829-0.877), with brier score of 0.063 (95% CI: 0.056-0.069) and provided clinical net benefits across risk thresholds from 0 to 0.6.
Conclusion: Cardiometabolic-kidney indices significantly associated with prognosis in CKM patients, highlighting the importance of heart-kidney-metabolism crosstalk. Combining easily accessible biomarkers with the XGBoost model may facilitate risk stratification
DOI: 10.15161/oar.it/211802
title: Carta Geologica d'Italia alla scala 1:50.000, F. 288 Arezzo
DOI: 10.5281/zenodo.8435748
title: WP2 - Athens Campaign - NTUA / Level 2 - (June-August 2023)

description: Level 2 of the lidar data obtained by the EOLE and DEPOLE lidar systems in the National Technical University of Athens (NTUA), during the EURAMET European Partnership on Metrology (EPM) project BIOSPHERE (June -  August 2023).
DOI: 10.15468/dl.jqzh6p
title: Occurrence Download

description: A dataset containing 641 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Arctium",
 "GadmGid is one of (USA.6_1, USA.17_1, USA.27_1, USA.28_1, USA.32_1, USA.35_1, USA.37_1, USA.42_1, USA.44_1, USA.51_1)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Human Observation, Machine Observation)"
 ]
}

 The dataset includes 641 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008099-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17704681
title: Glutamatergic projection neurons in the cholinergic basal forebrain underlie learned olfactory associational valence assignment

description: Dataset Descriptions for Zenodo

1. Datasetforfig2CD, DatasetforfigS2C, Datasetforfig1E_S1C_S1D

These datasets contain calcium imaging activity used to generate the heatmaps and average traces for excited, inhibited, and non-responsive neuronal populations.

Parameter indices:





RCall / RC_154 — excited neurons




ICall / IC_154 — inhibited neurons




NCall / NC_154 — non-responsive neurons




RCallaf / RC_154af — excited neurons after associative learning




ICallaf / IC_154af — inhibited neurons after associative learning




NCallaf / NC_154af — non-responsive neurons after associative learning



Additional variables:





submouseztracesmeanpercell — calcium traces for each neuron after subtracting mineral-oil–responsive baseline activity




mouseztracesmeanpercell — raw calcium activity for each neuron




BS — time before odor onset




FR — frame rate




RS — time after odor onset




TF — total plotted time window





2. Datasetforfig2CD_fig3BC_fig4H

This dataset contains calcium activity organized for principal component analysis (PCA). Data are structured to match the analyses presented in Figures 2C–D, 3B–C, and 4H.



3. 8mice_rawdata

This dataset contains the raw calcium imaging data from eight mice used for Figures 3–4 and Supplementary Figure S2. No preprocessing has been applied.