cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18366197
title: Keyboard Music Learning, Emotional Regulation, and Cognitive Engagement in Older Adults: A Taiwan–Australia Pilot Dataset (2026)

description: Description

This pilot dataset documents keyboard-based music learning practices among older adults (aged 60–80) in Taiwan and Australia. In 2026, Taiwan transitioned into a "hyper-aging society," prompting the "Phase Three Senior Citizen Education Project (2025-2028)" , while Australian music education increasingly emphasizes instrumental music as a tool for resilience and social flourishing.

The dataset focuses on three core dimensions:

1.Cognitive Engagement: Measured via the Stroop Test (executive function), MMSE (global cognition), and auditory-motor coordination. 

2.Emotional Regulation: Tracked through self-reported mood states (POMS 2nd Edition) and observed resilience during technical challenges. 

3.Practice Trajectories: MIDI-based data capturing tempo stability (BPM variance), pitch accuracy, and repertoire retention over 12 months.

The objective is to provide an empirical basis for music education as a non-pharmacological, dignity-preserving intervention . This dataset is intended for use in gerontology, music pedagogy, and human-centered AI for health innovation.
DOI: 10.5525/gla.researchdata.2110
title: Wide-Field, Non-Invasive Imaging of Brain Tumours with Scattered-Light Techniques

description: Data and code for recreation of the figures and analyses in the corresponding paper, “Wide-Field, Non-Invasive Imaging of Brain Tumours with Scattered-Light Techniques”.
DOI: 10.15159/phytop.152
title: Hino

description: Phytoplankton biomass, diversity and abundance in samples collected from Lake Hino during the period 1952-2001.
DOI: 10.5281/zenodo.18348050
title: Dataset for node optimization study using Learning-by-Printing

description: Image and parameter dataset for a Learning-by-Printing approach to optimize node connections in a 3D printed component. The method uses a parameterized path-planning algorithm that enables node corrections. The dataset contains images of nodes where the inner pattern and outer contour of a 3D-printing filament meet and should form a tight bond. The images were taken automatically using the fim-based RTDE control tool (see related works). The methodological approach is described in Bettermann et al. (2025) (https://mediatum.ub.tum.de/node?id=1781543).
DOI: 10.5281/zenodo.18348049
title: Dataset for node optimization study using Learning-by-Printing

description: Image and parameter dataset for a Learning-by-Printing approach to optimize node connections in a 3D printed component. The method uses a parameterized path-planning algorithm that enables node corrections. The dataset contains images of nodes where the inner pattern and outer contour of a 3D-printing filament meet and should form a tight bond. The images were taken automatically using the fim-based RTDE control tool (see related works). The methodological approach is described in Bettermann et al. (2025) (https://mediatum.ub.tum.de/node?id=1781543).
DOI: 10.5281/zenodo.18375776
title: Uniform Forward-Modeling Analysis of Ultracool Dwarfs. IV. Benchmarking the Sonora Diamondback and Saumon & Marley (2008) Atmospheric Models Across Late-M, L, and T types with Low-Resolution 0.8--2.5 μm Spectroscopy

description: This dataset contains the materials presented in the paper, "Uniform Forward-Modeling Analysis of Ultracool Dwarfs. IV. Benchmarking the Sonora Diamondback and Saumon & Marley (2008) Atmospheric Models Across Late-M, L, and T types with Low-Resolution 0.8--2.5 μm Spectroscopy" (Mader et al. 2026), accepted for publication in the Astronomical Journal.

Please cite this paper and the Zenodo repository if these data are used in your work.

 

Description:



summary_benchmarks.csv



Physical properties of all benchmark objects derived from evolution models and atmospheric models.



README_ANCHOR_IV_Benchmarking_SDB_SM08_models.dat



README file for the above CSV table



SDB_specfit_figures.zip



Data-model comparison figures for all objects based on the Sonora Diamondback spectral fits.



SDB_ext_specfit_figures.zip



Data-model comparison figures for all objects based on the Sonora Diamondback spectral fits with an ISM-like extinction term incorporated.



SM08_specfit_figures.zip



Data-model comparison figures for all objects based on the SM08 spectral fits.



SM08_ext_specfit_figures.zip



Data-model comparison figures for all objects based on the SM08 spectral fits with an ISM-like extinction term incorporated.
DOI: 10.5281/zenodo.18375777
title: Uniform Forward-Modeling Analysis of Ultracool Dwarfs. IV. Benchmarking the Sonora Diamondback and Saumon & Marley (2008) Atmospheric Models Across Late-M, L, and T types with Low-Resolution 0.8--2.5 μm Spectroscopy

description: This dataset contains the materials presented in the paper, "Uniform Forward-Modeling Analysis of Ultracool Dwarfs. IV. Benchmarking the Sonora Diamondback and Saumon & Marley (2008) Atmospheric Models Across Late-M, L, and T types with Low-Resolution 0.8--2.5 μm Spectroscopy" (Mader et al. 2026), accepted for publication in the Astronomical Journal.

Please cite this paper and the Zenodo repository if these data are used in your work.

 

Description:



summary_benchmarks.csv



Physical properties of all benchmark objects derived from evolution models and atmospheric models.



README_ANCHOR_IV_Benchmarking_SDB_SM08_models.dat



README file for the above CSV table



SDB_specfit_figures.zip



Data-model comparison figures for all objects based on the Sonora Diamondback spectral fits.



SDB_ext_specfit_figures.zip



Data-model comparison figures for all objects based on the Sonora Diamondback spectral fits with an ISM-like extinction term incorporated.



SM08_specfit_figures.zip



Data-model comparison figures for all objects based on the SM08 spectral fits.



SM08_ext_specfit_figures.zip



Data-model comparison figures for all objects based on the SM08 spectral fits with an ISM-like extinction term incorporated.
DOI: 10.25921/fq0a-7y11
title: Surface underway measurements of partial pressure of carbon dioxide (pCO2) during the Antarctic Research and Supply Vessel (ARSV) Laurence M. Gould expeditions in the Southern Ocean, Drake Passage, South Atlantic Ocean in 2022 (NCEI Accession 0276577)

description: This dataset includes surface underway, chemical, meteorological and physical data collected from ARSV Laurence M. Gould in the Southern Ocean, Drake Passage, South Atlantic Ocean from 2022-03-05 to 2022-10-19. These data include partial pressure (or fugacity) of carbon dioxide - atmosphere, partial pressure (or fugacity) of carbon dioxide - water, sea surface salinity, sea surface temperature and barometric pressure. The instruments used to collect these data include carbon dioxide (CO2) gas analyzer and shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement.
DOI: 10.17026/ar/z5gst3
title: Starnmeerdijk te Starnmeer, gemeente Alkmaar, tweede fase
title: Opgraving – variant Archeologische Begeleiding

description: &lt;p&gt;In opdracht van het Hoogheemraadschap Hollands Noorderkwartier (HHNK) 
heeft Sweco Nederland B.V. op 22 april 2025 de tweede fase van een 
opgraving – variant archeologische begeleiding uitgevoerd naar de locatie 
Starnmeerdijk nr. 1 te Alkmaar, gemeente Alkmaar. &lt;/p&gt;&lt;p&gt;
De aanleiding voor het archeologisch onderzoek is het verbreden van de sloot 
die in 2022 onder archeologische begeleiding opgegraven was. Toen werd de 
toenmalige sloot verlengd. &lt;/p&gt;&lt;p&gt;
Het doel van de opgraving – variant archeologische begeleiding is het ex situ 
veilig stellen en documenteren van de waarschijnlijk binnen het plangebied 
aanwezige archeologische waarden (vondsten en structuren) in het kader van 
dreigende verstoring van behoudenswaardige delen van het bodemarchief. &lt;/p&gt;&lt;p&gt;
De bodemopbouw in het plangebied bestaat uit een bouwvoor, op een dunne 
laag van veraard veen op een kleipakket (Laagpakket van Wormer, Formatie 
van Naaldwijk). &lt;/p&gt;&lt;p&gt;
Tijdens het veldonderzoek is de voortzetting van de drie sloten die in 2022 
aangetroffen waren, weer aangetroffen. Op basis van het in 2022 onderzochte 
vondstmateriaal is de vulling van twee van de sloten tussen 1700 en 1800 te 
dateren. Daarnaast zijn één muurbrok en een aantal houten palen aangetroffen. &lt;/p&gt;&lt;p&gt;
Deze horen zeer waarschijnlijk bij de boerderij die op een kaart uit 1745 (naar 
een origineel van J. Dou uit 1675), op het desbetreffende perceel, getekend is. &lt;/p&gt;&lt;p&gt;
Eén van de sloten zou ook afgebeeld kunnen zijn op die kaart. 
Tijdens het veldonderzoek zijn 8 vondsten aangetroffen. Het gaat om één 
baksteen, één deel van een houtenpaal en fragmenten van geglazuurd rood- en 
witbakkend aardewerk. Dit vondstmateriaal dateert waarschijnlijk uit de 
18e eeuw.&lt;/p&gt;
DOI: 10.3886/e244663
title: Aging TFC - Robinson et al 2025

description: Data associated with Robinson et al., 2025.
DOI: 10.3886/e244663v1
title: Aging TFC - Robinson et al 2025

description: Data associated with Robinson et al., 2025.
DOI: 10.5518/1544
title: Low Magnetic Field Induced Extrinsic Strains in Multifunctional Particulate Composites

description: The current paper reports on the quantification of the effect of magnetic field on the mechanical performance of ferromagnetic nanocomposites in situ during a basic standard tensile testing. The research investigates altering the basic mechanical properties (Modulus and Strength) via application of contact-less magnetic field, as primary attempt for a future composites strengthening mechanism. The nanocomposite specimens were fabricated using filament-based 3D printing and were comprised of ferromagnetic nanoparticle embedded thermoplastic polymers. The nanoparticles were iron particles dispersed at 21wt.% (10.2 Vol.%) inside polylactic acid (PLA) polymer, as characterized utilising optical microscopy and 3D X-ray computed tomography. The magnetic field was stationary and produced using permanent Neodymium round-shaped magnets available at two field strengths below 1 Tela. The 3D printing was a MakerBot Replicator machine operating based upon fused deposition method which utilised 1.75mm-diameter filaments made of the iron particles-based PLA composites. The magnetic field equipped tensile tests were accompanied with real-time digital image correlation technique for localized strain measurements across the specimens at 10-micron pixel resolution. It was observed that the lateral magnetic field induces slight Poisson’s effect on development of extrinsic strain across the length of the tensile specimens. However, the effect reasonably interferes with the evolution of strain fields via introduction of localised compressive strains attributed to accumulated magnetic polarisation at the magnetic particles at extrinsic scale. The theory overestimated the moduli by a factor of approximately 3.1. To enhance the accuracy of its solutions for 3D printed specimens, it is necessary to incorporate pore considerations into the theoretical derivations. Additionally, a modest 10% increase in ultimate tensile strength was observed during tensile loading. This finding suggests that field-assisted strengthening can be effective for as-received 3D printed magnetic composites in their solidified state, provided that the material and field are optimally designed and implemented. This approach could propose a viable method for remote field tailoring to strengthen the material by mitigating defects induced during the 3D printing process.
DOI: 10.25824/redu/xohisz
title: Industrial poultry quality control dataset: multi-class classification of pathological conditions in chicken carcasses

description: This repository contains a dataset of 20,000 chicken carcass images collected during Marcelo dos Santos' doctoral research. The images were acquired under industrial conditions in poultry processing plants and subsequently underwent a data augmentation process. The dataset is organized into 9 folders: one containing healthy carcasses and eight representing different types of lesions. The dataset was developed to train and evaluate artificial intelligence models for automated food inspection and quality control in poultry processing. Each image captures up to three carcasses photographed on the factory production line under normal working conditions. The images are stored in JPEG format with a resolution of approximately 1.3 megapixels (1280 × 1024 pixels) and an average file size of 500 KB. Dataset structure: • 1 PDF file: dataset description and metadata • 3 JPEG files: representative image samples • Compressed folders organized by classification: - Healthy carcasses - Scratch - Arthritis - Footpad dermatitis - Dermatitis - Dermatosis - Fracture - Hematoma - Skin tear
DOI: 10.25921/eyd3-aw75
title: Dissolved inorganic carbon (DIC) and total alkalinity (TA), water temperature, salinity and other parameters, collected from discrete sample and profile observations during the R/V Rachel Carson cruise RC0083 (EXPOCODE 32RC20220812) in the Gulf of Alaska, North Pacific Ocean from 2022-08-11 to 2022-08-24 (NCEI Accession 0297461)

description: This dataset includes discrete profile measurements of dissolved inorganic carbon (DIC), total alkalinity (TA), water temperature, salinity, dissolved oxygen, macronutrients, and oxygen isotopes measured during R/V Rachel Carson cruise RC0083 in the Gulf of Alaska from 2022-08-11 to 2022-08-24. The cruise was funded by the National Oceanic and Atmospheric Administration (NOAA) Ocean Acidification Program (OAP). The carbonate system data were collected and analyzed by members at the Ocean Acidification Research Center (OARC) at the University of Alaska Fairbanks (UAF). The dissolved oxygen and macronutrient samples were analyzed by Calvin Mordy's group at UW CICOES and NOAA PMEL. The oxygen stable isotopes were analyzed at the Oregon State University Stable Isotope Lab. CTD operations were led by the chief scientist, Jessica Cross, and the ship's crew.
DOI: 10.25921/4t1t-0249
title: Partial pressure of carbon dioxide, salinity, temperature and other variables collected from surface underway observations using carbon dioxide (CO2) gas analyzer, shower head chamber equilibrator for autonomous CO2 measurement and other instruments from R/V Keifu Maru II in the Pacific Ocean, East China Sea and Sea of Japan in 2024 (NCEI Accession 0301100)

description: This dataset includes surface underway data collected from R/V Keifu Maru II in the Pacific Ocean, East China Sea and Sea of Japan, from 2024-01-11 to 2024-11-02. These data include barometric pressure, partial pressure of carbon dioxide - atmosphere, partial pressure of carbon dioxide - water, sea surface salinity and sea surface temperature. The instruments used to collect these data include carbon dioxide (CO2) gas analyzer, shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement.
DOI: 10.25921/8m27-3x34
title: Surface underway measurements of partial pressure of carbon dioxide (pCO2) during the Antarctic Research and Supply Vessel (ARSV) Laurence M. Gould expeditions in the Southern Ocean, Drake Passage, South Atlantic Ocean in 2023 (NCEI Accession 0302041)

description: This dataset includes surface underway, chemical, meteorological and physical data collected from ARSV Laurence M. Gould in the Southern Ocean, Drake Passage, South Atlantic Ocean in 2023. These data include partial pressure (or fugacity) of carbon dioxide - atmosphere, partial pressure (or fugacity) of carbon dioxide - water, sea surface salinity, sea surface temperature and barometric pressure. The instruments used to collect these data include carbon dioxide (CO2) gas analyzer and shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement.
DOI: 10.25921/bfxh-d950
title: Surface underway measurements of partial pressure of carbon dioxide (pCO2) during the Antarctic Research and Supply Vessel (ARSV) Laurence M. Gould expeditions in the Southern Ocean, Drake Passage, South Atlantic Ocean in 2024 (NCEI Accession 0302064)

description: This dataset includes surface underway, chemical, meteorological and physical data collected from ARSV Laurence M. Gould in the Southern Ocean, Drake Passage, South Atlantic Ocean in 2024. These data include partial pressure (or fugacity) of carbon dioxide - atmosphere, partial pressure (or fugacity) of carbon dioxide - water, sea surface salinity, sea surface temperature and barometric pressure. The instruments used to collect these data include carbon dioxide (CO2) gas analyzer and shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement.
DOI: 10.24435/materialscloud:xm-46
title: Novel fast Li-ion conductors for solid-state electrolytes from first-principles

description: We present a high-throughput computational screening for fast lithium-ion conductors to identify promising materials for application in all solid-state electrolytes. Starting from more than 30,000 Li-containing experimental structures sourced from Crystallography Open Database, Inorganic Crystal Structure Database and Materials Platform for Data Science, we perform highly automated calculations to identify electronic insulators. On these ~1000 structures, we use molecular dynamics simulations to estimate Li-ion diffusivities using the pinball model, which describes the potential energy landscape of diffusing lithium with accuracy similar to density functional theory while being 200-500 times faster. Then we study the ~60 most promising and previously unknown fast conductors with full first-principles molecular dynamics simulations at several temperatures to estimate their activation barriers. The MD trajectories of these structures are included along with all the structures on which electronic strutcure calculations were performed. The entire screening provenance is provided for one structure to facilitate the reproduction of this screening.
DOI: 10.24435/materialscloud:zh-cn
title: Novel fast Li-ion conductors for solid-state electrolytes from first-principles

description: We present a high-throughput computational screening for fast lithium-ion conductors to identify promising materials for application in all solid-state electrolytes. Starting from more than 30,000 Li-containing experimental structures sourced from Crystallography Open Database, Inorganic Crystal Structure Database and Materials Platform for Data Science, we perform highly automated calculations to identify electronic insulators. On these ~1000 structures, we use molecular dynamics simulations to estimate Li-ion diffusivities using the pinball model, which describes the potential energy landscape of diffusing lithium with accuracy similar to density functional theory while being 200-500 times faster. Then we study the ~60 most promising and previously unknown fast conductors with full first-principles molecular dynamics simulations at several temperatures to estimate their activation barriers. The MD trajectories of these structures are included along with all the structures on which electronic strutcure calculations were performed. The entire screening provenance is provided for one structure to facilitate the reproduction of this screening.
DOI: 10.5281/zenodo.18376118
title: CAMBER Dataset – Road Survey Video #1

description: This dataset contains road survey video recordings collected within the CAMBER - European Road Infrastructure Monitoring Project. The videos capture forward-facing visual information on road infrastructure condition, including pavement defects, surface degradation, and road furniture elements.

**Data Generation Method:**
The video was recorded using mobile devices during road monitoring campaigns. Video frames were processed using YOLO-based computer vision models to detect road malfunctions including potholes, manholes, and speed breakers. Detections were geo-referenced using synchronized GPS track data.

**Type of Data:** Video / Image sequences

**Data Format(s):** MP4 (video), CSV (detection results), GPX (GPS track)

**Spatial Coverage:**
- Route distance: 6.48 km
- Geographic coordinates: WGS84 (EPSG:4326)

**Temporal Coverage:**
- Recording date: 2026-01-26 12:33:27 UTC
- Duration: 0.61 hours

**Processing Information:**
- Video ID: 1
- Processing status: Pending
- Safety assessment: Green (Totally Safe)
- Associated Route ID: 1

**Machine Learning Model:**
- Model: models/road_malfunction_3class.pt
- Detected classes: manhole,pothole,speedbreaker
- Confidence threshold: 0.45
- Minimum track age: 5 frames

**Data Access:**
The dataset files are stored on the CAMBER project infrastructure with S3-compatible storage. Zenodo serves as a persistent metadata record and DOI landing page. Access to the full dataset is provided via the related identifiers or upon request.

**Funding:**
This work was funded by the European Union under the Horizon Europe programme, Grant Agreement No. 101156387.
description: For access requests, technical questions, or further information about this dataset, please contact: data@camber-project.eu

Project website: https://camber-project.eu (TODO: Update with actual URL)
DOI: 10.5281/zenodo.18376119
title: CAMBER Dataset – Road Survey Video #1

description: This dataset contains road survey video recordings collected within the CAMBER - European Road Infrastructure Monitoring Project. The videos capture forward-facing visual information on road infrastructure condition, including pavement defects, surface degradation, and road furniture elements.

**Data Generation Method:**
The video was recorded using mobile devices during road monitoring campaigns. Video frames were processed using YOLO-based computer vision models to detect road malfunctions including potholes, manholes, and speed breakers. Detections were geo-referenced using synchronized GPS track data.

**Type of Data:** Video / Image sequences

**Data Format(s):** MP4 (video), CSV (detection results), GPX (GPS track)

**Spatial Coverage:**
- Route distance: 6.48 km
- Geographic coordinates: WGS84 (EPSG:4326)

**Temporal Coverage:**
- Recording date: 2026-01-26 12:33:27 UTC
- Duration: 0.61 hours

**Processing Information:**
- Video ID: 1
- Processing status: Pending
- Safety assessment: Green (Totally Safe)
- Associated Route ID: 1

**Machine Learning Model:**
- Model: models/road_malfunction_3class.pt
- Detected classes: manhole,pothole,speedbreaker
- Confidence threshold: 0.45
- Minimum track age: 5 frames

**Data Access:**
The dataset files are stored on the CAMBER project infrastructure with S3-compatible storage. Zenodo serves as a persistent metadata record and DOI landing page. Access to the full dataset is provided via the related identifiers or upon request.

**Funding:**
This work was funded by the European Union under the Horizon Europe programme, Grant Agreement No. 101156387.
description: For access requests, technical questions, or further information about this dataset, please contact: data@camber-project.eu

Project website: https://camber-project.eu (TODO: Update with actual URL)
DOI: 10.17026/ar/rr972i
title: Archeologisch onderzoek RWZI Lichtenvoorde, gemeente Oost Gelre
title: Inventariserend veldonderzoek door middel van boringen

description: In opdracht van het Waterschap Rijn en IJssel (WRIJ) heeft Sweco Nederland B.V. een 
archeologisch inventariserend veldonderzoek door middel van boringen (verkennende fase) 
uitgevoerd naar de locatie rioolwaterzuiveringsinstallatie (RWZI) aan de Boschlaan 18 te 
Lichtenvoorde, gemeente Oost Gelre. De aanleiding voor dit onderzoek is de uitbreiding en 
optimalisering van de RWZI.