cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.k38c7p
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lespedeza cuneata",
 "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)",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2014",
 "Month is greater than or equal to January",
 "Month is less than or equal to December"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026214-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fnubee
title: Occurrence Download

description: A dataset containing 59 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dischloridium",
 "HasCoordinate is true"
 ]
}

 The dataset includes 59 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026215-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30122212
title: Data for Markovic et al. 2025

description: <b>Experimental manipulation of ecological and cognitive conditions produces the entire conformity-diversity spectrum in a single species</b>AbstractIdentifying the factors that drive individuals in a population to conform to the same behavior or to exhibit behavioral diversity is crucial for understanding collective decision-making, information transmission and culture, yet remains challenging. Here we propose and test a conceptual model predicting a population’s position along a Conformity-Diversity (CD) spectrum based on two key axes shaping the CD landscape: an ecological axis, representing competition over depleted resources, which favors diversity over conformity (since resources are depleted sooner if all individuals conform to the same resource type), and a cognitive axis reflecting the relative ease of learning a behavior socially versus individually. Our experiments show that manipulating these two primary factors is sufficient to produce the full CD spectrum within a single species. Specifically, studying socially foraging house sparrows, we manipulated competition using depleted or non-depleted feeding wells and manipulated the relative ease of learning a task individually by manipulating levels of experience and task difficulty. As predicted by the model, sparrows exhibited strong conformity under the combination of “no food depletion” and “difficult individual learning” conditions, strong diversity under the combination of “food depletion” and “easy individual learning” conditions, and intermediate levels of conformity under mixed conditions. The results show that a population’s position along the CD spectrum is highly flexible and sensitive to ecological and task-related conditions. Accordingly, the demonstrated CD surface may be viewed as an evolving reaction norm, and hence as a baseline over which additional factors shaping social conformity and differentiation can be tested.
DOI: 10.6084/m9.figshare.30122212.v1
title: Data for Markovic et al. 2025

description: <b>Experimental manipulation of ecological and cognitive conditions produces the entire conformity-diversity spectrum in a single species</b>AbstractIdentifying the factors that drive individuals in a population to conform to the same behavior or to exhibit behavioral diversity is crucial for understanding collective decision-making, information transmission and culture, yet remains challenging. Here we propose and test a conceptual model predicting a population’s position along a Conformity-Diversity (CD) spectrum based on two key axes shaping the CD landscape: an ecological axis, representing competition over depleted resources, which favors diversity over conformity (since resources are depleted sooner if all individuals conform to the same resource type), and a cognitive axis reflecting the relative ease of learning a behavior socially versus individually. Our experiments show that manipulating these two primary factors is sufficient to produce the full CD spectrum within a single species. Specifically, studying socially foraging house sparrows, we manipulated competition using depleted or non-depleted feeding wells and manipulated the relative ease of learning a task individually by manipulating levels of experience and task difficulty. As predicted by the model, sparrows exhibited strong conformity under the combination of “no food depletion” and “difficult individual learning” conditions, strong diversity under the combination of “food depletion” and “easy individual learning” conditions, and intermediate levels of conformity under mixed conditions. The results show that a population’s position along the CD spectrum is highly flexible and sensitive to ecological and task-related conditions. Accordingly, the demonstrated CD surface may be viewed as an evolving reaction norm, and hence as a baseline over which additional factors shaping social conformity and differentiation can be tested.
DOI: 10.15468/dl.wztptq
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lespedeza",
 "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)",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2014",
 "Month is greater than or equal to January",
 "Month is less than or equal to December"
 ]
}

 The dataset includes 27 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026216-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k39d56
title: Occurrence Download

description: A dataset containing 130 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Costa Rica",
 "OccurrenceStatus is Present",
 "TaxonKey is Dipteryx oleifera"
 ]
}

 The dataset includes 130 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026217-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17807493
title: Evaluation of 0.15% Benzydamine Hydrochloride Oral Spray Effectiveness on Oral Mucositis in Patients Undergoing High-dose Radiotherapy: A Randomized Clinical Trial

description: This dataset accompanies a randomized clinical trial assessing the effectiveness of 0.15% benzydamine hydrochloride oral spray in reducing oral mucositis severity in cancer patients undergoing high-dose radiotherapy (>50 Gy). The study involved 29 patients divided into treatment and control groups, with weekly monitoring of mucositis severity over six weeks using WHO criteria. Results showed a significant reduction in mucositis severity in the benzydamine group compared to controls. This supports benzydamine as an effective supportive care intervention for patients undergoing intensive radiotherapy.
DOI: 10.15468/dl.u9x4y3
title: Occurrence Download

description: A dataset containing 166 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dothidotthia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 166 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026218-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wg6mkb
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leucanthemum vulgare",
 "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)",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2014",
 "Month is greater than or equal to January",
 "Month is less than or equal to December"
 ]
}

 The dataset includes 19 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026219-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5067/suborbital/pace-pax/data001
title: Plankton, Aerosol, Cloud, ocean Ecosystem - Postlaunch Airborne eXperiment Campaign Data
DOI: 10.5067/asdc/suborbital/pace-pax/er2/metnav_aircraftinsitu_1
title: PACE-PAX ER-2 In-Situ Meteorology and Navigation Data
DOI: 10.5067/asdc/suborbital/pace-pax/er2/aircraftremotesensing/airharp2-map_1
title: PACE-PAX ER-2 Airborne Hyper-Angular Rainbow Polarimeter - 2 (AirHARP2) Data
DOI: 10.5067/asdc/suborbital/pace-pax/er2/aircraftremotesensing/prism-picard-l1c_1
title: PACE-PAX ER-2 PRISM/PICARD Merged Level-1C Data
DOI: 10.5067/asdc/suborbital/pace-pax/cirpas-to/lineph_aircraftinsitu_1
title: PACE-PAX CIRPAS Twin Otter Laser Imaging Nephelometer (LI Neph) Data
DOI: 10.5067/asdc/suborbital/pace-pax/cirpas-to/cirpas-facility_aircraftinsitu_1
title: PACE-PAX CIRPAS Twin Otter Facility Instrument Data
DOI: 10.5067/asdc/suborbital/pace-pax/cirpas-to/large-aerosol_aircraftinsitu_1
title: PACE-PAX CIRPAS Twin Otter In-Situ Aerosol Data
DOI: 10.5067/asdc/suborbital/pace-pax/marina-tower/large-aerosol_1
title: PACE-PAX Marina Tower In-Situ Aerosol Data
DOI: 10.5067/asdc/suborbital/pace-pax/analysis/cirpas-to_1
title: PACE-PAX CIRPAS Twin Otter Analysis Data
DOI: 10.5067/asdc/suborbital/pace-pax/analysis/er2_1
title: PACE-PAX ER-2 Analysis Data
DOI: 10.5067/asdc/suborbital/pace-pax/er2/aircraftremotesensing/spexairborne_1
title: PACE-PAX SPEX Airborne Data
DOI: 10.5067/asdc/suborbital/pace-pax/er2/aircraftremotesensing/rsp_1
title: PACE-PAX Research Scanning Polarimeter (RSP) Data
DOI: 10.5067/asdc/suborbital/pace-pax/data001/er2/aircraftremotesensing/hsrl2_1
title: PACE-PAX High Spectral Resolution Lidar-2 (HSRL-2) Data
DOI: 10.5067/asdc/suborbital/pace-pax/ivanpah-playa_1
title: PACE-PAX Ivanpah Playa Data
DOI: 10.5067/asdc/suborbital/pace-pax/analysis/isara_1
title: PACE-PAX In-Situ Aerosol Retrieval Algorithm (ISARA) Data
DOI: 10.15468/dl.pmf5ev
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ligustrum japonicum",
 "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)",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2014",
 "Month is greater than or equal to January",
 "Month is less than or equal to December"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026222-251120083545085/datasets/export for details.
DOI: 10.15468/dl.qkwtcf
title: Occurrence Download

description: A dataset containing 3590 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Verticillium",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3590 records from 105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026221-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/13979285
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.7vzqm5
title: Occurrence Download

description: A dataset containing 7535 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Channa argus"
 ]
}

 The dataset includes 7535 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026223-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17807880
title: Cognitive Load, Fatigue & Decision Offloading Dataset 2025 — Human Clarity Institute

description: This dataset is part of the Human Clarity Institute’s AI–Human Experience Data Series. It measures how adults experience cognitive load, mental fatigue, decision offloading, and the growing mental demands created by digital and AI-mediated environments.

The dataset includes:• validated 1–7 Likert-scale items  • cognitive load and mental clutter indicators  • measures of AI reliance and decision offloading behaviour  • digital overstimulation and attention-drift metrics  • open-text reflections on AI’s impact on clarity, thinking, and decision-making  • demographic variables across five countries  

Data were collected via Prolific in 2025 from adults across the UK, US, Australia, New Zealand, and Ireland. All data were cleaned, anonymised, and verified according to the Human Clarity Institute’s open-data publication protocol.

This dataset contributes to understanding how AI-driven environments shape human cognitive strain, mental energy, and decision-making, providing foundational data for longitudinal tracking of cognitive and behavioural effects in the AI era.
DOI: 10.5281/zenodo.17636371
title: Cognitive Load, Fatigue & Decision Offloading Dataset 2025 — Human Clarity Institute

description: This dataset is part of the Human Clarity Institute’s AI–Human Experience Data Series. It measures how adults experience cognitive load, mental fatigue, decision offloading, and the growing mental demands created by digital and AI-mediated environments.

The dataset includes:• validated 1–7 Likert-scale items  • cognitive load and mental clutter indicators  • measures of AI reliance and decision offloading behaviour  • digital overstimulation and attention-drift metrics  • open-text reflections on AI’s impact on clarity, thinking, and decision-making  • demographic variables across five countries  

Data were collected via Prolific in 2025 from adults across the UK, US, Australia, New Zealand, and Ireland. All data were cleaned, anonymised, and verified according to the Human Clarity Institute’s open-data publication protocol.

This dataset contributes to understanding how AI-driven environments shape human cognitive strain, mental energy, and decision-making, providing foundational data for longitudinal tracking of cognitive and behavioural effects in the AI era.
DOI: 10.15468/dl.xdwg2j
title: Occurrence Download

description: A dataset containing 914 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mycocentrospora",
 "HasCoordinate is true"
 ]
}

 The dataset includes 914 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026226-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bkp5g9
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ligustrum sinense",
 "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)",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2014",
 "Month is greater than or equal to January",
 "Month is less than or equal to December"
 ]
}

 The dataset includes 23 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026225-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ncmvud
title: Occurrence Download

description: A dataset containing 27449 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is Vespa velutina",
 "Year is one of (2024, 2025)",
 "HasCoordinate is true",
 "Geometry POLYGON((4.0 44.0, 12.0 44.0, 12.0 50.0, 4.0 50.0, 4.0 44.0))"
 ]
}

 The dataset includes 27449 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026224-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17638022
title: Cognitive Load, Fatigue & Decision Offloading Dataset 2025 — Human Clarity Institute

description: This dataset is part of the Human Clarity Institute’s AI–Human Experience Data Series. It measures how adults experience cognitive load, mental fatigue, decision offloading, and the growing mental demands created by digital and AI-mediated environments.

The dataset includes:• validated 1–7 Likert-scale items  • cognitive load and mental clutter indicators  • measures of AI reliance and decision offloading behaviour  • digital overstimulation and attention-drift metrics  • open-text reflections on AI’s impact on clarity, thinking, and decision-making  • demographic variables across five countries  

Data were collected via Prolific in 2025 from adults across the UK, US, Australia, New Zealand, and Ireland. All data were cleaned, anonymised, and verified according to the Human Clarity Institute’s open-data publication protocol.

This dataset contributes to understanding how AI-driven environments shape human cognitive strain, mental energy, and decision-making, providing foundational data for longitudinal tracking of cognitive and behavioural effects in the AI era.
DOI: 10.5281/zenodo.17806696
title: Simulation output

description: Raw output from simulations conducted during the completion of my MSc Environmental Modelling dissertation 'Numerical modelling of the evolution of Alaska's land-terminating glaciers until 2100' using the Open Global Glacier Model (OGGM). 

Annual simulated glacier volume (m³), area (m²), and length (m) between 2020-2100 is stored in an individual file per GCM; 9 CMIP6 GCMs were used for simulation (Eyring et al., 2016).
DOI: 10.6084/m9.figshare.30780380
title: pH Map of cryoablated MDR2 mouse

description: Mice were imaged 7 days post-cryoablation. MRI and MR Spectroscopic Imaging (MRSI) data were acquired using a 9.4T Bruker horizontal bore spectrometer. Anatomical T<sub>1</sub>-weighted images were obtained using a field of view (FOV) of 25mm x 25mm and 15 slices of 0.5 mm thickness. The MRSI datasets were reconstructed to a 19×15×25 matrix, corresponding to a 1mm³ isotropic voxel resolution. The pH<sub>e</sub> in each voxel was calculated in MATLAB (MathWorks, Inc., Natick, MA) from the <sup>1</sup>H chemical shifts δ2, δ3, and δ6 of the H2, H3, and H6 protons of TmDOTP<sup>5-</sup>, respectively, as previously described. The MRSI signals were overlaid on the T<sub>1</sub>-weighted images for anatomical localization
DOI: 10.6084/m9.figshare.30780380.v1
title: pH Map of cryoablated MDR2 mouse

description: Mice were imaged 7 days post-cryoablation. MRI and MR Spectroscopic Imaging (MRSI) data were acquired using a 9.4T Bruker horizontal bore spectrometer. Anatomical T<sub>1</sub>-weighted images were obtained using a field of view (FOV) of 25mm x 25mm and 15 slices of 0.5 mm thickness. The MRSI datasets were reconstructed to a 19×15×25 matrix, corresponding to a 1mm³ isotropic voxel resolution. The pH<sub>e</sub> in each voxel was calculated in MATLAB (MathWorks, Inc., Natick, MA) from the <sup>1</sup>H chemical shifts δ2, δ3, and δ6 of the H2, H3, and H6 protons of TmDOTP<sup>5-</sup>, respectively, as previously described. The MRSI signals were overlaid on the T<sub>1</sub>-weighted images for anatomical localization
DOI: 10.5281/zenodo.17805171
title: Simulation output

description: Raw output from simulations conducted during the completion of my MSc Environmental Modelling dissertation 'Numerical modelling of the evolution of Alaska's land-terminating glaciers until 2100' using the Open Global Glacier Model (OGGM). 

Annual simulated glacier volume (m³), area (m²), and length (m) between 2020-2100 is stored in an individual file per GCM; 9 CMIP6 GCMs were used for simulation (Eyring et al., 2016).
DOI: 10.15468/dl.g3geh8
title: Occurrence Download

description: A dataset containing 27449 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is Vespa velutina",
 "Year is one of (2024, 2025)",
 "HasCoordinate is true",
 "Geometry POLYGON((4.0 44.0, 12.0 44.0, 12.0 50.0, 4.0 50.0, 4.0 44.0))"
 ]
}

 The dataset includes 27449 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026227-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17807934
title: The Furniture Industry's Use of Digital Supply Chain: a Sustainable Strategy for Growth and Efficiency

description: Digitalization and the need for sustainability are driving a significant revolution in the furniture sector.  Blockchain, artificial intelligence (AI), the Internet of Things (IoT), and big data analytics are examples of digital supply chain technologies that are crucial for increasing operational efficiency, transparency, and competitiveness.  This study looks at the strategic use of digital supply chain solutions in the furniture industry, focusing on the ways in which these solutions impact sustainability, productivity, and business growth. Results show that AI-based demand forecasting lowers overproduction and stock shortages, while IoT-driven real-time tracking enhances inventory management and logistics effectiveness. By guaranteeing ethical sourcing and regulatory compliance, the incorporation of blockchain technology improves supply chain transparency. Furthermore, the transition to a circular supply chain model encourages resource optimization and waste reduction, which is consistent with international sustainability objectives. Despite these benefits, challenges such as high infrastructure costs, cybersecurity risks, and workforce digital adaptation remain significant barriers to full digitalization. As a case study, IKEA has successfully implemented a digital supply chain strategy through its IWAY standards, ensuring sustainable raw material sourcing and data-driven logistics optimization. This research concludes that companies adopting digital supply chain strategies will gain long-term competitive advantages, allowing them to improve efficiency, adapt to market changes, and achieve sustainability goals in an increasingly dynamic global industry.