cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25934/pr00011018
title: Optimizing dose-finding in early oncology trials by utilizing information from multiple measures and simulations 

description: 
The goal of this research is to improve the process of determining the best dose of a new cancer treatment during early clinical trials. When developing cancer treatments, it is critical to find a dose that provides the most benefit while minimizing harmful side effects. Early-phase clinical trials often involve a small number of patients and try to minimize number of people treated with doses that are too high or too low. This can make it difficult to gather enough useful information about how the drug works.
 
To address this, our research will use a method called Monte Carlo simulation. Monte Carlo simulation is a statistical technique that creates synthetic data by predicting possible outcomes based on the information already collected from patients. By generating a range of possible results, this method can help researchers better understand the dose-response relationships both from the toxicity perspective (side effects), and efficacy perspective (how well the treatment works).
 
One of the main challenges is using all the information available about each patient at different dose levels measured by different variables. Our approach introduces a novel technique to combine various types of patient data more effectively and provides a structured way to evaluate the safety and effectiveness. The method also aligns with the recent guidance from the Food and Drug Administration (FDA) on dose optimization for cancer treatments.
DOI: 10.5281/zenodo.15596067
title: Electronic appendix to: "Linking Microbial Gene-Expression and Denitrification Rates in Aquifers: Insights From an Intermediate-Scale In-Situ Injection-Extraction Experiment and Reaction Model"

description: This is the electronic appendix to 

"Linking Microbial Gene-Expression and Denitrification Rates in Aquifers: Insights From an Intermediate-Scale In-Situ Injection-Extraction Experiment and Reaction Model", submitted to JGR Biogeosciences 06/2025
DOI: 10.15468/dl.ay26z8
title: Occurrence Download

description: A dataset containing 289 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Ecuador",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Miconia salicifolia (Bonpl. ex Naudin) Naudin"
 ]
}

 The dataset includes 289 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020998-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15166367
title: MagBac_Datensatz_LMU_2025

description: MagBacBayern ist ein Kooperationsprojekt der Ludwig-Maximilians-Universität München und Universität Bayreuth mit Schulen in München und Bayreuth. Es soll helfen mehr über magnetotaktischen Bakterien zu erfahren. Ziel ist es eine detaillierte Karte aller Fundorte zu erstellen.

Dieser Datensatz dient als Beispieldatensatz der LMU. Dabei wurden Gewässer in und um München beprobt und im Labor der Geophysik der LMU München auf magnetotaktische Bakterien untersucht.
DOI: 10.5281/zenodo.15166368
title: MagBac_Datensatz_LMU_2025

description: MagBacBayern ist ein Kooperationsprojekt der Ludwig-Maximilians-Universität München und Universität Bayreuth mit Schulen in München und Bayreuth. Es soll helfen mehr über magnetotaktischen Bakterien zu erfahren. Ziel ist es eine detaillierte Karte aller Fundorte zu erstellen.

Dieser Datensatz dient als Beispieldatensatz der LMU. Dabei wurden Gewässer in und um München beprobt und im Labor der Geophysik der LMU München auf magnetotaktische Bakterien untersucht.
DOI: 10.5281/zenodo.15533560
title: MagBac_Datensatz_LMU_2025

description: MagBacBayern ist ein Kooperationsprojekt der Ludwig-Maximilians-Universität München und Universität Bayreuth mit Schulen in München und Bayreuth. Es soll helfen mehr über magnetotaktischen Bakterien zu erfahren. Ziel ist es eine detaillierte Karte aller Fundorte zu erstellen.

Dieser Datensatz dient als Beispieldatensatz der LMU. Dabei wurden Gewässer in und um München beprobt und im Labor der Geophysik der LMU München auf magnetotaktische Bakterien untersucht.
DOI: 10.5281/zenodo.11479478
title: Fire-D: Analysis and ML-Ready NASA-Centric Remote Sensing of Wildfire and Smoke

description: Earth science remote sensing imagery is rich in structural and spectral information, making such data an ideal platform for benchmarking for a broad range of machine learning (ML) tasks, from pattern retrieval to physics-informed classification to anomaly detection to transfer learning. Nevertheless, the utility of Earth science remote sensing data remains largely unexplored by the broader ML community. Our goal is to bridge this gap and bring a rich variety of multisource multi-resolution Earth image data to a wider range of ML researchers who are non-experts in remote sensing, thereby increasing the utility and societal impact of such data products. In particular, motivated by the emerging wildfire crisis, we present radiometrically and geometrically calibrated radiance data from airborne and orbital instruments from the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the Korean Meteorological Administration (KMA).

Given the scarce occurrence of wildfires and complex spatio-temporal dependencies in radiance data, these datasets are especially well suited for benchmarking unsupervised and self-supervised learning tasks both on images and non-Euclidean objects. Our experiments on these datasets indicate that contrastive learning and transfer learning algorithms can capture the structures of views and scenes, map pixel space of multi-sensor imagery to a high-level embedding space for further downstream tasks, and facilitate more cohesive integration of the state-of-the-art ML approaches into wildfire risk analytics.

All NASA-based observations are freely usable under the Creative Commons Zero License.There are also no restrictions on the use of GOES Data. GK2A data are also open data without any restrictions on its use.

 

Use:

On the data input, input geometrically and radiometrically calibrated radiance data has been pulled from various NASA, NOAA, and KMA archives. For instruments that have multiple different spatial resolutions within their spectral bands (GOES and GK2A), all bands have been resampled to the lowest collective spatial resolution.

Geometric and radiometric calibration has been done by the science data processing pipelines of the various missions, and would not need to be done by anyone else looking to curate the same data. Further information for each instrument can be found in each of the publicly available Level-1 algorithm theoretical basis documents (ATBDs)

All input and label data has been put in GeoTiff format. Each band is in a separate raster band and each scene is in a separate GeoTiff file. Label files and input files are in subdirectories labeled respectively, and the file names match for input and labels, with the exception of an additional .fire and .smoke in the respective label filenames and subfolders.
DOI: 10.25417/uic.29060840
title: Gallium Nitride Photocathode Data

description: A zip file containing (i) the raw data (.tif image files) for the GaN photocathode characterization that was performed in June of 2024 and (ii) the OriginLab Origin 2024 data file used to create the plots in the associated publication (https://doi.org/10.48550/arXiv.2412.17207) which, itself, includes a spreadsheet containing the MTE and QE values obtained from analyzing the raw data as well as the GaAs MTE and QE from L. Jones, 2014 that is also presented in the same publication.
DOI: 10.25417/uic.29060840.v1
title: Gallium Nitride Photocathode Data

description: A zip file containing (i) the raw data (.tif image files) for the GaN photocathode characterization that was performed in June of 2024 and (ii) the OriginLab Origin 2024 data file used to create the plots in the associated publication (https://doi.org/10.48550/arXiv.2412.17207) which, itself, includes a spreadsheet containing the MTE and QE values obtained from analyzing the raw data as well as the GaAs MTE and QE from L. Jones, 2014 that is also presented in the same publication.
DOI: 10.15468/dl.vmcp3n
title: Occurrence Download

description: A dataset containing 34807 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "GadmGid is BRA.13_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Melastomataceae"
 ]
}

 The dataset includes 34807 records from 147 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020999-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.71486/2705-3f05
title: Dataset of the work "VALPECTIN_Research Article_JMS_708_August 2024_123054"

description: The dataset contains data used in the work "Fractionation and refining of pectic oligosaccharides derived from onion skins through continuous feed diafiltration", published in Journal of Membrane Science 708, 2024, 123054
DOI: 10.15468/dl.7trhvz
title: Occurrence Download

description: A dataset containing 1191 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Ambulocetidae, Pakicetidae, Remingtonocetidae, Protocetidae, Basilosauridae, Kekenodontidae, Coronodon Geisler et al., 2017, Mammalodon Pritchard, 1939, Mirocetus Mchedlidze, 1970, Simocetus Fordyce, 2002, Mystacodon Lambert et al., 2017, Llanocetus Mitchell, 1989, Albertocetus Uhen, 2008)"
 ]
}

 The dataset includes 1191 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019675-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15591057
title: Data for "Fluctuation as a probe of entanglement transition in a monitored free-fermion chain"
DOI: 10.5281/zenodo.15591058
title: Data for "Fluctuation as a probe of entanglement transition in a monitored free-fermion chain"
DOI: 10.5525/gla.researchdata.1989
title: Complexity and Manipulation of International Kidney Exchange Programmes with Country-Specific Parameters: Data and Code

description: The code and data sets used in the simulations in the paper “Complexity and Manipulation of International Kidney Exchange Programmes with Country-Specific Parameters”.
DOI: 10.5281/zenodo.15502499
title: pLM-SAV: A Δ-Embedding Approach for Predicting Pathogenic Single Amino Acid Variants

description: Data and scripts for pLM-SAV
DOI: 10.5281/zenodo.15591022
title: pLM-SAV: A Δ-Embedding Approach for Predicting Pathogenic Single Amino Acid Variants

description: Data and scripts for pLM-SAV, a Δ-embedding approach for predicting variant effects
DOI: 10.5281/zenodo.15591026
title: PANICOCENE_DATASET_MediaNarrativesOnCCIM_20250604

description: Dataset Description: Italian Newspaper Coverage of Climate Migration (2014-2024)This dataset comprises a systematic analysis of Italian newspaper coverage of climate migration over the decade spanning 2014-2024. The collection represents a comprehensive examination of how Italian media outlets have addressed the intersection between climate change and human mobility, providing critical insights into journalistic discourse on one of the most pressing contemporary issues.

The corpus was systematically compiled from the press review archive of the Associazione Carta di Roma, a prominent Italian media monitoring organization. Article selection employed targeted keyword searches focusing on climate-related terminology and migration themes, ensuring comprehensive coverage of relevant media content during the specified temporal period.

The analysis identified a total of 106 articles specifically addressing climate-induced migration phenomena across the ten-year period under examination. This relatively modest number of articles reveals significant findings about Italian media attention to climate migration topics, suggesting a notable gap in comprehensive coverage of this critical global issue.

The dataset demonstrates a heterogeneous distribution of coverage across major Italian newspapers, reflecting varying levels of editorial commitment to climate migration reporting. Avvenire emerged as the most prolific contributor with 18 articles, followed closely by La Stampa with 17 articles, and Corriere della Sera with 13 articles. Additional significant contributors include La Repubblica (7 articles), La Verità (6 articles), Il Fatto Quotidiano (5 articles), La Gazzetta del Mezzogiorno (4 articles), Libero Quotidiano (4 articles), Il Giornale (4 articles), and Il Sole 24 Ore (3 articles).

This dataset was created within the MSCA-funded project "PANICOCENE. Reframing Climate Change-induced Mobilities"( Grant agreement ID: 101105719).
DOI: 10.5281/zenodo.15591027
title: PANICOCENE_DATASET_MediaNarrativesOnCCIM_20250604

description: Dataset Description: Italian Newspaper Coverage of Climate Migration (2014-2024)This dataset comprises a systematic analysis of Italian newspaper coverage of climate migration over the decade spanning 2014-2024. The collection represents a comprehensive examination of how Italian media outlets have addressed the intersection between climate change and human mobility, providing critical insights into journalistic discourse on one of the most pressing contemporary issues.

The corpus was systematically compiled from the press review archive of the Associazione Carta di Roma, a prominent Italian media monitoring organization. Article selection employed targeted keyword searches focusing on climate-related terminology and migration themes, ensuring comprehensive coverage of relevant media content during the specified temporal period.

The analysis identified a total of 106 articles specifically addressing climate-induced migration phenomena across the ten-year period under examination. This relatively modest number of articles reveals significant findings about Italian media attention to climate migration topics, suggesting a notable gap in comprehensive coverage of this critical global issue.

The dataset demonstrates a heterogeneous distribution of coverage across major Italian newspapers, reflecting varying levels of editorial commitment to climate migration reporting. Avvenire emerged as the most prolific contributor with 18 articles, followed closely by La Stampa with 17 articles, and Corriere della Sera with 13 articles. Additional significant contributors include La Repubblica (7 articles), La Verità (6 articles), Il Fatto Quotidiano (5 articles), La Gazzetta del Mezzogiorno (4 articles), Libero Quotidiano (4 articles), Il Giornale (4 articles), and Il Sole 24 Ore (3 articles).

This dataset was created within the MSCA-funded project "PANICOCENE. Reframing Climate Change-induced Mobilities"( Grant agreement ID: 101105719).
DOI: 10.15468/dl.fp8bcz
title: Occurrence Download

description: A dataset containing 866 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Belgium, Germany, Switzerland, Luxembourg, Austria, Liechtenstein)",
 "Month is one of (June, July, August, September, October, November, December)",
 "TaxonKey is Faxonius limosus (Rafinesque, 1817)",
 "Year 2023-2023"
 ]
}

 The dataset includes 866 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019676-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14469804
title: Dataset of the Deep Potential Long Range Model and the Deep Wannier Model for Describing Solvated Glycine Tautomerism under Electric Field

description: The "dplr" dataset comprises configurations of glycine molecules in aqueous environments, including zwitterionic, neutral, anionic, and cationic forms, as well as pure water systems. All configurations are labeled using the M06-2X density functional and incorporate 0–1 pairs of hydronium and hydroxide ions to capture water autoionization effects through enhanced sampling techniques. This dataset is used to train the Deep Potential Long Range (DPLR) model to describe the influence of electric fields and interfacial effects on the tautomerism of solvated glycine.

The "dpwc" dataset contains the corresponding Wannier centroid positions for the above systems and is used to train the Deep Wannier model.

Additional details and data are available at the project’s [Github](https://github.com/Zhang-pchao/research/tree/main/GlycineEfield).
DOI: 10.5281/zenodo.14469805
title: Dataset of the Deep Potential Long Range Model and the Deep Wannier Model for Describing Solvated Glycine Tautomerism under Electric Field

description: The "dplr" dataset comprises configurations of glycine molecules in aqueous environments, including zwitterionic, neutral, anionic, and cationic forms, as well as pure water systems. All configurations are labeled using the M06-2X density functional and incorporate 0–1 pairs of hydronium and hydroxide ions to capture water autoionization effects through enhanced sampling techniques. This dataset is used to train the Deep Potential Long Range (DPLR) model to describe the influence of electric fields and interfacial effects on the tautomerism of solvated glycine.

The "dpwc" dataset contains the corresponding Wannier centroid positions for the above systems and is used to train the Deep Wannier model.

Additional details and data are available at the project’s [Github](https://github.com/Zhang-pchao/research/tree/main/GlycineEfield).
DOI: 10.6084/m9.figshare.29234528
title: SUTEEComp - Table with Categorization of Learning Activities

description: SUTEEComp Categorization of Learning Activities. The table shows examples of learning activities that integrate technologies to promote environmental awareness. The activities were suggested by 54 teachers during the ERASMUS+ Project SUTEE (https://www.sutee.eu). categorized according to the competences. The teachers were also aligning the activities with the seven competences of the SUTEEComp Framework.
DOI: 10.6084/m9.figshare.29234528.v1
title: SUTEEComp - Table with Categorization of Learning Activities

description: SUTEEComp Categorization of Learning Activities. The table shows examples of learning activities that integrate technologies to promote environmental awareness. The activities were suggested by 54 teachers during the ERASMUS+ Project SUTEE (https://www.sutee.eu). categorized according to the competences. The teachers were also aligning the activities with the seven competences of the SUTEEComp Framework.
DOI: 10.15468/dl.9ccenh
title: Occurrence Download

description: A dataset containing 11001 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hordeum pusillum Nutt."
 ]
}

 The dataset includes 11001 records from 269 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019678-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4g73wk
title: Occurrence Download

description: A dataset containing 15159 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Malva pusilla Sm."
 ]
}

 The dataset includes 15159 records from 445 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019679-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18419/darus-4761
title: Digital Twin for a Modular Collective Robotic Construction System

description: This dataset contains the digital twin developed for a Collective Robotic Construction (CRC) system, as published in &lt;b&gt;&lt;i&gt;Advanced Science&lt;/i&gt;&lt;/b&gt; (&lt;i&gt;Leder, S., Kim, H., Oguz, O.S., Kalousdian, N.K., Hartmann, V.N., Menges, A., Toussaint, M., Sitti, M.: 2022, Leveraging Building Material as Part of the In-Plane Robotic Kinematic System for Collective Construction. Advanced Science, 2201524. DOI: &lt;a href="https://doi.org/10.1002/advs.202201524"&gt;10.1002/advs.202201524&lt;/a&gt;&lt;/i&gt;).
&lt;p&gt;
&lt;p&gt;
In this version, the digital twin allows robotic plans in .JSON format to be loaded (&lt;i&gt;Load Plan&lt;/i&gt;), and either simulated without the physical CRC system or executed in real time. In both modes, plans can be played through continuously or stepped through action by action. During simulation, users can control the playback speed (&lt;i&gt;Speed&lt;/i&gt;), allowing the simulation to run faster than real-world robot operation.
&lt;p&gt;
&lt;p&gt;
In real-time execution mode (&lt;i&gt;Actuate Real Motors&lt;/i&gt;), communication with the robots occurs via serial communication over Bluetooth. The construction process is monitored using an external motion capture system. Implementations for both Vicon and OptiTrack are included in the digital twin. Data captured from the motion tracking system can be used for position correction (&lt;i&gt;Position Correction&lt;/i&gt;) at each step of the robotic plan, if desired.
&lt;p&gt;
&lt;p&gt;
Additionally, the robots in the CRC system can be manually controlled. Within the interface, users can rotate the main axis of each robot, open and close the top and bottom grippers, and control the tongue within the gripper. These controls are available for each deployed robot and are accompanied by visualizations of both the real-time robot positions and their expected positions based on the robotic plans.
&lt;p&gt;
&lt;p&gt;
The digital twin relies on external code based for some functionalities. Included in the dataset is a therefore README, which provides setup instructions, dependency guidelines, and licensing information.
description: Unity, 2022.3.7f1
DOI: 10.15468/dl.wkdpd7
title: Occurrence Download

description: A dataset containing 152351 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Phalaropus fulicarius (Linnaeus, 1758))",
 "Country is one of (Bermuda, Canada, Greenland, Saint Pierre and Miquelon, United States of America)"
 ]
}

 The dataset includes 152351 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019666-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e7zr6j
title: Occurrence Download

description: A dataset containing 42402 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Fimbristylis dichotoma (L.) Vahl"
 ]
}

 The dataset includes 42402 records from 711 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019677-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.