cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.y75rds
title: Occurrence Download

description: A dataset containing 12841 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Psychotria carthagenensis Jacq."
 ]
}

 The dataset includes 12841 records from 309 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008778-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ezbs89
title: Occurrence Download

description: A dataset containing 21 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Speculipastor bicolor Reichenow, 1879"
 ]
}

 The dataset includes 21 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008779-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12188839
title: MODIS NDVI, monthly aggregated time series for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023)

description: Normalized Difference Vegetation Index (NDVI) from MODIS data for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023).

Source data:- MODIS/Terra Vegetation Indices 16-Day L3 Global 1 km SIN Grid (MOD13A2 v061): https://lpdaac.usgs.gov/products/mod13a2v061/

The Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Indices 16-Day (MOD13A2) Version 6.1 product provides Vegetation Index (VI) values at a per pixel basis at 1 kilometer (km) spatial resolution. There are two primary vegetation layers. The first is the Normalized Difference Vegetation Index (NDVI), which is referred to as the continuity index to the existing National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) derived NDVI. The second vegetation layer is the Enhanced Vegetation Index (EVI), which has improved sensitivity over high biomass regions. The algorithm for this product chooses the best available pixel value from all the acquisitions from the 16 day period. The criteria used is low clouds, low view angle and the highest NDVI/EVI value.

For the time period January 2019 - December 2023, the NDVI layer of the original data has been processed. Bad quality pixels or pixels with snow/ice and/or cloud cover have been masked using the provided quality assurance (QA) layers and appear as "no data". These 16-Day data are then aggregated to monthly temporal resolution using the maximum and reprojected to Latitude-Longitude/WGS84.

File naming:ndvi_filt_YYYY_MM_01T00_00_00.tife.g.: ndvi_filt_2023_12_01T00_00_00.tif

The date within the filename is year and month of aggregated timestamp.

Pixel values:NDVI * 10000 Scaled to Integer, example: value 6473 = 0.6473

Projection + EPSG code:Latitude-Longitude/WGS84 (EPSG: 4326)

Spatial extent:north: 28Nsouth: 14Nwest: 18Weast: 4W

Temporal extent:January 2019 - December 2023

Spatial resolution:30 arc seconds (approx. 1000 m)

Temporal resolution:monthly

Software used:GRASS GIS 8.3.2

Format: GeoTIFF

Original dataset license:All data products distributed by NASA's Land Processes Distributed Active Archive Center (LP DAAC) are available at no charge. The LP DAAC requests that any author using NASA data products in their work provide credit for the data, and any assistance provided by the LP DAAC, in the data section of the paper, the acknowledgement section, and/or as a reference. The recommended citation for each data product is available on its Digital Object Identifier (DOI) Landing page, which can be accessed through the Search Data Catalog interface. For more information see: https://lpdaac.usgs.gov/products/mod13a2v061/

Processed by:mundialis GmbH & Co. KG, Germany (https://www.mundialis.de/)

Contact: mundialis GmbH & Co. KG, info@mundialis.de

 
description: Acknowledgements:This study was partially funded by EU grant 874850 MOOD. The contents of this publication are the sole responsibility of the authors and don't necessarily reflect the views of the European Commission.
DOI: 10.25574/62504
title: Chandra X-ray Observatory ObsId 62504
DOI: 10.5281/zenodo.12073127
title: Statistical analysis and dataset for: Invasive ants fed spinosad collectively recruit to known food faster yet individually abandon food earlier

description: Linked to the journal article published in bioRxiv (https://doi.org/10.1101/2024.06.20.599949).

Abstract

Current management strategies applied to invasive ants rely on slow-acting insecticides which aim to delay the ant’s ability to detect the poison until its effects are noticeable. Despite this, most control efforts are unsuccessful, likely due to bait abandonment and insufficient sustained consumption. Conditioned taste aversion, a learned avoidance of a particular taste, is a crucial survival mechanism which prevents animals from repeatedly ingesting toxic substances. However, whether ants are capable of this delayed association between food taste and subsequent illness remains largely unexplored. Here, we exposed colonies of the highly invasive Argentine ant, Linepithema humile, to a sublethal dose of the slow-acting insecticide spinosad. We combined measurements of individual-level feeding patterns with quantification of collective preferences and foraging dynamics to investigate the potential effects of the toxicant on behaviour. Collectively, ants preferred an odour associated with a previously experienced food, even if this contained spinosad, over a novel one. However, at the individual-level, previous exposure to spinosad resulted in reduced food consumption, as a consequence of earlier food abandonment. Moreover, while control-treated colonies recruited slower to a food source which tasted like a previously experienced one, spinosad-exposed colonies recruited equally fast to both novel and familiar foods. Although it appears that ants are unable to develop a conditioned taste aversion to sublethal doses of spinosad, ingestion of even small amounts of the toxicant strongly influences foraging behaviour. Understanding the subtle effects of slow-acting pesticides on ant cognition and behaviour can ultimately inspire the development of more efficient control methodologies.
DOI: 10.5281/zenodo.12188840
title: MODIS NDVI, monthly aggregated time series for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023)

description: Normalized Difference Vegetation Index (NDVI) from MODIS data for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023).

Source data:- MODIS/Terra Vegetation Indices 16-Day L3 Global 1 km SIN Grid (MOD13A2 v061): https://lpdaac.usgs.gov/products/mod13a2v061/

The Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Indices 16-Day (MOD13A2) Version 6.1 product provides Vegetation Index (VI) values at a per pixel basis at 1 kilometer (km) spatial resolution. There are two primary vegetation layers. The first is the Normalized Difference Vegetation Index (NDVI), which is referred to as the continuity index to the existing National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) derived NDVI. The second vegetation layer is the Enhanced Vegetation Index (EVI), which has improved sensitivity over high biomass regions. The algorithm for this product chooses the best available pixel value from all the acquisitions from the 16 day period. The criteria used is low clouds, low view angle and the highest NDVI/EVI value.

For the time period January 2019 - December 2023, the NDVI layer of the original data has been processed. Bad quality pixels or pixels with snow/ice and/or cloud cover have been masked using the provided quality assurance (QA) layers and appear as "no data". These 16-Day data are then aggregated to monthly temporal resolution using the maximum and reprojected to Latitude-Longitude/WGS84.

File naming:ndvi_filt_YYYY_MM_01T00_00_00.tife.g.: ndvi_filt_2023_12_01T00_00_00.tif

The date within the filename is year and month of aggregated timestamp.

Pixel values:NDVI * 10000 Scaled to Integer, example: value 6473 = 0.6473

Projection + EPSG code:Latitude-Longitude/WGS84 (EPSG: 4326)

Spatial extent:north: 28Nsouth: 14Nwest: 18Weast: 4W

Temporal extent:January 2019 - December 2023

Spatial resolution:30 arc seconds (approx. 1000 m)

Temporal resolution:monthly

Software used:GRASS GIS 8.3.2

Format: GeoTIFF

Original dataset license:All data products distributed by NASA's Land Processes Distributed Active Archive Center (LP DAAC) are available at no charge. The LP DAAC requests that any author using NASA data products in their work provide credit for the data, and any assistance provided by the LP DAAC, in the data section of the paper, the acknowledgement section, and/or as a reference. The recommended citation for each data product is available on its Digital Object Identifier (DOI) Landing page, which can be accessed through the Search Data Catalog interface. For more information see: https://lpdaac.usgs.gov/products/mod13a2v061/

Processed by:mundialis GmbH & Co. KG, Germany (https://www.mundialis.de/)

Contact: mundialis GmbH & Co. KG, info@mundialis.de

 
description: Acknowledgements:This study was partially funded by EU grant 874850 MOOD. The contents of this publication are the sole responsibility of the authors and don't necessarily reflect the views of the European Commission.
DOI: 10.5281/zenodo.12073128
title: Statistical analysis and dataset for: Invasive ants fed spinosad collectively recruit to known food faster yet individually abandon food earlier

description: Linked to the journal article published in bioRxiv (https://doi.org/10.1101/2024.06.20.599949).

Abstract

Current management strategies applied to invasive ants rely on slow-acting insecticides which aim to delay the ant’s ability to detect the poison until its effects are noticeable. Despite this, most control efforts are unsuccessful, likely due to bait abandonment and insufficient sustained consumption. Conditioned taste aversion, a learned avoidance of a particular taste, is a crucial survival mechanism which prevents animals from repeatedly ingesting toxic substances. However, whether ants are capable of this delayed association between food taste and subsequent illness remains largely unexplored. Here, we exposed colonies of the highly invasive Argentine ant, Linepithema humile, to a sublethal dose of the slow-acting insecticide spinosad. We combined measurements of individual-level feeding patterns with quantification of collective preferences and foraging dynamics to investigate the potential effects of the toxicant on behaviour. Collectively, ants preferred an odour associated with a previously experienced food, even if this contained spinosad, over a novel one. However, at the individual-level, previous exposure to spinosad resulted in reduced food consumption, as a consequence of earlier food abandonment. Moreover, while control-treated colonies recruited slower to a food source which tasted like a previously experienced one, spinosad-exposed colonies recruited equally fast to both novel and familiar foods. Although it appears that ants are unable to develop a conditioned taste aversion to sublethal doses of spinosad, ingestion of even small amounts of the toxicant strongly influences foraging behaviour. Understanding the subtle effects of slow-acting pesticides on ant cognition and behaviour can ultimately inspire the development of more efficient control methodologies.
DOI: 10.5281/zenodo.12608067
title: Detection and tracking of turbulent structures in the edge of tokamak plasmas using machine learning

description: This repository contains the data used in the study entitled "Detection and tracking of turbulent structures in the edge of tokamak plasmas: use of an ultra-fast camera and comparison of machine learning and Kalman filter methods". The data was collected using an ultra-fast camera on the COMPASS device.

This repository includes:

Fast passive imaging data: High-frequency captures of turbulent structures present in the edge of tokamak plasmas.Labels : Annotation of turbulent structures for training and validation of detection and tracking algorithms.Detection and tracking results using YOLO: Outputs from the YOLO (You Only Look Once) model applied to turbulent data.ObjectiveThis dataset is intended to provide a complete and reproducible set for research into the detection and tracking of turbulent structures in tokamak plasmas. It can be used to compare the performance of machine learning methods with traditional techniques, and to encourage further research in this crucial area for plasma physics and nuclear fusion.

Researchers are encouraged to use these data to:

Replicate the results of the original study.Develop and test new techniques for detecting and tracking turbulent structures.Compare the performance of machine learning algorithms with conventional methods.

References Please cite the repository as follows: S. Chouchene et al., (2024). Detection and tracking of turbulent structures in the edge of tokamak plasmas using machine learning. Zenodo. https://doi.org/10.5281/zenodo.12608068
DOI: 10.5281/zenodo.12608068
title: Detection and tracking of turbulent structures in the edge of tokamak plasmas using machine learning

description: This repository contains the data used in the study entitled "Detection and tracking of turbulent structures in the edge of tokamak plasmas: use of an ultra-fast camera and comparison of machine learning and Kalman filter methods". The data was collected using an ultra-fast camera on the COMPASS device.

This repository includes:

Fast passive imaging data: High-frequency captures of turbulent structures present in the edge of tokamak plasmas.Labels : Annotation of turbulent structures for training and validation of detection and tracking algorithms.Detection and tracking results using YOLO: Outputs from the YOLO (You Only Look Once) model applied to turbulent data.ObjectiveThis dataset is intended to provide a complete and reproducible set for research into the detection and tracking of turbulent structures in tokamak plasmas. It can be used to compare the performance of machine learning methods with traditional techniques, and to encourage further research in this crucial area for plasma physics and nuclear fusion.

Researchers are encouraged to use these data to:

Replicate the results of the original study.Develop and test new techniques for detecting and tracking turbulent structures.Compare the performance of machine learning algorithms with conventional methods.

References Please cite the repository as follows: S. Chouchene et al., (2024). Detection and tracking of turbulent structures in the edge of tokamak plasmas using machine learning. Zenodo. https://doi.org/10.5281/zenodo.12608068
DOI: 10.5281/zenodo.7366937
title: Wind radial obsevations: sample data

description: Remote sensing sample data for developing and testing the wind retrievals codes. The prefix indicates the instrument source. Prefix: wc: WindCube 200s lidar
DOI: 10.5281/zenodo.11997954
title: Safer Spaces für queere Asylbewerber*innen: Expert*inneninterviews mit LSBT-Organisationen in Deutschland

description: Im Jahr 2018 wurden Expert*inneninterviews mit LSBT-Organisationen zu ihrer Arbeit mit queeren Asylbewerber*innen und Geflüchteten geführt. Alle Beteiligten gaben ihr Einverständnis, die Transkripte für die Forschung zu verwenden und zu publizieren. Das Interview E4 fand im Rahmen einen studentischen Seminars statt. Die Autor*in begleitete die Student*innen bei der Durchführung des Interviews mit einem Vertreter von Queer Haven Potsdam. Alle weiteren Interviews wurden von der Autor*in allein durchgeführt.
DOI: 10.5281/zenodo.11997955
title: Safer Spaces für queere Asylbewerber*innen: Expert*inneninterviews mit LSBT-Organisationen in Deutschland

description: Im Jahr 2018 wurden Expert*inneninterviews mit LSBT-Organisationen zu ihrer Arbeit mit queeren Asylbewerber*innen und Geflüchteten geführt. Alle Beteiligten gaben ihr Einverständnis, die Transkripte für die Forschung zu verwenden und zu publizieren. Das Interview E4 fand im Rahmen einen studentischen Seminars statt. Die Autor*in begleitete die Student*innen bei der Durchführung des Interviews mit einem Vertreter von Queer Haven Potsdam. Alle weiteren Interviews wurden von der Autor*in allein durchgeführt.
DOI: 10.15468/dl.nvns3h
title: Occurrence Download

description: A dataset containing 2086 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhipsalis floccosa Salm-Dyck ex Pfeiff."
 ]
}

 The dataset includes 2086 records from 144 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008780-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.7366805
title: Wind radial obsevations: sample data

description: Remote sensing sample data for developing and testing the wind retrievals codes. The prefix indicates the instrument source. Prefix: wc: WindCube 200s lidar
DOI: 10.5281/zenodo.10040814
title: Dataset related to article "EMOTIONAL AWARENESS IN PATIENTS WITH AMYOTROPHIC LATERAL SCLEROSIS"

description: The database contains clinical and neuropsychological variables of a cohort of 68 non-demented ALS patients, specifically it contains scores of the 20-item toronto alexithymia scale, global cognitive efficiency, social cognition test scores and data concerning mood, behavioural assessment (Frontal Behavioural Inventory, the Dimensional Apathy Scale, the State- and Trait-Anxiety Inventory-Form and the Beck Depression Inventory-II). The databases contains also patient classification of frontotemporal syndromes according to the Strong et al.'s criteria, the type-of motor onset, genetic mutation. Finally motor-functional status (ALS Functional Rating Scale-Revised (ALSFRS-R), progression rate (ΔFS), disease duration in months and disease staging (via the King's system) are also included.
DOI: 10.5281/zenodo.10040815
title: Dataset related to article "EMOTIONAL AWARENESS IN PATIENTS WITH AMYOTROPHIC LATERAL SCLEROSIS"

description: The database contains clinical and neuropsychological variables of a cohort of 68 non-demented ALS patients, specifically it contains scores of the 20-item toronto alexithymia scale, global cognitive efficiency, social cognition test scores and data concerning mood, behavioural assessment (Frontal Behavioural Inventory, the Dimensional Apathy Scale, the State- and Trait-Anxiety Inventory-Form and the Beck Depression Inventory-II). The databases contains also patient classification of frontotemporal syndromes according to the Strong et al.'s criteria, the type-of motor onset, genetic mutation. Finally motor-functional status (ALS Functional Rating Scale-Revised (ALSFRS-R), progression rate (ΔFS), disease duration in months and disease staging (via the King's system) are also included.
DOI: 10.5281/zenodo.7312961
title: Wind radial obsevations: sample data

description: Remote sensing sample data for developing and testing the wind retrievals codes. The prefix indicates the instrument source. Prefix: wc: WindCube 200s lidar
DOI: 10.5281/zenodo.7366856
title: Wind radial obsevations: sample data

description: Remote sensing sample data for developing and testing the wind retrievals codes. The prefix indicates the instrument source. Prefix: wc: WindCube 200s lidar
DOI: 10.5281/zenodo.12626919
title: Wind radial obsevations: sample data

description: Remote sensing sample data for developing and testing the wind retrievals codes. The prefix indicates the instrument source.

Prefix:

wc: WindCube 200s lidar

rpg: Ka band RPG cloud radar
DOI: 10.5281/zenodo.7312960
title: Wind radial obsevations: sample data

description: Remote sensing sample data for developing and testing the wind retrievals codes. The prefix indicates the instrument source.

Prefix:

wc: WindCube 200s lidar

rpg: Ka band RPG cloud radar
DOI: 10.5281/zenodo.7366881
title: Wind radial obsevations: sample data

description: Remote sensing sample data for developing and testing the wind retrievals codes. The prefix indicates the instrument source. Prefix: wc: WindCube 200s lidar
DOI: 10.5281/zenodo.12627038
title: Intrinsic negative magnetoresistance from the chiral anomaly of multifold fermions

description: Data used for the plots in the publication "Intrinsic negative magnetoresistance from the chiral anomaly of multifold fermions" by F.Balduini et al
DOI: 10.5281/zenodo.12627039
title: Intrinsic negative magnetoresistance from the chiral anomaly of multifold fermions

description: Data used for the plots in the publication "Intrinsic negative magnetoresistance from the chiral anomaly of multifold fermions" by F.Balduini et al
DOI: 10.15468/dl.6d7ygm
title: Occurrence Download

description: A dataset containing 1339 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Solanum riparium Pers."
 ]
}

 The dataset includes 1339 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008781-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10804899
title: Bursts of rapid diversification, multiple dispersals out of southern Africa, and two origins of dioecy punctuate the evolutionary history of Asparagus

description: Dataset and result files from phylogenomic analysis and ancestral biogeography estimation across the genus Asparagus using the Asparagaceae1726 bait set

Contents:



BioGeoBEARS.zip = scripts and results from ancestral biogeographic estimation with BioGeoBEARS as well as ASTRAL scripts/results used to make the input species tree for analysis with BioGeoBEARS

mafft.zip = multiple sequence alignments for each Asparagaceae1726 target locus estimated with MAFFT

supercontigs.zip = exon + flanking intron gene assemblies from HybPiper

iqtree.zip = all IQ-TREE output for each Asparagaceae1726 target gene tree

trimal.zip = trimmed multiple sequence alignments for each Asparagaceae1726 target locus performed by trimAl

ASTRAL.zip = species trees reporting different branch supports and log files from ASTRAL runs

Quartet_Sampling.zip = input dataset and results from Quartet Sampling
DOI: 10.15468/dl.wptgba
title: Occurrence Download

description: A dataset containing 1148 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Psychotria grandis Sw."
 ]
}

 The dataset includes 1148 records from 76 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008782-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4aqkpp
title: Occurrence Download

description: A dataset containing 620 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Linnaea borealis L.",
 "Geometry POLYGON((-4.47763888888889 56.7401388888889, -2.79986111111111 56.7401388888889, -2.79986111111111 57.4134722222222, -4.47763888888889 57.4134722222222, -4.47763888888889 56.7401388888889))",
 "CoordinateUncertaintyInMeters is 0,101",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 620 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008783-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.